code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('content_management', '0023_auto_20180424_1227'),
]
operations = [
migrations.AlterField(
model_name='cataloger',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='cataloger',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='content',
name='copyright',
field=models.CharField(max_length=500, null=True),
),
migrations.AlterField(
model_name='content',
name='name',
field=models.CharField(max_length=300),
),
migrations.AlterField(
model_name='coverage',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='coverage',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='creator',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='creator',
name='name',
field=models.CharField(max_length=300, unique=True),
),
migrations.AlterField(
model_name='directory',
name='name',
field=models.CharField(max_length=100),
),
migrations.AlterField(
model_name='directorylayout',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='directorylayout',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='keyword',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='keyword',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='language',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='language',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='subject',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='subject',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='workarea',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='workarea',
name='name',
field=models.CharField(max_length=100, unique=True),
),
] | build_automation/content_management/migrations/0024_auto_20180428_1833.py |
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('content_management', '0023_auto_20180424_1227'),
]
operations = [
migrations.AlterField(
model_name='cataloger',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='cataloger',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='content',
name='copyright',
field=models.CharField(max_length=500, null=True),
),
migrations.AlterField(
model_name='content',
name='name',
field=models.CharField(max_length=300),
),
migrations.AlterField(
model_name='coverage',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='coverage',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='creator',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='creator',
name='name',
field=models.CharField(max_length=300, unique=True),
),
migrations.AlterField(
model_name='directory',
name='name',
field=models.CharField(max_length=100),
),
migrations.AlterField(
model_name='directorylayout',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='directorylayout',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='keyword',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='keyword',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='language',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='language',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='subject',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='subject',
name='name',
field=models.CharField(max_length=100, unique=True),
),
migrations.AlterField(
model_name='workarea',
name='description',
field=models.CharField(max_length=2000, null=True),
),
migrations.AlterField(
model_name='workarea',
name='name',
field=models.CharField(max_length=100, unique=True),
),
] | 0.6705 | 0.120284 |
import unittest
import orca
import os.path as path
from setup.settings import *
from pandas.util.testing import *
class Csv:
pdf_csv = None
odf_csv = None
class DataFrameReindexingTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
# configure data directory
DATA_DIR = path.abspath(path.join(__file__, "../setup/data"))
fileName = 'USPricesSample.csv'
data = os.path.join(DATA_DIR, fileName)
data = data.replace('\\', '/')
# connect to a DolphinDB server
orca.connect(HOST, PORT, "admin", "123456")
Csv.odf_csv = orca.read_csv(data, dtype={"DLSTCD": np.float32, "DLPRC": np.float32})
# pdf from import
Csv.pdf_csv = pd.read_csv(data, parse_dates=[1], dtype={"DLSTCD": np.float32, "DLPRC": np.float32})
Csv.odf_csv = Csv.odf_csv.drop(columns=['DLRET'])
Csv.pdf_csv.drop(columns=['DLRET'], inplace=True)
@property
def pdf_csv(self):
return Csv.pdf_csv
@property
def odf_csv(self):
return Csv.odf_csv
@property
def pdf(self):
return pd.DataFrame({
'a': [1, 2, 3, 4, 5, 6, 7, 8, 9],
'b': [4, 5, 6, 3, 2, 1, 0, 0, 0],
}, index=[0, 1, 3, 5, 6, 8, 9, 9, 9])
@property
def odf(self):
return orca.DataFrame(self.pdf)
def test_dataframe_reindexing_selection_label_mainpulation_between_time(self):
idx = pd.date_range('2018-04-09', periods=4, freq='1D20min')
pdf = pd.DataFrame({'A': [1, 2, 3, 4]}, index=idx)
odf = orca.DataFrame(pdf)
assert_frame_equal(odf.between_time('0:15', '0:45').to_pandas(), pdf.between_time('0:15', '0:45'))
assert_frame_equal(odf.between_time('0:45', '0:15').to_pandas(), pdf.between_time('0:45', '0:15'))
def test_dataframe_reindexing_selection_label_mainpulation_take(self):
n = np.array([0, 1, 4])
assert_frame_equal(self.odf.take(n).to_pandas(), self.pdf.take(n))
assert_frame_equal(self.odf.take([]).to_pandas(), self.pdf.take([]))
assert_frame_equal(self.odf.take([0, 1], axis=1).to_pandas(), self.pdf.take([0, 1], axis=1))
assert_frame_equal(self.odf.take([-1, -2], axis=0).to_pandas(), self.pdf.take([-1, -2], axis=0))
n = np.random.randint(0, 2999, 100)
assert_frame_equal(self.odf_csv.take(n).to_pandas(), self.pdf_csv.take(n), check_dtype=False)
assert_frame_equal(self.odf_csv.take([0, 1, 5, 7, 11, 15], axis=1).to_pandas(), self.pdf_csv.take([0, 1, 5, 7, 11, 15], axis=1), check_dtype=False)
def test_dataframe_reindexing_selection_label_mainpulation_equals(self):
pdf = pd.DataFrame({1: [10], 2: [20]})
p_exactly_equal = pd.DataFrame({1: [10], 2: [20]})
p_different_column_type = pd.DataFrame({1.0: [10], 2.0: [20]})
p_different_data_type = pd.DataFrame({1: [10.0], 2: [20.0]})
odf = orca.DataFrame(pdf)
o_exactly_equal = orca.DataFrame(p_exactly_equal)
o_different_column_type = orca.DataFrame(p_different_column_type)
o_different_data_type = orca.DataFrame(p_different_data_type)
self.assertEqual(odf.equals(o_exactly_equal), pdf.equals(p_exactly_equal))
self.assertEqual(odf.equals(o_different_column_type), pdf.equals(p_different_column_type))
self.assertEqual(odf.equals(o_different_data_type), pdf.equals(p_different_data_type))
if __name__ == '__main__':
unittest.main() | tests/orca_unit_testing/test_dataframe_reindexing_selection.py | import unittest
import orca
import os.path as path
from setup.settings import *
from pandas.util.testing import *
class Csv:
pdf_csv = None
odf_csv = None
class DataFrameReindexingTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
# configure data directory
DATA_DIR = path.abspath(path.join(__file__, "../setup/data"))
fileName = 'USPricesSample.csv'
data = os.path.join(DATA_DIR, fileName)
data = data.replace('\\', '/')
# connect to a DolphinDB server
orca.connect(HOST, PORT, "admin", "123456")
Csv.odf_csv = orca.read_csv(data, dtype={"DLSTCD": np.float32, "DLPRC": np.float32})
# pdf from import
Csv.pdf_csv = pd.read_csv(data, parse_dates=[1], dtype={"DLSTCD": np.float32, "DLPRC": np.float32})
Csv.odf_csv = Csv.odf_csv.drop(columns=['DLRET'])
Csv.pdf_csv.drop(columns=['DLRET'], inplace=True)
@property
def pdf_csv(self):
return Csv.pdf_csv
@property
def odf_csv(self):
return Csv.odf_csv
@property
def pdf(self):
return pd.DataFrame({
'a': [1, 2, 3, 4, 5, 6, 7, 8, 9],
'b': [4, 5, 6, 3, 2, 1, 0, 0, 0],
}, index=[0, 1, 3, 5, 6, 8, 9, 9, 9])
@property
def odf(self):
return orca.DataFrame(self.pdf)
def test_dataframe_reindexing_selection_label_mainpulation_between_time(self):
idx = pd.date_range('2018-04-09', periods=4, freq='1D20min')
pdf = pd.DataFrame({'A': [1, 2, 3, 4]}, index=idx)
odf = orca.DataFrame(pdf)
assert_frame_equal(odf.between_time('0:15', '0:45').to_pandas(), pdf.between_time('0:15', '0:45'))
assert_frame_equal(odf.between_time('0:45', '0:15').to_pandas(), pdf.between_time('0:45', '0:15'))
def test_dataframe_reindexing_selection_label_mainpulation_take(self):
n = np.array([0, 1, 4])
assert_frame_equal(self.odf.take(n).to_pandas(), self.pdf.take(n))
assert_frame_equal(self.odf.take([]).to_pandas(), self.pdf.take([]))
assert_frame_equal(self.odf.take([0, 1], axis=1).to_pandas(), self.pdf.take([0, 1], axis=1))
assert_frame_equal(self.odf.take([-1, -2], axis=0).to_pandas(), self.pdf.take([-1, -2], axis=0))
n = np.random.randint(0, 2999, 100)
assert_frame_equal(self.odf_csv.take(n).to_pandas(), self.pdf_csv.take(n), check_dtype=False)
assert_frame_equal(self.odf_csv.take([0, 1, 5, 7, 11, 15], axis=1).to_pandas(), self.pdf_csv.take([0, 1, 5, 7, 11, 15], axis=1), check_dtype=False)
def test_dataframe_reindexing_selection_label_mainpulation_equals(self):
pdf = pd.DataFrame({1: [10], 2: [20]})
p_exactly_equal = pd.DataFrame({1: [10], 2: [20]})
p_different_column_type = pd.DataFrame({1.0: [10], 2.0: [20]})
p_different_data_type = pd.DataFrame({1: [10.0], 2: [20.0]})
odf = orca.DataFrame(pdf)
o_exactly_equal = orca.DataFrame(p_exactly_equal)
o_different_column_type = orca.DataFrame(p_different_column_type)
o_different_data_type = orca.DataFrame(p_different_data_type)
self.assertEqual(odf.equals(o_exactly_equal), pdf.equals(p_exactly_equal))
self.assertEqual(odf.equals(o_different_column_type), pdf.equals(p_different_column_type))
self.assertEqual(odf.equals(o_different_data_type), pdf.equals(p_different_data_type))
if __name__ == '__main__':
unittest.main() | 0.609873 | 0.493958 |
import sys, os, pwd, string, re, selinux
obj = "(\{[^\}]*\}|[^ \t:]*)"
allow_regexp = "(allow|dontaudit)[ \t]+%s[ \t]*%s[ \t]*:[ \t]*%s[ \t]*%s" % (obj, obj, obj, obj)
awk_script = '/^[[:blank:]]*interface[[:blank:]]*\(/ {\n\
IFACEFILE=FILENAME\n\
IFACENAME = gensub("^[[:blank:]]*interface[[:blank:]]*\\\\(\`?","","g",$0);\n\
IFACENAME = gensub("\'?,.*$","","g",IFACENAME);\n\
}\n\
\n\
/^[[:blank:]]*(allow|dontaudit)[[:blank:]]+.*;[[:blank:]]*$/ {\n\
\n\
if ((length(IFACENAME) > 0) && (IFACEFILE == FILENAME)){\n\
ALLOW = gensub("^[[:blank:]]*","","g",$0)\n\
ALLOW = gensub(";[[:blank:]]*$","","g",$0)\n\
print FILENAME "\\t" IFACENAME "\\t" ALLOW;\n\
}\n\
}\
'
class context:
def __init__(self, scontext):
self.scontext = scontext
con=scontext.split(":")
self.user = con[0]
self.role = con[1]
self.type = con[2]
if len(con) > 3:
self.mls = con[3]
else:
self.mls = "s0"
def __str__(self):
return self.scontext
class accessTrans:
def __init__(self):
self.dict = {}
try:
fd = open("/usr/share/selinux/devel/include/support/obj_perm_sets.spt")
except IOError, error:
raise IOError("Reference policy generation requires the policy development package selinux-policy-devel.\n%s" % error)
records = fd.read().split("\n")
regexp = "^define *\(`([^']*)' *, *` *\{([^}]*)}'"
for r in records:
m = re.match(regexp,r)
if m != None:
self.dict[m.groups()[0]] = m.groups()[1].split()
fd.close()
def get(self, var):
l = []
for v in var:
if v in self.dict.keys():
l += self.dict[v]
else:
if v not in ("{", "}"):
l.append(v)
return l
class interfaces:
def __init__(self):
self.dict = {}
trans = accessTrans()
(input, output) = os.popen2("awk -f - /usr/share/selinux/devel/include/*/*.if 2> /dev/null")
input.write(awk_script)
input.close()
records = output.read().split("\n")
input.close()
if len(records) > 0:
regexp = "([^ \t]*)[ \t]+([^ \t]*)[ \t]+%s" % allow_regexp
for r in records:
m = re.match(regexp,r)
if m == None:
continue
val = m.groups()
file = os.path.basename(val[0]).split(".")[0]
iface = val[1]
Scon = val[3].split()
Tcon = val[4].split()
Class = val[5].split()
Access = trans.get(val[6].split())
for s in Scon:
for t in Tcon:
for c in Class:
if (s, t, c) not in self.dict.keys():
self.dict[(s, t, c)] = []
self.dict[(s, t, c)].append((Access, file, iface))
def out(self):
keys = self.dict.keys()
keys.sort()
for k in keys:
print k
for i in self.dict[k]:
print "\t", i
def match(self, Scon, Tcon, Class, Access):
keys = self.dict.keys()
ret = []
if (Scon, Tcon, Class) in keys:
for i in self.dict[(Scon, Tcon, Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
if ("$1", Tcon, Class) in keys:
for i in self.dict[("$1", Tcon, Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
if (Scon, "$1", Class) in keys:
for i in self.dict[(Scon, "$1", Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
else:
return ret
import glob, imp
pluginPath = "/usr/share/selinux/plugins"
if not pluginPath in sys.path:
sys.path.append(pluginPath)
class Analyze:
def __init__(self):
self.plugins = []
for p in glob.glob("/usr/share/selinux/plugins/*.py"):
plugin = os.path.basename(p)[:-3]
self.plugins.append(imp.load_module(plugin, *imp.find_module(plugin)))
def process(self, AVCS):
ret = []
avcs = AVCS
for p in self.plugins:
if avcs == None:
break;
r = p.analyze(avcs)
if len(r) == 0:
continue
avcs = r[1]
if len(r[0]) > 0:
ret.append(r[0])
return ret
class serule:
def __init__(self, key):
self.type = key[0]
self.source = key[1]
self.target = key[2]
self.seclass = key[3]
self.access = []
self.avcinfo = {}
self.iface = None
def add(self, avc):
for a in avc[0]:
if a not in self.avcinfo.keys():
self.avcinfo[a] = []
self.access.append(a)
self.avcinfo[a].append(avc[1:])
def getAccess(self):
if len(self.access) == 1:
return self.access[0]
else:
self.access.sort()
return "{ " + string.join(self.access) +" }"
def getName(self):
print self.avcinfo
def out(self, verbose = 0):
ret = ""
ret = ret+"%s %s %s:%s %s;" % (self.type, self.source, self.gettarget(), self.seclass, self.getAccess())
if verbose:
keys = self.avcinfo.keys()
keys.sort()
for i in keys:
for x in self.avcinfo[i]:
ret = ret+"\n\t#TYPE=AVC MSG=%s " % x[0]
if len(x[1]):
ret=ret+"COMM=%s " % x[1]
if len(x[2]):
ret=ret+"NAME=%s " % x[2]
ret = ret + " : " + i
return ret
def gen_reference_policy(self, iface):
ret = ""
Scon = self.source
Tcon = self.gettarget()
Class = self.seclass
Access = self.getAccess()
m = iface.match(Scon,Tcon,Class,Access)
if len(m) == 0:
return self.out()
else:
file = m[0][1]
ret = "\n#%s\n"% self.out()
ret += "optional_policy(`\n"
first = True
for i in m:
if file != i[1]:
ret += "')\ngen_require(`%s', `\n" % i[1]
file = i[1]
first = True
if first:
ret += "\t%s(%s)\n" % (i[2], Scon)
first = False
else:
ret += "#\t%s(%s)\n" % (i[2], Scon)
ret += "');"
return ret
def gettarget(self):
if self.source == self.target:
return "self"
else:
return self.target
def warning(error):
sys.stderr.write("%s: " % sys.argv[0])
sys.stderr.write("%s\n" % error)
sys.stderr.flush()
class TERules:
def __init__(self, serules):
self.VALID_CMDS = ("allow", "dontaudit", "auditallow")
self.serules = serules
def load(self, input):
line = input.readline()
while line:
rec = line.split()
if len(rec) and rec[0] in self.VALID_CMDS:
self.add_terule(line)
line = input.readline()
def add_terule(self, rule):
rc = rule.split(":")
rules = rc[0].split()
type = rules[0]
(sources, targets) = self.rules_split(rules[1:])
rules = rc[1].split()
(classes, access) = self.rules_split(rules)
for scon in sources:
for tcon in targets:
for seclass in classes:
self.serules.add_rule(type, scon, tcon, seclass,access)
def rules_split(self, rules):
(idx, target ) = self.get_target(0, rules)
(idx, subject) = self.get_target(idx, rules)
return (target, subject)
def get_target(self, i, rule):
target = []
if rule[i][0] == "{":
for t in rule[i].split("{"):
if len(t):
target.append(t)
i = i+1
for s in rule[i:]:
if s.find("}") >= 0:
for s1 in s.split("}"):
if len(s1):
target.append(s1)
i = i+1
return (i, target)
target.append(s)
i = i+1
else:
if rule[i].find(";") >= 0:
for s1 in rule[i].split(";"):
if len(s1):
target.append(s1)
else:
target.append(rule[i])
i = i+1
return (i, target)
ALLOW = 0
STYPE = 1
TTYPE = 2
CLASS = 3
COMM = 1
NAME = 3
class SERules:
def __init__(self, last_reload = 0, verbose = 0):
self.last_reload = last_reload
self.initialize()
self.gen_ref_policy = False
self.verbose = verbose
self.AVCS = []
self.INVALID_SIDS = {}
def initialize(self):
self.seRules = {}
self.classes = {}
self.types = []
self.roles = []
def load(self, input):
dict = []
found = 0
line = input.readline()
while line:
rec = line.split()
for i in rec:
if i == "avc:" or i == "message=avc:" or i == "msg='avc:":
found = 1
else:
if i == "security_compute_sid:":
self.security_compute_sid(rec)
found = 1
elif i == "type=MAC_POLICY_LOAD" and self.last_reload:
self.initialize()
break
else:
dict.append(i)
if not found:
regexp = "audit\(\d+\.\d+:\d+\): policy loaded"
m = re.match(regexp, line)
if m !=None:
found =1
dict.append("load_policy")
dict.append("granted")
if found:
self.translate(dict)
found = 0
dict = []
line = input.readline()
def translate(self,dict):
AVC = {}
AVC["access"] = []
if "load_policy" in dict and self.last_reload:
self.initialize()
if "granted" in dict:
return
try:
for i in range (0, len(dict)):
if dict[i] == "{":
i = i+1
while i<len(dict) and dict[i] != "}":
AVC["access"].append(dict[i])
i = i+1
continue
t = dict[i].split('=')
if len(t) < 2:
continue
AVC[t[0]] = t[1]
for i in ("scontext", "tcontext", "tclass"):
if i not in AVC.keys():
return
if len(AVC["access"]) == 0:
return
except IndexError, e:
warning("Bad AVC Line: %s" % avc)
return
self.add_allow(AVC)
def security_compute_sid(self, rec):
dict={}
for i in rec:
t = i.split('=')
if len(t) < 2:
continue
dict[t[0]]=t[1]
try:
r = context(dict["scontext"]).role
t = context(dict["tcontext"]).type
self.add_type(t)
self.add_role(r)
self.INVALID_SIDS[(r,t)]=rec
except:
return
def add_avc(self, AVC):
for a in self.AVCS:
if a["tclass"] == AVC["tclass"] and a["access"] == AVC["access"] and a["tcontext"] == AVC["tcontext"] and a["scontext"] == AVC["scontext"] and a["comm"] == AVC["comm"] and a["name"] == AVC["name"]:
return
self.AVCS.append(AVC)
def add_rule(self, rule_type, scon, tcon, tclass, access, msg = "", comm = "", name = ""):
AVC = {}
AVC["tclass"] = tclass
AVC["access"] = access
AVC["tcon"] = tcon
AVC["scon"] = scon
AVC["comm"] = comm
AVC["name"] = name
self.add_avc(AVC)
self.add_class(tclass, access)
self.add_type(tcon)
self.add_type(scon)
key = (rule_type, scon, tcon, seclass)
if key not in self.seRules.keys():
self.seRules[key] = serule(key)
self.seRules[key].add((access, msg, comm, name ))
def add_allow(self, AVC):
self.add_class(AVC["tclass"], AVC["access"])
tcontext = context(AVC["tcontext"])
scontext = context(AVC["scontext"])
self.add_type(tcontext.type)
self.add_type(scontext.type)
self.add_role(scontext.role)
key = ("allow", scontext.type, tcontext.type, AVC["tclass"])
if key not in self.seRules.keys():
self.seRules[key] = serule(key)
avckeys = AVC.keys()
for i in ( "name", "comm", "msg" ):
if i not in avckeys:
AVC[i] = ""
self.add_avc(AVC)
self.seRules[key].add((AVC["access"], AVC["msg"], AVC["comm"], AVC["name"]))
def add_class(self,seclass, access):
if seclass not in self.classes.keys():
self.classes[seclass] = []
for a in access:
if a not in self.classes[seclass]:
self.classes[seclass].append(a)
def add_role(self,role):
if role not in self.roles:
self.roles.append(role)
def add_type(self,type):
if type not in self.types:
self.types.append(type)
def gen_reference_policy(self):
self.gen_ref_policy = True
self.iface = interfaces()
def gen_module(self, module):
if self.gen_ref_policy:
return "policy_module(%s, 1.0);" % module
else:
return "module %s 1.0;" % module
def gen_requires(self):
self.roles.sort()
self.types.sort()
keys = self.classes.keys()
keys.sort()
rec = "\n\nrequire {\n"
if not self.gen_ref_policy:
for i in keys:
access = self.classes[i]
if len(access) > 1:
access.sort()
rec += "\tclass %s {" % i
for a in access:
rec += " %s" % a
rec += " }; \n"
else:
rec += "\tclass %s %s;\n" % (i, access[0])
for i in self.types:
rec += "\ttype %s; \n" % i
if not self.gen_ref_policy:
for i in self.roles:
rec += "\trole %s; \n" % i
rec += "};\n\n"
return rec
def analyze(self):
a = Analyze()
for i in a.process(self.AVCS):
print i[0][0]
print ""
def out(self, require = 0, module = ""):
rec = ""
if len(self.seRules.keys()) == 0 and len(self.INVALID_SIDS) == 0:
raise(ValueError("No AVC messages found."))
if module != "":
rec += self.gen_module(module)
rec += self.gen_requires()
else:
if require:
rec+=self.gen_requires()
for i in self.INVALID_SIDS.keys():
rec += "role %s types %s;\n" % i
keys = self.seRules.keys()
keys.sort()
for i in keys:
if self.gen_ref_policy:
rec += self.seRules[i].gen_reference_policy(self.iface)+"\n"
else:
rec += self.seRules[i].out(self.verbose)+"\n"
return rec | contrib/sebsd/policycoreutils/audit2allow/avc.py | import sys, os, pwd, string, re, selinux
obj = "(\{[^\}]*\}|[^ \t:]*)"
allow_regexp = "(allow|dontaudit)[ \t]+%s[ \t]*%s[ \t]*:[ \t]*%s[ \t]*%s" % (obj, obj, obj, obj)
awk_script = '/^[[:blank:]]*interface[[:blank:]]*\(/ {\n\
IFACEFILE=FILENAME\n\
IFACENAME = gensub("^[[:blank:]]*interface[[:blank:]]*\\\\(\`?","","g",$0);\n\
IFACENAME = gensub("\'?,.*$","","g",IFACENAME);\n\
}\n\
\n\
/^[[:blank:]]*(allow|dontaudit)[[:blank:]]+.*;[[:blank:]]*$/ {\n\
\n\
if ((length(IFACENAME) > 0) && (IFACEFILE == FILENAME)){\n\
ALLOW = gensub("^[[:blank:]]*","","g",$0)\n\
ALLOW = gensub(";[[:blank:]]*$","","g",$0)\n\
print FILENAME "\\t" IFACENAME "\\t" ALLOW;\n\
}\n\
}\
'
class context:
def __init__(self, scontext):
self.scontext = scontext
con=scontext.split(":")
self.user = con[0]
self.role = con[1]
self.type = con[2]
if len(con) > 3:
self.mls = con[3]
else:
self.mls = "s0"
def __str__(self):
return self.scontext
class accessTrans:
def __init__(self):
self.dict = {}
try:
fd = open("/usr/share/selinux/devel/include/support/obj_perm_sets.spt")
except IOError, error:
raise IOError("Reference policy generation requires the policy development package selinux-policy-devel.\n%s" % error)
records = fd.read().split("\n")
regexp = "^define *\(`([^']*)' *, *` *\{([^}]*)}'"
for r in records:
m = re.match(regexp,r)
if m != None:
self.dict[m.groups()[0]] = m.groups()[1].split()
fd.close()
def get(self, var):
l = []
for v in var:
if v in self.dict.keys():
l += self.dict[v]
else:
if v not in ("{", "}"):
l.append(v)
return l
class interfaces:
def __init__(self):
self.dict = {}
trans = accessTrans()
(input, output) = os.popen2("awk -f - /usr/share/selinux/devel/include/*/*.if 2> /dev/null")
input.write(awk_script)
input.close()
records = output.read().split("\n")
input.close()
if len(records) > 0:
regexp = "([^ \t]*)[ \t]+([^ \t]*)[ \t]+%s" % allow_regexp
for r in records:
m = re.match(regexp,r)
if m == None:
continue
val = m.groups()
file = os.path.basename(val[0]).split(".")[0]
iface = val[1]
Scon = val[3].split()
Tcon = val[4].split()
Class = val[5].split()
Access = trans.get(val[6].split())
for s in Scon:
for t in Tcon:
for c in Class:
if (s, t, c) not in self.dict.keys():
self.dict[(s, t, c)] = []
self.dict[(s, t, c)].append((Access, file, iface))
def out(self):
keys = self.dict.keys()
keys.sort()
for k in keys:
print k
for i in self.dict[k]:
print "\t", i
def match(self, Scon, Tcon, Class, Access):
keys = self.dict.keys()
ret = []
if (Scon, Tcon, Class) in keys:
for i in self.dict[(Scon, Tcon, Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
if ("$1", Tcon, Class) in keys:
for i in self.dict[("$1", Tcon, Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
if (Scon, "$1", Class) in keys:
for i in self.dict[(Scon, "$1", Class)]:
if Access in i[0]:
if i[2].find(Access) >= 0:
ret.insert(0, i)
else:
ret.append(i)
return ret
else:
return ret
import glob, imp
pluginPath = "/usr/share/selinux/plugins"
if not pluginPath in sys.path:
sys.path.append(pluginPath)
class Analyze:
def __init__(self):
self.plugins = []
for p in glob.glob("/usr/share/selinux/plugins/*.py"):
plugin = os.path.basename(p)[:-3]
self.plugins.append(imp.load_module(plugin, *imp.find_module(plugin)))
def process(self, AVCS):
ret = []
avcs = AVCS
for p in self.plugins:
if avcs == None:
break;
r = p.analyze(avcs)
if len(r) == 0:
continue
avcs = r[1]
if len(r[0]) > 0:
ret.append(r[0])
return ret
class serule:
def __init__(self, key):
self.type = key[0]
self.source = key[1]
self.target = key[2]
self.seclass = key[3]
self.access = []
self.avcinfo = {}
self.iface = None
def add(self, avc):
for a in avc[0]:
if a not in self.avcinfo.keys():
self.avcinfo[a] = []
self.access.append(a)
self.avcinfo[a].append(avc[1:])
def getAccess(self):
if len(self.access) == 1:
return self.access[0]
else:
self.access.sort()
return "{ " + string.join(self.access) +" }"
def getName(self):
print self.avcinfo
def out(self, verbose = 0):
ret = ""
ret = ret+"%s %s %s:%s %s;" % (self.type, self.source, self.gettarget(), self.seclass, self.getAccess())
if verbose:
keys = self.avcinfo.keys()
keys.sort()
for i in keys:
for x in self.avcinfo[i]:
ret = ret+"\n\t#TYPE=AVC MSG=%s " % x[0]
if len(x[1]):
ret=ret+"COMM=%s " % x[1]
if len(x[2]):
ret=ret+"NAME=%s " % x[2]
ret = ret + " : " + i
return ret
def gen_reference_policy(self, iface):
ret = ""
Scon = self.source
Tcon = self.gettarget()
Class = self.seclass
Access = self.getAccess()
m = iface.match(Scon,Tcon,Class,Access)
if len(m) == 0:
return self.out()
else:
file = m[0][1]
ret = "\n#%s\n"% self.out()
ret += "optional_policy(`\n"
first = True
for i in m:
if file != i[1]:
ret += "')\ngen_require(`%s', `\n" % i[1]
file = i[1]
first = True
if first:
ret += "\t%s(%s)\n" % (i[2], Scon)
first = False
else:
ret += "#\t%s(%s)\n" % (i[2], Scon)
ret += "');"
return ret
def gettarget(self):
if self.source == self.target:
return "self"
else:
return self.target
def warning(error):
sys.stderr.write("%s: " % sys.argv[0])
sys.stderr.write("%s\n" % error)
sys.stderr.flush()
class TERules:
def __init__(self, serules):
self.VALID_CMDS = ("allow", "dontaudit", "auditallow")
self.serules = serules
def load(self, input):
line = input.readline()
while line:
rec = line.split()
if len(rec) and rec[0] in self.VALID_CMDS:
self.add_terule(line)
line = input.readline()
def add_terule(self, rule):
rc = rule.split(":")
rules = rc[0].split()
type = rules[0]
(sources, targets) = self.rules_split(rules[1:])
rules = rc[1].split()
(classes, access) = self.rules_split(rules)
for scon in sources:
for tcon in targets:
for seclass in classes:
self.serules.add_rule(type, scon, tcon, seclass,access)
def rules_split(self, rules):
(idx, target ) = self.get_target(0, rules)
(idx, subject) = self.get_target(idx, rules)
return (target, subject)
def get_target(self, i, rule):
target = []
if rule[i][0] == "{":
for t in rule[i].split("{"):
if len(t):
target.append(t)
i = i+1
for s in rule[i:]:
if s.find("}") >= 0:
for s1 in s.split("}"):
if len(s1):
target.append(s1)
i = i+1
return (i, target)
target.append(s)
i = i+1
else:
if rule[i].find(";") >= 0:
for s1 in rule[i].split(";"):
if len(s1):
target.append(s1)
else:
target.append(rule[i])
i = i+1
return (i, target)
ALLOW = 0
STYPE = 1
TTYPE = 2
CLASS = 3
COMM = 1
NAME = 3
class SERules:
def __init__(self, last_reload = 0, verbose = 0):
self.last_reload = last_reload
self.initialize()
self.gen_ref_policy = False
self.verbose = verbose
self.AVCS = []
self.INVALID_SIDS = {}
def initialize(self):
self.seRules = {}
self.classes = {}
self.types = []
self.roles = []
def load(self, input):
dict = []
found = 0
line = input.readline()
while line:
rec = line.split()
for i in rec:
if i == "avc:" or i == "message=avc:" or i == "msg='avc:":
found = 1
else:
if i == "security_compute_sid:":
self.security_compute_sid(rec)
found = 1
elif i == "type=MAC_POLICY_LOAD" and self.last_reload:
self.initialize()
break
else:
dict.append(i)
if not found:
regexp = "audit\(\d+\.\d+:\d+\): policy loaded"
m = re.match(regexp, line)
if m !=None:
found =1
dict.append("load_policy")
dict.append("granted")
if found:
self.translate(dict)
found = 0
dict = []
line = input.readline()
def translate(self,dict):
AVC = {}
AVC["access"] = []
if "load_policy" in dict and self.last_reload:
self.initialize()
if "granted" in dict:
return
try:
for i in range (0, len(dict)):
if dict[i] == "{":
i = i+1
while i<len(dict) and dict[i] != "}":
AVC["access"].append(dict[i])
i = i+1
continue
t = dict[i].split('=')
if len(t) < 2:
continue
AVC[t[0]] = t[1]
for i in ("scontext", "tcontext", "tclass"):
if i not in AVC.keys():
return
if len(AVC["access"]) == 0:
return
except IndexError, e:
warning("Bad AVC Line: %s" % avc)
return
self.add_allow(AVC)
def security_compute_sid(self, rec):
dict={}
for i in rec:
t = i.split('=')
if len(t) < 2:
continue
dict[t[0]]=t[1]
try:
r = context(dict["scontext"]).role
t = context(dict["tcontext"]).type
self.add_type(t)
self.add_role(r)
self.INVALID_SIDS[(r,t)]=rec
except:
return
def add_avc(self, AVC):
for a in self.AVCS:
if a["tclass"] == AVC["tclass"] and a["access"] == AVC["access"] and a["tcontext"] == AVC["tcontext"] and a["scontext"] == AVC["scontext"] and a["comm"] == AVC["comm"] and a["name"] == AVC["name"]:
return
self.AVCS.append(AVC)
def add_rule(self, rule_type, scon, tcon, tclass, access, msg = "", comm = "", name = ""):
AVC = {}
AVC["tclass"] = tclass
AVC["access"] = access
AVC["tcon"] = tcon
AVC["scon"] = scon
AVC["comm"] = comm
AVC["name"] = name
self.add_avc(AVC)
self.add_class(tclass, access)
self.add_type(tcon)
self.add_type(scon)
key = (rule_type, scon, tcon, seclass)
if key not in self.seRules.keys():
self.seRules[key] = serule(key)
self.seRules[key].add((access, msg, comm, name ))
def add_allow(self, AVC):
self.add_class(AVC["tclass"], AVC["access"])
tcontext = context(AVC["tcontext"])
scontext = context(AVC["scontext"])
self.add_type(tcontext.type)
self.add_type(scontext.type)
self.add_role(scontext.role)
key = ("allow", scontext.type, tcontext.type, AVC["tclass"])
if key not in self.seRules.keys():
self.seRules[key] = serule(key)
avckeys = AVC.keys()
for i in ( "name", "comm", "msg" ):
if i not in avckeys:
AVC[i] = ""
self.add_avc(AVC)
self.seRules[key].add((AVC["access"], AVC["msg"], AVC["comm"], AVC["name"]))
def add_class(self,seclass, access):
if seclass not in self.classes.keys():
self.classes[seclass] = []
for a in access:
if a not in self.classes[seclass]:
self.classes[seclass].append(a)
def add_role(self,role):
if role not in self.roles:
self.roles.append(role)
def add_type(self,type):
if type not in self.types:
self.types.append(type)
def gen_reference_policy(self):
self.gen_ref_policy = True
self.iface = interfaces()
def gen_module(self, module):
if self.gen_ref_policy:
return "policy_module(%s, 1.0);" % module
else:
return "module %s 1.0;" % module
def gen_requires(self):
self.roles.sort()
self.types.sort()
keys = self.classes.keys()
keys.sort()
rec = "\n\nrequire {\n"
if not self.gen_ref_policy:
for i in keys:
access = self.classes[i]
if len(access) > 1:
access.sort()
rec += "\tclass %s {" % i
for a in access:
rec += " %s" % a
rec += " }; \n"
else:
rec += "\tclass %s %s;\n" % (i, access[0])
for i in self.types:
rec += "\ttype %s; \n" % i
if not self.gen_ref_policy:
for i in self.roles:
rec += "\trole %s; \n" % i
rec += "};\n\n"
return rec
def analyze(self):
a = Analyze()
for i in a.process(self.AVCS):
print i[0][0]
print ""
def out(self, require = 0, module = ""):
rec = ""
if len(self.seRules.keys()) == 0 and len(self.INVALID_SIDS) == 0:
raise(ValueError("No AVC messages found."))
if module != "":
rec += self.gen_module(module)
rec += self.gen_requires()
else:
if require:
rec+=self.gen_requires()
for i in self.INVALID_SIDS.keys():
rec += "role %s types %s;\n" % i
keys = self.seRules.keys()
keys.sort()
for i in keys:
if self.gen_ref_policy:
rec += self.seRules[i].gen_reference_policy(self.iface)+"\n"
else:
rec += self.seRules[i].out(self.verbose)+"\n"
return rec | 0.064337 | 0.147218 |
from datetime import datetime
from enum import IntEnum
from typing import Any, Optional, Union
from pydisco.http import Http
from pydisco.utils import convert_snowflake_to_datetime
class UserFlags(IntEnum):
"""
This enum represents flags that can be added to a user's account.
See Also
--------
Official Discord documentation:
https://discord.com/developers/docs/resources/user#user-object-user-flags
"""
NONE = 0
"""None"""
DISCORD_EMPLOYEE = 1 << 0
"""Discord Employee."""
PARTNERED_SERVER_OWNER = 1 << 1
"""Owner of a partnered Discord server."""
HYPESQUAD_EVENTS = 1 << 2
"""HypeSquad Events."""
BUG_HUNTER_LEVEL_1 = 1 << 3
"""Bug Hunter Level 1."""
HYPESQUAD_BRAVERY = 1 << 6
"""HypeSquad House of Bravery."""
HYPESQUAD_BRILLIANCE = 1 << 7
"""HypeSquad House of Brilliance."""
HYPESQUAD_BALANCE = 1 << 8
"""HypeSquad House of Balance."""
EARLY_SUPPORTER = 1 << 9
"""Early Supporter."""
TEAM_USER = 1 << 10
"""Team user."""
BUG_HUNTER_LEVEL_2 = 1 << 14
"""Bug Hunter Level 2."""
VERIFIED_BOT = 1 << 16
"""Verified Bot."""
EARLY_VERIFIED_DEVELOPER = 1 << 17
"""Early verified Bot Developer."""
DISCORD_CERTIFIED_MODERATOR = 1 << 18
"""Discord Certified Moderator."""
class PremiumType(IntEnum):
"""
This enum represents the types of paid user subscriptions.
See Also
--------
Official Discord documentation:
https://discord.com/developers/docs/resources/user#user-object-premium-types
"""
NONE = 0
"""No premium for this user."""
NITRO_CLASSIC = 1
"""This user have Nitro Classic subscription."""
FULL_NITRO = 2
"""This user have default Nitro subscription."""
class User:
"""
This class represents users in Discord.
Attributes
----------
id : int
Unique Snowflake ID for this user.
username : str
Displayed user's name.
discriminator : str
Not a unique set of 4 numbers that are required to find the user's account.
avatar : str, any
The hash string of the user's avatar.
bot : bool, optional
Is the user a bot?
system : bool, optional
Is the user a system?
mfa_enabled : bool, optional
Whether two-factor authentication is enabled?
banner : str, any, optional
This user's banner hash.
accent_color : int, any, optional
Hexadecimal value for color of this user.
locale : str, optional
Localization of the user's client.
verified : bool, optional
Is the user verified?
email : str, any, optional
E-mail address for this user.
flags : UserFlags, optional
Flags this user.
premium_type : PremiumType, optional
Type of premium user subscription.
public_flags : UserFlags, optional
Public flags of the user.
Methods
-------
human : bool
Is the user a human?
mention : str
Mention for this user.
created_at : datetime
When this user was created.
See Also
--------
Official Discord documentation: https://discord.com/developers/docs/resources/user
"""
def __init__(self, data, _http: Http) -> None:
self.id: int = int(data.get("id", 0))
self.username: str = data.get("username", None)
self.discriminator: str = data.get("discriminator", None)
self.avatar: Union[str, Any] = data.get("avatar", None)
self.bot: Optional[bool] = data.get("bot", False)
self.system: Optional[bool] = data.get("system", False)
self.mfa_enabled: Optional[bool] = data.get("mfa_enabled", False)
self.banner: Optional[Union[str, Any]] = data.get("banner", None)
self.accent_color: Optional[Union[int, Any]] = data.get("accent_color", 0)
self.locale: Optional[str] = data.get("locale", None)
self.verified: Optional[bool] = data.get("verified", False)
self.email: Optional[Union[str, Any]] = data.get("email", None)
self.flags: Optional[UserFlags] = UserFlags(data.get("flags", 0))
self.premium_type: Optional[PremiumType] = PremiumType(data.get("premium_type", 0))
self.public_flags: Optional[UserFlags] = UserFlags(data.get("public_flags", 0))
def __str__(self) -> str:
return f"{self.username}#{self.discriminator}"
@property
def created_at(self) -> datetime:
""":datetime: When this user was created."""
return convert_snowflake_to_datetime(self.id)
@property
def mention(self) -> str:
""":str: Mention for this user."""
return f"<@{self.id}>"
@property
def human(self) -> bool:
""":bool: Is the user a real person?"""
return not (self.bot and self.system) | pydisco/user.py | from datetime import datetime
from enum import IntEnum
from typing import Any, Optional, Union
from pydisco.http import Http
from pydisco.utils import convert_snowflake_to_datetime
class UserFlags(IntEnum):
"""
This enum represents flags that can be added to a user's account.
See Also
--------
Official Discord documentation:
https://discord.com/developers/docs/resources/user#user-object-user-flags
"""
NONE = 0
"""None"""
DISCORD_EMPLOYEE = 1 << 0
"""Discord Employee."""
PARTNERED_SERVER_OWNER = 1 << 1
"""Owner of a partnered Discord server."""
HYPESQUAD_EVENTS = 1 << 2
"""HypeSquad Events."""
BUG_HUNTER_LEVEL_1 = 1 << 3
"""Bug Hunter Level 1."""
HYPESQUAD_BRAVERY = 1 << 6
"""HypeSquad House of Bravery."""
HYPESQUAD_BRILLIANCE = 1 << 7
"""HypeSquad House of Brilliance."""
HYPESQUAD_BALANCE = 1 << 8
"""HypeSquad House of Balance."""
EARLY_SUPPORTER = 1 << 9
"""Early Supporter."""
TEAM_USER = 1 << 10
"""Team user."""
BUG_HUNTER_LEVEL_2 = 1 << 14
"""Bug Hunter Level 2."""
VERIFIED_BOT = 1 << 16
"""Verified Bot."""
EARLY_VERIFIED_DEVELOPER = 1 << 17
"""Early verified Bot Developer."""
DISCORD_CERTIFIED_MODERATOR = 1 << 18
"""Discord Certified Moderator."""
class PremiumType(IntEnum):
"""
This enum represents the types of paid user subscriptions.
See Also
--------
Official Discord documentation:
https://discord.com/developers/docs/resources/user#user-object-premium-types
"""
NONE = 0
"""No premium for this user."""
NITRO_CLASSIC = 1
"""This user have Nitro Classic subscription."""
FULL_NITRO = 2
"""This user have default Nitro subscription."""
class User:
"""
This class represents users in Discord.
Attributes
----------
id : int
Unique Snowflake ID for this user.
username : str
Displayed user's name.
discriminator : str
Not a unique set of 4 numbers that are required to find the user's account.
avatar : str, any
The hash string of the user's avatar.
bot : bool, optional
Is the user a bot?
system : bool, optional
Is the user a system?
mfa_enabled : bool, optional
Whether two-factor authentication is enabled?
banner : str, any, optional
This user's banner hash.
accent_color : int, any, optional
Hexadecimal value for color of this user.
locale : str, optional
Localization of the user's client.
verified : bool, optional
Is the user verified?
email : str, any, optional
E-mail address for this user.
flags : UserFlags, optional
Flags this user.
premium_type : PremiumType, optional
Type of premium user subscription.
public_flags : UserFlags, optional
Public flags of the user.
Methods
-------
human : bool
Is the user a human?
mention : str
Mention for this user.
created_at : datetime
When this user was created.
See Also
--------
Official Discord documentation: https://discord.com/developers/docs/resources/user
"""
def __init__(self, data, _http: Http) -> None:
self.id: int = int(data.get("id", 0))
self.username: str = data.get("username", None)
self.discriminator: str = data.get("discriminator", None)
self.avatar: Union[str, Any] = data.get("avatar", None)
self.bot: Optional[bool] = data.get("bot", False)
self.system: Optional[bool] = data.get("system", False)
self.mfa_enabled: Optional[bool] = data.get("mfa_enabled", False)
self.banner: Optional[Union[str, Any]] = data.get("banner", None)
self.accent_color: Optional[Union[int, Any]] = data.get("accent_color", 0)
self.locale: Optional[str] = data.get("locale", None)
self.verified: Optional[bool] = data.get("verified", False)
self.email: Optional[Union[str, Any]] = data.get("email", None)
self.flags: Optional[UserFlags] = UserFlags(data.get("flags", 0))
self.premium_type: Optional[PremiumType] = PremiumType(data.get("premium_type", 0))
self.public_flags: Optional[UserFlags] = UserFlags(data.get("public_flags", 0))
def __str__(self) -> str:
return f"{self.username}#{self.discriminator}"
@property
def created_at(self) -> datetime:
""":datetime: When this user was created."""
return convert_snowflake_to_datetime(self.id)
@property
def mention(self) -> str:
""":str: Mention for this user."""
return f"<@{self.id}>"
@property
def human(self) -> bool:
""":bool: Is the user a real person?"""
return not (self.bot and self.system) | 0.919077 | 0.356783 |
import torch
import torchaudio
from torch.utils.data import DataLoader
from torch import nn
from USDataset import US8KDataset
BATCH_SIZE = 64
EPOCHS = 20
LEARNING_RATE = 0.001
ANNOTATIONS_FILE = "UrbanSound8K/metadata/UrbanSound8K.csv"
AUDIO_DIR = "UrbanSound8K/audio"
SAMPLE_RATE = 44100
NUM_SAMPLES = 44100
device = "cpu"
class CNN(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Sequential(
nn.Conv2d(
in_channels=1,
out_channels=8,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(8),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv2 = nn.Sequential(
nn.Conv2d(
in_channels=8,
out_channels=16,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(16),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv3 = nn.Sequential(
nn.Conv2d(
in_channels=16,
out_channels=32,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(32),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv4 = nn.Sequential(
nn.Conv2d(
in_channels=32,
out_channels=64,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.flatten = nn.Flatten()
self.linear = nn.Linear(64, 10)
self.softmax = nn.Softmax(dim=1)
def forward(self, input_data):
x = self.conv1(input_data)
x = self.conv2(x)
x = self.conv3(x)
x = self.conv4(x)
x = self.flatten(x)
x = self.linear(x)
x = self.softmax(x)
return x
def train(model, train_loader, optimiser, device, epochs):
correctly_classified = 0
total = 0
for epochX in range(epochs):
print(f"Epoch {epochX + 1}")
for input, target in train_loader:
input, target = input.to(device), target.to(device)
optimiser.zero_grad()
output = model(input)
_, predicted = torch.max(output, 1)
total += target.size(0)
correctly_classified += (predicted == target).sum().item()
loss = nn.CrossEntropyLoss()(output, target)
loss.backward()
optimiser.step()
accuracy = 100.0 * correctly_classified / total
print(' Accuracy in Epoch {}: {:.0f}% \n'.format(epochX, accuracy))
print(f"loss: {loss.item()}")
print("---------------------------")
print("Finished training")
if __name__ == "__main__":
# instantiating our dataset object and create data loader
mel_spectrogram = torchaudio.transforms.MelSpectrogram(
sample_rate=SAMPLE_RATE,
n_fft=1024,
hop_length=512,
n_mels=64
)
usd = US8KDataset(ANNOTATIONS_FILE,
AUDIO_DIR,
mel_spectrogram,
SAMPLE_RATE,
NUM_SAMPLES,
device)
train_dataloader = DataLoader(usd, batch_size=BATCH_SIZE)
# construct model and assign it to device
cnn = CNN().to(device)
print(cnn)
optimiser = torch.optim.AdamW(cnn.parameters(), lr=LEARNING_RATE)
# train model
train(cnn, train_dataloader, optimiser, device, EPOCHS)
# save model
torch.save(cnn.state_dict(), "trainedCNN.pth")
print("Trained feed forward net saved at trainedCNN.pth") | model.py | import torch
import torchaudio
from torch.utils.data import DataLoader
from torch import nn
from USDataset import US8KDataset
BATCH_SIZE = 64
EPOCHS = 20
LEARNING_RATE = 0.001
ANNOTATIONS_FILE = "UrbanSound8K/metadata/UrbanSound8K.csv"
AUDIO_DIR = "UrbanSound8K/audio"
SAMPLE_RATE = 44100
NUM_SAMPLES = 44100
device = "cpu"
class CNN(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Sequential(
nn.Conv2d(
in_channels=1,
out_channels=8,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(8),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv2 = nn.Sequential(
nn.Conv2d(
in_channels=8,
out_channels=16,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(16),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv3 = nn.Sequential(
nn.Conv2d(
in_channels=16,
out_channels=32,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(32),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.conv4 = nn.Sequential(
nn.Conv2d(
in_channels=32,
out_channels=64,
kernel_size=3,
stride=2,
padding=2,
bias=False
),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2)
)
self.flatten = nn.Flatten()
self.linear = nn.Linear(64, 10)
self.softmax = nn.Softmax(dim=1)
def forward(self, input_data):
x = self.conv1(input_data)
x = self.conv2(x)
x = self.conv3(x)
x = self.conv4(x)
x = self.flatten(x)
x = self.linear(x)
x = self.softmax(x)
return x
def train(model, train_loader, optimiser, device, epochs):
correctly_classified = 0
total = 0
for epochX in range(epochs):
print(f"Epoch {epochX + 1}")
for input, target in train_loader:
input, target = input.to(device), target.to(device)
optimiser.zero_grad()
output = model(input)
_, predicted = torch.max(output, 1)
total += target.size(0)
correctly_classified += (predicted == target).sum().item()
loss = nn.CrossEntropyLoss()(output, target)
loss.backward()
optimiser.step()
accuracy = 100.0 * correctly_classified / total
print(' Accuracy in Epoch {}: {:.0f}% \n'.format(epochX, accuracy))
print(f"loss: {loss.item()}")
print("---------------------------")
print("Finished training")
if __name__ == "__main__":
# instantiating our dataset object and create data loader
mel_spectrogram = torchaudio.transforms.MelSpectrogram(
sample_rate=SAMPLE_RATE,
n_fft=1024,
hop_length=512,
n_mels=64
)
usd = US8KDataset(ANNOTATIONS_FILE,
AUDIO_DIR,
mel_spectrogram,
SAMPLE_RATE,
NUM_SAMPLES,
device)
train_dataloader = DataLoader(usd, batch_size=BATCH_SIZE)
# construct model and assign it to device
cnn = CNN().to(device)
print(cnn)
optimiser = torch.optim.AdamW(cnn.parameters(), lr=LEARNING_RATE)
# train model
train(cnn, train_dataloader, optimiser, device, EPOCHS)
# save model
torch.save(cnn.state_dict(), "trainedCNN.pth")
print("Trained feed forward net saved at trainedCNN.pth") | 0.931579 | 0.339007 |
import argparse
import pandas as pd
import numpy as np
def net_stats(net_df, n_edges, pos_df, neg_df, wt_attr):
top_df = net_df.head(n_edges)
tp_shape = top_df[ top_df.edge.isin(pos_df.edge) ].shape
fp_shape = top_df[ top_df.edge.isin(neg_df.edge) ].shape
max_wt = np.max(top_df[wt_attr])
min_wt = np.min(top_df[wt_attr])
ntp = float(tp_shape[0])
nfp = float(fp_shape[0])
nfn = float(pos_df.shape[0]) - ntp
ntn = float(neg_df.shape[0]) - nfp
stats_dct = {
'Edges': n_edges, 'MaxWt': max_wt, 'MinWt': min_wt,
'TP': ntp, 'FP': nfp, 'TN': ntn, 'FN': nfn,
'Sensitivity/Recall': ntp/(ntp+nfn),
'Specificity': ntn/(ntn+nfp) if (ntn+nfp) > 0 else 1.0,
'Precision': ntp/(ntp+nfp) if (ntp+nfp) > 0 else 1.0,
'Accuracy': (ntp+ntn)/(ntp+ntn+nfp+nfn),
'F1' : (2.0*ntp)/((2*ntp) + nfp + nfn)
}
return stats_dct
def network_stats_df(net_df, pos_df, neg_df, wt_attr):
stats_lst = [net_stats(net_df, nx, pos_df, neg_df, wt_attr) for nx in range(100_000, 10_000_000, 100_000)]
return pd.DataFrame(data=stats_lst)
def network_stats(network_file, pos_file, neg_file, wt_attr):
net_df = pd.read_csv(network_file, sep="\t")
net_df.sort_values(by=wt_attr, inplace=True, ascending=False)
pos_df = pd.read_csv(pos_file)
neg_df = pd.read_csv(neg_file)
return network_stats_df(net_df, pos_df, neg_df, wt_attr)
if __name__ == "__main__":
PROG_DESC = """Find Sensitivity Statistics"""
ARGPARSER = argparse.ArgumentParser(description=PROG_DESC)
ARGPARSER.add_argument("network_file")
ARGPARSER.add_argument("pos_file")
ARGPARSER.add_argument("neg_file")
ARGPARSER.add_argument("output_file")
ARGPARSER.add_argument("-t", "--wt_attr", type=str, default='wt',
help="name of weight attribute")
CMDARGS = ARGPARSER.parse_args()
print(CMDARGS.network_file, CMDARGS.pos_file, CMDARGS.neg_file,
CMDARGS.output_file, CMDARGS.wt_attr)
odf = network_stats(CMDARGS.network_file, CMDARGS.pos_file,
CMDARGS.neg_file, CMDARGS.wt_attr)
odf.to_csv(CMDARGS.output_file, sep="\t", index=False) | utils/analyse_network.py | import argparse
import pandas as pd
import numpy as np
def net_stats(net_df, n_edges, pos_df, neg_df, wt_attr):
top_df = net_df.head(n_edges)
tp_shape = top_df[ top_df.edge.isin(pos_df.edge) ].shape
fp_shape = top_df[ top_df.edge.isin(neg_df.edge) ].shape
max_wt = np.max(top_df[wt_attr])
min_wt = np.min(top_df[wt_attr])
ntp = float(tp_shape[0])
nfp = float(fp_shape[0])
nfn = float(pos_df.shape[0]) - ntp
ntn = float(neg_df.shape[0]) - nfp
stats_dct = {
'Edges': n_edges, 'MaxWt': max_wt, 'MinWt': min_wt,
'TP': ntp, 'FP': nfp, 'TN': ntn, 'FN': nfn,
'Sensitivity/Recall': ntp/(ntp+nfn),
'Specificity': ntn/(ntn+nfp) if (ntn+nfp) > 0 else 1.0,
'Precision': ntp/(ntp+nfp) if (ntp+nfp) > 0 else 1.0,
'Accuracy': (ntp+ntn)/(ntp+ntn+nfp+nfn),
'F1' : (2.0*ntp)/((2*ntp) + nfp + nfn)
}
return stats_dct
def network_stats_df(net_df, pos_df, neg_df, wt_attr):
stats_lst = [net_stats(net_df, nx, pos_df, neg_df, wt_attr) for nx in range(100_000, 10_000_000, 100_000)]
return pd.DataFrame(data=stats_lst)
def network_stats(network_file, pos_file, neg_file, wt_attr):
net_df = pd.read_csv(network_file, sep="\t")
net_df.sort_values(by=wt_attr, inplace=True, ascending=False)
pos_df = pd.read_csv(pos_file)
neg_df = pd.read_csv(neg_file)
return network_stats_df(net_df, pos_df, neg_df, wt_attr)
if __name__ == "__main__":
PROG_DESC = """Find Sensitivity Statistics"""
ARGPARSER = argparse.ArgumentParser(description=PROG_DESC)
ARGPARSER.add_argument("network_file")
ARGPARSER.add_argument("pos_file")
ARGPARSER.add_argument("neg_file")
ARGPARSER.add_argument("output_file")
ARGPARSER.add_argument("-t", "--wt_attr", type=str, default='wt',
help="name of weight attribute")
CMDARGS = ARGPARSER.parse_args()
print(CMDARGS.network_file, CMDARGS.pos_file, CMDARGS.neg_file,
CMDARGS.output_file, CMDARGS.wt_attr)
odf = network_stats(CMDARGS.network_file, CMDARGS.pos_file,
CMDARGS.neg_file, CMDARGS.wt_attr)
odf.to_csv(CMDARGS.output_file, sep="\t", index=False) | 0.418935 | 0.205197 |
import os
import re
from git import Repo
import syncmanagerclient.util.globalproperties as globalproperties
class DeletionRegistration:
def __init__(self, **kwargs):
self.branch_path = kwargs.get('branch_path', None)
self.registry_dir = globalproperties.var_dir
# first check if directory is a git working tree
self.dir = kwargs.get('git_repo_path')
self.configs = []
self.mode = kwargs.get('mode', None)
self.local_branch_exists = False
def get_mode(self):
if os.path.isdir(self.dir + '/.git'):
# first check if this branch exists
self.gitrepo = Repo(self.dir)
if not hasattr(self.gitrepo.heads, self.branch_path):
print('There is no local branch ' + self.branch_path)
self.mode = 'git'
return
self.mode = 'git'
self.local_branch_exists = True
return
# to be implemented: Unison check
def get_config(self):
self.get_mode()
if not self.mode:
return None
configs = []
# get remote repo
if self.mode == 'git':
# fetch url of origin
if self.gitrepo.remotes:
for remote in self.gitrepo.remotes:
remote_urls = []
for remote_url in remote.urls:
remote_urls.append(remote_url)
if len(remote_urls) > 1:
print(f"Multiple urls defined for this remote: {str(remote_urls)}. Skip")
continue
if len(remote_urls) == 0:
print(f"No remote url defined. Skip")
continue
remote_url = remote_urls[0]
config = dict()
config['source'] = self.dir
config['url'] = remote_url
config['remote_repo'] = remote.name
self.configs.append(config)
elif self.mode == 'unison':
# to be implemented
pass
def register_path(self):
self.get_config()
if self.mode == 'git':
for config in self.configs:
remote_repo_name = config.get('remote_repo', None)
if not remote_repo_name:
continue
registry_file = self.get_registry_file_path(remote_repo_name)
f = open(registry_file, 'a+')
entry = self.dir + '\t' + self.branch_path + '\n'
f.write(entry)
f.close()
def get_registry_file_path(self, repo_name):
return self.registry_dir + '/' + self.mode + '.' + repo_name + '.txt'
def read_and_flush_registry(self, repo_name):
registry_file = self.get_registry_file_path(repo_name)
if not os.path.isfile(registry_file):
return []
f = open(registry_file, 'r+')
entries = []
lines = f.readlines()
for line in lines:
# replace spaces with tab, in case tab has been replaced by space in the meantime
line = re.sub(' +', '\t', line)
line = line.strip()
if not line:
continue
entry = line.split('\t')
entry[0] = entry[0].strip()
entry[1] = entry[1].strip()
entries.append(entry)
f.seek(0)
f.close()
os.remove(registry_file)
return entries
def write_registry(self, repo_name, entries):
registry_file = self.get_registry_file_path(repo_name)
if len(entries) == 0:
return
f = open(registry_file, 'w+')
for entry in entries:
line = '\t'.join(entry) + '\n'
f.write(line)
f.close() | syncmanagerclient/syncmanagerclient/clients/deletion_registration.py | import os
import re
from git import Repo
import syncmanagerclient.util.globalproperties as globalproperties
class DeletionRegistration:
def __init__(self, **kwargs):
self.branch_path = kwargs.get('branch_path', None)
self.registry_dir = globalproperties.var_dir
# first check if directory is a git working tree
self.dir = kwargs.get('git_repo_path')
self.configs = []
self.mode = kwargs.get('mode', None)
self.local_branch_exists = False
def get_mode(self):
if os.path.isdir(self.dir + '/.git'):
# first check if this branch exists
self.gitrepo = Repo(self.dir)
if not hasattr(self.gitrepo.heads, self.branch_path):
print('There is no local branch ' + self.branch_path)
self.mode = 'git'
return
self.mode = 'git'
self.local_branch_exists = True
return
# to be implemented: Unison check
def get_config(self):
self.get_mode()
if not self.mode:
return None
configs = []
# get remote repo
if self.mode == 'git':
# fetch url of origin
if self.gitrepo.remotes:
for remote in self.gitrepo.remotes:
remote_urls = []
for remote_url in remote.urls:
remote_urls.append(remote_url)
if len(remote_urls) > 1:
print(f"Multiple urls defined for this remote: {str(remote_urls)}. Skip")
continue
if len(remote_urls) == 0:
print(f"No remote url defined. Skip")
continue
remote_url = remote_urls[0]
config = dict()
config['source'] = self.dir
config['url'] = remote_url
config['remote_repo'] = remote.name
self.configs.append(config)
elif self.mode == 'unison':
# to be implemented
pass
def register_path(self):
self.get_config()
if self.mode == 'git':
for config in self.configs:
remote_repo_name = config.get('remote_repo', None)
if not remote_repo_name:
continue
registry_file = self.get_registry_file_path(remote_repo_name)
f = open(registry_file, 'a+')
entry = self.dir + '\t' + self.branch_path + '\n'
f.write(entry)
f.close()
def get_registry_file_path(self, repo_name):
return self.registry_dir + '/' + self.mode + '.' + repo_name + '.txt'
def read_and_flush_registry(self, repo_name):
registry_file = self.get_registry_file_path(repo_name)
if not os.path.isfile(registry_file):
return []
f = open(registry_file, 'r+')
entries = []
lines = f.readlines()
for line in lines:
# replace spaces with tab, in case tab has been replaced by space in the meantime
line = re.sub(' +', '\t', line)
line = line.strip()
if not line:
continue
entry = line.split('\t')
entry[0] = entry[0].strip()
entry[1] = entry[1].strip()
entries.append(entry)
f.seek(0)
f.close()
os.remove(registry_file)
return entries
def write_registry(self, repo_name, entries):
registry_file = self.get_registry_file_path(repo_name)
if len(entries) == 0:
return
f = open(registry_file, 'w+')
for entry in entries:
line = '\t'.join(entry) + '\n'
f.write(line)
f.close() | 0.221687 | 0.058615 |
class ImageFolderDataset(Dataset):
def __init__(self, root_path, transform=None, target_window=100, first_k=None,
last_k=None, skip_every=1, repeat=1, cache='in_memory',
shuffle_mapping=False, forced_mapping=None, real_shuffle=False,
batch_size=args.batch_size, logger=print, config={
'train': {
'transform':None,
'repeat':10},
'eval': {
'transform': None,
'repeat': 1
}
}):
self.configs = config
self.current_mode = list(config.keys())[0]
self.repeat = repeat #config[self.current_mode]['repeat']
self.cache = cache
self.batch_size = batch_size
self.logger = logger
filenames = sorted(os.listdir(root_path))
self.sets = [f.split('_')[-1].split('--')[0] for f in filenames]
self.set_lookup = {f: s for f, s in zip(filenames, self.sets)}
self.set_list = []
total_labels = 0
for setname in np.unique(self.sets):
set_seen = 0
for i, f in enumerate([f for f in filenames if self.set_lookup[f] == setname]):
self.set_list.append({
"label": total_labels,
"file": f,
"order": i
})
set_seen += 1
if set_seen % target_window == 0:
total_labels += 1
total_labels += 1
self.target_lookup = {s["file"]: s["label"] for s in self.set_list}
self.order_lookup = {s["file"]: s["order"] for s in self.set_list}
if first_k is not None:
filenames = filenames[:first_k]
elif last_k is not None:
filenames = filenames[-last_k:]
filenames = filenames[::skip_every]
self.logger(f"Found {len(filenames)} files in {root_path}")
self.do_shuffle = real_shuffle
if shuffle_mapping:
self.init_mapping = np.random.permutation(len(filenames))
else:
self.init_mapping = [i for i in range(len(filenames))]
if forced_mapping is not None:
self.init_mapping = forced_mapping
self.logger(f"Using cache strategy '{cache}'")
self.files = []
self.filenames = []
with tqdm(self.init_mapping) as pbar:
for file_idx in pbar:
try:
filename = filenames[file_idx]
filepath = os.path.join(root_path, filename)
self.filenames.append(filename)
if cache == 'none':
self.files.append(filepath)
elif cache == 'bin':
bin_root = os.path.join(os.path.dirname(root_path),
'_bin_' + os.path.basename(root_path))
if not os.path.exists(bin_root):
os.mkdir(bin_root)
print('mkdir', bin_root)
bin_file = os.path.join(
bin_root, filename.split('.')[0] + '.pkl')
if not os.path.exists(bin_file):
with open(bin_file, 'wb') as f:
pickle.dump(imageio.imread(filepath), f)
print('dump', bin_file)
self.files.append(bin_file)
elif cache == 'in_memory':
self.files.append(Image.open(filepath).convert('RGB'))
except Exception as e:
print(f"Failed to load image {filepath}: {e}")
self.mapping = [i for i in range(len(self.files))]
self.actual_size = len(self.mapping)
self.targets = [self.target_lookup[f] for f in self.filenames]
self.classes = np.unique(self.targets)
self.num_class = len(self.classes)
self.transform = transform
def __len__(self):
return len(self.files) * self.repeat
def __getitem__(self, i):
i = self.mapping[i % len(self.files)]
x = self.files[i]
l = self.targets[i]
if self.cache == 'none':
return Image.open(x).convert('RGB'), l, i
elif self.cache == 'bin':
with open(x, 'rb') as f:
x = pickle.load(f)
x = np.ascontiguousarray(x.transpose(2, 0, 1))
x = torch.from_numpy(x).float() / 255
return x, l, i
elif self.cache == 'in_memory':
return x, l, i
def shuffle_mapping(self):
# can't easily shuffle and use indexes as labels
if self.do_shuffle:
random.shuffle(self.mapping)
def set_mode(self, name):
if name in self.configs:
try:
for a, v in self.configs[name].items():
if a in self.__dict__:
self.logger(f"[INFO]\tSetting {a} to {v}")
self.__dict__[a] = v
else:
self.logger(f"[INFO]\tSetting {a} not found")
self.logger(f"[INFO]\tMode switched from '{self.current_mode}' to '{name}'")
self.current_mode = name
except Exception as e:
self.logger(f"[INFO]\tMode switched from '{self.current_mode}' to 'error'")
self.current_mode = "error"
raise e
else:
raise AttributeError(f"No {name} config profile found")
class FractalLabelPair(ImageFolderDataset):
def __getitem__(self, index):
img, label, order = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img_1 = self.transform(img)
img_2 = self.transform(img)
return {
"images": (img_1, img_2),
"label": label,
"order": order
}
class FractalPair(ImageFolderDataset):
def __getitem__(self, index):
img, label, order = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img_1 = self.transform(img)
img_2 = self.transform(img)
return {
"images": (img_1, img_2),
"order": order
}
class FractalLabel(ImageFolderDataset):
def __getitem__(self, index):
img, label = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img = self.transform(img)
return {
"images": (img),
"label": label,
"order": order
}
class CIFAR10Pair(CIFAR10):
"""CIFAR10 Dataset.
"""
def __getitem__(self, index):
img = self.data[index]
img = Image.fromarray(img)
if self.transform is not None:
img_1 = self.transform(img)
img_2 = self.transform(img)
return img_1, img_2
class ConfigurableDataLoader(DataLoader):
def set_mode(self, name):
try:
self.dataset.set_mode(name)
except Exception as e:
print(f"[ERROR]\tFailed to switch to mode {name}:\n{e}") | datasets/contrastive.py | class ImageFolderDataset(Dataset):
def __init__(self, root_path, transform=None, target_window=100, first_k=None,
last_k=None, skip_every=1, repeat=1, cache='in_memory',
shuffle_mapping=False, forced_mapping=None, real_shuffle=False,
batch_size=args.batch_size, logger=print, config={
'train': {
'transform':None,
'repeat':10},
'eval': {
'transform': None,
'repeat': 1
}
}):
self.configs = config
self.current_mode = list(config.keys())[0]
self.repeat = repeat #config[self.current_mode]['repeat']
self.cache = cache
self.batch_size = batch_size
self.logger = logger
filenames = sorted(os.listdir(root_path))
self.sets = [f.split('_')[-1].split('--')[0] for f in filenames]
self.set_lookup = {f: s for f, s in zip(filenames, self.sets)}
self.set_list = []
total_labels = 0
for setname in np.unique(self.sets):
set_seen = 0
for i, f in enumerate([f for f in filenames if self.set_lookup[f] == setname]):
self.set_list.append({
"label": total_labels,
"file": f,
"order": i
})
set_seen += 1
if set_seen % target_window == 0:
total_labels += 1
total_labels += 1
self.target_lookup = {s["file"]: s["label"] for s in self.set_list}
self.order_lookup = {s["file"]: s["order"] for s in self.set_list}
if first_k is not None:
filenames = filenames[:first_k]
elif last_k is not None:
filenames = filenames[-last_k:]
filenames = filenames[::skip_every]
self.logger(f"Found {len(filenames)} files in {root_path}")
self.do_shuffle = real_shuffle
if shuffle_mapping:
self.init_mapping = np.random.permutation(len(filenames))
else:
self.init_mapping = [i for i in range(len(filenames))]
if forced_mapping is not None:
self.init_mapping = forced_mapping
self.logger(f"Using cache strategy '{cache}'")
self.files = []
self.filenames = []
with tqdm(self.init_mapping) as pbar:
for file_idx in pbar:
try:
filename = filenames[file_idx]
filepath = os.path.join(root_path, filename)
self.filenames.append(filename)
if cache == 'none':
self.files.append(filepath)
elif cache == 'bin':
bin_root = os.path.join(os.path.dirname(root_path),
'_bin_' + os.path.basename(root_path))
if not os.path.exists(bin_root):
os.mkdir(bin_root)
print('mkdir', bin_root)
bin_file = os.path.join(
bin_root, filename.split('.')[0] + '.pkl')
if not os.path.exists(bin_file):
with open(bin_file, 'wb') as f:
pickle.dump(imageio.imread(filepath), f)
print('dump', bin_file)
self.files.append(bin_file)
elif cache == 'in_memory':
self.files.append(Image.open(filepath).convert('RGB'))
except Exception as e:
print(f"Failed to load image {filepath}: {e}")
self.mapping = [i for i in range(len(self.files))]
self.actual_size = len(self.mapping)
self.targets = [self.target_lookup[f] for f in self.filenames]
self.classes = np.unique(self.targets)
self.num_class = len(self.classes)
self.transform = transform
def __len__(self):
return len(self.files) * self.repeat
def __getitem__(self, i):
i = self.mapping[i % len(self.files)]
x = self.files[i]
l = self.targets[i]
if self.cache == 'none':
return Image.open(x).convert('RGB'), l, i
elif self.cache == 'bin':
with open(x, 'rb') as f:
x = pickle.load(f)
x = np.ascontiguousarray(x.transpose(2, 0, 1))
x = torch.from_numpy(x).float() / 255
return x, l, i
elif self.cache == 'in_memory':
return x, l, i
def shuffle_mapping(self):
# can't easily shuffle and use indexes as labels
if self.do_shuffle:
random.shuffle(self.mapping)
def set_mode(self, name):
if name in self.configs:
try:
for a, v in self.configs[name].items():
if a in self.__dict__:
self.logger(f"[INFO]\tSetting {a} to {v}")
self.__dict__[a] = v
else:
self.logger(f"[INFO]\tSetting {a} not found")
self.logger(f"[INFO]\tMode switched from '{self.current_mode}' to '{name}'")
self.current_mode = name
except Exception as e:
self.logger(f"[INFO]\tMode switched from '{self.current_mode}' to 'error'")
self.current_mode = "error"
raise e
else:
raise AttributeError(f"No {name} config profile found")
class FractalLabelPair(ImageFolderDataset):
def __getitem__(self, index):
img, label, order = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img_1 = self.transform(img)
img_2 = self.transform(img)
return {
"images": (img_1, img_2),
"label": label,
"order": order
}
class FractalPair(ImageFolderDataset):
def __getitem__(self, index):
img, label, order = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img_1 = self.transform(img)
img_2 = self.transform(img)
return {
"images": (img_1, img_2),
"order": order
}
class FractalLabel(ImageFolderDataset):
def __getitem__(self, index):
img, label = super().__getitem__(index)
if self.transform is None:
self.transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(data_stats["mean"],
data_stats["std"])])
img = self.transform(img)
return {
"images": (img),
"label": label,
"order": order
}
class CIFAR10Pair(CIFAR10):
"""CIFAR10 Dataset.
"""
def __getitem__(self, index):
img = self.data[index]
img = Image.fromarray(img)
if self.transform is not None:
img_1 = self.transform(img)
img_2 = self.transform(img)
return img_1, img_2
class ConfigurableDataLoader(DataLoader):
def set_mode(self, name):
try:
self.dataset.set_mode(name)
except Exception as e:
print(f"[ERROR]\tFailed to switch to mode {name}:\n{e}") | 0.522689 | 0.175256 |
import typing
from dataclasses import dataclass
from aiothornode.types import ThorConstants, ThorMimir
from services.lib.texts import split_by_camel_case
from services.models.base import BaseModelMixin
@dataclass
class MimirEntry:
name: str
pretty_name: str
real_value: str
hard_coded_value: str
overridden: bool
changed_ts: int
is_rune: bool
is_blocks: bool
is_bool: bool
source: str
SOURCE_CONST = 'const'
SOURCE_MIMIR = 'mimir'
SOURCE_BOTH = 'both'
@dataclass
class MimirChange(BaseModelMixin):
kind: str
name: str
old_value: str
new_value: str
entry: MimirEntry
timestamp: float
VALUE_CHANGE = '~'
ADDED_MIMIR = '+'
REMOVED_MIMIR = '-'
def __post_init__(self):
self.timestamp = float(self.timestamp)
class MimirHolder:
def __init__(self) -> None:
self.last_constants: ThorConstants = ThorConstants()
self.last_mimir: ThorMimir = ThorMimir()
self.last_changes: typing.Dict[str, float] = {}
self._const_map = {}
def mimirize(arr):
return set([self.convert_name_to_mimir_key(n) for n in arr])
self._mimir_names_of_block_constants = mimirize(self.BLOCK_CONSTANTS)
self._mimir_names_of_rune_constants = mimirize(self.RUNE_CONSTANTS)
self._mimir_names_of_bool_constants = mimirize(self.BOOL_CONSTANTS)
self._all_names = set()
self._mimir_only_names = set()
MIMIR_PREFIX = 'mimir//'
BLOCK_CONSTANTS = {
'BlocksPerYear', 'FundMigrationInterval', 'ChurnInterval', 'ChurnRetryInterval',
'SigningTransactionPeriod', 'DoubleSignMaxAge', 'LiquidityLockUpBlocks',
'ObservationDelayFlexibility', 'YggFundRetry', 'JailTimeKeygen', 'JailTimeKeysign',
'NodePauseChainBlocks', 'FullImpLossProtectionBlocks', 'TxOutDelayMax', 'MaxTxOutOffset'
}
RUNE_CONSTANTS = {
'OutboundTransactionFee',
'NativeTransactionFee',
'StagedPoolCost',
'MinRunePoolDepth',
'MinimumBondInRune',
'MinTxOutVolumeThreshold',
'TxOutDelayRate',
'TNSFeePerBlock',
'TNSRegisterFee',
'MAXIMUMLIQUIDITYRUNE',
'MAXLIQUIDITYRUNE',
}
TRANSLATE_MIMIRS = {
'PAUSELPLTC': 'Pause LP LTC',
'PAUSELPETH': 'Pause LP ETH',
'PAUSELPBCH': 'Pause LP BCH',
'PAUSELPBNB': 'Pause LP BNB',
'PAUSELPBTC': 'Pause LP BTC',
'PAUSELP': 'Pause all LP',
'STOPFUNDYGGDRASIL': 'Stop Fund Yggdrasil',
'STOPSOLVENCYCHECK': 'Stol Solvency Check',
'NUMBEROFNEWNODESPERCHURN': 'Number of New Nodes per Churn',
'MINTSYNTHS': 'Mint Synths',
'HALTBCHCHAIN': 'Halt BCH Chain',
'HALTBCHTRADING': 'Halt BCH Trading',
'HALTBNBCHAIN': 'Halt BNB Chain',
'HALTBNBTRADING': 'Halt BNB Trading',
'HALTBTCCHAIN': 'Halt BTC Chain',
'HALTBTCTRADING': 'Halt BTC Trading',
'HALTETHCHAIN': 'Halt ETH Chain',
'HALTETHTRADING': 'Halt ETH Trading',
'HALTLTCCHAIN': 'Halt LTC Chain',
'HALTLTCTRADING': 'Halt LTC Trading',
'HALTTHORCHAIN': 'Halt ThorChain',
'HALTTRADING': 'Halt All Trading',
'MAXIMUMLIQUIDITYRUNE': 'Maximum Liquidity Rune',
'MAXLIQUIDITYRUNE': 'Max Liquidity Rune',
'MAXUTXOSTOSPEND': 'Max UTXO to Spend',
'THORNAME': 'THOR Name',
'THORNAMES': 'THOR Names',
'STOPSOLVENCYCHECKETH': 'Stop Solvency check ETH',
'STOPSOLVENCYCHECKBNB': 'Stop Solvency check BNB',
'STOPSOLVENCYCHECKLTC': 'Stop Solvency check LTC',
'STOPSOLVENCYCHECKBTC': 'Stop Solvency check BTC',
'STOPSOLVENCYCHECKBCH': 'Stop Solvency check BCH',
}
BOOL_CONSTANTS = {
"HALTBCHCHAIN",
"HALTBCHTRADING",
"HALTBNBCHAIN",
"HALTBNBTRADING",
"HALTBTCCHAIN",
"HALTBTCTRADING",
"HALTETHCHAIN",
"HALTETHTRADING",
"HALTLTCCHAIN",
"HALTLTCTRADING",
"HALTTHORCHAIN",
"HALTTRADING",
"MINTSYNTHS",
"PAUSELP",
"PAUSELPBCH",
"PAUSELPBNB",
"PAUSELPBTC",
"PAUSELPETH",
"PAUSELPLTC",
"STOPFUNDYGGDRASIL",
"STOPSOLVENCYCHECK",
"THORNAME",
"THORNAMES",
'STOPSOLVENCYCHECKETH',
'STOPSOLVENCYCHECKBNB',
'STOPSOLVENCYCHECKLTC',
'STOPSOLVENCYCHECKBTC',
'STOPSOLVENCYCHECKBCH',
}
@staticmethod
def convert_name_to_mimir_key(name):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
return name
else:
return f'{prefix}{name.upper()}'
@staticmethod
def pure_name(name: str):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
return name[len(prefix):]
else:
return name.upper()
def get_constant(self, name: str, default=0, const_type: typing.Optional[type] = int):
raw_hardcoded_value = self.last_constants.constants.get(name, 0)
hardcoded_value = const_type(raw_hardcoded_value) if const_type else raw_hardcoded_value
mimir_name = MimirHolder.convert_name_to_mimir_key(name)
if mimir_name in self.last_mimir.constants:
v = self.last_mimir.constants.get(mimir_name, default)
return const_type(v) if const_type is not None else v
else:
return hardcoded_value
def get_hardcoded_const(self, name: str, default=None):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
pure_name = name[len(prefix):]
for k, v in self.last_constants.constants.items():
if pure_name.upper() == k.upper():
return v
return default
else:
return self.last_constants.constants.get(name)
def get_entry(self, name) -> typing.Optional[MimirEntry]:
return self._const_map.get(name)
def update(self, constants: ThorConstants, mimir: ThorMimir):
consts = set(constants.constants.keys())
only_mimir_names = set()
overriden_names = set()
mimir_like_const_names = set(self.convert_name_to_mimir_key(n) for n in consts)
for mimir_name in mimir.constants.keys():
if mimir_name in mimir_like_const_names:
overriden_names.add(mimir_name)
else:
only_mimir_names.add(mimir_name)
self._const_map = {}
self._all_names = set()
self._mimir_only_names = set()
for name, value in constants.constants.items():
real_value = value
overriden = False
source = MimirEntry.SOURCE_CONST
mimir_name = self.convert_name_to_mimir_key(name)
if mimir_name in overriden_names:
overriden = True
source = MimirEntry.SOURCE_BOTH
real_value = mimir.constants.get(mimir_name)
last_change_ts = self.last_changes.get(name, 0)
entry = MimirEntry(name, split_by_camel_case(name),
real_value, value, overriden, last_change_ts,
is_rune=name in self.RUNE_CONSTANTS,
is_blocks=name in self.BLOCK_CONSTANTS,
is_bool=name in self.BOOL_CONSTANTS,
source=source)
self._const_map[name] = entry
self._const_map[mimir_name] = entry
self._all_names.add(name)
for name in only_mimir_names:
value = mimir.constants.get(name)
last_change_ts = self.last_changes.get(name, 0)
pure_name = self.pure_name(name)
pretty_name = self.TRANSLATE_MIMIRS.get(pure_name, pure_name)
entry = MimirEntry(name, pretty_name, value, value, True, last_change_ts,
is_rune=name in self._mimir_names_of_rune_constants,
is_blocks=name in self._mimir_names_of_block_constants,
is_bool=name in self._mimir_names_of_bool_constants,
source=MimirEntry.SOURCE_MIMIR)
self._const_map[name] = entry
self._const_map[pure_name] = entry
self._all_names.add(name)
self._mimir_only_names.add(name)
if constants:
self.last_constants = constants
if mimir:
self.last_mimir = mimir
@property
def all_entries(self) -> typing.List[MimirEntry]:
entries = [self._const_map[name] for name in self._all_names]
entries.sort(key=lambda en: en.pretty_name)
return entries
def register_change_ts(self, name, ts):
if name:
self.last_changes[name] = ts
entry: MimirEntry = self._const_map.get(name)
if entry and ts > 0:
entry.changed_ts = ts | app/services/models/mimir.py | import typing
from dataclasses import dataclass
from aiothornode.types import ThorConstants, ThorMimir
from services.lib.texts import split_by_camel_case
from services.models.base import BaseModelMixin
@dataclass
class MimirEntry:
name: str
pretty_name: str
real_value: str
hard_coded_value: str
overridden: bool
changed_ts: int
is_rune: bool
is_blocks: bool
is_bool: bool
source: str
SOURCE_CONST = 'const'
SOURCE_MIMIR = 'mimir'
SOURCE_BOTH = 'both'
@dataclass
class MimirChange(BaseModelMixin):
kind: str
name: str
old_value: str
new_value: str
entry: MimirEntry
timestamp: float
VALUE_CHANGE = '~'
ADDED_MIMIR = '+'
REMOVED_MIMIR = '-'
def __post_init__(self):
self.timestamp = float(self.timestamp)
class MimirHolder:
def __init__(self) -> None:
self.last_constants: ThorConstants = ThorConstants()
self.last_mimir: ThorMimir = ThorMimir()
self.last_changes: typing.Dict[str, float] = {}
self._const_map = {}
def mimirize(arr):
return set([self.convert_name_to_mimir_key(n) for n in arr])
self._mimir_names_of_block_constants = mimirize(self.BLOCK_CONSTANTS)
self._mimir_names_of_rune_constants = mimirize(self.RUNE_CONSTANTS)
self._mimir_names_of_bool_constants = mimirize(self.BOOL_CONSTANTS)
self._all_names = set()
self._mimir_only_names = set()
MIMIR_PREFIX = 'mimir//'
BLOCK_CONSTANTS = {
'BlocksPerYear', 'FundMigrationInterval', 'ChurnInterval', 'ChurnRetryInterval',
'SigningTransactionPeriod', 'DoubleSignMaxAge', 'LiquidityLockUpBlocks',
'ObservationDelayFlexibility', 'YggFundRetry', 'JailTimeKeygen', 'JailTimeKeysign',
'NodePauseChainBlocks', 'FullImpLossProtectionBlocks', 'TxOutDelayMax', 'MaxTxOutOffset'
}
RUNE_CONSTANTS = {
'OutboundTransactionFee',
'NativeTransactionFee',
'StagedPoolCost',
'MinRunePoolDepth',
'MinimumBondInRune',
'MinTxOutVolumeThreshold',
'TxOutDelayRate',
'TNSFeePerBlock',
'TNSRegisterFee',
'MAXIMUMLIQUIDITYRUNE',
'MAXLIQUIDITYRUNE',
}
TRANSLATE_MIMIRS = {
'PAUSELPLTC': 'Pause LP LTC',
'PAUSELPETH': 'Pause LP ETH',
'PAUSELPBCH': 'Pause LP BCH',
'PAUSELPBNB': 'Pause LP BNB',
'PAUSELPBTC': 'Pause LP BTC',
'PAUSELP': 'Pause all LP',
'STOPFUNDYGGDRASIL': 'Stop Fund Yggdrasil',
'STOPSOLVENCYCHECK': 'Stol Solvency Check',
'NUMBEROFNEWNODESPERCHURN': 'Number of New Nodes per Churn',
'MINTSYNTHS': 'Mint Synths',
'HALTBCHCHAIN': 'Halt BCH Chain',
'HALTBCHTRADING': 'Halt BCH Trading',
'HALTBNBCHAIN': 'Halt BNB Chain',
'HALTBNBTRADING': 'Halt BNB Trading',
'HALTBTCCHAIN': 'Halt BTC Chain',
'HALTBTCTRADING': 'Halt BTC Trading',
'HALTETHCHAIN': 'Halt ETH Chain',
'HALTETHTRADING': 'Halt ETH Trading',
'HALTLTCCHAIN': 'Halt LTC Chain',
'HALTLTCTRADING': 'Halt LTC Trading',
'HALTTHORCHAIN': 'Halt ThorChain',
'HALTTRADING': 'Halt All Trading',
'MAXIMUMLIQUIDITYRUNE': 'Maximum Liquidity Rune',
'MAXLIQUIDITYRUNE': 'Max Liquidity Rune',
'MAXUTXOSTOSPEND': 'Max UTXO to Spend',
'THORNAME': 'THOR Name',
'THORNAMES': 'THOR Names',
'STOPSOLVENCYCHECKETH': 'Stop Solvency check ETH',
'STOPSOLVENCYCHECKBNB': 'Stop Solvency check BNB',
'STOPSOLVENCYCHECKLTC': 'Stop Solvency check LTC',
'STOPSOLVENCYCHECKBTC': 'Stop Solvency check BTC',
'STOPSOLVENCYCHECKBCH': 'Stop Solvency check BCH',
}
BOOL_CONSTANTS = {
"HALTBCHCHAIN",
"HALTBCHTRADING",
"HALTBNBCHAIN",
"HALTBNBTRADING",
"HALTBTCCHAIN",
"HALTBTCTRADING",
"HALTETHCHAIN",
"HALTETHTRADING",
"HALTLTCCHAIN",
"HALTLTCTRADING",
"HALTTHORCHAIN",
"HALTTRADING",
"MINTSYNTHS",
"PAUSELP",
"PAUSELPBCH",
"PAUSELPBNB",
"PAUSELPBTC",
"PAUSELPETH",
"PAUSELPLTC",
"STOPFUNDYGGDRASIL",
"STOPSOLVENCYCHECK",
"THORNAME",
"THORNAMES",
'STOPSOLVENCYCHECKETH',
'STOPSOLVENCYCHECKBNB',
'STOPSOLVENCYCHECKLTC',
'STOPSOLVENCYCHECKBTC',
'STOPSOLVENCYCHECKBCH',
}
@staticmethod
def convert_name_to_mimir_key(name):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
return name
else:
return f'{prefix}{name.upper()}'
@staticmethod
def pure_name(name: str):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
return name[len(prefix):]
else:
return name.upper()
def get_constant(self, name: str, default=0, const_type: typing.Optional[type] = int):
raw_hardcoded_value = self.last_constants.constants.get(name, 0)
hardcoded_value = const_type(raw_hardcoded_value) if const_type else raw_hardcoded_value
mimir_name = MimirHolder.convert_name_to_mimir_key(name)
if mimir_name in self.last_mimir.constants:
v = self.last_mimir.constants.get(mimir_name, default)
return const_type(v) if const_type is not None else v
else:
return hardcoded_value
def get_hardcoded_const(self, name: str, default=None):
prefix = MimirHolder.MIMIR_PREFIX
if name.startswith(prefix):
pure_name = name[len(prefix):]
for k, v in self.last_constants.constants.items():
if pure_name.upper() == k.upper():
return v
return default
else:
return self.last_constants.constants.get(name)
def get_entry(self, name) -> typing.Optional[MimirEntry]:
return self._const_map.get(name)
def update(self, constants: ThorConstants, mimir: ThorMimir):
consts = set(constants.constants.keys())
only_mimir_names = set()
overriden_names = set()
mimir_like_const_names = set(self.convert_name_to_mimir_key(n) for n in consts)
for mimir_name in mimir.constants.keys():
if mimir_name in mimir_like_const_names:
overriden_names.add(mimir_name)
else:
only_mimir_names.add(mimir_name)
self._const_map = {}
self._all_names = set()
self._mimir_only_names = set()
for name, value in constants.constants.items():
real_value = value
overriden = False
source = MimirEntry.SOURCE_CONST
mimir_name = self.convert_name_to_mimir_key(name)
if mimir_name in overriden_names:
overriden = True
source = MimirEntry.SOURCE_BOTH
real_value = mimir.constants.get(mimir_name)
last_change_ts = self.last_changes.get(name, 0)
entry = MimirEntry(name, split_by_camel_case(name),
real_value, value, overriden, last_change_ts,
is_rune=name in self.RUNE_CONSTANTS,
is_blocks=name in self.BLOCK_CONSTANTS,
is_bool=name in self.BOOL_CONSTANTS,
source=source)
self._const_map[name] = entry
self._const_map[mimir_name] = entry
self._all_names.add(name)
for name in only_mimir_names:
value = mimir.constants.get(name)
last_change_ts = self.last_changes.get(name, 0)
pure_name = self.pure_name(name)
pretty_name = self.TRANSLATE_MIMIRS.get(pure_name, pure_name)
entry = MimirEntry(name, pretty_name, value, value, True, last_change_ts,
is_rune=name in self._mimir_names_of_rune_constants,
is_blocks=name in self._mimir_names_of_block_constants,
is_bool=name in self._mimir_names_of_bool_constants,
source=MimirEntry.SOURCE_MIMIR)
self._const_map[name] = entry
self._const_map[pure_name] = entry
self._all_names.add(name)
self._mimir_only_names.add(name)
if constants:
self.last_constants = constants
if mimir:
self.last_mimir = mimir
@property
def all_entries(self) -> typing.List[MimirEntry]:
entries = [self._const_map[name] for name in self._all_names]
entries.sort(key=lambda en: en.pretty_name)
return entries
def register_change_ts(self, name, ts):
if name:
self.last_changes[name] = ts
entry: MimirEntry = self._const_map.get(name)
if entry and ts > 0:
entry.changed_ts = ts | 0.650689 | 0.150559 |
import requests
import json
from django.shortcuts import render, redirect
from django.http import HttpResponse
from common.fetching import Fetcher as DataFetcher
from common.tokening import TokenManager
from .services.summary import (
BatchJobErrorSummary,
BatchJobExecutingSummary,
BatchJobWaitingSummary,
BatchJobWithholdSummary,
)
from .services.tables import (
SqlBlocking,
SqlLockInfo,
SqlInfo,
)
# Create your views here.
def index(request):
"""
Some description here.
"""
if not request.user.is_authenticated:
return redirect('/')
context = {}
context['resource_url'] = request.session.get('resource')
token_manager = TokenManager(
resource=request.session.get('resource'),
tenant=request.session.get('tenant'),
client_id=request.session.get('client_id'),
client_secret=request.session.get('client_secret'),
username=request.session.get('username'),
password=request.session.get('password')
)
data_fetcher = DataFetcher(token_manager)
batch_job_error = BatchJobErrorSummary(data_fetcher)
batch_job_error.fetch_data()
batch_job_executing = BatchJobExecutingSummary(data_fetcher)
batch_job_executing.fetch_data()
batch_job_waiting = BatchJobWaitingSummary(data_fetcher)
batch_job_waiting.fetch_data()
batch_job_withhold = BatchJobWithholdSummary(data_fetcher)
batch_job_withhold.fetch_data()
print('=========================================> SQL ANALYSES: Comecou',)
sql_blocking = SqlBlocking(data_fetcher)
sql_blocking.fetch_data()
sql_lock_info = SqlLockInfo(data_fetcher)
sql_lock_info.fetch_data()
sql_info = SqlInfo(data_fetcher)
sql_info.fetch_data()
print('=========================================> BLOCKING: ', len(sql_blocking.get_context_value()))
print('=========================================> LOCK: ', len(sql_lock_info.get_context_value()))
print('=========================================> INFO: ', sql_info.get_context_value())
context[batch_job_error.get_context_key()] = batch_job_error.get_context_value()
context[batch_job_executing.get_context_key()] = batch_job_executing.get_context_value()
context[batch_job_waiting.get_context_key()] = batch_job_waiting.get_context_value()
context[batch_job_withhold.get_context_key()] = batch_job_withhold.get_context_value()
return render(request, 'sysadmin/index.html', context) | daxboard/sysadmin/views.py | import requests
import json
from django.shortcuts import render, redirect
from django.http import HttpResponse
from common.fetching import Fetcher as DataFetcher
from common.tokening import TokenManager
from .services.summary import (
BatchJobErrorSummary,
BatchJobExecutingSummary,
BatchJobWaitingSummary,
BatchJobWithholdSummary,
)
from .services.tables import (
SqlBlocking,
SqlLockInfo,
SqlInfo,
)
# Create your views here.
def index(request):
"""
Some description here.
"""
if not request.user.is_authenticated:
return redirect('/')
context = {}
context['resource_url'] = request.session.get('resource')
token_manager = TokenManager(
resource=request.session.get('resource'),
tenant=request.session.get('tenant'),
client_id=request.session.get('client_id'),
client_secret=request.session.get('client_secret'),
username=request.session.get('username'),
password=request.session.get('password')
)
data_fetcher = DataFetcher(token_manager)
batch_job_error = BatchJobErrorSummary(data_fetcher)
batch_job_error.fetch_data()
batch_job_executing = BatchJobExecutingSummary(data_fetcher)
batch_job_executing.fetch_data()
batch_job_waiting = BatchJobWaitingSummary(data_fetcher)
batch_job_waiting.fetch_data()
batch_job_withhold = BatchJobWithholdSummary(data_fetcher)
batch_job_withhold.fetch_data()
print('=========================================> SQL ANALYSES: Comecou',)
sql_blocking = SqlBlocking(data_fetcher)
sql_blocking.fetch_data()
sql_lock_info = SqlLockInfo(data_fetcher)
sql_lock_info.fetch_data()
sql_info = SqlInfo(data_fetcher)
sql_info.fetch_data()
print('=========================================> BLOCKING: ', len(sql_blocking.get_context_value()))
print('=========================================> LOCK: ', len(sql_lock_info.get_context_value()))
print('=========================================> INFO: ', sql_info.get_context_value())
context[batch_job_error.get_context_key()] = batch_job_error.get_context_value()
context[batch_job_executing.get_context_key()] = batch_job_executing.get_context_value()
context[batch_job_waiting.get_context_key()] = batch_job_waiting.get_context_value()
context[batch_job_withhold.get_context_key()] = batch_job_withhold.get_context_value()
return render(request, 'sysadmin/index.html', context) | 0.340376 | 0.043164 |
polls = {
'newsint2_baseline' : ('Interest in news and public affairs',
'Some people seem to follow what\'s going on in government and public affairs most of the time, whether there\'s an election going on or not. Others aren\'t that interested. Would you say you follow what\'s going on in government and public affairs ...?',
[[1], [2], [3], [4]],
['Most of the time', 'Some of the time', 'Only now and then', 'Hardly at all']),
'newsint_2016' : ('Political Interest',
'Some people seem to follow what\'s going on in government and public affairs most of the time, whether there\'s an election going on or not. Others aren\'t that interested. Would you say you follow what\'s going on in government and public affairs ...?',
[[1], [2], [3], [4]],
['Most of the time', 'Some of the time', 'Only now and then', 'Hardly at all']),
'track_baseline' : ('Direction of the country',
'Would you say things in the country are...',
[[1], [2], [3]],
['Generally headed in the right direction', 'Off on the wrong track','Not sure']),
'track_2016' : ('Direction of the country (2016)',
'Would you say things in the country are...',
[[1], [2], [3]],
['Generally headed in the right direction', 'Off on the wrong track','Not sure']),
'americatrend_2016' : ('Life in America today for people like R compared to fifty years ago',
'In general, would you say life in America today is better, worse, or about the same as it was fifty years ago for people like you?',
[[1], [2], [3], [4]],
['Better', 'About the same', 'Worse', 'Don\'t Know']),
'wealth_2016' : ('Distribution of money and wealth in this country',
'Do you feel that the distribution of money and wealth in this country is fair, or do you feel that the money and wealth in this country should be more evenly distributed among more people?',
[[1], [2], [8]],
['Distribution is fair', 'Should be more evenly distributed', 'Don\'t know']),
'values_culture_2016' : ('In America, values and culture of people like R are...',
'In America today, do you feel the values and culture of people like you are:',
[[1], [2], [3], [8]],
['Generally becoming more widespread and accepted', 'Holding Steady', 'Generally becoming rarer', 'Don\'t Know']),
'trustgovt_baseline' : ('Trust government to do what\'s right',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'trustgovt_2016' : ('Trust government (2016)',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'trust_people_2016' : ('Most people can/can\'t be trusted',
'Generally speaking, would you say that most people can be trusted or that you can\'t be too careful in dealing with people?',
[[1], [2], [8]],
['Can\'t be too careful in dealing with people', 'Most people can be trusted', 'Don\'t know']),
'helpful_people_2016' : ('People try to be helpful or are they mostly just looking out for themselves',
'Would you say that most of the time people try to be helpful, or that they are mostly just looking out for themselves?',
[[1], [2], [8]],
['People try to be helpful', 'People are looking out for themselves', 'Don\'t know']),
'obamaapp_baseline' : ('Barack Obama Approval',
"Do you approve or dissaprove of the way Barack Obama is handlind his job as president?",
[[1],[2],[3],[4],[5]],
['Stronly approve', 'Somewhat approve', 'Somewhat disapprove', 'Strongly disapprove', 'Not Sure']),
'obamaapp_2016' : ('Barack Obama Approval (2016)',
"Do you approve or dissaprove of the way <NAME> is handlind his job as president?",
[[1],[2],[3],[4],[5]],
['Stronly approve', 'Somewhat approve', 'Somewhat disapprove', 'Strongly disapprove', 'Not Sure']),
'watchtv_baseline' : ('Hours watch TV daily',
"On a typical weekday, how many hours of TV do you watch?",
[[1],[2],[3],[4]],
['None', '1-2 Hours', '3-4 Hours', 'More than 4 hours']),
'ideo5_baseline' : ('Ideology',
"Thinking about politics these days, how would you describe your own political viewpoint?",
[[1],[2],[3],[4],[5],[6]],
['Very Liberal', 'Liberal', 'Moderate', 'Conservative', 'Very Conservative', 'Not Sure']),
'imiss_a_baseline' : ('Issue Importance: Iraq War',
"How important are the following issues to you -- The War in Iraq?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_b_baseline' : ('Issue Importance: The Economy',
"How important are the following issues to you -- The economy?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_c_baseline' : ('Issue Importance: Immigration',
"How important are the following issues to you -- Immigration?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_d_baseline' : ('Issue Importance: The Environment',
"How important are the following issues to you -- The Environment?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_f_baseline' : ('Issue Importance: Terrorism',
"How important are the following issues to you -- Terrorism?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_g_baseline' : ('Issue Importance: Gay Rights',
"How important are the following issues to you -- Gay Rights?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_baseline' : ('Issue Importance: Education',
"How important are the following issues to you -- Education?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_j_baseline' : ('Issue Importance: Health Care',
"How important are the following issues to you -- Health Care?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_m_baseline' : ('Issue Importance: Social Security',
"How important are the following issues to you -- Social Security?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_p_baseline' : ('Issue Importance: The Budget Deficit',
"How important are the following issues to you -- The Budget Deficit?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_q_baseline' : ('Issue Importance: The War in Afganistan',
"How important are the following issues to you -- The War in Afganistan?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_r_baseline' : ('Issue Importance: Taxes',
"How important are the following issues to you -- Taxes?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_s_baseline' : ('Issue Importance: Medicare',
"How important are the following issues to you -- Medicare?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_t_baseline' : ('Issue Importance: Abortion',
"How important are the following issues to you -- Abortion?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_a_2016' : ('Issue Importance: Crime (2016)',
"How important are the following issues to you -- Crime?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_b_2016' : ('Issue Importance: The Economy (2016)',
"How important are the following issues to you -- The economy?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_c_2016' : ('Issue Importance: Immigration (2016)',
"How important are the following issues to you -- Immigration?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_d_2016' : ('Issue Importance: The Environment (2016)',
"How important are the following issues to you -- The Environment?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_e_2016' : ('Issue Importance: Religious Liberty (2016)',
"How important are the following issues to you -- Religious Liberty?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_f_2016' : ('Issue Importance: Terrorism (2016)',
"How important are the following issues to you -- Terrorism?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_g_2016' : ('Issue Importance: Gay Rights (2016)',
"How important are the following issues to you -- Gay Rights?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_2016' : ('Issue Importance: Education (2016)',
"How important are the following issues to you -- Education?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_2016' : ('Issue Importance: Family and Medical Leave (2016)',
"How important are the following issues to you -- Family and Medical Leave?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_j_2016' : ('Issue Importance: Health Care (2016)',
"How important are the following issues to you -- Health Care?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_k_2016' : ('Issue Importance: Money in Politics (2016)',
"How important are the following issues to you -- Money in Politics?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_l_2016' : ('Issue Importance: Climate Change (2016)',
"How important are the following issues to you -- Climate Change?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_m_2016' : ('Issue Importance: Social Security',
"How important are the following issues to you -- Social Security?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_n_2016' : ('Issue Importance: Infrastructure Investment',
"How important are the following issues to you -- Infrastructure Investment'?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_o_2016' : ('Issue Importance: Jobs',
"How important are the following issues to you -- Jobs'?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_p_2016' : ('Issue Importance: The Budget Deficit (2016)',
"How important are the following issues to you -- The Budget Deficit?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_q_2016' : ('Issue Importance: Poverty',
"How important are the following issues to you -- Poverty?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_r_2016' : ('Issue Importance: Taxes (2016)',
"How important are the following issues to you -- Taxes?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_s_2016' : ('Issue Importance: Medicare (2016)',
"How important are the following issues to you -- Medicare?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_t_2016' : ('Issue Importance: Abortion (2016)',
"How important are the following issues to you -- Abortion?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_u_2016' : ('Issue Importance: The size of Government (2016)',
"How important are the following issues to you -- The size of Government?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_x_2016' : ('Issue Importance: Racial Equality (2016)',
"How important are the following issues to you -- Racial Equality?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_y_2016' : ('Issue Importance: Gender Equality (2016)',
"How important are the following issues to you -- Gender Equality?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imissf_baseline' : ('Most important issues',
"Which of these is most important to you?",
[[1],[2],[3],[4],[6],[7],[8],[10],[13],[16],[17],[18],[19],[20]],
['The war in Iraq','The economy', 'Immigration', 'The Evironmment','Terrorism', 'Gay Rights','Education','Health Care','Social Security','The Budget Deficit','The War in Afganistan','Taxes','Medicade','Abortion']),
'immi_contribution_baseline' : ('Illegal Immigrants Contribute or Drain',
"Overall, do you think illegal immigrants American society or are a drain?",
[[1],[2],[3],[4]],
['Mostly make a contribution','Neither', 'Mostly a drain', 'Not Sure']),
'immi_contribution_2016' : ('Illegal Immigrants Contribute or Drain (2016)',
"Overall, do you think illegal immigrants American society or are a drain?",
[[1],[2],[3],[4]],
['Mostly make a contribution','Neither', 'Mostly a drain', 'Not Sure']),
'immi_naturalize_baseline' : ('Illegal Immigrant Naturalization',
"Do you favor or oppose providing a legal way for illegal immigrants already in the United States to become U.S. citizens?",
[[1], [2], [3]],
['Favor', 'Oppose', 'Not sure']),
'immi_naturalize_2016' : ('Illegal Immigrant Naturalization (2016)',
"Do you favor or oppose providing a legal way for illegal immigrants already in the United States to become U.S. citizens?",
[[1], [2], [3]],
['Favor', 'Oppose', 'Not sure']),
'immi_makedifficult_baseline' : ('Harder/Easier to Immigrate',
"Do you think it should be easier or harder for foreigners to immigrate to the US?",
[[1],[2],[3],[4],[5],[8]],
['Much easier', 'Slightly easier','No change','Slightly Harder','Much harder','Not sure']),
'immi_makedifficult_2016' : ('Harder/Easier to Immigrate (2016)',
"Do you think it should be easier or harder for foreigners to immigrate to the US?",
[[1],[2],[3],[4],[5],[8]],
['Much easier', 'Slightly easier','No change','Slightly Harder','Much harder','Not sure']),
'abortview3_baseline' : ('Abortion views',
"Do you think abortion should be...",
[[1],[2],[3],[8]],
['Legal in all cases','Legal in some cases and illegal in others','Illegal in all cases','Not sure']),
'abortview3_2016' : ('Abortion views (2016)',
"Do you think abortion should be...",
[[1],[2],[3],[8]],
['Legal in all cases','Legal in some cases and illegal in others','Illegal in all cases','Not sure']),
'gaymar2_baseline' : ('Gay Marriage',
"Do you favor or oppose allowing gays and lesbians to marry legally?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'gaymar_2016' : ('Gay Marriage (2016)',
"Do you favor or oppose allowing gays and lesbians to marry legally?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenalty_baseline' : ('Death Penalty',
"Do you favor or oppose the death penatly for persons convicted of murder?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenfreq_baseline' : ('Death Penalty Frequency',
"Do you think the death penalty enough?",
[[1],[2],[3],[4]],
['Too often', 'About Right', 'Not Often Enough', 'Not Sure']),
'deathpen_2016' : ('Death Penalty (2016)',
"Do you favor or oppose the death penatly for persons convicted of murder?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenfreq_2016' : ('Death Penalty Frequency (2016)',
"Do you think the death penalty enough?",
[[1],[2],[3],[8]],
['Too often', 'About Right', 'Not Often Enough', 'Don\'t Know']),
'taxwealth_baseline' : ('Increase Taxes on Wealthy',
"Do you favor raising taxes on families with incomes over 200,000 dollars per year?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'univhealthcov_baseline' : ('Federal government responsibility for healthcare',
"Do you think it is the responsibility of the federal government to see to it that everyone has health care coverage?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'univhealthcov_2016' : ('Federal government responsibility for healthcare (2016)',
"Do you think it is the responsibility of the federal government to see to it that everyone has health care coverage?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'envwarm_baseline' : ('Existence of Global Warming',
"Some people say that global temperatures have been going up slowly over the past 100 years - the phenomenon called global warming. Do you think that global warming is happening?",
[[1],[2],[3],[4],[5]],
['Defintely is happening', 'Probably is happening','Probably is not happening','Definitely is not happening', 'Not Sure']),
'envwarm_2016' : ('Existence of Global Warming (2016)',
"Some people say that global temperatures have been going up slowly over the past 100 years - the phenomenon called global warming. Do you think that global warming is happening?",
[[1],[2],[3],[4],[5]],
['Defintely is happening', 'Probably is happening','Probably is not happening','Definitely is not happening', 'Not Sure']),
'envser2_baseline' : ('Seriousness of Global Warming Problem',
"How serious a problem do you think global warming is?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not Very', 'Not Sure']),
'envpoll2_baseline' : ('Cause of global warming',
"Do you think global warming has been caused by pollution from human activities (such as emissions from cars and factories) or by natural causes?",
[[1],[2],[3]],
['Pollution from human activities','Natural causes not related to human activities','Not sure']),
'envpoll2_2016' : ('Cause of global warming (2016)',
"Do you think global warming has been caused by pollution from human activities (such as emissions from cars and factories) or by natural causes?",
[[1],[2],[3]],
['Pollution from human activities','Natural causes not related to human activities','Not sure']),
'affirmact_gen_baseline' : ('Favor or oppose affirmative action for women and racial minorities',
"Do you generally favor or oppose affirmative action programs for women and racial minorities?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'affirmact_gen_2016' : ('Favor or oppose affirmative action for women and racial minorities (2016)',
"Do you generally favor or oppose affirmative action programs for women and racial minorities?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'tradepolicy_baseline' : ('Favor or oppose increasing trade',
"Do you favor or oppose increasing trade with other nations?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'tradepolicy_2016' : ('Favor or oppose increasing trade (2016)',
"Do you favor or oppose increasing trade with other nations?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'govt_reg_baseline' : ('Level of government regulation',
"In general, do you think there of business by the government?",
[[1],[2],[3],[8]],
['Too Much', 'About the right amount', 'Too little','Don\'t Know']),
'govt_reg_2016' : ('Level of government regulation (2016)',
"In general, do you think there of business by the government?",
[[1],[2],[3],[8]],
['Too Much', 'About the right amount','Too little', 'Don\'t Know']),
'pid7_baseline' : ('7 point party ID',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Strong Democrat','Not Very Strong Democrat','Lean Democrat','Independent','Lean Republican','Not very strong Republican','Strong Republican','Not sure']),
'pid7_2016' : ('7 point party ID (2016)',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Strong Democrat','Not Very Strong Democrat','Lean Democrat','Independent','Lean Republican','Not very strong Republican','Strong Republican','Not sure']),
'pid3_baseline' : ('3 point party ID',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5]],
['Democrat','Republican','Independent','Other','Not sure']),
'pid3_2016' : ('3 point party ID (2016)',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5]],
['Democrat','Republican','Independent','Other','Not sure']),
'vote_generic_baseline' : ('Generic Presidential Vote',
"If an election for president was going to be held now, would you vote for...",
[[1],[2],[3],[4],[5]],
['The Democratic Party','The Republican Party','Other','Not sure','I would not vote']),
'marstat_baseline' : ('Marital Status',
"Marital Status",
[[1],[2],[3],[4],[5],[6]],
['Married','Separated','Divorced','Widowed','Single','Domestic Partnership']),
'marstat_2016' : ('Marital Status (2016)',
"Marital Status",
[[1],[2],[3],[4],[5],[6]],
['Married','Separated','Divorced','Widowed','Single','Domestic Partnership']),
'teapartymemb_baseline' : ('Own involvement in Tea Party movement',
"Do you think of yourself as a part of the Tea Party movement?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'teapartsup_baseline' : ('Support for Tea Party',
"Generally speaking, do you support or oppose the goals of the Tea Party movement?",
[[1],[2],[3],[4],[5],[8]],
['Strongly Support', 'Somewhat Support','Neither Support nor Oppose', 'Somewhat Oppose','Strongly Oppose', 'Not Sure']),
'selfdescr_ccap_1_baseline' : ('Self Described Libertarian',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Libertarian",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_2_baseline' : ('Self Described Socialist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Socialist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_3_baseline' : ('Self Described Green',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Green",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_4_baseline' : ('Self Described Environmentalist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Environmentalist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_5_baseline' : ('Self Described Liberal',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Liberal",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_6_baseline' : ('Self Described Moderate',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Moderate",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_7_baseline' : ('Self Described Conservative',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Conservative",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_8_baseline' : ('Self Described Radical',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Radical",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_9_baseline' : ('Self Described Progressive',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Progressive",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_10_baseline' : ('Self Described Traditional',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Traditional",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_11_baseline' : ('Self Described Christian',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Christian",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_12_baseline' : ('Self Described Feminist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Feminist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_13_baseline' : ('Self Described Fundamentalist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Fundamentalist",
[[1],[2]],
['Yes', 'No']),
'abortidentity_baseline' : ('Pro-life or Pro-Choice',
"Would you call yourself as pro-life or pro-choice?",
[[1],[2],[3],[4],[8]],
['Pro-life','Pro-choice','Both','Neither','Not Sure']),
'race_deservemore_baseline': ('Black deservedeness',
"Agree or Disagree: over the past few years, Blacks have gotten less than they deserve.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_deservemore_2016': ('Black deservedeness (2016)',
"Agree or Disagree: over the past few years, Blacks have gotten less than they deserve.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_overcome_baseline' : ('Irish, Italians, and Jews Overcoming Prejudice',
"Agree or Disagree: Irish, Italian, Jewish and other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_overcome_2016' : ('Irish, Italians, and Jews Overcoming Prejudice (2016)',
"Agree or Disagree: Irish, Italian, Jewish and other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_tryharder_baseline': ('Blacks should try harder',
"It's really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_tryharder_2016': ('Blacks should try harder (2016)',
"It's really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_slave_baseline' : ('Modern day impact of slavery',
"Generation of slavery and discrimination have created conditions that make it difficult for black to work their way out of the lower class.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_slave_2016' : ('Modern day impact of slavery',
"Generation of slavery and discrimination have created conditions that make it difficult for black to work their way out of the lower class.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'ownorrent_baseline' : ('Own or Rent',
"Is the place you live owned or rented?",
[[1],[2],[3]],
['Owned', 'Rented', 'Other']),
'reliablevoter_baseline': ('Voting frequency',
"How often do you vote?",
[[1],[2],[3],[4]],
['Always','Nearly Always', 'Part of the time', 'Seldom']),
'straighttic_baseline' : ('Partisan Voter Reliability',
"Do you almost always vote for candidates from the same party or do you sometimes support candidates from different parties?",
[[1],[2],[3]],
['Almost always vote Republican','Almost always vote Democrat','Vote for both Democrats and Republicans']),
'voted08_cap_baseline' : ('Voted in 2008 Presidential Election',
"Did you happen to vote in the 2008 election?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'presvote08_baseline' : ('2008 Presidential Vote',
"Which candidate did you vote for in the 2008 Presidential Election?",
[[1],[2],[3,4,5]],
['<NAME>', '<NAME>', 'Other']),
'post_presvote12_2012' : ('2008 Presidential Vote',
"Which candidate did you vote for in the 2012 Presidential Election?",
[[1],[2],[3],[4],[5]],
['<NAME>', '<NAME>', 'Other', 'Didn\'t Vote in this race', 'Didn\'t vote', 'Not Sure']),
'congvote10_ccap_baseline' : ('2010 Vote',
"Did you happen to vote in the 2010 election?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'congvote10_ccap_baseline': ('2010 Congressional Vote',
"Which candidate did you vote for in the U.S. House election?",
[[1],[2],[3]],
['Democratic','Republican', 'Other']),
'fav_obama_baseline' : ( 'Barack Obama Favorability',
"Do you have an unfavorable or favorable opinion on the following people -- Barack Obama",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_hrc_baseline' : ('<NAME> Favorability',
"Do you have an unfavorable or favorable opinion on the following people -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'pew_bornagain_baseline' : ('Born Again Christains',
"Would you describe yourself as Christian, or not?",
[[1],[2]],
['Yes', 'No']),
'pew_bornagain_2016' : ('Born Again Christains (2016)',
"Would you describe yourself as Christian, or not?",
[[1],[2]],
['Yes', 'No']),
'pew_religimp_' : ('Imporance of religion',
"How impotant is religion in your life?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not too imporant', 'Not at all']),
'pew_religimp_2016' : ('Imporance of religion (2016)',
"How impotant is religion in your life?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not too imporant', 'Not at all']),
'pew_churchatd_baseline' : ('Church attendance',
"Aside from weddings and funerals, how often do you attend religious services?",
[[1],[2],[3],[4],[5],[6],[7]],
['More than once a week','Once a week','Once or twice a month','A few times a year','Seldom','Never','Don\'t know']),
'pew_churchatd_2016' : ('Church attendance (2016)',
"Aside from weddings and funerals, how often do you attend religious services?",
[[1],[2],[3],[4],[5],[6],[7]],
['More than once a week','Once a week','Once or twice a month','A few times a year','Seldom','Never','Don\'t know']),
'pew_prayer_baseline' : ('Frequency of prayer',
"People practice their religion in different ways. Outside of attending religious services, how often do you pray?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Several time a day','Once a day','A few times a week','Once a week','A few times a month','Seldom','Never','Don\'t know']),
'pew_prayer_2016' : ('Frequency of prayer (2016)',
"People practice their religion in different ways. Outside of attending religious services, how often do you pray?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Several time a day','Once a day','A few times a week','Once a week','A few times a month','Seldom','Never','Don\'t know']),
'religpew_basline' : ('Religion',
"What is your present religion, if any?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12]],
['Protestant','Roman Catholic','Mormon','Eastern or Greek Orthodox','Jewish','Muslim','Buddhist','Hindu','Athiest','Agnostic','Nothing in Particular','Something else']),
'religpew_2016' : ('Religion (2016)',
"What is your present religion, if any?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12]],
['Protestant','Roman Catholic','Mormon','Eastern or Greek Orthodox','Jewish','Muslim','Buddhist','Hindu','Athiest','Agnostic','Nothing in Particular','Something else']),
'gunown_baseline' : ('Gun Ownership',
"Do you or does anyone in your household own a gun?",
[[1],[2]],
['Yes', 'No']),
'gunown_2016' : ('Gun Ownership (2016)',
"Do you or does anyone in your household own a gun?",
[[1],[2],[3],[8]],
['Personally own a gun', 'Gun in household', 'No Guns', 'Don\'t know']),
'knowgay4_basline' : ('Know an LGBT Person',
"Do you personally know anybody who is gay, lesbian, bisexual, or transgender?",
[[1],[2]],
['Yes', 'No']),
'gender_baseline' : ('Gender',
"Are you male or female?",
[[1],[2]],
['Male','Female']),
'race_baseline' : ('Race',
"What racial or ethnic group best describes you?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['White','Black','Hispanic','Asian','Native American','Mixed','Other','Middle Eastern']),
'educ_baseline' : ('Education',
"What is the highest level of education you have completed?",
[[1],[2],[3],[4],[5],[6]],
['No HS', 'High School', 'Some college', '2 year', '4 year', 'Post Grad']),
'employstat2_basline' : ('Employment Status',
"What is your employment status?",
[[1],[2],[3],[4],[5],[6],[7],[8], [9]],
['Full-time employed','Part-time employed','Self-employed','Unemployed or temporarily laid off','Retired','Permanently disabled','Homemaker', 'Student','Other']),
'employ_2016' : ('Employment Status (2016)',
"What is your employment status?",
[[1],[2],[3],[4],[5],[6],[7],[8], [9]],
['Full-time employed','Part-time employed','Self-employed','Unemployed or temporarily laid off','Retired','Permanently disabled','Homemaker', 'Student','Other']),
'faminc_baseline' : ('Family Income',
"Thinking back over the last year, was your family's annual what income?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[31],[97]],
['<10k', '10-20k', '20-30k','30-40k', '40-50k', '50-60k', '60-70k', '70-80k', '80-100k', '100-120k', '120-150k', '150-200k', '200-250k', '250-350k', '350-500k', '500k+', '150k+', 'Prefer not to say']),
'faminc_2016' : ('Family Income',
"Thinking back over the last year, was your family's annual what income?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[31],[97]],
['<10k', '10-20k', '20-30k','30-40k', '40-50k', '50-60k', '60-70k', '70-80k', '80-100k', '100-120k', '120-150k', '150-200k', '200-250k', '250-350k', '350-500k', '500k+', '150k+', 'Prefer not to say']),
'votereg2_2016' : ('Voter Registration',
"Are you currently registered to vote?",
[[1],[2], [3]],
['Yes', 'No', 'Don\'t Know']),
'turnout16_2016' : ('Voter Turnout',
"Did you vote in the election on Tuesday, November 8th?",
[[1],[2]],
['Yes', 'No']),
'presvote16post_2016' : ('2016 Presidential Vote',
"Who did you vote for in the 2016 Presidential Election?",
[[1],[2],[3], [4], [5], [6], [7]],
['<NAME>', '<NAME>', '<NAME>', '<NAME>', '<NAME>', 'Other', 'Didn\'t vote for Pres']),
'vote2016_cand2_2016' : ('Vote for or against',
"Was your vote primarily a vote in favor of your choice or was it mostly a vote against the opponent?",
[[1],[2]],
['For candidate', 'Against Opponent']),
'Sanders_Trump_2016' : ('Sanders vs. Trump',
"If the 2016 election had been a race between <NAME> and <NAME>, who would you have voted for?",
[[1],[2],[3]],
['Sanders', 'Trump', 'Don\'t Know']),
'vote_regrets_2016' : ('Voter Regret',
"At this point, do you have any regrets about your vote in the 2016 Presidential Election?",
[[1],[2]],
['Yes', 'No']),
'fav_trump_2016' : ('Trump Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_cruz_2016' : ('Cruz Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_ryan_2016' : ('Ryan Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_romn_2016' : ('Romney Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_obama_2016' : ('Obama Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_hrc_2016' : ('Hillary Clinton Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_sanders_2016' : ('Sanders Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'RIGGED_SYSTEM_1_2016' : ('Rigged System',
"Agree or Disagree: Elections today don't matter; things stay the same no matter who we vote in.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_2_2016' : ('Fair Society',
"Agree or Disagree: America is a fair society where everyone has the opportunity to get ahead",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_3_2016' : ('Economic system favors the wealthy',
"Agree or Disagree: our economic system is biased in favor of the wealthiest Americans.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_4_2016' : ('Media Trust',
"Agree or Disagree: You can't believe what you hear from the mainstream media.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_5_2016' : ('Government Accountability',
"Agree or Disagree: People like me don't have any say in what the government does.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'americatrend_2016' : ('Life Better or Worse',
"In general, would you say life in America today is better, worse, or about the same for people like you?",
[[1],[2],[3],[4]],
['Better','About the same', 'Worse', 'Don\'t Know']),
'trustgovt_2016' : ('Trust government to do what\'s right (2016)',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'immi_muslim_2016' : ('Muslim Ban',
"Do you favor or oppose temporarily banning Muslims from other countries from entering the United States?",
[[1],[2],[3],[4],[8]],
['Strongly Favor', 'Somewhat Favor', 'Somwhat oppose', 'Strongly oppose', 'Not sure']),
'taxdoug_2016' : ('Raising Taxes for the Wealthy (2016)',
"Do you favor raising taxes on families making over 200,000 dollars per year?",
[[1],[2],[3]],
['Yes', 'No', 'Don\'t Know']),
'reverse_discrimination_2016' : ('Reverse Discrimination',
"Today discrimination against whites has become as big a problem as discrimination against blacks and other minorities.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'ideo5_2016' : ('Ideology (2016)',
"Thinking about politics these days, how would you describe your own political viewpoint?",
[[1],[2],[3],[4],[5],[6]],
['Very Liberal', 'Liberal', 'Moderate', 'Conservative','Very Conservative', 'Not Sure']),
'pp_primary16_2016' : ('Primary Vote (2016)',
"Did you vote in the Presidential Primary this spring?",
[[1],[2],[3],[4]],
['Democratic Primary','Republican Primary','Not in either', 'Not sure']),
'pp_demprim16_2016' : ('Democratic Primary (2016)',
"Who did you vote for in the Democratic Primary?",
[[1],[2],[3],[4]],
['<NAME>', '<NAME>', 'Someone else', 'Don\'t Recall']),
'pp_repprim16_2016' : ('Republican Primary (2016)',
"Who did you vote for in the Republican Primary?",
[[1],[2],[3],[4],[5],[6]],
['<NAME>', '<NAME>', '<NAME>', '<NAME>', 'Someone else', 'Don\'t recall']),
'ft_black_2016' : ('Feelings about Blacks',
"Feelings toward group -- Blacks",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_white_2016' : ('Feelings about Whites',
"Feelings toward group -- Whites",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_hisp_2016' : ('Feelings about Hispanics',
"Feelings toward group -- Hispanics",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_muslim_2016' : ('Feelings about Muslims',
"Feelings toward group -- Muslims",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_fem_2016' : ('Feelings about Feminists',
"Feelings toward group -- Feminists",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_immig_2016' : ('Feelings about Immigrants',
"Feelings toward group -- Immigrants",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_blm_2016' : ('Feelings about Black Lives Matter',
"Feelings toward group -- Black Lives Matter",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_wallst_2016' : ('Feelings about Wall Street Bankers',
"Feelings toward group -- Wall Street Bankers",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_gays_2016' : ('Feelings about Gays',
"Feelings toward group -- Gays",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_police_2016' : ('Feelings about Police',
"Feelings toward group -- Police",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_altright_2016' : ('Feelings about The Alt Right',
"Feelings toward group -- The Alt Right",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'birthyr_baseline' : ('Age',
"Repondents Age",
[[i for i in range(1921, 1951)], [i for i in range(1951, 1971)],
[i for i in range(1971, 1986)], [i for i in range(1986, 1995)]],
['18-29', '30-44', '45-64', '65+'])
} | polls.py | polls = {
'newsint2_baseline' : ('Interest in news and public affairs',
'Some people seem to follow what\'s going on in government and public affairs most of the time, whether there\'s an election going on or not. Others aren\'t that interested. Would you say you follow what\'s going on in government and public affairs ...?',
[[1], [2], [3], [4]],
['Most of the time', 'Some of the time', 'Only now and then', 'Hardly at all']),
'newsint_2016' : ('Political Interest',
'Some people seem to follow what\'s going on in government and public affairs most of the time, whether there\'s an election going on or not. Others aren\'t that interested. Would you say you follow what\'s going on in government and public affairs ...?',
[[1], [2], [3], [4]],
['Most of the time', 'Some of the time', 'Only now and then', 'Hardly at all']),
'track_baseline' : ('Direction of the country',
'Would you say things in the country are...',
[[1], [2], [3]],
['Generally headed in the right direction', 'Off on the wrong track','Not sure']),
'track_2016' : ('Direction of the country (2016)',
'Would you say things in the country are...',
[[1], [2], [3]],
['Generally headed in the right direction', 'Off on the wrong track','Not sure']),
'americatrend_2016' : ('Life in America today for people like R compared to fifty years ago',
'In general, would you say life in America today is better, worse, or about the same as it was fifty years ago for people like you?',
[[1], [2], [3], [4]],
['Better', 'About the same', 'Worse', 'Don\'t Know']),
'wealth_2016' : ('Distribution of money and wealth in this country',
'Do you feel that the distribution of money and wealth in this country is fair, or do you feel that the money and wealth in this country should be more evenly distributed among more people?',
[[1], [2], [8]],
['Distribution is fair', 'Should be more evenly distributed', 'Don\'t know']),
'values_culture_2016' : ('In America, values and culture of people like R are...',
'In America today, do you feel the values and culture of people like you are:',
[[1], [2], [3], [8]],
['Generally becoming more widespread and accepted', 'Holding Steady', 'Generally becoming rarer', 'Don\'t Know']),
'trustgovt_baseline' : ('Trust government to do what\'s right',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'trustgovt_2016' : ('Trust government (2016)',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'trust_people_2016' : ('Most people can/can\'t be trusted',
'Generally speaking, would you say that most people can be trusted or that you can\'t be too careful in dealing with people?',
[[1], [2], [8]],
['Can\'t be too careful in dealing with people', 'Most people can be trusted', 'Don\'t know']),
'helpful_people_2016' : ('People try to be helpful or are they mostly just looking out for themselves',
'Would you say that most of the time people try to be helpful, or that they are mostly just looking out for themselves?',
[[1], [2], [8]],
['People try to be helpful', 'People are looking out for themselves', 'Don\'t know']),
'obamaapp_baseline' : ('Barack Obama Approval',
"Do you approve or dissaprove of the way Barack Obama is handlind his job as president?",
[[1],[2],[3],[4],[5]],
['Stronly approve', 'Somewhat approve', 'Somewhat disapprove', 'Strongly disapprove', 'Not Sure']),
'obamaapp_2016' : ('Barack Obama Approval (2016)',
"Do you approve or dissaprove of the way <NAME> is handlind his job as president?",
[[1],[2],[3],[4],[5]],
['Stronly approve', 'Somewhat approve', 'Somewhat disapprove', 'Strongly disapprove', 'Not Sure']),
'watchtv_baseline' : ('Hours watch TV daily',
"On a typical weekday, how many hours of TV do you watch?",
[[1],[2],[3],[4]],
['None', '1-2 Hours', '3-4 Hours', 'More than 4 hours']),
'ideo5_baseline' : ('Ideology',
"Thinking about politics these days, how would you describe your own political viewpoint?",
[[1],[2],[3],[4],[5],[6]],
['Very Liberal', 'Liberal', 'Moderate', 'Conservative', 'Very Conservative', 'Not Sure']),
'imiss_a_baseline' : ('Issue Importance: Iraq War',
"How important are the following issues to you -- The War in Iraq?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_b_baseline' : ('Issue Importance: The Economy',
"How important are the following issues to you -- The economy?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_c_baseline' : ('Issue Importance: Immigration',
"How important are the following issues to you -- Immigration?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_d_baseline' : ('Issue Importance: The Environment',
"How important are the following issues to you -- The Environment?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_f_baseline' : ('Issue Importance: Terrorism',
"How important are the following issues to you -- Terrorism?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_g_baseline' : ('Issue Importance: Gay Rights',
"How important are the following issues to you -- Gay Rights?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_baseline' : ('Issue Importance: Education',
"How important are the following issues to you -- Education?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_j_baseline' : ('Issue Importance: Health Care',
"How important are the following issues to you -- Health Care?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_m_baseline' : ('Issue Importance: Social Security',
"How important are the following issues to you -- Social Security?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_p_baseline' : ('Issue Importance: The Budget Deficit',
"How important are the following issues to you -- The Budget Deficit?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_q_baseline' : ('Issue Importance: The War in Afganistan',
"How important are the following issues to you -- The War in Afganistan?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_r_baseline' : ('Issue Importance: Taxes',
"How important are the following issues to you -- Taxes?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_s_baseline' : ('Issue Importance: Medicare',
"How important are the following issues to you -- Medicare?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_t_baseline' : ('Issue Importance: Abortion',
"How important are the following issues to you -- Abortion?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_a_2016' : ('Issue Importance: Crime (2016)',
"How important are the following issues to you -- Crime?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_b_2016' : ('Issue Importance: The Economy (2016)',
"How important are the following issues to you -- The economy?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_c_2016' : ('Issue Importance: Immigration (2016)',
"How important are the following issues to you -- Immigration?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_d_2016' : ('Issue Importance: The Environment (2016)',
"How important are the following issues to you -- The Environment?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_e_2016' : ('Issue Importance: Religious Liberty (2016)',
"How important are the following issues to you -- Religious Liberty?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_f_2016' : ('Issue Importance: Terrorism (2016)',
"How important are the following issues to you -- Terrorism?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_g_2016' : ('Issue Importance: Gay Rights (2016)',
"How important are the following issues to you -- Gay Rights?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_2016' : ('Issue Importance: Education (2016)',
"How important are the following issues to you -- Education?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_h_2016' : ('Issue Importance: Family and Medical Leave (2016)',
"How important are the following issues to you -- Family and Medical Leave?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_j_2016' : ('Issue Importance: Health Care (2016)',
"How important are the following issues to you -- Health Care?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_k_2016' : ('Issue Importance: Money in Politics (2016)',
"How important are the following issues to you -- Money in Politics?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_l_2016' : ('Issue Importance: Climate Change (2016)',
"How important are the following issues to you -- Climate Change?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_m_2016' : ('Issue Importance: Social Security',
"How important are the following issues to you -- Social Security?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_n_2016' : ('Issue Importance: Infrastructure Investment',
"How important are the following issues to you -- Infrastructure Investment'?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_o_2016' : ('Issue Importance: Jobs',
"How important are the following issues to you -- Jobs'?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_p_2016' : ('Issue Importance: The Budget Deficit (2016)',
"How important are the following issues to you -- The Budget Deficit?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_q_2016' : ('Issue Importance: Poverty',
"How important are the following issues to you -- Poverty?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_r_2016' : ('Issue Importance: Taxes (2016)',
"How important are the following issues to you -- Taxes?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_s_2016' : ('Issue Importance: Medicare (2016)',
"How important are the following issues to you -- Medicare?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_t_2016' : ('Issue Importance: Abortion (2016)',
"How important are the following issues to you -- Abortion?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_u_2016' : ('Issue Importance: The size of Government (2016)',
"How important are the following issues to you -- The size of Government?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_x_2016' : ('Issue Importance: Racial Equality (2016)',
"How important are the following issues to you -- Racial Equality?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imiss_y_2016' : ('Issue Importance: Gender Equality (2016)',
"How important are the following issues to you -- Gender Equality?",
[[1],[2],[3],[4]],
['Very Important', 'Somewhat Important','Not Very Important', 'Unimportant']),
'imissf_baseline' : ('Most important issues',
"Which of these is most important to you?",
[[1],[2],[3],[4],[6],[7],[8],[10],[13],[16],[17],[18],[19],[20]],
['The war in Iraq','The economy', 'Immigration', 'The Evironmment','Terrorism', 'Gay Rights','Education','Health Care','Social Security','The Budget Deficit','The War in Afganistan','Taxes','Medicade','Abortion']),
'immi_contribution_baseline' : ('Illegal Immigrants Contribute or Drain',
"Overall, do you think illegal immigrants American society or are a drain?",
[[1],[2],[3],[4]],
['Mostly make a contribution','Neither', 'Mostly a drain', 'Not Sure']),
'immi_contribution_2016' : ('Illegal Immigrants Contribute or Drain (2016)',
"Overall, do you think illegal immigrants American society or are a drain?",
[[1],[2],[3],[4]],
['Mostly make a contribution','Neither', 'Mostly a drain', 'Not Sure']),
'immi_naturalize_baseline' : ('Illegal Immigrant Naturalization',
"Do you favor or oppose providing a legal way for illegal immigrants already in the United States to become U.S. citizens?",
[[1], [2], [3]],
['Favor', 'Oppose', 'Not sure']),
'immi_naturalize_2016' : ('Illegal Immigrant Naturalization (2016)',
"Do you favor or oppose providing a legal way for illegal immigrants already in the United States to become U.S. citizens?",
[[1], [2], [3]],
['Favor', 'Oppose', 'Not sure']),
'immi_makedifficult_baseline' : ('Harder/Easier to Immigrate',
"Do you think it should be easier or harder for foreigners to immigrate to the US?",
[[1],[2],[3],[4],[5],[8]],
['Much easier', 'Slightly easier','No change','Slightly Harder','Much harder','Not sure']),
'immi_makedifficult_2016' : ('Harder/Easier to Immigrate (2016)',
"Do you think it should be easier or harder for foreigners to immigrate to the US?",
[[1],[2],[3],[4],[5],[8]],
['Much easier', 'Slightly easier','No change','Slightly Harder','Much harder','Not sure']),
'abortview3_baseline' : ('Abortion views',
"Do you think abortion should be...",
[[1],[2],[3],[8]],
['Legal in all cases','Legal in some cases and illegal in others','Illegal in all cases','Not sure']),
'abortview3_2016' : ('Abortion views (2016)',
"Do you think abortion should be...",
[[1],[2],[3],[8]],
['Legal in all cases','Legal in some cases and illegal in others','Illegal in all cases','Not sure']),
'gaymar2_baseline' : ('Gay Marriage',
"Do you favor or oppose allowing gays and lesbians to marry legally?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'gaymar_2016' : ('Gay Marriage (2016)',
"Do you favor or oppose allowing gays and lesbians to marry legally?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenalty_baseline' : ('Death Penalty',
"Do you favor or oppose the death penatly for persons convicted of murder?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenfreq_baseline' : ('Death Penalty Frequency',
"Do you think the death penalty enough?",
[[1],[2],[3],[4]],
['Too often', 'About Right', 'Not Often Enough', 'Not Sure']),
'deathpen_2016' : ('Death Penalty (2016)',
"Do you favor or oppose the death penatly for persons convicted of murder?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'deathpenfreq_2016' : ('Death Penalty Frequency (2016)',
"Do you think the death penalty enough?",
[[1],[2],[3],[8]],
['Too often', 'About Right', 'Not Often Enough', 'Don\'t Know']),
'taxwealth_baseline' : ('Increase Taxes on Wealthy',
"Do you favor raising taxes on families with incomes over 200,000 dollars per year?",
[[1],[2],[3]],
['Favor','Oppose','Not sure']),
'univhealthcov_baseline' : ('Federal government responsibility for healthcare',
"Do you think it is the responsibility of the federal government to see to it that everyone has health care coverage?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'univhealthcov_2016' : ('Federal government responsibility for healthcare (2016)',
"Do you think it is the responsibility of the federal government to see to it that everyone has health care coverage?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'envwarm_baseline' : ('Existence of Global Warming',
"Some people say that global temperatures have been going up slowly over the past 100 years - the phenomenon called global warming. Do you think that global warming is happening?",
[[1],[2],[3],[4],[5]],
['Defintely is happening', 'Probably is happening','Probably is not happening','Definitely is not happening', 'Not Sure']),
'envwarm_2016' : ('Existence of Global Warming (2016)',
"Some people say that global temperatures have been going up slowly over the past 100 years - the phenomenon called global warming. Do you think that global warming is happening?",
[[1],[2],[3],[4],[5]],
['Defintely is happening', 'Probably is happening','Probably is not happening','Definitely is not happening', 'Not Sure']),
'envser2_baseline' : ('Seriousness of Global Warming Problem',
"How serious a problem do you think global warming is?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not Very', 'Not Sure']),
'envpoll2_baseline' : ('Cause of global warming',
"Do you think global warming has been caused by pollution from human activities (such as emissions from cars and factories) or by natural causes?",
[[1],[2],[3]],
['Pollution from human activities','Natural causes not related to human activities','Not sure']),
'envpoll2_2016' : ('Cause of global warming (2016)',
"Do you think global warming has been caused by pollution from human activities (such as emissions from cars and factories) or by natural causes?",
[[1],[2],[3]],
['Pollution from human activities','Natural causes not related to human activities','Not sure']),
'affirmact_gen_baseline' : ('Favor or oppose affirmative action for women and racial minorities',
"Do you generally favor or oppose affirmative action programs for women and racial minorities?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'affirmact_gen_2016' : ('Favor or oppose affirmative action for women and racial minorities (2016)',
"Do you generally favor or oppose affirmative action programs for women and racial minorities?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'tradepolicy_baseline' : ('Favor or oppose increasing trade',
"Do you favor or oppose increasing trade with other nations?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'tradepolicy_2016' : ('Favor or oppose increasing trade (2016)',
"Do you favor or oppose increasing trade with other nations?",
[[1],[2],[8]],
['Favor','Oppose','Not Sure']),
'govt_reg_baseline' : ('Level of government regulation',
"In general, do you think there of business by the government?",
[[1],[2],[3],[8]],
['Too Much', 'About the right amount', 'Too little','Don\'t Know']),
'govt_reg_2016' : ('Level of government regulation (2016)',
"In general, do you think there of business by the government?",
[[1],[2],[3],[8]],
['Too Much', 'About the right amount','Too little', 'Don\'t Know']),
'pid7_baseline' : ('7 point party ID',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Strong Democrat','Not Very Strong Democrat','Lean Democrat','Independent','Lean Republican','Not very strong Republican','Strong Republican','Not sure']),
'pid7_2016' : ('7 point party ID (2016)',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Strong Democrat','Not Very Strong Democrat','Lean Democrat','Independent','Lean Republican','Not very strong Republican','Strong Republican','Not sure']),
'pid3_baseline' : ('3 point party ID',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5]],
['Democrat','Republican','Independent','Other','Not sure']),
'pid3_2016' : ('3 point party ID (2016)',
"Generally speaking, do you think of yourself as a ...?",
[[1],[2],[3],[4],[5]],
['Democrat','Republican','Independent','Other','Not sure']),
'vote_generic_baseline' : ('Generic Presidential Vote',
"If an election for president was going to be held now, would you vote for...",
[[1],[2],[3],[4],[5]],
['The Democratic Party','The Republican Party','Other','Not sure','I would not vote']),
'marstat_baseline' : ('Marital Status',
"Marital Status",
[[1],[2],[3],[4],[5],[6]],
['Married','Separated','Divorced','Widowed','Single','Domestic Partnership']),
'marstat_2016' : ('Marital Status (2016)',
"Marital Status",
[[1],[2],[3],[4],[5],[6]],
['Married','Separated','Divorced','Widowed','Single','Domestic Partnership']),
'teapartymemb_baseline' : ('Own involvement in Tea Party movement',
"Do you think of yourself as a part of the Tea Party movement?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'teapartsup_baseline' : ('Support for Tea Party',
"Generally speaking, do you support or oppose the goals of the Tea Party movement?",
[[1],[2],[3],[4],[5],[8]],
['Strongly Support', 'Somewhat Support','Neither Support nor Oppose', 'Somewhat Oppose','Strongly Oppose', 'Not Sure']),
'selfdescr_ccap_1_baseline' : ('Self Described Libertarian',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Libertarian",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_2_baseline' : ('Self Described Socialist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Socialist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_3_baseline' : ('Self Described Green',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Green",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_4_baseline' : ('Self Described Environmentalist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Environmentalist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_5_baseline' : ('Self Described Liberal',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Liberal",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_6_baseline' : ('Self Described Moderate',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Moderate",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_7_baseline' : ('Self Described Conservative',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Conservative",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_8_baseline' : ('Self Described Radical',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Radical",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_9_baseline' : ('Self Described Progressive',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Progressive",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_10_baseline' : ('Self Described Traditional',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Traditional",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_11_baseline' : ('Self Described Christian',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Christian",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_12_baseline' : ('Self Described Feminist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Feminist",
[[1],[2]],
['Yes', 'No']),
'selfdescr_ccap_13_baseline' : ('Self Described Fundamentalist',
"Here are some words that people might use to describe themselves. Which of the following words, if any, would you use to describe yourself? Fundamentalist",
[[1],[2]],
['Yes', 'No']),
'abortidentity_baseline' : ('Pro-life or Pro-Choice',
"Would you call yourself as pro-life or pro-choice?",
[[1],[2],[3],[4],[8]],
['Pro-life','Pro-choice','Both','Neither','Not Sure']),
'race_deservemore_baseline': ('Black deservedeness',
"Agree or Disagree: over the past few years, Blacks have gotten less than they deserve.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_deservemore_2016': ('Black deservedeness (2016)',
"Agree or Disagree: over the past few years, Blacks have gotten less than they deserve.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_overcome_baseline' : ('Irish, Italians, and Jews Overcoming Prejudice',
"Agree or Disagree: Irish, Italian, Jewish and other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_overcome_2016' : ('Irish, Italians, and Jews Overcoming Prejudice (2016)',
"Agree or Disagree: Irish, Italian, Jewish and other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_tryharder_baseline': ('Blacks should try harder',
"It's really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_tryharder_2016': ('Blacks should try harder (2016)',
"It's really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_slave_baseline' : ('Modern day impact of slavery',
"Generation of slavery and discrimination have created conditions that make it difficult for black to work their way out of the lower class.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'race_slave_2016' : ('Modern day impact of slavery',
"Generation of slavery and discrimination have created conditions that make it difficult for black to work their way out of the lower class.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'ownorrent_baseline' : ('Own or Rent',
"Is the place you live owned or rented?",
[[1],[2],[3]],
['Owned', 'Rented', 'Other']),
'reliablevoter_baseline': ('Voting frequency',
"How often do you vote?",
[[1],[2],[3],[4]],
['Always','Nearly Always', 'Part of the time', 'Seldom']),
'straighttic_baseline' : ('Partisan Voter Reliability',
"Do you almost always vote for candidates from the same party or do you sometimes support candidates from different parties?",
[[1],[2],[3]],
['Almost always vote Republican','Almost always vote Democrat','Vote for both Democrats and Republicans']),
'voted08_cap_baseline' : ('Voted in 2008 Presidential Election',
"Did you happen to vote in the 2008 election?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'presvote08_baseline' : ('2008 Presidential Vote',
"Which candidate did you vote for in the 2008 Presidential Election?",
[[1],[2],[3,4,5]],
['<NAME>', '<NAME>', 'Other']),
'post_presvote12_2012' : ('2008 Presidential Vote',
"Which candidate did you vote for in the 2012 Presidential Election?",
[[1],[2],[3],[4],[5]],
['<NAME>', '<NAME>', 'Other', 'Didn\'t Vote in this race', 'Didn\'t vote', 'Not Sure']),
'congvote10_ccap_baseline' : ('2010 Vote',
"Did you happen to vote in the 2010 election?",
[[1],[2],[8]],
['Yes','No','Not Sure']),
'congvote10_ccap_baseline': ('2010 Congressional Vote',
"Which candidate did you vote for in the U.S. House election?",
[[1],[2],[3]],
['Democratic','Republican', 'Other']),
'fav_obama_baseline' : ( 'Barack Obama Favorability',
"Do you have an unfavorable or favorable opinion on the following people -- Barack Obama",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_hrc_baseline' : ('<NAME> Favorability',
"Do you have an unfavorable or favorable opinion on the following people -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'pew_bornagain_baseline' : ('Born Again Christains',
"Would you describe yourself as Christian, or not?",
[[1],[2]],
['Yes', 'No']),
'pew_bornagain_2016' : ('Born Again Christains (2016)',
"Would you describe yourself as Christian, or not?",
[[1],[2]],
['Yes', 'No']),
'pew_religimp_' : ('Imporance of religion',
"How impotant is religion in your life?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not too imporant', 'Not at all']),
'pew_religimp_2016' : ('Imporance of religion (2016)',
"How impotant is religion in your life?",
[[1],[2],[3],[4]],
['Very', 'Somewhat', 'Not too imporant', 'Not at all']),
'pew_churchatd_baseline' : ('Church attendance',
"Aside from weddings and funerals, how often do you attend religious services?",
[[1],[2],[3],[4],[5],[6],[7]],
['More than once a week','Once a week','Once or twice a month','A few times a year','Seldom','Never','Don\'t know']),
'pew_churchatd_2016' : ('Church attendance (2016)',
"Aside from weddings and funerals, how often do you attend religious services?",
[[1],[2],[3],[4],[5],[6],[7]],
['More than once a week','Once a week','Once or twice a month','A few times a year','Seldom','Never','Don\'t know']),
'pew_prayer_baseline' : ('Frequency of prayer',
"People practice their religion in different ways. Outside of attending religious services, how often do you pray?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Several time a day','Once a day','A few times a week','Once a week','A few times a month','Seldom','Never','Don\'t know']),
'pew_prayer_2016' : ('Frequency of prayer (2016)',
"People practice their religion in different ways. Outside of attending religious services, how often do you pray?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['Several time a day','Once a day','A few times a week','Once a week','A few times a month','Seldom','Never','Don\'t know']),
'religpew_basline' : ('Religion',
"What is your present religion, if any?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12]],
['Protestant','Roman Catholic','Mormon','Eastern or Greek Orthodox','Jewish','Muslim','Buddhist','Hindu','Athiest','Agnostic','Nothing in Particular','Something else']),
'religpew_2016' : ('Religion (2016)',
"What is your present religion, if any?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12]],
['Protestant','Roman Catholic','Mormon','Eastern or Greek Orthodox','Jewish','Muslim','Buddhist','Hindu','Athiest','Agnostic','Nothing in Particular','Something else']),
'gunown_baseline' : ('Gun Ownership',
"Do you or does anyone in your household own a gun?",
[[1],[2]],
['Yes', 'No']),
'gunown_2016' : ('Gun Ownership (2016)',
"Do you or does anyone in your household own a gun?",
[[1],[2],[3],[8]],
['Personally own a gun', 'Gun in household', 'No Guns', 'Don\'t know']),
'knowgay4_basline' : ('Know an LGBT Person',
"Do you personally know anybody who is gay, lesbian, bisexual, or transgender?",
[[1],[2]],
['Yes', 'No']),
'gender_baseline' : ('Gender',
"Are you male or female?",
[[1],[2]],
['Male','Female']),
'race_baseline' : ('Race',
"What racial or ethnic group best describes you?",
[[1],[2],[3],[4],[5],[6],[7],[8]],
['White','Black','Hispanic','Asian','Native American','Mixed','Other','Middle Eastern']),
'educ_baseline' : ('Education',
"What is the highest level of education you have completed?",
[[1],[2],[3],[4],[5],[6]],
['No HS', 'High School', 'Some college', '2 year', '4 year', 'Post Grad']),
'employstat2_basline' : ('Employment Status',
"What is your employment status?",
[[1],[2],[3],[4],[5],[6],[7],[8], [9]],
['Full-time employed','Part-time employed','Self-employed','Unemployed or temporarily laid off','Retired','Permanently disabled','Homemaker', 'Student','Other']),
'employ_2016' : ('Employment Status (2016)',
"What is your employment status?",
[[1],[2],[3],[4],[5],[6],[7],[8], [9]],
['Full-time employed','Part-time employed','Self-employed','Unemployed or temporarily laid off','Retired','Permanently disabled','Homemaker', 'Student','Other']),
'faminc_baseline' : ('Family Income',
"Thinking back over the last year, was your family's annual what income?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[31],[97]],
['<10k', '10-20k', '20-30k','30-40k', '40-50k', '50-60k', '60-70k', '70-80k', '80-100k', '100-120k', '120-150k', '150-200k', '200-250k', '250-350k', '350-500k', '500k+', '150k+', 'Prefer not to say']),
'faminc_2016' : ('Family Income',
"Thinking back over the last year, was your family's annual what income?",
[[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[31],[97]],
['<10k', '10-20k', '20-30k','30-40k', '40-50k', '50-60k', '60-70k', '70-80k', '80-100k', '100-120k', '120-150k', '150-200k', '200-250k', '250-350k', '350-500k', '500k+', '150k+', 'Prefer not to say']),
'votereg2_2016' : ('Voter Registration',
"Are you currently registered to vote?",
[[1],[2], [3]],
['Yes', 'No', 'Don\'t Know']),
'turnout16_2016' : ('Voter Turnout',
"Did you vote in the election on Tuesday, November 8th?",
[[1],[2]],
['Yes', 'No']),
'presvote16post_2016' : ('2016 Presidential Vote',
"Who did you vote for in the 2016 Presidential Election?",
[[1],[2],[3], [4], [5], [6], [7]],
['<NAME>', '<NAME>', '<NAME>', '<NAME>', '<NAME>', 'Other', 'Didn\'t vote for Pres']),
'vote2016_cand2_2016' : ('Vote for or against',
"Was your vote primarily a vote in favor of your choice or was it mostly a vote against the opponent?",
[[1],[2]],
['For candidate', 'Against Opponent']),
'Sanders_Trump_2016' : ('Sanders vs. Trump',
"If the 2016 election had been a race between <NAME> and <NAME>, who would you have voted for?",
[[1],[2],[3]],
['Sanders', 'Trump', 'Don\'t Know']),
'vote_regrets_2016' : ('Voter Regret',
"At this point, do you have any regrets about your vote in the 2016 Presidential Election?",
[[1],[2]],
['Yes', 'No']),
'fav_trump_2016' : ('Trump Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_cruz_2016' : ('Cruz Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_ryan_2016' : ('Ryan Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_romn_2016' : ('Romney Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_obama_2016' : ('Obama Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_hrc_2016' : ('Hillary Clinton Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'fav_sanders_2016' : ('Sanders Favorability',
"Do you have a favorable or unfavorable view of the following person -- <NAME>",
[[1],[2],[3],[4],[8]],
['Very favorable','Somewhat favorable','Somewhat unfavorable','Very unfavorable','Don\'t know']),
'RIGGED_SYSTEM_1_2016' : ('Rigged System',
"Agree or Disagree: Elections today don't matter; things stay the same no matter who we vote in.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_2_2016' : ('Fair Society',
"Agree or Disagree: America is a fair society where everyone has the opportunity to get ahead",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_3_2016' : ('Economic system favors the wealthy',
"Agree or Disagree: our economic system is biased in favor of the wealthiest Americans.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_4_2016' : ('Media Trust',
"Agree or Disagree: You can't believe what you hear from the mainstream media.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'RIGGED_SYSTEM_5_2016' : ('Government Accountability',
"Agree or Disagree: People like me don't have any say in what the government does.",
[[1],[2],[3],[4]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree']),
'americatrend_2016' : ('Life Better or Worse',
"In general, would you say life in America today is better, worse, or about the same for people like you?",
[[1],[2],[3],[4]],
['Better','About the same', 'Worse', 'Don\'t Know']),
'trustgovt_2016' : ('Trust government to do what\'s right (2016)',
'How much of the time do you think you can trust the government in Washington to do what is right?',
[[1], [2], [3]],
['Just about always', 'Most of the time', 'Some of the time']),
'immi_muslim_2016' : ('Muslim Ban',
"Do you favor or oppose temporarily banning Muslims from other countries from entering the United States?",
[[1],[2],[3],[4],[8]],
['Strongly Favor', 'Somewhat Favor', 'Somwhat oppose', 'Strongly oppose', 'Not sure']),
'taxdoug_2016' : ('Raising Taxes for the Wealthy (2016)',
"Do you favor raising taxes on families making over 200,000 dollars per year?",
[[1],[2],[3]],
['Yes', 'No', 'Don\'t Know']),
'reverse_discrimination_2016' : ('Reverse Discrimination',
"Today discrimination against whites has become as big a problem as discrimination against blacks and other minorities.",
[[1],[2],[3],[4],[5]],
['Strongly Agree', 'Agree', 'Don\'t know','Disagree', 'Strongly Disagree']),
'ideo5_2016' : ('Ideology (2016)',
"Thinking about politics these days, how would you describe your own political viewpoint?",
[[1],[2],[3],[4],[5],[6]],
['Very Liberal', 'Liberal', 'Moderate', 'Conservative','Very Conservative', 'Not Sure']),
'pp_primary16_2016' : ('Primary Vote (2016)',
"Did you vote in the Presidential Primary this spring?",
[[1],[2],[3],[4]],
['Democratic Primary','Republican Primary','Not in either', 'Not sure']),
'pp_demprim16_2016' : ('Democratic Primary (2016)',
"Who did you vote for in the Democratic Primary?",
[[1],[2],[3],[4]],
['<NAME>', '<NAME>', 'Someone else', 'Don\'t Recall']),
'pp_repprim16_2016' : ('Republican Primary (2016)',
"Who did you vote for in the Republican Primary?",
[[1],[2],[3],[4],[5],[6]],
['<NAME>', '<NAME>', '<NAME>', '<NAME>', 'Someone else', 'Don\'t recall']),
'ft_black_2016' : ('Feelings about Blacks',
"Feelings toward group -- Blacks",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_white_2016' : ('Feelings about Whites',
"Feelings toward group -- Whites",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_hisp_2016' : ('Feelings about Hispanics',
"Feelings toward group -- Hispanics",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_muslim_2016' : ('Feelings about Muslims',
"Feelings toward group -- Muslims",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_fem_2016' : ('Feelings about Feminists',
"Feelings toward group -- Feminists",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_immig_2016' : ('Feelings about Immigrants',
"Feelings toward group -- Immigrants",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_blm_2016' : ('Feelings about Black Lives Matter',
"Feelings toward group -- Black Lives Matter",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_wallst_2016' : ('Feelings about Wall Street Bankers',
"Feelings toward group -- Wall Street Bankers",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_gays_2016' : ('Feelings about Gays',
"Feelings toward group -- Gays",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_police_2016' : ('Feelings about Police',
"Feelings toward group -- Police",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'ft_altright_2016' : ('Feelings about The Alt Right',
"Feelings toward group -- The Alt Right",
[[0], [i for i in range(1,25)], [25], [i for i in range(26,50)], [50],
[i for i in range(51,75)], [75], [i for i in range(76,100)], [100]],
['Very Cold', 'Cold', 'Fairly cold', 'Somewhat cold','No feeling at all',
'Somewhat warm', 'Fairly warm', 'Warm', 'Very warm']),
'birthyr_baseline' : ('Age',
"Repondents Age",
[[i for i in range(1921, 1951)], [i for i in range(1951, 1971)],
[i for i in range(1971, 1986)], [i for i in range(1986, 1995)]],
['18-29', '30-44', '45-64', '65+'])
} | 0.272702 | 0.59884 |
import logging
from apel.db.records.storage import StorageRecord
from apel.db.records.group_attribute import GroupAttributeRecord
from apel.common.datetime_utils import parse_timestamp
from xml_parser import XMLParser, XMLParserException
log = logging.getLogger(__name__)
class StarParser(XMLParser):
'''
Parser for Storage Accounting Records
For documentation please visit:
https://twiki.cern.ch/twiki/bin/view/EMI/StorageAccounting
'''
NAMESPACE = "http://eu-emi.eu/namespaces/2011/02/storagerecord"
def get_records(self):
"""
Returns list of parsed records from STAR file.
Please notice that this parser _requires_ valid
structure of XML document, including namespace
information and prefixes in XML tag (like urf:StorageUsageRecord).
"""
records = []
xml_storage_records = self.doc.getElementsByTagNameNS(
self.NAMESPACE, 'StorageUsageRecord')
if len(xml_storage_records) == 0:
raise XMLParserException('File does not contain StAR records!')
for xml_storage_record in xml_storage_records:
# get record and associated attributes
record, group_attributes = self.parseStarRecord(xml_storage_record)
# add all of them to the record list
records.append(record)
records += group_attributes
return records
def parseStarRecord(self, xml_storage_record):
"""
Parses single entry for Storage Accounting Record.
Uses a dictionary containing fields from the storage record and methods
to extract them from the XML. Returns a list of StorageRecords (plus
GroupAttributeRecords if there are GroupAttributes that have an
attributeType that is NOT subgroup or role).
"""
functions = {
'RecordId': lambda nodes: self.getAttr(
nodes['RecordIdentity'][0], 'recordId'),
'CreateTime': lambda nodes: parse_timestamp(self.getAttr(
nodes['RecordIdentity'][0], 'createTime')),
'StorageSystem': lambda nodes: self.getText(
nodes['StorageSystem'][0].childNodes),
'Site': lambda nodes: self.getText(
nodes['Site'][0].childNodes),
'StorageShare': lambda nodes: self.getText(
nodes['StorageShare'][0].childNodes),
'StorageMedia': lambda nodes: self.getText(
nodes['StorageMedia'][0].childNodes),
'StorageClass': lambda nodes: self.getText(
nodes['StorageClass'][0].childNodes),
'FileCount': lambda nodes: self.getText(
nodes['FileCount'][0].childNodes),
'DirectoryPath': lambda nodes: self.getText(
nodes['DirectoryPath'][0].childNodes),
'LocalUser': lambda nodes: self.getText(
nodes['LocalUser'][0].childNodes),
'LocalGroup': lambda nodes: self.getText(
nodes['LocalGroup'][0].childNodes),
'UserIdentity': lambda nodes: self.getText(
nodes['UserIdentity'][0].childNodes),
'Group': lambda nodes: self.getText(
nodes['Group'][0].childNodes),
'SubGroup': lambda nodes: self.getText(self.getTagByAttr(
nodes['SubGroup'], 'attributeType', 'subgroup')[0].childNodes),
'Role': lambda nodes: self.getText(self.getTagByAttr(
nodes['Role'], 'attributeType', 'role')[0].childNodes),
'StartTime': lambda nodes: parse_timestamp(self.getText(
nodes['StartTime'][0].childNodes)),
'EndTime': lambda nodes: parse_timestamp(self.getText(
nodes['EndTime'][0].childNodes)),
'ResourceCapacityUsed': lambda nodes: self.getText(
nodes['ResourceCapacityUsed'][0].childNodes),
'LogicalCapacityUsed': lambda nodes: self.getText(
nodes['LogicalCapacityUsed'][0].childNodes),
'ResourceCapacityAllocated': lambda nodes: self.getText(
nodes['ResourceCapacityAllocated'][0].childNodes)
}
# Here we copy keys from functions.
# We only want to change 'RecordId' to 'RecordIdentity'.
nodes = {}.fromkeys(map(lambda f: f == 'RecordId' and
'RecordIdentity' or f, [S for S in functions]))
# nodes = {}.fromkeys(functions.keys())
data = {}
for node in nodes:
if node in ('SubGroup', 'Role'):
# For these attributes we need to dig into the GroupAttribute
# elements to get the values so we save the whole elements.
nodes[node] = xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, 'GroupAttribute')
else:
nodes[node] = xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, node)
# empty list = element have not been found in XML file
for field in functions:
try:
data[field] = functions[field](nodes)
except (IndexError, KeyError), e:
log.debug("Failed to get field %s: %s", field, e)
sr = StorageRecord()
sr.set_all(data)
return sr, self.parseGroupAttributes(
xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, 'GroupAttribute'), sr.get_field('RecordId'))
def parseGroupAttributes(self, nodes, star_record_id):
"""
Return a list of GroupAttributeRecords associated with a StarRecord.
Only returns records for attributeTypes other than subgroup and role as
those two types are stored in the StarRecord.
"""
ret = []
for node in nodes:
attr_type = self.getAttr(node, 'attributeType')
# Only create records for types other than subgroup and role
if attr_type not in ('subgroup', 'role'):
group_attr = GroupAttributeRecord()
group_attr.set_field('StarRecordID', star_record_id)
group_attr.set_field('AttributeType', attr_type)
attr_value = self.getText(node.childNodes)
group_attr.set_field('AttributeValue', attr_value)
ret.append(group_attr)
return ret | apel/db/loader/star_parser.py | import logging
from apel.db.records.storage import StorageRecord
from apel.db.records.group_attribute import GroupAttributeRecord
from apel.common.datetime_utils import parse_timestamp
from xml_parser import XMLParser, XMLParserException
log = logging.getLogger(__name__)
class StarParser(XMLParser):
'''
Parser for Storage Accounting Records
For documentation please visit:
https://twiki.cern.ch/twiki/bin/view/EMI/StorageAccounting
'''
NAMESPACE = "http://eu-emi.eu/namespaces/2011/02/storagerecord"
def get_records(self):
"""
Returns list of parsed records from STAR file.
Please notice that this parser _requires_ valid
structure of XML document, including namespace
information and prefixes in XML tag (like urf:StorageUsageRecord).
"""
records = []
xml_storage_records = self.doc.getElementsByTagNameNS(
self.NAMESPACE, 'StorageUsageRecord')
if len(xml_storage_records) == 0:
raise XMLParserException('File does not contain StAR records!')
for xml_storage_record in xml_storage_records:
# get record and associated attributes
record, group_attributes = self.parseStarRecord(xml_storage_record)
# add all of them to the record list
records.append(record)
records += group_attributes
return records
def parseStarRecord(self, xml_storage_record):
"""
Parses single entry for Storage Accounting Record.
Uses a dictionary containing fields from the storage record and methods
to extract them from the XML. Returns a list of StorageRecords (plus
GroupAttributeRecords if there are GroupAttributes that have an
attributeType that is NOT subgroup or role).
"""
functions = {
'RecordId': lambda nodes: self.getAttr(
nodes['RecordIdentity'][0], 'recordId'),
'CreateTime': lambda nodes: parse_timestamp(self.getAttr(
nodes['RecordIdentity'][0], 'createTime')),
'StorageSystem': lambda nodes: self.getText(
nodes['StorageSystem'][0].childNodes),
'Site': lambda nodes: self.getText(
nodes['Site'][0].childNodes),
'StorageShare': lambda nodes: self.getText(
nodes['StorageShare'][0].childNodes),
'StorageMedia': lambda nodes: self.getText(
nodes['StorageMedia'][0].childNodes),
'StorageClass': lambda nodes: self.getText(
nodes['StorageClass'][0].childNodes),
'FileCount': lambda nodes: self.getText(
nodes['FileCount'][0].childNodes),
'DirectoryPath': lambda nodes: self.getText(
nodes['DirectoryPath'][0].childNodes),
'LocalUser': lambda nodes: self.getText(
nodes['LocalUser'][0].childNodes),
'LocalGroup': lambda nodes: self.getText(
nodes['LocalGroup'][0].childNodes),
'UserIdentity': lambda nodes: self.getText(
nodes['UserIdentity'][0].childNodes),
'Group': lambda nodes: self.getText(
nodes['Group'][0].childNodes),
'SubGroup': lambda nodes: self.getText(self.getTagByAttr(
nodes['SubGroup'], 'attributeType', 'subgroup')[0].childNodes),
'Role': lambda nodes: self.getText(self.getTagByAttr(
nodes['Role'], 'attributeType', 'role')[0].childNodes),
'StartTime': lambda nodes: parse_timestamp(self.getText(
nodes['StartTime'][0].childNodes)),
'EndTime': lambda nodes: parse_timestamp(self.getText(
nodes['EndTime'][0].childNodes)),
'ResourceCapacityUsed': lambda nodes: self.getText(
nodes['ResourceCapacityUsed'][0].childNodes),
'LogicalCapacityUsed': lambda nodes: self.getText(
nodes['LogicalCapacityUsed'][0].childNodes),
'ResourceCapacityAllocated': lambda nodes: self.getText(
nodes['ResourceCapacityAllocated'][0].childNodes)
}
# Here we copy keys from functions.
# We only want to change 'RecordId' to 'RecordIdentity'.
nodes = {}.fromkeys(map(lambda f: f == 'RecordId' and
'RecordIdentity' or f, [S for S in functions]))
# nodes = {}.fromkeys(functions.keys())
data = {}
for node in nodes:
if node in ('SubGroup', 'Role'):
# For these attributes we need to dig into the GroupAttribute
# elements to get the values so we save the whole elements.
nodes[node] = xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, 'GroupAttribute')
else:
nodes[node] = xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, node)
# empty list = element have not been found in XML file
for field in functions:
try:
data[field] = functions[field](nodes)
except (IndexError, KeyError), e:
log.debug("Failed to get field %s: %s", field, e)
sr = StorageRecord()
sr.set_all(data)
return sr, self.parseGroupAttributes(
xml_storage_record.getElementsByTagNameNS(
self.NAMESPACE, 'GroupAttribute'), sr.get_field('RecordId'))
def parseGroupAttributes(self, nodes, star_record_id):
"""
Return a list of GroupAttributeRecords associated with a StarRecord.
Only returns records for attributeTypes other than subgroup and role as
those two types are stored in the StarRecord.
"""
ret = []
for node in nodes:
attr_type = self.getAttr(node, 'attributeType')
# Only create records for types other than subgroup and role
if attr_type not in ('subgroup', 'role'):
group_attr = GroupAttributeRecord()
group_attr.set_field('StarRecordID', star_record_id)
group_attr.set_field('AttributeType', attr_type)
attr_value = self.getText(node.childNodes)
group_attr.set_field('AttributeValue', attr_value)
ret.append(group_attr)
return ret | 0.456894 | 0.232795 |
import sys
import ast
import vim
import os.path
import pkgutil
class Pin:
def __init__(self):
self.cWORD = vim.eval("expand('<cWORD>')")
self.cword = vim.eval("expand('<cword>')")
self.cline = vim.eval("getline('.')")
if self.cWORD in ["import", "from", "as"]:
raise ValueError(
"The current word is an import statement keyword: "
"'import', 'from', 'as'."
)
def navigate(self):
# Parse the current line into an abstract syntax tree. This should
# fail if the current line is not syntactically correct Python 2.
try:
self.lineTree = ast.parse(self.cline)
except SyntaxError as se:
print se
raise ImportError(
"Import navigation failed. There is a syntax error on the "
"cursor's line.\n\n"
"Note: PIN only considers the current line of source code the "
"cursor is on.\n"
"Is this line a syntactically correct import statement?"
)
except TypeError as te:
print te
raise ImportError(
"Import navigation failed. There are null bytes on the cursor's "
"line.\n\n"
"Note: PIN only considers the current line of source code the "
"cursor is on.\n"
)
importTree = self.extractImportTree(self.lineTree)
module = self.extractModule(importTree)
package = pkgutil.get_loader(module)
if package is None:
raise ImportError("This module cannot be loaded.")
if os.path.isdir(package.filename):
if os.path.isfile(os.path.join(package.filename, "__init__.py")):
filename = os.path.join(package.filename, "__init__.py")
else:
raise ValueError("Unable to locate the module's file")
else:
filename = package.filename
vim.command("tabnew {file}".format(file=filename))
def extractImportTree(self, tree):
"""
Return the subtree rooted at the import statement containing
the descendant cword.
"""
# Extract the subtree rooted at the Import or ImportFrom node
# associated to the lexeme given by cword.
# If there is no import statement in lineTree raise a ValueError
def checkNames(tree):
for node in ast.walk(tree):
if isinstance(node, ast.alias) and\
(node.name == self.cword or\
node.asname == self.cword or\
node.name == self.cWORD):
return True
return False
if len(tree.body) == 1:
node = tree.body[0]
if isinstance(node, ast.Import) or\
isinstance(node, ast.ImportFrom):
return node
for node in ast.walk(tree):
if isinstance(node, ast.Import) and checkNames(node):
return node
if isinstance(node, ast.ImportFrom) and\
(checkNames(node) or self.cWORD == node.module):
return node
raise ValueError("The current word is not part of an import statement")
# Extract the module that contains cword; this may be cword itself.
def extractModule(self, tree):
""" Return the module name containing cword """
if isinstance(tree, ast.Import):
return self.extractModuleFromImport(tree)
else:
return self.extractModuleFromImportFrom(tree)
def extractModuleFromImport(self, tree):
""" Return the name of the module containing cword.
tree must be an ast.Import node. It is therefore the case
that for one of tree's ast.alias nodes:
1) cword and cWORD are equal to the asname of the alias
OR
2) cWORD is equal to the name of the alias and cword is
equal to one of the dot delimited name components
"""
if not isinstance(tree, ast.Import):
raise TypeError("Did not receive an ast.Import node.")
for node in tree.names:
if self.cword == node.asname:
return node.name
if self.cWORD in [node.name, node.asname]:
return node.name
raise ValueError(
"ast.Import node tree does not contain a descendant "
"with the current word under the cursor."
)
def extractModuleFromImportFrom(self, tree):
""" Return the name of the module containing cword.
tree must be an ast.ImportFrom node. Therefore either:
1) cWORD is equal to the tree's module attribute and cword
is equal to one of the dot delimited components of module
OR
2) cword and cWORD are equal to the name or asname of one of
the ast.alias child nodes of tree
"""
if not isinstance(tree, ast.ImportFrom):
raise TypeError("Did not receive an ast.ImportFrom node.")
if tree.module is None:
packagePath = os.path.dirname(vim.eval("expand('%:p')"))
sys.path.append(packagePath)
module = os.path.basename(packagePath)
tree.module = module
if self.cWORD == '.':
self.cWORD = module
if self.cWORD == tree.module:
return self.cWORD
for node in tree.names:
if self.cword in [node.name, node.asname]:
if pkgutil.get_loader(node.name) is not None:
return node.name
else:
return tree.module
raise ValueError(
"ast.ImportFrom node tree does not contain a descendant "
"with the current word under the cursor."
)
try:
Pin().navigate()
except ImportError as ie:
print ie
except ValueError as ve:
print ve
except TypeError as te:
print te | ftplugin/python/pin.py | import sys
import ast
import vim
import os.path
import pkgutil
class Pin:
def __init__(self):
self.cWORD = vim.eval("expand('<cWORD>')")
self.cword = vim.eval("expand('<cword>')")
self.cline = vim.eval("getline('.')")
if self.cWORD in ["import", "from", "as"]:
raise ValueError(
"The current word is an import statement keyword: "
"'import', 'from', 'as'."
)
def navigate(self):
# Parse the current line into an abstract syntax tree. This should
# fail if the current line is not syntactically correct Python 2.
try:
self.lineTree = ast.parse(self.cline)
except SyntaxError as se:
print se
raise ImportError(
"Import navigation failed. There is a syntax error on the "
"cursor's line.\n\n"
"Note: PIN only considers the current line of source code the "
"cursor is on.\n"
"Is this line a syntactically correct import statement?"
)
except TypeError as te:
print te
raise ImportError(
"Import navigation failed. There are null bytes on the cursor's "
"line.\n\n"
"Note: PIN only considers the current line of source code the "
"cursor is on.\n"
)
importTree = self.extractImportTree(self.lineTree)
module = self.extractModule(importTree)
package = pkgutil.get_loader(module)
if package is None:
raise ImportError("This module cannot be loaded.")
if os.path.isdir(package.filename):
if os.path.isfile(os.path.join(package.filename, "__init__.py")):
filename = os.path.join(package.filename, "__init__.py")
else:
raise ValueError("Unable to locate the module's file")
else:
filename = package.filename
vim.command("tabnew {file}".format(file=filename))
def extractImportTree(self, tree):
"""
Return the subtree rooted at the import statement containing
the descendant cword.
"""
# Extract the subtree rooted at the Import or ImportFrom node
# associated to the lexeme given by cword.
# If there is no import statement in lineTree raise a ValueError
def checkNames(tree):
for node in ast.walk(tree):
if isinstance(node, ast.alias) and\
(node.name == self.cword or\
node.asname == self.cword or\
node.name == self.cWORD):
return True
return False
if len(tree.body) == 1:
node = tree.body[0]
if isinstance(node, ast.Import) or\
isinstance(node, ast.ImportFrom):
return node
for node in ast.walk(tree):
if isinstance(node, ast.Import) and checkNames(node):
return node
if isinstance(node, ast.ImportFrom) and\
(checkNames(node) or self.cWORD == node.module):
return node
raise ValueError("The current word is not part of an import statement")
# Extract the module that contains cword; this may be cword itself.
def extractModule(self, tree):
""" Return the module name containing cword """
if isinstance(tree, ast.Import):
return self.extractModuleFromImport(tree)
else:
return self.extractModuleFromImportFrom(tree)
def extractModuleFromImport(self, tree):
""" Return the name of the module containing cword.
tree must be an ast.Import node. It is therefore the case
that for one of tree's ast.alias nodes:
1) cword and cWORD are equal to the asname of the alias
OR
2) cWORD is equal to the name of the alias and cword is
equal to one of the dot delimited name components
"""
if not isinstance(tree, ast.Import):
raise TypeError("Did not receive an ast.Import node.")
for node in tree.names:
if self.cword == node.asname:
return node.name
if self.cWORD in [node.name, node.asname]:
return node.name
raise ValueError(
"ast.Import node tree does not contain a descendant "
"with the current word under the cursor."
)
def extractModuleFromImportFrom(self, tree):
""" Return the name of the module containing cword.
tree must be an ast.ImportFrom node. Therefore either:
1) cWORD is equal to the tree's module attribute and cword
is equal to one of the dot delimited components of module
OR
2) cword and cWORD are equal to the name or asname of one of
the ast.alias child nodes of tree
"""
if not isinstance(tree, ast.ImportFrom):
raise TypeError("Did not receive an ast.ImportFrom node.")
if tree.module is None:
packagePath = os.path.dirname(vim.eval("expand('%:p')"))
sys.path.append(packagePath)
module = os.path.basename(packagePath)
tree.module = module
if self.cWORD == '.':
self.cWORD = module
if self.cWORD == tree.module:
return self.cWORD
for node in tree.names:
if self.cword in [node.name, node.asname]:
if pkgutil.get_loader(node.name) is not None:
return node.name
else:
return tree.module
raise ValueError(
"ast.ImportFrom node tree does not contain a descendant "
"with the current word under the cursor."
)
try:
Pin().navigate()
except ImportError as ie:
print ie
except ValueError as ve:
print ve
except TypeError as te:
print te | 0.41561 | 0.236197 |
from bio2bel_mirtarbase.manager import _build_entrez_map
from bio2bel_mirtarbase.models import Evidence, HGNC, MIRBASE, Mirna, NCBIGENE, Species, Target
from pybel import BELGraph
from pybel.constants import FUNCTION, IDENTIFIER, NAME, NAMESPACE
from pybel.dsl import BaseAbundance, mirna, rna
from tests.constants import TemporaryFilledCacheMixin
hif1a_symbol = 'HIF1A'
hif1a_hgnc_name = rna(name=hif1a_symbol, namespace=HGNC)
hif1a_hgnc_identifier = rna(identifier='4910', namespace=HGNC)
hif1a_entrez_name = rna(name='3091', namespace=NCBIGENE)
hif1a_entrez_identifier = rna(identifier='3091', namespace=NCBIGENE)
mi2_data = mirna(name='hsa-miR-20a-5p', namespace=MIRBASE)
mi5_data = mirna(name='mmu-miR-124-3p', namespace=MIRBASE)
class TestBuildDatabase(TemporaryFilledCacheMixin):
"""Test the database."""
def test_count_human_genes(self):
"""Test the number of genes in Bio2BEL HGNC."""
self.assertEqual(2, self.hgnc_manager.count_human_genes())
def test_count_mirnas(self):
"""Test the number of miRNAs."""
self.assertEqual(5, self.manager.count_mirnas())
def test_count_targets(self):
"""Test the number of targets."""
self.assertEqual(6, self.manager.count_targets())
def test_count_interactions(self):
"""Test the number of interactions."""
self.assertEqual(6, self.manager.count_interactions())
def test_count_evidences(self):
"""Test the number of evidences."""
self.assertEqual(10, self.manager.count_evidences())
def test_count_species(self):
"""Test the number of species."""
self.assertEqual(3, self.manager.session.query(Species).count())
def test_count_hgnc(self):
"""Test the number of human genes."""
self.assertEqual(2, len(self.hgnc_manager.hgnc()))
def test_get_cxcr4_by_entrez(self):
"""Test getting cxcr4 by its Entrez gene identifier."""
models = self.hgnc_manager.hgnc(entrez='7852')
self.assertEqual(1, len(models))
model = models[0]
self.assertIsNotNone(model)
self.assertEqual('CXCR4', model.symbol)
self.assertEqual('7852', model.entrez)
def test_get_hif1a_by_entrez(self):
"""Test getting hif1a by its Entrez gene identifier."""
models = self.hgnc_manager.hgnc(entrez='3091')
self.assertEqual(1, len(models))
model = models[0]
self.assertIsNotNone(model)
self.assertEqual('HIF1A', model.symbol)
self.assertEqual('3091', model.entrez)
def test_build_map(self):
"""Test building an Entrez map."""
emap = _build_entrez_map(self.hgnc_manager)
self.assertEqual(2, len(emap))
self.assertIn('7852', emap)
self.assertIn('3091', emap)
def test_evidence(self):
"""Test the populate function of the database manager."""
ev2 = self.manager.session.query(Evidence).filter(Evidence.reference == '18619591').first()
self.assertIsNotNone(ev2)
self.assertEqual("Luciferase reporter assay//qRT-PCR//Western blot//Reporter assay;Microarray", ev2.experiment)
def check_mir5(self, model: Mirna):
"""Help check the model has the right information for mmu-miR-124-3p."""
self.assertIsNotNone(model)
self.assertEqual("mmu-miR-124-3p", model.name)
self.assertTrue(any('MIRT000005' == interaction.mirtarbase_id for interaction in model.interactions))
bel_data = model.as_bel()
self.assertEqual(mi5_data.function, bel_data.function)
self.assertEqual(mi5_data.name, bel_data.name)
self.assertEqual(mi5_data.namespace, bel_data.namespace)
def test_mirna_by_mirtarbase_id(self):
"""Test getting an miRNA by a miRTarBase relationship identifier."""
mi5 = self.manager.query_mirna_by_mirtarbase_identifier('MIRT000005')
self.check_mir5(mi5)
def check_mir2(self, model: Mirna):
"""Help check the model has the right information for mmu-miR-124-3p."""
self.assertIsNotNone(model)
self.assertEqual("hsa-miR-20a-5p", model.name)
self.assertEqual(2, len(model.interactions))
self.assertTrue(any('MIRT000002' == interaction.mirtarbase_id for interaction in model.interactions))
bel_data = model.as_bel()
self.assertEqual(mi2_data[FUNCTION], bel_data[FUNCTION])
self.assertEqual(mi2_data[NAME], bel_data[NAME])
self.assertEqual(mi2_data[NAMESPACE], bel_data[NAMESPACE])
def test_mirna_2_by_mirtarbase_id(self):
"""Test getting an miRNA by a miRTarBase relationship identifier."""
mi2 = self.manager.query_mirna_by_mirtarbase_identifier('MIRT000002')
self.check_mir2(mi2)
def test_target(self):
"""Test getting a target by Entrez Gene identifier."""
target = self.manager.query_target_by_entrez_id('7852')
self.assertIsNotNone(target)
self.assertEqual("CXCR4", target.name)
self.assertIsNotNone(target.hgnc_id)
self.assertEqual("2561", target.hgnc_id)
def check_hif1a(self, model: Target):
"""Help check the model has all the right information for HIF1A.
:type model: Target
"""
self.assertIsNotNone(model)
self.assertEqual('HIF1A', model.name)
self.assertIsNotNone(model.hgnc_id)
self.assertEqual('4910', model.hgnc_id)
self.assertIsNotNone(model.hgnc_symbol)
self.assertEqual('HIF1A', model.hgnc_symbol)
self.assertIsNotNone(model.entrez_id)
self.assertEqual('3091', model.entrez_id)
self.assertEqual(1, len(model.interactions)) # all different evidences to hsa-miR-20a-5p
def test_target_by_entrez(self):
"""Test getting a target by Entrez Gene identifier."""
model = self.manager.query_target_by_entrez_id('3091')
self.check_hif1a(model)
def test_target_by_hgnc_id(self):
"""Test getting a target by Entrez Gene identifier."""
model = self.manager.query_target_by_hgnc_identifier('4910')
self.check_hif1a(model)
def test_target_by_hgnc_symbol(self):
"""Test getting a target by HGNC symbol."""
model = self.manager.query_target_by_hgnc_symbol(hif1a_symbol)
self.check_hif1a(model)
def help_enrich_hif1a(self, node: BaseAbundance):
"""Help check that different versions of HIF1A can be enriched properly.
:param pybel.dsl.BaseAbundance node: A PyBEL data dictionary
"""
self.assertIsInstance(node, BaseAbundance)
self.assertTrue(NAME in node or IDENTIFIER in node,
msg='Node missing information: {}'.format(node))
graph = BELGraph()
graph.add_node_from_data(node)
self.assertEqual(1, graph.number_of_nodes())
self.assertEqual(0, graph.number_of_edges())
self.manager.enrich_rnas(graph) # should enrich with the HIF1A - hsa-miR-20a-5p interaction
self.assertEqual(2, graph.number_of_nodes(), msg=f"""
Nodes:
{", ".join(map(str, graph))}
""")
self.assertEqual(3, graph.number_of_edges())
self.assertIn(mi2_data, graph)
self.assertTrue(graph.has_edge(mi2_data, node))
def test_enrich_hgnc_symbol(self):
"""Test enrichment of an HGNC gene symbol node."""
self.help_enrich_hif1a(hif1a_hgnc_name)
def test_enrich_hgnc_identifier(self):
"""Test enrichment of an HGNC identifier node."""
self.help_enrich_hif1a(hif1a_hgnc_identifier)
def test_enrich_entrez_name(self):
"""Test enrichment of an Entrez Gene node."""
self.help_enrich_hif1a(hif1a_entrez_name)
def test_enrich_entrez_id(self):
"""Test enrichment of an Entrez Gene node."""
self.help_enrich_hif1a(hif1a_entrez_identifier) | tests/test_build_db.py | from bio2bel_mirtarbase.manager import _build_entrez_map
from bio2bel_mirtarbase.models import Evidence, HGNC, MIRBASE, Mirna, NCBIGENE, Species, Target
from pybel import BELGraph
from pybel.constants import FUNCTION, IDENTIFIER, NAME, NAMESPACE
from pybel.dsl import BaseAbundance, mirna, rna
from tests.constants import TemporaryFilledCacheMixin
hif1a_symbol = 'HIF1A'
hif1a_hgnc_name = rna(name=hif1a_symbol, namespace=HGNC)
hif1a_hgnc_identifier = rna(identifier='4910', namespace=HGNC)
hif1a_entrez_name = rna(name='3091', namespace=NCBIGENE)
hif1a_entrez_identifier = rna(identifier='3091', namespace=NCBIGENE)
mi2_data = mirna(name='hsa-miR-20a-5p', namespace=MIRBASE)
mi5_data = mirna(name='mmu-miR-124-3p', namespace=MIRBASE)
class TestBuildDatabase(TemporaryFilledCacheMixin):
"""Test the database."""
def test_count_human_genes(self):
"""Test the number of genes in Bio2BEL HGNC."""
self.assertEqual(2, self.hgnc_manager.count_human_genes())
def test_count_mirnas(self):
"""Test the number of miRNAs."""
self.assertEqual(5, self.manager.count_mirnas())
def test_count_targets(self):
"""Test the number of targets."""
self.assertEqual(6, self.manager.count_targets())
def test_count_interactions(self):
"""Test the number of interactions."""
self.assertEqual(6, self.manager.count_interactions())
def test_count_evidences(self):
"""Test the number of evidences."""
self.assertEqual(10, self.manager.count_evidences())
def test_count_species(self):
"""Test the number of species."""
self.assertEqual(3, self.manager.session.query(Species).count())
def test_count_hgnc(self):
"""Test the number of human genes."""
self.assertEqual(2, len(self.hgnc_manager.hgnc()))
def test_get_cxcr4_by_entrez(self):
"""Test getting cxcr4 by its Entrez gene identifier."""
models = self.hgnc_manager.hgnc(entrez='7852')
self.assertEqual(1, len(models))
model = models[0]
self.assertIsNotNone(model)
self.assertEqual('CXCR4', model.symbol)
self.assertEqual('7852', model.entrez)
def test_get_hif1a_by_entrez(self):
"""Test getting hif1a by its Entrez gene identifier."""
models = self.hgnc_manager.hgnc(entrez='3091')
self.assertEqual(1, len(models))
model = models[0]
self.assertIsNotNone(model)
self.assertEqual('HIF1A', model.symbol)
self.assertEqual('3091', model.entrez)
def test_build_map(self):
"""Test building an Entrez map."""
emap = _build_entrez_map(self.hgnc_manager)
self.assertEqual(2, len(emap))
self.assertIn('7852', emap)
self.assertIn('3091', emap)
def test_evidence(self):
"""Test the populate function of the database manager."""
ev2 = self.manager.session.query(Evidence).filter(Evidence.reference == '18619591').first()
self.assertIsNotNone(ev2)
self.assertEqual("Luciferase reporter assay//qRT-PCR//Western blot//Reporter assay;Microarray", ev2.experiment)
def check_mir5(self, model: Mirna):
"""Help check the model has the right information for mmu-miR-124-3p."""
self.assertIsNotNone(model)
self.assertEqual("mmu-miR-124-3p", model.name)
self.assertTrue(any('MIRT000005' == interaction.mirtarbase_id for interaction in model.interactions))
bel_data = model.as_bel()
self.assertEqual(mi5_data.function, bel_data.function)
self.assertEqual(mi5_data.name, bel_data.name)
self.assertEqual(mi5_data.namespace, bel_data.namespace)
def test_mirna_by_mirtarbase_id(self):
"""Test getting an miRNA by a miRTarBase relationship identifier."""
mi5 = self.manager.query_mirna_by_mirtarbase_identifier('MIRT000005')
self.check_mir5(mi5)
def check_mir2(self, model: Mirna):
"""Help check the model has the right information for mmu-miR-124-3p."""
self.assertIsNotNone(model)
self.assertEqual("hsa-miR-20a-5p", model.name)
self.assertEqual(2, len(model.interactions))
self.assertTrue(any('MIRT000002' == interaction.mirtarbase_id for interaction in model.interactions))
bel_data = model.as_bel()
self.assertEqual(mi2_data[FUNCTION], bel_data[FUNCTION])
self.assertEqual(mi2_data[NAME], bel_data[NAME])
self.assertEqual(mi2_data[NAMESPACE], bel_data[NAMESPACE])
def test_mirna_2_by_mirtarbase_id(self):
"""Test getting an miRNA by a miRTarBase relationship identifier."""
mi2 = self.manager.query_mirna_by_mirtarbase_identifier('MIRT000002')
self.check_mir2(mi2)
def test_target(self):
"""Test getting a target by Entrez Gene identifier."""
target = self.manager.query_target_by_entrez_id('7852')
self.assertIsNotNone(target)
self.assertEqual("CXCR4", target.name)
self.assertIsNotNone(target.hgnc_id)
self.assertEqual("2561", target.hgnc_id)
def check_hif1a(self, model: Target):
"""Help check the model has all the right information for HIF1A.
:type model: Target
"""
self.assertIsNotNone(model)
self.assertEqual('HIF1A', model.name)
self.assertIsNotNone(model.hgnc_id)
self.assertEqual('4910', model.hgnc_id)
self.assertIsNotNone(model.hgnc_symbol)
self.assertEqual('HIF1A', model.hgnc_symbol)
self.assertIsNotNone(model.entrez_id)
self.assertEqual('3091', model.entrez_id)
self.assertEqual(1, len(model.interactions)) # all different evidences to hsa-miR-20a-5p
def test_target_by_entrez(self):
"""Test getting a target by Entrez Gene identifier."""
model = self.manager.query_target_by_entrez_id('3091')
self.check_hif1a(model)
def test_target_by_hgnc_id(self):
"""Test getting a target by Entrez Gene identifier."""
model = self.manager.query_target_by_hgnc_identifier('4910')
self.check_hif1a(model)
def test_target_by_hgnc_symbol(self):
"""Test getting a target by HGNC symbol."""
model = self.manager.query_target_by_hgnc_symbol(hif1a_symbol)
self.check_hif1a(model)
def help_enrich_hif1a(self, node: BaseAbundance):
"""Help check that different versions of HIF1A can be enriched properly.
:param pybel.dsl.BaseAbundance node: A PyBEL data dictionary
"""
self.assertIsInstance(node, BaseAbundance)
self.assertTrue(NAME in node or IDENTIFIER in node,
msg='Node missing information: {}'.format(node))
graph = BELGraph()
graph.add_node_from_data(node)
self.assertEqual(1, graph.number_of_nodes())
self.assertEqual(0, graph.number_of_edges())
self.manager.enrich_rnas(graph) # should enrich with the HIF1A - hsa-miR-20a-5p interaction
self.assertEqual(2, graph.number_of_nodes(), msg=f"""
Nodes:
{", ".join(map(str, graph))}
""")
self.assertEqual(3, graph.number_of_edges())
self.assertIn(mi2_data, graph)
self.assertTrue(graph.has_edge(mi2_data, node))
def test_enrich_hgnc_symbol(self):
"""Test enrichment of an HGNC gene symbol node."""
self.help_enrich_hif1a(hif1a_hgnc_name)
def test_enrich_hgnc_identifier(self):
"""Test enrichment of an HGNC identifier node."""
self.help_enrich_hif1a(hif1a_hgnc_identifier)
def test_enrich_entrez_name(self):
"""Test enrichment of an Entrez Gene node."""
self.help_enrich_hif1a(hif1a_entrez_name)
def test_enrich_entrez_id(self):
"""Test enrichment of an Entrez Gene node."""
self.help_enrich_hif1a(hif1a_entrez_identifier) | 0.724675 | 0.430866 |
class Word2Sequence:
UNK_TAG="<UNK>"
PAD_TAG = "<PAD>"
UNK = 0
PAD = 1
'''
1.初始化dict词典,加入初始字符,count词频统计
'''
def __init__(self):
self.dict={
self.UNK_TAG:self.UNK,
self.PAD_TAG:self.PAD
}
self.counter={}
'''
2.接收单个wordlist,统计进词频count
'''
def fit(self,word_list):
for word in word_list:
self.counter[word]=self.counter.get(word,0)+1
'''
3.根据词频,造词典:最小,最大词频,词个数
'''
def build_vocab(self,min_count=1,max_count=None,max_features=None):
'''
:param min_count: 入库的最小词频
:param max_count: 入库的最大词频
:param max_features: 整个词库的大小
:return:
'''
# 1.过滤counter
if min_count is not None:
self.counter={word:count for word,count in self.counter.items() if count>min_count}
if max_count is not None:
self.counter={word:count for word,count in self.counter.items() if count<max_count}
if max_features is not None:
self.counter=dict(sorted(self.counter.items(),reverse=True,key=lambda x:x[-1])[:max_features])
# 根据counter,建立词典
# 2.遍历counter,不断加入dict,key是word,value是索引,即dict的长度
for word in self.counter:
self.dict[word]=len(self.dict)
# 3.不仅创建dict,还要创建reverse_dict
self.reverse_dict=dict(zip(self.dict.values(),self.dict.keys()))
'''
4.接收文本,转数字序列:wordlist>sequence
'''
def transform(self,word_list,sequence_max=10):
# 1.规定序列长度,短了补,长了切
word_list_len=len(word_list)
if word_list_len>sequence_max:
word_list=word_list[:sequence_max]
if word_list_len<sequence_max:
#填充数组
word_list=word_list+[self.PAD_TAG]*(sequence_max-len(word_list))
# print(word_list)
# 最后转成数字列表
return [self.dict.get(word,self.UNK) for word in word_list]
'''
5.接收数字序列,转文本
'''
def inverse_transform(self,sequence_list):
# 1.接收索引列表,调用self.reverse_dict转成真实文本word_list
word_list=[self.reverse_dict.get(index,self.UNK_TAG) for index in sequence_list]
return word_list
def __len__(self):
return len(self.dict) | src/search/sort/word_to_sequence.py |
class Word2Sequence:
UNK_TAG="<UNK>"
PAD_TAG = "<PAD>"
UNK = 0
PAD = 1
'''
1.初始化dict词典,加入初始字符,count词频统计
'''
def __init__(self):
self.dict={
self.UNK_TAG:self.UNK,
self.PAD_TAG:self.PAD
}
self.counter={}
'''
2.接收单个wordlist,统计进词频count
'''
def fit(self,word_list):
for word in word_list:
self.counter[word]=self.counter.get(word,0)+1
'''
3.根据词频,造词典:最小,最大词频,词个数
'''
def build_vocab(self,min_count=1,max_count=None,max_features=None):
'''
:param min_count: 入库的最小词频
:param max_count: 入库的最大词频
:param max_features: 整个词库的大小
:return:
'''
# 1.过滤counter
if min_count is not None:
self.counter={word:count for word,count in self.counter.items() if count>min_count}
if max_count is not None:
self.counter={word:count for word,count in self.counter.items() if count<max_count}
if max_features is not None:
self.counter=dict(sorted(self.counter.items(),reverse=True,key=lambda x:x[-1])[:max_features])
# 根据counter,建立词典
# 2.遍历counter,不断加入dict,key是word,value是索引,即dict的长度
for word in self.counter:
self.dict[word]=len(self.dict)
# 3.不仅创建dict,还要创建reverse_dict
self.reverse_dict=dict(zip(self.dict.values(),self.dict.keys()))
'''
4.接收文本,转数字序列:wordlist>sequence
'''
def transform(self,word_list,sequence_max=10):
# 1.规定序列长度,短了补,长了切
word_list_len=len(word_list)
if word_list_len>sequence_max:
word_list=word_list[:sequence_max]
if word_list_len<sequence_max:
#填充数组
word_list=word_list+[self.PAD_TAG]*(sequence_max-len(word_list))
# print(word_list)
# 最后转成数字列表
return [self.dict.get(word,self.UNK) for word in word_list]
'''
5.接收数字序列,转文本
'''
def inverse_transform(self,sequence_list):
# 1.接收索引列表,调用self.reverse_dict转成真实文本word_list
word_list=[self.reverse_dict.get(index,self.UNK_TAG) for index in sequence_list]
return word_list
def __len__(self):
return len(self.dict) | 0.182826 | 0.403449 |
from abc import abstractmethod
from collections import OrderedDict
from django.utils.translation import ugettext
from datawinners.search.index_utils import es_unique_id_code_field_name, es_questionnaire_field_name
from datawinners.search.submission_index_constants import SubmissionIndexConstants
from datawinners.utils import translate
from mangrove.form_model.form_model import header_fields
class SubmissionHeader():
def __init__(self, form_model, language='en'):
self.form_model = form_model
self.language = language
def get_header_dict(self):
header_dict = OrderedDict()
header_dict.update(self.update_static_header_info())
def key_attribute(field):
return field.code
entity_questions = self.form_model.entity_questions
entity_question_dict = dict((field.code, field) for field in entity_questions)
headers = header_fields(self.form_model, key_attribute)
for field_code, val in headers.items():
key = es_questionnaire_field_name(field_code, self.form_model.id)
if field_code in entity_question_dict.keys():
self.add_unique_id_field(entity_question_dict.get(field_code), header_dict)
else:
header_dict.update({key: val})
return header_dict
def add_unique_id_field(self, unique_id_field, header_dict):
unique_id_question_code = unique_id_field.code
subject_title = unique_id_field.unique_id_type
unique_id_field_name = es_questionnaire_field_name(unique_id_question_code, self.form_model.id)
header_dict.update({unique_id_field_name: unique_id_field.label})
header_dict.update({es_unique_id_code_field_name(unique_id_field_name): "%s ID" % subject_title})
def get_header_field_names(self):
return self.get_header_dict().keys()
def get_header_field_dict(self):
return self.get_header_dict()
@abstractmethod
def update_static_header_info(self):
pass
class SubmissionAnalysisHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
return header_dict
class AllSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({"date_updated": translate("Updated Date", self.language, ugettext)})
header_dict.update({"status": translate("Status", self.language, ugettext)})
return header_dict
class SuccessSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
return header_dict
class ErroredSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({"error_msg": translate("Error Message", self.language, ugettext)})
return header_dict
class HeaderFactory():
def __init__(self, form_model, language='en'):
self.header_to_class_dict = {"all": AllSubmissionHeader, "deleted": AllSubmissionHeader,
"analysis": SubmissionAnalysisHeader,
"success": SuccessSubmissionHeader, "error": ErroredSubmissionHeader}
self.form_model = form_model
self.language = language
def create_header(self, submission_type):
header_class = self.header_to_class_dict.get(submission_type)
return header_class(self.form_model, self.language) | datawinners/search/submission_headers.py | from abc import abstractmethod
from collections import OrderedDict
from django.utils.translation import ugettext
from datawinners.search.index_utils import es_unique_id_code_field_name, es_questionnaire_field_name
from datawinners.search.submission_index_constants import SubmissionIndexConstants
from datawinners.utils import translate
from mangrove.form_model.form_model import header_fields
class SubmissionHeader():
def __init__(self, form_model, language='en'):
self.form_model = form_model
self.language = language
def get_header_dict(self):
header_dict = OrderedDict()
header_dict.update(self.update_static_header_info())
def key_attribute(field):
return field.code
entity_questions = self.form_model.entity_questions
entity_question_dict = dict((field.code, field) for field in entity_questions)
headers = header_fields(self.form_model, key_attribute)
for field_code, val in headers.items():
key = es_questionnaire_field_name(field_code, self.form_model.id)
if field_code in entity_question_dict.keys():
self.add_unique_id_field(entity_question_dict.get(field_code), header_dict)
else:
header_dict.update({key: val})
return header_dict
def add_unique_id_field(self, unique_id_field, header_dict):
unique_id_question_code = unique_id_field.code
subject_title = unique_id_field.unique_id_type
unique_id_field_name = es_questionnaire_field_name(unique_id_question_code, self.form_model.id)
header_dict.update({unique_id_field_name: unique_id_field.label})
header_dict.update({es_unique_id_code_field_name(unique_id_field_name): "%s ID" % subject_title})
def get_header_field_names(self):
return self.get_header_dict().keys()
def get_header_field_dict(self):
return self.get_header_dict()
@abstractmethod
def update_static_header_info(self):
pass
class SubmissionAnalysisHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
return header_dict
class AllSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({"date_updated": translate("Updated Date", self.language, ugettext)})
header_dict.update({"status": translate("Status", self.language, ugettext)})
return header_dict
class SuccessSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
return header_dict
class ErroredSubmissionHeader(SubmissionHeader):
def update_static_header_info(self):
header_dict = OrderedDict()
header_dict.update({SubmissionIndexConstants.DATASENDER_ID_KEY: translate("Datasender Id", self.language, ugettext)})
header_dict.update({SubmissionIndexConstants.DATASENDER_NAME_KEY: translate("Data Sender", self.language, ugettext)})
header_dict.update({"date": translate("Submission Date", self.language, ugettext)})
header_dict.update({"error_msg": translate("Error Message", self.language, ugettext)})
return header_dict
class HeaderFactory():
def __init__(self, form_model, language='en'):
self.header_to_class_dict = {"all": AllSubmissionHeader, "deleted": AllSubmissionHeader,
"analysis": SubmissionAnalysisHeader,
"success": SuccessSubmissionHeader, "error": ErroredSubmissionHeader}
self.form_model = form_model
self.language = language
def create_header(self, submission_type):
header_class = self.header_to_class_dict.get(submission_type)
return header_class(self.form_model, self.language) | 0.633637 | 0.131424 |
__all__ = ['test_endpoints', 'construct_method_to_params_dict', 'construct_request_type_filter',
'check_request_type_filter', 'determine_request_type_from_fields', 'determine_method_request_types',
'construct_method_to_params_map', 'construct_method_info_dict']
# Cell
from tqdm import tqdm
from warnings import warn
from functools import reduce
from . import rawgen, specgen, raw, utils
# Cell
def test_endpoints(
default_kwargs: dict
):
methods_to_test = [func for func in dir(raw) if 'get_' in func]
stream_to_df = dict()
for method_to_test in tqdm(methods_to_test):
method_func = getattr(raw, method_to_test)
func_kwargs = dict(zip(method_func.__code__.co_varnames, method_func.__defaults__))
for kwarg, value in default_kwargs.items():
if kwarg in func_kwargs.keys():
func_kwargs.update({kwarg: value})
r = method_func(**func_kwargs)
df = utils.parse_xml_response(r)
stream_to_df[method_to_test.split('_')[1]] = df
streams_without_content = []
for stream, df in stream_to_df.items():
if df.size == 0:
streams_without_content += [stream]
return streams_without_content
if len(streams_without_content) > 0:
warn(f"The following data streams returned no content data: {', '.join(streams_without_content)}")
return stream_to_df
# Cell
def construct_method_to_params_dict(API_yaml):
method_to_params = reduce(lambda k, v: {**k, **v}, [
{
f'{k}_{rawgen.clean_path_name(stream)}': {
parameter['name']: rawgen.extract_parameter_example(parameter)
for parameter
in v['parameters']
}
for k, v
in method.items()
if k in ['get', 'post']
}
for stream, method
in API_yaml['paths'].items()
])
return method_to_params
# Cell
def construct_request_type_filter(
has_start_time: bool,
has_end_time: bool,
has_start_date: bool,
has_end_date: bool,
has_date: bool,
has_SP: bool,
has_year: bool,
has_month: bool,
has_week: bool
):
request_type_filter = {
'year': (has_year + has_month + has_week == 1) and (has_year == 1),
'month': (has_year + has_month == 1) and (has_month == 1),
'week': (has_year + has_week == 1) and (has_week == 1),
'year_and_month': has_year + has_month == 2,
'year_and_week': has_year + has_week == 2,
'SP_and_date': has_SP + has_date == 2,
'date_range': has_start_time + has_end_time + has_start_date + has_end_date == 2,
'date_time_range': has_start_time + has_end_time + has_start_date + has_end_date == 4,
'non_temporal': has_start_time + has_end_time + has_start_date + has_end_date + has_SP + has_date + has_year + has_month == 0,
}
return request_type_filter
def check_request_type_filter(
field_names: list,
request_type_filter: dict,
has_start_time: bool,
has_end_time: bool,
has_start_date: bool,
has_end_date: bool,
has_date: bool,
has_SP: bool,
has_year: bool,
has_month: bool,
has_week: bool
):
"""
Checks the validity of the specified stream parameters
The following conditions will raise an error:
* has month without a year
* has only one of start/end time
* has only one of start/end date
* has only one settlement period or date
* filter does not contain only one request type
"""
filter_str = f'\n\nFilter:\n{request_type_filter}\n\nField Names:\n{", ".join(field_names)}'
assert {(False, True): True, (False, False): False, (True, True): False, (True, False): False}[(has_year, has_month)] == False, 'Cannot provide a month without a year' + filter_str
assert {(False, True): True, (False, False): False, (True, True): False, (True, False): False}[(has_year, has_week)] == False, 'Cannot provide a week without a year' + filter_str
assert has_start_time + has_end_time != 1, 'Only one of start/end time was provided' + filter_str
assert has_start_date + has_end_date != 1, 'Only one of start/end date was provided' + filter_str
assert (has_SP + has_date != 1) or (has_start_date + has_end_date == 2), 'Only one of date/SP was provided' + filter_str
assert sum(request_type_filter.values()) == 1, 'Request type could not be determined\n\nFilter' + filter_str
return
def determine_request_type_from_fields(
field_names: list,
start_time_cols: list=['StartTime'],
end_time_cols: list=['EndTime'],
start_date_cols: list=['StartDate', 'FromSettlementDate', 'FromDate'],
end_date_cols: list=['EndDate', 'ToSettlementDate', 'ToDate'],
date_cols: list=['SettlementDate', 'ImplementationDate', 'DecommissioningDate', 'Date', 'startTimeOfHalfHrPeriod'],
SP_cols: list=['SettlementPeriod', 'Period', 'settlementPeriod'],
year_cols: list=['Year'],
month_cols: list=['Month', 'MonthName'],
week_cols: list=['Week']
):
has_start_time = bool(set(field_names).intersection(set(start_time_cols)))
has_end_time = bool(set(field_names).intersection(set(end_time_cols)))
has_start_date = bool(set(field_names).intersection(set(start_date_cols)))
has_end_date = bool(set(field_names).intersection(set(end_date_cols)))
has_date = bool(set(field_names).intersection(set(date_cols)))
has_SP = bool(set(field_names).intersection(set(SP_cols)))
has_year = bool(set(field_names).intersection(set(year_cols)))
has_month = bool(set(field_names).intersection(set(month_cols)))
has_week = bool(set(field_names).intersection(set(week_cols)))
request_type_filter = construct_request_type_filter(
has_start_time, has_end_time, has_start_date,
has_end_date, has_date, has_SP, has_year, has_month, has_week
)
check_request_type_filter(
field_names, request_type_filter, has_start_time, has_end_time, has_start_date,
has_end_date, has_date, has_SP, has_year, has_month, has_week
)
request_type = [k for k, v in request_type_filter.items() if v==True][0]
return request_type
# Cell
def determine_method_request_types(method_to_params):
method_to_request_type = dict()
for method in method_to_params.keys():
field_names = list(method_to_params[method].keys())
method_to_request_type[method] = determine_request_type_from_fields(field_names)
return method_to_request_type
# Cell
def construct_method_to_params_map(method_to_params):
standardised_params_map = {
'start_time': ['StartTime'],
'end_time': ['EndTime'],
'start_date': ['StartDate', 'FromSettlementDate', 'FromDate'],
'end_date': ['EndDate', 'ToSettlementDate', 'ToDate'],
'date': ['SettlementDate', 'ImplementationDate', 'DecommissioningDate', 'Date', 'startTimeOfHalfHrPeriod'],
'SP': ['SettlementPeriod', 'Period', 'settlementPeriod'],
'year': ['Year'],
'month': ['Month', 'MonthName'],
'week': ['Week']
}
method_to_params_map = dict()
for method, params in method_to_params.items():
method_to_params_map[method] = dict()
for param in params.keys():
for standardised_param, bmrs_params in standardised_params_map.items():
if param in bmrs_params:
method_to_params_map[method][standardised_param] = param
return method_to_params_map
# Cell
def construct_method_info_dict(API_yaml_fp: str):
API_yaml = specgen.load_API_yaml(API_yaml_fp)
method_to_params = construct_method_to_params_dict(API_yaml)
method_to_request_type = determine_method_request_types(method_to_params)
method_to_params_map = construct_method_to_params_map(method_to_params)
method_info = dict()
for method, params in method_to_params.items():
method_info[method] = dict()
method_info[method]['request_type'] = method_to_request_type[method]
method_info[method]['kwargs_map'] = method_to_params_map[method]
method_info[method]['func_kwargs'] = {
(
{v: k for k, v in method_to_params_map[method].items()}[k]
if k in method_to_params_map[method].values()
else k
): v
for k, v
in method_to_params[method].items()
}
return method_info | ElexonDataPortal/dev/clientprep.py |
__all__ = ['test_endpoints', 'construct_method_to_params_dict', 'construct_request_type_filter',
'check_request_type_filter', 'determine_request_type_from_fields', 'determine_method_request_types',
'construct_method_to_params_map', 'construct_method_info_dict']
# Cell
from tqdm import tqdm
from warnings import warn
from functools import reduce
from . import rawgen, specgen, raw, utils
# Cell
def test_endpoints(
default_kwargs: dict
):
methods_to_test = [func for func in dir(raw) if 'get_' in func]
stream_to_df = dict()
for method_to_test in tqdm(methods_to_test):
method_func = getattr(raw, method_to_test)
func_kwargs = dict(zip(method_func.__code__.co_varnames, method_func.__defaults__))
for kwarg, value in default_kwargs.items():
if kwarg in func_kwargs.keys():
func_kwargs.update({kwarg: value})
r = method_func(**func_kwargs)
df = utils.parse_xml_response(r)
stream_to_df[method_to_test.split('_')[1]] = df
streams_without_content = []
for stream, df in stream_to_df.items():
if df.size == 0:
streams_without_content += [stream]
return streams_without_content
if len(streams_without_content) > 0:
warn(f"The following data streams returned no content data: {', '.join(streams_without_content)}")
return stream_to_df
# Cell
def construct_method_to_params_dict(API_yaml):
method_to_params = reduce(lambda k, v: {**k, **v}, [
{
f'{k}_{rawgen.clean_path_name(stream)}': {
parameter['name']: rawgen.extract_parameter_example(parameter)
for parameter
in v['parameters']
}
for k, v
in method.items()
if k in ['get', 'post']
}
for stream, method
in API_yaml['paths'].items()
])
return method_to_params
# Cell
def construct_request_type_filter(
has_start_time: bool,
has_end_time: bool,
has_start_date: bool,
has_end_date: bool,
has_date: bool,
has_SP: bool,
has_year: bool,
has_month: bool,
has_week: bool
):
request_type_filter = {
'year': (has_year + has_month + has_week == 1) and (has_year == 1),
'month': (has_year + has_month == 1) and (has_month == 1),
'week': (has_year + has_week == 1) and (has_week == 1),
'year_and_month': has_year + has_month == 2,
'year_and_week': has_year + has_week == 2,
'SP_and_date': has_SP + has_date == 2,
'date_range': has_start_time + has_end_time + has_start_date + has_end_date == 2,
'date_time_range': has_start_time + has_end_time + has_start_date + has_end_date == 4,
'non_temporal': has_start_time + has_end_time + has_start_date + has_end_date + has_SP + has_date + has_year + has_month == 0,
}
return request_type_filter
def check_request_type_filter(
field_names: list,
request_type_filter: dict,
has_start_time: bool,
has_end_time: bool,
has_start_date: bool,
has_end_date: bool,
has_date: bool,
has_SP: bool,
has_year: bool,
has_month: bool,
has_week: bool
):
"""
Checks the validity of the specified stream parameters
The following conditions will raise an error:
* has month without a year
* has only one of start/end time
* has only one of start/end date
* has only one settlement period or date
* filter does not contain only one request type
"""
filter_str = f'\n\nFilter:\n{request_type_filter}\n\nField Names:\n{", ".join(field_names)}'
assert {(False, True): True, (False, False): False, (True, True): False, (True, False): False}[(has_year, has_month)] == False, 'Cannot provide a month without a year' + filter_str
assert {(False, True): True, (False, False): False, (True, True): False, (True, False): False}[(has_year, has_week)] == False, 'Cannot provide a week without a year' + filter_str
assert has_start_time + has_end_time != 1, 'Only one of start/end time was provided' + filter_str
assert has_start_date + has_end_date != 1, 'Only one of start/end date was provided' + filter_str
assert (has_SP + has_date != 1) or (has_start_date + has_end_date == 2), 'Only one of date/SP was provided' + filter_str
assert sum(request_type_filter.values()) == 1, 'Request type could not be determined\n\nFilter' + filter_str
return
def determine_request_type_from_fields(
field_names: list,
start_time_cols: list=['StartTime'],
end_time_cols: list=['EndTime'],
start_date_cols: list=['StartDate', 'FromSettlementDate', 'FromDate'],
end_date_cols: list=['EndDate', 'ToSettlementDate', 'ToDate'],
date_cols: list=['SettlementDate', 'ImplementationDate', 'DecommissioningDate', 'Date', 'startTimeOfHalfHrPeriod'],
SP_cols: list=['SettlementPeriod', 'Period', 'settlementPeriod'],
year_cols: list=['Year'],
month_cols: list=['Month', 'MonthName'],
week_cols: list=['Week']
):
has_start_time = bool(set(field_names).intersection(set(start_time_cols)))
has_end_time = bool(set(field_names).intersection(set(end_time_cols)))
has_start_date = bool(set(field_names).intersection(set(start_date_cols)))
has_end_date = bool(set(field_names).intersection(set(end_date_cols)))
has_date = bool(set(field_names).intersection(set(date_cols)))
has_SP = bool(set(field_names).intersection(set(SP_cols)))
has_year = bool(set(field_names).intersection(set(year_cols)))
has_month = bool(set(field_names).intersection(set(month_cols)))
has_week = bool(set(field_names).intersection(set(week_cols)))
request_type_filter = construct_request_type_filter(
has_start_time, has_end_time, has_start_date,
has_end_date, has_date, has_SP, has_year, has_month, has_week
)
check_request_type_filter(
field_names, request_type_filter, has_start_time, has_end_time, has_start_date,
has_end_date, has_date, has_SP, has_year, has_month, has_week
)
request_type = [k for k, v in request_type_filter.items() if v==True][0]
return request_type
# Cell
def determine_method_request_types(method_to_params):
method_to_request_type = dict()
for method in method_to_params.keys():
field_names = list(method_to_params[method].keys())
method_to_request_type[method] = determine_request_type_from_fields(field_names)
return method_to_request_type
# Cell
def construct_method_to_params_map(method_to_params):
standardised_params_map = {
'start_time': ['StartTime'],
'end_time': ['EndTime'],
'start_date': ['StartDate', 'FromSettlementDate', 'FromDate'],
'end_date': ['EndDate', 'ToSettlementDate', 'ToDate'],
'date': ['SettlementDate', 'ImplementationDate', 'DecommissioningDate', 'Date', 'startTimeOfHalfHrPeriod'],
'SP': ['SettlementPeriod', 'Period', 'settlementPeriod'],
'year': ['Year'],
'month': ['Month', 'MonthName'],
'week': ['Week']
}
method_to_params_map = dict()
for method, params in method_to_params.items():
method_to_params_map[method] = dict()
for param in params.keys():
for standardised_param, bmrs_params in standardised_params_map.items():
if param in bmrs_params:
method_to_params_map[method][standardised_param] = param
return method_to_params_map
# Cell
def construct_method_info_dict(API_yaml_fp: str):
API_yaml = specgen.load_API_yaml(API_yaml_fp)
method_to_params = construct_method_to_params_dict(API_yaml)
method_to_request_type = determine_method_request_types(method_to_params)
method_to_params_map = construct_method_to_params_map(method_to_params)
method_info = dict()
for method, params in method_to_params.items():
method_info[method] = dict()
method_info[method]['request_type'] = method_to_request_type[method]
method_info[method]['kwargs_map'] = method_to_params_map[method]
method_info[method]['func_kwargs'] = {
(
{v: k for k, v in method_to_params_map[method].items()}[k]
if k in method_to_params_map[method].values()
else k
): v
for k, v
in method_to_params[method].items()
}
return method_info | 0.684475 | 0.428413 |
from unittest import TestCase
import httpretty
from click.testing import CliRunner
from arcsecond import cli
from arcsecond.api.error import ArcsecondError
from arcsecond.config import config_file_clear_section
from tests.utils import make_successful_login, mock_http_get, mock_http_post
class DatasetsInOrganisationsTestCase(TestCase):
def setUp(self):
config_file_clear_section('test')
httpretty.enable()
def tearDown(self):
httpretty.disable()
def test_datasets_list_unlogged(self):
"""As a simple user, I must not be able to access the list of datasets of an organisation."""
runner = CliRunner()
make_successful_login(runner)
result = runner.invoke(cli.datasets, ['--organisation', 'saao', '--debug', '--test'])
assert result.exit_code != 0 and isinstance(result.exception, ArcsecondError)
def test_organisation_GET_datasets_list_logged_but_wrong_organisation(self):
"""No matter role I have, accessing an unknown organisation must fail."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'superadmin')
result = runner.invoke(cli.datasets, ['--organisation', 'dummy', '--debug', '--test'])
assert result.exit_code != 0 and isinstance(result.exception, ArcsecondError)
def test_organisation_GET_datasets_list_valid_role(self):
"""As a SAAO member, I must be able to access the list of datasets."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'member')
mock_http_get('/saao/datasets/', '[]')
result = runner.invoke(cli.datasets, ['--organisation', 'saao', '--debug', '--test'])
assert result.exit_code == 0 and not result.exception
def test_organisation_POST_datasets_list_valid_member_role(self):
"""As a SAAO superadmin, I must be able to create a dataset."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'member')
mock_http_post('/saao/datasets/', '[]')
result = runner.invoke(cli.datasets, ['create', '--organisation', 'saao', '--debug', '--test'])
assert result.exit_code == 0 and not result.exception | tests/cli/test_datasets_organisations.py | from unittest import TestCase
import httpretty
from click.testing import CliRunner
from arcsecond import cli
from arcsecond.api.error import ArcsecondError
from arcsecond.config import config_file_clear_section
from tests.utils import make_successful_login, mock_http_get, mock_http_post
class DatasetsInOrganisationsTestCase(TestCase):
def setUp(self):
config_file_clear_section('test')
httpretty.enable()
def tearDown(self):
httpretty.disable()
def test_datasets_list_unlogged(self):
"""As a simple user, I must not be able to access the list of datasets of an organisation."""
runner = CliRunner()
make_successful_login(runner)
result = runner.invoke(cli.datasets, ['--organisation', 'saao', '--debug', '--test'])
assert result.exit_code != 0 and isinstance(result.exception, ArcsecondError)
def test_organisation_GET_datasets_list_logged_but_wrong_organisation(self):
"""No matter role I have, accessing an unknown organisation must fail."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'superadmin')
result = runner.invoke(cli.datasets, ['--organisation', 'dummy', '--debug', '--test'])
assert result.exit_code != 0 and isinstance(result.exception, ArcsecondError)
def test_organisation_GET_datasets_list_valid_role(self):
"""As a SAAO member, I must be able to access the list of datasets."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'member')
mock_http_get('/saao/datasets/', '[]')
result = runner.invoke(cli.datasets, ['--organisation', 'saao', '--debug', '--test'])
assert result.exit_code == 0 and not result.exception
def test_organisation_POST_datasets_list_valid_member_role(self):
"""As a SAAO superadmin, I must be able to create a dataset."""
runner = CliRunner()
make_successful_login(runner, 'saao', 'member')
mock_http_post('/saao/datasets/', '[]')
result = runner.invoke(cli.datasets, ['create', '--organisation', 'saao', '--debug', '--test'])
assert result.exit_code == 0 and not result.exception | 0.612773 | 0.414425 |
import os
import qrcode
from telegram.ext import Updater, CommandHandler, ConversationHandler, MessageHandler, Filters
from telegram import ChatAction
# Una variable para que el Bot se quede esperando el texto del QR
INPUT_TEXT = 0
def start(update, context):
update.message.reply_text('Bienvenido a el Bot de Prueba, que desea hacer hoy?\n\n'
'Usa /qr para generar un codigo QR')
# Despues de el start, le hace este comando, para el inicio del Bot
#aqui define una variable
def qr_command_handler(update,context):
update.message.reply_text('Enviame un texto para hacer el codigo QR')
return INPUT_TEXT
def generate_qr(text):
filename = text + '.jpg'
img = qrcode.make(text)
img.save(filename)
return filename
def send_qr(filename, chat):
chat.send_action(
action=ChatAction.UPLOAD_PHOTO,
timeout=None
)
chat.send_photo(
photo=open(filename, 'rb')
)
os.unlink(filename)
def input_text(update, context):
text = update.message.text
print(text)
#funcion que genera el codigo QR
filename = generate_qr(text)
chat = update.message.chat
print(chat)
print(filename)
#funcion que envio el codigo QR el usuario.
send_qr(filename, chat)
return ConversationHandler.END
if __name__ == '__main__':
# Aqui se defiene el Toiken que Genera el FatherBot, para el Bot
# con un /revoque, puede hacer otro token.
updater = Updater(token='<KEY>', use_context=True)
dp = updater.dispatcher
# Con esto inicia el Bot, para que puede iniciar
dp.add_handler(CommandHandler('start', start))
#incia la concersacion con el la persona el Bot
dp.add_handler(ConversationHandler(
entry_points=[
CommandHandler('qr',qr_command_handler)
],
# Es en los momentos que el Bot esta esperando los estados de la coversacion
states={
INPUT_TEXT: [MessageHandler(Filters.text, input_text)]
},
fallbacks=[]
))
updater.start_polling()
updater.idle() | bot.py | import os
import qrcode
from telegram.ext import Updater, CommandHandler, ConversationHandler, MessageHandler, Filters
from telegram import ChatAction
# Una variable para que el Bot se quede esperando el texto del QR
INPUT_TEXT = 0
def start(update, context):
update.message.reply_text('Bienvenido a el Bot de Prueba, que desea hacer hoy?\n\n'
'Usa /qr para generar un codigo QR')
# Despues de el start, le hace este comando, para el inicio del Bot
#aqui define una variable
def qr_command_handler(update,context):
update.message.reply_text('Enviame un texto para hacer el codigo QR')
return INPUT_TEXT
def generate_qr(text):
filename = text + '.jpg'
img = qrcode.make(text)
img.save(filename)
return filename
def send_qr(filename, chat):
chat.send_action(
action=ChatAction.UPLOAD_PHOTO,
timeout=None
)
chat.send_photo(
photo=open(filename, 'rb')
)
os.unlink(filename)
def input_text(update, context):
text = update.message.text
print(text)
#funcion que genera el codigo QR
filename = generate_qr(text)
chat = update.message.chat
print(chat)
print(filename)
#funcion que envio el codigo QR el usuario.
send_qr(filename, chat)
return ConversationHandler.END
if __name__ == '__main__':
# Aqui se defiene el Toiken que Genera el FatherBot, para el Bot
# con un /revoque, puede hacer otro token.
updater = Updater(token='<KEY>', use_context=True)
dp = updater.dispatcher
# Con esto inicia el Bot, para que puede iniciar
dp.add_handler(CommandHandler('start', start))
#incia la concersacion con el la persona el Bot
dp.add_handler(ConversationHandler(
entry_points=[
CommandHandler('qr',qr_command_handler)
],
# Es en los momentos que el Bot esta esperando los estados de la coversacion
states={
INPUT_TEXT: [MessageHandler(Filters.text, input_text)]
},
fallbacks=[]
))
updater.start_polling()
updater.idle() | 0.332852 | 0.090173 |
import kernel
from kernel.Interfaces.IStoreManager import IStoreManager
import jsonpickle
import os
import numpy as np
class JsonStoreManager(IStoreManager):
def __init__(self):
"""
Constructor that initializes entity
"""
super().__init__()
self.refresh()
def refresh(self):
"""
Reloads file with new information, in particular recreates the user collection and all info associated.
"""
root = kernel.get_connection_string()
path_to_user = os.path.join(root, "users.json")
try:
f = open(path_to_user, "r")
json = f.read()
frozen = jsonpickle.decode(json)
self.__users__ = frozen.__users__
except Exception as e:
print("Initial users file not found")
finally:
if 'f' in locals() and f is not None:
f.close()
@staticmethod
def version():
return 1.0
def get_user(self, user_id):
try:
for user_to_search in self.get_users():
if user_to_search.get_id() == int(user_id):
return user_to_search
except Exception as e:
return None
return None
def get_users(self):
return self.__users__
def add_user(self, user):
max_id = 0
if len(self.__users__) > 0:
max_id = max(self.__users__, key=lambda t: t.get_id()).get_id()
user.set_id(max_id + 1)
self.__users__.append(user)
def remove_user(self, user):
self.__users__.remove(user)
def update_user(self, user):
for i, user_to_update in enumerate(self.get_users()):
if user_to_update.get_id() == user.get_id():
self.__users__[i] = user
def get_user_folders(self, user_id):
"""
Get the user folder and creates them if necessary.
:param user_id: User id related to these folders.
:return: 3 folders, the user folder, the command folder to store EEG information and the model folder.
"""
root = kernel.get_connection_string()
user = self.get_user(user_id)
path_to_user = os.path.join(root, str(user.get_id()) + "_" + str(user.get_name()))
os.makedirs(path_to_user, exist_ok=True)
path_to_command = os.path.join(path_to_user, "cmd")
os.makedirs(path_to_command, exist_ok=True)
path_to_model = os.path.join(path_to_user, "model")
os.makedirs(path_to_model, exist_ok=True)
return path_to_user, path_to_command, path_to_model
def save_command(self, user_id, command):
"""
Saves command in command folder.
:param user_id: User id to find user folder.
:param command: Command folder to save.
"""
path_to_user, path_to_command, _ = self.get_user_folders(user_id)
path_data = os.path.join(path_to_command, str(command.get_id()))
np.savetxt(path_data, command.get_eeg())
def load_command(self, user_id, command):
"""
Loads a command using EEG saved file data.
:param user_id: User id to find user folder.
:param command: Command folder to save.
:return:
"""
_, path_to_command, _ = self.get_user_folders(user_id)
path_data = os.path.join(path_to_command, str(command.get_id()))
try:
data = np.loadtxt(path_data)
command.set_eeg(data)
except Exception as e:
print("No se ha podido cargar el archivo EEG")
return None
return command
def save(self):
"""
Saves all information in users.json file.
"""
try:
frozen = jsonpickle.encode(self)
root = kernel.get_connection_string()
path_to_user = os.path.join(root, "users.json")
f = open(path_to_user, "w+")
f.write(frozen)
f.close()
except Exception:
print("Error guardando datos")
def get_model_folder(self, user_id):
"""
Returns model folder.
:param user_id: User id to find user folder.
:return: Model folder.
"""
_, _, path_to_model = self.get_user_folders(user_id)
return path_to_model | backend/managers/JsonStoreManager.py | import kernel
from kernel.Interfaces.IStoreManager import IStoreManager
import jsonpickle
import os
import numpy as np
class JsonStoreManager(IStoreManager):
def __init__(self):
"""
Constructor that initializes entity
"""
super().__init__()
self.refresh()
def refresh(self):
"""
Reloads file with new information, in particular recreates the user collection and all info associated.
"""
root = kernel.get_connection_string()
path_to_user = os.path.join(root, "users.json")
try:
f = open(path_to_user, "r")
json = f.read()
frozen = jsonpickle.decode(json)
self.__users__ = frozen.__users__
except Exception as e:
print("Initial users file not found")
finally:
if 'f' in locals() and f is not None:
f.close()
@staticmethod
def version():
return 1.0
def get_user(self, user_id):
try:
for user_to_search in self.get_users():
if user_to_search.get_id() == int(user_id):
return user_to_search
except Exception as e:
return None
return None
def get_users(self):
return self.__users__
def add_user(self, user):
max_id = 0
if len(self.__users__) > 0:
max_id = max(self.__users__, key=lambda t: t.get_id()).get_id()
user.set_id(max_id + 1)
self.__users__.append(user)
def remove_user(self, user):
self.__users__.remove(user)
def update_user(self, user):
for i, user_to_update in enumerate(self.get_users()):
if user_to_update.get_id() == user.get_id():
self.__users__[i] = user
def get_user_folders(self, user_id):
"""
Get the user folder and creates them if necessary.
:param user_id: User id related to these folders.
:return: 3 folders, the user folder, the command folder to store EEG information and the model folder.
"""
root = kernel.get_connection_string()
user = self.get_user(user_id)
path_to_user = os.path.join(root, str(user.get_id()) + "_" + str(user.get_name()))
os.makedirs(path_to_user, exist_ok=True)
path_to_command = os.path.join(path_to_user, "cmd")
os.makedirs(path_to_command, exist_ok=True)
path_to_model = os.path.join(path_to_user, "model")
os.makedirs(path_to_model, exist_ok=True)
return path_to_user, path_to_command, path_to_model
def save_command(self, user_id, command):
"""
Saves command in command folder.
:param user_id: User id to find user folder.
:param command: Command folder to save.
"""
path_to_user, path_to_command, _ = self.get_user_folders(user_id)
path_data = os.path.join(path_to_command, str(command.get_id()))
np.savetxt(path_data, command.get_eeg())
def load_command(self, user_id, command):
"""
Loads a command using EEG saved file data.
:param user_id: User id to find user folder.
:param command: Command folder to save.
:return:
"""
_, path_to_command, _ = self.get_user_folders(user_id)
path_data = os.path.join(path_to_command, str(command.get_id()))
try:
data = np.loadtxt(path_data)
command.set_eeg(data)
except Exception as e:
print("No se ha podido cargar el archivo EEG")
return None
return command
def save(self):
"""
Saves all information in users.json file.
"""
try:
frozen = jsonpickle.encode(self)
root = kernel.get_connection_string()
path_to_user = os.path.join(root, "users.json")
f = open(path_to_user, "w+")
f.write(frozen)
f.close()
except Exception:
print("Error guardando datos")
def get_model_folder(self, user_id):
"""
Returns model folder.
:param user_id: User id to find user folder.
:return: Model folder.
"""
_, _, path_to_model = self.get_user_folders(user_id)
return path_to_model | 0.387922 | 0.097864 |
from optparse import OptionParser
from struct import *
import sys
import os.path
import time
import binascii
MAGIC = 0x27051956
IMG_NAME_LENGTH = 32
archs = {'invalid':0, 'alpha':1, 'arm':2, 'x86':3, 'ia64':4, 'm68k':12,
'microblaze':14, 'mips':5, 'mips64':6, 'nios':13, 'nios2':15,
'powerpc':7, 'ppc':7, 's390':8, 'sh':9, 'sparc':10,
'sparc64':11, 'blackfin':16, 'arv32':17, 'st200':18 }
oss = {'invalid':0, 'openbsd':1, 'netbsd':2, 'freebsd':3, '4_4bsd':4,
'linux':5, 'svr4':6, 'esix':7, 'solaris':8, 'irix':9,
'sco':10, 'dell':11, 'ncr':12, 'lynos':13, 'vxworks':14,
'psos':15, 'qnx':16, 'u-boot':17, 'rtems':18, 'artos':19,
'unity':20, 'integrity':21 }
types = {'invalid':0, 'standalone':1, 'kernel':2, 'ramdisk':3, 'multi':4,
'firmware':5,'script':6, 'filesystem':7, 'flat_dt':8 }
comps = {'none':0, 'bzip2':2, 'gzip':1, 'lzma':3 }
usage = "usage: %prog [options] image"
parser = OptionParser(usage=usage)
parser.add_option("-A","--arch", dest="arch", default="powerpc",
help="set architecture to 'arch'", metavar="ARCH")
parser.add_option("-O","--os", dest="os", default="linux",
help="set operating system to 'os'", metavar="OS")
parser.add_option("-T","--type", dest="type", default="kernel",
help="set image type to 'type'", metavar="TYPE")
parser.add_option("-C","--comp", dest="comp", default="gzip",
help="set compression type 'comp'", metavar="COMP")
parser.add_option("-a","--addr", dest="addr", default="0",
help="set load address to 'addr' (hex)", metavar="ADDR")
parser.add_option("-e","--ep", dest="ep", default="0",
help="set entry point to 'ep' (hex)", metavar="EP")
parser.add_option("-n","--name", dest="name", default="",
help="set image name to 'name'", metavar="NAME")
parser.add_option("-d","--datafile", dest="datafile",
help="use image data from 'datafile'", metavar="DATAFILE")
parser.add_option("-x","--xip", action="store_true", dest="xip", default=False,
help="set XIP (execute in place)")
(options, args) = parser.parse_args()
if len(args) != 1: parser.print_help()
if options.arch not in archs:
print "Invalid architecture specified, aborting"
sys.exit(2)
if options.os not in oss:
print "Invalid operating system specified, aborting"
sys.exit(2)
if options.comp not in comps:
print "Invalid compression specified, aborting"
sys.exit(2)
if options.type not in types:
print "Invalid image type specified, aborting"
sys.exit(2)
try:
inputsize = os.path.getsize(options.datafile)
inputfile = open(options.datafile, 'rb')
except IOError:
print "Invalid datafile specified, aborting"
sys.exit(2)
try:
outputfile = open(args[0],'wb')
except IOError:
print "Error opening output file for writing, aborting"
sys.exit(1)
struct = Struct("!IIIIIIIBBBB"+str(IMG_NAME_LENGTH)+"s")
outputfile.seek(struct.size);
inputcrc = 0;
while True:
inputblock = inputfile.read(4096)
if not inputblock: break
inputcrc = binascii.crc32(inputblock, inputcrc)
outputfile.write(inputblock)
inputcrc = inputcrc & 0xffffffff
structdata = struct.pack(MAGIC, 0, int(time.time()), inputsize,
int(options.addr,16), int(options.ep,16), inputcrc,
oss[options.os], archs[options.arch], types[options.type],
comps[options.comp], options.name)
headercrc = binascii.crc32(structdata) & 0xFFFFFFFF
structdata = struct.pack(MAGIC, headercrc, int(time.time()), inputsize,
int(options.addr,16), int(options.ep,16), inputcrc,
oss[options.os], archs[options.arch], types[options.type],
comps[options.comp], options.name)
outputfile.seek(0)
outputfile.write(structdata)
outputfile.close()
inputfile.close() | mkimage.py |
from optparse import OptionParser
from struct import *
import sys
import os.path
import time
import binascii
MAGIC = 0x27051956
IMG_NAME_LENGTH = 32
archs = {'invalid':0, 'alpha':1, 'arm':2, 'x86':3, 'ia64':4, 'm68k':12,
'microblaze':14, 'mips':5, 'mips64':6, 'nios':13, 'nios2':15,
'powerpc':7, 'ppc':7, 's390':8, 'sh':9, 'sparc':10,
'sparc64':11, 'blackfin':16, 'arv32':17, 'st200':18 }
oss = {'invalid':0, 'openbsd':1, 'netbsd':2, 'freebsd':3, '4_4bsd':4,
'linux':5, 'svr4':6, 'esix':7, 'solaris':8, 'irix':9,
'sco':10, 'dell':11, 'ncr':12, 'lynos':13, 'vxworks':14,
'psos':15, 'qnx':16, 'u-boot':17, 'rtems':18, 'artos':19,
'unity':20, 'integrity':21 }
types = {'invalid':0, 'standalone':1, 'kernel':2, 'ramdisk':3, 'multi':4,
'firmware':5,'script':6, 'filesystem':7, 'flat_dt':8 }
comps = {'none':0, 'bzip2':2, 'gzip':1, 'lzma':3 }
usage = "usage: %prog [options] image"
parser = OptionParser(usage=usage)
parser.add_option("-A","--arch", dest="arch", default="powerpc",
help="set architecture to 'arch'", metavar="ARCH")
parser.add_option("-O","--os", dest="os", default="linux",
help="set operating system to 'os'", metavar="OS")
parser.add_option("-T","--type", dest="type", default="kernel",
help="set image type to 'type'", metavar="TYPE")
parser.add_option("-C","--comp", dest="comp", default="gzip",
help="set compression type 'comp'", metavar="COMP")
parser.add_option("-a","--addr", dest="addr", default="0",
help="set load address to 'addr' (hex)", metavar="ADDR")
parser.add_option("-e","--ep", dest="ep", default="0",
help="set entry point to 'ep' (hex)", metavar="EP")
parser.add_option("-n","--name", dest="name", default="",
help="set image name to 'name'", metavar="NAME")
parser.add_option("-d","--datafile", dest="datafile",
help="use image data from 'datafile'", metavar="DATAFILE")
parser.add_option("-x","--xip", action="store_true", dest="xip", default=False,
help="set XIP (execute in place)")
(options, args) = parser.parse_args()
if len(args) != 1: parser.print_help()
if options.arch not in archs:
print "Invalid architecture specified, aborting"
sys.exit(2)
if options.os not in oss:
print "Invalid operating system specified, aborting"
sys.exit(2)
if options.comp not in comps:
print "Invalid compression specified, aborting"
sys.exit(2)
if options.type not in types:
print "Invalid image type specified, aborting"
sys.exit(2)
try:
inputsize = os.path.getsize(options.datafile)
inputfile = open(options.datafile, 'rb')
except IOError:
print "Invalid datafile specified, aborting"
sys.exit(2)
try:
outputfile = open(args[0],'wb')
except IOError:
print "Error opening output file for writing, aborting"
sys.exit(1)
struct = Struct("!IIIIIIIBBBB"+str(IMG_NAME_LENGTH)+"s")
outputfile.seek(struct.size);
inputcrc = 0;
while True:
inputblock = inputfile.read(4096)
if not inputblock: break
inputcrc = binascii.crc32(inputblock, inputcrc)
outputfile.write(inputblock)
inputcrc = inputcrc & 0xffffffff
structdata = struct.pack(MAGIC, 0, int(time.time()), inputsize,
int(options.addr,16), int(options.ep,16), inputcrc,
oss[options.os], archs[options.arch], types[options.type],
comps[options.comp], options.name)
headercrc = binascii.crc32(structdata) & 0xFFFFFFFF
structdata = struct.pack(MAGIC, headercrc, int(time.time()), inputsize,
int(options.addr,16), int(options.ep,16), inputcrc,
oss[options.os], archs[options.arch], types[options.type],
comps[options.comp], options.name)
outputfile.seek(0)
outputfile.write(structdata)
outputfile.close()
inputfile.close() | 0.214527 | 0.094803 |
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Menu',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=50, verbose_name='name')),
],
options={
'verbose_name': 'menu',
'verbose_name_plural': 'menus',
},
),
migrations.CreateModel(
name='MenuItem',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('caption', models.CharField(max_length=50, verbose_name='caption')),
('url', models.CharField(blank=True, max_length=200, verbose_name='URL')),
('named_url', models.CharField(blank=True, max_length=200, verbose_name='named URL')),
('level', models.IntegerField(default=0, editable=False, verbose_name='level')),
('rank', models.IntegerField(default=0, editable=False, verbose_name='rank')),
('menu', models.ForeignKey(blank=True, editable=False, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='contained_items', to='treemenus.Menu', verbose_name='menu')),
('parent', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='treemenus.MenuItem', verbose_name='parent')),
],
),
migrations.AddField(
model_name='menu',
name='root_item',
field=models.ForeignKey(blank=True, editable=False, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='is_root_item_of', to='treemenus.MenuItem', verbose_name='root item'),
),
] | treemenus/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Menu',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=50, verbose_name='name')),
],
options={
'verbose_name': 'menu',
'verbose_name_plural': 'menus',
},
),
migrations.CreateModel(
name='MenuItem',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('caption', models.CharField(max_length=50, verbose_name='caption')),
('url', models.CharField(blank=True, max_length=200, verbose_name='URL')),
('named_url', models.CharField(blank=True, max_length=200, verbose_name='named URL')),
('level', models.IntegerField(default=0, editable=False, verbose_name='level')),
('rank', models.IntegerField(default=0, editable=False, verbose_name='rank')),
('menu', models.ForeignKey(blank=True, editable=False, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='contained_items', to='treemenus.Menu', verbose_name='menu')),
('parent', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='treemenus.MenuItem', verbose_name='parent')),
],
),
migrations.AddField(
model_name='menu',
name='root_item',
field=models.ForeignKey(blank=True, editable=False, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='is_root_item_of', to='treemenus.MenuItem', verbose_name='root item'),
),
] | 0.568655 | 0.114715 |
import contextlib
import pathlib
import tempfile
import typing
from foodx_devops_tools.pipeline_config import load_template_context
@contextlib.contextmanager
def context_files(
content: typing.Dict[str, typing.Dict[str, str]]
) -> typing.Generator[typing.List[pathlib.Path], None, None]:
dir_paths = set()
file_paths = set()
with tempfile.TemporaryDirectory() as base_path:
for this_dir, file_data in content.items():
dir_path = pathlib.Path(base_path) / this_dir
dir_path.mkdir(parents=True)
dir_paths.add(dir_path)
for file_name, file_content in file_data.items():
this_file = dir_path / file_name
with this_file.open("w") as f:
f.write(file_content)
file_paths.add(this_file)
yield dir_paths, file_paths
def test_load_files():
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1: s1k1v
s1k2: s1k2v
s2:
s2k1: s2k1v
""",
"f2": """---
context:
s3:
s3k1: s3k1v
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert len(result.context) == 3
assert result.context == {
"s1": {
"s1k1": "s1k1v",
"s1k2": "s1k2v",
},
"s2": {"s2k1": "s2k1v"},
"s3": {"s3k1": "s3k1v"},
}
def test_load_dirs():
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1: s1k1v
s1k2: s1k2v
s2:
s2k1: s2k1v
""",
"f2": """---
context:
s3:
s3k1: s3k1v
""",
},
"b": {
"f1": """---
context:
s1:
s1k3: s1k3v
s4:
s4k1: s4k1v
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert len(result.context) == 4
assert result.context == {
"s1": {
"s1k1": "s1k1v",
"s1k2": "s1k2v",
"s1k3": "s1k3v",
},
"s2": {"s2k1": "s2k1v"},
"s3": {"s3k1": "s3k1v"},
"s4": {"s4k1": "s4k1v"},
}
def test_deep_merge():
"""yaml object data should be merged across all levels in the data."""
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1:
s1k1kk1: v1
""",
"f2": """---
context:
s1:
s1k1:
s1k1kk2:
s1k1kkk1: v2
""",
},
"b": {
"f1": """---
context:
s1:
s1k1:
s1k1kk2:
s1k1kkk2: v3
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert result.context == {
"s1": {
"s1k1": {
"s1k1kk1": "v1",
"s1k1kk2": {
"s1k1kkk1": "v2",
"s1k1kkk2": "v3",
},
},
},
} | tests/ci/unit_tests/pipeline_config/test_template_context.py |
import contextlib
import pathlib
import tempfile
import typing
from foodx_devops_tools.pipeline_config import load_template_context
@contextlib.contextmanager
def context_files(
content: typing.Dict[str, typing.Dict[str, str]]
) -> typing.Generator[typing.List[pathlib.Path], None, None]:
dir_paths = set()
file_paths = set()
with tempfile.TemporaryDirectory() as base_path:
for this_dir, file_data in content.items():
dir_path = pathlib.Path(base_path) / this_dir
dir_path.mkdir(parents=True)
dir_paths.add(dir_path)
for file_name, file_content in file_data.items():
this_file = dir_path / file_name
with this_file.open("w") as f:
f.write(file_content)
file_paths.add(this_file)
yield dir_paths, file_paths
def test_load_files():
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1: s1k1v
s1k2: s1k2v
s2:
s2k1: s2k1v
""",
"f2": """---
context:
s3:
s3k1: s3k1v
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert len(result.context) == 3
assert result.context == {
"s1": {
"s1k1": "s1k1v",
"s1k2": "s1k2v",
},
"s2": {"s2k1": "s2k1v"},
"s3": {"s3k1": "s3k1v"},
}
def test_load_dirs():
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1: s1k1v
s1k2: s1k2v
s2:
s2k1: s2k1v
""",
"f2": """---
context:
s3:
s3k1: s3k1v
""",
},
"b": {
"f1": """---
context:
s1:
s1k3: s1k3v
s4:
s4k1: s4k1v
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert len(result.context) == 4
assert result.context == {
"s1": {
"s1k1": "s1k1v",
"s1k2": "s1k2v",
"s1k3": "s1k3v",
},
"s2": {"s2k1": "s2k1v"},
"s3": {"s3k1": "s3k1v"},
"s4": {"s4k1": "s4k1v"},
}
def test_deep_merge():
"""yaml object data should be merged across all levels in the data."""
file_text = {
"a": {
"f1": """---
context:
s1:
s1k1:
s1k1kk1: v1
""",
"f2": """---
context:
s1:
s1k1:
s1k1kk2:
s1k1kkk1: v2
""",
},
"b": {
"f1": """---
context:
s1:
s1k1:
s1k1kk2:
s1k1kkk2: v3
""",
},
}
with context_files(file_text) as (dir_paths, file_paths):
result = load_template_context(file_paths)
assert result.context == {
"s1": {
"s1k1": {
"s1k1kk1": "v1",
"s1k1kk2": {
"s1k1kkk1": "v2",
"s1k1kkk2": "v3",
},
},
},
} | 0.566258 | 0.294665 |
from typing import Optional, Union
from matchsticks.game_types import Move
from matchsticks.utils import generate_allowed
class Game(object):
def __init__(self, num_layers: int = 4) -> None:
"""
A game of matchsticks.
:param num_layers: The number of layers of (odd numbers of) matchsticks you want to start the game with.
"""
# Check for valid number of layers
if not 1 <= num_layers <= 8:
print("Please choose a number of layers between 1 and 8 inclusive")
raise ValueError
# Store the number of layers so we can reset the game later
self._num_layers = num_layers
# Create the starting layers
self._state = list(map(lambda x: int(x * 2 + 1), range(num_layers)))
# Generate allowed moves reference (to be used by get_allowed)
self._allowed_reference = generate_allowed(num_layers * 2 - 1)
# print("starting allowed are", self._allowed_reference)
def is_still_on(self) -> bool:
"""
Checks whether the game is still going or not
:return: Whether or not the game is still happening
"""
return not not self._state
def get_allowed(self) -> list[Move]:
"""
Generate the allowed moves for the given layers.
:return: A list of lists of allowed moves, in the format (layer, low_idx, high_idx), all 1-indexed
"""
allowed = []
for i, layer_n in enumerate(self._state):
together = list(map(lambda tup: (i + 1,) + tup, self._allowed_reference[layer_n - 1]))
allowed += together
return allowed
def get_state(self) -> tuple[int]:
"""
Getter method for game state.
:return: 3-tuple representing the game state.
"""
return tuple(self._state)
def is_allowed(self, move: Move) -> bool:
"""
Check if a given move is valid.
:param move: The move, written as a triple (layer_i, low_idx, high_idx).
:return: True for valid move, False otherwise.
"""
layer_i, low, high = move
# Make layer 0-indexed
layer_i -= 1
return (
0 <= layer_i < len(self._state)
and 1 <= low <= high <= self._state[layer_i]
)
def play_move(self, move: Move) -> bool:
"""
Play a move.
:param move: A tuple containing your move, in the format (layer_i, low_idx, high_idx), where:
- layer_i is the index of the layer you want to play on (1-indexed).
- low_idx is the index of the lowest matchstick to cross off (1-indexed).
- high_idx is the index of the highest matchstick to cross off (1-indexed.
:return: whether or not the game is still going
"""
if not self.is_allowed(move):
raise Exception(f"The move ({move}) is not a valid move.")
layer_i, low_idx, high_idx = move
# Make the layer 0-indexed
layer_i -= 1
# Perform move # TODO: make this use the same code as imagine_move (no code duplication ideally)
active_layer = self._state.pop(layer_i)
left_result = low_idx - 1
right_result = active_layer - high_idx
if left_result > 0:
self._state.append(left_result)
if right_result > 0:
self._state.append(right_result)
self._state.sort()
# Return False if the game is over,
# and True if the game is still going
return self.is_still_on()
def reset(self, position: Optional[Union[list[int], tuple[int]]] = None) -> None:
"""
Reset the game to the original configuration.
:return:
"""
if position:
self._state = list(position)
else:
self._state = list(map(lambda x: int(x * 2 + 1),
range(self._num_layers)))
def end(self) -> None: # TODO: make this work with clicking on the 'x'
"""
End the game prematurely.
:return:
"""
self._state = None | matchsticks/game.py | from typing import Optional, Union
from matchsticks.game_types import Move
from matchsticks.utils import generate_allowed
class Game(object):
def __init__(self, num_layers: int = 4) -> None:
"""
A game of matchsticks.
:param num_layers: The number of layers of (odd numbers of) matchsticks you want to start the game with.
"""
# Check for valid number of layers
if not 1 <= num_layers <= 8:
print("Please choose a number of layers between 1 and 8 inclusive")
raise ValueError
# Store the number of layers so we can reset the game later
self._num_layers = num_layers
# Create the starting layers
self._state = list(map(lambda x: int(x * 2 + 1), range(num_layers)))
# Generate allowed moves reference (to be used by get_allowed)
self._allowed_reference = generate_allowed(num_layers * 2 - 1)
# print("starting allowed are", self._allowed_reference)
def is_still_on(self) -> bool:
"""
Checks whether the game is still going or not
:return: Whether or not the game is still happening
"""
return not not self._state
def get_allowed(self) -> list[Move]:
"""
Generate the allowed moves for the given layers.
:return: A list of lists of allowed moves, in the format (layer, low_idx, high_idx), all 1-indexed
"""
allowed = []
for i, layer_n in enumerate(self._state):
together = list(map(lambda tup: (i + 1,) + tup, self._allowed_reference[layer_n - 1]))
allowed += together
return allowed
def get_state(self) -> tuple[int]:
"""
Getter method for game state.
:return: 3-tuple representing the game state.
"""
return tuple(self._state)
def is_allowed(self, move: Move) -> bool:
"""
Check if a given move is valid.
:param move: The move, written as a triple (layer_i, low_idx, high_idx).
:return: True for valid move, False otherwise.
"""
layer_i, low, high = move
# Make layer 0-indexed
layer_i -= 1
return (
0 <= layer_i < len(self._state)
and 1 <= low <= high <= self._state[layer_i]
)
def play_move(self, move: Move) -> bool:
"""
Play a move.
:param move: A tuple containing your move, in the format (layer_i, low_idx, high_idx), where:
- layer_i is the index of the layer you want to play on (1-indexed).
- low_idx is the index of the lowest matchstick to cross off (1-indexed).
- high_idx is the index of the highest matchstick to cross off (1-indexed.
:return: whether or not the game is still going
"""
if not self.is_allowed(move):
raise Exception(f"The move ({move}) is not a valid move.")
layer_i, low_idx, high_idx = move
# Make the layer 0-indexed
layer_i -= 1
# Perform move # TODO: make this use the same code as imagine_move (no code duplication ideally)
active_layer = self._state.pop(layer_i)
left_result = low_idx - 1
right_result = active_layer - high_idx
if left_result > 0:
self._state.append(left_result)
if right_result > 0:
self._state.append(right_result)
self._state.sort()
# Return False if the game is over,
# and True if the game is still going
return self.is_still_on()
def reset(self, position: Optional[Union[list[int], tuple[int]]] = None) -> None:
"""
Reset the game to the original configuration.
:return:
"""
if position:
self._state = list(position)
else:
self._state = list(map(lambda x: int(x * 2 + 1),
range(self._num_layers)))
def end(self) -> None: # TODO: make this work with clicking on the 'x'
"""
End the game prematurely.
:return:
"""
self._state = None | 0.837736 | 0.618723 |
import logging
import sys
import time
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.select import Select
import settings
import utils
logging.info("starting teetime booking application")
#calculate date / time values
dates = utils.days_to_dates(settings.DAYS)
min_seconds = utils.timestr_to_seconds(settings.INTERVAL[0])
max_seconds = utils.timestr_to_seconds(settings.INTERVAL[1])
if not dates:
logging.info('no dates to book found, exiting')
sys.exit()
from pyvirtualdisplay import Display
display = Display(visible=0, size=(800, 600))
display.start()
logging.info('initializing browser')
browser = webdriver.Firefox()
browser.get(settings.BASE_URL)
time.sleep(2)
browser.find_element_by_id("btnSignIn").click()
time.sleep(2)
logging.info('logging in')
username = browser.find_element_by_id("txtLogInName")
password = browser.find_element_by_id("txtPassword")
username.send_keys(settings.USERNAME)
time.sleep(1)
password.send_keys(settings.PASSWORD)
time.sleep(1)
browser.find_element_by_id("btnLogIn").click()
logging.info('logged in')
for date in dates:
found_slot = False
logging.info('searching tee times for %s' % date.strftime('%m/%d/%Y'))
browser.find_element_by_id("rdpSearchStartDate_popupButton").click()
time.sleep(1)
calendar = browser.find_element_by_id("rdpSearchStartDate_dateInput")
calendar.click()
calendar.clear()
time.sleep(1)
calendar.send_keys(date.strftime('%m/%d/%Y'))
calendar.send_keys(Keys.ENTER)
time.sleep(16) #wait for the ajax call to complete
logging.info('selecting number of players: %s' % settings.PLAYERS)
select = Select(browser.find_element_by_id("ddlSearchPlayers"))
select.select_by_visible_text(str(settings.PLAYERS))
time.sleep(16) #wait for the ajax call to complete
elements = []
try:
elements.extend(browser.find_elements_by_class_name("pnlReservationSearch_PreLoaded_Even"))
except:
pass
try:
elements.extend(browser.find_elements_by_class_name("pnlReservationSearch_PreLoaded_Odd"))
except:
pass
if not elements:
logging.warning('could not find any available tee times for %s' % date.strftime('%m/%d/%Y'))
continue
elements = utils.sort_elements(elements)
for element in elements:
tms = element.find_elements_by_class_name('PodLabel_TeeTime')[0]
text = tms.get_attribute('innerHTML')
logging.info('checking timeslot: %s' % text)
seconds = utils.timestr_to_seconds(text)
if min_seconds <= seconds <= max_seconds:
#book
found_slot = True
logging.info('found timeslot: %s, booking it' % text)
button_class = 'PodButton_Reserve%d' % settings.PLAYERS
element.find_elements_by_class_name(button_class)[0].click()
time.sleep(16)
#use this to confirm
browser.find_element_by_id('chkPolicyAgreement').click()
time.sleep(1)
browser.find_element_by_id('btn_process').click()
time.sleep(1)
browser.find_element_by_id('btnFinish').click()
logging.info('booked timeslot %s' % text) #TODO: lblConfirmationNumber
time.sleep(16)
#use this to cancel
#browser.find_element_by_id('btnCancelReservation').click()
break
if found_slot:
break
else:
logging.warning('could not find any matching timeslot for %s' % date.strftime('%m/%d/%Y'))
logging.info('closing browser')
browser.close()
time.sleep(1)
logging.info('exiting')
display.stop() | teetime.py | import logging
import sys
import time
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.select import Select
import settings
import utils
logging.info("starting teetime booking application")
#calculate date / time values
dates = utils.days_to_dates(settings.DAYS)
min_seconds = utils.timestr_to_seconds(settings.INTERVAL[0])
max_seconds = utils.timestr_to_seconds(settings.INTERVAL[1])
if not dates:
logging.info('no dates to book found, exiting')
sys.exit()
from pyvirtualdisplay import Display
display = Display(visible=0, size=(800, 600))
display.start()
logging.info('initializing browser')
browser = webdriver.Firefox()
browser.get(settings.BASE_URL)
time.sleep(2)
browser.find_element_by_id("btnSignIn").click()
time.sleep(2)
logging.info('logging in')
username = browser.find_element_by_id("txtLogInName")
password = browser.find_element_by_id("txtPassword")
username.send_keys(settings.USERNAME)
time.sleep(1)
password.send_keys(settings.PASSWORD)
time.sleep(1)
browser.find_element_by_id("btnLogIn").click()
logging.info('logged in')
for date in dates:
found_slot = False
logging.info('searching tee times for %s' % date.strftime('%m/%d/%Y'))
browser.find_element_by_id("rdpSearchStartDate_popupButton").click()
time.sleep(1)
calendar = browser.find_element_by_id("rdpSearchStartDate_dateInput")
calendar.click()
calendar.clear()
time.sleep(1)
calendar.send_keys(date.strftime('%m/%d/%Y'))
calendar.send_keys(Keys.ENTER)
time.sleep(16) #wait for the ajax call to complete
logging.info('selecting number of players: %s' % settings.PLAYERS)
select = Select(browser.find_element_by_id("ddlSearchPlayers"))
select.select_by_visible_text(str(settings.PLAYERS))
time.sleep(16) #wait for the ajax call to complete
elements = []
try:
elements.extend(browser.find_elements_by_class_name("pnlReservationSearch_PreLoaded_Even"))
except:
pass
try:
elements.extend(browser.find_elements_by_class_name("pnlReservationSearch_PreLoaded_Odd"))
except:
pass
if not elements:
logging.warning('could not find any available tee times for %s' % date.strftime('%m/%d/%Y'))
continue
elements = utils.sort_elements(elements)
for element in elements:
tms = element.find_elements_by_class_name('PodLabel_TeeTime')[0]
text = tms.get_attribute('innerHTML')
logging.info('checking timeslot: %s' % text)
seconds = utils.timestr_to_seconds(text)
if min_seconds <= seconds <= max_seconds:
#book
found_slot = True
logging.info('found timeslot: %s, booking it' % text)
button_class = 'PodButton_Reserve%d' % settings.PLAYERS
element.find_elements_by_class_name(button_class)[0].click()
time.sleep(16)
#use this to confirm
browser.find_element_by_id('chkPolicyAgreement').click()
time.sleep(1)
browser.find_element_by_id('btn_process').click()
time.sleep(1)
browser.find_element_by_id('btnFinish').click()
logging.info('booked timeslot %s' % text) #TODO: lblConfirmationNumber
time.sleep(16)
#use this to cancel
#browser.find_element_by_id('btnCancelReservation').click()
break
if found_slot:
break
else:
logging.warning('could not find any matching timeslot for %s' % date.strftime('%m/%d/%Y'))
logging.info('closing browser')
browser.close()
time.sleep(1)
logging.info('exiting')
display.stop() | 0.09268 | 0.055285 |
import logging
import numpy as np
import onnx
import os
import tempfile
import torch
import unittest
from fairseq import models
from pytorch_translate import rnn # noqa
from pytorch_translate.ensemble_export import (
DecoderBatchedStepEnsemble,
DecoderStepEnsemble,
EncoderEnsemble,
BeamSearch
)
from pytorch_translate.test import utils as test_utils
from caffe2.python.onnx import backend as caffe2_backend
logger = logging.getLogger(__name__)
class TestONNX(unittest.TestCase):
def _test_ensemble_encoder_export(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
tmp_dir = tempfile.mkdtemp()
encoder_pb_path = os.path.join(tmp_dir, 'encoder.pb')
encoder_ensemble.onnx_export(encoder_pb_path)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
with open(encoder_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_encoder = caffe2_backend.prepare(onnx_model)
caffe2_encoder_outputs = onnx_encoder.run(
(
src_tokens.numpy(),
src_lengths.numpy(),
),
)
for i in range(len(pytorch_encoder_outputs)):
caffe2_out_value = caffe2_encoder_outputs[i]
pytorch_out_value = pytorch_encoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
encoder_ensemble.save_to_db(
os.path.join(tmp_dir, 'encoder.predictor_export'),
)
def test_ensemble_encoder_export_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_ensemble_encoder_export(test_args)
def test_ensemble_encoder_export_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_ensemble_encoder_export(test_args)
def _test_ensemble_encoder_object_export(self, encoder_ensemble):
tmp_dir = tempfile.mkdtemp()
encoder_pb_path = os.path.join(tmp_dir, 'encoder.pb')
encoder_ensemble.onnx_export(encoder_pb_path)
src_dict = encoder_ensemble.models[0].src_dict
token_list = [src_dict.unk()] * 4 + [src_dict.eos()]
src_tokens = torch.LongTensor(
np.array(token_list, dtype='int64').reshape(-1, 1),
)
src_lengths = torch.IntTensor(
np.array([len(token_list)], dtype='int32'),
)
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
with open(encoder_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_encoder = caffe2_backend.prepare(onnx_model)
srclen = src_tokens.size(1)
beam_size = 1
src_tokens = src_tokens.repeat(1, beam_size).view(-1, srclen).numpy()
src_lengths = src_lengths.repeat(beam_size).numpy()
caffe2_encoder_outputs = onnx_encoder.run(
(
src_tokens,
src_lengths,
),
)
for i in range(len(pytorch_encoder_outputs)):
caffe2_out_value = caffe2_encoder_outputs[i]
pytorch_out_value = pytorch_encoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
encoder_ensemble.save_to_db(
os.path.join(tmp_dir, 'encoder.predictor_export'),
)
def _test_full_ensemble_export(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
decoder_step_ensemble = DecoderStepEnsemble(
model_list,
beam_size=5,
)
tmp_dir = tempfile.mkdtemp()
decoder_step_pb_path = os.path.join(tmp_dir, 'decoder_step.pb')
decoder_step_ensemble.onnx_export(
decoder_step_pb_path,
pytorch_encoder_outputs,
)
# single EOS
input_token = torch.LongTensor(
np.array([[model_list[0].dst_dict.eos()]]),
)
timestep = torch.LongTensor(np.array([[0]]))
pytorch_decoder_outputs = decoder_step_ensemble(
input_token,
timestep,
*pytorch_encoder_outputs
)
with open(decoder_step_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_decoder = caffe2_backend.prepare(onnx_model)
decoder_inputs_numpy = [input_token.numpy(), timestep.numpy()]
for tensor in pytorch_encoder_outputs:
decoder_inputs_numpy.append(tensor.detach().numpy())
caffe2_decoder_outputs = onnx_decoder.run(tuple(decoder_inputs_numpy))
for i in range(len(pytorch_decoder_outputs)):
caffe2_out_value = caffe2_decoder_outputs[i]
pytorch_out_value = pytorch_decoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
decoder_step_ensemble.save_to_db(
os.path.join(tmp_dir, 'decoder_step.predictor_export'),
pytorch_encoder_outputs,
)
def test_full_ensemble_export_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_full_ensemble_export(test_args)
def test_full_ensemble_export_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_full_ensemble_export(test_args)
def _test_batched_beam_decoder_step(self, test_args):
beam_size = 5
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
decoder_step_ensemble = DecoderBatchedStepEnsemble(
model_list,
beam_size=beam_size,
)
tmp_dir = tempfile.mkdtemp()
decoder_step_pb_path = os.path.join(tmp_dir, 'decoder_step.pb')
decoder_step_ensemble.onnx_export(
decoder_step_pb_path,
pytorch_encoder_outputs,
)
# single EOS in flat array
input_tokens = torch.LongTensor(
np.array([model_list[0].dst_dict.eos()]),
)
prev_scores = torch.FloatTensor(np.array([0.0]))
timestep = torch.LongTensor(np.array([0]))
pytorch_first_step_outputs = decoder_step_ensemble(
input_tokens,
prev_scores,
timestep,
*pytorch_encoder_outputs
)
# next step inputs (input_tokesn shape: [beam_size])
next_input_tokens = torch.LongTensor(
np.array([i for i in range(4, 9)]),
)
next_prev_scores = pytorch_first_step_outputs[1]
next_timestep = timestep + 1
next_states = list(pytorch_first_step_outputs[4:])
# Tile these for the next timestep
for i in range(len(model_list)):
next_states[i] = next_states[i].repeat(1, beam_size, 1)
pytorch_next_step_outputs = decoder_step_ensemble(
next_input_tokens,
next_prev_scores,
next_timestep,
*next_states
)
with open(decoder_step_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_decoder = caffe2_backend.prepare(onnx_model)
decoder_inputs_numpy = [
next_input_tokens.numpy(),
next_prev_scores.detach().numpy(),
next_timestep.detach().numpy(),
]
for tensor in next_states:
decoder_inputs_numpy.append(tensor.detach().numpy())
caffe2_next_step_outputs = onnx_decoder.run(
tuple(decoder_inputs_numpy),
)
for i in range(len(pytorch_next_step_outputs)):
caffe2_out_value = caffe2_next_step_outputs[i]
pytorch_out_value = pytorch_next_step_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
def test_batched_beam_decoder_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_batched_beam_decoder_step(test_args)
def test_batched_beam_decoder_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_batched_beam_decoder_step(test_args)
def _test_full_beam_decoder(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(
test_args, src_dict, tgt_dict))
bs = BeamSearch(model_list, src_tokens, src_lengths,
beam_size=6)
prev_token = torch.LongTensor([0])
prev_scores = torch.FloatTensor([0.0])
attn_weights = torch.zeros(11)
prev_hypos_indices = torch.zeros(6, dtype=torch.int64)
outs = bs(src_tokens, src_lengths, prev_token, prev_scores,
attn_weights, prev_hypos_indices, torch.LongTensor([20]))
import io
f = io.BytesIO()
torch.onnx._export(
bs,
(src_tokens, src_lengths, prev_token, prev_scores, attn_weights,
prev_hypos_indices, torch.LongTensor([20])),
f, export_params=True, verbose=False, example_outputs=outs)
torch.onnx._export_to_pretty_string(
bs,
(src_tokens, src_lengths, prev_token, prev_scores, attn_weights,
prev_hypos_indices, torch.LongTensor([20])),
f, export_params=True, verbose=False, example_outputs=outs)
f.seek(0)
import onnx
onnx_model = onnx.load(f)
c2_model = caffe2_backend.prepare(onnx_model)
c2_model.run((src_tokens.numpy(), src_lengths.numpy(),
prev_token.numpy(), prev_scores.numpy(),
attn_weights.numpy(), prev_hypos_indices.numpy(),
np.array([20])))
@unittest.skip('Probably needs updated PyTorch')
def test_full_beam_decoder(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_full_beam_decoder(test_args) | pytorch_translate/test/test_onnx.py |
import logging
import numpy as np
import onnx
import os
import tempfile
import torch
import unittest
from fairseq import models
from pytorch_translate import rnn # noqa
from pytorch_translate.ensemble_export import (
DecoderBatchedStepEnsemble,
DecoderStepEnsemble,
EncoderEnsemble,
BeamSearch
)
from pytorch_translate.test import utils as test_utils
from caffe2.python.onnx import backend as caffe2_backend
logger = logging.getLogger(__name__)
class TestONNX(unittest.TestCase):
def _test_ensemble_encoder_export(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
tmp_dir = tempfile.mkdtemp()
encoder_pb_path = os.path.join(tmp_dir, 'encoder.pb')
encoder_ensemble.onnx_export(encoder_pb_path)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
with open(encoder_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_encoder = caffe2_backend.prepare(onnx_model)
caffe2_encoder_outputs = onnx_encoder.run(
(
src_tokens.numpy(),
src_lengths.numpy(),
),
)
for i in range(len(pytorch_encoder_outputs)):
caffe2_out_value = caffe2_encoder_outputs[i]
pytorch_out_value = pytorch_encoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
encoder_ensemble.save_to_db(
os.path.join(tmp_dir, 'encoder.predictor_export'),
)
def test_ensemble_encoder_export_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_ensemble_encoder_export(test_args)
def test_ensemble_encoder_export_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_ensemble_encoder_export(test_args)
def _test_ensemble_encoder_object_export(self, encoder_ensemble):
tmp_dir = tempfile.mkdtemp()
encoder_pb_path = os.path.join(tmp_dir, 'encoder.pb')
encoder_ensemble.onnx_export(encoder_pb_path)
src_dict = encoder_ensemble.models[0].src_dict
token_list = [src_dict.unk()] * 4 + [src_dict.eos()]
src_tokens = torch.LongTensor(
np.array(token_list, dtype='int64').reshape(-1, 1),
)
src_lengths = torch.IntTensor(
np.array([len(token_list)], dtype='int32'),
)
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
with open(encoder_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_encoder = caffe2_backend.prepare(onnx_model)
srclen = src_tokens.size(1)
beam_size = 1
src_tokens = src_tokens.repeat(1, beam_size).view(-1, srclen).numpy()
src_lengths = src_lengths.repeat(beam_size).numpy()
caffe2_encoder_outputs = onnx_encoder.run(
(
src_tokens,
src_lengths,
),
)
for i in range(len(pytorch_encoder_outputs)):
caffe2_out_value = caffe2_encoder_outputs[i]
pytorch_out_value = pytorch_encoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
encoder_ensemble.save_to_db(
os.path.join(tmp_dir, 'encoder.predictor_export'),
)
def _test_full_ensemble_export(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
decoder_step_ensemble = DecoderStepEnsemble(
model_list,
beam_size=5,
)
tmp_dir = tempfile.mkdtemp()
decoder_step_pb_path = os.path.join(tmp_dir, 'decoder_step.pb')
decoder_step_ensemble.onnx_export(
decoder_step_pb_path,
pytorch_encoder_outputs,
)
# single EOS
input_token = torch.LongTensor(
np.array([[model_list[0].dst_dict.eos()]]),
)
timestep = torch.LongTensor(np.array([[0]]))
pytorch_decoder_outputs = decoder_step_ensemble(
input_token,
timestep,
*pytorch_encoder_outputs
)
with open(decoder_step_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_decoder = caffe2_backend.prepare(onnx_model)
decoder_inputs_numpy = [input_token.numpy(), timestep.numpy()]
for tensor in pytorch_encoder_outputs:
decoder_inputs_numpy.append(tensor.detach().numpy())
caffe2_decoder_outputs = onnx_decoder.run(tuple(decoder_inputs_numpy))
for i in range(len(pytorch_decoder_outputs)):
caffe2_out_value = caffe2_decoder_outputs[i]
pytorch_out_value = pytorch_decoder_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
decoder_step_ensemble.save_to_db(
os.path.join(tmp_dir, 'decoder_step.predictor_export'),
pytorch_encoder_outputs,
)
def test_full_ensemble_export_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_full_ensemble_export(test_args)
def test_full_ensemble_export_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_full_ensemble_export(test_args)
def _test_batched_beam_decoder_step(self, test_args):
beam_size = 5
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(test_args, src_dict, tgt_dict))
encoder_ensemble = EncoderEnsemble(model_list)
# test equivalence
# The discrepancy in types here is a temporary expedient.
# PyTorch indexing requires int64 while support for tracing
# pack_padded_sequence() requires int32.
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
pytorch_encoder_outputs = encoder_ensemble(src_tokens, src_lengths)
decoder_step_ensemble = DecoderBatchedStepEnsemble(
model_list,
beam_size=beam_size,
)
tmp_dir = tempfile.mkdtemp()
decoder_step_pb_path = os.path.join(tmp_dir, 'decoder_step.pb')
decoder_step_ensemble.onnx_export(
decoder_step_pb_path,
pytorch_encoder_outputs,
)
# single EOS in flat array
input_tokens = torch.LongTensor(
np.array([model_list[0].dst_dict.eos()]),
)
prev_scores = torch.FloatTensor(np.array([0.0]))
timestep = torch.LongTensor(np.array([0]))
pytorch_first_step_outputs = decoder_step_ensemble(
input_tokens,
prev_scores,
timestep,
*pytorch_encoder_outputs
)
# next step inputs (input_tokesn shape: [beam_size])
next_input_tokens = torch.LongTensor(
np.array([i for i in range(4, 9)]),
)
next_prev_scores = pytorch_first_step_outputs[1]
next_timestep = timestep + 1
next_states = list(pytorch_first_step_outputs[4:])
# Tile these for the next timestep
for i in range(len(model_list)):
next_states[i] = next_states[i].repeat(1, beam_size, 1)
pytorch_next_step_outputs = decoder_step_ensemble(
next_input_tokens,
next_prev_scores,
next_timestep,
*next_states
)
with open(decoder_step_pb_path, 'r+b') as f:
onnx_model = onnx.load(f)
onnx_decoder = caffe2_backend.prepare(onnx_model)
decoder_inputs_numpy = [
next_input_tokens.numpy(),
next_prev_scores.detach().numpy(),
next_timestep.detach().numpy(),
]
for tensor in next_states:
decoder_inputs_numpy.append(tensor.detach().numpy())
caffe2_next_step_outputs = onnx_decoder.run(
tuple(decoder_inputs_numpy),
)
for i in range(len(pytorch_next_step_outputs)):
caffe2_out_value = caffe2_next_step_outputs[i]
pytorch_out_value = pytorch_next_step_outputs[i].data.numpy()
np.testing.assert_allclose(
caffe2_out_value,
pytorch_out_value,
rtol=1e-4,
atol=1e-6,
)
def test_batched_beam_decoder_default(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_batched_beam_decoder_step(test_args)
def test_batched_beam_decoder_vocab_reduction(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
lexical_dictionaries = test_utils.create_lexical_dictionaries()
test_args.vocab_reduction_params = {
'lexical_dictionaries': lexical_dictionaries,
'num_top_words': 5,
'max_translation_candidates_per_word': 1,
}
self._test_batched_beam_decoder_step(test_args)
def _test_full_beam_decoder(self, test_args):
samples, src_dict, tgt_dict = test_utils.prepare_inputs(test_args)
sample = next(samples)
src_tokens = sample['net_input']['src_tokens'][0:1].t()
src_lengths = sample['net_input']['src_lengths'][0:1].int()
num_models = 3
model_list = []
for _ in range(num_models):
model_list.append(models.build_model(
test_args, src_dict, tgt_dict))
bs = BeamSearch(model_list, src_tokens, src_lengths,
beam_size=6)
prev_token = torch.LongTensor([0])
prev_scores = torch.FloatTensor([0.0])
attn_weights = torch.zeros(11)
prev_hypos_indices = torch.zeros(6, dtype=torch.int64)
outs = bs(src_tokens, src_lengths, prev_token, prev_scores,
attn_weights, prev_hypos_indices, torch.LongTensor([20]))
import io
f = io.BytesIO()
torch.onnx._export(
bs,
(src_tokens, src_lengths, prev_token, prev_scores, attn_weights,
prev_hypos_indices, torch.LongTensor([20])),
f, export_params=True, verbose=False, example_outputs=outs)
torch.onnx._export_to_pretty_string(
bs,
(src_tokens, src_lengths, prev_token, prev_scores, attn_weights,
prev_hypos_indices, torch.LongTensor([20])),
f, export_params=True, verbose=False, example_outputs=outs)
f.seek(0)
import onnx
onnx_model = onnx.load(f)
c2_model = caffe2_backend.prepare(onnx_model)
c2_model.run((src_tokens.numpy(), src_lengths.numpy(),
prev_token.numpy(), prev_scores.numpy(),
attn_weights.numpy(), prev_hypos_indices.numpy(),
np.array([20])))
@unittest.skip('Probably needs updated PyTorch')
def test_full_beam_decoder(self):
test_args = test_utils.ModelParamsDict(
encoder_bidirectional=True,
sequence_lstm=True,
)
self._test_full_beam_decoder(test_args) | 0.466359 | 0.390592 |
from __future__ import print_function
from amuse.units import units, nbody_system
from amuse.datamodel import Particle
from amuse.community.athena.interface import Athena
from amuse.community.hermite.interface import Hermite
from matplotlib import pyplot
def hydro_grid_in_potential_well(mass=1 | units.MSun, length=100 | units.AU):
converter = nbody_system.nbody_to_si(mass, length)
# calculate density in field based on solar wind
# gives a very low number
molar_mass_hydrogen_proton = 1 | units.g / units.mol
density_hydrogen_in_stellar_wind = 10 | 1 / units.cm**3
particles_per_mol = 6.022e23 | 1 / units.mol
density_hydrogen_in_stellar_wind_in_moles = (
density_hydrogen_in_stellar_wind
/ particles_per_mol
)
density_gas = 100 * (
density_hydrogen_in_stellar_wind_in_moles
* molar_mass_hydrogen_proton
).as_quantity_in(units.MSun / units.AU**3)
# override with higher number for plotting
density_gas = 1e-3 | units.MSun / units.AU**3
instance = Athena(converter)
instance.initialize_code()
instance.parameters.nx = 50
instance.parameters.ny = 50
instance.parameters.nz = 1
instance.parameters.length_x = length
instance.parameters.length_y = length
instance.parameters.length_z = length
instance.parameters.x_boundary_conditions = ("periodic", "periodic")
instance.parameters.y_boundary_conditions = ("periodic", "periodic")
instance.parameters.z_boundary_conditions = ("outflow", "outflow")
# instance.stopping_conditions.number_of_steps_detection.enable()
instance.set_has_external_gravitational_potential(1)
instance.commit_parameters()
grid_in_memory = instance.grid.copy()
grid_in_memory.rho = density_gas
pressure = 1 | units.Pa
grid_in_memory.energy = pressure / (instance.parameters.gamma - 1)
channel = grid_in_memory.new_channel_to(instance.grid)
channel.copy()
instance.initialize_grid()
particle = Particle(
mass=mass,
position=length * [0.5, 0.5, 0.5],
velocity=[0.0, 0.0, 0.0] | units.kms
)
gravity = Hermite(converter)
dx = (grid_in_memory.x[1][0][0] - grid_in_memory.x[0]
[0][0]).as_quantity_in(units.AU)
gravity.parameters.epsilon_squared = dx**2
gravity.particles.add_particle(particle)
potential = gravity.get_potential_at_point(
0 * instance.potential_grid.x.flatten(),
instance.potential_grid.x.flatten(),
instance.potential_grid.y.flatten(),
instance.potential_grid.z.flatten()
)
potential = potential.reshape(instance.potential_grid.x.shape)
instance.potential_grid.potential = potential
instance.evolve_model(100 | units.yr)
print(instance.get_timestep().value_in(units.yr))
value_to_plot = instance.grid.rho[:, :, 0].value_in(
units.MSun / units.AU**3)
# value_to_plot = potential[...,...,0].value_in(potential.unit)
plot_grid(value_to_plot)
def plot_grid(x):
figure = pyplot.figure(figsize=(6, 6))
plot = figure.add_subplot(1, 1, 1)
mappable = plot.imshow(x, origin='lower')
pyplot.colorbar(mappable)
# figure.savefig('orszag_tang.png')
pyplot.show()
if __name__ == '__main__':
hydro_grid_in_potential_well() | examples/simple/grid_potential.py | from __future__ import print_function
from amuse.units import units, nbody_system
from amuse.datamodel import Particle
from amuse.community.athena.interface import Athena
from amuse.community.hermite.interface import Hermite
from matplotlib import pyplot
def hydro_grid_in_potential_well(mass=1 | units.MSun, length=100 | units.AU):
converter = nbody_system.nbody_to_si(mass, length)
# calculate density in field based on solar wind
# gives a very low number
molar_mass_hydrogen_proton = 1 | units.g / units.mol
density_hydrogen_in_stellar_wind = 10 | 1 / units.cm**3
particles_per_mol = 6.022e23 | 1 / units.mol
density_hydrogen_in_stellar_wind_in_moles = (
density_hydrogen_in_stellar_wind
/ particles_per_mol
)
density_gas = 100 * (
density_hydrogen_in_stellar_wind_in_moles
* molar_mass_hydrogen_proton
).as_quantity_in(units.MSun / units.AU**3)
# override with higher number for plotting
density_gas = 1e-3 | units.MSun / units.AU**3
instance = Athena(converter)
instance.initialize_code()
instance.parameters.nx = 50
instance.parameters.ny = 50
instance.parameters.nz = 1
instance.parameters.length_x = length
instance.parameters.length_y = length
instance.parameters.length_z = length
instance.parameters.x_boundary_conditions = ("periodic", "periodic")
instance.parameters.y_boundary_conditions = ("periodic", "periodic")
instance.parameters.z_boundary_conditions = ("outflow", "outflow")
# instance.stopping_conditions.number_of_steps_detection.enable()
instance.set_has_external_gravitational_potential(1)
instance.commit_parameters()
grid_in_memory = instance.grid.copy()
grid_in_memory.rho = density_gas
pressure = 1 | units.Pa
grid_in_memory.energy = pressure / (instance.parameters.gamma - 1)
channel = grid_in_memory.new_channel_to(instance.grid)
channel.copy()
instance.initialize_grid()
particle = Particle(
mass=mass,
position=length * [0.5, 0.5, 0.5],
velocity=[0.0, 0.0, 0.0] | units.kms
)
gravity = Hermite(converter)
dx = (grid_in_memory.x[1][0][0] - grid_in_memory.x[0]
[0][0]).as_quantity_in(units.AU)
gravity.parameters.epsilon_squared = dx**2
gravity.particles.add_particle(particle)
potential = gravity.get_potential_at_point(
0 * instance.potential_grid.x.flatten(),
instance.potential_grid.x.flatten(),
instance.potential_grid.y.flatten(),
instance.potential_grid.z.flatten()
)
potential = potential.reshape(instance.potential_grid.x.shape)
instance.potential_grid.potential = potential
instance.evolve_model(100 | units.yr)
print(instance.get_timestep().value_in(units.yr))
value_to_plot = instance.grid.rho[:, :, 0].value_in(
units.MSun / units.AU**3)
# value_to_plot = potential[...,...,0].value_in(potential.unit)
plot_grid(value_to_plot)
def plot_grid(x):
figure = pyplot.figure(figsize=(6, 6))
plot = figure.add_subplot(1, 1, 1)
mappable = plot.imshow(x, origin='lower')
pyplot.colorbar(mappable)
# figure.savefig('orszag_tang.png')
pyplot.show()
if __name__ == '__main__':
hydro_grid_in_potential_well() | 0.861378 | 0.400867 |
from django.shortcuts import render
from django.shortcuts import render_to_response
from django.template import RequestContext
from django.http import HttpResponse
import googlemaps
from vets.models import VetSpot
gmaps = googlemaps.Client(key='AIzaSyA0tl-yTrvyi_9UESPKQ27Ny4L0ONoktj8')
def index(request):
return render_to_response('search_page.html', context_instance=RequestContext(request))
def search_by_place(request):
keyw= ""
loc = ""
if request.method == 'POST':
loc = request.POST.get('location', '')
keyw = request.POST.get('what', '')
if not loc:
return render_to_response('missing_location.html', context_instance=RequestContext(request))
geocode_result = gmaps.geocode(loc)
if not geocode_result:
return render_to_response('incorrect_location.html', context_instance=RequestContext(request))
lat = float(geocode_result[0]['geometry']['location']['lat'])
lon = float(geocode_result[0]['geometry']['location']['lng'])
if keyw :
search_result = gmaps.places( keyw, location=(lat,lon), types='veterinary_care', radius = 10000)
else:
search_result = gmaps.places( 'animal', location=(lat,lon), types='veterinary_care', radius = 10000)
out = display_map_with_result(request, search_result, loc)
return HttpResponse(out)
def locate_around_me(request, lat, lon):
lat = float(lat)
lon = float(lon)
search_result = gmaps.places('animal', location=(lat,lon), types='veterinary_care', radius = 10000)
reverse_geocode_result = gmaps.reverse_geocode((lat, lon))
loc = reverse_geocode_result[0]['formatted_address']
out = display_map_with_result(request, search_result, loc)
return HttpResponse(out)
def display_map_with_result(request, search_result, place):
vslist = []
for r in search_result['results']:
vs = VetSpot()
vs.name = str(r['name'])
vs.address = r['formatted_address']
vs.latitude = r['geometry']['location']['lat']
vs.longitude = r['geometry']['location']['lng']
vs.place_id = r['place_id']
if 'rating' in r.keys():
vs.rating = r['rating']
if 'opening_hours' in r.keys():
if str(r['opening_hours']['open_now']).lower == "true":
vs.opennow = True
vslist.append(vs)
return render(request, 'poi_list.html', {'pois': vslist, 'place': place})
def details(request, p_id):
detail_result = gmaps.place(p_id)
info = detail_result['result']
lat = info['geometry']['location']['lat']
lon = info['geometry']['location']['lng']
display_info = {}
display_info['Name'] = info['name']
display_info['Address'] = info['formatted_address']
if 'formatted_phone_number' in info.keys():
display_info['Phone'] = info['formatted_phone_number']
if 'international_phone_number' in info.keys():
display_info['International'] = info['international_phone_number']
if 'opening_hours' in info.keys():
display_info['Hours'] = info['opening_hours']
if 'permanently_closed' in info.keys():
display_info['permanently_closed'] = info['permanently_closed']
if 'photos' in info.keys():
display_info['photos'] = info['photos']
if 'price_level' in info.keys():
display_info['expense'] = info['price_level']
if 'rating' in info.keys():
display_info['rating'] = info['rating']
if 'reviews' in info.keys():
display_info['reviews'] = info['reviews']
if 'website' in info.keys():
display_info['website'] = info['website']
if 'vicinity' in info.keys():
display_info['vicinity'] = info['vicinity']
if 'url' in info.keys():
display_info['url'] = info['url']
return render(request, 'place_details.html', {'details': display_info, 'lat': lat, 'lon': lon, 'pid': p_id}) | petcare/vets/views.py | from django.shortcuts import render
from django.shortcuts import render_to_response
from django.template import RequestContext
from django.http import HttpResponse
import googlemaps
from vets.models import VetSpot
gmaps = googlemaps.Client(key='AIzaSyA0tl-yTrvyi_9UESPKQ27Ny4L0ONoktj8')
def index(request):
return render_to_response('search_page.html', context_instance=RequestContext(request))
def search_by_place(request):
keyw= ""
loc = ""
if request.method == 'POST':
loc = request.POST.get('location', '')
keyw = request.POST.get('what', '')
if not loc:
return render_to_response('missing_location.html', context_instance=RequestContext(request))
geocode_result = gmaps.geocode(loc)
if not geocode_result:
return render_to_response('incorrect_location.html', context_instance=RequestContext(request))
lat = float(geocode_result[0]['geometry']['location']['lat'])
lon = float(geocode_result[0]['geometry']['location']['lng'])
if keyw :
search_result = gmaps.places( keyw, location=(lat,lon), types='veterinary_care', radius = 10000)
else:
search_result = gmaps.places( 'animal', location=(lat,lon), types='veterinary_care', radius = 10000)
out = display_map_with_result(request, search_result, loc)
return HttpResponse(out)
def locate_around_me(request, lat, lon):
lat = float(lat)
lon = float(lon)
search_result = gmaps.places('animal', location=(lat,lon), types='veterinary_care', radius = 10000)
reverse_geocode_result = gmaps.reverse_geocode((lat, lon))
loc = reverse_geocode_result[0]['formatted_address']
out = display_map_with_result(request, search_result, loc)
return HttpResponse(out)
def display_map_with_result(request, search_result, place):
vslist = []
for r in search_result['results']:
vs = VetSpot()
vs.name = str(r['name'])
vs.address = r['formatted_address']
vs.latitude = r['geometry']['location']['lat']
vs.longitude = r['geometry']['location']['lng']
vs.place_id = r['place_id']
if 'rating' in r.keys():
vs.rating = r['rating']
if 'opening_hours' in r.keys():
if str(r['opening_hours']['open_now']).lower == "true":
vs.opennow = True
vslist.append(vs)
return render(request, 'poi_list.html', {'pois': vslist, 'place': place})
def details(request, p_id):
detail_result = gmaps.place(p_id)
info = detail_result['result']
lat = info['geometry']['location']['lat']
lon = info['geometry']['location']['lng']
display_info = {}
display_info['Name'] = info['name']
display_info['Address'] = info['formatted_address']
if 'formatted_phone_number' in info.keys():
display_info['Phone'] = info['formatted_phone_number']
if 'international_phone_number' in info.keys():
display_info['International'] = info['international_phone_number']
if 'opening_hours' in info.keys():
display_info['Hours'] = info['opening_hours']
if 'permanently_closed' in info.keys():
display_info['permanently_closed'] = info['permanently_closed']
if 'photos' in info.keys():
display_info['photos'] = info['photos']
if 'price_level' in info.keys():
display_info['expense'] = info['price_level']
if 'rating' in info.keys():
display_info['rating'] = info['rating']
if 'reviews' in info.keys():
display_info['reviews'] = info['reviews']
if 'website' in info.keys():
display_info['website'] = info['website']
if 'vicinity' in info.keys():
display_info['vicinity'] = info['vicinity']
if 'url' in info.keys():
display_info['url'] = info['url']
return render(request, 'place_details.html', {'details': display_info, 'lat': lat, 'lon': lon, 'pid': p_id}) | 0.272896 | 0.125065 |
from bs4 import BeautifulSoup
import time
import requests
from random import randint
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
def offlineMode():
try:
file = open("quotes.txt","r")
except:
print 'Nothing found in offline data'
def compareResult():
file = open("result.txt","r")
data = file.read().splitlines()
file.close()
if data[-1] == max(data):
print 'It is your highest score'
else:
print bcolors.BOLD+bcolors.OKGREEN+'Your highest score is: '+str(max(data))+bcolors.ENDC
def addResult(result):
file = open("result.txt","a+")
file.write(result+'\n')
file.close()
def testingArea(real,typed):
wordCount = 0
wrongCount = 0
for i in xrange(len(real)):
for j in xrange(len(real[i])):
if real[i][j] == typed[i][j]:
if real[i][j] == ' ':
pass
else:
wordCount += 1
else:
wrongCount += 1
return wordCount,wrongCount
def randomNum(mx):
return randint(1,mx)
def getQuotes():
que = []
check = []
x = randomNum(219)
url = "http://www.values.com/inspirational-quotes?page="+str(x)
r = requests.get(url)
soup = BeautifulSoup(r.content)
h = soup.find_all("h6")
for i in xrange(2):
y = randomNum(len(h))
while True:
if y in que:
y = randomNum(len(h))
else:
break
check.append(str(h[y-1].text))
file = open("quotes.txt","a+")
file.write(str(h[y-1].text)+'\n')
file.close()
que.append(y)
return check
print bcolors.OKBLUE+'\n\n\nQypo - Make typing interesting'+bcolors.ENDC
print bcolors.OKBLUE+'"Increase your typing speed by reading quotes"'+bcolors.ENDC
raw_input(bcolors.WARNING+'Press Enter to continue...'+bcolors.ENDC)
print bcolors.OKBLUE+'\nTip: Make sure everything is exactly typed same.'+bcolors.ENDC
try:
text = getQuotes()
except:
xx = 1
while True:
print 'Trying . . .',xx
try:
text = getQuotes()
break
except:
xx+=1
if xx == 5:
print 'Internet is dead I guess'
print 'Want to try offline ? [Y]es / [N]o'
en = raw_input()
if en == 'Y':
offlineMode()
elif en == 'N':
print 'Ok Bye'
break
print bcolors.BOLD+bcolors.FAIL+'\n\nAll ready'+bcolors.ENDC
print bcolors.FAIL+'Starting in '+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'3'+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'2'+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'1'+bcolors.ENDC
time.sleep(1)
print '\n'
totalTime = 0
totalWords = 0
testingArea = []
for i in text:
t = time.time()
print '--------------------------\n'
print bcolors.BOLD+i+bcolors.ENDC
print '\n--------------------------'
test = raw_input()
print time.time() -t
totalTime += time.time() -t
testingArea.append(test)
time.sleep(1)
wordc = 0
wrongc = 0
#wordc,wrongc = testingArea(text,testing
for i in xrange(len(text)):
for j in xrange(len(text[i])):
try:
if text[i][j] == testingArea[i][j]:
if text[i][j] == ' ':
pass
else:
wordc += 1
else:
wrongc += 1
except:
wrongc += 1
if wrongc >= 1:
print bcolors.BOLD+bcolors.FAIL+'\n\nYou failed. Better luck next time'+bcolors.ENDC
else:
grosswpm = ((wordc+wrongc)/5)/(totalTime/60)
print bcolors.OKGREEN+'\n\n\nTotal time: ' + str(totalTime)+bcolors.ENDC
print bcolors.OKGREEN+'Gross WPM: '+ str(grosswpm)+bcolors.ENDC
print bcolors.FAIL+'Total Errors: '+str(wrongc)+bcolors.ENDC
print bcolors.OKGREEN+'Total words:' +str(wordc)+bcolors.ENDC
netwpm = grosswpm - (wrongc/(totalTime/60))
print bcolors.BOLD+bcolors.OKGREEN+'\nOverall your Typing Speed is: '+str(netwpm)+'\n\n'+bcolors.ENDC
addResult(str(netwpm))
compareResult() | learntype.py | from bs4 import BeautifulSoup
import time
import requests
from random import randint
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
def offlineMode():
try:
file = open("quotes.txt","r")
except:
print 'Nothing found in offline data'
def compareResult():
file = open("result.txt","r")
data = file.read().splitlines()
file.close()
if data[-1] == max(data):
print 'It is your highest score'
else:
print bcolors.BOLD+bcolors.OKGREEN+'Your highest score is: '+str(max(data))+bcolors.ENDC
def addResult(result):
file = open("result.txt","a+")
file.write(result+'\n')
file.close()
def testingArea(real,typed):
wordCount = 0
wrongCount = 0
for i in xrange(len(real)):
for j in xrange(len(real[i])):
if real[i][j] == typed[i][j]:
if real[i][j] == ' ':
pass
else:
wordCount += 1
else:
wrongCount += 1
return wordCount,wrongCount
def randomNum(mx):
return randint(1,mx)
def getQuotes():
que = []
check = []
x = randomNum(219)
url = "http://www.values.com/inspirational-quotes?page="+str(x)
r = requests.get(url)
soup = BeautifulSoup(r.content)
h = soup.find_all("h6")
for i in xrange(2):
y = randomNum(len(h))
while True:
if y in que:
y = randomNum(len(h))
else:
break
check.append(str(h[y-1].text))
file = open("quotes.txt","a+")
file.write(str(h[y-1].text)+'\n')
file.close()
que.append(y)
return check
print bcolors.OKBLUE+'\n\n\nQypo - Make typing interesting'+bcolors.ENDC
print bcolors.OKBLUE+'"Increase your typing speed by reading quotes"'+bcolors.ENDC
raw_input(bcolors.WARNING+'Press Enter to continue...'+bcolors.ENDC)
print bcolors.OKBLUE+'\nTip: Make sure everything is exactly typed same.'+bcolors.ENDC
try:
text = getQuotes()
except:
xx = 1
while True:
print 'Trying . . .',xx
try:
text = getQuotes()
break
except:
xx+=1
if xx == 5:
print 'Internet is dead I guess'
print 'Want to try offline ? [Y]es / [N]o'
en = raw_input()
if en == 'Y':
offlineMode()
elif en == 'N':
print 'Ok Bye'
break
print bcolors.BOLD+bcolors.FAIL+'\n\nAll ready'+bcolors.ENDC
print bcolors.FAIL+'Starting in '+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'3'+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'2'+bcolors.ENDC
time.sleep(1)
print bcolors.FAIL+'1'+bcolors.ENDC
time.sleep(1)
print '\n'
totalTime = 0
totalWords = 0
testingArea = []
for i in text:
t = time.time()
print '--------------------------\n'
print bcolors.BOLD+i+bcolors.ENDC
print '\n--------------------------'
test = raw_input()
print time.time() -t
totalTime += time.time() -t
testingArea.append(test)
time.sleep(1)
wordc = 0
wrongc = 0
#wordc,wrongc = testingArea(text,testing
for i in xrange(len(text)):
for j in xrange(len(text[i])):
try:
if text[i][j] == testingArea[i][j]:
if text[i][j] == ' ':
pass
else:
wordc += 1
else:
wrongc += 1
except:
wrongc += 1
if wrongc >= 1:
print bcolors.BOLD+bcolors.FAIL+'\n\nYou failed. Better luck next time'+bcolors.ENDC
else:
grosswpm = ((wordc+wrongc)/5)/(totalTime/60)
print bcolors.OKGREEN+'\n\n\nTotal time: ' + str(totalTime)+bcolors.ENDC
print bcolors.OKGREEN+'Gross WPM: '+ str(grosswpm)+bcolors.ENDC
print bcolors.FAIL+'Total Errors: '+str(wrongc)+bcolors.ENDC
print bcolors.OKGREEN+'Total words:' +str(wordc)+bcolors.ENDC
netwpm = grosswpm - (wrongc/(totalTime/60))
print bcolors.BOLD+bcolors.OKGREEN+'\nOverall your Typing Speed is: '+str(netwpm)+'\n\n'+bcolors.ENDC
addResult(str(netwpm))
compareResult() | 0.056986 | 0.076477 |
import importlib
from pydashery import Widget
def find_function(search_def):
"""
Dynamically load the function based on the search definition.
:param str search_def: A string to tell us the function to load, e.g.
module:funcname or module.path:class.staticmethod
:raises ValueError: In case configuration is invalid
:return function: A function
"""
try:
module_name, funcspec = search_def.split(":")
except ValueError:
raise ValueError("Function definition \"{}\" is not valid.".format(
search_def
))
try:
module = importlib.import_module(module_name)
except ImportError:
raise ValueError(
"Function definition \"{}\" is not valid. The module specified "
"was not found.".format(
search_def
)
)
if "." in funcspec:
class_name, func_name = funcspec.split(".")
try:
source = getattr(module, class_name)
except AttributeError:
raise ValueError(
"Function definition \"{}\" is not valid. The module does not "
"contain the specified class.".format(
search_def
)
)
else:
source = module
func_name = funcspec
try:
func = getattr(source, func_name)
except AttributeError:
raise ValueError(
"Function definition \"{}\" is not valid. The function specified "
"could not be found.".format(
search_def
)
)
return func
class FunctionResultWidget(Widget):
TYPE = "FunctionResult"
TEMPLATE = "functionresult.html"
DEFAULT_SETTINGS = {
"update_minutes": 1.0
}
def get_update_interval(self):
return float(self.settings["update_minutes"]) * 60.0
def update(self):
self.set_value(self.get_result())
def get_result(self):
f = find_function(self.settings["func"])
return f() | backend/widgets/functionresult.py | import importlib
from pydashery import Widget
def find_function(search_def):
"""
Dynamically load the function based on the search definition.
:param str search_def: A string to tell us the function to load, e.g.
module:funcname or module.path:class.staticmethod
:raises ValueError: In case configuration is invalid
:return function: A function
"""
try:
module_name, funcspec = search_def.split(":")
except ValueError:
raise ValueError("Function definition \"{}\" is not valid.".format(
search_def
))
try:
module = importlib.import_module(module_name)
except ImportError:
raise ValueError(
"Function definition \"{}\" is not valid. The module specified "
"was not found.".format(
search_def
)
)
if "." in funcspec:
class_name, func_name = funcspec.split(".")
try:
source = getattr(module, class_name)
except AttributeError:
raise ValueError(
"Function definition \"{}\" is not valid. The module does not "
"contain the specified class.".format(
search_def
)
)
else:
source = module
func_name = funcspec
try:
func = getattr(source, func_name)
except AttributeError:
raise ValueError(
"Function definition \"{}\" is not valid. The function specified "
"could not be found.".format(
search_def
)
)
return func
class FunctionResultWidget(Widget):
TYPE = "FunctionResult"
TEMPLATE = "functionresult.html"
DEFAULT_SETTINGS = {
"update_minutes": 1.0
}
def get_update_interval(self):
return float(self.settings["update_minutes"]) * 60.0
def update(self):
self.set_value(self.get_result())
def get_result(self):
f = find_function(self.settings["func"])
return f() | 0.547222 | 0.395426 |
from enum import Enum
from typing import Dict, List
from robot.board import Board
class PinMode(Enum):
"""A pin-mode for a pin on the servo board."""
INPUT = 'Z'
INPUT_PULLUP = 'P'
OUTPUT_HIGH = 'H'
OUTPUT_LOW = 'L'
class PinValue(Enum):
"""A value state for a pin on the servo board."""
HIGH = 'H'
LOW = 'L'
class Servo:
"""A servo output on a ``ServoBoard``."""
def __init__(self, servo_id, set_pos, get_pos):
self.servo_id = servo_id
self._set_pos = set_pos
self._get_pos = get_pos
@property
def position(self) -> float:
"""The configured position the servo output."""
return self._get_pos()
@position.setter
def position(self, position):
if position > 1 or position < -1:
raise ValueError("servo position must be between -1 and 1")
self._set_pos(position)
class Gpio:
"""A general-purpose input-output pin on a ``ServoBoard``."""
def __init__(self, pin_id, pin_read, pin_mode_get, pin_mode_set):
self._pin_id = pin_id
self._pin_read = pin_read
self._pin_mode_get = pin_mode_get
self._pin_mode_set = pin_mode_set
@property
def mode(self) -> PinMode:
"""The ``PinMode`` the pin is currently in."""
return PinMode(self._pin_mode_get())
@mode.setter
def mode(self, mode: PinMode):
"""
Set the mode the pin should be in.
:param mode: The ``PinMode`` to set the pin to.
"""
if mode not in (
PinMode.INPUT,
PinMode.INPUT_PULLUP,
PinMode.OUTPUT_HIGH,
PinMode.OUTPUT_LOW,
):
raise ValueError("Mode should be a valid 'PinMode', got {!r}".format(mode))
self._pin_mode_set(mode)
def read(self) -> PinValue:
"""Read the current ``PinValue`` of the pin."""
valid_read_modes = (PinMode.INPUT, PinMode.INPUT_PULLUP)
if self._pin_mode_get() not in valid_read_modes:
raise Exception(
"Pin mode needs to be in a valid read ``PinMode`` to be read. "
"Valid modes are: {}.".format(
", ".join(str(x) for x in valid_read_modes),
),
)
return self._pin_read()
class ArduinoError(Exception):
"""Base class for exceptions fed back from the ``ServoBoard`` (arduino)."""
pass
class CommandError(ArduinoError):
"""The servo assembly experienced an error in processing a command."""
pass
class InvalidResponse(ArduinoError):
"""The servo assembly emitted a response which could not be processed."""
pass
class ServoBoard(Board):
"""
A servo board, providing access to ``Servo``s and ``Gpio`` pins.
This is an arduino with a servo shield attached.
"""
def __init__(self, socket_path):
super().__init__(socket_path)
servo_ids = range(0, 16) # servos with a port 0-15
gpio_pins = range(2, 14) # gpio pins 2-13
self._servos = {} # type: Dict[int, Servo]
for x in servo_ids:
self._servos[x] = Servo(
x,
(lambda pos, x=x: self._set_servo_pos(x, pos)),
(lambda x=x: self._get_servo_pos(x)),
)
self._gpios = {
x: Gpio(
x,
(lambda x=x: self._read_pin(x)),
(lambda x=x: self._get_pin_mode(x)),
(lambda value, x=x: self._set_pin_mode(x, value)),
)
for x in gpio_pins
} # type: Dict[int, Gpio]
def direct_command(self, command_name: str, *args) -> List[str]:
"""
Issue a command directly to the arduino.
:Example:
>>> # arrives on the arduino as "my-command 4"
>>> servo_board.direct_command('my-command', 4)
["first line response from my command", "second line"]
The arguments to this method are bundled as a list and passed to robotd.
We expect to immediately get back a response message (as well as the
usual status blob) which contains either valid data from the arduino or
a description of the failure.
"""
command = (command_name,) + args
response = self._send_and_receive({'command': command})['response']
status = response['status']
# consume the broadcast status
self._receive()
if status == 'ok':
return response['data']
else:
for cls in (CommandError, InvalidResponse):
if cls.__name__ == response['type']:
raise cls(response['description'])
raise ArduinoError(response['description'])
# Servo code
@property
def servos(self) -> Dict[int, Servo]:
"""List of ``Servo`` outputs for the servo board."""
return self._servos
def _set_servo_pos(self, servo: int, pos: float):
self._send_and_receive({'servos': {servo: pos}})
def _get_servo_pos(self, servo: int) -> float:
data = self._send_and_receive({})
values = data['servos']
return float(values[str(servo)])
# GPIO code
@property
def gpios(self) -> Dict[int, Gpio]:
"""List of ``Gpio`` pins for the servo board."""
return self._gpios
def _read_pin(self, pin) -> PinValue:
# request a check for that pin by trying to set it to None
data = self._send_and_receive({'read-pins': [pin]})
# example data value:
# {'pin-values':{2:'high'}}
values = data['pin-values']
return PinValue(values[str(pin)])
def _get_pin_mode(self, pin) -> PinMode:
data = self._send_and_receive({})
# example data value:
# {'pins':{2:'pullup'}}
values = data['pins']
return PinMode(values[str(pin)])
def _set_pin_mode(self, pin, value: PinMode):
self._send_and_receive({'pins': {pin: value.value}})
def read_analogue(self) -> Dict[str, float]:
"""Read analogue values from the connected board."""
command = {'read-analogue': True}
return self._send_and_receive(command)['analogue-values']
def read_ultrasound(self, trigger_pin, echo_pin):
"""
Read an ultrasound value from an ultrasound sensor.
:param trigger_pin: The pin number on the servo board that the sensor's
trigger pin is connected to.
:param echo_pin: The pin number on the servo board that the sensor's
echo pin is connected to.
"""
command = {'read-ultrasound': [trigger_pin, echo_pin]}
return float(self._send_and_receive(command)['ultrasound']) | robot/servo.py | from enum import Enum
from typing import Dict, List
from robot.board import Board
class PinMode(Enum):
"""A pin-mode for a pin on the servo board."""
INPUT = 'Z'
INPUT_PULLUP = 'P'
OUTPUT_HIGH = 'H'
OUTPUT_LOW = 'L'
class PinValue(Enum):
"""A value state for a pin on the servo board."""
HIGH = 'H'
LOW = 'L'
class Servo:
"""A servo output on a ``ServoBoard``."""
def __init__(self, servo_id, set_pos, get_pos):
self.servo_id = servo_id
self._set_pos = set_pos
self._get_pos = get_pos
@property
def position(self) -> float:
"""The configured position the servo output."""
return self._get_pos()
@position.setter
def position(self, position):
if position > 1 or position < -1:
raise ValueError("servo position must be between -1 and 1")
self._set_pos(position)
class Gpio:
"""A general-purpose input-output pin on a ``ServoBoard``."""
def __init__(self, pin_id, pin_read, pin_mode_get, pin_mode_set):
self._pin_id = pin_id
self._pin_read = pin_read
self._pin_mode_get = pin_mode_get
self._pin_mode_set = pin_mode_set
@property
def mode(self) -> PinMode:
"""The ``PinMode`` the pin is currently in."""
return PinMode(self._pin_mode_get())
@mode.setter
def mode(self, mode: PinMode):
"""
Set the mode the pin should be in.
:param mode: The ``PinMode`` to set the pin to.
"""
if mode not in (
PinMode.INPUT,
PinMode.INPUT_PULLUP,
PinMode.OUTPUT_HIGH,
PinMode.OUTPUT_LOW,
):
raise ValueError("Mode should be a valid 'PinMode', got {!r}".format(mode))
self._pin_mode_set(mode)
def read(self) -> PinValue:
"""Read the current ``PinValue`` of the pin."""
valid_read_modes = (PinMode.INPUT, PinMode.INPUT_PULLUP)
if self._pin_mode_get() not in valid_read_modes:
raise Exception(
"Pin mode needs to be in a valid read ``PinMode`` to be read. "
"Valid modes are: {}.".format(
", ".join(str(x) for x in valid_read_modes),
),
)
return self._pin_read()
class ArduinoError(Exception):
"""Base class for exceptions fed back from the ``ServoBoard`` (arduino)."""
pass
class CommandError(ArduinoError):
"""The servo assembly experienced an error in processing a command."""
pass
class InvalidResponse(ArduinoError):
"""The servo assembly emitted a response which could not be processed."""
pass
class ServoBoard(Board):
"""
A servo board, providing access to ``Servo``s and ``Gpio`` pins.
This is an arduino with a servo shield attached.
"""
def __init__(self, socket_path):
super().__init__(socket_path)
servo_ids = range(0, 16) # servos with a port 0-15
gpio_pins = range(2, 14) # gpio pins 2-13
self._servos = {} # type: Dict[int, Servo]
for x in servo_ids:
self._servos[x] = Servo(
x,
(lambda pos, x=x: self._set_servo_pos(x, pos)),
(lambda x=x: self._get_servo_pos(x)),
)
self._gpios = {
x: Gpio(
x,
(lambda x=x: self._read_pin(x)),
(lambda x=x: self._get_pin_mode(x)),
(lambda value, x=x: self._set_pin_mode(x, value)),
)
for x in gpio_pins
} # type: Dict[int, Gpio]
def direct_command(self, command_name: str, *args) -> List[str]:
"""
Issue a command directly to the arduino.
:Example:
>>> # arrives on the arduino as "my-command 4"
>>> servo_board.direct_command('my-command', 4)
["first line response from my command", "second line"]
The arguments to this method are bundled as a list and passed to robotd.
We expect to immediately get back a response message (as well as the
usual status blob) which contains either valid data from the arduino or
a description of the failure.
"""
command = (command_name,) + args
response = self._send_and_receive({'command': command})['response']
status = response['status']
# consume the broadcast status
self._receive()
if status == 'ok':
return response['data']
else:
for cls in (CommandError, InvalidResponse):
if cls.__name__ == response['type']:
raise cls(response['description'])
raise ArduinoError(response['description'])
# Servo code
@property
def servos(self) -> Dict[int, Servo]:
"""List of ``Servo`` outputs for the servo board."""
return self._servos
def _set_servo_pos(self, servo: int, pos: float):
self._send_and_receive({'servos': {servo: pos}})
def _get_servo_pos(self, servo: int) -> float:
data = self._send_and_receive({})
values = data['servos']
return float(values[str(servo)])
# GPIO code
@property
def gpios(self) -> Dict[int, Gpio]:
"""List of ``Gpio`` pins for the servo board."""
return self._gpios
def _read_pin(self, pin) -> PinValue:
# request a check for that pin by trying to set it to None
data = self._send_and_receive({'read-pins': [pin]})
# example data value:
# {'pin-values':{2:'high'}}
values = data['pin-values']
return PinValue(values[str(pin)])
def _get_pin_mode(self, pin) -> PinMode:
data = self._send_and_receive({})
# example data value:
# {'pins':{2:'pullup'}}
values = data['pins']
return PinMode(values[str(pin)])
def _set_pin_mode(self, pin, value: PinMode):
self._send_and_receive({'pins': {pin: value.value}})
def read_analogue(self) -> Dict[str, float]:
"""Read analogue values from the connected board."""
command = {'read-analogue': True}
return self._send_and_receive(command)['analogue-values']
def read_ultrasound(self, trigger_pin, echo_pin):
"""
Read an ultrasound value from an ultrasound sensor.
:param trigger_pin: The pin number on the servo board that the sensor's
trigger pin is connected to.
:param echo_pin: The pin number on the servo board that the sensor's
echo pin is connected to.
"""
command = {'read-ultrasound': [trigger_pin, echo_pin]}
return float(self._send_and_receive(command)['ultrasound']) | 0.928198 | 0.432962 |
from django.contrib.auth.decorators import login_required
from django.http import HttpResponse
import datetime
from openpyxl import Workbook
import xlwt
from dashboard.sheet_builder import NewSheetBuilder
from dashboard.utils import extract_list_from_sheet, controlePlanosSheetFiller, cotachSheetFiller
from .models import *
@login_required(login_url='login')
def exportarProjetosExcel(request, cron_id):
unidades = Unidade.objects.all()
cronograma = Cronograma.objects.get(id = cron_id)
filename = f"Resumo Sistema - Planos de ação - {cronograma.inicio_servicos.strftime(f'%d')} a {cronograma.fim_servicos.strftime(f'%d de %B')}"
response = HttpResponse(content_type='application/ms-excel')
response['Content-Disposition'] = f'attachment; filename="{filename}.xls"'
wb = xlwt.Workbook(encoding='utf-8')
controlePlanosSheetFiller(wb.add_sheet('CONTROLE'),cronograma,unidades)
cotachSheetFiller(wb.add_sheet("COTAxCH"), cronograma, unidades )
wb.save(response)
return response
@login_required(login_url='login')
def exportarVagasExcel(request, cron_id, dia):
dia = datetime.datetime.strptime(dia, f"%Y-%m-%d").date()
vagas = Vaga.objects.filter(dia = dia)
filename = "Vagas "+dia.strftime(f"%d-%m-%Y")
response = HttpResponse(content_type='application/ms-excel')
response['Content-Disposition'] = f'attachment; filename="{filename}.xlsx"'
wb = Workbook()
sheet = wb.active
sheet.title="Vagas"
if not vagas.exists():
wb.save(response)
return response
sb = NewSheetBuilder(sheet)
sb.set_col_widths([10,10,35,30,10,10])
sb.write_header([
{'text':'DATA'},
{'text':'UNIDADE'},
{'text':'ATIVIDADE'},
{'text':'RESPONSÁVEL'},
{'text':'HORÁRIO'},
{'text':'CH'}])
sb.enter()
for vaga in vagas:
sb.write_cell(date_format(vaga.dia, "d-M"))
sb.write_cell(vaga.unidade.sigla, style = sb.get_random_color_style(vaga.unidade.id))
sb.write_cell(vaga.atividade)
sb.write_cell(vaga.responsavel)
sb.write_cell(vaga.horario, style=None if vaga.carga_horaria==12 else 'highlight_')
sb.write_cell(vaga.carga_horaria, carr_ret=True)
wb.save(response)
return response | projetos/reports.py | from django.contrib.auth.decorators import login_required
from django.http import HttpResponse
import datetime
from openpyxl import Workbook
import xlwt
from dashboard.sheet_builder import NewSheetBuilder
from dashboard.utils import extract_list_from_sheet, controlePlanosSheetFiller, cotachSheetFiller
from .models import *
@login_required(login_url='login')
def exportarProjetosExcel(request, cron_id):
unidades = Unidade.objects.all()
cronograma = Cronograma.objects.get(id = cron_id)
filename = f"Resumo Sistema - Planos de ação - {cronograma.inicio_servicos.strftime(f'%d')} a {cronograma.fim_servicos.strftime(f'%d de %B')}"
response = HttpResponse(content_type='application/ms-excel')
response['Content-Disposition'] = f'attachment; filename="{filename}.xls"'
wb = xlwt.Workbook(encoding='utf-8')
controlePlanosSheetFiller(wb.add_sheet('CONTROLE'),cronograma,unidades)
cotachSheetFiller(wb.add_sheet("COTAxCH"), cronograma, unidades )
wb.save(response)
return response
@login_required(login_url='login')
def exportarVagasExcel(request, cron_id, dia):
dia = datetime.datetime.strptime(dia, f"%Y-%m-%d").date()
vagas = Vaga.objects.filter(dia = dia)
filename = "Vagas "+dia.strftime(f"%d-%m-%Y")
response = HttpResponse(content_type='application/ms-excel')
response['Content-Disposition'] = f'attachment; filename="{filename}.xlsx"'
wb = Workbook()
sheet = wb.active
sheet.title="Vagas"
if not vagas.exists():
wb.save(response)
return response
sb = NewSheetBuilder(sheet)
sb.set_col_widths([10,10,35,30,10,10])
sb.write_header([
{'text':'DATA'},
{'text':'UNIDADE'},
{'text':'ATIVIDADE'},
{'text':'RESPONSÁVEL'},
{'text':'HORÁRIO'},
{'text':'CH'}])
sb.enter()
for vaga in vagas:
sb.write_cell(date_format(vaga.dia, "d-M"))
sb.write_cell(vaga.unidade.sigla, style = sb.get_random_color_style(vaga.unidade.id))
sb.write_cell(vaga.atividade)
sb.write_cell(vaga.responsavel)
sb.write_cell(vaga.horario, style=None if vaga.carga_horaria==12 else 'highlight_')
sb.write_cell(vaga.carga_horaria, carr_ret=True)
wb.save(response)
return response | 0.36886 | 0.069007 |
from version import __version__
import re
import os
import unittest
import logging
def SlashContrl(strpath):
'''
Solves windows - os.path normalize fail
for i.e. tests\\tests, considers \t an escape sequence.
:filters:: ['\\r', '\\t', '\\f', '\\a', '\\v'].
:return: true path [str]
*other specific escape chars not filtered*
'''
if not strpath or strpath == ' ':
return None
cntrls = ['r', 't', 'f', 'a', 'v']
res = None
dbblstr = None
for ct in cntrls:
res = re.search('[\\' + ct + ']', strpath)
if res:
dbblstr = strpath[0:res.start()] + r'\\' + ct + strpath[res.end():]
if not dbblstr:
return None
return os.path.normpath(os.path.abspath(dbblstr))
return os.path.normpath(os.path.abspath(strpath))
#pylint: disable=attribute-defined-outside-init
#pylint: disable=invalid-name
<EMAIL>("skipping TestCaseDoubleSlash")
class TestCaseDoubleSlash(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.cwd = os.getcwd()
cls.pardir = os.path.dirname(os.getcwd())
tdir = '\\Tests'
if 'Tests' in os.getcwd():
logging.warn('\n pardir {}'.format(cls.pardir))
cls.parStrs = {'0':'Tests\rtest.py',
'1': '..\\Tests\test.py',
'2': '.\\Tests/fest.py',
'3': '.\\tests\ttest.py'
}
cls.resultStrs = {'0':os.path.join(cls.cwd + tdir + '\\rtest.py'),
'1':os.path.join(os.path.dirname(cls.cwd) + tdir + \
'\\test.py'),
'2':os.path.join(cls.cwd + tdir + '\\fest.py'),
'3':os.path.join(cls.cwd + '\\tests\\ttest.py')
}
#logging.warn('\n dict slsh 3 {}'.format(cls.resultStrs['3']))
cls.cwd = os.getcwd()
print("\n\t" + cls.__name__ + " set-up")
@classmethod
def tearDownClass(cls):
print "\n" + cls.__name__ + " tear down"
def setUp(self):
print("\n" + self.id() + " Set-up")
def tearDown(self):
print "\n" + self.id() + " Tear down"
def test_backslash_and_Controls_0(self):
par = self.parStrs['0']
ret = self.resultStrs['0']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_1(self):
par = self.parStrs['1']
ret = self.resultStrs['1']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_2(self):
par = self.parStrs['2']
ret = self.resultStrs['2']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_3(self):
par = self.parStrs['3']
ret = self.resultStrs['3']
self.assertEqual(SlashContrl(par), ret)
if __name__ == '__main__':
tests = unittest.TestLoader().loadTestsFromTestCase(TestCaseDoubleSlash)
result = unittest.TextTestRunner(verbosity=3).run(tests)
status = 'OK' if result.wasSuccessful() else 'FAILED (failures = ' + \
str(len(result.failures)) + ')\n' + 'ERRORS (errors = ' + \
str(len(result.errors)) + ')\n'
print('\nRan {} tests \n\n{}' \
.format(result.testsRun, status))
if result.failures:
print(('Fails:' + '\n {}'*len(result.failures)) \
.format(*result.failures))
if result.errors:
print(('Errs:' + '\n{}'*len(result.errors[0])) \
.format(*result.errors[0]))
#pylint: enable=attribute-defined-outside-init
#pylint: enable=invalid-name | regt.py | from version import __version__
import re
import os
import unittest
import logging
def SlashContrl(strpath):
'''
Solves windows - os.path normalize fail
for i.e. tests\\tests, considers \t an escape sequence.
:filters:: ['\\r', '\\t', '\\f', '\\a', '\\v'].
:return: true path [str]
*other specific escape chars not filtered*
'''
if not strpath or strpath == ' ':
return None
cntrls = ['r', 't', 'f', 'a', 'v']
res = None
dbblstr = None
for ct in cntrls:
res = re.search('[\\' + ct + ']', strpath)
if res:
dbblstr = strpath[0:res.start()] + r'\\' + ct + strpath[res.end():]
if not dbblstr:
return None
return os.path.normpath(os.path.abspath(dbblstr))
return os.path.normpath(os.path.abspath(strpath))
#pylint: disable=attribute-defined-outside-init
#pylint: disable=invalid-name
<EMAIL>("skipping TestCaseDoubleSlash")
class TestCaseDoubleSlash(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.cwd = os.getcwd()
cls.pardir = os.path.dirname(os.getcwd())
tdir = '\\Tests'
if 'Tests' in os.getcwd():
logging.warn('\n pardir {}'.format(cls.pardir))
cls.parStrs = {'0':'Tests\rtest.py',
'1': '..\\Tests\test.py',
'2': '.\\Tests/fest.py',
'3': '.\\tests\ttest.py'
}
cls.resultStrs = {'0':os.path.join(cls.cwd + tdir + '\\rtest.py'),
'1':os.path.join(os.path.dirname(cls.cwd) + tdir + \
'\\test.py'),
'2':os.path.join(cls.cwd + tdir + '\\fest.py'),
'3':os.path.join(cls.cwd + '\\tests\\ttest.py')
}
#logging.warn('\n dict slsh 3 {}'.format(cls.resultStrs['3']))
cls.cwd = os.getcwd()
print("\n\t" + cls.__name__ + " set-up")
@classmethod
def tearDownClass(cls):
print "\n" + cls.__name__ + " tear down"
def setUp(self):
print("\n" + self.id() + " Set-up")
def tearDown(self):
print "\n" + self.id() + " Tear down"
def test_backslash_and_Controls_0(self):
par = self.parStrs['0']
ret = self.resultStrs['0']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_1(self):
par = self.parStrs['1']
ret = self.resultStrs['1']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_2(self):
par = self.parStrs['2']
ret = self.resultStrs['2']
self.assertEqual(SlashContrl(par), ret)
def test_backslash_and_Controls_3(self):
par = self.parStrs['3']
ret = self.resultStrs['3']
self.assertEqual(SlashContrl(par), ret)
if __name__ == '__main__':
tests = unittest.TestLoader().loadTestsFromTestCase(TestCaseDoubleSlash)
result = unittest.TextTestRunner(verbosity=3).run(tests)
status = 'OK' if result.wasSuccessful() else 'FAILED (failures = ' + \
str(len(result.failures)) + ')\n' + 'ERRORS (errors = ' + \
str(len(result.errors)) + ')\n'
print('\nRan {} tests \n\n{}' \
.format(result.testsRun, status))
if result.failures:
print(('Fails:' + '\n {}'*len(result.failures)) \
.format(*result.failures))
if result.errors:
print(('Errs:' + '\n{}'*len(result.errors[0])) \
.format(*result.errors[0]))
#pylint: enable=attribute-defined-outside-init
#pylint: enable=invalid-name | 0.324235 | 0.099645 |
from __future__ import annotations
from typing import TYPE_CHECKING, Union, Optional
from enum import Enum
from asyncio import Event
from random import sample
import discord
from rtlib import sendableString
from .music import Music, is_url
if TYPE_CHECKING:
from .__init__ import MusicCog
class NotAddedReason(Enum):
"キューに追加することに失敗した際に呼ばれる関数です。"
list_very_many = 1
queue_many = 2
class LoopMode(Enum):
"ループのモードの設定です。"
none = 1
all = 2
one = 3
class Player:
"音楽再生にサーバー毎に使う音楽プレイヤーのクラスです。"
def __init__(self, cog: MusicCog, guild: discord.Guild, voice_client: discord.VoiceClient):
self.cog, self.guild = cog, guild
self.queues: list[Music] = []
self._loop = LoopMode.none
self.channel: Optional[discord.TextChannel] = None
self.vc = voice_client
self._volume, self._skipped = 1.0, False
self._stopped = Event()
self._stopped.set()
self._closing = False
def print(self, *args, **kwargs):
"デバッグ用とかっこつけるためのprintです。"
self.cog.print(f"[{self}]", *args, **kwargs)
@property
def length(self) -> int:
"キューの長さを取得します。ただのエイリアス"
return len(self.queues)
async def add_from_url(self, author: discord.Member, url: str) -> Optional[
Union[NotAddedReason, Exception, list[Music]]
]:
"キューにURLから音楽を追加します。"
if isinstance((data := await Music.from_url(
self.cog, author, url, self.cog.max(self.guild)
)), Exception):
# 取得に失敗したのならエラーを起こす。
return data
elif isinstance(data, tuple):
# もし取得結果が複数あるなら
if not is_url(url):
# もし検索結果が返ってきたのならそれをそのまま返す。
return data[0]
# 量制限の確認をする。
if self.length + (queues_length := len(data[0])) > self.cog.max(author):
return NotAddedReason.queue_many
else:
self.print("Adding %s queues, Author: %s" % (queues_length, author))
self.queues.extend(data[0])
if data[1]:
return NotAddedReason.list_very_many
else:
# 通常
self.print("Adding queue: %s" % data)
return self.add(data)
def add(self, music: Music) -> Optional[NotAddedReason]:
"渡されたMusicをqueueに追加します。"
self.print("Adding queue: %s" % music)
if self.length >= self.cog.max(self.guild):
return NotAddedReason.queue_many
else:
self.queues.append(music)
@property
def now(self) -> Optional[Music]:
"あるなら現在再生中のキューのMusicを返します。"
self._assert_vc()
if self.queues and self.vc:
return self.queues[0]
def _process_closed_queue(self):
# 音楽再生終了後のキューの処理をする。
if self.vc.is_connected() and not self._skipped:
if self._loop == LoopMode.all:
self.queues.append(self.queues.pop(0))
elif self._loop == LoopMode.none:
del self.queues[0]
else:
del self.queues[0]
self._skipped = False
async def _after_play(self, e: Exception):
# 音楽再生終了後の後始末をする。
self.print("Finished to play a music")
if e and self.channel is not None:
self.print("Error:", e)
await self.channel.send(
{"ja": f"何かしらエラーが発生して再生に失敗しました。\ncode: `{e}`",
"en": f"Something went wrong.\ncode: `{e}`"}
)
# 音源のお片付けをしてキューのcloseをしてキューを消す。
self.print("Cleaning...")
await self.queues[0].stop(self._process_closed_queue)
self._stopped.set()
# 次のキューがあれば再生を行う。
if self.queues:
await self.play()
def _assert_vc(self):
# VCに接続済みかチェックをします。
assert self.vc is not None, "接続されていません。"
async def play(self):
"""現在登録されているキューの一番最初にある曲を再生します。
再生終了後にまだキューがある場合はもう一度この関数が呼ばれます。"""
self._assert_vc()
# キューを取って経過時間がわかるようにする。
queue = self.queues[0]
queue.start()
# sourceを用意する。
self.print("Loading music source...")
source = await queue.make_source()
# 音量を変更する。
source.volume = self._volume
self.print("Playing music...")
self._stopped.clear()
self.vc.play(
source, after=lambda e: self.cog.bot.loop.create_task(
self._after_play(e)
)
)
def _assert_playing(self):
assert self.vc.is_playing(), "現在は何も再生していません。"
def pause(self) -> bool:
"再生を一時停止します。二度目は再開します。"
self._assert_vc()
if self.now is not None:
self.now.toggle_pause()
if self.vc.is_paused():
self.vc.resume()
return True
else:
self._assert_vc()
self.vc.pause()
return False
def skip(self):
"次のキューにスキップします。"
self._assert_playing()
self._skipped = True
self.vc.stop()
@property
def volume(self) -> float:
"""音量を取得します。パーセントで返されます。
代入することで音量の変更することができます。"""
return self._volume * 100
@volume.setter
def volume(self, volume: int):
self._volume = volume / 100
# もし音楽の再生中なら再生中のものの音量を変更する。
if self.vc.is_playing():
self.vc.source.volume = self._volume
def shuffle(self):
"キューをシャッフルします。"
if self.queues:
self.queues[1:] = sample(self.queues[1:], len(self.queues[1:]))
def loop(self, mode: Optional[LoopMode] = None) -> LoopMode:
"ループを設定します。"
if mode is None:
if self._loop == LoopMode.none:
self._loop = LoopMode.one
elif self._loop == LoopMode.one:
self._loop = LoopMode.all
else:
self._loop = LoopMode.none
else:
self._loop = mode
return self._loop
async def wait_until_stopped(self) -> None:
"再生が停止するまで待機をします。"
await self._stopped.wait()
async def disconnect(
self, reason: Optional[sendableString] = None, force: bool = False
):
"お片付けをして切断をします。"
self._assert_vc()
self.print("Disconnecting...")
self._closing = True
# キューが二個以上あるならキューを一個以外全部消す。
if len(self.queues) > 1:
self.queues = self.queues[:1]
# 再生の停止をする。
if self.vc.is_connected():
await self.vc.disconnect(force=force)
await self.wait_until_stopped()
# もし理由があるなら送信しておく。
if self.channel is not None and reason is not None:
try: await self.channel.send(reason)
except Exception: ...
self.cog.bot.loop.call_soon(self.cog.remove_player, self.guild.id)
self.print("Done")
def __del__(self):
if self.vc is not None and self.vc.is_connected():
# 予期せずにこのクラスのインスタンスが消されたかつボイスチャンネルに接続してる場合は切断を行う。
# 念の為のメモリリーク防止用のもの。
self.cog.bot.loop.create_task(
self.disconnect(
{"ja": "何らかの原因により再生が停止されました。",
"en": "Something went wrong when playing a music."}
), name=f"{self}.disconnect"
)
def __str__(self):
return f"<Player Guild={self.guild} now={self.now}>" | cogs/music/player.py |
from __future__ import annotations
from typing import TYPE_CHECKING, Union, Optional
from enum import Enum
from asyncio import Event
from random import sample
import discord
from rtlib import sendableString
from .music import Music, is_url
if TYPE_CHECKING:
from .__init__ import MusicCog
class NotAddedReason(Enum):
"キューに追加することに失敗した際に呼ばれる関数です。"
list_very_many = 1
queue_many = 2
class LoopMode(Enum):
"ループのモードの設定です。"
none = 1
all = 2
one = 3
class Player:
"音楽再生にサーバー毎に使う音楽プレイヤーのクラスです。"
def __init__(self, cog: MusicCog, guild: discord.Guild, voice_client: discord.VoiceClient):
self.cog, self.guild = cog, guild
self.queues: list[Music] = []
self._loop = LoopMode.none
self.channel: Optional[discord.TextChannel] = None
self.vc = voice_client
self._volume, self._skipped = 1.0, False
self._stopped = Event()
self._stopped.set()
self._closing = False
def print(self, *args, **kwargs):
"デバッグ用とかっこつけるためのprintです。"
self.cog.print(f"[{self}]", *args, **kwargs)
@property
def length(self) -> int:
"キューの長さを取得します。ただのエイリアス"
return len(self.queues)
async def add_from_url(self, author: discord.Member, url: str) -> Optional[
Union[NotAddedReason, Exception, list[Music]]
]:
"キューにURLから音楽を追加します。"
if isinstance((data := await Music.from_url(
self.cog, author, url, self.cog.max(self.guild)
)), Exception):
# 取得に失敗したのならエラーを起こす。
return data
elif isinstance(data, tuple):
# もし取得結果が複数あるなら
if not is_url(url):
# もし検索結果が返ってきたのならそれをそのまま返す。
return data[0]
# 量制限の確認をする。
if self.length + (queues_length := len(data[0])) > self.cog.max(author):
return NotAddedReason.queue_many
else:
self.print("Adding %s queues, Author: %s" % (queues_length, author))
self.queues.extend(data[0])
if data[1]:
return NotAddedReason.list_very_many
else:
# 通常
self.print("Adding queue: %s" % data)
return self.add(data)
def add(self, music: Music) -> Optional[NotAddedReason]:
"渡されたMusicをqueueに追加します。"
self.print("Adding queue: %s" % music)
if self.length >= self.cog.max(self.guild):
return NotAddedReason.queue_many
else:
self.queues.append(music)
@property
def now(self) -> Optional[Music]:
"あるなら現在再生中のキューのMusicを返します。"
self._assert_vc()
if self.queues and self.vc:
return self.queues[0]
def _process_closed_queue(self):
# 音楽再生終了後のキューの処理をする。
if self.vc.is_connected() and not self._skipped:
if self._loop == LoopMode.all:
self.queues.append(self.queues.pop(0))
elif self._loop == LoopMode.none:
del self.queues[0]
else:
del self.queues[0]
self._skipped = False
async def _after_play(self, e: Exception):
# 音楽再生終了後の後始末をする。
self.print("Finished to play a music")
if e and self.channel is not None:
self.print("Error:", e)
await self.channel.send(
{"ja": f"何かしらエラーが発生して再生に失敗しました。\ncode: `{e}`",
"en": f"Something went wrong.\ncode: `{e}`"}
)
# 音源のお片付けをしてキューのcloseをしてキューを消す。
self.print("Cleaning...")
await self.queues[0].stop(self._process_closed_queue)
self._stopped.set()
# 次のキューがあれば再生を行う。
if self.queues:
await self.play()
def _assert_vc(self):
# VCに接続済みかチェックをします。
assert self.vc is not None, "接続されていません。"
async def play(self):
"""現在登録されているキューの一番最初にある曲を再生します。
再生終了後にまだキューがある場合はもう一度この関数が呼ばれます。"""
self._assert_vc()
# キューを取って経過時間がわかるようにする。
queue = self.queues[0]
queue.start()
# sourceを用意する。
self.print("Loading music source...")
source = await queue.make_source()
# 音量を変更する。
source.volume = self._volume
self.print("Playing music...")
self._stopped.clear()
self.vc.play(
source, after=lambda e: self.cog.bot.loop.create_task(
self._after_play(e)
)
)
def _assert_playing(self):
assert self.vc.is_playing(), "現在は何も再生していません。"
def pause(self) -> bool:
"再生を一時停止します。二度目は再開します。"
self._assert_vc()
if self.now is not None:
self.now.toggle_pause()
if self.vc.is_paused():
self.vc.resume()
return True
else:
self._assert_vc()
self.vc.pause()
return False
def skip(self):
"次のキューにスキップします。"
self._assert_playing()
self._skipped = True
self.vc.stop()
@property
def volume(self) -> float:
"""音量を取得します。パーセントで返されます。
代入することで音量の変更することができます。"""
return self._volume * 100
@volume.setter
def volume(self, volume: int):
self._volume = volume / 100
# もし音楽の再生中なら再生中のものの音量を変更する。
if self.vc.is_playing():
self.vc.source.volume = self._volume
def shuffle(self):
"キューをシャッフルします。"
if self.queues:
self.queues[1:] = sample(self.queues[1:], len(self.queues[1:]))
def loop(self, mode: Optional[LoopMode] = None) -> LoopMode:
"ループを設定します。"
if mode is None:
if self._loop == LoopMode.none:
self._loop = LoopMode.one
elif self._loop == LoopMode.one:
self._loop = LoopMode.all
else:
self._loop = LoopMode.none
else:
self._loop = mode
return self._loop
async def wait_until_stopped(self) -> None:
"再生が停止するまで待機をします。"
await self._stopped.wait()
async def disconnect(
self, reason: Optional[sendableString] = None, force: bool = False
):
"お片付けをして切断をします。"
self._assert_vc()
self.print("Disconnecting...")
self._closing = True
# キューが二個以上あるならキューを一個以外全部消す。
if len(self.queues) > 1:
self.queues = self.queues[:1]
# 再生の停止をする。
if self.vc.is_connected():
await self.vc.disconnect(force=force)
await self.wait_until_stopped()
# もし理由があるなら送信しておく。
if self.channel is not None and reason is not None:
try: await self.channel.send(reason)
except Exception: ...
self.cog.bot.loop.call_soon(self.cog.remove_player, self.guild.id)
self.print("Done")
def __del__(self):
if self.vc is not None and self.vc.is_connected():
# 予期せずにこのクラスのインスタンスが消されたかつボイスチャンネルに接続してる場合は切断を行う。
# 念の為のメモリリーク防止用のもの。
self.cog.bot.loop.create_task(
self.disconnect(
{"ja": "何らかの原因により再生が停止されました。",
"en": "Something went wrong when playing a music."}
), name=f"{self}.disconnect"
)
def __str__(self):
return f"<Player Guild={self.guild} now={self.now}>" | 0.776962 | 0.169234 |
from __future__ import annotations
import abc
import numpy as np
from pyrsistent.typing import PMap as PMapT
from pyrsistent import pmap
from typing import Union, Tuple, Any, FrozenSet, List
from dataclasses import dataclass
from functools import cached_property, cache
from more_itertools import zip_equal as zip
from pytools import UniqueNameGenerator
IntegralT = Union[int, np.int8, np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64]
INT_CLASSES = (int, np.int8, np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64)
ShapeComponentT = Union[IntegralT, "SizeParam"]
ShapeT = Tuple[ShapeComponentT, ...]
@dataclass(frozen=True, eq=True, repr=True)
class VeryLongAxis:
"""
Describes a dimension length which is to be assumed to be very large.
"""
# TODO: Record the threshold over which an axis could be considered as
# "VeryLong."
@dataclass(frozen=True, eq=True, repr=True)
class SizeParam:
name: str
@dataclass(frozen=True, repr=True, eq=True)
class EinsumAxisAccess(abc.ABC):
"""
Base class for axis access types in an einsum expression.
"""
@dataclass(frozen=True, repr=True, eq=True)
class FreeAxis(EinsumAxisAccess):
"""
Records the axis of an einsum argument over which contraction is not performed.
.. attribute:: output_index
Position of the corresponding index in the einsum's output.
"""
output_index: int
@dataclass(frozen=True, repr=True, eq=True)
class SummationAxis(EinsumAxisAccess):
"""
Records an index in an einsum expression over which reduction is performed.
Sometimes also referred to as an axis with a corresponding "dummy index" in
Ricci Calculus.
.. attribute:: index
An integer which is unique to a reduction index of an einsum.
"""
index: int
@dataclass(frozen=True, eq=True, repr=True)
class FusedEinsum:
"""
A fused einsum expression.
.. attribute:: shape
.. attribute:: ndim
.. automethod:: index_to_dim_length
.. automethod:: get_subscripts
"""
arg_shapes: Tuple[ShapeT, ...]
value_to_dtype: PMapT[str, np.dtype[Any]]
access_descriptors: Tuple[Tuple[EinsumAxisAccess, ...], ...]
use_matrix: Tuple[Tuple[FrozenSet[str], ...], ...]
index_names: PMapT[EinsumAxisAccess, str]
@property
def noutputs(self) -> int:
return len(self.use_matrix)
@cache
def index_to_dim_length(self) -> PMapT[EinsumAxisAccess, ShapeComponentT]:
index_to_dim = {}
for arg_shape, arg_axes in zip(self.arg_shapes,
self.access_descriptors):
for dim, index in zip(arg_shape, arg_axes):
if dim not in index_to_dim:
index_to_dim[index] = dim
else:
assert dim == index_to_dim[index]
return pmap(index_to_dim)
@cached_property
def shape(self) -> ShapeT:
free_index_to_dim = {idx: dim
for idx, dim in self.index_to_dim_length().items()
if isinstance(idx, FreeAxis)}
assert all(FreeAxis(idim) in free_index_to_dim
for idim in range(len(free_index_to_dim)))
return tuple(dim
for _, dim in sorted(free_index_to_dim.items(),
key=lambda x: x[0].output_index))
@property
def ndim(self) -> int:
return len(self.shape)
@cache
def get_subscripts(self) -> str:
"""
Returns the subscripts used in the building the *einsum* from it.
"""
return (",".join("".join(self.index_names[axis]
for axis in axes)
for axes in self.access_descriptors)
+ "->"
+ "".join(self.index_names[FreeAxis(i)]
for i in range(self.ndim))
)
def copy(self, **kwargs: Any) -> FusedEinsum:
from dataclasses import replace
return replace(self, **kwargs)
class Argument(abc.ABC):
"""
An abstract class denoting an argument to an einsum in
:class:`ContractionSchedule`. See :attr:`ContractionSchedule.arguments`.
"""
@dataclass(frozen=True, eq=True, repr=True)
class IntermediateResult(Argument):
"""
An :class:`Argument` representing an intermediate result available during
the current contraction.
"""
name: str
@dataclass(frozen=True, eq=True, repr=True)
class EinsumOperand(Argument):
"""
An :class:`Argument` representing the *ioperand*-th argument that was
passed to the parent einsum whose :class:`ContractionSchedule` is being
specified.
"""
ioperand: int
@dataclass(frozen=True, eq=True, repr=True)
class ContractionSchedule:
"""
Records the schedule in which contractions are to be performed in an einsum
as a series of einsums with the i-th einsum having subscript
``subscript[i]`` operating on ``arguments[i]`` and writing its result to
``result_names[i]``.
.. attribute:: result_names
Names of the result generated by each
.. attribute:: arguments
A :class:`tuple` containing :class:`tuple` of :class:`` for each
contraction in the schedule.
.. attribute:: nsteps
"""
subscripts: Tuple[str, ...]
result_names: Tuple[str, ...]
arguments: Tuple[Tuple[Argument, ...], ...]
def __post_init__(self) -> None:
assert len(self.subscripts) == len(self.result_names) == len(self.arguments)
@property
def nsteps(self) -> int:
"""
Returns the number of steps involved in scheduling the einsum.
"""
return len(self.subscripts)
def copy(self, **kwargs: Any) -> ContractionSchedule:
from dataclasses import replace
return replace(self, **kwargs)
def get_trivial_contraction_schedule(einsum: FusedEinsum) -> ContractionSchedule:
"""
Returns the :class:`ContractionSchedule` for *einsum* scheduled as a single
contraction.
"""
return ContractionSchedule((einsum.get_subscripts(),),
("_fe_out",),
(tuple(EinsumOperand(i)
for i, _ in enumerate(einsum.arg_shapes)),)
)
def get_opt_einsum_contraction_schedule(expr: FusedEinsum,
**opt_einsum_kwargs: Any,
) -> ContractionSchedule:
"""
Returns a :class:`ContractionSchedule` as computed by
:func:`opt_einsum.contract_path`.
:param opt_einsum_kwargs: kwargs to be passed to
:func:`opt_einsum.contract_path`.
.. note::
The following defaults are populated in *opt_einsum_kwargs*, if left
unspecified:
- ``optimize="optimal"``
- ``use_blas=False``
"""
import opt_einsum
from feinsum.make_einsum import array
long_dim_length = opt_einsum_kwargs.pop("long_dim_length", 1_000_000)
if "optimize" not in opt_einsum_kwargs:
opt_einsum_kwargs["optimize"] = "optimal"
if "use_blas" not in opt_einsum_kwargs:
opt_einsum_kwargs["use_blas"] = False
_, path = opt_einsum.contract_path(expr.get_subscripts(),
*[array([d if isinstance(op_shape,
INT_CLASSES)
else long_dim_length
for d in op_shape],
"float64")
for op_shape in expr.arg_shapes],
**opt_einsum_kwargs)
current_args: List[Argument] = [
EinsumOperand(i)
for i in range(path.input_subscripts.count(",") + 1)]
vng = UniqueNameGenerator()
subscripts: List[str] = []
result_names: List[str] = []
arguments: List[Tuple[Argument, ...]] = []
for contraction in path.contraction_list:
arg_indices, _, subscript, _, _ = contraction
arguments.append(tuple(current_args[idx]
for idx in arg_indices))
subscripts.append(subscript)
result_names.append(vng("_fe_tmp"))
current_args = ([arg
for idx, arg in enumerate(current_args)
if idx not in arg_indices]
+ [IntermediateResult(result_names[-1])])
assert len(current_args) == 1
result_names[-1] = vng("_fe_out")
return ContractionSchedule(tuple(subscripts),
tuple(result_names),
tuple(arguments)) | src/feinsum/einsum.py | from __future__ import annotations
import abc
import numpy as np
from pyrsistent.typing import PMap as PMapT
from pyrsistent import pmap
from typing import Union, Tuple, Any, FrozenSet, List
from dataclasses import dataclass
from functools import cached_property, cache
from more_itertools import zip_equal as zip
from pytools import UniqueNameGenerator
IntegralT = Union[int, np.int8, np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64]
INT_CLASSES = (int, np.int8, np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64)
ShapeComponentT = Union[IntegralT, "SizeParam"]
ShapeT = Tuple[ShapeComponentT, ...]
@dataclass(frozen=True, eq=True, repr=True)
class VeryLongAxis:
"""
Describes a dimension length which is to be assumed to be very large.
"""
# TODO: Record the threshold over which an axis could be considered as
# "VeryLong."
@dataclass(frozen=True, eq=True, repr=True)
class SizeParam:
name: str
@dataclass(frozen=True, repr=True, eq=True)
class EinsumAxisAccess(abc.ABC):
"""
Base class for axis access types in an einsum expression.
"""
@dataclass(frozen=True, repr=True, eq=True)
class FreeAxis(EinsumAxisAccess):
"""
Records the axis of an einsum argument over which contraction is not performed.
.. attribute:: output_index
Position of the corresponding index in the einsum's output.
"""
output_index: int
@dataclass(frozen=True, repr=True, eq=True)
class SummationAxis(EinsumAxisAccess):
"""
Records an index in an einsum expression over which reduction is performed.
Sometimes also referred to as an axis with a corresponding "dummy index" in
Ricci Calculus.
.. attribute:: index
An integer which is unique to a reduction index of an einsum.
"""
index: int
@dataclass(frozen=True, eq=True, repr=True)
class FusedEinsum:
"""
A fused einsum expression.
.. attribute:: shape
.. attribute:: ndim
.. automethod:: index_to_dim_length
.. automethod:: get_subscripts
"""
arg_shapes: Tuple[ShapeT, ...]
value_to_dtype: PMapT[str, np.dtype[Any]]
access_descriptors: Tuple[Tuple[EinsumAxisAccess, ...], ...]
use_matrix: Tuple[Tuple[FrozenSet[str], ...], ...]
index_names: PMapT[EinsumAxisAccess, str]
@property
def noutputs(self) -> int:
return len(self.use_matrix)
@cache
def index_to_dim_length(self) -> PMapT[EinsumAxisAccess, ShapeComponentT]:
index_to_dim = {}
for arg_shape, arg_axes in zip(self.arg_shapes,
self.access_descriptors):
for dim, index in zip(arg_shape, arg_axes):
if dim not in index_to_dim:
index_to_dim[index] = dim
else:
assert dim == index_to_dim[index]
return pmap(index_to_dim)
@cached_property
def shape(self) -> ShapeT:
free_index_to_dim = {idx: dim
for idx, dim in self.index_to_dim_length().items()
if isinstance(idx, FreeAxis)}
assert all(FreeAxis(idim) in free_index_to_dim
for idim in range(len(free_index_to_dim)))
return tuple(dim
for _, dim in sorted(free_index_to_dim.items(),
key=lambda x: x[0].output_index))
@property
def ndim(self) -> int:
return len(self.shape)
@cache
def get_subscripts(self) -> str:
"""
Returns the subscripts used in the building the *einsum* from it.
"""
return (",".join("".join(self.index_names[axis]
for axis in axes)
for axes in self.access_descriptors)
+ "->"
+ "".join(self.index_names[FreeAxis(i)]
for i in range(self.ndim))
)
def copy(self, **kwargs: Any) -> FusedEinsum:
from dataclasses import replace
return replace(self, **kwargs)
class Argument(abc.ABC):
"""
An abstract class denoting an argument to an einsum in
:class:`ContractionSchedule`. See :attr:`ContractionSchedule.arguments`.
"""
@dataclass(frozen=True, eq=True, repr=True)
class IntermediateResult(Argument):
"""
An :class:`Argument` representing an intermediate result available during
the current contraction.
"""
name: str
@dataclass(frozen=True, eq=True, repr=True)
class EinsumOperand(Argument):
"""
An :class:`Argument` representing the *ioperand*-th argument that was
passed to the parent einsum whose :class:`ContractionSchedule` is being
specified.
"""
ioperand: int
@dataclass(frozen=True, eq=True, repr=True)
class ContractionSchedule:
"""
Records the schedule in which contractions are to be performed in an einsum
as a series of einsums with the i-th einsum having subscript
``subscript[i]`` operating on ``arguments[i]`` and writing its result to
``result_names[i]``.
.. attribute:: result_names
Names of the result generated by each
.. attribute:: arguments
A :class:`tuple` containing :class:`tuple` of :class:`` for each
contraction in the schedule.
.. attribute:: nsteps
"""
subscripts: Tuple[str, ...]
result_names: Tuple[str, ...]
arguments: Tuple[Tuple[Argument, ...], ...]
def __post_init__(self) -> None:
assert len(self.subscripts) == len(self.result_names) == len(self.arguments)
@property
def nsteps(self) -> int:
"""
Returns the number of steps involved in scheduling the einsum.
"""
return len(self.subscripts)
def copy(self, **kwargs: Any) -> ContractionSchedule:
from dataclasses import replace
return replace(self, **kwargs)
def get_trivial_contraction_schedule(einsum: FusedEinsum) -> ContractionSchedule:
"""
Returns the :class:`ContractionSchedule` for *einsum* scheduled as a single
contraction.
"""
return ContractionSchedule((einsum.get_subscripts(),),
("_fe_out",),
(tuple(EinsumOperand(i)
for i, _ in enumerate(einsum.arg_shapes)),)
)
def get_opt_einsum_contraction_schedule(expr: FusedEinsum,
**opt_einsum_kwargs: Any,
) -> ContractionSchedule:
"""
Returns a :class:`ContractionSchedule` as computed by
:func:`opt_einsum.contract_path`.
:param opt_einsum_kwargs: kwargs to be passed to
:func:`opt_einsum.contract_path`.
.. note::
The following defaults are populated in *opt_einsum_kwargs*, if left
unspecified:
- ``optimize="optimal"``
- ``use_blas=False``
"""
import opt_einsum
from feinsum.make_einsum import array
long_dim_length = opt_einsum_kwargs.pop("long_dim_length", 1_000_000)
if "optimize" not in opt_einsum_kwargs:
opt_einsum_kwargs["optimize"] = "optimal"
if "use_blas" not in opt_einsum_kwargs:
opt_einsum_kwargs["use_blas"] = False
_, path = opt_einsum.contract_path(expr.get_subscripts(),
*[array([d if isinstance(op_shape,
INT_CLASSES)
else long_dim_length
for d in op_shape],
"float64")
for op_shape in expr.arg_shapes],
**opt_einsum_kwargs)
current_args: List[Argument] = [
EinsumOperand(i)
for i in range(path.input_subscripts.count(",") + 1)]
vng = UniqueNameGenerator()
subscripts: List[str] = []
result_names: List[str] = []
arguments: List[Tuple[Argument, ...]] = []
for contraction in path.contraction_list:
arg_indices, _, subscript, _, _ = contraction
arguments.append(tuple(current_args[idx]
for idx in arg_indices))
subscripts.append(subscript)
result_names.append(vng("_fe_tmp"))
current_args = ([arg
for idx, arg in enumerate(current_args)
if idx not in arg_indices]
+ [IntermediateResult(result_names[-1])])
assert len(current_args) == 1
result_names[-1] = vng("_fe_out")
return ContractionSchedule(tuple(subscripts),
tuple(result_names),
tuple(arguments)) | 0.780913 | 0.54952 |
import tensorflow as tf
from typing import Tuple
##-
def unet(input_size: Tuple[int,int,int] =(256, 256, 1)) -> tf.keras.Model:
"""Construct a basic U-Net model for baseline experiments.
Params:
input_size (tuple): image size to segment: (wodth, height, n_channels)
Return:
keras.model.Model: a Model with the basic U-Net architecture. The model is
not trained
"""
inputs = tf.keras.Input(input_size)
conv1 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(inputs)
conv1 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv1)
pool1 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv1)
conv2 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool1)
conv2 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv2)
pool2 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv2)
conv3 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool2)
conv3 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv3)
pool3 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv3)
conv4 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool3)
conv4 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv4)
drop4 = tf.keras.layers.Dropout(0.5)(conv4)
pool4 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(drop4)
conv5 = tf.keras.layers.Conv2D(1024, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool4)
conv5 = tf.keras.layers.Conv2D(1024, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv5)
drop5 = tf.keras.layers.Dropout(0.5)(conv5)
up6 = tf.keras.layers.Conv2D(512, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(drop5))
merge6 = tf.keras.layers.concatenate([drop4, up6], axis=3)
conv6 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge6)
conv6 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv6)
up7 = tf.keras.layers.Conv2D(256, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv6))
merge7 = tf.keras.layers.concatenate([conv3, up7], axis=3)
conv7 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge7)
conv7 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv7)
up8 = tf.keras.layers.Conv2D(128, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv7))
merge8 = tf.keras.layers.concatenate([conv2, up8], axis=3)
conv8 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge8)
conv8 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv8)
up9 = tf.keras.layers.Conv2D(64, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv8))
merge9 = tf.keras.layers.concatenate([conv1, up9], axis=3)
conv9 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge9)
conv9 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv9)
conv9 = tf.keras.layers.Conv2D(2, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv9)
conv10 = tf.keras.layers.Conv2D(1, 1, activation='sigmoid')(conv9)
model = tf.keras.Model(inputs=inputs, outputs=conv10)
# model.compile(optimizer=tf.keras.optimizers.Adam(lr=1e-4), loss='binary_crossentropy', metrics=['accuracy'])
# model.summary()
return model
##- | cpm/unet/basic.py | import tensorflow as tf
from typing import Tuple
##-
def unet(input_size: Tuple[int,int,int] =(256, 256, 1)) -> tf.keras.Model:
"""Construct a basic U-Net model for baseline experiments.
Params:
input_size (tuple): image size to segment: (wodth, height, n_channels)
Return:
keras.model.Model: a Model with the basic U-Net architecture. The model is
not trained
"""
inputs = tf.keras.Input(input_size)
conv1 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(inputs)
conv1 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv1)
pool1 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv1)
conv2 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool1)
conv2 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv2)
pool2 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv2)
conv3 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool2)
conv3 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv3)
pool3 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(conv3)
conv4 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool3)
conv4 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv4)
drop4 = tf.keras.layers.Dropout(0.5)(conv4)
pool4 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(drop4)
conv5 = tf.keras.layers.Conv2D(1024, 3, activation='relu', padding='same', kernel_initializer='he_normal')(pool4)
conv5 = tf.keras.layers.Conv2D(1024, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv5)
drop5 = tf.keras.layers.Dropout(0.5)(conv5)
up6 = tf.keras.layers.Conv2D(512, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(drop5))
merge6 = tf.keras.layers.concatenate([drop4, up6], axis=3)
conv6 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge6)
conv6 = tf.keras.layers.Conv2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv6)
up7 = tf.keras.layers.Conv2D(256, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv6))
merge7 = tf.keras.layers.concatenate([conv3, up7], axis=3)
conv7 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge7)
conv7 = tf.keras.layers.Conv2D(256, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv7)
up8 = tf.keras.layers.Conv2D(128, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv7))
merge8 = tf.keras.layers.concatenate([conv2, up8], axis=3)
conv8 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge8)
conv8 = tf.keras.layers.Conv2D(128, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv8)
up9 = tf.keras.layers.Conv2D(64, 2, activation='relu', padding='same', kernel_initializer='he_normal')(
tf.keras.layers.UpSampling2D(size=(2, 2))(conv8))
merge9 = tf.keras.layers.concatenate([conv1, up9], axis=3)
conv9 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(merge9)
conv9 = tf.keras.layers.Conv2D(64, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv9)
conv9 = tf.keras.layers.Conv2D(2, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv9)
conv10 = tf.keras.layers.Conv2D(1, 1, activation='sigmoid')(conv9)
model = tf.keras.Model(inputs=inputs, outputs=conv10)
# model.compile(optimizer=tf.keras.optimizers.Adam(lr=1e-4), loss='binary_crossentropy', metrics=['accuracy'])
# model.summary()
return model
##- | 0.940503 | 0.856272 |
import os
from decouple import config
import dj_database_url
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = config('SECRET_KEY')
CLIENT_ID = config('CLIENT_ID')
CLIENT_SECRET = config('CLIENT_SECRET')
GEOPOSITION_GOOGLE_MAPS_API_KEY = config('GEOPOSITION_GOOGLE_MAPS_API_KEY')
LOCATION_FIELD = {
'map.provider': 'google',
'map.zoom': 15,
'search.provider': 'google',
'provider.google.api': '//maps.google.com/maps/api/js?sensor=false',
'provider.google.api_key': config('GEOPOSITION_GOOGLE_MAPS_API_KEY'),
'provider.google.map.type': 'ROADMAP',
}
GEOPOSITION_MAP_OPTIONS = {
'minZoom': 3,
'maxZoom': 15,
}
GEOPOSITION_MARKER_OPTIONS = {
'cursor': 'move'
}
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = ['booky-ride.herokuapp.com', '127.0.0.1']
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'django.contrib.sites',
'driver.apps.DriverConfig',
'rider.apps.RiderConfig',
'bootstrap3',
'geoposition',
'cart',
]
SITE_ID = 1
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'whitenoise.middleware.WhiteNoiseMiddleware',
# Custom middleware
'booky.middleware.OnlineNowMiddleware',
]
ROOT_URLCONF = 'booky.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': ['templates'],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'booky.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.contrib.gis.db.backends.postgis',
'NAME': 'uber',
'USER': 'erick',
'PASSWORD':'<PASSWORD>',
}
}
db_from_env = dj_database_url.config(conn_max_age=500)
DATABASES['default'].update(db_from_env)
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'Africa/Nairobi'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles')
STATICFILES_DIRS = (
os.path.join(BASE_DIR, 'static'),
)
STATICFILES_STORAGE = 'whitenoise.django.GzipManifestStaticFilesStorage'
MEDIA_URL = '/media/'
MEDIA_ROOT = os.path.join(BASE_DIR, 'media') | booky/settings.py | import os
from decouple import config
import dj_database_url
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = config('SECRET_KEY')
CLIENT_ID = config('CLIENT_ID')
CLIENT_SECRET = config('CLIENT_SECRET')
GEOPOSITION_GOOGLE_MAPS_API_KEY = config('GEOPOSITION_GOOGLE_MAPS_API_KEY')
LOCATION_FIELD = {
'map.provider': 'google',
'map.zoom': 15,
'search.provider': 'google',
'provider.google.api': '//maps.google.com/maps/api/js?sensor=false',
'provider.google.api_key': config('GEOPOSITION_GOOGLE_MAPS_API_KEY'),
'provider.google.map.type': 'ROADMAP',
}
GEOPOSITION_MAP_OPTIONS = {
'minZoom': 3,
'maxZoom': 15,
}
GEOPOSITION_MARKER_OPTIONS = {
'cursor': 'move'
}
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = ['booky-ride.herokuapp.com', '127.0.0.1']
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'django.contrib.sites',
'driver.apps.DriverConfig',
'rider.apps.RiderConfig',
'bootstrap3',
'geoposition',
'cart',
]
SITE_ID = 1
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'whitenoise.middleware.WhiteNoiseMiddleware',
# Custom middleware
'booky.middleware.OnlineNowMiddleware',
]
ROOT_URLCONF = 'booky.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': ['templates'],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'booky.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.contrib.gis.db.backends.postgis',
'NAME': 'uber',
'USER': 'erick',
'PASSWORD':'<PASSWORD>',
}
}
db_from_env = dj_database_url.config(conn_max_age=500)
DATABASES['default'].update(db_from_env)
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'Africa/Nairobi'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles')
STATICFILES_DIRS = (
os.path.join(BASE_DIR, 'static'),
)
STATICFILES_STORAGE = 'whitenoise.django.GzipManifestStaticFilesStorage'
MEDIA_URL = '/media/'
MEDIA_ROOT = os.path.join(BASE_DIR, 'media') | 0.376738 | 0.067886 |
import unittest
from language_detector import detect_language
from language_detector.languages import LANGUAGES
class TestLanguageDetector(unittest.TestCase):
def test_detect_language_spanish(self):
text = """
<NAME> (Rosario, 24 de junio de 1987),
conocido como <NAME>, es un futbolista argentino11 que juega
como delantero en el Fútbol Club Barcelona y en la selección
argentina, de la que es capitán. Considerado con frecuencia el
mejor jugador del mundo y calificado en el ámbito deportivo como el
más grande de todos los tiempos, Messi es el único futbolista en la
historia que ha ganado cinco veces el FIFA Balón de Oro –cuatro de
ellos en forma consecutiva– y el primero en
recibir tres Botas de Oro.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'Spanish')
def test_detect_language_german(self):
text = """
Messi spielt seit seinem 14. Lebensjahr für den FC Barcelona.
Mit 24 Jahren wurde er Rekordtorschütze des FC Barcelona, mit 25
der jüngste Spieler in der La-Liga-Geschichte, der 200 Tore
erzielte. Inzwischen hat Messi als einziger Spieler mehr als 300
Erstligatore erzielt und ist damit Rekordtorschütze
der Primera División.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'German')
def test_detect_language_mixed_languages(self):
text = """
# spanish
<NAME> (Rosario, 24 de junio de 1987),
conocido como <NAME>, es un futbolista argentino11 que juega
como delantero en el Fútbol Club Barcelona y en la selección
argentina, de la que es capitán.
# german
Messi spielt seit seinem 14. Lebensjahr für den FC Barcelona.
Mit 24 Jahren wurde er Rekordtorschütze des FC Barcelona, mit 25
der jüngste Spieler in der La-Liga-Geschichte, der 200 Tore
erzielte.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'Spanish')
def test_detect_language_english(self):
# NOTE: You will first need to define a new "English" language
# in the languages.py module.
text = """
# english
<NAME> 'Leo' Messi is an Argentine professional footballer
who plays as a forward for Spanish club FC Barcelona and the
Argentina national team. Often considered the best player in the
world and rated by many in the sport as the greatest of all time,
Messi is the only football player in history to win five FIFA
Ballons, four of which he won consecutively, and the first player
to win three European Golden Shoes.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'English') | tests/test_main.py | import unittest
from language_detector import detect_language
from language_detector.languages import LANGUAGES
class TestLanguageDetector(unittest.TestCase):
def test_detect_language_spanish(self):
text = """
<NAME> (Rosario, 24 de junio de 1987),
conocido como <NAME>, es un futbolista argentino11 que juega
como delantero en el Fútbol Club Barcelona y en la selección
argentina, de la que es capitán. Considerado con frecuencia el
mejor jugador del mundo y calificado en el ámbito deportivo como el
más grande de todos los tiempos, Messi es el único futbolista en la
historia que ha ganado cinco veces el FIFA Balón de Oro –cuatro de
ellos en forma consecutiva– y el primero en
recibir tres Botas de Oro.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'Spanish')
def test_detect_language_german(self):
text = """
Messi spielt seit seinem 14. Lebensjahr für den FC Barcelona.
Mit 24 Jahren wurde er Rekordtorschütze des FC Barcelona, mit 25
der jüngste Spieler in der La-Liga-Geschichte, der 200 Tore
erzielte. Inzwischen hat Messi als einziger Spieler mehr als 300
Erstligatore erzielt und ist damit Rekordtorschütze
der Primera División.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'German')
def test_detect_language_mixed_languages(self):
text = """
# spanish
<NAME> (Rosario, 24 de junio de 1987),
conocido como <NAME>, es un futbolista argentino11 que juega
como delantero en el Fútbol Club Barcelona y en la selección
argentina, de la que es capitán.
# german
Messi spielt seit seinem 14. Lebensjahr für den FC Barcelona.
Mit 24 Jahren wurde er Rekordtorschütze des FC Barcelona, mit 25
der jüngste Spieler in der La-Liga-Geschichte, der 200 Tore
erzielte.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'Spanish')
def test_detect_language_english(self):
# NOTE: You will first need to define a new "English" language
# in the languages.py module.
text = """
# english
<NAME> 'Leo' Messi is an Argentine professional footballer
who plays as a forward for Spanish club FC Barcelona and the
Argentina national team. Often considered the best player in the
world and rated by many in the sport as the greatest of all time,
Messi is the only football player in history to win five FIFA
Ballons, four of which he won consecutively, and the first player
to win three European Golden Shoes.
"""
result = detect_language(text, LANGUAGES)
self.assertEqual(result, 'English') | 0.416441 | 0.511595 |
import torch
import torch.nn as nn
from torch.autograd import Function
import torch.nn.functional as F
import torch.nn.init as init
from torch.autograd import Variable
import math
class NormalizeLayer(torch.nn.Module):
"""Standardize the channels of a batch of images by subtracting the dataset mean
and dividing by the dataset standard deviation.
"""
def __init__(self, means, sds):
"""
:param means: the channel means
:param sds: the channel standard deviations
"""
super(NormalizeLayer, self).__init__()
self.means = torch.tensor(means).cuda()
self.sds = torch.tensor(sds).cuda()
def forward(self, input):
(batch_size, num_channels, height, width) = input.shape
means = self.means.repeat((batch_size, height, width, 1)).permute(0, 3, 1, 2)
sds = self.sds.repeat((batch_size, height, width, 1)).permute(0, 3, 1, 2)
return (input - means)/sds
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_planes, planes, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(
in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm2d(self.expansion*planes)
)
def forward(self, x):
out = F.relu(self.bn1(self.conv1(x)))
out = self.bn2(self.conv2(out))
out += self.shortcut(x)
out = F.relu(out)
return out
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, in_planes, planes, stride=1):
super(Bottleneck, self).__init__()
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3,
stride=stride, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.conv3 = nn.Conv2d(planes, self.expansion *
planes, kernel_size=1, bias=False)
self.bn3 = nn.BatchNorm2d(self.expansion*planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm2d(self.expansion*planes)
)
def forward(self, x):
out = F.relu(self.bn1(self.conv1(x)))
out = F.relu(self.bn2(self.conv2(out)))
out = self.bn3(self.conv3(out))
out += self.shortcut(x)
out = F.relu(out)
return out
class ResNet(nn.Module):
# ResNet34
def __init__(self, means, sds, block=BasicBlock, num_blocks=[3, 4, 6, 3], num_classes=10):
super(ResNet, self).__init__()
self.normalize_layer = NormalizeLayer(means, sds)
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(64)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
self.linear = nn.Linear(512*block.expansion, num_classes)
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1]*(num_blocks-1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def get_feature(self, x):
out = self.normalize_layer(x)
out = F.relu(self.bn1(self.conv1(out)))
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
out = out.view(out.size(0), -1)
return out
def forward(self, x):
out = self.normalize_layer(x)
out = F.relu(self.bn1(self.conv1(out)))
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
out = out.view(out.size(0), -1)
out = self.linear(out)
return out | RMC/models/resnet.py | import torch
import torch.nn as nn
from torch.autograd import Function
import torch.nn.functional as F
import torch.nn.init as init
from torch.autograd import Variable
import math
class NormalizeLayer(torch.nn.Module):
"""Standardize the channels of a batch of images by subtracting the dataset mean
and dividing by the dataset standard deviation.
"""
def __init__(self, means, sds):
"""
:param means: the channel means
:param sds: the channel standard deviations
"""
super(NormalizeLayer, self).__init__()
self.means = torch.tensor(means).cuda()
self.sds = torch.tensor(sds).cuda()
def forward(self, input):
(batch_size, num_channels, height, width) = input.shape
means = self.means.repeat((batch_size, height, width, 1)).permute(0, 3, 1, 2)
sds = self.sds.repeat((batch_size, height, width, 1)).permute(0, 3, 1, 2)
return (input - means)/sds
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_planes, planes, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(
in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm2d(self.expansion*planes)
)
def forward(self, x):
out = F.relu(self.bn1(self.conv1(x)))
out = self.bn2(self.conv2(out))
out += self.shortcut(x)
out = F.relu(out)
return out
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, in_planes, planes, stride=1):
super(Bottleneck, self).__init__()
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3,
stride=stride, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.conv3 = nn.Conv2d(planes, self.expansion *
planes, kernel_size=1, bias=False)
self.bn3 = nn.BatchNorm2d(self.expansion*planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm2d(self.expansion*planes)
)
def forward(self, x):
out = F.relu(self.bn1(self.conv1(x)))
out = F.relu(self.bn2(self.conv2(out)))
out = self.bn3(self.conv3(out))
out += self.shortcut(x)
out = F.relu(out)
return out
class ResNet(nn.Module):
# ResNet34
def __init__(self, means, sds, block=BasicBlock, num_blocks=[3, 4, 6, 3], num_classes=10):
super(ResNet, self).__init__()
self.normalize_layer = NormalizeLayer(means, sds)
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(64)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
self.linear = nn.Linear(512*block.expansion, num_classes)
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1]*(num_blocks-1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def get_feature(self, x):
out = self.normalize_layer(x)
out = F.relu(self.bn1(self.conv1(out)))
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
out = out.view(out.size(0), -1)
return out
def forward(self, x):
out = self.normalize_layer(x)
out = F.relu(self.bn1(self.conv1(out)))
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
out = out.view(out.size(0), -1)
out = self.linear(out)
return out | 0.964111 | 0.73137 |
import datetime
import webparser
import puzzleraw
import wordmatch
class Puzzle:
def __init__(self, date="", psid=""):
now = datetime.datetime.now()
if len(date) is 0:
date = str(now.year) + "-" + str(now.month) + "-" + str(now.day)
if len(psid) is 0:
psid = "100000252"
self.date = date
url = "https://data.puzzlexperts.com/puzzleapp/data.php?psid=" + psid + "&date=" + date
array = webparser.WebParser(url).parse_to_array()
raw = puzzleraw.PuzzleRaw(array)
pairs = raw.make_pairs()
self.scheme = pairs[0]
self.words = pairs[1]
"""
Finds occurrences of the character in a line
"""
@staticmethod
def find_indexes(line, char):
indexes = []
for i in range(0, len(line)):
if line[i] is char:
indexes.append(i)
return indexes
"""
Finds occurrences of the character in the grid
"""
def find_occurrences(self, char):
loc = []
for i in range(len(self.scheme)):
loc.append([i, self.find_indexes(self.scheme[i], char)])
return loc
"""
Returns adjacent slots (relative to a slot)
"""
def get_near(self, index, line_index):
scheme = self.scheme
near = []
index_not_first = index > 0
index_not_last = len(scheme) > line_index and index < len(scheme[line_index]) - 1
line_not_first = line_index > 0
line_not_last = line_index < len(scheme) - 1
if index_not_first:
near.append([index - 1, line_index, "left"])
if index_not_last:
near.append([index + 1, line_index, "right"])
if line_not_first:
near.append([index, line_index - 1, "up"])
if index_not_first:
near.append([index - 1, line_index - 1, "up,left"])
if index_not_last:
near.append([index + 1, line_index - 1, "up,right"])
if line_not_last:
near.append([index, line_index + 1, "down"])
if index_not_first:
near.append([index - 1, line_index + 1, "down,left"])
if index_not_last:
near.append([index + 1, line_index + 1, "down,right"])
return near
"""
Finds occurrences of the character in the adjacent slots (relative to a slot)
"""
def find_near_occurrences(self, char, index, line_index):
occurrences = []
for near in self.get_near(index, line_index):
if self.scheme[near[1]][near[0]] is char:
occurrences.append(near)
return occurrences
"""
Finds occurrences of string given a direction and a location
"""
def match_word_part(self, word_part, index, line_index, direction):
if len(word_part) is 1:
return [index, line_index]
word_part = word_part[1:len(word_part)]
switch = {
"left": [line_index, index - 1],
"right": [line_index, index + 1],
"up": [line_index - 1, index],
"up,left": [line_index - 1, index - 1],
"up,right": [line_index - 1, index + 1],
"down": [line_index + 1, index],
"down,left": [line_index + 1, index - 1],
"down,right": [line_index + 1, index + 1]
}
next_loc = switch[direction]
try:
slot = self.scheme[next_loc[0]][next_loc[1]]
return self.match_word_part(word_part, next_loc[1], next_loc[0], direction) if slot is word_part[0] else False
except IndexError:
return False
"""
Finds the word inside of the grid
"""
def match(self, word):
if word[0] is " ":
word = word[1:len(word)]
formatted_word = word.replace(" ", "")
first_char = formatted_word[0]
for occurrence in self.find_occurrences(first_char):
line_index = occurrence[0]
for index in occurrence[1]:
for near in self.find_near_occurrences(formatted_word[1], index, line_index):
match = self.match_word_part(formatted_word, index, occurrence[0], near[2])
if match:
return wordmatch.WordMatch(word, [index, line_index], [match[0], match[1]], near[2]) | puzzle.py | import datetime
import webparser
import puzzleraw
import wordmatch
class Puzzle:
def __init__(self, date="", psid=""):
now = datetime.datetime.now()
if len(date) is 0:
date = str(now.year) + "-" + str(now.month) + "-" + str(now.day)
if len(psid) is 0:
psid = "100000252"
self.date = date
url = "https://data.puzzlexperts.com/puzzleapp/data.php?psid=" + psid + "&date=" + date
array = webparser.WebParser(url).parse_to_array()
raw = puzzleraw.PuzzleRaw(array)
pairs = raw.make_pairs()
self.scheme = pairs[0]
self.words = pairs[1]
"""
Finds occurrences of the character in a line
"""
@staticmethod
def find_indexes(line, char):
indexes = []
for i in range(0, len(line)):
if line[i] is char:
indexes.append(i)
return indexes
"""
Finds occurrences of the character in the grid
"""
def find_occurrences(self, char):
loc = []
for i in range(len(self.scheme)):
loc.append([i, self.find_indexes(self.scheme[i], char)])
return loc
"""
Returns adjacent slots (relative to a slot)
"""
def get_near(self, index, line_index):
scheme = self.scheme
near = []
index_not_first = index > 0
index_not_last = len(scheme) > line_index and index < len(scheme[line_index]) - 1
line_not_first = line_index > 0
line_not_last = line_index < len(scheme) - 1
if index_not_first:
near.append([index - 1, line_index, "left"])
if index_not_last:
near.append([index + 1, line_index, "right"])
if line_not_first:
near.append([index, line_index - 1, "up"])
if index_not_first:
near.append([index - 1, line_index - 1, "up,left"])
if index_not_last:
near.append([index + 1, line_index - 1, "up,right"])
if line_not_last:
near.append([index, line_index + 1, "down"])
if index_not_first:
near.append([index - 1, line_index + 1, "down,left"])
if index_not_last:
near.append([index + 1, line_index + 1, "down,right"])
return near
"""
Finds occurrences of the character in the adjacent slots (relative to a slot)
"""
def find_near_occurrences(self, char, index, line_index):
occurrences = []
for near in self.get_near(index, line_index):
if self.scheme[near[1]][near[0]] is char:
occurrences.append(near)
return occurrences
"""
Finds occurrences of string given a direction and a location
"""
def match_word_part(self, word_part, index, line_index, direction):
if len(word_part) is 1:
return [index, line_index]
word_part = word_part[1:len(word_part)]
switch = {
"left": [line_index, index - 1],
"right": [line_index, index + 1],
"up": [line_index - 1, index],
"up,left": [line_index - 1, index - 1],
"up,right": [line_index - 1, index + 1],
"down": [line_index + 1, index],
"down,left": [line_index + 1, index - 1],
"down,right": [line_index + 1, index + 1]
}
next_loc = switch[direction]
try:
slot = self.scheme[next_loc[0]][next_loc[1]]
return self.match_word_part(word_part, next_loc[1], next_loc[0], direction) if slot is word_part[0] else False
except IndexError:
return False
"""
Finds the word inside of the grid
"""
def match(self, word):
if word[0] is " ":
word = word[1:len(word)]
formatted_word = word.replace(" ", "")
first_char = formatted_word[0]
for occurrence in self.find_occurrences(first_char):
line_index = occurrence[0]
for index in occurrence[1]:
for near in self.find_near_occurrences(formatted_word[1], index, line_index):
match = self.match_word_part(formatted_word, index, occurrence[0], near[2])
if match:
return wordmatch.WordMatch(word, [index, line_index], [match[0], match[1]], near[2]) | 0.4856 | 0.392977 |
import os
import requests
import time
from tests.integration import TestsBase
from tests.integration.test_file_storage import VALID_KML, NOT_WELL_FORMED_KML
class TestVarnish(TestsBase):
''' Testing the Varnish 'security' configuration. As some settings are IP address dependant,
we use an external HTTP Proxy to make the queries.
'''
def hash(self, bits=96):
assert bits % 8 == 0
return os.urandom(bits / 8).encode('hex')
def timestamp(self):
return int(round(time.time() * 1000.0))
def setUp(self):
super(TestVarnish, self).setUp()
self.registry = self.testapp.app.registry
try:
os.environ["http_proxy"] = self.registry.settings['http_proxy']
self.api_url = 'http:%s' % self.registry.settings['api_url']
self.alti_url = 'http:%s' % self.registry.settings['alti_url']
self.wmts_public_host = 'http://' + self.registry.settings['wmts_public_host'] + '/'
except KeyError as e:
raise e
def tearDown(self):
if "http_proxy" in os.environ:
del os.environ["http_proxy"]
super(TestVarnish, self).tearDown()
def has_geometric_attributes(self, attrs):
geometric_attrs = ['x', 'y', 'lon', 'lat', 'geom_st_box2d']
return len(set(geometric_attrs).intersection(attrs)) > 0
class TestHeight(TestVarnish):
def test_height_no_referer(self):
payload = {'easting': 600000.0, 'northing': 200000.0, '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/height', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_height_good_referer(self):
payload = {'easting': 600000.0, 'northing': 200000.0, '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/height', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestProfile(TestVarnish):
def test_profile_json_no_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/profile.json', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_profile_json_good_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/profile.json', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
def test_profile_csv_no_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/profile.csv', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_profile_csv_good_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/profile.csv', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestMapproxyGetTile(TestVarnish):
''' See https://github.com/geoadmin/mf-chsdi3/issues/873
'''
def test_mapproxy_no_referer(self):
payload = {'_id': self.hash()}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_mapproxy_bad_referer(self):
payload = {'_id': self.hash()}
headers = {'referer': 'http://gooffy-referer.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers=headers)
self.assertEqual(resp.status_code, 403)
def test_mapproxy_good_referer(self):
payload = {'_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestFilestorage(TestVarnish):
def test_post_filestorage_no_referer(self):
resp = requests.post(self.api_url + '/files', VALID_KML, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_post_filestorage_good_referer(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 200)
self.assertIn('adminId', resp.json())
self.assertIn('fileId', resp.json())
def test_post_filestorage_wrong_referer(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://foo.bar', 'User-Agent': 'mf-geaodmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 403)
def test_post_filestorage_wrong_content_type(self):
headers = {'Content-Type': 'application/xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 415)
def test_post_filestorage_not_well_formed(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', NOT_WELL_FORMED_KML, headers=headers)
self.assertEqual(resp.status_code, 415)
def test_post_filestorage_too_big(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
current_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(current_dir, '../integration', 'big.kml')) as f:
data = f.read()
resp = requests.post(self.api_url + '/files', data, headers=headers)
self.assertEqual(resp.status_code, 413) | tests/e2e/test_varnish.py |
import os
import requests
import time
from tests.integration import TestsBase
from tests.integration.test_file_storage import VALID_KML, NOT_WELL_FORMED_KML
class TestVarnish(TestsBase):
''' Testing the Varnish 'security' configuration. As some settings are IP address dependant,
we use an external HTTP Proxy to make the queries.
'''
def hash(self, bits=96):
assert bits % 8 == 0
return os.urandom(bits / 8).encode('hex')
def timestamp(self):
return int(round(time.time() * 1000.0))
def setUp(self):
super(TestVarnish, self).setUp()
self.registry = self.testapp.app.registry
try:
os.environ["http_proxy"] = self.registry.settings['http_proxy']
self.api_url = 'http:%s' % self.registry.settings['api_url']
self.alti_url = 'http:%s' % self.registry.settings['alti_url']
self.wmts_public_host = 'http://' + self.registry.settings['wmts_public_host'] + '/'
except KeyError as e:
raise e
def tearDown(self):
if "http_proxy" in os.environ:
del os.environ["http_proxy"]
super(TestVarnish, self).tearDown()
def has_geometric_attributes(self, attrs):
geometric_attrs = ['x', 'y', 'lon', 'lat', 'geom_st_box2d']
return len(set(geometric_attrs).intersection(attrs)) > 0
class TestHeight(TestVarnish):
def test_height_no_referer(self):
payload = {'easting': 600000.0, 'northing': 200000.0, '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/height', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_height_good_referer(self):
payload = {'easting': 600000.0, 'northing': 200000.0, '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/height', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestProfile(TestVarnish):
def test_profile_json_no_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/profile.json', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_profile_json_good_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/profile.json', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
def test_profile_csv_no_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
resp = requests.get(self.alti_url + '/rest/services/profile.csv', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_profile_csv_good_referer(self):
payload = {'geom': '{"type":"LineString","coordinates":[[550050,206550],[556950,204150],[561050,207950]]}', '_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.alti_url + '/rest/services/profile.csv', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestMapproxyGetTile(TestVarnish):
''' See https://github.com/geoadmin/mf-chsdi3/issues/873
'''
def test_mapproxy_no_referer(self):
payload = {'_id': self.hash()}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_mapproxy_bad_referer(self):
payload = {'_id': self.hash()}
headers = {'referer': 'http://gooffy-referer.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers=headers)
self.assertEqual(resp.status_code, 403)
def test_mapproxy_good_referer(self):
payload = {'_id': self.hash()}
headers = {'referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.get(self.wmts_public_host + '/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/13/4265/2883.jpeg', params=payload, headers=headers)
self.assertEqual(resp.status_code, 200)
class TestFilestorage(TestVarnish):
def test_post_filestorage_no_referer(self):
resp = requests.post(self.api_url + '/files', VALID_KML, headers={'User-Agent': 'mf-geoadmin/python'})
self.assertEqual(resp.status_code, 403)
def test_post_filestorage_good_referer(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 200)
self.assertIn('adminId', resp.json())
self.assertIn('fileId', resp.json())
def test_post_filestorage_wrong_referer(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://foo.bar', 'User-Agent': 'mf-geaodmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 403)
def test_post_filestorage_wrong_content_type(self):
headers = {'Content-Type': 'application/xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', VALID_KML, headers=headers)
self.assertEqual(resp.status_code, 415)
def test_post_filestorage_not_well_formed(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
resp = requests.post(self.api_url + '/files', NOT_WELL_FORMED_KML, headers=headers)
self.assertEqual(resp.status_code, 415)
def test_post_filestorage_too_big(self):
headers = {'Content-Type': 'application/vnd.google-earth.kml+xml', 'Referer': 'http://unittest.geo.admin.ch', 'User-Agent': 'mf-geoadmin/python'}
current_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(current_dir, '../integration', 'big.kml')) as f:
data = f.read()
resp = requests.post(self.api_url + '/files', data, headers=headers)
self.assertEqual(resp.status_code, 413) | 0.470737 | 0.174059 |
import re
import json
from collections import defaultdict
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector
from scrapy.http import Request, HtmlResponse, FormRequest
from scrapy.utils.response import get_base_url
from scrapy.utils.url import urljoin_rfc
from product_spiders.items import Product, ProductLoaderWithNameStrip as ProductLoader
from product_spiders.utils import extract_price
class TranscatSpider(BaseSpider):
name = 'transcat.com'
allowed_domains = ['transcat.com']
start_urls = ('http://www.transcat.com/Catalog/default.aspx',)
start_urls = ('http://www.transcat.com/Catalog/ProductSearch.aspx?SearchType=Combo&Mfg=&Cat=CL&SubCat=',)
def __init__(self, *args, **kwargs):
super(TranscatSpider, self).__init__(*args, **kwargs)
self.page_seen = defaultdict(dict)
def parse(self, response):
hxs = HtmlXPathSelector(response)
if response.url == self.start_urls[0]:
cats = hxs.select('//td[@class="catalog-list"]/strong/a/@href').extract()
for cat in cats:
yield Request(urljoin_rfc(get_base_url(response), cat))
pages = set(hxs.select('//tr[@class="Numbering"]//a/@href').re('_doPostBack\(.*,.*(Page\$\d+).*\)'))
for page in pages:
if not page in self.page_seen[response.url]:
self.page_seen[response.url][page] = True
r = FormRequest.from_response(response, formname='aspnetForm',
formdata={'__EVENTTARGET': 'ctl00$ContentPlaceHolderMiddle$TabContainer1$TabPanel2$grdSearch',
'__EVENTARGUMENT': page}, dont_click=True)
yield r
for product in self.parse_products(hxs, response):
yield product
def parse_products(self, hxs, response):
products = hxs.select('//table[@class="SearchGrid"]//td/a[contains(@href, "productdetail.aspx")]/../..')
for product in products:
loader = ProductLoader(item=Product(), selector=product)
url = product.select('.//a[contains(@href, "productdetail.aspx")]/@href').extract()[0]
url = urljoin_rfc(get_base_url(response), url)
loader.add_value('url', url)
loader.add_xpath('name', './/td[position() = 2]//a[contains(@href, "productdetail.aspx")]/text()')
loader.add_xpath('price', './/td[position() = 3]//text()')
yield loader.load_item() | portfolio/Python/scrapy/instrumart/transcat.py | import re
import json
from collections import defaultdict
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector
from scrapy.http import Request, HtmlResponse, FormRequest
from scrapy.utils.response import get_base_url
from scrapy.utils.url import urljoin_rfc
from product_spiders.items import Product, ProductLoaderWithNameStrip as ProductLoader
from product_spiders.utils import extract_price
class TranscatSpider(BaseSpider):
name = 'transcat.com'
allowed_domains = ['transcat.com']
start_urls = ('http://www.transcat.com/Catalog/default.aspx',)
start_urls = ('http://www.transcat.com/Catalog/ProductSearch.aspx?SearchType=Combo&Mfg=&Cat=CL&SubCat=',)
def __init__(self, *args, **kwargs):
super(TranscatSpider, self).__init__(*args, **kwargs)
self.page_seen = defaultdict(dict)
def parse(self, response):
hxs = HtmlXPathSelector(response)
if response.url == self.start_urls[0]:
cats = hxs.select('//td[@class="catalog-list"]/strong/a/@href').extract()
for cat in cats:
yield Request(urljoin_rfc(get_base_url(response), cat))
pages = set(hxs.select('//tr[@class="Numbering"]//a/@href').re('_doPostBack\(.*,.*(Page\$\d+).*\)'))
for page in pages:
if not page in self.page_seen[response.url]:
self.page_seen[response.url][page] = True
r = FormRequest.from_response(response, formname='aspnetForm',
formdata={'__EVENTTARGET': 'ctl00$ContentPlaceHolderMiddle$TabContainer1$TabPanel2$grdSearch',
'__EVENTARGUMENT': page}, dont_click=True)
yield r
for product in self.parse_products(hxs, response):
yield product
def parse_products(self, hxs, response):
products = hxs.select('//table[@class="SearchGrid"]//td/a[contains(@href, "productdetail.aspx")]/../..')
for product in products:
loader = ProductLoader(item=Product(), selector=product)
url = product.select('.//a[contains(@href, "productdetail.aspx")]/@href').extract()[0]
url = urljoin_rfc(get_base_url(response), url)
loader.add_value('url', url)
loader.add_xpath('name', './/td[position() = 2]//a[contains(@href, "productdetail.aspx")]/text()')
loader.add_xpath('price', './/td[position() = 3]//text()')
yield loader.load_item() | 0.275714 | 0.072472 |
import numpy as np
from scipy import ndimage as nd
from nilabels.tools.aux_methods.utils_nib import set_new_data
def contour_from_array_at_label(im_arr, lab, thr=0.3, omit_axis=None, verbose=0):
"""
Get the contour of a single label
:param im_arr: input array with segmentation
:param lab: considered label
:param thr: threshold (default 0.3) increase to increase the contour thickness.
:param omit_axis: a directional axis preference for the contour creation, to avoid "walls" when scrolling
the 3d image in a particular direction. None if no preference axis is expected.
:param verbose:
:return: boolean mask with the array labels.
"""
if verbose > 0:
print('Getting contour for label {}'.format(lab))
array_label_l = im_arr == lab
assert isinstance(array_label_l, np.ndarray)
gra = np.gradient(array_label_l.astype(np.bool).astype(np.float64))
if omit_axis is None:
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[1] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'x':
thresholded_gra = np.sqrt(gra[1] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'y':
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'z':
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[1] ** 2) > thr
else:
raise IOError
return thresholded_gra
def contour_from_segmentation(im_segm, omit_axis=None, verbose=0):
"""
From an input nibabel image segmentation, returns the contour of each segmented region with the original
label.
:param im_segm:
:param omit_axis: a directional axis preference for the contour creation, to avoid "walls" when scrolling
the 3d image in a particular direction. None if no preference axis is expected.
:param verbose: 0 no, 1 yes.
:return: return the contour of the provided segmentation
"""
list_labels = sorted(list(set(im_segm.get_data().flat)))[1:]
output_arr = np.zeros_like(im_segm.get_data(), dtype=im_segm.get_data_dtype())
for la in list_labels:
output_arr += contour_from_array_at_label(im_segm.get_data(), la, omit_axis=omit_axis, verbose=verbose)
return set_new_data(im_segm, output_arr.astype(np.bool) * im_segm.get_data(), new_dtype=im_segm.get_data_dtype())
def get_xyz_borders_of_a_label(segm_arr, label):
"""
:param segm_arr: array representing a segmentation
:param label: a single integer label
:return: box coordinates containing the given label in the segmentation, None if the label is not present.
"""
assert segm_arr.ndim == 3
if label not in segm_arr:
return None
X, Y, Z = np.where(segm_arr == label)
return [np.min(X), np.max(X), np.min(Y), np.max(Y), np.min(Z), np.max(Z)]
def get_internal_contour_with_erosion_at_label(segm_arr, lab, thickness=1):
"""
Get the internal contour for a given thickness.
:param segm_arr: input segmentation where to extract the contour
:param lab: label to extract the contour
:param thickness: final thickness of the segmentation
:return: image with only the contour of the given input image.
"""
im_lab = segm_arr == lab
return (im_lab ^ nd.morphology.binary_erosion(im_lab, iterations=thickness).astype(np.bool)).astype(segm_arr.dtype) * lab | nilabels/tools/detections/contours.py | import numpy as np
from scipy import ndimage as nd
from nilabels.tools.aux_methods.utils_nib import set_new_data
def contour_from_array_at_label(im_arr, lab, thr=0.3, omit_axis=None, verbose=0):
"""
Get the contour of a single label
:param im_arr: input array with segmentation
:param lab: considered label
:param thr: threshold (default 0.3) increase to increase the contour thickness.
:param omit_axis: a directional axis preference for the contour creation, to avoid "walls" when scrolling
the 3d image in a particular direction. None if no preference axis is expected.
:param verbose:
:return: boolean mask with the array labels.
"""
if verbose > 0:
print('Getting contour for label {}'.format(lab))
array_label_l = im_arr == lab
assert isinstance(array_label_l, np.ndarray)
gra = np.gradient(array_label_l.astype(np.bool).astype(np.float64))
if omit_axis is None:
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[1] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'x':
thresholded_gra = np.sqrt(gra[1] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'y':
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[2] ** 2) > thr
elif omit_axis == 'z':
thresholded_gra = np.sqrt(gra[0] ** 2 + gra[1] ** 2) > thr
else:
raise IOError
return thresholded_gra
def contour_from_segmentation(im_segm, omit_axis=None, verbose=0):
"""
From an input nibabel image segmentation, returns the contour of each segmented region with the original
label.
:param im_segm:
:param omit_axis: a directional axis preference for the contour creation, to avoid "walls" when scrolling
the 3d image in a particular direction. None if no preference axis is expected.
:param verbose: 0 no, 1 yes.
:return: return the contour of the provided segmentation
"""
list_labels = sorted(list(set(im_segm.get_data().flat)))[1:]
output_arr = np.zeros_like(im_segm.get_data(), dtype=im_segm.get_data_dtype())
for la in list_labels:
output_arr += contour_from_array_at_label(im_segm.get_data(), la, omit_axis=omit_axis, verbose=verbose)
return set_new_data(im_segm, output_arr.astype(np.bool) * im_segm.get_data(), new_dtype=im_segm.get_data_dtype())
def get_xyz_borders_of_a_label(segm_arr, label):
"""
:param segm_arr: array representing a segmentation
:param label: a single integer label
:return: box coordinates containing the given label in the segmentation, None if the label is not present.
"""
assert segm_arr.ndim == 3
if label not in segm_arr:
return None
X, Y, Z = np.where(segm_arr == label)
return [np.min(X), np.max(X), np.min(Y), np.max(Y), np.min(Z), np.max(Z)]
def get_internal_contour_with_erosion_at_label(segm_arr, lab, thickness=1):
"""
Get the internal contour for a given thickness.
:param segm_arr: input segmentation where to extract the contour
:param lab: label to extract the contour
:param thickness: final thickness of the segmentation
:return: image with only the contour of the given input image.
"""
im_lab = segm_arr == lab
return (im_lab ^ nd.morphology.binary_erosion(im_lab, iterations=thickness).astype(np.bool)).astype(segm_arr.dtype) * lab | 0.870556 | 0.799873 |
import ast
import requests
import configparser
from flask import Flask, request, jsonify, render_template
from flask import Flask, request
from flask_cors import CORS, cross_origin
app = Flask(__name__)
CORS(app)
a = 5.0
b = 5.0
c = 5.0
d = 5.0
e = 5.0
f = 5.0
g = 5.0
h = 5.0
i = 5.0
j = 5.0
k = 5.0
l = 5.0
m = 5.0
n = 5.0
o = 5.0
p = 5.0
q = 5.0
r = 5.0
av = 0.0
def refresh_average():
global av
av = (a + b + c + d + e + f + g + h +
i + j + k + l + m + n + o + p +
q + r) / 18 / 10
if av > 1:
av = 1.0
return av
elif av < 0:
av = 0
else:
return av
def parse_webhook(webhook_data):
data = ast.literal_eval(webhook_data)
return data
@app.route('/', methods=['GET'])
@cross_origin()
def index():
if request.method == 'GET':
print('Here is the current av')
return jsonify({'_result': str(refresh_average())})
else:
return {"code": "success"}
@app.route('/rsi_h', methods=['POST'])
@cross_origin()
def rsi_h():
if request.method == 'POST':
print('rsi sell alert received')
global a
global c
a = 10
c = 5
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
return {"code": "success"}
@app.route('/rsi_l', methods=['POST'])
@cross_origin()
def rsi_l():
if request.method == 'POST':
print('rsi buy alert received')
global c
global a
c = 0
a = 5
refresh_average()
return {"code": "success"}
else:
return {"code": "success"}
@app.route('/rsi_mfi_h', methods=['POST'])
@cross_origin()
def api_rsi_mfi_h_trigger():
if request.method == 'POST':
print('rsi sell alert received')
global d
global e
d = 15
e = 5
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/rsi_mfi_l', methods=['POST'])
@cross_origin()
def api_rsi_mfi_l_trigger():
if request.method == 'POST':
print('rsi buy alert received')
global e
global d
d = 5
e = -5
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_h', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_h_trigger():
if request.method == 'POST':
print('stoch sell alert received')
global f
global g
g = 5
f = 20
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_l', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_l_trigger():
if request.method == 'POST':
print('stoch buy alert received')
global g
global f
f = 5
g = -10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_mu', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_mu_trigger():
if request.method == 'POST':
print('stoch buy alert received')
global h
global i
i = 5
h = 0
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_md', methods=['POST'])
def api_rsi_stoch_k_md_trigger():
if request.method == 'POST':
print('stoch sell alert received')
global i
global h
h = 5
i = 10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_diamond', methods=['POST'])
def api_rsi_sell_diamond_trigger():
if request.method == 'POST':
print('sell diamond alert received')
global j
global k
k = 5
j = 30
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_diamond', methods=['POST'])
def api_rsi_buy_diamond_trigger():
if request.method == 'POST':
print('buy diamond alert received')
global k
global j
global r
r = 5
j = 5
k = -20
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle', methods=['POST'])
def api_rsi_sell_red_circle_trigger():
if request.method == 'POST':
print('sell alert recieved')
global l
global k
global n
k = 5
n = 5
l = 12
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle_5m', methods=['POST'])
def api_rsi_sell_red_circle_5_trigger():
if request.method == 'POST':
print('sell alert recieved')
global m
global o
o = 5
m = 10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle', methods=['POST'])
def api_rsi_buy_green_circle_trigger():
if request.method == 'POST':
print('buy alert recieved')
global n
global l
global j
j = 5
l = 5
n = -2
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle_5', methods=['POST'])
def api_rsi_buy_green_circle_5_trigger():
if request.method == 'POST':
print('buy alert recieved')
global o
global m
m = 5
o = 0
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle_div', methods=['POST'])
def api_rsi_sell_red_circle_div_trigger():
if request.method == 'POST':
print('sell alert recieved')
global p
global q
q = 5
p = 30
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle_div', methods=['POST'])
def api_rsi_buy_green_circle_div_trigger():
if request.method == 'POST':
print('buy alert recieved')
global q
global p
global r
p = 5
q = -20
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/gold_buy', methods=['POST'])
def api_rsi_gold_buy_trigger():
if request.method == 'POST':
print('gold alert recieved')
global r
global q
global k
q = 5
k = 5
r = 35
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
if __name__ == '__main__':
app.run(host="0.0.0.0", port=5000) | main.py | import ast
import requests
import configparser
from flask import Flask, request, jsonify, render_template
from flask import Flask, request
from flask_cors import CORS, cross_origin
app = Flask(__name__)
CORS(app)
a = 5.0
b = 5.0
c = 5.0
d = 5.0
e = 5.0
f = 5.0
g = 5.0
h = 5.0
i = 5.0
j = 5.0
k = 5.0
l = 5.0
m = 5.0
n = 5.0
o = 5.0
p = 5.0
q = 5.0
r = 5.0
av = 0.0
def refresh_average():
global av
av = (a + b + c + d + e + f + g + h +
i + j + k + l + m + n + o + p +
q + r) / 18 / 10
if av > 1:
av = 1.0
return av
elif av < 0:
av = 0
else:
return av
def parse_webhook(webhook_data):
data = ast.literal_eval(webhook_data)
return data
@app.route('/', methods=['GET'])
@cross_origin()
def index():
if request.method == 'GET':
print('Here is the current av')
return jsonify({'_result': str(refresh_average())})
else:
return {"code": "success"}
@app.route('/rsi_h', methods=['POST'])
@cross_origin()
def rsi_h():
if request.method == 'POST':
print('rsi sell alert received')
global a
global c
a = 10
c = 5
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
return {"code": "success"}
@app.route('/rsi_l', methods=['POST'])
@cross_origin()
def rsi_l():
if request.method == 'POST':
print('rsi buy alert received')
global c
global a
c = 0
a = 5
refresh_average()
return {"code": "success"}
else:
return {"code": "success"}
@app.route('/rsi_mfi_h', methods=['POST'])
@cross_origin()
def api_rsi_mfi_h_trigger():
if request.method == 'POST':
print('rsi sell alert received')
global d
global e
d = 15
e = 5
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/rsi_mfi_l', methods=['POST'])
@cross_origin()
def api_rsi_mfi_l_trigger():
if request.method == 'POST':
print('rsi buy alert received')
global e
global d
d = 5
e = -5
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_h', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_h_trigger():
if request.method == 'POST':
print('stoch sell alert received')
global f
global g
g = 5
f = 20
refresh_average()
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_l', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_l_trigger():
if request.method == 'POST':
print('stoch buy alert received')
global g
global f
f = 5
g = -10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_mu', methods=['POST'])
@cross_origin()
def api_rsi_stoch_k_mu_trigger():
if request.method == 'POST':
print('stoch buy alert received')
global h
global i
i = 5
h = 0
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/stoch_k_md', methods=['POST'])
def api_rsi_stoch_k_md_trigger():
if request.method == 'POST':
print('stoch sell alert received')
global i
global h
h = 5
i = 10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_diamond', methods=['POST'])
def api_rsi_sell_diamond_trigger():
if request.method == 'POST':
print('sell diamond alert received')
global j
global k
k = 5
j = 30
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_diamond', methods=['POST'])
def api_rsi_buy_diamond_trigger():
if request.method == 'POST':
print('buy diamond alert received')
global k
global j
global r
r = 5
j = 5
k = -20
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle', methods=['POST'])
def api_rsi_sell_red_circle_trigger():
if request.method == 'POST':
print('sell alert recieved')
global l
global k
global n
k = 5
n = 5
l = 12
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle_5m', methods=['POST'])
def api_rsi_sell_red_circle_5_trigger():
if request.method == 'POST':
print('sell alert recieved')
global m
global o
o = 5
m = 10
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle', methods=['POST'])
def api_rsi_buy_green_circle_trigger():
if request.method == 'POST':
print('buy alert recieved')
global n
global l
global j
j = 5
l = 5
n = -2
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle_5', methods=['POST'])
def api_rsi_buy_green_circle_5_trigger():
if request.method == 'POST':
print('buy alert recieved')
global o
global m
m = 5
o = 0
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/sell_red_circle_div', methods=['POST'])
def api_rsi_sell_red_circle_div_trigger():
if request.method == 'POST':
print('sell alert recieved')
global p
global q
q = 5
p = 30
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/buy_green_circle_div', methods=['POST'])
def api_rsi_buy_green_circle_div_trigger():
if request.method == 'POST':
print('buy alert recieved')
global q
global p
global r
p = 5
q = -20
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
@app.route('/gold_buy', methods=['POST'])
def api_rsi_gold_buy_trigger():
if request.method == 'POST':
print('gold alert recieved')
global r
global q
global k
q = 5
k = 5
r = 35
refresh_average()
print(refresh_average())
return {"code": "success"}
else:
print('do nothing')
return {"code": "success"}
if __name__ == '__main__':
app.run(host="0.0.0.0", port=5000) | 0.095941 | 0.097648 |
import lasagne
import theano
import lasagne.layers as L
import theano.tensor as T
import numpy as np
import sys
import time
from deep_dialog import dialog_config
from collections import Counter, defaultdict, deque
import random
import cPickle as pkl
EPS = 1e-10
def categorical_sample(probs, mode='sample'):
if mode=='max':
return np.argmax(probs)
else:
x = np.random.uniform()
s = probs[0]
i = 0
while s<x:
i += 1
try:
s += probs[i]
except IndexError:
sys.stderr.write('Sample out of Bounds!! Probs = {} Sample = {}\n'.format(probs, x))
return i-1
return i
def ordered_sample(probs, N, mode='sample'):
if mode=='max':
return np.argsort(probs)[::-1][:N]
else:
p = np.copy(probs)
pop = range(len(probs))
sample = []
for i in range(N):
s = categorical_sample(p)
sample.append(pop[s])
del pop[s]
p = np.delete(p,s)
p = p/p.sum()
return sample
def aggregate_rewards(rewards,discount):
running_add = 0.
for t in xrange(1,len(rewards)):
running_add += rewards[t]*discount**(t-1)
return running_add
class E2ERLAgent:
def _init_model(self, in_size, out_size, slot_sizes, db, \
n_hid=10, learning_rate_sl=0.005, learning_rate_rl=0.005, batch_size=32, ment=0.1, \
inputtype='full', sl='e2e', rl='e2e'):
self.in_size = in_size
self.out_size = out_size
self.slot_sizes = slot_sizes
self.batch_size = batch_size
self.learning_rate = learning_rate_rl
self.n_hid = n_hid
self.r_hid = self.n_hid
self.sl = sl
self.rl = rl
table = db.table
counts = db.counts
m_unk = [db.inv_counts[s][-1] for s in dialog_config.inform_slots]
prior = [db.priors[s] for s in dialog_config.inform_slots]
unknown = [db.unks[s] for s in dialog_config.inform_slots]
ids = [db.ids[s] for s in dialog_config.inform_slots]
input_var, turn_mask, act_mask, reward_var = T.ftensor3('in'), T.bmatrix('tm'), \
T.btensor3('am'), T.fvector('r')
T_var, N_var = T.as_tensor_variable(table), T.as_tensor_variable(counts)
db_index_var = T.imatrix('db')
db_index_switch = T.bvector('s')
l_mask_in = L.InputLayer(shape=(None,None), input_var=turn_mask)
flat_mask = T.reshape(turn_mask, (turn_mask.shape[0]*turn_mask.shape[1],1))
def _smooth(p):
p_n = p+EPS
return p_n/(p_n.sum(axis=1)[:,np.newaxis])
def _add_unk(p,m,N):
# p: B x V, m- num missing, N- total, p0: 1 x V
t_unk = T.as_tensor_variable(float(m)/N)
ps = p*(1.-t_unk)
return T.concatenate([ps, T.tile(t_unk, (ps.shape[0],1))], axis=1)
def kl_divergence(p,q):
p_n = _smooth(p)
return -T.sum(q*T.log(p_n), axis=1)
# belief tracking
l_in = L.InputLayer(shape=(None,None,self.in_size), input_var=input_var)
p_vars = []
pu_vars = []
phi_vars = []
p_targets = []
phi_targets = []
hid_in_vars = []
hid_out_vars = []
bt_loss = T.as_tensor_variable(0.)
kl_loss = []
x_loss = []
self.trackers = []
for i,s in enumerate(dialog_config.inform_slots):
hid_in = T.fmatrix('h')
l_rnn = L.GRULayer(l_in, self.r_hid, hid_init=hid_in, \
mask_input=l_mask_in,
grad_clipping=10.) # B x H x D
l_b_in = L.ReshapeLayer(l_rnn,
(input_var.shape[0]*input_var.shape[1], self.r_hid)) # BH x D
hid_out = L.get_output(l_rnn)[:,-1,:]
p_targ = T.ftensor3('p_target_'+s)
p_t = T.reshape(p_targ,
(p_targ.shape[0]*p_targ.shape[1],self.slot_sizes[i]))
phi_targ = T.fmatrix('phi_target'+s)
phi_t = T.reshape(phi_targ, (phi_targ.shape[0]*phi_targ.shape[1], 1))
l_b = L.DenseLayer(l_b_in, self.slot_sizes[i],
nonlinearity=lasagne.nonlinearities.softmax)
l_phi = L.DenseLayer(l_b_in, 1,
nonlinearity=lasagne.nonlinearities.sigmoid)
phi = T.clip(L.get_output(l_phi), 0.01, 0.99)
p = L.get_output(l_b)
p_u = _add_unk(p, m_unk[i], db.N)
kl_loss.append(T.sum(flat_mask.flatten()*kl_divergence(p, p_t))/T.sum(flat_mask))
x_loss.append(T.sum(flat_mask*lasagne.objectives.binary_crossentropy(phi,phi_t))/
T.sum(flat_mask))
bt_loss += kl_loss[-1] + x_loss[-1]
p_vars.append(p)
pu_vars.append(p_u)
phi_vars.append(phi)
p_targets.append(p_targ)
phi_targets.append(phi_targ)
hid_in_vars.append(hid_in)
hid_out_vars.append(hid_out)
self.trackers.append(l_b)
self.trackers.append(l_phi)
self.bt_params = L.get_all_params(self.trackers)
def check_db(pv, phi, Tb, N):
O = T.alloc(0.,pv[0].shape[0],Tb.shape[0]) # BH x T.shape[0]
for i,p in enumerate(pv):
p_dc = T.tile(phi[i], (1, Tb.shape[0]))
O += T.log(p_dc*(1./db.table.shape[0]) + \
(1.-p_dc)*(p[:,Tb[:,i]]/N[np.newaxis,:,i]))
Op = T.exp(O)#+EPS # BH x T.shape[0]
Os = T.sum(Op, axis=1)[:,np.newaxis] # BH x 1
return Op/Os
def entropy(p):
p = _smooth(p)
return -T.sum(p*T.log(p), axis=-1)
def weighted_entropy(p,q,p0,unks,idd):
w = T.dot(idd,q.transpose()) # Pi x BH
u = p0[np.newaxis,:]*(q[:,unks].sum(axis=1)[:,np.newaxis]) # BH x Pi
p_tilde = w.transpose()+u
return entropy(p_tilde)
p_db = check_db(pu_vars, phi_vars, T_var, N_var) # BH x T.shape[0]
if inputtype=='entropy':
H_vars = [weighted_entropy(pv,p_db,prior[i],unknown[i],ids[i]) \
for i,pv in enumerate(p_vars)]
H_db = entropy(p_db)
phv = [ph[:,0] for ph in phi_vars]
t_in = T.stacklists(H_vars+phv+[H_db]).transpose() # BH x 2M+1
t_in_resh = T.reshape(t_in, (turn_mask.shape[0], turn_mask.shape[1], \
t_in.shape[1])) # B x H x 2M+1
l_in_pol = L.InputLayer(
shape=(None,None,2*len(dialog_config.inform_slots)+1), \
input_var=t_in_resh)
else:
in_reshaped = T.reshape(input_var,
(input_var.shape[0]*input_var.shape[1], \
input_var.shape[2]))
prev_act = in_reshaped[:,-len(dialog_config.inform_slots):]
t_in = T.concatenate(pu_vars+phi_vars+[p_db,prev_act],
axis=1) # BH x D-sum+A
t_in_resh = T.reshape(t_in, (turn_mask.shape[0], turn_mask.shape[1], \
t_in.shape[1])) # B x H x D-sum
l_in_pol = L.InputLayer(shape=(None,None,sum(self.slot_sizes)+ \
3*len(dialog_config.inform_slots)+ \
table.shape[0]), input_var=t_in_resh)
pol_in = T.fmatrix('pol-h')
l_pol_rnn = L.GRULayer(l_in_pol, n_hid, hid_init=pol_in,
mask_input=l_mask_in,
grad_clipping=10.) # B x H x D
pol_out = L.get_output(l_pol_rnn)[:,-1,:]
l_den_in = L.ReshapeLayer(l_pol_rnn,
(turn_mask.shape[0]*turn_mask.shape[1], n_hid)) # BH x D
l_out = L.DenseLayer(l_den_in, self.out_size, \
nonlinearity=lasagne.nonlinearities.softmax) # BH x A
self.network = l_out
self.pol_params = L.get_all_params(self.network)
self.params = self.bt_params + self.pol_params
# db loss
p_db_reshaped = T.reshape(p_db, (turn_mask.shape[0],turn_mask.shape[1],table.shape[0]))
p_db_final = p_db_reshaped[:,-1,:] # B x T.shape[0]
p_db_final = _smooth(p_db_final)
ix = T.tile(T.arange(p_db_final.shape[0]),(db_index_var.shape[1],1)).transpose()
sample_probs = p_db_final[ix,db_index_var] # B x K
if dialog_config.SUCCESS_MAX_RANK==1:
log_db_probs = T.log(sample_probs).sum(axis=1)
else:
cum_probs,_ = theano.scan(fn=lambda x, prev: x+prev, \
outputs_info=T.zeros_like(sample_probs[:,0]), \
sequences=sample_probs[:,:-1].transpose())
cum_probs = T.clip(cum_probs.transpose(), 0., 1.-1e-5) # B x K-1
log_db_probs = T.log(sample_probs).sum(axis=1) - T.log(1.-cum_probs).sum(axis=1) # B
log_db_probs = log_db_probs * db_index_switch
# rl
probs = L.get_output(self.network) # BH x A
probs = _smooth(probs)
out_probs = T.reshape(probs, (turn_mask.shape[0],turn_mask.shape[1],self.out_size)) # B x H x A
log_probs = T.log(out_probs)
act_probs = (log_probs*act_mask).sum(axis=2) # B x H
ep_probs = (act_probs*turn_mask).sum(axis=1) # B
H_probs = -T.sum(T.sum(out_probs*log_probs,axis=2),axis=1) # B
self.act_loss = -T.mean(ep_probs*reward_var)
self.db_loss = -T.mean(log_db_probs*reward_var)
self.reg_loss = -T.mean(ment*H_probs)
self.loss = self.act_loss + self.db_loss + self.reg_loss
self.inps = [input_var, turn_mask, act_mask, reward_var, db_index_var, db_index_switch, \
pol_in] + hid_in_vars
self.obj_fn = theano.function(self.inps, self.loss, on_unused_input='warn')
self.act_fn = theano.function([input_var,turn_mask,pol_in]+hid_in_vars, \
[out_probs,p_db,pol_out]+pu_vars+phi_vars+hid_out_vars, on_unused_input='warn')
self.debug_fn = theano.function(self.inps, [probs, p_db, self.loss], on_unused_input='warn')
self._rl_train_fn(self.learning_rate)
## sl
sl_loss = 0. + bt_loss - T.mean(ep_probs)
if self.sl=='e2e':
sl_updates = lasagne.updates.rmsprop(sl_loss, self.params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
elif self.sl=='bel':
sl_updates = lasagne.updates.rmsprop(sl_loss, self.bt_params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
else:
sl_updates = lasagne.updates.rmsprop(sl_loss, self.pol_params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
sl_inps = [input_var, turn_mask, act_mask, pol_in] + p_targets + phi_targets + hid_in_vars
self.sl_train_fn = theano.function(sl_inps, [sl_loss]+kl_loss+x_loss, updates=sl_updates, \
on_unused_input='warn')
self.sl_obj_fn = theano.function(sl_inps, sl_loss, on_unused_input='warn')
def _rl_train_fn(self, lr):
if self.rl=='e2e':
updates = lasagne.updates.rmsprop(self.loss, self.params, learning_rate=lr, epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
elif self.rl=='bel':
updates = lasagne.updates.rmsprop(self.loss, self.bt_params, learning_rate=lr, \
epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
else:
updates = lasagne.updates.rmsprop(self.loss, self.pol_params, learning_rate=lr, \
epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
self.train_fn = theano.function(self.inps, [self.act_loss,self.db_loss,self.reg_loss], \
updates=updates)
def train(self, inp, tur, act, rew, db, dbs, pin, hin):
return self.train_fn(inp, tur, act, rew, db, dbs, pin, *hin)
def evaluate(self, inp, tur, act, rew, db, dbs, pin, hin):
return self.obj_fn(inp, tur, act, rew, db, dbs, pin, *hin)
def act(self, inp, pin, hin, mode='sample'):
tur = np.ones((inp.shape[0],inp.shape[1])).astype('int8')
outs = self.act_fn(inp, tur, pin, *hin)
act_p, db_p, p_out = outs[0], outs[1], outs[2]
n_slots = len(dialog_config.inform_slots)
pv = outs[3:3+n_slots]
phiv = outs[3+n_slots:3+2*n_slots]
h_out = outs[3+2*n_slots:]
action = categorical_sample(act_p.flatten(), mode=mode)
if action==self.out_size-1:
db_sample = ordered_sample(db_p.flatten(), dialog_config.SUCCESS_MAX_RANK, mode=mode)
else:
db_sample = []
return action, db_sample, db_p.flatten(), p_out, h_out, pv, phiv
def sl_train(self, inp, tur, act, pin, ptargets, phitargets, hin):
return self.sl_train_fn(inp, tur, act, pin, *ptargets+phitargets+hin)
def sl_evaluate(self, inp, tur, act, pin, ptargets, phitargets, hin):
return self.sl_obj_fn(inp, tur, act, pin, *ptargets+phitargets+hin)
def anneal_lr(self):
self.learning_rate /= 2.
self._rl_train_fn(self.learning_rate)
def _debug(self, inp, tur, act, rew, beliefs):
print 'Input = {}, Action = {}, Reward = {}'.format(inp, act, rew)
out = self.debug_fn(inp, tur, act, rew, *beliefs)
for item in out:
print item
def _init_experience_pool(self, pool):
self.input_pool = deque([], pool)
self.actmask_pool = deque([], pool)
self.reward_pool = deque([], pool)
self.db_pool = deque([], pool)
self.dbswitch_pool = deque([], pool)
self.turnmask_pool = deque([], pool)
self.ptarget_pool = deque([], pool)
self.phitarget_pool = deque([], pool)
def add_to_pool(self, inp, turn, act, rew, db, dbs, ptargets, phitargets):
self.input_pool.append(inp)
self.actmask_pool.append(act)
self.reward_pool.append(rew)
self.db_pool.append(db)
self.dbswitch_pool.append(dbs)
self.turnmask_pool.append(turn)
self.ptarget_pool.append(ptargets)
self.phitarget_pool.append(phitargets)
def _get_minibatch(self, N):
n = min(N, len(self.input_pool))
index = random.sample(range(len(self.input_pool)), n)
i = [self.input_pool[ii] for ii in index]
a = [self.actmask_pool[ii] for ii in index]
r = [self.reward_pool[ii] for ii in index]
d = [self.db_pool[ii] for ii in index]
ds = [self.dbswitch_pool[ii] for ii in index]
t = [self.turnmask_pool[ii] for ii in index]
p = [self.ptarget_pool[ii] for ii in index]
pp = [np.asarray([row[ii] for row in p], dtype='float32') for ii in range(len(p[0]))]
ph = [self.phitarget_pool[ii] for ii in index]
pph = [np.asarray([row[ii] for row in ph], dtype='float32') for ii in range(len(ph[0]))]
return np.asarray(i, dtype='float32'), \
np.asarray(t, dtype='int8'), \
np.asarray(a, dtype='int8'), \
np.asarray(r, dtype='float32'), \
np.asarray(d, dtype='int32'), \
np.asarray(ds, dtype='int8'), \
pp, pph
def update(self, verbose=False, regime='RL'):
i, t, a, r, d, ds, p, ph = self._get_minibatch(self.batch_size)
hi = [np.zeros((1,self.r_hid)).astype('float32') \
for s in dialog_config.inform_slots]
pi = np.zeros((1,self.n_hid)).astype('float32')
if verbose: print i, t, a, r, d, ds, p, ph, hi
if regime=='RL':
r -= np.mean(r)
al,dl,rl = self.train(i,t,a,r,d,ds,pi,hi)
g = al+dl+rl
else:
g = self.sl_train(i,t,a,pi,p,ph,hi)
return g
def eval_objective(self, N):
try:
obj = self.evaluate(self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b)
except AttributeError:
self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b = self._get_minibatch(N)
obj = self.evaluate(self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b)
return obj
def load_model(self, load_path):
with open(load_path, 'r') as f:
data = pkl.load(f)
L.set_all_param_values(self.network, data)
for item in self.trackers:
data = pkl.load(f)
L.set_all_param_values(item, data)
def save_model(self, save_path):
with open(save_path, 'w') as f:
data = L.get_all_param_values(self.network)
pkl.dump(data, f)
for item in self.trackers:
data = L.get_all_param_values(item)
pkl.dump(data, f) | deep_dialog/agents/agent_lu_rl.py | import lasagne
import theano
import lasagne.layers as L
import theano.tensor as T
import numpy as np
import sys
import time
from deep_dialog import dialog_config
from collections import Counter, defaultdict, deque
import random
import cPickle as pkl
EPS = 1e-10
def categorical_sample(probs, mode='sample'):
if mode=='max':
return np.argmax(probs)
else:
x = np.random.uniform()
s = probs[0]
i = 0
while s<x:
i += 1
try:
s += probs[i]
except IndexError:
sys.stderr.write('Sample out of Bounds!! Probs = {} Sample = {}\n'.format(probs, x))
return i-1
return i
def ordered_sample(probs, N, mode='sample'):
if mode=='max':
return np.argsort(probs)[::-1][:N]
else:
p = np.copy(probs)
pop = range(len(probs))
sample = []
for i in range(N):
s = categorical_sample(p)
sample.append(pop[s])
del pop[s]
p = np.delete(p,s)
p = p/p.sum()
return sample
def aggregate_rewards(rewards,discount):
running_add = 0.
for t in xrange(1,len(rewards)):
running_add += rewards[t]*discount**(t-1)
return running_add
class E2ERLAgent:
def _init_model(self, in_size, out_size, slot_sizes, db, \
n_hid=10, learning_rate_sl=0.005, learning_rate_rl=0.005, batch_size=32, ment=0.1, \
inputtype='full', sl='e2e', rl='e2e'):
self.in_size = in_size
self.out_size = out_size
self.slot_sizes = slot_sizes
self.batch_size = batch_size
self.learning_rate = learning_rate_rl
self.n_hid = n_hid
self.r_hid = self.n_hid
self.sl = sl
self.rl = rl
table = db.table
counts = db.counts
m_unk = [db.inv_counts[s][-1] for s in dialog_config.inform_slots]
prior = [db.priors[s] for s in dialog_config.inform_slots]
unknown = [db.unks[s] for s in dialog_config.inform_slots]
ids = [db.ids[s] for s in dialog_config.inform_slots]
input_var, turn_mask, act_mask, reward_var = T.ftensor3('in'), T.bmatrix('tm'), \
T.btensor3('am'), T.fvector('r')
T_var, N_var = T.as_tensor_variable(table), T.as_tensor_variable(counts)
db_index_var = T.imatrix('db')
db_index_switch = T.bvector('s')
l_mask_in = L.InputLayer(shape=(None,None), input_var=turn_mask)
flat_mask = T.reshape(turn_mask, (turn_mask.shape[0]*turn_mask.shape[1],1))
def _smooth(p):
p_n = p+EPS
return p_n/(p_n.sum(axis=1)[:,np.newaxis])
def _add_unk(p,m,N):
# p: B x V, m- num missing, N- total, p0: 1 x V
t_unk = T.as_tensor_variable(float(m)/N)
ps = p*(1.-t_unk)
return T.concatenate([ps, T.tile(t_unk, (ps.shape[0],1))], axis=1)
def kl_divergence(p,q):
p_n = _smooth(p)
return -T.sum(q*T.log(p_n), axis=1)
# belief tracking
l_in = L.InputLayer(shape=(None,None,self.in_size), input_var=input_var)
p_vars = []
pu_vars = []
phi_vars = []
p_targets = []
phi_targets = []
hid_in_vars = []
hid_out_vars = []
bt_loss = T.as_tensor_variable(0.)
kl_loss = []
x_loss = []
self.trackers = []
for i,s in enumerate(dialog_config.inform_slots):
hid_in = T.fmatrix('h')
l_rnn = L.GRULayer(l_in, self.r_hid, hid_init=hid_in, \
mask_input=l_mask_in,
grad_clipping=10.) # B x H x D
l_b_in = L.ReshapeLayer(l_rnn,
(input_var.shape[0]*input_var.shape[1], self.r_hid)) # BH x D
hid_out = L.get_output(l_rnn)[:,-1,:]
p_targ = T.ftensor3('p_target_'+s)
p_t = T.reshape(p_targ,
(p_targ.shape[0]*p_targ.shape[1],self.slot_sizes[i]))
phi_targ = T.fmatrix('phi_target'+s)
phi_t = T.reshape(phi_targ, (phi_targ.shape[0]*phi_targ.shape[1], 1))
l_b = L.DenseLayer(l_b_in, self.slot_sizes[i],
nonlinearity=lasagne.nonlinearities.softmax)
l_phi = L.DenseLayer(l_b_in, 1,
nonlinearity=lasagne.nonlinearities.sigmoid)
phi = T.clip(L.get_output(l_phi), 0.01, 0.99)
p = L.get_output(l_b)
p_u = _add_unk(p, m_unk[i], db.N)
kl_loss.append(T.sum(flat_mask.flatten()*kl_divergence(p, p_t))/T.sum(flat_mask))
x_loss.append(T.sum(flat_mask*lasagne.objectives.binary_crossentropy(phi,phi_t))/
T.sum(flat_mask))
bt_loss += kl_loss[-1] + x_loss[-1]
p_vars.append(p)
pu_vars.append(p_u)
phi_vars.append(phi)
p_targets.append(p_targ)
phi_targets.append(phi_targ)
hid_in_vars.append(hid_in)
hid_out_vars.append(hid_out)
self.trackers.append(l_b)
self.trackers.append(l_phi)
self.bt_params = L.get_all_params(self.trackers)
def check_db(pv, phi, Tb, N):
O = T.alloc(0.,pv[0].shape[0],Tb.shape[0]) # BH x T.shape[0]
for i,p in enumerate(pv):
p_dc = T.tile(phi[i], (1, Tb.shape[0]))
O += T.log(p_dc*(1./db.table.shape[0]) + \
(1.-p_dc)*(p[:,Tb[:,i]]/N[np.newaxis,:,i]))
Op = T.exp(O)#+EPS # BH x T.shape[0]
Os = T.sum(Op, axis=1)[:,np.newaxis] # BH x 1
return Op/Os
def entropy(p):
p = _smooth(p)
return -T.sum(p*T.log(p), axis=-1)
def weighted_entropy(p,q,p0,unks,idd):
w = T.dot(idd,q.transpose()) # Pi x BH
u = p0[np.newaxis,:]*(q[:,unks].sum(axis=1)[:,np.newaxis]) # BH x Pi
p_tilde = w.transpose()+u
return entropy(p_tilde)
p_db = check_db(pu_vars, phi_vars, T_var, N_var) # BH x T.shape[0]
if inputtype=='entropy':
H_vars = [weighted_entropy(pv,p_db,prior[i],unknown[i],ids[i]) \
for i,pv in enumerate(p_vars)]
H_db = entropy(p_db)
phv = [ph[:,0] for ph in phi_vars]
t_in = T.stacklists(H_vars+phv+[H_db]).transpose() # BH x 2M+1
t_in_resh = T.reshape(t_in, (turn_mask.shape[0], turn_mask.shape[1], \
t_in.shape[1])) # B x H x 2M+1
l_in_pol = L.InputLayer(
shape=(None,None,2*len(dialog_config.inform_slots)+1), \
input_var=t_in_resh)
else:
in_reshaped = T.reshape(input_var,
(input_var.shape[0]*input_var.shape[1], \
input_var.shape[2]))
prev_act = in_reshaped[:,-len(dialog_config.inform_slots):]
t_in = T.concatenate(pu_vars+phi_vars+[p_db,prev_act],
axis=1) # BH x D-sum+A
t_in_resh = T.reshape(t_in, (turn_mask.shape[0], turn_mask.shape[1], \
t_in.shape[1])) # B x H x D-sum
l_in_pol = L.InputLayer(shape=(None,None,sum(self.slot_sizes)+ \
3*len(dialog_config.inform_slots)+ \
table.shape[0]), input_var=t_in_resh)
pol_in = T.fmatrix('pol-h')
l_pol_rnn = L.GRULayer(l_in_pol, n_hid, hid_init=pol_in,
mask_input=l_mask_in,
grad_clipping=10.) # B x H x D
pol_out = L.get_output(l_pol_rnn)[:,-1,:]
l_den_in = L.ReshapeLayer(l_pol_rnn,
(turn_mask.shape[0]*turn_mask.shape[1], n_hid)) # BH x D
l_out = L.DenseLayer(l_den_in, self.out_size, \
nonlinearity=lasagne.nonlinearities.softmax) # BH x A
self.network = l_out
self.pol_params = L.get_all_params(self.network)
self.params = self.bt_params + self.pol_params
# db loss
p_db_reshaped = T.reshape(p_db, (turn_mask.shape[0],turn_mask.shape[1],table.shape[0]))
p_db_final = p_db_reshaped[:,-1,:] # B x T.shape[0]
p_db_final = _smooth(p_db_final)
ix = T.tile(T.arange(p_db_final.shape[0]),(db_index_var.shape[1],1)).transpose()
sample_probs = p_db_final[ix,db_index_var] # B x K
if dialog_config.SUCCESS_MAX_RANK==1:
log_db_probs = T.log(sample_probs).sum(axis=1)
else:
cum_probs,_ = theano.scan(fn=lambda x, prev: x+prev, \
outputs_info=T.zeros_like(sample_probs[:,0]), \
sequences=sample_probs[:,:-1].transpose())
cum_probs = T.clip(cum_probs.transpose(), 0., 1.-1e-5) # B x K-1
log_db_probs = T.log(sample_probs).sum(axis=1) - T.log(1.-cum_probs).sum(axis=1) # B
log_db_probs = log_db_probs * db_index_switch
# rl
probs = L.get_output(self.network) # BH x A
probs = _smooth(probs)
out_probs = T.reshape(probs, (turn_mask.shape[0],turn_mask.shape[1],self.out_size)) # B x H x A
log_probs = T.log(out_probs)
act_probs = (log_probs*act_mask).sum(axis=2) # B x H
ep_probs = (act_probs*turn_mask).sum(axis=1) # B
H_probs = -T.sum(T.sum(out_probs*log_probs,axis=2),axis=1) # B
self.act_loss = -T.mean(ep_probs*reward_var)
self.db_loss = -T.mean(log_db_probs*reward_var)
self.reg_loss = -T.mean(ment*H_probs)
self.loss = self.act_loss + self.db_loss + self.reg_loss
self.inps = [input_var, turn_mask, act_mask, reward_var, db_index_var, db_index_switch, \
pol_in] + hid_in_vars
self.obj_fn = theano.function(self.inps, self.loss, on_unused_input='warn')
self.act_fn = theano.function([input_var,turn_mask,pol_in]+hid_in_vars, \
[out_probs,p_db,pol_out]+pu_vars+phi_vars+hid_out_vars, on_unused_input='warn')
self.debug_fn = theano.function(self.inps, [probs, p_db, self.loss], on_unused_input='warn')
self._rl_train_fn(self.learning_rate)
## sl
sl_loss = 0. + bt_loss - T.mean(ep_probs)
if self.sl=='e2e':
sl_updates = lasagne.updates.rmsprop(sl_loss, self.params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
elif self.sl=='bel':
sl_updates = lasagne.updates.rmsprop(sl_loss, self.bt_params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
else:
sl_updates = lasagne.updates.rmsprop(sl_loss, self.pol_params, \
learning_rate=learning_rate_sl, epsilon=1e-4)
sl_updates_with_mom = lasagne.updates.apply_momentum(sl_updates)
sl_inps = [input_var, turn_mask, act_mask, pol_in] + p_targets + phi_targets + hid_in_vars
self.sl_train_fn = theano.function(sl_inps, [sl_loss]+kl_loss+x_loss, updates=sl_updates, \
on_unused_input='warn')
self.sl_obj_fn = theano.function(sl_inps, sl_loss, on_unused_input='warn')
def _rl_train_fn(self, lr):
if self.rl=='e2e':
updates = lasagne.updates.rmsprop(self.loss, self.params, learning_rate=lr, epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
elif self.rl=='bel':
updates = lasagne.updates.rmsprop(self.loss, self.bt_params, learning_rate=lr, \
epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
else:
updates = lasagne.updates.rmsprop(self.loss, self.pol_params, learning_rate=lr, \
epsilon=1e-4)
updates_with_mom = lasagne.updates.apply_momentum(updates)
self.train_fn = theano.function(self.inps, [self.act_loss,self.db_loss,self.reg_loss], \
updates=updates)
def train(self, inp, tur, act, rew, db, dbs, pin, hin):
return self.train_fn(inp, tur, act, rew, db, dbs, pin, *hin)
def evaluate(self, inp, tur, act, rew, db, dbs, pin, hin):
return self.obj_fn(inp, tur, act, rew, db, dbs, pin, *hin)
def act(self, inp, pin, hin, mode='sample'):
tur = np.ones((inp.shape[0],inp.shape[1])).astype('int8')
outs = self.act_fn(inp, tur, pin, *hin)
act_p, db_p, p_out = outs[0], outs[1], outs[2]
n_slots = len(dialog_config.inform_slots)
pv = outs[3:3+n_slots]
phiv = outs[3+n_slots:3+2*n_slots]
h_out = outs[3+2*n_slots:]
action = categorical_sample(act_p.flatten(), mode=mode)
if action==self.out_size-1:
db_sample = ordered_sample(db_p.flatten(), dialog_config.SUCCESS_MAX_RANK, mode=mode)
else:
db_sample = []
return action, db_sample, db_p.flatten(), p_out, h_out, pv, phiv
def sl_train(self, inp, tur, act, pin, ptargets, phitargets, hin):
return self.sl_train_fn(inp, tur, act, pin, *ptargets+phitargets+hin)
def sl_evaluate(self, inp, tur, act, pin, ptargets, phitargets, hin):
return self.sl_obj_fn(inp, tur, act, pin, *ptargets+phitargets+hin)
def anneal_lr(self):
self.learning_rate /= 2.
self._rl_train_fn(self.learning_rate)
def _debug(self, inp, tur, act, rew, beliefs):
print 'Input = {}, Action = {}, Reward = {}'.format(inp, act, rew)
out = self.debug_fn(inp, tur, act, rew, *beliefs)
for item in out:
print item
def _init_experience_pool(self, pool):
self.input_pool = deque([], pool)
self.actmask_pool = deque([], pool)
self.reward_pool = deque([], pool)
self.db_pool = deque([], pool)
self.dbswitch_pool = deque([], pool)
self.turnmask_pool = deque([], pool)
self.ptarget_pool = deque([], pool)
self.phitarget_pool = deque([], pool)
def add_to_pool(self, inp, turn, act, rew, db, dbs, ptargets, phitargets):
self.input_pool.append(inp)
self.actmask_pool.append(act)
self.reward_pool.append(rew)
self.db_pool.append(db)
self.dbswitch_pool.append(dbs)
self.turnmask_pool.append(turn)
self.ptarget_pool.append(ptargets)
self.phitarget_pool.append(phitargets)
def _get_minibatch(self, N):
n = min(N, len(self.input_pool))
index = random.sample(range(len(self.input_pool)), n)
i = [self.input_pool[ii] for ii in index]
a = [self.actmask_pool[ii] for ii in index]
r = [self.reward_pool[ii] for ii in index]
d = [self.db_pool[ii] for ii in index]
ds = [self.dbswitch_pool[ii] for ii in index]
t = [self.turnmask_pool[ii] for ii in index]
p = [self.ptarget_pool[ii] for ii in index]
pp = [np.asarray([row[ii] for row in p], dtype='float32') for ii in range(len(p[0]))]
ph = [self.phitarget_pool[ii] for ii in index]
pph = [np.asarray([row[ii] for row in ph], dtype='float32') for ii in range(len(ph[0]))]
return np.asarray(i, dtype='float32'), \
np.asarray(t, dtype='int8'), \
np.asarray(a, dtype='int8'), \
np.asarray(r, dtype='float32'), \
np.asarray(d, dtype='int32'), \
np.asarray(ds, dtype='int8'), \
pp, pph
def update(self, verbose=False, regime='RL'):
i, t, a, r, d, ds, p, ph = self._get_minibatch(self.batch_size)
hi = [np.zeros((1,self.r_hid)).astype('float32') \
for s in dialog_config.inform_slots]
pi = np.zeros((1,self.n_hid)).astype('float32')
if verbose: print i, t, a, r, d, ds, p, ph, hi
if regime=='RL':
r -= np.mean(r)
al,dl,rl = self.train(i,t,a,r,d,ds,pi,hi)
g = al+dl+rl
else:
g = self.sl_train(i,t,a,pi,p,ph,hi)
return g
def eval_objective(self, N):
try:
obj = self.evaluate(self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b)
except AttributeError:
self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b = self._get_minibatch(N)
obj = self.evaluate(self.eval_i, self.eval_t, self.eval_a, self.eval_r, self.eval_b)
return obj
def load_model(self, load_path):
with open(load_path, 'r') as f:
data = pkl.load(f)
L.set_all_param_values(self.network, data)
for item in self.trackers:
data = pkl.load(f)
L.set_all_param_values(item, data)
def save_model(self, save_path):
with open(save_path, 'w') as f:
data = L.get_all_param_values(self.network)
pkl.dump(data, f)
for item in self.trackers:
data = L.get_all_param_values(item)
pkl.dump(data, f) | 0.257485 | 0.213992 |
"""Low-level, core functionality for DayDream"""
__all__ = ['DayDreamError', 'Reference', 'Aggregator']
from copy import copy, deepcopy
from functools import reduce
from operator import add
from typing import Any, AbstractSet, Set, Optional, Union
class DayDreamError(Exception):
"""Error for package-specific issues."""
class Reference:
"""Creates a reference to an attribute present in a parent class.
:param name: name of the referenced attribute
:param target: type or name of the object with the referenced
attribute
:param modifier: this is added to the dereferenced value
"""
def dereference(self, instance: Any) -> Any:
"""Dereference an attribute on the instance.
:param instance: object whose attribute is referenced
:return: value of the referenced attribute
"""
result = self._dereference_name(instance)
try:
modifier = self._modifier.dereference(instance) # type: ignore
except (AttributeError, TypeError):
if result is self:
raise TypeError('Instance type is not referenced')
if self._modifier is not None:
result = result + self._modifier
else:
if result is self:
result = deepcopy(result)
# pylint: disable=protected-access
result._modifier = modifier
else:
result = result + modifier
return result
@property
def name(self) -> str:
"""Returns the name of the referenced attribute."""
return self._name
def __init__(self,
name: str,
target: Union[type, str],
modifier: Any = None) -> None:
self._name = name
self._target = target
self._modifier = modifier
def __repr__(self) -> str:
return (type(self).__name__
+ f'({repr(self._name)}, {self._type_name()}, '
+ f'{repr(self._modifier)})')
def __eq__(self, other: Any) -> bool:
if isinstance(other, type(self)):
# pylint: disable-msg=protected-access
result = (self._name == other._name
and self._target == other._target
and self._modifier == other._modifier)
else:
result = NotImplemented
return result
def __add__(self, other: Any) -> 'Reference':
if self._modifier is None:
modifier = other
else:
modifier = self._modifier + other
return type(self)(self._name, self._target, modifier)
__radd__ = __add__
def _refers_to(self, instance: Any) -> bool:
if not isinstance(instance, type):
instance = type(instance)
if isinstance(self._target, type):
result = issubclass(instance, self._target)
elif isinstance(self._target, str):
result = instance.__name__ == self._target
else:
raise NotImplementedError('Internal state is unexpected.')
return result
def _dereference_name(self, instance):
if self._refers_to(instance):
result = getattr(instance, self._name)
else:
result = self
return result
def _type_name(self):
if isinstance(self._target, str):
type_name = repr(self._target)
else:
type_name = self._target.__name__
return type_name
def _is_private(name: str) -> bool:
"""Return true if the name is private.
:param name: name of an attribute
"""
return name.startswith('_')
def _is_public(name: str) -> bool:
"""Return true if the name is not private, i.e. is public.
:param name: name of an attribute
"""
return not name.startswith('_')
class Aggregator:
"""Aggregate values from all objects attached to an instance.
This overrides attribute look up and allows combining (through
addition) values defined both on a particular instance and on its
attributes. This is used to allow multiple different sources to
modify a value.
For example, a character's strength is partially inherent and is
possibly modified by their race and levels in particular classes.
This class defines the interface by which all of these can be made
aware of each other with minimal boilerplate. To manage this, a
character will be an aggregator and have its own `strength`
attribute (i.e. the inherent part of its strength) and will add to
this value any attribute that also defines a `strength` attribute.
In this way, a class and a race that both define `strength` will
be added to the strength present on the character yielding a total
for that ability score.
"""
def __init_subclass__(cls,
ignore: Optional[AbstractSet[str]] = None) -> None:
"""Setup attributes to access directly."""
super().__init_subclass__()
if ignore is None:
cls._ignore: Set[str] = set()
else:
cls._ignore = set(ignore)
cls._instance_names: Set[str] = {k for k, v in vars(cls).items()
if isinstance(v, property)}
def __init__(self) -> None:
"""Initialize attribute name tracker."""
super().__init__()
self._instance_names = copy(self._instance_names)
def __setattr__(self, name: str, value: Any) -> None:
"""Track any attributes that are added to an instance."""
if _is_public(name) and name not in self._known_names:
self._instance_names.add(name)
super().__setattr__(name, value)
def __getattribute__(self, name: str) -> Any:
"""Aggregate value from each attribute if allowed."""
if _is_private(name) or name in super().__getattribute__('_ignore'):
result = super().__getattribute__(name)
else:
values = []
try:
values.append(super().__getattribute__(name))
except AttributeError:
pass
for name_other in super().__getattribute__('_instance_names'):
if name_other != name:
attribute = super().__getattribute__(name_other)
if hasattr(attribute, name):
values.append(getattr(attribute, name))
if values:
result = reduce(add, values)
else:
raise AttributeError(f'The desired attribute {name} could not'
f' be found')
try:
result = result.dereference(self)
except (AttributeError, TypeError):
pass
return result
def __delattr__(self, name: str) -> None:
"""Remove deleted attributes from tracker."""
super().__delattr__(name)
self._instance_names.remove(name)
@property
def _known_names(self) -> Set[str]:
"""Return all known names."""
return self._ignore | self._instance_names | defn/core.py | """Low-level, core functionality for DayDream"""
__all__ = ['DayDreamError', 'Reference', 'Aggregator']
from copy import copy, deepcopy
from functools import reduce
from operator import add
from typing import Any, AbstractSet, Set, Optional, Union
class DayDreamError(Exception):
"""Error for package-specific issues."""
class Reference:
"""Creates a reference to an attribute present in a parent class.
:param name: name of the referenced attribute
:param target: type or name of the object with the referenced
attribute
:param modifier: this is added to the dereferenced value
"""
def dereference(self, instance: Any) -> Any:
"""Dereference an attribute on the instance.
:param instance: object whose attribute is referenced
:return: value of the referenced attribute
"""
result = self._dereference_name(instance)
try:
modifier = self._modifier.dereference(instance) # type: ignore
except (AttributeError, TypeError):
if result is self:
raise TypeError('Instance type is not referenced')
if self._modifier is not None:
result = result + self._modifier
else:
if result is self:
result = deepcopy(result)
# pylint: disable=protected-access
result._modifier = modifier
else:
result = result + modifier
return result
@property
def name(self) -> str:
"""Returns the name of the referenced attribute."""
return self._name
def __init__(self,
name: str,
target: Union[type, str],
modifier: Any = None) -> None:
self._name = name
self._target = target
self._modifier = modifier
def __repr__(self) -> str:
return (type(self).__name__
+ f'({repr(self._name)}, {self._type_name()}, '
+ f'{repr(self._modifier)})')
def __eq__(self, other: Any) -> bool:
if isinstance(other, type(self)):
# pylint: disable-msg=protected-access
result = (self._name == other._name
and self._target == other._target
and self._modifier == other._modifier)
else:
result = NotImplemented
return result
def __add__(self, other: Any) -> 'Reference':
if self._modifier is None:
modifier = other
else:
modifier = self._modifier + other
return type(self)(self._name, self._target, modifier)
__radd__ = __add__
def _refers_to(self, instance: Any) -> bool:
if not isinstance(instance, type):
instance = type(instance)
if isinstance(self._target, type):
result = issubclass(instance, self._target)
elif isinstance(self._target, str):
result = instance.__name__ == self._target
else:
raise NotImplementedError('Internal state is unexpected.')
return result
def _dereference_name(self, instance):
if self._refers_to(instance):
result = getattr(instance, self._name)
else:
result = self
return result
def _type_name(self):
if isinstance(self._target, str):
type_name = repr(self._target)
else:
type_name = self._target.__name__
return type_name
def _is_private(name: str) -> bool:
"""Return true if the name is private.
:param name: name of an attribute
"""
return name.startswith('_')
def _is_public(name: str) -> bool:
"""Return true if the name is not private, i.e. is public.
:param name: name of an attribute
"""
return not name.startswith('_')
class Aggregator:
"""Aggregate values from all objects attached to an instance.
This overrides attribute look up and allows combining (through
addition) values defined both on a particular instance and on its
attributes. This is used to allow multiple different sources to
modify a value.
For example, a character's strength is partially inherent and is
possibly modified by their race and levels in particular classes.
This class defines the interface by which all of these can be made
aware of each other with minimal boilerplate. To manage this, a
character will be an aggregator and have its own `strength`
attribute (i.e. the inherent part of its strength) and will add to
this value any attribute that also defines a `strength` attribute.
In this way, a class and a race that both define `strength` will
be added to the strength present on the character yielding a total
for that ability score.
"""
def __init_subclass__(cls,
ignore: Optional[AbstractSet[str]] = None) -> None:
"""Setup attributes to access directly."""
super().__init_subclass__()
if ignore is None:
cls._ignore: Set[str] = set()
else:
cls._ignore = set(ignore)
cls._instance_names: Set[str] = {k for k, v in vars(cls).items()
if isinstance(v, property)}
def __init__(self) -> None:
"""Initialize attribute name tracker."""
super().__init__()
self._instance_names = copy(self._instance_names)
def __setattr__(self, name: str, value: Any) -> None:
"""Track any attributes that are added to an instance."""
if _is_public(name) and name not in self._known_names:
self._instance_names.add(name)
super().__setattr__(name, value)
def __getattribute__(self, name: str) -> Any:
"""Aggregate value from each attribute if allowed."""
if _is_private(name) or name in super().__getattribute__('_ignore'):
result = super().__getattribute__(name)
else:
values = []
try:
values.append(super().__getattribute__(name))
except AttributeError:
pass
for name_other in super().__getattribute__('_instance_names'):
if name_other != name:
attribute = super().__getattribute__(name_other)
if hasattr(attribute, name):
values.append(getattr(attribute, name))
if values:
result = reduce(add, values)
else:
raise AttributeError(f'The desired attribute {name} could not'
f' be found')
try:
result = result.dereference(self)
except (AttributeError, TypeError):
pass
return result
def __delattr__(self, name: str) -> None:
"""Remove deleted attributes from tracker."""
super().__delattr__(name)
self._instance_names.remove(name)
@property
def _known_names(self) -> Set[str]:
"""Return all known names."""
return self._ignore | self._instance_names | 0.89785 | 0.333693 |
import typing
from .error import fatalError, warnOrError
class Named:
def __init__(
self, name: str, context: "Named" = None, private: bool = False, inner: bool = False
):
self._name: str = name
sep = "$" if inner else "."
self._longname: str = (
f"{context.longname}{sep}{name}" if context is not None else self._name
)
self._private: bool = private or inner
@property
def name(self) -> str:
return self._name
@property
def longname(self) -> str:
return self._longname
@property
def llvm_name(self) -> str:
prefix = "_priv$" if self._private else ""
return f"{prefix}{self._longname}"
@property
def llvm_value(self) -> str:
pass
def extend(self, name: str) -> str:
return f"{self._longname}.{name}"
@property
def qualified(self) -> bool:
return self._longname.count(".") > 0
def defined_at(self):
pass
def type(self):
pass
class Value(Named):
pass
class Constant(Named):
pass
class Scope:
def __init__(self, parent: typing.Optional["Scope"] = None, share_temps: bool = True):
self._parent: typing.Optional["Scope"] = parent
self._values: typing.Dict[str, Named] = {}
self._share_temps: bool = share_temps
self._tmpname: int = 0
@property
def next_tmp(self) -> int:
tmp = self._tmpname
self._tmpname += 1
return tmp
def llvm_temp(self) -> str:
if self._share_temps and self._parent:
return self._parent.llvm_temp()
return f"%{self.next_tmp}"
def exists(self, name: str) -> bool:
if name in self._values:
return True
if self._parent is None:
return False
return self._parent.exists(name)
def get(self, name: str, usage) -> Named:
if name in self._values:
return self._values[name]
if self._parent is None:
fatalError("Unknown symbol", name=name, used=usage)
return self._parent.get(name, usage)
def add(self, item: Named):
if item.name in self._values:
fatalError(
"redefined value",
name=item.name,
new_def=item.defined_at(),
defined=self._values[item.name].defined_at(),
)
if self._parent and self._parent.exists(item.name):
warnOrError(
"shadowing existing name",
name=item.name,
new_def=item.defined_at(),
defined=self.get(item.name, None).defined_at(),
)
self._values[item.name] = item | bareAST/bare/scope.py | import typing
from .error import fatalError, warnOrError
class Named:
def __init__(
self, name: str, context: "Named" = None, private: bool = False, inner: bool = False
):
self._name: str = name
sep = "$" if inner else "."
self._longname: str = (
f"{context.longname}{sep}{name}" if context is not None else self._name
)
self._private: bool = private or inner
@property
def name(self) -> str:
return self._name
@property
def longname(self) -> str:
return self._longname
@property
def llvm_name(self) -> str:
prefix = "_priv$" if self._private else ""
return f"{prefix}{self._longname}"
@property
def llvm_value(self) -> str:
pass
def extend(self, name: str) -> str:
return f"{self._longname}.{name}"
@property
def qualified(self) -> bool:
return self._longname.count(".") > 0
def defined_at(self):
pass
def type(self):
pass
class Value(Named):
pass
class Constant(Named):
pass
class Scope:
def __init__(self, parent: typing.Optional["Scope"] = None, share_temps: bool = True):
self._parent: typing.Optional["Scope"] = parent
self._values: typing.Dict[str, Named] = {}
self._share_temps: bool = share_temps
self._tmpname: int = 0
@property
def next_tmp(self) -> int:
tmp = self._tmpname
self._tmpname += 1
return tmp
def llvm_temp(self) -> str:
if self._share_temps and self._parent:
return self._parent.llvm_temp()
return f"%{self.next_tmp}"
def exists(self, name: str) -> bool:
if name in self._values:
return True
if self._parent is None:
return False
return self._parent.exists(name)
def get(self, name: str, usage) -> Named:
if name in self._values:
return self._values[name]
if self._parent is None:
fatalError("Unknown symbol", name=name, used=usage)
return self._parent.get(name, usage)
def add(self, item: Named):
if item.name in self._values:
fatalError(
"redefined value",
name=item.name,
new_def=item.defined_at(),
defined=self._values[item.name].defined_at(),
)
if self._parent and self._parent.exists(item.name):
warnOrError(
"shadowing existing name",
name=item.name,
new_def=item.defined_at(),
defined=self.get(item.name, None).defined_at(),
)
self._values[item.name] = item | 0.635109 | 0.19789 |
import calc_postion
import datetime
import backend
import json
import io
from baselib import error_print
from flask import Flask, render_template, make_response
from flask import request
from flask_restful import reqparse, abort, Api, Resource
app = Flask(__name__)
api_loader = Api(app)
parser = reqparse.RequestParser()
for pa in ['la1', 'lo1', 'd1',
'la2', 'lo2', 'd2',
'la3', 'lo3', 'd3', 'EP',
'data', 'name', 'id', 'task',
'start', 'end', 'tunit', 'count',
'device', 'action', 'latitude', 'longitude',
'sign', 'gender', 'country', 'province', 'city',
'ocount', 'pcount',
]:
parser.add_argument(pa)
def html_template(page):
args = parser.parse_args()
args['name_js'] = page + '.js'
args['name_css'] = page + '.css'
return render_template('points_template.html', **args)
def html(page):
args = parser.parse_args()
args['name_js'] = page + '.js'
args['name_css'] = page + '.css'
if not args["id"]:
args["id"] = ''
return render_template('template_html.html', **args)
## For debug show demo page
@app.route('/demo', methods=['GET'])
def demo():
return html("demo")
## Show calc points page
@app.route('/cpoints', methods=['GET'])
def cpoints():
return html_template("cpoints")
## Show calc points page
@app.route('/opoints', methods=['GET'])
def opoints():
return html_template("opoints")
## Show near points page
@app.route('/npoints', methods=['GET'])
def npoints():
return html_template("npoints")
## Show device points page
@app.route('/dpoints', methods=['GET'])
def dpoints():
return html_template("dpoints")
@app.route('/name', methods=['GET'])
def js_page():
return html("name")
@app.route('/calc', methods=['GET'])
def calc():
args = parser.parse_args()
try:
la1 = float(args['la1'])
lo1 = float(args['lo1'])
d1 = float(args['d1'])
la2 = float(args['la2'])
lo2 = float(args['lo2'])
d2 = float(args['d2'])
la3 = float(args['la3'])
lo3 = float(args['lo3'])
d3 = float(args['d3'])
EP = 100
if args['EP']:
EP = float(args['EP'])
if not EP:
EP = 100
r = calc_postion.calc(la1, lo1, d1, la2, lo2, d2, la3, lo3, d3, EP)
if not r:
return '{"success": 0}'
# calc
return '{{"success": 1, "la":{0}, "lo":{1}, "dis":{2} }}'.format( r[0], r[1], r[2] )
except Exception as e:
return '{"success": 0}'
@app.route("/upload", methods=['GET', 'POST'])
def upload():
args = parser.parse_args()
try:
if 'data' not in args or not args['data']:
return '{"success": 0}'
if backend.unique_push_data(args['data']):
return '{"success": 1}'
except Exception as e:
print("{0} {1}".format(__name__, e))
pass
return '{"success": 0}'
@app.route("/show", methods=['GET', 'POST'])
def show():
args = parser.parse_args()
try:
ret = backend.unique_show_search(args)
if ret:
data = { "success": 1,
"data": ret}
ret = json.dumps(data, indent= None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/result", methods=['GET', 'POST'])
def result():
args = parser.parse_args()
if 'id' not in args or not args['id']:
return '{"success": 0}'
try:
ret = backend.unique_check_and_calc(args['id'], args['start'], args['end'], args['tunit'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
pass
return '{"success": 0}'
@app.route("/near", methods=['GET', 'POST'])
def near():
args = parser.parse_args()
try:
latitude = float(args['latitude'])
longitude = float(args['longitude'])
count = int(args['count'])
if not count:
count = 20
if latitude and longitude:
ret = backend.unique_NearPoint(latitude,longitude, count)
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/origin", methods=['GET', 'POST'])
def origin():
args = parser.parse_args()
if 'id' not in args or not args['id']:
return '{"success": 0}'
try:
ret = backend.unique_origin_points(args['id'], args['start'], args['end'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/device", methods=['GET', 'POST'])
def device():
args = parser.parse_args()
a = 'get'
task = "node"
if args['action']:
a = args['action'].lower()
if args['task'] and len(args['task']):
task = args['task']
if a == 'setall':
ret = backend.unique_setall_device(task, args['data'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
return '{"success": 0}'
if a == 'getall':
ret = backend.unique_get_device_all(task)
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
if not args['device']:
return '{"success": 0}'
if a == 'set' and args['latitude'] and args['longitude']:
if backend.unique_set_device(task, args['device'], float(args['latitude']), float(args['longitude'])):
return '{"success": 1}'
elif a == 'delete':
if backend.unique_delete_device(task, args['device']):
return '{"success": 1}'
else:
ret = backend.unique_get_device(task, args['device'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
return '{"success": 0}'
@app.route("/becareful", methods=['GET', 'POST'])
def becareful():
args = parser.parse_args()
action = args["action"]
name = args["name"]
i = args["id"]
if name != "IknowPasswoRd" or i != "RisIngRiRi":
return '{"success": 0}'
if action not in ["users", "device", "points"]:
return '{"success": 0}'
ret = backend.unique_delete_information(action)
if ret:
return '{"success": 1}'
return '{"success": 0}'
#main enter
global_main_enter = {}
for key in ["cpoints", "opoints", "npoints", "dpoints"]:
global_main_enter[key] = html_template
for key in ["demo", "name"]:
global_main_enter[key] = html
global_main_enter["calc"] = calc
## Show Main page
@app.route('/', methods=['GET'])
def index():
return html_template("index")
@app.route("/<action>", methods=['GET', 'POST'])
def enter(action):
try:
action = action.lower()
except Exception as e:
error_print(e)
abort(404)
return
if action not in global_main_enter:
abort(404)
return
function = global_main_enter[action]
return function(action) | gpsmap/work_app.py | import calc_postion
import datetime
import backend
import json
import io
from baselib import error_print
from flask import Flask, render_template, make_response
from flask import request
from flask_restful import reqparse, abort, Api, Resource
app = Flask(__name__)
api_loader = Api(app)
parser = reqparse.RequestParser()
for pa in ['la1', 'lo1', 'd1',
'la2', 'lo2', 'd2',
'la3', 'lo3', 'd3', 'EP',
'data', 'name', 'id', 'task',
'start', 'end', 'tunit', 'count',
'device', 'action', 'latitude', 'longitude',
'sign', 'gender', 'country', 'province', 'city',
'ocount', 'pcount',
]:
parser.add_argument(pa)
def html_template(page):
args = parser.parse_args()
args['name_js'] = page + '.js'
args['name_css'] = page + '.css'
return render_template('points_template.html', **args)
def html(page):
args = parser.parse_args()
args['name_js'] = page + '.js'
args['name_css'] = page + '.css'
if not args["id"]:
args["id"] = ''
return render_template('template_html.html', **args)
## For debug show demo page
@app.route('/demo', methods=['GET'])
def demo():
return html("demo")
## Show calc points page
@app.route('/cpoints', methods=['GET'])
def cpoints():
return html_template("cpoints")
## Show calc points page
@app.route('/opoints', methods=['GET'])
def opoints():
return html_template("opoints")
## Show near points page
@app.route('/npoints', methods=['GET'])
def npoints():
return html_template("npoints")
## Show device points page
@app.route('/dpoints', methods=['GET'])
def dpoints():
return html_template("dpoints")
@app.route('/name', methods=['GET'])
def js_page():
return html("name")
@app.route('/calc', methods=['GET'])
def calc():
args = parser.parse_args()
try:
la1 = float(args['la1'])
lo1 = float(args['lo1'])
d1 = float(args['d1'])
la2 = float(args['la2'])
lo2 = float(args['lo2'])
d2 = float(args['d2'])
la3 = float(args['la3'])
lo3 = float(args['lo3'])
d3 = float(args['d3'])
EP = 100
if args['EP']:
EP = float(args['EP'])
if not EP:
EP = 100
r = calc_postion.calc(la1, lo1, d1, la2, lo2, d2, la3, lo3, d3, EP)
if not r:
return '{"success": 0}'
# calc
return '{{"success": 1, "la":{0}, "lo":{1}, "dis":{2} }}'.format( r[0], r[1], r[2] )
except Exception as e:
return '{"success": 0}'
@app.route("/upload", methods=['GET', 'POST'])
def upload():
args = parser.parse_args()
try:
if 'data' not in args or not args['data']:
return '{"success": 0}'
if backend.unique_push_data(args['data']):
return '{"success": 1}'
except Exception as e:
print("{0} {1}".format(__name__, e))
pass
return '{"success": 0}'
@app.route("/show", methods=['GET', 'POST'])
def show():
args = parser.parse_args()
try:
ret = backend.unique_show_search(args)
if ret:
data = { "success": 1,
"data": ret}
ret = json.dumps(data, indent= None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/result", methods=['GET', 'POST'])
def result():
args = parser.parse_args()
if 'id' not in args or not args['id']:
return '{"success": 0}'
try:
ret = backend.unique_check_and_calc(args['id'], args['start'], args['end'], args['tunit'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
pass
return '{"success": 0}'
@app.route("/near", methods=['GET', 'POST'])
def near():
args = parser.parse_args()
try:
latitude = float(args['latitude'])
longitude = float(args['longitude'])
count = int(args['count'])
if not count:
count = 20
if latitude and longitude:
ret = backend.unique_NearPoint(latitude,longitude, count)
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/origin", methods=['GET', 'POST'])
def origin():
args = parser.parse_args()
if 'id' not in args or not args['id']:
return '{"success": 0}'
try:
ret = backend.unique_origin_points(args['id'], args['start'], args['end'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
except Exception as e:
print("{0} {1}".format(__name__, e))
return '{"success": 0}'
@app.route("/device", methods=['GET', 'POST'])
def device():
args = parser.parse_args()
a = 'get'
task = "node"
if args['action']:
a = args['action'].lower()
if args['task'] and len(args['task']):
task = args['task']
if a == 'setall':
ret = backend.unique_setall_device(task, args['data'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
return '{"success": 0}'
if a == 'getall':
ret = backend.unique_get_device_all(task)
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
if not args['device']:
return '{"success": 0}'
if a == 'set' and args['latitude'] and args['longitude']:
if backend.unique_set_device(task, args['device'], float(args['latitude']), float(args['longitude'])):
return '{"success": 1}'
elif a == 'delete':
if backend.unique_delete_device(task, args['device']):
return '{"success": 1}'
else:
ret = backend.unique_get_device(task, args['device'])
if ret:
data = {"success": 1,
"data": ret}
ret = json.dumps(data, indent=None)
return ret
return '{"success": 0}'
@app.route("/becareful", methods=['GET', 'POST'])
def becareful():
args = parser.parse_args()
action = args["action"]
name = args["name"]
i = args["id"]
if name != "IknowPasswoRd" or i != "RisIngRiRi":
return '{"success": 0}'
if action not in ["users", "device", "points"]:
return '{"success": 0}'
ret = backend.unique_delete_information(action)
if ret:
return '{"success": 1}'
return '{"success": 0}'
#main enter
global_main_enter = {}
for key in ["cpoints", "opoints", "npoints", "dpoints"]:
global_main_enter[key] = html_template
for key in ["demo", "name"]:
global_main_enter[key] = html
global_main_enter["calc"] = calc
## Show Main page
@app.route('/', methods=['GET'])
def index():
return html_template("index")
@app.route("/<action>", methods=['GET', 'POST'])
def enter(action):
try:
action = action.lower()
except Exception as e:
error_print(e)
abort(404)
return
if action not in global_main_enter:
abort(404)
return
function = global_main_enter[action]
return function(action) | 0.243642 | 0.143638 |
from functools import partial
import time
import os
import sys
import threading
import resotolib.proc
from typing import List, Dict
from .config import add_config
from resotolib.config import Config
from resotolib.logger import log, setup_logger, add_args as logging_add_args
from resotolib.jwt import add_args as jwt_add_args
from resotolib.baseplugin import BaseCollectorPlugin, PluginType
from resotolib.web import WebServer
from resotolib.web.metrics import WebApp
from resotolib.utils import log_stats, increase_limits
from resotolib.args import ArgumentParser
from resotolib.core import add_args as core_add_args, resotocore, wait_for_resotocore
from resotolib.core.ca import TLSData
from resotolib.core.actions import CoreActions
from resotolib.core.tasks import CoreTasks
from resotoworker.pluginloader import PluginLoader
from resotoworker.collect import collect_and_send
from resotoworker.cleanup import cleanup
from resotoworker.tag import core_tag_tasks_processor
from resotolib.event import (
add_event_listener,
Event,
EventType,
)
# This will be used in main() and shutdown()
shutdown_event = threading.Event()
collect_event = threading.Event()
def main() -> None:
setup_logger("resotoworker")
# Try to run in a new process group and
# ignore if not possible for whatever reason
try:
os.setpgid(0, 0)
except Exception:
pass
resotolib.proc.parent_pid = os.getpid()
arg_parser = ArgumentParser(
description="resoto worker",
env_args_prefix="RESOTOWORKER_",
)
add_args(arg_parser)
jwt_add_args(arg_parser)
logging_add_args(arg_parser)
core_add_args(arg_parser)
Config.add_args(arg_parser)
TLSData.add_args(arg_parser)
# Find resoto Plugins in the resoto.plugins module
plugin_loader = PluginLoader()
plugin_loader.add_plugin_args(arg_parser)
# At this point the CLI, all Plugins as well as the WebServer have
# added their args to the arg parser
arg_parser.parse_args()
try:
wait_for_resotocore(resotocore.http_uri)
except TimeoutError as e:
log.fatal(f"Failed to connect to resotocore: {e}")
sys.exit(1)
tls_data = None
if resotocore.is_secure:
tls_data = TLSData(
common_name=ArgumentParser.args.subscriber_id,
resotocore_uri=resotocore.http_uri,
)
tls_data.start()
config = Config(
ArgumentParser.args.subscriber_id,
resotocore_uri=resotocore.http_uri,
tls_data=tls_data,
)
add_config(config)
plugin_loader.add_plugin_config(config)
config.load_config()
# Handle Ctrl+c and other means of termination/shutdown
resotolib.proc.initializer()
add_event_listener(EventType.SHUTDOWN, shutdown, blocking=False)
# Try to increase nofile and nproc limits
increase_limits()
web_server_args = {}
if tls_data:
web_server_args = {
"ssl_cert": tls_data.cert_path,
"ssl_key": tls_data.key_path,
}
web_server = WebServer(
WebApp(mountpoint=Config.resotoworker.web_path),
web_host=Config.resotoworker.web_host,
web_port=Config.resotoworker.web_port,
**web_server_args,
)
web_server.daemon = True
web_server.start()
core_actions = CoreActions(
identifier=f"{ArgumentParser.args.subscriber_id}-collector",
resotocore_uri=resotocore.http_uri,
resotocore_ws_uri=resotocore.ws_uri,
actions={
"collect": {
"timeout": Config.resotoworker.timeout,
"wait_for_completion": True,
},
"cleanup": {
"timeout": Config.resotoworker.timeout,
"wait_for_completion": True,
},
},
message_processor=partial(core_actions_processor, plugin_loader, tls_data),
tls_data=tls_data,
)
task_queue_filter = {}
if len(Config.resotoworker.collector) > 0:
task_queue_filter = {"cloud": list(Config.resotoworker.collector)}
core_tasks = CoreTasks(
identifier=f"{ArgumentParser.args.subscriber_id}-tagger",
resotocore_ws_uri=resotocore.ws_uri,
tasks=["tag"],
task_queue_filter=task_queue_filter,
message_processor=core_tag_tasks_processor,
tls_data=tls_data,
)
core_actions.start()
core_tasks.start()
for Plugin in plugin_loader.plugins(PluginType.ACTION):
try:
log.debug(f"Starting action plugin {Plugin}")
plugin = Plugin(tls_data=tls_data)
plugin.start()
except Exception as e:
log.exception(f"Caught unhandled persistent Plugin exception {e}")
# We wait for the shutdown Event to be set() and then end the program
# While doing so we print the list of active threads once per 15 minutes
shutdown_event.wait()
web_server.shutdown()
time.sleep(1) # everything gets 1000ms to shutdown gracefully before we force it
resotolib.proc.kill_children(resotolib.proc.SIGTERM, ensure_death=True)
log.info("Shutdown complete")
os._exit(0)
def core_actions_processor(
plugin_loader: PluginLoader, tls_data: TLSData, message: Dict
) -> None:
collectors: List[BaseCollectorPlugin] = plugin_loader.plugins(PluginType.COLLECTOR)
if not isinstance(message, dict):
log.error(f"Invalid message: {message}")
return
kind = message.get("kind")
message_type = message.get("message_type")
data = message.get("data")
log.debug(f"Received message of kind {kind}, type {message_type}, data: {data}")
if kind == "action":
try:
if message_type == "collect":
start_time = time.time()
collect_and_send(collectors, tls_data=tls_data)
run_time = int(time.time() - start_time)
log.info(f"Collect ran for {run_time} seconds")
elif message_type == "cleanup":
start_time = time.time()
cleanup(tls_data=tls_data)
run_time = int(time.time() - start_time)
log.info(f"Cleanup ran for {run_time} seconds")
else:
raise ValueError(f"Unknown message type {message_type}")
except Exception as e:
log.exception(f"Failed to {message_type}: {e}")
reply_kind = "action_error"
else:
reply_kind = "action_done"
reply_message = {
"kind": reply_kind,
"message_type": message_type,
"data": data,
}
return reply_message
def shutdown(event: Event) -> None:
reason = event.data.get("reason")
emergency = event.data.get("emergency")
if emergency:
resotolib.proc.emergency_shutdown(reason)
current_pid = os.getpid()
if current_pid != resotolib.proc.parent_pid:
return
if reason is None:
reason = "unknown reason"
log.info(
(
f"Received shut down event {event.event_type}:"
f" {reason} - killing all threads and child processes"
)
)
shutdown_event.set() # and then end the program
def force_shutdown(delay: int = 10) -> None:
time.sleep(delay)
log_stats()
log.error(
(
"Some child process or thread timed out during shutdown"
" - forcing shutdown completion"
)
)
os._exit(0)
def add_args(arg_parser: ArgumentParser) -> None:
arg_parser.add_argument(
"--subscriber-id",
help="Unique subscriber ID (default: resoto.worker)",
default="resoto.worker",
dest="subscriber_id",
type=str,
)
if __name__ == "__main__":
main() | resotoworker/resotoworker/__main__.py | from functools import partial
import time
import os
import sys
import threading
import resotolib.proc
from typing import List, Dict
from .config import add_config
from resotolib.config import Config
from resotolib.logger import log, setup_logger, add_args as logging_add_args
from resotolib.jwt import add_args as jwt_add_args
from resotolib.baseplugin import BaseCollectorPlugin, PluginType
from resotolib.web import WebServer
from resotolib.web.metrics import WebApp
from resotolib.utils import log_stats, increase_limits
from resotolib.args import ArgumentParser
from resotolib.core import add_args as core_add_args, resotocore, wait_for_resotocore
from resotolib.core.ca import TLSData
from resotolib.core.actions import CoreActions
from resotolib.core.tasks import CoreTasks
from resotoworker.pluginloader import PluginLoader
from resotoworker.collect import collect_and_send
from resotoworker.cleanup import cleanup
from resotoworker.tag import core_tag_tasks_processor
from resotolib.event import (
add_event_listener,
Event,
EventType,
)
# This will be used in main() and shutdown()
shutdown_event = threading.Event()
collect_event = threading.Event()
def main() -> None:
setup_logger("resotoworker")
# Try to run in a new process group and
# ignore if not possible for whatever reason
try:
os.setpgid(0, 0)
except Exception:
pass
resotolib.proc.parent_pid = os.getpid()
arg_parser = ArgumentParser(
description="resoto worker",
env_args_prefix="RESOTOWORKER_",
)
add_args(arg_parser)
jwt_add_args(arg_parser)
logging_add_args(arg_parser)
core_add_args(arg_parser)
Config.add_args(arg_parser)
TLSData.add_args(arg_parser)
# Find resoto Plugins in the resoto.plugins module
plugin_loader = PluginLoader()
plugin_loader.add_plugin_args(arg_parser)
# At this point the CLI, all Plugins as well as the WebServer have
# added their args to the arg parser
arg_parser.parse_args()
try:
wait_for_resotocore(resotocore.http_uri)
except TimeoutError as e:
log.fatal(f"Failed to connect to resotocore: {e}")
sys.exit(1)
tls_data = None
if resotocore.is_secure:
tls_data = TLSData(
common_name=ArgumentParser.args.subscriber_id,
resotocore_uri=resotocore.http_uri,
)
tls_data.start()
config = Config(
ArgumentParser.args.subscriber_id,
resotocore_uri=resotocore.http_uri,
tls_data=tls_data,
)
add_config(config)
plugin_loader.add_plugin_config(config)
config.load_config()
# Handle Ctrl+c and other means of termination/shutdown
resotolib.proc.initializer()
add_event_listener(EventType.SHUTDOWN, shutdown, blocking=False)
# Try to increase nofile and nproc limits
increase_limits()
web_server_args = {}
if tls_data:
web_server_args = {
"ssl_cert": tls_data.cert_path,
"ssl_key": tls_data.key_path,
}
web_server = WebServer(
WebApp(mountpoint=Config.resotoworker.web_path),
web_host=Config.resotoworker.web_host,
web_port=Config.resotoworker.web_port,
**web_server_args,
)
web_server.daemon = True
web_server.start()
core_actions = CoreActions(
identifier=f"{ArgumentParser.args.subscriber_id}-collector",
resotocore_uri=resotocore.http_uri,
resotocore_ws_uri=resotocore.ws_uri,
actions={
"collect": {
"timeout": Config.resotoworker.timeout,
"wait_for_completion": True,
},
"cleanup": {
"timeout": Config.resotoworker.timeout,
"wait_for_completion": True,
},
},
message_processor=partial(core_actions_processor, plugin_loader, tls_data),
tls_data=tls_data,
)
task_queue_filter = {}
if len(Config.resotoworker.collector) > 0:
task_queue_filter = {"cloud": list(Config.resotoworker.collector)}
core_tasks = CoreTasks(
identifier=f"{ArgumentParser.args.subscriber_id}-tagger",
resotocore_ws_uri=resotocore.ws_uri,
tasks=["tag"],
task_queue_filter=task_queue_filter,
message_processor=core_tag_tasks_processor,
tls_data=tls_data,
)
core_actions.start()
core_tasks.start()
for Plugin in plugin_loader.plugins(PluginType.ACTION):
try:
log.debug(f"Starting action plugin {Plugin}")
plugin = Plugin(tls_data=tls_data)
plugin.start()
except Exception as e:
log.exception(f"Caught unhandled persistent Plugin exception {e}")
# We wait for the shutdown Event to be set() and then end the program
# While doing so we print the list of active threads once per 15 minutes
shutdown_event.wait()
web_server.shutdown()
time.sleep(1) # everything gets 1000ms to shutdown gracefully before we force it
resotolib.proc.kill_children(resotolib.proc.SIGTERM, ensure_death=True)
log.info("Shutdown complete")
os._exit(0)
def core_actions_processor(
plugin_loader: PluginLoader, tls_data: TLSData, message: Dict
) -> None:
collectors: List[BaseCollectorPlugin] = plugin_loader.plugins(PluginType.COLLECTOR)
if not isinstance(message, dict):
log.error(f"Invalid message: {message}")
return
kind = message.get("kind")
message_type = message.get("message_type")
data = message.get("data")
log.debug(f"Received message of kind {kind}, type {message_type}, data: {data}")
if kind == "action":
try:
if message_type == "collect":
start_time = time.time()
collect_and_send(collectors, tls_data=tls_data)
run_time = int(time.time() - start_time)
log.info(f"Collect ran for {run_time} seconds")
elif message_type == "cleanup":
start_time = time.time()
cleanup(tls_data=tls_data)
run_time = int(time.time() - start_time)
log.info(f"Cleanup ran for {run_time} seconds")
else:
raise ValueError(f"Unknown message type {message_type}")
except Exception as e:
log.exception(f"Failed to {message_type}: {e}")
reply_kind = "action_error"
else:
reply_kind = "action_done"
reply_message = {
"kind": reply_kind,
"message_type": message_type,
"data": data,
}
return reply_message
def shutdown(event: Event) -> None:
reason = event.data.get("reason")
emergency = event.data.get("emergency")
if emergency:
resotolib.proc.emergency_shutdown(reason)
current_pid = os.getpid()
if current_pid != resotolib.proc.parent_pid:
return
if reason is None:
reason = "unknown reason"
log.info(
(
f"Received shut down event {event.event_type}:"
f" {reason} - killing all threads and child processes"
)
)
shutdown_event.set() # and then end the program
def force_shutdown(delay: int = 10) -> None:
time.sleep(delay)
log_stats()
log.error(
(
"Some child process or thread timed out during shutdown"
" - forcing shutdown completion"
)
)
os._exit(0)
def add_args(arg_parser: ArgumentParser) -> None:
arg_parser.add_argument(
"--subscriber-id",
help="Unique subscriber ID (default: resoto.worker)",
default="resoto.worker",
dest="subscriber_id",
type=str,
)
if __name__ == "__main__":
main() | 0.405802 | 0.08882 |
import numpy as np
class OneHiddenLayerNN:
"""
@brief: One hidden layer neural network with batch gradient descent.
Currently supporting only relu, tanh and sigmoid activation functions.
"""
def __init__(self, number_of_neurons, batch_size = 20, hidden_activation='relu',
out_activation='sigmoid', epochs=100, learning_rate=0.1):
"""
:param number_of_neurons: number of neurons in hidden layer.
:param batch_size: batch size.
:param hidden_activation: hidden layer activation function.
:param out_activation: out layer activation function.
:param epochs: how many times do gradient descent.
:param learning_rate: learning rate.
"""
self.nn_size = number_of_neurons
self.epochs = epochs
self.alpha = learning_rate
self.W_h = None
self.W_out = None
self.batch_size = batch_size
self.hidden_func = hidden_activation
self.out_func = out_activation
@staticmethod
def __activation(z, func_name):
"""
:param z: dot(X, W_h).
:param func_name: function name to compute.
:return: activation_function(z).
"""
if func_name == 'relu':
# relu = max(0, z).
return np.maximum(z, 0)
elif func_name == 'tanh':
# tanh = (e^z - e(-z)) / (e^z + e(-z)).
return np.tanh(z)
elif func_name == 'sigmoid':
# sigmoid = 1 / (1 + e^(-z)).
return 1 / (1 + np.exp(-z))
@staticmethod
def __d_activation(func_out, func_name):
"""
:param func_out: dot(prev_layer, W_current).
:param func_name: function name to compute.
:return: derivative of activation function.
"""
if func_name == 'relu':
# d(relu) = 1 if relu > 0 else 0.
func_o_tmp = func_out.copy()
func_o_tmp[func_out <= 0] = 0
func_o_tmp[func_out > 0] = 1
return func_o_tmp
elif func_name == 'tanh':
# d(tanh) = 1 - tanh^2.
return 1 - func_out * func_out
elif func_name == 'sigmoid':
# d(sigmoid) = sigmoid * (1 - sigmoid).
return func_out * (1 - func_out)
@staticmethod
def __loss(a_out, a):
"""
:param a_out: network output.
:param a: desired output.
:return: sum of squared difference normalized.
"""
return np.sum(np.square(a_out - a)) / a.shape[0]
def __d_out(self, a_h, a_o, a):
"""
:param a_h: hidden output.
:param a_o: net_out.
:param a: desired out.
:return: d(Loss) / d(W_out(i, k)) = SUM_i((d(Loss) / d(a_o(i)) * (d(a_o(i)) / d(W_out(i, k)).
(d(a_o(i)) / d(W_out(i, k)) != 0 if and only if i == k because of z = SUM(a_h(i) * W_out(j, i) =>
d(Loss) / d(W_out(i, k)) = (d(Loss) / d(a_o(k)) * (d(a_o(k)) / d(W_out(i, k))
= (2 * (a_o(k) - a(k))) * ((d(activation(z) / d(z)) * (d(z) / d(W_out(i, k)))
= (2 * (a_o(k) - a(k))) * a_h(i) * (d(activation(z)) / d(z))
"""
d_loss = np.dot(a_h.T, (2.0 * (a_o - a) * self.__d_activation(a_o, self.out_func)))
return self.alpha * d_loss / a.shape[0]
def _d_hidden(self, X, a_h, a_o, a):
"""
:param X: input.
:param a_h: hidden output.
:param a_o: net_out.
:param a: desired out.
:return: d(Loss) / d(W_h(i, k)) = SUM_p((d(Loss) / d(a_o(p))) * SUM_j((d(a_o(p)) / d(a_h(j)) * (d(a_h(j)) / d(W_h(i, k))))
= SUM_p((d(Loss) / d(a_o(p))) * (d(a_o(p)) / d(a_h(k)) * (d(a_h(k)) / d(W_h(i, k)))
d(Loss) / d(a_o(p)) = 2 * (a_o(p) - a(p))
d(a_o(p)) / d(a_h(k)) = ((d(activation_out(z) / d(z)) * W_out(k, p) where z = a_o(p)
d(a_h(k)) / d(W_h(i, k)) = X(i) * (d(activation_hidden(z)) / d(z)) where z = a_h(k)
"""
# W_out[1:] because first row is bias.
d_loss = np.dot(X.T, np.dot(2.0 * (a_o - a) * self.__d_activation(a_o, self.out_func), self.W_out[1:].T) *
self.__d_activation(a_h, self.hidden_func))
return self.alpha * d_loss / a.shape[0]
@staticmethod
def __add_bias(X):
"""
:param X: input.
:return: concatenate ones to input to get bias term.
"""
bias = np.ones((X.shape[0], 1))
return np.concatenate((bias, X), axis=1)
def __forward_backward_prop(self, X, y):
"""
:param X: input.
:param y: ground truth.
:return: updated weights.
"""
# multiply input by weights.
z_h = np.dot(X, self.W_h)
# apply activation function.
a_h = self.__activation(z_h, self.hidden_func)
# add 1 to hidden layer to get bias term.
a_h_b = self.__add_bias(a_h)
# multiply previous layer output by weights of current layer.
z_o = np.dot(a_h_b, self.W_out)
# apply activation function.
a_o = self.__activation(z_o, self.out_func)
# calculate derivatives.
d_out = self.__d_out(a_h_b, a_o, y)
d_hidden = self._d_hidden(X, a_h, a_o, y)
# update weights using calculated gradients.
self.W_out -= d_out
self.W_h -= d_hidden
def fit(self, X, y):
"""
:param X: input. shape = (number_of_examples, features).
:param y: output. shape = (number_of_examples, classes).
"""
# add 1 to input layer to get bias term.
X = self.__add_bias(X)
# multiplying by sqrt(2.0 / input_shape_size) for vanishing exploding gradients. (<NAME>. deep learning course).
# put bias in weights.
self.W_h = np.random.randn(X.shape[1], self.nn_size) * np.sqrt(2.0 / X.shape[1])
self.W_out = np.random.randn(self.nn_size + 1, y.shape[1]) * np.sqrt(2.0 / (self.nn_size + 1))
batch_iters = int(X.shape[0] / self.batch_size)
batch_rem = X.shape[0] - self.batch_size * batch_iters
for i in range(self.epochs):
# update weights in every batch.
for j in range(batch_iters):
x_batch = X[j * self.batch_size : (j + 1) * self.batch_size, :]
y_batch = y[j * self.batch_size : (j + 1) * self.batch_size, :]
self.__forward_backward_prop(x_batch, y_batch)
x_batch = X[-batch_rem:]
y_batch = y[-batch_rem:]
self.__forward_backward_prop(x_batch, y_batch)
# print loss in end of epoch.
if i % 100 == 0:
a_o = self.predict_prob(X)
print("Loss = " + str(self.__loss(a_o, y)))
def predict_prob(self, X):
"""
:param X: input to predict.
:return: output vector of probabilities.
"""
z_h = np.dot(X, self.W_h)
a_h = self.__activation(z_h, self.hidden_func)
a_h_b = self.__add_bias(a_h)
z_o = np.dot(a_h_b, self.W_out)
a_o = self.__activation(z_o, self.out_func)
return a_o
def predict(self, X):
"""
:param X: input to predict.
:return: class that has max probability.
"""
a_o = self.predict_prob(X)
max_value = max(a_o)
max_index = np.where(max_value == a_o)[0]
print("Max probability is class " + str(max_index) + " with probability " + str(max_value)) | one_hidden_layer_nn.py | import numpy as np
class OneHiddenLayerNN:
"""
@brief: One hidden layer neural network with batch gradient descent.
Currently supporting only relu, tanh and sigmoid activation functions.
"""
def __init__(self, number_of_neurons, batch_size = 20, hidden_activation='relu',
out_activation='sigmoid', epochs=100, learning_rate=0.1):
"""
:param number_of_neurons: number of neurons in hidden layer.
:param batch_size: batch size.
:param hidden_activation: hidden layer activation function.
:param out_activation: out layer activation function.
:param epochs: how many times do gradient descent.
:param learning_rate: learning rate.
"""
self.nn_size = number_of_neurons
self.epochs = epochs
self.alpha = learning_rate
self.W_h = None
self.W_out = None
self.batch_size = batch_size
self.hidden_func = hidden_activation
self.out_func = out_activation
@staticmethod
def __activation(z, func_name):
"""
:param z: dot(X, W_h).
:param func_name: function name to compute.
:return: activation_function(z).
"""
if func_name == 'relu':
# relu = max(0, z).
return np.maximum(z, 0)
elif func_name == 'tanh':
# tanh = (e^z - e(-z)) / (e^z + e(-z)).
return np.tanh(z)
elif func_name == 'sigmoid':
# sigmoid = 1 / (1 + e^(-z)).
return 1 / (1 + np.exp(-z))
@staticmethod
def __d_activation(func_out, func_name):
"""
:param func_out: dot(prev_layer, W_current).
:param func_name: function name to compute.
:return: derivative of activation function.
"""
if func_name == 'relu':
# d(relu) = 1 if relu > 0 else 0.
func_o_tmp = func_out.copy()
func_o_tmp[func_out <= 0] = 0
func_o_tmp[func_out > 0] = 1
return func_o_tmp
elif func_name == 'tanh':
# d(tanh) = 1 - tanh^2.
return 1 - func_out * func_out
elif func_name == 'sigmoid':
# d(sigmoid) = sigmoid * (1 - sigmoid).
return func_out * (1 - func_out)
@staticmethod
def __loss(a_out, a):
"""
:param a_out: network output.
:param a: desired output.
:return: sum of squared difference normalized.
"""
return np.sum(np.square(a_out - a)) / a.shape[0]
def __d_out(self, a_h, a_o, a):
"""
:param a_h: hidden output.
:param a_o: net_out.
:param a: desired out.
:return: d(Loss) / d(W_out(i, k)) = SUM_i((d(Loss) / d(a_o(i)) * (d(a_o(i)) / d(W_out(i, k)).
(d(a_o(i)) / d(W_out(i, k)) != 0 if and only if i == k because of z = SUM(a_h(i) * W_out(j, i) =>
d(Loss) / d(W_out(i, k)) = (d(Loss) / d(a_o(k)) * (d(a_o(k)) / d(W_out(i, k))
= (2 * (a_o(k) - a(k))) * ((d(activation(z) / d(z)) * (d(z) / d(W_out(i, k)))
= (2 * (a_o(k) - a(k))) * a_h(i) * (d(activation(z)) / d(z))
"""
d_loss = np.dot(a_h.T, (2.0 * (a_o - a) * self.__d_activation(a_o, self.out_func)))
return self.alpha * d_loss / a.shape[0]
def _d_hidden(self, X, a_h, a_o, a):
"""
:param X: input.
:param a_h: hidden output.
:param a_o: net_out.
:param a: desired out.
:return: d(Loss) / d(W_h(i, k)) = SUM_p((d(Loss) / d(a_o(p))) * SUM_j((d(a_o(p)) / d(a_h(j)) * (d(a_h(j)) / d(W_h(i, k))))
= SUM_p((d(Loss) / d(a_o(p))) * (d(a_o(p)) / d(a_h(k)) * (d(a_h(k)) / d(W_h(i, k)))
d(Loss) / d(a_o(p)) = 2 * (a_o(p) - a(p))
d(a_o(p)) / d(a_h(k)) = ((d(activation_out(z) / d(z)) * W_out(k, p) where z = a_o(p)
d(a_h(k)) / d(W_h(i, k)) = X(i) * (d(activation_hidden(z)) / d(z)) where z = a_h(k)
"""
# W_out[1:] because first row is bias.
d_loss = np.dot(X.T, np.dot(2.0 * (a_o - a) * self.__d_activation(a_o, self.out_func), self.W_out[1:].T) *
self.__d_activation(a_h, self.hidden_func))
return self.alpha * d_loss / a.shape[0]
@staticmethod
def __add_bias(X):
"""
:param X: input.
:return: concatenate ones to input to get bias term.
"""
bias = np.ones((X.shape[0], 1))
return np.concatenate((bias, X), axis=1)
def __forward_backward_prop(self, X, y):
"""
:param X: input.
:param y: ground truth.
:return: updated weights.
"""
# multiply input by weights.
z_h = np.dot(X, self.W_h)
# apply activation function.
a_h = self.__activation(z_h, self.hidden_func)
# add 1 to hidden layer to get bias term.
a_h_b = self.__add_bias(a_h)
# multiply previous layer output by weights of current layer.
z_o = np.dot(a_h_b, self.W_out)
# apply activation function.
a_o = self.__activation(z_o, self.out_func)
# calculate derivatives.
d_out = self.__d_out(a_h_b, a_o, y)
d_hidden = self._d_hidden(X, a_h, a_o, y)
# update weights using calculated gradients.
self.W_out -= d_out
self.W_h -= d_hidden
def fit(self, X, y):
"""
:param X: input. shape = (number_of_examples, features).
:param y: output. shape = (number_of_examples, classes).
"""
# add 1 to input layer to get bias term.
X = self.__add_bias(X)
# multiplying by sqrt(2.0 / input_shape_size) for vanishing exploding gradients. (<NAME>. deep learning course).
# put bias in weights.
self.W_h = np.random.randn(X.shape[1], self.nn_size) * np.sqrt(2.0 / X.shape[1])
self.W_out = np.random.randn(self.nn_size + 1, y.shape[1]) * np.sqrt(2.0 / (self.nn_size + 1))
batch_iters = int(X.shape[0] / self.batch_size)
batch_rem = X.shape[0] - self.batch_size * batch_iters
for i in range(self.epochs):
# update weights in every batch.
for j in range(batch_iters):
x_batch = X[j * self.batch_size : (j + 1) * self.batch_size, :]
y_batch = y[j * self.batch_size : (j + 1) * self.batch_size, :]
self.__forward_backward_prop(x_batch, y_batch)
x_batch = X[-batch_rem:]
y_batch = y[-batch_rem:]
self.__forward_backward_prop(x_batch, y_batch)
# print loss in end of epoch.
if i % 100 == 0:
a_o = self.predict_prob(X)
print("Loss = " + str(self.__loss(a_o, y)))
def predict_prob(self, X):
"""
:param X: input to predict.
:return: output vector of probabilities.
"""
z_h = np.dot(X, self.W_h)
a_h = self.__activation(z_h, self.hidden_func)
a_h_b = self.__add_bias(a_h)
z_o = np.dot(a_h_b, self.W_out)
a_o = self.__activation(z_o, self.out_func)
return a_o
def predict(self, X):
"""
:param X: input to predict.
:return: class that has max probability.
"""
a_o = self.predict_prob(X)
max_value = max(a_o)
max_index = np.where(max_value == a_o)[0]
print("Max probability is class " + str(max_index) + " with probability " + str(max_value)) | 0.883513 | 0.687918 |
import time
import os
import psycopg2
import csv
import pandas as pd
import re
import tweepy
import json
from datetime import timedelta
from datetime import datetime
from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
from collections import defaultdict
def twitter_str_to_dt(dt_str):
return datetime.strptime(dt_str, "%a %b %d %H:%M:%S +0000 %Y")
def open_tweepy_api(twitter_c_key=None, twitter_c_key_secret=None,
twitter_a_key=None, twitter_a_key_secret=None,
credentials=None):
# This is a little stupid.
if credentials:
creds = {}
for line in open(credentials).readlines():
key, value = line.strip().split("=")
creds[key] = value
twitter_c_key = creds['twitter_c_key']
twitter_c_key_secret = creds['twitter_c_key_secret']
twitter_a_key = creds['twitter_a_key']
twitter_a_key_secret = creds['twitter_a_key_secret']
#authorize twitter, initialize tweepy
auth = tweepy.OAuthHandler(twitter_c_key, twitter_c_key_secret)
auth.set_access_token(twitter_a_key, twitter_a_key_secret)
api = tweepy.API(auth, wait_on_rate_limit=True, wait_on_rate_limit_notify=True)
return api
def open_database(database_name,
db_config_file,
overwrite_db=False,
owner='example',
admins=[],
named_cursor=None,
itersize=None,):
# Parse the database credentials out of the file
database_config = {"database": database_name}
for line in open(db_config_file).readlines():
key, value = line.strip().split("=")
database_config[key] = value
# cursor.execute("select * from information_schema.tables where table_name=%s", ('mytable',))
if overwrite_db:
create_statement = """CREATE DATABASE {db}
WITH
OWNER = {owner}
ENCODING = 'UTF8'
LC_COLLATE = 'en_US.UTF-8'
LC_CTYPE = 'en_US.UTF-8'
TABLESPACE = pg_default
CONNECTION LIMIT = -1;
""".format(db=database_name, owner=owner)
public_permissions = """GRANT TEMPORARY, CONNECT ON DATABASE {db} TO PUBLIC;""".format(db=database_name)
owner_permissions = """GRANT ALL ON DATABASE {db} TO {user};""".format(db=database_name, user=owner)
admin_permissions = []
for admin in admins:
admin_permissions += ['\nGRANT TEMPORARY ON DATABASE {db} to {user}'.format(db=database_name, user=admin)]
all_commands = [create_statement] + [public_permissions] + [owner_permissions] + admin_permissions
create_database_config = database_config
create_database_config['database'] = 'postgres'
database = psycopg2.connect(**database_config)
database.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
cursor = database.cursor(cursor_factory=psycopg2.extras.DictCursor)
for command in all_commands:
cursor.execute(command)
database.commit()
cursor.close()
database.close()
# Connect to the database and get a cursor object
database = psycopg2.connect(**database_config)
cursor = database.cursor(cursor_factory=psycopg2.extras.DictCursor, name=named_cursor)
if itersize is not None:
cursor.itersize = itersize
return database, cursor
def get_column_header_dict(input_column_csv):
column_header_dict = {}
with open(input_column_csv, 'r') as readfile:
reader = csv.reader(readfile, delimiter=',')
next(reader) # This line skips the header row.
for row in reader:
column_header_dict[row[0]] = {'type': row[2], 'json_fieldname': row[1], 'clean': row[4], 'instructions': row[5]}
if column_header_dict[row[0]]['clean'] == 'TRUE':
column_header_dict[row[0]]['clean'] = True
else:
column_header_dict[row[0]]['clean'] = False
return column_header_dict
def close_database(cursor, database, commit=True):
# Close everything
cursor.close()
if commit:
database.commit()
database.close()
def clean(s):
# Fix bytes/str mixing from earlier in code:
if type(s) is bytes:
s = s.decode('utf-8')
# Replace weird characters that make Postgres unhappy
s = s.replace("\x00", "") if s else None
# re_pattern = re.compile(u"\u0000", re.UNICODE)
# s = re_pattern.sub(u'\u0000', '')
# add_item = re.sub(r'(?<!\\)\\(?!["\\/bfnrt]|u[0-9a-fA-F]{4})', r'', add_item)
s = re.sub(r'(?<!\\)\\u0000', r'', s) if s else None
return s
def c(u):
# Encode unicode so it plays nice with the string formatting
return u.encode('utf8')
def get_last_modified(json_file):
return os.path.getmtime(json_file)
def within_time_bounds(json_file, start_time, end_time):
json_modified_time = get_last_modified(json_file)
return (json_modified_time >= time.mktime(start_time.timetuple())) and (json_modified_time <= (time.mktime(end_time.timetuple()) + timedelta(days=1).total_seconds()))
def save_to_csv(rows, output_filename, column_headers=None):
with open(output_filename, 'w') as outfile:
writer = csv.writer(outfile, delimiter=',')
if column_headers is None:
writer.writerow(rows[0].keys())
else:
writer.writerow(column_headers)
for item in rows:
if column_headers is None:
# This might not work if dictionaries don't pull out keys in same order.
writer.writerow(item.values())
else:
output_row = [item[column] for column in column_headers]
writer.writerow(output_row)
return
def load_from_csv(input_csv, time_columns=[]):
with open(input_csv, 'r') as readfile:
reader = csv.reader(readfile, delimiter=',')
output_dict_list = []
header = next(reader)
for row in reader:
output_dict = {}
for idx, item in enumerate(row):
# Time conversion is a little inefficient. But who cares!
if header[idx] in time_columns:
item = datetime.strptime(item, "%Y-%m-%d %H:%M:%S")
output_dict[header[idx]] = item
output_dict_list += [output_dict]
return output_dict_list
def list_on_key(dict_list, key):
""" Is there a one-liner for this?
"""
return_list = []
for sub_dict in dict_list:
return_list += [sub_dict[key]]
return return_list
def extract_entity_to_column():
return
def to_list_of_dicts(cursor):
results = cursor.fetchall()
dict_result = []
for row in results:
dict_result.append(dict(row))
return dict_result
def to_pandas(cursor, dtype=None):
results = cursor.fetchall()
column_headers = list(results[0].keys())
if not dtype:
data_frame = pd.DataFrame(results)
else:
new_results = []
for result in results:
new_results += [[str(x) if x else None for x in result]]
data_frame = pd.DataFrame(new_results, dtype='str')
data_frame.columns = column_headers
return data_frame
def sort_json(input_file, output_file=None, reverse=False, key='created_at', format=None):
if output_file is None:
output_file = input_file
with open(input_file, "r") as f:
json_dict = json.load(f)
if key == 'created_at':
json_dict.sort(reverse=reverse, key=lambda t: twitter_str_to_dt(t[key]))
else:
json_dict.sort(reverse=reverse, key=lambda t: t[key])
with open(output_file, 'w') as f:
json.dump(json_dict, f)
return
def write_json(input_file, output_file=None):
return
def format_json(input_file, output_file=None, json_format='newlines'):
if output_file is None:
output_file = input_file
with open(input_file, "r") as f:
json_dict = json.load(f)
if json_format == 'newlines':
with open(output_file, "w") as openfile:
openfile.write("[\n")
for idx, tweet in enumerate(json_dict):
json.dump(tweet, openfile)
if idx == len(json_dict) - 1:
openfile.write('\n')
else:
openfile.write(",\n")
openfile.write("]")
return
def sample_json_to_csv(input_directories, number, keys):
return
def int_dict():
return defaultdict(int)
def set_dict():
return defaultdict(set)
def dict_dict():
return defaultdict(dict)
def list_dict():
return defaultdict(dict)
def sql_type_dictionary():
""" Return a dictionary of PSQL types for typical column names
in Twitter2SQL databases.
"""
type_dict = {'user_id': 'bigint',
'tweet': 'TEXT',
'user_name': 'TEXT',
'user_screen_name': 'TEXT',
'in_reply_to_status_id': 'bigint',
'created_at': 'timestamptz',
'in_reply_to_user_screen_name': 'TEXT',
'in_reply_to_user_id': 'bigint'}
return type_dict | twitter2sql/core/util.py | import time
import os
import psycopg2
import csv
import pandas as pd
import re
import tweepy
import json
from datetime import timedelta
from datetime import datetime
from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
from collections import defaultdict
def twitter_str_to_dt(dt_str):
return datetime.strptime(dt_str, "%a %b %d %H:%M:%S +0000 %Y")
def open_tweepy_api(twitter_c_key=None, twitter_c_key_secret=None,
twitter_a_key=None, twitter_a_key_secret=None,
credentials=None):
# This is a little stupid.
if credentials:
creds = {}
for line in open(credentials).readlines():
key, value = line.strip().split("=")
creds[key] = value
twitter_c_key = creds['twitter_c_key']
twitter_c_key_secret = creds['twitter_c_key_secret']
twitter_a_key = creds['twitter_a_key']
twitter_a_key_secret = creds['twitter_a_key_secret']
#authorize twitter, initialize tweepy
auth = tweepy.OAuthHandler(twitter_c_key, twitter_c_key_secret)
auth.set_access_token(twitter_a_key, twitter_a_key_secret)
api = tweepy.API(auth, wait_on_rate_limit=True, wait_on_rate_limit_notify=True)
return api
def open_database(database_name,
db_config_file,
overwrite_db=False,
owner='example',
admins=[],
named_cursor=None,
itersize=None,):
# Parse the database credentials out of the file
database_config = {"database": database_name}
for line in open(db_config_file).readlines():
key, value = line.strip().split("=")
database_config[key] = value
# cursor.execute("select * from information_schema.tables where table_name=%s", ('mytable',))
if overwrite_db:
create_statement = """CREATE DATABASE {db}
WITH
OWNER = {owner}
ENCODING = 'UTF8'
LC_COLLATE = 'en_US.UTF-8'
LC_CTYPE = 'en_US.UTF-8'
TABLESPACE = pg_default
CONNECTION LIMIT = -1;
""".format(db=database_name, owner=owner)
public_permissions = """GRANT TEMPORARY, CONNECT ON DATABASE {db} TO PUBLIC;""".format(db=database_name)
owner_permissions = """GRANT ALL ON DATABASE {db} TO {user};""".format(db=database_name, user=owner)
admin_permissions = []
for admin in admins:
admin_permissions += ['\nGRANT TEMPORARY ON DATABASE {db} to {user}'.format(db=database_name, user=admin)]
all_commands = [create_statement] + [public_permissions] + [owner_permissions] + admin_permissions
create_database_config = database_config
create_database_config['database'] = 'postgres'
database = psycopg2.connect(**database_config)
database.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
cursor = database.cursor(cursor_factory=psycopg2.extras.DictCursor)
for command in all_commands:
cursor.execute(command)
database.commit()
cursor.close()
database.close()
# Connect to the database and get a cursor object
database = psycopg2.connect(**database_config)
cursor = database.cursor(cursor_factory=psycopg2.extras.DictCursor, name=named_cursor)
if itersize is not None:
cursor.itersize = itersize
return database, cursor
def get_column_header_dict(input_column_csv):
column_header_dict = {}
with open(input_column_csv, 'r') as readfile:
reader = csv.reader(readfile, delimiter=',')
next(reader) # This line skips the header row.
for row in reader:
column_header_dict[row[0]] = {'type': row[2], 'json_fieldname': row[1], 'clean': row[4], 'instructions': row[5]}
if column_header_dict[row[0]]['clean'] == 'TRUE':
column_header_dict[row[0]]['clean'] = True
else:
column_header_dict[row[0]]['clean'] = False
return column_header_dict
def close_database(cursor, database, commit=True):
# Close everything
cursor.close()
if commit:
database.commit()
database.close()
def clean(s):
# Fix bytes/str mixing from earlier in code:
if type(s) is bytes:
s = s.decode('utf-8')
# Replace weird characters that make Postgres unhappy
s = s.replace("\x00", "") if s else None
# re_pattern = re.compile(u"\u0000", re.UNICODE)
# s = re_pattern.sub(u'\u0000', '')
# add_item = re.sub(r'(?<!\\)\\(?!["\\/bfnrt]|u[0-9a-fA-F]{4})', r'', add_item)
s = re.sub(r'(?<!\\)\\u0000', r'', s) if s else None
return s
def c(u):
# Encode unicode so it plays nice with the string formatting
return u.encode('utf8')
def get_last_modified(json_file):
return os.path.getmtime(json_file)
def within_time_bounds(json_file, start_time, end_time):
json_modified_time = get_last_modified(json_file)
return (json_modified_time >= time.mktime(start_time.timetuple())) and (json_modified_time <= (time.mktime(end_time.timetuple()) + timedelta(days=1).total_seconds()))
def save_to_csv(rows, output_filename, column_headers=None):
with open(output_filename, 'w') as outfile:
writer = csv.writer(outfile, delimiter=',')
if column_headers is None:
writer.writerow(rows[0].keys())
else:
writer.writerow(column_headers)
for item in rows:
if column_headers is None:
# This might not work if dictionaries don't pull out keys in same order.
writer.writerow(item.values())
else:
output_row = [item[column] for column in column_headers]
writer.writerow(output_row)
return
def load_from_csv(input_csv, time_columns=[]):
with open(input_csv, 'r') as readfile:
reader = csv.reader(readfile, delimiter=',')
output_dict_list = []
header = next(reader)
for row in reader:
output_dict = {}
for idx, item in enumerate(row):
# Time conversion is a little inefficient. But who cares!
if header[idx] in time_columns:
item = datetime.strptime(item, "%Y-%m-%d %H:%M:%S")
output_dict[header[idx]] = item
output_dict_list += [output_dict]
return output_dict_list
def list_on_key(dict_list, key):
""" Is there a one-liner for this?
"""
return_list = []
for sub_dict in dict_list:
return_list += [sub_dict[key]]
return return_list
def extract_entity_to_column():
return
def to_list_of_dicts(cursor):
results = cursor.fetchall()
dict_result = []
for row in results:
dict_result.append(dict(row))
return dict_result
def to_pandas(cursor, dtype=None):
results = cursor.fetchall()
column_headers = list(results[0].keys())
if not dtype:
data_frame = pd.DataFrame(results)
else:
new_results = []
for result in results:
new_results += [[str(x) if x else None for x in result]]
data_frame = pd.DataFrame(new_results, dtype='str')
data_frame.columns = column_headers
return data_frame
def sort_json(input_file, output_file=None, reverse=False, key='created_at', format=None):
if output_file is None:
output_file = input_file
with open(input_file, "r") as f:
json_dict = json.load(f)
if key == 'created_at':
json_dict.sort(reverse=reverse, key=lambda t: twitter_str_to_dt(t[key]))
else:
json_dict.sort(reverse=reverse, key=lambda t: t[key])
with open(output_file, 'w') as f:
json.dump(json_dict, f)
return
def write_json(input_file, output_file=None):
return
def format_json(input_file, output_file=None, json_format='newlines'):
if output_file is None:
output_file = input_file
with open(input_file, "r") as f:
json_dict = json.load(f)
if json_format == 'newlines':
with open(output_file, "w") as openfile:
openfile.write("[\n")
for idx, tweet in enumerate(json_dict):
json.dump(tweet, openfile)
if idx == len(json_dict) - 1:
openfile.write('\n')
else:
openfile.write(",\n")
openfile.write("]")
return
def sample_json_to_csv(input_directories, number, keys):
return
def int_dict():
return defaultdict(int)
def set_dict():
return defaultdict(set)
def dict_dict():
return defaultdict(dict)
def list_dict():
return defaultdict(dict)
def sql_type_dictionary():
""" Return a dictionary of PSQL types for typical column names
in Twitter2SQL databases.
"""
type_dict = {'user_id': 'bigint',
'tweet': 'TEXT',
'user_name': 'TEXT',
'user_screen_name': 'TEXT',
'in_reply_to_status_id': 'bigint',
'created_at': 'timestamptz',
'in_reply_to_user_screen_name': 'TEXT',
'in_reply_to_user_id': 'bigint'}
return type_dict | 0.299617 | 0.059811 |
from fastapi import HTTPException
from iso639 import languages
import pytest
from textblob import TextBlob
from app.internal.translation import (
_detect_text_language, _get_language_code, _get_user_language,
translate_text, translate_text_for_user
)
TEXT = [
("Привет мой друг", "english", "russian"),
("Hola mi amigo", "english", "spanish"),
("Bonjour, mon ami", "english", "french"),
("Hallo, me<NAME>", "english", "german"),
]
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_original_lang(text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert "Hello my friend" == answer
assert TextBlob(text).detect_language() == languages.get(
name=original_lang.capitalize()).alpha2
assert TextBlob(answer).detect_language() == languages.get(
name=target_lang.capitalize()).alpha2
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_without_original_lang(
text, target_lang, original_lang):
answer = translate_text(text, target_lang)
assert "Hello my friend" == answer
assert TextBlob(answer).detect_language() == languages.get(
name=target_lang.capitalize()).alpha2
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_identical_original_and_target_lang(
text, target_lang, original_lang):
answer = translate_text(text, original_lang, original_lang)
assert answer == text
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_same_original_target_lang_without_original_lang(
text, target_lang, original_lang):
answer = translate_text(text, original_lang)
assert answer == text
def test_translate_text_without_text_with_original_target_lang():
answer = translate_text("", "english", "russian")
assert answer == ""
def test_translate_text_without_text_without_original_lang():
answer = translate_text("", "english")
assert answer == ""
def test_get_language_code():
answer = _get_language_code("english")
assert answer == "en"
def test_get_user_language(user, session):
user_id = user.id
answer = _get_user_language(user_id, session=session)
assert user_id == 1
assert answer.lower() == "english"
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_for_valid_user(
text, target_lang, original_lang, session, user):
user_id = user.id
answer = translate_text_for_user(text, session, user_id)
assert answer == "Hello my friend"
def test_translate_text_for_invalid_user(session, user):
user_id = user.id
answer = translate_text_for_user("Привет мой друг", session, user_id + 1)
assert answer == "Привет мой друг"
def test_detect_text_language():
answer = _detect_text_language("Hello my friend")
assert answer == "en"
@pytest.mark.parametrize("text, target_lang, original_lang",
[("Hoghhflaff", "english", "spanish"),
("Bdonfdjourr", "english", "french"),
("Hafdllnnc", "english", "german"),
])
def test_translate_text_with_text_impossible_to_translate(
text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert answer == text
@pytest.mark.parametrize("text, target_lang, original_lang",
[("@Здравствуй#мой$друг!", "english", "russian"),
("@Hola#mi$amigo!", "english", "spanish"),
("@Bonjour#mon$ami!", "english", "french"),
("@Hallo#mein$Freund!", "english", "german"),
])
def test_translate_text_with_symbols(text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert "@ Hello # my $ friend!" == answer
@pytest.mark.parametrize("text, target_lang, original_lang",
[("Привет мой друг", "italian", "spanish"),
("Hola mi amigo", "english", "russian"),
("Bonjour, mon ami", "russian", "german"),
("Ciao amico", "french", "german")
])
def test_translate_text_with_with_incorrect_lang(
text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert answer == text
def test_get_user_language_for_invalid_user(session, user):
user_id = user.id + 1
answer = _get_user_language(user_id, session=session)
assert not answer
def test_get_user_language_for_invalid_language(session, user):
user.language_id = 34
session.commit()
with pytest.raises(HTTPException):
_get_user_language(user.id, session=session) | tests/test_translation.py | from fastapi import HTTPException
from iso639 import languages
import pytest
from textblob import TextBlob
from app.internal.translation import (
_detect_text_language, _get_language_code, _get_user_language,
translate_text, translate_text_for_user
)
TEXT = [
("Привет мой друг", "english", "russian"),
("Hola mi amigo", "english", "spanish"),
("Bonjour, mon ami", "english", "french"),
("Hallo, me<NAME>", "english", "german"),
]
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_original_lang(text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert "Hello my friend" == answer
assert TextBlob(text).detect_language() == languages.get(
name=original_lang.capitalize()).alpha2
assert TextBlob(answer).detect_language() == languages.get(
name=target_lang.capitalize()).alpha2
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_without_original_lang(
text, target_lang, original_lang):
answer = translate_text(text, target_lang)
assert "Hello my friend" == answer
assert TextBlob(answer).detect_language() == languages.get(
name=target_lang.capitalize()).alpha2
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_identical_original_and_target_lang(
text, target_lang, original_lang):
answer = translate_text(text, original_lang, original_lang)
assert answer == text
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_with_same_original_target_lang_without_original_lang(
text, target_lang, original_lang):
answer = translate_text(text, original_lang)
assert answer == text
def test_translate_text_without_text_with_original_target_lang():
answer = translate_text("", "english", "russian")
assert answer == ""
def test_translate_text_without_text_without_original_lang():
answer = translate_text("", "english")
assert answer == ""
def test_get_language_code():
answer = _get_language_code("english")
assert answer == "en"
def test_get_user_language(user, session):
user_id = user.id
answer = _get_user_language(user_id, session=session)
assert user_id == 1
assert answer.lower() == "english"
@pytest.mark.parametrize("text, target_lang, original_lang", TEXT)
def test_translate_text_for_valid_user(
text, target_lang, original_lang, session, user):
user_id = user.id
answer = translate_text_for_user(text, session, user_id)
assert answer == "Hello my friend"
def test_translate_text_for_invalid_user(session, user):
user_id = user.id
answer = translate_text_for_user("Привет мой друг", session, user_id + 1)
assert answer == "Привет мой друг"
def test_detect_text_language():
answer = _detect_text_language("Hello my friend")
assert answer == "en"
@pytest.mark.parametrize("text, target_lang, original_lang",
[("Hoghhflaff", "english", "spanish"),
("Bdonfdjourr", "english", "french"),
("Hafdllnnc", "english", "german"),
])
def test_translate_text_with_text_impossible_to_translate(
text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert answer == text
@pytest.mark.parametrize("text, target_lang, original_lang",
[("@Здравствуй#мой$друг!", "english", "russian"),
("@Hola#mi$amigo!", "english", "spanish"),
("@Bonjour#mon$ami!", "english", "french"),
("@Hallo#mein$Freund!", "english", "german"),
])
def test_translate_text_with_symbols(text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert "@ Hello # my $ friend!" == answer
@pytest.mark.parametrize("text, target_lang, original_lang",
[("Привет мой друг", "italian", "spanish"),
("Hola mi amigo", "english", "russian"),
("Bonjour, mon ami", "russian", "german"),
("Ciao amico", "french", "german")
])
def test_translate_text_with_with_incorrect_lang(
text, target_lang, original_lang):
answer = translate_text(text, target_lang, original_lang)
assert answer == text
def test_get_user_language_for_invalid_user(session, user):
user_id = user.id + 1
answer = _get_user_language(user_id, session=session)
assert not answer
def test_get_user_language_for_invalid_language(session, user):
user.language_id = 34
session.commit()
with pytest.raises(HTTPException):
_get_user_language(user.id, session=session) | 0.503418 | 0.333246 |
import json
import os
import copy
from Evaluate import cocoTools
sourceJsonPath = './rainSnowGt.json'
destDir = ''
with open('./splitSequenceTranslator.json') as f:
splitSequenceTranslator = json.load(f)
# List rain removal methods here
methods = ['baseline',
'Fu2017',
'GargNayar/Median',
'GargNayar/STCorr',
'IDCGAN',
'Kang2012',
'Kim2015-blur']
with open(sourceJsonPath, 'r') as f:
sourceGt = json.load(f)
for method in methods:
methodGt = copy.deepcopy(sourceGt)
removedImageIds = dict()
if 'images' in methodGt:
images = []
imageList = methodGt['images']
for image in imageList:
methodImage = image
imageNumber = image['file_name'].split('-')[-1]
number = int(imageNumber.replace('.png',''))
if number >= 40 and number <= 5990:
scene = image['file_name'].split('/')[0]
sequence = image['file_name'].split('/')[1]
if 'baseline' not in method:
newMethodPath = os.path.join(destDir,
scene,
sequence,
method,
imageNumber)
methodImage['file_name'] = newMethodPath
images.append(methodImage)
else:
removedImageIds[image['id']] = image['id'] # Does't really matter what the entry is, only interested in key
if 'annotations' in methodGt:
annotations = []
for annotation in methodGt['annotations']:
if annotation['image_id'] not in removedImageIds:
annotations.append(annotation)
else:
print("Removed annotation " + str(annotation['id']) + ' for image ' + str(annotation['image_id']))
methodGt['images'] = images
methodGt['annotations'] = annotations
# Also make sure to remove the annotations at the removed image ID's
outputPath = os.path.join(destDir, method.replace('/', '-') + '.json')
with open(os.path.join(destDir, method.replace('/', '-') + '.json'), 'w') as f:
json.dump(methodGt, f)
cocoTools.removeInstancesInsideDontCare('P:/Private/Traffic safety/Data/RainSnow/PixelLevelAnnotationsOriginal',
outputPath,
splitSequenceTranslator,
destDir) | InstanceSegmentation/copyJsonForRainSnow.py | import json
import os
import copy
from Evaluate import cocoTools
sourceJsonPath = './rainSnowGt.json'
destDir = ''
with open('./splitSequenceTranslator.json') as f:
splitSequenceTranslator = json.load(f)
# List rain removal methods here
methods = ['baseline',
'Fu2017',
'GargNayar/Median',
'GargNayar/STCorr',
'IDCGAN',
'Kang2012',
'Kim2015-blur']
with open(sourceJsonPath, 'r') as f:
sourceGt = json.load(f)
for method in methods:
methodGt = copy.deepcopy(sourceGt)
removedImageIds = dict()
if 'images' in methodGt:
images = []
imageList = methodGt['images']
for image in imageList:
methodImage = image
imageNumber = image['file_name'].split('-')[-1]
number = int(imageNumber.replace('.png',''))
if number >= 40 and number <= 5990:
scene = image['file_name'].split('/')[0]
sequence = image['file_name'].split('/')[1]
if 'baseline' not in method:
newMethodPath = os.path.join(destDir,
scene,
sequence,
method,
imageNumber)
methodImage['file_name'] = newMethodPath
images.append(methodImage)
else:
removedImageIds[image['id']] = image['id'] # Does't really matter what the entry is, only interested in key
if 'annotations' in methodGt:
annotations = []
for annotation in methodGt['annotations']:
if annotation['image_id'] not in removedImageIds:
annotations.append(annotation)
else:
print("Removed annotation " + str(annotation['id']) + ' for image ' + str(annotation['image_id']))
methodGt['images'] = images
methodGt['annotations'] = annotations
# Also make sure to remove the annotations at the removed image ID's
outputPath = os.path.join(destDir, method.replace('/', '-') + '.json')
with open(os.path.join(destDir, method.replace('/', '-') + '.json'), 'w') as f:
json.dump(methodGt, f)
cocoTools.removeInstancesInsideDontCare('P:/Private/Traffic safety/Data/RainSnow/PixelLevelAnnotationsOriginal',
outputPath,
splitSequenceTranslator,
destDir) | 0.250271 | 0.17849 |
import abc
import spar_python.query_generation.query_schema as qs
"""
This class represents the vertical integration of creating aggregators
for queries, refining the queries within the batch, and writing the
selected queries and their results to the results database within one
object.
"""
class QueryBatch(object):
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def __init__(self, *args):
"""
Queries, and args needed to initialize that BOQ
"""
pass
@abc.abstractmethod
def produce_queries(self):
"""
Returns the query dicts that the bob is based around, used primarily
for debugging purposes
"""
pass
@abc.abstractmethod
def make_aggregator(self):
"""
Returns a gen_choose aggregator which wraps the associated
aggregators for the queries contained in the query batch
"""
pass
@abc.abstractmethod
def refine_queries(self, agg_result):
"""
Takes in the results of the aggregators and refines queries.
Selects which queries should be recorded in the results database.
To discard a query it simple does not add it to the refined list of
queries and their results. It then sets that equal to self.refined_queries_results.
It also returns a list of the refined queries and their results, which
can be ignored or used at top level.
"""
pass
@abc.abstractmethod
def process_results(self, agg_results, db_object, query_file_handle, refined_queries = None):
"""
Takes in the aggregator results, with those results, determines
which queries in the batch are 'interesting' it then instantiates
query_results for those queries and uses it to write it to the
results database.
Refine arguement is a list of already refined queries if the user
does not wish to rely on the pre-defined refine queries function
"""
@staticmethod
def _print_query(q, query_file_handler):
"""
Prints passed in query in specific format to the passed in file.
This is here so that it can toggle between * and id easily for now
"""
sql_line = '%d SELECT * FROM main WHERE %s\n' % \
(q[qs.QRY_QID], q['where_clause'].replace('\'\'','\''))
query_file_handler.write(sql_line) | spar_python/query_generation/BOQs/query_batch.py |
import abc
import spar_python.query_generation.query_schema as qs
"""
This class represents the vertical integration of creating aggregators
for queries, refining the queries within the batch, and writing the
selected queries and their results to the results database within one
object.
"""
class QueryBatch(object):
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def __init__(self, *args):
"""
Queries, and args needed to initialize that BOQ
"""
pass
@abc.abstractmethod
def produce_queries(self):
"""
Returns the query dicts that the bob is based around, used primarily
for debugging purposes
"""
pass
@abc.abstractmethod
def make_aggregator(self):
"""
Returns a gen_choose aggregator which wraps the associated
aggregators for the queries contained in the query batch
"""
pass
@abc.abstractmethod
def refine_queries(self, agg_result):
"""
Takes in the results of the aggregators and refines queries.
Selects which queries should be recorded in the results database.
To discard a query it simple does not add it to the refined list of
queries and their results. It then sets that equal to self.refined_queries_results.
It also returns a list of the refined queries and their results, which
can be ignored or used at top level.
"""
pass
@abc.abstractmethod
def process_results(self, agg_results, db_object, query_file_handle, refined_queries = None):
"""
Takes in the aggregator results, with those results, determines
which queries in the batch are 'interesting' it then instantiates
query_results for those queries and uses it to write it to the
results database.
Refine arguement is a list of already refined queries if the user
does not wish to rely on the pre-defined refine queries function
"""
@staticmethod
def _print_query(q, query_file_handler):
"""
Prints passed in query in specific format to the passed in file.
This is here so that it can toggle between * and id easily for now
"""
sql_line = '%d SELECT * FROM main WHERE %s\n' % \
(q[qs.QRY_QID], q['where_clause'].replace('\'\'','\''))
query_file_handler.write(sql_line) | 0.740456 | 0.403596 |
from sentiment_analysis import SentiStrength
from question_analysis.post import Post
import json
import os
class FeatureAnalysis:
def __init__(self,request={},config_file="config_question_analysis.json"):
in_file=open(os.path.dirname(os.path.abspath(__file__))+'/'+config_file,"r")
self.__config=json.loads(in_file.read())
in_file.close()
if request=={}:
raise Exception("Empty body")
else:
self.__post = Post(request)
self.__code_snippet = False
self.__weekday = None
self.__gmt_hour = None
self.__body_length = 0
self.__title_length= 0
self.__sentiment_positive_score= False
self.__sentiment_negative_score= False
self.__n_tag = False
self.__avg_upperchars_ppost = 0
self.__url = False
self.__avg_upperchars_ppost_disc = None
self.__user_reputation = None
def extract_features(self):
self.__analyze_features()
return {
"CodeSnippet":str(self.__code_snippet),
"Weekday": self.__weekday,
"GMTHour": self.__gmt_hour,
"BodyLength":self.__body_length,
"TitleLength": self.__title_length,
"SentimentPositiveScore": str(self.__sentiment_positive_score),
"SentimentNegativeScore": str(self.__sentiment_negative_score),
"NTag": str(self.__n_tag),
"AvgUpperCharsPPost":self.__avg_upperchars_ppost,
"URL": str(self.__url),
"AvgUpperCharsPPostDisc":self.__avg_upperchars_ppost_disc,
"UserReputation":self.__user_reputation
}
def __analyze_features(self):
#CodeSnippet
if len(self.__post.code) > 0:
self.__code_snippet= True
#Weekday
self.__weekday = self.__is_weekend()
#GMTHour
self.__gmt_hour = self.__get_day_time()
#BodyLength
self.__body_length = self.__assign_cluster(self.__get_text_length(self.__post.body),
self.__config["body_length_clusters"])
self.__title_length = self.__assign_cluster(self.__get_text_length(self.__post.title),
self.__config["title_length_clusters"])
#SentimentScore
senti_scores=SentiStrength('EN').get_sentiment(self.__post.title +" "+self.__post.body)
self.__sentiment_positive_score,self.__sentiment_negative_score= self.__get_sentiment_scores(senti_scores)
#Ntag
if len(self.__post.tags) > 1:
self.__n_tag = True
#AvgUpperCharsPPost
self.__avg_upperchars_ppost = str(((self.__get_uppercase_ratio(self.__post.body) +
self.__get_uppercase_ratio(self.__post.title))/2),
)
#AvgUpperCharsPPost cluster
self.__avg_upperchars_ppost_disc= self.__assign_cluster(float(self.__avg_upperchars_ppost),self.__config["uppercase_clusters"])
#URL
if len(self.__post.url) > 0:
self.__url= True
self.__user_reputation = self.__assign_cluster(self.__post.reputation, self.__config["reputation_clusters"])
def __is_weekend(self):
if int(self.__post.day) == 0 or int(self.__post.day) == 6:
return 'Weekend'
else:
return 'Weekday'
def __get_day_time(self):
int_hour = int(self.__post.hour)
if int_hour >= 12 and int_hour <= 17:
return 'Afternoon'
elif int_hour >= 18 and int_hour <= 22:
return 'Evening'
elif int_hour >= 23 or int_hour <= 5:
return 'Nigth'
else:
return 'Morning'
def __assign_cluster(self,n,clusters):
if n == 0:
return min(clusters.keys(),key=(lambda k: clusters[k]))
for key,value in clusters.items():
if n >= value[0] and n < value[1]:
return key
def __get_text_length(self,text):
return len(text.replace(" ", ""))
def __get_sentiment_scores(self,scores):
positive= False
negative= False
positive_score= float(scores['positive'])
negative_score= float(scores['negative'])
if positive_score > 1:
positive = True
if negative_score < -1:
negative = True
return positive,negative
def __get_uppercase_ratio(self,text):
ratio=0
upper_char=sum(1 for c in text if c.isupper())
if upper_char !=0:
ratio=upper_char/len(text)
return ratio | src/question_analysis/feature_analysis.py | from sentiment_analysis import SentiStrength
from question_analysis.post import Post
import json
import os
class FeatureAnalysis:
def __init__(self,request={},config_file="config_question_analysis.json"):
in_file=open(os.path.dirname(os.path.abspath(__file__))+'/'+config_file,"r")
self.__config=json.loads(in_file.read())
in_file.close()
if request=={}:
raise Exception("Empty body")
else:
self.__post = Post(request)
self.__code_snippet = False
self.__weekday = None
self.__gmt_hour = None
self.__body_length = 0
self.__title_length= 0
self.__sentiment_positive_score= False
self.__sentiment_negative_score= False
self.__n_tag = False
self.__avg_upperchars_ppost = 0
self.__url = False
self.__avg_upperchars_ppost_disc = None
self.__user_reputation = None
def extract_features(self):
self.__analyze_features()
return {
"CodeSnippet":str(self.__code_snippet),
"Weekday": self.__weekday,
"GMTHour": self.__gmt_hour,
"BodyLength":self.__body_length,
"TitleLength": self.__title_length,
"SentimentPositiveScore": str(self.__sentiment_positive_score),
"SentimentNegativeScore": str(self.__sentiment_negative_score),
"NTag": str(self.__n_tag),
"AvgUpperCharsPPost":self.__avg_upperchars_ppost,
"URL": str(self.__url),
"AvgUpperCharsPPostDisc":self.__avg_upperchars_ppost_disc,
"UserReputation":self.__user_reputation
}
def __analyze_features(self):
#CodeSnippet
if len(self.__post.code) > 0:
self.__code_snippet= True
#Weekday
self.__weekday = self.__is_weekend()
#GMTHour
self.__gmt_hour = self.__get_day_time()
#BodyLength
self.__body_length = self.__assign_cluster(self.__get_text_length(self.__post.body),
self.__config["body_length_clusters"])
self.__title_length = self.__assign_cluster(self.__get_text_length(self.__post.title),
self.__config["title_length_clusters"])
#SentimentScore
senti_scores=SentiStrength('EN').get_sentiment(self.__post.title +" "+self.__post.body)
self.__sentiment_positive_score,self.__sentiment_negative_score= self.__get_sentiment_scores(senti_scores)
#Ntag
if len(self.__post.tags) > 1:
self.__n_tag = True
#AvgUpperCharsPPost
self.__avg_upperchars_ppost = str(((self.__get_uppercase_ratio(self.__post.body) +
self.__get_uppercase_ratio(self.__post.title))/2),
)
#AvgUpperCharsPPost cluster
self.__avg_upperchars_ppost_disc= self.__assign_cluster(float(self.__avg_upperchars_ppost),self.__config["uppercase_clusters"])
#URL
if len(self.__post.url) > 0:
self.__url= True
self.__user_reputation = self.__assign_cluster(self.__post.reputation, self.__config["reputation_clusters"])
def __is_weekend(self):
if int(self.__post.day) == 0 or int(self.__post.day) == 6:
return 'Weekend'
else:
return 'Weekday'
def __get_day_time(self):
int_hour = int(self.__post.hour)
if int_hour >= 12 and int_hour <= 17:
return 'Afternoon'
elif int_hour >= 18 and int_hour <= 22:
return 'Evening'
elif int_hour >= 23 or int_hour <= 5:
return 'Nigth'
else:
return 'Morning'
def __assign_cluster(self,n,clusters):
if n == 0:
return min(clusters.keys(),key=(lambda k: clusters[k]))
for key,value in clusters.items():
if n >= value[0] and n < value[1]:
return key
def __get_text_length(self,text):
return len(text.replace(" ", ""))
def __get_sentiment_scores(self,scores):
positive= False
negative= False
positive_score= float(scores['positive'])
negative_score= float(scores['negative'])
if positive_score > 1:
positive = True
if negative_score < -1:
negative = True
return positive,negative
def __get_uppercase_ratio(self,text):
ratio=0
upper_char=sum(1 for c in text if c.isupper())
if upper_char !=0:
ratio=upper_char/len(text)
return ratio | 0.174762 | 0.132374 |
import os
from india_wris.base import WaterQualityBase
DATASET_NAME = 'India_WRIS_Surface'
## Defining MCF and TMCF template nodes
SOLUTE_MCF_NODES = """Node: dcid:Concentration_{variable}_BodyOfWater_SurfaceWater
name: Concentration of {variable}, SurfaceWater
typeOf: dcs:StatisticalVariable
populationType: dcs:BodyOfWater
contaminatedThing: dcs:SurfaceWater
contaminant: dcs:{variable}
measuredProperty: dcs:concentration
measurementMethod: dcs:WRIS_India
statType: dcs:measuredValue
"""
CHEMPROP_MCF_NODES = """Node: dcid:{variable}_BodyOfWater_SurfaceWater
name: {variable}, Surface Water
typeOf: dcs:StatisticalVariable
populationType: dcs:BodyOfWater
waterSource: dcs:SurfaceWater
measuredProperty: dcs:{dcid}
measurementMethod: dcs:WRIS_India
statType: dcs:measuredValue
"""
TMCF_ISOCODE = """Node: E:{dataset_name}->E0
dcid: C:{dataset_name}->dcid
typeOf: dcs:WaterQualitySite
Node: E:{dataset_name}->E1
typeOf: dcs:Place
lgdCode: C:{dataset_name}->DistrictCode
"""
SOLUTE_TMCF_NODES = """Node: E:{dataset_name}->E{index}
typeOf: dcid:StatVarObservation
observationDate: C:{dataset_name}->Month
observationAbout: E:{dataset_name}->E0
containedIn: E:{dataset_name}->E1
observationPeriod: "P1M"
variableMeasured: dcid:Concentration_{variable}_BodyOfWater_SurfaceWater
measuredProperty: dcs:concentration
value: C:{dataset_name}->"{name}"
"""
CHEMPROP_TMCF_NODES = """Node: E:{dataset_name}->E{index}
typeOf: dcid:StatVarObservation
observationDate: C:{dataset_name}->Month
observationAbout: E:{dataset_name}->E0
containedIn: E:{dataset_name}->E1
observationPeriod: "P1M"
variableMeasured: dcid:{variable}_BodyOfWater_SurfaceWater
measuredProperty: dcs:{dcid}
value: C:{dataset_name}->"{name}"
"""
UNIT = """unit: dcid:{unit}
"""
template_strings = {
'solute_mcf': SOLUTE_MCF_NODES,
'solute_tmcf': SOLUTE_TMCF_NODES,
'chemprop_mcf': CHEMPROP_MCF_NODES,
'chemprop_tmcf': CHEMPROP_TMCF_NODES,
'site_dcid': TMCF_ISOCODE,
'unit_node': UNIT
}
preprocessor = WaterQualityBase(dataset_name=DATASET_NAME,
util_names='surfaceWater',
template_strings=template_strings)
preprocessor.create_dcids_in_csv()
preprocessor.create_mcfs() | scripts/india_wris/India_WRIS_Surface/preprocess.py |
import os
from india_wris.base import WaterQualityBase
DATASET_NAME = 'India_WRIS_Surface'
## Defining MCF and TMCF template nodes
SOLUTE_MCF_NODES = """Node: dcid:Concentration_{variable}_BodyOfWater_SurfaceWater
name: Concentration of {variable}, SurfaceWater
typeOf: dcs:StatisticalVariable
populationType: dcs:BodyOfWater
contaminatedThing: dcs:SurfaceWater
contaminant: dcs:{variable}
measuredProperty: dcs:concentration
measurementMethod: dcs:WRIS_India
statType: dcs:measuredValue
"""
CHEMPROP_MCF_NODES = """Node: dcid:{variable}_BodyOfWater_SurfaceWater
name: {variable}, Surface Water
typeOf: dcs:StatisticalVariable
populationType: dcs:BodyOfWater
waterSource: dcs:SurfaceWater
measuredProperty: dcs:{dcid}
measurementMethod: dcs:WRIS_India
statType: dcs:measuredValue
"""
TMCF_ISOCODE = """Node: E:{dataset_name}->E0
dcid: C:{dataset_name}->dcid
typeOf: dcs:WaterQualitySite
Node: E:{dataset_name}->E1
typeOf: dcs:Place
lgdCode: C:{dataset_name}->DistrictCode
"""
SOLUTE_TMCF_NODES = """Node: E:{dataset_name}->E{index}
typeOf: dcid:StatVarObservation
observationDate: C:{dataset_name}->Month
observationAbout: E:{dataset_name}->E0
containedIn: E:{dataset_name}->E1
observationPeriod: "P1M"
variableMeasured: dcid:Concentration_{variable}_BodyOfWater_SurfaceWater
measuredProperty: dcs:concentration
value: C:{dataset_name}->"{name}"
"""
CHEMPROP_TMCF_NODES = """Node: E:{dataset_name}->E{index}
typeOf: dcid:StatVarObservation
observationDate: C:{dataset_name}->Month
observationAbout: E:{dataset_name}->E0
containedIn: E:{dataset_name}->E1
observationPeriod: "P1M"
variableMeasured: dcid:{variable}_BodyOfWater_SurfaceWater
measuredProperty: dcs:{dcid}
value: C:{dataset_name}->"{name}"
"""
UNIT = """unit: dcid:{unit}
"""
template_strings = {
'solute_mcf': SOLUTE_MCF_NODES,
'solute_tmcf': SOLUTE_TMCF_NODES,
'chemprop_mcf': CHEMPROP_MCF_NODES,
'chemprop_tmcf': CHEMPROP_TMCF_NODES,
'site_dcid': TMCF_ISOCODE,
'unit_node': UNIT
}
preprocessor = WaterQualityBase(dataset_name=DATASET_NAME,
util_names='surfaceWater',
template_strings=template_strings)
preprocessor.create_dcids_in_csv()
preprocessor.create_mcfs() | 0.40592 | 0.418697 |
set_name(0x8007B9C0, "GetTpY__FUs", SN_NOWARN)
set_name(0x8007B9DC, "GetTpX__FUs", SN_NOWARN)
set_name(0x8007B9E8, "Remove96__Fv", SN_NOWARN)
set_name(0x8007BA20, "AppMain", SN_NOWARN)
set_name(0x8007BAC0, "MAIN_RestartGameTask__Fv", SN_NOWARN)
set_name(0x8007BAEC, "GameTask__FP4TASK", SN_NOWARN)
set_name(0x8007BBD4, "MAIN_MainLoop__Fv", SN_NOWARN)
set_name(0x8007BC1C, "CheckMaxArgs__Fv", SN_NOWARN)
set_name(0x8007BC50, "GPUQ_InitModule__Fv", SN_NOWARN)
set_name(0x8007BC5C, "GPUQ_FlushQ__Fv", SN_NOWARN)
set_name(0x8007BDD0, "GPUQ_LoadImage__FP4RECTli", SN_NOWARN)
set_name(0x8007BE84, "GPUQ_DiscardHandle__Fl", SN_NOWARN)
set_name(0x8007BF24, "GPUQ_LoadClutAddr__FiiiPv", SN_NOWARN)
set_name(0x8007BFC0, "GPUQ_MoveImage__FP4RECTii", SN_NOWARN)
set_name(0x8007C060, "PRIM_Open__FiiiP10SCREEN_ENVUl", SN_NOWARN)
set_name(0x8007C17C, "InitPrimBuffer__FP11PRIM_BUFFERii", SN_NOWARN)
set_name(0x8007C258, "PRIM_Clip__FP4RECTi", SN_NOWARN)
set_name(0x8007C380, "PRIM_GetCurrentScreen__Fv", SN_NOWARN)
set_name(0x8007C38C, "PRIM_FullScreen__Fi", SN_NOWARN)
set_name(0x8007C3C8, "PRIM_Flush__Fv", SN_NOWARN)
set_name(0x8007C5DC, "PRIM_GetCurrentOtList__Fv", SN_NOWARN)
set_name(0x8007C5E8, "ClearPbOnDrawSync", SN_NOWARN)
set_name(0x8007C624, "ClearedYet__Fv", SN_NOWARN)
set_name(0x8007C630, "PrimDrawSycnCallBack", SN_NOWARN)
set_name(0x8007C650, "SendDispEnv__Fv", SN_NOWARN)
set_name(0x8007C674, "PRIM_GetNextPolyF4__Fv", SN_NOWARN)
set_name(0x8007C68C, "PRIM_GetNextPolyFt4__Fv", SN_NOWARN)
set_name(0x8007C6A4, "PRIM_GetNextPolyGt4__Fv", SN_NOWARN)
set_name(0x8007C6BC, "PRIM_GetNextPolyG4__Fv", SN_NOWARN)
set_name(0x8007C6D4, "PRIM_GetNextPolyF3__Fv", SN_NOWARN)
set_name(0x8007C6EC, "PRIM_GetNextDrArea__Fv", SN_NOWARN)
set_name(0x8007C704, "ClipRect__FRC4RECTR4RECT", SN_NOWARN)
set_name(0x8007C818, "IsColiding__FRC4RECTT0", SN_NOWARN)
set_name(0x8007C880, "VID_AfterDisplay__Fv", SN_NOWARN)
set_name(0x8007C8A0, "VID_ScrOn__Fv", SN_NOWARN)
set_name(0x8007C8C8, "VID_DoThisNextSync__FPFv_v", SN_NOWARN)
set_name(0x8007C920, "VID_NextSyncRoutHasExecuted__Fv", SN_NOWARN)
set_name(0x8007C92C, "VID_GetTick__Fv", SN_NOWARN)
set_name(0x8007C938, "VID_DispEnvSend", SN_NOWARN)
set_name(0x8007C974, "VID_SetXYOff__Fii", SN_NOWARN)
set_name(0x8007C984, "VID_GetXOff__Fv", SN_NOWARN)
set_name(0x8007C990, "VID_GetYOff__Fv", SN_NOWARN)
set_name(0x8007C99C, "VID_SetDBuffer__Fb", SN_NOWARN)
set_name(0x8007CB0C, "MyFilter__FUlUlPCc", SN_NOWARN)
set_name(0x8007CB14, "SlowMemMove__FPvT0Ul", SN_NOWARN)
set_name(0x8007CB34, "GetTpY__FUs_addr_8007CB34", SN_NOWARN)
set_name(0x8007CB50, "GetTpX__FUs_addr_8007CB50", SN_NOWARN)
set_name(0x8007CB5C, "SYSI_GetFs__Fv", SN_NOWARN)
set_name(0x8007CB68, "SYSI_GetOverlayFs__Fv", SN_NOWARN)
set_name(0x8007CB74, "SortOutFileSystem__Fv", SN_NOWARN)
set_name(0x8007CCB0, "MemCb__FlPvUlPCcii", SN_NOWARN)
set_name(0x8007CCD0, "Spanker__Fv", SN_NOWARN)
set_name(0x8007CD10, "GaryLiddon__Fv", SN_NOWARN)
set_name(0x8007CD18, "ReadPad__Fi", SN_NOWARN)
set_name(0x8007CE74, "DummyPoll__Fv", SN_NOWARN)
set_name(0x8007CE7C, "DaveOwens__Fv", SN_NOWARN)
set_name(0x8007CEA4, "GetCur__C4CPad", SN_NOWARN)
set_name(0x8007CECC, "CheckActive__4CPad", SN_NOWARN)
set_name(0x8007CED8, "GetTpY__FUs_addr_8007CED8", SN_NOWARN)
set_name(0x8007CEF4, "GetTpX__FUs_addr_8007CEF4", SN_NOWARN)
set_name(0x8007CF00, "TimSwann__Fv", SN_NOWARN)
set_name(0x8007CF08, "__6FileIOUl", SN_NOWARN)
set_name(0x8007CF58, "___6FileIO", SN_NOWARN)
set_name(0x8007CFAC, "Read__6FileIOPCcUl", SN_NOWARN)
set_name(0x8007D114, "FileLen__6FileIOPCc", SN_NOWARN)
set_name(0x8007D178, "FileNotFound__6FileIOPCc", SN_NOWARN)
set_name(0x8007D198, "StreamFile__6FileIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007D278, "ReadAtAddr__6FileIOPCcPUci", SN_NOWARN)
set_name(0x8007D33C, "DumpOldPath__6FileIO", SN_NOWARN)
set_name(0x8007D3A0, "SetSearchPath__6FileIOPCc", SN_NOWARN)
set_name(0x8007D47C, "FindFile__6FileIOPCcPc", SN_NOWARN)
set_name(0x8007D590, "CopyPathItem__6FileIOPcPCc", SN_NOWARN)
set_name(0x8007D638, "LockSearchPath__6FileIO", SN_NOWARN)
set_name(0x8007D690, "UnlockSearchPath__6FileIO", SN_NOWARN)
set_name(0x8007D6E8, "SearchPathExists__6FileIO", SN_NOWARN)
set_name(0x8007D6FC, "Save__6FileIOPCcPUci", SN_NOWARN)
set_name(0x8007D738, "__4PCIOUl", SN_NOWARN)
set_name(0x8007D7A0, "___4PCIO", SN_NOWARN)
set_name(0x8007D7F8, "FileExists__4PCIOPCc", SN_NOWARN)
set_name(0x8007D83C, "LoReadFileAtAddr__4PCIOPCcPUci", SN_NOWARN)
set_name(0x8007D900, "GetFileLength__4PCIOPCc", SN_NOWARN)
set_name(0x8007D9B8, "LoSave__4PCIOPCcPUci", SN_NOWARN)
set_name(0x8007DA8C, "LoStreamFile__4PCIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007DC9C, "__6SysObj", SN_NOWARN)
set_name(0x8007DCB4, "__nw__6SysObji", SN_NOWARN)
set_name(0x8007DCE0, "__nw__6SysObjiUl", SN_NOWARN)
set_name(0x8007DD5C, "__dl__6SysObjPv", SN_NOWARN)
set_name(0x8007DDC8, "__5DatIOUl", SN_NOWARN)
set_name(0x8007DE04, "___5DatIO", SN_NOWARN)
set_name(0x8007DE5C, "FileExists__5DatIOPCc", SN_NOWARN)
set_name(0x8007DE9C, "LoReadFileAtAddr__5DatIOPCcPUci", SN_NOWARN)
set_name(0x8007DF5C, "GetFileLength__5DatIOPCc", SN_NOWARN)
set_name(0x8007E010, "LoSave__5DatIOPCcPUci", SN_NOWARN)
set_name(0x8007E0B8, "LoStreamFile__5DatIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007E2C4, "__7TextDat", SN_NOWARN)
set_name(0x8007E304, "___7TextDat", SN_NOWARN)
set_name(0x8007E34C, "Use__7TextDat", SN_NOWARN)
set_name(0x8007E540, "TpLoadCallBack__FPUciib", SN_NOWARN)
set_name(0x8007E610, "StreamLoadTP__7TextDat", SN_NOWARN)
set_name(0x8007E6C8, "FinishedUsing__7TextDat", SN_NOWARN)
set_name(0x8007E724, "MakeBlockOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007E794, "MakeOffsetTab__C9CBlockHdr", SN_NOWARN)
set_name(0x8007E8C0, "SetUVTp__7TextDatP9FRAME_HDRP8POLY_FT4ii", SN_NOWARN)
set_name(0x8007E9C0, "PrintMonster__7TextDatiiibi", SN_NOWARN)
set_name(0x8007EDCC, "PrepareFt4__7TextDatP8POLY_FT4iiiii", SN_NOWARN)
set_name(0x8007F038, "GetDecompBufffer__7TextDati", SN_NOWARN)
set_name(0x8007F198, "SetUVTpGT4__7TextDatP9FRAME_HDRP8POLY_GT4ii", SN_NOWARN)
set_name(0x8007F298, "PrepareGt4__7TextDatP8POLY_GT4iiiii", SN_NOWARN)
set_name(0x8007F4F0, "SetUVTpGT3__7TextDatP9FRAME_HDRP8POLY_GT3", SN_NOWARN)
set_name(0x8007F574, "PrepareGt3__7TextDatP8POLY_GT3iii", SN_NOWARN)
set_name(0x8007F73C, "PrintFt4__7TextDatiiiiii", SN_NOWARN)
set_name(0x8007F890, "PrintGt4__7TextDatiiiiii", SN_NOWARN)
set_name(0x8007F9E4, "PrintGt3__7TextDatiiii", SN_NOWARN)
set_name(0x8007FAC8, "DecompFrame__7TextDatP9FRAME_HDR", SN_NOWARN)
set_name(0x8007FC20, "MakeCreatureOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007FD60, "MakePalOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007FE5C, "InitData__7TextDat", SN_NOWARN)
set_name(0x8007FE88, "DumpData__7TextDat", SN_NOWARN)
set_name(0x8007FFD0, "GM_UseTexData__Fi", SN_NOWARN)
set_name(0x800800F0, "GM_FinishedUsing__FP7TextDat", SN_NOWARN)
set_name(0x80080144, "SetPal__7TextDatP9FRAME_HDRP8POLY_FT4", SN_NOWARN)
set_name(0x80080208, "GetFrNum__7TextDatiiii", SN_NOWARN)
set_name(0x8008025C, "IsDirAliased__7TextDatiii", SN_NOWARN)
set_name(0x800802B4, "DoDecompRequests__7TextDat", SN_NOWARN)
set_name(0x800803D8, "FindDecompArea__7TextDatR4RECT", SN_NOWARN)
set_name(0x800804B0, "GetFileInfo__7TextDati", SN_NOWARN)
set_name(0x80080500, "GetSize__C15CCreatureAction", SN_NOWARN)
set_name(0x80080528, "GetFrNum__C15CCreatureActionii", SN_NOWARN)
set_name(0x800805D0, "InitDirRemap__15CCreatureAction", SN_NOWARN)
set_name(0x80080690, "GetFrNum__C12CCreatureHdriii", SN_NOWARN)
set_name(0x800806D4, "GetAction__C12CCreatureHdri", SN_NOWARN)
set_name(0x80080764, "InitActionDirRemaps__12CCreatureHdr", SN_NOWARN)
set_name(0x800807D4, "GetSize__C12CCreatureHdr", SN_NOWARN)
set_name(0x80080840, "LoadDat__C13CTextFileInfo", SN_NOWARN)
set_name(0x80080890, "LoadHdr__C13CTextFileInfo", SN_NOWARN)
set_name(0x800808B8, "GetFile__C13CTextFileInfoPc", SN_NOWARN)
set_name(0x80080954, "HasFile__C13CTextFileInfoPc", SN_NOWARN)
set_name(0x800809BC, "Un64__FPUcT0l", SN_NOWARN)
set_name(0x80080A90, "__7CScreen", SN_NOWARN)
set_name(0x80080AC4, "Load__7CScreeniii", SN_NOWARN)
set_name(0x80080D64, "Unload__7CScreen", SN_NOWARN)
set_name(0x80080D88, "Display__7CScreeniiii", SN_NOWARN)
set_name(0x80081068, "SetRect__5CPartR7TextDatR4RECT", SN_NOWARN)
set_name(0x800810E4, "GetBoundingBox__6CBlockR7TextDatR4RECT", SN_NOWARN)
set_name(0x80081240, "_GLOBAL__D_DatPool", SN_NOWARN)
set_name(0x80081298, "_GLOBAL__I_DatPool", SN_NOWARN)
set_name(0x800812EC, "PRIM_GetPrim__FPP8POLY_GT3", SN_NOWARN)
set_name(0x80081368, "PRIM_GetPrim__FPP8POLY_GT4", SN_NOWARN)
set_name(0x800813E4, "PRIM_GetPrim__FPP8POLY_FT4", SN_NOWARN)
set_name(0x80081460, "CanXferFrame__C7TextDat", SN_NOWARN)
set_name(0x80081488, "CanXferPal__C7TextDat", SN_NOWARN)
set_name(0x800814B0, "IsLoaded__C7TextDat", SN_NOWARN)
set_name(0x800814BC, "GetTexNum__C7TextDat", SN_NOWARN)
set_name(0x800814C8, "GetCreature__7TextDati", SN_NOWARN)
set_name(0x80081540, "GetNumOfCreatures__7TextDat", SN_NOWARN)
set_name(0x80081554, "SetFileInfo__7TextDatPC13CTextFileInfoi", SN_NOWARN)
set_name(0x80081560, "GetNumOfFrames__7TextDat", SN_NOWARN)
set_name(0x80081574, "GetPal__7TextDati", SN_NOWARN)
set_name(0x80081590, "GetFr__7TextDati", SN_NOWARN)
set_name(0x800815AC, "GetName__C13CTextFileInfo", SN_NOWARN)
set_name(0x800815B8, "HasDat__C13CTextFileInfo", SN_NOWARN)
set_name(0x800815E0, "HasTp__C13CTextFileInfo", SN_NOWARN)
set_name(0x80081608, "GetSize__C6CBlock", SN_NOWARN)
set_name(0x8008161C, "__4CdIOUl", SN_NOWARN)
set_name(0x80081660, "___4CdIO", SN_NOWARN)
set_name(0x800816B8, "FileExists__4CdIOPCc", SN_NOWARN)
set_name(0x800816DC, "LoReadFileAtAddr__4CdIOPCcPUci", SN_NOWARN)
set_name(0x80081760, "GetFileLength__4CdIOPCc", SN_NOWARN)
set_name(0x80081784, "LoSave__4CdIOPCcPUci", SN_NOWARN)
set_name(0x80081864, "LoStreamCallBack__Fi", SN_NOWARN)
set_name(0x80081874, "CD_GetCdlFILE__FPCcP7CdlFILE", SN_NOWARN)
set_name(0x800819C0, "LoStreamFile__4CdIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x80081C9C, "LoAsyncStreamFile__4CdIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x80081DFC, "BL_InitEAC__Fv", SN_NOWARN)
set_name(0x80081EE8, "BL_ReadFile__FPcUl", SN_NOWARN)
set_name(0x80082014, "BL_AsyncReadFile__FPcUl", SN_NOWARN)
set_name(0x80082188, "BL_LoadDirectory__Fv", SN_NOWARN)
set_name(0x800822B0, "BL_LoadStreamDir__Fv", SN_NOWARN)
set_name(0x80082590, "BL_MakeFilePosTab__FPUcUl", SN_NOWARN)
set_name(0x80082690, "BL_FindStreamFile__FPcc", SN_NOWARN)
set_name(0x8008285C, "BL_FileExists__FPcc", SN_NOWARN)
set_name(0x80082880, "BL_FileLength__FPcc", SN_NOWARN)
set_name(0x800828B4, "BL_LoadFileAtAddr__FPcPUcc", SN_NOWARN)
set_name(0x8008299C, "BL_AsyncLoadDone__Fv", SN_NOWARN)
set_name(0x800829A8, "BL_WaitForAsyncFinish__Fv", SN_NOWARN)
set_name(0x800829F4, "BL_AsyncLoadCallBack__Fi", SN_NOWARN)
set_name(0x80082A24, "BL_LoadFileAsync__FPcc", SN_NOWARN)
set_name(0x80082B9C, "BL_AsyncLoadFileAtAddr__FPcPUcc", SN_NOWARN)
set_name(0x80082C64, "BL_OpenStreamFile__FPcc", SN_NOWARN)
set_name(0x80082C90, "BL_CloseStreamFile__FP6STRHDR", SN_NOWARN)
set_name(0x80082CC8, "LZNP_Decode__FPUcT0", SN_NOWARN)
set_name(0x80082D9C, "Tmalloc__Fi", SN_NOWARN)
set_name(0x80082EC0, "Tfree__FPv", SN_NOWARN)
set_name(0x80082F70, "InitTmalloc__Fv", SN_NOWARN)
set_name(0x80082F98, "strupr__FPc", SN_NOWARN)
set_name(0x80082FEC, "PauseTask__FP4TASK", SN_NOWARN)
set_name(0x80083038, "GetPausePad__Fv", SN_NOWARN)
set_name(0x8008312C, "TryPadForPause__Fi", SN_NOWARN)
set_name(0x80083158, "DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x800833D8, "DoPausedMessage__14CPauseMessages", SN_NOWARN)
set_name(0x800836F0, "DoQuitMessage__14CPauseMessages", SN_NOWARN)
set_name(0x80083810, "AreYouSureMessage__14CPauseMessages", SN_NOWARN)
set_name(0x80083914, "PA_SetPauseOk__Fb", SN_NOWARN)
set_name(0x80083924, "PA_GetPauseOk__Fv", SN_NOWARN)
set_name(0x80083930, "MY_PausePrint__17CTempPauseMessageiPciP4RECT", SN_NOWARN)
set_name(0x80083A7C, "InitPrintQuitMessage__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083A84, "PrintQuitMessage__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083BA0, "LeavePrintQuitMessage__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083BA8, "InitPrintAreYouSure__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083BB0, "PrintAreYouSure__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083CCC, "LeavePrintAreYouSure__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083CD4, "InitPrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083CDC, "ShowInActive__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083DBC, "PrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F0C, "LeavePrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F14, "___17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F3C, "_GLOBAL__D_DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x80083F64, "_GLOBAL__I_DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x80083F8C, "__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083FD0, "___14CPauseMessages", SN_NOWARN)
set_name(0x80084004, "__14CPauseMessages", SN_NOWARN)
set_name(0x80084018, "SetRGB__6DialogUcUcUc", SN_NOWARN)
set_name(0x80084038, "SetBack__6Dialogi", SN_NOWARN)
set_name(0x80084040, "SetBorder__6Dialogi", SN_NOWARN)
set_name(0x80084048, "___6Dialog", SN_NOWARN)
set_name(0x80084070, "__6Dialog", SN_NOWARN)
set_name(0x800840CC, "GetDown__C4CPad", SN_NOWARN)
set_name(0x800840F4, "GetUp__C4CPad", SN_NOWARN)
set_name(0x8008411C, "CheckActive__4CPad_addr_8008411C", SN_NOWARN)
set_name(0x80084128, "ReadPadStream__Fv", SN_NOWARN)
set_name(0x80084240, "PAD_Handler__Fv", SN_NOWARN)
set_name(0x80084408, "PAD_GetPad__FiUc", SN_NOWARN)
set_name(0x800844A4, "NewVal__4CPadUs", SN_NOWARN)
set_name(0x800845DC, "BothNewVal__4CPadUsUs", SN_NOWARN)
set_name(0x80084738, "Trans__4CPadUs", SN_NOWARN)
set_name(0x8008485C, "_GLOBAL__I_Pad0", SN_NOWARN)
set_name(0x80084894, "SetPadType__4CPadUc", SN_NOWARN)
set_name(0x8008489C, "CheckActive__4CPad_addr_8008489C", SN_NOWARN)
set_name(0x800848A8, "SetActive__4CPadUc", SN_NOWARN)
set_name(0x800848B0, "SetBothFlag__4CPadUc", SN_NOWARN)
set_name(0x800848B8, "__4CPadi", SN_NOWARN)
set_name(0x800848EC, "Flush__4CPad", SN_NOWARN)
set_name(0x80084910, "Set__7FontTab", SN_NOWARN)
set_name(0x800849AC, "InitPrinty__Fv", SN_NOWARN)
set_name(0x80084A4C, "SetTextDat__5CFontP7TextDat", SN_NOWARN)
set_name(0x80084A54, "PrintChar__5CFontUsUscUcUcUc", SN_NOWARN)
set_name(0x80084BEC, "Print__5CFontiiPc8TXT_JUSTP4RECTUcUcUc", SN_NOWARN)
set_name(0x80085218, "GetStrWidth__5CFontPc", SN_NOWARN)
set_name(0x800852CC, "SetChar__5CFontiUs", SN_NOWARN)
set_name(0x80085330, "SetOTpos__5CFonti", SN_NOWARN)
set_name(0x8008533C, "ClearFont__5CFont", SN_NOWARN)
set_name(0x80085360, "IsDefined__5CFontUc", SN_NOWARN)
set_name(0x80085380, "GetCharFrameNum__5CFontc", SN_NOWARN)
set_name(0x80085398, "GetCharWidth__5CFontc", SN_NOWARN)
set_name(0x800853F0, "Init__5CFont", SN_NOWARN)
set_name(0x80085424, "GetFr__7TextDati_addr_80085424", SN_NOWARN)
set_name(0x80085440, "TrimCol__Fs", SN_NOWARN)
set_name(0x80085478, "DialogPrint__Fiiiiiiiiii", SN_NOWARN)
set_name(0x80085DF8, "GetDropShadowG4__FUcUcUcUcUcUcUcUcUcUcUcUc", SN_NOWARN)
set_name(0x80085F30, "DropShadows__Fiiii", SN_NOWARN)
set_name(0x800861D4, "InitDialog__Fv", SN_NOWARN)
set_name(0x8008630C, "GetSizes__6Dialog", SN_NOWARN)
set_name(0x80086590, "Back__6Dialogiiii", SN_NOWARN)
set_name(0x80087750, "Line__6Dialogiii", SN_NOWARN)
set_name(0x80087968, "GetPal__7TextDati_addr_80087968", SN_NOWARN)
set_name(0x80087984, "GetFr__7TextDati_addr_80087984", SN_NOWARN)
set_name(0x800879A0, "ATT_DoAttract__Fv", SN_NOWARN)
set_name(0x80087AF0, "CreatePlayersFromFeData__FR9FE_CREATE", SN_NOWARN)
set_name(0x80087BBC, "UpdateSel__FPUsUsPUc", SN_NOWARN)
set_name(0x80087BFC, "CycleSelCols__Fv", SN_NOWARN)
set_name(0x80087DB4, "FindTownCreature__7CBlocksi", SN_NOWARN)
set_name(0x80087E28, "FindCreature__7CBlocksi", SN_NOWARN)
set_name(0x80087E7C, "__7CBlocksiiiii", SN_NOWARN)
set_name(0x80087FD0, "SetTownersGraphics__7CBlocks", SN_NOWARN)
set_name(0x80088008, "SetMonsterGraphics__7CBlocksii", SN_NOWARN)
set_name(0x800880D0, "___7CBlocks", SN_NOWARN)
set_name(0x80088158, "DumpGt4s__7CBlocks", SN_NOWARN)
set_name(0x800881C0, "DumpRects__7CBlocks", SN_NOWARN)
set_name(0x80088228, "SetGraphics__7CBlocksPP7TextDatPii", SN_NOWARN)
set_name(0x80088284, "DumpGraphics__7CBlocksPP7TextDatPi", SN_NOWARN)
set_name(0x800882D4, "PrintBlockOutline__7CBlocksiiiii", SN_NOWARN)
set_name(0x80088620, "Load__7CBlocksi", SN_NOWARN)
set_name(0x800886CC, "MakeRectTable__7CBlocks", SN_NOWARN)
set_name(0x800887A0, "MakeGt4Table__7CBlocks", SN_NOWARN)
set_name(0x800888A8, "MakeGt4__7CBlocksP8POLY_GT4P9FRAME_HDR", SN_NOWARN)
set_name(0x800889E8, "GetBlock__7CBlocksi", SN_NOWARN)
set_name(0x80088A60, "Print__7CBlocks", SN_NOWARN)
set_name(0x80088A88, "SetXY__7CBlocksii", SN_NOWARN)
set_name(0x80088AB0, "GetXY__7CBlocksPiT1", SN_NOWARN)
set_name(0x80088AC8, "PrintMap__7CBlocksii", SN_NOWARN)
set_name(0x80089FB8, "PrintGameSprites__7CBlocksiiiii", SN_NOWARN)
set_name(0x8008A128, "PrintGameSprites__7CBlocksP8map_infoiiiiiii", SN_NOWARN)
set_name(0x8008AF2C, "PrintSprites__7CBlocksP8map_infoiiiiiii", SN_NOWARN)
set_name(0x8008B680, "PrintSprites__7CBlocksiiiii", SN_NOWARN)
set_name(0x8008B7F0, "ScrToWorldX__7CBlocksii", SN_NOWARN)
set_name(0x8008B804, "ScrToWorldY__7CBlocksii", SN_NOWARN)
set_name(0x8008B818, "SetScrollTarget__7CBlocksii", SN_NOWARN)
set_name(0x8008B8DC, "DoScroll__7CBlocks", SN_NOWARN)
set_name(0x8008B960, "SetPlayerPosBlocks__7CBlocksiii", SN_NOWARN)
set_name(0x8008BA00, "GetScrXY__7CBlocksR4RECTiiii", SN_NOWARN)
set_name(0x8008BAD4, "ShadScaleSkew__7CBlocksP8POLY_FT4", SN_NOWARN)
set_name(0x8008BB54, "WorldToScrX__7CBlocksii", SN_NOWARN)
set_name(0x8008BB5C, "WorldToScrY__7CBlocksii", SN_NOWARN)
set_name(0x8008BB70, "BL_GetCurrentBlocks__Fv", SN_NOWARN)
set_name(0x8008BB7C, "PRIM_GetPrim__FPP8POLY_FT4_addr_8008BB7C", SN_NOWARN)
set_name(0x8008BBF8, "GetHighlightCol__FiPiUsUsUs", SN_NOWARN)
set_name(0x8008BC40, "PRIM_GetCopy__FP8POLY_FT4", SN_NOWARN)
set_name(0x8008BC7C, "GetHighlightCol__FiPcUsUsUs", SN_NOWARN)
set_name(0x8008BCC4, "PRIM_GetPrim__FPP8POLY_GT4_addr_8008BCC4", SN_NOWARN)
set_name(0x8008BD40, "PRIM_GetPrim__FPP7LINE_F2", SN_NOWARN)
set_name(0x8008BDBC, "PRIM_CopyPrim__FP8POLY_FT4T0", SN_NOWARN)
set_name(0x8008BDE4, "GetCreature__14TownToCreaturei", SN_NOWARN)
set_name(0x8008BE00, "SetItemGraphics__7CBlocksi", SN_NOWARN)
set_name(0x8008BE28, "SetObjGraphics__7CBlocksi", SN_NOWARN)
set_name(0x8008BE50, "DumpItems__7CBlocks", SN_NOWARN)
set_name(0x8008BE74, "DumpObjs__7CBlocks", SN_NOWARN)
set_name(0x8008BE98, "DumpMonsters__7CBlocks", SN_NOWARN)
set_name(0x8008BEC0, "GetNumOfBlocks__7CBlocks", SN_NOWARN)
set_name(0x8008BECC, "CopyToGt4__9LittleGt4P8POLY_GT4", SN_NOWARN)
set_name(0x8008BF64, "InitFromGt4__9LittleGt4P8POLY_GT4ii", SN_NOWARN)
set_name(0x8008BFF4, "GetNumOfFrames__7TextDatii", SN_NOWARN)
set_name(0x8008C02C, "GetCreature__7TextDati_addr_8008C02C", SN_NOWARN)
set_name(0x8008C0A4, "GetNumOfCreatures__7TextDat_addr_8008C0A4", SN_NOWARN)
set_name(0x8008C0B8, "SetFileInfo__7TextDatPC13CTextFileInfoi_addr_8008C0B8", SN_NOWARN)
set_name(0x8008C0C4, "GetPal__7TextDati_addr_8008C0C4", SN_NOWARN)
set_name(0x8008C0E0, "GetFr__7TextDati_addr_8008C0E0", SN_NOWARN)
set_name(0x8008C0FC, "OVR_IsMemcardOverlayBlank__Fv", SN_NOWARN)
set_name(0x8008C128, "OVR_LoadPregame__Fv", SN_NOWARN)
set_name(0x8008C150, "OVR_LoadFrontend__Fv", SN_NOWARN)
set_name(0x8008C178, "OVR_LoadGame__Fv", SN_NOWARN)
set_name(0x8008C1A0, "OVR_LoadFmv__Fv", SN_NOWARN)
set_name(0x8008C1C8, "OVR_LoadMemcard__Fv", SN_NOWARN)
set_name(0x8008C1F4, "ClearOutOverlays__Fv", SN_NOWARN)
set_name(0x8008C24C, "ClearOut__7Overlay", SN_NOWARN)
set_name(0x8008C310, "Load__7Overlay", SN_NOWARN)
set_name(0x8008C380, "OVR_GetCurrentOverlay__Fv", SN_NOWARN)
set_name(0x8008C38C, "LoadOver__FR7Overlay", SN_NOWARN)
set_name(0x8008C3E0, "_GLOBAL__I_OVR_Open__Fv", SN_NOWARN)
set_name(0x8008C550, "GetOverType__7Overlay", SN_NOWARN)
set_name(0x8008C55C, "StevesDummyPoll__Fv", SN_NOWARN)
set_name(0x8008C564, "Lambo__Fv", SN_NOWARN)
set_name(0x8008C56C, "__7CPlayerbi", SN_NOWARN)
set_name(0x8008C650, "___7CPlayer", SN_NOWARN)
set_name(0x8008C6A8, "Load__7CPlayeri", SN_NOWARN)
set_name(0x8008C704, "SetBlockXY__7CPlayerR7CBlocksR12PlayerStruct", SN_NOWARN)
set_name(0x8008C850, "SetScrollTarget__7CPlayerR12PlayerStructR7CBlocks", SN_NOWARN)
set_name(0x8008CC7C, "GetNumOfSpellAnims__FR12PlayerStruct", SN_NOWARN)
set_name(0x8008CCFC, "Print__7CPlayerR12PlayerStructR7CBlocks", SN_NOWARN)
set_name(0x8008D1D4, "FindAction__7CPlayerR12PlayerStruct", SN_NOWARN)
set_name(0x8008D250, "FindActionEnum__7CPlayerR12PlayerStruct", SN_NOWARN)
set_name(0x8008D2CC, "Init__7CPlayer", SN_NOWARN)
set_name(0x8008D2D4, "Dump__7CPlayer", SN_NOWARN)
set_name(0x8008D2DC, "PRIM_GetPrim__FPP8POLY_FT4_addr_8008D2DC", SN_NOWARN)
set_name(0x8008D358, "PRIM_GetCopy__FP8POLY_FT4_addr_8008D358", SN_NOWARN)
set_name(0x8008D394, "PRIM_CopyPrim__FP8POLY_FT4T0_addr_8008D394", SN_NOWARN)
set_name(0x8008D3BC, "GetPlrOt__7CBlocksi", SN_NOWARN)
set_name(0x8008D3D0, "SetDecompArea__7TextDatiiii", SN_NOWARN)
set_name(0x8008D3E8, "GetNumOfFrames__7TextDatii_addr_8008D3E8", SN_NOWARN)
set_name(0x8008D420, "GetNumOfActions__7TextDati", SN_NOWARN)
set_name(0x8008D444, "GetCreature__7TextDati_addr_8008D444", SN_NOWARN)
set_name(0x8008D4BC, "GetNumOfCreatures__7TextDat_addr_8008D4BC", SN_NOWARN)
set_name(0x8008D4D0, "SetFileInfo__7TextDatPC13CTextFileInfoi_addr_8008D4D0", SN_NOWARN)
set_name(0x8008D4DC, "PROF_Open__Fv", SN_NOWARN)
set_name(0x8008D51C, "PROF_State__Fv", SN_NOWARN)
set_name(0x8008D528, "PROF_On__Fv", SN_NOWARN)
set_name(0x8008D538, "PROF_Off__Fv", SN_NOWARN)
set_name(0x8008D544, "PROF_CpuEnd__Fv", SN_NOWARN)
set_name(0x8008D574, "PROF_CpuStart__Fv", SN_NOWARN)
set_name(0x8008D598, "PROF_DrawStart__Fv", SN_NOWARN)
set_name(0x8008D5BC, "PROF_DrawEnd__Fv", SN_NOWARN)
set_name(0x8008D5EC, "PROF_Draw__FPUl", SN_NOWARN)
set_name(0x8008D7E0, "PROF_Restart__Fv", SN_NOWARN)
set_name(0x8008D800, "PSX_WndProc__FUilUl", SN_NOWARN)
set_name(0x8008D8C0, "PSX_PostWndProc__FUilUl", SN_NOWARN)
set_name(0x8008D970, "GoBackLevel__Fv", SN_NOWARN)
set_name(0x8008D9E8, "GoWarpLevel__Fv", SN_NOWARN)
set_name(0x8008DA20, "PostLoadGame__Fv", SN_NOWARN)
set_name(0x8008DABC, "GoLoadGame__Fv", SN_NOWARN)
set_name(0x8008DB18, "PostNewLevel__Fv", SN_NOWARN)
set_name(0x8008DBB4, "GoNewLevel__Fv", SN_NOWARN)
set_name(0x8008DC08, "PostGoBackLevel__Fv", SN_NOWARN)
set_name(0x8008DCA0, "GoForwardLevel__Fv", SN_NOWARN)
set_name(0x8008DCF8, "PostGoForwardLevel__Fv", SN_NOWARN)
set_name(0x8008DD90, "GoNewGame__Fv", SN_NOWARN)
set_name(0x8008DDE0, "PostNewGame__Fv", SN_NOWARN)
set_name(0x8008DE18, "LevelToLevelInit__Fv", SN_NOWARN)
set_name(0x8008DE60, "GetPal__6GPaneli", SN_NOWARN)
set_name(0x8008DEA4, "__6GPaneli", SN_NOWARN)
set_name(0x8008DEFC, "DrawFlask__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E37C, "DrawSpeedBar__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E800, "DrawSpell__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E9A0, "DrawMsgWindow__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E9EC, "DrawDurThingy__6GPaneliiP10ItemStructi", SN_NOWARN)
set_name(0x8008EDA8, "DrawDurIcon__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008EE9C, "Print__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008EFA0, "GetPal__7TextDati_addr_8008EFA0", SN_NOWARN)
set_name(0x8008EFBC, "GetFr__7TextDati_addr_8008EFBC", SN_NOWARN)
set_name(0x8008EFD8, "PrintCDWaitTask__FP4TASK", SN_NOWARN)
set_name(0x8008F090, "InitCDWaitIcon__Fv", SN_NOWARN)
set_name(0x8008F0C4, "STR_Debug__FP6SFXHDRPce", SN_NOWARN)
set_name(0x8008F0D8, "STR_SystemTask__FP4TASK", SN_NOWARN)
set_name(0x8008F120, "STR_AllocBuffer__Fv", SN_NOWARN)
set_name(0x8008F174, "STR_Init__Fv", SN_NOWARN)
set_name(0x8008F294, "STR_InitStream__Fv", SN_NOWARN)
set_name(0x8008F3CC, "STR_PlaySound__FUscic", SN_NOWARN)
set_name(0x8008F508, "STR_setvolume__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F560, "STR_PlaySFX__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F66C, "STR_pauseall__Fv", SN_NOWARN)
set_name(0x8008F6BC, "STR_resumeall__Fv", SN_NOWARN)
set_name(0x8008F70C, "STR_CloseStream__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F790, "STR_SoundCommand__FP6SFXHDRi", SN_NOWARN)
set_name(0x8008F89C, "STR_Command__FP6SFXHDR", SN_NOWARN)
set_name(0x8008FA48, "STR_DMAControl__FP6SFXHDR", SN_NOWARN)
set_name(0x8008FB10, "STR_PlayStream__FP6SFXHDRPUci", SN_NOWARN)
set_name(0x8008FCEC, "STR_AsyncWeeTASK__FP4TASK", SN_NOWARN)
set_name(0x8008FFEC, "STR_AsyncTASK__FP4TASK", SN_NOWARN)
set_name(0x80090420, "STR_StreamMainTask__FP6SFXHDRc", SN_NOWARN)
set_name(0x80090528, "SND_Monitor__FP4TASK", SN_NOWARN)
set_name(0x800905B4, "SPU_Init__Fv", SN_NOWARN)
set_name(0x800906C0, "SND_FindChannel__Fv", SN_NOWARN)
set_name(0x8009072C, "SND_ClearBank__Fv", SN_NOWARN)
set_name(0x800907A4, "SndLoadCallBack__FPUciib", SN_NOWARN)
set_name(0x8009081C, "SND_LoadBank__Fi", SN_NOWARN)
set_name(0x80090950, "SND_FindSFX__FUs", SN_NOWARN)
set_name(0x800909A4, "SND_StopSnd__Fi", SN_NOWARN)
set_name(0x800909C8, "SND_IsSfxPlaying__Fi", SN_NOWARN)
set_name(0x80090A04, "SND_RemapSnd__Fi", SN_NOWARN)
set_name(0x80090A78, "SND_PlaySnd__FUsiii", SN_NOWARN)
set_name(0x80090C34, "AS_CallBack0__Fi", SN_NOWARN)
set_name(0x80090C48, "AS_CallBack1__Fi", SN_NOWARN)
set_name(0x80090C5C, "AS_WasLastBlock__FiP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090D38, "AS_OpenStream__FP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090DD8, "AS_GetBlock__FP6SFXHDR", SN_NOWARN)
set_name(0x80090DE4, "AS_CloseStream__FP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090E10, "AS_LoopStream__FiP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090F30, "SCR_NeedHighlightPal__FUsUsi", SN_NOWARN)
set_name(0x80090F64, "Init__13PalCollectionPC7InitPos", SN_NOWARN)
set_name(0x80090FF4, "FindPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x800910D0, "NewPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x80091150, "MakePal__8PalEntryUsUsi", SN_NOWARN)
set_name(0x800911F0, "GetHighlightPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x80091284, "UpdatePals__13PalCollection", SN_NOWARN)
set_name(0x800912F8, "SCR_Handler__Fv", SN_NOWARN)
set_name(0x80091320, "GetNumOfObjs__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x80091328, "GetObj__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x80091364, "Init__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x800913C8, "MoveFromUsedToUnused__t10Collection2Z8PalEntryi20P8PalEntry", SN_NOWARN)
set_name(0x80091420, "MoveFromUnusedToUsed__t10Collection2Z8PalEntryi20P8PalEntry", SN_NOWARN)
set_name(0x80091478, "Set__8PalEntryUsUsi", SN_NOWARN)
set_name(0x8009148C, "Set__8PalEntryRC7InitPos", SN_NOWARN)
set_name(0x800914B8, "SetJustUsed__8PalEntryb", SN_NOWARN)
set_name(0x800914C0, "Init__8PalEntry", SN_NOWARN)
set_name(0x800914C8, "GetClut__C8PalEntry", SN_NOWARN)
set_name(0x800914D4, "IsEqual__C8PalEntryUsUsi", SN_NOWARN)
set_name(0x8009150C, "GetNext__Ct11TLinkedList1Z8PalEntry", SN_NOWARN)
set_name(0x80091518, "AddToList__t11TLinkedList1Z8PalEntryPP8PalEntry", SN_NOWARN)
set_name(0x80091538, "DetachFromList__t11TLinkedList1Z8PalEntryPP8PalEntry", SN_NOWARN)
set_name(0x80091584, "stub__FPcPv", SN_NOWARN)
set_name(0x8009158C, "new_eprint__FPcT0i", SN_NOWARN)
set_name(0x800915C0, "TonysGameTask__FP4TASK", SN_NOWARN)
set_name(0x80091648, "SetAmbientLight__Fv", SN_NOWARN)
set_name(0x800916CC, "print_demo_task__FP4TASK", SN_NOWARN)
set_name(0x800918D8, "TonysDummyPoll__Fv", SN_NOWARN)
set_name(0x800918FC, "load_demo_pad_data__FUl", SN_NOWARN)
set_name(0x8009195C, "save_demo_pad_data__FUl", SN_NOWARN)
set_name(0x800919BC, "set_pad_record_play__Fi", SN_NOWARN)
set_name(0x80091A30, "start_demo__Fv", SN_NOWARN)
set_name(0x80091ACC, "SetQuest__Fv", SN_NOWARN)
set_name(0x80091AF4, "CurrCheatStr__Fv", SN_NOWARN)
set_name(0x80091B14, "tony__Fv", SN_NOWARN)
set_name(0x80091B4C, "GLUE_SetMonsterList__Fi", SN_NOWARN)
set_name(0x80091B58, "GLUE_GetMonsterList__Fv", SN_NOWARN)
set_name(0x80091B64, "GLUE_SuspendGame__Fv", SN_NOWARN)
set_name(0x80091BB8, "GLUE_ResumeGame__Fv", SN_NOWARN)
set_name(0x80091C0C, "GLUE_PreTown__Fv", SN_NOWARN)
set_name(0x80091C70, "GLUE_PreDun__Fv", SN_NOWARN)
set_name(0x80091CBC, "GLUE_Finished__Fv", SN_NOWARN)
set_name(0x80091CC8, "GLUE_SetFinished__Fb", SN_NOWARN)
set_name(0x80091CD4, "GLUE_StartBg__Fibi", SN_NOWARN)
set_name(0x80091D58, "GLUE_SetShowGameScreenFlag__Fb", SN_NOWARN)
set_name(0x80091D68, "GLUE_SetHomingScrollFlag__Fb", SN_NOWARN)
set_name(0x80091D78, "GLUE_SetShowPanelFlag__Fb", SN_NOWARN)
set_name(0x80091D88, "DoShowPanelGFX__FP6GPanelT0", SN_NOWARN)
set_name(0x80091E60, "BgTask__FP4TASK", SN_NOWARN)
set_name(0x800923C0, "FindPlayerChar__FPc", SN_NOWARN)
set_name(0x80092458, "FindPlayerChar__Fiii", SN_NOWARN)
set_name(0x800924B4, "FindPlayerChar__FP12PlayerStruct", SN_NOWARN)
set_name(0x800924E4, "FindPlayerChar__FP12PlayerStructb", SN_NOWARN)
set_name(0x80092544, "MakeSurePlayerDressedProperly__FR7CPlayerR12PlayerStructb", SN_NOWARN)
set_name(0x800925C4, "GLUE_GetCurrentList__Fi", SN_NOWARN)
set_name(0x80092670, "GetTexId__7CPlayer", SN_NOWARN)
set_name(0x8009267C, "SetTown__7CBlocksb", SN_NOWARN)
set_name(0x80092684, "MoveToScrollTarget__7CBlocks", SN_NOWARN)
set_name(0x80092698, "SetDemoKeys__FPi", SN_NOWARN)
set_name(0x80092770, "RestoreDemoKeys__FPi", SN_NOWARN)
set_name(0x80092800, "get_action_str__Fii", SN_NOWARN)
set_name(0x80092878, "get_key_pad__Fi", SN_NOWARN)
set_name(0x800928B0, "checkvalid__Fv", SN_NOWARN)
set_name(0x80092914, "RemoveCtrlScreen__Fv", SN_NOWARN)
set_name(0x8009297C, "Init_ctrl_pos__Fv", SN_NOWARN)
set_name(0x80092A34, "remove_padval__Fi", SN_NOWARN)
set_name(0x80092A74, "remove_comboval__Fi", SN_NOWARN)
set_name(0x80092AB4, "set_buttons__Fii", SN_NOWARN)
set_name(0x80092C08, "restore_controller_settings__Fv", SN_NOWARN)
set_name(0x80092C50, "only_one_button__Fi", SN_NOWARN)
set_name(0x80092C7C, "main_ctrl_setup__Fv", SN_NOWARN)
set_name(0x8009312C, "PrintCtrlString__FiiUcic", SN_NOWARN)
set_name(0x80093628, "DrawCtrlSetup__Fv", SN_NOWARN)
set_name(0x80093AE4, "_GLOBAL__D_ctrlflag", SN_NOWARN)
set_name(0x80093B0C, "_GLOBAL__I_ctrlflag", SN_NOWARN)
set_name(0x80093B34, "GetTick__C4CPad", SN_NOWARN)
set_name(0x80093B5C, "GetDown__C4CPad_addr_80093B5C", SN_NOWARN)
set_name(0x80093B84, "GetUp__C4CPad_addr_80093B84", SN_NOWARN)
set_name(0x80093BAC, "SetPadTickMask__4CPadUs", SN_NOWARN)
set_name(0x80093BB4, "SetPadTick__4CPadUs", SN_NOWARN)
set_name(0x80093BBC, "SetRGB__6DialogUcUcUc_addr_80093BBC", SN_NOWARN)
set_name(0x80093BDC, "SetBorder__6Dialogi_addr_80093BDC", SN_NOWARN)
set_name(0x80093BE4, "SetOTpos__6Dialogi", SN_NOWARN)
set_name(0x80093BF0, "___6Dialog_addr_80093BF0", SN_NOWARN)
set_name(0x80093C18, "__6Dialog_addr_80093C18", SN_NOWARN)
set_name(0x80093C74, "switchnight__FP4TASK", SN_NOWARN)
set_name(0x80093CC0, "city_lights__FP4TASK", SN_NOWARN)
set_name(0x80093E14, "color_cycle__FP4TASK", SN_NOWARN)
set_name(0x80093F58, "ReInitDFL__Fv", SN_NOWARN)
set_name(0x80093F90, "DrawFlameLogo__Fv", SN_NOWARN)
set_name(0x80094334, "TitleScreen__FP7CScreen", SN_NOWARN)
set_name(0x80094388, "TryCreaturePrint__Fiiiiiii", SN_NOWARN)
set_name(0x800945EC, "TryWater__FiiP8POLY_GT4i", SN_NOWARN)
set_name(0x800947C4, "nightgfx__FibiP8POLY_GT4i", SN_NOWARN)
set_name(0x80094850, "PRIM_GetCopy__FP8POLY_FT4_addr_80094850", SN_NOWARN)
set_name(0x8009488C, "PRIM_CopyPrim__FP8POLY_FT4T0_addr_8009488C", SN_NOWARN)
set_name(0x800948B4, "PRIM_GetPrim__FPP8POLY_FT4_addr_800948B4", SN_NOWARN)
set_name(0x80094930, "GetNumOfActions__7TextDati_addr_80094930", SN_NOWARN)
set_name(0x80094954, "GetCreature__7TextDati_addr_80094954", SN_NOWARN)
set_name(0x800949CC, "GetNumOfCreatures__7TextDat_addr_800949CC", SN_NOWARN)
set_name(0x800949E0, "DaveLDummyPoll__Fv", SN_NOWARN)
set_name(0x800949E8, "DaveL__Fv", SN_NOWARN)
set_name(0x80094A10, "DoReflection__FP8POLY_FT4iii", SN_NOWARN)
set_name(0x80094CFC, "mteleportfx__Fv", SN_NOWARN)
set_name(0x80094FFC, "invistimer__Fv", SN_NOWARN)
set_name(0x800950D4, "setUVparams__FP8POLY_FT4P9FRAME_HDR", SN_NOWARN)
set_name(0x80095164, "drawparticle__Fiiiiii", SN_NOWARN)
set_name(0x80095354, "drawpolyF4__Fiiiiii", SN_NOWARN)
set_name(0x80095488, "drawpolyG4__Fiiiiiiii", SN_NOWARN)
set_name(0x80095658, "particlejump__Fv", SN_NOWARN)
set_name(0x80095808, "particleglow__Fv", SN_NOWARN)
set_name(0x800958FC, "doparticlejump__Fv", SN_NOWARN)
set_name(0x8009593C, "StartPartJump__Fiiiiii", SN_NOWARN)
set_name(0x80095AA4, "doparticlechain__Fiiiiiiiiiiii", SN_NOWARN)
set_name(0x80095EA0, "ParticleBlob__FP13MissileStructiiii", SN_NOWARN)
set_name(0x80095F38, "ParticleMissile__FP13MissileStructiiii", SN_NOWARN)
set_name(0x80095FF8, "Teleportfx__Fiiiiiiii", SN_NOWARN)
set_name(0x800962EC, "ResurrectFX__Fiiii", SN_NOWARN)
set_name(0x80096514, "ParticleExp__FP13MissileStructiiii", SN_NOWARN)
set_name(0x800965B0, "GetPlrPos__11SPELLFX_DATP12PlayerStruct", SN_NOWARN)
set_name(0x800966D4, "healFX__Fv", SN_NOWARN)
set_name(0x80096810, "HealStart__Fi", SN_NOWARN)
set_name(0x80096844, "HealotherStart__Fi", SN_NOWARN)
set_name(0x8009687C, "TeleStart__Fi", SN_NOWARN)
set_name(0x800968D8, "PhaseStart__Fi", SN_NOWARN)
set_name(0x8009690C, "PhaseEnd__Fi", SN_NOWARN)
set_name(0x80096938, "ApocInit__11SPELLFX_DATP12PlayerStruct", SN_NOWARN)
set_name(0x80096B14, "ApocaStart__Fi", SN_NOWARN)
set_name(0x80096B6C, "DaveLTask__FP4TASK", SN_NOWARN)
set_name(0x80096C08, "PRIM_GetPrim__FPP7POLY_G4", SN_NOWARN)
set_name(0x80096C84, "PRIM_GetPrim__FPP7POLY_F4", SN_NOWARN)
set_name(0x80096D00, "PRIM_GetPrim__FPP8POLY_FT4_addr_80096D00", SN_NOWARN)
set_name(0x80096D7C, "GetPlayer__7CPlayeri", SN_NOWARN)
set_name(0x80096DCC, "GetLastOtPos__C7CPlayer", SN_NOWARN)
set_name(0x80096DD8, "GetFr__7TextDati_addr_80096DD8", SN_NOWARN)
set_name(0x80096DF4, "DrawArrow__Fii", SN_NOWARN)
set_name(0x80096FF8, "show_spell_dir__Fi", SN_NOWARN)
set_name(0x80097490, "release_spell__Fi", SN_NOWARN)
set_name(0x80097504, "select_belt_item__Fi", SN_NOWARN)
set_name(0x8009750C, "any_belt_items__Fv", SN_NOWARN)
set_name(0x80097574, "get_last_inv__Fv", SN_NOWARN)
set_name(0x800976A4, "get_next_inv__Fv", SN_NOWARN)
set_name(0x800977DC, "pad_func_up__Fi", SN_NOWARN)
set_name(0x80097808, "pad_func_down__Fi", SN_NOWARN)
set_name(0x80097834, "pad_func_left__Fi", SN_NOWARN)
set_name(0x8009783C, "pad_func_right__Fi", SN_NOWARN)
set_name(0x80097844, "pad_func_select__Fi", SN_NOWARN)
set_name(0x80097900, "pad_func_Attack__Fi", SN_NOWARN)
set_name(0x80097D8C, "pad_func_Action__Fi", SN_NOWARN)
set_name(0x800980D8, "InitTargetCursor__Fi", SN_NOWARN)
set_name(0x800981E0, "RemoveTargetCursor__Fi", SN_NOWARN)
set_name(0x80098270, "pad_func_Cast_Spell__Fi", SN_NOWARN)
set_name(0x80098670, "pad_func_Use_Item__Fi", SN_NOWARN)
set_name(0x80098730, "pad_func_Chr__Fi", SN_NOWARN)
set_name(0x80098838, "pad_func_Inv__Fi", SN_NOWARN)
set_name(0x80098930, "pad_func_SplBook__Fi", SN_NOWARN)
set_name(0x80098A1C, "pad_func_QLog__Fi", SN_NOWARN)
set_name(0x80098AA0, "pad_func_SpellBook__Fi", SN_NOWARN)
set_name(0x80098B38, "pad_func_AutoMap__Fi", SN_NOWARN)
set_name(0x80098BF4, "pad_func_Quick_Spell__Fi", SN_NOWARN)
set_name(0x80098C70, "check_inv__FiPci", SN_NOWARN)
set_name(0x80098E38, "pad_func_Quick_Use_Health__Fi", SN_NOWARN)
set_name(0x80098E60, "pad_func_Quick_Use_Mana__Fi", SN_NOWARN)
set_name(0x80098E88, "get_max_find_size__FPici", SN_NOWARN)
set_name(0x80098FC8, "sort_gold__Fi", SN_NOWARN)
set_name(0x800990D4, "DrawObjSelector__Fi", SN_NOWARN)
set_name(0x80099954, "DrawObjTask__FP4TASK", SN_NOWARN)
set_name(0x80099A30, "add_area_find_object__Fciii", SN_NOWARN)
set_name(0x80099B3C, "CheckRangeObject__Fiici", SN_NOWARN)
set_name(0x80099EFC, "CheckArea__FiiicUci", SN_NOWARN)
set_name(0x8009A1D4, "PlacePlayer__FiiiUc", SN_NOWARN)
set_name(0x8009A3F8, "_GLOBAL__D_gplayer", SN_NOWARN)
set_name(0x8009A420, "_GLOBAL__I_gplayer", SN_NOWARN)
set_name(0x8009A448, "SetRGB__6DialogUcUcUc_addr_8009A448", SN_NOWARN)
set_name(0x8009A468, "SetBack__6Dialogi_addr_8009A468", SN_NOWARN)
set_name(0x8009A470, "SetBorder__6Dialogi_addr_8009A470", SN_NOWARN)
set_name(0x8009A478, "___6Dialog_addr_8009A478", SN_NOWARN)
set_name(0x8009A4A0, "__6Dialog_addr_8009A4A0", SN_NOWARN)
set_name(0x8009A4FC, "GetTick__C4CPad_addr_8009A4FC", SN_NOWARN)
set_name(0x8009A524, "GetDown__C4CPad_addr_8009A524", SN_NOWARN)
set_name(0x8009A54C, "GetCur__C4CPad_addr_8009A54C", SN_NOWARN)
set_name(0x8009A574, "SetPadTickMask__4CPadUs_addr_8009A574", SN_NOWARN)
set_name(0x8009A57C, "SetPadTick__4CPadUs_addr_8009A57C", SN_NOWARN)
set_name(0x8009A584, "DEC_AddAsDecRequestor__FP7TextDat", SN_NOWARN)
set_name(0x8009A600, "DEC_RemoveAsDecRequestor__FP7TextDat", SN_NOWARN)
set_name(0x8009A658, "DEC_DoDecompRequests__Fv", SN_NOWARN)
set_name(0x8009A6B4, "FindThisTd__FP7TextDat", SN_NOWARN)
set_name(0x8009A6EC, "FindEmptyIndex__Fv", SN_NOWARN)
set_name(0x8009A724, "UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009A784, "IsGameLoading__Fv", SN_NOWARN)
set_name(0x8009A790, "PutUpCutScreenTSK__FP4TASK", SN_NOWARN)
set_name(0x8009AC04, "PutUpCutScreen__Fi", SN_NOWARN)
set_name(0x8009ACC4, "TakeDownCutScreen__Fv", SN_NOWARN)
set_name(0x8009AD50, "FinishProgress__Fv", SN_NOWARN)
set_name(0x8009ADB4, "PRIM_GetPrim__FPP7POLY_G4_addr_8009ADB4", SN_NOWARN)
set_name(0x8009AE30, "_GLOBAL__D_UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009AE68, "_GLOBAL__I_UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009AEA0, "SetRGB__6DialogUcUcUc_addr_8009AEA0", SN_NOWARN)
set_name(0x8009AEC0, "SetBack__6Dialogi_addr_8009AEC0", SN_NOWARN)
set_name(0x8009AEC8, "SetBorder__6Dialogi_addr_8009AEC8", SN_NOWARN)
set_name(0x8009AED0, "___6Dialog_addr_8009AED0", SN_NOWARN)
set_name(0x8009AEF8, "__6Dialog_addr_8009AEF8", SN_NOWARN)
set_name(0x8009AF54, "___7CScreen", SN_NOWARN)
set_name(0x8009AF74, "init_mem_card__FPFii_vUc", SN_NOWARN)
set_name(0x8009B1AC, "memcard_event__Fii", SN_NOWARN)
set_name(0x8009B1B4, "init_card__Fib", SN_NOWARN)
set_name(0x8009B274, "ping_card__Fi", SN_NOWARN)
set_name(0x8009B308, "CardUpdateTask__FP4TASK", SN_NOWARN)
set_name(0x8009B340, "MemcardON__Fv", SN_NOWARN)
set_name(0x8009B3B0, "MemcardOFF__Fv", SN_NOWARN)
set_name(0x8009B400, "CheckSavedOptions__Fv", SN_NOWARN)
set_name(0x8009B488, "card_removed__Fi", SN_NOWARN)
set_name(0x8009B4B0, "read_card_block__Fii", SN_NOWARN)
set_name(0x8009B4F8, "test_hw_event__Fv", SN_NOWARN)
set_name(0x8009B578, "PrintSelectBack__FbT0", SN_NOWARN)
set_name(0x8009B6F8, "DrawDialogBox__FiiP4RECTiiii", SN_NOWARN)
set_name(0x8009B7DC, "DrawSpinner__FiiUcUcUciiibiT8", SN_NOWARN)
set_name(0x8009BCD0, "DrawMenu__Fi", SN_NOWARN)
set_name(0x8009C960, "who_pressed__Fi", SN_NOWARN)
set_name(0x8009C9E8, "ShowCharacterFiles__Fv", SN_NOWARN)
set_name(0x8009CFEC, "MemcardPad__Fv", SN_NOWARN)
set_name(0x8009D664, "SoundPad__Fv", SN_NOWARN)
set_name(0x8009DE80, "CentrePad__Fv", SN_NOWARN)
set_name(0x8009E2D8, "CalcVolumes__Fv", SN_NOWARN)
set_name(0x8009E410, "SetLoadedVolumes__Fv", SN_NOWARN)
set_name(0x8009E498, "GetVolumes__Fv", SN_NOWARN)
set_name(0x8009E534, "PrintInfoMenu__Fv", SN_NOWARN)
set_name(0x8009E6DC, "SeedPad__Fv", SN_NOWARN)
set_name(0x8009E960, "DrawOptions__FP4TASK", SN_NOWARN)
set_name(0x8009F234, "ToggleOptions__Fv", SN_NOWARN)
set_name(0x8009F2EC, "FormatPad__Fv", SN_NOWARN)
set_name(0x8009F61C, "ActivateMemcard__Fv", SN_NOWARN)
set_name(0x8009F6A0, "PRIM_GetPrim__FPP7POLY_G4_addr_8009F6A0", SN_NOWARN)
set_name(0x8009F71C, "GetTick__C4CPad_addr_8009F71C", SN_NOWARN)
set_name(0x8009F744, "GetDown__C4CPad_addr_8009F744", SN_NOWARN)
set_name(0x8009F76C, "GetUp__C4CPad_addr_8009F76C", SN_NOWARN)
set_name(0x8009F794, "SetPadTickMask__4CPadUs_addr_8009F794", SN_NOWARN)
set_name(0x8009F79C, "SetPadTick__4CPadUs_addr_8009F79C", SN_NOWARN)
set_name(0x8009F7A4, "Flush__4CPad_addr_8009F7A4", SN_NOWARN)
set_name(0x8009F7C8, "SetRGB__6DialogUcUcUc_addr_8009F7C8", SN_NOWARN)
set_name(0x8009F7E8, "SetBack__6Dialogi_addr_8009F7E8", SN_NOWARN)
set_name(0x8009F7F0, "SetBorder__6Dialogi_addr_8009F7F0", SN_NOWARN)
set_name(0x8009F7F8, "___6Dialog_addr_8009F7F8", SN_NOWARN)
set_name(0x8009F820, "__6Dialog_addr_8009F820", SN_NOWARN)
set_name(0x8009F87C, "GetFr__7TextDati_addr_8009F87C", SN_NOWARN)
set_name(0x8009F898, "BirdDistanceOK__Fiiii", SN_NOWARN)
set_name(0x8009F8F0, "AlterBirdPos__FP10BIRDSTRUCTUc", SN_NOWARN)
set_name(0x8009FA34, "BirdWorld__FP10BIRDSTRUCTii", SN_NOWARN)
set_name(0x8009FAB0, "BirdScared__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FC3C, "GetPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FC90, "BIRD_StartHop__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FDF8, "BIRD_DoHop__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FEFC, "BIRD_StartPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FF68, "BIRD_DoPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FFEC, "BIRD_DoScatter__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0098, "CheckDirOk__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A01A8, "BIRD_StartScatter__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0254, "BIRD_StartFly__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A02F8, "BIRD_DoFly__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A05A4, "BIRD_StartLanding__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A05FC, "BIRD_DoLanding__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0668, "PlaceFlock__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0754, "ProcessFlock__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0884, "InitBird__Fv", SN_NOWARN)
set_name(0x800A095C, "ProcessBird__Fv", SN_NOWARN)
set_name(0x800A0AB4, "GetBirdFrame__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0B50, "bscale__FP8POLY_FT4i", SN_NOWARN)
set_name(0x800A0C80, "doshadow__FP10BIRDSTRUCTii", SN_NOWARN)
set_name(0x800A0D8C, "DrawLBird__Fv", SN_NOWARN)
set_name(0x800A0F98, "PRIM_GetPrim__FPP8POLY_FT4_addr_800A0F98", SN_NOWARN)
set_name(0x800A1014, "PlayFMV__FPcii", SN_NOWARN)
set_name(0x800A10E8, "play_movie", SN_NOWARN)
set_name(0x800A11A4, "DisplayMonsterTypes__Fv", SN_NOWARN)
set_name(0x800A1640, "GetDown__C4CPad_addr_800A1640", SN_NOWARN)
set_name(0x800A1668, "GetNumOfFrames__7TextDatii_addr_800A1668", SN_NOWARN)
set_name(0x800A16A0, "GetCreature__7TextDati_addr_800A16A0", SN_NOWARN)
set_name(0x800A1718, "GetNumOfCreatures__7TextDat_addr_800A1718", SN_NOWARN)
set_name(0x800A172C, "GetFr__7TextDati_addr_800A172C", SN_NOWARN)
set_name(0x800A1748, "LoadKanjiFont__FPc", SN_NOWARN)
set_name(0x800A1838, "LoadKanjiIndex__FPc", SN_NOWARN)
set_name(0x800A1948, "FreeKanji__Fv", SN_NOWARN)
set_name(0x800A19D0, "LoadKanji__F10LANG_DB_NO", SN_NOWARN)
set_name(0x800A1AA4, "getb__FUs", SN_NOWARN)
set_name(0x800A1B14, "_get_font__FPUsUsUs", SN_NOWARN)
set_name(0x800A1BE4, "KPrintChar__FUsUsUcUcUs", SN_NOWARN)
set_name(0x800A1D50, "PRIM_GetPrim__FPP8POLY_FT4_addr_800A1D50", SN_NOWARN)
set_name(0x800A1DCC, "writeblock__FP5block", SN_NOWARN)
set_name(0x800A1EB4, "PAK_DoPak__FPUcT0i", SN_NOWARN)
set_name(0x800A20F4, "PAK_DoUnpak__FPUcT0", SN_NOWARN)
set_name(0x800A2194, "fputc__5blockUc", SN_NOWARN)
set_name(0x800A21BC, "HelpPad__Fv", SN_NOWARN)
set_name(0x800A22C4, "InitHelp__Fv", SN_NOWARN)
set_name(0x800A2308, "GetControlKey__FiPb", SN_NOWARN)
set_name(0x800A23B0, "CheckStr__FPcT0i", SN_NOWARN)
set_name(0x800A2484, "DisplayHelp__Fv", SN_NOWARN)
set_name(0x800A2848, "DrawHelp__Fv", SN_NOWARN)
set_name(0x800A28E4, "_GLOBAL__D_DrawHelp__Fv", SN_NOWARN)
set_name(0x800A290C, "_GLOBAL__I_DrawHelp__Fv", SN_NOWARN)
set_name(0x800A2934, "SetRGB__6DialogUcUcUc_addr_800A2934", SN_NOWARN)
set_name(0x800A2954, "SetBorder__6Dialogi_addr_800A2954", SN_NOWARN)
set_name(0x800A295C, "___6Dialog_addr_800A295C", SN_NOWARN)
set_name(0x800A2984, "__6Dialog_addr_800A2984", SN_NOWARN)
set_name(0x800A29E0, "GetCharWidth__5CFontc_addr_800A29E0", SN_NOWARN)
set_name(0x800A2A38, "GetFr__7TextDati_addr_800A2A38", SN_NOWARN)
set_name(0x800A2A54, "GetTick__C4CPad_addr_800A2A54", SN_NOWARN)
set_name(0x800A2A7C, "GetDown__C4CPad_addr_800A2A7C", SN_NOWARN)
set_name(0x800A2AA4, "SetPadTickMask__4CPadUs_addr_800A2AA4", SN_NOWARN)
set_name(0x800A2AAC, "SetPadTick__4CPadUs_addr_800A2AAC", SN_NOWARN)
set_name(0x8002E8B0, "TrimCol__Fs_addr_8002E8B0", SN_NOWARN)
set_name(0x8002E8E8, "DrawSpellCel__FllUclUc", SN_NOWARN)
set_name(0x8002F408, "SetSpellTrans__Fc", SN_NOWARN)
set_name(0x8002F414, "DrawSpellBookTSK__FP4TASK", SN_NOWARN)
set_name(0x8002F4B0, "DrawSpeedSpellTSK__FP4TASK", SN_NOWARN)
set_name(0x8002F554, "ToggleSpell__Fi", SN_NOWARN)
set_name(0x8002F608, "DrawSpellList__Fv", SN_NOWARN)
set_name(0x800301CC, "SetSpell__Fi", SN_NOWARN)
set_name(0x800302A0, "AddPanelString__FPCci", SN_NOWARN)
set_name(0x80030350, "ClearPanel__Fv", SN_NOWARN)
set_name(0x80030380, "InitPanelStr__Fv", SN_NOWARN)
set_name(0x800303A0, "InitControlPan__Fv", SN_NOWARN)
set_name(0x800305C0, "DrawCtrlPan__Fv", SN_NOWARN)
set_name(0x800305EC, "DoAutoMap__Fv", SN_NOWARN)
set_name(0x80030660, "CheckPanelInfo__Fv", SN_NOWARN)
set_name(0x80030D80, "FreeControlPan__Fv", SN_NOWARN)
set_name(0x80030E90, "CPrintString__FiPci", SN_NOWARN)
set_name(0x80030FAC, "PrintInfo__Fv", SN_NOWARN)
set_name(0x80031268, "DrawInfoBox__FP4RECT", SN_NOWARN)
set_name(0x8003191C, "MY_PlrStringXY__Fv", SN_NOWARN)
set_name(0x80031E6C, "ADD_PlrStringXY__FPCcc", SN_NOWARN)
set_name(0x80031F14, "DrawPlus__Fii", SN_NOWARN)
set_name(0x8003207C, "ChrCheckValidButton__Fi", SN_NOWARN)
set_name(0x80032158, "DrawArrows__Fv", SN_NOWARN)
set_name(0x80032250, "BuildChr__Fv", SN_NOWARN)
set_name(0x80033528, "DrawChr__Fv", SN_NOWARN)
set_name(0x80033984, "DrawChrTSK__FP4TASK", SN_NOWARN)
set_name(0x80033A68, "DrawLevelUpIcon__Fi", SN_NOWARN)
set_name(0x80033AFC, "CheckChrBtns__Fv", SN_NOWARN)
set_name(0x80033E68, "DrawDurIcon4Item__FPC10ItemStructii", SN_NOWARN)
set_name(0x80033EEC, "RedBack__Fv", SN_NOWARN)
set_name(0x80033FD4, "PrintSBookStr__FiiUcPCcUc", SN_NOWARN)
set_name(0x8003406C, "GetSBookTrans__FiUc", SN_NOWARN)
set_name(0x80034284, "DrawSpellBook__Fv", SN_NOWARN)
set_name(0x80034C60, "CheckSBook__Fv", SN_NOWARN)
set_name(0x80034E94, "get_pieces_str__Fi", SN_NOWARN)
set_name(0x80034EC8, "_GLOBAL__D_DrawLevelUpFlag", SN_NOWARN)
set_name(0x80034EF0, "_GLOBAL__I_DrawLevelUpFlag", SN_NOWARN)
set_name(0x80034F2C, "GetTick__C4CPad_addr_80034F2C", SN_NOWARN)
set_name(0x80034F54, "GetDown__C4CPad_addr_80034F54", SN_NOWARN)
set_name(0x80034F7C, "SetPadTickMask__4CPadUs_addr_80034F7C", SN_NOWARN)
set_name(0x80034F84, "SetPadTick__4CPadUs_addr_80034F84", SN_NOWARN)
set_name(0x80034F8C, "SetRGB__6DialogUcUcUc_addr_80034F8C", SN_NOWARN)
set_name(0x80034FAC, "SetBack__6Dialogi_addr_80034FAC", SN_NOWARN)
set_name(0x80034FB4, "SetBorder__6Dialogi_addr_80034FB4", SN_NOWARN)
set_name(0x80034FBC, "___6Dialog_addr_80034FBC", SN_NOWARN)
set_name(0x80034FE4, "__6Dialog_addr_80034FE4", SN_NOWARN)
set_name(0x80035040, "GetPal__7TextDati_addr_80035040", SN_NOWARN)
set_name(0x8003505C, "GetFr__7TextDati_addr_8003505C", SN_NOWARN)
set_name(0x80035078, "InitCursor__Fv", SN_NOWARN)
set_name(0x80035080, "FreeCursor__Fv", SN_NOWARN)
set_name(0x80035088, "SetICursor__Fi", SN_NOWARN)
set_name(0x800350E4, "SetCursor__Fi", SN_NOWARN)
set_name(0x80035148, "NewCursor__Fi", SN_NOWARN)
set_name(0x80035168, "InitLevelCursor__Fv", SN_NOWARN)
set_name(0x800351C8, "CheckTown__Fv", SN_NOWARN)
set_name(0x80035454, "CheckRportal__Fv", SN_NOWARN)
set_name(0x800356B4, "CheckCursMove__Fv", SN_NOWARN)
set_name(0x800356BC, "InitDead__Fv", SN_NOWARN)
set_name(0x800358B8, "AddDead__Fiici", SN_NOWARN)
set_name(0x80035900, "FreeGameMem__Fv", SN_NOWARN)
set_name(0x80035950, "start_game__FUi", SN_NOWARN)
set_name(0x800359AC, "free_game__Fv", SN_NOWARN)
set_name(0x80035A20, "LittleStart__FUcUc", SN_NOWARN)
set_name(0x80035AE4, "StartGame__FUcUc", SN_NOWARN)
set_name(0x80035CCC, "run_game_loop__FUi", SN_NOWARN)
set_name(0x80035E3C, "TryIconCurs__Fv", SN_NOWARN)
set_name(0x80036218, "DisableInputWndProc__FUlUilUl", SN_NOWARN)
set_name(0x80036220, "GM_Game__FUlUilUl", SN_NOWARN)
set_name(0x800362D0, "LoadLvlGFX__Fv", SN_NOWARN)
set_name(0x8003636C, "LoadAllGFX__Fv", SN_NOWARN)
set_name(0x8003638C, "CreateLevel__Fi", SN_NOWARN)
set_name(0x80036484, "LoCreateLevel__FPv", SN_NOWARN)
set_name(0x8003660C, "ClearOutDungeonMap__Fv", SN_NOWARN)
set_name(0x800366E8, "LoadGameLevel__FUci", SN_NOWARN)
set_name(0x80037044, "game_logic__Fv", SN_NOWARN)
set_name(0x80037150, "timeout_cursor__FUc", SN_NOWARN)
set_name(0x800371F8, "game_loop__FUc", SN_NOWARN)
set_name(0x80037230, "alloc_plr__Fv", SN_NOWARN)
set_name(0x80037238, "plr_encrypt__FUc", SN_NOWARN)
set_name(0x80037240, "assert_fail__FiPCcT1", SN_NOWARN)
set_name(0x80037260, "assert_fail__FiPCc", SN_NOWARN)
set_name(0x80037280, "app_fatal", SN_NOWARN)
set_name(0x800372B0, "DoMemCardFromFrontEnd__Fv", SN_NOWARN)
set_name(0x800372D8, "DoMemCardFromInGame__Fv", SN_NOWARN)
set_name(0x80037300, "GetActiveTowner__Fi", SN_NOWARN)
set_name(0x80037354, "SetTownerGPtrs__FPUcPPUc", SN_NOWARN)
set_name(0x80037374, "NewTownerAnim__FiPUcii", SN_NOWARN)
set_name(0x800373BC, "InitTownerInfo__FilUciiici", SN_NOWARN)
set_name(0x8003751C, "InitQstSnds__Fi", SN_NOWARN)
set_name(0x800375D4, "InitSmith__Fv", SN_NOWARN)
set_name(0x80037700, "InitBarOwner__Fv", SN_NOWARN)
set_name(0x80037834, "InitTownDead__Fv", SN_NOWARN)
set_name(0x80037964, "InitWitch__Fv", SN_NOWARN)
set_name(0x80037A94, "InitBarmaid__Fv", SN_NOWARN)
set_name(0x80037BC4, "InitBoy__Fv", SN_NOWARN)
set_name(0x80037CFC, "InitHealer__Fv", SN_NOWARN)
set_name(0x80037E2C, "InitTeller__Fv", SN_NOWARN)
set_name(0x80037F5C, "InitDrunk__Fv", SN_NOWARN)
set_name(0x8003808C, "InitCows__Fv", SN_NOWARN)
set_name(0x80038350, "InitTowners__Fv", SN_NOWARN)
set_name(0x800383DC, "FreeTownerGFX__Fv", SN_NOWARN)
set_name(0x80038480, "TownCtrlMsg__Fi", SN_NOWARN)
set_name(0x800385B0, "TownBlackSmith__Fv", SN_NOWARN)
set_name(0x800385E4, "TownBarOwner__Fv", SN_NOWARN)
set_name(0x80038618, "TownDead__Fv", SN_NOWARN)
set_name(0x80038700, "TownHealer__Fv", SN_NOWARN)
set_name(0x80038728, "TownStory__Fv", SN_NOWARN)
set_name(0x80038750, "TownDrunk__Fv", SN_NOWARN)
set_name(0x80038778, "TownBoy__Fv", SN_NOWARN)
set_name(0x800387A0, "TownWitch__Fv", SN_NOWARN)
set_name(0x800387C8, "TownBarMaid__Fv", SN_NOWARN)
set_name(0x800387F0, "TownCow__Fv", SN_NOWARN)
set_name(0x80038818, "ProcessTowners__Fv", SN_NOWARN)
set_name(0x80038A68, "PlrHasItem__FiiRi", SN_NOWARN)
set_name(0x80038B3C, "CowSFX__Fi", SN_NOWARN)
set_name(0x80038C58, "TownerTalk__Fii", SN_NOWARN)
set_name(0x80038C98, "TalkToTowner__Fii", SN_NOWARN)
set_name(0x8003A16C, "effect_is_playing__Fi", SN_NOWARN)
set_name(0x8003A174, "stream_stop__Fv", SN_NOWARN)
set_name(0x8003A1C8, "stream_play__FP4TSFXll", SN_NOWARN)
set_name(0x8003A2B8, "stream_update__Fv", SN_NOWARN)
set_name(0x8003A2C0, "sfx_stop__Fv", SN_NOWARN)
set_name(0x8003A2DC, "InitMonsterSND__Fi", SN_NOWARN)
set_name(0x8003A334, "FreeMonsterSnd__Fv", SN_NOWARN)
set_name(0x8003A33C, "calc_snd_position__FiiPlT2", SN_NOWARN)
set_name(0x8003A440, "PlaySFX_priv__FP4TSFXUcii", SN_NOWARN)
set_name(0x8003A53C, "PlayEffect__Fii", SN_NOWARN)
set_name(0x8003A680, "RndSFX__Fi", SN_NOWARN)
set_name(0x8003A718, "PlaySFX__Fi", SN_NOWARN)
set_name(0x8003A758, "PlaySfxLoc__Fiii", SN_NOWARN)
set_name(0x8003A7AC, "sound_stop__Fv", SN_NOWARN)
set_name(0x8003A844, "sound_update__Fv", SN_NOWARN)
set_name(0x8003A878, "priv_sound_init__FUc", SN_NOWARN)
set_name(0x8003A8BC, "sound_init__Fv", SN_NOWARN)
set_name(0x8003A964, "GetDirection__Fiiii", SN_NOWARN)
set_name(0x8003AA08, "SetRndSeed__Fl", SN_NOWARN)
set_name(0x8003AA18, "GetRndSeed__Fv", SN_NOWARN)
set_name(0x8003AA60, "random__Fil", SN_NOWARN)
set_name(0x8003AACC, "DiabloAllocPtr__FUl", SN_NOWARN)
set_name(0x8003AB18, "mem_free_dbg__FPv", SN_NOWARN)
set_name(0x8003AB68, "LoadFileInMem__FPCcPUl", SN_NOWARN)
set_name(0x8003AB70, "PlayInGameMovie__FPCc", SN_NOWARN)
set_name(0x8003AB78, "Enter__9CCritSect", SN_NOWARN)
set_name(0x8003AB80, "InitDiabloMsg__Fc", SN_NOWARN)
set_name(0x8003AC14, "ClrDiabloMsg__Fv", SN_NOWARN)
set_name(0x8003AC40, "DrawDiabloMsg__Fv", SN_NOWARN)
set_name(0x8003AD4C, "interface_msg_pump__Fv", SN_NOWARN)
set_name(0x8003AD54, "ShowProgress__FUi", SN_NOWARN)
set_name(0x8003B28C, "InitAllItemsUseable__Fv", SN_NOWARN)
set_name(0x8003B2C4, "InitItemGFX__Fv", SN_NOWARN)
set_name(0x8003B2F0, "ItemPlace__Fii", SN_NOWARN)
set_name(0x8003B3B8, "AddInitItems__Fv", SN_NOWARN)
set_name(0x8003B5D0, "InitItems__Fv", SN_NOWARN)
set_name(0x8003B7A8, "CalcPlrItemVals__FiUc", SN_NOWARN)
set_name(0x8003C258, "CalcPlrScrolls__Fi", SN_NOWARN)
set_name(0x8003C5D8, "CalcPlrStaff__FP12PlayerStruct", SN_NOWARN)
set_name(0x8003C674, "CalcSelfItems__Fi", SN_NOWARN)
set_name(0x8003C7D4, "ItemMinStats__FPC12PlayerStructPC10ItemStruct", SN_NOWARN)
set_name(0x8003C820, "CalcPlrItemMin__Fi", SN_NOWARN)
set_name(0x8003C900, "CalcPlrBookVals__Fi", SN_NOWARN)
set_name(0x8003CB94, "CalcPlrInv__FiUc", SN_NOWARN)
set_name(0x8003CC58, "SetPlrHandItem__FP10ItemStructi", SN_NOWARN)
set_name(0x8003CD70, "GetPlrHandSeed__FP10ItemStruct", SN_NOWARN)
set_name(0x8003CD9C, "GetGoldSeed__FiP10ItemStruct", SN_NOWARN)
set_name(0x8003CF18, "SetPlrHandSeed__FP10ItemStructi", SN_NOWARN)
set_name(0x8003CF20, "SetPlrHandGoldCurs__FP10ItemStruct", SN_NOWARN)
set_name(0x8003CF50, "CreatePlrItems__Fi", SN_NOWARN)
set_name(0x8003D38C, "ItemSpaceOk__Fii", SN_NOWARN)
set_name(0x8003D664, "GetItemSpace__Fiic", SN_NOWARN)
set_name(0x8003D890, "GetSuperItemSpace__Fiic", SN_NOWARN)
set_name(0x8003D9F8, "GetSuperItemLoc__FiiRiT2", SN_NOWARN)
set_name(0x8003DAC0, "CalcItemValue__Fi", SN_NOWARN)
set_name(0x8003DB78, "GetBookSpell__Fii", SN_NOWARN)
set_name(0x8003DDE0, "GetStaffPower__FiiiUc", SN_NOWARN)
set_name(0x8003DFD0, "GetStaffSpell__FiiUc", SN_NOWARN)
set_name(0x8003E284, "GetItemAttrs__Fiii", SN_NOWARN)
set_name(0x8003E7D0, "RndPL__Fii", SN_NOWARN)
set_name(0x8003E808, "PLVal__Fiiiii", SN_NOWARN)
set_name(0x8003E87C, "SaveItemPower__Fiiiiiii", SN_NOWARN)
set_name(0x8003FFA8, "GetItemPower__FiiilUc", SN_NOWARN)
set_name(0x80040410, "GetItemBonus__FiiiiUc", SN_NOWARN)
set_name(0x8004050C, "SetupItem__Fi", SN_NOWARN)
set_name(0x80040614, "RndItem__Fi", SN_NOWARN)
set_name(0x80040858, "RndUItem__Fi", SN_NOWARN)
set_name(0x80040A98, "RndAllItems__Fv", SN_NOWARN)
set_name(0x80040C0C, "RndTypeItems__Fii", SN_NOWARN)
set_name(0x80040D0C, "CheckUnique__FiiiUc", SN_NOWARN)
set_name(0x80040EBC, "GetUniqueItem__Fii", SN_NOWARN)
set_name(0x80041164, "SpawnUnique__Fiii", SN_NOWARN)
set_name(0x8004129C, "ItemRndDur__Fi", SN_NOWARN)
set_name(0x8004132C, "SetupAllItems__FiiiiiUcUcUc", SN_NOWARN)
set_name(0x80041638, "SpawnItem__FiiiUc", SN_NOWARN)
set_name(0x80041880, "CreateItem__Fiii", SN_NOWARN)
set_name(0x800419B0, "CreateRndItem__FiiUcUcUc", SN_NOWARN)
set_name(0x80041AF8, "SetupAllUseful__Fiii", SN_NOWARN)
set_name(0x80041BD0, "CreateRndUseful__FiiiUc", SN_NOWARN)
set_name(0x80041C90, "CreateTypeItem__FiiUciiUcUc", SN_NOWARN)
set_name(0x80041DD4, "RecreateEar__FiUsiUciiiiii", SN_NOWARN)
set_name(0x80041FC0, "SpawnQuestItem__Fiiiii", SN_NOWARN)
set_name(0x80042234, "SpawnRock__Fv", SN_NOWARN)
set_name(0x800423F4, "RespawnItem__FiUc", SN_NOWARN)
set_name(0x800425AC, "DeleteItem__Fii", SN_NOWARN)
set_name(0x80042600, "ItemDoppel__Fv", SN_NOWARN)
set_name(0x800426C8, "ProcessItems__Fv", SN_NOWARN)
set_name(0x800428D0, "FreeItemGFX__Fv", SN_NOWARN)
set_name(0x800428D8, "GetItemStr__Fi", SN_NOWARN)
set_name(0x80042A80, "CheckIdentify__Fii", SN_NOWARN)
set_name(0x80042B70, "RepairItem__FP10ItemStructi", SN_NOWARN)
set_name(0x80042C40, "DoRepair__Fii", SN_NOWARN)
set_name(0x80042D04, "RechargeItem__FP10ItemStructi", SN_NOWARN)
set_name(0x80042D74, "DoRecharge__Fii", SN_NOWARN)
set_name(0x80042E74, "PrintItemOil__Fc", SN_NOWARN)
set_name(0x80042F68, "PrintItemPower__FcPC10ItemStruct", SN_NOWARN)
set_name(0x80043624, "PrintUString__FiiUcPcc", SN_NOWARN)
set_name(0x8004362C, "PrintItemMisc__FPC10ItemStruct", SN_NOWARN)
set_name(0x800437B8, "PrintItemDetails__FPC10ItemStruct", SN_NOWARN)
set_name(0x80043B28, "PrintItemDur__FPC10ItemStruct", SN_NOWARN)
set_name(0x80043E38, "CastScroll__Fii", SN_NOWARN)
set_name(0x80043E50, "UseItem__Fiii", SN_NOWARN)
set_name(0x80044468, "StoreStatOk__FP10ItemStruct", SN_NOWARN)
set_name(0x800444FC, "PremiumItemOk__Fi", SN_NOWARN)
set_name(0x80044578, "RndPremiumItem__Fii", SN_NOWARN)
set_name(0x80044680, "SpawnOnePremium__Fii", SN_NOWARN)
set_name(0x800448A0, "SpawnPremium__Fi", SN_NOWARN)
set_name(0x80044AE4, "WitchBookLevel__Fi", SN_NOWARN)
set_name(0x80044C34, "SpawnStoreGold__Fv", SN_NOWARN)
set_name(0x80044CB8, "RecalcStoreStats__Fv", SN_NOWARN)
set_name(0x80044E58, "ItemNoFlippy__Fv", SN_NOWARN)
set_name(0x80044EBC, "CreateSpellBook__FiiiUcUc", SN_NOWARN)
set_name(0x8004504C, "CreateMagicArmor__FiiiiUcUc", SN_NOWARN)
set_name(0x800451C8, "CreateMagicWeapon__FiiiiUcUc", SN_NOWARN)
set_name(0x80045344, "DrawUniqueInfo__Fv", SN_NOWARN)
set_name(0x800454B8, "MakeItemStr__FP10ItemStructUsUs", SN_NOWARN)
set_name(0x800456B8, "veclen2__Fii", SN_NOWARN)
set_name(0x80045720, "set_light_bands__Fv", SN_NOWARN)
set_name(0x8004579C, "SetLightFX__FiisssUcUcUc", SN_NOWARN)
set_name(0x80045808, "DoLighting__Fiiii", SN_NOWARN)
set_name(0x800464B8, "DoUnLight__Fv", SN_NOWARN)
set_name(0x80046700, "DoUnVision__Fiii", SN_NOWARN)
set_name(0x800467C4, "DoVision__FiiiUcUc", SN_NOWARN)
set_name(0x80046CD4, "FreeLightTable__Fv", SN_NOWARN)
set_name(0x80046CDC, "InitLightTable__Fv", SN_NOWARN)
set_name(0x80046CE4, "MakeLightTable__Fv", SN_NOWARN)
set_name(0x80046CEC, "InitLightMax__Fv", SN_NOWARN)
set_name(0x80046D10, "InitLighting__Fv", SN_NOWARN)
set_name(0x80046D54, "AddLight__Fiii", SN_NOWARN)
set_name(0x80046DC0, "AddUnLight__Fi", SN_NOWARN)
set_name(0x80046DF0, "ChangeLightRadius__Fii", SN_NOWARN)
set_name(0x80046E1C, "ChangeLightXY__Fiii", SN_NOWARN)
set_name(0x80046E58, "light_fix__Fi", SN_NOWARN)
set_name(0x80046E60, "ChangeLightOff__Fiii", SN_NOWARN)
set_name(0x80046E94, "ChangeLight__Fiiii", SN_NOWARN)
set_name(0x80046ECC, "ChangeLightColour__Fii", SN_NOWARN)
set_name(0x80046EF4, "ProcessLightList__Fv", SN_NOWARN)
set_name(0x80047018, "SavePreLighting__Fv", SN_NOWARN)
set_name(0x80047020, "InitVision__Fv", SN_NOWARN)
set_name(0x80047070, "AddVision__FiiiUc", SN_NOWARN)
set_name(0x800470EC, "ChangeVisionRadius__Fii", SN_NOWARN)
set_name(0x800471A0, "ChangeVisionXY__Fiii", SN_NOWARN)
set_name(0x80047220, "ProcessVisionList__Fv", SN_NOWARN)
set_name(0x80047420, "FreeQuestText__Fv", SN_NOWARN)
set_name(0x80047428, "InitQuestText__Fv", SN_NOWARN)
set_name(0x80047434, "CalcTextSpeed__FPCc", SN_NOWARN)
set_name(0x80047588, "InitQTextMsg__Fi", SN_NOWARN)
set_name(0x80047730, "DrawQTextBack__Fv", SN_NOWARN)
set_name(0x800477A0, "DrawQTextTSK__FP4TASK", SN_NOWARN)
set_name(0x800478E0, "DrawQText__Fv", SN_NOWARN)
set_name(0x80047C4C, "_GLOBAL__D_QBack", SN_NOWARN)
set_name(0x80047C74, "_GLOBAL__I_QBack", SN_NOWARN)
set_name(0x80047C9C, "SetRGB__6DialogUcUcUc_addr_80047C9C", SN_NOWARN)
set_name(0x80047CBC, "SetBorder__6Dialogi_addr_80047CBC", SN_NOWARN)
set_name(0x80047CC4, "___6Dialog_addr_80047CC4", SN_NOWARN)
set_name(0x80047CEC, "__6Dialog_addr_80047CEC", SN_NOWARN)
set_name(0x80047D48, "GetCharWidth__5CFontc_addr_80047D48", SN_NOWARN)
set_name(0x80047DA0, "GetDown__C4CPad_addr_80047DA0", SN_NOWARN)
set_name(0x80047DC8, "GetFr__7TextDati_addr_80047DC8", SN_NOWARN)
set_name(0x80047DE4, "nullmissile__Fiiiiiicii", SN_NOWARN)
set_name(0x80047DEC, "FuncNULL__FP13MissileStructiii", SN_NOWARN)
set_name(0x80047DF4, "delta_init__Fv", SN_NOWARN)
set_name(0x80047E54, "delta_kill_monster__FiUcUcUc", SN_NOWARN)
set_name(0x80047EF0, "delta_monster_hp__FilUc", SN_NOWARN)
set_name(0x80047F74, "delta_sync_golem__FPC9TCmdGolemiUc", SN_NOWARN)
set_name(0x80048004, "delta_leave_sync__FUc", SN_NOWARN)
set_name(0x80048330, "delta_sync_object__FiUcUc", SN_NOWARN)
set_name(0x80048390, "delta_get_item__FPC9TCmdGItemUc", SN_NOWARN)
set_name(0x80048554, "delta_put_item__FPC9TCmdPItemiiUc", SN_NOWARN)
set_name(0x800486DC, "delta_portal_inited__Fi", SN_NOWARN)
set_name(0x80048700, "delta_quest_inited__Fi", SN_NOWARN)
set_name(0x80048724, "DeltaAddItem__Fi", SN_NOWARN)
set_name(0x80048938, "DeltaExportData__FPc", SN_NOWARN)
set_name(0x800489E0, "DeltaImportData__FPc", SN_NOWARN)
set_name(0x80048A8C, "DeltaSaveLevel__Fv", SN_NOWARN)
set_name(0x80048B88, "NetSendCmd__FUcUc", SN_NOWARN)
set_name(0x80048BB0, "NetSendCmdGolem__FUcUcUcUclUc", SN_NOWARN)
set_name(0x80048BFC, "NetSendCmdLoc__FUcUcUcUc", SN_NOWARN)
set_name(0x80048C2C, "NetSendCmdLocParam1__FUcUcUcUcUs", SN_NOWARN)
set_name(0x80048C64, "NetSendCmdLocParam2__FUcUcUcUcUsUs", SN_NOWARN)
set_name(0x80048CA4, "NetSendCmdLocParam3__FUcUcUcUcUsUsUs", SN_NOWARN)
set_name(0x80048CEC, "NetSendCmdParam1__FUcUcUs", SN_NOWARN)
set_name(0x80048D18, "NetSendCmdParam2__FUcUcUsUs", SN_NOWARN)
set_name(0x80048D48, "NetSendCmdParam3__FUcUcUsUsUs", SN_NOWARN)
set_name(0x80048D80, "NetSendCmdQuest__FUcUc", SN_NOWARN)
set_name(0x80048DF4, "NetSendCmdGItem__FUcUcUcUcUc", SN_NOWARN)
set_name(0x80048F28, "NetSendCmdGItem2__FUcUcUcUcPC9TCmdGItem", SN_NOWARN)
set_name(0x80048FA4, "NetSendCmdReq2__FUcUcUcPC9TCmdGItem", SN_NOWARN)
set_name(0x80048FFC, "NetSendCmdExtra__FPC9TCmdGItem", SN_NOWARN)
set_name(0x80049064, "NetSendCmdPItem__FUcUcUcUc", SN_NOWARN)
set_name(0x8004916C, "NetSendCmdChItem__FUcUc", SN_NOWARN)
set_name(0x80049210, "NetSendCmdDelItem__FUcUc", SN_NOWARN)
set_name(0x80049240, "NetSendCmdDItem__FUci", SN_NOWARN)
set_name(0x80049354, "i_own_level__Fi", SN_NOWARN)
set_name(0x8004935C, "NetSendCmdDamage__FUcUcUl", SN_NOWARN)
set_name(0x80049390, "delta_open_portal__FiUcUcUcUcUc", SN_NOWARN)
set_name(0x800493EC, "delta_close_portal__Fi", SN_NOWARN)
set_name(0x8004942C, "check_update_plr__Fi", SN_NOWARN)
set_name(0x80049434, "On_WALKXY__FPC4TCmdi", SN_NOWARN)
set_name(0x800494B4, "On_ADDSTR__FPC4TCmdi", SN_NOWARN)
set_name(0x800494E4, "On_ADDMAG__FPC4TCmdi", SN_NOWARN)
set_name(0x80049514, "On_ADDDEX__FPC4TCmdi", SN_NOWARN)
set_name(0x80049544, "On_ADDVIT__FPC4TCmdi", SN_NOWARN)
set_name(0x80049574, "On_SBSPELL__FPC4TCmdi", SN_NOWARN)
set_name(0x800495E8, "On_GOTOGETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049670, "On_REQUESTGITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x800497B0, "On_GETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049980, "On_GOTOAGETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049A08, "On_REQUESTAGITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049B3C, "On_AGETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049D04, "On_ITEMEXTRA__FPC4TCmdi", SN_NOWARN)
set_name(0x80049D50, "On_PUTITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049E68, "On_SYNCPUTITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049F68, "On_RESPAWNITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049FC0, "On_SATTACKXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A04C, "On_SPELLXYD__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A134, "On_SPELLXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A20C, "On_TSPELLXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A2E8, "On_OPOBJXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A3C8, "On_DISARMXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A4A8, "On_OPOBJT__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A4F4, "On_ATTACKID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A628, "On_SPELLID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A6F0, "On_SPELLPID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A7B0, "On_TSPELLID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A874, "On_TSPELLPID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A938, "On_KNOCKBACK__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A980, "On_RESURRECT__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A9B8, "On_HEALOTHER__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A9E0, "On_TALKXY__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AA68, "On_NEWLVL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AA98, "On_WARP__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AB8C, "On_MONSTDEATH__FPC4TCmdi", SN_NOWARN)
set_name(0x8004ABF8, "On_KILLGOLEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AC64, "On_AWAKEGOLEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AD7C, "On_MONSTDAMAGE__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AE68, "On_PLRDEAD__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AEB0, "On_PLRDAMAGE__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B06C, "On_OPENDOOR__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B0E8, "On_CLOSEDOOR__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B164, "On_OPERATEOBJ__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B1E0, "On_PLROPOBJ__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B25C, "On_BREAKOBJ__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B2D4, "On_CHANGEPLRITEMS__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B2DC, "On_DELPLRITEMS__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B2E4, "On_PLRLEVEL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B2EC, "On_DROPITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B344, "On_PLAYER_JOINLEVEL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B5BC, "On_ACTIVATEPORTAL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B74C, "On_DEACTIVATEPORTAL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B79C, "On_RETOWN__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B7E4, "On_SETSTR__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B824, "On_SETDEX__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B864, "On_SETMAG__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B8A4, "On_SETVIT__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B8E4, "On_SYNCQUEST__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B92C, "On_ENDSHIELD__FPC4TCmdi", SN_NOWARN)
set_name(0x8004BA08, "ParseCmd__FiPC4TCmd", SN_NOWARN)
set_name(0x8004BE28, "GetDLevel__Fib", SN_NOWARN)
set_name(0x8004BEB8, "ReleaseDLevel__FP6DLevel", SN_NOWARN)
set_name(0x8004BEF0, "NetSendLoPri__FPCUcUc", SN_NOWARN)
set_name(0x8004BF1C, "InitLevelType__Fi", SN_NOWARN)
set_name(0x8004BF68, "SetupLocalCoords__Fv", SN_NOWARN)
set_name(0x8004C0F8, "InitNewSeed__Fl", SN_NOWARN)
set_name(0x8004C16C, "NetInit__FUcPUc", SN_NOWARN)
set_name(0x8004C3C0, "PostAddL1Door__Fiiii", SN_NOWARN)
set_name(0x8004C4F8, "PostAddL2Door__Fiiii", SN_NOWARN)
set_name(0x8004C644, "PostAddArmorStand__Fi", SN_NOWARN)
set_name(0x8004C6CC, "PostTorchLocOK__Fii", SN_NOWARN)
set_name(0x8004C70C, "PostAddObjLight__Fii", SN_NOWARN)
set_name(0x8004C7B0, "PostObjObjAddSwitch__Fiiii", SN_NOWARN)
set_name(0x8004C840, "InitObjectGFX__Fv", SN_NOWARN)
set_name(0x8004CA5C, "FreeObjectGFX__Fv", SN_NOWARN)
set_name(0x8004CA68, "DeleteObject__Fii", SN_NOWARN)
set_name(0x8004CB20, "SetupObject__Fiiii", SN_NOWARN)
set_name(0x8004CDA4, "SetObjMapRange__Fiiiiii", SN_NOWARN)
set_name(0x8004CE04, "SetBookMsg__Fii", SN_NOWARN)
set_name(0x8004CE2C, "AddObject__Fiii", SN_NOWARN)
set_name(0x8004CF38, "PostAddObject__Fiii", SN_NOWARN)
set_name(0x8004D044, "Obj_Light__Fii", SN_NOWARN)
set_name(0x8004D254, "Obj_Circle__Fi", SN_NOWARN)
set_name(0x8004D590, "Obj_StopAnim__Fi", SN_NOWARN)
set_name(0x8004D5F4, "DrawExpl__Fiiiiiccc", SN_NOWARN)
set_name(0x8004D8D0, "DrawObjExpl__FP12ObjectStructiii", SN_NOWARN)
set_name(0x8004D940, "Obj_Door__Fi", SN_NOWARN)
set_name(0x8004DAD4, "Obj_Sarc__Fi", SN_NOWARN)
set_name(0x8004DB20, "ActivateTrapLine__Fii", SN_NOWARN)
set_name(0x8004DC44, "Obj_FlameTrap__Fi", SN_NOWARN)
set_name(0x8004DF14, "Obj_Trap__Fi", SN_NOWARN)
set_name(0x8004E264, "Obj_BCrossDamage__Fi", SN_NOWARN)
set_name(0x8004E4F4, "ProcessObjects__Fv", SN_NOWARN)
set_name(0x8004E7D0, "ObjSetMicro__Fiii", SN_NOWARN)
set_name(0x8004E808, "ObjSetMini__Fiii", SN_NOWARN)
set_name(0x8004E8DC, "ObjL1Special__Fiiii", SN_NOWARN)
set_name(0x8004E8E4, "ObjL2Special__Fiiii", SN_NOWARN)
set_name(0x8004E8EC, "DoorSet__Fiii", SN_NOWARN)
set_name(0x8004EB6C, "RedoPlayerVision__Fv", SN_NOWARN)
set_name(0x8004EC10, "OperateL1RDoor__FiiUc", SN_NOWARN)
set_name(0x8004EFB4, "OperateL1LDoor__FiiUc", SN_NOWARN)
set_name(0x8004F38C, "OperateL2RDoor__FiiUc", SN_NOWARN)
set_name(0x8004F724, "OperateL2LDoor__FiiUc", SN_NOWARN)
set_name(0x8004FABC, "OperateL3RDoor__FiiUc", SN_NOWARN)
set_name(0x8004FDC4, "OperateL3LDoor__FiiUc", SN_NOWARN)
set_name(0x800500CC, "MonstCheckDoors__Fi", SN_NOWARN)
set_name(0x800505C8, "PostAddL1Objs__Fiiii", SN_NOWARN)
set_name(0x80050700, "PostAddL2Objs__Fiiii", SN_NOWARN)
set_name(0x80050814, "ObjChangeMap__Fiiii", SN_NOWARN)
set_name(0x800509CC, "DRLG_MRectTrans__Fiiii", SN_NOWARN)
set_name(0x80050A78, "ObjChangeMapResync__Fiiii", SN_NOWARN)
set_name(0x80050BFC, "OperateL1Door__FiiUc", SN_NOWARN)
set_name(0x80050D58, "OperateLever__Fii", SN_NOWARN)
set_name(0x80050F44, "OperateBook__Fii", SN_NOWARN)
set_name(0x8005146C, "OperateBookLever__Fii", SN_NOWARN)
set_name(0x800519FC, "OperateSChambBk__Fii", SN_NOWARN)
set_name(0x80051C3C, "OperateChest__FiiUc", SN_NOWARN)
set_name(0x8005200C, "OperateMushPatch__Fii", SN_NOWARN)
set_name(0x800521D8, "OperateInnSignChest__Fii", SN_NOWARN)
set_name(0x8005238C, "OperateSlainHero__FiiUc", SN_NOWARN)
set_name(0x800525E0, "OperateTrapLvr__Fi", SN_NOWARN)
set_name(0x800527B0, "OperateSarc__FiiUc", SN_NOWARN)
set_name(0x80052968, "OperateL2Door__FiiUc", SN_NOWARN)
set_name(0x80052AC4, "OperateL3Door__FiiUc", SN_NOWARN)
set_name(0x80052C20, "LoadMapObjs__FPUcii", SN_NOWARN)
set_name(0x80052D28, "OperatePedistal__Fii", SN_NOWARN)
set_name(0x80053240, "TryDisarm__Fii", SN_NOWARN)
set_name(0x80053404, "ItemMiscIdIdx__Fi", SN_NOWARN)
set_name(0x80053474, "OperateShrine__Fiii", SN_NOWARN)
set_name(0x80055A44, "OperateSkelBook__FiiUc", SN_NOWARN)
set_name(0x80055BC0, "OperateBookCase__FiiUc", SN_NOWARN)
set_name(0x80055DC4, "OperateDecap__FiiUc", SN_NOWARN)
set_name(0x80055EAC, "OperateArmorStand__FiiUc", SN_NOWARN)
set_name(0x8005601C, "FindValidShrine__Fi", SN_NOWARN)
set_name(0x8005610C, "OperateGoatShrine__Fiii", SN_NOWARN)
set_name(0x800561B4, "OperateCauldron__Fiii", SN_NOWARN)
set_name(0x80056258, "OperateFountains__Fii", SN_NOWARN)
set_name(0x80056804, "OperateWeaponRack__FiiUc", SN_NOWARN)
set_name(0x800569B0, "OperateStoryBook__Fii", SN_NOWARN)
set_name(0x80056AA0, "OperateLazStand__Fii", SN_NOWARN)
set_name(0x80056C04, "OperateObject__FiiUc", SN_NOWARN)
set_name(0x8005703C, "SyncOpL1Door__Fiii", SN_NOWARN)
set_name(0x80057150, "SyncOpL2Door__Fiii", SN_NOWARN)
set_name(0x80057264, "SyncOpL3Door__Fiii", SN_NOWARN)
set_name(0x80057378, "SyncOpObject__Fiii", SN_NOWARN)
set_name(0x80057578, "BreakCrux__Fi", SN_NOWARN)
set_name(0x80057768, "BreakBarrel__FiiiUcUc", SN_NOWARN)
set_name(0x80057CBC, "BreakObject__Fii", SN_NOWARN)
set_name(0x80057E1C, "SyncBreakObj__Fii", SN_NOWARN)
set_name(0x80057E78, "SyncL1Doors__Fi", SN_NOWARN)
set_name(0x80057F90, "SyncCrux__Fi", SN_NOWARN)
set_name(0x800580C8, "SyncLever__Fi", SN_NOWARN)
set_name(0x80058144, "SyncQSTLever__Fi", SN_NOWARN)
set_name(0x80058250, "SyncPedistal__Fi", SN_NOWARN)
set_name(0x800583AC, "SyncL2Doors__Fi", SN_NOWARN)
set_name(0x80058514, "SyncL3Doors__Fi", SN_NOWARN)
set_name(0x80058640, "SyncObjectAnim__Fi", SN_NOWARN)
set_name(0x80058780, "GetObjectStr__Fi", SN_NOWARN)
set_name(0x80058B9C, "RestoreObjectLight__Fv", SN_NOWARN)
set_name(0x80058DB8, "GetNumOfFrames__7TextDatii_addr_80058DB8", SN_NOWARN)
set_name(0x80058DF0, "GetCreature__7TextDati_addr_80058DF0", SN_NOWARN)
set_name(0x80058E68, "GetNumOfCreatures__7TextDat_addr_80058E68", SN_NOWARN)
set_name(0x80058E7C, "FindPath__FPFiii_UciiiiiPc", SN_NOWARN)
set_name(0x80058E84, "game_2_ui_class__FPC12PlayerStruct", SN_NOWARN)
set_name(0x80058EB0, "game_2_ui_player__FPC12PlayerStructP11_uiheroinfoUc", SN_NOWARN)
set_name(0x80058F64, "SetupLocalPlayer__Fv", SN_NOWARN)
set_name(0x80058F84, "ismyplr__FP12PlayerStruct", SN_NOWARN)
set_name(0x80058FC8, "plrind__FP12PlayerStruct", SN_NOWARN)
set_name(0x80058FDC, "InitPlayerGFX__FP12PlayerStruct", SN_NOWARN)
set_name(0x80058FFC, "FreePlayerGFX__FP12PlayerStruct", SN_NOWARN)
set_name(0x80059004, "NewPlrAnim__FP12PlayerStructiii", SN_NOWARN)
set_name(0x80059020, "ClearPlrPVars__FP12PlayerStruct", SN_NOWARN)
set_name(0x80059044, "SetPlrAnims__FP12PlayerStruct", SN_NOWARN)
set_name(0x80059280, "CreatePlayer__FP12PlayerStructc", SN_NOWARN)
set_name(0x8005969C, "CalcStatDiff__FP12PlayerStruct", SN_NOWARN)
set_name(0x80059704, "NextPlrLevel__FP12PlayerStruct", SN_NOWARN)
set_name(0x80059874, "AddPlrExperience__FP12PlayerStructil", SN_NOWARN)
set_name(0x80059A80, "AddPlrMonstExper__Filc", SN_NOWARN)
set_name(0x80059B04, "InitPlayer__FP12PlayerStructUc", SN_NOWARN)
set_name(0x80059EA4, "InitMultiView__Fv", SN_NOWARN)
set_name(0x80059EAC, "CheckLeighSolid__Fii", SN_NOWARN)
set_name(0x80059F44, "SolidLoc__Fii", SN_NOWARN)
set_name(0x80059FCC, "PlrClrTrans__Fii", SN_NOWARN)
set_name(0x8005A060, "PlrDoTrans__Fii", SN_NOWARN)
set_name(0x8005A154, "SetPlayerOld__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A168, "StartStand__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A1F4, "StartWalkStand__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A258, "PM_ChangeLightOff__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A294, "PM_ChangeOffset__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A2C0, "StartAttack__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A3F8, "StartPlrBlock__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A490, "StartSpell__FP12PlayerStructiii", SN_NOWARN)
set_name(0x8005A62C, "RemovePlrFromMap__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A74C, "StartPlrHit__FP12PlayerStructiUc", SN_NOWARN)
set_name(0x8005A86C, "RespawnDeadItem__FP10ItemStructii", SN_NOWARN)
set_name(0x8005AA08, "PlrDeadItem__FP12PlayerStructP10ItemStructii", SN_NOWARN)
set_name(0x8005ABD0, "StartPlayerKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005AED8, "DropHalfPlayersGold__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B320, "StartPlrKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005B478, "SyncPlrKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005B498, "RemovePlrMissiles__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B780, "InitLevelChange__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B844, "StartNewLvl__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005B988, "RestartTownLvl__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BA18, "StartWarpLvl__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005BAD4, "PM_DoStand__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BADC, "ChkPlrOffsets__Fiiii", SN_NOWARN)
set_name(0x8005BB64, "PM_DoWalk__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BED0, "WeaponDur__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005C070, "PlrHitMonst__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005C6A0, "PlrHitPlr__FP12PlayerStructc", SN_NOWARN)
set_name(0x8005CA50, "PlrHitObj__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005CAE0, "PM_DoAttack__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005CE6C, "PM_DoRangeAttack__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005CF6C, "ShieldDur__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005D030, "PM_DoBlock__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005D0D0, "do_spell_anim__FiiiP12PlayerStruct", SN_NOWARN)
set_name(0x8005E094, "PM_DoSpell__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E3D4, "ArmorDur__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E4D4, "PM_DoGotHit__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E550, "PM_DoDeath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E690, "PM_DoNewLvl__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E698, "CheckNewPath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005EAD8, "PlrDeathModeOK__Fi", SN_NOWARN)
set_name(0x8005EB40, "ValidatePlayer__Fv", SN_NOWARN)
set_name(0x8005F028, "CheckCheatStats__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005F0C4, "ProcessPlayers__Fv", SN_NOWARN)
set_name(0x8005F3F8, "ClrPlrPath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005F420, "PosOkPlayer__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005F5C8, "MakePlrPath__FP12PlayerStructiiUc", SN_NOWARN)
set_name(0x8005F5D0, "CheckPlrSpell__Fv", SN_NOWARN)
set_name(0x8005F9E0, "SyncInitPlrPos__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005FB08, "SyncInitPlr__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005FB38, "CheckStats__Fi", SN_NOWARN)
set_name(0x8005FCD4, "ModifyPlrStr__Fii", SN_NOWARN)
set_name(0x8005FDF0, "ModifyPlrMag__Fii", SN_NOWARN)
set_name(0x8005FEDC, "ModifyPlrDex__Fii", SN_NOWARN)
set_name(0x8005FFC0, "ModifyPlrVit__Fii", SN_NOWARN)
set_name(0x8006009C, "SetPlayerHitPoints__FP12PlayerStructi", SN_NOWARN)
set_name(0x800600E0, "SetPlrStr__Fii", SN_NOWARN)
set_name(0x800601BC, "SetPlrMag__Fii", SN_NOWARN)
set_name(0x8006022C, "SetPlrDex__Fii", SN_NOWARN)
set_name(0x80060308, "SetPlrVit__Fii", SN_NOWARN)
set_name(0x80060374, "InitDungMsgs__FP12PlayerStruct", SN_NOWARN)
set_name(0x8006037C, "PlayDungMsgs__Fv", SN_NOWARN)
set_name(0x800606AC, "CreatePlrItems__FP12PlayerStruct", SN_NOWARN)
set_name(0x800606D4, "WorldToOffset__FP12PlayerStructii", SN_NOWARN)
set_name(0x80060718, "SetSpdbarGoldCurs__FP12PlayerStructi", SN_NOWARN)
set_name(0x8006074C, "GetSpellLevel__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060780, "BreakObject__FP12PlayerStructi", SN_NOWARN)
set_name(0x800607B4, "CalcPlrInv__FP12PlayerStructUc", SN_NOWARN)
set_name(0x800607E8, "RemoveSpdBarItem__FP12PlayerStructi", SN_NOWARN)
set_name(0x8006081C, "M_StartKill__FiP12PlayerStruct", SN_NOWARN)
set_name(0x80060854, "SetGoldCurs__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060888, "HealStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x800608B0, "HealotherStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x800608D8, "CalculateGold__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060900, "M_StartHit__FiP12PlayerStructi", SN_NOWARN)
set_name(0x80060948, "TeleStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060970, "PhaseStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060998, "RemoveInvItem__FP12PlayerStructi", SN_NOWARN)
set_name(0x800609CC, "PhaseEnd__FP12PlayerStruct", SN_NOWARN)
set_name(0x800609F4, "OperateObject__FP12PlayerStructiUc", SN_NOWARN)
set_name(0x80060A38, "TryDisarm__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060A6C, "TalkToTowner__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060AA0, "PosOkPlayer__Fiii", SN_NOWARN)
set_name(0x80060AEC, "CalcStatDiff__Fi", SN_NOWARN)
set_name(0x80060B38, "StartNewLvl__Fiii", SN_NOWARN)
set_name(0x80060B84, "CreatePlayer__Fic", SN_NOWARN)
set_name(0x80060BD8, "StartStand__Fii", SN_NOWARN)
set_name(0x80060C24, "SetPlayerHitPoints__Fii", SN_NOWARN)
set_name(0x80060C70, "MakePlrPath__FiiiUc", SN_NOWARN)
set_name(0x80060CC0, "StartWarpLvl__Fii", SN_NOWARN)
set_name(0x80060D0C, "SyncPlrKill__Fii", SN_NOWARN)
set_name(0x80060D58, "StartPlrKill__Fii", SN_NOWARN)
set_name(0x80060DA4, "NewPlrAnim__Fiiii", SN_NOWARN)
set_name(0x80060DF0, "AddPlrExperience__Fiil", SN_NOWARN)
set_name(0x80060E3C, "StartPlrBlock__Fii", SN_NOWARN)
set_name(0x80060E88, "StartPlrHit__FiiUc", SN_NOWARN)
set_name(0x80060ED8, "StartSpell__Fiiii", SN_NOWARN)
set_name(0x80060F24, "InitPlayer__FiUc", SN_NOWARN)
set_name(0x80060F74, "PM_ChangeLightOff__Fi", SN_NOWARN)
set_name(0x80060FC0, "CheckNewPath__Fi", SN_NOWARN)
set_name(0x8006100C, "FreePlayerGFX__Fi", SN_NOWARN)
set_name(0x80061058, "InitDungMsgs__Fi", SN_NOWARN)
set_name(0x800610A4, "InitPlayerGFX__Fi", SN_NOWARN)
set_name(0x800610F0, "SyncInitPlrPos__Fi", SN_NOWARN)
set_name(0x8006113C, "SetPlrAnims__Fi", SN_NOWARN)
set_name(0x80061188, "ClrPlrPath__Fi", SN_NOWARN)
set_name(0x800611D4, "SyncInitPlr__Fi", SN_NOWARN)
set_name(0x80061220, "RestartTownLvl__Fi", SN_NOWARN)
set_name(0x8006126C, "SetPlayerOld__Fi", SN_NOWARN)
set_name(0x800612B8, "GetGoldSeed__FP12PlayerStructP10ItemStruct", SN_NOWARN)
set_name(0x800612EC, "PRIM_GetPrim__FPP8POLY_FT4_addr_800612EC", SN_NOWARN)
set_name(0x80061368, "GetPlayer__7CPlayeri_addr_80061368", SN_NOWARN)
set_name(0x800613B8, "GetLastOtPos__C7CPlayer_addr_800613B8", SN_NOWARN)
set_name(0x800613C4, "GetLastScrY__C7CPlayer", SN_NOWARN)
set_name(0x800613D0, "GetLastScrX__C7CPlayer", SN_NOWARN)
set_name(0x800613DC, "TSK_Lava2Water__FP4TASK", SN_NOWARN)
set_name(0x80061628, "CheckQuests__Fv", SN_NOWARN)
set_name(0x80061ADC, "ForceQuests__Fv", SN_NOWARN)
set_name(0x80061C80, "QuestStatus__Fi", SN_NOWARN)
set_name(0x80061D14, "CheckQuestKill__FiUc", SN_NOWARN)
set_name(0x800622F4, "SetReturnLvlPos__Fv", SN_NOWARN)
set_name(0x80062404, "GetReturnLvlPos__Fv", SN_NOWARN)
set_name(0x80062458, "ResyncMPQuests__Fv", SN_NOWARN)
set_name(0x80062594, "ResyncQuests__Fv", SN_NOWARN)
set_name(0x80062AF4, "PrintQLString__FiiUcPcc", SN_NOWARN)
set_name(0x80062D20, "DrawQuestLog__Fv", SN_NOWARN)
set_name(0x80062EE8, "DrawQuestLogTSK__FP4TASK", SN_NOWARN)
set_name(0x80062F80, "StartQuestlog__Fv", SN_NOWARN)
set_name(0x80063098, "QuestlogUp__Fv", SN_NOWARN)
set_name(0x800630EC, "QuestlogDown__Fv", SN_NOWARN)
set_name(0x80063158, "RemoveQLog__Fv", SN_NOWARN)
set_name(0x800631D0, "QuestlogEnter__Fv", SN_NOWARN)
set_name(0x80063294, "QuestlogESC__Fv", SN_NOWARN)
set_name(0x800632BC, "SetMultiQuest__FiiUci", SN_NOWARN)
set_name(0x8006333C, "_GLOBAL__D_questlog", SN_NOWARN)
set_name(0x80063364, "_GLOBAL__I_questlog", SN_NOWARN)
set_name(0x8006338C, "GetBlockTexDat__7CBlocks", SN_NOWARN)
set_name(0x80063398, "SetRGB__6DialogUcUcUc_addr_80063398", SN_NOWARN)
set_name(0x800633B8, "SetBack__6Dialogi_addr_800633B8", SN_NOWARN)
set_name(0x800633C0, "SetBorder__6Dialogi_addr_800633C0", SN_NOWARN)
set_name(0x800633C8, "___6Dialog_addr_800633C8", SN_NOWARN)
set_name(0x800633F0, "__6Dialog_addr_800633F0", SN_NOWARN)
set_name(0x8006344C, "GetPal__7TextDati_addr_8006344C", SN_NOWARN)
set_name(0x80063468, "GetFr__7TextDati_addr_80063468", SN_NOWARN)
set_name(0x80063484, "DrawView__Fii", SN_NOWARN)
set_name(0x8006364C, "DrawAndBlit__Fv", SN_NOWARN)
set_name(0x80063778, "FreeStoreMem__Fv", SN_NOWARN)
set_name(0x80063780, "DrawSTextBack__Fv", SN_NOWARN)
set_name(0x800637F0, "PrintSString__FiiUcPcci", SN_NOWARN)
set_name(0x80063BE4, "DrawSLine__Fi", SN_NOWARN)
set_name(0x80063C78, "ClearSText__Fii", SN_NOWARN)
set_name(0x80063D10, "AddSLine__Fi", SN_NOWARN)
set_name(0x80063D60, "AddSTextVal__Fii", SN_NOWARN)
set_name(0x80063D88, "AddSText__FiiUcPccUc", SN_NOWARN)
set_name(0x80063E3C, "PrintStoreItem__FPC10ItemStructic", SN_NOWARN)
set_name(0x800642C4, "StoreAutoPlace__Fv", SN_NOWARN)
set_name(0x800648E4, "S_StartSmith__Fv", SN_NOWARN)
set_name(0x80064A6C, "S_ScrollSBuy__Fi", SN_NOWARN)
set_name(0x80064C24, "S_StartSBuy__Fv", SN_NOWARN)
set_name(0x80064D54, "S_ScrollSPBuy__Fi", SN_NOWARN)
set_name(0x80064F74, "S_StartSPBuy__Fv", SN_NOWARN)
set_name(0x800650C4, "SmithSellOk__Fi", SN_NOWARN)
set_name(0x800651A8, "S_ScrollSSell__Fi", SN_NOWARN)
set_name(0x800653D0, "S_StartSSell__Fv", SN_NOWARN)
set_name(0x80065800, "SmithRepairOk__Fi", SN_NOWARN)
set_name(0x800658A4, "AddStoreHoldRepair__FP10ItemStructi", SN_NOWARN)
set_name(0x80065A84, "S_StartSRepair__Fv", SN_NOWARN)
set_name(0x80065F54, "S_StartWitch__Fv", SN_NOWARN)
set_name(0x80066094, "S_ScrollWBuy__Fi", SN_NOWARN)
set_name(0x8006626C, "S_StartWBuy__Fv", SN_NOWARN)
set_name(0x80066398, "WitchSellOk__Fi", SN_NOWARN)
set_name(0x800664BC, "S_StartWSell__Fv", SN_NOWARN)
set_name(0x80066B14, "WitchRechargeOk__Fi", SN_NOWARN)
set_name(0x80066B9C, "AddStoreHoldRecharge__FG10ItemStructi", SN_NOWARN)
set_name(0x80066D1C, "S_StartWRecharge__Fv", SN_NOWARN)
set_name(0x8006713C, "S_StartNoMoney__Fv", SN_NOWARN)
set_name(0x800671A4, "S_StartNoRoom__Fv", SN_NOWARN)
set_name(0x80067204, "S_StartConfirm__Fv", SN_NOWARN)
set_name(0x8006757C, "S_StartBoy__Fv", SN_NOWARN)
set_name(0x8006770C, "S_StartBBoy__Fv", SN_NOWARN)
set_name(0x80067894, "S_StartHealer__Fv", SN_NOWARN)
set_name(0x80067A68, "S_ScrollHBuy__Fi", SN_NOWARN)
set_name(0x80067BD4, "S_StartHBuy__Fv", SN_NOWARN)
set_name(0x80067CF4, "S_StartStory__Fv", SN_NOWARN)
set_name(0x80067DE4, "IdItemOk__FP10ItemStruct", SN_NOWARN)
set_name(0x80067E18, "AddStoreHoldId__FG10ItemStructi", SN_NOWARN)
set_name(0x80067EEC, "S_StartSIdentify__Fv", SN_NOWARN)
set_name(0x8006894C, "S_StartIdShow__Fv", SN_NOWARN)
set_name(0x80068B20, "S_StartTalk__Fv", SN_NOWARN)
set_name(0x80068D50, "S_StartTavern__Fv", SN_NOWARN)
set_name(0x80068E48, "S_StartBarMaid__Fv", SN_NOWARN)
set_name(0x80068F1C, "S_StartDrunk__Fv", SN_NOWARN)
set_name(0x80068FF0, "StartStore__Fc", SN_NOWARN)
set_name(0x800692D8, "DrawSText__Fv", SN_NOWARN)
set_name(0x80069318, "DrawSTextTSK__FP4TASK", SN_NOWARN)
set_name(0x800693E0, "DoThatDrawSText__Fv", SN_NOWARN)
set_name(0x8006958C, "STextESC__Fv", SN_NOWARN)
set_name(0x80069700, "STextUp__Fv", SN_NOWARN)
set_name(0x80069898, "STextDown__Fv", SN_NOWARN)
set_name(0x80069A48, "S_SmithEnter__Fv", SN_NOWARN)
set_name(0x80069B1C, "SetGoldCurs__Fii", SN_NOWARN)
set_name(0x80069B98, "SetSpdbarGoldCurs__Fii", SN_NOWARN)
set_name(0x80069C14, "TakePlrsMoney__Fl", SN_NOWARN)
set_name(0x8006A060, "SmithBuyItem__Fv", SN_NOWARN)
set_name(0x8006A254, "S_SBuyEnter__Fv", SN_NOWARN)
set_name(0x8006A478, "SmithBuyPItem__Fv", SN_NOWARN)
set_name(0x8006A600, "S_SPBuyEnter__Fv", SN_NOWARN)
set_name(0x8006A830, "StoreGoldFit__Fi", SN_NOWARN)
set_name(0x8006AAE8, "PlaceStoreGold__Fl", SN_NOWARN)
set_name(0x8006AD4C, "StoreSellItem__Fv", SN_NOWARN)
set_name(0x8006B040, "S_SSellEnter__Fv", SN_NOWARN)
set_name(0x8006B144, "SmithRepairItem__Fv", SN_NOWARN)
set_name(0x8006B3B4, "S_SRepairEnter__Fv", SN_NOWARN)
set_name(0x8006B510, "S_WitchEnter__Fv", SN_NOWARN)
set_name(0x8006B5C0, "WitchBuyItem__Fv", SN_NOWARN)
set_name(0x8006B7C0, "S_WBuyEnter__Fv", SN_NOWARN)
set_name(0x8006B9AC, "S_WSellEnter__Fv", SN_NOWARN)
set_name(0x8006BAB0, "WitchRechargeItem__Fv", SN_NOWARN)
set_name(0x8006BC28, "S_WRechargeEnter__Fv", SN_NOWARN)
set_name(0x8006BD84, "S_BoyEnter__Fv", SN_NOWARN)
set_name(0x8006BEBC, "BoyBuyItem__Fv", SN_NOWARN)
set_name(0x8006BF40, "HealerBuyItem__Fv", SN_NOWARN)
set_name(0x8006C1E4, "S_BBuyEnter__Fv", SN_NOWARN)
set_name(0x8006C3CC, "StoryIdItem__Fv", SN_NOWARN)
set_name(0x8006C718, "S_ConfirmEnter__Fv", SN_NOWARN)
set_name(0x8006C834, "S_HealerEnter__Fv", SN_NOWARN)
set_name(0x8006C8CC, "S_HBuyEnter__Fv", SN_NOWARN)
set_name(0x8006CAD8, "S_StoryEnter__Fv", SN_NOWARN)
set_name(0x8006CB70, "S_SIDEnter__Fv", SN_NOWARN)
set_name(0x8006CCEC, "S_TalkEnter__Fv", SN_NOWARN)
set_name(0x8006CEE4, "S_TavernEnter__Fv", SN_NOWARN)
set_name(0x8006CF54, "S_BarmaidEnter__Fv", SN_NOWARN)
set_name(0x8006CFC4, "S_DrunkEnter__Fv", SN_NOWARN)
set_name(0x8006D034, "STextEnter__Fv", SN_NOWARN)
set_name(0x8006D1F8, "CheckStoreBtn__Fv", SN_NOWARN)
set_name(0x8006D2D0, "ReleaseStoreBtn__Fv", SN_NOWARN)
set_name(0x8006D2E4, "_GLOBAL__D_pSTextBoxCels", SN_NOWARN)
set_name(0x8006D30C, "_GLOBAL__I_pSTextBoxCels", SN_NOWARN)
set_name(0x8006D334, "GetDown__C4CPad_addr_8006D334", SN_NOWARN)
set_name(0x8006D35C, "SetRGB__6DialogUcUcUc_addr_8006D35C", SN_NOWARN)
set_name(0x8006D37C, "SetBorder__6Dialogi_addr_8006D37C", SN_NOWARN)
set_name(0x8006D384, "___6Dialog_addr_8006D384", SN_NOWARN)
set_name(0x8006D3AC, "__6Dialog_addr_8006D3AC", SN_NOWARN)
set_name(0x8006D408, "T_DrawView__Fii", SN_NOWARN)
set_name(0x8006D5B8, "T_FillSector__FPUcT0iiiib", SN_NOWARN)
set_name(0x8006D7B0, "T_FillTile__FPUciii", SN_NOWARN)
set_name(0x8006D8A0, "T_Pass3__Fv", SN_NOWARN)
set_name(0x8006DC60, "CreateTown__Fi", SN_NOWARN)
set_name(0x8006DDC8, "GRL_LoadFileInMemSig__FPCcPUl", SN_NOWARN)
set_name(0x8006DEAC, "GRL_StripDir__FPcPCc", SN_NOWARN)
set_name(0x8006DF44, "InitVPTriggers__Fv", SN_NOWARN)
set_name(0x8006DF8C, "ForceTownTrig__Fv", SN_NOWARN)
set_name(0x8006E2A4, "ForceL1Trig__Fv", SN_NOWARN)
set_name(0x8006E554, "ForceL2Trig__Fv", SN_NOWARN)
set_name(0x8006E9B4, "ForceL3Trig__Fv", SN_NOWARN)
set_name(0x8006EE30, "ForceL4Trig__Fv", SN_NOWARN)
set_name(0x8006F33C, "Freeupstairs__Fv", SN_NOWARN)
set_name(0x8006F3FC, "ForceSKingTrig__Fv", SN_NOWARN)
set_name(0x8006F4F0, "ForceSChambTrig__Fv", SN_NOWARN)
set_name(0x8006F5E4, "ForcePWaterTrig__Fv", SN_NOWARN)
set_name(0x8006F6D8, "CheckTrigForce__Fv", SN_NOWARN)
set_name(0x8006F9E0, "FadeGameOut__Fv", SN_NOWARN)
set_name(0x8006FA7C, "IsTrigger__Fii", SN_NOWARN)
set_name(0x8006FAE0, "CheckTriggers__Fi", SN_NOWARN)
set_name(0x8006FFFC, "GetManaAmount__Fii", SN_NOWARN)
set_name(0x800702C4, "UseMana__Fii", SN_NOWARN)
set_name(0x80070408, "CheckSpell__FiicUc", SN_NOWARN)
set_name(0x800704A8, "CastSpell__Fiiiiiiii", SN_NOWARN)
set_name(0x80070754, "DoResurrect__Fii", SN_NOWARN)
set_name(0x80070A08, "DoHealOther__Fii", SN_NOWARN)
set_name(0x80070C6C, "snd_update__FUc", SN_NOWARN)
set_name(0x80070C74, "snd_get_volume__FPCcPl", SN_NOWARN)
set_name(0x80070CDC, "snd_stop_snd__FP4TSnd", SN_NOWARN)
set_name(0x80070CFC, "snd_play_snd__FP4TSFXll", SN_NOWARN)
set_name(0x80070D5C, "snd_play_msnd__FUsll", SN_NOWARN)
set_name(0x80070DEC, "snd_init__FUl", SN_NOWARN)
set_name(0x80070E3C, "music_stop__Fv", SN_NOWARN)
set_name(0x80070E80, "music_fade__Fv", SN_NOWARN)
set_name(0x80070EC0, "music_start__Fi", SN_NOWARN)
set_name(0x80070F44, "music_hold__Fv", SN_NOWARN)
set_name(0x80070FA4, "music_release__Fv", SN_NOWARN)
set_name(0x80070FF4, "snd_playing__Fi", SN_NOWARN)
set_name(0x80071014, "ClrCursor__Fi", SN_NOWARN)
set_name(0x80071064, "flyabout__7GamePad", SN_NOWARN)
set_name(0x80071520, "CloseInvChr__Fv", SN_NOWARN)
set_name(0x80071570, "LeftOf__Fi", SN_NOWARN)
set_name(0x80071588, "RightOf__Fi", SN_NOWARN)
set_name(0x800715A4, "WorldToOffset__Fiii", SN_NOWARN)
set_name(0x80071650, "pad_UpIsUpRight__Fic", SN_NOWARN)
set_name(0x80071714, "__7GamePadi", SN_NOWARN)
set_name(0x80071808, "SetMoveStyle__7GamePadc", SN_NOWARN)
set_name(0x80071810, "SetDownButton__7GamePadiPFi_v", SN_NOWARN)
set_name(0x80071854, "SetComboDownButton__7GamePadiPFi_v", SN_NOWARN)
set_name(0x80071898, "SetAllButtons__7GamePadP11KEY_ASSIGNS", SN_NOWARN)
set_name(0x80071AF8, "GetAllButtons__7GamePadP11KEY_ASSIGNS", SN_NOWARN)
set_name(0x80071CA8, "GetActionButton__7GamePadPFi_v", SN_NOWARN)
set_name(0x80071D04, "SetUpAction__7GamePadPFi_vT1", SN_NOWARN)
set_name(0x80071D40, "RunFunc__7GamePadi", SN_NOWARN)
set_name(0x80071E04, "ButtonDown__7GamePadi", SN_NOWARN)
set_name(0x80072210, "TestButtons__7GamePad", SN_NOWARN)
set_name(0x80072354, "CheckCentre__FP12PlayerStructi", SN_NOWARN)
set_name(0x80072448, "CheckDirs__7GamePadi", SN_NOWARN)
set_name(0x80072560, "CheckSide__7GamePadi", SN_NOWARN)
set_name(0x800725B4, "CheckBodge__7GamePadi", SN_NOWARN)
set_name(0x800729C0, "walk__7GamePadc", SN_NOWARN)
set_name(0x80072CD8, "check_around_player__7GamePad", SN_NOWARN)
set_name(0x800730B8, "show_combos__7GamePad", SN_NOWARN)
set_name(0x80073258, "Handle__7GamePad", SN_NOWARN)
set_name(0x80073930, "GamePadTask__FP4TASK", SN_NOWARN)
set_name(0x800739FC, "PostGamePad__Fiiii", SN_NOWARN)
set_name(0x80073B0C, "Init_GamePad__Fv", SN_NOWARN)
set_name(0x80073B3C, "InitGamePadVars__Fv", SN_NOWARN)
set_name(0x80073BCC, "SetWalkStyle__Fii", SN_NOWARN)
set_name(0x80073C3C, "GetPadStyle__Fi", SN_NOWARN)
set_name(0x80073C60, "_GLOBAL__I_flyflag", SN_NOWARN)
set_name(0x80073C98, "MoveToScrollTarget__7CBlocks_addr_80073C98", SN_NOWARN)
set_name(0x80073CAC, "GetDown__C4CPad_addr_80073CAC", SN_NOWARN)
set_name(0x80073CD4, "GetUp__C4CPad_addr_80073CD4", SN_NOWARN)
set_name(0x80073CFC, "GetCur__C4CPad_addr_80073CFC", SN_NOWARN)
set_name(0x80073D24, "DoGameTestStuff__Fv", SN_NOWARN)
set_name(0x80073D50, "DoInitGameStuff__Fv", SN_NOWARN)
set_name(0x80073D84, "SMemAlloc", SN_NOWARN)
set_name(0x80073DA4, "SMemFree", SN_NOWARN)
set_name(0x80073DC4, "GRL_InitGwin__Fv", SN_NOWARN)
set_name(0x80073DD0, "GRL_SetWindowProc__FPFUlUilUl_Ul", SN_NOWARN)
set_name(0x80073DE0, "GRL_CallWindowProc__FUlUilUl", SN_NOWARN)
set_name(0x80073E08, "GRL_PostMessage__FUlUilUl", SN_NOWARN)
set_name(0x80073EB4, "Msg2Txt__Fi", SN_NOWARN)
set_name(0x80073EFC, "LANG_GetLang__Fv", SN_NOWARN)
set_name(0x80073F08, "LANG_SetDb__F10LANG_DB_NO", SN_NOWARN)
set_name(0x80074074, "GetStr__Fi", SN_NOWARN)
set_name(0x800740DC, "LANG_ReloadMainTXT__Fv", SN_NOWARN)
set_name(0x80074110, "LANG_SetLang__F9LANG_TYPE", SN_NOWARN)
set_name(0x80074274, "DumpCurrentText__Fv", SN_NOWARN)
set_name(0x800742CC, "CalcNumOfStrings__FPPc", SN_NOWARN)
set_name(0x800742D8, "GetLangFileName__F9LANG_TYPEPc", SN_NOWARN)
set_name(0x800743A0, "GetLangFileNameExt__F9LANG_TYPE", SN_NOWARN)
set_name(0x80074420, "TempPrintMissile__FiiiiiiiiccUcUcUcc", SN_NOWARN)
set_name(0x80074858, "FuncTOWN__FP13MissileStructiii", SN_NOWARN)
set_name(0x800749D8, "FuncRPORTAL__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074B38, "FuncFIREBOLT__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074BD0, "FuncHBOLT__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074C80, "FuncLIGHTNING__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074CE4, "FuncGUARDIAN__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074DFC, "FuncFIREWALL__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074E94, "FuncFIREMOVE__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074F2C, "FuncFLAME__FP13MissileStructiii", SN_NOWARN)
set_name(0x80074F94, "FuncARROW__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075034, "FuncFARROW__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075114, "FuncLARROW__FP13MissileStructiii", SN_NOWARN)
set_name(0x800751EC, "FuncMAGMABALL__FP13MissileStructiii", SN_NOWARN)
set_name(0x8007527C, "FuncBONESPIRIT__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075398, "FuncACID__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075434, "FuncACIDSPLAT__FP13MissileStructiii", SN_NOWARN)
set_name(0x8007549C, "FuncACIDPUD__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075504, "FuncFLARE__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075668, "FuncFLAREXP__FP13MissileStructiii", SN_NOWARN)
set_name(0x800757AC, "FuncCBOLT__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075814, "FuncBOOM__FP13MissileStructiii", SN_NOWARN)
set_name(0x8007586C, "FuncELEMENT__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075938, "FuncMISEXP__FP13MissileStructiii", SN_NOWARN)
set_name(0x8007599C, "FuncRHINO__FP13MissileStructiii", SN_NOWARN)
set_name(0x800759A4, "FuncFLASH__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075ECC, "FuncMANASHIELD__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075F74, "FuncFLASH2__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075F7C, "FuncRESURRECTBEAM__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075FB0, "FuncWEAPEXP__FP13MissileStructiii", SN_NOWARN)
set_name(0x80075FD4, "PRIM_GetPrim__FPP8POLY_FT4_addr_80075FD4", SN_NOWARN)
set_name(0x80076050, "GetPlayer__7CPlayeri_addr_80076050", SN_NOWARN)
set_name(0x800760A0, "GetLastOtPos__C7CPlayer_addr_800760A0", SN_NOWARN)
set_name(0x800760AC, "GetLastScrY__C7CPlayer_addr_800760AC", SN_NOWARN)
set_name(0x800760B8, "GetLastScrX__C7CPlayer_addr_800760B8", SN_NOWARN)
set_name(0x800760C4, "GetNumOfFrames__7TextDat_addr_800760C4", SN_NOWARN)
set_name(0x800760D8, "GetFr__7TextDati_addr_800760D8", SN_NOWARN)
set_name(0x800760F4, "ML_Init__Fv", SN_NOWARN)
set_name(0x8007612C, "ML_GetList__Fi", SN_NOWARN)
set_name(0x800761AC, "ML_SetRandomList__Fi", SN_NOWARN)
set_name(0x80076244, "ML_SetList__Fii", SN_NOWARN)
set_name(0x800762F4, "ML_GetPresetMonsters__FiPiUl", SN_NOWARN)
set_name(0x800764B0, "DefaultObjPrint__FP12ObjectStructiiP7TextDatiii", SN_NOWARN)
set_name(0x80076644, "LightObjPrint__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x800766FC, "DoorObjPrint__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076990, "DrawLightSpark__Fiii", SN_NOWARN)
set_name(0x80076A68, "PrintOBJ_L1LIGHT__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076AF0, "PrintOBJ_SKFIRE__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076B1C, "PrintOBJ_LEVER__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076B48, "PrintOBJ_CHEST1__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076B74, "PrintOBJ_CHEST2__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076BA0, "PrintOBJ_CHEST3__FP12ObjectStructiiP7TextDati", SN_NOWARN)
set_name(0x80076BCC, "PrintOBJ_CANDLE1__FP12ObjectStructiiP7TextDati", SN_NOWARN)
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set_name(0x80020AD4, "GAL_MemBase", SN_NOWARN)
set_name(0x80020B28, "GAL_DefragMem", SN_NOWARN)
set_name(0x80020BAC, "GSetError", SN_NOWARN)
set_name(0x80020C08, "GAL_CheckMem", SN_NOWARN)
set_name(0x80020D04, "CheckCollisions", SN_NOWARN)
set_name(0x80020DB0, "AreBlocksColliding", SN_NOWARN)
set_name(0x80020E08, "GAL_GetErrorText", SN_NOWARN)
set_name(0x80020E38, "GAL_GetLastErrorCode", SN_NOWARN)
set_name(0x80020E48, "GAL_GetLastErrorText", SN_NOWARN)
set_name(0x80020E70, "GAL_HowManyEmptyRegions", SN_NOWARN)
set_name(0x80020ED8, "GAL_HowManyUsedRegions", SN_NOWARN)
set_name(0x80020F40, "GAL_SetTimeStamp", SN_NOWARN)
set_name(0x80020F50, "GAL_IncTimeStamp", SN_NOWARN)
set_name(0x80020F70, "GAL_GetTimeStamp", SN_NOWARN)
set_name(0x80020F80, "GAL_AlignSizeToType", SN_NOWARN)
set_name(0x80020FD0, "GAL_AllocMultiStruct", SN_NOWARN)
set_name(0x80021020, "GAL_ProcessMultiStruct", SN_NOWARN)
set_name(0x800210CC, "GAL_GetSize", SN_NOWARN)
set_name(0x80021120, "GazDefragMem", SN_NOWARN)
set_name(0x80021288, "PutBlocksInRegionIntoList", SN_NOWARN)
set_name(0x8002132C, "CollideRegions", SN_NOWARN)
set_name(0x80021360, "DeleteEmptyBlocks", SN_NOWARN)
set_name(0x800213CC, "GetRegion", SN_NOWARN)
set_name(0x800214C4, "FindNextBlock", SN_NOWARN)
set_name(0x80021500, "ShuffleBlocks", SN_NOWARN)
set_name(0x80021590, "PutAllLockedBlocksOntoList", SN_NOWARN)
set_name(0x8002160C, "SortMemHdrListByAddr", SN_NOWARN)
set_name(0x800216C0, "GraftMemHdrList", SN_NOWARN)
set_name(0x8002171C, "GAL_MemDump", SN_NOWARN)
set_name(0x80021790, "GAL_SetVerbosity", SN_NOWARN)
set_name(0x800217A0, "CountFreeBlocks", SN_NOWARN)
set_name(0x800217CC, "SetBlockName", SN_NOWARN)
set_name(0x80021814, "GAL_GetNumFreeHeaders", SN_NOWARN)
set_name(0x80021824, "GAL_GetLastTypeAlloced", SN_NOWARN)
set_name(0x80021834, "GAL_SetAllocFilter", SN_NOWARN)
set_name(0x8002184C, "GAL_SortUsedRegionsBySize", SN_NOWARN)
set_name(0x800218A0, "SortSize", SN_NOWARN)
set_name(0x800218B0, "SortMemHdrList", SN_NOWARN)
set_name(0x80023C6C, "vsprintf", SN_NOWARN)
set_name(0x80023CB8, "_doprnt", SN_NOWARN)
set_name(0x8012CDC8, "NumOfMonsterListLevels", SN_NOWARN)
set_name(0x800A9BE0, "AllLevels", SN_NOWARN)
set_name(0x8012CAAC, "NumsLEV1M1A", SN_NOWARN)
set_name(0x8012CAB0, "NumsLEV1M1B", SN_NOWARN)
set_name(0x8012CAB4, "NumsLEV1M1C", SN_NOWARN)
set_name(0x8012CABC, "NumsLEV2M2A", SN_NOWARN)
set_name(0x8012CAC0, "NumsLEV2M2B", SN_NOWARN)
set_name(0x8012CAC4, "NumsLEV2M2C", SN_NOWARN)
set_name(0x8012CAC8, "NumsLEV2M2D", SN_NOWARN)
set_name(0x8012CACC, "NumsLEV2M2QA", SN_NOWARN)
set_name(0x8012CAD0, "NumsLEV2M2QB", SN_NOWARN)
set_name(0x8012CAD4, "NumsLEV3M3A", SN_NOWARN)
set_name(0x8012CAD8, "NumsLEV3M3QA", SN_NOWARN)
set_name(0x8012CADC, "NumsLEV3M3B", SN_NOWARN)
set_name(0x8012CAE0, "NumsLEV3M3C", SN_NOWARN)
set_name(0x8012CAE4, "NumsLEV4M4A", SN_NOWARN)
set_name(0x8012CAE8, "NumsLEV4M4QA", SN_NOWARN)
set_name(0x8012CAEC, "NumsLEV4M4B", SN_NOWARN)
set_name(0x8012CAF0, "NumsLEV4M4QB", SN_NOWARN)
set_name(0x8012CAF8, "NumsLEV4M4C", SN_NOWARN)
set_name(0x8012CAFC, "NumsLEV4M4QC", SN_NOWARN)
set_name(0x8012CB04, "NumsLEV4M4D", SN_NOWARN)
set_name(0x8012CB08, "NumsLEV5M5A", SN_NOWARN)
set_name(0x8012CB0C, "NumsLEV5M5B", SN_NOWARN)
set_name(0x8012CB10, "NumsLEV5M5C", SN_NOWARN)
set_name(0x8012CB14, "NumsLEV5M5D", SN_NOWARN)
set_name(0x8012CB18, "NumsLEV5M5E", SN_NOWARN)
set_name(0x8012CB1C, "NumsLEV5M5F", SN_NOWARN)
set_name(0x8012CB20, "NumsLEV5M5QA", SN_NOWARN)
set_name(0x8012CB24, "NumsLEV6M6A", SN_NOWARN)
set_name(0x8012CB2C, "NumsLEV6M6B", SN_NOWARN)
set_name(0x8012CB30, "NumsLEV6M6C", SN_NOWARN)
set_name(0x8012CB34, "NumsLEV6M6D", SN_NOWARN)
set_name(0x8012CB38, "NumsLEV6M6E", SN_NOWARN)
set_name(0x8012CB3C, "NumsLEV6M6QA", SN_NOWARN)
set_name(0x8012CB40, "NumsLEV7M7A", SN_NOWARN)
set_name(0x8012CB44, "NumsLEV7M7B", SN_NOWARN)
set_name(0x8012CB48, "NumsLEV7M7C", SN_NOWARN)
set_name(0x8012CB4C, "NumsLEV7M7D", SN_NOWARN)
set_name(0x8012CB50, "NumsLEV7M7E", SN_NOWARN)
set_name(0x8012CB54, "NumsLEV8M8QA", SN_NOWARN)
set_name(0x8012CB58, "NumsLEV8M8A", SN_NOWARN)
set_name(0x8012CB5C, "NumsLEV8M8B", SN_NOWARN)
set_name(0x8012CB60, "NumsLEV8M8C", SN_NOWARN)
set_name(0x8012CB64, "NumsLEV8M8D", SN_NOWARN)
set_name(0x8012CB68, "NumsLEV8M8E", SN_NOWARN)
set_name(0x8012CB6C, "NumsLEV9M9A", SN_NOWARN)
set_name(0x8012CB70, "NumsLEV9M9B", SN_NOWARN)
set_name(0x8012CB74, "NumsLEV9M9C", SN_NOWARN)
set_name(0x8012CB78, "NumsLEV9M9D", SN_NOWARN)
set_name(0x8012CB7C, "NumsLEV10M10A", SN_NOWARN)
set_name(0x8012CB80, "NumsLEV10M10B", SN_NOWARN)
set_name(0x8012CB84, "NumsLEV10M10C", SN_NOWARN)
set_name(0x8012CB88, "NumsLEV10M10D", SN_NOWARN)
set_name(0x8012CB8C, "NumsLEV10M10QA", SN_NOWARN)
set_name(0x8012CB90, "NumsLEV11M11A", SN_NOWARN)
set_name(0x8012CB94, "NumsLEV11M11B", SN_NOWARN)
set_name(0x8012CB98, "NumsLEV11M11C", SN_NOWARN)
set_name(0x8012CB9C, "NumsLEV11M11D", SN_NOWARN)
set_name(0x8012CBA0, "NumsLEV11M11E", SN_NOWARN)
set_name(0x8012CBA4, "NumsLEV12M12A", SN_NOWARN)
set_name(0x8012CBA8, "NumsLEV12M12B", SN_NOWARN)
set_name(0x8012CBAC, "NumsLEV12M12C", SN_NOWARN)
set_name(0x8012CBB0, "NumsLEV12M12D", SN_NOWARN)
set_name(0x8012CBB4, "NumsLEV13M13A", SN_NOWARN)
set_name(0x8012CBB8, "NumsLEV13M13B", SN_NOWARN)
set_name(0x8012CBBC, "NumsLEV13M13QB", SN_NOWARN)
set_name(0x8012CBC0, "NumsLEV13M13C", SN_NOWARN)
set_name(0x8012CBC4, "NumsLEV13M13D", SN_NOWARN)
set_name(0x8012CBC8, "NumsLEV14M14A", SN_NOWARN)
set_name(0x8012CBCC, "NumsLEV14M14B", SN_NOWARN)
set_name(0x8012CBD0, "NumsLEV14M14QB", SN_NOWARN)
set_name(0x8012CBD4, "NumsLEV14M14C", SN_NOWARN)
set_name(0x8012CBD8, "NumsLEV14M14D", SN_NOWARN)
set_name(0x8012CBDC, "NumsLEV14M14E", SN_NOWARN)
set_name(0x8012CBE0, "NumsLEV15M15A", SN_NOWARN)
set_name(0x8012CBE4, "NumsLEV15M15B", SN_NOWARN)
set_name(0x8012CBE8, "NumsLEV15M15C", SN_NOWARN)
set_name(0x8012CBEC, "NumsLEV15M15QA", SN_NOWARN)
set_name(0x8012CBF0, "NumsLEV16M16D", SN_NOWARN)
set_name(0x800A9700, "ChoiceListLEV1", SN_NOWARN)
set_name(0x800A9730, "ChoiceListLEV2", SN_NOWARN)
set_name(0x800A9790, "ChoiceListLEV3", SN_NOWARN)
set_name(0x800A97D0, "ChoiceListLEV4", SN_NOWARN)
set_name(0x800A9840, "ChoiceListLEV5", SN_NOWARN)
set_name(0x800A98B0, "ChoiceListLEV6", SN_NOWARN)
set_name(0x800A9910, "ChoiceListLEV7", SN_NOWARN)
set_name(0x800A9960, "ChoiceListLEV8", SN_NOWARN)
set_name(0x800A99C0, "ChoiceListLEV9", SN_NOWARN)
set_name(0x800A9A00, "ChoiceListLEV10", SN_NOWARN)
set_name(0x800A9A50, "ChoiceListLEV11", SN_NOWARN)
set_name(0x800A9AA0, "ChoiceListLEV12", SN_NOWARN)
set_name(0x800A9AE0, "ChoiceListLEV13", SN_NOWARN)
set_name(0x800A9B30, "ChoiceListLEV14", SN_NOWARN)
set_name(0x800A9B90, "ChoiceListLEV15", SN_NOWARN)
set_name(0x800A9BD0, "ChoiceListLEV16", SN_NOWARN)
set_name(0x8012E688, "GameTaskPtr", SN_NOWARN)
set_name(0x800A9C60, "AllArgs", SN_NOWARN)
set_name(0x8012CDD8, "ArgsSoFar", SN_NOWARN)
set_name(0x8012CDE8, "ThisOt", SN_NOWARN)
set_name(0x8012CDEC, "ThisPrimAddr", SN_NOWARN)
set_name(0x8012E68C, "hndPrimBuffers", SN_NOWARN)
set_name(0x8012E690, "PrimBuffers", SN_NOWARN)
set_name(0x8012E694, "BufferDepth", SN_NOWARN)
set_name(0x8012E695, "WorkRamId", SN_NOWARN)
set_name(0x8012E696, "ScrNum", SN_NOWARN)
set_name(0x8012E698, "Screens", SN_NOWARN)
set_name(0x8012E69C, "PbToClear", SN_NOWARN)
set_name(0x8012E6A0, "BufferNum", SN_NOWARN)
set_name(0x8012CDF0, "AddrToAvoid", SN_NOWARN)
set_name(0x8012E6A1, "LastBuffer", SN_NOWARN)
set_name(0x8012E6A4, "DispEnvToPut", SN_NOWARN)
set_name(0x8012E6A8, "ThisOtSize", SN_NOWARN)
set_name(0x8012CDF4, "ScrRect", SN_NOWARN)
set_name(0x8012E6AC, "VidWait", SN_NOWARN)
set_name(0x8012EB28, "screen", SN_NOWARN)
set_name(0x8012E6B0, "VbFunc", SN_NOWARN)
set_name(0x8012E6B4, "VidTick", SN_NOWARN)
set_name(0x8012E6B8, "VXOff", SN_NOWARN)
set_name(0x8012E6BC, "VYOff", SN_NOWARN)
set_name(0x8012CE08, "Gaz", SN_NOWARN)
set_name(0x8012CE0C, "LastFmem", SN_NOWARN)
set_name(0x8012CDFC, "GSYS_MemStart", SN_NOWARN)
set_name(0x8012CE00, "GSYS_MemEnd", SN_NOWARN)
set_name(0x800A9FA8, "PsxMem", SN_NOWARN)
set_name(0x800A9FD0, "PsxFastMem", SN_NOWARN)
set_name(0x8012CE04, "LowestFmem", SN_NOWARN)
set_name(0x8012CE1C, "FileSYS", SN_NOWARN)
set_name(0x8012E6C0, "FileSystem", SN_NOWARN)
set_name(0x8012E6C4, "OverlayFileSystem", SN_NOWARN)
set_name(0x8012CE36, "DavesPad", SN_NOWARN)
set_name(0x8012CE38, "DavesPadDeb", SN_NOWARN)
set_name(0x800A9FF8, "_6FileIO_FileToLoad", SN_NOWARN)
set_name(0x8012EC08, "MyFT4", SN_NOWARN)
set_name(0x800AA89C, "AllDats", SN_NOWARN)
set_name(0x8012CE88, "TpW", SN_NOWARN)
set_name(0x8012CE8C, "TpH", SN_NOWARN)
set_name(0x8012CE90, "TpXDest", SN_NOWARN)
set_name(0x8012CE94, "TpYDest", SN_NOWARN)
set_name(0x8012CE98, "R", SN_NOWARN)
set_name(0x800AAE5C, "MyGT4", SN_NOWARN)
set_name(0x800AAE90, "MyGT3", SN_NOWARN)
set_name(0x800AA02C, "DatPool", SN_NOWARN)
set_name(0x8012CEAC, "ChunkGot", SN_NOWARN)
set_name(0x800AAEB8, "STREAM_DIR", SN_NOWARN)
set_name(0x800AAEC8, "STREAM_BIN", SN_NOWARN)
set_name(0x800AAED8, "EAC_DirectoryCache", SN_NOWARN)
set_name(0x8012CEC0, "BL_NoLumpFiles", SN_NOWARN)
set_name(0x8012CEC4, "BL_NoStreamFiles", SN_NOWARN)
set_name(0x8012CEC8, "LFileTab", SN_NOWARN)
set_name(0x8012CECC, "SFileTab", SN_NOWARN)
set_name(0x8012CED0, "FileLoaded", SN_NOWARN)
set_name(0x8012CEF4, "NoTAllocs", SN_NOWARN)
set_name(0x800AB004, "MemBlock", SN_NOWARN)
set_name(0x8012E6D0, "CanPause", SN_NOWARN)
set_name(0x8012E6D4, "Paused", SN_NOWARN)
set_name(0x8012E6D8, "InActivePad", SN_NOWARN)
set_name(0x8012EC30, "PBack", SN_NOWARN)
set_name(0x800AB26C, "RawPadData0", SN_NOWARN)
set_name(0x800AB290, "RawPadData1", SN_NOWARN)
set_name(0x800AB2B4, "demo_buffer", SN_NOWARN)
set_name(0x8012CF10, "demo_pad_time", SN_NOWARN)
set_name(0x8012CF14, "demo_pad_count", SN_NOWARN)
set_name(0x800AB194, "Pad0", SN_NOWARN)
set_name(0x800AB200, "Pad1", SN_NOWARN)
set_name(0x8012CF18, "demo_finish", SN_NOWARN)
set_name(0x8012CF1C, "cac_pad", SN_NOWARN)
set_name(0x8012CF3C, "CharFt4", SN_NOWARN)
set_name(0x8012CF40, "CharFrm", SN_NOWARN)
set_name(0x8012CF29, "WHITER", SN_NOWARN)
set_name(0x8012CF2A, "WHITEG", SN_NOWARN)
set_name(0x8012CF2B, "WHITEB", SN_NOWARN)
set_name(0x8012CF2C, "BLUER", SN_NOWARN)
set_name(0x8012CF2D, "BLUEG", SN_NOWARN)
set_name(0x8012CF2E, "BLUEB", SN_NOWARN)
set_name(0x8012CF2F, "REDR", SN_NOWARN)
set_name(0x8012CF30, "REDG", SN_NOWARN)
set_name(0x8012CF31, "REDB", SN_NOWARN)
set_name(0x8012CF32, "GOLDR", SN_NOWARN)
set_name(0x8012CF33, "GOLDG", SN_NOWARN)
set_name(0x8012CF34, "GOLDB", SN_NOWARN)
set_name(0x800AB638, "MediumFont", SN_NOWARN)
set_name(0x800AB854, "LargeFont", SN_NOWARN)
set_name(0x8012CF38, "buttoncol", SN_NOWARN)
set_name(0x800ABA70, "LFontTab", SN_NOWARN)
set_name(0x800ABB24, "LFont", SN_NOWARN)
set_name(0x800ABB34, "MFontTab", SN_NOWARN)
set_name(0x800ABC6C, "MFont", SN_NOWARN)
set_name(0x8012CF55, "DialogRed", SN_NOWARN)
set_name(0x8012CF56, "DialogGreen", SN_NOWARN)
set_name(0x8012CF57, "DialogBlue", SN_NOWARN)
set_name(0x8012CF58, "DialogTRed", SN_NOWARN)
set_name(0x8012CF59, "DialogTGreen", SN_NOWARN)
set_name(0x8012CF5A, "DialogTBlue", SN_NOWARN)
set_name(0x8012CF5C, "DialogTData", SN_NOWARN)
set_name(0x8012CF60, "DialogBackGfx", SN_NOWARN)
set_name(0x8012CF64, "DialogBackW", SN_NOWARN)
set_name(0x8012CF68, "DialogBackH", SN_NOWARN)
set_name(0x8012CF6C, "DialogBorderGfx", SN_NOWARN)
set_name(0x8012CF70, "DialogBorderTLW", SN_NOWARN)
set_name(0x8012CF74, "DialogBorderTLH", SN_NOWARN)
set_name(0x8012CF78, "DialogBorderTRW", SN_NOWARN)
set_name(0x8012CF7C, "DialogBorderTRH", SN_NOWARN)
set_name(0x8012CF80, "DialogBorderBLW", SN_NOWARN)
set_name(0x8012CF84, "DialogBorderBLH", SN_NOWARN)
set_name(0x8012CF88, "DialogBorderBRW", SN_NOWARN)
set_name(0x8012CF8C, "DialogBorderBRH", SN_NOWARN)
set_name(0x8012CF90, "DialogBorderTW", SN_NOWARN)
set_name(0x8012CF94, "DialogBorderTH", SN_NOWARN)
set_name(0x8012CF98, "DialogBorderBW", SN_NOWARN)
set_name(0x8012CF9C, "DialogBorderBH", SN_NOWARN)
set_name(0x8012CFA0, "DialogBorderLW", SN_NOWARN)
set_name(0x8012CFA4, "DialogBorderLH", SN_NOWARN)
set_name(0x8012CFA8, "DialogBorderRW", SN_NOWARN)
set_name(0x8012CFAC, "DialogBorderRH", SN_NOWARN)
set_name(0x8012CFB0, "DialogBevelGfx", SN_NOWARN)
set_name(0x8012CFB4, "DialogBevelCW", SN_NOWARN)
set_name(0x8012CFB8, "DialogBevelCH", SN_NOWARN)
set_name(0x8012CFBC, "DialogBevelLRW", SN_NOWARN)
set_name(0x8012CFC0, "DialogBevelLRH", SN_NOWARN)
set_name(0x8012CFC4, "DialogBevelUDW", SN_NOWARN)
set_name(0x8012CFC8, "DialogBevelUDH", SN_NOWARN)
set_name(0x8012CFCC, "MY_DialogOTpos", SN_NOWARN)
set_name(0x8012E6DC, "DialogGBack", SN_NOWARN)
set_name(0x8012E6DD, "GShadeX", SN_NOWARN)
set_name(0x8012E6DE, "GShadeY", SN_NOWARN)
set_name(0x8012E6E4, "RandBTab", SN_NOWARN)
set_name(0x800ABCBC, "Cxy", SN_NOWARN)
set_name(0x8012CF4F, "BORDERR", SN_NOWARN)
set_name(0x8012CF50, "BORDERG", SN_NOWARN)
set_name(0x8012CF51, "BORDERB", SN_NOWARN)
set_name(0x8012CF52, "BACKR", SN_NOWARN)
set_name(0x8012CF53, "BACKG", SN_NOWARN)
set_name(0x8012CF54, "BACKB", SN_NOWARN)
set_name(0x800ABC7C, "GShadeTab", SN_NOWARN)
set_name(0x8012CF4D, "GShadePX", SN_NOWARN)
set_name(0x8012CF4E, "GShadePY", SN_NOWARN)
set_name(0x8012CFD9, "PlayDemoFlag", SN_NOWARN)
set_name(0x8012EC40, "rgbb", SN_NOWARN)
set_name(0x8012EC70, "rgbt", SN_NOWARN)
set_name(0x8012E6EC, "blockr", SN_NOWARN)
set_name(0x8012E6F0, "blockg", SN_NOWARN)
set_name(0x8012E6F4, "blockb", SN_NOWARN)
set_name(0x8012E6F8, "InfraFlag", SN_NOWARN)
set_name(0x8012E6FC, "blank_bit", SN_NOWARN)
set_name(0x8012CFED, "P1ObjSelCount", SN_NOWARN)
set_name(0x8012CFEE, "P2ObjSelCount", SN_NOWARN)
set_name(0x8012CFEF, "P12ObjSelCount", SN_NOWARN)
set_name(0x8012CFF0, "P1ItemSelCount", SN_NOWARN)
set_name(0x8012CFF1, "P2ItemSelCount", SN_NOWARN)
set_name(0x8012CFF2, "P12ItemSelCount", SN_NOWARN)
set_name(0x8012CFF3, "P1MonstSelCount", SN_NOWARN)
set_name(0x8012CFF4, "P2MonstSelCount", SN_NOWARN)
set_name(0x8012CFF5, "P12MonstSelCount", SN_NOWARN)
set_name(0x8012CFF6, "P1ObjSelCol", SN_NOWARN)
set_name(0x8012CFF8, "P2ObjSelCol", SN_NOWARN)
set_name(0x8012CFFA, "P12ObjSelCol", SN_NOWARN)
set_name(0x8012CFFC, "P1ItemSelCol", SN_NOWARN)
set_name(0x8012CFFE, "P2ItemSelCol", SN_NOWARN)
set_name(0x8012D000, "P12ItemSelCol", SN_NOWARN)
set_name(0x8012D002, "P1MonstSelCol", SN_NOWARN)
set_name(0x8012D004, "P2MonstSelCol", SN_NOWARN)
set_name(0x8012D006, "P12MonstSelCol", SN_NOWARN)
set_name(0x8012D008, "CurrentBlocks", SN_NOWARN)
set_name(0x800ABD2C, "TownConv", SN_NOWARN)
set_name(0x8012D024, "CurrentOverlay", SN_NOWARN)
set_name(0x80122750, "HaltTab", SN_NOWARN)
set_name(0x8012ECA0, "FrontEndOver", SN_NOWARN)
set_name(0x8012ECB0, "PregameOver", SN_NOWARN)
set_name(0x8012ECC0, "GameOver", SN_NOWARN)
set_name(0x8012ECD0, "FmvOver", SN_NOWARN)
set_name(0x8012E700, "OWorldX", SN_NOWARN)
set_name(0x8012E704, "OWorldY", SN_NOWARN)
set_name(0x8012E708, "WWorldX", SN_NOWARN)
set_name(0x8012E70C, "WWorldY", SN_NOWARN)
set_name(0x801227CC, "TxyAdd", SN_NOWARN)
set_name(0x8012D048, "GXAdj2", SN_NOWARN)
set_name(0x8012E710, "TimePerFrame", SN_NOWARN)
set_name(0x8012E714, "CpuStart", SN_NOWARN)
set_name(0x8012E718, "CpuTime", SN_NOWARN)
set_name(0x8012E71C, "DrawTime", SN_NOWARN)
set_name(0x8012E720, "DrawStart", SN_NOWARN)
set_name(0x8012E724, "LastCpuTime", SN_NOWARN)
set_name(0x8012E728, "LastDrawTime", SN_NOWARN)
set_name(0x8012E72C, "DrawArea", SN_NOWARN)
set_name(0x8012D050, "ProfOn", SN_NOWARN)
set_name(0x800ABD44, "LevPals", SN_NOWARN)
set_name(0x80122928, "Level2Bgdata", SN_NOWARN)
set_name(0x800ABD58, "DefP1PanelXY", SN_NOWARN)
set_name(0x800ABDAC, "DefP1PanelXY2", SN_NOWARN)
set_name(0x800ABE00, "DefP2PanelXY", SN_NOWARN)
set_name(0x800ABE54, "DefP2PanelXY2", SN_NOWARN)
set_name(0x800ABEA8, "SpeedBarGfxTable", SN_NOWARN)
set_name(0x8012D078, "hof", SN_NOWARN)
set_name(0x8012D07C, "mof", SN_NOWARN)
set_name(0x800ABF70, "SFXTab", SN_NOWARN)
set_name(0x800AC070, "STR_Buffer", SN_NOWARN)
set_name(0x8012D0B0, "Time", SN_NOWARN)
set_name(0x8012D0B4, "CDWAIT", SN_NOWARN)
set_name(0x800BE070, "voice_attr", SN_NOWARN)
set_name(0x800BE0B0, "STRSave", SN_NOWARN)
set_name(0x8012E730, "SavePause", SN_NOWARN)
set_name(0x8012D089, "NoActiveStreams", SN_NOWARN)
set_name(0x8012D08C, "STRInit", SN_NOWARN)
set_name(0x8012D090, "frame_rate", SN_NOWARN)
set_name(0x8012D094, "CDAngle", SN_NOWARN)
set_name(0x8012D0D8, "SFXNotPlayed", SN_NOWARN)
set_name(0x8012D0D9, "SFXNotInBank", SN_NOWARN)
set_name(0x8012ECE0, "spu_management", SN_NOWARN)
set_name(0x8012EDF0, "rev_attr", SN_NOWARN)
set_name(0x8012E738, "NoSfx", SN_NOWARN)
set_name(0x8012EE10, "CHStatus", SN_NOWARN)
set_name(0x8012D0C4, "BankOffsets", SN_NOWARN)
set_name(0x8012D0C8, "OffsetHandle", SN_NOWARN)
set_name(0x8012D0CC, "BankBase", SN_NOWARN)
set_name(0x8012D0D0, "SPU_Done", SN_NOWARN)
set_name(0x80122CD0, "SFXRemapTab", SN_NOWARN)
set_name(0x8012D0D4, "NoSNDRemaps", SN_NOWARN)
set_name(0x800BE130, "ThePals", SN_NOWARN)
set_name(0x80122D7C, "InitialPositions", SN_NOWARN)
set_name(0x8012D11C, "demo_level", SN_NOWARN)
set_name(0x8012EE40, "buff", SN_NOWARN)
set_name(0x8012D120, "old_val", SN_NOWARN)
set_name(0x8012D124, "DemoTask", SN_NOWARN)
set_name(0x8012D128, "DemoGameTask", SN_NOWARN)
set_name(0x8012D12C, "tonys", SN_NOWARN)
set_name(0x8012D104, "demo_load", SN_NOWARN)
set_name(0x8012D108, "demo_record_load", SN_NOWARN)
set_name(0x8012D10C, "level_record", SN_NOWARN)
set_name(0x8012D110, "demo_fade_finished", SN_NOWARN)
set_name(0x8012D113, "demo_which", SN_NOWARN)
set_name(0x800BE35C, "demolevel", SN_NOWARN)
set_name(0x8012D111, "quest_cheat_num", SN_NOWARN)
set_name(0x8012D112, "cheat_quest_flag", SN_NOWARN)
set_name(0x8012D100, "moo_moo", SN_NOWARN)
set_name(0x800BE31C, "quest_seed", SN_NOWARN)
set_name(0x8012D114, "demo_flash", SN_NOWARN)
set_name(0x8012D118, "tonys_Task", SN_NOWARN)
set_name(0x8012D288, "DoShowPanel", SN_NOWARN)
set_name(0x8012D28C, "DoDrawBg", SN_NOWARN)
set_name(0x8012E73C, "GlueFinished", SN_NOWARN)
set_name(0x8012E740, "DoHomingScroll", SN_NOWARN)
set_name(0x8012E744, "TownerGfx", SN_NOWARN)
set_name(0x8012E748, "CurrentMonsterList", SN_NOWARN)
set_name(0x8012D139, "started_grtask", SN_NOWARN)
set_name(0x800BE370, "PlayerInfo", SN_NOWARN)
set_name(0x8012D290, "ArmourChar", SN_NOWARN)
set_name(0x80122E70, "WepChar", SN_NOWARN)
set_name(0x8012D294, "CharChar", SN_NOWARN)
set_name(0x8012E74C, "ctrl_select_line", SN_NOWARN)
set_name(0x8012E74D, "ctrl_select_side", SN_NOWARN)
set_name(0x8012E74E, "ckeyheld", SN_NOWARN)
set_name(0x8012E754, "CtrlRect", SN_NOWARN)
set_name(0x8012D2A8, "ctrlflag", SN_NOWARN)
set_name(0x800BE7E4, "txt_actions", SN_NOWARN)
set_name(0x800BE73C, "pad_txt", SN_NOWARN)
set_name(0x8012D2A4, "toppos", SN_NOWARN)
set_name(0x8012EE60, "CtrlBack", SN_NOWARN)
set_name(0x800BE914, "controller_defaults", SN_NOWARN)
set_name(0x8012D314, "gr_scrxoff", SN_NOWARN)
set_name(0x8012D318, "gr_scryoff", SN_NOWARN)
set_name(0x8012D320, "water_clut", SN_NOWARN)
set_name(0x8012D323, "visible_level", SN_NOWARN)
set_name(0x8012D311, "last_type", SN_NOWARN)
set_name(0x8012D325, "daylight", SN_NOWARN)
set_name(0x8012D322, "cow_in_sight", SN_NOWARN)
set_name(0x8012D31C, "water_count", SN_NOWARN)
set_name(0x8012D324, "lastrnd", SN_NOWARN)
set_name(0x8012D328, "call_clock", SN_NOWARN)
set_name(0x8012D338, "TitleAnimCount", SN_NOWARN)
set_name(0x8012D33C, "flametick", SN_NOWARN)
set_name(0x800BE9AC, "ypos", SN_NOWARN)
set_name(0x800BE9C4, "frmlist", SN_NOWARN)
set_name(0x800BE9DC, "xoff", SN_NOWARN)
set_name(0x8012D340, "startx", SN_NOWARN)
set_name(0x8012D344, "hellomumflag", SN_NOWARN)
set_name(0x800BEA14, "SpellFXDat", SN_NOWARN)
set_name(0x8012EE70, "PartArray", SN_NOWARN)
set_name(0x8012E75C, "partOtPos", SN_NOWARN)
set_name(0x8012D364, "SetParticle", SN_NOWARN)
set_name(0x8012D368, "p1partexecnum", SN_NOWARN)
set_name(0x8012D36C, "p2partexecnum", SN_NOWARN)
set_name(0x800BE9F4, "JumpArray", SN_NOWARN)
set_name(0x8012D370, "partjumpflag", SN_NOWARN)
set_name(0x8012D374, "partglowflag", SN_NOWARN)
set_name(0x8012D378, "partcolour", SN_NOWARN)
set_name(0x8012D37C, "anyfuckingmenus", SN_NOWARN)
set_name(0x800BEAA4, "SplTarget", SN_NOWARN)
set_name(0x8012D39D, "select_flag", SN_NOWARN)
set_name(0x8012E760, "SelectRect", SN_NOWARN)
set_name(0x8012E768, "item_select", SN_NOWARN)
set_name(0x8012D3A0, "QSpell", SN_NOWARN)
set_name(0x8012D3A4, "_spltotype", SN_NOWARN)
set_name(0x8012D3A8, "force_attack", SN_NOWARN)
set_name(0x8012D390, "gplayer", SN_NOWARN)
set_name(0x8012F0B0, "SelectBack", SN_NOWARN)
set_name(0x8012D394, "mana_order", SN_NOWARN)
set_name(0x8012D398, "health_order", SN_NOWARN)
set_name(0x8012D39C, "birdcheck", SN_NOWARN)
set_name(0x8012F0C0, "DecRequestors", SN_NOWARN)
set_name(0x8012E76C, "progress", SN_NOWARN)
set_name(0x80122FFC, "Level2CutScreen", SN_NOWARN)
set_name(0x8012F0E8, "Scr", SN_NOWARN)
set_name(0x8012D3C8, "CutScreenTSK", SN_NOWARN)
set_name(0x8012D3CC, "GameLoading", SN_NOWARN)
set_name(0x8012F168, "LBack", SN_NOWARN)
set_name(0x800BEAD4, "block_buf", SN_NOWARN)
set_name(0x8012D3E8, "card_ev0", SN_NOWARN)
set_name(0x8012D3EC, "card_ev1", SN_NOWARN)
set_name(0x8012D3F0, "card_ev2", SN_NOWARN)
set_name(0x8012D3F4, "card_ev3", SN_NOWARN)
set_name(0x8012D3F8, "card_ev10", SN_NOWARN)
set_name(0x8012D3FC, "card_ev11", SN_NOWARN)
set_name(0x8012D400, "card_ev12", SN_NOWARN)
set_name(0x8012D404, "card_ev13", SN_NOWARN)
set_name(0x8012D408, "card_dirty", SN_NOWARN)
set_name(0x8012D410, "MemcardTask", SN_NOWARN)
set_name(0x8012E770, "card_event", SN_NOWARN)
set_name(0x8012D3E4, "mem_card_event_handler", SN_NOWARN)
set_name(0x8012D3DC, "MemCardActive", SN_NOWARN)
set_name(0x8012D3E0, "never_hooked_events", SN_NOWARN)
set_name(0x8012D46C, "MasterVol", SN_NOWARN)
set_name(0x8012D470, "MusicVol", SN_NOWARN)
set_name(0x8012D474, "SoundVol", SN_NOWARN)
set_name(0x8012D478, "VideoVol", SN_NOWARN)
set_name(0x8012D47C, "SpeechVol", SN_NOWARN)
set_name(0x8012E774, "Slider", SN_NOWARN)
set_name(0x8012E778, "sw", SN_NOWARN)
set_name(0x8012E77C, "sx", SN_NOWARN)
set_name(0x8012E780, "sy", SN_NOWARN)
set_name(0x8012E784, "Adjust", SN_NOWARN)
set_name(0x8012E785, "qspin", SN_NOWARN)
set_name(0x8012E786, "lqspin", SN_NOWARN)
set_name(0x8012E788, "OrigLang", SN_NOWARN)
set_name(0x8012E78C, "OldLang", SN_NOWARN)
set_name(0x8012E790, "NewLang", SN_NOWARN)
set_name(0x8012D480, "save_blocks", SN_NOWARN)
set_name(0x8012D484, "Savefilename", SN_NOWARN)
set_name(0x8012D488, "ReturnMenu", SN_NOWARN)
set_name(0x8012E794, "ORect", SN_NOWARN)
set_name(0x8012E79C, "McState", SN_NOWARN)
set_name(0x8012D48C, "they_pressed", SN_NOWARN)
set_name(0x8012E7A4, "Seed", SN_NOWARN)
set_name(0x8012D440, "optionsflag", SN_NOWARN)
set_name(0x8012D434, "cmenu", SN_NOWARN)
set_name(0x8012D44C, "options_pad", SN_NOWARN)
set_name(0x8012D43C, "allspellsflag", SN_NOWARN)
set_name(0x800BF5F4, "Circle", SN_NOWARN)
set_name(0x8012D420, "goldcheat", SN_NOWARN)
set_name(0x8012D450, "OptionsSeed", SN_NOWARN)
set_name(0x8012D454, "OptionsSetSeed", SN_NOWARN)
set_name(0x8012D424, "Qfromoptions", SN_NOWARN)
set_name(0x8012D428, "Spacing", SN_NOWARN)
set_name(0x8012D42C, "cs", SN_NOWARN)
set_name(0x8012D430, "lastcs", SN_NOWARN)
set_name(0x8012D438, "MemcardOverlay", SN_NOWARN)
set_name(0x8012D444, "saveflag", SN_NOWARN)
set_name(0x8012D448, "loadflag", SN_NOWARN)
set_name(0x8012D458, "PadFrig", SN_NOWARN)
set_name(0x800BEB54, "MainMenu", SN_NOWARN)
set_name(0x800BEC2C, "GameMenu", SN_NOWARN)
set_name(0x800BED34, "SoundMenu", SN_NOWARN)
set_name(0x800BEDC4, "CentreMenu", SN_NOWARN)
set_name(0x800BEE6C, "LangMenu", SN_NOWARN)
set_name(0x800BEF14, "QuitMenu", SN_NOWARN)
set_name(0x800BEF74, "MemcardMenu", SN_NOWARN)
set_name(0x800BF01C, "MemcardLoadGameMenu", SN_NOWARN)
set_name(0x800BF07C, "MemcardSaveGameMenu", SN_NOWARN)
set_name(0x800BF0DC, "MemcardSaveOptionsMenu", SN_NOWARN)
set_name(0x800BF13C, "MemcardLoadOptionsMenu", SN_NOWARN)
set_name(0x800BF19C, "MemcardCharacterMenu", SN_NOWARN)
set_name(0x800BF1FC, "MemcardSelectCard1", SN_NOWARN)
set_name(0x800BF2A4, "MemcardSelectCard2", SN_NOWARN)
set_name(0x800BF34C, "MemcardFormatMenu", SN_NOWARN)
set_name(0x800BF3AC, "CheatMenu", SN_NOWARN)
set_name(0x800BF49C, "InfoMenu", SN_NOWARN)
set_name(0x800BF4CC, "MonstViewMenu", SN_NOWARN)
set_name(0x800BF514, "SeedMenu", SN_NOWARN)
set_name(0x800BF55C, "MenuList", SN_NOWARN)
set_name(0x8012D45C, "debounce", SN_NOWARN)
set_name(0x8012D460, "KeyPos", SN_NOWARN)
set_name(0x800BF674, "KeyTab", SN_NOWARN)
set_name(0x8012D464, "SeedPos", SN_NOWARN)
set_name(0x800BF688, "BirdList", SN_NOWARN)
set_name(0x8012E7AC, "last_seenx", SN_NOWARN)
set_name(0x8012E7B4, "last_seeny", SN_NOWARN)
set_name(0x8012D499, "hop_height", SN_NOWARN)
set_name(0x8012D49C, "perches", SN_NOWARN)
set_name(0x800BF808, "FmvTab", SN_NOWARN)
set_name(0x8012D4B0, "CurMons", SN_NOWARN)
set_name(0x8012D4B4, "Frame", SN_NOWARN)
set_name(0x8012D4B8, "Action", SN_NOWARN)
set_name(0x8012D4BC, "Dir", SN_NOWARN)
set_name(0x8012D520, "indsize", SN_NOWARN)
set_name(0x8012D500, "kanjbuff", SN_NOWARN)
set_name(0x8012D504, "kindex", SN_NOWARN)
set_name(0x8012D508, "hndKanjBuff", SN_NOWARN)
set_name(0x8012D50C, "hndKanjIndex", SN_NOWARN)
set_name(0x8012E7BC, "HelpRect", SN_NOWARN)
set_name(0x8012E7C4, "HelpTop", SN_NOWARN)
set_name(0x8012F178, "HelpBack", SN_NOWARN)
set_name(0x8012D530, "helpflag", SN_NOWARN)
set_name(0x800BF848, "HelpList", SN_NOWARN)
set_name(0x8012D580, "FeBackX", SN_NOWARN)
set_name(0x8012D584, "FeBackY", SN_NOWARN)
set_name(0x8012D588, "FeBackW", SN_NOWARN)
set_name(0x8012D58C, "FeBackH", SN_NOWARN)
set_name(0x8012D590, "FeFlag", SN_NOWARN)
set_name(0x800BFE50, "FeBuffer", SN_NOWARN)
set_name(0x8012D594, "FePlayerNo", SN_NOWARN)
set_name(0x8012E7C8, "CStruct", SN_NOWARN)
set_name(0x8012D598, "FeBufferCount", SN_NOWARN)
set_name(0x8012D59C, "FeNoOfPlayers", SN_NOWARN)
set_name(0x8012D5A0, "FeChrClass", SN_NOWARN)
set_name(0x800C05D0, "FePlayerName", SN_NOWARN)
set_name(0x8012D5A8, "FeCurMenu", SN_NOWARN)
set_name(0x8012D5AC, "FePlayerNameFlag", SN_NOWARN)
set_name(0x8012D5B0, "FeCount", SN_NOWARN)
set_name(0x8012D5B4, "fileselect", SN_NOWARN)
set_name(0x8012D5B8, "BookMenu", SN_NOWARN)
set_name(0x8012D5BC, "FeAttractMode", SN_NOWARN)
set_name(0x8012D5C0, "FMVPress", SN_NOWARN)
set_name(0x8012D54C, "FeTData", SN_NOWARN)
set_name(0x8012D554, "LoadedChar", SN_NOWARN)
set_name(0x8012D550, "FlameTData", SN_NOWARN)
set_name(0x8012D55C, "FeIsAVirgin", SN_NOWARN)
set_name(0x8012D560, "FeMenuDelay", SN_NOWARN)
set_name(0x800BF950, "DummyMenu", SN_NOWARN)
set_name(0x800BF96C, "FeMainMenu", SN_NOWARN)
set_name(0x800BF988, "FeNewGameMenu", SN_NOWARN)
set_name(0x800BF9A4, "FeNewP1ClassMenu", SN_NOWARN)
set_name(0x800BF9C0, "FeNewP1NameMenu", SN_NOWARN)
set_name(0x800BF9DC, "FeNewP2ClassMenu", SN_NOWARN)
set_name(0x800BF9F8, "FeNewP2NameMenu", SN_NOWARN)
set_name(0x800BFA14, "FeDifficultyMenu", SN_NOWARN)
set_name(0x800BFA30, "FeBackgroundMenu", SN_NOWARN)
set_name(0x800BFA4C, "FeBook1Menu", SN_NOWARN)
set_name(0x800BFA68, "FeBook2Menu", SN_NOWARN)
set_name(0x800BFA84, "FeLoadCharMenu", SN_NOWARN)
set_name(0x800BFAA0, "FeLoadChar1Menu", SN_NOWARN)
set_name(0x800BFABC, "FeLoadChar2Menu", SN_NOWARN)
set_name(0x8012D564, "fadeval", SN_NOWARN)
set_name(0x800BFAD8, "FeMainMenuTable", SN_NOWARN)
set_name(0x800BFB50, "FeNewGameMenuTable", SN_NOWARN)
set_name(0x800BFB98, "FePlayerClassMenuTable", SN_NOWARN)
set_name(0x800BFC10, "FeNameEngMenuTable", SN_NOWARN)
set_name(0x800BFC58, "FeMemcardMenuTable", SN_NOWARN)
set_name(0x800BFCA0, "FeDifficultyMenuTable", SN_NOWARN)
set_name(0x800BFD00, "FeBackgroundMenuTable", SN_NOWARN)
set_name(0x800BFD60, "FeBook1MenuTable", SN_NOWARN)
set_name(0x800BFDD8, "FeBook2MenuTable", SN_NOWARN)
set_name(0x8012D570, "DrawBackOn", SN_NOWARN)
set_name(0x8012D574, "AttractTitleDelay", SN_NOWARN)
set_name(0x8012D578, "AttractMainDelay", SN_NOWARN)
set_name(0x8012D57C, "FMVEndPad", SN_NOWARN)
set_name(0x8012D5F4, "InCredits", SN_NOWARN)
set_name(0x8012D5F8, "CreditTitleNo", SN_NOWARN)
set_name(0x8012D5FC, "CreditSubTitleNo", SN_NOWARN)
set_name(0x8012D610, "card_status", SN_NOWARN)
set_name(0x8012D618, "card_usable", SN_NOWARN)
set_name(0x8012D620, "card_files", SN_NOWARN)
set_name(0x8012D628, "card_changed", SN_NOWARN)
set_name(0x8012D66C, "AlertTxt", SN_NOWARN)
set_name(0x8012D670, "current_card", SN_NOWARN)
set_name(0x8012D674, "LoadType", SN_NOWARN)
set_name(0x8012D678, "McMenuPos", SN_NOWARN)
set_name(0x8012D67C, "McCurMenu", SN_NOWARN)
set_name(0x8012D668, "fileinfoflag", SN_NOWARN)
set_name(0x8012D63C, "DiabloGameFile", SN_NOWARN)
set_name(0x8012D640, "DiabloOptionFile", SN_NOWARN)
set_name(0x8012D660, "McState_addr_8012D660", SN_NOWARN)
set_name(0x8012D758, "mdec_audio_buffer", SN_NOWARN)
set_name(0x8012D760, "mdec_audio_sec", SN_NOWARN)
set_name(0x8012D764, "mdec_audio_offs", SN_NOWARN)
set_name(0x8012D768, "mdec_audio_playing", SN_NOWARN)
set_name(0x8012D76C, "mdec_audio_rate_shift", SN_NOWARN)
set_name(0x8012D770, "vlcbuf", SN_NOWARN)
set_name(0x8012D778, "slice_size", SN_NOWARN)
set_name(0x8012D77C, "slice", SN_NOWARN)
set_name(0x8012D784, "slice_inc", SN_NOWARN)
set_name(0x8012D788, "area_pw", SN_NOWARN)
set_name(0x8012D78C, "area_ph", SN_NOWARN)
set_name(0x8012D790, "tmdc_pol_dirty", SN_NOWARN)
set_name(0x8012D794, "num_pol", SN_NOWARN)
set_name(0x8012D79C, "mdec_cx", SN_NOWARN)
set_name(0x8012D7A0, "mdec_cy", SN_NOWARN)
set_name(0x8012D7A4, "mdec_w", SN_NOWARN)
set_name(0x8012D7A8, "mdec_h", SN_NOWARN)
set_name(0x8012D7AC, "mdec_pw", SN_NOWARN)
set_name(0x8012D7B4, "mdec_ph", SN_NOWARN)
set_name(0x8012D7BC, "move_x", SN_NOWARN)
set_name(0x8012D7C0, "move_y", SN_NOWARN)
set_name(0x8012D7C4, "move_scale", SN_NOWARN)
set_name(0x8012D7C8, "stream_frames", SN_NOWARN)
set_name(0x8012D7CC, "last_stream_frame", SN_NOWARN)
set_name(0x8012D7D0, "mdec_framecount", SN_NOWARN)
set_name(0x8012D7D4, "mdec_speed", SN_NOWARN)
set_name(0x8012D7D8, "mdec_stream_starting", SN_NOWARN)
set_name(0x8012D7DC, "mdec_last_frame", SN_NOWARN)
set_name(0x8012D7E0, "mdec_sectors_per_frame", SN_NOWARN)
set_name(0x8012D7E4, "vlctab", SN_NOWARN)
set_name(0x8012D7E8, "mdc_buftop", SN_NOWARN)
set_name(0x8012D7EC, "mdc_bufstart", SN_NOWARN)
set_name(0x8012D7F0, "mdc_bufleft", SN_NOWARN)
set_name(0x8012D7F4, "mdc_buftotal", SN_NOWARN)
set_name(0x8012D7F8, "ordertab_length", SN_NOWARN)
set_name(0x8012D7FC, "time_in_frames", SN_NOWARN)
set_name(0x8012D800, "stream_chunksize", SN_NOWARN)
set_name(0x8012D804, "stream_bufsize", SN_NOWARN)
set_name(0x8012D808, "stream_subsec", SN_NOWARN)
set_name(0x8012D80C, "stream_secnum", SN_NOWARN)
set_name(0x8012D810, "stream_last_sector", SN_NOWARN)
set_name(0x8012D814, "stream_startsec", SN_NOWARN)
set_name(0x8012D818, "stream_opened", SN_NOWARN)
set_name(0x8012D81C, "stream_last_chunk", SN_NOWARN)
set_name(0x8012D820, "stream_got_chunks", SN_NOWARN)
set_name(0x8012D824, "last_sector", SN_NOWARN)
set_name(0x8012D828, "cdstream_resetsec", SN_NOWARN)
set_name(0x8012D82C, "last_handler_event", SN_NOWARN)
set_name(0x8012D6F4, "user_start", SN_NOWARN)
set_name(0x8012D68C, "vlc_tab", SN_NOWARN)
set_name(0x8012D690, "vlc_buf", SN_NOWARN)
set_name(0x8012D694, "img_buf", SN_NOWARN)
set_name(0x8012D698, "vbuf", SN_NOWARN)
set_name(0x8012D69C, "last_fn", SN_NOWARN)
set_name(0x8012D6A0, "last_mdc", SN_NOWARN)
set_name(0x8012D6A4, "slnum", SN_NOWARN)
set_name(0x8012D6A8, "slices_to_do", SN_NOWARN)
set_name(0x8012D6AC, "mbuf", SN_NOWARN)
set_name(0x8012D6B0, "mfn", SN_NOWARN)
set_name(0x8012D6B4, "last_move_mbuf", SN_NOWARN)
set_name(0x8012D6B8, "move_request", SN_NOWARN)
set_name(0x8012D6BC, "mdec_scale", SN_NOWARN)
set_name(0x8012D6C0, "do_brightness", SN_NOWARN)
set_name(0x8012D6C4, "frame_decoded", SN_NOWARN)
set_name(0x8012D6C8, "mdec_streaming", SN_NOWARN)
set_name(0x8012D6CC, "mdec_stream_size", SN_NOWARN)
set_name(0x8012D6D0, "first_stream_frame", SN_NOWARN)
set_name(0x8012D6D4, "stream_frames_played", SN_NOWARN)
set_name(0x8012D6D8, "num_mdcs", SN_NOWARN)
set_name(0x8012D6DC, "mdec_head", SN_NOWARN)
set_name(0x8012D6E0, "mdec_tail", SN_NOWARN)
set_name(0x8012D6E4, "mdec_waiting_tail", SN_NOWARN)
set_name(0x8012D6E8, "mdecs_queued", SN_NOWARN)
set_name(0x8012D6EC, "mdecs_waiting", SN_NOWARN)
set_name(0x8012D6F0, "sfx_volume", SN_NOWARN)
set_name(0x8012D6F8, "DiabEnd", SN_NOWARN)
set_name(0x8012D6FC, "stream_chunks_in", SN_NOWARN)
set_name(0x8012D700, "stream_chunks_total", SN_NOWARN)
set_name(0x8012D704, "stream_in", SN_NOWARN)
set_name(0x8012D708, "stream_out", SN_NOWARN)
set_name(0x8012D70C, "stream_stalled", SN_NOWARN)
set_name(0x8012D710, "stream_ending", SN_NOWARN)
set_name(0x8012D714, "stream_open", SN_NOWARN)
set_name(0x8012D718, "stream_handler_installed", SN_NOWARN)
set_name(0x8012D71C, "stream_chunks_borrowed", SN_NOWARN)
set_name(0x8012D720, "_get_count", SN_NOWARN)
set_name(0x8012D724, "_discard_count", SN_NOWARN)
set_name(0x8012D728, "CDTask", SN_NOWARN)
set_name(0x8012D72C, "CDStream", SN_NOWARN)
set_name(0x8012D730, "cdready_calls", SN_NOWARN)
set_name(0x8012D734, "cdready_errors", SN_NOWARN)
set_name(0x8012D738, "cdready_out_of_sync", SN_NOWARN)
set_name(0x8012D73C, "cdstream_resetting", SN_NOWARN)
set_name(0x8012D740, "sector_dma", SN_NOWARN)
set_name(0x8012D744, "sector_dma_in", SN_NOWARN)
set_name(0x8012D748, "chkaddr", SN_NOWARN)
set_name(0x8012D74C, "chunk", SN_NOWARN)
set_name(0x8012D750, "first_handler_event", SN_NOWARN)
set_name(0x8012D754, "DOSLEEP", SN_NOWARN)
set_name(0x8012D8AC, "pStatusPanel", SN_NOWARN)
set_name(0x8012D8B0, "pGBoxBuff", SN_NOWARN)
set_name(0x8012D8B4, "dropGoldFlag", SN_NOWARN)
set_name(0x8012D8B8, "_pinfoflag", SN_NOWARN)
set_name(0x800C0AE8, "_infostr", SN_NOWARN)
set_name(0x8012D8BC, "_infoclr", SN_NOWARN)
set_name(0x800C0CE8, "tempstr", SN_NOWARN)
set_name(0x8012D8BE, "drawhpflag", SN_NOWARN)
set_name(0x8012D8BF, "drawmanaflag", SN_NOWARN)
set_name(0x8012D8C0, "chrflag", SN_NOWARN)
set_name(0x8012D8C1, "drawbtnflag", SN_NOWARN)
set_name(0x8012D8C2, "panbtndown", SN_NOWARN)
set_name(0x8012D8C3, "panelflag", SN_NOWARN)
set_name(0x8012D8C4, "chrbtndown", SN_NOWARN)
set_name(0x8012D8C5, "lvlbtndown", SN_NOWARN)
set_name(0x8012D8C6, "sbookflag", SN_NOWARN)
set_name(0x8012D8C7, "talkflag", SN_NOWARN)
set_name(0x8012D8C8, "dropGoldValue", SN_NOWARN)
set_name(0x8012D8CC, "initialDropGoldValue", SN_NOWARN)
set_name(0x8012D8D0, "initialDropGoldIndex", SN_NOWARN)
set_name(0x8012D8D4, "pPanelButtons", SN_NOWARN)
set_name(0x8012D8D8, "pPanelText", SN_NOWARN)
set_name(0x8012D8DC, "pManaBuff", SN_NOWARN)
set_name(0x8012D8E0, "pLifeBuff", SN_NOWARN)
set_name(0x8012D8E4, "pChrPanel", SN_NOWARN)
set_name(0x8012D8E8, "pChrButtons", SN_NOWARN)
set_name(0x8012D8EC, "pSpellCels", SN_NOWARN)
set_name(0x8012F1C8, "_panelstr", SN_NOWARN)
set_name(0x8012F5C8, "_pstrjust", SN_NOWARN)
set_name(0x8012E7D8, "_pnumlines", SN_NOWARN)
set_name(0x8012D8F0, "InfoBoxRect", SN_NOWARN)
set_name(0x8012D8F4, "CSRect", SN_NOWARN)
set_name(0x8012E7E8, "_pSpell", SN_NOWARN)
set_name(0x8012E7F0, "_pSplType", SN_NOWARN)
set_name(0x8012D8FC, "numpanbtns", SN_NOWARN)
set_name(0x8012D900, "pDurIcons", SN_NOWARN)
set_name(0x8012D904, "drawdurflag", SN_NOWARN)
set_name(0x8012E7F8, "chrbtn", SN_NOWARN)
set_name(0x8012D905, "chrbtnactive", SN_NOWARN)
set_name(0x8012D908, "pSpellBkCel", SN_NOWARN)
set_name(0x8012D90C, "pSBkBtnCel", SN_NOWARN)
set_name(0x8012D910, "pSBkIconCels", SN_NOWARN)
set_name(0x8012D914, "sbooktab", SN_NOWARN)
set_name(0x8012D918, "cur_spel", SN_NOWARN)
set_name(0x8012E800, "talkofs", SN_NOWARN)
set_name(0x8012F618, "sgszTalkMsg", SN_NOWARN)
set_name(0x8012E804, "sgbTalkSavePos", SN_NOWARN)
set_name(0x8012E805, "sgbNextTalkSave", SN_NOWARN)
set_name(0x8012E806, "sgbPlrTalkTbl", SN_NOWARN)
set_name(0x8012E808, "pTalkPanel", SN_NOWARN)
set_name(0x8012E80C, "pMultiBtns", SN_NOWARN)
set_name(0x8012E810, "pTalkBtns", SN_NOWARN)
set_name(0x8012E814, "talkbtndown", SN_NOWARN)
set_name(0x800C05FC, "SpellITbl", SN_NOWARN)
set_name(0x8012D839, "DrawLevelUpFlag", SN_NOWARN)
set_name(0x8012D860, "_spselflag", SN_NOWARN)
set_name(0x8012D85C, "spspelstate", SN_NOWARN)
set_name(0x8012D87C, "initchr", SN_NOWARN)
set_name(0x8012D83C, "SPLICONNO", SN_NOWARN)
set_name(0x8012D840, "SPLICONY", SN_NOWARN)
set_name(0x8012E7E0, "SPLICONRIGHT", SN_NOWARN)
set_name(0x8012D844, "scx", SN_NOWARN)
set_name(0x8012D848, "scy", SN_NOWARN)
set_name(0x8012D84C, "scx1", SN_NOWARN)
set_name(0x8012D850, "scy1", SN_NOWARN)
set_name(0x8012D854, "scx2", SN_NOWARN)
set_name(0x8012D858, "scy2", SN_NOWARN)
set_name(0x8012D868, "SpellCol", SN_NOWARN)
set_name(0x800C05E8, "SpellColors", SN_NOWARN)
set_name(0x800C0624, "SpellPages", SN_NOWARN)
set_name(0x8012D86C, "lus", SN_NOWARN)
set_name(0x8012D870, "CsNo", SN_NOWARN)
set_name(0x8012D874, "plusanim", SN_NOWARN)
set_name(0x8012F608, "CSBack", SN_NOWARN)
set_name(0x8012D878, "CS_XOFF", SN_NOWARN)
set_name(0x800C0688, "CS_Tab", SN_NOWARN)
set_name(0x8012D880, "NoCSEntries", SN_NOWARN)
set_name(0x8012D884, "SPALOFF", SN_NOWARN)
set_name(0x8012D888, "paloffset1", SN_NOWARN)
set_name(0x8012D88C, "paloffset2", SN_NOWARN)
set_name(0x8012D890, "paloffset3", SN_NOWARN)
set_name(0x8012D894, "paloffset4", SN_NOWARN)
set_name(0x8012D898, "pinc1", SN_NOWARN)
set_name(0x8012D89C, "pinc2", SN_NOWARN)
set_name(0x8012D8A0, "pinc3", SN_NOWARN)
set_name(0x8012D8A4, "pinc4", SN_NOWARN)
set_name(0x8012D92C, "_pcurs", SN_NOWARN)
set_name(0x8012D934, "cursW", SN_NOWARN)
set_name(0x8012D938, "cursH", SN_NOWARN)
set_name(0x8012D93C, "icursW", SN_NOWARN)
set_name(0x8012D940, "icursH", SN_NOWARN)
set_name(0x8012D944, "icursW28", SN_NOWARN)
set_name(0x8012D948, "icursH28", SN_NOWARN)
set_name(0x8012D94C, "cursmx", SN_NOWARN)
set_name(0x8012D950, "cursmy", SN_NOWARN)
set_name(0x8012D954, "_pcursmonst", SN_NOWARN)
set_name(0x8012D95C, "_pcursobj", SN_NOWARN)
set_name(0x8012D960, "_pcursitem", SN_NOWARN)
set_name(0x8012D964, "_pcursinvitem", SN_NOWARN)
set_name(0x8012D968, "_pcursplr", SN_NOWARN)
set_name(0x8012D928, "sel_data", SN_NOWARN)
set_name(0x800C0DE8, "dead", SN_NOWARN)
set_name(0x8012D96C, "spurtndx", SN_NOWARN)
set_name(0x8012D970, "stonendx", SN_NOWARN)
set_name(0x8012D974, "pSquareCel", SN_NOWARN)
set_name(0x8012D9B4, "ghInst", SN_NOWARN)
set_name(0x8012D9B8, "svgamode", SN_NOWARN)
set_name(0x8012D9BC, "MouseX", SN_NOWARN)
set_name(0x8012D9C0, "MouseY", SN_NOWARN)
set_name(0x8012D9C4, "gv1", SN_NOWARN)
set_name(0x8012D9C8, "gv2", SN_NOWARN)
set_name(0x8012D9CC, "gv3", SN_NOWARN)
set_name(0x8012D9D0, "gv4", SN_NOWARN)
set_name(0x8012D9D4, "gv5", SN_NOWARN)
set_name(0x8012D9D8, "gbProcessPlayers", SN_NOWARN)
set_name(0x800C0F5C, "DebugMonsters", SN_NOWARN)
set_name(0x800C0F84, "glSeedTbl", SN_NOWARN)
set_name(0x800C0FC8, "gnLevelTypeTbl", SN_NOWARN)
set_name(0x8012D9D9, "gbDoEnding", SN_NOWARN)
set_name(0x8012D9DA, "gbRunGame", SN_NOWARN)
set_name(0x8012D9DB, "gbRunGameResult", SN_NOWARN)
set_name(0x8012D9DC, "gbGameLoopStartup", SN_NOWARN)
set_name(0x8012F668, "glEndSeed", SN_NOWARN)
set_name(0x8012F6B8, "glMid1Seed", SN_NOWARN)
set_name(0x8012F708, "glMid2Seed", SN_NOWARN)
set_name(0x8012F758, "glMid3Seed", SN_NOWARN)
set_name(0x8012E818, "sg_previousFilter", SN_NOWARN)
set_name(0x800C100C, "CreateEnv", SN_NOWARN)
set_name(0x8012D9E0, "Passedlvldir", SN_NOWARN)
set_name(0x8012D9E4, "TempStack", SN_NOWARN)
set_name(0x8012D984, "ghMainWnd", SN_NOWARN)
set_name(0x8012D988, "fullscreen", SN_NOWARN)
set_name(0x8012D98C, "force_redraw", SN_NOWARN)
set_name(0x8012D9A0, "PauseMode", SN_NOWARN)
set_name(0x8012D9A1, "FriendlyMode", SN_NOWARN)
set_name(0x8012D991, "visiondebug", SN_NOWARN)
set_name(0x8012D993, "light4flag", SN_NOWARN)
set_name(0x8012D994, "leveldebug", SN_NOWARN)
set_name(0x8012D995, "monstdebug", SN_NOWARN)
set_name(0x8012D99C, "debugmonsttypes", SN_NOWARN)
set_name(0x8012D990, "cineflag", SN_NOWARN)
set_name(0x8012D992, "scrollflag", SN_NOWARN)
set_name(0x8012D996, "trigdebug", SN_NOWARN)
set_name(0x8012D998, "setseed", SN_NOWARN)
set_name(0x8012D9A4, "sgnTimeoutCurs", SN_NOWARN)
set_name(0x8012D9A8, "sgbMouseDown", SN_NOWARN)
set_name(0x800C16D8, "towner", SN_NOWARN)
set_name(0x8012D9FC, "numtowners", SN_NOWARN)
set_name(0x8012DA00, "storeflag", SN_NOWARN)
set_name(0x8012DA01, "boyloadflag", SN_NOWARN)
set_name(0x8012DA02, "bannerflag", SN_NOWARN)
set_name(0x8012DA04, "pCowCels", SN_NOWARN)
set_name(0x8012E81C, "sgdwCowClicks", SN_NOWARN)
set_name(0x8012E820, "sgnCowMsg", SN_NOWARN)
set_name(0x800C1418, "Qtalklist", SN_NOWARN)
set_name(0x8012D9F4, "CowPlaying", SN_NOWARN)
set_name(0x800C103C, "AnimOrder", SN_NOWARN)
set_name(0x800C13B4, "TownCowX", SN_NOWARN)
set_name(0x800C13C0, "TownCowY", SN_NOWARN)
set_name(0x800C13CC, "TownCowDir", SN_NOWARN)
set_name(0x800C13D8, "cowoffx", SN_NOWARN)
set_name(0x800C13F8, "cowoffy", SN_NOWARN)
set_name(0x8012DA1C, "sfxdelay", SN_NOWARN)
set_name(0x8012DA20, "sfxdnum", SN_NOWARN)
set_name(0x8012DA14, "sghStream", SN_NOWARN)
set_name(0x800C24D8, "sgSFX", SN_NOWARN)
set_name(0x8012DA18, "sgpStreamSFX", SN_NOWARN)
set_name(0x8012DA24, "orgseed", SN_NOWARN)
set_name(0x8012E824, "sglGameSeed", SN_NOWARN)
set_name(0x8012DA28, "SeedCount", SN_NOWARN)
set_name(0x8012E828, "sgMemCrit", SN_NOWARN)
set_name(0x8012E82C, "sgnWidth", SN_NOWARN)
set_name(0x8012DA36, "msgflag", SN_NOWARN)
set_name(0x8012DA37, "msgdelay", SN_NOWARN)
set_name(0x800C3500, "msgtable", SN_NOWARN)
set_name(0x800C3450, "MsgStrings", SN_NOWARN)
set_name(0x8012DA35, "msgcnt", SN_NOWARN)
set_name(0x8012E830, "sgdwProgress", SN_NOWARN)
set_name(0x8012E834, "sgdwXY", SN_NOWARN)
set_name(0x800C3550, "AllItemsUseable", SN_NOWARN)
set_name(0x80123788, "AllItemsList", SN_NOWARN)
set_name(0x80124B28, "PL_Prefix", SN_NOWARN)
set_name(0x80125848, "PL_Suffix", SN_NOWARN)
set_name(0x80126748, "UniqueItemList", SN_NOWARN)
set_name(0x800C3764, "item", SN_NOWARN)
set_name(0x800C8364, "itemactive", SN_NOWARN)
set_name(0x800C83E4, "itemavail", SN_NOWARN)
set_name(0x800C8464, "UniqueItemFlag", SN_NOWARN)
set_name(0x8012DA70, "uitemflag", SN_NOWARN)
set_name(0x8012E838, "tem", SN_NOWARN)
set_name(0x8012F7A0, "curruitem", SN_NOWARN)
set_name(0x8012F840, "itemhold", SN_NOWARN)
set_name(0x8012DA74, "ScrollType", SN_NOWARN)
set_name(0x800C84E4, "ItemStr", SN_NOWARN)
set_name(0x800C8524, "SufStr", SN_NOWARN)
set_name(0x8012DA50, "numitems", SN_NOWARN)
set_name(0x8012DA54, "gnNumGetRecords", SN_NOWARN)
set_name(0x800C36C0, "ItemInvSnds", SN_NOWARN)
set_name(0x800C35F0, "ItemCAnimTbl", SN_NOWARN)
set_name(0x80128570, "SinTab", SN_NOWARN)
set_name(0x801285B0, "Item2Frm", SN_NOWARN)
set_name(0x800C369C, "ItemAnimLs", SN_NOWARN)
set_name(0x8012DA58, "ItemAnimSnds", SN_NOWARN)
set_name(0x8012DA5C, "idoppely", SN_NOWARN)
set_name(0x8012DA60, "ScrollFlag", SN_NOWARN)
set_name(0x800C374C, "premiumlvladd", SN_NOWARN)
set_name(0x800C9310, "LightList", SN_NOWARN)
set_name(0x800C9450, "lightactive", SN_NOWARN)
set_name(0x8012DA88, "numlights", SN_NOWARN)
set_name(0x8012DA8C, "lightmax", SN_NOWARN)
set_name(0x800C9478, "VisionList", SN_NOWARN)
set_name(0x8012DA90, "numvision", SN_NOWARN)
set_name(0x8012DA94, "dovision", SN_NOWARN)
set_name(0x8012DA98, "visionid", SN_NOWARN)
set_name(0x8012E83C, "disp_mask", SN_NOWARN)
set_name(0x8012E840, "weird", SN_NOWARN)
set_name(0x8012E844, "disp_tab_r", SN_NOWARN)
set_name(0x8012E848, "dispy_r", SN_NOWARN)
set_name(0x8012E84C, "disp_tab_g", SN_NOWARN)
set_name(0x8012E850, "dispy_g", SN_NOWARN)
set_name(0x8012E854, "disp_tab_b", SN_NOWARN)
set_name(0x8012E858, "dispy_b", SN_NOWARN)
set_name(0x8012E85C, "radius", SN_NOWARN)
set_name(0x8012E860, "bright", SN_NOWARN)
set_name(0x8012F850, "mult_tab", SN_NOWARN)
set_name(0x8012DA78, "lightflag", SN_NOWARN)
set_name(0x800C9024, "vCrawlTable", SN_NOWARN)
set_name(0x800C92D8, "RadiusAdj", SN_NOWARN)
set_name(0x800C8564, "CrawlTable", SN_NOWARN)
set_name(0x8012DA7C, "restore_r", SN_NOWARN)
set_name(0x8012DA80, "restore_g", SN_NOWARN)
set_name(0x8012DA84, "restore_b", SN_NOWARN)
set_name(0x800C92F0, "radius_tab", SN_NOWARN)
set_name(0x800C9300, "bright_tab", SN_NOWARN)
set_name(0x8012DAB9, "qtextflag", SN_NOWARN)
set_name(0x8012DABC, "qtextSpd", SN_NOWARN)
set_name(0x8012E864, "pMedTextCels", SN_NOWARN)
set_name(0x8012E868, "pTextBoxCels", SN_NOWARN)
set_name(0x8012E86C, "qtextptr", SN_NOWARN)
set_name(0x8012E870, "qtexty", SN_NOWARN)
set_name(0x8012E874, "qtextDelay", SN_NOWARN)
set_name(0x8012E878, "sgLastScroll", SN_NOWARN)
set_name(0x8012E87C, "scrolltexty", SN_NOWARN)
set_name(0x8012E880, "sglMusicVolumeSave", SN_NOWARN)
set_name(0x8012DAA8, "qtbodge", SN_NOWARN)
set_name(0x800C9638, "QBack", SN_NOWARN)
set_name(0x800C9648, "missiledata", SN_NOWARN)
set_name(0x800C9DB8, "misfiledata", SN_NOWARN)
set_name(0x800C9CA8, "MissPrintRoutines", SN_NOWARN)
set_name(0x800C9EA4, "sgLevels", SN_NOWARN)
set_name(0x800DDBF0, "sgLocals", SN_NOWARN)
set_name(0x8012F8D0, "sgJunk", SN_NOWARN)
set_name(0x8012E885, "sgbRecvCmd", SN_NOWARN)
set_name(0x8012E888, "sgdwRecvOffset", SN_NOWARN)
set_name(0x8012E88C, "sgbDeltaChunks", SN_NOWARN)
set_name(0x8012E88D, "sgbDeltaChanged", SN_NOWARN)
set_name(0x8012E890, "sgdwOwnerWait", SN_NOWARN)
set_name(0x8012E894, "sgpMegaPkt", SN_NOWARN)
set_name(0x8012E898, "sgpCurrPkt", SN_NOWARN)
set_name(0x8012E89C, "sgnCurrMegaPlayer", SN_NOWARN)
set_name(0x8012DAD5, "deltaload", SN_NOWARN)
set_name(0x8012DAD6, "gbBufferMsgs", SN_NOWARN)
set_name(0x8012DAD8, "dwRecCount", SN_NOWARN)
set_name(0x8012DADC, "LevelOut", SN_NOWARN)
set_name(0x8012DAF2, "gbMaxPlayers", SN_NOWARN)
set_name(0x8012DAF3, "gbActivePlayers", SN_NOWARN)
set_name(0x8012DAF4, "gbGameDestroyed", SN_NOWARN)
set_name(0x8012DAF5, "gbDeltaSender", SN_NOWARN)
set_name(0x8012DAF6, "gbSelectProvider", SN_NOWARN)
set_name(0x8012DAF7, "gbSomebodyWonGameKludge", SN_NOWARN)
set_name(0x8012E8A0, "sgbSentThisCycle", SN_NOWARN)
set_name(0x8012E8A4, "sgdwGameLoops", SN_NOWARN)
set_name(0x8012E8A8, "sgwPackPlrOffsetTbl", SN_NOWARN)
set_name(0x8012E8AC, "sgbPlayerLeftGameTbl", SN_NOWARN)
set_name(0x8012E8B0, "sgdwPlayerLeftReasonTbl", SN_NOWARN)
set_name(0x8012E8B8, "sgbSendDeltaTbl", SN_NOWARN)
set_name(0x8012E8C0, "sgGameInitInfo", SN_NOWARN)
set_name(0x8012E8C8, "sgbTimeout", SN_NOWARN)
set_name(0x8012E8CC, "sglTimeoutStart", SN_NOWARN)
set_name(0x8012DAEC, "gszVersionNumber", SN_NOWARN)
set_name(0x8012DAF1, "sgbNetInited", SN_NOWARN)
set_name(0x800DEC58, "ObjTypeConv", SN_NOWARN)
set_name(0x800DEE1C, "AllObjects", SN_NOWARN)
set_name(0x80128CD8, "ObjMasterLoadList", SN_NOWARN)
set_name(0x800DF5FC, "object", SN_NOWARN)
set_name(0x8012DB18, "numobjects", SN_NOWARN)
set_name(0x800E0BD0, "objectactive", SN_NOWARN)
set_name(0x800E0C50, "objectavail", SN_NOWARN)
set_name(0x8012DB1C, "InitObjFlag", SN_NOWARN)
set_name(0x8012DB20, "trapid", SN_NOWARN)
set_name(0x800E0CD0, "ObjFileList", SN_NOWARN)
set_name(0x8012DB24, "trapdir", SN_NOWARN)
set_name(0x8012DB28, "leverid", SN_NOWARN)
set_name(0x8012DB10, "numobjfiles", SN_NOWARN)
set_name(0x800DF514, "bxadd", SN_NOWARN)
set_name(0x800DF534, "byadd", SN_NOWARN)
set_name(0x800DF5BC, "shrineavail", SN_NOWARN)
set_name(0x800DF554, "shrinestrs", SN_NOWARN)
set_name(0x800DF5D8, "StoryBookName", SN_NOWARN)
set_name(0x8012DB14, "myscale", SN_NOWARN)
set_name(0x8012DB3C, "gbValidSaveFile", SN_NOWARN)
set_name(0x8012DB38, "DoLoadedChar", SN_NOWARN)
set_name(0x800E0EF0, "plr", SN_NOWARN)
set_name(0x8012DB5C, "myplr", SN_NOWARN)
set_name(0x8012DB60, "deathdelay", SN_NOWARN)
set_name(0x8012DB64, "deathflag", SN_NOWARN)
set_name(0x8012DB65, "light_rad", SN_NOWARN)
set_name(0x8012DB54, "light_level", SN_NOWARN)
set_name(0x800E0DE8, "MaxStats", SN_NOWARN)
set_name(0x8012DB4C, "PlrStructSize", SN_NOWARN)
set_name(0x8012DB50, "ItemStructSize", SN_NOWARN)
set_name(0x800E0CF8, "plrxoff", SN_NOWARN)
set_name(0x800E0D1C, "plryoff", SN_NOWARN)
set_name(0x800E0D40, "plrxoff2", SN_NOWARN)
set_name(0x800E0D64, "plryoff2", SN_NOWARN)
set_name(0x800E0D88, "PlrGFXAnimLens", SN_NOWARN)
set_name(0x800E0DAC, "StrengthTbl", SN_NOWARN)
set_name(0x800E0DB8, "MagicTbl", SN_NOWARN)
set_name(0x800E0DC4, "DexterityTbl", SN_NOWARN)
set_name(0x800E0DD0, "VitalityTbl", SN_NOWARN)
set_name(0x800E0DDC, "ToBlkTbl", SN_NOWARN)
set_name(0x800E0E18, "ExpLvlsTbl", SN_NOWARN)
set_name(0x800E5778, "quests", SN_NOWARN)
set_name(0x8012DB94, "pQLogCel", SN_NOWARN)
set_name(0x8012DB98, "ReturnLvlX", SN_NOWARN)
set_name(0x8012DB9C, "ReturnLvlY", SN_NOWARN)
set_name(0x8012DBA0, "ReturnLvl", SN_NOWARN)
set_name(0x8012DBA4, "ReturnLvlT", SN_NOWARN)
set_name(0x8012DBA8, "rporttest", SN_NOWARN)
set_name(0x8012DBAC, "qline", SN_NOWARN)
set_name(0x8012DBB0, "numqlines", SN_NOWARN)
set_name(0x8012DBB4, "qtopline", SN_NOWARN)
set_name(0x8012F8E8, "qlist", SN_NOWARN)
set_name(0x8012E8D0, "QSRect", SN_NOWARN)
set_name(0x8012DB71, "questlog", SN_NOWARN)
set_name(0x800E5640, "questlist", SN_NOWARN)
set_name(0x8012DB74, "ALLQUESTS", SN_NOWARN)
set_name(0x800E5754, "QuestGroup1", SN_NOWARN)
set_name(0x800E5760, "QuestGroup2", SN_NOWARN)
set_name(0x800E576C, "QuestGroup3", SN_NOWARN)
set_name(0x8012DB78, "QuestGroup4", SN_NOWARN)
set_name(0x8012DB90, "WaterDone", SN_NOWARN)
set_name(0x800E5740, "questtrigstr", SN_NOWARN)
set_name(0x8012DB80, "QS_PX", SN_NOWARN)
set_name(0x8012DB84, "QS_PY", SN_NOWARN)
set_name(0x8012DB88, "QS_PW", SN_NOWARN)
set_name(0x8012DB8C, "QS_PH", SN_NOWARN)
set_name(0x8012F928, "QSBack", SN_NOWARN)
set_name(0x800E58B8, "spelldata", SN_NOWARN)
set_name(0x8012DBEF, "stextflag", SN_NOWARN)
set_name(0x800E6160, "smithitem", SN_NOWARN)
set_name(0x800E6D40, "premiumitem", SN_NOWARN)
set_name(0x8012DBF0, "numpremium", SN_NOWARN)
set_name(0x8012DBF4, "premiumlevel", SN_NOWARN)
set_name(0x800E70D0, "witchitem", SN_NOWARN)
set_name(0x800E7CB0, "boyitem", SN_NOWARN)
set_name(0x8012DBF8, "boylevel", SN_NOWARN)
set_name(0x800E7D48, "golditem", SN_NOWARN)
set_name(0x800E7DE0, "healitem", SN_NOWARN)
set_name(0x8012DBFC, "stextsize", SN_NOWARN)
set_name(0x8012DBFD, "stextscrl", SN_NOWARN)
set_name(0x8012E8D8, "stextsel", SN_NOWARN)
set_name(0x8012E8DC, "stextlhold", SN_NOWARN)
set_name(0x8012E8E0, "stextshold", SN_NOWARN)
set_name(0x8012E8E4, "stextvhold", SN_NOWARN)
set_name(0x8012E8E8, "stextsval", SN_NOWARN)
set_name(0x8012E8EC, "stextsmax", SN_NOWARN)
set_name(0x8012E8F0, "stextup", SN_NOWARN)
set_name(0x8012E8F4, "stextdown", SN_NOWARN)
set_name(0x8012E8F8, "stextscrlubtn", SN_NOWARN)
set_name(0x8012E8F9, "stextscrldbtn", SN_NOWARN)
set_name(0x8012E8FA, "SItemListFlag", SN_NOWARN)
set_name(0x8012F938, "stext", SN_NOWARN)
set_name(0x800E89C0, "storehold", SN_NOWARN)
set_name(0x800EA640, "storehidx", SN_NOWARN)
set_name(0x8012E8FC, "storenumh", SN_NOWARN)
set_name(0x8012E900, "gossipstart", SN_NOWARN)
set_name(0x8012E904, "gossipend", SN_NOWARN)
set_name(0x8012E908, "StoreBackRect", SN_NOWARN)
set_name(0x8012E910, "talker", SN_NOWARN)
set_name(0x8012DBDC, "pSTextBoxCels", SN_NOWARN)
set_name(0x8012DBE0, "pSTextSlidCels", SN_NOWARN)
set_name(0x8012DBE4, "SStringY", SN_NOWARN)
set_name(0x800E603C, "SBack", SN_NOWARN)
set_name(0x800E604C, "SStringYNorm", SN_NOWARN)
set_name(0x800E609C, "SStringYBuy0", SN_NOWARN)
set_name(0x800E60EC, "SStringYBuy1", SN_NOWARN)
set_name(0x800E613C, "talkname", SN_NOWARN)
set_name(0x8012DBEE, "InStoreFlag", SN_NOWARN)
set_name(0x8012A024, "alltext", SN_NOWARN)
set_name(0x8012DC0C, "gdwAllTextEntries", SN_NOWARN)
set_name(0x8012E914, "P3Tiles", SN_NOWARN)
set_name(0x8012DC1C, "tile", SN_NOWARN)
set_name(0x8012DC2C, "_trigflag", SN_NOWARN)
set_name(0x800EA8A8, "trigs", SN_NOWARN)
set_name(0x8012DC30, "numtrigs", SN_NOWARN)
set_name(0x8012DC34, "townwarps", SN_NOWARN)
set_name(0x8012DC38, "TWarpFrom", SN_NOWARN)
set_name(0x800EA670, "TownDownList", SN_NOWARN)
set_name(0x800EA69C, "TownWarp1List", SN_NOWARN)
set_name(0x800EA6D0, "L1UpList", SN_NOWARN)
set_name(0x800EA700, "L1DownList", SN_NOWARN)
set_name(0x800EA728, "L2UpList", SN_NOWARN)
set_name(0x800EA734, "L2DownList", SN_NOWARN)
set_name(0x800EA748, "L2TWarpUpList", SN_NOWARN)
set_name(0x800EA754, "L3UpList", SN_NOWARN)
set_name(0x800EA790, "L3DownList", SN_NOWARN)
set_name(0x800EA7B4, "L3TWarpUpList", SN_NOWARN)
set_name(0x800EA7EC, "L4UpList", SN_NOWARN)
set_name(0x800EA7FC, "L4DownList", SN_NOWARN)
set_name(0x800EA814, "L4TWarpUpList", SN_NOWARN)
set_name(0x800EA824, "L4PentaList", SN_NOWARN)
set_name(0x8012DC51, "gbSndInited", SN_NOWARN)
set_name(0x8012DC54, "sglMasterVolume", SN_NOWARN)
set_name(0x8012DC58, "sglMusicVolume", SN_NOWARN)
set_name(0x8012DC5C, "sglSoundVolume", SN_NOWARN)
set_name(0x8012DC60, "sglSpeechVolume", SN_NOWARN)
set_name(0x8012DC64, "sgnMusicTrack", SN_NOWARN)
set_name(0x8012DC52, "gbDupSounds", SN_NOWARN)
set_name(0x8012DC68, "sghMusic", SN_NOWARN)
set_name(0x8012AE58, "sgszMusicTracks", SN_NOWARN)
set_name(0x8012DC80, "_pcurr_inv", SN_NOWARN)
set_name(0x800EA8F8, "_pfind_list", SN_NOWARN)
set_name(0x8012DC88, "_pfind_index", SN_NOWARN)
set_name(0x8012DC8C, "_pfindx", SN_NOWARN)
set_name(0x8012DC90, "_pfindy", SN_NOWARN)
set_name(0x8012DC92, "automapmoved", SN_NOWARN)
set_name(0x8012DC75, "flyflag", SN_NOWARN)
set_name(0x8012DC76, "seen_combo", SN_NOWARN)
set_name(0x80130658, "GPad1", SN_NOWARN)
set_name(0x801306F8, "GPad2", SN_NOWARN)
set_name(0x8012E918, "CurrentProc", SN_NOWARN)
set_name(0x8012AFEC, "AllMsgs", SN_NOWARN)
set_name(0x8012DCCC, "NumOfStrings", SN_NOWARN)
set_name(0x8012DCA0, "LanguageType", SN_NOWARN)
set_name(0x8012DCA4, "hndText", SN_NOWARN)
set_name(0x8012DCA8, "TextPtr", SN_NOWARN)
set_name(0x8012DCAC, "LangDbNo", SN_NOWARN)
set_name(0x8012DCDC, "MissDat", SN_NOWARN)
set_name(0x8012DCE0, "CharFade", SN_NOWARN)
set_name(0x8012DCE4, "rotateness", SN_NOWARN)
set_name(0x8012DCE8, "spiralling_shape", SN_NOWARN)
set_name(0x8012DCEC, "down", SN_NOWARN)
set_name(0x800EA948, "MlTab", SN_NOWARN)
set_name(0x800EA958, "QlTab", SN_NOWARN)
set_name(0x800EA968, "ObjPrintFuncs", SN_NOWARN)
set_name(0x8012DD08, "MyXoff1", SN_NOWARN)
set_name(0x8012DD0C, "MyYoff1", SN_NOWARN)
set_name(0x8012DD10, "MyXoff2", SN_NOWARN)
set_name(0x8012DD14, "MyYoff2", SN_NOWARN)
set_name(0x8012DD24, "iscflag", SN_NOWARN)
set_name(0x8012DD31, "sgbFadedIn", SN_NOWARN)
set_name(0x8012DD32, "screenbright", SN_NOWARN)
set_name(0x8012DD34, "faderate", SN_NOWARN)
set_name(0x8012DD38, "fading", SN_NOWARN)
set_name(0x8012DD44, "FadeCoords", SN_NOWARN)
set_name(0x8012DD3C, "st", SN_NOWARN)
set_name(0x8012DD40, "mode", SN_NOWARN)
set_name(0x800EAAF0, "portal", SN_NOWARN)
set_name(0x8012DD76, "portalindex", SN_NOWARN)
set_name(0x8012DD70, "WarpDropX", SN_NOWARN)
set_name(0x8012DD74, "WarpDropY", SN_NOWARN)
set_name(0x800EAB08, "MyVerString", SN_NOWARN)
set_name(0x8012DED4, "Year", SN_NOWARN)
set_name(0x8012DED8, "Day", SN_NOWARN)
set_name(0x8012E91C, "tbuff", SN_NOWARN)
set_name(0x800EAB80, "IconBuffer", SN_NOWARN)
set_name(0x8012E920, "HR1", SN_NOWARN)
set_name(0x8012E921, "HR2", SN_NOWARN)
set_name(0x8012E922, "HR3", SN_NOWARN)
set_name(0x8012E923, "VR1", SN_NOWARN)
set_name(0x8012E924, "VR2", SN_NOWARN)
set_name(0x8012E925, "VR3", SN_NOWARN)
set_name(0x8012DF48, "pHallList", SN_NOWARN)
set_name(0x8012DF4C, "nRoomCnt", SN_NOWARN)
set_name(0x8012DF50, "nSx1", SN_NOWARN)
set_name(0x8012DF54, "nSy1", SN_NOWARN)
set_name(0x8012DF58, "nSx2", SN_NOWARN)
set_name(0x8012DF5C, "nSy2", SN_NOWARN)
set_name(0x8012DF00, "Area_Min", SN_NOWARN)
set_name(0x8012DF04, "Room_Max", SN_NOWARN)
set_name(0x8012DF08, "Room_Min", SN_NOWARN)
set_name(0x8012DF0C, "BIG3", SN_NOWARN)
set_name(0x8012DF14, "BIG4", SN_NOWARN)
set_name(0x8012DF1C, "BIG6", SN_NOWARN)
set_name(0x8012DF24, "BIG7", SN_NOWARN)
set_name(0x8012DF2C, "RUINS1", SN_NOWARN)
set_name(0x8012DF30, "RUINS2", SN_NOWARN)
set_name(0x8012DF34, "RUINS3", SN_NOWARN)
set_name(0x8012DF38, "RUINS4", SN_NOWARN)
set_name(0x8012DF3C, "RUINS5", SN_NOWARN)
set_name(0x8012DF40, "RUINS6", SN_NOWARN)
set_name(0x8012DF44, "RUINS7", SN_NOWARN)
set_name(0x8012E928, "abyssx", SN_NOWARN)
set_name(0x8012E92C, "lavapool", SN_NOWARN)
set_name(0x8012DFE8, "lockoutcnt", SN_NOWARN)
set_name(0x8012DF6C, "L3TITE12", SN_NOWARN)
set_name(0x8012DF74, "L3TITE13", SN_NOWARN)
set_name(0x8012DF7C, "L3CREV1", SN_NOWARN)
set_name(0x8012DF84, "L3CREV2", SN_NOWARN)
set_name(0x8012DF8C, "L3CREV3", SN_NOWARN)
set_name(0x8012DF94, "L3CREV4", SN_NOWARN)
set_name(0x8012DF9C, "L3CREV5", SN_NOWARN)
set_name(0x8012DFA4, "L3CREV6", SN_NOWARN)
set_name(0x8012DFAC, "L3CREV7", SN_NOWARN)
set_name(0x8012DFB4, "L3CREV8", SN_NOWARN)
set_name(0x8012DFBC, "L3CREV9", SN_NOWARN)
set_name(0x8012DFC4, "L3CREV10", SN_NOWARN)
set_name(0x8012DFCC, "L3CREV11", SN_NOWARN)
set_name(0x8012DFD4, "L3XTRA1", SN_NOWARN)
set_name(0x8012DFD8, "L3XTRA2", SN_NOWARN)
set_name(0x8012DFDC, "L3XTRA3", SN_NOWARN)
set_name(0x8012DFE0, "L3XTRA4", SN_NOWARN)
set_name(0x8012DFE4, "L3XTRA5", SN_NOWARN)
set_name(0x8012DFEC, "diabquad1x", SN_NOWARN)
set_name(0x8012DFF0, "diabquad2x", SN_NOWARN)
set_name(0x8012DFF4, "diabquad3x", SN_NOWARN)
set_name(0x8012DFF8, "diabquad4x", SN_NOWARN)
set_name(0x8012DFFC, "diabquad1y", SN_NOWARN)
set_name(0x8012E000, "diabquad2y", SN_NOWARN)
set_name(0x8012E004, "diabquad3y", SN_NOWARN)
set_name(0x8012E008, "diabquad4y", SN_NOWARN)
set_name(0x8012E00C, "SP4x1", SN_NOWARN)
set_name(0x8012E010, "SP4y1", SN_NOWARN)
set_name(0x8012E014, "SP4x2", SN_NOWARN)
set_name(0x8012E018, "SP4y2", SN_NOWARN)
set_name(0x8012E01C, "l4holdx", SN_NOWARN)
set_name(0x8012E020, "l4holdy", SN_NOWARN)
set_name(0x8012E930, "lpSetPiece1", SN_NOWARN)
set_name(0x8012E934, "lpSetPiece2", SN_NOWARN)
set_name(0x8012E938, "lpSetPiece3", SN_NOWARN)
set_name(0x8012E93C, "lpSetPiece4", SN_NOWARN)
set_name(0x8012E940, "lppSetPiece2", SN_NOWARN)
set_name(0x8012E944, "lppSetPiece3", SN_NOWARN)
set_name(0x8012E948, "lppSetPiece4", SN_NOWARN)
set_name(0x8012E030, "SkelKingTrans1", SN_NOWARN)
set_name(0x8012E038, "SkelKingTrans2", SN_NOWARN)
set_name(0x800EAE80, "SkelKingTrans3", SN_NOWARN)
set_name(0x800EAE94, "SkelKingTrans4", SN_NOWARN)
set_name(0x800EAEB0, "SkelChamTrans1", SN_NOWARN)
set_name(0x8012E040, "SkelChamTrans2", SN_NOWARN)
set_name(0x800EAEC4, "SkelChamTrans3", SN_NOWARN)
set_name(0x8012E134, "DoUiForChooseMonster", SN_NOWARN)
set_name(0x800EAEE8, "MgToText", SN_NOWARN)
set_name(0x800EAF70, "StoryText", SN_NOWARN)
set_name(0x800EAF94, "dungeon", SN_NOWARN)
set_name(0x800EC194, "pdungeon", SN_NOWARN)
set_name(0x800EC7D4, "dflags", SN_NOWARN)
set_name(0x8012E158, "setpc_x", SN_NOWARN)
set_name(0x8012E15C, "setpc_y", SN_NOWARN)
set_name(0x8012E160, "setpc_w", SN_NOWARN)
set_name(0x8012E164, "setpc_h", SN_NOWARN)
set_name(0x8012E168, "setloadflag", SN_NOWARN)
set_name(0x8012E16C, "pMegaTiles", SN_NOWARN)
set_name(0x800ECE14, "nBlockTable", SN_NOWARN)
set_name(0x800ED618, "nSolidTable", SN_NOWARN)
set_name(0x800EDE1C, "nTransTable", SN_NOWARN)
set_name(0x800EE620, "nMissileTable", SN_NOWARN)
set_name(0x800EEE24, "nTrapTable", SN_NOWARN)
set_name(0x8012E170, "dminx", SN_NOWARN)
set_name(0x8012E174, "dminy", SN_NOWARN)
set_name(0x8012E178, "dmaxx", SN_NOWARN)
set_name(0x8012E17C, "dmaxy", SN_NOWARN)
set_name(0x8012E180, "gnDifficulty", SN_NOWARN)
set_name(0x8012E184, "currlevel", SN_NOWARN)
set_name(0x8012E185, "leveltype", SN_NOWARN)
set_name(0x8012E186, "setlevel", SN_NOWARN)
set_name(0x8012E187, "setlvlnum", SN_NOWARN)
set_name(0x8012E188, "setlvltype", SN_NOWARN)
set_name(0x8012E18C, "ViewX", SN_NOWARN)
set_name(0x8012E190, "ViewY", SN_NOWARN)
set_name(0x8012E194, "ViewDX", SN_NOWARN)
set_name(0x8012E198, "ViewDY", SN_NOWARN)
set_name(0x8012E19C, "ViewBX", SN_NOWARN)
set_name(0x8012E1A0, "ViewBY", SN_NOWARN)
set_name(0x800EF628, "ScrollInfo", SN_NOWARN)
set_name(0x8012E1A4, "LvlViewX", SN_NOWARN)
set_name(0x8012E1A8, "LvlViewY", SN_NOWARN)
set_name(0x8012E1AC, "btmbx", SN_NOWARN)
set_name(0x8012E1B0, "btmby", SN_NOWARN)
set_name(0x8012E1B4, "btmdx", SN_NOWARN)
set_name(0x8012E1B8, "btmdy", SN_NOWARN)
set_name(0x8012E1BC, "MicroTileLen", SN_NOWARN)
set_name(0x8012E1C0, "TransVal", SN_NOWARN)
set_name(0x800EF63C, "TransList", SN_NOWARN)
set_name(0x8012E1C4, "themeCount", SN_NOWARN)
set_name(0x800EF65C, "dung_map", SN_NOWARN)
set_name(0x8011191C, "dung_map_r", SN_NOWARN)
set_name(0x80112480, "dung_map_g", SN_NOWARN)
set_name(0x80112FE4, "dung_map_b", SN_NOWARN)
set_name(0x80113B48, "MinisetXY", SN_NOWARN)
set_name(0x8012E150, "pSetPiece", SN_NOWARN)
set_name(0x8012E154, "DungSize", SN_NOWARN)
set_name(0x80113D14, "theme", SN_NOWARN)
set_name(0x8012E204, "numthemes", SN_NOWARN)
set_name(0x8012E208, "zharlib", SN_NOWARN)
set_name(0x8012E20C, "armorFlag", SN_NOWARN)
set_name(0x8012E20D, "bCrossFlag", SN_NOWARN)
set_name(0x8012E20E, "weaponFlag", SN_NOWARN)
set_name(0x8012E210, "themex", SN_NOWARN)
set_name(0x8012E214, "themey", SN_NOWARN)
set_name(0x8012E218, "themeVar1", SN_NOWARN)
set_name(0x8012E21C, "bFountainFlag", SN_NOWARN)
set_name(0x8012E21D, "cauldronFlag", SN_NOWARN)
set_name(0x8012E21E, "mFountainFlag", SN_NOWARN)
set_name(0x8012E21F, "pFountainFlag", SN_NOWARN)
set_name(0x8012E220, "tFountainFlag", SN_NOWARN)
set_name(0x8012E221, "treasureFlag", SN_NOWARN)
set_name(0x8012E224, "ThemeGoodIn", SN_NOWARN)
set_name(0x80113BF4, "ThemeGood", SN_NOWARN)
set_name(0x80113C04, "trm5x", SN_NOWARN)
set_name(0x80113C68, "trm5y", SN_NOWARN)
set_name(0x80113CCC, "trm3x", SN_NOWARN)
set_name(0x80113CF0, "trm3y", SN_NOWARN)
set_name(0x8012E2FC, "nummissiles", SN_NOWARN)
set_name(0x80113F2C, "missileactive", SN_NOWARN)
set_name(0x80114120, "missileavail", SN_NOWARN)
set_name(0x8012E300, "MissilePreFlag", SN_NOWARN)
set_name(0x80114314, "missile", SN_NOWARN)
set_name(0x8012E301, "ManashieldFlag", SN_NOWARN)
set_name(0x8012E302, "ManashieldFlag2", SN_NOWARN)
set_name(0x80113EA4, "XDirAdd", SN_NOWARN)
set_name(0x80113EC4, "YDirAdd", SN_NOWARN)
set_name(0x8012E2C9, "fadetor", SN_NOWARN)
set_name(0x8012E2CA, "fadetog", SN_NOWARN)
set_name(0x8012E2CB, "fadetob", SN_NOWARN)
set_name(0x80113EE4, "ValueTable", SN_NOWARN)
set_name(0x80113EF4, "StringTable", SN_NOWARN)
set_name(0x80116BC4, "monster", SN_NOWARN)
set_name(0x8012E364, "nummonsters", SN_NOWARN)
set_name(0x8011C344, "monstactive", SN_NOWARN)
set_name(0x8011C4D4, "monstkills", SN_NOWARN)
set_name(0x8011C664, "Monsters", SN_NOWARN)
set_name(0x8012E368, "monstimgtot", SN_NOWARN)
set_name(0x8012E36C, "totalmonsters", SN_NOWARN)
set_name(0x8012E370, "uniquetrans", SN_NOWARN)
set_name(0x8012E94C, "sgbSaveSoundOn", SN_NOWARN)
set_name(0x8012E334, "offset_x", SN_NOWARN)
set_name(0x8012E33C, "offset_y", SN_NOWARN)
set_name(0x8012E31C, "left", SN_NOWARN)
set_name(0x8012E324, "right", SN_NOWARN)
set_name(0x8012E32C, "opposite", SN_NOWARN)
set_name(0x8012E310, "nummtypes", SN_NOWARN)
set_name(0x8012E314, "animletter", SN_NOWARN)
set_name(0x80116A24, "MWVel", SN_NOWARN)
set_name(0x8012E344, "rnd5", SN_NOWARN)
set_name(0x8012E348, "rnd10", SN_NOWARN)
set_name(0x8012E34C, "rnd20", SN_NOWARN)
set_name(0x8012E350, "rnd60", SN_NOWARN)
set_name(0x80116B44, "AiProc", SN_NOWARN)
set_name(0x8011CB3C, "monsterdata", SN_NOWARN)
set_name(0x8011E57C, "MonstConvTbl", SN_NOWARN)
set_name(0x8011E5FC, "MonstAvailTbl", SN_NOWARN)
set_name(0x8011E66C, "UniqMonst", SN_NOWARN)
set_name(0x8011C924, "TransPals", SN_NOWARN)
set_name(0x8011C824, "StonePals", SN_NOWARN)
set_name(0x8012E3A8, "invflag", SN_NOWARN)
set_name(0x8012E3A9, "drawsbarflag", SN_NOWARN)
set_name(0x8012E3AC, "InvBackY", SN_NOWARN)
set_name(0x8012E3B0, "InvCursPos", SN_NOWARN)
set_name(0x8011F614, "InvSlotTable", SN_NOWARN)
set_name(0x8012E3B4, "InvBackAY", SN_NOWARN)
set_name(0x8012E3B8, "InvSel", SN_NOWARN)
set_name(0x8012E3BC, "ItemW", SN_NOWARN)
set_name(0x8012E3C0, "ItemH", SN_NOWARN)
set_name(0x8012E3C4, "ItemNo", SN_NOWARN)
set_name(0x8012E3C8, "BRect", SN_NOWARN)
set_name(0x8012E390, "InvPanelTData", SN_NOWARN)
set_name(0x8012E394, "InvGfxTData", SN_NOWARN)
set_name(0x8012E38C, "InvPageNo", SN_NOWARN)
set_name(0x8011EF9C, "AP2x2Tbl", SN_NOWARN)
set_name(0x8011EFC4, "InvRect", SN_NOWARN)
set_name(0x8011F20C, "InvGfxTable", SN_NOWARN)
set_name(0x8011F4AC, "InvItemWidth", SN_NOWARN)
set_name(0x8011F560, "InvItemHeight", SN_NOWARN)
set_name(0x8012E3A0, "InvOn", SN_NOWARN)
set_name(0x8012E3A4, "sgdwLastTime", SN_NOWARN)
set_name(0x8012E3FF, "automapflag", SN_NOWARN)
set_name(0x8011F678, "automapview", SN_NOWARN)
set_name(0x8011F740, "automaptype", SN_NOWARN)
set_name(0x8012E400, "AMLWallFlag", SN_NOWARN)
set_name(0x8012E401, "AMRWallFlag", SN_NOWARN)
set_name(0x8012E402, "AMLLWallFlag", SN_NOWARN)
set_name(0x8012E403, "AMLRWallFlag", SN_NOWARN)
set_name(0x8012E404, "AMDirtFlag", SN_NOWARN)
set_name(0x8012E405, "AMColumnFlag", SN_NOWARN)
set_name(0x8012E406, "AMStairFlag", SN_NOWARN)
set_name(0x8012E407, "AMLDoorFlag", SN_NOWARN)
set_name(0x8012E408, "AMLGrateFlag", SN_NOWARN)
set_name(0x8012E409, "AMLArchFlag", SN_NOWARN)
set_name(0x8012E40A, "AMRDoorFlag", SN_NOWARN)
set_name(0x8012E40B, "AMRGrateFlag", SN_NOWARN)
set_name(0x8012E40C, "AMRArchFlag", SN_NOWARN)
set_name(0x8012E410, "AutoMapX", SN_NOWARN)
set_name(0x8012E414, "AutoMapY", SN_NOWARN)
set_name(0x8012E418, "AutoMapXOfs", SN_NOWARN)
set_name(0x8012E41C, "AutoMapYOfs", SN_NOWARN)
set_name(0x8012E420, "AMPlayerX", SN_NOWARN)
set_name(0x8012E424, "AMPlayerY", SN_NOWARN)
set_name(0x8012E3DC, "AutoMapScale", SN_NOWARN)
set_name(0x8012E3E0, "AutoMapPlayerR", SN_NOWARN)
set_name(0x8012E3E1, "AutoMapPlayerG", SN_NOWARN)
set_name(0x8012E3E2, "AutoMapPlayerB", SN_NOWARN)
set_name(0x8012E3E3, "AutoMapWallR", SN_NOWARN)
set_name(0x8012E3E4, "AutoMapWallG", SN_NOWARN)
set_name(0x8012E3E5, "AutoMapWallB", SN_NOWARN)
set_name(0x8012E3E6, "AutoMapDoorR", SN_NOWARN)
set_name(0x8012E3E7, "AutoMapDoorG", SN_NOWARN)
set_name(0x8012E3E8, "AutoMapDoorB", SN_NOWARN)
set_name(0x8012E3E9, "AutoMapColumnR", SN_NOWARN)
set_name(0x8012E3EA, "AutoMapColumnG", SN_NOWARN)
set_name(0x8012E3EB, "AutoMapColumnB", SN_NOWARN)
set_name(0x8012E3EC, "AutoMapArchR", SN_NOWARN)
set_name(0x8012E3ED, "AutoMapArchG", SN_NOWARN)
set_name(0x8012E3EE, "AutoMapArchB", SN_NOWARN)
set_name(0x8012E3EF, "AutoMapStairR", SN_NOWARN)
set_name(0x8012E3F0, "AutoMapStairG", SN_NOWARN)
set_name(0x8012E3F1, "AutoMapStairB", SN_NOWARN)
set_name(0x8011F660, "SetLevelName", SN_NOWARN)
set_name(0x8012EAA8, "GazTick", SN_NOWARN)
set_name(0x80135560, "RndTabs", SN_NOWARN)
set_name(0x800A89D4, "DefaultRnd", SN_NOWARN)
set_name(0x8012EAD0, "PollFunc", SN_NOWARN)
set_name(0x8012EAB4, "MsgFunc", SN_NOWARN)
set_name(0x8012EB00, "ErrorFunc", SN_NOWARN)
set_name(0x8012E9D4, "ActiveTasks", SN_NOWARN)
set_name(0x8012E9D8, "CurrentTask", SN_NOWARN)
set_name(0x8012E9DC, "T", SN_NOWARN)
set_name(0x8012E9E0, "MemTypeForTasker", SN_NOWARN)
set_name(0x80132D90, "SchEnv", SN_NOWARN)
set_name(0x8012E9E4, "ExecId", SN_NOWARN)
set_name(0x8012E9E8, "ExecMask", SN_NOWARN)
set_name(0x8012E9EC, "TasksActive", SN_NOWARN)
set_name(0x8012E9F0, "EpiFunc", SN_NOWARN)
set_name(0x8012E9F4, "ProFunc", SN_NOWARN)
set_name(0x8012E9F8, "EpiProId", SN_NOWARN)
set_name(0x8012E9FC, "EpiProMask", SN_NOWARN)
set_name(0x8012EA00, "DoTasksPrologue", SN_NOWARN)
set_name(0x8012EA04, "DoTasksEpilogue", SN_NOWARN)
set_name(0x8012EA08, "StackFloodCallback", SN_NOWARN)
set_name(0x8012EA0C, "ExtraStackProtection", SN_NOWARN)
set_name(0x8012EA10, "ExtraStackSizeLongs", SN_NOWARN)
set_name(0x8012EABC, "LastPtr", SN_NOWARN)
set_name(0x800A8A0C, "WorkMemInfo", SN_NOWARN)
set_name(0x8012EA14, "MemInitBlocks", SN_NOWARN)
set_name(0x80132DC0, "MemHdrBlocks", SN_NOWARN)
set_name(0x8012EA18, "FreeBlocks", SN_NOWARN)
set_name(0x8012EA1C, "LastError", SN_NOWARN)
set_name(0x8012EA20, "TimeStamp", SN_NOWARN)
set_name(0x8012EA24, "FullErrorChecking", SN_NOWARN)
set_name(0x8012EA28, "LastAttemptedAlloc", SN_NOWARN)
set_name(0x8012EA2C, "LastDeallocedBlock", SN_NOWARN)
set_name(0x8012EA30, "VerbLev", SN_NOWARN)
set_name(0x8012EA34, "NumOfFreeHdrs", SN_NOWARN)
set_name(0x8012EA38, "LastTypeAlloced", SN_NOWARN)
set_name(0x8012EA3C, "AllocFilter", SN_NOWARN)
set_name(0x800A8A14, "GalErrors", SN_NOWARN)
set_name(0x800A8A3C, "PhantomMem", SN_NOWARN)
set_name(0x80133F40, "buf", SN_NOWARN)
set_name(0x800A8A64, "NULL_REP", SN_NOWARN) | psx/_dump_/35/_dump_ida_/make_psx.py | set_name(0x8007B9C0, "GetTpY__FUs", SN_NOWARN)
set_name(0x8007B9DC, "GetTpX__FUs", SN_NOWARN)
set_name(0x8007B9E8, "Remove96__Fv", SN_NOWARN)
set_name(0x8007BA20, "AppMain", SN_NOWARN)
set_name(0x8007BAC0, "MAIN_RestartGameTask__Fv", SN_NOWARN)
set_name(0x8007BAEC, "GameTask__FP4TASK", SN_NOWARN)
set_name(0x8007BBD4, "MAIN_MainLoop__Fv", SN_NOWARN)
set_name(0x8007BC1C, "CheckMaxArgs__Fv", SN_NOWARN)
set_name(0x8007BC50, "GPUQ_InitModule__Fv", SN_NOWARN)
set_name(0x8007BC5C, "GPUQ_FlushQ__Fv", SN_NOWARN)
set_name(0x8007BDD0, "GPUQ_LoadImage__FP4RECTli", SN_NOWARN)
set_name(0x8007BE84, "GPUQ_DiscardHandle__Fl", SN_NOWARN)
set_name(0x8007BF24, "GPUQ_LoadClutAddr__FiiiPv", SN_NOWARN)
set_name(0x8007BFC0, "GPUQ_MoveImage__FP4RECTii", SN_NOWARN)
set_name(0x8007C060, "PRIM_Open__FiiiP10SCREEN_ENVUl", SN_NOWARN)
set_name(0x8007C17C, "InitPrimBuffer__FP11PRIM_BUFFERii", SN_NOWARN)
set_name(0x8007C258, "PRIM_Clip__FP4RECTi", SN_NOWARN)
set_name(0x8007C380, "PRIM_GetCurrentScreen__Fv", SN_NOWARN)
set_name(0x8007C38C, "PRIM_FullScreen__Fi", SN_NOWARN)
set_name(0x8007C3C8, "PRIM_Flush__Fv", SN_NOWARN)
set_name(0x8007C5DC, "PRIM_GetCurrentOtList__Fv", SN_NOWARN)
set_name(0x8007C5E8, "ClearPbOnDrawSync", SN_NOWARN)
set_name(0x8007C624, "ClearedYet__Fv", SN_NOWARN)
set_name(0x8007C630, "PrimDrawSycnCallBack", SN_NOWARN)
set_name(0x8007C650, "SendDispEnv__Fv", SN_NOWARN)
set_name(0x8007C674, "PRIM_GetNextPolyF4__Fv", SN_NOWARN)
set_name(0x8007C68C, "PRIM_GetNextPolyFt4__Fv", SN_NOWARN)
set_name(0x8007C6A4, "PRIM_GetNextPolyGt4__Fv", SN_NOWARN)
set_name(0x8007C6BC, "PRIM_GetNextPolyG4__Fv", SN_NOWARN)
set_name(0x8007C6D4, "PRIM_GetNextPolyF3__Fv", SN_NOWARN)
set_name(0x8007C6EC, "PRIM_GetNextDrArea__Fv", SN_NOWARN)
set_name(0x8007C704, "ClipRect__FRC4RECTR4RECT", SN_NOWARN)
set_name(0x8007C818, "IsColiding__FRC4RECTT0", SN_NOWARN)
set_name(0x8007C880, "VID_AfterDisplay__Fv", SN_NOWARN)
set_name(0x8007C8A0, "VID_ScrOn__Fv", SN_NOWARN)
set_name(0x8007C8C8, "VID_DoThisNextSync__FPFv_v", SN_NOWARN)
set_name(0x8007C920, "VID_NextSyncRoutHasExecuted__Fv", SN_NOWARN)
set_name(0x8007C92C, "VID_GetTick__Fv", SN_NOWARN)
set_name(0x8007C938, "VID_DispEnvSend", SN_NOWARN)
set_name(0x8007C974, "VID_SetXYOff__Fii", SN_NOWARN)
set_name(0x8007C984, "VID_GetXOff__Fv", SN_NOWARN)
set_name(0x8007C990, "VID_GetYOff__Fv", SN_NOWARN)
set_name(0x8007C99C, "VID_SetDBuffer__Fb", SN_NOWARN)
set_name(0x8007CB0C, "MyFilter__FUlUlPCc", SN_NOWARN)
set_name(0x8007CB14, "SlowMemMove__FPvT0Ul", SN_NOWARN)
set_name(0x8007CB34, "GetTpY__FUs_addr_8007CB34", SN_NOWARN)
set_name(0x8007CB50, "GetTpX__FUs_addr_8007CB50", SN_NOWARN)
set_name(0x8007CB5C, "SYSI_GetFs__Fv", SN_NOWARN)
set_name(0x8007CB68, "SYSI_GetOverlayFs__Fv", SN_NOWARN)
set_name(0x8007CB74, "SortOutFileSystem__Fv", SN_NOWARN)
set_name(0x8007CCB0, "MemCb__FlPvUlPCcii", SN_NOWARN)
set_name(0x8007CCD0, "Spanker__Fv", SN_NOWARN)
set_name(0x8007CD10, "GaryLiddon__Fv", SN_NOWARN)
set_name(0x8007CD18, "ReadPad__Fi", SN_NOWARN)
set_name(0x8007CE74, "DummyPoll__Fv", SN_NOWARN)
set_name(0x8007CE7C, "DaveOwens__Fv", SN_NOWARN)
set_name(0x8007CEA4, "GetCur__C4CPad", SN_NOWARN)
set_name(0x8007CECC, "CheckActive__4CPad", SN_NOWARN)
set_name(0x8007CED8, "GetTpY__FUs_addr_8007CED8", SN_NOWARN)
set_name(0x8007CEF4, "GetTpX__FUs_addr_8007CEF4", SN_NOWARN)
set_name(0x8007CF00, "TimSwann__Fv", SN_NOWARN)
set_name(0x8007CF08, "__6FileIOUl", SN_NOWARN)
set_name(0x8007CF58, "___6FileIO", SN_NOWARN)
set_name(0x8007CFAC, "Read__6FileIOPCcUl", SN_NOWARN)
set_name(0x8007D114, "FileLen__6FileIOPCc", SN_NOWARN)
set_name(0x8007D178, "FileNotFound__6FileIOPCc", SN_NOWARN)
set_name(0x8007D198, "StreamFile__6FileIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007D278, "ReadAtAddr__6FileIOPCcPUci", SN_NOWARN)
set_name(0x8007D33C, "DumpOldPath__6FileIO", SN_NOWARN)
set_name(0x8007D3A0, "SetSearchPath__6FileIOPCc", SN_NOWARN)
set_name(0x8007D47C, "FindFile__6FileIOPCcPc", SN_NOWARN)
set_name(0x8007D590, "CopyPathItem__6FileIOPcPCc", SN_NOWARN)
set_name(0x8007D638, "LockSearchPath__6FileIO", SN_NOWARN)
set_name(0x8007D690, "UnlockSearchPath__6FileIO", SN_NOWARN)
set_name(0x8007D6E8, "SearchPathExists__6FileIO", SN_NOWARN)
set_name(0x8007D6FC, "Save__6FileIOPCcPUci", SN_NOWARN)
set_name(0x8007D738, "__4PCIOUl", SN_NOWARN)
set_name(0x8007D7A0, "___4PCIO", SN_NOWARN)
set_name(0x8007D7F8, "FileExists__4PCIOPCc", SN_NOWARN)
set_name(0x8007D83C, "LoReadFileAtAddr__4PCIOPCcPUci", SN_NOWARN)
set_name(0x8007D900, "GetFileLength__4PCIOPCc", SN_NOWARN)
set_name(0x8007D9B8, "LoSave__4PCIOPCcPUci", SN_NOWARN)
set_name(0x8007DA8C, "LoStreamFile__4PCIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007DC9C, "__6SysObj", SN_NOWARN)
set_name(0x8007DCB4, "__nw__6SysObji", SN_NOWARN)
set_name(0x8007DCE0, "__nw__6SysObjiUl", SN_NOWARN)
set_name(0x8007DD5C, "__dl__6SysObjPv", SN_NOWARN)
set_name(0x8007DDC8, "__5DatIOUl", SN_NOWARN)
set_name(0x8007DE04, "___5DatIO", SN_NOWARN)
set_name(0x8007DE5C, "FileExists__5DatIOPCc", SN_NOWARN)
set_name(0x8007DE9C, "LoReadFileAtAddr__5DatIOPCcPUci", SN_NOWARN)
set_name(0x8007DF5C, "GetFileLength__5DatIOPCc", SN_NOWARN)
set_name(0x8007E010, "LoSave__5DatIOPCcPUci", SN_NOWARN)
set_name(0x8007E0B8, "LoStreamFile__5DatIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x8007E2C4, "__7TextDat", SN_NOWARN)
set_name(0x8007E304, "___7TextDat", SN_NOWARN)
set_name(0x8007E34C, "Use__7TextDat", SN_NOWARN)
set_name(0x8007E540, "TpLoadCallBack__FPUciib", SN_NOWARN)
set_name(0x8007E610, "StreamLoadTP__7TextDat", SN_NOWARN)
set_name(0x8007E6C8, "FinishedUsing__7TextDat", SN_NOWARN)
set_name(0x8007E724, "MakeBlockOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007E794, "MakeOffsetTab__C9CBlockHdr", SN_NOWARN)
set_name(0x8007E8C0, "SetUVTp__7TextDatP9FRAME_HDRP8POLY_FT4ii", SN_NOWARN)
set_name(0x8007E9C0, "PrintMonster__7TextDatiiibi", SN_NOWARN)
set_name(0x8007EDCC, "PrepareFt4__7TextDatP8POLY_FT4iiiii", SN_NOWARN)
set_name(0x8007F038, "GetDecompBufffer__7TextDati", SN_NOWARN)
set_name(0x8007F198, "SetUVTpGT4__7TextDatP9FRAME_HDRP8POLY_GT4ii", SN_NOWARN)
set_name(0x8007F298, "PrepareGt4__7TextDatP8POLY_GT4iiiii", SN_NOWARN)
set_name(0x8007F4F0, "SetUVTpGT3__7TextDatP9FRAME_HDRP8POLY_GT3", SN_NOWARN)
set_name(0x8007F574, "PrepareGt3__7TextDatP8POLY_GT3iii", SN_NOWARN)
set_name(0x8007F73C, "PrintFt4__7TextDatiiiiii", SN_NOWARN)
set_name(0x8007F890, "PrintGt4__7TextDatiiiiii", SN_NOWARN)
set_name(0x8007F9E4, "PrintGt3__7TextDatiiii", SN_NOWARN)
set_name(0x8007FAC8, "DecompFrame__7TextDatP9FRAME_HDR", SN_NOWARN)
set_name(0x8007FC20, "MakeCreatureOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007FD60, "MakePalOffsetTab__7TextDat", SN_NOWARN)
set_name(0x8007FE5C, "InitData__7TextDat", SN_NOWARN)
set_name(0x8007FE88, "DumpData__7TextDat", SN_NOWARN)
set_name(0x8007FFD0, "GM_UseTexData__Fi", SN_NOWARN)
set_name(0x800800F0, "GM_FinishedUsing__FP7TextDat", SN_NOWARN)
set_name(0x80080144, "SetPal__7TextDatP9FRAME_HDRP8POLY_FT4", SN_NOWARN)
set_name(0x80080208, "GetFrNum__7TextDatiiii", SN_NOWARN)
set_name(0x8008025C, "IsDirAliased__7TextDatiii", SN_NOWARN)
set_name(0x800802B4, "DoDecompRequests__7TextDat", SN_NOWARN)
set_name(0x800803D8, "FindDecompArea__7TextDatR4RECT", SN_NOWARN)
set_name(0x800804B0, "GetFileInfo__7TextDati", SN_NOWARN)
set_name(0x80080500, "GetSize__C15CCreatureAction", SN_NOWARN)
set_name(0x80080528, "GetFrNum__C15CCreatureActionii", SN_NOWARN)
set_name(0x800805D0, "InitDirRemap__15CCreatureAction", SN_NOWARN)
set_name(0x80080690, "GetFrNum__C12CCreatureHdriii", SN_NOWARN)
set_name(0x800806D4, "GetAction__C12CCreatureHdri", SN_NOWARN)
set_name(0x80080764, "InitActionDirRemaps__12CCreatureHdr", SN_NOWARN)
set_name(0x800807D4, "GetSize__C12CCreatureHdr", SN_NOWARN)
set_name(0x80080840, "LoadDat__C13CTextFileInfo", SN_NOWARN)
set_name(0x80080890, "LoadHdr__C13CTextFileInfo", SN_NOWARN)
set_name(0x800808B8, "GetFile__C13CTextFileInfoPc", SN_NOWARN)
set_name(0x80080954, "HasFile__C13CTextFileInfoPc", SN_NOWARN)
set_name(0x800809BC, "Un64__FPUcT0l", SN_NOWARN)
set_name(0x80080A90, "__7CScreen", SN_NOWARN)
set_name(0x80080AC4, "Load__7CScreeniii", SN_NOWARN)
set_name(0x80080D64, "Unload__7CScreen", SN_NOWARN)
set_name(0x80080D88, "Display__7CScreeniiii", SN_NOWARN)
set_name(0x80081068, "SetRect__5CPartR7TextDatR4RECT", SN_NOWARN)
set_name(0x800810E4, "GetBoundingBox__6CBlockR7TextDatR4RECT", SN_NOWARN)
set_name(0x80081240, "_GLOBAL__D_DatPool", SN_NOWARN)
set_name(0x80081298, "_GLOBAL__I_DatPool", SN_NOWARN)
set_name(0x800812EC, "PRIM_GetPrim__FPP8POLY_GT3", SN_NOWARN)
set_name(0x80081368, "PRIM_GetPrim__FPP8POLY_GT4", SN_NOWARN)
set_name(0x800813E4, "PRIM_GetPrim__FPP8POLY_FT4", SN_NOWARN)
set_name(0x80081460, "CanXferFrame__C7TextDat", SN_NOWARN)
set_name(0x80081488, "CanXferPal__C7TextDat", SN_NOWARN)
set_name(0x800814B0, "IsLoaded__C7TextDat", SN_NOWARN)
set_name(0x800814BC, "GetTexNum__C7TextDat", SN_NOWARN)
set_name(0x800814C8, "GetCreature__7TextDati", SN_NOWARN)
set_name(0x80081540, "GetNumOfCreatures__7TextDat", SN_NOWARN)
set_name(0x80081554, "SetFileInfo__7TextDatPC13CTextFileInfoi", SN_NOWARN)
set_name(0x80081560, "GetNumOfFrames__7TextDat", SN_NOWARN)
set_name(0x80081574, "GetPal__7TextDati", SN_NOWARN)
set_name(0x80081590, "GetFr__7TextDati", SN_NOWARN)
set_name(0x800815AC, "GetName__C13CTextFileInfo", SN_NOWARN)
set_name(0x800815B8, "HasDat__C13CTextFileInfo", SN_NOWARN)
set_name(0x800815E0, "HasTp__C13CTextFileInfo", SN_NOWARN)
set_name(0x80081608, "GetSize__C6CBlock", SN_NOWARN)
set_name(0x8008161C, "__4CdIOUl", SN_NOWARN)
set_name(0x80081660, "___4CdIO", SN_NOWARN)
set_name(0x800816B8, "FileExists__4CdIOPCc", SN_NOWARN)
set_name(0x800816DC, "LoReadFileAtAddr__4CdIOPCcPUci", SN_NOWARN)
set_name(0x80081760, "GetFileLength__4CdIOPCc", SN_NOWARN)
set_name(0x80081784, "LoSave__4CdIOPCcPUci", SN_NOWARN)
set_name(0x80081864, "LoStreamCallBack__Fi", SN_NOWARN)
set_name(0x80081874, "CD_GetCdlFILE__FPCcP7CdlFILE", SN_NOWARN)
set_name(0x800819C0, "LoStreamFile__4CdIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x80081C9C, "LoAsyncStreamFile__4CdIOPCciPFPUciib_bii", SN_NOWARN)
set_name(0x80081DFC, "BL_InitEAC__Fv", SN_NOWARN)
set_name(0x80081EE8, "BL_ReadFile__FPcUl", SN_NOWARN)
set_name(0x80082014, "BL_AsyncReadFile__FPcUl", SN_NOWARN)
set_name(0x80082188, "BL_LoadDirectory__Fv", SN_NOWARN)
set_name(0x800822B0, "BL_LoadStreamDir__Fv", SN_NOWARN)
set_name(0x80082590, "BL_MakeFilePosTab__FPUcUl", SN_NOWARN)
set_name(0x80082690, "BL_FindStreamFile__FPcc", SN_NOWARN)
set_name(0x8008285C, "BL_FileExists__FPcc", SN_NOWARN)
set_name(0x80082880, "BL_FileLength__FPcc", SN_NOWARN)
set_name(0x800828B4, "BL_LoadFileAtAddr__FPcPUcc", SN_NOWARN)
set_name(0x8008299C, "BL_AsyncLoadDone__Fv", SN_NOWARN)
set_name(0x800829A8, "BL_WaitForAsyncFinish__Fv", SN_NOWARN)
set_name(0x800829F4, "BL_AsyncLoadCallBack__Fi", SN_NOWARN)
set_name(0x80082A24, "BL_LoadFileAsync__FPcc", SN_NOWARN)
set_name(0x80082B9C, "BL_AsyncLoadFileAtAddr__FPcPUcc", SN_NOWARN)
set_name(0x80082C64, "BL_OpenStreamFile__FPcc", SN_NOWARN)
set_name(0x80082C90, "BL_CloseStreamFile__FP6STRHDR", SN_NOWARN)
set_name(0x80082CC8, "LZNP_Decode__FPUcT0", SN_NOWARN)
set_name(0x80082D9C, "Tmalloc__Fi", SN_NOWARN)
set_name(0x80082EC0, "Tfree__FPv", SN_NOWARN)
set_name(0x80082F70, "InitTmalloc__Fv", SN_NOWARN)
set_name(0x80082F98, "strupr__FPc", SN_NOWARN)
set_name(0x80082FEC, "PauseTask__FP4TASK", SN_NOWARN)
set_name(0x80083038, "GetPausePad__Fv", SN_NOWARN)
set_name(0x8008312C, "TryPadForPause__Fi", SN_NOWARN)
set_name(0x80083158, "DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x800833D8, "DoPausedMessage__14CPauseMessages", SN_NOWARN)
set_name(0x800836F0, "DoQuitMessage__14CPauseMessages", SN_NOWARN)
set_name(0x80083810, "AreYouSureMessage__14CPauseMessages", SN_NOWARN)
set_name(0x80083914, "PA_SetPauseOk__Fb", SN_NOWARN)
set_name(0x80083924, "PA_GetPauseOk__Fv", SN_NOWARN)
set_name(0x80083930, "MY_PausePrint__17CTempPauseMessageiPciP4RECT", SN_NOWARN)
set_name(0x80083A7C, "InitPrintQuitMessage__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083A84, "PrintQuitMessage__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083BA0, "LeavePrintQuitMessage__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083BA8, "InitPrintAreYouSure__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083BB0, "PrintAreYouSure__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083CCC, "LeavePrintAreYouSure__17CTempPauseMessagei", SN_NOWARN)
set_name(0x80083CD4, "InitPrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083CDC, "ShowInActive__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083DBC, "PrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F0C, "LeavePrintPaused__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F14, "___17CTempPauseMessage", SN_NOWARN)
set_name(0x80083F3C, "_GLOBAL__D_DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x80083F64, "_GLOBAL__I_DoPause__14CPauseMessagesi", SN_NOWARN)
set_name(0x80083F8C, "__17CTempPauseMessage", SN_NOWARN)
set_name(0x80083FD0, "___14CPauseMessages", SN_NOWARN)
set_name(0x80084004, "__14CPauseMessages", SN_NOWARN)
set_name(0x80084018, "SetRGB__6DialogUcUcUc", SN_NOWARN)
set_name(0x80084038, "SetBack__6Dialogi", SN_NOWARN)
set_name(0x80084040, "SetBorder__6Dialogi", SN_NOWARN)
set_name(0x80084048, "___6Dialog", SN_NOWARN)
set_name(0x80084070, "__6Dialog", SN_NOWARN)
set_name(0x800840CC, "GetDown__C4CPad", SN_NOWARN)
set_name(0x800840F4, "GetUp__C4CPad", SN_NOWARN)
set_name(0x8008411C, "CheckActive__4CPad_addr_8008411C", SN_NOWARN)
set_name(0x80084128, "ReadPadStream__Fv", SN_NOWARN)
set_name(0x80084240, "PAD_Handler__Fv", SN_NOWARN)
set_name(0x80084408, "PAD_GetPad__FiUc", SN_NOWARN)
set_name(0x800844A4, "NewVal__4CPadUs", SN_NOWARN)
set_name(0x800845DC, "BothNewVal__4CPadUsUs", SN_NOWARN)
set_name(0x80084738, "Trans__4CPadUs", SN_NOWARN)
set_name(0x8008485C, "_GLOBAL__I_Pad0", SN_NOWARN)
set_name(0x80084894, "SetPadType__4CPadUc", SN_NOWARN)
set_name(0x8008489C, "CheckActive__4CPad_addr_8008489C", SN_NOWARN)
set_name(0x800848A8, "SetActive__4CPadUc", SN_NOWARN)
set_name(0x800848B0, "SetBothFlag__4CPadUc", SN_NOWARN)
set_name(0x800848B8, "__4CPadi", SN_NOWARN)
set_name(0x800848EC, "Flush__4CPad", SN_NOWARN)
set_name(0x80084910, "Set__7FontTab", SN_NOWARN)
set_name(0x800849AC, "InitPrinty__Fv", SN_NOWARN)
set_name(0x80084A4C, "SetTextDat__5CFontP7TextDat", SN_NOWARN)
set_name(0x80084A54, "PrintChar__5CFontUsUscUcUcUc", SN_NOWARN)
set_name(0x80084BEC, "Print__5CFontiiPc8TXT_JUSTP4RECTUcUcUc", SN_NOWARN)
set_name(0x80085218, "GetStrWidth__5CFontPc", SN_NOWARN)
set_name(0x800852CC, "SetChar__5CFontiUs", SN_NOWARN)
set_name(0x80085330, "SetOTpos__5CFonti", SN_NOWARN)
set_name(0x8008533C, "ClearFont__5CFont", SN_NOWARN)
set_name(0x80085360, "IsDefined__5CFontUc", SN_NOWARN)
set_name(0x80085380, "GetCharFrameNum__5CFontc", SN_NOWARN)
set_name(0x80085398, "GetCharWidth__5CFontc", SN_NOWARN)
set_name(0x800853F0, "Init__5CFont", SN_NOWARN)
set_name(0x80085424, "GetFr__7TextDati_addr_80085424", SN_NOWARN)
set_name(0x80085440, "TrimCol__Fs", SN_NOWARN)
set_name(0x80085478, "DialogPrint__Fiiiiiiiiii", SN_NOWARN)
set_name(0x80085DF8, "GetDropShadowG4__FUcUcUcUcUcUcUcUcUcUcUcUc", SN_NOWARN)
set_name(0x80085F30, "DropShadows__Fiiii", SN_NOWARN)
set_name(0x800861D4, "InitDialog__Fv", SN_NOWARN)
set_name(0x8008630C, "GetSizes__6Dialog", SN_NOWARN)
set_name(0x80086590, "Back__6Dialogiiii", SN_NOWARN)
set_name(0x80087750, "Line__6Dialogiii", SN_NOWARN)
set_name(0x80087968, "GetPal__7TextDati_addr_80087968", SN_NOWARN)
set_name(0x80087984, "GetFr__7TextDati_addr_80087984", SN_NOWARN)
set_name(0x800879A0, "ATT_DoAttract__Fv", SN_NOWARN)
set_name(0x80087AF0, "CreatePlayersFromFeData__FR9FE_CREATE", SN_NOWARN)
set_name(0x80087BBC, "UpdateSel__FPUsUsPUc", SN_NOWARN)
set_name(0x80087BFC, "CycleSelCols__Fv", SN_NOWARN)
set_name(0x80087DB4, "FindTownCreature__7CBlocksi", SN_NOWARN)
set_name(0x80087E28, "FindCreature__7CBlocksi", SN_NOWARN)
set_name(0x80087E7C, "__7CBlocksiiiii", SN_NOWARN)
set_name(0x80087FD0, "SetTownersGraphics__7CBlocks", SN_NOWARN)
set_name(0x80088008, "SetMonsterGraphics__7CBlocksii", SN_NOWARN)
set_name(0x800880D0, "___7CBlocks", SN_NOWARN)
set_name(0x80088158, "DumpGt4s__7CBlocks", SN_NOWARN)
set_name(0x800881C0, "DumpRects__7CBlocks", SN_NOWARN)
set_name(0x80088228, "SetGraphics__7CBlocksPP7TextDatPii", SN_NOWARN)
set_name(0x80088284, "DumpGraphics__7CBlocksPP7TextDatPi", SN_NOWARN)
set_name(0x800882D4, "PrintBlockOutline__7CBlocksiiiii", SN_NOWARN)
set_name(0x80088620, "Load__7CBlocksi", SN_NOWARN)
set_name(0x800886CC, "MakeRectTable__7CBlocks", SN_NOWARN)
set_name(0x800887A0, "MakeGt4Table__7CBlocks", SN_NOWARN)
set_name(0x800888A8, "MakeGt4__7CBlocksP8POLY_GT4P9FRAME_HDR", SN_NOWARN)
set_name(0x800889E8, "GetBlock__7CBlocksi", SN_NOWARN)
set_name(0x80088A60, "Print__7CBlocks", SN_NOWARN)
set_name(0x80088A88, "SetXY__7CBlocksii", SN_NOWARN)
set_name(0x80088AB0, "GetXY__7CBlocksPiT1", SN_NOWARN)
set_name(0x80088AC8, "PrintMap__7CBlocksii", SN_NOWARN)
set_name(0x80089FB8, "PrintGameSprites__7CBlocksiiiii", SN_NOWARN)
set_name(0x8008A128, "PrintGameSprites__7CBlocksP8map_infoiiiiiii", SN_NOWARN)
set_name(0x8008AF2C, "PrintSprites__7CBlocksP8map_infoiiiiiii", SN_NOWARN)
set_name(0x8008B680, "PrintSprites__7CBlocksiiiii", SN_NOWARN)
set_name(0x8008B7F0, "ScrToWorldX__7CBlocksii", SN_NOWARN)
set_name(0x8008B804, "ScrToWorldY__7CBlocksii", SN_NOWARN)
set_name(0x8008B818, "SetScrollTarget__7CBlocksii", SN_NOWARN)
set_name(0x8008B8DC, "DoScroll__7CBlocks", SN_NOWARN)
set_name(0x8008B960, "SetPlayerPosBlocks__7CBlocksiii", SN_NOWARN)
set_name(0x8008BA00, "GetScrXY__7CBlocksR4RECTiiii", SN_NOWARN)
set_name(0x8008BAD4, "ShadScaleSkew__7CBlocksP8POLY_FT4", SN_NOWARN)
set_name(0x8008BB54, "WorldToScrX__7CBlocksii", SN_NOWARN)
set_name(0x8008BB5C, "WorldToScrY__7CBlocksii", SN_NOWARN)
set_name(0x8008BB70, "BL_GetCurrentBlocks__Fv", SN_NOWARN)
set_name(0x8008BB7C, "PRIM_GetPrim__FPP8POLY_FT4_addr_8008BB7C", SN_NOWARN)
set_name(0x8008BBF8, "GetHighlightCol__FiPiUsUsUs", SN_NOWARN)
set_name(0x8008BC40, "PRIM_GetCopy__FP8POLY_FT4", SN_NOWARN)
set_name(0x8008BC7C, "GetHighlightCol__FiPcUsUsUs", SN_NOWARN)
set_name(0x8008BCC4, "PRIM_GetPrim__FPP8POLY_GT4_addr_8008BCC4", SN_NOWARN)
set_name(0x8008BD40, "PRIM_GetPrim__FPP7LINE_F2", SN_NOWARN)
set_name(0x8008BDBC, "PRIM_CopyPrim__FP8POLY_FT4T0", SN_NOWARN)
set_name(0x8008BDE4, "GetCreature__14TownToCreaturei", SN_NOWARN)
set_name(0x8008BE00, "SetItemGraphics__7CBlocksi", SN_NOWARN)
set_name(0x8008BE28, "SetObjGraphics__7CBlocksi", SN_NOWARN)
set_name(0x8008BE50, "DumpItems__7CBlocks", SN_NOWARN)
set_name(0x8008BE74, "DumpObjs__7CBlocks", SN_NOWARN)
set_name(0x8008BE98, "DumpMonsters__7CBlocks", SN_NOWARN)
set_name(0x8008BEC0, "GetNumOfBlocks__7CBlocks", SN_NOWARN)
set_name(0x8008BECC, "CopyToGt4__9LittleGt4P8POLY_GT4", SN_NOWARN)
set_name(0x8008BF64, "InitFromGt4__9LittleGt4P8POLY_GT4ii", SN_NOWARN)
set_name(0x8008BFF4, "GetNumOfFrames__7TextDatii", SN_NOWARN)
set_name(0x8008C02C, "GetCreature__7TextDati_addr_8008C02C", SN_NOWARN)
set_name(0x8008C0A4, "GetNumOfCreatures__7TextDat_addr_8008C0A4", SN_NOWARN)
set_name(0x8008C0B8, "SetFileInfo__7TextDatPC13CTextFileInfoi_addr_8008C0B8", SN_NOWARN)
set_name(0x8008C0C4, "GetPal__7TextDati_addr_8008C0C4", SN_NOWARN)
set_name(0x8008C0E0, "GetFr__7TextDati_addr_8008C0E0", SN_NOWARN)
set_name(0x8008C0FC, "OVR_IsMemcardOverlayBlank__Fv", SN_NOWARN)
set_name(0x8008C128, "OVR_LoadPregame__Fv", SN_NOWARN)
set_name(0x8008C150, "OVR_LoadFrontend__Fv", SN_NOWARN)
set_name(0x8008C178, "OVR_LoadGame__Fv", SN_NOWARN)
set_name(0x8008C1A0, "OVR_LoadFmv__Fv", SN_NOWARN)
set_name(0x8008C1C8, "OVR_LoadMemcard__Fv", SN_NOWARN)
set_name(0x8008C1F4, "ClearOutOverlays__Fv", SN_NOWARN)
set_name(0x8008C24C, "ClearOut__7Overlay", SN_NOWARN)
set_name(0x8008C310, "Load__7Overlay", SN_NOWARN)
set_name(0x8008C380, "OVR_GetCurrentOverlay__Fv", SN_NOWARN)
set_name(0x8008C38C, "LoadOver__FR7Overlay", SN_NOWARN)
set_name(0x8008C3E0, "_GLOBAL__I_OVR_Open__Fv", SN_NOWARN)
set_name(0x8008C550, "GetOverType__7Overlay", SN_NOWARN)
set_name(0x8008C55C, "StevesDummyPoll__Fv", SN_NOWARN)
set_name(0x8008C564, "Lambo__Fv", SN_NOWARN)
set_name(0x8008C56C, "__7CPlayerbi", SN_NOWARN)
set_name(0x8008C650, "___7CPlayer", SN_NOWARN)
set_name(0x8008C6A8, "Load__7CPlayeri", SN_NOWARN)
set_name(0x8008C704, "SetBlockXY__7CPlayerR7CBlocksR12PlayerStruct", SN_NOWARN)
set_name(0x8008C850, "SetScrollTarget__7CPlayerR12PlayerStructR7CBlocks", SN_NOWARN)
set_name(0x8008CC7C, "GetNumOfSpellAnims__FR12PlayerStruct", SN_NOWARN)
set_name(0x8008CCFC, "Print__7CPlayerR12PlayerStructR7CBlocks", SN_NOWARN)
set_name(0x8008D1D4, "FindAction__7CPlayerR12PlayerStruct", SN_NOWARN)
set_name(0x8008D250, "FindActionEnum__7CPlayerR12PlayerStruct", SN_NOWARN)
set_name(0x8008D2CC, "Init__7CPlayer", SN_NOWARN)
set_name(0x8008D2D4, "Dump__7CPlayer", SN_NOWARN)
set_name(0x8008D2DC, "PRIM_GetPrim__FPP8POLY_FT4_addr_8008D2DC", SN_NOWARN)
set_name(0x8008D358, "PRIM_GetCopy__FP8POLY_FT4_addr_8008D358", SN_NOWARN)
set_name(0x8008D394, "PRIM_CopyPrim__FP8POLY_FT4T0_addr_8008D394", SN_NOWARN)
set_name(0x8008D3BC, "GetPlrOt__7CBlocksi", SN_NOWARN)
set_name(0x8008D3D0, "SetDecompArea__7TextDatiiii", SN_NOWARN)
set_name(0x8008D3E8, "GetNumOfFrames__7TextDatii_addr_8008D3E8", SN_NOWARN)
set_name(0x8008D420, "GetNumOfActions__7TextDati", SN_NOWARN)
set_name(0x8008D444, "GetCreature__7TextDati_addr_8008D444", SN_NOWARN)
set_name(0x8008D4BC, "GetNumOfCreatures__7TextDat_addr_8008D4BC", SN_NOWARN)
set_name(0x8008D4D0, "SetFileInfo__7TextDatPC13CTextFileInfoi_addr_8008D4D0", SN_NOWARN)
set_name(0x8008D4DC, "PROF_Open__Fv", SN_NOWARN)
set_name(0x8008D51C, "PROF_State__Fv", SN_NOWARN)
set_name(0x8008D528, "PROF_On__Fv", SN_NOWARN)
set_name(0x8008D538, "PROF_Off__Fv", SN_NOWARN)
set_name(0x8008D544, "PROF_CpuEnd__Fv", SN_NOWARN)
set_name(0x8008D574, "PROF_CpuStart__Fv", SN_NOWARN)
set_name(0x8008D598, "PROF_DrawStart__Fv", SN_NOWARN)
set_name(0x8008D5BC, "PROF_DrawEnd__Fv", SN_NOWARN)
set_name(0x8008D5EC, "PROF_Draw__FPUl", SN_NOWARN)
set_name(0x8008D7E0, "PROF_Restart__Fv", SN_NOWARN)
set_name(0x8008D800, "PSX_WndProc__FUilUl", SN_NOWARN)
set_name(0x8008D8C0, "PSX_PostWndProc__FUilUl", SN_NOWARN)
set_name(0x8008D970, "GoBackLevel__Fv", SN_NOWARN)
set_name(0x8008D9E8, "GoWarpLevel__Fv", SN_NOWARN)
set_name(0x8008DA20, "PostLoadGame__Fv", SN_NOWARN)
set_name(0x8008DABC, "GoLoadGame__Fv", SN_NOWARN)
set_name(0x8008DB18, "PostNewLevel__Fv", SN_NOWARN)
set_name(0x8008DBB4, "GoNewLevel__Fv", SN_NOWARN)
set_name(0x8008DC08, "PostGoBackLevel__Fv", SN_NOWARN)
set_name(0x8008DCA0, "GoForwardLevel__Fv", SN_NOWARN)
set_name(0x8008DCF8, "PostGoForwardLevel__Fv", SN_NOWARN)
set_name(0x8008DD90, "GoNewGame__Fv", SN_NOWARN)
set_name(0x8008DDE0, "PostNewGame__Fv", SN_NOWARN)
set_name(0x8008DE18, "LevelToLevelInit__Fv", SN_NOWARN)
set_name(0x8008DE60, "GetPal__6GPaneli", SN_NOWARN)
set_name(0x8008DEA4, "__6GPaneli", SN_NOWARN)
set_name(0x8008DEFC, "DrawFlask__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E37C, "DrawSpeedBar__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E800, "DrawSpell__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E9A0, "DrawMsgWindow__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008E9EC, "DrawDurThingy__6GPaneliiP10ItemStructi", SN_NOWARN)
set_name(0x8008EDA8, "DrawDurIcon__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008EE9C, "Print__6GPanelP7PanelXYP12PlayerStruct", SN_NOWARN)
set_name(0x8008EFA0, "GetPal__7TextDati_addr_8008EFA0", SN_NOWARN)
set_name(0x8008EFBC, "GetFr__7TextDati_addr_8008EFBC", SN_NOWARN)
set_name(0x8008EFD8, "PrintCDWaitTask__FP4TASK", SN_NOWARN)
set_name(0x8008F090, "InitCDWaitIcon__Fv", SN_NOWARN)
set_name(0x8008F0C4, "STR_Debug__FP6SFXHDRPce", SN_NOWARN)
set_name(0x8008F0D8, "STR_SystemTask__FP4TASK", SN_NOWARN)
set_name(0x8008F120, "STR_AllocBuffer__Fv", SN_NOWARN)
set_name(0x8008F174, "STR_Init__Fv", SN_NOWARN)
set_name(0x8008F294, "STR_InitStream__Fv", SN_NOWARN)
set_name(0x8008F3CC, "STR_PlaySound__FUscic", SN_NOWARN)
set_name(0x8008F508, "STR_setvolume__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F560, "STR_PlaySFX__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F66C, "STR_pauseall__Fv", SN_NOWARN)
set_name(0x8008F6BC, "STR_resumeall__Fv", SN_NOWARN)
set_name(0x8008F70C, "STR_CloseStream__FP6SFXHDR", SN_NOWARN)
set_name(0x8008F790, "STR_SoundCommand__FP6SFXHDRi", SN_NOWARN)
set_name(0x8008F89C, "STR_Command__FP6SFXHDR", SN_NOWARN)
set_name(0x8008FA48, "STR_DMAControl__FP6SFXHDR", SN_NOWARN)
set_name(0x8008FB10, "STR_PlayStream__FP6SFXHDRPUci", SN_NOWARN)
set_name(0x8008FCEC, "STR_AsyncWeeTASK__FP4TASK", SN_NOWARN)
set_name(0x8008FFEC, "STR_AsyncTASK__FP4TASK", SN_NOWARN)
set_name(0x80090420, "STR_StreamMainTask__FP6SFXHDRc", SN_NOWARN)
set_name(0x80090528, "SND_Monitor__FP4TASK", SN_NOWARN)
set_name(0x800905B4, "SPU_Init__Fv", SN_NOWARN)
set_name(0x800906C0, "SND_FindChannel__Fv", SN_NOWARN)
set_name(0x8009072C, "SND_ClearBank__Fv", SN_NOWARN)
set_name(0x800907A4, "SndLoadCallBack__FPUciib", SN_NOWARN)
set_name(0x8009081C, "SND_LoadBank__Fi", SN_NOWARN)
set_name(0x80090950, "SND_FindSFX__FUs", SN_NOWARN)
set_name(0x800909A4, "SND_StopSnd__Fi", SN_NOWARN)
set_name(0x800909C8, "SND_IsSfxPlaying__Fi", SN_NOWARN)
set_name(0x80090A04, "SND_RemapSnd__Fi", SN_NOWARN)
set_name(0x80090A78, "SND_PlaySnd__FUsiii", SN_NOWARN)
set_name(0x80090C34, "AS_CallBack0__Fi", SN_NOWARN)
set_name(0x80090C48, "AS_CallBack1__Fi", SN_NOWARN)
set_name(0x80090C5C, "AS_WasLastBlock__FiP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090D38, "AS_OpenStream__FP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090DD8, "AS_GetBlock__FP6SFXHDR", SN_NOWARN)
set_name(0x80090DE4, "AS_CloseStream__FP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090E10, "AS_LoopStream__FiP6STRHDRP6SFXHDR", SN_NOWARN)
set_name(0x80090F30, "SCR_NeedHighlightPal__FUsUsi", SN_NOWARN)
set_name(0x80090F64, "Init__13PalCollectionPC7InitPos", SN_NOWARN)
set_name(0x80090FF4, "FindPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x800910D0, "NewPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x80091150, "MakePal__8PalEntryUsUsi", SN_NOWARN)
set_name(0x800911F0, "GetHighlightPal__13PalCollectionUsUsi", SN_NOWARN)
set_name(0x80091284, "UpdatePals__13PalCollection", SN_NOWARN)
set_name(0x800912F8, "SCR_Handler__Fv", SN_NOWARN)
set_name(0x80091320, "GetNumOfObjs__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x80091328, "GetObj__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x80091364, "Init__t10Collection2Z8PalEntryi20", SN_NOWARN)
set_name(0x800913C8, "MoveFromUsedToUnused__t10Collection2Z8PalEntryi20P8PalEntry", SN_NOWARN)
set_name(0x80091420, "MoveFromUnusedToUsed__t10Collection2Z8PalEntryi20P8PalEntry", SN_NOWARN)
set_name(0x80091478, "Set__8PalEntryUsUsi", SN_NOWARN)
set_name(0x8009148C, "Set__8PalEntryRC7InitPos", SN_NOWARN)
set_name(0x800914B8, "SetJustUsed__8PalEntryb", SN_NOWARN)
set_name(0x800914C0, "Init__8PalEntry", SN_NOWARN)
set_name(0x800914C8, "GetClut__C8PalEntry", SN_NOWARN)
set_name(0x800914D4, "IsEqual__C8PalEntryUsUsi", SN_NOWARN)
set_name(0x8009150C, "GetNext__Ct11TLinkedList1Z8PalEntry", SN_NOWARN)
set_name(0x80091518, "AddToList__t11TLinkedList1Z8PalEntryPP8PalEntry", SN_NOWARN)
set_name(0x80091538, "DetachFromList__t11TLinkedList1Z8PalEntryPP8PalEntry", SN_NOWARN)
set_name(0x80091584, "stub__FPcPv", SN_NOWARN)
set_name(0x8009158C, "new_eprint__FPcT0i", SN_NOWARN)
set_name(0x800915C0, "TonysGameTask__FP4TASK", SN_NOWARN)
set_name(0x80091648, "SetAmbientLight__Fv", SN_NOWARN)
set_name(0x800916CC, "print_demo_task__FP4TASK", SN_NOWARN)
set_name(0x800918D8, "TonysDummyPoll__Fv", SN_NOWARN)
set_name(0x800918FC, "load_demo_pad_data__FUl", SN_NOWARN)
set_name(0x8009195C, "save_demo_pad_data__FUl", SN_NOWARN)
set_name(0x800919BC, "set_pad_record_play__Fi", SN_NOWARN)
set_name(0x80091A30, "start_demo__Fv", SN_NOWARN)
set_name(0x80091ACC, "SetQuest__Fv", SN_NOWARN)
set_name(0x80091AF4, "CurrCheatStr__Fv", SN_NOWARN)
set_name(0x80091B14, "tony__Fv", SN_NOWARN)
set_name(0x80091B4C, "GLUE_SetMonsterList__Fi", SN_NOWARN)
set_name(0x80091B58, "GLUE_GetMonsterList__Fv", SN_NOWARN)
set_name(0x80091B64, "GLUE_SuspendGame__Fv", SN_NOWARN)
set_name(0x80091BB8, "GLUE_ResumeGame__Fv", SN_NOWARN)
set_name(0x80091C0C, "GLUE_PreTown__Fv", SN_NOWARN)
set_name(0x80091C70, "GLUE_PreDun__Fv", SN_NOWARN)
set_name(0x80091CBC, "GLUE_Finished__Fv", SN_NOWARN)
set_name(0x80091CC8, "GLUE_SetFinished__Fb", SN_NOWARN)
set_name(0x80091CD4, "GLUE_StartBg__Fibi", SN_NOWARN)
set_name(0x80091D58, "GLUE_SetShowGameScreenFlag__Fb", SN_NOWARN)
set_name(0x80091D68, "GLUE_SetHomingScrollFlag__Fb", SN_NOWARN)
set_name(0x80091D78, "GLUE_SetShowPanelFlag__Fb", SN_NOWARN)
set_name(0x80091D88, "DoShowPanelGFX__FP6GPanelT0", SN_NOWARN)
set_name(0x80091E60, "BgTask__FP4TASK", SN_NOWARN)
set_name(0x800923C0, "FindPlayerChar__FPc", SN_NOWARN)
set_name(0x80092458, "FindPlayerChar__Fiii", SN_NOWARN)
set_name(0x800924B4, "FindPlayerChar__FP12PlayerStruct", SN_NOWARN)
set_name(0x800924E4, "FindPlayerChar__FP12PlayerStructb", SN_NOWARN)
set_name(0x80092544, "MakeSurePlayerDressedProperly__FR7CPlayerR12PlayerStructb", SN_NOWARN)
set_name(0x800925C4, "GLUE_GetCurrentList__Fi", SN_NOWARN)
set_name(0x80092670, "GetTexId__7CPlayer", SN_NOWARN)
set_name(0x8009267C, "SetTown__7CBlocksb", SN_NOWARN)
set_name(0x80092684, "MoveToScrollTarget__7CBlocks", SN_NOWARN)
set_name(0x80092698, "SetDemoKeys__FPi", SN_NOWARN)
set_name(0x80092770, "RestoreDemoKeys__FPi", SN_NOWARN)
set_name(0x80092800, "get_action_str__Fii", SN_NOWARN)
set_name(0x80092878, "get_key_pad__Fi", SN_NOWARN)
set_name(0x800928B0, "checkvalid__Fv", SN_NOWARN)
set_name(0x80092914, "RemoveCtrlScreen__Fv", SN_NOWARN)
set_name(0x8009297C, "Init_ctrl_pos__Fv", SN_NOWARN)
set_name(0x80092A34, "remove_padval__Fi", SN_NOWARN)
set_name(0x80092A74, "remove_comboval__Fi", SN_NOWARN)
set_name(0x80092AB4, "set_buttons__Fii", SN_NOWARN)
set_name(0x80092C08, "restore_controller_settings__Fv", SN_NOWARN)
set_name(0x80092C50, "only_one_button__Fi", SN_NOWARN)
set_name(0x80092C7C, "main_ctrl_setup__Fv", SN_NOWARN)
set_name(0x8009312C, "PrintCtrlString__FiiUcic", SN_NOWARN)
set_name(0x80093628, "DrawCtrlSetup__Fv", SN_NOWARN)
set_name(0x80093AE4, "_GLOBAL__D_ctrlflag", SN_NOWARN)
set_name(0x80093B0C, "_GLOBAL__I_ctrlflag", SN_NOWARN)
set_name(0x80093B34, "GetTick__C4CPad", SN_NOWARN)
set_name(0x80093B5C, "GetDown__C4CPad_addr_80093B5C", SN_NOWARN)
set_name(0x80093B84, "GetUp__C4CPad_addr_80093B84", SN_NOWARN)
set_name(0x80093BAC, "SetPadTickMask__4CPadUs", SN_NOWARN)
set_name(0x80093BB4, "SetPadTick__4CPadUs", SN_NOWARN)
set_name(0x80093BBC, "SetRGB__6DialogUcUcUc_addr_80093BBC", SN_NOWARN)
set_name(0x80093BDC, "SetBorder__6Dialogi_addr_80093BDC", SN_NOWARN)
set_name(0x80093BE4, "SetOTpos__6Dialogi", SN_NOWARN)
set_name(0x80093BF0, "___6Dialog_addr_80093BF0", SN_NOWARN)
set_name(0x80093C18, "__6Dialog_addr_80093C18", SN_NOWARN)
set_name(0x80093C74, "switchnight__FP4TASK", SN_NOWARN)
set_name(0x80093CC0, "city_lights__FP4TASK", SN_NOWARN)
set_name(0x80093E14, "color_cycle__FP4TASK", SN_NOWARN)
set_name(0x80093F58, "ReInitDFL__Fv", SN_NOWARN)
set_name(0x80093F90, "DrawFlameLogo__Fv", SN_NOWARN)
set_name(0x80094334, "TitleScreen__FP7CScreen", SN_NOWARN)
set_name(0x80094388, "TryCreaturePrint__Fiiiiiii", SN_NOWARN)
set_name(0x800945EC, "TryWater__FiiP8POLY_GT4i", SN_NOWARN)
set_name(0x800947C4, "nightgfx__FibiP8POLY_GT4i", SN_NOWARN)
set_name(0x80094850, "PRIM_GetCopy__FP8POLY_FT4_addr_80094850", SN_NOWARN)
set_name(0x8009488C, "PRIM_CopyPrim__FP8POLY_FT4T0_addr_8009488C", SN_NOWARN)
set_name(0x800948B4, "PRIM_GetPrim__FPP8POLY_FT4_addr_800948B4", SN_NOWARN)
set_name(0x80094930, "GetNumOfActions__7TextDati_addr_80094930", SN_NOWARN)
set_name(0x80094954, "GetCreature__7TextDati_addr_80094954", SN_NOWARN)
set_name(0x800949CC, "GetNumOfCreatures__7TextDat_addr_800949CC", SN_NOWARN)
set_name(0x800949E0, "DaveLDummyPoll__Fv", SN_NOWARN)
set_name(0x800949E8, "DaveL__Fv", SN_NOWARN)
set_name(0x80094A10, "DoReflection__FP8POLY_FT4iii", SN_NOWARN)
set_name(0x80094CFC, "mteleportfx__Fv", SN_NOWARN)
set_name(0x80094FFC, "invistimer__Fv", SN_NOWARN)
set_name(0x800950D4, "setUVparams__FP8POLY_FT4P9FRAME_HDR", SN_NOWARN)
set_name(0x80095164, "drawparticle__Fiiiiii", SN_NOWARN)
set_name(0x80095354, "drawpolyF4__Fiiiiii", SN_NOWARN)
set_name(0x80095488, "drawpolyG4__Fiiiiiiii", SN_NOWARN)
set_name(0x80095658, "particlejump__Fv", SN_NOWARN)
set_name(0x80095808, "particleglow__Fv", SN_NOWARN)
set_name(0x800958FC, "doparticlejump__Fv", SN_NOWARN)
set_name(0x8009593C, "StartPartJump__Fiiiiii", SN_NOWARN)
set_name(0x80095AA4, "doparticlechain__Fiiiiiiiiiiii", SN_NOWARN)
set_name(0x80095EA0, "ParticleBlob__FP13MissileStructiiii", SN_NOWARN)
set_name(0x80095F38, "ParticleMissile__FP13MissileStructiiii", SN_NOWARN)
set_name(0x80095FF8, "Teleportfx__Fiiiiiiii", SN_NOWARN)
set_name(0x800962EC, "ResurrectFX__Fiiii", SN_NOWARN)
set_name(0x80096514, "ParticleExp__FP13MissileStructiiii", SN_NOWARN)
set_name(0x800965B0, "GetPlrPos__11SPELLFX_DATP12PlayerStruct", SN_NOWARN)
set_name(0x800966D4, "healFX__Fv", SN_NOWARN)
set_name(0x80096810, "HealStart__Fi", SN_NOWARN)
set_name(0x80096844, "HealotherStart__Fi", SN_NOWARN)
set_name(0x8009687C, "TeleStart__Fi", SN_NOWARN)
set_name(0x800968D8, "PhaseStart__Fi", SN_NOWARN)
set_name(0x8009690C, "PhaseEnd__Fi", SN_NOWARN)
set_name(0x80096938, "ApocInit__11SPELLFX_DATP12PlayerStruct", SN_NOWARN)
set_name(0x80096B14, "ApocaStart__Fi", SN_NOWARN)
set_name(0x80096B6C, "DaveLTask__FP4TASK", SN_NOWARN)
set_name(0x80096C08, "PRIM_GetPrim__FPP7POLY_G4", SN_NOWARN)
set_name(0x80096C84, "PRIM_GetPrim__FPP7POLY_F4", SN_NOWARN)
set_name(0x80096D00, "PRIM_GetPrim__FPP8POLY_FT4_addr_80096D00", SN_NOWARN)
set_name(0x80096D7C, "GetPlayer__7CPlayeri", SN_NOWARN)
set_name(0x80096DCC, "GetLastOtPos__C7CPlayer", SN_NOWARN)
set_name(0x80096DD8, "GetFr__7TextDati_addr_80096DD8", SN_NOWARN)
set_name(0x80096DF4, "DrawArrow__Fii", SN_NOWARN)
set_name(0x80096FF8, "show_spell_dir__Fi", SN_NOWARN)
set_name(0x80097490, "release_spell__Fi", SN_NOWARN)
set_name(0x80097504, "select_belt_item__Fi", SN_NOWARN)
set_name(0x8009750C, "any_belt_items__Fv", SN_NOWARN)
set_name(0x80097574, "get_last_inv__Fv", SN_NOWARN)
set_name(0x800976A4, "get_next_inv__Fv", SN_NOWARN)
set_name(0x800977DC, "pad_func_up__Fi", SN_NOWARN)
set_name(0x80097808, "pad_func_down__Fi", SN_NOWARN)
set_name(0x80097834, "pad_func_left__Fi", SN_NOWARN)
set_name(0x8009783C, "pad_func_right__Fi", SN_NOWARN)
set_name(0x80097844, "pad_func_select__Fi", SN_NOWARN)
set_name(0x80097900, "pad_func_Attack__Fi", SN_NOWARN)
set_name(0x80097D8C, "pad_func_Action__Fi", SN_NOWARN)
set_name(0x800980D8, "InitTargetCursor__Fi", SN_NOWARN)
set_name(0x800981E0, "RemoveTargetCursor__Fi", SN_NOWARN)
set_name(0x80098270, "pad_func_Cast_Spell__Fi", SN_NOWARN)
set_name(0x80098670, "pad_func_Use_Item__Fi", SN_NOWARN)
set_name(0x80098730, "pad_func_Chr__Fi", SN_NOWARN)
set_name(0x80098838, "pad_func_Inv__Fi", SN_NOWARN)
set_name(0x80098930, "pad_func_SplBook__Fi", SN_NOWARN)
set_name(0x80098A1C, "pad_func_QLog__Fi", SN_NOWARN)
set_name(0x80098AA0, "pad_func_SpellBook__Fi", SN_NOWARN)
set_name(0x80098B38, "pad_func_AutoMap__Fi", SN_NOWARN)
set_name(0x80098BF4, "pad_func_Quick_Spell__Fi", SN_NOWARN)
set_name(0x80098C70, "check_inv__FiPci", SN_NOWARN)
set_name(0x80098E38, "pad_func_Quick_Use_Health__Fi", SN_NOWARN)
set_name(0x80098E60, "pad_func_Quick_Use_Mana__Fi", SN_NOWARN)
set_name(0x80098E88, "get_max_find_size__FPici", SN_NOWARN)
set_name(0x80098FC8, "sort_gold__Fi", SN_NOWARN)
set_name(0x800990D4, "DrawObjSelector__Fi", SN_NOWARN)
set_name(0x80099954, "DrawObjTask__FP4TASK", SN_NOWARN)
set_name(0x80099A30, "add_area_find_object__Fciii", SN_NOWARN)
set_name(0x80099B3C, "CheckRangeObject__Fiici", SN_NOWARN)
set_name(0x80099EFC, "CheckArea__FiiicUci", SN_NOWARN)
set_name(0x8009A1D4, "PlacePlayer__FiiiUc", SN_NOWARN)
set_name(0x8009A3F8, "_GLOBAL__D_gplayer", SN_NOWARN)
set_name(0x8009A420, "_GLOBAL__I_gplayer", SN_NOWARN)
set_name(0x8009A448, "SetRGB__6DialogUcUcUc_addr_8009A448", SN_NOWARN)
set_name(0x8009A468, "SetBack__6Dialogi_addr_8009A468", SN_NOWARN)
set_name(0x8009A470, "SetBorder__6Dialogi_addr_8009A470", SN_NOWARN)
set_name(0x8009A478, "___6Dialog_addr_8009A478", SN_NOWARN)
set_name(0x8009A4A0, "__6Dialog_addr_8009A4A0", SN_NOWARN)
set_name(0x8009A4FC, "GetTick__C4CPad_addr_8009A4FC", SN_NOWARN)
set_name(0x8009A524, "GetDown__C4CPad_addr_8009A524", SN_NOWARN)
set_name(0x8009A54C, "GetCur__C4CPad_addr_8009A54C", SN_NOWARN)
set_name(0x8009A574, "SetPadTickMask__4CPadUs_addr_8009A574", SN_NOWARN)
set_name(0x8009A57C, "SetPadTick__4CPadUs_addr_8009A57C", SN_NOWARN)
set_name(0x8009A584, "DEC_AddAsDecRequestor__FP7TextDat", SN_NOWARN)
set_name(0x8009A600, "DEC_RemoveAsDecRequestor__FP7TextDat", SN_NOWARN)
set_name(0x8009A658, "DEC_DoDecompRequests__Fv", SN_NOWARN)
set_name(0x8009A6B4, "FindThisTd__FP7TextDat", SN_NOWARN)
set_name(0x8009A6EC, "FindEmptyIndex__Fv", SN_NOWARN)
set_name(0x8009A724, "UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009A784, "IsGameLoading__Fv", SN_NOWARN)
set_name(0x8009A790, "PutUpCutScreenTSK__FP4TASK", SN_NOWARN)
set_name(0x8009AC04, "PutUpCutScreen__Fi", SN_NOWARN)
set_name(0x8009ACC4, "TakeDownCutScreen__Fv", SN_NOWARN)
set_name(0x8009AD50, "FinishProgress__Fv", SN_NOWARN)
set_name(0x8009ADB4, "PRIM_GetPrim__FPP7POLY_G4_addr_8009ADB4", SN_NOWARN)
set_name(0x8009AE30, "_GLOBAL__D_UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009AE68, "_GLOBAL__I_UPDATEPROGRESS__Fi", SN_NOWARN)
set_name(0x8009AEA0, "SetRGB__6DialogUcUcUc_addr_8009AEA0", SN_NOWARN)
set_name(0x8009AEC0, "SetBack__6Dialogi_addr_8009AEC0", SN_NOWARN)
set_name(0x8009AEC8, "SetBorder__6Dialogi_addr_8009AEC8", SN_NOWARN)
set_name(0x8009AED0, "___6Dialog_addr_8009AED0", SN_NOWARN)
set_name(0x8009AEF8, "__6Dialog_addr_8009AEF8", SN_NOWARN)
set_name(0x8009AF54, "___7CScreen", SN_NOWARN)
set_name(0x8009AF74, "init_mem_card__FPFii_vUc", SN_NOWARN)
set_name(0x8009B1AC, "memcard_event__Fii", SN_NOWARN)
set_name(0x8009B1B4, "init_card__Fib", SN_NOWARN)
set_name(0x8009B274, "ping_card__Fi", SN_NOWARN)
set_name(0x8009B308, "CardUpdateTask__FP4TASK", SN_NOWARN)
set_name(0x8009B340, "MemcardON__Fv", SN_NOWARN)
set_name(0x8009B3B0, "MemcardOFF__Fv", SN_NOWARN)
set_name(0x8009B400, "CheckSavedOptions__Fv", SN_NOWARN)
set_name(0x8009B488, "card_removed__Fi", SN_NOWARN)
set_name(0x8009B4B0, "read_card_block__Fii", SN_NOWARN)
set_name(0x8009B4F8, "test_hw_event__Fv", SN_NOWARN)
set_name(0x8009B578, "PrintSelectBack__FbT0", SN_NOWARN)
set_name(0x8009B6F8, "DrawDialogBox__FiiP4RECTiiii", SN_NOWARN)
set_name(0x8009B7DC, "DrawSpinner__FiiUcUcUciiibiT8", SN_NOWARN)
set_name(0x8009BCD0, "DrawMenu__Fi", SN_NOWARN)
set_name(0x8009C960, "who_pressed__Fi", SN_NOWARN)
set_name(0x8009C9E8, "ShowCharacterFiles__Fv", SN_NOWARN)
set_name(0x8009CFEC, "MemcardPad__Fv", SN_NOWARN)
set_name(0x8009D664, "SoundPad__Fv", SN_NOWARN)
set_name(0x8009DE80, "CentrePad__Fv", SN_NOWARN)
set_name(0x8009E2D8, "CalcVolumes__Fv", SN_NOWARN)
set_name(0x8009E410, "SetLoadedVolumes__Fv", SN_NOWARN)
set_name(0x8009E498, "GetVolumes__Fv", SN_NOWARN)
set_name(0x8009E534, "PrintInfoMenu__Fv", SN_NOWARN)
set_name(0x8009E6DC, "SeedPad__Fv", SN_NOWARN)
set_name(0x8009E960, "DrawOptions__FP4TASK", SN_NOWARN)
set_name(0x8009F234, "ToggleOptions__Fv", SN_NOWARN)
set_name(0x8009F2EC, "FormatPad__Fv", SN_NOWARN)
set_name(0x8009F61C, "ActivateMemcard__Fv", SN_NOWARN)
set_name(0x8009F6A0, "PRIM_GetPrim__FPP7POLY_G4_addr_8009F6A0", SN_NOWARN)
set_name(0x8009F71C, "GetTick__C4CPad_addr_8009F71C", SN_NOWARN)
set_name(0x8009F744, "GetDown__C4CPad_addr_8009F744", SN_NOWARN)
set_name(0x8009F76C, "GetUp__C4CPad_addr_8009F76C", SN_NOWARN)
set_name(0x8009F794, "SetPadTickMask__4CPadUs_addr_8009F794", SN_NOWARN)
set_name(0x8009F79C, "SetPadTick__4CPadUs_addr_8009F79C", SN_NOWARN)
set_name(0x8009F7A4, "Flush__4CPad_addr_8009F7A4", SN_NOWARN)
set_name(0x8009F7C8, "SetRGB__6DialogUcUcUc_addr_8009F7C8", SN_NOWARN)
set_name(0x8009F7E8, "SetBack__6Dialogi_addr_8009F7E8", SN_NOWARN)
set_name(0x8009F7F0, "SetBorder__6Dialogi_addr_8009F7F0", SN_NOWARN)
set_name(0x8009F7F8, "___6Dialog_addr_8009F7F8", SN_NOWARN)
set_name(0x8009F820, "__6Dialog_addr_8009F820", SN_NOWARN)
set_name(0x8009F87C, "GetFr__7TextDati_addr_8009F87C", SN_NOWARN)
set_name(0x8009F898, "BirdDistanceOK__Fiiii", SN_NOWARN)
set_name(0x8009F8F0, "AlterBirdPos__FP10BIRDSTRUCTUc", SN_NOWARN)
set_name(0x8009FA34, "BirdWorld__FP10BIRDSTRUCTii", SN_NOWARN)
set_name(0x8009FAB0, "BirdScared__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FC3C, "GetPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FC90, "BIRD_StartHop__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FDF8, "BIRD_DoHop__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FEFC, "BIRD_StartPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FF68, "BIRD_DoPerch__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x8009FFEC, "BIRD_DoScatter__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0098, "CheckDirOk__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A01A8, "BIRD_StartScatter__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0254, "BIRD_StartFly__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A02F8, "BIRD_DoFly__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A05A4, "BIRD_StartLanding__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A05FC, "BIRD_DoLanding__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0668, "PlaceFlock__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0754, "ProcessFlock__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0884, "InitBird__Fv", SN_NOWARN)
set_name(0x800A095C, "ProcessBird__Fv", SN_NOWARN)
set_name(0x800A0AB4, "GetBirdFrame__FP10BIRDSTRUCT", SN_NOWARN)
set_name(0x800A0B50, "bscale__FP8POLY_FT4i", SN_NOWARN)
set_name(0x800A0C80, "doshadow__FP10BIRDSTRUCTii", SN_NOWARN)
set_name(0x800A0D8C, "DrawLBird__Fv", SN_NOWARN)
set_name(0x800A0F98, "PRIM_GetPrim__FPP8POLY_FT4_addr_800A0F98", SN_NOWARN)
set_name(0x800A1014, "PlayFMV__FPcii", SN_NOWARN)
set_name(0x800A10E8, "play_movie", SN_NOWARN)
set_name(0x800A11A4, "DisplayMonsterTypes__Fv", SN_NOWARN)
set_name(0x800A1640, "GetDown__C4CPad_addr_800A1640", SN_NOWARN)
set_name(0x800A1668, "GetNumOfFrames__7TextDatii_addr_800A1668", SN_NOWARN)
set_name(0x800A16A0, "GetCreature__7TextDati_addr_800A16A0", SN_NOWARN)
set_name(0x800A1718, "GetNumOfCreatures__7TextDat_addr_800A1718", SN_NOWARN)
set_name(0x800A172C, "GetFr__7TextDati_addr_800A172C", SN_NOWARN)
set_name(0x800A1748, "LoadKanjiFont__FPc", SN_NOWARN)
set_name(0x800A1838, "LoadKanjiIndex__FPc", SN_NOWARN)
set_name(0x800A1948, "FreeKanji__Fv", SN_NOWARN)
set_name(0x800A19D0, "LoadKanji__F10LANG_DB_NO", SN_NOWARN)
set_name(0x800A1AA4, "getb__FUs", SN_NOWARN)
set_name(0x800A1B14, "_get_font__FPUsUsUs", SN_NOWARN)
set_name(0x800A1BE4, "KPrintChar__FUsUsUcUcUs", SN_NOWARN)
set_name(0x800A1D50, "PRIM_GetPrim__FPP8POLY_FT4_addr_800A1D50", SN_NOWARN)
set_name(0x800A1DCC, "writeblock__FP5block", SN_NOWARN)
set_name(0x800A1EB4, "PAK_DoPak__FPUcT0i", SN_NOWARN)
set_name(0x800A20F4, "PAK_DoUnpak__FPUcT0", SN_NOWARN)
set_name(0x800A2194, "fputc__5blockUc", SN_NOWARN)
set_name(0x800A21BC, "HelpPad__Fv", SN_NOWARN)
set_name(0x800A22C4, "InitHelp__Fv", SN_NOWARN)
set_name(0x800A2308, "GetControlKey__FiPb", SN_NOWARN)
set_name(0x800A23B0, "CheckStr__FPcT0i", SN_NOWARN)
set_name(0x800A2484, "DisplayHelp__Fv", SN_NOWARN)
set_name(0x800A2848, "DrawHelp__Fv", SN_NOWARN)
set_name(0x800A28E4, "_GLOBAL__D_DrawHelp__Fv", SN_NOWARN)
set_name(0x800A290C, "_GLOBAL__I_DrawHelp__Fv", SN_NOWARN)
set_name(0x800A2934, "SetRGB__6DialogUcUcUc_addr_800A2934", SN_NOWARN)
set_name(0x800A2954, "SetBorder__6Dialogi_addr_800A2954", SN_NOWARN)
set_name(0x800A295C, "___6Dialog_addr_800A295C", SN_NOWARN)
set_name(0x800A2984, "__6Dialog_addr_800A2984", SN_NOWARN)
set_name(0x800A29E0, "GetCharWidth__5CFontc_addr_800A29E0", SN_NOWARN)
set_name(0x800A2A38, "GetFr__7TextDati_addr_800A2A38", SN_NOWARN)
set_name(0x800A2A54, "GetTick__C4CPad_addr_800A2A54", SN_NOWARN)
set_name(0x800A2A7C, "GetDown__C4CPad_addr_800A2A7C", SN_NOWARN)
set_name(0x800A2AA4, "SetPadTickMask__4CPadUs_addr_800A2AA4", SN_NOWARN)
set_name(0x800A2AAC, "SetPadTick__4CPadUs_addr_800A2AAC", SN_NOWARN)
set_name(0x8002E8B0, "TrimCol__Fs_addr_8002E8B0", SN_NOWARN)
set_name(0x8002E8E8, "DrawSpellCel__FllUclUc", SN_NOWARN)
set_name(0x8002F408, "SetSpellTrans__Fc", SN_NOWARN)
set_name(0x8002F414, "DrawSpellBookTSK__FP4TASK", SN_NOWARN)
set_name(0x8002F4B0, "DrawSpeedSpellTSK__FP4TASK", SN_NOWARN)
set_name(0x8002F554, "ToggleSpell__Fi", SN_NOWARN)
set_name(0x8002F608, "DrawSpellList__Fv", SN_NOWARN)
set_name(0x800301CC, "SetSpell__Fi", SN_NOWARN)
set_name(0x800302A0, "AddPanelString__FPCci", SN_NOWARN)
set_name(0x80030350, "ClearPanel__Fv", SN_NOWARN)
set_name(0x80030380, "InitPanelStr__Fv", SN_NOWARN)
set_name(0x800303A0, "InitControlPan__Fv", SN_NOWARN)
set_name(0x800305C0, "DrawCtrlPan__Fv", SN_NOWARN)
set_name(0x800305EC, "DoAutoMap__Fv", SN_NOWARN)
set_name(0x80030660, "CheckPanelInfo__Fv", SN_NOWARN)
set_name(0x80030D80, "FreeControlPan__Fv", SN_NOWARN)
set_name(0x80030E90, "CPrintString__FiPci", SN_NOWARN)
set_name(0x80030FAC, "PrintInfo__Fv", SN_NOWARN)
set_name(0x80031268, "DrawInfoBox__FP4RECT", SN_NOWARN)
set_name(0x8003191C, "MY_PlrStringXY__Fv", SN_NOWARN)
set_name(0x80031E6C, "ADD_PlrStringXY__FPCcc", SN_NOWARN)
set_name(0x80031F14, "DrawPlus__Fii", SN_NOWARN)
set_name(0x8003207C, "ChrCheckValidButton__Fi", SN_NOWARN)
set_name(0x80032158, "DrawArrows__Fv", SN_NOWARN)
set_name(0x80032250, "BuildChr__Fv", SN_NOWARN)
set_name(0x80033528, "DrawChr__Fv", SN_NOWARN)
set_name(0x80033984, "DrawChrTSK__FP4TASK", SN_NOWARN)
set_name(0x80033A68, "DrawLevelUpIcon__Fi", SN_NOWARN)
set_name(0x80033AFC, "CheckChrBtns__Fv", SN_NOWARN)
set_name(0x80033E68, "DrawDurIcon4Item__FPC10ItemStructii", SN_NOWARN)
set_name(0x80033EEC, "RedBack__Fv", SN_NOWARN)
set_name(0x80033FD4, "PrintSBookStr__FiiUcPCcUc", SN_NOWARN)
set_name(0x8003406C, "GetSBookTrans__FiUc", SN_NOWARN)
set_name(0x80034284, "DrawSpellBook__Fv", SN_NOWARN)
set_name(0x80034C60, "CheckSBook__Fv", SN_NOWARN)
set_name(0x80034E94, "get_pieces_str__Fi", SN_NOWARN)
set_name(0x80034EC8, "_GLOBAL__D_DrawLevelUpFlag", SN_NOWARN)
set_name(0x80034EF0, "_GLOBAL__I_DrawLevelUpFlag", SN_NOWARN)
set_name(0x80034F2C, "GetTick__C4CPad_addr_80034F2C", SN_NOWARN)
set_name(0x80034F54, "GetDown__C4CPad_addr_80034F54", SN_NOWARN)
set_name(0x80034F7C, "SetPadTickMask__4CPadUs_addr_80034F7C", SN_NOWARN)
set_name(0x80034F84, "SetPadTick__4CPadUs_addr_80034F84", SN_NOWARN)
set_name(0x80034F8C, "SetRGB__6DialogUcUcUc_addr_80034F8C", SN_NOWARN)
set_name(0x80034FAC, "SetBack__6Dialogi_addr_80034FAC", SN_NOWARN)
set_name(0x80034FB4, "SetBorder__6Dialogi_addr_80034FB4", SN_NOWARN)
set_name(0x80034FBC, "___6Dialog_addr_80034FBC", SN_NOWARN)
set_name(0x80034FE4, "__6Dialog_addr_80034FE4", SN_NOWARN)
set_name(0x80035040, "GetPal__7TextDati_addr_80035040", SN_NOWARN)
set_name(0x8003505C, "GetFr__7TextDati_addr_8003505C", SN_NOWARN)
set_name(0x80035078, "InitCursor__Fv", SN_NOWARN)
set_name(0x80035080, "FreeCursor__Fv", SN_NOWARN)
set_name(0x80035088, "SetICursor__Fi", SN_NOWARN)
set_name(0x800350E4, "SetCursor__Fi", SN_NOWARN)
set_name(0x80035148, "NewCursor__Fi", SN_NOWARN)
set_name(0x80035168, "InitLevelCursor__Fv", SN_NOWARN)
set_name(0x800351C8, "CheckTown__Fv", SN_NOWARN)
set_name(0x80035454, "CheckRportal__Fv", SN_NOWARN)
set_name(0x800356B4, "CheckCursMove__Fv", SN_NOWARN)
set_name(0x800356BC, "InitDead__Fv", SN_NOWARN)
set_name(0x800358B8, "AddDead__Fiici", SN_NOWARN)
set_name(0x80035900, "FreeGameMem__Fv", SN_NOWARN)
set_name(0x80035950, "start_game__FUi", SN_NOWARN)
set_name(0x800359AC, "free_game__Fv", SN_NOWARN)
set_name(0x80035A20, "LittleStart__FUcUc", SN_NOWARN)
set_name(0x80035AE4, "StartGame__FUcUc", SN_NOWARN)
set_name(0x80035CCC, "run_game_loop__FUi", SN_NOWARN)
set_name(0x80035E3C, "TryIconCurs__Fv", SN_NOWARN)
set_name(0x80036218, "DisableInputWndProc__FUlUilUl", SN_NOWARN)
set_name(0x80036220, "GM_Game__FUlUilUl", SN_NOWARN)
set_name(0x800362D0, "LoadLvlGFX__Fv", SN_NOWARN)
set_name(0x8003636C, "LoadAllGFX__Fv", SN_NOWARN)
set_name(0x8003638C, "CreateLevel__Fi", SN_NOWARN)
set_name(0x80036484, "LoCreateLevel__FPv", SN_NOWARN)
set_name(0x8003660C, "ClearOutDungeonMap__Fv", SN_NOWARN)
set_name(0x800366E8, "LoadGameLevel__FUci", SN_NOWARN)
set_name(0x80037044, "game_logic__Fv", SN_NOWARN)
set_name(0x80037150, "timeout_cursor__FUc", SN_NOWARN)
set_name(0x800371F8, "game_loop__FUc", SN_NOWARN)
set_name(0x80037230, "alloc_plr__Fv", SN_NOWARN)
set_name(0x80037238, "plr_encrypt__FUc", SN_NOWARN)
set_name(0x80037240, "assert_fail__FiPCcT1", SN_NOWARN)
set_name(0x80037260, "assert_fail__FiPCc", SN_NOWARN)
set_name(0x80037280, "app_fatal", SN_NOWARN)
set_name(0x800372B0, "DoMemCardFromFrontEnd__Fv", SN_NOWARN)
set_name(0x800372D8, "DoMemCardFromInGame__Fv", SN_NOWARN)
set_name(0x80037300, "GetActiveTowner__Fi", SN_NOWARN)
set_name(0x80037354, "SetTownerGPtrs__FPUcPPUc", SN_NOWARN)
set_name(0x80037374, "NewTownerAnim__FiPUcii", SN_NOWARN)
set_name(0x800373BC, "InitTownerInfo__FilUciiici", SN_NOWARN)
set_name(0x8003751C, "InitQstSnds__Fi", SN_NOWARN)
set_name(0x800375D4, "InitSmith__Fv", SN_NOWARN)
set_name(0x80037700, "InitBarOwner__Fv", SN_NOWARN)
set_name(0x80037834, "InitTownDead__Fv", SN_NOWARN)
set_name(0x80037964, "InitWitch__Fv", SN_NOWARN)
set_name(0x80037A94, "InitBarmaid__Fv", SN_NOWARN)
set_name(0x80037BC4, "InitBoy__Fv", SN_NOWARN)
set_name(0x80037CFC, "InitHealer__Fv", SN_NOWARN)
set_name(0x80037E2C, "InitTeller__Fv", SN_NOWARN)
set_name(0x80037F5C, "InitDrunk__Fv", SN_NOWARN)
set_name(0x8003808C, "InitCows__Fv", SN_NOWARN)
set_name(0x80038350, "InitTowners__Fv", SN_NOWARN)
set_name(0x800383DC, "FreeTownerGFX__Fv", SN_NOWARN)
set_name(0x80038480, "TownCtrlMsg__Fi", SN_NOWARN)
set_name(0x800385B0, "TownBlackSmith__Fv", SN_NOWARN)
set_name(0x800385E4, "TownBarOwner__Fv", SN_NOWARN)
set_name(0x80038618, "TownDead__Fv", SN_NOWARN)
set_name(0x80038700, "TownHealer__Fv", SN_NOWARN)
set_name(0x80038728, "TownStory__Fv", SN_NOWARN)
set_name(0x80038750, "TownDrunk__Fv", SN_NOWARN)
set_name(0x80038778, "TownBoy__Fv", SN_NOWARN)
set_name(0x800387A0, "TownWitch__Fv", SN_NOWARN)
set_name(0x800387C8, "TownBarMaid__Fv", SN_NOWARN)
set_name(0x800387F0, "TownCow__Fv", SN_NOWARN)
set_name(0x80038818, "ProcessTowners__Fv", SN_NOWARN)
set_name(0x80038A68, "PlrHasItem__FiiRi", SN_NOWARN)
set_name(0x80038B3C, "CowSFX__Fi", SN_NOWARN)
set_name(0x80038C58, "TownerTalk__Fii", SN_NOWARN)
set_name(0x80038C98, "TalkToTowner__Fii", SN_NOWARN)
set_name(0x8003A16C, "effect_is_playing__Fi", SN_NOWARN)
set_name(0x8003A174, "stream_stop__Fv", SN_NOWARN)
set_name(0x8003A1C8, "stream_play__FP4TSFXll", SN_NOWARN)
set_name(0x8003A2B8, "stream_update__Fv", SN_NOWARN)
set_name(0x8003A2C0, "sfx_stop__Fv", SN_NOWARN)
set_name(0x8003A2DC, "InitMonsterSND__Fi", SN_NOWARN)
set_name(0x8003A334, "FreeMonsterSnd__Fv", SN_NOWARN)
set_name(0x8003A33C, "calc_snd_position__FiiPlT2", SN_NOWARN)
set_name(0x8003A440, "PlaySFX_priv__FP4TSFXUcii", SN_NOWARN)
set_name(0x8003A53C, "PlayEffect__Fii", SN_NOWARN)
set_name(0x8003A680, "RndSFX__Fi", SN_NOWARN)
set_name(0x8003A718, "PlaySFX__Fi", SN_NOWARN)
set_name(0x8003A758, "PlaySfxLoc__Fiii", SN_NOWARN)
set_name(0x8003A7AC, "sound_stop__Fv", SN_NOWARN)
set_name(0x8003A844, "sound_update__Fv", SN_NOWARN)
set_name(0x8003A878, "priv_sound_init__FUc", SN_NOWARN)
set_name(0x8003A8BC, "sound_init__Fv", SN_NOWARN)
set_name(0x8003A964, "GetDirection__Fiiii", SN_NOWARN)
set_name(0x8003AA08, "SetRndSeed__Fl", SN_NOWARN)
set_name(0x8003AA18, "GetRndSeed__Fv", SN_NOWARN)
set_name(0x8003AA60, "random__Fil", SN_NOWARN)
set_name(0x8003AACC, "DiabloAllocPtr__FUl", SN_NOWARN)
set_name(0x8003AB18, "mem_free_dbg__FPv", SN_NOWARN)
set_name(0x8003AB68, "LoadFileInMem__FPCcPUl", SN_NOWARN)
set_name(0x8003AB70, "PlayInGameMovie__FPCc", SN_NOWARN)
set_name(0x8003AB78, "Enter__9CCritSect", SN_NOWARN)
set_name(0x8003AB80, "InitDiabloMsg__Fc", SN_NOWARN)
set_name(0x8003AC14, "ClrDiabloMsg__Fv", SN_NOWARN)
set_name(0x8003AC40, "DrawDiabloMsg__Fv", SN_NOWARN)
set_name(0x8003AD4C, "interface_msg_pump__Fv", SN_NOWARN)
set_name(0x8003AD54, "ShowProgress__FUi", SN_NOWARN)
set_name(0x8003B28C, "InitAllItemsUseable__Fv", SN_NOWARN)
set_name(0x8003B2C4, "InitItemGFX__Fv", SN_NOWARN)
set_name(0x8003B2F0, "ItemPlace__Fii", SN_NOWARN)
set_name(0x8003B3B8, "AddInitItems__Fv", SN_NOWARN)
set_name(0x8003B5D0, "InitItems__Fv", SN_NOWARN)
set_name(0x8003B7A8, "CalcPlrItemVals__FiUc", SN_NOWARN)
set_name(0x8003C258, "CalcPlrScrolls__Fi", SN_NOWARN)
set_name(0x8003C5D8, "CalcPlrStaff__FP12PlayerStruct", SN_NOWARN)
set_name(0x8003C674, "CalcSelfItems__Fi", SN_NOWARN)
set_name(0x8003C7D4, "ItemMinStats__FPC12PlayerStructPC10ItemStruct", SN_NOWARN)
set_name(0x8003C820, "CalcPlrItemMin__Fi", SN_NOWARN)
set_name(0x8003C900, "CalcPlrBookVals__Fi", SN_NOWARN)
set_name(0x8003CB94, "CalcPlrInv__FiUc", SN_NOWARN)
set_name(0x8003CC58, "SetPlrHandItem__FP10ItemStructi", SN_NOWARN)
set_name(0x8003CD70, "GetPlrHandSeed__FP10ItemStruct", SN_NOWARN)
set_name(0x8003CD9C, "GetGoldSeed__FiP10ItemStruct", SN_NOWARN)
set_name(0x8003CF18, "SetPlrHandSeed__FP10ItemStructi", SN_NOWARN)
set_name(0x8003CF20, "SetPlrHandGoldCurs__FP10ItemStruct", SN_NOWARN)
set_name(0x8003CF50, "CreatePlrItems__Fi", SN_NOWARN)
set_name(0x8003D38C, "ItemSpaceOk__Fii", SN_NOWARN)
set_name(0x8003D664, "GetItemSpace__Fiic", SN_NOWARN)
set_name(0x8003D890, "GetSuperItemSpace__Fiic", SN_NOWARN)
set_name(0x8003D9F8, "GetSuperItemLoc__FiiRiT2", SN_NOWARN)
set_name(0x8003DAC0, "CalcItemValue__Fi", SN_NOWARN)
set_name(0x8003DB78, "GetBookSpell__Fii", SN_NOWARN)
set_name(0x8003DDE0, "GetStaffPower__FiiiUc", SN_NOWARN)
set_name(0x8003DFD0, "GetStaffSpell__FiiUc", SN_NOWARN)
set_name(0x8003E284, "GetItemAttrs__Fiii", SN_NOWARN)
set_name(0x8003E7D0, "RndPL__Fii", SN_NOWARN)
set_name(0x8003E808, "PLVal__Fiiiii", SN_NOWARN)
set_name(0x8003E87C, "SaveItemPower__Fiiiiiii", SN_NOWARN)
set_name(0x8003FFA8, "GetItemPower__FiiilUc", SN_NOWARN)
set_name(0x80040410, "GetItemBonus__FiiiiUc", SN_NOWARN)
set_name(0x8004050C, "SetupItem__Fi", SN_NOWARN)
set_name(0x80040614, "RndItem__Fi", SN_NOWARN)
set_name(0x80040858, "RndUItem__Fi", SN_NOWARN)
set_name(0x80040A98, "RndAllItems__Fv", SN_NOWARN)
set_name(0x80040C0C, "RndTypeItems__Fii", SN_NOWARN)
set_name(0x80040D0C, "CheckUnique__FiiiUc", SN_NOWARN)
set_name(0x80040EBC, "GetUniqueItem__Fii", SN_NOWARN)
set_name(0x80041164, "SpawnUnique__Fiii", SN_NOWARN)
set_name(0x8004129C, "ItemRndDur__Fi", SN_NOWARN)
set_name(0x8004132C, "SetupAllItems__FiiiiiUcUcUc", SN_NOWARN)
set_name(0x80041638, "SpawnItem__FiiiUc", SN_NOWARN)
set_name(0x80041880, "CreateItem__Fiii", SN_NOWARN)
set_name(0x800419B0, "CreateRndItem__FiiUcUcUc", SN_NOWARN)
set_name(0x80041AF8, "SetupAllUseful__Fiii", SN_NOWARN)
set_name(0x80041BD0, "CreateRndUseful__FiiiUc", SN_NOWARN)
set_name(0x80041C90, "CreateTypeItem__FiiUciiUcUc", SN_NOWARN)
set_name(0x80041DD4, "RecreateEar__FiUsiUciiiiii", SN_NOWARN)
set_name(0x80041FC0, "SpawnQuestItem__Fiiiii", SN_NOWARN)
set_name(0x80042234, "SpawnRock__Fv", SN_NOWARN)
set_name(0x800423F4, "RespawnItem__FiUc", SN_NOWARN)
set_name(0x800425AC, "DeleteItem__Fii", SN_NOWARN)
set_name(0x80042600, "ItemDoppel__Fv", SN_NOWARN)
set_name(0x800426C8, "ProcessItems__Fv", SN_NOWARN)
set_name(0x800428D0, "FreeItemGFX__Fv", SN_NOWARN)
set_name(0x800428D8, "GetItemStr__Fi", SN_NOWARN)
set_name(0x80042A80, "CheckIdentify__Fii", SN_NOWARN)
set_name(0x80042B70, "RepairItem__FP10ItemStructi", SN_NOWARN)
set_name(0x80042C40, "DoRepair__Fii", SN_NOWARN)
set_name(0x80042D04, "RechargeItem__FP10ItemStructi", SN_NOWARN)
set_name(0x80042D74, "DoRecharge__Fii", SN_NOWARN)
set_name(0x80042E74, "PrintItemOil__Fc", SN_NOWARN)
set_name(0x80042F68, "PrintItemPower__FcPC10ItemStruct", SN_NOWARN)
set_name(0x80043624, "PrintUString__FiiUcPcc", SN_NOWARN)
set_name(0x8004362C, "PrintItemMisc__FPC10ItemStruct", SN_NOWARN)
set_name(0x800437B8, "PrintItemDetails__FPC10ItemStruct", SN_NOWARN)
set_name(0x80043B28, "PrintItemDur__FPC10ItemStruct", SN_NOWARN)
set_name(0x80043E38, "CastScroll__Fii", SN_NOWARN)
set_name(0x80043E50, "UseItem__Fiii", SN_NOWARN)
set_name(0x80044468, "StoreStatOk__FP10ItemStruct", SN_NOWARN)
set_name(0x800444FC, "PremiumItemOk__Fi", SN_NOWARN)
set_name(0x80044578, "RndPremiumItem__Fii", SN_NOWARN)
set_name(0x80044680, "SpawnOnePremium__Fii", SN_NOWARN)
set_name(0x800448A0, "SpawnPremium__Fi", SN_NOWARN)
set_name(0x80044AE4, "WitchBookLevel__Fi", SN_NOWARN)
set_name(0x80044C34, "SpawnStoreGold__Fv", SN_NOWARN)
set_name(0x80044CB8, "RecalcStoreStats__Fv", SN_NOWARN)
set_name(0x80044E58, "ItemNoFlippy__Fv", SN_NOWARN)
set_name(0x80044EBC, "CreateSpellBook__FiiiUcUc", SN_NOWARN)
set_name(0x8004504C, "CreateMagicArmor__FiiiiUcUc", SN_NOWARN)
set_name(0x800451C8, "CreateMagicWeapon__FiiiiUcUc", SN_NOWARN)
set_name(0x80045344, "DrawUniqueInfo__Fv", SN_NOWARN)
set_name(0x800454B8, "MakeItemStr__FP10ItemStructUsUs", SN_NOWARN)
set_name(0x800456B8, "veclen2__Fii", SN_NOWARN)
set_name(0x80045720, "set_light_bands__Fv", SN_NOWARN)
set_name(0x8004579C, "SetLightFX__FiisssUcUcUc", SN_NOWARN)
set_name(0x80045808, "DoLighting__Fiiii", SN_NOWARN)
set_name(0x800464B8, "DoUnLight__Fv", SN_NOWARN)
set_name(0x80046700, "DoUnVision__Fiii", SN_NOWARN)
set_name(0x800467C4, "DoVision__FiiiUcUc", SN_NOWARN)
set_name(0x80046CD4, "FreeLightTable__Fv", SN_NOWARN)
set_name(0x80046CDC, "InitLightTable__Fv", SN_NOWARN)
set_name(0x80046CE4, "MakeLightTable__Fv", SN_NOWARN)
set_name(0x80046CEC, "InitLightMax__Fv", SN_NOWARN)
set_name(0x80046D10, "InitLighting__Fv", SN_NOWARN)
set_name(0x80046D54, "AddLight__Fiii", SN_NOWARN)
set_name(0x80046DC0, "AddUnLight__Fi", SN_NOWARN)
set_name(0x80046DF0, "ChangeLightRadius__Fii", SN_NOWARN)
set_name(0x80046E1C, "ChangeLightXY__Fiii", SN_NOWARN)
set_name(0x80046E58, "light_fix__Fi", SN_NOWARN)
set_name(0x80046E60, "ChangeLightOff__Fiii", SN_NOWARN)
set_name(0x80046E94, "ChangeLight__Fiiii", SN_NOWARN)
set_name(0x80046ECC, "ChangeLightColour__Fii", SN_NOWARN)
set_name(0x80046EF4, "ProcessLightList__Fv", SN_NOWARN)
set_name(0x80047018, "SavePreLighting__Fv", SN_NOWARN)
set_name(0x80047020, "InitVision__Fv", SN_NOWARN)
set_name(0x80047070, "AddVision__FiiiUc", SN_NOWARN)
set_name(0x800470EC, "ChangeVisionRadius__Fii", SN_NOWARN)
set_name(0x800471A0, "ChangeVisionXY__Fiii", SN_NOWARN)
set_name(0x80047220, "ProcessVisionList__Fv", SN_NOWARN)
set_name(0x80047420, "FreeQuestText__Fv", SN_NOWARN)
set_name(0x80047428, "InitQuestText__Fv", SN_NOWARN)
set_name(0x80047434, "CalcTextSpeed__FPCc", SN_NOWARN)
set_name(0x80047588, "InitQTextMsg__Fi", SN_NOWARN)
set_name(0x80047730, "DrawQTextBack__Fv", SN_NOWARN)
set_name(0x800477A0, "DrawQTextTSK__FP4TASK", SN_NOWARN)
set_name(0x800478E0, "DrawQText__Fv", SN_NOWARN)
set_name(0x80047C4C, "_GLOBAL__D_QBack", SN_NOWARN)
set_name(0x80047C74, "_GLOBAL__I_QBack", SN_NOWARN)
set_name(0x80047C9C, "SetRGB__6DialogUcUcUc_addr_80047C9C", SN_NOWARN)
set_name(0x80047CBC, "SetBorder__6Dialogi_addr_80047CBC", SN_NOWARN)
set_name(0x80047CC4, "___6Dialog_addr_80047CC4", SN_NOWARN)
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set_name(0x80047D48, "GetCharWidth__5CFontc_addr_80047D48", SN_NOWARN)
set_name(0x80047DA0, "GetDown__C4CPad_addr_80047DA0", SN_NOWARN)
set_name(0x80047DC8, "GetFr__7TextDati_addr_80047DC8", SN_NOWARN)
set_name(0x80047DE4, "nullmissile__Fiiiiiicii", SN_NOWARN)
set_name(0x80047DEC, "FuncNULL__FP13MissileStructiii", SN_NOWARN)
set_name(0x80047DF4, "delta_init__Fv", SN_NOWARN)
set_name(0x80047E54, "delta_kill_monster__FiUcUcUc", SN_NOWARN)
set_name(0x80047EF0, "delta_monster_hp__FilUc", SN_NOWARN)
set_name(0x80047F74, "delta_sync_golem__FPC9TCmdGolemiUc", SN_NOWARN)
set_name(0x80048004, "delta_leave_sync__FUc", SN_NOWARN)
set_name(0x80048330, "delta_sync_object__FiUcUc", SN_NOWARN)
set_name(0x80048390, "delta_get_item__FPC9TCmdGItemUc", SN_NOWARN)
set_name(0x80048554, "delta_put_item__FPC9TCmdPItemiiUc", SN_NOWARN)
set_name(0x800486DC, "delta_portal_inited__Fi", SN_NOWARN)
set_name(0x80048700, "delta_quest_inited__Fi", SN_NOWARN)
set_name(0x80048724, "DeltaAddItem__Fi", SN_NOWARN)
set_name(0x80048938, "DeltaExportData__FPc", SN_NOWARN)
set_name(0x800489E0, "DeltaImportData__FPc", SN_NOWARN)
set_name(0x80048A8C, "DeltaSaveLevel__Fv", SN_NOWARN)
set_name(0x80048B88, "NetSendCmd__FUcUc", SN_NOWARN)
set_name(0x80048BB0, "NetSendCmdGolem__FUcUcUcUclUc", SN_NOWARN)
set_name(0x80048BFC, "NetSendCmdLoc__FUcUcUcUc", SN_NOWARN)
set_name(0x80048C2C, "NetSendCmdLocParam1__FUcUcUcUcUs", SN_NOWARN)
set_name(0x80048C64, "NetSendCmdLocParam2__FUcUcUcUcUsUs", SN_NOWARN)
set_name(0x80048CA4, "NetSendCmdLocParam3__FUcUcUcUcUsUsUs", SN_NOWARN)
set_name(0x80048CEC, "NetSendCmdParam1__FUcUcUs", SN_NOWARN)
set_name(0x80048D18, "NetSendCmdParam2__FUcUcUsUs", SN_NOWARN)
set_name(0x80048D48, "NetSendCmdParam3__FUcUcUsUsUs", SN_NOWARN)
set_name(0x80048D80, "NetSendCmdQuest__FUcUc", SN_NOWARN)
set_name(0x80048DF4, "NetSendCmdGItem__FUcUcUcUcUc", SN_NOWARN)
set_name(0x80048F28, "NetSendCmdGItem2__FUcUcUcUcPC9TCmdGItem", SN_NOWARN)
set_name(0x80048FA4, "NetSendCmdReq2__FUcUcUcPC9TCmdGItem", SN_NOWARN)
set_name(0x80048FFC, "NetSendCmdExtra__FPC9TCmdGItem", SN_NOWARN)
set_name(0x80049064, "NetSendCmdPItem__FUcUcUcUc", SN_NOWARN)
set_name(0x8004916C, "NetSendCmdChItem__FUcUc", SN_NOWARN)
set_name(0x80049210, "NetSendCmdDelItem__FUcUc", SN_NOWARN)
set_name(0x80049240, "NetSendCmdDItem__FUci", SN_NOWARN)
set_name(0x80049354, "i_own_level__Fi", SN_NOWARN)
set_name(0x8004935C, "NetSendCmdDamage__FUcUcUl", SN_NOWARN)
set_name(0x80049390, "delta_open_portal__FiUcUcUcUcUc", SN_NOWARN)
set_name(0x800493EC, "delta_close_portal__Fi", SN_NOWARN)
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set_name(0x800494B4, "On_ADDSTR__FPC4TCmdi", SN_NOWARN)
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set_name(0x80049544, "On_ADDVIT__FPC4TCmdi", SN_NOWARN)
set_name(0x80049574, "On_SBSPELL__FPC4TCmdi", SN_NOWARN)
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set_name(0x80049670, "On_REQUESTGITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x800497B0, "On_GETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049980, "On_GOTOAGETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049A08, "On_REQUESTAGITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049B3C, "On_AGETITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049D04, "On_ITEMEXTRA__FPC4TCmdi", SN_NOWARN)
set_name(0x80049D50, "On_PUTITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049E68, "On_SYNCPUTITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049F68, "On_RESPAWNITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x80049FC0, "On_SATTACKXY__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004A2E8, "On_OPOBJXY__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004A6F0, "On_SPELLPID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A7B0, "On_TSPELLID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A874, "On_TSPELLPID__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A938, "On_KNOCKBACK__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A980, "On_RESURRECT__FPC4TCmdi", SN_NOWARN)
set_name(0x8004A9B8, "On_HEALOTHER__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004AA98, "On_WARP__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AB8C, "On_MONSTDEATH__FPC4TCmdi", SN_NOWARN)
set_name(0x8004ABF8, "On_KILLGOLEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AC64, "On_AWAKEGOLEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AD7C, "On_MONSTDAMAGE__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AE68, "On_PLRDEAD__FPC4TCmdi", SN_NOWARN)
set_name(0x8004AEB0, "On_PLRDAMAGE__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004B2EC, "On_DROPITEM__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B344, "On_PLAYER_JOINLEVEL__FPC4TCmdi", SN_NOWARN)
set_name(0x8004B5BC, "On_ACTIVATEPORTAL__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004B8E4, "On_SYNCQUEST__FPC4TCmdi", SN_NOWARN)
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set_name(0x8004C644, "PostAddArmorStand__Fi", SN_NOWARN)
set_name(0x8004C6CC, "PostTorchLocOK__Fii", SN_NOWARN)
set_name(0x8004C70C, "PostAddObjLight__Fii", SN_NOWARN)
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set_name(0x8004E4F4, "ProcessObjects__Fv", SN_NOWARN)
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set_name(0x8004E8DC, "ObjL1Special__Fiiii", SN_NOWARN)
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set_name(0x8004E8EC, "DoorSet__Fiii", SN_NOWARN)
set_name(0x8004EB6C, "RedoPlayerVision__Fv", SN_NOWARN)
set_name(0x8004EC10, "OperateL1RDoor__FiiUc", SN_NOWARN)
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set_name(0x8004FABC, "OperateL3RDoor__FiiUc", SN_NOWARN)
set_name(0x8004FDC4, "OperateL3LDoor__FiiUc", SN_NOWARN)
set_name(0x800500CC, "MonstCheckDoors__Fi", SN_NOWARN)
set_name(0x800505C8, "PostAddL1Objs__Fiiii", SN_NOWARN)
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set_name(0x80050814, "ObjChangeMap__Fiiii", SN_NOWARN)
set_name(0x800509CC, "DRLG_MRectTrans__Fiiii", SN_NOWARN)
set_name(0x80050A78, "ObjChangeMapResync__Fiiii", SN_NOWARN)
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set_name(0x80050D58, "OperateLever__Fii", SN_NOWARN)
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set_name(0x80053474, "OperateShrine__Fiii", SN_NOWARN)
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set_name(0x80055EAC, "OperateArmorStand__FiiUc", SN_NOWARN)
set_name(0x8005601C, "FindValidShrine__Fi", SN_NOWARN)
set_name(0x8005610C, "OperateGoatShrine__Fiii", SN_NOWARN)
set_name(0x800561B4, "OperateCauldron__Fiii", SN_NOWARN)
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set_name(0x80056804, "OperateWeaponRack__FiiUc", SN_NOWARN)
set_name(0x800569B0, "OperateStoryBook__Fii", SN_NOWARN)
set_name(0x80056AA0, "OperateLazStand__Fii", SN_NOWARN)
set_name(0x80056C04, "OperateObject__FiiUc", SN_NOWARN)
set_name(0x8005703C, "SyncOpL1Door__Fiii", SN_NOWARN)
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set_name(0x80057264, "SyncOpL3Door__Fiii", SN_NOWARN)
set_name(0x80057378, "SyncOpObject__Fiii", SN_NOWARN)
set_name(0x80057578, "BreakCrux__Fi", SN_NOWARN)
set_name(0x80057768, "BreakBarrel__FiiiUcUc", SN_NOWARN)
set_name(0x80057CBC, "BreakObject__Fii", SN_NOWARN)
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set_name(0x80057E78, "SyncL1Doors__Fi", SN_NOWARN)
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set_name(0x80058E7C, "FindPath__FPFiii_UciiiiiPc", SN_NOWARN)
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set_name(0x80059704, "NextPlrLevel__FP12PlayerStruct", SN_NOWARN)
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set_name(0x80059A80, "AddPlrMonstExper__Filc", SN_NOWARN)
set_name(0x80059B04, "InitPlayer__FP12PlayerStructUc", SN_NOWARN)
set_name(0x80059EA4, "InitMultiView__Fv", SN_NOWARN)
set_name(0x80059EAC, "CheckLeighSolid__Fii", SN_NOWARN)
set_name(0x80059F44, "SolidLoc__Fii", SN_NOWARN)
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set_name(0x8005A060, "PlrDoTrans__Fii", SN_NOWARN)
set_name(0x8005A154, "SetPlayerOld__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A168, "StartStand__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A1F4, "StartWalkStand__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A258, "PM_ChangeLightOff__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A294, "PM_ChangeOffset__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A2C0, "StartAttack__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A3F8, "StartPlrBlock__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005A490, "StartSpell__FP12PlayerStructiii", SN_NOWARN)
set_name(0x8005A62C, "RemovePlrFromMap__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005A74C, "StartPlrHit__FP12PlayerStructiUc", SN_NOWARN)
set_name(0x8005A86C, "RespawnDeadItem__FP10ItemStructii", SN_NOWARN)
set_name(0x8005AA08, "PlrDeadItem__FP12PlayerStructP10ItemStructii", SN_NOWARN)
set_name(0x8005ABD0, "StartPlayerKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005AED8, "DropHalfPlayersGold__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B320, "StartPlrKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005B478, "SyncPlrKill__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005B498, "RemovePlrMissiles__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B780, "InitLevelChange__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005B844, "StartNewLvl__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005B988, "RestartTownLvl__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BA18, "StartWarpLvl__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005BAD4, "PM_DoStand__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BADC, "ChkPlrOffsets__Fiiii", SN_NOWARN)
set_name(0x8005BB64, "PM_DoWalk__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005BED0, "WeaponDur__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005C070, "PlrHitMonst__FP12PlayerStructi", SN_NOWARN)
set_name(0x8005C6A0, "PlrHitPlr__FP12PlayerStructc", SN_NOWARN)
set_name(0x8005CA50, "PlrHitObj__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005CAE0, "PM_DoAttack__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005CE6C, "PM_DoRangeAttack__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005CF6C, "ShieldDur__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005D030, "PM_DoBlock__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005D0D0, "do_spell_anim__FiiiP12PlayerStruct", SN_NOWARN)
set_name(0x8005E094, "PM_DoSpell__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E3D4, "ArmorDur__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E4D4, "PM_DoGotHit__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E550, "PM_DoDeath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E690, "PM_DoNewLvl__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005E698, "CheckNewPath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005EAD8, "PlrDeathModeOK__Fi", SN_NOWARN)
set_name(0x8005EB40, "ValidatePlayer__Fv", SN_NOWARN)
set_name(0x8005F028, "CheckCheatStats__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005F0C4, "ProcessPlayers__Fv", SN_NOWARN)
set_name(0x8005F3F8, "ClrPlrPath__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005F420, "PosOkPlayer__FP12PlayerStructii", SN_NOWARN)
set_name(0x8005F5C8, "MakePlrPath__FP12PlayerStructiiUc", SN_NOWARN)
set_name(0x8005F5D0, "CheckPlrSpell__Fv", SN_NOWARN)
set_name(0x8005F9E0, "SyncInitPlrPos__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005FB08, "SyncInitPlr__FP12PlayerStruct", SN_NOWARN)
set_name(0x8005FB38, "CheckStats__Fi", SN_NOWARN)
set_name(0x8005FCD4, "ModifyPlrStr__Fii", SN_NOWARN)
set_name(0x8005FDF0, "ModifyPlrMag__Fii", SN_NOWARN)
set_name(0x8005FEDC, "ModifyPlrDex__Fii", SN_NOWARN)
set_name(0x8005FFC0, "ModifyPlrVit__Fii", SN_NOWARN)
set_name(0x8006009C, "SetPlayerHitPoints__FP12PlayerStructi", SN_NOWARN)
set_name(0x800600E0, "SetPlrStr__Fii", SN_NOWARN)
set_name(0x800601BC, "SetPlrMag__Fii", SN_NOWARN)
set_name(0x8006022C, "SetPlrDex__Fii", SN_NOWARN)
set_name(0x80060308, "SetPlrVit__Fii", SN_NOWARN)
set_name(0x80060374, "InitDungMsgs__FP12PlayerStruct", SN_NOWARN)
set_name(0x8006037C, "PlayDungMsgs__Fv", SN_NOWARN)
set_name(0x800606AC, "CreatePlrItems__FP12PlayerStruct", SN_NOWARN)
set_name(0x800606D4, "WorldToOffset__FP12PlayerStructii", SN_NOWARN)
set_name(0x80060718, "SetSpdbarGoldCurs__FP12PlayerStructi", SN_NOWARN)
set_name(0x8006074C, "GetSpellLevel__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060780, "BreakObject__FP12PlayerStructi", SN_NOWARN)
set_name(0x800607B4, "CalcPlrInv__FP12PlayerStructUc", SN_NOWARN)
set_name(0x800607E8, "RemoveSpdBarItem__FP12PlayerStructi", SN_NOWARN)
set_name(0x8006081C, "M_StartKill__FiP12PlayerStruct", SN_NOWARN)
set_name(0x80060854, "SetGoldCurs__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060888, "HealStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x800608B0, "HealotherStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x800608D8, "CalculateGold__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060900, "M_StartHit__FiP12PlayerStructi", SN_NOWARN)
set_name(0x80060948, "TeleStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060970, "PhaseStart__FP12PlayerStruct", SN_NOWARN)
set_name(0x80060998, "RemoveInvItem__FP12PlayerStructi", SN_NOWARN)
set_name(0x800609CC, "PhaseEnd__FP12PlayerStruct", SN_NOWARN)
set_name(0x800609F4, "OperateObject__FP12PlayerStructiUc", SN_NOWARN)
set_name(0x80060A38, "TryDisarm__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060A6C, "TalkToTowner__FP12PlayerStructi", SN_NOWARN)
set_name(0x80060AA0, "PosOkPlayer__Fiii", SN_NOWARN)
set_name(0x80060AEC, "CalcStatDiff__Fi", SN_NOWARN)
set_name(0x80060B38, "StartNewLvl__Fiii", SN_NOWARN)
set_name(0x80060B84, "CreatePlayer__Fic", SN_NOWARN)
set_name(0x80060BD8, "StartStand__Fii", SN_NOWARN)
set_name(0x80060C24, "SetPlayerHitPoints__Fii", SN_NOWARN)
set_name(0x80060C70, "MakePlrPath__FiiiUc", SN_NOWARN)
set_name(0x80060CC0, "StartWarpLvl__Fii", SN_NOWARN)
set_name(0x80060D0C, "SyncPlrKill__Fii", SN_NOWARN)
set_name(0x80060D58, "StartPlrKill__Fii", SN_NOWARN)
set_name(0x80060DA4, "NewPlrAnim__Fiiii", SN_NOWARN)
set_name(0x80060DF0, "AddPlrExperience__Fiil", SN_NOWARN)
set_name(0x80060E3C, "StartPlrBlock__Fii", SN_NOWARN)
set_name(0x80060E88, "StartPlrHit__FiiUc", SN_NOWARN)
set_name(0x80060ED8, "StartSpell__Fiiii", SN_NOWARN)
set_name(0x80060F24, "InitPlayer__FiUc", SN_NOWARN)
set_name(0x80060F74, "PM_ChangeLightOff__Fi", SN_NOWARN)
set_name(0x80060FC0, "CheckNewPath__Fi", SN_NOWARN)
set_name(0x8006100C, "FreePlayerGFX__Fi", SN_NOWARN)
set_name(0x80061058, "InitDungMsgs__Fi", SN_NOWARN)
set_name(0x800610A4, "InitPlayerGFX__Fi", SN_NOWARN)
set_name(0x800610F0, "SyncInitPlrPos__Fi", SN_NOWARN)
set_name(0x8006113C, "SetPlrAnims__Fi", SN_NOWARN)
set_name(0x80061188, "ClrPlrPath__Fi", SN_NOWARN)
set_name(0x800611D4, "SyncInitPlr__Fi", SN_NOWARN)
set_name(0x80061220, "RestartTownLvl__Fi", SN_NOWARN)
set_name(0x8006126C, "SetPlayerOld__Fi", SN_NOWARN)
set_name(0x800612B8, "GetGoldSeed__FP12PlayerStructP10ItemStruct", SN_NOWARN)
set_name(0x800612EC, "PRIM_GetPrim__FPP8POLY_FT4_addr_800612EC", SN_NOWARN)
set_name(0x80061368, "GetPlayer__7CPlayeri_addr_80061368", SN_NOWARN)
set_name(0x800613B8, "GetLastOtPos__C7CPlayer_addr_800613B8", SN_NOWARN)
set_name(0x800613C4, "GetLastScrY__C7CPlayer", SN_NOWARN)
set_name(0x800613D0, "GetLastScrX__C7CPlayer", SN_NOWARN)
set_name(0x800613DC, "TSK_Lava2Water__FP4TASK", SN_NOWARN)
set_name(0x80061628, "CheckQuests__Fv", SN_NOWARN)
set_name(0x80061ADC, "ForceQuests__Fv", SN_NOWARN)
set_name(0x80061C80, "QuestStatus__Fi", SN_NOWARN)
set_name(0x80061D14, "CheckQuestKill__FiUc", SN_NOWARN)
set_name(0x800622F4, "SetReturnLvlPos__Fv", SN_NOWARN)
set_name(0x80062404, "GetReturnLvlPos__Fv", SN_NOWARN)
set_name(0x80062458, "ResyncMPQuests__Fv", SN_NOWARN)
set_name(0x80062594, "ResyncQuests__Fv", SN_NOWARN)
set_name(0x80062AF4, "PrintQLString__FiiUcPcc", SN_NOWARN)
set_name(0x80062D20, "DrawQuestLog__Fv", SN_NOWARN)
set_name(0x80062EE8, "DrawQuestLogTSK__FP4TASK", SN_NOWARN)
set_name(0x80062F80, "StartQuestlog__Fv", SN_NOWARN)
set_name(0x80063098, "QuestlogUp__Fv", SN_NOWARN)
set_name(0x800630EC, "QuestlogDown__Fv", SN_NOWARN)
set_name(0x80063158, "RemoveQLog__Fv", SN_NOWARN)
set_name(0x800631D0, "QuestlogEnter__Fv", SN_NOWARN)
set_name(0x80063294, "QuestlogESC__Fv", SN_NOWARN)
set_name(0x800632BC, "SetMultiQuest__FiiUci", SN_NOWARN)
set_name(0x8006333C, "_GLOBAL__D_questlog", SN_NOWARN)
set_name(0x80063364, "_GLOBAL__I_questlog", SN_NOWARN)
set_name(0x8006338C, "GetBlockTexDat__7CBlocks", SN_NOWARN)
set_name(0x80063398, "SetRGB__6DialogUcUcUc_addr_80063398", SN_NOWARN)
set_name(0x800633B8, "SetBack__6Dialogi_addr_800633B8", SN_NOWARN)
set_name(0x800633C0, "SetBorder__6Dialogi_addr_800633C0", SN_NOWARN)
set_name(0x800633C8, "___6Dialog_addr_800633C8", SN_NOWARN)
set_name(0x800633F0, "__6Dialog_addr_800633F0", SN_NOWARN)
set_name(0x8006344C, "GetPal__7TextDati_addr_8006344C", SN_NOWARN)
set_name(0x80063468, "GetFr__7TextDati_addr_80063468", SN_NOWARN)
set_name(0x80063484, "DrawView__Fii", SN_NOWARN)
set_name(0x8006364C, "DrawAndBlit__Fv", SN_NOWARN)
set_name(0x80063778, "FreeStoreMem__Fv", SN_NOWARN)
set_name(0x80063780, "DrawSTextBack__Fv", SN_NOWARN)
set_name(0x800637F0, "PrintSString__FiiUcPcci", SN_NOWARN)
set_name(0x80063BE4, "DrawSLine__Fi", SN_NOWARN)
set_name(0x80063C78, "ClearSText__Fii", SN_NOWARN)
set_name(0x80063D10, "AddSLine__Fi", SN_NOWARN)
set_name(0x80063D60, "AddSTextVal__Fii", SN_NOWARN)
set_name(0x80063D88, "AddSText__FiiUcPccUc", SN_NOWARN)
set_name(0x80063E3C, "PrintStoreItem__FPC10ItemStructic", SN_NOWARN)
set_name(0x800642C4, "StoreAutoPlace__Fv", SN_NOWARN)
set_name(0x800648E4, "S_StartSmith__Fv", SN_NOWARN)
set_name(0x80064A6C, "S_ScrollSBuy__Fi", SN_NOWARN)
set_name(0x80064C24, "S_StartSBuy__Fv", SN_NOWARN)
set_name(0x80064D54, "S_ScrollSPBuy__Fi", SN_NOWARN)
set_name(0x80064F74, "S_StartSPBuy__Fv", SN_NOWARN)
set_name(0x800650C4, "SmithSellOk__Fi", SN_NOWARN)
set_name(0x800651A8, "S_ScrollSSell__Fi", SN_NOWARN)
set_name(0x800653D0, "S_StartSSell__Fv", SN_NOWARN)
set_name(0x80065800, "SmithRepairOk__Fi", SN_NOWARN)
set_name(0x800658A4, "AddStoreHoldRepair__FP10ItemStructi", SN_NOWARN)
set_name(0x80065A84, "S_StartSRepair__Fv", SN_NOWARN)
set_name(0x80065F54, "S_StartWitch__Fv", SN_NOWARN)
set_name(0x80066094, "S_ScrollWBuy__Fi", SN_NOWARN)
set_name(0x8006626C, "S_StartWBuy__Fv", SN_NOWARN)
set_name(0x80066398, "WitchSellOk__Fi", SN_NOWARN)
set_name(0x800664BC, "S_StartWSell__Fv", SN_NOWARN)
set_name(0x80066B14, "WitchRechargeOk__Fi", SN_NOWARN)
set_name(0x80066B9C, "AddStoreHoldRecharge__FG10ItemStructi", SN_NOWARN)
set_name(0x80066D1C, "S_StartWRecharge__Fv", SN_NOWARN)
set_name(0x8006713C, "S_StartNoMoney__Fv", SN_NOWARN)
set_name(0x800671A4, "S_StartNoRoom__Fv", SN_NOWARN)
set_name(0x80067204, "S_StartConfirm__Fv", SN_NOWARN)
set_name(0x8006757C, "S_StartBoy__Fv", SN_NOWARN)
set_name(0x8006770C, "S_StartBBoy__Fv", SN_NOWARN)
set_name(0x80067894, "S_StartHealer__Fv", SN_NOWARN)
set_name(0x80067A68, "S_ScrollHBuy__Fi", SN_NOWARN)
set_name(0x80067BD4, "S_StartHBuy__Fv", SN_NOWARN)
set_name(0x80067CF4, "S_StartStory__Fv", SN_NOWARN)
set_name(0x80067DE4, "IdItemOk__FP10ItemStruct", SN_NOWARN)
set_name(0x80067E18, "AddStoreHoldId__FG10ItemStructi", SN_NOWARN)
set_name(0x80067EEC, "S_StartSIdentify__Fv", SN_NOWARN)
set_name(0x8006894C, "S_StartIdShow__Fv", SN_NOWARN)
set_name(0x80068B20, "S_StartTalk__Fv", SN_NOWARN)
set_name(0x80068D50, "S_StartTavern__Fv", SN_NOWARN)
set_name(0x80068E48, "S_StartBarMaid__Fv", SN_NOWARN)
set_name(0x80068F1C, "S_StartDrunk__Fv", SN_NOWARN)
set_name(0x80068FF0, "StartStore__Fc", SN_NOWARN)
set_name(0x800692D8, "DrawSText__Fv", SN_NOWARN)
set_name(0x80069318, "DrawSTextTSK__FP4TASK", SN_NOWARN)
set_name(0x800693E0, "DoThatDrawSText__Fv", SN_NOWARN)
set_name(0x8006958C, "STextESC__Fv", SN_NOWARN)
set_name(0x80069700, "STextUp__Fv", SN_NOWARN)
set_name(0x80069898, "STextDown__Fv", SN_NOWARN)
set_name(0x80069A48, "S_SmithEnter__Fv", SN_NOWARN)
set_name(0x80069B1C, "SetGoldCurs__Fii", SN_NOWARN)
set_name(0x80069B98, "SetSpdbarGoldCurs__Fii", SN_NOWARN)
set_name(0x80069C14, "TakePlrsMoney__Fl", SN_NOWARN)
set_name(0x8006A060, "SmithBuyItem__Fv", SN_NOWARN)
set_name(0x8006A254, "S_SBuyEnter__Fv", SN_NOWARN)
set_name(0x8006A478, "SmithBuyPItem__Fv", SN_NOWARN)
set_name(0x8006A600, "S_SPBuyEnter__Fv", SN_NOWARN)
set_name(0x8006A830, "StoreGoldFit__Fi", SN_NOWARN)
set_name(0x8006AAE8, "PlaceStoreGold__Fl", SN_NOWARN)
set_name(0x8006AD4C, "StoreSellItem__Fv", SN_NOWARN)
set_name(0x8006B040, "S_SSellEnter__Fv", SN_NOWARN)
set_name(0x8006B144, "SmithRepairItem__Fv", SN_NOWARN)
set_name(0x8006B3B4, "S_SRepairEnter__Fv", SN_NOWARN)
set_name(0x8006B510, "S_WitchEnter__Fv", SN_NOWARN)
set_name(0x8006B5C0, "WitchBuyItem__Fv", SN_NOWARN)
set_name(0x8006B7C0, "S_WBuyEnter__Fv", SN_NOWARN)
set_name(0x8006B9AC, "S_WSellEnter__Fv", SN_NOWARN)
set_name(0x8006BAB0, "WitchRechargeItem__Fv", SN_NOWARN)
set_name(0x8006BC28, "S_WRechargeEnter__Fv", SN_NOWARN)
set_name(0x8006BD84, "S_BoyEnter__Fv", SN_NOWARN)
set_name(0x8006BEBC, "BoyBuyItem__Fv", SN_NOWARN)
set_name(0x8006BF40, "HealerBuyItem__Fv", SN_NOWARN)
set_name(0x8006C1E4, "S_BBuyEnter__Fv", SN_NOWARN)
set_name(0x8006C3CC, "StoryIdItem__Fv", SN_NOWARN)
set_name(0x8006C718, "S_ConfirmEnter__Fv", SN_NOWARN)
set_name(0x8006C834, "S_HealerEnter__Fv", SN_NOWARN)
set_name(0x8006C8CC, "S_HBuyEnter__Fv", SN_NOWARN)
set_name(0x8006CAD8, "S_StoryEnter__Fv", SN_NOWARN)
set_name(0x8006CB70, "S_SIDEnter__Fv", SN_NOWARN)
set_name(0x8006CCEC, "S_TalkEnter__Fv", SN_NOWARN)
set_name(0x8006CEE4, "S_TavernEnter__Fv", SN_NOWARN)
set_name(0x8006CF54, "S_BarmaidEnter__Fv", SN_NOWARN)
set_name(0x8006CFC4, "S_DrunkEnter__Fv", SN_NOWARN)
set_name(0x8006D034, "STextEnter__Fv", SN_NOWARN)
set_name(0x8006D1F8, "CheckStoreBtn__Fv", SN_NOWARN)
set_name(0x8006D2D0, "ReleaseStoreBtn__Fv", SN_NOWARN)
set_name(0x8006D2E4, "_GLOBAL__D_pSTextBoxCels", SN_NOWARN)
set_name(0x8006D30C, "_GLOBAL__I_pSTextBoxCels", SN_NOWARN)
set_name(0x8006D334, "GetDown__C4CPad_addr_8006D334", SN_NOWARN)
set_name(0x8006D35C, "SetRGB__6DialogUcUcUc_addr_8006D35C", SN_NOWARN)
set_name(0x8006D37C, "SetBorder__6Dialogi_addr_8006D37C", SN_NOWARN)
set_name(0x8006D384, "___6Dialog_addr_8006D384", SN_NOWARN)
set_name(0x8006D3AC, "__6Dialog_addr_8006D3AC", SN_NOWARN)
set_name(0x8006D408, "T_DrawView__Fii", SN_NOWARN)
set_name(0x8006D5B8, "T_FillSector__FPUcT0iiiib", SN_NOWARN)
set_name(0x8006D7B0, "T_FillTile__FPUciii", SN_NOWARN)
set_name(0x8006D8A0, "T_Pass3__Fv", SN_NOWARN)
set_name(0x8006DC60, "CreateTown__Fi", SN_NOWARN)
set_name(0x8006DDC8, "GRL_LoadFileInMemSig__FPCcPUl", SN_NOWARN)
set_name(0x8006DEAC, "GRL_StripDir__FPcPCc", SN_NOWARN)
set_name(0x8006DF44, "InitVPTriggers__Fv", SN_NOWARN)
set_name(0x8006DF8C, "ForceTownTrig__Fv", SN_NOWARN)
set_name(0x8006E2A4, "ForceL1Trig__Fv", SN_NOWARN)
set_name(0x8006E554, "ForceL2Trig__Fv", SN_NOWARN)
set_name(0x8006E9B4, "ForceL3Trig__Fv", SN_NOWARN)
set_name(0x8006EE30, "ForceL4Trig__Fv", SN_NOWARN)
set_name(0x8006F33C, "Freeupstairs__Fv", SN_NOWARN)
set_name(0x8006F3FC, "ForceSKingTrig__Fv", SN_NOWARN)
set_name(0x8006F4F0, "ForceSChambTrig__Fv", SN_NOWARN)
set_name(0x8006F5E4, "ForcePWaterTrig__Fv", SN_NOWARN)
set_name(0x8006F6D8, "CheckTrigForce__Fv", SN_NOWARN)
set_name(0x8006F9E0, "FadeGameOut__Fv", SN_NOWARN)
set_name(0x8006FA7C, "IsTrigger__Fii", SN_NOWARN)
set_name(0x8006FAE0, "CheckTriggers__Fi", SN_NOWARN)
set_name(0x8006FFFC, "GetManaAmount__Fii", SN_NOWARN)
set_name(0x800702C4, "UseMana__Fii", SN_NOWARN)
set_name(0x80070408, "CheckSpell__FiicUc", SN_NOWARN)
set_name(0x800704A8, "CastSpell__Fiiiiiiii", SN_NOWARN)
set_name(0x80070754, "DoResurrect__Fii", SN_NOWARN)
set_name(0x80070A08, "DoHealOther__Fii", SN_NOWARN)
set_name(0x80070C6C, "snd_update__FUc", SN_NOWARN)
set_name(0x80070C74, "snd_get_volume__FPCcPl", SN_NOWARN)
set_name(0x80070CDC, "snd_stop_snd__FP4TSnd", SN_NOWARN)
set_name(0x80070CFC, "snd_play_snd__FP4TSFXll", SN_NOWARN)
set_name(0x80070D5C, "snd_play_msnd__FUsll", SN_NOWARN)
set_name(0x80070DEC, "snd_init__FUl", SN_NOWARN)
set_name(0x80070E3C, "music_stop__Fv", SN_NOWARN)
set_name(0x80070E80, "music_fade__Fv", SN_NOWARN)
set_name(0x80070EC0, "music_start__Fi", SN_NOWARN)
set_name(0x80070F44, "music_hold__Fv", SN_NOWARN)
set_name(0x80070FA4, "music_release__Fv", SN_NOWARN)
set_name(0x80070FF4, "snd_playing__Fi", SN_NOWARN)
set_name(0x80071014, "ClrCursor__Fi", SN_NOWARN)
set_name(0x80071064, "flyabout__7GamePad", SN_NOWARN)
set_name(0x80071520, "CloseInvChr__Fv", SN_NOWARN)
set_name(0x80071570, "LeftOf__Fi", SN_NOWARN)
set_name(0x80071588, "RightOf__Fi", SN_NOWARN)
set_name(0x800715A4, "WorldToOffset__Fiii", SN_NOWARN)
set_name(0x80071650, "pad_UpIsUpRight__Fic", SN_NOWARN)
set_name(0x80071714, "__7GamePadi", SN_NOWARN)
set_name(0x80071808, "SetMoveStyle__7GamePadc", SN_NOWARN)
set_name(0x80071810, "SetDownButton__7GamePadiPFi_v", SN_NOWARN)
set_name(0x80071854, "SetComboDownButton__7GamePadiPFi_v", SN_NOWARN)
set_name(0x80071898, "SetAllButtons__7GamePadP11KEY_ASSIGNS", SN_NOWARN)
set_name(0x80071AF8, "GetAllButtons__7GamePadP11KEY_ASSIGNS", SN_NOWARN)
set_name(0x80071CA8, "GetActionButton__7GamePadPFi_v", SN_NOWARN)
set_name(0x80071D04, "SetUpAction__7GamePadPFi_vT1", SN_NOWARN)
set_name(0x80071D40, "RunFunc__7GamePadi", SN_NOWARN)
set_name(0x80071E04, "ButtonDown__7GamePadi", SN_NOWARN)
set_name(0x80072210, "TestButtons__7GamePad", SN_NOWARN)
set_name(0x80072354, "CheckCentre__FP12PlayerStructi", SN_NOWARN)
set_name(0x80072448, "CheckDirs__7GamePadi", SN_NOWARN)
set_name(0x80072560, "CheckSide__7GamePadi", SN_NOWARN)
set_name(0x800725B4, "CheckBodge__7GamePadi", SN_NOWARN)
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set_name(0x8007B988, "VER_GetVerString__Fv", SN_NOWARN)
set_name(0x8007B998, "CharPair2Num__FPc", SN_NOWARN)
set_name(0x8001E6A8, "TICK_InitModule", SN_NOWARN)
set_name(0x8001E6C8, "TICK_Set", SN_NOWARN)
set_name(0x8001E6D8, "TICK_Get", SN_NOWARN)
set_name(0x8001E6E8, "TICK_Update", SN_NOWARN)
set_name(0x8001E708, "TICK_GetAge", SN_NOWARN)
set_name(0x8001E734, "TICK_GetDateString", SN_NOWARN)
set_name(0x8001E744, "TICK_GetTimeString", SN_NOWARN)
set_name(0x8001E754, "GU_InitModule", SN_NOWARN)
set_name(0x8001E780, "GU_SetRndSeed", SN_NOWARN)
set_name(0x8001E7B0, "GU_GetRnd", SN_NOWARN)
set_name(0x8001E840, "GU_GetSRnd", SN_NOWARN)
set_name(0x8001E860, "GU_GetRndRange", SN_NOWARN)
set_name(0x8001E89C, "GU_AlignVal", SN_NOWARN)
set_name(0x8001E8C0, "main", SN_NOWARN)
set_name(0x8001E910, "DBG_OpenModule", SN_NOWARN)
set_name(0x8001E918, "DBG_PollHost", SN_NOWARN)
set_name(0x8001E920, "DBG_Halt", SN_NOWARN)
set_name(0x8001E928, "DBG_SendMessage", SN_NOWARN)
set_name(0x8001E940, "DBG_SetMessageHandler", SN_NOWARN)
set_name(0x8001E950, "DBG_Error", SN_NOWARN)
set_name(0x8001E97C, "DBG_SetErrorFunc", SN_NOWARN)
set_name(0x8001E98C, "SendPsyqString", SN_NOWARN)
set_name(0x8001E994, "DBG_SetPollRoutine", SN_NOWARN)
set_name(0x8001E9A4, "GTIMSYS_GetTimer", SN_NOWARN)
set_name(0x8001E9C8, "GTIMSYS_ResetTimer", SN_NOWARN)
set_name(0x8001E9EC, "GTIMSYS_InitTimer", SN_NOWARN)
set_name(0x8001EC20, "DoEpi", SN_NOWARN)
set_name(0x8001EC70, "DoPro", SN_NOWARN)
set_name(0x8001ECC0, "TSK_OpenModule", SN_NOWARN)
set_name(0x8001ED34, "TSK_AddTask", SN_NOWARN)
set_name(0x8001EF1C, "TSK_DoTasks", SN_NOWARN)
set_name(0x8001F0DC, "TSK_Sleep", SN_NOWARN)
set_name(0x8001F1B8, "ReturnToSchedulerIfCurrentTask", SN_NOWARN)
set_name(0x8001F240, "TSK_Die", SN_NOWARN)
set_name(0x8001F26C, "TSK_Kill", SN_NOWARN)
set_name(0x8001F2BC, "TSK_GetFirstActive", SN_NOWARN)
set_name(0x8001F2CC, "TSK_IsStackCorrupted", SN_NOWARN)
set_name(0x8001F348, "TSK_JumpAndResetStack", SN_NOWARN)
set_name(0x8001F390, "TSK_RepointProc", SN_NOWARN)
set_name(0x8001F3D4, "TSK_GetCurrentTask", SN_NOWARN)
set_name(0x8001F3E4, "TSK_IsCurrentTask", SN_NOWARN)
set_name(0x8001F3FC, "TSK_Exist", SN_NOWARN)
set_name(0x8001F454, "TSK_SetExecFilter", SN_NOWARN)
set_name(0x8001F46C, "TSK_ClearExecFilter", SN_NOWARN)
set_name(0x8001F490, "TSK_KillTasks", SN_NOWARN)
set_name(0x8001F590, "TSK_IterateTasks", SN_NOWARN)
set_name(0x8001F608, "TSK_MakeTaskInactive", SN_NOWARN)
set_name(0x8001F61C, "TSK_MakeTaskActive", SN_NOWARN)
set_name(0x8001F630, "TSK_MakeTaskImmortal", SN_NOWARN)
set_name(0x8001F644, "TSK_MakeTaskMortal", SN_NOWARN)
set_name(0x8001F658, "TSK_IsTaskActive", SN_NOWARN)
set_name(0x8001F66C, "TSK_IsTaskMortal", SN_NOWARN)
set_name(0x8001F680, "DetachFromList", SN_NOWARN)
set_name(0x8001F6CC, "AddToList", SN_NOWARN)
set_name(0x8001F6EC, "LoTskKill", SN_NOWARN)
set_name(0x8001F75C, "ExecuteTask", SN_NOWARN)
set_name(0x8001F7AC, "TSK_SetDoTasksPrologue", SN_NOWARN)
set_name(0x8001F7C4, "TSK_SetDoTasksEpilogue", SN_NOWARN)
set_name(0x8001F7DC, "TSK_SetTaskPrologue", SN_NOWARN)
set_name(0x8001F7F4, "TSK_SetTaskEpilogue", SN_NOWARN)
set_name(0x8001F80C, "TSK_SetEpiProFilter", SN_NOWARN)
set_name(0x8001F824, "TSK_ClearEpiProFilter", SN_NOWARN)
set_name(0x8001F858, "TSK_SetExtraStackProtection", SN_NOWARN)
set_name(0x8001F868, "TSK_SetStackFloodCallback", SN_NOWARN)
set_name(0x8001F880, "TSK_SetExtraStackSize", SN_NOWARN)
set_name(0x8001F8A8, "ExtraMarkStack", SN_NOWARN)
set_name(0x8001F8D4, "CheckExtraStack", SN_NOWARN)
set_name(0x8001F910, "GSYS_GetWorkMemInfo", SN_NOWARN)
set_name(0x8001F920, "GSYS_SetStackAndJump", SN_NOWARN)
set_name(0x8001F95C, "GSYS_MarkStack", SN_NOWARN)
set_name(0x8001F96C, "GSYS_IsStackCorrupted", SN_NOWARN)
set_name(0x8001F984, "GSYS_InitMachine", SN_NOWARN)
set_name(0x8001F9D8, "GSYS_CheckPtr", SN_NOWARN)
set_name(0x8001FA0C, "GSYS_IsStackOutOfBounds", SN_NOWARN)
set_name(0x8001FA88, "GAL_SetErrorChecking", SN_NOWARN)
set_name(0x8001FA98, "GAL_SplitBlock", SN_NOWARN)
set_name(0x8001FBCC, "GAL_InitModule", SN_NOWARN)
set_name(0x8001FC84, "GAL_AddMemType", SN_NOWARN)
set_name(0x8001FDA4, "GAL_Alloc", SN_NOWARN)
set_name(0x8001FF3C, "GAL_Lock", SN_NOWARN)
set_name(0x8001FF9C, "GAL_Unlock", SN_NOWARN)
set_name(0x80020018, "GAL_Free", SN_NOWARN)
set_name(0x800200B8, "GAL_GetFreeMem", SN_NOWARN)
set_name(0x8002012C, "GAL_GetUsedMem", SN_NOWARN)
set_name(0x800201A0, "GAL_LargestFreeBlock", SN_NOWARN)
set_name(0x8002021C, "AttachHdrToList", SN_NOWARN)
set_name(0x8002023C, "DetachHdrFromList", SN_NOWARN)
set_name(0x80020288, "IsActiveValidHandle", SN_NOWARN)
set_name(0x800202B8, "AlignPtr", SN_NOWARN)
set_name(0x800202E8, "AlignSize", SN_NOWARN)
set_name(0x80020318, "FindClosestSizedBlock", SN_NOWARN)
set_name(0x80020370, "FindHighestMemBlock", SN_NOWARN)
set_name(0x800203D8, "FindLowestMemBlock", SN_NOWARN)
set_name(0x80020440, "GetMemInitInfoBlockFromType", SN_NOWARN)
set_name(0x8002047C, "MergeToEmptyList", SN_NOWARN)
set_name(0x80020550, "GAL_AllocAt", SN_NOWARN)
set_name(0x8002062C, "LoAlloc", SN_NOWARN)
set_name(0x800207C4, "FindBlockInTheseBounds", SN_NOWARN)
set_name(0x80020830, "GetFreeMemHdrBlock", SN_NOWARN)
set_name(0x800208B8, "ReleaseMemHdrBlock", SN_NOWARN)
set_name(0x800208F8, "GAL_IterateEmptyMem", SN_NOWARN)
set_name(0x8002097C, "GAL_IterateUsedMem", SN_NOWARN)
set_name(0x80020A18, "GAL_SetMemName", SN_NOWARN)
set_name(0x80020A80, "GAL_TotalMem", SN_NOWARN)
set_name(0x80020AD4, "GAL_MemBase", SN_NOWARN)
set_name(0x80020B28, "GAL_DefragMem", SN_NOWARN)
set_name(0x80020BAC, "GSetError", SN_NOWARN)
set_name(0x80020C08, "GAL_CheckMem", SN_NOWARN)
set_name(0x80020D04, "CheckCollisions", SN_NOWARN)
set_name(0x80020DB0, "AreBlocksColliding", SN_NOWARN)
set_name(0x80020E08, "GAL_GetErrorText", SN_NOWARN)
set_name(0x80020E38, "GAL_GetLastErrorCode", SN_NOWARN)
set_name(0x80020E48, "GAL_GetLastErrorText", SN_NOWARN)
set_name(0x80020E70, "GAL_HowManyEmptyRegions", SN_NOWARN)
set_name(0x80020ED8, "GAL_HowManyUsedRegions", SN_NOWARN)
set_name(0x80020F40, "GAL_SetTimeStamp", SN_NOWARN)
set_name(0x80020F50, "GAL_IncTimeStamp", SN_NOWARN)
set_name(0x80020F70, "GAL_GetTimeStamp", SN_NOWARN)
set_name(0x80020F80, "GAL_AlignSizeToType", SN_NOWARN)
set_name(0x80020FD0, "GAL_AllocMultiStruct", SN_NOWARN)
set_name(0x80021020, "GAL_ProcessMultiStruct", SN_NOWARN)
set_name(0x800210CC, "GAL_GetSize", SN_NOWARN)
set_name(0x80021120, "GazDefragMem", SN_NOWARN)
set_name(0x80021288, "PutBlocksInRegionIntoList", SN_NOWARN)
set_name(0x8002132C, "CollideRegions", SN_NOWARN)
set_name(0x80021360, "DeleteEmptyBlocks", SN_NOWARN)
set_name(0x800213CC, "GetRegion", SN_NOWARN)
set_name(0x800214C4, "FindNextBlock", SN_NOWARN)
set_name(0x80021500, "ShuffleBlocks", SN_NOWARN)
set_name(0x80021590, "PutAllLockedBlocksOntoList", SN_NOWARN)
set_name(0x8002160C, "SortMemHdrListByAddr", SN_NOWARN)
set_name(0x800216C0, "GraftMemHdrList", SN_NOWARN)
set_name(0x8002171C, "GAL_MemDump", SN_NOWARN)
set_name(0x80021790, "GAL_SetVerbosity", SN_NOWARN)
set_name(0x800217A0, "CountFreeBlocks", SN_NOWARN)
set_name(0x800217CC, "SetBlockName", SN_NOWARN)
set_name(0x80021814, "GAL_GetNumFreeHeaders", SN_NOWARN)
set_name(0x80021824, "GAL_GetLastTypeAlloced", SN_NOWARN)
set_name(0x80021834, "GAL_SetAllocFilter", SN_NOWARN)
set_name(0x8002184C, "GAL_SortUsedRegionsBySize", SN_NOWARN)
set_name(0x800218A0, "SortSize", SN_NOWARN)
set_name(0x800218B0, "SortMemHdrList", SN_NOWARN)
set_name(0x80023C6C, "vsprintf", SN_NOWARN)
set_name(0x80023CB8, "_doprnt", SN_NOWARN)
set_name(0x8012CDC8, "NumOfMonsterListLevels", SN_NOWARN)
set_name(0x800A9BE0, "AllLevels", SN_NOWARN)
set_name(0x8012CAAC, "NumsLEV1M1A", SN_NOWARN)
set_name(0x8012CAB0, "NumsLEV1M1B", SN_NOWARN)
set_name(0x8012CAB4, "NumsLEV1M1C", SN_NOWARN)
set_name(0x8012CABC, "NumsLEV2M2A", SN_NOWARN)
set_name(0x8012CAC0, "NumsLEV2M2B", SN_NOWARN)
set_name(0x8012CAC4, "NumsLEV2M2C", SN_NOWARN)
set_name(0x8012CAC8, "NumsLEV2M2D", SN_NOWARN)
set_name(0x8012CACC, "NumsLEV2M2QA", SN_NOWARN)
set_name(0x8012CAD0, "NumsLEV2M2QB", SN_NOWARN)
set_name(0x8012CAD4, "NumsLEV3M3A", SN_NOWARN)
set_name(0x8012CAD8, "NumsLEV3M3QA", SN_NOWARN)
set_name(0x8012CADC, "NumsLEV3M3B", SN_NOWARN)
set_name(0x8012CAE0, "NumsLEV3M3C", SN_NOWARN)
set_name(0x8012CAE4, "NumsLEV4M4A", SN_NOWARN)
set_name(0x8012CAE8, "NumsLEV4M4QA", SN_NOWARN)
set_name(0x8012CAEC, "NumsLEV4M4B", SN_NOWARN)
set_name(0x8012CAF0, "NumsLEV4M4QB", SN_NOWARN)
set_name(0x8012CAF8, "NumsLEV4M4C", SN_NOWARN)
set_name(0x8012CAFC, "NumsLEV4M4QC", SN_NOWARN)
set_name(0x8012CB04, "NumsLEV4M4D", SN_NOWARN)
set_name(0x8012CB08, "NumsLEV5M5A", SN_NOWARN)
set_name(0x8012CB0C, "NumsLEV5M5B", SN_NOWARN)
set_name(0x8012CB10, "NumsLEV5M5C", SN_NOWARN)
set_name(0x8012CB14, "NumsLEV5M5D", SN_NOWARN)
set_name(0x8012CB18, "NumsLEV5M5E", SN_NOWARN)
set_name(0x8012CB1C, "NumsLEV5M5F", SN_NOWARN)
set_name(0x8012CB20, "NumsLEV5M5QA", SN_NOWARN)
set_name(0x8012CB24, "NumsLEV6M6A", SN_NOWARN)
set_name(0x8012CB2C, "NumsLEV6M6B", SN_NOWARN)
set_name(0x8012CB30, "NumsLEV6M6C", SN_NOWARN)
set_name(0x8012CB34, "NumsLEV6M6D", SN_NOWARN)
set_name(0x8012CB38, "NumsLEV6M6E", SN_NOWARN)
set_name(0x8012CB3C, "NumsLEV6M6QA", SN_NOWARN)
set_name(0x8012CB40, "NumsLEV7M7A", SN_NOWARN)
set_name(0x8012CB44, "NumsLEV7M7B", SN_NOWARN)
set_name(0x8012CB48, "NumsLEV7M7C", SN_NOWARN)
set_name(0x8012CB4C, "NumsLEV7M7D", SN_NOWARN)
set_name(0x8012CB50, "NumsLEV7M7E", SN_NOWARN)
set_name(0x8012CB54, "NumsLEV8M8QA", SN_NOWARN)
set_name(0x8012CB58, "NumsLEV8M8A", SN_NOWARN)
set_name(0x8012CB5C, "NumsLEV8M8B", SN_NOWARN)
set_name(0x8012CB60, "NumsLEV8M8C", SN_NOWARN)
set_name(0x8012CB64, "NumsLEV8M8D", SN_NOWARN)
set_name(0x8012CB68, "NumsLEV8M8E", SN_NOWARN)
set_name(0x8012CB6C, "NumsLEV9M9A", SN_NOWARN)
set_name(0x8012CB70, "NumsLEV9M9B", SN_NOWARN)
set_name(0x8012CB74, "NumsLEV9M9C", SN_NOWARN)
set_name(0x8012CB78, "NumsLEV9M9D", SN_NOWARN)
set_name(0x8012CB7C, "NumsLEV10M10A", SN_NOWARN)
set_name(0x8012CB80, "NumsLEV10M10B", SN_NOWARN)
set_name(0x8012CB84, "NumsLEV10M10C", SN_NOWARN)
set_name(0x8012CB88, "NumsLEV10M10D", SN_NOWARN)
set_name(0x8012CB8C, "NumsLEV10M10QA", SN_NOWARN)
set_name(0x8012CB90, "NumsLEV11M11A", SN_NOWARN)
set_name(0x8012CB94, "NumsLEV11M11B", SN_NOWARN)
set_name(0x8012CB98, "NumsLEV11M11C", SN_NOWARN)
set_name(0x8012CB9C, "NumsLEV11M11D", SN_NOWARN)
set_name(0x8012CBA0, "NumsLEV11M11E", SN_NOWARN)
set_name(0x8012CBA4, "NumsLEV12M12A", SN_NOWARN)
set_name(0x8012CBA8, "NumsLEV12M12B", SN_NOWARN)
set_name(0x8012CBAC, "NumsLEV12M12C", SN_NOWARN)
set_name(0x8012CBB0, "NumsLEV12M12D", SN_NOWARN)
set_name(0x8012CBB4, "NumsLEV13M13A", SN_NOWARN)
set_name(0x8012CBB8, "NumsLEV13M13B", SN_NOWARN)
set_name(0x8012CBBC, "NumsLEV13M13QB", SN_NOWARN)
set_name(0x8012CBC0, "NumsLEV13M13C", SN_NOWARN)
set_name(0x8012CBC4, "NumsLEV13M13D", SN_NOWARN)
set_name(0x8012CBC8, "NumsLEV14M14A", SN_NOWARN)
set_name(0x8012CBCC, "NumsLEV14M14B", SN_NOWARN)
set_name(0x8012CBD0, "NumsLEV14M14QB", SN_NOWARN)
set_name(0x8012CBD4, "NumsLEV14M14C", SN_NOWARN)
set_name(0x8012CBD8, "NumsLEV14M14D", SN_NOWARN)
set_name(0x8012CBDC, "NumsLEV14M14E", SN_NOWARN)
set_name(0x8012CBE0, "NumsLEV15M15A", SN_NOWARN)
set_name(0x8012CBE4, "NumsLEV15M15B", SN_NOWARN)
set_name(0x8012CBE8, "NumsLEV15M15C", SN_NOWARN)
set_name(0x8012CBEC, "NumsLEV15M15QA", SN_NOWARN)
set_name(0x8012CBF0, "NumsLEV16M16D", SN_NOWARN)
set_name(0x800A9700, "ChoiceListLEV1", SN_NOWARN)
set_name(0x800A9730, "ChoiceListLEV2", SN_NOWARN)
set_name(0x800A9790, "ChoiceListLEV3", SN_NOWARN)
set_name(0x800A97D0, "ChoiceListLEV4", SN_NOWARN)
set_name(0x800A9840, "ChoiceListLEV5", SN_NOWARN)
set_name(0x800A98B0, "ChoiceListLEV6", SN_NOWARN)
set_name(0x800A9910, "ChoiceListLEV7", SN_NOWARN)
set_name(0x800A9960, "ChoiceListLEV8", SN_NOWARN)
set_name(0x800A99C0, "ChoiceListLEV9", SN_NOWARN)
set_name(0x800A9A00, "ChoiceListLEV10", SN_NOWARN)
set_name(0x800A9A50, "ChoiceListLEV11", SN_NOWARN)
set_name(0x800A9AA0, "ChoiceListLEV12", SN_NOWARN)
set_name(0x800A9AE0, "ChoiceListLEV13", SN_NOWARN)
set_name(0x800A9B30, "ChoiceListLEV14", SN_NOWARN)
set_name(0x800A9B90, "ChoiceListLEV15", SN_NOWARN)
set_name(0x800A9BD0, "ChoiceListLEV16", SN_NOWARN)
set_name(0x8012E688, "GameTaskPtr", SN_NOWARN)
set_name(0x800A9C60, "AllArgs", SN_NOWARN)
set_name(0x8012CDD8, "ArgsSoFar", SN_NOWARN)
set_name(0x8012CDE8, "ThisOt", SN_NOWARN)
set_name(0x8012CDEC, "ThisPrimAddr", SN_NOWARN)
set_name(0x8012E68C, "hndPrimBuffers", SN_NOWARN)
set_name(0x8012E690, "PrimBuffers", SN_NOWARN)
set_name(0x8012E694, "BufferDepth", SN_NOWARN)
set_name(0x8012E695, "WorkRamId", SN_NOWARN)
set_name(0x8012E696, "ScrNum", SN_NOWARN)
set_name(0x8012E698, "Screens", SN_NOWARN)
set_name(0x8012E69C, "PbToClear", SN_NOWARN)
set_name(0x8012E6A0, "BufferNum", SN_NOWARN)
set_name(0x8012CDF0, "AddrToAvoid", SN_NOWARN)
set_name(0x8012E6A1, "LastBuffer", SN_NOWARN)
set_name(0x8012E6A4, "DispEnvToPut", SN_NOWARN)
set_name(0x8012E6A8, "ThisOtSize", SN_NOWARN)
set_name(0x8012CDF4, "ScrRect", SN_NOWARN)
set_name(0x8012E6AC, "VidWait", SN_NOWARN)
set_name(0x8012EB28, "screen", SN_NOWARN)
set_name(0x8012E6B0, "VbFunc", SN_NOWARN)
set_name(0x8012E6B4, "VidTick", SN_NOWARN)
set_name(0x8012E6B8, "VXOff", SN_NOWARN)
set_name(0x8012E6BC, "VYOff", SN_NOWARN)
set_name(0x8012CE08, "Gaz", SN_NOWARN)
set_name(0x8012CE0C, "LastFmem", SN_NOWARN)
set_name(0x8012CDFC, "GSYS_MemStart", SN_NOWARN)
set_name(0x8012CE00, "GSYS_MemEnd", SN_NOWARN)
set_name(0x800A9FA8, "PsxMem", SN_NOWARN)
set_name(0x800A9FD0, "PsxFastMem", SN_NOWARN)
set_name(0x8012CE04, "LowestFmem", SN_NOWARN)
set_name(0x8012CE1C, "FileSYS", SN_NOWARN)
set_name(0x8012E6C0, "FileSystem", SN_NOWARN)
set_name(0x8012E6C4, "OverlayFileSystem", SN_NOWARN)
set_name(0x8012CE36, "DavesPad", SN_NOWARN)
set_name(0x8012CE38, "DavesPadDeb", SN_NOWARN)
set_name(0x800A9FF8, "_6FileIO_FileToLoad", SN_NOWARN)
set_name(0x8012EC08, "MyFT4", SN_NOWARN)
set_name(0x800AA89C, "AllDats", SN_NOWARN)
set_name(0x8012CE88, "TpW", SN_NOWARN)
set_name(0x8012CE8C, "TpH", SN_NOWARN)
set_name(0x8012CE90, "TpXDest", SN_NOWARN)
set_name(0x8012CE94, "TpYDest", SN_NOWARN)
set_name(0x8012CE98, "R", SN_NOWARN)
set_name(0x800AAE5C, "MyGT4", SN_NOWARN)
set_name(0x800AAE90, "MyGT3", SN_NOWARN)
set_name(0x800AA02C, "DatPool", SN_NOWARN)
set_name(0x8012CEAC, "ChunkGot", SN_NOWARN)
set_name(0x800AAEB8, "STREAM_DIR", SN_NOWARN)
set_name(0x800AAEC8, "STREAM_BIN", SN_NOWARN)
set_name(0x800AAED8, "EAC_DirectoryCache", SN_NOWARN)
set_name(0x8012CEC0, "BL_NoLumpFiles", SN_NOWARN)
set_name(0x8012CEC4, "BL_NoStreamFiles", SN_NOWARN)
set_name(0x8012CEC8, "LFileTab", SN_NOWARN)
set_name(0x8012CECC, "SFileTab", SN_NOWARN)
set_name(0x8012CED0, "FileLoaded", SN_NOWARN)
set_name(0x8012CEF4, "NoTAllocs", SN_NOWARN)
set_name(0x800AB004, "MemBlock", SN_NOWARN)
set_name(0x8012E6D0, "CanPause", SN_NOWARN)
set_name(0x8012E6D4, "Paused", SN_NOWARN)
set_name(0x8012E6D8, "InActivePad", SN_NOWARN)
set_name(0x8012EC30, "PBack", SN_NOWARN)
set_name(0x800AB26C, "RawPadData0", SN_NOWARN)
set_name(0x800AB290, "RawPadData1", SN_NOWARN)
set_name(0x800AB2B4, "demo_buffer", SN_NOWARN)
set_name(0x8012CF10, "demo_pad_time", SN_NOWARN)
set_name(0x8012CF14, "demo_pad_count", SN_NOWARN)
set_name(0x800AB194, "Pad0", SN_NOWARN)
set_name(0x800AB200, "Pad1", SN_NOWARN)
set_name(0x8012CF18, "demo_finish", SN_NOWARN)
set_name(0x8012CF1C, "cac_pad", SN_NOWARN)
set_name(0x8012CF3C, "CharFt4", SN_NOWARN)
set_name(0x8012CF40, "CharFrm", SN_NOWARN)
set_name(0x8012CF29, "WHITER", SN_NOWARN)
set_name(0x8012CF2A, "WHITEG", SN_NOWARN)
set_name(0x8012CF2B, "WHITEB", SN_NOWARN)
set_name(0x8012CF2C, "BLUER", SN_NOWARN)
set_name(0x8012CF2D, "BLUEG", SN_NOWARN)
set_name(0x8012CF2E, "BLUEB", SN_NOWARN)
set_name(0x8012CF2F, "REDR", SN_NOWARN)
set_name(0x8012CF30, "REDG", SN_NOWARN)
set_name(0x8012CF31, "REDB", SN_NOWARN)
set_name(0x8012CF32, "GOLDR", SN_NOWARN)
set_name(0x8012CF33, "GOLDG", SN_NOWARN)
set_name(0x8012CF34, "GOLDB", SN_NOWARN)
set_name(0x800AB638, "MediumFont", SN_NOWARN)
set_name(0x800AB854, "LargeFont", SN_NOWARN)
set_name(0x8012CF38, "buttoncol", SN_NOWARN)
set_name(0x800ABA70, "LFontTab", SN_NOWARN)
set_name(0x800ABB24, "LFont", SN_NOWARN)
set_name(0x800ABB34, "MFontTab", SN_NOWARN)
set_name(0x800ABC6C, "MFont", SN_NOWARN)
set_name(0x8012CF55, "DialogRed", SN_NOWARN)
set_name(0x8012CF56, "DialogGreen", SN_NOWARN)
set_name(0x8012CF57, "DialogBlue", SN_NOWARN)
set_name(0x8012CF58, "DialogTRed", SN_NOWARN)
set_name(0x8012CF59, "DialogTGreen", SN_NOWARN)
set_name(0x8012CF5A, "DialogTBlue", SN_NOWARN)
set_name(0x8012CF5C, "DialogTData", SN_NOWARN)
set_name(0x8012CF60, "DialogBackGfx", SN_NOWARN)
set_name(0x8012CF64, "DialogBackW", SN_NOWARN)
set_name(0x8012CF68, "DialogBackH", SN_NOWARN)
set_name(0x8012CF6C, "DialogBorderGfx", SN_NOWARN)
set_name(0x8012CF70, "DialogBorderTLW", SN_NOWARN)
set_name(0x8012CF74, "DialogBorderTLH", SN_NOWARN)
set_name(0x8012CF78, "DialogBorderTRW", SN_NOWARN)
set_name(0x8012CF7C, "DialogBorderTRH", SN_NOWARN)
set_name(0x8012CF80, "DialogBorderBLW", SN_NOWARN)
set_name(0x8012CF84, "DialogBorderBLH", SN_NOWARN)
set_name(0x8012CF88, "DialogBorderBRW", SN_NOWARN)
set_name(0x8012CF8C, "DialogBorderBRH", SN_NOWARN)
set_name(0x8012CF90, "DialogBorderTW", SN_NOWARN)
set_name(0x8012CF94, "DialogBorderTH", SN_NOWARN)
set_name(0x8012CF98, "DialogBorderBW", SN_NOWARN)
set_name(0x8012CF9C, "DialogBorderBH", SN_NOWARN)
set_name(0x8012CFA0, "DialogBorderLW", SN_NOWARN)
set_name(0x8012CFA4, "DialogBorderLH", SN_NOWARN)
set_name(0x8012CFA8, "DialogBorderRW", SN_NOWARN)
set_name(0x8012CFAC, "DialogBorderRH", SN_NOWARN)
set_name(0x8012CFB0, "DialogBevelGfx", SN_NOWARN)
set_name(0x8012CFB4, "DialogBevelCW", SN_NOWARN)
set_name(0x8012CFB8, "DialogBevelCH", SN_NOWARN)
set_name(0x8012CFBC, "DialogBevelLRW", SN_NOWARN)
set_name(0x8012CFC0, "DialogBevelLRH", SN_NOWARN)
set_name(0x8012CFC4, "DialogBevelUDW", SN_NOWARN)
set_name(0x8012CFC8, "DialogBevelUDH", SN_NOWARN)
set_name(0x8012CFCC, "MY_DialogOTpos", SN_NOWARN)
set_name(0x8012E6DC, "DialogGBack", SN_NOWARN)
set_name(0x8012E6DD, "GShadeX", SN_NOWARN)
set_name(0x8012E6DE, "GShadeY", SN_NOWARN)
set_name(0x8012E6E4, "RandBTab", SN_NOWARN)
set_name(0x800ABCBC, "Cxy", SN_NOWARN)
set_name(0x8012CF4F, "BORDERR", SN_NOWARN)
set_name(0x8012CF50, "BORDERG", SN_NOWARN)
set_name(0x8012CF51, "BORDERB", SN_NOWARN)
set_name(0x8012CF52, "BACKR", SN_NOWARN)
set_name(0x8012CF53, "BACKG", SN_NOWARN)
set_name(0x8012CF54, "BACKB", SN_NOWARN)
set_name(0x800ABC7C, "GShadeTab", SN_NOWARN)
set_name(0x8012CF4D, "GShadePX", SN_NOWARN)
set_name(0x8012CF4E, "GShadePY", SN_NOWARN)
set_name(0x8012CFD9, "PlayDemoFlag", SN_NOWARN)
set_name(0x8012EC40, "rgbb", SN_NOWARN)
set_name(0x8012EC70, "rgbt", SN_NOWARN)
set_name(0x8012E6EC, "blockr", SN_NOWARN)
set_name(0x8012E6F0, "blockg", SN_NOWARN)
set_name(0x8012E6F4, "blockb", SN_NOWARN)
set_name(0x8012E6F8, "InfraFlag", SN_NOWARN)
set_name(0x8012E6FC, "blank_bit", SN_NOWARN)
set_name(0x8012CFED, "P1ObjSelCount", SN_NOWARN)
set_name(0x8012CFEE, "P2ObjSelCount", SN_NOWARN)
set_name(0x8012CFEF, "P12ObjSelCount", SN_NOWARN)
set_name(0x8012CFF0, "P1ItemSelCount", SN_NOWARN)
set_name(0x8012CFF1, "P2ItemSelCount", SN_NOWARN)
set_name(0x8012CFF2, "P12ItemSelCount", SN_NOWARN)
set_name(0x8012CFF3, "P1MonstSelCount", SN_NOWARN)
set_name(0x8012CFF4, "P2MonstSelCount", SN_NOWARN)
set_name(0x8012CFF5, "P12MonstSelCount", SN_NOWARN)
set_name(0x8012CFF6, "P1ObjSelCol", SN_NOWARN)
set_name(0x8012CFF8, "P2ObjSelCol", SN_NOWARN)
set_name(0x8012CFFA, "P12ObjSelCol", SN_NOWARN)
set_name(0x8012CFFC, "P1ItemSelCol", SN_NOWARN)
set_name(0x8012CFFE, "P2ItemSelCol", SN_NOWARN)
set_name(0x8012D000, "P12ItemSelCol", SN_NOWARN)
set_name(0x8012D002, "P1MonstSelCol", SN_NOWARN)
set_name(0x8012D004, "P2MonstSelCol", SN_NOWARN)
set_name(0x8012D006, "P12MonstSelCol", SN_NOWARN)
set_name(0x8012D008, "CurrentBlocks", SN_NOWARN)
set_name(0x800ABD2C, "TownConv", SN_NOWARN)
set_name(0x8012D024, "CurrentOverlay", SN_NOWARN)
set_name(0x80122750, "HaltTab", SN_NOWARN)
set_name(0x8012ECA0, "FrontEndOver", SN_NOWARN)
set_name(0x8012ECB0, "PregameOver", SN_NOWARN)
set_name(0x8012ECC0, "GameOver", SN_NOWARN)
set_name(0x8012ECD0, "FmvOver", SN_NOWARN)
set_name(0x8012E700, "OWorldX", SN_NOWARN)
set_name(0x8012E704, "OWorldY", SN_NOWARN)
set_name(0x8012E708, "WWorldX", SN_NOWARN)
set_name(0x8012E70C, "WWorldY", SN_NOWARN)
set_name(0x801227CC, "TxyAdd", SN_NOWARN)
set_name(0x8012D048, "GXAdj2", SN_NOWARN)
set_name(0x8012E710, "TimePerFrame", SN_NOWARN)
set_name(0x8012E714, "CpuStart", SN_NOWARN)
set_name(0x8012E718, "CpuTime", SN_NOWARN)
set_name(0x8012E71C, "DrawTime", SN_NOWARN)
set_name(0x8012E720, "DrawStart", SN_NOWARN)
set_name(0x8012E724, "LastCpuTime", SN_NOWARN)
set_name(0x8012E728, "LastDrawTime", SN_NOWARN)
set_name(0x8012E72C, "DrawArea", SN_NOWARN)
set_name(0x8012D050, "ProfOn", SN_NOWARN)
set_name(0x800ABD44, "LevPals", SN_NOWARN)
set_name(0x80122928, "Level2Bgdata", SN_NOWARN)
set_name(0x800ABD58, "DefP1PanelXY", SN_NOWARN)
set_name(0x800ABDAC, "DefP1PanelXY2", SN_NOWARN)
set_name(0x800ABE00, "DefP2PanelXY", SN_NOWARN)
set_name(0x800ABE54, "DefP2PanelXY2", SN_NOWARN)
set_name(0x800ABEA8, "SpeedBarGfxTable", SN_NOWARN)
set_name(0x8012D078, "hof", SN_NOWARN)
set_name(0x8012D07C, "mof", SN_NOWARN)
set_name(0x800ABF70, "SFXTab", SN_NOWARN)
set_name(0x800AC070, "STR_Buffer", SN_NOWARN)
set_name(0x8012D0B0, "Time", SN_NOWARN)
set_name(0x8012D0B4, "CDWAIT", SN_NOWARN)
set_name(0x800BE070, "voice_attr", SN_NOWARN)
set_name(0x800BE0B0, "STRSave", SN_NOWARN)
set_name(0x8012E730, "SavePause", SN_NOWARN)
set_name(0x8012D089, "NoActiveStreams", SN_NOWARN)
set_name(0x8012D08C, "STRInit", SN_NOWARN)
set_name(0x8012D090, "frame_rate", SN_NOWARN)
set_name(0x8012D094, "CDAngle", SN_NOWARN)
set_name(0x8012D0D8, "SFXNotPlayed", SN_NOWARN)
set_name(0x8012D0D9, "SFXNotInBank", SN_NOWARN)
set_name(0x8012ECE0, "spu_management", SN_NOWARN)
set_name(0x8012EDF0, "rev_attr", SN_NOWARN)
set_name(0x8012E738, "NoSfx", SN_NOWARN)
set_name(0x8012EE10, "CHStatus", SN_NOWARN)
set_name(0x8012D0C4, "BankOffsets", SN_NOWARN)
set_name(0x8012D0C8, "OffsetHandle", SN_NOWARN)
set_name(0x8012D0CC, "BankBase", SN_NOWARN)
set_name(0x8012D0D0, "SPU_Done", SN_NOWARN)
set_name(0x80122CD0, "SFXRemapTab", SN_NOWARN)
set_name(0x8012D0D4, "NoSNDRemaps", SN_NOWARN)
set_name(0x800BE130, "ThePals", SN_NOWARN)
set_name(0x80122D7C, "InitialPositions", SN_NOWARN)
set_name(0x8012D11C, "demo_level", SN_NOWARN)
set_name(0x8012EE40, "buff", SN_NOWARN)
set_name(0x8012D120, "old_val", SN_NOWARN)
set_name(0x8012D124, "DemoTask", SN_NOWARN)
set_name(0x8012D128, "DemoGameTask", SN_NOWARN)
set_name(0x8012D12C, "tonys", SN_NOWARN)
set_name(0x8012D104, "demo_load", SN_NOWARN)
set_name(0x8012D108, "demo_record_load", SN_NOWARN)
set_name(0x8012D10C, "level_record", SN_NOWARN)
set_name(0x8012D110, "demo_fade_finished", SN_NOWARN)
set_name(0x8012D113, "demo_which", SN_NOWARN)
set_name(0x800BE35C, "demolevel", SN_NOWARN)
set_name(0x8012D111, "quest_cheat_num", SN_NOWARN)
set_name(0x8012D112, "cheat_quest_flag", SN_NOWARN)
set_name(0x8012D100, "moo_moo", SN_NOWARN)
set_name(0x800BE31C, "quest_seed", SN_NOWARN)
set_name(0x8012D114, "demo_flash", SN_NOWARN)
set_name(0x8012D118, "tonys_Task", SN_NOWARN)
set_name(0x8012D288, "DoShowPanel", SN_NOWARN)
set_name(0x8012D28C, "DoDrawBg", SN_NOWARN)
set_name(0x8012E73C, "GlueFinished", SN_NOWARN)
set_name(0x8012E740, "DoHomingScroll", SN_NOWARN)
set_name(0x8012E744, "TownerGfx", SN_NOWARN)
set_name(0x8012E748, "CurrentMonsterList", SN_NOWARN)
set_name(0x8012D139, "started_grtask", SN_NOWARN)
set_name(0x800BE370, "PlayerInfo", SN_NOWARN)
set_name(0x8012D290, "ArmourChar", SN_NOWARN)
set_name(0x80122E70, "WepChar", SN_NOWARN)
set_name(0x8012D294, "CharChar", SN_NOWARN)
set_name(0x8012E74C, "ctrl_select_line", SN_NOWARN)
set_name(0x8012E74D, "ctrl_select_side", SN_NOWARN)
set_name(0x8012E74E, "ckeyheld", SN_NOWARN)
set_name(0x8012E754, "CtrlRect", SN_NOWARN)
set_name(0x8012D2A8, "ctrlflag", SN_NOWARN)
set_name(0x800BE7E4, "txt_actions", SN_NOWARN)
set_name(0x800BE73C, "pad_txt", SN_NOWARN)
set_name(0x8012D2A4, "toppos", SN_NOWARN)
set_name(0x8012EE60, "CtrlBack", SN_NOWARN)
set_name(0x800BE914, "controller_defaults", SN_NOWARN)
set_name(0x8012D314, "gr_scrxoff", SN_NOWARN)
set_name(0x8012D318, "gr_scryoff", SN_NOWARN)
set_name(0x8012D320, "water_clut", SN_NOWARN)
set_name(0x8012D323, "visible_level", SN_NOWARN)
set_name(0x8012D311, "last_type", SN_NOWARN)
set_name(0x8012D325, "daylight", SN_NOWARN)
set_name(0x8012D322, "cow_in_sight", SN_NOWARN)
set_name(0x8012D31C, "water_count", SN_NOWARN)
set_name(0x8012D324, "lastrnd", SN_NOWARN)
set_name(0x8012D328, "call_clock", SN_NOWARN)
set_name(0x8012D338, "TitleAnimCount", SN_NOWARN)
set_name(0x8012D33C, "flametick", SN_NOWARN)
set_name(0x800BE9AC, "ypos", SN_NOWARN)
set_name(0x800BE9C4, "frmlist", SN_NOWARN)
set_name(0x800BE9DC, "xoff", SN_NOWARN)
set_name(0x8012D340, "startx", SN_NOWARN)
set_name(0x8012D344, "hellomumflag", SN_NOWARN)
set_name(0x800BEA14, "SpellFXDat", SN_NOWARN)
set_name(0x8012EE70, "PartArray", SN_NOWARN)
set_name(0x8012E75C, "partOtPos", SN_NOWARN)
set_name(0x8012D364, "SetParticle", SN_NOWARN)
set_name(0x8012D368, "p1partexecnum", SN_NOWARN)
set_name(0x8012D36C, "p2partexecnum", SN_NOWARN)
set_name(0x800BE9F4, "JumpArray", SN_NOWARN)
set_name(0x8012D370, "partjumpflag", SN_NOWARN)
set_name(0x8012D374, "partglowflag", SN_NOWARN)
set_name(0x8012D378, "partcolour", SN_NOWARN)
set_name(0x8012D37C, "anyfuckingmenus", SN_NOWARN)
set_name(0x800BEAA4, "SplTarget", SN_NOWARN)
set_name(0x8012D39D, "select_flag", SN_NOWARN)
set_name(0x8012E760, "SelectRect", SN_NOWARN)
set_name(0x8012E768, "item_select", SN_NOWARN)
set_name(0x8012D3A0, "QSpell", SN_NOWARN)
set_name(0x8012D3A4, "_spltotype", SN_NOWARN)
set_name(0x8012D3A8, "force_attack", SN_NOWARN)
set_name(0x8012D390, "gplayer", SN_NOWARN)
set_name(0x8012F0B0, "SelectBack", SN_NOWARN)
set_name(0x8012D394, "mana_order", SN_NOWARN)
set_name(0x8012D398, "health_order", SN_NOWARN)
set_name(0x8012D39C, "birdcheck", SN_NOWARN)
set_name(0x8012F0C0, "DecRequestors", SN_NOWARN)
set_name(0x8012E76C, "progress", SN_NOWARN)
set_name(0x80122FFC, "Level2CutScreen", SN_NOWARN)
set_name(0x8012F0E8, "Scr", SN_NOWARN)
set_name(0x8012D3C8, "CutScreenTSK", SN_NOWARN)
set_name(0x8012D3CC, "GameLoading", SN_NOWARN)
set_name(0x8012F168, "LBack", SN_NOWARN)
set_name(0x800BEAD4, "block_buf", SN_NOWARN)
set_name(0x8012D3E8, "card_ev0", SN_NOWARN)
set_name(0x8012D3EC, "card_ev1", SN_NOWARN)
set_name(0x8012D3F0, "card_ev2", SN_NOWARN)
set_name(0x8012D3F4, "card_ev3", SN_NOWARN)
set_name(0x8012D3F8, "card_ev10", SN_NOWARN)
set_name(0x8012D3FC, "card_ev11", SN_NOWARN)
set_name(0x8012D400, "card_ev12", SN_NOWARN)
set_name(0x8012D404, "card_ev13", SN_NOWARN)
set_name(0x8012D408, "card_dirty", SN_NOWARN)
set_name(0x8012D410, "MemcardTask", SN_NOWARN)
set_name(0x8012E770, "card_event", SN_NOWARN)
set_name(0x8012D3E4, "mem_card_event_handler", SN_NOWARN)
set_name(0x8012D3DC, "MemCardActive", SN_NOWARN)
set_name(0x8012D3E0, "never_hooked_events", SN_NOWARN)
set_name(0x8012D46C, "MasterVol", SN_NOWARN)
set_name(0x8012D470, "MusicVol", SN_NOWARN)
set_name(0x8012D474, "SoundVol", SN_NOWARN)
set_name(0x8012D478, "VideoVol", SN_NOWARN)
set_name(0x8012D47C, "SpeechVol", SN_NOWARN)
set_name(0x8012E774, "Slider", SN_NOWARN)
set_name(0x8012E778, "sw", SN_NOWARN)
set_name(0x8012E77C, "sx", SN_NOWARN)
set_name(0x8012E780, "sy", SN_NOWARN)
set_name(0x8012E784, "Adjust", SN_NOWARN)
set_name(0x8012E785, "qspin", SN_NOWARN)
set_name(0x8012E786, "lqspin", SN_NOWARN)
set_name(0x8012E788, "OrigLang", SN_NOWARN)
set_name(0x8012E78C, "OldLang", SN_NOWARN)
set_name(0x8012E790, "NewLang", SN_NOWARN)
set_name(0x8012D480, "save_blocks", SN_NOWARN)
set_name(0x8012D484, "Savefilename", SN_NOWARN)
set_name(0x8012D488, "ReturnMenu", SN_NOWARN)
set_name(0x8012E794, "ORect", SN_NOWARN)
set_name(0x8012E79C, "McState", SN_NOWARN)
set_name(0x8012D48C, "they_pressed", SN_NOWARN)
set_name(0x8012E7A4, "Seed", SN_NOWARN)
set_name(0x8012D440, "optionsflag", SN_NOWARN)
set_name(0x8012D434, "cmenu", SN_NOWARN)
set_name(0x8012D44C, "options_pad", SN_NOWARN)
set_name(0x8012D43C, "allspellsflag", SN_NOWARN)
set_name(0x800BF5F4, "Circle", SN_NOWARN)
set_name(0x8012D420, "goldcheat", SN_NOWARN)
set_name(0x8012D450, "OptionsSeed", SN_NOWARN)
set_name(0x8012D454, "OptionsSetSeed", SN_NOWARN)
set_name(0x8012D424, "Qfromoptions", SN_NOWARN)
set_name(0x8012D428, "Spacing", SN_NOWARN)
set_name(0x8012D42C, "cs", SN_NOWARN)
set_name(0x8012D430, "lastcs", SN_NOWARN)
set_name(0x8012D438, "MemcardOverlay", SN_NOWARN)
set_name(0x8012D444, "saveflag", SN_NOWARN)
set_name(0x8012D448, "loadflag", SN_NOWARN)
set_name(0x8012D458, "PadFrig", SN_NOWARN)
set_name(0x800BEB54, "MainMenu", SN_NOWARN)
set_name(0x800BEC2C, "GameMenu", SN_NOWARN)
set_name(0x800BED34, "SoundMenu", SN_NOWARN)
set_name(0x800BEDC4, "CentreMenu", SN_NOWARN)
set_name(0x800BEE6C, "LangMenu", SN_NOWARN)
set_name(0x800BEF14, "QuitMenu", SN_NOWARN)
set_name(0x800BEF74, "MemcardMenu", SN_NOWARN)
set_name(0x800BF01C, "MemcardLoadGameMenu", SN_NOWARN)
set_name(0x800BF07C, "MemcardSaveGameMenu", SN_NOWARN)
set_name(0x800BF0DC, "MemcardSaveOptionsMenu", SN_NOWARN)
set_name(0x800BF13C, "MemcardLoadOptionsMenu", SN_NOWARN)
set_name(0x800BF19C, "MemcardCharacterMenu", SN_NOWARN)
set_name(0x800BF1FC, "MemcardSelectCard1", SN_NOWARN)
set_name(0x800BF2A4, "MemcardSelectCard2", SN_NOWARN)
set_name(0x800BF34C, "MemcardFormatMenu", SN_NOWARN)
set_name(0x800BF3AC, "CheatMenu", SN_NOWARN)
set_name(0x800BF49C, "InfoMenu", SN_NOWARN)
set_name(0x800BF4CC, "MonstViewMenu", SN_NOWARN)
set_name(0x800BF514, "SeedMenu", SN_NOWARN)
set_name(0x800BF55C, "MenuList", SN_NOWARN)
set_name(0x8012D45C, "debounce", SN_NOWARN)
set_name(0x8012D460, "KeyPos", SN_NOWARN)
set_name(0x800BF674, "KeyTab", SN_NOWARN)
set_name(0x8012D464, "SeedPos", SN_NOWARN)
set_name(0x800BF688, "BirdList", SN_NOWARN)
set_name(0x8012E7AC, "last_seenx", SN_NOWARN)
set_name(0x8012E7B4, "last_seeny", SN_NOWARN)
set_name(0x8012D499, "hop_height", SN_NOWARN)
set_name(0x8012D49C, "perches", SN_NOWARN)
set_name(0x800BF808, "FmvTab", SN_NOWARN)
set_name(0x8012D4B0, "CurMons", SN_NOWARN)
set_name(0x8012D4B4, "Frame", SN_NOWARN)
set_name(0x8012D4B8, "Action", SN_NOWARN)
set_name(0x8012D4BC, "Dir", SN_NOWARN)
set_name(0x8012D520, "indsize", SN_NOWARN)
set_name(0x8012D500, "kanjbuff", SN_NOWARN)
set_name(0x8012D504, "kindex", SN_NOWARN)
set_name(0x8012D508, "hndKanjBuff", SN_NOWARN)
set_name(0x8012D50C, "hndKanjIndex", SN_NOWARN)
set_name(0x8012E7BC, "HelpRect", SN_NOWARN)
set_name(0x8012E7C4, "HelpTop", SN_NOWARN)
set_name(0x8012F178, "HelpBack", SN_NOWARN)
set_name(0x8012D530, "helpflag", SN_NOWARN)
set_name(0x800BF848, "HelpList", SN_NOWARN)
set_name(0x8012D580, "FeBackX", SN_NOWARN)
set_name(0x8012D584, "FeBackY", SN_NOWARN)
set_name(0x8012D588, "FeBackW", SN_NOWARN)
set_name(0x8012D58C, "FeBackH", SN_NOWARN)
set_name(0x8012D590, "FeFlag", SN_NOWARN)
set_name(0x800BFE50, "FeBuffer", SN_NOWARN)
set_name(0x8012D594, "FePlayerNo", SN_NOWARN)
set_name(0x8012E7C8, "CStruct", SN_NOWARN)
set_name(0x8012D598, "FeBufferCount", SN_NOWARN)
set_name(0x8012D59C, "FeNoOfPlayers", SN_NOWARN)
set_name(0x8012D5A0, "FeChrClass", SN_NOWARN)
set_name(0x800C05D0, "FePlayerName", SN_NOWARN)
set_name(0x8012D5A8, "FeCurMenu", SN_NOWARN)
set_name(0x8012D5AC, "FePlayerNameFlag", SN_NOWARN)
set_name(0x8012D5B0, "FeCount", SN_NOWARN)
set_name(0x8012D5B4, "fileselect", SN_NOWARN)
set_name(0x8012D5B8, "BookMenu", SN_NOWARN)
set_name(0x8012D5BC, "FeAttractMode", SN_NOWARN)
set_name(0x8012D5C0, "FMVPress", SN_NOWARN)
set_name(0x8012D54C, "FeTData", SN_NOWARN)
set_name(0x8012D554, "LoadedChar", SN_NOWARN)
set_name(0x8012D550, "FlameTData", SN_NOWARN)
set_name(0x8012D55C, "FeIsAVirgin", SN_NOWARN)
set_name(0x8012D560, "FeMenuDelay", SN_NOWARN)
set_name(0x800BF950, "DummyMenu", SN_NOWARN)
set_name(0x800BF96C, "FeMainMenu", SN_NOWARN)
set_name(0x800BF988, "FeNewGameMenu", SN_NOWARN)
set_name(0x800BF9A4, "FeNewP1ClassMenu", SN_NOWARN)
set_name(0x800BF9C0, "FeNewP1NameMenu", SN_NOWARN)
set_name(0x800BF9DC, "FeNewP2ClassMenu", SN_NOWARN)
set_name(0x800BF9F8, "FeNewP2NameMenu", SN_NOWARN)
set_name(0x800BFA14, "FeDifficultyMenu", SN_NOWARN)
set_name(0x800BFA30, "FeBackgroundMenu", SN_NOWARN)
set_name(0x800BFA4C, "FeBook1Menu", SN_NOWARN)
set_name(0x800BFA68, "FeBook2Menu", SN_NOWARN)
set_name(0x800BFA84, "FeLoadCharMenu", SN_NOWARN)
set_name(0x800BFAA0, "FeLoadChar1Menu", SN_NOWARN)
set_name(0x800BFABC, "FeLoadChar2Menu", SN_NOWARN)
set_name(0x8012D564, "fadeval", SN_NOWARN)
set_name(0x800BFAD8, "FeMainMenuTable", SN_NOWARN)
set_name(0x800BFB50, "FeNewGameMenuTable", SN_NOWARN)
set_name(0x800BFB98, "FePlayerClassMenuTable", SN_NOWARN)
set_name(0x800BFC10, "FeNameEngMenuTable", SN_NOWARN)
set_name(0x800BFC58, "FeMemcardMenuTable", SN_NOWARN)
set_name(0x800BFCA0, "FeDifficultyMenuTable", SN_NOWARN)
set_name(0x800BFD00, "FeBackgroundMenuTable", SN_NOWARN)
set_name(0x800BFD60, "FeBook1MenuTable", SN_NOWARN)
set_name(0x800BFDD8, "FeBook2MenuTable", SN_NOWARN)
set_name(0x8012D570, "DrawBackOn", SN_NOWARN)
set_name(0x8012D574, "AttractTitleDelay", SN_NOWARN)
set_name(0x8012D578, "AttractMainDelay", SN_NOWARN)
set_name(0x8012D57C, "FMVEndPad", SN_NOWARN)
set_name(0x8012D5F4, "InCredits", SN_NOWARN)
set_name(0x8012D5F8, "CreditTitleNo", SN_NOWARN)
set_name(0x8012D5FC, "CreditSubTitleNo", SN_NOWARN)
set_name(0x8012D610, "card_status", SN_NOWARN)
set_name(0x8012D618, "card_usable", SN_NOWARN)
set_name(0x8012D620, "card_files", SN_NOWARN)
set_name(0x8012D628, "card_changed", SN_NOWARN)
set_name(0x8012D66C, "AlertTxt", SN_NOWARN)
set_name(0x8012D670, "current_card", SN_NOWARN)
set_name(0x8012D674, "LoadType", SN_NOWARN)
set_name(0x8012D678, "McMenuPos", SN_NOWARN)
set_name(0x8012D67C, "McCurMenu", SN_NOWARN)
set_name(0x8012D668, "fileinfoflag", SN_NOWARN)
set_name(0x8012D63C, "DiabloGameFile", SN_NOWARN)
set_name(0x8012D640, "DiabloOptionFile", SN_NOWARN)
set_name(0x8012D660, "McState_addr_8012D660", SN_NOWARN)
set_name(0x8012D758, "mdec_audio_buffer", SN_NOWARN)
set_name(0x8012D760, "mdec_audio_sec", SN_NOWARN)
set_name(0x8012D764, "mdec_audio_offs", SN_NOWARN)
set_name(0x8012D768, "mdec_audio_playing", SN_NOWARN)
set_name(0x8012D76C, "mdec_audio_rate_shift", SN_NOWARN)
set_name(0x8012D770, "vlcbuf", SN_NOWARN)
set_name(0x8012D778, "slice_size", SN_NOWARN)
set_name(0x8012D77C, "slice", SN_NOWARN)
set_name(0x8012D784, "slice_inc", SN_NOWARN)
set_name(0x8012D788, "area_pw", SN_NOWARN)
set_name(0x8012D78C, "area_ph", SN_NOWARN)
set_name(0x8012D790, "tmdc_pol_dirty", SN_NOWARN)
set_name(0x8012D794, "num_pol", SN_NOWARN)
set_name(0x8012D79C, "mdec_cx", SN_NOWARN)
set_name(0x8012D7A0, "mdec_cy", SN_NOWARN)
set_name(0x8012D7A4, "mdec_w", SN_NOWARN)
set_name(0x8012D7A8, "mdec_h", SN_NOWARN)
set_name(0x8012D7AC, "mdec_pw", SN_NOWARN)
set_name(0x8012D7B4, "mdec_ph", SN_NOWARN)
set_name(0x8012D7BC, "move_x", SN_NOWARN)
set_name(0x8012D7C0, "move_y", SN_NOWARN)
set_name(0x8012D7C4, "move_scale", SN_NOWARN)
set_name(0x8012D7C8, "stream_frames", SN_NOWARN)
set_name(0x8012D7CC, "last_stream_frame", SN_NOWARN)
set_name(0x8012D7D0, "mdec_framecount", SN_NOWARN)
set_name(0x8012D7D4, "mdec_speed", SN_NOWARN)
set_name(0x8012D7D8, "mdec_stream_starting", SN_NOWARN)
set_name(0x8012D7DC, "mdec_last_frame", SN_NOWARN)
set_name(0x8012D7E0, "mdec_sectors_per_frame", SN_NOWARN)
set_name(0x8012D7E4, "vlctab", SN_NOWARN)
set_name(0x8012D7E8, "mdc_buftop", SN_NOWARN)
set_name(0x8012D7EC, "mdc_bufstart", SN_NOWARN)
set_name(0x8012D7F0, "mdc_bufleft", SN_NOWARN)
set_name(0x8012D7F4, "mdc_buftotal", SN_NOWARN)
set_name(0x8012D7F8, "ordertab_length", SN_NOWARN)
set_name(0x8012D7FC, "time_in_frames", SN_NOWARN)
set_name(0x8012D800, "stream_chunksize", SN_NOWARN)
set_name(0x8012D804, "stream_bufsize", SN_NOWARN)
set_name(0x8012D808, "stream_subsec", SN_NOWARN)
set_name(0x8012D80C, "stream_secnum", SN_NOWARN)
set_name(0x8012D810, "stream_last_sector", SN_NOWARN)
set_name(0x8012D814, "stream_startsec", SN_NOWARN)
set_name(0x8012D818, "stream_opened", SN_NOWARN)
set_name(0x8012D81C, "stream_last_chunk", SN_NOWARN)
set_name(0x8012D820, "stream_got_chunks", SN_NOWARN)
set_name(0x8012D824, "last_sector", SN_NOWARN)
set_name(0x8012D828, "cdstream_resetsec", SN_NOWARN)
set_name(0x8012D82C, "last_handler_event", SN_NOWARN)
set_name(0x8012D6F4, "user_start", SN_NOWARN)
set_name(0x8012D68C, "vlc_tab", SN_NOWARN)
set_name(0x8012D690, "vlc_buf", SN_NOWARN)
set_name(0x8012D694, "img_buf", SN_NOWARN)
set_name(0x8012D698, "vbuf", SN_NOWARN)
set_name(0x8012D69C, "last_fn", SN_NOWARN)
set_name(0x8012D6A0, "last_mdc", SN_NOWARN)
set_name(0x8012D6A4, "slnum", SN_NOWARN)
set_name(0x8012D6A8, "slices_to_do", SN_NOWARN)
set_name(0x8012D6AC, "mbuf", SN_NOWARN)
set_name(0x8012D6B0, "mfn", SN_NOWARN)
set_name(0x8012D6B4, "last_move_mbuf", SN_NOWARN)
set_name(0x8012D6B8, "move_request", SN_NOWARN)
set_name(0x8012D6BC, "mdec_scale", SN_NOWARN)
set_name(0x8012D6C0, "do_brightness", SN_NOWARN)
set_name(0x8012D6C4, "frame_decoded", SN_NOWARN)
set_name(0x8012D6C8, "mdec_streaming", SN_NOWARN)
set_name(0x8012D6CC, "mdec_stream_size", SN_NOWARN)
set_name(0x8012D6D0, "first_stream_frame", SN_NOWARN)
set_name(0x8012D6D4, "stream_frames_played", SN_NOWARN)
set_name(0x8012D6D8, "num_mdcs", SN_NOWARN)
set_name(0x8012D6DC, "mdec_head", SN_NOWARN)
set_name(0x8012D6E0, "mdec_tail", SN_NOWARN)
set_name(0x8012D6E4, "mdec_waiting_tail", SN_NOWARN)
set_name(0x8012D6E8, "mdecs_queued", SN_NOWARN)
set_name(0x8012D6EC, "mdecs_waiting", SN_NOWARN)
set_name(0x8012D6F0, "sfx_volume", SN_NOWARN)
set_name(0x8012D6F8, "DiabEnd", SN_NOWARN)
set_name(0x8012D6FC, "stream_chunks_in", SN_NOWARN)
set_name(0x8012D700, "stream_chunks_total", SN_NOWARN)
set_name(0x8012D704, "stream_in", SN_NOWARN)
set_name(0x8012D708, "stream_out", SN_NOWARN)
set_name(0x8012D70C, "stream_stalled", SN_NOWARN)
set_name(0x8012D710, "stream_ending", SN_NOWARN)
set_name(0x8012D714, "stream_open", SN_NOWARN)
set_name(0x8012D718, "stream_handler_installed", SN_NOWARN)
set_name(0x8012D71C, "stream_chunks_borrowed", SN_NOWARN)
set_name(0x8012D720, "_get_count", SN_NOWARN)
set_name(0x8012D724, "_discard_count", SN_NOWARN)
set_name(0x8012D728, "CDTask", SN_NOWARN)
set_name(0x8012D72C, "CDStream", SN_NOWARN)
set_name(0x8012D730, "cdready_calls", SN_NOWARN)
set_name(0x8012D734, "cdready_errors", SN_NOWARN)
set_name(0x8012D738, "cdready_out_of_sync", SN_NOWARN)
set_name(0x8012D73C, "cdstream_resetting", SN_NOWARN)
set_name(0x8012D740, "sector_dma", SN_NOWARN)
set_name(0x8012D744, "sector_dma_in", SN_NOWARN)
set_name(0x8012D748, "chkaddr", SN_NOWARN)
set_name(0x8012D74C, "chunk", SN_NOWARN)
set_name(0x8012D750, "first_handler_event", SN_NOWARN)
set_name(0x8012D754, "DOSLEEP", SN_NOWARN)
set_name(0x8012D8AC, "pStatusPanel", SN_NOWARN)
set_name(0x8012D8B0, "pGBoxBuff", SN_NOWARN)
set_name(0x8012D8B4, "dropGoldFlag", SN_NOWARN)
set_name(0x8012D8B8, "_pinfoflag", SN_NOWARN)
set_name(0x800C0AE8, "_infostr", SN_NOWARN)
set_name(0x8012D8BC, "_infoclr", SN_NOWARN)
set_name(0x800C0CE8, "tempstr", SN_NOWARN)
set_name(0x8012D8BE, "drawhpflag", SN_NOWARN)
set_name(0x8012D8BF, "drawmanaflag", SN_NOWARN)
set_name(0x8012D8C0, "chrflag", SN_NOWARN)
set_name(0x8012D8C1, "drawbtnflag", SN_NOWARN)
set_name(0x8012D8C2, "panbtndown", SN_NOWARN)
set_name(0x8012D8C3, "panelflag", SN_NOWARN)
set_name(0x8012D8C4, "chrbtndown", SN_NOWARN)
set_name(0x8012D8C5, "lvlbtndown", SN_NOWARN)
set_name(0x8012D8C6, "sbookflag", SN_NOWARN)
set_name(0x8012D8C7, "talkflag", SN_NOWARN)
set_name(0x8012D8C8, "dropGoldValue", SN_NOWARN)
set_name(0x8012D8CC, "initialDropGoldValue", SN_NOWARN)
set_name(0x8012D8D0, "initialDropGoldIndex", SN_NOWARN)
set_name(0x8012D8D4, "pPanelButtons", SN_NOWARN)
set_name(0x8012D8D8, "pPanelText", SN_NOWARN)
set_name(0x8012D8DC, "pManaBuff", SN_NOWARN)
set_name(0x8012D8E0, "pLifeBuff", SN_NOWARN)
set_name(0x8012D8E4, "pChrPanel", SN_NOWARN)
set_name(0x8012D8E8, "pChrButtons", SN_NOWARN)
set_name(0x8012D8EC, "pSpellCels", SN_NOWARN)
set_name(0x8012F1C8, "_panelstr", SN_NOWARN)
set_name(0x8012F5C8, "_pstrjust", SN_NOWARN)
set_name(0x8012E7D8, "_pnumlines", SN_NOWARN)
set_name(0x8012D8F0, "InfoBoxRect", SN_NOWARN)
set_name(0x8012D8F4, "CSRect", SN_NOWARN)
set_name(0x8012E7E8, "_pSpell", SN_NOWARN)
set_name(0x8012E7F0, "_pSplType", SN_NOWARN)
set_name(0x8012D8FC, "numpanbtns", SN_NOWARN)
set_name(0x8012D900, "pDurIcons", SN_NOWARN)
set_name(0x8012D904, "drawdurflag", SN_NOWARN)
set_name(0x8012E7F8, "chrbtn", SN_NOWARN)
set_name(0x8012D905, "chrbtnactive", SN_NOWARN)
set_name(0x8012D908, "pSpellBkCel", SN_NOWARN)
set_name(0x8012D90C, "pSBkBtnCel", SN_NOWARN)
set_name(0x8012D910, "pSBkIconCels", SN_NOWARN)
set_name(0x8012D914, "sbooktab", SN_NOWARN)
set_name(0x8012D918, "cur_spel", SN_NOWARN)
set_name(0x8012E800, "talkofs", SN_NOWARN)
set_name(0x8012F618, "sgszTalkMsg", SN_NOWARN)
set_name(0x8012E804, "sgbTalkSavePos", SN_NOWARN)
set_name(0x8012E805, "sgbNextTalkSave", SN_NOWARN)
set_name(0x8012E806, "sgbPlrTalkTbl", SN_NOWARN)
set_name(0x8012E808, "pTalkPanel", SN_NOWARN)
set_name(0x8012E80C, "pMultiBtns", SN_NOWARN)
set_name(0x8012E810, "pTalkBtns", SN_NOWARN)
set_name(0x8012E814, "talkbtndown", SN_NOWARN)
set_name(0x800C05FC, "SpellITbl", SN_NOWARN)
set_name(0x8012D839, "DrawLevelUpFlag", SN_NOWARN)
set_name(0x8012D860, "_spselflag", SN_NOWARN)
set_name(0x8012D85C, "spspelstate", SN_NOWARN)
set_name(0x8012D87C, "initchr", SN_NOWARN)
set_name(0x8012D83C, "SPLICONNO", SN_NOWARN)
set_name(0x8012D840, "SPLICONY", SN_NOWARN)
set_name(0x8012E7E0, "SPLICONRIGHT", SN_NOWARN)
set_name(0x8012D844, "scx", SN_NOWARN)
set_name(0x8012D848, "scy", SN_NOWARN)
set_name(0x8012D84C, "scx1", SN_NOWARN)
set_name(0x8012D850, "scy1", SN_NOWARN)
set_name(0x8012D854, "scx2", SN_NOWARN)
set_name(0x8012D858, "scy2", SN_NOWARN)
set_name(0x8012D868, "SpellCol", SN_NOWARN)
set_name(0x800C05E8, "SpellColors", SN_NOWARN)
set_name(0x800C0624, "SpellPages", SN_NOWARN)
set_name(0x8012D86C, "lus", SN_NOWARN)
set_name(0x8012D870, "CsNo", SN_NOWARN)
set_name(0x8012D874, "plusanim", SN_NOWARN)
set_name(0x8012F608, "CSBack", SN_NOWARN)
set_name(0x8012D878, "CS_XOFF", SN_NOWARN)
set_name(0x800C0688, "CS_Tab", SN_NOWARN)
set_name(0x8012D880, "NoCSEntries", SN_NOWARN)
set_name(0x8012D884, "SPALOFF", SN_NOWARN)
set_name(0x8012D888, "paloffset1", SN_NOWARN)
set_name(0x8012D88C, "paloffset2", SN_NOWARN)
set_name(0x8012D890, "paloffset3", SN_NOWARN)
set_name(0x8012D894, "paloffset4", SN_NOWARN)
set_name(0x8012D898, "pinc1", SN_NOWARN)
set_name(0x8012D89C, "pinc2", SN_NOWARN)
set_name(0x8012D8A0, "pinc3", SN_NOWARN)
set_name(0x8012D8A4, "pinc4", SN_NOWARN)
set_name(0x8012D92C, "_pcurs", SN_NOWARN)
set_name(0x8012D934, "cursW", SN_NOWARN)
set_name(0x8012D938, "cursH", SN_NOWARN)
set_name(0x8012D93C, "icursW", SN_NOWARN)
set_name(0x8012D940, "icursH", SN_NOWARN)
set_name(0x8012D944, "icursW28", SN_NOWARN)
set_name(0x8012D948, "icursH28", SN_NOWARN)
set_name(0x8012D94C, "cursmx", SN_NOWARN)
set_name(0x8012D950, "cursmy", SN_NOWARN)
set_name(0x8012D954, "_pcursmonst", SN_NOWARN)
set_name(0x8012D95C, "_pcursobj", SN_NOWARN)
set_name(0x8012D960, "_pcursitem", SN_NOWARN)
set_name(0x8012D964, "_pcursinvitem", SN_NOWARN)
set_name(0x8012D968, "_pcursplr", SN_NOWARN)
set_name(0x8012D928, "sel_data", SN_NOWARN)
set_name(0x800C0DE8, "dead", SN_NOWARN)
set_name(0x8012D96C, "spurtndx", SN_NOWARN)
set_name(0x8012D970, "stonendx", SN_NOWARN)
set_name(0x8012D974, "pSquareCel", SN_NOWARN)
set_name(0x8012D9B4, "ghInst", SN_NOWARN)
set_name(0x8012D9B8, "svgamode", SN_NOWARN)
set_name(0x8012D9BC, "MouseX", SN_NOWARN)
set_name(0x8012D9C0, "MouseY", SN_NOWARN)
set_name(0x8012D9C4, "gv1", SN_NOWARN)
set_name(0x8012D9C8, "gv2", SN_NOWARN)
set_name(0x8012D9CC, "gv3", SN_NOWARN)
set_name(0x8012D9D0, "gv4", SN_NOWARN)
set_name(0x8012D9D4, "gv5", SN_NOWARN)
set_name(0x8012D9D8, "gbProcessPlayers", SN_NOWARN)
set_name(0x800C0F5C, "DebugMonsters", SN_NOWARN)
set_name(0x800C0F84, "glSeedTbl", SN_NOWARN)
set_name(0x800C0FC8, "gnLevelTypeTbl", SN_NOWARN)
set_name(0x8012D9D9, "gbDoEnding", SN_NOWARN)
set_name(0x8012D9DA, "gbRunGame", SN_NOWARN)
set_name(0x8012D9DB, "gbRunGameResult", SN_NOWARN)
set_name(0x8012D9DC, "gbGameLoopStartup", SN_NOWARN)
set_name(0x8012F668, "glEndSeed", SN_NOWARN)
set_name(0x8012F6B8, "glMid1Seed", SN_NOWARN)
set_name(0x8012F708, "glMid2Seed", SN_NOWARN)
set_name(0x8012F758, "glMid3Seed", SN_NOWARN)
set_name(0x8012E818, "sg_previousFilter", SN_NOWARN)
set_name(0x800C100C, "CreateEnv", SN_NOWARN)
set_name(0x8012D9E0, "Passedlvldir", SN_NOWARN)
set_name(0x8012D9E4, "TempStack", SN_NOWARN)
set_name(0x8012D984, "ghMainWnd", SN_NOWARN)
set_name(0x8012D988, "fullscreen", SN_NOWARN)
set_name(0x8012D98C, "force_redraw", SN_NOWARN)
set_name(0x8012D9A0, "PauseMode", SN_NOWARN)
set_name(0x8012D9A1, "FriendlyMode", SN_NOWARN)
set_name(0x8012D991, "visiondebug", SN_NOWARN)
set_name(0x8012D993, "light4flag", SN_NOWARN)
set_name(0x8012D994, "leveldebug", SN_NOWARN)
set_name(0x8012D995, "monstdebug", SN_NOWARN)
set_name(0x8012D99C, "debugmonsttypes", SN_NOWARN)
set_name(0x8012D990, "cineflag", SN_NOWARN)
set_name(0x8012D992, "scrollflag", SN_NOWARN)
set_name(0x8012D996, "trigdebug", SN_NOWARN)
set_name(0x8012D998, "setseed", SN_NOWARN)
set_name(0x8012D9A4, "sgnTimeoutCurs", SN_NOWARN)
set_name(0x8012D9A8, "sgbMouseDown", SN_NOWARN)
set_name(0x800C16D8, "towner", SN_NOWARN)
set_name(0x8012D9FC, "numtowners", SN_NOWARN)
set_name(0x8012DA00, "storeflag", SN_NOWARN)
set_name(0x8012DA01, "boyloadflag", SN_NOWARN)
set_name(0x8012DA02, "bannerflag", SN_NOWARN)
set_name(0x8012DA04, "pCowCels", SN_NOWARN)
set_name(0x8012E81C, "sgdwCowClicks", SN_NOWARN)
set_name(0x8012E820, "sgnCowMsg", SN_NOWARN)
set_name(0x800C1418, "Qtalklist", SN_NOWARN)
set_name(0x8012D9F4, "CowPlaying", SN_NOWARN)
set_name(0x800C103C, "AnimOrder", SN_NOWARN)
set_name(0x800C13B4, "TownCowX", SN_NOWARN)
set_name(0x800C13C0, "TownCowY", SN_NOWARN)
set_name(0x800C13CC, "TownCowDir", SN_NOWARN)
set_name(0x800C13D8, "cowoffx", SN_NOWARN)
set_name(0x800C13F8, "cowoffy", SN_NOWARN)
set_name(0x8012DA1C, "sfxdelay", SN_NOWARN)
set_name(0x8012DA20, "sfxdnum", SN_NOWARN)
set_name(0x8012DA14, "sghStream", SN_NOWARN)
set_name(0x800C24D8, "sgSFX", SN_NOWARN)
set_name(0x8012DA18, "sgpStreamSFX", SN_NOWARN)
set_name(0x8012DA24, "orgseed", SN_NOWARN)
set_name(0x8012E824, "sglGameSeed", SN_NOWARN)
set_name(0x8012DA28, "SeedCount", SN_NOWARN)
set_name(0x8012E828, "sgMemCrit", SN_NOWARN)
set_name(0x8012E82C, "sgnWidth", SN_NOWARN)
set_name(0x8012DA36, "msgflag", SN_NOWARN)
set_name(0x8012DA37, "msgdelay", SN_NOWARN)
set_name(0x800C3500, "msgtable", SN_NOWARN)
set_name(0x800C3450, "MsgStrings", SN_NOWARN)
set_name(0x8012DA35, "msgcnt", SN_NOWARN)
set_name(0x8012E830, "sgdwProgress", SN_NOWARN)
set_name(0x8012E834, "sgdwXY", SN_NOWARN)
set_name(0x800C3550, "AllItemsUseable", SN_NOWARN)
set_name(0x80123788, "AllItemsList", SN_NOWARN)
set_name(0x80124B28, "PL_Prefix", SN_NOWARN)
set_name(0x80125848, "PL_Suffix", SN_NOWARN)
set_name(0x80126748, "UniqueItemList", SN_NOWARN)
set_name(0x800C3764, "item", SN_NOWARN)
set_name(0x800C8364, "itemactive", SN_NOWARN)
set_name(0x800C83E4, "itemavail", SN_NOWARN)
set_name(0x800C8464, "UniqueItemFlag", SN_NOWARN)
set_name(0x8012DA70, "uitemflag", SN_NOWARN)
set_name(0x8012E838, "tem", SN_NOWARN)
set_name(0x8012F7A0, "curruitem", SN_NOWARN)
set_name(0x8012F840, "itemhold", SN_NOWARN)
set_name(0x8012DA74, "ScrollType", SN_NOWARN)
set_name(0x800C84E4, "ItemStr", SN_NOWARN)
set_name(0x800C8524, "SufStr", SN_NOWARN)
set_name(0x8012DA50, "numitems", SN_NOWARN)
set_name(0x8012DA54, "gnNumGetRecords", SN_NOWARN)
set_name(0x800C36C0, "ItemInvSnds", SN_NOWARN)
set_name(0x800C35F0, "ItemCAnimTbl", SN_NOWARN)
set_name(0x80128570, "SinTab", SN_NOWARN)
set_name(0x801285B0, "Item2Frm", SN_NOWARN)
set_name(0x800C369C, "ItemAnimLs", SN_NOWARN)
set_name(0x8012DA58, "ItemAnimSnds", SN_NOWARN)
set_name(0x8012DA5C, "idoppely", SN_NOWARN)
set_name(0x8012DA60, "ScrollFlag", SN_NOWARN)
set_name(0x800C374C, "premiumlvladd", SN_NOWARN)
set_name(0x800C9310, "LightList", SN_NOWARN)
set_name(0x800C9450, "lightactive", SN_NOWARN)
set_name(0x8012DA88, "numlights", SN_NOWARN)
set_name(0x8012DA8C, "lightmax", SN_NOWARN)
set_name(0x800C9478, "VisionList", SN_NOWARN)
set_name(0x8012DA90, "numvision", SN_NOWARN)
set_name(0x8012DA94, "dovision", SN_NOWARN)
set_name(0x8012DA98, "visionid", SN_NOWARN)
set_name(0x8012E83C, "disp_mask", SN_NOWARN)
set_name(0x8012E840, "weird", SN_NOWARN)
set_name(0x8012E844, "disp_tab_r", SN_NOWARN)
set_name(0x8012E848, "dispy_r", SN_NOWARN)
set_name(0x8012E84C, "disp_tab_g", SN_NOWARN)
set_name(0x8012E850, "dispy_g", SN_NOWARN)
set_name(0x8012E854, "disp_tab_b", SN_NOWARN)
set_name(0x8012E858, "dispy_b", SN_NOWARN)
set_name(0x8012E85C, "radius", SN_NOWARN)
set_name(0x8012E860, "bright", SN_NOWARN)
set_name(0x8012F850, "mult_tab", SN_NOWARN)
set_name(0x8012DA78, "lightflag", SN_NOWARN)
set_name(0x800C9024, "vCrawlTable", SN_NOWARN)
set_name(0x800C92D8, "RadiusAdj", SN_NOWARN)
set_name(0x800C8564, "CrawlTable", SN_NOWARN)
set_name(0x8012DA7C, "restore_r", SN_NOWARN)
set_name(0x8012DA80, "restore_g", SN_NOWARN)
set_name(0x8012DA84, "restore_b", SN_NOWARN)
set_name(0x800C92F0, "radius_tab", SN_NOWARN)
set_name(0x800C9300, "bright_tab", SN_NOWARN)
set_name(0x8012DAB9, "qtextflag", SN_NOWARN)
set_name(0x8012DABC, "qtextSpd", SN_NOWARN)
set_name(0x8012E864, "pMedTextCels", SN_NOWARN)
set_name(0x8012E868, "pTextBoxCels", SN_NOWARN)
set_name(0x8012E86C, "qtextptr", SN_NOWARN)
set_name(0x8012E870, "qtexty", SN_NOWARN)
set_name(0x8012E874, "qtextDelay", SN_NOWARN)
set_name(0x8012E878, "sgLastScroll", SN_NOWARN)
set_name(0x8012E87C, "scrolltexty", SN_NOWARN)
set_name(0x8012E880, "sglMusicVolumeSave", SN_NOWARN)
set_name(0x8012DAA8, "qtbodge", SN_NOWARN)
set_name(0x800C9638, "QBack", SN_NOWARN)
set_name(0x800C9648, "missiledata", SN_NOWARN)
set_name(0x800C9DB8, "misfiledata", SN_NOWARN)
set_name(0x800C9CA8, "MissPrintRoutines", SN_NOWARN)
set_name(0x800C9EA4, "sgLevels", SN_NOWARN)
set_name(0x800DDBF0, "sgLocals", SN_NOWARN)
set_name(0x8012F8D0, "sgJunk", SN_NOWARN)
set_name(0x8012E885, "sgbRecvCmd", SN_NOWARN)
set_name(0x8012E888, "sgdwRecvOffset", SN_NOWARN)
set_name(0x8012E88C, "sgbDeltaChunks", SN_NOWARN)
set_name(0x8012E88D, "sgbDeltaChanged", SN_NOWARN)
set_name(0x8012E890, "sgdwOwnerWait", SN_NOWARN)
set_name(0x8012E894, "sgpMegaPkt", SN_NOWARN)
set_name(0x8012E898, "sgpCurrPkt", SN_NOWARN)
set_name(0x8012E89C, "sgnCurrMegaPlayer", SN_NOWARN)
set_name(0x8012DAD5, "deltaload", SN_NOWARN)
set_name(0x8012DAD6, "gbBufferMsgs", SN_NOWARN)
set_name(0x8012DAD8, "dwRecCount", SN_NOWARN)
set_name(0x8012DADC, "LevelOut", SN_NOWARN)
set_name(0x8012DAF2, "gbMaxPlayers", SN_NOWARN)
set_name(0x8012DAF3, "gbActivePlayers", SN_NOWARN)
set_name(0x8012DAF4, "gbGameDestroyed", SN_NOWARN)
set_name(0x8012DAF5, "gbDeltaSender", SN_NOWARN)
set_name(0x8012DAF6, "gbSelectProvider", SN_NOWARN)
set_name(0x8012DAF7, "gbSomebodyWonGameKludge", SN_NOWARN)
set_name(0x8012E8A0, "sgbSentThisCycle", SN_NOWARN)
set_name(0x8012E8A4, "sgdwGameLoops", SN_NOWARN)
set_name(0x8012E8A8, "sgwPackPlrOffsetTbl", SN_NOWARN)
set_name(0x8012E8AC, "sgbPlayerLeftGameTbl", SN_NOWARN)
set_name(0x8012E8B0, "sgdwPlayerLeftReasonTbl", SN_NOWARN)
set_name(0x8012E8B8, "sgbSendDeltaTbl", SN_NOWARN)
set_name(0x8012E8C0, "sgGameInitInfo", SN_NOWARN)
set_name(0x8012E8C8, "sgbTimeout", SN_NOWARN)
set_name(0x8012E8CC, "sglTimeoutStart", SN_NOWARN)
set_name(0x8012DAEC, "gszVersionNumber", SN_NOWARN)
set_name(0x8012DAF1, "sgbNetInited", SN_NOWARN)
set_name(0x800DEC58, "ObjTypeConv", SN_NOWARN)
set_name(0x800DEE1C, "AllObjects", SN_NOWARN)
set_name(0x80128CD8, "ObjMasterLoadList", SN_NOWARN)
set_name(0x800DF5FC, "object", SN_NOWARN)
set_name(0x8012DB18, "numobjects", SN_NOWARN)
set_name(0x800E0BD0, "objectactive", SN_NOWARN)
set_name(0x800E0C50, "objectavail", SN_NOWARN)
set_name(0x8012DB1C, "InitObjFlag", SN_NOWARN)
set_name(0x8012DB20, "trapid", SN_NOWARN)
set_name(0x800E0CD0, "ObjFileList", SN_NOWARN)
set_name(0x8012DB24, "trapdir", SN_NOWARN)
set_name(0x8012DB28, "leverid", SN_NOWARN)
set_name(0x8012DB10, "numobjfiles", SN_NOWARN)
set_name(0x800DF514, "bxadd", SN_NOWARN)
set_name(0x800DF534, "byadd", SN_NOWARN)
set_name(0x800DF5BC, "shrineavail", SN_NOWARN)
set_name(0x800DF554, "shrinestrs", SN_NOWARN)
set_name(0x800DF5D8, "StoryBookName", SN_NOWARN)
set_name(0x8012DB14, "myscale", SN_NOWARN)
set_name(0x8012DB3C, "gbValidSaveFile", SN_NOWARN)
set_name(0x8012DB38, "DoLoadedChar", SN_NOWARN)
set_name(0x800E0EF0, "plr", SN_NOWARN)
set_name(0x8012DB5C, "myplr", SN_NOWARN)
set_name(0x8012DB60, "deathdelay", SN_NOWARN)
set_name(0x8012DB64, "deathflag", SN_NOWARN)
set_name(0x8012DB65, "light_rad", SN_NOWARN)
set_name(0x8012DB54, "light_level", SN_NOWARN)
set_name(0x800E0DE8, "MaxStats", SN_NOWARN)
set_name(0x8012DB4C, "PlrStructSize", SN_NOWARN)
set_name(0x8012DB50, "ItemStructSize", SN_NOWARN)
set_name(0x800E0CF8, "plrxoff", SN_NOWARN)
set_name(0x800E0D1C, "plryoff", SN_NOWARN)
set_name(0x800E0D40, "plrxoff2", SN_NOWARN)
set_name(0x800E0D64, "plryoff2", SN_NOWARN)
set_name(0x800E0D88, "PlrGFXAnimLens", SN_NOWARN)
set_name(0x800E0DAC, "StrengthTbl", SN_NOWARN)
set_name(0x800E0DB8, "MagicTbl", SN_NOWARN)
set_name(0x800E0DC4, "DexterityTbl", SN_NOWARN)
set_name(0x800E0DD0, "VitalityTbl", SN_NOWARN)
set_name(0x800E0DDC, "ToBlkTbl", SN_NOWARN)
set_name(0x800E0E18, "ExpLvlsTbl", SN_NOWARN)
set_name(0x800E5778, "quests", SN_NOWARN)
set_name(0x8012DB94, "pQLogCel", SN_NOWARN)
set_name(0x8012DB98, "ReturnLvlX", SN_NOWARN)
set_name(0x8012DB9C, "ReturnLvlY", SN_NOWARN)
set_name(0x8012DBA0, "ReturnLvl", SN_NOWARN)
set_name(0x8012DBA4, "ReturnLvlT", SN_NOWARN)
set_name(0x8012DBA8, "rporttest", SN_NOWARN)
set_name(0x8012DBAC, "qline", SN_NOWARN)
set_name(0x8012DBB0, "numqlines", SN_NOWARN)
set_name(0x8012DBB4, "qtopline", SN_NOWARN)
set_name(0x8012F8E8, "qlist", SN_NOWARN)
set_name(0x8012E8D0, "QSRect", SN_NOWARN)
set_name(0x8012DB71, "questlog", SN_NOWARN)
set_name(0x800E5640, "questlist", SN_NOWARN)
set_name(0x8012DB74, "ALLQUESTS", SN_NOWARN)
set_name(0x800E5754, "QuestGroup1", SN_NOWARN)
set_name(0x800E5760, "QuestGroup2", SN_NOWARN)
set_name(0x800E576C, "QuestGroup3", SN_NOWARN)
set_name(0x8012DB78, "QuestGroup4", SN_NOWARN)
set_name(0x8012DB90, "WaterDone", SN_NOWARN)
set_name(0x800E5740, "questtrigstr", SN_NOWARN)
set_name(0x8012DB80, "QS_PX", SN_NOWARN)
set_name(0x8012DB84, "QS_PY", SN_NOWARN)
set_name(0x8012DB88, "QS_PW", SN_NOWARN)
set_name(0x8012DB8C, "QS_PH", SN_NOWARN)
set_name(0x8012F928, "QSBack", SN_NOWARN)
set_name(0x800E58B8, "spelldata", SN_NOWARN)
set_name(0x8012DBEF, "stextflag", SN_NOWARN)
set_name(0x800E6160, "smithitem", SN_NOWARN)
set_name(0x800E6D40, "premiumitem", SN_NOWARN)
set_name(0x8012DBF0, "numpremium", SN_NOWARN)
set_name(0x8012DBF4, "premiumlevel", SN_NOWARN)
set_name(0x800E70D0, "witchitem", SN_NOWARN)
set_name(0x800E7CB0, "boyitem", SN_NOWARN)
set_name(0x8012DBF8, "boylevel", SN_NOWARN)
set_name(0x800E7D48, "golditem", SN_NOWARN)
set_name(0x800E7DE0, "healitem", SN_NOWARN)
set_name(0x8012DBFC, "stextsize", SN_NOWARN)
set_name(0x8012DBFD, "stextscrl", SN_NOWARN)
set_name(0x8012E8D8, "stextsel", SN_NOWARN)
set_name(0x8012E8DC, "stextlhold", SN_NOWARN)
set_name(0x8012E8E0, "stextshold", SN_NOWARN)
set_name(0x8012E8E4, "stextvhold", SN_NOWARN)
set_name(0x8012E8E8, "stextsval", SN_NOWARN)
set_name(0x8012E8EC, "stextsmax", SN_NOWARN)
set_name(0x8012E8F0, "stextup", SN_NOWARN)
set_name(0x8012E8F4, "stextdown", SN_NOWARN)
set_name(0x8012E8F8, "stextscrlubtn", SN_NOWARN)
set_name(0x8012E8F9, "stextscrldbtn", SN_NOWARN)
set_name(0x8012E8FA, "SItemListFlag", SN_NOWARN)
set_name(0x8012F938, "stext", SN_NOWARN)
set_name(0x800E89C0, "storehold", SN_NOWARN)
set_name(0x800EA640, "storehidx", SN_NOWARN)
set_name(0x8012E8FC, "storenumh", SN_NOWARN)
set_name(0x8012E900, "gossipstart", SN_NOWARN)
set_name(0x8012E904, "gossipend", SN_NOWARN)
set_name(0x8012E908, "StoreBackRect", SN_NOWARN)
set_name(0x8012E910, "talker", SN_NOWARN)
set_name(0x8012DBDC, "pSTextBoxCels", SN_NOWARN)
set_name(0x8012DBE0, "pSTextSlidCels", SN_NOWARN)
set_name(0x8012DBE4, "SStringY", SN_NOWARN)
set_name(0x800E603C, "SBack", SN_NOWARN)
set_name(0x800E604C, "SStringYNorm", SN_NOWARN)
set_name(0x800E609C, "SStringYBuy0", SN_NOWARN)
set_name(0x800E60EC, "SStringYBuy1", SN_NOWARN)
set_name(0x800E613C, "talkname", SN_NOWARN)
set_name(0x8012DBEE, "InStoreFlag", SN_NOWARN)
set_name(0x8012A024, "alltext", SN_NOWARN)
set_name(0x8012DC0C, "gdwAllTextEntries", SN_NOWARN)
set_name(0x8012E914, "P3Tiles", SN_NOWARN)
set_name(0x8012DC1C, "tile", SN_NOWARN)
set_name(0x8012DC2C, "_trigflag", SN_NOWARN)
set_name(0x800EA8A8, "trigs", SN_NOWARN)
set_name(0x8012DC30, "numtrigs", SN_NOWARN)
set_name(0x8012DC34, "townwarps", SN_NOWARN)
set_name(0x8012DC38, "TWarpFrom", SN_NOWARN)
set_name(0x800EA670, "TownDownList", SN_NOWARN)
set_name(0x800EA69C, "TownWarp1List", SN_NOWARN)
set_name(0x800EA6D0, "L1UpList", SN_NOWARN)
set_name(0x800EA700, "L1DownList", SN_NOWARN)
set_name(0x800EA728, "L2UpList", SN_NOWARN)
set_name(0x800EA734, "L2DownList", SN_NOWARN)
set_name(0x800EA748, "L2TWarpUpList", SN_NOWARN)
set_name(0x800EA754, "L3UpList", SN_NOWARN)
set_name(0x800EA790, "L3DownList", SN_NOWARN)
set_name(0x800EA7B4, "L3TWarpUpList", SN_NOWARN)
set_name(0x800EA7EC, "L4UpList", SN_NOWARN)
set_name(0x800EA7FC, "L4DownList", SN_NOWARN)
set_name(0x800EA814, "L4TWarpUpList", SN_NOWARN)
set_name(0x800EA824, "L4PentaList", SN_NOWARN)
set_name(0x8012DC51, "gbSndInited", SN_NOWARN)
set_name(0x8012DC54, "sglMasterVolume", SN_NOWARN)
set_name(0x8012DC58, "sglMusicVolume", SN_NOWARN)
set_name(0x8012DC5C, "sglSoundVolume", SN_NOWARN)
set_name(0x8012DC60, "sglSpeechVolume", SN_NOWARN)
set_name(0x8012DC64, "sgnMusicTrack", SN_NOWARN)
set_name(0x8012DC52, "gbDupSounds", SN_NOWARN)
set_name(0x8012DC68, "sghMusic", SN_NOWARN)
set_name(0x8012AE58, "sgszMusicTracks", SN_NOWARN)
set_name(0x8012DC80, "_pcurr_inv", SN_NOWARN)
set_name(0x800EA8F8, "_pfind_list", SN_NOWARN)
set_name(0x8012DC88, "_pfind_index", SN_NOWARN)
set_name(0x8012DC8C, "_pfindx", SN_NOWARN)
set_name(0x8012DC90, "_pfindy", SN_NOWARN)
set_name(0x8012DC92, "automapmoved", SN_NOWARN)
set_name(0x8012DC75, "flyflag", SN_NOWARN)
set_name(0x8012DC76, "seen_combo", SN_NOWARN)
set_name(0x80130658, "GPad1", SN_NOWARN)
set_name(0x801306F8, "GPad2", SN_NOWARN)
set_name(0x8012E918, "CurrentProc", SN_NOWARN)
set_name(0x8012AFEC, "AllMsgs", SN_NOWARN)
set_name(0x8012DCCC, "NumOfStrings", SN_NOWARN)
set_name(0x8012DCA0, "LanguageType", SN_NOWARN)
set_name(0x8012DCA4, "hndText", SN_NOWARN)
set_name(0x8012DCA8, "TextPtr", SN_NOWARN)
set_name(0x8012DCAC, "LangDbNo", SN_NOWARN)
set_name(0x8012DCDC, "MissDat", SN_NOWARN)
set_name(0x8012DCE0, "CharFade", SN_NOWARN)
set_name(0x8012DCE4, "rotateness", SN_NOWARN)
set_name(0x8012DCE8, "spiralling_shape", SN_NOWARN)
set_name(0x8012DCEC, "down", SN_NOWARN)
set_name(0x800EA948, "MlTab", SN_NOWARN)
set_name(0x800EA958, "QlTab", SN_NOWARN)
set_name(0x800EA968, "ObjPrintFuncs", SN_NOWARN)
set_name(0x8012DD08, "MyXoff1", SN_NOWARN)
set_name(0x8012DD0C, "MyYoff1", SN_NOWARN)
set_name(0x8012DD10, "MyXoff2", SN_NOWARN)
set_name(0x8012DD14, "MyYoff2", SN_NOWARN)
set_name(0x8012DD24, "iscflag", SN_NOWARN)
set_name(0x8012DD31, "sgbFadedIn", SN_NOWARN)
set_name(0x8012DD32, "screenbright", SN_NOWARN)
set_name(0x8012DD34, "faderate", SN_NOWARN)
set_name(0x8012DD38, "fading", SN_NOWARN)
set_name(0x8012DD44, "FadeCoords", SN_NOWARN)
set_name(0x8012DD3C, "st", SN_NOWARN)
set_name(0x8012DD40, "mode", SN_NOWARN)
set_name(0x800EAAF0, "portal", SN_NOWARN)
set_name(0x8012DD76, "portalindex", SN_NOWARN)
set_name(0x8012DD70, "WarpDropX", SN_NOWARN)
set_name(0x8012DD74, "WarpDropY", SN_NOWARN)
set_name(0x800EAB08, "MyVerString", SN_NOWARN)
set_name(0x8012DED4, "Year", SN_NOWARN)
set_name(0x8012DED8, "Day", SN_NOWARN)
set_name(0x8012E91C, "tbuff", SN_NOWARN)
set_name(0x800EAB80, "IconBuffer", SN_NOWARN)
set_name(0x8012E920, "HR1", SN_NOWARN)
set_name(0x8012E921, "HR2", SN_NOWARN)
set_name(0x8012E922, "HR3", SN_NOWARN)
set_name(0x8012E923, "VR1", SN_NOWARN)
set_name(0x8012E924, "VR2", SN_NOWARN)
set_name(0x8012E925, "VR3", SN_NOWARN)
set_name(0x8012DF48, "pHallList", SN_NOWARN)
set_name(0x8012DF4C, "nRoomCnt", SN_NOWARN)
set_name(0x8012DF50, "nSx1", SN_NOWARN)
set_name(0x8012DF54, "nSy1", SN_NOWARN)
set_name(0x8012DF58, "nSx2", SN_NOWARN)
set_name(0x8012DF5C, "nSy2", SN_NOWARN)
set_name(0x8012DF00, "Area_Min", SN_NOWARN)
set_name(0x8012DF04, "Room_Max", SN_NOWARN)
set_name(0x8012DF08, "Room_Min", SN_NOWARN)
set_name(0x8012DF0C, "BIG3", SN_NOWARN)
set_name(0x8012DF14, "BIG4", SN_NOWARN)
set_name(0x8012DF1C, "BIG6", SN_NOWARN)
set_name(0x8012DF24, "BIG7", SN_NOWARN)
set_name(0x8012DF2C, "RUINS1", SN_NOWARN)
set_name(0x8012DF30, "RUINS2", SN_NOWARN)
set_name(0x8012DF34, "RUINS3", SN_NOWARN)
set_name(0x8012DF38, "RUINS4", SN_NOWARN)
set_name(0x8012DF3C, "RUINS5", SN_NOWARN)
set_name(0x8012DF40, "RUINS6", SN_NOWARN)
set_name(0x8012DF44, "RUINS7", SN_NOWARN)
set_name(0x8012E928, "abyssx", SN_NOWARN)
set_name(0x8012E92C, "lavapool", SN_NOWARN)
set_name(0x8012DFE8, "lockoutcnt", SN_NOWARN)
set_name(0x8012DF6C, "L3TITE12", SN_NOWARN)
set_name(0x8012DF74, "L3TITE13", SN_NOWARN)
set_name(0x8012DF7C, "L3CREV1", SN_NOWARN)
set_name(0x8012DF84, "L3CREV2", SN_NOWARN)
set_name(0x8012DF8C, "L3CREV3", SN_NOWARN)
set_name(0x8012DF94, "L3CREV4", SN_NOWARN)
set_name(0x8012DF9C, "L3CREV5", SN_NOWARN)
set_name(0x8012DFA4, "L3CREV6", SN_NOWARN)
set_name(0x8012DFAC, "L3CREV7", SN_NOWARN)
set_name(0x8012DFB4, "L3CREV8", SN_NOWARN)
set_name(0x8012DFBC, "L3CREV9", SN_NOWARN)
set_name(0x8012DFC4, "L3CREV10", SN_NOWARN)
set_name(0x8012DFCC, "L3CREV11", SN_NOWARN)
set_name(0x8012DFD4, "L3XTRA1", SN_NOWARN)
set_name(0x8012DFD8, "L3XTRA2", SN_NOWARN)
set_name(0x8012DFDC, "L3XTRA3", SN_NOWARN)
set_name(0x8012DFE0, "L3XTRA4", SN_NOWARN)
set_name(0x8012DFE4, "L3XTRA5", SN_NOWARN)
set_name(0x8012DFEC, "diabquad1x", SN_NOWARN)
set_name(0x8012DFF0, "diabquad2x", SN_NOWARN)
set_name(0x8012DFF4, "diabquad3x", SN_NOWARN)
set_name(0x8012DFF8, "diabquad4x", SN_NOWARN)
set_name(0x8012DFFC, "diabquad1y", SN_NOWARN)
set_name(0x8012E000, "diabquad2y", SN_NOWARN)
set_name(0x8012E004, "diabquad3y", SN_NOWARN)
set_name(0x8012E008, "diabquad4y", SN_NOWARN)
set_name(0x8012E00C, "SP4x1", SN_NOWARN)
set_name(0x8012E010, "SP4y1", SN_NOWARN)
set_name(0x8012E014, "SP4x2", SN_NOWARN)
set_name(0x8012E018, "SP4y2", SN_NOWARN)
set_name(0x8012E01C, "l4holdx", SN_NOWARN)
set_name(0x8012E020, "l4holdy", SN_NOWARN)
set_name(0x8012E930, "lpSetPiece1", SN_NOWARN)
set_name(0x8012E934, "lpSetPiece2", SN_NOWARN)
set_name(0x8012E938, "lpSetPiece3", SN_NOWARN)
set_name(0x8012E93C, "lpSetPiece4", SN_NOWARN)
set_name(0x8012E940, "lppSetPiece2", SN_NOWARN)
set_name(0x8012E944, "lppSetPiece3", SN_NOWARN)
set_name(0x8012E948, "lppSetPiece4", SN_NOWARN)
set_name(0x8012E030, "SkelKingTrans1", SN_NOWARN)
set_name(0x8012E038, "SkelKingTrans2", SN_NOWARN)
set_name(0x800EAE80, "SkelKingTrans3", SN_NOWARN)
set_name(0x800EAE94, "SkelKingTrans4", SN_NOWARN)
set_name(0x800EAEB0, "SkelChamTrans1", SN_NOWARN)
set_name(0x8012E040, "SkelChamTrans2", SN_NOWARN)
set_name(0x800EAEC4, "SkelChamTrans3", SN_NOWARN)
set_name(0x8012E134, "DoUiForChooseMonster", SN_NOWARN)
set_name(0x800EAEE8, "MgToText", SN_NOWARN)
set_name(0x800EAF70, "StoryText", SN_NOWARN)
set_name(0x800EAF94, "dungeon", SN_NOWARN)
set_name(0x800EC194, "pdungeon", SN_NOWARN)
set_name(0x800EC7D4, "dflags", SN_NOWARN)
set_name(0x8012E158, "setpc_x", SN_NOWARN)
set_name(0x8012E15C, "setpc_y", SN_NOWARN)
set_name(0x8012E160, "setpc_w", SN_NOWARN)
set_name(0x8012E164, "setpc_h", SN_NOWARN)
set_name(0x8012E168, "setloadflag", SN_NOWARN)
set_name(0x8012E16C, "pMegaTiles", SN_NOWARN)
set_name(0x800ECE14, "nBlockTable", SN_NOWARN)
set_name(0x800ED618, "nSolidTable", SN_NOWARN)
set_name(0x800EDE1C, "nTransTable", SN_NOWARN)
set_name(0x800EE620, "nMissileTable", SN_NOWARN)
set_name(0x800EEE24, "nTrapTable", SN_NOWARN)
set_name(0x8012E170, "dminx", SN_NOWARN)
set_name(0x8012E174, "dminy", SN_NOWARN)
set_name(0x8012E178, "dmaxx", SN_NOWARN)
set_name(0x8012E17C, "dmaxy", SN_NOWARN)
set_name(0x8012E180, "gnDifficulty", SN_NOWARN)
set_name(0x8012E184, "currlevel", SN_NOWARN)
set_name(0x8012E185, "leveltype", SN_NOWARN)
set_name(0x8012E186, "setlevel", SN_NOWARN)
set_name(0x8012E187, "setlvlnum", SN_NOWARN)
set_name(0x8012E188, "setlvltype", SN_NOWARN)
set_name(0x8012E18C, "ViewX", SN_NOWARN)
set_name(0x8012E190, "ViewY", SN_NOWARN)
set_name(0x8012E194, "ViewDX", SN_NOWARN)
set_name(0x8012E198, "ViewDY", SN_NOWARN)
set_name(0x8012E19C, "ViewBX", SN_NOWARN)
set_name(0x8012E1A0, "ViewBY", SN_NOWARN)
set_name(0x800EF628, "ScrollInfo", SN_NOWARN)
set_name(0x8012E1A4, "LvlViewX", SN_NOWARN)
set_name(0x8012E1A8, "LvlViewY", SN_NOWARN)
set_name(0x8012E1AC, "btmbx", SN_NOWARN)
set_name(0x8012E1B0, "btmby", SN_NOWARN)
set_name(0x8012E1B4, "btmdx", SN_NOWARN)
set_name(0x8012E1B8, "btmdy", SN_NOWARN)
set_name(0x8012E1BC, "MicroTileLen", SN_NOWARN)
set_name(0x8012E1C0, "TransVal", SN_NOWARN)
set_name(0x800EF63C, "TransList", SN_NOWARN)
set_name(0x8012E1C4, "themeCount", SN_NOWARN)
set_name(0x800EF65C, "dung_map", SN_NOWARN)
set_name(0x8011191C, "dung_map_r", SN_NOWARN)
set_name(0x80112480, "dung_map_g", SN_NOWARN)
set_name(0x80112FE4, "dung_map_b", SN_NOWARN)
set_name(0x80113B48, "MinisetXY", SN_NOWARN)
set_name(0x8012E150, "pSetPiece", SN_NOWARN)
set_name(0x8012E154, "DungSize", SN_NOWARN)
set_name(0x80113D14, "theme", SN_NOWARN)
set_name(0x8012E204, "numthemes", SN_NOWARN)
set_name(0x8012E208, "zharlib", SN_NOWARN)
set_name(0x8012E20C, "armorFlag", SN_NOWARN)
set_name(0x8012E20D, "bCrossFlag", SN_NOWARN)
set_name(0x8012E20E, "weaponFlag", SN_NOWARN)
set_name(0x8012E210, "themex", SN_NOWARN)
set_name(0x8012E214, "themey", SN_NOWARN)
set_name(0x8012E218, "themeVar1", SN_NOWARN)
set_name(0x8012E21C, "bFountainFlag", SN_NOWARN)
set_name(0x8012E21D, "cauldronFlag", SN_NOWARN)
set_name(0x8012E21E, "mFountainFlag", SN_NOWARN)
set_name(0x8012E21F, "pFountainFlag", SN_NOWARN)
set_name(0x8012E220, "tFountainFlag", SN_NOWARN)
set_name(0x8012E221, "treasureFlag", SN_NOWARN)
set_name(0x8012E224, "ThemeGoodIn", SN_NOWARN)
set_name(0x80113BF4, "ThemeGood", SN_NOWARN)
set_name(0x80113C04, "trm5x", SN_NOWARN)
set_name(0x80113C68, "trm5y", SN_NOWARN)
set_name(0x80113CCC, "trm3x", SN_NOWARN)
set_name(0x80113CF0, "trm3y", SN_NOWARN)
set_name(0x8012E2FC, "nummissiles", SN_NOWARN)
set_name(0x80113F2C, "missileactive", SN_NOWARN)
set_name(0x80114120, "missileavail", SN_NOWARN)
set_name(0x8012E300, "MissilePreFlag", SN_NOWARN)
set_name(0x80114314, "missile", SN_NOWARN)
set_name(0x8012E301, "ManashieldFlag", SN_NOWARN)
set_name(0x8012E302, "ManashieldFlag2", SN_NOWARN)
set_name(0x80113EA4, "XDirAdd", SN_NOWARN)
set_name(0x80113EC4, "YDirAdd", SN_NOWARN)
set_name(0x8012E2C9, "fadetor", SN_NOWARN)
set_name(0x8012E2CA, "fadetog", SN_NOWARN)
set_name(0x8012E2CB, "fadetob", SN_NOWARN)
set_name(0x80113EE4, "ValueTable", SN_NOWARN)
set_name(0x80113EF4, "StringTable", SN_NOWARN)
set_name(0x80116BC4, "monster", SN_NOWARN)
set_name(0x8012E364, "nummonsters", SN_NOWARN)
set_name(0x8011C344, "monstactive", SN_NOWARN)
set_name(0x8011C4D4, "monstkills", SN_NOWARN)
set_name(0x8011C664, "Monsters", SN_NOWARN)
set_name(0x8012E368, "monstimgtot", SN_NOWARN)
set_name(0x8012E36C, "totalmonsters", SN_NOWARN)
set_name(0x8012E370, "uniquetrans", SN_NOWARN)
set_name(0x8012E94C, "sgbSaveSoundOn", SN_NOWARN)
set_name(0x8012E334, "offset_x", SN_NOWARN)
set_name(0x8012E33C, "offset_y", SN_NOWARN)
set_name(0x8012E31C, "left", SN_NOWARN)
set_name(0x8012E324, "right", SN_NOWARN)
set_name(0x8012E32C, "opposite", SN_NOWARN)
set_name(0x8012E310, "nummtypes", SN_NOWARN)
set_name(0x8012E314, "animletter", SN_NOWARN)
set_name(0x80116A24, "MWVel", SN_NOWARN)
set_name(0x8012E344, "rnd5", SN_NOWARN)
set_name(0x8012E348, "rnd10", SN_NOWARN)
set_name(0x8012E34C, "rnd20", SN_NOWARN)
set_name(0x8012E350, "rnd60", SN_NOWARN)
set_name(0x80116B44, "AiProc", SN_NOWARN)
set_name(0x8011CB3C, "monsterdata", SN_NOWARN)
set_name(0x8011E57C, "MonstConvTbl", SN_NOWARN)
set_name(0x8011E5FC, "MonstAvailTbl", SN_NOWARN)
set_name(0x8011E66C, "UniqMonst", SN_NOWARN)
set_name(0x8011C924, "TransPals", SN_NOWARN)
set_name(0x8011C824, "StonePals", SN_NOWARN)
set_name(0x8012E3A8, "invflag", SN_NOWARN)
set_name(0x8012E3A9, "drawsbarflag", SN_NOWARN)
set_name(0x8012E3AC, "InvBackY", SN_NOWARN)
set_name(0x8012E3B0, "InvCursPos", SN_NOWARN)
set_name(0x8011F614, "InvSlotTable", SN_NOWARN)
set_name(0x8012E3B4, "InvBackAY", SN_NOWARN)
set_name(0x8012E3B8, "InvSel", SN_NOWARN)
set_name(0x8012E3BC, "ItemW", SN_NOWARN)
set_name(0x8012E3C0, "ItemH", SN_NOWARN)
set_name(0x8012E3C4, "ItemNo", SN_NOWARN)
set_name(0x8012E3C8, "BRect", SN_NOWARN)
set_name(0x8012E390, "InvPanelTData", SN_NOWARN)
set_name(0x8012E394, "InvGfxTData", SN_NOWARN)
set_name(0x8012E38C, "InvPageNo", SN_NOWARN)
set_name(0x8011EF9C, "AP2x2Tbl", SN_NOWARN)
set_name(0x8011EFC4, "InvRect", SN_NOWARN)
set_name(0x8011F20C, "InvGfxTable", SN_NOWARN)
set_name(0x8011F4AC, "InvItemWidth", SN_NOWARN)
set_name(0x8011F560, "InvItemHeight", SN_NOWARN)
set_name(0x8012E3A0, "InvOn", SN_NOWARN)
set_name(0x8012E3A4, "sgdwLastTime", SN_NOWARN)
set_name(0x8012E3FF, "automapflag", SN_NOWARN)
set_name(0x8011F678, "automapview", SN_NOWARN)
set_name(0x8011F740, "automaptype", SN_NOWARN)
set_name(0x8012E400, "AMLWallFlag", SN_NOWARN)
set_name(0x8012E401, "AMRWallFlag", SN_NOWARN)
set_name(0x8012E402, "AMLLWallFlag", SN_NOWARN)
set_name(0x8012E403, "AMLRWallFlag", SN_NOWARN)
set_name(0x8012E404, "AMDirtFlag", SN_NOWARN)
set_name(0x8012E405, "AMColumnFlag", SN_NOWARN)
set_name(0x8012E406, "AMStairFlag", SN_NOWARN)
set_name(0x8012E407, "AMLDoorFlag", SN_NOWARN)
set_name(0x8012E408, "AMLGrateFlag", SN_NOWARN)
set_name(0x8012E409, "AMLArchFlag", SN_NOWARN)
set_name(0x8012E40A, "AMRDoorFlag", SN_NOWARN)
set_name(0x8012E40B, "AMRGrateFlag", SN_NOWARN)
set_name(0x8012E40C, "AMRArchFlag", SN_NOWARN)
set_name(0x8012E410, "AutoMapX", SN_NOWARN)
set_name(0x8012E414, "AutoMapY", SN_NOWARN)
set_name(0x8012E418, "AutoMapXOfs", SN_NOWARN)
set_name(0x8012E41C, "AutoMapYOfs", SN_NOWARN)
set_name(0x8012E420, "AMPlayerX", SN_NOWARN)
set_name(0x8012E424, "AMPlayerY", SN_NOWARN)
set_name(0x8012E3DC, "AutoMapScale", SN_NOWARN)
set_name(0x8012E3E0, "AutoMapPlayerR", SN_NOWARN)
set_name(0x8012E3E1, "AutoMapPlayerG", SN_NOWARN)
set_name(0x8012E3E2, "AutoMapPlayerB", SN_NOWARN)
set_name(0x8012E3E3, "AutoMapWallR", SN_NOWARN)
set_name(0x8012E3E4, "AutoMapWallG", SN_NOWARN)
set_name(0x8012E3E5, "AutoMapWallB", SN_NOWARN)
set_name(0x8012E3E6, "AutoMapDoorR", SN_NOWARN)
set_name(0x8012E3E7, "AutoMapDoorG", SN_NOWARN)
set_name(0x8012E3E8, "AutoMapDoorB", SN_NOWARN)
set_name(0x8012E3E9, "AutoMapColumnR", SN_NOWARN)
set_name(0x8012E3EA, "AutoMapColumnG", SN_NOWARN)
set_name(0x8012E3EB, "AutoMapColumnB", SN_NOWARN)
set_name(0x8012E3EC, "AutoMapArchR", SN_NOWARN)
set_name(0x8012E3ED, "AutoMapArchG", SN_NOWARN)
set_name(0x8012E3EE, "AutoMapArchB", SN_NOWARN)
set_name(0x8012E3EF, "AutoMapStairR", SN_NOWARN)
set_name(0x8012E3F0, "AutoMapStairG", SN_NOWARN)
set_name(0x8012E3F1, "AutoMapStairB", SN_NOWARN)
set_name(0x8011F660, "SetLevelName", SN_NOWARN)
set_name(0x8012EAA8, "GazTick", SN_NOWARN)
set_name(0x80135560, "RndTabs", SN_NOWARN)
set_name(0x800A89D4, "DefaultRnd", SN_NOWARN)
set_name(0x8012EAD0, "PollFunc", SN_NOWARN)
set_name(0x8012EAB4, "MsgFunc", SN_NOWARN)
set_name(0x8012EB00, "ErrorFunc", SN_NOWARN)
set_name(0x8012E9D4, "ActiveTasks", SN_NOWARN)
set_name(0x8012E9D8, "CurrentTask", SN_NOWARN)
set_name(0x8012E9DC, "T", SN_NOWARN)
set_name(0x8012E9E0, "MemTypeForTasker", SN_NOWARN)
set_name(0x80132D90, "SchEnv", SN_NOWARN)
set_name(0x8012E9E4, "ExecId", SN_NOWARN)
set_name(0x8012E9E8, "ExecMask", SN_NOWARN)
set_name(0x8012E9EC, "TasksActive", SN_NOWARN)
set_name(0x8012E9F0, "EpiFunc", SN_NOWARN)
set_name(0x8012E9F4, "ProFunc", SN_NOWARN)
set_name(0x8012E9F8, "EpiProId", SN_NOWARN)
set_name(0x8012E9FC, "EpiProMask", SN_NOWARN)
set_name(0x8012EA00, "DoTasksPrologue", SN_NOWARN)
set_name(0x8012EA04, "DoTasksEpilogue", SN_NOWARN)
set_name(0x8012EA08, "StackFloodCallback", SN_NOWARN)
set_name(0x8012EA0C, "ExtraStackProtection", SN_NOWARN)
set_name(0x8012EA10, "ExtraStackSizeLongs", SN_NOWARN)
set_name(0x8012EABC, "LastPtr", SN_NOWARN)
set_name(0x800A8A0C, "WorkMemInfo", SN_NOWARN)
set_name(0x8012EA14, "MemInitBlocks", SN_NOWARN)
set_name(0x80132DC0, "MemHdrBlocks", SN_NOWARN)
set_name(0x8012EA18, "FreeBlocks", SN_NOWARN)
set_name(0x8012EA1C, "LastError", SN_NOWARN)
set_name(0x8012EA20, "TimeStamp", SN_NOWARN)
set_name(0x8012EA24, "FullErrorChecking", SN_NOWARN)
set_name(0x8012EA28, "LastAttemptedAlloc", SN_NOWARN)
set_name(0x8012EA2C, "LastDeallocedBlock", SN_NOWARN)
set_name(0x8012EA30, "VerbLev", SN_NOWARN)
set_name(0x8012EA34, "NumOfFreeHdrs", SN_NOWARN)
set_name(0x8012EA38, "LastTypeAlloced", SN_NOWARN)
set_name(0x8012EA3C, "AllocFilter", SN_NOWARN)
set_name(0x800A8A14, "GalErrors", SN_NOWARN)
set_name(0x800A8A3C, "PhantomMem", SN_NOWARN)
set_name(0x80133F40, "buf", SN_NOWARN)
set_name(0x800A8A64, "NULL_REP", SN_NOWARN) | 0.16175 | 0.060891 |
import sys
import dlib
import cv2
import os
import argparse
import largest_face_detector
import copy
Images_Folder = 'train/personB'
OutFace_Folder = 'train/personB_face/'
Images_Path = os.path.join(os.path.realpath('.'), Images_Folder)
Out_Path = os.path.join(os.path.realpath('.'), OutFace_Folder)
pictures = os.listdir(Images_Path)
# initialize hog + svm based face detector
detector = dlib.get_frontal_face_detector()
# # handle command line arguments
# ap = argparse.ArgumentParser()
# ap.add_argument('-w', '--weights', default='./mmod_human_face_detector.dat',
# help='path to weights file')
# args = ap.parse_args()
# # initialize CNN based face detector
# detector = dlib.cnn_face_detection_model_v1(args.weights)
print(pictures)
def rotate(img):
rows,cols,_ = img.shape
M = cv2.getRotationMatrix2D((cols, rows ), 0, 1)
dst = cv2.warpAffine(img, M, (cols, rows))
return dst
for f in pictures:
print('processing image')
img = cv2.imread(os.path.join(Images_Path,f), cv2.IMREAD_COLOR)
b, g, r = cv2.split(img)
img2 = cv2.merge([r, g, b])
img = rotate(img)
# f_copy = copy.deepcopy(f)
# image = largest_face_detector.detect_largest_face(str(Images_Path)+'/'+str(f_copy))
# cv2.imwrite(OutFace_Folder+f_copy[:-4]+"_large_face.jpg", image)
print(' processing image 2')
dets = detector(img, 1)
print("Number of faces detected: {}".format(len(dets)))
for idx, face in enumerate(dets):
# print('face{}; left{}; top {}; right {}; bot {}'.format(idx, face.left(). face.top(), face.right(), face.bottom()))
left = face.left()
top = face.top()
right = face.right()
bot = face.bottom()
#print(left, top, right, bot)
#cv2.rectangle(img, (left, top), (right, bot), (0, 255, 0), 3)
#print(img.shape)
crop_img = img[top:bot, left:right]
#cv2.imshow(f, img)
#cv2.imshow(f, crop_img)
print(OutFace_Folder,f[:-4],"_face.jpg")
cv2.imwrite(OutFace_Folder+f[:-4]+"_face.jpg", crop_img)
#k = cv2.waitKey(1000)
#cv2.destroyAllWindows() | Ref/deepfake-pytorch/crop_face.py |
import sys
import dlib
import cv2
import os
import argparse
import largest_face_detector
import copy
Images_Folder = 'train/personB'
OutFace_Folder = 'train/personB_face/'
Images_Path = os.path.join(os.path.realpath('.'), Images_Folder)
Out_Path = os.path.join(os.path.realpath('.'), OutFace_Folder)
pictures = os.listdir(Images_Path)
# initialize hog + svm based face detector
detector = dlib.get_frontal_face_detector()
# # handle command line arguments
# ap = argparse.ArgumentParser()
# ap.add_argument('-w', '--weights', default='./mmod_human_face_detector.dat',
# help='path to weights file')
# args = ap.parse_args()
# # initialize CNN based face detector
# detector = dlib.cnn_face_detection_model_v1(args.weights)
print(pictures)
def rotate(img):
rows,cols,_ = img.shape
M = cv2.getRotationMatrix2D((cols, rows ), 0, 1)
dst = cv2.warpAffine(img, M, (cols, rows))
return dst
for f in pictures:
print('processing image')
img = cv2.imread(os.path.join(Images_Path,f), cv2.IMREAD_COLOR)
b, g, r = cv2.split(img)
img2 = cv2.merge([r, g, b])
img = rotate(img)
# f_copy = copy.deepcopy(f)
# image = largest_face_detector.detect_largest_face(str(Images_Path)+'/'+str(f_copy))
# cv2.imwrite(OutFace_Folder+f_copy[:-4]+"_large_face.jpg", image)
print(' processing image 2')
dets = detector(img, 1)
print("Number of faces detected: {}".format(len(dets)))
for idx, face in enumerate(dets):
# print('face{}; left{}; top {}; right {}; bot {}'.format(idx, face.left(). face.top(), face.right(), face.bottom()))
left = face.left()
top = face.top()
right = face.right()
bot = face.bottom()
#print(left, top, right, bot)
#cv2.rectangle(img, (left, top), (right, bot), (0, 255, 0), 3)
#print(img.shape)
crop_img = img[top:bot, left:right]
#cv2.imshow(f, img)
#cv2.imshow(f, crop_img)
print(OutFace_Folder,f[:-4],"_face.jpg")
cv2.imwrite(OutFace_Folder+f[:-4]+"_face.jpg", crop_img)
#k = cv2.waitKey(1000)
#cv2.destroyAllWindows() | 0.188026 | 0.136464 |
import unittest
from kubedriver.kubeobjects.names import NameHelper
class TestNameHelper(unittest.TestCase):
def setUp(self):
self.helper = NameHelper()
def test_is_valid_subdomain_name_allows_lowercase(self):
valid, reason = self.helper.is_valid_subdomain_name('testing')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_uppercase(self):
valid, reason = self.helper.is_valid_subdomain_name('tESting')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 1\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_allows_dots(self):
valid, reason = self.helper.is_valid_subdomain_name('testing.dots')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_allows_dash(self):
valid, reason = self.helper.is_valid_subdomain_name('testing-dashes')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_non_alphanumeric_start(self):
valid, reason = self.helper.is_valid_subdomain_name('-non-alphanum-start')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid start\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_non_alphanumeric_end(self):
valid, reason = self.helper.is_valid_subdomain_name('non-alphanum-end-')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 16\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_special_character(self):
valid, reason = self.helper.is_valid_subdomain_name('testing@specialchars')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_exceed_max_length(self):
test_str = 'a' * 254
valid, reason = self.helper.is_valid_subdomain_name(test_str)
self.assertEqual(reason, 'Subdomain names must contain no more than 253 characters -> Contained 254')
self.assertFalse(valid)
def test_is_valid_subdomain_name_allows_string_at_max_length(self):
test_str = 'a' * 253
valid, reason = self.helper.is_valid_subdomain_name(test_str)
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_none(self):
valid, reason = self.helper.is_valid_subdomain_name(None)
self.assertEqual(reason, 'Subdomains cannot be empty')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_empty_string(self):
valid, reason = self.helper.is_valid_subdomain_name('')
self.assertEqual(reason, 'Subdomains cannot be empty')
self.assertFalse(valid)
def test_is_valid_label_name_allows_lowercase(self):
valid, reason = self.helper.is_valid_label_name('testing')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_uppercase(self):
valid, reason = self.helper.is_valid_label_name('tESting')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 1\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_dots(self):
valid, reason = self.helper.is_valid_label_name('testing.dots')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_label_name_allows_dash(self):
valid, reason = self.helper.is_valid_label_name('testing-dashes')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_non_alphanumeric_start(self):
valid, reason = self.helper.is_valid_label_name('-non-alphanum-start')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid start\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_non_alphanumeric_end(self):
valid, reason = self.helper.is_valid_label_name('non-alphanum-end-')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 16\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_special_character(self):
valid, reason = self.helper.is_valid_label_name('testing@specialchars')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_exceed_max_length(self):
test_str = 'a' * 64
valid, reason = self.helper.is_valid_label_name(test_str)
self.assertEqual(reason, 'Label names must contain no more than 63 characters -> Contained 64')
self.assertFalse(valid)
def test_is_valid_label_name_allows_string_at_max_length(self):
test_str = 'a' * 63
valid, reason = self.helper.is_valid_label_name(test_str)
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_none(self):
valid, reason = self.helper.is_valid_label_name(None)
self.assertEqual(reason, 'Label names cannot be empty')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_empty_string(self):
valid, reason = self.helper.is_valid_label_name('')
self.assertEqual(reason, 'Label names cannot be empty')
self.assertFalse(valid) | tests/unit/kubeobjects/test_names.py | import unittest
from kubedriver.kubeobjects.names import NameHelper
class TestNameHelper(unittest.TestCase):
def setUp(self):
self.helper = NameHelper()
def test_is_valid_subdomain_name_allows_lowercase(self):
valid, reason = self.helper.is_valid_subdomain_name('testing')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_uppercase(self):
valid, reason = self.helper.is_valid_subdomain_name('tESting')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 1\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_allows_dots(self):
valid, reason = self.helper.is_valid_subdomain_name('testing.dots')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_allows_dash(self):
valid, reason = self.helper.is_valid_subdomain_name('testing-dashes')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_non_alphanumeric_start(self):
valid, reason = self.helper.is_valid_subdomain_name('-non-alphanum-start')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid start\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_non_alphanumeric_end(self):
valid, reason = self.helper.is_valid_subdomain_name('non-alphanum-end-')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 16\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_special_character(self):
valid, reason = self.helper.is_valid_subdomain_name('testing@specialchars')
self.assertEqual(reason, 'Subdomain names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters, \'-\' or \'.\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_exceed_max_length(self):
test_str = 'a' * 254
valid, reason = self.helper.is_valid_subdomain_name(test_str)
self.assertEqual(reason, 'Subdomain names must contain no more than 253 characters -> Contained 254')
self.assertFalse(valid)
def test_is_valid_subdomain_name_allows_string_at_max_length(self):
test_str = 'a' * 253
valid, reason = self.helper.is_valid_subdomain_name(test_str)
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_subdomain_name_false_on_none(self):
valid, reason = self.helper.is_valid_subdomain_name(None)
self.assertEqual(reason, 'Subdomains cannot be empty')
self.assertFalse(valid)
def test_is_valid_subdomain_name_false_on_empty_string(self):
valid, reason = self.helper.is_valid_subdomain_name('')
self.assertEqual(reason, 'Subdomains cannot be empty')
self.assertFalse(valid)
def test_is_valid_label_name_allows_lowercase(self):
valid, reason = self.helper.is_valid_label_name('testing')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_uppercase(self):
valid, reason = self.helper.is_valid_label_name('tESting')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 1\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_dots(self):
valid, reason = self.helper.is_valid_label_name('testing.dots')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_label_name_allows_dash(self):
valid, reason = self.helper.is_valid_label_name('testing-dashes')
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_non_alphanumeric_start(self):
valid, reason = self.helper.is_valid_label_name('-non-alphanum-start')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid start\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_non_alphanumeric_end(self):
valid, reason = self.helper.is_valid_label_name('non-alphanum-end-')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 16\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_special_character(self):
valid, reason = self.helper.is_valid_label_name('testing@specialchars')
self.assertEqual(reason, 'Label names must start and end with an alphanumeric character and consist of only lower case alphanumeric characters or \'-\' -> [\'Invalid at index 7\']')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_exceed_max_length(self):
test_str = 'a' * 64
valid, reason = self.helper.is_valid_label_name(test_str)
self.assertEqual(reason, 'Label names must contain no more than 63 characters -> Contained 64')
self.assertFalse(valid)
def test_is_valid_label_name_allows_string_at_max_length(self):
test_str = 'a' * 63
valid, reason = self.helper.is_valid_label_name(test_str)
self.assertIsNone(reason)
self.assertTrue(valid)
def test_is_valid_label_name_false_on_none(self):
valid, reason = self.helper.is_valid_label_name(None)
self.assertEqual(reason, 'Label names cannot be empty')
self.assertFalse(valid)
def test_is_valid_label_name_false_on_empty_string(self):
valid, reason = self.helper.is_valid_label_name('')
self.assertEqual(reason, 'Label names cannot be empty')
self.assertFalse(valid) | 0.683525 | 0.501526 |
# Description:
# This tool helps you to find hack attempts
# within webserver log files (e.g. Apache2 access logs).
# Features:
# - Error handling
# - Scan a log file for four different attack types
# - Display a short scan report
# - Write scan results to a new log file
# - Easy to use (everything is simple and automated
# Usage example:
# scan_log.py -file vhost_access.log
# Known issue:
# XSS attempt discovery feature can be a little bit buggy.
# Disclaimer:
# I am not responsible if this script or you cause any damage
# to your system. The memory consumption can become
# quite large and the generated reports very huge. So be sure
# you know what you are doing. I highly recommend you
# download your log files on a separate machine and
# analyze these files there.
# I know that there are much better tools, but well, I do
# this for learning and fun =)
# Attention: Tool is far away from being perfect, so don't rely a 100 percent on it.
# A BIG "Thank you!" to all who publish their awesome Python
# scripts online and help other ppl learning this language.
# Modify, distribute, share and copy this code in any way you like!
# Power to the cows!
import sys, string, re, time
from time import strftime, localtime
def print_usage():
print ""
print ""
print "[!] Use parameter --help for help!"
print ""
print ""
return
def print_help():
print ""
print "The Simple Log File Analyzer helps you to find"
print "common hack attempts within your webserver log."
print ""
print "Supported attacks:"
print " - SQL Injection"
print " - Local File Inclusion"
print " - Remote File Inclusion"
print " - Cross-Site Scripting"
print ""
print "This scanner doesn't find everything so don't"
print "rely on it!"
print ""
print "Usage example:"
print "scan_log.py -file vhost_access.log"
print ""
print "Options:"
print " -file <file> (starts the main analyzing function"
print " --help (displays this text)"
print ""
print "Features:"
print " - Error handling"
print " - Scan a log file for four different attack types"
print " - Display a short scan report"
print " - Write scan results to a new log file"
print " - Easy to use (everything is simple and automated)"
print ""
print "Additional information:"
print "I only tested this tool with Apache2 log files (up to 2000 lines)."
print "It may happen that the tool crashes when the provided log"
print "file is too big or contains too many lines/characters."
print "Scanning a 4000 lines log file only takes one second."
print ""
print "Hint: The XSS discovery feature is a little bit buggy."
print ""
print ""
return
def print_banner():
print ""
return
# Define the function for analyzing log files
def analyze_log_file(provided_file):
# Defining some important vars
sqli_found_list = {}
lfi_found_list = {}
rfi_found_list = {}
xss_found_list = {}
# I know, there are better methods for doing/defining this...
sql_injection_1 = "UNION"
sql_injection_2 = "ORDER"
sql_injection_3 = "GROUP"
local_file_inclusion_1 = "/etc/passwd"
local_file_inclusion_2 = "/etc/passwd%20"
local_file_inclusion_3 = "=../"
remote_file_inclusion_1 = "c99"
remote_file_inclusion_2 = "=http://"
cross_site_scripting_1 = "XSS"
cross_site_scripting_2 = "alert"
cross_site_scripting_3 = "String.fromCharCode"
cross_site_scripting_4 = "iframe"
cross_site_scripting_5 = "javascript"
print "[i] >>", provided_file
print "[i] Assuming you provided a readable log file."
print "[i] Trying to open the log file now."
print ""
# Opening the log file
try:
f = open(provided_file, "r")
except IOError:
print "[!] The file doesn't exist."
print "[!] Exiting now!"
print ""
sys.exit(1)
print "[i] Opening the log file was successfull."
print "[i] Moving on now..."
print ""
# Storing every single line in a list
line_list = [line for line in f]
max_lines = len(line_list)
print "[i] The file contains", max_lines, "lines."
print "[i] Now looking for possible hack attempts..."
# Viewing every single line
for x in xrange(1, max_lines):
current_line = line_list[x:x+1]
# For some strange list behaviour we convert the list into a string
current_line_string = "".join(current_line)
# Search for SQL injections
find_sql_injection_1 = re.findall(sql_injection_1, current_line_string)
if len(find_sql_injection_1) != 0:
sqli_found_list[x+1] = current_line_string
else:
find_sql_injection_2 = re.findall(sql_injection_2, current_line_string)
if len(find_sql_injection_2) != 0:
sqli_found_list[x+1] = current_line_string
else:
find_sql_injection_3 = re.findall(sql_injection_3, current_line_string)
if len(find_sql_injection_3) != 0:
sqli_found_list[x+1] = current_line_string
# Search for local file inclusions
find_local_file_inclusion_1 = re.findall(local_file_inclusion_1, current_line_string)
if len(find_local_file_inclusion_1) != 0:
lfi_found_list[x+1] = current_line_string
else:
find_local_file_inclusion_2 = re.findall(local_file_inclusion_2, current_line_string)
if len(find_local_file_inclusion_2) != 0:
lfi_found_list[x+1] = current_line_string
else:
find_local_file_inclusion_3 = re.findall(local_file_inclusion_3, current_line_string)
if len(find_local_file_inclusion_3) != 0:
lfi_found_list[x+1] = current_line_string
# Search for remote file inclusions
find_remote_file_inclusion_1 = re.findall(remote_file_inclusion_1, current_line_string)
if len(find_remote_file_inclusion_1) != 0:
rfi_found_list[x+1] = current_line_string
else:
find_remote_file_inclusion_2 = re.findall(remote_file_inclusion_2, current_line_string)
if len(find_remote_file_inclusion_2) != 0:
rfi_found_list[x+1] = current_line_string
# Search for cross-site scripting attempts
find_cross_site_scripting_1 = re.findall(cross_site_scripting_1, current_line_string)
if len(find_cross_site_scripting_1) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_2 = re.findall(cross_site_scripting_2, current_line_string)
if len(find_cross_site_scripting_2) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_3 = re.findall(cross_site_scripting_3, current_line_string)
if len(find_cross_site_scripting_3) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_4= re.findall(cross_site_scripting_4, current_line_string)
if len(find_cross_site_scripting_4) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_5 = re.findall(cross_site_scripting_5, current_line_string)
if len(find_cross_site_scripting_5) != 0:
xss_found_list[x+1] = current_line_string
# Close the file we opened recently
f.close()
# Generating a short report
print "[i] Done."
print ""
print "[#] Simple report for analyzed log file"
check_for_sqli_attempts = len(sqli_found_list)
if check_for_sqli_attempts > 0:
print "[!]", check_for_sqli_attempts, "SQL injection attempt(s) was/were found."
else:
print "[+] No SQL injection attempt was found."
check_for_lfi_attempts = len(lfi_found_list)
if check_for_lfi_attempts > 0:
print "[!]", check_for_lfi_attempts, "local file inclusion attempt(s) was/were found."
else:
print "[+] No local file inclusion attempt was found."
check_for_rfi_attempts = len(rfi_found_list)
if check_for_rfi_attempts > 0:
print "[!]", check_for_rfi_attempts, "remote file inclusion attempt(s) was/were found."
else:
print "[+] No remote file inclusion attempt was found."
check_for_xss_attempts = len(xss_found_list)
if check_for_xss_attempts > 0:
print "[!]", check_for_xss_attempts, "cross-site scripting attempt(s) was/were found."
else:
print "[+] No crosse-site scripting attempt was found."
# Now generate the report
print ""
print "[i] Generating report..."
# Define variables for the report name
time_string = strftime("%a_%d_%b_%Y_%H_%M_%S", localtime())
time_string_for_report = strftime("%a the %d %b %Y, %H:%M:%S", localtime())
name_of_report_file = provided_file + "_scan_report_from_" + time_string
# Convert the ints to strings
sqli_numbers = str(check_for_sqli_attempts)
lfi_numbers = str(check_for_lfi_attempts)
rfi_numbers = str(check_for_rfi_attempts)
xss_numbers = str(check_for_xss_attempts)
# Create the file
generated_report = open(name_of_report_file, "w")
# Write the content
generated_report.write("\n")
generated_report.write("Simple Log File Analyzer\n")
generated_report.write("\n")
generated_report.write("Scan report for " +provided_file + " on " + time_string_for_report + "\n")
generated_report.write("Hint: XSS attempt discovery feature might be a little bit buggy.\n")
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("Number of possible SQL injection attempts found: " + sqli_numbers + "\n")
generated_report.write("Number of possible local file inclusion attempts found: " + lfi_numbers + "\n")
generated_report.write("Number of possible remote file inclusion attempts found: " + rfi_numbers + "\n")
generated_report.write("Number of possible cross-site scripting attempts found: " + xss_numbers + "\n")
generated_report.write("\n")
generated_report.write("\n")
if len(sqli_found_list) != 0:
sqli_found_list_string = ""
sqli_found_list_string = "".join(str(sqli_found_list))
generated_report.write("Details for the SQL injection attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(sqli_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(lfi_found_list) != 0:
lfi_found_list_string = ""
lfi_found_list_string = "".join(str(lfi_found_list))
generated_report.write("Details for the local file inclusion attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(lfi_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(rfi_found_list) != 0:
rfi_found_list_string = ""
rfi_found_list_string = "".join(str(rfi_found_list))
generated_report.write("Details for the remote file inclusion attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(rfi_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(xss_found_list) != 0:
xss_found_list_string = ""
xss_found_list_string = "".join(str(xss_found_list))
generated_report.write("Details for the cross-site scripting attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(xss_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
# Close the file
generated_report.close()
print "[i] Finished writing the report."
print "[i] Hint: The report file can become quite large."
print "[i] Hint: The XSS attempt discovery feature might be a little bit buggy."
print ""
print "[i] That's it, bye!"
print ""
print ""
return
# End of the log file function
# Checking if argument was provided
if len(sys.argv) <=1:
print_usage()
sys.exit(1)
for arg in sys.argv:
# Checking if help was called
if arg == "--help":
print_help()
sys.exit(1)
# Checking if a log file was provided, if yes -> go!
if arg == "-file":
provided_file = sys.argv[2]
print_banner()
# Start the main analyze function
analyze_log_file(provided_file)
sys.exit(1)
### EOF ### | machine-learning-gists/a25a81cdaf63c90d0c08cb466a0371b8f9273d00/snippet.py |
# Description:
# This tool helps you to find hack attempts
# within webserver log files (e.g. Apache2 access logs).
# Features:
# - Error handling
# - Scan a log file for four different attack types
# - Display a short scan report
# - Write scan results to a new log file
# - Easy to use (everything is simple and automated
# Usage example:
# scan_log.py -file vhost_access.log
# Known issue:
# XSS attempt discovery feature can be a little bit buggy.
# Disclaimer:
# I am not responsible if this script or you cause any damage
# to your system. The memory consumption can become
# quite large and the generated reports very huge. So be sure
# you know what you are doing. I highly recommend you
# download your log files on a separate machine and
# analyze these files there.
# I know that there are much better tools, but well, I do
# this for learning and fun =)
# Attention: Tool is far away from being perfect, so don't rely a 100 percent on it.
# A BIG "Thank you!" to all who publish their awesome Python
# scripts online and help other ppl learning this language.
# Modify, distribute, share and copy this code in any way you like!
# Power to the cows!
import sys, string, re, time
from time import strftime, localtime
def print_usage():
print ""
print ""
print "[!] Use parameter --help for help!"
print ""
print ""
return
def print_help():
print ""
print "The Simple Log File Analyzer helps you to find"
print "common hack attempts within your webserver log."
print ""
print "Supported attacks:"
print " - SQL Injection"
print " - Local File Inclusion"
print " - Remote File Inclusion"
print " - Cross-Site Scripting"
print ""
print "This scanner doesn't find everything so don't"
print "rely on it!"
print ""
print "Usage example:"
print "scan_log.py -file vhost_access.log"
print ""
print "Options:"
print " -file <file> (starts the main analyzing function"
print " --help (displays this text)"
print ""
print "Features:"
print " - Error handling"
print " - Scan a log file for four different attack types"
print " - Display a short scan report"
print " - Write scan results to a new log file"
print " - Easy to use (everything is simple and automated)"
print ""
print "Additional information:"
print "I only tested this tool with Apache2 log files (up to 2000 lines)."
print "It may happen that the tool crashes when the provided log"
print "file is too big or contains too many lines/characters."
print "Scanning a 4000 lines log file only takes one second."
print ""
print "Hint: The XSS discovery feature is a little bit buggy."
print ""
print ""
return
def print_banner():
print ""
return
# Define the function for analyzing log files
def analyze_log_file(provided_file):
# Defining some important vars
sqli_found_list = {}
lfi_found_list = {}
rfi_found_list = {}
xss_found_list = {}
# I know, there are better methods for doing/defining this...
sql_injection_1 = "UNION"
sql_injection_2 = "ORDER"
sql_injection_3 = "GROUP"
local_file_inclusion_1 = "/etc/passwd"
local_file_inclusion_2 = "/etc/passwd%20"
local_file_inclusion_3 = "=../"
remote_file_inclusion_1 = "c99"
remote_file_inclusion_2 = "=http://"
cross_site_scripting_1 = "XSS"
cross_site_scripting_2 = "alert"
cross_site_scripting_3 = "String.fromCharCode"
cross_site_scripting_4 = "iframe"
cross_site_scripting_5 = "javascript"
print "[i] >>", provided_file
print "[i] Assuming you provided a readable log file."
print "[i] Trying to open the log file now."
print ""
# Opening the log file
try:
f = open(provided_file, "r")
except IOError:
print "[!] The file doesn't exist."
print "[!] Exiting now!"
print ""
sys.exit(1)
print "[i] Opening the log file was successfull."
print "[i] Moving on now..."
print ""
# Storing every single line in a list
line_list = [line for line in f]
max_lines = len(line_list)
print "[i] The file contains", max_lines, "lines."
print "[i] Now looking for possible hack attempts..."
# Viewing every single line
for x in xrange(1, max_lines):
current_line = line_list[x:x+1]
# For some strange list behaviour we convert the list into a string
current_line_string = "".join(current_line)
# Search for SQL injections
find_sql_injection_1 = re.findall(sql_injection_1, current_line_string)
if len(find_sql_injection_1) != 0:
sqli_found_list[x+1] = current_line_string
else:
find_sql_injection_2 = re.findall(sql_injection_2, current_line_string)
if len(find_sql_injection_2) != 0:
sqli_found_list[x+1] = current_line_string
else:
find_sql_injection_3 = re.findall(sql_injection_3, current_line_string)
if len(find_sql_injection_3) != 0:
sqli_found_list[x+1] = current_line_string
# Search for local file inclusions
find_local_file_inclusion_1 = re.findall(local_file_inclusion_1, current_line_string)
if len(find_local_file_inclusion_1) != 0:
lfi_found_list[x+1] = current_line_string
else:
find_local_file_inclusion_2 = re.findall(local_file_inclusion_2, current_line_string)
if len(find_local_file_inclusion_2) != 0:
lfi_found_list[x+1] = current_line_string
else:
find_local_file_inclusion_3 = re.findall(local_file_inclusion_3, current_line_string)
if len(find_local_file_inclusion_3) != 0:
lfi_found_list[x+1] = current_line_string
# Search for remote file inclusions
find_remote_file_inclusion_1 = re.findall(remote_file_inclusion_1, current_line_string)
if len(find_remote_file_inclusion_1) != 0:
rfi_found_list[x+1] = current_line_string
else:
find_remote_file_inclusion_2 = re.findall(remote_file_inclusion_2, current_line_string)
if len(find_remote_file_inclusion_2) != 0:
rfi_found_list[x+1] = current_line_string
# Search for cross-site scripting attempts
find_cross_site_scripting_1 = re.findall(cross_site_scripting_1, current_line_string)
if len(find_cross_site_scripting_1) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_2 = re.findall(cross_site_scripting_2, current_line_string)
if len(find_cross_site_scripting_2) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_3 = re.findall(cross_site_scripting_3, current_line_string)
if len(find_cross_site_scripting_3) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_4= re.findall(cross_site_scripting_4, current_line_string)
if len(find_cross_site_scripting_4) != 0:
xss_found_list[x+1] = current_line_string
else:
find_cross_site_scripting_5 = re.findall(cross_site_scripting_5, current_line_string)
if len(find_cross_site_scripting_5) != 0:
xss_found_list[x+1] = current_line_string
# Close the file we opened recently
f.close()
# Generating a short report
print "[i] Done."
print ""
print "[#] Simple report for analyzed log file"
check_for_sqli_attempts = len(sqli_found_list)
if check_for_sqli_attempts > 0:
print "[!]", check_for_sqli_attempts, "SQL injection attempt(s) was/were found."
else:
print "[+] No SQL injection attempt was found."
check_for_lfi_attempts = len(lfi_found_list)
if check_for_lfi_attempts > 0:
print "[!]", check_for_lfi_attempts, "local file inclusion attempt(s) was/were found."
else:
print "[+] No local file inclusion attempt was found."
check_for_rfi_attempts = len(rfi_found_list)
if check_for_rfi_attempts > 0:
print "[!]", check_for_rfi_attempts, "remote file inclusion attempt(s) was/were found."
else:
print "[+] No remote file inclusion attempt was found."
check_for_xss_attempts = len(xss_found_list)
if check_for_xss_attempts > 0:
print "[!]", check_for_xss_attempts, "cross-site scripting attempt(s) was/were found."
else:
print "[+] No crosse-site scripting attempt was found."
# Now generate the report
print ""
print "[i] Generating report..."
# Define variables for the report name
time_string = strftime("%a_%d_%b_%Y_%H_%M_%S", localtime())
time_string_for_report = strftime("%a the %d %b %Y, %H:%M:%S", localtime())
name_of_report_file = provided_file + "_scan_report_from_" + time_string
# Convert the ints to strings
sqli_numbers = str(check_for_sqli_attempts)
lfi_numbers = str(check_for_lfi_attempts)
rfi_numbers = str(check_for_rfi_attempts)
xss_numbers = str(check_for_xss_attempts)
# Create the file
generated_report = open(name_of_report_file, "w")
# Write the content
generated_report.write("\n")
generated_report.write("Simple Log File Analyzer\n")
generated_report.write("\n")
generated_report.write("Scan report for " +provided_file + " on " + time_string_for_report + "\n")
generated_report.write("Hint: XSS attempt discovery feature might be a little bit buggy.\n")
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("Number of possible SQL injection attempts found: " + sqli_numbers + "\n")
generated_report.write("Number of possible local file inclusion attempts found: " + lfi_numbers + "\n")
generated_report.write("Number of possible remote file inclusion attempts found: " + rfi_numbers + "\n")
generated_report.write("Number of possible cross-site scripting attempts found: " + xss_numbers + "\n")
generated_report.write("\n")
generated_report.write("\n")
if len(sqli_found_list) != 0:
sqli_found_list_string = ""
sqli_found_list_string = "".join(str(sqli_found_list))
generated_report.write("Details for the SQL injection attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(sqli_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(lfi_found_list) != 0:
lfi_found_list_string = ""
lfi_found_list_string = "".join(str(lfi_found_list))
generated_report.write("Details for the local file inclusion attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(lfi_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(rfi_found_list) != 0:
rfi_found_list_string = ""
rfi_found_list_string = "".join(str(rfi_found_list))
generated_report.write("Details for the remote file inclusion attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(rfi_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
if len(xss_found_list) != 0:
xss_found_list_string = ""
xss_found_list_string = "".join(str(xss_found_list))
generated_report.write("Details for the cross-site scripting attempts (line, log entry)\n")
generated_report.write("------------------------------------------------\n")
generated_report.write(xss_found_list_string)
generated_report.write("\n")
generated_report.write("\n")
generated_report.write("\n")
# Close the file
generated_report.close()
print "[i] Finished writing the report."
print "[i] Hint: The report file can become quite large."
print "[i] Hint: The XSS attempt discovery feature might be a little bit buggy."
print ""
print "[i] That's it, bye!"
print ""
print ""
return
# End of the log file function
# Checking if argument was provided
if len(sys.argv) <=1:
print_usage()
sys.exit(1)
for arg in sys.argv:
# Checking if help was called
if arg == "--help":
print_help()
sys.exit(1)
# Checking if a log file was provided, if yes -> go!
if arg == "-file":
provided_file = sys.argv[2]
print_banner()
# Start the main analyze function
analyze_log_file(provided_file)
sys.exit(1)
### EOF ### | 0.46223 | 0.197541 |
import pytest
import pyeventdispatcher
from pyeventdispatcher import (
EventDispatcher,
Event,
EventDispatcherException,
EventSubscriber,
listen,
)
from pyeventdispatcher.event_dispatcher import (
MemoryRegistry,
register_global_listener,
register_event_subscribers,
)
class TestRegister:
class MyListener:
def call_on_event(self, event):
print(event.data)
@pytest.mark.parametrize(
"registered", [MyListener().call_on_event, lambda event: print(event.data)]
)
def test_it_allows_to_register(self, registered, capsys):
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.register("foo.bar", registered)
py_event_dispatcher.dispatch(Event("foo.bar", {"a": "b"}))
captured = capsys.readouterr()
assert captured.out == "{'a': 'b'}\n"
@pytest.mark.parametrize(
"to_register, output",
[
# With default "priority" - in order they were added
(
(
{"lambda": lambda event: print("First"), "priority": 0},
{"lambda": lambda event: print("Second"), "priority": 0},
),
"First\nSecond\n",
),
# Based on priority
(
(
{"lambda": lambda event: print("First"), "priority": 0},
{"lambda": lambda event: print("Second"), "priority": -100},
),
"Second\nFirst\n",
),
],
)
def test_listeners_executed_in_order(self, to_register, output, capsys):
py_event_dispatcher = EventDispatcher()
for register in to_register:
py_event_dispatcher.register(
"foo.bar", register["lambda"], register["priority"]
)
py_event_dispatcher.dispatch(Event("foo.bar", {"a": "b"}))
captured = capsys.readouterr()
assert captured.out == output
def test_it_raises_an_exception_when_non_callable_is_trying_to_be_registered(self):
py_event_dispatcher = EventDispatcher()
with pytest.raises(EventDispatcherException):
py_event_dispatcher.register("foo.bar", "")
@pytest.mark.parametrize("priority", [None, ""])
def test_it_raises_an_exception_when_priority_is_not_integer(self, priority):
py_event_dispatcher = EventDispatcher()
with pytest.raises(EventDispatcherException):
py_event_dispatcher.register(
"foo.bar", lambda event: print(event), priority
)
class TestRegisterGlobal:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_it_allows_to_register_listener_globally(self, capsys):
def my_listener(event):
print("my_listener")
def global_listener(event):
print("global")
register_global_listener("foo.bar", global_listener)
py_event_dispatcher_1 = EventDispatcher()
py_event_dispatcher_1.register("foo.bar", my_listener)
py_event_dispatcher_2 = EventDispatcher()
py_event_dispatcher_2.register("foo.bar", my_listener)
py_event_dispatcher_1.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "my_listener\nglobal\n"
class TestRegisterSubscribers:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
class MySubscriber1(EventSubscriber):
EVENTS = {"foo.bar": "execute_one", "bar.foo": ("execute_two", -10)}
@staticmethod
def execute_one(event):
print("MySubscriber1::execute_one")
@staticmethod
def execute_two(event):
print("MySubscriber1::execute_two")
def test_register_global_listeners_by_subscriber(self, capsys):
register_event_subscribers()
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "MySubscriber1::execute_one\n"
class TestRegisterThroughDecorator:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_register_global_listener_by_decorator(self, capsys):
@listen("foo.bar")
def my_test_function(event):
print(event.name)
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "foo.bar\n"
class TestStopPropagation:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_it_stops_propagation(self, capsys):
def first_listener(event):
event.stop = True
print("first_listener")
def second_listener(event):
print("first_listener")
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.register("foo.bar", first_listener)
py_event_dispatcher.register("foo.bar", second_listener)
py_event_dispatcher.dispatch(Event("foo.bar", {}))
captured = capsys.readouterr()
assert captured.out == "first_listener\n" | test/test_pyeventdispatcher.py | import pytest
import pyeventdispatcher
from pyeventdispatcher import (
EventDispatcher,
Event,
EventDispatcherException,
EventSubscriber,
listen,
)
from pyeventdispatcher.event_dispatcher import (
MemoryRegistry,
register_global_listener,
register_event_subscribers,
)
class TestRegister:
class MyListener:
def call_on_event(self, event):
print(event.data)
@pytest.mark.parametrize(
"registered", [MyListener().call_on_event, lambda event: print(event.data)]
)
def test_it_allows_to_register(self, registered, capsys):
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.register("foo.bar", registered)
py_event_dispatcher.dispatch(Event("foo.bar", {"a": "b"}))
captured = capsys.readouterr()
assert captured.out == "{'a': 'b'}\n"
@pytest.mark.parametrize(
"to_register, output",
[
# With default "priority" - in order they were added
(
(
{"lambda": lambda event: print("First"), "priority": 0},
{"lambda": lambda event: print("Second"), "priority": 0},
),
"First\nSecond\n",
),
# Based on priority
(
(
{"lambda": lambda event: print("First"), "priority": 0},
{"lambda": lambda event: print("Second"), "priority": -100},
),
"Second\nFirst\n",
),
],
)
def test_listeners_executed_in_order(self, to_register, output, capsys):
py_event_dispatcher = EventDispatcher()
for register in to_register:
py_event_dispatcher.register(
"foo.bar", register["lambda"], register["priority"]
)
py_event_dispatcher.dispatch(Event("foo.bar", {"a": "b"}))
captured = capsys.readouterr()
assert captured.out == output
def test_it_raises_an_exception_when_non_callable_is_trying_to_be_registered(self):
py_event_dispatcher = EventDispatcher()
with pytest.raises(EventDispatcherException):
py_event_dispatcher.register("foo.bar", "")
@pytest.mark.parametrize("priority", [None, ""])
def test_it_raises_an_exception_when_priority_is_not_integer(self, priority):
py_event_dispatcher = EventDispatcher()
with pytest.raises(EventDispatcherException):
py_event_dispatcher.register(
"foo.bar", lambda event: print(event), priority
)
class TestRegisterGlobal:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_it_allows_to_register_listener_globally(self, capsys):
def my_listener(event):
print("my_listener")
def global_listener(event):
print("global")
register_global_listener("foo.bar", global_listener)
py_event_dispatcher_1 = EventDispatcher()
py_event_dispatcher_1.register("foo.bar", my_listener)
py_event_dispatcher_2 = EventDispatcher()
py_event_dispatcher_2.register("foo.bar", my_listener)
py_event_dispatcher_1.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "my_listener\nglobal\n"
class TestRegisterSubscribers:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
class MySubscriber1(EventSubscriber):
EVENTS = {"foo.bar": "execute_one", "bar.foo": ("execute_two", -10)}
@staticmethod
def execute_one(event):
print("MySubscriber1::execute_one")
@staticmethod
def execute_two(event):
print("MySubscriber1::execute_two")
def test_register_global_listeners_by_subscriber(self, capsys):
register_event_subscribers()
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "MySubscriber1::execute_one\n"
class TestRegisterThroughDecorator:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_register_global_listener_by_decorator(self, capsys):
@listen("foo.bar")
def my_test_function(event):
print(event.name)
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.dispatch(Event("foo.bar", None))
captured = capsys.readouterr()
assert captured.out == "foo.bar\n"
class TestStopPropagation:
def setup_method(self):
pyeventdispatcher.event_dispatcher.global_registry = MemoryRegistry()
def test_it_stops_propagation(self, capsys):
def first_listener(event):
event.stop = True
print("first_listener")
def second_listener(event):
print("first_listener")
py_event_dispatcher = EventDispatcher()
py_event_dispatcher.register("foo.bar", first_listener)
py_event_dispatcher.register("foo.bar", second_listener)
py_event_dispatcher.dispatch(Event("foo.bar", {}))
captured = capsys.readouterr()
assert captured.out == "first_listener\n" | 0.530723 | 0.413536 |
import base64
import subprocess
import json
import sys
import logging
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
from urllib.parse import urljoin
from kubernetes import client, config
class APIRequest(object):
"""
Example use:
api_request = APIRequest('http://api.com')
response = api_request('GET', '/get/stuff')
print (f"response.status_code")
print (f"{response.status_code}")
print()
print (f"response.reason")
print (f"{response.reason}")
print()
print (f"response.text")
print (f"{response.text}")
print()
print (f"response.json")
print (f"{response.json()}")
"""
def __init__(self, base_url, headers=None):
if not base_url.endswith('/'):
base_url += '/'
self._base_url = base_url
if headers is not None:
self._headers = headers
else:
self._headers = {}
def __call__(self, method, route, **kwargs):
if route.startswith('/'):
route = route[1:]
url = urljoin(self._base_url, route, allow_fragments=False)
headers = kwargs.pop('headers', {})
headers.update(self._headers)
retry_strategy = Retry(
total=10,
backoff_factor=0.1,
status_forcelist=[429, 500, 502, 503, 504],
method_whitelist=["PATCH", "DELETE", "POST", "HEAD", "GET", "OPTIONS"]
)
adapter = HTTPAdapter(max_retries=retry_strategy)
http = requests.Session()
http.mount("https://", adapter)
http.mount("http://", adapter)
response = http.request(method=method, url=url, headers=headers, **kwargs)
if 'data' in kwargs:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}"
f"and data:"
f"{json.dumps(kwargs['data'], indent=4)}")
elif 'json' in kwargs:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}"
f"and JSON:"
f"{json.dumps(kwargs['json'], indent=4)}")
else:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}")
log.debug(f"Response to {method} {url} => {response.status_code} {response.reason}"
f"{response.text}")
return response
# globals
gw_api = APIRequest('https://api-gw-service-nmn.local')
log = logging.getLogger(__name__)
log.setLevel(logging.WARN)
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
log.addHandler(handler)
def token():
# setup kubernetes client
config.load_kube_config()
v1 = client.CoreV1Api()
# get kubernetes admin secret
secret = v1.read_namespaced_secret("admin-client-auth", "default").data
# decode the base64 secret
token = base64.b64decode(secret['client-secret']).decode('utf-8')
# create post data to keycloak istio ingress
token_data = {'grant_type': 'client_credentials', 'client_id': 'admin-client', 'client_secret': token}
# query keycloack
token_url = '/keycloak/realms/shasta/protocol/openid-connect/token'
token_resp = gw_api('POST', token_url, data=token_data)
access_token = token_resp.json()['access_token']
# print (f'access_token')
return access_token
def main():
error_found = False
bearer_token = token()
# request header passing token
headers = {'Authorization': 'Bearer ' + bearer_token}
# query SMD EthernetInterfaces
smd_url = '/apis/smd/hsm/v2/Inventory/EthernetInterfaces'
smd_resp = gw_api('GET', smd_url, headers=headers)
smd_ethernet_interfaces = smd_resp.json()
# query SLS hardware
sls_url = '/apis/sls/v1/hardware'
sls_resp = gw_api('GET', sls_url, headers=headers)
sls_hardware = sls_resp.json()
ip_set = set()
for smd_entry in smd_ethernet_interfaces:
# print (smd_entry)
if smd_entry['IPAddresses'] != '[]':
ip_addresses = smd_entry['IPAddresses']
for ips in ip_addresses:
ip = ips['IPAddress']
# print (ip)
if ip != '':
if ip in ip_set:
log.error(f'Error: found duplicate IP: {ip}')
error_found = True
nslookup_cmd = subprocess.Popen(('nslookup', ip), stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
output, errors = nslookup_cmd.communicate()
print("output.decode('ascii')")
else:
ip_set.add(ip)
hostname_list = []
for i in range(len(sls_hardware)):
if 'ExtraProperties' in sls_hardware[i]:
if 'Role' in sls_hardware[i]['ExtraProperties'] and (
sls_hardware[i]['ExtraProperties']['Role'] == 'Application' or sls_hardware[i]['ExtraProperties'][
'Role'] == 'Management'):
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.nmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.can')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.hmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '-mgmt')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.cmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.chn')
for hostname in hostname_list:
dig_cmd = subprocess.Popen(('dig', hostname, '+short'), stdout=subprocess.PIPE)
wc_cmd = subprocess.check_output(('wc', '-l'), stdin=dig_cmd.stdout)
result = int(wc_cmd.decode('ascii').strip())
if result > 1:
error_found = True
log.error(f'ERROR: {hostname} has more than 1 DNS entry')
nslookup_cmd = subprocess.Popen(('nslookup', hostname), stdout=subprocess.PIPE, stderr=subprocess.PIPE)
output, errors = nslookup_cmd.communicate()
print(f"{output.decode('ascii')}")
if error_found:
log.error('ERRORS: see above output.')
sys.exit(1)
else:
log.debug('No errors found.')
sys.exit(0)
if __name__ == "__main__":
main() | goss-testing/scripts/python/check_ncn_uan_ip_dns.py | import base64
import subprocess
import json
import sys
import logging
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
from urllib.parse import urljoin
from kubernetes import client, config
class APIRequest(object):
"""
Example use:
api_request = APIRequest('http://api.com')
response = api_request('GET', '/get/stuff')
print (f"response.status_code")
print (f"{response.status_code}")
print()
print (f"response.reason")
print (f"{response.reason}")
print()
print (f"response.text")
print (f"{response.text}")
print()
print (f"response.json")
print (f"{response.json()}")
"""
def __init__(self, base_url, headers=None):
if not base_url.endswith('/'):
base_url += '/'
self._base_url = base_url
if headers is not None:
self._headers = headers
else:
self._headers = {}
def __call__(self, method, route, **kwargs):
if route.startswith('/'):
route = route[1:]
url = urljoin(self._base_url, route, allow_fragments=False)
headers = kwargs.pop('headers', {})
headers.update(self._headers)
retry_strategy = Retry(
total=10,
backoff_factor=0.1,
status_forcelist=[429, 500, 502, 503, 504],
method_whitelist=["PATCH", "DELETE", "POST", "HEAD", "GET", "OPTIONS"]
)
adapter = HTTPAdapter(max_retries=retry_strategy)
http = requests.Session()
http.mount("https://", adapter)
http.mount("http://", adapter)
response = http.request(method=method, url=url, headers=headers, **kwargs)
if 'data' in kwargs:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}"
f"and data:"
f"{json.dumps(kwargs['data'], indent=4)}")
elif 'json' in kwargs:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}"
f"and JSON:"
f"{json.dumps(kwargs['json'], indent=4)}")
else:
log.debug(f"{method} {url} with headers:"
f"{json.dumps(headers, indent=4)}")
log.debug(f"Response to {method} {url} => {response.status_code} {response.reason}"
f"{response.text}")
return response
# globals
gw_api = APIRequest('https://api-gw-service-nmn.local')
log = logging.getLogger(__name__)
log.setLevel(logging.WARN)
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
log.addHandler(handler)
def token():
# setup kubernetes client
config.load_kube_config()
v1 = client.CoreV1Api()
# get kubernetes admin secret
secret = v1.read_namespaced_secret("admin-client-auth", "default").data
# decode the base64 secret
token = base64.b64decode(secret['client-secret']).decode('utf-8')
# create post data to keycloak istio ingress
token_data = {'grant_type': 'client_credentials', 'client_id': 'admin-client', 'client_secret': token}
# query keycloack
token_url = '/keycloak/realms/shasta/protocol/openid-connect/token'
token_resp = gw_api('POST', token_url, data=token_data)
access_token = token_resp.json()['access_token']
# print (f'access_token')
return access_token
def main():
error_found = False
bearer_token = token()
# request header passing token
headers = {'Authorization': 'Bearer ' + bearer_token}
# query SMD EthernetInterfaces
smd_url = '/apis/smd/hsm/v2/Inventory/EthernetInterfaces'
smd_resp = gw_api('GET', smd_url, headers=headers)
smd_ethernet_interfaces = smd_resp.json()
# query SLS hardware
sls_url = '/apis/sls/v1/hardware'
sls_resp = gw_api('GET', sls_url, headers=headers)
sls_hardware = sls_resp.json()
ip_set = set()
for smd_entry in smd_ethernet_interfaces:
# print (smd_entry)
if smd_entry['IPAddresses'] != '[]':
ip_addresses = smd_entry['IPAddresses']
for ips in ip_addresses:
ip = ips['IPAddress']
# print (ip)
if ip != '':
if ip in ip_set:
log.error(f'Error: found duplicate IP: {ip}')
error_found = True
nslookup_cmd = subprocess.Popen(('nslookup', ip), stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
output, errors = nslookup_cmd.communicate()
print("output.decode('ascii')")
else:
ip_set.add(ip)
hostname_list = []
for i in range(len(sls_hardware)):
if 'ExtraProperties' in sls_hardware[i]:
if 'Role' in sls_hardware[i]['ExtraProperties'] and (
sls_hardware[i]['ExtraProperties']['Role'] == 'Application' or sls_hardware[i]['ExtraProperties'][
'Role'] == 'Management'):
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.nmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.can')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.hmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '-mgmt')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.cmn')
hostname_list.append(sls_hardware[i]['ExtraProperties']['Aliases'][0] + '.chn')
for hostname in hostname_list:
dig_cmd = subprocess.Popen(('dig', hostname, '+short'), stdout=subprocess.PIPE)
wc_cmd = subprocess.check_output(('wc', '-l'), stdin=dig_cmd.stdout)
result = int(wc_cmd.decode('ascii').strip())
if result > 1:
error_found = True
log.error(f'ERROR: {hostname} has more than 1 DNS entry')
nslookup_cmd = subprocess.Popen(('nslookup', hostname), stdout=subprocess.PIPE, stderr=subprocess.PIPE)
output, errors = nslookup_cmd.communicate()
print(f"{output.decode('ascii')}")
if error_found:
log.error('ERRORS: see above output.')
sys.exit(1)
else:
log.debug('No errors found.')
sys.exit(0)
if __name__ == "__main__":
main() | 0.126961 | 0.048858 |
import smbus
import time
HTS221_ADDR = 0x5F
HTS221_WHO_AM_I = 0x0F
HTS221_ID = 0xBC
HTS221_AV_CONF = 0x10
HTS221_CTRL_REG1 = 0x20
# Humidity
HTS221_H0_rH_x2 = 0x30
HTS221_H1_rH_x2 = 0x31
HTS221_H0_T0_OUT_L = 0x36
HTS221_H0_T0_OUT_H = 0x37
HTS221_H1_T0_OUT_L = 0x3A
HTS221_H1_T0_OUT_H = 0x3B
HTS221_H_OUT_L = 0x28
HTS221_H_OUT_H = 0x29
# Temperature
HTS221_T0_DEGC_X8 = 0x32
HTS221_T1_DEGC_X8 = 0x33
HTS221_T0_T1_MSB = 0x35
HTS221_T0_OUT_L = 0x3C
HTS221_T0_OUT_H = 0x3D
HTS221_T1_OUT_L = 0x3E
HTS221_T1_OUT_H = 0x3F
HTS221_T_OUT_L = 0x2A
HTS221_T_OUT_H = 0x2B
class HTS221:
def __init__(self):
self.bus = smbus.SMBus(1)
# Temperature average samples = 16(MAX 256), Humidity average samples = 32(MAX 512)
self.bus.write_byte_data(HTS221_ADDR, HTS221_AV_CONF, 0x1B)
# Power ON, Continuous update, Data ouput rate = 1Hz
self.bus.write_byte_data(HTS221_ADDR, HTS221_CTRL_REG1, 0x81)
time.sleep(0.5)
def getDeviceID(self):
return self.bus.read_byte_data(HTS221_ADDR, HTS221_WHO_AM_I)
def getHumidity(self):
val = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_rH_x2)
H0 = val / 2
val = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_rH_x2)
H1 = val /2
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_T0_OUT_H)
H2 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_T0_OUT_H)
H3 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
Hl = self.bus.read_byte_data(HTS221_ADDR, HTS221_H_OUT_L)
Hh = self.bus.read_byte_data(HTS221_ADDR, HTS221_H_OUT_H)
humidity = (Hh * 256) + Hl
humidity = ((1.0 * H1) - (1.0 * H0)) * (1.0 * humidity - 1.0 * H2) / (1.0 * H3 - 1.0 * H2) + (1.0 * H0)
return humidity
def getCTemperature(self):
T0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_DEGC_X8)
T0 = (T0 & 0xFF)
T1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_DEGC_X8)
T1 = (T1 & 0xFF)
raw = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_T1_MSB)
raw = (T1 & 0xFF)
T0 = ((raw & 0x03) * 256) + T0
T1 = ((raw & 0x0C) * 64) + T1
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_OUT_H)
T2 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_OUT_H)
T3 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
Tl = self.bus.read_byte_data(HTS221_ADDR, HTS221_T_OUT_L)
Th = self.bus.read_byte_data(HTS221_ADDR, HTS221_T_OUT_H)
temperature = (Th * 256) + Tl
if temperature > 32767:
temperature -= 65536
cTemp = ((T1 - T0) / 8.0) * (temperature - T2) / (T3 - T2) + (T0 / 8.0)
return cTemp
def getFTemperature(self):
return (self.getCTemperature() * 1.8) + 32 | CZNBIoT/HTS221.py | import smbus
import time
HTS221_ADDR = 0x5F
HTS221_WHO_AM_I = 0x0F
HTS221_ID = 0xBC
HTS221_AV_CONF = 0x10
HTS221_CTRL_REG1 = 0x20
# Humidity
HTS221_H0_rH_x2 = 0x30
HTS221_H1_rH_x2 = 0x31
HTS221_H0_T0_OUT_L = 0x36
HTS221_H0_T0_OUT_H = 0x37
HTS221_H1_T0_OUT_L = 0x3A
HTS221_H1_T0_OUT_H = 0x3B
HTS221_H_OUT_L = 0x28
HTS221_H_OUT_H = 0x29
# Temperature
HTS221_T0_DEGC_X8 = 0x32
HTS221_T1_DEGC_X8 = 0x33
HTS221_T0_T1_MSB = 0x35
HTS221_T0_OUT_L = 0x3C
HTS221_T0_OUT_H = 0x3D
HTS221_T1_OUT_L = 0x3E
HTS221_T1_OUT_H = 0x3F
HTS221_T_OUT_L = 0x2A
HTS221_T_OUT_H = 0x2B
class HTS221:
def __init__(self):
self.bus = smbus.SMBus(1)
# Temperature average samples = 16(MAX 256), Humidity average samples = 32(MAX 512)
self.bus.write_byte_data(HTS221_ADDR, HTS221_AV_CONF, 0x1B)
# Power ON, Continuous update, Data ouput rate = 1Hz
self.bus.write_byte_data(HTS221_ADDR, HTS221_CTRL_REG1, 0x81)
time.sleep(0.5)
def getDeviceID(self):
return self.bus.read_byte_data(HTS221_ADDR, HTS221_WHO_AM_I)
def getHumidity(self):
val = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_rH_x2)
H0 = val / 2
val = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_rH_x2)
H1 = val /2
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H0_T0_OUT_H)
H2 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_H1_T0_OUT_H)
H3 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
Hl = self.bus.read_byte_data(HTS221_ADDR, HTS221_H_OUT_L)
Hh = self.bus.read_byte_data(HTS221_ADDR, HTS221_H_OUT_H)
humidity = (Hh * 256) + Hl
humidity = ((1.0 * H1) - (1.0 * H0)) * (1.0 * humidity - 1.0 * H2) / (1.0 * H3 - 1.0 * H2) + (1.0 * H0)
return humidity
def getCTemperature(self):
T0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_DEGC_X8)
T0 = (T0 & 0xFF)
T1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_DEGC_X8)
T1 = (T1 & 0xFF)
raw = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_T1_MSB)
raw = (T1 & 0xFF)
T0 = ((raw & 0x03) * 256) + T0
T1 = ((raw & 0x0C) * 64) + T1
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T0_OUT_H)
T2 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
val0 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_OUT_L)
val1 = self.bus.read_byte_data(HTS221_ADDR, HTS221_T1_OUT_H)
T3 = ((val1 & 0xFF) * 256) + (val0 & 0xFF)
Tl = self.bus.read_byte_data(HTS221_ADDR, HTS221_T_OUT_L)
Th = self.bus.read_byte_data(HTS221_ADDR, HTS221_T_OUT_H)
temperature = (Th * 256) + Tl
if temperature > 32767:
temperature -= 65536
cTemp = ((T1 - T0) / 8.0) * (temperature - T2) / (T3 - T2) + (T0 / 8.0)
return cTemp
def getFTemperature(self):
return (self.getCTemperature() * 1.8) + 32 | 0.379608 | 0.240017 |
import copy
class System:
pass
class LinearSystem(System):
def __init__(self, equations):
self.equations = equations
def __str__(self):
eqsStr = []
greaterEqualSignPos = 0
for eq in self.equations:
eqStr = str(eq)
equalSignPos = eqStr.find('=')
if equalSignPos > greaterEqualSignPos:
greaterEqualSignPos = equalSignPos
eqsStr.append(eqStr)
# Sexy printing
i = 0
for eqStr in eqsStr:
equalSignPos = eqStr.find('=')
eqStr = ' '*(greaterEqualSignPos - equalSignPos) + eqStr
eqsStr[i] = eqStr
i += 1
return '\n'.join(eqsStr)
def __len__(self):
return len(self.equations)
def __iter__(self):
return iter(self.equations)
def __getitem__(self, key):
return self.equations[key]
def __reversed__(self):
return LinearSystem(reversed(self.equations))
def pivot(self):
allNull = True
for eq in self.equations:
if len(eq):
allNull = False
break
if allNull:
return self
pivot = None
pivotCoeff = None
pivotEq = None
for eq in self.equations:
for letter in eq:
if not letter: continue
coeff = eq[letter]
if pivotCoeff is None or abs(coeff) < abs(pivotCoeff):
pivotCoeff = coeff
pivot = letter
pivotEq = eq
eqs = []
for eq in self.equations:
if eq is pivotEq: continue
if pivot in eq:
eqPivotCoeff = eq[pivot]
else:
eqPivotCoeff = 0
eq *= pivotCoeff
eqPivotEq = pivotEq * eqPivotCoeff
eqs.append(eqPivotEq - eq)
if len(eqs) > 1:
subsys = LinearSystem(eqs)
eqs = subsys.pivot().equations
eqs.insert(0, pivotEq)
return LinearSystem(eqs)
def solve(self):
reducedSys = reversed(self.pivot())
found = {}
for eq in reducedSys:
result = eq.solve(found)
if result == False:
return False
elif isinstance(result, dict):
for letter in result:
if letter in found:
if found[letter] != result[letter]:
return False
else:
found[letter] = result[letter]
return found
class Equation:
pass
class LinearEquation(Equation):
def __init__(self, data = None):
if isinstance(data, str):
members = data.split('=')
firstMember = LinearExpression(members[0])
if len(members) > 1:
secondMember = LinearExpression(members[1])
self.expression = firstMember - secondMember
else:
self.expression = firstMember
else:
self.expression = LinearExpression(data)
def __str__(self):
return str(self.expression) + '= 0'
def __iter__(self):
return iter(self.expression)
def __getitem__(self, key):
return self.expression[key]
def __len__(self):
return len(self.expression)
def __mul__(self, factor):
return LinearEquation(self.expression * factor)
def __add__(self, other):
if isinstance(other, LinearEquation):
other = other.expression
return LinearEquation(self.expression + other)
def __neg__(self):
return self * (-1)
def __sub__(self, other):
return self + (-other)
def solve(self, found = {}):
primaryUnknown = None
secondaryUnknowns = {}
value = 0
for letter in self:
if letter == '':
value = - self[letter]
elif letter in found:
value = value - found[letter] * self[letter]
else:
if primaryUnknown is None:
primaryUnknown = letter
else:
secondaryUnknowns[letter] = - self[letter] / self[primaryUnknown]
if primaryUnknown is None:
return (value == 0)
elif len(secondaryUnknowns) == 0:
return { primaryUnknown: value / self[primaryUnknown] }
else:
# TODO: didnt managed to find a clean way to do this
# Even with the __div__ magic method
secondaryUnknowns[''] = value * (1 / self[primaryUnknown])
return { primaryUnknown: LinearExpression(secondaryUnknowns) }
class Expression:
pass
class LinearExpression(Expression):
def __init__(self, data = None):
self.data = {}
if isinstance(data, LinearExpression):
self.fromCoeff(data.data)
elif isinstance(data, int):
self.fromCoeff({ '': data })
elif isinstance(data, dict):
self.fromCoeff(data)
elif isinstance(data, str):
self.fromStr(data)
def fromCoeff(self, data):
self.data = {}
addAfter = None
if '' in data and isinstance(data[''], LinearExpression):
addAfter = data['']
data[''] = 0
for letter in data:
coeff = data[letter]
if coeff == 0:
continue
else:
self.data[letter] = coeff
if addAfter:
self.data = (self + addAfter).data
def fromStr(self, string):
expData = { '': 0 }
coeff = ''
def coeffToInt(coeff):
if coeff in ['+', '-']:
coeff += '1'
if coeff == '':
coeff = 1
else:
coeff = int(coeff)
return coeff
for char in string:
if char.isdigit():
coeff += char
elif char in ['+', '-']:
coeff = char
elif char.isalpha() or char == '':
expData[char] = coeffToInt(coeff)
coeff = ''
if coeff:
coeff = coeffToInt(coeff)
expData[''] += coeff
return self.fromCoeff(expData)
def __str__(self):
string = ''
for letter in self:
coeff = self[letter]
if coeff < 0: string += '- '
elif string: string += '+ '
string += str(abs(coeff))+letter+' '
if not string: string = '0 '
return string
def __repr__(self): # TODO: find a way to print solutions of a system without this
return str(self)
def __iter__(self):
return iter(self.data)
def __getitem__(self, key):
return self.data[key]
def __setitem__(self, key, value):
self.data[key] = value
def __len__(self):
return len(self.data.keys())
def __add__(self, other):
if not isinstance(other, Expression):
other = LinearExpression(other)
expData = copy.copy(self.data)
for letter in other:
if not letter in expData:
expData[letter] = 0
expData[letter] += other[letter]
return LinearExpression(expData)
def __radd__(self, other):
return self + other
def __iadd__(self, other):
return self + other
def __sub__(self, other):
return self + (-other)
def __rsub__(self, other):
return self - other
def __isub__(self, other):
return self - other
def __mul__(self, other):
expData = {}
for letter in self:
expData[letter] = self[letter] * other
return LinearExpression(expData)
def __rmul__(self, other):
return self * other
def __neg__(self):
return self * (-1)
def __div__(self, other):
return self * (1 / other)
def __rdiv__(self, other):
return (1 / self) * other
if __name__ == '__main__':
print('Entrez le système :')
eqs = []
while True:
eqStr = input()
if not eqStr:
break
else:
eqs.append(LinearEquation(eqStr))
sys = LinearSystem(eqs)
print(sys.solve()) | main.py |
import copy
class System:
pass
class LinearSystem(System):
def __init__(self, equations):
self.equations = equations
def __str__(self):
eqsStr = []
greaterEqualSignPos = 0
for eq in self.equations:
eqStr = str(eq)
equalSignPos = eqStr.find('=')
if equalSignPos > greaterEqualSignPos:
greaterEqualSignPos = equalSignPos
eqsStr.append(eqStr)
# Sexy printing
i = 0
for eqStr in eqsStr:
equalSignPos = eqStr.find('=')
eqStr = ' '*(greaterEqualSignPos - equalSignPos) + eqStr
eqsStr[i] = eqStr
i += 1
return '\n'.join(eqsStr)
def __len__(self):
return len(self.equations)
def __iter__(self):
return iter(self.equations)
def __getitem__(self, key):
return self.equations[key]
def __reversed__(self):
return LinearSystem(reversed(self.equations))
def pivot(self):
allNull = True
for eq in self.equations:
if len(eq):
allNull = False
break
if allNull:
return self
pivot = None
pivotCoeff = None
pivotEq = None
for eq in self.equations:
for letter in eq:
if not letter: continue
coeff = eq[letter]
if pivotCoeff is None or abs(coeff) < abs(pivotCoeff):
pivotCoeff = coeff
pivot = letter
pivotEq = eq
eqs = []
for eq in self.equations:
if eq is pivotEq: continue
if pivot in eq:
eqPivotCoeff = eq[pivot]
else:
eqPivotCoeff = 0
eq *= pivotCoeff
eqPivotEq = pivotEq * eqPivotCoeff
eqs.append(eqPivotEq - eq)
if len(eqs) > 1:
subsys = LinearSystem(eqs)
eqs = subsys.pivot().equations
eqs.insert(0, pivotEq)
return LinearSystem(eqs)
def solve(self):
reducedSys = reversed(self.pivot())
found = {}
for eq in reducedSys:
result = eq.solve(found)
if result == False:
return False
elif isinstance(result, dict):
for letter in result:
if letter in found:
if found[letter] != result[letter]:
return False
else:
found[letter] = result[letter]
return found
class Equation:
pass
class LinearEquation(Equation):
def __init__(self, data = None):
if isinstance(data, str):
members = data.split('=')
firstMember = LinearExpression(members[0])
if len(members) > 1:
secondMember = LinearExpression(members[1])
self.expression = firstMember - secondMember
else:
self.expression = firstMember
else:
self.expression = LinearExpression(data)
def __str__(self):
return str(self.expression) + '= 0'
def __iter__(self):
return iter(self.expression)
def __getitem__(self, key):
return self.expression[key]
def __len__(self):
return len(self.expression)
def __mul__(self, factor):
return LinearEquation(self.expression * factor)
def __add__(self, other):
if isinstance(other, LinearEquation):
other = other.expression
return LinearEquation(self.expression + other)
def __neg__(self):
return self * (-1)
def __sub__(self, other):
return self + (-other)
def solve(self, found = {}):
primaryUnknown = None
secondaryUnknowns = {}
value = 0
for letter in self:
if letter == '':
value = - self[letter]
elif letter in found:
value = value - found[letter] * self[letter]
else:
if primaryUnknown is None:
primaryUnknown = letter
else:
secondaryUnknowns[letter] = - self[letter] / self[primaryUnknown]
if primaryUnknown is None:
return (value == 0)
elif len(secondaryUnknowns) == 0:
return { primaryUnknown: value / self[primaryUnknown] }
else:
# TODO: didnt managed to find a clean way to do this
# Even with the __div__ magic method
secondaryUnknowns[''] = value * (1 / self[primaryUnknown])
return { primaryUnknown: LinearExpression(secondaryUnknowns) }
class Expression:
pass
class LinearExpression(Expression):
def __init__(self, data = None):
self.data = {}
if isinstance(data, LinearExpression):
self.fromCoeff(data.data)
elif isinstance(data, int):
self.fromCoeff({ '': data })
elif isinstance(data, dict):
self.fromCoeff(data)
elif isinstance(data, str):
self.fromStr(data)
def fromCoeff(self, data):
self.data = {}
addAfter = None
if '' in data and isinstance(data[''], LinearExpression):
addAfter = data['']
data[''] = 0
for letter in data:
coeff = data[letter]
if coeff == 0:
continue
else:
self.data[letter] = coeff
if addAfter:
self.data = (self + addAfter).data
def fromStr(self, string):
expData = { '': 0 }
coeff = ''
def coeffToInt(coeff):
if coeff in ['+', '-']:
coeff += '1'
if coeff == '':
coeff = 1
else:
coeff = int(coeff)
return coeff
for char in string:
if char.isdigit():
coeff += char
elif char in ['+', '-']:
coeff = char
elif char.isalpha() or char == '':
expData[char] = coeffToInt(coeff)
coeff = ''
if coeff:
coeff = coeffToInt(coeff)
expData[''] += coeff
return self.fromCoeff(expData)
def __str__(self):
string = ''
for letter in self:
coeff = self[letter]
if coeff < 0: string += '- '
elif string: string += '+ '
string += str(abs(coeff))+letter+' '
if not string: string = '0 '
return string
def __repr__(self): # TODO: find a way to print solutions of a system without this
return str(self)
def __iter__(self):
return iter(self.data)
def __getitem__(self, key):
return self.data[key]
def __setitem__(self, key, value):
self.data[key] = value
def __len__(self):
return len(self.data.keys())
def __add__(self, other):
if not isinstance(other, Expression):
other = LinearExpression(other)
expData = copy.copy(self.data)
for letter in other:
if not letter in expData:
expData[letter] = 0
expData[letter] += other[letter]
return LinearExpression(expData)
def __radd__(self, other):
return self + other
def __iadd__(self, other):
return self + other
def __sub__(self, other):
return self + (-other)
def __rsub__(self, other):
return self - other
def __isub__(self, other):
return self - other
def __mul__(self, other):
expData = {}
for letter in self:
expData[letter] = self[letter] * other
return LinearExpression(expData)
def __rmul__(self, other):
return self * other
def __neg__(self):
return self * (-1)
def __div__(self, other):
return self * (1 / other)
def __rdiv__(self, other):
return (1 / self) * other
if __name__ == '__main__':
print('Entrez le système :')
eqs = []
while True:
eqStr = input()
if not eqStr:
break
else:
eqs.append(LinearEquation(eqStr))
sys = LinearSystem(eqs)
print(sys.solve()) | 0.425605 | 0.305089 |
import sys
sys.path.append('/home/george2/Raise/ProgramRepair/CodeSeer/projects/src/main/python')
from CodeJam.Y14R5P1.Grzesiu.A import *
def func_0c1046dd31d944ea823eab991f0e63dc(totalsum, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
return kA
def func_422fc4f073a5491ca907af456989307d(totalsum, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
return kB
def func_cb25b39d091a4ed0be971403e40545e8(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kC
def func_48ddb4d7198042df9124af4330d4a9de(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kB
def func_bba41d648d0441dca54c56d48145d9af(kB, kA, totalsum, total, b):
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_130b9eec4f0f4f0491610e9a630f05df(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kB
def func_c418382fb0eb4534952deae538bb9d95(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kA
def func_dfb1511a80fe42d0920b4b71b233a7ac(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kC
def func_b007cdf7074f4d2382215cd9b63f23b6(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_e65f348d9f5c470e812bbdfd0bb9769b(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_8e4850ce4f84418ebfc04ad182d62d33(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return p
def func_7116f7f249d84c3e8c2e9376e5e146f0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return s
def func_416f54a060fd409d8a38cf6f7339f537(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return A
def func_da0f02fa2fab4bfd90e55bb5c1f3897a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return q
def func_f1cafdeac7924855905a43e0e50f8c85(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return i
def func_af94cd7291db4d8392637e0964190c75(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return r
def func_dd4ee7dff058465e8f9093c72bf44be5(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return N
def func_6dd4a037ee1c41ed8bdf11451d7e1266(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return total
def func_954d03bde7054130aab706fa6da97018(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return A
def func_82ac2147bb5d453ca2588da6a7904c95(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return i
def func_9391841ca22f4e45864b78ca7501bd3b(A):
total = sum(A)
totalsum = [a for a in A]
return total
def func_5fa8c3c70c6b4c4d824ad7d14417620a(A):
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_94aff88d4b4848d3bd7c9da2849f2741(A):
total = sum(A)
totalsum = [a for a in A]
return a
def func_deacbfabc9ed40e0a33ec1637bf3430d(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_9d5cfc4a34764e4f867da51ac2811b37(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_03d2f890a2c949a89793ecdc37f01f8f(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_bc6e0ffb677a4a67b1ba826848706e9a(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_6193114b510e409fbb3ed2fb52bd8b7d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_78f971ff88584c14ad46ac76e6fc8032(total):
best = total
b = 0
return b
def func_f3a042db45ca47a0880954620f7b5783(total):
best = total
b = 0
return best
def func_d26fbe01c90148db82aaa7350d85683b(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_b2b1a0159b424f4a8e5e2b5bac201d3d(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_00ae7a5021ec492d8850a5f8530f152f(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_eba418b4202c415fb7e3f41e9688876c(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_a55d54ba506b4cd2ad93472f66412496(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_5c90fc2fd4474d2f8fe63538661a736b(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_cb9fa78f3b444f86ad7698e0c085d7c8(T, total):
best = total - best('Case #%d' % T)
return best
def func_93deb75380134701984007a407855566(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return q
def func_d92a13d828a942c28298b66ca886930d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return p
def func_5a6d25f1446a46529d652fb6c2ae134f(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return r
def func_150486a3999145ec89520933b8f88e70(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return i
def func_0d712110dc7c47779dd70c540d1aa50d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return A
def func_7937b50a609540bdb874c3ad9fcda873(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return s
def func_3073a97d9ecd4a1c92b7db471d088adb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return total
def func_b43a45da96df4bc199eada33015296a5(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return N
def func_6a89344f1c3c4b8da1b282d31691fa98(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_8fb52450fc054702b35b62053f47b93d(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return A
def func_a5faeb40726d4e7287b8837bc707874f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return i
def func_bb60e94bb9a14c1bae93b1a33d441eef(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return a
def func_b47f7a892dd2437bbb253b9fb787f688(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return total
def func_0287b13dbc004259bde8be86e46d338a(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_721f8e105ea84f1eac5263bbeb281074(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_8007080568044eaaa1129ad105693aaf(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_8c742d967969486fb7cf47965a68ccad(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_cba549662da849b58feff5076242d903(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_5427bae4642e4fdeb8cc62f7b3113952(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_099d62d420a14be2af61d0eef35882cc(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_412aa6909aca4e2f958cf37202da9dd7(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_e35f043e8aa84ecc8b3e0393dfd707bc(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_8beeb2ec54f54b3391cac4ec0668b67d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_652d5bbc2211491288de6c3066a45dce(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_d184302c4fe64cde800c5118ad0b7f31(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_d016d8debeab484193fc6070b396464f(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_c668763de076457cafe3d525f03b9aed(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_ce9c680390fa4a739bcb2f216f41cc08(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_8cefb7563b65491f840bd963a4e06e28(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_9205e1b6d15c47ae95da73e32aa7d2c2(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_7d3bdd4aaa334ab79331397a4270a372(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_8819fef0fc5148e4a0470dcfa8346b13(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_83b5413719db4c81ba4a54550c7a474e(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_4628dff9ecb34bc9b8665814ed14c2d3(T, total):
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_f6c3835ea4824cbf80d96583a94cb3d0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return A
def func_a2a7841663d749e0b6a1538c684e1b57(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return N
def func_a433cc19c124454a97c8a4cf27bcd898(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return total
def func_f24006dc23f846e185568867764af2ee(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_c3c09e290323417ba11580f0e7713ce4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return s
def func_0945d65e8a434ee9a719cfdfaf94fcd4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return r
def func_f149df5fefb448f49ed7ffaf58d287e6(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return p
def func_d7b19a4983f64e608c3a2995ec0ffc2d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return a
def func_5aaf89c6004f40429b036ef3d20be59f(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return i
def func_b33308ebf4ba4c2f86b38d6d146ad9cc(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return q
def func_ed829d76cfdd4b59a9adc102aa0fbaa5(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_95540fe1d5db495a96297feb9ab821b2(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return A
def func_8ab2527b70af452baf1cf9779d1cbcaf(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_a8cd2d6b156e44b2ad0e6504ac6bbed1(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_d06f6698c2a846998ba7071fd9458b55(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_3644d4881d65454a8b0e9d0510e38422(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_b3feac9ec0694c90b19b8e431568b51d(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_f9479ff289a948be8c2d7a7b0f2dfa83(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_ac8b92c83ce248479046b3d1191f9935(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_4875af921b0c4977ba51da4e664ab59b(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_31a999361e184b9b8d1f149a051ddcc1(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_df07ccb748a54e528df29cc926af1ee4(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_d398a0b3c1c94fae9678823ece240fea(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_faff262f409e4f248fa54d003c00fefb(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_114e4fe8358a4f32a697fd438e39773e(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_668cfa2fae264d36867d27ffd2ae1e2b(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_cdd19a5dbfc643abaeaec08464a05c9d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_2174296acb144810a55351d88c5dcce7(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1f03d84bfae0482f9aa5f9d61a1da0c7(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_5833337ca69a40a181bf8c1cc7d68ff7(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_fe7110a853a64080b6fbd23084718eaa(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_b1f3ff45a4c94846843ba29db93fe331(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_81ea9263f3e842a9ae01a7433382d4c8(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_bf9d5058feb84aee80c5ca00a2cb54b2(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_030442168f234726b610e6a0c02e47a9(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_ec1d02104ff94365a146555cb0225777(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_68b2410982af4f4a96700459610ac3f8(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_ea040bbde3f44a7cb65e7b1f853f83e2(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_0e8c513fb442411f97db0855e99c9cfc(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return N
def func_c7aac4232ceb4332bb6765fe230eb8cb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return r
def func_c64ef9dd33e540a1933b88193be1c149(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return s
def func_b70140caa4824149831541bdc759ac7b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_d8e62241fbe24924a08ed3df065f67da(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_3c475224df74450ebbbebd68db957a8b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return q
def func_43f87e93b79b46e9b36f5ec1ac85c946(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_241fa146277d48f2b99447ee62343980(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_190c482f8d024b3599d388e753beb073(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return A
def func_8c8a3306df2b4e8c8535f5c1df820f9e(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return p
def func_cd51604d70bb4ef5933fa927221116fa(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_bb3e4b971f22470da676c5b725207f07(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_a019d6d9f147401e9081f89d7dbe4bba(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_e05db95d4c7a47b89133877c29283d4e(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return A
def func_771e4fdad22c419e80e2672653ef8ad7(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_6e414cd37558425f9ae245e0f4b7c937(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_785e8ebf3c9146ce952803401103dabe(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_9d95579b9fda4f26b88e39b79c5059d5(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_1b7921098626402992761f63a58479ce(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_68e5b2a66f5a4bddae385b8336308872(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_9dc316eb090e414098169c7abcf13cb7(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_80d4864700ce4dd0ad11216a8af20a43(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_b64703189512463e9ee70d7dc83fc375(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_bd4c2269f3a444c580534180fd56666c(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_0eb21573e19d44e0904f29a1a176a7b4(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_6e165c549d7349069dcad42585d4381a(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_f5e3925197d94712bb243ebda63886d0(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_0932f865260643f1a109fb1ae90c5edf(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_1390dd1047e146e1b1a6cf7838cfb5c2(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_75b310ced29e4f85b6ffa5be84905f4e(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_e19d5aceda4d42708e3d55d1748c2237(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_a4c25e095ba743018293dafb1fadc8fb(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_fc482b6c95e542c4b070b3f2c6e75c4c(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_68482c37c95e43219306daddda33308c(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_689e87938d01400d89fcdbd0a1657e42(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_a33e235cc6ce497db3a71f850c881560(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_73eacd2b66e2428facf6fe9dcd7caa33(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_fcb42c7f0c6141958b4c4eb757cf8ced(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_1b522bba99d244768f92ca0d66907596(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return r
def func_f7b9697a0bbe437eaca9e33bb5952488(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_fe527a3ce0b3419aae5f158d3651b562(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_63de86573b224aae9f1f9e8474443dcb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return s
def func_6462f1db1fbf46449e1f9f9c17b4ca86(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return A
def func_15a8181c64ab4692a82de8ea05f134df(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_8b434e63e32147d2bc32c6d882bf50f6(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return q
def func_06849a63535c47c5a28626d1066aa50c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return p
def func_993fcca1c0e649cc8d64de87bd4242ee(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_e2f8594e9ca64dcd8654f23efbcc83ad(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return N
def func_a8bb40fc65134737ba360f8f3cd4b5ba(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_5c936034506c47c5bd14033a6b953f6a(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_ed345658196c43768f6c38d1cd4015d4(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_3e88384849a9496ba926be882060713b(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_6d4fff6f763647ea8f0e9dd103679f30(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_a5c7bc28811e4fd1ac02c08c235801d5(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return A
def func_7248f802060a4e7794c8959d6107aced(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_bed0aeae57e14a26a98754c47d037921(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1031ea5561494143b4f27b3c582366d1(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_53561c5d176f45759894a733267b6035(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_88aabe94e6764b318ca15090dd04797b(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_aeff768c0ff849b28f22b3666805f417(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_7f27c39d96914c7ca3021ab236623286(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_9bd6ec8d36d940eeb9c65f5f0fee09bd(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_fff41eaa356b426abbec77e0ae7cc499(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_76d4ce7de8cd4ebdaea20dfb1d396722(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_533c9fcc8ae8408a928cf5db36ca6bab(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_c6ebc6f32ada46b89d186717cd7f078e(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_f781a8c9fa3547e0bbec9cee8cd9dc58(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_71f4942496a64bf18d521cf89329fc4c(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_c3f89268148b4e67be97d9e5a2e5914e(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_1e34644ed714453fa16f2cadc0130a53(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_01e307c903734bd9aefbc95a706f28b8(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_61e5332a00f8429382f5e19b86b0d934(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_5eb9c9bbd97d4c67928fcd40c9ac09e6(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_3eca48fdc68a451eb952d89dadf9c55d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return p
def func_7d3910e9f0b74b938c3dd982d0e5d964(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return q
def func_d917dff6872b4f9088039baa3af2221d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return N
def func_01a1ccf646a24ddb8981de1e709514b2(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return r
def func_6cc54bb0375142feb13cf04e82a65936(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return A
def func_0be6caff8ed74f02b53e6aa04d43bf93(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_3d82270a03184d0e85302a0befa29e7d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_2199d683b992451d9c735d69c8380c8c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_13c29f009dca43cea9c187660f33a6db(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_49b4495284ab46febcbc82c7168483c0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_7a087966ced24570a7629b2dc30f9a29(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return s
def func_479c4c122a8b4679b2faaa9b5d48f378(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_f4ad26e4e8b4430daaf801ac9274191c(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_d9e3392f603c479ca85259bc0c7b34b2(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1d7d2382410e4afbad6e132229e3df25(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return A
def func_893929db04274d1f82a7d73563096ef6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_50795ee331ee43258656611679f9b6d6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_818782be43824fbabb7740c3f72462ce(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_1b4eba326d7447e585ef56ee6461ac8f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_d28aa504c42b4e95a31d5ecc209cc372(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_a0601ae8aa534f048cb6098f9f85db51(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_c952a48a25e247f8be18eabaf023cdfd(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_835332840fcf4d8e917feeca658aec77(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_1a6aa03d8fed4735b6c35cda31b064e8(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_41a16dbe9ef949c3a0325a4933038f16(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_297acb7c309b46209e1a96b19a82e91a(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_8c735db321ef4188a222ecdcd7b2efe8(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_dd31827642ae4575831fe6cda5a39b91(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_1d7e4a5716a44b22a2305573c28676a1(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_c4ac65d1931343bb9b6e996ad4152ef3(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_f27c58c7cc4d4147a89c1096958515f5(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_e62fe36dc80e44a0a41bea416e4f92f1(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_e11294462e2445489b52e6b0eed435ee(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_49924ab686004a759bf4948f2bb194d6(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_75b0e58d5c2046e0bb5b1406882523c4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return r
def func_4e2e5c8fcc194f20993cddfdc052c55a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_7403b011372b40a3a65d9ad4ebe400ba(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return N
def func_27cd90810fbf4495ae543bd7962d072b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return A
def func_00ffe956dfba46ddbc805bd41de24ddf(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return p
def func_9bbacec9b3af419cb486abe3fb656408(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_93308f57be724854adc102abcc118d34(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_b0aa3e8451194389961221e9c416616a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_f56482a2429e4e148f120717c06e84b8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return q
def func_8055994d0065464d93ef85cd8c21131e(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return s
def func_3bcd690eec1940128543fccbf5c22bfb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_0221858737204fa389e982dac0799bbd(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_5139fada504242c281e3dfaf4c5444b6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_4df52d7b70ad4a37810abf46330a3aa3(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_c5d31a6eb622455b9f7c863026b5eada(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_6d0a581ab9084400bc2ad4509dd962e0(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_47d3b72343c94709985a4ec5a9754219(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_10c189a3fd28494689725a3fdc8f9891(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return A
def func_d43643d34ebd49c591a6a144a9caf44f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_c6d2018833c143c2bd608c67feb3227d(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_526fa2fc984f4447b08763398b048a81(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_3366a28a998f41dc933c3362dceb1430(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_e61ed751ed6c464ea3c72675a48a505b(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_698f2fced81d49a7b92b09b9cc787229(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_2e985ed82f844b43a73426f35f0d4513(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_326a084b251c474aba3bf5157e019e23(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_83f866438efe4c8f894f8b44ba707abe(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_192877dd3f8542e0a895f6b9f318d9a9(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_6be1570d9df14bdeabe0c780d71063f1(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_ea53fec8af8b41f69313c3e927e451d9(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_172a73f5168749b1ac20de58ee22ef30(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return N
def func_76570db24c144caa91967ac9ac1e9e4c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return r
def func_adbf640f1e9e4cc0a7fd3eaee07b38a9(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_2aaa3e8ae0c640c793a528fc63a5e41c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_957089c5fc5545cb9ce942b5d4ef80e8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return q
def func_366f89dec9974b10990f0331536c05c8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return p
def func_7d49a5cd82954d9bb8f4557a9e1764de(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return s
def func_59a339997e42418688238fc08183ea56(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_9411e23d1c104f8b81d7ae15d9cd790d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_38ef4e85f58242eb890ce11e30ee544b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return A
def func_0a3d9c5358794d96a07a86e88bd11f43(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_a89677cd5d8b407aaf99ada694aa9eac(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_7fbab4a6a241418781b5a2d12d1a7f03(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_9aa3be1304334d078816c173dc2f37d7(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_6187c62abd5d4f4ea088f53fc2d4a8cf(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_ff3b2d5022b841e495bea0c9eb53a45a(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_1f93aa92e947411b91e6f2783d55222a(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return A
def func_597204c0cb404c9983974cf8f235e6ca(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_8605c097769648f3819629d43916b606(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_ef7dba35d5834656a73cd78555f023b1(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_45b5aec34b7548d7b1f5f9d42de99bd8(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_d6b516d8e9234a5dad5dc8802b0504ab(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_611534ecf9b2487c9cdcd23bf333395c(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_7934f1a86e094e1d864da8df5603aa7c(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_e5b4633dc62346eba6d8ace8f7f5b9e6(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_c8ac40984b3c4144871b8690b2828687(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return N
def func_809b9e1e6c3a496f9caa599728bbb901(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_1ceb53a530e1435bb681a95a0d241be1(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return s
def func_97d13fa555774b9e84f227df329b52f2(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_bb6de3759b69441ea78b54431633b006(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return A
def func_05499c2e780348f98504bf8f7b9c7d9d(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return p
def func_00d72e88b8404654b956708f231daadc(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return q
def func_af9e65eec45c451b8eb830b4b95345aa(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_b0ff1c498786447195d14db4860ca57f(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return r
def func_411779ddb1ec4ade957f1d8871308397(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_81c3b38dac0c48fca84e80de2cad5358(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_72dc98d4f7504e5387cd75838acb038e(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_8ce62155b9734233b417516d60100590(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_70be2c23b409422c9fdf414d68939ccb(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_e3a7d5c635e54faa89dea71f048d02ab(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_0f4fb040495b4139925341acd807c78c(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_f539a9e24bac4f8796e02e51c3d12476(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_ec4ef50f73ed4cae94034202d150039b(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_5288b32e62e7470fab938555be76d716(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return A
def func_efaa44fe3f2b4b2c9855bfd133bd99b0(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_56c37c59c8934f7aa515817dbe7140a2(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_7495008816464a76bb91d2ffc4988345(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_beef533c5bd543f695c4e264d1cd8fe0(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return A
def func_e3493e1ae4b94c3b88b0cacdc6ceb441(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_48e70dfd9719447583b13b505e41e402(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_002b1a05bdcd4e15a8af5576d9b91ca5(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return p
def func_1e9868541192432497f7afddf6598f40(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return r
def func_15358d1d753f4af0b5abf587f122981a(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return s
def func_525021bbfb694e2d81ea77e6dfdfb893(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return q
def func_3085b093b0094ae3babe3700b49f3241(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return N
def func_529d5d0ce6d24c7b89be80d23f00dc9d(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_d3f7b486a618491a9a2c5ce79bc867c9():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
return T
def func_0784b0652171461a8249f952f2b48000():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
return infile
def func_379b3ac414f3412d82a2a3d21559845e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return i
def func_a15be2b4249741d2a57c8a1a96e038dd(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return p
def func_ddaa4aa4e21a46f1a02effc47cf59045(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return r
def func_f2ee59dcc42c4d53b8a37093f7e40f19(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return A
def func_4e6cc241c7314974b4d28fd300c27ef7(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return totalsum
def func_dc36827cd4164af3965269e69805f105(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return N
def func_311acdaf55a14825b30544b6f62de751(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return best
def func_2b849feb727142e989b398248e69c4b0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return total
def func_84004c157eb24824a7dd45092acff705(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return a
def func_ed9f2e9046bd48a6bc7b1f2cbd4b3307(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return s
def func_06ac1429d0dd4b6786a480a62be93d63(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return q
def func_358f85f329ad449f915a3878e2b03ee6(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return b
def func_d96a764c862148198fc928d5c4aea2ef(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return T
def func_392b3c81c3aa40eda55980e1c2344b73(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_d17b7e8cddaf4ab9b9cec7ed00676ccb(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_160b060d21ff4a44a65dff46a628505c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_d52463c4007c4b1298b2c5b933e78cab(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_03d836aa566443159aaee96fbb4e9967(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_7e38d9e98b1049158c869d531753c12f(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_10894e4371e1435d9b05f716a68add7b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_0a11821b1137476e88c18298384deb8b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_15bad475ff63420baa3ece9f13f35a04(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_caf0cedfefe54103993a5aaffc3a5f5b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_73f6530a43ca4df1af33294cc65337cc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_5ad67b425b01433da824f5b458409971(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_2a6eb9490f3b4fa89c4c00fe246f8bcf(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_39b5ff4411a3446aa7aa21c266357ed7(N, a, total, totalsum):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_8abb784db8474fe48574d1cf6e65cedc(N, a, total, totalsum, infile):
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_c10f7260f9ae4d4db9084aa2e4364cda():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return A
def func_1e62ef3080d34852a8994b744dd7cf8b():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return totalsum
def func_2fe7817bb9454ac4a7f42c36b06e5656():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return N
def func_41b7bcd3d9054f88afd5d7481ab082db():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return s
def func_2c40fb27367d4bb09fd59d10002217fe():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return best
def func_879c0a5a046d402197301a1dd262a502():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return T
def func_5700b7f5ad5445a2ae57b59931d8218f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return q
def func_3fb83ef4cbac4845919264234344ea5b():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return total
def func_ed1ca0fdfe934213a9689a109a05a323():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return a
def func_14b182e6c4d442a2a6333c20f33098af():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return b
def func_74cdc7c4ea58410b9e9e3d4153b8528f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return infile
def func_52fd8244225c47539b667eff5ac1c506():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return r
def func_1e280bac5e4f4881b06a6ffb6c3bcd27():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return p
def func_97bfc163c6f94530a61ae008f98138c5():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return i
def func_7f420ba7f38040f9bdf680eed5f6ca30(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_f1905696e0384d21b40588505d7d96a4(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_10ccb346b51f4c6bbbd2924a66031d26(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_dd77ecfb51634b54906d9828787b665a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_2df92723130a4dbb9e3bd917045f1364(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_a4f0e5f3379042e6868bfda705691e5a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_eeffb7d067d94cf895a14810273b3adb(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_5b593d280d894227886d9820e2620ed7(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_8fc587178b0f425893cfb8b8d0bf3ab0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_eb5f88e2fd7749f08864f8f47842b573(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_1ca496655a6749638375900047039b79(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_d398731c95e149a2a588991bfb6cc19c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_10873cb0fc834b2e8aae8c536c30e9ff(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_b564fdc0138845c596ef79cd1a15d0bc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_b42646bf57b04e1ba5eb398e69ab566a(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_f13a21b1f8294c6ea4692285e7257508(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_e6c89cbce82b4fe59072ac31bd8cccfc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_7b973b66bfe248a1b083a7b65d8747cb(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_06a170a9d28944df9bd77ac6dbfc9bb9(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_e56980d85c51442fa98eaac3e42761f6(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_ff24164b9e5c498eb583322af419353c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_d22a16a174d74323bcdfc0748c900fb7(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_3198becba046425b9f7701a079086953(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_42bb0ea960504637ac6203bee7e46b30(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_510efd6a1bef4ea4915b38410ec44f95(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_d4db808b5c5f4ad19f746d92b5eceea1(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_0fe0cb5387d84c33a820ce7538128287(N, a, total, totalsum, infile):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_a4c9e7f7ac2d41169d555389b022f1b2():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_df00b7d4111b4b17ae5338bc5d859307():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_e3759d7baf854516acd05dd65f58e267():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_001061ffe51349cbb94a04ecda918986():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_b5cf5d42ed4d46ce9647adf74afadbdf():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_c8c31fa793ec4baf9ebe919e60d10e63():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_81d7ec305fd14deea9aae3abfb35ea46():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_b78708fc55d5493dbd5bf9e59d12fffc():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_dc22601ca4164c319547ec8092cd1ca0():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_c41e70b8b5b145f3b436438803d19f3e():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_7649988e353d42b4b610723f812d4f3e():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_60b98beb7ef74a05829454996e6baf05():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return infile
def func_3fd2df326bee456eba012bbca72a6827():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_8b92c7641e484c3185ac21b876e1c6a3():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_a058fb23c70c4f83b621ff8b996ca757(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_79cd49364c704b2481ae80b0d388570e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_6beb80e3001a481a84058c4d33a9c8ce(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_1691ea258a804e008ed80b0b27bfe0b0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_684fcc825d8c47bcad7082f202f2183f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_c1bd00b0cf194523b77e76a0ff6c7b63(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_cedb8992c5f34bb4a21e2acfb535ab9a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_f25afc94d1bf4c3cb31d44c394340e06(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_754e6e270ffc43aea9841c9db716860a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_ad489c77b0394a6d991496c4c1d96e9a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_d2f5cfd435914ff79a6b5ec165eb991c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_a834e99521a342968ed049cd9018765f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_368aa2f7d8f843508c1434ee4c9483aa(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_a8cf91de524d4990853190090965d2ff(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_5a1da4b690934fcfa28be57548550a80(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_c24477c0275f4141bc5892c5976f4776(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_347910efdefd4af6a57bfb08473be165(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_fb81a2754a094fd5a2d0d9692c491195(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_4ef8b31e24144bee942d35ba1d2774b8(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_c39bfa9851fc481fae8afe335afe55fd(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_8f7d9b18b0f14b1e8ab440a10887730d(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_70a941215b834f7eac54b7c1636adfb4(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_b4cd67a31efc4ead91b67fbc22e24dac(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q
def func_a22c619581fb44ae9f584033f0899eb8(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_693ed1bad29e4b8a95d978208b7d6f86(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_07cf1ae667834722a41368a3a3a52f0c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_c172c6329ac8403aae7f07e75e313b64():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_6c62f09ceaea47129e83e1b939749cb9():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_01dc285a49b245bb9b0949a7ec01a023():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_f1811e15e03843e49fea3ba532ea8abe():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_dd8add574ccb4aae9485ee4faad801bf():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_afac472c35384280869ae404198805bc():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_ebc4290fb5fb4b4299252ce7da042619():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_7f3b9e7f1be74cb8a0529d04b3de64d8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_735b12cfd01b4a4c81f3ece45e4a28c2():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_cf36e98c4f894327bcf08c3194ae7721():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return infile
def func_cb643894a3014ef1b37f5c0d1b54a565():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_a107482df78246eb8d81ca5011347c4c():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_918853ad2ecf47eaba61a6f1fc6d92df():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_8f053287fe174bdf8ad67b55f778290f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_4e14ae8b08734803a9a1388cc930810a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_dbd53d84aa8b47279f057ebe3203305e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_0bd728dcd1ac4427bbd2f8f5b9caf23d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_745b0911081e4c1096ca52012199c83c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_779e7f4767144f6e8016401603b095b1(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_68558b99861c4206a49c8c7e776ad176(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q
def func_9317c45f78c1496bb6b2d72ec0df9393(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_f74e74844ed94f00bade2c9e428e8d12(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_8b1d8cfc9aa14b8e86397102da61361d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_5a3ff70a1bc943febae09e1fabf395d2(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_512bd04277844ab09213194c90f64f0f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_de5c06ddd14d4f9a800fe3568514c055(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_3dabdf4bb9bd4b19862c5bafe2e6a31d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_905f4c30854f45e6a2a1e429dcc65ffa():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return infile
def func_c4b455e670464f0abb57a45a200956ec():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_424728ccf8bf444ebac61c68c76f4d3f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_b2fbcb34b7bc404195a6d2b707095403():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_9c2399ce63344af09045aa205c8e5ec3():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_0baf7a2224154215ad97b22e7a041b21():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_d1a5f32b7cd240c0b383329cd5fc9faa():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_7a1ced1d999d45729628f9914c8dc9a8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_5c85d4feecc64c9cbbafcefb97477778():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_a0bf93db7a5e4eff9bf8c8b9f3acefae():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_acfda2965eb343009d6f0e762bc726f0():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_4898b02e04f14731b38090bd045f16b8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_48cfc21f8f454641b8ba772c3aae73e7():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_109fbb71de58446b8ad0e46b3e8f694f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q | projects/src/main/python/CodeJam/Y14R5P1/Grzesiu/generated_py_84e0dc4f0d374ae0ba338a870469e2f9.py | import sys
sys.path.append('/home/george2/Raise/ProgramRepair/CodeSeer/projects/src/main/python')
from CodeJam.Y14R5P1.Grzesiu.A import *
def func_0c1046dd31d944ea823eab991f0e63dc(totalsum, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
return kA
def func_422fc4f073a5491ca907af456989307d(totalsum, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
return kB
def func_cb25b39d091a4ed0be971403e40545e8(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kC
def func_48ddb4d7198042df9124af4330d4a9de(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kB
def func_bba41d648d0441dca54c56d48145d9af(kB, kA, totalsum, total, b):
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_130b9eec4f0f4f0491610e9a630f05df(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kB
def func_c418382fb0eb4534952deae538bb9d95(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kA
def func_dfb1511a80fe42d0920b4b71b233a7ac(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return kC
def func_b007cdf7074f4d2382215cd9b63f23b6(kA, totalsum, total, b):
kB = totalsum[b] - kA
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_e65f348d9f5c470e812bbdfd0bb9769b(totalsum, total, b, a):
kA = totalsum[a - 1] if a > 0 else 0
kB = totalsum[b] - kA
kC = total - totalsum[b]
return max(kA, kB, kC)
def func_8e4850ce4f84418ebfc04ad182d62d33(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return p
def func_7116f7f249d84c3e8c2e9376e5e146f0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return s
def func_416f54a060fd409d8a38cf6f7339f537(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return A
def func_da0f02fa2fab4bfd90e55bb5c1f3897a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return q
def func_f1cafdeac7924855905a43e0e50f8c85(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return i
def func_af94cd7291db4d8392637e0964190c75(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return r
def func_dd4ee7dff058465e8f9093c72bf44be5(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
return N
def func_6dd4a037ee1c41ed8bdf11451d7e1266(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return total
def func_954d03bde7054130aab706fa6da97018(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return A
def func_82ac2147bb5d453ca2588da6a7904c95(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return i
def func_9391841ca22f4e45864b78ca7501bd3b(A):
total = sum(A)
totalsum = [a for a in A]
return total
def func_5fa8c3c70c6b4c4d824ad7d14417620a(A):
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_94aff88d4b4848d3bd7c9da2849f2741(A):
total = sum(A)
totalsum = [a for a in A]
return a
def func_deacbfabc9ed40e0a33ec1637bf3430d(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_9d5cfc4a34764e4f867da51ac2811b37(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_03d2f890a2c949a89793ecdc37f01f8f(N, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_bc6e0ffb677a4a67b1ba826848706e9a(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_6193114b510e409fbb3ed2fb52bd8b7d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_78f971ff88584c14ad46ac76e6fc8032(total):
best = total
b = 0
return b
def func_f3a042db45ca47a0880954620f7b5783(total):
best = total
b = 0
return best
def func_d26fbe01c90148db82aaa7350d85683b(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_b2b1a0159b424f4a8e5e2b5bac201d3d(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_00ae7a5021ec492d8850a5f8530f152f(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_eba418b4202c415fb7e3f41e9688876c(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_a55d54ba506b4cd2ad93472f66412496(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_5c90fc2fd4474d2f8fe63538661a736b(N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_cb9fa78f3b444f86ad7698e0c085d7c8(T, total):
best = total - best('Case #%d' % T)
return best
def func_93deb75380134701984007a407855566(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return q
def func_d92a13d828a942c28298b66ca886930d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return p
def func_5a6d25f1446a46529d652fb6c2ae134f(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return r
def func_150486a3999145ec89520933b8f88e70(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return i
def func_0d712110dc7c47779dd70c540d1aa50d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return A
def func_7937b50a609540bdb874c3ad9fcda873(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return s
def func_3073a97d9ecd4a1c92b7db471d088adb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return total
def func_b43a45da96df4bc199eada33015296a5(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
return N
def func_6a89344f1c3c4b8da1b282d31691fa98(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_8fb52450fc054702b35b62053f47b93d(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return A
def func_a5faeb40726d4e7287b8837bc707874f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return i
def func_bb60e94bb9a14c1bae93b1a33d441eef(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return a
def func_b47f7a892dd2437bbb253b9fb787f688(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return total
def func_0287b13dbc004259bde8be86e46d338a(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_721f8e105ea84f1eac5263bbeb281074(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_8007080568044eaaa1129ad105693aaf(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_8c742d967969486fb7cf47965a68ccad(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_cba549662da849b58feff5076242d903(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_5427bae4642e4fdeb8cc62f7b3113952(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_099d62d420a14be2af61d0eef35882cc(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_412aa6909aca4e2f958cf37202da9dd7(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_e35f043e8aa84ecc8b3e0393dfd707bc(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_8beeb2ec54f54b3391cac4ec0668b67d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_652d5bbc2211491288de6c3066a45dce(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_d184302c4fe64cde800c5118ad0b7f31(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_d016d8debeab484193fc6070b396464f(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_c668763de076457cafe3d525f03b9aed(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_ce9c680390fa4a739bcb2f216f41cc08(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_8cefb7563b65491f840bd963a4e06e28(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_9205e1b6d15c47ae95da73e32aa7d2c2(N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_7d3bdd4aaa334ab79331397a4270a372(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_8819fef0fc5148e4a0470dcfa8346b13(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_83b5413719db4c81ba4a54550c7a474e(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_4628dff9ecb34bc9b8665814ed14c2d3(T, total):
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_f6c3835ea4824cbf80d96583a94cb3d0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return A
def func_a2a7841663d749e0b6a1538c684e1b57(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return N
def func_a433cc19c124454a97c8a4cf27bcd898(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return total
def func_f24006dc23f846e185568867764af2ee(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return totalsum
def func_c3c09e290323417ba11580f0e7713ce4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return s
def func_0945d65e8a434ee9a719cfdfaf94fcd4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return r
def func_f149df5fefb448f49ed7ffaf58d287e6(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return p
def func_d7b19a4983f64e608c3a2995ec0ffc2d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return a
def func_5aaf89c6004f40429b036ef3d20be59f(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return i
def func_b33308ebf4ba4c2f86b38d6d146ad9cc(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
return q
def func_ed829d76cfdd4b59a9adc102aa0fbaa5(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_95540fe1d5db495a96297feb9ab821b2(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return A
def func_8ab2527b70af452baf1cf9779d1cbcaf(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_a8cd2d6b156e44b2ad0e6504ac6bbed1(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_d06f6698c2a846998ba7071fd9458b55(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_3644d4881d65454a8b0e9d0510e38422(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_b3feac9ec0694c90b19b8e431568b51d(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_f9479ff289a948be8c2d7a7b0f2dfa83(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_ac8b92c83ce248479046b3d1191f9935(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_4875af921b0c4977ba51da4e664ab59b(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_31a999361e184b9b8d1f149a051ddcc1(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_df07ccb748a54e528df29cc926af1ee4(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_d398a0b3c1c94fae9678823ece240fea(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_faff262f409e4f248fa54d003c00fefb(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_114e4fe8358a4f32a697fd438e39773e(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_668cfa2fae264d36867d27ffd2ae1e2b(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_cdd19a5dbfc643abaeaec08464a05c9d(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_2174296acb144810a55351d88c5dcce7(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1f03d84bfae0482f9aa5f9d61a1da0c7(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_5833337ca69a40a181bf8c1cc7d68ff7(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_fe7110a853a64080b6fbd23084718eaa(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_b1f3ff45a4c94846843ba29db93fe331(N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_81ea9263f3e842a9ae01a7433382d4c8(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_bf9d5058feb84aee80c5ca00a2cb54b2(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_030442168f234726b610e6a0c02e47a9(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_ec1d02104ff94365a146555cb0225777(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_68b2410982af4f4a96700459610ac3f8(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_ea040bbde3f44a7cb65e7b1f853f83e2(T, N, total, totalsum):
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_0e8c513fb442411f97db0855e99c9cfc(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return N
def func_c7aac4232ceb4332bb6765fe230eb8cb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return r
def func_c64ef9dd33e540a1933b88193be1c149(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return s
def func_b70140caa4824149831541bdc759ac7b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return total
def func_d8e62241fbe24924a08ed3df065f67da(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return totalsum
def func_3c475224df74450ebbbebd68db957a8b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return q
def func_43f87e93b79b46e9b36f5ec1ac85c946(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return a
def func_241fa146277d48f2b99447ee62343980(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return i
def func_190c482f8d024b3599d388e753beb073(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return A
def func_8c8a3306df2b4e8c8535f5c1df820f9e(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
return p
def func_cd51604d70bb4ef5933fa927221116fa(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_bb3e4b971f22470da676c5b725207f07(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_a019d6d9f147401e9081f89d7dbe4bba(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_e05db95d4c7a47b89133877c29283d4e(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return A
def func_771e4fdad22c419e80e2672653ef8ad7(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_6e414cd37558425f9ae245e0f4b7c937(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_785e8ebf3c9146ce952803401103dabe(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_9d95579b9fda4f26b88e39b79c5059d5(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_1b7921098626402992761f63a58479ce(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_68e5b2a66f5a4bddae385b8336308872(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_9dc316eb090e414098169c7abcf13cb7(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_80d4864700ce4dd0ad11216a8af20a43(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_b64703189512463e9ee70d7dc83fc375(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_bd4c2269f3a444c580534180fd56666c(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_0eb21573e19d44e0904f29a1a176a7b4(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_6e165c549d7349069dcad42585d4381a(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_f5e3925197d94712bb243ebda63886d0(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_0932f865260643f1a109fb1ae90c5edf(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_1390dd1047e146e1b1a6cf7838cfb5c2(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_75b310ced29e4f85b6ffa5be84905f4e(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_e19d5aceda4d42708e3d55d1748c2237(N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_a4c25e095ba743018293dafb1fadc8fb(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_fc482b6c95e542c4b070b3f2c6e75c4c(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_68482c37c95e43219306daddda33308c(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_689e87938d01400d89fcdbd0a1657e42(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_a33e235cc6ce497db3a71f850c881560(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_73eacd2b66e2428facf6fe9dcd7caa33(T, N, total, totalsum):
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_fcb42c7f0c6141958b4c4eb757cf8ced(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return best
def func_1b522bba99d244768f92ca0d66907596(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return r
def func_f7b9697a0bbe437eaca9e33bb5952488(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return totalsum
def func_fe527a3ce0b3419aae5f158d3651b562(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return a
def func_63de86573b224aae9f1f9e8474443dcb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return s
def func_6462f1db1fbf46449e1f9f9c17b4ca86(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return A
def func_15a8181c64ab4692a82de8ea05f134df(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return total
def func_8b434e63e32147d2bc32c6d882bf50f6(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return q
def func_06849a63535c47c5a28626d1066aa50c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return p
def func_993fcca1c0e649cc8d64de87bd4242ee(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return i
def func_e2f8594e9ca64dcd8654f23efbcc83ad(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
return N
def func_a8bb40fc65134737ba360f8f3cd4b5ba(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_5c936034506c47c5bd14033a6b953f6a(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_ed345658196c43768f6c38d1cd4015d4(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_3e88384849a9496ba926be882060713b(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_6d4fff6f763647ea8f0e9dd103679f30(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_a5c7bc28811e4fd1ac02c08c235801d5(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return A
def func_7248f802060a4e7794c8959d6107aced(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_bed0aeae57e14a26a98754c47d037921(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1031ea5561494143b4f27b3c582366d1(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_53561c5d176f45759894a733267b6035(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_88aabe94e6764b318ca15090dd04797b(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_aeff768c0ff849b28f22b3666805f417(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_7f27c39d96914c7ca3021ab236623286(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_9bd6ec8d36d940eeb9c65f5f0fee09bd(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_fff41eaa356b426abbec77e0ae7cc499(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_76d4ce7de8cd4ebdaea20dfb1d396722(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_533c9fcc8ae8408a928cf5db36ca6bab(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_c6ebc6f32ada46b89d186717cd7f078e(N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_f781a8c9fa3547e0bbec9cee8cd9dc58(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_71f4942496a64bf18d521cf89329fc4c(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_c3f89268148b4e67be97d9e5a2e5914e(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_1e34644ed714453fa16f2cadc0130a53(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_01e307c903734bd9aefbc95a706f28b8(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_61e5332a00f8429382f5e19b86b0d934(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_5eb9c9bbd97d4c67928fcd40c9ac09e6(T, N, total, totalsum):
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_3eca48fdc68a451eb952d89dadf9c55d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return p
def func_7d3910e9f0b74b938c3dd982d0e5d964(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return q
def func_d917dff6872b4f9088039baa3af2221d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return N
def func_01a1ccf646a24ddb8981de1e709514b2(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return r
def func_6cc54bb0375142feb13cf04e82a65936(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return A
def func_0be6caff8ed74f02b53e6aa04d43bf93(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return i
def func_3d82270a03184d0e85302a0befa29e7d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return best
def func_2199d683b992451d9c735d69c8380c8c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return a
def func_13c29f009dca43cea9c187660f33a6db(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return b
def func_49b4495284ab46febcbc82c7168483c0(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return total
def func_7a087966ced24570a7629b2dc30f9a29(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return s
def func_479c4c122a8b4679b2faaa9b5d48f378(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
return totalsum
def func_f4ad26e4e8b4430daaf801ac9274191c(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_d9e3392f603c479ca85259bc0c7b34b2(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_1d7d2382410e4afbad6e132229e3df25(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return A
def func_893929db04274d1f82a7d73563096ef6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_50795ee331ee43258656611679f9b6d6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_818782be43824fbabb7740c3f72462ce(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_1b4eba326d7447e585ef56ee6461ac8f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_d28aa504c42b4e95a31d5ecc209cc372(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_a0601ae8aa534f048cb6098f9f85db51(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_c952a48a25e247f8be18eabaf023cdfd(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_835332840fcf4d8e917feeca658aec77(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_1a6aa03d8fed4735b6c35cda31b064e8(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_41a16dbe9ef949c3a0325a4933038f16(N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_297acb7c309b46209e1a96b19a82e91a(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_8c735db321ef4188a222ecdcd7b2efe8(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_dd31827642ae4575831fe6cda5a39b91(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_1d7e4a5716a44b22a2305573c28676a1(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_c4ac65d1931343bb9b6e996ad4152ef3(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_f27c58c7cc4d4147a89c1096958515f5(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_e62fe36dc80e44a0a41bea416e4f92f1(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_e11294462e2445489b52e6b0eed435ee(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_49924ab686004a759bf4948f2bb194d6(T, N, total, totalsum):
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_75b0e58d5c2046e0bb5b1406882523c4(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return r
def func_4e2e5c8fcc194f20993cddfdc052c55a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return b
def func_7403b011372b40a3a65d9ad4ebe400ba(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return N
def func_27cd90810fbf4495ae543bd7962d072b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return A
def func_00ffe956dfba46ddbc805bd41de24ddf(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return p
def func_9bbacec9b3af419cb486abe3fb656408(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return totalsum
def func_93308f57be724854adc102abcc118d34(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return i
def func_b0aa3e8451194389961221e9c416616a(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return a
def func_f56482a2429e4e148f120717c06e84b8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return q
def func_8055994d0065464d93ef85cd8c21131e(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return s
def func_3bcd690eec1940128543fccbf5c22bfb(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return total
def func_0221858737204fa389e982dac0799bbd(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
return best
def func_5139fada504242c281e3dfaf4c5444b6(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_4df52d7b70ad4a37810abf46330a3aa3(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_c5d31a6eb622455b9f7c863026b5eada(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_6d0a581ab9084400bc2ad4509dd962e0(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_47d3b72343c94709985a4ec5a9754219(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_10c189a3fd28494689725a3fdc8f9891(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return A
def func_d43643d34ebd49c591a6a144a9caf44f(p, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_c6d2018833c143c2bd608c67feb3227d(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_526fa2fc984f4447b08763398b048a81(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_3366a28a998f41dc933c3362dceb1430(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_e61ed751ed6c464ea3c72675a48a505b(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_698f2fced81d49a7b92b09b9cc787229(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_2e985ed82f844b43a73426f35f0d4513(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_326a084b251c474aba3bf5157e019e23(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_83f866438efe4c8f894f8b44ba707abe(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_192877dd3f8542e0a895f6b9f318d9a9(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_6be1570d9df14bdeabe0c780d71063f1(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_ea53fec8af8b41f69313c3e927e451d9(T, N, total, A):
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_172a73f5168749b1ac20de58ee22ef30(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return N
def func_76570db24c144caa91967ac9ac1e9e4c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return r
def func_adbf640f1e9e4cc0a7fd3eaee07b38a9(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return totalsum
def func_2aaa3e8ae0c640c793a528fc63a5e41c(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return total
def func_957089c5fc5545cb9ce942b5d4ef80e8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return q
def func_366f89dec9974b10990f0331536c05c8(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return p
def func_7d49a5cd82954d9bb8f4557a9e1764de(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return s
def func_59a339997e42418688238fc08183ea56(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return best
def func_9411e23d1c104f8b81d7ae15d9cd790d(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return a
def func_38ef4e85f58242eb890ce11e30ee544b(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return A
def func_0a3d9c5358794d96a07a86e88bd11f43(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return i
def func_a89677cd5d8b407aaf99ada694aa9eac(infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
return b
def func_7fbab4a6a241418781b5a2d12d1a7f03(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_9aa3be1304334d078816c173dc2f37d7(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_6187c62abd5d4f4ea088f53fc2d4a8cf(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_ff3b2d5022b841e495bea0c9eb53a45a(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_1f93aa92e947411b91e6f2783d55222a(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return A
def func_597204c0cb404c9983974cf8f235e6ca(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_8605c097769648f3819629d43916b606(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_ef7dba35d5834656a73cd78555f023b1(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_45b5aec34b7548d7b1f5f9d42de99bd8(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_d6b516d8e9234a5dad5dc8802b0504ab(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_611534ecf9b2487c9cdcd23bf333395c(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_7934f1a86e094e1d864da8df5603aa7c(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_e5b4633dc62346eba6d8ace8f7f5b9e6(T, N, A):
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_c8ac40984b3c4144871b8690b2828687(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return N
def func_809b9e1e6c3a496f9caa599728bbb901(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return i
def func_1ceb53a530e1435bb681a95a0d241be1(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return s
def func_97d13fa555774b9e84f227df329b52f2(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return total
def func_bb6de3759b69441ea78b54431633b006(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return A
def func_05499c2e780348f98504bf8f7b9c7d9d(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return p
def func_00d72e88b8404654b956708f231daadc(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return q
def func_af9e65eec45c451b8eb830b4b95345aa(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return totalsum
def func_b0ff1c498786447195d14db4860ca57f(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return r
def func_411779ddb1ec4ade957f1d8871308397(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return a
def func_81c3b38dac0c48fca84e80de2cad5358(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return best
def func_72dc98d4f7504e5387cd75838acb038e(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)
return b
def func_8ce62155b9734233b417516d60100590(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_70be2c23b409422c9fdf414d68939ccb(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_e3a7d5c635e54faa89dea71f048d02ab(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_0f4fb040495b4139925341acd807c78c(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_f539a9e24bac4f8796e02e51c3d12476(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_ec4ef50f73ed4cae94034202d150039b(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_5288b32e62e7470fab938555be76d716(p, T, N, q, s, r):
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return A
def func_efaa44fe3f2b4b2c9855bfd133bd99b0(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return b
def func_56c37c59c8934f7aa515817dbe7140a2(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return a
def func_7495008816464a76bb91d2ffc4988345(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return i
def func_beef533c5bd543f695c4e264d1cd8fe0(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return A
def func_e3493e1ae4b94c3b88b0cacdc6ceb441(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return totalsum
def func_48e70dfd9719447583b13b505e41e402(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return best
def func_002b1a05bdcd4e15a8af5576d9b91ca5(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return p
def func_1e9868541192432497f7afddf6598f40(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return r
def func_15358d1d753f4af0b5abf587f122981a(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return s
def func_525021bbfb694e2d81ea77e6dfdfb893(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return q
def func_3085b093b0094ae3babe3700b49f3241(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return N
def func_529d5d0ce6d24c7b89be80d23f00dc9d(T, infile):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b +
1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best('Case #%d' % T)('Case #%d: %.10f' % (T, 1.0 * best /
total))
return total
def func_d3f7b486a618491a9a2c5ce79bc867c9():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
return T
def func_0784b0652171461a8249f952f2b48000():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
return infile
def func_379b3ac414f3412d82a2a3d21559845e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return i
def func_a15be2b4249741d2a57c8a1a96e038dd(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return p
def func_ddaa4aa4e21a46f1a02effc47cf59045(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return r
def func_f2ee59dcc42c4d53b8a37093f7e40f19(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return A
def func_4e6cc241c7314974b4d28fd300c27ef7(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return totalsum
def func_dc36827cd4164af3965269e69805f105(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return N
def func_311acdaf55a14825b30544b6f62de751(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return best
def func_2b849feb727142e989b398248e69c4b0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return total
def func_84004c157eb24824a7dd45092acff705(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return a
def func_ed9f2e9046bd48a6bc7b1f2cbd4b3307(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return s
def func_06ac1429d0dd4b6786a480a62be93d63(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return q
def func_358f85f329ad449f915a3878e2b03ee6(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return b
def func_d96a764c862148198fc928d5c4aea2ef(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return T
def func_392b3c81c3aa40eda55980e1c2344b73(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_d17b7e8cddaf4ab9b9cec7ed00676ccb(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_160b060d21ff4a44a65dff46a628505c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_d52463c4007c4b1298b2c5b933e78cab(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_03d836aa566443159aaee96fbb4e9967(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_7e38d9e98b1049158c869d531753c12f(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_10894e4371e1435d9b05f716a68add7b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_0a11821b1137476e88c18298384deb8b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_15bad475ff63420baa3ece9f13f35a04(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_caf0cedfefe54103993a5aaffc3a5f5b(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_73f6530a43ca4df1af33294cc65337cc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_5ad67b425b01433da824f5b458409971(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_2a6eb9490f3b4fa89c4c00fe246f8bcf(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_39b5ff4411a3446aa7aa21c266357ed7(N, a, total, totalsum):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_8abb784db8474fe48574d1cf6e65cedc(N, a, total, totalsum, infile):
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_c10f7260f9ae4d4db9084aa2e4364cda():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return A
def func_1e62ef3080d34852a8994b744dd7cf8b():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return totalsum
def func_2fe7817bb9454ac4a7f42c36b06e5656():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return N
def func_41b7bcd3d9054f88afd5d7481ab082db():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return s
def func_2c40fb27367d4bb09fd59d10002217fe():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return best
def func_879c0a5a046d402197301a1dd262a502():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return T
def func_5700b7f5ad5445a2ae57b59931d8218f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return q
def func_3fb83ef4cbac4845919264234344ea5b():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return total
def func_ed1ca0fdfe934213a9689a109a05a323():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return a
def func_14b182e6c4d442a2a6333c20f33098af():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return b
def func_74cdc7c4ea58410b9e9e3d4153b8528f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return infile
def func_52fd8244225c47539b667eff5ac1c506():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return r
def func_1e280bac5e4f4881b06a6ffb6c3bcd27():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return p
def func_97bfc163c6f94530a61ae008f98138c5():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
return i
def func_7f420ba7f38040f9bdf680eed5f6ca30(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_f1905696e0384d21b40588505d7d96a4(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_10ccb346b51f4c6bbbd2924a66031d26(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_dd77ecfb51634b54906d9828787b665a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_2df92723130a4dbb9e3bd917045f1364(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_a4f0e5f3379042e6868bfda705691e5a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_eeffb7d067d94cf895a14810273b3adb(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_5b593d280d894227886d9820e2620ed7(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_8fc587178b0f425893cfb8b8d0bf3ab0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_eb5f88e2fd7749f08864f8f47842b573(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_1ca496655a6749638375900047039b79(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_d398731c95e149a2a588991bfb6cc19c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_10873cb0fc834b2e8aae8c536c30e9ff(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_b564fdc0138845c596ef79cd1a15d0bc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_b42646bf57b04e1ba5eb398e69ab566a(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_f13a21b1f8294c6ea4692285e7257508(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_e6c89cbce82b4fe59072ac31bd8cccfc(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_7b973b66bfe248a1b083a7b65d8747cb(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_06a170a9d28944df9bd77ac6dbfc9bb9(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_e56980d85c51442fa98eaac3e42761f6(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_ff24164b9e5c498eb583322af419353c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_d22a16a174d74323bcdfc0748c900fb7(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_3198becba046425b9f7701a079086953(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_42bb0ea960504637ac6203bee7e46b30(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_510efd6a1bef4ea4915b38410ec44f95(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_d4db808b5c5f4ad19f746d92b5eceea1(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_0fe0cb5387d84c33a820ce7538128287(N, a, total, totalsum, infile):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_a4c9e7f7ac2d41169d555389b022f1b2():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return totalsum
def func_df00b7d4111b4b17ae5338bc5d859307():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return A
def func_e3759d7baf854516acd05dd65f58e267():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return p
def func_001061ffe51349cbb94a04ecda918986():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return N
def func_b5cf5d42ed4d46ce9647adf74afadbdf():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return best
def func_c8c31fa793ec4baf9ebe919e60d10e63():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return r
def func_81d7ec305fd14deea9aae3abfb35ea46():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return T
def func_b78708fc55d5493dbd5bf9e59d12fffc():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return a
def func_dc22601ca4164c319547ec8092cd1ca0():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return total
def func_c41e70b8b5b145f3b436438803d19f3e():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return i
def func_7649988e353d42b4b610723f812d4f3e():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return q
def func_60b98beb7ef74a05829454996e6baf05():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return infile
def func_3fd2df326bee456eba012bbca72a6827():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return s
def func_8b92c7641e484c3185ac21b876e1c6a3():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
return b
def func_a058fb23c70c4f83b621ff8b996ca757(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_79cd49364c704b2481ae80b0d388570e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_6beb80e3001a481a84058c4d33a9c8ce(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_1691ea258a804e008ed80b0b27bfe0b0(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_684fcc825d8c47bcad7082f202f2183f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_c1bd00b0cf194523b77e76a0ff6c7b63(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_cedb8992c5f34bb4a21e2acfb535ab9a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_f25afc94d1bf4c3cb31d44c394340e06(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_754e6e270ffc43aea9841c9db716860a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_ad489c77b0394a6d991496c4c1d96e9a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_d2f5cfd435914ff79a6b5ec165eb991c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_a834e99521a342968ed049cd9018765f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_368aa2f7d8f843508c1434ee4c9483aa(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_a8cf91de524d4990853190090965d2ff(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_5a1da4b690934fcfa28be57548550a80(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_c24477c0275f4141bc5892c5976f4776(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_347910efdefd4af6a57bfb08473be165(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_fb81a2754a094fd5a2d0d9692c491195(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_4ef8b31e24144bee942d35ba1d2774b8(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_c39bfa9851fc481fae8afe335afe55fd(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_8f7d9b18b0f14b1e8ab440a10887730d(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_70a941215b834f7eac54b7c1636adfb4(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_b4cd67a31efc4ead91b67fbc22e24dac(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q
def func_a22c619581fb44ae9f584033f0899eb8(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_693ed1bad29e4b8a95d978208b7d6f86(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_07cf1ae667834722a41368a3a3a52f0c(infile):
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_c172c6329ac8403aae7f07e75e313b64():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return a
def func_6c62f09ceaea47129e83e1b939749cb9():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return T
def func_01dc285a49b245bb9b0949a7ec01a023():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return r
def func_f1811e15e03843e49fea3ba532ea8abe():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return A
def func_dd8add574ccb4aae9485ee4faad801bf():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return b
def func_afac472c35384280869ae404198805bc():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return best
def func_ebc4290fb5fb4b4299252ce7da042619():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return i
def func_7f3b9e7f1be74cb8a0529d04b3de64d8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return totalsum
def func_735b12cfd01b4a4c81f3ece45e4a28c2():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return N
def func_cf36e98c4f894327bcf08c3194ae7721():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return infile
def func_cb643894a3014ef1b37f5c0d1b54a565():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return p
def func_a107482df78246eb8d81ca5011347c4c():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return q
def func_918853ad2ecf47eaba61a6f1fc6d92df():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return s
def func_8f053287fe174bdf8ad67b55f778290f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
return total
def func_4e14ae8b08734803a9a1388cc930810a(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_dbd53d84aa8b47279f057ebe3203305e(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_0bd728dcd1ac4427bbd2f8f5b9caf23d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_745b0911081e4c1096ca52012199c83c(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_779e7f4767144f6e8016401603b095b1(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_68558b99861c4206a49c8c7e776ad176(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q
def func_9317c45f78c1496bb6b2d72ec0df9393(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_f74e74844ed94f00bade2c9e428e8d12(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_8b1d8cfc9aa14b8e86397102da61361d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_5a3ff70a1bc943febae09e1fabf395d2(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_512bd04277844ab09213194c90f64f0f(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_de5c06ddd14d4f9a800fe3568514c055(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_3dabdf4bb9bd4b19862c5bafe2e6a31d(infile):
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_905f4c30854f45e6a2a1e429dcc65ffa():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return infile
def func_c4b455e670464f0abb57a45a200956ec():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return r
def func_424728ccf8bf444ebac61c68c76f4d3f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return b
def func_b2fbcb34b7bc404195a6d2b707095403():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return A
def func_9c2399ce63344af09045aa205c8e5ec3():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return T
def func_0baf7a2224154215ad97b22e7a041b21():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return best
def func_d1a5f32b7cd240c0b383329cd5fc9faa():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return N
def func_7a1ced1d999d45729628f9914c8dc9a8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return a
def func_5c85d4feecc64c9cbbafcefb97477778():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return i
def func_a0bf93db7a5e4eff9bf8c8b9f3acefae():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return s
def func_acfda2965eb343009d6f0e762bc726f0():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return p
def func_4898b02e04f14731b38090bd045f16b8():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return total
def func_48cfc21f8f454641b8ba772c3aae73e7():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return totalsum
def func_109fbb71de58446b8ad0e46b3e8f694f():
infile = open('codejam/test_files/Y14R5P1/A.in')
T, = line(infile)
for T in xrange(1, T + 1):
N, p, q, r, s = line(infile)
A = [((i * p + q) % r + s) for i in xrange(N)]
total = sum(A)
totalsum = [a for a in A]
for i in xrange(1, N):
totalsum[i] += totalsum[i - 1]
best = total
b = 0
for a in xrange(N):
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a,
b + 1, total, totalsum):
b += 1
best = min(best, getsum(a, b, total, totalsum))
best = total - best
print >> stderr, 'Case #%d' % T
print 'Case #%d: %.10f' % (T, 1.0 * best / total)
if b < a:
b += 1
while b < N - 1 and getsum(a, b, total, totalsum) >= getsum(a, b + 1,
total, totalsum):
b += 1
infile.close()
return q | 0.205535 | 0.34798 |
from __future__ import absolute_import
from __future__ import print_function
import sys
import getopt
import os
import csv
from six.moves import range
from six.moves import zip
PROG = os.path.basename(sys.argv[0])
def main(args):
opts, args = getopt.getopt(args, "f:s:hk:H")
func = None
sep = ","
lambda_key = ""
has_header = False
for opt, arg in opts:
if opt == "-s":
sep = arg
elif opt == "-f":
func = eval(arg)
elif opt == "-k":
lambda_key = arg
elif opt == "-H":
has_header = True
elif opt == "-h":
usage()
raise SystemExit
if func is None:
usage("lambda expression is required!")
return 1
rdr = csv.reader(sys.stdin)
wtr = csv.writer(sys.stdout)
first = next(rdr)
indexes = None
if has_header:
# Treat first row as a header.
if lambda_key:
if lambda_key in first:
raise ValueError("%r is already in %s" % (lambda_key, first))
first.append(lambda_key)
rdr = csv.DictReader(sys.stdin, fieldnames=first, restval="")
wtr = csv.DictWriter(sys.stdout, fieldnames=first)
wtr.writerow(dict(list(zip(first, first))))
indexes = enumerate(first)
for row in rdr:
type_convert(row)
if has_header:
eff_row = row.copy()
for index, key in indexes:
eff_row[index] = eff_row[key]
val = func(eff_row)
if lambda_key:
row[lambda_key] = val
wtr.writerow(row)
elif val:
wtr.writerow(row)
else:
val = func(row)
if lambda_key:
row.append(val)
wtr.writerow(row)
elif val:
wtr.writerow(row)
return 0
def no_floats(row):
for elt in row:
try:
float(elt)
except ValueError:
pass
else:
return False
return True
def type_convert(row):
if isinstance(row, dict):
for k in row:
row[k] = floatify(row[k])
else:
for i in range(len(row)):
row[i] = floatify(row[i])
def floatify(val):
try:
val = int(val)
except ValueError:
try:
val = float(val)
except ValueError:
pass
return val
def usage(msg=""):
if msg:
print(msg, file=sys.stderr)
print(__doc__ % globals(), file=sys.stderr)
if __name__ == "__main__":
sys.exit(main(sys.argv[1:])) | data_filters/src/filter.py | from __future__ import absolute_import
from __future__ import print_function
import sys
import getopt
import os
import csv
from six.moves import range
from six.moves import zip
PROG = os.path.basename(sys.argv[0])
def main(args):
opts, args = getopt.getopt(args, "f:s:hk:H")
func = None
sep = ","
lambda_key = ""
has_header = False
for opt, arg in opts:
if opt == "-s":
sep = arg
elif opt == "-f":
func = eval(arg)
elif opt == "-k":
lambda_key = arg
elif opt == "-H":
has_header = True
elif opt == "-h":
usage()
raise SystemExit
if func is None:
usage("lambda expression is required!")
return 1
rdr = csv.reader(sys.stdin)
wtr = csv.writer(sys.stdout)
first = next(rdr)
indexes = None
if has_header:
# Treat first row as a header.
if lambda_key:
if lambda_key in first:
raise ValueError("%r is already in %s" % (lambda_key, first))
first.append(lambda_key)
rdr = csv.DictReader(sys.stdin, fieldnames=first, restval="")
wtr = csv.DictWriter(sys.stdout, fieldnames=first)
wtr.writerow(dict(list(zip(first, first))))
indexes = enumerate(first)
for row in rdr:
type_convert(row)
if has_header:
eff_row = row.copy()
for index, key in indexes:
eff_row[index] = eff_row[key]
val = func(eff_row)
if lambda_key:
row[lambda_key] = val
wtr.writerow(row)
elif val:
wtr.writerow(row)
else:
val = func(row)
if lambda_key:
row.append(val)
wtr.writerow(row)
elif val:
wtr.writerow(row)
return 0
def no_floats(row):
for elt in row:
try:
float(elt)
except ValueError:
pass
else:
return False
return True
def type_convert(row):
if isinstance(row, dict):
for k in row:
row[k] = floatify(row[k])
else:
for i in range(len(row)):
row[i] = floatify(row[i])
def floatify(val):
try:
val = int(val)
except ValueError:
try:
val = float(val)
except ValueError:
pass
return val
def usage(msg=""):
if msg:
print(msg, file=sys.stderr)
print(__doc__ % globals(), file=sys.stderr)
if __name__ == "__main__":
sys.exit(main(sys.argv[1:])) | 0.308086 | 0.142411 |
from src.params.NeuronTypes import *
class ParamsIzhikevich:
"""
This class contains Izhikevich parameters.
:param peak_potential: potential at which spikes terminate.
:type peak_potential: float
:param alpha_E: describes the timescale of recovery for excitatory neurons.
:type alpha_E: float
:param beta_E: describes the sensitivity of recovery to the subthreshold fluctuations of potential for excitatory neurons.
:type beta_E: float
:param gamma_E: describes the after-spike reset value of potential for excitatory neurons.
:type gamma_E: float
:param zeta_E: describes the after-spike reset of recovery for excitatory neurons.
:type zeta_E: float
:param alpha_I: describes the timescale of recovery for inhibitory neurons.
:type alpha_I: float
:param beta_I: describes the sensitivity of recovery to the subthreshold fluctuations of potential for inhibitory neurons.
:type beta_I: float
:param gamma_I: describes the after-spike reset value of potential for inhibitory neurons.
:type gamma_I: float
:param zeta_I: describes the after-spike reset of recovery for inhibitory neurons.
:type zeta_I: float
:ivar peak_potential: potential at which spikes terminate.
:ivar alpha: describes the timescale of recovery.
:ivar beta: describes the sensitivity of recovery to the subthreshold fluctuations of potential.
:ivar gamma: gamma describes the after-spike reset value of potential.
:ivar zeta: zeta describes the after-spike reset of recovery.
"""
def __init__(
self,
peak_potential: float,
alpha_E: float, beta_E: float, gamma_E: float, zeta_E: float,
alpha_I: float, beta_I: float, gamma_I: float, zeta_I: float
):
self.peak_potential: float = peak_potential
self.alpha: dict[NeuronTypes, float] = {
NeuronTypes.EX: alpha_E,
NeuronTypes.IN: alpha_I
}
self.beta: dict[NeuronTypes, float] = {
NeuronTypes.EX: beta_E,
NeuronTypes.IN: beta_I
}
self.gamma: dict[NeuronTypes, float] = {
NeuronTypes.EX: gamma_E,
NeuronTypes.IN: gamma_I
}
self.zeta: dict[NeuronTypes, float] = {
NeuronTypes.EX: zeta_E,
NeuronTypes.IN: zeta_I
} | src/params/ParamsIzhikevich.py | from src.params.NeuronTypes import *
class ParamsIzhikevich:
"""
This class contains Izhikevich parameters.
:param peak_potential: potential at which spikes terminate.
:type peak_potential: float
:param alpha_E: describes the timescale of recovery for excitatory neurons.
:type alpha_E: float
:param beta_E: describes the sensitivity of recovery to the subthreshold fluctuations of potential for excitatory neurons.
:type beta_E: float
:param gamma_E: describes the after-spike reset value of potential for excitatory neurons.
:type gamma_E: float
:param zeta_E: describes the after-spike reset of recovery for excitatory neurons.
:type zeta_E: float
:param alpha_I: describes the timescale of recovery for inhibitory neurons.
:type alpha_I: float
:param beta_I: describes the sensitivity of recovery to the subthreshold fluctuations of potential for inhibitory neurons.
:type beta_I: float
:param gamma_I: describes the after-spike reset value of potential for inhibitory neurons.
:type gamma_I: float
:param zeta_I: describes the after-spike reset of recovery for inhibitory neurons.
:type zeta_I: float
:ivar peak_potential: potential at which spikes terminate.
:ivar alpha: describes the timescale of recovery.
:ivar beta: describes the sensitivity of recovery to the subthreshold fluctuations of potential.
:ivar gamma: gamma describes the after-spike reset value of potential.
:ivar zeta: zeta describes the after-spike reset of recovery.
"""
def __init__(
self,
peak_potential: float,
alpha_E: float, beta_E: float, gamma_E: float, zeta_E: float,
alpha_I: float, beta_I: float, gamma_I: float, zeta_I: float
):
self.peak_potential: float = peak_potential
self.alpha: dict[NeuronTypes, float] = {
NeuronTypes.EX: alpha_E,
NeuronTypes.IN: alpha_I
}
self.beta: dict[NeuronTypes, float] = {
NeuronTypes.EX: beta_E,
NeuronTypes.IN: beta_I
}
self.gamma: dict[NeuronTypes, float] = {
NeuronTypes.EX: gamma_E,
NeuronTypes.IN: gamma_I
}
self.zeta: dict[NeuronTypes, float] = {
NeuronTypes.EX: zeta_E,
NeuronTypes.IN: zeta_I
} | 0.9231 | 0.812867 |
class Filter:
exactKeyFilter = ['name', 'ele', 'comment', 'image', 'symbol', 'deanery', 'jel', 'rating', 'school:FR', 'alt', 'is_in', 'url', 'web',
'wikipedia', 'email', 'converted_by', 'phone', 'opening_hours', 'date', 'time', 'collection_times', 'website',
'colour', 'fee', 'population', 'access', 'noexit', 'towards', 'bus_routes', 'busline', 'lines', 'type', 'denotation',
'CONTINUE', 'continue', 'copyright', 'stop', 'network', 'comment', 'old_name', 'destination', 'brand', 'fax', 'designation',
'turn:lanes', 'owner', 'fire_hydrant:city', 'fire_hydrant:street', 'country', 'contact:google_plus', 'wikipedia:ru', 'note', 'height',
'short_name:ru', 'tpuk_ref', 'wikimedia_commons', 'operator', 'source', 'wikipedia', 'wikipedia:en', 'wikipedia:de', 'railway:etcs',
'de:regionalschluessel', 'de:amtlicher_gemeindeschluessel', 'contact:xing', 'nspn', '_picture_', 'postal_code', 'exit_to',
'_waypoint_', 'label', 'branch', 'note', 'phone', 'created_by', 'start_date', 'end_date', 'description', 'description:ru',
'lacounty:bld_id', 'lacounty:ain', 'uir_adr:ADRESA_KOD']
prefixKeyFilter = ['name:', 'note:', 'alt_name', 'int_name', 'loc_name', 'not:name', 'nat_name', 'official_name', 'short_name', 'reg_name', 'sorting_name',
'contact:', 'addr', 'icao', 'iata', 'onkz', 'is_in', 'fixme', 'seamark:fixme',
'ois:fixme', 'todo', 'type:', 'admin_level', 'AND_', 'AND:', 'seamark:', 'attribution', 'openGeoDB', 'ref', 'source_ref', 'tiger',
'yh:', 'ngbe:', 'gvr:code', 'old_ref_legislative', 'sl_stop_id', 'ele:', 'source:',
'osak:', 'kms', 'gnis:', 'nhd', 'chicago:building_id', 'hgv', 'nhs', 'ncat', 'nhd-shp:', 'osmc:', 'kp',
'int_name', 'CLC:', 'naptan:', 'building:ruian:', 'massgis:', 'WroclawGIS:', 'ref:FR:FANTOIR', 'rednap:', 'ts_', 'type:FR:FINESS',
'route_ref', 'lcn_ref', 'ncn_ref', 'rcn', 'rwn_ref', 'old_ref', 'prow_ref', 'local_ref', 'loc_ref', 'reg_ref', 'url',
'nat_ref', 'int_ref', 'uic_ref', 'asset_ref', 'carriageway_ref', 'junction:ref', 'fhrs:', 'osmc:', 'cep', 'protection_title',
'bag:extract', 'ref:bagid', 'adr_les', 'bag:', 'fresno_', 'uuid', 'uic_name', 'gtfs_id', 'USGS-LULC:', 'reg_', 'IBGE:',
'sagns_id', 'protect_id', 'PMSA_ref', 'destination:', 'EH_ref', 'rtc_rate', 'cyclestreets_id', 'woeid', 'CEMT',
'depth:dredged']
exactValueFilter = []
prefixValueFilter = []
def completeFilterList(self):
'''Merges and returns the exact and prefix filter list'''
return self.exactKeyFilter + list(set(self.prefixKeyFilter) - set(self.exactKeyFilter))
def hasKey(self, strKey):
''' Checks if 'strKey' is in any key filter list'''
return self.hasKeyExact(strKey) or self.hasKeyPrefix(strKey)
def hasKeyExact(self, strKey):
return strKey in self.exactKeyFilter
def hasKeyPrefix(self, strKey):
'''Checks if 'strKey' is in prefixKeyFilter list.'''
for pkf in self.prefixKeyFilter:
lowStrKey = strKey.lower()
lowKeyFilter = pkf.lower()
if(lowStrKey.startswith(lowKeyFilter)):
return True
return False
def hasValue(self, strValue):
''' Checks if 'strValue' is in any key filter list'''
return self.hasValueExact(strValue) or self.hasValuePrefix(strValue)
def hasValueExact(self, strValue):
return strValue in self.exactValueFilter
def hasValuePrefix(self, strValue):
'''Checks if 'strValue' is in prefixValueFilter list.'''
for pvf in self.prefixValueFilter:
lowStrValue = strValue.lower()
lowValueFilter = pvf.lower()
if(lowStrValue.startswith(lowValueFilter)):
return True
return False | OSMTagFinder/thesaurus/filter.py | class Filter:
exactKeyFilter = ['name', 'ele', 'comment', 'image', 'symbol', 'deanery', 'jel', 'rating', 'school:FR', 'alt', 'is_in', 'url', 'web',
'wikipedia', 'email', 'converted_by', 'phone', 'opening_hours', 'date', 'time', 'collection_times', 'website',
'colour', 'fee', 'population', 'access', 'noexit', 'towards', 'bus_routes', 'busline', 'lines', 'type', 'denotation',
'CONTINUE', 'continue', 'copyright', 'stop', 'network', 'comment', 'old_name', 'destination', 'brand', 'fax', 'designation',
'turn:lanes', 'owner', 'fire_hydrant:city', 'fire_hydrant:street', 'country', 'contact:google_plus', 'wikipedia:ru', 'note', 'height',
'short_name:ru', 'tpuk_ref', 'wikimedia_commons', 'operator', 'source', 'wikipedia', 'wikipedia:en', 'wikipedia:de', 'railway:etcs',
'de:regionalschluessel', 'de:amtlicher_gemeindeschluessel', 'contact:xing', 'nspn', '_picture_', 'postal_code', 'exit_to',
'_waypoint_', 'label', 'branch', 'note', 'phone', 'created_by', 'start_date', 'end_date', 'description', 'description:ru',
'lacounty:bld_id', 'lacounty:ain', 'uir_adr:ADRESA_KOD']
prefixKeyFilter = ['name:', 'note:', 'alt_name', 'int_name', 'loc_name', 'not:name', 'nat_name', 'official_name', 'short_name', 'reg_name', 'sorting_name',
'contact:', 'addr', 'icao', 'iata', 'onkz', 'is_in', 'fixme', 'seamark:fixme',
'ois:fixme', 'todo', 'type:', 'admin_level', 'AND_', 'AND:', 'seamark:', 'attribution', 'openGeoDB', 'ref', 'source_ref', 'tiger',
'yh:', 'ngbe:', 'gvr:code', 'old_ref_legislative', 'sl_stop_id', 'ele:', 'source:',
'osak:', 'kms', 'gnis:', 'nhd', 'chicago:building_id', 'hgv', 'nhs', 'ncat', 'nhd-shp:', 'osmc:', 'kp',
'int_name', 'CLC:', 'naptan:', 'building:ruian:', 'massgis:', 'WroclawGIS:', 'ref:FR:FANTOIR', 'rednap:', 'ts_', 'type:FR:FINESS',
'route_ref', 'lcn_ref', 'ncn_ref', 'rcn', 'rwn_ref', 'old_ref', 'prow_ref', 'local_ref', 'loc_ref', 'reg_ref', 'url',
'nat_ref', 'int_ref', 'uic_ref', 'asset_ref', 'carriageway_ref', 'junction:ref', 'fhrs:', 'osmc:', 'cep', 'protection_title',
'bag:extract', 'ref:bagid', 'adr_les', 'bag:', 'fresno_', 'uuid', 'uic_name', 'gtfs_id', 'USGS-LULC:', 'reg_', 'IBGE:',
'sagns_id', 'protect_id', 'PMSA_ref', 'destination:', 'EH_ref', 'rtc_rate', 'cyclestreets_id', 'woeid', 'CEMT',
'depth:dredged']
exactValueFilter = []
prefixValueFilter = []
def completeFilterList(self):
'''Merges and returns the exact and prefix filter list'''
return self.exactKeyFilter + list(set(self.prefixKeyFilter) - set(self.exactKeyFilter))
def hasKey(self, strKey):
''' Checks if 'strKey' is in any key filter list'''
return self.hasKeyExact(strKey) or self.hasKeyPrefix(strKey)
def hasKeyExact(self, strKey):
return strKey in self.exactKeyFilter
def hasKeyPrefix(self, strKey):
'''Checks if 'strKey' is in prefixKeyFilter list.'''
for pkf in self.prefixKeyFilter:
lowStrKey = strKey.lower()
lowKeyFilter = pkf.lower()
if(lowStrKey.startswith(lowKeyFilter)):
return True
return False
def hasValue(self, strValue):
''' Checks if 'strValue' is in any key filter list'''
return self.hasValueExact(strValue) or self.hasValuePrefix(strValue)
def hasValueExact(self, strValue):
return strValue in self.exactValueFilter
def hasValuePrefix(self, strValue):
'''Checks if 'strValue' is in prefixValueFilter list.'''
for pvf in self.prefixValueFilter:
lowStrValue = strValue.lower()
lowValueFilter = pvf.lower()
if(lowStrValue.startswith(lowValueFilter)):
return True
return False | 0.494385 | 0.433082 |
import os
import re
import sys
import math
import time
import jieba
import torch
import config # 常规参数设置
import random
import argparse
import numpy as np
import pandas as pd
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
from torch.autograd import Variable
from preprocessing import Corpuspreprocessing
import seq2seq.seq2seq as Encoder_Decoder
os.environ['CUDA_LAUNCH_BLOCKING'] = "1" # 方便定位报错信息
USE_CUDA = torch.cuda.is_available()
SOS_token = 2
EOS_token = 1
parser = argparse.ArgumentParser(description='manual to seq2seq.py')
parser.add_argument('--run_type', help="本文件运行模式，主要分为train和predict两种", type=str, default = "train")
parser.add_argument('--input_size', help="Encoder对应的词嵌入的词库大小，等于vocab的大小+1", type=int, default = config.question_word_num)
parser.add_argument('--hidden_size', help="隐层大小", type=int, default = 256)
parser.add_argument('--output_size', help="Decoder对应的词嵌入的词库大小，等于vocab的大小+1", type=int, default = config.answer_word_num)
parser.add_argument('--n_layers', help="Encoder/Decoder网络层数", type=int, default = 2)
parser.add_argument('--dropout_p', help="dropout概率", type=float, default = 0.25)
parser.add_argument('--max_length', help="最大长度", type=int, default = 32)
parser.add_argument('--max_epoches', help="最大epoches", type=int, default = 100000)
parser.add_argument('--beam_search', help="是否进行beam_search算法搜索", type=bool, default = True)
parser.add_argument('--use_cuda', help="是否使用CUDA训练", type=bool, default = USE_CUDA)
parser.add_argument('--model_path', help="训练好的模型路径，默认为: .model/+Corpus+/", type=str, default = config.Modelpath)
parser.add_argument('--Corpus', help="对话语料库名称，文件格式为.tsv，每一行为一个句子对，形式为:Q \t A, 可选择: Chatterbot、Douban、Ptt、Qingyun、Subtitle、Tieba、Weibo、Xiaohuangji", type=str, default = config.Corpus)
parser.add_argument('--Filepath', help="文件路径", type=str, default = config.Filepath)
parser.add_argument('--rnn_type', help="RNN结构，可以选择RNN、LSTM、GRU，默认为GRU", type=str, default = "GRU")
parser.add_argument('--gpu_id', help="GPU_ID", type=str, default = "0,1,2,3,4")
args = parser.parse_args()
os.environ["CUDA_VISIBLE_DEVICES"] = args.gpu_id
device = torch.device("cuda:"+re.split(r",",args.gpu_id)[0] if USE_CUDA else "cpu")
gpu_id = list(map(int, re.split(r",",args.gpu_id)))
print("当前GPU: ", torch.cuda.current_device())
if __name__ == '__main__':
question_word_num, answer_word_num = config.Check_Preprocess(Filepath = args.Filepath, Corpus = args.Corpus)
gcr = Encoder_Decoder(input_size = question_word_num,
hidden_size = args.hidden_size,
output_size = answer_word_num,
n_layers = args.n_layers,
dropout_p = args.dropout_p,
max_length = args.max_length,
max_epoches = args.max_epoches,
beam_search = args.beam_search,
rnn_type = args.rnn_type,
use_cuda = args.use_cuda,
model_path = "./model/"+args.Corpus+"/",
Corpus = args.Corpus,
Filepath = args.Filepath)
gcr = torch.nn.DataParallel(gcr, device_ids = gpu_id)
gcr.to(device)
print("网络参数如下: ")
print("input_size: ", question_word_num)
print("hidden_size: ", args.hidden_size)
print("output_size: ", answer_word_num)
print("n_layers: ", args.n_layers)
print("dropout_p: ", args.dropout_p)
print("max_length: ", args.max_length)
print("max_epoches: ", args.max_epoches)
print("beam_search: ", args.beam_search)
print("rnn_type: ", args.rnn_type)
print("use_cuda: ", args.use_cuda)
print("model_path: ", "./model/"+args.Corpus+"/")
print("Corpus: ", args.Corpus)
print("Filepath: ", args.Filepath)
if os.path.exists("./model/"+args.Corpus+"/") == False:
os.mkdir("./model/"+args.Corpus+"/")
netparam = open("./model/"+str(args.Corpus)+"/"+"Networkparameters.txt", "w")
netparam.write("input_size: "+str(question_word_num)+"\n")
netparam.write("hidden_size: "+str(args.hidden_size)+"\n")
netparam.write("output_size: "+str(answer_word_num)+"\n")
netparam.write("n_layers: "+str(args.n_layers)+"\n")
netparam.write("dropout_p: "+str(args.dropout_p)+"\n")
netparam.write("max_length: "+str(args.max_length)+"\n")
netparam.write("imax_epoches: "+str(args.max_epoches)+"\n")
netparam.write("beam_search: "+str(args.beam_search)+"\n")
netparam.write("rnn_type: "+str(args.rnn_type)+"\n")
netparam.write("use_cuda: "+str(args.use_cuda)+"\n")
netparam.write("model_path: "+str("./model/"+args.Corpus+"/")+"\n")
netparam.write("Corpus: "+str(args.Corpus)+"\n")
netparam.write("Filepath: "+str(args.Filepath)+"\n")
netparam.close()
if args.run_type == 'train':
#seq.train() # 单GPU
seq.module.train() # 加上.module
elif args.run_type == 'predict':
#seq.predict() # 单GPU
seq.module.predict() # 加上.module
elif args.run_type == 'retrain':
#seq.retrain() # 单GPU
seq.module.retrain() # 加上.module | gru_seq2seq/evaluate.py | import os
import re
import sys
import math
import time
import jieba
import torch
import config # 常规参数设置
import random
import argparse
import numpy as np
import pandas as pd
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
from torch.autograd import Variable
from preprocessing import Corpuspreprocessing
import seq2seq.seq2seq as Encoder_Decoder
os.environ['CUDA_LAUNCH_BLOCKING'] = "1" # 方便定位报错信息
USE_CUDA = torch.cuda.is_available()
SOS_token = 2
EOS_token = 1
parser = argparse.ArgumentParser(description='manual to seq2seq.py')
parser.add_argument('--run_type', help="本文件运行模式，主要分为train和predict两种", type=str, default = "train")
parser.add_argument('--input_size', help="Encoder对应的词嵌入的词库大小，等于vocab的大小+1", type=int, default = config.question_word_num)
parser.add_argument('--hidden_size', help="隐层大小", type=int, default = 256)
parser.add_argument('--output_size', help="Decoder对应的词嵌入的词库大小，等于vocab的大小+1", type=int, default = config.answer_word_num)
parser.add_argument('--n_layers', help="Encoder/Decoder网络层数", type=int, default = 2)
parser.add_argument('--dropout_p', help="dropout概率", type=float, default = 0.25)
parser.add_argument('--max_length', help="最大长度", type=int, default = 32)
parser.add_argument('--max_epoches', help="最大epoches", type=int, default = 100000)
parser.add_argument('--beam_search', help="是否进行beam_search算法搜索", type=bool, default = True)
parser.add_argument('--use_cuda', help="是否使用CUDA训练", type=bool, default = USE_CUDA)
parser.add_argument('--model_path', help="训练好的模型路径，默认为: .model/+Corpus+/", type=str, default = config.Modelpath)
parser.add_argument('--Corpus', help="对话语料库名称，文件格式为.tsv，每一行为一个句子对，形式为:Q \t A, 可选择: Chatterbot、Douban、Ptt、Qingyun、Subtitle、Tieba、Weibo、Xiaohuangji", type=str, default = config.Corpus)
parser.add_argument('--Filepath', help="文件路径", type=str, default = config.Filepath)
parser.add_argument('--rnn_type', help="RNN结构，可以选择RNN、LSTM、GRU，默认为GRU", type=str, default = "GRU")
parser.add_argument('--gpu_id', help="GPU_ID", type=str, default = "0,1,2,3,4")
args = parser.parse_args()
os.environ["CUDA_VISIBLE_DEVICES"] = args.gpu_id
device = torch.device("cuda:"+re.split(r",",args.gpu_id)[0] if USE_CUDA else "cpu")
gpu_id = list(map(int, re.split(r",",args.gpu_id)))
print("当前GPU: ", torch.cuda.current_device())
if __name__ == '__main__':
question_word_num, answer_word_num = config.Check_Preprocess(Filepath = args.Filepath, Corpus = args.Corpus)
gcr = Encoder_Decoder(input_size = question_word_num,
hidden_size = args.hidden_size,
output_size = answer_word_num,
n_layers = args.n_layers,
dropout_p = args.dropout_p,
max_length = args.max_length,
max_epoches = args.max_epoches,
beam_search = args.beam_search,
rnn_type = args.rnn_type,
use_cuda = args.use_cuda,
model_path = "./model/"+args.Corpus+"/",
Corpus = args.Corpus,
Filepath = args.Filepath)
gcr = torch.nn.DataParallel(gcr, device_ids = gpu_id)
gcr.to(device)
print("网络参数如下: ")
print("input_size: ", question_word_num)
print("hidden_size: ", args.hidden_size)
print("output_size: ", answer_word_num)
print("n_layers: ", args.n_layers)
print("dropout_p: ", args.dropout_p)
print("max_length: ", args.max_length)
print("max_epoches: ", args.max_epoches)
print("beam_search: ", args.beam_search)
print("rnn_type: ", args.rnn_type)
print("use_cuda: ", args.use_cuda)
print("model_path: ", "./model/"+args.Corpus+"/")
print("Corpus: ", args.Corpus)
print("Filepath: ", args.Filepath)
if os.path.exists("./model/"+args.Corpus+"/") == False:
os.mkdir("./model/"+args.Corpus+"/")
netparam = open("./model/"+str(args.Corpus)+"/"+"Networkparameters.txt", "w")
netparam.write("input_size: "+str(question_word_num)+"\n")
netparam.write("hidden_size: "+str(args.hidden_size)+"\n")
netparam.write("output_size: "+str(answer_word_num)+"\n")
netparam.write("n_layers: "+str(args.n_layers)+"\n")
netparam.write("dropout_p: "+str(args.dropout_p)+"\n")
netparam.write("max_length: "+str(args.max_length)+"\n")
netparam.write("imax_epoches: "+str(args.max_epoches)+"\n")
netparam.write("beam_search: "+str(args.beam_search)+"\n")
netparam.write("rnn_type: "+str(args.rnn_type)+"\n")
netparam.write("use_cuda: "+str(args.use_cuda)+"\n")
netparam.write("model_path: "+str("./model/"+args.Corpus+"/")+"\n")
netparam.write("Corpus: "+str(args.Corpus)+"\n")
netparam.write("Filepath: "+str(args.Filepath)+"\n")
netparam.close()
if args.run_type == 'train':
#seq.train() # 单GPU
seq.module.train() # 加上.module
elif args.run_type == 'predict':
#seq.predict() # 单GPU
seq.module.predict() # 加上.module
elif args.run_type == 'retrain':
#seq.retrain() # 单GPU
seq.module.retrain() # 加上.module | 0.145813 | 0.060363 |
import numpy as np
from qlazy import QState
Hamming = np.array([[0,1,1,1,1,0,0], [1,0,1,1,0,1,0], [1,1,0,1,0,0,1]])
Hamming_T = Hamming.T
Steane_0 = ['0000000', '1101001', '1011010', '0110011',
'0111100', '1010101', '1100110', '0001111']
Steane_1 = ['1111111', '0010110', '0100101', '1001100',
'1000011', '0101010', '0011001', '1110000']
class MyQState(QState):
def noise(self, qid):
i = np.random.randint(len(qid))
alpha, beta, gamma = np.random.rand(3)
self.u3(qid[i], alpha=alpha, beta=beta, gamma=gamma)
print("== random noise (random U3 operation)==")
print("- qubit id = #{0:}".format(i, alpha, beta, gamma))
print("- parameter of U3 = {0:.4f},{1:.4f},{2:.4f}".format(alpha, beta, gamma))
return self
def correct(self, kind, qid_C, qid_S):
self.reset(qid=qid_S)
if kind == 'phase_flip': [self.h(q) for q in qid_C]
# syndrome
for i, row in enumerate(Hamming):
[self.cx(qid_C[j], qid_S[i]) if row[j] == 1 else False for j in range(len(row))]
#[self.cx(qid_C[j], qid_S[i], cond=(row[j] == 1)) for j in range(len(row))]
# correction
for i, row in enumerate(Hamming_T):
[self.x(qid_S[j]) if row[j] == 0 else False for j in range(len(row))]
self.mcx(qid=qid_S+[qid_C[i]])
[self.x(qid_S[j]) if row[j] == 0 else False for j in range(len(row))]
if kind == 'phase_flip': [self.h(q) for q in qid_C]
return self
def generate_qstate(qid_C, qid_S):
a = np.random.rand() + np.random.rand() * 1.j
b = np.random.rand() + np.random.rand() * 1.j
qvec = np.full(2**len(qid_C), 0.+0.j)
for s in Steane_0: qvec[int(s, 2)] = a
for s in Steane_1: qvec[int(s, 2)] = b
norm = np.linalg.norm(qvec)
qvec = qvec / norm
qs_C = MyQState(vector=qvec)
qs_S = MyQState(len(qid_S))
qs_ini = qs_C.tenspro(qs_S)
qs_fin = qs_ini.clone()
print("== random state (a |0L> + b |1L>) ==")
print("- a = {:.4f}".format(a))
print("- b = {:.4f}".format(b))
# QState.free_all(qs_C, qs_S)
return qs_ini, qs_fin
if __name__ == '__main__':
# set registers
qid_C = QState.create_register(7) # registers for code space
qid_S = QState.create_register(3) # registers for error syndrome
QState.init_register(qid_C, qid_S)
# generate initial quantum state
qs_ini, qs_fin = generate_qstate(qid_C, qid_S)
# add noise
qs_fin.noise(qid_C)
# error correction
qs_fin.correct('bit_flip', qid_C, qid_S)
qs_fin.correct('phase_flip', qid_C, qid_S)
# print result
print("== result ==")
print("- fidelity = {:.6f}".format(qs_fin.fidelity(qs_ini, qid=qid_C))) | example/py/ErrorCorrection/steane_code_0.py | import numpy as np
from qlazy import QState
Hamming = np.array([[0,1,1,1,1,0,0], [1,0,1,1,0,1,0], [1,1,0,1,0,0,1]])
Hamming_T = Hamming.T
Steane_0 = ['0000000', '1101001', '1011010', '0110011',
'0111100', '1010101', '1100110', '0001111']
Steane_1 = ['1111111', '0010110', '0100101', '1001100',
'1000011', '0101010', '0011001', '1110000']
class MyQState(QState):
def noise(self, qid):
i = np.random.randint(len(qid))
alpha, beta, gamma = np.random.rand(3)
self.u3(qid[i], alpha=alpha, beta=beta, gamma=gamma)
print("== random noise (random U3 operation)==")
print("- qubit id = #{0:}".format(i, alpha, beta, gamma))
print("- parameter of U3 = {0:.4f},{1:.4f},{2:.4f}".format(alpha, beta, gamma))
return self
def correct(self, kind, qid_C, qid_S):
self.reset(qid=qid_S)
if kind == 'phase_flip': [self.h(q) for q in qid_C]
# syndrome
for i, row in enumerate(Hamming):
[self.cx(qid_C[j], qid_S[i]) if row[j] == 1 else False for j in range(len(row))]
#[self.cx(qid_C[j], qid_S[i], cond=(row[j] == 1)) for j in range(len(row))]
# correction
for i, row in enumerate(Hamming_T):
[self.x(qid_S[j]) if row[j] == 0 else False for j in range(len(row))]
self.mcx(qid=qid_S+[qid_C[i]])
[self.x(qid_S[j]) if row[j] == 0 else False for j in range(len(row))]
if kind == 'phase_flip': [self.h(q) for q in qid_C]
return self
def generate_qstate(qid_C, qid_S):
a = np.random.rand() + np.random.rand() * 1.j
b = np.random.rand() + np.random.rand() * 1.j
qvec = np.full(2**len(qid_C), 0.+0.j)
for s in Steane_0: qvec[int(s, 2)] = a
for s in Steane_1: qvec[int(s, 2)] = b
norm = np.linalg.norm(qvec)
qvec = qvec / norm
qs_C = MyQState(vector=qvec)
qs_S = MyQState(len(qid_S))
qs_ini = qs_C.tenspro(qs_S)
qs_fin = qs_ini.clone()
print("== random state (a |0L> + b |1L>) ==")
print("- a = {:.4f}".format(a))
print("- b = {:.4f}".format(b))
# QState.free_all(qs_C, qs_S)
return qs_ini, qs_fin
if __name__ == '__main__':
# set registers
qid_C = QState.create_register(7) # registers for code space
qid_S = QState.create_register(3) # registers for error syndrome
QState.init_register(qid_C, qid_S)
# generate initial quantum state
qs_ini, qs_fin = generate_qstate(qid_C, qid_S)
# add noise
qs_fin.noise(qid_C)
# error correction
qs_fin.correct('bit_flip', qid_C, qid_S)
qs_fin.correct('phase_flip', qid_C, qid_S)
# print result
print("== result ==")
print("- fidelity = {:.6f}".format(qs_fin.fidelity(qs_ini, qid=qid_C))) | 0.50293 | 0.459925 |
import sys
from xml.sax.saxutils import escape
USAGE_TEXT = """
usage:
python3 Ch02Ex04.py [maxwidth=int] [format=str] <infile.csv> <outfile.html>
maxwidth is an optional integer; if specified, it sets the maximum
number of characters that can be output for string fields,
otherwise a default of 100 characters is used.
format is the format to use for numbers; if not specified it
defaults to ".0f". For allowed format types, see Figure 2.6.
"""
NUMBER_TEMPLATE = "<td align='right'>{0:{1}}</td>\n"
def main():
# Get parameters from command line
max_width, int_format = process_options(sys.argv)
if max_width is None or int_format is None:
return
input_filename = sys.argv[-2]
output_filename = sys.argv[-1]
table = ""
table += print_start()
count = 0
# Read in data from file, instead of with call to input()
file_object = open(input_filename, "r")
data = file_object.read()
file_object.close()
# Convert data to html
lines = data.splitlines()
for line in lines:
try:
if count == 0:
color = "lightgreen"
elif count % 2 == 0:
color = "white"
else:
color = "lightyellow"
table = print_line(table, line, color, max_width, int_format)
count += 1
except EOFError:
break
table += print_end()
# Dump html into output file
output_file_object = open(output_filename, "w")
output_file_object.write(table)
output_file_object.close()
def process_options(cmd_args):
# Set the defaults. These will change if the user has defined alternatives
max_width = 100
int_format = '.0f'
# Produce the USAGE_TEXT if user asks for help, otherwise handle maxwidth
# and format if they are defined by the user
if cmd_args[1] in ('-h', '--help'):
print(USAGE_TEXT)
return None, None
else:
# cmd_args[1:-2] excludes the script name, input filename and output
# filename, leaving only maxwidth and format should they exist.
for arg in cmd_args[1:-2]:
if 'maxwidth' in arg:
width_num = arg.replace('maxwidth=', '')
try:
# If the user enters maxwidth=5.0, this is a valid integer
# but not a valid int. We should handle this.
if '.' in width_num:
max_width = int(float(width_num))
else:
max_width = int(width_num)
# If the user entered a width that couldn't be converted to an
# int terminate the program
except ValueError:
print('Incorrect value for '
'maxwidth. Enter an '
'integer.')
max_width = None
break
elif 'format' in arg:
int_format = arg.replace('format=', '')
# Call str.format(...) and terminate the program if an
# exception is raised
try:
'{0:{1}}'.format(1, int_format)
except ValueError as e:
print('Incorrect value for format. '
+ e.__str__() + '.')
int_format = None
break
return max_width, int_format
def print_start():
return "<table border='1'>\n"
def print_end():
return "</table>\n"
def print_line(table, line, color, max_width, int_format):
table += "<tr bgcolor='{0}'>\n".format(color)
fields = extract_fields(line)
for field in fields:
if not field:
table += "<td></td>\n"
else:
number = field.replace(",", "")
try:
x = float(number)
# const NUMBER_TEMPLATE is defined so this line isn't too long
table += NUMBER_TEMPLATE.format(round(x), int_format)
except ValueError:
field = field.title()
field = field.replace(" And ", " and ")
if len(field) <= max_width:
field = escape(field)
else:
field = "{0} ...".format(escape(field[:max_width]))
table += "<td>{0}</td>\n".format(field)
table += "</tr>\n"
return table
def extract_fields(line):
fields = []
field = ""
quote = None
for c in line:
if c in "\"'":
if quote is None: # start of quoted string
quote = c
elif quote == c: # end of quoted string
quote = None
else:
field += c # other quote inside quoted string
continue
if quote is None and c == ",": # end of a field
fields.append(field)
field = ""
else:
field += c # accumulating a field
if field:
fields.append(field) # adding the last field
return fields
main() | Chapter 02/Ch02Ex04.py | import sys
from xml.sax.saxutils import escape
USAGE_TEXT = """
usage:
python3 Ch02Ex04.py [maxwidth=int] [format=str] <infile.csv> <outfile.html>
maxwidth is an optional integer; if specified, it sets the maximum
number of characters that can be output for string fields,
otherwise a default of 100 characters is used.
format is the format to use for numbers; if not specified it
defaults to ".0f". For allowed format types, see Figure 2.6.
"""
NUMBER_TEMPLATE = "<td align='right'>{0:{1}}</td>\n"
def main():
# Get parameters from command line
max_width, int_format = process_options(sys.argv)
if max_width is None or int_format is None:
return
input_filename = sys.argv[-2]
output_filename = sys.argv[-1]
table = ""
table += print_start()
count = 0
# Read in data from file, instead of with call to input()
file_object = open(input_filename, "r")
data = file_object.read()
file_object.close()
# Convert data to html
lines = data.splitlines()
for line in lines:
try:
if count == 0:
color = "lightgreen"
elif count % 2 == 0:
color = "white"
else:
color = "lightyellow"
table = print_line(table, line, color, max_width, int_format)
count += 1
except EOFError:
break
table += print_end()
# Dump html into output file
output_file_object = open(output_filename, "w")
output_file_object.write(table)
output_file_object.close()
def process_options(cmd_args):
# Set the defaults. These will change if the user has defined alternatives
max_width = 100
int_format = '.0f'
# Produce the USAGE_TEXT if user asks for help, otherwise handle maxwidth
# and format if they are defined by the user
if cmd_args[1] in ('-h', '--help'):
print(USAGE_TEXT)
return None, None
else:
# cmd_args[1:-2] excludes the script name, input filename and output
# filename, leaving only maxwidth and format should they exist.
for arg in cmd_args[1:-2]:
if 'maxwidth' in arg:
width_num = arg.replace('maxwidth=', '')
try:
# If the user enters maxwidth=5.0, this is a valid integer
# but not a valid int. We should handle this.
if '.' in width_num:
max_width = int(float(width_num))
else:
max_width = int(width_num)
# If the user entered a width that couldn't be converted to an
# int terminate the program
except ValueError:
print('Incorrect value for '
'maxwidth. Enter an '
'integer.')
max_width = None
break
elif 'format' in arg:
int_format = arg.replace('format=', '')
# Call str.format(...) and terminate the program if an
# exception is raised
try:
'{0:{1}}'.format(1, int_format)
except ValueError as e:
print('Incorrect value for format. '
+ e.__str__() + '.')
int_format = None
break
return max_width, int_format
def print_start():
return "<table border='1'>\n"
def print_end():
return "</table>\n"
def print_line(table, line, color, max_width, int_format):
table += "<tr bgcolor='{0}'>\n".format(color)
fields = extract_fields(line)
for field in fields:
if not field:
table += "<td></td>\n"
else:
number = field.replace(",", "")
try:
x = float(number)
# const NUMBER_TEMPLATE is defined so this line isn't too long
table += NUMBER_TEMPLATE.format(round(x), int_format)
except ValueError:
field = field.title()
field = field.replace(" And ", " and ")
if len(field) <= max_width:
field = escape(field)
else:
field = "{0} ...".format(escape(field[:max_width]))
table += "<td>{0}</td>\n".format(field)
table += "</tr>\n"
return table
def extract_fields(line):
fields = []
field = ""
quote = None
for c in line:
if c in "\"'":
if quote is None: # start of quoted string
quote = c
elif quote == c: # end of quoted string
quote = None
else:
field += c # other quote inside quoted string
continue
if quote is None and c == ",": # end of a field
fields.append(field)
field = ""
else:
field += c # accumulating a field
if field:
fields.append(field) # adding the last field
return fields
main() | 0.260672 | 0.139279 |
"""Take usage data .csv file from SCE, parse it, and analyze it"""
import sys
import os
import re
import datetime
from power_plotting import PowerPlotting
def print_usage(error_string=""):
"""Print usage in the case of bad inputs"""
script_name = os.path.basename(__file__)
print "=========================="
if error_string:
print "Error: "
print "\t " + error_string
print "Usage: "
print "\t" + script_name + " /path/to/usage.csv"
print "=========================="
raise ValueError("Incorrect Parameters")
def verify_inputs(args):
"""Verify the validity of the inputs.
We need at least one argument, the csv file we are going to process."""
if not args:
print_usage(error_string="Not enough arguments")
return False
for csv_file_path in args:
if not os.path.exists(csv_file_path):
print_usage(error_string="Cannot locate file: " + str(csv_file_path))
return False
return True
def convert_date_dict_to_datetime(date_dict):
"""Take in a dictionary and return datetime"""
return datetime.datetime(int(date_dict['year']), int(date_dict['month']), \
int(date_dict['day']), int(date_dict['hour']), \
int(date_dict['minute']), int(date_dict['second']))
def get_dates_from_line(csv_line):
"""Take in CSV line. If it is a line that contains two dates, extract and return them"""
line_regex = re.compile(r'((?P<year>(?:19|20)\d\d)([- /.])' + \
'(?P<month>0[1-9]|1[012])-(?P<day>0[1-9]|[12][0-9]|3[01])' + \
'.(?P<hour>[0-1][0-9]|2[0-3]):(?P<minute>[0-5][0-9]):(?P<second>[0-5][0-9]))')
dates = [m.groupdict() for m in line_regex.finditer(csv_line)]
if len(dates) >= 2:
#Make sure we get both a start and end time
start_date = convert_date_dict_to_datetime(dates[0])
end_date = convert_date_dict_to_datetime(dates[1])
return [start_date, end_date]
return None
def parse_csv_file(csv_path):
"""Read in a CSV file and return the data"""
# This is only a CSV in that it's values are separted by commas.
# There is a lot of non-tabular data in this file.
print "Parsing " + csv_path
consumption_data = []
with open(csv_path) as csv_file_handle:
for line in csv_file_handle:
#Replace non-printable characters with a space
line = re.sub(r'[^\x00-\x7F]+', ' ', line)
times = get_dates_from_line(line)
if times:
split_line = line.split(",")
#Second column contains usage data we are interested in
consumption_value = float(split_line[1].replace('"', ''))
#The end time is implied. Data is in one hour increments.
consumption_data.append({'time': times[0], 'value': consumption_value})
return consumption_data
def main(args):
"""Main function. Takes a list of csv filenames/paths"""
print "Starting"
verify_inputs(args)
parsed_files = []
for csv_file in args:
parsed_files.append(parse_csv_file(csv_file))
plotting = PowerPlotting(parsed_files[0])
plotting.plot_all_usage()
plotting.plot_usage_per_week_day()
plotting.plot_weekly_usage()
plotting.plot_hourly_usage() #All days
plotting.plot_hourly_usage(valid_days=range(0, 5)) #Only Week Days
plotting.plot_hourly_usage(valid_days=range(5, 7)) #Only weekends
plotting.show_plots()
return True
if __name__ == "__main__":
main(sys.argv[1:]) | power_parser.py | """Take usage data .csv file from SCE, parse it, and analyze it"""
import sys
import os
import re
import datetime
from power_plotting import PowerPlotting
def print_usage(error_string=""):
"""Print usage in the case of bad inputs"""
script_name = os.path.basename(__file__)
print "=========================="
if error_string:
print "Error: "
print "\t " + error_string
print "Usage: "
print "\t" + script_name + " /path/to/usage.csv"
print "=========================="
raise ValueError("Incorrect Parameters")
def verify_inputs(args):
"""Verify the validity of the inputs.
We need at least one argument, the csv file we are going to process."""
if not args:
print_usage(error_string="Not enough arguments")
return False
for csv_file_path in args:
if not os.path.exists(csv_file_path):
print_usage(error_string="Cannot locate file: " + str(csv_file_path))
return False
return True
def convert_date_dict_to_datetime(date_dict):
"""Take in a dictionary and return datetime"""
return datetime.datetime(int(date_dict['year']), int(date_dict['month']), \
int(date_dict['day']), int(date_dict['hour']), \
int(date_dict['minute']), int(date_dict['second']))
def get_dates_from_line(csv_line):
"""Take in CSV line. If it is a line that contains two dates, extract and return them"""
line_regex = re.compile(r'((?P<year>(?:19|20)\d\d)([- /.])' + \
'(?P<month>0[1-9]|1[012])-(?P<day>0[1-9]|[12][0-9]|3[01])' + \
'.(?P<hour>[0-1][0-9]|2[0-3]):(?P<minute>[0-5][0-9]):(?P<second>[0-5][0-9]))')
dates = [m.groupdict() for m in line_regex.finditer(csv_line)]
if len(dates) >= 2:
#Make sure we get both a start and end time
start_date = convert_date_dict_to_datetime(dates[0])
end_date = convert_date_dict_to_datetime(dates[1])
return [start_date, end_date]
return None
def parse_csv_file(csv_path):
"""Read in a CSV file and return the data"""
# This is only a CSV in that it's values are separted by commas.
# There is a lot of non-tabular data in this file.
print "Parsing " + csv_path
consumption_data = []
with open(csv_path) as csv_file_handle:
for line in csv_file_handle:
#Replace non-printable characters with a space
line = re.sub(r'[^\x00-\x7F]+', ' ', line)
times = get_dates_from_line(line)
if times:
split_line = line.split(",")
#Second column contains usage data we are interested in
consumption_value = float(split_line[1].replace('"', ''))
#The end time is implied. Data is in one hour increments.
consumption_data.append({'time': times[0], 'value': consumption_value})
return consumption_data
def main(args):
"""Main function. Takes a list of csv filenames/paths"""
print "Starting"
verify_inputs(args)
parsed_files = []
for csv_file in args:
parsed_files.append(parse_csv_file(csv_file))
plotting = PowerPlotting(parsed_files[0])
plotting.plot_all_usage()
plotting.plot_usage_per_week_day()
plotting.plot_weekly_usage()
plotting.plot_hourly_usage() #All days
plotting.plot_hourly_usage(valid_days=range(0, 5)) #Only Week Days
plotting.plot_hourly_usage(valid_days=range(5, 7)) #Only weekends
plotting.show_plots()
return True
if __name__ == "__main__":
main(sys.argv[1:]) | 0.369884 | 0.38027 |
import random
from pathlib import Path
import numpy as np
import tensorflow as tf
from models.PositiveLearningElkan.pu_learning import PULogisticRegressionSK
from models.baselines import LogisticRegressionSK
from models.recurrent.basic_recurrent import BasicRecurrent
from project_paths import ProjectPaths
from run_files.single_train import single_training
from util.learning_rate_utilities import linear_geometric_curve
from util.tensor_provider import TensorProvider
if __name__ == "__main__":
# Initialize tensor-provider (data-source)
the_tensor_provider = TensorProvider(verbose=True)
# Results path
used_base_path = Path(ProjectPaths.results, "single_train")
# Settings
test_ratio = 0.11
# Models
n_batches = 2000
learning_rates = linear_geometric_curve(n=n_batches,
starting_value=5e-4,
end_value=1e-10,
geometric_component=3. / 4,
geometric_end=5)
a_model = BasicRecurrent(
tensor_provider=the_tensor_provider,
results_path=used_base_path,
use_bow=False,
n_batches=n_batches,
batch_size=64,
learning_rate_progression=learning_rates,
recurrent_units=400,
feedforward_units=[200],
dropouts=[1],
recurrent_neuron_type=tf.nn.rnn_cell.GRUCell,
training_curve_y_limit=1000
)
# a_model = LogisticRegression(
# tensor_provider=the_tensor_provider,
# )
# a_model = MLP(
# tensor_provider=the_tensor_provider,
# )
# a_model = SVMSK(
# tensor_provider=the_tensor_provider,
# verbose=True
# )
# a_model = LogisticRegressionSK(
# tensor_provider=the_tensor_provider,
# )
# a_model = PULogisticRegressionSK(
# tensor_provider=the_tensor_provider,
# )
# Select random sentences for training and test
keys = the_tensor_provider.accessible_annotated_keys
random.shuffle(keys)
loc_split = int(len(keys) * test_ratio)
training_keys = keys[loc_split:]
test_keys = keys[:loc_split]
# Run training on a single model
single_training(
tensor_provider=the_tensor_provider,
model=a_model,
test_split=test_keys,
training_split=training_keys,
base_path=used_base_path,
split_is_keys=True
) | run_files/random_sample_train.py | import random
from pathlib import Path
import numpy as np
import tensorflow as tf
from models.PositiveLearningElkan.pu_learning import PULogisticRegressionSK
from models.baselines import LogisticRegressionSK
from models.recurrent.basic_recurrent import BasicRecurrent
from project_paths import ProjectPaths
from run_files.single_train import single_training
from util.learning_rate_utilities import linear_geometric_curve
from util.tensor_provider import TensorProvider
if __name__ == "__main__":
# Initialize tensor-provider (data-source)
the_tensor_provider = TensorProvider(verbose=True)
# Results path
used_base_path = Path(ProjectPaths.results, "single_train")
# Settings
test_ratio = 0.11
# Models
n_batches = 2000
learning_rates = linear_geometric_curve(n=n_batches,
starting_value=5e-4,
end_value=1e-10,
geometric_component=3. / 4,
geometric_end=5)
a_model = BasicRecurrent(
tensor_provider=the_tensor_provider,
results_path=used_base_path,
use_bow=False,
n_batches=n_batches,
batch_size=64,
learning_rate_progression=learning_rates,
recurrent_units=400,
feedforward_units=[200],
dropouts=[1],
recurrent_neuron_type=tf.nn.rnn_cell.GRUCell,
training_curve_y_limit=1000
)
# a_model = LogisticRegression(
# tensor_provider=the_tensor_provider,
# )
# a_model = MLP(
# tensor_provider=the_tensor_provider,
# )
# a_model = SVMSK(
# tensor_provider=the_tensor_provider,
# verbose=True
# )
# a_model = LogisticRegressionSK(
# tensor_provider=the_tensor_provider,
# )
# a_model = PULogisticRegressionSK(
# tensor_provider=the_tensor_provider,
# )
# Select random sentences for training and test
keys = the_tensor_provider.accessible_annotated_keys
random.shuffle(keys)
loc_split = int(len(keys) * test_ratio)
training_keys = keys[loc_split:]
test_keys = keys[:loc_split]
# Run training on a single model
single_training(
tensor_provider=the_tensor_provider,
model=a_model,
test_split=test_keys,
training_split=training_keys,
base_path=used_base_path,
split_is_keys=True
) | 0.563618 | 0.268538 |
import scrapy
from alleco.objects.official import Official
class braddock_b(scrapy.Spider):
name = "braddock_b"
muniName = "BRADDOCK"
muniType = "BOROUGH"
complete = True
def start_requests(self):
urls = ['http://www.braddockborough.com/council/',
'http://www.braddockborough.com/staff',
'https://www.braddockborough.com/council/chardae-jones']
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
if response.url[-1] == "s":
for quote in response.xpath("//div[contains(@class, 'row container-box-med') and contains(.//div/@class, 'it-grid-one start bl')]"):
bio = quote.xpath('div/p/text()').getall()
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="MAYOR",
name=" ".join(quote.xpath("div/h1/text()").get().split(" ")[1:3]),
phone=bio[-1],
email=bio[-3].replace(" ",""),
url=response.url)
elif response.url[-1] == "/":
for quote in response.xpath("//div[@class='med information-text']//div[@class='itg-teambox']")[1:]:
name = quote.xpath("h3/text()").get()
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="MEMBER OF COUNCIL",
name=name,
district=self._districts(name.split(" ")[-1]),
url=response.url)
elif response.url[-1] == "f":
for quote in response.xpath("//p[contains(text(), 'Tax Department Manager')]/.."):
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="TAX COLLECTOR",
name=quote.xpath("h3/text()").get(),
url=response.url)
def _districts(self, string):
#Note: In the future, figure out a better way to do this
#Because this information is not on the Braddock website,
#I am using the 2017 and 2019 election records to deduce districts
if string=="Parker": return "WARD 3"
elif string=="Berry": return "WARD 2"
elif string=="Doose": return "WARD 2"
elif string=="Dudley": return "WARD 1"
elif string=="Clark": return "WARD 3"
elif string=="Henderson": return "WARD 1"
elif string=="Scales": return "AT-LARGE"
else: return None | alleco/spiders/braddock_b.py | import scrapy
from alleco.objects.official import Official
class braddock_b(scrapy.Spider):
name = "braddock_b"
muniName = "BRADDOCK"
muniType = "BOROUGH"
complete = True
def start_requests(self):
urls = ['http://www.braddockborough.com/council/',
'http://www.braddockborough.com/staff',
'https://www.braddockborough.com/council/chardae-jones']
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
if response.url[-1] == "s":
for quote in response.xpath("//div[contains(@class, 'row container-box-med') and contains(.//div/@class, 'it-grid-one start bl')]"):
bio = quote.xpath('div/p/text()').getall()
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="MAYOR",
name=" ".join(quote.xpath("div/h1/text()").get().split(" ")[1:3]),
phone=bio[-1],
email=bio[-3].replace(" ",""),
url=response.url)
elif response.url[-1] == "/":
for quote in response.xpath("//div[@class='med information-text']//div[@class='itg-teambox']")[1:]:
name = quote.xpath("h3/text()").get()
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="MEMBER OF COUNCIL",
name=name,
district=self._districts(name.split(" ")[-1]),
url=response.url)
elif response.url[-1] == "f":
for quote in response.xpath("//p[contains(text(), 'Tax Department Manager')]/.."):
yield Official(
muniName=self.muniName,
muniType=self.muniType,
office="TAX COLLECTOR",
name=quote.xpath("h3/text()").get(),
url=response.url)
def _districts(self, string):
#Note: In the future, figure out a better way to do this
#Because this information is not on the Braddock website,
#I am using the 2017 and 2019 election records to deduce districts
if string=="Parker": return "WARD 3"
elif string=="Berry": return "WARD 2"
elif string=="Doose": return "WARD 2"
elif string=="Dudley": return "WARD 1"
elif string=="Clark": return "WARD 3"
elif string=="Henderson": return "WARD 1"
elif string=="Scales": return "AT-LARGE"
else: return None | 0.064831 | 0.140926 |
#SILENCING THE FALSE POSITIVE WARNINGS
import warnings
warnings.simplefilter('always')
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=pd.core.common.SettingWithCopyWarning)
#IMPORTING DEPENDENCIES
import tensorflow as tf
import pandas as pd
import numpy as np
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Embedding, Conv1D, GlobalMaxPooling1D, Activation
#IMPORTING DATASET
data = pd.read_csv('/content/gdrive/My Drive/Colab Notebooks/train.csv', index_col=False)
df = data
#Filling Missing Values in Data
#print(df.isna().sum())
df[['title', 'author']] = df[['title', 'author']].fillna(value = 'Missing Value')
df = df.dropna()
df['length'] = df.iloc[:,3].str.len()
#print(df.isna().sum())
df[df['length'] < 50].count()
df = df.drop(df['text'][df['length'] < 50].index, axis=0)
df_reverse = pd.DataFrame()
#Categorical to Numeric
for col_name in df.columns:
if(df[col_name].dtype == 'object'):
df[col_name]= df[col_name].astype('category')
d = dict(enumerate(df[col_name].cat.categories))
df[col_name] = df[col_name].cat.codes
df_reverse[col_name+"_code"] = df[col_name]
df_reverse[col_name] = df[col_name].map(d)
features_cols = ['id', 'title', 'author', 'text']
#FEATURES AND LABELS
X = df[features_cols]
Y = df.label
#PREPARING TRAINING DATASET AND TEST DATASET
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=1)
#DECISION TREE CLASSIFIER - UNPRUNDED TREE
from sklearn.tree import DecisionTreeClassifier
from sklearn import metrics
dtc_unpruned = DecisionTreeClassifier()
dtc_unpruned.fit(X_train, Y_train)
Y_pred_dtc_unpruned = dtc_unpruned.predict(X_test)
acc_score_dtc_unpruned = round(metrics.accuracy_score(Y_test,Y_pred_dtc_unpruned) * 100)
print("Accuracy of DecisionTreeClassifier:", acc_score_dtc_unpruned, "%")
X_test_cp = X_test
#Decoding Data - ONE TIME STEP - DO NOT REPEAT
df_reverse.set_index('title_code', inplace=False)
title_dict = df_reverse.to_dict()['title']
df_reverse.set_index('author_code', inplace=False)
author_dict = df_reverse.to_dict()['author']
df_reverse.set_index('text_code', inplace=False)
text_dict = df_reverse.to_dict()['text']
X_test_cp['title'] = X_test_cp['title'].map(title_dict)
X_test_cp['author'] = X_test_cp['author'].map(author_dict)
X_test_cp['text'] = X_test_cp['text'].map(text_dict)
X_test_cp.set_index('id', inplace=True)
#DISPLAYING DECSIONTREECLASSIFIER - DECODED - RESULTS
X_test_cp['Prediction'] = Y_pred_dtc_unpruned
X_test_cp['Prediction'].replace([0,1],['Fake News','Relaible News'],inplace=True)
pd.set_option('display.max_columns', 1000)
pd.set_option('display.max_rows', 1000)
#PREDICTION RESULTS
X_test_cp.tail()
#Visualizing DecisionTree
from sklearn.tree import export_graphviz
from sklearn.externals.six import StringIO
from IPython.display import Image
import pydotplus
dot_data = StringIO()
export_graphviz(dtc_unpruned, out_file=dot_data,
filled=True, rounded=True,
special_characters=True,feature_names = features_cols,class_names=['0','1'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_png('fakeNews.png')
Image(graph.create_png()) | .py files/decisiontreeclassifier_unpruned(fake_news_detection).py | #SILENCING THE FALSE POSITIVE WARNINGS
import warnings
warnings.simplefilter('always')
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=pd.core.common.SettingWithCopyWarning)
#IMPORTING DEPENDENCIES
import tensorflow as tf
import pandas as pd
import numpy as np
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Embedding, Conv1D, GlobalMaxPooling1D, Activation
#IMPORTING DATASET
data = pd.read_csv('/content/gdrive/My Drive/Colab Notebooks/train.csv', index_col=False)
df = data
#Filling Missing Values in Data
#print(df.isna().sum())
df[['title', 'author']] = df[['title', 'author']].fillna(value = 'Missing Value')
df = df.dropna()
df['length'] = df.iloc[:,3].str.len()
#print(df.isna().sum())
df[df['length'] < 50].count()
df = df.drop(df['text'][df['length'] < 50].index, axis=0)
df_reverse = pd.DataFrame()
#Categorical to Numeric
for col_name in df.columns:
if(df[col_name].dtype == 'object'):
df[col_name]= df[col_name].astype('category')
d = dict(enumerate(df[col_name].cat.categories))
df[col_name] = df[col_name].cat.codes
df_reverse[col_name+"_code"] = df[col_name]
df_reverse[col_name] = df[col_name].map(d)
features_cols = ['id', 'title', 'author', 'text']
#FEATURES AND LABELS
X = df[features_cols]
Y = df.label
#PREPARING TRAINING DATASET AND TEST DATASET
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=1)
#DECISION TREE CLASSIFIER - UNPRUNDED TREE
from sklearn.tree import DecisionTreeClassifier
from sklearn import metrics
dtc_unpruned = DecisionTreeClassifier()
dtc_unpruned.fit(X_train, Y_train)
Y_pred_dtc_unpruned = dtc_unpruned.predict(X_test)
acc_score_dtc_unpruned = round(metrics.accuracy_score(Y_test,Y_pred_dtc_unpruned) * 100)
print("Accuracy of DecisionTreeClassifier:", acc_score_dtc_unpruned, "%")
X_test_cp = X_test
#Decoding Data - ONE TIME STEP - DO NOT REPEAT
df_reverse.set_index('title_code', inplace=False)
title_dict = df_reverse.to_dict()['title']
df_reverse.set_index('author_code', inplace=False)
author_dict = df_reverse.to_dict()['author']
df_reverse.set_index('text_code', inplace=False)
text_dict = df_reverse.to_dict()['text']
X_test_cp['title'] = X_test_cp['title'].map(title_dict)
X_test_cp['author'] = X_test_cp['author'].map(author_dict)
X_test_cp['text'] = X_test_cp['text'].map(text_dict)
X_test_cp.set_index('id', inplace=True)
#DISPLAYING DECSIONTREECLASSIFIER - DECODED - RESULTS
X_test_cp['Prediction'] = Y_pred_dtc_unpruned
X_test_cp['Prediction'].replace([0,1],['Fake News','Relaible News'],inplace=True)
pd.set_option('display.max_columns', 1000)
pd.set_option('display.max_rows', 1000)
#PREDICTION RESULTS
X_test_cp.tail()
#Visualizing DecisionTree
from sklearn.tree import export_graphviz
from sklearn.externals.six import StringIO
from IPython.display import Image
import pydotplus
dot_data = StringIO()
export_graphviz(dtc_unpruned, out_file=dot_data,
filled=True, rounded=True,
special_characters=True,feature_names = features_cols,class_names=['0','1'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_png('fakeNews.png')
Image(graph.create_png()) | 0.357119 | 0.260754 |
import base64
import rapidjson
import logging
import asyncio
# redis pool
import aioredis
from aiohttp import web, hdrs
from .base import BaseAuthBackend
from navigator.exceptions import (
NavException,
UserDoesntExists,
InvalidAuth
)
from datetime import datetime, timedelta
from navigator.conf import (
SESSION_URL,
SESSION_TIMEOUT,
SECRET_KEY,
SESSION_PREFIX,
SESSION_KEY
)
class DjangoAuth(BaseAuthBackend):
"""Django SessionID Authentication Handler."""
redis = None
_scheme: str = "Bearer"
def configure(self, app, router):
async def _setup_redis(app):
self.redis = aioredis.from_url(
SESSION_URL,
decode_responses=True,
encoding='utf-8'
)
async def _close_redis(app):
await self.redis.close()
app.on_cleanup.append(_close_redis)
return self.redis
asyncio.get_event_loop().run_until_complete(_setup_redis(app))
# executing parent configurations
super(DjangoAuth, self).configure(app, router)
async def check_credentials(self, request):
""" Authentication and create a session."""
return True
async def get_payload(self, request):
id = None
try:
if "Authorization" in request.headers:
try:
scheme, id = request.headers.get("Authorization").strip().split(" ")
except ValueError:
raise web.HTTPForbidden(
reason="Invalid authorization Header",
)
if scheme != self._scheme:
raise web.HTTPForbidden(
reason="Invalid Session scheme",
)
elif "X-Sessionid" in request.headers:
id = request.headers.get("X-Sessionid", None)
except Exception as e:
print(e)
return None
return id
async def validate_session(self, key: str = None):
try:
print(SESSION_PREFIX)
async with await self.redis as redis:
result = await redis.get("{}:{}".format(SESSION_PREFIX, key))
print(result)
if not result:
raise Exception('Empty or non-existing Session')
data = base64.b64decode(result)
session_data = data.decode("utf-8").split(":", 1)
user = rapidjson.loads(session_data[1])
session = {
"key": key,
"session_id": session_data[0],
self.user_property: user,
}
return session
except Exception as err:
logging.debug("Django Decoding Error: {}".format(err))
raise Exception("Django Decoding Error: {}".format(err))
async def validate_user(self, login: str = None):
# get the user based on Model
search = {self.userid_attribute: login}
try:
user = await self.get_user(**search)
return user
except UserDoesntExists as err:
raise UserDoesntExists(f"User {login} doesn\'t exists")
except Exception as err:
raise Exception(err)
return None
async def authenticate(self, request):
""" Authenticate against user credentials (django session id)."""
try:
sessionid = await self.get_payload(request)
logging.debug(f"Session ID: {sessionid}")
except Exception as err:
raise NavException(err, state=400)
if not sessionid:
raise InvalidAuth(
"Auth: Invalid Credentials",
state=401
)
else:
try:
data = await self.validate_session(key=sessionid)
except Exception as err:
raise InvalidAuth(f"Invalid Session: {err!s}", state=401)
# making validation
if not data:
raise InvalidAuth("Missing User Information", state=403)
try:
u = data[self.user_property]
username = u[self.userid_attribute]
except KeyError as err:
print(err)
raise InvalidAuth(
f"Missing {self.userid_attribute} attribute: {err!s}", state=401
)
try:
user = await self.validate_user(login=username)
except UserDoesntExists as err:
raise UserDoesntExists(err)
except Exception as err:
raise NavException(err, state=500)
try:
userdata = self.get_userdata(user)
userdata["session"] = data
userdata[self.session_key_property] = sessionid
# saving user-data into request:
request['userdata'] = userdata
request[SESSION_KEY] = sessionid
payload = {
self.user_property: user[self.userid_attribute],
self.username_attribute: user[self.username_attribute],
self.userid_attribute: user[self.userid_attribute],
self.session_key_property: sessionid
}
token = self.create_jwt(
data=payload
)
return {
"token": token,
**userdata
}
except Exception as err:
print(err)
return False | navigator/auth/backends/django.py | import base64
import rapidjson
import logging
import asyncio
# redis pool
import aioredis
from aiohttp import web, hdrs
from .base import BaseAuthBackend
from navigator.exceptions import (
NavException,
UserDoesntExists,
InvalidAuth
)
from datetime import datetime, timedelta
from navigator.conf import (
SESSION_URL,
SESSION_TIMEOUT,
SECRET_KEY,
SESSION_PREFIX,
SESSION_KEY
)
class DjangoAuth(BaseAuthBackend):
"""Django SessionID Authentication Handler."""
redis = None
_scheme: str = "Bearer"
def configure(self, app, router):
async def _setup_redis(app):
self.redis = aioredis.from_url(
SESSION_URL,
decode_responses=True,
encoding='utf-8'
)
async def _close_redis(app):
await self.redis.close()
app.on_cleanup.append(_close_redis)
return self.redis
asyncio.get_event_loop().run_until_complete(_setup_redis(app))
# executing parent configurations
super(DjangoAuth, self).configure(app, router)
async def check_credentials(self, request):
""" Authentication and create a session."""
return True
async def get_payload(self, request):
id = None
try:
if "Authorization" in request.headers:
try:
scheme, id = request.headers.get("Authorization").strip().split(" ")
except ValueError:
raise web.HTTPForbidden(
reason="Invalid authorization Header",
)
if scheme != self._scheme:
raise web.HTTPForbidden(
reason="Invalid Session scheme",
)
elif "X-Sessionid" in request.headers:
id = request.headers.get("X-Sessionid", None)
except Exception as e:
print(e)
return None
return id
async def validate_session(self, key: str = None):
try:
print(SESSION_PREFIX)
async with await self.redis as redis:
result = await redis.get("{}:{}".format(SESSION_PREFIX, key))
print(result)
if not result:
raise Exception('Empty or non-existing Session')
data = base64.b64decode(result)
session_data = data.decode("utf-8").split(":", 1)
user = rapidjson.loads(session_data[1])
session = {
"key": key,
"session_id": session_data[0],
self.user_property: user,
}
return session
except Exception as err:
logging.debug("Django Decoding Error: {}".format(err))
raise Exception("Django Decoding Error: {}".format(err))
async def validate_user(self, login: str = None):
# get the user based on Model
search = {self.userid_attribute: login}
try:
user = await self.get_user(**search)
return user
except UserDoesntExists as err:
raise UserDoesntExists(f"User {login} doesn\'t exists")
except Exception as err:
raise Exception(err)
return None
async def authenticate(self, request):
""" Authenticate against user credentials (django session id)."""
try:
sessionid = await self.get_payload(request)
logging.debug(f"Session ID: {sessionid}")
except Exception as err:
raise NavException(err, state=400)
if not sessionid:
raise InvalidAuth(
"Auth: Invalid Credentials",
state=401
)
else:
try:
data = await self.validate_session(key=sessionid)
except Exception as err:
raise InvalidAuth(f"Invalid Session: {err!s}", state=401)
# making validation
if not data:
raise InvalidAuth("Missing User Information", state=403)
try:
u = data[self.user_property]
username = u[self.userid_attribute]
except KeyError as err:
print(err)
raise InvalidAuth(
f"Missing {self.userid_attribute} attribute: {err!s}", state=401
)
try:
user = await self.validate_user(login=username)
except UserDoesntExists as err:
raise UserDoesntExists(err)
except Exception as err:
raise NavException(err, state=500)
try:
userdata = self.get_userdata(user)
userdata["session"] = data
userdata[self.session_key_property] = sessionid
# saving user-data into request:
request['userdata'] = userdata
request[SESSION_KEY] = sessionid
payload = {
self.user_property: user[self.userid_attribute],
self.username_attribute: user[self.username_attribute],
self.userid_attribute: user[self.userid_attribute],
self.session_key_property: sessionid
}
token = self.create_jwt(
data=payload
)
return {
"token": token,
**userdata
}
except Exception as err:
print(err)
return False | 0.475605 | 0.080683 |
import os
import json
import iso8601
from hashlib import sha256
import requests
from requests.compat import urlencode
PYBOSSA_API_KEY = os.environ.get("PYBOSSA_API_KEY")
SCISTARTER_API_KEY = os.environ.get("SCISTARTER_API_KEY")
def retrieve_email(user_id):
"""
Input: A user_id mapping to some User Profile in Public Editor
Output: The email that belongs to the user with the userid input
"""
# Construct and call a GET request to public editor to get email given id
url = f"https://pe.goodlylabs.org/api/user/{user_id}?api_key={PYBOSSA_API_KEY}"
response = requests.get(url, headers={"Content-Type": "application/json"})
# error handling
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
data = response.json()
return data["email_addr"]
def retrieve_taskrun(taskrun_id):
"""
Input: A taskrun_id mapping to some Taskrun in Public Editor
Output: A json representing the data of a taskrun instance
"""
url = f"https://pe.goodlylabs.org/api/taskrun/{taskrun_id}?api_key={PYBOSSA_API_KEY}"
response = requests.get(url, headers={"Content-Type": "application/json"})
# error handling
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
data = response.json()
return data
def record_participation(taskrun_id, project_slug):
"""
Input: A userid mapping to some User Profile in Public Editor, A project_slug representing a unique project on SciStarter
Action:
Retrieves the email associated with userid and hashes the email.
Record participation for the specified user in the specified project
This will appear to succeed, regardless of whether the user is
actually a SciStarter user or not. However, in that case this API
call is a no-op. It only reports an error if the request is
incorrect in some way.
If the email address does *not* belong to a SciStarter user, all
we've received is an opaque hash value, which preserves the user's
privacy; we have no way of reversing the hashing process to
discover the email.
The project_slug parameter should contain the textual unique
identifier of the project. It is easily accesible from the project
URL. In the URL https://scistarter.org/airborne-walrus-capture the
slug is the string airborne-walrus-capture
"""
# retrieve necessary data from a specific taskrun
taskrun_json = retrieve_taskrun(taskrun_id)
# calculate the total seconds user spent on task
pybossa_created = iso8601.parse_date(taskrun_json.get('created'))
pybossa_finish_time = iso8601.parse_date(taskrun_json.get('finish_time'))
elapsed_time = pybossa_finish_time - pybossa_created
total_seconds = int(elapsed_time.total_seconds())
# retrieve email from user_id and hash the email
email = retrieve_email(taskrun_json.get('user_id'))
hashed = sha256(email.encode("utf8")).hexdigest()
# construct parameters for POST request to SciStarter
url = "https://scistarter.org/api/participation/hashed/" + \
project_slug + "?key=" + SCISTARTER_API_KEY
data = {
"hashed": hashed,
"type": "classification", # other options: 'collection', 'signup'
"duration": total_seconds, # Seconds the user spent participating, or an estimate
}
response = requests.post(url=url, data=data)
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
return response.json()
if __name__ == "__main__":
print(record_participation(input("TaskRun ID: "), input("Project slug: "))) | vdashboard/scistarter.py | import os
import json
import iso8601
from hashlib import sha256
import requests
from requests.compat import urlencode
PYBOSSA_API_KEY = os.environ.get("PYBOSSA_API_KEY")
SCISTARTER_API_KEY = os.environ.get("SCISTARTER_API_KEY")
def retrieve_email(user_id):
"""
Input: A user_id mapping to some User Profile in Public Editor
Output: The email that belongs to the user with the userid input
"""
# Construct and call a GET request to public editor to get email given id
url = f"https://pe.goodlylabs.org/api/user/{user_id}?api_key={PYBOSSA_API_KEY}"
response = requests.get(url, headers={"Content-Type": "application/json"})
# error handling
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
data = response.json()
return data["email_addr"]
def retrieve_taskrun(taskrun_id):
"""
Input: A taskrun_id mapping to some Taskrun in Public Editor
Output: A json representing the data of a taskrun instance
"""
url = f"https://pe.goodlylabs.org/api/taskrun/{taskrun_id}?api_key={PYBOSSA_API_KEY}"
response = requests.get(url, headers={"Content-Type": "application/json"})
# error handling
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
data = response.json()
return data
def record_participation(taskrun_id, project_slug):
"""
Input: A userid mapping to some User Profile in Public Editor, A project_slug representing a unique project on SciStarter
Action:
Retrieves the email associated with userid and hashes the email.
Record participation for the specified user in the specified project
This will appear to succeed, regardless of whether the user is
actually a SciStarter user or not. However, in that case this API
call is a no-op. It only reports an error if the request is
incorrect in some way.
If the email address does *not* belong to a SciStarter user, all
we've received is an opaque hash value, which preserves the user's
privacy; we have no way of reversing the hashing process to
discover the email.
The project_slug parameter should contain the textual unique
identifier of the project. It is easily accesible from the project
URL. In the URL https://scistarter.org/airborne-walrus-capture the
slug is the string airborne-walrus-capture
"""
# retrieve necessary data from a specific taskrun
taskrun_json = retrieve_taskrun(taskrun_id)
# calculate the total seconds user spent on task
pybossa_created = iso8601.parse_date(taskrun_json.get('created'))
pybossa_finish_time = iso8601.parse_date(taskrun_json.get('finish_time'))
elapsed_time = pybossa_finish_time - pybossa_created
total_seconds = int(elapsed_time.total_seconds())
# retrieve email from user_id and hash the email
email = retrieve_email(taskrun_json.get('user_id'))
hashed = sha256(email.encode("utf8")).hexdigest()
# construct parameters for POST request to SciStarter
url = "https://scistarter.org/api/participation/hashed/" + \
project_slug + "?key=" + SCISTARTER_API_KEY
data = {
"hashed": hashed,
"type": "classification", # other options: 'collection', 'signup'
"duration": total_seconds, # Seconds the user spent participating, or an estimate
}
response = requests.post(url=url, data=data)
if response.status_code != 200:
raise Exception(response.status_code, response.reason)
return response.json()
if __name__ == "__main__":
print(record_participation(input("TaskRun ID: "), input("Project slug: "))) | 0.588889 | 0.171651 |
import django.db.models.deletion
from django.conf import settings
from django.db import migrations
from django.db import models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
("contenttypes", "0002_remove_content_type_name"),
("checkerapp", "0011_auto_20200702_0615"),
]
operations = [
migrations.CreateModel(
name="AlertPluginUserData",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("sent_at", models.DateTimeField(auto_now_add=True)),
(
"alert_receiver",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
related_name="alert_receiver",
to=settings.AUTH_USER_MODEL,
),
),
(
"check_obj",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to="checkerapp.BaseCheck",
),
),
(
"polymorphic_ctype",
models.ForeignKey(
editable=False,
null=True,
on_delete=django.db.models.deletion.CASCADE,
related_name="polymorphic_checkerapp.alertpluginuserdata_set+",
to="contenttypes.ContentType",
),
),
],
options={"abstract": False, "base_manager_name": "objects"},
),
migrations.CreateModel(
name="AlertPlugin",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("title", models.CharField(editable=False, max_length=30, unique=True)),
("enabled", models.BooleanField(default=True)),
(
"polymorphic_ctype",
models.ForeignKey(
editable=False,
null=True,
on_delete=django.db.models.deletion.CASCADE,
related_name="polymorphic_checkerapp.alertplugin_set+",
to="contenttypes.ContentType",
),
),
],
options={"abstract": False, "base_manager_name": "objects"},
),
] | checkerapp/migrations/0012_alertplugin_alertpluginuserdata.py | import django.db.models.deletion
from django.conf import settings
from django.db import migrations
from django.db import models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
("contenttypes", "0002_remove_content_type_name"),
("checkerapp", "0011_auto_20200702_0615"),
]
operations = [
migrations.CreateModel(
name="AlertPluginUserData",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("sent_at", models.DateTimeField(auto_now_add=True)),
(
"alert_receiver",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
related_name="alert_receiver",
to=settings.AUTH_USER_MODEL,
),
),
(
"check_obj",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to="checkerapp.BaseCheck",
),
),
(
"polymorphic_ctype",
models.ForeignKey(
editable=False,
null=True,
on_delete=django.db.models.deletion.CASCADE,
related_name="polymorphic_checkerapp.alertpluginuserdata_set+",
to="contenttypes.ContentType",
),
),
],
options={"abstract": False, "base_manager_name": "objects"},
),
migrations.CreateModel(
name="AlertPlugin",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("title", models.CharField(editable=False, max_length=30, unique=True)),
("enabled", models.BooleanField(default=True)),
(
"polymorphic_ctype",
models.ForeignKey(
editable=False,
null=True,
on_delete=django.db.models.deletion.CASCADE,
related_name="polymorphic_checkerapp.alertplugin_set+",
to="contenttypes.ContentType",
),
),
],
options={"abstract": False, "base_manager_name": "objects"},
),
] | 0.426799 | 0.124266 |
import datetime
import json
import logging
from decimal import Decimal
from typing import Generator, Tuple
import boto3
from botocore.config import Config
from igata import settings
logger = logging.getLogger("cliexecutor")
TEN_SECONDS = 10
config = Config(connect_timeout=TEN_SECONDS, retries={"max_attempts": 5})
DYNAMODB = boto3.resource("dynamodb", config=config, region_name=settings.AWS_REGION, endpoint_url=settings.DYNAMODB_ENDPOINT)
def update_item(item: dict, tablename: str) -> dict:
"""
Update the given item entry in the Dynamodb REQUESTS table
item is expected to have the following keys:
- REQUESTS_TABLE_HASHKEY_KEYNAME
- RESULTS_TABLE_STATE_FIELDNAME
"""
table = DYNAMODB.Table(tablename)
logger.info(f"Updating item in Table({tablename})...")
logger.debug(f"item: {item}")
processed_timestamp_utc = int(datetime.datetime.now(datetime.timezone.utc).timestamp())
try:
# Assure that updated `errors` field is not None
errors_field_value = "[]"
if "errors" in item and item["errors"] is not None:
errors_field_value = item["errors"]
logger.info(f"errors={errors_field_value}")
response = table.update_item(
Key={settings.DYNAMODB_REQUESTS_TABLE_HASHKEY_KEYNAME: item[settings.DYNAMODB_REQUESTS_TABLE_HASHKEY_KEYNAME]},
UpdateExpression=(
# should be REQUESTS_TABLE_RESULTS_KEYNAME
"SET #s = :predictor_status, #r = :result_s3_uris, #e = :errors, #u = :updated_timestamp, #c = :completed_timestamp"
),
ExpressionAttributeNames={
"#s": "predictor_status", # settings.DYNAMODB_RESULTS_TABLE_STATE_FIELDNAME,
"#u": "updated_timestamp", # settings.DYNAMODB_REQUESTS_TABLE_RESULTS_KEYNAME,
"#c": "completed_timestamp",
"#r": "result_s3_uris",
"#e": "errors",
},
ExpressionAttributeValues={
":predictor_status": item[settings.DYNAMODB_RESULTS_TABLE_STATE_FIELDNAME],
":result_s3_uris": item["result_s3_uris"],
":errors": errors_field_value,
":updated_timestamp": item.get("updated_timestamp", processed_timestamp_utc),
":completed_timestamp": item.get("completed_timestamp", processed_timestamp_utc),
},
)
except Exception as e:
logger.exception(e)
logger.error(f"unable to put_item() to table: {tablename}")
response = {}
return response
def get_nested_keys(record: dict) -> Generator[str, None, None]:
"""get all keys in a dictionary that contains nested mappings/elements"""
for k, v in record.items():
if isinstance(v, (list, tuple, dict)):
yield k
def check_and_convert(value, precision=settings.DYNAMODB_DECIMAL_PRECISION_DIGITS):
"""convert float to decimal for dynamodb"""
return value if not isinstance(value, float) else round(Decimal(value), precision)
def prepare_record(record: dict) -> Tuple[dict, dict]:
"""
Convert record data for DynamoDB insertion
record: updated record with json dumps fields for nested record values
original_nested_data: untouched nested key record data
"""
original_nested_data = {} # used for processing the results into the results table
nested_keys = get_nested_keys(record)
if not nested_keys:
logger.warning(f"No nested_keys found for record: {record}")
else:
for nested_key in nested_keys:
# jsonize and byteify nested items
value = record[nested_key]
original_nested_data[nested_key] = value # keep original value for later processing
value_json_bytes = json.dumps(value)
record[nested_key] = value_json_bytes
non_nested_keys = set(record.keys()) - set(nested_keys)
for k in non_nested_keys:
v = record[k]
record[k] = check_and_convert(v)
return record, original_nested_data | igata/handlers/aws/output/utils.py | import datetime
import json
import logging
from decimal import Decimal
from typing import Generator, Tuple
import boto3
from botocore.config import Config
from igata import settings
logger = logging.getLogger("cliexecutor")
TEN_SECONDS = 10
config = Config(connect_timeout=TEN_SECONDS, retries={"max_attempts": 5})
DYNAMODB = boto3.resource("dynamodb", config=config, region_name=settings.AWS_REGION, endpoint_url=settings.DYNAMODB_ENDPOINT)
def update_item(item: dict, tablename: str) -> dict:
"""
Update the given item entry in the Dynamodb REQUESTS table
item is expected to have the following keys:
- REQUESTS_TABLE_HASHKEY_KEYNAME
- RESULTS_TABLE_STATE_FIELDNAME
"""
table = DYNAMODB.Table(tablename)
logger.info(f"Updating item in Table({tablename})...")
logger.debug(f"item: {item}")
processed_timestamp_utc = int(datetime.datetime.now(datetime.timezone.utc).timestamp())
try:
# Assure that updated `errors` field is not None
errors_field_value = "[]"
if "errors" in item and item["errors"] is not None:
errors_field_value = item["errors"]
logger.info(f"errors={errors_field_value}")
response = table.update_item(
Key={settings.DYNAMODB_REQUESTS_TABLE_HASHKEY_KEYNAME: item[settings.DYNAMODB_REQUESTS_TABLE_HASHKEY_KEYNAME]},
UpdateExpression=(
# should be REQUESTS_TABLE_RESULTS_KEYNAME
"SET #s = :predictor_status, #r = :result_s3_uris, #e = :errors, #u = :updated_timestamp, #c = :completed_timestamp"
),
ExpressionAttributeNames={
"#s": "predictor_status", # settings.DYNAMODB_RESULTS_TABLE_STATE_FIELDNAME,
"#u": "updated_timestamp", # settings.DYNAMODB_REQUESTS_TABLE_RESULTS_KEYNAME,
"#c": "completed_timestamp",
"#r": "result_s3_uris",
"#e": "errors",
},
ExpressionAttributeValues={
":predictor_status": item[settings.DYNAMODB_RESULTS_TABLE_STATE_FIELDNAME],
":result_s3_uris": item["result_s3_uris"],
":errors": errors_field_value,
":updated_timestamp": item.get("updated_timestamp", processed_timestamp_utc),
":completed_timestamp": item.get("completed_timestamp", processed_timestamp_utc),
},
)
except Exception as e:
logger.exception(e)
logger.error(f"unable to put_item() to table: {tablename}")
response = {}
return response
def get_nested_keys(record: dict) -> Generator[str, None, None]:
"""get all keys in a dictionary that contains nested mappings/elements"""
for k, v in record.items():
if isinstance(v, (list, tuple, dict)):
yield k
def check_and_convert(value, precision=settings.DYNAMODB_DECIMAL_PRECISION_DIGITS):
"""convert float to decimal for dynamodb"""
return value if not isinstance(value, float) else round(Decimal(value), precision)
def prepare_record(record: dict) -> Tuple[dict, dict]:
"""
Convert record data for DynamoDB insertion
record: updated record with json dumps fields for nested record values
original_nested_data: untouched nested key record data
"""
original_nested_data = {} # used for processing the results into the results table
nested_keys = get_nested_keys(record)
if not nested_keys:
logger.warning(f"No nested_keys found for record: {record}")
else:
for nested_key in nested_keys:
# jsonize and byteify nested items
value = record[nested_key]
original_nested_data[nested_key] = value # keep original value for later processing
value_json_bytes = json.dumps(value)
record[nested_key] = value_json_bytes
non_nested_keys = set(record.keys()) - set(nested_keys)
for k in non_nested_keys:
v = record[k]
record[k] = check_and_convert(v)
return record, original_nested_data | 0.658966 | 0.291731 |
import json
import requests
from config import Config, CAR0, CAR1, CAR2, CAR3 #pylint: disable=unused-import
class Coordinator:
"""
Provides all communication between the Starting Gate and the Race Coordinator
The local race controller communicates with the Race Coordinator at via 4 interactions:
* register: upon startup, if multi-track racing is selected, the local track registers
with the Race Coordinator providing the track_name, number of lanes, and
car icon selections.
* deregister: at shut-down or if the user switches to single-track racing, the local track
removes its registration with the Race Coordinator.
* start: Indicates that the local track is ready to start a race. The Race
Coordinator will only respond to the request once all tracks are ready
* results: The local track reports its results and awaits the global results.
"""
# PUBLIC:
def __init__(self, config):
self.config = config
self.register_url = "http://{}:{}/register".format(config.coord_host, config.coord_port)
self.start_url = "http://{}:{}/start".format(config.coord_host, config.coord_port)
self.results_url = "http://{}:{}/results".format(config.coord_host, config.coord_port)
self.deregister_url = "http://{}:{}/deregister".format(config.coord_host, config.coord_port)
def register(self):
"""
Register with the race coordinator.
See Coordinator/drr_server.js for detail of the json request/response format
"""
headers = {'Content-Type': 'application/json'}
registration = {}
registration['circuit'] = self.config.circuit
registration['trackName'] = self.config.track_name
registration['numLanes'] = self.config.num_lanes
registration['carIcons'] = self.config.car_icons
json_string = json.dumps(registration).encode('utf-8')
print("register: ", json_string)
response = requests.post(self.register_url, data=json_string, headers=headers)
print("response=", response)
reply = response.json()
print("reply=", reply)
remote = reply['remoteRegistrations'][0]
self.config.ip_address = reply['ip']
self.config.remote_track_name = remote['trackName']
self.config.remote_num_lanes = remote['numLanes']
self.config.remote_car_icons = remote['carIcons']
def deregister(self):
"""
Deregister from the race coordinator, thus leaving the circuit
"""
print("deregister: ")
response = requests.post(self.deregister_url, data="")
print("response=", response)
def start_race(self):
"""
Send message to coordinator that the local track is ready for the start of the
race. The GET request only returns when all tracks in the circuit are ready.
"""
print("start_race: GET ", self.start_url)
response = requests.get(self.start_url)
print("response=", response)
def results(self, local_results):
"""
Send local race results to the race coordintor and collect circuit-wide results
in the response.
"""
headers = {'Content-Type': 'application/json'}
json_string = json.dumps(local_results).encode('utf-8')
print("register: ", json_string)
response = requests.post(self.results_url, data=json_string, headers=headers)
print("response=", response)
print("response.text=", response.text)
result_string = response.text
return result_string
# PRIVATE:
if __name__ == '__main__':
def do_main():
#pylint: disable=attribute-defined-outside-init, no-member
"""
At some point I should write legitimate unit tests. But for now, I just exercise
some basic functionality if the class is invoked as the Python main.
"""
main_config = Config("/home/tom/Raceway/StartingGate/config/starting_gate.json")
main_config.car_icons[CAR1] = "white"
main_config.car_icons[CAR2] = "police"
main_coord = Coordinator(main_config)
main_coord.register()
main_coord.start_race()
do_main()
# vim: expandtab sw=4 | StartingGate/coordinator.py | import json
import requests
from config import Config, CAR0, CAR1, CAR2, CAR3 #pylint: disable=unused-import
class Coordinator:
"""
Provides all communication between the Starting Gate and the Race Coordinator
The local race controller communicates with the Race Coordinator at via 4 interactions:
* register: upon startup, if multi-track racing is selected, the local track registers
with the Race Coordinator providing the track_name, number of lanes, and
car icon selections.
* deregister: at shut-down or if the user switches to single-track racing, the local track
removes its registration with the Race Coordinator.
* start: Indicates that the local track is ready to start a race. The Race
Coordinator will only respond to the request once all tracks are ready
* results: The local track reports its results and awaits the global results.
"""
# PUBLIC:
def __init__(self, config):
self.config = config
self.register_url = "http://{}:{}/register".format(config.coord_host, config.coord_port)
self.start_url = "http://{}:{}/start".format(config.coord_host, config.coord_port)
self.results_url = "http://{}:{}/results".format(config.coord_host, config.coord_port)
self.deregister_url = "http://{}:{}/deregister".format(config.coord_host, config.coord_port)
def register(self):
"""
Register with the race coordinator.
See Coordinator/drr_server.js for detail of the json request/response format
"""
headers = {'Content-Type': 'application/json'}
registration = {}
registration['circuit'] = self.config.circuit
registration['trackName'] = self.config.track_name
registration['numLanes'] = self.config.num_lanes
registration['carIcons'] = self.config.car_icons
json_string = json.dumps(registration).encode('utf-8')
print("register: ", json_string)
response = requests.post(self.register_url, data=json_string, headers=headers)
print("response=", response)
reply = response.json()
print("reply=", reply)
remote = reply['remoteRegistrations'][0]
self.config.ip_address = reply['ip']
self.config.remote_track_name = remote['trackName']
self.config.remote_num_lanes = remote['numLanes']
self.config.remote_car_icons = remote['carIcons']
def deregister(self):
"""
Deregister from the race coordinator, thus leaving the circuit
"""
print("deregister: ")
response = requests.post(self.deregister_url, data="")
print("response=", response)
def start_race(self):
"""
Send message to coordinator that the local track is ready for the start of the
race. The GET request only returns when all tracks in the circuit are ready.
"""
print("start_race: GET ", self.start_url)
response = requests.get(self.start_url)
print("response=", response)
def results(self, local_results):
"""
Send local race results to the race coordintor and collect circuit-wide results
in the response.
"""
headers = {'Content-Type': 'application/json'}
json_string = json.dumps(local_results).encode('utf-8')
print("register: ", json_string)
response = requests.post(self.results_url, data=json_string, headers=headers)
print("response=", response)
print("response.text=", response.text)
result_string = response.text
return result_string
# PRIVATE:
if __name__ == '__main__':
def do_main():
#pylint: disable=attribute-defined-outside-init, no-member
"""
At some point I should write legitimate unit tests. But for now, I just exercise
some basic functionality if the class is invoked as the Python main.
"""
main_config = Config("/home/tom/Raceway/StartingGate/config/starting_gate.json")
main_config.car_icons[CAR1] = "white"
main_config.car_icons[CAR2] = "police"
main_coord = Coordinator(main_config)
main_coord.register()
main_coord.start_race()
do_main()
# vim: expandtab sw=4 | 0.606265 | 0.294262 |
from django.conf import settings
from django.contrib.auth import get_backends
from django.utils.functional import cached_property
from social_core.backends.base import BaseAuth
class BackendMetaMetaclass(type):
def __new__(mcs, name, bases, attrs):
cls = type.__new__(mcs, name, bases, attrs)
if cls.backend_id:
cls.registry[cls.backend_id] = cls()
return cls
class BackendMeta(metaclass=BackendMetaMetaclass):
registry = {}
backend_id = None
@classmethod
def wrap(cls, user_social_auth):
return type(cls.registry.get(user_social_auth.provider))(user_social_auth)
def __init__(self, user_social_auth=None):
self.user_social_auth = user_social_auth
@property
def username(self):
return self.user_social_auth.uid
@property
def provider(self):
return self.user_social_auth.provider
@property
def id(self):
return self.user_social_auth.id
@cached_property
def enabled(self):
return any(isinstance(b, BaseAuth) and b.name == self.backend_id and all(b.get_key_and_secret())
for b in get_backends())
@property
def show(self):
return self.enabled
@property
def profile_url(self):
return None
class TwitterBackendMeta(BackendMeta):
backend_id = 'twitter'
name = 'Twitter'
font_icon = 'fab fa-twitter'
@property
def username(self):
return self.user_social_auth.extra_data['access_token']['screen_name']
@property
def profile_url(self):
return 'https://twitter.com/' + self.username
class GoogleOAuth2BackendMeta(BackendMeta):
backend_id = 'google-oauth2'
name = 'Google'
font_icon = 'fab fa-google'
class ORCIDBackendMeta(BackendMeta):
backend_id = 'orcid'
name = 'ORCID'
font_icon = 'ai ai-orcid'
class FacebookBackendMeta(BackendMeta):
backend_id = 'facebook'
name = 'Facebook'
font_icon = 'fab fa-facebook'
class FigshareBackendMeta(BackendMeta):
backend_id = 'figshare'
name = 'Figshare'
font_icon = 'ai ai-figshare'
class LinkedinBackendMeta(BackendMeta):
backend_id = 'linkedin-oauth2'
name = 'LinkedIn'
font_icon = 'fab fa-linkedin'
@property
def username(self):
return None
class GithubBackendMeta(BackendMeta):
backend_id = 'github'
name = 'GitHub'
font_icon = 'fab fa-github'
@property
def username(self):
return self.user_social_auth.extra_data['login']
@property
def profile_url(self):
return 'https://github.com/' + self.username | forsta_auth/backend_meta.py | from django.conf import settings
from django.contrib.auth import get_backends
from django.utils.functional import cached_property
from social_core.backends.base import BaseAuth
class BackendMetaMetaclass(type):
def __new__(mcs, name, bases, attrs):
cls = type.__new__(mcs, name, bases, attrs)
if cls.backend_id:
cls.registry[cls.backend_id] = cls()
return cls
class BackendMeta(metaclass=BackendMetaMetaclass):
registry = {}
backend_id = None
@classmethod
def wrap(cls, user_social_auth):
return type(cls.registry.get(user_social_auth.provider))(user_social_auth)
def __init__(self, user_social_auth=None):
self.user_social_auth = user_social_auth
@property
def username(self):
return self.user_social_auth.uid
@property
def provider(self):
return self.user_social_auth.provider
@property
def id(self):
return self.user_social_auth.id
@cached_property
def enabled(self):
return any(isinstance(b, BaseAuth) and b.name == self.backend_id and all(b.get_key_and_secret())
for b in get_backends())
@property
def show(self):
return self.enabled
@property
def profile_url(self):
return None
class TwitterBackendMeta(BackendMeta):
backend_id = 'twitter'
name = 'Twitter'
font_icon = 'fab fa-twitter'
@property
def username(self):
return self.user_social_auth.extra_data['access_token']['screen_name']
@property
def profile_url(self):
return 'https://twitter.com/' + self.username
class GoogleOAuth2BackendMeta(BackendMeta):
backend_id = 'google-oauth2'
name = 'Google'
font_icon = 'fab fa-google'
class ORCIDBackendMeta(BackendMeta):
backend_id = 'orcid'
name = 'ORCID'
font_icon = 'ai ai-orcid'
class FacebookBackendMeta(BackendMeta):
backend_id = 'facebook'
name = 'Facebook'
font_icon = 'fab fa-facebook'
class FigshareBackendMeta(BackendMeta):
backend_id = 'figshare'
name = 'Figshare'
font_icon = 'ai ai-figshare'
class LinkedinBackendMeta(BackendMeta):
backend_id = 'linkedin-oauth2'
name = 'LinkedIn'
font_icon = 'fab fa-linkedin'
@property
def username(self):
return None
class GithubBackendMeta(BackendMeta):
backend_id = 'github'
name = 'GitHub'
font_icon = 'fab fa-github'
@property
def username(self):
return self.user_social_auth.extra_data['login']
@property
def profile_url(self):
return 'https://github.com/' + self.username | 0.554832 | 0.070977 |
import pandas as pd
TIME = {
'a': 3,
'b': 5,
'c': 2,
'd': 4,
'e': 3,
'f': 1,
'g': 4,
'h': 3,
'i': 3,
'j': 2,
'k': 5
}
# Функция формирования таблицы.
def create_table(data_, id_):
with pd.option_context('display.width', None):
table = pd.DataFrame(data_, index=id_)
print(table)
# Парсер файла с исходными данными.
def parse_file(file_):
counter_ = -1
tasks_ = {}
for line in file_:
parsed_line = line.split(',')
counter_ += 1
for i in range(len(parsed_line)):
tasks_['task' + str(parsed_line[0])] = dict()
tasks_['task' + str(parsed_line[0])]['id'] = parsed_line[0]
tasks_['task' + str(parsed_line[0])]['name'] = parsed_line[0]
tasks_['task' + str(parsed_line[0])]['duration'] = parsed_line[1]
if parsed_line[2] != "\n":
tasks_['task' + str(parsed_line[0])]['dependencies'] = parsed_line[2].strip().split(';')
else:
tasks_['task' + str(parsed_line[0])]['dependencies'] = ['-1']
tasks_['task' + str(parsed_line[0])]['e_s'] = 0
tasks_['task' + str(parsed_line[0])]['e_f'] = 0
tasks_['task' + str(parsed_line[0])]['l_s'] = 0
tasks_['task' + str(parsed_line[0])]['l_f'] = 0
tasks_['task' + str(parsed_line[0])]['f'] = 0
tasks_['task' + str(parsed_line[0])]['isCritical'] = False
return tasks_
def forward(__data):
for forward_bypass in __data:
# Если это первая задача.
if '-1' in __data[forward_bypass]['dependencies']:
__data[forward_bypass]['e_s'] = 0
__data[forward_bypass]['e_f'] = (__data[forward_bypass]['duration'])
else:
for key in __data.keys():
for dependence in __data[key]['dependencies']:
# Если у задачи есть одна предшествующая задача.
if dependence != '-1' and len(__data[key]['dependencies']) == 1:
__data[key]['e_s'] = int(__data['task' + dependence]['e_f'])
__data[key]['e_f'] = int(__data[key]['e_s']) + int(__data[key]['duration'])
# Если у задачи есть более одной предшествующей задачи.
elif dependence != '-1':
if int(__data['task' + dependence]['e_f']) > int(__data[key]['e_s']):
__data[key]['e_s'] = int(__data['task' + dependence]['e_f'])
__data[key]['e_f'] = int(__data[key]['e_s']) + int(__data[key]['duration'])
return __data
def backward(data__, tasks):
for backward_bypass in data__:
# Если задача последняя.
if data__.index(backward_bypass) == 0:
tasks[backward_bypass]['l_f'] = tasks[backward_bypass]['e_f']
tasks[backward_bypass]['l_s'] = tasks[backward_bypass]['e_s']
for dependence in tasks[backward_bypass]['dependencies']:
# Если задача не последняя.
if dependence != '-1':
if tasks['task' + dependence]['l_f'] == 0:
tasks['task' + dependence]['l_f'] = int(tasks[backward_bypass]['l_s'])
tasks['task' + dependence]['l_s'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['duration'])
tasks['task' + dependence]['f'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['e_f'])
if int(tasks['task' + dependence]['l_f']) > int(tasks[backward_bypass]['l_s']):
tasks['task' + dependence]['l_f'] = int(tasks[backward_bypass]['l_s'])
tasks['task' + dependence]['l_s'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['duration'])
tasks['task' + dependence]['f'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['e_f'])
return tasks
if __name__ == '__main__':
file = open('input.txt')
tasks = parse_file(file)
# Прямой проход.
tasks = forward(tasks)
# Копируем и переворачиваем tasks.
array1 = []
for task in tasks.keys():
array1.append(task)
array2 = array1[:]
array2.reverse()
# Обратный проход.
tasks = backward(array2, tasks)
ID = []
data = {
'Длительность задачи': [],
'Раннее начало': [],
'Раннее окончание': [],
'Позднее начало': [],
'Позднее окончание': [],
'Полный резерв': [],
'Критический путь': []
}
for task in tasks:
ID.append(tasks[task]['id'])
data['Длительность задачи'].append(tasks[task]['duration'])
data['Раннее начало'].append(tasks[task]['e_s'])
data['Раннее окончание'].append(tasks[task]['e_f'])
data['Позднее начало'].append((tasks[task]['l_s']))
data['Позднее окончание'].append((tasks[task]['l_f']))
data['Полный резерв'].append((tasks[task]['f']))
data['Критический путь'].append(tasks[task]['f'] == 0)
create_table(data, ID)
print('\nДлина критического пути:', tasks['taskstop']['l_s']) | lab7/main.py |
import pandas as pd
TIME = {
'a': 3,
'b': 5,
'c': 2,
'd': 4,
'e': 3,
'f': 1,
'g': 4,
'h': 3,
'i': 3,
'j': 2,
'k': 5
}
# Функция формирования таблицы.
def create_table(data_, id_):
with pd.option_context('display.width', None):
table = pd.DataFrame(data_, index=id_)
print(table)
# Парсер файла с исходными данными.
def parse_file(file_):
counter_ = -1
tasks_ = {}
for line in file_:
parsed_line = line.split(',')
counter_ += 1
for i in range(len(parsed_line)):
tasks_['task' + str(parsed_line[0])] = dict()
tasks_['task' + str(parsed_line[0])]['id'] = parsed_line[0]
tasks_['task' + str(parsed_line[0])]['name'] = parsed_line[0]
tasks_['task' + str(parsed_line[0])]['duration'] = parsed_line[1]
if parsed_line[2] != "\n":
tasks_['task' + str(parsed_line[0])]['dependencies'] = parsed_line[2].strip().split(';')
else:
tasks_['task' + str(parsed_line[0])]['dependencies'] = ['-1']
tasks_['task' + str(parsed_line[0])]['e_s'] = 0
tasks_['task' + str(parsed_line[0])]['e_f'] = 0
tasks_['task' + str(parsed_line[0])]['l_s'] = 0
tasks_['task' + str(parsed_line[0])]['l_f'] = 0
tasks_['task' + str(parsed_line[0])]['f'] = 0
tasks_['task' + str(parsed_line[0])]['isCritical'] = False
return tasks_
def forward(__data):
for forward_bypass in __data:
# Если это первая задача.
if '-1' in __data[forward_bypass]['dependencies']:
__data[forward_bypass]['e_s'] = 0
__data[forward_bypass]['e_f'] = (__data[forward_bypass]['duration'])
else:
for key in __data.keys():
for dependence in __data[key]['dependencies']:
# Если у задачи есть одна предшествующая задача.
if dependence != '-1' and len(__data[key]['dependencies']) == 1:
__data[key]['e_s'] = int(__data['task' + dependence]['e_f'])
__data[key]['e_f'] = int(__data[key]['e_s']) + int(__data[key]['duration'])
# Если у задачи есть более одной предшествующей задачи.
elif dependence != '-1':
if int(__data['task' + dependence]['e_f']) > int(__data[key]['e_s']):
__data[key]['e_s'] = int(__data['task' + dependence]['e_f'])
__data[key]['e_f'] = int(__data[key]['e_s']) + int(__data[key]['duration'])
return __data
def backward(data__, tasks):
for backward_bypass in data__:
# Если задача последняя.
if data__.index(backward_bypass) == 0:
tasks[backward_bypass]['l_f'] = tasks[backward_bypass]['e_f']
tasks[backward_bypass]['l_s'] = tasks[backward_bypass]['e_s']
for dependence in tasks[backward_bypass]['dependencies']:
# Если задача не последняя.
if dependence != '-1':
if tasks['task' + dependence]['l_f'] == 0:
tasks['task' + dependence]['l_f'] = int(tasks[backward_bypass]['l_s'])
tasks['task' + dependence]['l_s'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['duration'])
tasks['task' + dependence]['f'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['e_f'])
if int(tasks['task' + dependence]['l_f']) > int(tasks[backward_bypass]['l_s']):
tasks['task' + dependence]['l_f'] = int(tasks[backward_bypass]['l_s'])
tasks['task' + dependence]['l_s'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['duration'])
tasks['task' + dependence]['f'] = \
int(tasks['task' + dependence]['l_f']) - int(tasks['task' + dependence]['e_f'])
return tasks
if __name__ == '__main__':
file = open('input.txt')
tasks = parse_file(file)
# Прямой проход.
tasks = forward(tasks)
# Копируем и переворачиваем tasks.
array1 = []
for task in tasks.keys():
array1.append(task)
array2 = array1[:]
array2.reverse()
# Обратный проход.
tasks = backward(array2, tasks)
ID = []
data = {
'Длительность задачи': [],
'Раннее начало': [],
'Раннее окончание': [],
'Позднее начало': [],
'Позднее окончание': [],
'Полный резерв': [],
'Критический путь': []
}
for task in tasks:
ID.append(tasks[task]['id'])
data['Длительность задачи'].append(tasks[task]['duration'])
data['Раннее начало'].append(tasks[task]['e_s'])
data['Раннее окончание'].append(tasks[task]['e_f'])
data['Позднее начало'].append((tasks[task]['l_s']))
data['Позднее окончание'].append((tasks[task]['l_f']))
data['Полный резерв'].append((tasks[task]['f']))
data['Критический путь'].append(tasks[task]['f'] == 0)
create_table(data, ID)
print('\nДлина критического пути:', tasks['taskstop']['l_s']) | 0.224565 | 0.318684 |
# Manage DNS Records
# Functions:
# - Add
# - Update
# - Delete
# Usage:
# ./dns_records.py <zone_id> <command> [name] [type] [content] [ttl] [record_id]
# WGM CloudFlare integration
import cf
# WGM DB Integration
import wgm_db
# Other dependencies
import sys
import psycopg2.extras
def update_dns_record(zone_id,record_id,name,rtype,content,ttl):
record_name = name
record_type = rtype
record_content = content
record_ttl = ttl
status = {"command":"update_dns_record","status":False,"message":"False"}
# Should have everything we need. Let's find out what type of provider this is.
# Now check to make sure provider id is valid, die quickly otherwise.
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
#print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+zone_id
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
status['message']="Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+zone_id
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
status['message']="Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
# Find out Record UID
get_record_sql = "SELECT provider_uid FROM dns_zone_records WHERE id="+record_id
cur.execute(get_record_sql)
get_record_row = cur.fetchone()
if get_record_row is None:
status['message']="Record has no uid"
return status
# Setup record variables
record_uid = get_record_row['provider_uid']
if provider_type == "1": ## UPDATE A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare DNS Provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+provider_id
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
status['message']="Auth Token Unavailable"
return status
# Setup Auth Token
auth_token = get_auth_row['auth_key0']
success = cf.update_dns_record(zone_uid,record_uid,auth_token,record_name,record_type,record_content,record_ttl)
if success == True:
#print("---SUCCESS---")
#print("Updating db")
update_rec_sql = "UPDATE dns_zone_records SET name = %s, type = %s, content = %s, ttl = %s WHERE id = %s"
cur.execute(update_rec_sql,(record_name,record_type,record_content,record_ttl,record_id))
db_conn.commit()
#print("DB Updated")
else:
status['message']="Failed to update DNS record"
return status
else:
status['message']="Provider Type Unknown"
return status
status['status']=True
status['message']="Success"
return status
def delete_dns_record(zone_id,record_id):
status = {"command":"delete_dns_record","status":False,"message":"False"}
# Find out what kind of provider this is.
# Should have everything we need. Let's find out what type of provider this is.
# Now check to make sure provider id is valid, die quickly otherwise.
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
#print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+str(zone_id)
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
#print("Zone Not Found")
status['message']="Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+str(zone_id)
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
status['message']="Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
# Find Record provider_uid
get_record_sql = "SELECT provider_uid FROM dns_zone_records WHERE id="+str(record_id)
cur.execute(get_record_sql)
get_record_row = cur.fetchone()
if get_record_row is None:
status['message'] = "Provider uid does not exist"
return status
record_uid = get_record_row['provider_uid']
if provider_type == "1": ## DELETE A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+str(provider_id)
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
status['message']="Auth Token Unavailable"
return status
# Setup Auth Token
auth_token = get_auth_row['auth_key0']
# Deleting DNS Record
#print("Deleting Record in Cloudflare")
success = cf.delete_dns_record(zone_uid,record_uid,auth_token)
if success == True:
#print("---SUCCESS---")
#print("Deleting from DB")
delete_rec_sql = "DELETE FROM dns_zone_records WHERE id="+str(record_id)
cur.execute(delete_rec_sql)
db_conn.commit()
else:
status['Message']="Failed to delete DNS Record"
return status
else:
status['message']="Unknown Provider"
return status
status['status']=True
status['message']="Success"
return status
def add_dns_record(zone_id,name,rtype,content,ttl):
record_name = name
record_type = rtype
record_content = content
record_ttl = ttl
status = {"command":"add_dns_record","status":False,"message":"False","record_uid":""}
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+zone_id
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
#print("Zone Not Found")
status['message'] = "Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+zone_id
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
#print("Provider Does Not Exist")
status['message'] = "Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
if provider_type == "1": ## ADD A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare DNS Provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+provider_id
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
#print("Auth Token Unavailable")
status['message'] = "Auth Token Unavailable"
return status
# Setup Auth token
auth_token = get_auth_row['auth_key0']
# We should have everything we need now to create the record in Cloudflare
#print("Creating Record in Cloudflare")
record_uid = cf.add_dns_record(zone_uid, auth_token, record_name, record_type, record_content, record_ttl)
if record_uid != "FALSE":
#print("Successfully created record in Cloudflare with uid: "+record_uid)
#print("---SUCCESS---")
#print("Updating Database")
new_unique_id = wgm_db.get_unique_id(64,'dns_zone_records',db_conn)
sql = "INSERT INTO dns_zone_records (name, type, content, zone, ttl, unique_id, provider_uid) VALUES (%s, %s, %s, %s, %s, %s, %s)"
cur.execute(sql,(record_name,record_type,record_content,zone_id,record_ttl,new_unique_id,record_uid))
db_conn.commit()
#print("DB Updated")
else:
#print("---FAILED---")
status['message']="Failed to Create DNS Record"
return status
else:
#print("Unknown Provider Type, Failing")
status['message']="Unknown Provider Type"
return status
status['message']="Success"
status['status']=True
status['record_uid']=record_uid
return status | wgm/cli/dns/dns_records.py |
# Manage DNS Records
# Functions:
# - Add
# - Update
# - Delete
# Usage:
# ./dns_records.py <zone_id> <command> [name] [type] [content] [ttl] [record_id]
# WGM CloudFlare integration
import cf
# WGM DB Integration
import wgm_db
# Other dependencies
import sys
import psycopg2.extras
def update_dns_record(zone_id,record_id,name,rtype,content,ttl):
record_name = name
record_type = rtype
record_content = content
record_ttl = ttl
status = {"command":"update_dns_record","status":False,"message":"False"}
# Should have everything we need. Let's find out what type of provider this is.
# Now check to make sure provider id is valid, die quickly otherwise.
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
#print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+zone_id
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
status['message']="Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+zone_id
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
status['message']="Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
# Find out Record UID
get_record_sql = "SELECT provider_uid FROM dns_zone_records WHERE id="+record_id
cur.execute(get_record_sql)
get_record_row = cur.fetchone()
if get_record_row is None:
status['message']="Record has no uid"
return status
# Setup record variables
record_uid = get_record_row['provider_uid']
if provider_type == "1": ## UPDATE A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare DNS Provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+provider_id
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
status['message']="Auth Token Unavailable"
return status
# Setup Auth Token
auth_token = get_auth_row['auth_key0']
success = cf.update_dns_record(zone_uid,record_uid,auth_token,record_name,record_type,record_content,record_ttl)
if success == True:
#print("---SUCCESS---")
#print("Updating db")
update_rec_sql = "UPDATE dns_zone_records SET name = %s, type = %s, content = %s, ttl = %s WHERE id = %s"
cur.execute(update_rec_sql,(record_name,record_type,record_content,record_ttl,record_id))
db_conn.commit()
#print("DB Updated")
else:
status['message']="Failed to update DNS record"
return status
else:
status['message']="Provider Type Unknown"
return status
status['status']=True
status['message']="Success"
return status
def delete_dns_record(zone_id,record_id):
status = {"command":"delete_dns_record","status":False,"message":"False"}
# Find out what kind of provider this is.
# Should have everything we need. Let's find out what type of provider this is.
# Now check to make sure provider id is valid, die quickly otherwise.
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
#print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+str(zone_id)
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
#print("Zone Not Found")
status['message']="Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+str(zone_id)
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
status['message']="Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
# Find Record provider_uid
get_record_sql = "SELECT provider_uid FROM dns_zone_records WHERE id="+str(record_id)
cur.execute(get_record_sql)
get_record_row = cur.fetchone()
if get_record_row is None:
status['message'] = "Provider uid does not exist"
return status
record_uid = get_record_row['provider_uid']
if provider_type == "1": ## DELETE A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+str(provider_id)
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
status['message']="Auth Token Unavailable"
return status
# Setup Auth Token
auth_token = get_auth_row['auth_key0']
# Deleting DNS Record
#print("Deleting Record in Cloudflare")
success = cf.delete_dns_record(zone_uid,record_uid,auth_token)
if success == True:
#print("---SUCCESS---")
#print("Deleting from DB")
delete_rec_sql = "DELETE FROM dns_zone_records WHERE id="+str(record_id)
cur.execute(delete_rec_sql)
db_conn.commit()
else:
status['Message']="Failed to delete DNS Record"
return status
else:
status['message']="Unknown Provider"
return status
status['status']=True
status['message']="Success"
return status
def add_dns_record(zone_id,name,rtype,content,ttl):
record_name = name
record_type = rtype
record_content = content
record_ttl = ttl
status = {"command":"add_dns_record","status":False,"message":"False","record_uid":""}
db_conn = wgm_db.connect()
#print("DB Connection Open")
cur = db_conn.cursor(cursor_factory = psycopg2.extras.DictCursor)
print("Zone id: %s" % zone_id)
# Find out Zone specific information
get_zone_sql = "SELECT * FROM dns_zones WHERE id="+zone_id
cur.execute(get_zone_sql)
get_zone_row = cur.fetchone()
if get_zone_row is None:
#print("Zone Not Found")
status['message'] = "Zone Not Found"
return status
# Setup Zone provider_uid
zone_uid = get_zone_row['value']
#print("Zone value: "+zone_uid)
# Find out Provider Specific Information
get_provider_sql = "SELECT p.type,p.id FROM dns_providers AS p JOIN dns_zones AS z ON z.provider=p.id WHERE z.id="+zone_id
# query db for zone
cur.execute(get_provider_sql)
get_provider_row = cur.fetchone()
# make sure we have a legit digitalocean provider
if get_provider_row is None:
#print("Provider Does Not Exist")
status['message'] = "Provider Does Not Exist"
return status
# Set up provider variables
provider_id = str(get_provider_row['id'])
provider_type = get_provider_row['type']
if provider_type == "1": ## ADD A RECORD FOR A CLOUDFLARE DNS PROVIDER TYPE
#print("Cloudflare DNS Provider")
#print("Unique Provider ID: "+provider_id)
# Now we can get the auth_token
get_auth_sql = "SELECT auth_key0 FROM dns_auth_configs WHERE provider="+provider_id
cur.execute(get_auth_sql)
get_auth_row = cur.fetchone()
if get_auth_row is None:
#print("Auth Token Unavailable")
status['message'] = "Auth Token Unavailable"
return status
# Setup Auth token
auth_token = get_auth_row['auth_key0']
# We should have everything we need now to create the record in Cloudflare
#print("Creating Record in Cloudflare")
record_uid = cf.add_dns_record(zone_uid, auth_token, record_name, record_type, record_content, record_ttl)
if record_uid != "FALSE":
#print("Successfully created record in Cloudflare with uid: "+record_uid)
#print("---SUCCESS---")
#print("Updating Database")
new_unique_id = wgm_db.get_unique_id(64,'dns_zone_records',db_conn)
sql = "INSERT INTO dns_zone_records (name, type, content, zone, ttl, unique_id, provider_uid) VALUES (%s, %s, %s, %s, %s, %s, %s)"
cur.execute(sql,(record_name,record_type,record_content,zone_id,record_ttl,new_unique_id,record_uid))
db_conn.commit()
#print("DB Updated")
else:
#print("---FAILED---")
status['message']="Failed to Create DNS Record"
return status
else:
#print("Unknown Provider Type, Failing")
status['message']="Unknown Provider Type"
return status
status['message']="Success"
status['status']=True
status['record_uid']=record_uid
return status | 0.106058 | 0.089694 |
import math
import components_3d as com
import esper
import glm
import pygame
import pygame.locals
import resources as res
def add_systems_1_to_world(world):
world.add_processor(GameControlSystem())
def add_systems_2_to_world(world):
world.add_processor(ThirdPersonCameraSystem())
world.add_processor(FreeCamOrientation())
def clamp(value, m_min, m_max):
if value <= m_min:
return m_min
if value >= m_max:
return m_max
return value
class GameControlSystem(esper.Processor):
def process(self):
keys = pygame.key.get_pressed()
controls: res.GameControlState = self.world.controls
# Swap camera
if keys[controls.key_swap_camera] and not controls.key_swap_camera_state and controls.allow_camera_swap:
# swap camera
self.world._swap_camera()
# Reset
if keys[controls.key_return_to_home] and not controls.key_return_to_home_state:
self.world.home_entities()
controls.key_swap_camera_state = keys[controls.key_swap_camera]
controls.key_return_to_home_state = keys[controls.key_return_to_home]
self._acknowledge_input()
def _acknowledge_input(self):
controls: res.GameControlState = self.world.controls
if controls.control_mode == res.GameControlState.PLAYER_MODE:
self._wasd_movement(
self.world.player_object,
controls.player_speed,
False,
0.0)
self._arrow_key_rotation(self.world.player_object, enable_pitch=False)
self._mouse_control(self.world.player_object, enable_pitch=False)
# self._player_jump()
else:
self._wasd_movement(
self.world.free_cam,
controls.free_camera_speed,
True,
controls.free_camera_vertical_speed)
self._arrow_key_rotation(self.world.free_cam)
self._mouse_control(self.world.free_cam)
# self._change_light(self.world.win_object)
def _wasd_movement(self, entity_id, speed, vertical_movement, vertical_speed):
keys = pygame.key.get_pressed()
velocity = self.world.component_for_entity(entity_id, com.Velocity)
# WASD
direction = glm.vec3()
if keys[pygame.locals.K_w]:
direction.y += 1
if keys[pygame.locals.K_s]:
direction.y -= 1
if keys[pygame.locals.K_a]:
direction.x += 1
if keys[pygame.locals.K_d]:
direction.x -= 1
if glm.length(direction) > 0.001:
new_v = glm.normalize(direction) * speed
velocity.value.x = new_v.x
velocity.value.y = new_v.y
else:
velocity.value.x = 0.0
velocity.value.y = 0.0
if vertical_movement:
velocity.value.z = 0
if keys[pygame.locals.K_SPACE]:
velocity.value.z += vertical_speed
if keys[pygame.locals.K_LSHIFT]:
velocity.value.z -= vertical_speed
if keys[pygame.locals.K_p]:
tra = self.world.component_for_entity(entity_id, com.Transformation)
print(f"Transformation(Position: {tra.position}, Rotation: {tra.rotation})")
def _mouse_control(self, entity_id, enable_pitch=True):
controls: res.GameControlState = self.world.controls
screen_center = self.world.resolution / 2.0
# If python breaks on this try updating pygame :D
(is_pressed, _, _, _, _) = pygame.mouse.get_pressed()
if is_pressed:
transformation = self.world.component_for_entity(entity_id, com.Transformation)
#(rel_x, rel_y) = pygame.mouse.get_rel()
(pos_x, pos_y) = pygame.mouse.get_pos()
rel_x = screen_center.x - pos_x
rel_y = screen_center.y - pos_y
if enable_pitch:
pitch_change = rel_y * controls.mouse_sensitivity
transformation.rotation.y = clamp(
transformation.rotation.y + pitch_change,
(math.pi - 0.2) / -2,
(math.pi - 0.2) / 2)
transformation.rotation.x += rel_x * controls.mouse_sensitivity
pygame.mouse.set_pos([screen_center.x, screen_center.y])
def _arrow_key_rotation(self, entity_id, enable_pitch=True):
transformation = self.world.component_for_entity(entity_id, com.Transformation)
keys = pygame.key.get_pressed()
if enable_pitch:
pitch_change = 0.0
if keys[pygame.locals.K_UP]:
pitch_change += 0.1
if keys[pygame.locals.K_DOWN]:
pitch_change -= 0.1
transformation.rotation.y = clamp(
transformation.rotation.y + pitch_change,
(math.pi - 0.2) / -2,
(math.pi - 0.2) / 2)
if keys[pygame.locals.K_LEFT]:
transformation.rotation.x += 0.1
if keys[pygame.locals.K_RIGHT]:
transformation.rotation.x -= 0.1
def _player_jump(self):
collision = self.world.component_for_entity(self.world.player_object, com.CollisionComponent)
if collision.is_colliding_z:
keys = pygame.key.get_pressed()
if keys[pygame.locals.K_SPACE]:
v = self.world.component_for_entity(self.world.player_object, com.Velocity)
v.value.z += self.world.controls.player_jump_height
def _change_light(self, entity_id):
keys = pygame.key.get_pressed()
light: com.Light = self.world.component_for_entity(entity_id, com.Light)
if keys[pygame.locals.K_t]:
light.color.x += 0.01
if keys[pygame.locals.K_g]:
light.color.x -= 0.01
if keys[pygame.locals.K_z]:
light.color.y += 0.01
if keys[pygame.locals.K_h]:
light.color.y -= 0.01
if keys[pygame.locals.K_u]:
light.color.z += 0.01
if keys[pygame.locals.K_h]:
light.color.z -= 0.01
if keys[pygame.locals.K_u]:
light.attenuation.x += 0.01
if keys[pygame.locals.K_j]:
light.attenuation.x -= 0.01
if keys[pygame.locals.K_i]:
light.attenuation.y += 0.01
if keys[pygame.locals.K_k]:
light.attenuation.y -= 0.01
if keys[pygame.locals.K_o]:
light.attenuation.z += 0.01
if keys[pygame.locals.K_l]:
light.attenuation.z -= 0.01
if keys[pygame.locals.K_p]:
print(f"Light(color: {light.color}, attenuation: {light.attenuation})")
class ThirdPersonCameraSystem(esper.Processor):
def process(self):
for _id, (transformation, orientation, third_person_cam) in self.world.get_components(
com.Transformation,
com.CameraOrientation,
com.ThirdPersonCamera):
orientation.look_at = self.world.component_for_entity(third_person_cam.target, com.Transformation).position
yaw = self.world.component_for_entity(third_person_cam.target, com.Transformation).rotation.x
pitch = third_person_cam.pitch
dir_height = math.sin(pitch)
dir_vec = glm.vec3(
math.cos(yaw) * (1.0 - abs(dir_height)),
math.sin(yaw) * (1.0 - abs(dir_height)),
dir_height
)
target_pos = self.world.component_for_entity(third_person_cam.target, com.Transformation).position
transformation.position = target_pos - (dir_vec * third_person_cam.distance)
class FreeCamOrientation(esper.Processor):
def process(self):
for _id, (transformation, orientation, _free_cam) in self.world.get_components(
com.Transformation,
com.CameraOrientation,
com.FreeCamera):
height = math.sin(transformation.rotation.y)
orientation.look_at = transformation.position + glm.vec3(
math.cos(transformation.rotation.x) * (1.0 - abs(height)),
math.sin(transformation.rotation.x) * (1.0 - abs(height)),
height
) | src/control_system.py | import math
import components_3d as com
import esper
import glm
import pygame
import pygame.locals
import resources as res
def add_systems_1_to_world(world):
world.add_processor(GameControlSystem())
def add_systems_2_to_world(world):
world.add_processor(ThirdPersonCameraSystem())
world.add_processor(FreeCamOrientation())
def clamp(value, m_min, m_max):
if value <= m_min:
return m_min
if value >= m_max:
return m_max
return value
class GameControlSystem(esper.Processor):
def process(self):
keys = pygame.key.get_pressed()
controls: res.GameControlState = self.world.controls
# Swap camera
if keys[controls.key_swap_camera] and not controls.key_swap_camera_state and controls.allow_camera_swap:
# swap camera
self.world._swap_camera()
# Reset
if keys[controls.key_return_to_home] and not controls.key_return_to_home_state:
self.world.home_entities()
controls.key_swap_camera_state = keys[controls.key_swap_camera]
controls.key_return_to_home_state = keys[controls.key_return_to_home]
self._acknowledge_input()
def _acknowledge_input(self):
controls: res.GameControlState = self.world.controls
if controls.control_mode == res.GameControlState.PLAYER_MODE:
self._wasd_movement(
self.world.player_object,
controls.player_speed,
False,
0.0)
self._arrow_key_rotation(self.world.player_object, enable_pitch=False)
self._mouse_control(self.world.player_object, enable_pitch=False)
# self._player_jump()
else:
self._wasd_movement(
self.world.free_cam,
controls.free_camera_speed,
True,
controls.free_camera_vertical_speed)
self._arrow_key_rotation(self.world.free_cam)
self._mouse_control(self.world.free_cam)
# self._change_light(self.world.win_object)
def _wasd_movement(self, entity_id, speed, vertical_movement, vertical_speed):
keys = pygame.key.get_pressed()
velocity = self.world.component_for_entity(entity_id, com.Velocity)
# WASD
direction = glm.vec3()
if keys[pygame.locals.K_w]:
direction.y += 1
if keys[pygame.locals.K_s]:
direction.y -= 1
if keys[pygame.locals.K_a]:
direction.x += 1
if keys[pygame.locals.K_d]:
direction.x -= 1
if glm.length(direction) > 0.001:
new_v = glm.normalize(direction) * speed
velocity.value.x = new_v.x
velocity.value.y = new_v.y
else:
velocity.value.x = 0.0
velocity.value.y = 0.0
if vertical_movement:
velocity.value.z = 0
if keys[pygame.locals.K_SPACE]:
velocity.value.z += vertical_speed
if keys[pygame.locals.K_LSHIFT]:
velocity.value.z -= vertical_speed
if keys[pygame.locals.K_p]:
tra = self.world.component_for_entity(entity_id, com.Transformation)
print(f"Transformation(Position: {tra.position}, Rotation: {tra.rotation})")
def _mouse_control(self, entity_id, enable_pitch=True):
controls: res.GameControlState = self.world.controls
screen_center = self.world.resolution / 2.0
# If python breaks on this try updating pygame :D
(is_pressed, _, _, _, _) = pygame.mouse.get_pressed()
if is_pressed:
transformation = self.world.component_for_entity(entity_id, com.Transformation)
#(rel_x, rel_y) = pygame.mouse.get_rel()
(pos_x, pos_y) = pygame.mouse.get_pos()
rel_x = screen_center.x - pos_x
rel_y = screen_center.y - pos_y
if enable_pitch:
pitch_change = rel_y * controls.mouse_sensitivity
transformation.rotation.y = clamp(
transformation.rotation.y + pitch_change,
(math.pi - 0.2) / -2,
(math.pi - 0.2) / 2)
transformation.rotation.x += rel_x * controls.mouse_sensitivity
pygame.mouse.set_pos([screen_center.x, screen_center.y])
def _arrow_key_rotation(self, entity_id, enable_pitch=True):
transformation = self.world.component_for_entity(entity_id, com.Transformation)
keys = pygame.key.get_pressed()
if enable_pitch:
pitch_change = 0.0
if keys[pygame.locals.K_UP]:
pitch_change += 0.1
if keys[pygame.locals.K_DOWN]:
pitch_change -= 0.1
transformation.rotation.y = clamp(
transformation.rotation.y + pitch_change,
(math.pi - 0.2) / -2,
(math.pi - 0.2) / 2)
if keys[pygame.locals.K_LEFT]:
transformation.rotation.x += 0.1
if keys[pygame.locals.K_RIGHT]:
transformation.rotation.x -= 0.1
def _player_jump(self):
collision = self.world.component_for_entity(self.world.player_object, com.CollisionComponent)
if collision.is_colliding_z:
keys = pygame.key.get_pressed()
if keys[pygame.locals.K_SPACE]:
v = self.world.component_for_entity(self.world.player_object, com.Velocity)
v.value.z += self.world.controls.player_jump_height
def _change_light(self, entity_id):
keys = pygame.key.get_pressed()
light: com.Light = self.world.component_for_entity(entity_id, com.Light)
if keys[pygame.locals.K_t]:
light.color.x += 0.01
if keys[pygame.locals.K_g]:
light.color.x -= 0.01
if keys[pygame.locals.K_z]:
light.color.y += 0.01
if keys[pygame.locals.K_h]:
light.color.y -= 0.01
if keys[pygame.locals.K_u]:
light.color.z += 0.01
if keys[pygame.locals.K_h]:
light.color.z -= 0.01
if keys[pygame.locals.K_u]:
light.attenuation.x += 0.01
if keys[pygame.locals.K_j]:
light.attenuation.x -= 0.01
if keys[pygame.locals.K_i]:
light.attenuation.y += 0.01
if keys[pygame.locals.K_k]:
light.attenuation.y -= 0.01
if keys[pygame.locals.K_o]:
light.attenuation.z += 0.01
if keys[pygame.locals.K_l]:
light.attenuation.z -= 0.01
if keys[pygame.locals.K_p]:
print(f"Light(color: {light.color}, attenuation: {light.attenuation})")
class ThirdPersonCameraSystem(esper.Processor):
def process(self):
for _id, (transformation, orientation, third_person_cam) in self.world.get_components(
com.Transformation,
com.CameraOrientation,
com.ThirdPersonCamera):
orientation.look_at = self.world.component_for_entity(third_person_cam.target, com.Transformation).position
yaw = self.world.component_for_entity(third_person_cam.target, com.Transformation).rotation.x
pitch = third_person_cam.pitch
dir_height = math.sin(pitch)
dir_vec = glm.vec3(
math.cos(yaw) * (1.0 - abs(dir_height)),
math.sin(yaw) * (1.0 - abs(dir_height)),
dir_height
)
target_pos = self.world.component_for_entity(third_person_cam.target, com.Transformation).position
transformation.position = target_pos - (dir_vec * third_person_cam.distance)
class FreeCamOrientation(esper.Processor):
def process(self):
for _id, (transformation, orientation, _free_cam) in self.world.get_components(
com.Transformation,
com.CameraOrientation,
com.FreeCamera):
height = math.sin(transformation.rotation.y)
orientation.look_at = transformation.position + glm.vec3(
math.cos(transformation.rotation.x) * (1.0 - abs(height)),
math.sin(transformation.rotation.x) * (1.0 - abs(height)),
height
) | 0.383295 | 0.272917 |
from unittest import TestCase
from exceptions import InvalidCardSize, InvalidPlayerMove
from game.game_state_machine import GameStateMachine
from game.game_variant import GameVariantGrand
from game.state.game_state_bid import GameStateBid, BidStateCallTurn, BidCallAction, BidStateResponseTurn, \
BidAcceptAction, BidPassAction, BidStateEnd
from game.game import Game
from game.state.game_state_play import GameStatePlay
from model.player import Player
from model.card import Card
# TODO check for correct action delegation with substates
class GameStateBidTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_pickUpSkat(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
skat = self.game.skat
skat.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
skat.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when
self.state.pick_up_skat(player)
# then
self.assertEquals(len(player.cards), 4)
self.assertEquals(len(skat), 0)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) in player.cards)
def test_pickUpSkat_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
skat = self.game.skat
skat.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
skat.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when/then
self.assertRaises(InvalidPlayerMove, self.state.pick_up_skat, player)
def test_putDownSkat(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when
self.state.put_down_skat(player, cards_to_put)
# then
self.assertEquals(len(player.cards), 2)
self.assertEquals(len(self.game.skat), 2)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) not in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) not in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) in self.game.skat)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) in self.game.skat)
def test_putDownSkat_lessThanTwoFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
# when/then
self.assertRaises(InvalidCardSize, self.state.put_down_skat, player, cards_to_put)
def test_putDownSkat_moreThanTwoFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.NINE))
# when/then
self.assertRaises(InvalidCardSize, self.state.put_down_skat, player, cards_to_put)
def test_putDownSkat_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when/then
self.assertRaises(InvalidPlayerMove, self.state.put_down_skat, player, cards_to_put)
def test_declareGame(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
game_variant = GameVariantGrand()
# when
self.state.declare_game(player, game_variant)
# then
self.assertEquals(self.game.game_variant, game_variant)
self.assertTrue(isinstance(self.state_machine.current_state, GameStatePlay))
def test_declareGame_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
game_variant = GameVariantGrand()
# when/then
self.assertRaises(InvalidPlayerMove, self.state.declare_game, player, game_variant)
def test_bidPass(self):
# given
player = self.game.players[0]
# when
self.state.bid_pass(self.game, player)
# then
self.assertEquals(player.type, Player.Type.DEFENDER)
self.assertTrue(player in self.game.passed_bid_players)
def test_bidPass_playerAlreadyPassedFails(self):
# given
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.bid_pass, self.game, player)
def test_checkPlayerHasPassed(self):
# given
player = self.game.players[0]
# when
self.state.check_player_has_passed(self.game, player)
# then nothing happens
def test_checkPlayerHasPassed_Fails(self):
# given
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.check_player_has_passed, self.game, player)
def test_twoPlayerPasses(self):
# given
self.game.dealer = 0
declarer = self.game.get_second_seat()
defender1 = self.game.get_first_seat()
defender2 = self.game.get_third_seat()
# when
self.state.handle_action(BidCallAction(declarer, 18))
self.state.handle_action(BidPassAction(defender1, 18))
self.state.handle_action(BidPassAction(defender2, 18))
# then
self.assertEquals(declarer.type, Player.Type.DECLARER)
self.assertEquals(defender1.type, Player.Type.DEFENDER)
self.assertEquals(defender2.type, Player.Type.DEFENDER)
class BidResponseAction(object):
pass
class BidStateCallTurnTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_transitionFromCallTurnToResponseTurn(self):
# given
value = 18
player = self.game.players[0]
self.state.current_bid_state = BidStateCallTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidCallAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateResponseTurn))
def test_transitionFromCallTurnToEnd(self):
# given
value = 18
player = self.game.players[0]
self.game.passed_bid_players.append(self.game.players[1])
self.state.current_bid_state = BidStateCallTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidPassAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateEnd))
def test_bidCall(self):
# given
value = 18
self.game.bid_value = -1
player = self.game.players[0]
# when
self.state.current_bid_state.bid_call(player, value)
# then
self.assertEquals(self.game.bid_value, value)
def test_bidCall_playerAlreadyPassedFails(self):
# given
value = 18
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_call, player, value)
def test_bidCall_unavailableBidValueFails(self):
# given
value = 5
player = self.game.players[0]
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_call, player, value)
class BidStateCallResponseTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
self.state_machine = GameStateMachine(self.state)
def test_transitionFromResponseTurnToEnd(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.game.passed_bid_players.append(self.game.players[1])
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidPassAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateEnd))
def test_transitionFromResponseTurnToCallTurn(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidAcceptAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateCallTurn))
def test_bidAccept(self):
# given
value = 18
self.game.bid_value = 18
player = self.game.players[0]
# when
self.state.current_bid_state.bid_accept(player, value)
# then nothing should happen (beside state changed)
def test_bidCall_playerAlreadyPassedFails(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_accept, player, value)
def test_bidCall_unavailableBidValueFails(self):
# given
value = 18
self.game.bid_value = 20
player = self.game.players[0]
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_accept, player, value)
class BidStateEndTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_firstSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_second_seat(), self.game.get_third_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_first_seat().type, Player.Type.DECLARER)
def test_secondSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_first_seat(), self.game.get_third_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_second_seat().type, Player.Type.DECLARER)
def test_thirdSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_first_seat(), self.game.get_second_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_third_seat().type, Player.Type.DECLARER) | tests/game/state/test_game_state_bid.py | from unittest import TestCase
from exceptions import InvalidCardSize, InvalidPlayerMove
from game.game_state_machine import GameStateMachine
from game.game_variant import GameVariantGrand
from game.state.game_state_bid import GameStateBid, BidStateCallTurn, BidCallAction, BidStateResponseTurn, \
BidAcceptAction, BidPassAction, BidStateEnd
from game.game import Game
from game.state.game_state_play import GameStatePlay
from model.player import Player
from model.card import Card
# TODO check for correct action delegation with substates
class GameStateBidTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_pickUpSkat(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
skat = self.game.skat
skat.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
skat.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when
self.state.pick_up_skat(player)
# then
self.assertEquals(len(player.cards), 4)
self.assertEquals(len(skat), 0)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) in player.cards)
def test_pickUpSkat_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
skat = self.game.skat
skat.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
skat.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when/then
self.assertRaises(InvalidPlayerMove, self.state.pick_up_skat, player)
def test_putDownSkat(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when
self.state.put_down_skat(player, cards_to_put)
# then
self.assertEquals(len(player.cards), 2)
self.assertEquals(len(self.game.skat), 2)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) not in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) not in player.cards)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.SEVEN) in self.game.skat)
self.assertTrue(Card(Card.Suit.HEARTS, Card.Face.EIGHT) in self.game.skat)
def test_putDownSkat_lessThanTwoFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
# when/then
self.assertRaises(InvalidCardSize, self.state.put_down_skat, player, cards_to_put)
def test_putDownSkat_moreThanTwoFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.NINE))
# when/then
self.assertRaises(InvalidCardSize, self.state.put_down_skat, player, cards_to_put)
def test_putDownSkat_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.DIAMOND, Card.Face.EIGHT))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
player.cards.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
cards_to_put = list()
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.SEVEN))
cards_to_put.append(Card(Card.Suit.HEARTS, Card.Face.EIGHT))
# when/then
self.assertRaises(InvalidPlayerMove, self.state.put_down_skat, player, cards_to_put)
def test_declareGame(self):
# given
player = self.game.players[0]
player.type = Player.Type.DECLARER
game_variant = GameVariantGrand()
# when
self.state.declare_game(player, game_variant)
# then
self.assertEquals(self.game.game_variant, game_variant)
self.assertTrue(isinstance(self.state_machine.current_state, GameStatePlay))
def test_declareGame_notDeclarerFails(self):
# given
player = self.game.players[0]
player.type = Player.Type.DEFENDER
game_variant = GameVariantGrand()
# when/then
self.assertRaises(InvalidPlayerMove, self.state.declare_game, player, game_variant)
def test_bidPass(self):
# given
player = self.game.players[0]
# when
self.state.bid_pass(self.game, player)
# then
self.assertEquals(player.type, Player.Type.DEFENDER)
self.assertTrue(player in self.game.passed_bid_players)
def test_bidPass_playerAlreadyPassedFails(self):
# given
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.bid_pass, self.game, player)
def test_checkPlayerHasPassed(self):
# given
player = self.game.players[0]
# when
self.state.check_player_has_passed(self.game, player)
# then nothing happens
def test_checkPlayerHasPassed_Fails(self):
# given
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.check_player_has_passed, self.game, player)
def test_twoPlayerPasses(self):
# given
self.game.dealer = 0
declarer = self.game.get_second_seat()
defender1 = self.game.get_first_seat()
defender2 = self.game.get_third_seat()
# when
self.state.handle_action(BidCallAction(declarer, 18))
self.state.handle_action(BidPassAction(defender1, 18))
self.state.handle_action(BidPassAction(defender2, 18))
# then
self.assertEquals(declarer.type, Player.Type.DECLARER)
self.assertEquals(defender1.type, Player.Type.DEFENDER)
self.assertEquals(defender2.type, Player.Type.DEFENDER)
class BidResponseAction(object):
pass
class BidStateCallTurnTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_transitionFromCallTurnToResponseTurn(self):
# given
value = 18
player = self.game.players[0]
self.state.current_bid_state = BidStateCallTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidCallAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateResponseTurn))
def test_transitionFromCallTurnToEnd(self):
# given
value = 18
player = self.game.players[0]
self.game.passed_bid_players.append(self.game.players[1])
self.state.current_bid_state = BidStateCallTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidPassAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateEnd))
def test_bidCall(self):
# given
value = 18
self.game.bid_value = -1
player = self.game.players[0]
# when
self.state.current_bid_state.bid_call(player, value)
# then
self.assertEquals(self.game.bid_value, value)
def test_bidCall_playerAlreadyPassedFails(self):
# given
value = 18
player = self.game.players[0]
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_call, player, value)
def test_bidCall_unavailableBidValueFails(self):
# given
value = 5
player = self.game.players[0]
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_call, player, value)
class BidStateCallResponseTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
self.state_machine = GameStateMachine(self.state)
def test_transitionFromResponseTurnToEnd(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.game.passed_bid_players.append(self.game.players[1])
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidPassAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateEnd))
def test_transitionFromResponseTurnToCallTurn(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.state.current_bid_state = BidStateResponseTurn(self.game)
self.state.current_bid_state.state_finished_handler = self.state.bid_state_finished_handler
# when
self.state.current_bid_state.handle_action(BidAcceptAction(player, value))
# then
self.assertTrue(isinstance(self.state.current_bid_state, BidStateCallTurn))
def test_bidAccept(self):
# given
value = 18
self.game.bid_value = 18
player = self.game.players[0]
# when
self.state.current_bid_state.bid_accept(player, value)
# then nothing should happen (beside state changed)
def test_bidCall_playerAlreadyPassedFails(self):
# given
value = 18
player = self.game.players[0]
self.game.bid_value = 18
self.game.passed_bid_players.append(player)
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_accept, player, value)
def test_bidCall_unavailableBidValueFails(self):
# given
value = 18
self.game.bid_value = 20
player = self.game.players[0]
# when/then
self.assertRaises(InvalidPlayerMove, self.state.current_bid_state.bid_accept, player, value)
class BidStateEndTest(TestCase):
def setUp(self):
self.game = Game([Player(1, "P1"), Player(2, "P2"), Player(3, "P3")])
self.state = GameStateBid(self.game)
self.state_machine = GameStateMachine(self.state)
def test_firstSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_second_seat(), self.game.get_third_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_first_seat().type, Player.Type.DECLARER)
def test_secondSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_first_seat(), self.game.get_third_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_second_seat().type, Player.Type.DECLARER)
def test_thirdSeatIsDeclarer(self):
# given
self.game.bid_value = 18
self.game.passed_bid_players = [self.game.get_first_seat(), self.game.get_second_seat()]
self.state.current_bid_state = BidStateEnd(self.game)
# then
self.assertEquals(self.game.get_third_seat().type, Player.Type.DECLARER) | 0.400515 | 0.308529 |
from __future__ import unicode_literals
from rest_framework.views import APIView
from rest_framework.parsers import JSONParser
from rest_framework.response import Response
from rest_framework import status
from credocommon.exceptions import RegistrationException
from credoapiv2.authentication import DRFTokenAuthentication
from credoapiv2.exceptions import CredoAPIException, LoginException
from credoapiv2.handlers import (
handle_registration,
handle_login,
handle_oauth_login,
handle_user_id,
handle_detection,
handle_update_info,
handle_ping,
handle_data_export,
handle_mapping_export,
)
import logging
logger = logging.getLogger(__name__)
class UserRegistrationView(APIView):
"""
post:
Register user
"""
parser_classes = (JSONParser,)
def post(self, request):
try:
handle_registration(request)
return Response(
status=status.HTTP_200_OK,
data={"message": "Please check your email for activation link."},
)
except RegistrationException as e:
return Response(
data={"message": "Registration failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserLoginView(APIView):
"""
post:
Login user
"""
parser_classes = (JSONParser,)
def post(self, request, format=None):
try:
return Response(data=handle_login(request), status=status.HTTP_200_OK)
except LoginException as e:
return Response(
data={"message": "Login failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserOAuthLoginView(APIView):
"""
post:
Login user with OAuth provider
"""
parser_classes = (JSONParser,)
def post(self, request, format=None):
try:
return Response(data=handle_oauth_login(request), status=status.HTTP_200_OK)
except LoginException as e:
return Response(
data={"message": "OAuth login failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserInfoView(APIView):
"""
post:
Change information about user
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
data = handle_update_info(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Updating user info failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class UserIdView(APIView):
"""
get:
Get unique user ID
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def get(self, request):
if request.user.is_authenticated:
try:
data = handle_user_id(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Getting user ID failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class DetectionView(APIView):
"""
post:
Submit detection
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
data = handle_detection(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Submitting detection failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class PingView(APIView):
"""
post:
Submit ping
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
handle_ping(request)
return Response(status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Ping failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class DataExportView(APIView):
"""
post:
Export data
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
throttle_scope = "data_export"
def post(self, request):
if request.user.is_authenticated and request.user.is_staff:
try:
return Response(
data=handle_data_export(request), status=status.HTTP_200_OK
)
except CredoAPIException as e:
return Response(
data={"message": "Data export failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class MappingExportView(APIView):
"""
post:
Export mapping
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
throttle_scope = "mapping_export"
def post(self, request):
if request.user.is_authenticated and request.user.is_staff:
try:
return Response(
data=handle_mapping_export(request), status=status.HTTP_200_OK
)
except CredoAPIException as e:
return Response(
data={"message": "Mapping export failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
) | credoapiv2/views.py | from __future__ import unicode_literals
from rest_framework.views import APIView
from rest_framework.parsers import JSONParser
from rest_framework.response import Response
from rest_framework import status
from credocommon.exceptions import RegistrationException
from credoapiv2.authentication import DRFTokenAuthentication
from credoapiv2.exceptions import CredoAPIException, LoginException
from credoapiv2.handlers import (
handle_registration,
handle_login,
handle_oauth_login,
handle_user_id,
handle_detection,
handle_update_info,
handle_ping,
handle_data_export,
handle_mapping_export,
)
import logging
logger = logging.getLogger(__name__)
class UserRegistrationView(APIView):
"""
post:
Register user
"""
parser_classes = (JSONParser,)
def post(self, request):
try:
handle_registration(request)
return Response(
status=status.HTTP_200_OK,
data={"message": "Please check your email for activation link."},
)
except RegistrationException as e:
return Response(
data={"message": "Registration failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserLoginView(APIView):
"""
post:
Login user
"""
parser_classes = (JSONParser,)
def post(self, request, format=None):
try:
return Response(data=handle_login(request), status=status.HTTP_200_OK)
except LoginException as e:
return Response(
data={"message": "Login failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserOAuthLoginView(APIView):
"""
post:
Login user with OAuth provider
"""
parser_classes = (JSONParser,)
def post(self, request, format=None):
try:
return Response(data=handle_oauth_login(request), status=status.HTTP_200_OK)
except LoginException as e:
return Response(
data={"message": "OAuth login failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except CredoAPIException as e:
return Response(
data={"message": str(e)}, status=status.HTTP_400_BAD_REQUEST
)
except Exception as e:
logger.exception(e)
raise e
class UserInfoView(APIView):
"""
post:
Change information about user
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
data = handle_update_info(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Updating user info failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class UserIdView(APIView):
"""
get:
Get unique user ID
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def get(self, request):
if request.user.is_authenticated:
try:
data = handle_user_id(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Getting user ID failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class DetectionView(APIView):
"""
post:
Submit detection
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
data = handle_detection(request)
return Response(data=data, status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Submitting detection failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class PingView(APIView):
"""
post:
Submit ping
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
def post(self, request):
if request.user.is_authenticated:
try:
handle_ping(request)
return Response(status=status.HTTP_200_OK)
except CredoAPIException as e:
return Response(
data={"message": "Ping failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class DataExportView(APIView):
"""
post:
Export data
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
throttle_scope = "data_export"
def post(self, request):
if request.user.is_authenticated and request.user.is_staff:
try:
return Response(
data=handle_data_export(request), status=status.HTTP_200_OK
)
except CredoAPIException as e:
return Response(
data={"message": "Data export failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
)
class MappingExportView(APIView):
"""
post:
Export mapping
"""
authentication_classes = (DRFTokenAuthentication,)
parser_classes = (JSONParser,)
throttle_scope = "mapping_export"
def post(self, request):
if request.user.is_authenticated and request.user.is_staff:
try:
return Response(
data=handle_mapping_export(request), status=status.HTTP_200_OK
)
except CredoAPIException as e:
return Response(
data={"message": "Mapping export failed. Reason: " + str(e)},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
logger.exception(e)
raise e
else:
return Response(
data={"message": "Invalid token"}, status=status.HTTP_401_UNAUTHORIZED
) | 0.500244 | 0.088583 |
from __future__ import absolute_import
import sys
from esky.util import lazy_import
@lazy_import
def os():
import os
return os
@lazy_import
def tempfile():
import tempfile
return tempfile
@lazy_import
def threading():
try:
import threading
except ImportError:
threading = None
return threading
@lazy_import
def ctypes():
import ctypes
import ctypes.wintypes
return ctypes
def monitor_master_process(fpath):
"""Watch the given path to detect the master process dying.
If the master process dies, the current process is terminated.
"""
if not threading:
return None
def monitor():
if wait_for_master(fpath):
os._exit(1)
t = threading.Thread(target=monitor)
t.daemon = True
t.start()
return t
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
def run_startup_hooks():
if len(sys.argv) > 1 and sys.argv[1] == "--esky-slave-proc":
del sys.argv[1]
if len(sys.argv) > 1:
arg = sys.argv[1]
del sys.argv[1]
else:
arg = None
monitor_master_process(arg)
if sys.platform == "win32":
# On win32, the master process creates a tempfile that will be deleted
# when it exits. Use ReadDirectoryChanges to block on this event.
def wait_for_master(fpath):
"""Wait for the master process to die."""
try:
RDCW = ctypes.windll.kernel32.ReadDirectoryChangesW
except AttributeError:
return False
INVALID_HANDLE_VALUE = 0xFFFFFFFF
FILE_NOTIFY_CHANGE_FILE_NAME = 0x01
FILE_LIST_DIRECTORY = 0x01
FILE_SHARE_READ = 0x01
FILE_SHARE_WRITE = 0x02
OPEN_EXISTING = 3
FILE_FLAG_BACKUP_SEMANTICS = 0x02000000
try:
ctypes.wintypes.LPVOID
except AttributeError:
ctypes.wintypes.LPVOID = ctypes.c_void_p
def _errcheck_bool(value,func,args):
if not value:
raise ctypes.WinError()
return args
def _errcheck_handle(value,func,args):
if not value:
raise ctypes.WinError()
if value == INVALID_HANDLE_VALUE:
raise ctypes.WinError()
return args
RDCW.errcheck = _errcheck_bool
RDCW.restype = ctypes.wintypes.BOOL
RDCW.argtypes = (
ctypes.wintypes.HANDLE, # hDirectory
ctypes.wintypes.LPVOID, # lpBuffer
ctypes.wintypes.DWORD, # nBufferLength
ctypes.wintypes.BOOL, # bWatchSubtree
ctypes.wintypes.DWORD, # dwNotifyFilter
ctypes.POINTER(ctypes.wintypes.DWORD), # lpBytesReturned
ctypes.wintypes.LPVOID, # lpOverlapped
ctypes.wintypes.LPVOID # lpCompletionRoutine
)
CreateFileW = ctypes.windll.kernel32.CreateFileW
CreateFileW.errcheck = _errcheck_handle
CreateFileW.restype = ctypes.wintypes.HANDLE
CreateFileW.argtypes = (
ctypes.wintypes.LPCWSTR, # lpFileName
ctypes.wintypes.DWORD, # dwDesiredAccess
ctypes.wintypes.DWORD, # dwShareMode
ctypes.wintypes.LPVOID, # lpSecurityAttributes
ctypes.wintypes.DWORD, # dwCreationDisposition
ctypes.wintypes.DWORD, # dwFlagsAndAttributes
ctypes.wintypes.HANDLE # hTemplateFile
)
CloseHandle = ctypes.windll.kernel32.CloseHandle
CloseHandle.restype = ctypes.wintypes.BOOL
CloseHandle.argtypes = (
ctypes.wintypes.HANDLE, # hObject
)
result = ctypes.create_string_buffer(1024)
nbytes = ctypes.c_ulong()
handle = CreateFileW(os.path.join(os.path.dirname(fpath),u""),
FILE_LIST_DIRECTORY,
FILE_SHARE_READ | FILE_SHARE_WRITE,
None,
OPEN_EXISTING,
FILE_FLAG_BACKUP_SEMANTICS,
0
)
# Since this loop may still be running at interpreter close, we
# take local references to our imported functions to avoid
# garbage-collection-related errors at shutdown.
byref = ctypes.byref
pathexists = os.path.exists
try:
while pathexists(fpath):
RDCW(handle,byref(result),len(result),
True,FILE_NOTIFY_CHANGE_FILE_NAME,
byref(nbytes),None,None)
finally:
CloseHandle(handle)
return True
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
try:
flags = os.O_CREAT|os.O_EXCL|os.O_TEMPORARY|os.O_NOINHERIT
tfile = tempfile.mktemp()
fd = os.open(tfile,flags)
except EnvironmentError:
return []
else:
return ["--esky-slave-proc",tfile]
else:
# On unix, the master process takes an exclusive flock on the given file.
# We try to take one as well, which will block until the master dies.
import fcntl
def wait_for_master(fpath):
"""Wait for the master process to die."""
try:
fd = os.open(fpath,os.O_RDWR)
fcntl.flock(fd,fcntl.LOCK_EX)
return True
except EnvironmentError:
return False
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
try:
(fd,tfile) = tempfile.mkstemp()
fcntl.flock(fd,fcntl.LOCK_EX)
except EnvironmentError:
return []
else:
return ["--esky-slave-proc",tfile] | esky/slaveproc.py | from __future__ import absolute_import
import sys
from esky.util import lazy_import
@lazy_import
def os():
import os
return os
@lazy_import
def tempfile():
import tempfile
return tempfile
@lazy_import
def threading():
try:
import threading
except ImportError:
threading = None
return threading
@lazy_import
def ctypes():
import ctypes
import ctypes.wintypes
return ctypes
def monitor_master_process(fpath):
"""Watch the given path to detect the master process dying.
If the master process dies, the current process is terminated.
"""
if not threading:
return None
def monitor():
if wait_for_master(fpath):
os._exit(1)
t = threading.Thread(target=monitor)
t.daemon = True
t.start()
return t
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
def run_startup_hooks():
if len(sys.argv) > 1 and sys.argv[1] == "--esky-slave-proc":
del sys.argv[1]
if len(sys.argv) > 1:
arg = sys.argv[1]
del sys.argv[1]
else:
arg = None
monitor_master_process(arg)
if sys.platform == "win32":
# On win32, the master process creates a tempfile that will be deleted
# when it exits. Use ReadDirectoryChanges to block on this event.
def wait_for_master(fpath):
"""Wait for the master process to die."""
try:
RDCW = ctypes.windll.kernel32.ReadDirectoryChangesW
except AttributeError:
return False
INVALID_HANDLE_VALUE = 0xFFFFFFFF
FILE_NOTIFY_CHANGE_FILE_NAME = 0x01
FILE_LIST_DIRECTORY = 0x01
FILE_SHARE_READ = 0x01
FILE_SHARE_WRITE = 0x02
OPEN_EXISTING = 3
FILE_FLAG_BACKUP_SEMANTICS = 0x02000000
try:
ctypes.wintypes.LPVOID
except AttributeError:
ctypes.wintypes.LPVOID = ctypes.c_void_p
def _errcheck_bool(value,func,args):
if not value:
raise ctypes.WinError()
return args
def _errcheck_handle(value,func,args):
if not value:
raise ctypes.WinError()
if value == INVALID_HANDLE_VALUE:
raise ctypes.WinError()
return args
RDCW.errcheck = _errcheck_bool
RDCW.restype = ctypes.wintypes.BOOL
RDCW.argtypes = (
ctypes.wintypes.HANDLE, # hDirectory
ctypes.wintypes.LPVOID, # lpBuffer
ctypes.wintypes.DWORD, # nBufferLength
ctypes.wintypes.BOOL, # bWatchSubtree
ctypes.wintypes.DWORD, # dwNotifyFilter
ctypes.POINTER(ctypes.wintypes.DWORD), # lpBytesReturned
ctypes.wintypes.LPVOID, # lpOverlapped
ctypes.wintypes.LPVOID # lpCompletionRoutine
)
CreateFileW = ctypes.windll.kernel32.CreateFileW
CreateFileW.errcheck = _errcheck_handle
CreateFileW.restype = ctypes.wintypes.HANDLE
CreateFileW.argtypes = (
ctypes.wintypes.LPCWSTR, # lpFileName
ctypes.wintypes.DWORD, # dwDesiredAccess
ctypes.wintypes.DWORD, # dwShareMode
ctypes.wintypes.LPVOID, # lpSecurityAttributes
ctypes.wintypes.DWORD, # dwCreationDisposition
ctypes.wintypes.DWORD, # dwFlagsAndAttributes
ctypes.wintypes.HANDLE # hTemplateFile
)
CloseHandle = ctypes.windll.kernel32.CloseHandle
CloseHandle.restype = ctypes.wintypes.BOOL
CloseHandle.argtypes = (
ctypes.wintypes.HANDLE, # hObject
)
result = ctypes.create_string_buffer(1024)
nbytes = ctypes.c_ulong()
handle = CreateFileW(os.path.join(os.path.dirname(fpath),u""),
FILE_LIST_DIRECTORY,
FILE_SHARE_READ | FILE_SHARE_WRITE,
None,
OPEN_EXISTING,
FILE_FLAG_BACKUP_SEMANTICS,
0
)
# Since this loop may still be running at interpreter close, we
# take local references to our imported functions to avoid
# garbage-collection-related errors at shutdown.
byref = ctypes.byref
pathexists = os.path.exists
try:
while pathexists(fpath):
RDCW(handle,byref(result),len(result),
True,FILE_NOTIFY_CHANGE_FILE_NAME,
byref(nbytes),None,None)
finally:
CloseHandle(handle)
return True
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
try:
flags = os.O_CREAT|os.O_EXCL|os.O_TEMPORARY|os.O_NOINHERIT
tfile = tempfile.mktemp()
fd = os.open(tfile,flags)
except EnvironmentError:
return []
else:
return ["--esky-slave-proc",tfile]
else:
# On unix, the master process takes an exclusive flock on the given file.
# We try to take one as well, which will block until the master dies.
import fcntl
def wait_for_master(fpath):
"""Wait for the master process to die."""
try:
fd = os.open(fpath,os.O_RDWR)
fcntl.flock(fd,fcntl.LOCK_EX)
return True
except EnvironmentError:
return False
def get_slave_process_args():
"""Get the arguments that should be passed to a new slave process."""
try:
(fd,tfile) = tempfile.mkstemp()
fcntl.flock(fd,fcntl.LOCK_EX)
except EnvironmentError:
return []
else:
return ["--esky-slave-proc",tfile] | 0.382949 | 0.124612 |
import random
from typing import Type, Union, Dict, Any, List, Tuple
# 3rd party imports
import streamlit as st
import numpy as np
import pandas as pd
import altair as alt
import seaborn as sns
from wordcloud import WordCloud
from yellowbrick.classifier import classification_report
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
def sidebar() -> None:
"""
Purpose:
Shows the side bar
Args:
N/A
Returns:
N/A
"""
st.sidebar.title("Python Web Conf")
# Create the Navigation Section
st.sidebar.image(
"https://2022.pythonwebconf.com/python-web-conference-2022/@@images/logo_image"
)
pages = ["Home", "Playground", "Schedule", "Team"]
default_page = 0
page = st.sidebar.selectbox("Go To", options=pages, index=default_page)
if page == "Home":
home_page()
elif page == "Playground":
playground_page()
elif page == "Schedule":
schedule_page()
elif page == "Team":
team_page()
else:
st.error("Invalid Page")
def app() -> None:
"""
Purpose:
Controls the app flow
Args:
N/A
Returns:
N/A
"""
# Spin up the sidebar, will control which page is loaded in the
# main app
sidebar()
def data_prep(df: pd.DataFrame) -> Tuple[List, List, List, List]:
"""
Purpose:
Prep data for modeling
Args:
df - Pandas dataframe
Returns:
test_features - test set features
train_features - train set feautres
test_target - test set target
train_target - train set target
"""
# Specify the target classes
target_string = st.selectbox("Select Target Column", df.columns)
target = np.array(df[target_string])
# Select Features you want
feature_cols = st.multiselect("Select Modeling Features", df.columns)
# Get all features
features = df[feature_cols]
featurestmp = np.array(features)
feats = []
# find all bad rows
for index, featarr in enumerate(featurestmp):
try:
featarr = featarr.astype(float)
feats.append(featarr)
except Exception as error:
st.error(error)
st.error(featarr)
st.stop()
featuresarr = np.array(feats)
# Split Data
randInt = random.randint(1, 200)
(
test_features,
train_features,
test_target,
train_target,
) = train_test_split(featuresarr, target, test_size=0.75, random_state=randInt)
return (
test_features,
train_features,
test_target,
train_target,
)
def show_classification_report(
df: pd.DataFrame,
) -> None:
"""
Purpose:
Renders a classification_report
Args:
df - Pandas dataframe
Returns:
N/A
"""
# Prep data for model training
(
test_features,
train_features,
test_target,
train_target,
) = data_prep(df)
if st.button("Train Model"):
st.header("Classification Report")
st.markdown(
"The classification report visualizer displays the precision, recall, F1, and support scores for the model. In order to support easier interpretation and problem detection, the report integrates numerical scores with a color-coded heatmap. All heatmaps are in the range (0.0, 1.0) to facilitate easy comparison of classification models across different classification reports."
)
# Instantiate the visualizer
visualizer = classification_report(
GaussianNB(),
train_features,
train_target,
test_features,
test_target,
support=True,
)
# Get the viz
fig = visualizer.fig
ax = visualizer.show()
fig.axes.append(ax)
# show the viz
st.write(fig)
def gen_wordcloud(df: pd.DataFrame, repeat: bool) -> None:
"""
Purpose:
Generate Word Cloud from Column
Args:
df - Pandas dataframe
Returns:
N/A
"""
# List of all non-numeric fields of given dataframe
non_num_cols = df.select_dtypes(include=object).columns
# selected column
column = st.selectbox("Column", non_num_cols)
column = df[column]
# generate word cloud image from unique values of selected non-numeric field
wc = WordCloud(
max_font_size=25, background_color="white", repeat=repeat, height=500, width=800
).generate(" ".join(column.unique()))
# Display the generated image:
st.image(wc.to_image())
def bar_chart(
df: pd.DataFrame,
):
"""
Purpose:
Renders bar chart
Args:
df - Pandas dataframe
Returns:
N/A
"""
# Bar Chart Example
x_col = st.selectbox("Select x axis for bar chart", df.columns)
xcol_string = x_col + ":O"
if st.checkbox("Show as continuous?", key="bar_chart_x_is_cont"):
xcol_string = x_col + ":Q"
y_col = st.selectbox("Select y axis for bar chart", df.columns)
z_col = st.selectbox("Select z axis for bar chart", df.columns)
chart = (
alt.Chart(df)
.mark_bar()
.encode(x=xcol_string, y=y_col, color=z_col, tooltip=list(df.columns))
.interactive()
.properties(title="Bar Chart for " + x_col + "," + y_col)
.configure_title(
fontSize=20,
)
.configure_axis(labelFontSize=20, titleFontSize=20)
.configure_legend(labelFontSize=20, titleFontSize=20)
)
st.altair_chart(chart, use_container_width=True)
def show_metrics(df: pd.DataFrame) -> None:
"""
Purpose:
Render mean,max,min,std,count metrics of numeric fields
Args:
df - Pandas dataframe
Returns:
N/A
"""
# List of all numeric fields of given dataframe
columns = df.select_dtypes(include="number").columns
# selected column
column = st.selectbox("Column", options=columns)
column = df[column]
# Rendering metrics
col1, col2, col3, col4, col5 = st.columns(5)
col1.metric("Mean", round(column.mean(), 2))
col2.metric("Max", column.max())
col3.metric("Min", column.min())
col4.metric("Std", round(column.std(), 2))
col5.metric("Count", int(column.count()))
def playground_page():
"""
Purpose:
Render playground page
Args:
N/A
Returns:
N/A
"""
st.header("Playground")
df = pd.read_csv("data/iris.csv")
bar_chart(df)
st.subheader("Metrics")
show_metrics(df)
talk_df = pd.read_csv("data/talks.csv")
st.subheader("WordCloud")
repeat = st.checkbox("Repeat words?")
gen_wordcloud(talk_df, repeat)
st.subheader("Classification Report")
show_classification_report(df)
def write_talk_data(datum, col):
"""
Purpose:
Render schedule data
Args:
datum - data
col - column to write
Returns:
N/A
"""
col.write(datum["title"])
col.write(datum["speaker"])
def schedule_page():
"""
Purpose:
Render schedule page
Args:
N/A
Returns:
N/A
"""
st.header("Schedule")
talk_data = pd.read_csv("data/talks.csv")
with st.expander("Monday,March 21,2022"):
datum = talk_data.iloc[0]
col1, col2 = st.columns([1, 3])
col1.write(datum["time"])
col2.header("KEYNOTE")
col2.subheader(datum["title"])
col2.write(datum["speaker"])
with st.expander("Tuesday,March 22,2022"):
datum = talk_data.iloc[2]
col1, col2, col3, col4, col5, col6, col7 = st.columns(7)
# Header rows
col1.write("TIME(US EDT/UTC-4)")
col2.write("APP DEV 1")
col3.write("APP DEV 2")
col4.write("CLOUD")
col5.write("CULTURE")
col6.write("PYDATA")
col7.write("TUTORIALS")
# Data Rows
col1.write(datum["time"])
write_talk_data(datum, col2)
datum = talk_data.iloc[3]
write_talk_data(datum, col3)
datum = talk_data.iloc[4]
write_talk_data(datum, col4)
datum = talk_data.iloc[5]
write_talk_data(datum, col5)
datum = talk_data.iloc[6]
write_talk_data(datum, col6)
datum = talk_data.iloc[7]
write_talk_data(datum, col7)
def render_team_member(datum):
"""
Purpose:
Render team members
Args:
N/A
Returns:
N/A
"""
st.image(datum["picture"])
st.write(datum["name"])
st.write(datum["title"])
st.markdown(f"[Linkedin]({datum['linkedin']})")
st.markdown(f"[Twitter]({datum['twitter']})")
def team_page():
"""
Purpose:
Show team page
Args:
N/A
Returns:
N/A
"""
st.header("Meet the Team")
st.subheader(
"Meet the Sixie team behind the 4th annual 2022 Python Web Conference:"
)
team_data = pd.read_csv("data/team.csv")
# st.write(team_data)
col1, col2, col3 = st.columns(3)
with col1:
datum = team_data.iloc[0]
render_team_member(datum)
datum = team_data.iloc[3]
render_team_member(datum)
with col2:
datum = team_data.iloc[1]
render_team_member(datum)
datum = team_data.iloc[4]
render_team_member(datum)
with col3:
datum = team_data.iloc[2]
render_team_member(datum)
def home_page():
"""
Purpose:
Show home page
Args:
N/A
Returns:
N/A
"""
with st.echo(code_location="below"):
st.title("Python Web Conf")
st.subheader("The most in-depth Python conference for web developers")
st.image(
"https://2022.pythonwebconf.com/python-web-conference-2022/@@images/logo_image"
)
st.write("https://2022.pythonwebconf.com/")
def main() -> None:
"""
Purpose:
Controls the flow of the streamlit app
Args:
N/A
Returns:
N/A
"""
# Start the streamlit app
app()
if __name__ == "__main__":
main() | pywebconf_st.py | import random
from typing import Type, Union, Dict, Any, List, Tuple
# 3rd party imports
import streamlit as st
import numpy as np
import pandas as pd
import altair as alt
import seaborn as sns
from wordcloud import WordCloud
from yellowbrick.classifier import classification_report
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
def sidebar() -> None:
"""
Purpose:
Shows the side bar
Args:
N/A
Returns:
N/A
"""
st.sidebar.title("Python Web Conf")
# Create the Navigation Section
st.sidebar.image(
"https://2022.pythonwebconf.com/python-web-conference-2022/@@images/logo_image"
)
pages = ["Home", "Playground", "Schedule", "Team"]
default_page = 0
page = st.sidebar.selectbox("Go To", options=pages, index=default_page)
if page == "Home":
home_page()
elif page == "Playground":
playground_page()
elif page == "Schedule":
schedule_page()
elif page == "Team":
team_page()
else:
st.error("Invalid Page")
def app() -> None:
"""
Purpose:
Controls the app flow
Args:
N/A
Returns:
N/A
"""
# Spin up the sidebar, will control which page is loaded in the
# main app
sidebar()
def data_prep(df: pd.DataFrame) -> Tuple[List, List, List, List]:
"""
Purpose:
Prep data for modeling
Args:
df - Pandas dataframe
Returns:
test_features - test set features
train_features - train set feautres
test_target - test set target
train_target - train set target
"""
# Specify the target classes
target_string = st.selectbox("Select Target Column", df.columns)
target = np.array(df[target_string])
# Select Features you want
feature_cols = st.multiselect("Select Modeling Features", df.columns)
# Get all features
features = df[feature_cols]
featurestmp = np.array(features)
feats = []
# find all bad rows
for index, featarr in enumerate(featurestmp):
try:
featarr = featarr.astype(float)
feats.append(featarr)
except Exception as error:
st.error(error)
st.error(featarr)
st.stop()
featuresarr = np.array(feats)
# Split Data
randInt = random.randint(1, 200)
(
test_features,
train_features,
test_target,
train_target,
) = train_test_split(featuresarr, target, test_size=0.75, random_state=randInt)
return (
test_features,
train_features,
test_target,
train_target,
)
def show_classification_report(
df: pd.DataFrame,
) -> None:
"""
Purpose:
Renders a classification_report
Args:
df - Pandas dataframe
Returns:
N/A
"""
# Prep data for model training
(
test_features,
train_features,
test_target,
train_target,
) = data_prep(df)
if st.button("Train Model"):
st.header("Classification Report")
st.markdown(
"The classification report visualizer displays the precision, recall, F1, and support scores for the model. In order to support easier interpretation and problem detection, the report integrates numerical scores with a color-coded heatmap. All heatmaps are in the range (0.0, 1.0) to facilitate easy comparison of classification models across different classification reports."
)
# Instantiate the visualizer
visualizer = classification_report(
GaussianNB(),
train_features,
train_target,
test_features,
test_target,
support=True,
)
# Get the viz
fig = visualizer.fig
ax = visualizer.show()
fig.axes.append(ax)
# show the viz
st.write(fig)
def gen_wordcloud(df: pd.DataFrame, repeat: bool) -> None:
"""
Purpose:
Generate Word Cloud from Column
Args:
df - Pandas dataframe
Returns:
N/A
"""
# List of all non-numeric fields of given dataframe
non_num_cols = df.select_dtypes(include=object).columns
# selected column
column = st.selectbox("Column", non_num_cols)
column = df[column]
# generate word cloud image from unique values of selected non-numeric field
wc = WordCloud(
max_font_size=25, background_color="white", repeat=repeat, height=500, width=800
).generate(" ".join(column.unique()))
# Display the generated image:
st.image(wc.to_image())
def bar_chart(
df: pd.DataFrame,
):
"""
Purpose:
Renders bar chart
Args:
df - Pandas dataframe
Returns:
N/A
"""
# Bar Chart Example
x_col = st.selectbox("Select x axis for bar chart", df.columns)
xcol_string = x_col + ":O"
if st.checkbox("Show as continuous?", key="bar_chart_x_is_cont"):
xcol_string = x_col + ":Q"
y_col = st.selectbox("Select y axis for bar chart", df.columns)
z_col = st.selectbox("Select z axis for bar chart", df.columns)
chart = (
alt.Chart(df)
.mark_bar()
.encode(x=xcol_string, y=y_col, color=z_col, tooltip=list(df.columns))
.interactive()
.properties(title="Bar Chart for " + x_col + "," + y_col)
.configure_title(
fontSize=20,
)
.configure_axis(labelFontSize=20, titleFontSize=20)
.configure_legend(labelFontSize=20, titleFontSize=20)
)
st.altair_chart(chart, use_container_width=True)
def show_metrics(df: pd.DataFrame) -> None:
"""
Purpose:
Render mean,max,min,std,count metrics of numeric fields
Args:
df - Pandas dataframe
Returns:
N/A
"""
# List of all numeric fields of given dataframe
columns = df.select_dtypes(include="number").columns
# selected column
column = st.selectbox("Column", options=columns)
column = df[column]
# Rendering metrics
col1, col2, col3, col4, col5 = st.columns(5)
col1.metric("Mean", round(column.mean(), 2))
col2.metric("Max", column.max())
col3.metric("Min", column.min())
col4.metric("Std", round(column.std(), 2))
col5.metric("Count", int(column.count()))
def playground_page():
"""
Purpose:
Render playground page
Args:
N/A
Returns:
N/A
"""
st.header("Playground")
df = pd.read_csv("data/iris.csv")
bar_chart(df)
st.subheader("Metrics")
show_metrics(df)
talk_df = pd.read_csv("data/talks.csv")
st.subheader("WordCloud")
repeat = st.checkbox("Repeat words?")
gen_wordcloud(talk_df, repeat)
st.subheader("Classification Report")
show_classification_report(df)
def write_talk_data(datum, col):
"""
Purpose:
Render schedule data
Args:
datum - data
col - column to write
Returns:
N/A
"""
col.write(datum["title"])
col.write(datum["speaker"])
def schedule_page():
"""
Purpose:
Render schedule page
Args:
N/A
Returns:
N/A
"""
st.header("Schedule")
talk_data = pd.read_csv("data/talks.csv")
with st.expander("Monday,March 21,2022"):
datum = talk_data.iloc[0]
col1, col2 = st.columns([1, 3])
col1.write(datum["time"])
col2.header("KEYNOTE")
col2.subheader(datum["title"])
col2.write(datum["speaker"])
with st.expander("Tuesday,March 22,2022"):
datum = talk_data.iloc[2]
col1, col2, col3, col4, col5, col6, col7 = st.columns(7)
# Header rows
col1.write("TIME(US EDT/UTC-4)")
col2.write("APP DEV 1")
col3.write("APP DEV 2")
col4.write("CLOUD")
col5.write("CULTURE")
col6.write("PYDATA")
col7.write("TUTORIALS")
# Data Rows
col1.write(datum["time"])
write_talk_data(datum, col2)
datum = talk_data.iloc[3]
write_talk_data(datum, col3)
datum = talk_data.iloc[4]
write_talk_data(datum, col4)
datum = talk_data.iloc[5]
write_talk_data(datum, col5)
datum = talk_data.iloc[6]
write_talk_data(datum, col6)
datum = talk_data.iloc[7]
write_talk_data(datum, col7)
def render_team_member(datum):
"""
Purpose:
Render team members
Args:
N/A
Returns:
N/A
"""
st.image(datum["picture"])
st.write(datum["name"])
st.write(datum["title"])
st.markdown(f"[Linkedin]({datum['linkedin']})")
st.markdown(f"[Twitter]({datum['twitter']})")
def team_page():
"""
Purpose:
Show team page
Args:
N/A
Returns:
N/A
"""
st.header("Meet the Team")
st.subheader(
"Meet the Sixie team behind the 4th annual 2022 Python Web Conference:"
)
team_data = pd.read_csv("data/team.csv")
# st.write(team_data)
col1, col2, col3 = st.columns(3)
with col1:
datum = team_data.iloc[0]
render_team_member(datum)
datum = team_data.iloc[3]
render_team_member(datum)
with col2:
datum = team_data.iloc[1]
render_team_member(datum)
datum = team_data.iloc[4]
render_team_member(datum)
with col3:
datum = team_data.iloc[2]
render_team_member(datum)
def home_page():
"""
Purpose:
Show home page
Args:
N/A
Returns:
N/A
"""
with st.echo(code_location="below"):
st.title("Python Web Conf")
st.subheader("The most in-depth Python conference for web developers")
st.image(
"https://2022.pythonwebconf.com/python-web-conference-2022/@@images/logo_image"
)
st.write("https://2022.pythonwebconf.com/")
def main() -> None:
"""
Purpose:
Controls the flow of the streamlit app
Args:
N/A
Returns:
N/A
"""
# Start the streamlit app
app()
if __name__ == "__main__":
main() | 0.847211 | 0.379608 |
import os
import shutil
import math
import time
import menpo.io as mio
import menpo3d.io as m3io
import numpy as np
from pathlib import Path
from functools import partial
# deepmachine
import keras
import tensorflow as tf
import deepmachine as dm
# flag definitions
from deepmachine.flags import FLAGS
def main():
tf.reset_default_graph()
BATCH_SIZE = FLAGS.batch_size
INPUT_SHAPE = 256
LR = FLAGS.lr
DATA_PATH = FLAGS.dataset_path
LOGDIR = "{}/model_{}".format(FLAGS.logdir, time.time()
) if 'model_' not in FLAGS.logdir else FLAGS.logdir
# Dataset
def build_data():
dataset = dm.data.provider.TFRecordNoFlipProvider(
DATA_PATH,
dm.data.provider.features.FeatureIUVHM,
augmentation=True,
resolvers={
'images': dm.data.provider.resolvers.image_resolver,
'iuvs': partial(dm.data.provider.resolvers.iuv_resolver, n_parts=2, dtype=tf.float32),
'heatmaps': dm.data.provider.resolvers.heatmap_resolver_face,
}
)
dataset = dm.data.provider.DatasetQueue(
dataset, n_proccess=FLAGS.no_thread, batch_size=BATCH_SIZE)
tf_data = dataset.get('images', 'iuvs', 'heatmaps')
return [tf_data['images']], [tf_data['iuvs'], tf_data['heatmaps']]
# Model
def build_model():
input_image = dm.layers.Input(
shape=[INPUT_SHAPE, INPUT_SHAPE, 3], name='input_image')
iuv_prediction = dm.networks.Hourglass(
input_image, [INPUT_SHAPE, INPUT_SHAPE, 6], depth=4, batch_norm=True, use_coordconv=False)
merged_inputs = dm.layers.Concatenate()([input_image, iuv_prediction])
hm_prediction = dm.networks.Hourglass(
merged_inputs, [INPUT_SHAPE, INPUT_SHAPE, 68], depth=4, batch_norm=True, use_coordconv=False)
train_model = dm.DeepMachine(
inputs=input_image, outputs=[
iuv_prediction, hm_prediction])
train_model.compile(
optimizer=dm.optimizers.Adam(lr=LR),
loss=[dm.losses.loss_iuv_regression,
dm.losses.loss_heatmap_regression],
)
return train_model
build_model().fit(
build_data(),
epochs=200,
step_per_epoch=40000 // BATCH_SIZE,
logdir=LOGDIR,
lr_decay=0.99,
verbose=2
)
if __name__ == '__main__':
main() | deepmachine/contrib/training/DenseRegFace.py | import os
import shutil
import math
import time
import menpo.io as mio
import menpo3d.io as m3io
import numpy as np
from pathlib import Path
from functools import partial
# deepmachine
import keras
import tensorflow as tf
import deepmachine as dm
# flag definitions
from deepmachine.flags import FLAGS
def main():
tf.reset_default_graph()
BATCH_SIZE = FLAGS.batch_size
INPUT_SHAPE = 256
LR = FLAGS.lr
DATA_PATH = FLAGS.dataset_path
LOGDIR = "{}/model_{}".format(FLAGS.logdir, time.time()
) if 'model_' not in FLAGS.logdir else FLAGS.logdir
# Dataset
def build_data():
dataset = dm.data.provider.TFRecordNoFlipProvider(
DATA_PATH,
dm.data.provider.features.FeatureIUVHM,
augmentation=True,
resolvers={
'images': dm.data.provider.resolvers.image_resolver,
'iuvs': partial(dm.data.provider.resolvers.iuv_resolver, n_parts=2, dtype=tf.float32),
'heatmaps': dm.data.provider.resolvers.heatmap_resolver_face,
}
)
dataset = dm.data.provider.DatasetQueue(
dataset, n_proccess=FLAGS.no_thread, batch_size=BATCH_SIZE)
tf_data = dataset.get('images', 'iuvs', 'heatmaps')
return [tf_data['images']], [tf_data['iuvs'], tf_data['heatmaps']]
# Model
def build_model():
input_image = dm.layers.Input(
shape=[INPUT_SHAPE, INPUT_SHAPE, 3], name='input_image')
iuv_prediction = dm.networks.Hourglass(
input_image, [INPUT_SHAPE, INPUT_SHAPE, 6], depth=4, batch_norm=True, use_coordconv=False)
merged_inputs = dm.layers.Concatenate()([input_image, iuv_prediction])
hm_prediction = dm.networks.Hourglass(
merged_inputs, [INPUT_SHAPE, INPUT_SHAPE, 68], depth=4, batch_norm=True, use_coordconv=False)
train_model = dm.DeepMachine(
inputs=input_image, outputs=[
iuv_prediction, hm_prediction])
train_model.compile(
optimizer=dm.optimizers.Adam(lr=LR),
loss=[dm.losses.loss_iuv_regression,
dm.losses.loss_heatmap_regression],
)
return train_model
build_model().fit(
build_data(),
epochs=200,
step_per_epoch=40000 // BATCH_SIZE,
logdir=LOGDIR,
lr_decay=0.99,
verbose=2
)
if __name__ == '__main__':
main() | 0.537284 | 0.183246 |
import logging
import os.path
import subprocess
import tarfile
import tempfile
from dbnd import output, task
from dbnd._core.constants import CloudType
from dbnd._core.errors import DatabandRuntimeError
from dbnd._core.utils.timezone import utcnow
from targets.types import Path
logger = logging.getLogger(__name__)
@task(archive=output(output_ext=".tar.gz")[Path])
def export_db(
archive,
include_db=True,
include_logs=True,
task_version=utcnow().strftime("%Y%m%d_%H%M%S"),
):
# type: (Path, bool, bool, str)-> None
from dbnd._core.current import get_databand_context
logger.info("Compressing files to %s..." % archive)
with tarfile.open(str(archive), "w:gz") as tar:
if include_db:
dbnd_context = get_databand_context()
conn_string = dbnd_context.settings.web.get_sql_alchemy_conn()
if conn_string.startswith("sqlite:"):
from dbnd_web.utils.dbnd_db import get_sqlite_db_location
db_file = get_sqlite_db_location(conn_string)
logger.info("Exporting DB=%s", db_file)
tar.add(db_file, arcname="dbnd.db")
elif conn_string.startswith("postgresql"):
with tempfile.NamedTemporaryFile(prefix="dbdump.", suffix=".sql") as tf:
from dbnd_web.utils.dbnd_db import dump_postgres
dump_postgres(conn_string, tf.name)
tar.add(tf.name, arcname="postgres-dbnd.sql")
else:
raise DatabandRuntimeError(
"Can not export db! "
"Currently, we support only sqlite and postgres db in automatic export"
)
if include_logs:
context = get_databand_context()
local_env = context.settings.get_env_config(CloudType.local)
logs_folder = local_env.dbnd_local_root.folder("logs").path
if os.path.exists(logs_folder):
logger.info("Adding run folder from '%s'", logs_folder)
tar.add(logs_folder, "run")
else:
logger.warning("Logs dir '%s' is not found", logs_folder)
def dump_postgres(conn_string, dump_file):
logger.info(
"backing up postgres DB to %s, pg_dump and sqlalchemy are required!", dump_file
)
from sqlalchemy.engine.url import make_url
url = make_url(conn_string)
cmd = [
"pg_dump",
"-h",
url.host,
"-p",
str(url.port),
"-U",
url.username,
"-Fc",
"-f",
dump_file,
"-d",
url.database,
]
logger.info("Running command: %s", subprocess.list2cmdline(cmd))
env = os.environ.copy()
env["PGPASSWORD"] = <PASSWORD>
subprocess.check_call(args=cmd, env=env) | modules/dbnd/src/dbnd/tasks/basics/export.py | import logging
import os.path
import subprocess
import tarfile
import tempfile
from dbnd import output, task
from dbnd._core.constants import CloudType
from dbnd._core.errors import DatabandRuntimeError
from dbnd._core.utils.timezone import utcnow
from targets.types import Path
logger = logging.getLogger(__name__)
@task(archive=output(output_ext=".tar.gz")[Path])
def export_db(
archive,
include_db=True,
include_logs=True,
task_version=utcnow().strftime("%Y%m%d_%H%M%S"),
):
# type: (Path, bool, bool, str)-> None
from dbnd._core.current import get_databand_context
logger.info("Compressing files to %s..." % archive)
with tarfile.open(str(archive), "w:gz") as tar:
if include_db:
dbnd_context = get_databand_context()
conn_string = dbnd_context.settings.web.get_sql_alchemy_conn()
if conn_string.startswith("sqlite:"):
from dbnd_web.utils.dbnd_db import get_sqlite_db_location
db_file = get_sqlite_db_location(conn_string)
logger.info("Exporting DB=%s", db_file)
tar.add(db_file, arcname="dbnd.db")
elif conn_string.startswith("postgresql"):
with tempfile.NamedTemporaryFile(prefix="dbdump.", suffix=".sql") as tf:
from dbnd_web.utils.dbnd_db import dump_postgres
dump_postgres(conn_string, tf.name)
tar.add(tf.name, arcname="postgres-dbnd.sql")
else:
raise DatabandRuntimeError(
"Can not export db! "
"Currently, we support only sqlite and postgres db in automatic export"
)
if include_logs:
context = get_databand_context()
local_env = context.settings.get_env_config(CloudType.local)
logs_folder = local_env.dbnd_local_root.folder("logs").path
if os.path.exists(logs_folder):
logger.info("Adding run folder from '%s'", logs_folder)
tar.add(logs_folder, "run")
else:
logger.warning("Logs dir '%s' is not found", logs_folder)
def dump_postgres(conn_string, dump_file):
logger.info(
"backing up postgres DB to %s, pg_dump and sqlalchemy are required!", dump_file
)
from sqlalchemy.engine.url import make_url
url = make_url(conn_string)
cmd = [
"pg_dump",
"-h",
url.host,
"-p",
str(url.port),
"-U",
url.username,
"-Fc",
"-f",
dump_file,
"-d",
url.database,
]
logger.info("Running command: %s", subprocess.list2cmdline(cmd))
env = os.environ.copy()
env["PGPASSWORD"] = <PASSWORD>
subprocess.check_call(args=cmd, env=env) | 0.26218 | 0.069668 |
import cv2
from image_morphing.np import np, GPU
from image_morphing.utils import load_points, resize_v
from image_morphing.render import render_animation
from image_morphing.optimize_v import adam
from image_morphing.quadratic_motion_path import adam_w
import os
def image_morphing(img0_path, img1_path, p0_path, p1_path, vmax_size=32, render_name='animation.mov',
lr_v=7e-2, tol_v=1e-1, lr_w=7e-2, tol_w=1e-3, lambda_tps=1e-3, gamma_ui=1e2,
tol_count_v=20, tol_count_w=3, render=False, render_steps=60, render_time=1,
save_dir='.cache'):
img0_src = cv2.imread(img0_path)
img1_src = cv2.imread(img1_path)
p0_src = load_points(p0_path)
p1_src = load_points(p1_path)
size = 8
v = np.random.randn(size, size, 2)
w = np.random.randn(size, size, 2)
# sizes = np.arange(8, vmax_size + 1, 8)
sizes = 2 ** np.arange(3, 10)
sizes = sizes[sizes <= vmax_size]
if GPU:
sizes = np.asnumpy(sizes)
for size in sizes:
print('\nOptimization size {:3d} start.'.format(size))
name = os.path.join(save_dir, 'v{:03d}'.format(size))
if os.path.exists(name):
v = np.load(name)
else:
print('Optimization of v start.')
v = adam(size, img0_src, img1_src, v, p0_src, p1_src, lr=lr_v, tol=tol_v,
render=render, tol_count=tol_count_v, lambda_tps=lambda_tps,
gamma_ui=gamma_ui, save_dir=save_dir)
name = os.path.join(save_dir, 'w{:03d}'.format(size))
if os.path.exists(name):
w = np.load(w)
else:
print('Optimization of w start.')
w = adam_w(size, w, v, lr=lr_w, tol=tol_w, tol_count=tol_count_w,
save_dir=save_dir)
v_final = resize_v(v=v, size=img0_src.shape[0], size_x=img0_src.shape[1])
w_final = resize_v(v=w, size=img0_src.shape[0], size_x=img0_src.shape[1])
img1 = cv2.resize(img1_src, (img0_src.shape[0], img0_src.shape[1]))
render_path = os.path.join(save_dir, render_name)
render_animation(img0_src, img1, v_final, w=w_final, steps=render_steps,
time=render_time, file_name=render_path) | image_morphing/morpher.py | import cv2
from image_morphing.np import np, GPU
from image_morphing.utils import load_points, resize_v
from image_morphing.render import render_animation
from image_morphing.optimize_v import adam
from image_morphing.quadratic_motion_path import adam_w
import os
def image_morphing(img0_path, img1_path, p0_path, p1_path, vmax_size=32, render_name='animation.mov',
lr_v=7e-2, tol_v=1e-1, lr_w=7e-2, tol_w=1e-3, lambda_tps=1e-3, gamma_ui=1e2,
tol_count_v=20, tol_count_w=3, render=False, render_steps=60, render_time=1,
save_dir='.cache'):
img0_src = cv2.imread(img0_path)
img1_src = cv2.imread(img1_path)
p0_src = load_points(p0_path)
p1_src = load_points(p1_path)
size = 8
v = np.random.randn(size, size, 2)
w = np.random.randn(size, size, 2)
# sizes = np.arange(8, vmax_size + 1, 8)
sizes = 2 ** np.arange(3, 10)
sizes = sizes[sizes <= vmax_size]
if GPU:
sizes = np.asnumpy(sizes)
for size in sizes:
print('\nOptimization size {:3d} start.'.format(size))
name = os.path.join(save_dir, 'v{:03d}'.format(size))
if os.path.exists(name):
v = np.load(name)
else:
print('Optimization of v start.')
v = adam(size, img0_src, img1_src, v, p0_src, p1_src, lr=lr_v, tol=tol_v,
render=render, tol_count=tol_count_v, lambda_tps=lambda_tps,
gamma_ui=gamma_ui, save_dir=save_dir)
name = os.path.join(save_dir, 'w{:03d}'.format(size))
if os.path.exists(name):
w = np.load(w)
else:
print('Optimization of w start.')
w = adam_w(size, w, v, lr=lr_w, tol=tol_w, tol_count=tol_count_w,
save_dir=save_dir)
v_final = resize_v(v=v, size=img0_src.shape[0], size_x=img0_src.shape[1])
w_final = resize_v(v=w, size=img0_src.shape[0], size_x=img0_src.shape[1])
img1 = cv2.resize(img1_src, (img0_src.shape[0], img0_src.shape[1]))
render_path = os.path.join(save_dir, render_name)
render_animation(img0_src, img1, v_final, w=w_final, steps=render_steps,
time=render_time, file_name=render_path) | 0.386532 | 0.24271 |
import os
from pathlib import Path
import albumentations as A
import cv2
import matplotlib.pyplot as plt
import torch
from albumentations.pytorch import ToTensorV2
from ignite.contrib.handlers import ProgressBar
from ignite.contrib.metrics import GpuInfo
from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer
from ignite.metrics import Accuracy, Loss
from segmentation_models_pytorch.losses import DiceLoss
from torch.optim import SGD
from torch.utils.data import DataLoader, Dataset
from unet.model import Unet
dataset = Path("/home/dylan/Dropbox/Projects/datasets/aerial_segmentation/dataset/semantic_drone_dataset")
imgs = dataset / "original_images"
masks = dataset / "label_images_semantic"
class SemanticDroneDataset(Dataset):
def __init__(self, images_path, masks_path):
super().__init__()
self.images_path, self.masks_path = images_path, masks_path
self.image_names = self._get_matched_images()
self.output_transform = A.Compose(
[
A.RandomCrop(height=256, width=256, always_apply=True),
# A.Resize(height=256, width=256, always_apply=True),
A.ToFloat(always_apply=True),
ToTensorV2(always_apply=True),
],
)
def _get_matched_images(self):
matched_image_names = []
for img_name in self.images_path.glob(f"*.jpg"):
label_name = img_name.with_suffix(".png").name
labels = list(self.masks_path.glob(label_name))
if len(labels) == 1:
matched_image_names.append(img_name.stem)
return matched_image_names
def __len__(self):
return len(self.image_names)
def __getitem__(self, item):
filename = self.image_names[item]
img_path, mask_path = self.images_path / filename, self.masks_path / filename
img = cv2.imread(str(img_path.with_suffix(".jpg")), cv2.IMREAD_COLOR)
mask = cv2.imread(str(mask_path.with_suffix(".png")), cv2.IMREAD_GRAYSCALE)
aug = self.output_transform(image=img, mask=mask)
return aug["image"], aug["mask"].to(torch.int64)
def show_plot(self, item):
img, mask = self[0]
img, mask = img.numpy(), mask.numpy()
fig, (ax1, ax2) = plt.subplots(2, 1)
ax1.imshow(img)
ax2.imshow(mask)
plt.tight_layout()
plt.show()
train_dataset = SemanticDroneDataset(imgs, masks)
img, mask = train_dataset[0]
train_loader = DataLoader(train_dataset, batch_size=8, shuffle=True, num_workers=os.cpu_count())
model = Unet(3, 24, attention=True)
criterion = DiceLoss("multiclass")
device = "cuda"
model.to(device) # Move model before creating optimizer
optimizer = SGD(model.parameters(), lr=0.001, momentum=0.1)
trainer = create_supervised_trainer(model, optimizer, criterion, device=device)
evaluator = create_supervised_evaluator(model, metrics={"accuracy": Accuracy(), "loss": Loss(criterion)}, device=device)
GpuInfo().attach(trainer, name="gpu")
pbar = ProgressBar(persist=True)
pbar.attach(trainer, metric_names="all")
@trainer.on(Events.EPOCH_COMPLETED)
def log_training_results(engine):
evaluator.run(train_loader)
metrics = evaluator.state.metrics
avg_accuracy = metrics["accuracy"]
avg_loss = metrics["loss"]
pbar.log_message(
f"Training Results - Epoch: {engine.state.epoch} Avg accuracy: {avg_accuracy:.2f} Avg loss: {avg_loss:.2f}"
)
trainer.run(train_loader, max_epochs=3) | unet/train.py | import os
from pathlib import Path
import albumentations as A
import cv2
import matplotlib.pyplot as plt
import torch
from albumentations.pytorch import ToTensorV2
from ignite.contrib.handlers import ProgressBar
from ignite.contrib.metrics import GpuInfo
from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer
from ignite.metrics import Accuracy, Loss
from segmentation_models_pytorch.losses import DiceLoss
from torch.optim import SGD
from torch.utils.data import DataLoader, Dataset
from unet.model import Unet
dataset = Path("/home/dylan/Dropbox/Projects/datasets/aerial_segmentation/dataset/semantic_drone_dataset")
imgs = dataset / "original_images"
masks = dataset / "label_images_semantic"
class SemanticDroneDataset(Dataset):
def __init__(self, images_path, masks_path):
super().__init__()
self.images_path, self.masks_path = images_path, masks_path
self.image_names = self._get_matched_images()
self.output_transform = A.Compose(
[
A.RandomCrop(height=256, width=256, always_apply=True),
# A.Resize(height=256, width=256, always_apply=True),
A.ToFloat(always_apply=True),
ToTensorV2(always_apply=True),
],
)
def _get_matched_images(self):
matched_image_names = []
for img_name in self.images_path.glob(f"*.jpg"):
label_name = img_name.with_suffix(".png").name
labels = list(self.masks_path.glob(label_name))
if len(labels) == 1:
matched_image_names.append(img_name.stem)
return matched_image_names
def __len__(self):
return len(self.image_names)
def __getitem__(self, item):
filename = self.image_names[item]
img_path, mask_path = self.images_path / filename, self.masks_path / filename
img = cv2.imread(str(img_path.with_suffix(".jpg")), cv2.IMREAD_COLOR)
mask = cv2.imread(str(mask_path.with_suffix(".png")), cv2.IMREAD_GRAYSCALE)
aug = self.output_transform(image=img, mask=mask)
return aug["image"], aug["mask"].to(torch.int64)
def show_plot(self, item):
img, mask = self[0]
img, mask = img.numpy(), mask.numpy()
fig, (ax1, ax2) = plt.subplots(2, 1)
ax1.imshow(img)
ax2.imshow(mask)
plt.tight_layout()
plt.show()
train_dataset = SemanticDroneDataset(imgs, masks)
img, mask = train_dataset[0]
train_loader = DataLoader(train_dataset, batch_size=8, shuffle=True, num_workers=os.cpu_count())
model = Unet(3, 24, attention=True)
criterion = DiceLoss("multiclass")
device = "cuda"
model.to(device) # Move model before creating optimizer
optimizer = SGD(model.parameters(), lr=0.001, momentum=0.1)
trainer = create_supervised_trainer(model, optimizer, criterion, device=device)
evaluator = create_supervised_evaluator(model, metrics={"accuracy": Accuracy(), "loss": Loss(criterion)}, device=device)
GpuInfo().attach(trainer, name="gpu")
pbar = ProgressBar(persist=True)
pbar.attach(trainer, metric_names="all")
@trainer.on(Events.EPOCH_COMPLETED)
def log_training_results(engine):
evaluator.run(train_loader)
metrics = evaluator.state.metrics
avg_accuracy = metrics["accuracy"]
avg_loss = metrics["loss"]
pbar.log_message(
f"Training Results - Epoch: {engine.state.epoch} Avg accuracy: {avg_accuracy:.2f} Avg loss: {avg_loss:.2f}"
)
trainer.run(train_loader, max_epochs=3) | 0.782164 | 0.356587 |
import builtins
import keyword
import sys
import textwrap
from typing import Any, List, Optional, TextIO, Tuple
import pydantic
from . import utils
def build_from_document(doc: dict) -> dict:
return build_models(doc["schemas"])
def build_models(schemas: dict) -> dict:
"""Create schema models from an API service discovery document."""
parser = SchemaParser(schemas)
global_context = dict(globals())
local_context = {}
for name, model_string in parser.model_defs.items():
code_obj = compile(model_string, "<string>", "exec")
exec(code_obj, global_context, local_context)
for name in local_context:
# Resolve ForwardRef types to actual models.
local_context[name].update_forward_refs(**local_context)
return local_context
def write_models(schemas: dict, fh: TextIO):
"""Create data models for schemas and write them to a file."""
parser = SchemaParser(schemas)
value = "\n\n".join(parser.model_defs.values())
fh.write(value)
class SchemaParser:
simple_types = {
# There's also "object" and "array" which are special-cased.
# https://tools.ietf.org/html/draft-zyp-json-schema-03#section-5.1
"any": "Any",
"boolean": "bool",
"integer": "int",
"null": "None",
"number": "float",
"string": "str",
}
python_keywords = set(keyword.kwlist) | set(dir(builtins))
def __init__(self, schemas: dict):
# Parsing a schema may result in several data models for the nested
# objects, so we use the model_defs dict to collect the results.
self.model_defs = {}
for name, schema in schemas.items():
self.schema_as_string(schema, class_name=name)
def schema_as_string(self, schema: dict, class_name: Optional[str] = None):
"""Make a string for a data class from a schema, that can be exec'd."""
indent = " " * 4
description = schema.get("description", "")
docstring = self.format_docstring(description, indent=indent)
type_ = schema.get("type")
id_ = schema.get("id")
# Items are (name, type_, default).
properties = []
if "properties" in schema:
for pname, pschema in schema["properties"].items():
pname = self.valid_property_name(pname)
prop_type, pdefault = self.parse_property(pschema, pname)
properties.append((pname, prop_type, pdefault))
# Some objects have no structure, e.g. storage#bucket which has "labels"
# which are arbitrary key/value pairs. Ignoring them for now.
if "additionalProperties" in schema:
pass
if not id_:
if class_name:
id_ = class_name
else:
# Make up a name for the model.
names = "".join(name.capitalize() for name, _, _ in properties)
id_ = "_" + names
result = f'''class {id_}(pydantic.BaseModel):\n{docstring}'''
for name, type_, default in properties:
if default:
line = f"{name}: {type_} = {default}"
else:
line = f"{name}: {type_}"
result += f"{indent}{line}\n"
# No class body, make it valid Python.
if not properties and not docstring:
result += f"{indent}pass\n"
self.model_defs[id_] = result
@classmethod
def valid_property_name(cls, name: str) -> str:
"""Make valid Python identifiers for a property name.
A name like "class" is a Python keyword so has to be converted. A name
like "next" is a built-in, so it can be confusing to have it re-defined
by a model.
"""
if name in cls.python_keywords:
name += "_"
return name
def parse_property(self, schema: dict,
name: str) -> Tuple[str, Optional[str]]:
"""Return the type (as a string) and default value (as string or None)."""
# Easy case.
try:
type_ = schema["type"]
except KeyError:
type_ = schema["$ref"]
if type_ in self.simple_types:
default = schema.get("default")
if default is not None:
default = repr(default)
py_type = self.simple_types[type_]
return py_type, default
elif type_ == "object":
class_name = f"_{name}"
self.schema_as_string(schema, class_name=class_name)
return f'"{class_name}"', None
elif type_ == "array":
items = schema["items"]
py_type, default = self.parse_property(items, name)
return f"List[{py_type}]", default
else:
# Must be a $ref.
return f'"{type_}"', None
@classmethod
def format_docstring(cls, text: str, indent: str = "") -> str:
if text:
wrapper = textwrap.TextWrapper(subsequent_indent=indent)
result = wrapper.fill(text)
result = f'{indent}"""{result}'
max_line_length = 80
if len(result) > (max_line_length - len('"""')):
result += f'\n{indent}"""\n'
else:
result += '"""\n'
else:
result = ""
return result
def main(argv: list):
"""Write API schema classes for a service discovery document to STDOUT."""
location = argv[1]
doc = utils.load_location(location)
write_models(doc["schemas"], sys.stdout) | src/verydisco/schemas.py | import builtins
import keyword
import sys
import textwrap
from typing import Any, List, Optional, TextIO, Tuple
import pydantic
from . import utils
def build_from_document(doc: dict) -> dict:
return build_models(doc["schemas"])
def build_models(schemas: dict) -> dict:
"""Create schema models from an API service discovery document."""
parser = SchemaParser(schemas)
global_context = dict(globals())
local_context = {}
for name, model_string in parser.model_defs.items():
code_obj = compile(model_string, "<string>", "exec")
exec(code_obj, global_context, local_context)
for name in local_context:
# Resolve ForwardRef types to actual models.
local_context[name].update_forward_refs(**local_context)
return local_context
def write_models(schemas: dict, fh: TextIO):
"""Create data models for schemas and write them to a file."""
parser = SchemaParser(schemas)
value = "\n\n".join(parser.model_defs.values())
fh.write(value)
class SchemaParser:
simple_types = {
# There's also "object" and "array" which are special-cased.
# https://tools.ietf.org/html/draft-zyp-json-schema-03#section-5.1
"any": "Any",
"boolean": "bool",
"integer": "int",
"null": "None",
"number": "float",
"string": "str",
}
python_keywords = set(keyword.kwlist) | set(dir(builtins))
def __init__(self, schemas: dict):
# Parsing a schema may result in several data models for the nested
# objects, so we use the model_defs dict to collect the results.
self.model_defs = {}
for name, schema in schemas.items():
self.schema_as_string(schema, class_name=name)
def schema_as_string(self, schema: dict, class_name: Optional[str] = None):
"""Make a string for a data class from a schema, that can be exec'd."""
indent = " " * 4
description = schema.get("description", "")
docstring = self.format_docstring(description, indent=indent)
type_ = schema.get("type")
id_ = schema.get("id")
# Items are (name, type_, default).
properties = []
if "properties" in schema:
for pname, pschema in schema["properties"].items():
pname = self.valid_property_name(pname)
prop_type, pdefault = self.parse_property(pschema, pname)
properties.append((pname, prop_type, pdefault))
# Some objects have no structure, e.g. storage#bucket which has "labels"
# which are arbitrary key/value pairs. Ignoring them for now.
if "additionalProperties" in schema:
pass
if not id_:
if class_name:
id_ = class_name
else:
# Make up a name for the model.
names = "".join(name.capitalize() for name, _, _ in properties)
id_ = "_" + names
result = f'''class {id_}(pydantic.BaseModel):\n{docstring}'''
for name, type_, default in properties:
if default:
line = f"{name}: {type_} = {default}"
else:
line = f"{name}: {type_}"
result += f"{indent}{line}\n"
# No class body, make it valid Python.
if not properties and not docstring:
result += f"{indent}pass\n"
self.model_defs[id_] = result
@classmethod
def valid_property_name(cls, name: str) -> str:
"""Make valid Python identifiers for a property name.
A name like "class" is a Python keyword so has to be converted. A name
like "next" is a built-in, so it can be confusing to have it re-defined
by a model.
"""
if name in cls.python_keywords:
name += "_"
return name
def parse_property(self, schema: dict,
name: str) -> Tuple[str, Optional[str]]:
"""Return the type (as a string) and default value (as string or None)."""
# Easy case.
try:
type_ = schema["type"]
except KeyError:
type_ = schema["$ref"]
if type_ in self.simple_types:
default = schema.get("default")
if default is not None:
default = repr(default)
py_type = self.simple_types[type_]
return py_type, default
elif type_ == "object":
class_name = f"_{name}"
self.schema_as_string(schema, class_name=class_name)
return f'"{class_name}"', None
elif type_ == "array":
items = schema["items"]
py_type, default = self.parse_property(items, name)
return f"List[{py_type}]", default
else:
# Must be a $ref.
return f'"{type_}"', None
@classmethod
def format_docstring(cls, text: str, indent: str = "") -> str:
if text:
wrapper = textwrap.TextWrapper(subsequent_indent=indent)
result = wrapper.fill(text)
result = f'{indent}"""{result}'
max_line_length = 80
if len(result) > (max_line_length - len('"""')):
result += f'\n{indent}"""\n'
else:
result += '"""\n'
else:
result = ""
return result
def main(argv: list):
"""Write API schema classes for a service discovery document to STDOUT."""
location = argv[1]
doc = utils.load_location(location)
write_models(doc["schemas"], sys.stdout) | 0.656328 | 0.241959 |
from __future__ import annotations
from typing import Tuple, Union, Any, Optional
from engine.threed.base.plane import AbstractPlane
from engine.threed.base.vector import AbstractVector
from engine.threed.base.point import AbstractPoint
from engine.threed.base.line import AbstractLine
from engine.threed.point import Point
from engine.tools.options import Options
class Plane(AbstractPlane):
"""Mathmatical 3d plane."""
def __repr__(self) -> str:
"""
Returns:
str: readable representation of the values of this class.
"""
text = "Plane(position=%(position)s, " % self.__dict__
text += "direction_a=%(direction_a)s, direction_b=%(direction_b)s)" % self.__dict__
return text
def __eq__(self, other: object) -> bool:
"""
Args:
other(Plane): another plane to use for comparison.
Returns:
bool: True when both planes are equal otherwise false
"""
if isinstance(other, Plane):
return self.position == other.position and \
self.direction_a == other.direction_a and \
self.direction_b == other.direction_b
return False
def point(self, factor_a: Union[int, float], factor_b: Union[int, float]) -> AbstractPoint:
"""
Provide point on plane by two factors (0=start point, 1=end point).
Args:
factor_a(float or int): the factor to control which point (0=start point, 1=end point).
factor_b(float or int): the factor to control which point (0=start point, 1=end point).
Raises:
TypeError: when given parameter is not an int or a float
"""
if isinstance(factor_a, (int, float)) and isinstance(factor_b, (int, float)):
return self.position \
+ self.direction_a.scaled(factor_a) \
+ self.direction_b.scaled(factor_b)
raise TypeError("Not all parameter are either an int or a float")
def intersection(self, other: Any) -> Optional[AbstractPoint]:
"""
Calculate intersection between given plane and a line.
Args:
other(AbstractLine): line to find intersection point.
Returns:
Point: found intersection point or None if not found.
Raises:
TypeError: when given parameter is not a line.
Note:
The method does not check whether a found point lies inbetween
the start point and end point of the line or inside the limits
defined for the plane.
"""
if isinstance(other, AbstractLine):
line = other
# p1 + a * v1 = p2 + b * v2 + c * v3 | - p1
# a * v1 = (p2 - p1) + b * v2 + c * v3 | x v3
# a * (v1 x v3) = (p2 - p1) x v3 + b * (v2 x v3) | x (v2 x v3)
# a * (v1 x v3) x (v2 x v3) = ((p2 - p1) x v3)) x (v2 x v3)
vector_a = line.direction.cross_product(self.direction_b) \
.cross_product(self.direction_a.cross_product(self.direction_b))
vector_b = (self.position - line.position).cross_product(self.direction_b) \
.cross_product(self.direction_a.cross_product(self.direction_b))
if abs(vector_a.x) > Options.PRECISION:
return line.point(vector_b.x / vector_a.x)
if abs(vector_a.y) > Options.PRECISION:
return line.point(vector_b.y / vector_a.y)
if abs(vector_a.z) > Options.PRECISION:
return line.point(vector_b.z / vector_a.z)
# no intersection
return None
raise TypeError("Given parameter is not a line")
def has_point(self, point: AbstractPoint, exact_match: bool = True) -> bool:
"""
Args:
point(AbstractPoint): point to check to be on the plane.
exact_match(bool): when true (default) both factors have to be in range(0.0..1.0)
Returns:
bool: True when point is on the plane.
Raises:
TypeError: if given Parameter is not a point
"""
factor_a, factor_b = self.calculate_point_factors(point)
if factor_a is not None and factor_b is not None:
return not exact_match or (0.0 <= factor_a <= 1.0 and 0.0 <= factor_b <= 1.0)
return False
def normal(self) -> AbstractVector:
"""
Returns:
AbstractVector: plane normal.
"""
return self.direction_a.cross_product(self.direction_b).normalized()
def calculate_point_factors(
self, point: AbstractPoint) -> Tuple[Optional[float], Optional[float]]:
"""
Args:
point(Point): point to check to be on the plane.
exact_match(bool): when true (default) both factors have to be in range(0.0..1.0)
Returns:
Tuple[float, float]: tuple of two float factors or None's
if no intersection is possible.
Raises:
TypeError: if given Parameter is not a point
"""
if isinstance(point, AbstractPoint):
# p1 = p2 + a * v1 + b * v2 | -p2
# p1 - p2 = a * v1 + b * v2
# 1) -b * v2
# (p1 - p2) - b * v2 = a * v1 | x v2
# (p1 - p2) x v2 = a * v1 x v2
# 2) -a * v1
# (p1 - p2) - a * v1 = b * v2 | x v1
# (p1 - p2) x v1 = b * v2 x v1
vector_a = (point - self.position).cross_product(self.direction_b)
vector_b = self.direction_a.cross_product(self.direction_b)
factor_a = Plane.factor_check(vector_a, vector_b)
factor_b = None
if factor_a is not None:
vector_c = (point - self.position).cross_product(self.direction_a)
vector_d = self.direction_b.cross_product(self.direction_a)
factor_b = Plane.factor_check(vector_c, vector_d)
return factor_a, factor_b
raise TypeError("Given parameter is not a point")
@staticmethod
def factor_check(vector_a: AbstractVector, vector_b: AbstractVector) -> Optional[float]:
"""
Args:
vector_a(AbstractVector): first vector
vector_b(AbstractVector): second vector to use for division
Returns:
float: factor if found otherwise None
"""
factor = None
if abs(vector_b.x) > Options.PRECISION:
factor = vector_a.x / vector_b.x
elif not vector_a.x == vector_b.x:
return None
if abs(vector_b.y) > Options.PRECISION:
factor = vector_a.y / vector_b.y
elif not vector_a.y == vector_b.y:
return None
if abs(vector_b.z) > Options.PRECISION:
factor = vector_a.z / vector_b.z
elif not vector_b.z == vector_a.z:
return None
return factor
def projection_point(self, point: AbstractPoint) -> AbstractPoint:
"""
Projection of point on given plane.
Args:
plane(AbstractPlane): plane to use for point -> plane projection.
Returns:
AbstractPoint: projection point onto given plane.
"""
if isinstance(point, AbstractPoint):
vector_1 = point - self.position
vector_2 = self.normal()
return Point.from_vector(vector_1 - vector_2.scaled(vector_1.dot_product(vector_2)))
raise TypeError("Given parameter is not a point") | engine/threed/plane.py | from __future__ import annotations
from typing import Tuple, Union, Any, Optional
from engine.threed.base.plane import AbstractPlane
from engine.threed.base.vector import AbstractVector
from engine.threed.base.point import AbstractPoint
from engine.threed.base.line import AbstractLine
from engine.threed.point import Point
from engine.tools.options import Options
class Plane(AbstractPlane):
"""Mathmatical 3d plane."""
def __repr__(self) -> str:
"""
Returns:
str: readable representation of the values of this class.
"""
text = "Plane(position=%(position)s, " % self.__dict__
text += "direction_a=%(direction_a)s, direction_b=%(direction_b)s)" % self.__dict__
return text
def __eq__(self, other: object) -> bool:
"""
Args:
other(Plane): another plane to use for comparison.
Returns:
bool: True when both planes are equal otherwise false
"""
if isinstance(other, Plane):
return self.position == other.position and \
self.direction_a == other.direction_a and \
self.direction_b == other.direction_b
return False
def point(self, factor_a: Union[int, float], factor_b: Union[int, float]) -> AbstractPoint:
"""
Provide point on plane by two factors (0=start point, 1=end point).
Args:
factor_a(float or int): the factor to control which point (0=start point, 1=end point).
factor_b(float or int): the factor to control which point (0=start point, 1=end point).
Raises:
TypeError: when given parameter is not an int or a float
"""
if isinstance(factor_a, (int, float)) and isinstance(factor_b, (int, float)):
return self.position \
+ self.direction_a.scaled(factor_a) \
+ self.direction_b.scaled(factor_b)
raise TypeError("Not all parameter are either an int or a float")
def intersection(self, other: Any) -> Optional[AbstractPoint]:
"""
Calculate intersection between given plane and a line.
Args:
other(AbstractLine): line to find intersection point.
Returns:
Point: found intersection point or None if not found.
Raises:
TypeError: when given parameter is not a line.
Note:
The method does not check whether a found point lies inbetween
the start point and end point of the line or inside the limits
defined for the plane.
"""
if isinstance(other, AbstractLine):
line = other
# p1 + a * v1 = p2 + b * v2 + c * v3 | - p1
# a * v1 = (p2 - p1) + b * v2 + c * v3 | x v3
# a * (v1 x v3) = (p2 - p1) x v3 + b * (v2 x v3) | x (v2 x v3)
# a * (v1 x v3) x (v2 x v3) = ((p2 - p1) x v3)) x (v2 x v3)
vector_a = line.direction.cross_product(self.direction_b) \
.cross_product(self.direction_a.cross_product(self.direction_b))
vector_b = (self.position - line.position).cross_product(self.direction_b) \
.cross_product(self.direction_a.cross_product(self.direction_b))
if abs(vector_a.x) > Options.PRECISION:
return line.point(vector_b.x / vector_a.x)
if abs(vector_a.y) > Options.PRECISION:
return line.point(vector_b.y / vector_a.y)
if abs(vector_a.z) > Options.PRECISION:
return line.point(vector_b.z / vector_a.z)
# no intersection
return None
raise TypeError("Given parameter is not a line")
def has_point(self, point: AbstractPoint, exact_match: bool = True) -> bool:
"""
Args:
point(AbstractPoint): point to check to be on the plane.
exact_match(bool): when true (default) both factors have to be in range(0.0..1.0)
Returns:
bool: True when point is on the plane.
Raises:
TypeError: if given Parameter is not a point
"""
factor_a, factor_b = self.calculate_point_factors(point)
if factor_a is not None and factor_b is not None:
return not exact_match or (0.0 <= factor_a <= 1.0 and 0.0 <= factor_b <= 1.0)
return False
def normal(self) -> AbstractVector:
"""
Returns:
AbstractVector: plane normal.
"""
return self.direction_a.cross_product(self.direction_b).normalized()
def calculate_point_factors(
self, point: AbstractPoint) -> Tuple[Optional[float], Optional[float]]:
"""
Args:
point(Point): point to check to be on the plane.
exact_match(bool): when true (default) both factors have to be in range(0.0..1.0)
Returns:
Tuple[float, float]: tuple of two float factors or None's
if no intersection is possible.
Raises:
TypeError: if given Parameter is not a point
"""
if isinstance(point, AbstractPoint):
# p1 = p2 + a * v1 + b * v2 | -p2
# p1 - p2 = a * v1 + b * v2
# 1) -b * v2
# (p1 - p2) - b * v2 = a * v1 | x v2
# (p1 - p2) x v2 = a * v1 x v2
# 2) -a * v1
# (p1 - p2) - a * v1 = b * v2 | x v1
# (p1 - p2) x v1 = b * v2 x v1
vector_a = (point - self.position).cross_product(self.direction_b)
vector_b = self.direction_a.cross_product(self.direction_b)
factor_a = Plane.factor_check(vector_a, vector_b)
factor_b = None
if factor_a is not None:
vector_c = (point - self.position).cross_product(self.direction_a)
vector_d = self.direction_b.cross_product(self.direction_a)
factor_b = Plane.factor_check(vector_c, vector_d)
return factor_a, factor_b
raise TypeError("Given parameter is not a point")
@staticmethod
def factor_check(vector_a: AbstractVector, vector_b: AbstractVector) -> Optional[float]:
"""
Args:
vector_a(AbstractVector): first vector
vector_b(AbstractVector): second vector to use for division
Returns:
float: factor if found otherwise None
"""
factor = None
if abs(vector_b.x) > Options.PRECISION:
factor = vector_a.x / vector_b.x
elif not vector_a.x == vector_b.x:
return None
if abs(vector_b.y) > Options.PRECISION:
factor = vector_a.y / vector_b.y
elif not vector_a.y == vector_b.y:
return None
if abs(vector_b.z) > Options.PRECISION:
factor = vector_a.z / vector_b.z
elif not vector_b.z == vector_a.z:
return None
return factor
def projection_point(self, point: AbstractPoint) -> AbstractPoint:
"""
Projection of point on given plane.
Args:
plane(AbstractPlane): plane to use for point -> plane projection.
Returns:
AbstractPoint: projection point onto given plane.
"""
if isinstance(point, AbstractPoint):
vector_1 = point - self.position
vector_2 = self.normal()
return Point.from_vector(vector_1 - vector_2.scaled(vector_1.dot_product(vector_2)))
raise TypeError("Given parameter is not a point") | 0.968306 | 0.568655 |
import logging
import pyarrow as pa
import pyarrow.csv as pv
import pyarrow.parquet as pq
from dataset_builder.exceptions.exceptions import BuilderStepError
logger = logging.getLogger()
def _get_read_options():
return pv.ReadOptions(
skip_rows=0,
encoding="utf8",
column_names=[
"unit_id", "value", "start", "stop",
"start_year", "start_epoch_days", "stop_epoch_days"
]
)
def _create_table(csv_convert_options: str, csv_parse_options: str,
data_path: str) -> pa.Table:
table = pv.read_csv(
input_file=data_path,
read_options=_get_read_options(),
parse_options=csv_parse_options,
convert_options=csv_convert_options
)
return table
def _create_list_of_fields(data_type: str, partitioned: bool = False) -> list:
types = dict(
STRING=pa.string(),
LONG=pa.int64(),
DOUBLE=pa.float64(),
INSTANT=pa.int64(),
DATE=pa.int64()
)
if data_type.upper() not in types:
raise ValueError(f'Unknown datatype {data_type}')
fields = [
pa.field(name='unit_id', type=pa.uint64(), nullable=False),
pa.field(name='value', type=types[data_type.upper()], nullable=False),
pa.field(name='start_epoch_days', type=pa.int16(), nullable=False),
pa.field(name='stop_epoch_days', type=pa.int16(), nullable=False)
]
if partitioned:
start_year_field = [
pa.field(name='start_year', type=pa.string(), nullable=True)
]
fields = start_year_field + fields
return fields
def _create_table_for_simple_parquet(data_path: str,
data_type: str) -> pa.Table:
data_schema = pa.schema(_create_list_of_fields(data_type))
csv_convert_options = pv.ConvertOptions(
column_types=data_schema,
include_columns=[
"unit_id", "value", "start_epoch_days", "stop_epoch_days"
]
)
return _create_table(
csv_convert_options, pv.ParseOptions(delimiter=';'), data_path
)
def _create_table_for_partitioned_parquet(data_path: str,
data_type: str) -> pa.Table:
data_schema = pa.schema(_create_list_of_fields(data_type, True))
csv_convert_options = pv.ConvertOptions(
column_types=data_schema,
include_columns=[
"unit_id", "value", "start_year",
"start_epoch_days", "stop_epoch_days"
]
)
return _create_table(
csv_convert_options, pv.ParseOptions(delimiter=';'), data_path
)
def _convert_csv_to_simple_parquet(csv_data_path: str, data_type: str) -> str:
parquet_file_path = csv_data_path.replace(
'_enhanced.csv', '__0_0.parquet'
)
logger.info(
f"Converts csv {csv_data_path} "
f"to simple parquet {parquet_file_path}"
)
table = _create_table_for_simple_parquet(csv_data_path, data_type)
logger.info(f"Number of rows in parquet file: {table.num_rows}")
pq.write_table(table, parquet_file_path)
logger.info("Converted csv to simple parquet successfully")
return parquet_file_path
def _convert_csv_to_partitioned_parquet(csv_data_path: str,
data_type: str) -> str:
parquet_partition_path = csv_data_path.replace(
'_enhanced.csv', '__0_0'
)
logger.info(
f"Converts csv {csv_data_path} "
f"to partitioned parquet {parquet_partition_path}"
)
table = _create_table_for_partitioned_parquet(csv_data_path, data_type)
logger.info(f"Number of rows in parquet file: {table.num_rows}")
metadata_collector = []
pq.write_to_dataset(
table,
root_path=parquet_partition_path,
partition_cols=['start_year'],
metadata_collector=metadata_collector
)
logger.info("Converted csv to partitioned parquet successfully")
return parquet_partition_path
def run(csv_data_path: str, temporality_type: str, data_type: str) -> str:
"""
Converts a csv file to parquet format. Will partition the parquet
if given temporality type is "STATUS" or "ACCUMULATED".
"""
try:
logger.info(
f'''
Converting {csv_data_path} to parquet
data_type: {data_type}
temporality_type: {temporality_type}
'''
)
if temporality_type in ["STATUS", "ACCUMULATED"]:
parquet_path = _convert_csv_to_partitioned_parquet(
csv_data_path, data_type
)
logger.info(
'Converted csv to partitioned parquet and wrote to '
f'{parquet_path}'
)
else:
parquet_path = _convert_csv_to_simple_parquet(
csv_data_path, data_type
)
logger.info(
'Converted csv to parquet and wrote to '
f'{parquet_path}'
)
return parquet_path
except Exception as e:
logger.error(f'Error during conversion: {str(e)}')
raise BuilderStepError('Failed to convert dataset') | dataset_builder/steps/dataset_converter.py | import logging
import pyarrow as pa
import pyarrow.csv as pv
import pyarrow.parquet as pq
from dataset_builder.exceptions.exceptions import BuilderStepError
logger = logging.getLogger()
def _get_read_options():
return pv.ReadOptions(
skip_rows=0,
encoding="utf8",
column_names=[
"unit_id", "value", "start", "stop",
"start_year", "start_epoch_days", "stop_epoch_days"
]
)
def _create_table(csv_convert_options: str, csv_parse_options: str,
data_path: str) -> pa.Table:
table = pv.read_csv(
input_file=data_path,
read_options=_get_read_options(),
parse_options=csv_parse_options,
convert_options=csv_convert_options
)
return table
def _create_list_of_fields(data_type: str, partitioned: bool = False) -> list:
types = dict(
STRING=pa.string(),
LONG=pa.int64(),
DOUBLE=pa.float64(),
INSTANT=pa.int64(),
DATE=pa.int64()
)
if data_type.upper() not in types:
raise ValueError(f'Unknown datatype {data_type}')
fields = [
pa.field(name='unit_id', type=pa.uint64(), nullable=False),
pa.field(name='value', type=types[data_type.upper()], nullable=False),
pa.field(name='start_epoch_days', type=pa.int16(), nullable=False),
pa.field(name='stop_epoch_days', type=pa.int16(), nullable=False)
]
if partitioned:
start_year_field = [
pa.field(name='start_year', type=pa.string(), nullable=True)
]
fields = start_year_field + fields
return fields
def _create_table_for_simple_parquet(data_path: str,
data_type: str) -> pa.Table:
data_schema = pa.schema(_create_list_of_fields(data_type))
csv_convert_options = pv.ConvertOptions(
column_types=data_schema,
include_columns=[
"unit_id", "value", "start_epoch_days", "stop_epoch_days"
]
)
return _create_table(
csv_convert_options, pv.ParseOptions(delimiter=';'), data_path
)
def _create_table_for_partitioned_parquet(data_path: str,
data_type: str) -> pa.Table:
data_schema = pa.schema(_create_list_of_fields(data_type, True))
csv_convert_options = pv.ConvertOptions(
column_types=data_schema,
include_columns=[
"unit_id", "value", "start_year",
"start_epoch_days", "stop_epoch_days"
]
)
return _create_table(
csv_convert_options, pv.ParseOptions(delimiter=';'), data_path
)
def _convert_csv_to_simple_parquet(csv_data_path: str, data_type: str) -> str:
parquet_file_path = csv_data_path.replace(
'_enhanced.csv', '__0_0.parquet'
)
logger.info(
f"Converts csv {csv_data_path} "
f"to simple parquet {parquet_file_path}"
)
table = _create_table_for_simple_parquet(csv_data_path, data_type)
logger.info(f"Number of rows in parquet file: {table.num_rows}")
pq.write_table(table, parquet_file_path)
logger.info("Converted csv to simple parquet successfully")
return parquet_file_path
def _convert_csv_to_partitioned_parquet(csv_data_path: str,
data_type: str) -> str:
parquet_partition_path = csv_data_path.replace(
'_enhanced.csv', '__0_0'
)
logger.info(
f"Converts csv {csv_data_path} "
f"to partitioned parquet {parquet_partition_path}"
)
table = _create_table_for_partitioned_parquet(csv_data_path, data_type)
logger.info(f"Number of rows in parquet file: {table.num_rows}")
metadata_collector = []
pq.write_to_dataset(
table,
root_path=parquet_partition_path,
partition_cols=['start_year'],
metadata_collector=metadata_collector
)
logger.info("Converted csv to partitioned parquet successfully")
return parquet_partition_path
def run(csv_data_path: str, temporality_type: str, data_type: str) -> str:
"""
Converts a csv file to parquet format. Will partition the parquet
if given temporality type is "STATUS" or "ACCUMULATED".
"""
try:
logger.info(
f'''
Converting {csv_data_path} to parquet
data_type: {data_type}
temporality_type: {temporality_type}
'''
)
if temporality_type in ["STATUS", "ACCUMULATED"]:
parquet_path = _convert_csv_to_partitioned_parquet(
csv_data_path, data_type
)
logger.info(
'Converted csv to partitioned parquet and wrote to '
f'{parquet_path}'
)
else:
parquet_path = _convert_csv_to_simple_parquet(
csv_data_path, data_type
)
logger.info(
'Converted csv to parquet and wrote to '
f'{parquet_path}'
)
return parquet_path
except Exception as e:
logger.error(f'Error during conversion: {str(e)}')
raise BuilderStepError('Failed to convert dataset') | 0.461502 | 0.213039 |
from ion_functions.data.perf.test_performance import PerformanceTestCase, a_deca
from ion_functions.data import opt_functions as optfunc
import numpy as np
class TestOPTAAPerformance(PerformanceTestCase):
def setUp(self):
### realistic values for ac-s data packets:
n_wvl = 90 # number of wavelengths specified in DPS is incorrect
wvl_tile = n_wvl/6 # test arrays have 6 values
n_tbins = 35
tbin_tile = n_tbins/7 # test array has 7 tbin values
### test data common to both OPTATTN and OPTABSN
self.traw = 48355
self.tcal = 20.0
self.T = 12.0
self.S = 35.0
# tbin values are used in an interpolation algorithm; make sure
# their values are monotonic
self.tbins = np.array(range(n_tbins))
### test data for OPTATTN
self.c_sig = np.tile([150., 225., 200., 350., 450., 495.], (1, wvl_tile))
self.c_ref = np.tile([550., 540., 530., 520., 510., 500.], (1, wvl_tile))
self.c_off = np.tile([1.35, 1.30, 1.25, 1.20, 1.15, 1.10], (1, wvl_tile))
self.c_wvl = np.tile([510., 540., 580., 630., 670., 710.], (1, wvl_tile))
self.tc_arr = np.tile([
[0.0, -0.004929, -0.004611, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004611, -0.004418, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004418, -0.004355, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004355, -0.004131, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004131, -0.003422, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.003422, -0.002442, 0.0, 0.0, 0.0, 0.0]], (wvl_tile, tbin_tile))
### test data for OPTABSN
self.a_sig = np.tile([250., 300., 210., 430., 470., 495.], (1, wvl_tile))
self.a_ref = np.tile([450., 460., 470., 480., 490., 500.], (1, wvl_tile))
self.a_off = np.tile([0.35, 0.30, 0.25, 0.20, 0.15, 0.10], (1, wvl_tile))
self.a_wvl = np.tile([500., 550., 600., 650., 700., 715.], (1, wvl_tile))
# note, even though here ta_arr and tc_arr are identical, in actual calibration
# data they will be different.
self.ta_arr = np.tile([
[0.0, -0.004929, -0.004611, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004611, -0.004418, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004418, -0.004355, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004355, -0.004131, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004131, -0.003422, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.003422, -0.002442, 0.0, 0.0, 0.0, 0.0]], (wvl_tile, tbin_tile))
self.cpd_ts = np.tile([6.553771, 4.807914, 5.156010, 2.788715, 1.655607, 1.171965],
(1, wvl_tile))
# test data for ocr-507 (spectir = downwelling irradiance)
# counts offset scale mrsn
self.ocr_507 = np.transpose(np.array([
[2148370944, 2148377867.8, 2.09023117662E-07, 1.368],
[2200000000, 2148218092.4, 2.06543624674E-07, 1.410],
[2300000000, 2147607229.7, 2.12484770952E-07, 1.365],
[2400000000, 2147789959.1, 2.07241106309E-07, 1.354],
[2500000000, 2148047456.7, 1.99358530187E-07, 1.372],
[2600000000, 2147335412.8, 2.06033896796E-07, 1.404],
[2700000000, 2146998228.4, 2.14806273478E-07, 1.347]
]))
def test_opt_beam_attenuation(self):
stats = []
# create 10000 data packets
# common input variables: traw, Tcal, T, and PS
traw = np.tile(self.traw, (a_deca, 1))
tcal = np.tile(self.tcal, (a_deca, 1))
T = np.tile(self.T, (a_deca, 1))
PS = np.tile(self.S, (a_deca, 1))
tbins = np.tile(self.tbins, (a_deca, 1))
# variables unique to beam attenuation: 1D -> 2D
c_sig = np.tile(self.c_sig, (a_deca, 1))
c_ref = np.tile(self.c_ref, (a_deca, 1))
c_off = np.tile(self.c_off, (a_deca, 1))
c_wvl = np.tile(self.c_wvl, (a_deca, 1))
# variables unique to beam attenuation: 2D -> 3D
tc_arr = np.tile(self.tc_arr, (a_deca, 1, 1))
# timing test
self.profile(stats, optfunc.opt_beam_attenuation, c_ref, c_sig, traw, c_wvl, c_off, tcal,
tbins, tc_arr, T, PS)
def test_opt_optical_absorption(self):
stats = []
# create 10000 data packets
# common input variables: traw, Tcal, T, and PS
traw = np.tile(self.traw, (a_deca, 1))
tcal = np.tile(self.tcal, (a_deca, 1))
T = np.tile(self.T, (a_deca, 1))
PS = np.tile(self.S, (a_deca, 1))
tbins = np.tile(self.tbins, (a_deca, 1))
# variables unique to beam attenuation: 1D -> 2D
a_sig = np.tile(self.a_sig, (a_deca, 1))
a_ref = np.tile(self.a_ref, (a_deca, 1))
a_off = np.tile(self.a_off, (a_deca, 1))
a_wvl = np.tile(self.a_wvl, (a_deca, 1))
# variables unique to beam attenuation: 2D -> 3D
ta_arr = np.tile(self.ta_arr, (a_deca, 1, 1))
cpd_ts = np.tile(self.cpd_ts, (a_deca, 1))
c_wvl = np.tile(self.c_wvl, (a_deca, 1))
# timing test
self.profile(stats, optfunc.opt_optical_absorption, a_ref, a_sig, traw, a_wvl, a_off, tcal,
tbins, ta_arr, cpd_ts, c_wvl, T, PS)
def test_opt_ocr507_irradiance(self):
stats = []
# create 10000 data packets
counts = np.tile(self.ocr_507[0, :], (a_deca, 1))
offset = np.tile(self.ocr_507[1, :], (a_deca, 1))
scale = np.tile(self.ocr_507[2, :], (a_deca, 1))
immersion_factor = np.tile(self.ocr_507[3, :], (a_deca, 1))
# timing test
self.profile(stats, optfunc.opt_ocr507_irradiance, counts, offset, scale, immersion_factor) | ion_functions/data/perf/test_opt_performance.py | from ion_functions.data.perf.test_performance import PerformanceTestCase, a_deca
from ion_functions.data import opt_functions as optfunc
import numpy as np
class TestOPTAAPerformance(PerformanceTestCase):
def setUp(self):
### realistic values for ac-s data packets:
n_wvl = 90 # number of wavelengths specified in DPS is incorrect
wvl_tile = n_wvl/6 # test arrays have 6 values
n_tbins = 35
tbin_tile = n_tbins/7 # test array has 7 tbin values
### test data common to both OPTATTN and OPTABSN
self.traw = 48355
self.tcal = 20.0
self.T = 12.0
self.S = 35.0
# tbin values are used in an interpolation algorithm; make sure
# their values are monotonic
self.tbins = np.array(range(n_tbins))
### test data for OPTATTN
self.c_sig = np.tile([150., 225., 200., 350., 450., 495.], (1, wvl_tile))
self.c_ref = np.tile([550., 540., 530., 520., 510., 500.], (1, wvl_tile))
self.c_off = np.tile([1.35, 1.30, 1.25, 1.20, 1.15, 1.10], (1, wvl_tile))
self.c_wvl = np.tile([510., 540., 580., 630., 670., 710.], (1, wvl_tile))
self.tc_arr = np.tile([
[0.0, -0.004929, -0.004611, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004611, -0.004418, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004418, -0.004355, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004355, -0.004131, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004131, -0.003422, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.003422, -0.002442, 0.0, 0.0, 0.0, 0.0]], (wvl_tile, tbin_tile))
### test data for OPTABSN
self.a_sig = np.tile([250., 300., 210., 430., 470., 495.], (1, wvl_tile))
self.a_ref = np.tile([450., 460., 470., 480., 490., 500.], (1, wvl_tile))
self.a_off = np.tile([0.35, 0.30, 0.25, 0.20, 0.15, 0.10], (1, wvl_tile))
self.a_wvl = np.tile([500., 550., 600., 650., 700., 715.], (1, wvl_tile))
# note, even though here ta_arr and tc_arr are identical, in actual calibration
# data they will be different.
self.ta_arr = np.tile([
[0.0, -0.004929, -0.004611, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004611, -0.004418, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004418, -0.004355, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004355, -0.004131, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.004131, -0.003422, 0.0, 0.0, 0.0, 0.0],
[0.0, -0.003422, -0.002442, 0.0, 0.0, 0.0, 0.0]], (wvl_tile, tbin_tile))
self.cpd_ts = np.tile([6.553771, 4.807914, 5.156010, 2.788715, 1.655607, 1.171965],
(1, wvl_tile))
# test data for ocr-507 (spectir = downwelling irradiance)
# counts offset scale mrsn
self.ocr_507 = np.transpose(np.array([
[2148370944, 2148377867.8, 2.09023117662E-07, 1.368],
[2200000000, 2148218092.4, 2.06543624674E-07, 1.410],
[2300000000, 2147607229.7, 2.12484770952E-07, 1.365],
[2400000000, 2147789959.1, 2.07241106309E-07, 1.354],
[2500000000, 2148047456.7, 1.99358530187E-07, 1.372],
[2600000000, 2147335412.8, 2.06033896796E-07, 1.404],
[2700000000, 2146998228.4, 2.14806273478E-07, 1.347]
]))
def test_opt_beam_attenuation(self):
stats = []
# create 10000 data packets
# common input variables: traw, Tcal, T, and PS
traw = np.tile(self.traw, (a_deca, 1))
tcal = np.tile(self.tcal, (a_deca, 1))
T = np.tile(self.T, (a_deca, 1))
PS = np.tile(self.S, (a_deca, 1))
tbins = np.tile(self.tbins, (a_deca, 1))
# variables unique to beam attenuation: 1D -> 2D
c_sig = np.tile(self.c_sig, (a_deca, 1))
c_ref = np.tile(self.c_ref, (a_deca, 1))
c_off = np.tile(self.c_off, (a_deca, 1))
c_wvl = np.tile(self.c_wvl, (a_deca, 1))
# variables unique to beam attenuation: 2D -> 3D
tc_arr = np.tile(self.tc_arr, (a_deca, 1, 1))
# timing test
self.profile(stats, optfunc.opt_beam_attenuation, c_ref, c_sig, traw, c_wvl, c_off, tcal,
tbins, tc_arr, T, PS)
def test_opt_optical_absorption(self):
stats = []
# create 10000 data packets
# common input variables: traw, Tcal, T, and PS
traw = np.tile(self.traw, (a_deca, 1))
tcal = np.tile(self.tcal, (a_deca, 1))
T = np.tile(self.T, (a_deca, 1))
PS = np.tile(self.S, (a_deca, 1))
tbins = np.tile(self.tbins, (a_deca, 1))
# variables unique to beam attenuation: 1D -> 2D
a_sig = np.tile(self.a_sig, (a_deca, 1))
a_ref = np.tile(self.a_ref, (a_deca, 1))
a_off = np.tile(self.a_off, (a_deca, 1))
a_wvl = np.tile(self.a_wvl, (a_deca, 1))
# variables unique to beam attenuation: 2D -> 3D
ta_arr = np.tile(self.ta_arr, (a_deca, 1, 1))
cpd_ts = np.tile(self.cpd_ts, (a_deca, 1))
c_wvl = np.tile(self.c_wvl, (a_deca, 1))
# timing test
self.profile(stats, optfunc.opt_optical_absorption, a_ref, a_sig, traw, a_wvl, a_off, tcal,
tbins, ta_arr, cpd_ts, c_wvl, T, PS)
def test_opt_ocr507_irradiance(self):
stats = []
# create 10000 data packets
counts = np.tile(self.ocr_507[0, :], (a_deca, 1))
offset = np.tile(self.ocr_507[1, :], (a_deca, 1))
scale = np.tile(self.ocr_507[2, :], (a_deca, 1))
immersion_factor = np.tile(self.ocr_507[3, :], (a_deca, 1))
# timing test
self.profile(stats, optfunc.opt_ocr507_irradiance, counts, offset, scale, immersion_factor) | 0.498779 | 0.512693 |
import numpy as np
import tensorflow as tf
class ANN(object):
def __init__(self, size, logPath):
"""
创建一个神经网络
"""
# 重置tensorflow的graph，确保神经网络可多次运行
tf.reset_default_graph()
tf.set_random_seed(1908)
self.logPath = logPath
self.layerNum = len(size)
self.size = size
def defineANN(self):
"""
定义神经网络的结构
"""
# self.input是训练数据里自变量
prevSize = self.input.shape[1].value
prevOut = self.input
# self.size是神经网络的结构，也就是每一层的神经元个数
size = self.size
layer = 1
# 定义隐藏层
for currentSize in size[:-1]:
weights = tf.Variable(
tf.truncated_normal([prevSize, currentSize],
stddev=1.0 / np.sqrt(float(prevSize))))
# 记录隐藏层的模型参数
tf.summary.histogram("hidden%s" % layer, weights)
layer += 1
biases = tf.Variable(tf.zeros([currentSize]))
prevOut = tf.nn.sigmoid(tf.matmul(prevOut, weights) + biases)
prevSize = currentSize
# 定义输出层
weights = tf.Variable(
tf.truncated_normal([prevSize, size[-1]],
stddev=1.0 / np.sqrt(float(prevSize))))
biases = tf.Variable(tf.zeros([size[-1]]))
self.out = tf.matmul(prevOut, weights) + biases
return self
def defineLoss(self):
"""
定义神经网络的损失函数
"""
# 定义单点损失，self.label是训练数据里的标签变量
loss = tf.nn.softmax_cross_entropy_with_logits(
labels=self.label, logits=self.out, name="loss")
# 定义整体损失
self.loss = tf.reduce_mean(loss, name="average_loss")
return self
def SGD(self, X, Y, learningRate, miniBatchFraction, epoch):
"""
使用随机梯度下降法训练模型
参数
----
X : np.array, 自变量
Y : np.array, 因变量
"""
# 记录训练的细节
tf.summary.scalar("loss", self.loss)
summary = tf.summary.merge_all()
method = tf.train.GradientDescentOptimizer(learningRate)
optimizer= method.minimize(self.loss)
batchSize = int(X.shape[0] * miniBatchFraction)
batchNum = int(np.ceil(1 / miniBatchFraction))
sess = tf.Session()
init = tf.global_variables_initializer()
sess.run(init)
summary_writer = tf.summary.FileWriter(self.logPath, graph=tf.get_default_graph())
step = 0
while (step < epoch):
for i in range(batchNum):
batchX = X[i * batchSize: (i + 1) * batchSize]
batchY = Y[i * batchSize: (i + 1) * batchSize]
sess.run([optimizer],
feed_dict={self.input: batchX, self.label: batchY})
step += 1
# 将日志写入文件
summary_str = sess.run(summary, feed_dict={self.input: X, self.label: Y})
summary_writer.add_summary(summary_str, step)
summary_writer.flush()
self.sess = sess
return self
def fit(self, X, Y, learningRate=0.3, miniBatchFraction=0.1, epoch=2500):
"""
训练模型
参数
----
X : np.array, 自变量
Y : np.array, 因变量
"""
self.input = tf.placeholder(tf.float32, shape=[None, X.shape[1]], name="X")
self.label = tf.placeholder(tf.int64, shape=[None, self.size[-1]], name="Y")
self.defineANN()
self.defineLoss()
self.SGD(X, Y, learningRate, miniBatchFraction, epoch)
def predict_proba(self, X):
"""
使用神经网络对未知数据进行预测
"""
sess = self.sess
pred = tf.nn.softmax(logits=self.out, name="pred")
prob = sess.run(pred, feed_dict={self.input: X})
return prob | ch12-ann/mlp.py | import numpy as np
import tensorflow as tf
class ANN(object):
def __init__(self, size, logPath):
"""
创建一个神经网络
"""
# 重置tensorflow的graph，确保神经网络可多次运行
tf.reset_default_graph()
tf.set_random_seed(1908)
self.logPath = logPath
self.layerNum = len(size)
self.size = size
def defineANN(self):
"""
定义神经网络的结构
"""
# self.input是训练数据里自变量
prevSize = self.input.shape[1].value
prevOut = self.input
# self.size是神经网络的结构，也就是每一层的神经元个数
size = self.size
layer = 1
# 定义隐藏层
for currentSize in size[:-1]:
weights = tf.Variable(
tf.truncated_normal([prevSize, currentSize],
stddev=1.0 / np.sqrt(float(prevSize))))
# 记录隐藏层的模型参数
tf.summary.histogram("hidden%s" % layer, weights)
layer += 1
biases = tf.Variable(tf.zeros([currentSize]))
prevOut = tf.nn.sigmoid(tf.matmul(prevOut, weights) + biases)
prevSize = currentSize
# 定义输出层
weights = tf.Variable(
tf.truncated_normal([prevSize, size[-1]],
stddev=1.0 / np.sqrt(float(prevSize))))
biases = tf.Variable(tf.zeros([size[-1]]))
self.out = tf.matmul(prevOut, weights) + biases
return self
def defineLoss(self):
"""
定义神经网络的损失函数
"""
# 定义单点损失，self.label是训练数据里的标签变量
loss = tf.nn.softmax_cross_entropy_with_logits(
labels=self.label, logits=self.out, name="loss")
# 定义整体损失
self.loss = tf.reduce_mean(loss, name="average_loss")
return self
def SGD(self, X, Y, learningRate, miniBatchFraction, epoch):
"""
使用随机梯度下降法训练模型
参数
----
X : np.array, 自变量
Y : np.array, 因变量
"""
# 记录训练的细节
tf.summary.scalar("loss", self.loss)
summary = tf.summary.merge_all()
method = tf.train.GradientDescentOptimizer(learningRate)
optimizer= method.minimize(self.loss)
batchSize = int(X.shape[0] * miniBatchFraction)
batchNum = int(np.ceil(1 / miniBatchFraction))
sess = tf.Session()
init = tf.global_variables_initializer()
sess.run(init)
summary_writer = tf.summary.FileWriter(self.logPath, graph=tf.get_default_graph())
step = 0
while (step < epoch):
for i in range(batchNum):
batchX = X[i * batchSize: (i + 1) * batchSize]
batchY = Y[i * batchSize: (i + 1) * batchSize]
sess.run([optimizer],
feed_dict={self.input: batchX, self.label: batchY})
step += 1
# 将日志写入文件
summary_str = sess.run(summary, feed_dict={self.input: X, self.label: Y})
summary_writer.add_summary(summary_str, step)
summary_writer.flush()
self.sess = sess
return self
def fit(self, X, Y, learningRate=0.3, miniBatchFraction=0.1, epoch=2500):
"""
训练模型
参数
----
X : np.array, 自变量
Y : np.array, 因变量
"""
self.input = tf.placeholder(tf.float32, shape=[None, X.shape[1]], name="X")
self.label = tf.placeholder(tf.int64, shape=[None, self.size[-1]], name="Y")
self.defineANN()
self.defineLoss()
self.SGD(X, Y, learningRate, miniBatchFraction, epoch)
def predict_proba(self, X):
"""
使用神经网络对未知数据进行预测
"""
sess = self.sess
pred = tf.nn.softmax(logits=self.out, name="pred")
prob = sess.run(pred, feed_dict={self.input: X})
return prob | 0.581065 | 0.549943 |
from sns_boomerang.common.items import sns_client, Job, Topic, JOB_TABLE
from contextlib import contextmanager
import pytest
from unittest.mock import MagicMock
from datetime import datetime
def test_new_job():
job = Job('topic', 'payload', 123)
assert job.id
assert job.topic == 'topic'
assert job.payload == 'payload'
def test_add_or_update(monkeypatch):
def mock_put_item(Item, **kwargs):
assert Item['topic'] == 'topic'
assert Item['time_scheduled'] > 0
# mock_datetime = datetime.now()
# monkeypatch.setattr(datetime, 'utcnow', mock_datetime)
monkeypatch.setattr(JOB_TABLE, 'put_item', mock_put_item)
job = Job('topic', 'payload', 123)
job.add_or_update()
@pytest.mark.parametrize("test_input, status, check, expected", [
("active-job", 1, True, True),
("not-active-check-status", 0, True, False),
("not-active-check-status", 0, False, True)
])
def test_job_get_by_id_status(test_input, status, check, expected, monkeypatch):
topic_name = f'{test_input}-topic'
def mock_get_item(Key, **kwargs):
assert Key['id'] == test_input
return {'Item': {'topic': topic_name, 'payload': 'payload', 'time_due': 111, 'is_valid': status}}
monkeypatch.setattr(JOB_TABLE, 'get_item', mock_get_item)
job = Job.get(test_input, check)
if expected:
assert job.topic == topic_name
else:
assert job == None
def test_job_flush(monkeypatch):
test_key_id = 'x'
class batch_mock:
def delete_item(self, Key):
assert Key['id'] == test_key_id
@contextmanager
def mock_managed_context(*args, **kwds):
try:
yield batch_mock()
finally:
pass
def mock_query(IndexName, KeyConditionExpression, **kwargs):
assert IndexName == 'is_valid-time_due-index'
assert KeyConditionExpression is not None
return {'Items': [{'id': test_key_id, 'is_valid': 1}]}
monkeypatch.setattr(JOB_TABLE, 'query', mock_query)
monkeypatch.setattr(JOB_TABLE, 'batch_writer', mock_managed_context)
Job.flush()
def test_job_publish_success(monkeypatch):
mock_topic = Topic('x', arn='existing')
mock_job = Job('x', '{"a": "b"}', 123)
def mock_publish(TopicArn, Message, MessageStructure, **kwargs):
assert MessageStructure == 'json'
def mock_topic_get(topic_name):
assert topic_name == 'x'
return mock_topic
monkeypatch.setattr(Topic, 'get', mock_topic_get)
monkeypatch.setattr(sns_client, 'publish', mock_publish)
mock_job.publish() | tests/test_item_job.py | from sns_boomerang.common.items import sns_client, Job, Topic, JOB_TABLE
from contextlib import contextmanager
import pytest
from unittest.mock import MagicMock
from datetime import datetime
def test_new_job():
job = Job('topic', 'payload', 123)
assert job.id
assert job.topic == 'topic'
assert job.payload == 'payload'
def test_add_or_update(monkeypatch):
def mock_put_item(Item, **kwargs):
assert Item['topic'] == 'topic'
assert Item['time_scheduled'] > 0
# mock_datetime = datetime.now()
# monkeypatch.setattr(datetime, 'utcnow', mock_datetime)
monkeypatch.setattr(JOB_TABLE, 'put_item', mock_put_item)
job = Job('topic', 'payload', 123)
job.add_or_update()
@pytest.mark.parametrize("test_input, status, check, expected", [
("active-job", 1, True, True),
("not-active-check-status", 0, True, False),
("not-active-check-status", 0, False, True)
])
def test_job_get_by_id_status(test_input, status, check, expected, monkeypatch):
topic_name = f'{test_input}-topic'
def mock_get_item(Key, **kwargs):
assert Key['id'] == test_input
return {'Item': {'topic': topic_name, 'payload': 'payload', 'time_due': 111, 'is_valid': status}}
monkeypatch.setattr(JOB_TABLE, 'get_item', mock_get_item)
job = Job.get(test_input, check)
if expected:
assert job.topic == topic_name
else:
assert job == None
def test_job_flush(monkeypatch):
test_key_id = 'x'
class batch_mock:
def delete_item(self, Key):
assert Key['id'] == test_key_id
@contextmanager
def mock_managed_context(*args, **kwds):
try:
yield batch_mock()
finally:
pass
def mock_query(IndexName, KeyConditionExpression, **kwargs):
assert IndexName == 'is_valid-time_due-index'
assert KeyConditionExpression is not None
return {'Items': [{'id': test_key_id, 'is_valid': 1}]}
monkeypatch.setattr(JOB_TABLE, 'query', mock_query)
monkeypatch.setattr(JOB_TABLE, 'batch_writer', mock_managed_context)
Job.flush()
def test_job_publish_success(monkeypatch):
mock_topic = Topic('x', arn='existing')
mock_job = Job('x', '{"a": "b"}', 123)
def mock_publish(TopicArn, Message, MessageStructure, **kwargs):
assert MessageStructure == 'json'
def mock_topic_get(topic_name):
assert topic_name == 'x'
return mock_topic
monkeypatch.setattr(Topic, 'get', mock_topic_get)
monkeypatch.setattr(sns_client, 'publish', mock_publish)
mock_job.publish() | 0.520496 | 0.468122 |
__author__ = '<EMAIL> (<NAME>)'
import logging
from categories import test_set_base
from categories import test_set_params
_CATEGORY = 'reflow'
class ReflowTest(test_set_base.TestBase):
TESTS_URL_PATH = '/%s/test' % _CATEGORY
def __init__(self, key, name, doc):
test_set_base.TestBase.__init__(
self,
key=key,
name=name,
url='%s?t=%s' % (self.TESTS_URL_PATH, key),
doc=doc,
min_value=0,
max_value=60000)
_TESTS = (
# key, name, doc
ReflowTest('testDisplay', 'Display Block',
'''This test takes an element and sets its
style.display="none". According to the folks at Mozilla this has
the effect of taking an element out of the browser's "render tree"
(the in-memory representation of all of results of
geometry/positioning calculations for that particular
element). Setting an element to display="none" has the additional
effect of removing all of an element's children from the render tree
as well. Next, the test resets the element's style.display="", which
sets the element's display back to its original value. Our thinking
was that this operation ought to approximate the max cost of reflowing
an element on a page since the browser has to
recalculate all positions and sizes for every child within the
element as well as any changes to the overall document.'''),
ReflowTest('testVisibility', 'Visiblility None',
'''Much like the display test above, this test sets an element's
style.visibility="hidden" and then resets it back to its default,
which is "visible". This change should be less costly than
changing display from "none" to the default since the browser
should not be purging the element from the render tree.'''),
ReflowTest('testNonMatchingClass', 'Non Matching Class',
'''This test adds a class name to an element where that
class name is not present in the document's CSS object
model. This tests CSS selector match time, and more specifically
against selectors with classnames.'''),
ReflowTest('testFourClassReflows', 'Four Reflows by Class',
'''This test adds a class name to an element that will match a
previously added CSS declaration added to the CSSOM. This
declaration is set with four property value pairs which should in
and of themselves be capable of causing a 1x reflow time. For
instance, "font-size: 20px; line-height: 10px; padding-left: 10px;
margin-top: 7px;". This test aims to test whether reflow
operations occur in a single queue flush or if they are performed
one at a time when these changes are made via a CSS
classname. This test is a sort of opposite to the Four Reflows By
Script.'''),
ReflowTest('testFourScriptReflows', 'Four Reflows by Script',
'''Like the Four Reflows By Class test, but instead this test has
four lines of Javascript, each of which alters the style object
with a property/value that by itself could cause a 1x reflow
time.'''),
ReflowTest('testTwoScriptReflows', 'Two Reflows by Script',
'''Like the Four Reflows By Script test, except with only two lines
of Javascript.'''),
ReflowTest('testPaddingPx', 'Padding px',
'''This test sets style.padding="FOOpx", aka padding on all sides of
the box model.'''),
ReflowTest('testPaddingLeftPx', 'Padding Left px',
'''This test sets style.paddingLeft="FOOpx", aka padding on only the
left side of the box.'''),
ReflowTest('testFontSizeEm', 'Font Size em',
'''This test changes an element's style.fontSize to an em-based
value.'''),
ReflowTest('testWidthPercent', 'Width %',
'''This test sets an element's style.width="FOO%"'''),
ReflowTest('testBackground', 'Background Color',
'''This test sets an element's style.background="#FOO", aka a
hexadecimal color.'''),
ReflowTest('testOverflowHidden', 'Overflow Hidden',
'''This test sets an element's style.overflow="hidden" and then back
again, timing the cost of an element returning to the default
overflow which is "visible"'''),
ReflowTest('testGetOffsetHeight', 'Do Nothing / OffsetHeight',
'''This test does nothing other than the request for offsetHeight
after already having done so. Theoretically, this test is
something like a control for our test and should have a 0 or very
low time.'''),
)
BASELINE_TEST_NAME = 'testDisplay'
class ReflowTestSet(test_set_base.TestSet):
def AdjustResults(self, results):
"""Re-scores the actual value against a baseline score for reflow.
Sets the 1x reflow time for this test run and compares other times
against that. This is to try to account for issues around selection
bias, processor speed, etc...
We'll preserve the original millisecond time as an expando value in case
we want to do some calculations with it later.
Args:
results: {
test_key_1: {'raw_score': raw_score_1},
test_key_2: {'raw_score': raw_score_2},
...
}
Returns:
{ test_key_1: {'raw_score': adjusted_raw_score_1, 'expando': score_1},
test_key_2: {'raw_score': adjusted_raw_score_2, 'expando': score_2},
...
}
"""
if BASELINE_TEST_NAME not in results:
raise NameError('No baseline score found in the test results')
baseline_score = float(results[BASELINE_TEST_NAME]['raw_score'])
# Turn all values into some computed percentage of the baseline score.
# This resets the score in the dict, but adds an expando to preserve the
# original score's milliseconds value.
for result in results.values():
result['expando'] = result['raw_score']
result['raw_score'] = int(100.0 * result['raw_score'] / baseline_score)
return results
def GetTestScoreAndDisplayValue(self, test_key, raw_scores):
"""Get a normalized score (0 to 100) and a value to output to the display.
Args:
test_key: a key for a test_set test.
raw_scores: a dict of raw_scores indexed by test keys.
Returns:
score, display_value
# score is from 0 to 100.
# display_value is the text for the cell.
"""
raw_score = raw_scores.get(test_key, None)
if raw_score in (None, ''):
return 0, ''
raw_score = int(raw_score)
if raw_score <= 10:
score, display = 100, '0X'
elif raw_score <= 35:
score, display = 97, '¼X'
elif raw_score <= 65:
score, display = 95, '½X'
elif raw_score <= 85:
score, display = 93, '¾X'
elif raw_score <= 110:
score, display = 90, '1X'
elif raw_score <= 180:
score, display = 80, '2X'
else:
score, display = 60, '3X'
return score, display
def GetRowScoreAndDisplayValue(self, results):
"""Get the overall score for this row of results data.
Args:
results: {
'test_key_1': {'score': score_1, 'raw_score': raw_score_1, ...},
'test_key_2': {'score': score_2, 'raw_score': raw_score_2, ...},
...
}
Returns:
score, display_value
# score is from 0 to 100.
# display_value is the text for the cell.
"""
return 90, ''
TEST_SET = ReflowTestSet(
category=_CATEGORY,
category_name='Reflow',
summary_doc='Tests of reflow time for different CSS selectors.',
tests=_TESTS,
# default_params=Params(
# 'nested_anchors', 'num_elements=400', 'num_nest=4',
# 'css_selector=#g-content *', 'num_css_rules=1000',
# 'css_text=border: 1px solid #0C0; padding: 8px;'),
#default_params=test_set_params.Params('acid1', 'num_elements=300'),
test_page='/%s/test_acid1' % _CATEGORY
) | categories/reflow/test_set.py | __author__ = '<EMAIL> (<NAME>)'
import logging
from categories import test_set_base
from categories import test_set_params
_CATEGORY = 'reflow'
class ReflowTest(test_set_base.TestBase):
TESTS_URL_PATH = '/%s/test' % _CATEGORY
def __init__(self, key, name, doc):
test_set_base.TestBase.__init__(
self,
key=key,
name=name,
url='%s?t=%s' % (self.TESTS_URL_PATH, key),
doc=doc,
min_value=0,
max_value=60000)
_TESTS = (
# key, name, doc
ReflowTest('testDisplay', 'Display Block',
'''This test takes an element and sets its
style.display="none". According to the folks at Mozilla this has
the effect of taking an element out of the browser's "render tree"
(the in-memory representation of all of results of
geometry/positioning calculations for that particular
element). Setting an element to display="none" has the additional
effect of removing all of an element's children from the render tree
as well. Next, the test resets the element's style.display="", which
sets the element's display back to its original value. Our thinking
was that this operation ought to approximate the max cost of reflowing
an element on a page since the browser has to
recalculate all positions and sizes for every child within the
element as well as any changes to the overall document.'''),
ReflowTest('testVisibility', 'Visiblility None',
'''Much like the display test above, this test sets an element's
style.visibility="hidden" and then resets it back to its default,
which is "visible". This change should be less costly than
changing display from "none" to the default since the browser
should not be purging the element from the render tree.'''),
ReflowTest('testNonMatchingClass', 'Non Matching Class',
'''This test adds a class name to an element where that
class name is not present in the document's CSS object
model. This tests CSS selector match time, and more specifically
against selectors with classnames.'''),
ReflowTest('testFourClassReflows', 'Four Reflows by Class',
'''This test adds a class name to an element that will match a
previously added CSS declaration added to the CSSOM. This
declaration is set with four property value pairs which should in
and of themselves be capable of causing a 1x reflow time. For
instance, "font-size: 20px; line-height: 10px; padding-left: 10px;
margin-top: 7px;". This test aims to test whether reflow
operations occur in a single queue flush or if they are performed
one at a time when these changes are made via a CSS
classname. This test is a sort of opposite to the Four Reflows By
Script.'''),
ReflowTest('testFourScriptReflows', 'Four Reflows by Script',
'''Like the Four Reflows By Class test, but instead this test has
four lines of Javascript, each of which alters the style object
with a property/value that by itself could cause a 1x reflow
time.'''),
ReflowTest('testTwoScriptReflows', 'Two Reflows by Script',
'''Like the Four Reflows By Script test, except with only two lines
of Javascript.'''),
ReflowTest('testPaddingPx', 'Padding px',
'''This test sets style.padding="FOOpx", aka padding on all sides of
the box model.'''),
ReflowTest('testPaddingLeftPx', 'Padding Left px',
'''This test sets style.paddingLeft="FOOpx", aka padding on only the
left side of the box.'''),
ReflowTest('testFontSizeEm', 'Font Size em',
'''This test changes an element's style.fontSize to an em-based
value.'''),
ReflowTest('testWidthPercent', 'Width %',
'''This test sets an element's style.width="FOO%"'''),
ReflowTest('testBackground', 'Background Color',
'''This test sets an element's style.background="#FOO", aka a
hexadecimal color.'''),
ReflowTest('testOverflowHidden', 'Overflow Hidden',
'''This test sets an element's style.overflow="hidden" and then back
again, timing the cost of an element returning to the default
overflow which is "visible"'''),
ReflowTest('testGetOffsetHeight', 'Do Nothing / OffsetHeight',
'''This test does nothing other than the request for offsetHeight
after already having done so. Theoretically, this test is
something like a control for our test and should have a 0 or very
low time.'''),
)
BASELINE_TEST_NAME = 'testDisplay'
class ReflowTestSet(test_set_base.TestSet):
def AdjustResults(self, results):
"""Re-scores the actual value against a baseline score for reflow.
Sets the 1x reflow time for this test run and compares other times
against that. This is to try to account for issues around selection
bias, processor speed, etc...
We'll preserve the original millisecond time as an expando value in case
we want to do some calculations with it later.
Args:
results: {
test_key_1: {'raw_score': raw_score_1},
test_key_2: {'raw_score': raw_score_2},
...
}
Returns:
{ test_key_1: {'raw_score': adjusted_raw_score_1, 'expando': score_1},
test_key_2: {'raw_score': adjusted_raw_score_2, 'expando': score_2},
...
}
"""
if BASELINE_TEST_NAME not in results:
raise NameError('No baseline score found in the test results')
baseline_score = float(results[BASELINE_TEST_NAME]['raw_score'])
# Turn all values into some computed percentage of the baseline score.
# This resets the score in the dict, but adds an expando to preserve the
# original score's milliseconds value.
for result in results.values():
result['expando'] = result['raw_score']
result['raw_score'] = int(100.0 * result['raw_score'] / baseline_score)
return results
def GetTestScoreAndDisplayValue(self, test_key, raw_scores):
"""Get a normalized score (0 to 100) and a value to output to the display.
Args:
test_key: a key for a test_set test.
raw_scores: a dict of raw_scores indexed by test keys.
Returns:
score, display_value
# score is from 0 to 100.
# display_value is the text for the cell.
"""
raw_score = raw_scores.get(test_key, None)
if raw_score in (None, ''):
return 0, ''
raw_score = int(raw_score)
if raw_score <= 10:
score, display = 100, '0X'
elif raw_score <= 35:
score, display = 97, '¼X'
elif raw_score <= 65:
score, display = 95, '½X'
elif raw_score <= 85:
score, display = 93, '¾X'
elif raw_score <= 110:
score, display = 90, '1X'
elif raw_score <= 180:
score, display = 80, '2X'
else:
score, display = 60, '3X'
return score, display
def GetRowScoreAndDisplayValue(self, results):
"""Get the overall score for this row of results data.
Args:
results: {
'test_key_1': {'score': score_1, 'raw_score': raw_score_1, ...},
'test_key_2': {'score': score_2, 'raw_score': raw_score_2, ...},
...
}
Returns:
score, display_value
# score is from 0 to 100.
# display_value is the text for the cell.
"""
return 90, ''
TEST_SET = ReflowTestSet(
category=_CATEGORY,
category_name='Reflow',
summary_doc='Tests of reflow time for different CSS selectors.',
tests=_TESTS,
# default_params=Params(
# 'nested_anchors', 'num_elements=400', 'num_nest=4',
# 'css_selector=#g-content *', 'num_css_rules=1000',
# 'css_text=border: 1px solid #0C0; padding: 8px;'),
#default_params=test_set_params.Params('acid1', 'num_elements=300'),
test_page='/%s/test_acid1' % _CATEGORY
) | 0.713931 | 0.411702 |
__version__ = "1.0"
__author__ = "2-REC"
import logging
logger = logging.getLogger(__name__)
from Qt.QtCore import Qt as qt
from Qt.QtWidgets import (
QMessageBox,
QTextEdit,
QDialogButtonBox,
QSizePolicy
)
class ResizableMessageBox(QMessageBox):
_max_width = 4096
_max_height = 2048
def __init__(self, *args, **kwargs):
super(ResizableMessageBox, self).__init__(*args, **kwargs)
self.clearDetailBox()
def setDetailedText(self, text):
super(ResizableMessageBox, self).setDetailedText(text)
if not text:
self.clearDetailBox()
return
details_box = self.findChild(QTextEdit)
if not details_box:
logger.error("No 'QTextEdit' found in 'QDialogButtonBox'")
return
self.details_box = details_box
dialog_button_box = self.findChild(QDialogButtonBox)
if dialog_button_box:
for button in dialog_button_box.buttons():
if (
dialog_button_box.buttonRole(button)
== QDialogButtonBox.ButtonRole.ActionRole
):
button.released.connect(self.detailsToggle)
break
else:
logger.error("No 'ActionRole' button in 'QDialogButtonBox'")
def resizeEvent(self, event):
result = super(ResizableMessageBox, self).resizeEvent(event)
if self.details_visible:
self.setSizing()
return result
def clearDetailBox(self):
self.details_box = None
self.details_visible = False
self.setSizeGripEnabled(False)
def detailsToggle(self):
self.details_visible = not self.details_visible
self.setSizeGripEnabled(self.details_visible)
if self.details_visible:
self.setSizing()
def setSizing(self):
self.setWidgetSizing(self)
self.setWidgetSizing(self.details_box)
@classmethod
def setWidgetSizing(cls, widget):
widget.setMaximumHeight(cls._max_width)
widget.setMaximumWidth(cls._max_height)
widget.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding) | resizable_messagebox.py | __version__ = "1.0"
__author__ = "2-REC"
import logging
logger = logging.getLogger(__name__)
from Qt.QtCore import Qt as qt
from Qt.QtWidgets import (
QMessageBox,
QTextEdit,
QDialogButtonBox,
QSizePolicy
)
class ResizableMessageBox(QMessageBox):
_max_width = 4096
_max_height = 2048
def __init__(self, *args, **kwargs):
super(ResizableMessageBox, self).__init__(*args, **kwargs)
self.clearDetailBox()
def setDetailedText(self, text):
super(ResizableMessageBox, self).setDetailedText(text)
if not text:
self.clearDetailBox()
return
details_box = self.findChild(QTextEdit)
if not details_box:
logger.error("No 'QTextEdit' found in 'QDialogButtonBox'")
return
self.details_box = details_box
dialog_button_box = self.findChild(QDialogButtonBox)
if dialog_button_box:
for button in dialog_button_box.buttons():
if (
dialog_button_box.buttonRole(button)
== QDialogButtonBox.ButtonRole.ActionRole
):
button.released.connect(self.detailsToggle)
break
else:
logger.error("No 'ActionRole' button in 'QDialogButtonBox'")
def resizeEvent(self, event):
result = super(ResizableMessageBox, self).resizeEvent(event)
if self.details_visible:
self.setSizing()
return result
def clearDetailBox(self):
self.details_box = None
self.details_visible = False
self.setSizeGripEnabled(False)
def detailsToggle(self):
self.details_visible = not self.details_visible
self.setSizeGripEnabled(self.details_visible)
if self.details_visible:
self.setSizing()
def setSizing(self):
self.setWidgetSizing(self)
self.setWidgetSizing(self.details_box)
@classmethod
def setWidgetSizing(cls, widget):
widget.setMaximumHeight(cls._max_width)
widget.setMaximumWidth(cls._max_height)
widget.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding) | 0.337968 | 0.052038 |