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 abc import ABC
from .const import math
class Variable(ABC):
"""
Abstract class for a variable with some schedule
"""
_opvalue_ = None
_value_ = None
def __call__(self):
self._step_()
return self.value
@property
def value(self):
"""
Main property for the class to output its value.
To advance one step first call the variable
returns value
"""
return self._value_
def _step_(self):
"""
Method to update the variable value of the object
each time is called. Can be passed to have a manual
step calling
"""
pass
def step(self):
"""
Method to update the variable in a manual manner.
"""
raise NotImplementedError
def restore(self, step:int = -1):
"""
Restore the intial value to the variable or if a step
is given restores from that step
returns None
"""
if step <= 0:
self._i_ = 0
self._value_ = self._opvalue_
else:
self._i_ = step -1
self.step()
def __eq__(self, other):
self._step_()
return self._value_.__eq__(other)
def __le__(self, other):
self._step_()
return self._value_.__le__(other)
def __lt__(self, other):
self._step_()
return self._value_.__lt__(other)
def __gt__(self, other):
self._step_()
return self._value_.__gt__(other)
def __ge__(self, other):
self._step_()
return self._value_.__ge__(other)
def __add__(self, other):
return self._value_.__add__(other)
def __mul__(self, other):
self._step_()
return self._value_.__mul__(other)
def __repr__(self):
return self._value_.__repr__()
def __float__(self):
self._step_()
return self._value_.__float__()
def __div__(self, other):
self._step_()
return self._value_.__div__(other)
def __truediv__(self, other):
self._step_()
return self._value_.__truediv__(other)
def __floordiv__(self, other):
self._step_()
return self._value_.__floordiv__(other)
def __neg__(self):
self._step_()
return self._value_.__neg__()
def updateVar(config):
vrs = config.get("variables", [])
for v in vrs:
v.step()
class linearSchedule(Variable):
def __init__(self, initValue, lastValue, life:int):
assert initValue != lastValue, "Values need to be different!"
assert life > 0, "Life of the variable must be positive. Live Chill"
if initValue < lastValue:
self._F = min
else:
self._F = max
self._opvalue_, self._last_ = initValue,lastValue
self._value_ = initValue
self._diff_ = self._last_ - self._opvalue_
self._i_ = 0
self._life_ = life
self.step()
def step(self):
xm = self._diff_ * self._i_ / self._life_
y = self._opvalue_ + xm
self._i_ += 1
self._value_ = self._F(self._last_, y)
def __repr__(self):
s = "linearSchedule: value {} init {}, last {}, life {}".format(self._value_, self._opvalue_, self._last_, self._life_)
return s
class runningStat():
"""
Custom class to keep track of a single value running
statistic.
Defaults to zeros, usual method to add the values with the
operator +=, eg
x = runningStat()\\
x += 2\\
x += 3\\
x()
Based from http://www.johndcook.com/blog/standard_deviation/
"""
def __init__(self):
self.__mn__ = 0.0
self.__sn__ = 0.0
self.__n__ = 0
def __call__(self):
return (self.mean, self.std)
def __iadd__(self, other):
if self.__n__ == 0:
self.__mn__ = other
self.__n__ += 1
else:
self.__n__ += 1
oldMN = self.__mn__
self.__mn__ += (other - oldMN) / self.__n__
self.__sn__ += (other - oldMN) * (other - self.__mn__)
return self
def add(self, x):
self += x
@property
def mean(self):
return self.__mn__
@property
def var(self):
return self.__sn__ / (self.__n__ - 1) if self.__n__ > 1 else math.pow(self.__sn__, 2)
@property
def std(self):
return math.sqrt(self.var)
def reset(self):
self.__init__()
def __repr__(self):
return "runningStat: mean {:.4f} std {:.4f}".format(*self()) | rofl/functions/vars.py | from abc import ABC
from .const import math
class Variable(ABC):
"""
Abstract class for a variable with some schedule
"""
_opvalue_ = None
_value_ = None
def __call__(self):
self._step_()
return self.value
@property
def value(self):
"""
Main property for the class to output its value.
To advance one step first call the variable
returns value
"""
return self._value_
def _step_(self):
"""
Method to update the variable value of the object
each time is called. Can be passed to have a manual
step calling
"""
pass
def step(self):
"""
Method to update the variable in a manual manner.
"""
raise NotImplementedError
def restore(self, step:int = -1):
"""
Restore the intial value to the variable or if a step
is given restores from that step
returns None
"""
if step <= 0:
self._i_ = 0
self._value_ = self._opvalue_
else:
self._i_ = step -1
self.step()
def __eq__(self, other):
self._step_()
return self._value_.__eq__(other)
def __le__(self, other):
self._step_()
return self._value_.__le__(other)
def __lt__(self, other):
self._step_()
return self._value_.__lt__(other)
def __gt__(self, other):
self._step_()
return self._value_.__gt__(other)
def __ge__(self, other):
self._step_()
return self._value_.__ge__(other)
def __add__(self, other):
return self._value_.__add__(other)
def __mul__(self, other):
self._step_()
return self._value_.__mul__(other)
def __repr__(self):
return self._value_.__repr__()
def __float__(self):
self._step_()
return self._value_.__float__()
def __div__(self, other):
self._step_()
return self._value_.__div__(other)
def __truediv__(self, other):
self._step_()
return self._value_.__truediv__(other)
def __floordiv__(self, other):
self._step_()
return self._value_.__floordiv__(other)
def __neg__(self):
self._step_()
return self._value_.__neg__()
def updateVar(config):
vrs = config.get("variables", [])
for v in vrs:
v.step()
class linearSchedule(Variable):
def __init__(self, initValue, lastValue, life:int):
assert initValue != lastValue, "Values need to be different!"
assert life > 0, "Life of the variable must be positive. Live Chill"
if initValue < lastValue:
self._F = min
else:
self._F = max
self._opvalue_, self._last_ = initValue,lastValue
self._value_ = initValue
self._diff_ = self._last_ - self._opvalue_
self._i_ = 0
self._life_ = life
self.step()
def step(self):
xm = self._diff_ * self._i_ / self._life_
y = self._opvalue_ + xm
self._i_ += 1
self._value_ = self._F(self._last_, y)
def __repr__(self):
s = "linearSchedule: value {} init {}, last {}, life {}".format(self._value_, self._opvalue_, self._last_, self._life_)
return s
class runningStat():
"""
Custom class to keep track of a single value running
statistic.
Defaults to zeros, usual method to add the values with the
operator +=, eg
x = runningStat()\\
x += 2\\
x += 3\\
x()
Based from http://www.johndcook.com/blog/standard_deviation/
"""
def __init__(self):
self.__mn__ = 0.0
self.__sn__ = 0.0
self.__n__ = 0
def __call__(self):
return (self.mean, self.std)
def __iadd__(self, other):
if self.__n__ == 0:
self.__mn__ = other
self.__n__ += 1
else:
self.__n__ += 1
oldMN = self.__mn__
self.__mn__ += (other - oldMN) / self.__n__
self.__sn__ += (other - oldMN) * (other - self.__mn__)
return self
def add(self, x):
self += x
@property
def mean(self):
return self.__mn__
@property
def var(self):
return self.__sn__ / (self.__n__ - 1) if self.__n__ > 1 else math.pow(self.__sn__, 2)
@property
def std(self):
return math.sqrt(self.var)
def reset(self):
self.__init__()
def __repr__(self):
return "runningStat: mean {:.4f} std {:.4f}".format(*self()) | 0.88669 | 0.35113 |
from RGT.XML.SVG.baseContainerNode import BaseContainerNode
from RGT.XML.SVG.Attribs.conditionalProcessingAttributes import ConditionalProcessingAttributes
from RGT.XML.SVG.Attribs.xlinkAttributes import XlinkAttributes
from RGT.XML.SVG.Attribs.positionAttributes import PositionAttributes
from RGT.XML.SVG.Attribs.sizeAttributes import SizeAttributes
from types import StringType
from RGT.XML.SVG.basicSvgNode import BasicSvgNode
class PatternNode(BaseContainerNode, PositionAttributes, SizeAttributes, ConditionalProcessingAttributes,
XlinkAttributes):
svgNodeType = BasicSvgNode.SVG_PATTERN_NODE
ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED = 'externalResourcesRequired'
ATTRIBUTE_VIEW_BOX = 'viewBox'
ATTRIBUTE_PRESERVE_ASPECT_RATIO = 'preserveAspectRatio'
ATTRIBUTE_WIDTH = 'width'
ATTRIBUTE_HEIGHT = 'height'
ATTRIBUTE_PATTERN_UNITS = 'patternUnits'
ATTRIBUTE_PATTERN_CONTENT_UNITS = 'patternContentUnits'
ATTRIBUTE_PATTERN_TRANSFORM = 'patternTransform'
def __init__(self, ownerDoc):
BaseContainerNode.__init__(self, ownerDoc, 'pattern')
PositionAttributes.__init__(self)
SizeAttributes.__init__(self)
ConditionalProcessingAttributes.__init__(self)
XlinkAttributes.__init__(self)
#add groups
self._allowedSvgChildNodes.update(self.SVG_GROUP_ANIMATION_ELEMENTS, self.SVG_GROUP_DESCRIPTIVE_ELEMENTS,
self.SVG_GROUP_SHAPE_ELEMENTS, self.SVG_GROUP_STRUCTURAL_ELEMENTS,
self.SVG_GROUP_GRADIENT_ELEMENTS)
#add indivudual elements
self._allowedSvgChildNodes.update(
{self.SVG_A_NODE, self.SVG_ALT_GLYPH_DEF_NODE, self.SVG_CLIP_PATH_NODE, self.SVG_COLOR_PROFILE_NODE,
self.SVG_CURSOR_NODE, self.SVG_FILTER_NODE, self.SVG_FONT_NODE,
self.SVG_FONT_FACE_NODE, self.SVG_FOREIGN_OBJECT_NODE, self.SVG_IMAGE_NODE, self.SVG_MARKER_NODE,
self.SVG_MASK_NODE, self.SVG_PATTERN_NODE, self.SVG_SCRIPT_NODE,
self.SVG_STYLE_NODE, self.SVG_SWITCH_NODE, self.SVG_TEXT_NODE, self.SVG_VIEW_NODE})
def setExternalResourcesRequired(self, data):
allowedValues = ['true', 'false']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED, data)
def setViewBox(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_VIEW_BOX, data)
def setPreserveAspectRatio(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_PRESERVE_ASPECT_RATIO, data)
def setPatternUnits(self, data):
allowedValues = ['userSpaceOnUse', 'objectBoundingBox']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_UNITS, data)
def setPatternContentUnits(self, data):
allowedValues = ['userSpaceOnUse', 'objectBoundingBox']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_CONTENT_UNITS, data)
def setPatternTranform(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_TRANSFORM, data)
def getExternalResourcesRequired(self):
node = self._getNodeAttribute(self.ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED)
if node is not None:
return node.nodeValue
return None
def getViewBox(self):
node = self._getNodeAttribute(self.ATTRIBUTE_VIEW_BOX)
if node is not None:
return node.nodeValue
return None
def getPreserveAspectRatio(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PRESERVE_ASPECT_RATIO)
if node is not None:
return node.nodeValue
return None
def getPatternUnits(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_UNITS)
if node is not None:
return node.nodeValue
return None
def getPatternContentUnits(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_CONTENT_UNITS)
if node is not None:
return node.nodeValue
return None
def getPatternTransform(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_TRANSFORM)
if node is not None:
return node.nodeValue
return None | src/RGT/XML/SVG/patternNode.py | from RGT.XML.SVG.baseContainerNode import BaseContainerNode
from RGT.XML.SVG.Attribs.conditionalProcessingAttributes import ConditionalProcessingAttributes
from RGT.XML.SVG.Attribs.xlinkAttributes import XlinkAttributes
from RGT.XML.SVG.Attribs.positionAttributes import PositionAttributes
from RGT.XML.SVG.Attribs.sizeAttributes import SizeAttributes
from types import StringType
from RGT.XML.SVG.basicSvgNode import BasicSvgNode
class PatternNode(BaseContainerNode, PositionAttributes, SizeAttributes, ConditionalProcessingAttributes,
XlinkAttributes):
svgNodeType = BasicSvgNode.SVG_PATTERN_NODE
ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED = 'externalResourcesRequired'
ATTRIBUTE_VIEW_BOX = 'viewBox'
ATTRIBUTE_PRESERVE_ASPECT_RATIO = 'preserveAspectRatio'
ATTRIBUTE_WIDTH = 'width'
ATTRIBUTE_HEIGHT = 'height'
ATTRIBUTE_PATTERN_UNITS = 'patternUnits'
ATTRIBUTE_PATTERN_CONTENT_UNITS = 'patternContentUnits'
ATTRIBUTE_PATTERN_TRANSFORM = 'patternTransform'
def __init__(self, ownerDoc):
BaseContainerNode.__init__(self, ownerDoc, 'pattern')
PositionAttributes.__init__(self)
SizeAttributes.__init__(self)
ConditionalProcessingAttributes.__init__(self)
XlinkAttributes.__init__(self)
#add groups
self._allowedSvgChildNodes.update(self.SVG_GROUP_ANIMATION_ELEMENTS, self.SVG_GROUP_DESCRIPTIVE_ELEMENTS,
self.SVG_GROUP_SHAPE_ELEMENTS, self.SVG_GROUP_STRUCTURAL_ELEMENTS,
self.SVG_GROUP_GRADIENT_ELEMENTS)
#add indivudual elements
self._allowedSvgChildNodes.update(
{self.SVG_A_NODE, self.SVG_ALT_GLYPH_DEF_NODE, self.SVG_CLIP_PATH_NODE, self.SVG_COLOR_PROFILE_NODE,
self.SVG_CURSOR_NODE, self.SVG_FILTER_NODE, self.SVG_FONT_NODE,
self.SVG_FONT_FACE_NODE, self.SVG_FOREIGN_OBJECT_NODE, self.SVG_IMAGE_NODE, self.SVG_MARKER_NODE,
self.SVG_MASK_NODE, self.SVG_PATTERN_NODE, self.SVG_SCRIPT_NODE,
self.SVG_STYLE_NODE, self.SVG_SWITCH_NODE, self.SVG_TEXT_NODE, self.SVG_VIEW_NODE})
def setExternalResourcesRequired(self, data):
allowedValues = ['true', 'false']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED, data)
def setViewBox(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_VIEW_BOX, data)
def setPreserveAspectRatio(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_PRESERVE_ASPECT_RATIO, data)
def setPatternUnits(self, data):
allowedValues = ['userSpaceOnUse', 'objectBoundingBox']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_UNITS, data)
def setPatternContentUnits(self, data):
allowedValues = ['userSpaceOnUse', 'objectBoundingBox']
if data is not None:
if data not in allowedValues:
values = ''
for value in allowedValues:
values += value + ', '
values = values[0: len(values) - 2]
raise ValueError('Value not allowed, only ' + values + 'are allowed')
else:
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_CONTENT_UNITS, data)
def setPatternTranform(self, data):
if data is not None:
if type(data) is not StringType:
data = str(data)
self._setNodeAttribute(self.ATTRIBUTE_PATTERN_TRANSFORM, data)
def getExternalResourcesRequired(self):
node = self._getNodeAttribute(self.ATTRIBUTE_EXTERNAL_RESOURCES_REQUIRED)
if node is not None:
return node.nodeValue
return None
def getViewBox(self):
node = self._getNodeAttribute(self.ATTRIBUTE_VIEW_BOX)
if node is not None:
return node.nodeValue
return None
def getPreserveAspectRatio(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PRESERVE_ASPECT_RATIO)
if node is not None:
return node.nodeValue
return None
def getPatternUnits(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_UNITS)
if node is not None:
return node.nodeValue
return None
def getPatternContentUnits(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_CONTENT_UNITS)
if node is not None:
return node.nodeValue
return None
def getPatternTransform(self):
node = self._getNodeAttribute(self.ATTRIBUTE_PATTERN_TRANSFORM)
if node is not None:
return node.nodeValue
return None | 0.461259 | 0.242632 |
import asyncio
from collections import defaultdict
import logging
import immp
log = logging.getLogger(__name__)
class AccessPredicate:
"""
Interface for hooks to provide channel access control from a backing source.
"""
async def channel_access(self, channel, user):
"""
Verify if a user is allowed access to a channel.
Args:
channel (.Channel):
Target channel.
user (.User):
Incoming user to be verified.
Returns:
bool:
``True`` if the user is to be granted access.
"""
raise NotImplementedError
class ChannelAccessHook(immp.Hook, AccessPredicate):
"""
Hook for controlling membership of, and joins to, secure channels.
"""
schema = immp.Schema({immp.Optional("hooks", dict): {str: [str]},
immp.Optional("exclude", dict): {str: [str]},
immp.Optional("joins", True): bool,
immp.Optional("startup", False): bool,
immp.Optional("passive", False): bool})
@property
def hooks(self):
mapping = {}
for name, channels in self.config["hooks"].items():
try:
hook = self.host.hooks[name]
except KeyError:
raise immp.ConfigError("Hook '{}' not registered to host".format(name))
if not isinstance(hook, AccessPredicate):
raise immp.HookError("Hook '{}' does not implement AccessPredicate".format(name))
try:
channels = tuple(self.host.channels[label] for label in channels)
except KeyError as e:
raise immp.ConfigError("Channel '{}' not registered to host".format(e.args[0]))
mapping[hook] = channels
return mapping
@property
def channels(self):
inverse = defaultdict(list)
for hook, channels in self.hooks.items():
for channel in channels:
inverse[channel].append(hook)
return inverse
async def channel_access(self, channel, user):
# Example predicate to block all access.
return False
async def _predicate(self, hook, channel, user):
if not isinstance(hook, AccessPredicate):
raise immp.HookError("Hook '{}' does not implement AccessPredicate".format(hook.name))
allow = await hook.channel_access(channel, user)
if not allow:
log.debug("Hook %r disallows %r in %r", hook.name, user, channel)
if not self.config["passive"]:
await channel.remove(user)
return allow
async def _verify(self, channel, user):
if user.id in self.config["exclude"].get(user.plug.name, []):
log.debug("Skipping excluded user %r in channel %r", user, channel)
return
elif await user.is_system():
log.debug("Skipping system user %r in channel %r", user, channel)
return
try:
hooks = self.channels[channel]
except KeyError:
return
for hook in hooks:
if not await self._predicate(hook, channel, user):
break
async def _startup_check(self):
log.debug("Running startup access checks")
for channel in self.channels:
members = await channel.members()
if not members:
continue
for user in members:
await self._verify(channel, user)
log.debug("Finished startup access checks")
async def start(self):
await super().start()
if self.config["startup"]:
asyncio.ensure_future(self._startup_check())
async def on_receive(self, sent, source, primary):
await super().on_receive(sent, source, primary)
if not self.config["joins"] or not primary or sent != source or not source.joined:
return
for user in source.joined:
await self._verify(sent.channel, user) | immp/hook/access.py | import asyncio
from collections import defaultdict
import logging
import immp
log = logging.getLogger(__name__)
class AccessPredicate:
"""
Interface for hooks to provide channel access control from a backing source.
"""
async def channel_access(self, channel, user):
"""
Verify if a user is allowed access to a channel.
Args:
channel (.Channel):
Target channel.
user (.User):
Incoming user to be verified.
Returns:
bool:
``True`` if the user is to be granted access.
"""
raise NotImplementedError
class ChannelAccessHook(immp.Hook, AccessPredicate):
"""
Hook for controlling membership of, and joins to, secure channels.
"""
schema = immp.Schema({immp.Optional("hooks", dict): {str: [str]},
immp.Optional("exclude", dict): {str: [str]},
immp.Optional("joins", True): bool,
immp.Optional("startup", False): bool,
immp.Optional("passive", False): bool})
@property
def hooks(self):
mapping = {}
for name, channels in self.config["hooks"].items():
try:
hook = self.host.hooks[name]
except KeyError:
raise immp.ConfigError("Hook '{}' not registered to host".format(name))
if not isinstance(hook, AccessPredicate):
raise immp.HookError("Hook '{}' does not implement AccessPredicate".format(name))
try:
channels = tuple(self.host.channels[label] for label in channels)
except KeyError as e:
raise immp.ConfigError("Channel '{}' not registered to host".format(e.args[0]))
mapping[hook] = channels
return mapping
@property
def channels(self):
inverse = defaultdict(list)
for hook, channels in self.hooks.items():
for channel in channels:
inverse[channel].append(hook)
return inverse
async def channel_access(self, channel, user):
# Example predicate to block all access.
return False
async def _predicate(self, hook, channel, user):
if not isinstance(hook, AccessPredicate):
raise immp.HookError("Hook '{}' does not implement AccessPredicate".format(hook.name))
allow = await hook.channel_access(channel, user)
if not allow:
log.debug("Hook %r disallows %r in %r", hook.name, user, channel)
if not self.config["passive"]:
await channel.remove(user)
return allow
async def _verify(self, channel, user):
if user.id in self.config["exclude"].get(user.plug.name, []):
log.debug("Skipping excluded user %r in channel %r", user, channel)
return
elif await user.is_system():
log.debug("Skipping system user %r in channel %r", user, channel)
return
try:
hooks = self.channels[channel]
except KeyError:
return
for hook in hooks:
if not await self._predicate(hook, channel, user):
break
async def _startup_check(self):
log.debug("Running startup access checks")
for channel in self.channels:
members = await channel.members()
if not members:
continue
for user in members:
await self._verify(channel, user)
log.debug("Finished startup access checks")
async def start(self):
await super().start()
if self.config["startup"]:
asyncio.ensure_future(self._startup_check())
async def on_receive(self, sent, source, primary):
await super().on_receive(sent, source, primary)
if not self.config["joins"] or not primary or sent != source or not source.joined:
return
for user in source.joined:
await self._verify(sent.channel, user) | 0.820901 | 0.163546 |
class MnExtractor:
def __init__(self):
self.binarizer = Binarizer()
self.skeletonizer = Skeletonizer()
#Calculate the crossing number
def calculate_cn(self, img, row_pos, col_pos):
#Iterating through the neighbour of p from p2 -> p3 -> p4 -> p5 -> p6 -> p7 -> p8
transitions = [(-1, 0), (-1, 1), (0, 1), (1, 1), (1, 0), (1, -1), (0, -1), (-1, -1), (-1, 0)]
total = 0
for transition in range(len(transitions) - 1):
row = row_pos + transitions[transition][0]
col = col_pos + transitions[transition][1]
next_row = row_pos + transitions[transition + 1][0]
next_col = col_pos + transitions[transition + 1][1]
total += abs(img[row, col] / 255 - img[next_row, next_col] / 255) #Normalize to 0 - 1
return total / 2
#Check if the point is located at the edge of the region or not
#Shifing from right to left
def isLeftBoundary(self, img, row_pos, col_pos):
rows, cols = img.shape
isBound = True
for k in range(col_pos - 1, -1, -1):
#If detected black part within the block
if img[row_pos, k] == 0:
isBound = False
break
return isBound
#Shifing from left to right
def isRightBoundary(self, img, row_pos, col_pos):
rows, cols = img.shape
isBound = True
for k in range(col_pos + 1, cols):
#If detected black part within the block
if img[row_pos, k] == 0:
isBound = False
break
return isBound
#This is used to handle bifurcation minutia case since it's joint between 3 lines and not the endpoint.
def isBoundary(self, img, row_pos, col_pos):
if self.isLeftBoundary(img, row_pos, col_pos) or self.isRightBoundary(img, row_pos, col_pos):
return True
return False
#Euclidian distance between 2 points
def distance(self, x1, y1, x2, y2):
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def extract(self, enhancedImg):
rows, cols = enhancedImg.shape
binImg = self.binarizer.binarize(enhancedImg)
skeletonImg = self.skeletonizer.skeletonize(binImg)
#Set of minutias
mnSet = []
count = 0
for row in range(1, rows - 1):
for col in range(1, cols - 1):
if(skeletonImg[row, col] == 0):
cn = self.calculate_cn(skeletonImg, row, col)
if cn == 1:
#In case that crossing number is 1 -> Endpoint Minutia
mnSet.append([row, col, M_TYPE_ENDPOINT])
elif cn == 3 and not self.isBoundary(enhancedImg, row, col):
#In case that crossing number is 3 -> Bifurcation Minutia
mnSet.append([row, col, M_TYPE_BIFURCATION])
#Sort all of detected minutiae by distance between coordinate of minutia point from the center of enhanced image
mnSet.sort(key=lambda coord: self.distance(rows // 2, cols // 2, coord[0], coord[1]))
return mnSet | MnExtractor.py | class MnExtractor:
def __init__(self):
self.binarizer = Binarizer()
self.skeletonizer = Skeletonizer()
#Calculate the crossing number
def calculate_cn(self, img, row_pos, col_pos):
#Iterating through the neighbour of p from p2 -> p3 -> p4 -> p5 -> p6 -> p7 -> p8
transitions = [(-1, 0), (-1, 1), (0, 1), (1, 1), (1, 0), (1, -1), (0, -1), (-1, -1), (-1, 0)]
total = 0
for transition in range(len(transitions) - 1):
row = row_pos + transitions[transition][0]
col = col_pos + transitions[transition][1]
next_row = row_pos + transitions[transition + 1][0]
next_col = col_pos + transitions[transition + 1][1]
total += abs(img[row, col] / 255 - img[next_row, next_col] / 255) #Normalize to 0 - 1
return total / 2
#Check if the point is located at the edge of the region or not
#Shifing from right to left
def isLeftBoundary(self, img, row_pos, col_pos):
rows, cols = img.shape
isBound = True
for k in range(col_pos - 1, -1, -1):
#If detected black part within the block
if img[row_pos, k] == 0:
isBound = False
break
return isBound
#Shifing from left to right
def isRightBoundary(self, img, row_pos, col_pos):
rows, cols = img.shape
isBound = True
for k in range(col_pos + 1, cols):
#If detected black part within the block
if img[row_pos, k] == 0:
isBound = False
break
return isBound
#This is used to handle bifurcation minutia case since it's joint between 3 lines and not the endpoint.
def isBoundary(self, img, row_pos, col_pos):
if self.isLeftBoundary(img, row_pos, col_pos) or self.isRightBoundary(img, row_pos, col_pos):
return True
return False
#Euclidian distance between 2 points
def distance(self, x1, y1, x2, y2):
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def extract(self, enhancedImg):
rows, cols = enhancedImg.shape
binImg = self.binarizer.binarize(enhancedImg)
skeletonImg = self.skeletonizer.skeletonize(binImg)
#Set of minutias
mnSet = []
count = 0
for row in range(1, rows - 1):
for col in range(1, cols - 1):
if(skeletonImg[row, col] == 0):
cn = self.calculate_cn(skeletonImg, row, col)
if cn == 1:
#In case that crossing number is 1 -> Endpoint Minutia
mnSet.append([row, col, M_TYPE_ENDPOINT])
elif cn == 3 and not self.isBoundary(enhancedImg, row, col):
#In case that crossing number is 3 -> Bifurcation Minutia
mnSet.append([row, col, M_TYPE_BIFURCATION])
#Sort all of detected minutiae by distance between coordinate of minutia point from the center of enhanced image
mnSet.sort(key=lambda coord: self.distance(rows // 2, cols // 2, coord[0], coord[1]))
return mnSet | 0.624866 | 0.506286 |
import asyncio
import logging
import sys
import unittest
from typing import AsyncIterator, Iterable
from unittest.mock import Mock, call
import pytest
from amundsen_gremlin.utils.streams import (
PeekingIterator, _assure_collection, async_consume_in_chunks,
consume_in_chunks, consume_in_chunks_with_state, one_chunk,
reduce_in_chunks
)
class TestConsumer(unittest.TestCase):
def test_consume_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
parent = Mock()
parent.values = values
parent.consumer = consumer
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
count = consume_in_chunks(stream=stream(), n=2, consumer=consumer)
self.assertEqual(count, 5)
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1)),
call.values(), call.values(), call.consumer((2, 3)), call.consumer((4,))],
parent.mock_calls)
def test_consume_in_chunks_with_exception(self) -> None:
consumer = Mock()
def stream() -> Iterable[int]:
yield from range(10)
raise KeyError('hi')
with self.assertRaisesRegex(KeyError, 'hi'):
consume_in_chunks(stream=stream(), n=4, consumer=consumer)
self.assertSequenceEqual([call.consumer((0, 1, 2, 3)), call.consumer((4, 5, 6, 7))], consumer.mock_calls)
def test_consume_in_chunks_with_state(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
consumer.side_effect = list(range(1, 4))
state = Mock()
state.side_effect = lambda x: x * 10
parent = Mock()
parent.values = values
parent.consumer = consumer
parent.state = state
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
result = consume_in_chunks_with_state(stream=stream(), n=2, consumer=consumer, state=state)
self.assertSequenceEqual(tuple(result), (0, 10, 20, 30, 40))
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.state(0), call.state(1),
call.consumer((0, 1)), call.values(), call.values(), call.state(2), call.state(3),
call.consumer((2, 3)), call.state(4), call.consumer((4,))],
parent.mock_calls)
def test_consume_in_chunks_no_batch(self) -> None:
consumer = Mock()
count = consume_in_chunks(stream=range(100000000), n=-1, consumer=consumer)
self.assertEqual(100000000, count)
consumer.assert_called_once()
def test_reduce_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
consumer.side_effect = list(range(1, 4))
parent = Mock()
parent.values = values
parent.consumer = consumer
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
result = reduce_in_chunks(stream=stream(), n=2, initial=0, consumer=consumer)
self.assertEqual(result, 3)
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1), 0),
call.values(), call.values(), call.consumer((2, 3), 1), call.consumer((4,), 2)],
parent.mock_calls)
@pytest.mark.skipif(sys.version_info < (3, 7), reason="requires python3.7 or higher")
def test_async_consume_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
parent = Mock()
parent.values = values
parent.consumer = consumer
async def stream() -> AsyncIterator[int]:
for i in range(5):
yield values()
count = asyncio.run(async_consume_in_chunks(stream=stream(), n=2, consumer=consumer))
self.assertEqual(5, count, 'count')
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1)),
call.values(), call.values(), call.consumer((2, 3)), call.consumer((4,))],
parent.mock_calls)
def test_one_chunk_logging(self) -> None:
it = PeekingIterator(range(1, 4))
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([1], tuple(actual))
self.assertTrue(has_more)
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([2], tuple(actual))
self.assertTrue(has_more)
with self.assertLogs(logger='amundsen_gremlin.utils.streams', level=logging.ERROR):
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([3], tuple(actual))
self.assertFalse(has_more)
def test_assure_collection(self) -> None:
actual = _assure_collection(iter(range(2)))
self.assertIsInstance(actual, tuple)
self.assertEqual((0, 1), actual)
actual = _assure_collection(list(range(2)))
self.assertIsInstance(actual, list)
self.assertEqual([0, 1], actual)
actual = _assure_collection(set(range(2)))
self.assertIsInstance(actual, set)
self.assertEqual({0, 1}, actual)
actual = _assure_collection(frozenset(range(2)))
self.assertIsInstance(actual, frozenset)
self.assertEqual(frozenset({0, 1}), actual)
class TestPeekingIterator(unittest.TestCase):
# TODO: it'd be good to test the locking
def test_no_peek(self) -> None:
it = PeekingIterator(range(3))
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
self.assertEqual(2, next(it))
with self.assertRaises(StopIteration):
next(it)
def test_peek_is_next(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
self.assertTrue(it.has_more())
self.assertEqual(0, next(it))
self.assertTrue(it.has_more())
self.assertEqual(1, next(it))
self.assertFalse(it.has_more())
with self.assertRaises(StopIteration):
next(it)
def test_peek_repeats(self) -> None:
it = PeekingIterator(range(2))
for _ in range(100):
self.assertEqual(0, it.peek())
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
def test_peek_after_exhaustion(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
with self.assertRaises(StopIteration):
next(it)
with self.assertRaises(StopIteration):
it.peek()
self.assertEqual(999, it.peek_default(999))
def test_take_peeked(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
it.take_peeked(0)
self.assertEqual(1, next(it))
with self.assertRaises(StopIteration):
next(it)
def test_take_peeked_wrong_value(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
with self.assertRaisesRegex(AssertionError, 'expected the peaked value to be the same'):
it.take_peeked(1)
it.take_peeked(0)
self.assertEqual(1, next(it))
# TODO: test PeekingAsyncIterator directly | amundsengremlin/tests/unit/utils/test_streams.py |
import asyncio
import logging
import sys
import unittest
from typing import AsyncIterator, Iterable
from unittest.mock import Mock, call
import pytest
from amundsen_gremlin.utils.streams import (
PeekingIterator, _assure_collection, async_consume_in_chunks,
consume_in_chunks, consume_in_chunks_with_state, one_chunk,
reduce_in_chunks
)
class TestConsumer(unittest.TestCase):
def test_consume_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
parent = Mock()
parent.values = values
parent.consumer = consumer
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
count = consume_in_chunks(stream=stream(), n=2, consumer=consumer)
self.assertEqual(count, 5)
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1)),
call.values(), call.values(), call.consumer((2, 3)), call.consumer((4,))],
parent.mock_calls)
def test_consume_in_chunks_with_exception(self) -> None:
consumer = Mock()
def stream() -> Iterable[int]:
yield from range(10)
raise KeyError('hi')
with self.assertRaisesRegex(KeyError, 'hi'):
consume_in_chunks(stream=stream(), n=4, consumer=consumer)
self.assertSequenceEqual([call.consumer((0, 1, 2, 3)), call.consumer((4, 5, 6, 7))], consumer.mock_calls)
def test_consume_in_chunks_with_state(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
consumer.side_effect = list(range(1, 4))
state = Mock()
state.side_effect = lambda x: x * 10
parent = Mock()
parent.values = values
parent.consumer = consumer
parent.state = state
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
result = consume_in_chunks_with_state(stream=stream(), n=2, consumer=consumer, state=state)
self.assertSequenceEqual(tuple(result), (0, 10, 20, 30, 40))
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.state(0), call.state(1),
call.consumer((0, 1)), call.values(), call.values(), call.state(2), call.state(3),
call.consumer((2, 3)), call.state(4), call.consumer((4,))],
parent.mock_calls)
def test_consume_in_chunks_no_batch(self) -> None:
consumer = Mock()
count = consume_in_chunks(stream=range(100000000), n=-1, consumer=consumer)
self.assertEqual(100000000, count)
consumer.assert_called_once()
def test_reduce_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
consumer.side_effect = list(range(1, 4))
parent = Mock()
parent.values = values
parent.consumer = consumer
def stream() -> Iterable[int]:
for _ in range(5):
yield values()
result = reduce_in_chunks(stream=stream(), n=2, initial=0, consumer=consumer)
self.assertEqual(result, 3)
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1), 0),
call.values(), call.values(), call.consumer((2, 3), 1), call.consumer((4,), 2)],
parent.mock_calls)
@pytest.mark.skipif(sys.version_info < (3, 7), reason="requires python3.7 or higher")
def test_async_consume_in_chunks(self) -> None:
values = Mock()
values.side_effect = list(range(5))
consumer = Mock()
parent = Mock()
parent.values = values
parent.consumer = consumer
async def stream() -> AsyncIterator[int]:
for i in range(5):
yield values()
count = asyncio.run(async_consume_in_chunks(stream=stream(), n=2, consumer=consumer))
self.assertEqual(5, count, 'count')
# this might look at little weird, but PeekingIterator is why
self.assertSequenceEqual([call.values(), call.values(), call.values(), call.consumer((0, 1)),
call.values(), call.values(), call.consumer((2, 3)), call.consumer((4,))],
parent.mock_calls)
def test_one_chunk_logging(self) -> None:
it = PeekingIterator(range(1, 4))
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([1], tuple(actual))
self.assertTrue(has_more)
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([2], tuple(actual))
self.assertTrue(has_more)
with self.assertLogs(logger='amundsen_gremlin.utils.streams', level=logging.ERROR):
actual, has_more = one_chunk(it=it, n=2, metric=lambda x: x)
self.assertSequenceEqual([3], tuple(actual))
self.assertFalse(has_more)
def test_assure_collection(self) -> None:
actual = _assure_collection(iter(range(2)))
self.assertIsInstance(actual, tuple)
self.assertEqual((0, 1), actual)
actual = _assure_collection(list(range(2)))
self.assertIsInstance(actual, list)
self.assertEqual([0, 1], actual)
actual = _assure_collection(set(range(2)))
self.assertIsInstance(actual, set)
self.assertEqual({0, 1}, actual)
actual = _assure_collection(frozenset(range(2)))
self.assertIsInstance(actual, frozenset)
self.assertEqual(frozenset({0, 1}), actual)
class TestPeekingIterator(unittest.TestCase):
# TODO: it'd be good to test the locking
def test_no_peek(self) -> None:
it = PeekingIterator(range(3))
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
self.assertEqual(2, next(it))
with self.assertRaises(StopIteration):
next(it)
def test_peek_is_next(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
self.assertTrue(it.has_more())
self.assertEqual(0, next(it))
self.assertTrue(it.has_more())
self.assertEqual(1, next(it))
self.assertFalse(it.has_more())
with self.assertRaises(StopIteration):
next(it)
def test_peek_repeats(self) -> None:
it = PeekingIterator(range(2))
for _ in range(100):
self.assertEqual(0, it.peek())
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
def test_peek_after_exhaustion(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, next(it))
self.assertEqual(1, next(it))
with self.assertRaises(StopIteration):
next(it)
with self.assertRaises(StopIteration):
it.peek()
self.assertEqual(999, it.peek_default(999))
def test_take_peeked(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
it.take_peeked(0)
self.assertEqual(1, next(it))
with self.assertRaises(StopIteration):
next(it)
def test_take_peeked_wrong_value(self) -> None:
it = PeekingIterator(range(2))
self.assertEqual(0, it.peek())
with self.assertRaisesRegex(AssertionError, 'expected the peaked value to be the same'):
it.take_peeked(1)
it.take_peeked(0)
self.assertEqual(1, next(it))
# TODO: test PeekingAsyncIterator directly | 0.539469 | 0.486697 |
from PySide2.QtWidgets import *
from model import configuration
from resources.ui import config_item_ui
import vcs.p4manager as p4
class ConfigurationItemView(QWidget, config_item_ui.Ui_PackageConfiguration):
def __init__(self, packageConfig):
QWidget.__init__(self)
self.setupUi(self)
self.connectionType.currentIndexChanged.connect(self.on_index_changed)
self.vcs_checkbox.stateChanged.connect(self.on_vcs_checkbox_changed)
self.isValid = False
if packageConfig:
self.packageConfiguration = packageConfig
self.load_setting()
else:
self.packageConfiguration = configuration.PackageConfiguration()
if self.packageConfiguration.connection_type == configuration.ConnectionType.LOCAL:
self.display_network_ui()
elif self.packageConfiguration.connection_type == configuration.ConnectionType.FTP:
self.display_ftp_ui()
self.vcs_checkbox.setChecked(self.packageConfiguration.use_vcs)
self.vcs_widget.setEnabled(self.vcs_checkbox.isChecked())
def on_vcs_checkbox_changed(self):
self.vcs_widget.setEnabled(self.vcs_checkbox.isChecked())
def on_index_changed(self, index):
if index == 0:
self.display_network_ui()
self.packageConfiguration.set_local_network_connection()
if index == 1:
self.display_ftp_ui()
self.packageConfiguration.set_ftp_connection()
def display_ftp_ui(self):
self.networkPath.setDisabled(True)
self.networkPath.hide()
self.pathLbl.hide()
self.host.setEnabled(True)
self.host.show()
self.hostLbl.show()
self.password.setEnabled(True)
self.password.show()
self.passwordLbl.show()
self.username.setEnabled(True)
self.username.show()
self.usernameLbl.show()
self.ftppath.setEnabled(True)
self.ftppath.show()
self.ftpPathLbl.show()
def display_network_ui(self):
self.networkPath.setEnabled(True)
self.networkPath.show()
self.pathLbl.show()
self.host.setDisabled(True)
self.host.hide()
self.hostLbl.hide()
self.password.setDisabled(True)
self.password.hide()
self.passwordLbl.hide()
self.username.setDisabled(True)
self.username.hide()
self.usernameLbl.hide()
self.ftppath.setDisabled(True)
self.ftppath.hide()
self.ftpPathLbl.hide()
def load_setting(self):
self.packageName.setText(self.packageConfiguration.package_name)
self.networkPath.setText(self.packageConfiguration.network_path)
self.host.setText(self.packageConfiguration.host)
self.password.setText(self.packageConfiguration.password)
self.username.setText(self.packageConfiguration.username)
self.ftppath.setText(self.packageConfiguration.ftp_path)
useVCS = True if self.packageConfiguration.use_vcs=="True" else False
self.vcs_checkbox.setChecked(useVCS)
vcsType = configuration.VCSType.Perforce
self.vcs_combobox.setCurrentIndex(vcsType)
if vcsType == configuration.VCSType.Perforce:
clientName, clientRoot = p4.getP4info()
self.client_edit.setText(clientName)
if self.packageConfiguration.host:
self.connectionType.setCurrentIndex(1)
else:
self.connectionType.setCurrentIndex(0)
def get_setting(self):
self.packageConfiguration.package_name = self.packageName.text()
self.packageConfiguration.network_path = self.networkPath.text()
self.packageConfiguration.host = self.host.text()
self.packageConfiguration.password = self.password.text()
self.packageConfiguration.username = self.username.text()
self.packageConfiguration.ftp_path = self.ftppath.text()
self.packageConfiguration.use_vcs =self.vcs_checkbox.isChecked()
self.packageConfiguration.vcs_type = self.vcs_combobox.currentText()
if self.packageConfiguration.isValid():
return self.packageConfiguration
else:
return None | src/max_tools_updater/controller/configurationItemView.py | from PySide2.QtWidgets import *
from model import configuration
from resources.ui import config_item_ui
import vcs.p4manager as p4
class ConfigurationItemView(QWidget, config_item_ui.Ui_PackageConfiguration):
def __init__(self, packageConfig):
QWidget.__init__(self)
self.setupUi(self)
self.connectionType.currentIndexChanged.connect(self.on_index_changed)
self.vcs_checkbox.stateChanged.connect(self.on_vcs_checkbox_changed)
self.isValid = False
if packageConfig:
self.packageConfiguration = packageConfig
self.load_setting()
else:
self.packageConfiguration = configuration.PackageConfiguration()
if self.packageConfiguration.connection_type == configuration.ConnectionType.LOCAL:
self.display_network_ui()
elif self.packageConfiguration.connection_type == configuration.ConnectionType.FTP:
self.display_ftp_ui()
self.vcs_checkbox.setChecked(self.packageConfiguration.use_vcs)
self.vcs_widget.setEnabled(self.vcs_checkbox.isChecked())
def on_vcs_checkbox_changed(self):
self.vcs_widget.setEnabled(self.vcs_checkbox.isChecked())
def on_index_changed(self, index):
if index == 0:
self.display_network_ui()
self.packageConfiguration.set_local_network_connection()
if index == 1:
self.display_ftp_ui()
self.packageConfiguration.set_ftp_connection()
def display_ftp_ui(self):
self.networkPath.setDisabled(True)
self.networkPath.hide()
self.pathLbl.hide()
self.host.setEnabled(True)
self.host.show()
self.hostLbl.show()
self.password.setEnabled(True)
self.password.show()
self.passwordLbl.show()
self.username.setEnabled(True)
self.username.show()
self.usernameLbl.show()
self.ftppath.setEnabled(True)
self.ftppath.show()
self.ftpPathLbl.show()
def display_network_ui(self):
self.networkPath.setEnabled(True)
self.networkPath.show()
self.pathLbl.show()
self.host.setDisabled(True)
self.host.hide()
self.hostLbl.hide()
self.password.setDisabled(True)
self.password.hide()
self.passwordLbl.hide()
self.username.setDisabled(True)
self.username.hide()
self.usernameLbl.hide()
self.ftppath.setDisabled(True)
self.ftppath.hide()
self.ftpPathLbl.hide()
def load_setting(self):
self.packageName.setText(self.packageConfiguration.package_name)
self.networkPath.setText(self.packageConfiguration.network_path)
self.host.setText(self.packageConfiguration.host)
self.password.setText(self.packageConfiguration.password)
self.username.setText(self.packageConfiguration.username)
self.ftppath.setText(self.packageConfiguration.ftp_path)
useVCS = True if self.packageConfiguration.use_vcs=="True" else False
self.vcs_checkbox.setChecked(useVCS)
vcsType = configuration.VCSType.Perforce
self.vcs_combobox.setCurrentIndex(vcsType)
if vcsType == configuration.VCSType.Perforce:
clientName, clientRoot = p4.getP4info()
self.client_edit.setText(clientName)
if self.packageConfiguration.host:
self.connectionType.setCurrentIndex(1)
else:
self.connectionType.setCurrentIndex(0)
def get_setting(self):
self.packageConfiguration.package_name = self.packageName.text()
self.packageConfiguration.network_path = self.networkPath.text()
self.packageConfiguration.host = self.host.text()
self.packageConfiguration.password = self.password.text()
self.packageConfiguration.username = self.username.text()
self.packageConfiguration.ftp_path = self.ftppath.text()
self.packageConfiguration.use_vcs =self.vcs_checkbox.isChecked()
self.packageConfiguration.vcs_type = self.vcs_combobox.currentText()
if self.packageConfiguration.isValid():
return self.packageConfiguration
else:
return None | 0.44083 | 0.095771 |
from django.views.decorators.cache import never_cache
from django.views.generic import TemplateView
from django_filters import rest_framework as django_filters
from rest_framework import filters
from rest_framework import viewsets, permissions
from rest_framework.pagination import PageNumberPagination
from rest_framework.response import Response
from rest_framework.views import APIView
from rest_framework_simplejwt import authentication
from backend.api import utils
from backend.api.filters import LibraryGameFilter
from backend.api.serializers import *
User = get_user_model()
# Serve Vue Application
index_view = never_cache(TemplateView.as_view(template_name='index.html'))
class StandardResultsSetPagination(PageNumberPagination):
"""60 is divisible by 2,3,4,5 and 6 making it flexible to adjust frontend layout.
All requests with pagination should take page_size with a base of 60"""
page_size = 60
page_size_query_param = 'page_size'
max_page_size = 1000
class SupplierViewSet(viewsets.ModelViewSet):
queryset = Supplier.objects.order_by('name')
serializer_class = SupplierSerializer
authentication_classes = (authentication.JWTAuthentication,)
permission_classes = (permissions.IsAdminUser,)
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
search_fields = ['name']
class PlayerViewSet(viewsets.ModelViewSet):
queryset = User.objects.order_by('first_name', 'last_name')
serializer_class = PlayerSerializer
authentication_classes = (authentication.JWTAuthentication,)
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
search_fields = ['first_name', 'last_name', 'username', 'email']
# permission_classes = (permissions.IsAdminUser,)
class LibraryGameViewSet(viewsets.ModelViewSet):
queryset = LibraryGame.objects.order_by('game__name')
serializer_class = LibraryGameSerializer
search_fields = ['game__name', 'game__other_names']
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
filterset_class = LibraryGameFilter
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,)
authentication_classes = [authentication.JWTAuthentication]
pagination_class = StandardResultsSetPagination
def perform_create(self, serializer):
bggid = serializer.initial_data['game_id']
game = utils.BGGGame.find(bggid)
if game is None:
game = utils.BGGGame.create(bggid)
serializer.is_valid()
serializer.save(game=game)
class StoreGameViewSet(viewsets.ModelViewSet):
queryset = StoreGame.objects.order_by('game__name')
search_fields = ['game__name', 'game__other_names']
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,)
authentication_classes = [authentication.JWTAuthentication]
pagination_class = StandardResultsSetPagination
def get_serializer_class(self):
if self.request.user.is_staff:
return StoreGameSerializer
return AnonStoreGameSerializer
def perform_create(self, serializer):
bggid = serializer.initial_data['game_id']
game = utils.BGGGame.find(bggid)
if game is None:
game = utils.BGGGame.create(bggid)
serializer.is_valid()
serializer.save(game=game)
class UserViewSet(viewsets.ModelViewSet):
queryset = User.objects.all()
serializer_class = UserSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.IsAdminUser,)
def get_object(self):
pk = self.kwargs.get('pk')
if pk == "current":
return self.request.user
return super(UserViewSet, self).get_object()
class WithdrawViewSet(viewsets.ModelViewSet):
queryset = Withdraw.objects.all()
serializer_class = WithdrawSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.IsAdminUser,)
class StatisticsViewSet(APIView):
def get(self, request, format=None):
library_games = {
"total": LibraryGame.objects.all().count(),
"being_played": LibraryGame.objects.filter(withdraw__date_returned__isnull=True)
}
return Response({"library_games": library_games})
class LocationViewSet(viewsets.ModelViewSet):
queryset = Location.objects.order_by('name').all()
serializer_class = LocationSerializer
class ConfigurationViewSet(viewsets.ModelViewSet):
queryset = Configuration.objects.all()
serializer_class = ConfigurationSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,) | backend/api/views.py | from django.views.decorators.cache import never_cache
from django.views.generic import TemplateView
from django_filters import rest_framework as django_filters
from rest_framework import filters
from rest_framework import viewsets, permissions
from rest_framework.pagination import PageNumberPagination
from rest_framework.response import Response
from rest_framework.views import APIView
from rest_framework_simplejwt import authentication
from backend.api import utils
from backend.api.filters import LibraryGameFilter
from backend.api.serializers import *
User = get_user_model()
# Serve Vue Application
index_view = never_cache(TemplateView.as_view(template_name='index.html'))
class StandardResultsSetPagination(PageNumberPagination):
"""60 is divisible by 2,3,4,5 and 6 making it flexible to adjust frontend layout.
All requests with pagination should take page_size with a base of 60"""
page_size = 60
page_size_query_param = 'page_size'
max_page_size = 1000
class SupplierViewSet(viewsets.ModelViewSet):
queryset = Supplier.objects.order_by('name')
serializer_class = SupplierSerializer
authentication_classes = (authentication.JWTAuthentication,)
permission_classes = (permissions.IsAdminUser,)
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
search_fields = ['name']
class PlayerViewSet(viewsets.ModelViewSet):
queryset = User.objects.order_by('first_name', 'last_name')
serializer_class = PlayerSerializer
authentication_classes = (authentication.JWTAuthentication,)
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
search_fields = ['first_name', 'last_name', 'username', 'email']
# permission_classes = (permissions.IsAdminUser,)
class LibraryGameViewSet(viewsets.ModelViewSet):
queryset = LibraryGame.objects.order_by('game__name')
serializer_class = LibraryGameSerializer
search_fields = ['game__name', 'game__other_names']
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
filterset_class = LibraryGameFilter
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,)
authentication_classes = [authentication.JWTAuthentication]
pagination_class = StandardResultsSetPagination
def perform_create(self, serializer):
bggid = serializer.initial_data['game_id']
game = utils.BGGGame.find(bggid)
if game is None:
game = utils.BGGGame.create(bggid)
serializer.is_valid()
serializer.save(game=game)
class StoreGameViewSet(viewsets.ModelViewSet):
queryset = StoreGame.objects.order_by('game__name')
search_fields = ['game__name', 'game__other_names']
filter_backends = (filters.SearchFilter, django_filters.DjangoFilterBackend)
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,)
authentication_classes = [authentication.JWTAuthentication]
pagination_class = StandardResultsSetPagination
def get_serializer_class(self):
if self.request.user.is_staff:
return StoreGameSerializer
return AnonStoreGameSerializer
def perform_create(self, serializer):
bggid = serializer.initial_data['game_id']
game = utils.BGGGame.find(bggid)
if game is None:
game = utils.BGGGame.create(bggid)
serializer.is_valid()
serializer.save(game=game)
class UserViewSet(viewsets.ModelViewSet):
queryset = User.objects.all()
serializer_class = UserSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.IsAdminUser,)
def get_object(self):
pk = self.kwargs.get('pk')
if pk == "current":
return self.request.user
return super(UserViewSet, self).get_object()
class WithdrawViewSet(viewsets.ModelViewSet):
queryset = Withdraw.objects.all()
serializer_class = WithdrawSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.IsAdminUser,)
class StatisticsViewSet(APIView):
def get(self, request, format=None):
library_games = {
"total": LibraryGame.objects.all().count(),
"being_played": LibraryGame.objects.filter(withdraw__date_returned__isnull=True)
}
return Response({"library_games": library_games})
class LocationViewSet(viewsets.ModelViewSet):
queryset = Location.objects.order_by('name').all()
serializer_class = LocationSerializer
class ConfigurationViewSet(viewsets.ModelViewSet):
queryset = Configuration.objects.all()
serializer_class = ConfigurationSerializer
authentication_classes = [authentication.JWTAuthentication]
permission_classes = (permissions.DjangoModelPermissionsOrAnonReadOnly,) | 0.675015 | 0.169819 |
import torch
import torch.nn as nn
import torch.nn.functional as F
CHANNELS = [20, 50, 500]
#CHANNELS = [40, 100, 500]
#CHANNELS = [10, 20, 100]
#CHANNELS = [6, 16, 120, 84]
#CHANNELS = [12, 32, 120, 84]
#CHANNELS = [32, 32, 120, 84]
class NetCCFFF(nn.Module):
def __init__(self, input_channels):
super(NetCCFFF, self).__init__()
self.conv1 = nn.Conv2d(input_channels, CHANNELS[0], 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(CHANNELS[0], CHANNELS[1], 5)
self.fc1 = nn.Linear(CHANNELS[1] * 12 * 12, CHANNELS[2])
self.fc2 = nn.Linear(CHANNELS[2], CHANNELS[3])
self.fc3 = nn.Linear(CHANNELS[3], 2)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, x.shape[1] * x.shape[2] * x.shape[3])
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
class Net(nn.Module):
def __init__(self, input_channels):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(input_channels, CHANNELS[0], 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(CHANNELS[0], CHANNELS[1], 5)
self.fc1 = nn.Linear(CHANNELS[1] * 12 * 12, CHANNELS[2])
self.fc2 = nn.Linear(CHANNELS[2], 2)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, x.shape[1] * x.shape[2] * x.shape[3])
x = F.relu(self.fc1(x))
x = self.fc2(x)
return x
def train(model, criterion, optimizer, data, device):
# Get the inputs and transfer them to the CPU/GPU.
inputs, labels = data
inputs = inputs.to(device)
labels = labels.to(device)
# Reset the parameter gradients.
optimizer.zero_grad()
# Forward + backward + optimize.
outputs = model(inputs)
loss = criterion(outputs, labels.long())
loss.backward()
optimizer.step()
return loss
def eval(model, test_loader, device):
model.eval()
correct = 0
total = 0
print('Testing the network on the test data ...')
with torch.no_grad():
for data in test_loader:
inputs, labels = data
inputs = inputs.to(device)
labels = labels.to(device)
# Forward
outputs = model(inputs)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels.long()).sum().item()
accuracy = 100.0 * float(correct) / float(total)
print('Accuracy of the network on the test set: %.3f%%' % (
accuracy))
return accuracy | pytorch/network.py | import torch
import torch.nn as nn
import torch.nn.functional as F
CHANNELS = [20, 50, 500]
#CHANNELS = [40, 100, 500]
#CHANNELS = [10, 20, 100]
#CHANNELS = [6, 16, 120, 84]
#CHANNELS = [12, 32, 120, 84]
#CHANNELS = [32, 32, 120, 84]
class NetCCFFF(nn.Module):
def __init__(self, input_channels):
super(NetCCFFF, self).__init__()
self.conv1 = nn.Conv2d(input_channels, CHANNELS[0], 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(CHANNELS[0], CHANNELS[1], 5)
self.fc1 = nn.Linear(CHANNELS[1] * 12 * 12, CHANNELS[2])
self.fc2 = nn.Linear(CHANNELS[2], CHANNELS[3])
self.fc3 = nn.Linear(CHANNELS[3], 2)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, x.shape[1] * x.shape[2] * x.shape[3])
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
class Net(nn.Module):
def __init__(self, input_channels):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(input_channels, CHANNELS[0], 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(CHANNELS[0], CHANNELS[1], 5)
self.fc1 = nn.Linear(CHANNELS[1] * 12 * 12, CHANNELS[2])
self.fc2 = nn.Linear(CHANNELS[2], 2)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, x.shape[1] * x.shape[2] * x.shape[3])
x = F.relu(self.fc1(x))
x = self.fc2(x)
return x
def train(model, criterion, optimizer, data, device):
# Get the inputs and transfer them to the CPU/GPU.
inputs, labels = data
inputs = inputs.to(device)
labels = labels.to(device)
# Reset the parameter gradients.
optimizer.zero_grad()
# Forward + backward + optimize.
outputs = model(inputs)
loss = criterion(outputs, labels.long())
loss.backward()
optimizer.step()
return loss
def eval(model, test_loader, device):
model.eval()
correct = 0
total = 0
print('Testing the network on the test data ...')
with torch.no_grad():
for data in test_loader:
inputs, labels = data
inputs = inputs.to(device)
labels = labels.to(device)
# Forward
outputs = model(inputs)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels.long()).sum().item()
accuracy = 100.0 * float(correct) / float(total)
print('Accuracy of the network on the test set: %.3f%%' % (
accuracy))
return accuracy | 0.933952 | 0.510496 |
from django.conf import settings
from django.contrib.contenttypes.models import ContentType
from .models import Car
from .test import TestCase
class RateViewTest(TestCase):
"""
tests for the RateView
"""
def setUp(self):
self.test_user = self.make_user(username="test_user")
self.forester = Car.objects.create(name="Subaru Forester")
def test_post_rating_returns_404(self):
"""
Ensure view returns 404 if object is not found. This should
typically happen when one of the two kwargs i.e content_type_id
and object_id have invalid data
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=400,
object_id=1,
data={
"rating": 3,
"category": "handling"
},
)
self.response_404(response)
def test_post_rating_with_invalid_category(self):
"""
Ensure view returns 403 if an invalid category choice
is provided in the POST data. category choices are added
to the PINAX_RATINGS_CATEGORY_CHOICES setting in settings.py
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": settings.PINAX_RATINGS_NUM_OF_RATINGS,
"category": "non-existing-category"
},
)
self.response_403(response)
def test_post_rating_greater_than_range(self):
"""
Ensure view returns 403 if the rating is greater
than the minimum rating enforced by RatingView
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": settings.PINAX_RATINGS_NUM_OF_RATINGS + 1,
"category": "handling"
},
)
self.response_403(response)
def test_post_rating_less_than_range(self):
"""
Ensure view returns 403 if the rating is less
than the minimum rating enforced by RatingView
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": -1,
"category": "handling"
},
)
self.response_403(response)
def test_post_rating_with_valid_data(self):
"""
Ensure view returns 200 if valid data is passed to
the view. For data to be valid, the following conditions
must be met;
1. The url kwargs content_type_id and object_id both have valid IDs
2. The body of the POST request has keys rating and category with
valid values of rating num within the the range and valid category choice
"""
with self.login(self.test_user):
content_type_id = ContentType.objects.get_for_model(self.forester).pk
object_id = self.forester.pk
response = self.post(
"pinax_ratings:rate",
content_type_id=content_type_id,
object_id=object_id,
data={
"rating": 3,
"category": "handling"
},
)
self.response_200(response)
self.assertContext("user_rating", 3)
self.assertContext("category", "handling")
self.assertContext("overall_rating", 3.0) | pinax/ratings/tests/test_views.py | from django.conf import settings
from django.contrib.contenttypes.models import ContentType
from .models import Car
from .test import TestCase
class RateViewTest(TestCase):
"""
tests for the RateView
"""
def setUp(self):
self.test_user = self.make_user(username="test_user")
self.forester = Car.objects.create(name="Subaru Forester")
def test_post_rating_returns_404(self):
"""
Ensure view returns 404 if object is not found. This should
typically happen when one of the two kwargs i.e content_type_id
and object_id have invalid data
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=400,
object_id=1,
data={
"rating": 3,
"category": "handling"
},
)
self.response_404(response)
def test_post_rating_with_invalid_category(self):
"""
Ensure view returns 403 if an invalid category choice
is provided in the POST data. category choices are added
to the PINAX_RATINGS_CATEGORY_CHOICES setting in settings.py
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": settings.PINAX_RATINGS_NUM_OF_RATINGS,
"category": "non-existing-category"
},
)
self.response_403(response)
def test_post_rating_greater_than_range(self):
"""
Ensure view returns 403 if the rating is greater
than the minimum rating enforced by RatingView
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": settings.PINAX_RATINGS_NUM_OF_RATINGS + 1,
"category": "handling"
},
)
self.response_403(response)
def test_post_rating_less_than_range(self):
"""
Ensure view returns 403 if the rating is less
than the minimum rating enforced by RatingView
"""
with self.login(self.test_user):
response = self.post(
"pinax_ratings:rate",
content_type_id=ContentType.objects.get_for_model(self.forester).pk,
object_id=self.forester.pk,
data={
"rating": -1,
"category": "handling"
},
)
self.response_403(response)
def test_post_rating_with_valid_data(self):
"""
Ensure view returns 200 if valid data is passed to
the view. For data to be valid, the following conditions
must be met;
1. The url kwargs content_type_id and object_id both have valid IDs
2. The body of the POST request has keys rating and category with
valid values of rating num within the the range and valid category choice
"""
with self.login(self.test_user):
content_type_id = ContentType.objects.get_for_model(self.forester).pk
object_id = self.forester.pk
response = self.post(
"pinax_ratings:rate",
content_type_id=content_type_id,
object_id=object_id,
data={
"rating": 3,
"category": "handling"
},
)
self.response_200(response)
self.assertContext("user_rating", 3)
self.assertContext("category", "handling")
self.assertContext("overall_rating", 3.0) | 0.657758 | 0.318326 |
import psycopg2
import os
from dotenv import load_dotenv
import json
from psycopg2.extras import execute_values
import sqlite3
import wget
load_dotenv() # look in the .env file for env vars, and add them to the env
DB_NAME= os.getenv("DB_NAME", default="oops")
DB_USER= os.getenv("DB_USER", default="oops")
DB_PASSWORD= os.getenv("DB_PASSWORD", default="<PASSWORD>")
DB_HOST= os.getenv("DB_HOST", default="oops")
# COPPIED FROM ABOVE IN THE HELP SECTION EXCEPT I ADDED HOST
pg_conn = psycopg2.connect(database=DB_NAME, user=DB_USER, password=<PASSWORD>, host=DB_HOST) # pg means POSTGRES
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print("1. PG_CONNECTION:\n", pg_conn)
print('\n')
# CURSOR ALLOWS US TO USE A DB
pg_curs = pg_conn.cursor()
print("2. PG_CURS:\n", pg_curs)
print('\n')
# EXECUTE A QUERY WITH LINE 2, FETCH THE RESULTS WITH LINE 3
pg_curs.execute('SELECT * FROM test_table;')
print('3. SELECT * FROM test_table;\n', pg_curs.fetchall())
print('\n')
# MAKE A CONNECTION VIA SQLITE3 (DOESN'T REQUIRE USERNAME/PASSWORD)
DB_FILE_PATH = 'DS-Unit-3-Sprint-2-SQL-and-Databases/module1-introduction-to-sql/rpg_db.sqlite3'
sl_conn = sqlite3.connect(DB_FILE_PATH)
print('4. SL_CONN\n', sl_conn)
print('\n')
# AFTER MAKING CONNECTION, MAKE A CURSOR
sl_curs = sl_conn.cursor()
print('5. SL_CURS\n',sl_curs,'\n\n')
print('\n')
# wget.download('https://github.com/jacobpad/DS-Unit-3-Sprint-2-SQL-and-Databases/blob/master/module1-introduction-to-sql/rpg_db.sqlite3?raw=true')
# # LET'S EXECUTE A QUERY TO DOUBLE CHECK
# # QUERY CHECKS THE NUMBER OF CHARACTERS IN DATABASE
# sl_curs.execute('SELECT COUNT(*) FROM charactercreator_character;').fetchall()
# # .fetchall() works on sqlite3
# SAVE THE CHARACTERS & INFO
characters = sl_curs.execute('SELECT * FROM charactercreator_character;').fetchall()
print('6. SELECT * FROM charactercreator_character;\n',characters)
print('\n')
# SEE FIRST CHARACTER
print('7. See first character\n',characters[0])
print('\n')
# SEE LAST CHARACTER
print('8. See last character\n',characters[-1])
print('\n')
# GET USFUL INFORMATION ABOUT THE TABLE
# PASSING THE TABLE, WE GET
# COLUMN NAMES, DATATYPE, AND MORE
# FOR EXAMLE - 'character_id' COLUMN IS AN 'integer'
see = sl_curs.execute('PRAGMA table_info(charactercreator_character);').fetchall()
print('9. See usful info about charactercreator_character table:\n',see)
print('\n')
# CREATE THE QUERY FOR THE TABLE TO RUN IN POSTGRESQL
create_character_table = """
DROP TABLE charactercreator_character;
CREATE TABLE IF NOT EXISTS charactercreator_character (
character_id SERIAL PRIMARY KEY,
name VARCHAR(30),
level INT,
exp INT,
hp INT,
strength INT,
intelligence INT,
dexterity INT,
wisdom INT
);
"""
create_character_table
print('10. create_character_table query\n', create_character_table)
print('\n')
# RUN THE QUERY TO CREATE THE TABLE IN POSTGRES
pg_curs.execute(create_character_table)
print('11. If this outputs, table was successfully created')
print('\n')
# DOUBLE CHECK TO MAKE SURE IT WORKED
# FIRST CREATE A QUERY TO SHOW US
show_tables = """
SELECT *
FROM pg_catalog.pg_tables
WHERE schemaname != 'pg_catalog'
AND schemaname != 'information_schema';
"""
print('12. show_table query\nDOUBLE CHECK TO MAKE SURE IT WORKED FIRST CREATE A QUERY TO SHOW US', show_tables)
print('\n')
# EXECUTE THE QUERY ABOVE
pg_curs.execute(show_tables)
print('13. If this outputs, query was successfully run')
print('\n')
# RUN FETCHALL TO SEE IT
print('14. RUN FETCHALL TO SEE IT\n',pg_curs.fetchall())
# Yep, there's the charactercreator_character table
print('\n')
print('--- Yep, it worked, see, charactercreator_character is a thing now\n')
print('\n')
# THIS IS THE CURRENT FORM IT'S IN AND IT'S NOT HOW WE WANT IT TO BE
print('15. THIS IS THE CURRENT FORM IT\'S IN AND IT\'S NOT HOW WE WANT IT TO BE\n',characters[0])
print('\n')
# TURN IT INTO A STRING AND SLICE AWAY THE FIRST COLUMN
print('16. TURN IT INTO A STRING AND SLICE AWAY THE FIRST COLUMN\n',str(characters[0][1:]))
print('\n')
# EXAMPLE INSERT
example_insert = """
INSERT INTO charactercreator_character
(name, level, exp, hp, strength, intelligence, dexterity, wisdom)
VALUES """ + str(characters[0][1:]) + ';'
print('17. example_insert\n', example_insert)
print('\n')
# MAKE A LOOP TO ADD ALL AT ONCE INSTEAD OF ADDING ONE BY ONE
for character in characters:
insert_character = """
INSERT INTO charactercreator_character
(name, level, exp, hp, strength, intelligence, dexterity, wisdom)
VALUES """ + str(character[1:]) + ';'
pg_curs.execute(insert_character) # THIS LINE IN THE FOR LOOP ALLOWS THE QUERY
# TO ADD A ROW
print('18. MAKE A LOOP TO ADD ALL AT ONCE INSTEAD OF ADDING ONE BY ONE')
print('for character in characters:')
print(' insert_character = """')
print(' INSERT INTO charactercreator_character')
print(' (name, level, exp, hp, strength, intelligence, dexterity, wisdom)')
print(' VALUES """ + str(character[1:]) + \';\'')
print('pg_curs.execute(insert_character)')
print('\n')
# SEE THE TABLE
pg_curs.execute('SELECT * FROM charactercreator_character;')
see = pg_curs.fetchall()
print('19. See it all\n',see)
print('\n')
print('\n')
print('\n')
# COMMIT AND CLOSE
pg_curs.close()
pg_conn.commit()
# print('\n') | module2-sql-for-analysis/rpg_to_postgres.py | import psycopg2
import os
from dotenv import load_dotenv
import json
from psycopg2.extras import execute_values
import sqlite3
import wget
load_dotenv() # look in the .env file for env vars, and add them to the env
DB_NAME= os.getenv("DB_NAME", default="oops")
DB_USER= os.getenv("DB_USER", default="oops")
DB_PASSWORD= os.getenv("DB_PASSWORD", default="<PASSWORD>")
DB_HOST= os.getenv("DB_HOST", default="oops")
# COPPIED FROM ABOVE IN THE HELP SECTION EXCEPT I ADDED HOST
pg_conn = psycopg2.connect(database=DB_NAME, user=DB_USER, password=<PASSWORD>, host=DB_HOST) # pg means POSTGRES
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print('\n')
print("1. PG_CONNECTION:\n", pg_conn)
print('\n')
# CURSOR ALLOWS US TO USE A DB
pg_curs = pg_conn.cursor()
print("2. PG_CURS:\n", pg_curs)
print('\n')
# EXECUTE A QUERY WITH LINE 2, FETCH THE RESULTS WITH LINE 3
pg_curs.execute('SELECT * FROM test_table;')
print('3. SELECT * FROM test_table;\n', pg_curs.fetchall())
print('\n')
# MAKE A CONNECTION VIA SQLITE3 (DOESN'T REQUIRE USERNAME/PASSWORD)
DB_FILE_PATH = 'DS-Unit-3-Sprint-2-SQL-and-Databases/module1-introduction-to-sql/rpg_db.sqlite3'
sl_conn = sqlite3.connect(DB_FILE_PATH)
print('4. SL_CONN\n', sl_conn)
print('\n')
# AFTER MAKING CONNECTION, MAKE A CURSOR
sl_curs = sl_conn.cursor()
print('5. SL_CURS\n',sl_curs,'\n\n')
print('\n')
# wget.download('https://github.com/jacobpad/DS-Unit-3-Sprint-2-SQL-and-Databases/blob/master/module1-introduction-to-sql/rpg_db.sqlite3?raw=true')
# # LET'S EXECUTE A QUERY TO DOUBLE CHECK
# # QUERY CHECKS THE NUMBER OF CHARACTERS IN DATABASE
# sl_curs.execute('SELECT COUNT(*) FROM charactercreator_character;').fetchall()
# # .fetchall() works on sqlite3
# SAVE THE CHARACTERS & INFO
characters = sl_curs.execute('SELECT * FROM charactercreator_character;').fetchall()
print('6. SELECT * FROM charactercreator_character;\n',characters)
print('\n')
# SEE FIRST CHARACTER
print('7. See first character\n',characters[0])
print('\n')
# SEE LAST CHARACTER
print('8. See last character\n',characters[-1])
print('\n')
# GET USFUL INFORMATION ABOUT THE TABLE
# PASSING THE TABLE, WE GET
# COLUMN NAMES, DATATYPE, AND MORE
# FOR EXAMLE - 'character_id' COLUMN IS AN 'integer'
see = sl_curs.execute('PRAGMA table_info(charactercreator_character);').fetchall()
print('9. See usful info about charactercreator_character table:\n',see)
print('\n')
# CREATE THE QUERY FOR THE TABLE TO RUN IN POSTGRESQL
create_character_table = """
DROP TABLE charactercreator_character;
CREATE TABLE IF NOT EXISTS charactercreator_character (
character_id SERIAL PRIMARY KEY,
name VARCHAR(30),
level INT,
exp INT,
hp INT,
strength INT,
intelligence INT,
dexterity INT,
wisdom INT
);
"""
create_character_table
print('10. create_character_table query\n', create_character_table)
print('\n')
# RUN THE QUERY TO CREATE THE TABLE IN POSTGRES
pg_curs.execute(create_character_table)
print('11. If this outputs, table was successfully created')
print('\n')
# DOUBLE CHECK TO MAKE SURE IT WORKED
# FIRST CREATE A QUERY TO SHOW US
show_tables = """
SELECT *
FROM pg_catalog.pg_tables
WHERE schemaname != 'pg_catalog'
AND schemaname != 'information_schema';
"""
print('12. show_table query\nDOUBLE CHECK TO MAKE SURE IT WORKED FIRST CREATE A QUERY TO SHOW US', show_tables)
print('\n')
# EXECUTE THE QUERY ABOVE
pg_curs.execute(show_tables)
print('13. If this outputs, query was successfully run')
print('\n')
# RUN FETCHALL TO SEE IT
print('14. RUN FETCHALL TO SEE IT\n',pg_curs.fetchall())
# Yep, there's the charactercreator_character table
print('\n')
print('--- Yep, it worked, see, charactercreator_character is a thing now\n')
print('\n')
# THIS IS THE CURRENT FORM IT'S IN AND IT'S NOT HOW WE WANT IT TO BE
print('15. THIS IS THE CURRENT FORM IT\'S IN AND IT\'S NOT HOW WE WANT IT TO BE\n',characters[0])
print('\n')
# TURN IT INTO A STRING AND SLICE AWAY THE FIRST COLUMN
print('16. TURN IT INTO A STRING AND SLICE AWAY THE FIRST COLUMN\n',str(characters[0][1:]))
print('\n')
# EXAMPLE INSERT
example_insert = """
INSERT INTO charactercreator_character
(name, level, exp, hp, strength, intelligence, dexterity, wisdom)
VALUES """ + str(characters[0][1:]) + ';'
print('17. example_insert\n', example_insert)
print('\n')
# MAKE A LOOP TO ADD ALL AT ONCE INSTEAD OF ADDING ONE BY ONE
for character in characters:
insert_character = """
INSERT INTO charactercreator_character
(name, level, exp, hp, strength, intelligence, dexterity, wisdom)
VALUES """ + str(character[1:]) + ';'
pg_curs.execute(insert_character) # THIS LINE IN THE FOR LOOP ALLOWS THE QUERY
# TO ADD A ROW
print('18. MAKE A LOOP TO ADD ALL AT ONCE INSTEAD OF ADDING ONE BY ONE')
print('for character in characters:')
print(' insert_character = """')
print(' INSERT INTO charactercreator_character')
print(' (name, level, exp, hp, strength, intelligence, dexterity, wisdom)')
print(' VALUES """ + str(character[1:]) + \';\'')
print('pg_curs.execute(insert_character)')
print('\n')
# SEE THE TABLE
pg_curs.execute('SELECT * FROM charactercreator_character;')
see = pg_curs.fetchall()
print('19. See it all\n',see)
print('\n')
print('\n')
print('\n')
# COMMIT AND CLOSE
pg_curs.close()
pg_conn.commit()
# print('\n') | 0.244904 | 0.036322 |
def isWordGuessed(secretWord, lettersGuessed):
lettersFound = []
for i in secretWord:
for n in lettersGuessed:
if n == i:
lettersFound.append(i)
break
len(secretWord) == len(lettersFound)
return len(secretWord) == len(lettersFound)
def getGuessedWord(secretWord, lettersGuessed):
'''
secretWord: string, the word the user is guessing
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters and underscores that represents
what letters in secretWord have been guessed so far.
'''
lettersFound = []
if lettersGuessed == []:
bad_payer = str("_ ")*len(secretWord)
return bad_payer
else:
for i in secretWord:
lettersGuessedCounter = 0
for idx, n in enumerate(lettersGuessed):
if n == i:
lettersFound.append(i)
lettersGuessedCounter = 0
break
if idx == len(lettersGuessed)-1:
lettersFound.append("_ ")
str_final_word = ''.join(lettersFound)
return str_final_word
def getAvailableLetters(lettersGuessed):
'''
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters that represents what letters have not
yet been guessed.
'''
alphabet = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
for n in lettersGuessed:
for i in alphabet:
if n==i:
alphabet.remove(i)
alphabet = ''.join(alphabet)
return alphabets
def hangman(secretWord):
'''
secretWord: string, the secret word to guess.
Starts up an interactive game of Hangman.
* At the start of the game, let the user know how many
letters the secretWord contains.
* Ask the user to supply one guess (i.e. letter) per round.
* The user should receive feedback immediately after each guess
about whether their guess appears in the computers word.
* After each round, you should also display to the user the
partially guessed word so far, as well as letters that the
user has not yet guessed.
Follows the other limitations detailed in the problem write-up.
'''
how_long = len(secretWord)
secretWordinLowecase = secretWord.lower()
print('Welcome to the game, Hangman!')
print('I am thinking of a word that is '+str(how_long)+' letters long')
mistekesMade = 0
lettersGuessed = []
previusAvailableLetters = [(getAvailableLetters(lettersGuessed))]
while mistekesMade < 9:
print("-----------")
print("You have ", (8-mistekesMade)," guesses left")
print("Available Letters:",getAvailableLetters(lettersGuessed))
letter = input("Please guess a letter: ")
letter = letter[0]
lowerCaseLetter = letter.lower()
lettersGuessed.append(lowerCaseLetter)
if getAvailableLetters(lettersGuessed)==previusAvailableLetters:
mistekesMade+=0
else:
mistekesMade+=1
if (isWordGuessed(secretWordinLowecase, lettersGuessed)) == True:
print("Good guess: "+letter)
break
if (isWordGuessed(secretWordinLowecase, lettersGuessed)) == True:
print("-----------")
print("Congratulations, you won!")
else:
print("-----------")
print("Sorry, you ran out of guesses. The word was "+secretWord+".") | Python/Python - MIT 6.0/Week 3/ps3.py | def isWordGuessed(secretWord, lettersGuessed):
lettersFound = []
for i in secretWord:
for n in lettersGuessed:
if n == i:
lettersFound.append(i)
break
len(secretWord) == len(lettersFound)
return len(secretWord) == len(lettersFound)
def getGuessedWord(secretWord, lettersGuessed):
'''
secretWord: string, the word the user is guessing
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters and underscores that represents
what letters in secretWord have been guessed so far.
'''
lettersFound = []
if lettersGuessed == []:
bad_payer = str("_ ")*len(secretWord)
return bad_payer
else:
for i in secretWord:
lettersGuessedCounter = 0
for idx, n in enumerate(lettersGuessed):
if n == i:
lettersFound.append(i)
lettersGuessedCounter = 0
break
if idx == len(lettersGuessed)-1:
lettersFound.append("_ ")
str_final_word = ''.join(lettersFound)
return str_final_word
def getAvailableLetters(lettersGuessed):
'''
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters that represents what letters have not
yet been guessed.
'''
alphabet = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
for n in lettersGuessed:
for i in alphabet:
if n==i:
alphabet.remove(i)
alphabet = ''.join(alphabet)
return alphabets
def hangman(secretWord):
'''
secretWord: string, the secret word to guess.
Starts up an interactive game of Hangman.
* At the start of the game, let the user know how many
letters the secretWord contains.
* Ask the user to supply one guess (i.e. letter) per round.
* The user should receive feedback immediately after each guess
about whether their guess appears in the computers word.
* After each round, you should also display to the user the
partially guessed word so far, as well as letters that the
user has not yet guessed.
Follows the other limitations detailed in the problem write-up.
'''
how_long = len(secretWord)
secretWordinLowecase = secretWord.lower()
print('Welcome to the game, Hangman!')
print('I am thinking of a word that is '+str(how_long)+' letters long')
mistekesMade = 0
lettersGuessed = []
previusAvailableLetters = [(getAvailableLetters(lettersGuessed))]
while mistekesMade < 9:
print("-----------")
print("You have ", (8-mistekesMade)," guesses left")
print("Available Letters:",getAvailableLetters(lettersGuessed))
letter = input("Please guess a letter: ")
letter = letter[0]
lowerCaseLetter = letter.lower()
lettersGuessed.append(lowerCaseLetter)
if getAvailableLetters(lettersGuessed)==previusAvailableLetters:
mistekesMade+=0
else:
mistekesMade+=1
if (isWordGuessed(secretWordinLowecase, lettersGuessed)) == True:
print("Good guess: "+letter)
break
if (isWordGuessed(secretWordinLowecase, lettersGuessed)) == True:
print("-----------")
print("Congratulations, you won!")
else:
print("-----------")
print("Sorry, you ran out of guesses. The word was "+secretWord+".") | 0.327883 | 0.318578 |
from app.tomograph import Tomograph
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import argparse
parser = argparse.ArgumentParser(description='Process image like tomograph.')
parser.add_argument('--anim', default=False, type=bool, help='whether to animate output')
parser.add_argument('--input', default="./data/test_details_240.png", help='input image path')
parser.add_argument('--alpha', default=5, type=float, help='alpha step')
parser.add_argument('--count', default=100, type=int, help='count of detectors')
parser.add_argument('--span', default=1, type=float, help='span between detectors')
def update_frame(frame, f, tomograph, axarr):
print(frame)
tomograph.measure(with_mask=True)
tomograph.construct()
tomograph.next_step()
axarr[1].clear()
axarr[1].set_title('Sinogram')
axarr[1].imshow(tomograph.sinogram, cmap="gray", aspect="auto")
axarr[2].clear()
axarr[2].set_title('Reconstructed image')
axarr[2].imshow(tomograph.constructed_img, cmap="gray", aspect="auto")
f.text(0.91, 0.5, 'err: ' + str(tomograph.get_error()), bbox={'facecolor':'red', 'pad': 5})
return axarr,
def main(args):
print(args)
tomograph = Tomograph(args.alpha, args.count, args.span, args.input)
f, axarr = plt.subplots(1, 3, figsize=(12, 3))
axarr[0].set_title('Original image')
axarr[0].imshow(tomograph.orginal_img, cmap="gray", aspect="auto")
if not args.anim:
for i in range(int(180 / args.alpha)):
print(i, '/', int(180 / args.alpha)-1)
tomograph.measure(with_mask=True)
tomograph.construct()
tomograph.next_step()
axarr[1].set_title('Sinogram')
axarr[1].imshow(tomograph.sinogram, cmap="gray", aspect="auto")
axarr[2].set_title('Reconstructed image')
axarr[2].imshow(tomograph.constructed_img, cmap="gray", aspect="auto")
f.text(0.91, 0.5, 'err: ' + str(tomograph.get_error()), bbox={'facecolor':'red', 'pad': 5})
else:
anim = FuncAnimation(f, update_frame, init_func=lambda: 0, frames=int(180 / args.alpha), fargs=(f, tomograph, axarr), interval=1, repeat=False)
plt.show()
if __name__ == "__main__":
args = parser.parse_args()
main(args) | main.py | from app.tomograph import Tomograph
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import argparse
parser = argparse.ArgumentParser(description='Process image like tomograph.')
parser.add_argument('--anim', default=False, type=bool, help='whether to animate output')
parser.add_argument('--input', default="./data/test_details_240.png", help='input image path')
parser.add_argument('--alpha', default=5, type=float, help='alpha step')
parser.add_argument('--count', default=100, type=int, help='count of detectors')
parser.add_argument('--span', default=1, type=float, help='span between detectors')
def update_frame(frame, f, tomograph, axarr):
print(frame)
tomograph.measure(with_mask=True)
tomograph.construct()
tomograph.next_step()
axarr[1].clear()
axarr[1].set_title('Sinogram')
axarr[1].imshow(tomograph.sinogram, cmap="gray", aspect="auto")
axarr[2].clear()
axarr[2].set_title('Reconstructed image')
axarr[2].imshow(tomograph.constructed_img, cmap="gray", aspect="auto")
f.text(0.91, 0.5, 'err: ' + str(tomograph.get_error()), bbox={'facecolor':'red', 'pad': 5})
return axarr,
def main(args):
print(args)
tomograph = Tomograph(args.alpha, args.count, args.span, args.input)
f, axarr = plt.subplots(1, 3, figsize=(12, 3))
axarr[0].set_title('Original image')
axarr[0].imshow(tomograph.orginal_img, cmap="gray", aspect="auto")
if not args.anim:
for i in range(int(180 / args.alpha)):
print(i, '/', int(180 / args.alpha)-1)
tomograph.measure(with_mask=True)
tomograph.construct()
tomograph.next_step()
axarr[1].set_title('Sinogram')
axarr[1].imshow(tomograph.sinogram, cmap="gray", aspect="auto")
axarr[2].set_title('Reconstructed image')
axarr[2].imshow(tomograph.constructed_img, cmap="gray", aspect="auto")
f.text(0.91, 0.5, 'err: ' + str(tomograph.get_error()), bbox={'facecolor':'red', 'pad': 5})
else:
anim = FuncAnimation(f, update_frame, init_func=lambda: 0, frames=int(180 / args.alpha), fargs=(f, tomograph, axarr), interval=1, repeat=False)
plt.show()
if __name__ == "__main__":
args = parser.parse_args()
main(args) | 0.520496 | 0.280165 |
from datasets import fashion200k
from datasets import fashion_iq
from datasets import shoes
from datasets import vocabulary
import numpy as np
import tensorflow as tf
# python read_glove.py --dataset='fashion_iq' --data_path='datasets/fashion_iq/image_data'
# python read_glove.py --dataset='shoes' --data_path=''
# python read_glove.py --dataset='fashion200k' --data_path='datasets/fashion200k'
tf.app.flags.DEFINE_string(
'glove_size', "42B", '')
tf.app.flags.DEFINE_string(
'dataset', "fashion200k", '')
tf.app.flags.DEFINE_string(
'data_path', None, 'path of dataset.')
tf.app.flags.DEFINE_string(
'data_split', "train", 'either "train" or "test".')
tf.app.flags.DEFINE_string(
'subset', None, 'can be "dress" or "shirt" or "toptee".')
tf.app.flags.DEFINE_boolean(
'remove_rare_words', False, 'whether to remove the rare words.')
FLAGS = tf.app.flags.FLAGS
########### read dataset
print("Construct dataset")
if FLAGS.dataset == "fashion200k":
trainset = fashion200k.fashion200k(path=FLAGS.data_path, split=FLAGS.data_split)
elif FLAGS.dataset == "fashion_iq":
trainset = fashion_iq.fashion_iq(path=FLAGS.data_path, split=FLAGS.data_split, subset=FLAGS.subset)
elif FLAGS.dataset == "shoes":
trainset = shoes.shoes(path=FLAGS.data_path, split=FLAGS.data_split)
else:
raise ValueError("dataset is unknown.")
num_images = len(trainset.filenames)
### initialize the relations between source and target
if FLAGS.dataset == "fashion_iq":
trainset.generate_queries_(subset=FLAGS.subset)
all_texts = trainset.get_all_texts(subset=FLAGS.subset)
elif FLAGS.dataset == "shoes":
trainset.generate_queries_()
all_texts = trainset.get_all_texts()
elif FLAGS.dataset == "fashion200k":
### initialize the relations between source and target
trainset.caption_index_init_()
all_texts = trainset.get_all_texts()
else:
raise ValueError("dataset is unknown.")
num_modif = trainset.num_modifiable_imgs
vocab = vocabulary.SimpleVocab()
for text in all_texts:
vocab.add_text_to_vocab(text)
if FLAGS.remove_rare_words:
print('Remove rare words')
vocab.threshold_rare_words()
vocab_size = vocab.get_size()
print("Number of samples = {}. Number of words = {}.".format(num_modif, vocab_size)) # lấy được vocab
########### read glove
filename = "glove/glove." + FLAGS.glove_size + ".300d.txt"
def loadGloveModel(File):
print("Loading Glove Model")
f = open(File,'r')
gloveModel = {}
for line in f:
splitLines = line.split()
word = splitLines[0]
wordEmbedding = np.array([float(value) for value in splitLines[1:]])
gloveModel[word] = wordEmbedding
print(len(gloveModel)," words loaded!")
f.close()
return gloveModel
embedding_dict = loadGloveModel(filename) # đọc pretrain model của Glove
glove_vectors = np.zeros((len(vocab.word2id), len(embedding_dict['the'])))
print(glove_vectors.shape)
all_words = list(vocab.word2id.keys())
glove_all_words = list(embedding_dict.keys())
dim = len(embedding_dict['the'])
mu, sigma = 0, 0.09 # mean and standard deviation
print('2')
count = 0
for i in range(len(vocab.word2id)):
word = all_words[i]
idx = vocab.word2id[word]
if word not in glove_all_words:
count = count + 1
vec = np.random.normal(mu, sigma, dim)
else:
vec = np.asarray(embedding_dict[word])
glove_vectors[idx,:] = vec
print('3')
filename = 'glove/' + FLAGS.dataset + '.' + FLAGS.glove_size + '.300d.npy'
print(count)
print(filename)
np.save(filename, glove_vectors) #lưu lại glove của toàn bộ text mô tả | read_glove.py | from datasets import fashion200k
from datasets import fashion_iq
from datasets import shoes
from datasets import vocabulary
import numpy as np
import tensorflow as tf
# python read_glove.py --dataset='fashion_iq' --data_path='datasets/fashion_iq/image_data'
# python read_glove.py --dataset='shoes' --data_path=''
# python read_glove.py --dataset='fashion200k' --data_path='datasets/fashion200k'
tf.app.flags.DEFINE_string(
'glove_size', "42B", '')
tf.app.flags.DEFINE_string(
'dataset', "fashion200k", '')
tf.app.flags.DEFINE_string(
'data_path', None, 'path of dataset.')
tf.app.flags.DEFINE_string(
'data_split', "train", 'either "train" or "test".')
tf.app.flags.DEFINE_string(
'subset', None, 'can be "dress" or "shirt" or "toptee".')
tf.app.flags.DEFINE_boolean(
'remove_rare_words', False, 'whether to remove the rare words.')
FLAGS = tf.app.flags.FLAGS
########### read dataset
print("Construct dataset")
if FLAGS.dataset == "fashion200k":
trainset = fashion200k.fashion200k(path=FLAGS.data_path, split=FLAGS.data_split)
elif FLAGS.dataset == "fashion_iq":
trainset = fashion_iq.fashion_iq(path=FLAGS.data_path, split=FLAGS.data_split, subset=FLAGS.subset)
elif FLAGS.dataset == "shoes":
trainset = shoes.shoes(path=FLAGS.data_path, split=FLAGS.data_split)
else:
raise ValueError("dataset is unknown.")
num_images = len(trainset.filenames)
### initialize the relations between source and target
if FLAGS.dataset == "fashion_iq":
trainset.generate_queries_(subset=FLAGS.subset)
all_texts = trainset.get_all_texts(subset=FLAGS.subset)
elif FLAGS.dataset == "shoes":
trainset.generate_queries_()
all_texts = trainset.get_all_texts()
elif FLAGS.dataset == "fashion200k":
### initialize the relations between source and target
trainset.caption_index_init_()
all_texts = trainset.get_all_texts()
else:
raise ValueError("dataset is unknown.")
num_modif = trainset.num_modifiable_imgs
vocab = vocabulary.SimpleVocab()
for text in all_texts:
vocab.add_text_to_vocab(text)
if FLAGS.remove_rare_words:
print('Remove rare words')
vocab.threshold_rare_words()
vocab_size = vocab.get_size()
print("Number of samples = {}. Number of words = {}.".format(num_modif, vocab_size)) # lấy được vocab
########### read glove
filename = "glove/glove." + FLAGS.glove_size + ".300d.txt"
def loadGloveModel(File):
print("Loading Glove Model")
f = open(File,'r')
gloveModel = {}
for line in f:
splitLines = line.split()
word = splitLines[0]
wordEmbedding = np.array([float(value) for value in splitLines[1:]])
gloveModel[word] = wordEmbedding
print(len(gloveModel)," words loaded!")
f.close()
return gloveModel
embedding_dict = loadGloveModel(filename) # đọc pretrain model của Glove
glove_vectors = np.zeros((len(vocab.word2id), len(embedding_dict['the'])))
print(glove_vectors.shape)
all_words = list(vocab.word2id.keys())
glove_all_words = list(embedding_dict.keys())
dim = len(embedding_dict['the'])
mu, sigma = 0, 0.09 # mean and standard deviation
print('2')
count = 0
for i in range(len(vocab.word2id)):
word = all_words[i]
idx = vocab.word2id[word]
if word not in glove_all_words:
count = count + 1
vec = np.random.normal(mu, sigma, dim)
else:
vec = np.asarray(embedding_dict[word])
glove_vectors[idx,:] = vec
print('3')
filename = 'glove/' + FLAGS.dataset + '.' + FLAGS.glove_size + '.300d.npy'
print(count)
print(filename)
np.save(filename, glove_vectors) #lưu lại glove của toàn bộ text mô tả | 0.515864 | 0.245973 |
import os
from apsimRegions.preprocess.configMaker import create_many_config_files
from apsimRegions.preprocess.apsimPreprocess import preprocess_many
from apsimRegions.preprocess.batch import create_run_all_batchfile
def main():
experimentName = 'test'
outputDir = 'C:/ExampleProject/output/experiments/maize/{0}'.format(experimentName)
# validArgs are 'resolution','crop','model','crit_fr_asw', 'sowStart', or 'soilName'
#factorials = {'soilName':['auto','HCGEN0001','HCGEN0003','HCGEN0007','HCGEN0010','HCGEN0011','HCGEN0013','HCGEN0014','HCGEN0015','HCGEN0016','HCGEN0017','HCGEN0025']}
#factorials = {'sowStart':['auto','01-apr','08-apr','15-apr','22-apr','01-may','08-may','15-may','22-may','01-jun','08-jun','15-jun','22-jun','01-jul']}
factorials = {'crit_fr_asw':['0.0','0.05','0.15','0.25','0.50','0.75','0.95','1.0']}
otherArgs = {'metFileDir':'C:/ExampleProject/metfiles/working/%(met)s',\
'gridLutPath':'C:/ExampleProject/lookupTables/exampleLookupTable.csv',\
'clockStart':'1/1/2001', 'clockEnd':'31/12/2010'}
# create directory if it doesn't exist
if not os.path.isdir(outputDir):
os.mkdir(outputDir)
# create config files
print 'Creating configuration files...'
runs = create_many_config_files(outputDir, factorials, otherArgs)
# create apsim files
print 'Saving .apsim and .bat files...'
preprocess_many(outputDir, runs.keys()[0], runs.keys()[-1])
# create run all batchfile
create_run_all_batchfile(outputDir, runs, experimentName)
# feedback
print 'All files saved to:\r', outputDir
print '\nFolder', ': Variable'
for key in runs.keys():
print '{0:6} : {1}'.format(key, runs[key])
# save text file of run data
if not os.path.isfile(os.path.join(outputDir,'readme.txt')):
mode = 'w'
else:
mode = 'a'
with open(os.path.join(outputDir,'readme.txt'),mode=mode) as f:
f.write('Folder : Variable')
for key in runs.keys():
f.write('\n{0:6} : {1}'.format(key, runs[key]))
f.write('\n')
print '\n***** Done! *****'
# Run main() if module is run as a program
if __name__ == '__main__':
main() | scripts/preprocess.py |
import os
from apsimRegions.preprocess.configMaker import create_many_config_files
from apsimRegions.preprocess.apsimPreprocess import preprocess_many
from apsimRegions.preprocess.batch import create_run_all_batchfile
def main():
experimentName = 'test'
outputDir = 'C:/ExampleProject/output/experiments/maize/{0}'.format(experimentName)
# validArgs are 'resolution','crop','model','crit_fr_asw', 'sowStart', or 'soilName'
#factorials = {'soilName':['auto','HCGEN0001','HCGEN0003','HCGEN0007','HCGEN0010','HCGEN0011','HCGEN0013','HCGEN0014','HCGEN0015','HCGEN0016','HCGEN0017','HCGEN0025']}
#factorials = {'sowStart':['auto','01-apr','08-apr','15-apr','22-apr','01-may','08-may','15-may','22-may','01-jun','08-jun','15-jun','22-jun','01-jul']}
factorials = {'crit_fr_asw':['0.0','0.05','0.15','0.25','0.50','0.75','0.95','1.0']}
otherArgs = {'metFileDir':'C:/ExampleProject/metfiles/working/%(met)s',\
'gridLutPath':'C:/ExampleProject/lookupTables/exampleLookupTable.csv',\
'clockStart':'1/1/2001', 'clockEnd':'31/12/2010'}
# create directory if it doesn't exist
if not os.path.isdir(outputDir):
os.mkdir(outputDir)
# create config files
print 'Creating configuration files...'
runs = create_many_config_files(outputDir, factorials, otherArgs)
# create apsim files
print 'Saving .apsim and .bat files...'
preprocess_many(outputDir, runs.keys()[0], runs.keys()[-1])
# create run all batchfile
create_run_all_batchfile(outputDir, runs, experimentName)
# feedback
print 'All files saved to:\r', outputDir
print '\nFolder', ': Variable'
for key in runs.keys():
print '{0:6} : {1}'.format(key, runs[key])
# save text file of run data
if not os.path.isfile(os.path.join(outputDir,'readme.txt')):
mode = 'w'
else:
mode = 'a'
with open(os.path.join(outputDir,'readme.txt'),mode=mode) as f:
f.write('Folder : Variable')
for key in runs.keys():
f.write('\n{0:6} : {1}'.format(key, runs[key]))
f.write('\n')
print '\n***** Done! *****'
# Run main() if module is run as a program
if __name__ == '__main__':
main() | 0.250821 | 0.116487 |
import sys
import os
from matplotlib import pyplot as plt
import numpy as np
import csv
from collections import Counter
sys.path.append(os.getcwd())
os.environ["DJANGO_SETTINGS_MODULE"] = "as8_db.settings"
import django
django.setup()
from core import backup
def main():
backup.main()
organization_location()
organization_is_club()
organization_popularity()
organization_is_active()
organization_initiatives()
organization_resources()
consumer_age()
consumer_location()
consumer_profession()
consumer_institution()
Consumer_send_newsletter()
def height_calc(num):
if num <= 2:
return 2
elif num <= 5:
return 4
elif num <= 10:
return 7
elif num <= 20:
return 10
else:
return 15
def organization_location():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
location_dict = Counter()
next(my_reader)
for line in my_reader:
location_dict.update([line[3]])
temp_tuple_list = sorted(dict(location_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' LOCATION")
plt.xlabel("Number Of Organizations")
plt.ylabel("Location")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot1.png")
def organization_is_club():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
is_club_dict = Counter()
next(my_reader)
for line in my_reader:
is_club_dict.update([line[4]])
temp_tuple_list = sorted(dict(is_club_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' IS_CLUB")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot2.png")
def organization_popularity():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
popularity_dict = Counter()
next(my_reader)
for line in my_reader:
popularity_dict.update([line[6]])
temp_tuple_list = sorted(dict(popularity_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7", "#26849e"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' POPULARITY")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot3.png")
def organization_is_active():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
is_active_dict = Counter()
next(my_reader)
for line in my_reader:
is_active_dict.update([line[7]])
temp_tuple_list = sorted(dict(is_active_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' IS_ACTIVE")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot4.png")
def organization_initiatives():
with open("backupfiles/InitiativeBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
org_dict = Counter()
next(my_reader)
for line in my_reader:
org_dict.update([line[3]])
temp_tuple_list = sorted(dict(org_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
if tup[0] == "":
x_value.append("Others")
else:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' INITIATIVES")
plt.xlabel("Number Of Initiatives")
plt.ylabel("Organization")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot5.png")
def organization_resources():
with open("backupfiles/ResourceBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
org_dict = Counter()
next(my_reader)
for line in my_reader:
org_dict.update([line[4]])
temp_tuple_list = sorted(dict(org_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
if tup[0] == "":
x_value.append("Others")
else:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' RESOURCES")
plt.xlabel("Number Of Resources")
plt.ylabel("Organization")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot6.png")
def consumer_location():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
location_dict = Counter()
next(my_reader)
for line in my_reader:
location_dict.update([line[3]])
temp_tuple_list = sorted(dict(location_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' LOCATION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Location")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot7.png")
def consumer_age():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
age_list = []
next(my_reader)
for line in my_reader:
age = int(line[2])
age_list.append(age)
lowest = min(age_list)
highest = max(age_list)
bins = [0]
current = lowest
while current <= highest:
bins.append(current)
current += 5
bins.append(current)
plt.style.use("seaborn")
plt.figure(figsize=(10, 6))
plt.hist(age_list, bins=bins, color="#3dc5eb", edgecolor="#ffffff")
plt.title("CONSUMERS' AGE")
plt.xlabel("Age")
plt.ylabel("Number of Consumers")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot8.png")
def consumer_profession():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
profession_dict = Counter()
next(my_reader)
for line in my_reader:
profession_dict.update([line[4]])
temp_tuple_list = sorted(dict(profession_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' PROFESSION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Professsion")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot9.png")
def consumer_institution():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
institution_dict = Counter()
next(my_reader)
for line in my_reader:
institution_dict.update([line[5]])
temp_tuple_list = sorted(dict(institution_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' INSTITUTION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Institution")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot10.png")
def Consumer_send_newsletter():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
send_newsletter_dict = Counter()
next(my_reader)
for line in my_reader:
send_newsletter_dict.update([line[8]])
temp_tuple_list = sorted(dict(send_newsletter_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("CONSUMERS' SEND_NEWSLETTER")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot11.png") | core/analytics.py | import sys
import os
from matplotlib import pyplot as plt
import numpy as np
import csv
from collections import Counter
sys.path.append(os.getcwd())
os.environ["DJANGO_SETTINGS_MODULE"] = "as8_db.settings"
import django
django.setup()
from core import backup
def main():
backup.main()
organization_location()
organization_is_club()
organization_popularity()
organization_is_active()
organization_initiatives()
organization_resources()
consumer_age()
consumer_location()
consumer_profession()
consumer_institution()
Consumer_send_newsletter()
def height_calc(num):
if num <= 2:
return 2
elif num <= 5:
return 4
elif num <= 10:
return 7
elif num <= 20:
return 10
else:
return 15
def organization_location():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
location_dict = Counter()
next(my_reader)
for line in my_reader:
location_dict.update([line[3]])
temp_tuple_list = sorted(dict(location_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' LOCATION")
plt.xlabel("Number Of Organizations")
plt.ylabel("Location")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot1.png")
def organization_is_club():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
is_club_dict = Counter()
next(my_reader)
for line in my_reader:
is_club_dict.update([line[4]])
temp_tuple_list = sorted(dict(is_club_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' IS_CLUB")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot2.png")
def organization_popularity():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
popularity_dict = Counter()
next(my_reader)
for line in my_reader:
popularity_dict.update([line[6]])
temp_tuple_list = sorted(dict(popularity_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7", "#26849e"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' POPULARITY")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot3.png")
def organization_is_active():
with open("backupfiles/OrganizationBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
is_active_dict = Counter()
next(my_reader)
for line in my_reader:
is_active_dict.update([line[7]])
temp_tuple_list = sorted(dict(is_active_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("ORGANIZATIONS' IS_ACTIVE")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot4.png")
def organization_initiatives():
with open("backupfiles/InitiativeBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
org_dict = Counter()
next(my_reader)
for line in my_reader:
org_dict.update([line[3]])
temp_tuple_list = sorted(dict(org_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
if tup[0] == "":
x_value.append("Others")
else:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' INITIATIVES")
plt.xlabel("Number Of Initiatives")
plt.ylabel("Organization")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot5.png")
def organization_resources():
with open("backupfiles/ResourceBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
org_dict = Counter()
next(my_reader)
for line in my_reader:
org_dict.update([line[4]])
temp_tuple_list = sorted(dict(org_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
if tup[0] == "":
x_value.append("Others")
else:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("ORGANIZATIONS' RESOURCES")
plt.xlabel("Number Of Resources")
plt.ylabel("Organization")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot6.png")
def consumer_location():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
location_dict = Counter()
next(my_reader)
for line in my_reader:
location_dict.update([line[3]])
temp_tuple_list = sorted(dict(location_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' LOCATION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Location")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot7.png")
def consumer_age():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
age_list = []
next(my_reader)
for line in my_reader:
age = int(line[2])
age_list.append(age)
lowest = min(age_list)
highest = max(age_list)
bins = [0]
current = lowest
while current <= highest:
bins.append(current)
current += 5
bins.append(current)
plt.style.use("seaborn")
plt.figure(figsize=(10, 6))
plt.hist(age_list, bins=bins, color="#3dc5eb", edgecolor="#ffffff")
plt.title("CONSUMERS' AGE")
plt.xlabel("Age")
plt.ylabel("Number of Consumers")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot8.png")
def consumer_profession():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
profession_dict = Counter()
next(my_reader)
for line in my_reader:
profession_dict.update([line[4]])
temp_tuple_list = sorted(dict(profession_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' PROFESSION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Professsion")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot9.png")
def consumer_institution():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
institution_dict = Counter()
next(my_reader)
for line in my_reader:
institution_dict.update([line[5]])
temp_tuple_list = sorted(dict(institution_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
height_num = len(x_value)
plt.style.use("seaborn")
plt.figure(figsize=(10,height_calc(height_num)))
plt.barh(x_value, y_value , color="#3dc5eb")
plt.title("CONSUMERS' INSTITUTION")
plt.xlabel("Number Of Consumers")
plt.ylabel("Institution")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot10.png")
def Consumer_send_newsletter():
with open("backupfiles/ConsumerBUF.csv", "r") as rfile:
my_reader = csv.reader(rfile)
send_newsletter_dict = Counter()
next(my_reader)
for line in my_reader:
send_newsletter_dict.update([line[8]])
temp_tuple_list = sorted(dict(send_newsletter_dict).items(), key=lambda x:x[1])
x_value = []
y_value = []
for tup in temp_tuple_list:
x_value.append(tup[0])
y_value.append(tup[1])
colors = ["#3dc5eb", "#30a6c7"]
plt.style.use("seaborn")
plt.figure(figsize=(10,4))
_, _, autotexts = plt.pie(y_value, labels=x_value , colors=colors, wedgeprops={"edgecolor":"white"}, autopct="%1.1f%%")
for autotext in autotexts:
autotext.set_color('white')
plt.title("CONSUMERS' SEND_NEWSLETTER")
plt.tight_layout()
plt.savefig("core/static/core/images/plots/plot11.png") | 0.13005 | 0.270444 |
from __future__ import division
import optparse
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import colorsys
os.system('clear')
plt.ion()
Savepath = '/afs/psi.ch/project/EssentialMed/Dev/Images/CMOSDistance'
# Use Pythons Optionparser to define and read the options, and also
# give some help to the user
parser = optparse.OptionParser()
usage = "usage: %prog [options] arg"
# 17.526 is the standard lenght of the mounting surface to sensor length,
# according to <NAME> from Lensation and
# books.google.ch/books?id=DaQY8CrmqFcC&pg=PA140&lpg=PA140&dq=17.526+mm
parser.add_option('-d', dest='CMOSDistance', type='float',
help='CMOS-Lens-Distance [mm]. Default=%default',
default=17.526, metavar='13')
parser.add_option('-s', dest='UseSensor', type='int',
help='Sensor to use. 1=AR0130 , 2= AR0132, 3= MT9M0010. '
'Default=%default', default=2, metavar='2')
(options, args) = parser.parse_args()
'''
for i in {100..150};
do for s in {1,2,3};
do python lens_simulation.py -d $i -s $s;
done;
done
'''
print 'TEMPORARY'
print
print 'CMOSDistance converted from', options.CMOSDistance, 'mm to',
options.CMOSDistance = options.CMOSDistance / 10
print options.CMOSDistance, 'mm'
print
print 'TEMPORARY'
def plotcolors(NumberOfColors):
# After http://stackoverflow.com/a/9701141/323100
colors = []
for i in np.arange(0., 360., 360. / NumberOfColors):
hue = i / 360.
lightness = (50 + np.random.rand() * 10) / 100.
saturation = (90 + np.random.rand() * 10) / 100.
colors.append(colorsys.hls_to_rgb(hue, lightness, saturation))
return colors
def add_lens(z, f, diam, lbl):
# simply draws a thin-lens at the provided location parameters:
# - z: location along the optical axis (in mm)
# - f: focal length (in mm, can be negative if div. lens)
# - diam: lens diameter in mm
# - lbl: label to identify the lens on the drawing
ww, tw, rad = diam / 10.0, diam / 3.0, diam / 2.0
plt.plot([z, z], [-rad, rad], 'k', linewidth=2)
# plt.plot([z, z + tw], [-rad, -rad + np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z - tw], [-rad, -rad + np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z + tw], [rad, rad - np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z - tw], [rad, rad - np.sign(f) * ww], 'y', linewidth=2)
plt.plot([z + f, z + f], [-ww, ww], 'y', linewidth=2)
plt.plot([z - f, z - f], [-ww, ww], 'y', linewidth=2)
lens = patches.Ellipse((z, 0), width=2 * f, height=diam,
facecolor='y', linewidth=2, alpha=0.125)
plt.gcf().gca().add_patch(lens)
plt.text(z, rad + 2.0, lbl + '\nf=' + str(round(f, 2)),
horizontalalignment='center')
def propagate_beam(p0, NA, nr, zl, ff, raycolor='b'):
# geometrical propagation of light rays from given source parameters:
# - p0: location of the source (z0, x0) along and off axis (in mm)
# - NA: numerical aperture of the beam (in degrees)
# - nr: number of rays to trace
# - zl: array with the location of the lenses
# - ff: array with the focal length of lenses
# - raycolor: color of the rays on plot
apa = NA * np.pi / 180.0
z0 = p0[0]
if (np.size(p0) == 2):
x0 = p0[1]
else:
x0 = 0.0
zl1, ff1 = zl[(z0 < zl)], ff[(z0 < zl)]
nl = np.size(zl1) # number of lenses
zz, xx, tani = np.zeros(nl + 2), np.zeros(nl + 2), np.zeros(nl + 2)
tan0 = np.tan(apa / 2.0) - np.tan(apa) * np.arange(nr) / (nr - 1)
for i in range(nr):
tani[0] = tan0[i] # initial incidence angle
zz[0], xx[0] = z0, x0
for j in range(nl):
zz[j + 1] = zl1[j]
xx[j + 1] = xx[j] + (zz[j + 1] - zz[j]) * tani[j]
tani[j + 1] = tani[j] - xx[j + 1] / ff1[j]
zz[nl + 1] = zmax
xx[nl + 1] = xx[nl] + (zz[nl + 1] - zz[nl]) * tani[nl]
plt.plot(zz, xx, color=raycolor)
FOVSize = np.array([430 / 3., 430 / 4.])
FOVDiagonal = np.sqrt(FOVSize[0] ** 2 + FOVSize[1] ** 2)
if options.UseSensor == 1:
Sensor = 'AR0130'
# Full Resolution: 1280H x 960V (1.2Mp)
# Pixel Size: 3.75um x 3.75um
pixelsize = 3.75 / 1000
CMOSSize = np.array([1280 * pixelsize, 960 * pixelsize])
elif options.UseSensor == 2:
Sensor = 'AR0132'
# Full Resolution: 1280H x 960V (1.2Mp)
# Pixel Size: 3.75um x 3.75um
pixelsize = 3.75 / 1000
CMOSSize = np.array([1280 * pixelsize, 960 * pixelsize])
elif options.UseSensor == 3:
Sensor = 'MT9M0010'
# Active pixels: 1,280H x 1,024V
# Pixel size: 5.2um x 5.2um
pixelsize = 5.2 / 1000
CMOSSize = np.array([1280 * pixelsize, 1024 * pixelsize])
# Make output directory
try:
os.makedirs(os.path.join(Savepath, Sensor))
except OSError:
# Don't do anything if the folder already exists
pass
CMOSDiagonal = np.sqrt(CMOSSize[0] ** 2 + CMOSSize[1] ** 2)
print 'We are calcuating with the', Sensor, 'sensor, which has a size of', \
round(CMOSSize[0], 2), 'x', round(CMOSSize[1], 2), \
'mm, a diagonal of', round(CMOSDiagonal, 2), 'mm (or', \
round(CMOSDiagonal * 0.0393701, 2), 'inch).'
print 'The FOV we want to look at is', round(FOVSize[0], 2), 'x', \
round(FOVSize[1], 2), 'mm (430 x 430mm @ 4:3), a diagonal of', \
round(FOVDiagonal, 2), 'mm'
Magnification = FOVDiagonal / CMOSDiagonal
print 'We thus have a (de)magnification of', round(Magnification, 2), 'x'
# Draw the different sizes.
figure1 = plt.figure(figsize=(9, 9))
plt.title("Sizes, head on")
plt.show()
Scintillator = patches.Rectangle((0, 0), 430, 430, facecolor='g', linewidth=2)
figure1.gca().add_patch(Scintillator)
for x in range(3):
for y in range(4):
# Draw rectangles: http://is.gd/rmDuV1
FOV = patches.Rectangle((x * FOVSize[0], y * FOVSize[1]),
width=FOVSize[0], height=FOVSize[1],
facecolor='g', linewidth=2)
figure1.gca().add_patch(FOV)
Ellipse = patches.Ellipse((FOVSize[0] / 2 - CMOSSize[0] / 2 + x *
FOVSize[0], FOVSize[1] / 2 -
CMOSSize[1] / 2 + y * FOVSize[1]),
width=FOVSize[0] / 0.618,
height=FOVSize[1] / 0.618, color='k',
alpha=0.125)
figure1.gca().add_patch(Ellipse)
CMOS = patches.Rectangle((FOVSize[0] / 2 - CMOSSize[0] / 2 + x *
FOVSize[0], FOVSize[1] / 2 -
CMOSSize[1] / 2 + y * FOVSize[1]),
width=CMOSSize[0], height=CMOSSize[1],
facecolor='b', linewidth=2)
figure1.gca().add_patch(CMOS)
# Draw one more so we can get labels
FOV = patches.Rectangle((0, 0), FOVSize[0], FOVSize[1], facecolor='g',
linewidth=2, label='FOV')
figure1.gca().add_patch(FOV)
Ellipse = patches.Ellipse((FOVSize[0] / 2 - CMOSSize[0] / 2,
FOVSize[1] / 2 - CMOSSize[1] / 2),
width=FOVSize[0] / 0.618, height=FOVSize[1] / 0.618,
color='k', alpha=0.125, label='Opt. Circle')
figure1.gca().add_patch(Ellipse)
CMOS = patches.Rectangle((FOVSize[0] / 2 - CMOSSize[0] / 2,
FOVSize[1] / 2 - CMOSSize[1] / 2), CMOSSize[0],
CMOSSize[1], facecolor='b', linewidth=2,
label=Sensor)
figure1.gca().add_patch(CMOS)
plt.legend()
plt.axis('scaled')
plt.xlabel('Length [mm]')
plt.ylabel('Length [mm]')
plt.savefig(os.path.join(Savepath, Sensor,
'lens_simulation_sizecomparison.png'),
transparent=True)
print 80 * '-'
# www.physicsclassroom.com/class/refrn/Lesson-5/The-Mathematics-of-Lenses
# The magnification equation relates the ratio of the image distance and
# object distance to the ratio of the image height (hi) and object height
# (ho). The magnification equation is stated as follows:
# 1/f = 1/do + 1/di
# M = hi/ho = - di/do
# --> M * ho = hi or M * -do = di
# options.CMOSDistance comes from the options.CMOSDistance option, which is set
# to a default of 17.526 mm
FOVPosition = Magnification * options.CMOSDistance
FocalLength = 1 / ((1 / options.CMOSDistance) + (1 / FOVPosition))
print 'If the CMOS is set to be', options.CMOSDistance, 'mm away from the', \
'lens, the Scintillator has to be', round(FOVPosition, 2), \
'mm away from the lens.'
print 'This means that the total optical length is', \
round(options.CMOSDistance + FOVPosition, 2), 'mm'
print 'Since the CMOS is', round(options.CMOSDistance, 2), 'mm away from', \
'the lens we thus need a lens with a focal length of approximately', \
int(round(FocalLength))
print 'You can set the distance between the CMOS and the lens with the', \
'"-d" option.'
print sys.argv[0], '-d', options.CMOSDistance
print 'was used to generate this plot'
print 80 * '-'
# ~ Lens
# Draw the lens at the origin, to simplify things
LensPosition = np.array([0])
# Since we only draw *one* lens for the moment, we convert the focal length
# calculated above to a NumPy array, so we can use the drawing code
FocalLength = np.array([FocalLength])
# FNumber = FocalLength / LensDiameter
# FNumber = 1 / ( 2 * NumericalAperture)
# -> 1 / ( 2 * FNumber) = NumericalAperture
FNumber = 1.4
NumericalAperture = 1 / (2 * FNumber)
SzintillatorWidth = 5
figure2 = plt.figure(figsize=(16, 9))
plt.show()
# Draw top view
plt.subplot(121)
plt.title(' '.join([Sensor, '| Top view | CMOS-Lens-distance',
str(options.CMOSDistance), 'mm']))
# Draw CMOS and Scintillator
plt.plot((-options.CMOSDistance, -options.CMOSDistance),
(-CMOSSize[0] / 2, CMOSSize[0] / 2), color='b', linewidth=2)
plt.plot((FOVPosition, FOVPosition), (-FOVSize[0] / 2, FOVSize[0] / 2),
color='g', linewidth=SzintillatorWidth)
plt.xlabel('Distance [mm]')
plt.ylabel('Distance [mm]')
# Draw Lens(es)
LensDiameter = 12.0
for i in range(np.size(LensPosition)):
add_lens(LensPosition[i], FocalLength[i], LensDiameter, "L" + str(i))
zmin, zmax = -options.CMOSDistance, FOVPosition
# Draw beam paths
c = plotcolors(5)
c = ['blue', 'blue', 'blue', 'blue', 'blue', 'blue']
NumberOfRays = 5
BeamNA = 10
propagate_beam((-options.CMOSDistance, 0), BeamNA, NumberOfRays, LensPosition,
FocalLength, raycolor=c[0])
propagate_beam((-options.CMOSDistance, CMOSSize[0] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[1])
propagate_beam((-options.CMOSDistance, CMOSSize[0] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[2])
propagate_beam((-options.CMOSDistance, -CMOSSize[0] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[3])
propagate_beam((-options.CMOSDistance, -CMOSSize[0] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[4])
plt.xlim([-30, 250])
plt.ylim([-FOVSize[0] / 2 * 1.1, FOVSize[0] / 2 * 1.1])
# Draw side view
plt.subplot(122)
plt.title(' '.join([Sensor, '| Side view | CMOS-Lens-distance',
str(options.CMOSDistance), 'mm']))
# Draw CMOS and Scintillator
plt.plot((-options.CMOSDistance, -options.CMOSDistance),
(-CMOSSize[1] / 2, CMOSSize[1] / 2), color='b', linewidth=2)
plt.plot((FOVPosition, FOVPosition), (-FOVSize[1] / 2, FOVSize[1] / 2),
color='g', linewidth=SzintillatorWidth)
# Draw Lens(es)
for i in range(np.size(LensPosition)):
add_lens(LensPosition[i], FocalLength[i], LensDiameter, "L" + str(i))
# Draw beam paths
propagate_beam((-options.CMOSDistance, 0), BeamNA, NumberOfRays, LensPosition,
FocalLength, raycolor=c[0])
propagate_beam((-options.CMOSDistance, CMOSSize[1] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[1])
propagate_beam((-options.CMOSDistance, CMOSSize[1] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[2])
propagate_beam((-options.CMOSDistance, -CMOSSize[1] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[3])
propagate_beam((-options.CMOSDistance, -CMOSSize[1] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[4])
plt.xlabel('Distance [mm]')
plt.ylabel('Distance [mm]')
plt.xlim([-30, 250])
plt.ylim([-FOVSize[0] / 2 * 1.1, FOVSize[0] / 2 * 1.1])
plt.draw()
plt.savefig(os.path.join(Savepath, Sensor, 'lens_simulation_view_' +
str(round(options.CMOSDistance, 1)).zfill(
5) + 'mm.png'),
transparent=True)
plt.savefig(os.path.join(Savepath, Sensor, 'movie_lens_simulation_view_' +
str(int(round(options.CMOSDistance, 1) * 10)).zfill(
7) + 'mm.png'),
transparent=True)
plt.ioff()
plt.show() | lens_simulation.py | from __future__ import division
import optparse
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import colorsys
os.system('clear')
plt.ion()
Savepath = '/afs/psi.ch/project/EssentialMed/Dev/Images/CMOSDistance'
# Use Pythons Optionparser to define and read the options, and also
# give some help to the user
parser = optparse.OptionParser()
usage = "usage: %prog [options] arg"
# 17.526 is the standard lenght of the mounting surface to sensor length,
# according to <NAME> from Lensation and
# books.google.ch/books?id=DaQY8CrmqFcC&pg=PA140&lpg=PA140&dq=17.526+mm
parser.add_option('-d', dest='CMOSDistance', type='float',
help='CMOS-Lens-Distance [mm]. Default=%default',
default=17.526, metavar='13')
parser.add_option('-s', dest='UseSensor', type='int',
help='Sensor to use. 1=AR0130 , 2= AR0132, 3= MT9M0010. '
'Default=%default', default=2, metavar='2')
(options, args) = parser.parse_args()
'''
for i in {100..150};
do for s in {1,2,3};
do python lens_simulation.py -d $i -s $s;
done;
done
'''
print 'TEMPORARY'
print
print 'CMOSDistance converted from', options.CMOSDistance, 'mm to',
options.CMOSDistance = options.CMOSDistance / 10
print options.CMOSDistance, 'mm'
print
print 'TEMPORARY'
def plotcolors(NumberOfColors):
# After http://stackoverflow.com/a/9701141/323100
colors = []
for i in np.arange(0., 360., 360. / NumberOfColors):
hue = i / 360.
lightness = (50 + np.random.rand() * 10) / 100.
saturation = (90 + np.random.rand() * 10) / 100.
colors.append(colorsys.hls_to_rgb(hue, lightness, saturation))
return colors
def add_lens(z, f, diam, lbl):
# simply draws a thin-lens at the provided location parameters:
# - z: location along the optical axis (in mm)
# - f: focal length (in mm, can be negative if div. lens)
# - diam: lens diameter in mm
# - lbl: label to identify the lens on the drawing
ww, tw, rad = diam / 10.0, diam / 3.0, diam / 2.0
plt.plot([z, z], [-rad, rad], 'k', linewidth=2)
# plt.plot([z, z + tw], [-rad, -rad + np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z - tw], [-rad, -rad + np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z + tw], [rad, rad - np.sign(f) * ww], 'y', linewidth=2)
# plt.plot([z, z - tw], [rad, rad - np.sign(f) * ww], 'y', linewidth=2)
plt.plot([z + f, z + f], [-ww, ww], 'y', linewidth=2)
plt.plot([z - f, z - f], [-ww, ww], 'y', linewidth=2)
lens = patches.Ellipse((z, 0), width=2 * f, height=diam,
facecolor='y', linewidth=2, alpha=0.125)
plt.gcf().gca().add_patch(lens)
plt.text(z, rad + 2.0, lbl + '\nf=' + str(round(f, 2)),
horizontalalignment='center')
def propagate_beam(p0, NA, nr, zl, ff, raycolor='b'):
# geometrical propagation of light rays from given source parameters:
# - p0: location of the source (z0, x0) along and off axis (in mm)
# - NA: numerical aperture of the beam (in degrees)
# - nr: number of rays to trace
# - zl: array with the location of the lenses
# - ff: array with the focal length of lenses
# - raycolor: color of the rays on plot
apa = NA * np.pi / 180.0
z0 = p0[0]
if (np.size(p0) == 2):
x0 = p0[1]
else:
x0 = 0.0
zl1, ff1 = zl[(z0 < zl)], ff[(z0 < zl)]
nl = np.size(zl1) # number of lenses
zz, xx, tani = np.zeros(nl + 2), np.zeros(nl + 2), np.zeros(nl + 2)
tan0 = np.tan(apa / 2.0) - np.tan(apa) * np.arange(nr) / (nr - 1)
for i in range(nr):
tani[0] = tan0[i] # initial incidence angle
zz[0], xx[0] = z0, x0
for j in range(nl):
zz[j + 1] = zl1[j]
xx[j + 1] = xx[j] + (zz[j + 1] - zz[j]) * tani[j]
tani[j + 1] = tani[j] - xx[j + 1] / ff1[j]
zz[nl + 1] = zmax
xx[nl + 1] = xx[nl] + (zz[nl + 1] - zz[nl]) * tani[nl]
plt.plot(zz, xx, color=raycolor)
FOVSize = np.array([430 / 3., 430 / 4.])
FOVDiagonal = np.sqrt(FOVSize[0] ** 2 + FOVSize[1] ** 2)
if options.UseSensor == 1:
Sensor = 'AR0130'
# Full Resolution: 1280H x 960V (1.2Mp)
# Pixel Size: 3.75um x 3.75um
pixelsize = 3.75 / 1000
CMOSSize = np.array([1280 * pixelsize, 960 * pixelsize])
elif options.UseSensor == 2:
Sensor = 'AR0132'
# Full Resolution: 1280H x 960V (1.2Mp)
# Pixel Size: 3.75um x 3.75um
pixelsize = 3.75 / 1000
CMOSSize = np.array([1280 * pixelsize, 960 * pixelsize])
elif options.UseSensor == 3:
Sensor = 'MT9M0010'
# Active pixels: 1,280H x 1,024V
# Pixel size: 5.2um x 5.2um
pixelsize = 5.2 / 1000
CMOSSize = np.array([1280 * pixelsize, 1024 * pixelsize])
# Make output directory
try:
os.makedirs(os.path.join(Savepath, Sensor))
except OSError:
# Don't do anything if the folder already exists
pass
CMOSDiagonal = np.sqrt(CMOSSize[0] ** 2 + CMOSSize[1] ** 2)
print 'We are calcuating with the', Sensor, 'sensor, which has a size of', \
round(CMOSSize[0], 2), 'x', round(CMOSSize[1], 2), \
'mm, a diagonal of', round(CMOSDiagonal, 2), 'mm (or', \
round(CMOSDiagonal * 0.0393701, 2), 'inch).'
print 'The FOV we want to look at is', round(FOVSize[0], 2), 'x', \
round(FOVSize[1], 2), 'mm (430 x 430mm @ 4:3), a diagonal of', \
round(FOVDiagonal, 2), 'mm'
Magnification = FOVDiagonal / CMOSDiagonal
print 'We thus have a (de)magnification of', round(Magnification, 2), 'x'
# Draw the different sizes.
figure1 = plt.figure(figsize=(9, 9))
plt.title("Sizes, head on")
plt.show()
Scintillator = patches.Rectangle((0, 0), 430, 430, facecolor='g', linewidth=2)
figure1.gca().add_patch(Scintillator)
for x in range(3):
for y in range(4):
# Draw rectangles: http://is.gd/rmDuV1
FOV = patches.Rectangle((x * FOVSize[0], y * FOVSize[1]),
width=FOVSize[0], height=FOVSize[1],
facecolor='g', linewidth=2)
figure1.gca().add_patch(FOV)
Ellipse = patches.Ellipse((FOVSize[0] / 2 - CMOSSize[0] / 2 + x *
FOVSize[0], FOVSize[1] / 2 -
CMOSSize[1] / 2 + y * FOVSize[1]),
width=FOVSize[0] / 0.618,
height=FOVSize[1] / 0.618, color='k',
alpha=0.125)
figure1.gca().add_patch(Ellipse)
CMOS = patches.Rectangle((FOVSize[0] / 2 - CMOSSize[0] / 2 + x *
FOVSize[0], FOVSize[1] / 2 -
CMOSSize[1] / 2 + y * FOVSize[1]),
width=CMOSSize[0], height=CMOSSize[1],
facecolor='b', linewidth=2)
figure1.gca().add_patch(CMOS)
# Draw one more so we can get labels
FOV = patches.Rectangle((0, 0), FOVSize[0], FOVSize[1], facecolor='g',
linewidth=2, label='FOV')
figure1.gca().add_patch(FOV)
Ellipse = patches.Ellipse((FOVSize[0] / 2 - CMOSSize[0] / 2,
FOVSize[1] / 2 - CMOSSize[1] / 2),
width=FOVSize[0] / 0.618, height=FOVSize[1] / 0.618,
color='k', alpha=0.125, label='Opt. Circle')
figure1.gca().add_patch(Ellipse)
CMOS = patches.Rectangle((FOVSize[0] / 2 - CMOSSize[0] / 2,
FOVSize[1] / 2 - CMOSSize[1] / 2), CMOSSize[0],
CMOSSize[1], facecolor='b', linewidth=2,
label=Sensor)
figure1.gca().add_patch(CMOS)
plt.legend()
plt.axis('scaled')
plt.xlabel('Length [mm]')
plt.ylabel('Length [mm]')
plt.savefig(os.path.join(Savepath, Sensor,
'lens_simulation_sizecomparison.png'),
transparent=True)
print 80 * '-'
# www.physicsclassroom.com/class/refrn/Lesson-5/The-Mathematics-of-Lenses
# The magnification equation relates the ratio of the image distance and
# object distance to the ratio of the image height (hi) and object height
# (ho). The magnification equation is stated as follows:
# 1/f = 1/do + 1/di
# M = hi/ho = - di/do
# --> M * ho = hi or M * -do = di
# options.CMOSDistance comes from the options.CMOSDistance option, which is set
# to a default of 17.526 mm
FOVPosition = Magnification * options.CMOSDistance
FocalLength = 1 / ((1 / options.CMOSDistance) + (1 / FOVPosition))
print 'If the CMOS is set to be', options.CMOSDistance, 'mm away from the', \
'lens, the Scintillator has to be', round(FOVPosition, 2), \
'mm away from the lens.'
print 'This means that the total optical length is', \
round(options.CMOSDistance + FOVPosition, 2), 'mm'
print 'Since the CMOS is', round(options.CMOSDistance, 2), 'mm away from', \
'the lens we thus need a lens with a focal length of approximately', \
int(round(FocalLength))
print 'You can set the distance between the CMOS and the lens with the', \
'"-d" option.'
print sys.argv[0], '-d', options.CMOSDistance
print 'was used to generate this plot'
print 80 * '-'
# ~ Lens
# Draw the lens at the origin, to simplify things
LensPosition = np.array([0])
# Since we only draw *one* lens for the moment, we convert the focal length
# calculated above to a NumPy array, so we can use the drawing code
FocalLength = np.array([FocalLength])
# FNumber = FocalLength / LensDiameter
# FNumber = 1 / ( 2 * NumericalAperture)
# -> 1 / ( 2 * FNumber) = NumericalAperture
FNumber = 1.4
NumericalAperture = 1 / (2 * FNumber)
SzintillatorWidth = 5
figure2 = plt.figure(figsize=(16, 9))
plt.show()
# Draw top view
plt.subplot(121)
plt.title(' '.join([Sensor, '| Top view | CMOS-Lens-distance',
str(options.CMOSDistance), 'mm']))
# Draw CMOS and Scintillator
plt.plot((-options.CMOSDistance, -options.CMOSDistance),
(-CMOSSize[0] / 2, CMOSSize[0] / 2), color='b', linewidth=2)
plt.plot((FOVPosition, FOVPosition), (-FOVSize[0] / 2, FOVSize[0] / 2),
color='g', linewidth=SzintillatorWidth)
plt.xlabel('Distance [mm]')
plt.ylabel('Distance [mm]')
# Draw Lens(es)
LensDiameter = 12.0
for i in range(np.size(LensPosition)):
add_lens(LensPosition[i], FocalLength[i], LensDiameter, "L" + str(i))
zmin, zmax = -options.CMOSDistance, FOVPosition
# Draw beam paths
c = plotcolors(5)
c = ['blue', 'blue', 'blue', 'blue', 'blue', 'blue']
NumberOfRays = 5
BeamNA = 10
propagate_beam((-options.CMOSDistance, 0), BeamNA, NumberOfRays, LensPosition,
FocalLength, raycolor=c[0])
propagate_beam((-options.CMOSDistance, CMOSSize[0] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[1])
propagate_beam((-options.CMOSDistance, CMOSSize[0] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[2])
propagate_beam((-options.CMOSDistance, -CMOSSize[0] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[3])
propagate_beam((-options.CMOSDistance, -CMOSSize[0] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[4])
plt.xlim([-30, 250])
plt.ylim([-FOVSize[0] / 2 * 1.1, FOVSize[0] / 2 * 1.1])
# Draw side view
plt.subplot(122)
plt.title(' '.join([Sensor, '| Side view | CMOS-Lens-distance',
str(options.CMOSDistance), 'mm']))
# Draw CMOS and Scintillator
plt.plot((-options.CMOSDistance, -options.CMOSDistance),
(-CMOSSize[1] / 2, CMOSSize[1] / 2), color='b', linewidth=2)
plt.plot((FOVPosition, FOVPosition), (-FOVSize[1] / 2, FOVSize[1] / 2),
color='g', linewidth=SzintillatorWidth)
# Draw Lens(es)
for i in range(np.size(LensPosition)):
add_lens(LensPosition[i], FocalLength[i], LensDiameter, "L" + str(i))
# Draw beam paths
propagate_beam((-options.CMOSDistance, 0), BeamNA, NumberOfRays, LensPosition,
FocalLength, raycolor=c[0])
propagate_beam((-options.CMOSDistance, CMOSSize[1] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[1])
propagate_beam((-options.CMOSDistance, CMOSSize[1] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[2])
propagate_beam((-options.CMOSDistance, -CMOSSize[1] / 4), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[3])
propagate_beam((-options.CMOSDistance, -CMOSSize[1] / 2), BeamNA, NumberOfRays,
LensPosition, FocalLength, raycolor=c[4])
plt.xlabel('Distance [mm]')
plt.ylabel('Distance [mm]')
plt.xlim([-30, 250])
plt.ylim([-FOVSize[0] / 2 * 1.1, FOVSize[0] / 2 * 1.1])
plt.draw()
plt.savefig(os.path.join(Savepath, Sensor, 'lens_simulation_view_' +
str(round(options.CMOSDistance, 1)).zfill(
5) + 'mm.png'),
transparent=True)
plt.savefig(os.path.join(Savepath, Sensor, 'movie_lens_simulation_view_' +
str(int(round(options.CMOSDistance, 1) * 10)).zfill(
7) + 'mm.png'),
transparent=True)
plt.ioff()
plt.show() | 0.500488 | 0.312331 |
import tensorflow as tf
import tensorflow
from tensorflow.python.keras.models import Model
from tensorflow.python.keras.layers import (
Input,
concatenate,
ZeroPadding2D,
Lambda,
Dense,
Dropout,
Activation,
Convolution2D,
AveragePooling2D,
GlobalAveragePooling2D,
MaxPooling2D,
BatchNormalization,
)
from handcam.ltt.network.model.DenseNet.custom_layers import Scale
def DenseNet(
nb_dense_block=4,
growth_rate=48,
nb_filter=96,
reduction=0.0,
dropout_rate=0.0,
weight_decay=1e-4,
classes=1000,
weights_path=None,
):
"""Instantiate the DenseNet 161 architecture,
# Arguments
nb_dense_block: number of dense blocks to add to end
growth_rate: number of filters to add per dense block
nb_filter: initial number of filters
reduction: reduction factor of transition blocks.
dropout_rate: dropout rate
weight_decay: weight decay factor
classes: optional number of classes to classify images
weights_path: path to pre-trained weights
# Returns
A Keras model instance.
"""
eps = 1.1e-5
# compute compression factor
compression = 1.0 - reduction
# Handle Dimension Ordering for different backends
global concat_axis
concat_axis = 3
img_input = Input(
shape=(224, 224, 4), name="data"
) # BGR-D. Treat the BGR and depth with separate pipelines.
bgr_img_input = crop(dimension=3, start=0, end=3)(img_input)
depth_img_input = crop(dimension=3, start=3, end=4)(img_input)
# From architecture for ImageNet (Table 1 in the paper)
nb_filter = 96
nb_layers = [6, 12, 36, 24] # For DenseNet-161
"""
Begin BGR treatment
"""
# Initial convolution
x = ZeroPadding2D((3, 3), name="conv1_zeropadding")(bgr_img_input)
x = Convolution2D(nb_filter, 7, strides=2, name="conv1", use_bias=False)(x)
x = BatchNormalization(epsilon=eps, axis=concat_axis, name="conv1_bn")(x)
x = Scale(axis=concat_axis, name="conv1_scale")(x)
x = Activation("relu", name="relu1")(x)
x = ZeroPadding2D((1, 1), name="pool1_zeropadding")(x)
x = MaxPooling2D((3, 3), strides=(2, 2), name="pool1")(x)
# Add dense blocks
for block_idx in range(nb_dense_block - 1):
stage = block_idx + 2
x, nb_filter = dense_block(
x,
stage,
nb_layers[block_idx],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
# Add transition_block
x = transition_block(
x,
stage,
nb_filter,
compression=compression,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
nb_filter = int(nb_filter * compression)
final_stage = stage + 1
x, nb_filter = dense_block(
x,
final_stage,
nb_layers[-1],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name="conv" + str(final_stage) + "_blk_bn"
)(x)
x = Scale(axis=concat_axis, name="conv" + str(final_stage) + "_blk_scale")(x)
x = Activation("relu", name="relu" + str(final_stage) + "_blk")(x)
x = GlobalAveragePooling2D(name="pool" + str(final_stage))(x)
"""
Begin depth treatment
"""
# From architecture for ImageNet (Table 1 in the paper)
nb_filter = 96
nb_layers = [6, 12, 36, 24] # For DenseNet-161
# Initial convolution
y = ZeroPadding2D((3, 3), name="conv1_depth_zeropadding")(depth_img_input)
y = Convolution2D(nb_filter, 7, strides=2, name="conv1_depth", use_bias=False)(y)
y = BatchNormalization(epsilon=eps, axis=concat_axis, name="conv1_depth_bn")(y)
y = Scale(axis=concat_axis, name="conv1_depth_scale")(y)
y = Activation("relu", name="relu1_depth")(y)
y = ZeroPadding2D((1, 1), name="pool1_depth_zeropadding")(y)
y = MaxPooling2D((3, 3), strides=(2, 2), name="pool1_depth")(y)
# Add dense blocks
for block_idx in range(nb_dense_block - 1):
stage = block_idx + 2
y, nb_filter = dense_block(
y,
stage,
nb_layers[block_idx],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
# Add transition_block
y = transition_block(
y,
stage,
nb_filter,
compression=compression,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
nb_filter = int(nb_filter * compression)
final_stage = stage + 1
y, nb_filter = dense_block(
y,
final_stage,
nb_layers[-1],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
y = BatchNormalization(
epsilon=eps,
axis=concat_axis,
name="conv" + "_depth_" + str(final_stage) + "_blk_bn",
)(y)
y = Scale(
axis=concat_axis, name="conv" + "_depth_" + str(final_stage) + "_blk_scale"
)(y)
y = Activation("relu", name="relu" + "_depth_" + str(final_stage) + "_blk")(y)
y = GlobalAveragePooling2D(name="pool" + "_depth_" + str(final_stage))(y)
"""
Combine BGR and depth before the fully connected layers.
"""
x = concatenate([x, y])
# x = Dense(1024, name='fc1')(x) # Don't use name fc6, because we're loading weights by name.
x = Dense(classes, name="fc1")(x)
x = Activation("softmax", name="prob_out")(x)
model = Model(img_input, x, name="densenet")
if weights_path is not None:
model.load_weights(weights_path, by_name=True)
return model
def crop(dimension, start, end):
# Crops (or slices) a Tensor on a given dimension from start to end
# example : to crop tensor x[:, :, 5:10]
# call slice(2, 5, 10) as you want to crop on the second dimension
def func(x):
if dimension == 0:
return x[start:end]
if dimension == 1:
return x[:, start:end]
if dimension == 2:
return x[:, :, start:end]
if dimension == 3:
return x[:, :, :, start:end]
if dimension == 4:
return x[:, :, :, :, start:end]
return Lambda(func)
def conv_block(
x, stage, branch, nb_filter, dropout_rate=None, weight_decay=1e-4, depth_block=False
):
"""Apply BatchNorm, Relu, bottleneck 1x1 Conv2D, 3x3 Conv2D, and option dropout
# Arguments
x: input tensor
stage: index for dense block
branch: layer index within each dense block
nb_filter: number of filters
dropout_rate: dropout rate
weight_decay: weight decay factor
"""
eps = 1.1e-5
conv_name_base = "conv" + str(stage) + "_" + str(branch)
relu_name_base = "relu" + str(stage) + "_" + str(branch)
if depth_block:
conv_name_base = "conv_depth_" + str(stage) + "_" + str(branch)
relu_name_base = "relu_depth_" + str(stage) + "_" + str(branch)
# 1x1 Convolution (Bottleneck layer)
inter_channel = nb_filter * 4
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name=conv_name_base + "_x1_bn"
)(x)
x = Scale(axis=concat_axis, name=conv_name_base + "_x1_scale")(x)
x = Activation("relu", name=relu_name_base + "_x1")(x)
x = Convolution2D(inter_channel, 1, name=conv_name_base + "_x1", use_bias=False)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
# 3x3 Convolution
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name=conv_name_base + "_x2_bn"
)(x)
x = Scale(axis=concat_axis, name=conv_name_base + "_x2_scale")(x)
x = Activation("relu", name=relu_name_base + "_x2")(x)
x = ZeroPadding2D((1, 1), name=conv_name_base + "_x2_zeropadding")(x)
x = Convolution2D(nb_filter, 3, name=conv_name_base + "_x2", use_bias=False)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
return x
def transition_block(
x,
stage,
nb_filter,
compression=1.0,
dropout_rate=None,
weight_decay=1e-4,
depth_block=False,
):
"""Apply BatchNorm, 1x1 Convolution, averagePooling, optional compression, dropout
# Arguments
x: input tensor
stage: index for dense block
nb_filter: number of filters
compression: calculated as 1 - reduction. Reduces the number of feature maps in the transition block.
dropout_rate: dropout rate
weight_decay: weight decay factor
"""
eps = 1.1e-5
conv_name_base = "conv" + str(stage) + "_blk"
relu_name_base = "relu" + str(stage) + "_blk"
pool_name_base = "pool" + str(stage)
if depth_block:
conv_name_base = "conv_depth_" + str(stage) + "_blk"
relu_name_base = "relu_depth_" + str(stage) + "_blk"
pool_name_base = "pool_depth_" + str(stage)
x = BatchNormalization(epsilon=eps, axis=concat_axis, name=conv_name_base + "_bn")(
x
)
x = Scale(axis=concat_axis, name=conv_name_base + "_scale")(x)
x = Activation("relu", name=relu_name_base)(x)
x = Convolution2D(
int(nb_filter * compression), 1, name=conv_name_base, use_bias=False
)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
x = AveragePooling2D((2, 2), strides=(2, 2), name=pool_name_base)(x)
return x
def dense_block(
x,
stage,
nb_layers,
nb_filter,
growth_rate,
dropout_rate=None,
weight_decay=1e-4,
grow_nb_filters=True,
depth_block=False,
):
"""Build a dense_block where the output of each conv_block is fed to subsequent ones
# Arguments
x: input tensor
stage: index for dense block
nb_layers: the number of layers of conv_block to append to the model.
nb_filter: number of filters
growth_rate: growth rate
dropout_rate: dropout rate
weight_decay: weight decay factor
grow_nb_filters: flag to decide to allow number of filters to grow
"""
eps = 1.1e-5
concat_feat = x
concat_name_base = "concat_"
if depth_block:
concat_name_base = "concat_depth_"
for i in range(nb_layers):
branch = i + 1
x = conv_block(
concat_feat,
stage,
branch,
growth_rate,
dropout_rate,
weight_decay,
depth_block=depth_block,
)
concat_feat = concatenate(
[concat_feat, x],
axis=concat_axis,
name=concat_name_base + str(stage) + "_" + str(branch),
)
if grow_nb_filters:
nb_filter += growth_rate
return concat_feat, nb_filter | handcam/ltt/network/model/DenseNet/densenet161_depth.py | import tensorflow as tf
import tensorflow
from tensorflow.python.keras.models import Model
from tensorflow.python.keras.layers import (
Input,
concatenate,
ZeroPadding2D,
Lambda,
Dense,
Dropout,
Activation,
Convolution2D,
AveragePooling2D,
GlobalAveragePooling2D,
MaxPooling2D,
BatchNormalization,
)
from handcam.ltt.network.model.DenseNet.custom_layers import Scale
def DenseNet(
nb_dense_block=4,
growth_rate=48,
nb_filter=96,
reduction=0.0,
dropout_rate=0.0,
weight_decay=1e-4,
classes=1000,
weights_path=None,
):
"""Instantiate the DenseNet 161 architecture,
# Arguments
nb_dense_block: number of dense blocks to add to end
growth_rate: number of filters to add per dense block
nb_filter: initial number of filters
reduction: reduction factor of transition blocks.
dropout_rate: dropout rate
weight_decay: weight decay factor
classes: optional number of classes to classify images
weights_path: path to pre-trained weights
# Returns
A Keras model instance.
"""
eps = 1.1e-5
# compute compression factor
compression = 1.0 - reduction
# Handle Dimension Ordering for different backends
global concat_axis
concat_axis = 3
img_input = Input(
shape=(224, 224, 4), name="data"
) # BGR-D. Treat the BGR and depth with separate pipelines.
bgr_img_input = crop(dimension=3, start=0, end=3)(img_input)
depth_img_input = crop(dimension=3, start=3, end=4)(img_input)
# From architecture for ImageNet (Table 1 in the paper)
nb_filter = 96
nb_layers = [6, 12, 36, 24] # For DenseNet-161
"""
Begin BGR treatment
"""
# Initial convolution
x = ZeroPadding2D((3, 3), name="conv1_zeropadding")(bgr_img_input)
x = Convolution2D(nb_filter, 7, strides=2, name="conv1", use_bias=False)(x)
x = BatchNormalization(epsilon=eps, axis=concat_axis, name="conv1_bn")(x)
x = Scale(axis=concat_axis, name="conv1_scale")(x)
x = Activation("relu", name="relu1")(x)
x = ZeroPadding2D((1, 1), name="pool1_zeropadding")(x)
x = MaxPooling2D((3, 3), strides=(2, 2), name="pool1")(x)
# Add dense blocks
for block_idx in range(nb_dense_block - 1):
stage = block_idx + 2
x, nb_filter = dense_block(
x,
stage,
nb_layers[block_idx],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
# Add transition_block
x = transition_block(
x,
stage,
nb_filter,
compression=compression,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
nb_filter = int(nb_filter * compression)
final_stage = stage + 1
x, nb_filter = dense_block(
x,
final_stage,
nb_layers[-1],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
)
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name="conv" + str(final_stage) + "_blk_bn"
)(x)
x = Scale(axis=concat_axis, name="conv" + str(final_stage) + "_blk_scale")(x)
x = Activation("relu", name="relu" + str(final_stage) + "_blk")(x)
x = GlobalAveragePooling2D(name="pool" + str(final_stage))(x)
"""
Begin depth treatment
"""
# From architecture for ImageNet (Table 1 in the paper)
nb_filter = 96
nb_layers = [6, 12, 36, 24] # For DenseNet-161
# Initial convolution
y = ZeroPadding2D((3, 3), name="conv1_depth_zeropadding")(depth_img_input)
y = Convolution2D(nb_filter, 7, strides=2, name="conv1_depth", use_bias=False)(y)
y = BatchNormalization(epsilon=eps, axis=concat_axis, name="conv1_depth_bn")(y)
y = Scale(axis=concat_axis, name="conv1_depth_scale")(y)
y = Activation("relu", name="relu1_depth")(y)
y = ZeroPadding2D((1, 1), name="pool1_depth_zeropadding")(y)
y = MaxPooling2D((3, 3), strides=(2, 2), name="pool1_depth")(y)
# Add dense blocks
for block_idx in range(nb_dense_block - 1):
stage = block_idx + 2
y, nb_filter = dense_block(
y,
stage,
nb_layers[block_idx],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
# Add transition_block
y = transition_block(
y,
stage,
nb_filter,
compression=compression,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
nb_filter = int(nb_filter * compression)
final_stage = stage + 1
y, nb_filter = dense_block(
y,
final_stage,
nb_layers[-1],
nb_filter,
growth_rate,
dropout_rate=dropout_rate,
weight_decay=weight_decay,
depth_block=True,
)
y = BatchNormalization(
epsilon=eps,
axis=concat_axis,
name="conv" + "_depth_" + str(final_stage) + "_blk_bn",
)(y)
y = Scale(
axis=concat_axis, name="conv" + "_depth_" + str(final_stage) + "_blk_scale"
)(y)
y = Activation("relu", name="relu" + "_depth_" + str(final_stage) + "_blk")(y)
y = GlobalAveragePooling2D(name="pool" + "_depth_" + str(final_stage))(y)
"""
Combine BGR and depth before the fully connected layers.
"""
x = concatenate([x, y])
# x = Dense(1024, name='fc1')(x) # Don't use name fc6, because we're loading weights by name.
x = Dense(classes, name="fc1")(x)
x = Activation("softmax", name="prob_out")(x)
model = Model(img_input, x, name="densenet")
if weights_path is not None:
model.load_weights(weights_path, by_name=True)
return model
def crop(dimension, start, end):
# Crops (or slices) a Tensor on a given dimension from start to end
# example : to crop tensor x[:, :, 5:10]
# call slice(2, 5, 10) as you want to crop on the second dimension
def func(x):
if dimension == 0:
return x[start:end]
if dimension == 1:
return x[:, start:end]
if dimension == 2:
return x[:, :, start:end]
if dimension == 3:
return x[:, :, :, start:end]
if dimension == 4:
return x[:, :, :, :, start:end]
return Lambda(func)
def conv_block(
x, stage, branch, nb_filter, dropout_rate=None, weight_decay=1e-4, depth_block=False
):
"""Apply BatchNorm, Relu, bottleneck 1x1 Conv2D, 3x3 Conv2D, and option dropout
# Arguments
x: input tensor
stage: index for dense block
branch: layer index within each dense block
nb_filter: number of filters
dropout_rate: dropout rate
weight_decay: weight decay factor
"""
eps = 1.1e-5
conv_name_base = "conv" + str(stage) + "_" + str(branch)
relu_name_base = "relu" + str(stage) + "_" + str(branch)
if depth_block:
conv_name_base = "conv_depth_" + str(stage) + "_" + str(branch)
relu_name_base = "relu_depth_" + str(stage) + "_" + str(branch)
# 1x1 Convolution (Bottleneck layer)
inter_channel = nb_filter * 4
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name=conv_name_base + "_x1_bn"
)(x)
x = Scale(axis=concat_axis, name=conv_name_base + "_x1_scale")(x)
x = Activation("relu", name=relu_name_base + "_x1")(x)
x = Convolution2D(inter_channel, 1, name=conv_name_base + "_x1", use_bias=False)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
# 3x3 Convolution
x = BatchNormalization(
epsilon=eps, axis=concat_axis, name=conv_name_base + "_x2_bn"
)(x)
x = Scale(axis=concat_axis, name=conv_name_base + "_x2_scale")(x)
x = Activation("relu", name=relu_name_base + "_x2")(x)
x = ZeroPadding2D((1, 1), name=conv_name_base + "_x2_zeropadding")(x)
x = Convolution2D(nb_filter, 3, name=conv_name_base + "_x2", use_bias=False)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
return x
def transition_block(
x,
stage,
nb_filter,
compression=1.0,
dropout_rate=None,
weight_decay=1e-4,
depth_block=False,
):
"""Apply BatchNorm, 1x1 Convolution, averagePooling, optional compression, dropout
# Arguments
x: input tensor
stage: index for dense block
nb_filter: number of filters
compression: calculated as 1 - reduction. Reduces the number of feature maps in the transition block.
dropout_rate: dropout rate
weight_decay: weight decay factor
"""
eps = 1.1e-5
conv_name_base = "conv" + str(stage) + "_blk"
relu_name_base = "relu" + str(stage) + "_blk"
pool_name_base = "pool" + str(stage)
if depth_block:
conv_name_base = "conv_depth_" + str(stage) + "_blk"
relu_name_base = "relu_depth_" + str(stage) + "_blk"
pool_name_base = "pool_depth_" + str(stage)
x = BatchNormalization(epsilon=eps, axis=concat_axis, name=conv_name_base + "_bn")(
x
)
x = Scale(axis=concat_axis, name=conv_name_base + "_scale")(x)
x = Activation("relu", name=relu_name_base)(x)
x = Convolution2D(
int(nb_filter * compression), 1, name=conv_name_base, use_bias=False
)(x)
if dropout_rate:
x = Dropout(dropout_rate)(x)
x = AveragePooling2D((2, 2), strides=(2, 2), name=pool_name_base)(x)
return x
def dense_block(
x,
stage,
nb_layers,
nb_filter,
growth_rate,
dropout_rate=None,
weight_decay=1e-4,
grow_nb_filters=True,
depth_block=False,
):
"""Build a dense_block where the output of each conv_block is fed to subsequent ones
# Arguments
x: input tensor
stage: index for dense block
nb_layers: the number of layers of conv_block to append to the model.
nb_filter: number of filters
growth_rate: growth rate
dropout_rate: dropout rate
weight_decay: weight decay factor
grow_nb_filters: flag to decide to allow number of filters to grow
"""
eps = 1.1e-5
concat_feat = x
concat_name_base = "concat_"
if depth_block:
concat_name_base = "concat_depth_"
for i in range(nb_layers):
branch = i + 1
x = conv_block(
concat_feat,
stage,
branch,
growth_rate,
dropout_rate,
weight_decay,
depth_block=depth_block,
)
concat_feat = concatenate(
[concat_feat, x],
axis=concat_axis,
name=concat_name_base + str(stage) + "_" + str(branch),
)
if grow_nb_filters:
nb_filter += growth_rate
return concat_feat, nb_filter | 0.930777 | 0.473414 |
import argparse
import csv
import multiprocessing
import os
import pickle
from pathlib import Path
from typing import Optional, Tuple
from attr import attrs
from nerpy import load_json
from nerpy.scoring import ScoringResult
from scripts.train_test import train_test
@attrs(auto_attribs=True)
class ExperimentConfiguration:
name: str
train_path: str
test_path: str
training_params_path: str
feature_params_path: str
mention_encoding_name: str
ablation_size: int
random_seed: Optional[int]
output_dir: str
def run_expts(
name_prefix: str,
train_path: str,
test_path: str,
training_params_path: str,
feature_params_path: str,
mention_encodings_path: str,
ablation_path: str,
random_seed_path: str,
workers: int,
output_base: str,
) -> None:
# Load experiment conditions
mention_encodings = load_json(mention_encodings_path)
ablation_sizes = load_json(ablation_path)
assert isinstance(ablation_sizes, list)
random_seeds = load_json(random_seed_path)
# Create configurations
configs = []
for random_seed in random_seeds:
# Hack to allow for no shuffle: replace random seed of -1 with None
random_seed = None if random_seed == -1 else random_seed
# Reverse ablation sizes so longest jobs start first
for ablation_size in reversed(ablation_sizes):
for mention_encoding in mention_encodings:
# Name
config_name = "_".join(
(
name_prefix,
f"rand-{random_seed}",
f"ablation-{ablation_size}",
mention_encoding,
)
)
# Output path
output_dir = os.path.join(output_base, config_name)
config = ExperimentConfiguration(
config_name,
train_path,
test_path,
training_params_path,
feature_params_path,
mention_encoding,
int(ablation_size),
random_seed,
output_dir,
)
configs.append(config)
print(f"Generated {len(configs)} configurations")
# To conserve memory, only allow one task per child
pool = multiprocessing.Pool(workers, maxtasksperchild=1)
# Chunksize of 1 since each task is long-lived
results = pool.imap_unordered(run_configuration, configs, chunksize=1)
pool.close()
output_dir = Path(output_base)
output_dir.mkdir(parents=True, exist_ok=True)
csv_path = output_dir / "scores.csv"
# Line buffered output so results appear quickly
with open(csv_path, "w", encoding="utf8", buffering=1) as score_csv:
writer = csv.writer(score_csv)
writer.writerow(
[
"Name",
"Features",
"Training",
"Algorithm",
"Documents",
"Random",
"Encoding",
"P",
"R",
"F1",
]
)
for config, score in results:
print("*" * 40)
print(config.name)
score.print()
print()
writer.writerow(
[
config.name,
os.path.basename(config.feature_params_path),
os.path.basename(config.training_params_path),
config.ablation_size,
config.random_seed if config.random_seed is not None else -1,
config.mention_encoding_name,
score.precision,
score.recall,
score.fscore,
]
)
pool.join()
def run_configuration(
config: ExperimentConfiguration,
) -> Tuple[ExperimentConfiguration, ScoringResult]:
out = Path(config.output_dir)
out.mkdir(parents=True, exist_ok=True)
model_path = str(out / "model.crfsuite") # crfsuite demands a string
pred_path = out / "test.nerpydoc"
with (out / "train.log").open("w", encoding="utf8", buffering=1) as log_file, (
out / "score.pkl"
).open("wb") as score_file:
score = train_test(
config.train_path,
model_path,
config.test_path,
config.training_params_path,
config.feature_params_path,
config.mention_encoding_name,
pred_path,
truncate=config.ablation_size,
log_file=log_file,
random_seed=config.random_seed,
)
pickle.dump(score, score_file, protocol=pickle.HIGHEST_PROTOCOL)
return (config, score)
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("prefix", help="prefix for configuration names")
parser.add_argument("train_path", help="path to train pickle file")
parser.add_argument("test_path", help="path to test pickle file")
parser.add_argument("train_params", help="path to training parameters")
parser.add_argument("feature_params", help="path to feature parameters")
parser.add_argument("mention_encoding_path", help="path to list of mention encodings")
parser.add_argument("ablation_path", help="path to list of ablation points")
parser.add_argument("random_seed_path", help="path to list of random seeds")
parser.add_argument("output_base", help="base output directory")
parser.add_argument(
"-n", "--num_workers", type=int, default=1, help="number of workers"
)
args = parser.parse_args()
run_expts(
args.prefix,
args.train_path,
args.test_path,
args.train_params,
args.feature_params,
args.mention_encoding_path,
args.ablation_path,
args.random_seed_path,
args.num_workers,
args.output_base,
)
if __name__ == "__main__":
main() | scripts/run_full_expts.py | import argparse
import csv
import multiprocessing
import os
import pickle
from pathlib import Path
from typing import Optional, Tuple
from attr import attrs
from nerpy import load_json
from nerpy.scoring import ScoringResult
from scripts.train_test import train_test
@attrs(auto_attribs=True)
class ExperimentConfiguration:
name: str
train_path: str
test_path: str
training_params_path: str
feature_params_path: str
mention_encoding_name: str
ablation_size: int
random_seed: Optional[int]
output_dir: str
def run_expts(
name_prefix: str,
train_path: str,
test_path: str,
training_params_path: str,
feature_params_path: str,
mention_encodings_path: str,
ablation_path: str,
random_seed_path: str,
workers: int,
output_base: str,
) -> None:
# Load experiment conditions
mention_encodings = load_json(mention_encodings_path)
ablation_sizes = load_json(ablation_path)
assert isinstance(ablation_sizes, list)
random_seeds = load_json(random_seed_path)
# Create configurations
configs = []
for random_seed in random_seeds:
# Hack to allow for no shuffle: replace random seed of -1 with None
random_seed = None if random_seed == -1 else random_seed
# Reverse ablation sizes so longest jobs start first
for ablation_size in reversed(ablation_sizes):
for mention_encoding in mention_encodings:
# Name
config_name = "_".join(
(
name_prefix,
f"rand-{random_seed}",
f"ablation-{ablation_size}",
mention_encoding,
)
)
# Output path
output_dir = os.path.join(output_base, config_name)
config = ExperimentConfiguration(
config_name,
train_path,
test_path,
training_params_path,
feature_params_path,
mention_encoding,
int(ablation_size),
random_seed,
output_dir,
)
configs.append(config)
print(f"Generated {len(configs)} configurations")
# To conserve memory, only allow one task per child
pool = multiprocessing.Pool(workers, maxtasksperchild=1)
# Chunksize of 1 since each task is long-lived
results = pool.imap_unordered(run_configuration, configs, chunksize=1)
pool.close()
output_dir = Path(output_base)
output_dir.mkdir(parents=True, exist_ok=True)
csv_path = output_dir / "scores.csv"
# Line buffered output so results appear quickly
with open(csv_path, "w", encoding="utf8", buffering=1) as score_csv:
writer = csv.writer(score_csv)
writer.writerow(
[
"Name",
"Features",
"Training",
"Algorithm",
"Documents",
"Random",
"Encoding",
"P",
"R",
"F1",
]
)
for config, score in results:
print("*" * 40)
print(config.name)
score.print()
print()
writer.writerow(
[
config.name,
os.path.basename(config.feature_params_path),
os.path.basename(config.training_params_path),
config.ablation_size,
config.random_seed if config.random_seed is not None else -1,
config.mention_encoding_name,
score.precision,
score.recall,
score.fscore,
]
)
pool.join()
def run_configuration(
config: ExperimentConfiguration,
) -> Tuple[ExperimentConfiguration, ScoringResult]:
out = Path(config.output_dir)
out.mkdir(parents=True, exist_ok=True)
model_path = str(out / "model.crfsuite") # crfsuite demands a string
pred_path = out / "test.nerpydoc"
with (out / "train.log").open("w", encoding="utf8", buffering=1) as log_file, (
out / "score.pkl"
).open("wb") as score_file:
score = train_test(
config.train_path,
model_path,
config.test_path,
config.training_params_path,
config.feature_params_path,
config.mention_encoding_name,
pred_path,
truncate=config.ablation_size,
log_file=log_file,
random_seed=config.random_seed,
)
pickle.dump(score, score_file, protocol=pickle.HIGHEST_PROTOCOL)
return (config, score)
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("prefix", help="prefix for configuration names")
parser.add_argument("train_path", help="path to train pickle file")
parser.add_argument("test_path", help="path to test pickle file")
parser.add_argument("train_params", help="path to training parameters")
parser.add_argument("feature_params", help="path to feature parameters")
parser.add_argument("mention_encoding_path", help="path to list of mention encodings")
parser.add_argument("ablation_path", help="path to list of ablation points")
parser.add_argument("random_seed_path", help="path to list of random seeds")
parser.add_argument("output_base", help="base output directory")
parser.add_argument(
"-n", "--num_workers", type=int, default=1, help="number of workers"
)
args = parser.parse_args()
run_expts(
args.prefix,
args.train_path,
args.test_path,
args.train_params,
args.feature_params,
args.mention_encoding_path,
args.ablation_path,
args.random_seed_path,
args.num_workers,
args.output_base,
)
if __name__ == "__main__":
main() | 0.743261 | 0.20836 |
import json
import logging
from datetime import datetime
from typing import List, Optional
import requests
from bs4 import BeautifulSoup
from feature.base import Feature
from utility.constant import DATE_FORMAT
from utility.system import get_res_path
from utility.html_builder import html_img, html_div, html_a, html_tag
HEADER = {
"Host": "www.zhihu.com",
"Referer": "https://www.zhihu.com/",
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36"
" (KHTML, like Gecko) Chrome/56.0.2924.87",
}
class ZhihuStory(Feature):
def __init__(
self,
file_name: str,
start_date: str,
avatar_style: str = "border-radius: 50%; width: 64px;",
div_style: str = "",
title: Optional[str] = "知乎收录",
):
super().__init__(div_style, title)
self.file_path = get_res_path(file_name)
self.start_date = datetime.strptime(start_date, DATE_FORMAT)
self.avatar_style = avatar_style
self.current_date_time = None # lazy initialization by Recipient class
def generate_content(self) -> str:
index = max(0, (self.current_date_time - self.start_date).days)
logging.info(f"Zhihu Index: {index}")
answer_url = open(self.file_path, "r").readlines()[index]
logging.info(f"Zhihu Answer URL: {answer_url}")
return self._request_answer(answer_url)
def _request_answer(self, answer_url: str) -> str:
answer_id = answer_url[answer_url.rfind("/") + 1 :]
api_url = f"https://www.zhihu.com/api/v4/answers/{answer_id}?include=content"
response = requests.get(api_url, headers=HEADER).json()
content = response["content"]
content = content.replace("<noscript>", "").replace("</noscript>", "")
soup = BeautifulSoup(content, "html.parser")
for tag in soup.find_all(lambda t: "data-actualsrc" in t.attrs):
tag.extract()
for tag in soup.find_all("p", {"class": "ztext-empty-paragraph"}):
tag.extract()
for tag in soup.find_all("img"):
tag["style"] = "width:95%;"
if "data-original" in tag.attrs:
del tag["data-original"]
if "data-rawheight" in tag.attrs:
del tag["data-rawheight"]
if "data-rawwidth" in tag.attrs:
del tag["data-rawwidth"]
if "class" in tag.attrs:
del tag["class"]
if "width" in tag.attrs:
del tag["width"]
for fig in soup.find_all("figure"):
fig.attrs.clear()
str_soup = str(soup)
return f"""{html_tag(name="h3", paired=True, inner_html=response["question"]["title"])}
{html_img(url=response["author"]["avatar_url"], style=self.avatar_style)}
作者: {response["author"]["name"]}
<br>
{html_div(inner_html=str_soup)}
<br>
{html_a(text="知乎原文", url=answer_url)}
"""
# ON HOLD, NOT IN USE
@staticmethod
def _request_answer_by_question(qid, total=10, page_num=0, limit=10) -> List:
answers = []
count = 0
while True:
url = (
"https://www.zhihu.com/api/v4/questions/"
+ str(qid)
+ "/answers?include=data%5B%2A%5D.is_normal%2Cadmin_closedsfd_comment%2Creward_info"
"%2Cis_collapsed%2Cannotation_action%2Cannotation_detail%2Ccollapse_reason"
"%2Cis_sticky%2Ccollapsed_by%2Csuggest_edit%2Ccomment_count%2Ccan_comment"
"%2Ccontent%2Ceditable_content%2Cvoteup_count%2Creshipment_settings"
"%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info"
"%2Crelevant_info%2Cquestion%2Cexcerpt%2Crelationship.is_authorized"
"%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_labeled%3Bdata%5B%2A%5D"
".mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cbadge%5B%2A"
"%5D.topics&limit="
+ str(limit)
+ "&offset="
+ str(page_num * limit)
+ "&platform=desktop&sort_by=default"
)
req = requests.get(url, headers=HEADER)
res_json = json.loads(req.text)
data = res_json["data"]
page_num += 1
for item in data:
count += 1
if count > total:
return answers
else:
title = item["question"]["title"]
author = item["author"]["name"]
content = (
item["content"]
.replace("<noscript>", "")
.replace("</noscript>", "")
.replace('<img src="data:img/svg+xml', '<meta src="')
)
# further use title, author, content here
# ...
if res_json["paging"]["is_end"] or count >= res_json["paging"]["totals"]:
break
return answers | feature/zhihu_story.py | import json
import logging
from datetime import datetime
from typing import List, Optional
import requests
from bs4 import BeautifulSoup
from feature.base import Feature
from utility.constant import DATE_FORMAT
from utility.system import get_res_path
from utility.html_builder import html_img, html_div, html_a, html_tag
HEADER = {
"Host": "www.zhihu.com",
"Referer": "https://www.zhihu.com/",
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36"
" (KHTML, like Gecko) Chrome/56.0.2924.87",
}
class ZhihuStory(Feature):
def __init__(
self,
file_name: str,
start_date: str,
avatar_style: str = "border-radius: 50%; width: 64px;",
div_style: str = "",
title: Optional[str] = "知乎收录",
):
super().__init__(div_style, title)
self.file_path = get_res_path(file_name)
self.start_date = datetime.strptime(start_date, DATE_FORMAT)
self.avatar_style = avatar_style
self.current_date_time = None # lazy initialization by Recipient class
def generate_content(self) -> str:
index = max(0, (self.current_date_time - self.start_date).days)
logging.info(f"Zhihu Index: {index}")
answer_url = open(self.file_path, "r").readlines()[index]
logging.info(f"Zhihu Answer URL: {answer_url}")
return self._request_answer(answer_url)
def _request_answer(self, answer_url: str) -> str:
answer_id = answer_url[answer_url.rfind("/") + 1 :]
api_url = f"https://www.zhihu.com/api/v4/answers/{answer_id}?include=content"
response = requests.get(api_url, headers=HEADER).json()
content = response["content"]
content = content.replace("<noscript>", "").replace("</noscript>", "")
soup = BeautifulSoup(content, "html.parser")
for tag in soup.find_all(lambda t: "data-actualsrc" in t.attrs):
tag.extract()
for tag in soup.find_all("p", {"class": "ztext-empty-paragraph"}):
tag.extract()
for tag in soup.find_all("img"):
tag["style"] = "width:95%;"
if "data-original" in tag.attrs:
del tag["data-original"]
if "data-rawheight" in tag.attrs:
del tag["data-rawheight"]
if "data-rawwidth" in tag.attrs:
del tag["data-rawwidth"]
if "class" in tag.attrs:
del tag["class"]
if "width" in tag.attrs:
del tag["width"]
for fig in soup.find_all("figure"):
fig.attrs.clear()
str_soup = str(soup)
return f"""{html_tag(name="h3", paired=True, inner_html=response["question"]["title"])}
{html_img(url=response["author"]["avatar_url"], style=self.avatar_style)}
作者: {response["author"]["name"]}
<br>
{html_div(inner_html=str_soup)}
<br>
{html_a(text="知乎原文", url=answer_url)}
"""
# ON HOLD, NOT IN USE
@staticmethod
def _request_answer_by_question(qid, total=10, page_num=0, limit=10) -> List:
answers = []
count = 0
while True:
url = (
"https://www.zhihu.com/api/v4/questions/"
+ str(qid)
+ "/answers?include=data%5B%2A%5D.is_normal%2Cadmin_closedsfd_comment%2Creward_info"
"%2Cis_collapsed%2Cannotation_action%2Cannotation_detail%2Ccollapse_reason"
"%2Cis_sticky%2Ccollapsed_by%2Csuggest_edit%2Ccomment_count%2Ccan_comment"
"%2Ccontent%2Ceditable_content%2Cvoteup_count%2Creshipment_settings"
"%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info"
"%2Crelevant_info%2Cquestion%2Cexcerpt%2Crelationship.is_authorized"
"%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_labeled%3Bdata%5B%2A%5D"
".mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cbadge%5B%2A"
"%5D.topics&limit="
+ str(limit)
+ "&offset="
+ str(page_num * limit)
+ "&platform=desktop&sort_by=default"
)
req = requests.get(url, headers=HEADER)
res_json = json.loads(req.text)
data = res_json["data"]
page_num += 1
for item in data:
count += 1
if count > total:
return answers
else:
title = item["question"]["title"]
author = item["author"]["name"]
content = (
item["content"]
.replace("<noscript>", "")
.replace("</noscript>", "")
.replace('<img src="data:img/svg+xml', '<meta src="')
)
# further use title, author, content here
# ...
if res_json["paging"]["is_end"] or count >= res_json["paging"]["totals"]:
break
return answers | 0.549157 | 0.08374 |
from github_automation.common.constants import OR
def get_first_column_items(client, config):
response = client.get_first_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
is_org_project=config.is_org_project)
project = get_project_from_response(response, config.is_org_project)
project_cards = get_project_cards(project)
cards_page_info = project_cards.get('pageInfo', {})
while cards_page_info.get('hasNextPage'):
new_response = client.get_first_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
start_cards_cursor=cards_page_info['endCursor'],
is_org_project=config.is_org_project)
project = get_project_from_response(new_response, config.is_org_project)
new_cards = get_project_cards(project)
project_cards['edges'].extend(new_cards['edges'])
cards_page_info = new_cards['pageInfo']
return response
def get_column_items_with_prev_column(client, config, prev_cursor):
response = client.get_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
prev_column_id=prev_cursor,
is_org_project=config.is_org_project)
project = get_project_from_response(response, config.is_org_project)
project_cards = get_project_cards(project)
cards_page_info = project_cards.get('pageInfo', {})
while cards_page_info.get('hasNextPage'):
new_response = client.get_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
prev_column_id=prev_cursor,
start_cards_cursor=cards_page_info['endCursor'],
is_org_project=config.is_org_project)
project = get_project_from_response(new_response, config.is_org_project)
new_cards = get_project_cards(project)
project_cards['edges'].extend(new_cards['edges'])
cards_page_info = new_cards['pageInfo']
return response
def is_matching_project_item(item_labels, must_have_labels, cant_have_labels, filter_labels):
if not any([(value in item_labels) for value in filter_labels]):
return False
for label in must_have_labels:
if OR in label:
new_labels = label.split(OR)
if all(new_label not in item_labels for new_label in new_labels):
return False
elif label not in item_labels:
return False
for label in cant_have_labels:
if label in item_labels:
return False
return True
def get_labels(label_edges):
label_names = []
for edge in label_edges:
node_data = edge.get('node')
if node_data:
label_names.append(node_data['name'])
return label_names
def get_project_from_response(response, is_org_project):
root = response['organization'] if is_org_project else response['repository']
return root.get('project', {})
def get_project_cards(project):
if project:
if 'columns' in project:
columns = project['columns']
if 'nodes' in columns and isinstance(columns['nodes'], list):
nodes = columns['nodes']
if len(nodes) > 0 and 'cards' in nodes[0]:
return nodes[0]['cards']
return {} | src/github_automation/common/utils.py | from github_automation.common.constants import OR
def get_first_column_items(client, config):
response = client.get_first_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
is_org_project=config.is_org_project)
project = get_project_from_response(response, config.is_org_project)
project_cards = get_project_cards(project)
cards_page_info = project_cards.get('pageInfo', {})
while cards_page_info.get('hasNextPage'):
new_response = client.get_first_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
start_cards_cursor=cards_page_info['endCursor'],
is_org_project=config.is_org_project)
project = get_project_from_response(new_response, config.is_org_project)
new_cards = get_project_cards(project)
project_cards['edges'].extend(new_cards['edges'])
cards_page_info = new_cards['pageInfo']
return response
def get_column_items_with_prev_column(client, config, prev_cursor):
response = client.get_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
prev_column_id=prev_cursor,
is_org_project=config.is_org_project)
project = get_project_from_response(response, config.is_org_project)
project_cards = get_project_cards(project)
cards_page_info = project_cards.get('pageInfo', {})
while cards_page_info.get('hasNextPage'):
new_response = client.get_column_items(owner=config.project_owner,
name=config.repository_name,
project_number=config.project_number,
prev_column_id=prev_cursor,
start_cards_cursor=cards_page_info['endCursor'],
is_org_project=config.is_org_project)
project = get_project_from_response(new_response, config.is_org_project)
new_cards = get_project_cards(project)
project_cards['edges'].extend(new_cards['edges'])
cards_page_info = new_cards['pageInfo']
return response
def is_matching_project_item(item_labels, must_have_labels, cant_have_labels, filter_labels):
if not any([(value in item_labels) for value in filter_labels]):
return False
for label in must_have_labels:
if OR in label:
new_labels = label.split(OR)
if all(new_label not in item_labels for new_label in new_labels):
return False
elif label not in item_labels:
return False
for label in cant_have_labels:
if label in item_labels:
return False
return True
def get_labels(label_edges):
label_names = []
for edge in label_edges:
node_data = edge.get('node')
if node_data:
label_names.append(node_data['name'])
return label_names
def get_project_from_response(response, is_org_project):
root = response['organization'] if is_org_project else response['repository']
return root.get('project', {})
def get_project_cards(project):
if project:
if 'columns' in project:
columns = project['columns']
if 'nodes' in columns and isinstance(columns['nodes'], list):
nodes = columns['nodes']
if len(nodes) > 0 and 'cards' in nodes[0]:
return nodes[0]['cards']
return {} | 0.368974 | 0.085442 |
import neovim
from html.parser import HTMLParser
import urllib.request
import re
import subprocess
import json
@neovim.plugin
class Main(object):
def __init__(self, vim):
self.vim = vim
self.opts = "{'relative': 'editor', 'width': 30, 'height': 30, 'col': &columns, 'row': 0, 'style': 'minimal'}"
self.running = False
self.correct_num = 0
self.sample_num = 0
def parse_html(self, body):
repatter = re.compile(r'<h3>入力例.*?</pre>', flags=re.DOTALL)
in_samples = repatter.findall(body)
repatter = re.compile(r'<h3>出力例.*?</pre>', flags=re.DOTALL)
out_samples = repatter.findall(body)
repatter = re.compile(r'^.*<pre>(.*)</pre>.*$', flags=re.DOTALL)
in_samples = list(map(lambda string: repatter.sub('\\1', string), in_samples))
out_samples = list(map(lambda string: repatter.sub('\\1', string), out_samples))
samples = [(i, o) for i, o in zip(in_samples, out_samples)]
return samples
def get_sample_data(self, contest_name, task_name):
url = 'https://atcoder.jp/contests/{0}/tasks/{0}_{1}'.format(contest_name, task_name)
req = urllib.request.Request(url)
with urllib.request.urlopen(req) as res:
body = res.read().decode('utf-8')
samples = self.parse_html(body)
return samples
def update_correct(self):
buf_str = 'Correct: {} / {}'.format(self.correct_num, self.sample_num)
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, 0, 1, v:true, ["{}"])'.format(buf_str))
if self.correct_num == self.sample_num:
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "PmenuSel", 0, 0, -1)')
else:
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "IncSearch", 0, 0, -1)')
def check_correct(self, ans1, ans2):
ans1 = ans1.replace('\r', '').replace('\n', '').split()
ans2 = ans2.replace('\r', '').replace('\n', '').split()
if ans1 == ans2:
self.correct_num += 1
self.update_correct()
def insert_sample_string_to_buffer(self, string):
line_num = self.vim.eval('nvim_buf_line_count(g:AtcoderTester_buf)')
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, -1, -1, v:true, {})'.format(json.dumps(string.split('\n'))))
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "LineNr", {}, 0, -1)'.format(line_num))
def test_code(self, samples):
ans = []
for sample in samples:
command = 'echo "{}" | ./a.out'.format(sample[0])
process = subprocess.Popen(
command,
stderr=subprocess.PIPE,
stdout=subprocess.PIPE,
shell=True
)
res = process.communicate()[0].decode('utf-8')
self.check_correct(res, sample[1])
buf_strs = [''] * 3
buf_strs[0] = 'IN:\n{}'.format(sample[0]).replace('\r', '')
buf_strs[1] = 'OUT:\n{}'.format(res).replace('\r', '')
buf_strs[2] = 'ANS:\n{}\n'.format(sample[1]).replace('\r', '')
for string in buf_strs:
self.insert_sample_string_to_buffer(string)
@neovim.function('AtcoderTester_run', eval='expand("%")')
def do(self, args, filename):
try:
if self.running:
self.vim.command('echo "already running do()"')
return
self.running = True
win_id = self.vim.eval('bufwinid(g:AtcoderTester_buf)')
contest_name, task_name = filename.split('/')[-1].split('.')[0].split('-')
samples = self.get_sample_data(contest_name, task_name)
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, 0, -1, v:true, ["", ""])')
self.sample_num = len(samples)
self.correct_num = 0
self.update_correct()
if win_id == -1:
self.vim.command('let g:AtcoderTester_win = nvim_open_win(g:AtcoderTester_buf, v:true, {})'.format(self.opts))
else:
self.vim.command('call win_gotoid(g:AtcoderTester_win)')
self.test_code(samples)
self.running = False
except:
win_id = self.vim.eval('bufwinid(g:AtcoderTester_buf)')
if win_id != -1:
self.vim.command('call nvim_win_close(g:AtcoderTester_win, v:true)')
self.vim.command('echo "do() failed"')
self.running = False | rplugin/python3/atcoder-tester.py | import neovim
from html.parser import HTMLParser
import urllib.request
import re
import subprocess
import json
@neovim.plugin
class Main(object):
def __init__(self, vim):
self.vim = vim
self.opts = "{'relative': 'editor', 'width': 30, 'height': 30, 'col': &columns, 'row': 0, 'style': 'minimal'}"
self.running = False
self.correct_num = 0
self.sample_num = 0
def parse_html(self, body):
repatter = re.compile(r'<h3>入力例.*?</pre>', flags=re.DOTALL)
in_samples = repatter.findall(body)
repatter = re.compile(r'<h3>出力例.*?</pre>', flags=re.DOTALL)
out_samples = repatter.findall(body)
repatter = re.compile(r'^.*<pre>(.*)</pre>.*$', flags=re.DOTALL)
in_samples = list(map(lambda string: repatter.sub('\\1', string), in_samples))
out_samples = list(map(lambda string: repatter.sub('\\1', string), out_samples))
samples = [(i, o) for i, o in zip(in_samples, out_samples)]
return samples
def get_sample_data(self, contest_name, task_name):
url = 'https://atcoder.jp/contests/{0}/tasks/{0}_{1}'.format(contest_name, task_name)
req = urllib.request.Request(url)
with urllib.request.urlopen(req) as res:
body = res.read().decode('utf-8')
samples = self.parse_html(body)
return samples
def update_correct(self):
buf_str = 'Correct: {} / {}'.format(self.correct_num, self.sample_num)
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, 0, 1, v:true, ["{}"])'.format(buf_str))
if self.correct_num == self.sample_num:
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "PmenuSel", 0, 0, -1)')
else:
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "IncSearch", 0, 0, -1)')
def check_correct(self, ans1, ans2):
ans1 = ans1.replace('\r', '').replace('\n', '').split()
ans2 = ans2.replace('\r', '').replace('\n', '').split()
if ans1 == ans2:
self.correct_num += 1
self.update_correct()
def insert_sample_string_to_buffer(self, string):
line_num = self.vim.eval('nvim_buf_line_count(g:AtcoderTester_buf)')
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, -1, -1, v:true, {})'.format(json.dumps(string.split('\n'))))
self.vim.command('call nvim_buf_add_highlight(g:AtcoderTester_buf, 0, "LineNr", {}, 0, -1)'.format(line_num))
def test_code(self, samples):
ans = []
for sample in samples:
command = 'echo "{}" | ./a.out'.format(sample[0])
process = subprocess.Popen(
command,
stderr=subprocess.PIPE,
stdout=subprocess.PIPE,
shell=True
)
res = process.communicate()[0].decode('utf-8')
self.check_correct(res, sample[1])
buf_strs = [''] * 3
buf_strs[0] = 'IN:\n{}'.format(sample[0]).replace('\r', '')
buf_strs[1] = 'OUT:\n{}'.format(res).replace('\r', '')
buf_strs[2] = 'ANS:\n{}\n'.format(sample[1]).replace('\r', '')
for string in buf_strs:
self.insert_sample_string_to_buffer(string)
@neovim.function('AtcoderTester_run', eval='expand("%")')
def do(self, args, filename):
try:
if self.running:
self.vim.command('echo "already running do()"')
return
self.running = True
win_id = self.vim.eval('bufwinid(g:AtcoderTester_buf)')
contest_name, task_name = filename.split('/')[-1].split('.')[0].split('-')
samples = self.get_sample_data(contest_name, task_name)
self.vim.command('call nvim_buf_set_lines(g:AtcoderTester_buf, 0, -1, v:true, ["", ""])')
self.sample_num = len(samples)
self.correct_num = 0
self.update_correct()
if win_id == -1:
self.vim.command('let g:AtcoderTester_win = nvim_open_win(g:AtcoderTester_buf, v:true, {})'.format(self.opts))
else:
self.vim.command('call win_gotoid(g:AtcoderTester_win)')
self.test_code(samples)
self.running = False
except:
win_id = self.vim.eval('bufwinid(g:AtcoderTester_buf)')
if win_id != -1:
self.vim.command('call nvim_win_close(g:AtcoderTester_win, v:true)')
self.vim.command('echo "do() failed"')
self.running = False | 0.124519 | 0.115536 |
from .utils import ConfiguratorTestCase
from unittest.mock import MagicMock
from ignition.boot.config import BootstrapApplicationConfiguration, BootProperties
from ignition.boot.configurators.messaging import MessagingConfigurator
from ignition.service.messaging import MessagingProperties, DeliveryCapability, PostalCapability, KafkaDeliveryService, PostalService, KafkaInboxService
from ignition.service.framework import ServiceRegistration
class TestMessagingConfigurator(ConfiguratorTestCase):
def __bootstrap_config(self):
configuration = BootstrapApplicationConfiguration()
boot_config = BootProperties()
configuration.property_groups.add_property_group(boot_config)
messaging_conf = MessagingProperties()
configuration.property_groups.add_property_group(messaging_conf)
return configuration
def test_configure_nothing_when_disabled(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = False
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = False
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = False
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.mock_service_register.add_service.assert_not_called()
def test_configure_postal(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = True
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(PostalService, delivery_service=DeliveryCapability))
def test_configure_postal_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = True
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Postal Service capability but bootstrap.messaging.postal_enabled has not been disabled')
def test_configure_delivery(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(KafkaDeliveryService, messaging_properties=MessagingProperties))
def test_configure_delivery_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Delivery Service capability but bootstrap.messaging.delivery_enabled has not been disabled')
def test_configure_delivery_fails_when_messaging_connection_address_not_set(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = None
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'messaging.connection_address must be set when bootstrap.messaging.delivery_enabled is True')
def test_configure_inbox(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(KafkaInboxService, messaging_properties=MessagingProperties))
def test_configure_inbox_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Inbox Service capability but bootstrap.messaging.inbox_enabled has not been disabled')
def test_configure_inbox_fails_when_messaging_connection_address_not_set(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = None
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'messaging.connection_address must be set when bootstrap.messaging.inbox_enabled is True') | tests/unit/boot/configurators/test_messaging.py | from .utils import ConfiguratorTestCase
from unittest.mock import MagicMock
from ignition.boot.config import BootstrapApplicationConfiguration, BootProperties
from ignition.boot.configurators.messaging import MessagingConfigurator
from ignition.service.messaging import MessagingProperties, DeliveryCapability, PostalCapability, KafkaDeliveryService, PostalService, KafkaInboxService
from ignition.service.framework import ServiceRegistration
class TestMessagingConfigurator(ConfiguratorTestCase):
def __bootstrap_config(self):
configuration = BootstrapApplicationConfiguration()
boot_config = BootProperties()
configuration.property_groups.add_property_group(boot_config)
messaging_conf = MessagingProperties()
configuration.property_groups.add_property_group(messaging_conf)
return configuration
def test_configure_nothing_when_disabled(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = False
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = False
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = False
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.mock_service_register.add_service.assert_not_called()
def test_configure_postal(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = True
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(PostalService, delivery_service=DeliveryCapability))
def test_configure_postal_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.postal_enabled = True
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Postal Service capability but bootstrap.messaging.postal_enabled has not been disabled')
def test_configure_delivery(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(KafkaDeliveryService, messaging_properties=MessagingProperties))
def test_configure_delivery_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Delivery Service capability but bootstrap.messaging.delivery_enabled has not been disabled')
def test_configure_delivery_fails_when_messaging_connection_address_not_set(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.delivery_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = None
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'messaging.connection_address must be set when bootstrap.messaging.delivery_enabled is True')
def test_configure_inbox(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = None
MessagingConfigurator().configure(configuration, self.mock_service_register)
registered_service = self.assert_single_service_registered()
self.assert_service_registration_equal(registered_service, ServiceRegistration(KafkaInboxService, messaging_properties=MessagingProperties))
def test_configure_inbox_fails_when_already_registered(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = 'testaddr'
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'An existing service has been registered to serve the Inbox Service capability but bootstrap.messaging.inbox_enabled has not been disabled')
def test_configure_inbox_fails_when_messaging_connection_address_not_set(self):
configuration = self.__bootstrap_config()
configuration.property_groups.get_property_group(BootProperties).messaging.inbox_enabled = True
configuration.property_groups.get_property_group(MessagingProperties).connection_address = None
self.mock_service_register.get_service_offering_capability.return_value = MagicMock()
with self.assertRaises(ValueError) as context:
MessagingConfigurator().configure(configuration, self.mock_service_register)
self.assertEqual(str(context.exception), 'messaging.connection_address must be set when bootstrap.messaging.inbox_enabled is True') | 0.729134 | 0.166286 |
from flask import Flask, redirect, url_for, request, render_template
import requests
import json
from collections import namedtuple
import ipaddress
from ipaddress import ip_network, IPv4Network
import time
app = Flask(__name__)
class Controller:
def __init__(self):
from longlists import class_subs,subnet_bits,subnet_len,max_subnets,hosts_persub
self.subnet_bits = subnet_bits
self.tools_links = ['/calc']
self.class_subs = class_subs
self.subnet_len = subnet_len
self.max_subnets = max_subnets
self.hosts_persub = hosts_persub
self.max_subnets = max_subnets
def ProcessIp(self,ip,subnet):
errors = ['IP address format error']
try:
ipnet = ipaddress.ip_network(ip+'/'+subnet, strict=False)
except ValueError as e:
wild_card_mask = errors[0]
subnetid = errors[0]
broadcast_address = errors[0]
dottedhex = errors[0]
return wild_card_mask,subnetid,broadcast_address,dottedhex
else:
pass
"""
Get the wildcardmask
"""
wild_card_mask= ipnet.hostmask
"""
Get the subnet ID
"""
subnetid = ipnet.network_address
"""
Get the broadcast address
"""
broadcast_address = ipnet.broadcast_address
"""
Get the Hex Format
of the IP address
"""
prefix_split = str(ip).split('.')
fullhex = "".join([hex(int(value))[2:].zfill(2) for value in prefix_split])
dottedhex = (fullhex[0:2])+'.'+(fullhex[2:4])+'.'+(fullhex[4:6])+'.'+(fullhex[6:8])
return wild_card_mask,subnetid,broadcast_address,dottedhex
app.add_url_rule('/', 'index', lambda: controller.index())
def index(self):
return render_template('index.html',tools_links=self.tools_links)
app.add_url_rule('/calc', 'calc', lambda: controller.subnetcalc(),methods=['POST','GET'])
def subnetcalc(self):
default_hex = '0.0.0.0'
dottedhex = 'c0.a8.00.01'
wild_card_mask = '0.0.0.255'
radio_select = 'radioButton3'
default_prefix = '192.168.1.1'
subnetin = '255.255.255.0'##used
subnet_back = self.class_subs[16:]##used
bits_back = self.subnet_bits[:7]##used
mask_back = self.subnet_len[16:]##used
subnetid = '192.168.1.0'#used
broadcast_address = '192.168.1.255'#used
subitsin = '0'#used
maskbitsin = '24'#used
max_subs = self.max_subnets[:7]
max_hostsin ='254'#used
max_subsin = '1'#used
hosts_persub = self.hosts_persub[15:]
rad_select=''
first_oct = '192 - 223'
if request.method == "POST":
time.sleep(1)
rad_select = request.form['radioButton']#The passed value ip class radio selection
if rad_select =='1':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton1'
subnet_back = self.class_subs
bits_back = self.subnet_bits
mask_back = self.subnet_len
max_subs = self.max_subnets
hosts_persub = self.hosts_persub
first_oct = '1 - 126'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
if rad_select =='2':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton2'
subnet_back = self.class_subs[8:]
bits_back = self.subnet_bits[:15]
mask_back = self.subnet_len[8:]
max_subs = self.max_subnets[:15]
hosts_persub = self.hosts_persub[7:]
first_oct = '128 - 191'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
if rad_select =='3':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton3'
subnet_back = self.class_subs[16:]
bits_back = self.subnet_bits[:7]
mask_back = self.subnet_len[16:]
max_subs = self.max_subnets[:7]
hosts_persub = self.hosts_persub[15:]
first_oct = '192 - 223'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
"""
1. class_subs - All possible Subnets
2. subnet_bits - All possible subnet bits
3. wild_card_mask - Pyhton processed wildcard mask
4. dottedhex - Pyhton processed Hex format of input IP address
5. default_prefix - The default prefix vlaue: see id="prefix" in .html
6. radio_select - current user radio button selection for ipv4 class
7. subnet_back - Sets the vlaues of the subnet select options: see id='subnetout' in .html
8. bits_back - Sets the vlaues of the Subnet Bits select options: see id="ipclassbits" in .html
9. subnet_len - Sets the values of the Mask Bits select options: see var class_mask* in .html and .js
10. mask_back - Sets the values for the Mask Bits select options: see id="maskbits" in .html
11. subnetid - Pyhton Processed subnet ID of prefix
12. broadcast_address -
13. subnetin -
14. subitsin -
15. max_subs -
16. hosts_persub -
17. max_hostsin -
18. max_subsin -
19. first_oct -
"""
return render_template('calc.html',class_subs=self.class_subs,
subnet_bits=self.subnet_bits,
wild_card_mask=wild_card_mask,
dottedhex=dottedhex,
default_prefix=default_prefix,
radio_select=radio_select,
subnet_back=subnet_back,
bits_back=bits_back,
subnet_len = self.subnet_len,
mask_back=mask_back,
subnetid=subnetid,
broadcast_address = broadcast_address,
subnetin = subnetin ,
subitsin = subitsin,
maskbitsin = maskbitsin,
max_subs = max_subs,
hosts_persub=hosts_persub,
max_hostsin = max_hostsin,
max_subsin=max_subsin,
first_oct=first_oct
)
app.add_url_rule('/test', 'test', lambda: controller.testpage(),methods=['POST','GET'])
def testpage(self):
if request.method == "POST":
todo = request.form.get("todo")
return render_template('testjs.html')
controller = Controller()
if __name__ == "__main__":
app.run(debug=True)
a = Controller() | main.py | from flask import Flask, redirect, url_for, request, render_template
import requests
import json
from collections import namedtuple
import ipaddress
from ipaddress import ip_network, IPv4Network
import time
app = Flask(__name__)
class Controller:
def __init__(self):
from longlists import class_subs,subnet_bits,subnet_len,max_subnets,hosts_persub
self.subnet_bits = subnet_bits
self.tools_links = ['/calc']
self.class_subs = class_subs
self.subnet_len = subnet_len
self.max_subnets = max_subnets
self.hosts_persub = hosts_persub
self.max_subnets = max_subnets
def ProcessIp(self,ip,subnet):
errors = ['IP address format error']
try:
ipnet = ipaddress.ip_network(ip+'/'+subnet, strict=False)
except ValueError as e:
wild_card_mask = errors[0]
subnetid = errors[0]
broadcast_address = errors[0]
dottedhex = errors[0]
return wild_card_mask,subnetid,broadcast_address,dottedhex
else:
pass
"""
Get the wildcardmask
"""
wild_card_mask= ipnet.hostmask
"""
Get the subnet ID
"""
subnetid = ipnet.network_address
"""
Get the broadcast address
"""
broadcast_address = ipnet.broadcast_address
"""
Get the Hex Format
of the IP address
"""
prefix_split = str(ip).split('.')
fullhex = "".join([hex(int(value))[2:].zfill(2) for value in prefix_split])
dottedhex = (fullhex[0:2])+'.'+(fullhex[2:4])+'.'+(fullhex[4:6])+'.'+(fullhex[6:8])
return wild_card_mask,subnetid,broadcast_address,dottedhex
app.add_url_rule('/', 'index', lambda: controller.index())
def index(self):
return render_template('index.html',tools_links=self.tools_links)
app.add_url_rule('/calc', 'calc', lambda: controller.subnetcalc(),methods=['POST','GET'])
def subnetcalc(self):
default_hex = '0.0.0.0'
dottedhex = 'c0.a8.00.01'
wild_card_mask = '0.0.0.255'
radio_select = 'radioButton3'
default_prefix = '192.168.1.1'
subnetin = '255.255.255.0'##used
subnet_back = self.class_subs[16:]##used
bits_back = self.subnet_bits[:7]##used
mask_back = self.subnet_len[16:]##used
subnetid = '192.168.1.0'#used
broadcast_address = '192.168.1.255'#used
subitsin = '0'#used
maskbitsin = '24'#used
max_subs = self.max_subnets[:7]
max_hostsin ='254'#used
max_subsin = '1'#used
hosts_persub = self.hosts_persub[15:]
rad_select=''
first_oct = '192 - 223'
if request.method == "POST":
time.sleep(1)
rad_select = request.form['radioButton']#The passed value ip class radio selection
if rad_select =='1':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton1'
subnet_back = self.class_subs
bits_back = self.subnet_bits
mask_back = self.subnet_len
max_subs = self.max_subnets
hosts_persub = self.hosts_persub
first_oct = '1 - 126'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
if rad_select =='2':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton2'
subnet_back = self.class_subs[8:]
bits_back = self.subnet_bits[:15]
mask_back = self.subnet_len[8:]
max_subs = self.max_subnets[:15]
hosts_persub = self.hosts_persub[7:]
first_oct = '128 - 191'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
if rad_select =='3':
prefixin = request.form.get("prefix")#The user input IP Address
subnetin = request.form.get("subnetout")
subitsin = request.form.get("ipclassbits")
maskbitsin = request.form.get("maskbits")
max_hostsin = request.form.get("hostspersub")
max_subsin = request.form.get("maxsubnets")
default_prefix = prefixin
radio_select = 'radioButton3'
subnet_back = self.class_subs[16:]
bits_back = self.subnet_bits[:7]
mask_back = self.subnet_len[16:]
max_subs = self.max_subnets[:7]
hosts_persub = self.hosts_persub[15:]
first_oct = '192 - 223'
wild_card_mask,subnetid,broadcast_address,dottedhex=self.ProcessIp(prefixin,subnetin)
"""
1. class_subs - All possible Subnets
2. subnet_bits - All possible subnet bits
3. wild_card_mask - Pyhton processed wildcard mask
4. dottedhex - Pyhton processed Hex format of input IP address
5. default_prefix - The default prefix vlaue: see id="prefix" in .html
6. radio_select - current user radio button selection for ipv4 class
7. subnet_back - Sets the vlaues of the subnet select options: see id='subnetout' in .html
8. bits_back - Sets the vlaues of the Subnet Bits select options: see id="ipclassbits" in .html
9. subnet_len - Sets the values of the Mask Bits select options: see var class_mask* in .html and .js
10. mask_back - Sets the values for the Mask Bits select options: see id="maskbits" in .html
11. subnetid - Pyhton Processed subnet ID of prefix
12. broadcast_address -
13. subnetin -
14. subitsin -
15. max_subs -
16. hosts_persub -
17. max_hostsin -
18. max_subsin -
19. first_oct -
"""
return render_template('calc.html',class_subs=self.class_subs,
subnet_bits=self.subnet_bits,
wild_card_mask=wild_card_mask,
dottedhex=dottedhex,
default_prefix=default_prefix,
radio_select=radio_select,
subnet_back=subnet_back,
bits_back=bits_back,
subnet_len = self.subnet_len,
mask_back=mask_back,
subnetid=subnetid,
broadcast_address = broadcast_address,
subnetin = subnetin ,
subitsin = subitsin,
maskbitsin = maskbitsin,
max_subs = max_subs,
hosts_persub=hosts_persub,
max_hostsin = max_hostsin,
max_subsin=max_subsin,
first_oct=first_oct
)
app.add_url_rule('/test', 'test', lambda: controller.testpage(),methods=['POST','GET'])
def testpage(self):
if request.method == "POST":
todo = request.form.get("todo")
return render_template('testjs.html')
controller = Controller()
if __name__ == "__main__":
app.run(debug=True)
a = Controller() | 0.329284 | 0.05921 |
import os
import torch
import torch.nn.functional as F
import numpy as np
from PIL import Image
from skimage import io
import cv2
def create_anchors_3d_stride(grid_size,
voxel_size=[0.16, 0.16, 0.5],
coordinates_offsets=[0, -19.84, -2.5],
dtype=np.float32):
"""
Args:
feature_size: list [D, H, W](zyx)
sizes: [N, 3] list of list or array, size of anchors, xyz
Returns:
anchors: [*feature_size, num_sizes, num_rots, 7] tensor.
"""
# almost 2x faster than v1
x_stride, y_stride, z_stride = voxel_size
x_offset, y_offset, z_offset = coordinates_offsets
x_centers = np.arange(grid_size[0], dtype=dtype)
y_centers = np.arange(grid_size[1], dtype=dtype)
z_centers = np.arange(grid_size[2], dtype=dtype)
z_centers = z_centers * z_stride + z_offset + 0.25
y_centers = y_centers * y_stride + y_offset + 0.08
x_centers = x_centers * x_stride + x_offset + 0.08
xx, yy, zz = np.meshgrid(x_centers, y_centers, z_centers)
sizes = np.stack((xx, yy , zz), axis=-1)
sizes = np.reshape(sizes, [-1,3])
return sizes
def lidar_to_camera(points, r_rect, velo2cam):
points_shape = list(points.shape[:-1]) # N
if points.shape[-1] == 3:
points = np.concatenate([points, np.ones(points_shape + [1])], axis=-1)
camera_points = points @ (r_rect @ velo2cam).T
return camera_points[..., :3]
def project_to_image(points_3d, proj_mat):
points_shape = list(points_3d.shape)
points_shape[-1] = 1
points_4 = np.concatenate([points_3d, np.zeros(points_shape)], axis=-1)
point_2d = points_4 @ proj_mat.T
point_2d_res = point_2d[..., :2] / point_2d[..., 2:3]
return point_2d_res
def _extend_matrix(mat):
mat = np.concatenate([mat, np.array([[0., 0., 0., 1.]])], axis=0)
return mat
def read_kitti_calib(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'P2:':
calib_P2 = np.array([float(x) for x in data[1:13]])
calib_P2 = calib_P2.reshape(3, 4)
return _extend_matrix(calib_P2)
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def read_kitti_R0_rect(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'R0_rect:':
R0_rect = np.array([float(x) for x in data[1:13]])
R0_rect = R0_rect.reshape(3,3)
rect_4x4 = np.zeros([4, 4], dtype=R0_rect.dtype)
rect_4x4[3, 3] = 1.
rect_4x4[:3, :3] = R0_rect
return rect_4x4
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def read_kitti_Tr_velo_to_cam(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'Tr_velo_to_cam:':
calib = np.array([float(x) for x in data[1:13]])
calib = calib.reshape(3, 4)
return _extend_matrix(calib)
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def oft(features, calib, r_rect, velo2cam): # grid x y z
H, W = features.shape
features = np.swapaxes(features, 0,1)
corners = create_anchors_3d_stride([296,248,6])
corners = lidar_to_camera(corners, r_rect, velo2cam)
points_v_to_image = project_to_image(corners, calib)
num_points = len(points_v_to_image)
pointing = np.zeros(num_points)
for num in range(num_points):
u = int(round(points_v_to_image[num][0]))
v = int(round(points_v_to_image[num][1]))
if -1 < u < W and -1< v < H:
pointing[num] = features[u][v]
pointing = pointing.reshape(248,296,6) # 248 296 8 3
pointing = np.swapaxes(pointing,0,2)
pointing = np.swapaxes(pointing, 1, 2)
pointing= pointing.astype(np.float32)
return pointing
def main():
path = os.path.dirname(os.path.abspath(__file__))
image_path = os.path.join(path, 'training/image_2')
data_dir = image_path
images = os.listdir(data_dir)
if len(images) == 0:
print('There are no images at directory %s. Check the data path.' % (data_dir))
else:
print('There are %d images to be processed.' % (len(images)))
images.sort()
for img_id, img_name in enumerate(images):
img_dir = os.path.join(data_dir, img_name)
img_shape = np.array(
io.imread(img_dir).shape[:2], dtype=np.int32)
h, w = np.array(img_shape, dtype=np.int32)
img_num = img_name.split(".png")[0]
calib_id = img_num + '.txt'
calib_file = os.path.join(path, 'training/calib')
calib_file = os.path.join(calib_file, calib_id)
seg_score_id = img_num + '.bin'
seg_score_file = os.path.join(path, 'training/seg_score')
seg_score_file = os.path.join(seg_score_file, seg_score_id)
seg_score = np.fromfile(str(seg_score_file), dtype=np.float32, count=-1).reshape([-1, h, w])
seg_score = np.argmax(seg_score, axis=0)
#seg_score = seg_score[np.newaxis, :, :]
seg_score = seg_score.astype(np.float32)
calib = read_kitti_calib(calib_file)
calib = calib.astype(np.float32)
r_rect = read_kitti_R0_rect(calib_file)
r_rect = r_rect.astype(np.float32)
velo2cam = read_kitti_Tr_velo_to_cam(calib_file)
velo2cam = velo2cam.astype(np.float32)
trans = oft(seg_score, calib, r_rect, velo2cam)
save_id = img_num + '.npy'
save_path = os.path.join(path, 'training/oft_class')
save_path = os.path.join(save_path, save_id)
np.save(save_path,trans)
print(img_num)
if __name__ == '__main__':
main() | pcdet/fusion/pointpillars_center.py | import os
import torch
import torch.nn.functional as F
import numpy as np
from PIL import Image
from skimage import io
import cv2
def create_anchors_3d_stride(grid_size,
voxel_size=[0.16, 0.16, 0.5],
coordinates_offsets=[0, -19.84, -2.5],
dtype=np.float32):
"""
Args:
feature_size: list [D, H, W](zyx)
sizes: [N, 3] list of list or array, size of anchors, xyz
Returns:
anchors: [*feature_size, num_sizes, num_rots, 7] tensor.
"""
# almost 2x faster than v1
x_stride, y_stride, z_stride = voxel_size
x_offset, y_offset, z_offset = coordinates_offsets
x_centers = np.arange(grid_size[0], dtype=dtype)
y_centers = np.arange(grid_size[1], dtype=dtype)
z_centers = np.arange(grid_size[2], dtype=dtype)
z_centers = z_centers * z_stride + z_offset + 0.25
y_centers = y_centers * y_stride + y_offset + 0.08
x_centers = x_centers * x_stride + x_offset + 0.08
xx, yy, zz = np.meshgrid(x_centers, y_centers, z_centers)
sizes = np.stack((xx, yy , zz), axis=-1)
sizes = np.reshape(sizes, [-1,3])
return sizes
def lidar_to_camera(points, r_rect, velo2cam):
points_shape = list(points.shape[:-1]) # N
if points.shape[-1] == 3:
points = np.concatenate([points, np.ones(points_shape + [1])], axis=-1)
camera_points = points @ (r_rect @ velo2cam).T
return camera_points[..., :3]
def project_to_image(points_3d, proj_mat):
points_shape = list(points_3d.shape)
points_shape[-1] = 1
points_4 = np.concatenate([points_3d, np.zeros(points_shape)], axis=-1)
point_2d = points_4 @ proj_mat.T
point_2d_res = point_2d[..., :2] / point_2d[..., 2:3]
return point_2d_res
def _extend_matrix(mat):
mat = np.concatenate([mat, np.array([[0., 0., 0., 1.]])], axis=0)
return mat
def read_kitti_calib(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'P2:':
calib_P2 = np.array([float(x) for x in data[1:13]])
calib_P2 = calib_P2.reshape(3, 4)
return _extend_matrix(calib_P2)
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def read_kitti_R0_rect(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'R0_rect:':
R0_rect = np.array([float(x) for x in data[1:13]])
R0_rect = R0_rect.reshape(3,3)
rect_4x4 = np.zeros([4, 4], dtype=R0_rect.dtype)
rect_4x4[3, 3] = 1.
rect_4x4[:3, :3] = R0_rect
return rect_4x4
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def read_kitti_Tr_velo_to_cam(filename):
"""Read the camera 2 calibration matrix from a text file"""
with open(filename) as f:
for line in f:
data = line.split(' ')
if data[0] == 'Tr_velo_to_cam:':
calib = np.array([float(x) for x in data[1:13]])
calib = calib.reshape(3, 4)
return _extend_matrix(calib)
raise Exception(
'Could not find entry for P2 in calib file {}'.format(filename))
def oft(features, calib, r_rect, velo2cam): # grid x y z
H, W = features.shape
features = np.swapaxes(features, 0,1)
corners = create_anchors_3d_stride([296,248,6])
corners = lidar_to_camera(corners, r_rect, velo2cam)
points_v_to_image = project_to_image(corners, calib)
num_points = len(points_v_to_image)
pointing = np.zeros(num_points)
for num in range(num_points):
u = int(round(points_v_to_image[num][0]))
v = int(round(points_v_to_image[num][1]))
if -1 < u < W and -1< v < H:
pointing[num] = features[u][v]
pointing = pointing.reshape(248,296,6) # 248 296 8 3
pointing = np.swapaxes(pointing,0,2)
pointing = np.swapaxes(pointing, 1, 2)
pointing= pointing.astype(np.float32)
return pointing
def main():
path = os.path.dirname(os.path.abspath(__file__))
image_path = os.path.join(path, 'training/image_2')
data_dir = image_path
images = os.listdir(data_dir)
if len(images) == 0:
print('There are no images at directory %s. Check the data path.' % (data_dir))
else:
print('There are %d images to be processed.' % (len(images)))
images.sort()
for img_id, img_name in enumerate(images):
img_dir = os.path.join(data_dir, img_name)
img_shape = np.array(
io.imread(img_dir).shape[:2], dtype=np.int32)
h, w = np.array(img_shape, dtype=np.int32)
img_num = img_name.split(".png")[0]
calib_id = img_num + '.txt'
calib_file = os.path.join(path, 'training/calib')
calib_file = os.path.join(calib_file, calib_id)
seg_score_id = img_num + '.bin'
seg_score_file = os.path.join(path, 'training/seg_score')
seg_score_file = os.path.join(seg_score_file, seg_score_id)
seg_score = np.fromfile(str(seg_score_file), dtype=np.float32, count=-1).reshape([-1, h, w])
seg_score = np.argmax(seg_score, axis=0)
#seg_score = seg_score[np.newaxis, :, :]
seg_score = seg_score.astype(np.float32)
calib = read_kitti_calib(calib_file)
calib = calib.astype(np.float32)
r_rect = read_kitti_R0_rect(calib_file)
r_rect = r_rect.astype(np.float32)
velo2cam = read_kitti_Tr_velo_to_cam(calib_file)
velo2cam = velo2cam.astype(np.float32)
trans = oft(seg_score, calib, r_rect, velo2cam)
save_id = img_num + '.npy'
save_path = os.path.join(path, 'training/oft_class')
save_path = os.path.join(save_path, save_id)
np.save(save_path,trans)
print(img_num)
if __name__ == '__main__':
main() | 0.635675 | 0.532121 |
import comet_ml
import sys
sys.path.append('..')
import numpy as np
from tcr_embedding.models.model_selection import run_model_selection
import tcr_embedding.utils_training as utils
from tcr_embedding.utils_preprocessing import group_shuffle_split
import os
import argparse
random_seed = 42
utils.fix_seeds(random_seed)
parser = argparse.ArgumentParser()
parser.add_argument('--rna_weight', type=int, default=1)
parser.add_argument('--gpus', type=int, default=1)
args = parser.parse_args()
adata = utils.load_data('borcherding')
print(len(adata))
# Randomly select patients to be left out during training
def get_n_patients(amount_patients):
if amount_patients <= 5:
return 0
else:
return 2
holdout_patients = {}
adata.obs['Tissue+Type'] = [f'{tissue}.{type_}' for tissue, type_ in zip(adata.obs['Tissue'], adata.obs['Type'])]
counts = adata.obs.groupby('Tissue+Type')['Sample'].value_counts()
for cat in adata.obs['Tissue+Type'].unique():
n = get_n_patients(len(counts[cat]))
choice = np.random.choice(counts[cat].index, n, replace=False).tolist()
holdout_patients[cat] = choice
for patients in holdout_patients.values():
adata = adata[~adata.obs['Sample'].isin(patients)]
train, val = group_shuffle_split(adata, group_col='clonotype', val_split=0.2, random_seed=random_seed)
adata.obs['set'] = 'train'
adata.obs.loc[val.obs.index, 'set'] = 'val'
print(len(adata))
params_experiment = {
'study_name': f'borcherding_moe_full_weight_{args.rna_weight}',
'comet_workspace': None, # 'borcherding',
'model_name': 'moe',
'early_stop': 5,
'balanced_sampling': 'clonotype',
'metadata': ['clonotype', 'Sample', 'Type', 'Tissue', 'functional.cluster'],
'save_path': os.path.join(os.path.dirname(__file__), '..', 'optuna', f'borcherding_moe_{args.rna_weight}')
}
params_optimization = {
'name': 'pseudo_metric',
'prediction_labels':
{'clonotype': 1,
'functional.cluster': args.rna_weight}
}
timeout = (2 * 24 * 60 * 60) - 300
run_model_selection(adata, params_experiment, params_optimization, None, timeout, args.gpus) | experiments/borcherding.py | import comet_ml
import sys
sys.path.append('..')
import numpy as np
from tcr_embedding.models.model_selection import run_model_selection
import tcr_embedding.utils_training as utils
from tcr_embedding.utils_preprocessing import group_shuffle_split
import os
import argparse
random_seed = 42
utils.fix_seeds(random_seed)
parser = argparse.ArgumentParser()
parser.add_argument('--rna_weight', type=int, default=1)
parser.add_argument('--gpus', type=int, default=1)
args = parser.parse_args()
adata = utils.load_data('borcherding')
print(len(adata))
# Randomly select patients to be left out during training
def get_n_patients(amount_patients):
if amount_patients <= 5:
return 0
else:
return 2
holdout_patients = {}
adata.obs['Tissue+Type'] = [f'{tissue}.{type_}' for tissue, type_ in zip(adata.obs['Tissue'], adata.obs['Type'])]
counts = adata.obs.groupby('Tissue+Type')['Sample'].value_counts()
for cat in adata.obs['Tissue+Type'].unique():
n = get_n_patients(len(counts[cat]))
choice = np.random.choice(counts[cat].index, n, replace=False).tolist()
holdout_patients[cat] = choice
for patients in holdout_patients.values():
adata = adata[~adata.obs['Sample'].isin(patients)]
train, val = group_shuffle_split(adata, group_col='clonotype', val_split=0.2, random_seed=random_seed)
adata.obs['set'] = 'train'
adata.obs.loc[val.obs.index, 'set'] = 'val'
print(len(adata))
params_experiment = {
'study_name': f'borcherding_moe_full_weight_{args.rna_weight}',
'comet_workspace': None, # 'borcherding',
'model_name': 'moe',
'early_stop': 5,
'balanced_sampling': 'clonotype',
'metadata': ['clonotype', 'Sample', 'Type', 'Tissue', 'functional.cluster'],
'save_path': os.path.join(os.path.dirname(__file__), '..', 'optuna', f'borcherding_moe_{args.rna_weight}')
}
params_optimization = {
'name': 'pseudo_metric',
'prediction_labels':
{'clonotype': 1,
'functional.cluster': args.rna_weight}
}
timeout = (2 * 24 * 60 * 60) - 300
run_model_selection(adata, params_experiment, params_optimization, None, timeout, args.gpus) | 0.303009 | 0.177454 |
import numpy as np
def edit_distance_with_errors(str1, str2, debug = False):
"""
Calculates Levenstein distance a.k.a. edit distance of two lists, and
number of each error type.
Returns dictionary:
"edit_distance"
"substitutions"
"insertions"
"deletions"
"""
distances = np.zeros(shape = [len(str1) + 1, len(str2) + 1],\
dtype = np.int32)
for idx1 in range(0, len(str1) + 1):
distances[idx1, 0] = idx1
for idx2 in range(0, len(str2) + 1):
distances[0, idx2] = idx2
for idx1 in range(0, len(str1)):
for idx2 in range(0, len(str2)):
distances[idx1 + 1, idx2 + 1] = min(\
distances[idx1, idx2 + 1],\
distances[idx1 + 1, idx2],\
distances[idx1, idx2]) + 1
if str1[idx1] == str2[idx2]:
distances[idx1 + 1, idx2 + 1] = min(\
distances[idx1 + 1, idx2 + 1],\
distances[idx1, idx2])
#Backtrack to get error types
pos = [len(str1), len(str2)]
insertions = 0
deletions = 0
substitutions = 0
while pos != [0, 0]:
curx = pos[0]
cury = pos[1]
curdist = distances[curx, cury]
if curx == 0:
if debug:
print('delb @', pos)
deletions+= 1
pos[1]-= 1
elif cury == 0:
if debug:
print('insb @', pos)
insertions+= 1
pos[0]-= 1
elif (distances[curx - 1, cury - 1] == curdist) and (str1[curx - 1] == str2[cury - 1]):
pass
pos[0]-= 1
pos[1]-= 1
elif (distances[curx - 1, cury - 1] == curdist - 1) and (str1[curx - 1] != str2[cury - 1]):
substitutions+= 1
if debug:
print('sub @ ', pos)
pos[0]-= 1
pos[1]-= 1
elif (distances[curx, cury - 1] == curdist - 1):
if debug:
print('del @ ', pos)
deletions+= 1
pos[1]-= 1
elif distances[curx - 1, cury] == curdist - 1:
if debug:
print('ins @', pos)
insertions+= 1
pos[0]-= 1
res = {}
res['edit_distance'] = distances[-1, -1]
res['insertions'] = insertions
res['substitutions'] = substitutions
res['deletions'] = deletions
res['error_rate'] = res['edit_distance'] / len(str2)
res['accuracy'] = 1 - res['error_rate']
return res
def edit_distance(str1, str2):
"""
Calculates Levenstein distance a.k.a. edit distance of two lists.
"""
return edit_distance_with_errors(str1, str2)['edit_distance']
def similarity_metric(str1, str2):
"""
Calculates similarity metric I made up of two lists.
"""
return 1 - edit_distance(str1, str2) / max(len(str1), len(str2))
def split_words(str1):
result = []
word = ''
for char in str1:
if char != ' ':
word+= char
elif char == ' ':
if len(word) > 0:
result.append(word)
word = ''
if word != '':
result.append(word)
return result
def error_rate(str1, str2):
return edit_distance(str1, str2) / len(str2)
def accuracy(str1, str2):
return 1 - error_rate(str1, str2) | code/stringmetrics.py | import numpy as np
def edit_distance_with_errors(str1, str2, debug = False):
"""
Calculates Levenstein distance a.k.a. edit distance of two lists, and
number of each error type.
Returns dictionary:
"edit_distance"
"substitutions"
"insertions"
"deletions"
"""
distances = np.zeros(shape = [len(str1) + 1, len(str2) + 1],\
dtype = np.int32)
for idx1 in range(0, len(str1) + 1):
distances[idx1, 0] = idx1
for idx2 in range(0, len(str2) + 1):
distances[0, idx2] = idx2
for idx1 in range(0, len(str1)):
for idx2 in range(0, len(str2)):
distances[idx1 + 1, idx2 + 1] = min(\
distances[idx1, idx2 + 1],\
distances[idx1 + 1, idx2],\
distances[idx1, idx2]) + 1
if str1[idx1] == str2[idx2]:
distances[idx1 + 1, idx2 + 1] = min(\
distances[idx1 + 1, idx2 + 1],\
distances[idx1, idx2])
#Backtrack to get error types
pos = [len(str1), len(str2)]
insertions = 0
deletions = 0
substitutions = 0
while pos != [0, 0]:
curx = pos[0]
cury = pos[1]
curdist = distances[curx, cury]
if curx == 0:
if debug:
print('delb @', pos)
deletions+= 1
pos[1]-= 1
elif cury == 0:
if debug:
print('insb @', pos)
insertions+= 1
pos[0]-= 1
elif (distances[curx - 1, cury - 1] == curdist) and (str1[curx - 1] == str2[cury - 1]):
pass
pos[0]-= 1
pos[1]-= 1
elif (distances[curx - 1, cury - 1] == curdist - 1) and (str1[curx - 1] != str2[cury - 1]):
substitutions+= 1
if debug:
print('sub @ ', pos)
pos[0]-= 1
pos[1]-= 1
elif (distances[curx, cury - 1] == curdist - 1):
if debug:
print('del @ ', pos)
deletions+= 1
pos[1]-= 1
elif distances[curx - 1, cury] == curdist - 1:
if debug:
print('ins @', pos)
insertions+= 1
pos[0]-= 1
res = {}
res['edit_distance'] = distances[-1, -1]
res['insertions'] = insertions
res['substitutions'] = substitutions
res['deletions'] = deletions
res['error_rate'] = res['edit_distance'] / len(str2)
res['accuracy'] = 1 - res['error_rate']
return res
def edit_distance(str1, str2):
"""
Calculates Levenstein distance a.k.a. edit distance of two lists.
"""
return edit_distance_with_errors(str1, str2)['edit_distance']
def similarity_metric(str1, str2):
"""
Calculates similarity metric I made up of two lists.
"""
return 1 - edit_distance(str1, str2) / max(len(str1), len(str2))
def split_words(str1):
result = []
word = ''
for char in str1:
if char != ' ':
word+= char
elif char == ' ':
if len(word) > 0:
result.append(word)
word = ''
if word != '':
result.append(word)
return result
def error_rate(str1, str2):
return edit_distance(str1, str2) / len(str2)
def accuracy(str1, str2):
return 1 - error_rate(str1, str2) | 0.417984 | 0.508117 |
from os import system,environ,getlogin,mkdir
from time import sleep,ctime
from shutil import *
from os.path import *
from sys import argv,platform,version,stdout
from urllib.request import urlopen as buka
from random import choice
from json import load
def main():
system('clear')
try:
print ('\033[94m[\033[91m1\033[94m] \033[92mTambahkan Tombol Termux\n\033[94m[\033[91m2\033[94m] \033[96mInformation\n\033[94m[\033[91m0\033[94m] \033[91mexit')
nanya = int(input('\033[97m>>> '))
if nanya == 1:
tombol()
elif nanya == 2:
Info()
elif nanya == 0:
exit()
except ValueError as bulat:
print ('[!]',bulat)
sleep(2)
main()
except Exception as err:
print (err)
def tombol():
info = "Tekan CTRL + t untuk buat-sesi\nTekan CTRL + 5 untuk sesi berikutnya\nTekan CTRL + 4 untuk sesi sebelumnya"
data = "extra-keys = [ ['ESC','|','/','HOME','UP','END','PGUP','DEL'],['TAB','CTRL','ALT','LEFT','DOWN','RIGHT','PGDN','BKSP']]"
try:
print ('\033[94m[\033[91m!\033[94m] \033[93mMembuat Folder')
try:
mkdir('/data/data/com.termux/files/home/.termux')
except:
pass
file = open('/data/data/com.termux/files/home/.termux/termux.properties','w')
print ('\033[94m[\033[91m!\033[94m] \033[93mMembuka',basename(file.name))
file.write("shortcut.create-session = ctrl + t\n")
file.write("shortcut.next-session = ctrl + 5\n")
file.write("shortcut.previous-session = ctrl + 4\n")
file.write(data)
file.close()
try:
with open('Informasi.txt','w') as my:
my.write(info)
except:
pass
print ('\033[94m[\033[91m✓\033[94m] \033[93mSukses')
system('termux-reload-settings')
print ('\n\033[92mINFO TAMBAHAN')
print (20* '\033[96m=')
print (info)
exit()
except KeyboardInterrupt:
exit ('\033[94m[\033[91m!\033[94m] \033[91mExit')
def storage():
anjay = environ["EXTERNAL_STORAGE"]
try:
total, used, free = disk_usage(anjay)
print ('\033[92m[✓] DISK USAGE : ')
print(" \033[93m- Total: %d GiB" % (total // (2**30)))
print(" \033[94m- Used: %d GiB" % (used // (2**30)))
print(" \033[95m- Free: %d GiB" % (free // (2**30)))
except Exception as err:
print (err)
def info_lainnya():
data = []
try:
for a in environ:
data.append(a)
data.remove('LS_COLORS')
for b in data:
warna = ["\033[91m","\033[92m","\033[93m","\033[94m","\033[95m","\033[96m","\033[97m"]
acak =choice(warna)
print('\033[92m[✓]',b,':',acak,environ[b])
except Exception as err:
print(err)
def Info():
system('clear')
animasi = ['. ','.. ','... ']
for me in animasi:
print("\r\033[94m[\033[91m!\033[94m] \033[92mMemuat"+me, end = ''),;stdout.flush();sleep(0.1)
system('clear')
url = "https://api.myip.com"
ip = []
try:
a = buka(url)
b = load(a)
c = b['ip']
ip.append(c)
except:
ip.append(None)
print ('\033[92m[✓] Date : \033[97m',ctime())
print ('\033[92m[✓] OS :\033[91m',platform)
print ('\033[92m[✓] Script :\033[96m',basename(argv[0]))
print ('\033[92m[✓] python : \033[95m',version[0])
print ('\033[92m[✓]',get_terminal_size())
print ('\033[92m[✓] IP :',ip[0])
print ('\033[92m[✓] AUTHOR : \033[93m<NAME>')
info_lainnya()
storage()
print ('\n\033[96m\t___Contact me___')
print (' \033[97mEmail : \033[97mra<EMAIL>')
print (' \033[97mGithub : \033[90mMR-X-Junior')
print (' \033[97mWhatsApp : \033[92m6285754629509')
print (' \033[97mFacebook : \033[94mhttps://www.facebook.com/Anjay.pro098')
exit()
if __name__=="__main__":
if platform == "'linux2'" or platform == "linux":
main()
else:
exit(f'\033[91mProgram tidak di dukung pada {platform}') | tombol.py | from os import system,environ,getlogin,mkdir
from time import sleep,ctime
from shutil import *
from os.path import *
from sys import argv,platform,version,stdout
from urllib.request import urlopen as buka
from random import choice
from json import load
def main():
system('clear')
try:
print ('\033[94m[\033[91m1\033[94m] \033[92mTambahkan Tombol Termux\n\033[94m[\033[91m2\033[94m] \033[96mInformation\n\033[94m[\033[91m0\033[94m] \033[91mexit')
nanya = int(input('\033[97m>>> '))
if nanya == 1:
tombol()
elif nanya == 2:
Info()
elif nanya == 0:
exit()
except ValueError as bulat:
print ('[!]',bulat)
sleep(2)
main()
except Exception as err:
print (err)
def tombol():
info = "Tekan CTRL + t untuk buat-sesi\nTekan CTRL + 5 untuk sesi berikutnya\nTekan CTRL + 4 untuk sesi sebelumnya"
data = "extra-keys = [ ['ESC','|','/','HOME','UP','END','PGUP','DEL'],['TAB','CTRL','ALT','LEFT','DOWN','RIGHT','PGDN','BKSP']]"
try:
print ('\033[94m[\033[91m!\033[94m] \033[93mMembuat Folder')
try:
mkdir('/data/data/com.termux/files/home/.termux')
except:
pass
file = open('/data/data/com.termux/files/home/.termux/termux.properties','w')
print ('\033[94m[\033[91m!\033[94m] \033[93mMembuka',basename(file.name))
file.write("shortcut.create-session = ctrl + t\n")
file.write("shortcut.next-session = ctrl + 5\n")
file.write("shortcut.previous-session = ctrl + 4\n")
file.write(data)
file.close()
try:
with open('Informasi.txt','w') as my:
my.write(info)
except:
pass
print ('\033[94m[\033[91m✓\033[94m] \033[93mSukses')
system('termux-reload-settings')
print ('\n\033[92mINFO TAMBAHAN')
print (20* '\033[96m=')
print (info)
exit()
except KeyboardInterrupt:
exit ('\033[94m[\033[91m!\033[94m] \033[91mExit')
def storage():
anjay = environ["EXTERNAL_STORAGE"]
try:
total, used, free = disk_usage(anjay)
print ('\033[92m[✓] DISK USAGE : ')
print(" \033[93m- Total: %d GiB" % (total // (2**30)))
print(" \033[94m- Used: %d GiB" % (used // (2**30)))
print(" \033[95m- Free: %d GiB" % (free // (2**30)))
except Exception as err:
print (err)
def info_lainnya():
data = []
try:
for a in environ:
data.append(a)
data.remove('LS_COLORS')
for b in data:
warna = ["\033[91m","\033[92m","\033[93m","\033[94m","\033[95m","\033[96m","\033[97m"]
acak =choice(warna)
print('\033[92m[✓]',b,':',acak,environ[b])
except Exception as err:
print(err)
def Info():
system('clear')
animasi = ['. ','.. ','... ']
for me in animasi:
print("\r\033[94m[\033[91m!\033[94m] \033[92mMemuat"+me, end = ''),;stdout.flush();sleep(0.1)
system('clear')
url = "https://api.myip.com"
ip = []
try:
a = buka(url)
b = load(a)
c = b['ip']
ip.append(c)
except:
ip.append(None)
print ('\033[92m[✓] Date : \033[97m',ctime())
print ('\033[92m[✓] OS :\033[91m',platform)
print ('\033[92m[✓] Script :\033[96m',basename(argv[0]))
print ('\033[92m[✓] python : \033[95m',version[0])
print ('\033[92m[✓]',get_terminal_size())
print ('\033[92m[✓] IP :',ip[0])
print ('\033[92m[✓] AUTHOR : \033[93m<NAME>')
info_lainnya()
storage()
print ('\n\033[96m\t___Contact me___')
print (' \033[97mEmail : \033[97mra<EMAIL>')
print (' \033[97mGithub : \033[90mMR-X-Junior')
print (' \033[97mWhatsApp : \033[92m6285754629509')
print (' \033[97mFacebook : \033[94mhttps://www.facebook.com/Anjay.pro098')
exit()
if __name__=="__main__":
if platform == "'linux2'" or platform == "linux":
main()
else:
exit(f'\033[91mProgram tidak di dukung pada {platform}') | 0.037117 | 0.074164 |
kannada = {
"ಅಂಕ":True,
"ಅಂಕಗಣಿತ":True,
"ಅಂಕಣ":True,
"ಅಂಕಣಗಾರ":True,
"ಅಂಕಿ":True,
"ಅಂಕಿ":True,
"ಅಂಕಿಅಂಶ":True,
"ಅಂಕಿತ":True,
"ಅಂಕಿತನಾಮ":True,
"ಅಂಕುಡೊಂಕು":True,
"ಅಂಕುರ":True,
"ಅಂಕುರಾರ್ಪಣ":True,
"ಅಂಕುರಿಸು":True,
"ಅಂಕುಶ":True,
"ಅಂಕೆ":True,
"ಅಂಗ":True,
"ಅಂಗಚೇಷ್ಟೆ":True,
"ಅಂಗಡಿ":True,
"ಅಂಗಡಿಕೇರಿ":True,
"ಅಂಗಡಿಬೀದಿ":True,
"ಅಂಗಣ":True,
"ಅಂಗತ":True,
"ಅಂಗತ್ತ":True,
"ಅಂಗನೆ":True,
"ಅಂಗಭಾಗ":True,
"ಅಂಗಮರ್ದ":True,
"ಅಂಗಮರ್ದನ":True,
"ಅಂಗರಕ್ಷ":True,
"ಅಂಗರಕ್ಷಕ":True,
"ಅಂಗರಕ್ಷೆ":True,
"ಅಂಗರಚನಾಶಾಸ್ತ್ರ":True,
"ಅಂಗಲಾಚು":True,
"ಅಂಗವಸ್ತ್ರ":True,
"ಅಂಗವಿಕಲಗೊಳಿಸು":True,
"ಅಂಗವಿಕಾರ":True,
"ಅಂಗಸಂಗ":True,
"ಅಂಗಸಂಸ್ಥೆ":True,
"ಅಂಗಸಾಧನೆ":True,
"ಅಂಗಳ":True,
"ಅಂಗಾರಕ":True,
"ಅಂಗಾಲು":True,
"ಅಂಗಿ":True,
"ಅಂಗೀಕರಿಸದಿರು":True,
"ಅಂಗೀಕರಿಸು":True,
"ಅಂಗೀಕಾರ":True,
"ಅಂಗೀಕಾರಾರ್ಹ":True,
"ಅಂಗೀಕಾರಾರ್ಹತೆ":True,
"ಅಂಗೀಕೃತ":True,
"ಅಂಗುಟ":True,
"ಅಂಗುಲ":True,
"ಅಂಗುಲಿ":True,
"ಅಂಗುಲೀಯ":True,
"ಅಂಗುಷ್ಠ":True,
"ಅಂಗುಳು":True,
"ಅಂಗೈ":True,
"ಅಂಘ್ರಿ":True,
"ಅಂಚು":True,
"ಅಂಚಿ":True,
"ಅಂಚೆಯಾಳು":True,
"ಅಂಚಿಕಚೇರಿ":True,
"ಅಂಜನ":True,
"ಅಂಜಲಿ":True,
"ಅಂಜಿಕೆ":True,
"ಅಂಜು":True,
"ಅಂಜುಕುಳಿ":True,
"ಅಂಜುಗುಳಿ":True,
"ಅಂಜೂರ":True,
"ಅಂಟಿಕೊ":True,
"ಅಂಟಿಸು":True,
"ಅಂಟು":True,
"ಅಂಟುಜಾಡ್ಯ":True,
"ಅಂಟುಪುರಲೆ":True,
"ಅಂಟುರೋಗ":True,
"ಅಂಡ":True,
"ಅಂಡಕೋಶ":True,
"ಅಂಡಜ":True,
"ಅಂಡಲೆ":True,
"ಅಂಡವಾಯ":True,
"ಅಂಡು":True,
"ಅಂತ":True,
"ಅಂತಃಕರಣ":True,
"ಅಂತಃಕಲಹ":True,
"ಅಂತಃಪಟ":True,
"ಅಂತಃಪುರ":True,
"ಅಂತಃಸಾಮಥ್ರ್ಯ":True,
"ಅಂತಕ":True,
"ಅಂತರ":True,
"ಅಂತರಂಗ":True,
"ಅಂತರಪಿಶಾಚಿ":True,
"ಅಂತರಕ್ರಿಯ":True,
"ಅಂತರಬಂಧನ":True,
"ಅಂತರಾತ್ಮ":True,
"ಅಂತರಾಳ":True,
"ಅಂತರಿಕ್ಷ":True,
"ಅಂತರ್ಗತ":True,
"ಅಂತರ್ಜಾತೀಯ":True,
"ಅಂತರ್ಜೋತಿ":True,
"ಅಂತರ್ದಹನ":True,
"ಅಂತರ್ದೃಷ್ಟಿ":True,
"ಅಂತರ್ದೇಶಿಯ":True,
"ಅಂತರ್ದಾನ":True,
"ಅಂತರ್ಬೋಧೆ":True,
"ಅಂತರ್ಮುಖ":True,
"ಅಂತರ್ಮುಖಿ":True,
"ಅಂತರ್ಯಾಮಿ":True,
"ಅಂತರಾರ್ಷೀಯ":True,
"ಅಂತರ್ವಾಣಿ":True,
"ಅಂತಸ್ತು":True,
"ಅಂತಹ":True,
"ಅಂತಿಮೆ":True,
"ಅಂತ್ಯ":True,
"ಅಂತ್ಯಕಾಲ":True,
"ಅಂತ್ಯಗೊಳಿಸು":True,
"ಅಂಥ":True,
"ಅಂತ್ಯಸಂಸ್ಕಾರ":True,
"ಅಂದ":True,
"ಅಂದಗಾತಿ":True,
"ಅಂದಗೇಡಿ":True,
"ಅಂದಣ":True,
"ಅಂದಳ":True,
"ಅಂದಾಜು":True,
"ಅಂದಿಗೆ":True,
"ಅಂದು":True,
"ಅಂದುಗೆ":True,
"ಅಂಧ":True,
"ಅಂಧಕಾರ":True,
"ಅಂಧಶ್ರದ್ದೆ":True,
"ಅಂಬರ":True,
"ಅಂಬಲಿ":True,
"ಅಂಬಾರಿ":True,
"ಅಂಬಿಗ":True,
"ಅಂಬು":True,
"ಅಂಬುಜ":True,
"ಅಂಬುಧಿ":True,
"ಅಂಬೆ":True,
"ಅಂಬೆಗಾಲು":True,
"ಅಂಶ":True,
"ಅಂಶಕಾಲಿಕ":True,
"ಅಕಟ":True,
"ಅಕರಾಸ್ತ":True,
"ಅಕಲಂಕ":True,
"ಅಕಲಾಯ":True,
"ಅಕಸ್ಮಾತ್":True,
"ಅಕಳಂಕ":True,
"ಅಕಾರಣ":True,
"ಅಕಾಲ":True,
"ಅಕಾಲಮರಣ":True,
"ಅಕಾಲವರ್ಷ":True,
"ಅಕಾಲವೃಷ್ಟಿ":True,
"ಅಕಾಲಿಕ":True,
"ಅಕಿಂಚನ":True,
"ಅಕುಟಿಲ":True,
"ಅಕೃತ್ಯ":True,
"ಅಕ್ಕ":True,
"ಅಕ್ಕಟ":True,
"ಅಕ್ಕರೆ":True,
"ಅಕ್ಕಸಾಲಿಗ":True,
"ಅಕ್ಕಸಾಲೆ":True,
"ಅಕ್ಕಿ":True,
"ಅಕ್ರಮ":True,
"ಅಕ್ರಮಕೂಟ":True,
"ಅಕ್ರಮಪ್ರವೇಶ":True,
"ಅಕ್ರಮಸಭೆ":True,
"ಅಕ್ಷ":True,
"ಅಕ್ಷತ":True,
"ಅಕ್ಷಮ್ಯ":True,
"ಅಕ್ಷಯ":True,
"ಅಕ್ಷರ":True,
"ಅಕ್ಷರಮಾಲೆ":True,
"ಅಕ್ಷರಶಃ":True,
"ಅಕ್ಷರಶತ್ರು":True,
"ಅಕ್ಷರಸ್ಥ":True,
"ಅಕ್ಷರೇಖೆ":True,
"ಅಕ್ಷಾಂಶ":True,
"ಅಕ್ಷಿ":True,
"ಅಕ್ಷೋಹಿಣಿ":True,
"ಅಕ್ಷೌಹಿಣಿ":True,
"ಅಖಂಡ":True,
"ಅಖಂಡತೆ":True,
"ಅಖಾಡ":True,
"ಅಖಾದ್ಯ":True,
"ಅಖಿಲ":True,
"ಅಗಚಾಟಲು":True,
"ಅಗಣಿ":True,
"ಅಗಣಿತ":True,
"ಅಗತುಕೊ":True,
"ಅಗತ್ಯ":True,
"ಅಗಮ್ಯ":True,
"ಅಗಲ":True,
"ಅಗಲಿಕೆ":True,
"ಅಗಲಿಸು":True,
"ಅಗಲು":True,
"ಅಗಸ":True,
"ಅಗಸಗಿತ್ತಿ":True,
"ಅಗಸೆ":True,
"ಅಗಳಿ":True,
"ಅಗುಳು":True,
"ಅಗಾಧ":True,
"ಅಗಿ":True,
"ಅಗುಳಿ":True,
"ಅಗೆ":True,
"ಅಗೆತ":True,
"ಅಗೋಚರ":True,
"ಅಗೌರವ":True,
"ಅಗ್ಗ":True,
"ಅಗ್ಗಳಿಕೆ":True,
"ಅಗ್ರ":True,
"ಅಗ್ರಕರ್ಮಿಕ":True,
"ಅಗ್ರಗಣ್ಯ":True,
"ಅಗ್ರಜ":True,
"ಅಗ್ರಪೂಜೆ":True,
"ಅಗ್ರಮಹಿಷಿ":True,
"ಅಗ್ಗಿಷ್ಟಗೆ":True,
"ಅಗ್ನಿ":True,
"ಅಗ್ನಿದಿವ್ಯ":True,
"ಅಗ್ನಿಪರ್ವತ":True,
"ಅಗ್ನಿಪರೀಕ್ಷೆ":True,
"ಅಗ್ನಿಭಕ್ಷಕ":True,
"ಅಗ್ನಿಮಾಂದ್ಯ":True,
"ಅಗ್ನಿಶಾಮಕ":True,
"ಅಗ್ನಿಶಾಮಕದಳ":True,
"ಅಗ್ನಿಶಾಮಕಯಂತ್ರ":True,
"ಅಗ್ರಸ್ಥಾನ":True,
"ಅಗ್ರಾಸನ":True,
"ಅಗ್ರೇಸರ":True,
"ಅಘ್":True,
"ಅಚಲ":True,
"ಅಚಾತುರ್ಯ":True,
"ಅಜಾನಕ":True,
"ಅಚಿಂತ್ಯ":True,
"ಅಚ್ಚ":True,
"ಅಚ್ಚಕನ್ನಡ":True,
"ಅಚ್ಚಗನ್ನಡ":True,
"ಅಚ್ಚರಿ":True,
"ಅಚ್ಚರಿಗೊಳಿಸು":True,
"ಅಚ್ಚು":True,
"ಅಚ್ಚುಕಟ್ಟು":True,
"ಅಚ್ಚುಕೂಟ":True,
"ಅಚ್ಚುಪಡಿ":True,
"ಅಚ್ಚುಮೆಚ್ಚು":True,
"ಅಚ್ಚುಮೊಳೆ":True,
"ಅಚ್ಚುಹಾಕು":True,
"ಅಚ್ಚೊತ್ತು":True,
"ಅಚ್ಘಿನ್ನ":True,
"ಅಚ್ಚೋದ":True,
"ಅಚ್ಚುತ":True,
"ಅಜ":True,
"ಅಜಗಜಾಂತರ":True,
"ಅಜಗರ":True,
"ಅಜರ":True,
"ಅಜರಾಮರ":True,
"ಅಜಸ್ತ್ರ":True,
"ಅಜಾಗರೂಕ":True,
"ಅಜಾಗರೂಕತೆ":True,
"ಅಜಾಗ್ರತೆ":True,
"ಅಜಾತಶತ್ರು":True,
"ಅಜಿನ":True,
"ಅಜೀರ್ಣ":True,
"ಅಜೇಯ":True,
"ಅಜ್ಜ":True,
"ಅಜ್ಜಿ":True,
"ಅಜ್ಞ":True,
"ಅಜ್ಞಾತ":True,
"ಅಜ್ಞಾತವಾಸ":True,
"ಅಜ್ಞಾನ":True,
"ಅಜ್ಞಾನಿ":True,
"ಅಜ್ಞೇಯ":True,
"ಅಟಕಾಯಿಸು":True,
"ಅಟಮಡ":True,
"ಅಟಮಟಿಸು":True,
"ಅಟಾಟೊಪ":True,
"ಅಟ್ಟಿ":True,
"ಅಟ್ಟಣಿಗೆ":True,
"ಅಟ್ಟಹಾಸ":True,
"ಅಟ್ಟಿಸು":True,
"ಅಟ್ಟು":True,
"ಅಟ್ಟೆ":True,
"ಅಠಾರ":True,
"ಅಡಕ":True,
"ಅಡಕತ್ತರಿ":True,
"ಅಡಕಲೆ":True,
"ಅಡಗಿಸು":True,
"ಅಡಚಣೆ":True,
"ಅಡತಡೆ":True,
"ಅಡನಾಡಿ":True,
"ಅಡಮಾನ":True,
"ಅಡರು":True,
"ಅಡವಿ":True,
"ಅಡವಿಸು":True,
"ಅಡಸು":True,
"ಅಡಾವುಡಿ":True,
"ಅಡಿ":True,
"ಅಡಿಗಟ್ಟು":True,
"ಅಡಿಗಲ್ಲು":True,
"ಅಡಿಗೆ":True,
"ಅಡಿಗೆ":True,
"ಅಡಿಗೆಯವನು":True,
"ಅಡಿ ಟಿಪ್ಪಣಿ":True,
"ಅಡಿದೀಪ":True,
"ಅಡಿಪಾಯ":True,
"ಅಡಿಮಟ್ಟ":True,
"ಅಡಿಮುಸಿ":True,
"ಅಡಿಯಾಳು":True,
"ಅಡಿಯಾಳುತನ":True,
"ಅಡಿಯಿಡು":True,
"ಅಡಿಯೂರು":True,
"ಅಡಹತ್ತು":True,
"ಅಡುಗೊಲಜ್ಜಿ":True,
"ಅಡೆತಡೆ":True,
"ಅಡೆಹಾಕು":True,
"ಅಡ್ಡ":True,
"ಅಡ್ಡಕಥೆ":True,
"ಅಡ್ಡಕಸಬಿ":True,
"ಅಡ್ಡಕಸಬು":True,
"ಅಡ್ಡಕೊಯ್ತ":True,
"ಅಡ್ಡಗಲ":True,
"ಅಡ್ಡಗಟ್ಟು":True,
"ಅಡ್ಡಗೆರೆ":True,
"ಅಡ್ಡಗೋಡೆ":True,
"ಅಡ್ಡಣಿಗೆ":True,
"ಅಡ್ಡತಳಿ":True,
"ಅಡ್ಡದಾರಿ":True,
"ಅಡ್ಡ ಪಂಕ್ತಿ":True,
"ಅಡ್ಡ ಬರು":True,
"ಅಡ್ಡಬಯಿಹಾಕು":True,
"ಅಡ್ಡಮಳೆ":True,
"ಅಡ್ಡಮಾತು":True,
"ಅಡ್ಡಮಾರ್ಗ":True,
"ಅಡ್ಡರಸ್ತೆ":True,
"ಅಡ್ಡಸುಳಿ":True,
"ಅಡ್ಡಹಾಕು":True,
"ಅಡ್ಡಹಾಯು":True,
"ಅಡ್ಡಹೆಸರು":True,
"ಅಡ್ಡಾಗು":True,
"ಅಡ್ಡಾಡು":True,
"ಅಡ್ಡಾದಿಡ್ಡಿ":True,
"ಅಡ್ಡಿ":True,
"ಅಡ್ಡಿಕೆ":True,
"ಅಡ್ಡಿತರು":True,
"ಅಡ್ಡೇಟು":True,
"ಅಣಕ":True,
"ಅಣಕ":True,
"ಅಣಕವಾಡು":True,
"ಅಣಕಿಸು":True,
"ಅಣಗಿಸು":True,
"ಅಣಗು":True,
"ಅಣಿ":True,
"ಅಣಿಗೊಳಿಸು":True,
"ಅಣಿಗೊಳಿಸುವನು":True,
"ಅನುಗ":True,
"ಅಣುಗಿ":True,
"ಅನುಶಕ್ತ":True,
"ಅನೆ":True,
"ಅಣ್ಣ":True,
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"ಹೇತು":True,
"ಹೇನು":True,
"ಹೇಮ":True,
"ಹೇಯ":True,
"ಹೇರು":True,
"ಹೇಸರಿಸು":True,
"ಹೇಸಿಕೆ":True,
"ಹೇಸಿಗೆ":True,
"ಹೇಸು":True,
"ಹೇಳಿಕೆ":True,
"ಹೇಳು":True,
"ಹೈಕು":True,
"ಹೈನು":True,
"ಹೈನುಕ್ಷೇತ್ರ":True,
"ಹೈನುಗಾರಿಕೆ":True,
"ಹೊಂಚು":True,
"ಹೋಂಚುಹಾಕು":True,
"ಹೊಂದದ":True,
"ಹೊಂದಾಣಿಕೆ":True,
"ಹೊಮದಿಕೆ":True,
"ಹೊಮದಿಕೊ":True,
"ಹೊಂದು":True,
"ಹೊಕ್ಕು":True,
"ಹೊಕ್ಕುಳು":True,
"ಹೊಗರು":True,
"ಹೊಗಳಿಕೆ":True,
"ಹೊಗಳು":True,
"ಹೊಗಳುಭಟ":True,
"ಹೊಗಳುಬಟ್ಟ":True,
"ಹೊಗು":True,
"ಹೋಗೆ":True,
"ಹೊಗೆಬಂಡಿ":True,
"ಹೊಗೆಬತ್ತಿ":True,
"ಹೊಗೆಯಾಡು":True,
"ಹೊಗೆಹಾಕು":True,
"ಹೊಟ್ಟು":True,
"ಹೊಟ್ಟೆ":True,
"ಹೊಟ್ಟೆಕಿಚ್ಚು":True,
"ಹೊಟ್ಟೆಪಾಡು":True,
"ಹೊಟ್ಟೆಬಾಕ":True,
"ಹೊಟ್ಟೆಯುರಿ":True,
"ಹೊಟ್ಟೆಹೊರೆ":True,
"ಹೊಡೆ":True,
"ಹೊಡತೆ":True,
"ಹೊಣೆ":True,
"ಹೊಣೆಗಾರ":True,
"ಹೊಣೆಮಾಡು":True,
"ಹೊತ್ತಗೆ":True,
"ಹೊತ್ತಾರೆ":True,
"ಹೊತ್ತಿಗೆ":True,
"ಹೊತ್ತಿಸು":True,
"ಹೊತ್ತಿಳಿ":True,
"ಹೊತ್ತುಗಳೆ":True,
"ಹೊತ್ತುಮೀರು":True,
"ಹೊದಿಕೇ":True,
"ಹೋದಿಸು":True,
"ಹೊದೆ":True,
"ಹೊನಲು":True,
"ಹೊನ್ನು":True,
"ಹೊಪ್ಪಳೆ":True,
"ಹೊಮ್ಮು":True,
"ಹೊಯ್ಯು":True,
"ಹೊರ":True,
"ಹೊರಗಟ್ಟು":True,
"ಹರಗಡೆ":True,
"ಹೊರಗೆ":True,
"ಹೊರಗೆಡವು":True,
"ಹೊರಡು":True,
"ಹೊರತರು":True,
"ಹೊರತು":True,
"ಹೊರತೋರಿಕೆ":True,
"ಹೊರದಾರಿ":True,
"ಹೊರನೋಟ":True,
"ಹೊರಪಡು":True,
"ಹೊರಬೀಳು":True,
"ಹೊರಹಾಕು":True,
"ಹೊರಳು":True,
"ಹೊರಳುನುಡಿ":True,
"ಹೂರಿಸು":True,
"ಹೂರೆ":True,
"ಹೂಲ":True,
"ಹೂಲಬು":True,
"ಹೂಲಸು":True,
"ಹೂಲಸುತ":True,
"ಹೂಲಸುನಾತ":True,
"ಹೂಲಸಮಾತು":True,
"ಹೂಲಿಗ":True,
"ಎ ಹೂಲೆ":True,
"ಹೂಲ್ಲ":True,
"ಹೂಸ":True,
"ಹೂಸಕು":True,
"ಹೂಸತನ":True,
"ಹೂಸತು":True,
"ಹೂಸಬ":True,
"ಹೂಸಲು":True,
"ಹೂಸಿಲು":True,
"ಹೂಸೆ":True,
"ಹೂಸ್ತಿಲು":True,
"ಹೂಳಪು":True,
"ಹೂಳಲು":True,
"ಹೋಳಹು":True,
"ಹೂಳೆ":True,
"ಹೂಳ್ಳೆ":True,
"ಹೋಗು":True,
"ಹೋರಾಟ":True,
"ಹೋರಾಡು":True,
"ಹೋರಿ":True,
"ಹೋರು":True,
"ಹೋಲಿಕೆ":True,
"ಹೋಲಿಸು":True,
"ಹೋಲು":True,
"ಹೋಳು":True,
"ಹೊಳು":True,
"ಹೌದು":True,
"ಹೌಹಾರು":True,
"ಹ್ರಸ್ವ":True,
"ಹ್ರಸ್ವಗೊಳಿಸು":True,
"ಹಾಡುಗಾರ":True,
"ಹಾತೆ":True,
"ಹತೊರೆ":True,
"ಹಾದರ":True,
"ಹಾದರಗಿತ್ತಿ":True,
"ಹಾದಿ":True,
"ಹಾದಿಹೋಕ":True,
"ಹಾನಿ":True,
"ಹಾನಿಕರ":True,
"ಹಾಯಾಗು":True,
"ಹಾಯಿ":True,
"ಹಾಯಿಸು":True,
"ಹಾರ":True,
"ಹಾರವ":True,
"ಹಾರಾಟ":True,
"ಹಾರಾಡು":True,
"ಹಾರಿಕೆ":True,
"ಹಾರಿಕೆಮಾತು":True,
"ಹಾರಿಸು":True,
"ಹಾರು":True,
"ಹಾರೆ":True,
"ಹಾರೈಕೆ":True,
"ಹಾರೈಸು":True,
"ಹಾರ್ದಿಕ":True,
"ಹಾಲಾಹಲ":True,
"ಹಾಲಿ":True,
"ಹಾಲು":True,
"ಹಾವ":True,
"ಹಾವಸೆ":True,
"ಹಾವಳಿ":True,
"ಹಾವಾಡಿಗ":True,
"ಹವು":True,
"ಹಾಷಿಷ್":True,
"ಹಾಸಲು":True,
"ಹಾಸಿಗೆ":True,
"ಹಾಸಿಗೆಹಿಡಿ":True,
"ಹಾಸು":True,
"ಹಾಸುಗಲ್ಲು":True,
"ಹಾಸುಹೊಕ್ಕು":True,
"ಹಾಸ್ಯ":True,
"ಹಾಸ್ಯಗಾರ":True,
"ಹಾಸ್ಯಚಿತ್ರ":True,
"ಹಾಸ್ವಾಸ್ಪದ":True,
"ಹಾಹಾಕಾರ":True,
"ಹಾಳತ":True,
"ಹಾಳಾಗು":True,
"ಹಾಳು":True,
"ಹಾಳುಪಾಳು":True,
"ಹಾಳುಬೀಳು":True,
"ಹಾಳುಮಾಡು":True,
"ಹಾಳುಮೂಳು":True,
"ಹಾಳುಸುರಿ":True,
"ಹಾಳುಹರಟೆ":True,
"ಹಾಳೂರು":True,
"ಹಾಳೆ":True,
"ಹಿಂಗಾರು":True,
"ಹಿಂಗಿಸು":True,
"ಹಿಂಗು":True,
"ಹಿಂಜರಿ":True,
"ಹರಿಜರಿಕೆ":True,
"ಹಿಂಜು":True,
"ಹಿಂಡಿ":True,
"ಹಿಂಡು":True,
"ಹಿಂದು":True,
"ಹಿಂದುಳಿ":True,
"ಹಿಂದೆ":True,
"ಹಿಂದೆಗೆ":True,
"ಹಿಂದೇಟು":True,
"ಹಿಂಬಡತಿ":True,
"ಹಿಂಬದಿ":True,
"ಹಿಂಬಾಲಕ":True,
"ಹಿಂಬಾಲಿಸು":True,
"ಹಿಂಭಾಗ":True,
"ಹಿಂಸಾಚಾರ":True,
"ಹಿಂಸಿಸು":True,
"ಹಿಂಸೆ":True,
"ಹಿಕ್ಮತ್ತು":True,
"ಹಿಕ್ಮತ್ತುಗಾರ":True,
"ಹಿಗ್ಗಲಿಸು":True,
"ಹಿಗ್ಗಾಮುಗ್ಗ":True,
"ಹಿಗ್ಗು":True,
"ಹಿಚುಕು":True,
"ಹಿಟ್ಟು":True,
"ಹಿಡಿಮಾಡು":True,
"ಹಿಡಿ":True,
"ಹಿಡಿಕೆ":True,
"ಹಿಡಿತ":True,
"ಹಿಡುವಳಿ":True,
"ಹಿಡುವಳಿದಾರ":True,
"ಹಿತ":True,
"ಹಿತಕರ":True,
"ಹಿತಚಿಂತಕ":True,
"ಹಿತವಚನ":True,
"ಹಿತಶತ್ತು":True,
"ಹಿತಾಸಕ್ತಿ":True,
"ಹಿತೈಷಿ":True,
"ಹಿತೋಪದೇಶ":True,
"ಹಿತ್ತಲು":True,
"ಹಿತ್ತಾಳೆ":True,
"ಹಿತ್ತಾಳೆಕಿವಿ":True,
"ಹಿತ್ತಿಲು":True,
"ಹಿನ್ನಡೆ":True,
"ಹಿನ್ನಾಡು":True,
"ಹಿನ್ನುಡಿ":True,
"ನಿಮ":True,
"ಹಿಮನದಿ":True,
"ಹಿಮಪಾತ":True,
"ಹಿಮ್ಮಡಿ":True,
"ಹಿಮ್ಮಟ್ಟಸು":True,
"ಹಿಮ್ಮಟ್ಟು":True,
"ಹಿಮ್ಮಳ":True,
"ಹಿಯ್ಯಾಳಿಕೆ":True,
"ಹಿಯ್ಯಾಳಿಸು":True,
"ಹಿರಣ್ಯ":True,
"ಹಿರಿ":True,
"ಹಿರಿತನ":True,
"ಹಿರಿದು":True,
"ಹಿರಿಮೆ":True,
"ಹಿರಿಯ":True,
"ಹಿರಿಹಿಗ್ಗು":True,
"ಹಿಲಾಲು":True,
"ಹಿಸುಕು":True,
"ಹಿಸ್ಸೆ":True,
"ಹಿಸ್ಸೆದಾರ":True,
"ಹೀಗಳ":True,
"ಹೀಗೆ":True,
"ಹೀಚು":True,
"ಹೀನ":True,
"ಹೀನತ":True,
"ಹೀನತೆ":True,
"ಹೀನದೇಶೆ":True,
"ಹೀನನುಡಿ":True,
"ಹೀನಾಮಾನ":True,
"ಹೀನಾಯ":True,
"ಹೀನೈಸು":True,
"ಹೀಯಾಳಿಕೆ":True,
"ಹೀಯಾಳಿಸು":True,
"ಹೀರು":True,
"ಹುಂಜ":True,
"ಹುಂಡಿ":True,
"ಹುಂಬ":True,
"ಹುಕುಂ":True,
"ಹುಕ್ಕಾ":True,
"ಹುಗಿ":True,
"ಹುಚ್ಚ":True,
"ಹುಚ್ಚಾಟ":True,
"ಹುಚ್ಚಾಟಕೆ":True,
"ಹುಚ್ಚಾಬಟ್ಟೆ":True,
"ಹುಚ್ಚಿ":True,
"ಹುಚ್ಚು":True,
"ಹುಚ್ಚುತನ":True,
"ಹುಚ್ಚುಮಳೆ":True,
"ಹುಚ್ಚುಹಿಡಿ":True,
"ಹುಚ್ಚುಹೊಳೆ":True,
"ಹುಟ್ಟಿಸು":True,
"ಹುಟ್ಟು":True,
"ಹುಟ್ಟುಗುಣ":True,
"ಹುಟ್ಟುವಳಿ":True,
"ಹುಟ್ಟುಹಬ್ಬ":True,
"ಹುಟ್ಟುಹಾಕು":True,
"ಹುಡಿ":True,
"ಹುಡಿಮಾಡು":True,
"ಹುಡುಕಾಟ":True,
"ಹುಡುಕು":True,
"ಹುಡುಗ":True,
"ಹುಡುಗಾಟ":True,
"ಹುಡುಗಿ":True,
"ಹುಡುಗು":True,
"ಹುಡುಗುತನ":True,
"ಹುಡುಗುಬುದ್ದಿ":True,
"ಹುಣ್ಣಿಮೆ":True,
"ಹುಣ್ಣು":True,
"ಹುತಾತ್ಮ":True,
"ಹುದುಗು":True,
"ಹುದ್ದೆ":True,
"ಹುನ್ನಾರ":True,
"ಹುಬ್ಬು":True,
"ಹುಬ್ಬಗಂಟಕ್ಕು":True,
"ಹಮ್ಮಸ್ಸು":True,
"ಹುಯಿಲಿಡು":True,
"ಹುಯಿಲು":True,
"ಹುರಿ":True,
"ಹುರಿದುಂಬಿಸು":True,
"ಹುರಿಯಾಳು":True,
"ಹುರುಡು":True,
"ಹುರುಪು":True,
"ಹುರುಳು":True,
"ಹುಲಿ":True,
"ಹುಲು":True,
"ಹುಲುಬಯಕೆ":True,
"ಹುಲುಮನುಜ":True,
"ಹುಲುಸು":True,
"ಹುಲ್ಲು":True,
"ಹುಲ್ಲುಗಾವಲು":True,
"ಹುಲ್ಲುಮೆದೆ":True,
"ಹುಲ್ಲೆ":True,
"ಹುಷಾರಿ":True,
"ಹುಸಿ":True,
"ಹುಸಿಗುಂಡುಮ ಹುಸಿನಗು":True,
"ಹುಸಿಮುನಿಸು":True,
"ಹುಳಿ":True,
"ಹುಳಿಹಿಂಡು":True,
"ಹುಳು":True,
"ಹುಳುಕಡ್ಡ":True,
"ಹುಳುಕು":True,
"ಹುಳುಕುಹಲ್ಲು":True,
"ಹೂಂ":True,
"ಹೂಜಿ":True,
"ಹೂಟ":True,
"ಹೂಡು":True,
"ಹೂತಿಡು":True,
"ಹೂದಾನಿ ಹೋದೋಟ":True,
"ಹೂಬಿಸಿಲು":True,
"ಹೂವಾಡಗಿತ್ತಿ":True,
"ಹೂವಾಡಿಗ":True,
"ಹೂವು":True,
"ಹೂಳು":True,
"ಹೃತ್ಪೂರ್ವಕ":True,
"ಹೃದಯ":True,
"ಹೃದಯಂಗಮ":True,
"ಹೃದಯಕ್ರಿಯೆ":True,
"ಹೃದಯಲೇಖ":True,
"ಹೃದಯಲೇಖಿ":True,
"ಹೇದಯವಂತಿಕೆ":True,
"ಹೃದಯವಿದ್ರಾವಕ":True,
} | wordmatki/kannada.py | kannada = {
"ಅಂಕ":True,
"ಅಂಕಗಣಿತ":True,
"ಅಂಕಣ":True,
"ಅಂಕಣಗಾರ":True,
"ಅಂಕಿ":True,
"ಅಂಕಿ":True,
"ಅಂಕಿಅಂಶ":True,
"ಅಂಕಿತ":True,
"ಅಂಕಿತನಾಮ":True,
"ಅಂಕುಡೊಂಕು":True,
"ಅಂಕುರ":True,
"ಅಂಕುರಾರ್ಪಣ":True,
"ಅಂಕುರಿಸು":True,
"ಅಂಕುಶ":True,
"ಅಂಕೆ":True,
"ಅಂಗ":True,
"ಅಂಗಚೇಷ್ಟೆ":True,
"ಅಂಗಡಿ":True,
"ಅಂಗಡಿಕೇರಿ":True,
"ಅಂಗಡಿಬೀದಿ":True,
"ಅಂಗಣ":True,
"ಅಂಗತ":True,
"ಅಂಗತ್ತ":True,
"ಅಂಗನೆ":True,
"ಅಂಗಭಾಗ":True,
"ಅಂಗಮರ್ದ":True,
"ಅಂಗಮರ್ದನ":True,
"ಅಂಗರಕ್ಷ":True,
"ಅಂಗರಕ್ಷಕ":True,
"ಅಂಗರಕ್ಷೆ":True,
"ಅಂಗರಚನಾಶಾಸ್ತ್ರ":True,
"ಅಂಗಲಾಚು":True,
"ಅಂಗವಸ್ತ್ರ":True,
"ಅಂಗವಿಕಲಗೊಳಿಸು":True,
"ಅಂಗವಿಕಾರ":True,
"ಅಂಗಸಂಗ":True,
"ಅಂಗಸಂಸ್ಥೆ":True,
"ಅಂಗಸಾಧನೆ":True,
"ಅಂಗಳ":True,
"ಅಂಗಾರಕ":True,
"ಅಂಗಾಲು":True,
"ಅಂಗಿ":True,
"ಅಂಗೀಕರಿಸದಿರು":True,
"ಅಂಗೀಕರಿಸು":True,
"ಅಂಗೀಕಾರ":True,
"ಅಂಗೀಕಾರಾರ್ಹ":True,
"ಅಂಗೀಕಾರಾರ್ಹತೆ":True,
"ಅಂಗೀಕೃತ":True,
"ಅಂಗುಟ":True,
"ಅಂಗುಲ":True,
"ಅಂಗುಲಿ":True,
"ಅಂಗುಲೀಯ":True,
"ಅಂಗುಷ್ಠ":True,
"ಅಂಗುಳು":True,
"ಅಂಗೈ":True,
"ಅಂಘ್ರಿ":True,
"ಅಂಚು":True,
"ಅಂಚಿ":True,
"ಅಂಚೆಯಾಳು":True,
"ಅಂಚಿಕಚೇರಿ":True,
"ಅಂಜನ":True,
"ಅಂಜಲಿ":True,
"ಅಂಜಿಕೆ":True,
"ಅಂಜು":True,
"ಅಂಜುಕುಳಿ":True,
"ಅಂಜುಗುಳಿ":True,
"ಅಂಜೂರ":True,
"ಅಂಟಿಕೊ":True,
"ಅಂಟಿಸು":True,
"ಅಂಟು":True,
"ಅಂಟುಜಾಡ್ಯ":True,
"ಅಂಟುಪುರಲೆ":True,
"ಅಂಟುರೋಗ":True,
"ಅಂಡ":True,
"ಅಂಡಕೋಶ":True,
"ಅಂಡಜ":True,
"ಅಂಡಲೆ":True,
"ಅಂಡವಾಯ":True,
"ಅಂಡು":True,
"ಅಂತ":True,
"ಅಂತಃಕರಣ":True,
"ಅಂತಃಕಲಹ":True,
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"ಹಾಳಾಗು":True,
"ಹಾಳು":True,
"ಹಾಳುಪಾಳು":True,
"ಹಾಳುಬೀಳು":True,
"ಹಾಳುಮಾಡು":True,
"ಹಾಳುಮೂಳು":True,
"ಹಾಳುಸುರಿ":True,
"ಹಾಳುಹರಟೆ":True,
"ಹಾಳೂರು":True,
"ಹಾಳೆ":True,
"ಹಿಂಗಾರು":True,
"ಹಿಂಗಿಸು":True,
"ಹಿಂಗು":True,
"ಹಿಂಜರಿ":True,
"ಹರಿಜರಿಕೆ":True,
"ಹಿಂಜು":True,
"ಹಿಂಡಿ":True,
"ಹಿಂಡು":True,
"ಹಿಂದು":True,
"ಹಿಂದುಳಿ":True,
"ಹಿಂದೆ":True,
"ಹಿಂದೆಗೆ":True,
"ಹಿಂದೇಟು":True,
"ಹಿಂಬಡತಿ":True,
"ಹಿಂಬದಿ":True,
"ಹಿಂಬಾಲಕ":True,
"ಹಿಂಬಾಲಿಸು":True,
"ಹಿಂಭಾಗ":True,
"ಹಿಂಸಾಚಾರ":True,
"ಹಿಂಸಿಸು":True,
"ಹಿಂಸೆ":True,
"ಹಿಕ್ಮತ್ತು":True,
"ಹಿಕ್ಮತ್ತುಗಾರ":True,
"ಹಿಗ್ಗಲಿಸು":True,
"ಹಿಗ್ಗಾಮುಗ್ಗ":True,
"ಹಿಗ್ಗು":True,
"ಹಿಚುಕು":True,
"ಹಿಟ್ಟು":True,
"ಹಿಡಿಮಾಡು":True,
"ಹಿಡಿ":True,
"ಹಿಡಿಕೆ":True,
"ಹಿಡಿತ":True,
"ಹಿಡುವಳಿ":True,
"ಹಿಡುವಳಿದಾರ":True,
"ಹಿತ":True,
"ಹಿತಕರ":True,
"ಹಿತಚಿಂತಕ":True,
"ಹಿತವಚನ":True,
"ಹಿತಶತ್ತು":True,
"ಹಿತಾಸಕ್ತಿ":True,
"ಹಿತೈಷಿ":True,
"ಹಿತೋಪದೇಶ":True,
"ಹಿತ್ತಲು":True,
"ಹಿತ್ತಾಳೆ":True,
"ಹಿತ್ತಾಳೆಕಿವಿ":True,
"ಹಿತ್ತಿಲು":True,
"ಹಿನ್ನಡೆ":True,
"ಹಿನ್ನಾಡು":True,
"ಹಿನ್ನುಡಿ":True,
"ನಿಮ":True,
"ಹಿಮನದಿ":True,
"ಹಿಮಪಾತ":True,
"ಹಿಮ್ಮಡಿ":True,
"ಹಿಮ್ಮಟ್ಟಸು":True,
"ಹಿಮ್ಮಟ್ಟು":True,
"ಹಿಮ್ಮಳ":True,
"ಹಿಯ್ಯಾಳಿಕೆ":True,
"ಹಿಯ್ಯಾಳಿಸು":True,
"ಹಿರಣ್ಯ":True,
"ಹಿರಿ":True,
"ಹಿರಿತನ":True,
"ಹಿರಿದು":True,
"ಹಿರಿಮೆ":True,
"ಹಿರಿಯ":True,
"ಹಿರಿಹಿಗ್ಗು":True,
"ಹಿಲಾಲು":True,
"ಹಿಸುಕು":True,
"ಹಿಸ್ಸೆ":True,
"ಹಿಸ್ಸೆದಾರ":True,
"ಹೀಗಳ":True,
"ಹೀಗೆ":True,
"ಹೀಚು":True,
"ಹೀನ":True,
"ಹೀನತ":True,
"ಹೀನತೆ":True,
"ಹೀನದೇಶೆ":True,
"ಹೀನನುಡಿ":True,
"ಹೀನಾಮಾನ":True,
"ಹೀನಾಯ":True,
"ಹೀನೈಸು":True,
"ಹೀಯಾಳಿಕೆ":True,
"ಹೀಯಾಳಿಸು":True,
"ಹೀರು":True,
"ಹುಂಜ":True,
"ಹುಂಡಿ":True,
"ಹುಂಬ":True,
"ಹುಕುಂ":True,
"ಹುಕ್ಕಾ":True,
"ಹುಗಿ":True,
"ಹುಚ್ಚ":True,
"ಹುಚ್ಚಾಟ":True,
"ಹುಚ್ಚಾಟಕೆ":True,
"ಹುಚ್ಚಾಬಟ್ಟೆ":True,
"ಹುಚ್ಚಿ":True,
"ಹುಚ್ಚು":True,
"ಹುಚ್ಚುತನ":True,
"ಹುಚ್ಚುಮಳೆ":True,
"ಹುಚ್ಚುಹಿಡಿ":True,
"ಹುಚ್ಚುಹೊಳೆ":True,
"ಹುಟ್ಟಿಸು":True,
"ಹುಟ್ಟು":True,
"ಹುಟ್ಟುಗುಣ":True,
"ಹುಟ್ಟುವಳಿ":True,
"ಹುಟ್ಟುಹಬ್ಬ":True,
"ಹುಟ್ಟುಹಾಕು":True,
"ಹುಡಿ":True,
"ಹುಡಿಮಾಡು":True,
"ಹುಡುಕಾಟ":True,
"ಹುಡುಕು":True,
"ಹುಡುಗ":True,
"ಹುಡುಗಾಟ":True,
"ಹುಡುಗಿ":True,
"ಹುಡುಗು":True,
"ಹುಡುಗುತನ":True,
"ಹುಡುಗುಬುದ್ದಿ":True,
"ಹುಣ್ಣಿಮೆ":True,
"ಹುಣ್ಣು":True,
"ಹುತಾತ್ಮ":True,
"ಹುದುಗು":True,
"ಹುದ್ದೆ":True,
"ಹುನ್ನಾರ":True,
"ಹುಬ್ಬು":True,
"ಹುಬ್ಬಗಂಟಕ್ಕು":True,
"ಹಮ್ಮಸ್ಸು":True,
"ಹುಯಿಲಿಡು":True,
"ಹುಯಿಲು":True,
"ಹುರಿ":True,
"ಹುರಿದುಂಬಿಸು":True,
"ಹುರಿಯಾಳು":True,
"ಹುರುಡು":True,
"ಹುರುಪು":True,
"ಹುರುಳು":True,
"ಹುಲಿ":True,
"ಹುಲು":True,
"ಹುಲುಬಯಕೆ":True,
"ಹುಲುಮನುಜ":True,
"ಹುಲುಸು":True,
"ಹುಲ್ಲು":True,
"ಹುಲ್ಲುಗಾವಲು":True,
"ಹುಲ್ಲುಮೆದೆ":True,
"ಹುಲ್ಲೆ":True,
"ಹುಷಾರಿ":True,
"ಹುಸಿ":True,
"ಹುಸಿಗುಂಡುಮ ಹುಸಿನಗು":True,
"ಹುಸಿಮುನಿಸು":True,
"ಹುಳಿ":True,
"ಹುಳಿಹಿಂಡು":True,
"ಹುಳು":True,
"ಹುಳುಕಡ್ಡ":True,
"ಹುಳುಕು":True,
"ಹುಳುಕುಹಲ್ಲು":True,
"ಹೂಂ":True,
"ಹೂಜಿ":True,
"ಹೂಟ":True,
"ಹೂಡು":True,
"ಹೂತಿಡು":True,
"ಹೂದಾನಿ ಹೋದೋಟ":True,
"ಹೂಬಿಸಿಲು":True,
"ಹೂವಾಡಗಿತ್ತಿ":True,
"ಹೂವಾಡಿಗ":True,
"ಹೂವು":True,
"ಹೂಳು":True,
"ಹೃತ್ಪೂರ್ವಕ":True,
"ಹೃದಯ":True,
"ಹೃದಯಂಗಮ":True,
"ಹೃದಯಕ್ರಿಯೆ":True,
"ಹೃದಯಲೇಖ":True,
"ಹೃದಯಲೇಖಿ":True,
"ಹೇದಯವಂತಿಕೆ":True,
"ಹೃದಯವಿದ್ರಾವಕ":True,
} | 0.147893 | 0.9601 |
from __future__ import unicode_literals
from StringIO import StringIO
import binascii
import os
import struct
import time
import win32file
import yaml
import glob
from _analyzemft.mftsession import _MftSession
from disk_analysis import DiskAnalysis
from environment_settings import Partitions, Disks, OperatingSystem # , EnvironmentVariable
from mbr import Mbr
from vbr import Vbr
from settings import LONGLONGSIZE, BYTESIZE, WORDSIZE
from utils.utils import get_local_drives, create_driver_service, start_service, stop_and_delete_driver_service
from utils.utils_rawstring import decodeATRHeader, decode_data_runs, get_physical_drives
from winpmem import _Image
from filecatcher.archives import _Archives
from utils.vss import _VSS
class _Dump(object):
def __init__(self, params):
self.computer_name = params['computer_name']
self.output_dir = params['output_dir']
self.logger = params['logger']
self.mft_export = yaml.load(params['mft_export'])
self.rand_ext = params['rand_ext']
self.userprofile = params['USERPROFILE']
self.params = params
def __extract_mft(self):
local_drives = get_local_drives()
for local_drive in local_drives:
self.logger.info('Exporting MFT for drive : ' + local_drive)
ntfsdrive = file('\\\\.\\' + local_drive.replace('\\', ''), 'rb')
path_current_mft = self.output_dir + '\\' + self.computer_name + '_mft_' + local_drive[0] + '.mft'
if os.name == 'nt':
# poor win can't seek a drive to individual bytes..only 1 sector at a time..
# convert MBR to stringio to make it seekable
ntfs = ntfsdrive.read(512)
ntfsfile = StringIO(ntfs)
else:
ntfsfile = ntfsdrive
# parse the MBR for this drive to get the bytes per sector,sectors per cluster and MFT location.
# bytes per sector
ntfsfile.seek(0x0b)
bytesPerSector = ntfsfile.read(WORDSIZE)
bytesPerSector = struct.unpack(b'<h', binascii.unhexlify(binascii.hexlify(bytesPerSector)))[0]
# sectors per cluster
ntfsfile.seek(0x0d)
sectorsPerCluster = ntfsfile.read(BYTESIZE)
sectorsPerCluster = struct.unpack(b'<b', binascii.unhexlify(binascii.hexlify(sectorsPerCluster)))[0]
# get mftlogical cluster number
ntfsfile.seek(0x30)
cno = ntfsfile.read(LONGLONGSIZE)
mftClusterNumber = struct.unpack(b'<q', binascii.unhexlify(binascii.hexlify(cno)))[0]
# MFT is then at NTFS + (bytesPerSector*sectorsPerCluster*mftClusterNumber)
mftloc = long(bytesPerSector * sectorsPerCluster * mftClusterNumber)
ntfsdrive.seek(0)
ntfsdrive.seek(mftloc)
mftraw = ntfsdrive.read(1024)
# We've got the MFT record for the MFT itself.
# parse it to the DATA section, decode the data runs and send the MFT over TCP
mftDict = {}
mftDict['attr_off'] = struct.unpack(b"<H", mftraw[20:22])[0]
ReadPtr = mftDict['attr_off']
with open(path_current_mft, 'wb') as output:
while ReadPtr < len(mftraw):
ATRrecord = decodeATRHeader(mftraw[ReadPtr:])
if ATRrecord['type'] == 0x80:
dataruns = mftraw[ReadPtr + ATRrecord['run_off']:ReadPtr + ATRrecord['len']]
prevCluster = None
prevSeek = 0
for length, cluster in decode_data_runs(dataruns):
if prevCluster is None:
ntfsdrive.seek(cluster * bytesPerSector * sectorsPerCluster)
prevSeek = ntfsdrive.tell()
r_data = ntfsdrive.read(length * bytesPerSector * sectorsPerCluster)
output.write(r_data)
prevCluster = cluster
else:
ntfsdrive.seek(prevSeek)
newpos = prevSeek + (cluster * bytesPerSector * sectorsPerCluster)
ntfsdrive.seek(newpos)
prevSeek = ntfsdrive.tell()
r_data = ntfsdrive.read(length * bytesPerSector * sectorsPerCluster)
output.write(r_data)
prevCluster = cluster
break
if ATRrecord['len'] > 0:
ReadPtr = ReadPtr + ATRrecord['len']
yield path_current_mft
def csv_mft(self):
"""Exports the MFT from each local drives and creates a csv from it."""
# export on csv
for path_current_mft in self.__extract_mft():
if self.mft_export:
session = _MftSession(self.logger, path_current_mft, path_current_mft.replace('.mft', self.rand_ext))
session.open_files()
session.process_mft_file()
def json_mft(self):
for path_current_mft in self.__extract_mft():
if self.mft_export:
session = _MftSession(self.logger, path_current_mft, path_current_mft.replace('.mft', self.rand_ext),
True)
session.open_files()
session.process_mft_file()
def csv_export_dd(self):
"""Dumps the disk image"""
for d, size in get_physical_drives():
already = 0
buff = 65536
with open(self.output_dir + '\\' + self.computer_name + '.dd', 'wb') as fw:
with open(d, 'rb') as fr:
while already < int(size):
already += buff
r = fr.read(buff)
fw.write(r)
def json_export_dd(self):
self.csv_export_dd()
def csv_export_ram(self):
"""Dump ram using winpmem"""
hSvc = create_driver_service(self.logger)
start_service(hSvc, self.logger)
try:
fd = win32file.CreateFile(
"\\\\.\\pmem",
win32file.GENERIC_READ | win32file.GENERIC_WRITE,
win32file.FILE_SHARE_READ | win32file.FILE_SHARE_WRITE,
None,
win32file.OPEN_EXISTING,
win32file.FILE_ATTRIBUTE_NORMAL,
None)
try:
t = time.time()
image = _Image(fd)
self.logger.info("Imaging to " + self.output_dir + '\\' + self.computer_name + '_memdump.raw')
image.DumpWithRead(self.output_dir + '\\' + self.computer_name + '_memdump.raw')
self.logger.info("Completed in %s seconds" % (time.time() - t))
finally:
win32file.CloseHandle(fd)
finally:
stop_and_delete_driver_service(hSvc)
def json_mbr(self):
self.csv_mbr()
def csv_mbr(self):
"""Extract MBR and BootLoader"""
informations = DiskAnalysis(self.output_dir)
partition = Partitions(self.output_dir, self.logger)
disk = Disks()
operatingSystem = OperatingSystem()
# env_var = EnvironmentVariable()
mbr = Mbr(self.output_dir)
informations.os = operatingSystem.os_information(informations.currentMachine)
informations.listDisks = disk.get_disk_information(informations.currentMachine)
self.logger.info('MBR Extracting')
for d in informations.listDisks:
informations.mbrDisk = mbr.mbr_parsing(d.deviceID)
mbr.boot_loader_disassembly()
for p in informations.mbrDisk.partitions:
if p.state == "ACTIVE":
vbr = Vbr(d.deviceID, p.sector_offset, self.output_dir)
self.logger.info('VBR Extracting')
vbr.extract_vbr()
vbr.vbrDisassembly()
self.logger.info('BootLoader Extracting')
informations.envVarList = os.environ
informations.listPartitions = partition.partition_information(informations.currentMachine)
informations.save_informations()
def __get_registry(self):
arch = _Archives(os.path.join(self.output_dir, 'dump_registry.zip'), self.logger)
if hasattr(self, 'root_reg'):
files_to_zip = [os.path.join(self.root_reg, f) for f in os.listdir(self.root_reg) if
os.path.isfile(os.path.join(self.root_reg, f))]
path_ntuserdat = os.path.join(self.userprofile, '*', 'NTUSER.DAT')
files_to_zip.extend([os.path.join(_VSS._get_instance(self.params, os.path.splitdrive(f)[0])._return_root(),
os.path.splitdrive(f)[1].lstrip('\\')) for f in glob.glob(path_ntuserdat) if
os.path.isfile(f)])
for f in files_to_zip:
arch.record(f)
def csv_registry(self):
self.__get_registry()
def json_registry(self):
self.csv_registry() | Fastir_Collector/dump/dump.py | from __future__ import unicode_literals
from StringIO import StringIO
import binascii
import os
import struct
import time
import win32file
import yaml
import glob
from _analyzemft.mftsession import _MftSession
from disk_analysis import DiskAnalysis
from environment_settings import Partitions, Disks, OperatingSystem # , EnvironmentVariable
from mbr import Mbr
from vbr import Vbr
from settings import LONGLONGSIZE, BYTESIZE, WORDSIZE
from utils.utils import get_local_drives, create_driver_service, start_service, stop_and_delete_driver_service
from utils.utils_rawstring import decodeATRHeader, decode_data_runs, get_physical_drives
from winpmem import _Image
from filecatcher.archives import _Archives
from utils.vss import _VSS
class _Dump(object):
def __init__(self, params):
self.computer_name = params['computer_name']
self.output_dir = params['output_dir']
self.logger = params['logger']
self.mft_export = yaml.load(params['mft_export'])
self.rand_ext = params['rand_ext']
self.userprofile = params['USERPROFILE']
self.params = params
def __extract_mft(self):
local_drives = get_local_drives()
for local_drive in local_drives:
self.logger.info('Exporting MFT for drive : ' + local_drive)
ntfsdrive = file('\\\\.\\' + local_drive.replace('\\', ''), 'rb')
path_current_mft = self.output_dir + '\\' + self.computer_name + '_mft_' + local_drive[0] + '.mft'
if os.name == 'nt':
# poor win can't seek a drive to individual bytes..only 1 sector at a time..
# convert MBR to stringio to make it seekable
ntfs = ntfsdrive.read(512)
ntfsfile = StringIO(ntfs)
else:
ntfsfile = ntfsdrive
# parse the MBR for this drive to get the bytes per sector,sectors per cluster and MFT location.
# bytes per sector
ntfsfile.seek(0x0b)
bytesPerSector = ntfsfile.read(WORDSIZE)
bytesPerSector = struct.unpack(b'<h', binascii.unhexlify(binascii.hexlify(bytesPerSector)))[0]
# sectors per cluster
ntfsfile.seek(0x0d)
sectorsPerCluster = ntfsfile.read(BYTESIZE)
sectorsPerCluster = struct.unpack(b'<b', binascii.unhexlify(binascii.hexlify(sectorsPerCluster)))[0]
# get mftlogical cluster number
ntfsfile.seek(0x30)
cno = ntfsfile.read(LONGLONGSIZE)
mftClusterNumber = struct.unpack(b'<q', binascii.unhexlify(binascii.hexlify(cno)))[0]
# MFT is then at NTFS + (bytesPerSector*sectorsPerCluster*mftClusterNumber)
mftloc = long(bytesPerSector * sectorsPerCluster * mftClusterNumber)
ntfsdrive.seek(0)
ntfsdrive.seek(mftloc)
mftraw = ntfsdrive.read(1024)
# We've got the MFT record for the MFT itself.
# parse it to the DATA section, decode the data runs and send the MFT over TCP
mftDict = {}
mftDict['attr_off'] = struct.unpack(b"<H", mftraw[20:22])[0]
ReadPtr = mftDict['attr_off']
with open(path_current_mft, 'wb') as output:
while ReadPtr < len(mftraw):
ATRrecord = decodeATRHeader(mftraw[ReadPtr:])
if ATRrecord['type'] == 0x80:
dataruns = mftraw[ReadPtr + ATRrecord['run_off']:ReadPtr + ATRrecord['len']]
prevCluster = None
prevSeek = 0
for length, cluster in decode_data_runs(dataruns):
if prevCluster is None:
ntfsdrive.seek(cluster * bytesPerSector * sectorsPerCluster)
prevSeek = ntfsdrive.tell()
r_data = ntfsdrive.read(length * bytesPerSector * sectorsPerCluster)
output.write(r_data)
prevCluster = cluster
else:
ntfsdrive.seek(prevSeek)
newpos = prevSeek + (cluster * bytesPerSector * sectorsPerCluster)
ntfsdrive.seek(newpos)
prevSeek = ntfsdrive.tell()
r_data = ntfsdrive.read(length * bytesPerSector * sectorsPerCluster)
output.write(r_data)
prevCluster = cluster
break
if ATRrecord['len'] > 0:
ReadPtr = ReadPtr + ATRrecord['len']
yield path_current_mft
def csv_mft(self):
"""Exports the MFT from each local drives and creates a csv from it."""
# export on csv
for path_current_mft in self.__extract_mft():
if self.mft_export:
session = _MftSession(self.logger, path_current_mft, path_current_mft.replace('.mft', self.rand_ext))
session.open_files()
session.process_mft_file()
def json_mft(self):
for path_current_mft in self.__extract_mft():
if self.mft_export:
session = _MftSession(self.logger, path_current_mft, path_current_mft.replace('.mft', self.rand_ext),
True)
session.open_files()
session.process_mft_file()
def csv_export_dd(self):
"""Dumps the disk image"""
for d, size in get_physical_drives():
already = 0
buff = 65536
with open(self.output_dir + '\\' + self.computer_name + '.dd', 'wb') as fw:
with open(d, 'rb') as fr:
while already < int(size):
already += buff
r = fr.read(buff)
fw.write(r)
def json_export_dd(self):
self.csv_export_dd()
def csv_export_ram(self):
"""Dump ram using winpmem"""
hSvc = create_driver_service(self.logger)
start_service(hSvc, self.logger)
try:
fd = win32file.CreateFile(
"\\\\.\\pmem",
win32file.GENERIC_READ | win32file.GENERIC_WRITE,
win32file.FILE_SHARE_READ | win32file.FILE_SHARE_WRITE,
None,
win32file.OPEN_EXISTING,
win32file.FILE_ATTRIBUTE_NORMAL,
None)
try:
t = time.time()
image = _Image(fd)
self.logger.info("Imaging to " + self.output_dir + '\\' + self.computer_name + '_memdump.raw')
image.DumpWithRead(self.output_dir + '\\' + self.computer_name + '_memdump.raw')
self.logger.info("Completed in %s seconds" % (time.time() - t))
finally:
win32file.CloseHandle(fd)
finally:
stop_and_delete_driver_service(hSvc)
def json_mbr(self):
self.csv_mbr()
def csv_mbr(self):
"""Extract MBR and BootLoader"""
informations = DiskAnalysis(self.output_dir)
partition = Partitions(self.output_dir, self.logger)
disk = Disks()
operatingSystem = OperatingSystem()
# env_var = EnvironmentVariable()
mbr = Mbr(self.output_dir)
informations.os = operatingSystem.os_information(informations.currentMachine)
informations.listDisks = disk.get_disk_information(informations.currentMachine)
self.logger.info('MBR Extracting')
for d in informations.listDisks:
informations.mbrDisk = mbr.mbr_parsing(d.deviceID)
mbr.boot_loader_disassembly()
for p in informations.mbrDisk.partitions:
if p.state == "ACTIVE":
vbr = Vbr(d.deviceID, p.sector_offset, self.output_dir)
self.logger.info('VBR Extracting')
vbr.extract_vbr()
vbr.vbrDisassembly()
self.logger.info('BootLoader Extracting')
informations.envVarList = os.environ
informations.listPartitions = partition.partition_information(informations.currentMachine)
informations.save_informations()
def __get_registry(self):
arch = _Archives(os.path.join(self.output_dir, 'dump_registry.zip'), self.logger)
if hasattr(self, 'root_reg'):
files_to_zip = [os.path.join(self.root_reg, f) for f in os.listdir(self.root_reg) if
os.path.isfile(os.path.join(self.root_reg, f))]
path_ntuserdat = os.path.join(self.userprofile, '*', 'NTUSER.DAT')
files_to_zip.extend([os.path.join(_VSS._get_instance(self.params, os.path.splitdrive(f)[0])._return_root(),
os.path.splitdrive(f)[1].lstrip('\\')) for f in glob.glob(path_ntuserdat) if
os.path.isfile(f)])
for f in files_to_zip:
arch.record(f)
def csv_registry(self):
self.__get_registry()
def json_registry(self):
self.csv_registry() | 0.398641 | 0.067547 |
__author__ = '<NAME>'
__version__ = '1.0.0'
import argparse
import hashlib
import json
import os
import requests
import select
import socket
import time
parser = argparse.ArgumentParser()
parser.add_argument('--virus-total', action='store_true')
parser.add_argument('--team-cymru', action='store_true')
args = parser.parse_args()
def collect():
directory = os.scandir('.')
files = []
for item in directory:
if item.is_file():
files.append(item.name)
fingerprint(files)
def fingerprint(files):
evidence = {}
for filename in files:
md5 = hashlib.md5()
blocksize = 65536
with open(filename,'rb') as item:
filebuffer = item.read(blocksize)
while len(filebuffer) > 0:
md5.update(filebuffer)
filebuffer = item.read(blocksize)
digest = md5.hexdigest()
evidence[digest] = filename
total = len(evidence)
banner = "[+] Pivoting to " + data_source + " with " + str(total) + " values of interest"
if data_source == 'VirusTotal' and total > 4:
minutes = str(int((total * 15) / 60))
seconds = time.time() + (total * 15)
future = time.gmtime(seconds)
timestamp = time.strftime("%H:%M:%S", future)
eta = " (ETA: " + minutes + " minutes, " + timestamp + ")."
print(banner + eta)
else:
print(banner + '.')
pivot(evidence)
def pivot_2_virus_total(evidence):
try:
vt = 'https://www.virustotal.com/api/v3/files/'
#key = ''
key = input("[>] VirusTotal API key: ")
for digest in evidence:
filename = evidence[digest]
with requests.session() as browser:
url = vt + digest
custom_headers = { 'x-apikey': key }
response = requests.get(url, headers = custom_headers)
if response.status_code == 200:
results = json.loads(response.content)['data']
attributes = results.get('attributes')
detected = attributes['last_analysis_stats']['malicious']
if detected > 0:
undetected = attributes['last_analysis_stats']['undetected']
scanner_count = detected + undetected
percent = str(detected) + '/' + str(scanner_count)
print(" --> " + percent, digest, filename)
if len(evidence) > 4:
time.sleep(15)
except:
print("[x] Failed to pivot to VirusTotal.")
exit()
def pivot_2_team_cymru(evidence):
try:
mhr = ('hash.cymru.com', 43)
hashes = ['begin']
for digest in evidence:
hashes.append(digest)
hashes.append('end')
hashes = '\n'.join(hashes)
client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
client.connect(mhr)
client.sendall(bytes(hashes,'UTF-8'))
data = client.recv(1)
on,off,out = select.select([client],[client],[client])
while on:
data += client.recv(2048)
time.sleep(.15)
on,off,out = select.select([client],[client],[client])
client.close()
results = data.decode().split('\n')[:-1]
del results[0:2]
for result in results:
percent = result.split(' ')[-1]
if percent != 'NO_DATA':
digest = result.split(' ')[0]
filename = evidence[digest]
print(" --> " + percent, digest, filename)
except:
print("[x] Failed to pivot to Team Cymru's Malware Hash Registry.")
exit()
if __name__ == "__main__":
if args.virus_total:
data_source = 'VirusTotal'
pivot = pivot_2_virus_total
elif args.team_cymru:
data_source = 'Team Cymru'
pivot = pivot_2_team_cymru
else:
data_source = 'VirusTotal'
pivot = pivot_2_virus_total
collect()
# REFERENCES
# https://developers.virustotal.com/reference#file-search
# https://stackoverflow.com/questions/22058048/hashing-a-file-in-python
# https://docs.python.org/3/library/os.html#os.scandir
# https://developers.google.com/edu/python/dict-files
# https://stackoverflow.com/questions/930397/getting-the-last-element-of-a-list
# https://gist.github.com/aunyks/042c2798383f016939c40aa1be4f4aaf | Python/pivot2osint.py | __author__ = '<NAME>'
__version__ = '1.0.0'
import argparse
import hashlib
import json
import os
import requests
import select
import socket
import time
parser = argparse.ArgumentParser()
parser.add_argument('--virus-total', action='store_true')
parser.add_argument('--team-cymru', action='store_true')
args = parser.parse_args()
def collect():
directory = os.scandir('.')
files = []
for item in directory:
if item.is_file():
files.append(item.name)
fingerprint(files)
def fingerprint(files):
evidence = {}
for filename in files:
md5 = hashlib.md5()
blocksize = 65536
with open(filename,'rb') as item:
filebuffer = item.read(blocksize)
while len(filebuffer) > 0:
md5.update(filebuffer)
filebuffer = item.read(blocksize)
digest = md5.hexdigest()
evidence[digest] = filename
total = len(evidence)
banner = "[+] Pivoting to " + data_source + " with " + str(total) + " values of interest"
if data_source == 'VirusTotal' and total > 4:
minutes = str(int((total * 15) / 60))
seconds = time.time() + (total * 15)
future = time.gmtime(seconds)
timestamp = time.strftime("%H:%M:%S", future)
eta = " (ETA: " + minutes + " minutes, " + timestamp + ")."
print(banner + eta)
else:
print(banner + '.')
pivot(evidence)
def pivot_2_virus_total(evidence):
try:
vt = 'https://www.virustotal.com/api/v3/files/'
#key = ''
key = input("[>] VirusTotal API key: ")
for digest in evidence:
filename = evidence[digest]
with requests.session() as browser:
url = vt + digest
custom_headers = { 'x-apikey': key }
response = requests.get(url, headers = custom_headers)
if response.status_code == 200:
results = json.loads(response.content)['data']
attributes = results.get('attributes')
detected = attributes['last_analysis_stats']['malicious']
if detected > 0:
undetected = attributes['last_analysis_stats']['undetected']
scanner_count = detected + undetected
percent = str(detected) + '/' + str(scanner_count)
print(" --> " + percent, digest, filename)
if len(evidence) > 4:
time.sleep(15)
except:
print("[x] Failed to pivot to VirusTotal.")
exit()
def pivot_2_team_cymru(evidence):
try:
mhr = ('hash.cymru.com', 43)
hashes = ['begin']
for digest in evidence:
hashes.append(digest)
hashes.append('end')
hashes = '\n'.join(hashes)
client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
client.connect(mhr)
client.sendall(bytes(hashes,'UTF-8'))
data = client.recv(1)
on,off,out = select.select([client],[client],[client])
while on:
data += client.recv(2048)
time.sleep(.15)
on,off,out = select.select([client],[client],[client])
client.close()
results = data.decode().split('\n')[:-1]
del results[0:2]
for result in results:
percent = result.split(' ')[-1]
if percent != 'NO_DATA':
digest = result.split(' ')[0]
filename = evidence[digest]
print(" --> " + percent, digest, filename)
except:
print("[x] Failed to pivot to Team Cymru's Malware Hash Registry.")
exit()
if __name__ == "__main__":
if args.virus_total:
data_source = 'VirusTotal'
pivot = pivot_2_virus_total
elif args.team_cymru:
data_source = 'Team Cymru'
pivot = pivot_2_team_cymru
else:
data_source = 'VirusTotal'
pivot = pivot_2_virus_total
collect()
# REFERENCES
# https://developers.virustotal.com/reference#file-search
# https://stackoverflow.com/questions/22058048/hashing-a-file-in-python
# https://docs.python.org/3/library/os.html#os.scandir
# https://developers.google.com/edu/python/dict-files
# https://stackoverflow.com/questions/930397/getting-the-last-element-of-a-list
# https://gist.github.com/aunyks/042c2798383f016939c40aa1be4f4aaf | 0.294519 | 0.087058 |
from __future__ import print_function, division, absolute_import
from .. import imgaug as ia
# TODO replace these imports with iap.XYZ
from ..parameters import StochasticParameter, Deterministic, DiscreteUniform, Uniform
import numpy as np
from scipy import ndimage
from skimage import draw
from skimage import data
from skimage import io
from skimage import util
import six.moves as sm
import random
from .meta import Augmenter
class Spot(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long
def __init__(self, sigma=0, name=None, deterministic=False, random_state=None):
super(Spot, self).__init__(name=name, deterministic=deterministic, random_state=random_state)
if ia.is_single_number(sigma):
self.sigma = Deterministic(sigma)
elif ia.is_iterable(sigma):
ia.do_assert(len(sigma) == 2, "Expected tuple/list with 2 entries, got %d entries." % (len(sigma),))
self.sigma = Uniform(sigma[0], sigma[1])
elif isinstance(sigma, StochasticParameter):
self.sigma = sigma
else:
raise Exception("Expected float, int, tuple/list with 2 entries or StochasticParameter. Got %s." % (type(sigma),))
self.eps = 0.001 # epsilon value to estimate whether sigma is above 0
def _augment_images(self, images, random_state, parents, hooks):
result = images
nb_images = len(images)
samples = self.sigma.draw_samples((nb_images,), random_state=random_state)
def spots(img,x,y,r):
opacity = 0.3
while r>0:
rr, cc = draw.circle(x,y,r)
draw.set_color(img,[rr,cc],[255,255,255],alpha=opacity)
r -= 1
opacity += 0.2
if opacity>1:
opacity = 1
for i in sm.xrange(nb_images):
sig = samples[i]
if sig > 0 + self.eps:
for num in range(0,10):
r = sig*random.random()
x = random.randint(10,images[i].shape[0]-11)
y = random.randint(10,images[i].shape[1]-11)
spots(images[i],x,y,r)
r2 = r-1
x2 = random.randint(int(x-sig/2),int(x+sig/2))
y2 = random.randint(int(y-sig/2),int(y+sig/2))
spots(images[i],x2,y2,r2)
return result
def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks):
return keypoints_on_images
def get_parameters(self):
return [self.sigma] | imgaug/augmenters/spot.py | from __future__ import print_function, division, absolute_import
from .. import imgaug as ia
# TODO replace these imports with iap.XYZ
from ..parameters import StochasticParameter, Deterministic, DiscreteUniform, Uniform
import numpy as np
from scipy import ndimage
from skimage import draw
from skimage import data
from skimage import io
from skimage import util
import six.moves as sm
import random
from .meta import Augmenter
class Spot(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long
def __init__(self, sigma=0, name=None, deterministic=False, random_state=None):
super(Spot, self).__init__(name=name, deterministic=deterministic, random_state=random_state)
if ia.is_single_number(sigma):
self.sigma = Deterministic(sigma)
elif ia.is_iterable(sigma):
ia.do_assert(len(sigma) == 2, "Expected tuple/list with 2 entries, got %d entries." % (len(sigma),))
self.sigma = Uniform(sigma[0], sigma[1])
elif isinstance(sigma, StochasticParameter):
self.sigma = sigma
else:
raise Exception("Expected float, int, tuple/list with 2 entries or StochasticParameter. Got %s." % (type(sigma),))
self.eps = 0.001 # epsilon value to estimate whether sigma is above 0
def _augment_images(self, images, random_state, parents, hooks):
result = images
nb_images = len(images)
samples = self.sigma.draw_samples((nb_images,), random_state=random_state)
def spots(img,x,y,r):
opacity = 0.3
while r>0:
rr, cc = draw.circle(x,y,r)
draw.set_color(img,[rr,cc],[255,255,255],alpha=opacity)
r -= 1
opacity += 0.2
if opacity>1:
opacity = 1
for i in sm.xrange(nb_images):
sig = samples[i]
if sig > 0 + self.eps:
for num in range(0,10):
r = sig*random.random()
x = random.randint(10,images[i].shape[0]-11)
y = random.randint(10,images[i].shape[1]-11)
spots(images[i],x,y,r)
r2 = r-1
x2 = random.randint(int(x-sig/2),int(x+sig/2))
y2 = random.randint(int(y-sig/2),int(y+sig/2))
spots(images[i],x2,y2,r2)
return result
def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks):
return keypoints_on_images
def get_parameters(self):
return [self.sigma] | 0.340156 | 0.229298 |
from splinter import Browser
from bs4 import BeautifulSoup
from webdriver_manager.chrome import ChromeDriverManager
import requests
import pandas as pd
import time
import os
def scrape_all():
browser=init_browser()
news_title, news_p=scrape_Nasa_Mars_news(browser)
mars_dict={
"Title":news_title,
"Paragraph":news_p,
"FeaturedImage": scrape_JPL_Mars_Space_images(browser),
"MarsFacts": scrape_Mars_fact(),
"hemispheres": scrape_Mars_hemispheres(browser)
}
browser.quit()
return mars_dict
def init_browser():
# NOTE: Replace the path with your actual path to the chromedriver
executable_path = {'executable_path': ChromeDriverManager().install()}
return Browser('chrome', **executable_path, headless=False)
# -------------------------------------------------------------------------------
def scrape_Nasa_Mars_news(browser):
browser.visit('https://mars.nasa.gov/news/')
html = browser.html
soup = BeautifulSoup(html, 'html.parser')
gallery = soup.find(class_='grid_gallery')
news_title = gallery.find(class_="content_title").text
news_p = gallery.find(class_='article_teaser_body').text
# browser.quit()
return news_title, news_p
# -------------------------------------------------------------------------------
# MARS Images
def scrape_JPL_Mars_Space_images(browser):
url='https://spaceimages-mars.com'
browser.visit(url)
elem=browser.find_by_tag('button')[1]
elem.click()
html=browser.html
image_soup=BeautifulSoup(html,'html.parser')
image_url=image_soup.find('img',class_='fancybox-image').get('src')
featured_image_url=f'https://spaceimages-mars.com/{image_url}'
# browser.find_by_tag('input').first.fill('Featured Mars')
# browser.find_by_id('searchHelpers_sortBy').first.select('latestDate')
# results = browser.find_by_id('SearchListingPageResults')
# results.links.find_by_partial_href('images').click()
# browser.find_by_text('Download JPG ').click
# featured_image_url = browser.url
return featured_image_url
# -------------------------------------------------------------------------------
# Mars Facts
def scrape_Mars_fact():
df=pd.read_html('https://space-facts.com/mars/')[0]
df.columns=['Description','Mars']
html_table= df.to_html(index=False, classes=("table table-stripe"))
return html_table
# -------------------------------------------------------------------------------
def scrape_Mars_hemispheres(browser):
url = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars'
browser.visit(url)
hemisphere_images_url=[]
links=browser.find_by_css('a.product-item img')
for i in range(4):
hemisphere={}
browser.find_by_css('a.product-item img')[i].click()
sample_elem=browser.links.find_by_text('Sample').first
hemisphere['img_url']=sample_elem['href']
hemisphere['title']=browser.find_by_css('h2.title').text
# html=browser.html
# image_soup=BeautifulSoup(html,'html.parser')
# image=image_soup.find_all('div',class_='downloads')[0].find('a')['href']
# title=image_soup.find_all('h2',class_='title')[0].text
# hemisphere['title']=title
# hemisphere['image_url']=image
hemisphere_images_url.append(hemisphere)
browser.back()
# browser.quit()
return hemisphere_images_url
# -------------------------------------------------------------------------------
def quit_browser():
browser.quit() | Missions_to_Mars/scrape_mars.py | from splinter import Browser
from bs4 import BeautifulSoup
from webdriver_manager.chrome import ChromeDriverManager
import requests
import pandas as pd
import time
import os
def scrape_all():
browser=init_browser()
news_title, news_p=scrape_Nasa_Mars_news(browser)
mars_dict={
"Title":news_title,
"Paragraph":news_p,
"FeaturedImage": scrape_JPL_Mars_Space_images(browser),
"MarsFacts": scrape_Mars_fact(),
"hemispheres": scrape_Mars_hemispheres(browser)
}
browser.quit()
return mars_dict
def init_browser():
# NOTE: Replace the path with your actual path to the chromedriver
executable_path = {'executable_path': ChromeDriverManager().install()}
return Browser('chrome', **executable_path, headless=False)
# -------------------------------------------------------------------------------
def scrape_Nasa_Mars_news(browser):
browser.visit('https://mars.nasa.gov/news/')
html = browser.html
soup = BeautifulSoup(html, 'html.parser')
gallery = soup.find(class_='grid_gallery')
news_title = gallery.find(class_="content_title").text
news_p = gallery.find(class_='article_teaser_body').text
# browser.quit()
return news_title, news_p
# -------------------------------------------------------------------------------
# MARS Images
def scrape_JPL_Mars_Space_images(browser):
url='https://spaceimages-mars.com'
browser.visit(url)
elem=browser.find_by_tag('button')[1]
elem.click()
html=browser.html
image_soup=BeautifulSoup(html,'html.parser')
image_url=image_soup.find('img',class_='fancybox-image').get('src')
featured_image_url=f'https://spaceimages-mars.com/{image_url}'
# browser.find_by_tag('input').first.fill('Featured Mars')
# browser.find_by_id('searchHelpers_sortBy').first.select('latestDate')
# results = browser.find_by_id('SearchListingPageResults')
# results.links.find_by_partial_href('images').click()
# browser.find_by_text('Download JPG ').click
# featured_image_url = browser.url
return featured_image_url
# -------------------------------------------------------------------------------
# Mars Facts
def scrape_Mars_fact():
df=pd.read_html('https://space-facts.com/mars/')[0]
df.columns=['Description','Mars']
html_table= df.to_html(index=False, classes=("table table-stripe"))
return html_table
# -------------------------------------------------------------------------------
def scrape_Mars_hemispheres(browser):
url = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars'
browser.visit(url)
hemisphere_images_url=[]
links=browser.find_by_css('a.product-item img')
for i in range(4):
hemisphere={}
browser.find_by_css('a.product-item img')[i].click()
sample_elem=browser.links.find_by_text('Sample').first
hemisphere['img_url']=sample_elem['href']
hemisphere['title']=browser.find_by_css('h2.title').text
# html=browser.html
# image_soup=BeautifulSoup(html,'html.parser')
# image=image_soup.find_all('div',class_='downloads')[0].find('a')['href']
# title=image_soup.find_all('h2',class_='title')[0].text
# hemisphere['title']=title
# hemisphere['image_url']=image
hemisphere_images_url.append(hemisphere)
browser.back()
# browser.quit()
return hemisphere_images_url
# -------------------------------------------------------------------------------
def quit_browser():
browser.quit() | 0.343232 | 0.081849 |
import scrapy
from scrapy import log
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from rcbi.items import Part
import copy
import re
import urllib
import urlparse
MANUFACTURERS = ["Pololu"]
CORRECT = {"GemFan": "Gemfan"}
MANUFACTURERS.extend(CORRECT.keys())
QUANTITY = {" 8 pack": 8}
COMBINATION_RE = re.compile("addCombination\([0-9]+, new Array\(([0-9\' ]+)\), ([0-9]+), .*\);")
ATTRIBUTE_RE = re.compile("tabInfos\['id_attribute'\] = ('[0-9]+');\s+tabInfos\['attribute'\] = '(\w+)';", re.UNICODE)
class LizardRCSpider(CrawlSpider):
name = "lizardrc"
allowed_domains = ["lizard-rc.se"]
start_urls = ["http://lizard-rc.se"]
rules = (
Rule(LinkExtractor(restrict_css=["#menu-wrap", ".pagination", ".categories_box"])),
Rule(LinkExtractor(restrict_css=".ajax_block_product"), callback='parse_item'),
)
def parse_item(self, response):
item = Part()
item["site"] = self.name
product_name = response.css("#pb-left-column h1")
if not product_name:
return
item["name"] = product_name[0].xpath("text()").extract()[0].strip()
variant = {}
item["variants"] = []
variant["url"] = response.url
price = response.css("#our_price_display")
if price:
variant["price"] = price.xpath("text()").extract()[0].strip()
for quantity in QUANTITY:
if quantity in item["name"]:
variant["quantity"] = QUANTITY[quantity]
item["name"] = item["name"].replace(quantity, "")
body = response.body_as_unicode()
attr_map = {}
for attr in ATTRIBUTE_RE.finditer(body):
g = attr.groups()
attr_map[g[0]] = g[1]
if not attr_map:
quantity = response.css("#quantityAvailable::text")
if quantity:
stock_quantity = int(quantity.extract_first().strip())
if stock_quantity == 0:
variant["stock_state"] = "out_of_stock"
else:
variant["stock_state"] = "in_stock"
variant["stock_text"] = str(stock_quantity) + " items in stock"
item["variants"].append(variant)
else:
for combo in COMBINATION_RE.finditer(body):
g = combo.groups()
if "," in g[0]:
print(g)
continue
variant["description"] = attr_map[g[0]]
stock_quantity = int(g[1])
if stock_quantity == 0:
variant["stock_state"] = "out_of_stock"
else:
variant["stock_state"] = "in_stock"
variant["stock_text"] = str(stock_quantity) + " items in stock"
item["variants"].append(variant)
variant = copy.deepcopy(variant)
for m in MANUFACTURERS:
if item["name"].startswith(m):
item["name"] = item["name"][len(m):].strip("- ")
item["manufacturer"] = m
break
elif item["name"].endswith(m):
item["name"] = item["name"][:-len(m)].strip("- ")
item["manufacturer"] = m
break
if "manufacturer" in item:
m = item["manufacturer"]
if m in CORRECT:
item["manufacturer"] = CORRECT[m]
return item | rcbi/rcbi/spiders/LizardRC.py | import scrapy
from scrapy import log
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from rcbi.items import Part
import copy
import re
import urllib
import urlparse
MANUFACTURERS = ["Pololu"]
CORRECT = {"GemFan": "Gemfan"}
MANUFACTURERS.extend(CORRECT.keys())
QUANTITY = {" 8 pack": 8}
COMBINATION_RE = re.compile("addCombination\([0-9]+, new Array\(([0-9\' ]+)\), ([0-9]+), .*\);")
ATTRIBUTE_RE = re.compile("tabInfos\['id_attribute'\] = ('[0-9]+');\s+tabInfos\['attribute'\] = '(\w+)';", re.UNICODE)
class LizardRCSpider(CrawlSpider):
name = "lizardrc"
allowed_domains = ["lizard-rc.se"]
start_urls = ["http://lizard-rc.se"]
rules = (
Rule(LinkExtractor(restrict_css=["#menu-wrap", ".pagination", ".categories_box"])),
Rule(LinkExtractor(restrict_css=".ajax_block_product"), callback='parse_item'),
)
def parse_item(self, response):
item = Part()
item["site"] = self.name
product_name = response.css("#pb-left-column h1")
if not product_name:
return
item["name"] = product_name[0].xpath("text()").extract()[0].strip()
variant = {}
item["variants"] = []
variant["url"] = response.url
price = response.css("#our_price_display")
if price:
variant["price"] = price.xpath("text()").extract()[0].strip()
for quantity in QUANTITY:
if quantity in item["name"]:
variant["quantity"] = QUANTITY[quantity]
item["name"] = item["name"].replace(quantity, "")
body = response.body_as_unicode()
attr_map = {}
for attr in ATTRIBUTE_RE.finditer(body):
g = attr.groups()
attr_map[g[0]] = g[1]
if not attr_map:
quantity = response.css("#quantityAvailable::text")
if quantity:
stock_quantity = int(quantity.extract_first().strip())
if stock_quantity == 0:
variant["stock_state"] = "out_of_stock"
else:
variant["stock_state"] = "in_stock"
variant["stock_text"] = str(stock_quantity) + " items in stock"
item["variants"].append(variant)
else:
for combo in COMBINATION_RE.finditer(body):
g = combo.groups()
if "," in g[0]:
print(g)
continue
variant["description"] = attr_map[g[0]]
stock_quantity = int(g[1])
if stock_quantity == 0:
variant["stock_state"] = "out_of_stock"
else:
variant["stock_state"] = "in_stock"
variant["stock_text"] = str(stock_quantity) + " items in stock"
item["variants"].append(variant)
variant = copy.deepcopy(variant)
for m in MANUFACTURERS:
if item["name"].startswith(m):
item["name"] = item["name"][len(m):].strip("- ")
item["manufacturer"] = m
break
elif item["name"].endswith(m):
item["name"] = item["name"][:-len(m)].strip("- ")
item["manufacturer"] = m
break
if "manufacturer" in item:
m = item["manufacturer"]
if m in CORRECT:
item["manufacturer"] = CORRECT[m]
return item | 0.213213 | 0.085862 |
import json, logging, os
from datetime import datetime
from urllib.parse import urlencode, urlparse, parse_qs
from django.http import HttpResponse, JsonResponse
from django.contrib.auth import forms as userforms
from django.urls import reverse
from django.shortcuts import render_to_response, redirect
from django.utils.cache import patch_response_headers
from django.conf import settings
from django.middleware import csrf
from django.views.decorators.csrf import csrf_exempt
from api_app.model_files import apikeysmodel
from api_app.actions import get_actions, create_actions
from api_app import request_parser
# Get an instance of a logger
logger = logging.getLogger(__name__)
def generate_default_data(request=None):
data = {'built': datetime.now().strftime("%H:%M:%S")}
if request is not None:
data['csrf'] = csrf.get_token(request)
return data
def initRequest(request):
"""
A function to check and verify request
:param request:
:return:
"""
url = request.get_full_path()
u = urlparse(url)
query = parse_qs(u.query)
query.pop('timestamp', None)
try:
u = u._replace(query=urlencode(query, True))
except UnicodeEncodeError:
data = {
'errormessage': 'Error appeared while encoding URL!'
}
return False, render_to_response(json.dumps(data), content_type='text/html')
## Set default page lifetime in the http header, for the use of the front end cache
request.session['max_age_minutes'] = 10
## Create a dict in session for storing request params
requestParams = {}
request.session['requestParams'] = requestParams
if getattr(settings, 'SESSION_COOKIE_AGE', None):
request.session.set_expiry(settings.SESSION_COOKIE_AGE)
api_secret_key = None
if request.method == 'POST':
for p in request.POST:
pval = request.POST[p]
pval = pval.replace('+', ' ')
request.session['requestParams'][p.lower()] = pval
if 'secret_key' in request.POST:
api_secret_key = request.POST['secret_key']
else:
for p in request.GET:
pval = request.GET[p]
pval = pval.replace('+', ' ')
## Here check if int or date type params can be placed
request.session['requestParams'][p.lower()] = pval
if 'secret_key' in request.GET:
api_secret_key = request.GET['secret_key']
if not api_secret_key is None:
valid, api_key = apikeysmodel.APIKey.validate_api(api_secret_key)
if valid:
request.api_key = api_key
return True, None
else:
if api_key is None:
return False, HttpResponse(status=401)
else:
return False, HttpResponse(status=401)
return False, HttpResponse(status=402)
def check_settings(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['success'] = True
data['expires_on'] = request.api_key.expireon
return JsonResponse(data, status=200)
@csrf_exempt
def missed_request(request):
data = {}
return JsonResponse(data, status=400)
def add_computer_to_client(request, clientuuid):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
company = get_actions.get_client(clientuuid)
if company is not None:
args = request_parser.computer_update_request(request, company)
if args is not None:
success, comp = create_actions.update_computer_with_ser_number(**args)
if success and comp is not None:
data['computerid'] = comp.id
return JsonResponse(data, status=200)
return JsonResponse(data, status=400)
def get_all_clients(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['client_list'] = get_actions.get_all_clients_unid_name()
if data['client_list'] is None:
return JsonResponse(data, status=404)
return JsonResponse(data, status=200)
def get_domain_clients(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['client_list'] = get_actions.get_domain_clients_unid_name()
if data['client_list'] is None:
return JsonResponse(data, status=404)
return JsonResponse(data, status=200)
def get_domain_info(request, clientuuid):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
company = get_actions.get_client(clientuuid)
if company is not None:
info = get_actions.get_domain_info_for_client(company)
if info is not None:
data['domain'] = info
return JsonResponse(data, status=200)
return JsonResponse(data, status=400) | api_app/views.py | import json, logging, os
from datetime import datetime
from urllib.parse import urlencode, urlparse, parse_qs
from django.http import HttpResponse, JsonResponse
from django.contrib.auth import forms as userforms
from django.urls import reverse
from django.shortcuts import render_to_response, redirect
from django.utils.cache import patch_response_headers
from django.conf import settings
from django.middleware import csrf
from django.views.decorators.csrf import csrf_exempt
from api_app.model_files import apikeysmodel
from api_app.actions import get_actions, create_actions
from api_app import request_parser
# Get an instance of a logger
logger = logging.getLogger(__name__)
def generate_default_data(request=None):
data = {'built': datetime.now().strftime("%H:%M:%S")}
if request is not None:
data['csrf'] = csrf.get_token(request)
return data
def initRequest(request):
"""
A function to check and verify request
:param request:
:return:
"""
url = request.get_full_path()
u = urlparse(url)
query = parse_qs(u.query)
query.pop('timestamp', None)
try:
u = u._replace(query=urlencode(query, True))
except UnicodeEncodeError:
data = {
'errormessage': 'Error appeared while encoding URL!'
}
return False, render_to_response(json.dumps(data), content_type='text/html')
## Set default page lifetime in the http header, for the use of the front end cache
request.session['max_age_minutes'] = 10
## Create a dict in session for storing request params
requestParams = {}
request.session['requestParams'] = requestParams
if getattr(settings, 'SESSION_COOKIE_AGE', None):
request.session.set_expiry(settings.SESSION_COOKIE_AGE)
api_secret_key = None
if request.method == 'POST':
for p in request.POST:
pval = request.POST[p]
pval = pval.replace('+', ' ')
request.session['requestParams'][p.lower()] = pval
if 'secret_key' in request.POST:
api_secret_key = request.POST['secret_key']
else:
for p in request.GET:
pval = request.GET[p]
pval = pval.replace('+', ' ')
## Here check if int or date type params can be placed
request.session['requestParams'][p.lower()] = pval
if 'secret_key' in request.GET:
api_secret_key = request.GET['secret_key']
if not api_secret_key is None:
valid, api_key = apikeysmodel.APIKey.validate_api(api_secret_key)
if valid:
request.api_key = api_key
return True, None
else:
if api_key is None:
return False, HttpResponse(status=401)
else:
return False, HttpResponse(status=401)
return False, HttpResponse(status=402)
def check_settings(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['success'] = True
data['expires_on'] = request.api_key.expireon
return JsonResponse(data, status=200)
@csrf_exempt
def missed_request(request):
data = {}
return JsonResponse(data, status=400)
def add_computer_to_client(request, clientuuid):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
company = get_actions.get_client(clientuuid)
if company is not None:
args = request_parser.computer_update_request(request, company)
if args is not None:
success, comp = create_actions.update_computer_with_ser_number(**args)
if success and comp is not None:
data['computerid'] = comp.id
return JsonResponse(data, status=200)
return JsonResponse(data, status=400)
def get_all_clients(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['client_list'] = get_actions.get_all_clients_unid_name()
if data['client_list'] is None:
return JsonResponse(data, status=404)
return JsonResponse(data, status=200)
def get_domain_clients(request):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
data['client_list'] = get_actions.get_domain_clients_unid_name()
if data['client_list'] is None:
return JsonResponse(data, status=404)
return JsonResponse(data, status=200)
def get_domain_info(request, clientuuid):
valid, response = initRequest(request)
if not valid:
return response
data = generate_default_data(request)
company = get_actions.get_client(clientuuid)
if company is not None:
info = get_actions.get_domain_info_for_client(company)
if info is not None:
data['domain'] = info
return JsonResponse(data, status=200)
return JsonResponse(data, status=400) | 0.372619 | 0.067485 |
import argparse
import pika
import os
import sys
import binascii
import json
from DefenseLab import config
def callback(ch, method, properties, body):
print body
ch.basic_ack(delivery_tag=method.delivery_tag)
sys.exit()
return
def serviceStart(args):
connection = pika.BlockingConnection(pika.ConnectionParameters(config.RABBITMQ_SERVER))
channel = connection.channel()
channel.queue_declare(queue='serviceQueue', durable=True)
userInfo = binascii.hexlify(os.urandom(32)).decode('ascii')
service = {
'serviceName': args.service_name,
'imageName': args.image_name,
'volumeLocation': args.volume,
'exploitModule': args.exploit,
'serviceCheckName': args.service_check,
'serviceHost': None,
'servicePort': args.port,
'userInfo': userInfo
}
print "Pushing: {}".format(service)
channel.basic_publish(exchange='',
routing_key='serviceQueue',
body=json.dumps(service))
connection = pika.BlockingConnection(pika.ConnectionParameters(config.RABBITMQ_SERVER))
userChannel = connection.channel()
userChannel.exchange_declare(exchange='resultX', exchange_type='direct')
userChannel.queue_declare(queue='resultQueue', durable=True)
userChannel.queue_bind(exchange='resultX',
queue='resultQueue',
routing_key=userInfo)
print "Waiting for result"
userChannel.basic_consume(callback, queue='resultQueue')
userChannel.start_consuming()
userChannel.close()
def labStart(args):
if args.attack_workers is not None:
config.NUM_ATTACK_WORKERS = args.attack_workers
if args.service_workers is not None:
config.NUM_SERVICE_WORKERS = args.service_workers
if args.cleanup_workers is not None:
config.NUM_CLEANUP_WORKERS = args.cleanup_workers
from DefenseLab import DefenseLab # NOQA
def main():
parser = argparse.ArgumentParser(description="Command Line Interface for Defense Lab")
subparsers = parser.add_subparsers(title="Lab Commands", help="Commands to start and interact with Defense Lab", description="Commands to start and interact with Defense Lab")
startArgs = subparsers.add_parser("start", help="Start up the defense lab", description="Start up the defense lab")
startArgs.add_argument("-wa", "--attack-workers", type=int, help="Number of attack workers to start with. Default is two.")
startArgs.add_argument("-ws", "--service-workers", type=int, help="Number of service workers to start with. Default is two.")
startArgs.add_argument("-wc", "--cleanup-workers", type=int, help="Number of cleanup workers to start with. Default is two.")
serviceArgs = subparsers.add_parser("send", description="Info to push onto the service queue")
serviceArgs.add_argument("-s", "--service-name", required=True, help="Name of docker container to create")
serviceArgs.add_argument("-i", "--image-name", required=True, help="Name of docker image to use")
serviceArgs.add_argument("-v", "--volume", required=True, help="Location of files to test")
serviceArgs.add_argument("-e", "--exploit", required=True, help="Name of exploit module to use")
serviceArgs.add_argument("-c", "--service-check", required=True, help="Name of service check module to use")
serviceArgs.add_argument("-p", "--port", required=True, type=int, help="Port number of service")
args = parser.parse_args()
try:
args.attack_workers
labStart(args)
except AttributeError:
serviceStart(args)
if __name__ == '__main__':
main() | DefenseCLI.py | import argparse
import pika
import os
import sys
import binascii
import json
from DefenseLab import config
def callback(ch, method, properties, body):
print body
ch.basic_ack(delivery_tag=method.delivery_tag)
sys.exit()
return
def serviceStart(args):
connection = pika.BlockingConnection(pika.ConnectionParameters(config.RABBITMQ_SERVER))
channel = connection.channel()
channel.queue_declare(queue='serviceQueue', durable=True)
userInfo = binascii.hexlify(os.urandom(32)).decode('ascii')
service = {
'serviceName': args.service_name,
'imageName': args.image_name,
'volumeLocation': args.volume,
'exploitModule': args.exploit,
'serviceCheckName': args.service_check,
'serviceHost': None,
'servicePort': args.port,
'userInfo': userInfo
}
print "Pushing: {}".format(service)
channel.basic_publish(exchange='',
routing_key='serviceQueue',
body=json.dumps(service))
connection = pika.BlockingConnection(pika.ConnectionParameters(config.RABBITMQ_SERVER))
userChannel = connection.channel()
userChannel.exchange_declare(exchange='resultX', exchange_type='direct')
userChannel.queue_declare(queue='resultQueue', durable=True)
userChannel.queue_bind(exchange='resultX',
queue='resultQueue',
routing_key=userInfo)
print "Waiting for result"
userChannel.basic_consume(callback, queue='resultQueue')
userChannel.start_consuming()
userChannel.close()
def labStart(args):
if args.attack_workers is not None:
config.NUM_ATTACK_WORKERS = args.attack_workers
if args.service_workers is not None:
config.NUM_SERVICE_WORKERS = args.service_workers
if args.cleanup_workers is not None:
config.NUM_CLEANUP_WORKERS = args.cleanup_workers
from DefenseLab import DefenseLab # NOQA
def main():
parser = argparse.ArgumentParser(description="Command Line Interface for Defense Lab")
subparsers = parser.add_subparsers(title="Lab Commands", help="Commands to start and interact with Defense Lab", description="Commands to start and interact with Defense Lab")
startArgs = subparsers.add_parser("start", help="Start up the defense lab", description="Start up the defense lab")
startArgs.add_argument("-wa", "--attack-workers", type=int, help="Number of attack workers to start with. Default is two.")
startArgs.add_argument("-ws", "--service-workers", type=int, help="Number of service workers to start with. Default is two.")
startArgs.add_argument("-wc", "--cleanup-workers", type=int, help="Number of cleanup workers to start with. Default is two.")
serviceArgs = subparsers.add_parser("send", description="Info to push onto the service queue")
serviceArgs.add_argument("-s", "--service-name", required=True, help="Name of docker container to create")
serviceArgs.add_argument("-i", "--image-name", required=True, help="Name of docker image to use")
serviceArgs.add_argument("-v", "--volume", required=True, help="Location of files to test")
serviceArgs.add_argument("-e", "--exploit", required=True, help="Name of exploit module to use")
serviceArgs.add_argument("-c", "--service-check", required=True, help="Name of service check module to use")
serviceArgs.add_argument("-p", "--port", required=True, type=int, help="Port number of service")
args = parser.parse_args()
try:
args.attack_workers
labStart(args)
except AttributeError:
serviceStart(args)
if __name__ == '__main__':
main() | 0.305386 | 0.125762 |
from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import relationship
from src.model import db
from src.model import common
class MovieColor(db.ModelBase):
""" Movie color """
__tablename__ = 'movie_colors'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Movie color text
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='movie_color')
def __repr__(self):
return '<MovieColor(name="%s")>' % self.name
def __str__(self):
return self.name
class Country(db.ModelBase):
""" Country """
__tablename__ = 'country'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Country name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='country')
def __repr__(self):
return '<Country(name="%s")>' % self.name
def __str__(self):
return self.name
class Language(db.ModelBase):
""" Movie Language """
__tablename__ = 'language'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Language name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='language')
def __repr__(self):
return '<Language(name="%s")>' % self.name
def __str__(self):
return self.name
class ContentRating(db.ModelBase):
""" Movie content rating """
__tablename__ = 'content_rating'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Rating name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='content_rating')
def __repr__(self):
return '<Content Rating(name="%s")>' % self.name
def __str__(self):
return self.name
class Genre(db.ModelBase):
""" Movie genre """
__tablename__ = 'genre'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Genre name
name = Column(String(31), nullable=False, unique=True)
movies = relationship(
'Movie', secondary=common.movie_genres, back_populates='genres'
)
class Keyword(db.ModelBase):
""" Movie plot keyword """
__tablename__ = 'keyword'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Keyword name
name = Column(String(31), nullable=False, unique=True)
movies = relationship(
'Movie', secondary=common.movie_keywords, back_populates='keywords'
) | src/model/fields.py | from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import relationship
from src.model import db
from src.model import common
class MovieColor(db.ModelBase):
""" Movie color """
__tablename__ = 'movie_colors'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Movie color text
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='movie_color')
def __repr__(self):
return '<MovieColor(name="%s")>' % self.name
def __str__(self):
return self.name
class Country(db.ModelBase):
""" Country """
__tablename__ = 'country'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Country name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='country')
def __repr__(self):
return '<Country(name="%s")>' % self.name
def __str__(self):
return self.name
class Language(db.ModelBase):
""" Movie Language """
__tablename__ = 'language'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Language name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='language')
def __repr__(self):
return '<Language(name="%s")>' % self.name
def __str__(self):
return self.name
class ContentRating(db.ModelBase):
""" Movie content rating """
__tablename__ = 'content_rating'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Rating name
name = Column(String(31), nullable=False, unique=True)
#: Movie relationship
movies = relationship('Movie', back_populates='content_rating')
def __repr__(self):
return '<Content Rating(name="%s")>' % self.name
def __str__(self):
return self.name
class Genre(db.ModelBase):
""" Movie genre """
__tablename__ = 'genre'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Genre name
name = Column(String(31), nullable=False, unique=True)
movies = relationship(
'Movie', secondary=common.movie_genres, back_populates='genres'
)
class Keyword(db.ModelBase):
""" Movie plot keyword """
__tablename__ = 'keyword'
#: Primary key
pk = Column(Integer, primary_key=True, autoincrement=True)
#: Keyword name
name = Column(String(31), nullable=False, unique=True)
movies = relationship(
'Movie', secondary=common.movie_keywords, back_populates='keywords'
) | 0.790207 | 0.22212 |
import torch
from torch import Tensor
from pytorch_transformers import XLNetConfig, XLNetModel, XLNetTokenizer
from pytorch_transformers.modeling_xlnet import XLNetPreTrainedModel
from typing import Union, Tuple, List
from .. import LossFunction
from .. import SentenceTransformerConfig
from .TransformerModel import TransformerModel
from torch import nn
from torch.nn import functional as F
from torch.nn import CrossEntropyLoss, MSELoss
class XLNet(XLNetPreTrainedModel, TransformerModel):
def __init__(self, config: XLNetConfig, sentence_transformer_config: SentenceTransformerConfig = None):
XLNetPreTrainedModel.__init__(self, config)
self.model_config = config
self.model_hidden_size = config.d_model
TransformerModel.__init__(self, sentence_transformer_config)
self.transformer = XLNetModel(config)
self.apply(self.init_weights)
##Code from summary
self.summary = nn.Identity()
if hasattr(config, 'summary_use_proj') and config.summary_use_proj:
self.summary = nn.Linear(config.d_model, config.d_model)
self.activation = nn.Identity()
if hasattr(config, 'summary_activation') and config.summary_activation=='tanh':
self.activation = nn.Tanh()
self.first_dropout = nn.Identity()
if hasattr(config, 'summary_first_dropout') and config.summary_first_dropout > 0:
self.first_dropout = nn.Dropout(config.summary_first_dropout)
self.last_dropout = nn.Identity()
if hasattr(config, 'summary_last_dropout') and config.summary_last_dropout > 0:
self.last_dropout = nn.Dropout(config.summary_last_dropout)
def set_tokenizer(self, tokenizer_model: str, do_lower_case: bool):
"""
Sets the tokenizer for this model
"""
self.tokenizer_model = XLNetTokenizer.from_pretrained(tokenizer_model, do_lower_case=do_lower_case)
def forward(self, input_ids: List[Tensor], token_type_ids: List[Tensor], attention_mask: List[Tensor],
labels: Tensor = None, alternative_loss: LossFunction = None) -> Union[
Tensor, Tuple[List[Tensor], Tensor]]:
"""
Forward pass of the model for a variable number of sentences, each represented as input ids,
segment ids and masks.
If labels are given, then the training loss is returned otherwise sentence embeddings
and the LossFunction value is returned.
The training loss is not the same as the LossFunction value.
:param input_ids:
list of Tensors of the token embedding ids
:param token_type_ids:
list of Tensors of the segment ids
:param attention_mask:
list of Tensors of the masks
:param labels:
Tensor of the training labels
:param alternative_loss:
an alternative loss different to self.sentence_transformer_config.loss_function for multitask learning.
the loss still uses the configuration as given in self.sbert_config, so you cannot for example
have two different LossFunction.SOFTMAX with different number of labels
:return: the training loss or the two sentence embeddings and the LossFunction value (if available for the
chosen loss)
"""
reps = [self.get_sentence_representation(ids, seg, mask) for ids, seg, mask
in zip(input_ids, token_type_ids, attention_mask)]
return self.compute_loss(reps, labels, alternative_loss)
def _get_transformer_output(self, input_ids: Tensor, token_type_ids: Tensor, attention_mask: Tensor):
"""
Internal method that invokes the underlying model
and returns the output vectors for all input tokens
"""
transformer_outputs = self.transformer(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask)
output_tokens = transformer_outputs[0]
cls_tokens = output_tokens[:, -1] # CLS token is the last token
#cls_tokens = self.first_dropout(cls_tokens)
cls_tokens = self.summary(cls_tokens)
cls_tokens = self.activation(cls_tokens)
#cls_tokens = self.last_dropout(cls_tokens)
return output_tokens, cls_tokens
def get_sentence_features(self, tokens: List[str], max_seq_length: int) -> Tuple[List[int], List[int], List[int]]:
"""
Convert tokenized sentence in its embedding ids, segment ids and mask
:param tokens:
a tokenized sentence
:param max_seq_length:
the maximal length of the sequence.
If this is greater than self.max_seq_length, then self.max_seq_length is used.
If this is 0, then self.max_seq_length is used.
:return: embedding ids, segment ids and mask for the sentence
"""
sep_token = self.tokenizer_model.sep_token
cls_token = self.tokenizer_model.cls_token
sequence_a_segment_id = 0
cls_token_segment_id = 2
pad_token_segment_id = 4
pad_token = 0
max_seq_length += 2 ##Add space for CLS + SEP token
tokens = tokens[:(max_seq_length - 2)] + [sep_token]
segment_ids = [sequence_a_segment_id] * len(tokens)
# XLNet CLS token at at
tokens = tokens + [cls_token]
segment_ids = segment_ids + [cls_token_segment_id]
input_ids = self.tokenizer_model.convert_tokens_to_ids(tokens)
input_mask = [1] * len(input_ids)
# Zero-pad up to the sequence length. XLNet: Pad to the left
padding_length = max_seq_length - len(input_ids)
input_ids = ([pad_token] * padding_length) + input_ids
input_mask = ([0] * padding_length) + input_mask
segment_ids = ([pad_token_segment_id] * padding_length) + segment_ids
assert len(input_ids)==max_seq_length
assert len(input_mask)==max_seq_length
assert len(segment_ids)==max_seq_length
return input_ids, segment_ids, input_mask | sentence_transformers/models/XLNet.py | import torch
from torch import Tensor
from pytorch_transformers import XLNetConfig, XLNetModel, XLNetTokenizer
from pytorch_transformers.modeling_xlnet import XLNetPreTrainedModel
from typing import Union, Tuple, List
from .. import LossFunction
from .. import SentenceTransformerConfig
from .TransformerModel import TransformerModel
from torch import nn
from torch.nn import functional as F
from torch.nn import CrossEntropyLoss, MSELoss
class XLNet(XLNetPreTrainedModel, TransformerModel):
def __init__(self, config: XLNetConfig, sentence_transformer_config: SentenceTransformerConfig = None):
XLNetPreTrainedModel.__init__(self, config)
self.model_config = config
self.model_hidden_size = config.d_model
TransformerModel.__init__(self, sentence_transformer_config)
self.transformer = XLNetModel(config)
self.apply(self.init_weights)
##Code from summary
self.summary = nn.Identity()
if hasattr(config, 'summary_use_proj') and config.summary_use_proj:
self.summary = nn.Linear(config.d_model, config.d_model)
self.activation = nn.Identity()
if hasattr(config, 'summary_activation') and config.summary_activation=='tanh':
self.activation = nn.Tanh()
self.first_dropout = nn.Identity()
if hasattr(config, 'summary_first_dropout') and config.summary_first_dropout > 0:
self.first_dropout = nn.Dropout(config.summary_first_dropout)
self.last_dropout = nn.Identity()
if hasattr(config, 'summary_last_dropout') and config.summary_last_dropout > 0:
self.last_dropout = nn.Dropout(config.summary_last_dropout)
def set_tokenizer(self, tokenizer_model: str, do_lower_case: bool):
"""
Sets the tokenizer for this model
"""
self.tokenizer_model = XLNetTokenizer.from_pretrained(tokenizer_model, do_lower_case=do_lower_case)
def forward(self, input_ids: List[Tensor], token_type_ids: List[Tensor], attention_mask: List[Tensor],
labels: Tensor = None, alternative_loss: LossFunction = None) -> Union[
Tensor, Tuple[List[Tensor], Tensor]]:
"""
Forward pass of the model for a variable number of sentences, each represented as input ids,
segment ids and masks.
If labels are given, then the training loss is returned otherwise sentence embeddings
and the LossFunction value is returned.
The training loss is not the same as the LossFunction value.
:param input_ids:
list of Tensors of the token embedding ids
:param token_type_ids:
list of Tensors of the segment ids
:param attention_mask:
list of Tensors of the masks
:param labels:
Tensor of the training labels
:param alternative_loss:
an alternative loss different to self.sentence_transformer_config.loss_function for multitask learning.
the loss still uses the configuration as given in self.sbert_config, so you cannot for example
have two different LossFunction.SOFTMAX with different number of labels
:return: the training loss or the two sentence embeddings and the LossFunction value (if available for the
chosen loss)
"""
reps = [self.get_sentence_representation(ids, seg, mask) for ids, seg, mask
in zip(input_ids, token_type_ids, attention_mask)]
return self.compute_loss(reps, labels, alternative_loss)
def _get_transformer_output(self, input_ids: Tensor, token_type_ids: Tensor, attention_mask: Tensor):
"""
Internal method that invokes the underlying model
and returns the output vectors for all input tokens
"""
transformer_outputs = self.transformer(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask)
output_tokens = transformer_outputs[0]
cls_tokens = output_tokens[:, -1] # CLS token is the last token
#cls_tokens = self.first_dropout(cls_tokens)
cls_tokens = self.summary(cls_tokens)
cls_tokens = self.activation(cls_tokens)
#cls_tokens = self.last_dropout(cls_tokens)
return output_tokens, cls_tokens
def get_sentence_features(self, tokens: List[str], max_seq_length: int) -> Tuple[List[int], List[int], List[int]]:
"""
Convert tokenized sentence in its embedding ids, segment ids and mask
:param tokens:
a tokenized sentence
:param max_seq_length:
the maximal length of the sequence.
If this is greater than self.max_seq_length, then self.max_seq_length is used.
If this is 0, then self.max_seq_length is used.
:return: embedding ids, segment ids and mask for the sentence
"""
sep_token = self.tokenizer_model.sep_token
cls_token = self.tokenizer_model.cls_token
sequence_a_segment_id = 0
cls_token_segment_id = 2
pad_token_segment_id = 4
pad_token = 0
max_seq_length += 2 ##Add space for CLS + SEP token
tokens = tokens[:(max_seq_length - 2)] + [sep_token]
segment_ids = [sequence_a_segment_id] * len(tokens)
# XLNet CLS token at at
tokens = tokens + [cls_token]
segment_ids = segment_ids + [cls_token_segment_id]
input_ids = self.tokenizer_model.convert_tokens_to_ids(tokens)
input_mask = [1] * len(input_ids)
# Zero-pad up to the sequence length. XLNet: Pad to the left
padding_length = max_seq_length - len(input_ids)
input_ids = ([pad_token] * padding_length) + input_ids
input_mask = ([0] * padding_length) + input_mask
segment_ids = ([pad_token_segment_id] * padding_length) + segment_ids
assert len(input_ids)==max_seq_length
assert len(input_mask)==max_seq_length
assert len(segment_ids)==max_seq_length
return input_ids, segment_ids, input_mask | 0.914105 | 0.428413 |
import sys
from collections import namedtuple
# b:begin, m: middle, e: end
LR = namedtuple('LR', 'l l_tag r r_tag b m e')
class BaseTemplateMatcher:
def generate(self, token):
raise NotImplementedError
class EojeolTemplateMatcher(BaseTemplateMatcher):
def __init__(self, dictionary, single_tags=None, lr_templates=None):
if not single_tags:
single_tags = ['Noun', 'Verb', 'Adjective', 'Adverb', 'Exclamation']
if not lr_templates:
lr_templates = [('Noun', 'Verb'), ('Noun', 'Adjective'), ('Noun', 'Josa')]
self.dictionary = dictionary
self.single_tags = single_tags
self.lr_templates = lr_templates
def generate(self, eojeol):
n = len(eojeol)
candidates = []
for tag in self.dictionary.get_pos(eojeol):
if tag in self.single_tags:
candidates.append([LR(eojeol, tag, '', None, 0, n, n)])
if not candidates:
candidates.append([LR(eojeol, None, '', None, 0, n, n)])
for b in range(1, n):
l, r = eojeol[:b], eojeol[b:]
for l_tag, r_tag in self.lr_templates:
if self.dictionary.word_is_tag(l, l_tag) and self.dictionary.word_is_tag(r, r_tag):
candidates.append([LR(l, l_tag, r, r_tag, 0, b, n)])
compound_noun = self._decompose_compound(eojeol, 'Noun')
if compound_noun:
candidates.append(compound_noun)
compound_adverb = self._decompose_compound(eojeol, 'Adverb')
if compound_adverb:
candidates.append(compound_adverb)
return candidates
def _decompose_compound(self, eojeol, tag):
n, b = len(eojeol), 0
words = []
while b < n:
e = b + 1
next_round = False
for i in range(e, n+1):
if next_round or (b == 0 and i == n):
break
subword = eojeol[b:i]
if self.dictionary.word_is_tag(subword, tag):
words.append(LR(subword, tag, '', None, b, i, i))
b = i
next_round = True
break
if not next_round:
return []
return words
class LRTemplateMatcher(BaseTemplateMatcher):
def __init__(self, dictionary, ltags=None, templates=None):
if not ltags:
ltags = {'Noun', 'Adjective', 'Verb', 'Adverb', 'Exclamation'}
if not templates:
templates = {'Noun': ('Josa', 'Verb', 'Adjective')}
self.dictionary = dictionary
self.ltags = ltags
self.rtags = {tag for tags in templates.values() for tag in tags}
self.templates = templates
def generate(self, token):
if sys.version_info.major == 2:
token = unicode(token)
candidates = self._initialize_L(token)
candidates = self._expand_R(token, candidates)
return candidates
def _pos_L(self, word):
poses = self.dictionary.get_pos(word)
poses = {pos for pos in poses if pos in self.ltags}
return poses
def _initialize_L(self, t):
n = len(t)
candidates = []
for b in range(n):
for e in range(b+2, min(n, b + self.dictionary.max_length) + 1):
l = t[b:e]
l_tags = self._pos_L(l)
if not l_tags:
continue
for l_tag in l_tags:
candidates.append([l, l_tag, b, e])
candidates = self._remove_subset_l(candidates)
return sorted(candidates, key=lambda x:x[2])
def _remove_subset_l(self, candidates):
candidates_ = []
for l_tag in self.ltags:
# Sort by length of L
sorted_ = sorted(
filter(lambda x:x[1] == l_tag, candidates),
key=lambda x:-(x[3] - x[2])
)
while sorted_:
candidates_.append(sorted_.pop(0))
(b, e) = (candidates_[-1][2], candidates_[-1][3])
# Find overlapped
removals = [i for i, c in enumerate(sorted_) if b <= c[2] and e >= c[3]]
for idx in reversed(removals):
del sorted_[idx]
return candidates_
def _expand_R(self, t, candidates):
n = len(t)
expanded = []
for (l, l_tag, b, e1) in candidates:
last = min(self.dictionary.max_length + e1, n)
for e2 in range(e1, last + 1):
r = t[e1:e2]
if not r:
expanded.append(LR(l, l_tag, r, None, b, e1, e2))
else:
for r_tag in self.templates.get(l_tag, []):
if not self.dictionary.word_is_tag(r, r_tag):
continue
expanded.append(LR(l, l_tag, r, r_tag, b, e1, e2))
expanded = self._remove_subset_r(expanded)
return sorted(expanded, key=lambda x:x.b)
def _remove_subset_r(self, expanded):
expanded_ = []
rtags = [rtag for rtag in self.rtags] + [None]
for r_tag in rtags:
# Sory by length of R
sorted_ = sorted(
filter(lambda x:x.r_tag == r_tag, expanded),
key=lambda x:-(x.e - x.m)
)
while sorted_:
expanded_.append(sorted_.pop(0))
l_tag = expanded_[-1].l_tag
(b, m, e) = expanded_[-1][-3:]
# Find subset
removals = [i for i, c in enumerate(sorted_)
if ((c.l_tag == l_tag)
and (b == c.b and m == c.m)
and (m <= c.m and e >= c.e))
]
for idx in reversed(removals):
del sorted_[idx]
return expanded_ | SoyNLP/soynlp/pos/_template.py | import sys
from collections import namedtuple
# b:begin, m: middle, e: end
LR = namedtuple('LR', 'l l_tag r r_tag b m e')
class BaseTemplateMatcher:
def generate(self, token):
raise NotImplementedError
class EojeolTemplateMatcher(BaseTemplateMatcher):
def __init__(self, dictionary, single_tags=None, lr_templates=None):
if not single_tags:
single_tags = ['Noun', 'Verb', 'Adjective', 'Adverb', 'Exclamation']
if not lr_templates:
lr_templates = [('Noun', 'Verb'), ('Noun', 'Adjective'), ('Noun', 'Josa')]
self.dictionary = dictionary
self.single_tags = single_tags
self.lr_templates = lr_templates
def generate(self, eojeol):
n = len(eojeol)
candidates = []
for tag in self.dictionary.get_pos(eojeol):
if tag in self.single_tags:
candidates.append([LR(eojeol, tag, '', None, 0, n, n)])
if not candidates:
candidates.append([LR(eojeol, None, '', None, 0, n, n)])
for b in range(1, n):
l, r = eojeol[:b], eojeol[b:]
for l_tag, r_tag in self.lr_templates:
if self.dictionary.word_is_tag(l, l_tag) and self.dictionary.word_is_tag(r, r_tag):
candidates.append([LR(l, l_tag, r, r_tag, 0, b, n)])
compound_noun = self._decompose_compound(eojeol, 'Noun')
if compound_noun:
candidates.append(compound_noun)
compound_adverb = self._decompose_compound(eojeol, 'Adverb')
if compound_adverb:
candidates.append(compound_adverb)
return candidates
def _decompose_compound(self, eojeol, tag):
n, b = len(eojeol), 0
words = []
while b < n:
e = b + 1
next_round = False
for i in range(e, n+1):
if next_round or (b == 0 and i == n):
break
subword = eojeol[b:i]
if self.dictionary.word_is_tag(subword, tag):
words.append(LR(subword, tag, '', None, b, i, i))
b = i
next_round = True
break
if not next_round:
return []
return words
class LRTemplateMatcher(BaseTemplateMatcher):
def __init__(self, dictionary, ltags=None, templates=None):
if not ltags:
ltags = {'Noun', 'Adjective', 'Verb', 'Adverb', 'Exclamation'}
if not templates:
templates = {'Noun': ('Josa', 'Verb', 'Adjective')}
self.dictionary = dictionary
self.ltags = ltags
self.rtags = {tag for tags in templates.values() for tag in tags}
self.templates = templates
def generate(self, token):
if sys.version_info.major == 2:
token = unicode(token)
candidates = self._initialize_L(token)
candidates = self._expand_R(token, candidates)
return candidates
def _pos_L(self, word):
poses = self.dictionary.get_pos(word)
poses = {pos for pos in poses if pos in self.ltags}
return poses
def _initialize_L(self, t):
n = len(t)
candidates = []
for b in range(n):
for e in range(b+2, min(n, b + self.dictionary.max_length) + 1):
l = t[b:e]
l_tags = self._pos_L(l)
if not l_tags:
continue
for l_tag in l_tags:
candidates.append([l, l_tag, b, e])
candidates = self._remove_subset_l(candidates)
return sorted(candidates, key=lambda x:x[2])
def _remove_subset_l(self, candidates):
candidates_ = []
for l_tag in self.ltags:
# Sort by length of L
sorted_ = sorted(
filter(lambda x:x[1] == l_tag, candidates),
key=lambda x:-(x[3] - x[2])
)
while sorted_:
candidates_.append(sorted_.pop(0))
(b, e) = (candidates_[-1][2], candidates_[-1][3])
# Find overlapped
removals = [i for i, c in enumerate(sorted_) if b <= c[2] and e >= c[3]]
for idx in reversed(removals):
del sorted_[idx]
return candidates_
def _expand_R(self, t, candidates):
n = len(t)
expanded = []
for (l, l_tag, b, e1) in candidates:
last = min(self.dictionary.max_length + e1, n)
for e2 in range(e1, last + 1):
r = t[e1:e2]
if not r:
expanded.append(LR(l, l_tag, r, None, b, e1, e2))
else:
for r_tag in self.templates.get(l_tag, []):
if not self.dictionary.word_is_tag(r, r_tag):
continue
expanded.append(LR(l, l_tag, r, r_tag, b, e1, e2))
expanded = self._remove_subset_r(expanded)
return sorted(expanded, key=lambda x:x.b)
def _remove_subset_r(self, expanded):
expanded_ = []
rtags = [rtag for rtag in self.rtags] + [None]
for r_tag in rtags:
# Sory by length of R
sorted_ = sorted(
filter(lambda x:x.r_tag == r_tag, expanded),
key=lambda x:-(x.e - x.m)
)
while sorted_:
expanded_.append(sorted_.pop(0))
l_tag = expanded_[-1].l_tag
(b, m, e) = expanded_[-1][-3:]
# Find subset
removals = [i for i, c in enumerate(sorted_)
if ((c.l_tag == l_tag)
and (b == c.b and m == c.m)
and (m <= c.m and e >= c.e))
]
for idx in reversed(removals):
del sorted_[idx]
return expanded_ | 0.350199 | 0.337067 |
from pickle import load
from pickle import dump
from collections import Counter
# load a clean dataset
def load_clean_sentences(filename):
return load(open(filename, 'rb'))
# save a list of clean sentences to file
def save_clean_sentences(sentences, filename):
dump(sentences, open(filename, 'wb'))
print('Saved: %s' % filename)
# create a frequency table for all words
def to_vocab(lines):
vocab = Counter()
for line in lines:
tokens = line.split()
vocab.update(tokens)
return vocab
# remove all words with a frequency below a threshold
def trim_vocab(vocab, min_occurance):
tokens = [k for k,c in vocab.items() if c >= min_occurance]
return set(tokens)
# mark all OOV with "unk" for all lines
def update_dataset(lines, vocab):
new_lines = list()
for line in lines:
new_tokens = list()
for token in line.split():
if token in vocab:
new_tokens.append(token)
else:
new_tokens.append('unk')
new_line = ' '.join(new_tokens)
new_lines.append(new_line)
return new_lines
# load English dataset
filename = 'English.pkl'
lines = load_clean_sentences(filename)
# calculate vocabulary
vocab = to_vocab(lines)
print('English Vocabulary: %d' % len(vocab))
# reduce vocabulary
vocab = trim_vocab(vocab, 5)
print('New English Vocabulary: %d' % len(vocab))
# mark out of vocabulary words
lines = update_dataset(lines, vocab)
# save updated dataset
filename = 'english_vocab.pkl'
save_clean_sentences(lines, filename)
# spot check
for i in range(20):
print("line",i,":",lines[i])
# load French dataset
filename = 'French.pkl'
lines = load_clean_sentences(filename)
# calculate vocabulary
vocab = to_vocab(lines)
print('French Vocabulary: %d' % len(vocab))
# reduce vocabulary
vocab = trim_vocab(vocab, 5)
print('New French Vocabulary: %d' % len(vocab))
# mark out of vocabulary words
lines = update_dataset(lines, vocab)
# save updated dataset
filename = 'french_vocab.pkl'
save_clean_sentences(lines, filename)
# spot check
for i in range(20):
print("line",i,":",lines[i]) | Chapter06/read_clean.py |
from pickle import load
from pickle import dump
from collections import Counter
# load a clean dataset
def load_clean_sentences(filename):
return load(open(filename, 'rb'))
# save a list of clean sentences to file
def save_clean_sentences(sentences, filename):
dump(sentences, open(filename, 'wb'))
print('Saved: %s' % filename)
# create a frequency table for all words
def to_vocab(lines):
vocab = Counter()
for line in lines:
tokens = line.split()
vocab.update(tokens)
return vocab
# remove all words with a frequency below a threshold
def trim_vocab(vocab, min_occurance):
tokens = [k for k,c in vocab.items() if c >= min_occurance]
return set(tokens)
# mark all OOV with "unk" for all lines
def update_dataset(lines, vocab):
new_lines = list()
for line in lines:
new_tokens = list()
for token in line.split():
if token in vocab:
new_tokens.append(token)
else:
new_tokens.append('unk')
new_line = ' '.join(new_tokens)
new_lines.append(new_line)
return new_lines
# load English dataset
filename = 'English.pkl'
lines = load_clean_sentences(filename)
# calculate vocabulary
vocab = to_vocab(lines)
print('English Vocabulary: %d' % len(vocab))
# reduce vocabulary
vocab = trim_vocab(vocab, 5)
print('New English Vocabulary: %d' % len(vocab))
# mark out of vocabulary words
lines = update_dataset(lines, vocab)
# save updated dataset
filename = 'english_vocab.pkl'
save_clean_sentences(lines, filename)
# spot check
for i in range(20):
print("line",i,":",lines[i])
# load French dataset
filename = 'French.pkl'
lines = load_clean_sentences(filename)
# calculate vocabulary
vocab = to_vocab(lines)
print('French Vocabulary: %d' % len(vocab))
# reduce vocabulary
vocab = trim_vocab(vocab, 5)
print('New French Vocabulary: %d' % len(vocab))
# mark out of vocabulary words
lines = update_dataset(lines, vocab)
# save updated dataset
filename = 'french_vocab.pkl'
save_clean_sentences(lines, filename)
# spot check
for i in range(20):
print("line",i,":",lines[i]) | 0.318591 | 0.21566 |
import copy
from kripke_model import get_relations, generate_worlds, get_proposition
from codemaker import LENGTH_OF_CODE
from github_com.erohkohl.mlsolver.kripke import KripkeStructure
class KnowledgeManager:
"""
Maintains the knowledge structure for the game.
Initialises with a Kripke Model for the game.
Keeps track of the real world, according to the secret code.
Processes every move to update the knowledge structure accrodingly.
"""
def __init__(self):
worlds = generate_worlds()
relations = get_relations(worlds)
self.model = KripkeStructure(worlds, relations)
def get_real_world(self, code):
"""
Initialises the real world in the Kripke Model
from the secret code generated for the game.
"""
real_world_assignment = get_assignment(code)
for world in self.model.worlds:
if world.assignment == real_world_assignment:
self.real_world = world
return
def handle_move(self, move, feedback):
"""
Handles each move and its feedback as a public
announcement, and restricts the available model
accordingly.
"""
for i in range(0, LENGTH_OF_CODE):
if feedback[i] == 1:
assignment = get_proposition(i+1, move[i])
self.__handle_perfectly_correct_element(assignment)
if feedback[i] == 0:
assignment = get_proposition(i+1, move[i])
self.__handle_wrongly_positioned_element(
assignment)
if feedback[i] == -1:
self.__handle_incorrect_element(move[i])
return
def __handle_perfectly_correct_element(self, assignment):
"""
For correctly guessed color, remove the worlds
which have some other color at this position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
if not (assignment in w.assignment):
self.model.remove_node_by_name(w.name)
return
def __handle_wrongly_positioned_element(self, assignment):
"""
For wrongly positioned color, remove the worlds
which have this color at this position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
if assignment in w.assignment:
self.model.remove_node_by_name(w.name)
return
def __handle_incorrect_element(self, color_number):
"""
For incorrectly guessed color, remove the worlds
which have this color at any position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
for i in range(1, LENGTH_OF_CODE+1):
assignment = get_proposition(i, color_number)
if assignment in w.assignment:
self.model.remove_node_by_name(w.name)
return
def get_assignment(code):
"""
Get world assignment from the code
[1 2 3 4] -> {'1:yellow', '2:violet', '3:red', '4:green'}
"""
assignment = {}
for i in range(0, LENGTH_OF_CODE):
proposition = get_proposition(i+1, code[i])
assignment[proposition] = True
return assignment | knowledge_manager.py | import copy
from kripke_model import get_relations, generate_worlds, get_proposition
from codemaker import LENGTH_OF_CODE
from github_com.erohkohl.mlsolver.kripke import KripkeStructure
class KnowledgeManager:
"""
Maintains the knowledge structure for the game.
Initialises with a Kripke Model for the game.
Keeps track of the real world, according to the secret code.
Processes every move to update the knowledge structure accrodingly.
"""
def __init__(self):
worlds = generate_worlds()
relations = get_relations(worlds)
self.model = KripkeStructure(worlds, relations)
def get_real_world(self, code):
"""
Initialises the real world in the Kripke Model
from the secret code generated for the game.
"""
real_world_assignment = get_assignment(code)
for world in self.model.worlds:
if world.assignment == real_world_assignment:
self.real_world = world
return
def handle_move(self, move, feedback):
"""
Handles each move and its feedback as a public
announcement, and restricts the available model
accordingly.
"""
for i in range(0, LENGTH_OF_CODE):
if feedback[i] == 1:
assignment = get_proposition(i+1, move[i])
self.__handle_perfectly_correct_element(assignment)
if feedback[i] == 0:
assignment = get_proposition(i+1, move[i])
self.__handle_wrongly_positioned_element(
assignment)
if feedback[i] == -1:
self.__handle_incorrect_element(move[i])
return
def __handle_perfectly_correct_element(self, assignment):
"""
For correctly guessed color, remove the worlds
which have some other color at this position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
if not (assignment in w.assignment):
self.model.remove_node_by_name(w.name)
return
def __handle_wrongly_positioned_element(self, assignment):
"""
For wrongly positioned color, remove the worlds
which have this color at this position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
if assignment in w.assignment:
self.model.remove_node_by_name(w.name)
return
def __handle_incorrect_element(self, color_number):
"""
For incorrectly guessed color, remove the worlds
which have this color at any position
and derive the reduced model.
"""
worlds = copy.deepcopy(self.model.worlds)
for w in worlds:
for i in range(1, LENGTH_OF_CODE+1):
assignment = get_proposition(i, color_number)
if assignment in w.assignment:
self.model.remove_node_by_name(w.name)
return
def get_assignment(code):
"""
Get world assignment from the code
[1 2 3 4] -> {'1:yellow', '2:violet', '3:red', '4:green'}
"""
assignment = {}
for i in range(0, LENGTH_OF_CODE):
proposition = get_proposition(i+1, code[i])
assignment[proposition] = True
return assignment | 0.626581 | 0.482551 |
from tectle.db import get_connection_non_flask
from tectle.config import load_config_non_flask
import requests
def upgrade(conn, cur, config):
version = get_version(cur)
new_version = version
try:
if version < 1:
query = """
CREATE TABLE db_version (
version INTEGER
);
"""
cur.execute(query)
query = """
INSERT INTO db_version (version)
VALUES (0);
"""
cur.execute(query)
query = """
CREATE TABLE gcodes (
id INTEGER PRIMARY KEY,
filename TEXT,
date_modified INTEGER
);
"""
cur.execute(query)
query = """
CREATE TABLE printer_gcodes (
id INTEGER PRIMARY KEY,
filename TEXT,
printer_ip TEXT,
date_modified INTEGER
)
"""
cur.execute(query)
conn.commit()
new_version = 1
if version < 2:
query = """
ALTER TABLE printer_gcodes ADD COLUMN progress INTEGER DEFAULT 100
"""
cur.executescript(query)
conn.commit()
new_version = 2
if version < 3:
query = """
ALTER TABLE printers ADD COLUMN progress INTEGER DEFAULT 0
"""
cur.executescript(query)
conn.commit()
new_version = 3
if version < 4:
query = """
ALTER TABLE printers ADD COLUMN waterplate_only INTEGER DEFAULT 0
"""
cur.executescript(query)
conn.commit()
new_version = 4
if version < 5:
response = requests.get("https://openapi.etsy.com/v2/countries?api_key="+config['API_KEY'])
rows = response.json()['results']
query = """
CREATE TABLE countries (
id INTEGER PRIMARY KEY,
country_id INTEGER, /* Etsy */
country_code TEXT, /* CA, US, FR */
name TEXT /* Canada */
);
INSERT INTO countries (country_id, country_code, name)
VALUES %s
""" % ',\n'.join(["(%(country_id)s, '%(iso_country_code)s', '%(name)s')" % row for row in rows])
cur.executescript(query)
conn.commit()
new_version = 5
if version < 6:
fh = open('scripts/resources/country_values.txt', 'r')
values = fh.read()
fh.close()
query = """
DROP TABLE IF EXISTS countries;
CREATE TABLE countries (
id INTEGER PRIMARY KEY,
country_id INTEGER, /* Etsy */
country_code TEXT, /* CA, US, FR */
name TEXT, /* Canada */
currency TEXT, /* CAD */
fxrate REAL /* 1.0 */
);
INSERT INTO countries (country_id, country_code, name, currency, fxrate)
VALUES %s
""" % values
cur.executescript(query)
conn.commit()
new_version = 6
if version < 7:
query = """
UPDATE colors SET color_abbr = 'SK', color = 'Sky Blue' WHERE color = 'Blue';
UPDATE printers SET color = 'Sky Blue' WHERE color = 'Blue';
UPDATE products SET sku = REPLACE(sku, 'BT', 'SK'), color = 'Sky Blue' WHERE color = 'Blue';
UPDATE receipt_packages SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE inventory SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE printer_queue SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE colors SET color_abbr = 'BK' WHERE color = 'Black';
UPDATE products SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE receipt_packages SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE inventory SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE printer_queue SET sku = REPLACE(sku, 'KT', 'BK');
DELETE FROM colors WHERE color = 'Red';
UPDATE printers SET color = 'White' WHERE color = 'Red';
"""
cur.executescript(query)
conn.commit()
new_version = 7
if version < 8:
query = """
UPDATE colors SET color_abbr = 'SB' WHERE color = 'Sky Blue';
UPDATE products SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE receipt_packages SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE inventory SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE printer_queue SET sku = REPLACE(sku, 'SK', 'SB');
"""
cur.executescript(query)
conn.commit()
new_version = 8
if version < 9:
# delete gcodes and printer_gcodes on next version
gcode_folder = config['GCODE_FOLDER']
query = """
CREATE TABLE file_manager (
id INTEGER PRIMARY KEY,
filename TEXT,
date_modified INTEGER,
local_parent TEXT,
remote_path TEXT
);
CREATE TABLE printer_files (
id INTEGER PRIMARY KEY,
file_manager_id TEXT,
filename TEXT,
printer_ip TEXT,
date_modified INTEGER,
remote_path TEXT,
progress INTEGER DEFAULT 100,
FOREIGN KEY (file_manager_id) REFERENCES file_manager(id)
);
INSERT INTO file_manager (filename, date_modified, local_parent, remote_path)
SELECT filename,
date_modified,
"%s" as local_parent,
"gcodes\" as remote_path
FROM gcodes;
INSERT INTO printer_files (file_manager_id, filename, printer_ip, date_modified, remote_path)
SELECT fm.id as file_manager_id,
pg.filename,
pg.printer_ip,
pg.date_modified,
fm.remote_path
FROM printer_gcodes pg
JOIN file_manager fm ON pg.filename = fm.filename;
""" % gcode_folder
cur.executescript(query)
new_version = 9
if version < 10:
query = """
CREATE TABLE filament_inventory (
id INTEGER PRIMARY KEY,
color TEXT,
weight_kg REAL DEFAULT 0
);
INSERT INTO filament_inventory (color)
SELECT color
FROM colors;
ALTER TABLE boxes ADD COLUMN quantity INTEGER DEFAULT 0;
ALTER TABLE products ADD COLUMN print_time INTEGER DEFAULT 0;
ALTER TABLE products ADD COLUMN filament_weight_kg REAL DEFAULT 0;
"""
cur.executescript(query)
new_version = 10
if version < 11:
query = """
CREATE TABLE exceptions (
id INTEGER PRIMARY KEY,
query TEXT NOT NULL, /* must be a query that evaluates to COUNT(1) > 0 if error */
message TEXT NOT NULL, /* query allows for %s with the count amount as replacement */
level INTEGER DEFAULT 0, /* warning = 0, error = 1 */
status INTEGER DEFAULT 0 /* enabled = 0, disabled = 1 */
);
INSERT INTO exceptions (query, message, level, status)
VALUES ('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''White'' ',
'Low on White filament', 0, 0),
('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''Sky Blue'' ',
'Low on Sky Blue filament', 0, 0),
('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''Black'' ',
'Low on Black filament', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''A'' ',
'Low on Box A', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''B'' ',
'Low on Box B', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''C'' ',
'Low on Box C', 0, 0);
"""
cur.executescript(query)
new_version = 11
if version < 12:
query = """
ALTER TABLE manifest_links ADD COLUMN po_number TEXT;
"""
cur.executescript(query)
new_version = 12
if version < 13:
query = """
ALTER TABLE printers ADD COLUMN rtsp_url TEXT;
"""
cur.executescript(query)
new_version = 13
if version < 14:
query = """
INSERT INTO colors (color, color_abbr)
VALUES ('Blue', 'BL'),
('Teal', 'TL'),
('Orange', 'OJ'),
('Yellow', 'YL');
INSERT INTO filament_inventory (color)
VALUES ('Blue'),
('Teal'),
('Orange'),
('Yellow');
"""
cur.executescript(query)
new_version = 14
except Exception as e:
conn.rollback()
print(e)
if new_version > version:
try:
update_version(cur, new_version)
conn.commit()
print('Updated to version %s' % new_version)
except:
conn.rollback()
print('Failed to update please re-run')
else:
print('DB Version %s' % version)
def get_version(cur):
query = """
SELECT COUNT(1)
FROM sqlite_master
WHERE type = 'table'
AND name = 'db_version'
"""
cur.execute(query)
exists = cur.fetchone()[0]
version = 0
if exists:
query = """
SELECT version
FROM db_version
"""
cur.execute(query)
version = cur.fetchone()[0]
return version
def update_version(cur, new_version):
query = "UPDATE db_version SET version = %s" % new_version
cur.execute(query)
def upgrade_non_flask():
config = load_config_non_flask()
conn = get_connection_non_flask(config['DEBUG'] == 'True')
cur = conn.cursor()
upgrade(conn, cur, config)
if __name__ == '__main__':
upgrade_non_flask() | scripts/upgrade.py | from tectle.db import get_connection_non_flask
from tectle.config import load_config_non_flask
import requests
def upgrade(conn, cur, config):
version = get_version(cur)
new_version = version
try:
if version < 1:
query = """
CREATE TABLE db_version (
version INTEGER
);
"""
cur.execute(query)
query = """
INSERT INTO db_version (version)
VALUES (0);
"""
cur.execute(query)
query = """
CREATE TABLE gcodes (
id INTEGER PRIMARY KEY,
filename TEXT,
date_modified INTEGER
);
"""
cur.execute(query)
query = """
CREATE TABLE printer_gcodes (
id INTEGER PRIMARY KEY,
filename TEXT,
printer_ip TEXT,
date_modified INTEGER
)
"""
cur.execute(query)
conn.commit()
new_version = 1
if version < 2:
query = """
ALTER TABLE printer_gcodes ADD COLUMN progress INTEGER DEFAULT 100
"""
cur.executescript(query)
conn.commit()
new_version = 2
if version < 3:
query = """
ALTER TABLE printers ADD COLUMN progress INTEGER DEFAULT 0
"""
cur.executescript(query)
conn.commit()
new_version = 3
if version < 4:
query = """
ALTER TABLE printers ADD COLUMN waterplate_only INTEGER DEFAULT 0
"""
cur.executescript(query)
conn.commit()
new_version = 4
if version < 5:
response = requests.get("https://openapi.etsy.com/v2/countries?api_key="+config['API_KEY'])
rows = response.json()['results']
query = """
CREATE TABLE countries (
id INTEGER PRIMARY KEY,
country_id INTEGER, /* Etsy */
country_code TEXT, /* CA, US, FR */
name TEXT /* Canada */
);
INSERT INTO countries (country_id, country_code, name)
VALUES %s
""" % ',\n'.join(["(%(country_id)s, '%(iso_country_code)s', '%(name)s')" % row for row in rows])
cur.executescript(query)
conn.commit()
new_version = 5
if version < 6:
fh = open('scripts/resources/country_values.txt', 'r')
values = fh.read()
fh.close()
query = """
DROP TABLE IF EXISTS countries;
CREATE TABLE countries (
id INTEGER PRIMARY KEY,
country_id INTEGER, /* Etsy */
country_code TEXT, /* CA, US, FR */
name TEXT, /* Canada */
currency TEXT, /* CAD */
fxrate REAL /* 1.0 */
);
INSERT INTO countries (country_id, country_code, name, currency, fxrate)
VALUES %s
""" % values
cur.executescript(query)
conn.commit()
new_version = 6
if version < 7:
query = """
UPDATE colors SET color_abbr = 'SK', color = 'Sky Blue' WHERE color = 'Blue';
UPDATE printers SET color = 'Sky Blue' WHERE color = 'Blue';
UPDATE products SET sku = REPLACE(sku, 'BT', 'SK'), color = 'Sky Blue' WHERE color = 'Blue';
UPDATE receipt_packages SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE inventory SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE printer_queue SET sku = REPLACE(sku, 'BT', 'SK');
UPDATE colors SET color_abbr = 'BK' WHERE color = 'Black';
UPDATE products SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE receipt_packages SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE inventory SET sku = REPLACE(sku, 'KT', 'BK');
UPDATE printer_queue SET sku = REPLACE(sku, 'KT', 'BK');
DELETE FROM colors WHERE color = 'Red';
UPDATE printers SET color = 'White' WHERE color = 'Red';
"""
cur.executescript(query)
conn.commit()
new_version = 7
if version < 8:
query = """
UPDATE colors SET color_abbr = 'SB' WHERE color = 'Sky Blue';
UPDATE products SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE receipt_packages SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE inventory SET sku = REPLACE(sku, 'SK', 'SB');
UPDATE printer_queue SET sku = REPLACE(sku, 'SK', 'SB');
"""
cur.executescript(query)
conn.commit()
new_version = 8
if version < 9:
# delete gcodes and printer_gcodes on next version
gcode_folder = config['GCODE_FOLDER']
query = """
CREATE TABLE file_manager (
id INTEGER PRIMARY KEY,
filename TEXT,
date_modified INTEGER,
local_parent TEXT,
remote_path TEXT
);
CREATE TABLE printer_files (
id INTEGER PRIMARY KEY,
file_manager_id TEXT,
filename TEXT,
printer_ip TEXT,
date_modified INTEGER,
remote_path TEXT,
progress INTEGER DEFAULT 100,
FOREIGN KEY (file_manager_id) REFERENCES file_manager(id)
);
INSERT INTO file_manager (filename, date_modified, local_parent, remote_path)
SELECT filename,
date_modified,
"%s" as local_parent,
"gcodes\" as remote_path
FROM gcodes;
INSERT INTO printer_files (file_manager_id, filename, printer_ip, date_modified, remote_path)
SELECT fm.id as file_manager_id,
pg.filename,
pg.printer_ip,
pg.date_modified,
fm.remote_path
FROM printer_gcodes pg
JOIN file_manager fm ON pg.filename = fm.filename;
""" % gcode_folder
cur.executescript(query)
new_version = 9
if version < 10:
query = """
CREATE TABLE filament_inventory (
id INTEGER PRIMARY KEY,
color TEXT,
weight_kg REAL DEFAULT 0
);
INSERT INTO filament_inventory (color)
SELECT color
FROM colors;
ALTER TABLE boxes ADD COLUMN quantity INTEGER DEFAULT 0;
ALTER TABLE products ADD COLUMN print_time INTEGER DEFAULT 0;
ALTER TABLE products ADD COLUMN filament_weight_kg REAL DEFAULT 0;
"""
cur.executescript(query)
new_version = 10
if version < 11:
query = """
CREATE TABLE exceptions (
id INTEGER PRIMARY KEY,
query TEXT NOT NULL, /* must be a query that evaluates to COUNT(1) > 0 if error */
message TEXT NOT NULL, /* query allows for %s with the count amount as replacement */
level INTEGER DEFAULT 0, /* warning = 0, error = 1 */
status INTEGER DEFAULT 0 /* enabled = 0, disabled = 1 */
);
INSERT INTO exceptions (query, message, level, status)
VALUES ('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''White'' ',
'Low on White filament', 0, 0),
('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''Sky Blue'' ',
'Low on Sky Blue filament', 0, 0),
('SELECT COUNT(1) FROM filament_inventory WHERE weight_kg < 15 AND color = ''Black'' ',
'Low on Black filament', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''A'' ',
'Low on Box A', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''B'' ',
'Low on Box B', 0, 0),
('SELECT COUNT(1) FROM boxes WHERE quantity < 20 AND type = ''C'' ',
'Low on Box C', 0, 0);
"""
cur.executescript(query)
new_version = 11
if version < 12:
query = """
ALTER TABLE manifest_links ADD COLUMN po_number TEXT;
"""
cur.executescript(query)
new_version = 12
if version < 13:
query = """
ALTER TABLE printers ADD COLUMN rtsp_url TEXT;
"""
cur.executescript(query)
new_version = 13
if version < 14:
query = """
INSERT INTO colors (color, color_abbr)
VALUES ('Blue', 'BL'),
('Teal', 'TL'),
('Orange', 'OJ'),
('Yellow', 'YL');
INSERT INTO filament_inventory (color)
VALUES ('Blue'),
('Teal'),
('Orange'),
('Yellow');
"""
cur.executescript(query)
new_version = 14
except Exception as e:
conn.rollback()
print(e)
if new_version > version:
try:
update_version(cur, new_version)
conn.commit()
print('Updated to version %s' % new_version)
except:
conn.rollback()
print('Failed to update please re-run')
else:
print('DB Version %s' % version)
def get_version(cur):
query = """
SELECT COUNT(1)
FROM sqlite_master
WHERE type = 'table'
AND name = 'db_version'
"""
cur.execute(query)
exists = cur.fetchone()[0]
version = 0
if exists:
query = """
SELECT version
FROM db_version
"""
cur.execute(query)
version = cur.fetchone()[0]
return version
def update_version(cur, new_version):
query = "UPDATE db_version SET version = %s" % new_version
cur.execute(query)
def upgrade_non_flask():
config = load_config_non_flask()
conn = get_connection_non_flask(config['DEBUG'] == 'True')
cur = conn.cursor()
upgrade(conn, cur, config)
if __name__ == '__main__':
upgrade_non_flask() | 0.22051 | 0.050471 |
from collections import defaultdict
import sys
UP = (-1, 0)
DOWN = (1, 0)
LEFT = (0, -1)
RIGHT = (0, 1)
def default_factory():
return "."
def turn_left(direction):
if direction == UP:
return LEFT
if direction == LEFT:
return DOWN
if direction == DOWN:
return RIGHT
if direction == RIGHT:
return UP
def turn_right(direction):
if direction == UP:
return RIGHT
if direction == RIGHT:
return DOWN
if direction == DOWN:
return LEFT
if direction == LEFT:
return UP
def turn_around(direction):
if direction == UP:
return DOWN
if direction == RIGHT:
return LEFT
if direction == DOWN:
return UP
if direction == LEFT:
return RIGHT
def do_moves(map, cur_pos, num_moves):
cur_direction = UP
infected = 0
for _ in xrange(num_moves):
# Infect / cleanse / choose direction of travel
if map[cur_pos] == ".":
map[cur_pos] = "W"
cur_direction = turn_left(cur_direction)
elif map[cur_pos] == "W":
map[cur_pos] = "#"
infected += 1
elif map[cur_pos] == "#":
map[cur_pos] = "F"
cur_direction = turn_right(cur_direction)
elif map[cur_pos] == "F":
map[cur_pos] = "."
cur_direction = turn_around(cur_direction)
# Do move
cur_pos = (cur_pos[0] + cur_direction[0], cur_pos[1] + cur_direction[1])
return infected
def load_map(filename):
cur_pos = (0, 0)
map = defaultdict(default_factory)
with open(filename, "r") as f:
for row_idx, line in enumerate(f.readlines()):
line = line.strip()
cur_pos = (row_idx, 0)
for cell_idx, cell in zip(xrange(len(line)), line):
map[(row_idx, cell_idx)] = cell
cur_pos = (row_idx, cell_idx)
cur_pos = (cur_pos[0] / 2), (cur_pos[1] / 2)
return map, cur_pos
def dump_map(map):
for row_idx in xrange(-5, 10, 1):
row = "{:03} ".format(row_idx)
for cell_idx in xrange(-5, 10, 1):
row += map[(row_idx, cell_idx)]
print row
# Run some tests on the code.
MAP, CUR_POS = load_map("test_map.txt")
INFECTIONS = do_moves(MAP, CUR_POS, 100)
if INFECTIONS != 26:
print "First map moves failed. [{0}]".format(INFECTIONS)
dump_map(MAP)
sys.exit(-1)
print "First moves ok"
MAP, CUR_POS = load_map("test_map.txt")
INFECTIONS = do_moves(MAP, CUR_POS, 10000000)
if INFECTIONS != 2511944:
print "Second map moves failed. [{0}]".format(INFECTIONS)
dump_map(MAP)
sys.exit(-1)
print "Second moves ok"
print "All tests passed."
# All tests passing...
MAP, CUR_POS = load_map("input.txt")
print "Solution is: {0}".format(do_moves(MAP, CUR_POS, 10000000)) | 2017/day_22/solution_p2.py | from collections import defaultdict
import sys
UP = (-1, 0)
DOWN = (1, 0)
LEFT = (0, -1)
RIGHT = (0, 1)
def default_factory():
return "."
def turn_left(direction):
if direction == UP:
return LEFT
if direction == LEFT:
return DOWN
if direction == DOWN:
return RIGHT
if direction == RIGHT:
return UP
def turn_right(direction):
if direction == UP:
return RIGHT
if direction == RIGHT:
return DOWN
if direction == DOWN:
return LEFT
if direction == LEFT:
return UP
def turn_around(direction):
if direction == UP:
return DOWN
if direction == RIGHT:
return LEFT
if direction == DOWN:
return UP
if direction == LEFT:
return RIGHT
def do_moves(map, cur_pos, num_moves):
cur_direction = UP
infected = 0
for _ in xrange(num_moves):
# Infect / cleanse / choose direction of travel
if map[cur_pos] == ".":
map[cur_pos] = "W"
cur_direction = turn_left(cur_direction)
elif map[cur_pos] == "W":
map[cur_pos] = "#"
infected += 1
elif map[cur_pos] == "#":
map[cur_pos] = "F"
cur_direction = turn_right(cur_direction)
elif map[cur_pos] == "F":
map[cur_pos] = "."
cur_direction = turn_around(cur_direction)
# Do move
cur_pos = (cur_pos[0] + cur_direction[0], cur_pos[1] + cur_direction[1])
return infected
def load_map(filename):
cur_pos = (0, 0)
map = defaultdict(default_factory)
with open(filename, "r") as f:
for row_idx, line in enumerate(f.readlines()):
line = line.strip()
cur_pos = (row_idx, 0)
for cell_idx, cell in zip(xrange(len(line)), line):
map[(row_idx, cell_idx)] = cell
cur_pos = (row_idx, cell_idx)
cur_pos = (cur_pos[0] / 2), (cur_pos[1] / 2)
return map, cur_pos
def dump_map(map):
for row_idx in xrange(-5, 10, 1):
row = "{:03} ".format(row_idx)
for cell_idx in xrange(-5, 10, 1):
row += map[(row_idx, cell_idx)]
print row
# Run some tests on the code.
MAP, CUR_POS = load_map("test_map.txt")
INFECTIONS = do_moves(MAP, CUR_POS, 100)
if INFECTIONS != 26:
print "First map moves failed. [{0}]".format(INFECTIONS)
dump_map(MAP)
sys.exit(-1)
print "First moves ok"
MAP, CUR_POS = load_map("test_map.txt")
INFECTIONS = do_moves(MAP, CUR_POS, 10000000)
if INFECTIONS != 2511944:
print "Second map moves failed. [{0}]".format(INFECTIONS)
dump_map(MAP)
sys.exit(-1)
print "Second moves ok"
print "All tests passed."
# All tests passing...
MAP, CUR_POS = load_map("input.txt")
print "Solution is: {0}".format(do_moves(MAP, CUR_POS, 10000000)) | 0.424054 | 0.510069 |
import requests
import json
import seismo
import numpy as np
from . import utils
class RemoteFunction(object):
'''
This class represents a remote function that can be called on a
seismo-server
'''
def __init__(self, name, host='http://localhost', port=5000):
'''
Initialise this with the name of the remote function. This is meant
to be one of the functions as part of seismo
'''
self.name = name
self.host = host
self.port = port
# create remote url command
self.command_url = "{}:{}/run_command".format(self.host, self.port)
def __call__(self, *args):
''' Function that calls name(*args) on remote server'''
payload = utils.pickle_zip(args)
data = {'command': self.name, 'args': payload}
req = requests.put(self.command_url, data=data)
try:
result = utils.unpickle_zip(req.json())
except TypeError:
print(req.json())
return result
class Session(object):
'''
Represents a session
'''
def __init__(self, host='http://localhost', port=5000):
''' Returns instance of session
arguments
---------
host : IP address of the host to connnect to. Defaults to
'http://localhost'
port : Port number of the host. Defaults to 5000
'''
self.host = host
self.port = port
self.register_functions()
def register_functions(self):
''' Register all seismo functions as methods on self'''
# must register functions so we can call e.g.
# Session = session()
# f, a = Session.deeming(t, m)
funcs = ['deeming', 'fast_deeming', 'signal', 'sinewave']
for func in funcs:
remote_func = RemoteFunction(func, self.host, self.port)
# set docstring
seismo_func = getattr(seismo, func)
remote_func.__doc__ = seismo_func.__doc__
self.__setattr__(func, remote_func)
if __name__ == "__main__":
session = Session() | seismo/session.py | import requests
import json
import seismo
import numpy as np
from . import utils
class RemoteFunction(object):
'''
This class represents a remote function that can be called on a
seismo-server
'''
def __init__(self, name, host='http://localhost', port=5000):
'''
Initialise this with the name of the remote function. This is meant
to be one of the functions as part of seismo
'''
self.name = name
self.host = host
self.port = port
# create remote url command
self.command_url = "{}:{}/run_command".format(self.host, self.port)
def __call__(self, *args):
''' Function that calls name(*args) on remote server'''
payload = utils.pickle_zip(args)
data = {'command': self.name, 'args': payload}
req = requests.put(self.command_url, data=data)
try:
result = utils.unpickle_zip(req.json())
except TypeError:
print(req.json())
return result
class Session(object):
'''
Represents a session
'''
def __init__(self, host='http://localhost', port=5000):
''' Returns instance of session
arguments
---------
host : IP address of the host to connnect to. Defaults to
'http://localhost'
port : Port number of the host. Defaults to 5000
'''
self.host = host
self.port = port
self.register_functions()
def register_functions(self):
''' Register all seismo functions as methods on self'''
# must register functions so we can call e.g.
# Session = session()
# f, a = Session.deeming(t, m)
funcs = ['deeming', 'fast_deeming', 'signal', 'sinewave']
for func in funcs:
remote_func = RemoteFunction(func, self.host, self.port)
# set docstring
seismo_func = getattr(seismo, func)
remote_func.__doc__ = seismo_func.__doc__
self.__setattr__(func, remote_func)
if __name__ == "__main__":
session = Session() | 0.497803 | 0.182535 |
from copy import copy
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import brewer2mpl as b2mpl
from tqdm import tqdm
import seaborn.apionly as sns
from .FS_colorLUT import get_lut
from seaborn.utils import set_hls_values
def electrode_grid(gridx=16, gridy=16, elects_to_plot=None, anatomy=None,
xlims=(-1., 1.), ylims=(-.5, 2.), anat_colors=None,
xlabel_elect=None, ylabel_elect=256, anat_legend=True,
elect_num_pos='ul', clinical_num_pos=None,
grid_orientation='lr', xlabel='time (s)', ylabel='HG',
channel_order=None, fig=None, anat_legend_kwargs=None,
clinical_number_kwargs=None, elec_number_kwargs=None,
spineless=True, lighten=.93):
"""
Create electrode grid for plotting.
Parameters
----------
gridx, gridy: int
How many electrodes are there in the x and y dimensions of the grid?
Default: 16
elects_to_plot: list
List of electrodes by number indexed from 0 or boolean array
anatomy: np.array
List of anatomy_ID for each electrode. Used to color background of each
axis.
xlims, ylims: tuple
axes are set using these xlims and ylims
anat_colors: None o| dict
region (str) -> r,g,b (as 0>x>1). Default is the freesurfer
colormap, but any of the rois colors can be replaced
here.
xlabel_elect, ylabel_elect: int
Which electrode gets the xlabel and ylabel
anat_legend: bool
whether to show the anatomy legend
elect_num_pos: str or None
where to put the electrode number. If None, no electrode number is
shown. Otherwise, use
'ul': upper left (Default)
'll': lower left
'ur': upper right
'lr': lower right
clinical_num_pos: str or None
Same as elect_num_pos. 1 in ever 4 electrodes is clinical.
Default = None
grid_orientation: str
Where is electrode #1? Follows elect_num_pos rules.
xlabel: str
Default: 'time (s)'
ylabel: str
Default: 'HG'
channel_order: list
Should be used if channels are in an arrangement that cannot be
captured by grid_orientation. Supercedes
grid_orientation.
fig: plt.Figure
Default: None
anat_legend_kwargs: None or dict
clinical_number_kwargs: None or dict
elec_number_kwargs: None or dict
Returns
-------
fig: plt.Figure
axs: list(plt.Axes)
elects_to_plot: np.array()
"""
nelect = gridx * gridy
if fig is None:
fig = plt.figure(figsize=(gridx, gridy))
clinical_electrodes = np.hstack([np.arange(1, 16, 2) + x for x in
np.arange(0, 256, 32)])
if elects_to_plot is None:
elects_to_plot = np.arange(nelect)
elects_to_plot = np.array(elects_to_plot)
if elects_to_plot.dtype == np.bool:
elects_to_plot = np.where(elects_to_plot)[0]
if xlabel_elect is None:
if elects_to_plot is None:
xlabel_elect = 241
else:
rows = np.arange(256, 0, -16)
for row in rows:
col = np.arange(row - 16, row)
elecs = [x for x in elects_to_plot if x in col]
if len(elecs):
xlabel_elect = min(elecs) + 1
ylabel_elect = max(elecs) + 1
break
# Define axes face color to illustrate anatomy
# initialize to light gray
anat_color_array = np.array([[0.9, 0.9, 0.9]] * nelect)
if anat_colors is not None:
if anatomy is None:
raise Warning('anat colors set without anatomy specified.')
# set up anatomy colors
input_anat_colors = copy(anat_colors)
anat_colors = get_lut() # use freesurfer defaults
if input_anat_colors:
anat_colors.update(**input_anat_colors)
anatomy = anatomy[elects_to_plot]
regions, region_indices = np.unique(anatomy, return_inverse=True)
anat_legend_h = []
for i, region in enumerate(regions):
# mpl takes colors as (0≤x≤1)
color = np.array(anat_colors['ctx-rh-' + region]) / 255.
anat_color_array[region_indices == i, :] = color
light_color = set_hls_values(color, l=lighten)
anat_legend_h.append(mpl.patches.Patch(color=light_color,
label=region))
# create smart anat legend
true_anat_legend_kwargs = {'loc': 'upper left'}
if len(regions) > 4:
true_anat_legend_kwargs.update(ncol=2)
if anat_legend_kwargs:
true_anat_legend_kwargs.update(**anat_legend_kwargs)
if anat_legend:
fig.legend(handles=anat_legend_h, labels=regions,
**true_anat_legend_kwargs)
if channel_order is None:
# Rotate grid by indexing
elecs_grid = np.array(range(1, nelect + 1)).reshape(gridx, gridy)
rotation_num = ('straight', 'll', 'lr', 'ur').index(grid_orientation)
channel_order = np.rot90(elecs_grid.transpose(),
rotation_num).reshape(nelect)
# set electrode number properties
true_elec_number_kwargs = {'fontsize': 10}
if elec_number_kwargs:
true_elec_number_kwargs.update(**elec_number_kwargs)
true_clinical_number_kwargs = {'fontsize': 10, 'color': 'r'}
if clinical_number_kwargs:
true_clinical_number_kwargs.update(**clinical_number_kwargs)
# Add subplot for each electrode
a = [] # axes list
for ielect, (elect_number, this_anat_color) in \
tqdm(enumerate(zip(elects_to_plot, anat_color_array)),
total=len(elects_to_plot), desc='Drawing electrode grid'):
ax = fig.add_subplot(gridy, gridx, channel_order[elect_number])
ax.set_xlim(xlims)
ax.set_ylim(ylims)
ax.set_facecolor(set_hls_values(this_anat_color, l=lighten)) # lighten color
for spine in ax.spines.values():
if spineless:
spine.set_visible(False)
else:
spine.set_color(this_anat_color)
a.append(ax)
# Add electrode numbers
if elect_num_pos:
corner_text(str(elect_number + 1), elect_num_pos, ax,
**true_elec_number_kwargs)
if clinical_num_pos:
if (elect_number + 1) in clinical_electrodes:
clinical_number = np.where(
clinical_electrodes == (elect_number + 1))[0] + 1
corner_text(str(clinical_number), clinical_num_pos, ax,
**true_clinical_number_kwargs)
# Add axes labels only on corner electrodes
ax.set_xticks((xlims[0], 0, xlims[1]))
# set axes labels
if elect_number == xlabel_elect - 1:
ax.set_xlabel(xlabel)
else:
ax.set_xticklabels([])
if elect_number == ylabel_elect - 1:
ax.set_ylabel(ylabel)
else:
ax.set_yticklabels([])
fig.subplots_adjust(left=.05, right=.99, bottom=.1, top=.9,
hspace=0.1, wspace=0.1)
return fig, a, elects_to_plot
def show_erps(Ds, align_window, labels=None, show_sem=True, co_data=None,
**kwargs):
"""
Use plot ERPs on electrode_grid
Parameters
----------
Ds: list
list of D tensors (electrodes x time x trials)
align_window: tuple
time before and after stim in seconds
labels: tuple
Optional. labels for data legend
show_sem: bool
co_data: list
List of RGB (0<x<1) values for the data colors. Default: cbrewer Set1
kwargs: see electrode_grid
Returns
-------
fig: plt.Figure
axs: list(plt.Axes)
"""
if co_data is None:
co_data = b2mpl.get_map('Set1', 'Qualitative', 4).mpl_colors[1:]
fig, axs, elects_to_plot = electrode_grid(xlims=align_window, **kwargs)
h_lines = []
for D, color in zip(Ds, co_data):
D = D[np.array(elects_to_plot).astype(int)]
mean_erp = np.ma.mean(D, axis=2)
tt = np.linspace(align_window[0], align_window[1], mean_erp.shape[1])
for ax, data in tqdm(zip(axs, mean_erp), desc='Drawing data'):
h_line, = ax.plot(tt, data, color=color, linewidth=1)
h_lines.append(h_line)
if show_sem:
sem_erp = np.ma.std(D, axis=2) / np.sqrt(D.shape[2])
for ax, data, err in tqdm(zip(axs, mean_erp, sem_erp),
desc='Drawing sem'):
ax.fill_between(tt, data - err, data + err,
alpha=.4, facecolor=color, edgecolor=color)
for ax in axs:
yl = ax.get_ylim()
ax.set_yticks((yl[0], 0, yl[1]))
ax.grid(True)
if labels is not None:
fig.legend(h_lines, labels, loc='upper right', ncol=2)
return fig, axs
def get_channel_order(subject):
if subject == 'EC141':
co1 = np.rot90((np.arange(128) + 129).reshape(8, 16).T, 3).ravel()
co2 = np.rot90((np.arange(128) + 1).reshape(8, 16).T, 3).ravel()
channel_order = np.concatenate((co1, co2))
else:
channel_order = None
return channel_order
def compute_ERP(Ds):
data_list = []
for iD, D in enumerate(Ds):
this_means = np.mean(D, axis=2)
this_stes = np.std(D, axis=2) / np.sqrt(D.shape[2])
D2 = np.concatenate((np.expand_dims(this_means, 1),
np.expand_dims(this_stes, 1)), 1)
data_list.append(D2)
data_list = np.array(data_list)
data_list = np.swapaxes(data_list, 0, 1)
data_list = np.swapaxes(data_list, 1, 3)
data_list = np.swapaxes(data_list, 2, 3)
return data_list
def plotSingleERP(tt, data, labels=None, alpha=.5,
co=b2mpl.get_map('Set1', 'Qualitative', 8).mpl_colors,
ax=None):
# expects data of size ntime x ncases x 1 (for just mean) or 2 (for mean and standard error)
data = np.swapaxes(data, 0, 2)
data = np.swapaxes(data, 0, 1)
if ax is None:
ax = plt.gca()
if not labels:
labels = [' '] * len(data)
for (di, label, c) in zip(data, labels, co):
if di.shape[0] <= 2:
ax.plot(tt, di[0], color=c, label=label)
if len(di) == 2:
ax.fill_between(tt, di[0] - di[1], di[0] + di[1], color=c, alpha=alpha)
else:
ax.plot(tt, di, color=c, label=label)
ylim = ax.get_ylim()
ax.plot([0, 0], [-9999999, 999999999], color='black', alpha=.4)
# plt.gca().set_yscale("log", nonposx='clip')
ax.set_ylim(ylim)
ax.set_xlim(np.min(tt), np.max(tt))
sns.despine(ax=ax)
return plt.gca()
def corner_text(text, spec, ax, **kwargs):
"""
Puts `text` in the corner of `ax` specified by `spec`. additional arguments
are passed to plt.text.
Parameters
----------
text: str
string to placed
spec: str
specifies which corner. e.g. 'ul' = upper left, 'lr' = lower right
ax: plt.axes
kwargs: optional arguments get passed to plt.text.
Returns
-------
h: plt.text
"""
if type(spec) is not str or spec[0] not in 'ul' or spec[1] not in 'lr':
raise ValueError('spec must be string: [u|l][l|r]')
x = 0.
y = 1.
va = 'top'
ha = 'left'
if spec[0] == 'l':
y = 0.0
va = 'bottom'
if spec[1] == 'r':
x = 1.0
ha = 'right'
true_kwargs = {'va': va, 'ha': ha}
true_kwargs.update(**kwargs)
h = plt.text(x, y, str(text), transform=ax.transAxes, **true_kwargs)
return h | electrode_grid/electrode_grid.py | from copy import copy
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import brewer2mpl as b2mpl
from tqdm import tqdm
import seaborn.apionly as sns
from .FS_colorLUT import get_lut
from seaborn.utils import set_hls_values
def electrode_grid(gridx=16, gridy=16, elects_to_plot=None, anatomy=None,
xlims=(-1., 1.), ylims=(-.5, 2.), anat_colors=None,
xlabel_elect=None, ylabel_elect=256, anat_legend=True,
elect_num_pos='ul', clinical_num_pos=None,
grid_orientation='lr', xlabel='time (s)', ylabel='HG',
channel_order=None, fig=None, anat_legend_kwargs=None,
clinical_number_kwargs=None, elec_number_kwargs=None,
spineless=True, lighten=.93):
"""
Create electrode grid for plotting.
Parameters
----------
gridx, gridy: int
How many electrodes are there in the x and y dimensions of the grid?
Default: 16
elects_to_plot: list
List of electrodes by number indexed from 0 or boolean array
anatomy: np.array
List of anatomy_ID for each electrode. Used to color background of each
axis.
xlims, ylims: tuple
axes are set using these xlims and ylims
anat_colors: None o| dict
region (str) -> r,g,b (as 0>x>1). Default is the freesurfer
colormap, but any of the rois colors can be replaced
here.
xlabel_elect, ylabel_elect: int
Which electrode gets the xlabel and ylabel
anat_legend: bool
whether to show the anatomy legend
elect_num_pos: str or None
where to put the electrode number. If None, no electrode number is
shown. Otherwise, use
'ul': upper left (Default)
'll': lower left
'ur': upper right
'lr': lower right
clinical_num_pos: str or None
Same as elect_num_pos. 1 in ever 4 electrodes is clinical.
Default = None
grid_orientation: str
Where is electrode #1? Follows elect_num_pos rules.
xlabel: str
Default: 'time (s)'
ylabel: str
Default: 'HG'
channel_order: list
Should be used if channels are in an arrangement that cannot be
captured by grid_orientation. Supercedes
grid_orientation.
fig: plt.Figure
Default: None
anat_legend_kwargs: None or dict
clinical_number_kwargs: None or dict
elec_number_kwargs: None or dict
Returns
-------
fig: plt.Figure
axs: list(plt.Axes)
elects_to_plot: np.array()
"""
nelect = gridx * gridy
if fig is None:
fig = plt.figure(figsize=(gridx, gridy))
clinical_electrodes = np.hstack([np.arange(1, 16, 2) + x for x in
np.arange(0, 256, 32)])
if elects_to_plot is None:
elects_to_plot = np.arange(nelect)
elects_to_plot = np.array(elects_to_plot)
if elects_to_plot.dtype == np.bool:
elects_to_plot = np.where(elects_to_plot)[0]
if xlabel_elect is None:
if elects_to_plot is None:
xlabel_elect = 241
else:
rows = np.arange(256, 0, -16)
for row in rows:
col = np.arange(row - 16, row)
elecs = [x for x in elects_to_plot if x in col]
if len(elecs):
xlabel_elect = min(elecs) + 1
ylabel_elect = max(elecs) + 1
break
# Define axes face color to illustrate anatomy
# initialize to light gray
anat_color_array = np.array([[0.9, 0.9, 0.9]] * nelect)
if anat_colors is not None:
if anatomy is None:
raise Warning('anat colors set without anatomy specified.')
# set up anatomy colors
input_anat_colors = copy(anat_colors)
anat_colors = get_lut() # use freesurfer defaults
if input_anat_colors:
anat_colors.update(**input_anat_colors)
anatomy = anatomy[elects_to_plot]
regions, region_indices = np.unique(anatomy, return_inverse=True)
anat_legend_h = []
for i, region in enumerate(regions):
# mpl takes colors as (0≤x≤1)
color = np.array(anat_colors['ctx-rh-' + region]) / 255.
anat_color_array[region_indices == i, :] = color
light_color = set_hls_values(color, l=lighten)
anat_legend_h.append(mpl.patches.Patch(color=light_color,
label=region))
# create smart anat legend
true_anat_legend_kwargs = {'loc': 'upper left'}
if len(regions) > 4:
true_anat_legend_kwargs.update(ncol=2)
if anat_legend_kwargs:
true_anat_legend_kwargs.update(**anat_legend_kwargs)
if anat_legend:
fig.legend(handles=anat_legend_h, labels=regions,
**true_anat_legend_kwargs)
if channel_order is None:
# Rotate grid by indexing
elecs_grid = np.array(range(1, nelect + 1)).reshape(gridx, gridy)
rotation_num = ('straight', 'll', 'lr', 'ur').index(grid_orientation)
channel_order = np.rot90(elecs_grid.transpose(),
rotation_num).reshape(nelect)
# set electrode number properties
true_elec_number_kwargs = {'fontsize': 10}
if elec_number_kwargs:
true_elec_number_kwargs.update(**elec_number_kwargs)
true_clinical_number_kwargs = {'fontsize': 10, 'color': 'r'}
if clinical_number_kwargs:
true_clinical_number_kwargs.update(**clinical_number_kwargs)
# Add subplot for each electrode
a = [] # axes list
for ielect, (elect_number, this_anat_color) in \
tqdm(enumerate(zip(elects_to_plot, anat_color_array)),
total=len(elects_to_plot), desc='Drawing electrode grid'):
ax = fig.add_subplot(gridy, gridx, channel_order[elect_number])
ax.set_xlim(xlims)
ax.set_ylim(ylims)
ax.set_facecolor(set_hls_values(this_anat_color, l=lighten)) # lighten color
for spine in ax.spines.values():
if spineless:
spine.set_visible(False)
else:
spine.set_color(this_anat_color)
a.append(ax)
# Add electrode numbers
if elect_num_pos:
corner_text(str(elect_number + 1), elect_num_pos, ax,
**true_elec_number_kwargs)
if clinical_num_pos:
if (elect_number + 1) in clinical_electrodes:
clinical_number = np.where(
clinical_electrodes == (elect_number + 1))[0] + 1
corner_text(str(clinical_number), clinical_num_pos, ax,
**true_clinical_number_kwargs)
# Add axes labels only on corner electrodes
ax.set_xticks((xlims[0], 0, xlims[1]))
# set axes labels
if elect_number == xlabel_elect - 1:
ax.set_xlabel(xlabel)
else:
ax.set_xticklabels([])
if elect_number == ylabel_elect - 1:
ax.set_ylabel(ylabel)
else:
ax.set_yticklabels([])
fig.subplots_adjust(left=.05, right=.99, bottom=.1, top=.9,
hspace=0.1, wspace=0.1)
return fig, a, elects_to_plot
def show_erps(Ds, align_window, labels=None, show_sem=True, co_data=None,
**kwargs):
"""
Use plot ERPs on electrode_grid
Parameters
----------
Ds: list
list of D tensors (electrodes x time x trials)
align_window: tuple
time before and after stim in seconds
labels: tuple
Optional. labels for data legend
show_sem: bool
co_data: list
List of RGB (0<x<1) values for the data colors. Default: cbrewer Set1
kwargs: see electrode_grid
Returns
-------
fig: plt.Figure
axs: list(plt.Axes)
"""
if co_data is None:
co_data = b2mpl.get_map('Set1', 'Qualitative', 4).mpl_colors[1:]
fig, axs, elects_to_plot = electrode_grid(xlims=align_window, **kwargs)
h_lines = []
for D, color in zip(Ds, co_data):
D = D[np.array(elects_to_plot).astype(int)]
mean_erp = np.ma.mean(D, axis=2)
tt = np.linspace(align_window[0], align_window[1], mean_erp.shape[1])
for ax, data in tqdm(zip(axs, mean_erp), desc='Drawing data'):
h_line, = ax.plot(tt, data, color=color, linewidth=1)
h_lines.append(h_line)
if show_sem:
sem_erp = np.ma.std(D, axis=2) / np.sqrt(D.shape[2])
for ax, data, err in tqdm(zip(axs, mean_erp, sem_erp),
desc='Drawing sem'):
ax.fill_between(tt, data - err, data + err,
alpha=.4, facecolor=color, edgecolor=color)
for ax in axs:
yl = ax.get_ylim()
ax.set_yticks((yl[0], 0, yl[1]))
ax.grid(True)
if labels is not None:
fig.legend(h_lines, labels, loc='upper right', ncol=2)
return fig, axs
def get_channel_order(subject):
if subject == 'EC141':
co1 = np.rot90((np.arange(128) + 129).reshape(8, 16).T, 3).ravel()
co2 = np.rot90((np.arange(128) + 1).reshape(8, 16).T, 3).ravel()
channel_order = np.concatenate((co1, co2))
else:
channel_order = None
return channel_order
def compute_ERP(Ds):
data_list = []
for iD, D in enumerate(Ds):
this_means = np.mean(D, axis=2)
this_stes = np.std(D, axis=2) / np.sqrt(D.shape[2])
D2 = np.concatenate((np.expand_dims(this_means, 1),
np.expand_dims(this_stes, 1)), 1)
data_list.append(D2)
data_list = np.array(data_list)
data_list = np.swapaxes(data_list, 0, 1)
data_list = np.swapaxes(data_list, 1, 3)
data_list = np.swapaxes(data_list, 2, 3)
return data_list
def plotSingleERP(tt, data, labels=None, alpha=.5,
co=b2mpl.get_map('Set1', 'Qualitative', 8).mpl_colors,
ax=None):
# expects data of size ntime x ncases x 1 (for just mean) or 2 (for mean and standard error)
data = np.swapaxes(data, 0, 2)
data = np.swapaxes(data, 0, 1)
if ax is None:
ax = plt.gca()
if not labels:
labels = [' '] * len(data)
for (di, label, c) in zip(data, labels, co):
if di.shape[0] <= 2:
ax.plot(tt, di[0], color=c, label=label)
if len(di) == 2:
ax.fill_between(tt, di[0] - di[1], di[0] + di[1], color=c, alpha=alpha)
else:
ax.plot(tt, di, color=c, label=label)
ylim = ax.get_ylim()
ax.plot([0, 0], [-9999999, 999999999], color='black', alpha=.4)
# plt.gca().set_yscale("log", nonposx='clip')
ax.set_ylim(ylim)
ax.set_xlim(np.min(tt), np.max(tt))
sns.despine(ax=ax)
return plt.gca()
def corner_text(text, spec, ax, **kwargs):
"""
Puts `text` in the corner of `ax` specified by `spec`. additional arguments
are passed to plt.text.
Parameters
----------
text: str
string to placed
spec: str
specifies which corner. e.g. 'ul' = upper left, 'lr' = lower right
ax: plt.axes
kwargs: optional arguments get passed to plt.text.
Returns
-------
h: plt.text
"""
if type(spec) is not str or spec[0] not in 'ul' or spec[1] not in 'lr':
raise ValueError('spec must be string: [u|l][l|r]')
x = 0.
y = 1.
va = 'top'
ha = 'left'
if spec[0] == 'l':
y = 0.0
va = 'bottom'
if spec[1] == 'r':
x = 1.0
ha = 'right'
true_kwargs = {'va': va, 'ha': ha}
true_kwargs.update(**kwargs)
h = plt.text(x, y, str(text), transform=ax.transAxes, **true_kwargs)
return h | 0.750187 | 0.493409 |
import numpy as np
import tensorflow as tf
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import RandomForestClassifier, VotingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
__author__ = "<NAME>"
__version__ = "1.0"
__email__ = "<EMAIL>"
class EnsembleVotingModel:
"""
Class represents model for ensemble voting algorithm.
"""
def __init__(self, X, Y):
self._X = X
self._Y = Y
self._models = []
def with_SVM_model(self):
estimatior = SVC(kernel='rbf')
self._models.append(('svm', estimatior))
return self
def with_RandomForest_model(self):
estimatior = RandomForestClassifier(random_state=1)
self._models.append(('rf', estimatior))
return self
def with_LogisticRegression(self):
estimatior = LogisticRegression(random_state=1)
self._models.append(('lr', estimatior))
return self
def with_SVM_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(SVC(kernel='rbf', probability=True), n_estimators=n_estimators)
self._models.append(('svm_ada', estimatior))
return self
def with_RandomForest_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(RandomForestClassifier(random_state=1), n_estimators=n_estimators)
self._models.append(('rf_ada', estimatior))
return self
def with_LogisticRegression_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(LogisticRegression(random_state=1), n_estimators=n_estimators)
self._models.append(('lr_ada', estimatior))
return self
def train(self):
print('Building ensemble model')
self.voting_model = VotingClassifier(estimators=self._models, voting='hard')
print('Training ensemble model')
self.voting_model.fit(self._X, self._Y)
return self
def predict(self, X):
return self.voting_model.predict(X)
def score(self, X, Y):
return self.voting_model.score(X, Y)
class NeuralNetworkModel:
"""
Class represents model for multilayer perceptron.
"""
def __init__(self, X, Y, learning_rate=1e-4, num_steps=10000, batch_size=64, display_step=100, n_hidden_1=1024):
self._X = X
self._Y = Y
self._learning_rate = learning_rate
self._num_steps = num_steps
self._batch_size = batch_size
self._display_step = display_step
self._n_hidden_1 = n_hidden_1
self._num_input = X.shape[1]
self._num_classes = Y.shape[1]
def predict(self, X):
return self._session.run(self._prediction, feed_dict={self._X_p: X})
def score(self, X, Y):
return self._session.run(self._accuracy, feed_dict={self._X_p: X, self._Y_p: Y})
def _random_batch_data(self, data_x, data_y):
num_images = len(data_x)
idx = np.random.choice(num_images, size=self._batch_size, replace=False)
x_batch = data_x[idx]
y_batch = data_y[idx]
return x_batch, y_batch
def _build_graph(self):
self._X_p = tf.placeholder("float", [None, self._num_input])
self._Y_p = tf.placeholder("float", [None, self._num_classes])
# Construct model
logits = self._build_net_model(self._X_p)
# Define loss and optimizer
self._loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits, labels=self._Y_p))
optimizer = tf.train.AdamOptimizer(learning_rate=self._learning_rate)
self._train_op = optimizer.minimize(self._loss_op)
# Evaluate model (with test logits, for dropout to be disabled)
self._prediction = tf.argmax(logits, 1)
correct_pred = tf.equal(self._prediction, tf.argmax(self._Y_p, 1))
self._accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
def _build_net_model(self, x):
weights = {
'h1': tf.Variable(tf.random_normal([self._num_input, self._n_hidden_1])),
'out': tf.Variable(tf.random_normal([self._n_hidden_1, self._num_classes]))
}
biases = {
'b1': tf.Variable(tf.random_normal([self._n_hidden_1])),
'out': tf.Variable(tf.random_normal([self._num_classes]))
}
# Hidden fully connected layer with 256 neurons
layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
# Output fully connected layer with a neuron for each class
out_layer = tf.matmul(layer_1, weights['out']) + biases['out']
return out_layer
def train(self):
self._build_graph()
# Initialize the variables (i.e. assign their default value)
init = tf.global_variables_initializer()
self._session = tf.Session()
self._session.run(init)
for step in range(1, self._num_steps + 1):
batch_x, batch_y = self._random_batch_data(self._X, self._Y)
# Run optimization op (backprop)
self._session.run(self._train_op, feed_dict={self._X_p: batch_x, self._Y_p: batch_y})
if step % self._display_step == 0 or step == 1:
# Calculate batch loss and accuracy
loss, acc = self._session.run([self._loss_op, self._accuracy],
feed_dict={self._X_p: batch_x, self._Y_p: batch_y})
print("Step " + str(step) + ", Minibatch Loss= " + \
"{:.4f}".format(loss) + ", Training Accuracy= " + \
"{:.3f}".format(acc))
print("Optimization Finished!")
return self | classification_service.py | import numpy as np
import tensorflow as tf
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import RandomForestClassifier, VotingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
__author__ = "<NAME>"
__version__ = "1.0"
__email__ = "<EMAIL>"
class EnsembleVotingModel:
"""
Class represents model for ensemble voting algorithm.
"""
def __init__(self, X, Y):
self._X = X
self._Y = Y
self._models = []
def with_SVM_model(self):
estimatior = SVC(kernel='rbf')
self._models.append(('svm', estimatior))
return self
def with_RandomForest_model(self):
estimatior = RandomForestClassifier(random_state=1)
self._models.append(('rf', estimatior))
return self
def with_LogisticRegression(self):
estimatior = LogisticRegression(random_state=1)
self._models.append(('lr', estimatior))
return self
def with_SVM_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(SVC(kernel='rbf', probability=True), n_estimators=n_estimators)
self._models.append(('svm_ada', estimatior))
return self
def with_RandomForest_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(RandomForestClassifier(random_state=1), n_estimators=n_estimators)
self._models.append(('rf_ada', estimatior))
return self
def with_LogisticRegression_AdaBoost_model(self, n_estimators=2):
estimatior = AdaBoostClassifier(LogisticRegression(random_state=1), n_estimators=n_estimators)
self._models.append(('lr_ada', estimatior))
return self
def train(self):
print('Building ensemble model')
self.voting_model = VotingClassifier(estimators=self._models, voting='hard')
print('Training ensemble model')
self.voting_model.fit(self._X, self._Y)
return self
def predict(self, X):
return self.voting_model.predict(X)
def score(self, X, Y):
return self.voting_model.score(X, Y)
class NeuralNetworkModel:
"""
Class represents model for multilayer perceptron.
"""
def __init__(self, X, Y, learning_rate=1e-4, num_steps=10000, batch_size=64, display_step=100, n_hidden_1=1024):
self._X = X
self._Y = Y
self._learning_rate = learning_rate
self._num_steps = num_steps
self._batch_size = batch_size
self._display_step = display_step
self._n_hidden_1 = n_hidden_1
self._num_input = X.shape[1]
self._num_classes = Y.shape[1]
def predict(self, X):
return self._session.run(self._prediction, feed_dict={self._X_p: X})
def score(self, X, Y):
return self._session.run(self._accuracy, feed_dict={self._X_p: X, self._Y_p: Y})
def _random_batch_data(self, data_x, data_y):
num_images = len(data_x)
idx = np.random.choice(num_images, size=self._batch_size, replace=False)
x_batch = data_x[idx]
y_batch = data_y[idx]
return x_batch, y_batch
def _build_graph(self):
self._X_p = tf.placeholder("float", [None, self._num_input])
self._Y_p = tf.placeholder("float", [None, self._num_classes])
# Construct model
logits = self._build_net_model(self._X_p)
# Define loss and optimizer
self._loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits, labels=self._Y_p))
optimizer = tf.train.AdamOptimizer(learning_rate=self._learning_rate)
self._train_op = optimizer.minimize(self._loss_op)
# Evaluate model (with test logits, for dropout to be disabled)
self._prediction = tf.argmax(logits, 1)
correct_pred = tf.equal(self._prediction, tf.argmax(self._Y_p, 1))
self._accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
def _build_net_model(self, x):
weights = {
'h1': tf.Variable(tf.random_normal([self._num_input, self._n_hidden_1])),
'out': tf.Variable(tf.random_normal([self._n_hidden_1, self._num_classes]))
}
biases = {
'b1': tf.Variable(tf.random_normal([self._n_hidden_1])),
'out': tf.Variable(tf.random_normal([self._num_classes]))
}
# Hidden fully connected layer with 256 neurons
layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
# Output fully connected layer with a neuron for each class
out_layer = tf.matmul(layer_1, weights['out']) + biases['out']
return out_layer
def train(self):
self._build_graph()
# Initialize the variables (i.e. assign their default value)
init = tf.global_variables_initializer()
self._session = tf.Session()
self._session.run(init)
for step in range(1, self._num_steps + 1):
batch_x, batch_y = self._random_batch_data(self._X, self._Y)
# Run optimization op (backprop)
self._session.run(self._train_op, feed_dict={self._X_p: batch_x, self._Y_p: batch_y})
if step % self._display_step == 0 or step == 1:
# Calculate batch loss and accuracy
loss, acc = self._session.run([self._loss_op, self._accuracy],
feed_dict={self._X_p: batch_x, self._Y_p: batch_y})
print("Step " + str(step) + ", Minibatch Loss= " + \
"{:.4f}".format(loss) + ", Training Accuracy= " + \
"{:.3f}".format(acc))
print("Optimization Finished!")
return self | 0.806738 | 0.387401 |
import warnings
warnings.filterwarnings("ignore")
import os
os.environ["CUDA_VISIBLE_DEVICES"] = '0'
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow.keras import Sequential, layers, utils
from sklearn.model_selection import train_test_split
data = pd.read_csv("data/bike_data.csv", encoding="gbk")
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace("Women's Mountain Shorts", '未知名称'))
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace("(", ""))
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace(")", ""))
data['Model'] = data['Model'].astype(str).apply(lambda x: x + " ")
df = data.groupby(['OrderNumber'])['Model'].sum().reset_index()
df['Model'] = df['Model'].astype(str).apply(lambda x: x.strip())
df['count'] = df['Model'].astype(str).apply(lambda x: x.split(' ')).apply(len)
texts = df[df['count']>=2].Model.tolist()
all_texts = texts[0]
for i in texts[1:]:
all_texts += " " + i
all_texts = list(set(all_texts.split(' ')))
all_texts.append("<PAD>")
all_texts = set(all_texts)
text_to_id = {c: i for i, c in enumerate(all_texts)}
id_to_text = {i: c for i, c in enumerate(all_texts)}
df['Model'] = df['Model'].astype(str).apply(lambda x: "<PAD> <PAD> <PAD> " + x)
df['Model'] = df['Model'].astype(str).apply(lambda x: x.split(' '))
x = []
y = []
for values in df['Model'].tolist():
if len(values) == 5:
x.append(" ".join(values[:4]))
y.append(values[-1])
else:
for i in np.arange(0, len(values)-4, step=1):
x.append(" ".join(values[i: i+4]))
y.append("".join(values[i+4]))
texts = []
for text in x:
texts.append([text_to_id[i] for i in text.split(' ')])
label = [text_to_id[i] for i in y]
texts = np.array(texts)
label = np.array(label)
texts = texts / len(all_texts)
x = texts.reshape(texts.shape[0], 4, 1)
y = tf.keras.utils.to_categorical(label)
x_train, x_test, y_train, y_test = train_test_split(x, y,
test_size=0.2,
random_state=2021)
model = Sequential([
layers.LSTM(units=800, input_shape=(4, 1), return_sequences=True),
layers.Dropout(0.3),
layers.LSTM(units=800, return_sequences=True),
layers.Dropout(0.2),
layers.LSTM(units=800),
layers.Dropout(0.2),
layers.Dense(y.shape[1], activation='softmax')
])
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])
model.fit(x, y,
# validation_data=(x_test, y_test),
epochs=500,
batch_size=64) | recommender_system_lstm.py |
import warnings
warnings.filterwarnings("ignore")
import os
os.environ["CUDA_VISIBLE_DEVICES"] = '0'
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow.keras import Sequential, layers, utils
from sklearn.model_selection import train_test_split
data = pd.read_csv("data/bike_data.csv", encoding="gbk")
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace("Women's Mountain Shorts", '未知名称'))
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace("(", ""))
data['Model'] = data['Model'].astype(str).apply(lambda x: x.replace(")", ""))
data['Model'] = data['Model'].astype(str).apply(lambda x: x + " ")
df = data.groupby(['OrderNumber'])['Model'].sum().reset_index()
df['Model'] = df['Model'].astype(str).apply(lambda x: x.strip())
df['count'] = df['Model'].astype(str).apply(lambda x: x.split(' ')).apply(len)
texts = df[df['count']>=2].Model.tolist()
all_texts = texts[0]
for i in texts[1:]:
all_texts += " " + i
all_texts = list(set(all_texts.split(' ')))
all_texts.append("<PAD>")
all_texts = set(all_texts)
text_to_id = {c: i for i, c in enumerate(all_texts)}
id_to_text = {i: c for i, c in enumerate(all_texts)}
df['Model'] = df['Model'].astype(str).apply(lambda x: "<PAD> <PAD> <PAD> " + x)
df['Model'] = df['Model'].astype(str).apply(lambda x: x.split(' '))
x = []
y = []
for values in df['Model'].tolist():
if len(values) == 5:
x.append(" ".join(values[:4]))
y.append(values[-1])
else:
for i in np.arange(0, len(values)-4, step=1):
x.append(" ".join(values[i: i+4]))
y.append("".join(values[i+4]))
texts = []
for text in x:
texts.append([text_to_id[i] for i in text.split(' ')])
label = [text_to_id[i] for i in y]
texts = np.array(texts)
label = np.array(label)
texts = texts / len(all_texts)
x = texts.reshape(texts.shape[0], 4, 1)
y = tf.keras.utils.to_categorical(label)
x_train, x_test, y_train, y_test = train_test_split(x, y,
test_size=0.2,
random_state=2021)
model = Sequential([
layers.LSTM(units=800, input_shape=(4, 1), return_sequences=True),
layers.Dropout(0.3),
layers.LSTM(units=800, return_sequences=True),
layers.Dropout(0.2),
layers.LSTM(units=800),
layers.Dropout(0.2),
layers.Dense(y.shape[1], activation='softmax')
])
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])
model.fit(x, y,
# validation_data=(x_test, y_test),
epochs=500,
batch_size=64) | 0.418935 | 0.330714 |
import re
import json
import hashlib
import yaml
import numpy as np
import pymatgen as pmg
from ..schema import PotentialSchema
from ..parameter import FloatParameter
from ..utils import get_naive_attr_path
class Potential:
def __init__(self, schema):
schema_load, errors = PotentialSchema().load(schema)
self.schema = schema_load
self._apply_constraints()
self._collect_parameters()
def _apply_constraints(self):
for constraint, value in self.schema['spec'].get('constraint', {}).items():
if constraint == 'charge_balance':
composition = pmg.core.Composition(value)
charges = self.schema['spec'].get('charge', {})
if not {e.symbol for e in composition.keys()} <= charges.keys():
raise ValueError('charge ballance constrains requires all elements to be defined in charge')
for charge_element in sorted(charges):
parameter = charges[charge_element]
if isinstance(parameter, FloatParameter) and not parameter.fixed:
break
else:
if abs(sum(float(charges[element.symbol]) * amount for element, amount in composition.items())) > 1e-8:
raise ValueError('no parameters to apply charge constraint and charge does ballance')
continue
parameter.computed = lambda: -sum(float(charges[element.symbol]) * amount for element, amount in composition.items() if element.symbol != charge_element)
elif constraint == 'equations':
for equation in value:
left = get_naive_attr_path(self.schema['spec'], equation['left'])
right_terms = []
for right_term in equation['right']:
v = get_naive_attr_path(self.schema['spec'], right_term[0])
right_terms.append([v, right_term[1]])
left.computed = lambda: sum(float(v[0]) * v[1] for v in right_terms)
else:
raise ValueError('contraint %s not implemented' % constraint)
def _collect_parameters(self):
self._parameters = []
def _walk(value): # Ordered traversal of dictionary
if isinstance(value, dict):
for key in sorted(value.keys()):
_walk(value[key])
elif isinstance(value, (tuple, list)):
for item in value:
_walk(item)
elif isinstance(value, FloatParameter):
self._parameters.append(value)
_walk(self.schema)
self._optimization_parameters = []
self._optimization_parameter_indicies = []
for i, p in enumerate(self._parameters):
if not p.fixed:
self._optimization_parameters.append(p)
self._optimization_parameter_indicies.append(i)
@classmethod
def from_file(cls, filename, format=None):
if format not in {'json', 'yaml'}:
if filename.endswith('json'):
format = 'json'
elif filename.endswith('yaml') or filename.endswith('yml'):
format = 'yaml'
else:
raise ValueError('unrecognized filetype from filename %s' % filename)
if format == 'json':
with open(filename) as f:
return cls(json.load(f))
elif format in {'yaml', 'yml'}:
with open(filename) as f:
return cls(yaml.safe_load(f))
@classmethod
def from_run_evaluation(cls, schema, initial_parameters, optimization_indicies, optimization_parameters, optimization_bounds):
parameters = [value for value in initial_parameters]
for i, value, bounds in zip(optimization_indicies, optimization_parameters, optimization_bounds):
parameters[i] = {'initial': value, 'bounds': bounds}
index = 0
def _walk(value): # Ordered traversal of dictionary
nonlocal index
if isinstance(value, dict):
for key in sorted(value.keys()):
if isinstance(value[key], str) and value[key] == 'FloatParameter':
value[key] = parameters[index]
index += 1
else:
_walk(value[key])
elif isinstance(value, (list)):
for i, item in enumerate(value):
if isinstance(item, str) and item == 'FloatParameter':
value[i] = parameters[index]
index += 1
else:
_walk(item)
_walk(schema)
# Adding constraints
for constraint, value in schema['spec'].get('constraint', {}).items():
if constraint == 'charge_balance':
composition = pmg.core.Composition(value)
charges = schema['spec'].get('charge', {})
if not {e.symbol for e in composition.keys()} <= charges.keys():
raise ValueError('charge ballance constrains requires all elements to be defined in charge')
for charge_element in sorted(charges):
parameter = charges[charge_element]
if isinstance(parameter, (float, int)):
charge = 0
bounds = [0, 0]
for element, amount in composition.items():
if element.symbol != charge_element:
if isinstance(charges[element.symbol], dict):
charge -= charges[element.symbol]['initial'] * amount
bounds[0] -= charges[element.symbol].get('bounds', [0.0, 0.0])[1] * amount
bounds[1] -= charges[element.symbol].get('bounds', [0.0, 0.0])[0] * amount
else:
charge -= float(charges[element.symbol])
charges[charge_element] = {'initial': charge, 'bounds': bounds}
break
else:
raise ValueError('unable to apply charge constraint no fixed values')
return cls(schema)
@property
def md5hash(self):
potential_str = json.dumps(self.as_dict(with_parameters=False), sort_keys=True)
return hashlib.md5(potential_str.encode('utf-8')).hexdigest()
def as_dict(self, with_parameters=True):
if with_parameters:
schema_dump, errors = PotentialSchema().dump(self.schema)
return schema_dump
else:
class CustomEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, FloatParameter):
return "FloatParameter"
else:
return super().default(obj)
return json.loads(json.dumps(self.schema, cls=CustomEncoder))
def write_file(self, filename):
with open(filename, 'w') as f:
f.write(str(self))
def __copy__(self):
return type(self)(self.as_dict())
def copy(self):
return self.__copy__()
def __hash__(self):
return hash(json.dumps(self.as_dict(with_parameters=False), sort_keys=True))
def __eq__(self, other):
return hash(self) == hash(other) and np.all(np.isclose(self.parameters, other.parameters, rtol=1e-16))
@property
def parameters(self):
""" Returns parameters for potentials as a list of float values
"""
return np.array([float(parameter) for parameter in self._parameters])
@property
def optimization_parameters(self):
return np.array([float(parameter) for parameter in self._optimization_parameters])
@optimization_parameters.setter
def optimization_parameters(self, parameters):
""" Update potential with given parameters
"""
if len(parameters) != len(self._optimization_parameters):
raise ValueError('updating parameters does not match length of potential parameters')
for parameter, update_parameter in zip(self._optimization_parameters, parameters):
parameter.current = float(update_parameter)
@property
def optimization_bounds(self):
return np.array([parameter.bounds for parameter in self._optimization_parameters])
@property
def optimization_parameter_indicies(self):
return np.array(self._optimization_parameter_indicies)
@property
def elements(self):
""" Return a set of the elements that potential applies to
"""
elements = set()
for element in self.schema['spec'].get('charge', {}):
elements.add(element)
for pair_potential in self.schema['spec'].get('pair', []):
parameters = pair_potential.get('parameters', [])
for parameter in parameters:
for element in parameter.get('elements', []):
elements.add(element)
return elements
def __repr__(self):
return self.__str__()
def __str__(self):
return json.dumps(self.as_dict(), sort_keys=True, indent=4) | dftfit/potential/representation.py | import re
import json
import hashlib
import yaml
import numpy as np
import pymatgen as pmg
from ..schema import PotentialSchema
from ..parameter import FloatParameter
from ..utils import get_naive_attr_path
class Potential:
def __init__(self, schema):
schema_load, errors = PotentialSchema().load(schema)
self.schema = schema_load
self._apply_constraints()
self._collect_parameters()
def _apply_constraints(self):
for constraint, value in self.schema['spec'].get('constraint', {}).items():
if constraint == 'charge_balance':
composition = pmg.core.Composition(value)
charges = self.schema['spec'].get('charge', {})
if not {e.symbol for e in composition.keys()} <= charges.keys():
raise ValueError('charge ballance constrains requires all elements to be defined in charge')
for charge_element in sorted(charges):
parameter = charges[charge_element]
if isinstance(parameter, FloatParameter) and not parameter.fixed:
break
else:
if abs(sum(float(charges[element.symbol]) * amount for element, amount in composition.items())) > 1e-8:
raise ValueError('no parameters to apply charge constraint and charge does ballance')
continue
parameter.computed = lambda: -sum(float(charges[element.symbol]) * amount for element, amount in composition.items() if element.symbol != charge_element)
elif constraint == 'equations':
for equation in value:
left = get_naive_attr_path(self.schema['spec'], equation['left'])
right_terms = []
for right_term in equation['right']:
v = get_naive_attr_path(self.schema['spec'], right_term[0])
right_terms.append([v, right_term[1]])
left.computed = lambda: sum(float(v[0]) * v[1] for v in right_terms)
else:
raise ValueError('contraint %s not implemented' % constraint)
def _collect_parameters(self):
self._parameters = []
def _walk(value): # Ordered traversal of dictionary
if isinstance(value, dict):
for key in sorted(value.keys()):
_walk(value[key])
elif isinstance(value, (tuple, list)):
for item in value:
_walk(item)
elif isinstance(value, FloatParameter):
self._parameters.append(value)
_walk(self.schema)
self._optimization_parameters = []
self._optimization_parameter_indicies = []
for i, p in enumerate(self._parameters):
if not p.fixed:
self._optimization_parameters.append(p)
self._optimization_parameter_indicies.append(i)
@classmethod
def from_file(cls, filename, format=None):
if format not in {'json', 'yaml'}:
if filename.endswith('json'):
format = 'json'
elif filename.endswith('yaml') or filename.endswith('yml'):
format = 'yaml'
else:
raise ValueError('unrecognized filetype from filename %s' % filename)
if format == 'json':
with open(filename) as f:
return cls(json.load(f))
elif format in {'yaml', 'yml'}:
with open(filename) as f:
return cls(yaml.safe_load(f))
@classmethod
def from_run_evaluation(cls, schema, initial_parameters, optimization_indicies, optimization_parameters, optimization_bounds):
parameters = [value for value in initial_parameters]
for i, value, bounds in zip(optimization_indicies, optimization_parameters, optimization_bounds):
parameters[i] = {'initial': value, 'bounds': bounds}
index = 0
def _walk(value): # Ordered traversal of dictionary
nonlocal index
if isinstance(value, dict):
for key in sorted(value.keys()):
if isinstance(value[key], str) and value[key] == 'FloatParameter':
value[key] = parameters[index]
index += 1
else:
_walk(value[key])
elif isinstance(value, (list)):
for i, item in enumerate(value):
if isinstance(item, str) and item == 'FloatParameter':
value[i] = parameters[index]
index += 1
else:
_walk(item)
_walk(schema)
# Adding constraints
for constraint, value in schema['spec'].get('constraint', {}).items():
if constraint == 'charge_balance':
composition = pmg.core.Composition(value)
charges = schema['spec'].get('charge', {})
if not {e.symbol for e in composition.keys()} <= charges.keys():
raise ValueError('charge ballance constrains requires all elements to be defined in charge')
for charge_element in sorted(charges):
parameter = charges[charge_element]
if isinstance(parameter, (float, int)):
charge = 0
bounds = [0, 0]
for element, amount in composition.items():
if element.symbol != charge_element:
if isinstance(charges[element.symbol], dict):
charge -= charges[element.symbol]['initial'] * amount
bounds[0] -= charges[element.symbol].get('bounds', [0.0, 0.0])[1] * amount
bounds[1] -= charges[element.symbol].get('bounds', [0.0, 0.0])[0] * amount
else:
charge -= float(charges[element.symbol])
charges[charge_element] = {'initial': charge, 'bounds': bounds}
break
else:
raise ValueError('unable to apply charge constraint no fixed values')
return cls(schema)
@property
def md5hash(self):
potential_str = json.dumps(self.as_dict(with_parameters=False), sort_keys=True)
return hashlib.md5(potential_str.encode('utf-8')).hexdigest()
def as_dict(self, with_parameters=True):
if with_parameters:
schema_dump, errors = PotentialSchema().dump(self.schema)
return schema_dump
else:
class CustomEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, FloatParameter):
return "FloatParameter"
else:
return super().default(obj)
return json.loads(json.dumps(self.schema, cls=CustomEncoder))
def write_file(self, filename):
with open(filename, 'w') as f:
f.write(str(self))
def __copy__(self):
return type(self)(self.as_dict())
def copy(self):
return self.__copy__()
def __hash__(self):
return hash(json.dumps(self.as_dict(with_parameters=False), sort_keys=True))
def __eq__(self, other):
return hash(self) == hash(other) and np.all(np.isclose(self.parameters, other.parameters, rtol=1e-16))
@property
def parameters(self):
""" Returns parameters for potentials as a list of float values
"""
return np.array([float(parameter) for parameter in self._parameters])
@property
def optimization_parameters(self):
return np.array([float(parameter) for parameter in self._optimization_parameters])
@optimization_parameters.setter
def optimization_parameters(self, parameters):
""" Update potential with given parameters
"""
if len(parameters) != len(self._optimization_parameters):
raise ValueError('updating parameters does not match length of potential parameters')
for parameter, update_parameter in zip(self._optimization_parameters, parameters):
parameter.current = float(update_parameter)
@property
def optimization_bounds(self):
return np.array([parameter.bounds for parameter in self._optimization_parameters])
@property
def optimization_parameter_indicies(self):
return np.array(self._optimization_parameter_indicies)
@property
def elements(self):
""" Return a set of the elements that potential applies to
"""
elements = set()
for element in self.schema['spec'].get('charge', {}):
elements.add(element)
for pair_potential in self.schema['spec'].get('pair', []):
parameters = pair_potential.get('parameters', [])
for parameter in parameters:
for element in parameter.get('elements', []):
elements.add(element)
return elements
def __repr__(self):
return self.__str__()
def __str__(self):
return json.dumps(self.as_dict(), sort_keys=True, indent=4) | 0.633977 | 0.286662 |
import datetime
diagram = modeler.script.diagram()
stream = modeler.script.stream()
p_first = stream.getParameterValue("P_FIRST")
p_last = stream.getParameterValue("P_LAST")
# Data Directory
direc = "C:/.."
# Periods List
def periods_between(p_first,p_last):
periods_list = []
date = datetime.date(int('20' + str(p_first)[0:2]), int(str(p_first)[2:4]), 1)
iteration = 0
while True:
if iteration == 0:
dxdate = date
else:
dxdate = dxdate - datetime.timedelta(days=1)
dxdate = dxdate.replace(day=1)
if len(str(dxdate.month)) == 1:
dxperiod_month = '0' + str(dxdate.month)
else:
dxperiod_month = str(dxdate.month)
periods_list.insert(iteration, str(dxdate.year)[2:4] + dxperiod_month)
iteration = iteration + 1
if (str(dxdate.year)[2:4] + dxperiod_month) == str(p_last):
break
return periods_list
periods_list = periods_between(p_first,p_last)
# Renaming on Filter Node
ID_FIELD = "IDFIELD"
renamers = [
'_3M',
'_6M',
'_9M',
'_12M',
]
for ren in renamers:
node = diagram.findByType("filternode",ren)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
node.setKeyedPropertyValue("new_name", field, field + ren)
# Rename Aggregations
for period in ('_3M','_6M','_9M','_12M'):
# DX
node = diagram.findByType("filternode",'_DX' + period)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
field_cut = field.replace('_Sum','')
node.setKeyedPropertyValue("new_name", field, field_cut + '_DX' + period)
# AVGDX
node = diagram.findByType("filternode",'_AVGDX' + period)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
field_cut = field.replace('_Mean_Sum','')
node.setKeyedPropertyValue("new_name", field, field_cut + '_AVGDX' + period)
# Historia Rename & Run
periods = 12
iteration = 0
for period in periods_list:
iteration = iteration + 1
historia_list = []
date = datetime.date(int('20'+str(period)[0:2]),int(str(period)[2:4]),1)
h_iter = 0
while True:
if h_iter == 0:
dxdate = date
else:
dxdate = dxdate - datetime.timedelta(days=1)
dxdate = dxdate.replace(day=1)
dxperiod_year = str(dxdate.year)[2:4]
if len(str(dxdate.month)) == 1:
dxperiod_month = '0' + str(dxdate.month)
else:
dxperiod_month = str(dxdate.month)
historia_list.insert(h_iter, str(dxdate.year)[2:4] + dxperiod_month)
h_iter = h_iter + 1
if h_iter == periods:
break
# Rename In/Out
diagram.findByType("statisticsexport","out").setPropertyValue("full_filename", direc + period + "_12M.sav")
for p in range(periods):
diagram.findByType("statisticsimport",str(p + 1)).setPropertyValue("full_filename", direc + historia_list[p] + ".sav")
# Run Stream
diagram.findByType("dataaudit","QUALI").run(None)
diagram.findByType("statisticsexport","out").run(None) | exec_date_aggs.py | import datetime
diagram = modeler.script.diagram()
stream = modeler.script.stream()
p_first = stream.getParameterValue("P_FIRST")
p_last = stream.getParameterValue("P_LAST")
# Data Directory
direc = "C:/.."
# Periods List
def periods_between(p_first,p_last):
periods_list = []
date = datetime.date(int('20' + str(p_first)[0:2]), int(str(p_first)[2:4]), 1)
iteration = 0
while True:
if iteration == 0:
dxdate = date
else:
dxdate = dxdate - datetime.timedelta(days=1)
dxdate = dxdate.replace(day=1)
if len(str(dxdate.month)) == 1:
dxperiod_month = '0' + str(dxdate.month)
else:
dxperiod_month = str(dxdate.month)
periods_list.insert(iteration, str(dxdate.year)[2:4] + dxperiod_month)
iteration = iteration + 1
if (str(dxdate.year)[2:4] + dxperiod_month) == str(p_last):
break
return periods_list
periods_list = periods_between(p_first,p_last)
# Renaming on Filter Node
ID_FIELD = "IDFIELD"
renamers = [
'_3M',
'_6M',
'_9M',
'_12M',
]
for ren in renamers:
node = diagram.findByType("filternode",ren)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
node.setKeyedPropertyValue("new_name", field, field + ren)
# Rename Aggregations
for period in ('_3M','_6M','_9M','_12M'):
# DX
node = diagram.findByType("filternode",'_DX' + period)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
field_cut = field.replace('_Sum','')
node.setKeyedPropertyValue("new_name", field, field_cut + '_DX' + period)
# AVGDX
node = diagram.findByType("filternode",'_AVGDX' + period)
for field in node.getInputDataModel().nameIterator():
if field == ID_FIELD:
pass
else:
field_cut = field.replace('_Mean_Sum','')
node.setKeyedPropertyValue("new_name", field, field_cut + '_AVGDX' + period)
# Historia Rename & Run
periods = 12
iteration = 0
for period in periods_list:
iteration = iteration + 1
historia_list = []
date = datetime.date(int('20'+str(period)[0:2]),int(str(period)[2:4]),1)
h_iter = 0
while True:
if h_iter == 0:
dxdate = date
else:
dxdate = dxdate - datetime.timedelta(days=1)
dxdate = dxdate.replace(day=1)
dxperiod_year = str(dxdate.year)[2:4]
if len(str(dxdate.month)) == 1:
dxperiod_month = '0' + str(dxdate.month)
else:
dxperiod_month = str(dxdate.month)
historia_list.insert(h_iter, str(dxdate.year)[2:4] + dxperiod_month)
h_iter = h_iter + 1
if h_iter == periods:
break
# Rename In/Out
diagram.findByType("statisticsexport","out").setPropertyValue("full_filename", direc + period + "_12M.sav")
for p in range(periods):
diagram.findByType("statisticsimport",str(p + 1)).setPropertyValue("full_filename", direc + historia_list[p] + ".sav")
# Run Stream
diagram.findByType("dataaudit","QUALI").run(None)
diagram.findByType("statisticsexport","out").run(None) | 0.261708 | 0.192634 |
g1_1 = '↘️Як укласти договір на підключення до мережі Інтернет?\n\n' \
'✏️Потрібно просто залишити заявку на підключення.\n' \
'Договір з Вами укладе наш фахівець при підключенні.\n' \
'Для цього Вам необхідно мати при собі паспорт або ID-карту\n'
g1_2 = '↘️Я переїжджаю, але не хочу відмовлятися від послуг зв\'язку?\n\n' \
'✏️Технічну можливість підключення за новою адресою Ви можете дізнатись за телефонами:\n ' \
'(0522) 27-60-06\n(050) 341-61-00\n(067) 233-86-10\n(063) 462-21-22\n'
g1_3 = '↘️Для чого потрібен Особистий Кабінет?\n\n' \
'✏️Особистий Кабінет - це місце, де ви можете стежити за станом свого\n' \
'особового рахунку, оплатами і списаннями коштів за послуги, змінювати тарифний план.\n'
g1_4 = '↘️Як мені дізнатися про новини компанії?\n\n' \
'✏️Всі змiни, новини i акцiї публікуються на офіційному сайті imperial.net.ua\n'
g1_5 = '↘️Які бувають акції?\n\n' \
'✏️Про всі акції Ви зможете дізнатися на офіційному сайті компанії imperial.net.ua\n' \
'або за телефонами:\n(0522) 21-60-06\n(050) 341-61-00\n(067) 233-86-10\n(063) 462-21-22\n'
g1_6 = '↘️Де знаходиться офіс компанії?\n\n' \
'✏️Офіс компанії знаходиться за адресою: м. Кропивницький, вул. Єгорова 8\n'
c1_1 = '↘️Як можна залишити заявку на підключення?\n\n' \
'✏️ANSWER\n'
c1_2 = '↘️Чи є можливість підключення на мою адресу?\n\n' \
'✏️ANSWER\n'
c1_3 = '↘️Як підключити 2 комп\'ютери до інтернету?\n\n' \
'✏️ANSWER\n'
c1_4 = '↘️Як краще організувати домашню мережу?\n\n' \
'✏️ANSWER\n'
i1_1 = '↘️Чи є обмеження по трафіку (поріг скачування)?\n\n' \
'✏️ANSWER\n'
i1_2 = '↘️Як налаштувати інтернет підключення після зміни системного блоку або перевстановлення мережевої карти?\n\n' \
'✏️ANSWER\n'
i1_3 = '↘️Мені здається, що швидкість не відповідає заявленій. Що робити?\n\n' \
'✏️ANSWER\n'
i1_4 = '↘️Як перезавантажити роутер?\n\n' \
'✏️ANSWER\n'
i1_5 = '↘️У мене повільно завантажуються файли з визначеного сайту.\n\n' \
'✏️ANSWER\n'
i1_6 = '↘️Не можу вийти в інтернет, у мене маршрутизатор.\n\n' \
'✏️ANSWER\n'
t1_1 = '↘️Що це за телебачення, які канали в нього включені і яка вартість оплати?\n\n' \
'✏️ANSWER\n'
t1_2 = '↘️Чи потрібно протягувати ще один кабель для ТВ якщо я вже підключений до інтернету?\n\n' \
'✏️ANSWER\n'
t1_3 = '↘️Хочу підключити до однієї приставки кілька телевізорів. Чи можна це зробити?\n\n' \
'✏️ANSWER\n'
t1_4 = '↘️Чи можу я переглядати телебачення на комп\'ютері, не використовуючи приставку?\n\n' \
'✏️ANSWER\n'
t1_5 = '↘️Як налаштувати приставку на перегляд телебачення?\n\n' \
'✏️ANSWER\n'
t1_6 = '↘️Чи можу я переглядати телебачення на телевізорі з функцією SMART TV?\n\n' \
'✏️ANSWER\n'
t1_7 = '↘️Спільна робота ТВ та інтернет-з\'єднання\n\n' \
'✏️ANSWER\n'
p1_1 = '↘️В який період необхідно оплачувати послуги?\n\n' \
'✏️ANSWER\n'
p1_2 = '↘️Як списуються кошти з особового рахунку?\n\n' \
'✏️ANSWER\n'
p1_3 = '↘️Де можна подивитися деталізацію рахунка?\n\n' \
'✏️ANSWER\n'
p1_4 = '↘️Як перевірити баланс?\n\n' \
'✏️ANSWER\n'
p1_5 = '↘️Як поповнити рахунок?\n\n' \
'✏️ANSWER\n'
p1_6 = '↘️Куди необхідно звернутися, якщо платіж не дійшов або оплачений невірно?\n\n' \
'✏️ANSWER\n'
p1_7 = '↘️Платив через термінал, але чек термінал не видав і гроші на рахунок не надійшли. Що робити?\n\n' \
'✏️ANSWER\n'
p1_8 = '↘️Звідки у мене мінус на рахунку?\n\n' \
'✏️ANSWER\n' | telegram_bot/utils/faq_answers.py | g1_1 = '↘️Як укласти договір на підключення до мережі Інтернет?\n\n' \
'✏️Потрібно просто залишити заявку на підключення.\n' \
'Договір з Вами укладе наш фахівець при підключенні.\n' \
'Для цього Вам необхідно мати при собі паспорт або ID-карту\n'
g1_2 = '↘️Я переїжджаю, але не хочу відмовлятися від послуг зв\'язку?\n\n' \
'✏️Технічну можливість підключення за новою адресою Ви можете дізнатись за телефонами:\n ' \
'(0522) 27-60-06\n(050) 341-61-00\n(067) 233-86-10\n(063) 462-21-22\n'
g1_3 = '↘️Для чого потрібен Особистий Кабінет?\n\n' \
'✏️Особистий Кабінет - це місце, де ви можете стежити за станом свого\n' \
'особового рахунку, оплатами і списаннями коштів за послуги, змінювати тарифний план.\n'
g1_4 = '↘️Як мені дізнатися про новини компанії?\n\n' \
'✏️Всі змiни, новини i акцiї публікуються на офіційному сайті imperial.net.ua\n'
g1_5 = '↘️Які бувають акції?\n\n' \
'✏️Про всі акції Ви зможете дізнатися на офіційному сайті компанії imperial.net.ua\n' \
'або за телефонами:\n(0522) 21-60-06\n(050) 341-61-00\n(067) 233-86-10\n(063) 462-21-22\n'
g1_6 = '↘️Де знаходиться офіс компанії?\n\n' \
'✏️Офіс компанії знаходиться за адресою: м. Кропивницький, вул. Єгорова 8\n'
c1_1 = '↘️Як можна залишити заявку на підключення?\n\n' \
'✏️ANSWER\n'
c1_2 = '↘️Чи є можливість підключення на мою адресу?\n\n' \
'✏️ANSWER\n'
c1_3 = '↘️Як підключити 2 комп\'ютери до інтернету?\n\n' \
'✏️ANSWER\n'
c1_4 = '↘️Як краще організувати домашню мережу?\n\n' \
'✏️ANSWER\n'
i1_1 = '↘️Чи є обмеження по трафіку (поріг скачування)?\n\n' \
'✏️ANSWER\n'
i1_2 = '↘️Як налаштувати інтернет підключення після зміни системного блоку або перевстановлення мережевої карти?\n\n' \
'✏️ANSWER\n'
i1_3 = '↘️Мені здається, що швидкість не відповідає заявленій. Що робити?\n\n' \
'✏️ANSWER\n'
i1_4 = '↘️Як перезавантажити роутер?\n\n' \
'✏️ANSWER\n'
i1_5 = '↘️У мене повільно завантажуються файли з визначеного сайту.\n\n' \
'✏️ANSWER\n'
i1_6 = '↘️Не можу вийти в інтернет, у мене маршрутизатор.\n\n' \
'✏️ANSWER\n'
t1_1 = '↘️Що це за телебачення, які канали в нього включені і яка вартість оплати?\n\n' \
'✏️ANSWER\n'
t1_2 = '↘️Чи потрібно протягувати ще один кабель для ТВ якщо я вже підключений до інтернету?\n\n' \
'✏️ANSWER\n'
t1_3 = '↘️Хочу підключити до однієї приставки кілька телевізорів. Чи можна це зробити?\n\n' \
'✏️ANSWER\n'
t1_4 = '↘️Чи можу я переглядати телебачення на комп\'ютері, не використовуючи приставку?\n\n' \
'✏️ANSWER\n'
t1_5 = '↘️Як налаштувати приставку на перегляд телебачення?\n\n' \
'✏️ANSWER\n'
t1_6 = '↘️Чи можу я переглядати телебачення на телевізорі з функцією SMART TV?\n\n' \
'✏️ANSWER\n'
t1_7 = '↘️Спільна робота ТВ та інтернет-з\'єднання\n\n' \
'✏️ANSWER\n'
p1_1 = '↘️В який період необхідно оплачувати послуги?\n\n' \
'✏️ANSWER\n'
p1_2 = '↘️Як списуються кошти з особового рахунку?\n\n' \
'✏️ANSWER\n'
p1_3 = '↘️Де можна подивитися деталізацію рахунка?\n\n' \
'✏️ANSWER\n'
p1_4 = '↘️Як перевірити баланс?\n\n' \
'✏️ANSWER\n'
p1_5 = '↘️Як поповнити рахунок?\n\n' \
'✏️ANSWER\n'
p1_6 = '↘️Куди необхідно звернутися, якщо платіж не дійшов або оплачений невірно?\n\n' \
'✏️ANSWER\n'
p1_7 = '↘️Платив через термінал, але чек термінал не видав і гроші на рахунок не надійшли. Що робити?\n\n' \
'✏️ANSWER\n'
p1_8 = '↘️Звідки у мене мінус на рахунку?\n\n' \
'✏️ANSWER\n' | 0.046823 | 0.25239 |
from django.shortcuts import render
from django.http import HttpResponse, HttpResponseRedirect
from django.views.generic import ListView, CreateView, UpdateView, TemplateView, DeleteView, DetailView
from django.contrib.auth.mixins import LoginRequiredMixin
from .models import Book
from .forms import CreateBookForm, UpdateBookForm
from reference_book.models import Author, Genre, Serie, Publisher
class CreateBookView(LoginRequiredMixin, CreateView):
model = Book
form_class = CreateBookForm
success_url = '/book'
template_name = 'refs/create_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Создать книгу"
return context
class UpdateBookView(LoginRequiredMixin, UpdateView):
model = Book
form_class = UpdateBookForm
success_url = '/book'
template_name = 'refs/create_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Обновить карточку книги"
return context
class DeleteBookView(LoginRequiredMixin, DeleteView):
model = Book
success_url = '/book'
template_name = 'refs/delete_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Удалить книгу"
key = self.kwargs.get(self.pk_url_kwarg)
context["obj"] = Book.objects.get(pk=key)
return context
class ShowBookByPKView(DetailView):
template_name = "refs/book.html"
model = Book
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
key = self.kwargs.get(self.pk_url_kwarg)
some_book = Book.objects.get(pk=key)
context["book_obj"] = some_book
context["author_obj"] = some_book.book_author.all()
context["genre_obj"] = some_book.book_genre.all()
return context
class ShowBookListView(ListView):
template_name = 'refs/book_list.html'
paginate_by = 10
model = Book
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Список книг"
return context | src/books/views.py | from django.shortcuts import render
from django.http import HttpResponse, HttpResponseRedirect
from django.views.generic import ListView, CreateView, UpdateView, TemplateView, DeleteView, DetailView
from django.contrib.auth.mixins import LoginRequiredMixin
from .models import Book
from .forms import CreateBookForm, UpdateBookForm
from reference_book.models import Author, Genre, Serie, Publisher
class CreateBookView(LoginRequiredMixin, CreateView):
model = Book
form_class = CreateBookForm
success_url = '/book'
template_name = 'refs/create_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Создать книгу"
return context
class UpdateBookView(LoginRequiredMixin, UpdateView):
model = Book
form_class = UpdateBookForm
success_url = '/book'
template_name = 'refs/create_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Обновить карточку книги"
return context
class DeleteBookView(LoginRequiredMixin, DeleteView):
model = Book
success_url = '/book'
template_name = 'refs/delete_object.html'
login_url = '/auth_login'
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Удалить книгу"
key = self.kwargs.get(self.pk_url_kwarg)
context["obj"] = Book.objects.get(pk=key)
return context
class ShowBookByPKView(DetailView):
template_name = "refs/book.html"
model = Book
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
key = self.kwargs.get(self.pk_url_kwarg)
some_book = Book.objects.get(pk=key)
context["book_obj"] = some_book
context["author_obj"] = some_book.book_author.all()
context["genre_obj"] = some_book.book_genre.all()
return context
class ShowBookListView(ListView):
template_name = 'refs/book_list.html'
paginate_by = 10
model = Book
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["header"] = "Список книг"
return context | 0.311846 | 0.0524 |
import html.parser
import logging
import time
import sys
# Third-Party Libraries
from bs4 import BeautifulSoup
import requests
# Custom Libraries
import version
parser = html.parser.HTMLParser()
def request_sentences():
# TODO: Create with keyword parameters
pass
def generate_example_sentences(keyword_to_search_for):
endpoint = "https://tatoeba.org/eng/sentences/search"
language_from = "jpn"
language_to = "eng"
# https://tatoeba.org/eng/sentences/search
# ?
# from=jpn
# has_audio=
# list=
# native=yes
# orphans=no
# query=%E7%94%A8%E8%AA%9E
# sort=words
# tags=
# to=eng
# trans_filter=limit
# trans_has_audio=
# trans_link=
# trans_orphan=
# trans_to=eng
# trans_unapproved=
# trans_user=
# unapproved=no
# user=
response = requests.get(
endpoint,
params={
"from": language_from,
"native": "yes",
"orphans": "no",
"query": keyword_to_search_for,
"sort": "words",
"to": language_to,
"trans_to": "eng",
"unapproved": "no",
}
)
soup = BeautifulSoup(response.text, "html.parser")
sentences_and_translations = soup.findAll(
"div", {"class": "sentence-and-translations"}
)
# list of tuples, where first index is japanese sentence, second index is
# english sentence [(source, translation), ...]
sentences_found = []
for sentence_and_translation in sentences_and_translations:
print("-" * 80)
# print(sentence_and_translation)
japanese_sentence = "MISSING"
english_sentence = "MISSING"
# Japanese sentence selection
sentence_elements = sentence_and_translation.findAll(
"div", {"class": "sentence"}
)
for sentence_element in sentence_elements:
text_elements = sentence_element.findAll("div", {"class": "text"})
# Should really be only one element
for text_element in text_elements:
japanese_sentence = text_element.text.strip()
# English sentence selection
translation_elements = sentence_and_translation.findAll(
"div", {"class": "translation"}
)
for translation_element in translation_elements:
text_elements = translation_element.findAll(
"div", {"class": "text"}
)
# Should really be only one element
for text_element in text_elements:
english_sentence = text_element.string.strip()
print("japanese_sentence: {}".format(japanese_sentence))
print("english_sentence: {}".format(english_sentence))
sentences_found.append((japanese_sentence, english_sentence))
return sentences_found
if __name__ == "__main__":
generate_example_sentences("用語") | source_code/tatoeba_scraper.py | import html.parser
import logging
import time
import sys
# Third-Party Libraries
from bs4 import BeautifulSoup
import requests
# Custom Libraries
import version
parser = html.parser.HTMLParser()
def request_sentences():
# TODO: Create with keyword parameters
pass
def generate_example_sentences(keyword_to_search_for):
endpoint = "https://tatoeba.org/eng/sentences/search"
language_from = "jpn"
language_to = "eng"
# https://tatoeba.org/eng/sentences/search
# ?
# from=jpn
# has_audio=
# list=
# native=yes
# orphans=no
# query=%E7%94%A8%E8%AA%9E
# sort=words
# tags=
# to=eng
# trans_filter=limit
# trans_has_audio=
# trans_link=
# trans_orphan=
# trans_to=eng
# trans_unapproved=
# trans_user=
# unapproved=no
# user=
response = requests.get(
endpoint,
params={
"from": language_from,
"native": "yes",
"orphans": "no",
"query": keyword_to_search_for,
"sort": "words",
"to": language_to,
"trans_to": "eng",
"unapproved": "no",
}
)
soup = BeautifulSoup(response.text, "html.parser")
sentences_and_translations = soup.findAll(
"div", {"class": "sentence-and-translations"}
)
# list of tuples, where first index is japanese sentence, second index is
# english sentence [(source, translation), ...]
sentences_found = []
for sentence_and_translation in sentences_and_translations:
print("-" * 80)
# print(sentence_and_translation)
japanese_sentence = "MISSING"
english_sentence = "MISSING"
# Japanese sentence selection
sentence_elements = sentence_and_translation.findAll(
"div", {"class": "sentence"}
)
for sentence_element in sentence_elements:
text_elements = sentence_element.findAll("div", {"class": "text"})
# Should really be only one element
for text_element in text_elements:
japanese_sentence = text_element.text.strip()
# English sentence selection
translation_elements = sentence_and_translation.findAll(
"div", {"class": "translation"}
)
for translation_element in translation_elements:
text_elements = translation_element.findAll(
"div", {"class": "text"}
)
# Should really be only one element
for text_element in text_elements:
english_sentence = text_element.string.strip()
print("japanese_sentence: {}".format(japanese_sentence))
print("english_sentence: {}".format(english_sentence))
sentences_found.append((japanese_sentence, english_sentence))
return sentences_found
if __name__ == "__main__":
generate_example_sentences("用語") | 0.134037 | 0.138258 |
import csv
from dataclasses import dataclass
from datetime import date
from pathlib import Path
from typing import Optional, Iterable
@dataclass
class ReportEntry:
"""An entry in a report."""
pdf_path: Path
"""The path on disk to the pdf file."""
pdf_hash_type: str
"""The hash algorithm used to generate the pdf file hash value."""
pdf_hash_value: str
"""The pdf file hash digest."""
pdf_page: str
"""The page number in the pdf file."""
pdf_line: str
"""The line number in the pdf page."""
pdf_created_date: Optional[date]
"""The created date from the pdf file metadata."""
pdf_modified_date: Optional[date]
"""The modified date from the pdf file metadata."""
pdf_downloaded_date: date
"""The date the pdf file was downloaded."""
pdf_url: str
"""The absolute url for the pdf file."""
referrer_url: Optional[str]
"""The referrer url that lead to the pdf url."""
website_modified_date: Optional[date]
"""The last updated date parsed from the website."""
processed_date: Optional[date]
"""The processed date from the pdf file."""
signed_date: Optional[date]
"""The signed date from the pdf file."""
assembly: str
"""
The involvement the person has:
'member' (house of reps) or 'senator' (senate).
"""
last_name: str
"""The person's last name."""
first_name: str
"""The person's first name."""
state_or_territory: str
"""The Australian state or territory the person is representing."""
electorate: Optional[str]
"""Name of person's electorate for house of representatives."""
register_section: str
"""The title of the section in the register of member's interests form."""
change_type: str
"""The type of change to the register: addition or deletion."""
# --- form table headings ---
form_who: str
"""
The person or people relevant to the entry for all sections:
'self', 'partner', 'dependent'.
"""
form_name: Optional[str] = None
"""
Name of the thing.
Name for section
1. Shareholdings - company;
2. i. trust beneficial interest - trust/nominee;
2. ii. trustee and beneficial interest - trust/nominee;
4. Directorships of companies - company;
5. Partnerships - partnership;
6. Liabilities - creditor;
7. bonds and other investments - body in which investment is held;
8. Saving or investment accounts - name of bank/institution;
13. Organisation membership - name of organisation;
"""
form_activity: Optional[str] = None
"""
What does the thing do.
Nature / activities of trust / company for section
2. i. trust beneficial interest - trust operation;
2. ii. trustee and beneficial interest - trust operation;
4. Directorships of companies - company;
5. Partnerships - partnership;
"""
form_participation: Optional[str] = None
"""
What is your interest / participation / involvement in the thing.
Beneficial interest / nature of participation for section
2. i. trust beneficial interest - Beneficial interest;
2. ii. trustee and beneficial interest - Beneficial interest;
3. Real estate - Purpose for which owned;
5. Partnerships - nature of interest;
6. Liabilities - nature of liability;
7. bonds and other investments - type of investment;
8. Saving or investment accounts - nature of account;
9. other assets - nature of any other assets;
10. Other income - nature of income;
11. Gifts - details of gifts;
12. travel and hospitality - details of travel/hospitality;
14. Other interests - nature of interest;
"""
form_location: Optional[str] = None
"""
Where is the thing physically located.
Real estate location for section
3. Real estate;
"""
@property
def is_valid(self):
return all(
[
self.pdf_url,
self.assembly,
self.last_name,
self.state_or_territory,
self.register_section,
self.change_type,
any(
[
self.form_location,
self.form_who,
self.form_name,
self.form_activity,
self.form_participation,
]
),
]
)
@property
def short_hash(self):
return self.pdf_hash_value[0:15]
@classmethod
def save(cls, path: Path, items: Iterable["ReportEntry"]):
"""Save items to a csv file."""
fields = [
"assembly",
"state_or_territory",
"electorate",
"last_name",
"first_name",
"register_section",
"change_type",
"form_who",
"form_name",
"form_activity",
"form_participation",
"form_location",
"pdf_created_date",
"pdf_modified_date",
"pdf_downloaded_date",
"website_modified_date",
"processed_date",
"signed_date",
"pdf_page",
"pdf_line",
"pdf_url",
"referrer_url",
"pdf_hash_type",
"pdf_hash_value",
]
path.parent.mkdir(parents=True, exist_ok=True)
with open(path, "wt", newline="", encoding="utf8") as f:
writer = csv.DictWriter(f, fields, dialect="excel")
writer.writeheader()
for i in items:
writer.writerow(
{
"pdf_hash_type": i.pdf_hash_type,
"pdf_hash_value": i.pdf_hash_value,
"pdf_page": i.pdf_page,
"pdf_line": i.pdf_line,
"pdf_created_date": cls.fmt_date(i.pdf_created_date),
"pdf_modified_date": cls.fmt_date(i.pdf_modified_date),
"pdf_downloaded_date": cls.fmt_date(i.pdf_downloaded_date),
"pdf_url": i.pdf_url,
"referrer_url": i.referrer_url,
"website_modified_date": cls.fmt_date(i.website_modified_date),
"processed_date": cls.fmt_date(i.processed_date),
"signed_date": cls.fmt_date(i.signed_date),
"assembly": i.assembly,
"last_name": i.last_name,
"first_name": i.first_name,
"state_or_territory": i.state_or_territory,
"electorate": i.electorate,
"register_section": i.register_section,
"change_type": i.change_type,
"form_who": i.form_who,
"form_name": i.form_name,
"form_activity": i.form_activity,
"form_participation": i.form_participation,
"form_location": i.form_location,
}
)
@classmethod
def fmt_date(cls, value: date) -> str:
if not value:
return ""
return value.isoformat()
def __str__(self):
items = [
("doc", self.short_hash),
("page", self.pdf_page),
("line", self.pdf_line),
("person", self.last_name),
("group", self.register_section),
("location", self.form_location),
("who", self.form_who),
("name", self.form_name),
("activity", self.form_activity),
("participation", self.form_participation),
]
return "; ".join(f"{k}={v}" for k, v in items if v) | leaf_focus/report/item/report_entry.py | import csv
from dataclasses import dataclass
from datetime import date
from pathlib import Path
from typing import Optional, Iterable
@dataclass
class ReportEntry:
"""An entry in a report."""
pdf_path: Path
"""The path on disk to the pdf file."""
pdf_hash_type: str
"""The hash algorithm used to generate the pdf file hash value."""
pdf_hash_value: str
"""The pdf file hash digest."""
pdf_page: str
"""The page number in the pdf file."""
pdf_line: str
"""The line number in the pdf page."""
pdf_created_date: Optional[date]
"""The created date from the pdf file metadata."""
pdf_modified_date: Optional[date]
"""The modified date from the pdf file metadata."""
pdf_downloaded_date: date
"""The date the pdf file was downloaded."""
pdf_url: str
"""The absolute url for the pdf file."""
referrer_url: Optional[str]
"""The referrer url that lead to the pdf url."""
website_modified_date: Optional[date]
"""The last updated date parsed from the website."""
processed_date: Optional[date]
"""The processed date from the pdf file."""
signed_date: Optional[date]
"""The signed date from the pdf file."""
assembly: str
"""
The involvement the person has:
'member' (house of reps) or 'senator' (senate).
"""
last_name: str
"""The person's last name."""
first_name: str
"""The person's first name."""
state_or_territory: str
"""The Australian state or territory the person is representing."""
electorate: Optional[str]
"""Name of person's electorate for house of representatives."""
register_section: str
"""The title of the section in the register of member's interests form."""
change_type: str
"""The type of change to the register: addition or deletion."""
# --- form table headings ---
form_who: str
"""
The person or people relevant to the entry for all sections:
'self', 'partner', 'dependent'.
"""
form_name: Optional[str] = None
"""
Name of the thing.
Name for section
1. Shareholdings - company;
2. i. trust beneficial interest - trust/nominee;
2. ii. trustee and beneficial interest - trust/nominee;
4. Directorships of companies - company;
5. Partnerships - partnership;
6. Liabilities - creditor;
7. bonds and other investments - body in which investment is held;
8. Saving or investment accounts - name of bank/institution;
13. Organisation membership - name of organisation;
"""
form_activity: Optional[str] = None
"""
What does the thing do.
Nature / activities of trust / company for section
2. i. trust beneficial interest - trust operation;
2. ii. trustee and beneficial interest - trust operation;
4. Directorships of companies - company;
5. Partnerships - partnership;
"""
form_participation: Optional[str] = None
"""
What is your interest / participation / involvement in the thing.
Beneficial interest / nature of participation for section
2. i. trust beneficial interest - Beneficial interest;
2. ii. trustee and beneficial interest - Beneficial interest;
3. Real estate - Purpose for which owned;
5. Partnerships - nature of interest;
6. Liabilities - nature of liability;
7. bonds and other investments - type of investment;
8. Saving or investment accounts - nature of account;
9. other assets - nature of any other assets;
10. Other income - nature of income;
11. Gifts - details of gifts;
12. travel and hospitality - details of travel/hospitality;
14. Other interests - nature of interest;
"""
form_location: Optional[str] = None
"""
Where is the thing physically located.
Real estate location for section
3. Real estate;
"""
@property
def is_valid(self):
return all(
[
self.pdf_url,
self.assembly,
self.last_name,
self.state_or_territory,
self.register_section,
self.change_type,
any(
[
self.form_location,
self.form_who,
self.form_name,
self.form_activity,
self.form_participation,
]
),
]
)
@property
def short_hash(self):
return self.pdf_hash_value[0:15]
@classmethod
def save(cls, path: Path, items: Iterable["ReportEntry"]):
"""Save items to a csv file."""
fields = [
"assembly",
"state_or_territory",
"electorate",
"last_name",
"first_name",
"register_section",
"change_type",
"form_who",
"form_name",
"form_activity",
"form_participation",
"form_location",
"pdf_created_date",
"pdf_modified_date",
"pdf_downloaded_date",
"website_modified_date",
"processed_date",
"signed_date",
"pdf_page",
"pdf_line",
"pdf_url",
"referrer_url",
"pdf_hash_type",
"pdf_hash_value",
]
path.parent.mkdir(parents=True, exist_ok=True)
with open(path, "wt", newline="", encoding="utf8") as f:
writer = csv.DictWriter(f, fields, dialect="excel")
writer.writeheader()
for i in items:
writer.writerow(
{
"pdf_hash_type": i.pdf_hash_type,
"pdf_hash_value": i.pdf_hash_value,
"pdf_page": i.pdf_page,
"pdf_line": i.pdf_line,
"pdf_created_date": cls.fmt_date(i.pdf_created_date),
"pdf_modified_date": cls.fmt_date(i.pdf_modified_date),
"pdf_downloaded_date": cls.fmt_date(i.pdf_downloaded_date),
"pdf_url": i.pdf_url,
"referrer_url": i.referrer_url,
"website_modified_date": cls.fmt_date(i.website_modified_date),
"processed_date": cls.fmt_date(i.processed_date),
"signed_date": cls.fmt_date(i.signed_date),
"assembly": i.assembly,
"last_name": i.last_name,
"first_name": i.first_name,
"state_or_territory": i.state_or_territory,
"electorate": i.electorate,
"register_section": i.register_section,
"change_type": i.change_type,
"form_who": i.form_who,
"form_name": i.form_name,
"form_activity": i.form_activity,
"form_participation": i.form_participation,
"form_location": i.form_location,
}
)
@classmethod
def fmt_date(cls, value: date) -> str:
if not value:
return ""
return value.isoformat()
def __str__(self):
items = [
("doc", self.short_hash),
("page", self.pdf_page),
("line", self.pdf_line),
("person", self.last_name),
("group", self.register_section),
("location", self.form_location),
("who", self.form_who),
("name", self.form_name),
("activity", self.form_activity),
("participation", self.form_participation),
]
return "; ".join(f"{k}={v}" for k, v in items if v) | 0.888396 | 0.526465 |
"""Test result collection model."""
import itertools
from nose.tools import *
from mock import patch
from default import Test, with_context, flask_app
from requests.exceptions import HTTPError
from factories import UserFactory, TaskFactory
from flask import url_for, current_app
from pybossa.model.task import Task
from pybossa_lc.model.base import Base
from pybossa_lc.model.result_collection import ResultCollection
@patch('pybossa_lc.model.base.wa_client')
class TestResultCollection(Test):
def setUp(self):
super(TestResultCollection, self).setUp()
assert_dict_equal.__self__.maxDiff = None
@with_context
def test_add_comment(self, mock_client):
"""Test that a comment Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
user = UserFactory.create()
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_comment(task, target, value, user)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'commenting',
'type': 'Annotation',
'creator': {
'id': url_for('api.api_user', oid=user.id),
'type': 'Person',
'name': user.fullname,
'nickname': user.name
},
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'commenting',
'value': value,
'format': 'text/plain'
},
'target': target
})
@with_context
def test_add_tag(self, mock_client):
"""Test that a tagging Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_tag(task, target, value)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'tagging',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'tagging',
'value': value
},
'target': target
})
@with_context
def test_add_tag_with_fragment(self, mock_client):
"""Test that a tagging Annotation is added with a FragmentSelector."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
task = TaskFactory()
rect = dict(x=100, y=100, w=50, h=50)
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_tag(task, target, value, rect)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'tagging',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'tagging',
'value': value
},
'target': {
'source': target,
'selector': {
'conformsTo': 'http://www.w3.org/TR/media-frags/',
'type': 'FragmentSelector',
'value': '?xywh={0},{1},{2},{3}'.format(rect['x'],
rect['y'],
rect['w'],
rect['h'])
}
}
})
@with_context
def test_add_transcription(self, mock_client):
"""Test that a describing Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
tag = 'baz'
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_transcription(task, target, value, tag)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'describing',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': [
{
"type": "TextualBody",
"purpose": "describing",
"value": value,
"format": "text/plain"
},
{
"type": "TextualBody",
"purpose": "tagging",
"value": tag
}
],
'target': target
})
@with_context
def test_error_when_invalid_comment_values(self, mock_client):
"""Test ValueError raised when invalid comment values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_comment(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_error_when_invalid_tag_values(self, mock_client):
"""Test ValueError raised when invalid tag values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_tag(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_error_when_invalid_transcription_values(self, mock_client):
"""Test ValueError raised when invalid transcription values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value', 'tag']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_transcription(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_annotations_searched_by_task(self, mock_client):
"""Test Annotations are searched for by task."""
iri = 'example.com'
rc = ResultCollection(iri)
task = Task(project_id=1)
rc.get_by_task_id(task.id)
contains = {
'generator': [
{
'id': url_for('api.api_task', oid=task.id),
'type': 'Software'
}
]
}
mock_client.search_annotations.assert_called_once_with(iri, contains)
@with_context
def test_batch_delete_annotations(self, mock_client):
"""Test Annotations are deleted."""
rc = ResultCollection(None)
annos = [
{
'id': 'foo',
'type': 'Annotation'
},
{
'id': 'bar',
'type': 'Annotation'
}
]
rc.delete_batch(annos)
mock_client.delete_batch.assert_called_once_with(annos)
@with_context
def test_transcription_values_validated(self, mock_client):
"""Test validation for required transcription values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_transcription(task, 'example.com', u'\xa3', 42)
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', 'bar', '', None], 3):
assert_raises(ValueError, rc.add_transcription, task, comb[0],
comb[1], comb[2])
@with_context
def test_tagging_values_validated(self, mock_client):
"""Test validation for required tagging values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_tag(task, 'example.com', u'\xa3')
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', '', None], 2):
assert_raises(ValueError, rc.add_tag, task, comb[0], comb[1])
@with_context
def test_comment_values_validated(self, mock_client):
"""Test validation for required comment values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_comment(task, 'example.com', u'\xa3')
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', '', None], 2):
assert_raises(ValueError, rc.add_comment, task, comb[0], comb[1])
@with_context
def test_get_annotation_base(self, mock_client):
"""Test get Annotation base."""
rc = ResultCollection(None)
task = TaskFactory()
motivation = 'foo'
base = rc._get_annotation_base(task, motivation)
assert_equal(base, {
'type': 'Annotation',
'motivation': motivation,
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
]
})
@with_context
def test_get_annotation_base_with_manifest(self, mock_client):
"""Test get Annotation base with a manifest."""
rc = ResultCollection(None)
manifest = 'example.com'
task = TaskFactory(info=dict(manifest=manifest))
motivation = 'foo'
base = rc._get_annotation_base(task, motivation)
assert_equal(base, {
'type': 'Annotation',
'motivation': motivation,
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'partOf': manifest
}) | test/test_model/test_result_collection.py | """Test result collection model."""
import itertools
from nose.tools import *
from mock import patch
from default import Test, with_context, flask_app
from requests.exceptions import HTTPError
from factories import UserFactory, TaskFactory
from flask import url_for, current_app
from pybossa.model.task import Task
from pybossa_lc.model.base import Base
from pybossa_lc.model.result_collection import ResultCollection
@patch('pybossa_lc.model.base.wa_client')
class TestResultCollection(Test):
def setUp(self):
super(TestResultCollection, self).setUp()
assert_dict_equal.__self__.maxDiff = None
@with_context
def test_add_comment(self, mock_client):
"""Test that a comment Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
user = UserFactory.create()
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_comment(task, target, value, user)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'commenting',
'type': 'Annotation',
'creator': {
'id': url_for('api.api_user', oid=user.id),
'type': 'Person',
'name': user.fullname,
'nickname': user.name
},
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'commenting',
'value': value,
'format': 'text/plain'
},
'target': target
})
@with_context
def test_add_tag(self, mock_client):
"""Test that a tagging Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_tag(task, target, value)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'tagging',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'tagging',
'value': value
},
'target': target
})
@with_context
def test_add_tag_with_fragment(self, mock_client):
"""Test that a tagging Annotation is added with a FragmentSelector."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
task = TaskFactory()
rect = dict(x=100, y=100, w=50, h=50)
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_tag(task, target, value, rect)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'tagging',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': {
'type': 'TextualBody',
'purpose': 'tagging',
'value': value
},
'target': {
'source': target,
'selector': {
'conformsTo': 'http://www.w3.org/TR/media-frags/',
'type': 'FragmentSelector',
'value': '?xywh={0},{1},{2},{3}'.format(rect['x'],
rect['y'],
rect['w'],
rect['h'])
}
}
})
@with_context
def test_add_transcription(self, mock_client):
"""Test that a describing Annotation is added."""
iri = 'example.com'
rc = ResultCollection(iri)
target = 'foo'
value = 'bar'
tag = 'baz'
task = TaskFactory()
fake_anno = dict(foo='bar')
mock_client.create_annotation.return_value = fake_anno
anno = rc.add_transcription(task, target, value, tag)
assert_equal(anno, fake_anno)
mock_client.create_annotation.assert_called_once_with(iri, {
'motivation': 'describing',
'type': 'Annotation',
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'body': [
{
"type": "TextualBody",
"purpose": "describing",
"value": value,
"format": "text/plain"
},
{
"type": "TextualBody",
"purpose": "tagging",
"value": tag
}
],
'target': target
})
@with_context
def test_error_when_invalid_comment_values(self, mock_client):
"""Test ValueError raised when invalid comment values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_comment(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_error_when_invalid_tag_values(self, mock_client):
"""Test ValueError raised when invalid tag values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_tag(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_error_when_invalid_transcription_values(self, mock_client):
"""Test ValueError raised when invalid transcription values."""
iri = 'example.com'
rc = ResultCollection(iri)
task = TaskFactory()
required = ['target', 'value', 'tag']
invalid = ['', None]
for key in required:
for bad_value in invalid:
values = {k: 'foo' for k in required}
values[key] = bad_value
with assert_raises(ValueError) as exc:
rc.add_transcription(task, **values)
err_msg = exc.exception.message
assert_equal(err_msg, '"{}" is a required value'.format(key))
@with_context
def test_annotations_searched_by_task(self, mock_client):
"""Test Annotations are searched for by task."""
iri = 'example.com'
rc = ResultCollection(iri)
task = Task(project_id=1)
rc.get_by_task_id(task.id)
contains = {
'generator': [
{
'id': url_for('api.api_task', oid=task.id),
'type': 'Software'
}
]
}
mock_client.search_annotations.assert_called_once_with(iri, contains)
@with_context
def test_batch_delete_annotations(self, mock_client):
"""Test Annotations are deleted."""
rc = ResultCollection(None)
annos = [
{
'id': 'foo',
'type': 'Annotation'
},
{
'id': 'bar',
'type': 'Annotation'
}
]
rc.delete_batch(annos)
mock_client.delete_batch.assert_called_once_with(annos)
@with_context
def test_transcription_values_validated(self, mock_client):
"""Test validation for required transcription values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_transcription(task, 'example.com', u'\xa3', 42)
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', 'bar', '', None], 3):
assert_raises(ValueError, rc.add_transcription, task, comb[0],
comb[1], comb[2])
@with_context
def test_tagging_values_validated(self, mock_client):
"""Test validation for required tagging values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_tag(task, 'example.com', u'\xa3')
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', '', None], 2):
assert_raises(ValueError, rc.add_tag, task, comb[0], comb[1])
@with_context
def test_comment_values_validated(self, mock_client):
"""Test validation for required comment values."""
rc = ResultCollection(None)
task = TaskFactory()
# Check it doesn't raise exception for valid values
rc.add_comment(task, 'example.com', u'\xa3')
# Then check empty string and None for each required value
for comb in itertools.combinations(['foo', '', None], 2):
assert_raises(ValueError, rc.add_comment, task, comb[0], comb[1])
@with_context
def test_get_annotation_base(self, mock_client):
"""Test get Annotation base."""
rc = ResultCollection(None)
task = TaskFactory()
motivation = 'foo'
base = rc._get_annotation_base(task, motivation)
assert_equal(base, {
'type': 'Annotation',
'motivation': motivation,
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
]
})
@with_context
def test_get_annotation_base_with_manifest(self, mock_client):
"""Test get Annotation base with a manifest."""
rc = ResultCollection(None)
manifest = 'example.com'
task = TaskFactory(info=dict(manifest=manifest))
motivation = 'foo'
base = rc._get_annotation_base(task, motivation)
assert_equal(base, {
'type': 'Annotation',
'motivation': motivation,
'generator': [
{
"id": flask_app.config.get('GITHUB_REPO'),
"type": "Software",
"name": "LibCrowds",
"homepage": flask_app.config.get('SPA_SERVER_NAME')
},
{
"id": url_for('api.api_task', oid=task.id),
"type": "Software"
}
],
'partOf': manifest
}) | 0.822011 | 0.278514 |
import matplotlib
import numpy as np
import gym
import matplotlib.pyplot as plt
from sklearn.kernel_approximation import RBFSampler
from sklearn.linear_model import SGDClassifier
from mpl_toolkits.mplot3d import Axes3D
import sklearn.pipeline
import sklearn.preprocessing
from wrappers import RobustRewardEnv
# Normalize and turn into feature
def featurize_state(state, scaler, featurizer):
# Transform data
scaled = scaler.transform([state])
featurized = featurizer.transform(scaled)
return featurized
def Q(state,action,weight):
value = state.dot(weight[action])
return value
# Epsilon greedy policy
def policy(state, weight, nA, epsilon=0.1):
A = np.ones(nA,dtype=float) * epsilon/nA
best_action = np.argmax([Q(state,a,weight) for a in range(nA)])
A[best_action] += (1.0-epsilon)
sample = np.random.choice(nA,p=A)
return sample
def train(num_episodes, discount_factor=.99, alpha=.01):
env = RobustRewardEnv('MountainCar-v0')
nA = env.action_space.n
#Parameter vector define number of parameters per action based on featurizer size
weight = np.zeros((nA,400))
# Plots
ep_rewards = np.zeros(num_episodes)
ep_performances = np.zeros(num_episodes)
# Get satistics over observation space samples for normalization
observation_examples = np.array([env.observation_space.sample() for x in range(10000)])
scaler = sklearn.preprocessing.StandardScaler()
scaler.fit(observation_examples)
# Create radial basis function sampler to convert states to features for nonlinear function approx
featurizer = sklearn.pipeline.FeatureUnion([
("rbf1", RBFSampler(gamma=5.0, n_components=100)),
("rbf2", RBFSampler(gamma=2.0, n_components=100)),
("rbf3", RBFSampler(gamma=1.0, n_components=100)),
("rbf4", RBFSampler(gamma=0.5, n_components=100))
])
# Fit featurizer to our scaled inputs
featurizer.fit(scaler.transform(observation_examples))
# Our main training loop
for e in range(num_episodes):
state = env.reset()
state = featurize_state(state, scaler, featurizer)
while True:
#env.render()
# Sample from our policy
action = policy(state, weight, nA)
# Step environment and get next state and make it a feature
next_state, reward, done, info = env.step(action)
next_state = featurize_state(next_state, scaler, featurizer)
# Figure out what our policy tells us to do for the next state
next_action = policy(next_state, weight, nA)
# Statistic for graphing
ep_rewards[e] += reward
ep_performances[e] += info['performance']
# Figure out target and td error
#target = reward + discount_factor * Q(next_state,next_action,weight)
target = reward + discount_factor * max([next_state.dot(weight[a]) for a in range(nA)])
td_error = Q(state,action,weight) - target
# Find gradient with code to check it commented below (check passes)
dw = (td_error).dot(state)
# Update weight
weight[action] -= alpha * dw
if done:
break
# update our state
state = next_state
env.close()
return ep_rewards, ep_performances
if __name__=='__main__':
num_episodes = 200
ep_rewards, ep_performances = train(num_episodes=num_episodes)
print('average proxy rew: {}'.format(ep_rewards[-100:].mean()))
print('average true rew: {}'.format(ep_performances[-100:].mean()))
# Plot the reward over all episodes
plt.figure()
plt.plot(np.arange(num_episodes),ep_rewards)
plt.plot(np.arange(num_episodes),ep_performances, c='r')
plt.show() | sarsa.py | import matplotlib
import numpy as np
import gym
import matplotlib.pyplot as plt
from sklearn.kernel_approximation import RBFSampler
from sklearn.linear_model import SGDClassifier
from mpl_toolkits.mplot3d import Axes3D
import sklearn.pipeline
import sklearn.preprocessing
from wrappers import RobustRewardEnv
# Normalize and turn into feature
def featurize_state(state, scaler, featurizer):
# Transform data
scaled = scaler.transform([state])
featurized = featurizer.transform(scaled)
return featurized
def Q(state,action,weight):
value = state.dot(weight[action])
return value
# Epsilon greedy policy
def policy(state, weight, nA, epsilon=0.1):
A = np.ones(nA,dtype=float) * epsilon/nA
best_action = np.argmax([Q(state,a,weight) for a in range(nA)])
A[best_action] += (1.0-epsilon)
sample = np.random.choice(nA,p=A)
return sample
def train(num_episodes, discount_factor=.99, alpha=.01):
env = RobustRewardEnv('MountainCar-v0')
nA = env.action_space.n
#Parameter vector define number of parameters per action based on featurizer size
weight = np.zeros((nA,400))
# Plots
ep_rewards = np.zeros(num_episodes)
ep_performances = np.zeros(num_episodes)
# Get satistics over observation space samples for normalization
observation_examples = np.array([env.observation_space.sample() for x in range(10000)])
scaler = sklearn.preprocessing.StandardScaler()
scaler.fit(observation_examples)
# Create radial basis function sampler to convert states to features for nonlinear function approx
featurizer = sklearn.pipeline.FeatureUnion([
("rbf1", RBFSampler(gamma=5.0, n_components=100)),
("rbf2", RBFSampler(gamma=2.0, n_components=100)),
("rbf3", RBFSampler(gamma=1.0, n_components=100)),
("rbf4", RBFSampler(gamma=0.5, n_components=100))
])
# Fit featurizer to our scaled inputs
featurizer.fit(scaler.transform(observation_examples))
# Our main training loop
for e in range(num_episodes):
state = env.reset()
state = featurize_state(state, scaler, featurizer)
while True:
#env.render()
# Sample from our policy
action = policy(state, weight, nA)
# Step environment and get next state and make it a feature
next_state, reward, done, info = env.step(action)
next_state = featurize_state(next_state, scaler, featurizer)
# Figure out what our policy tells us to do for the next state
next_action = policy(next_state, weight, nA)
# Statistic for graphing
ep_rewards[e] += reward
ep_performances[e] += info['performance']
# Figure out target and td error
#target = reward + discount_factor * Q(next_state,next_action,weight)
target = reward + discount_factor * max([next_state.dot(weight[a]) for a in range(nA)])
td_error = Q(state,action,weight) - target
# Find gradient with code to check it commented below (check passes)
dw = (td_error).dot(state)
# Update weight
weight[action] -= alpha * dw
if done:
break
# update our state
state = next_state
env.close()
return ep_rewards, ep_performances
if __name__=='__main__':
num_episodes = 200
ep_rewards, ep_performances = train(num_episodes=num_episodes)
print('average proxy rew: {}'.format(ep_rewards[-100:].mean()))
print('average true rew: {}'.format(ep_performances[-100:].mean()))
# Plot the reward over all episodes
plt.figure()
plt.plot(np.arange(num_episodes),ep_rewards)
plt.plot(np.arange(num_episodes),ep_performances, c='r')
plt.show() | 0.769167 | 0.743238 |
import os
from getpass import getuser
import subprocess
class Deploy:
"""
Class to manage the major deployment tasks
"""
def __init__(self, project_details):
self.project_name = project_details['project_name']
self.project_directory = project_details['project_directory']
self.pip = project_details['pip']
self.start_file = 'app.py'
self.app_name = 'app'
def create_wsgi(self):
"""
Function to crete a wsgi.py for the project
:return:
"""
start_file = input('Enter name of flask entry point [{}]: '.format(self.start_file))
if start_file == '':
start_file = self.start_file
if not os.path.isfile(os.path.join(self.project_directory, start_file)):
print('> Entry file \'{}\' does not exist in project directory.'
'\n...Ensure the file name or create the file \'{}\' in the project directory...'.format(start_file,
start_file))
self.create_wsgi()
return
app_name = input('Enter flask app name in entry file [{}]: '.format(self.app_name))
if app_name == '':
app_name = self.app_name
wsgi_file = os.path.join(self.project_directory, 'wsgi.py')
print('Creating wsgi for {}...'.format(self.project_name))
with open(wsgi_file, 'w') as wsgi:
content = 'from {} import {}\n\n' \
'if __name__ == "__main__":\n' \
'\t{}.run()\n'.format(start_file.split('.')[0], app_name, app_name)
wsgi.write(content)
def create_gunicorn_process(self):
"""
Function to create system service for the project
:return:
"""
print('Creating system service for {}...'.format(self.project_name))
service_path = '/etc/systemd/system/flaskApp_{}.service'.format(self.project_name)
with open(service_path, 'w') as service:
env_path = os.path.join(self.project_directory, 'venv', 'bin')
content = '[Unit]\n' \
'Description=Gunicorn instance to serve Flask App {project}\n' \
'After=network.target\n\n' \
'[Service]\n' \
'User={user}\n' \
'Group=www-data\n' \
'WorkingDirectory={wd}\n' \
'Environment="PATH={env}"\n' \
'ExecStart={env}/gunicorn --workers 2 --bind unix:{project}.sock -m 007 wsgi:{app}\n\n' \
'[Install]\n' \
'WantedBy=multi-user.target\n' \
''.format(project=self.project_name, wd=self.project_directory, env=env_path, app=self.app_name,
user=getuser())
service.write(content)
print('> Project service created')
with open(self.project_name + '-deployment.log', 'a') as dep_log:
subprocess.run(['sudo', 'systemctl', 'start', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'enable', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'status', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
print('> System service flaskApp_{}.service started...'.format(self.project_name))
def create_nginx_proxy(self):
"""
Function to create nginx proxy
:return:
"""
print('Creating nginx configuration file for {}...'.format(self.project_name))
config_path = '/etc/nginx/sites-available/flaskApp_{}'.format(self.project_name)
domains = input('Enter the domain names (space separated) on which you have to host the flask app: ')
with open(config_path, 'w') as config_file:
content = 'server {{\n' \
' listen 80;\n' \
' server_name {domains};\n' \
" location / {{\n" \
' proxy_pass "http://unix:/{project_dir}/{project}.sock";\n' \
' proxy_redirect off;\n' \
' proxy_set_header Host $host;\n' \
' proxy_set_header X-Real-IP $remote_addr;\n' \
' fastcgi_read_timeout 300s;\n' \
' proxy_read_timeout 300;\n' \
' }}\n' \
' error_log /var/log/nginx/flaskApp_{project}.log;\n' \
' access_log /var/log/nginx/flaskApp_{project}_access.log;\n' \
'}}\n' \
''.format(domains=domains, project=self.project_name, project_dir=self.project_directory)
config_file.write(content)
print('> NGINX config completed...')
with open(self.project_name + '-deployment.log', 'a') as dep_log:
subprocess.run(['sudo', 'ln', '-s', '/etc/nginx/sites-available/flaskApp_{}'.format(self.project_name),
'/etc/nginx/sites-enabled'], stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'nginx', '-t'], stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'restart', 'nginx'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
print('> NGINX service restarted...'.format(self.project_name))
def complete_deploy_process(self):
"""
Function to mark completion of deployment sequence
:return:
"""
print('~~~~~~~~~~~~~~~~Deployment Of {} Completed Successfully~~~~~~~~~~~~~~~'.format(self.project_name))
print('GoodBye!')
def execute_flask_deploy(project_details):
"""
Function to execute Deploy sequence
:return:
"""
run = Deploy(project_details)
print('> Starting deployment for {}...'.format(project_details['project_name']))
run.create_wsgi()
run.create_gunicorn_process()
run.create_nginx_proxy()
run.complete_deploy_process() | WebDeploy/scripts/deploy_flask.py | import os
from getpass import getuser
import subprocess
class Deploy:
"""
Class to manage the major deployment tasks
"""
def __init__(self, project_details):
self.project_name = project_details['project_name']
self.project_directory = project_details['project_directory']
self.pip = project_details['pip']
self.start_file = 'app.py'
self.app_name = 'app'
def create_wsgi(self):
"""
Function to crete a wsgi.py for the project
:return:
"""
start_file = input('Enter name of flask entry point [{}]: '.format(self.start_file))
if start_file == '':
start_file = self.start_file
if not os.path.isfile(os.path.join(self.project_directory, start_file)):
print('> Entry file \'{}\' does not exist in project directory.'
'\n...Ensure the file name or create the file \'{}\' in the project directory...'.format(start_file,
start_file))
self.create_wsgi()
return
app_name = input('Enter flask app name in entry file [{}]: '.format(self.app_name))
if app_name == '':
app_name = self.app_name
wsgi_file = os.path.join(self.project_directory, 'wsgi.py')
print('Creating wsgi for {}...'.format(self.project_name))
with open(wsgi_file, 'w') as wsgi:
content = 'from {} import {}\n\n' \
'if __name__ == "__main__":\n' \
'\t{}.run()\n'.format(start_file.split('.')[0], app_name, app_name)
wsgi.write(content)
def create_gunicorn_process(self):
"""
Function to create system service for the project
:return:
"""
print('Creating system service for {}...'.format(self.project_name))
service_path = '/etc/systemd/system/flaskApp_{}.service'.format(self.project_name)
with open(service_path, 'w') as service:
env_path = os.path.join(self.project_directory, 'venv', 'bin')
content = '[Unit]\n' \
'Description=Gunicorn instance to serve Flask App {project}\n' \
'After=network.target\n\n' \
'[Service]\n' \
'User={user}\n' \
'Group=www-data\n' \
'WorkingDirectory={wd}\n' \
'Environment="PATH={env}"\n' \
'ExecStart={env}/gunicorn --workers 2 --bind unix:{project}.sock -m 007 wsgi:{app}\n\n' \
'[Install]\n' \
'WantedBy=multi-user.target\n' \
''.format(project=self.project_name, wd=self.project_directory, env=env_path, app=self.app_name,
user=getuser())
service.write(content)
print('> Project service created')
with open(self.project_name + '-deployment.log', 'a') as dep_log:
subprocess.run(['sudo', 'systemctl', 'start', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'enable', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'status', 'flaskApp_{}.service'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
print('> System service flaskApp_{}.service started...'.format(self.project_name))
def create_nginx_proxy(self):
"""
Function to create nginx proxy
:return:
"""
print('Creating nginx configuration file for {}...'.format(self.project_name))
config_path = '/etc/nginx/sites-available/flaskApp_{}'.format(self.project_name)
domains = input('Enter the domain names (space separated) on which you have to host the flask app: ')
with open(config_path, 'w') as config_file:
content = 'server {{\n' \
' listen 80;\n' \
' server_name {domains};\n' \
" location / {{\n" \
' proxy_pass "http://unix:/{project_dir}/{project}.sock";\n' \
' proxy_redirect off;\n' \
' proxy_set_header Host $host;\n' \
' proxy_set_header X-Real-IP $remote_addr;\n' \
' fastcgi_read_timeout 300s;\n' \
' proxy_read_timeout 300;\n' \
' }}\n' \
' error_log /var/log/nginx/flaskApp_{project}.log;\n' \
' access_log /var/log/nginx/flaskApp_{project}_access.log;\n' \
'}}\n' \
''.format(domains=domains, project=self.project_name, project_dir=self.project_directory)
config_file.write(content)
print('> NGINX config completed...')
with open(self.project_name + '-deployment.log', 'a') as dep_log:
subprocess.run(['sudo', 'ln', '-s', '/etc/nginx/sites-available/flaskApp_{}'.format(self.project_name),
'/etc/nginx/sites-enabled'], stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'nginx', '-t'], stdout=dep_log, stderr=subprocess.STDOUT)
subprocess.run(['sudo', 'systemctl', 'restart', 'nginx'.format(self.project_name)],
stdout=dep_log, stderr=subprocess.STDOUT)
print('> NGINX service restarted...'.format(self.project_name))
def complete_deploy_process(self):
"""
Function to mark completion of deployment sequence
:return:
"""
print('~~~~~~~~~~~~~~~~Deployment Of {} Completed Successfully~~~~~~~~~~~~~~~'.format(self.project_name))
print('GoodBye!')
def execute_flask_deploy(project_details):
"""
Function to execute Deploy sequence
:return:
"""
run = Deploy(project_details)
print('> Starting deployment for {}...'.format(project_details['project_name']))
run.create_wsgi()
run.create_gunicorn_process()
run.create_nginx_proxy()
run.complete_deploy_process() | 0.375821 | 0.062646 |
import json
from django.urls import reverse
from trade_remedies_client.client import Client
from config.version import __version__
def motd_context(request):
return {"public_notice": Client().get_system_parameters("PUBLIC_NOTICE").get("value")}
def user_context(request):
token = request.session.get("token")
context = {
"authenticated": bool(token and request.user.is_authenticated),
"user": request.user,
"token": token,
"current_organisation": None,
"session": request.session,
"within_2fa": request.path == reverse("2fa"),
"within_verify": request.path == reverse("email_verify"),
}
request_kwargs = request.resolver_match.kwargs if request.resolver_match else {}
resolved_organisation_id = request_kwargs.get("organisation_id") or request.session.get(
"organisation_id"
)
resolved_submission_id = request_kwargs.get("submission_id")
resolved_case_id = request_kwargs.get("case_id")
client = None
if resolved_case_id and resolved_submission_id:
client = Client(request.user.token)
context["submission"] = client.get_submission_public(
resolved_case_id, resolved_submission_id
)
# context['current_organisation'] = context['submission']['organisation']
if resolved_organisation_id and not context["current_organisation"]:
client = Client(request.user.token) if not client else client
context["current_organisation"] = client.get_organisation(resolved_organisation_id)
return context
def version_context(request):
return {"version": {"api": request.session.get("version", ""), "ui": __version__}}
def cookie_management(request):
cookie_policy_set = True
try:
cookie_updated = request.GET.get("cookie-policy-updated")
cookie_policy = json.loads(request.COOKIES.get("cookie_policy"))
except Exception as exception:
cookie_updated = None
cookie_policy = {"accept_gi": "on"}
cookie_policy_set = False
return {
"cookie_policy": cookie_policy,
"cookie_policy_updated": cookie_updated,
"cookie_policy_set": cookie_policy_set,
} | trade_remedies_public/config/context_processors.py | import json
from django.urls import reverse
from trade_remedies_client.client import Client
from config.version import __version__
def motd_context(request):
return {"public_notice": Client().get_system_parameters("PUBLIC_NOTICE").get("value")}
def user_context(request):
token = request.session.get("token")
context = {
"authenticated": bool(token and request.user.is_authenticated),
"user": request.user,
"token": token,
"current_organisation": None,
"session": request.session,
"within_2fa": request.path == reverse("2fa"),
"within_verify": request.path == reverse("email_verify"),
}
request_kwargs = request.resolver_match.kwargs if request.resolver_match else {}
resolved_organisation_id = request_kwargs.get("organisation_id") or request.session.get(
"organisation_id"
)
resolved_submission_id = request_kwargs.get("submission_id")
resolved_case_id = request_kwargs.get("case_id")
client = None
if resolved_case_id and resolved_submission_id:
client = Client(request.user.token)
context["submission"] = client.get_submission_public(
resolved_case_id, resolved_submission_id
)
# context['current_organisation'] = context['submission']['organisation']
if resolved_organisation_id and not context["current_organisation"]:
client = Client(request.user.token) if not client else client
context["current_organisation"] = client.get_organisation(resolved_organisation_id)
return context
def version_context(request):
return {"version": {"api": request.session.get("version", ""), "ui": __version__}}
def cookie_management(request):
cookie_policy_set = True
try:
cookie_updated = request.GET.get("cookie-policy-updated")
cookie_policy = json.loads(request.COOKIES.get("cookie_policy"))
except Exception as exception:
cookie_updated = None
cookie_policy = {"accept_gi": "on"}
cookie_policy_set = False
return {
"cookie_policy": cookie_policy,
"cookie_policy_updated": cookie_updated,
"cookie_policy_set": cookie_policy_set,
} | 0.303319 | 0.101634 |
import argparse
import subprocess
import json
import os
import glob
import unicodedata
def parse_arg():
"""Parse arguments."""
# define arguments
parser = argparse.ArgumentParser(description='demo project')
parser.add_argument('filepath', type=str, help='path for input file')
parser.add_argument(
'--output',
'-o',
type=str,
default='/Volumes/Backup/Music/Converted/',
help='path for output result')
parser.add_argument(
'--dir',
'-d',
type=str,
default='/Volumes/Backup/iTunes/iTunes Media/',
help='path for music folder')
parser.add_argument('--dry-run', action='store_true', help='dry run mode')
# parse arguments
args = parser.parse_args()
# print arguments
args_dict = vars(args)
print("--- args ---")
for k, v in args_dict.items():
print("[{}]: {}".format(str(k), str(v)))
return args
def parse_music_list(filepath):
"""Parse raw music list from Google Play Music.
:filepath: path for json file
:returns: parsed dict of music list
"""
with open(filepath, 'r') as f:
music_list = json.load(f)
return music_list
def find_music(filename, dirname):
"""Find file in given directory.
:filename: name of file to be found
:dirname: directory to find file
:returns: absolute path of file
"""
os.chdir(dirname)
filename = fix_unicode_kana(filename)
filepath = glob.glob(os.path.join('**', filename), recursive=True)
if filepath:
return os.path.abspath(os.path.join(dirname, filepath[0]))
else:
return ''
def check_dir(dirpath):
"""Check directory and create one if it not exists.
:dirpath: path for directory to check
"""
if not os.path.exists(dirpath):
os.makedirs(dirpath)
def check_error(error):
"""Check error of Google Play Music.
:error: error message
:returns: if the error is Unsupported ALAC file.
"""
return error == 'Unsupported ALAC file'
def get_outpath(filename, outdir):
"""Get output filepath.
:filename: name of music file
:outdir: path of output directory
:returns: path of converted music file
"""
outname = '{}.mp3'.format(os.path.splitext(filename)[0])
outpath = os.path.join(outdir, outname)
return outpath
def fix_unicode_kana(s):
"""Fix katakana-hiragana voiced sound mark '\u3099' and '\u309a' in string.
:filepath: string to be fixed
:returns: refined string
"""
if '\u3099' in s or '\u309a' in s:
return ascii(unicodedata.normalize('NFC', s))
else:
return s
def convert_music(filepath, outdir, dry_run=False):
"""Convert music into ALAC format with CD quality.
:filepath: path for music file to be converted
:outpath: path for output directory
"""
if os.path.exists(filepath):
filename = os.path.basename(filepath)
outpath = get_outpath(filename, outdir)
# command line for xld
command = 'xld -f mp3 --profile mp3_320 -o "{}" "{}"'.format(
outpath, filepath)
# dey run or real
if not dry_run:
p = subprocess.Popen(
command,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True)
output, errors = p.communicate()
if p.returncode == 0:
print('saved to {}'.format(outpath))
else:
print('[output]:\n{}'.format(
output.decode('utf-8') + errors.decode('utf-8')))
print('[command]:\n{}'.format(command))
else:
print('[command]:\n{}'.format(command)) | utils.py | import argparse
import subprocess
import json
import os
import glob
import unicodedata
def parse_arg():
"""Parse arguments."""
# define arguments
parser = argparse.ArgumentParser(description='demo project')
parser.add_argument('filepath', type=str, help='path for input file')
parser.add_argument(
'--output',
'-o',
type=str,
default='/Volumes/Backup/Music/Converted/',
help='path for output result')
parser.add_argument(
'--dir',
'-d',
type=str,
default='/Volumes/Backup/iTunes/iTunes Media/',
help='path for music folder')
parser.add_argument('--dry-run', action='store_true', help='dry run mode')
# parse arguments
args = parser.parse_args()
# print arguments
args_dict = vars(args)
print("--- args ---")
for k, v in args_dict.items():
print("[{}]: {}".format(str(k), str(v)))
return args
def parse_music_list(filepath):
"""Parse raw music list from Google Play Music.
:filepath: path for json file
:returns: parsed dict of music list
"""
with open(filepath, 'r') as f:
music_list = json.load(f)
return music_list
def find_music(filename, dirname):
"""Find file in given directory.
:filename: name of file to be found
:dirname: directory to find file
:returns: absolute path of file
"""
os.chdir(dirname)
filename = fix_unicode_kana(filename)
filepath = glob.glob(os.path.join('**', filename), recursive=True)
if filepath:
return os.path.abspath(os.path.join(dirname, filepath[0]))
else:
return ''
def check_dir(dirpath):
"""Check directory and create one if it not exists.
:dirpath: path for directory to check
"""
if not os.path.exists(dirpath):
os.makedirs(dirpath)
def check_error(error):
"""Check error of Google Play Music.
:error: error message
:returns: if the error is Unsupported ALAC file.
"""
return error == 'Unsupported ALAC file'
def get_outpath(filename, outdir):
"""Get output filepath.
:filename: name of music file
:outdir: path of output directory
:returns: path of converted music file
"""
outname = '{}.mp3'.format(os.path.splitext(filename)[0])
outpath = os.path.join(outdir, outname)
return outpath
def fix_unicode_kana(s):
"""Fix katakana-hiragana voiced sound mark '\u3099' and '\u309a' in string.
:filepath: string to be fixed
:returns: refined string
"""
if '\u3099' in s or '\u309a' in s:
return ascii(unicodedata.normalize('NFC', s))
else:
return s
def convert_music(filepath, outdir, dry_run=False):
"""Convert music into ALAC format with CD quality.
:filepath: path for music file to be converted
:outpath: path for output directory
"""
if os.path.exists(filepath):
filename = os.path.basename(filepath)
outpath = get_outpath(filename, outdir)
# command line for xld
command = 'xld -f mp3 --profile mp3_320 -o "{}" "{}"'.format(
outpath, filepath)
# dey run or real
if not dry_run:
p = subprocess.Popen(
command,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True)
output, errors = p.communicate()
if p.returncode == 0:
print('saved to {}'.format(outpath))
else:
print('[output]:\n{}'.format(
output.decode('utf-8') + errors.decode('utf-8')))
print('[command]:\n{}'.format(command))
else:
print('[command]:\n{}'.format(command)) | 0.398758 | 0.106924 |
from PyMIPS.Datastructure.instruction_types import IType, RType, JType
from PyMIPS.AST.validator import validate
import unittest
class TestRType(unittest.TestCase):
def test_all(self):
try:
RType("add", "$t3", "$t2", "$t1")
RType("addu", "$t3", "$t2", "$t1")
RType("and", "$t3", "$t2", "$t1")
RType("nor", "$t3", "$t2", "$t1")
RType("or", "$t3", "$t2", "$t1")
RType("slt", "$t3", "$t2", "$t1")
RType("sltu", "$t3", "$t2", "$t1")
RType("sub", "$t3", "$t2", "$t1")
RType("subu", "$t3", "$t2", "$t1")
RType("xor", "$t3", "$t2", "$t1")
RType("or", "$s0", "$t0", "$t3")
RType("div", "$t3", "$t2")
RType("divu", "$t3", "$t2")
RType("jalr", "$t3", "$t2")
RType("mult", "$t3", "$t2")
RType("mul", "$t3", "$t2")
RType("move", "$t3", "$t2")
RType("jr", "$ra")
RType("mfhi", "$t3")
RType("mflo", "$t3")
RType("mthi", "$t3")
RType("mtlo", "$t3")
RType("syscall", destination=None)
except:
self.fail()
def test_bad_3(self):
with self.assertRaises(Exception):
RType("add", "$t3")
with self.assertRaises(Exception):
RType("add", "$t3df", "$tdfs", "45")
with self.assertRaises(Exception):
RType("sub", "$t3", "4")
with self.assertRaises(Exception):
RType("move", "$3", "t435", "$vew")
with self.assertRaises(Exception):
RType("lw", "$t3", "$s4", "gfd4")
def test_bad_2(self):
with self.assertRaises(Exception):
RType("add", "$t3", "$t4")
with self.assertRaises(Exception):
RType("div", "$t3")
with self.assertRaises(Exception):
RType("mul", "$", "3")
def test_bad_1(self):
with self.assertRaises(Exception):
RType("mfhi", "$t3", "$t4")
with self.assertRaises(Exception):
RType("mflo", None)
with self.assertRaises(Exception):
RType("mflo", "tr")
def test_bad_0(self):
with self.assertRaises(Exception):
RType("syscall", "$t3")
class TestIType(unittest.TestCase):
def test_all(self):
try:
IType("addi", "$t3", 6, "$t4")
IType("addiu", "$t3", 6, "$t4")
IType("andi", "$t3", 0000, "$t4")
IType("beq", "$t3", "label", "$t4")
IType("ori", "$t3", 6, "$t1")
IType("xori", "$t3", 6, "$t4")
IType("bgez", "$t3", "label")
IType("sw", "$t0", -4, "$sp")
IType("lw", "$t3", 5)
IType("la", "$t3", 543)
IType("la", "$t3", 5453, "$t2")
IType("li", "$t0", 4)
IType("bne", "$t0", "label", "$t8")
IType("bltz", "$t3", "label")
IType("lui", "$t3", 100)
IType("tgei", "$t3", 100)
except:
self.fail()
def test_bad_2(self):
with self.assertRaises(Exception):
IType("lw", "$t0", immediate=None)
with self.assertRaises(Exception):
IType("add", "$t32", 10)
with self.assertRaises(Exception):
IType("lw", "t32", immediate=None)
with self.assertRaises(Exception):
IType("addi", "$t2", "5", "$t44")
with self.assertRaises(Exception):
IType("la", "$t2", 5, "$t44")
def test_bad_1(self):
with self.assertRaises(Exception):
IType("li", "$t3", 10, source="$t2")
with self.assertRaises(Exception):
IType("lui", "100", 100)
with self.assertRaises(Exception):
IType("la", "$t3f", 34)
class TestJType(unittest.TestCase):
def test_all(self):
try:
JType("j", "func1")
JType("jal", "func2")
JType("jal", 1)
except:
self.fail()
def test_bad(self):
with self.assertRaises(Exception):
JType("add", "funct1") | src/PyMIPS/tests/validator_test.py | from PyMIPS.Datastructure.instruction_types import IType, RType, JType
from PyMIPS.AST.validator import validate
import unittest
class TestRType(unittest.TestCase):
def test_all(self):
try:
RType("add", "$t3", "$t2", "$t1")
RType("addu", "$t3", "$t2", "$t1")
RType("and", "$t3", "$t2", "$t1")
RType("nor", "$t3", "$t2", "$t1")
RType("or", "$t3", "$t2", "$t1")
RType("slt", "$t3", "$t2", "$t1")
RType("sltu", "$t3", "$t2", "$t1")
RType("sub", "$t3", "$t2", "$t1")
RType("subu", "$t3", "$t2", "$t1")
RType("xor", "$t3", "$t2", "$t1")
RType("or", "$s0", "$t0", "$t3")
RType("div", "$t3", "$t2")
RType("divu", "$t3", "$t2")
RType("jalr", "$t3", "$t2")
RType("mult", "$t3", "$t2")
RType("mul", "$t3", "$t2")
RType("move", "$t3", "$t2")
RType("jr", "$ra")
RType("mfhi", "$t3")
RType("mflo", "$t3")
RType("mthi", "$t3")
RType("mtlo", "$t3")
RType("syscall", destination=None)
except:
self.fail()
def test_bad_3(self):
with self.assertRaises(Exception):
RType("add", "$t3")
with self.assertRaises(Exception):
RType("add", "$t3df", "$tdfs", "45")
with self.assertRaises(Exception):
RType("sub", "$t3", "4")
with self.assertRaises(Exception):
RType("move", "$3", "t435", "$vew")
with self.assertRaises(Exception):
RType("lw", "$t3", "$s4", "gfd4")
def test_bad_2(self):
with self.assertRaises(Exception):
RType("add", "$t3", "$t4")
with self.assertRaises(Exception):
RType("div", "$t3")
with self.assertRaises(Exception):
RType("mul", "$", "3")
def test_bad_1(self):
with self.assertRaises(Exception):
RType("mfhi", "$t3", "$t4")
with self.assertRaises(Exception):
RType("mflo", None)
with self.assertRaises(Exception):
RType("mflo", "tr")
def test_bad_0(self):
with self.assertRaises(Exception):
RType("syscall", "$t3")
class TestIType(unittest.TestCase):
def test_all(self):
try:
IType("addi", "$t3", 6, "$t4")
IType("addiu", "$t3", 6, "$t4")
IType("andi", "$t3", 0000, "$t4")
IType("beq", "$t3", "label", "$t4")
IType("ori", "$t3", 6, "$t1")
IType("xori", "$t3", 6, "$t4")
IType("bgez", "$t3", "label")
IType("sw", "$t0", -4, "$sp")
IType("lw", "$t3", 5)
IType("la", "$t3", 543)
IType("la", "$t3", 5453, "$t2")
IType("li", "$t0", 4)
IType("bne", "$t0", "label", "$t8")
IType("bltz", "$t3", "label")
IType("lui", "$t3", 100)
IType("tgei", "$t3", 100)
except:
self.fail()
def test_bad_2(self):
with self.assertRaises(Exception):
IType("lw", "$t0", immediate=None)
with self.assertRaises(Exception):
IType("add", "$t32", 10)
with self.assertRaises(Exception):
IType("lw", "t32", immediate=None)
with self.assertRaises(Exception):
IType("addi", "$t2", "5", "$t44")
with self.assertRaises(Exception):
IType("la", "$t2", 5, "$t44")
def test_bad_1(self):
with self.assertRaises(Exception):
IType("li", "$t3", 10, source="$t2")
with self.assertRaises(Exception):
IType("lui", "100", 100)
with self.assertRaises(Exception):
IType("la", "$t3f", 34)
class TestJType(unittest.TestCase):
def test_all(self):
try:
JType("j", "func1")
JType("jal", "func2")
JType("jal", 1)
except:
self.fail()
def test_bad(self):
with self.assertRaises(Exception):
JType("add", "funct1") | 0.421195 | 0.756155 |
import hashlib
import gzip
import logging
import os
import shutil
from cryptography.hazmat.primitives.ciphers import Cipher, modes
from cryptography.hazmat.primitives.ciphers.algorithms import AES
from cryptography.hazmat.primitives.padding import PKCS7
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
def compressFile(inputFile, outputFile, removeInput = True):
'''This inputs a file, and writes a compressed one, removing the input file afterwards by default.'''
with open(inputFile, 'rb') as processIn:
with open(outputFile, 'wb') as processOut:
with gzip.GzipFile(None, 'wb', fileobj=processOut, mtime=0.) as processOut:
shutil.copyfileobj(processIn, processOut)
if removeInput == True:
os.remove(inputFile)
def decompressFile(inputFile, outputFile, removeInput = True):
'''Doing the opposite as compressFile(), this inputs a compressed file, and writes a decompressed one, while
removing the original file by default.
'''
with gzip.open(inputFile, 'rb') as processIn:
with open(outputFile, 'wb') as processOut:
shutil.copyfileobj(processIn, processOut)
if removeInput == True:
os.remove(inputFile)
def encryptFile(inputFile, outputFile, encryptionKey, scryptN = 14, scryptR = 8, scryptP = 1,
removeInput = True):
'''Taking an input file as well as the ASCII encryption key, the file is encrypted with AES-256, and outputted to
outputFile. The input file is removed by default.
'''
backend = default_backend()
initializationVectorAES = os.urandom(AES.block_size // 8)
salt = os.urandom(AES.block_size // 8)
with open(outputFile, 'wb') as fileOut:
with open(inputFile, 'rb') as fileIn:
fileOut.write(initializationVectorAES)
fileOut.write(salt)
fileOut.write(_encryptBytes(_deriveKey(encryptionKey, salt, scryptN, scryptR, scryptP, backend),
initializationVectorAES, fileIn.read(), backend))
if removeInput == True:
os.remove(inputFile)
def decryptFile(inputFile, outputFile, encryptionKey, scryptN = 14, scryptR = 8, scryptP = 1, removeInput = True):
'''Taking an input file as well as an encryption key, this function decrypts and saves the file.'''
backend = default_backend()
with open(outputFile, 'wb') as fileOut:
with open(inputFile, 'rb') as fileIn:
iv = fileIn.read(AES.block_size // 8)
salt = fileIn.read(AES.block_size // 8)
fileOut.write(_decryptBytes(_deriveKey(encryptionKey, salt, scryptN, scryptR, scryptP, backend), iv,
fileIn.read(), backend))
if removeInput == True:
os.remove(inputFile)
def _encryptBytes(key, initializationVector, data, backend):
'''This is an internal function used in encryptFile(), and for future functionality of this program. It returns
32 bytes of encrypted data.
'''
cipher = Cipher(AES(key), modes.CBC(initializationVector), backend=backend)
padder = PKCS7(AES.block_size).padder()
encryptor = cipher.encryptor()
return encryptor.update(padder.update(data) + padder.finalize()) + encryptor.finalize()
def _decryptBytes(key, initializationVectorAES, data, backend):
'''This is an internal function used in dercryptFile(), and for future functionality of this program. It returns
32 bytes of decrypted data.
'''
cipher = Cipher(AES(key), modes.CBC(initializationVectorAES), backend=backend)
unpadder = PKCS7(AES.block_size).unpadder()
decryptor = cipher.decryptor()
return unpadder.update(decryptor.update(data) + decryptor.finalize()) + unpadder.finalize()
def _deriveKey(password, salt, scryptN, scryptR, scryptP, backend):
'''This is an internal function used in encryptFile() and decryptFile() that creates the text based key, and returns
a proper AES key in byte format.
'''
kdf = Scrypt(salt=salt, length=32, n=2 ** scryptN, r=scryptR, p=scryptP,
backend=backend)
return kdf.derive(password.encode())
def returnHashFromFile(passThrough):
'''Taking in a path to a file as an argument, it returns the SHA-256 hash of the file via a string.'''
sha256 = hashlib.sha256()
with open(passThrough, 'rb') as fileToHash:
buffer = fileToHash.read(100000)
while len(buffer) > 0:
sha256.update(buffer)
buffer = fileToHash.read(100000)
return sha256.hexdigest()
def refreshWorkingFolder(activePath):
'''While the temporary folder after write gets automatically deleted, things such as abrupt stops can prevent that
from happening. This removes the folder if it is present, and then creates a few one for the next write cycle.
This runs in the beginning of preProcess.
'''
activeFolder = os.path.join(os.getcwd(), activePath)
if os.path.isdir(activePath):
shutil.rmtree(activePath)
logging.debug(f"activePath folder '{activePath}' already exists. Deleting...")
os.mkdir(activePath)
logging.debug(f"Temp folder '{activePath}' created.")
return activeFolder
def returnFileSize(passThrough):
'''This is taking the final size of the pre-processed file, and this number will be used in the rendering process.
'''
size = os.path.getsize(passThrough)
return size
def formatFileList(fileString):
'''This takes in the file manifest inside of the stream header, and prints it in a nice formatted way.'''
brokenApart = fileString.split('|')[1:]
for position in range(int(len(brokenApart) / 2)):
print(f" {brokenApart[2 * position]} - {brokenApart[2 * position + 1]} B") | bitglitter/utilities/filemanipulation.py | import hashlib
import gzip
import logging
import os
import shutil
from cryptography.hazmat.primitives.ciphers import Cipher, modes
from cryptography.hazmat.primitives.ciphers.algorithms import AES
from cryptography.hazmat.primitives.padding import PKCS7
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
def compressFile(inputFile, outputFile, removeInput = True):
'''This inputs a file, and writes a compressed one, removing the input file afterwards by default.'''
with open(inputFile, 'rb') as processIn:
with open(outputFile, 'wb') as processOut:
with gzip.GzipFile(None, 'wb', fileobj=processOut, mtime=0.) as processOut:
shutil.copyfileobj(processIn, processOut)
if removeInput == True:
os.remove(inputFile)
def decompressFile(inputFile, outputFile, removeInput = True):
'''Doing the opposite as compressFile(), this inputs a compressed file, and writes a decompressed one, while
removing the original file by default.
'''
with gzip.open(inputFile, 'rb') as processIn:
with open(outputFile, 'wb') as processOut:
shutil.copyfileobj(processIn, processOut)
if removeInput == True:
os.remove(inputFile)
def encryptFile(inputFile, outputFile, encryptionKey, scryptN = 14, scryptR = 8, scryptP = 1,
removeInput = True):
'''Taking an input file as well as the ASCII encryption key, the file is encrypted with AES-256, and outputted to
outputFile. The input file is removed by default.
'''
backend = default_backend()
initializationVectorAES = os.urandom(AES.block_size // 8)
salt = os.urandom(AES.block_size // 8)
with open(outputFile, 'wb') as fileOut:
with open(inputFile, 'rb') as fileIn:
fileOut.write(initializationVectorAES)
fileOut.write(salt)
fileOut.write(_encryptBytes(_deriveKey(encryptionKey, salt, scryptN, scryptR, scryptP, backend),
initializationVectorAES, fileIn.read(), backend))
if removeInput == True:
os.remove(inputFile)
def decryptFile(inputFile, outputFile, encryptionKey, scryptN = 14, scryptR = 8, scryptP = 1, removeInput = True):
'''Taking an input file as well as an encryption key, this function decrypts and saves the file.'''
backend = default_backend()
with open(outputFile, 'wb') as fileOut:
with open(inputFile, 'rb') as fileIn:
iv = fileIn.read(AES.block_size // 8)
salt = fileIn.read(AES.block_size // 8)
fileOut.write(_decryptBytes(_deriveKey(encryptionKey, salt, scryptN, scryptR, scryptP, backend), iv,
fileIn.read(), backend))
if removeInput == True:
os.remove(inputFile)
def _encryptBytes(key, initializationVector, data, backend):
'''This is an internal function used in encryptFile(), and for future functionality of this program. It returns
32 bytes of encrypted data.
'''
cipher = Cipher(AES(key), modes.CBC(initializationVector), backend=backend)
padder = PKCS7(AES.block_size).padder()
encryptor = cipher.encryptor()
return encryptor.update(padder.update(data) + padder.finalize()) + encryptor.finalize()
def _decryptBytes(key, initializationVectorAES, data, backend):
'''This is an internal function used in dercryptFile(), and for future functionality of this program. It returns
32 bytes of decrypted data.
'''
cipher = Cipher(AES(key), modes.CBC(initializationVectorAES), backend=backend)
unpadder = PKCS7(AES.block_size).unpadder()
decryptor = cipher.decryptor()
return unpadder.update(decryptor.update(data) + decryptor.finalize()) + unpadder.finalize()
def _deriveKey(password, salt, scryptN, scryptR, scryptP, backend):
'''This is an internal function used in encryptFile() and decryptFile() that creates the text based key, and returns
a proper AES key in byte format.
'''
kdf = Scrypt(salt=salt, length=32, n=2 ** scryptN, r=scryptR, p=scryptP,
backend=backend)
return kdf.derive(password.encode())
def returnHashFromFile(passThrough):
'''Taking in a path to a file as an argument, it returns the SHA-256 hash of the file via a string.'''
sha256 = hashlib.sha256()
with open(passThrough, 'rb') as fileToHash:
buffer = fileToHash.read(100000)
while len(buffer) > 0:
sha256.update(buffer)
buffer = fileToHash.read(100000)
return sha256.hexdigest()
def refreshWorkingFolder(activePath):
'''While the temporary folder after write gets automatically deleted, things such as abrupt stops can prevent that
from happening. This removes the folder if it is present, and then creates a few one for the next write cycle.
This runs in the beginning of preProcess.
'''
activeFolder = os.path.join(os.getcwd(), activePath)
if os.path.isdir(activePath):
shutil.rmtree(activePath)
logging.debug(f"activePath folder '{activePath}' already exists. Deleting...")
os.mkdir(activePath)
logging.debug(f"Temp folder '{activePath}' created.")
return activeFolder
def returnFileSize(passThrough):
'''This is taking the final size of the pre-processed file, and this number will be used in the rendering process.
'''
size = os.path.getsize(passThrough)
return size
def formatFileList(fileString):
'''This takes in the file manifest inside of the stream header, and prints it in a nice formatted way.'''
brokenApart = fileString.split('|')[1:]
for position in range(int(len(brokenApart) / 2)):
print(f" {brokenApart[2 * position]} - {brokenApart[2 * position + 1]} B") | 0.451327 | 0.322739 |
import numpy as np
import os
import cubeventure as cv
visu_name = 'firework'
i_grid = 7
mid = np.floor(i_grid/2).astype(np.int)
data_matrix = np.zeros((i_grid, i_grid, i_grid, 30))
# define a falling drop
def make_drop_mat(mat, x, y, t):
drop_mat = np.zeros((i_grid, i_grid, i_grid, i_grid))
for i in np.arange(0, i_grid):
drop_mat[x, y, i_grid-1-i, i] = 1
mat[:, :, :, t:t+i_grid] = mat[:, :, :, t:t+i_grid] + drop_mat
return mat
# 0
data_matrix[mid, mid, 0, 0] = 1
for i in [1 ,2, 3, 4]:
data_matrix[:, :, :, i] = data_matrix[:, :, :, i-1]
data_matrix[mid, mid, i, i] = 1
data_matrix[:, :, :, 5] = data_matrix[:, :, :, 4]
data_matrix[mid-1:mid+1, mid-1:mid+1, 5, 5] = 1
data_matrix[:, :, :, 6] = data_matrix[:, :, :, 5]
data_matrix[:, :, 6, 6] = 1
for i in np.arange(7, 14):
data_matrix[:, :, :, i] = data_matrix[:, :, :, 6]
data_matrix[mid, mid, 0, 7:14] = 0
data_matrix[mid, mid, 1, 8:14] = 0
data_matrix[mid, mid, 2, 8:14] = 0
data_matrix[mid, mid, 3, 9:14] = 0
data_matrix[mid, mid, 4, 9:14] = 0
data_matrix[mid-1:mid+1, mid-1:mid+1, 5, 10:14] = 0
data_matrix[0::3, fdf8:f53e:61e4::18, 6, 10:14] = 0
data_matrix[0::2, fc00:db20:35b:7399::5, 6, 11:14] = 0
data_matrix = make_drop_mat(data_matrix, 0, 2, 7)
data_matrix = make_drop_mat(data_matrix, 0, 3, 8)
data_matrix = make_drop_mat(data_matrix, 0, 6, 7)
data_matrix = make_drop_mat(data_matrix, 6, 2, 8)
data_matrix = make_drop_mat(data_matrix, 6, 4, 9)
data_matrix = make_drop_mat(data_matrix, 2, 0, 7)
data_matrix = make_drop_mat(data_matrix, 3, 0, 8)
data_matrix = make_drop_mat(data_matrix, 6, 0, 9)
data_matrix = make_drop_mat(data_matrix, 2, 6, 8)
data_matrix = make_drop_mat(data_matrix, 4, 6, 7)
data_matrix = make_drop_mat(data_matrix, 2, 2, 8)
# crop un-used volumes
final_vol = np.max(np.nonzero(data_matrix.reshape(-1, data_matrix.shape[-1])))
data_matrix = data_matrix[:, :, :, 0:final_vol]
cv.save_matrix(data_matrix, visu_name)
# call visualization script
os.system(f'python visualization_wrapper.py --fname {visu_name} --vis_type plot --time_step 0.2') | visu_firework.py | import numpy as np
import os
import cubeventure as cv
visu_name = 'firework'
i_grid = 7
mid = np.floor(i_grid/2).astype(np.int)
data_matrix = np.zeros((i_grid, i_grid, i_grid, 30))
# define a falling drop
def make_drop_mat(mat, x, y, t):
drop_mat = np.zeros((i_grid, i_grid, i_grid, i_grid))
for i in np.arange(0, i_grid):
drop_mat[x, y, i_grid-1-i, i] = 1
mat[:, :, :, t:t+i_grid] = mat[:, :, :, t:t+i_grid] + drop_mat
return mat
# 0
data_matrix[mid, mid, 0, 0] = 1
for i in [1 ,2, 3, 4]:
data_matrix[:, :, :, i] = data_matrix[:, :, :, i-1]
data_matrix[mid, mid, i, i] = 1
data_matrix[:, :, :, 5] = data_matrix[:, :, :, 4]
data_matrix[mid-1:mid+1, mid-1:mid+1, 5, 5] = 1
data_matrix[:, :, :, 6] = data_matrix[:, :, :, 5]
data_matrix[:, :, 6, 6] = 1
for i in np.arange(7, 14):
data_matrix[:, :, :, i] = data_matrix[:, :, :, 6]
data_matrix[mid, mid, 0, 7:14] = 0
data_matrix[mid, mid, 1, 8:14] = 0
data_matrix[mid, mid, 2, 8:14] = 0
data_matrix[mid, mid, 3, 9:14] = 0
data_matrix[mid, mid, 4, 9:14] = 0
data_matrix[mid-1:mid+1, mid-1:mid+1, 5, 10:14] = 0
data_matrix[0::3, fdf8:f53e:61e4::18, 6, 10:14] = 0
data_matrix[0::2, fc00:db20:35b:7399::5, 6, 11:14] = 0
data_matrix = make_drop_mat(data_matrix, 0, 2, 7)
data_matrix = make_drop_mat(data_matrix, 0, 3, 8)
data_matrix = make_drop_mat(data_matrix, 0, 6, 7)
data_matrix = make_drop_mat(data_matrix, 6, 2, 8)
data_matrix = make_drop_mat(data_matrix, 6, 4, 9)
data_matrix = make_drop_mat(data_matrix, 2, 0, 7)
data_matrix = make_drop_mat(data_matrix, 3, 0, 8)
data_matrix = make_drop_mat(data_matrix, 6, 0, 9)
data_matrix = make_drop_mat(data_matrix, 2, 6, 8)
data_matrix = make_drop_mat(data_matrix, 4, 6, 7)
data_matrix = make_drop_mat(data_matrix, 2, 2, 8)
# crop un-used volumes
final_vol = np.max(np.nonzero(data_matrix.reshape(-1, data_matrix.shape[-1])))
data_matrix = data_matrix[:, :, :, 0:final_vol]
cv.save_matrix(data_matrix, visu_name)
# call visualization script
os.system(f'python visualization_wrapper.py --fname {visu_name} --vis_type plot --time_step 0.2') | 0.330471 | 0.540985 |
import platform
import webbrowser
from pathlib import Path
from invoke import task # type: ignore
from invoke.runners import Failure, Result # type: ignore
ROOT_DIR = Path(__file__).parent
DOCS_DIR = ROOT_DIR.joinpath("docs")
DOCS_BUILD_DIR = DOCS_DIR.joinpath("_build")
DOCS_INDEX = DOCS_BUILD_DIR.joinpath("index.html")
TEST_DIR = ROOT_DIR.joinpath("tests")
SETUP_PY = ROOT_DIR.joinpath("setup.py")
TASKS_PY = ROOT_DIR.joinpath("tasks.py")
PYTHON_DIRS = [str(d) for d in [SETUP_PY, TASKS_PY, TEST_DIR]]
def _run(context, command, **kwargs):
return context.run(command, pty=platform.system() != "Windows", **kwargs)
@task
def test(context):
"""
Run tests
"""
_run(context, "pytest")
@task(help={"check": "Checks if source is formatted without applying changes"})
def style(context, check=False):
"""
Format code
"""
for result in [
isort(context, check),
pipenv_setup(context, check),
black(context, check),
]:
if result.failed:
raise Failure(result)
def isort(context, check=False) -> Result:
"""Runs isort."""
isort_options = "{}".format("--check-only --diff" if check else "")
return _run(
context, "isort {} {}".format(isort_options, " ".join(PYTHON_DIRS)), warn=True
)
def pipenv_setup(context, check=False) -> Result:
"""Runs pipenv-setup."""
isort_options = "{}".format("check --strict" if check else "sync --pipfile")
return _run(context, "pipenv-setup {}".format(isort_options), warn=True)
def black(context, check=False) -> Result:
"""Runs black."""
black_options = "{}".format("--check --diff" if check else "")
return _run(
context, "black {} {}".format(black_options, " ".join(PYTHON_DIRS)), warn=True
)
@task
def lint_flake8(context):
"""
Lint code with flake8
"""
_run(context, "flake8 {} {}".format("--radon-show-closures", " ".join(PYTHON_DIRS)))
@task
def lint_pylint(context):
"""
Lint code with pylint
"""
_run(context, "pylint {}".format(" ".join(PYTHON_DIRS)))
@task
def lint_mypy(context):
"""
Lint code with pylint
"""
_run(context, "mypy {}".format(" ".join(PYTHON_DIRS)))
@task(lint_flake8, lint_pylint, lint_mypy)
def lint(_context):
"""
Run all linting
"""
@task
def radon_cc(context):
"""
Reports code complexity.
"""
_run(context, "radon cc {}".format(" ".join(PYTHON_DIRS)))
@task
def radon_mi(context):
"""
Reports maintainability index.
"""
_run(context, "radon mi {}".format(" ".join(PYTHON_DIRS)))
@task(radon_cc, radon_mi)
def radon(_context):
"""
Reports radon.
"""
@task
def xenon(context):
"""
Check code complexity.
"""
_run(
context,
"xenon --max-absolute A --max-modules A --max-average A {}".format(
" ".join(PYTHON_DIRS)
),
)
@task
def docs(context):
"""
Generate documentation
"""
_run(context, "sphinx-build -b html {} {}".format(DOCS_DIR, DOCS_BUILD_DIR))
webbrowser.open(DOCS_INDEX.absolute().as_uri())
@task
def clean_docs(context):
"""
Clean up files from documentation builds
"""
_run(context, "rm -fr {}".format(DOCS_BUILD_DIR)) | tasks.py |
import platform
import webbrowser
from pathlib import Path
from invoke import task # type: ignore
from invoke.runners import Failure, Result # type: ignore
ROOT_DIR = Path(__file__).parent
DOCS_DIR = ROOT_DIR.joinpath("docs")
DOCS_BUILD_DIR = DOCS_DIR.joinpath("_build")
DOCS_INDEX = DOCS_BUILD_DIR.joinpath("index.html")
TEST_DIR = ROOT_DIR.joinpath("tests")
SETUP_PY = ROOT_DIR.joinpath("setup.py")
TASKS_PY = ROOT_DIR.joinpath("tasks.py")
PYTHON_DIRS = [str(d) for d in [SETUP_PY, TASKS_PY, TEST_DIR]]
def _run(context, command, **kwargs):
return context.run(command, pty=platform.system() != "Windows", **kwargs)
@task
def test(context):
"""
Run tests
"""
_run(context, "pytest")
@task(help={"check": "Checks if source is formatted without applying changes"})
def style(context, check=False):
"""
Format code
"""
for result in [
isort(context, check),
pipenv_setup(context, check),
black(context, check),
]:
if result.failed:
raise Failure(result)
def isort(context, check=False) -> Result:
"""Runs isort."""
isort_options = "{}".format("--check-only --diff" if check else "")
return _run(
context, "isort {} {}".format(isort_options, " ".join(PYTHON_DIRS)), warn=True
)
def pipenv_setup(context, check=False) -> Result:
"""Runs pipenv-setup."""
isort_options = "{}".format("check --strict" if check else "sync --pipfile")
return _run(context, "pipenv-setup {}".format(isort_options), warn=True)
def black(context, check=False) -> Result:
"""Runs black."""
black_options = "{}".format("--check --diff" if check else "")
return _run(
context, "black {} {}".format(black_options, " ".join(PYTHON_DIRS)), warn=True
)
@task
def lint_flake8(context):
"""
Lint code with flake8
"""
_run(context, "flake8 {} {}".format("--radon-show-closures", " ".join(PYTHON_DIRS)))
@task
def lint_pylint(context):
"""
Lint code with pylint
"""
_run(context, "pylint {}".format(" ".join(PYTHON_DIRS)))
@task
def lint_mypy(context):
"""
Lint code with pylint
"""
_run(context, "mypy {}".format(" ".join(PYTHON_DIRS)))
@task(lint_flake8, lint_pylint, lint_mypy)
def lint(_context):
"""
Run all linting
"""
@task
def radon_cc(context):
"""
Reports code complexity.
"""
_run(context, "radon cc {}".format(" ".join(PYTHON_DIRS)))
@task
def radon_mi(context):
"""
Reports maintainability index.
"""
_run(context, "radon mi {}".format(" ".join(PYTHON_DIRS)))
@task(radon_cc, radon_mi)
def radon(_context):
"""
Reports radon.
"""
@task
def xenon(context):
"""
Check code complexity.
"""
_run(
context,
"xenon --max-absolute A --max-modules A --max-average A {}".format(
" ".join(PYTHON_DIRS)
),
)
@task
def docs(context):
"""
Generate documentation
"""
_run(context, "sphinx-build -b html {} {}".format(DOCS_DIR, DOCS_BUILD_DIR))
webbrowser.open(DOCS_INDEX.absolute().as_uri())
@task
def clean_docs(context):
"""
Clean up files from documentation builds
"""
_run(context, "rm -fr {}".format(DOCS_BUILD_DIR)) | 0.579638 | 0.13489 |
import os.path
class Properties:
_default_properties_file = "fwd-ansible.properties"
def __init__(self, module, properties_file_path):
if properties_file_path is not None and not os.path.isfile(properties_file_path):
module.fail_json(rc=256, msg="Forward server properties file '%s' does not exist." % properties_file_path)
self.properties = Properties._get_properties(properties_file_path)
if 'url' in module.params and module.params['url'] is not None and module.params['url'].strip() != '':
self.properties['url'] = module.params['url']
if 'username' in module.params and module.params['username'] is not None and module.params[
'username'].strip() != '':
self.properties['username'] = module.params['username']
if 'password' in module.params and module.params['password'] is not None and module.params[
'password'].strip() != '':
self.properties['password'] = module.params['password']
if 'network_name' in module.params and module.params['network_name'] is not None and module.params[
'network_name'].strip() != '':
self.properties['network_name'] = module.params['network_name']
@staticmethod
def _get_properties(properties_file_path):
properties = {}
if properties_file_path is None:
properties_file_path = Properties._default_properties_file
if not os.path.isfile(properties_file_path):
return properties
with open(properties_file_path) as properties_file:
for line in properties_file:
name, var = line.partition("=")[::2]
properties[name.strip()] = var.strip()
return properties
def get_url(self):
if 'url' not in self.properties or self.properties['url'] is None or self.properties['url'].strip() == '':
return None
return self.properties['url']
def get_username(self):
if 'username' not in self.properties or self.properties['username'] is None or self.properties['username'].strip() == '':
return None
return self.properties['username']
def get_password(self):
if 'password' not in self.properties or self.properties['password'] is None or self.properties['password'].strip() == '':
return None
return self.properties['password']
def get_network_name(self):
if 'network_name' not in self.properties or self.properties['network_name'] is None:
return None
return self.properties['network_name']
class Utils:
def __init__(self):
return
@staticmethod
def get_network_id(fwd_client_instance, network_name):
result = fwd_client_instance.get_networks_info(verbose=False)
if len(result) == 0:
return -1
for network in result:
if network.get_name() == network_name:
return network.get_id()
return -1
@staticmethod
def search_networks(fwd_client_instance, search_keyword):
networks = fwd_client_instance.get_networks_info(verbose=False)
if len(networks) == 0:
return -1
result = []
for network in networks:
if search_keyword in network.get_name():
result.append({'name': network.get_name(), 'id': network.get_id()})
return result | module_utils/forward.py |
import os.path
class Properties:
_default_properties_file = "fwd-ansible.properties"
def __init__(self, module, properties_file_path):
if properties_file_path is not None and not os.path.isfile(properties_file_path):
module.fail_json(rc=256, msg="Forward server properties file '%s' does not exist." % properties_file_path)
self.properties = Properties._get_properties(properties_file_path)
if 'url' in module.params and module.params['url'] is not None and module.params['url'].strip() != '':
self.properties['url'] = module.params['url']
if 'username' in module.params and module.params['username'] is not None and module.params[
'username'].strip() != '':
self.properties['username'] = module.params['username']
if 'password' in module.params and module.params['password'] is not None and module.params[
'password'].strip() != '':
self.properties['password'] = module.params['password']
if 'network_name' in module.params and module.params['network_name'] is not None and module.params[
'network_name'].strip() != '':
self.properties['network_name'] = module.params['network_name']
@staticmethod
def _get_properties(properties_file_path):
properties = {}
if properties_file_path is None:
properties_file_path = Properties._default_properties_file
if not os.path.isfile(properties_file_path):
return properties
with open(properties_file_path) as properties_file:
for line in properties_file:
name, var = line.partition("=")[::2]
properties[name.strip()] = var.strip()
return properties
def get_url(self):
if 'url' not in self.properties or self.properties['url'] is None or self.properties['url'].strip() == '':
return None
return self.properties['url']
def get_username(self):
if 'username' not in self.properties or self.properties['username'] is None or self.properties['username'].strip() == '':
return None
return self.properties['username']
def get_password(self):
if 'password' not in self.properties or self.properties['password'] is None or self.properties['password'].strip() == '':
return None
return self.properties['password']
def get_network_name(self):
if 'network_name' not in self.properties or self.properties['network_name'] is None:
return None
return self.properties['network_name']
class Utils:
def __init__(self):
return
@staticmethod
def get_network_id(fwd_client_instance, network_name):
result = fwd_client_instance.get_networks_info(verbose=False)
if len(result) == 0:
return -1
for network in result:
if network.get_name() == network_name:
return network.get_id()
return -1
@staticmethod
def search_networks(fwd_client_instance, search_keyword):
networks = fwd_client_instance.get_networks_info(verbose=False)
if len(networks) == 0:
return -1
result = []
for network in networks:
if search_keyword in network.get_name():
result.append({'name': network.get_name(), 'id': network.get_id()})
return result | 0.424889 | 0.10004 |
# Control our fan
import RPi.GPIO as GPIO
from subprocess import Popen, PIPE
import argparse
# setup pin for fan
fan = 17
feedback = 13
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
# these are the arguments to be passed into our program
parser = argparse.ArgumentParser()
parser.add_argument("-o", "--option", metavar="OPTION",
help="on, off or status")
parser.add_argument("-v", "--verbose", help="outputs more information")
args = parser.parse_args()
# print out more information
v = False
if args.verbose:
v = True
# functions for doing stuffs
def is_compressor_on():
return False
# process = Popen(["python", "compressor-control.py", "-o", "status"], stdout=PIPE)
# (output, err) = process.communicate()
# exit_code = process.wait()
# if output == "on\n":
# return True
# else:
# return False
def fan_on():
if v:
print("turning fan on")
# setup pin for output
GPIO.setup(fan, GPIO.OUT)
# set the pin high
GPIO.output(fan, GPIO.HIGH)
def fan_off():
if v:
pass
#print "checking if compressor is on"
if not is_compressor_on():
if v:
print("turning fan off")
# setup pin for output
GPIO.setup(fan, GPIO.OUT)
# set the pin low
GPIO.output(fan, GPIO.LOW)
else:
if v:
print("NOT turning fan off, compressor on!")
else:
print("compressor on")
def fan_status():
status = "status: "
# setup pin for input
GPIO.setup(feedback, GPIO.IN)
if GPIO.input(feedback):
if v:
print(status+"off")
else:
print("off")
else:
if v:
print(status+"on")
else:
print("on")
# handle arguments
if args.option:
opt = args.option
if (opt == "on"):
fan_on()
elif (opt == "off"):
fan_off()
elif (opt == "status"):
fan_status()
else:
print(opt+" is an invaild option") | fan-control.py |
# Control our fan
import RPi.GPIO as GPIO
from subprocess import Popen, PIPE
import argparse
# setup pin for fan
fan = 17
feedback = 13
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
# these are the arguments to be passed into our program
parser = argparse.ArgumentParser()
parser.add_argument("-o", "--option", metavar="OPTION",
help="on, off or status")
parser.add_argument("-v", "--verbose", help="outputs more information")
args = parser.parse_args()
# print out more information
v = False
if args.verbose:
v = True
# functions for doing stuffs
def is_compressor_on():
return False
# process = Popen(["python", "compressor-control.py", "-o", "status"], stdout=PIPE)
# (output, err) = process.communicate()
# exit_code = process.wait()
# if output == "on\n":
# return True
# else:
# return False
def fan_on():
if v:
print("turning fan on")
# setup pin for output
GPIO.setup(fan, GPIO.OUT)
# set the pin high
GPIO.output(fan, GPIO.HIGH)
def fan_off():
if v:
pass
#print "checking if compressor is on"
if not is_compressor_on():
if v:
print("turning fan off")
# setup pin for output
GPIO.setup(fan, GPIO.OUT)
# set the pin low
GPIO.output(fan, GPIO.LOW)
else:
if v:
print("NOT turning fan off, compressor on!")
else:
print("compressor on")
def fan_status():
status = "status: "
# setup pin for input
GPIO.setup(feedback, GPIO.IN)
if GPIO.input(feedback):
if v:
print(status+"off")
else:
print("off")
else:
if v:
print(status+"on")
else:
print("on")
# handle arguments
if args.option:
opt = args.option
if (opt == "on"):
fan_on()
elif (opt == "off"):
fan_off()
elif (opt == "status"):
fan_status()
else:
print(opt+" is an invaild option") | 0.150684 | 0.116261 |
from __future__ import print_function, unicode_literals
import os
import magic
import json
import hashlib
import uuid
"""Utils module"""
class utils:
"""
Regroupment of useful functions
All methods are static
"""
@staticmethod
def check_mime_type(filename, mime_type_allowed):
"""
Check if the mime type of the file is in the allowed type
Return bool valid
"""
if not isinstance(mime_type_allowed, (list, tuple)):
raise TypeError('"mime_type_allowed" is not a list or a tuple')
mime_type = magic.from_file(filename, mime=True)
if(mime_type in mime_type_allowed):
return True
return False
@staticmethod
def generate_uuid():
"""
Get a unique id
Return uuid unique id
"""
return uuid.uuid4()
@staticmethod
def file_hash(algo, filename):
"""
Hash a file with given algorithm
[sha256, md5]
Return string hash
"""
if(algo == 'sha256'):
return utils.file_hash_sha256(filename)
elif(algo == 'md5'):
return utils.file_hash_md5(filename)
raise ValueError('Algorithm {} not implemented.'.format(algo))
@staticmethod
def file_hash_sha256(filename):
"""
Get the file SHA256
Return string hash
"""
h = hashlib.sha256()
with open(filename, 'rb', buffering=0) as f:
for b in iter(lambda: f.read(128*1024), b''):
h.update(b)
return h.hexdigest()
@staticmethod
def file_hash_md5(filename):
"""
Get the file MD5
Return string hash
"""
hash_md5 = hashlib.md5()
with open(filename, "rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
hash_md5.update(chunk)
return hash_md5.hexdigest()
@staticmethod
def file_get_contents(filename, mode='r'):
"""
Get the content of a file
Return string content
"""
content = ''
if os.path.exists(filename):
fp = open(filename, mode)
content = fp.read()
fp.close()
return content
@staticmethod
def file_put_contents(filename, contents):
"""
Write content to a file
"""
file = open(filename, 'w')
file.write(contents)
file.close()
@staticmethod
def file_get_json(filename):
"""
Load a json object from file
Return collection json
"""
if os.path.exists(filename):
if(utils.check_mime_type(filename, ['application/json', 'text/plain'])):
content = utils.file_get_contents(filename)
return json.loads(content)
else:
raise ValueError(
'{} is not a valid json file.'.format(filename)) | cerespacketexploder/utils.py |
from __future__ import print_function, unicode_literals
import os
import magic
import json
import hashlib
import uuid
"""Utils module"""
class utils:
"""
Regroupment of useful functions
All methods are static
"""
@staticmethod
def check_mime_type(filename, mime_type_allowed):
"""
Check if the mime type of the file is in the allowed type
Return bool valid
"""
if not isinstance(mime_type_allowed, (list, tuple)):
raise TypeError('"mime_type_allowed" is not a list or a tuple')
mime_type = magic.from_file(filename, mime=True)
if(mime_type in mime_type_allowed):
return True
return False
@staticmethod
def generate_uuid():
"""
Get a unique id
Return uuid unique id
"""
return uuid.uuid4()
@staticmethod
def file_hash(algo, filename):
"""
Hash a file with given algorithm
[sha256, md5]
Return string hash
"""
if(algo == 'sha256'):
return utils.file_hash_sha256(filename)
elif(algo == 'md5'):
return utils.file_hash_md5(filename)
raise ValueError('Algorithm {} not implemented.'.format(algo))
@staticmethod
def file_hash_sha256(filename):
"""
Get the file SHA256
Return string hash
"""
h = hashlib.sha256()
with open(filename, 'rb', buffering=0) as f:
for b in iter(lambda: f.read(128*1024), b''):
h.update(b)
return h.hexdigest()
@staticmethod
def file_hash_md5(filename):
"""
Get the file MD5
Return string hash
"""
hash_md5 = hashlib.md5()
with open(filename, "rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
hash_md5.update(chunk)
return hash_md5.hexdigest()
@staticmethod
def file_get_contents(filename, mode='r'):
"""
Get the content of a file
Return string content
"""
content = ''
if os.path.exists(filename):
fp = open(filename, mode)
content = fp.read()
fp.close()
return content
@staticmethod
def file_put_contents(filename, contents):
"""
Write content to a file
"""
file = open(filename, 'w')
file.write(contents)
file.close()
@staticmethod
def file_get_json(filename):
"""
Load a json object from file
Return collection json
"""
if os.path.exists(filename):
if(utils.check_mime_type(filename, ['application/json', 'text/plain'])):
content = utils.file_get_contents(filename)
return json.loads(content)
else:
raise ValueError(
'{} is not a valid json file.'.format(filename)) | 0.672977 | 0.15961 |
from django.conf import settings
from django.contrib import admin
from django.urls import path
from django.conf.urls import url
from django.conf.urls.static import static
from funnysociety import views
from django.urls import path, include
from django.views.generic.base import TemplateView
from django.contrib.auth.views import LoginView
urlpatterns = [
# url(r'^$', home, name='home'),
url(r'^admin/', admin.site.urls), # Admin page
url(r'^register/$', views.UserFormView.as_view(),name='register'), #User registration page
url(r'^edit_profile/(?P<pk>[0-9]+)/$', views.edit_profile,name='edit_profile_with_pk'), #User edit page
path('accounts/', include('django.contrib.auth.urls')), # User sign in, sign out default pages
path('profile/', TemplateView.as_view(template_name='profile.html'), name='profile'), # Home page is the profile page
path('', LoginView.as_view(template_name='registration/login.html'), name="home"),
url(r'^profile/create_discussion/$', views.create_discussion,name='create_discussion'), #Create discussion
url(r'^profile/get_discussion/$', views.get_discussion,name='get_discussion'), #Get user discussion
url(r'^profile/discussion/(?P<pk>[0-9]+)/$', views.discussion_page,name='discussion_page'), #Get user discussion
url(r'^profile/create_post/$', views.create_post,name='create_post'), #User registration page
url(r'^profile/get_status/$', views.get_status,name='get_status'), #Get user status
url(r'^profile/(?P<username>[\w\-]+)/get_status/$', views.get_status,name='get_status'), #Get user status
url(r'^profile/create_post/$', views.create_post,name='create_post'), #Add status post
url(r'^profile/post_comment/$', views.post_comment,name='post_comment'), #Post comment
url(r'^profile/(?P<username>[\w\-]+)/post_comment/$', views.post_comment,name='post_comment'), #Post comment
url(r'^profile/get_comments/$', views.get_comments,name='get_comments'), #Get comments
url(r'^profile/(?P<username>[\w\-]+)/get_comments/$', views.get_comments,name='get_comments'), #Get comments
url(r'^profile/add_friend/$', views.add_friend,name='add_friend'), #Add friend
url(r'^profile/get_friends/$', views.get_friends,name='get_friends'), #Get current friends
url(r'^profile/accept_friend/$', views.accept_friend,name='accept_friend'), #Accept friend request
url(r'^profile/decline_friend/$', views.decline_friend,name='decline_friend'), #Decline friend request
url(r'^profile/delete_friend_request/$', views.delete_friend_request,name='delete_friend_request'), #Delete friend request
url(r'^profile/delete_friend/$', views.delete_friend,name='delete_friend'), #Delete friend
url(r'^profile/(?P<username>[\w\-]+)/friend_list/$', views.friend_list,name='friend_list'), # Friend List Page
url(r'^profile/search/?$', views.search,name='search'), #Search friend / discussion
url(r'^profile/(?P<username>[\w\-]+)/$', views.profile_friend,name='profile_friend'), #Profile friend
url(r'^profile/discussion/(?P<pk>[0-9]+)/post_chat/$', views.post_chat,name='post_chat'), #Post user chats
url(r'^profile/discussion/(?P<pk>[0-9]+)/load_chat/$', views.load_chat,name='load_chat'), #Get discussion chats
#url(r'^event/$', event, name='event'),
]
if settings.DEBUG:
urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) | bwa2018djangoproject/urls.py | from django.conf import settings
from django.contrib import admin
from django.urls import path
from django.conf.urls import url
from django.conf.urls.static import static
from funnysociety import views
from django.urls import path, include
from django.views.generic.base import TemplateView
from django.contrib.auth.views import LoginView
urlpatterns = [
# url(r'^$', home, name='home'),
url(r'^admin/', admin.site.urls), # Admin page
url(r'^register/$', views.UserFormView.as_view(),name='register'), #User registration page
url(r'^edit_profile/(?P<pk>[0-9]+)/$', views.edit_profile,name='edit_profile_with_pk'), #User edit page
path('accounts/', include('django.contrib.auth.urls')), # User sign in, sign out default pages
path('profile/', TemplateView.as_view(template_name='profile.html'), name='profile'), # Home page is the profile page
path('', LoginView.as_view(template_name='registration/login.html'), name="home"),
url(r'^profile/create_discussion/$', views.create_discussion,name='create_discussion'), #Create discussion
url(r'^profile/get_discussion/$', views.get_discussion,name='get_discussion'), #Get user discussion
url(r'^profile/discussion/(?P<pk>[0-9]+)/$', views.discussion_page,name='discussion_page'), #Get user discussion
url(r'^profile/create_post/$', views.create_post,name='create_post'), #User registration page
url(r'^profile/get_status/$', views.get_status,name='get_status'), #Get user status
url(r'^profile/(?P<username>[\w\-]+)/get_status/$', views.get_status,name='get_status'), #Get user status
url(r'^profile/create_post/$', views.create_post,name='create_post'), #Add status post
url(r'^profile/post_comment/$', views.post_comment,name='post_comment'), #Post comment
url(r'^profile/(?P<username>[\w\-]+)/post_comment/$', views.post_comment,name='post_comment'), #Post comment
url(r'^profile/get_comments/$', views.get_comments,name='get_comments'), #Get comments
url(r'^profile/(?P<username>[\w\-]+)/get_comments/$', views.get_comments,name='get_comments'), #Get comments
url(r'^profile/add_friend/$', views.add_friend,name='add_friend'), #Add friend
url(r'^profile/get_friends/$', views.get_friends,name='get_friends'), #Get current friends
url(r'^profile/accept_friend/$', views.accept_friend,name='accept_friend'), #Accept friend request
url(r'^profile/decline_friend/$', views.decline_friend,name='decline_friend'), #Decline friend request
url(r'^profile/delete_friend_request/$', views.delete_friend_request,name='delete_friend_request'), #Delete friend request
url(r'^profile/delete_friend/$', views.delete_friend,name='delete_friend'), #Delete friend
url(r'^profile/(?P<username>[\w\-]+)/friend_list/$', views.friend_list,name='friend_list'), # Friend List Page
url(r'^profile/search/?$', views.search,name='search'), #Search friend / discussion
url(r'^profile/(?P<username>[\w\-]+)/$', views.profile_friend,name='profile_friend'), #Profile friend
url(r'^profile/discussion/(?P<pk>[0-9]+)/post_chat/$', views.post_chat,name='post_chat'), #Post user chats
url(r'^profile/discussion/(?P<pk>[0-9]+)/load_chat/$', views.load_chat,name='load_chat'), #Get discussion chats
#url(r'^event/$', event, name='event'),
]
if settings.DEBUG:
urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) | 0.134094 | 0.045142 |
from datetime import datetime
import argparse
from model.metatile import Metatile
from utils import read_pickle, write_pickle, get_filepath, error_exit
def main(game, level, metatile_coords_dict_file, metatile_id_map_file, player_img):
start_time = datetime.now()
print("\nCreating {(tile id, extra_info): coords} map ...")
metatile_coords_dict = read_pickle(metatile_coords_dict_file)
metatile_id_map = read_pickle(metatile_id_map_file)
tile_id_extra_info_coords_map = {}
for metatile_str, coords in metatile_coords_dict.items():
metatile = Metatile.from_str(metatile_str)
metatile_id = metatile_id_map.get(metatile_str)
if metatile_id is None:
error_exit("metatile_str not found in metatile_id_map")
has_graph = bool(metatile.graph_as_dict)
extra_info = ""
if not has_graph:
extra_info += "E" # metatile graph is empty
if len(coords) == 1:
extra_info += "S" # metatile was only used for one tile
tile_id_extra_info_coords_map[(metatile_id, extra_info)] = coords
save_directory = "level_saved_files_%s/tile_id_coords_maps/%s/" % (player_img, game)
tile_id_extra_info_coords_map_file = get_filepath(save_directory, "%s.pickle" % level)
write_pickle(tile_id_extra_info_coords_map_file, tile_id_extra_info_coords_map)
end_time = datetime.now()
runtime = str(end_time-start_time)
print("Runtime: %s\n" % runtime)
return tile_id_extra_info_coords_map_file, runtime
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Create {tile id: coords} map from the given files')
parser.add_argument('game', type=str, help='Name of the game')
parser.add_argument('level', type=str, help='Name of the level')
parser.add_argument('metatile_coords_dict_file', type=str, help="File path of the metatile_coords dict to use")
parser.add_argument('metatile_id_map_file', type=str, help="File path of the metatile_id map to use")
parser.add_argument('--player_img', type=str, help='Player image', default='block')
args = parser.parse_args()
main(args.game, args.level, args.metatile_coords_dict_file, args.metatile_id_map_file, args.player_img) | get_tile_id_coords_map.py | from datetime import datetime
import argparse
from model.metatile import Metatile
from utils import read_pickle, write_pickle, get_filepath, error_exit
def main(game, level, metatile_coords_dict_file, metatile_id_map_file, player_img):
start_time = datetime.now()
print("\nCreating {(tile id, extra_info): coords} map ...")
metatile_coords_dict = read_pickle(metatile_coords_dict_file)
metatile_id_map = read_pickle(metatile_id_map_file)
tile_id_extra_info_coords_map = {}
for metatile_str, coords in metatile_coords_dict.items():
metatile = Metatile.from_str(metatile_str)
metatile_id = metatile_id_map.get(metatile_str)
if metatile_id is None:
error_exit("metatile_str not found in metatile_id_map")
has_graph = bool(metatile.graph_as_dict)
extra_info = ""
if not has_graph:
extra_info += "E" # metatile graph is empty
if len(coords) == 1:
extra_info += "S" # metatile was only used for one tile
tile_id_extra_info_coords_map[(metatile_id, extra_info)] = coords
save_directory = "level_saved_files_%s/tile_id_coords_maps/%s/" % (player_img, game)
tile_id_extra_info_coords_map_file = get_filepath(save_directory, "%s.pickle" % level)
write_pickle(tile_id_extra_info_coords_map_file, tile_id_extra_info_coords_map)
end_time = datetime.now()
runtime = str(end_time-start_time)
print("Runtime: %s\n" % runtime)
return tile_id_extra_info_coords_map_file, runtime
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Create {tile id: coords} map from the given files')
parser.add_argument('game', type=str, help='Name of the game')
parser.add_argument('level', type=str, help='Name of the level')
parser.add_argument('metatile_coords_dict_file', type=str, help="File path of the metatile_coords dict to use")
parser.add_argument('metatile_id_map_file', type=str, help="File path of the metatile_id map to use")
parser.add_argument('--player_img', type=str, help='Player image', default='block')
args = parser.parse_args()
main(args.game, args.level, args.metatile_coords_dict_file, args.metatile_id_map_file, args.player_img) | 0.397237 | 0.111434 |
import numpy as np
from preprocessing import augment_data, convert_images_gray2rgb
from unet_model import unet
import tiramisu_model as tiramisu
import argparse
#Importing keras function
from keras.models import Model
from keras.layers import Input, concatenate, Conv2D, MaxPooling2D, Conv2DTranspose
from keras.optimizers import Adam
from keras import backend as K
def fit(training_images, mask_images, save_path, model):
'''
This function trains the UNET model and saves it.
Args:
training_images: prepared training images
type: np.array
mask_images: prepared mask images
type: np.array
save_path: path where the model will be saved
type: STRING
model: tiramisu or unet
type: STRING
'''
if model is 'tiramisu':
model= tiramisu.create_tiramisu(3, nb_layers_per_block=[4,5,7,10,12,15], p=0.2, wd=1e-4)
training_images= convert_images_gray2rgb(training_images)
mask_images= convert_images_gray2rgb(mask_images)
else:
model = unet()
model.fit(training_images, mask_images, batch_size=4, epochs=100, verbose=1, shuffle=True)
model.save(save_path+"/"+"model.h5")
def predict(testing_images, model_path, save_result_path, model):
'''
This function predicts the test images and saves the predictions
Args:
testing_images: prepared testing images
type: np.array
model_path: path to the model
type: STRING
save_result_path: path where the predictions will be saved
type: STRING
model: tiramisu or unet
type: STRING
'''
if model is 'tiramisu':
model= tiramisu.create_tiramisu(3, nb_layers_per_block=[4,5,7,10,12,15], p=0.2, wd=1e-4)
testing_images= convert_images_gray2rgb(training_images)
else:
model=unet()
model.load_weights(model_path)
prediction = model.predict(testing_images, batch_size=4,verbose=1)
np.save(save_result_path+'/prediction.npy', prediction)
def call_dl_model(args):
'''
This function is used to prepare data and train or predict depending on the argument
Args:
args: passed from user's arguments
'''
if(args.mode=="fit"):
images,mask = augment_data(args.image_path, args.mask_path, args.mode)
fit(images, mask, args.save_path, args.model)
if(args.mode=="predict"):
images = augment_data(args.image_path,args.mask_path,args.mode)
predict(images,args.model_path,args.save_path, args.model) | hastings/fit_predict_unet.py | import numpy as np
from preprocessing import augment_data, convert_images_gray2rgb
from unet_model import unet
import tiramisu_model as tiramisu
import argparse
#Importing keras function
from keras.models import Model
from keras.layers import Input, concatenate, Conv2D, MaxPooling2D, Conv2DTranspose
from keras.optimizers import Adam
from keras import backend as K
def fit(training_images, mask_images, save_path, model):
'''
This function trains the UNET model and saves it.
Args:
training_images: prepared training images
type: np.array
mask_images: prepared mask images
type: np.array
save_path: path where the model will be saved
type: STRING
model: tiramisu or unet
type: STRING
'''
if model is 'tiramisu':
model= tiramisu.create_tiramisu(3, nb_layers_per_block=[4,5,7,10,12,15], p=0.2, wd=1e-4)
training_images= convert_images_gray2rgb(training_images)
mask_images= convert_images_gray2rgb(mask_images)
else:
model = unet()
model.fit(training_images, mask_images, batch_size=4, epochs=100, verbose=1, shuffle=True)
model.save(save_path+"/"+"model.h5")
def predict(testing_images, model_path, save_result_path, model):
'''
This function predicts the test images and saves the predictions
Args:
testing_images: prepared testing images
type: np.array
model_path: path to the model
type: STRING
save_result_path: path where the predictions will be saved
type: STRING
model: tiramisu or unet
type: STRING
'''
if model is 'tiramisu':
model= tiramisu.create_tiramisu(3, nb_layers_per_block=[4,5,7,10,12,15], p=0.2, wd=1e-4)
testing_images= convert_images_gray2rgb(training_images)
else:
model=unet()
model.load_weights(model_path)
prediction = model.predict(testing_images, batch_size=4,verbose=1)
np.save(save_result_path+'/prediction.npy', prediction)
def call_dl_model(args):
'''
This function is used to prepare data and train or predict depending on the argument
Args:
args: passed from user's arguments
'''
if(args.mode=="fit"):
images,mask = augment_data(args.image_path, args.mask_path, args.mode)
fit(images, mask, args.save_path, args.model)
if(args.mode=="predict"):
images = augment_data(args.image_path,args.mask_path,args.mode)
predict(images,args.model_path,args.save_path, args.model) | 0.791176 | 0.58353 |
import string
import hashlib
from datetime import datetime
from nltk import *
class TweetProcess:
"""class for processing the textual content of a tweet"""
def __init__(self,tweet):
"""Constructor method for TweetTextProcess"""
#json formatted tweet from twitter stream
self.tweet = tweet
#english stopwords, gets the english stopwords from the file: "englishStopWords" stored in utilFiles folder
self.english_stopwords = [lines.rstrip() for lines in open("..\\Resources\\englishStopwords")]
#list of slang words used in twitter, gets the twitter slang words from the file: "TwitterSlangList.txt" stored in utilFiles folder
self.twitter_slang = [lines.rstrip() for lines in open("..\\Resources\\TwitterSlangList.txt")]
#general internet slang words, gets the general internet slang words from the file: "internetSlang.txt" stored in utilFiles folder
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open("..\\Resources\\internetSlang.txt")]
#feeling words from wefeelfine.org, gets the feeling words from the file: "feelingWords.txt" stored in utilFiles folder
self.feelingWords = [lines.rstrip().split()[0] for lines in open("..\\Resources\\feelingWords.txt")]
#number of filtered hashtags in the tweet
self.noHashTags = 0
#number of user mentions in the tweet
self.noUserMentions = 0
#number of urls in the tweet
self.noUrls = 0
#actual list of hashtags present in the tweet
self.rawHashTags = []
#actual number of hashtags present in the tweet
self.noRawHashTags = 0
#list of urls present in the tweet
self.urls = []
#list of nouns extracted from the tweet text
self.nouns = []
#list of cleaned unigram tokens of the tweet text
self.tokens = []
#number of special characters detected in the tweet text
self.noSpecialChars = 0
#length of the tweet
self.tweetLength = 0
#number of unique characters used in the tweet text
self.noUniqueChars = 0
#number of feeling words expressing emotions detected in the tweet text
self.noFeelingWords = 0
#number of slang words detected in the tweet text
self.noSlangWords = 0
#number of english stop words detected in the tweet text
self.noEnglishStopWords = 0
#list of unigrams extracted from tweet text without filtering out the slangs and stopwords
self.rawTokens = []
#misspelling ratio
#self.misspellingRatio = 0.0
#md5 hashvalue of the tweet's text
self.tweetHashValue = 0.0
#indicates whether the tweet comes from a verified source or not
self.isVerified = 0
#indicates whether the tweet contains url or not
self.hasUrl = 0
#tweet feature dictionary
self.featureDict = {}
#retweet count of a tweet
self.retweetCount = 0
#favorite counts of the tweet
self.favoriteCount = 0
#number of extracted tokens
self.noTokens = 0
#initial informativeness score of a tweet
self.initInfoScore = 0.0
self.setterMethodCalls()
def setterMethodCalls(self):
#called methods for setting the instance variables
#calling method for setting the length of the tweet text
self.setTweetLength()
#calling method for setting the list of raw unigram tokens extracted from the tweet text
self.setTweetRawTokens()
#calling method for setting the list of cleaned unigrams extracted from the tweet text
self.setCleanedTweetTextTokens()
#calling method for setting the list of raw hashtags in tweet text
self.setTweetRawHashTags()
#calling method for setting the number of raw hashtags in a tweet
self.setNoRawHashTags()
#calling method for setting the list of nouns extracted from tweet text
self.setNouns()
#calling method for setting the number of user mentions in the tweet
self.setNoUserMentions()
#calling method for setting the list of urls in the tweet
self.setTweetUrls()
#calling method for setting the number of special characters detected in the tweet text
self.noOfSpecialCharacters()
#calling method for setting the number of unique characters detected in the tweet text
self.setNoUniqueChars()
#calling method for setting the number of feeling words detected in the tweet text
self.setNoFeelingWords()
#calling method for setting the number of slang words detected in the tweet text
self.setNoSlangWords()
#calling method for setting the number of stop words detected in the tweet text
self.setNoEnglishStopWords()
#calling method for setting the number of urls present in the tweet
self.setNoOfUrls()
#calling method for setting the misspelling ratio
#self.setMisSpellingRatio()
#calling method for knowing if the tweet comes from a verified source
self.isTweetVerified()
#calling method for setting the md5 hash value of the tweet's text
self.setTweetHashValue()
#calling method for setting the retweet count
self.setRetweetCount()
#calling method for setting the favorite count
self.setFavoriteCount()
#calling method for setting the number of tokens extracted from the tweet
self.setNoOfTokens()
#calling method for setting the tweet's feature dictionary
self.setTweetFeatureDict()
# #calling method for setting initial informativeness score of the tweet
# self.setTweetInitScore()
def setNoEnglishStopWords(self):
"""setter method for detecting the english stop words from the tweet text"""
tweetTokens = self.tweet["text"].split()
self.noEnglishStopWords = len([stopWord for stopWord in tweetTokens if stopWord.lower() in self.english_stopwords])
def getNoEnglishStopWords(self):
"""getter method for getting the number of english stop words detected in the tweet text"""
return self.noEnglishStopWords
def setNoSlangWords(self):
"""setter method for detecting the english slang words from the tweet text"""
tweetTokens = self.tweet["text"].split()
self.noSlangWords = len([slangWord for slangWord in tweetTokens if slangWord.lower() in self.twitter_slang or slangWord.lower() in self.internet_slang ])
def getNoSlangWords(self):
"""getter method for getting the number of english slang words detected in the tweet text"""
return self.noSlangWords
def setNoFeelingWords(self):
"""setter method for detecting the english feeling words from the tweet text text"""
tweetTokens = self.tweet["text"].split()
self.noFeelingWords = len([feelingWord for feelingWord in tweetTokens if feelingWord.lower() in self.feelingWords])
def getNoFeelingWords(self):
"""getter method for getting the number of english feeling words detected in the tweet text"""
return self.noFeelingWords
def isAscii(self,s):
"""detect if a string is Ascii or not"""
for c in s:
if c not in string.ascii_letters:
return False
return True
def getTweet(self):
"""getter method for getting the tweet"""
return self.tweet
def setTweet(self,tweet):
"""setter method for setting the tweet"""
self.tweet = tweet
def getTweetRawText(self):
"""getter method for getting the raw text of the tweet"""
return self.tweet["text"]
def setTweetRawHashTags(self):
"""setter method for setting the list of all the hashtags used in the tweet"""
self.rawHashTags = [hashTag["text"] for hashTag in self.tweet["entities"]["hashtags"]]
def getTweetRawHashTags(self):
"""getter method for getting a list of all the hashtags used in the tweet"""
return self.rawHashTags
def setNoUserMentions(self):
"""setter method for setting the number of user mentions in the tweet"""
self.noUserMentions = len(self.tweet["entities"]["user_mentions"])
def getNoUserMentions(self):
"""getter method for getting the number of user mentions in the tweet"""
return self.noUserMentions
def setNoRawHashTags(self):
"""setter method for setting the number of hashtags used in the tweet"""
self.noRawHashTags = len(self.rawHashTags)
def getNoRawHashTags(self):
"""getter method for getting the number of hashtags used in the tweet"""
return self.noRawHashTags
def setTweetUrls(self):
"""setter method for setting the list of urls used in the tweet"""
self.urls = [u["url"] for u in self.tweet["entities"]["urls"]]
def getTweetUrls(self):
"""getter method for getting the list of urls used in the tweet"""
return self.urls
def setNoOfUrls(self):
"""setter method for setting the number of urls used in the tweet"""
self.noUrls = len(self.urls)
def getNoOfUrls(self):
"""getter method for getting the number of urls used in the tweet"""
return self.noUrls
def setEnglishStopWords(self,stopwordFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\englishStopwords"):
"""setter method for setting the list of english stop words"""
englishStopwords = [lines.rstrip() for lines in open(stopwordFile)]
self.english_stopwords = englishStopwords
def getEnglishStopWords(self):
"""getter method for getting the list of english stop words"""
return self.english_stopwords
def setInternetSlangWords(self,internetSlangFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\internetSlang.txt"):
"""setter method for setting the list of general internet slang words"""
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open(internetSlangFile)]
def getInternetSlangWords(self):
"""getter method for getting the list of general internet slang words"""
return self.internet_slang
def setTwitterSlangWords(self, twitterSlangFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\TwitterSlangList.txt"):
"""setter method for setting the list of twitter slang words published by FBI"""
self.twitter_slang = [lines.rstrip() for lines in open(twitterSlangFile)]
def getTwitterSlangWords(self):
"""getter method for getting the list of twitter slang words published by FBI"""
return self.twitter_slang
def setCleanedTweetTextTokens(self):
"""cleans tweet text and filters out all the hashtags, user mentions, and urls, also tokenizes the tweet text
filters out all the tokens that contain english stop words or contains non-ascii non alphanumeric characters,
also filters out the slang words"""
stopWords = self.english_stopwords #gets the provided english stop words
internetSlangWords = self.internet_slang #gets the provided commonly used internet slang words
twitterSlangWords = self.twitter_slang
wordTokens = self.rawTokens #splits the tweet text at whitespaces
cleanedWordList = [] #container for cleaned tokens
if wordTokens != []:
for wrd in wordTokens:
word = wrd.lower()
if word.find("#") != -1 or word.find("@") != -1 or word.find("http") != -1:
pass
else:
cleanWord = ''.join(e for e in word if e.isalpha())
if cleanWord != "" and cleanWord.lower() not in twitterSlangWords and cleanWord.lower() not in stopWords and cleanWord.lower() not in internetSlangWords and self.isAscii(cleanWord):
cleanedWordList.append(cleanWord)
self.tokens = cleanedWordList
def setTweetRawTokens(self):
"""setter method for setting the list of raw unigram tokens extracted from the tweet"""
self.rawTokens = self.tweet["text"].split()
def noOfSpecialCharacters(self):
"""setter method for setting the number of special characters used in the tweet. The characters like:
@(used for user mention), #(used for hashtags) are not counted as special characters as they have their
own significance in TwitterSphere"""
noSpecialChars = 0
for char in self.tweet["text"].encode("utf-8"):
if char == "@" or char == "#" or char == " ":
pass
else:
if char.isalnum() == False:
noSpecialChars += 1
self.noSpecialChars = noSpecialChars
def getNoOfSpecialCharacters(self):
"""getter method for getting the number of special characters used in the tweet"""
return self.noSpecialChars
def getTokenPOSTags(self):
"""getter method for annotating the tweet tokens with their corresponding POS tags. The default Penn Tree Bank POS tags
are used"""
tweetTokens = self.rawTokens
taggedTokens = pos_tag(tweetTokens)
return taggedTokens
def getNoOfArticles(self):
"""getter method for getting the number of articles of english grammar "a","an","the" detected in the tweet"""
return len([article for article in self.rawTokens if article.lower() in ["a","an","the"]])
def setNouns(self):
"""setter method for setting the list of nouns extracted from the tweet text"""
self.nouns = [noun[0].lower() for noun in self.getTokenPOSTags() if noun[1][0] == "N" and noun[0].lower() in self.tokens]
def getNouns(self):
"""getter method for getting the nouns extracted from the tweet text"""
return self.nouns
def getNoOfNouns(self):
"""getter method for getting the number of nouns extracted from the tweet"""
return len([noun for noun in self.getTokenPOSTags() if noun[1][0] == "N"])
def getNoOfAdjectives(self):
"""getter method for getting the number of adjectives extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "J"])
def getNoOfPrepositions(self):
"""getter method for getting the number of prepositions extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "IN"])
def getNoOfPronouns(self):
"""getter method for getting the number of pronouns extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1] == "PRP" or token[1] == "PRP$"])
def getNoOfVerbs(self):
"""getter method for getting the number of verbs extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "V"])
def getNoOfAdVerbs(self):
"""getter method for getting the number of adverbs extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "R"])
def getNoOfInterjections(self):
"""getter method for getting the number of interjections extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1] == "UH"])
def getTweetTextFormality(self):
"""getter method for getting the formality index of the tweet. Formality Index or F Measure of the tweet is calculated
as follows:
F-Measure = (noun frequency + adjective freq. + preposition freq. + article freq. - pronoun freq. - verb freq. - adverb freq. - interjection freq. + 100)/2
<NAME>. and <NAME>. (1999). Formality of language: definition, measurement
and behavioral determinants. Technical report, Free University of Brussels."""
tweetTokens = self.tweet["text"].split()
if len(tweetTokens) == 0:
formalityIndex = 0.0
else:
formalityIndex = float(((self.getNoOfNouns()+self.getNoOfAdjectives()+self.getNoOfPrepositions()+self.getNoOfArticles())-(self.getNoOfPronouns()+self.getNoOfVerbs()+self.getNoOfAdVerbs()+self.getNoOfInterjections()))+100.0)/2.0
return formalityIndex
def setTweetLength(self):
"""setter method for setting the length of the tweet, which is the number of characters in the tweet"""
self.tweetLength = len(self.tweet["text"])
def getTweetLength(self):
"""getter method for getting the length of the tweet"""
return self.tweetLength
def setNoUniqueChars(self):
"""setter method for setting the number of unique characters in the tweet"""
self.noUniqueChars = len(set(self.tweet["text"]))
def getNoUniqueChars(self):
"""getter method for getting the number of unique characters in the tweet"""
return self.noUniqueChars
def generateHashValue(self,tweetStr):
"""method for generating md5 code for a given string 'str'"""
hash_object = hashlib.md5(tweetStr)
return hash_object.hexdigest()
def setTweetHashValue(self):
"""setter method for setting md5 hash value of the tweet text"""
tweetWords = "".join(self.tokens)
self.tweetHashValue = self.generateHashValue(tweetWords)
def getTweetHashValue(self):
"""getter method for getting the hash value of a tweet"""
return self.tweetHashValue
def isTweetVerified(self):
"""sets the value to 1 if the tweet comes from a verified source else 0"""
if self.tweet["user"]["verified"] == True:
self.isVerified = 1
else:
self.isVerified = 0
def getTweetVerified(self):
"""getter method to get if the tweet is verified or not"""
return self.isVerified
def tweetHasUrl(self):
"""setter method for hasUrl. If tweet has url then 1 else 0"""
if self.urls != []:
self.hasUrl = 1
else:
self.hasUrl = 0
def getCreatedTime(self):
"""gets the tweets post time in python datetime format"""
return datetime.strptime(self.tweet["created_at"], '%a %b %d %H:%M:%S +0000 %Y')
def setRetweetCount(self):
"""setter method for setting the number of times a tweet is retweeted"""
retweetCount = 0
if "retweeted_status" in self.tweet:
retweetCount = self.tweet["retweeted_status"]["retweet_count"]
self.retweetCount = retweetCount
# self.retweetCount = self.tweet["retweet_count"]
def getRetweetCount(self):
"""getter method for getting the retweet count of a tweet"""
return self.retweetCount
def setFavoriteCount(self):
"""setter method for setting the number of favorite counts for the tweet"""
favoriteCount = 0
if "retweeted_status" in self.tweet:
favoriteCount = self.tweet["retweeted_status"]["favorite_count"]
self.favoriteCount = favoriteCount
# self.favoriteCount = self.tweet["favorite_count"]
def getFavoriteCount(self):
"""getter method for getting the favorite count of the tweet"""
return self.favoriteCount
def setNoOfTokens(self):
"""setter method for setting the number of tokens extracted from the tweet"""
self.noTokens = len(self.tokens)
def getNoOfTokens(self):
"""getter method for getting the number of tokens extracted from the tweet"""
return self.noTokens
def setTweetFeatureDict(self):
""""sets the feature dictionary for the tweet"""
self.featureDict = {"tweetUrls":self.getTweetUrls(),"md5Hash":self.getTweetHashValue(),"createdTime":self.getCreatedTime(),"tokens":self.tokens,"nouns":self.nouns,"favoriteCount":self.getFavoriteCount(),"retweetCount":self.getRetweetCount(),"formality":self.getTweetTextFormality(),"isTweetVerified":self.getTweetVerified(),"hasUrl":self.hasUrl,"noWords":self.getNoOfTokens(),"noStopWords":self.getNoEnglishStopWords(),"noFeelingWords":self.getNoFeelingWords(),"noSlangWords":self.getNoSlangWords(),"noHashTags":self.getNoRawHashTags(),"noUserMentions":self.getNoUserMentions(),"tweetLen":self.getTweetLength(),"noUrls":self.getNoOfUrls(),"uniqueChars":self.getNoUniqueChars(),"noSpecialChars":self.getNoOfSpecialCharacters()}
def getTweetFeatureDict(self):
"""getter method for getting the tweet's features"""
return self.featureDict
def getDataInstanceForClassification(self):
"""getter method for getting the features of a tweet for initial classification as informative/non-informative"""
dataInstance = [1.0]
if self.featureDict["noUrls"] > 0:
dataInstance.append(float(1.0))
else:
dataInstance.append(float(0.0))
dataInstance.append(float(self.featureDict["noWords"])/20.0)
dataInstance.append(float(self.featureDict["noStopWords"])/21.0)
dataInstance.append(float(self.featureDict["noFeelingWords"])/7.0)
dataInstance.append(float(self.featureDict["noSlangWords"])/7.0)
dataInstance.append(float(self.featureDict["noHashTags"])/17.0)
dataInstance.append(float(self.featureDict["noUserMentions"])/8.0)
dataInstance.append(float(self.featureDict["noUrls"])/3.0)
dataInstance.append(float(self.featureDict["tweetLen"])/140.0)
dataInstance.append(float(self.featureDict["uniqueChars"])/140.0)
dataInstance.append(float(self.featureDict["noSpecialChars"])/140.0)
dataInstance.append(float(self.featureDict["favoriteCount"])/13802.0)
dataInstance.append(float(self.featureDict["retweetCount"])/41633.0)
dataInstance.append(float(self.featureDict["formality"])/63.5)
dataInstance.append(float(self.featureDict["isTweetVerified"]))
return dataInstance
class LoadSlang:
"""class for loading and getting the slang words to be filtered out during processing of tweets"""
def __init__(self):
#english stopwords, gets the english stopwords from the file: "englishStopWords" stored in utilFiles folder
self.english_stopwords = [lines.rstrip() for lines in open("..\\Resources\\englishStopwords")]
#list of slang words used in twitter, gets the twitter slang words from the file: "TwitterSlangList.txt" stored in utilFiles folder
self.twitter_slang = [lines.rstrip() for lines in open("..\\Resources\\TwitterSlangList.txt")]
#general internet slang words, gets the general internet slang words from the file: "internetSlang.txt" stored in utilFiles folder
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open("..\\Resources\\internetSlang.txt")]
#masterList
self.slangWords = self.english_stopwords+self.twitter_slang+self.internet_slang
def getSlang(self):
"""getter method for getting a list of slang words to be filtered out from the tweet text"""
return self.slangWords | EventInfoProcess/EventTweetProcess.py | import string
import hashlib
from datetime import datetime
from nltk import *
class TweetProcess:
"""class for processing the textual content of a tweet"""
def __init__(self,tweet):
"""Constructor method for TweetTextProcess"""
#json formatted tweet from twitter stream
self.tweet = tweet
#english stopwords, gets the english stopwords from the file: "englishStopWords" stored in utilFiles folder
self.english_stopwords = [lines.rstrip() for lines in open("..\\Resources\\englishStopwords")]
#list of slang words used in twitter, gets the twitter slang words from the file: "TwitterSlangList.txt" stored in utilFiles folder
self.twitter_slang = [lines.rstrip() for lines in open("..\\Resources\\TwitterSlangList.txt")]
#general internet slang words, gets the general internet slang words from the file: "internetSlang.txt" stored in utilFiles folder
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open("..\\Resources\\internetSlang.txt")]
#feeling words from wefeelfine.org, gets the feeling words from the file: "feelingWords.txt" stored in utilFiles folder
self.feelingWords = [lines.rstrip().split()[0] for lines in open("..\\Resources\\feelingWords.txt")]
#number of filtered hashtags in the tweet
self.noHashTags = 0
#number of user mentions in the tweet
self.noUserMentions = 0
#number of urls in the tweet
self.noUrls = 0
#actual list of hashtags present in the tweet
self.rawHashTags = []
#actual number of hashtags present in the tweet
self.noRawHashTags = 0
#list of urls present in the tweet
self.urls = []
#list of nouns extracted from the tweet text
self.nouns = []
#list of cleaned unigram tokens of the tweet text
self.tokens = []
#number of special characters detected in the tweet text
self.noSpecialChars = 0
#length of the tweet
self.tweetLength = 0
#number of unique characters used in the tweet text
self.noUniqueChars = 0
#number of feeling words expressing emotions detected in the tweet text
self.noFeelingWords = 0
#number of slang words detected in the tweet text
self.noSlangWords = 0
#number of english stop words detected in the tweet text
self.noEnglishStopWords = 0
#list of unigrams extracted from tweet text without filtering out the slangs and stopwords
self.rawTokens = []
#misspelling ratio
#self.misspellingRatio = 0.0
#md5 hashvalue of the tweet's text
self.tweetHashValue = 0.0
#indicates whether the tweet comes from a verified source or not
self.isVerified = 0
#indicates whether the tweet contains url or not
self.hasUrl = 0
#tweet feature dictionary
self.featureDict = {}
#retweet count of a tweet
self.retweetCount = 0
#favorite counts of the tweet
self.favoriteCount = 0
#number of extracted tokens
self.noTokens = 0
#initial informativeness score of a tweet
self.initInfoScore = 0.0
self.setterMethodCalls()
def setterMethodCalls(self):
#called methods for setting the instance variables
#calling method for setting the length of the tweet text
self.setTweetLength()
#calling method for setting the list of raw unigram tokens extracted from the tweet text
self.setTweetRawTokens()
#calling method for setting the list of cleaned unigrams extracted from the tweet text
self.setCleanedTweetTextTokens()
#calling method for setting the list of raw hashtags in tweet text
self.setTweetRawHashTags()
#calling method for setting the number of raw hashtags in a tweet
self.setNoRawHashTags()
#calling method for setting the list of nouns extracted from tweet text
self.setNouns()
#calling method for setting the number of user mentions in the tweet
self.setNoUserMentions()
#calling method for setting the list of urls in the tweet
self.setTweetUrls()
#calling method for setting the number of special characters detected in the tweet text
self.noOfSpecialCharacters()
#calling method for setting the number of unique characters detected in the tweet text
self.setNoUniqueChars()
#calling method for setting the number of feeling words detected in the tweet text
self.setNoFeelingWords()
#calling method for setting the number of slang words detected in the tweet text
self.setNoSlangWords()
#calling method for setting the number of stop words detected in the tweet text
self.setNoEnglishStopWords()
#calling method for setting the number of urls present in the tweet
self.setNoOfUrls()
#calling method for setting the misspelling ratio
#self.setMisSpellingRatio()
#calling method for knowing if the tweet comes from a verified source
self.isTweetVerified()
#calling method for setting the md5 hash value of the tweet's text
self.setTweetHashValue()
#calling method for setting the retweet count
self.setRetweetCount()
#calling method for setting the favorite count
self.setFavoriteCount()
#calling method for setting the number of tokens extracted from the tweet
self.setNoOfTokens()
#calling method for setting the tweet's feature dictionary
self.setTweetFeatureDict()
# #calling method for setting initial informativeness score of the tweet
# self.setTweetInitScore()
def setNoEnglishStopWords(self):
"""setter method for detecting the english stop words from the tweet text"""
tweetTokens = self.tweet["text"].split()
self.noEnglishStopWords = len([stopWord for stopWord in tweetTokens if stopWord.lower() in self.english_stopwords])
def getNoEnglishStopWords(self):
"""getter method for getting the number of english stop words detected in the tweet text"""
return self.noEnglishStopWords
def setNoSlangWords(self):
"""setter method for detecting the english slang words from the tweet text"""
tweetTokens = self.tweet["text"].split()
self.noSlangWords = len([slangWord for slangWord in tweetTokens if slangWord.lower() in self.twitter_slang or slangWord.lower() in self.internet_slang ])
def getNoSlangWords(self):
"""getter method for getting the number of english slang words detected in the tweet text"""
return self.noSlangWords
def setNoFeelingWords(self):
"""setter method for detecting the english feeling words from the tweet text text"""
tweetTokens = self.tweet["text"].split()
self.noFeelingWords = len([feelingWord for feelingWord in tweetTokens if feelingWord.lower() in self.feelingWords])
def getNoFeelingWords(self):
"""getter method for getting the number of english feeling words detected in the tweet text"""
return self.noFeelingWords
def isAscii(self,s):
"""detect if a string is Ascii or not"""
for c in s:
if c not in string.ascii_letters:
return False
return True
def getTweet(self):
"""getter method for getting the tweet"""
return self.tweet
def setTweet(self,tweet):
"""setter method for setting the tweet"""
self.tweet = tweet
def getTweetRawText(self):
"""getter method for getting the raw text of the tweet"""
return self.tweet["text"]
def setTweetRawHashTags(self):
"""setter method for setting the list of all the hashtags used in the tweet"""
self.rawHashTags = [hashTag["text"] for hashTag in self.tweet["entities"]["hashtags"]]
def getTweetRawHashTags(self):
"""getter method for getting a list of all the hashtags used in the tweet"""
return self.rawHashTags
def setNoUserMentions(self):
"""setter method for setting the number of user mentions in the tweet"""
self.noUserMentions = len(self.tweet["entities"]["user_mentions"])
def getNoUserMentions(self):
"""getter method for getting the number of user mentions in the tweet"""
return self.noUserMentions
def setNoRawHashTags(self):
"""setter method for setting the number of hashtags used in the tweet"""
self.noRawHashTags = len(self.rawHashTags)
def getNoRawHashTags(self):
"""getter method for getting the number of hashtags used in the tweet"""
return self.noRawHashTags
def setTweetUrls(self):
"""setter method for setting the list of urls used in the tweet"""
self.urls = [u["url"] for u in self.tweet["entities"]["urls"]]
def getTweetUrls(self):
"""getter method for getting the list of urls used in the tweet"""
return self.urls
def setNoOfUrls(self):
"""setter method for setting the number of urls used in the tweet"""
self.noUrls = len(self.urls)
def getNoOfUrls(self):
"""getter method for getting the number of urls used in the tweet"""
return self.noUrls
def setEnglishStopWords(self,stopwordFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\englishStopwords"):
"""setter method for setting the list of english stop words"""
englishStopwords = [lines.rstrip() for lines in open(stopwordFile)]
self.english_stopwords = englishStopwords
def getEnglishStopWords(self):
"""getter method for getting the list of english stop words"""
return self.english_stopwords
def setInternetSlangWords(self,internetSlangFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\internetSlang.txt"):
"""setter method for setting the list of general internet slang words"""
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open(internetSlangFile)]
def getInternetSlangWords(self):
"""getter method for getting the list of general internet slang words"""
return self.internet_slang
def setTwitterSlangWords(self, twitterSlangFile="C:\\Users\\cisstudent\\EIIMWorkspace\\SeenAPI\\utilFiles\\TwitterSlangList.txt"):
"""setter method for setting the list of twitter slang words published by FBI"""
self.twitter_slang = [lines.rstrip() for lines in open(twitterSlangFile)]
def getTwitterSlangWords(self):
"""getter method for getting the list of twitter slang words published by FBI"""
return self.twitter_slang
def setCleanedTweetTextTokens(self):
"""cleans tweet text and filters out all the hashtags, user mentions, and urls, also tokenizes the tweet text
filters out all the tokens that contain english stop words or contains non-ascii non alphanumeric characters,
also filters out the slang words"""
stopWords = self.english_stopwords #gets the provided english stop words
internetSlangWords = self.internet_slang #gets the provided commonly used internet slang words
twitterSlangWords = self.twitter_slang
wordTokens = self.rawTokens #splits the tweet text at whitespaces
cleanedWordList = [] #container for cleaned tokens
if wordTokens != []:
for wrd in wordTokens:
word = wrd.lower()
if word.find("#") != -1 or word.find("@") != -1 or word.find("http") != -1:
pass
else:
cleanWord = ''.join(e for e in word if e.isalpha())
if cleanWord != "" and cleanWord.lower() not in twitterSlangWords and cleanWord.lower() not in stopWords and cleanWord.lower() not in internetSlangWords and self.isAscii(cleanWord):
cleanedWordList.append(cleanWord)
self.tokens = cleanedWordList
def setTweetRawTokens(self):
"""setter method for setting the list of raw unigram tokens extracted from the tweet"""
self.rawTokens = self.tweet["text"].split()
def noOfSpecialCharacters(self):
"""setter method for setting the number of special characters used in the tweet. The characters like:
@(used for user mention), #(used for hashtags) are not counted as special characters as they have their
own significance in TwitterSphere"""
noSpecialChars = 0
for char in self.tweet["text"].encode("utf-8"):
if char == "@" or char == "#" or char == " ":
pass
else:
if char.isalnum() == False:
noSpecialChars += 1
self.noSpecialChars = noSpecialChars
def getNoOfSpecialCharacters(self):
"""getter method for getting the number of special characters used in the tweet"""
return self.noSpecialChars
def getTokenPOSTags(self):
"""getter method for annotating the tweet tokens with their corresponding POS tags. The default Penn Tree Bank POS tags
are used"""
tweetTokens = self.rawTokens
taggedTokens = pos_tag(tweetTokens)
return taggedTokens
def getNoOfArticles(self):
"""getter method for getting the number of articles of english grammar "a","an","the" detected in the tweet"""
return len([article for article in self.rawTokens if article.lower() in ["a","an","the"]])
def setNouns(self):
"""setter method for setting the list of nouns extracted from the tweet text"""
self.nouns = [noun[0].lower() for noun in self.getTokenPOSTags() if noun[1][0] == "N" and noun[0].lower() in self.tokens]
def getNouns(self):
"""getter method for getting the nouns extracted from the tweet text"""
return self.nouns
def getNoOfNouns(self):
"""getter method for getting the number of nouns extracted from the tweet"""
return len([noun for noun in self.getTokenPOSTags() if noun[1][0] == "N"])
def getNoOfAdjectives(self):
"""getter method for getting the number of adjectives extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "J"])
def getNoOfPrepositions(self):
"""getter method for getting the number of prepositions extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "IN"])
def getNoOfPronouns(self):
"""getter method for getting the number of pronouns extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1] == "PRP" or token[1] == "PRP$"])
def getNoOfVerbs(self):
"""getter method for getting the number of verbs extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "V"])
def getNoOfAdVerbs(self):
"""getter method for getting the number of adverbs extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1][0] == "R"])
def getNoOfInterjections(self):
"""getter method for getting the number of interjections extracted from the tweet"""
return len([token for token in self.getTokenPOSTags() if token[1] == "UH"])
def getTweetTextFormality(self):
"""getter method for getting the formality index of the tweet. Formality Index or F Measure of the tweet is calculated
as follows:
F-Measure = (noun frequency + adjective freq. + preposition freq. + article freq. - pronoun freq. - verb freq. - adverb freq. - interjection freq. + 100)/2
<NAME>. and <NAME>. (1999). Formality of language: definition, measurement
and behavioral determinants. Technical report, Free University of Brussels."""
tweetTokens = self.tweet["text"].split()
if len(tweetTokens) == 0:
formalityIndex = 0.0
else:
formalityIndex = float(((self.getNoOfNouns()+self.getNoOfAdjectives()+self.getNoOfPrepositions()+self.getNoOfArticles())-(self.getNoOfPronouns()+self.getNoOfVerbs()+self.getNoOfAdVerbs()+self.getNoOfInterjections()))+100.0)/2.0
return formalityIndex
def setTweetLength(self):
"""setter method for setting the length of the tweet, which is the number of characters in the tweet"""
self.tweetLength = len(self.tweet["text"])
def getTweetLength(self):
"""getter method for getting the length of the tweet"""
return self.tweetLength
def setNoUniqueChars(self):
"""setter method for setting the number of unique characters in the tweet"""
self.noUniqueChars = len(set(self.tweet["text"]))
def getNoUniqueChars(self):
"""getter method for getting the number of unique characters in the tweet"""
return self.noUniqueChars
def generateHashValue(self,tweetStr):
"""method for generating md5 code for a given string 'str'"""
hash_object = hashlib.md5(tweetStr)
return hash_object.hexdigest()
def setTweetHashValue(self):
"""setter method for setting md5 hash value of the tweet text"""
tweetWords = "".join(self.tokens)
self.tweetHashValue = self.generateHashValue(tweetWords)
def getTweetHashValue(self):
"""getter method for getting the hash value of a tweet"""
return self.tweetHashValue
def isTweetVerified(self):
"""sets the value to 1 if the tweet comes from a verified source else 0"""
if self.tweet["user"]["verified"] == True:
self.isVerified = 1
else:
self.isVerified = 0
def getTweetVerified(self):
"""getter method to get if the tweet is verified or not"""
return self.isVerified
def tweetHasUrl(self):
"""setter method for hasUrl. If tweet has url then 1 else 0"""
if self.urls != []:
self.hasUrl = 1
else:
self.hasUrl = 0
def getCreatedTime(self):
"""gets the tweets post time in python datetime format"""
return datetime.strptime(self.tweet["created_at"], '%a %b %d %H:%M:%S +0000 %Y')
def setRetweetCount(self):
"""setter method for setting the number of times a tweet is retweeted"""
retweetCount = 0
if "retweeted_status" in self.tweet:
retweetCount = self.tweet["retweeted_status"]["retweet_count"]
self.retweetCount = retweetCount
# self.retweetCount = self.tweet["retweet_count"]
def getRetweetCount(self):
"""getter method for getting the retweet count of a tweet"""
return self.retweetCount
def setFavoriteCount(self):
"""setter method for setting the number of favorite counts for the tweet"""
favoriteCount = 0
if "retweeted_status" in self.tweet:
favoriteCount = self.tweet["retweeted_status"]["favorite_count"]
self.favoriteCount = favoriteCount
# self.favoriteCount = self.tweet["favorite_count"]
def getFavoriteCount(self):
"""getter method for getting the favorite count of the tweet"""
return self.favoriteCount
def setNoOfTokens(self):
"""setter method for setting the number of tokens extracted from the tweet"""
self.noTokens = len(self.tokens)
def getNoOfTokens(self):
"""getter method for getting the number of tokens extracted from the tweet"""
return self.noTokens
def setTweetFeatureDict(self):
""""sets the feature dictionary for the tweet"""
self.featureDict = {"tweetUrls":self.getTweetUrls(),"md5Hash":self.getTweetHashValue(),"createdTime":self.getCreatedTime(),"tokens":self.tokens,"nouns":self.nouns,"favoriteCount":self.getFavoriteCount(),"retweetCount":self.getRetweetCount(),"formality":self.getTweetTextFormality(),"isTweetVerified":self.getTweetVerified(),"hasUrl":self.hasUrl,"noWords":self.getNoOfTokens(),"noStopWords":self.getNoEnglishStopWords(),"noFeelingWords":self.getNoFeelingWords(),"noSlangWords":self.getNoSlangWords(),"noHashTags":self.getNoRawHashTags(),"noUserMentions":self.getNoUserMentions(),"tweetLen":self.getTweetLength(),"noUrls":self.getNoOfUrls(),"uniqueChars":self.getNoUniqueChars(),"noSpecialChars":self.getNoOfSpecialCharacters()}
def getTweetFeatureDict(self):
"""getter method for getting the tweet's features"""
return self.featureDict
def getDataInstanceForClassification(self):
"""getter method for getting the features of a tweet for initial classification as informative/non-informative"""
dataInstance = [1.0]
if self.featureDict["noUrls"] > 0:
dataInstance.append(float(1.0))
else:
dataInstance.append(float(0.0))
dataInstance.append(float(self.featureDict["noWords"])/20.0)
dataInstance.append(float(self.featureDict["noStopWords"])/21.0)
dataInstance.append(float(self.featureDict["noFeelingWords"])/7.0)
dataInstance.append(float(self.featureDict["noSlangWords"])/7.0)
dataInstance.append(float(self.featureDict["noHashTags"])/17.0)
dataInstance.append(float(self.featureDict["noUserMentions"])/8.0)
dataInstance.append(float(self.featureDict["noUrls"])/3.0)
dataInstance.append(float(self.featureDict["tweetLen"])/140.0)
dataInstance.append(float(self.featureDict["uniqueChars"])/140.0)
dataInstance.append(float(self.featureDict["noSpecialChars"])/140.0)
dataInstance.append(float(self.featureDict["favoriteCount"])/13802.0)
dataInstance.append(float(self.featureDict["retweetCount"])/41633.0)
dataInstance.append(float(self.featureDict["formality"])/63.5)
dataInstance.append(float(self.featureDict["isTweetVerified"]))
return dataInstance
class LoadSlang:
"""class for loading and getting the slang words to be filtered out during processing of tweets"""
def __init__(self):
#english stopwords, gets the english stopwords from the file: "englishStopWords" stored in utilFiles folder
self.english_stopwords = [lines.rstrip() for lines in open("..\\Resources\\englishStopwords")]
#list of slang words used in twitter, gets the twitter slang words from the file: "TwitterSlangList.txt" stored in utilFiles folder
self.twitter_slang = [lines.rstrip() for lines in open("..\\Resources\\TwitterSlangList.txt")]
#general internet slang words, gets the general internet slang words from the file: "internetSlang.txt" stored in utilFiles folder
self.internet_slang = [lines.rstrip().split(":")[0].lower() for lines in open("..\\Resources\\internetSlang.txt")]
#masterList
self.slangWords = self.english_stopwords+self.twitter_slang+self.internet_slang
def getSlang(self):
"""getter method for getting a list of slang words to be filtered out from the tweet text"""
return self.slangWords | 0.41941 | 0.129375 |
import random
class TaskDistributions:
EXP_TASKS, EXP_JOBS, CONSTANT = range(3)
class Job(object):
job_count = 0
def __init__(self, num_tasks, start_time, task_distribution, median_task_duration, scheduler=0):
self.id = Job.job_count
Job.job_count += 1
self.num_tasks = num_tasks
self.completed_tasks_count = 0
self.start_time = start_time
self.end_time = start_time
self.unscheduled_tasks = []
# TODO: This won't be correctly populated when tasks are stolen.
self.time_all_tasks_scheduled = 0
self.last_probe_reply_time= 0
# Change this line to change to distribution of task durations.
if task_distribution == TaskDistributions.EXP_TASKS:
self.exponentially_distributed_tasks(median_task_duration)
elif task_distribution == TaskDistributions.EXP_JOBS:
self.exponentially_distributed_jobs(median_task_duration)
elif task_distribution == TaskDistributions.CONSTANT:
self.constant_distributed_tasks(median_task_duration)
self.longest_task = max(self.unscheduled_tasks)
self.scheduler = scheduler
self.probed_workers = set()
def add_probe_response(self, worker, current_time):
self.probed_workers.remove(worker.id)
assert current_time >= self.last_probe_reply_time
self.last_probe_reply_time = current_time
if len(self.unscheduled_tasks) > 0:
assert current_time >= self.time_all_tasks_scheduled
self.time_all_tasks_scheduled = current_time
def task_completed(self, completion_time):
""" Returns true if the job has completed, and false otherwise. """
self.completed_tasks_count += 1
self.end_time = max(completion_time, self.end_time)
assert self.completed_tasks_count <= self.num_tasks
return self.num_tasks == self.completed_tasks_count
def exponentially_distributed_tasks(self, median_task_duration):
while len(self.unscheduled_tasks) < self.num_tasks:
# Exponentially distributed task durations.
self.unscheduled_tasks.append(random.expovariate(1.0 / median_task_duration))
def exponentially_distributed_jobs(self, median_task_duration):
# Choose one exponentially-distributed task duration for all tasks in the job.
task_duration = random.expovariate(1.0 / median_task_duration)
while len(self.unscheduled_tasks) < self.num_tasks:
self.unscheduled_tasks.append(task_duration)
def constant_distributed_tasks(self, median_task_duration):
while len(self.unscheduled_tasks) < self.num_tasks:
self.unscheduled_tasks.append(median_task_duration) | simulation/util.py |
import random
class TaskDistributions:
EXP_TASKS, EXP_JOBS, CONSTANT = range(3)
class Job(object):
job_count = 0
def __init__(self, num_tasks, start_time, task_distribution, median_task_duration, scheduler=0):
self.id = Job.job_count
Job.job_count += 1
self.num_tasks = num_tasks
self.completed_tasks_count = 0
self.start_time = start_time
self.end_time = start_time
self.unscheduled_tasks = []
# TODO: This won't be correctly populated when tasks are stolen.
self.time_all_tasks_scheduled = 0
self.last_probe_reply_time= 0
# Change this line to change to distribution of task durations.
if task_distribution == TaskDistributions.EXP_TASKS:
self.exponentially_distributed_tasks(median_task_duration)
elif task_distribution == TaskDistributions.EXP_JOBS:
self.exponentially_distributed_jobs(median_task_duration)
elif task_distribution == TaskDistributions.CONSTANT:
self.constant_distributed_tasks(median_task_duration)
self.longest_task = max(self.unscheduled_tasks)
self.scheduler = scheduler
self.probed_workers = set()
def add_probe_response(self, worker, current_time):
self.probed_workers.remove(worker.id)
assert current_time >= self.last_probe_reply_time
self.last_probe_reply_time = current_time
if len(self.unscheduled_tasks) > 0:
assert current_time >= self.time_all_tasks_scheduled
self.time_all_tasks_scheduled = current_time
def task_completed(self, completion_time):
""" Returns true if the job has completed, and false otherwise. """
self.completed_tasks_count += 1
self.end_time = max(completion_time, self.end_time)
assert self.completed_tasks_count <= self.num_tasks
return self.num_tasks == self.completed_tasks_count
def exponentially_distributed_tasks(self, median_task_duration):
while len(self.unscheduled_tasks) < self.num_tasks:
# Exponentially distributed task durations.
self.unscheduled_tasks.append(random.expovariate(1.0 / median_task_duration))
def exponentially_distributed_jobs(self, median_task_duration):
# Choose one exponentially-distributed task duration for all tasks in the job.
task_duration = random.expovariate(1.0 / median_task_duration)
while len(self.unscheduled_tasks) < self.num_tasks:
self.unscheduled_tasks.append(task_duration)
def constant_distributed_tasks(self, median_task_duration):
while len(self.unscheduled_tasks) < self.num_tasks:
self.unscheduled_tasks.append(median_task_duration) | 0.375363 | 0.304436 |
from collections import defaultdict
from decr_prob_counter import DecreasingProbCounter
from exact_counter import ExactCounter
from fixed_prob_counter import FixedProbCounter
import time
from math import sqrt
from tabulate import tabulate
from utils import *
import matplotlib.pyplot as plt
class Test():
def __init__(self, fname="datasets/it_book.txt", rep=1000, k=10):
self.fname = fname
self.rep = rep
self.k = k
self.run_test()
def run_test(self):
exact_counter, fixed_prob_counter, decr_prob_counter =\
ExactCounter(self.fname), FixedProbCounter(self.fname), DecreasingProbCounter(self.fname)
self.get_stats(exact_counter, exact_counter=True)
self.get_stats(fixed_prob_counter)
self.get_stats(decr_prob_counter)
def get_stats(self, counter, exact_counter=False):
print(f"{counter}\n")
total_time, total_means, total_countings, total_estimated_events,\
total_alp_size, total_min_events, total_max_events =\
0, 0, 0, 0, 0, 0, 0,
total_letter_occur = defaultdict(lambda: [])
plot_data = [[], [], []]
for i in range(self.rep):
tic = time.time()
counter.count()
total_time += time.time() - tic
if not exact_counter:
counter.estimate_events()
total_countings += sum(counter.letter_occur.values())
total_alp_size += len(counter.letter_occur)
total_estimated_events += sum(counter.estimated_letter_occur.values())
total_min_events += min(counter.estimated_letter_occur.values())
total_max_events += max(counter.estimated_letter_occur.values())
total_means += calc_mean(counter.estimated_letter_occur.values())
merge_dicts(total_letter_occur, counter.estimated_letter_occur)
rep = i + 1
plot_data[0].append(rep)
plot_data[1].append(abs(self.total_events - (total_estimated_events / rep)) / self.total_events * 100)
rel_errors = [abs(sum(occur) / rep - self.exact_letter_occur[letter]) for letter, occur in total_letter_occur.items()]
avg_rel_errors = sum(rel_errors) / len(rel_errors)
plot_data[2].append(avg_rel_errors)
avg_time = round(total_time / self.rep, 3)
data = [["Counting Time (s)", avg_time], ["Alphabet Size"], ["Events"], ["Mean"], ["Minimum"], ["Maximum"]]
headers = ["Measure", "Value"]
if exact_counter:
self.exact_letter_occur = counter.letter_occur
self.exact_top_k_letters = counter.top_k_letters(self.k)
self.k = len(self.exact_top_k_letters)
self.alphabet_size = len(counter.letter_occur)
self.total_events = total_countings = sum(counter.letter_occur.values())
self.mean = mean = calc_mean(counter.letter_occur.values())
self.min_events = min_events = min(counter.letter_occur.values())
self.max_events = max_events = max(counter.letter_occur.values())
data[1].append(self.alphabet_size)
data[2].append(round(self.total_events, 2))
data[3].append(round(self.mean, 2))
data[4].append(round(self.min_events, 2))
data[5].append(round(self.max_events, 2))
else:
headers.extend(["Absolute Error", "Relative Error (%)"])
headers.extend([["Absolute Error"], ["Relative Error (%)"]])
total_alp_size = round(total_alp_size / self.rep, 2)
total_countings = round(total_countings / self.rep, 2)
total_events = round(total_estimated_events / self.rep, 2)
mean = round(total_means / self.rep, 2)
min_events = round(total_min_events / self.rep, 2)
max_events = round(total_max_events / self.rep, 2)
common_top_k_letters = most_frequent(total_letter_occur, self.k)
data[0].extend(['-', '-'])
data[1].extend([total_alp_size, round(abs(self.alphabet_size - total_alp_size), 2),
round(abs(self.alphabet_size - total_alp_size) / self.alphabet_size * 100, 2)])
data[2].extend([total_events, round(abs(self.total_events - total_events), 2),
round(abs(self.total_events - total_events) / self.total_events * 100, 2)])
data[3].extend([mean, round(abs(self.mean - mean), 2),
round(abs(self.mean - mean) / self.mean * 100, 2)])
data[4].extend([min_events, round(abs(self.min_events - min_events), 2),
round(abs(self.min_events - min_events) / self.min_events * 100, 2)])
data[5].extend([max_events, round(abs(self.max_events - max_events), 2),
round(abs(self.max_events - max_events) / self.max_events * 100, 2)])
print(f"Results for {self.rep} repetition{'s' if self.rep != 1 else ''}:")
print(f"Total Elapsed Time: {round(total_time, 3)} s\nTotal Events Counted: {total_countings}")
print("\nAverage Values for a Repetition:")
print(tabulate(data, headers=headers))
print(f"\nTop {self.k} Most Frequent Letters:")
if exact_counter:
print(tabulate(self.exact_top_k_letters.items(), headers=["Letter", "Exact Events"]))
else:
relative_precision, right_position_letters = 0, 0
exact_top_k_letters = list(self.exact_top_k_letters.keys())
headers = ["Letter", "Min", "Max", "Mean", "Mean Absolute Error", "Mean Relative Error (%)"]
data = []
for i, letter_occur in enumerate(common_top_k_letters.items()):
letter, occur = letter_occur
mean_occur = calc_mean(occur)
abs_error = abs(self.exact_letter_occur[letter] - mean_occur)
rel_error = round(abs_error / self.exact_letter_occur[letter] * 100, 2)
if self.rep > 1:
variance = calc_variance(occur, mean=mean_occur)
std_dvt = sqrt(variance)
headers.extend(["Variance", "Standard Deviation"])
data.append([letter, min(occur), max(occur), mean_occur, abs_error, rel_error, variance, std_dvt])
else:
data.append([letter, min(occur), max(occur), mean_occur, abs_error, rel_error])
if letter == exact_top_k_letters[i]:
right_position_letters += 1
relative_precision += right_position_letters / (i + 1)
print(tabulate(data, headers=headers))
avg_relative_precision = relative_precision / self.k * 100
TP = len([letter for letter in common_top_k_letters.keys() if letter in self.exact_top_k_letters.keys()])
FP = self.k - TP
TN = self.alphabet_size - self.k - FP
precision = TP / self.k * 100
accuracy = (TP + TN) / self.alphabet_size * 100
# recall not appropriate since it is evaluated top n most frequent letters
print(f"Accuracy: {accuracy:.2f} %")
print(f"Precision: {precision:.2f} %")
print(f"Average Precision (relative order): {avg_relative_precision:.2f} %")
if self.rep > 1:
plt.plot(plot_data[0], plot_data[1], label="Total Events Relative Error")
plt.ylabel("Relative Error (%)")
plt.xlabel("Repetition")
plt.title(counter)
plt.legend()
plt.show()
plt.plot(plot_data[0], plot_data[2], label="Mean Relative Error")
plt.ylabel("Relative Error (%)")
plt.xlabel("Repetition")
plt.title(counter)
plt.legend()
plt.show()
print("\n") | src/tests.py | from collections import defaultdict
from decr_prob_counter import DecreasingProbCounter
from exact_counter import ExactCounter
from fixed_prob_counter import FixedProbCounter
import time
from math import sqrt
from tabulate import tabulate
from utils import *
import matplotlib.pyplot as plt
class Test():
def __init__(self, fname="datasets/it_book.txt", rep=1000, k=10):
self.fname = fname
self.rep = rep
self.k = k
self.run_test()
def run_test(self):
exact_counter, fixed_prob_counter, decr_prob_counter =\
ExactCounter(self.fname), FixedProbCounter(self.fname), DecreasingProbCounter(self.fname)
self.get_stats(exact_counter, exact_counter=True)
self.get_stats(fixed_prob_counter)
self.get_stats(decr_prob_counter)
def get_stats(self, counter, exact_counter=False):
print(f"{counter}\n")
total_time, total_means, total_countings, total_estimated_events,\
total_alp_size, total_min_events, total_max_events =\
0, 0, 0, 0, 0, 0, 0,
total_letter_occur = defaultdict(lambda: [])
plot_data = [[], [], []]
for i in range(self.rep):
tic = time.time()
counter.count()
total_time += time.time() - tic
if not exact_counter:
counter.estimate_events()
total_countings += sum(counter.letter_occur.values())
total_alp_size += len(counter.letter_occur)
total_estimated_events += sum(counter.estimated_letter_occur.values())
total_min_events += min(counter.estimated_letter_occur.values())
total_max_events += max(counter.estimated_letter_occur.values())
total_means += calc_mean(counter.estimated_letter_occur.values())
merge_dicts(total_letter_occur, counter.estimated_letter_occur)
rep = i + 1
plot_data[0].append(rep)
plot_data[1].append(abs(self.total_events - (total_estimated_events / rep)) / self.total_events * 100)
rel_errors = [abs(sum(occur) / rep - self.exact_letter_occur[letter]) for letter, occur in total_letter_occur.items()]
avg_rel_errors = sum(rel_errors) / len(rel_errors)
plot_data[2].append(avg_rel_errors)
avg_time = round(total_time / self.rep, 3)
data = [["Counting Time (s)", avg_time], ["Alphabet Size"], ["Events"], ["Mean"], ["Minimum"], ["Maximum"]]
headers = ["Measure", "Value"]
if exact_counter:
self.exact_letter_occur = counter.letter_occur
self.exact_top_k_letters = counter.top_k_letters(self.k)
self.k = len(self.exact_top_k_letters)
self.alphabet_size = len(counter.letter_occur)
self.total_events = total_countings = sum(counter.letter_occur.values())
self.mean = mean = calc_mean(counter.letter_occur.values())
self.min_events = min_events = min(counter.letter_occur.values())
self.max_events = max_events = max(counter.letter_occur.values())
data[1].append(self.alphabet_size)
data[2].append(round(self.total_events, 2))
data[3].append(round(self.mean, 2))
data[4].append(round(self.min_events, 2))
data[5].append(round(self.max_events, 2))
else:
headers.extend(["Absolute Error", "Relative Error (%)"])
headers.extend([["Absolute Error"], ["Relative Error (%)"]])
total_alp_size = round(total_alp_size / self.rep, 2)
total_countings = round(total_countings / self.rep, 2)
total_events = round(total_estimated_events / self.rep, 2)
mean = round(total_means / self.rep, 2)
min_events = round(total_min_events / self.rep, 2)
max_events = round(total_max_events / self.rep, 2)
common_top_k_letters = most_frequent(total_letter_occur, self.k)
data[0].extend(['-', '-'])
data[1].extend([total_alp_size, round(abs(self.alphabet_size - total_alp_size), 2),
round(abs(self.alphabet_size - total_alp_size) / self.alphabet_size * 100, 2)])
data[2].extend([total_events, round(abs(self.total_events - total_events), 2),
round(abs(self.total_events - total_events) / self.total_events * 100, 2)])
data[3].extend([mean, round(abs(self.mean - mean), 2),
round(abs(self.mean - mean) / self.mean * 100, 2)])
data[4].extend([min_events, round(abs(self.min_events - min_events), 2),
round(abs(self.min_events - min_events) / self.min_events * 100, 2)])
data[5].extend([max_events, round(abs(self.max_events - max_events), 2),
round(abs(self.max_events - max_events) / self.max_events * 100, 2)])
print(f"Results for {self.rep} repetition{'s' if self.rep != 1 else ''}:")
print(f"Total Elapsed Time: {round(total_time, 3)} s\nTotal Events Counted: {total_countings}")
print("\nAverage Values for a Repetition:")
print(tabulate(data, headers=headers))
print(f"\nTop {self.k} Most Frequent Letters:")
if exact_counter:
print(tabulate(self.exact_top_k_letters.items(), headers=["Letter", "Exact Events"]))
else:
relative_precision, right_position_letters = 0, 0
exact_top_k_letters = list(self.exact_top_k_letters.keys())
headers = ["Letter", "Min", "Max", "Mean", "Mean Absolute Error", "Mean Relative Error (%)"]
data = []
for i, letter_occur in enumerate(common_top_k_letters.items()):
letter, occur = letter_occur
mean_occur = calc_mean(occur)
abs_error = abs(self.exact_letter_occur[letter] - mean_occur)
rel_error = round(abs_error / self.exact_letter_occur[letter] * 100, 2)
if self.rep > 1:
variance = calc_variance(occur, mean=mean_occur)
std_dvt = sqrt(variance)
headers.extend(["Variance", "Standard Deviation"])
data.append([letter, min(occur), max(occur), mean_occur, abs_error, rel_error, variance, std_dvt])
else:
data.append([letter, min(occur), max(occur), mean_occur, abs_error, rel_error])
if letter == exact_top_k_letters[i]:
right_position_letters += 1
relative_precision += right_position_letters / (i + 1)
print(tabulate(data, headers=headers))
avg_relative_precision = relative_precision / self.k * 100
TP = len([letter for letter in common_top_k_letters.keys() if letter in self.exact_top_k_letters.keys()])
FP = self.k - TP
TN = self.alphabet_size - self.k - FP
precision = TP / self.k * 100
accuracy = (TP + TN) / self.alphabet_size * 100
# recall not appropriate since it is evaluated top n most frequent letters
print(f"Accuracy: {accuracy:.2f} %")
print(f"Precision: {precision:.2f} %")
print(f"Average Precision (relative order): {avg_relative_precision:.2f} %")
if self.rep > 1:
plt.plot(plot_data[0], plot_data[1], label="Total Events Relative Error")
plt.ylabel("Relative Error (%)")
plt.xlabel("Repetition")
plt.title(counter)
plt.legend()
plt.show()
plt.plot(plot_data[0], plot_data[2], label="Mean Relative Error")
plt.ylabel("Relative Error (%)")
plt.xlabel("Repetition")
plt.title(counter)
plt.legend()
plt.show()
print("\n") | 0.501953 | 0.309324 |
import frida
import sys
import time
import os
import codecs
def on_message(message, data):
if message['type'] == 'send':
print("[*] {0}".format(message['payload']))
else:
print(message)
def loadJSScript(filePath):
source = ''
script_dir = os.path.dirname(os.path.realpath(__file__))
JSHookFile = os.path.join(script_dir, filePath)
with codecs.open(JSHookFile, 'r', 'utf-8') as f:
source = source + f.read()
return source
#/art/runtime/dex/art_dex_file_loader.cc on android 9
#std::unique_ptr<DexFile> ArtDexFileLoader::OpenCommon(const uint8_t* base,
# size_t size,
# const uint8_t* data_base,
# size_t data_size,
# const std::string& location,
# uint32_t location_checksum,
# const OatDexFile* oat_dex_file,
# bool verify,
# bool verify_checksum,
# std::string* error_msg,
# std::unique_ptr<DexFileContainer> container,
# VerifyResult* verify_result)
def do_hook():
hook_script = '''
XLOG("Init Android Native Frida Hook!");
var funcName = "_ZN3art13DexFileLoader10OpenCommonEPKhjS2_jRKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEjPKNS_10OatDexFileEbbPS9_NS3_10unique_ptrINS_16DexFileContainerENS3_14default_deleteISH_EEEEPNS0_12VerifyResultE";
xia0NativeHook("libart.so", funcName, function (){
if(Memory.readU32(args[1]) == DEX_MAGIC) {
dexrec.push(args[1]);
}
},function (){
XLOG(" I am in onLeave");
});
Java.perform(function(){
var hookClass = Java.use("android.os.ServiceManager");
XLOG("Inited Android Java Frida Hook! Waiting for triggle");
});
'''
source = loadJSScript('../androidFridaLib.js')
return hook_script + source
app_package = "com.lvse.juren"
device = frida.get_remote_device()
pid = device.spawn(app_package)
session = device.attach(pid)
script = session.create_script(do_hook())
script.on("message", on_message)
script.load()
sys.stdin.read() | Android/sample/android-app-dexdump.py | import frida
import sys
import time
import os
import codecs
def on_message(message, data):
if message['type'] == 'send':
print("[*] {0}".format(message['payload']))
else:
print(message)
def loadJSScript(filePath):
source = ''
script_dir = os.path.dirname(os.path.realpath(__file__))
JSHookFile = os.path.join(script_dir, filePath)
with codecs.open(JSHookFile, 'r', 'utf-8') as f:
source = source + f.read()
return source
#/art/runtime/dex/art_dex_file_loader.cc on android 9
#std::unique_ptr<DexFile> ArtDexFileLoader::OpenCommon(const uint8_t* base,
# size_t size,
# const uint8_t* data_base,
# size_t data_size,
# const std::string& location,
# uint32_t location_checksum,
# const OatDexFile* oat_dex_file,
# bool verify,
# bool verify_checksum,
# std::string* error_msg,
# std::unique_ptr<DexFileContainer> container,
# VerifyResult* verify_result)
def do_hook():
hook_script = '''
XLOG("Init Android Native Frida Hook!");
var funcName = "_ZN3art13DexFileLoader10OpenCommonEPKhjS2_jRKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEjPKNS_10OatDexFileEbbPS9_NS3_10unique_ptrINS_16DexFileContainerENS3_14default_deleteISH_EEEEPNS0_12VerifyResultE";
xia0NativeHook("libart.so", funcName, function (){
if(Memory.readU32(args[1]) == DEX_MAGIC) {
dexrec.push(args[1]);
}
},function (){
XLOG(" I am in onLeave");
});
Java.perform(function(){
var hookClass = Java.use("android.os.ServiceManager");
XLOG("Inited Android Java Frida Hook! Waiting for triggle");
});
'''
source = loadJSScript('../androidFridaLib.js')
return hook_script + source
app_package = "com.lvse.juren"
device = frida.get_remote_device()
pid = device.spawn(app_package)
session = device.attach(pid)
script = session.create_script(do_hook())
script.on("message", on_message)
script.load()
sys.stdin.read() | 0.067171 | 0.05301 |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from pylab import *
from netCDF4 import Dataset
import datetime
__author__ = '<NAME>'
__email__ = '<EMAIL>'
__created__ = datetime.datetime(2012, 8, 20)
__modified__ = datetime.datetime(2014, 2, 11)
__version__ = "1.0"
__status__ = "Development, 20.8.2012, 9.7.2013, 16.7.2013, 11.2.2014"
doc ="""This script reads the output of running ROMS and plots defined variables
at z-levels using pyroms.
"""
def contourMap(myCDFU,myCDFV):
"""Get the apporporiate grid"""
tlat = myCDFU.variables["lat"][:]
tlon = myCDFU.variables["lon"][:]
mydataU = np.squeeze(myCDFU.variables['u_eastward'][:]) * 100.
mydataV = np.squeeze(myCDFV.variables['v_northward'][:]) * 100.
print "U:",mydataU.min(), mydataU.max()
print "V:",mydataV.min(), mydataV.max()
mydata = np.sqrt(mydataU**2 + mydataV**2)
plt.figure(figsize=(10,10), frameon=False)
map = Basemap(llcrnrlon=-18.0,
llcrnrlat=46.0,
urcrnrlon=25.5,
urcrnrlat=67.5,
resolution='l',projection='tmerc',lon_0=0,lat_0=50,area_thresh=200.)
delta=20
levels = np.arange(-60,60,10)
x, y = map(tlon,tlat)
map.drawcoastlines()
map.fillcontinents(color='grey')
map.drawcountries()
map.drawmapboundary()
# map.drawmeridians(np.arange(0,360,1))
# map.drawparallels(np.arange(0,90,1))
# mymaskeddata = np.ma.masked_values(mydata,mymask)
CS1 = map.contourf(x,y,mydataV,levels,cmap=cm.get_cmap('RdBu_r',len(levels)-1) )#,alpha=0.5)
delta=2
# map.quiver(tlon[::delta,::delta],
# tlat[::delta,::delta],
# mydataU[::delta,::delta],
# mydataV[::delta,::delta],
# scale=2500,color='#000099',
# latlon=True)
plt.colorbar(CS1,orientation='vertical',extend='both', shrink=0.5)
plotfile='figures/quiver_climatology.png'
plt.savefig(plotfile,bbox_inches='tight')
plt.show()
plt.close()
"""" ------------------------------------------------------------------
MAIN
<NAME>, 09.07.2013, 11.02.2014
<EMAIL>
------------------------------------------------------------------
"""
doc="""This script reads the output from running createAveragesOnHexagon_part2.py"""
depth='10'
season='all'
myfileU = 'northsea_8km_timmean_u_eastward_depth_'+str(depth)+'_season_'+str(season)+'.nc'
myfileV = 'northsea_8km_timmean_v_northward_depth_'+str(depth)+'_season_'+str(season)+'.nc'
myCDFU=Dataset(myfileU)
myCDFV=Dataset(myfileV)
contourMap(myCDFU, myCDFV)
myCDFU.close()
myCDFV.close() | TimeseriesAndDomainAnalysis/createOceanCurrentMaps.py | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from pylab import *
from netCDF4 import Dataset
import datetime
__author__ = '<NAME>'
__email__ = '<EMAIL>'
__created__ = datetime.datetime(2012, 8, 20)
__modified__ = datetime.datetime(2014, 2, 11)
__version__ = "1.0"
__status__ = "Development, 20.8.2012, 9.7.2013, 16.7.2013, 11.2.2014"
doc ="""This script reads the output of running ROMS and plots defined variables
at z-levels using pyroms.
"""
def contourMap(myCDFU,myCDFV):
"""Get the apporporiate grid"""
tlat = myCDFU.variables["lat"][:]
tlon = myCDFU.variables["lon"][:]
mydataU = np.squeeze(myCDFU.variables['u_eastward'][:]) * 100.
mydataV = np.squeeze(myCDFV.variables['v_northward'][:]) * 100.
print "U:",mydataU.min(), mydataU.max()
print "V:",mydataV.min(), mydataV.max()
mydata = np.sqrt(mydataU**2 + mydataV**2)
plt.figure(figsize=(10,10), frameon=False)
map = Basemap(llcrnrlon=-18.0,
llcrnrlat=46.0,
urcrnrlon=25.5,
urcrnrlat=67.5,
resolution='l',projection='tmerc',lon_0=0,lat_0=50,area_thresh=200.)
delta=20
levels = np.arange(-60,60,10)
x, y = map(tlon,tlat)
map.drawcoastlines()
map.fillcontinents(color='grey')
map.drawcountries()
map.drawmapboundary()
# map.drawmeridians(np.arange(0,360,1))
# map.drawparallels(np.arange(0,90,1))
# mymaskeddata = np.ma.masked_values(mydata,mymask)
CS1 = map.contourf(x,y,mydataV,levels,cmap=cm.get_cmap('RdBu_r',len(levels)-1) )#,alpha=0.5)
delta=2
# map.quiver(tlon[::delta,::delta],
# tlat[::delta,::delta],
# mydataU[::delta,::delta],
# mydataV[::delta,::delta],
# scale=2500,color='#000099',
# latlon=True)
plt.colorbar(CS1,orientation='vertical',extend='both', shrink=0.5)
plotfile='figures/quiver_climatology.png'
plt.savefig(plotfile,bbox_inches='tight')
plt.show()
plt.close()
"""" ------------------------------------------------------------------
MAIN
<NAME>, 09.07.2013, 11.02.2014
<EMAIL>
------------------------------------------------------------------
"""
doc="""This script reads the output from running createAveragesOnHexagon_part2.py"""
depth='10'
season='all'
myfileU = 'northsea_8km_timmean_u_eastward_depth_'+str(depth)+'_season_'+str(season)+'.nc'
myfileV = 'northsea_8km_timmean_v_northward_depth_'+str(depth)+'_season_'+str(season)+'.nc'
myCDFU=Dataset(myfileU)
myCDFV=Dataset(myfileV)
contourMap(myCDFU, myCDFV)
myCDFU.close()
myCDFV.close() | 0.402862 | 0.35869 |
import random, json
from colorful.fields import RGBColorField
from django.contrib.auth.models import User
from django.core.urlresolvers import reverse
from django.db import models
from django.utils import timezone
from django_redis import get_redis_connection
BEST_COLOURS = (
"#1b85b8",
"#03c03c",
"#559e83",
"#ae5a41",
"#c3cb71",
"#c23b22",
"#ffb347",
"#f49ac2",
"#dea5a4",
"#e3e387",
"#77dd77",
"#b19cd9",
"#ffd1dc",
"#779ecb",
"#cb99c9",
"#966fd6"
)
def best_colour():
return random.choice(BEST_COLOURS)
def best_hug():
return HugKind.objects.order_by('?')[0]
class Pronoun(models.Model):
subject = models.CharField(max_length=20)
object = models.CharField(max_length=20)
possessive_determiner = models.CharField(max_length=20)
possessive_pronoun = models.CharField(max_length=20)
reflexive = models.CharField(max_length=25)
def __str__(self):
return "/".join(
(self.subject, self.object, self.possessive_determiner, self.possessive_pronoun, self.reflexive))
class Userware(models.Model):
user = models.OneToOneField(User, related_name="userware")
daily_notifications = models.BooleanField(default=True, help_text="Those will be sent to your email no more often" +
" than once a day, at 13:37 server time.")
hourly_notifications = models.BooleanField(default=False, help_text="Those will be sent to your email no more oft" +
"en than once per hour.")
news_emails = models.BooleanField(default=True, help_text="Those will be sent whenever I have something to announ" +
"ce, which probably won't be too often.")
colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
pronoun = models.ForeignKey(Pronoun, related_name="pronouns",
help_text="Is your pronoun missing? Shoot an email " +
"at <EMAIL> and we'll look into it!")
followers = models.ManyToManyField('self', blank=True, related_name="following")
hugs_to_notify = models.ManyToManyField('Hug', blank=True)
def __str__(self):
return self.user.get_username()
def hugs_come_and_gone(self):
return Hug.objects.filter(models.Q(source=self.user) | models.Q(target=self.user)).order_by('-timestamp')
def get_absolute_url(self):
return reverse("user_page", kwargs=dict(username=self.user.username))
class Follow(models.Model):
source = models.ForeignKey(User, related_name="following")
target = models.ForeignKey(User, related_name="followers")
timestamp = models.DateTimeField(default=timezone.now)
def __str__(self):
return "%s -> %s" % (self.source, self.target)
class Meta:
unique_together = ('source', 'target'),
class HugKind(models.Model):
name = models.CharField(max_length=20, db_index=True)
verb = models.CharField(max_length=20, db_index=True)
verb_tercery = models.CharField(max_length=20)
past = models.CharField(max_length=30)
def serialize(self) -> dict:
return dict(noun=self.name, verb=self.verb, verb_third=self.verb_tercery, verb_past=self.past)
def __str__(self):
return self.name
class Hug(models.Model):
source = models.ForeignKey(User, db_index=True, related_name="hugs_given")
source_colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
target = models.ForeignKey(User, db_index=True, related_name="hugs_gotten")
target_colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
kind = models.ForeignKey(HugKind, db_index=True, related_name="hugs")
inspiration = models.ForeignKey('self', null=True, blank=True, related_name="kids")
timestamp = models.DateTimeField(default=timezone.now)
def serialize(self) -> dict:
return dict(id=self.pk, source=self.source.username, target=self.target.username, source_colour=self.source_colour, target_colour=self.target_colour, kind=self.kind.serialize(), inspiration=self.inspiration.pk if self.inspiration else None)
def publish(self):
red = get_redis_connection("default")
serial = dict(channel="global", content=self.serialize())
red.publish("hugs", json.dumps(serial))
for subber in User.objects.only('username').filter(models.Q(pk=self.target.pk)|models.Q(pk=self.source.pk)|models.Q(following__target=self.target)|models.Q(following__target=self.source)).distinct():
serial["channel"] = subber.username
red.publish("hugs", json.dumps(serial)) | nyuuustead/models.py | import random, json
from colorful.fields import RGBColorField
from django.contrib.auth.models import User
from django.core.urlresolvers import reverse
from django.db import models
from django.utils import timezone
from django_redis import get_redis_connection
BEST_COLOURS = (
"#1b85b8",
"#03c03c",
"#559e83",
"#ae5a41",
"#c3cb71",
"#c23b22",
"#ffb347",
"#f49ac2",
"#dea5a4",
"#e3e387",
"#77dd77",
"#b19cd9",
"#ffd1dc",
"#779ecb",
"#cb99c9",
"#966fd6"
)
def best_colour():
return random.choice(BEST_COLOURS)
def best_hug():
return HugKind.objects.order_by('?')[0]
class Pronoun(models.Model):
subject = models.CharField(max_length=20)
object = models.CharField(max_length=20)
possessive_determiner = models.CharField(max_length=20)
possessive_pronoun = models.CharField(max_length=20)
reflexive = models.CharField(max_length=25)
def __str__(self):
return "/".join(
(self.subject, self.object, self.possessive_determiner, self.possessive_pronoun, self.reflexive))
class Userware(models.Model):
user = models.OneToOneField(User, related_name="userware")
daily_notifications = models.BooleanField(default=True, help_text="Those will be sent to your email no more often" +
" than once a day, at 13:37 server time.")
hourly_notifications = models.BooleanField(default=False, help_text="Those will be sent to your email no more oft" +
"en than once per hour.")
news_emails = models.BooleanField(default=True, help_text="Those will be sent whenever I have something to announ" +
"ce, which probably won't be too often.")
colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
pronoun = models.ForeignKey(Pronoun, related_name="pronouns",
help_text="Is your pronoun missing? Shoot an email " +
"at <EMAIL> and we'll look into it!")
followers = models.ManyToManyField('self', blank=True, related_name="following")
hugs_to_notify = models.ManyToManyField('Hug', blank=True)
def __str__(self):
return self.user.get_username()
def hugs_come_and_gone(self):
return Hug.objects.filter(models.Q(source=self.user) | models.Q(target=self.user)).order_by('-timestamp')
def get_absolute_url(self):
return reverse("user_page", kwargs=dict(username=self.user.username))
class Follow(models.Model):
source = models.ForeignKey(User, related_name="following")
target = models.ForeignKey(User, related_name="followers")
timestamp = models.DateTimeField(default=timezone.now)
def __str__(self):
return "%s -> %s" % (self.source, self.target)
class Meta:
unique_together = ('source', 'target'),
class HugKind(models.Model):
name = models.CharField(max_length=20, db_index=True)
verb = models.CharField(max_length=20, db_index=True)
verb_tercery = models.CharField(max_length=20)
past = models.CharField(max_length=30)
def serialize(self) -> dict:
return dict(noun=self.name, verb=self.verb, verb_third=self.verb_tercery, verb_past=self.past)
def __str__(self):
return self.name
class Hug(models.Model):
source = models.ForeignKey(User, db_index=True, related_name="hugs_given")
source_colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
target = models.ForeignKey(User, db_index=True, related_name="hugs_gotten")
target_colour = RGBColorField(default=best_colour, colors=BEST_COLOURS)
kind = models.ForeignKey(HugKind, db_index=True, related_name="hugs")
inspiration = models.ForeignKey('self', null=True, blank=True, related_name="kids")
timestamp = models.DateTimeField(default=timezone.now)
def serialize(self) -> dict:
return dict(id=self.pk, source=self.source.username, target=self.target.username, source_colour=self.source_colour, target_colour=self.target_colour, kind=self.kind.serialize(), inspiration=self.inspiration.pk if self.inspiration else None)
def publish(self):
red = get_redis_connection("default")
serial = dict(channel="global", content=self.serialize())
red.publish("hugs", json.dumps(serial))
for subber in User.objects.only('username').filter(models.Q(pk=self.target.pk)|models.Q(pk=self.source.pk)|models.Q(following__target=self.target)|models.Q(following__target=self.source)).distinct():
serial["channel"] = subber.username
red.publish("hugs", json.dumps(serial)) | 0.528047 | 0.176565 |
import numpy as np
import matplotlib.pyplot as plt
from custom_poling.utils.pmf import pmf
class Crystal:
""" A class for a poled crystal.
Attr:
domain_width
number_domains
z0
length = domain_width * number_domains
domain_walls
domain_middles
"""
def __init__(self, domain_width, number_domains, z0=0):
""" Initialize the Crystal class.
Params:
domain_width
number_domains
"""
self.domain_width = domain_width
self.number_domains = number_domains
self.z0 = z0
self.length = self.number_domains * self.domain_width
self.domain_walls = np.arange(z0, z0 + (self.number_domains + 1) * self.domain_width, self.domain_width)
self.domain_middles = (self.domain_walls + self.domain_width/2)[0:-1]
def compute_pmf(self, domain_configuration, k_array):
"""Returns the phasematching function (PMF) as a function of k for a given domain_configuration.
Args:
domain_configuration (list of int): elements of list must be +1 or -1
k_array (array of floats)
Returns:
PMF as an array of floats
"""
self.domain_configuration = domain_configuration
self.k_array = k_array
self.pmf = pmf(self.domain_walls, self.domain_configuration, self.k_array)
return self.pmf
def plot_pmf(self):
"""Plots the phasematching function (PMF) as a function of k for a given domain_configuration.
Args:
domain_configuration (list of int): elements of list must be +1 or -1
k_array (array of floats)
Returns:
Plot of PMF as a function of k_array
"""
plt.plot(self.k_array,np.abs(self.pmf),label='abs')
plt.plot(self.k_array,np.real(self.pmf),'--',label='real')
plt.plot(self.k_array,np.imag(self.pmf),'--',label='imag')
plt.xlabel('Delta k')
plt.ylabel('PMF')
plt.legend()
plt.show()
def plot_domains(self,domain_configuration):
plt.step(self.domain_walls,[domain_configuration[0]]+domain_configuration)
plt.xlabel('z')
plt.ylabel('g(z)')
plt.ylim([-1.2, 1.2])
plt.show() | custom_poling/core/crystal.py | import numpy as np
import matplotlib.pyplot as plt
from custom_poling.utils.pmf import pmf
class Crystal:
""" A class for a poled crystal.
Attr:
domain_width
number_domains
z0
length = domain_width * number_domains
domain_walls
domain_middles
"""
def __init__(self, domain_width, number_domains, z0=0):
""" Initialize the Crystal class.
Params:
domain_width
number_domains
"""
self.domain_width = domain_width
self.number_domains = number_domains
self.z0 = z0
self.length = self.number_domains * self.domain_width
self.domain_walls = np.arange(z0, z0 + (self.number_domains + 1) * self.domain_width, self.domain_width)
self.domain_middles = (self.domain_walls + self.domain_width/2)[0:-1]
def compute_pmf(self, domain_configuration, k_array):
"""Returns the phasematching function (PMF) as a function of k for a given domain_configuration.
Args:
domain_configuration (list of int): elements of list must be +1 or -1
k_array (array of floats)
Returns:
PMF as an array of floats
"""
self.domain_configuration = domain_configuration
self.k_array = k_array
self.pmf = pmf(self.domain_walls, self.domain_configuration, self.k_array)
return self.pmf
def plot_pmf(self):
"""Plots the phasematching function (PMF) as a function of k for a given domain_configuration.
Args:
domain_configuration (list of int): elements of list must be +1 or -1
k_array (array of floats)
Returns:
Plot of PMF as a function of k_array
"""
plt.plot(self.k_array,np.abs(self.pmf),label='abs')
plt.plot(self.k_array,np.real(self.pmf),'--',label='real')
plt.plot(self.k_array,np.imag(self.pmf),'--',label='imag')
plt.xlabel('Delta k')
plt.ylabel('PMF')
plt.legend()
plt.show()
def plot_domains(self,domain_configuration):
plt.step(self.domain_walls,[domain_configuration[0]]+domain_configuration)
plt.xlabel('z')
plt.ylabel('g(z)')
plt.ylim([-1.2, 1.2])
plt.show() | 0.885173 | 0.463444 |
from datetime import datetime
from playhouse.apsw_ext import (
Model,
Proxy,
CharField,
CompositeKey,
DateTimeField,
ForeignKeyField,
IntegerField,
TextField,
)
db = Proxy()
class BaseModel(Model):
class Meta:
database = db
class Limit(BaseModel):
key = CharField(max_length=32, primary_key=True)
value = CharField()
class TaskGroup(BaseModel):
name = CharField(primary_key=True)
class Task(BaseModel):
group = ForeignKeyField(TaskGroup, backref="tasks")
path = CharField(primary_key=True)
class Tool(BaseModel):
module = CharField()
name = CharField(primary_key=True)
class ParameterGroup(BaseModel):
name = CharField()
tool = ForeignKeyField(Tool, backref="parameter_groups")
class Meta:
indexes = ((("name", "tool"), True),)
class Parameter(BaseModel):
group = ForeignKeyField(ParameterGroup, backref="parameters")
key = CharField()
value = CharField()
class Meta:
primary_key = CompositeKey("group", "key")
class BasePlugin(BaseModel):
module = CharField(index=True)
config = TextField()
class Step(BasePlugin):
RUN = "run"
ANALYSIS = "analysis"
CATEGORY_CHOICES = ((RUN, "Single run step"), (ANALYSIS, "Analysis step"))
category = CharField(choices=CATEGORY_CHOICES, index=True)
class Observer(BasePlugin):
pass
class Run(BaseModel):
FAILED = -2
CANCELED = -1
PENDING = 0
SUBMITTED = 1
RUNNING = 2
DONE = 3
STATUS_CHOICES = (
(FAILED, "Failed"),
(CANCELED, "Canceled"),
(PENDING, "Pending"),
(SUBMITTED, "Submitted"),
(RUNNING, "Running"),
(DONE, "Done"),
)
id = CharField(null=True, primary_key=True)
created_at = DateTimeField(default=datetime.now)
tool = ForeignKeyField(Tool, backref="runs")
tool_version = CharField(null=True)
parameter_group = ForeignKeyField(ParameterGroup, backref="runs")
task = ForeignKeyField(Task, backref="runs")
status = IntegerField(choices=STATUS_CHOICES, default=PENDING)
last_step = ForeignKeyField(Step, null=True)
iteration = IntegerField(default=0)
MODELS = (Limit, TaskGroup, Task, Tool, ParameterGroup, Parameter, Run, Step, Observer) | reprobench/core/db.py | from datetime import datetime
from playhouse.apsw_ext import (
Model,
Proxy,
CharField,
CompositeKey,
DateTimeField,
ForeignKeyField,
IntegerField,
TextField,
)
db = Proxy()
class BaseModel(Model):
class Meta:
database = db
class Limit(BaseModel):
key = CharField(max_length=32, primary_key=True)
value = CharField()
class TaskGroup(BaseModel):
name = CharField(primary_key=True)
class Task(BaseModel):
group = ForeignKeyField(TaskGroup, backref="tasks")
path = CharField(primary_key=True)
class Tool(BaseModel):
module = CharField()
name = CharField(primary_key=True)
class ParameterGroup(BaseModel):
name = CharField()
tool = ForeignKeyField(Tool, backref="parameter_groups")
class Meta:
indexes = ((("name", "tool"), True),)
class Parameter(BaseModel):
group = ForeignKeyField(ParameterGroup, backref="parameters")
key = CharField()
value = CharField()
class Meta:
primary_key = CompositeKey("group", "key")
class BasePlugin(BaseModel):
module = CharField(index=True)
config = TextField()
class Step(BasePlugin):
RUN = "run"
ANALYSIS = "analysis"
CATEGORY_CHOICES = ((RUN, "Single run step"), (ANALYSIS, "Analysis step"))
category = CharField(choices=CATEGORY_CHOICES, index=True)
class Observer(BasePlugin):
pass
class Run(BaseModel):
FAILED = -2
CANCELED = -1
PENDING = 0
SUBMITTED = 1
RUNNING = 2
DONE = 3
STATUS_CHOICES = (
(FAILED, "Failed"),
(CANCELED, "Canceled"),
(PENDING, "Pending"),
(SUBMITTED, "Submitted"),
(RUNNING, "Running"),
(DONE, "Done"),
)
id = CharField(null=True, primary_key=True)
created_at = DateTimeField(default=datetime.now)
tool = ForeignKeyField(Tool, backref="runs")
tool_version = CharField(null=True)
parameter_group = ForeignKeyField(ParameterGroup, backref="runs")
task = ForeignKeyField(Task, backref="runs")
status = IntegerField(choices=STATUS_CHOICES, default=PENDING)
last_step = ForeignKeyField(Step, null=True)
iteration = IntegerField(default=0)
MODELS = (Limit, TaskGroup, Task, Tool, ParameterGroup, Parameter, Run, Step, Observer) | 0.603114 | 0.109944 |
import unidecode
def convert_input_units(decoded_data):
latitude_data = decoded_data[0]
longitude_data = decoded_data[1]
altitude_data = decoded_data[2]
instruction_data = decoded_data[3]
name_data = decoded_data[4]
latitude_data_converted=[]
longitude_data_converted=[]
altitude_data_converted=[]
instruction_data_converted=[]
name_data_converted=[] #tbd update
# converting lat, lon and alt to units used in .fit files
for latitude in latitude_data:
latitude_data_converted.append(int(float(latitude)*1000000))
for longitude in longitude_data:
longitude_data_converted.append(int(float(longitude)*1000000))
for altitude in altitude_data:
altitude_data_converted.append(int((float(altitude)*5)+2500))
for instruction in instruction_data:
if instruction == 0:
ins = b'\x03' # left
elif instruction == 1:
ins = b'\x02' # right
elif instruction == 2:
ins = b'\x07' # close left
elif instruction == 3:
ins = b'\x06' # close right
elif instruction == 4:
ins = b'\x05' # slight left
elif instruction == 5:
ins = b'\x04' # slight right
elif instruction == 6:
ins = b'\x01' # go ahead
elif instruction == 7:
ins = b'\x01' # go ahead
elif instruction == 8:
ins = b'\x08' # exit right
elif instruction == 9:
ins = b'\x07' # uturn left
elif instruction == 10:
ins = b'\x01' # go ahead
elif instruction == 11:
ins = b'\x01' # go ahead
elif instruction == 12:
ins = b'\x09' # exit left
elif instruction == 13:
ins = b'\x08' # exit right
elif instruction == 14:
ins = b'\x01' # go ahead
else:
ins = b'\xff' # none
instruction_data_converted.append(ins)
for name in name_data:
name = unidecode.unidecode(name)
name = name.replace('A(c)','e')
name = name.replace('A!','a')
name = name.replace('A\'','o')
name=name.replace('ASS', 'c')
name=name.replace('APS', 'a')
name=name.replace('A3', 'o')
name = name.replace('Rua','R')
name = name.replace('Avenida', 'Av')
name = name.replace('Professora', 'Prf')
name = name.replace('Professor', 'Prf')
name = name.replace('Doutora', 'Dr')
name = name.replace('Doutor', 'Dr')
name = name.replace('Estrada', 'Est')
name = name.replace('Eduardo', 'Edu')
name = name.replace('Monte', 'Mt')
name = name.replace('Viaduto', 'Via')
name=name.replace('Passagem', 'Ps')
name=name.replace('NAvel', 'Nv')
name = name.replace('Engenheira', 'Eng')
name = name.replace('Engenheiro', 'Eng')
name = name.replace('Marechal', 'Mrc')
name_data_converted.append(name[:32])
decoded_data = [latitude_data_converted,longitude_data_converted,altitude_data_converted,instruction_data_converted,name_data_converted]
return decoded_data | source/units_conversion.py | import unidecode
def convert_input_units(decoded_data):
latitude_data = decoded_data[0]
longitude_data = decoded_data[1]
altitude_data = decoded_data[2]
instruction_data = decoded_data[3]
name_data = decoded_data[4]
latitude_data_converted=[]
longitude_data_converted=[]
altitude_data_converted=[]
instruction_data_converted=[]
name_data_converted=[] #tbd update
# converting lat, lon and alt to units used in .fit files
for latitude in latitude_data:
latitude_data_converted.append(int(float(latitude)*1000000))
for longitude in longitude_data:
longitude_data_converted.append(int(float(longitude)*1000000))
for altitude in altitude_data:
altitude_data_converted.append(int((float(altitude)*5)+2500))
for instruction in instruction_data:
if instruction == 0:
ins = b'\x03' # left
elif instruction == 1:
ins = b'\x02' # right
elif instruction == 2:
ins = b'\x07' # close left
elif instruction == 3:
ins = b'\x06' # close right
elif instruction == 4:
ins = b'\x05' # slight left
elif instruction == 5:
ins = b'\x04' # slight right
elif instruction == 6:
ins = b'\x01' # go ahead
elif instruction == 7:
ins = b'\x01' # go ahead
elif instruction == 8:
ins = b'\x08' # exit right
elif instruction == 9:
ins = b'\x07' # uturn left
elif instruction == 10:
ins = b'\x01' # go ahead
elif instruction == 11:
ins = b'\x01' # go ahead
elif instruction == 12:
ins = b'\x09' # exit left
elif instruction == 13:
ins = b'\x08' # exit right
elif instruction == 14:
ins = b'\x01' # go ahead
else:
ins = b'\xff' # none
instruction_data_converted.append(ins)
for name in name_data:
name = unidecode.unidecode(name)
name = name.replace('A(c)','e')
name = name.replace('A!','a')
name = name.replace('A\'','o')
name=name.replace('ASS', 'c')
name=name.replace('APS', 'a')
name=name.replace('A3', 'o')
name = name.replace('Rua','R')
name = name.replace('Avenida', 'Av')
name = name.replace('Professora', 'Prf')
name = name.replace('Professor', 'Prf')
name = name.replace('Doutora', 'Dr')
name = name.replace('Doutor', 'Dr')
name = name.replace('Estrada', 'Est')
name = name.replace('Eduardo', 'Edu')
name = name.replace('Monte', 'Mt')
name = name.replace('Viaduto', 'Via')
name=name.replace('Passagem', 'Ps')
name=name.replace('NAvel', 'Nv')
name = name.replace('Engenheira', 'Eng')
name = name.replace('Engenheiro', 'Eng')
name = name.replace('Marechal', 'Mrc')
name_data_converted.append(name[:32])
decoded_data = [latitude_data_converted,longitude_data_converted,altitude_data_converted,instruction_data_converted,name_data_converted]
return decoded_data | 0.223716 | 0.463869 |
# Python imports
from __future__ import print_function
import argparse
import distutils.spawn
import os
import subprocess
import sys
# Parse arguments
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('--builddir',
help=('Build directory. If not specified, it is determined'
' using the Enstore configuration client.'))
args = parser.parse_args()
# Test Sphinx for availability
try:
import sphinx
except ImportError:
msg = ('Sphinx could not be imported. '
'To install it for Python 2.7.9 or newer, run as root:\n'
'\tpython -m ensurepip --upgrade\n'
'\tpip install --upgrade pip\n'
'\tpip install --upgrade sphinx')
exit(msg)
# Note: Minimal version requirement for Sphinx is defined in source/conf.py.
# Test Graphviz dot for availability
if distutils.spawn.find_executable('dot') is None:
msg = ("The Graphviz dot executable is required but could not be found. "
"To install its x86_64 RPM, run:\n"
"\tyum install graphviz.x86_64")
exit(msg)
# Determine make directory
make_dir = os.path.abspath(os.path.dirname(__file__))
py_rst_dir = os.path.join(make_dir, 'source', 'modules')
# Determine and export build directory
build_dir = args.builddir
if not build_dir:
try:
import configuration_client
config_client = configuration_client.ConfigurationClient()
build_dir = config_client.get('crons')['html_dir']
build_dir = os.path.join(build_dir, 'docs')
except:
msg = ('Error determining build directory automatically using the '
'Enstore configuration client. It can be specified as a '
'command-line option. (--builddir)')
print(msg, end='\n\n', file=sys.stderr)
raise
build_dir = os.path.abspath(build_dir)
os.environ['BUILDDIR'] = build_dir
# Note: The build directory is created automatically if it doesn't exist.
print("""The HTML directory path is printed after the build has finished.
General troubleshooting steps:
• If the HTML output fails to get generated for a Python module, ensure the
module can be imported by Python, and that its .rst file exists in
{}.
• If the HTML output exists but fails to get updated for a Python module,
"touch" the module's .rst file.
""".format(py_rst_dir))
# GNU make
make_cmd = 'make --directory="{}" html'.format(make_dir)
make_exit_status = subprocess.call(make_cmd, shell=True)
# Note: Not using "shell=True" raises "OSError: [Errno 2]".
exit(make_exit_status) | sphinx/make.py | # Python imports
from __future__ import print_function
import argparse
import distutils.spawn
import os
import subprocess
import sys
# Parse arguments
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('--builddir',
help=('Build directory. If not specified, it is determined'
' using the Enstore configuration client.'))
args = parser.parse_args()
# Test Sphinx for availability
try:
import sphinx
except ImportError:
msg = ('Sphinx could not be imported. '
'To install it for Python 2.7.9 or newer, run as root:\n'
'\tpython -m ensurepip --upgrade\n'
'\tpip install --upgrade pip\n'
'\tpip install --upgrade sphinx')
exit(msg)
# Note: Minimal version requirement for Sphinx is defined in source/conf.py.
# Test Graphviz dot for availability
if distutils.spawn.find_executable('dot') is None:
msg = ("The Graphviz dot executable is required but could not be found. "
"To install its x86_64 RPM, run:\n"
"\tyum install graphviz.x86_64")
exit(msg)
# Determine make directory
make_dir = os.path.abspath(os.path.dirname(__file__))
py_rst_dir = os.path.join(make_dir, 'source', 'modules')
# Determine and export build directory
build_dir = args.builddir
if not build_dir:
try:
import configuration_client
config_client = configuration_client.ConfigurationClient()
build_dir = config_client.get('crons')['html_dir']
build_dir = os.path.join(build_dir, 'docs')
except:
msg = ('Error determining build directory automatically using the '
'Enstore configuration client. It can be specified as a '
'command-line option. (--builddir)')
print(msg, end='\n\n', file=sys.stderr)
raise
build_dir = os.path.abspath(build_dir)
os.environ['BUILDDIR'] = build_dir
# Note: The build directory is created automatically if it doesn't exist.
print("""The HTML directory path is printed after the build has finished.
General troubleshooting steps:
• If the HTML output fails to get generated for a Python module, ensure the
module can be imported by Python, and that its .rst file exists in
{}.
• If the HTML output exists but fails to get updated for a Python module,
"touch" the module's .rst file.
""".format(py_rst_dir))
# GNU make
make_cmd = 'make --directory="{}" html'.format(make_dir)
make_exit_status = subprocess.call(make_cmd, shell=True)
# Note: Not using "shell=True" raises "OSError: [Errno 2]".
exit(make_exit_status) | 0.490968 | 0.073563 |
import os
from hstest.exceptions import WrongAnswerException
from hstest.exceptions import ExceptionWithFeedback
from hstest.exceptions import SyntaxException
from hstest.exceptions import TimeLimitException
from hstest.exceptions import FatalErrorException
from hstest.utils import get_stacktrace, get_report
from hstest.dynamic.handle_stdout import StdoutHandler
from hstest.test_run import TestRun
class Outcome:
def __init__(self):
self.test_number: int = 0
self.error_text: str = ''
self.stack_trace: str = ''
def get_type(self) -> str:
raise NotImplementedError()
def get_type_suffix(self) -> str:
return ''
def __str__(self):
if self.test_number == 0:
when_error_happened = ' during testing'
else:
when_error_happened = f' in test #{self.test_number}'
result = self.get_type() + when_error_happened + self.get_type_suffix()
if self.error_text:
result += '\n\n' + self.error_text.strip()
if self.stack_trace:
result += '\n\n' + self.stack_trace.strip()
full_log = StdoutHandler.get_dynamic_output()
if len(full_log.strip()) > 0:
result += ('\n\nPlease find below the output '
'of your program during this failed test.\n')
if TestRun.curr_test_run.input_used:
result += ("Note that the '>' character indicates "
"the beginning of the input line.\n")
result += '\n---\n\n'
result += full_log
return result.strip()
@staticmethod
def get_outcome(ex: BaseException, stage, test_num: int):
if isinstance(ex, WrongAnswerException):
return WrongAnswerOutcome(test_num, ex.feedback)
elif isinstance(ex, ExceptionWithFeedback):
return ExceptionOutcome(test_num, ex.real_exception, ex.feedback, stage)
elif isinstance(ex, TimeLimitException):
return ErrorOutcome(test_num, ex)
elif isinstance(ex, SyntaxException):
return SyntaxErrorOutcome(ex.exception, stage)
if isinstance(ex, FatalErrorException) and ex.exception is not None:
ex = ex.exception
return FatalErrorOutcome(test_num, ex, stage)
class WrongAnswerOutcome(Outcome):
def __init__(self, test_num: int, feedback: str):
super().__init__()
self.test_number = test_num
self.error_text = feedback
def get_type(self) -> str:
return 'Wrong answer'
class ExceptionOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException, feedback: str, stage):
super().__init__()
self.test_number = test_num
self.error_text = feedback
self.stack_trace = get_stacktrace(stage.file_to_test, cause, hide_internals=True)
if self.stack_trace.strip().endswith('EOFError: EOF when reading a line'):
self.error_text += '\n\nProbably your program run out of input (tried to read more than expected)'
def get_type(self) -> str:
return 'Exception'
class ErrorOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException):
super().__init__()
self.test_number = test_num
if isinstance(cause, TimeLimitException):
time_limit: int = cause.time_limit_ms
time_unit: str = 'milliseconds'
if time_limit > 1999:
time_limit //= 1000
time_unit = 'seconds'
self.error_text = (
'In this test, the program is running for a long time, ' +
f'more than {time_limit} {time_unit}. Most likely, ' +
'the program has gone into an infinite loop.'
)
def get_type(self) -> str:
return 'Error'
class FatalErrorOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException, stage):
super().__init__()
self.test_number = test_num
self.error_text = get_report()
self.stack_trace = get_stacktrace(stage.file_to_test, cause, hide_internals=False)
def get_type(self) -> str:
return 'Fatal error'
def get_type_suffix(self) -> str:
return ', please send the report to <EMAIL>'
class SyntaxErrorOutcome(Outcome):
def __init__(self, cause: SyntaxError, stage):
super().__init__()
file = cause.filename
file = file.replace(os.sep, '.')
file = file[file.index(stage.module_to_test):-3]
file = file.replace('.', os.sep) + '.py'
output = f'File "{file}", line {cause.lineno}\n' \
+ cause.text.strip()[: cause.offset - 1] + '\n' \
f'SyntaxError: {cause.msg}'
self.error_text = output
def get_type(self) -> str:
return 'Syntax error'
def __str__(self):
return self.error_text | .idea/VirtualEnvironment/Lib/site-packages/hstest/outcomes.py | import os
from hstest.exceptions import WrongAnswerException
from hstest.exceptions import ExceptionWithFeedback
from hstest.exceptions import SyntaxException
from hstest.exceptions import TimeLimitException
from hstest.exceptions import FatalErrorException
from hstest.utils import get_stacktrace, get_report
from hstest.dynamic.handle_stdout import StdoutHandler
from hstest.test_run import TestRun
class Outcome:
def __init__(self):
self.test_number: int = 0
self.error_text: str = ''
self.stack_trace: str = ''
def get_type(self) -> str:
raise NotImplementedError()
def get_type_suffix(self) -> str:
return ''
def __str__(self):
if self.test_number == 0:
when_error_happened = ' during testing'
else:
when_error_happened = f' in test #{self.test_number}'
result = self.get_type() + when_error_happened + self.get_type_suffix()
if self.error_text:
result += '\n\n' + self.error_text.strip()
if self.stack_trace:
result += '\n\n' + self.stack_trace.strip()
full_log = StdoutHandler.get_dynamic_output()
if len(full_log.strip()) > 0:
result += ('\n\nPlease find below the output '
'of your program during this failed test.\n')
if TestRun.curr_test_run.input_used:
result += ("Note that the '>' character indicates "
"the beginning of the input line.\n")
result += '\n---\n\n'
result += full_log
return result.strip()
@staticmethod
def get_outcome(ex: BaseException, stage, test_num: int):
if isinstance(ex, WrongAnswerException):
return WrongAnswerOutcome(test_num, ex.feedback)
elif isinstance(ex, ExceptionWithFeedback):
return ExceptionOutcome(test_num, ex.real_exception, ex.feedback, stage)
elif isinstance(ex, TimeLimitException):
return ErrorOutcome(test_num, ex)
elif isinstance(ex, SyntaxException):
return SyntaxErrorOutcome(ex.exception, stage)
if isinstance(ex, FatalErrorException) and ex.exception is not None:
ex = ex.exception
return FatalErrorOutcome(test_num, ex, stage)
class WrongAnswerOutcome(Outcome):
def __init__(self, test_num: int, feedback: str):
super().__init__()
self.test_number = test_num
self.error_text = feedback
def get_type(self) -> str:
return 'Wrong answer'
class ExceptionOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException, feedback: str, stage):
super().__init__()
self.test_number = test_num
self.error_text = feedback
self.stack_trace = get_stacktrace(stage.file_to_test, cause, hide_internals=True)
if self.stack_trace.strip().endswith('EOFError: EOF when reading a line'):
self.error_text += '\n\nProbably your program run out of input (tried to read more than expected)'
def get_type(self) -> str:
return 'Exception'
class ErrorOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException):
super().__init__()
self.test_number = test_num
if isinstance(cause, TimeLimitException):
time_limit: int = cause.time_limit_ms
time_unit: str = 'milliseconds'
if time_limit > 1999:
time_limit //= 1000
time_unit = 'seconds'
self.error_text = (
'In this test, the program is running for a long time, ' +
f'more than {time_limit} {time_unit}. Most likely, ' +
'the program has gone into an infinite loop.'
)
def get_type(self) -> str:
return 'Error'
class FatalErrorOutcome(Outcome):
def __init__(self, test_num: int, cause: BaseException, stage):
super().__init__()
self.test_number = test_num
self.error_text = get_report()
self.stack_trace = get_stacktrace(stage.file_to_test, cause, hide_internals=False)
def get_type(self) -> str:
return 'Fatal error'
def get_type_suffix(self) -> str:
return ', please send the report to <EMAIL>'
class SyntaxErrorOutcome(Outcome):
def __init__(self, cause: SyntaxError, stage):
super().__init__()
file = cause.filename
file = file.replace(os.sep, '.')
file = file[file.index(stage.module_to_test):-3]
file = file.replace('.', os.sep) + '.py'
output = f'File "{file}", line {cause.lineno}\n' \
+ cause.text.strip()[: cause.offset - 1] + '\n' \
f'SyntaxError: {cause.msg}'
self.error_text = output
def get_type(self) -> str:
return 'Syntax error'
def __str__(self):
return self.error_text | 0.52342 | 0.194712 |
import base64
from datetime import datetime, timedelta
import jwt
import requests
class LoginService:
"""
This class is meant to be whole static to simulate singleton
It is collection of functions for login handling
"""
access_route = "https://auth.fit.cvut.cz/oauth/oauth/token"
check_route = "https://auth.fit.cvut.cz/oauth/oauth/check_token"
secret = None
client_id = None
client_secret = None
redirect_uri = None
authorization = None
@classmethod
def init(cls):
from octoprint_dashboard.model import Config
config = Config.query.first()
if config:
cls.secret = config.secret
cls.client_id = config.oauth_client_id
cls.client_secret = config.oauth_client_secret
cls.redirect_uri = config.oauth_redirect_uri
cls.authorization = "Basic " + base64.b64encode(
"{0}:{1}".format(cls.client_id, cls.client_secret).encode('ascii')).decode('utf-8')
@staticmethod
def create_api_token(username, role):
"""
Returns token for access to API
"""
payload = {
'username': username,
'role': role,
'iat': datetime.utcnow(),
'exp': datetime.utcnow() + timedelta(days=14)
}
token = jwt.encode(payload, LoginService.secret, algorithm="HS256")
return token.decode('unicode_escape')
@staticmethod
def parse_api_token(request):
"""
Returns parsed and decoded token from authorization header
"""
token = request.headers.get('Authorization').split()[1]
return jwt.decode(token, LoginService.secret)
@staticmethod
def parse_api_token_direct(token):
"""
Returns parsed and decoded token from authorization header
"""
return jwt.decode(token, LoginService.secret)
@staticmethod
def get_access_code(code):
"""
Makes request to OAuth to exchange code for access_token and returns response
"""
response = requests.post(LoginService.access_route, headers={
"Authorization": LoginService.authorization
}, data={
"grant_type": "authorization_code",
"code": code,
"scope": "urn:zuul:oauth",
"redirect_uri": LoginService.redirect_uri
})
response.raise_for_status()
return response.json()
@staticmethod
def check_token(access_token):
"""
Makes request to OAuth check token route and returns response
Returns information about token (user)
"""
response = requests.post(LoginService.check_route, data={
"token": access_token
})
response.raise_for_status()
return response.json()
@staticmethod
def refresh_token(refresh_token):
"""
Makes request to OAuth to refresh access token and returns response
"""
response = requests.post(LoginService.access_route, headers={
"Authorization": LoginService.authorization
}, data={
"grant_type": "refresh_token",
"scope": "urn:zuul:oauth",
"refresh_token": refresh_token
})
response.raise_for_status()
return response.json() | octoprint_dashboard/services/loginService.py | import base64
from datetime import datetime, timedelta
import jwt
import requests
class LoginService:
"""
This class is meant to be whole static to simulate singleton
It is collection of functions for login handling
"""
access_route = "https://auth.fit.cvut.cz/oauth/oauth/token"
check_route = "https://auth.fit.cvut.cz/oauth/oauth/check_token"
secret = None
client_id = None
client_secret = None
redirect_uri = None
authorization = None
@classmethod
def init(cls):
from octoprint_dashboard.model import Config
config = Config.query.first()
if config:
cls.secret = config.secret
cls.client_id = config.oauth_client_id
cls.client_secret = config.oauth_client_secret
cls.redirect_uri = config.oauth_redirect_uri
cls.authorization = "Basic " + base64.b64encode(
"{0}:{1}".format(cls.client_id, cls.client_secret).encode('ascii')).decode('utf-8')
@staticmethod
def create_api_token(username, role):
"""
Returns token for access to API
"""
payload = {
'username': username,
'role': role,
'iat': datetime.utcnow(),
'exp': datetime.utcnow() + timedelta(days=14)
}
token = jwt.encode(payload, LoginService.secret, algorithm="HS256")
return token.decode('unicode_escape')
@staticmethod
def parse_api_token(request):
"""
Returns parsed and decoded token from authorization header
"""
token = request.headers.get('Authorization').split()[1]
return jwt.decode(token, LoginService.secret)
@staticmethod
def parse_api_token_direct(token):
"""
Returns parsed and decoded token from authorization header
"""
return jwt.decode(token, LoginService.secret)
@staticmethod
def get_access_code(code):
"""
Makes request to OAuth to exchange code for access_token and returns response
"""
response = requests.post(LoginService.access_route, headers={
"Authorization": LoginService.authorization
}, data={
"grant_type": "authorization_code",
"code": code,
"scope": "urn:zuul:oauth",
"redirect_uri": LoginService.redirect_uri
})
response.raise_for_status()
return response.json()
@staticmethod
def check_token(access_token):
"""
Makes request to OAuth check token route and returns response
Returns information about token (user)
"""
response = requests.post(LoginService.check_route, data={
"token": access_token
})
response.raise_for_status()
return response.json()
@staticmethod
def refresh_token(refresh_token):
"""
Makes request to OAuth to refresh access token and returns response
"""
response = requests.post(LoginService.access_route, headers={
"Authorization": LoginService.authorization
}, data={
"grant_type": "refresh_token",
"scope": "urn:zuul:oauth",
"refresh_token": refresh_token
})
response.raise_for_status()
return response.json() | 0.622574 | 0.182134 |
import numpy as np
import os
from ..molecules import Protein
def gen_tripeptides(protein=None, gaussian=True, header=None, save_pdb=True,
folder=None, main_base='6-311+G(2d,p)', minor_base='3-21G'):
"""
protein : str
path to pdb file
gaussian : bool
If True a gaussian job file will be generated along the tripeptides. Defaults to True.
header : str
Valid header for Gaussian job file. Only works if `gaussian` is True
save_pdb : bool
If True a pdb for each tripeptide will be saved to hardisk. Defaults to True.
folder : str
Path to the folder containing the generated files. If none provided it will use the basename of the
protein file without extension.
main_base : str
valid gaussian DFT base. This will be used for the central residue's atoms.
Defaults to `6-311+G(2d,p)`.
minor_base : str
valid gaussian DFT base. This will be used for the non-central residue's atoms.
Defaults to `3-21G`.
"""
if folder is None:
folder = os.path.splitext(os.path.basename(protein))[0]
prot = Protein(pdb=protein, regularize=False)
tors = prot.get_torsionals()
seq = prot.sequence
for idx, aa in enumerate(seq[1:-1]):
pept = Protein('BG{}GZ'.format(aa))
for i in range(0, 3):
phi = tors.iloc[idx+i].phi
psi = tors.iloc[idx+i].psi
if np.isfinite(phi):
pept.set_phi(i+1, phi)
if np.isfinite(psi):
pept.set_psi(i+1, psi)
if i == 2:
for j in range(1, 6):
chi = tors.iloc[idx+i]['chi{}'.format(j)]
if np.isfinite(chi):
pept.set_chi(2, j, chi)
directory = '{}/M_{}'.format(folder, idx)
if not os.path.exists(directory):
os.makedirs(directory)
if save_pdb:
pept.dump_pdb('{}/test'.format(directory))
if gaussian:
_write_gaussian_file(pept, directory, header, main_base, minor_base)
def _write_gaussian_file(pept, directory, header, main_base, minor_base):
"""
pept : protein object
directory : str
Path to the directory containing the generated files.
header : str
Valid header for Gaussian job file. Only works if `gaussian` is True
main_base : str
valid gaussian DFT base. This will be used for the central residue's atoms.
minor_base : str
valid gaussian DFT base. This will be used for the non-central residue's atoms.
"""
fd = open('{}/RES.com'.format(directory), 'w')
fd.write(header)
for idx, xyz in enumerate(pept.coords):
atom_type = pept._elements[idx]
fd.write(' %s%9.3f%8.3f%8.3f\n' % (atom_type, *xyz))
fd.write('\n')
string = " 1 2 3 4 5 6 7 8 9 10 11 12 13 0\n 3-21G\n ****\n"
atoms = len(pept.at_coords(2))
for atom in range(14, atoms+14):
string = string + ' %s ' % atom
string = string + '0\n {}\n ****\n'.format(main_base)
for atom in range(atoms+14, atoms+27):
string = string + ' %s ' % atom
string = string + '0\n {}\n ****\n\n\n'.format(minor_base)
fd.write(string)
fd.close() | bomeba0/external/gaussian.py | import numpy as np
import os
from ..molecules import Protein
def gen_tripeptides(protein=None, gaussian=True, header=None, save_pdb=True,
folder=None, main_base='6-311+G(2d,p)', minor_base='3-21G'):
"""
protein : str
path to pdb file
gaussian : bool
If True a gaussian job file will be generated along the tripeptides. Defaults to True.
header : str
Valid header for Gaussian job file. Only works if `gaussian` is True
save_pdb : bool
If True a pdb for each tripeptide will be saved to hardisk. Defaults to True.
folder : str
Path to the folder containing the generated files. If none provided it will use the basename of the
protein file without extension.
main_base : str
valid gaussian DFT base. This will be used for the central residue's atoms.
Defaults to `6-311+G(2d,p)`.
minor_base : str
valid gaussian DFT base. This will be used for the non-central residue's atoms.
Defaults to `3-21G`.
"""
if folder is None:
folder = os.path.splitext(os.path.basename(protein))[0]
prot = Protein(pdb=protein, regularize=False)
tors = prot.get_torsionals()
seq = prot.sequence
for idx, aa in enumerate(seq[1:-1]):
pept = Protein('BG{}GZ'.format(aa))
for i in range(0, 3):
phi = tors.iloc[idx+i].phi
psi = tors.iloc[idx+i].psi
if np.isfinite(phi):
pept.set_phi(i+1, phi)
if np.isfinite(psi):
pept.set_psi(i+1, psi)
if i == 2:
for j in range(1, 6):
chi = tors.iloc[idx+i]['chi{}'.format(j)]
if np.isfinite(chi):
pept.set_chi(2, j, chi)
directory = '{}/M_{}'.format(folder, idx)
if not os.path.exists(directory):
os.makedirs(directory)
if save_pdb:
pept.dump_pdb('{}/test'.format(directory))
if gaussian:
_write_gaussian_file(pept, directory, header, main_base, minor_base)
def _write_gaussian_file(pept, directory, header, main_base, minor_base):
"""
pept : protein object
directory : str
Path to the directory containing the generated files.
header : str
Valid header for Gaussian job file. Only works if `gaussian` is True
main_base : str
valid gaussian DFT base. This will be used for the central residue's atoms.
minor_base : str
valid gaussian DFT base. This will be used for the non-central residue's atoms.
"""
fd = open('{}/RES.com'.format(directory), 'w')
fd.write(header)
for idx, xyz in enumerate(pept.coords):
atom_type = pept._elements[idx]
fd.write(' %s%9.3f%8.3f%8.3f\n' % (atom_type, *xyz))
fd.write('\n')
string = " 1 2 3 4 5 6 7 8 9 10 11 12 13 0\n 3-21G\n ****\n"
atoms = len(pept.at_coords(2))
for atom in range(14, atoms+14):
string = string + ' %s ' % atom
string = string + '0\n {}\n ****\n'.format(main_base)
for atom in range(atoms+14, atoms+27):
string = string + ' %s ' % atom
string = string + '0\n {}\n ****\n\n\n'.format(minor_base)
fd.write(string)
fd.close() | 0.501953 | 0.218941 |
class CircularQueue:
def __init__(self, k: int):
self.queue = [0] * k # initialize list with size `k`(`max_size`).
self.size = 0 # number of elements present in the queue.
self.max_size = k
self.front = self.rear = -1
def enqueue(self, value: int) -> bool:
if self.is_empty(): # As the queue is empty, front = rear = -1.
# set front = rear = 0, as there will be only 1 element in the queue.
self.front = self.rear = 0
self.queue[self.rear] = value
self.size += 1
return True
if self.is_full():
# As the queue is full we cannot add more elements to the queue.
return False
# As this is a circular queue use the mod operator to find the next position to the element.
# eg. [4, 1, 3, 4, 5]
# f r , where f = front, r = rear
# next position = (r + 1) % max_size = (4 + 1) % 5 = 0
self.rear = (self.rear + 1) % self.max_size
self.queue[self.rear] = value
self.size += 1
return True
def dequeue(self) -> bool:
if self.is_empty():
# As the queue is empty we cannot remove elements from the queue.
return False
if self.size == 1:
# As the queue contains only 1 element, after remove that element queue will be empty.
self.front = self.rear = -1 # So, set the front = rear = -1
self.size -= 1
return True
self.front = (self.front + 1) % self.max_size # refer enqueue.
self.size -= 1
return True
def front(self) -> int:
if self.is_empty():
return self.front
return self.queue[self.front]
def rear(self) -> int:
if self.is_empty():
return self.rear
return self.queue[self.rear]
def is_empty(self) -> bool:
return self.size == 0
def is_full(self) -> bool:
return self.size == self.max_size
def main():
circular_queue = CircularQueue(3)
print(circular_queue.enqueue(1))
print(circular_queue.enqueue(2))
print(circular_queue.is_empty())
if __name__ == "__main__":
main() | algorithms/data_structures/queue/problems/design_circular_queue.py |
class CircularQueue:
def __init__(self, k: int):
self.queue = [0] * k # initialize list with size `k`(`max_size`).
self.size = 0 # number of elements present in the queue.
self.max_size = k
self.front = self.rear = -1
def enqueue(self, value: int) -> bool:
if self.is_empty(): # As the queue is empty, front = rear = -1.
# set front = rear = 0, as there will be only 1 element in the queue.
self.front = self.rear = 0
self.queue[self.rear] = value
self.size += 1
return True
if self.is_full():
# As the queue is full we cannot add more elements to the queue.
return False
# As this is a circular queue use the mod operator to find the next position to the element.
# eg. [4, 1, 3, 4, 5]
# f r , where f = front, r = rear
# next position = (r + 1) % max_size = (4 + 1) % 5 = 0
self.rear = (self.rear + 1) % self.max_size
self.queue[self.rear] = value
self.size += 1
return True
def dequeue(self) -> bool:
if self.is_empty():
# As the queue is empty we cannot remove elements from the queue.
return False
if self.size == 1:
# As the queue contains only 1 element, after remove that element queue will be empty.
self.front = self.rear = -1 # So, set the front = rear = -1
self.size -= 1
return True
self.front = (self.front + 1) % self.max_size # refer enqueue.
self.size -= 1
return True
def front(self) -> int:
if self.is_empty():
return self.front
return self.queue[self.front]
def rear(self) -> int:
if self.is_empty():
return self.rear
return self.queue[self.rear]
def is_empty(self) -> bool:
return self.size == 0
def is_full(self) -> bool:
return self.size == self.max_size
def main():
circular_queue = CircularQueue(3)
print(circular_queue.enqueue(1))
print(circular_queue.enqueue(2))
print(circular_queue.is_empty())
if __name__ == "__main__":
main() | 0.781997 | 0.461441 |
import requests
from time import sleep
from random import seed
from random import randint
url = "https://api.telegram.org/bot780148416:AAF7vAzAs7kHR5jmHA6ANsP3ZL5KnAWettU/"
def get_updates_json(request):
response = requests.get(request + 'getUpdates')
return response.json()
def last_update(data):
results = data['result']
total_updates = len(results) - 1
return results[total_updates]
def get_chat_id(update):
chat_id = update['message']['chat']['id']
return chat_id
def get_chat_text(update):
text = update['message']['text']
return text
def send_mess(chat, text):
params = {'chat_id': chat, 'text': text}
response = requests.post(url + 'sendMessage', data=params)
return response
#chat_id = get_chat_id(last_update(get_updates_json(url)))
#send_mess(chat_id, 'this shit work')
def main():
update_id = last_update(get_updates_json(url))['update_id']
#Нужен массив из ClientID и вариантов
a = {}
seed(1)
while True:
if update_id == last_update(get_updates_json(url))['update_id']:
chat_id = get_chat_id(last_update(get_updates_json(url)))
if chat_id not in a:
a[chat_id]=[]
client_text = get_chat_text(last_update(get_updates_json(url)))
#Если текст был не /random то выводить "Введите вариант", иначе Результат "Пожалуй это лучшее решение: "
result_text = 'Enter opinion' if client_text<>'/random' else 'Just Do It: '
if client_text<>'/random':
a[chat_id].append(client_text)
elif client_text == '/random':
if chat_id not in a:
result_text = 'Before type some opinions'
elif len(a[chat_id])<1:
result_text = 'Before type some opinions'
else:
size = len(a[chat_id])
index = randint(0,size-1)
result_text += a[chat_id][index]
del a[chat_id]
send_mess(chat_id, result_text)
update_id += 1
sleep(1)
if __name__ == '__main__':
main() | app.py | import requests
from time import sleep
from random import seed
from random import randint
url = "https://api.telegram.org/bot780148416:AAF7vAzAs7kHR5jmHA6ANsP3ZL5KnAWettU/"
def get_updates_json(request):
response = requests.get(request + 'getUpdates')
return response.json()
def last_update(data):
results = data['result']
total_updates = len(results) - 1
return results[total_updates]
def get_chat_id(update):
chat_id = update['message']['chat']['id']
return chat_id
def get_chat_text(update):
text = update['message']['text']
return text
def send_mess(chat, text):
params = {'chat_id': chat, 'text': text}
response = requests.post(url + 'sendMessage', data=params)
return response
#chat_id = get_chat_id(last_update(get_updates_json(url)))
#send_mess(chat_id, 'this shit work')
def main():
update_id = last_update(get_updates_json(url))['update_id']
#Нужен массив из ClientID и вариантов
a = {}
seed(1)
while True:
if update_id == last_update(get_updates_json(url))['update_id']:
chat_id = get_chat_id(last_update(get_updates_json(url)))
if chat_id not in a:
a[chat_id]=[]
client_text = get_chat_text(last_update(get_updates_json(url)))
#Если текст был не /random то выводить "Введите вариант", иначе Результат "Пожалуй это лучшее решение: "
result_text = 'Enter opinion' if client_text<>'/random' else 'Just Do It: '
if client_text<>'/random':
a[chat_id].append(client_text)
elif client_text == '/random':
if chat_id not in a:
result_text = 'Before type some opinions'
elif len(a[chat_id])<1:
result_text = 'Before type some opinions'
else:
size = len(a[chat_id])
index = randint(0,size-1)
result_text += a[chat_id][index]
del a[chat_id]
send_mess(chat_id, result_text)
update_id += 1
sleep(1)
if __name__ == '__main__':
main() | 0.08629 | 0.050424 |
import warnings
import numpy as np
import tensorflow as tf
from keras import backend as K
from sklearn.metrics import confusion_matrix
def dice_multiclass(smooth=0, ignore_background=0, n_classes=26):
"""DICE coefficient for multiclass classification for integer inputs (not one-hot-encoded).
Computes the DICE coefficient as average over multiple classes. Also known as F1-score or F-measure.
Can ignore background label 0.
:param y_true: Ground truth target values.
:param y_pred: The logits.
:param smooth: Smoothing factor.
:param ignore_background: 0 for compute the average witch background label. 1 for compute the average without
background label.
:param n_classes: Number of classes to predict.
:return: DICE coefficient as average of all classes in multilabel classification.
"""
def dice_multi(y_true, y_pred):
y_true = K.one_hot(K.cast(y_true, 'uint8'), num_classes=n_classes)
y_true_f = K.reshape(y_true[..., ignore_background:], (-1, n_classes))
y_pred_f = K.reshape(y_pred[..., ignore_background:], (-1, n_classes))
intersect = K.sum(y_true_f * y_pred_f, axis=0)
numerator = 2. * intersect
denominator = K.sum(y_true_f + y_pred_f, axis=0)
dice = K.mean((numerator + smooth) / (denominator + smooth))
return dice
return dice_multi
def balanced_accuracy_score(y_true, y_pred, sample_weight=None,
adjusted=False):
"""Compute the balanced accuracy
The balanced accuracy in binary and multiclass classification problems to
deal with imbalanced datasets. It is defined as the average of recall
obtained on each class.
The best value is 1 and the worst value is 0 when ``adjusted=False``.
This is a re-implementation of the balanced_accuracy_score for scikit-learn. The only difference is that this
function returns also the average class accuracy per each class, which takes place at the end of the code in:
> return score, per_class
Parameters
----------
y_true : 1d array-like
Ground truth (correct) target values.
y_pred : 1d array-like
Estimated targets as returned by a classifier.
sample_weight : array-like of shape = [n_samples], optional
Sample weights.
adjusted : bool, default=False
When true, the result is adjusted for chance, so that random
performance would score 0, and perfect performance scores 1.
Returns
-------
balanced_accuracy : float
Notes
-----
Some literature promotes alternative definitions of balanced accuracy. Our
definition is equivalent to :func:`accuracy_score` with class-balanced
sample weights, and shares desirable properties with the binary case.
See the :ref:`User Guide <balanced_accuracy_score>`.
References
----------
.. [1] <NAME>.; <NAME>.; <NAME>.; <NAME>. (2010).
The balanced accuracy and its posterior distribution.
Proceedings of the 20th International Conference on Pattern
Recognition, 3121-24.
.. [2] <NAME>, <NAME>, <NAME>, (2015).
`Fundamentals of Machine Learning for Predictive Data Analytics:
Algorithms, Worked Examples, and Case Studies
<https://mitpress.mit.edu/books/fundamentals-machine-learning-predictive-data-analytics>`_.
"""
C = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
with np.errstate(divide='ignore', invalid='ignore'):
per_class = np.diag(C) / C.sum(axis=1)
if np.any(np.isnan(per_class)):
warnings.warn('y_pred contains classes not in y_true')
per_class = per_class[~np.isnan(per_class)]
score = np.mean(per_class)
if adjusted:
n_classes = len(per_class)
chance = 1 / n_classes
score -= chance
score /= 1 - chance
return score, per_class | src/generalutils/metrics.py | import warnings
import numpy as np
import tensorflow as tf
from keras import backend as K
from sklearn.metrics import confusion_matrix
def dice_multiclass(smooth=0, ignore_background=0, n_classes=26):
"""DICE coefficient for multiclass classification for integer inputs (not one-hot-encoded).
Computes the DICE coefficient as average over multiple classes. Also known as F1-score or F-measure.
Can ignore background label 0.
:param y_true: Ground truth target values.
:param y_pred: The logits.
:param smooth: Smoothing factor.
:param ignore_background: 0 for compute the average witch background label. 1 for compute the average without
background label.
:param n_classes: Number of classes to predict.
:return: DICE coefficient as average of all classes in multilabel classification.
"""
def dice_multi(y_true, y_pred):
y_true = K.one_hot(K.cast(y_true, 'uint8'), num_classes=n_classes)
y_true_f = K.reshape(y_true[..., ignore_background:], (-1, n_classes))
y_pred_f = K.reshape(y_pred[..., ignore_background:], (-1, n_classes))
intersect = K.sum(y_true_f * y_pred_f, axis=0)
numerator = 2. * intersect
denominator = K.sum(y_true_f + y_pred_f, axis=0)
dice = K.mean((numerator + smooth) / (denominator + smooth))
return dice
return dice_multi
def balanced_accuracy_score(y_true, y_pred, sample_weight=None,
adjusted=False):
"""Compute the balanced accuracy
The balanced accuracy in binary and multiclass classification problems to
deal with imbalanced datasets. It is defined as the average of recall
obtained on each class.
The best value is 1 and the worst value is 0 when ``adjusted=False``.
This is a re-implementation of the balanced_accuracy_score for scikit-learn. The only difference is that this
function returns also the average class accuracy per each class, which takes place at the end of the code in:
> return score, per_class
Parameters
----------
y_true : 1d array-like
Ground truth (correct) target values.
y_pred : 1d array-like
Estimated targets as returned by a classifier.
sample_weight : array-like of shape = [n_samples], optional
Sample weights.
adjusted : bool, default=False
When true, the result is adjusted for chance, so that random
performance would score 0, and perfect performance scores 1.
Returns
-------
balanced_accuracy : float
Notes
-----
Some literature promotes alternative definitions of balanced accuracy. Our
definition is equivalent to :func:`accuracy_score` with class-balanced
sample weights, and shares desirable properties with the binary case.
See the :ref:`User Guide <balanced_accuracy_score>`.
References
----------
.. [1] <NAME>.; <NAME>.; <NAME>.; <NAME>. (2010).
The balanced accuracy and its posterior distribution.
Proceedings of the 20th International Conference on Pattern
Recognition, 3121-24.
.. [2] <NAME>, <NAME>, <NAME>, (2015).
`Fundamentals of Machine Learning for Predictive Data Analytics:
Algorithms, Worked Examples, and Case Studies
<https://mitpress.mit.edu/books/fundamentals-machine-learning-predictive-data-analytics>`_.
"""
C = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
with np.errstate(divide='ignore', invalid='ignore'):
per_class = np.diag(C) / C.sum(axis=1)
if np.any(np.isnan(per_class)):
warnings.warn('y_pred contains classes not in y_true')
per_class = per_class[~np.isnan(per_class)]
score = np.mean(per_class)
if adjusted:
n_classes = len(per_class)
chance = 1 / n_classes
score -= chance
score /= 1 - chance
return score, per_class | 0.943582 | 0.726098 |
from ESNtools import *
from pandas import DataFrame, concat
from sklearn.metrics import mean_squared_error, f1_score
from sklearn.preprocessing import MinMaxScaler
dataset = np.load("Datasets/dataset_A_normal_subs_sepsis_late.npy")
# features = dataset[:-6, :-3]
# labels = dataset[6:, :-3]
def timeseries_to_supervised(data, lag=1):
'''
Construct the problem as supervised. I did NOT do this function, it was taken from:
https://machinelearningmastery.com/time-series-forecasting-long-short-term-memory-network-python/
'''
df = DataFrame(data)
columns = [df.shift(i) for i in range(1, lag+1)]
columns.append(df)
df = concat(columns, axis=1)
df.fillna(0, inplace=True)
return df
'''
In the rest of the script, I assumed that the dataset was in the form of features, labels per sample, labels per patient, patient ID.
'''
rmse_list = []
for patient_id in np.unique(dataset[:, -1]):
print(patient_id)
# Get patient
patient = dataset[np.where(dataset[:, -1] == patient_id)[0]][:, :-3]
scaler = MinMaxScaler(feature_range=(0, 1))
scaler = scaler.fit(patient)
patient = scaler.transform(patient)
# The framing of the problem is done for each patient
train = timeseries_to_supervised(patient[:, :-3], 6).values
# The labels/target are now future samples. The transformation done by timeseries_to_supervised()
# allow us to divide the input an output as such:
X, y = train[:, 0:-patient.shape[1]], train[:, -patient.shape[1]:]
# Build the Net
ESN = feedESN(X, 200, scale=.001, mem=.1, func=sigmoid, f_arg=10, silent=True)
w = get_weights_lu_biasedNE(ESN, y)
# The predictions should correspond to a future sample, so, the shape is (1, 40)
predictions = np.matmul(ESN, w)
# Evaluate the performance.
rmse = np.sqrt(mean_squared_error(y, predictions))
print("RMSE: ", rmse)
rmse_list.append(rmse)
# I don't remember why I did this...
sepsis_label = []
for patient_id in np.unique(dataset[:, -1]):
print(patient_id)
sepsis_label.append(dataset[np.where(dataset[:, -1] == patient_id)[0]][:, -2][0])
# This was a tentative based on the comparison of what was expected and what we got.
# The threshold was used to optimise the f1-score.
f1_list = []
new_rmse_list = rmse_list
for value in np.arange(0, 100, .001):
print(value)
new_rmse_list[np.where(rmse_list <= np.percentile(rmse_list, value))[0]] = 0
new_rmse_list[np.where(rmse_list > np.percentile(rmse_list, value))[0]] = 1
f1_list.append(f1_score(sepsis_label, new_rmse_list))
print("Mean RMSE: ", np.mean(rmse_list)) | Rui/test_network_predictions.py | from ESNtools import *
from pandas import DataFrame, concat
from sklearn.metrics import mean_squared_error, f1_score
from sklearn.preprocessing import MinMaxScaler
dataset = np.load("Datasets/dataset_A_normal_subs_sepsis_late.npy")
# features = dataset[:-6, :-3]
# labels = dataset[6:, :-3]
def timeseries_to_supervised(data, lag=1):
'''
Construct the problem as supervised. I did NOT do this function, it was taken from:
https://machinelearningmastery.com/time-series-forecasting-long-short-term-memory-network-python/
'''
df = DataFrame(data)
columns = [df.shift(i) for i in range(1, lag+1)]
columns.append(df)
df = concat(columns, axis=1)
df.fillna(0, inplace=True)
return df
'''
In the rest of the script, I assumed that the dataset was in the form of features, labels per sample, labels per patient, patient ID.
'''
rmse_list = []
for patient_id in np.unique(dataset[:, -1]):
print(patient_id)
# Get patient
patient = dataset[np.where(dataset[:, -1] == patient_id)[0]][:, :-3]
scaler = MinMaxScaler(feature_range=(0, 1))
scaler = scaler.fit(patient)
patient = scaler.transform(patient)
# The framing of the problem is done for each patient
train = timeseries_to_supervised(patient[:, :-3], 6).values
# The labels/target are now future samples. The transformation done by timeseries_to_supervised()
# allow us to divide the input an output as such:
X, y = train[:, 0:-patient.shape[1]], train[:, -patient.shape[1]:]
# Build the Net
ESN = feedESN(X, 200, scale=.001, mem=.1, func=sigmoid, f_arg=10, silent=True)
w = get_weights_lu_biasedNE(ESN, y)
# The predictions should correspond to a future sample, so, the shape is (1, 40)
predictions = np.matmul(ESN, w)
# Evaluate the performance.
rmse = np.sqrt(mean_squared_error(y, predictions))
print("RMSE: ", rmse)
rmse_list.append(rmse)
# I don't remember why I did this...
sepsis_label = []
for patient_id in np.unique(dataset[:, -1]):
print(patient_id)
sepsis_label.append(dataset[np.where(dataset[:, -1] == patient_id)[0]][:, -2][0])
# This was a tentative based on the comparison of what was expected and what we got.
# The threshold was used to optimise the f1-score.
f1_list = []
new_rmse_list = rmse_list
for value in np.arange(0, 100, .001):
print(value)
new_rmse_list[np.where(rmse_list <= np.percentile(rmse_list, value))[0]] = 0
new_rmse_list[np.where(rmse_list > np.percentile(rmse_list, value))[0]] = 1
f1_list.append(f1_score(sepsis_label, new_rmse_list))
print("Mean RMSE: ", np.mean(rmse_list)) | 0.572723 | 0.505493 |
import cloudinary.models
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='Profile',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('profile_photo', cloudinary.models.CloudinaryField(max_length=255, verbose_name='profile_photo')),
('bio', models.TextField()),
('phone_number', models.IntegerField()),
('email', models.EmailField(max_length=254)),
('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='Project',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('project_title', models.CharField(max_length=20)),
('project_description', models.CharField(max_length=20)),
('project_screenshot', cloudinary.models.CloudinaryField(max_length=255, verbose_name='project_screenshot')),
('project_link', models.URLField()),
('date_posted', models.DateTimeField(auto_now_add=True)),
('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='awards.Profile')),
],
),
migrations.CreateModel(
name='Review',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('design', models.IntegerField()),
('usability', models.IntegerField()),
('content', models.IntegerField()),
('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='awards.Project')),
('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
] | awards/migrations/0001_initial.py |
import cloudinary.models
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='Profile',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('profile_photo', cloudinary.models.CloudinaryField(max_length=255, verbose_name='profile_photo')),
('bio', models.TextField()),
('phone_number', models.IntegerField()),
('email', models.EmailField(max_length=254)),
('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='Project',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('project_title', models.CharField(max_length=20)),
('project_description', models.CharField(max_length=20)),
('project_screenshot', cloudinary.models.CloudinaryField(max_length=255, verbose_name='project_screenshot')),
('project_link', models.URLField()),
('date_posted', models.DateTimeField(auto_now_add=True)),
('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='awards.Profile')),
],
),
migrations.CreateModel(
name='Review',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('design', models.IntegerField()),
('usability', models.IntegerField()),
('content', models.IntegerField()),
('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='awards.Project')),
('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
] | 0.524882 | 0.101367 |
import ns_nested_sampling_ray as ns
import numpy as np
from contextlib import contextmanager
import os
import sys
from input_deck import inputs
import multiprocessing
import ns_data_modules as dm
# the input deck : specify these input parameters
import ns_show_results as sr
def driver(c,suppress_output=False):
check_inputs(c=c)
trial1 = ns.nested_sampling(Nb_sequences=c.Nb_sequences)
step = c.nb_loops // c.nb_snapshots
loops_2_show=np.arange(0,c.nb_loops+step,step)
loops_2_show[-1]=c.nb_loops-1
if suppress_output is True:
with dm.suppress_stdout():
times=trial1.nested_sample(c=c,loops_2_show=loops_2_show)
else:
times = trial1.nested_sample(c=c,loops_2_show=loops_2_show)
return times
print('with %i cpus'%multiprocessing.cpu_count())
print(times)
def check_inputs(c):
if c.nb_loops<0 or c.nb_steps<0:
raise AttributeError('Number of loops or number of steps is less than zero')
if c.nb_snapshots > c.nb_loops:
raise AttributeError('Number of snapshots is greater than Number of loops')
if c.mutation_type != 'static' and c.mutation_type!='dynamic':
raise AttributeError('invalid mutations type: %s'%c.mutation_type)
if c.nb_mutations<0 or c.nb_mutations>16:
raise AttributeError('Invalid # of mutations: %i'%c.nb_mutations)
if c.Nb_sequences <0:
raise AttributeError('Invalid # of sequences: %i'%c.Nb_sequences)
# c=inputs(nb_loops=100000,
# nb_steps=5,
# mutation_type='dynamic',
# nb_mutations=10,
# nb_snapshots=25,
# Nb_sequences=10000,
# yield2optimize='Developability',
# nb_cores=8)
c=inputs(nb_loops=5,
nb_steps=2,
mutation_type='dynamic',
nb_mutations=12,
nb_snapshots=3,
Nb_sequences=1000,
yield2optimize='Developability',
nb_cores=8)
#todo:
# find a way to get the number of cores on a numa node
# stop output from cores so their is no core files in your directories.
if sys.platform=='darwin':
suppress_output = False
else:
suppress_output=True
driver(c=c,suppress_output=False)
# sr.main(C=[c]) | ns_main_sampling.py | import ns_nested_sampling_ray as ns
import numpy as np
from contextlib import contextmanager
import os
import sys
from input_deck import inputs
import multiprocessing
import ns_data_modules as dm
# the input deck : specify these input parameters
import ns_show_results as sr
def driver(c,suppress_output=False):
check_inputs(c=c)
trial1 = ns.nested_sampling(Nb_sequences=c.Nb_sequences)
step = c.nb_loops // c.nb_snapshots
loops_2_show=np.arange(0,c.nb_loops+step,step)
loops_2_show[-1]=c.nb_loops-1
if suppress_output is True:
with dm.suppress_stdout():
times=trial1.nested_sample(c=c,loops_2_show=loops_2_show)
else:
times = trial1.nested_sample(c=c,loops_2_show=loops_2_show)
return times
print('with %i cpus'%multiprocessing.cpu_count())
print(times)
def check_inputs(c):
if c.nb_loops<0 or c.nb_steps<0:
raise AttributeError('Number of loops or number of steps is less than zero')
if c.nb_snapshots > c.nb_loops:
raise AttributeError('Number of snapshots is greater than Number of loops')
if c.mutation_type != 'static' and c.mutation_type!='dynamic':
raise AttributeError('invalid mutations type: %s'%c.mutation_type)
if c.nb_mutations<0 or c.nb_mutations>16:
raise AttributeError('Invalid # of mutations: %i'%c.nb_mutations)
if c.Nb_sequences <0:
raise AttributeError('Invalid # of sequences: %i'%c.Nb_sequences)
# c=inputs(nb_loops=100000,
# nb_steps=5,
# mutation_type='dynamic',
# nb_mutations=10,
# nb_snapshots=25,
# Nb_sequences=10000,
# yield2optimize='Developability',
# nb_cores=8)
c=inputs(nb_loops=5,
nb_steps=2,
mutation_type='dynamic',
nb_mutations=12,
nb_snapshots=3,
Nb_sequences=1000,
yield2optimize='Developability',
nb_cores=8)
#todo:
# find a way to get the number of cores on a numa node
# stop output from cores so their is no core files in your directories.
if sys.platform=='darwin':
suppress_output = False
else:
suppress_output=True
driver(c=c,suppress_output=False)
# sr.main(C=[c]) | 0.277375 | 0.271053 |
from threading import Thread
import socket
class Listener(Thread):
def __init__ (self, my_color, queue_receiver, queue_sender, ips, my_ip, socket):
Thread.__init__(self)
self.my_ip = my_ip
self.port = 5001
self.queue_receiver = queue_receiver
self.queue_sender = queue_sender
self.my_color = my_color
self.ips = ips
self.socket = socket
def run(self):
self.socket.pop()
self.socket.append(socket.socket(socket.AF_INET, socket.SOCK_STREAM))
self.socket[0].bind((self.my_ip, self.port))
self.socket[0].listen(10)
while True:
print("Waiting for senders on " + self.my_ip + ":" + str(self.port))
connection, client = self.socket[0].accept()
print("Receiving data from " + client[0] + ":" + str(client[1]))
while True:
data_raw = connection.recv(65565)
if not data_raw:
print(client[0] + ":" + str(client[1]) + " Disconnected")
break
data = data_raw.decode('utf-8')
data = data.split(":")
index = 1
while index < len(data):
color = (int(data[index]), int(data[index+1]), int(data[index+2]))
if color != self.my_color:
if color not in self.queue_receiver:
self.queue_receiver[color] = []
if data[index+3] == "x":
self.queue_receiver[color].append("x")
self.queue_sender.append(":" + data[index] + ":" + data[index+1] + ":" + data[index+2] + ":x")
index = index + 4
else:
point = (int(data[index+3]), int(data[index+4]))
self.queue_receiver[color].append(point)
self.queue_sender.append(":" + data[index] + ":" + data[index+1] + ":" + data[index+2] + ":" + data[index+3] + ":" + data[index+4])
index = index + 5
else:
index = len(data) | Peer/listener.py | from threading import Thread
import socket
class Listener(Thread):
def __init__ (self, my_color, queue_receiver, queue_sender, ips, my_ip, socket):
Thread.__init__(self)
self.my_ip = my_ip
self.port = 5001
self.queue_receiver = queue_receiver
self.queue_sender = queue_sender
self.my_color = my_color
self.ips = ips
self.socket = socket
def run(self):
self.socket.pop()
self.socket.append(socket.socket(socket.AF_INET, socket.SOCK_STREAM))
self.socket[0].bind((self.my_ip, self.port))
self.socket[0].listen(10)
while True:
print("Waiting for senders on " + self.my_ip + ":" + str(self.port))
connection, client = self.socket[0].accept()
print("Receiving data from " + client[0] + ":" + str(client[1]))
while True:
data_raw = connection.recv(65565)
if not data_raw:
print(client[0] + ":" + str(client[1]) + " Disconnected")
break
data = data_raw.decode('utf-8')
data = data.split(":")
index = 1
while index < len(data):
color = (int(data[index]), int(data[index+1]), int(data[index+2]))
if color != self.my_color:
if color not in self.queue_receiver:
self.queue_receiver[color] = []
if data[index+3] == "x":
self.queue_receiver[color].append("x")
self.queue_sender.append(":" + data[index] + ":" + data[index+1] + ":" + data[index+2] + ":x")
index = index + 4
else:
point = (int(data[index+3]), int(data[index+4]))
self.queue_receiver[color].append(point)
self.queue_sender.append(":" + data[index] + ":" + data[index+1] + ":" + data[index+2] + ":" + data[index+3] + ":" + data[index+4])
index = index + 5
else:
index = len(data) | 0.252753 | 0.129568 |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
"""
The vyos logging_global fact class
It is in this file the configuration is collected from the device
for a given resource, parsed, and the facts tree is populated
based on the configuration.
"""
from ansible.module_utils.six import iteritems
from ansible_collections.ansible.netcommon.plugins.module_utils.network.common import (
utils,
)
from ansible_collections.vyos.vyos.plugins.module_utils.network.vyos.rm_templates.logging_global import (
Logging_globalTemplate,
)
from ansible_collections.vyos.vyos.plugins.module_utils.network.vyos.argspec.logging_global.logging_global import (
Logging_globalArgs,
)
class Logging_globalFacts(object):
"""The vyos logging_global facts class"""
def __init__(self, module, subspec="config", options="options"):
self._module = module
self.argument_spec = Logging_globalArgs.argument_spec
def get_logging_data(self, connection):
return connection.get("show configuration commands | grep syslog")
def process_facts(self, objFinal):
if objFinal:
for ke, vl in iteritems(objFinal):
if ke == "files":
_files = []
for k, v in vl.items():
_files.append(v)
objFinal[ke] = _files
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["path"]
)
elif ke == "hosts":
_hosts = []
for k, v in vl.items():
_hosts.append(v)
objFinal[ke] = _hosts
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["hostname"]
)
elif ke == "users":
_users = []
for k, v in vl.items():
_users.append(v)
objFinal[ke] = _users
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["username"]
)
elif ke == "console" or ke == "global_params":
if objFinal[ke].get("facilities"):
objFinal[ke]["facilities"] = sorted(
objFinal[ke]["facilities"],
key=lambda item: item["facility"],
)
return objFinal
def populate_facts(self, connection, ansible_facts, data=None):
"""Populate the facts for Logging_global network resource
:param connection: the device connection
:param ansible_facts: Facts dictionary
:param data: previously collected conf
:rtype: dictionary
:returns: facts
"""
facts = {}
objs = []
if not data:
data = self.get_logging_data(connection)
# parse native config using the Logging_global template
logging_global_parser = Logging_globalTemplate(
lines=data.splitlines(), module=self._module
)
objs = logging_global_parser.parse()
ansible_facts["ansible_network_resources"].pop("logging_global", None)
objs = self.process_facts(objs)
params = utils.remove_empties(
logging_global_parser.validate_config(
self.argument_spec, {"config": objs}, redact=True
)
)
facts["logging_global"] = params.get("config", {})
ansible_facts["ansible_network_resources"].update(facts)
return ansible_facts | venv/lib/python3.6/site-packages/ansible_collections/vyos/vyos/plugins/module_utils/network/vyos/facts/logging_global/logging_global.py |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
"""
The vyos logging_global fact class
It is in this file the configuration is collected from the device
for a given resource, parsed, and the facts tree is populated
based on the configuration.
"""
from ansible.module_utils.six import iteritems
from ansible_collections.ansible.netcommon.plugins.module_utils.network.common import (
utils,
)
from ansible_collections.vyos.vyos.plugins.module_utils.network.vyos.rm_templates.logging_global import (
Logging_globalTemplate,
)
from ansible_collections.vyos.vyos.plugins.module_utils.network.vyos.argspec.logging_global.logging_global import (
Logging_globalArgs,
)
class Logging_globalFacts(object):
"""The vyos logging_global facts class"""
def __init__(self, module, subspec="config", options="options"):
self._module = module
self.argument_spec = Logging_globalArgs.argument_spec
def get_logging_data(self, connection):
return connection.get("show configuration commands | grep syslog")
def process_facts(self, objFinal):
if objFinal:
for ke, vl in iteritems(objFinal):
if ke == "files":
_files = []
for k, v in vl.items():
_files.append(v)
objFinal[ke] = _files
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["path"]
)
elif ke == "hosts":
_hosts = []
for k, v in vl.items():
_hosts.append(v)
objFinal[ke] = _hosts
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["hostname"]
)
elif ke == "users":
_users = []
for k, v in vl.items():
_users.append(v)
objFinal[ke] = _users
objFinal[ke] = sorted(
objFinal[ke], key=lambda item: item["username"]
)
elif ke == "console" or ke == "global_params":
if objFinal[ke].get("facilities"):
objFinal[ke]["facilities"] = sorted(
objFinal[ke]["facilities"],
key=lambda item: item["facility"],
)
return objFinal
def populate_facts(self, connection, ansible_facts, data=None):
"""Populate the facts for Logging_global network resource
:param connection: the device connection
:param ansible_facts: Facts dictionary
:param data: previously collected conf
:rtype: dictionary
:returns: facts
"""
facts = {}
objs = []
if not data:
data = self.get_logging_data(connection)
# parse native config using the Logging_global template
logging_global_parser = Logging_globalTemplate(
lines=data.splitlines(), module=self._module
)
objs = logging_global_parser.parse()
ansible_facts["ansible_network_resources"].pop("logging_global", None)
objs = self.process_facts(objs)
params = utils.remove_empties(
logging_global_parser.validate_config(
self.argument_spec, {"config": objs}, redact=True
)
)
facts["logging_global"] = params.get("config", {})
ansible_facts["ansible_network_resources"].update(facts)
return ansible_facts | 0.701406 | 0.171442 |
import os
import argparse
import pandas as pd
import numpy as np
from modelmodel.behave import behave
from modelmodel.hrf import double_gamma as dg
from modelmodel.dm import convolve_hrf
parser = argparse.ArgumentParser(
description="Create a table of simulated behave data",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument(
"name", type=str,
help="Name of table"
)
parser.add_argument(
"N", type=int,
help="Number of samples"
)
parser.add_argument(
"--behave", type=str, default='learn',
help="Behavior learning mode"
)
parser.add_argument(
"--n_cond", type=int, default=1,
help="N cond"
)
parser.add_argument(
"--n_trials", type=int, default=60,
help="N trials/cond"
)
parser.add_argument(
"--convolve", type=bool, default=False,
help="Convolve each col with the (canonical) double gamma HRF"
)
parser.add_argument(
"--seed",
default=42, type=int,
help="RandomState seed"
)
args = parser.parse_args()
prng = np.random.RandomState(args.seed)
trials = []
ps = []
accs = []
count = []
index = []
for n in range(args.N):
if args.behave == 'learn':
trial, acc, p, prng = behave.learn(
args.n_cond, args.n_trials,
loc=prng.normal(3, .3), prng=prng
)
elif args.behave == 'random':
trial, acc, p, prng = behave.random(
args.n_cond, args.n_trials, prng=prng
)
else:
raise ValueError('--behave not understood')
trials.append(trial)
ps.append(p)
accs.append(acc)
l = trial.shape[0]
count.append(np.repeat(n, l))
index.append(np.arange(l, dtype=np.int))
count = np.concatenate(count)
index = np.concatenate(index)
trials = np.concatenate(trials)
accs = np.concatenate(accs)
ps = np.concatenate(ps)
box = np.zeros_like(trials)
box[trials > 0] = 1
data = np.vstack([count, index, trials, box, accs, ps]).transpose()
df = pd.DataFrame(data=data, columns=(
'count', 'index', 'trials', 'box', 'acc', 'p'
))
if args.convolve:
tocon = ['box', 'acc', 'p']
condf = convolve_hrf(df, dg(), tocon)
for con in tocon:
df[con] = condf[con]
df.to_csv(args.name, index=False, float_format='%.8f') | bin/behave.py | import os
import argparse
import pandas as pd
import numpy as np
from modelmodel.behave import behave
from modelmodel.hrf import double_gamma as dg
from modelmodel.dm import convolve_hrf
parser = argparse.ArgumentParser(
description="Create a table of simulated behave data",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument(
"name", type=str,
help="Name of table"
)
parser.add_argument(
"N", type=int,
help="Number of samples"
)
parser.add_argument(
"--behave", type=str, default='learn',
help="Behavior learning mode"
)
parser.add_argument(
"--n_cond", type=int, default=1,
help="N cond"
)
parser.add_argument(
"--n_trials", type=int, default=60,
help="N trials/cond"
)
parser.add_argument(
"--convolve", type=bool, default=False,
help="Convolve each col with the (canonical) double gamma HRF"
)
parser.add_argument(
"--seed",
default=42, type=int,
help="RandomState seed"
)
args = parser.parse_args()
prng = np.random.RandomState(args.seed)
trials = []
ps = []
accs = []
count = []
index = []
for n in range(args.N):
if args.behave == 'learn':
trial, acc, p, prng = behave.learn(
args.n_cond, args.n_trials,
loc=prng.normal(3, .3), prng=prng
)
elif args.behave == 'random':
trial, acc, p, prng = behave.random(
args.n_cond, args.n_trials, prng=prng
)
else:
raise ValueError('--behave not understood')
trials.append(trial)
ps.append(p)
accs.append(acc)
l = trial.shape[0]
count.append(np.repeat(n, l))
index.append(np.arange(l, dtype=np.int))
count = np.concatenate(count)
index = np.concatenate(index)
trials = np.concatenate(trials)
accs = np.concatenate(accs)
ps = np.concatenate(ps)
box = np.zeros_like(trials)
box[trials > 0] = 1
data = np.vstack([count, index, trials, box, accs, ps]).transpose()
df = pd.DataFrame(data=data, columns=(
'count', 'index', 'trials', 'box', 'acc', 'p'
))
if args.convolve:
tocon = ['box', 'acc', 'p']
condf = convolve_hrf(df, dg(), tocon)
for con in tocon:
df[con] = condf[con]
df.to_csv(args.name, index=False, float_format='%.8f') | 0.462959 | 0.147494 |
import argparse
import copy
import os
import sys
import time
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(parent_dir)
from taiyaki.taiyaki import Taiyaki
def run(taiyaki, query):
cp_list = taiyaki.commonPrefixSearch(query)
print('Common prefixes: {}'.format(cp_list))
tokens = taiyaki.tokenize(query)
print('Tokenized tokens (min cost):')
print('{}\t{}\t{}\t{}'.format('表層系', '品詞', '発音', '未知語'))
for t in tokens:
print('{}\t{}\t{}\t{}'.format(t['surface'], t['pos'], t['pron'], t['unk']))
tokens = taiyaki.longestSearch(query)
print('Tokenized tokens (longest match):', tokens)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--da_dic_file',
type=str,
default='./data/da.dict',
metavar='PATH',
help='double-array dictionary')
parser.add_argument('--vocab_dic_file',
type=str,
metavar='PATH',
default='./data/vocab.dict',
help='vocabulary dictionary')
parser.add_argument('--trans_cost_file',
type=str,
metavar='PATH',
default='./data/trans_cost.dict',
help='token transition cost dictionary')
parser.add_argument('--char_cat_def_file',
type=str,
metavar='PATH',
default='./data/char_cat_def.dict',
help='char.def dictionary for unk words')
parser.add_argument('-q', '--query',
type=str,
help='input query')
args = parser.parse_args()
taiyaki = Taiyaki(args.da_dic_file, args.vocab_dic_file, args.trans_cost_file, args.char_cat_def_file)
query = args.query
if query:
print('Input:', query)
run(taiyaki, query)
else:
while True:
query =input('Query (press "end" to exit)>> ')
if query == 'end':
break
run(taiyaki, query)
if __name__ == '__main__':
main() | examples/run_tokenizer.py | import argparse
import copy
import os
import sys
import time
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(parent_dir)
from taiyaki.taiyaki import Taiyaki
def run(taiyaki, query):
cp_list = taiyaki.commonPrefixSearch(query)
print('Common prefixes: {}'.format(cp_list))
tokens = taiyaki.tokenize(query)
print('Tokenized tokens (min cost):')
print('{}\t{}\t{}\t{}'.format('表層系', '品詞', '発音', '未知語'))
for t in tokens:
print('{}\t{}\t{}\t{}'.format(t['surface'], t['pos'], t['pron'], t['unk']))
tokens = taiyaki.longestSearch(query)
print('Tokenized tokens (longest match):', tokens)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--da_dic_file',
type=str,
default='./data/da.dict',
metavar='PATH',
help='double-array dictionary')
parser.add_argument('--vocab_dic_file',
type=str,
metavar='PATH',
default='./data/vocab.dict',
help='vocabulary dictionary')
parser.add_argument('--trans_cost_file',
type=str,
metavar='PATH',
default='./data/trans_cost.dict',
help='token transition cost dictionary')
parser.add_argument('--char_cat_def_file',
type=str,
metavar='PATH',
default='./data/char_cat_def.dict',
help='char.def dictionary for unk words')
parser.add_argument('-q', '--query',
type=str,
help='input query')
args = parser.parse_args()
taiyaki = Taiyaki(args.da_dic_file, args.vocab_dic_file, args.trans_cost_file, args.char_cat_def_file)
query = args.query
if query:
print('Input:', query)
run(taiyaki, query)
else:
while True:
query =input('Query (press "end" to exit)>> ')
if query == 'end':
break
run(taiyaki, query)
if __name__ == '__main__':
main() | 0.201813 | 0.088151 |
import logging
from vindauga.constants.buttons import bfDefault, bfNormal
from vindauga.constants.command_codes import cmSave, cmSaveAs, cmCut, cmCopy, cmPaste, cmClear, cmUndo, wnNoNumber, \
cmCancel
from vindauga.constants.command_codes import cmOpen, cmNew, cmTile, cmCascade, cmOK, hcNoContext, cmQuit, cmResize, \
cmZoom, cmNext, cmPrev, cmClose, cmMenu
from vindauga.constants.message_flags import mfError, mfInformation, mfYesButton, mfNoButton, mfOKButton, mfCancelButton
from vindauga.constants.edit_command_codes import *
from vindauga.constants.event_codes import evCommand
from vindauga.constants.keys import *
from vindauga.constants.std_dialog_commands import cdNormal
from vindauga.constants.option_flags import ofCentered, ofTileable
from vindauga.constants.state_flags import sfVisible
from vindauga.dialogs.change_dir_dialog import ChangeDirDialog
from vindauga.dialogs.file_dialog import FileDialog, fdOpenButton, fdOKButton
from vindauga.dialogs.message_box import messageBox, messageBoxRect
from vindauga.menus.menu_bar import MenuBar
from vindauga.menus.menu_item import MenuItem
from vindauga.menus.sub_menu import SubMenu
from vindauga.types.records.data_record import DataRecord
from vindauga.types.command_set import CommandSet
from vindauga.types.rect import Rect
from vindauga.types.status_def import StatusDef
from vindauga.types.status_item import StatusItem
from vindauga.widgets.application import Application
from vindauga.widgets.button import Button
from vindauga.widgets.check_boxes import CheckBoxes
from vindauga.widgets.edit_window import EditWindow
from vindauga.widgets.dialog import Dialog
from vindauga.widgets.history import History
from vindauga.widgets.input_line import InputLine
from vindauga.widgets.label import Label
from vindauga.widgets.program import Program
from vindauga.widgets.status_line import StatusLine
cmChangeDrct = 102
cmDosShell = 103
cmCalculator = 104
cmShowClip = 105
cmMacros = 106
def execDialog(d, data):
if data:
d.setData([data])
p = Program.application.validView(d)
if not p:
return cmCancel
result = Program.desktop.execView(p)
if result != cmCancel and data:
d = p.getData()
result = d.value
return result
def createFindDialog():
d = Dialog(Rect(0, 0, 38, 12), 'Find')
d.options |= ofCentered
control = InputLine(Rect(3, 3, 32, 4), 80)
d.insert(control)
d.insert(Label(Rect(2, 2, 32, 3), '~T~ext to find', control))
d.insert(History(Rect(32, 3, 35, 4), control, 10))
d.insert(CheckBoxes(Rect(3, 5, 35, 7), ('~C~ase sensitive', '~W~hole words only', None)))
d.insert(Button(Rect(14, 9, 24, 11), 'O~K~', cmOK, bfDefault))
d.insert(Button(Rect(26, 9, 36, 11), 'Cancel', cmCancel, bfNormal))
d.selectNext(False)
return d
def createReplaceDialog():
d = Dialog(Rect(0, 0, 40, 16), 'Replace')
d.options |= ofCentered
control = InputLine(Rect(3, 3, 34, 4), 80)
d.insert(control)
d.insert(Label(Rect(2, 2, 34, 3), '~T~ext to find', control))
d.insert(History(Rect(34, 3, 37, 4), control, 10))
control = InputLine(Rect(3, 6, 34, 7), 80)
d.insert(control)
d.insert(Label(Rect(2, 5, 34, 6), '~N~ew _text', control))
d.insert(History(Rect(34, 6, 37, 7), control, 11))
d.insert(CheckBoxes(Rect(3, 8, 37, 12), ('~C~ase sensitive', '~W~hole words only','~P~rompt on replace',
'~R~eplace all')))
d.insert(
Button(Rect(17, 13, 27, 15), 'O~K~', cmOK, bfDefault))
d.insert(Button(Rect(28, 13, 38, 15), 'Cancel', cmCancel, bfNormal))
d.selectNext(False)
return d
def isTileable(p, *args):
return p.options & ofTileable and p.state * sfVisible
class EditorApp(Application):
def __init__(self):
super().__init__()
ts = CommandSet()
ts.enableCmd(cmSave)
ts.enableCmd(cmSaveAs)
ts.enableCmd(cmCut)
ts.enableCmd(cmCopy)
ts.enableCmd(cmPaste)
ts.enableCmd(cmClear)
ts.enableCmd(cmUndo)
ts.enableCmd(cmFind)
ts.enableCmd(cmReplace)
ts.enableCmd(cmSearchAgain)
self.disableCommands(ts)
self.editorDialog = self.doEditorDialog
self.clipWindow = self.openEditor(None, False)
def initMenuBar(self, bounds):
bounds.bottomRight.y = bounds.topLeft.y + 1
sub1 = (SubMenu('~F~ile', kbAltF) +
MenuItem("~O~pen", cmOpen, kbF3, hcNoContext, "F3") +
MenuItem("~N~ew", cmNew, kbNoKey) +
MenuItem("~S~ave", cmSave, kbF2, hcNoContext, "F2") +
MenuItem("S~a~ve as...", cmSaveAs, kbNoKey) +
MenuItem.newLine() +
MenuItem("~C~hange dir...", cmChangeDrct, kbNoKey) +
MenuItem("E~x~it", cmQuit, kbAltX, hcNoContext, "Alt+X"))
sub2 = (SubMenu("~E~dit", kbAltE) +
MenuItem("~U~ndo", cmUndo, kbNoKey) +
MenuItem.newLine() +
MenuItem("Cu~t~", cmCut, kbShiftDel, hcNoContext, "Shift+Del") +
MenuItem("~C~opy", cmCopy, kbCtrlIns, hcNoContext, "Ctrl+Ins") +
MenuItem("~P~aste", cmPaste, kbShiftIns, hcNoContext, "Shift+Ins") +
MenuItem("~S~how clipboard", cmShowClip, kbNoKey) +
MenuItem.newLine() +
MenuItem("~C~lear", cmClear, kbCtrlDel, hcNoContext, "Ctrl+Del"))
sub3 = (SubMenu("~S~earch", kbAltS) +
MenuItem("~F~ind...", cmFind, kbNoKey) +
MenuItem("~R~eplace...", cmReplace, kbNoKey) +
MenuItem("~S~earch again", cmSearchAgain, kbNoKey))
sub4 = (SubMenu("~W~indows", kbAltW) +
MenuItem("~S~ize/move", cmResize, kbCtrlF5, hcNoContext, "Ctrl+F5") +
MenuItem("~Z~oom", cmZoom, kbF5, hcNoContext, "F5") +
MenuItem("~T~ile", cmTile, kbNoKey) +
MenuItem("C~a~scade", cmCascade, kbNoKey) +
MenuItem("~N~ext", cmNext, kbF6, hcNoContext, "F6") +
MenuItem("~P~revious", cmPrev, kbShiftF6, hcNoContext, "Shift+F6") +
MenuItem("~C~lose", cmClose, kbCtrlW, hcNoContext, "Ctrl+W"))
return MenuBar(bounds, sub1 + sub2 + sub3 + sub4)
def initStatusLine(self, bounds):
bounds.topLeft.y = bounds.bottomRight.y - 1
return StatusLine(bounds, StatusDef(0, 0xFFFF) +
StatusItem("~F10~ Menu", kbF10, cmMenu) +
StatusItem("~F2~ Save", kbF2, cmSave) +
StatusItem("~F3~ Open", kbF3, cmOpen) +
StatusItem("~Ctrl+W~ Close", kbCtrlW, cmClose) +
StatusItem("~F5~ Zoom", kbF5, cmZoom) +
StatusItem("~F6~ Next", kbF6, cmNext) +
StatusItem(0, kbCtrlF5, cmResize)
)
def doEditorDialog(self, dialog, *args):
if dialog == edOutOfMemory:
return messageBox('Not enough memory for this operation', mfError, (mfOKButton,))
if dialog == edReadError:
return messageBox('Error reading file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edWriteError:
return messageBox('Error writing file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edCreateError:
return messageBox('Error creating file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edSaveModify:
return messageBox('%s has been modified. Save?'.format(args[0]), mfInformation,
(mfYesButton, mfNoButton, mfCancelButton))
if dialog == edSaveUntitled:
return messageBox('Save untitled file?', mfInformation,
(mfYesButton, mfNoButton, mfCancelButton))
if dialog == edSaveUntitled:
return execDialog(
FileDialog('*.*', 'Save file as', '~N~ame', fdOKButton, 101), args[0]
)
if dialog == edSearchFailed:
return messageBox('Search string not found', mfError, (mfOKButton,))
if dialog == edReplace:
return execDialog(createReplaceDialog(), args[0])
if dialog == edReplacePrompt:
return self.doReplacePrompt(args[0])
def doReplacePrompt(self, cursor):
r = Rect(0, 2, 40, 9)
r.move((self.desktop.size.x - r.bottomRight.x) // 2, 0)
lower = self.desktop.makeGlobal(r.bottomRight)
if cursor.y <= lower.y:
r.move(0, (self.desktop.size.y - r.bottomRight.y) // 2)
return messageBoxRect(r, 'Replace this occurrence?', mfInformation, (mfYesButton, mfNoButton, mfCancelButton))
def openEditor(self, filename, visible):
r = self.desktop.getExtent()
p = self.validView(EditWindow(r, filename, wnNoNumber))
if not visible:
p.hide()
self.desktop.insert(p)
return p
def fileOpen(self):
filename = '*'
c = execDialog(FileDialog('*', 'Open file', '~N~ame', fdOpenButton, 100), filename)
if c != cmCancel:
self.openEditor(c, True)
def fileNew(self):
self.openEditor(None, True)
def changeDir(self):
execDialog(ChangeDirDialog(cdNormal, 0), None)
def doShell(self):
pass
def showClip(self):
self.clipWindow.select()
self.clipWindow.show()
def tile(self):
self.desktop.tile(self.desktop.getExtent())
def cascade(self):
self.desktop.cascade(self.desktop.getExtent())
def handleEvent(self, event):
super().handleEvent(event)
if event.what != evCommand:
return
emc = event.message.command
if emc == cmOpen:
if event.message.infoPtr:
self.openEditor(event.message.infoPtr, True)
else:
self.fileOpen()
elif emc == cmNew:
self.fileNew()
elif emc == cmChangeDrct:
self.changeDir()
elif emc == cmShowClip:
self.showClip()
elif emc == cmTile:
self.tile()
elif emc == cmCascade:
self.cascade()
else:
return
self.clearEvent(event)
def idle(self):
super().idle()
if self.desktop.firstThat(isTileable, 0):
self.enableCommand(cmTile)
self.enableCommand(cmCascade)
else:
for command in (cmSave, cmSaveAs, cmUndo, cmCut, cmCopy, cmPaste, cmClear,
cmFind, cmReplace, cmSearchAgain, cmTile, cmCascade):
self.disableCommand(command)
def setupLogging():
logger = logging.getLogger('vindauga')
logger.propagate = False
format = "%(name)s\t %(message)s"
logger.setLevel(logging.DEBUG)
handler = logging.StreamHandler(open('vindauga.log', 'wt'))
handler.setFormatter(logging.Formatter(format))
logger.addHandler(handler)
if __name__ == '__main__':
setupLogging()
app = EditorApp()
app.run() | examples/editor-app.py | import logging
from vindauga.constants.buttons import bfDefault, bfNormal
from vindauga.constants.command_codes import cmSave, cmSaveAs, cmCut, cmCopy, cmPaste, cmClear, cmUndo, wnNoNumber, \
cmCancel
from vindauga.constants.command_codes import cmOpen, cmNew, cmTile, cmCascade, cmOK, hcNoContext, cmQuit, cmResize, \
cmZoom, cmNext, cmPrev, cmClose, cmMenu
from vindauga.constants.message_flags import mfError, mfInformation, mfYesButton, mfNoButton, mfOKButton, mfCancelButton
from vindauga.constants.edit_command_codes import *
from vindauga.constants.event_codes import evCommand
from vindauga.constants.keys import *
from vindauga.constants.std_dialog_commands import cdNormal
from vindauga.constants.option_flags import ofCentered, ofTileable
from vindauga.constants.state_flags import sfVisible
from vindauga.dialogs.change_dir_dialog import ChangeDirDialog
from vindauga.dialogs.file_dialog import FileDialog, fdOpenButton, fdOKButton
from vindauga.dialogs.message_box import messageBox, messageBoxRect
from vindauga.menus.menu_bar import MenuBar
from vindauga.menus.menu_item import MenuItem
from vindauga.menus.sub_menu import SubMenu
from vindauga.types.records.data_record import DataRecord
from vindauga.types.command_set import CommandSet
from vindauga.types.rect import Rect
from vindauga.types.status_def import StatusDef
from vindauga.types.status_item import StatusItem
from vindauga.widgets.application import Application
from vindauga.widgets.button import Button
from vindauga.widgets.check_boxes import CheckBoxes
from vindauga.widgets.edit_window import EditWindow
from vindauga.widgets.dialog import Dialog
from vindauga.widgets.history import History
from vindauga.widgets.input_line import InputLine
from vindauga.widgets.label import Label
from vindauga.widgets.program import Program
from vindauga.widgets.status_line import StatusLine
cmChangeDrct = 102
cmDosShell = 103
cmCalculator = 104
cmShowClip = 105
cmMacros = 106
def execDialog(d, data):
if data:
d.setData([data])
p = Program.application.validView(d)
if not p:
return cmCancel
result = Program.desktop.execView(p)
if result != cmCancel and data:
d = p.getData()
result = d.value
return result
def createFindDialog():
d = Dialog(Rect(0, 0, 38, 12), 'Find')
d.options |= ofCentered
control = InputLine(Rect(3, 3, 32, 4), 80)
d.insert(control)
d.insert(Label(Rect(2, 2, 32, 3), '~T~ext to find', control))
d.insert(History(Rect(32, 3, 35, 4), control, 10))
d.insert(CheckBoxes(Rect(3, 5, 35, 7), ('~C~ase sensitive', '~W~hole words only', None)))
d.insert(Button(Rect(14, 9, 24, 11), 'O~K~', cmOK, bfDefault))
d.insert(Button(Rect(26, 9, 36, 11), 'Cancel', cmCancel, bfNormal))
d.selectNext(False)
return d
def createReplaceDialog():
d = Dialog(Rect(0, 0, 40, 16), 'Replace')
d.options |= ofCentered
control = InputLine(Rect(3, 3, 34, 4), 80)
d.insert(control)
d.insert(Label(Rect(2, 2, 34, 3), '~T~ext to find', control))
d.insert(History(Rect(34, 3, 37, 4), control, 10))
control = InputLine(Rect(3, 6, 34, 7), 80)
d.insert(control)
d.insert(Label(Rect(2, 5, 34, 6), '~N~ew _text', control))
d.insert(History(Rect(34, 6, 37, 7), control, 11))
d.insert(CheckBoxes(Rect(3, 8, 37, 12), ('~C~ase sensitive', '~W~hole words only','~P~rompt on replace',
'~R~eplace all')))
d.insert(
Button(Rect(17, 13, 27, 15), 'O~K~', cmOK, bfDefault))
d.insert(Button(Rect(28, 13, 38, 15), 'Cancel', cmCancel, bfNormal))
d.selectNext(False)
return d
def isTileable(p, *args):
return p.options & ofTileable and p.state * sfVisible
class EditorApp(Application):
def __init__(self):
super().__init__()
ts = CommandSet()
ts.enableCmd(cmSave)
ts.enableCmd(cmSaveAs)
ts.enableCmd(cmCut)
ts.enableCmd(cmCopy)
ts.enableCmd(cmPaste)
ts.enableCmd(cmClear)
ts.enableCmd(cmUndo)
ts.enableCmd(cmFind)
ts.enableCmd(cmReplace)
ts.enableCmd(cmSearchAgain)
self.disableCommands(ts)
self.editorDialog = self.doEditorDialog
self.clipWindow = self.openEditor(None, False)
def initMenuBar(self, bounds):
bounds.bottomRight.y = bounds.topLeft.y + 1
sub1 = (SubMenu('~F~ile', kbAltF) +
MenuItem("~O~pen", cmOpen, kbF3, hcNoContext, "F3") +
MenuItem("~N~ew", cmNew, kbNoKey) +
MenuItem("~S~ave", cmSave, kbF2, hcNoContext, "F2") +
MenuItem("S~a~ve as...", cmSaveAs, kbNoKey) +
MenuItem.newLine() +
MenuItem("~C~hange dir...", cmChangeDrct, kbNoKey) +
MenuItem("E~x~it", cmQuit, kbAltX, hcNoContext, "Alt+X"))
sub2 = (SubMenu("~E~dit", kbAltE) +
MenuItem("~U~ndo", cmUndo, kbNoKey) +
MenuItem.newLine() +
MenuItem("Cu~t~", cmCut, kbShiftDel, hcNoContext, "Shift+Del") +
MenuItem("~C~opy", cmCopy, kbCtrlIns, hcNoContext, "Ctrl+Ins") +
MenuItem("~P~aste", cmPaste, kbShiftIns, hcNoContext, "Shift+Ins") +
MenuItem("~S~how clipboard", cmShowClip, kbNoKey) +
MenuItem.newLine() +
MenuItem("~C~lear", cmClear, kbCtrlDel, hcNoContext, "Ctrl+Del"))
sub3 = (SubMenu("~S~earch", kbAltS) +
MenuItem("~F~ind...", cmFind, kbNoKey) +
MenuItem("~R~eplace...", cmReplace, kbNoKey) +
MenuItem("~S~earch again", cmSearchAgain, kbNoKey))
sub4 = (SubMenu("~W~indows", kbAltW) +
MenuItem("~S~ize/move", cmResize, kbCtrlF5, hcNoContext, "Ctrl+F5") +
MenuItem("~Z~oom", cmZoom, kbF5, hcNoContext, "F5") +
MenuItem("~T~ile", cmTile, kbNoKey) +
MenuItem("C~a~scade", cmCascade, kbNoKey) +
MenuItem("~N~ext", cmNext, kbF6, hcNoContext, "F6") +
MenuItem("~P~revious", cmPrev, kbShiftF6, hcNoContext, "Shift+F6") +
MenuItem("~C~lose", cmClose, kbCtrlW, hcNoContext, "Ctrl+W"))
return MenuBar(bounds, sub1 + sub2 + sub3 + sub4)
def initStatusLine(self, bounds):
bounds.topLeft.y = bounds.bottomRight.y - 1
return StatusLine(bounds, StatusDef(0, 0xFFFF) +
StatusItem("~F10~ Menu", kbF10, cmMenu) +
StatusItem("~F2~ Save", kbF2, cmSave) +
StatusItem("~F3~ Open", kbF3, cmOpen) +
StatusItem("~Ctrl+W~ Close", kbCtrlW, cmClose) +
StatusItem("~F5~ Zoom", kbF5, cmZoom) +
StatusItem("~F6~ Next", kbF6, cmNext) +
StatusItem(0, kbCtrlF5, cmResize)
)
def doEditorDialog(self, dialog, *args):
if dialog == edOutOfMemory:
return messageBox('Not enough memory for this operation', mfError, (mfOKButton,))
if dialog == edReadError:
return messageBox('Error reading file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edWriteError:
return messageBox('Error writing file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edCreateError:
return messageBox('Error creating file {}'.format(args[0]), mfError, (mfOKButton,))
if dialog == edSaveModify:
return messageBox('%s has been modified. Save?'.format(args[0]), mfInformation,
(mfYesButton, mfNoButton, mfCancelButton))
if dialog == edSaveUntitled:
return messageBox('Save untitled file?', mfInformation,
(mfYesButton, mfNoButton, mfCancelButton))
if dialog == edSaveUntitled:
return execDialog(
FileDialog('*.*', 'Save file as', '~N~ame', fdOKButton, 101), args[0]
)
if dialog == edSearchFailed:
return messageBox('Search string not found', mfError, (mfOKButton,))
if dialog == edReplace:
return execDialog(createReplaceDialog(), args[0])
if dialog == edReplacePrompt:
return self.doReplacePrompt(args[0])
def doReplacePrompt(self, cursor):
r = Rect(0, 2, 40, 9)
r.move((self.desktop.size.x - r.bottomRight.x) // 2, 0)
lower = self.desktop.makeGlobal(r.bottomRight)
if cursor.y <= lower.y:
r.move(0, (self.desktop.size.y - r.bottomRight.y) // 2)
return messageBoxRect(r, 'Replace this occurrence?', mfInformation, (mfYesButton, mfNoButton, mfCancelButton))
def openEditor(self, filename, visible):
r = self.desktop.getExtent()
p = self.validView(EditWindow(r, filename, wnNoNumber))
if not visible:
p.hide()
self.desktop.insert(p)
return p
def fileOpen(self):
filename = '*'
c = execDialog(FileDialog('*', 'Open file', '~N~ame', fdOpenButton, 100), filename)
if c != cmCancel:
self.openEditor(c, True)
def fileNew(self):
self.openEditor(None, True)
def changeDir(self):
execDialog(ChangeDirDialog(cdNormal, 0), None)
def doShell(self):
pass
def showClip(self):
self.clipWindow.select()
self.clipWindow.show()
def tile(self):
self.desktop.tile(self.desktop.getExtent())
def cascade(self):
self.desktop.cascade(self.desktop.getExtent())
def handleEvent(self, event):
super().handleEvent(event)
if event.what != evCommand:
return
emc = event.message.command
if emc == cmOpen:
if event.message.infoPtr:
self.openEditor(event.message.infoPtr, True)
else:
self.fileOpen()
elif emc == cmNew:
self.fileNew()
elif emc == cmChangeDrct:
self.changeDir()
elif emc == cmShowClip:
self.showClip()
elif emc == cmTile:
self.tile()
elif emc == cmCascade:
self.cascade()
else:
return
self.clearEvent(event)
def idle(self):
super().idle()
if self.desktop.firstThat(isTileable, 0):
self.enableCommand(cmTile)
self.enableCommand(cmCascade)
else:
for command in (cmSave, cmSaveAs, cmUndo, cmCut, cmCopy, cmPaste, cmClear,
cmFind, cmReplace, cmSearchAgain, cmTile, cmCascade):
self.disableCommand(command)
def setupLogging():
logger = logging.getLogger('vindauga')
logger.propagate = False
format = "%(name)s\t %(message)s"
logger.setLevel(logging.DEBUG)
handler = logging.StreamHandler(open('vindauga.log', 'wt'))
handler.setFormatter(logging.Formatter(format))
logger.addHandler(handler)
if __name__ == '__main__':
setupLogging()
app = EditorApp()
app.run() | 0.366023 | 0.070496 |
import json
import logging
import operator
import os
import sys
import webbrowser
from enum import Enum
from enum import unique
from typing import Optional
import click
import click_spinner
from tabulate import tabulate
from taurus_datajob_api import DataJobExecution
from taurus_datajob_api import DataJobExecutionLogs
from taurus_datajob_api import DataJobExecutionRequest
from vdk.internal.control.configuration.defaults_config import load_default_team_name
from vdk.internal.control.exception.vdk_exception import VDKException
from vdk.internal.control.rest_lib.factory import ApiClientFactory
from vdk.internal.control.rest_lib.rest_client_errors import ApiClientErrorDecorator
from vdk.internal.control.utils import cli_utils
from vdk.internal.control.utils.cli_utils import get_or_prompt
from vdk.internal.control.utils.cli_utils import OutputFormat
log = logging.getLogger(__name__)
@unique
class ExecuteOperation(Enum):
"""
An enum used to store the types of deploy operations
"""
START = "start"
CANCEL = "cancel"
WAIT = "wait"
SHOW = "show"
LIST = "list"
LOGS = "logs"
class JobExecute:
def __init__(self, rest_api_url: str):
self.__execution_api = ApiClientFactory(rest_api_url).get_execution_api()
@staticmethod
def __model_executions(executions, output: OutputFormat) -> str:
def transform_execution(e: DataJobExecution):
d = e.to_dict()
d["job_version"] = e.deployment.job_version
del d["deployment"]
return d
executions = list(map(lambda e: transform_execution(e), executions))
if output == OutputFormat.TEXT.value:
return tabulate(executions, headers="keys")
elif output == OutputFormat.JSON.value:
return cli_utils.json_format(list(executions))
@staticmethod
def __validate_and_parse_args(arguments: str) -> str:
try:
if arguments:
return json.loads(arguments)
else:
return {}
except Exception as e:
vdk_ex = VDKException(
what="Failed to validate job arguments.",
why=str(e),
consequence="I will not make the API call.",
countermeasure="Make sure provided --arguments is a valid JSON string.",
)
raise vdk_ex
@ApiClientErrorDecorator()
def start(self, name: str, team: str, output: OutputFormat, arguments: str) -> None:
execution_request = DataJobExecutionRequest(
started_by=f"vdk-control-cli",
args=self.__validate_and_parse_args(arguments),
)
log.debug(f"Starting job with request {execution_request}")
_, _, headers = self.__execution_api.data_job_execution_start_with_http_info(
team_name=team,
job_name=name,
deployment_id="production", # TODO
data_job_execution_request=execution_request,
)
log.debug(f"Received headers: {headers}")
location = headers["Location"]
execution_id = os.path.basename(location)
if output == OutputFormat.TEXT.value:
click.echo(
f"Execution of Data Job {name} started. "
f"See execution status using: \n\n"
f"vdk execute --show --execution-id {execution_id} -n {name} -t {team}\n\n"
f"See execution logs using: \n\n"
f"vdk execute --logs --execution-id {execution_id} -n {name} -t {team}"
)
elif output == OutputFormat.JSON.value:
result = {
"job_name": name,
"team": team,
"execution_id": execution_id,
}
click.echo(json.dumps(result))
@ApiClientErrorDecorator()
def cancel(self, name: str, team: str, execution_id: str) -> None:
click.echo("Cancelling data job execution. Might take some time...")
with click_spinner.spinner():
response = self.__execution_api.data_job_execution_cancel(
team_name=team, job_name=name, execution_id=execution_id
)
log.debug(f"Response: {response}")
click.echo("Job cancelled successfully.")
@ApiClientErrorDecorator()
def show(
self, name: str, team: str, execution_id: str, output: OutputFormat
) -> None:
execution: DataJobExecution = self.__execution_api.data_job_execution_read(
team_name=team, job_name=name, execution_id=execution_id
)
click.echo(self.__model_executions([execution], output))
@ApiClientErrorDecorator()
def list(self, name: str, team: str, output: OutputFormat) -> None:
executions: list[
DataJobExecution
] = self.__execution_api.data_job_execution_list(team_name=team, job_name=name)
click.echo(self.__model_executions(executions, output))
def __get_execution_to_log(
self, name: str, team: str, execution_id: str
) -> Optional[DataJobExecution]:
if not execution_id:
executions: list[
DataJobExecution
] = self.__execution_api.data_job_execution_list(
team_name=team, job_name=name
)
if not executions:
return None
log.info(
"No execution id has been passed as argument. "
"We will print the logs of the last started execution."
)
executions.sort(key=operator.attrgetter("start_time"), reverse=True)
execution = executions[0]
else:
execution: DataJobExecution = self.__execution_api.data_job_execution_read(
team_name=team, job_name=name, execution_id=execution_id
)
return execution
@ApiClientErrorDecorator()
def logs(self, name: str, team: str, execution_id: str) -> None:
execution = self.__get_execution_to_log(name, team, execution_id)
if not execution:
log.info("No executions found.")
return
log.debug(f"Get execution details: {execution.to_dict()}")
log.info(f"Logs for execution with id {execution.id} ...")
if execution.logs_url:
log.info(f"Opening browser to check logs at:\n{execution.logs_url}")
is_open = webbrowser.open(execution.logs_url)
if not is_open:
log.info(
"We failed to open the browser automatically .\n"
f"Navigate manually in your favourite browser to {execution.logs_url} to find the execution logs."
)
else:
log.debug("Fetch logs from Execution Current Logs API: ")
logs: DataJobExecutionLogs = self.__execution_api.data_job_logs_download(
team_name=team, job_name=name, execution_id=execution.id
)
click.echo(logs.logs)
# Below is the definition of the CLI API/UX users will be interacting
# Above is the actual implementation of the operations
@click.command(
help="Starts execution of a data job that is deployed or check status of job execution(s). (Beta)"
"""
Examples:
\b
# Start new remote execution of Data Job 'example-job'
# As an output it will print how to get starts and it's execution ID:
vdk execute --start -n example-job -t "Example Team"
\b
# Start a new remote execution of Data Job 'example-job' with extra arguments
# Arguments are passed to each step. Arguments must be a valid JSON object with key/value pairs.
vdk execute --start -n example-job -t "Example Team" --arguments '{"key1": "value1", "key2": "value2"}'
\b
# Check status of a currently executing Data Job:
vdk execute --show --execution-id example-job-1619094633811-cc49d -n example-job -t "Example Team"
\b
# Cancel a currently executing Data Job:
vdk execute --cancel -t "Example Team" -n example-job --execution-id example-job-1619094633811-cc49d
\b
# List recent execution of a Data Job:
vdk execute --list -n example-job -t "Example Team"
\b
# We want to see the logs of the current execution that is running.
vdk execute --logs -n example-job -t "Example Team" --execution-id example-job-1619094633811-cc49d
""",
)
@click.option("-n", "--name", type=click.STRING, help="The job name.")
@click.option(
"-t",
"--team",
type=click.STRING,
default=load_default_team_name(),
required=True,
prompt="Job Team",
help="The team name to which the job belong to.",
)
@click.option("-i", "--execution-id", type=click.STRING, help="The job execution ID.")
@click.option(
"--start",
"operation",
flag_value=ExecuteOperation.START.value,
help="Start execution of a Data Job. ",
)
@click.option(
"--wait",
"operation",
hidden=True,
flag_value=ExecuteOperation.WAIT.value,
help="Wait for current job execution (if any) to finish "
"(if specified execution id wait for execution with given id to finish)."
"Require --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--cancel",
"operation",
flag_value=ExecuteOperation.CANCEL.value,
help="Cancels a running or submitted Data Job execution. Requires --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--list",
"operation",
flag_value=ExecuteOperation.LIST.value,
help="List recent and/or current executions of the Data Job. ",
)
@click.option(
"--show",
"operation",
flag_value=ExecuteOperation.SHOW.value,
help="Shows details Data Job Executions. Requires --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--logs",
"operation",
flag_value=ExecuteOperation.LOGS.value,
help="Shows logs about Data Job Execution. It will either provide link to central logging system or"
" print the logs locally."
"If --execution-id is omitted, it will fetch logs from more recently started job execution."
" --execution-id should be provided to get logs from specific job execution."
"Execution id is printed when using vdk execute --start. "
"You can also see execution id with vdk execute --list operation.",
)
@cli_utils.rest_api_url_option()
@cli_utils.output_option()
@click.option(
"--arguments",
type=click.STRING,
required=False,
help="Pass arguments when starting a data job. "
"Those arguments will be passed to each step. "
"Must be in valid JSON format",
)
@cli_utils.check_required_parameters
def execute(
name, team, execution_id, operation, rest_api_url, output, arguments
) -> None:
cmd = JobExecute(rest_api_url)
if operation == ExecuteOperation.START.value:
name = get_or_prompt("Job Name", name)
cmd.start(name, team, output, arguments)
elif operation == ExecuteOperation.SHOW.value:
name = get_or_prompt("Job Name", name)
execution_id = get_or_prompt("Job Execution ID", execution_id)
cmd.show(name, team, execution_id, output)
elif operation == ExecuteOperation.LIST.value:
name = get_or_prompt("Job Name", name)
cmd.list(name, team, output)
elif operation == ExecuteOperation.CANCEL.value:
name = get_or_prompt("Job Name", name)
team = get_or_prompt("Job Team", team)
execution_id = get_or_prompt("Job Execution ID", execution_id)
cmd.cancel(name, team, execution_id)
elif operation == ExecuteOperation.LOGS.value:
name = get_or_prompt("Job Name", name)
team = get_or_prompt("Job Team", team)
cmd.logs(name, team, execution_id)
elif operation == ExecuteOperation.WAIT.value:
name = get_or_prompt("Job Name", name)
# cmd.wait(name, team)
click.echo("Operation wait not implemented")
else:
click.echo(
f"No execute operation specified. "
f"Please specify one of: {['--' + str(op.value) for op in ExecuteOperation]}"
) | projects/vdk-control-cli/src/vdk/internal/control/command_groups/job/execute.py | import json
import logging
import operator
import os
import sys
import webbrowser
from enum import Enum
from enum import unique
from typing import Optional
import click
import click_spinner
from tabulate import tabulate
from taurus_datajob_api import DataJobExecution
from taurus_datajob_api import DataJobExecutionLogs
from taurus_datajob_api import DataJobExecutionRequest
from vdk.internal.control.configuration.defaults_config import load_default_team_name
from vdk.internal.control.exception.vdk_exception import VDKException
from vdk.internal.control.rest_lib.factory import ApiClientFactory
from vdk.internal.control.rest_lib.rest_client_errors import ApiClientErrorDecorator
from vdk.internal.control.utils import cli_utils
from vdk.internal.control.utils.cli_utils import get_or_prompt
from vdk.internal.control.utils.cli_utils import OutputFormat
log = logging.getLogger(__name__)
@unique
class ExecuteOperation(Enum):
"""
An enum used to store the types of deploy operations
"""
START = "start"
CANCEL = "cancel"
WAIT = "wait"
SHOW = "show"
LIST = "list"
LOGS = "logs"
class JobExecute:
def __init__(self, rest_api_url: str):
self.__execution_api = ApiClientFactory(rest_api_url).get_execution_api()
@staticmethod
def __model_executions(executions, output: OutputFormat) -> str:
def transform_execution(e: DataJobExecution):
d = e.to_dict()
d["job_version"] = e.deployment.job_version
del d["deployment"]
return d
executions = list(map(lambda e: transform_execution(e), executions))
if output == OutputFormat.TEXT.value:
return tabulate(executions, headers="keys")
elif output == OutputFormat.JSON.value:
return cli_utils.json_format(list(executions))
@staticmethod
def __validate_and_parse_args(arguments: str) -> str:
try:
if arguments:
return json.loads(arguments)
else:
return {}
except Exception as e:
vdk_ex = VDKException(
what="Failed to validate job arguments.",
why=str(e),
consequence="I will not make the API call.",
countermeasure="Make sure provided --arguments is a valid JSON string.",
)
raise vdk_ex
@ApiClientErrorDecorator()
def start(self, name: str, team: str, output: OutputFormat, arguments: str) -> None:
execution_request = DataJobExecutionRequest(
started_by=f"vdk-control-cli",
args=self.__validate_and_parse_args(arguments),
)
log.debug(f"Starting job with request {execution_request}")
_, _, headers = self.__execution_api.data_job_execution_start_with_http_info(
team_name=team,
job_name=name,
deployment_id="production", # TODO
data_job_execution_request=execution_request,
)
log.debug(f"Received headers: {headers}")
location = headers["Location"]
execution_id = os.path.basename(location)
if output == OutputFormat.TEXT.value:
click.echo(
f"Execution of Data Job {name} started. "
f"See execution status using: \n\n"
f"vdk execute --show --execution-id {execution_id} -n {name} -t {team}\n\n"
f"See execution logs using: \n\n"
f"vdk execute --logs --execution-id {execution_id} -n {name} -t {team}"
)
elif output == OutputFormat.JSON.value:
result = {
"job_name": name,
"team": team,
"execution_id": execution_id,
}
click.echo(json.dumps(result))
@ApiClientErrorDecorator()
def cancel(self, name: str, team: str, execution_id: str) -> None:
click.echo("Cancelling data job execution. Might take some time...")
with click_spinner.spinner():
response = self.__execution_api.data_job_execution_cancel(
team_name=team, job_name=name, execution_id=execution_id
)
log.debug(f"Response: {response}")
click.echo("Job cancelled successfully.")
@ApiClientErrorDecorator()
def show(
self, name: str, team: str, execution_id: str, output: OutputFormat
) -> None:
execution: DataJobExecution = self.__execution_api.data_job_execution_read(
team_name=team, job_name=name, execution_id=execution_id
)
click.echo(self.__model_executions([execution], output))
@ApiClientErrorDecorator()
def list(self, name: str, team: str, output: OutputFormat) -> None:
executions: list[
DataJobExecution
] = self.__execution_api.data_job_execution_list(team_name=team, job_name=name)
click.echo(self.__model_executions(executions, output))
def __get_execution_to_log(
self, name: str, team: str, execution_id: str
) -> Optional[DataJobExecution]:
if not execution_id:
executions: list[
DataJobExecution
] = self.__execution_api.data_job_execution_list(
team_name=team, job_name=name
)
if not executions:
return None
log.info(
"No execution id has been passed as argument. "
"We will print the logs of the last started execution."
)
executions.sort(key=operator.attrgetter("start_time"), reverse=True)
execution = executions[0]
else:
execution: DataJobExecution = self.__execution_api.data_job_execution_read(
team_name=team, job_name=name, execution_id=execution_id
)
return execution
@ApiClientErrorDecorator()
def logs(self, name: str, team: str, execution_id: str) -> None:
execution = self.__get_execution_to_log(name, team, execution_id)
if not execution:
log.info("No executions found.")
return
log.debug(f"Get execution details: {execution.to_dict()}")
log.info(f"Logs for execution with id {execution.id} ...")
if execution.logs_url:
log.info(f"Opening browser to check logs at:\n{execution.logs_url}")
is_open = webbrowser.open(execution.logs_url)
if not is_open:
log.info(
"We failed to open the browser automatically .\n"
f"Navigate manually in your favourite browser to {execution.logs_url} to find the execution logs."
)
else:
log.debug("Fetch logs from Execution Current Logs API: ")
logs: DataJobExecutionLogs = self.__execution_api.data_job_logs_download(
team_name=team, job_name=name, execution_id=execution.id
)
click.echo(logs.logs)
# Below is the definition of the CLI API/UX users will be interacting
# Above is the actual implementation of the operations
@click.command(
help="Starts execution of a data job that is deployed or check status of job execution(s). (Beta)"
"""
Examples:
\b
# Start new remote execution of Data Job 'example-job'
# As an output it will print how to get starts and it's execution ID:
vdk execute --start -n example-job -t "Example Team"
\b
# Start a new remote execution of Data Job 'example-job' with extra arguments
# Arguments are passed to each step. Arguments must be a valid JSON object with key/value pairs.
vdk execute --start -n example-job -t "Example Team" --arguments '{"key1": "value1", "key2": "value2"}'
\b
# Check status of a currently executing Data Job:
vdk execute --show --execution-id example-job-1619094633811-cc49d -n example-job -t "Example Team"
\b
# Cancel a currently executing Data Job:
vdk execute --cancel -t "Example Team" -n example-job --execution-id example-job-1619094633811-cc49d
\b
# List recent execution of a Data Job:
vdk execute --list -n example-job -t "Example Team"
\b
# We want to see the logs of the current execution that is running.
vdk execute --logs -n example-job -t "Example Team" --execution-id example-job-1619094633811-cc49d
""",
)
@click.option("-n", "--name", type=click.STRING, help="The job name.")
@click.option(
"-t",
"--team",
type=click.STRING,
default=load_default_team_name(),
required=True,
prompt="Job Team",
help="The team name to which the job belong to.",
)
@click.option("-i", "--execution-id", type=click.STRING, help="The job execution ID.")
@click.option(
"--start",
"operation",
flag_value=ExecuteOperation.START.value,
help="Start execution of a Data Job. ",
)
@click.option(
"--wait",
"operation",
hidden=True,
flag_value=ExecuteOperation.WAIT.value,
help="Wait for current job execution (if any) to finish "
"(if specified execution id wait for execution with given id to finish)."
"Require --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--cancel",
"operation",
flag_value=ExecuteOperation.CANCEL.value,
help="Cancels a running or submitted Data Job execution. Requires --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--list",
"operation",
flag_value=ExecuteOperation.LIST.value,
help="List recent and/or current executions of the Data Job. ",
)
@click.option(
"--show",
"operation",
flag_value=ExecuteOperation.SHOW.value,
help="Shows details Data Job Executions. Requires --execution-id to be provided. "
"Should be printed when using vdk execute --start",
)
@click.option(
"--logs",
"operation",
flag_value=ExecuteOperation.LOGS.value,
help="Shows logs about Data Job Execution. It will either provide link to central logging system or"
" print the logs locally."
"If --execution-id is omitted, it will fetch logs from more recently started job execution."
" --execution-id should be provided to get logs from specific job execution."
"Execution id is printed when using vdk execute --start. "
"You can also see execution id with vdk execute --list operation.",
)
@cli_utils.rest_api_url_option()
@cli_utils.output_option()
@click.option(
"--arguments",
type=click.STRING,
required=False,
help="Pass arguments when starting a data job. "
"Those arguments will be passed to each step. "
"Must be in valid JSON format",
)
@cli_utils.check_required_parameters
def execute(
name, team, execution_id, operation, rest_api_url, output, arguments
) -> None:
cmd = JobExecute(rest_api_url)
if operation == ExecuteOperation.START.value:
name = get_or_prompt("Job Name", name)
cmd.start(name, team, output, arguments)
elif operation == ExecuteOperation.SHOW.value:
name = get_or_prompt("Job Name", name)
execution_id = get_or_prompt("Job Execution ID", execution_id)
cmd.show(name, team, execution_id, output)
elif operation == ExecuteOperation.LIST.value:
name = get_or_prompt("Job Name", name)
cmd.list(name, team, output)
elif operation == ExecuteOperation.CANCEL.value:
name = get_or_prompt("Job Name", name)
team = get_or_prompt("Job Team", team)
execution_id = get_or_prompt("Job Execution ID", execution_id)
cmd.cancel(name, team, execution_id)
elif operation == ExecuteOperation.LOGS.value:
name = get_or_prompt("Job Name", name)
team = get_or_prompt("Job Team", team)
cmd.logs(name, team, execution_id)
elif operation == ExecuteOperation.WAIT.value:
name = get_or_prompt("Job Name", name)
# cmd.wait(name, team)
click.echo("Operation wait not implemented")
else:
click.echo(
f"No execute operation specified. "
f"Please specify one of: {['--' + str(op.value) for op in ExecuteOperation]}"
) | 0.505615 | 0.093761 |
import json
import time
from typing import Dict, List
from redis import Redis
from spire.journal import models as journal_models
from spire.humbug import models as humbug_models
from spire.humbug.data import HumbugCreateReportTask
from sqlalchemy.orm.session import Session
from sqlalchemy.orm import aliased
from spire.db import redis_connection
from .data import HumbugFailedReportTask
from .settings import REDIS_FAILED_REPORTS_QUEUE
def upload_report_tasks(
redis_client: Redis, queue_key: str, command: str, chunk_size: int
):
"""
Return parsed reports from redis
"""
if command == "lrange":
reports_json = redis_client.execute_command(
command, queue_key, 0, chunk_size - 1
)
else:
reports_json = redis_client.execute_command(command, queue_key, chunk_size)
print(
f"Redis command {command} results count: {len(reports_json) if reports_json else 0}"
)
try:
if reports_json is not None:
return [
HumbugCreateReportTask(**json.loads(report)) for report in reports_json
]
except Exception as err:
print(f"Error in parsing reports proccess: {err}")
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE, *reports_json,
)
def get_humbug_integrations(
db_session: Session, report_tasks: List[HumbugCreateReportTask]
):
"""
Generate journal_id by tokens key value pairs
"""
humbug_event_alias = aliased(humbug_models.HumbugEvent)
journal_and_tokens = (
db_session.query(
humbug_models.HumbugBugoutUserToken.restricted_token_id,
humbug_models.HumbugEvent.journal_id,
)
.join(
humbug_models.HumbugBugoutUserToken,
humbug_models.HumbugEvent.id
== humbug_models.HumbugBugoutUserToken.event_id,
)
.filter(
humbug_models.HumbugBugoutUserToken.restricted_token_id.in_(
tuple(set([str(task.bugout_token) for task in report_tasks]))
)
)
.filter(
db_session.query(journal_models.Journal)
.filter(journal_models.Journal.id == humbug_event_alias.journal_id)
.exists()
)
.distinct()
)
return {str(token): journal_id for token, journal_id in journal_and_tokens.all()}
def write_reports(
db_session: Session,
redis_client: Redis,
report_tasks: List[HumbugCreateReportTask],
journal_by_token: Dict[str, str],
):
"""
Push all reports to database in one chunk
"""
pushed = 0
for report_task in report_tasks:
try:
if not journal_by_token.get(str(report_task.bugout_token)):
continue
entry_object = journal_models.JournalEntry(
journal_id=journal_by_token[str(report_task.bugout_token)],
title=report_task.report.title,
content=report_task.report.content,
context_id=str(report_task.bugout_token),
context_type="humbug",
created_at=report_task.report.created_at,
updated_at=report_task.report.created_at,
)
tags = report_task.report.tags[:]
tags.append(f"reporter_token:{str(report_task.bugout_token)}")
entry_object.tags.extend(
[
journal_models.JournalEntryTag(tag=tag)
for tag in list(set(tags))
if tag
]
)
db_session.add(entry_object)
db_session.commit()
pushed += 1
except Exception as err:
print(f"Error in writing reports to datbase: {err}")
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE,
HumbugFailedReportTask(
bugout_token=report_task.bugout_token,
report=report_task.report,
error=str(err),
).json(),
)
db_session.rollback()
return pushed
def process_humbug_tasks_queue(
db_session: Session,
queue_key: str,
upload_command: str,
chunk_size: int,
block: bool,
timeout: int,
):
print("Polling reports queue start")
print(f"Redis is connected:{redis_connection().execute_command('PING')}")
while True:
try:
redis_client = redis_connection()
# get all new reports
report_tasks = upload_report_tasks(
redis_client=redis_client,
queue_key=queue_key,
command=upload_command,
chunk_size=chunk_size,
)
if not report_tasks:
if block:
time.sleep(timeout)
continue
else:
return
# fetching pairs of journal ids and tokens
journal_by_token = get_humbug_integrations(
db_session=db_session, report_tasks=report_tasks
)
written_count = write_reports(
db_session=db_session,
redis_client=redis_client,
report_tasks=report_tasks,
journal_by_token=journal_by_token,
)
print(f"{written_count} pushed to database")
except Exception as err:
print(err)
if report_tasks:
for tasks in report_tasks:
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE,
HumbugFailedReportTask(
bugout_token=tasks.bugout_token,
report=tasks.report,
error=str(err),
).json(),
)
def pick_humbug_tasks_queue(
queue_key: str, command: str, chunk_size: int, start: int,
):
redis_client = redis_connection()
if command == "lrange":
reports_json = redis_client.execute_command(
command, queue_key, start, chunk_size - 1
)
else:
reports_json = redis_client.execute_command(command, queue_key, chunk_size)
if reports_json:
for i in reports_json:
print(reports_json) | drones/humbug_reports.py | import json
import time
from typing import Dict, List
from redis import Redis
from spire.journal import models as journal_models
from spire.humbug import models as humbug_models
from spire.humbug.data import HumbugCreateReportTask
from sqlalchemy.orm.session import Session
from sqlalchemy.orm import aliased
from spire.db import redis_connection
from .data import HumbugFailedReportTask
from .settings import REDIS_FAILED_REPORTS_QUEUE
def upload_report_tasks(
redis_client: Redis, queue_key: str, command: str, chunk_size: int
):
"""
Return parsed reports from redis
"""
if command == "lrange":
reports_json = redis_client.execute_command(
command, queue_key, 0, chunk_size - 1
)
else:
reports_json = redis_client.execute_command(command, queue_key, chunk_size)
print(
f"Redis command {command} results count: {len(reports_json) if reports_json else 0}"
)
try:
if reports_json is not None:
return [
HumbugCreateReportTask(**json.loads(report)) for report in reports_json
]
except Exception as err:
print(f"Error in parsing reports proccess: {err}")
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE, *reports_json,
)
def get_humbug_integrations(
db_session: Session, report_tasks: List[HumbugCreateReportTask]
):
"""
Generate journal_id by tokens key value pairs
"""
humbug_event_alias = aliased(humbug_models.HumbugEvent)
journal_and_tokens = (
db_session.query(
humbug_models.HumbugBugoutUserToken.restricted_token_id,
humbug_models.HumbugEvent.journal_id,
)
.join(
humbug_models.HumbugBugoutUserToken,
humbug_models.HumbugEvent.id
== humbug_models.HumbugBugoutUserToken.event_id,
)
.filter(
humbug_models.HumbugBugoutUserToken.restricted_token_id.in_(
tuple(set([str(task.bugout_token) for task in report_tasks]))
)
)
.filter(
db_session.query(journal_models.Journal)
.filter(journal_models.Journal.id == humbug_event_alias.journal_id)
.exists()
)
.distinct()
)
return {str(token): journal_id for token, journal_id in journal_and_tokens.all()}
def write_reports(
db_session: Session,
redis_client: Redis,
report_tasks: List[HumbugCreateReportTask],
journal_by_token: Dict[str, str],
):
"""
Push all reports to database in one chunk
"""
pushed = 0
for report_task in report_tasks:
try:
if not journal_by_token.get(str(report_task.bugout_token)):
continue
entry_object = journal_models.JournalEntry(
journal_id=journal_by_token[str(report_task.bugout_token)],
title=report_task.report.title,
content=report_task.report.content,
context_id=str(report_task.bugout_token),
context_type="humbug",
created_at=report_task.report.created_at,
updated_at=report_task.report.created_at,
)
tags = report_task.report.tags[:]
tags.append(f"reporter_token:{str(report_task.bugout_token)}")
entry_object.tags.extend(
[
journal_models.JournalEntryTag(tag=tag)
for tag in list(set(tags))
if tag
]
)
db_session.add(entry_object)
db_session.commit()
pushed += 1
except Exception as err:
print(f"Error in writing reports to datbase: {err}")
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE,
HumbugFailedReportTask(
bugout_token=report_task.bugout_token,
report=report_task.report,
error=str(err),
).json(),
)
db_session.rollback()
return pushed
def process_humbug_tasks_queue(
db_session: Session,
queue_key: str,
upload_command: str,
chunk_size: int,
block: bool,
timeout: int,
):
print("Polling reports queue start")
print(f"Redis is connected:{redis_connection().execute_command('PING')}")
while True:
try:
redis_client = redis_connection()
# get all new reports
report_tasks = upload_report_tasks(
redis_client=redis_client,
queue_key=queue_key,
command=upload_command,
chunk_size=chunk_size,
)
if not report_tasks:
if block:
time.sleep(timeout)
continue
else:
return
# fetching pairs of journal ids and tokens
journal_by_token = get_humbug_integrations(
db_session=db_session, report_tasks=report_tasks
)
written_count = write_reports(
db_session=db_session,
redis_client=redis_client,
report_tasks=report_tasks,
journal_by_token=journal_by_token,
)
print(f"{written_count} pushed to database")
except Exception as err:
print(err)
if report_tasks:
for tasks in report_tasks:
redis_client.rpush(
REDIS_FAILED_REPORTS_QUEUE,
HumbugFailedReportTask(
bugout_token=tasks.bugout_token,
report=tasks.report,
error=str(err),
).json(),
)
def pick_humbug_tasks_queue(
queue_key: str, command: str, chunk_size: int, start: int,
):
redis_client = redis_connection()
if command == "lrange":
reports_json = redis_client.execute_command(
command, queue_key, start, chunk_size - 1
)
else:
reports_json = redis_client.execute_command(command, queue_key, chunk_size)
if reports_json:
for i in reports_json:
print(reports_json) | 0.460046 | 0.102439 |
import re
import os
import time
import warnings
import PIL.Image
from concurrent.futures import ThreadPoolExecutor
from .exceptions import ImageDownloadError
from .session import SessionMgr
from .utils import ensure_file_dir_exists
HERE = os.path.abspath(os.path.dirname(__file__))
PROJECT_HOME = os.path.abspath(os.path.join(HERE, os.path.pardir))
def retry(times=3, delay=0):
def _wrapper1(func):
def _wrapper2(*args, **kwargs):
i = 0
while True:
try:
return func(*args, **kwargs)
except Exception as e:
i += 1
if i > times:
raise e
time.sleep(delay)
return _wrapper2
return _wrapper1
def walk(rootdir):
for parent, dirnames, filenames in os.walk(rootdir):
for filename in filenames:
yield os.path.join(parent, filename)
class WorkerPoolMgr(object):
WORKER_POOL = None
POOL_SIZE = 4
@classmethod
def get_pool(cls):
if cls.WORKER_POOL is None:
cls.WORKER_POOL = ThreadPoolExecutor(max_workers=cls.POOL_SIZE)
return cls.WORKER_POOL
@classmethod
def set_worker(cls, worker=4):
cls.POOL_SIZE = worker
if cls.WORKER_POOL:
cls.WORKER_POOL._max_workers = worker
class ImageDownloader(object):
URL_PATTERN = re.compile(r'^https?://.*')
def __init__(self, site):
self.site = site
self.image_download_pool = None
self.pool_size = 4
self.verify = True
self.timeout = 30
def set_verify(self, verify=True):
self.verify = verify
def set_timeout(self, timeout=30):
self.timeout = timeout
def get_session(self):
return SessionMgr.get_session(site=self.site)
@retry(times=3, delay=1)
def download_image(self, image_url, target_path, **kwargs):
if os.path.exists(target_path):
try:
self.verify_image(target_path)
return target_path
except Exception:
pass
try:
session = self.get_session()
response = session.get(image_url, verify=self.verify, timeout=self.timeout, **kwargs)
if response.status_code != 200:
msg = 'img download error: url=%s status_code=%s' % (image_url, response.status_code)
raise ImageDownloadError(msg)
except Exception as e:
msg = "img download error: url=%s error: %s" % (image_url, e)
raise ImageDownloadError(msg) from e
ensure_file_dir_exists(target_path)
with open(target_path, 'wb') as f:
f.write(response.content)
try:
self.verify_image(target_path)
except Exception as e:
os.unlink(target_path)
raise ImageDownloadError(f'Corrupt image from {image_url}') from e
return target_path
def verify_image(self, image_path):
with PIL.Image.open(image_path) as img:
img.verify()
def download_images(self, image_urls, output_dir, **kwargs):
"""下载出错只打印出警告信息，不抛出异常
"""
pool = WorkerPoolMgr.get_pool()
future_list = []
for idx, image_url in enumerate(image_urls, start=1):
ext = self.find_suffix(image_url)
target_path = os.path.join(output_dir.rstrip(), "{}.{}".format(idx, ext))
future = pool.submit(
self.download_image,
image_url=image_url, target_path=target_path, **kwargs)
future_list.append(future)
# 等全部图片下载完成
for future in future_list:
try:
future.result()
except Exception as e:
warnings.warn(str(e))
return output_dir
@staticmethod
def find_suffix(image_url, default='jpg',
allow=frozenset(['jpg', 'png', 'jpeg', 'gif', 'webp'])):
"""从图片url提取图片扩展名
:param image_url: 图片链接
:param default: 扩展名不在 allow 内，则返回默认扩展名
:param allow: 允许的扩展名
:return ext: 扩展名，不包含.
"""
url = image_url.split('?')[0]
ext = url.rsplit('.', 1)[-1].lower()
if ext in allow:
return ext
return default | onepiece/image.py | import re
import os
import time
import warnings
import PIL.Image
from concurrent.futures import ThreadPoolExecutor
from .exceptions import ImageDownloadError
from .session import SessionMgr
from .utils import ensure_file_dir_exists
HERE = os.path.abspath(os.path.dirname(__file__))
PROJECT_HOME = os.path.abspath(os.path.join(HERE, os.path.pardir))
def retry(times=3, delay=0):
def _wrapper1(func):
def _wrapper2(*args, **kwargs):
i = 0
while True:
try:
return func(*args, **kwargs)
except Exception as e:
i += 1
if i > times:
raise e
time.sleep(delay)
return _wrapper2
return _wrapper1
def walk(rootdir):
for parent, dirnames, filenames in os.walk(rootdir):
for filename in filenames:
yield os.path.join(parent, filename)
class WorkerPoolMgr(object):
WORKER_POOL = None
POOL_SIZE = 4
@classmethod
def get_pool(cls):
if cls.WORKER_POOL is None:
cls.WORKER_POOL = ThreadPoolExecutor(max_workers=cls.POOL_SIZE)
return cls.WORKER_POOL
@classmethod
def set_worker(cls, worker=4):
cls.POOL_SIZE = worker
if cls.WORKER_POOL:
cls.WORKER_POOL._max_workers = worker
class ImageDownloader(object):
URL_PATTERN = re.compile(r'^https?://.*')
def __init__(self, site):
self.site = site
self.image_download_pool = None
self.pool_size = 4
self.verify = True
self.timeout = 30
def set_verify(self, verify=True):
self.verify = verify
def set_timeout(self, timeout=30):
self.timeout = timeout
def get_session(self):
return SessionMgr.get_session(site=self.site)
@retry(times=3, delay=1)
def download_image(self, image_url, target_path, **kwargs):
if os.path.exists(target_path):
try:
self.verify_image(target_path)
return target_path
except Exception:
pass
try:
session = self.get_session()
response = session.get(image_url, verify=self.verify, timeout=self.timeout, **kwargs)
if response.status_code != 200:
msg = 'img download error: url=%s status_code=%s' % (image_url, response.status_code)
raise ImageDownloadError(msg)
except Exception as e:
msg = "img download error: url=%s error: %s" % (image_url, e)
raise ImageDownloadError(msg) from e
ensure_file_dir_exists(target_path)
with open(target_path, 'wb') as f:
f.write(response.content)
try:
self.verify_image(target_path)
except Exception as e:
os.unlink(target_path)
raise ImageDownloadError(f'Corrupt image from {image_url}') from e
return target_path
def verify_image(self, image_path):
with PIL.Image.open(image_path) as img:
img.verify()
def download_images(self, image_urls, output_dir, **kwargs):
"""下载出错只打印出警告信息，不抛出异常
"""
pool = WorkerPoolMgr.get_pool()
future_list = []
for idx, image_url in enumerate(image_urls, start=1):
ext = self.find_suffix(image_url)
target_path = os.path.join(output_dir.rstrip(), "{}.{}".format(idx, ext))
future = pool.submit(
self.download_image,
image_url=image_url, target_path=target_path, **kwargs)
future_list.append(future)
# 等全部图片下载完成
for future in future_list:
try:
future.result()
except Exception as e:
warnings.warn(str(e))
return output_dir
@staticmethod
def find_suffix(image_url, default='jpg',
allow=frozenset(['jpg', 'png', 'jpeg', 'gif', 'webp'])):
"""从图片url提取图片扩展名
:param image_url: 图片链接
:param default: 扩展名不在 allow 内，则返回默认扩展名
:param allow: 允许的扩展名
:return ext: 扩展名，不包含.
"""
url = image_url.split('?')[0]
ext = url.rsplit('.', 1)[-1].lower()
if ext in allow:
return ext
return default | 0.312895 | 0.070368 |
import rospy
from rospy.exceptions import ROSException
from std_msgs.msg import Empty, String
from std_srvs.srv import Empty as EmptySrv
from std_srvs.srv import EmptyResponse as EmptySrvResponse
class SignalBridgeNode(object):
def __init__(self):
self.name = rospy.get_name()
# init publishers, subscribers and services
self.ros_init()
# notify user
rospy.loginfo('%s: initialized' % self.name)
def ros_init(self):
# create services
rospy.loginfo('%s: starting reset robot service' % self.name)
self.reset_robot_srv = rospy.Service(
'/rl/reset_robot', EmptySrv, self.reset_robot)
rospy.loginfo('%s: starting reset stop service' % self.name)
self.stop_robot_srv = rospy.Service(
'/rl/stop_robot', EmptySrv, self.stop_robot)
def reset_robot(self, req):
rospy.loginfo("%s: resetting plant" % self.name)
return EmptySrvResponse()
def stop_robot(self, req):
rospy.loginfo("%s: stopping plant" % self.name)
return EmptySrvResponse()
def spin(self):
rospy.spin()
class GazeboSignalBridgeNode(SignalBridgeNode):
def __init__(self):
super(GazeboSignalBridgeNode, self).__init__()
self.name += '_gazebo'
def ros_init(self):
# wait for services
rospy.loginfo(
'%s: waiting for /gazebo/reset_world...' % self.name)
rospy.wait_for_service('/gazebo/reset_world')
self.reset_gz_world = rospy.ServiceProxy(
"/gazebo/reset_world", EmptySrv)
rospy.loginfo(
'%s: waiting for /gazebo/pause_physics...' % self.name)
rospy.wait_for_service('/gazebo/pause_physics')
self.pause = rospy.ServiceProxy('/gazebo/pause_physics', EmptySrv)
rospy.loginfo(
'%s: waiting for /gazebo/unpause_physics...' % self.name)
rospy.wait_for_service('/gazebo/unpause_physics')
self.unpause = rospy.ServiceProxy(
'/gazebo/unpause_physics', EmptySrv)
self.unpause()
super(GazeboSignalBridgeNode, self).ros_init()
def reset_robot(self, req):
try:
self.reset_gz_world()
self.unpause()
rospy.sleep(0.5)
except rospy.ServiceException, e:
rospy.logerr(
"%s: service call(s) failed in reset_robot: %s" % (self.name,
e))
return EmptySrvResponse()
def stop_robot(self, req):
try:
rospy.sleep(6.0)
self.pause()
except rospy.ServiceException, e:
rospy.logerr(
"%s: service call(s) failed in stop_robot: %s" % (name, e))
return EmptySrvResponse()
class MarshallSignalBridgeNode(SignalBridgeNode):
def __init__(self):
self.has_trigger_start = False
self.marshall_mode = ''
super(MarshallSignalBridgeNode, self).__init__()
self.name += '_marshall'
def ros_init(self):
rospy.loginfo(
'%s: waiting for /rl_marshall/set_mode...' % self.name)
rospy.wait_for_service('/rl_marshall/set_mode')
self.trigger_reset_pub = rospy.Publisher(
'/rl/trigger_reset', Empty, queue_size=10)
self.trigger_stop_pub = rospy.Publisher(
'/rl/trigger_stop', Empty, queue_size=10)
self.trigger_start_sub = rospy.Subscriber(
'/rl/trigger_start', Empty, self.callback_to_trigger_start)
self.marshall_mode_sub = rospy.Subscriber(
'/rl_marshall/mode', String, self.callback_to_marshall_mode)
super(MarshallSignalBridgeNode, self).ros_init()
def stop_robot(self, req):
self.trigger_stop_pub.publish()
while self.marshall_mode == 'rl':
rospy.sleep(0.01)
return EmptySrvResponse()
def reset_robot(self, req):
rospy.loginfo("%s: resetting plant" % rospy.get_name())
self.has_trigger_start = False
self.trigger_reset_pub.publish() # tell marshall to prompt user
msg_ = "%s: in reset_plant, waiting for /rl/trigger_start..."
rospy.loginfo(msg_ % rospy.get_name())
# wait till received /aqua_rl/trigger_start (from joy/user)
while not self.has_trigger_start and not rospy.is_shutdown():
rospy.sleep(0.1)
rospy.sleep(0.1)
return EmptySrvResponse()
def callback_to_trigger_start(self, msg):
self.has_trigger_start = True
def callback_to_marshall_mode(self, msg):
self.marshall_mode = msg.data
if __name__ == "__main__":
rospy.init_node('signal_bridge_node')
is_sim = True
if rospy.has_param('~is_sim'):
is_sim = rospy.get_param('~is_sim')
else: # attempt to automatically determine if gazebo is present
try:
name = rospy.get_name()
rospy.loginfo(
'%s: auto-setting is_sim via /gazebo/reset_world...' % name)
rospy.wait_for_service('/gazebo/reset_world', timeout=4.0)
except ROSException:
is_sim = False
if is_sim:
rospy.loginfo("Initializing Gazebo signal bridge")
node = GazeboSignalBridgeNode()
else:
rospy.loginfo("Initializing marshall signal bridge")
node = MarshallSignalBridgeNode()
rospy.loginfo('%s: is_sim <- %d' % (node.name, is_sim))
try:
node.spin()
except rospy.ROSInterruptException:
pass | scripts/signal_bridge_node.py | import rospy
from rospy.exceptions import ROSException
from std_msgs.msg import Empty, String
from std_srvs.srv import Empty as EmptySrv
from std_srvs.srv import EmptyResponse as EmptySrvResponse
class SignalBridgeNode(object):
def __init__(self):
self.name = rospy.get_name()
# init publishers, subscribers and services
self.ros_init()
# notify user
rospy.loginfo('%s: initialized' % self.name)
def ros_init(self):
# create services
rospy.loginfo('%s: starting reset robot service' % self.name)
self.reset_robot_srv = rospy.Service(
'/rl/reset_robot', EmptySrv, self.reset_robot)
rospy.loginfo('%s: starting reset stop service' % self.name)
self.stop_robot_srv = rospy.Service(
'/rl/stop_robot', EmptySrv, self.stop_robot)
def reset_robot(self, req):
rospy.loginfo("%s: resetting plant" % self.name)
return EmptySrvResponse()
def stop_robot(self, req):
rospy.loginfo("%s: stopping plant" % self.name)
return EmptySrvResponse()
def spin(self):
rospy.spin()
class GazeboSignalBridgeNode(SignalBridgeNode):
def __init__(self):
super(GazeboSignalBridgeNode, self).__init__()
self.name += '_gazebo'
def ros_init(self):
# wait for services
rospy.loginfo(
'%s: waiting for /gazebo/reset_world...' % self.name)
rospy.wait_for_service('/gazebo/reset_world')
self.reset_gz_world = rospy.ServiceProxy(
"/gazebo/reset_world", EmptySrv)
rospy.loginfo(
'%s: waiting for /gazebo/pause_physics...' % self.name)
rospy.wait_for_service('/gazebo/pause_physics')
self.pause = rospy.ServiceProxy('/gazebo/pause_physics', EmptySrv)
rospy.loginfo(
'%s: waiting for /gazebo/unpause_physics...' % self.name)
rospy.wait_for_service('/gazebo/unpause_physics')
self.unpause = rospy.ServiceProxy(
'/gazebo/unpause_physics', EmptySrv)
self.unpause()
super(GazeboSignalBridgeNode, self).ros_init()
def reset_robot(self, req):
try:
self.reset_gz_world()
self.unpause()
rospy.sleep(0.5)
except rospy.ServiceException, e:
rospy.logerr(
"%s: service call(s) failed in reset_robot: %s" % (self.name,
e))
return EmptySrvResponse()
def stop_robot(self, req):
try:
rospy.sleep(6.0)
self.pause()
except rospy.ServiceException, e:
rospy.logerr(
"%s: service call(s) failed in stop_robot: %s" % (name, e))
return EmptySrvResponse()
class MarshallSignalBridgeNode(SignalBridgeNode):
def __init__(self):
self.has_trigger_start = False
self.marshall_mode = ''
super(MarshallSignalBridgeNode, self).__init__()
self.name += '_marshall'
def ros_init(self):
rospy.loginfo(
'%s: waiting for /rl_marshall/set_mode...' % self.name)
rospy.wait_for_service('/rl_marshall/set_mode')
self.trigger_reset_pub = rospy.Publisher(
'/rl/trigger_reset', Empty, queue_size=10)
self.trigger_stop_pub = rospy.Publisher(
'/rl/trigger_stop', Empty, queue_size=10)
self.trigger_start_sub = rospy.Subscriber(
'/rl/trigger_start', Empty, self.callback_to_trigger_start)
self.marshall_mode_sub = rospy.Subscriber(
'/rl_marshall/mode', String, self.callback_to_marshall_mode)
super(MarshallSignalBridgeNode, self).ros_init()
def stop_robot(self, req):
self.trigger_stop_pub.publish()
while self.marshall_mode == 'rl':
rospy.sleep(0.01)
return EmptySrvResponse()
def reset_robot(self, req):
rospy.loginfo("%s: resetting plant" % rospy.get_name())
self.has_trigger_start = False
self.trigger_reset_pub.publish() # tell marshall to prompt user
msg_ = "%s: in reset_plant, waiting for /rl/trigger_start..."
rospy.loginfo(msg_ % rospy.get_name())
# wait till received /aqua_rl/trigger_start (from joy/user)
while not self.has_trigger_start and not rospy.is_shutdown():
rospy.sleep(0.1)
rospy.sleep(0.1)
return EmptySrvResponse()
def callback_to_trigger_start(self, msg):
self.has_trigger_start = True
def callback_to_marshall_mode(self, msg):
self.marshall_mode = msg.data
if __name__ == "__main__":
rospy.init_node('signal_bridge_node')
is_sim = True
if rospy.has_param('~is_sim'):
is_sim = rospy.get_param('~is_sim')
else: # attempt to automatically determine if gazebo is present
try:
name = rospy.get_name()
rospy.loginfo(
'%s: auto-setting is_sim via /gazebo/reset_world...' % name)
rospy.wait_for_service('/gazebo/reset_world', timeout=4.0)
except ROSException:
is_sim = False
if is_sim:
rospy.loginfo("Initializing Gazebo signal bridge")
node = GazeboSignalBridgeNode()
else:
rospy.loginfo("Initializing marshall signal bridge")
node = MarshallSignalBridgeNode()
rospy.loginfo('%s: is_sim <- %d' % (node.name, is_sim))
try:
node.spin()
except rospy.ROSInterruptException:
pass | 0.475362 | 0.099645 |
import os
import pytest
import numpy as np
from xarray import DataArray
from typing import Mapping
from fv3gfs.util import Quantity
from emulation._monitor.monitor import (
StorageHook,
_bool_from_str,
_load_nml,
_get_timestep,
_remove_io_suffix,
_get_attrs,
_convert_to_quantities,
_convert_to_xr_dataset,
_translate_time,
_create_nc_path,
)
def save_var_metadata(path):
metadata_content = """
air_temperature:
units: K
specific_humidity:
units: kg/kg
"""
with open(path, "w") as f:
f.write(metadata_content)
@pytest.mark.parametrize(
"value, expected",
[
("y", True),
("yes", True),
("true", True),
("n", False),
("no", False),
("false", False),
],
)
def test__bool_from_str(value, expected):
assert _bool_from_str(value) == expected
assert _bool_from_str(value.capitalize()) == expected
assert _bool_from_str(value.upper()) == expected
def test__bool_from_str_unrecognized():
with pytest.raises(ValueError):
_bool_from_str("not-translatable-to-bool")
def test__load_nml(dummy_rundir):
namelist = _load_nml()
assert namelist["coupler_nml"]["hours"] == 1
def test__get_timestep(dummy_rundir):
namelist = _load_nml()
timestep = _get_timestep(namelist)
assert timestep == 900
@pytest.mark.parametrize(
"value,expected",
[
("a_input", "a"),
("a_output", "a"),
("a_input_a", "a_input_a"),
("a_output_output", "a_output"),
],
ids=["input-remove", "no-change", "output-remove", "double-match-no-change"],
)
def test__remove_io_suffix(value, expected):
result = _remove_io_suffix(value)
assert result == expected
def test__get_attrs():
metadata = dict(number={"a_number": 1, "a_list": [1, 2, 3]})
dat = _get_attrs("number", metadata)
for k, v in dat.items():
assert isinstance(v, str)
dat = _get_attrs("nonexistent", metadata)
assert not dat
assert isinstance(dat, Mapping)
def get_state_meta_for_conversion():
metadata = dict(
field_A={"units": "beepboop", "real-name": "missingno"},
field_B={"units": "goobgob", "real-name": "trivial"},
)
state = {
"field_A": np.ones(50).reshape(2, 25),
"field_B": np.ones(50).reshape(2, 25),
}
return state, metadata
@pytest.mark.parametrize(
"convert_func, expected_type",
[(_convert_to_quantities, Quantity), (_convert_to_xr_dataset, DataArray)],
ids=["to-quantity", "to-xr-dataset"],
)
def test__conversions(convert_func, expected_type):
state, meta = get_state_meta_for_conversion()
quantities = convert_func(state, meta)
for data in quantities.values():
assert isinstance(data, expected_type)
assert data.values.shape == (25, 2)
def test__translate_time():
year = 2016
month = 10
day = 29
time = _translate_time([year, month, day, None, 0, 0])
assert time.year == year
assert time.month == month
assert time.day == day
def test__create_nc_path(dummy_rundir):
_create_nc_path()
assert os.path.exists(dummy_rundir / "netcdf_output")
@pytest.mark.parametrize("save_nc", [True, False])
@pytest.mark.parametrize("save_zarr", [True, False])
def test_Config_integration(dummy_rundir, save_nc, save_zarr):
meta_path = dummy_rundir / "var_metadata.yaml"
save_var_metadata(meta_path)
config = StorageHook(meta_path, 900, save_nc=save_nc, save_zarr=save_zarr)
state = {
"model_time": [2016, 10, 8, None, 0, 0],
"air_temperature": np.arange(790).reshape(10, 79),
"specific_humidity": np.arange(790).reshape(10, 79),
}
config.store(state)
assert (dummy_rundir / "state_output.zarr").exists() == save_zarr
nc_files = list((dummy_rundir / "netcdf_output").glob("*.nc"))
assert len(nc_files) == save_nc
def test_error_on_call():
with pytest.raises(ImportError):
from emulation import store
store({}) | external/emulation/tests/test_zc_emu_monitor.py | import os
import pytest
import numpy as np
from xarray import DataArray
from typing import Mapping
from fv3gfs.util import Quantity
from emulation._monitor.monitor import (
StorageHook,
_bool_from_str,
_load_nml,
_get_timestep,
_remove_io_suffix,
_get_attrs,
_convert_to_quantities,
_convert_to_xr_dataset,
_translate_time,
_create_nc_path,
)
def save_var_metadata(path):
metadata_content = """
air_temperature:
units: K
specific_humidity:
units: kg/kg
"""
with open(path, "w") as f:
f.write(metadata_content)
@pytest.mark.parametrize(
"value, expected",
[
("y", True),
("yes", True),
("true", True),
("n", False),
("no", False),
("false", False),
],
)
def test__bool_from_str(value, expected):
assert _bool_from_str(value) == expected
assert _bool_from_str(value.capitalize()) == expected
assert _bool_from_str(value.upper()) == expected
def test__bool_from_str_unrecognized():
with pytest.raises(ValueError):
_bool_from_str("not-translatable-to-bool")
def test__load_nml(dummy_rundir):
namelist = _load_nml()
assert namelist["coupler_nml"]["hours"] == 1
def test__get_timestep(dummy_rundir):
namelist = _load_nml()
timestep = _get_timestep(namelist)
assert timestep == 900
@pytest.mark.parametrize(
"value,expected",
[
("a_input", "a"),
("a_output", "a"),
("a_input_a", "a_input_a"),
("a_output_output", "a_output"),
],
ids=["input-remove", "no-change", "output-remove", "double-match-no-change"],
)
def test__remove_io_suffix(value, expected):
result = _remove_io_suffix(value)
assert result == expected
def test__get_attrs():
metadata = dict(number={"a_number": 1, "a_list": [1, 2, 3]})
dat = _get_attrs("number", metadata)
for k, v in dat.items():
assert isinstance(v, str)
dat = _get_attrs("nonexistent", metadata)
assert not dat
assert isinstance(dat, Mapping)
def get_state_meta_for_conversion():
metadata = dict(
field_A={"units": "beepboop", "real-name": "missingno"},
field_B={"units": "goobgob", "real-name": "trivial"},
)
state = {
"field_A": np.ones(50).reshape(2, 25),
"field_B": np.ones(50).reshape(2, 25),
}
return state, metadata
@pytest.mark.parametrize(
"convert_func, expected_type",
[(_convert_to_quantities, Quantity), (_convert_to_xr_dataset, DataArray)],
ids=["to-quantity", "to-xr-dataset"],
)
def test__conversions(convert_func, expected_type):
state, meta = get_state_meta_for_conversion()
quantities = convert_func(state, meta)
for data in quantities.values():
assert isinstance(data, expected_type)
assert data.values.shape == (25, 2)
def test__translate_time():
year = 2016
month = 10
day = 29
time = _translate_time([year, month, day, None, 0, 0])
assert time.year == year
assert time.month == month
assert time.day == day
def test__create_nc_path(dummy_rundir):
_create_nc_path()
assert os.path.exists(dummy_rundir / "netcdf_output")
@pytest.mark.parametrize("save_nc", [True, False])
@pytest.mark.parametrize("save_zarr", [True, False])
def test_Config_integration(dummy_rundir, save_nc, save_zarr):
meta_path = dummy_rundir / "var_metadata.yaml"
save_var_metadata(meta_path)
config = StorageHook(meta_path, 900, save_nc=save_nc, save_zarr=save_zarr)
state = {
"model_time": [2016, 10, 8, None, 0, 0],
"air_temperature": np.arange(790).reshape(10, 79),
"specific_humidity": np.arange(790).reshape(10, 79),
}
config.store(state)
assert (dummy_rundir / "state_output.zarr").exists() == save_zarr
nc_files = list((dummy_rundir / "netcdf_output").glob("*.nc"))
assert len(nc_files) == save_nc
def test_error_on_call():
with pytest.raises(ImportError):
from emulation import store
store({}) | 0.727685 | 0.575081 |
import unittest
from mock_decorators.dict_mock import DictMock
from tests.mock_decorators import module_test
class TestDictMock(unittest.TestCase):
def test_dict_mock_ok(self):
changed_result = 20
old_value = module_test.a_dict['value_a']
old_value_hardcoded = 22
@DictMock(module_test.a_dict, 'value_a', changed_result, True)
def inner_test():
return module_test.a_dict['value_a']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertEqual(module_test.a_dict['value_a'], old_value)
self.assertEqual(module_test.a_dict['value_a'], old_value_hardcoded)
self.assertNotEqual(module_test.a_dict['value_a'], changed_result)
def test_dict_mock_ok_no_exists(self):
changed_result = 20
@DictMock(module_test.a_dict, 'value_c', changed_result, False)
def inner_test():
return module_test.a_dict['value_c']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertFalse('value_c' in module_test.a_dict)
def test_dict_mock_error_no_exists(self):
changed_result = 20
@DictMock(module_test.a_dict, 'value_c', changed_result, True)
def inner_test():
return module_test.a_dict['value_c']
self.assertRaises(TypeError, inner_test)
def test_dict_none_ok(self):
changed_result = 20
old_value = module_test.a_dict['value_b']
old_value_hardcoded = None
@DictMock(module_test.a_dict, 'value_b', changed_result, True)
def inner_test():
return module_test.a_dict['value_b']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertEqual(module_test.a_dict['value_b'], old_value)
self.assertEqual(module_test.a_dict['value_b'], old_value_hardcoded)
self.assertNotEqual(module_test.a_dict['value_b'], changed_result)
self.assertTrue('value_b' in module_test.a_dict) | tests/mock_decorators/test_dict_mock.py | import unittest
from mock_decorators.dict_mock import DictMock
from tests.mock_decorators import module_test
class TestDictMock(unittest.TestCase):
def test_dict_mock_ok(self):
changed_result = 20
old_value = module_test.a_dict['value_a']
old_value_hardcoded = 22
@DictMock(module_test.a_dict, 'value_a', changed_result, True)
def inner_test():
return module_test.a_dict['value_a']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertEqual(module_test.a_dict['value_a'], old_value)
self.assertEqual(module_test.a_dict['value_a'], old_value_hardcoded)
self.assertNotEqual(module_test.a_dict['value_a'], changed_result)
def test_dict_mock_ok_no_exists(self):
changed_result = 20
@DictMock(module_test.a_dict, 'value_c', changed_result, False)
def inner_test():
return module_test.a_dict['value_c']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertFalse('value_c' in module_test.a_dict)
def test_dict_mock_error_no_exists(self):
changed_result = 20
@DictMock(module_test.a_dict, 'value_c', changed_result, True)
def inner_test():
return module_test.a_dict['value_c']
self.assertRaises(TypeError, inner_test)
def test_dict_none_ok(self):
changed_result = 20
old_value = module_test.a_dict['value_b']
old_value_hardcoded = None
@DictMock(module_test.a_dict, 'value_b', changed_result, True)
def inner_test():
return module_test.a_dict['value_b']
result_mocked = inner_test()
self.assertEqual(result_mocked, changed_result)
self.assertEqual(module_test.a_dict['value_b'], old_value)
self.assertEqual(module_test.a_dict['value_b'], old_value_hardcoded)
self.assertNotEqual(module_test.a_dict['value_b'], changed_result)
self.assertTrue('value_b' in module_test.a_dict) | 0.628749 | 0.45647 |
import os
from os import environ
import random
import config
import dbworker
import datetime
import requests
import urllib.request
import subprocess
import telebot
from telebot.types import Message
bot = telebot.TeleBot(config.TOKEN)
#BOT_TOKEN = '...'
# bot = telebot.TeleBot(environ['BOT_TOKEN'])
@bot.message_handler(commands=['start'])
def cmd_start(message):
bot.send_message(message.chat.id, "Hello from Wonderland! 💙"
"\nLet's start our journey 🌹 and try to find Cheshire Cat 🐱"
"\n \nHere are some commands: "
"\n🔹 /dialog - start dialog"
"\n🔹 /reset - reset dialog"
"\n🔹 /recognition - image classification"
"\n🔹 /help")
bot.send_sticker(message.chat.id, '<KEY>')
# Start of dialogue
@bot.message_handler(commands=["dialog"])
def cmd_start_dialog(message):
state = dbworker.get_current_state(message.chat.id)
if state == config.States.S_ENTER_NAME.value:
bot.send_message(message.chat.id, "It seems that someone promised to send his name, but did not do it 🙁 "
"I’m still waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_ENTER_AGE.value:
bot.send_message(message.chat.id, "It seems that someone promised to send his age, but did not do it 😔 "
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_LOCATION.value:
bot.send_message(message.chat.id, "It seems that someone promised to send where is he from 📍"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_PIC.value:
bot.send_message(message.chat.id, "It seems that someone promised to send a picture"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_MOVIE.value:
bot.send_message(message.chat.id, "It seems that someone promised to send favourite movie 🎥🎞"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
else: # By "else" mean the state "0" - the beginning of the dialogue
bot.send_message(message.chat.id, "So what is your name?")
bot.send_sticker(message.chat.id, '<KEY>')
dbworker.set_state(message.chat.id, config.States.S_ENTER_NAME.value)
# Using the / reset command, we will reset the states, returning to the beginning of the dialogue
@bot.message_handler(commands=["reset"])
def cmd_reset(message):
bot.send_message(message.chat.id, "Well, let's start in a new way. What's your name?")
dbworker.set_state(message.chat.id, config.States.S_ENTER_NAME.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_ENTER_NAME.value)
def user_entering_name(message):
# In the case of the name don’t check anything
bot.send_message(message.chat.id, "Good name, I'll remember! "
"\nNow tell me your age, please?")
dbworker.set_state(message.chat.id, config.States.S_ENTER_AGE.value)
@bot.message_handler(commands=['help'])
def cmd_help(message):
bot.send_message(message.chat.id, "Here are commands: "
"\n \n🔹 /dialog - start dialog"
"\n🔹 /reset - reset dialog"
"\n🔹 /recognition - image classification"
"\n🔹 /help")
dbworker.set_state(message.chat.id, config.States.S_START.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_ENTER_AGE.value)
def user_entering_age(message):
# Here we’ll do a check
if not message.text.isdigit():
# Состояние не меняем, поэтому только выводим сообщение об ошибке и ждём дальше
bot.send_message(message.chat.id, "Something get wrong 🤔 Try again!")
bot.send_sticker(message.chat.id, 'CAACAgQAAxkBAAIlml5BssgRiup761KZTm_eAfnNwhmQAAIeAQACu-RJAAEYZh0WQkIVsRgE')
return
# At this stage, we are sure that message.text can be converted to a number, so we do not risk anything
if int(message.text) < 10 or int(message.text) > 100:
bot.send_message(message.chat.id, "What a strange age! I don't believe you! Answer honestly 🙃")
bot.send_sticker(message.chat.id, 'CAACAgIAAxkBAAIloF5BtAPCWDpC4NmBuqPSqgN9dCz1AAKWAQACW90SCIRDegskrgwjGAQ')
return
else:
# Age entered correctly, can go further
bot.send_message(message.chat.id, "Once upon a time, I was the same age as you do ... oh ... "
"However, we will not be distracted. "
"\nLet me know a little bit more about you ☺️"
"\nWhere are you from?")
dbworker.set_state(message.chat.id, config.States.S_SEND_LOCATION.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) ==
config.States.S_SEND_LOCATION.value)
def user_sending_location(message):
bot.send_message(message.chat.id, "Wow! It seems far away from Wonderland..."
"\nSend me any picture you like 😊")
dbworker.set_state(message.chat.id, config.States.S_SEND_PIC.value)
@bot.message_handler(content_types=["photo"],
func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_SEND_PIC.value)
def user_sending_photo(message):
# We already checked that this is a photo in the handler, no additional actions are needed.
bot.send_message(message.chat.id, "That's nice!"
"\nWhat is your favourite movie? 🎥🎞")
dbworker.set_state(message.chat.id, config.States.S_SEND_MOVIE.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) ==
config.States.S_SEND_MOVIE.value)
def user_sending_location(message):
bot.send_message(message.chat.id, "Excellent! 🤗"
"\n\nIf you would like to chat again - send the command /dialog.")
bot.send_sticker(message.chat.id, 'CAACAgIAAxkBAAImEF5DHKHzt_ncvcof707s0hmWXTq9AAKJAQACW90SCCBacVSfHiAlGAQ')
dbworker.set_state(message.chat.id, config.States.S_START.value)
# ----------- Recognition ---------------
bot_text = '''
✨ Hi once more! ✨
So let's classify images using neural networks ✨
Send any pictures you like and I with Cheshire Cat 🐱 will classify them for you 🙃
'''
# store files in /tmp so storage does not get complete
result_storage_path = 'tmp'
@bot.message_handler(commands=['recognition'])
def send_welcome(message):
bot.send_message(message.chat.id, bot_text)
bot.send_sticker(message.chat.id, '<KEY>')
@bot.message_handler(content_types=['photo'])
def handle(message):
log_request(message)
image_name = save_image_from_message(message)
# object recognition
object_recognition_image(image_name)
bot.send_photo(message.chat.id, open('.data/darknet/predictions.jpg','rb'), 'Identified objects, if any! 😊')
# image classification
classification_list_result = classify_image(image_name)
# send classification results
output = 'The image classifies as:\n'
for result in classification_list_result:
output += result
output += '\n Gimme more pictures! 🌸'
bot.reply_to(message, output)
cleanup_remove_image(image_name);
# ----------- Helper functions ---------------
def log_request(message):
file = open('.data/logs.txt', 'a') #append to file
file.write("{0} - {1} {2} [{3}]\n".format(datetime.datetime.now(), message.from_user.first_name, message.from_user.last_name, message.from_user.id))
print("{0} - {1} {2} [{3}]".format(datetime.datetime.now(), message.from_user.first_name, message.from_user.last_name, message.from_user.id))
file.close()
def get_image_id_from_message(message):
# there are multiple array of images, check the biggest
return message.photo[len(message.photo)-1].file_id
def save_image_from_message(message):
cid = message.chat.id
image_id = get_image_id_from_message(message)
bot.send_message(cid, '🌹 I am analyzing image, be patient! 🌹 ')
# prepare image for downlading
file_path = bot.get_file(image_id).file_path
# generate image download url
#image_url = "https://api.telegram.org/file/bot{0}/{1}".format(environ['BOT_TOKEN'], file_path)
image_url = "https://api.telegram.org/file/bot{0}/{1}".format(config.TOKEN, file_path)
print(image_url)
# create folder to store pic temporary, if it doesnt exist
if not os.path.exists(result_storage_path):
os.makedirs(result_storage_path)
# retrieve and save image
image_name = "{0}.jpg".format(image_id)
urllib.request.urlretrieve(image_url, "{0}/{1}".format(result_storage_path,image_name))
return image_name;
def classify_image(image_name):
# classify image -> https://pjreddie.com/darknet/imagenet/
os.system('cd .data/darknet && ./darknet classifier predict cfg/imagenet1k.data cfg/darknet19.cfg darknet19.weights ../../{0}/{1} > ../../{0}/results.txt'.format(result_storage_path, image_name))
# retrieve classification results
results_file = open("{0}/results.txt".format(result_storage_path),"r")
results = results_file.readlines()
results_file.close()
return results
def object_recognition_image(image_name):
# object recognition -> https://pjreddie.com/darknet/yolo/
os.system('cd .data/darknet && ./darknet detect cfg/yolov3-tiny.cfg yolov3-tiny.weights ../../{0}/{1}'.format(result_storage_path, image_name))
def cleanup_remove_image(image_name):
os.remove('{0}/{1}'.format(result_storage_path, image_name))
alice_stickers = [
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'CAACAgIAAxkBAAIlIF5ATu9ivvNnO91pe6rK8NfAUbLtAAKNAQACW90SCC481L9ADH7WGAQ',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>--<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
]
@bot.message_handler(func = lambda message: True)
def send_sticker(message: Message):
bot.send_sticker(message.chat.id, random.choice(alice_stickers))
if __name__ == "__main__":
bot.infinity_polling() | Alice/scripts/bot.py | import os
from os import environ
import random
import config
import dbworker
import datetime
import requests
import urllib.request
import subprocess
import telebot
from telebot.types import Message
bot = telebot.TeleBot(config.TOKEN)
#BOT_TOKEN = '...'
# bot = telebot.TeleBot(environ['BOT_TOKEN'])
@bot.message_handler(commands=['start'])
def cmd_start(message):
bot.send_message(message.chat.id, "Hello from Wonderland! 💙"
"\nLet's start our journey 🌹 and try to find Cheshire Cat 🐱"
"\n \nHere are some commands: "
"\n🔹 /dialog - start dialog"
"\n🔹 /reset - reset dialog"
"\n🔹 /recognition - image classification"
"\n🔹 /help")
bot.send_sticker(message.chat.id, '<KEY>')
# Start of dialogue
@bot.message_handler(commands=["dialog"])
def cmd_start_dialog(message):
state = dbworker.get_current_state(message.chat.id)
if state == config.States.S_ENTER_NAME.value:
bot.send_message(message.chat.id, "It seems that someone promised to send his name, but did not do it 🙁 "
"I’m still waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_ENTER_AGE.value:
bot.send_message(message.chat.id, "It seems that someone promised to send his age, but did not do it 😔 "
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_LOCATION.value:
bot.send_message(message.chat.id, "It seems that someone promised to send where is he from 📍"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_PIC.value:
bot.send_message(message.chat.id, "It seems that someone promised to send a picture"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
elif state == config.States.S_SEND_MOVIE.value:
bot.send_message(message.chat.id, "It seems that someone promised to send favourite movie 🎥🎞"
"I’m waiting ...")
bot.send_sticker(message.chat.id, '<KEY>')
else: # By "else" mean the state "0" - the beginning of the dialogue
bot.send_message(message.chat.id, "So what is your name?")
bot.send_sticker(message.chat.id, '<KEY>')
dbworker.set_state(message.chat.id, config.States.S_ENTER_NAME.value)
# Using the / reset command, we will reset the states, returning to the beginning of the dialogue
@bot.message_handler(commands=["reset"])
def cmd_reset(message):
bot.send_message(message.chat.id, "Well, let's start in a new way. What's your name?")
dbworker.set_state(message.chat.id, config.States.S_ENTER_NAME.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_ENTER_NAME.value)
def user_entering_name(message):
# In the case of the name don’t check anything
bot.send_message(message.chat.id, "Good name, I'll remember! "
"\nNow tell me your age, please?")
dbworker.set_state(message.chat.id, config.States.S_ENTER_AGE.value)
@bot.message_handler(commands=['help'])
def cmd_help(message):
bot.send_message(message.chat.id, "Here are commands: "
"\n \n🔹 /dialog - start dialog"
"\n🔹 /reset - reset dialog"
"\n🔹 /recognition - image classification"
"\n🔹 /help")
dbworker.set_state(message.chat.id, config.States.S_START.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_ENTER_AGE.value)
def user_entering_age(message):
# Here we’ll do a check
if not message.text.isdigit():
# Состояние не меняем, поэтому только выводим сообщение об ошибке и ждём дальше
bot.send_message(message.chat.id, "Something get wrong 🤔 Try again!")
bot.send_sticker(message.chat.id, 'CAACAgQAAxkBAAIlml5BssgRiup761KZTm_eAfnNwhmQAAIeAQACu-RJAAEYZh0WQkIVsRgE')
return
# At this stage, we are sure that message.text can be converted to a number, so we do not risk anything
if int(message.text) < 10 or int(message.text) > 100:
bot.send_message(message.chat.id, "What a strange age! I don't believe you! Answer honestly 🙃")
bot.send_sticker(message.chat.id, 'CAACAgIAAxkBAAIloF5BtAPCWDpC4NmBuqPSqgN9dCz1AAKWAQACW90SCIRDegskrgwjGAQ')
return
else:
# Age entered correctly, can go further
bot.send_message(message.chat.id, "Once upon a time, I was the same age as you do ... oh ... "
"However, we will not be distracted. "
"\nLet me know a little bit more about you ☺️"
"\nWhere are you from?")
dbworker.set_state(message.chat.id, config.States.S_SEND_LOCATION.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) ==
config.States.S_SEND_LOCATION.value)
def user_sending_location(message):
bot.send_message(message.chat.id, "Wow! It seems far away from Wonderland..."
"\nSend me any picture you like 😊")
dbworker.set_state(message.chat.id, config.States.S_SEND_PIC.value)
@bot.message_handler(content_types=["photo"],
func=lambda message: dbworker.get_current_state(message.chat.id) == config.States.S_SEND_PIC.value)
def user_sending_photo(message):
# We already checked that this is a photo in the handler, no additional actions are needed.
bot.send_message(message.chat.id, "That's nice!"
"\nWhat is your favourite movie? 🎥🎞")
dbworker.set_state(message.chat.id, config.States.S_SEND_MOVIE.value)
@bot.message_handler(func=lambda message: dbworker.get_current_state(message.chat.id) ==
config.States.S_SEND_MOVIE.value)
def user_sending_location(message):
bot.send_message(message.chat.id, "Excellent! 🤗"
"\n\nIf you would like to chat again - send the command /dialog.")
bot.send_sticker(message.chat.id, 'CAACAgIAAxkBAAImEF5DHKHzt_ncvcof707s0hmWXTq9AAKJAQACW90SCCBacVSfHiAlGAQ')
dbworker.set_state(message.chat.id, config.States.S_START.value)
# ----------- Recognition ---------------
bot_text = '''
✨ Hi once more! ✨
So let's classify images using neural networks ✨
Send any pictures you like and I with Cheshire Cat 🐱 will classify them for you 🙃
'''
# store files in /tmp so storage does not get complete
result_storage_path = 'tmp'
@bot.message_handler(commands=['recognition'])
def send_welcome(message):
bot.send_message(message.chat.id, bot_text)
bot.send_sticker(message.chat.id, '<KEY>')
@bot.message_handler(content_types=['photo'])
def handle(message):
log_request(message)
image_name = save_image_from_message(message)
# object recognition
object_recognition_image(image_name)
bot.send_photo(message.chat.id, open('.data/darknet/predictions.jpg','rb'), 'Identified objects, if any! 😊')
# image classification
classification_list_result = classify_image(image_name)
# send classification results
output = 'The image classifies as:\n'
for result in classification_list_result:
output += result
output += '\n Gimme more pictures! 🌸'
bot.reply_to(message, output)
cleanup_remove_image(image_name);
# ----------- Helper functions ---------------
def log_request(message):
file = open('.data/logs.txt', 'a') #append to file
file.write("{0} - {1} {2} [{3}]\n".format(datetime.datetime.now(), message.from_user.first_name, message.from_user.last_name, message.from_user.id))
print("{0} - {1} {2} [{3}]".format(datetime.datetime.now(), message.from_user.first_name, message.from_user.last_name, message.from_user.id))
file.close()
def get_image_id_from_message(message):
# there are multiple array of images, check the biggest
return message.photo[len(message.photo)-1].file_id
def save_image_from_message(message):
cid = message.chat.id
image_id = get_image_id_from_message(message)
bot.send_message(cid, '🌹 I am analyzing image, be patient! 🌹 ')
# prepare image for downlading
file_path = bot.get_file(image_id).file_path
# generate image download url
#image_url = "https://api.telegram.org/file/bot{0}/{1}".format(environ['BOT_TOKEN'], file_path)
image_url = "https://api.telegram.org/file/bot{0}/{1}".format(config.TOKEN, file_path)
print(image_url)
# create folder to store pic temporary, if it doesnt exist
if not os.path.exists(result_storage_path):
os.makedirs(result_storage_path)
# retrieve and save image
image_name = "{0}.jpg".format(image_id)
urllib.request.urlretrieve(image_url, "{0}/{1}".format(result_storage_path,image_name))
return image_name;
def classify_image(image_name):
# classify image -> https://pjreddie.com/darknet/imagenet/
os.system('cd .data/darknet && ./darknet classifier predict cfg/imagenet1k.data cfg/darknet19.cfg darknet19.weights ../../{0}/{1} > ../../{0}/results.txt'.format(result_storage_path, image_name))
# retrieve classification results
results_file = open("{0}/results.txt".format(result_storage_path),"r")
results = results_file.readlines()
results_file.close()
return results
def object_recognition_image(image_name):
# object recognition -> https://pjreddie.com/darknet/yolo/
os.system('cd .data/darknet && ./darknet detect cfg/yolov3-tiny.cfg yolov3-tiny.weights ../../{0}/{1}'.format(result_storage_path, image_name))
def cleanup_remove_image(image_name):
os.remove('{0}/{1}'.format(result_storage_path, image_name))
alice_stickers = [
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'CAACAgIAAxkBAAIlIF5ATu9ivvNnO91pe6rK8NfAUbLtAAKNAQACW90SCC481L9ADH7WGAQ',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>--<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
'<KEY>',
]
@bot.message_handler(func = lambda message: True)
def send_sticker(message: Message):
bot.send_sticker(message.chat.id, random.choice(alice_stickers))
if __name__ == "__main__":
bot.infinity_polling() | 0.271541 | 0.055797 |
import os
import json
import click
from os import mkdir
from numpy import inf
from glob import glob
from shutil import rmtree
from os.path import join, isdir, abspath
from .common import success, status, error, warn, setup_spark
from .. import load, convert
@click.argument('output', nargs=1, metavar='<output directory>', required=False, default=None)
@click.argument('input', nargs=1, metavar='<input directory>', required=True)
@click.option('--overwrite', is_flag=True, help='Overwrite if directory already exists')
@click.option('--url', is_flag=False, nargs=1, help='URL of the master node of a Spark cluster')
@click.option('--ext', nargs=1, default='tif')
@click.command('convert', short_help='process raw data by converting into images', options_metavar='<options>')
def convert_command(input, output, ext, url, overwrite):
input = abspath(input)
output = input + '_converted' if output is None else abspath(output)
if isdir(output) and not overwrite:
error('directory already exists and overwrite is false')
return
elif isdir(output) and overwrite:
rmtree(output)
mkdir(output)
engine = setup_spark(url)
status('reading data from %s' % input)
if len(glob(join(input, '*.json'))) == 0:
error('no json metadata found in %s' % input)
return
if len(glob(join(input, '*.tif'))) == 0 and len(glob(join(input, '*.tiff'))) == 0:
error('no tif or tiff files found in %s' % input)
return
data, meta = load(input, input, engine=engine)
status('converting')
newdata, newmeta = convert(data, meta)
status('writing data to %s' % output)
if ext == 'tif':
newdata.clip(0, inf).astype('uint16').totif(output, overwrite=overwrite)
elif ext == 'bin':
newdata.clip(0, inf).astype('uint16').tobinary(output, overwrite=overwrite)
else:
error('extenstion %s not recognized' % ext)
with open(join(output, 'metadata.json'), 'w') as f:
f.write(json.dumps(newmeta, indent=2))
success('data written') | mesoscope/commands/convert.py | import os
import json
import click
from os import mkdir
from numpy import inf
from glob import glob
from shutil import rmtree
from os.path import join, isdir, abspath
from .common import success, status, error, warn, setup_spark
from .. import load, convert
@click.argument('output', nargs=1, metavar='<output directory>', required=False, default=None)
@click.argument('input', nargs=1, metavar='<input directory>', required=True)
@click.option('--overwrite', is_flag=True, help='Overwrite if directory already exists')
@click.option('--url', is_flag=False, nargs=1, help='URL of the master node of a Spark cluster')
@click.option('--ext', nargs=1, default='tif')
@click.command('convert', short_help='process raw data by converting into images', options_metavar='<options>')
def convert_command(input, output, ext, url, overwrite):
input = abspath(input)
output = input + '_converted' if output is None else abspath(output)
if isdir(output) and not overwrite:
error('directory already exists and overwrite is false')
return
elif isdir(output) and overwrite:
rmtree(output)
mkdir(output)
engine = setup_spark(url)
status('reading data from %s' % input)
if len(glob(join(input, '*.json'))) == 0:
error('no json metadata found in %s' % input)
return
if len(glob(join(input, '*.tif'))) == 0 and len(glob(join(input, '*.tiff'))) == 0:
error('no tif or tiff files found in %s' % input)
return
data, meta = load(input, input, engine=engine)
status('converting')
newdata, newmeta = convert(data, meta)
status('writing data to %s' % output)
if ext == 'tif':
newdata.clip(0, inf).astype('uint16').totif(output, overwrite=overwrite)
elif ext == 'bin':
newdata.clip(0, inf).astype('uint16').tobinary(output, overwrite=overwrite)
else:
error('extenstion %s not recognized' % ext)
with open(join(output, 'metadata.json'), 'w') as f:
f.write(json.dumps(newmeta, indent=2))
success('data written') | 0.216674 | 0.112162 |
import setpath
import functions
import json
registered=True
'''
Highcharts.chart('container', {
chart: { type: 'bubble', plotBorderWidth: 1, zoomType: 'xy' },
title: { text: 'Highcharts bubbles with radial gradient fill' },
xAxis: { gridLineWidth: 1 },
yAxis: { startOnTick: false, endOnTick: false },
series: [{
data: [
[9, 81, 63],
[44, 83, 22]
]
}]
});
'''
class highchartbubble(functions.vtable.vtbase.VT):
def VTiter(self, *parsedArgs,**envars):
largs, dictargs = self.full_parse(parsedArgs)
if 'query' not in dictargs:
raise functions.OperatorError(__name__.rsplit('.')[-1],"No query argument ")
query = dictargs['query']
if 'title' not in dictargs:
raise functions.OperatorError(__name__.rsplit('.')[-1],"No title argument ")
cur = envars['db'].cursor()
c=cur.execute(query)
schema = cur.getdescriptionsafe()
mydata = []
for myrow in c:
mydata.append(list(myrow))
#print schema[2]
#print schema[2][0]
if len(schema)!=3 or (len(schema)==3 and str(schema[2][0])!='noofpoints'):
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"subtitle":{"text":"The plot is empty as there are not two variables "}
}
}
elif len(mydata)==0:
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"subtitle":{"text":"The plot is empty as there are not data points"}
}
}
else:
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"xAxis" : { "gridLineWidth": 1, "title": {"text": str(schema[0][0]), "align":"middle" }},
"yAxis": { "gridLineWidth": 1, "title": {"text": str(schema[1][0]), "align":"middle" }},
"series": [{ "data": mydata}]
}
}
myjsonresult = json.dumps(myresult)
yield [('highchartresult',)]
yield (myjsonresult,)
def Source():
return functions.vtable.vtbase.VTGenerator(highchartbubble)
if not ('.' in __name__):
"""
This is needed to be able to test the function, put it at the end of every
new function you create
"""
import sys
import setpath
from functions import *
testfunction()
if __name__ == "__main__":
reload(sys)
sys.setdefaultencoding('utf-8')
import doctest
doctest.tesdoctest.tes | Exareme-Docker/src/exareme/exareme-tools/madis/src/functionslocal/vtable/highchartbubble.py | import setpath
import functions
import json
registered=True
'''
Highcharts.chart('container', {
chart: { type: 'bubble', plotBorderWidth: 1, zoomType: 'xy' },
title: { text: 'Highcharts bubbles with radial gradient fill' },
xAxis: { gridLineWidth: 1 },
yAxis: { startOnTick: false, endOnTick: false },
series: [{
data: [
[9, 81, 63],
[44, 83, 22]
]
}]
});
'''
class highchartbubble(functions.vtable.vtbase.VT):
def VTiter(self, *parsedArgs,**envars):
largs, dictargs = self.full_parse(parsedArgs)
if 'query' not in dictargs:
raise functions.OperatorError(__name__.rsplit('.')[-1],"No query argument ")
query = dictargs['query']
if 'title' not in dictargs:
raise functions.OperatorError(__name__.rsplit('.')[-1],"No title argument ")
cur = envars['db'].cursor()
c=cur.execute(query)
schema = cur.getdescriptionsafe()
mydata = []
for myrow in c:
mydata.append(list(myrow))
#print schema[2]
#print schema[2][0]
if len(schema)!=3 or (len(schema)==3 and str(schema[2][0])!='noofpoints'):
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"subtitle":{"text":"The plot is empty as there are not two variables "}
}
}
elif len(mydata)==0:
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"subtitle":{"text":"The plot is empty as there are not data points"}
}
}
else:
myresult = {
"type" : "application/vnd.highcharts+json",
"data" : { "chart" : { "type": "bubble", "plotBorderWidth": 1, "zoomType": "xy"},
"title" : { "text": str(dictargs['title']) },
"xAxis" : { "gridLineWidth": 1, "title": {"text": str(schema[0][0]), "align":"middle" }},
"yAxis": { "gridLineWidth": 1, "title": {"text": str(schema[1][0]), "align":"middle" }},
"series": [{ "data": mydata}]
}
}
myjsonresult = json.dumps(myresult)
yield [('highchartresult',)]
yield (myjsonresult,)
def Source():
return functions.vtable.vtbase.VTGenerator(highchartbubble)
if not ('.' in __name__):
"""
This is needed to be able to test the function, put it at the end of every
new function you create
"""
import sys
import setpath
from functions import *
testfunction()
if __name__ == "__main__":
reload(sys)
sys.setdefaultencoding('utf-8')
import doctest
doctest.tesdoctest.tes | 0.207054 | 0.39321 |