code stringlengths 1 1.49M | vector listlengths 0 7.38k | snippet listlengths 0 7.38k |
|---|---|---|
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
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"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
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"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
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"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
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"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
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... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
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0.0097,
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[
1,
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0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
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1,
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0,
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[
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1,
799,
4,
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]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
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0,
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0,
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0,
0,
192,
0,
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],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
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1,
0,
0,
905,
0,
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[
1,
0,
0.3214,
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0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
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0,
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[
2,
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... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
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1,
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0.0156,
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[
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],
[
1,
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0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
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0.0049,
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0,
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0,
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[
1,
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[
3,
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0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.36,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
0.66,
0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
0.66,
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0,
0,
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0,
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[
1,
0,
0.3036,
0.0179,
0,
0.66,
0.0385,
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1,
0,
0,
905,
0,
0
],
[
1,
0,
0.3214,
0.0179,
0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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[
1,
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
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0,
1,
0,
0,
878,
0,
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],
[
1,
0,
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0,
0,
154,
0,
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],
[
2,
0,
0.8333,
0.3667,
0,
0.66,
... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
0,
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0,
509,
0,
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0,
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509,
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],
[
1,
0,
0.2188,
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0,
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79,
0,
0
],
[
1,
0,
0.2344,
0.0156,
0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
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],
[
1,
0,
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0.0049,
0,
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0.5,
878,
0,
1,
0,
0,
878,
0,
0
],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.85,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
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0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
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1,
0,
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0.0128,
0,
0.66,
0,
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0,
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0,
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14,
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0.7564,
0,
0.66,
1,
799,
4,
0,
0,
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0,
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]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
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[
1,
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[
1,
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... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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[
1,
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0,
0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
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1,
0,
0.5,
0.0333,
0,
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0,
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[
2,
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0,
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... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
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0,
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0,
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],
[
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],
[
1,
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0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
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],
[
1,
0,
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878,
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[
3,
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0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.05,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
0.66,
0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
0.66,
0,
192,
0,
1,
0,
0,
192,
0,
0
],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
0.0385,
905,
0,
1,
0,
0,
905,
0,
0
],
[
1,
0,
0.3214,
0.0179,
0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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1,
0,
0.0818,
0.0063,
0,
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0,
88,
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1,
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0,
715,
0,
0
],
[
1,
0,
0.0943,
0.0063,
0,
0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
878,
0,
1,
0,
0,
878,
0,
0
],
[
1,
0,
0.5333,
0.0333,
0,
0.66,
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154,
0,
1,
0,
0,
154,
0,
0
],
[
2,
0,
0.8333,
0.3667,
0,
0.66,
... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
0,
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0,
509,
0,
1,
0,
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],
[
1,
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79,
0,
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],
[
1,
0,
0.2344,
0.0156,
0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
0
],
[
1,
0,
0.0683,
0.0049,
0,
0.66,
0.5,
878,
0,
1,
0,
0,
878,
0,
0
],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.13,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
0.66,
0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
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... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
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0,
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[
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0,
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],
[
2,
0,
0.8333,
0.3667,
0,
0.66,
... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
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"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
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"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
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0.0227,
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[
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],
[
8,
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0.4773,
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1,
0.06,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
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[
1,
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0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
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[
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1,
799,
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]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
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0,
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0,
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0,
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],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
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905,
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0,
905,
0,
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[
1,
0,
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0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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[
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
878,
0,
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[
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[
2,
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... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
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[
1,
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[
1,
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0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
0
],
[
1,
0,
0.0683,
0.0049,
0,
0.66,
0.5,
878,
0,
1,
0,
0,
878,
0,
0
],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.09,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
0.66,
0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
0.66,
0,
192,
0,
1,
0,
0,
192,
0,
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],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
0.0385,
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1,
0,
0,
905,
0,
0
],
[
1,
0,
0.3214,
0.0179,
0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
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0,
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0,
1,
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],
[
1,
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0,
0,
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0,
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],
[
2,
0,
0.8333,
0.3667,
0,
0.66,
... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
0,
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0,
509,
0,
1,
0,
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509,
0,
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],
[
1,
0,
0.2188,
0.0156,
0,
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79,
0,
1,
0,
0,
79,
0,
0
],
[
1,
0,
0.2344,
0.0156,
0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
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],
[
1,
0,
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0.0049,
0,
0.66,
0.5,
878,
0,
1,
0,
0,
878,
0,
0
],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.88,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
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0.0097,
0,
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0,
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[
1,
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[
1,
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0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
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0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
0.66,
0,
192,
0,
1,
0,
0,
192,
0,
0
],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
0.0385,
905,
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1,
0,
0,
905,
0,
0
],
[
1,
0,
0.3214,
0.0179,
0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
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[
1,
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0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
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0,
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[
1,
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0,
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],
[
2,
0,
0.8333,
0.3667,
0,
0.66,
... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
0,
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0,
509,
0,
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0,
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509,
0,
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],
[
1,
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0,
79,
0,
0
],
[
1,
0,
0.2344,
0.0156,
0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
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],
[
1,
0,
0.0683,
0.0049,
0,
0.66,
0.5,
878,
0,
1,
0,
0,
878,
0,
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],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.89,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
0,
0.66,
0.1111,
99,
0,
1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import cvarray
import mp_map
import prog_bar
import numpy_help_cpp
import python_obj_cpp
import matrix_cpp
import gamma_cpp
import setProcName
import start_cpp
import make
import doc_gen
# Setup...
doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of miscellaneous stuff - most modules depend on this.')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('numpy_help_cpp.numpy_util_code', 'Assorted utility functions for accessing numpy arrays within scipy.weave C++ code.')
doc.addVariable('python_obj_cpp.python_obj_code', 'Assorted utility functions for interfacing with python objects from scipy.weave C++ code.')
doc.addVariable('matrix_cpp.matrix_code', 'Matrix manipulation routines for use in scipy.weave C++')
doc.addVariable('gamma_cpp.gamma_code', 'Gamma and related functions for use in scipy.weave C++')
# Functions...
doc.addFunction(make.make_mod)
doc.addFunction(cvarray.cv2array)
doc.addFunction(cvarray.array2cv)
doc.addFunction(mp_map.repeat)
doc.addFunction(mp_map.mp_map)
doc.addFunction(setProcName.setProcName)
doc.addFunction(start_cpp.start_cpp)
doc.addFunction(make.make_mod)
# Classes...
doc.addClass(prog_bar.ProgBar)
doc.addClass(doc_gen.DocGen)
| [
[
1,
0,
0.2857,
0.0179,
0,
0.66,
0,
192,
0,
1,
0,
0,
192,
0,
0
],
[
1,
0,
0.3036,
0.0179,
0,
0.66,
0.0385,
905,
0,
1,
0,
0,
905,
0,
0
],
[
1,
0,
0.3214,
0.0179,
0,
... | [
"import cvarray",
"import mp_map",
"import prog_bar",
"import numpy_help_cpp",
"import python_obj_cpp",
"import matrix_cpp",
"import gamma_cpp",
"import setProcName",
"import start_cpp",
"import make",
"import doc_gen",
"doc = doc_gen.DocGen('utils', 'Utilities/Miscellaneous', 'Library of misc... |
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
import random
import math
from scipy.special import gammaln, psi, polygamma
from scipy import weave
from utils.start_cpp import start_cpp
# Provides various gamma-related functions...
gamma_code = start_cpp() + """
#ifndef GAMMA_CODE
#define GAMMA_CODE
#include <cmath>
// Returns the natural logarithm of the Gamma function...
// (Uses Lanczos's approximation.)
double lnGamma(double z)
{
static const double coeff[9] = {0.99999999999980993, 676.5203681218851, -1259.1392167224028, 771.32342877765313, -176.61502916214059, 12.507343278686905, -0.13857109526572012, 9.9843695780195716e-6, 1.5056327351493116e-7};
if (z<0.5)
{
// Use reflection formula, as approximation doesn't work down here...
return log(M_PI) - log(sin(M_PI*z)) - lnGamma(1.0-z);
}
else
{
double x = coeff[0];
for (int i=1;i<9;i++) x += coeff[i]/(z+i-1);
double t = z + 6.5;
return log(sqrt(2.0*M_PI)) + (z-0.5)*log(t) - t + log(x);
}
}
// Calculates the Digamma function, i.e. the derivative of the log of the Gamma function - uses a partial expansion of an infinite series to 4 terms that is good for high values, and an identity to express lower values in terms of higher values...
double digamma(double z)
{
static const double highVal = 13.0; // A bit of fiddling shows that the last term with this is of the order 1e-10, so we can expect at least 9 digits of accuracy past the decimal point.
double ret = 0.0;
while (z<highVal)
{
ret -= 1.0/z;
z += 1.0;
}
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz4 = iz2*iz2;
double iz6 = iz4*iz2;
ret += log(z) - iz1/2.0 - iz2/12.0 + iz4/120.0 - iz6/252.0;
return ret;
}
// Calculates the trigamma function - uses a partial expansion of an infinite series that is accurate for large values, and then uses an identity to express lower values in terms of higher values - same approach as for the digamma function basically...
double trigamma(double z)
{
static const double highVal = 8.0;
double ret = 0.0;
while (z<highVal)
{
ret += 1.0/(z*z);
z += 1.0;
}
z -= 1.0;
double iz1 = 1.0/z;
double iz2 = iz1*iz1;
double iz3 = iz1*iz2;
double iz5 = iz3*iz2;
double iz7 = iz5*iz2;
double iz9 = iz7*iz2;
ret += iz1 - 0.5*iz2 + iz3/6.0 - iz5/30.0 + iz7/42.0 - iz9/30.0;
return ret;
}
#endif
"""
def lnGamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns the logorithm of the gamma function"""
code = start_cpp(gamma_code) + """
return_val = lnGamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def digamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the digamma function"""
code = start_cpp(gamma_code) + """
return_val = digamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
def trigamma(z):
"""Pointless as scipy, a library this is dependent on, defines this, but useful for testing. Returns an evaluation of the trigamma function"""
code = start_cpp(gamma_code) + """
return_val = trigamma(z);
"""
return weave.inline(code, ['z'], support_code=gamma_code)
class TestFuncs(unittest.TestCase):
"""Test code for the assorted gamma-related functions."""
def test_compile(self):
code = start_cpp(gamma_code) + """
"""
weave.inline(code, support_code=gamma_code)
def test_error_lngamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = lnGamma(z)
good = gammaln(z)
assert(math.fabs(own-good)<1e-12)
def test_error_digamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = digamma(z)
good = psi(z)
assert(math.fabs(own-good)<1e-9)
def test_error_trigamma(self):
for _ in xrange(1000):
z = random.uniform(0.01, 100.0)
own = trigamma(z)
good = polygamma(1,z)
assert(math.fabs(own-good)<1e-9)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.0818,
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0,
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],
[
1,
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715,
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1,
0,
0,
715,
0,
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],
[
1,
0,
0.0943,
0.0063,
0,
0.... | [
"import unittest",
"import random",
"import math",
"from scipy.special import gammaln, psi, polygamma",
"from scipy import weave",
"from utils.start_cpp import start_cpp",
"gamma_code = start_cpp() + \"\"\"\n#ifndef GAMMA_CODE\n#define GAMMA_CODE\n\n#include <cmath>\n\n// Returns the natural logarithm o... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import inspect
import hashlib
def start_cpp(hash_str = None):
"""This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for working around the fact the scipy.weave only recompiles if the hash of the code changes, but ignores the support_code - passing the support_code into start_cpp avoids this problem by putting its hash into the code and forcing a recompile when that code changes. Usage is <code variable> = start_cpp([support_code variable]) + <3 quotations to start big comment with code in, typically going over many lines.>"""
frame = inspect.currentframe().f_back
info = inspect.getframeinfo(frame)
if hash_str==None:
return '#line %i "%s"\n'%(info[1],info[0])
else:
h = hashlib.md5()
h.update(hash_str)
hash_val = h.hexdigest()
return '#line %i "%s" // %s\n'%(info[1],info[0],hash_val)
| [
[
1,
0,
0.5,
0.0333,
0,
0.66,
0,
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0,
1,
0,
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],
[
1,
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0,
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],
[
2,
0,
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0.3667,
0,
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... | [
"import inspect",
"import hashlib",
"def start_cpp(hash_str = None):\n \"\"\"This method does two things - firstly it adds the correct line numbers to scipy.weave code (Good for debugging) and secondly it can optionaly inserts a hash code of some other code into the code. This latter feature is useful for work... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import os.path
import tempfile
import shutil
from distutils.core import setup, Extension
import distutils.ccompiler
import distutils.dep_util
try:
__default_compiler = distutils.ccompiler.new_compiler()
except:
__default_compiler = None
def make_mod(name, base, source, openCL = False):
"""Uses distutils to compile a python module - really just a set of hacks to allow this to be done 'on demand', so it only compiles if the module does not exist or is older than the current source, and after compilation the program can continue on its merry way, and immediatly import the just compiled module. Note that on failure erros can be thrown - its your choice to catch them or not. name is the modules name, i.e. what you want to use with the import statement. base is the base directory for the module, which contains the source file - often you would want to set this to 'os.path.dirname(__file__)', assuming the .py file that imports the module is in the same directory as the code. It is this directory that the module is output to. source is the filename of the source code to compile, or alternativly a list of filenames. openCL indicates if OpenCL is used by the module, in which case it does all the necesary setup - done like this so these setting can be kept centralised, so when they need to be different for a new platform they only have to be changed in one place."""
if __default_compiler==None: raise Exception('No compiler!')
# Work out the various file names - check if we actually need to do anything...
if not isinstance(source, list): source = [source]
source_path = map(lambda s: os.path.join(base, s), source)
library_path = os.path.join(base, __default_compiler.shared_object_filename(name))
if reduce(lambda a,b: a or b, map(lambda s: distutils.dep_util.newer(s, library_path), source_path)):
try:
print 'b'
# Backup the argv variable and create a temporary directory to do all work in...
old_argv = sys.argv[:]
temp_dir = tempfile.mkdtemp()
# Prepare the extension...
sys.argv = ['','build_ext','--build-lib', base, '--build-temp', temp_dir]
comp_path = filter(lambda s: not s.endswith('.h'), source_path)
depends = filter(lambda s: s.endswith('.h'), source_path)
if openCL:
ext = Extension(name, comp_path, include_dirs=['/usr/local/cuda/include', '/opt/AMDAPP/include'], libraries = ['OpenCL'], library_dirs = ['/usr/lib64/nvidia', '/opt/AMDAPP/lib/x86_64'], depends=depends)
else:
ext = Extension(name, comp_path, depends=depends)
# Compile...
setup(name=name, version='1.0.0', ext_modules=[ext])
finally:
# Cleanup the argv variable and the temporary directory...
sys.argv = old_argv
shutil.rmtree(temp_dir, True)
| [
[
1,
0,
0.2031,
0.0156,
0,
0.66,
0,
509,
0,
1,
0,
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509,
0,
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],
[
1,
0,
0.2188,
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79,
0,
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],
[
1,
0,
0.2344,
0.0156,
0,
0.6... | [
"import sys",
"import os.path",
"import tempfile",
"import shutil",
"from distutils.core import setup, Extension",
"import distutils.ccompiler",
"import distutils.dep_util",
"try:\n __default_compiler = distutils.ccompiler.new_compiler()\nexcept:\n __default_compiler = None",
" __default_compiler... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pydoc
import inspect
class DocGen:
"""A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code."""
def __init__(self, name, title = None, summary = None):
"""name is the module name - primarilly used for the file names. title is the title used as applicable - if not provide it just uses the name. summary is an optional line to go below the title."""
if title==None: title = name
if summary==None: summary = title
self.doc = pydoc.HTMLDoc()
self.html = open('%s.html'%name,'w')
self.html.write('<html>\n')
self.html.write('<head>\n')
self.html.write('<title>%s</title>\n'%title)
self.html.write('</head>\n')
self.html.write('<body>\n')
self.html_variables = ''
self.html_functions = ''
self.html_classes = ''
self.wiki = open('%s.wiki'%name,'w')
self.wiki.write('#summary %s\n\n'%summary)
self.wiki.write('= %s= \n\n'%title)
self.wiki_variables = ''
self.wiki_functions = ''
self.wiki_classes = ''
def __del__(self):
if self.html_variables!='':
self.html.write(self.doc.bigsection('Synonyms', '#ffffff', '#8d50ff', self.html_variables))
if self.html_functions!='':
self.html.write(self.doc.bigsection('Functions', '#ffffff', '#eeaa77', self.html_functions))
if self.html_classes!='':
self.html.write(self.doc.bigsection('Classes', '#ffffff', '#ee77aa', self.html_classes))
self.html.write('</body>\n')
self.html.write('</html>\n')
self.html.close()
if self.wiki_variables!='':
self.wiki.write('= Variables =\n\n')
self.wiki.write(self.wiki_variables)
self.wiki.write('\n')
if self.wiki_functions!='':
self.wiki.write('= Functions =\n\n')
self.wiki.write(self.wiki_functions)
self.wiki.write('\n')
if self.wiki_classes!='':
self.wiki.write('= Classes =\n\n')
self.wiki.write(self.wiki_classes)
self.wiki.write('\n')
self.wiki.close()
def addFile(self, fn, title, fls = True):
"""Given a filename and section title adds the contents of said file to the output. Various flags influence how this works."""
html = []
wiki = []
for i, line in enumerate(open(fn,'r').readlines()):
hl = line.replace('\n', '')
if i==0 and fls:
hl = '<strong>' + hl + '</strong>'
for ext in ['py','txt']:
if '.%s - '%ext in hl:
s = hl.split('.%s - '%ext, 1)
hl = '<i>' + s[0] + '.%s</i> - '%ext + s[1]
html.append(hl)
wl = line.strip()
if i==0 and fls:
wl = '*%s*'%wl
for ext in ['py','txt']:
if '.%s - '%ext in wl:
s = wl.split('.%s - '%ext, 1)
wl = '`' + s[0] + '.%s` - '%ext + s[1] + '\n'
wiki.append(wl)
self.html.write(self.doc.bigsection(title, '#ffffff', '#7799ee', '<br/>'.join(html)))
self.wiki.write('== %s ==\n'%title)
self.wiki.write('\n'.join(wiki))
self.wiki.write('----\n\n')
def addVariable(self, var, desc):
"""Adds a variable to the documentation. Given the nature of this you provide it as a pair of strings - one referencing the variable, the other some kind of description of its use etc.."""
self.html_variables += '<strong>%s</strong><br/>'%var
self.html_variables += '%s<br/><br/>\n'%desc
self.wiki_variables += '*`%s`*\n'%var
self.wiki_variables += ' %s\n\n'%desc
def addFunction(self, func):
"""Adds a function to the documentation. You provide the actual function instance."""
self.html_functions += self.doc.docroutine(func).replace(' ',' ')
self.html_functions += '\n'
name = func.__name__
args, varargs, keywords, defaults = inspect.getargspec(func)
doc = inspect.getdoc(func)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
self.wiki_functions += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_functions += ' %s\n\n'%doc
def addClass(self, cls):
"""Adds a class to the documentation. You provide the actual class object."""
self.html_classes += self.doc.docclass(cls).replace(' ',' ')
self.html_classes += '\n'
name = cls.__name__
parents = filter(lambda a: a!=cls, inspect.getmro(cls))
doc = inspect.getdoc(cls)
par_str = ''
if len(parents)!=0:
par_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda p: p.__name__, parents))
self.wiki_classes += '== %s(%s) ==\n'%(name, par_str)
self.wiki_classes += ' %s\n\n'%doc
methods = inspect.getmembers(cls, inspect.ismethod)
def method_key(pair):
if pair[0]=='__init__': return '___'
else: return pair[0]
methods.sort(key=method_key)
for name, method in methods:
if not name.startswith('_%s'%cls.__name__):
args, varargs, keywords, defaults = inspect.getargspec(method)
if defaults==None: defaults = list()
defaults = (len(args)-len(defaults)) * [None] + list(defaults)
arg_str = ''
if len(args)!=0:
arg_str += reduce(lambda a, b: '%s, %s'%(a,b), map(lambda arg, d: arg if d==None else '%s = %s'%(arg,d), args, defaults))
if varargs!=None:
arg_str += ', *%s'%varargs if arg_str!='' else '*%s'%varargs
if keywords!=None:
arg_str += ', **%s'%keywords if arg_str!='' else '**%s'%keywords
def fetch_doc(cls, name):
try:
method = getattr(cls, name)
if method.__doc__!=None: return inspect.getdoc(method)
except: pass
for parent in filter(lambda a: a!=cls, inspect.getmro(cls)):
ret = fetch_doc(parent, name)
if ret!=None: return ret
return None
doc = fetch_doc(cls, name)
self.wiki_classes += '*`%s(%s)`*\n'%(name, arg_str)
self.wiki_classes += ' %s\n\n'%doc
variables = inspect.getmembers(cls, lambda x: isinstance(x, int) or isinstance(x, str) or isinstance(x, float))
for name, var in variables:
if not name.startswith('__'):
self.wiki_classes += '*`%s`* = %s\n\n'%(name, str(var))
| [
[
1,
0,
0.0634,
0.0049,
0,
0.66,
0,
291,
0,
1,
0,
0,
291,
0,
0
],
[
1,
0,
0.0683,
0.0049,
0,
0.66,
0.5,
878,
0,
1,
0,
0,
878,
0,
0
],
[
3,
0,
0.5439,
0.9171,
0,
0.6... | [
"import pydoc",
"import inspect",
"class DocGen:\n \"\"\"A helper class that is used to generate documentation for the system. Outputs multiple formats simultaneously, specifically html for local reading with a webbrowser and the markup used by the wiki system on Google code.\"\"\"\n def __init__(self, name, ... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from ctypes import *
def setProcName(name):
"""Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differing amounts in differing cases."""
# Call the process control function...
libc = cdll.LoadLibrary('libc.so.6')
libc.prctl(15, c_char_p(name), 0, 0, 0)
# Update argv...
charPP = POINTER(POINTER(c_char))
argv = charPP.in_dll(libc,'_dl_argv')
size = libc.strlen(argv[0])
libc.strncpy(argv[0],c_char_p(name),size)
if __name__=='__main__':
# Quick test that it works...
import os
ps1 = 'ps'
ps2 = 'ps -f'
os.system(ps1)
os.system(ps2)
setProcName('wibble_wobble')
os.system(ps1)
os.system(ps2)
| [
[
1,
0,
0.3636,
0.0227,
0,
0.66,
0,
182,
0,
1,
0,
0,
182,
0,
0
],
[
2,
0,
0.5682,
0.25,
0,
0.66,
0.5,
903,
0,
1,
0,
0,
0,
0,
9
],
[
8,
1,
0.4773,
0.0227,
1,
0.44,
... | [
"from ctypes import *",
"def setProcName(name):\n \"\"\"Sets the process name, linux only - useful for those programs where you might want to do a killall, but don't want to slaughter all the other python processes. Note that there are multiple mechanisms, and that the given new name can be shortened by differin... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import types
import marshal
import unittest
def repeat(x):
"""A generator that repeats the input forever - can be used with the mp_map function to give data to a function that is constant."""
while True: yield x
def run_code(code,args):
"""Internal use function that does the work in each process."""
code = marshal.loads(code)
func = types.FunctionType(code, globals(), '_')
return func(*args)
def mp_map(func, *iters, **keywords):
"""A multiprocess version of the map function. Note that func must limit itself to the data provided - if it accesses anything else (globals, locals to its definition.) it will fail. There is a repeat generator provided in this module to work around such issues. Note that, unlike map, this iterates the length of the shortest of inputs, rather than the longest - whilst this makes it not a perfect substitute it makes passing constant argumenmts easier as they can just repeat for infinity."""
if 'pool' in keywords: pool = keywords['pool']
else: pool = mp.Pool()
code = marshal.dumps(func.func_code)
jobs = []
for args in zip(*iters):
jobs.append(pool.apply_async(run_code,(code,args)))
for i in xrange(len(jobs)):
jobs[i] = jobs[i].get()
return jobs
class TestMpMap(unittest.TestCase):
def test_simple1(self):
data = ['a','b','c','d']
def noop(data):
return data
data_noop = mp_map(noop, data)
self.assertEqual(data, data_noop)
def test_simple2(self):
data = [x for x in xrange(1000)]
data_double = mp_map(lambda a: a*2, data)
self.assertEqual(map(lambda a: a*2,data), data_double)
def test_gen(self):
def gen():
for i in xrange(100): yield i
data_double = mp_map(lambda a: a*2, gen())
self.assertEqual(map(lambda a: a*2,gen()), data_double)
def test_repeat(self):
def mult(a,b):
return a*b
data = [x for x in xrange(50,5000,5)]
data_triple = mp_map(mult, data, repeat(3))
self.assertEqual(map(lambda a: a*3,data),data_triple)
def test_none(self):
data = []
data_sqr = mp_map(lambda x: x*x, data)
self.assertEqual([],data_sqr)
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.1456,
0.0097,
0,
0.66,
0,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1553,
0.0097,
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99,
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1,
0,
0,
99,
0,
0
],
[
1,
0,
0.1748,
0.0097,
0,
0.... | [
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import types",
"import marshal",
"import unittest",
"def repeat(x):\n \"\"\"A generator that repeats the input forever - can be used with the mp_map function to give data to a function tha... |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Defines helper functions for accessing numpy arrays...
numpy_util_code = start_cpp() + """
#ifndef NUMPY_UTIL_CODE
#define NUMPY_UTIL_CODE
float & Float1D(PyArrayObject * arr, int index = 0)
{
return *(float*)(arr->data + index*arr->strides[0]);
}
float & Float2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
float & Float3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
return *(float*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
unsigned char & Byte1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index*arr->strides[0]);
}
unsigned char & Byte2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
unsigned char & Byte3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(unsigned char));
return *(unsigned char*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
int & Int1D(PyArrayObject * arr, int index = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index*arr->strides[0]);
}
int & Int2D(PyArrayObject * arr, int index1 = 0, int index2 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1]);
}
int & Int3D(PyArrayObject * arr, int index1 = 0, int index2 = 0, int index3 = 0)
{
//assert(arr->strides[0]==sizeof(int));
return *(int*)(arr->data + index1*arr->strides[0] + index2*arr->strides[1] + index3*arr->strides[2]);
}
#endif
"""
| [
[
1,
0,
0.1923,
0.0128,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.6282,
0.7564,
0,
0.66,
1,
799,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"numpy_util_code = start_cpp() + \"\"\"\n#ifndef NUMPY_UTIL_CODE\n#define NUMPY_UTIL_CODE\n\nfloat & Float1D(PyArrayObject * arr, int index = 0)\n{\n return *(float*)(arr->data + index*arr->strides[0]);\n}"
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 2011 Tom SF Haines
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import rlda
from utils import doc_gen
# Setup...
doc = doc_gen.DocGen('rlda', 'Region Latent Dirichlet Allocation', 'Topic model that learns synonyms')
doc.addFile('readme.txt', 'Overview')
# Functions...
doc.addFunction(rlda.getAlgorithm)
# Classes...
doc.addClass(rlda.Document)
doc.addClass(rlda.Corpus)
doc.addClass(rlda.Params)
| [
[
1,
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0.0256,
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],
[
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1,
0,
0,
970,
0,
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],
[
14,
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0.0256,
0,
... | [
"import rlda",
"from utils import doc_gen",
"doc = doc_gen.DocGen('rlda', 'Region Latent Dirichlet Allocation', 'Topic model that learns synonyms')",
"doc.addFile('readme.txt', 'Overview')",
"doc.addFunction(rlda.getAlgorithm)",
"doc.addClass(rlda.Document)",
"doc.addClass(rlda.Corpus)",
"doc.addClass... |
# -*- coding: utf-8 -*-
# Copyright 2010 Tom SF Haines
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import numpy
import scipy.special
import scipy.weave as weave
import solve_shared as shared
def iniGibbs(st):
# Code...
code = """
// t phase - iterate the state matrix...
for (int w=0;w<Nstate[0];w++)
{
int doc = STATE2(w,0);
int region = ir[STATE2(w,2)];
int word = STATE2(w,3);
// Calculate the probability distribution based on the current state, unnormalised but with a sum so it can be normalised in use...
float sum = 0.0;
for (int t=0;t<NdistT[0];t++)
{
float val = (DT2(doc,t) + alpha) * (WRT3(word,region,t) + beta);
val /= mt[t] + (Nwrt[0]*Nwrt[1]*beta);
sum += val;
distT[t] = val;
}
// Draw a sample from the distribution, update the state accordingly...
int topic = 0;
float total = 0.0;
for (;topic<NdistT[0]-1;topic++)
{
total += distT[topic]/sum;
if (total>randomT[w]) break;
}
STATE2(w,1) = topic;
// Add the sample into the relevant data structures...
DT2(doc,topic) += 1;
WRT3(word,region,topic) += 1;
mt[topic] += 1;
mr[region] += 1;
}
// r phase - iterate the ir matrix...
for (int i=0;i<Nir[0];i++)
{
int region = ir[i];
// Remove all the state rows that use the identifier in question from dt and wrt...
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
//int doc = STATE2(w,0);
int topic = STATE2(w,1);
int word = STATE2(w,3);
//DT2(doc,topic) -= 1;
WRT3(word,region,topic) -= 1;
//mt[topic] -= 1;
mr[region] -= 1;
}
// Calculate the distribution - have to loop the rows...
float sum = float(NdistR[0]);
for (int r=0;r<NdistR[0];r++) distR[r] = 1.0;
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
int topic = STATE2(w,1);
int word = STATE2(w,3);
float nSum = 0.0;
for (int r=0;r<NdistR[0];r++)
{
float val = (distR[r] / sum) * (WRT3(word,r,topic) + gamma);
val /= mr[r] + (Nwrt[0]*Nwrt[2]*gamma);
nSum += val;
distR[r] = val;
}
sum = nSum;
}
// Draw from the distribution, update the ir matrix...
float total = 0.0;
for (region=0;region<NdistR[0]-1;region++)
{
total += distR[region]/sum;
if (total>randomR[i]) break;
}
ir[i] = region;
// Add all the rows that use the identifier in question to dr and wrt...
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
//int doc = STATE2(w,0);
int topic = STATE2(w,1);
int word = STATE2(w,3);
//DT2(doc,topic) += 1;
WRT3(word,region,topic) += 1;
//mt[topic] += 1;
mr[region] += 1;
}
}
"""
# Move relevant variables into the local namespace...
alpha = st.alpha
beta = st.beta
gamma = st.gamma
state = st.state
sIndex = st.sIndex
ir = st.ir
wrt = st.wrt
mt = st.mt
mr = st.mr
dt = st.dt
# Create extra variables as required...
distT = numpy.empty(wrt.shape[2], dtype = numpy.float_)
distR = numpy.empty(wrt.shape[1], dtype = numpy.float_)
randomT = numpy.random.random(state.shape[0])
randomR = numpy.random.random(ir.shape[0])
# Run it...
weave.inline(code, ['alpha', 'beta', 'gamma', 'state', 'sIndex', 'ir', 'wrt', 'mt', 'mr', 'dt', 'distT', 'distR', 'randomT', 'randomR'])
def gibbs(st, iterCount, tCount, rCount, next, randMemUsage = 64*1024*1024):
# Code...
code = """
// Iterate the given number of times...
for (int iter=0;iter<iters;iter++)
{
// t phase - iterate the state matrix...
for (int tp=0;tp<tCount;tp++)
{
for (int w=0;w<Nstate[0];w++)
{
int doc = STATE2(w,0);
int topic = STATE2(w,1);
int region = ir[STATE2(w,2)];
int word = STATE2(w,3);
// Remove the sample from the relevant data structures...
DT2(doc,topic) -= 1;
WRT3(word,region,topic) -= 1;
mt[topic] -= 1;
//mr[region] -= 1;
// Calculate the probability distribution based on the current state, unnormalised but with a sum so it can be normalised in use...
float sum = 0.0;
for (int t=0;t<NdistT[0];t++)
{
float val = (DT2(doc,t) + alpha) * (WRT3(word,region,t) + beta);
val /= mt[t] + (Nwrt[0]*Nwrt[1]*beta);
sum += val;
distT[t] = val;
}
// Draw a sample from the distribution, update the state accordingly...
float total = 0.0;
float limit = RANDOMT3(iter,tp,w) * sum;
for (topic=0;topic<NdistT[0]-1;topic++)
{
total += distT[topic];
if (total>limit) break;
}
STATE2(w,1) = topic;
// Add the sample into the relevant data structures...
DT2(doc,topic) += 1;
WRT3(word,region,topic) += 1;
mt[topic] += 1;
//mr[region] += 1;
}
}
// r phase - iterate the ir matrix...
for (int rp=0;rp<rCount;rp++)
{
for (int i=0;i<Nir[0];i++)
{
int region = ir[i];
// Remove all the state rows that use the identifier in question from dt and wrt...
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
//int doc = STATE2(w,0);
int topic = STATE2(w,1);
int word = STATE2(w,3);
//DT2(doc,topic) -= 1;
WRT3(word,region,topic) -= 1;
//mt[topic] -= 1;
mr[region] -= 1;
}
// Calculate the distribution - have to loop the rows...
float sum = float(NdistR[0]);
for (int r=0;r<NdistR[0];r++) distR[r] = 1.0;
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
int topic = STATE2(w,1);
int word = STATE2(w,3);
float nSum = 0.0;
if ((sum>1e3)||(sum<1e-3)) // Only divide when needed.
{
for (int r=0;r<NdistR[0];r++)
{
float val = (distR[r] / sum) * (WRT3(word,r,topic) + gamma);
val /= mr[r] + (Nwrt[0]*Nwrt[2]*gamma);
nSum += val;
distR[r] = val;
}
}
else
{
for (int r=0;r<NdistR[0];r++)
{
float val = distR[r] * (WRT3(word,r,topic) + gamma);
val /= mr[r] + (Nwrt[0]*Nwrt[2]*gamma);
nSum += val;
distR[r] = val;
}
}
sum = nSum;
}
// Draw from the distribution, update the ir matrix...
float total = 0.0;
float limit = RANDOMR3(iter,rp,i) * sum;
for (region=0;region<NdistR[0]-1;region++)
{
total += distR[region];
if (total>limit) break;
}
ir[i] = region;
// Add all the rows that use the identifier in question to dr and wrt...
for (int w=sIndex[i];w<sIndex[i+1];w++)
{
//int doc = STATE2(w,0);
int topic = STATE2(w,1);
int word = STATE2(w,3);
//DT2(doc,topic) += 1;
WRT3(word,region,topic) += 1;
//mt[topic] += 1;
mr[region] += 1;
}
}
}
}
"""
# Move relevant variables into the local namespace...
alpha = st.alpha
beta = st.beta
gamma = st.gamma
state = st.state
sIndex = st.sIndex
ir = st.ir
wrt = st.wrt
mt = st.mt
mr = st.mr
dt = st.dt
# Create extra variables as required...
distT = numpy.empty(wrt.shape[2], dtype = numpy.float_)
distR = numpy.empty(wrt.shape[1], dtype = numpy.float_)
# Run it...
chunkSize = randMemUsage/(8*(tCount*state.shape[0] + rCount*ir.shape[0])) + 1
while iterCount!=0:
iters = min(chunkSize,iterCount)
iterCount -= iters
randomT = numpy.random.random((iters,tCount,state.shape[0]))
randomR = numpy.random.random((iters,rCount,ir.shape[0]))
weave.inline(code, ['iters', 'tCount', 'rCount', 'alpha', 'beta', 'gamma', 'state', 'sIndex', 'ir', 'wrt', 'mt', 'mr', 'dt', 'distT', 'distR', 'randomT', 'randomR'])
next(iters)
def fitModel(state,params,next):
"""Given a state object generates samples."""
iniGibbs(state)
next()
if params.burnIn>params.lag:
gibbs(state,params.burnIn-params.lag,params.iterT,params.iterR,next)
for i in xrange(params.samples):
gibbs(state,params.lag,params.iterT,params.iterR,next)
state.sample()
next()
def fit(corpus, params, callback = None):
"""Complete fitting function - given a corpus fits a model. params is a Params object. callback if provided should take two numbers - the first is the number of iterations done, the second the number of iterations that need to be done; used to report progress. Note that it will probably not be called for every iteration, as that would be frightfully slow."""
# Class to allow progress to be reported...
class Reporter:
def __init__(self,params,callback):
self.doneIters = 0
self.totalIters = params.runs * (1 + params.burnIn + params.samples + (params.samples-1)*params.lag)
self.callback = callback
if self.callback:
self.callback(self.doneIters,self.totalIters)
def next(self,amount = 1):
self.doneIters += amount
if self.callback:
self.callback(self.doneIters,self.totalIters)
report = Reporter(params,callback)
s = shared.State(corpus)
# Iterate and do each of the runs...
for r in xrange(params.runs):
ss = shared.State(s)
fitModel(ss,params,report.next)
s.absorbClone(ss)
# Extract the final model into the corpus...
s.extractModel(corpus)
def iniGibbsDoc(state, tCount, ir, wrt, alpha):
# Code...
code = """
// Draw a new region assignment for each identifier...
for (int i=0;i<Ni2r[0];i++)
{
float total = 0.0;
for (i2r[i]=0; i2r[i]<(Nir[1]-1); i2r[i]++)
{
total += IR2(i,i2r[i]);
if (total>randomR[i]) break;
}
}
// Iterate the state matrix and reassign topics...
for (int w=0;w<Nstate[0];w++)
{
int region = i2r[STATE2(w,1)];
int word = STATE2(w,2);
// Calculate the probability distribution based on the current state, unnormalised but with a sum so it can be normalised in use...
float sum = 0.0;
for (int t=0;t<Ndist[0];t++)
{
float val = (tCount[t] + alpha) * WRT3(word,region,t);
sum += val;
dist[t] = val;
}
// Draw a sample from the distribution, update the state accordingly...
int topic = 0;
float total = 0.0;
for (;topic<Ndist[0]-1;topic++)
{
total += dist[topic]/sum;
if (total>randomT[w]) break;
}
STATE2(w,0) = topic;
// Add the sample into the documents topic count array...
tCount[topic] += 1;
}
"""
# Create extra variables needed...
i2r = numpy.empty(ir.shape[0], dtype = numpy.int_)
dist = numpy.empty(wrt.shape[2], dtype = numpy.float_)
randomT = numpy.random.random(state.shape[0])
randomR = numpy.random.random(ir.shape[0])
# Run it...
weave.inline(code, ['state', 'tCount', 'ir', 'wrt', 'alpha', 'i2r', 'dist', 'randomT', 'randomR'])
def gibbsDoc(state, tCount, ir, wrt, iters, alpha):
# Code...
code = """
// Iterate...
for (int iter=0;iter<innerIters;iter++)
{
// Draw a new region assignment for each identifier...
for (int i=0;i<Ni2r[0];i++)
{
float total = 0.0;
for (i2r[i]=0; i2r[i]<(Nir[1]-1); i2r[i]++)
{
total += IR2(i,i2r[i]);
if (total>RANDOMR2(iter,i)) break;
}
}
// Iterate the state matrix and reassign topics...
for (int w=0;w<Nstate[0];w++)
{
int topic = STATE2(w,0);
int region = i2r[STATE2(w,1)];
int word = STATE2(w,2);
// Remove the sample from the documents topic count array...
tCount[topic] -= 1;
// Calculate the probability distribution based on the current state, unnormalised but with a sum so it can be normalised in use...
float sum = 0.0;
for (int t=0;t<Ndist[0];t++)
{
float val = (tCount[t] + alpha) * WRT3(word,region,t);
sum += val;
dist[t] = val;
}
// Draw a sample from the distribution, update the state accordingly...
float total = 0.0;
for (topic=0;topic<Ndist[0]-1;topic++)
{
total += dist[topic]/sum;
if (total>RANDOMT2(iter,w)) break;
}
STATE2(w,0) = topic;
// Add the sample into the documents topic count array...
tCount[topic] += 1;
}
}
"""
# Create extra variables needed...
i2r = numpy.empty(ir.shape[0], dtype = numpy.int_)
dist = numpy.empty(wrt.shape[2], dtype = numpy.float_)
chunkSize = (64*1024*1024)/(8*(state.shape[0] + ir.shape[0])) + 1
while iters!=0:
innerIters = min((iters,chunkSize))
iters -= innerIters
randomT = numpy.random.random((innerIters,state.shape[0]))
randomR = numpy.random.random((innerIters,ir.shape[0]))
# Run it, doing all the iterations...
weave.inline(code, ['innerIters', 'state', 'tCount', 'ir', 'wrt', 'alpha', 'i2r', 'dist', 'randomT', 'randomR'])
return i2r
def fitModelDoc(state, tCount, irR, wrtT, wrt, alpha, params, norm):
samples = []
# Construct an array for quickly calculating normalising constants...
if norm<0.0:
logFact = numpy.log(numpy.arange(state.shape[0]+1))
logFact[0] = 0.0
for i in xrange(1,logFact.shape[0]): logFact[i] += logFact[i-1]
# Initialise, do the iterations, collect samples...
iniGibbsDoc(state,tCount,irR,wrtT,alpha)
if params.burnIn>params.lag:
gibbsDoc(state,tCount,irR,wrtT,params.burnIn-params.lag,alpha)
for i in xrange(params.samples):
i2r = gibbsDoc(state,tCount,irR,wrtT,params.lag,alpha)
# Make a sample - need a copy of the topics distribution plus the negative log likelihood of each region given the current assignment...
if norm<0.0:
# Standard multinomial used for per-region negative log likelihood - suffers from regions having lots of samples always being less likelly than regions with a few...
## Marginalise etc. to get log P(w,t|r)...
nll_wrt = wrt.copy() * (tCount.astype(numpy.float_) + alpha)
for r in xrange(nll_wrt.shape[1]):
nll_wrt[:,r,:] /= nll_wrt[:,r,:].sum()
nll_wrt = numpy.log(nll_wrt)
## Sum for all samples...
nlr = numpy.zeros(wrt.shape[1],dtype=numpy.float_)
count_wr = numpy.zeros((wrt.shape[0],wrt.shape[1]),dtype=numpy.int_)
for i in xrange(state.shape[0]):
t = state[i,0]
r = i2r[state[i,1]]
w = state[i,2]
nlr[r] += nll_wrt[w,r,t]
count_wr[w,r] += 1
## Normalise...
for r in xrange(nlr.shape[0]):
nlr[r] += logFact[count_wr[:,r].sum()]
nlr[r] -= logFact[count_wr[:,r]].sum()
## Make *negative* log likelihood...
nlr *= -1.0
else:
# Re-weighted multinomial, which assigns negative log likelihoods to regions that are size agnostic...
## Marginalise etc. to get log P(w,t|r)...
nll_wrt = wrt.copy() * (tCount.astype(numpy.float_) + alpha)
for r in xrange(nll_wrt.shape[1]):
nll_wrt[:,r,:] /= nll_wrt[:,r,:].sum()
nll_wrt = numpy.log(nll_wrt)
## Sum how many samples are in each region...
count_wrt = numpy.zeros(wrt.shape,dtype=numpy.float_)
for i in xrange(state.shape[0]):
t = state[i,0]
r = i2r[state[i,1]]
w = state[i,2]
count_wrt[w,r,t] += 1.0
## Normalise the regions...
for r in xrange(count_wrt.shape[1]):
rSum = count_wrt[:,r,:].sum()
if rSum>0.5: count_wrt[:,r,:] *= norm/rSum
## Sum the per-region multinomial terms...
nlr = numpy.empty(wrt.shape[1],dtype=numpy.float_)
nlr = (nll_wrt*count_wrt).sum(axis=2).sum(axis=0)
## Normalise each region...
nlr += scipy.special.gammaln(norm + 1.0)
nlr -= scipy.special.gammaln(count_wrt + 1.0).sum(axis=2).sum(axis=0)
## Make *negative* log likelihood...
nlr *= -1.0
samples.append((tCount.copy(),nlr,count_wrt.sum(axis=2).sum(axis=0)))
# Return a list of samples...
return samples
def fitDoc(doc, ir, wrt, alpha, params, norm):
"""Given a document, the two parts of a model (ir and wrt) plus an alpha value and params object this Gibbs samples under the assumption that ir and wrt are correct, to determine the documents model, i.e. the multinomial from which topics are drawn for the given document. norm indicates the method used to calculate the region negative log likelihood - negtaive means it uses the standard multinomial distribution, positive means it renormalises the samples to be weighted such that there are norm many samples all together, and then uses an updated multinomial distribution that deals with non-integers. This allows the comparison of regions with very different numbers of samples in."""
# Normalise the relevant rows/columns of ir and wrt to generate the matrices we need...
irR = (ir.T/ir.sum(axis=1)).T
wrtT = wrt.copy()
for t in xrange(wrt.shape[2]): wrtT[:,:,t] /= wrtT[:,:,t].sum()
# Construct the state matrix - each row is (topic,identifier,word)...
state = numpy.empty((doc.getSampleCount(),3),dtype=numpy.uint)
index = 0
words = doc.getWords()
for w in xrange(words.shape[0]):
for c in xrange(words[w,2]):
state[index,0] = 10000000 # Deliberate bad value, so bad initialisation would cause a crash.
state[index,1] = words[w,0]
state[index,2] = words[w,1]
index += 1
assert(index==state.shape[0])
# Do all the runs, collate the samples...
samples = []
for r in xrange(params.getRuns()):
tCount = numpy.zeros(wrt.shape[2],dtype=numpy.uint)
samples += fitModelDoc(state,tCount,irR,wrtT,wrt,alpha,params,norm)
# Merge the samples to get the final model, write it into the given doc object...
model = numpy.zeros(wrt.shape[2],dtype=numpy.float_)
for i,sample in enumerate(samples):
model += ((sample[0].astype(numpy.float_) + alpha) - model) / float(i+1)
doc.setModel(model)
# Combine the region probability estimates, write the region negative log likelihoods to the document...
doc.nllRegion = numpy.zeros(wrt.shape[1],dtype=numpy.float_)
doc.sizeRegion = numpy.zeros(wrt.shape[1],dtype=numpy.float_)
for i,sample in enumerate(samples):
doc.nllRegion += (sample[1] - doc.nllRegion) / float(i+1)
doc.sizeRegion += (sample[2].astype(numpy.float_) - doc.sizeRegion) / float(i+1)
| [
[
1,
0,
0.033,
0.0017,
0,
0.66,
0,
954,
0,
1,
0,
0,
954,
0,
0
],
[
1,
0,
0.0347,
0.0017,
0,
0.66,
0.0909,
253,
0,
1,
0,
0,
253,
0,
0
],
[
1,
0,
0.0363,
0.0017,
0,
0... | [
"import numpy",
"import scipy.special",
"import scipy.weave as weave",
"import solve_shared as shared",
"def iniGibbs(st):\n # Code...\n code = \"\"\"\n // t phase - iterate the state matrix...\n for (int w=0;w<Nstate[0];w++)\n {\n int doc = STATE2(w,0);\n int region = ir[STATE2(w,2)];",
" c... |
# -*- coding: utf-8 -*-
# Copyright 2010 Tom SF Haines
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import time
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
import numpy
import solve_shared as shared
from solve_weave import fitModel, fitModelDoc
def fitModelWrapper(state, params, doneIters, seed):
"""Wrapper around fitModel to make it suitable for multiprocessing."""
numpy.random.seed(seed)
def next(amount = 1):
doneIters.value += amount
fitModel(state,params,next)
return state
def fit(corpus, params, callback = None):
"""Complete fitting function - given a corpus fits a model. params is a Params object from solve-shared. callback if provided should take two numbers - the first is the number of iterations done, the second the number of iterations that need to be done; used to report progress. Note that it will probably not be called for every iteration, as that would be frightfully slow."""
# Create the state from the corpus and a pool of worker proccesses...
s = shared.State(corpus)
pool = mp.Pool()
# Create a value for sub-processes to report back their progress with...
manager = mp.Manager()
doneIters = manager.Value('i',0)
totalIters = params.runs * (1 + params.burnIn + params.samples + (params.samples-1)*params.lag)
# Create a callback for when a job completes...
def onComplete(state):
s.absorbClone(state)
# Create all the jobs...
try:
jobs = []
seeds = numpy.random.random_integers(0,10000000,params.runs)
for r in xrange(params.runs):
jobs.append(pool.apply_async(fitModelWrapper,(shared.State(s),params,doneIters,seeds[r]),callback = onComplete))
finally:
# Close the pool and wait for all the jobs to complete...
pool.close()
while len(jobs)!=0:
if jobs[0].ready():
del jobs[0]
continue
time.sleep(0.01)
if callback!=None:
callback(doneIters.value,totalIters)
pool.join()
# Extract the final model into the corpus...
s.extractModel(corpus)
def fitModelDocWrapper(state,irR,wrtT,wrt,alpha,params,norm,seed):
"""Wrapper around fitModel to make it suitable for multiprocessing."""
numpy.random.seed(seed)
tCount = numpy.zeros(wrt.shape[2],dtype=numpy.uint)
return fitModelDoc(state,tCount,irR,wrtT,wrt,alpha,params,norm)
def fitDoc(doc,ir,wrt,alpha,params,norm):
"""Given a document, the two parts of a model (ir and wrt) plus an alpha value and params object this Gibbs samples under the assumption that ir and wrt are correct, to determine the documents model, i.e. the multinomial from which topics are drawn for the given document."""
irR = (ir.T/ir.sum(axis=1)).T
wrtT = wrt.copy()
for t in xrange(wrt.shape[2]): wrtT[:,:,t] /= wrtT[:,:,t].sum()
# Construct the state matrix - each row is (topic,identifier,word)...
state = numpy.empty((doc.getSampleCount(),3),dtype=numpy.uint)
index = 0
words = doc.getWords()
for w in xrange(words.shape[0]):
for c in xrange(words[w,2]):
state[index,0] = 10000000 # Deliberate bad value, so bad initialisation would cause a crash.
state[index,1] = words[w,0]
state[index,2] = words[w,1]
index += 1
assert(index==state.shape[0])
# Create the process pool, create the callback for when jobs complete...
pool = mp.Pool()
samples = []
def onComplete(samp):
samples.extend(samp)
# Do all the runs, collate the samples...
# Create all the jobs...
try:
jobs = []
seeds = numpy.random.random_integers(0,10000000,params.runs)
for r in xrange(params.runs):
jobs.append(pool.apply_async(fitModelDocWrapper,(state.copy(),irR,wrtT,wrt,alpha,params,norm,seeds[r]),callback = onComplete))
finally:
# Close the pool and wait for all the jobs to complete...
pool.close()
while len(jobs)!=0:
if jobs[0].ready():
del jobs[0]
continue
time.sleep(0.01)
pool.join()
# Merge the samples to get the final model, write it into the given doc object...
model = numpy.zeros(wrt.shape[2],dtype=numpy.float_)
for i,sample in enumerate(samples):
model += ((sample[0].astype(numpy.float_) + alpha) - model) / float(i+1)
doc.setModel(model)
# Combine the region probability estimates, write the region negative log likelihoods to the document...
doc.nllRegion = numpy.zeros(wrt.shape[1],dtype=numpy.float_)
doc.sizeRegion = numpy.zeros(wrt.shape[1],dtype=numpy.float_)
for i,sample in enumerate(samples):
doc.nllRegion += (sample[1] - doc.nllRegion) / float(i+1)
doc.sizeRegion += (sample[2].astype(numpy.float_) - doc.sizeRegion) / float(i+1)
| [
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[
1,
0,
0.1549,
0.007,
0,
0.6... | [
"import time",
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"import numpy",
"import solve_shared as shared",
"from solve_weave import fitModel, fitModelDoc",
"def fitModelWrapper(state, params, doneIters, seed):\n \"\"\"Wrapper arou... |
# -*- coding: utf-8 -*-
__all__ = ['rlda'] | [
[
14,
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0.3333,
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0.66,
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]
] | [
"__all__ = ['rlda']"
] |
# -*- coding: utf-8 -*-
# Copyright 2010 Tom SF Haines
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import numpy
import rlda
class Corpus:
"""Defines a corpus, i.e. the input to the rLDA algorithm. Consists of documents, identifiers and words, plus counts of how many regions and topics a fitted model should have. Has a method to fit a model, after which you can retrieve the models parameters."""
def __init__(self, regions, topics):
"""Construct a corpus - you are required to provide the number of regions and topics to be used by the fitting model."""
# Model size parameters...
self.regions = regions
self.topics = topics
# Create the array of documents, plus support variables...
self.docs = []
self.sampleCount = 0 # Number of samples - summed from all documents.
self.maxIdentNum = -1
self.maxWordNum = -1
# Parameters for the priors...
self.alpha = 1.0
self.beta = 1.0
self.gamma = 1.0
# Multinomial distribution indexed as [word,region,topic] - part of the fitted model, None when not fitted... (Not normalised.)
self.wrt = None
# Second part of model - multinomial distribution indexed as [identifier,region]... (Not normalised.)
self.ir = None
def setRegionTopicCounts(self, regions, topics):
"""Sets the number of regions and topics. Note that this will reset the model, so after doing this all the model variables will be None."""
self.regions = regions
self.topics = topics
self.wrt = None
self.ir = None
# Remove models from documents...
for doc in self.docs:
doc.model = None
def getRegionCount(self):
"""Returns the number of regions that will be used."""
return self.regions
def getTopicCount(self):
"""Returns the number of topics that will be used."""
return self.topics
def setAlpha(self, alpha):
"""Sets the alpha value - 1 is more often than not a good value, and is the default."""
self.alpha = alpha
def setBeta(self, beta):
"""Sets the beta value. Defaults to 1.0."""
self.beta = beta
def setGamma(self, gamma):
"""Sets the gamma value. Defaults to 1.0. One will note that it doesn't actually get used in the formulation, so in a slight abuse it is used in place of beta during the r-step - this provides a touch more control to the user."""
self.gamma = gamma
def getAlpha(self):
"""Returns the current alpha value."""
return self.alpha
def getBeta(self):
"""Returns the current beta value."""
return self.beta
def getGamma(self):
"""Returns the current gamma value."""
return self.gamma
def add(self, doc):
"""Adds a document to the corpus."""
doc.num = len(self.docs)
self.docs.append(doc)
self.sampleCount += doc.getSampleCount()
self.maxIdentNum = max((self.maxIdentNum,doc.getMaxIdentNum()))
self.maxWordNum = max((self.maxWordNum,doc.getMaxWordNum()))
def setIdentWordCounts(self, identCount, wordCount):
"""Because the system autodetects identifiers and words as being the range 0..max where max is the largest number seen it is possible for you to tightly pack words but to want to reserve some past the end. Its also possible for a data set to never contain the last entity, creating problems. This allows you to set the numbers, forcing the issue. Note that setting the number less than actually exist is a guaranteed crash, at a later time."""
self.maxIdentNum = identCount-1
self.maxWordNum = wordCount-1
def getSampleCount(self):
"""Returns the number of identifier-word pairs in all the documents, counting duplicates."""
return self.sampleCount
def getMaxIdentNum(self):
"""Returns the largest ident number it has seen."""
return self.maxIdentNum
def getMaxWordNum(self):
"""Returns the largest word number it has seen."""
return self.maxWordNum
def documentList(self):
"""Returns a list of all documents."""
return self.docs
def fit(self, params = rlda.Params(), callback = None):
"""Fits a model to this Corpus."""
rlda.fit(self, params, callback)
def setModel(self, wrt, ir):
"""Sets the model, in terms of the wrt and ir count matrices. For internal use only really."""
self.wrt = wrt
self.ir = ir
def getIR(self):
"""Returns an unnormalised multinomial distribution indexed by [identifier,region]"""
return self.ir
def getWRT(self):
"""Returns an unnormalised multinomial distribution indexed by [word,region,topic]"""
return self.wrt
| [
[
1,
0,
0.137,
0.0068,
0,
0.66,
0,
954,
0,
1,
0,
0,
954,
0,
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[
1,
0,
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0.0068,
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[
3,
0,
0.589,
0.8288,
0,
0.66,... | [
"import numpy",
"import rlda",
"class Corpus:\n \"\"\"Defines a corpus, i.e. the input to the rLDA algorithm. Consists of documents, identifiers and words, plus counts of how many regions and topics a fitted model should have. Has a method to fit a model, after which you can retrieve the models parameters.\"\"... |
# -*- coding: utf-8 -*-
# Copyright 2010 Tom SF Haines
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import math
import numpy
import rlda
class Document:
"""A document, consists of a list of all the word/identifier pairs in the document."""
def __init__(self, dic):
"""Constructs a document given a dictionary dic[(identifier num, word num)] = count, where identifier num is the natural number that indicates which identifier, and word num the natural number which indicates which word. Count is how many times that identifier-word pair exist in the document. Excluded entries are effectivly assumed to have a count of zero."""
# Create data store with columns (identifier,word,count)...
self.words = numpy.empty((len(dic),3),dtype=numpy.uint)
# Copy in the data...
index = 0
self.sampleCount = 0
self.maxIdentNum = -1
self.maxWordNum = -1
for key, value in dic.iteritems():
self.words[index,0] = key[0]
self.words[index,1] = key[1]
self.words[index,2] = value
self.maxIdentNum = max((self.maxIdentNum,key[0]))
self.maxWordNum = max((self.maxWordNum,key[1]))
self.sampleCount += value
index += 1
# Sorts the data...
self.words = self.words[self.words[:,0].argsort(),:]
# Set the model variable to None, so it can be filled in later. It will ultimatly contain a numpy.array parametrising the multinomial distribution from which topics are drawn...
self.model = None
# Array indexed by regions of their negative log likelihood, plus average region size...
self.nllRegion = None
self.sizeRegion = None
# Document number, stored in here for conveniance. Only assigned when the document is stuffed into a Corpus...
self.num = None
def getDic(self):
"""Returns a dictionary object that represents the document, basically a recreated version of the dictionary handed in to the constructor."""
ret = dict()
for i in xrange(self.words.shape[0]):
ret[(self.words[i,0],self.words[i,1])] = self.words[i,2]
return ret
def getNum(self):
"""Number - just the offset into the array in the corpus where this document is stored, or None if its yet to be stored anywhere."""
return self.num
def getSampleCount(self):
"""Returns the number of identifier-word pairs in the document, counting duplicates."""
return self.sampleCount
def getMaxIdentNum(self):
"""Returns the largest ident number it has seen."""
return self.maxIdentNum
def getMaxWordNum(self):
"""Returns the largest word number it has seen."""
return self.maxWordNum
def getWords(self):
"""Returns an array of all the words in the document, row per word with the columns [identifier,word,count]."""
return self.words
def fit(self, ir, wrt, params = rlda.Params(), alpha = 1.0, norm = 100.0):
"""Given the model provided by a corpus (ir and wrt.) this fits the documents model, independent of the corpus itself. Uses Gibbs sampling as you would expect."""
rlda.fitDoc(self, ir, wrt, alpha, params, norm)
def getModel(self):
"""Returns the vector defining the multinomial from which topics are drawn, P(topic), if it has been calculated, or None if it hasn't."""
return self.model
def setModel(self, model):
"""Sets the model for the document. For internal use only really."""
self.model = model
def probTopic(self, topic):
"""Returns the probability of the document emitting the given topic, where topics are represented by their ident. Do not call if model not calculated."""
assert(self.model!=None)
return self.model[topic]
def regionSize(self, region):
"""Returns the average size of the region, as sampled when sampling the region probabilities."""
return self.sizeRegion[region]
def regionSizeVec(self):
"""Returns a vector of the average size of each region, as sampled when sampling the region probabilities."""
return self.sizeRegion
def negLogLikeRegion(self, region):
"""Returns the negative log likelihood of the words being drawn in the region, sampled and calculated during a call of fit. Do not call if fit has not been run, noting that fitting an entire corpus does not count."""
return self.nllRegion[region]
def negLogLikeRegionVec(self):
"""Returns a vector of negative log likelihhods for each region in the document."""
return self.nllRegion
def negLogLikeRegionAlt(self, region, ir, wrt, sampleCount=64):
"""Returns the negative log likelihood of the given region, alternate calculation - designed to decide if a region is being normal or not. Assuming that the documents model and the given model are all correct, rather than averages of samples from a distribution. This is obviously incorrect, but gives a good enough approximation for most uses. Has to use sampling in part, hence the sampleCount parameter."""
# Normalise ir to get P(r|i)...
ir = ir / ir.sum(axis=0)
# Get a multinomial distribution on the words by fixing the region, multiplying with the distribution on topics and then marginalising topics out. Just for kicks make it the negative log, to save on later calculation...
lmn = (wrt[:,region,:] * self.model).sum(axis=1)
lmn /= lmn.sum()
lmn = -numpy.log(lmn)
# Construct an array for quickly calculating normalising constants...
logInt = numpy.log(numpy.arange(self.sampleCount+1))
logInt[0] = 0.0
for i in xrange(1,logInt.shape[0]): logInt[i] += logInt[i-1]
# Iterate and collect samples - samples are needed to deal with the 'r' distribution on each identifier...
samples = []
for s in xrange(sampleCount):
wordCount = numpy.zeros(wrt.shape[0],dtype=numpy.int_)
# Draw a sample of identifiers that match the region - 1 if accepted, 0 if not...
vim = (ir[:,region]>numpy.random.random(ir.shape[0])).astype(numpy.int_)
# Draw samples using the region mapping...
sample = 0.0
for i in xrange(self.words.shape[0]): # Iterate all identifier/word/count sets...
sample += vim[self.words[i,0]] * self.words[i,2] * lmn[self.words[i,1]]
wordCount[self.words[i,1]] += vim[self.words[i,0]] * self.words[i,2]
# Normalising constant (Tell me this isn't a slick way to write this...)...
sample += logInt[wordCount.sum()]
sample -= logInt[wordCount].sum()
# Store
samples.append(sample)
# Average them in a stable way, return...
offset = min(samples)
res = 0.0
for i,sample in enumerate(samples):
prob = math.exp(offset-sample)
res += (prob-res)/float(i+1)
return offset - math.log(res)
| [
[
1,
0,
0.1156,
0.0058,
0,
0.66,
0,
526,
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[
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0,
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[
1,
0,
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0.0058,
0,
... | [
"import math",
"import numpy",
"import rlda",
"class Document:\n \"\"\"A document, consists of a list of all the word/identifier pairs in the document.\"\"\"\n def __init__(self, dic):\n \"\"\"Constructs a document given a dictionary dic[(identifier num, word num)] = count, where identifier num is the na... |
# Copyright 2012 Tom SF Haines
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
import numpy
from df.df import *
from kde_inc.kde_inc import KDE_INC
from prob_cat import ProbCat
class ClassifyDF_KDE(ProbCat):
"""A classifier that uses decision forests. Includes the use of a density estimate decision forest as a psuedo-prior. The incrimental method used is rather simple, but still works reasonably well. Provides default parameters for the decision forests, but allows access to them for if you want to mess around. Internally the decision forests have two channels - the first is the data, the second the class."""
def __init__(self, prec, cap, treeCount, incAdd = 1, testDims = 3, dimCount = 4, rotCount = 32):
"""prec is the precision matrix for the density estimate done with kernel density estimation; cap is the component cap for said kernel density estimate. treeCount is how many trees to use for the classifying decision forest whilst incAdd is how many to train for each new sample. testDims is the number of dimensions to use for each test, dimCount the number of combinations of dimensions to try for generating each nodes decision and rotCount the number of orientations to try for each nodes test generation."""
# Support structures...
self.cats = dict() # Dictionary from cat to internal indexing number.
self.treeCount = treeCount
self.incAdd = incAdd
# Setup the classification forest...
self.classify = DF()
self.classify.setInc(True)
self.classify.setGoal(Classification(None, 1))
self.classify.setGen(LinearClassifyGen(0, 1, testDims, dimCount, rotCount))
self.classifyData = MatrixGrow()
self.classifyTrain = self.treeCount
# Setup the density estimation kde...
self.density = KDE_INC(prec, cap)
def getClassifier(self):
"""Returns the decision forest used for classification."""
return self.classify
def getDensityEstimate(self):
"""Returns the KDE_INC used for density estimation, as a psuedo-prior."""
return self.density
def priorAdd(self, sample):
self.density.add(sample)
def add(self, sample, cat):
if cat in self.cats:
c = self.cats[cat]
else:
c = len(self.cats)
self.cats[cat] = c
self.classifyData.append(numpy.asarray(sample, dtype=numpy.float32), numpy.asarray(c, dtype=numpy.int32).reshape((1,)))
self.classifyTrain += self.incAdd
def getSampleTotal(self):
return self.classifyData.exemplars()
def getCatTotal(self):
return len(self.cats)
def getCatList(self):
return self.cats.keys()
def getCatCounts(self):
if len(self.cats)==0: return dict()
counts = numpy.bincount(self.classifyData[1,:,0])
ret = dict()
for cat, c in self.cats.iteritems():
ret[cat] = counts[c] if c<counts.shape[0] else 0
return ret
def listMode(self):
return True
def getDataProb(self, sample, state = None):
# Update the model as needed - this will potentially take some time...
if self.classifyTrain!=0 and self.classifyData.exemplars()!=0:
self.classify.learn(min(self.classifyTrain, self.treeCount), self.classifyData, clamp = self.treeCount, mp=False)
self.classifyTrain = 0
# Generate the result and create and return the right output structure...
ret = dict()
if self.classify.size()!=0:
eval_c = self.classify.evaluate(MatrixES(sample), which = 'gen')[0]
for cat, c in self.cats.iteritems():
ret[cat] = eval_c[c] if c<eval_c.shape[0] else 0.0
ret[None] = self.density.prob(sample)
return ret
def getDataProbList(self, sample, state = None):
# Update the models as needed - this will potentially take some time...
if self.classifyTrain!=0 and self.classifyData.exemplars()!=0:
self.classify.learn(min(self.classifyTrain, self.treeCount), self.classifyData, clamp = self.treeCount, mp=False)
self.classifyTrain = 0
# Fetch the required information...
if self.classify.size()!=0:
eval_c = self.classify.evaluate(MatrixES(sample), which = 'gen_list')[0]
else:
return [{None:1.0}]
eval_d = self.density.prob(sample)
# Construct and return the output...
ret = []
for ec in eval_c:
r = {None:eval_d}
for cat, c in self.cats.iteritems():
r[cat] = ec[c] if c<ec.shape[0] else 0.0
ret.append(r)
return ret
| [
[
1,
0,
0.084,
0.0076,
0,
0.66,
0,
954,
0,
1,
0,
0,
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0,
0
],
[
1,
0,
0.0916,
0.0076,
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0,
0
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[
1,
0,
0.0992,
0.0076,
0,
0.6... | [
"import numpy",
"from df.df import *",
"from kde_inc.kde_inc import KDE_INC",
"from prob_cat import ProbCat",
"class ClassifyDF_KDE(ProbCat):\n \"\"\"A classifier that uses decision forests. Includes the use of a density estimate decision forest as a psuedo-prior. The incrimental method used is rather simp... |
# Copyright 2011 Tom SF Haines
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
from dpgmm.dpgmm import DPGMM
from prob_cat import ProbCat
class ClassifyDPGMM(ProbCat):
"""A classifier that uses a Dirichlet process Gaussian mixture model (DPGMM) for each category. Also includes a psuedo-prior in the form of an extra DPGMM that you can feed. Trains them incrimentally, increasing the mixture component cap when that results in an improvement in model performance. Be aware that whilst this is awesome its memory consumption can be fierce, and its a computational hog. Includes the ability to switch off incrimental learning, which can save some time if your not using the model between trainning samples."""
def __init__(self, dims, runs = 1):
"""dims is the number of dimensions the input vectors have, whilst runs is how many starting points to converge from for each variational run. Increasing runs helps to avoid local minima at the expense of computation, but as it often converges well enough with the first attempt, so this is only for the paranoid."""
self.dims = dims
self.runs = runs
self.inc = True
self.prior = DPGMM(self.dims)
self.cats = dict() # Dictionary indexed by category going to the associated DPGMM object.
self.counts = None
def priorAdd(self, sample):
self.prior.add(sample)
if self.inc and self.prior.setPrior():
self.prior = self.prior.multiGrowSolve(self.runs)
def add(self, sample, cat):
if cat not in self.cats: self.cats[cat] = DPGMM(self.dims)
self.cats[cat].add(sample)
if self.inc and self.cats[cat].setPrior():
self.cats[cat] = self.cats[cat].multiGrowSolve(self.runs)
self.counts = None
def setInc(self, state):
"""With a state of False it disables incrimental learning until further notice, with a state of True it reenables it, and makes sure that it is fully up to date by updating everything. Note that when reenabled it assumes that enough data is avaliable, and will crash if not, unlike the incrimental approach that just twiddles its thumbs - in a sense this is safer if you want to avoid bad results."""
self.inc = state
if self.inc:
self.prior.setPrior()
self.prior = self.prior.multiGrowSolve(self.runs)
for cat in self.cats.iterkeys():
self.cats[cat].setPrior()
self.cats[cat] = self.cats[cat].multiGrowSolve(self.runs)
def getSampleTotal(self):
sum(map(lambda mm: mm.size(), self.cats.itervalues()))
def getCatTotal(self):
return len(self.cats)
def getCatList(self):
return self.cats.keys()
def getCatCounts(self):
if self.counts==None:
self.counts = dict()
for cat, mm in self.cats.iteritems():
self.counts[cat] = mm.size()
return self.counts
def getDataProb(self, sample, state = None):
ret = dict()
for cat, mm in self.cats.iteritems(): ret[cat] = mm.prob(sample)
return ret
| [
[
1,
0,
0.1358,
0.0123,
0,
0.66,
0,
752,
0,
1,
0,
0,
752,
0,
0
],
[
1,
0,
0.1605,
0.0123,
0,
0.66,
0.5,
787,
0,
1,
0,
0,
787,
0,
0
],
[
3,
0,
0.6049,
0.8025,
0,
0.6... | [
"from dpgmm.dpgmm import DPGMM",
"from prob_cat import ProbCat",
"class ClassifyDPGMM(ProbCat):\n \"\"\"A classifier that uses a Dirichlet process Gaussian mixture model (DPGMM) for each category. Also includes a psuedo-prior in the form of an extra DPGMM that you can feed. Trains them incrimentally, increasin... |
# Copyright 2011 Tom SF Haines
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
from gcp import gcp
from prob_cat import ProbCat
class ClassifyGaussian(ProbCat):
"""A simplistic Gaussian classifier, that uses a single Gaussian to represent each category/the prior. It is of course fully Bayesian. It keeps a prior that is worth the number of dimensions with the mean and covariance of all the samples provided for its construction. Implimentation is not very efficient, though includes some caching to stop things being too slow."""
def __init__(self, dims):
"""dims is the number of dimensions."""
self.dims = dims
self.prior = gcp.GaussianPrior(self.dims)
self.cats = dict() # Dictionary indexed by categories with a value of the associated GaussianPrior object, without the current prior included - it is merged in as needed.
self.counts = None # Dictionary going to sample counts for each category.
self.cst = None # Dictionary indexed as above, but going to student-t distributions representing the current state. A caching layer that gets invalidated as needed.
def priorAdd(self, sample):
self.prior.addSample(sample)
self.cst = None
def add(self, sample, cat):
if cat not in self.cats: self.cats[cat] = gcp.GaussianPrior(self.dims)
self.cats[cat].addSample(sample)
self.counts = None
self.cst = None
def getSampleTotal(self):
return sum(map(lambda gp: int(gp.getN()), self.cats.itervalues()))
def getCatTotal(self):
return len(self.cats)
def getCatList(self):
return self.cats.keys()
def getCatCounts(self):
if self.counts==None:
self.counts = dict()
for cat, gp in self.cats.iteritems():
self.counts[cat] = int(gp.getN())
return self.counts
def getStudentT(self):
"""Returns a dictionary with categories as keys and StudentT distributions as values, these being the probabilities of samples belonging to each class with the actual draw from the posterior integrated out. Also stores the prior, under a key of None."""
if self.cst==None:
self.cst = dict()
# First prep the prior...
prior = gcp.GaussianPrior(self.prior)
prior.make_safe()
prior.reweight()
self.cst[None] = prior.intProb()
# Then iterate the categories and extract their student-t's, after updating with the prior...
for cat, gp in self.cats.iteritems():
ngp = gcp.GaussianPrior(gp)
ngp.addGP(prior)
self.cst[cat] = ngp.intProb()
return self.cst
def getDataProb(self, sample, state = None):
ret = dict()
for cat, st in self.getStudentT().iteritems(): ret[cat] = st.prob(sample)
return ret
| [
[
1,
0,
0.131,
0.0119,
0,
0.66,
0,
884,
0,
1,
0,
0,
884,
0,
0
],
[
1,
0,
0.1548,
0.0119,
0,
0.66,
0.5,
787,
0,
1,
0,
0,
787,
0,
0
],
[
3,
0,
0.6012,
0.8095,
0,
0.66... | [
"from gcp import gcp",
"from prob_cat import ProbCat",
"class ClassifyGaussian(ProbCat):\n \"\"\"A simplistic Gaussian classifier, that uses a single Gaussian to represent each category/the prior. It is of course fully Bayesian. It keeps a prior that is worth the number of dimensions with the mean and covarian... |
# Copyright 2012 Tom SF Haines
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
import numpy
from df.df import *
from prob_cat import ProbCat
class ClassifyDF(ProbCat):
"""A classifier that uses decision forests. Includes the use of a density estimate decision forest as a psuedo-prior. The incrimental method used is rather simple, but still works reasonably well. Provides default parameters for the decision forests, but allows access to them for if you want to mess around. Internally the decision forests have two channels - the first is the data, the second the class."""
def __init__(self, dims, treeCount, incAdd = 1, testDims = 3, dimCount = 4, rotCount = 32):
"""dims is the number of dimensions in each sample. treeCount is how many trees to use whilst incAdd is how many to train for each new sample. testDims is the number of dimensions to use for each test, dimCount the number of combinations of dimensions to try for generating each nodes decision and rotCount the number of orientations to try for each nodes test generation."""
# Support structures...
self.cats = dict() # Dictionary from cat to internal indexing number.
self.treeCount = treeCount
self.incAdd = incAdd
# Setup the classification forest...
self.classify = DF()
self.classify.setInc(True)
self.classify.setGoal(Classification(None, 1))
self.classify.setGen(LinearClassifyGen(0, 1, testDims, dimCount, rotCount))
self.classifyData = MatrixGrow()
self.classifyTrain = self.treeCount
# Setup the density estimation forest...
self.density = DF()
self.density.setInc(True)
self.density.setGoal(DensityGaussian(dims))
self.density.setGen(LinearMedianGen(0, testDims, dimCount, rotCount))
self.density.getPruner().setMinTrain(48)
self.densityData = MatrixGrow()
self.densityTrain = self.treeCount
def getClassifier(self):
"""Returns the decision forest used for classification."""
return self.classify
def getDensityEstimate(self):
"""Returns the decision forest used for density estimation, as a psuedo-prior."""
return self.density
def setDensityMinTrain(self, count):
self.density.getPruner().setMinTrain(count)
def priorAdd(self, sample):
self.densityData.append(numpy.asarray(sample, dtype=numpy.float32))
self.densityTrain += self.incAdd
def add(self, sample, cat):
if cat in self.cats:
c = self.cats[cat]
else:
c = len(self.cats)
self.cats[cat] = c
self.classifyData.append(numpy.asarray(sample, dtype=numpy.float32), numpy.asarray(c, dtype=numpy.int32).reshape((1,)))
self.classifyTrain += self.incAdd
def getSampleTotal(self):
return self.classifyData.exemplars()
def getCatTotal(self):
return len(self.cats)
def getCatList(self):
return self.cats.keys()
def getCatCounts(self):
if len(self.cats)==0: return dict()
counts = numpy.bincount(self.classifyData[1,:,0])
ret = dict()
for cat, c in self.cats.iteritems():
ret[cat] = counts[c] if c<counts.shape[0] else 0
return ret
def listMode(self):
return True
def getDataProb(self, sample, state = None):
# Update the models as needed - this will potentially take some time...
if self.classifyTrain!=0 and self.classifyData.exemplars()!=0:
self.classify.learn(min(self.classifyTrain, self.treeCount), self.classifyData, clamp = self.treeCount, mp=False)
self.classifyTrain = 0
if self.densityTrain!=0 and self.densityData.exemplars()!=0:
self.density.learn(min(self.densityTrain, self.treeCount), self.densityData, clamp = self.treeCount, mp=False)
self.densityTrain = 0
# Generate the result and create and return the right output structure...
ret = dict()
if self.classify.size()!=0:
eval_c = self.classify.evaluate(MatrixES(sample), which = 'gen')[0]
for cat, c in self.cats.iteritems():
ret[cat] = eval_c[c] if c<eval_c.shape[0] else 0.0
if self.density.size()!=0:
eval_d = self.density.evaluate(MatrixES(sample), which = 'best')[0]
ret[None] = eval_d
else:
ret[None] = 1.0
return ret
def getDataProbList(self, sample, state = None):
# Update the models as needed - this will potentially take some time...
if self.classifyTrain!=0 and self.classifyData.exemplars()!=0:
self.classify.learn(min(self.classifyTrain, self.treeCount), self.classifyData, clamp = self.treeCount, mp=False)
self.classifyTrain = 0
if self.densityTrain!=0 and self.densityData.exemplars()!=0:
self.density.learn(min(self.densityTrain, self.treeCount), self.densityData, clamp = self.treeCount, mp=False)
self.densityTrain = 0
# Fetch the required information...
if self.classify.size()!=0:
eval_c = self.classify.evaluate(MatrixES(sample), which = 'gen_list')[0]
else:
return [{None:1.0}]
if self.density.size()!=0:
eval_d = self.density.evaluate(MatrixES(sample), which = 'best')[0]
else:
eval_d = 1.0
# Construct and return the output...
ret = []
for ec in eval_c:
r = {None:eval_d}
for cat, c in self.cats.iteritems():
r[cat] = ec[c] if c<ec.shape[0] else 0.0
ret.append(r)
return ret
| [
[
1,
0,
0.0705,
0.0064,
0,
0.66,
0,
954,
0,
1,
0,
0,
954,
0,
0
],
[
1,
0,
0.0769,
0.0064,
0,
0.66,
0.3333,
270,
0,
1,
0,
0,
270,
0,
0
],
[
1,
0,
0.0897,
0.0064,
0,
... | [
"import numpy",
"from df.df import *",
"from prob_cat import ProbCat",
"class ClassifyDF(ProbCat):\n \"\"\"A classifier that uses decision forests. Includes the use of a density estimate decision forest as a psuedo-prior. The incrimental method used is rather simple, but still works reasonably well. Provides... |
# Copyright 2011 Tom SF Haines
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
from prob_cat import ProbCat
try: from classify_gaussian import ClassifyGaussian
except: pass
try: from classify_kde import ClassifyKDE
except: pass
try: from classify_bag_kde import ClassifyBagKDE
except: pass
try: from classify_dpgmm import ClassifyDPGMM
except: pass
try: from classify_df import ClassifyDF
except: pass
try: from classify_df_kde import ClassifyDF_KDE
except: pass
| [
[
1,
0,
0.3793,
0.0345,
0,
0.66,
0,
787,
0,
1,
0,
0,
787,
0,
0
],
[
7,
0,
0.4655,
0.069,
0,
0.66,
0.1667,
0,
0,
1,
0,
0,
0,
0,
0
],
[
1,
1,
0.4483,
0.0345,
1,
0.78,... | [
"from prob_cat import ProbCat",
"try: from classify_gaussian import ClassifyGaussian\nexcept: pass",
"try: from classify_gaussian import ClassifyGaussian",
"try: from classify_kde import ClassifyKDE\nexcept: pass",
"try: from classify_kde import ClassifyKDE",
"try: from classify_bag_kde import ClassifyBag... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import time
class ProgBar:
"""Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops."""
def __init__(self, width = 60, onCallback = None):
self.start = time.time()
self.fill = 0
self.width = width
self.onCallback = onCallback
sys.stdout.write(('_'*self.width)+'\n')
sys.stdout.flush()
def __del__(self):
self.end = time.time()
self.__show(self.width)
sys.stdout.write('\nDone - '+str(self.end-self.start)+' seconds\n\n')
sys.stdout.flush()
def callback(self, nDone, nToDo):
"""Hand this into the callback of methods to get a progress bar - it works by users repeatedly calling it to indicate how many units of work they have done (nDone) out of the total number of units required (nToDo)."""
if self.onCallback:
self.onCallback()
n = int(float(self.width)*float(nDone)/float(nToDo))
n = min((n,self.width))
if n>self.fill:
self.__show(n)
def __show(self,n):
sys.stdout.write('|'*(n-self.fill))
sys.stdout.flush()
self.fill = n
| [
[
1,
0,
0.2941,
0.0196,
0,
0.66,
0,
509,
0,
1,
0,
0,
509,
0,
0
],
[
1,
0,
0.3137,
0.0196,
0,
0.66,
0.5,
654,
0,
1,
0,
0,
654,
0,
0
],
[
3,
0,
0.6863,
0.6078,
0,
0.6... | [
"import sys",
"import time",
"class ProgBar:\n \"\"\"Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops.\"\"\"\n def __init__(self, width = 60, onCallback = None):\n self.start = time.time()\n self.fill = 0\n ... |
# -*- coding: utf-8 -*-
# Code copied from http://opencv.willowgarage.com/wiki/PythonInterface - license unknown, but presumed to be at least as liberal as bsd (The license for opencv.).
import cv
import numpy as np
def cv2array(im):
"""Converts a cv array to a numpy array."""
depth2dtype = {
cv.IPL_DEPTH_8U: 'uint8',
cv.IPL_DEPTH_8S: 'int8',
cv.IPL_DEPTH_16U: 'uint16',
cv.IPL_DEPTH_16S: 'int16',
cv.IPL_DEPTH_32S: 'int32',
cv.IPL_DEPTH_32F: 'float32',
cv.IPL_DEPTH_64F: 'float64',
}
arrdtype=im.depth
a = np.fromstring(
im.tostring(),
dtype=depth2dtype[im.depth],
count=im.width*im.height*im.nChannels)
a.shape = (im.height,im.width,im.nChannels)
return a
def array2cv(a):
"""Converts a numpy array to a cv array, if possible."""
dtype2depth = {
'uint8': cv.IPL_DEPTH_8U,
'int8': cv.IPL_DEPTH_8S,
'uint16': cv.IPL_DEPTH_16U,
'int16': cv.IPL_DEPTH_16S,
'int32': cv.IPL_DEPTH_32S,
'float32': cv.IPL_DEPTH_32F,
'float64': cv.IPL_DEPTH_64F,
}
try:
nChannels = a.shape[2]
except:
nChannels = 1
cv_im = cv.CreateImageHeader((a.shape[1],a.shape[0]),
dtype2depth[str(a.dtype)],
nChannels)
cv.SetData(cv_im, a.tostring(),
a.dtype.itemsize*nChannels*a.shape[1])
return cv_im
| [
[
1,
0,
0.1296,
0.0185,
0,
0.66,
0,
492,
0,
1,
0,
0,
492,
0,
0
],
[
1,
0,
0.1481,
0.0185,
0,
0.66,
0.3333,
954,
0,
1,
0,
0,
954,
0,
0
],
[
2,
0,
0.3889,
0.3519,
0,
... | [
"import cv",
"import numpy as np",
"def cv2array(im):\n \"\"\"Converts a cv array to a numpy array.\"\"\"\n depth2dtype = {\n cv.IPL_DEPTH_8U: 'uint8',\n cv.IPL_DEPTH_8S: 'int8',\n cv.IPL_DEPTH_16U: 'uint16',\n cv.IPL_DEPTH_16S: 'int16',\n cv.IPL_DEPTH_32S: 'int32',",
" \... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Some basic matrix operations that come in use...
matrix_code = start_cpp() + """
#ifndef MATRIX_CODE
#define MATRIX_CODE
template <typename T>
inline void MemSwap(T * lhs, T * rhs, int count = 1)
{
while(count!=0)
{
T t = *lhs;
*lhs = *rhs;
*rhs = t;
++lhs;
++rhs;
--count;
}
}
// Calculates the determinant - you give it a pointer to the first elment of the array, and its size (It must be square), plus its stride, which would typically be identical to size, which is the default.
template <typename T>
inline T Determinant(T * pos, int size, int stride = -1)
{
if (stride==-1) stride = size;
if (size==1) return pos[0];
else
{
if (size==2) return pos[0]*pos[stride+1] - pos[1]*pos[stride];
else
{
T ret = 0.0;
for (int i=0; i<size; i++)
{
if (i!=0) MemSwap(&pos[0], &pos[stride*i], size-1);
T sub = Determinant(&pos[stride], size-1, stride) * pos[stride*i + size-1];
if ((i+size)%2) ret += sub;
else ret -= sub;
}
for (int i=1; i<size; i++)
{
MemSwap(&pos[(i-1)*stride], &pos[i*stride], size-1);
}
return ret;
}
}
}
// Inverts a square matrix, will fail on singular and very occasionally on
// non-singular matrices, returns true on success. Uses Gauss-Jordan elimination
// with partial pivoting.
// in is the input matrix, out the output matrix, just be aware that the input matrix is trashed.
// You have to provide its size (Its square, obviously.), and optionally a stride if different from size.
template <typename T>
inline bool Inverse(T * in, T * out, int size, int stride = -1)
{
if (stride==-1) stride = size;
for (int r=0; r<size; r++)
{
for (int c=0; c<size; c++)
{
out[r*stride + c] = (c==r)?1.0:0.0;
}
}
for (int r=0; r<size; r++)
{
// Find largest pivot and swap in, fail if best we can get is 0...
T max = in[r*stride + r];
int index = r;
for (int i=r+1; i<size; i++)
{
if (fabs(in[i*stride + r])>fabs(max))
{
max = in[i*stride + r];
index = i;
}
}
if (index!=r)
{
MemSwap(&in[index*stride], &in[r*stride], size);
MemSwap(&out[index*stride], &out[r*stride], size);
}
if (fabs(max-0.0)<1e-6) return false;
// Divide through the entire row...
max = 1.0/max;
in[r*stride + r] = 1.0;
for (int i=r+1; i<size; i++) in[r*stride + i] *= max;
for (int i=0; i<size; i++) out[r*stride + i] *= max;
// Row subtract to generate 0's in the current column, so it matches an identity matrix...
for (int i=0; i<size; i++)
{
if (i==r) continue;
T factor = in[i*stride + r];
in[i*stride + r] = 0.0;
for (int j=r+1; j<size; j++) in[i*stride + j] -= factor * in[r*stride + j];
for (int j=0; j<size; j++) out[i*stride + j] -= factor * out[r*stride + j];
}
}
return true;
}
#endif
"""
| [
[
1,
0,
0.1,
0.0077,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.5692,
0.8692,
0,
0.66,
1,
974,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"matrix_code = start_cpp() + \"\"\"\n#ifndef MATRIX_CODE\n#define MATRIX_CODE\n\ntemplate <typename T>\ninline void MemSwap(T * lhs, T * rhs, int count = 1)\n{\n while(count!=0)"
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
from utils.numpy_help_cpp import numpy_util_code
# Provides various functions to assist with manipulating python objects from c++ code.
python_obj_code = numpy_util_code + start_cpp() + """
#ifndef PYTHON_OBJ_CODE
#define PYTHON_OBJ_CODE
// Extracts a boolean from an object...
bool GetObjectBoolean(PyObject * obj, const char * name)
{
PyObject * b = PyObject_GetAttrString(obj, name);
bool ret = b!=Py_False;
Py_DECREF(b);
return ret;
}
// Extracts an int from an object...
int GetObjectInt(PyObject * obj, const char * name)
{
PyObject * i = PyObject_GetAttrString(obj, name);
int ret = PyInt_AsLong(i);
Py_DECREF(i);
return ret;
}
// Extracts a float from an object...
float GetObjectFloat(PyObject * obj, const char * name)
{
PyObject * f = PyObject_GetAttrString(obj, name);
float ret = PyFloat_AsDouble(f);
Py_DECREF(f);
return ret;
}
// Extracts an array from an object, returning it as a new[] unsigned char array. You can also pass in a pointer to an int to have the size of the array stored...
unsigned char * GetObjectByte1D(PyObject * obj, const char * name, int * size = 0)
{
PyArrayObject * nao = (PyArrayObject*)PyObject_GetAttrString(obj, name);
unsigned char * ret = new unsigned char[nao->dimensions[0]];
if (size) *size = nao->dimensions[0];
for (int i=0;i<nao->dimensions[0];i++) ret[i] = Byte1D(nao,i);
Py_DECREF(nao);
return ret;
}
// Extracts an array from an object, returning it as a new[] float array. You can also pass in a pointer to an int to have the size of the array stored...
float * GetObjectFloat1D(PyObject * obj, const char * name, int * size = 0)
{
PyArrayObject * nao = (PyArrayObject*)PyObject_GetAttrString(obj, name);
float * ret = new float[nao->dimensions[0]];
if (size) *size = nao->dimensions[0];
for (int i=0;i<nao->dimensions[0];i++) ret[i] = Float1D(nao,i);
Py_DECREF(nao);
return ret;
}
#endif
"""
| [
[
1,
0,
0.1875,
0.0125,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
1,
0,
0.2,
0.0125,
0,
0.66,
0.5,
884,
0,
1,
0,
0,
884,
0,
0
],
[
14,
0,
0.6312,
0.75,
0,
0.66,
... | [
"from utils.start_cpp import start_cpp",
"from utils.numpy_help_cpp import numpy_util_code",
"python_obj_code = numpy_util_code + start_cpp() + \"\"\"\n#ifndef PYTHON_OBJ_CODE\n#define PYTHON_OBJ_CODE\n\n// Extracts a boolean from an object...\nbool GetObjectBoolean(PyObject * obj, const char * name)\n{\n PyObj... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import time
class ProgBar:
"""Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops."""
def __init__(self, width = 60, onCallback = None):
self.start = time.time()
self.fill = 0
self.width = width
self.onCallback = onCallback
sys.stdout.write(('_'*self.width)+'\n')
sys.stdout.flush()
def __del__(self):
self.end = time.time()
self.__show(self.width)
sys.stdout.write('\nDone - '+str(self.end-self.start)+' seconds\n\n')
sys.stdout.flush()
def callback(self, nDone, nToDo):
"""Hand this into the callback of methods to get a progress bar - it works by users repeatedly calling it to indicate how many units of work they have done (nDone) out of the total number of units required (nToDo)."""
if self.onCallback:
self.onCallback()
n = int(float(self.width)*float(nDone)/float(nToDo))
n = min((n,self.width))
if n>self.fill:
self.__show(n)
def __show(self,n):
sys.stdout.write('|'*(n-self.fill))
sys.stdout.flush()
self.fill = n
| [
[
1,
0,
0.2941,
0.0196,
0,
0.66,
0,
509,
0,
1,
0,
0,
509,
0,
0
],
[
1,
0,
0.3137,
0.0196,
0,
0.66,
0.5,
654,
0,
1,
0,
0,
654,
0,
0
],
[
3,
0,
0.6863,
0.6078,
0,
0.6... | [
"import sys",
"import time",
"class ProgBar:\n \"\"\"Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops.\"\"\"\n def __init__(self, width = 60, onCallback = None):\n self.start = time.time()\n self.fill = 0\n ... |
# -*- coding: utf-8 -*-
# Code copied from http://opencv.willowgarage.com/wiki/PythonInterface - license unknown, but presumed to be at least as liberal as bsd (The license for opencv.).
import cv
import numpy as np
def cv2array(im):
"""Converts a cv array to a numpy array."""
depth2dtype = {
cv.IPL_DEPTH_8U: 'uint8',
cv.IPL_DEPTH_8S: 'int8',
cv.IPL_DEPTH_16U: 'uint16',
cv.IPL_DEPTH_16S: 'int16',
cv.IPL_DEPTH_32S: 'int32',
cv.IPL_DEPTH_32F: 'float32',
cv.IPL_DEPTH_64F: 'float64',
}
arrdtype=im.depth
a = np.fromstring(
im.tostring(),
dtype=depth2dtype[im.depth],
count=im.width*im.height*im.nChannels)
a.shape = (im.height,im.width,im.nChannels)
return a
def array2cv(a):
"""Converts a numpy array to a cv array, if possible."""
dtype2depth = {
'uint8': cv.IPL_DEPTH_8U,
'int8': cv.IPL_DEPTH_8S,
'uint16': cv.IPL_DEPTH_16U,
'int16': cv.IPL_DEPTH_16S,
'int32': cv.IPL_DEPTH_32S,
'float32': cv.IPL_DEPTH_32F,
'float64': cv.IPL_DEPTH_64F,
}
try:
nChannels = a.shape[2]
except:
nChannels = 1
cv_im = cv.CreateImageHeader((a.shape[1],a.shape[0]),
dtype2depth[str(a.dtype)],
nChannels)
cv.SetData(cv_im, a.tostring(),
a.dtype.itemsize*nChannels*a.shape[1])
return cv_im
| [
[
1,
0,
0.1296,
0.0185,
0,
0.66,
0,
492,
0,
1,
0,
0,
492,
0,
0
],
[
1,
0,
0.1481,
0.0185,
0,
0.66,
0.3333,
954,
0,
1,
0,
0,
954,
0,
0
],
[
2,
0,
0.3889,
0.3519,
0,
... | [
"import cv",
"import numpy as np",
"def cv2array(im):\n \"\"\"Converts a cv array to a numpy array.\"\"\"\n depth2dtype = {\n cv.IPL_DEPTH_8U: 'uint8',\n cv.IPL_DEPTH_8S: 'int8',\n cv.IPL_DEPTH_16U: 'uint16',\n cv.IPL_DEPTH_16S: 'int16',\n cv.IPL_DEPTH_32S: 'int32',",
" \... |
# Copyright (c) 2012, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
# Some basic matrix operations that come in use...
matrix_code = start_cpp() + """
#ifndef MATRIX_CODE
#define MATRIX_CODE
template <typename T>
inline void MemSwap(T * lhs, T * rhs, int count = 1)
{
while(count!=0)
{
T t = *lhs;
*lhs = *rhs;
*rhs = t;
++lhs;
++rhs;
--count;
}
}
// Calculates the determinant - you give it a pointer to the first elment of the array, and its size (It must be square), plus its stride, which would typically be identical to size, which is the default.
template <typename T>
inline T Determinant(T * pos, int size, int stride = -1)
{
if (stride==-1) stride = size;
if (size==1) return pos[0];
else
{
if (size==2) return pos[0]*pos[stride+1] - pos[1]*pos[stride];
else
{
T ret = 0.0;
for (int i=0; i<size; i++)
{
if (i!=0) MemSwap(&pos[0], &pos[stride*i], size-1);
T sub = Determinant(&pos[stride], size-1, stride) * pos[stride*i + size-1];
if ((i+size)%2) ret += sub;
else ret -= sub;
}
for (int i=1; i<size; i++)
{
MemSwap(&pos[(i-1)*stride], &pos[i*stride], size-1);
}
return ret;
}
}
}
// Inverts a square matrix, will fail on singular and very occasionally on
// non-singular matrices, returns true on success. Uses Gauss-Jordan elimination
// with partial pivoting.
// in is the input matrix, out the output matrix, just be aware that the input matrix is trashed.
// You have to provide its size (Its square, obviously.), and optionally a stride if different from size.
template <typename T>
inline bool Inverse(T * in, T * out, int size, int stride = -1)
{
if (stride==-1) stride = size;
for (int r=0; r<size; r++)
{
for (int c=0; c<size; c++)
{
out[r*stride + c] = (c==r)?1.0:0.0;
}
}
for (int r=0; r<size; r++)
{
// Find largest pivot and swap in, fail if best we can get is 0...
T max = in[r*stride + r];
int index = r;
for (int i=r+1; i<size; i++)
{
if (fabs(in[i*stride + r])>fabs(max))
{
max = in[i*stride + r];
index = i;
}
}
if (index!=r)
{
MemSwap(&in[index*stride], &in[r*stride], size);
MemSwap(&out[index*stride], &out[r*stride], size);
}
if (fabs(max-0.0)<1e-6) return false;
// Divide through the entire row...
max = 1.0/max;
in[r*stride + r] = 1.0;
for (int i=r+1; i<size; i++) in[r*stride + i] *= max;
for (int i=0; i<size; i++) out[r*stride + i] *= max;
// Row subtract to generate 0's in the current column, so it matches an identity matrix...
for (int i=0; i<size; i++)
{
if (i==r) continue;
T factor = in[i*stride + r];
in[i*stride + r] = 0.0;
for (int j=r+1; j<size; j++) in[i*stride + j] -= factor * in[r*stride + j];
for (int j=0; j<size; j++) out[i*stride + j] -= factor * out[r*stride + j];
}
}
return true;
}
#endif
"""
| [
[
1,
0,
0.1,
0.0077,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
14,
0,
0.5692,
0.8692,
0,
0.66,
1,
974,
4,
0,
0,
0,
0,
0,
1
]
] | [
"from utils.start_cpp import start_cpp",
"matrix_code = start_cpp() + \"\"\"\n#ifndef MATRIX_CODE\n#define MATRIX_CODE\n\ntemplate <typename T>\ninline void MemSwap(T * lhs, T * rhs, int count = 1)\n{\n while(count!=0)"
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2011, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from utils.start_cpp import start_cpp
from utils.numpy_help_cpp import numpy_util_code
# Provides various functions to assist with manipulating python objects from c++ code.
python_obj_code = numpy_util_code + start_cpp() + """
#ifndef PYTHON_OBJ_CODE
#define PYTHON_OBJ_CODE
// Extracts a boolean from an object...
bool GetObjectBoolean(PyObject * obj, const char * name)
{
PyObject * b = PyObject_GetAttrString(obj, name);
bool ret = b!=Py_False;
Py_DECREF(b);
return ret;
}
// Extracts an int from an object...
int GetObjectInt(PyObject * obj, const char * name)
{
PyObject * i = PyObject_GetAttrString(obj, name);
int ret = PyInt_AsLong(i);
Py_DECREF(i);
return ret;
}
// Extracts a float from an object...
float GetObjectFloat(PyObject * obj, const char * name)
{
PyObject * f = PyObject_GetAttrString(obj, name);
float ret = PyFloat_AsDouble(f);
Py_DECREF(f);
return ret;
}
// Extracts an array from an object, returning it as a new[] unsigned char array. You can also pass in a pointer to an int to have the size of the array stored...
unsigned char * GetObjectByte1D(PyObject * obj, const char * name, int * size = 0)
{
PyArrayObject * nao = (PyArrayObject*)PyObject_GetAttrString(obj, name);
unsigned char * ret = new unsigned char[nao->dimensions[0]];
if (size) *size = nao->dimensions[0];
for (int i=0;i<nao->dimensions[0];i++) ret[i] = Byte1D(nao,i);
Py_DECREF(nao);
return ret;
}
// Extracts an array from an object, returning it as a new[] float array. You can also pass in a pointer to an int to have the size of the array stored...
float * GetObjectFloat1D(PyObject * obj, const char * name, int * size = 0)
{
PyArrayObject * nao = (PyArrayObject*)PyObject_GetAttrString(obj, name);
float * ret = new float[nao->dimensions[0]];
if (size) *size = nao->dimensions[0];
for (int i=0;i<nao->dimensions[0];i++) ret[i] = Float1D(nao,i);
Py_DECREF(nao);
return ret;
}
#endif
"""
| [
[
1,
0,
0.1875,
0.0125,
0,
0.66,
0,
972,
0,
1,
0,
0,
972,
0,
0
],
[
1,
0,
0.2,
0.0125,
0,
0.66,
0.5,
884,
0,
1,
0,
0,
884,
0,
0
],
[
14,
0,
0.6312,
0.75,
0,
0.66,
... | [
"from utils.start_cpp import start_cpp",
"from utils.numpy_help_cpp import numpy_util_code",
"python_obj_code = numpy_util_code + start_cpp() + \"\"\"\n#ifndef PYTHON_OBJ_CODE\n#define PYTHON_OBJ_CODE\n\n// Extracts a boolean from an object...\nbool GetObjectBoolean(PyObject * obj, const char * name)\n{\n PyObj... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010, Tom SF Haines
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import time
class ProgBar:
"""Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops."""
def __init__(self, width = 60, onCallback = None):
self.start = time.time()
self.fill = 0
self.width = width
self.onCallback = onCallback
sys.stdout.write(('_'*self.width)+'\n')
sys.stdout.flush()
def __del__(self):
self.end = time.time()
self.__show(self.width)
sys.stdout.write('\nDone - '+str(self.end-self.start)+' seconds\n\n')
sys.stdout.flush()
def callback(self, nDone, nToDo):
"""Hand this into the callback of methods to get a progress bar - it works by users repeatedly calling it to indicate how many units of work they have done (nDone) out of the total number of units required (nToDo)."""
if self.onCallback:
self.onCallback()
n = int(float(self.width)*float(nDone)/float(nToDo))
n = min((n,self.width))
if n>self.fill:
self.__show(n)
def __show(self,n):
sys.stdout.write('|'*(n-self.fill))
sys.stdout.flush()
self.fill = n
| [
[
1,
0,
0.2941,
0.0196,
0,
0.66,
0,
509,
0,
1,
0,
0,
509,
0,
0
],
[
1,
0,
0.3137,
0.0196,
0,
0.66,
0.5,
654,
0,
1,
0,
0,
654,
0,
0
],
[
3,
0,
0.6863,
0.6078,
0,
0.6... | [
"import sys",
"import time",
"class ProgBar:\n \"\"\"Simple console progress bar class. Note that object creation and destruction matter, as they indicate when processing starts and when it stops.\"\"\"\n def __init__(self, width = 60, onCallback = None):\n self.start = time.time()\n self.fill = 0\n ... |
# -*- coding: utf-8 -*-
# Code copied from http://opencv.willowgarage.com/wiki/PythonInterface - license unknown, but presumed to be at least as liberal as bsd (The license for opencv.).
import cv
import numpy as np
def cv2array(im):
"""Converts a cv array to a numpy array."""
depth2dtype = {
cv.IPL_DEPTH_8U: 'uint8',
cv.IPL_DEPTH_8S: 'int8',
cv.IPL_DEPTH_16U: 'uint16',
cv.IPL_DEPTH_16S: 'int16',
cv.IPL_DEPTH_32S: 'int32',
cv.IPL_DEPTH_32F: 'float32',
cv.IPL_DEPTH_64F: 'float64',
}
arrdtype=im.depth
a = np.fromstring(
im.tostring(),
dtype=depth2dtype[im.depth],
count=im.width*im.height*im.nChannels)
a.shape = (im.height,im.width,im.nChannels)
return a
def array2cv(a):
"""Converts a numpy array to a cv array, if possible."""
dtype2depth = {
'uint8': cv.IPL_DEPTH_8U,
'int8': cv.IPL_DEPTH_8S,
'uint16': cv.IPL_DEPTH_16U,
'int16': cv.IPL_DEPTH_16S,
'int32': cv.IPL_DEPTH_32S,
'float32': cv.IPL_DEPTH_32F,
'float64': cv.IPL_DEPTH_64F,
}
try:
nChannels = a.shape[2]
except:
nChannels = 1
cv_im = cv.CreateImageHeader((a.shape[1],a.shape[0]),
dtype2depth[str(a.dtype)],
nChannels)
cv.SetData(cv_im, a.tostring(),
a.dtype.itemsize*nChannels*a.shape[1])
return cv_im
| [
[
1,
0,
0.1296,
0.0185,
0,
0.66,
0,
492,
0,
1,
0,
0,
492,
0,
0
],
[
1,
0,
0.1481,
0.0185,
0,
0.66,
0.3333,
954,
0,
1,
0,
0,
954,
0,
0
],
[
2,
0,
0.3889,
0.3519,
0,
... | [
"import cv",
"import numpy as np",
"def cv2array(im):\n \"\"\"Converts a cv array to a numpy array.\"\"\"\n depth2dtype = {\n cv.IPL_DEPTH_8U: 'uint8',\n cv.IPL_DEPTH_8S: 'int8',\n cv.IPL_DEPTH_16U: 'uint16',\n cv.IPL_DEPTH_16S: 'int16',\n cv.IPL_DEPTH_32S: 'int32',",
" \... |
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