code stringlengths 1 1.49M | vector listlengths 0 7.38k | snippet listlengths 0 7.38k |
|---|---|---|
#! /usr/bin/env python
# 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 dp_utils
from utils import doc_gen
# Setup...
doc = doc_gen.DocGen('dp_utils', 'Dirichlet Process Utilities', 'Utility library for handling Dirichlet processes')
doc.addFile('readme.txt', 'Overview')
# Variables...
doc.addVariable('sampling_code', 'Code for sampling from various distributions - uniform, Gaussian, gamma and beta.')
doc.addVariable('conc_code', 'Contains code to sample a concentration parameter and two classes - one to represent the status of a concentration parameter - its prior and its estimated value, and another to do the same thing for when a concentration parameter is shared between multiple Dirichlet processes.')
doc.addVariable('dir_est_code', 'Contains a class for doing maximum likelihood estimation of a Dirichlet distrbution given multinomials that have been drawn from it.')
doc.addVariable('linked_list_code', 'A linked list implimentation - doubly linked, adds data via templated inheritance.')
doc.addVariable('linked_list_gc_code', 'A linked list with reference counting and garabge collection for its entries. Happens to be very good at representing a Dirichlet process.')
doc.addVariable('dp_utils_code', 'Combines all of the code provided in this module into a single variable.')
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"import dp_utils",
"from utils import doc_gen",
"doc = doc_gen.DocGen('dp_utils', 'Dirichlet Process Utilities', 'Utility library for handling Dirichlet processes')",
"doc.addFile('readme.txt', 'Overview')",
"doc.addVariable('sampling_code', 'Code for sampling from various distributions - uniform, Gaussian,... |
# 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 scipy import weave
import unittest
from utils.start_cpp import start_cpp
# Defines code for a doubly linked list - simple but works as expected... (Includes its data via templated inheritance - a little strange, but neat and saves on memory thrashing.)
linked_list_code = start_cpp() + """
// Predefinitions...
template <typename ITEM, typename BODY> class Item;
template <typename ITEM, typename BODY> class List;
// Useful default...
struct Empty {};
// Item for the linked list data structure - simply inherits extra data stuff...
template <typename ITEM = Empty, typename BODY = Empty>
class Item : public ITEM
{
public:
Item(List<ITEM,BODY> * head):head(head),next(this),prev(this) {}
~Item() {}
Item<ITEM,BODY> * Next() {return next;}
Item<ITEM,BODY> * Prev() {return prev;}
List<ITEM,BODY> * GetList() {return head;}
bool Valid() {return static_cast< Item<ITEM,BODY>* >(head)!=this;}
bool IsDummy() {return static_cast< Item<ITEM,BODY>* >(head)==this;}
Item<ITEM,BODY> * PreNew() // Adds a new item before this one.
{
Item<ITEM,BODY> * ret = new Item<ITEM,BODY>(head);
head->size += 1;
ret->prev = this->prev;
ret->next = this;
ret->prev->next = ret;
ret->next->prev = ret;
return ret;
}
Item<ITEM,BODY> * PostNew() // Adds a new item after this one.
{
Item<ITEM,BODY> * ret = new Item<ITEM,BODY>(head);
head->size += 1;
ret->prev = this;
ret->next = this->next;
ret->prev->next = ret;
ret->next->prev = ret;
return ret;
}
void Suicide() // Removes this node from its list and makes it delete itself.
{
head->size -= 1;
next->prev = prev;
prev->next = next;
delete this;
}
protected:
List<ITEM,BODY> * head;
Item<ITEM,BODY> * next;
Item<ITEM,BODY> * prev;
};
// Simple totally inline doubly linked list structure, where
template <typename ITEM = Empty, typename BODY = Empty>
class List : protected Item<ITEM,BODY>
{
public:
List():Item<ITEM,BODY>(this),size(0) {}
~List()
{
while(this->size!=0)
{
this->next->Suicide();
}
}
Item<ITEM,BODY> * Append() {return this->PreNew();}
Item<ITEM,BODY> * Prepend() {return this->PostNew();}
Item<ITEM,BODY> * First() {return this->next;}
Item<ITEM,BODY> * Last() {return this->prev;}
int Size() {return this->size;}
BODY & Body() {return body;}
Item<ITEM,BODY> * Index(int i)
{
Item<ITEM,BODY> * ret = this->next;
while(i>0)
{
ret = ret->next;
i -= 1;
}
return ret;
}
protected:
friend class Item<ITEM,BODY>;
int size;
BODY body;
};
"""
class TestLinkedList(unittest.TestCase):
"""Test code for the linked list."""
def test_compile(self):
code = start_cpp(linked_list) + """
"""
weave.inline(code, support_code=linked_list)
def test_size(self):
code = start_cpp(linked_list) + """
int errors = 0;
List<> wibble;
if (wibble.Size()!=0) errors += 1;
Item<> * it = wibble.Append();
if (wibble.Size()!=1) errors += 1;
it->Suicide();
if (wibble.Size()!=0) errors += 1;
return_val = errors;
"""
errors = weave.inline(code, support_code=linked_list)
self.assertEqual(errors,0)
def test_loop(self):
extra = """
struct Number
{
int num;
};
"""
code = start_cpp(linked_list_code+extra) + """
int errors = 0;
List<Number> wibble;
for (int i=0;i<10;i++)
{
Item<Number> * it = wibble.Append();
it->num = i;
}
if (wibble.Size()!=10) errors += 1;
int i = 0;
for (Item<Number> * targ = wibble.First(); targ->Valid(); targ = targ->Next())
{
if (i!=targ->num) errors += 1;
i += 1;
}
return_val = errors;
"""
errors = weave.inline(code, support_code=linked_list_code+extra)
self.assertEqual(errors,0)
# Code for a linked list with garbage collection - each entry has a reference count, and it also allows access of the reference counts and the total number of reference counts for all entrys. This structure is very useful for modelling a Dirichlet process as a direct consequence, as it has all its properties...
linked_list_gc_code = linked_list_code + start_cpp() + """
// Predefinitions...
template <typename ITEM, typename BODY> class ItemRef;
template <typename ITEM, typename BODY> class ListRef;
// Item for the linked list data structure - simply inherits extra data stuff...
template <typename ITEM = Empty, typename BODY = Empty>
class ItemRef : public ITEM
{
public:
ItemRef(ListRef<ITEM,BODY> * head):head(head),next(this),prev(this),refCount(0) {}
~ItemRef() {}
ItemRef<ITEM,BODY> * Next() {return next;}
ItemRef<ITEM,BODY> * Prev() {return prev;}
ListRef<ITEM,BODY> * GetList() {return head;}
bool Valid() {return static_cast< ItemRef<ITEM,BODY>* >(head)!=this;}
bool IsDummy() {return static_cast< ItemRef<ITEM,BODY>* >(head)==this;}
ItemRef<ITEM,BODY> * PreNew() // Adds a new item before this one.
{
ItemRef<ITEM,BODY> * ret = new ItemRef<ITEM,BODY>(head);
head->size += 1;
ret->prev = this->prev;
ret->next = this;
ret->prev->next = ret;
ret->next->prev = ret;
return ret;
}
ItemRef<ITEM,BODY> * PostNew() // Adds a new item after this one.
{
ItemRef<ITEM,BODY> * ret = new ItemRef<ITEM,BODY>(head);
head->size += 1;
ret->prev = this;
ret->next = this->next;
ret->prev->next = ret;
ret->next->prev = ret;
return ret;
}
void Suicide() // Removes this node from its list and makes it delete itself.
{
head->size -= 1;
head->refTotal -= refCount;
next->prev = prev;
prev->next = next;
delete this;
}
void IncRef(int amount = 1)
{
this->refCount += amount;
head->refTotal += amount;
}
void DecRef(int amount = 1) // If the ref count reaches zero the object will delete itself.
{
this->refCount -= amount;
head->refTotal -= amount;
if (refCount<=0) this->Suicide();
}
int RefCount() {return refCount;}
protected:
ListRef<ITEM,BODY> * head;
ItemRef<ITEM,BODY> * next;
ItemRef<ITEM,BODY> * prev;
int refCount;
};
// Simple totally inline doubly linked list structure...
template <typename ITEM = Empty, typename BODY = Empty>
class ListRef : protected ItemRef<ITEM,BODY>
{
public:
ListRef():ItemRef<ITEM,BODY>(this),size(0),refTotal(0) {}
~ListRef()
{
while(this->size!=0)
{
this->next->Suicide();
}
}
ItemRef<ITEM,BODY> * Append() {return this->PreNew();}
ItemRef<ITEM,BODY> * Prepend() {return this->PostNew();}
ItemRef<ITEM,BODY> * First() {return this->next;}
ItemRef<ITEM,BODY> * Last() {return this->prev;}
int Size() {return this->size;}
int RefTotal() {return this->refTotal;}
BODY & Body() {return body;}
ItemRef<ITEM,BODY> * Index(int i)
{
ItemRef<ITEM,BODY> * ret = this->next;
while(i>0)
{
ret = ret->Next();
i -= 1;
}
return ret;
}
protected:
friend class ItemRef<ITEM,BODY>;
int size;
int refTotal;
BODY body;
};
"""
class TestLinkedListGC(unittest.TestCase):
"""Test code for the linked list with garbage collection."""
def test_compile(self):
code = start_cpp(linked_list_gc) + """
"""
weave.inline(code, support_code=linked_list_gc)
def test_size_gc(self):
code = start_cpp(linked_list_gc_code) + """
int errors = 0;
ListRef<> wibble;
if (wibble.Size()!=0) errors += 1;
ItemRef<> * it = wibble.Append();
if (wibble.Size()!=1) errors += 1;
if (wibble.RefTotal()!=0) errors += 1;
it->IncRef();
it->IncRef();
if (it->RefCount()!=2) errors += 1;
if (wibble.RefTotal()!=2) errors += 1;
it->DecRef();
it->DecRef();
if (wibble.RefTotal()!=0) errors += 1;
if (wibble.Size()!=0) errors += 1;
return_val = errors;
"""
errors = weave.inline(code, support_code=linked_list_gc_code)
self.assertEqual(errors,0)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
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"from scipy import weave",
"import unittest",
"from utils.start_cpp import start_cpp",
"linked_list_code = start_cpp() + \"\"\"\n// Predefinitions...\ntemplate <typename ITEM, typename BODY> class Item;\ntemplate <typename ITEM, typename BODY> class List;\n\n// Useful default...\nstruct Empty {};",
"class T... |
# 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
# Code for sampling from various distributions, including some very specific situations involving Dirichlet processes...
sampling_code = start_cpp() + """
#ifndef SAMPLING_CODE
#define SAMPLING_CODE
#include <stdlib.h>
#include <math.h>
const double gamma_approx = 32.0; // Threshold between the two methods of doing a gamma draw.
// Returns a sample from the natural numbers [0,n)...
int sample_nat(int n)
{
return lrand48()%n;
}
// Returns a sample from [0.0,1.0)...
double sample_uniform()
{
return drand48();
//return double(random())/(double(RAND_MAX)+1.0);
}
// Samples from a normal distribution with a mean of 0 and a standard deviation of 1...
double sample_standard_normal()
{
double u = 1.0-sample_uniform();
double v = 1.0-sample_uniform();
return sqrt(-2.0*log(u)) * cos(2.0*M_PI*v);
}
// Samples from a normal distribution with the given mean and standard deviation...
double sample_normal(double mean, double sd)
{
return mean + sd*sample_standard_normal();
}
// Samples from the Gamma distribution, base version that has no scaling parameter...
/*double sample_gamma(double alpha)
{
// Check if the alpha value is high enough to approximate via a normal distribution...
if (alpha>gamma_approx)
{
while (true)
{
double ret = sample_normal(alpha, sqrt(alpha));
if (ret<0.0) continue;
return ret;
}
}
// First do the integer part of gamma(alpha)...
double ret = 0.0; // 1.0
while (alpha>=1.0)
{
alpha -= 1.0;
//ret /= 1.0 - sample_uniform();
ret -= log(1.0-sample_uniform());
}
//ret = log(ret);
// Now do the remaining fractional part and sum it in - uses rejection sampling...
if (alpha>1e-4)
{
while (true)
{
double u1 = 1.0 - sample_uniform();
double u2 = 1.0 - sample_uniform();
double u3 = 1.0 - sample_uniform();
double frac, point;
if (u1<=(M_E/(M_E+alpha)))
{
frac = pow(u2,1.0/alpha);
point = u3*pow(frac,alpha-1.0);
}
else
{
frac = 1.0 - log(u2);
point = u3*exp(-frac);
}
if (point<=(pow(frac,alpha-1.0)*exp(-frac)))
{
ret += frac;
break;
}
}
}
// Finally return...
return ret;
}*/
// As above, but faster...
double sample_gamma(double alpha)
{
// Check if the alpha value is high enough to approximate via a normal distribution...
if (alpha>gamma_approx)
{
while (true)
{
double ret = sample_normal(alpha, sqrt(alpha));
if (ret<0.0) continue;
return ret;
}
}
// If alpha is one, within tolerance, just use an exponential distribution...
if (fabs(alpha-1.0)<1e-4)
{
return -log(1.0-sample_uniform());
}
if (alpha>1.0)
{
// If alpha is 1 or greater use the Cheng/Feast method...
while (true)
{
double u1 = sample_uniform();
double u2 = sample_uniform();
double v = ((alpha - 1.0/(6.0*alpha))*u1) / ((alpha-1.0)*u2);
double lt2 = 2.0*(u2-1.0)/(alpha-1) + v + 1.0/v;
if (lt2<=2.0)
{
return (alpha-1.0)*v;
}
double lt1 = 2.0*log(u2)/(alpha-1.0) - log(v) + v;
if (lt1<=1.0)
{
return (alpha-1.0)*v;
}
}
}
else
{
// If alpha is less than 1 use a rejection sampling method...
while (true)
{
double u1 = 1.0 - sample_uniform();
double u2 = 1.0 - sample_uniform();
double u3 = 1.0 - sample_uniform();
double frac, point;
if (u1<=(M_E/(M_E+alpha)))
{
frac = pow(u2,1.0/alpha);
point = u3*pow(frac,alpha-1.0);
}
else
{
frac = 1.0 - log(u2);
point = u3*exp(-frac);
}
if (point<=(pow(frac,alpha-1.0)*exp(-frac)))
{
return frac;
break;
}
}
}
}
// Samples from the Gamma distribution, version that has a scaling parameter...
double sample_gamma(double alpha, double beta)
{
return sample_gamma(alpha)/beta;
}
// Samples from the Beta distribution...
double sample_beta(double alpha, double beta)
{
double g1 = sample_gamma(alpha);
double g2 = sample_gamma(beta);
return g1 / (g1 + g2);
}
#endif
"""
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"from utils.start_cpp import start_cpp",
"sampling_code = start_cpp() + \"\"\"\n#ifndef SAMPLING_CODE\n#define SAMPLING_CODE\n\n#include <stdlib.h>\n#include <math.h>\n\nconst double gamma_approx = 32.0; // Threshold between the two methods of doing a gamma draw."
] |
# 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
conc_code = start_cpp() + """
// This funky little function is used to resample the concentration parameter of a Dirichlet process, using the previous parameter - allows this parameter to be Gibbs sampled. Also works for any level of a HDP, due to the limited interactions.
// Parameters are:
// pcp - previous concentration parameter.
// n - number of samples taken from the Dirichlet process
// k - number of discretly different samples, i.e. table count in the Chinese restaurant process.
// prior_alpha - alpha value of the Gamma prior on the concentration parameter.
// prior_beta - beta value of the Gamma prior on the concentration parameter.
double sample_dirichlet_proc_conc(double pcp, double n, double k, double prior_alpha = 1.01, double prior_beta = 0.01)
{
if ((n<(1.0-1e-6))||(k<(2.0-1e-6)))
{
return pcp; // Doesn't work in this case, so just repeat.
}
double nn = sample_beta(pcp+1.0, n);
double log_nn = log(nn);
double f_alpha = prior_alpha + k;
double f_beta = prior_beta - log_nn;
double pi_n_mod = (f_alpha - 1.0) / (n * f_beta);
double r = sample_uniform();
double r_mod = r / (1.0 - r);
if (r_mod>=pi_n_mod) f_alpha -= 1.0;
double ret = sample_gamma(f_alpha, f_beta);
if (ret<1e-3) ret = 1e-3;
return ret;
}
// Class to represent the concentration parameter associated with a DP - consists of the prior and the previous/current value...
struct Conc
{
float alpha; // Parameter for Gamma prior.
float beta; // "
float conc; // Previously sampled concentration value - needed for next sample, and for output/use.
// Resamples the concentration value, assuming only a single DP is using it. n = number of samples from DP, k = number of unique samples, i.e. respectivly RefTotal() and Size() for a ListRef.
void ResampleConc(int n, int k)
{
conc = sample_dirichlet_proc_conc(conc, n, k, alpha, beta);
if (conc<1e-3) conc = 1e-3;
}
};
// This class is the generalisation of the above for when multiple Dirichlet processes share a single concentration parameter - again allows a new concentration parameter to be drawn given the previous one and a Gamma prior, but takes multiple pairs of sample count/discrete sample counts, hence the class interface to allow it to accumilate the relevant information.
class SampleConcDP
{
public:
SampleConcDP():f_alpha(1.0),f_beta(1.0),prev_conc(1.0) {}
~SampleConcDP() {}
// Sets the prior and resets the entire class....
void SetPrior(double alpha, double beta)
{
f_alpha = alpha;
f_beta = beta;
}
// Set the previous concetration parameter - must be called before any DP stats are added...
void SetPrevConc(double prev)
{
prev_conc = prev;
}
// Call once for each DP that is using the concentration parameter...
// (n is the number of samples drawn, k the number of discretly different samples.)
void AddDP(double n, double k)
{
if (k>1.0)
{
double s = 0.0;
if (sample_uniform()>(1.0/(1.0+n/prev_conc))) s = 1.0;
double w = sample_beta(prev_conc+1.0,n);
f_alpha += k - s;
f_beta -= log(w);
}
}
// Once all DP have been added call this to draw a new concentration value...
double Sample()
{
double ret = sample_gamma(f_alpha, f_beta);
if (ret<1e-3) ret = 1e-3;
return ret;
}
private:
double f_alpha;
double f_beta;
double prev_conc;
};
"""
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"from utils.start_cpp import start_cpp",
"conc_code = start_cpp() + \"\"\"\n\n// This funky little function is used to resample the concentration parameter of a Dirichlet process, using the previous parameter - allows this parameter to be Gibbs sampled. Also works for any level of a HDP, due to the limited intera... |
# 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 numpy
class FlagIndexArray:
"""Provides a register for flag lists - given a list of true/false flags gives a unique number for each combination. Requesting the numebr associated with a combination that has already been entered will always return the same number. All flag lists should be the same length and you can obtain a numpy matrix of {0,1} valued unsigned chars where each row corresponds to the flag list with that index. Also has a function to add the flags for each case of only one flag being on, which if called before anything else puts them so the index of the flag and the index of the flag list correspond - a trick required by the rest of the system."""
def __init__(self, length, addSingles = False):
"""Requires the length of the flag lists. Alternativly it can clone another FlagIndexArray. Will call the addSingles method for you if the flag is set."""
if isinstance(length, FlagIndexArray):
self.length = length.length
self.flags = dict(length.flags)
else:
self.length = length
self.flags = dict() # Dictionary from flag lists to integers. Flag lists are represented with tuples of {0,1}.
if addSingles: self.addSingles()
def getLength(self):
"""Return the length that all flag lists should be."""
return self.length
def addSingles(self):
"""Adds the entries where only a single flag is set, with the index of the flag list set to match the index of the flag that is set. Must be called first, before flagIndex is ever called."""
for i in xrange(self.length):
t = tuple([0]*i + [1] + [0]*(self.length-(i+1)))
self.flags[t] = i
def flagIndex(self, flags, create = True):
"""Given a flag list returns its index - if it has been previously supplied then it will be the same index, otherwise a new one. Can be passed any entity that can be indexed via [] to get the integers {0,1}. Returns a natural. If the create flag is set to False in the event of a previously unseen flag list it will raise an exception instead of assigning it a new natural."""
f = [0]*self.length
for i in xrange(self.length):
if flags[i]!=0: f[i] = 1
f = tuple(f)
if f in self.flags: return self.flags[f]
if create==False: raise Exception('Unrecognised flag list')
index = len(self.flags)
self.flags[f] = index
return index
def addFlagIndexArray(self, fia, remap = None):
"""Given a flag index array this merges its flags into the new flags, returning a dictionary indexed by fia's indices that converts them to the new indices in self. remap is optionally a dictionary converting flag indices in fia to flag indexes in self - remap[fia index] = self index."""
def adjust(fi):
fo = [0]*self.length
for i in xrange(fia.length):
fo[remap[i]] = fi[i]
return tuple(fo)
ret = dict()
for f, index in fia.flags.iteritems():
if remap: f = adjust(f)
ret[index] = self.flagIndex(f)
return ret
def flagCount(self):
"""Returns the number of flag lists that are in the system."""
return len(self.flags)
def getFlagMatrix(self):
"""Returns a 2D numpy array of type numpy.uint8 containing {0,1}, indexed by [flag index,flag entry] - basically all the flags stacked into a single matrix and indexed by the entries returned by flagIndex. Often refered to as a 'flag index array' (fia)."""
ret = numpy.zeros((len(self.flags),self.length), dtype=numpy.uint8)
for flags,row in self.flags.iteritems():
for col in xrange(self.length):
if flags[col]!=0: ret[row,col] = 1
return ret
| [
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0.0119,
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0.66,
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0,
954,
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],
[
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0.631,
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],
[
8,
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0.2738,
0.0119,
1,
0.33,
... | [
"import numpy",
"class FlagIndexArray:\n \"\"\"Provides a register for flag lists - given a list of true/false flags gives a unique number for each combination. Requesting the numebr associated with a combination that has already been entered will always return the same number. All flag lists should be the same ... |
#! /usr/bin/env python
# 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 ddhdp
from utils import doc_gen
# Setup...
doc = doc_gen.DocGen('ddhdp', 'Delta-Dual Hierarchical Dirichlet Processes', 'Semi-supervised topic model, with clustering')
doc.addFile('readme.txt', 'Overview')
# Functions...
doc.addFunction(ddhdp.getAlgorithm)
# Classes...
doc.addClass(ddhdp.PriorConcDP)
doc.addClass(ddhdp.Params)
doc.addClass(ddhdp.Document)
doc.addClass(ddhdp.Corpus)
doc.addClass(ddhdp.DocSample)
doc.addClass(ddhdp.Sample)
doc.addClass(ddhdp.Model)
doc.addClass(ddhdp.DocModel)
| [
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[
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... | [
"import ddhdp",
"from utils import doc_gen",
"doc = doc_gen.DocGen('ddhdp', 'Delta-Dual Hierarchical Dirichlet Processes', 'Semi-supervised topic model, with clustering')",
"doc.addFile('readme.txt', 'Overview')",
"doc.addFunction(ddhdp.getAlgorithm)",
"doc.addClass(ddhdp.PriorConcDP)",
"doc.addClass(dd... |
# 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 unittest
import math
from params import Params
from solve_shared import State
from model import DocModel
from utils.start_cpp import start_cpp
from ds_link_cpp import ds_link_code
from scipy import weave
# Shared code used to Gibbs sample the model - provides operations used repeatedly by the sampling code. Note that this contains all the heavy code used by the system - the rest is basically just loops. Additionally the data structure code is prepended to this, so this is the only shared code...
shared_code = ds_link_code + start_cpp() + """
#include <sys/time.h>
// Code for resampling a documents cluster assignment...
void ResampleDocumentCluster(State & state, Document & doc)
{
// If the document does not currently have a cluster then create one for it - let 'em cluster in non-initialisation iterations...
if (doc.GetCluster()==0)
{
ItemRef<Cluster,Conc> * newC = state.clusters.Append();
newC->Body().alpha = state.rho.alpha;
newC->Body().beta = state.rho.beta;
newC->Body().conc = state.rho.conc;
float * bmn = new float[state.behCount];
float bmnDiv = 0.0;
for (int b=0;b<state.behCount;b++)
{
bmn[b] = state.phi[b];
bmnDiv += state.phi[b];
}
for (int b=0;b<state.behCount;b++) bmn[b] /= bmnDiv;
newC->SetBMN(bmn);
doc.SetCluster(newC);
return;
}
// Fill probAux of the topics with the counts of how many of each topic exist in the document whilst at the same time detaching the cluster instances from the document instances...
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->probAux = 0.0;
topic = topic->Next();
}
}
int normalDocInst = 0;
{
ItemRef<DocInst,Conc> * docInst = doc.First();
while (docInst->Valid())
{
docInst->topic = docInst->GetClusterInst()->GetTopic();
if (docInst->topic->beh==0) // Only need to redo the normal ones, as that is all resampling the cluster affects.
{
docInst->topic->IncRef(); // Could be that this is the last (indirect) reference to the topic, and the next line could delete it - would be bad.
docInst->SetClusterInst(0);
docInst->topic->probAux += 1.0;
normalDocInst += 1;
}
docInst = docInst->Next();
}
}
// Detach the document from its current cluster...
doc.SetCluster(0);
// Work out the log probabilities of assigning one of the known clusters to the document - store them in the cluster prob values. Uses the topic prob values as intermediates, for the probability of drawing each topic from the cluster...
float maxLogProb = -1e100;
{
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
// We need the probability of drawing each topic from the cluster, which we write into the prob variable of the topics...
// Zero out the prob values of the topics...
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->prob = 0.0;
topic = topic->Next();
}
}
// Count how many times each topic has been drawn from the cluster, storing in the topic prob values...
{
ItemRef<ClusterInst,Conc> * cluInst = cluster->First();
while (cluInst->Valid())
{
cluInst->GetTopic()->prob += cluInst->RefCount();
cluInst = cluInst->Next();
}
}
// Normalise whilst adding in the probability of drawing the given topic...
// (There is some cleverness here to account for the extra references to the topics obtained from the document being resampled.)
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->prob += cluster->Body().conc * float(topic->RefCount()-topic->probAux) / (state.topics.RefTotal() - normalDocInst + state.topics.Body().conc);
topic->prob /= cluster->RefTotal() + cluster->Body().conc;
topic = topic->Next();
}
}
// Now calculate the log probability of the cluster - involves a loop over the topics plus the inclusion of the probability of drawing this cluster...
cluster->prob = log(cluster->RefCount());
//cluster->prob -= log(state.clusters.RefTotal() + state.clusters.Body().conc);
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
cluster->prob += topic->probAux * log(topic->prob);
topic = topic->Next();
}
}
// Factor in the probability of the clusters distribution over behaviours...
float bmnDiv = cluster->GetBMN()[0];
bool hasAbnorm = false;
for (int b=1;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0)
{
bmnDiv += cluster->GetBMN()[b];
hasAbnorm = true;
}
}
if (hasAbnorm)
{
cluster->prob += lnGamma(doc.SampleCount()+1.0);
for (int b=0;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0)
{
cluster->prob += doc.GetBehCounts()[b] * log(cluster->GetBMN()[b]/bmnDiv);
cluster->prob -= lnGamma(doc.GetBehCounts()[b]+1.0);
}
}
}
if (cluster->prob>maxLogProb) maxLogProb = cluster->prob;
cluster = cluster->Next();
}
}
// Calculate the log probability of assigning a new cluster - involves quite a few terms, including a loop over the topics to get many of them...
float probNew = log(state.clusters.Body().conc);
//probNew -= log(state.clusters.RefTotal() + state.clusters.Body().conc);
probNew += lnGamma(doc.Body().conc);
probNew -= lnGamma(doc.Body().conc + doc.Size());
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
float tProb = float(topic->RefCount()-topic->probAux) / (state.topics.RefTotal() - normalDocInst + state.topics.Body().conc);
float tWeight = doc.Body().conc * tProb;
probNew += lnGamma(tWeight + topic->probAux);
probNew -= lnGamma(tWeight);
topic = topic->Next();
}
}
{
float phiDiv = state.phi[0];
bool hasAbnorm = false;
for (int b=1;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0)
{
phiDiv += state.phi[b];
hasAbnorm = true;
}
}
if (hasAbnorm)
{
probNew += lnGamma(doc.SampleCount()+1.0);
for (int b=0;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0)
{
probNew += doc.GetBehCounts()[b] * log(state.phi[b]/phiDiv);
probNew -= lnGamma(doc.GetBehCounts()[b]+1.0);
}
}
}
}
if (probNew>maxLogProb) maxLogProb = probNew;
// Convert from logs to actual probabilities, with partial normalisation and summing for implicit precise normalisation later...
float sumProb = 0.0;
probNew = exp(probNew - maxLogProb);
sumProb += probNew;
{
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
cluster->prob = exp(cluster->prob - maxLogProb);
sumProb += cluster->prob;
cluster = cluster->Next();
}
}
// Draw which cluster we are to assign; in the event of a new cluster create it...
ItemRef<Cluster,Conc> * selected = 0;
{
float rand = sample_uniform() * sumProb;
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
rand -= cluster->prob;
if (rand<0.0)
{
selected = cluster;
break;
}
cluster = cluster->Next();
}
}
if (selected==0)
{
selected = state.clusters.Append();
selected->Body().alpha = state.rho.alpha;
selected->Body().beta = state.rho.beta;
selected->Body().conc = state.rho.conc;
float * bmn = new float[state.behCount];
float bmnDiv = 0.0;
for (int b=0;b<state.behCount;b++)
{
bmn[b] = state.phi[b];
bmnDiv += state.phi[b];
}
for (int b=0;b<state.behCount;b++) bmn[b] /= bmnDiv;
selected->SetBMN(bmn);
}
// Update the document with its new cluster - consists of setting the documents cluster and updating the document instances to use the new cluster, which requires more sampling...
doc.SetCluster(selected);
ItemRef<DocInst,Conc> * docInst = doc.First();
while(docInst->Valid())
{
if (docInst->topic->beh==0)
{
// Update the cluster instance for this document instance - treat as a draw from the cluster DP with a hard requiremement that we draw an instance with the same topic as currently (What to do here is not given by the dual-hdp paper - this is just one option amung many, choosen for being good for convergance and relativly easy to impliment.)...
// Sum weights from the cluster instances, but only when they are the correct topic; also add in the probability of creating a new cluster instance with the relevant topic...
float probSum = selected->Body().conc * float(docInst->topic->RefCount()) / (state.topics.RefTotal() + state.topics.Body().conc);
{
ItemRef<ClusterInst,Conc> * targ2 = selected->First();
while (targ2->Valid())
{
if (targ2->GetTopic()==docInst->topic) probSum += targ2->RefCount();
targ2 = targ2->Next();
}
}
// Select the relevant one...
ItemRef<ClusterInst,Conc> * relevant = 0;
{
float rand = sample_uniform() * probSum;
ItemRef<ClusterInst,Conc> * cluInst = selected->First();
while (cluInst->Valid())
{
if (cluInst->GetTopic()==docInst->topic)
{
rand -= cluInst->RefCount();
if (rand<0.0)
{
relevant = cluInst;
break;
}
}
cluInst = cluInst->Next();
}
}
if (relevant==0)
{
relevant = selected->Append();
relevant->SetTopic(docInst->topic);
}
// Assign it...
docInst->SetClusterInst(relevant);
// Temporary with topic in is no longer needed - decriment the reference...
docInst->topic->DecRef();
}
docInst = docInst->Next();
}
}
// Code for resampling the topics associated with cluster instances - single function that does them all - designed this way for efficiency reasons...
void ResampleClusterInstances(State & state)
{
// First construct a linked list in each ClusterInst of all samples currently assigned to that ClusterInst, ready for the next bit - quite an involved process due to the multiple levels...
{
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
ItemRef<ClusterInst,Conc> * cluInst = cluster->First();
while (cluInst->Valid())
{
cluInst->first = 0;
cluInst = cluInst->Next();
}
cluster = cluster->Next();
}
}
for (int d=0;d<state.docCount;d++)
{
Document & doc = state.doc[d];
for (int s=0;s<doc.SampleCount();s++)
{
Sample & sam = doc.GetSample(s);
ItemRef<ClusterInst,Conc> * ci = sam.GetDocInst()->GetClusterInst();
sam.next = ci->first; // Note that doing this for abnormal cluster instances makes no sense, but causes no harm either, hence leaving it with the simpler code.
ci->first = &sam;
}
}
// Now iterate all the cluster instances and resample each in turn...
{
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
ItemRef<ClusterInst,Conc> * cluInst = cluster->First();
while (cluInst->Valid())
{
// First decriment the topic word counts for all the using samples and remove its topic...
{
Sample * sam = cluInst->first;
while (sam)
{
ItemRef<Topic,Conc> * topic = sam->GetDocInst()->GetClusterInst()->GetTopic();
topic->wc[sam->GetWord()] -= 1;
topic->wcTotal -= 1;
sam = sam->next;
}
}
cluInst->SetTopic(0);
// Count the number of each word type used by all the children of the cluster instance...
{
for (int w=0;w<state.wordCount;w++) state.tempWord[w] = 0;
Sample * sam = cluInst->first;
while (sam)
{
state.tempWord[sam->GetWord()] += 1;
sam = sam->next;
}
}
// Iterate the topics and calculate the log probability of each, find maximum log probability...
float maxLogProb = -1e100;
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->prob = log(topic->RefCount());
float samDiv = log(topic->wcTotal + state.betaSum);
for (int w=0;w<state.wordCount;w++)
{
if (state.tempWord[w]!=0)
{
topic->prob += state.tempWord[w]*(log(topic->wc[w] + state.beta[w]) - samDiv);
}
}
if (topic->prob>maxLogProb) maxLogProb = topic->prob;
topic = topic->Next();
}
}
// Calculate the log probability of a new topic; maintain maximum...
float probNew = log(state.topics.Body().conc);
{
for (int w=0;w<state.wordCount;w++)
{
if (state.tempWord[w]!=0)
{
probNew += state.tempWord[w]*log(state.beta[w]/state.betaSum);
}
}
}
if (probNew>maxLogProb) maxLogProb = probNew;
// Convert log probabilities to actual probabilities in a numerically safe way, and sum them up for selection...
float probSum = 0.0;
probNew = exp(probNew-maxLogProb);
probSum += probNew;
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->prob = exp(topic->prob-maxLogProb);
probSum += topic->prob;
topic = topic->Next();
}
}
// Select the resampled topic, creating a new one if required...
ItemRef<Topic,Conc> * nt = 0;
float rand = probSum * sample_uniform();
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
rand -= topic->prob;
if (rand<0.0)
{
nt = topic;
break;
}
topic = topic->Next();
}
}
if (nt==0)
{
nt = state.topics.Append();
nt->wc = new int[state.wordCount];
for (int w=0;w<state.wordCount;w++) nt->wc[w] = 0;
nt->wcTotal = 0;
nt->beh = 0;
}
// Finally set its topic and sum back in the topic usage by its using samples...
cluInst->SetTopic(nt);
{
Sample * sam = cluInst->first;
while (sam)
{
ItemRef<Topic,Conc> * topic = sam->GetDocInst()->GetClusterInst()->GetTopic();
topic->wc[sam->GetWord()] += 1;
topic->wcTotal += 1;
sam = sam->next;
}
}
cluInst = cluInst->Next();
}
cluster = cluster->Next();
}
}
}
// Code for resampling a document instance's cluster instance - actually does all document instances for a single document with each call, for efficiency reasons...
void ResampleDocumentInstances(State & state, Document & doc)
{
// Calculate the normaliser for the behaviour multinomial and the log probability of normal behaviour...
float bmnNorm = 0.0;
for (int b=0;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0) bmnNorm += doc.GetCluster()->GetBMN()[b];
}
float logProbNorm = log(doc.GetCluster()->GetBMN()[0]/bmnNorm);
// Construct a linked list in each DocInst of the samples contained within - needed to do the next task efficiently...
{
ItemRef<DocInst,Conc> * docInst = doc.First();
while (docInst->Valid())
{
docInst->first = 0;
docInst = docInst->Next();
}
}
for (int s=0;s<doc.SampleCount();s++)
{
Sample & sam = doc.GetSample(s);
sam.next = sam.GetDocInst()->first;
sam.GetDocInst()->first = &sam;
}
// Now iterate all DocInst in the document, resampling each in turn...
{
ItemRef<DocInst,Conc> * docInst = doc.First();
while (docInst->Valid())
{
// Detach from its cluster instance, removing all topic references at the same time, also, count how many words it has...
{
for (int w=0;w<state.wordCount;w++) state.tempWord[w] = 0;
Sample * sample = docInst->first;
while (sample)
{
ItemRef<Topic,Conc> * topic = sample->GetDocInst()->GetClusterInst()->GetTopic();
topic->wc[sample->GetWord()] -= 1;
state.tempWord[sample->GetWord()] += 1;
topic->wcTotal -= 1;
doc.GetBehCounts()[topic->beh] -= 1;
sample = sample->next;
}
}
docInst->SetClusterInst(0);
// Iterate the topics and determine the log probability of each topic for the samples in probAux and the log probability of drawing a new cluster instance with the given topic in prob. The latter has its max recorded for numerically stable normalisation later...
float maxLogProb = -1e100;
float logTopicNorm = log(state.topics.RefTotal() + state.topics.Body().conc);
float logCluNorm = log(doc.GetCluster()->RefTotal() + doc.GetCluster()->Body().conc);
{
float baseTopicLogProb = logProbNorm + log(doc.GetCluster()->Body().conc) - logCluNorm - logTopicNorm;
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->probAux = 0.0;
float samDiv = log(topic->wcTotal + state.betaSum);
for (int w=0;w<state.wordCount;w++)
{
if (state.tempWord[w]!=0)
{
topic->probAux += state.tempWord[w]*(logf(topic->wc[w] + state.beta[w]) - samDiv); // Don't normalise for arbitrary order, as same constant for all.
}
}
topic->prob = baseTopicLogProb + logf(topic->RefCount()) + topic->probAux;
if (topic->prob>maxLogProb) maxLogProb = topic->prob;
topic = topic->Next();
}
}
// Iterate the cluster instances and calculate their log probabilities, maintaining knowledge of the maximum...
{
ItemRef<ClusterInst,Conc> * cluInst = doc.GetCluster()->First();
while (cluInst->Valid())
{
cluInst->prob = logProbNorm + logf(cluInst->RefCount()) - logCluNorm + cluInst->GetTopic()->probAux;
if (cluInst->prob>maxLogProb) maxLogProb = cluInst->prob;
cluInst = cluInst->Next();
}
}
// Calculate the log probability of a new topic and new cluster instance, factor into the maximum...
float probAllNew = logProbNorm + log(doc.GetCluster()->Body().conc) - logCluNorm + log(state.topics.Body().conc) - logTopicNorm;
{
for (int w=0;w<state.wordCount;w++)
{
if (state.tempWord[w]!=0)
{
probAllNew += state.tempWord[w]*logf(state.beta[w]/state.betaSum); // Ignore ordering irrelevance normalisation, as done throughout due to being constant.
}
}
}
if (probAllNew>maxLogProb) maxLogProb = probAllNew;
// Do all the abnormal topics - same idea as previously...
{
ItemRef<Topic,Conc> * topic = state.behTopics.First()->Next();
while (topic->Valid())
{
if (doc.GetBehFlags()[topic->beh]!=0)
{
topic->prob = log(doc.GetCluster()->GetBMN()[topic->beh]/bmnNorm);
float samDiv = log(topic->wcTotal + state.betaSum);
for (int w=0;w<state.wordCount;w++)
{
if (state.tempWord[w]!=0)
{
topic->prob += state.tempWord[w]*(logf(topic->wc[w] + state.beta[w]) - samDiv); // Don't normalise for arbitrary ordering, as same constant for all.
}
}
if (topic->prob>maxLogProb) maxLogProb = topic->prob;
}
topic = topic->Next();
}
}
// Use the maximum log probability to convert all values to normal probabilities in a numerically safe way, storing a sum ready for drawing from the various options...
float probSum = 0.0;
probAllNew = exp(probAllNew-maxLogProb);
probSum += probAllNew;
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
topic->prob = exp(topic->prob-maxLogProb);
probSum += topic->prob;
topic = topic->Next();
}
}
{
ItemRef<ClusterInst,Conc> * cluInst = doc.GetCluster()->First();
while (cluInst->Valid())
{
cluInst->prob = exp(cluInst->prob-maxLogProb);
probSum += cluInst->prob;
cluInst = cluInst->Next();
}
}
{
ItemRef<Topic,Conc> * topic = state.behTopics.First()->Next();
while (topic->Valid())
{
if (doc.GetBehFlags()[topic->beh]!=0)
{
topic->prob = exp(topic->prob-maxLogProb);
probSum += topic->prob;
}
topic = topic->Next();
}
}
// Draw the new cluster instance - can involve creating a new one and even creating a new topic...
ItemRef<ClusterInst,Conc> * nci = 0;
float rand = sample_uniform() * probSum;
// Is it a normal cluster instance that already exists?..
{
ItemRef<ClusterInst,Conc> * cluInst = doc.GetCluster()->First();
while (cluInst->Valid())
{
rand -= cluInst->prob;
if (rand<0.0)
{
nci = cluInst;
break;
}
cluInst = cluInst->Next();
}
}
// Is it an abnormal topic?..
if (nci==0)
{
ItemRef<ClusterInst,Conc> * cluInst = state.behCluInsts.First()->Next();
while (cluInst->Valid())
{
if (doc.GetBehFlags()[cluInst->GetTopic()->beh]!=0)
{
rand -= cluInst->GetTopic()->prob;
if (rand<0.0)
{
nci = cluInst;
break;
}
}
cluInst = cluInst->Next();
}
}
// Is it a new cluster instance?..
if (nci==0)
{
nci = doc.GetCluster()->Append();
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
rand -= topic->prob;
if (rand<0.0)
{
nci->SetTopic(topic);
break;
}
topic = topic->Next();
}
}
// Is it a new topic as well as a new cluster instance?..
if (nci->GetTopic()==0)
{
ItemRef<Topic,Conc> * nt = state.topics.Append();
nt->wc = new int[state.wordCount];
for (int w=0;w<state.wordCount;w++) nt->wc[w] = 0;
nt->wcTotal = 0;
nt->beh = 0;
nci->SetTopic(nt);
}
// Reattach its resampled cluster instance, and incriment the topic word counts...
docInst->SetClusterInst(nci);
{
Sample * sample = docInst->first;
while (sample)
{
ItemRef<Topic,Conc> * topic = sample->GetDocInst()->GetClusterInst()->GetTopic();
topic->wc[sample->GetWord()] += 1;
topic->wcTotal += 1;
doc.GetBehCounts()[topic->beh] += 1;
sample = sample->next;
}
}
docInst = docInst->Next();
}
}
}
// Helper for below, seperated out as required seperate for the left to right algorithm later on. Returns the sum of all the probabilities of the options for the sample just calculated, and leaves correct values in all the relevant ->prob variables...
float CalcSampleProb(State & state, Document & doc, Sample & sam)
{
float pSum = 0.0;
// Calculate the normalising constant for the associated clusters behaviour multinomial given the documents behaviour flags...
float bmvDiv = 0.0;
for (int b=0;b<state.behCount;b++)
{
if (doc.GetBehFlags()[b]!=0) bmvDiv += doc.GetCluster()->GetBMN()[b];
}
// Probability of going for something normal...
float probNormal = doc.GetCluster()->GetBMN()[0] / bmvDiv;
// Calculate the probabilities of various 'new' events...
float probNewDocInst = doc.Body().conc / (doc.RefTotal() + doc.Body().conc);
float probNewCluInst = probNewDocInst * doc.GetCluster()->Body().conc / (doc.GetCluster()->RefTotal() + doc.GetCluster()->Body().conc);
float probNewTopic = probNewCluInst * state.topics.Body().conc / (state.topics.RefTotal() + state.topics.Body().conc);
// The probability of a new topic...
pSum += probNormal * probNewTopic * state.beta[sam.GetWord()] / state.betaSum;
// The topics - keep the probabilities of drawing the word in question from the topic in the aux variables, to save computation in the following steps...
float betaWeight = state.beta[sam.GetWord()];
{
ItemRef<Topic,Conc> * topic = state.topics.First();
float base = probNormal * probNewCluInst / (state.topics.RefTotal() + state.topics.Body().conc);
while (topic->Valid())
{
topic->probAux = (topic->wc[sam.GetWord()] + betaWeight) / (topic->wcTotal + state.betaSum);
topic->prob = topic->probAux * topic->RefCount() * base;
pSum += topic->prob;
topic = topic->Next();
}
}
// The abnormal topics...
{
ItemRef<Topic,Conc> * topic = state.behTopics.First()->Next();
while (topic->Valid())
{
if (doc.GetBehFlags()[topic->beh]!=0)
{
topic->probAux = (topic->wc[sam.GetWord()] + betaWeight) / (topic->wcTotal + state.betaSum);
float probBeh = doc.GetCluster()->GetBMN()[topic->beh] / bmvDiv;
topic->prob = probBeh * probNewDocInst * topic->probAux;
pSum += topic->prob;
}
topic = topic->Next();
}
}
// The cluster instances...
{
ItemRef<ClusterInst,Conc> * cluInst = doc.GetCluster()->First();
float base = probNormal * probNewDocInst / (doc.GetCluster()->RefTotal() + doc.GetCluster()->Body().conc);
while (cluInst->Valid())
{
cluInst->prob = cluInst->GetTopic()->probAux * cluInst->RefCount() * base;
pSum += cluInst->prob;
cluInst = cluInst->Next();
}
}
// The document instances...
{
ItemRef<DocInst,Conc> * docInst = doc.First();
float divisor = doc.RefTotal() + doc.Body().conc;
while (docInst->Valid())
{
docInst->prob = docInst->GetClusterInst()->GetTopic()->probAux * docInst->RefCount() / divisor;
pSum += docInst->prob;
docInst = docInst->Next();
}
}
return pSum;
}
// Code for resampling a samples topic instance assignment...
// (Everything must be assigned - no null pointers on the chain from sample to topic.)
// (You can seperatly call CalcSampleProb and put its return value in pSum if you want, though that requires that you really, really know what your doing.)
void ResampleSample(State & state, Document & doc, Sample & sam, float pSum = -1.0)
{
// Remove the samples current assignment...
if (sam.GetDocInst())
{
int beh = sam.GetDocInst()->GetClusterInst()->GetTopic()->beh;
doc.GetBehCounts()[beh] -= 1;
sam.SetDocInst(0);
}
// Assign probabilities to the various possibilities - there are temporary variables in the data structure to make this elegant. Sum up the total probability ready for the sampling phase. In all cases an entity is assigned the probability of using that entity with everything below it being created from scratch...
if (pSum<0.0)
{
pSum = CalcSampleProb(state, doc, sam);
}
// Now draw from the distribution and assign the result, creating new entities as required. The checking is done in order of (typically) largest to smallest, to maximise the chance of an early bail out...
// Draw the random uniform, scaled by the pSum - we will repeatedly subtract from this random variable for each item - when it becomes negative we have found the item to draw...
float rand = sample_uniform() * pSum;
// Check the document instances...
{
ItemRef<DocInst,Conc> * docInst = doc.First();
while (docInst->Valid())
{
rand -= docInst->prob;
if (rand<0.0)
{
// A document instance has been selected - simplest reassignment case...
sam.SetDocInst(docInst);
int beh = sam.GetDocInst()->GetClusterInst()->GetTopic()->beh;
doc.GetBehCounts()[beh] += 1;
return;
}
docInst = docInst->Next();
}
}
// Check the cluster instances - would involve a new document instance...
{
ItemRef<ClusterInst,Conc> * cluInst = doc.GetCluster()->First();
while (cluInst->Valid())
{
rand -= cluInst->prob;
if (rand<0.0)
{
// A cluster instance has been selected - need to create a new document instance...
ItemRef<DocInst,Conc> * ndi = doc.Append();
ndi->SetClusterInst(cluInst);
sam.SetDocInst(ndi);
doc.GetBehCounts()[0] += 1;
return;
}
cluInst = cluInst->Next();
}
}
// Check the abnormal topics...
{
ItemRef<ClusterInst,Conc> * cluInst = state.behCluInsts.First()->Next();
while (cluInst->Valid())
{
if (doc.GetBehFlags()[cluInst->GetTopic()->beh]!=0)
{
rand -= cluInst->GetTopic()->prob;
if (rand<0.0)
{
// An abnormal topic has been selected - need a new document instance...
ItemRef<DocInst,Conc> * ndi = doc.Append();
ndi->SetClusterInst(cluInst);
sam.SetDocInst(ndi);
doc.GetBehCounts()[cluInst->GetTopic()->beh] += 1;
return;
}
}
cluInst = cluInst->Next();
}
}
// Check the topics - would involve both a new cluster and document instance...
{
ItemRef<Topic,Conc> * topic = state.topics.First();
while (topic->Valid())
{
rand -= topic->prob;
if (rand<0.0)
{
// A topic has been selected - need a new cluster and a new document instance...
ItemRef<ClusterInst,Conc> * nci = doc.GetCluster()->Append();
nci->SetTopic(topic);
ItemRef<DocInst,Conc> * ndi = doc.Append();
ndi->SetClusterInst(nci);
sam.SetDocInst(ndi);
doc.GetBehCounts()[0] += 1;
return;
}
topic = topic->Next();
}
}
// If we have got this far then its a new topic, with a new cluster and document instance as well...
ItemRef<Topic,Conc> * nt = state.topics.Append();
nt->wc = new int[state.wordCount];
for (int w=0;w<state.wordCount;w++) nt->wc[w] = 0;
nt->wcTotal = 0;
nt->beh = 0;
ItemRef<ClusterInst,Conc> * nci = doc.GetCluster()->Append();
nci->SetTopic(nt);
ItemRef<DocInst,Conc> * ndi = doc.Append();
ndi->SetClusterInst(nci);
sam.SetDocInst(ndi);
doc.GetBehCounts()[0] += 1;
}
// Code for resampling all the concentration parameters - just have to iterate through and call all the resampling methods...
void ResampleConcs(State & state, bool doClu = true, bool doDoc = true)
{
// Concentrations for DPs from which topics and clusters are drawn...
state.topics.Body().ResampleConc(state.topics.RefTotal(), state.topics.Size());
state.clusters.Body().ResampleConc(state.clusters.RefTotal(), state.clusters.Size());
// Concentrations for clusters...
if (doClu)
{
if (state.seperateClusterConc)
{
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
cluster->Body().ResampleConc(cluster->RefTotal(), cluster->Size());
cluster = cluster->Next();
}
}
else
{
if (state.clusters.Size()>0)
{
SampleConcDP scdp;
scdp.SetPrior(state.rho.alpha,state.rho.beta);
scdp.SetPrevConc(state.clusters.First()->Body().conc);
ItemRef<Cluster,Conc> * cluster = state.clusters.First();
while (cluster->Valid())
{
scdp.AddDP(cluster->RefTotal(), cluster->Size());
cluster = cluster->Next();
}
double newConc = scdp.Sample();
cluster = state.clusters.First();
while (cluster->Valid())
{
cluster->Body().conc = newConc;
cluster = cluster->Next();
}
state.rho.conc = newConc;
}
}
}
// Concentrations for documents...
if (doDoc)
{
if (state.seperateDocumentConc)
{
for (int d=0;d<state.docCount;d++)
{
state.doc[d].Body().ResampleConc(state.doc[d].RefTotal(), state.doc[d].Size());
}
}
else
{
SampleConcDP scdp;
scdp.SetPrior(state.doc[0].Body().alpha,state.doc[0].Body().beta);
scdp.SetPrevConc(state.doc[0].Body().conc);
for (int d=0;d<state.docCount;d++)
{
scdp.AddDP(state.doc[d].RefTotal(), state.doc[d].Size());
}
double newConc = scdp.Sample();
for (int d=0;d<state.docCount;d++)
{
state.doc[d].Body().conc = newConc;
}
}
}
}
// Helper function used during the left to right algorithm - a comparator for the qsort function for sorting an array of ints...
int compareInt(const void * lhs, const void * rhs)
{
return *(int*)lhs - *(int*)rhs;
}
// Helper function for timming...
float micro_seconds()
{
static double prev = 0.0;
timeval tv;
gettimeofday(&tv,0);
double now = tv.tv_sec + (tv.tv_usec/1e6);
float ret = (now-prev)*1e6;
prev = now;
return ret;
}
"""
# The actual function for Gibbs iterating the data structure - takes as input the State object as 'state' and the number of iterations to do as 'iters'...
gibbs_code = start_cpp(shared_code) + """
// State...
State s;
StatePyToCpp(state, &s);
// Declare some stuff for efficiency...
float * mn = new float[s.wordCount];
SMP smp(s.flagSets->dimensions[1], s.flagSets->dimensions[0]);
smp.SetFIA(s.flagSets);
smp.SetSampleCount(s.behSamples);
// If there is only one behaviour force disable bmn and phi estimation - things go pear-shaped otherwise...
if (s.flagSets->dimensions[1]<2) s.calcCluBmn = false;
// No point resampling phi if not resampling the bmn's...
if (s.calcCluBmn==false) s.calcPhi = false;
// Iterations...
bool verbose = false;
for (int iter=0;iter<iters;iter++)
{
if (verbose) printf("iter %i | %f\\n", iter, micro_seconds());
// Iterate the documents...
for (int d=0;d<s.docCount;d++)
{
if (verbose) printf("iter %i, doc %i | %f\\n", iter, d, micro_seconds());
// Resample the documents cluster...
if (s.doc[d].GetCluster()==0)
{
if (s.clusters.Size()==0)
{
ItemRef<Cluster,Conc> * newC = s.clusters.Append();
newC->Body().alpha = s.rho.alpha;
newC->Body().beta = s.rho.beta;
newC->Body().conc = s.rho.conc;
float * bmn = new float[s.behCount];
for (int b=0;b<s.behCount;b++) bmn[b] = s.phi[b];
newC->SetBMN(bmn);
s.doc[d].SetCluster(newC);
}
else
{
s.doc[d].SetCluster(s.clusters.First());
}
}
else
{
if (!s.oneCluster)
{
ResampleDocumentCluster(s, s.doc[d]);
}
}
if (verbose) printf("resampled cluster | %f\\n", micro_seconds());
// Resample the documents samples (words)...
for (int ss=0;ss<s.doc[d].SampleCount();ss++)
{
ResampleSample(s, s.doc[d], s.doc[d].GetSample(ss));
}
if (verbose) printf("resampled words | %f\\n", micro_seconds());
// Resample the cluster instance that each document instance is assigned to...
if (!s.dnrDocInsts)
{
ResampleDocumentInstances(s,s.doc[d]);
}
if (verbose) printf("resampled doc instances | %f\\n", micro_seconds());
// Resample the many concentration parameters every document - need to do this regularly to make sure the initialisation values don't cause the algorithm to get stuck (Plus its such a cheap operation that it doesn't matter if its done too frequently.)...
if (s.resampleConcs)
{
ResampleConcs(s);
}
if (verbose) printf("resampled concentrations | %f\\n", micro_seconds());
}
// Resample the cluster instances assigned topics...
if (!s.dnrCluInsts)
{
if (verbose) printf("resampling cluster instances... | %f\\n", micro_seconds());
ResampleClusterInstances(s);
}
// Resample each clusters bmn...
if (s.calcCluBmn)
{
if (verbose) printf("resampling cluster bmn's... | %f\\n", micro_seconds());
// Update the prior for the smp object from phi...
smp.SetPrior(s.phi);
// Go through the documents and construct a list of documents belonging to each cluster...
ItemRef<Cluster,Conc> * targClu = s.clusters.First();
while (targClu->Valid())
{
targClu->first = 0;
targClu = targClu->Next();
}
for (int d=0;d<s.docCount;d++)
{
targClu = s.doc[d].GetCluster();
s.doc[d].next = targClu->first;
targClu->first = &s.doc[d];
}
// Iterate and do the calculation for each cluster...
targClu = s.clusters.First();
while (targClu->Valid())
{
// Reset the smp object, add the prior...
smp.Reset();
int * priorPower = targClu->GetBehCountPrior();
if (priorPower) smp.Add(priorPower);
// Add samples by iterating the relevant documents...
Document * targ = targClu->first;
while (targ)
{
if (targ->GetFlagIndex()>=s.flagSets->dimensions[1])
{
smp.Add(targ->GetFlagIndex(), targ->GetBehCounts());
}
targ = targ->next;
}
// Extract the estimate...
smp.Mean(targClu->GetBMN());
targClu = targClu->Next();
}
}
// Resample phi, the prior on the cluster bmn-s...
if (s.calcPhi)
{
if (verbose) printf("resampling phi... | %f\\n", micro_seconds());
EstimateDir ed(s.behCount);
ItemRef<Cluster,Conc> * cluster = s.clusters.First();
while (cluster->Valid())
{
ed.Add(cluster->GetBMN()); // Not actually correct - see below with beta for reason/justification.
cluster = cluster->Next();
}
ed.Update(s.phi);
}
// If requested recalculate beta...
if (s.calcBeta&&((s.topics.Size()+s.behTopics.Size()-1)>1))
{
if (verbose) printf("resampling beta... | %f\\n", micro_seconds());
EstimateDir ed(s.wordCount);
ItemRef<Topic,Conc> * topic = s.topics.First();
while (topic->Valid())
{
float div = 0.0;
for (int i=0;i<s.wordCount;i++)
{
mn[i] = topic->wc[i] + s.beta[i];
div += mn[i];
}
for (int i=0;i<s.wordCount;i++) mn[i] /= div;
ed.Add(mn); // Not actually correct - we are using the mean of the distribution from which we should draw the multinomial, rather than actually drawing. This is easier however, and not that unreasonable.
topic = topic->Next();
}
topic = s.behTopics.First()->Next(); // Skip the normal behaviour dummy.
while (topic->Valid())
{
float div = 0.0;
for (int i=0;i<s.wordCount;i++)
{
mn[i] = topic->wc[i] + s.beta[i];
div += mn[i];
}
for (int i=0;i<s.wordCount;i++) mn[i] /= div;
ed.Add(mn);
topic = topic->Next();
}
ed.Update(s.beta);
s.betaSum = 0.0;
for (int i=0;i<s.wordCount;i++) s.betaSum += s.beta[i];
}
// Verify the state is consistant - for debugging (Only works when there is no prior)...
//VerifyState(s);
}
delete[] mn;
StateCppToPy(&s, state);
"""
class ProgReporter:
"""Class to allow progress to be reported."""
def __init__(self,params,callback,mult = 1):
self.doneIters = 0
self.totalIters = mult * params.runs * (max((params.burnIn,params.lag)) + 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)
def gibbs(state, total_iters, next, step = 64):
"""Does the requested number of Gibbs iterations to the passed in state. If state has not been initialised the first iteration will be an incrimental construction."""
while total_iters>0:
iters = total_iters
if iters>step: iters = step
total_iters -= iters
weave.inline(gibbs_code, ['state', 'iters'], support_code=shared_code)
next(iters)
def gibbs_run(state, next):
"""Does a single run on the given state object, adding the relevant samples."""
params = state.getParams()
if params.burnIn>params.lag: gibbs(state, params.burnIn-params.lag,next)
for s in xrange(params.samples):
gibbs(state, params.lag,next)
state.sample()
next()
def gibbs_all(state, callback = None):
"""Does all the runs requested by a states params object, collating all the samples into the State."""
params = state.getParams()
reporter = ProgReporter(params,callback)
for r in xrange(params.runs):
tempState = State(state)
gibbs_run(tempState,reporter.next)
state.absorbClone(tempState)
def gibbs_doc(model, doc, params = None, callback = None):
"""Runs Gibbs iterations on a single document, by sampling with a prior constructed from each sample in the given Model. params applies to each sample, so should probably be much more limited than usual - the default if its undefined is to use 1 run and 1 sample and a burn in of only 500. Returns a DocModel with all the relevant samples in."""
# Initialisation stuff - handle params, create the state and the DocModel object, plus a reporter...
if params==None:
params = Params()
params.runs = 1
params.samples = 1
params.burnIn = 500
state = State(doc, params)
dm = DocModel()
reporter = ProgReporter(params,callback,model.sampleCount())
# Iterate and run for each sample in the model...
for sample in model.sampleList():
tempState = State(state)
tempState.setGlobalParams(sample)
tempState.addPrior(sample)
gibbs_run(tempState,reporter.next)
dm.addFrom(tempState.getModel())
# Return...
return dm
def leftRightNegLogProbWord(sample, doc, cluster, particles, cap):
"""Does a left to right estimate of the negative log probability of the words in the given document, given a sample, the documents abnormalities and a cluster assignment. cap defines a cap on the number of documents resampled before each word is sampled for inclusion - set to a negative number for no cap, but be warned that the algorithm is then O(n^2) with regard to the number of words in the document. Should be set quite high in practise for a reasonable trade off between quality and run-time."""
code = start_cpp(shared_code) + """
// Setup - create the state, extract the document, set its cluster...
State state;
StatePyToCpp(stateIn, &state);
Document & doc = state.doc[0];
if (cluster>=0)
{
// Existing cluster...
doc.SetCluster(state.clusters.Index(cluster));
}
else
{
// New cluster...
ItemRef<Cluster,Conc> * newC = state.clusters.Append();
newC->Body().alpha = state.rho.alpha;
newC->Body().beta = state.rho.beta;
newC->Body().conc = state.rho.conc;
float * bmn = new float[state.behCount];
float bmnDiv = 0.0;
for (int b=0;b<state.behCount;b++)
{
bmn[b] = state.phi[b];
bmnDiv += state.phi[b];
}
for (int b=0;b<state.behCount;b++) bmn[b] /= bmnDiv;
newC->SetBMN(bmn);
doc.SetCluster(newC);
}
// If the cap is negative set it to include all words, otherwise we need some storage...
int * samIndex = 0;
if (cap<0) cap = doc.SampleCount();
else
{
samIndex = new int[cap];
}
// Create some memory for storing the results into, zeroed out...
float * samProb = new float[doc.SampleCount()];
for (int s=0;s<doc.SampleCount();s++) samProb[s] = 0.0;
// Do all the particles, summing the results into the samProb array...
for (int p=0;p<particles;p++)
{
// Reset the document to have no assignments to words...
for (int s=0;s<doc.SampleCount();s++)
{
doc.GetSample(s).SetDocInst(0);
}
// Iterate and factor in the result from each sample...
for (int s=0;s<doc.SampleCount();s++)
{
// Resample preceding samples - 3 scenarios with regards to the cap...
// (Note that duplication is allowed in the random sample selection - whilst strictly forbidden the situation is such that it can not cause any issues.)
if (s<=cap)
{
// Less or equal number of samples than the cap - do them all...
for (int s2=0;s2<s;s2++)
{
ResampleSample(state, doc, doc.GetSample(s2));
}
}
else
{
if (s<=cap*2)
{
// Need to miss some samples out, but due to numbers its best to randomly select the ones to miss rather than the ones to do...
int missCount = s-cap;
for (int m=0;m<missCount;m++) samIndex[m] = sample_nat(s);
qsort(samIndex, missCount, sizeof(int), compareInt);
for (int s2=0;s2<samIndex[0];s2++)
{
ResampleSample(state, doc, doc.GetSample(s2));
}
for (int m=0;m<missCount-1;m++)
{
for (int s2=samIndex[m]+1;s2<samIndex[m+1];s2++)
{
ResampleSample(state, doc, doc.GetSample(s2));
}
}
for (int s2=samIndex[missCount-1]+1;s2<s;s2++)
{
ResampleSample(state, doc, doc.GetSample(s2));
}
}
else
{
// Need to select a subset of samples to do...
for (int m=0;m<cap;m++) samIndex[m] = sample_nat(s);
qsort(samIndex, cap, sizeof(int), compareInt);
for (int m=0;m<cap;m++)
{
ResampleSample(state, doc, doc.GetSample(samIndex[m]));
}
}
}
// Calculate the contribution of this sample, whilst simultaneously filling out so we can make a draw from them...
float pSum = CalcSampleProb(state, doc, doc.GetSample(s));
samProb[s] += (pSum - samProb[s]) / (p+1);
// Draw an assignment for the current sample, ready for the next iteration...
ResampleSample(state, doc, doc.GetSample(s), pSum);
}
}
// Sumarise the results buffer into a single log probability and return it...
float ret = 0.0;
for (int s=0;s<doc.SampleCount();s++) ret += log(samProb[s]);
return_val = ret;
// Clean up...
delete[] samIndex;
delete[] samProb;
"""
stateIn = State(doc, Params())
stateIn.setGlobalParams(sample)
stateIn.addPrior(sample)
ret = weave.inline(code,['stateIn','cluster','particles','cap'] , support_code=shared_code)
return -ret # Convert to negative log on the return - before then stick to positive.
class TestShared(unittest.TestCase):
"""Test code for the data structure."""
def test_compile(self):
code = start_cpp(shared_code) + """
"""
weave.inline(code, support_code=shared_code)
# If this file is run do the unit tests...
if __name__ == '__main__':
unittest.main()
| [
[
1,
0,
0.0117,
0.0006,
0,
0.66,
0,
88,
0,
1,
0,
0,
88,
0,
0
],
[
1,
0,
0.0123,
0.0006,
0,
0.66,
0.0588,
526,
0,
1,
0,
0,
526,
0,
0
],
[
1,
0,
0.0136,
0.0006,
0,
0.... | [
"import unittest",
"import math",
"from params import Params",
"from solve_shared import State",
"from model import DocModel",
"from utils.start_cpp import start_cpp",
"from ds_link_cpp import ds_link_code",
"from scipy import weave",
"shared_code = ds_link_code + start_cpp() + \"\"\"\n\n#include <s... |
# 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 time
import multiprocessing as mp
import multiprocessing.synchronize # To make sure we have all the functionality.
from solve_shared import Params, State
from solve_weave import gibbs_run
from model import DocModel
def gibbs_run_wrap(state, doneIters):
"""Wrapper around gibbs_run to make it suitable for multiprocessing."""
def next(amount = 1):
doneIters.value += amount
gibbs_run(state, next)
return state
def gibbs_all_mp(state, callback = None):
"""Identical to gibbs_all, except it does each run in a different process, to fully stress the computer."""
# Need the parameters object so we do the correct amount of work...
params = state.getParams()
# Create a pool of worker processes...
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 * (max((params.burnIn,params.lag)) + params.samples + (params.samples-1)*params.lag)
# Create a callback for when a job completes...
def onComplete(s):
state.absorbClone(s)
# Create all the jobs, wait for their completion, report progress...
try:
jobs = []
for r in xrange(params.runs):
jobs.append(pool.apply_async(gibbs_run_wrap,(State(state),doneIters), 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()
def gibbs_doc_mp(model, doc, params = None, callback = None):
"""Runs Gibbs iterations on a single document, by sampling with a prior constructed from each sample in the given Model. params applies to each sample, so should probably be much more limited than usual - the default if its undefined is to use 1 run and 1 sample and a burn in of only 500. Returns a DocModel with all the relevant samples in."""
# Initialisation stuff - handle params, create the state and the DocModel object, plus a reporter...
if params==None:
params = Params()
params.runs = 1
params.samples = 1
params.burnIn = 500
state = State(doc, params)
dm = DocModel()
# Create a pool of worker processes...
pool = mp.Pool()
# Create a value for sub-processes to report back their progress with...
manager = mp.Manager()
doneIters = manager.Value('i',0)
totalIters = model.sampleCount() * params.runs * (params.burnIn + params.samples + (params.samples-1)*params.lag)
# Create a callback for when a job completes...
def onComplete(s):
dm.addFrom(s.getModel())
# Create all the jobs, wait for their completion, report progress...
try:
jobs = []
for sample in model.sampleList():
tempState = State(state)
tempState.setGlobalParams(sample)
tempState.addPrior(sample)
jobs.append(pool.apply_async(gibbs_run_wrap,(tempState,doneIters), 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()
# Return...
return dm
| [
[
1,
0,
0.1513,
0.0084,
0,
0.66,
0,
654,
0,
1,
0,
0,
654,
0,
0
],
[
1,
0,
0.1597,
0.0084,
0,
0.66,
0.125,
901,
0,
1,
0,
0,
901,
0,
0
],
[
1,
0,
0.1681,
0.0084,
0,
0... | [
"import time",
"import multiprocessing as mp",
"import multiprocessing.synchronize # To make sure we have all the functionality.",
"from solve_shared import Params, State",
"from solve_weave import gibbs_run",
"from model import DocModel",
"def gibbs_run_wrap(state, doneIters):\n \"\"\"Wrapper around g... |
# 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.python_obj_cpp import python_obj_code
from linked_list_cpp import linked_list_gc_code
from utils.gamma_cpp import gamma_code
from sampling_cpp import sampling_code
from conc_cpp import conc_code
from dir_est_cpp import dir_est_code
# Put all the suplied code together into one easy to use include...
dp_utils_code = python_obj_code + linked_list_gc_code + gamma_code + sampling_code + conc_code + dir_est_code
| [
[
1,
0,
0.5652,
0.0435,
0,
0.66,
0,
249,
0,
1,
0,
0,
249,
0,
0
],
[
1,
0,
0.6087,
0.0435,
0,
0.66,
0.1667,
190,
0,
1,
0,
0,
190,
0,
0
],
[
1,
0,
0.6522,
0.0435,
0,
... | [
"from utils.python_obj_cpp import python_obj_code",
"from linked_list_cpp import linked_list_gc_code",
"from utils.gamma_cpp import gamma_code",
"from sampling_cpp import sampling_code",
"from conc_cpp import conc_code",
"from dir_est_cpp import dir_est_code",
"dp_utils_code = python_obj_code + linked_l... |
# -*- 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',",
" \... |
# 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',",
" \... |
# 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',",
" \... |
# 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,
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],
[
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,
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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',",
" \... |
# 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',",
" \... |
# 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',",
" \... |
# 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',",
" \... |
# 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',",
" \... |
# 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,
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],
[
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,
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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)"
] |
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