def OnGraphInbreed(self, event):
# try:
if hasattr(self, '_pedigree'):
if not self._pedigree.kw['f_computed']:
_ped_inbr = pyp_nrm.inbreeding(self._pedigree)
pyp_db.loadPedigreeTable(self._pedigree)
_coi_by_year = pyp_reports.meanMetricBy(self._pedigree,
metric='fa',
byvar='by')
del (_coi_by_year[1900])
_graph = pyp_graphics.plot_line_xy(
_coi_by_year,
gfilename='_coi_by_year',
gtitle='Average coefficients of inbreeding',
gxlabel='Birth year',
gylabel='f')
if _graph:
# wx.InitAllImageHandlers()
# _i = wx.Image('_coi_by_year.png', wx.BITMAP_TYPE_PNG)
# _b = wx.BitmapFromImage(_i)
# _sb = wx.StaticBitmap(self, -1, _b, (10, 10), (_b.GetWidth(), _b.GetHeight()))
dlg = pyp_gui_graphs.PyPedalGraphDialogInbreeding(
self, ID_MAIN_TB,
'PyPedal - View inbreeding by birth year')
try:
dlg.ShowModal()
finally:
dlg.Destroy()
def MetricsEffectiveFounders(self):
if hasattr(self,'_pedigree'):
self._inbreeding = pyp_nrm.inbreeding(self._pedigree)
self.textbox.Clear()
print pyp_io.summary_inbreeding(self._inbreeding['metadata'])
self.textbox.AppendText(pyp_io.summary_inbreeding(self._inbreeding['metadata']))
else:
pyp_gui_graphs.PyPedalShowErrorDialog(self,sedTitle='Calculate effective founder', sedMessage='This calculation cannot be displayed because you have not yet loaded a pedigree!')
def MetricsEffectiveFounders(self):
if hasattr(self, '_pedigree'):
self._inbreeding = pyp_nrm.inbreeding(self._pedigree)
self.textbox.Clear()
print pyp_io.summary_inbreeding(self._inbreeding['metadata'])
self.textbox.AppendText(
pyp_io.summary_inbreeding(self._inbreeding['metadata']))
else:
pyp_gui_graphs.PyPedalShowErrorDialog(
self,
sedTitle='Calculate effective founder',
sedMessage=
'This calculation cannot be displayed because you have not yet loaded a pedigree!'
)
def OnGraphInbreed(self,event):
# try:
if hasattr(self,'_pedigree'):
if not self._pedigree.kw['f_computed']:
_ped_inbr = pyp_nrm.inbreeding(self._pedigree)
pyp_db.loadPedigreeTable(self._pedigree)
_coi_by_year = pyp_reports.meanMetricBy(self._pedigree,metric='fa',byvar='by')
del(_coi_by_year[1900])
_graph = pyp_graphics.plot_line_xy(_coi_by_year,gfilename='_coi_by_year',gtitle='Average coefficients of inbreeding',gxlabel='Birth year',gylabel='f')
if _graph:
# wx.InitAllImageHandlers()
# _i = wx.Image('_coi_by_year.png', wx.BITMAP_TYPE_PNG)
# _b = wx.BitmapFromImage(_i)
# _sb = wx.StaticBitmap(self, -1, _b, (10, 10), (_b.GetWidth(), _b.GetHeight()))
dlg = pyp_gui_graphs.PyPedalGraphDialogInbreeding(self,ID_MAIN_TB,'PyPedal - View inbreeding by birth year')
try:
dlg.ShowModal()
finally:
dlg.Destroy()
from PyPedal import pyp_newclasses
from PyPedal import pyp_metrics
from PyPedal import pyp_nrm
from PyPedal import pyp_utils
from PyPedal.pyp_utils import pyp_nice_time
if __name__=='__main__':
print 'Starting pypedal.py at %s' % ( pyp_nice_time() )
example = pyp_newclasses.loadPedigree(optionsfile='new_format.ini')
#pyp_utils.assign_offspring(example)
#print 'First ID: %s' % ( example.kw['id_first'] )
#print 'Last ID: %s' % ( example.kw['id_last'] )
inbr, reln = inbr, reln = pyp_nrm.inbreeding(example,method='vanraden',rels=1)
print 'inbr: ', inbr
print 'reln: ', reln
example.nrm = pyp_newclasses.NewAMatrix(example.kw)
example.nrm.form_a_matrix(example.pedigree)
example.nrm.save('Amatrix.txt')
inbr2, reln2 = pyp_nrm.inbreeding(example,method='vanraden',rels=1)
print 'inbr2: ', inbr2
print 'reln2: ', reln2
example.nrm2 = pyp_newclasses.NewAMatrix(example.kw)
example.nrm2.load('Amatrix.txt')
#example.nrm2.printme()
#!/usr/bin/python ############################################################################### # NAME: new_graphics.py # VERSION: 2.0.0b5 (19DECEMBER2005) # AUTHOR: John B. Cole, PhD ([email protected]) # LICENSE: LGPL ############################################################################### from PyPedal import pyp_graphics from PyPedal import pyp_newclasses from PyPedal import pyp_nrm if __name__ == '__main__': example = pyp_newclasses.loadPedigree(optionsfile='new_renumbering.ini') print '-'*80 print 'INFO: Pedigree ID map: %s' % (example.idmap) print '-'*80 print 'INFO: Pedigree ID reverse map: %s' % (example.backmap) print '-'*80 myinbr = pyp_nrm.inbreeding(example) print 'INFO: Coefficients of inbreeding: %s' % (myinbr) pyp_graphics.draw_pedigree(example,gfilename='new_renumbering',gtitle='My Pedigree')
from PyPedal import pyp_jbc
from PyPedal import pyp_network
from PyPedal import pyp_newclasses
from PyPedal import pyp_nrm
from PyPedal import pyp_metrics
if __name__ == '__main__':
example = pyp_newclasses.loadPedigree(optionsfile='newfoundland.ini')
print example.idmap
print example.backmap
print example.namemap
print example.namebackmap
newf_f = pyp_nrm.inbreeding(example)
print newf_f['fx'][example.idmap[
example.namemap['Kaptn Kvols von Widdersdorf']]]
## dussel_id = example.idmap[example.namemap['King von der Dussel']]
## print 'dussel_id: ', dussel_id
##
## print 'Empirical proof that ancestor loss coefficients are the same'
## print 'as pedigree completeness.'
##
## pedcomp3 = pyp_metrics.pedigree_completeness(example,gens=3)
## print example.pedigree[dussel_id-1].pedcomp
## pedcomp4 = pyp_metrics.pedigree_completeness(example,gens=4)
## print example.pedigree[dussel_id-1].pedcomp
## pedcomp5 = pyp_metrics.pedigree_completeness(example,gens=5)
## print example.pedigree[dussel_id-1].pedcomp
#
# pyp_graphics.draw_pedigree(horse, gfilename='blue_joe',
# gtitle='Blue Joe\'s Pedigree', gorient='p', gname=1, gdirec='RL',
# gfontsize=12, garrow=0, gtitloc='b')
## print '\nRen ID\tName\n------\t----'
## for _k in horse.backmap.keys():
## print '%s\t%s' % ( _k, horse.pedigree[int(_k)-1].name )
## print '-'*80
## horse_inbreeding = pyp_nrm.inbreeding(horse, method='vanraden', gens=2)
## print '\nHorse 2 gen inbreeding: %s' % ( horse_inbreeding )
## print '\nHorse mean 2 gen CoI: %s' % ( horse_inbreeding['metadata']['all']['f_avg'] )
horse_inbreeding, horse_rels = pyp_nrm.inbreeding(horse, method='tabular', rels=1)
print '\nHorse inbreeding: %s' % ( horse_inbreeding )
print '\nHorses wth non-zero coefficients of inbreeding:'
print '-----------------------------------------------'
for _h in horse_inbreeding['fx'].keys():
if horse_inbreeding['fx'][_h] > 0.:
print '%s\t\t%s' % ( horse.pedigree[int(_h)-1].name, horse_inbreeding['fx'][_h] )
print '\nHorse mean CoI:\t\t%s' % ( horse_inbreeding['metadata']['all']['f_avg'] )
## print '-'*80
##
## hg = pyp_network.ped_to_graph(horse)
## _2g = pyp_network.find_ancestors_g(hg, len(horse.idmap), {}, 2)
## _2g[len(horse.idmap)] = 1
## _names = []
## for _h in _2g.keys():
options['pedformat'] = 'asd'
options['pedname'] = 'My Pedigree'
options['matrix_type'] = 'sparse'
options['renumber'] = 0
options['pedigree_is_renumbered'] = 1
if __name__ == '__main__':
# example = pyp_newclasses.loadPedigree(optionsfile='new_inbreeding.ini')
example = pyp_newclasses.loadPedigree(options)
print example
print '[DEBUG]: matrix_type = ', example.kw['matrix_type']
print 'Started computing inbreeding at %s' % (pyp_nice_time())
example_inbreeding_vr = pyp_nrm.inbreeding(example,method='vanraden')
example_inbreeding_ml = pyp_nrm.inbreeding(example,method='meu_luo')
example_inbreeding_qu = pyp_nrm.inbreeding(example,method='mod_meu_luo')
print 'Finished computing inbreeding at %s' % (pyp_nice_time())
# print example_inbreeding
# print example_inbreeding['fx'][28]
print '\nVanRaden : ', example_inbreeding_vr['metadata']
print '\nMeuwissen and Luo : ', example_inbreeding_ml['metadata']
print '\nModified Meuwissen and Luo: ', example_inbreeding_qu['metadata']
# example_2 = pyp_newclasses.loadPedigree(optionsfile='new_inbreeding_2.ini')
# example_inbreeding_2 = pyp_nrm.inbreeding(example_2)
# print example_inbreeding_2
# print 'f_x for 73543: ', example_inbreeding_2['fx'][example_2.idmap[int('73543')]]
from PyPedal import pyp_graphics
options = {}
options['messages'] = 'verbose'
options['pedfile'] = 'hartlandclark.ped'
options['pedname'] = 'Pedigree from van Noordwijck and Scharloo (1981)'
options['pedformat'] = 'asdb'
options['pedigree_is_renumbered'] = 1
options['database_name'] = 'new_db_test'
options['dbtable_name'] = 'test'
options['database_type'] = 'sqlite'
if __name__ == '__main__':
example = pyp_newclasses.loadPedigree(options)
pyp_nrm.inbreeding(example)
print 'Dropping existing table...'
pyp_db.deleteTable(example)
print 'Checking to see if the table is gone...'
pyp_db.doesTableExist(example)
print 'Creating the table...'
pyp_db.createPedigreeTable(example)
print 'Populating the table...'
pyp_db.populatePedigreeTable(example)
mean_inbreeding = pyp_reports.meanMetricBy(example,
metric='fa',
byvar='by')
print mean_inbreeding
#!/usr/bin/python ############################################################################### # NAME: new_hartl.py # VERSION: 2.0.0b12 (15MAY2060) # AUTHOR: John B. Cole, PhD ([email protected]) # LICENSE: LGPL ############################################################################### from PyPedal import pyp_graphics from PyPedal import pyp_newclasses from PyPedal import pyp_nrm if __name__ == '__main__': example = pyp_newclasses.loadPedigree(optionsfile='new_hartl.ini') pyp_graphics.draw_pedigree( example, gfilename='hartlandclark', gtitle='Pedigree from van Noordwijck and Scharloo (1981)', gorient='p', gname=0, gdirec='', gfontsize=12, garrow=0) example_inbreeding = pyp_nrm.inbreeding(example) print example_inbreeding
# Here's how to save the A matrix to a binary file.
amatrix.save('boichard2_pedigree.bin')
# Here's how to load the A matrix from a binary file.
amatrix2 = pyp_newclasses.NewAMatrix(example.kw)
amatrix2.load('boichard2_pedigree.bin')
# Now we're going to calculate coefficients of inbreeding for the individuals
# in this pedigree. There are a few different algorithms for doing this in
# PyPedal.
# VanRaden's method is slow, but it will work (eventually) on just about any
# pedigree you give it. It also is the only method that will allow you to
# compute summary statistics about coefficients of relationship.
print '\tEntering pyp_nrm.inbreeding() at %s' % (pyp_utils.pyp_nice_time())
example_inbreeding = pyp_nrm.inbreeding(example, method='vanraden')
print '\tReturning from pyp_nrm.inbreeding() at %s' % (
pyp_utils.pyp_nice_time())
print example_inbreeding['metadata']
# If all you want are fast calculations of inbreeding coefficients, then you
# should use the Meuwissen & Luo or modified Meuwissen & Luo methods.
print '\tStarted computing inbreeding using Meuwissen and Luo\'s method at %s' % (
pyp_utils.pyp_nice_time())
test_inbreeding_ml = pyp_nrm.inbreeding(example, method='meu_luo')
print '\tFinished computing inbreeding using Meuwissen and Luo\'s method at %s' % (
pyp_utils.pyp_nice_time())
print test_inbreeding_ml['metadata']
# All methods should produce the same coefficients of inbreeding.
print '\n\tStarted computing inbreeding using Meuwissen and Luo\'s modified method at %s' % (
from PyPedal import pyp_network
from PyPedal import pyp_newclasses
from PyPedal import pyp_nrm
#from PyPedal import pyp_reports
from PyPedal import pyp_metrics
if __name__ == '__main__':
example = pyp_newclasses.loadPedigree(optionsfile='new_reporting.ini')
#example.printoptions()
#pyp_reports.pdfPedigreeMetadata(example, titlepage = 1, reporttitle = 'Metadada for My Pedigree', reportauthor = 'John B. Cole, PhD')
#pyp_reports.pdfPedigreeMetadata(example, titlepage = 1, reportauthor = 'John B. Cole, PhD', reportfile = 'metadata_report.pdf')
ib = pyp_nrm.inbreeding(example)
#coi_by_year = pyp_reports.meanMetricBy(example,metric='fa',byvar='by',createpdf=1)
#coi_by_year
#print ib
#for _e in example.pedigree:
#print _e.name, _e.fa
print example.kw['paper_size']
#print example.backmap
## Use with new_renumbering.ped.
#pyp_reports.pdf3GenPed([56,72], example)
## Use with horse.ped.
#pyp_reports.pdf3GenPed(["Pie's Joseph","Green's Dingo"], example)
#pyp_reports.pdf3GenPed("Green's Dingo", example,reportfile='greens_dingo_pedigree.pdf')
###############################################################################
from PyPedal import pyp_newclasses
from PyPedal import pyp_nrm
from PyPedal.pyp_utils import pyp_nice_time
import numpy
import time
if __name__ == '__main__':
print 'Starting pypedal.py at %s' % (pyp_nice_time())
example = pyp_newclasses.loadPedigree(optionsfile='new_amatrix.ini')
amatrix = pyp_newclasses.NewAMatrix(example.kw)
amatrix.form_a_matrix(example.pedigree)
# Here's how to save a matrix to a binary file.
# amatrix.save('boichard2_pedigree.bin')
# Here's how to load a matrix from a binary file.
# amatrix2 = pyp_newclasses.NewAMatrix(example.kw)
# amatrix2.load('boichard2_pedigree.bin')
# Calculate coefficients of inbreeding on this pedigree.
print '\tEntering pyp_nrm.inbreeding() at %s' % (pyp_nice_time())
example_inbreeding = pyp_nrm.inbreeding(example,method='vanraden')
print '\tReturning from pyp_nrm.inbreeding() at %s' % (pyp_nice_time())
print example_inbreeding['metadata']
from PyPedal import pyp_jbc
from PyPedal import pyp_network
from PyPedal import pyp_newclasses
from PyPedal import pyp_nrm
from PyPedal import pyp_metrics
if __name__ == '__main__':
example = pyp_newclasses.loadPedigree(optionsfile='newfoundland.ini')
print example.idmap
print example.backmap
print example.namemap
print example.namebackmap
newf_f = pyp_nrm.inbreeding(example)
print newf_f['fx'][example.idmap[example.namemap['Kaptn Kvols von Widdersdorf']]]
## dussel_id = example.idmap[example.namemap['King von der Dussel']]
## print 'dussel_id: ', dussel_id
##
## print 'Empirical proof that ancestor loss coefficients are the same'
## print 'as pedigree completeness.'
##
## pedcomp3 = pyp_metrics.pedigree_completeness(example,gens=3)
## print example.pedigree[dussel_id-1].pedcomp
## pedcomp4 = pyp_metrics.pedigree_completeness(example,gens=4)
## print example.pedigree[dussel_id-1].pedcomp
## pedcomp5 = pyp_metrics.pedigree_completeness(example,gens=5)
## print example.pedigree[dussel_id-1].pedcomp
###############################################################################
from PyPedal import pyp_newclasses
from PyPedal import pyp_nrm
from PyPedal.pyp_utils import pyp_nice_time
import numpy
import time
if __name__ == '__main__':
print 'Starting pypedal.py at %s' % (pyp_nice_time())
example = pyp_newclasses.loadPedigree(optionsfile='new_amatrix.ini')
amatrix = pyp_newclasses.NewAMatrix(example.kw)
amatrix.form_a_matrix(example.pedigree)
# Here's how to save a matrix to a binary file.
# amatrix.save('boichard2_pedigree.bin')
# Here's how to load a matrix from a binary file.
# amatrix2 = pyp_newclasses.NewAMatrix(example.kw)
# amatrix2.load('boichard2_pedigree.bin')
# Calculate coefficients of inbreeding on this pedigree.
print '\tEntering pyp_nrm.inbreeding() at %s' % (pyp_nice_time())
example_inbreeding = pyp_nrm.inbreeding(example, method='vanraden')
print '\tReturning from pyp_nrm.inbreeding() at %s' % (pyp_nice_time())
print example_inbreeding['metadata']
#!/usr/bin/python ############################################################################### # NAME: new_hartl.py # VERSION: 2.0.0b12 (15MAY2060) # AUTHOR: John B. Cole, PhD ([email protected]) # LICENSE: LGPL ############################################################################### from PyPedal import pyp_graphics from PyPedal import pyp_newclasses from PyPedal import pyp_nrm if __name__ == '__main__': example = pyp_newclasses.loadPedigree(optionsfile='new_hartl.ini') pyp_graphics.draw_pedigree(example, gfilename='hartlandclark', gtitle='Pedigree from van Noordwijck and Scharloo (1981)', gorient='p', gname=0, gdirec='', gfontsize=12, garrow=0) example_inbreeding = pyp_nrm.inbreeding(example) print example_inbreeding
