import time, copy, pickle

import os, os.path

import sys

import numpy, pylab, itertools

sys.path.append('C:/Users/Gregoire/Documents/PythonCode/JCAP')

from readplatemap import *

modelpath=r'D:\Google Drive\Documents\CaltechWork\platemaps\4x6_20intervs_rightcolumnsforcharacterization\0037-04-0730-mp.txt'

newpath=r'D:\Google Drive\Documents\CaltechWork\platemaps\4x6_20intervs_rightcolumnsforcharacterization\v2.txt'

writelines=[]

f=open(modelpath, mode='r')

ls=f.readlines()[:2]

writelines+=[l.strip() for l in ls]

f.close()

dlist=readsingleplatemaptxt(modelpath, returnfiducials=False)

smps=numpy.array([d['Sample'] for d in dlist])

codes=numpy.array([d['code'] for d in dlist])

xset=sorted(list(set([d['x'] for d in dlist])))

xposns_refcolumns=numpy.array(xset)[[7, 15, 23, 31, 39, 47, 55]]#range(7, 64, 8)

xtouse=[x for x in xset if not x in xposns_refcolumns]

[d.update(code=4, A=0, B=0, C=0, D=0) for d in dlist if d['x'] in xtouse]

xset=sorted(list(set([d['x'] for d in dlist])))

xposns_refcolumns=numpy.array(xset)[range(7, 64, 8)]

xforchar=xtouse[-15:]

yset=sorted(list(set([d['y'] for d in dlist])))

yforchar=yset[:15]

inds_char=[count for count, d in enumerate(dlist) if d['x'] in xforchar and d['y'] in yforchar]

inds_charpop=copy.copy(inds_char)

inds_main=[count for count, d in enumerate(dlist) if d['code']==4 and not count in inds_char]

inds_mainpop=copy.copy(inds_main)

intervs=20

#comps=[[1.0*b/intervs, 1.0*c/intervs, 1.0*(intervs-a-b-c)/intervs, 1.0*a/intervs] for a in numpy.arange(0,intervs+1)[::-1] for b in numpy.arange(0,intervs+1-a) for c in numpy.arange(0, intervs+1-a-b)][::-1]

comps=[[b, c, (intervs-a-b-c), a] for a in numpy.arange(0,intervs+1)[::-1] for b in numpy.arange(0,intervs+1-a) for c in numpy.arange(0, intervs+1-a-b)][::-1]

compsnotinnertern10=copy.copy(comps)

ternintervs=10

compsinnertern=[[2*b, 2*(ternintervs-a-b), 2*a, 0] for a in numpy.arange(1,ternintervs)[::-1] for b in numpy.arange(1,ternintervs-a) ][::-1]

compstern=numpy.array(compsinnertern)[:, :3]

for count, t in enumerate(itertools.combinations(range(4),3)):

tempcompsinnertern=numpy.zeros((len(compstern), 4), dtype='int32')

tempcompsinnertern[:, list(t)]=compstern[:, :]

compsnotinnertern10=[c for c in numpy.array(compsnotinnertern10) if not True in [numpy.all(c==cv) for cv in tempcompsinnertern]]

code=100*(count+1)

for av, bv, cv, dv in tempcompsinnertern:

i=inds_charpop.pop(0)

dlist[i].update(A=av, B=bv, C=cv, D=dv, code=code)

for count in range(15):

i=inds_charpop.pop(0)

dlist[i].update(code=4)

def genbinarycomps(intervs, elind1, elind2, ndim=4):

return c

codes=[0]*len(comps)

binintervs=10

for count, (i, j) in enumerate([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]):

tempcomps=list(genbinarycomps(binintervs, i, j))

code=1000*(count+1)

for av, bv, cv, dv in tempcomps:

i=inds_charpop.pop(0)

dlist[i].update(A=av, B=bv, C=cv, D=dv, code=code)

for count, (av, bv, cv, dv) in enumerate(compsnotinnertern10):

i=inds_mainpop.pop(0)

dlist[i].update(A=av, B=bv, C=cv, D=dv, code=0)

for d in dlist:

for k in ['A', 'B', 'C', 'D']:

d[k]*=1./intervs

c=numpy.array([d[el] for el in ['A', 'B', 'C', 'D']])

if c.sum()>0:

c/=c.sum()

d['compositions']=c

k_f=[\

]

writelines+=[', '.join([f %d[k] for k, f in k_f]) for d in dlist]

f=open(newpath, mode='w')

f.write('\n'.join(writelines))

f.close()

codeset=sorted(list(set([d['code'] for d in dlist])))

marks=['s', 's', 's', 's','o', 'v', '^', '<','>','o','D','o','D','o','D']

def rgb_comp(cmp):

return rgb_cmyk(cmp)

fig=pylab.figure()

ax=pylab.subplot(111)

ax.set_aspect(1)

for d in dlist:

mark=marks[codeset.index(d['code'])]

col=rgb_comp(d['compositions'])

if d['compositions'].sum==0:

pylab.scatter(d['x'], d['y'],color=col,s=14,marker=mark, edgecolor='k')

else:

pylab.scatter(d['x'], d['y'],color=col,s=14,marker=mark, edgecolor='none')

for cd, ma in zip(codeset, marks):

pylab.plot([], [], 'k'+ma, mec='none', label=`cd`)

pylab.legend(loc=6)

sys.path.append(r'D:\Google Drive\Documents\PythonCode\JCAP\PythonCompositionPlots')

from myquaternaryutility import QuaternaryPlot

pylab.figure()

carr=numpy.array([d['compositions'] for d in dlist])

stpq=QuaternaryPlot(111)

stpq.scatter(carr)

pylab.show()

errortime