# Path: phievo/AnalysisTools/palette.py
# def update_default_colormap(colormap):
# def HSL_to_RGB(h,s,l):
#     def Hue_2_RGB( v1, v2, vH ):
# def floatrange(start,stop,steps):
# def color_generate(n,colormap=None):
# def make_colormap(seq):
# def generate_gradient(values,seq):


import numpy
import pylab
import linecache, copy
import matplotlib.gridspec as gridspec
import phievo.Networks.deriv2 as deriv2
from phievo.initialization_code import *
from phievo.AnalysisTools import palette
#from popen2 import Popen3
#from phievo.Networks.classes_eds2 import draw_Network


#exec('from '+name_pretty_graph+' import *')




""" Functions to  plot results for the immune recognition problem"""

ylimmax = 1.2





def Plot_pMHC(Name, ncelltot, total_size,ntau,list_ligands, position='best', list_species=[],list_AP=[], list_output=[]):
    """ Plot profile of all proteins as function of ligand concentration (list_ligands) contain the list, for the differeent taus (number ntau)"""
    result = numpy.zeros((total_size, ncelltot,ntau),dtype=float)  # creates a table result to store data, results[i,j] will contain the concentration of protein i in cell j at time defined by nline

# Path: phievo/AnalysisTools/palette.py
# def update_default_colormap(colormap):
# def HSL_to_RGB(h,s,l):
#     def Hue_2_RGB( v1, v2, vH ):
# def floatrange(start,stop,steps):
# def color_generate(n,colormap=None):
# def make_colormap(seq):
# def generate_gradient(values,seq):


# Path: Examples/immune/Immune/plotdata_pMHC.py
import numpy
import pylab
import linecache, copy
import matplotlib.gridspec as gridspec
import phievo.Networks.deriv2 as deriv2
from phievo.initialization_code import *
from phievo.AnalysisTools import palette

#from popen2 import Popen3
#from phievo.Networks.classes_eds2 import draw_Network


#exec('from '+name_pretty_graph+' import *')




""" Functions to  plot results for the immune recognition problem"""

ylimmax = 1.2





def Plot_pMHC(Name, ncelltot, total_size,ntau,list_ligands, position='best', list_species=[],list_AP=[], list_output=[]):
    """ Plot profile of all proteins as function of ligand concentration (list_ligands) contain the list, for the differeent taus (number ntau)"""
    result = numpy.zeros((total_size, ncelltot,ntau),dtype=float)  # creates a table result to store data, results[i,j] will contain the concentration of protein i in cell j at time defined by nline

    colors = palette.color_generate(total_size)