# -*- coding: utf-8 -*-
"""
.. module:: pytfa
:platform: Unix, Windows
:synopsis: Thermodynamics-based Flux Analysis
.. moduleauthor:: pyTFA team
Plotting results
"""
import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource, DataRange1d, LinearAxis, \
Grid,CategoricalTicker, FuncTickFormatter
from bokeh.models.glyphs import HBar
from bokeh.io import show
from bokeh.plotting import figure
from ..optim.variables import ThermoDisplacement
def plot_fva_tva_comparison(fva,tva):
all_va = pd.merge(fva,tva, left_index = True, right_index=True)
all_va['y'] = range(len(all_va))
source = ColumnDataSource(all_va)
xdr = DataRange1d()
ydr = DataRange1d()
plot = figure(title=None, x_range=xdr, y_range=ydr, plot_width=600,
plot_height=1000, h_symmetry=False, v_symmetry=False, min_border=0)
glyph_fva = HBar(y="y", right="maximum_x", left="minimum_x", height=0.5,
fill_color="#b3de69", fill_alpha = 0.5)
glyph_tva = HBar(y="y", right="maximum_y", left="minimum_y", height=0.8,
fill_color="#2e86c1", fill_alpha = 0.5)
plot.add_glyph(source, glyph_tva)
plot.add_glyph(source, glyph_fva)
# Fix ticks
label_dict = {}
for i, s in enumerate(tva.index):
label_dict[i] = s
plot.yaxis.formatter = FuncTickFormatter(code="""
var labels = %s;
return labels[tick];
""" % label_dict)
plot.yaxis.ticker = [x for x in range(len(tva))]
return plot
def plot_thermo_displacement_histogram(tmodel,solution = None):
"""
Plot a histogram of the thermodynamic displacement. if no solution is
provided, will look at the cobra_model's own solution
:param tmodel:
:param solution:
:return:
"""
if solution is None:
values = tmodel.get_primal(ThermoDisplacement)
else:
thermo_displacements = tmodel.get_variables_of_type(ThermoDisplacement)
varnames = [x.name for x in thermo_displacements]
values = solution.raw[varnames]
p1 = plot_histogram(values)
p1.legend.location = "center_right"
p1.legend.background_fill_color = "darkgrey"
p1.xaxis.axis_label = 'ln(Γ)'
p1.yaxis.axis_label = 'count'
p1.title = "Histogram: Thermodynamic displacement"
return p1
def plot_histogram(values, **kwargs):
"""
Convenience function. Plots a histogram of flat 1D data.
:param values:
:return:
"""
hist, edges = np.histogram(values, **kwargs)
p1 = figure(tools="save")
p1.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:],
fill_color="#036564", line_color="#033649")
return p1
