"""
CBMPy: CBPlot module
====================
PySCeS Constraint Based Modelling (http://cbmpy.sourceforge.net)
Copyright (C) 2009-2017 Brett G. Olivier, VU University Amsterdam, Amsterdam, The Netherlands
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/>
Author: Brett G. Olivier
Contact email: bgoli@users.sourceforge.net
Last edit: $Author: bgoli $ ($Id: CBPlot.py 575 2017-04-13 12:18:44Z bgoli $)
"""
# preparing for Python 3 port
from __future__ import division, print_function
from __future__ import absolute_import
#from __future__ import unicode_literals
import os, time, gc
import numpy
from . import CBWrite, CBTools
from .CBConfig import __CBCONFIG__ as __CBCONFIG__
__DEBUG__ = __CBCONFIG__['DEBUG']
__version__ = __CBCONFIG__['VERSION']
_HAVE_MATPLOTLIB_ = True
try:
import matplotlib
import matplotlib.pyplot as pyplot
except ImportError:
print('No Matplotlib available')
matplotlib = None
pyplot = None
_HAVE_MATPLOTLIB_ = False
[docs]def plotFluxVariability(fva_data, fva_names, fname, work_dir=None, title=None, ySlice=None, minHeight=None, maxHeight=None, roundec=None, autoclose=True, fluxval=True, type='png'):
"""
Plots and saves as an image the flux variability results as generated by CBSolver.FluxVariabilityAnalysis.
- *fva_data* FluxVariabilityAnalysis() FVA OUTPUT_ARRAY
- *fva_names* FluxVariabilityAnalysis() FVA OUTPUT_NAMES
- *fname* filename_base for the CSV output
- *work_dir* [default=None] if set the output directory for the csv files
- *title* [default=None] the user defined title for the graph
- *ySlice* [default=None] this sets an absolute (fixed) limit on the Y-axis (+- ySlice)
- *minHeight* [default=None] the minimum length that defined a span
- *maxHeight* [default=None] the maximum length a span can obtain, bar will be limited to maxHeight and coloured yellow
- *roundec* [default=None] an integer indicating at which decimal to round off output. Default is no rounding.
- *autoclose* [default=True] autoclose plot after save
- *fluxval* [default=True] plot the flux value
- *type* [default='png'] the output format, depends on matplotlib backend e.g. 'png', 'pdf', 'eps'
"""
assert _HAVE_MATPLOTLIB_, "\nPlotting requires Matplotlib"
l_cntr = 0
c_width = 0.8
g_bars = []
g_bars_lcorner =[]
fba_val_lines =[]
vResults = {}
PLOTLOG = False
outputNames = []
Ymagic = []
FIG = matplotlib.pyplot.figure(num=5, figsize=(16,9))
pyplot.hold(True)
for r in range(fva_data.shape[0]):
HASMIN = False
HASMAX = False
if roundec == None:
fv_min = fva_data[r,2]
fv_fba = fva_data[r,0]
fv_max = fva_data[r,3]
else:
fv_min = round(fva_data[r,2], roundec)
fv_fba = round(fva_data[r,0], roundec)
fv_max = round(fva_data[r,3], roundec)
if fv_fba != numpy.NaN:
if fv_min != numpy.NaN:
if fv_min < fv_fba:
HASMIN = True
if fv_max != numpy.NaN:
if fv_max > fv_fba:
HASMAX = True
b_height = 0.0
b_height1 = 0.0
b_height2 = 0.0
if HASMAX:
b_height1 = fv_max-fv_fba
if HASMIN:
b_height2 = fv_fba-fv_min
b_height = abs(b_height1)+abs(b_height2)
HCheckMin = False
HCheckMax = False
if minHeight == None:
HCheckMin = True
elif minHeight != None and b_height >= minHeight:
HCheckMin = True
if maxHeight == None:
HCheckMax = True
elif maxHeight != None and b_height <= maxHeight:
HCheckMax = True
if b_height > 0.0 and HCheckMin and HCheckMax:
outputNames.append(fva_names[r])
if HASMIN:
bottom = fv_min
else:
bottom = fv_fba
Ymagic.append(bottom)
Ymagic.append(bottom+b_height)
## print 'Bar = (%s,%s)' % (bottom, bottom+b_height)
g_bars.append(matplotlib.pyplot.bar(left=l_cntr, height=b_height,\
width=c_width, bottom=bottom, log=PLOTLOG, hold=True))
if fluxval:
fba_val_lines.append(matplotlib.pyplot.hlines(fv_fba, g_bars[-1][0].get_x(),\
g_bars[-1][0].get_x()+g_bars[-1][0].get_width(), colors='r', linestyles='solid', lw=2))
g_bars_lcorner.append(l_cntr)
l_cntr += c_width
vResults.update({fva_names[r] : fva_data[r].copy()})
elif b_height > 0.0 and HCheckMin:
outputNames.append(fva_names[r])
if HASMIN:
bottom = fv_min
else:
bottom = fv_fba
if bottom < fv_fba - maxHeight:
bottom = fv_fba- maxHeight
if bottom + b_height > fv_fba + maxHeight:
b_height = abs(fv_fba - bottom) + maxHeight
Ymagic.append(bottom)
Ymagic.append(bottom+b_height)
## print 'Bar = (%s,%s)' % (bottom, bottom+b_height)
g_bars.append(matplotlib.pyplot.bar(left=l_cntr, height=b_height,\
width=c_width, bottom=bottom, log=PLOTLOG, hold=True, color='y', lw=0.5))
if fluxval:
fba_val_lines.append(matplotlib.pyplot.hlines(fv_fba, g_bars[-1][0].get_x(),\
g_bars[-1][0].get_x()+g_bars[-1][0].get_width(), colors='r', linestyles='solid', lw=2))
g_bars_lcorner.append(l_cntr)
l_cntr += c_width
vResults.update({fva_names[r] : fva_data[r].copy()})
if __DEBUG__: print('len fva_names', len(fva_names))
if __DEBUG__: print('len g_bars', len(g_bars))
## print 'fva_data.shape', fva_data.shape
outputNames = [l.replace('_LPAREN_e_RPAREN_','_e') for l in outputNames]
matplotlib.pyplot.xticks(numpy.array(g_bars_lcorner)+(c_width/2.0), outputNames,\
rotation='vertical', size='xx-small')
if title == None:
matplotlib.pyplot.title('%s has %i varying fluxes' % (fname, len(g_bars)))
else:
matplotlib.pyplot.title('%s' % (title))
matplotlib.pyplot.ylabel('Variability')
if len(Ymagic) > 0:
yhi = max(Ymagic) + 0.01*max(Ymagic)
ylow = min(Ymagic) - abs(0.01*min(Ymagic))
if ySlice != None:
yhi = abs(ySlice)
ylow = -abs(ySlice)
matplotlib.pyplot.ylim(ylow, yhi)
if __DEBUG__: print('Plotting y %s --> %s' % (ylow, yhi))
if work_dir != None:
fname = os.path.join(work_dir, fname)
matplotlib.pyplot.savefig(fname+'.%s' % type)
pyplot.hold(False)
if autoclose:
matplotlib.pyplot.close('all')
