# Copyright 2015 Novo Nordisk Foundation Center for Biosustainability, DTU.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from cameo.util import partition
from cameo import config, util
import logging
logger = logging.getLogger(__name__)
logger.setLevel(logging.WARNING)
__all__ = ['plot_production_envelope', 'plot_2_production_envelopes', 'plot_flux_variability_analysis']
MISSING_PLOTTING_BACKEND_MESSAGE = "No supported plotting backend could be found. Please install bokeh if you'd like to generate plots (other backends will be supported in the future)."
GOLDEN_RATIO = 1.618033988
try:
from bokeh import plotting
from bokeh.models import GridPlot
except ImportError:
pass
else:
def _figure(title, width, height, **kwargs):
return plotting.figure(title=title,
tools="save",
plot_width=width if width is not None else 700,
plot_height=height if height is not None else 700,
**kwargs)
def _add_production_envelope(plot, envelope, key, patch_color="#99d8c9", patch_alpha=0.3, line_color="blue"):
ub = envelope["objective_upper_bound"].values
lb = envelope["objective_lower_bound"].values
var = envelope[key].values
x = [v for v in var] + [v for v in reversed(var)]
y = [v for v in lb] + [v for v in reversed(ub)]
plot.patch(x=x, y=y, color=patch_color, alpha=patch_alpha)
if "label" in envelope.columns:
plot.text(envelope["label"].values, var, ub)
plot.line(var, ub, color=line_color)
plot.line(var, lb, color=line_color)
if ub[-1] != lb[-1]:
plot.line((var[-1], var[-1]), (ub[-1], lb[-1]), color=line_color)
def plot_flux_variability_analysis_bokeh(fva_result, grid=None, width=None, height=None, title=None,
axis_font_size=None, color="blue"):
title = "Flux Variability Analysis" if title is None else title
factors = list(fva_result.index)
x0 = list(fva_result.lower_bound.values)
x1 = list(fva_result.upper_bound.values)
min_value = min([min(x0), min(x1)])
max_value = max([max(x0), max(x1)])
p = _figure(title, width, height, y_range=factors, x_range=[min_value - 5, max_value + 5])
line_width = (width - 30) / len(factors) / 2
p.segment(x0, factors, x1, factors, line_width=line_width, line_color=color)
for x_0, x_1, f in zip(x0, x1, factors):
if x_0 == x_1:
p.segment([x_0 - 0.01], [f], [x_1 + 0.01], [f], line_width=line_width, color=color)
p.line([0, 0], [0, len(factors) + 1], line_color="black", line_width=1, line_alpha=0.3)
if axis_font_size is not None:
p.xaxis.axis_label_text_font_size = axis_font_size
p.yaxis.axis_label_text_font_size = axis_font_size
if grid is not None:
grid.append(p)
else:
plotting.show(p)
def plot_2_flux_variability_analysis_bokeh(fva_result1, fva_result2, grid=None, width=None, height=None, title=None,
axis_font_size=None, color1="blue", color2="orange"):
factors = list(fva_result1.index)
left1 = list(fva_result1.upper_bound)
right1 = list(fva_result1.lower_bound)
top1 = [i for i in range(0, len(factors))]
bottom1 = [i + 0.5 for i in range(0, len(factors))]
left2 = list(fva_result2.upper_bound)
right2 = list(fva_result2.lower_bound)
top2 = [i for i in range(0, len(factors))]
bottom2 = [i - 0.5 for i in range(0, len(factors))]
x_range = [min([min(bottom1), min(bottom2)]) - 5, max([max(top1), max(top2)]) + 5]
title = "Comparing Flux Variability Results" if title is None else title
p = _figure(title, width, height, x_range=x_range, y_range=factors)
p.quad(top=top1, bottom=bottom1, left=left1, right=right1, color=color1)
p.quad(top=top2, bottom=bottom2, left=left2, right=right2, color=color2)
if axis_font_size is not None:
p.xaxis.axis_label_text_font_size = axis_font_size
p.yaxis.axis_label_text_font_size = axis_font_size
if grid is not None:
grid.append(p)
else:
plotting.show(p)
def plot_production_envelope_bokeh(envelope, objective, key, grid=None, width=None, height=None, title=None,
points=None, points_colors=None, axis_font_size=None, color="blue"):
title = "Production Envelope" if title is None else title
p = _figure(title, width, height)
p.xaxis.axis_label = key
p.yaxis.axis_label = objective
_add_production_envelope(p, envelope, key, patch_color=color, patch_alpha=0.3, line_color=color)
if axis_font_size is not None:
p.xaxis.axis_label_text_font_size = axis_font_size
p.yaxis.axis_label_text_font_size = axis_font_size
if points is not None:
p.scatter(*zip(*points), color="green" if points_colors is None else points_colors)
if grid is not None:
grid.append(p)
else:
plotting.show(p)
def plot_2_production_envelopes_bokeh(envelope1, envelope2, objective, key, grid=None, width=None,
height=None, title=None, points=None, points_colors=None,
axis_font_size=None, color1="blue", color2="orange"):
title = "2 Production Envelopes" if title is None else title
p = _figure(title, width, height)
p.xaxis.axis_label = key
p.yaxis.axis_label = objective
_add_production_envelope(p, envelope1, key, patch_color=color1, patch_alpha=0.3, line_color=color1)
_add_production_envelope(p, envelope2, key, patch_color=color2, patch_alpha=0.3, line_color=color2)
if axis_font_size is not None:
p.xaxis.axis_label_text_font_size = axis_font_size
p.yaxis.axis_label_text_font_size = axis_font_size
if points is not None:
p.scatter(*zip(*points), color="green" if points_colors is None else points_colors)
if grid is not None:
grid.append(p)
else:
plotting.show(p)
try:
from bashplotlib import scatterplot
except ImportError:
pass
else:
def plot_production_envelope_cli(envelope, objective, key, grid=None, width=None, height=None, title=None,
points=None, points_colors=None, axis_font_size=None, color="blue"):
scatterplot.plot_scatter(None, envelope[key], envelope["objective_upper_bound"], "*")
[docs]def plot_production_envelope(envelope, objective, key, grid=None, width=None, height=None, title=None,
points=None, points_colors=None, axis_font_size=None, color="blue"):
if width is None and height is None:
width = 700
if width is None or height is None:
width, height = _golden_ratio(width, height)
try:
if config.use_bokeh:
plot_production_envelope_bokeh(envelope, objective, key, grid=grid, width=width, height=height,
title=title, points=points, points_colors=points_colors,
axis_font_size=axis_font_size, color=color)
else:
plot_production_envelope_cli(envelope, objective, key, width=width, height=height, title=title,
points=points,
points_colors=points_colors, axis_font_size=axis_font_size, color=color)
except NameError:
logger.logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
[docs]def plot_2_production_envelopes(envelope1, envelope2, objective, key, grid=None, width=None, height=None, title=None,
points=None, points_colors=None, axis_font_size=None, color1="blue", color2="orange"):
if width is None and height is None:
width = 700
if width is None or height is None:
width, height = _golden_ratio(width, height)
try:
if config.use_bokeh:
plot_2_production_envelopes_bokeh(envelope1, envelope2, objective, key, grid=grid, width=width,
height=height,
title=title, points=points, points_colors=points_colors,
axis_font_size=axis_font_size, color1=color1, color2=color2)
else:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
except NameError:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
[docs]def plot_flux_variability_analysis(fva_result, grid=None, width=None, height=None, title=None, axis_font_size=None,
color="blue"):
if width is None and height is None:
width = 700
if width is None or height is None:
width, height = _golden_ratio(width, height)
try:
if config.use_bokeh:
plot_flux_variability_analysis_bokeh(fva_result, grid=grid, width=width, height=height, title=title,
axis_font_size=axis_font_size, color=color)
else:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
except NameError:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
def plot_2_flux_variability_analysis(fva_result1, fva_result2, grid=None, width=None, height=None, title=None,
axis_font_size=None, color1="blue", color2="orange"):
if width is None and height is None:
width = 700
if width is None or height is None:
width, height = _golden_ratio(width, height)
try:
if config.use_bokeh:
plot_2_flux_variability_analysis_bokeh(fva_result1, fva_result2, grid=grid, width=width, height=height,
title=title, axis_font_size=axis_font_size, color1=color1,
color2=color2)
else:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
except NameError:
logger.warn(MISSING_PLOTTING_BACKEND_MESSAGE)
class Grid(object):
def __init__(self, nrows=1, title=None):
self.plots = []
if nrows <= 1:
nrows = 1
self.nrows = nrows
self.title = title
def __enter__(self):
return self
def append(self, plot):
self.plots.append(plot)
def __exit__(self, exc_type, exc_val, exc_tb):
self._plot_grid()
def _plot_grid(self):
if util.in_ipnb():
if config.use_bokeh:
self._plot_bokeh_grid()
elif config.use_matplotlib:
self._plot_matplotlib_grid()
else:
self._plot_cli_grid()
def _plot_bokeh_grid(self):
if len(self.plots) > 0:
grid = GridPlot(children=partition(self.plots, self.nrows), title=self.title)
plotting.show(grid)
def _golden_ratio(width, height):
if width is None:
width = int(height + height / GOLDEN_RATIO)
elif height is None:
height = int(width / GOLDEN_RATIO)
return width, height
