def plot(iter_info, min_max_concns):
axis = figure.add_subplot('', 111, frameon=options.frameon)
toolbox_idynomics.color_cells_by_species(iter_info.agent_output,
species_color_dict)
toolbox_idynomics.plot_cells_2d(axis, iter_info.agent_output)
if options.substratum:
axis.fill_between([0, nJ*res], [0]*2, y2=[-res]*2, color='k', zorder=-1)
figure.subplots_adjust(left=0.01, bottom=0.01, right=0.9, top=0.9)
figure.inset_axes()
if not options.solute_name == "none":
#print min_max_concns[options.solute_name]
solute_output = toolbox_results.SoluteOutput(iter_info.env_output,
name=options.solute_name)
cs = toolbox_idynomics.solute_contour(axis, solute_output,
concn_range=min_max_concns[options.solute_name],
interpolation='bicubic')
if options.color_bar:
toolbox_plotting.make_colorbar(axis, cs)
if options.titleon:
axis.set_title(r'Biofilm (%s g L$^{-1}$)'%(options.solute_name))
if options.frameon:
axis.set_xlabel('x')
axis.set_ylabel('y')
if options.timeon:
axis.text(0.0, nI*res, 'Time: %d h'%(int(iter_info.time)),
va='top', ha='left')
axis.set_xlim(0, nJ * res)
axis.set_ylim(-res, nI * res)
save_num = str(iter_info.number)
#save_num = str(counter)
#counter += 1
save_num = (num_digits - len(save_num))*'0' + save_num
save_path = os.path.join(sim.figures_dir,
save_name+'_'+save_num+options.file_ext)
figure.save(save_path, dpi=options.dpi)
def plot(iter_info, min_max_concns):
axis = figure.add_subplot('', 111, frameon=options.frameon)
for species in iter_info.agent_output.species_outputs:
species_name = species.name
for cell in species.members:
spStatus = cell.vars['sporeStatus']
mbStatus = cell.vars['metabolismStatus']
if spStatus == 'spore':
cell.color = species_color_dict[species_name+"_spore"]
continue
if spStatus == 'sporulating':
cell.color = species_color_dict[species_name+"_sporulating"]
continue
if mbStatus == 'glycolysis':
cell.color = species_color_dict[species_name+"_glycolysis"]
continue
if mbStatus == 'solventogenesis':
cell.color = species_color_dict[species_name+"_solventogenesis"]
continue
toolbox_idynomics.plot_cells_2d(axis, iter_info.agent_output)
if options.substratum:
axis.fill_between([0, nJ*res], [0]*2, y2=[-res]*2, color='k', zorder=-1)
lb = 0.01
if options.frameon:
lb = 0.12
figure.process_lines()
figure.subplots_adjust(left=lb, bottom=lb, right=0.9, top=0.9)
figure.inset_axes()
if not options.solute_name == "none":
#print min_max_concns[options.solute_name]
solute_output = toolbox_results.SoluteOutput(iter_info.env_output,
name=options.solute_name)
cs = toolbox_idynomics.solute_contour(axis, solute_output,
concn_range=min_max_concns[options.solute_name],
interpolation='bicubic')
if options.color_bar:
toolbox_plotting.make_colorbar(axis, cs)
if options.titleon:
axis.set_title(r'Biofilm (%s g L$^{-1}$)'%(options.solute_name))
if options.frameon:
axis.set_xlabel(r'x ($\mu$m)')
axis.set_ylabel(r'y ($\mu$m)')
if options.timeon:
axis.text(0.1*res, (nI+0.1)*res, 'Time: %.2f h'%(iter_info.time),
va='bottom', ha='left', color='0.5')
axis.set_xlim(0, nJ * res)
axis.set_ylim(-res, nI * res)
save_num = str(iter_info.number)
#save_num = str(counter)
#counter += 1
save_num = (num_digits - len(save_num))*'0' + save_num
save_path = os.path.join(sim.figures_dir,
save_name+'_'+save_num+options.file_ext)
figure.save(save_path, dpi=options.dpi)
def single_time(fol, time):
os.chdir(fol + '/agent_State/')
axis = plt.subplot(111)
output = results.AgentOutput(path=time)
time = (output.time)
for species in output.species_outputs:
if species.members == []:
continue
for cell in species.members:
name = species.name
for (species_name,
colormap_name) in species_color_dict.iteritems():
if name == species_name:
norm = matplotlib.colors.Normalize(vmin=0, vmax=1)
colormap = matplotlib.cm.get_cmap(colormap_name, 256)
m = matplotlib.cm.ScalarMappable(norm=norm, cmap=colormap)
age = float(cell.vars['age'])
cell.color = m.to_rgba(age)
toolbox_idynomics.plot_cells_2d(axis, output)
output = results.EnvOutput(path='env_State(last).xml')
for solute in output.solute_outputs:
if solute.name == 'glucose':
solute_output = solute
toolbox_idynomics.solute_contour(axis,
solute_output,
interpolation='bicubic')
axis.text(250,
250,
'Time: ' + str(int(time)) + 'h',
va='top',
ha='right',
color='#bd0303',
fontsize=fs)
axis.set_xlabel(r'$\mu$m', fontsize=fs)
axis.set_ylabel(r'$\mu$m', fontsize=fs)
os.mkdir(fol + '/times/')
os.chdir(fol + '/times/')
plt.savefig('Biofilm time ' + time[12:-5] + '.png', bbox_inches='tight')
plt.close()
def plot(iter_info, min_max_concns):
axis = figure.add_subplot('', 111, frameon=options.frameon)
toolbox_idynomics.color_cells_by_species(iter_info.agent_output,
species_color_dict)
toolbox_idynomics.plot_cells_2d(axis, iter_info.agent_output)
if options.substratum:
axis.fill_between([0, nJ * res], [0] * 2,
y2=[-res] * 2,
color='k',
zorder=-1)
lb = 0.01
if options.frameon:
lb = 0.06
figure.process_lines()
figure.subplots_adjust(left=lb, bottom=lb, right=0.9, top=0.9)
figure.inset_axes()
if not options.solute_name == "none":
#print min_max_concns[options.solute_name]
solute_output = toolbox_results.SoluteOutput(iter_info.env_output,
name=options.solute_name)
cs = toolbox_idynomics.solute_contour(
axis,
solute_output,
concn_range=min_max_concns[options.solute_name],
interpolation='bicubic')
if options.color_bar:
toolbox_plotting.make_colorbar(axis, cs)
if options.titleon:
axis.set_title(r'Biofilm (%s g L$^{-1}$)' % (options.solute_name))
if options.frameon:
axis.set_xlabel(r'x ($\mu$m)')
axis.set_ylabel(r'y ($\mu$m)')
if options.timeon:
axis.text(0.1 * res, (nI + 0.1) * res,
'Time: %d h' % (int(iter_info.time)),
va='bottom',
ha='left',
color='0.5')
axis.set_xlim(0, nJ * res)
axis.set_ylim(-res, nI * res)
save_num = str(iter_info.number)
#save_num = str(counter)
#counter += 1
save_num = (num_digits - len(save_num)) * '0' + save_num
save_path = os.path.join(sim.figures_dir,
save_name + '_' + save_num + options.file_ext)
figure.save(save_path, dpi=options.dpi)
def single_time(fol, time_fn, count, arate=True):
biomass_names = [
'activeBiomassGrowth', 'activeBiomassRepair', 'inactiveBiomassGrowth',
'inactiveBiomassRepair'
]
ax = plt.subplot(111)
os.chdir(fol + '/agent_State/')
output = results.AgentOutput(path=time_fn)
time = (output.time)
ma1, ma2 = 0, 0
for species in output.species_outputs:
if species.members == []:
continue
if not arate:
all_growth = []
for cell in species.members:
all_growth.append(
float(cell.get_specific_growth_rate(biomass_names)))
ma = max(all_growth)
if ma1 == 0: ma1 = ma
else: ma2 = ma
for cell in species.members:
name = species.name
for (species_name, colormap_name) in species_color_dict.items():
if name == species_name:
colormap = matplotlib.cm.get_cmap(colormap_name, 256)
if not arate:
l0, l06 = numpy.log(0.001), numpy.log(0.6)
norm = matplotlib.colors.Normalize(vmin=l0, vmax=l06)
else:
norm = matplotlib.colors.Normalize(vmin=0, vmax=1)
m = matplotlib.cm.ScalarMappable(norm=norm, cmap=colormap)
if arate:
age = float(cell.vars['age'])
else:
gr = float(
cell.get_specific_growth_rate(biomass_names))
if gr == 0: gr = numpy.log(0.001)
else: gr = numpy.log(gr)
if arate:
cell.color = m.to_rgba(age)
else:
cell.color = m.to_rgba(gr)
toolbox_idynomics.plot_cells_2d(ax, output)
os.chdir(fol + '/env_State/')
output = results.EnvOutput(path=time_fn.replace('agent', 'env'))
for solute in output.solute_outputs:
if solute.name == 'glucose':
solute_output = solute
toolbox_idynomics.solute_contour(ax,
solute_output,
interpolation='bicubic')
ax.text(250,
250,
'Time: ' + str(count) + 'h',
va='top',
ha='right',
color='#bd0303',
fontsize=fs)
os.chdir(fol)
if arate:
plt.savefig(fol + '/times/' + str(count) + '.png',
bbox_inches='tight',
dpi=300)
else:
plt.savefig(fol + '/times_gr/' + str(count) + '.png',
bbox_inches='tight',
dpi=300)
plt.close()
return
cell.color = species_color_dict[0]
elif growthrate == 0:
cell.color = species_color_dict[1]
elif species.name == 'OldieB':
if growthrate == 1:
cell.color = species_color_dict[2]
elif growthrate == 0:
cell.color = species_color_dict[3]
toolbox_idynomics.plot_cells_2d(axis, output)
os.chdir(folder + f + '/env_State')
output = results.EnvOutput(path='env_State' + times[a][11:])
for solute in output.solute_outputs:
if solute.name == 'glucose':
solute_output = solute
toolbox_idynomics.solute_contour(axis,
solute_output,
interpolation='bicubic')
axis.text(250,
250,
'Time: ' + str(int(time)) + 'h',
va='top',
ha='right',
color='#bd0303',
fontsize=fs)
axis.set_xlabel(r'$\mu$m', fontsize=fs)
axis.set_ylabel(r'$\mu$m', fontsize=fs)
os.chdir(
'/Users/u1560915/Documents/OneDrive/Aging_of_Biofilms/Write up/paper_july_2018/one_biofilm_over_time/proportional/'
)
plt.savefig('Growth biofilm time ' + times[a][12:-5] + '.png',
dpi=300,
