def do_plot(self, seedOutDir, plotOutDir, plotOutFileName, simDataFile,
validationDataFile, metadata):
if not os.path.isdir(seedOutDir):
raise Exception, "seedOutDir does not currently exist as a directory"
if not os.path.exists(plotOutDir):
os.mkdir(plotOutDir)
ap = AnalysisPaths(seedOutDir, multi_gen_plot=True)
# TODO: Declutter Y-axis
# Get all cells
allDir = ap.get_cells().tolist()
massNames = [
"dryMass",
]
cleanNames = [
"Dry\nmass",
]
for simDir in allDir:
simOutDir = os.path.join(simDir, "simOut")
initialTime = TableReader(os.path.join(
simOutDir, "Main")).readAttribute("initialTime")
time = TableReader(os.path.join(
simOutDir, "Main")).readColumn("time") - initialTime
mass = TableReader(os.path.join(simOutDir, "Mass"))
for idx, massType in enumerate(massNames):
massToPlot = mass.readColumn(massNames[idx])
f = plt.figure(figsize=(1.25, 0.8), frameon=False)
ax = f.add_axes([0, 0, 1, 1])
ax.axis("off")
ax.plot(time, massToPlot, linewidth=2)
ax.set_ylim([massToPlot.min(), massToPlot.max()])
ax.set_xlim([time.min(), time.max()])
exportFigure(
plt, plotOutDir,
"r01_{}_gen{}".format(massType, allDir.index(simDir)))
plt.close("all")
def do_plot(self, simOutDir, plotOutDir, plotOutFileName, simDataFile,
validationDataFile, metadata):
if not os.path.isdir(simOutDir):
raise Exception, "simOutDir does not currently exist as a directory"
if not os.path.exists(plotOutDir):
os.mkdir(plotOutDir)
# Load data from KB
sim_data = cPickle.load(open(simDataFile, "rb"))
nAvogadro = sim_data.constants.nAvogadro
moleculeIds = sim_data.moleculeGroups.aaIDs
moleculeIds.append('GTP[c] (translation)')
moleculeIds.extend(sim_data.moleculeGroups.ntpIds)
# Load time
initialTime = TableReader(os.path.join(
simOutDir, "Main")).readAttribute("initialTime")
time = TableReader(os.path.join(
simOutDir, "Main")).readColumn("time") - initialTime
# Load data
growthLimitsDataFile = TableReader(
os.path.join(simOutDir, "GrowthLimits"))
# Translation
gtpPoolSize = growthLimitsDataFile.readColumn("gtpPoolSize")
gtpRequestSize = growthLimitsDataFile.readColumn("gtpRequestSize")
gtpAllocated = growthLimitsDataFile.readColumn("gtpAllocated")
gtpUsed = growthLimitsDataFile.readColumn("gtpUsed")
aaPoolSize = growthLimitsDataFile.readColumn("aaPoolSize")
aaRequestSize = growthLimitsDataFile.readColumn("aaRequestSize")
aaAllocated = growthLimitsDataFile.readColumn("aaAllocated")
aasUsed = growthLimitsDataFile.readColumn("aasUsed")
# Transcription
ntpPoolSize = growthLimitsDataFile.readColumn("ntpPoolSize")
ntpRequestSize = growthLimitsDataFile.readColumn("ntpRequestSize")
ntpAllocated = growthLimitsDataFile.readColumn("ntpAllocated")
ntpUsed = growthLimitsDataFile.readColumn("ntpUsed")
# Create aggregate
poolSize = np.hstack(
(aaPoolSize, gtpPoolSize.reshape(gtpPoolSize.size,
1), ntpPoolSize))
requestSize = np.hstack(
(aaRequestSize, gtpRequestSize.reshape(gtpPoolSize.size,
1), ntpRequestSize))
allocated = np.hstack(
(aaAllocated, gtpAllocated.reshape(gtpPoolSize.size,
1), ntpAllocated))
used = np.hstack((aasUsed, gtpUsed.reshape(gtpPoolSize.size,
1), ntpUsed))
growthLimitsDataFile.close()
# Load ATP usage
# ATPusageListenerFile = TableReader(os.path.join(simOutDir, "ATPhydrolyzedUsageListener"))
# atpsHydrolyzed = ATPusageListenerFile.readColumn('atpsHydrolyzed')
# ATPusageListenerFile.close()
# bulkMolecules = TableReader(os.path.join(simOutDir, "BulkMolecules"))
# bulkMoleculeIds = bulkMolecules.readAttribute("objectNames")
# bulkMolecules.close()
# Plot
fig = plt.figure(figsize=(11, 11))
# Plot GTP consumption
# plt.rc('xtick', labelsize=5)
# plt.rc('ytick', labelsize=5)
# plt.plot(time / 60., gtpUsed)
# plt.plot(time / 60., atpsHydrolyzed)
# plt.xlabel("Time (min)", fontsize = 5)
# plt.ylabel("GTP counts", fontsize = 5)
print "GTP consumption by polypeptide elongation = %d" % np.sum(
gtpUsed)
# print "ATP hydrolyzed for non-growth associated maintenance = %d" % np.sum(atpsHydrolyzed)
for idx in range(len(moleculeIds)):
ax = plt.subplot(7, 4, idx + 1)
ax.plot(time / 60.,
poolSize[:, idx],
linewidth=2,
label="pool size",
color='k')
ax.plot(time / 60.,
requestSize[:, idx],
linewidth=2,
label="request size",
color='b')
ax.plot(time / 60.,
allocated[:, idx],
linewidth=2,
label="allocated",
color='r',
linestyle='--')
ax.plot(time / 60.,
used[:, idx],
linewidth=2,
label="used",
color="c",
linestyle=":")
# Highlight title if request is greater than pool
bbox = None
if (poolSize < requestSize)[:, idx].any() or (
allocated < requestSize)[:, idx].any():
bbox = {'facecolor': 'red', 'alpha': 0.5, 'pad': 10}
elif (used[:, idx] < allocated[:, idx]).any():
bbox = {'facecolor': 'orange', 'alpha': 0.5, 'pad': 10}
ax.set_title(moleculeIds[idx], bbox=bbox)
# Set ticks so this is all easy to read
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('none')
ax.tick_params(which='both', direction='out', labelsize=10)
ax.set_xticks([time.min() / 60., time.max() / 60.])
ax.set_yticks([
0.,
np.max([
poolSize[:, idx].max(), requestSize[:, idx].max(),
allocated[:, idx].max()
])
])
# Create legend
ax = plt.subplot(7, 4, len(moleculeIds) + 1)
ax.plot(0, 0, linewidth=2, label="pool size", color='k')
ax.plot(0, 0, linewidth=2, label="request size", color='b')
ax.plot(0,
0,
linewidth=2,
label="allocated",
color='r',
linestyle='--')
ax.plot(0, 0, linewidth=2, label="used", color="c", linestyle=':')
ax.legend(loc=10, prop={'size': 10})
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none')
ax.set_xticks([])
ax.set_yticks([])
ax.set_title("Highlights process under-usage",
fontsize=12,
bbox={
'facecolor': 'orange',
'alpha': 0.5,
'pad': 10
})
ax.set_xlabel("Highlights pool/allocation limit",
fontsize=12,
bbox={
'facecolor': 'red',
'alpha': 0.5,
'pad': 10
})
# Save
plt.subplots_adjust(hspace=0.5, wspace=0.5)
exportFigure(plt, plotOutDir, plotOutFileName, metadata)
plt.close("all")
