def __init__(self, parent, identifiers, listOfArrays):
TableBase.__init__(self, parent)
self.resize(1, 2 * len(identifiers))
self.setColumnLabels(statisticsLabels(identifiers))
mean, stdDev = meanStdDev(listOfArrays)
row = 0
self.SetRowLabelValue(row, str(row + 1))
col = 0
for i in range(len(mean)):
self.SetCellValue(row, col, '%g' % mean[i])
col += 1
self.SetCellValue(row, col, '%g' % stdDev[i])
col += 1
def __init__(self, parent, identifiers, times, listOfArrays):
TableBase.__init__(self, parent)
self.resize(len(times), 1 + 2 * len(identifiers))
self.setColumnLabels(['Time'] + statisticsLabels(identifiers))
mean, stdDev = meanStdDev(listOfArrays)
row = 0
for frame in range(len(times)):
self.SetRowLabelValue(row, str(row + 1))
col = 0
# Time.
self.SetCellValue(row, col, '%g' % times[frame])
col += 1
for i in range(len(mean[frame])):
self.SetCellValue(row, col, '%g' % mean[frame][i])
col += 1
self.SetCellValue(row, col, '%g' % stdDev[frame][i])
col += 1
row += 1
def framesBinnedStat(self, model, output, selected, writer):
# Whether to output the std. dev.
stdDev = [self.grid.GetCellValue(i, 1) for i in selected]
# The headers.
headers = ['Time']
for i in selected:
identifier = model.reactions[output.recordedReactions[i]].id
headers.append('m(%s)' % identifier)
if stdDev[i]:
headers.append('s(%s)' % identifier)
writer.writerow(headers)
# Write each data row.
for f in range(len(output.frameTimes) - 1):
row = [output.frameTimes[f]]
for s in selected:
data = [x[f + 1, s] - x[f, s] for x in output.reactionCounts]
# If the standard deviation box is checked.
if stdDev[s]:
row.extend(list(meanStdDev(data)))
else:
row.append(mean(data))
writer.writerow(row)
def __init__(self, parent, identifiers, times, listOfArrays):
TableBase.__init__(self, parent)
assert len(times) > 1
self.resize(len(times) - 1, 1 + 2 * len(identifiers))
self.setColumnLabels(['Interval'] + statisticsLabels(identifiers))
mean, stdDev = meanStdDev([x[1:] - x[:-1] for x in listOfArrays])
row = 0
for frame in range(len(times) - 1):
self.SetRowLabelValue(row, str(row + 1))
col = 0
# Interval.
self.SetCellValue(row, col, '%g to %g' %
(times[frame], times[frame + 1]))
col += 1
for i in range(len(mean[frame])):
self.SetCellValue(row, col, '%g' % mean[frame][i])
col += 1
self.SetCellValue(row, col, '%g' % stdDev[frame][i])
col += 1
row += 1
def plotFrames(self, output):
# Record the kind of plot to generate.
isSpeciesSelected = self.species.GetValue()
isCumulativeReactionsSelected = self.cumulativeReactions.GetValue()
#isBinnedReactionsSelected = self.binnedReactions.GetValue()
isTrajectoriesSelected = self.trajectories.GetValue()
isMeanSelected = self.mean.GetValue()
#isStdDevSelected = self.stdDev.GetValue()
# Check that at least one row has been selected.
if not self.grid.areAnyItemsSelected():
wx.MessageBox('No rows are selected.', 'Error.')
return
# The items to plot.
indices = self.grid.getCheckedItems()
if not indices:
return
if isTrajectoriesSelected:
# Plot each trajectory.
for i in range(len(output.populations)):
for index in indices:
if isSpeciesSelected:
p = output.populations[i][:, index]
times = output.frameTimes
elif isCumulativeReactionsSelected:
p = output.reactionCounts[i][:, index]
times = output.frameTimes
else: # Binned reaction counts.
p = output.reactionCounts[i][1:, index] - \
output.reactionCounts[i][:-1, index]
# Midpoints.
times = 0.5 * (output.frameTimes[0:-1] +
output.frameTimes[1:])
if self.grid.useMarkers(index):
plot(times, p,
**self.grid.getLineAndMarkerStyles(index))
else:
plot(times, p, **self.grid.getLineStyles(index))
elif isMeanSelected:
# Plot the mean and optionally the standard deviation.
for index in indices:
if isSpeciesSelected:
data = [x[:, index] for x in output.populations]
times = output.frameTimes
elif isCumulativeReactionsSelected:
data = [x[:, index] for x in output.reactionCounts]
times = output.frameTimes
else: # Binned reaction counts.
data = [x[1:, index] - x[:-1, index] for x in
output.reactionCounts]
# Midpoints.
times = output.frameTimes
times = 0.5 * (times[0:-1] + times[1:])
# If the standard deviation box is checked.
if self.grid.GetCellValue(index, 1):
y, yerr = meanStdDev(data)
else:
y = mean(data)
yerr = None
if self.grid.useMarkers(index):
errorbar(times, y, yerr = yerr,
**self.grid.getLineAndMarkerStyles(index))
else:
errorbar(times, y, yerr=yerr,
**self.grid.getLineStyles(index))
else: # isStdDevSelected
# Plot the standard deviation.
for index in indices:
if isSpeciesSelected:
data = [x[:, index] for x in output.populations]
times = output.frameTimes
elif isCumulativeReactionsSelected:
data = [x[:, index] for x in output.reactionCounts]
times = output.frameTimes
else: # Binned reaction counts.
data = [x[1:, index] - x[:-1, index] for x in
output.reactionCounts]
# Midpoints.
times = output.frameTimes
times = 0.5 * (times[0:-1] + times[1:])
# If the standard deviation box is checked.
y, yerr = meanStdDev(data)
if self.grid.useMarkers(index):
plot(times, yerr, **self.grid.getLineAndMarkerStyles(index))
else:
plot(times, yerr, **self.grid.getLineStyles(index))
self._showLegendAndLabels(indices)
self.options.setLimits()
draw()