def plotArray(self, hitDataParam, filename, plotDir=None, labeledPosD=None,
title='', type='png',
label_colors = True, colVecL=None, legend_plot = False, legend_filename=None,
control_color='black', numeric_as_int = False,
grid=True, max_val=0.3, min_val=0.0, cut_data = True):
if plotDir is None:
plotDir = self.plotDir
full_filename = os.path.join(plotDir, filename)
#hitData = copy.deepcopy(hitDataParam)
hitData = hitDataParam
#nrow = len(hitData)
#ncol = len(hitData[0])
nrow = self.nb_row
ncol = self.nb_col
xL = range(1, self.nb_col + 1)
yL = range(1, self.nb_row + 1)
rdev = plot_utilities.RDevice(name = full_filename, title=title, plotType=type,
width=640, height=250)
if label_colors:
# in this case, the data is considered to consist of labels
labelL = []
for i in range(nrow):
for j in range(ncol):
if hitData[i][j] not in labelL:
labelL.append(hitData[i][j])
if colVecL is None:
colVecL = r.rainbow(len(labelL))
colBreaksL = range(len(colVecL) + 1)
if legend_plot:
self.plotLabelLegend(colVecL, plotType=type, filename=legend_filename)
else:
# in this case, the data is numeric.
if cut_data:
max_rel_cell_count = max_val
min_rel_cell_count = 0.0
for i in range(nrow):
for j in range(ncol):
hitData[i][j] = max(min_rel_cell_count, min(max_rel_cell_count, hitData[i][j]))
else:
max_rel_cell_count = max([max(x) for x in hitData.tolist() ])
min_rel_cell_count = min([min(x) for x in hitData.tolist() ])
if numeric_as_int:
nb_colors = max_rel_cell_count
else:
nb_colors = 500
if colVecL is None:
pattern = [(0,0,0),(0.7,0,0),(1,1,0),(1,1,1)]
colVecL = colors.make_colors(pattern, nb_colors)
colBreaksL = [1.0/ (len(colVecL) - 1) * x * (max_rel_cell_count - min_rel_cell_count) + min_rel_cell_count for x in range(len(colVecL) + 1)]
if legend_plot:
self.plotNumLegend(colVecL, colBreaksL, 16, filename=legend_filename, type=type, int_labels=numeric_as_int, legendDir = plotDir)
axisSize = .8
r("par(mar=c(1.6,1.6,0.1,0.1))")
r.image(xL, yL, r.t(hitData), axes = False, ann=False, cex=1, col=colVecL, breaks=colBreaksL)
r.box()
if not labeledPosD is None:
for label in labeledPosD.keys():
posL = labeledPosD[label]
if len(posL) > 0:
xlL = [(int(x)-1) % self.nb_col + 1 for x in posL]
ylL = [(int(x)-1) / self.nb_col + 1 for x in posL]
r.points(xlL, ylL, pch=label, col=control_color, cex=axisSize)
print
print xlL
print ylL
print
# grid
if grid:
for i in range(self.nb_col):
r.abline(h=i+.5, lty=3, lwd=1, col='grey')
for i in range(self.nb_row):
r.abline(v=i+.5, lty=3, lwd=1, col='grey')
r.axis(1, at=xL, labels=[str(x) for x in xL], tick=False, line=-1.0, cex_axis=axisSize)
r.axis(2, at=yL, labels=[str(y) for y in yL], tick=False, line=-1.0, cex_axis=axisSize)
rdev.close()
return
def plotBundle(self, bundleD, full_filename, colorsD=None, bundlePointsD=None, legendL=None, title=None, y_max=None):
if y_max is None:
y_max = 0.4
if legendL is None:
legendL = bundleD.keys()
legendL.sort()
if title is None:
title = 'data'
bundleIdL = bundleD.keys()
bundleIdL.sort()
if colorsD is None:
colorsL = r.rainbow(len(bundleIdL))
colorsD = dict(zip(bundleIdL, colorsL))
colorsL = [colorsD[x] for x in bundleIdL]
time_min = min([len(bundleD[x]) for x in bundleD.keys()])
timeVec = [0.5 * x for x in range(time_min)]
try:
r.png(full_filename, width=800, height=600)
oldPar = r.par(xpd = True, mar = [x + y for (x,y) in zip(r.par()['mar'], [0,0,0,6])])
print 'plot %s' % full_filename
r.plot(timeVec, timeVec,
type='n',
main=title, ylim=(0, y_max),
xlab="time in hours after transfection", ylab="Relative Cell Counts",
pch=20, lwd=1, lty = 1,
cex=1.0, cex_lab=1.2, cex_main=1.5)
for bundleId in bundleIdL:
if not bundlePointsD is None:
r.points(timeVec, bundlePointsD[bundleId],
col=colorsD[bundleId], pch=20,
lwd=1)
r.lines(timeVec, bundlePointsD[bundleId],
col=colorsD[bundleId],
lwd=1, lty = 1)
r.lines(timeVec, bundleD[bundleId],
col=colorsD[bundleId],
lwd=3, lty = 1)
r.legend(max(timeVec) * 1.1, y_max, legend=legendL, fill=colorsL, cex=1.0, bg= 'whitesmoke')
r.par(oldPar)
r.grid(col="darkgrey")
r.dev_off()
except:
r.dev_off()
print full_filename + ' has not been printed.'
return
