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