analysis/webservice/algorithms/HofMoeller.py [263:359]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - def createHoffmueller(self, data, coordSeries, timeSeries, coordName, title, interpolate='nearest'): cmap = cm.coolwarm # ls = LightSource(315, 45) # rgb = ls.shade(data, cmap) fig, ax = plt.subplots() fig.set_size_inches(11.0, 8.5) cax = ax.imshow(data, interpolation=interpolate, cmap=cmap) def yFormatter(y, pos): if y < len(coordSeries): return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.) else: return "" def xFormatter(x, pos): if x < len(timeSeries): return timeSeries[int(x)].strftime('%b %Y') else: return "" ax.xaxis.set_major_formatter(FuncFormatter(xFormatter)) ax.yaxis.set_major_formatter(FuncFormatter(yFormatter)) ax.set_title(title) ax.set_ylabel(coordName) ax.set_xlabel('Date') fig.colorbar(cax) fig.autofmt_xdate() labels = ['point {0}'.format(i + 1) for i in range(len(data))] # plugins.connect(fig, plugins.MousePosition(fontsize=14)) tooltip = mpld3.plugins.PointLabelTooltip(cax, labels=labels) sio = StringIO() plt.savefig(sio, format='png') return sio.getvalue() def createLongitudeHoffmueller(self, res, meta): lonSeries = [m['longitude'] for m in res[0]['lons']] timeSeries = [datetime.fromtimestamp(m['time'] / 1000) for m in res] data = np.zeros((len(lonSeries), len(timeSeries))) plotSeries = self.computeOptions().get_plot_series(default="avg") if self.computeOptions is not None else None if plotSeries is None: plotSeries = "avg" for t in range(0, len(timeSeries)): timeSet = res[t] for l in range(0, len(lonSeries)): latSet = timeSet['lons'][l] value = latSet[plotSeries] data[len(lonSeries) - l - 1][t] = value title = meta['title'] source = meta['source'] dateRange = "%s - %s" % (timeSeries[0].strftime('%b %Y'), timeSeries[-1].strftime('%b %Y')) return self.createHoffmueller(data, lonSeries, timeSeries, "Longitude", "%s\n%s\n%s" % (title, source, dateRange), interpolate='nearest') def createLatitudeHoffmueller(self, res, meta): latSeries = [m['latitude'] for m in res[0]['lats']] timeSeries = [datetime.fromtimestamp(m['time'] / 1000) for m in res] data = np.zeros((len(latSeries), len(timeSeries))) plotSeries = self.computeOptions().get_plot_series(default="avg") if self.computeOptions is not None else None if plotSeries is None: plotSeries = "avg" for t in range(0, len(timeSeries)): timeSet = res[t] for l in range(0, len(latSeries)): latSet = timeSet['lats'][l] value = latSet[plotSeries] data[len(latSeries) - l - 1][t] = value title = meta['title'] source = meta['source'] dateRange = "%s - %s" % (timeSeries[0].strftime('%b %Y'), timeSeries[-1].strftime('%b %Y')) return self.createHoffmueller(data, latSeries, timeSeries, "Latitude", title="%s\n%s\n%s" % (title, source, dateRange), interpolate='nearest') def toImage(self): res = self.results() meta = self.meta() if self.__type == HoffMoellerResults.LATITUDE: return self.createLatitudeHoffmueller(res, meta) elif self.__type == HoffMoellerResults.LONGITUDE: return self.createLongitudeHoffmueller(res, meta) else: raise Exception("Unsupported HoffMoeller Plot Type") - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - analysis/webservice/algorithms_spark/HofMoellerSpark.py [457:553]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - def createHoffmueller(self, data, coordSeries, timeSeries, coordName, title, interpolate='nearest'): cmap = cm.coolwarm # ls = LightSource(315, 45) # rgb = ls.shade(data, cmap) fig, ax = plt.subplots() fig.set_size_inches(11.0, 8.5) cax = ax.imshow(data, interpolation=interpolate, cmap=cmap) def yFormatter(y, pos): if y < len(coordSeries): return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.) else: return "" def xFormatter(x, pos): if x < len(timeSeries): return timeSeries[int(x)].strftime('%b %Y') else: return "" ax.xaxis.set_major_formatter(FuncFormatter(xFormatter)) ax.yaxis.set_major_formatter(FuncFormatter(yFormatter)) ax.set_title(title) ax.set_ylabel(coordName) ax.set_xlabel('Date') fig.colorbar(cax) fig.autofmt_xdate() labels = ['point {0}'.format(i + 1) for i in range(len(data))] # plugins.connect(fig, plugins.MousePosition(fontsize=14)) tooltip = mpld3.plugins.PointLabelTooltip(cax, labels=labels) sio = StringIO() plt.savefig(sio, format='png') return sio.getvalue() def createLongitudeHoffmueller(self, res, meta): lonSeries = [m['longitude'] for m in res[0]['lons']] timeSeries = [datetime.fromtimestamp(m['time'] / 1000) for m in res] data = np.zeros((len(lonSeries), len(timeSeries))) plotSeries = self.computeOptions().get_plot_series(default="avg") if self.computeOptions is not None else None if plotSeries is None: plotSeries = "avg" for t in range(0, len(timeSeries)): timeSet = res[t] for l in range(0, len(lonSeries)): latSet = timeSet['lons'][l] value = latSet[plotSeries] data[len(lonSeries) - l - 1][t] = value title = meta['title'] source = meta['source'] dateRange = "%s - %s" % (timeSeries[0].strftime('%b %Y'), timeSeries[-1].strftime('%b %Y')) return self.createHoffmueller(data, lonSeries, timeSeries, "Longitude", "%s\n%s\n%s" % (title, source, dateRange), interpolate='nearest') def createLatitudeHoffmueller(self, res, meta): latSeries = [m['latitude'] for m in res[0]['lats']] timeSeries = [datetime.fromtimestamp(m['time'] / 1000) for m in res] data = np.zeros((len(latSeries), len(timeSeries))) plotSeries = self.computeOptions().get_plot_series(default="avg") if self.computeOptions is not None else None if plotSeries is None: plotSeries = "avg" for t in range(0, len(timeSeries)): timeSet = res[t] for l in range(0, len(latSeries)): latSet = timeSet['lats'][l] value = latSet[plotSeries] data[len(latSeries) - l - 1][t] = value title = meta['title'] source = meta['source'] dateRange = "%s - %s" % (timeSeries[0].strftime('%b %Y'), timeSeries[-1].strftime('%b %Y')) return self.createHoffmueller(data, latSeries, timeSeries, "Latitude", title="%s\n%s\n%s" % (title, source, dateRange), interpolate='nearest') def toImage(self): res = self.results() meta = self.meta() if self.__type == HoffMoellerResults.LATITUDE: return self.createLatitudeHoffmueller(res, meta) elif self.__type == HoffMoellerResults.LONGITUDE: return self.createLongitudeHoffmueller(res, meta) else: raise Exception("Unsupported HoffMoeller Plot Type") - 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