def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT))
nbins = self.getParameterValue(self.BINS)
outputplot = self.getOutputValue(self.PLOT)
outputtable = self.getOutputFromName(self.TABLE)
values = raster.scanraster(layer, progress)
# ALERT: this is potentially blocking if the layer is too big
plt.close()
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
(n, bins, values) = plt.hist(valueslist, nbins)
fields = [QgsField('CENTER_VALUE', QVariant.Double),
QgsField('NUM_ELEM', QVariant.Double)]
writer = outputtable.getTableWriter(fields)
for i in range(len(values)):
writer.addRecord([str(bins[i]) + '-' + str(bins[i + 1]), n[i]])
plotFilename = outputplot + '.png'
lab.savefig(plotFilename)
with open(outputplot, 'w') as f:
f.write('<html><img src="' + plotFilename + '"/></html>')
def processAlgorithm(self, progress):
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
uri = self.getParameterValue(self.INPUT)
layer = dataobjects.getObjectFromUri(uri)
values = raster.scanraster(layer, progress)
n = 0
nodata = 0
mean = 0
M2 = 0
sum = 0
minvalue = None
maxvalue = None
for v in values:
if v is not None:
sum += v
n = n + 1
delta = v - mean
mean = mean + delta / n
M2 = M2 + delta * (v - mean)
if minvalue is None:
minvalue = v
maxvalue = v
else:
minvalue = min(v, minvalue)
maxvalue = max(v, maxvalue)
else:
nodata += 1
variance = M2 / (n - 1)
stddev = math.sqrt(variance)
data = []
data.append('Valid cells: ' + unicode(n))
data.append('No-data cells: ' + unicode(nodata))
data.append('Minimum value: ' + unicode(minvalue))
data.append('Maximum value: ' + unicode(maxvalue))
data.append('Sum: ' + unicode(sum))
data.append('Mean value: ' + unicode(mean))
data.append('Standard deviation: ' + unicode(stddev))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, n)
self.setOutputValue(self.NO_DATA_COUNT, nodata)
self.setOutputValue(self.MIN, minvalue)
self.setOutputValue(self.MAX, maxvalue)
self.setOutputValue(self.SUM, sum)
self.setOutputValue(self.MEAN, mean)
self.setOutputValue(self.STD_DEV, stddev)
def processAlgorithm(self, parameters, context, feedback):
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
uri = self.getParameterValue(self.INPUT)
layer = QgsProcessingUtils.mapLayerFromString(uri, context)
values = raster.scanraster(layer, feedback)
n = 0
nodata = 0
mean = 0
M2 = 0
sum = 0
minvalue = None
maxvalue = None
for v in values:
if v is not None:
sum += v
n = n + 1
delta = v - mean
mean = mean + delta / n
M2 = M2 + delta * (v - mean)
if minvalue is None:
minvalue = v
maxvalue = v
else:
minvalue = min(v, minvalue)
maxvalue = max(v, maxvalue)
else:
nodata += 1
variance = M2 / (n - 1)
stddev = math.sqrt(variance)
data = []
data.append('Valid cells: ' + str(n))
data.append('No-data cells: ' + str(nodata))
data.append('Minimum value: ' + str(minvalue))
data.append('Maximum value: ' + str(maxvalue))
data.append('Sum: ' + str(sum))
data.append('Mean value: ' + str(mean))
data.append('Standard deviation: ' + str(stddev))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, n)
self.setOutputValue(self.NO_DATA_COUNT, nodata)
self.setOutputValue(self.MIN, minvalue)
self.setOutputValue(self.MAX, maxvalue)
self.setOutputValue(self.SUM, sum)
self.setOutputValue(self.MEAN, mean)
self.setOutputValue(self.STD_DEV, stddev)
def processAlgorithm(self, progress):
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
uri = self.getParameterValue(self.INPUT)
layer = QGisLayers.getObjectFromUri(uri)
values = raster.scanraster(layer, progress)
n = 0
nodata = 0
mean = 0
M2 = 0
sum = 0
minvalue = None
maxvalue = None
for v in values:
if v is not None:
sum += v
n = n + 1
delta = v - mean
mean = mean + delta / n
M2 = M2 + delta * (v - mean)
if minvalue is None:
minvalue = v
maxvalue = v
else:
minvalue = min(v, minvalue)
maxvalue = max(v, maxvalue)
else:
nodata += 1
variance = M2 / (n - 1)
stddev = math.sqrt(variance)
data = []
data.append("Valid cells: " + unicode(n))
data.append("No-data cells: " + unicode(nodata))
data.append("Minimum value: " + unicode(minvalue))
data.append("Maximum value: " + unicode(maxvalue))
data.append("Sum: " + unicode(sum))
data.append("Mean value: " + unicode(mean))
data.append("Standard deviation: " + unicode(stddev))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, n)
self.setOutputValue(self.NO_DATA_COUNT, nodata)
self.setOutputValue(self.MIN, minvalue)
self.setOutputValue(self.MAX, maxvalue)
self.setOutputValue(self.SUM, sum)
self.setOutputValue(self.MEAN, mean)
self.setOutputValue(self.STD_DEV, stddev)
def processAlgorithm(self, feedback):
layer = dataobjects.getObjectFromUri(self.getParameterValue(
self.INPUT))
nbins = self.getParameterValue(self.BINS)
output = self.getOutputValue(self.PLOT)
# ALERT: this is potentially blocking if the layer is too big
values = raster.scanraster(layer, feedback)
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
data = [go.Histogram(x=valueslist, nbinsx=nbins)]
plt.offline.plot(data, filename=output, auto_open=False)
def processAlgorithm(self, parameters, context, feedback):
layer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.INPUT), context)
nbins = self.getParameterValue(self.BINS)
output = self.getOutputValue(self.PLOT)
# ALERT: this is potentially blocking if the layer is too big
values = raster.scanraster(layer, feedback)
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
data = [go.Histogram(x=valueslist,
nbinsx=nbins)]
plt.offline.plot(data, filename=output, auto_open=False)
def processAlgorithm(self, parameters, context, feedback):
layer = self.parameterAsRasterLayer(parameters, self.INPUT, context)
band = self.parameterAsInt(parameters, self.BAND, context)
nbins = self.parameterAsInt(parameters, self.BINS, context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
# ALERT: this is potentially blocking if the layer is too big
values = raster.scanraster(layer, feedback, band)
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
data = [go.Histogram(x=valueslist, nbinsx=nbins)]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, parameters, context, feedback):
layer = self.parameterAsRasterLayer(parameters, self.INPUT, context)
band = self.parameterAsInt(parameters, self.BAND, context)
nbins = self.parameterAsInt(parameters, self.BINS, context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
# ALERT: this is potentially blocking if the layer is too big
values = raster.scanraster(layer, feedback, band)
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
data = [go.Histogram(x=valueslist,
nbinsx=nbins)]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, progress):
uri = self.getParameterValue(self.INPUT)
layer = QGisLayers.getObjectFromUri(uri)
outputplot = self.getOutputValue(self.PLOT)
outputtable = self.getOutputFromName(self.TABLE)
values = raster.scanraster(layer, progress)
nbins = self.getParameterValue(self.BINS)
#ALERT:this is potentially blocking if the layer is too big
plt.close()
valueslist = []
for v in values:
if v is not None:
valueslist.append(v)
n, bins, values = plt.hist(valueslist, nbins)
fields = [QgsField("CENTER_VALUE", QVariant.Double), QgsField("NUM_ELEM", QVariant.Double)]
writer = outputtable.getTableWriter(fields)
for i in xrange(len(values)):
writer.addRecord([str(bins[i]) + "-" + str(bins[i+1]) , n[i]])
plotFilename = outputplot +".png"
lab.savefig(plotFilename)
f = open(outputplot, "w")
f.write("<img src=\"" + plotFilename + "\"/>")
f.close()