def testConvertNulls(self):
self.assertEqual(vector.convert_nulls([]), [])
self.assertEqual(vector.convert_nulls([], '_'), [])
self.assertEqual(vector.convert_nulls([NULL]), [None])
self.assertEqual(vector.convert_nulls([NULL], '_'), ['_'])
self.assertEqual(vector.convert_nulls([NULL], -1), [-1])
self.assertEqual(vector.convert_nulls([1, 2, 3]), [1, 2, 3])
self.assertEqual(vector.convert_nulls([1, None, 3]), [1, None, 3])
self.assertEqual(vector.convert_nulls([1, NULL, 3, NULL]), [1, None, 3, None])
self.assertEqual(vector.convert_nulls([1, NULL, 3, NULL], '_'), [1, '_', 3, '_'])
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
values = vector.values(source, valuefieldname)
x_index = source.fields().lookupField(namefieldname)
x_var = vector.convert_nulls([i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([x_index]))], '<NULL>')
msdIndex = self.parameterAsEnum(parameters, self.MSD, context)
msd = True
if msdIndex == 1:
msd = 'sd'
elif msdIndex == 2:
msd = False
data = [go.Box(
x=x_var,
y=values[valuefieldname],
boxmean=msd)]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
namefieldname = self.parameterAsString(parameters, self.NAME_FIELD,
context)
valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD,
context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
values = vector.values(source, valuefieldname)
x_index = source.fields().lookupField(namefieldname)
x_var = vector.convert_nulls([
i[namefieldname]
for i in source.getFeatures(QgsFeatureRequest().setFlags(
QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([x_index]))
], '<NULL>')
msdIndex = self.parameterAsEnum(parameters, self.MSD, context)
msd = True
if msdIndex == 1:
msd = 'sd'
elif msdIndex == 2:
msd = False
data = [go.Box(x=x_var, y=values[valuefieldname], boxmean=msd)]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, parameters, context, feedback):
try:
# importing plotly throws Python warnings from within the library - filter these out
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=ResourceWarning)
warnings.filterwarnings("ignore", category=ImportWarning)
import plotly as plt
import plotly.graph_objs as go
except ImportError:
raise QgsProcessingException(
QCoreApplication.translate(
'BoxPlot',
'This algorithm requires the Python “plotly” library. Please install this library and try again.'
))
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
namefieldname = self.parameterAsString(parameters, self.NAME_FIELD,
context)
valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD,
context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
values = vector.values(source, valuefieldname)
x_index = source.fields().lookupField(namefieldname)
x_var = vector.convert_nulls([
i[namefieldname]
for i in source.getFeatures(QgsFeatureRequest().setFlags(
QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([x_index]))
], '<NULL>')
msdIndex = self.parameterAsEnum(parameters, self.MSD, context)
msd = True
if msdIndex == 1:
msd = 'sd'
elif msdIndex == 2:
msd = False
data = [go.Box(x=x_var, y=values[valuefieldname], boxmean=msd)]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
values = vector.values(source, valuefieldname)
x_var = vector.convert_nulls([i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry))], '<NULL>')
data = [go.Bar(x=x_var,
y=values[valuefieldname])]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)
output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
values = vector.values(source, valuefieldname)
x_var = vector.convert_nulls([i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry))], '<NULL>')
data = [go.Bar(x=x_var,
y=values[valuefieldname])]
plt.offline.plot(data, filename=output, auto_open=False)
return {self.OUTPUT: output}
