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execution) Because: 1. It's nicer to show all algorithms on all installs, and give a descriptive error message to users when they try to run algorithms which depend on Plotly if the library is missing. Otherwise on some installs these algorithms are just missing for no apparent reason. 2. The plotly library takes a long time to load on windows (3-4 seconds), so by moving this load to an on-demand load at time of algorithm execution we can shave a few seconds off the QGIS startup time for ALL users.
122 lines
4.9 KiB
Python
122 lines
4.9 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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BarPlot.py
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---------------------
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Date : March 2015
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Copyright : (C) 2017 by Matteo Ghetta
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Email : matteo dot ghetta at gmail dot com
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***************************************************************************
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* *
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* This program is free software; you can redistribute it and/or modify *
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* it under the terms of the GNU General Public License as published by *
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* the Free Software Foundation; either version 2 of the License, or *
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* (at your option) any later version. *
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* *
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***************************************************************************
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"""
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__author__ = 'Matteo Ghetta'
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__date__ = 'March 2017'
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__copyright__ = '(C) 2017, Matteo Ghetta'
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import warnings
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from qgis.core import (QgsProcessingException,
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QgsProcessingParameterFeatureSource,
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QgsProcessingParameterField,
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QgsProcessingParameterEnum,
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QgsProcessingParameterFileDestination,
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QgsFeatureRequest)
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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from processing.tools import vector
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class BoxPlot(QgisAlgorithm):
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INPUT = 'INPUT'
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OUTPUT = 'OUTPUT'
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NAME_FIELD = 'NAME_FIELD'
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VALUE_FIELD = 'VALUE_FIELD'
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MSD = 'MSD'
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def group(self):
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return self.tr('Graphics')
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def groupId(self):
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return 'graphics'
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def __init__(self):
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super().__init__()
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def initAlgorithm(self, config=None):
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self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
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self.tr('Input layer')))
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self.addParameter(QgsProcessingParameterField(self.NAME_FIELD,
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self.tr('Category name field'),
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parentLayerParameterName=self.INPUT,
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type=QgsProcessingParameterField.Any))
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self.addParameter(QgsProcessingParameterField(self.VALUE_FIELD,
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self.tr('Value field'),
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parentLayerParameterName=self.INPUT,
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type=QgsProcessingParameterField.Numeric))
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msd = [self.tr('Show Mean'),
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self.tr('Show Standard Deviation'),
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self.tr('Don\'t show Mean and Standard Deviation')
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]
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self.addParameter(QgsProcessingParameterEnum(
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self.MSD,
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self.tr('Additional Statistic Lines'),
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options=msd, defaultValue=0))
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self.addParameter(QgsProcessingParameterFileDestination(self.OUTPUT, self.tr('Box plot'), self.tr('HTML files (*.html)')))
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def name(self):
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return 'boxplot'
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def displayName(self):
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return self.tr('Box plot')
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def processAlgorithm(self, parameters, context, feedback):
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try:
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# importing plotly throws Python warnings from within the library - filter these out
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with warnings.catch_warnings():
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warnings.filterwarnings("ignore", category=ResourceWarning)
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warnings.filterwarnings("ignore", category=ImportWarning)
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import plotly as plt
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import plotly.graph_objs as go
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except ImportError:
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raise QgsProcessingException(self.tr('This algorithm requires the Python “plotly” library. Please install this library and try again.'))
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source = self.parameterAsSource(parameters, self.INPUT, context)
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if source is None:
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raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
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namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
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valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)
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output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
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values = vector.values(source, valuefieldname)
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x_index = source.fields().lookupField(namefieldname)
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x_var = vector.convert_nulls([i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([x_index]))], '<NULL>')
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msdIndex = self.parameterAsEnum(parameters, self.MSD, context)
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msd = True
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if msdIndex == 1:
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msd = 'sd'
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elif msdIndex == 2:
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msd = False
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data = [go.Box(
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x=x_var,
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y=values[valuefieldname],
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boxmean=msd)]
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plt.offline.plot(data, filename=output, auto_open=False)
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return {self.OUTPUT: output}
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