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			108 lines
		
	
	
		
			4.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			108 lines
		
	
	
		
			4.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # -*- coding: utf-8 -*-
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| 
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| """
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| ***************************************************************************
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|     MeanAndStdDevPlot.py
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|     ---------------------
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|     Date                 : January 2013
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|     Copyright            : (C) 2013 by Victor Olaya
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|     Email                : volayaf 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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| 
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| __author__ = 'Victor Olaya'
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| __date__ = 'January 2013'
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| __copyright__ = '(C) 2013, Victor Olaya'
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| 
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| import warnings
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| 
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| from qgis.core import (QgsProcessingParameterFeatureSource,
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|                        QgsProcessingParameterField,
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|                        QgsProcessingException,
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|                        QgsProcessingParameterFileDestination)
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| from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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| 
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| from processing.tools import vector
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| 
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| from qgis.PyQt.QtCore import QCoreApplication
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| 
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| 
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| class MeanAndStdDevPlot(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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| 
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|     def group(self):
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|         return self.tr('Plots')
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| 
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|     def groupId(self):
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|         return 'plots'
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| 
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|     def __init__(self):
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|         super().__init__()
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| 
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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 table')))
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|         self.addParameter(QgsProcessingParameterField(self.NAME_FIELD,
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|                                                       self.tr('Category name field'), 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'), parentLayerParameterName=self.INPUT))
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| 
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|         self.addParameter(QgsProcessingParameterFileDestination(self.OUTPUT, self.tr('Plot'), self.tr('HTML files (*.html)')))
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| 
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|     def name(self):
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|         return 'meanandstandarddeviationplot'
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| 
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|     def displayName(self):
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|         return self.tr('Mean and standard deviation plot')
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| 
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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(QCoreApplication.translate('MeanAndStdDevPlot', 'This algorithm requires the Python “plotly” library. Please install this library and try again.'))
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| 
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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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| 
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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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| 
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|         output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)
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| 
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|         values = vector.values(source, namefieldname, valuefieldname)
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| 
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|         d = {}
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|         for i in range(len(values[namefieldname])):
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|             v = values[namefieldname][i]
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|             if v not in d:
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|                 d[v] = [values[valuefieldname][i]]
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|             else:
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|                 d[v].append(values[valuefieldname][i])
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| 
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|         data = []
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|         for k, v in d.items():
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|             data.append(go.Box(y=list(v),
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|                                boxmean='sd',
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|                                name=k
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|                                ))
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|         plt.offline.plot(data, filename=output, auto_open=False)
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| 
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|         return {self.OUTPUT: output}
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