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orange-nmf / orangecontrib / nmf / widgets / OWPivotData.py

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"""
<name>Pivot Data</name>
<description>Pivot data</description>
<icon>icons/PivotIcon.png</icon>
<priority>30</priority>
"""

import numpy as np

#import sys
#sys.path.append("C:\\Python27\\Lib\site-packages\\Orange\\OrangeWidgets")
from OWWidget import *
import OWGUI

NAME = "Pivot Data"
DESCRIPTION = "Pivot data"
ICON = "icons/PivotIcon.png"
PRIORITY = 30

INPUTS = [("Data", ExampleTable, "data")]
OUTPUTS = [("Pivoted Data", ExampleTable)]

REPLACES = ["_nmf.widgets.OWPivotData.OWPivotData"]

class OWPivotData(OWWidget):
    settingsList = []
    def __init__(self, parent=None, signalManager=None):
        OWWidget.__init__(self, parent, signalManager, 'Pivot Data')
        
        self.inputs = [("Data", ExampleTable, self.data)]
        self.outputs = [("Pivoted Data", ExampleTable)]
        self.loadSettings()

        # GUI
        box = OWGUI.widgetBox(self.controlArea, "Info")
        self.infoa = OWGUI.widgetLabel(box, 'No data on input yet, waiting to get something.')
        self.infob = OWGUI.widgetLabel(box, '')

        OWGUI.separator(self.controlArea)
        OWGUI.button(self.controlArea, self, "Pivot long", callback=self.pivotLong)
        OWGUI.button(self.controlArea, self, "Pivot short", callback=self.pivotShort)        
        self.resize(100,50)

    def data(self, dataset):
        if dataset:
            self.dataset = dataset
            self.infoa.setText('%d variables in input data set' % len(dataset[0]))
            self.infob.setText('%d observations in input data set' % len(dataset))
        else:
            self.send("Pivoted Data", None)
            self.infoa.setText('No data on input yet, waiting to get something.')
            self.infob.setText('')
                      
        
    def pivotLong(self):
        self.outputData=[]
        colVal=[]
        colNames=[]
        colID=[]
        for j in range(0, len(self.dataset.domain)):
            for i in range(0, len(self.dataset)): 
                colVal.append(self.dataset[i][j].value)
                colNames.append(self.dataset.domain[j].name)
                colID.append(self.dataset[i]["ID"].value)
        self.outputData=map(list, zip(*[colVal]))
        dom=[Orange.feature.Continuous("Value")]
        dom=Orange.data.Domain(dom,0)
        dom.addmetas(self.dataset.domain.getmetas()) #add "ID"
        newid = Orange.feature.Descriptor.new_meta_id()
        dom.add_meta(newid, Orange.feature.String("Names")) #add "Names"
        self.outputData=Orange.data.Table(dom,self.outputData)
        for i in range(0,len(self.outputData)):        
            self.outputData[i]["ID"]=colID[i]
            self.outputData[i]["Names"]=colNames[i]
        self.send("Pivoted Data", self.outputData)

    def pivotShort(self):
        self.outputData=[]
        domList=[]
        nameMeta=self.dataset.domain.getmetas().values()
        if nameMeta[0].name=="ID":
            nameMeta=nameMeta[1].name
        else:
            nameMeta=nameMeta[0].name
        i=0
        while i<len(self.dataset):
            col=[]
            nameCol=self.dataset[i][nameMeta].value
            domList.append(Orange.feature.Continuous(nameCol))
            while (i<len(self.dataset)) and self.dataset[i][nameMeta].value == nameCol:
                col.append(self.dataset[i][0].value)
                i+=1
            self.outputData.append(col)
        self.outputData=map(list, zip(*self.outputData))
        dom=Orange.data.Domain(domList,0)
        dom.addmetas(self.dataset.domain.getmetas()) #add "ID"
        dom.remove_meta(nameMeta)
        self.outputData=Orange.data.Table(dom,self.outputData)
        for i in range(0,len(self.outputData)):        
            self.outputData[i]["ID"]=self.dataset[i]["ID"]
        self.send("Pivoted Data", self.outputData)     

            
# Test the widget, run from prompt

if __name__=="__main__":
    appl = QApplication(sys.argv)
    ow = OWPivotData()
    ow.show()
    dataset = orange.ExampleTable('C:/Users/Paul Fogel/Desktop/testPivot.tab')
    ow.data(dataset)
    appl.exec_()