예제 #1
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def run(self,*event):

        #I tried for WAY to long to get this to work with the high-level interface
        #but it usually resulted in the output having a very long label that
        #contained all the data in the vector we passed to it, still not sure
        #how to resolve it

        args = rdict()

        args['mu'] = self.parameters['Mu'].get()
        args['conf.level'] = float( self.parameters['Confidence Level'].get() )
        #args['paired'] = self.parameters['Paired'].get()
        args['var.equal'] = self.parameters['Equal Variances'].get()
        #R takes the first character as an argument
        args['alternative'] = self.parameters['Alternative Hypothesis'].get().lower()[0]

        args = rsession.arguments_to_string(args)
        print args

        s1lab,s1data = self.custom_variables['samples'][0]
        if len(self.custom_variables['samples'])>1:
            s2lab,s2data = self.custom_variables['samples'][1]
            x = self.active_r_object[s1lab]
            y = self.active_r_object[s2lab]
            anova_output = rsession.r('t.test(x=%s,y=%s,data=%s,%s)' % (x, y, self.active_r_object.label, args))
        else:
            x = self.active_r_object[s1lab]
            anova_output = rsession.r('t.test(x=%s,data=%s,%s)' % (x, self.active_r_object.label, args))

        name = 'T-Test ' + str(self.active_r_object.label)

        self.parent.render_description(anova_output,label=name)
예제 #2
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def run(self,*event):

        #I tried for WAY to long to get this to work with the high-level interface
        #but it usually resulted in the output having a very long label that
        #contained all the data in the vector we passed to it, still not sure
        #how to resolve it

        args = rdict()

        args['correct'] = self.parameters['Apply continuity correction'].get()

        args = rsession.arguments_to_string(args)

        s1lab,s1data = self.custom_variables['samples'][0]
        if len(self.custom_variables['samples'])==2:
            s2lab,s2data = self.custom_variables['samples'][1]
            x = self.active_r_object[s1lab]
            y = self.active_r_object[s2lab]
            anova_output = rsession.r('mcnemar.test(x=%s,y=%s%s)' % (x, y, args))
        else:
            info('Please select two samples.')

        name = 'T-Test ' + str(self.active_r_object.label)

        self.parent.render_description(anova_output,label=name)
예제 #3
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_fit(self,event,image=None):

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        #These return the parent$column strings
        x = self.active_r_object[ilab]
        y = self.active_r_object[dlab]

        fit = rsession.r('lm(%s~poly(%s,%i))' % (y,x,self.degree.get_value()))
        self.result = fit

        data={'x':idata,'y':ddata}
        args={'xlab':ilab,'ylab':dlab}

        plotwindow = rsession.RPlotThread(data=data,
                                        args=args,
                                        par_mode=(1,1),
                                        export=image,
                                        type='scatter')

        plotwindow.start()

        seq=rsession.r['seq']
        min=rsession.r['min']
        max=rsession.r['max']

        object = rsession.env[self.active_r_object.label]
        range = seq(min(object), max(object), length_out = 100)
        predicted = rsession.r['predict'](fit,data_frame=range)
        plotwindow.add_cmd(rsession.ro.r.lines,idata,predicted,col='red')
        self.active_threads.append(plotwindow)
예제 #4
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_fit(self,event,image=None):

        if not self.variables_are_set():
            error('Required variables are not set.')
            return

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        x = self.active_r_object[ilab]
        y = self.active_r_object[dlab]
        fit = rsession.r('lm(%s ~ %s,data=%s)' % (y,x,self.active_r_object.label))
        self.result = fit

        data={'x':idata,'y':ddata}
        args={'xlab':ilab,'ylab':dlab}

        plotwindow = rsession.RPlotThread(data=data,
                                        args=args,
                                        type='scatter',
                                        export=image,
                                        par_mode=(1,1))

        plotwindow.add_cmd(rsession.r['abline'],fit,col='red')

        plotwindow.start()
        self.active_threads.append(plotwindow)
예제 #5
0
파일: main.py 프로젝트: sdiehl/rpygtk
 def freqtable(self,event):
     condition = variable_prompt.VariablePrompt(['Condition(s):']).get_inputs()
     #This is dirty but ro.RFormula will not parse
     try:
         filter = rsession.r('with(%s,table(%s))' % (self.active_robject.label,condition[0]))
     except:
         error('Formula is not valid. \n Enter conditions seperated by commas. Ex: V1>3,V4<1')
         return
     self.output(filter,title='Frequency Table: ' + condition[0])
     self.active_output = rsession.description(filter,tabelize=False)
예제 #6
0
파일: main.py 프로젝트: sdiehl/rpygtk
    def export_latex(self,event):
        try:
            rsession.r('library(xtable)')
            rprint = rsession.r['print']
            xtable = rsession.r['xtable']
            table = rsession.r['table']

            activetab = self.builder.get_object('main_tabview').get_current_page()

            #Data Tab
            if activetab == 0:
                if not self.active_robject:
                    error('No active dataframe.')
                    return
                object = self.active_robject.object
                label = self.active_robject.label
                text = str(xtable(object,caption=label))
                TextOutput(text)
            #Output Tab
            elif activetab == 1:
                if not self.active_output:
                    error('No active output.')
                    return
                object = self.active_output.object
                label = self.active_output.label
                if not label:
                    label = rsession.null
                if self.active_output.tabelize: 
                    text = str(xtable(table(object),caption=label))
                else:
                    text = str(xtable(object,caption=label))
                TextOutput(text)
            #Console Tab
            elif activetab == 2:
                console = self.builder.get_object('consoleview').get_buffer()
                lower,upper = console.get_bounds()
                text = console.get_text(lower,upper)
                TextOutput('\\begin{verbatim}\n' + text + '\n\end{verbatim}')
        except:
            error("Could not load the xtable library.")
예제 #7
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_fit(self,event,image=None):

        if not self.variables_are_set():
            error('Required variables are not set.')
            return

        rsession.r('par(mfrow=c(1,1))')

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        #fit = rsession.r['loess'](idata,ddata).object

        data={'x':idata,'y':ddata}
        args={'xlab':ilab,'ylab':dlab}

        plotwindow = rsession.RPlotThread(data=data,
                                          args=args,
                                          type='scatter.smooth')

        plotwindow.start()
        self.active_threads.append(plotwindow)
예제 #8
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_summary(self,event,image=None):

        if not self.variables_are_set():
            error('Required variables are not set.')
            return

        rsession.r('par(mfrow=c(2,2))')

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        x = self.active_r_object[ilab]
        y = self.active_r_object[dlab]
        fit = rsession.r('lm(%s ~ %s,data=%s)' % (x,y,self.active_r_object.label))
        self.result = fit

        plotwindow = rsession.RPlotThread(data=fit,
                                          type='general',
                                          par_mode=True)


        plotwindow.start()
        self.active_threads.append(plotwindow)
예제 #9
0
파일: main.py 프로젝트: sdiehl/rpygtk
 def transform(self,event):
     cols = self.active_robject.columns.keys()
     transforms = zip(cols,variable_prompt.VariablePrompt(cols).get_inputs(allow_empty=True))
     try:
         args = rdict()
         argument_string = ''
         for col,transform in transforms:
             if col and transform:
                 argument_string += ',%s=%s' % (col,transform)
         print argument_string
         label = self.active_robject.label
         obj = rsession.env[label]
         transformed = rsession.r('transform(%s %s)' % (label,argument_string))
         #transformed = rsession.r['transform'](obj,args)
     except:
         error('Transformations were not well formed')
         return
     rsession.env[label] = transformed
     self.sync_with_r()
예제 #10
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_summary(self,event,image=None):

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        #These return the parent$column strings
        x = self.active_r_object[ilab]
        y = self.active_r_object[dlab]

        fit = rsession.r('lm(%s~poly(%s,%i))' % (y,x,self.degree.get_value()))
        self.result = fit

        plotwindow = rsession.RPlotThread(data=fit,
                                        type='general',
                                        par_mode=(2,2),
                                        export=image)

        plotwindow.start()

        self.active_threads.append(plotwindow)
예제 #11
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def run(self,*event):
        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        x = self.active_r_object[ilab]
        y = self.active_r_object[dlab]
        fit = rsession.r('lm(%s ~ %s,data=%s)' % (y,x,self.active_r_object.label))

        if idata == ddata:
            error('Variables are identical, results may not be accurate.')

        anova_output = rsession.r['anova'](fit)

        name = 'ANOVA ' + str(self.active_r_object.label)

        #This isn't good if there are variables called x,y in the workspace
        rsession.rm('x')
        rsession.rm('y')

        self.parent.render_description(anova_output,label=name)
예제 #12
0
파일: plots.py 프로젝트: sdiehl/rpygtk
    def plot(self,event,image=None):
        _xlab,_ylab,_title,_xmin,_ymin,_xmax,_ymax = self.fetch_labels()

        data = self.data

        args = rdict()

        if self.parameters['Lower Panels'].get():
            args['lower.panel'] = rsession.r('panel.smooth')
        else:
            args['lower.panel'] = rsession.null

        args['gap'] = self.parameters['Plot Gap'].get()
        args['pch'] = self.get_point_style()

        #Advanced Parameters

        plotwindow = rsession.RPlotThread(data=data,
                                        args=args,
                                        type='matplot',
                                        export=image)

        plotwindow.start()
        self.active_threads.append(plotwindow)
예제 #13
0
파일: main.py 프로젝트: sdiehl/rpygtk
 def context_delcol(self,*args):
     #Its much easier to resolve this on the R side, rather than using numpy
     rsession.r('%s = transform(%s,%s)' % (self.active_robject.label, self.active_robject.label,self.active_column+'=NULL'))
     self.sync_with_r()
예제 #14
0
파일: main.py 프로젝트: sdiehl/rpygtk
 def subset(self,event):
     condition = variable_prompt.VariablePrompt(['Condition(s):']).get_inputs()[0]
     rsession.env['subset %s' % (self.active_robject.label)] = rsession.r('subset(%s,%s)' % (self.active_robject.label,condition))
     self.sync_with_r()
예제 #15
0
파일: main.py 프로젝트: sdiehl/rpygtk
 def shutdown_cleanly(self):
     '''If the user CTRL-Cs, make sure the threads die and graphics get turned off'''
     #iterate over the shared state of ThreadHandler to fetch all threads and kill them
     for thread in self.active_threads.iter_shared():
         thread.halt = True
     rsession.r('graphics.off()')
예제 #16
0
파일: stat_tests.py 프로젝트: sdiehl/rpygtk
    def plot_fit(self,event,image=None):
        model = self.get_model().lower()

        dependent = model.partition('~')[0]
        independent = model.partition('~')[2]

        coefs = set()
        vars = set()

        #We're iterating over the variables, so that later it will be easier to do this in more than 2D
        for symbol in model:
            if symbol is 'x' or symbol is 'y':
                vars.add(symbol)
            elif symbol.isalpha():
                coefs.add(symbol)

        ilab,idata = self.custom_variables['independent'].get_first()
        dlab,ddata = self.custom_variables['dependent'].get_first()

        try:
            fmla = rsession.ro.RFormula(model)
        except:
            error('The model you specified is not valid.')
            return
        env = fmla.getenvironment()
        env['x'] = idata
        env['y'] = ddata

        #I love R, this would take like 30 hours to implement in python
        #this fetches all coefficents but ignores functions like sin,cos...
        coefs = list ( rsession.r['all.vars'](fmla)  )

        #Don't consider x and y as coefficents
        coefs.remove('y')
        coefs.remove('x')

        data={'x':idata,'y':ddata}
        args={'xlab':ilab,'ylab':dlab}

        object = rsession.r(self.active_r_object.label)

        startdict = {}

        for i in coefs:
            startdict[i]= 1

        startlist=rsession.r['list'](**startdict)

        seq=rsession.r['seq']
        rmin=rsession.r['min']
        rmax=rsession.r['max']

        # There is nothing truly beautiful but that which can never be of any use whatsoever; everything
        # useful is ugly; keep that in mine while reading the next 40 lines.

        #Generate a range of points so our predicted curve is smooth
        lenout = {'length.out':500}
        df = rsession.r['data.frame']
        smooth_range = rsession.r['seq'](  rsession.r['min'](idata) , rsession.r['max'](idata),**lenout)

        fit_found = False
        predicted = None

        #Try and find the fit, loop using the user provided starting values until we find a fit
        while(fit_found == False):
            try:
                #Try to find a fit
                fit = rsession.r['nls'](formula=fmla.r_repr(),data=object,start=startlist)
                #Interpolate the fit over the the range of the independent variable
                predicted = rsession.r['predict'](fit,df(x=smooth_range))

            #If we fail to achieve convergance
            except:
                #Prompt the user for more information about coefficents
                info('Fit could not be found, please adjust starting values for coefficents.')
                startvalues = VariablePrompt(startdict.keys()).get_inputs()
                if not startvalues:
                    return
                for coef,value in zip(startdict.keys(),startvalues):
                    startdict[coef] = value
                startlist=rsession.r['list'](**startdict)

            if predicted:
                #info('Fit Found')
                fit_found = True
                self.fit = fit
                self.result = fit

        plotwindow = rsession.RPlotThread(data=data,
                                args=args,
                                type='scatter',
                                export=image,
                                par_mode=(1,1))

        #print 'predicted',predicted
        #print 'smooth',smooth_range

        plotwindow.add_cmd(rsession.ro.r.lines,smooth_range,predicted,col='red')
        plotwindow.start()

        self.active_threads.append(plotwindow)