Plotting

geoscript/examples/plot/box_population.py

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+from geoscript.plot.functions import  attributesasdict
+from geoscript.layer.shapefile import Shapefile
+from geoscript.plot.box import box
+from geoscript.filter import Filter
+
+if __name__ == '__main__':       
+    layer = Shapefile('D:/gisdata/denver_shapefiles/census_boundaries.shp')    
+    chart = box(attributesasdict(layer, ['BLACK', 'AMERI_ES', 'ASIAN', 'OTHER', 'HISPANIC'], Filter("COUNTYNAME = 'DENVER'")))
+    chart.show()
+

geoscript/examples/plot/correlation_attributes.py

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+from geoscript.processing.sampledata import sampledata
+from geoscript.plot import attribute
+from geoscript.plot.regression import linearregression
+
+if __name__ == '__main__':       
+    layer = sampledata.get('heights')
+    chart = linearregression(attribute(layer, 'VALUE'), attribute(layer, 'VALUE'))
+    chart.show()

geoscript/examples/plot/correlation_distance.py

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+from geoscript.processing.sampledata import sampledata
+from geoscript.plot import linearregression
+from geoscript.plot import attribute
+from geoscript.plot import disttopoint
+
+if __name__ == '__main__':       
+    layer = sampledata.get('heights')    
+    pt = layer.features().next().geom.centroid            
+    chart = linearregression(disttopoint(layer, pt.x, pt.y), attribute(layer, 'VALUE'))
+    chart.savepng("d:\\chart.png")
+    chart.show()

geoscript/examples/plot/distance_distribution.py

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+from geoscript.plot import *
+from geoscript.layer.shapefile import Shapefile
+from geoscript.processing.sampledata import sampledata
+
+if __name__ == '__main__':  
+
+    #layer = Shapefile('/home/myuser/points.shp')
+    #===========================================================================
+    # layer = sampledata.get('heights')
+    # x = y = ifeat = 0
+    # for feature in layer.features():        
+    #    pt = feature.geom.centroid
+    #    x += pt.x
+    #    y += pt.y
+    #    ifeat += 1
+    # x /= float(ifeat)
+    # y /= float(ifeat)
+    # chart = xybars(frequency(disttopoint(layer, x, y), 10))
+    # chart.show()
+    #===========================================================================
+
+    #the same thing using the xy function to calculate the mean center
+    layer = sampledata.get('heights')
+    x = y = ifeat = 0
+    xy = xy(layer)
+    for px,py in xy:                
+        x += px
+        y += py
+        ifeat += 1
+    x /= float(ifeat)
+    y /= float(ifeat)
+    chart = xybars(frequency(disttopoint(layer, x, y), 10))
+    chart.show()
+
+
+

geoscript/examples/plot/multiple_bars.py

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+from geoscript.plot import *
+from geoscript.layer.shapefile import Shapefile
+
+if __name__ == '__main__':       
+    layer = Shapefile('D:/gisdata/denver_shapefiles/census_boundaries.shp')    
+    chart = categorybars(summarize(layer, 'BLKGRP', ['BLACK', 'ASIAN', 'HISPANIC']), stacked=True)
+    chart.show()
+

geoscript/examples/plot/overlay.py

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+from geoscript.plot import *
+import random
+
+'''An example that shows how plots can be overlayed'''
+
+if __name__ == '__main__':          
+    xy = [(i,random.random() * 10) for i in range(10)]    
+    chart = curve(xy)
+    xy2 = [(i,random.random() * 3) for i in range(10)]    
+    chart2 = curve(xy2)
+    xy3 = [(i,random.random()) for i in range(10)]    
+    chart3 = curve(xy3)
+    xy4 = [(random.random() * 10,random.random() * 10) for i in range(100)]    
+    chart4 = scatterplot(xy4)
+    chart.overlay(chart2, chart3, chart4)
+    chart.show()
+

geoscript/examples/plot/plot_points.py

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+from geoscript.plot import *
+from geoscript.processing.sampledata import sampledata
+
+if __name__ == '__main__':  
+
+    layer = sampledata.get('heights')    
+    chart = scatterplot(xy(layer))
+    chart.show()
+

geoscript/examples/plot/semivariogram.py

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+from geoscript.plot import *
+from geoscript.processing.sampledata import sampledata
+
+'''An example that plots a semivariogram cloud'''
+import math
+import random
+
+if __name__ == '__main__':      
+    layer = sampledata.get('heights') 
+    semivar = []
+    i= 0
+    for feature in layer.features():
+        pt1 = feature.geom.getCoordinates()[0]
+        value1 = feature.get('VALUE')
+        i2 = 0         
+        for feature2 in layer.features():
+            if i2 > i:
+                pt2 = feature2.geom.getCoordinates()[0]
+                value2 = feature2.get('VALUE')
+                semivar.append((pt1.distance(pt2), math.pow(value2-value1,2.)))
+            i2 += 1
+        i+=1               
+    # we do not plot all points, as that would mean a large                                     
+    chart = scatterplot(semivar)
+    chart.show()
+

geoscript/examples/plot/unique_barchart.py

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+from geoscript.processing.sampledata import sampledata
+from geoscript.plot import *
+
+if __name__ == '__main__':       
+    layer = sampledata.get('landcover')                  
+    chart = categorybars(uniquecounts(layer, 'LANDCOVER'))
+    chart.show()

geoscript/examples/plot/unique_pie.py

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+from geoscript.processing.sampledata import sampledata
+from geoscript.plot import *
+
+if __name__ == '__main__':       
+    layer = sampledata.get('landcover')                  
+    chart = pie(uniquecounts(layer, 'LANDCOVER'))
+    chart.show()

geoscript/plot/__init__.py

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+from regression import linearregression, powregression
+from bars import xybars, categorybars
+from pie import pie
+from box import box
+from curve import curve
+from scatterplot import scatterplot
+from functions import attribute, attributes, attributesasdict, x, y, disttopoint,\
+            uniquecounts, frequency, xy, summarize

geoscript/plot/bars.py

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+from org.jfree.data.xy import XYSeriesCollection, XYSeries
+from org.jfree.data.category import DefaultCategoryDataset
+from org.jfree.chart import ChartFactory
+from org.jfree.chart.plot import PlotOrientation
+from geoscript.plot.chart import Chart
+
+def xybars(data, name="xybars"):
+    '''Creates a xy bars chart. 
+
+    Input is a list of tuples with (x,y) values'''
+    series = XYSeries(name);
+    for x,y in data:
+        series.add(x,y)
+    dataset =  XYSeriesCollection(series)
+    chart = ChartFactory.createXYBarChart(None, "X", False,"Y", 
+            dataset, PlotOrientation.VERTICAL, True, True, False)
+    return Chart(chart)
+
+def intervalbars(data, name="xybars"):
+    '''Creates a xy bars chart, whit bars defining intervals. 
+    Input is a list of tuples in the form ((lo,hi),y), *lo* and *hi* being
+    the lower and upper limits of the interval and *y* the count on that interval'''
+    pass
+
+def categorybars(cat, name="", xlab="", ylab="", stacked=False, tridim=False):
+    '''Creates a barchart with categorical data.
+
+    The input is a dict with category names as keys and numerical values
+    (the height of the bar) corresponding to that category as values.
+
+    Multiple series can be plot, by passing a dict with series names as keys
+    and dicts as the one described above as values.
+
+    By setting *stacked* to true the result will be a stacked bar chart''' 
+    dataset = DefaultCategoryDataset();
+    for k,v in cat.iteritems():    
+        if isinstance(v, dict):
+            for k2,v2 in v.iteritems():
+                dataset.addValue(v2, k2, k)    
+        else:
+            dataset.addValue(v, "", k) 
+
+    if tridim:
+        if stacked:
+            chart = ChartFactory.createStackedBarChart3D(name, xlab, ylab, dataset,
+                                           PlotOrientation.VERTICAL, True, True, True)
+        else:
+            chart = ChartFactory.createBarChart3D(name, xlab, ylab, dataset,
+                                           PlotOrientation.VERTICAL, True, True, True) 
+    else:
+        if stacked:
+            chart = ChartFactory.createStackedBarChart(name, xlab, ylab, dataset,
+                                           PlotOrientation.VERTICAL, True, True, True)
+        else:
+            chart = ChartFactory.createBarChart(name, xlab, ylab, dataset,
+                                           PlotOrientation.VERTICAL, True, True, True)
+    return Chart(chart)

geoscript/plot/box.py

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+from org.jfree.data.statistics import DefaultBoxAndWhiskerCategoryDataset
+from org.jfree.chart import ChartFactory
+from geoscript.plot.chart import Chart
+
+def box(data):
+    '''creates a box and whiskers plot.
+    Data is passed as a dict with category names as keys and lists of numbers as values
+    '''
+    dataset  = DefaultBoxAndWhiskerCategoryDataset()
+    for name, values in data.iteritems():    
+        dataset.add(values, "", name);
+    chart = ChartFactory.createBoxAndWhiskerChart("", "", "", dataset, True)
+    return Chart(chart)
+
+
+

geoscript/plot/chart.py

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+from javax import swing
+from org.jfree.chart import ChartPanel, ChartUtilities
+from geoscript import util
+from org.jfree.chart.plot import DatasetRenderingOrder
+from org.jfree.chart.axis import NumberAxis
+
+class Chart():
+    '''A class that wraps a JFreeChart Chart object and has method
+    to easily show or save it'''
+
+    def __init__(self,chart):
+        self.chart = chart
+        self.datasets = 1
+
+    def show(self, size=(500,500)):
+        panel = ChartPanel(self.chart) 
+        frame = swing.JFrame()
+        frame.setContentPane(panel)
+        frame.size = size
+        frame.visible = True
+
+    def savepng(self, filename, size=(500,500)):
+        ChartUtilities.saveChartAsPNG(util.toFile(filename), self.chart, size[0], size[1])
+
+    def overlay(self, *charts):
+        for chart in charts:
+            self._overlay(chart)
+
+    def _overlay(self, chart):        
+        plot = self.chart.getPlot()
+        plot.setDataset(self.datasets, chart.chart.getPlot().getDataset())
+        plot.setRenderer(self.datasets, chart.chart.getPlot().getRenderer())
+        plot.setDatasetRenderingOrder(DatasetRenderingOrder.FORWARD)
+        yAxis = NumberAxis("") 
+        plot.setRangeAxis(self.datasets, yAxis); 
+        plot.mapDatasetToRangeAxis(self.datasets, self.datasets)
+        self.datasets += 1

geoscript/plot/curve.py

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+from org.jfree.data.xy import XYSeries, XYSeriesCollection
+from org.jfree.chart.plot import PlotOrientation
+from org.jfree.chart import ChartFactory
+from geoscript.plot.chart import Chart
+from org.jfree.chart.renderer.xy import XYSplineRenderer, XYLine3DRenderer
+
+def curve(data, name="", smooth=True, tridim=True):
+    '''Creates a curve based on a list of (x,y) tuples.
+
+    If *smooth* is true, then it uses a spline renderer.
+
+    If *tridim* is true, then it creates a 3d-like plot.In this case
+    smooth value is neglected and no smoothing is added'''
+    dataset = XYSeriesCollection()
+    xy = XYSeries(name);        
+    for d in data:
+        xy.add(d[0], d[1])
+    dataset.addSeries(xy);
+    chart = ChartFactory.createXYLineChart(
+                None, None, None, dataset, PlotOrientation.VERTICAL, True, True, False)
+    if smooth:
+        chart.getXYPlot().setRenderer(XYSplineRenderer())
+    if tridim:
+        chart.getXYPlot().setRenderer(XYLine3DRenderer())        
+
+    return Chart(chart)    
+