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From ah...@apache.org
Subject svn commit: r1515622 - /incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py
Date Mon, 19 Aug 2013 21:43:45 GMT
Author: ahart
Date: Mon Aug 19 21:43:45 2013
New Revision: 1515622

URL: http://svn.apache.org/r1515622
Log:
CLIMATE-259: add utility class for generating taylor diagrams

Added:
    incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py

Added: incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py
URL: http://svn.apache.org/viewvc/incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py?rev=1515622&view=auto
==============================================================================
--- incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py (added)
+++ incubator/climate/branches/RefactorPlots/rcmet/src/main/python/rcmes/utils/taylor.py Mon
Aug 19 21:43:45 2013
@@ -0,0 +1,144 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+"""
+Taylor diagram (Taylor, 2001) test implementation.
+ 
+http://www-pcmdi.llnl.gov/about/staff/Taylor/CV/Taylor_diagram_primer.htm
+"""
+ 
+__version__ = "Time-stamp: <2012-02-17 20:59:35 ycopin>"
+__author__ = "Yannick Copin <yannick.copin@laposte.net>"
+ 
+import numpy as NP
+import matplotlib.pyplot as PLT
+ 
+class TaylorDiagram(object):
+    """Taylor diagram: plot model standard deviation and correlation
+    to reference (data) sample in a single-quadrant polar plot, with
+    r=stddev and theta=arccos(correlation).
+    """
+ 
+    def __init__(self, refstd, radmax=1.5, fig=None, rect=111, label='_'):
+        """Set up Taylor diagram axes, i.e. single quadrant polar
+        plot, using mpl_toolkits.axisartist.floating_axes. refstd is
+        the reference standard deviation to be compared to.
+        """
+ 
+        from matplotlib.projections import PolarAxes
+        import mpl_toolkits.axisartist.floating_axes as FA
+        import mpl_toolkits.axisartist.grid_finder as GF
+ 
+        self.refstd = refstd            # Reference standard deviation
+ 
+        tr = PolarAxes.PolarTransform()
+ 
+        # Correlation labels
+        rlocs = NP.concatenate((NP.arange(10)/10.,[0.95,0.99]))
+        tlocs = NP.arccos(rlocs)        # Conversion to polar angles
+        gl1 = GF.FixedLocator(tlocs)    # Positions
+        tf1 = GF.DictFormatter(dict(zip(tlocs, map(str,rlocs))))
+ 
+        # Standard deviation axis extent
+        self.smin = 0
+        self.smax = radmax*self.refstd
+ 
+        ghelper = FA.GridHelperCurveLinear(tr,
+                                           extremes=(0,NP.pi/2, # 1st quadrant
+                                                     self.smin,self.smax),
+                                           grid_locator1=gl1,
+                                           tick_formatter1=tf1,
+                                           )
+ 
+        if fig is None:
+            fig = PLT.figure()
+ 
+        ax = FA.FloatingSubplot(fig, rect, grid_helper=ghelper)
+        fig.add_subplot(ax)
+ 
+        # Adjust axes
+        ax.axis["top"].set_axis_direction("bottom")  # "Angle axis"
+        ax.axis["top"].toggle(ticklabels=True, label=True)
+        ax.axis["top"].major_ticklabels.set_axis_direction("top")
+        ax.axis["top"].label.set_axis_direction("top")
+        ax.axis["top"].label.set_text("Correlation")
+ 
+        ax.axis["left"].set_axis_direction("bottom") # "X axis"
+        ax.axis["left"].label.set_text("Standard deviation")
+ 
+        ax.axis["right"].set_axis_direction("top")   # "Y axis"
+        ax.axis["right"].toggle(ticklabels=True)
+        ax.axis["right"].major_ticklabels.set_axis_direction("left")
+ 
+        ax.axis["bottom"].set_visible(False)         # Useless
+        
+        # Contours along standard deviations
+        ax.grid(False)
+ 
+        self._ax = ax                   # Graphical axes
+        self.ax = ax.get_aux_axes(tr)   # Polar coordinates
+ 
+        # Add reference point and stddev contour
+        # print "Reference std:", self.refstd
+        l, = self.ax.plot([0], self.refstd, 'k*',
+                          ls='', ms=10, label=label)
+        t = NP.linspace(0, NP.pi/2)
+        r = NP.zeros_like(t) + self.refstd
+        self.ax.plot(t,r, 'k--', label='_')
+ 
+        # Collect sample points for latter use (e.g. legend)
+        self.samplePoints = [l]
+ 
+    def add_sample(self, stddev, corrcoef, *args, **kwargs):
+        """Add sample (stddev,corrcoeff) to the Taylor diagram. args
+        and kwargs are directly propagated to the Figure.plot
+        command."""
+ 
+        l, = self.ax.plot(NP.arccos(corrcoef), stddev,
+                          *args, **kwargs) # (theta,radius)
+        self.samplePoints.append(l)
+ 
+        return l
+ 
+    def add_rms_contours(self, levels=5, **kwargs):
+        """Add constant centered RMS difference contours."""
+ 
+        rs,ts = NP.meshgrid(NP.linspace(self.smin,self.smax),
+                            NP.linspace(0,NP.pi/2))
+        # Compute centered RMS difference
+        rms = NP.sqrt(self.refstd**2 + rs**2 - 2*self.refstd*rs*NP.cos(ts))
+        
+        contours = self.ax.contour(ts, rs, rms, levels, **kwargs)
+    
+    def add_stddev_contours(self, std, corr1, corr2, **kwargs):
+        """Add a curved line with a radius of std between two points
+        [std, corr1] and [std, corr2]"""
+
+        t = NP.linspace(NP.arccos(corr1), NP.arccos(corr2)) 
+        r = NP.zeros_like(t) + std
+        return self.ax.plot(t,r,'red', linewidth=2)
+    
+    def add_contours(self,std1,corr1,std2,corr2, **kwargs):
+        """Add a line between two points
+        [std1, corr1] and [std2, corr2]"""
+        
+        t = NP.linspace(NP.arccos(corr1), NP.arccos(corr2)) 
+        r = NP.linspace(std1, std2)
+
+        return self.ax.plot(t,r,'red',linewidth=2)
+ 



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