add square function

MeteoInfoLab/milconfig.xml

@@ -1,9 +1,6 @@
 <?xml version="1.0" encoding="UTF-8" standalone="no"?>
 <MeteoInfo File="milconfig.xml" Type="configurefile">
-  <Path OpenPath="D:\Working\MIScript\Jython\mis\satellite\calipso">
-    <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types"/>
-    <RecentFolder Folder="D:\Working\MIScript\Jython\mis"/>
-    <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types\contour"/>
+  <Path OpenPath="D:\Working\MIScript\Jython\mis\plot_types\wind">
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types\fill_between"/>
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\chart\legend"/>
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\chart"/>
@@ -16,24 +13,27 @@
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\chart\text"/>
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\ascii"/>
     <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types\bar"/>
+    <RecentFolder Folder="D:\Working\MIScript\Jython\mis\meteo"/>
+    <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types"/>
+    <RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types\wind"/>
   </Path>
   <File>
     <OpenedFiles>
       <OpenedFile File="D:\Working\MIScript\Jython\mis\plot_types\3d\jogl\traj_4.py"/>
       <OpenedFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\cluster\dbscan_1.py"/>
       <OpenedFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\deep_learning\classifer_linear_1.py"/>
-      <OpenedFile File="D:\Working\MIScript\Jython\mis\satellite\calipso\CALIPSO_aerosol_type-1.py"/>
+      <OpenedFile File="D:\Working\MIScript\Jython\mis\plot_types\wind\quiverm_2-1.py"/>
     </OpenedFiles>
     <RecentFiles>
       <RecentFile File="D:\Working\MIScript\Jython\mis\plot_types\3d\jogl\traj_4.py"/>
       <RecentFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\cluster\dbscan_1.py"/>
       <RecentFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\deep_learning\classifer_linear_1.py"/>
-      <RecentFile File="D:\Working\MIScript\Jython\mis\satellite\calipso\CALIPSO_aerosol_type-1.py"/>
+      <RecentFile File="D:\Working\MIScript\Jython\mis\plot_types\wind\quiverm_2-1.py"/>
     </RecentFiles>
   </File>
   <Font>
     <TextFont FontName="YaHei Consolas Hybrid" FontSize="14"/>
   </Font>
   <LookFeel Name="Darcula"/>
-  <Startup MainFormLocation="-7,-7" MainFormSize="1293,693"/>
+  <Startup MainFormLocation="-7,4" MainFormSize="1389,805"/>
 </MeteoInfo>

MeteoInfoLab/pylib/mipylib/meteolib/meteo.py

@@ -797,4 +797,47 @@ def varimax(x, normalize=False, tol=1e-10, it_max=1000):
             
     # Final matrix.
     r = np.dot(x, TT)
-    return r, TT
+    return r, TT
+
+def centered_rms_dev(predicted,reference):
+    '''
+    Calculates the centered root-mean-square (RMS) difference between
+    two variables PREDICTED and REFERENCE (E'). The latter is calculated
+    using the formula:
+    (E')^2 = sum_(n=1)^N [(p_n - mean(p))(r_n - mean(r))]^2/N
+    where p is the predicted values, r is the reference values, and
+    N is the total number of values in p & r. Note that p & r must
+    have the same number of values.
+    Input:
+    PREDICTED : predicted field
+    REFERENCE : reference field
+    Output:
+    CRMSDIFF : centered root-mean-square (RMS) difference (E')^2
+    Author: Peter A. Rochford
+        Symplectic, LLC
+        www.thesymplectic.com
+        prochford@thesymplectic.com
+    Created on Nov 24, 2016
+    '''
+
+    # Check that dimensions of predicted and reference fields match
+    pdims= predicted.shape
+    rdims= reference.shape
+    if not np.array_equal(pdims,rdims):
+        message = 'predicted and reference field dimensions do not' + \
+                  ' match.\n' + \
+                  'shape(predicted)= ' + str(pdims) + ', ' + \
+                  'shape(reference)= ' + str(rdims) + \
+                  '\npredicted type: ' + str(type(predicted))
+        raise ValueError(message)
+
+    # Calculate means
+    pmean = np.mean(predicted)
+    rmean = np.mean(reference)
+
+    # Calculate (E')^2
+    crmsd = np.square((predicted - pmean) - (reference - rmean))
+    crmsd = np.sum(crmsd)/predicted.size
+    crmsd = np.sqrt(crmsd)
+
+    return crmsd

MeteoInfoLab/pylib/mipylib/numeric/core/multiarray.py

@@ -670,7 +670,10 @@ class NDArray(object):
         else:
             r = ArrayMath.std(self._array, axis)
             return NDArray(r)
-            
+
+    def square(self):
+        return self.__mul__(self)
+
     def sqrt(self):
         return NDArray(ArrayMath.sqrt(self._array))
     

MeteoInfoLab/pylib/mipylib/numeric/core/numeric.py

@@ -44,7 +44,7 @@ __all__ = [
     'logspace','magnitude','max','maximum','mean','median','meshgrid','min','minimum','monthname',
     'newaxis','nonzero','ones','ones_like','pol2cart','polyval','power',
     'radians','ravel','reshape','repeat',
-    'rolling_mean','rot90','sin','smooth5','smooth9','sort','squeeze','argsort','sqrt','std','sum','swapaxes','tan',
+    'rolling_mean','rot90','sin','smooth5','smooth9','sort','squeeze','argsort','sqrt','square','std','sum','swapaxes','tan',
     'tile','transpose','trapz','vdot','unique','unravel_index','var','vstack',
     'where','zeros','zeros_like'
     ]
@@ -550,6 +550,21 @@ def absolute(x):
         return x.abs()
     else:
         return abs(x)
+
+def square(x):
+    """
+    Return the element-wise square of the input.
+
+    :param x: (*array_like*) Input data.
+
+    :returns: Element-wise x*x, of the same shape and dtype as x. This is a scalar if x is a scalar.
+    """
+    if isinstance(x, list):
+        return array(x).square()
+    elif isinstance(x, NDArray):
+        return x.square()
+    else:
+        return x * x
     
 def sqrt(x):
     """
@@ -557,7 +572,7 @@ def sqrt(x):
     
     :param x: (*array_like*) The values whose square-roots are required.
     
-    :returns y: (*array_like*) An array of the same shape as *x*, containing the positive
+    :returns: (*array_like*) An array of the same shape as *x*, containing the positive
         square-root of each element in *x*.
         
     Examples::