added boxplot demos

svn path=/trunk/matplotlib/; revision=1099

Author: jdh2358

CHANGELOG

@@ -1,11 +1,18 @@
 New entries should be added at the top
 
+2005-03-28 Added Jarrod's svg patch for text - JDH
+
+2005-03-28 Added ludal arrow and quiver patch - JDH
+
+2005-03-28 Added label kwarg to Axes to facilitate forcing the
+           creation of new Axes with otherwise identical attributes
+
 2005-03-28 Applied boxplot and OSX font search patches
 
 2005-03-27 Added ft2font NULL check to fix Japanase font bug - JDH
 
-2005-03-27 Added sprint legend patch plus John Gill's tests and fix
-           - JDH
+2005-03-27 Added sprint legend patch plus John Gill's tests and fix --
+           see examples/legend_auto.py  - JDH
 
 ==========================================================================
 

TODO

@@ -683,7 +683,7 @@ ZeroDivisionError: SeparableTransformation::eval_scalars yin interval is zero; c
 
 -- direction fields
 
--- add a force option to the add_axes code.
+-- DONE add a force option to the add_axes code.
 
 -- DONE move object inspector into Artist method
 
@@ -693,4 +693,4 @@ ZeroDivisionError: SeparableTransformation::eval_scalars yin interval is zero; c
 
 -- add a get description to axes which returns the args and kwargs to construct it 
 
--- restore __all__ to pylab and add ArtistInspector\
+-- restore __all__ to pylab and add ArtistInspector

boilerplate.py

@@ -75,6 +75,7 @@ def %(func)s(*args, **kwargs):
     'spy2',
     'stem',
     'vlines',
+    'quiver',
     )
 
 _misccommands = (

examples/boxplot_demo.py

@@ -0,0 +1,61 @@
+#!/usr/bin/python
+
+#
+# Example boxplot code
+#
+
+from pylab import *
+
+# fake up some data
+spread= rand(50) * 100
+center = ones(25) * 50
+flier_high = rand(10) * 100 + 100
+flier_low = rand(10) * -100 
+data =concatenate((spread, center, flier_high, flier_low), 0)
+
+# basic plot
+boxplot(data)
+#savefig('box1')
+
+# notched plot
+figure()
+boxplot(data,1)
+#savefig('box2')
+
+# change outlier point symbols
+figure()
+boxplot(data,0,'gD')
+#savefig('box3')
+
+# don't show outlier points
+figure()
+boxplot(data,0,'')
+#savefig('box4')
+
+# horizontal boxes
+figure()
+boxplot(data,0,'rs',0)
+#savefig('box5')
+
+# change whisker length
+figure()
+boxplot(data,0,'rs',0,0.75)
+#savefig('box6')
+
+# fake up some more data
+spread= rand(50) * 100
+center = ones(25) * 40
+flier_high = rand(10) * 100 + 100
+flier_low = rand(10) * -100 
+d2 = concatenate( (spread, center, flier_high, flier_low), 0 )
+data.shape = (-1, 1)
+d2.shape = (-1, 1)
+data = concatenate( (data, d2), 1 )
+
+# multiple box plots on one figure
+figure()
+boxplot(data)
+#savefig('box7')
+
+show()
+

examples/legend_auto.py

@@ -0,0 +1,90 @@
+"""
+This file was written to test matplotlib's autolegend placement
+algorithm, but shows lots of different ways to create legends so is
+useful as a general examples
+
+Thanks to John Gill and Phil ?? for help at the matplotlib sprint at
+pycon 2005 where the auto-legend support was written.
+"""
+from pylab import *
+import sys
+
+
+N = 100
+x = arange(N)
+
+def fig_1():
+    figure(1)
+    t = arange(0, 40.0 * pi, 0.1)
+    l, = plot(t, 100*sin(t), 'r', label='sine')
+    legend()
+
+def fig_2():
+    figure(2)
+    plot(x, 'o', label='x=y')
+    legend()
+
+def fig_3():
+    figure(3)
+    plot(x, -x, 'o', label='x= -y')
+    legend()
+
+def fig_4():
+    figure(4)
+    plot(x, ones(len(x)), 'o', label='y=1')
+    plot(x, -ones(len(x)), 'o', label='y=-1')
+    legend()
+
+def fig_5():
+    figure(5)
+    n, bins, patches = hist(randn(1000), 40, normed=1)
+    l, = plot(bins, normpdf(bins, 0.0, 1.0), 'r--', label='fit', linewidth=3)
+    legend([l, patches[0]], ['fit', 'hist'])
+
+def fig_6():
+    figure(6)
+    plot(x, 50-x, 'o', label='y=1')
+    plot(x, x-50, 'o', label='y=-1')
+    legend()
+
+def fig_7():
+    figure(7)
+    xx = x - (N/2.0)
+    plot(xx, (xx*xx)-1225, 'bo', label='$y=x^2$')
+    plot(xx, 25*xx, 'go', label='$y=25x$')
+    plot(xx, -25*xx, 'mo', label='$y=-25x$')
+    legend()
+
+def fig_8():
+    figure(8)
+    b1 = bar(x, x, color='m')
+    b2 = bar(x, x[::-1], color='g')
+    legend([b1[0], b2[0]], ['up', 'down'])
+
+def fig_9():
+    figure(9)
+    b1 = bar(x, -x)
+    b2 = bar(x, -x[::-1], color='r')
+    legend([b1[0], b2[0]], ['down', 'up'])
+
+def fig_10():
+    figure(10)
+    b1 = bar(x, x, bottom=-100, color='m')
+    b2 = bar(x, x[::-1], bottom=-100, color='g')
+    b3 = bar(x, -x, bottom=100)
+    b4 = bar(x, -x[::-1], bottom=100, color='r')
+    legend([b1[0], b2[0], b3[0], b4[0]], ['bottom right', 'bottom left',
+                                          'top left', 'top right'])
+
+if __name__ == '__main__':
+    nfigs = 10
+    figures = [int(f) for f in sys.argv[1:]]
+    if len(figures) == 0:
+        figures = range(1, nfigs+1)
+
+    for fig in figures:
+        fn_name = "fig_%d" % fig
+        fn = globals()[fn_name]
+        fn()
+        
+    show()

lib/matplotlib/axes.py

@@ -5,15 +5,15 @@
 from numerix import absolute, arange, array, asarray, ones, divide,\
      transpose, log, log10, Float, Float32, ravel, zeros,\
      Int16, Int32, Int, Float64, ceil, indices, \
-     shape, which, where, sqrt, asum, compress
+     shape, which, where, sqrt, asum, compress, maximum, minimum
 
 import matplotlib.mlab
 from artist import Artist
 from axis import XAxis, YAxis
 from cbook import iterable, is_string_like, flatten, enumerate, \
      allequal, dict_delall, strip_math, popd, popall, silent_list
 from collections import RegularPolyCollection, PolyCollection, LineCollection
-from colors import colorConverter, normalize, Colormap, LinearSegmentedColormap
+from colors import colorConverter, normalize, Colormap, LinearSegmentedColormap, looks_like_color
 import cm
 #from cm import ColormapJet, Grayscale, ScalarMappable
 from cm import ScalarMappable
@@ -31,7 +31,7 @@
 from matplotlib.numerix.mlab import flipud, amin, amax
 
 from matplotlib import rcParams
-from patches import Patch, Rectangle, Circle, Polygon, Wedge, Shadow, bbox_artist
+from patches import Patch, Rectangle, Circle, Polygon, Arrow, Wedge, Shadow, bbox_artist
 from table import Table
 from text import Text, _process_text_args
 from transforms import Bbox, Point, Value, Affine, NonseparableTransformation
@@ -315,13 +315,14 @@ def __init__(self, fig, rect,
                  frameon = True,
                  sharex=None, # use Axes instance's xaxis info
                  sharey=None, # use Axes instance's yaxis info
+                 label='',
                  ):
         Artist.__init__(self)
         self._position = map(makeValue, rect)
         # must be set before set_figure
         self._sharex = sharex
         self._sharey = sharey
-
+        self.set_label(label)
         self.set_figure(fig)
 
         # this call may differ for non-sep axes, eg polar
@@ -758,6 +759,131 @@ def autoscale_view(self):
         locator = self.yaxis.get_major_locator()
         self.set_ylim(locator.autoscale())
 
+
+    def quiver(self, U, V, *args, **kwargs ):
+        """
+        QUIVER( X, Y, U, V )
+        QUIVER( U, V )
+        QUIVER( X, Y, U, V, S)
+        QUIVER( U, V, S )
+        QUIVER( ..., color=None, width=1.0, cmap=None,norm=None )
+
+        Make a vector plot (U, V) with arrows on a grid (X, Y)
+
+        The optional arguments color and width are used to specify the color and width
+        of the arrow. color can be an array of colors in which case the arrows can be
+        colored according to another dataset.
+        
+        If cm is specied and color is None, the colormap is used to give a color
+        according to the vector's length.
+        
+        If color is a scalar field, the colormap is used to map the scalar to a color
+        If a colormap is specified and color is an array of color triplets, then the
+        colormap is ignored
+
+        width is a scalar that controls the width of the arrows
+
+        if S is specified it is used to scale the vectors. Use S=0 to disable automatic
+        scaling.
+        If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.
+        
+
+        """
+        if not self._hold: self.cla()
+        do_scale = True
+        S = 1.0
+        if len(args)==0:
+            # ( U, V )
+            U = asarray(U)
+            V = asarray(V)
+            X,Y = meshgrid( arange(U.shape[0]), arange(U.shape[1]) )
+        elif len(args)==1:
+            # ( U, V, S )
+            U = asarray(U)
+            V = asarray(V)
+            X,Y = meshgrid( arange(U.shape[0]), arange(U.shape[1]) )
+            S = float(args[0])
+            do_scale = ( S != 0.0 )
+        elif len(args)==2:
+            # ( X, Y, U, V )
+            X = asarray(U)
+            Y = asarray(V)
+            U = asarray(args[0])
+            V = asarray(args[1])
+        elif len(args)==3:
+            # ( X, Y, U, V )
+            X = asarray(U)
+            Y = asarray(V)
+            U = asarray(args[0])
+            V = asarray(args[1])
+            S = float(args[2])
+            do_scale = ( S != 0.0 )
+
+        assert U.shape == V.shape
+        assert X.shape == Y.shape
+        assert U.shape == X.shape
+        
+        arrows = []
+        N = sqrt( U**2+V**2 )
+        if do_scale:
+            Nmax = maximum.reduce(maximum.reduce(N))
+            U *= (S/Nmax)
+            V *= (S/Nmax)
+            N /= Nmax
+            
+        alpha = kwargs.get('alpha', 1.0)
+        width = kwargs.get('width', 0.25)
+        norm = kwargs.get('norm', None)
+        cmap = kwargs.get('cmap', None)
+        vmin = kwargs.get('vmin', None)
+        vmax = kwargs.get('vmax', None)
+        color = kwargs.get('color', None)
+        shading = kwargs.get('shading', 'faceted')
+
+        C = None
+        I,J = U.shape
+        if color is not None and not looks_like_color(color):
+            clr = asarray(color)
+            if clr.shape==U.shape:
+                C = array([ clr[i,j] for i in xrange(I)  for j in xrange(J)])
+            elif clr.shape == () and color:
+                # a scalar (1, True,...)
+                C = array([ N[i,j] for i in xrange(I)  for j in xrange(J)])
+            else:
+                color = (0.,0.,0.,1.)
+        elif color is None:
+            color = (0.,0.,0.,1.)
+        else:
+            color = colorConverter.to_rgba( color, alpha )
+
+
+        arrows = [ Arrow(X[i,j],Y[i,j],U[i,j],V[i,j],0.1*S ).get_verts()
+                   for i in xrange(I) for j in xrange(J) ]
+        collection = PolyCollection(
+            arrows,
+            edgecolors = 'None',
+            facecolors = (color,),
+            antialiaseds = (0,),
+            linewidths = (width,),
+            )
+        if C:
+            collection.set_array( C )
+        else:
+            collection.set_facecolor( (color,) )
+        collection.set_cmap(cmap)
+        collection.set_norm(norm)
+        if norm is not None:
+            collection.set_clim( vmin, vmax )
+        self.add_collection( collection )
+        lims = asarray(arrows)
+        _max = maximum.reduce( maximum.reduce( lims ))
+        _min = minimum.reduce( minimum.reduce( lims ))
+        self.update_datalim( [ tuple(_min), tuple(_max) ] )
+        self.autoscale_view()
+        return arrows
+                
+
+
     def bar(self, left, height, width=0.8, bottom=0,
             color='b', yerr=None, xerr=None, ecolor='k', capsize=3
             ):
@@ -882,7 +1008,7 @@ def boxplot(self, x, notch=0, sym='b+', vert=1, whis=1.5):
         # if we've got a vector, reshape it
         rank = len(x.shape)
         if 1 == rank:
-            x.shape(-1, 1)
+            x.shape = -1, 1
 
         row, col = x.shape