refactored numerix

svn path=/trunk/matplotlib/; revision=880

Author: jdh2358

CHANGELOG

@@ -1,5 +1,9 @@
 New entries should be added at the top
 
+2005-01-21 Refactored numerix to solve vexing namespace issues - JDH
+
+2005-01-21 Applied Nadia's contour bug fix - JDH
+
 2005-01-20 Made some changes to the contour routine - particularly
            region=1 seems t fix a lot of the zigzag strangeness.
            Added colormaps as default for contour - JDH

MANIFEST

@@ -4,6 +4,7 @@ CHANGELOG
 INSTALL
 INTERACTIVE
 KNOWN_BUGS
+MANIFEST
 MANIFEST.in
 Makefile
 README
@@ -246,6 +247,7 @@ agg22/svg/win32_api/svg_test.dsp
 agg22/svg/win32_api/svg_test.dsw
 examples/README
 examples/__init__.py
+examples/accented_text.py
 examples/alignment_test.py
 examples/anim.py
 examples/anim_tk.py
@@ -262,6 +264,7 @@ examples/break.py
 examples/color_demo.py
 examples/colours.py
 examples/contour_demo.py
+examples/contour_demo2.py
 examples/coords_demo.py
 examples/coords_report.py
 examples/csd_demo.py
@@ -524,9 +527,6 @@ lib/matplotlib/lines.py
 lib/matplotlib/mathtext.py
 lib/matplotlib/matlab.py
 lib/matplotlib/mlab.py
-lib/matplotlib/na_imports.py
-lib/matplotlib/nc_imports.py
-lib/matplotlib/numerix.py
 lib/matplotlib/patches.py
 lib/matplotlib/pylab.py
 lib/matplotlib/pyparsing.py
@@ -553,6 +553,13 @@ lib/matplotlib/backends/backend_tkagg.py
 lib/matplotlib/backends/backend_wx.py
 lib/matplotlib/backends/backend_wxagg.py
 lib/matplotlib/backends/tkagg.py
+lib/matplotlib/numerix/__init__.py
+lib/matplotlib/numerix/_na_imports.py
+lib/matplotlib/numerix/_nc_imports.py
+lib/matplotlib/numerix/fft/__init__.py
+lib/matplotlib/numerix/linear_algebra/__init__.py
+lib/matplotlib/numerix/mlab/__init__.py
+lib/matplotlib/numerix/random_array/__init__.py
 lib/pytz/__init__.py
 lib/pytz/reference.py
 lib/pytz/test_tzinfo.py

examples/anscombe.py

@@ -21,7 +21,7 @@ def fit(x):
 
 
 
-xfit = array( [min(x), max(x) ] )
+xfit = array( [amin(x), amax(x) ] )
 
 subplot(221)
 plot(x,y1,'ks', xfit, fit(xfit), 'r-', lw=2)
@@ -43,7 +43,7 @@ def fit(x):
 
 subplot(224)
 
-xfit = array([min(x4),max(x4)])
+xfit = array([amin(x4),amax(x4)])
 plot(x4,y4,'ks', xfit, fit(xfit), 'r-', lw=2)
 axis([2,20,2,14])
 set(gca(), yticklabels=[], yticks=(4,8,12), xticks=(0,10,20))

examples/axes_demo.py

@@ -11,7 +11,7 @@
 
 # the main axes is subplot(111) by default
 plot(t, s)
-axis([0, 1, 1.1*min(s), 2*max(s) ])
+axis([0, 1, 1.1*amin(s), 2*amax(s) ])
 xlabel('time (s)')
 ylabel('current (nA)')
 title('Gaussian colored noise')

examples/backend_driver.py

@@ -106,7 +106,7 @@ def drive(backend, python='python2.3'):
 #backends = ['Agg', 'Cairo', 'GDK', 'PS', 'SVG', 'Template']
 backends = ['Agg', 'PS', 'SVG', 'Template']
 #backends = [ 'GTK', 'WX', 'TkAgg']
-
+#backends = ['Agg']
 python = 'python2.3'
 for backend in backends:
     print 'testing %s' % backend

examples/colours.py

@@ -2,7 +2,7 @@
 """
 Some simple functions to generate colours.
 """
-from matplotlib.numerix import asarray
+from matplotlib.numerix import asarray, asum
 from matplotlib.mlab import linspace
 from matplotlib.colors import colorConverter
 from matplotlib.numerix import sum
@@ -17,7 +17,7 @@ def pastel(colour, weight=2.4):
         scale = 1.0 / maxc
         rgb = rgb * scale
     # now decrease saturation
-    total = sum(rgb)
+    total = asum(rgb)
     slack = 0
     for x in rgb:
         slack += 1.0 - x

examples/embedding_in_wx3.py

@@ -27,6 +27,7 @@
 from matplotlib.backends.backend_wxagg import Toolbar, FigureCanvasWxAgg
 from matplotlib.figure import Figure
 import matplotlib.numerix as numerix
+import matplotlib.numerix.mlab as mlab
 from matplotlib.mlab import meshgrid
 
 from wxPython.wx import *
@@ -66,7 +67,7 @@ def init_plot_data(self):
         z = numerix.sin(self.x) + numerix.cos(self.y)
         self.im = a.imshow( z, cmap=cm.jet)#, interpolation='nearest')
 
-        zmax = numerix.max(numerix.max(z))-ERR_TOL
+        zmax = mlab.max(mlab.max(z))-ERR_TOL
 
         ymax_i, xmax_i = numerix.nonzero(
             numerix.greater_equal(z, zmax))
@@ -87,7 +88,7 @@ def OnWhiz(self,evt):
         z = numerix.sin(self.x) + numerix.cos(self.y)
         self.im.set_array(z)
 
-        zmax = numerix.max(numerix.max(z))-ERR_TOL
+        zmax = mlab.max(mlab.max(z))-ERR_TOL
         ymax_i, xmax_i = numerix.nonzero(
             numerix.greater_equal(z, zmax))
         if self.im.origin == 'upper':

examples/image_demo2.py

@@ -23,7 +23,7 @@
 title('CT density')
 
 if 0:
-    x = sum(A,0)
+    x = asum(A,0)
     subplot(212)
     bar(arange(w), x)
     xlim(0,h-1)

examples/layer_images.py

@@ -23,7 +23,7 @@ def func3(x,y):
 # for the images their apparent extent could be different due to
 # interpolation edge effects
 
-xmin, xmax, ymin, ymax = min(x), max(x), min(y), max(y)
+xmin, xmax, ymin, ymax = amin(x), amax(x), amin(y), amax(y)
 extent = xmin, xmax, ymin, ymax
 Z1 = array(([0,1]*4 + [1,0]*4)*4); Z1.shape = 8,8  # chessboard
 im1 = imshow(Z1, cmap=cm.gray, interpolation='nearest',

examples/object_picker.py

@@ -10,6 +10,7 @@
 
 from __future__ import division
 from matplotlib.numerix import sin, pi, arange, absolute, sqrt
+from matplotlib.numerix.mlab import amin, amax
 
 import matplotlib
 matplotlib.use('GTKAgg')
@@ -248,7 +249,7 @@ def over_line(line):
             xdata, ydata = trans.numerix_x_y(line.get_xdata(),
                                              line.get_ydata())
             distances = sqrt((x-xdata)**2 + (y-ydata)**2)
-            return min(distances)<epsilon
+            return amin(distances)<epsilon
 
         for ax in self.figure.axes: