matplotlib-checkins Mailing List for matplotlib (Page 201)

Brought to you by: cjgohlke, dsdale, efiring, heeres, and 8 others

matplotlib-checkins — Commit notification. DO NOT POST to this list, just subscribe to it.

You can subscribe to this list here.

2007	Jan	Feb	Mar	Apr	May	Jun	Jul (115)	Aug (120)	Sep (137)	Oct (170)	Nov (461)	Dec (263)
2008	Jan (120)	Feb (74)	Mar (35)	Apr (74)	May (245)	Jun (356)	Jul (240)	Aug (115)	Sep (78)	Oct (225)	Nov (98)	Dec (271)
2009	Jan (132)	Feb (84)	Mar (74)	Apr (56)	May (90)	Jun (79)	Jul (83)	Aug (296)	Sep (214)	Oct (76)	Nov (82)	Dec (66)
2010	Jan (46)	Feb (58)	Mar (51)	Apr (77)	May (58)	Jun (126)	Jul (128)	Aug (64)	Sep (50)	Oct (44)	Nov (48)	Dec (54)
2011	Jan (68)	Feb (52)	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec (1)
2018	Jan	Feb	Mar	Apr	May (1)	Jun	Jul	Aug	Sep	Oct	Nov	Dec

Flat | Threaded

<< < 1 .. 199 200 201 202 203 .. 219 > >> (Page 201 of 219)

SF.net SVN: matplotlib: [3986] branches/transforms/src/_backend_agg.cpp

From: <md...@us...> - 2007-10-23 16:54:56

Revision: 3986
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3986&view=rev
Author:   mdboom
Date:     2007-10-23 09:54:51 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
Fix bug that broke draw_image

Modified Paths:
--------------
    branches/transforms/src/_backend_agg.cpp

Modified: branches/transforms/src/_backend_agg.cpp
===================================================================
--- branches/transforms/src/_backend_agg.cpp	2007-10-23 16:40:25 UTC (rev 3985)
+++ branches/transforms/src/_backend_agg.cpp	2007-10-23 16:54:51 UTC (rev 3986)
@@ -48,17 +48,11 @@
   PyArrayObject* matrix = NULL;
   
   try {
-    if (obj.ptr() == Py_None) {
-      if (errors)
-	throw Py::Exception();
-      return agg::trans_affine();
-    }
+    if (obj.ptr() == Py_None)
+      throw Py::Exception();
     matrix = (PyArrayObject*) PyArray_FromObject(obj.ptr(), PyArray_DOUBLE, 2, 2);
-    if (!matrix) {
-      if (errors)
-	throw Py::Exception();
-      return agg::trans_affine();
-    }
+    if (!matrix)
+      throw Py::Exception();
     if (matrix->nd == 2 || matrix->dimensions[0] == 3 || matrix->dimensions[1] == 3) {
       size_t stride0 = matrix->strides[0];
       size_t stride1 = matrix->strides[1];
@@ -81,16 +75,16 @@
       
       return agg::trans_affine(a, b, c, d, e, f);
     }
+
+    throw Py::Exception();
   } catch (...) {
     if (errors) {
       Py_XDECREF(matrix);
-      throw;
+      throw Py::TypeError("Invalid affine transformation matrix");
     }
   }
 
   Py_XDECREF(matrix);
-  if (errors)
-    throw Py::TypeError("Invalid affine transformation matrix");
   return agg::trans_affine();
 }
 
@@ -797,6 +791,7 @@
 Py::Object
 RendererAgg::draw_image(const Py::Tuple& args) {
   _VERBOSE("RendererAgg::draw_image");
+
   args.verify_length(4, 6);
   
   float x = Py::Float(args[0]);
@@ -807,7 +802,7 @@
   agg::trans_affine clippath_trans;
   if (args.size() == 6) {
     clippath = args[4];
-    clippath_trans = py_to_agg_transformation_matrix(args[5]);
+    clippath_trans = py_to_agg_transformation_matrix(args[5], false);
   }
  
   theRasterizer->reset_clipping();


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3985] branches/transforms/lib/matplotlib

From: <md...@us...> - 2007-10-23 16:40:32

Revision: 3985
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3985&view=rev
Author:   mdboom
Date:     2007-10-23 09:40:25 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
More progress on SVG.  Refactored PS collection drawing to make it
easier to reuse the (fairly complex) code.

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/backend_bases.py
    branches/transforms/lib/matplotlib/backends/backend_ps.py
    branches/transforms/lib/matplotlib/backends/backend_svg.py

Modified: branches/transforms/lib/matplotlib/backend_bases.py
===================================================================
--- branches/transforms/lib/matplotlib/backend_bases.py	2007-10-23 14:30:57 UTC (rev 3984)
+++ branches/transforms/lib/matplotlib/backend_bases.py	2007-10-23 16:40:25 UTC (rev 3985)
@@ -55,13 +55,90 @@
                              offsetTrans, facecolors, edgecolors, linewidths,
                              linestyles, antialiaseds):
         """
-        MGDTODO: Document me.  Explain that often the backend will not
-        want to override this.
+        This provides a fallback implementation of
+        draw_path_collection that makes multiple calls to draw_path.
+        Often, the backend will want to override this in order to
+        render each set of path data only once, and then reference
+        that path multiple times with the different offsets, colors,
+        styles etc.  The methods _iter_collection_raw_paths and
+        _iter_collection are provided to help with (and standardize)
+        the implementation that in each backend.
         """
+        path_ids = []
+        for path, transform in self._iter_collection_raw_paths(
+            master_transform, paths, all_transforms):
+            path_ids.append((path, transform))
+
+        for xo, yo, path_id, gc, rgbFace in self._iter_collection(
+            path_ids, cliprect, clippath, clippath_trans,
+            offsets, offsetTrans, facecolors, edgecolors,
+            linewidths, linestyles, antialiaseds):
+            path, transform = path_id
+            transform = transform.frozen().translate(xo, yo)
+            self.draw_path(gc, path, transform, rgbFace)
+            
+    def _iter_collection_raw_paths(self, master_transform, paths, all_transforms):
+        """
+        This is a helper method (along with _iter_collection) to make
+        it easier to write a space-efficent draw_path_collection
+        implementation in a backend.
+
+        This method yields all of the base path/transform
+        combinations, given a master transform, a list of paths and
+        list of transforms.
+
+        The arguments should be exactly what is passed in to
+        draw_path_collection.
+
+        The backend should take each yielded path and transform and
+        create an object can be referenced (reused) later.
+        """
         Npaths      = len(paths)
+        Ntransforms = len(all_transforms)
+        N           = max(Npaths, Ntransforms)
+
+        if Npaths == 0:
+            return
+
+        for i in xrange(N):
+            path = paths[i % Npaths]
+            transform = all_transforms[i % Ntransforms]
+            if transform is None:
+                transform = transforms.IdentityTransform()
+            transform += master_transform
+            yield path, transform
+
+    def _iter_collection(self, path_ids, cliprect, clippath, clippath_trans,
+                         offsets, offsetTrans, facecolors, edgecolors,
+                         linewidths, linestyles, antialiaseds):
+        """
+        This is a helper method (along with
+        _iter_collection_raw_paths) to make it easier to write a
+        space-efficent draw_path_collection implementation in a
+        backend.
+
+        This method yields all of the path, offset and graphics
+        context combinations to draw the path collection.  The caller
+        should already have looped over the results of
+        _iter_collection_raw_paths to draw this collection.
+
+        The arguments should be the same as that passed into
+        draw_path_collection, with the exception of path_ids, which
+        is a list of arbitrary objects that the backend will use to
+        reference one of the paths created in the
+        _iter_collection_raw_paths stage.
+
+        Each yielded result is of the form:
+
+           xo, yo, path_id, gc, rgbFace
+
+        where xo, yo is an offset; path_id is one of the elements of
+        path_ids; gc is a graphics context and rgbFace is a color to
+        use for filling the path.
+        """
+        Npaths      = len(path_ids)
         Noffsets    = len(offsets)
         N           = max(Npaths, Noffsets)
-        Ntransforms = min(len(all_transforms), N)
         Nfacecolors = len(facecolors)
         Nedgecolors = len(edgecolors)
         Nlinewidths = len(linewidths)
@@ -71,16 +148,10 @@
         if (Nfacecolors == 0 and Nedgecolors == 0) or Npaths == 0:
             return
         
-        ttransforms = []
-        for i in range(Ntransforms):
-            transform = all_transforms[i]
-            if transform is None:
-                transform = transforms.IdentityTransform()
-            ttransforms.append((transform + master_transform).frozen())
-
         toffsets = offsetTrans.transform(offsets)
             
         gc = self.new_gc()
+
         gc.set_clip_rectangle(cliprect)
         if clippath is not None:
             clippath = transforms.TransformedPath(clippath, clippath_trans)
@@ -89,12 +160,9 @@
         if Nfacecolors == 0:
             rgbFace = None
 
-        print linewidths, edgecolors
-            
         for i in xrange(N):
-            path = paths[i % Npaths]
+            path_id = path_ids[i % Npaths]
             xo, yo = toffsets[i % Noffsets]
-            transform = ttransforms[i % Ntransforms].frozen().translate(xo, yo)
             if Nfacecolors:
                 rgbFace = facecolors[i % Nfacecolors]
             if Nedgecolors:
@@ -103,8 +171,8 @@
                 gc.set_dashes(*linestyles[i % Nlinestyles])
             gc.set_antialiased(antialiaseds[i % Naa])
 
-            self.draw_path(gc, path, transform, rgbFace)
-                
+            yield xo, yo, path_id, gc, rgbFace
+        
     def get_image_magnification(self):
         """
         Get the factor by which to magnify images passed to draw_image.

Modified: branches/transforms/lib/matplotlib/backends/backend_ps.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-23 14:30:57 UTC (rev 3984)
+++ branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-23 16:40:25 UTC (rev 3985)
@@ -503,57 +503,22 @@
                              linestyles, antialiaseds):
         write = self._pswriter.write
         
-        Npaths      = len(paths)
-        Noffsets    = len(offsets)
-        N           = max(Npaths, Noffsets)
-        Ntransforms = min(len(all_transforms), N)
-        Ntpaths     = max(Npaths, Ntransforms)
-        Nfacecolors = len(facecolors)
-        Nedgecolors = len(edgecolors)
-        Nlinewidths = len(linewidths)
-        Nlinestyles = len(linestyles)
-        Naa         = len(antialiaseds)
-
-        if (Nfacecolors == 0 and Nedgecolors == 0) or Npaths == 0:
-            return
-        
-        for i in range(Ntpaths):
-            path = paths[i % Npaths]
-            transform = all_transforms[i % Ntransforms]
-            if transform is None:
-                transform = IdentityTransform()
-            transform += master_transform
-
+        path_codes = []
+        for i, (path, transform) in enumerate(self._iter_collection_raw_paths(
+            master_transform, paths, all_transforms)):
             ps_cmd = ['/p%x_%x {' % (self._path_collection_id, i),
                       'newpath', 'translate']
             ps_cmd.append(self._convert_path(path, transform))
             ps_cmd.extend(['} bind def\n'])
             write('\n'.join(ps_cmd))
+            path_codes.append("p%x_%x" % (self._path_collection_id, i))
             
-        toffsets = offsetTrans.transform(offsets)
-            
-        gc = self.new_gc()
+        for xo, yo, path_id, gc, rgbFace in self._iter_collection(
+            path_codes, cliprect, clippath, clippath_trans,
+            offsets, offsetTrans, facecolors, edgecolors,
+            linewidths, linestyles, antialiaseds):
 
-        gc.set_clip_rectangle(cliprect)
-        if clippath is not None:
-            clippath = transforms.TransformedPath(clippath, clippath_trans)
-            gc.set_clippath(clippath)
-        
-        if Nfacecolors == 0:
-            rgbFace = None
-
-        for i in xrange(N):
-            path_id = i % Ntpaths
-            xo, yo = toffsets[i % Noffsets]
-            if Nfacecolors:
-                rgbFace = facecolors[i % Nfacecolors]
-            if Nedgecolors:
-                gc.set_foreground(edgecolors[i % Nedgecolors])
-                gc.set_linewidth(linewidths[i % Nlinewidths])
-                gc.set_dashes(*linestyles[i % Nlinestyles])
-            gc.set_antialiased(antialiaseds[i % Naa])
-
-            ps = "%g %g p%x_%x" % (xo, yo, self._path_collection_id, path_id)
+            ps = "%g %g %s" % (xo, yo, path_id)
             self._draw_ps(ps, gc, rgbFace)
 
         self._path_collection_id += 1
@@ -786,7 +751,9 @@
         cint = gc.get_capstyle()
         self.set_linecap(cint)
         self.set_linedash(*gc.get_dashes())
-                  
+        if self.linewidth > 0 and stroke:
+            self.set_color(*gc.get_rgb()[:3])
+
         cliprect = gc.get_clip_rectangle()
         if cliprect:
             x,y,w,h=cliprect.bounds

Modified: branches/transforms/lib/matplotlib/backends/backend_svg.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_svg.py	2007-10-23 14:30:57 UTC (rev 3984)
+++ branches/transforms/lib/matplotlib/backends/backend_svg.py	2007-10-23 16:40:25 UTC (rev 3985)
@@ -47,16 +47,16 @@
         svgwriter.write(svgProlog%(width,height,width,height))
 
     def _draw_svg_element(self, element, details, gc, rgbFace):
-        cliprect, clipid = self._get_gc_clip_svg(gc)
+        clipid = self._get_gc_clip_svg(gc)
         if clipid is None:
             clippath = ''
         else:
             clippath = 'clip-path="url(#%s)"' % clipid
 
         style = self._get_style(gc, rgbFace)
-        self._svgwriter.write ('%s<%s style="%s" %s %s/>\n' % (
-            cliprect, element, style, clippath, details))
-
+        self._svgwriter.write ('<%s style="%s" %s %s/>\n' % (
+                element, style, clippath, details))
+        
     def _get_font(self, prop):
         key = hash(prop)
         font = self.fontd.get(key)
@@ -108,36 +108,23 @@
         cliprect = gc.get_clip_rectangle()
         clippath, clippath_trans = gc.get_clip_path()
         if clippath is not None:
-            pathkey = (hash(clippath), hash(clippath_trans))
-            path = ''
-            if self._clipd.get(pathkey) is None:
-                self._clipd[pathkey] = clippath
-                path_data = self._convert_path(clippath, clippath_trans)
-                path = """\
-<defs>
-    <clipPath id="%(pathkey)s">
-    <path d="%(path_data)s"/>
-    </clipPath>
-</defs>
-""" % locals()
-            return path, pathkey
+            path_data = self._convert_path(clippath, clippath_trans)
+            path = '<path d="%s"/>' % path_data
         elif cliprect is not None:
-            rectkey = hash(cliprect)
-            box = ''
-            if self._clipd.get(rectkey) is None:
-                self._clipd[rectkey] = cliprect
-                x, y, w, h = cliprect.bounds
-                y = self.height-(y+h)
-                box = """\
-<defs>
-    <clipPath id="%(rectkey)s">
-    <rect x="%(x)s" y="%(y)s" width="%(w)s" height="%(h)s"/>
-    </clipPath>
-</defs>
-""" % locals()
-            return box, rectkey
-        
-        return '', None
+            x, y, w, h = cliprect.bounds
+            y = self.height-(y+h)
+            path = '<rect x="%(x)s" y="%(y)s" width="%(w)s" height="%(h)s"/>' % locals()
+        else:
+            return None
+            
+        id = self._clipd.get(path)
+        if id is None:
+            id = 'p%x' % len(self._clipd)
+            self._svgwriter.write('<defs>\n  <clipPath id="%s">\n' % id)
+            self._svgwriter.write(path)
+            self._svgwriter.write('\n  </clipPath>\n</defs>')
+            self._clipd[path] = id
+        return id
 
     def open_group(self, s):
         self._groupd[s] = self._groupd.get(s,0) + 1
@@ -193,17 +180,17 @@
     def draw_markers(self, gc, marker_path, marker_trans, path, trans, rgbFace=None):
         write = self._svgwriter.write
         
-        key = self._convert_path(marker_path, marker_trans + Affine2D().scale(0, -1.0))
+        key = self._convert_path(marker_path, marker_trans + Affine2D().scale(1.0, -1.0))
         name = self._markers.get(key)
         if name is None:
-            name = 'm_%x' % len(self._markers)
+            name = 'm%x' % len(self._markers)
             write('<defs><path id="%s" d="%s"/></defs>\n' % (name, key))
             self._markers[key] = name
 
         trans_and_flip = self._make_flip_transform(trans)
         tpath = trans_and_flip.transform_path(path)
         for x, y in tpath.vertices:
-            details = 'xlink:href="#%s" transform="translate(%f, %f)"' % (name, x, y)
+            details = 'xlink:href="#%s" x="%f" y="%f"' % (name, x, y)
             self._draw_svg_element('use', details, gc, rgbFace)
             
     def draw_image(self, x, y, im, bbox):
@@ -307,7 +294,7 @@
 
                 svg.append('<use xlink:href="#%s"' % charid)
                 if currx != 0:
-                    svg.append(' transform="translate(%s)"' %
+                    svg.append(' x="%s"' %
                                (currx * (self.FONT_SCALE / fontsize)))
                 svg.append('/>\n')
                 currx += (glyph.linearHoriAdvance / 65536.0)
@@ -364,7 +351,7 @@
 
             if step[0] != 4:
                 currx, curry = step[-2], -step[-1]
-        char_num = 'c_%x' % len(self._char_defs)
+        char_num = 'c%x' % len(self._char_defs)
         path_element = '<path id="%s" d="%s"/>\n' % (char_num, ''.join(path_data))
         self._char_defs[char_id] = (char_num, path_element)
         return char_num


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3984] branches/transforms

From: <md...@us...> - 2007-10-23 14:30:59

Revision: 3984
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3984&view=rev
Author:   mdboom
Date:     2007-10-23 07:30:57 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
Merged revisions 3962-3983 via svnmerge from 
http://matplotlib.svn.sf.net/svnroot/matplotlib/trunk/matplotlib

........
  r3963 | mdboom | 2007-10-18 13:40:30 -0400 (Thu, 18 Oct 2007) | 1 line
  
  Major speedup in PDF backend by using hasattr() rather than 'in dir()'
........
  r3964 | mdboom | 2007-10-18 14:07:06 -0400 (Thu, 18 Oct 2007) | 1 line
  
  Faster version of fill() for PDF writing
........
  r3966 | jdh2358 | 2007-10-19 10:23:48 -0400 (Fri, 19 Oct 2007) | 2 lines
  
  fixed a verbose report bug in patches
........
  r3967 | dsdale | 2007-10-19 10:43:21 -0400 (Fri, 19 Oct 2007) | 2 lines
  
  removed a gsave/grestore pair surrounding _draw_ps
........
  r3968 | dsdale | 2007-10-19 11:37:41 -0400 (Fri, 19 Oct 2007) | 3 lines
  
  changed dependency check for ghostscript, which was failing to identify svn 
  versions
........
  r3969 | dsdale | 2007-10-19 11:41:25 -0400 (Fri, 19 Oct 2007) | 2 lines
  
  whitespace cleanup
........
  r3975 | jdh2358 | 2007-10-21 12:02:07 -0400 (Sun, 21 Oct 2007) | 1 line
  
  added a show method for gtk fig manager
........

Modified Paths:
--------------
    branches/transforms/CHANGELOG
    branches/transforms/lib/matplotlib/__init__.py
    branches/transforms/lib/matplotlib/backends/backend_gtk.py
    branches/transforms/lib/matplotlib/backends/backend_ps.py
    branches/transforms/lib/matplotlib/collections.py
    branches/transforms/lib/matplotlib/config/checkdep.py
    branches/transforms/setup.py
    branches/transforms/setupext.py

Property Changed:
----------------
    branches/transforms/


Property changes on: branches/transforms
___________________________________________________________________
Name: svnmerge-integrated
   - /trunk/matplotlib:1-3961
   + /trunk/matplotlib:1-3983

Modified: branches/transforms/CHANGELOG
===================================================================
--- branches/transforms/CHANGELOG	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/CHANGELOG	2007-10-23 14:30:57 UTC (rev 3984)
@@ -1,3 +1,8 @@
+2007-10-19 Removed a gsave/grestore pair surrounding _draw_ps, which
+           was causing a loss graphics state info (see "EPS output
+           problem - scatter & edgecolors" on mpl-dev, 2007-10-29)
+           - DSD
+
 2007-10-15 Fixed a bug in patches.Ellipse that was broken for
            aspect='auto'.  Scale free ellipses now work properly for
            equal and auto on Agg and PS, and they fall back on a

Modified: branches/transforms/lib/matplotlib/__init__.py
===================================================================
--- branches/transforms/lib/matplotlib/__init__.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/lib/matplotlib/__init__.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -149,13 +149,10 @@
     # --verbose-silent or --verbose-helpful
     _commandLineVerbose = None
 
-
     for arg in sys.argv[1:]:
         if not arg.startswith('--verbose-'): continue
         _commandLineVerbose = arg[10:]
 
-
-
     def __init__(self):
         self.set_level('silent')
         self.fileo = sys.stdout
@@ -195,8 +192,6 @@
             return True
         return False
 
-
-
     def wrap(self, fmt, func, level='helpful', always=True):
         """
         return a callable function that wraps func and reports it
@@ -225,6 +220,7 @@
 
 verbose=Verbose()
 
+
 def checkdep_dvipng():
     try:
         stdin, stdout = os.popen4('dvipng -version')
@@ -243,7 +239,7 @@
             command = 'gs -v'
         stdin, stdout = os.popen4(command)
         line = stdout.readlines()[0]
-        v = line.split()[2]
+        v = line.split()[-2]
         vtest = '.'.join(v.split('.')[:2]) # deal with version numbers like '7.07.1'
         float(vtest)
         return vtest

Modified: branches/transforms/lib/matplotlib/backends/backend_gtk.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_gtk.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/lib/matplotlib/backends/backend_gtk.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -390,7 +390,7 @@
 
         self.window = gtk.Window()
         self.window.set_title("Figure %d" % num)
-
+        
         self.vbox = gtk.VBox()
         self.window.add(self.vbox)
         self.vbox.show()
@@ -439,7 +439,10 @@
                gtk.main_level() >= 1:
             gtk.main_quit()
 
-
+    def show(self):
+        # show the figure window
+        self.window.show()
+        
     def full_screen_toggle (self):
         self._full_screen_flag = not self._full_screen_flag
         if self._full_screen_flag:

Modified: branches/transforms/lib/matplotlib/backends/backend_ps.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -777,7 +777,6 @@
         """
         # local variable eliminates all repeated attribute lookups
         write = self._pswriter.write
-        # write('gsave\n')
         if debugPS and command:
             write("% "+command+"\n")
 
@@ -818,7 +817,6 @@
             write("grestore\n")
         if cliprect:
             write("grestore\n")
-        #write('grestore\n')
 
             
 class GraphicsContextPS(GraphicsContextBase):

Modified: branches/transforms/lib/matplotlib/collections.py
===================================================================
--- branches/transforms/lib/matplotlib/collections.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/lib/matplotlib/collections.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -288,7 +288,6 @@
                 raise ValueError()
         except ValueError:
             raise ValueError('Do not know how to convert %s to dashes'%ls)
-
         self._linestyles = dashes
     set_dashes = set_linestyle = set_linestyles
         

Modified: branches/transforms/lib/matplotlib/config/checkdep.py
===================================================================
--- branches/transforms/lib/matplotlib/config/checkdep.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/lib/matplotlib/config/checkdep.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -1,4 +1,7 @@
-import os, re, sys
+import os
+import re
+import sys
+import warnings
 import distutils.version as version
 
 def dvipng():
@@ -19,7 +22,7 @@
             command = 'gs -v'
         stdin, stdout = os.popen4(command)
         line = stdout.readlines()[0]
-        v = line.split()[2]
+        v = line.split()[-2]
         vtest = '.'.join(v.split('.')[:2]) # deal with version numbers like '7.07.1'
         float(vtest)
         return vtest
@@ -130,4 +133,4 @@
                        'unless ghostscript-%s or later is '
                        'installed on your system') % gs_req)
 
-    return flag
\ No newline at end of file
+    return flag

Modified: branches/transforms/setup.py
===================================================================
--- branches/transforms/setup.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/setup.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -24,8 +24,8 @@
 # it.  It makes very nice antialiased output and also supports alpha
 # blending
 BUILD_AGG          = 1
-BUILD_GTKAGG       = 'auto'
-BUILD_GTK          = 'auto'
+BUILD_GTKAGG       = 1
+BUILD_GTK          = 1
 
 # build TK GUI with Agg renderer ; requires Tkinter Python extension
 # and Tk includes
@@ -271,7 +271,7 @@
 # packagers: set rc['numerix'] and rc['backend'] here to override the auto
 # defaults, eg
 #rc['numerix'] = numpy
-#rc['backend'] = GTKAgg
+#rc['backend'] = 'GTKAgg'
 if sys.platform=='win32':
     rc = dict(backend='TkAgg', numerix='numpy')
 template = file('matplotlibrc.template').read()

Modified: branches/transforms/setupext.py
===================================================================
--- branches/transforms/setupext.py	2007-10-23 14:25:49 UTC (rev 3983)
+++ branches/transforms/setupext.py	2007-10-23 14:30:57 UTC (rev 3984)
@@ -43,9 +43,10 @@
 
 import os
 
+
 basedir = {
     'win32'  : ['win32_static',],
-    'linux2' : ['/usr/local', '/usr',],
+    'linux2' : ['/usr/local', '/usr'],
     'linux'  : ['/usr/local', '/usr',],
     'cygwin' : ['/usr/local', '/usr',],
     'darwin' : ['/sw/lib/freetype2', '/sw/lib/freetype219', '/usr/local',
@@ -170,6 +171,7 @@
     if sys.platform == 'win32':
         has_pkgconfig.cache = False
     else:
+        #print 'environ',  os.environ['PKG_CONFIG_PATH']
         status, output = commands.getstatusoutput("pkg-config --help")
         has_pkgconfig.cache = (status == 0)
     return has_pkgconfig.cache
@@ -192,6 +194,9 @@
 
     status, output = commands.getstatusoutput(
         "%s %s %s" % (pkg_config_exec, flags, packages))
+    #if packages.startswith('pygtk'):
+    #    print 'status', status, output
+    #    raise SystemExit
     if status == 0:
         for token in output.split():
             attr = _flags.get(token[:2], None)


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3983] branches/transforms/lib/matplotlib/backends/ backend_svg.py

From: <md...@us...> - 2007-10-23 14:25:52

Revision: 3983
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3983&view=rev
Author:   mdboom
Date:     2007-10-23 07:25:49 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
First pass at SVG support

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/backends/backend_svg.py

Modified: branches/transforms/lib/matplotlib/backends/backend_svg.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_svg.py	2007-10-23 14:24:49 UTC (rev 3982)
+++ branches/transforms/lib/matplotlib/backends/backend_svg.py	2007-10-23 14:25:49 UTC (rev 3983)
@@ -10,6 +10,8 @@
 from matplotlib.font_manager import findfont, FontProperties
 from matplotlib.ft2font import FT2Font, KERNING_DEFAULT, LOAD_NO_HINTING
 from matplotlib.mathtext import MathTextParser
+from matplotlib.path import Path
+from matplotlib.transforms import Affine2D
 
 from xml.sax.saxutils import escape as escape_xml_text
 
@@ -39,6 +41,7 @@
             self._imaged = {}
         self._clipd = {}
         self._char_defs = {}
+        self._markers = {}
         self.mathtext_parser = MathTextParser('SVG')
         self.fontd = {}
         svgwriter.write(svgProlog%(width,height,width,height))
@@ -74,7 +77,7 @@
         if rgbFace is None:
             fill = 'none'
         else:
-            fill = rgb2hex(rgbFace)
+            fill = rgb2hex(rgbFace[:3])
 
         offset, seq = gc.get_dashes()
         if seq is None:
@@ -103,28 +106,38 @@
 
     def _get_gc_clip_svg(self, gc):
         cliprect = gc.get_clip_rectangle()
-        if cliprect is None:
-            return '', None
-        else:
-            # See if we've already seen this clip rectangle
-            key = hash(cliprect)
-            if self._clipd.get(key) is None:  # If not, store a new clipPath
-                self._clipd[key] = cliprect
-                x, y, w, h = cliprect
+        clippath, clippath_trans = gc.get_clip_path()
+        if clippath is not None:
+            pathkey = (hash(clippath), hash(clippath_trans))
+            path = ''
+            if self._clipd.get(pathkey) is None:
+                self._clipd[pathkey] = clippath
+                path_data = self._convert_path(clippath, clippath_trans)
+                path = """\
+<defs>
+    <clipPath id="%(pathkey)s">
+    <path d="%(path_data)s"/>
+    </clipPath>
+</defs>
+""" % locals()
+            return path, pathkey
+        elif cliprect is not None:
+            rectkey = hash(cliprect)
+            box = ''
+            if self._clipd.get(rectkey) is None:
+                self._clipd[rectkey] = cliprect
+                x, y, w, h = cliprect.bounds
                 y = self.height-(y+h)
-                style = "stroke: gray; fill: none;"
                 box = """\
 <defs>
-    <clipPath id="%(key)s">
-    <rect x="%(x)s" y="%(y)s" width="%(w)s" height="%(h)s"
-    style="%(style)s"/>
+    <clipPath id="%(rectkey)s">
+    <rect x="%(x)s" y="%(y)s" width="%(w)s" height="%(h)s"/>
     </clipPath>
 </defs>
 """ % locals()
-                return box, key
-            else:
-                # return id of previously defined clipPath
-                return '', key
+            return box, rectkey
+        
+        return '', None
 
     def open_group(self, s):
         self._groupd[s] = self._groupd.get(s,0) + 1
@@ -133,20 +146,66 @@
     def close_group(self, s):
         self._svgwriter.write('</g>\n')
 
-    def draw_arc(self, gc, rgbFace, x, y, width, height, angle1, angle2, rotation):
-        """
-        Ignores angles for now
-        """
-        details = 'cx="%s" cy="%s" rx="%s" ry="%s" transform="rotate(%1.1f %s %s)"' % \
-            (x,  self.height-y, width/2.0, height/2.0, -rotation, x, self.height-y)
-        self._draw_svg_element('ellipse', details, gc, rgbFace)
-
     def option_image_nocomposite(self):
         """
         if svg.image_noscale is True, compositing multiple images into one is prohibited
         """
         return rcParams['svg.image_noscale']
 
+    _path_commands = {
+        Path.MOVETO: 'M%s %s',
+        Path.LINETO: 'L%s %s',
+        Path.CURVE3: 'Q%s %s %s %s',
+        Path.CURVE4: 'C%s %s %s %s %s %s'
+        }
+
+    def _make_flip_transform(self, transform):
+        return (transform +
+                Affine2D()
+                .scale(1.0, -1.0)
+                .translate(0.0, self.height))
+    
+    def _convert_path(self, path, transform):
+        tpath = transform.transform_path(path)
+
+        path_data = []
+        appender = path_data.append
+        path_commands = self._path_commands
+        currpos = 0
+        for points, code in tpath.iter_segments():
+            if code == Path.CLOSEPOLY:
+                segment = 'z'
+            else:
+                segment = path_commands[code] % tuple(points)
+
+            if currpos + len(segment) > 75:
+                appender("\n")
+                currpos = 0
+            appender(segment)
+            currpos += len(segment)
+        return ''.join(path_data)
+    
+    def draw_path(self, gc, path, transform, rgbFace=None):
+        trans_and_flip = self._make_flip_transform(transform)
+        path_data = self._convert_path(path, trans_and_flip)
+        self._draw_svg_element('path', 'd="%s"' % path_data, gc, rgbFace)
+
+    def draw_markers(self, gc, marker_path, marker_trans, path, trans, rgbFace=None):
+        write = self._svgwriter.write
+        
+        key = self._convert_path(marker_path, marker_trans + Affine2D().scale(0, -1.0))
+        name = self._markers.get(key)
+        if name is None:
+            name = 'm_%x' % len(self._markers)
+            write('<defs><path id="%s" d="%s"/></defs>\n' % (name, key))
+            self._markers[key] = name
+
+        trans_and_flip = self._make_flip_transform(trans)
+        tpath = trans_and_flip.transform_path(path)
+        for x, y in tpath.vertices:
+            details = 'xlink:href="#%s" transform="translate(%f, %f)"' % (name, x, y)
+            self._draw_svg_element('use', details, gc, rgbFace)
+            
     def draw_image(self, x, y, im, bbox):
         trans = [1,0,0,1,0,0]
         transstr = ''
@@ -204,38 +263,6 @@
             'xlink:href="%s" %s/>\n'%(x/trans[0], (self.height-y)/trans[3]-h, w, h, hrefstr, transstr)
             )
 
-    def draw_line(self, gc, x1, y1, x2, y2):
-        details = 'd="M%s,%sL%s,%s"' % (x1, self.height-y1,
-                                           x2, self.height-y2)
-        self._draw_svg_element('path', details, gc, None)
-
-    def draw_lines(self, gc, x, y, transform=None):
-        if len(x)==0: return
-        if len(x)!=len(y):
-            raise ValueError('x and y must be the same length')
-
-        y = self.height - y
-        details = ['d="M%s,%s' % (x[0], y[0])]
-        xys = zip(x[1:], y[1:])
-        details.extend(['L%s,%s' % tup for tup in xys])
-        details.append('"')
-        details = ''.join(details)
-        self._draw_svg_element('path', details, gc, None)
-
-    def draw_point(self, gc, x, y):
-        # result seems to have a hole in it...
-        self.draw_arc(gc, gc.get_rgb(), x, y, 1, 0, 0, 0, 0)
-
-    def draw_polygon(self, gc, rgbFace, points):
-        details = 'points = "%s"' % ' '.join(['%s,%s'%(x,self.height-y)
-                                              for x, y in points])
-        self._draw_svg_element('polygon', details, gc, rgbFace)
-
-    def draw_rectangle(self, gc, rgbFace, x, y, width, height):
-        details = 'width="%s" height="%s" x="%s" y="%s"' % (width, height, x,
-                                                            self.height-y-height)
-        self._draw_svg_element('rect', details, gc, rgbFace)
-
     def draw_text(self, gc, x, y, s, prop, angle, ismath):
         if ismath:
             self._draw_mathtext(gc, x, y, s, prop, angle)
@@ -467,7 +494,7 @@
         return self._print_svg(filename, svgwriter)
     
     def _print_svg(self, filename, svgwriter):
-        self.figure.dpi.set(72)
+        self.figure.set_dpi(72.0)
         width, height = self.figure.get_size_inches()
         w, h = width*72, height*72
 


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3982] branches/transforms/lib/matplotlib/backends/ backend_pdf.py

From: <md...@us...> - 2007-10-23 14:24:50

Revision: 3982
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3982&view=rev
Author:   mdboom
Date:     2007-10-23 07:24:49 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
Marker objects should be keyed off of whether or not they are filled
and their line width (since the line width affects the bounding box).

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/backends/backend_pdf.py

Modified: branches/transforms/lib/matplotlib/backends/backend_pdf.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_pdf.py	2007-10-23 14:23:19 UTC (rev 3981)
+++ branches/transforms/lib/matplotlib/backends/backend_pdf.py	2007-10-23 14:24:49 UTC (rev 3982)
@@ -1024,7 +1024,7 @@
 
     def markerObject(self, path, trans, fillp, lw):
         """Return name of a marker XObject representing the given path."""
-        key = (path, trans)
+        key = (path, trans, fillp is not None, lw)
         result = self.markers.get(key)
         if result is None:
             name = Name('M%d' % len(self.markers))


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3981] branches/transforms/lib/matplotlib/ projections/polar.py

From: <md...@us...> - 2007-10-23 14:23:21

Revision: 3981
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3981&view=rev
Author:   mdboom
Date:     2007-10-23 07:23:19 -0700 (Tue, 23 Oct 2007)

Log Message:
-----------
Decreasing polar interpolation resolution.

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/projections/polar.py

Modified: branches/transforms/lib/matplotlib/projections/polar.py
===================================================================
--- branches/transforms/lib/matplotlib/projections/polar.py	2007-10-21 21:19:51 UTC (rev 3980)
+++ branches/transforms/lib/matplotlib/projections/polar.py	2007-10-23 14:23:19 UTC (rev 3981)
@@ -151,7 +151,7 @@
         def refresh(self):
             return self.base.refresh()
 
-    RESOLUTION = 100
+    RESOLUTION = 50
         
     def __init__(self, *args, **kwargs):
         """


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3980] trunk/py4science/examples/glass_dots2.py

From: <jd...@us...> - 2007-10-21 21:19:57

Revision: 3980
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3980&view=rev
Author:   jdh2358
Date:     2007-10-21 14:19:51 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
added glass dots2

Added Paths:
-----------
    trunk/py4science/examples/glass_dots2.py

Added: trunk/py4science/examples/glass_dots2.py
===================================================================
--- trunk/py4science/examples/glass_dots2.py	                        (rev 0)
+++ trunk/py4science/examples/glass_dots2.py	2007-10-21 21:19:51 UTC (rev 3980)
@@ -0,0 +1,83 @@
+import numpy as npy
+import numpy.linalg as linalg
+from pylab import figure, show
+
+class Transformer:
+    def __init__(self, axes):
+        self.theta = 0
+        self.dtheta = 0.01
+        self.sx = 1.
+        self.sy = 1.
+        self.dx = 0.001
+        self.axes = axes
+        self.canvas = axes.figure.canvas
+        self.canvas.mpl_connect('button_press_event', self.press)
+        self.canvas.mpl_connect('button_release_event', self.release)        
+        self.canvas.mpl_connect('motion_notify_event', self.move)        
+
+        X1 = self.X1 = npy.matrix(npy.random.rand(2,2000))-0.5
+
+        x1 = X1[0].flat
+        y1 = X1[1].flat
+        x2 = X1[0].flat # no transformation yet
+        y2 = X1[1].flat
+        self.line1, self.line2 = ax.plot(x1, y1,'go', x2, y2, 'ro', markersize=2)
+        self.xlast = None
+        self.ylast = None
+        self.title = ax.set_title('drag the left or right mouse to stretch and rotate', fontweight='bold')
+
+    def press(self, event):
+        'mouse press, save the x and y locations'
+        self.xlast = event.xdata
+        self.ylast = event.ydata
+
+
+    def release(self, event):
+        'release the mouse'
+        self.xlast = None
+        self.ylast = None
+        self.draw()
+        
+    def draw(self):
+        sx, sy, theta = self.sx, self.sy, self.theta
+        a =  sx*npy.cos(theta)
+        b = -sx*npy.sin(theta)
+        c =  sy*npy.sin(theta)
+        d =  sy*npy.cos(theta)
+        M =  npy.matrix([[a,b],[c,d]])
+
+        X2 = M*self.X1        
+        x2 = X2[0].flat
+        y2 = X2[1].flat
+        self.line2.set_data(x2,y2)
+
+        self.canvas.draw()
+        
+    def move(self, event):
+
+        if not event.inaxes: return    # not over axes
+        if self.xlast is None: return  # no initial data
+        if not event.button: return    # no button press
+        
+        dx = event.xdata - self.xlast
+        dy = event.ydata - self.ylast        
+
+        if event.button==1:
+            self.theta += dx
+        elif event.button==3:
+            self.sx += dx
+            self.sy += dy
+            
+        self.title.set_text('sx=%1.2f, sy=%1.2f, theta=%1.2f'%(self.sx, self.sy, self.theta))
+        self.draw()
+        self.xlast = event.xdata
+        self.ylast = event.ydata
+
+
+
+        
+from pylab import subplot, show        
+fig = figure()
+ax = fig.add_subplot(111)
+t = Transformer(ax)
+show()


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3979] trunk/py4science/examples/skel

From: <jd...@us...> - 2007-10-21 21:08:55

Revision: 3979
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3979&view=rev
Author:   jdh2358
Date:     2007-10-21 14:08:53 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
rename skel

Added Paths:
-----------
    trunk/py4science/examples/skel/glass_dots1_skel.py

Removed Paths:
-------------
    trunk/py4science/examples/skel/glass_dots_skel.py

Copied: trunk/py4science/examples/skel/glass_dots1_skel.py (from rev 3978, trunk/py4science/examples/skel/glass_dots_skel.py)
===================================================================
--- trunk/py4science/examples/skel/glass_dots1_skel.py	                        (rev 0)
+++ trunk/py4science/examples/skel/glass_dots1_skel.py	2007-10-21 21:08:53 UTC (rev 3979)
@@ -0,0 +1,77 @@
+"""
+Moire patterns from random dot fields
+
+http://en.wikipedia.org/wiki/Moir%C3%A9_pattern
+
+See L. Glass. 'Moire effect from random dots' Nature 223, 578580 (1969).
+"""
+from numpy import cos, sin, pi, matrix
+import numpy as npy
+import numpy.linalg as linalg
+from pylab import figure, show
+
+def csqrt(x):
+    """
+    sqrt func that handles returns sqrt(x)j for x<0
+    """
+    XXX
+    
+def myeig(M):
+    """
+    compute eigen values and eigenvectors analytically
+
+    Solve quadratic:
+
+      lamba^2 - tau*lambda + Delta = 0
+
+    where tau = trace(M) and Delta = Determinant(M)
+    
+    """
+    XXX
+    return lambda1, lambda2
+    
+# 2000 random x,y points in the interval[-0.5 ... 0.5]
+X1 = XXX
+
+name =  'saddle'
+#sx, sy, angle = XXX
+
+#name = 'center'
+#sx, sy, angle = XXX
+
+#name = 'stable focus'  # spiral
+#sx, sy, angle = XXX
+
+name= 'spiral'
+sx, sy, angle = XXX
+
+theta = angle * pi/180.  # the rotation in radians
+
+
+# the scaling matrix
+# | sx 0 |
+# | 0 sy |
+S = XXX
+
+# the rotation matrix
+# | cos(theta)  -sin(theta) |
+# | sin(theta)  cos(theta)  |
+R = XXX
+
+# the transformation is the matrix product of the scaling and rotation
+M = XXX
+
+# compute the eigenvalues using numpy linear algebra
+vals, vecs = XXX
+print 'numpy eigenvalues', vals
+
+# compare with the analytic values from myeig
+avals = myeig(M)
+print 'analytic eigenvalues', avals
+
+# transform X1 by the matrix M
+X2 = XXX
+
+# plot the original x,y as green dots and the transformed x, y as red
+# dots
+show()

Deleted: trunk/py4science/examples/skel/glass_dots_skel.py
===================================================================
--- trunk/py4science/examples/skel/glass_dots_skel.py	2007-10-21 21:08:33 UTC (rev 3978)
+++ trunk/py4science/examples/skel/glass_dots_skel.py	2007-10-21 21:08:53 UTC (rev 3979)
@@ -1,77 +0,0 @@
-"""
-Moire patterns from random dot fields
-
-http://en.wikipedia.org/wiki/Moir%C3%A9_pattern
-
-See L. Glass. 'Moire effect from random dots' Nature 223, 578580 (1969).
-"""
-from numpy import cos, sin, pi, matrix
-import numpy as npy
-import numpy.linalg as linalg
-from pylab import figure, show
-
-def csqrt(x):
-    """
-    sqrt func that handles returns sqrt(x)j for x<0
-    """
-    XXX
-    
-def myeig(M):
-    """
-    compute eigen values and eigenvectors analytically
-
-    Solve quadratic:
-
-      lamba^2 - tau*lambda + Delta = 0
-
-    where tau = trace(M) and Delta = Determinant(M)
-    
-    """
-    XXX
-    return lambda1, lambda2
-    
-# 2000 random x,y points in the interval[-0.5 ... 0.5]
-X1 = XXX
-
-name =  'saddle'
-#sx, sy, angle = XXX
-
-#name = 'center'
-#sx, sy, angle = XXX
-
-#name = 'stable focus'  # spiral
-#sx, sy, angle = XXX
-
-name= 'spiral'
-sx, sy, angle = XXX
-
-theta = angle * pi/180.  # the rotation in radians
-
-
-# the scaling matrix
-# | sx 0 |
-# | 0 sy |
-S = XXX
-
-# the rotation matrix
-# | cos(theta)  -sin(theta) |
-# | sin(theta)  cos(theta)  |
-R = XXX
-
-# the transformation is the matrix product of the scaling and rotation
-M = XXX
-
-# compute the eigenvalues using numpy linear algebra
-vals, vecs = XXX
-print 'numpy eigenvalues', vals
-
-# compare with the analytic values from myeig
-avals = myeig(M)
-print 'analytic eigenvalues', avals
-
-# transform X1 by the matrix M
-X2 = XXX
-
-# plot the original x,y as green dots and the transformed x, y as red
-# dots
-show()


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3978] trunk/py4science/examples

From: <jd...@us...> - 2007-10-21 21:08:35

Revision: 3978
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3978&view=rev
Author:   jdh2358
Date:     2007-10-21 14:08:33 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
minor tweaks to glass dots

Modified Paths:
--------------
    trunk/py4science/examples/glass_dots1.py
    trunk/py4science/examples/skel/glass_dots_skel.py

Modified: trunk/py4science/examples/glass_dots1.py
===================================================================
--- trunk/py4science/examples/glass_dots1.py	2007-10-21 20:57:54 UTC (rev 3977)
+++ trunk/py4science/examples/glass_dots1.py	2007-10-21 21:08:33 UTC (rev 3978)
@@ -42,16 +42,13 @@
 X1 = matrix(npy.random.rand(2,2000))-0.5
 
 name =  'saddle'
-#sx, sy, angle = 1.05, 0.95, 0.
+sx, sy, angle = 1.05, 0.95, 0.
 
-#name = 'focus'
-#sx, sy, angle = 1.05, 0.95, 2.6
-
 #name = 'center'
 #sx, sy, angle = 1., 1., 2.5
 
-name= 'spiral'
-sx, sy, angle = 0.95, 0.95, 2.5
+#name= 'stable focus'  # spiral
+#sx, sy, angle = 0.95, 0.95, 2.5
 
 theta = angle * pi/180.
 
@@ -72,7 +69,7 @@
 avals = myeig(M)
 print 'analytic eigenvalues', avals
 
-# transform X by the matrix
+# transform X1 by the matrix
 X2 = M*X1
 
 # plot the original x,y as green dots and the transformed x, y as red

Modified: trunk/py4science/examples/skel/glass_dots_skel.py
===================================================================
--- trunk/py4science/examples/skel/glass_dots_skel.py	2007-10-21 20:57:54 UTC (rev 3977)
+++ trunk/py4science/examples/skel/glass_dots_skel.py	2007-10-21 21:08:33 UTC (rev 3978)
@@ -36,10 +36,10 @@
 name =  'saddle'
 #sx, sy, angle = XXX
 
-#name = 'focus'
+#name = 'center'
 #sx, sy, angle = XXX
 
-#name = 'center'
+#name = 'stable focus'  # spiral
 #sx, sy, angle = XXX
 
 name= 'spiral'


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3977] trunk/py4science

From: <jd...@us...> - 2007-10-21 20:57:56

Revision: 3977
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3977&view=rev
Author:   jdh2358
Date:     2007-10-21 13:57:54 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
added glass moire pattern example

Added Paths:
-----------
    trunk/py4science/examples/glass_dots1.py
    trunk/py4science/examples/skel/glass_dots_skel.py
    trunk/py4science/workbook/fig/glass_dots1.eps
    trunk/py4science/workbook/fig/glass_dots1.png

Added: trunk/py4science/examples/glass_dots1.py
===================================================================
--- trunk/py4science/examples/glass_dots1.py	                        (rev 0)
+++ trunk/py4science/examples/glass_dots1.py	2007-10-21 20:57:54 UTC (rev 3977)
@@ -0,0 +1,95 @@
+"""
+Moire patterns from random dot fields
+
+http://en.wikipedia.org/wiki/Moir%C3%A9_pattern
+
+See L. Glass. 'Moire effect from random dots' Nature 223, 578580 (1969).
+"""
+from numpy import cos, sin, pi, matrix
+import numpy as npy
+import numpy.linalg as linalg
+from pylab import figure, show
+
+def csqrt(x):
+    """
+    sqrt func that handles returns sqrt(x)j for x<0
+    """
+    if x<0: return complex(0, npy.sqrt(abs(x)))
+    else: return npy.sqrt(x)
+
+def myeig(M):
+    """
+    compute eigen values and eigenvectors analytically
+
+    Solve quadratic:
+
+      lamba^2 - tau*lambda + Delta = 0
+
+    where tau = trace(M) and Delta = Determinant(M)
+    
+    """
+
+    a,b = M[0,0], M[0,1]
+    c,d = M[1,0], M[1,1]
+    tau = a+d       # the trace
+    delta = a*d-b*c # the determinant
+
+    lambda1 = (tau + csqrt(tau**2 - 4*delta))/2.
+    lambda2 = (tau - csqrt(tau**2 - 4*delta))/2.
+    return lambda1, lambda2
+    
+# 2000 random x,y points in the interval[-0.5 ... 0.5]
+X1 = matrix(npy.random.rand(2,2000))-0.5
+
+name =  'saddle'
+#sx, sy, angle = 1.05, 0.95, 0.
+
+#name = 'focus'
+#sx, sy, angle = 1.05, 0.95, 2.6
+
+#name = 'center'
+#sx, sy, angle = 1., 1., 2.5
+
+name= 'spiral'
+sx, sy, angle = 0.95, 0.95, 2.5
+
+theta = angle * pi/180.
+
+
+S = matrix([[sx, 0],
+            [0, sy]])
+
+R = matrix([[cos(theta),  -sin(theta)],
+            [sin(theta), cos(theta)],])
+
+M = S*R  # rotate then stretch
+
+# compute the eigenvalues using numpy linear algebra
+vals, vecs = linalg.eig(M)
+print 'numpy eigenvalues', vals
+
+# compare with the analytic values from myeig
+avals = myeig(M)
+print 'analytic eigenvalues', avals
+
+# transform X by the matrix
+X2 = M*X1
+
+# plot the original x,y as green dots and the transformed x, y as red
+# dots
+fig = figure()
+ax = fig.add_subplot(111)
+
+x1 = X1[0].flat
+y1 = X1[1].flat
+x2 = X2[0].flat
+y2 = X2[1].flat
+
+ax = fig.add_subplot(111)
+line1, line2 = ax.plot(x1, y1, 'go', x2, y2, 'ro', markersize=2)
+ax.set_title(name)
+
+
+fig.savefig('glass_dots1.png', dpi=100)
+fig.savefig('glass_dots1.eps', dpi=100)
+show()

Added: trunk/py4science/examples/skel/glass_dots_skel.py
===================================================================
--- trunk/py4science/examples/skel/glass_dots_skel.py	                        (rev 0)
+++ trunk/py4science/examples/skel/glass_dots_skel.py	2007-10-21 20:57:54 UTC (rev 3977)
@@ -0,0 +1,77 @@
+"""
+Moire patterns from random dot fields
+
+http://en.wikipedia.org/wiki/Moir%C3%A9_pattern
+
+See L. Glass. 'Moire effect from random dots' Nature 223, 578580 (1969).
+"""
+from numpy import cos, sin, pi, matrix
+import numpy as npy
+import numpy.linalg as linalg
+from pylab import figure, show
+
+def csqrt(x):
+    """
+    sqrt func that handles returns sqrt(x)j for x<0
+    """
+    XXX
+    
+def myeig(M):
+    """
+    compute eigen values and eigenvectors analytically
+
+    Solve quadratic:
+
+      lamba^2 - tau*lambda + Delta = 0
+
+    where tau = trace(M) and Delta = Determinant(M)
+    
+    """
+    XXX
+    return lambda1, lambda2
+    
+# 2000 random x,y points in the interval[-0.5 ... 0.5]
+X1 = XXX
+
+name =  'saddle'
+#sx, sy, angle = XXX
+
+#name = 'focus'
+#sx, sy, angle = XXX
+
+#name = 'center'
+#sx, sy, angle = XXX
+
+name= 'spiral'
+sx, sy, angle = XXX
+
+theta = angle * pi/180.  # the rotation in radians
+
+
+# the scaling matrix
+# | sx 0 |
+# | 0 sy |
+S = XXX
+
+# the rotation matrix
+# | cos(theta)  -sin(theta) |
+# | sin(theta)  cos(theta)  |
+R = XXX
+
+# the transformation is the matrix product of the scaling and rotation
+M = XXX
+
+# compute the eigenvalues using numpy linear algebra
+vals, vecs = XXX
+print 'numpy eigenvalues', vals
+
+# compare with the analytic values from myeig
+avals = myeig(M)
+print 'analytic eigenvalues', avals
+
+# transform X1 by the matrix M
+X2 = XXX
+
+# plot the original x,y as green dots and the transformed x, y as red
+# dots
+show()

Added: trunk/py4science/workbook/fig/glass_dots1.eps
===================================================================
--- trunk/py4science/workbook/fig/glass_dots1.eps	                        (rev 0)
+++ trunk/py4science/workbook/fig/glass_dots1.eps	2007-10-21 20:57:54 UTC (rev 3977)
@@ -0,0 +1,4719 @@
+%!PS-Adobe-3.0 EPSF-3.0
+%%Title: glass_dots1.eps
+%%Creator: matplotlib version 0.90.1, http://matplotlib.sourceforge.net/
+%%CreationDate: Sun Oct 21 15:51:47 2007
+%%Orientation: portrait
+%%BoundingBox: 11 173 600 618
+%%EndComments
+%%BeginProlog
+/mpldict 7 dict def
+mpldict begin
+/m { moveto } bind def
+/l { lineto } bind def
+/r { rlineto } bind def
+/box {
+m
+1 index 0 r
+0 exch r
+neg 0 r
+closepath
+} bind def
+/clipbox {
+box
+clip
+newpath
+} bind def
+/ellipse {
+newpath
+matrix currentmatrix 7 1 roll
+translate
+scale
+0 0 1 5 3 roll arc
+setmatrix
+closepath
+} bind def
+%!PS-Adobe-3.0 Resource-Font
+%%Title: Bitstream Vera Sans
+%%Copyright: Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved.
+%%Creator: Converted from TrueType by PPR
+25 dict begin
+/_d{bind def}bind def
+/_m{moveto}_d
+/_l{lineto}_d
+/_cl{closepath eofill}_d
+/_c{curveto}_d
+/_sc{7 -1 roll{setcachedevice}{pop pop pop pop pop pop}ifelse}_d
+/_e{exec}_d
+/FontName /BitstreamVeraSans-Roman def
+/PaintType 0 def
+/FontMatrix[.001 0 0 .001 0 0]def
+/FontBBox[-182 -235 1287 928]def
+/FontType 3 def
+/Encoding StandardEncoding def
+/FontInfo 10 dict dup begin
+/FamilyName (Bitstream Vera Sans) def
+/FullName (Bitstream Vera Sans) def
+/Notice (Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved. Bitstream Vera is a trademark of Bitstream, Inc.) def
+/Weight (Roman) def
+/Version (Release 1.10) def
+/ItalicAngle 0.0 def
+/isFixedPitch false def
+/UnderlinePosition -213 def
+/UnderlineThickness 143 def
+end readonly def
+/CharStrings 12 dict dup begin
+/hyphen{361 0 49 234 312 314 _sc
+49 314 _m
+312 314 _l
+312 234 _l
+49 234 _l
+49 314 _l
+_cl}_d
+/period{318 0 107 0 210 124 _sc
+107 124 _m
+210 124 _l
+210 0 _l
+107 0 _l
+107 124 _l
+_cl}_d
+/zero{636 0 66 -13 570 742 _sc
+318 664 _m
+267 664 229 639 203 589 _c
+177 539 165 464 165 364 _c
+165 264 177 189 203 139 _c
+229 89 267 64 318 64 _c
+369 64 407 89 433 139 _c
+458 189 471 264 471 364 _c
+471 464 458 539 433 589 _c
+407 639 369 664 318 664 _c
+318 742 _m
+399 742 461 709 505 645 _c
+548 580 570 486 570 364 _c
+570 241 548 147 505 83 _c
+461 19 399 -13 318 -13 _c
+236 -13 173 19 130 83 _c
+87 147 66 241 66 364 _c
+66 486 87 580 130 645 _c
+173 709 236 742 318 742 _c
+_cl}_d
+/two{{636 0 73 0 536 742 _sc
+192 83 _m
+536 83 _l
+536 0 _l
+73 0 _l
+73 83 _l
+110 121 161 173 226 239 _c
+290 304 331 346 348 365 _c
+380 400 402 430 414 455 _c
+426 479 433 504 433 528 _c
+433 566 419 598 392 622 _c
+365 646 330 659 286 659 _c
+255 659 222 653 188 643 _c
+154 632 117 616 78 594 _c
+78 694 _l
+118 710 155 722 189 730 _c
+223 738 255 742 284 742 _c
+359 742 419 723 464 685 _c
+509 647 532 597 532 534 _c
+532 504 526 475 515 449 _c
+504 422 484 390 454 354 _c
+446 344 420 317 376 272 _c
+332 227 271 164 192 83 _c
+_cl}_e}_d
+/four{636 0 49 0 580 729 _sc
+378 643 _m
+129 254 _l
+378 254 _l
+378 643 _l
+352 729 _m
+476 729 _l
+476 254 _l
+580 254 _l
+580 172 _l
+476 172 _l
+476 0 _l
+378 0 _l
+378 172 _l
+49 172 _l
+49 267 _l
+352 729 _l
+_cl}_d
+/six{{636 0 70 -13 573 742 _sc
+330 404 _m
+286 404 251 388 225 358 _c
+199 328 186 286 186 234 _c
+186 181 199 139 225 109 _c
+251 79 286 64 330 64 _c
+374 64 409 79 435 109 _c
+461 139 474 181 474 234 _c
+474 286 461 328 435 358 _c
+409 388 374 404 330 404 _c
+526 713 _m
+526 623 _l
+501 635 476 644 451 650 _c
+425 656 400 659 376 659 _c
+310 659 260 637 226 593 _c
+192 549 172 482 168 394 _c
+187 422 211 444 240 459 _c
+269 474 301 482 336 482 _c
+409 482 467 459 509 415 _c
+551 371 573 310 573 234 _c
+573 159 550 99 506 54 _c
+462 9 403 -13 330 -13 _c
+246 -13 181 19 137 83 _c
+92 147 70 241 70 364 _c
+70 479 97 571 152 639 _c
+206 707 280 742 372 742 _c
+}_e{396 742 421 739 447 735 _c
+472 730 498 723 526 713 _c
+_cl}_e}_d
+/a{{613 0 60 -13 522 560 _sc
+343 275 _m
+270 275 220 266 192 250 _c
+164 233 150 205 150 165 _c
+150 133 160 107 181 89 _c
+202 70 231 61 267 61 _c
+317 61 357 78 387 114 _c
+417 149 432 196 432 255 _c
+432 275 _l
+343 275 _l
+522 312 _m
+522 0 _l
+432 0 _l
+432 83 _l
+411 49 385 25 355 10 _c
+325 -5 287 -13 243 -13 _c
+187 -13 142 2 109 33 _c
+76 64 60 106 60 159 _c
+60 220 80 266 122 298 _c
+163 329 224 345 306 345 _c
+432 345 _l
+432 354 _l
+432 395 418 427 391 450 _c
+364 472 326 484 277 484 _c
+245 484 215 480 185 472 _c
+155 464 127 453 100 439 _c
+100 522 _l
+}_e{132 534 164 544 195 550 _c
+226 556 256 560 286 560 _c
+365 560 424 539 463 498 _c
+502 457 522 395 522 312 _c
+_cl}_e}_d
+/i{278 0 94 0 184 760 _sc
+94 547 _m
+184 547 _l
+184 0 _l
+94 0 _l
+94 547 _l
+94 760 _m
+184 760 _l
+184 646 _l
+94 646 _l
+94 760 _l
+_cl}_d
+/l{278 0 94 0 184 760 _sc
+94 760 _m
+184 760 _l
+184 0 _l
+94 0 _l
+94 760 _l
+_cl}_d
+/p{{635 0 91 -207 580 560 _sc
+181 82 _m
+181 -207 _l
+91 -207 _l
+91 547 _l
+181 547 _l
+181 464 _l
+199 496 223 520 252 536 _c
+281 552 316 560 356 560 _c
+422 560 476 533 518 481 _c
+559 428 580 359 580 273 _c
+580 187 559 117 518 65 _c
+476 13 422 -13 356 -13 _c
+316 -13 281 -5 252 10 _c
+223 25 199 49 181 82 _c
+487 273 _m
+487 339 473 390 446 428 _c
+418 466 381 485 334 485 _c
+286 485 249 466 222 428 _c
+194 390 181 339 181 273 _c
+181 207 194 155 222 117 _c
+249 79 286 61 334 61 _c
+381 61 418 79 446 117 _c
+473 155 487 207 487 273 _c
+_cl}_e}_d
+/r{411 0 91 0 411 560 _sc
+411 463 _m
+401 469 390 473 378 476 _c
+366 478 353 480 339 480 _c
+288 480 249 463 222 430 _c
+194 397 181 350 181 288 _c
+181 0 _l
+91 0 _l
+91 547 _l
+181 547 _l
+181 462 _l
+199 495 224 520 254 536 _c
+284 552 321 560 365 560 _c
+371 560 378 559 386 559 _c
+393 558 401 557 411 555 _c
+411 463 _l
+_cl}_d
+/s{{521 0 54 -13 472 560 _sc
+443 531 _m
+443 446 _l
+417 458 391 468 364 475 _c
+336 481 308 485 279 485 _c
+234 485 200 478 178 464 _c
+156 450 145 430 145 403 _c
+145 382 153 366 169 354 _c
+185 342 217 330 265 320 _c
+296 313 _l
+360 299 405 279 432 255 _c
+458 230 472 195 472 151 _c
+472 100 452 60 412 31 _c
+372 1 316 -13 246 -13 _c
+216 -13 186 -10 154 -5 _c
+122 0 89 8 54 20 _c
+54 113 _l
+87 95 120 82 152 74 _c
+184 65 216 61 248 61 _c
+290 61 323 68 346 82 _c
+368 96 380 117 380 144 _c
+380 168 371 187 355 200 _c
+339 213 303 226 247 238 _c
+216 245 _l
+160 257 119 275 95 299 _c
+70 323 58 356 58 399 _c
+58 450 76 490 112 518 _c
+148 546 200 560 268 560 _c
+}_e{301 560 332 557 362 552 _c
+391 547 418 540 443 531 _c
+_cl}_e}_d
+end readonly def
+
+/BuildGlyph
+ {exch begin
+ CharStrings exch
+ 2 copy known not{pop /.notdef}if
+ true 3 1 roll get exec
+ end}_d
+
+/BuildChar {
+ 1 index /Encoding get exch get
+ 1 index /BuildGlyph get exec
+}_d
+
+FontName currentdict end definefont pop
+%%EOF
+end
+%%EndProlog
+mpldict begin
+11.7 173.7 translate
+588.6 444.6 0 0 clipbox
+gsave
+1.000 setgray
+1.000 setlinewidth
+0 setlinejoin
+2 setlinecap
+[] 0 setdash
+0 0 m
+0 444.6 l
+588.6 444.6 l
+588.6 0 l
+closepath
+gsave
+fill
+grestore
+stroke
+grestore
+gsave
+0.000 setgray
+73.575 44.46 m
+73.575 400.14 l
+529.74 400.14 l
+529.74 44.46 l
+closepath
+gsave
+1.000 setgray
+fill
+grestore
+stroke
+grestore
+0.500 setlinewidth
+0 setlinecap
+gsave
+456.165 355.68 73.575 44.46 clipbox
+/o { gsave
+newpath
+translate
+1 0 m
+0.992115 0.125333 l
+0.968583 0.24869 l
+0.929776 0.368125 l
+0.876307 0.481754 l
+0.809017 0.587785 l
+0.728969 0.684547 l
+0.637424 0.770513 l
+0.535827 0.844328 l
+0.425779 0.904827 l
+0.309017 0.951057 l
+0.187381 0.982287 l
+0.0627905 0.998027 l
+-0.0627905 0.998027 l
+-0.187381 0.982287 l
+-0.309017 0.951057 l
+-0.425779 0.904827 l
+-0.535827 0.844328 l
+-0.637424 0.770513 l
+-0.728969 0.684547 l
+-0.809017 0.587785 l
+-0.876307 0.481754 l
+-0.929776 0.368125 l
+-0.968583 0.24869 l
+-0.992115 0.125333 l
+-1 -3.21625e-16 l
+-0.992115 -0.125333 l
+-0.968583 -0.24869 l
+-0.929776 -0.368125 l
+-0.876307 -0.481754 l
+-0.809017 -0.587785 l
+-0.728969 -0.684547 l
+-0.637424 -0.770513 l
+-0.535827 -0.844328 l
+-0.425779 -0.904827 l
+-0.309017 -0.951057 l
+-0.187381 -0.982287 l
+-0.0627905 -0.998027 l
+0.0627905 -0.998027 l
+0.187381 -0.982287 l
+0.309017 -0.951057 l
+0.425779 -0.904827 l
+0.535827 -0.844328 l
+0.637424 -0.770513 l
+0.728969 -0.684547 l
+0.809017 -0.587785 l
+0.876307 -0.481754 l
+0.929776 -0.368125 l
+0.968583 -0.24869 l
+0.992115 -0.125333 l
+closepath
+gsave
+0.000 0.500 0.000 setrgbcolor
+fill
+grestore
+stroke
+grestore } bind def
+138.872 320.348 o
+181.354 288.083 o
+357.964 322.431 o
+202.996 278.417 o
+479.1 277 o
+260.058 194.004 o
+234.101 204.196 o
+410.704 284.956 o
+199.64 248.815 o
+134.449 296.136 o
+330.037 298.035 o
+344.126 345.135 o
+425.543 352.504 o
+415.221 304.834 o
+197.037 276.79 o
+170.12 254.009 o
+190.512 250.384 o
+324.695 186.827 o
+432.329 245.359 o
+336.339 125.487 o
+287.791 89.5204 o
+381.68 184.249 o
+230.466 295.632 o
+305.554 357.729 o
+249.578 281.911 o
+321.573 358.13 o
+350.908 176.412 o
+257.443 213.254 o
+450.114 165.748 o
+408.095 324.504 o
+431.163 227.839 o
+292.916 130.22 o
+468.11 283.741 o
+172.187 290.341 o
+194.8 238.493 o
+177.859 363.466 o
+430.112 76.7245 o
+201.049 181.351 o
+440.312 241.362 o
+207.565 190.797 o
+339.893 261.469 o
+454.246 207.628 o
+352.919 105.208 o
+116.475 107.987 o
+395.899 203.544 o
+180.572 294.822 o
+300.245 74.522 o
+479.409 259.564 o
+372.722 87.9586 o
+385.381 176.45 o
+143.08 185.238 o
+317.094 266.568 o
+263.482 142.769 o
+398.103 241.449 o
+365.896 94.5178 o
+237.9 180.849 o
+333.754 280.745 o
+207.62 243.104 o
+118.806 295.197 o
+126.636 157.277 o
+218.643 106.715 o
+254.875 118.286 o
+147.65 195.146 o
+225.248 74.5246 o
+355.066 268.333 o
+290.841 344.053 o
+403.564 288.753 o
+258.632 169.655 o
+131.654 215.147 o
+390.072 276 o
+248.767 76.1061 o
+341.527 102.451 o
+308.153 362.83 o
+389.696 307.53 o
+341.991 320.747 o
+145.6 310.19 o
+458.027 139.011 o
+156.005 334.202 o
+199.174 175.718 o
+231.551 350.143 o
+419.825 158.443 o
+296.386 91.4108 o
+128.923 366.976 o
+353.954 191.492 o
+241.684 135.018 o
+363.991 339.889 o
+126.512 362.686 o
+199.101 103.509 o
+484.743 363.956 o
+305.536 131.847 o
+119.381 348.64 o
+416.115 104.531 o
+286.516 309.527 o
+199.992 222.584 o
+355.444 144.896 o
+427.214 234.784 o
+168.757 329.679 o
+455.83 88.4333 o
+285.905 172.676 o
+156.026 164.155 o
+188.071 273.666 o
+187.916 136.562 o
+407.909 323.552 o
+135.324 258.64 o
+287.746 278.231 o
+207.449 179.942 o
+421.334 305.842 o
+314.663 190.183 o
+351.187 213.08 o
+176.022 282.36 o
+138.019 327.616 o
+169.827 96.2728 o
+464.91 121.37 o
+373.796 366.374 o
+145.208 109.952 o
+175.089 194.515 o
+294.383 338.347 o
+249.915 156.283 o
+119.525 111.341 o
+244.53 103.544 o
+409.808 292.664 o
+308.461 359.93 o
+287.776 348.745 o
+173.773 346.218 o
+425.432 186.799 o
+254.747 134.214 o
+256.286 180.301 o
+419.538 85.9271 o
+250.207 178.698 o
+300.684 87.3235 o
+131.184 257.7 o
+192.259 161.9 o
+456.53 166.659 o
+316.836 86.7519 o
+407.628 106.727 o
+190.232 273.035 o
+312.55 146.774 o
+428.198 204 o
+368.553 150.419 o
+278.036 191.729 o
+224.856 121.302 o
+150.41 315.313 o
+260.425 231.498 o
+309.768 184.187 o
+304.958 153.568 o
+112.915 276.316 o
+309.354 177.085 o
+336.929 167.493 o
+180.567 223.19 o
+229.777 297.53 o
+455.815 283.428 o
+421.887 290.296 o
+446.669 119.702 o
+487.66 108.829 o
+182.089 346.473 o
+145.699 137.244 o
+192.039 250.998 o
+398.202 216.872 o
+231.752 364.519 o
+240.127 90.9055 o
+217.391 202.029 o
+392.399 239.735 o
+437.822 77.0468 o
+224.397 276.118 o
+279.636 363.825 o
+193.176 175.589 o
+363.001 101.526 o
+274.929 209.605 o
+272.618 205.443 o
+300.278 165.258 o
+337.662 79.5305 o
+187.498 184.977 o
+228.513 106.44 o
+478.56 252.935 o
+329.047 325.459 o
+359.016 176.736 o
+359.717 274.494 o
+332.58 255.906 o
+491.435 77.3955 o
+114.727 254.287 o
+402.668 333.981 o
+194.344 121.25 o
+206.262 295.478 o
+282.273 106.178 o
+389.608 116.418 o
+126.291 207.928 o
+283.15 346.093 o
+467.219 123.922 o
+421.747 300.785 o
+314.434 291.814 o
+390.887 238.758 o
+462.319 202.901 o
+202.757 79.7886 o
+400.616 337.799 o
+212.296 155.408 o
+312.638 328.75 o
+117.786 282.263 o
+119.206 245.575 o
+476.181 164.201 o
+235.461 316.76 o
+405.659 189.849 o
+146.85 351.285 o
+196.558 148.499 o
+116.967 250.082 o
+179.907 251.714 o
+294.156 184.762 o
+401.435 333.759 o
+311.458 158.996 o
+136.051 229.14 o
+209.875 81.7894 o
+361.768 271.649 o
+483.416 366.668 o
+481.696 140.925 o
+417.553 108.185 o
+375.311 356.113 o
+387.829 105.223 o
+116.154 268.893 o
+467.238 125.51 o
+267.525 293.436 o
+304.527 340.005 o
+122.639 171.326 o
+190.546 350.555 o
+469.441 191.214 o
+304.82 242.737 o
+122.584 228.077 o
+132.956 175.495 o
+279.462 218.933 o
+164.331 250.829 o
+341.961 98.307 o
+307.81 281.154 o
+277.775 189.146 o
+417.441 132.333 o
+199.899 155.381 o
+443.963 91.6086 o
+473.56 354.32 o
+387.867 278.511 o
+421.998 298.133 o
+150.223 288.239 o
+184.043 262.236 o
+272.41 279.249 o
+461.759 368.618 o
+150.902 334.741 o
+400.53 354.612 o
+242.094 182.986 o
+308.826 215.268 o
+376.791 289.966 o
+122.726 250.887 o
+405.98 98.6444 o
+214.821 241.789 o
+309.771 112.835 o
+470.463 346.819 o
+279.301 249.964 o
+430.109 250.444 o
+301.819 328.806 o
+298.424 76.3392 o
+331.973 248.671 o
+249.522 146.086 o
+175.401 99.2822 o
+228.554 159.894 o
+175.303 234.465 o
+346.902 342.171 o
+128.284 299.681 o
+319.009 259.775 o
+446.993 135.097 o
+336.261 297.841 o
+387.981 76.0156 o
+190.093 284.984 o
+117.289 101.364 o
+177.671 156.473 o
+179.57 295.492 o
+176.206 170.879 o
+129.225 252.213 o
+260.081 331.309 o
+331.658 179.715 o
+227.209 369.702 o
+197.356 110.128 o
+464.369 332.035 o
+333.249 368.434 o
+126.467 369.582 o
+466.127 261.302 o
+147.438 208.562 o
+122.22 114.402 o
+348.608 293.847 o
+112.082 130.39 o
+476.315 255.352 o
+195.357 207.548 o
+227.454 227.203 o
+476.759 240.468 o
+422.782 249.771 o
+254.722 228.519 o
+453.002 135.992 o
+265.675 178.509 o
+246.471 317.55 o
+471.567 317.835 o
+375.672 264.932 o
+274.95 333.545 o
+168.689 148.823 o
+420.695 280.624 o
+241.393 149.525 o
+404.501 138.059 o
+199.358 195.928 o
+138.249 117.846 o
+364.454 139.238 o
+431.845 264.249 o
+316.338 129.832 o
+163.309 237.242 o
+172.075 146.488 o
+439.508 115.453 o
+278.259 353.724 o
+210.058 334.132 o
+202.302 166.265 o
+158.446 356.173 o
+285.194 106.091 o
+248.611 341.771 o
+489.604 322.867 o
+456.071 312.406 o
+464.79 119.087 o
+425.438 256.533 o
+439.461 369.864 o
+282.93 346.27 o
+251.5 296.727 o
+457.394 109.83 o
+384.418 133.061 o
+118.674 234.819 o
+293.419 314.397 o
+170.163 212.113 o
+404.43 118.935 o
+475.415 341.091 o
+376.482 158.784 o
+126.798 114.33 o
+256.396 254.601 o
+426.809 321.956 o
+441.437 297.873 o
+161.82 234.899 o
+188.165 267.244 o
+255.668 137.541 o
+160.94 191.408 o
+175.552 150.902 o
+297.53 218.974 o
+233.205 185.763 o
+473.534 155.634 o
+244.774 316.598 o
+420.461 304.322 o
+345.5 217.364 o
+485.143 325.216 o
+426.435 125.277 o
+201.243 235.749 o
+360.772 303.009 o
+446.355 239.652 o
+211.585 80.2485 o
+336.016 274.146 o
+342.914 258.117 o
+213.597 149.515 o
+231.369 259.409 o
+229.053 225.945 o
+370.259 177.794 o
+112.131 298.327 o
+385.197 362.949 o
+388.187 223.292 o
+490.034 205.446 o
+252.65 253.679 o
+468.172 165.86 o
+147.742 229.936 o
+419.906 274.743 o
+467.227 282.59 o
+127.635 223.748 o
+146.136 273.682 o
+170.22 167.226 o
+163.095 367.957 o
+208.991 115.787 o
+359.526 236.957 o
+422.731 295.167 o
+287.769 285.945 o
+319.457 182.818 o
+208.088 177.499 o
+388.5 233.284 o
+186.328 144.152 o
+349.178 234.061 o
+191.316 356.356 o
+479.372 96.7753 o
+300.029 267.359 o
+488.623 284.206 o
+177.986 253.078 o
+456.294 179.236 o
+311.016 178.261 o
+264.545 337.775 o
+318.581 161.266 o
+113.048 359.916 o
+214.652 147.24 o
+279.008 137.104 o
+382.272 134.789 o
+426.872 185.952 o
+426.592 267.595 o
+405.404 84.9546 o
+131.186 135.731 o
+343.325 255.998 o
+396.665 172.218 o
+434.62 188.597 o
+194.766 283.685 o
+459.152 234.457 o
+323.366 220.7 o
+314.503 76.0085 o
+120.381 329.056 o
+196.149 358.486 o
+323.186 370.27 o
+369.75 193.826 o
+316.729 216.584 o
+414.292 149.839 o
+341.67 145.787 o
+275.993 162.224 o
+299.881 358.158 o
+270.493 303.614 o
+232.2 188.779 o
+326.502 206.428 o
+319.078 130.5 o
+424.659 253.071 o
+445.607 214.259 o
+233.549 188.714 o
+252.863 202.873 o
+206.441 187.757 o
+292.182 96.865 o
+199.952 312.41 o
+339.094 138.393 o
+271.671 363.771 o
+483.17 89.8751 o
+379.847 183.692 o
+388.276 306.95 o
+407.382 152.418 o
+260.009 204.048 o
+450.009 77.5324 o
+251.32 286.543 o
+466.056 203.204 o
+429.98 297.422 o
+451.667 248.032 o
+151.126 94.5473 o
+241.892 340.781 o
+346.822 81.9414 o
+146.017 206.552 o
+329.07 190.48 o
+437.428 306.507 o
+160.391 97.9028 o
+191.69 308.678 o
+205.407 264.776 o
+432.084 322.55 o
+375.411 192.394 o
+386.484 269.544 o
+185.603 101.241 o
+156.272 117.931 o
+329.991 98.3565 o
+471.725 312.131 o
+411.405 193.621 o
+347.449 332.048 o
+323.722 301.559 o
+231.999 110.582 o
+200.458 253.133 o
+168.099 158.044 o
+486.024 333.549 o
+126.05 206.857 o
+114.305 224.244 o
+284.349 302.934 o
+142.903 75.4316 o
+317.773 350.971 o
+146.487 295.744 o
+453.998 187.824 o
+339.836 234.517 o
+425.8 203.241 o
+219.678 126.347 o
+197.342 229.044 o
+329.781 139.385 o
+485.509 332.31 o
+326.141 256.716 o
+150.478 191.463 o
+220.661 143.763 o
+117.456 231.471 o
+418.767 229.043 o
+469.284 279.977 o
+356.521 336.279 o
+404.954 299.058 o
+129.752 266.034 o
+167.307 284.833 o
+379.813 103.665 o
+197.774 314.785 o
+172.341 127.62 o
+324.304 212.454 o
+355.613 274.041 o
+472.143 110.404 o
+200.519 103.87 o
+123.023 228.516 o
+157.332 267.395 o
+303.247 148.734 o
+317.328 261.994 o
+275.182 314.317 o
+249.326 153.465 o
+463.299 251.449 o
+250.225 165.016 o
+437.22 117.623 o
+436.544 323.89 o
+212.403 149.415 o
+145.903 88.3748 o
+265.877 186.575 o
+209.452 117.661 o
+209.452 117.661 o
+262.591 220.262 o
+126.206 87.5087 o
+207.374 82.8823 o
+459.273 209.611 o
+274.284 215.536 o
+119.198 193.967 o
+319.686 101.089 o
+243.833 331.438 o
+184.327 130.54 o
+228.309 156.197 o
+161.58 183.569 o
+277.253 225.941 o
+385.147 311.286 o
+239.987 318.041 o
+304.848 127.524 o
+381.714 293.54 o
+315.335 321.244 o
+300.244 92.9418 o
+116.06 242.752 o
+425.72 79.8241 o
+154.998 331.116 o
+265.339 237.098 o
+345.449 331.946 o
+271.478 113.69 o
+225.288 203.971 o
+466.438 255.239 o
+127.979 122.105 o
+123.557 244.453 o
+334.649 98.4301 o
+470.524 159.202 o
+221.416 327.764 o
+302.744 306.569 o
+347.35 370.113 o
+420.085 282.824 o
+189.848 181.249 o
+322.098 159.457 o
+326.839 256.731 o
+276.552 236.102 o
+485.957 357.223 o
+464.292 250.328 o
+123.079 264.788 o
+262.148 310.214 o
+454.816 103.646 o
+457.076 345.077 o
+217.586 265.513 o
+381.333 94.1881 o
+254.763 126.501 o
+328.943 211.738 o
+279.842 235.05 o
+448.752 142.956 o
+287.251 360.986 o
+302.827 160.105 o
+208.751 210.961 o
+242.68 99.4743 o
+377.223 245.872 o
+292.601 123.931 o
+491.541 243.084 o
+225.37 91.3451 o
+462.242 298.244 o
+336.902 136.076 o
+185.049 246.218 o
+205.497 169.403 o
+164.792 254.569 o
+219.508 324.853 o
+240.776 166.459 o
+353.514 207.892 o
+221.089 91.1437 o
+337.128 205.989 o
+167.607 370.225 o
+395.301 328.821 o
+173.856 228.073 o
+263.982 153.956 o
+476.128 158.786 o
+326.157 323.651 o
+348.227 110.074 o
+472.657 192.951 o
+212.006 102.889 o
+222.094 298.664 o
+125.434 74.5151 o
+436.449 128.176 o
+355.465 231.62 o
+297.807 91.6613 o
+461.726 283.76 o
+334.445 326.366 o
+220.797 141.381 o
+375.034 136.138 o
+272.121 288.651 o
+285 355.465 o
+326.257 304.117 o
+357.178 286.842 o
+386.798 274.605 o
+336.801 245.333 o
+330.22 91.4168 o
+450.264 257.51 o
+486.517 268.173 o
+327.665 281.828 o
+297.565 220.59 o
+281.859 197.172 o
+451.466 152.291 o
+251.104 162.593 o
+427.846 241.001 o
+246.731 135.993 o
+177.908 333.232 o
+377.003 265.604 o
+235.095 193.156 o
+192.608 88.3428 o
+439.761 249.946 o
+470.617 182.678 o
+172.077 268.477 o
+165.904 201.147 o
+287.379 175.569 o
+184.022 118.105 o
+249.374 320.284 o
+376.145 309.887 o
+365.245 143.057 o
+198.846 134.505 o
+341.165 368.199 o
+188.346 147.785 o
+278.043 267.894 o
+124.597 222.114 o
+185.488 119.102 o
+161.879 87.5924 o
+452.444 306.578 o
+198.437 203.248 o
+302.604 352.444 o
+425.461 202.834 o
+219.247 172.592 o
+239.708 131.357 o
+359.21 166.85 o
+135.084 130.122 o
+263.029 203.495 o
+341.101 341.379 o
+484.162 174.977 o
+237.854 277.199 o
+390.883 74.6849 o
+256.827 221.996 o
+442.711 197.518 o
+305.619 191.565 o
+200.31 264.455 o
+316.027 117.921 o
+484.668 118.798 o
+120.803 75.0655 o
+357.17 112.013 o
+182.192 174.212 o
+462.279 174.348 o
+118.207 117.31 o
+165.791 112.013 o
+419.604 246.714 o
+255.534 305.299 o
+223.828 298.405 o
+214.932 341.14 o
+404.503 235.041 o
+247.952 368.14 o
+423.445 280.724 o
+313.817 292.171 o
+180.267 333.95 o
+421.12 356.534 o
+304.003 127.154 o
+287.581 153.024 o
+472.41 94.7735 o
+146.653 271.935 o
+341.174 248.123 o
+206.522 94.76 o
+213.061 146.064 o
+397.491 99.0448 o
+473.672 296.444 o
+199.147 96.3443 o
+461.825 249.601 o
+378.72 279.374 o
+137.275 325.583 o
+330.202 318.84 o
+189.58 101.269 o
+347.169 116.202 o
+226.231 112.9 o
+127.691 232.846 o
+448.114 207.306 o
+427.888 95.6066 o
+298.996 138.184 o
+177.258 227.673 o
+340.498 157.921 o
+392.048 337.841 o
+138.916 238.515 o
+241.33 214.351 o
+462.051 201.482 o
+214.546 146.194 o
+469.628 334.673 o
+136.906 152.197 o
+161.445 186.556 o
+397.279 364.709 o
+112.744 137.61 o
+297.888 122.822 o
+226.216 235.284 o
+308.253 124.639 o
+331.04 291.399 o
+448.281 119.13 o
+307.754 242.104 o
+180.866 187.577 o
+329.523 91.0822 o
+355.427 106.784 o
+246.386 305.307 o
+427.444 269.358 o
+201.551 267.456 o
+219.501 96.7771 o
+470.982 303.996 o
+152.923 309.043 o
+249.903 186.509 o
+122.773 98.7548 o
+306.934 132.89 o
+429.148 220.57 o
+471.389 104.551 o
+326.948 215.22 o
+142.076 282.781 o
+220.74 329.318 o
+310.728 81.463 o
+155.519 224.173 o
+280.518 95.2028 o
+428.439 322.552 o
+245.495 268.051 o
+123.142 285.316 o
+228.955 185.923 o
+151.552 194.478 o
+284.897 303.773 o
+115.64 308.694 o
+197.563 190.69 o
+385.377 137.499 o
+163.257 368.599 o
+147.488 302.78 o
+466.302 189.63 o
+158.522 357.538 o
+340.232 211.745 o
+238.959 187.842 o
+195.198 225.206 o
+266.295 226.52 o
+338.931 194.137 o
+286.844 313.444 o
+123.976 129.878 o
+112.535 326.028 o
+136.933 181.161 o
+327.827 200.662 o
+240.974 275.35 o
+485.102 223.927 o
+278.836 241.064 o
+195.593 86.3321 o
+343.915 226.532 o
+326.033 77.6533 o
+185.821 140.726 o
+451.66 356.774 o
+471.059 338.89 o
+481.747 251.686 o
+287.385 120.691 o
+289.57 116.179 o
+228.758 207.552 o
+165.8 286.13 o
+265.118 159.587 o
+328.086 362.39 o
+247.918 123.576 o
+352.641 91.9426 o
+439.844 147.201 o
+143.116 102.545 o
+470.171 329.396 o
+190.675 95.5264 o
+473.536 144.819 o
+333.693 113.015 o
+432.968 85.527 o
+379.426 81.7622 o
+387.507 319.292 o
+178.664 198.677 o
+267.542 264.484 o
+340.919 253.008 o
+356.65 309.005 o
+326.206 342.744 o
+212.952 313.491 o
+213.819 141.78 o
+363.025 108.076 o
+249.005 269.242 o
+405.377 346.644 o
+240.38 236.501 o
+161.788 217.861 o
+223.97 218.424 o
+263.242 207.594 o
+144.606 326.233 o
+345.948 178.2 o
+174.699 367.85 o
+205.278 139.698 o
+352.064 317.67 o
+239.632 330.922 o
+230.785 232.449 o
+218.874 145.831 o
+283.62 325.524 o
+294.351 292.526 o
+410.915 331.606 o
+405.5 138.956 o
+465.853 330.204 o
+360.469 122.693 o
+473.741 160.765 o
+172.641 189.137 o
+383.933 88.3344 o
+211.338 201.8 o
+192.466 329.209 o
+303.869 290.361 o
+211.287 137.987 o
+236.702 132.451 o
+290.084 133.841 o
+462.477 215.11 o
+297.687 291.864 o
+478.869 95.3053 o
+455.169 101.553 o
+312.954 339.831 o
+176.85 227.521 o
+300.725 349.222 o
+300.367 99.3729 o
+130.904 319.089 o
+412.904 171.574 o
+362.817 144.547 o
+301.785 141.68 o
+291.47 178.912 o
+321.632 154.375 o
+254.182 246.577 o
+451.523 185.495 o
+451.067 182.018 o
+449.112 268.544 o
+208.569 329.019 o
+432.825 116.606 o
+468.412 261.828 o
+339.374 313.676 o
+184.972 163.393 o
+125.342 356.719 o
+204.323 276.126 o
+399.439 340.84 o
+255.953 286.988 o
+344.723 201.842 o
+447.254 178.187 o
+138.24 365.53 o
+388.642 210.858 o
+331.833 237.443 o
+395.871 365.135 o
+267.862 132.264 o
+469.069 142.773 o
+295.811 214.643 o
+479.962 249.584 o
+453.643 273.34 o
+348.186 238.763 o
+401.619 195.618 o
+476.082 184.478 o
+398.943 236.479 o
+302.748 286.303 o
+348.316 296.573 o
+458.867 248.343 o
+460.914 209.172 o
+257.481 156.686 o
+324.111 282.608 o
+402.448 127.687 o
+472.839 114.649 o
+461.882 130.3 o
+416.763 278.834 o
+407.168 347.513 o
+121.553 311.21 o
+282.579 120.951 o
+201.005 350.103 o
+218.913 114.12 o
+484.928 247.951 o
+340.118 95.8858 o
+183.713 364.322 o
+480.709 179.5 o
+336.987 178.97 o
+256.437 76.911 o
+198.532 351.991 o
+405.908 366.991 o
+222.633 261.06 o
+450.787 88.5983 o
+341.629 164.589 o
+483.808 317.428 o
+133.411 177.218 o
+113.785 292.221 o
+182.681 286.221 o
+281.047 257.139 o
+171.391 88.9033 o
+311.44 258.558 o
+269.54 283.723 o
+257.826 129.656 o
+279.093 83.72 o
+140.71 254.831 o
+217.489 80.4373 o
+376.069 157.762 o
+324.871 170.869 o
+247.499 286.086 o
+235.729 278.737 o
+174.419 170.063 o
+348.297 210.958 o
+204.858 326.267 o
+406.743 343.877 o
+270.909 278.989 o
+339.439 160.776 o
+248.943 312.775 o
+226.529 282.485 o
+149.004 260.838 o
+146.189 322.394 o
+188.456 197.232 o
+482.904 288.155 o
+405.356 102.254 o
+336.958 95.8941 o
+301.773 317.607 o
+436.905 101.889 o
+377.844 135.755 o
+375.728 329.221 o
+375.623 324.795 o
+288.715 182.255 o
+484.533 188.424 o
+357.602 113.142 o
+367.87 240.278 o
+465.576 205.013 o
+393.843 268.567 o
+251.895 137.167 o
+354.533 330.311 o
+402.986 278.187 o
+197.738 96.4223 o
+221.711 214.719 o
+174.156 186.916 o
+305.664 181.281 o
+343.263 271.617 o
+260.854 83.7153 o
+272.557 241.097 o
+135.784 276.112 o
+218.485 326.944 o
+204.853 150.586 o
+170.578 153.642 o
+384.244 210.049 o
+282.37 312.351 o
+254.859 203.903 o
+485.847 248.538 o
+463.762 323.685 o
+182.079 87.2553 o
+167.149 245.019 o
+186.408 187.366 o
+267.518 104.609 o
+428.962 283.088 o
+474.401 342.905 o
+254.625 227.442 o
+130.771 160.608 o
+182.769 108.261 o
+463.223 225.205 o
+280.82 327.489 o
+213.009 170.446 o
+339.525 268.306 o
+255.888 112.293 o
+397.823 302.237 o
+240.22 210.837 o
+408.251 314.152 o
+377.336 178.246 o
+311.943 163.464 o
+364.679 85.1074 o
+333.158 142.482 o
+374.703 113.199 o
+183.361 100.464 o
+321.021 243.288 o
+290.025 82.11 o
+208.264 285.77 o
+336.646 125.747 o
+222.724 139.244 o
+315.949 255.978 o
+275.164 235.814 o
+186.206 246.296 o
+113.208 347.606 o
+414.054 206.685 o
+169.448 253.647 o
+476.664 92.9164 o
+461.366 353.304 o
+311.439 147.096 o
+230.029 167.854 o
+321.203 103.146 o
+465.61 91.7564 o
+379.839 104.974 o
+150.244 143.995 o
+349.267 188.331 o
+111.904 259.111 o
+340.881 152.435 o
+157.774 362.801 o
+358.848 316.66 o
+139.902 286.125 o
+115.404 228.927 o
+271.113 220.826 o
+428.353 193.197 o
+268.255 108.389 o
+139.834 101.412 o
+151.952 159.081 o
+274.748 119.762 o
+431.088 325.418 o
+415.007 310.416 o
+481.51 324.235 o
+428.838 346.782 o
+116.86 150.312 o
+259.881 93.37 o
+167.958 208.889 o
+408.653 192.334 o
+257.879 216.837 o
+169.338 148.057 o
+317.02 214.097 o
+289.861 369.658 o
+333.189 338.391 o
+449.042 310.993 o
+449.042 310.993 o
+230.071 327.532 o
+169.765 192.02 o
+152.408 74.8528 o
+125.671 209.888 o
+145.095 184.249 o
+187.01 362.025 o
+471.71 80.365 o
+360.921 274.085 o
+431.609 249.018 o
+448.272 233.457 o
+240.971 91.2614 o
+467.904 293.456 o
+126.199 96.6715 o
+276.015 249.69 o
+223.132 255.028 o
+115.036 234.064 o
+305.187 329.47 o
+338.585 201.779 o
+481.048 337.152 o
+123.308 138.297 o
+164.318 77.0981 o
+306.436 111.115 o
+191.305 368.988 o
+231.544 97.6631 o
+465.676 186.379 o
+238.549 336.432 o
+344.374 331.995 o
+137.167 250.581 o
+159.745 217.67 o
+127.543 85.1101 o
+428.211 250.176 o
+346.652 358.055 o
+293.293 282.373 o
+222.459 330.461 o
+222.479 217.724 o
+205.617 269.194 o
+318.476 98.8214 o
+244.36 190.44 o
+469.092 297.91 o
+185.248 331.118 o
+431.148 247.766 o
+260.834 354.222 o
+297.88 218.459 o
+116.595 319.367 o
+247.371 156.208 o
+201.1 313.175 o
+214.661 150.876 o
+352.452 178.311 o
+214.894 244.549 o
+138.527 108.885 o
+397.018 351.134 o
+325.674 270.495 o
+377.628 358.197 o
+121.311 89.7141 o
+131.22 136.061 o
+257.758 196.95 o
+394.862 135.851 o
+185.004 338.204 o
+164.733 82.145 o
+460.033 147.389 o
+232.819 83.898 o
+361.064 221.258 o
+355.07 208.59 o
+324.129 189.879 o
+447.268 332.942 o
+160.083 194.53 o
+174.6 295.516 o
+114.192 231.4 o
+480.986 125.748 o
+461.1 183.677 o
+320.243 259.395 o
+366.682 226.23 o
+116.961 263.477 o
+135.063 176.121 o
+337.979 306.837 o
+161.164 134.644 o
+255.149 89.4746 o
+463.592 316.335 o
+337.698 254.069 o
+402.458 179.217 o
+179.425 354.039 o
+146 246.154 o
+411.529 303.016 o
+139.19 314.984 o
+453.351 222.71 o
+190.951 246.933 o
+140.153 121.322 o
+127.02 238.223 o
+148.394 216.051 o
+140.926 100.712 o
+270.64 294.19 o
+482.843 308.648 o
+122.967 192.656 o
+156.16 287.6 o
+242.226 276.291 o
+181.986 256.224 o
+471.739 237.244 o
+113.295 289.592 o
+373.492 268.011 o
+412.194 291.41 o
+288.023 343.826 o
+237.823 297.31 o
+224.79 277.375 o
+146.545 116.74 o
+141.695 313.398 o
+353.695 155.367 o
+326.418 215.387 o
+369.05 134.421 o
+451.351 208.43 o
+287.103 290.488 o
+247.864 178.706 o
+260.613 339.631 o
+259.287 172.083 o
+377.414 304.321 o
+173.679 86.2304 o
+136.911 176.166 o
+470.54 168.157 o
+347.677 132.329 o
+178.442 114.751 o
+280.344 219.067 o
+376.335 269.533 o
+351.856 366.87 o
+313.373 156.965 o
+302.696 206.567 o
+305.98 329.823 o
+197.215 222.556 o
+490.767 224.008 o
+173.796 244.504 o
+267.566 309.695 o
+398.032 98.1237 o
+393.342 293.743 o
+466.145 138.194 o
+225.348 117.937 o
+411.378 176.032 o
+453.386 206.354 o
+342.76 239.1 o
+340.046 127.226 o
+338.268 154.736 o
+444.052 310.66 o
+120.753 360.497 o
+143.419 364.422 o
+457.459 354.063 o
+174.012 117.993 o
+339.353 253.843 o
+363.07 100.236 o
+367.39 362.519 o
+227.587 125.22 o
+367.894 282.953 o
+145.445 269.803 o
+112.025 272.013 o
+257.6 309.425 o
+151.151 223.95 o
+324.483 182.249 o
+173.436 191.799 o
+348.194 177.171 o
+257.222 166.54 o
+269.928 278.997 o
+134.974 343.631 o
+440.307 284.848 o
+436 295.309 o
+270.134 245.566 o
+467.14 326.694 o
+226.08 341.162 o
+112.516 229.885 o
+401.16 114.882 o
+142.252 117.857 o
+187.772 109.633 o
+162.944 78.3937 o
+257.718 97.5874 o
+362.218 94.1442 o
+353.182 181.177 o
+259.491 196.301 o
+161.084 291.397 o
+219.517 91.2703 o
+328.784 325.283 o
+411.171 215.068 o
+440.083 366.906 o
+304.35 278.739 o
+234.154 296.194 o
+195.219 316.551 o
+427.112 166.145 o
+113.656 206.854 o
+278.964 333.99 o
+120.5 84.9609 o
+179.65 362.181 o
+369.498 242.068 o
+126.99 302.654 o
+469.435 148.485 o
+309.753 181.316 o
+259.454 296.58 o
+242.419 329.716 o
+282.757 330.124 o
+374.876 124.03 o
+457 318.452 o
+447.827 222.977 o
+125.687 312.766 o
+389.29 169.921 o
+192.098 251.358 o
+452.88 323.345 o
+454.384 114.662 o
+277.087 96.7285 o
+219.28 83.3024 o
+452.739 301.539 o
+241.485 193.11 o
+304.592 268.569 o
+391.098 210.573 o
+460.222 253.193 o
+423.704 366.478 o
+320.354 82.977 o
+374.081 118.531 o
+117.336 245.092 o
+374.885 259.618 o
+490.216 244.77 o
+135.865 77.6026 o
+459.177 164.219 o
+391.229 286.068 o
+442.762 321.656 o
+147.608 236.146 o
+148.759 210.102 o
+228.081 336.311 o
+421.626 233.859 o
+168.724 299.257 o
+491.114 350.003 o
+457.568 271.968 o
+177.364 335.23 o
+433.182 128.464 o
+249.708 347.092 o
+419.613 117.545 o
+239.424 318.832 o
+285.189 150.4 o
+321.017 213.57 o
+322.948 368.425 o
+196.271 214.703 o
+367.057 175.306 o
+242.488 367.207 o
+296.755 90.0569 o
+448.867 127.242 o
+364.823 186.115 o
+326.693 123.348 o
+312.984 184.891 o
+260.971 120.38 o
+159.206 148.363 o
+245.126 177.574 o
+470.898 257.794 o
+170.009 269.782 o
+415.918 357.153 o
+396.386 249.562 o
+315.877 368.729 o
+335.352 81.9932 o
+465.122 81.3471 o
+304.285 352.915 o
+364.221 116.467 o
+290.689 288.663 o
+441.549 324.914 o
+302.139 248.372 o
+400.541 284.378 o
+225.174 81.0732 o
+456.738 285.721 o
+286.151 108.038 o
+214.653 220.49 o
+351.386 179.889 o
+215.238 332.813 o
+439.126 111.9 o
+159.62 225.208 o
+287.312 150.937 o
+412.149 346.054 o
+331.626 280.217 o
+249.309 161.256 o
+204.51 231.813 o
+327.434 353.332 o
+223.744 328.31 o
+386.362 124.722 o
+386.944 200.394 o
+175.975 274.011 o
+401.988 177.46 o
+167.062 127.908 o
+299.015 321.591 o
+318.757 139.796 o
+170.004 317.43 o
+436.758 123.446 o
+214.296 275.576 o
+400.027 253.085 o
+130.366 216.071 o
+449.381 113.818 o
+202.734 202.77 o
+393.784 291.251 o
+228.798 326.471 o
+137.226 317.576 o
+462.921 328.906 o
+373.558 331.842 o
+429.807 148.739 o
+260.378 249.134 o
+151.11 360.018 o
+226.746 194.417 o
+347.161 307.61 o
+172.921 346.786 o
+443.706 137.208 o
+307.714 179.131 o
+387.331 167.383 o
+395.829 191.575 o
+438.425 226.867 o
+488.582 181.494 o
+413.208 247.968 o
+318.259 94.7168 o
+300.982 177.026 o
+262.819 363.335 o
+414.382 164.552 o
+410.81 179.936 o
+119.129 321.892 o
+188.822 321.559 o
+122.426 307.439 o
+486.877 276.714 o
+127.046 327.249 o
+296.792 282.851 o
+481.745 291.546 o
+384.018 110.89 o
+160.672 174.147 o
+247.512 260.742 o
+172.107 118.008 o
+303.432 117.225 o
+276.065 185.818 o
+233.356 105.804 o
+209.537 88.6185 o
+242.378 126.178 o
+439.257 145.76 o
+345.787 104.369 o
+293.021 338.258 o
+322.522 173.289 o
+203.614 134.567 o
+325.474 283.109 o
+117.762 324.851 o
+286.279 206.252 o
+382.502 236.092 o
+459.575 307.252 o
+214.749 219.505 o
+148.662 161.784 o
+137.338 88.1992 o
+312.737 363.339 o
+328.063 164.294 o
+178.992 243.324 o
+163.237 171.27 o
+267.433 245.24 o
+319.834 164.095 o
+375.144 295.233 o
+259.102 107.75 o
+392.699 276.767 o
+391.691 204.319 o
+191.902 231.978 o
+386.915 239.014 o
+173.738 299.101 o
+441.171 218.606 o
+433.56 205.023 o
+294.507 238.357 o
+244.474 326.735 o
+395.717 337.651 o
+113.115 260.654 o
+311.343 169.363 o
+169.068 137.107 o
+224.866 158.43 o
+429.421 222.162 o
+359.743 149 o
+282.6 159.052 o
+390.569 204.985 o
+362.753 183.236 o
+262.533 324.614 o
+334.777 365.532 o
+140.009 251.832 o
+219.799 300.38 o
+445.515 152.523 o
+418.375 80.9914 o
+445.002 160.369 o
+220.552 315.193 o
+219.931 340.377 o
+172.85 296.889 o
+111.657 286.822 o
+141.645 76.739 o
+462.098 195.384 o
+234.188 317.995 o
+357.84 324.207 o
+341.406 323.862 o
+445.458 329.996 o
+373.008 81.7091 o
+319.047 131.166 o
+488.926 368.786 o
+148.207 218.967 o
+297.168 280.434 o
+464.95 161.951 o
+326.349 145.08 o
+194.684 100.673 o
+228.215 83.5134 o
+340.552 357.034 o
+343.385 171.784 o
+232.921 249.973 o
+352.914 242.648 o
+258.74 244.429 o
+347.248 309.586 o
+290.628 343.714 o
+452.706 163.697 o
+311.123 243.288 o
+311.824 355.239 o
+171.681 254.353 o
+206.849 288.472 o
+402.451 294.508 o
+236.571 309.878 o
+470.687 277.59 o
+218.295 370.412 o
+489.191 193.343 o
+146.549 100.5 o
+465.89 309.806 o
+255.609 237.653 o
+186.838 357.331 o
+397.218 182.209 o
+295.498 369.436 o
+166.213 323.048 o
+265.448 363.836 o
+334.545 303.352 o
+382.656 319.504 o
+392.663 217.432 o
+188.232 105.453 o
+353.967 332.577 o
+313.355 291.371 o
+189.654 226.05 o
+488.126 233.962 o
+462.039 298.355 o
+422.036 270.53 o
+295.648 162.11 o
+395.498 233.206 o
+277.027 176.625 o
+167.533 127.078 o
+438.237 224.302 o
+427.82 238.514 o
+415.582 253.417 o
+226.201 139.765 o
+271.567 154.682 o
+403.876 370.111 o
+132.727 129.687 o
+236.103 141.182 o
+255.964 319.083 o
+271.761 320.419 o
+389.424 173.27 o
+159.048 119.739 o
+135.831 256.809 o
+219.334 220.279 o
+115.493 151.414 o
+216.987 344.594 o
+114.852 120.835 o
+473.535 354.597 o
+164.868 267.906 o
+285.759 200.603 o
+444.005 214.607 o
+332.616 194.389 o
+265.987 311.361 o
+455.137 322.855 o
+258.028 272.029 o
+324.434 155.212 o
+276.686 273.476 o
+224.264 321.544 o
+275.379 330.977 o
+337.922 209.395 o
+420.71 335.119 o
+489.437 164.871 o
+288.57 306.517 o
+289.189 180.662 o
+428.578 211.337 o
+409.359 195.569 o
+164.783 208.909 o
+309.069 313.877 o
+411.255 79.1339 o
+295.611 180.802 o
+151.741 322.454 o
+310.622 244.259 o
+113.08 337.238 o
+125.908 290.947 o
+334.123 207.767 o
+477.1 263.948 o
+239.929 159.029 o
+299.706 251.853 o
+409.427 333.963 o
+291.335 361.009 o
+391.799 195.363 o
+147.257 192.948 o
+240.682 342.86 o
+291.309 137.413 o
+212.556 211.898 o
+223.437 80.3394 o
+453.089 326.74 o
+268.276 220.324 o
+183.958 93.5576 o
+377.568 200.699 o
+158.448 245 o
+134.272 156.722 o
+407.949 308.258 o
+285.029 157.309 o
+244.278 224.225 o
+365.784 245.406 o
+431.778 263.426 o
+149.284 120.221 o
+285.944 97.845 o
+478.381 200.685 o
+345.955 148.513 o
+345.955 148.513 o
+289.066 206.922 o
+170.067 339.131 o
+223.496 197.279 o
+112.239 123.13 o
+257.45 77.1489 o
+216.234 254.535 o
+364.774 253.972 o
+236.956 133.709 o
+258.001 244.962 o
+445.647 203.085 o
+421.761 290.749 o
+378.5 270.765 o
+180.731 242.786 o
+290.381 170.15 o
+286.351 340.074 o
+115.567 165.702 o
+228.817 340.854 o
+354.088 273.08 o
+473.527 114.457 o
+381.696 163.286 o
+303.737 277.347 o
+426.668 352.176 o
+466.517 268.623 o
+218.313 276.676 o
+191.707 119.979 o
+143.758 212.116 o
+119.057 320.484 o
+300.596 209.376 o
+203.27 167.709 o
+168.009 201.423 o
+132.68 198.154 o
+384.686 342.321 o
+226.779 300.969 o
+286.137 168.448 o
+112.189 341.182 o
+181.409 86.8985 o
+114.889 258.069 o
+448.31 246.205 o
+175.45 103.297 o
+181.839 102.314 o
+133.951 83.8023 o
+442.758 238.115 o
+473.849 268.08 o
+113.726 77.0226 o
+276.155 230.666 o
+470.316 362.875 o
+327.971 135.012 o
+461.388 295.974 o
+149.544 247.175 o
+117.06 351.098 o
+391.517 219.52 o
+362.844 139.016 o
+212.532 293.678 o
+440.664 289.412 o
+360.889 180.707 o
+218.579 108.836 o
+285.694 121.59 o
+326.496 328.628 o
+199.702 99.6927 o
+307.075 161.22 o
+482.499 99.0487 o
+359.867 217.65 o
+357.153 167.905 o
+470.042 320.102 o
+201.174 219.776 o
+341.183 122.206 o
+471.591 225.872 o
+255.171 350.732 o
+117.529 295.58 o
+163.378 75.5144 o
+362.399 196.646 o
+226.959 192.084 o
+469.986 312.81 o
+186.05 257.211 o
+335.757 116.78 o
+169.18 144.119 o
+294.643 113.897 o
+370.889 308.577 o
+122.868 139.292 o
+464.463 360.364 o
+273.222 185 o
+189.253 235.181 o
+135.311 368.563 o
+330.741 98.1635 o
+120.925 360.281 o
+234.233 157.952 o
+442.677 262.404 o
+235.029 291.647 o
+438.884 216.446 o
+178.718 250.255 o
+336.514 249.43 o
+217.262 125.306 o
+215.18 238.736 o
+429.868 172.787 o
+469.196 221.921 o
+344.142 115.126 o
+162.361 153.129 o
+469.271 245.413 o
+231.622 342.105 o
+251.338 292.569 o
+184.201 248.411 o
+264.928 276.408 o
+431.713 277.379 o
+369.131 141.829 o
+238.889 183.372 o
+437.879 358.291 o
+408.177 210.657 o
+233.505 124.909 o
+162.059 87.6701 o
+278.868 242.895 o
+174.469 348.555 o
+222.204 133.162 o
+237.7 325.19 o
+410.363 348.649 o
+261.919 192.918 o
+483.908 166.883 o
+154.679 282.411 o
+189.27 291.17 o
+162.043 210.024 o
+249.552 244.816 o
+219.077 359.079 o
+135.441 215.602 o
+388.579 264.358 o
+163.988 238.053 o
+309.539 355.035 o
+294.827 334.219 o
+139.792 306.947 o
+485.155 187.234 o
+342.185 165.215 o
+143.136 312.884 o
+479.619 279.472 o
+193.965 135.318 o
+147.058 80.8624 o
+281.73 238.428 o
+359.004 155.674 o
+138.568 335.513 o
+475.472 229.206 o
+184.735 345.452 o
+138.825 166.27 o
+247.199 229.569 o
+323.124 310.632 o
+196.353 205.89 o
+116.991 259.104 o
+369.062 127.985 o
+369.048 221.724 o
+401.768 175.487 o
+151.337 98.309 o
+257.994 103.595 o
+302.134 307.824 o
+166.404 107.664 o
+279.755 319.095 o
+309.52 201.588 o
+336.188 338.886 o
+146.748 308.157 o
+457.478 348.168 o
+389.174 293.196 o
+158.689 285.516 o
+135.881 240.379 o
+376.772 364.998 o
+114.867 201.167 o
+309.296 331.707 o
+115.871 268.97 o
+231.033 107.198 o
+165.388 86.5341 o
+173.499 121.961 o
+438.866 142.694 o
+424.036 314.283 o
+195.45 262.876 o
+190.159 283.921 o
+268.097 164.449 o
+295.755 362.353 o
+196.869 75.1325 o
+383.271 105.331 o
+152.864 156.095 o
+227.751 173.519 o
+147.827 360.681 o
+248.672 319.443 o
+209.178 302.125 o
+135.127 129.642 o
+255.071 111.735 o
+232.257 182.248 o
+357.104 137.55 o
+429.939 180.669 o
+180.846 272.543 o
+326.739 369.356 o
+301.398 219.534 o
+216.101 307.636 o
+489.583 149.35 o
+363.164 348.406 o
+274.712 175.767 o
+398.836 340.834 o
+327.527 83.7424 o
+390.716 241.864 o
+344.56 354.832 o
+447.984 144.76 o
+340.32 232.134 o
+205.536 213.88 o
+195.437 330.023 o
+391.695 205.476 o
+354.051 239.269 o
+302.44 118.799 o
+185.508 218.995 o
+114.032 246.527 o
+203.441 291.263 o
+414.604 278.249 o
+222.239 95.6682 o
+409.842 257.033 o
+299.59 330.801 o
+458.332 243.665 o
+399.575 303.861 o
+262.816 164.961 o
+186.088 178.08 o
+334.806 151.452 o
+260.911 299.905 o
+279.954 145.152 o
+273.105 290.772 o
+445.083 264.005 o
+178.466 279.769 o
+440.034 79.0233 o
+349.33 280.715 o
+336.441 114.71 o
+322.181 299.937 o
+490.914 271.426 o
+138.705 359.236 o
+376.471 219.915 o
+400.988 152.771 o
+117.747 188.526 o
+307.254 83.3886 o
+425.378 166.744 o
+313.442 150.238 o
+421.254 133.283 o
+183.466 192.334 o
+484.285 318.5 o
+304.369 302.921 o
+186.306 170.489 o
+366.757 247.74 o
+191.422 187.814 o
+335.795 286.454 o
+288.462 190.647 o
+424.466 356.687 o
+144.208 360.707 o
+131.26 272.793 o
+405.738 186.054 o
+357.852 143.05 o
+417.321 307.758 o
+462.987 75.9591 o
+444.404 265.32 o
+191.222 226.292 o
+243.615 226.097 o
+203.269 304.868 o
+162.277 350.208 o
+317.248 227.141 o
+423.073 151.768 o
+360.812 254.779 o
+436.532 191.807 o
+259.007 292.046 o
+396.798 365.26 o
+391.698 260.093 o
+131.449 295.38 o
+333.482 284.416 o
+274.839 254.635 o
+287.247 142.062 o
+143.469 272.449 o
+272.218 166.527 o
+243.758 106.82 o
+217.445 96.8161 o
+398.859 120.269 o
+190.67 170.866 o
+396.265 237.201 o
+176.98 251.588 o
+284.486 343.003 o
+161.398 304.657 o
+290.525 85.7818 o
+396.092 298.384 o
+284.817 164.009 o
+467.268 277.802 o
+342.393 330.311 o
+225.084 169.053 o
+204.268 342.176 o
+363.999 270.425 o
+130.688 240.901 o
+282.43 146.03 o
+479.45 152.984 o
+189.407 137.626 o
+279.4 192.659 o
+436.378 253.654 o
+292.477 226.992 o
+362.571 321.225 o
+178.623 327.984 o
+476.323 245.63 o
+219.464 97.3292 o
+216.389 235.981 o
+156.923 192.615 o
+282.17 335.314 o
+242.398 345.859 o
+120.684 130.177 o
+231.727 246.16 o
+295.557 174.878 o
+145.964 227.489 o
+144.795 208.902 o
+173.892 248.371 o
+279.533 317.001 o
+458.178 295.63 o
+466.305 329.748 o
+305.636 215.341 o
+376.716 270.894 o
+114.318 204.298 o
+140.888 140.315 o
+152.856 186.641 o
+485.382 291.041 o
+154.798 253.943 o
+189.772 365.688 o
+335.706 255.779 o
+303.199 331.373 o
+323.081 209.531 o
+435.437 111.956 o
+239.023 299.992 o
+477.493 91.4192 o
+462.763 358.509 o
+196.418 279.241 o
+353.83 210.574 o
+166.98 277.972 o
+472.552 331.482 o
+407.668 192.099 o
+244.773 329.311 o
+440.051 305.505 o
+268.002 237.85 o
+337.155 165.768 o
+415.508 277.48 o
+255.319 117.816 o
+210.598 174.491 o
+185.088 229.795 o
+344.059 302.361 o
+361.143 99.696 o
+412.428 353.2 o
+301.389 238.643 o
+217.641 333.597 o
+386.132 100.714 o
+383.482 350.856 o
+145.448 114.526 o
+384.478 104.062 o
+414.764 164.96 o
+282.385 365.609 o
+280.04 119.736 o
+334.931 239.08 o
+264.041 264.26 o
+268.195 269.298 o
+238.758 239.685 o
+367.012 107.149 o
+254.039 319.574 o
+146.883 249.039 o
+212.066 362.928 o
+405.445 350.339 o
+393.728 78.6964 o
+235.27 119.463 o
+390.524 201.093 o
+486.447 303.815 o
+272.341 93.4554 o
+244.842 264.97 o
+404.064 342.974 o
+464.049 126.185 o
+211.223 360.426 o
+296.057 167.313 o
+490.508 290.569 o
+320.655 196.956 o
+230.054 257.551 o
+244.161 131.443 o
+289.135 198.111 o
+253.018 326.064 o
+282.517 157.432 o
+395.265 182.595 o
+201.664 183.961 o
+190.822 205.643 o
+300.585 215.37 o
+319.016 157.411 o
+460.714 357.133 o
+266.554 354.175 o
+171.775 241.92 o
+209.27 171.162 o
+325.503 171.451 o
+151.16 99.7775 o
+461.094 80.2036 o
+439.971 281.439 o
+425.381 352.525 o
+377.9 362.515 o
+429.347 225.153 o
+201.717 139.017 o
+131.273 162.918 o
+220.638 151.443 o
+162.362 158.945 o
+361.487 257 o
+444.09 233.397 o
+344.74 155.248 o
+236.009 275.369 o
+272.234 253.042 o
+158.056 128.078 o
+473.215 193.23 o
+194.988 194.265 o
+307.45 102.966 o
+249.061 363.794 o
+433.707 252.247 o
+321.235 130.224 o
+279.145 91.669 o
+118.158 119.211 o
+414.906 359.465 o
+359.447 284.041 o
+133.373 333.028 o
+245.815 118.28 o
+319.399 235.203 o
+399.717 279.832 o
+452.879 343.913 o
+465.374 221.034 o
+467.121 327.315 o
+130.323 294.172 o
+468.596 88.8917 o
+394.544 354.61 o
+142.286 154.263 o
+236.094 285.725 o
+379.912 208.111 o
+413.551 355.13 o
+206.456 181.966 o
+446.551 236.377 o
+444.985 320.215 o
+354.535 264.857 o
+323.441 223.136 o
+488.039 316.446 o
+447.963 92.2288 o
+475.134 234.765 o
+250.879 322.908 o
+134.565 287.553 o
+372.353 315.817 o
+347.657 268.578 o
+315.334 341.447 o
+227.151 272.361 o
+251.798 189.409 o
+284.381 192.602 o
+464.537 361.335 o
+184.243 166.173 o
+375.653 205.489 o
+351.795 234.282 o
+186.972 271.266 o
+154.164 186.083 o
+164.595 313.03 o
+251.292 157.761 o
+377.68 143.072 o
+423.28 243.038 o
+470.735 331.967 o
+245.713 88.7982 o
+282.434 280.546 o
+178.059 219.665 o
+179.848 215.338 o
+226.016 88.4789 o
+416.733 197.088 o
+254.33 118.649 o
+422.273 266.306 o
+356.691 319.863 o
+427.831 104.759 o
+269.878 110.662 o
+403.025 239.419 o
+457.935 119.042 o
+171.023 212.11 o
+170.031 199.403 o
+234.463 171.575 o
+258.209 259.439 o
+381.527 153.006 o
+395.79 239.453 o
+219.763 291.731 o
+215.804 319.155 o
+318.612 341.637 o
+176.667 197.788 o
+465.53 177.024 o
+118.524 290.943 o
+124.926 297.832 o
+327.281 151.359 o
+428.668 104.481 o
+198.62 189.024 o
+302.98 100.107 o
+191.028 195.399 o
+369.778 124.82 o
+221.589 159.492 o
+483.096 167.947 o
+368.466 250.33 o
+342.588 201.786 o
+234.694 230.036 o
+211.52 90.1258 o
+224.466 271.846 o
+177.198 160.065 o
+213.964 81.7332 o
+362.845 364.893 o
+275.366 358.65 o
+399.385 241.743 o
+136.546 287.894 o
+323.334 336.138 o
+190.913 233.411 o
+333.291 273.411 o
+283.715 142.159 o
+257.917 90.6669 o
+219.362 105.772 o
+465.887 173.157 o
+grestore
+gsave
+456.165 355.68 73.575 44.46 clipbox
+/o { gsave
+newpath
+translate
+1 0 m
+0.992115 0.125333 l
+0.968583 0.24869 l
+0.929776 0.368125 l
+0.876307 0.481754 l
+0.809017 0.587785 l
+0.728969 0.684547 l
+0.637424 0.770513 l
+0.535827 0.844328 l
+0.425779 0.904827 l
+0.309017 0.951057 l
+0.187381 0.982287 l
+0.0627905 0.998027 l
+-0.0627905 0.998027 l
+-0.187381 0.982287 l
+-0.309017 0.951057 l
+-0.425779 0.904827 l
+-0.535827 0.844328 l
+-0.637424 0.770513 l
+-0.728969 0.684547 l
+-0.809017 0.587785 l
+-0.876307 0.481754 l
+-0.929776 0.368125 l
+-0.968583 0.24869 l
+-0.992115 0.125333 l
+-1 -3.21625e-16 l
+-0.992115 -0.125333 l
+-0.968583 -0.24869 l
+-0.929776 -0.368125 l
+-0.876307 -0.481754 l
+-0.809017 -0.587785 l
+-0.728969 -0.684547 l
+-0.637424 -0.770513 l
+-0.535827 -0.844328 l
+-0.425779 -0.904827 l
+-0.309017 -0.951057 l
+-0.187381 -0.982287 l
+-0.0627905 -0.998027 l
+0.0627905 -0.998027 l
+0.187381 -0.982287 l
+0.309017 -0.951057 l
+0.425779 -0.904827 l
+0.535827 -0.844328 l
+0.637424 -0.770513 l
+0.728969 -0.684547 l
+0.809017 -0.587785 l
+0.876307 -0.481754 l
+0.929776 -0.368125 l
+0.968583 -0.24869 l
+0.992115 -0.125333 l
+closepath
+gsave
+1.000 0.000 0.000 setrgbcolor
+fill
+grestore
+stroke
+grestore } bind def
+141.948 310.097 o
+183.982 280.847 o
+349.776 319.154 o
+205.036 272.373 o
+467.16 279.949 o
+263.68 194.1 o
+238.502 202.935 o
+401.823 285.29 o
+203.424 244.169 o
+139.037 286.975 o
+324.567 295.097 o
+335.436 340.255 o
+412.317 349.879 o
+405.054 304.302 o
+199.467 270.636 o
+175.13 248.145 o
+194.677 245.363 o
+325.407 189.377 o
+424.452 248.408 o
+339.718 131.535 o
+295.553 95.8314 o
+379.629 188.771 o
+230.192 289.599 o
+298.158 350.961 o
+249.061 277.194 o
+313.34 351.859 o
+350.84 180.339 o
+260.174 212.286 o
+445.562 173.424 o
+397.245 322.741 o
+424.276 231.741 o
+298.255 134.624 o
+456.372 285.992 o
+175.162 282.695 o
+199.379 234.216 o
+176.658 352.28 o
+431.31 88.2854 o
+208.346 180.185 o
+432.24 244.871 o
+214.029 189.36 o
+335.865 260.71 o
+447.259 213.305 o
+356.532 112.824 o
+131.977 107.822 o
+392.098 207.543 o
+182.882 287.218 o
+308.171 81.9989 o
+468.38 263.41 o
+376.244 97.0933 o
+383.555 181.489 o
+153.122 182.001 o
+313.956 264.813 o
+269.652 145.584 o
+392.175 243.59 o
+369.417 103.098 o
+243.348 180.899 o
+329.014 278.807 o
+211.301 239.006 o
+124.24 285.578 o
+139.001 154.932 o
+229.012 109.917 o
+262.784 122.07 o
+156.932 191.552 o
+236.992 79.5782 o
+349.901 267.715 o
+284.921 337.506 o
+394.845 288.663 o
+263.62 170.945 o
+140.688 210.018 o
+382.718 276.123 o
+259.229 81.8391 o
+345.867 109.84 o
+300.354 355.886 o
+380.685 306.036 o
+334.705 317.039 o
+148.873 300.674 o
+454.493 148.303 o
+157.473 323.8 o
+206.867 174.778 o
+228.325 341.37 o
+417.203 165.512 o
+303.61 97.9033 o
+130.027 354.03 o
+352.929 194.75 o
+249.376 137.524 o
+354.568 335.917 o
+127.967 349.881 o
+210.635 106.242 o
+467.895 362.661 o
+310.146 136.577 o
+121.945 336.32 o
+416.548 114.224 o
+282.651 304.598 o
+205.152 219.285 o
+356.82 150.574 o
+420.159 238.205 o
+169.816 319.918 o
+455.096 100.229 o
+289.344 174.693 o
+166.53 162.409 o
+191.123 267.381 o
+198.263 137.251 o
+397.119 321.831 o
+141.86 251.416 o
+285.482 274.935 o
+214.496 179.054 o
+410.802 305.456 o
+315.708 192.239 o
+349.155 215.149 o
+179.225 275.243 o
+140.752 316.968 o
+183.235 98.4286 o
+461.964 131.782 o
+362.467 361.371 o
+159.142 110.616 o
+183.009 191.84 o
+288.586 332.205 o
+256.058 157.972 o
+134.693 111.105 o
+253.75 107.743 o
+400.563 292.576 o
+300.8 353.144 o
+281.763 341.86 o
+173.697 335.778 o
+421.018 192.605 o
+261.816 137.183 o
+260.828 180.973 o
+420.785 96.6778 o
+255.143 179.255 o
+307.907 94.1629 o
+137.98 250.39 o
+201.038 161.44 o
+451.603 174.495 o
+323.267 94.1423 o
+408.375 116.034 o
+193.208 266.852 o
+316.01 150.97 o
+422.729 209.021 o
+368.968 156.24 o
+280.863 192.522 o
+234.134 123.962 o
+153.166 305.691 o
+262.035 229.698 o
+311.38 186.389 o
+308.443 157.173 o
+119.652 267.468 o
+311.365 179.635 o
+338.046 171.422 o
+186.684 219.232 o
+229.438 291.378 o
+444.719 285.297 o
+412.153 290.719 o
+444.74 129.61 o
+484.222 120.615 o
+181.576 336.288 o
+158.158 136.535 o
+196.094 245.995 o
+393.576 220.268 o
+227.753 355.021 o
+250.242 95.606 o
+222.758 200.339 o
+386.853 241.779 o
+438.61 88.8403 o
+225.47 270.882 o
+273.236 355.909 o
+201.18 174.462 o
+366.297 109.656 o
+276.964 209.388 o
+274.992 205.363 o
+303.379 168.117 o
+343.416 87.9614 o
+195.293 183.188 o
+238.394 109.974 o
+467.927 257.092 o
+322.17 321.093 o
+358.518 180.909 o
+353.988 273.713 o
+329.22 255.194 o
+489.475 90.9035 o
+122.542 246.619 o
+391.59 331.56 o
+205.177 122.927 o
+207.229 288.67 o
+289.431 111.462 o
+390.758 124.65 o
+135.982 202.994 o
+277.513 339.194 o
+464.019 134.279 o
+411.462 300.67 o
+310.09 288.688 o
+385.47 240.803 o
+455.172 209.08 o
+215.365 83.8475 o
+389.44 335.117 o
+220.399 155.926 o
+306.422 323.686 o
+123.959 273.269 o
+127.257 238.495 o
+470.385 172.798 o
+233.811 309.813 o
+402.089 194.862 o
+147.875 339.717 o
+205.831 148.86 o
+124.892 242.701 o
+184.541 246.283 o
+296.533 186.43 o
+390.433 331.309 o
+314.324 162.535 o
+144.118 223.441 o
+222.014 85.9764 o
+356.086 271.079 o
+466.492 365.192 o
+476.856 150.885 o
+417.718 117.738 o
+364.45 351.681 o
+389.665 113.967 o
+123.121 260.528 o
+463.954 135.787 o
+265.482 288.712 o
+298.125 334.107 o
+134.461 168.137 o
+189.386 340.436 o
+462.552 198.218 o
+303.573 241.799 o
+131.393 221.997 o
+144.031 172.427 o
+280.771 218.387 o
+169.805 244.94 o
+346.499 105.921 o
+304.369 278.357 o
+280.753 190.062 o
+416.329 140.654 o
+208.635 155.5 o
+443.665 102.859 o
+457.793 353.154 o
+380.491 278.435 o
+411.842 298.161 o
+154.428 279.989 o
+187.908 256.403 o
+270.873 275.405 o
+445.833 366.343 o
+152.601 324.146 o
+388.465 351.072 o
+247.216 183.063 o
+308.835 215.858 o
+369.37 288.949 o
+130.315 243.651 o
+407.241 108.31 o
+218.206 237.992 o
+315.175 118.669 o
+455.252 345.935 o
+278.969 247.833 o
+422.075 253.161 o
+296.151 323.389 o
+306.346 83.6648 o
+329.028 248.308 o
+256.226 148.281 o
+188.366 101.465 o
+235.592 160.708 o
+181.088 229.763 o
+338.228 337.531 o
+132.997 290.14 o
+316.134 258.428 o
+444.229 144.232 o
+330.485 295.114 o
+391.362 86.2513 o
+192.441 278.188 o
+133.101 101.563 o
+187.481 155.818 o
+181.895 287.821 o
+185.325 169.443 o
+136.413 245.119 o
+256.404 324.417 o
+332.394 182.852 o
+223.165 359.793 o
+208.627 112.468 o
+450.255 331.706 o
+323.875 362.016 o
+127.557 356.425 o
+455.683 264.63 o
+156.019 204.278 o
+137.088 114.097 o
+342.416 291.722 o
+126.617 128.944 o
+465.668 259.313 o
+201.552 204.864 o
+230.971 224.556 o
+466.88 245.201 o
+415.157 252.287 o
+256.781 226.686 o
+449.885 145.275 o
+269.834 179.576 o
+244.218 310.918 o
+457.841 318.462 o
+369.639 265.153 o
+270.398 327.019 o
+179.362 148.267 o
+411.536 281.501 o
+248.329 151.283 o
+403.743 145.67 o
+205.967 193.965 o
+152.118 117.884 o
+365.671 145.495 o
+422.989 266.32 o
+320.505 135.014 o
+169.558 232.011 o
+182.7 146.16 o
+438.169 125.346 o
+272.465 346.278 o
+208.778 325.48 o
+210.338 165.907 o
+158.622 344.731 o
+292.208 111.474 o
+244.962 333.976 o
+474.692 323.821 o
+443.422 312.808 o
+461.972 129.612 o
+417.317 258.79 o
+424.603 366.805 o
+277.295 339.354 o
+250.098 291.318 o
+455.443 120.587 o
+384.947 140.277 o
+127.324 228.269 o
+288.944 309.443 o
+177.398 208.383 o
+404.692 127.518 o
+460.257 340.659 o
+376.049 164.435 o
+141.437 114.176 o
+256.983 251.494 o
+415.142 320.927 o
+430.305 298.543 o
+168.269 229.74 o
+191.554 261.289 o
+262.514 140.37 o
+169.745 188.434 o
+185.766 150.462 o
+297.917 219.01 o
+238.631 185.411 o
+468.328 164.581 o
+242.658 309.96 o
+410.054 303.985 o
+343.531 219.031 o
+470.333 325.906 o
+425.24 134.247 o
+205.64 231.82 o
+353.474 300.811 o
+438.067 243.444 o
+223.719 84.5693 o
+331.511 272.617 o
+338.91 257.627 o
+221.947 150.375 o
+232.974 255.249 o
+232.555 223.414 o
+369.132 182.276 o
+117.738 288.333 o
+373.469 358.488 o
+383.729 226.038 o
+481.341 212.39 o
+253.477 250.498 o
+462.695 174.113 o
+155.171 224.574 o
+411.099 275.894 o
+455.595 284.871 o
+136.417 218.051 o
+151.322 266.042 o
+179.838 165.783 o
+162.408 356.066 o
+219.369 118.214 o
+355.801 238.081 o
+412.696 295.37 o
+285.094 282.256 o
+320.649 185.403 o
+215.232 176.756 o
+383.496 235.53 o
+196.352 144.404 o
+346.134 234.998 o
+189.808 345.967 o
+476.996 108.907 o
+297.717 265.013 o
+475.816 287.095 o
+182.646 247.516 o
+450.711 186.425 o
+312.88 180.805 o
+260.297 330.697 o
+320.963 164.92 o
+115.336 346.817 o
+223.07 148.25 o
+284.689 140.709 o
+382.819 141.848 o
+422.43 191.848 o
+417.825 269.326 o
+407.422 95.2982 o
+144.465 134.63 o
+339.413 255.629 o
+394.49 177.837 o
+429.643 194.609 o
+196.945 277.106 o
+450.489 238.926 o
+322.346 221.482 o
+321.624 83.8704 o
+123.935 317.764 o
+194.282 348.145 o
+314.227 363.433 o
+367.797 197.475 o
+316.266 217.362 o
+412.409 157.167 o
+343.699 150.974 o
+280.492 164.453 o
+292.752 351.185 o
+267.757 298.468 o
+237.517 188.241 o
+326.081 208.039 o
+323.07 135.736 o
+416.763 255.479 o
+438.707 219.32 o
+238.801 188.223 o
+256.379 202.286 o
+213.124 186.439 o
+299.33 102.944 o
+200.341 304.537 o
+341.647 143.874 o
+265.679 355.6 o
+480.968 102.481 o
+377.918 188.184 o
+379.368 305.439 o
+405.715 159.391 o
+263.099 203.631 o
+450.151 89.6949 o
+250.468 281.646 o
+458.703 209.487 o
+419.456 297.744 o
+442.664 251.569 o
+165.578 96.1867 o
+238.637 332.818 o
+351.982 90.5455 o
+154.777 202.325 o
+329.365 192.986 o
+426.041 306.607 o
+174.193 99.6708 o
+192.697 300.728 o
+208.049 259.504 o
+420.117 321.661 o
+373.246 196.299 o
+379.655 269.88 o
+197.944 103.654 o
+169.22 118.546 o
+335.136 105.581 o
+458.294 313.053 o
+407.343 198.627 o
+339.286 327.941 o
+318.386 298.237 o
+241.482 114.018 o
+203.971 248.294 o
+178.313 1...
 
[truncated message content]

SF.net SVN: matplotlib: [3976] trunk/scipy06/scripts/stock_scatter2.py

From: <jd...@us...> - 2007-10-21 16:07:01

Revision: 3976
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3976&view=rev
Author:   jdh2358
Date:     2007-10-21 09:06:57 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
fixed stock scatter

Modified Paths:
--------------
    trunk/scipy06/scripts/stock_scatter2.py

Modified: trunk/scipy06/scripts/stock_scatter2.py
===================================================================
--- trunk/scipy06/scripts/stock_scatter2.py	2007-10-21 16:02:07 UTC (rev 3975)
+++ trunk/scipy06/scripts/stock_scatter2.py	2007-10-21 16:06:57 UTC (rev 3976)
@@ -34,7 +34,7 @@
             converters={0:datestr2num},
             skiprows=1, unpack=True)            
 
-if 0:  # pay the load only once in interactive mode
+if 1:  # pay the load only once in interactive mode
     tickerd = dict()
     for ticker in tickers:
         tickerd[ticker] = DailyData(ticker)
@@ -138,9 +138,8 @@
 
         fig.subplots_adjust(bottom=0.15, hspace=0.05)        
 
+        fig.canvas.manager.show()
 
-        draw()
-
 class ScatterPoints:
     def __init__(self, ax, pnts, **kwargs):
         """


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3975] trunk/matplotlib

From: <jd...@us...> - 2007-10-21 16:02:11

Revision: 3975
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3975&view=rev
Author:   jdh2358
Date:     2007-10-21 09:02:07 -0700 (Sun, 21 Oct 2007)

Log Message:
-----------
added a show method for gtk fig manager

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/__init__.py
    trunk/matplotlib/lib/matplotlib/backends/backend_gtk.py
    trunk/matplotlib/setup.py
    trunk/matplotlib/setupext.py

Modified: trunk/matplotlib/lib/matplotlib/__init__.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-20 21:57:26 UTC (rev 3974)
+++ trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-21 16:02:07 UTC (rev 3975)
@@ -55,7 +55,7 @@
 """
 from __future__ import generators
 
-NEWCONFIG = True
+NEWCONFIG = False
 
 __version__  = '0.90.1'
 __revision__ = '$Revision$'

Modified: trunk/matplotlib/lib/matplotlib/backends/backend_gtk.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/backends/backend_gtk.py	2007-10-20 21:57:26 UTC (rev 3974)
+++ trunk/matplotlib/lib/matplotlib/backends/backend_gtk.py	2007-10-21 16:02:07 UTC (rev 3975)
@@ -390,7 +390,7 @@
 
         self.window = gtk.Window()
         self.window.set_title("Figure %d" % num)
-
+        
         self.vbox = gtk.VBox()
         self.window.add(self.vbox)
         self.vbox.show()
@@ -439,7 +439,10 @@
                gtk.main_level() >= 1:
             gtk.main_quit()
 
-
+    def show(self):
+        # show the figure window
+        self.window.show()
+        
     def full_screen_toggle (self):
         self._full_screen_flag = not self._full_screen_flag
         if self._full_screen_flag:

Modified: trunk/matplotlib/setup.py
===================================================================
--- trunk/matplotlib/setup.py	2007-10-20 21:57:26 UTC (rev 3974)
+++ trunk/matplotlib/setup.py	2007-10-21 16:02:07 UTC (rev 3975)
@@ -24,8 +24,8 @@
 # it.  It makes very nice antialiased output and also supports alpha
 # blending
 BUILD_AGG          = 1
-BUILD_GTKAGG       = 'auto'
-BUILD_GTK          = 'auto'
+BUILD_GTKAGG       = 1
+BUILD_GTK          = 1
 
 # build TK GUI with Agg renderer ; requires Tkinter Python extension
 # and Tk includes
@@ -271,7 +271,7 @@
 # packagers: set rc['numerix'] and rc['backend'] here to override the auto
 # defaults, eg
 #rc['numerix'] = numpy
-#rc['backend'] = GTKAgg
+#rc['backend'] = 'GTKAgg'
 if sys.platform=='win32':
     rc = dict(backend='TkAgg', numerix='numpy')
 template = file('matplotlibrc.template').read()

Modified: trunk/matplotlib/setupext.py
===================================================================
--- trunk/matplotlib/setupext.py	2007-10-20 21:57:26 UTC (rev 3974)
+++ trunk/matplotlib/setupext.py	2007-10-21 16:02:07 UTC (rev 3975)
@@ -43,9 +43,10 @@
 
 import os
 
+
 basedir = {
     'win32'  : ['win32_static',],
-    'linux2' : ['/usr/local', '/usr',],
+    'linux2' : ['/usr/local', '/usr'],
     'linux'  : ['/usr/local', '/usr',],
     'cygwin' : ['/usr/local', '/usr',],
     'darwin' : ['/sw/lib/freetype2', '/sw/lib/freetype219', '/usr/local',
@@ -170,6 +171,7 @@
     if sys.platform == 'win32':
         has_pkgconfig.cache = False
     else:
+        #print 'environ',  os.environ['PKG_CONFIG_PATH']
         status, output = commands.getstatusoutput("pkg-config --help")
         has_pkgconfig.cache = (status == 0)
     return has_pkgconfig.cache
@@ -192,6 +194,9 @@
 
     status, output = commands.getstatusoutput(
         "%s %s %s" % (pkg_config_exec, flags, packages))
+    #if packages.startswith('pygtk'):
+    #    print 'status', status, output
+    #    raise SystemExit
     if status == 0:
         for token in output.split():
             attr = _flags.get(token[:2], None)


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3974] trunk/py4science/workbook/files_etc.tex

From: <jd...@us...> - 2007-10-20 21:57:27

Revision: 3974
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3974&view=rev
Author:   jdh2358
Date:     2007-10-20 14:57:26 -0700 (Sat, 20 Oct 2007)

Log Message:
-----------
finished working with files chapter

Modified Paths:
--------------
    trunk/py4science/workbook/files_etc.tex

Modified: trunk/py4science/workbook/files_etc.tex
===================================================================
--- trunk/py4science/workbook/files_etc.tex	2007-10-20 21:32:59 UTC (rev 3973)
+++ trunk/py4science/workbook/files_etc.tex	2007-10-20 21:57:26 UTC (rev 3974)
@@ -202,3 +202,96 @@
   since 2003}
 \end{figure}
 \par\end{center}
+
+
+\subsection{Loading and saving binary data}
+\label{sec:binary_data}
+
+ASCII is bloated and slow for working with large arrays, and so binary
+data should be used if performance is a consideration.  To save an
+array \texttt{X} in binary form, you can use the numpy
+\texttt{tostring} method
+
+\begin{lstlisting}
+In [16]: import numpy
+
+# create some random numbers
+In [17]: x = numpy.random.rand(5,2)
+
+In [19]: print x
+[[ 0.56331918  0.519582  ]
+ [ 0.22685429  0.18371135]
+ [ 0.19384767  0.27367054]
+ [ 0.35935445  0.95795884]
+ [ 0.37646642  0.14431089]]
+
+# save it to a data file in binary
+In [20]: x.tofile(file('myx.dat', 'wb'))
+
+# load it into a new array
+In [21]: y = numpy.fromfile(file('myx.dat', 'rb'))
+
+# the shape is not preserved, so we will have to reshape it
+In [22]: print y
+[ 0.56331918  0.519582    0.22685429  0.18371135  0.19384767
+0.27367054
+  0.35935445  0.95795884  0.37646642  0.14431089]
+
+In [23]: y.shape
+Out[23]: (10,)
+
+# restore the original shape
+In [24]: y.shape = 5, 2
+
+In [25]: print y
+[[ 0.56331918  0.519582  ]
+ [ 0.22685429  0.18371135]
+ [ 0.19384767  0.27367054]
+ [ 0.35935445  0.95795884]
+ [ 0.37646642  0.14431089]]
+\end{lstlisting}
+
+The advantage of numpy \texttt{tofile} and \texttt{fromfile} over
+ASCII data is that the data storage is compact and the read and write
+are very fast.  It is a bit of a pain that that meta ata like array
+datatype and shape are not stored.  In this format, just the raw binary
+numeric data is stored, so you will have to keep track of the data
+type and shape by other means.  This is a good solution if you need to
+port binary data files between different packages, but if you know you
+will always be working in python, you can use the python pickle
+function to preserve all metadata (pickle also works with all standard
+python data types, but has the disadvantage that other programs and
+applications cannot easily read it)
+
+\begin{lstlisting}
+# create a 6,3 array of random integers
+In [36]: x = (256*numpy.random.rand(6,3)).astype(numpy.int)
+
+In [37]: print x
+[[173  38   2]
+ [243 207 155]
+ [127  62 140]
+ [ 46  29  98]
+ [  0  46 156]
+ [ 20 177  36]]
+
+# use pickle to save the data to a file myint.dat
+In [38]: import cPickle
+
+In [39]: cPickle.dump(x, file('myint.dat', 'wb'))
+
+# load the data into a new array
+In [40]: y = cPickle.load(file('myint.dat', 'rb'))
+
+# the array type and share are preserved
+In [41]: print y
+[[173  38   2]
+ [243 207 155]
+ [127  62 140]
+ [ 46  29  98]
+ [  0  46 156]
+ [ 20 177  36]]
+\end{lstlisting}
+
+
+


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3973] trunk/py4science/workbook

From: <jd...@us...> - 2007-10-20 21:33:00

Revision: 3973
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3973&view=rev
Author:   jdh2358
Date:     2007-10-20 14:32:59 -0700 (Sat, 20 Oct 2007)

Log Message:
-----------
added stock records exercise

Modified Paths:
--------------
    trunk/py4science/workbook/files_etc.tex
    trunk/py4science/workbook/main.tex

Added Paths:
-----------
    trunk/py4science/workbook/fig/stock_records.eps
    trunk/py4science/workbook/fig/stock_records.png

Added: trunk/py4science/workbook/fig/stock_records.eps
===================================================================
--- trunk/py4science/workbook/fig/stock_records.eps	                        (rev 0)
+++ trunk/py4science/workbook/fig/stock_records.eps	2007-10-20 21:32:59 UTC (rev 3973)
@@ -0,0 +1,9121 @@
+%!PS-Adobe-3.0 EPSF-3.0
+%%Title: fig/stock_records.eps
+%%Creator: matplotlib version 0.90.1, http://matplotlib.sourceforge.net/
+%%CreationDate: Sat Oct 20 15:31:09 2007
+%%Orientation: portrait
+%%BoundingBox: 18 180 594 612
+%%EndComments
+%%BeginProlog
+/mpldict 7 dict def
+mpldict begin
+/m { moveto } bind def
+/l { lineto } bind def
+/r { rlineto } bind def
+/box {
+m
+1 index 0 r
+0 exch r
+neg 0 r
+closepath
+} bind def
+/clipbox {
+box
+clip
+newpath
+} bind def
+/ellipse {
+newpath
+matrix currentmatrix 7 1 roll
+translate
+scale
+0 0 1 5 3 roll arc
+setmatrix
+closepath
+} bind def
+%!PS-Adobe-3.0 Resource-Font
+%%Title: Bitstream Vera Sans
+%%Copyright: Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved.
+%%Creator: Converted from TrueType by PPR
+25 dict begin
+/_d{bind def}bind def
+/_m{moveto}_d
+/_l{lineto}_d
+/_cl{closepath eofill}_d
+/_c{curveto}_d
+/_sc{7 -1 roll{setcachedevice}{pop pop pop pop pop pop}ifelse}_d
+/_e{exec}_d
+/FontName /BitstreamVeraSans-Roman def
+/PaintType 0 def
+/FontMatrix[.001 0 0 .001 0 0]def
+/FontBBox[-182 -235 1287 928]def
+/FontType 3 def
+/Encoding StandardEncoding def
+/FontInfo 10 dict dup begin
+/FamilyName (Bitstream Vera Sans) def
+/FullName (Bitstream Vera Sans) def
+/Notice (Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved. Bitstream Vera is a trademark of Bitstream, Inc.) def
+/Weight (Roman) def
+/Version (Release 1.10) def
+/ItalicAngle 0.0 def
+/isFixedPitch false def
+/UnderlinePosition -213 def
+/UnderlineThickness 143 def
+end readonly def
+/CharStrings 30 dict dup begin
+/hyphen{361 0 49 234 312 314 _sc
+49 314 _m
+312 314 _l
+312 234 _l
+49 234 _l
+49 314 _l
+_cl}_d
+/zero{636 0 66 -13 570 742 _sc
+318 664 _m
+267 664 229 639 203 589 _c
+177 539 165 464 165 364 _c
+165 264 177 189 203 139 _c
+229 89 267 64 318 64 _c
+369 64 407 89 433 139 _c
+458 189 471 264 471 364 _c
+471 464 458 539 433 589 _c
+407 639 369 664 318 664 _c
+318 742 _m
+399 742 461 709 505 645 _c
+548 580 570 486 570 364 _c
+570 241 548 147 505 83 _c
+461 19 399 -13 318 -13 _c
+236 -13 173 19 130 83 _c
+87 147 66 241 66 364 _c
+66 486 87 580 130 645 _c
+173 709 236 742 318 742 _c
+_cl}_d
+/one{636 0 110 0 544 729 _sc
+124 83 _m
+285 83 _l
+285 639 _l
+110 604 _l
+110 694 _l
+284 729 _l
+383 729 _l
+383 83 _l
+544 83 _l
+544 0 _l
+124 0 _l
+124 83 _l
+_cl}_d
+/two{{636 0 73 0 536 742 _sc
+192 83 _m
+536 83 _l
+536 0 _l
+73 0 _l
+73 83 _l
+110 121 161 173 226 239 _c
+290 304 331 346 348 365 _c
+380 400 402 430 414 455 _c
+426 479 433 504 433 528 _c
+433 566 419 598 392 622 _c
+365 646 330 659 286 659 _c
+255 659 222 653 188 643 _c
+154 632 117 616 78 594 _c
+78 694 _l
+118 710 155 722 189 730 _c
+223 738 255 742 284 742 _c
+359 742 419 723 464 685 _c
+509 647 532 597 532 534 _c
+532 504 526 475 515 449 _c
+504 422 484 390 454 354 _c
+446 344 420 317 376 272 _c
+332 227 271 164 192 83 _c
+_cl}_e}_d
+/three{{636 0 76 -13 556 742 _sc
+406 393 _m
+453 383 490 362 516 330 _c
+542 298 556 258 556 212 _c
+556 140 531 84 482 45 _c
+432 6 362 -13 271 -13 _c
+240 -13 208 -10 176 -4 _c
+144 1 110 10 76 22 _c
+76 117 _l
+103 101 133 89 166 81 _c
+198 73 232 69 268 69 _c
+330 69 377 81 409 105 _c
+441 129 458 165 458 212 _c
+458 254 443 288 413 312 _c
+383 336 341 349 287 349 _c
+202 349 _l
+202 430 _l
+291 430 _l
+339 430 376 439 402 459 _c
+428 478 441 506 441 543 _c
+441 580 427 609 401 629 _c
+374 649 336 659 287 659 _c
+260 659 231 656 200 650 _c
+169 644 135 635 98 623 _c
+98 711 _l
+135 721 170 729 203 734 _c
+235 739 266 742 296 742 _c
+}_e{370 742 429 725 473 691 _c
+517 657 539 611 539 553 _c
+539 513 527 479 504 451 _c
+481 423 448 403 406 393 _c
+_cl}_e}_d
+/four{636 0 49 0 580 729 _sc
+378 643 _m
+129 254 _l
+378 254 _l
+378 643 _l
+352 729 _m
+476 729 _l
+476 254 _l
+580 254 _l
+580 172 _l
+476 172 _l
+476 0 _l
+378 0 _l
+378 172 _l
+49 172 _l
+49 267 _l
+352 729 _l
+_cl}_d
+/five{{636 0 77 -13 549 729 _sc
+108 729 _m
+495 729 _l
+495 646 _l
+198 646 _l
+198 467 _l
+212 472 227 476 241 478 _c
+255 480 270 482 284 482 _c
+365 482 429 459 477 415 _c
+525 370 549 310 549 234 _c
+549 155 524 94 475 51 _c
+426 8 357 -13 269 -13 _c
+238 -13 207 -10 175 -6 _c
+143 -1 111 6 77 17 _c
+77 116 _l
+106 100 136 88 168 80 _c
+199 72 232 69 267 69 _c
+323 69 368 83 401 113 _c
+433 143 450 183 450 234 _c
+450 284 433 324 401 354 _c
+368 384 323 399 267 399 _c
+241 399 214 396 188 390 _c
+162 384 135 375 108 363 _c
+108 729 _l
+_cl}_e}_d
+/six{{636 0 70 -13 573 742 _sc
+330 404 _m
+286 404 251 388 225 358 _c
+199 328 186 286 186 234 _c
+186 181 199 139 225 109 _c
+251 79 286 64 330 64 _c
+374 64 409 79 435 109 _c
+461 139 474 181 474 234 _c
+474 286 461 328 435 358 _c
+409 388 374 404 330 404 _c
+526 713 _m
+526 623 _l
+501 635 476 644 451 650 _c
+425 656 400 659 376 659 _c
+310 659 260 637 226 593 _c
+192 549 172 482 168 394 _c
+187 422 211 444 240 459 _c
+269 474 301 482 336 482 _c
+409 482 467 459 509 415 _c
+551 371 573 310 573 234 _c
+573 159 550 99 506 54 _c
+462 9 403 -13 330 -13 _c
+246 -13 181 19 137 83 _c
+92 147 70 241 70 364 _c
+70 479 97 571 152 639 _c
+206 707 280 742 372 742 _c
+}_e{396 742 421 739 447 735 _c
+472 730 498 723 526 713 _c
+_cl}_e}_d
+/seven{636 0 82 0 551 729 _sc
+82 729 _m
+551 729 _l
+551 687 _l
+286 0 _l
+183 0 _l
+432 646 _l
+82 646 _l
+82 729 _l
+_cl}_d
+/eight{{636 0 68 -13 568 742 _sc
+318 346 _m
+271 346 234 333 207 308 _c
+180 283 167 249 167 205 _c
+167 161 180 126 207 101 _c
+234 76 271 64 318 64 _c
+364 64 401 76 428 102 _c
+455 127 469 161 469 205 _c
+469 249 455 283 429 308 _c
+402 333 365 346 318 346 _c
+219 388 _m
+177 398 144 418 120 447 _c
+96 476 85 511 85 553 _c
+85 611 105 657 147 691 _c
+188 725 245 742 318 742 _c
+390 742 447 725 489 691 _c
+530 657 551 611 551 553 _c
+551 511 539 476 515 447 _c
+491 418 459 398 417 388 _c
+464 377 501 355 528 323 _c
+554 291 568 251 568 205 _c
+568 134 546 80 503 43 _c
+459 5 398 -13 318 -13 _c
+237 -13 175 5 132 43 _c
+89 80 68 134 68 205 _c
+68 251 81 291 108 323 _c
+134 355 171 377 219 388 _c
+}_e{183 544 _m
+183 506 194 476 218 455 _c
+242 434 275 424 318 424 _c
+360 424 393 434 417 455 _c
+441 476 453 506 453 544 _c
+453 582 441 611 417 632 _c
+393 653 360 664 318 664 _c
+275 664 242 653 218 632 _c
+194 611 183 582 183 544 _c
+_cl}_e}_d
+/A{684 0 8 0 676 729 _sc
+342 632 _m
+208 269 _l
+476 269 _l
+342 632 _l
+286 729 _m
+398 729 _l
+676 0 _l
+573 0 _l
+507 187 _l
+178 187 _l
+112 0 _l
+8 0 _l
+286 729 _l
+_cl}_d
+/C{{698 0 56 -13 644 742 _sc
+644 673 _m
+644 569 _l
+610 599 575 622 537 638 _c
+499 653 460 661 418 661 _c
+334 661 270 635 226 584 _c
+182 533 160 460 160 364 _c
+160 268 182 194 226 143 _c
+270 92 334 67 418 67 _c
+460 67 499 74 537 90 _c
+575 105 610 128 644 159 _c
+644 56 _l
+609 32 572 15 534 4 _c
+496 -7 455 -13 412 -13 _c
+302 -13 215 20 151 87 _c
+87 154 56 246 56 364 _c
+56 481 87 573 151 641 _c
+215 708 302 742 412 742 _c
+456 742 497 736 535 725 _c
+573 713 610 696 644 673 _c
+_cl}_e}_d
+/E{632 0 98 0 568 729 _sc
+98 729 _m
+559 729 _l
+559 646 _l
+197 646 _l
+197 430 _l
+544 430 _l
+544 347 _l
+197 347 _l
+197 83 _l
+568 83 _l
+568 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/F{575 0 98 0 517 729 _sc
+98 729 _m
+517 729 _l
+517 646 _l
+197 646 _l
+197 431 _l
+486 431 _l
+486 348 _l
+197 348 _l
+197 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/G{{775 0 56 -13 693 742 _sc
+595 104 _m
+595 300 _l
+434 300 _l
+434 381 _l
+693 381 _l
+693 68 _l
+655 40 613 20 567 7 _c
+521 -6 472 -13 420 -13 _c
+306 -13 216 20 152 86 _c
+88 152 56 245 56 364 _c
+56 482 88 575 152 642 _c
+216 708 306 742 420 742 _c
+467 742 512 736 555 724 _c
+598 712 638 695 674 673 _c
+674 568 _l
+637 598 598 621 557 637 _c
+516 653 473 661 428 661 _c
+338 661 271 636 227 586 _c
+182 536 160 462 160 364 _c
+160 265 182 191 227 141 _c
+271 91 338 67 428 67 _c
+462 67 493 70 521 76 _c
+549 82 573 91 595 104 _c
+_cl}_e}_d
+/H{752 0 98 0 654 729 _sc
+98 729 _m
+197 729 _l
+197 430 _l
+555 430 _l
+555 729 _l
+654 729 _l
+654 0 _l
+555 0 _l
+555 347 _l
+197 347 _l
+197 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/I{295 0 98 0 197 729 _sc
+98 729 _m
+197 729 _l
+197 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/L{557 0 98 0 552 729 _sc
+98 729 _m
+197 729 _l
+197 83 _l
+552 83 _l
+552 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/M{863 0 98 0 765 729 _sc
+98 729 _m
+245 729 _l
+431 233 _l
+618 729 _l
+765 729 _l
+765 0 _l
+669 0 _l
+669 640 _l
+481 140 _l
+382 140 _l
+194 640 _l
+194 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/N{748 0 98 0 650 729 _sc
+98 729 _m
+231 729 _l
+554 119 _l
+554 729 _l
+650 729 _l
+650 0 _l
+517 0 _l
+194 610 _l
+194 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/O{787 0 56 -13 731 742 _sc
+394 662 _m
+322 662 265 635 223 582 _c
+181 528 160 456 160 364 _c
+160 272 181 199 223 146 _c
+265 92 322 66 394 66 _c
+465 66 522 92 564 146 _c
+606 199 627 272 627 364 _c
+627 456 606 528 564 582 _c
+522 635 465 662 394 662 _c
+394 742 _m
+496 742 577 707 639 639 _c
+700 571 731 479 731 364 _c
+731 248 700 157 639 89 _c
+577 21 496 -13 394 -13 _c
+291 -13 209 21 148 89 _c
+86 157 56 248 56 364 _c
+56 479 86 571 148 639 _c
+209 707 291 742 394 742 _c
+_cl}_d
+/P{603 0 98 0 569 729 _sc
+197 648 _m
+197 374 _l
+321 374 _l
+367 374 402 385 427 409 _c
+452 433 465 467 465 511 _c
+465 555 452 588 427 612 _c
+402 636 367 648 321 648 _c
+197 648 _l
+98 729 _m
+321 729 _l
+402 729 464 710 506 673 _c
+548 636 569 582 569 511 _c
+569 439 548 384 506 348 _c
+464 311 402 293 321 293 _c
+197 293 _l
+197 0 _l
+98 0 _l
+98 729 _l
+_cl}_d
+/S{{635 0 66 -13 579 742 _sc
+535 705 _m
+535 609 _l
+497 627 462 640 429 649 _c
+395 657 363 662 333 662 _c
+279 662 237 651 208 631 _c
+179 610 165 580 165 542 _c
+165 510 174 485 194 469 _c
+213 452 250 439 304 429 _c
+364 417 _l
+437 403 491 378 526 343 _c
+561 307 579 260 579 201 _c
+579 130 555 77 508 41 _c
+460 5 391 -13 300 -13 _c
+265 -13 228 -9 189 -2 _c
+150 5 110 16 69 32 _c
+69 134 _l
+109 111 148 94 186 83 _c
+224 71 262 66 300 66 _c
+356 66 399 77 430 99 _c
+460 121 476 152 476 194 _c
+476 230 465 258 443 278 _c
+421 298 385 313 335 323 _c
+275 335 _l
+201 349 148 372 115 404 _c
+82 435 66 478 66 534 _c
+66 598 88 649 134 686 _c
+179 723 242 742 322 742 _c
+}_e{356 742 390 739 426 733 _c
+461 727 497 717 535 705 _c
+_cl}_e}_d
+/T{611 0 -2 0 614 729 _sc
+-2 729 _m
+614 729 _l
+614 646 _l
+355 646 _l
+355 0 _l
+256 0 _l
+256 646 _l
+-2 646 _l
+-2 729 _l
+_cl}_d
+/W{989 0 33 0 956 729 _sc
+33 729 _m
+133 729 _l
+286 113 _l
+439 729 _l
+550 729 _l
+703 113 _l
+856 729 _l
+956 729 _l
+773 0 _l
+649 0 _l
+495 633 _l
+340 0 _l
+216 0 _l
+33 729 _l
+_cl}_d
+/Y{611 0 -1 0 613 729 _sc
+-1 729 _m
+104 729 _l
+306 429 _l
+507 729 _l
+613 729 _l
+355 347 _l
+355 0 _l
+256 0 _l
+256 347 _l
+-1 729 _l
+_cl}_d
+/a{{613 0 60 -13 522 560 _sc
+343 275 _m
+270 275 220 266 192 250 _c
+164 233 150 205 150 165 _c
+150 133 160 107 181 89 _c
+202 70 231 61 267 61 _c
+317 61 357 78 387 114 _c
+417 149 432 196 432 255 _c
+432 275 _l
+343 275 _l
+522 312 _m
+522 0 _l
+432 0 _l
+432 83 _l
+411 49 385 25 355 10 _c
+325 -5 287 -13 243 -13 _c
+187 -13 142 2 109 33 _c
+76 64 60 106 60 159 _c
+60 220 80 266 122 298 _c
+163 329 224 345 306 345 _c
+432 345 _l
+432 354 _l
+432 395 418 427 391 450 _c
+364 472 326 484 277 484 _c
+245 484 215 480 185 472 _c
+155 464 127 453 100 439 _c
+100 522 _l
+}_e{132 534 164 544 195 550 _c
+226 556 256 560 286 560 _c
+365 560 424 539 463 498 _c
+502 457 522 395 522 312 _c
+_cl}_e}_d
+/d{{635 0 55 -13 544 760 _sc
+454 464 _m
+454 760 _l
+544 760 _l
+544 0 _l
+454 0 _l
+454 82 _l
+435 49 411 25 382 10 _c
+353 -5 319 -13 279 -13 _c
+213 -13 159 13 117 65 _c
+75 117 55 187 55 273 _c
+55 359 75 428 117 481 _c
+159 533 213 560 279 560 _c
+319 560 353 552 382 536 _c
+411 520 435 496 454 464 _c
+148 273 _m
+148 207 161 155 188 117 _c
+215 79 253 61 301 61 _c
+348 61 385 79 413 117 _c
+440 155 454 207 454 273 _c
+454 339 440 390 413 428 _c
+385 466 348 485 301 485 _c
+253 485 215 466 188 428 _c
+161 390 148 339 148 273 _c
+_cl}_e}_d
+/e{{615 0 55 -13 562 560 _sc
+562 296 _m
+562 252 _l
+149 252 _l
+153 190 171 142 205 110 _c
+238 78 284 62 344 62 _c
+378 62 412 66 444 74 _c
+476 82 509 95 541 113 _c
+541 28 _l
+509 14 476 3 442 -3 _c
+408 -9 373 -13 339 -13 _c
+251 -13 182 12 131 62 _c
+80 112 55 181 55 268 _c
+55 357 79 428 127 481 _c
+175 533 241 560 323 560 _c
+397 560 455 536 498 489 _c
+540 441 562 377 562 296 _c
+472 322 _m
+471 371 457 410 431 440 _c
+404 469 368 484 324 484 _c
+274 484 234 469 204 441 _c
+174 413 156 373 152 322 _c
+472 322 _l
+_cl}_e}_d
+/t{392 0 27 0 368 702 _sc
+183 702 _m
+183 547 _l
+368 547 _l
+368 477 _l
+183 477 _l
+183 180 _l
+183 135 189 106 201 94 _c
+213 81 238 75 276 75 _c
+368 75 _l
+368 0 _l
+276 0 _l
+206 0 158 13 132 39 _c
+106 65 93 112 93 180 _c
+93 477 _l
+27 477 _l
+27 547 _l
+93 547 _l
+93 702 _l
+183 702 _l
+_cl}_d
+end readonly def
+
+/BuildGlyph
+ {exch begin
+ CharStrings exch
+ 2 copy known not{pop /.notdef}if
+ true 3 1 roll get exec
+ end}_d
+
+/BuildChar {
+ 1 index /Encoding get exch get
+ 1 index /BuildGlyph get exec
+}_d
+
+FontName currentdict end definefont pop
+%%EOF
+end
+%%EndProlog
+mpldict begin
+18 180 translate
+576 432 0 0 clipbox
+1.000 setgray
+1.000 setlinewidth
+0 setlinejoin
+2 setlinecap
+[] 0 setdash
+0 0 m
+0 432 l
+576 432 l
+576 0 l
+closepath
+gsave
+fill
+grestore
+stroke
+0.000 setgray
+72 43.2 m
+72 388.8 l
+518.4 388.8 l
+518.4 43.2 l
+closepath
+gsave
+1.000 setgray
+fill
+grestore
+stroke
+0.000 0.000 1.000 setrgbcolor
+gsave
+446.4 345.6 72 43.2 clipbox
+110.389 100.8 m
+110.598 100.698 l
+111.228 101.137 l
+111.438 101.261 l
+111.647 100.793 l
+111.857 101.056 l
+112.067 101.305 l
+112.696 101.276 l
+112.906 101.554 l
+113.116 101.254 l
+113.326 101.151 l
+113.535 100.558 l
+114.374 100.522 l
+114.584 100.493 l
+114.794 100.785 l
+115.004 100.222 l
+115.633 100.236 l
+115.843 100.346 l
+116.053 100.778 l
+116.262 100.171 l
+116.472 100.09 l
+117.102 100.171 l
+117.311 100.075 l
+117.521 100.046 l
+117.731 99.929 l
+117.941 99.6802 l
+118.57 99.8339 l
+118.78 99.8778 l
+118.989 99.7461 l
+119.199 100.01 l
+119.409 100.441 l
+120.248 100.844 l
+120.458 100.873 l
+120.668 100.998 l
+120.877 100.881 l
+121.507 100.712 l
+121.717 100.844 l
+121.926 100.5 l
+122.136 100.822 l
+122.346 101.203 l
+122.975 100.793 l
+123.185 100.763 l
+123.395 101.012 l
+123.605 100.793 l
+123.814 100.346 l
+124.444 100.266 l
+124.653 100.229 l
+124.863 100.456 l
+125.073 101.268 l
+125.283 101.144 l
+125.912 101.759 l
+126.122 101.891 l
+126.332 101.708 l
+126.541 101.905 l
+126.751 102.352 l
+127.38 101.59 l
+127.59 101.744 l
+127.8 101.642 l
+128.01 101.429 l
+128.22 101.181 l
+128.849 100.529 l
+129.059 100.624 l
+129.268 101.386 l
+129.478 101.422 l
+129.688 101.063 l
+130.317 101.268 l
+130.527 101.093 l
+130.737 100.807 l
+130.947 100.946 l
+131.156 100.851 l
+131.786 101.137 l
+131.995 101.115 l
+132.205 101.832 l
+132.415 102.176 l
+133.254 102.169 l
+133.464 102.41 l
+133.674 102.74 l
+133.883 102.374 l
+134.093 101.912 l
+134.723 102.235 l
+134.932 102.352 l
+135.142 101.993 l
+135.352 102.088 l
+135.562 102.432 l
+136.191 102.439 l
+136.401 102.791 l
+136.611 102.564 l
+136.82 102.33 l
+137.03 102.827 l
+137.659 103.105 l
+137.869 102.996 l
+138.079 102.879 l
+138.289 103.113 l
+138.498 102.769 l
+139.128 102.198 l
+139.338 102.191 l
+139.547 102.315 l
+139.757 102.264 l
+139.967 102.293 l
+140.806 102.959 l
+141.016 102.937 l
+141.226 103.691 l
+141.435 103.684 l
+142.065 103.376 l
+142.274 103.874 l
+142.484 104.072 l
+142.694 104.386 l
+142.904 104.335 l
+143.533 104.269 l
+143.743 104.474 l
+143.953 104.423 l
+144.162 104.599 l
+144.372 104.057 l
+145.002 104.408 l
+145.211 104.115 l
+145.421 104.328 l
+145.631 103.889 l
+145.841 103.581 l
+146.47 103.362 l
+146.68 103.427 l
+146.889 103.142 l
+147.099 103.552 l
+147.309 103.508 l
+147.938 103.676 l
+148.148 104.094 l
+148.358 104.642 l
+148.568 104.306 l
+149.407 105.125 l
+149.617 105.294 l
+149.826 105.521 l
+150.036 105.125 l
+150.246 105.426 l
+150.875 105.894 l
+151.085 105.953 l
+151.295 106.787 l
+151.505 106.523 l
+151.714 106.34 l
+152.344 105.923 l
+152.553 106.172 l
+152.763 106.443 l
+152.973 105.865 l
+153.183 106.509 l
+153.812 106.406 l
+154.022 106.501 l
+154.232 106.223 l
+154.441 106.494 l
+154.651 106.589 l
+155.28 106.662 l
+155.49 106.084 l
+155.7 105.989 l
+155.91 105.887 l
+156.12 105.601 l
+156.749 105.828 l
+156.959 106.15 l
+157.168 106.384 l
+157.378 106.684 l
+157.588 106.619 l
+158.217 107.409 l
+158.427 107.607 l
+158.637 107.526 l
+158.847 107.548 l
+159.056 108.243 l
+159.686 108.141 l
+159.895 108.463 l
+160.105 108.675 l
+160.315 108.873 l
+160.525 109.07 l
+161.364 109.173 l
+161.574 108.814 l
+161.783 109.078 l
+161.993 109.158 l
+162.623 109.48 l
+162.832 109.209 l
+163.042 108.426 l
+163.252 108.682 l
+163.462 108.902 l
+164.091 108.661 l
+164.301 109.297 l
+164.511 109.275 l
+164.72 109.466 l
+164.93 109.473 l
+165.559 109.026 l
+165.769 109.312 l
+165.979 108.514 l
+166.189 108.28 l
+166.398 108.156 l
+167.028 108.917 l
+167.238 108.331 l
+167.447 109.1 l
+167.657 109.092 l
+167.867 109.78 l
+168.496 109.744 l
+168.706 110.015 l
+168.916 109.817 l
+169.126 109.89 l
+169.335 110.344 l
+169.965 110.6 l
+170.174 110.798 l
+170.384 111.266 l
+170.594 111.595 l
+170.804 111.2 l
+171.433 111.544 l
+171.643 111.515 l
+171.853 111.098 l
+172.062 110.893 l
+172.272 110.798 l
+172.902 111.032 l
+173.111 111.896 l
+173.321 111.991 l
+173.531 112.049 l
+173.741 112.093 l
+174.37 112.847 l
+174.58 112.598 l
+174.789 112.649 l
+174.999 112.913 l
+175.209 112.744 l
+175.838 112.408 l
+176.048 112.422 l
+176.258 112.898 l
+176.468 112.679 l
+176.677 111.998 l
+177.307 111.603 l
+177.517 111.339 l
+177.726 111.808 l
+177.936 111.332 l
+178.146 111.669 l
+178.775 112.459 l
+178.985 112.188 l
+179.195 112.379 l
+179.614 112.51 l
+180.244 112.862 l
+180.453 112.73 l
+180.663 112.371 l
+180.873 112.51 l
+181.083 111.515 l
+181.712 111.2 l
+181.922 110.234 l
+182.132 110.351 l
+182.341 110.688 l
+182.551 110.659 l
+183.18 110.227 l
+183.39 110.241 l
+183.6 110.176 l
+183.81 110.688 l
+184.02 110.454 l
+184.649 110.351 l
+184.859 110.827 l
+185.068 110.812 l
+185.488 111.003 l
+186.117 111.552 l
+186.327 111.471 l
+186.537 111.478 l
+186.956 111.559 l
+187.586 112.078 l
+187.795 112.071 l
+188.005 112.825 l
+188.215 113.001 l
+188.425 112.81 l
+189.054 112.935 l
+189.264 112.547 l
+189.474 112.408 l
+189.683 112.181 l
+189.893 112.064 l
+190.732 111.866 l
+190.942 111.588 l
+191.152 111.193 l
+191.362 111.273 l
+191.991 111.742 l
+192.201 111.193 l
+192.411 111.017 l
+192.62 110.681 l
+192.83 110.424 l
+193.459 110.285 l
+193.669 111.032 l
+193.879 110.102 l
+194.089 110.029 l
+194.298 110.695 l
+194.928 110.483 l
+195.138 110.461 l
+195.347 110.776 l
+195.557 110.6 l
+195.767 110.183 l
+196.606 110.651 l
+196.816 110.505 l
+197.026 110.015 l
+197.235 110.088 l
+197.865 109.392 l
+198.074 109.531 l
+198.284 109.824 l
+198.494 109.744 l
+198.704 109.531 l
+199.333 109.875 l
+199.543 109.81 l
+199.753 109.422 l
+199.962 109.846 l
+200.172 109.356 l
+200.802 108.492 l
+201.011 108.69 l
+201.221 108.221 l
+201.431 108.06 l
+201.641 108.485 l
+202.27 108.075 l
+202.48 108.119 l
+202.689 108.558 l
+202.899 108.148 l
+203.109 107.651 l
+203.738 107.475 l
+203.948 107.424 l
+204.158 107.68 l
+204.368 108.558 l
+204.577 108.273 l
+205.207 108.485 l
+205.417 108.302 l
+205.626 108.148 l
+205.836 108.273 l
+206.046 108.785 l
+206.675 109.085 l
+206.885 108.887 l
+207.095 108.434 l
+207.305 108.265 l
+208.144 108.426 l
+208.353 108.47 l
+208.563 108.265 l
+208.773 107.768 l
+208.983 107.629 l
+209.612 107.782 l
+209.822 107.365 l
+210.032 107.504 l
+210.241 107.672 l
+210.451 108.375 l
+211.08 108.112 l
+211.29 107.921 l
+211.5 107.555 l
+211.71 107.402 l
+211.92 107.124 l
+212.549 107.343 l
+212.759 107.504 l
+212.968 107.482 l
+213.178 107.328 l
+213.388 107.665 l
+214.017 107.724 l
+214.227 108.573 l
+214.437 108.434 l
+214.647 108.339 l
+214.856 108.06 l
+215.486 107.921 l
+215.695 108.141 l
+215.905 108.112 l
+216.115 108.324 l
+216.325 108.419 l
+216.954 108.551 l
+217.164 108.8 l
+217.374 108.99 l
+217.583 109.041 l
+217.793 109.114 l
+218.632 108.961 l
+218.842 108.734 l
+219.052 108.324 l
+219.262 108.829 l
+219.891 109.253 l
+220.101 109.414 l
+220.311 109.005 l
+220.52 109.173 l
+221.359 108.726 l
+221.569 109.026 l
+221.779 108.814 l
+221.989 108.47 l
+222.198 108.478 l
+222.828 108.397 l
+223.038 108.756 l
+223.247 109.092 l
+223.457 108.697 l
+223.667 108.58 l
+224.296 108.302 l
+224.506 108.456 l
+224.716 108.456 l
+224.926 108.046 l
+225.135 107.57 l
+225.974 107.416 l
+226.184 107.577 l
+226.394 107.497 l
+226.604 107.738 l
+227.233 107.504 l
+227.443 107.438 l
+227.653 105.521 l
+227.862 105.36 l
+228.072 105.067 l
+228.702 105.191 l
+228.911 105.426 l
+229.121 104.95 l
+229.331 105.448 l
+229.541 105.03 l
+230.17 105.235 l
+230.38 105.448 l
+230.589 105.579 l
+230.799 106.121 l
+231.009 106.216 l
+231.638 106.575 l
+231.848 106.07 l
+232.058 105.96 l
+232.268 105.748 l
+232.477 105.125 l
+233.107 104.986 l
+233.317 104.964 l
+233.526 104.701 l
+233.736 104.057 l
+233.946 104.284 l
+234.575 104.181 l
+234.785 104.247 l
+234.995 104.738 l
+235.205 104.591 l
+235.414 104.32 l
+236.044 104.511 l
+236.253 104.357 l
+236.463 104.555 l
+236.673 104.43 l
+236.883 104.599 l
+237.512 104.306 l
+237.722 104.094 l
+237.932 104.189 l
+238.141 104.328 l
+238.351 103.23 l
+239.19 103.12 l
+239.4 103.003 l
+239.61 103.318 l
+239.82 103.596 l
+240.449 103.75 l
+240.659 103.735 l
+240.868 103.486 l
+241.078 103.274 l
+241.288 103.603 l
+241.917 103.837 l
+242.127 103.947 l
+242.337 103.486 l
+242.547 103.457 l
+242.756 103.288 l
+243.386 103.142 l
+243.595 102.974 l
+243.805 103.245 l
+244.015 103.237 l
+244.225 103.786 l
+244.854 103.984 l
+245.064 104.115 l
+245.274 103.984 l
+245.483 104.057 l
+245.693 103.581 l
+246.323 103.618 l
+246.532 103.391 l
+246.742 103.881 l
+246.952 103.552 l
+247.162 103.618 l
+247.791 103.742 l
+248.001 103.75 l
+248.211 104.203 l
+248.42 104.372 l
+248.63 104.101 l
+249.259 104.108 l
+249.469 104.167 l
+249.679 104.584 l
+249.889 104.774 l
+250.098 104.767 l
+250.728 104.891 l
+250.938 105.008 l
+251.147 105.082 l
+251.357 105.228 l
+251.567 105.565 l
+252.196 105.469 l
+252.406 105.367 l
+252.616 105.213 l
+252.826 105.433 l
+253.035 105.792 l
+253.665 105.85 l
+253.874 105.894 l
+254.084 106.231 l
+254.294 106.567 l
+254.504 106.121 l
+255.133 106.077 l
+255.343 105.572 l
+255.553 105.74 l
+255.972 105.455 l
+256.602 105.352 l
+256.811 104.877 l
+257.021 105.382 l
+257.231 105.111 l
+257.441 105.945 l
+258.07 106.018 l
+258.28 105.645 l
+258.489 105.316 l
+258.699 105.147 l
+258.909 105.008 l
+259.538 105.052 l
+259.748 105.477 l
+259.958 105.411 l
+260.168 105.221 l
+260.377 105.155 l
+261.007 105.104 l
+261.217 105.652 l
+261.426 105.623 l
+261.636 105.689 l
+262.475 105.572 l
+262.685 105.506 l
+262.895 105.484 l
+263.105 105.484 l
+263.314 105.587 l
+263.944 105.36 l
+264.153 105.038 l
+264.363 104.884 l
+264.573 104.935 l
+264.783 105.169 l
+265.412 105.228 l
+265.622 104.994 l
+265.832 105.426 l
+266.041 105.184 l
+266.251 105.323 l
+267.09 105.272 l
+267.3 105.03 l
+267.51 105.016 l
+267.72 104.906 l
+268.349 104.606 l
+268.559 104.796 l
+268.768 104.906 l
+268.978 104.833 l
+269.188 104.781 l
+269.817 104.928 l
+270.027 105.052 l
+270.237 105.016 l
+270.447 104.935 l
+270.656 105.367 l
+271.286 105.308 l
+271.495 105.652 l
+271.705 105.579 l
+271.915 105.718 l
+272.125 106.187 l
+272.754 106.282 l
+272.964 106.399 l
+273.174 106.165 l
+273.383 105.806 l
+273.593 106.084 l
+274.432 105.901 l
+274.642 105.587 l
+274.852 105.857 l
+275.062 106.128 l
+275.691 106.062 l
+275.901 106.501 l
+276.111 106.436 l
+276.32 106.421 l
+276.53 106.545 l
+277.159 106.845 l
+277.369 106.626 l
+277.579 106.655 l
+277.789 106.662 l
+277.998 106.209 l
+278.628 106.26 l
+278.838 105.982 l
+279.047 105.748 l
+279.257 105.652 l
+279.467 105.652 l
+280.096 105.718 l
+280.306 105.382 l
+280.516 105.645 l
+280.726 105.491 l
+281.565 105.579 l
+281.774 105.477 l
+281.984 105.711 l
+282.194 105.528 l
+282.404 105.374 l
+283.033 105.323 l
+283.243 105.462 l
+283.453 105.404 l
+283.662 105.652 l
+283.872 105.572 l
+284.502 105.455 l
+284.711 105.521 l
+284.921 105.243 l
+285.131 105.008 l
+285.341 104.752 l
+285.97 104.818 l
+286.18 105.111 l
+286.389 105.133 l
+286.599 105.623 l
+286.809 105.535 l
+287.438 105.652 l
+287.648 105.594 l
+287.858 105.726 l
+288.068 105.499 l
+288.277 105.733 l
+288.907 105.755 l
+289.117 105.953 l
+289.326 106.201 l
+289.536 106.304 l
+289.746 106.472 l
+290.375 106.684 l
+290.585 106.597 l
+290.795 106.662 l
+291.005 106.714 l
+291.214 106.911 l
+291.844 107.058 l
+292.053 107.321 l
+292.263 107.482 l
+292.473 107.533 l
+292.683 107.775 l
+293.312 107.877 l
+293.522 108.199 l
+293.732 108.229 l
+293.941 108.492 l
+294.151 108.507 l
+294.99 108.199 l
+295.2 108.434 l
+295.41 108.646 l
+295.62 108.463 l
+296.249 108.353 l
+296.459 108.134 l
+296.668 108.302 l
+296.878 108.719 l
+297.088 108.214 l
+297.717 108.229 l
+297.927 108.016 l
+298.137 108.185 l
+298.347 108.317 l
+298.556 108.317 l
+299.186 108.163 l
+299.395 108.353 l
+299.605 108.309 l
+299.815 108.068 l
+300.025 107.599 l
+300.654 107.431 l
+300.864 107.76 l
+301.074 107.702 l
+301.283 107.541 l
+301.493 107.672 l
+302.332 108.009 l
+302.542 107.877 l
+302.752 107.921 l
+302.962 108.426 l
+303.591 108.719 l
+303.801 108.756 l
+304.011 108.646 l
+304.22 108.851 l
+304.43 109.144 l
+305.059 109.092 l
+305.269 109.429 l
+305.479 108.536 l
+305.689 108.251 l
+305.898 108.053 l
+306.528 107.892 l
+306.738 108.156 l
+306.947 108.273 l
+307.157 108.47 l
+307.367 108.331 l
+307.996 108.309 l
+308.206 108.624 l
+308.416 108.734 l
+308.626 108.295 l
+308.835 108.126 l
+309.465 108.082 l
+309.674 108.214 l
+309.884 108.199 l
+310.094 108.156 l
+310.304 107.797 l
+310.933 107.958 l
+311.143 107.585 l
+311.353 107.643 l
+311.562 107.497 l
+311.772 107.336 l
+312.402 107.621 l
+312.611 107.387 l
+312.821 107.248 l
+313.031 107.204 l
+313.241 107.167 l
+313.87 107.394 l
+314.08 107.277 l
+314.289 107.387 l
+314.499 107.058 l
+314.709 107.072 l
+315.548 107.372 l
+315.758 107.343 l
+315.968 107.643 l
+316.177 107.05 l
+316.807 106.867 l
+317.017 106.809 l
+317.226 106.516 l
+317.436 106.56 l
+317.646 106.743 l
+318.275 106.655 l
+318.485 106.509 l
+318.695 106.523 l
+318.905 106.567 l
+319.114 106.443 l
+319.744 106.326 l
+319.953 106.055 l
+320.163 106.136 l
+320.373 106.509 l
+320.583 106.633 l
+321.212 106.597 l
+321.422 106.523 l
+321.632 106.223 l
+321.841 106.004 l
+322.051 106.048 l
+322.68 105.762 l
+322.89 105.762 l
+323.1 105.638 l
+323.31 105.609 l
+323.52 105.63 l
+324.149 105.792 l
+324.359 105.974 l
+324.568 105.953 l
+324.778 105.909 l
+324.988 105.572 l
+325.617 105.543 l
+325.827 105.55 l
+326.037 105.521 l
+326.247 105.36 l
+326.456 105.704 l
+327.086 105.821 l
+327.295 105.221 l
+327.505 105.733 l
+327.715 106.157 l
+327.925 106.223 l
+328.554 106.582 l
+328.764 106.619 l
+328.974 106.794 l
+329.183 107.109 l
+329.393 107.028 l
+330.023 107.197 l
+330.232 106.992 l
+330.442 106.875 l
+330.652 107.014 l
+330.862 107.153 l
+331.491 107.116 l
+331.701 107.76 l
+331.911 108.097 l
+332.33 108.214 l
+332.959 108.251 l
+333.169 108.192 l
+333.379 108.126 l
+333.589 108.478 l
+333.798 108.653 l
+334.428 108.28 l
+334.638 108.119 l
+334.847 107.753 l
+335.057 107.431 l
+335.267 107.702 l
+335.896 108.082 l
+336.106 108.156 l
+336.316 108.09 l
+336.526 108.053 l
+336.735 107.914 l
+337.365 107.49 l
+337.574 107.511 l
+337.784 107.563 l
+337.994 107.621 l
+338.204 107.621 l
+339.043 107.263 l
+339.253 107.248 l
+339.462 106.984 l
+339.672 106.911 l
+340.511 107.343 l
+340.721 107.577 l
+340.931 107.833 l
+341.141 107.863 l
+341.77 107.98 l
+341.98 107.731 l
+342.189 107.746 l
+342.399 107.621 l
+342.609 107.497 l
+343.448 107.307 l
+343.658 105.243 l
+343.868 105.104 l
+344.077 104.65 l
+344.707 104.357 l
+344.917 104.313 l
+345.126 104.262 l
+345.336 104.459 l
+345.546 104.584 l
+346.175 104.569 l
+346.385 104.298 l
+346.595 104.503 l
+346.805 104.255 l
+347.014 103.998 l
+347.644 103.903 l
+347.853 103.947 l
+348.063 103.947 l
+348.273 104.181 l
+348.483 104.386 l
+349.112 104.276 l
+349.322 104.445 l
+349.532 104.43 l
+349.741 104.43 l
+349.951 103.903 l
+350.79 103.911 l
+351 103.581 l
+351.21 103.676 l
+351.42 103.728 l
+352.049 103.845 l
+352.259 103.896 l
+352.468 104.042 l
+352.678 103.823 l
+352.888 103.698 l
+353.517 103.684 l
+353.727 103.515 l
+353.937 103.479 l
+354.147 103.296 l
+354.356 103.369 l
+354.986 103.281 l
+355.195 103.303 l
+355.405 103.42 l
+355.615 103.223 l
+355.825 103.149 l
+356.454 103.201 l
+356.664 103.318 l
+356.874 103.457 l
+357.083 103.259 l
+357.293 103.186 l
+357.923 103.296 l
+358.132 103.179 l
+358.342 103.347 l
+358.552 103.259 l
+358.762 103.091 l
+359.391 103.01 l
+359.601 102.974 l
+359.811 103.105 l
+360.02 103.032 l
+360.23 102.937 l
+360.859 103.018 l
+361.069 102.879 l
+361.279 102.849 l
+361.489 103.084 l
+362.328 102.901 l
+362.538 103.04 l
+362.747 103.164 l
+362.957 103.084 l
+363.167 102.805 l
+363.796 102.703 l
+364.006 102.871 l
+364.216 103.113 l
+364.426 103.53 l
+364.635 103.457 l
+365.265 103.113 l
+365.474 103.186 l
+365.684 102.944 l
+365.894 103.076 l
+366.104 103.193 l
+366.733 103.625 l
+366.943 103.471 l
+367.153 103.245 l
+367.362 103.091 l
+367.572 102.864 l
+368.202 103.062 l
+368.411 102.879 l
+368.621 102.593 l
+368.831 102.586 l
+369.041 102.374 l
+369.67 102.125 l
+369.88 102.081 l
+370.089 102.044 l
+370.299 102.154 l
+370.509 102.278 l
+371.348 101.986 l
+371.558 102.132 l
+371.768 102.147 l
+371.977 102.286 l
+372.607 102.103 l
+372.817 101.971 l
+373.026 101.686 l
+373.236 101.488 l
+373.446 101.517 l
+374.075 101.305 l
+374.285 101.495 l
+374.495 101.927 l
+374.705 102.205 l
+374.914 102.337 l
+375.544 102.293 l
+375.753 102.227 l
+375.963 102.403 l
+376.173 102.3 l
+376.383 102.117 l
+377.012 102.322 l
+377.222 102.154 l
+377.432 102.593 l
+377.641 103.062 l
+377.851 102.835 l
+378.48 103.091 l
+378.9 102.652 l
+379.11 102.725 l
+379.32 102.52 l
+379.949 102.249 l
+380.159 102.6 l
+380.368 102.037 l
+380.578 101.92 l
+380.788 102.037 l
+381.417 102.008 l
+381.627 102.271 l
+381.837 102.469 l
+382.047 101.481 l
+382.256 101.51 l
+382.886 101.751 l
+383.095 101.788 l
+383.305 101.766 l
+383.515 101.744 l
+383.725 102.249 l
+384.354 102.117 l
+384.564 101.876 l
+384.774 101.825 l
+384.983 101.715 l
+385.193 101.825 l
+385.823 101.708 l
+386.032 101.737 l
+386.242 101.766 l
+386.452 102.015 l
+386.662 101.773 l
+387.291 102.103 l
+387.501 102.286 l
+387.711 102.63 l
+387.92 102.593 l
+388.13 102.483 l
+388.759 102.374 l
+388.969 102.439 l
+389.179 102.469 l
+389.389 102.593 l
+389.598 102.842 l
+390.228 103.186 l
+390.438 103.398 l
+390.647 103.515 l
+390.857 103.318 l
+391.067 103.545 l
+391.906 103.618 l
+392.116 103.135 l
+392.326 103.069 l
+392.535 103.23 l
+393.165 103.201 l
+393.374 103.449 l
+393.584 103.508 l
+393.794 103.471 l
+394.004 103.274 l
+394.633 103.376 l
+394.843 103.215 l
+395.053 103.259 l
+395.262 103.047 l
+395.472 102.959 l
+396.102 103.208 l
+396.311 103.596 l
+396.521 103.911 l
+396.731 104.181 l
+396.941 104.035 l
+397.57 103.947 l
+397.78 104.035 l
+397.989 104.218 l
+398.199 104.189 l
+398.409 104.079 l
+399.038 104.072 l
+399.248 104.269 l
+399.458 104.269 l
+399.668 104.694 l
+399.877 104.774 l
+400.507 104.781 l
+400.717 104.276 l
+400.926 104.423 l
+401.136 104.364 l
+401.346 104.584 l
+401.975 104.672 l
+402.185 104.789 l
+402.395 104.862 l
+402.605 104.899 l
+402.814 104.416 l
+403.444 104.533 l
+403.653 104.591 l
+403.863 104.357 l
+404.073 104.115 l
+404.283 104.064 l
+404.912 104.291 l
+405.122 104.276 l
+405.332 104.211 l
+405.541 103.998 l
+405.751 104.115 l
+406.38 104.416 l
+406.59 105.052 l
+406.8 105.367 l
+407.01 105.374 l
+407.22 105.213 l
+407.849 105.33 l
+408.059 104.833 l
+408.268 104.943 l
+408.688 104.847 l
+409.317 104.43 l
+409.527 104.401 l
+409.737 104.591 l
+409.947 104.708 l
+410.156 104.372 l
+410.786 104.577 l
+410.995 104.503 l
+411.205 104.35 l
+411.415 104.167 l
+411.625 104.189 l
+412.254 104.203 l
+412.464 104.225 l
+412.674 104.203 l
+412.883 104.255 l
+413.093 104.386 l
+413.723 104.306 l
+413.932 104.174 l
+414.142 104.13 l
+414.352 103.962 l
+414.562 103.757 l
+415.401 103.808 l
+415.611 103.984 l
+415.82 103.998 l
+416.03 103.881 l
+417.079 103.947 l
+417.289 104.54 l
+417.498 104.489 l
+418.128 104.423 l
+418.338 104.438 l
+418.547 104.796 l
+418.757 105.082 l
+418.967 105.235 l
+419.806 105.352 l
+420.016 104.445 l
+420.226 104.167 l
+420.435 104.291 l
+421.065 104.269 l
+421.274 104.094 l
+421.484 104.306 l
+421.694 104.13 l
+421.904 104.079 l
+422.533 104.342 l
+422.743 104.372 l
+422.953 104.386 l
+423.162 104.496 l
+423.372 104.584 l
+424.002 104.701 l
+424.211 104.723 l
+424.421 104.869 l
+424.631 104.76 l
+424.841 104.518 l
+425.47 104.357 l
+425.68 104.408 l
+425.889 104.599 l
+426.099 104.723 l
+426.309 104.664 l
+427.148 104.628 l
+427.358 104.416 l
+427.568 104.474 l
+427.777 104.328 l
+428.407 104.394 l
+428.617 103.793 l
+428.826 103.676 l
+429.036 103.479 l
+429.246 103.208 l
+429.875 103.127 l
+430.085 103.34 l
+430.295 103.135 l
+430.505 103.215 l
+430.714 103.12 l
+431.344 103.398 l
+431.553 103.135 l
+431.763 103.215 l
+431.973 103.149 l
+432.183 103.157 l
+432.812 103.127 l
+433.022 103.04 l
+433.232 103.296 l
+433.441 103.164 l
+433.651 103.245 l
+434.28 103.259 l
+434.49 103.091 l
+434.7 102.952 l
+434.91 103.113 l
+435.12 103.142 l
+435.749 103.142 l
+435.959 103.274 l
+436.168 103.325 l
+436.378 103.471 l
+437.217 103.845 l
+437.427 104.269 l
+437.637 104.115 l
+437.847 104.137 l
+438.056 104.108 l
+438.686 104.276 l
+438.895 104.481 l
+439.105 104.752 l
+439.315 105.089 l
+439.525 105.338 l
+440.154 105.162 l
+440.364 105.184 l
+440.574 105.411 l
+440.783 105.287 l
+440.993 105.133 l
+441.623 104.862 l
+441.832 105.082 l
+442.042 105.177 l
+442.252 105.118 l
+442.462 105.235 l
+443.091 105.279 l
+443.301 105.418 l
+443.511 105.652 l
+443.72 105.462 l
+443.93 105.513 l
+444.559 105.396 l
+444.769 105.316 l
+444.979 105.44 l
+445.189 105.477 l
+445.398 105.813 l
+446.028 105.762 l
+446.238 106.026 l
+446.447 105.792 l
+446.657 105.287 l
+446.867 105.426 l
+447.706 105.528 l
+447.916 105.367 l
+448.126 105.44 l
+448.335 105.572 l
+448.965 105.426 l
+449.174 105.279 l
+449.384 104.935 l
+449.594 104.803 l
+449.804 105.184 l
+450.433 105.257 l
+450.643 105.455 l
+450.853 105.792 l
+451.062 106.201 l
+451.272 106.941 l
+451.902 106.889 l
+452.111 106.838 l
+452.321 106.721 l
+452.531 106.977 l
+452.741 106.545 l
+453.37 106.384 l
+453.58 106.311 l
+453.789 106.611 l
+453.999 106.706 l
+454.209 106.575 l
+454.838 106.963 l
+455.048 107.197 l
+455.468 107.204 l
+455.677 107.263 l
+456.307 107.46 l
+456.517 107.468 l
+456.726 107.182 l
+456.936 108.221 l
+457.146 108.199 l
+457.775 108.185 l
+457.985 108.463 l
+458.195 107.533 l
+458.405 107.68 l
+458.614 107.167 l
+459.244 107.292 l
+459.453 107.153 l
+459.663 107.131 l
+459.873 106.765 l
+460.083 106.428 l
+460.712 106.655 l
+460.922 106.487 l
+461.132 106.619 l
+461.341 106.984 l
+461.551 106.78 l
+462.18 106.941 l
+462.39 106.941 l
+462.6 107.343 l
+462.81 106.787 l
+463.02 106.831 l
+463.649 106.86 l
+463.859 106.699 l
+464.068 106.275 l
+464.278 106.187 l
+464.488 106.626 l
+465.117 106.926 l
+465.327 106.765 l
+465.537 106.955 l
+465.747 107.014 l
+465.956 107.424 l
+466.586 107.175 l
+466.795 106.816 l
+467.005 107.643 l
+467.215 107.782 l
+467.425 108.126 l
+468.264 108.441 l
+468.474 108.302 l
+468.683 108.419 l
+468.893 107.921 l
+469.523 107.833 l
+469.732 108.06 l
+469.942 107.914 l
+470.152 107.833 l
+470.362 107.526 l
+470.991 107.468 l
+471.201 107.877 l
+471.411 108.075 l
+471.62 108.17 l
+471.83 108.214 l
+472.459 108.295 l
+472.669 108.229 l
+472.879 108.243 l
+473.089 108.134 l
+473.298 108.207 l
+473.928 108.58 l
+474.138 108.587 l
+474.347 108.17 l
+474.557 108.016 l
+474.767 107.973 l
+475.396 108.06 l
+475.606 108.192 l
+475.816 108.221 l
+476.026 107.892 l
+476.235 107.98 l
+476.865 108.126 l
+477.074 107.929 l
+477.284 108.836 l
+477.494 109.019 l
+477.704 108.529 l
+stroke
+grestore
+0.000 0.500 0.000 setrgbcolor
+gsave
+446.4 345.6 72 43.2 clipbox
+110.389 100.8 m
+110.598 100.815 l
+111.228 101.026 l
+111.438 101.247 l
+111.647 100.91 l
+111.857 101.247 l
+112.067 101.272 l
+112.696 101.372 l
+112.906 101.497 l
+113.116 101.347 l
+113.326 101.151 l
+113.535 100.313 l
+114.374 100.288 l
+114.584 100.218 l
+114.794 100.489 l
+115.004 99.9721 l
+115.633 99.8266 l
+115.843 99.7514 l
+116.053 99.9822 l
+116.262 99.6259 l
+116.472 99.4553 l
+117.102 99.6911 l
+117.311 99.4252 l
+117.521 99.35 l
+117.731 99.4503 l
+117.941 99.2697 l
+118.57 99.4403 l
+118.78 99.2396 l
+118.989 99.2396 l
+119.199 99.355 l
+119.409 99.636 l
+120.248 99.9872 l
+120.458 99.8367 l
+120.668 99.6661 l
+120.877 99.8768 l
+121.507 99.636 l
+121.717 99.6861 l
+121.926 99.4403 l
+122.136 99.4252 l
+122.346 99.4754 l
+122.975 99.4102 l
+123.185 99.2045 l
+123.395 99.365 l
+123.605 99.2948 l
+123.814 99.4152 l
+124.444 99.1543 l
+124.653 99.0891 l
+124.863 99.3449 l
+125.073 99.8969 l
+125.283 99.9771 l
+125.912 100.439 l
+126.122 100.484 l
+126.332 100.604 l
+126.541 100.574 l
+126.751 100.715 l
+127.38 100.163 l
+127.59 100.248 l
+127.8 100.143 l
+128.01 100.052 l
+128.22 99.8969 l
+128.849 99.6962 l
+129.059 99.7564 l
+129.268 100.348 l
+129.478 100.348 l
+129.688 100.077 l
+130.317 100.108 l
+130.527 100.288 l
+130.737 99.8517 l
+130.947 99.8617 l
+131.156 99.6911 l
+131.786 99.932 l
+131.995 99.8668 l
+132.205 100.002 l
+132.415 100.253 l
+133.254 100.128 l
+133.464 100.363 l
+133.674 100.348 l
+133.883 100.248 l
+134.093 100.133 l
+134.723 100.353 l
+134.932 100.379 l
+135.142 100.283 l
+135.352 100.348 l
+135.562 100.509 l
+136.191 100.409 l
+136.401 100.624 l
+136.611 100.464 l
+136.82 100.353 l
+137.03 100.619 l
+137.659 100.554 l
+137.869 100.464 l
+138.079 100.303 l
+138.289 100.379 l
+138.498 100.283 l
+139.128 99.932 l
+139.338 99.8768 l
+139.547 99.6209 l
+139.757 99.6761 l
+139.967 99.7012 l
+140.806 99.947 l
+141.016 99.7815 l
+141.226 99.7764 l
+141.435 99.8668 l
+142.065 99.8818 l
+142.274 99.9872 l
+142.484 99.9822 l
+142.694 99.646 l
+142.904 99.4654 l
+143.533 99.5005 l
+143.743 99.8969 l
+143.953 99.9872 l
+144.162 100.032 l
+144.372 99.8868 l
+145.002 100.203 l
+145.211 100.449 l
+145.421 100.499 l
+145.631 100.499 l
+145.841 100.609 l
+146.47 100.374 l
+146.68 100.338 l
+146.889 100.148 l
+147.099 100.358 l
+147.309 100.308 l
+147.938 100.313 l
+148.148 100.529 l
+148.358 100.845 l
+148.568 100.685 l
+149.407 101.076 l
+149.617 101.196 l
+149.826 101.101 l
+150.036 100.86 l
+150.246 101.031 l
+150.875 101.071 l
+151.085 101.016 l
+151.295 101.121 l
+151.505 100.765 l
+151.714 100.85 l
+152.344 100.484 l
+152.553 100.629 l
+152.763 100.66 l
+152.973 100.469 l
+153.183 100.85 l
+153.812 100.73 l
+154.022 100.67 l
+154.232 100.564 l
+154.441 100.644 l
+154.651 100.539 l
+155.28 100.544 l
+155.49 100.318 l
+155.7 100.318 l
+155.91 100.343 l
+156.12 100.288 l
+156.749 100.298 l
+156.959 100.348 l
+157.168 100.293 l
+157.378 100.308 l
+157.588 100.268 l
+158.217 100.338 l
+158.427 100.735 l
+158.637 100.66 l
+158.847 100.569 l
+159.056 100.559 l
+159.686 100.685 l
+159.895 100.715 l
+160.105 100.649 l
+160.315 100.685 l
+160.525 100.69 l
+161.364 101.011 l
+161.574 101.457 l
+161.783 101.512 l
+161.993 101.492 l
+162.623 101.688 l
+162.832 101.487 l
+163.042 101.136 l
+163.252 101.257 l
+163.462 101.472 l
+164.091 101.482 l
+164.301 101.713 l
+164.511 101.543 l
+164.72 101.974 l
+164.93 102.17 l
+165.559 101.788 l
+165.769 102.014 l
+165.979 101.528 l
+166.189 101.432 l
+166.398 101.407 l
+167.028 101.683 l
+167.238 101.242 l
+167.447 101.553 l
+167.657 101.543 l
+167.867 101.793 l
+168.496 101.839 l
+168.706 101.819 l
+168.916 101.678 l
+169.126 101.733 l
+169.335 101.718 l
+169.965 101.663 l
+170.174 101.618 l
+170.384 101.859 l
+170.594 101.929 l
+170.804 101.798 l
+171.433 101.979 l
+171.643 101.979 l
+171.853 101.778 l
+172.062 101.788 l
+172.272 100.795 l
+172.902 100.925 l
+173.111 101.051 l
+173.321 100.85 l
+173.531 100.579 l
+173.741 100.589 l
+174.37 100.825 l
+174.58 100.559 l
+174.789 100.574 l
+174.999 100.629 l
+175.209 100.574 l
+175.838 100.529 l
+176.048 100.444 l
+176.258 100.519 l
+176.468 100.394 l
+176.677 100.313 l
+177.307 100.163 l
+177.517 100.163 l
+177.726 100.248 l
+177.936 100.143 l
+178.146 100.143 l
+178.775 100.414 l
+178.985 100.268 l
+179.195 100.293 l
+179.614 100.404 l
+180.244 100.459 l
+180.453 100.384 l
+180.663 100.389 l
+180.873 100.614 l
+181.083 100.519 l
+181.712 100.634 l
+181.922 100.695 l
+182.132 100.785 l
+182.341 100.795 l
+182.551 100.81 l
+183.18 100.85 l
+183.39 100.991 l
+183.6 100.981 l
+183.81 101.136 l
+184.02 101.116 l
+184.649 101.041 l
+184.859 101.026 l
+185.068 100.981 l
+185.488 101.051 l
+186.117 101.161 l
+186.327 101.186 l
+186.537 101.121 l
+186.956 101.156 l
+187.586 101.457 l
+187.795 101.497 l
+188.005 101.487 l
+188.215 101.462 l
+188.425 101.247 l
+189.054 101.211 l
+189.264 101.146 l
+189.474 101.267 l
+189.683 101.196 l
+189.893 101.312 l
+190.732 101.437 l
+190.942 101.523 l
+191.152 101.397 l
+191.362 101.603 l
+191.991 101.743 l
+192.201 101.502 l
+192.411 101.272 l
+192.62 101.357 l
+192.83 101.242 l
+193.459 101.136 l
+193.669 101.086 l
+193.879 100.966 l
+194.089 100.946 l
+194.298 100.996 l
+194.928 100.92 l
+195.138 100.971 l
+195.347 101.026 l
+195.557 100.94 l
+195.767 100.785 l
+196.606 100.961 l
+196.816 100.865 l
+197.026 100.73 l
+197.235 100.775 l
+197.865 100.795 l
+198.074 100.91 l
+198.284 100.835 l
+198.494 100.745 l
+198.704 100.76 l
+199.333 100.835 l
+199.543 100.7 l
+199.753 100.69 l
+199.962 100.69 l
+200.172 100.68 l
+200.802 100.454 l
+201.011 100.409 l
+201.221 100.258 l
+201.431 100.138 l
+201.641 100.263 l
+202.27 100.168 l
+202.48 100.173 l
+202.689 100.153 l
+202.899 100.047 l
+203.109 99.937 l
+203.738 99.8818 l
+203.948 99.7313 l
+204.158 99.8417 l
+204.368 100.178 l
+204.577 100.108 l
+205.207 100.233 l
+205.417 100.183 l
+205.626 100.067 l
+205.836 100.133 l
+206.046 100.464 l
+206.675 100.509 l
+206.885 100.444 l
+207.095 100.353 l
+207.305 100.303 l
+208.144 100.363 l
+208.353 100.293 l
+208.563 100.318 l
+208.773 100.193 l
+208.983 100.168 l
+209.612 100.328 l
+209.822 100.238 l
+210.032 100.293 l
+210.241 100.509 l
+210.451 101.196 l
+211.08 101.066 l
+211.29 101.056 l
+211.5 100.77 l
+211.71 100.74 l
+211.92 100.584 l
+212.549 100.68 l
+212.759 100.675 l
+212.968 100.66 l
+213.178 100.579 l
+213.388 100.434 l
+214.017 100.499 l
+214.227 100.504 l
+214.437 100.504 l
+214.647 100.574 l
+214.856 100.469 l
+215.486 100.328 l
+215.695 100.454 l
+215.905 100.363 l
+216.115 100.414 l
+216.325 100.484 l
+216.954 100.424 l
+217.164 100.574 l
+217.374 100.589 l
+217.583 100.614 l
+217.793 100.629 l
+218.632 100.579 l
+218.842 100.584 l
+219.052 100.484 l
+219.262 100.509 l
+219.891 100.715 l
+220.101 100.79 l
+220.311 100.735 l
+220.52 100.865 l
+221.359 100.92 l
+221.569 101.141 l
+221.779 101.101 l
+221.989 101.297 l
+222.198 101.548 l
+222.828 101.548 l
+223.038 101.523 l
+223.247 101.523 l
+223.457 101.563 l
+223.667 101.643 l
+224.296 101.517 l
+224.506 101.613 l
+224.716 101.638 l
+224.926 101.668 l
+225.135 101.643 l
+225.974 101.402 l
+226.184 101.437 l
+226.394 101.242 l
+226.604 101.337 l
+227.233 101.347 l
+227.443 101.221 l
+227.653 101.452 l
+227.862 101.337 l
+228.072 101.171 l
+228.702 101.372 l
+228.911 101.533 l
+229.121 101.768 l
+229.331 101.829 l
+229.541 101.407 l
+230.17 101.683 l
+230.38 101.588 l
+230.589 101.648 l
+230.799 101.603 l
+231.009 101.608 l
+231.638 101.618 l
+231.848 101.427 l
+232.058 101.422 l
+232.268 101.191 l
+232.477 101.021 l
+233.107 101.041 l
+233.317 101.272 l
+233.526 101.141 l
+233.736 100.91 l
+233.946 100.971 l
+234.575 101.001 l
+234.785 100.986 l
+234.995 101.161 l
+235.205 101.016 l
+235.414 101.051 l
+236.044 101.101 l
+236.253 101.101 l
+236.463 101.237 l
+236.673 101.186 l
+236.883 101.196 l
+237.512 101.126 l
+237.722 101.126 l
+237.932 101.166 l
+238.141 101.267 l
+238.351 101.046 l
+239.19 101.151 l
+239.4 101.111 l
+239.61 101.116 l
+239.82 101.211 l
+240.449 101.106 l
+240.659 101.186 l
+240.868 101.081 l
+241.078 101.111 l
+241.288 101.216 l
+241.917 101.216 l
+242.127 101.111 l
+242.337 101.051 l
+242.547 101.151 l
+242.756 101.121 l
+243.386 101.081 l
+243.595 101.116 l
+243.805 101.247 l
+244.015 101.277 l
+244.225 101.538 l
+244.854 101.482 l
+245.064 101.598 l
+245.274 101.663 l
+245.483 101.502 l
+245.693 101.427 l
+246.323 101.457 l
+246.532 101.442 l
+246.742 101.442 l
+246.952 101.342 l
+247.162 101.427 l
+247.791 101.608 l
+248.001 101.507 l
+248.211 101.733 l
+248.42 101.673 l
+248.63 101.317 l
+249.259 101.272 l
+249.469 101.387 l
+249.679 101.497 l
+249.889 101.437 l
+250.098 101.417 l
+250.728 101.467 l
+250.938 101.533 l
+251.147 101.633 l
+251.357 101.864 l
+251.567 101.999 l
+252.196 101.984 l
+252.406 102.2 l
+252.616 102.18 l
+252.826 102.29 l
+253.035 102.285 l
+253.665 102.526 l
+253.874 102.396 l
+254.084 102.421 l
+254.294 102.37 l
+254.504 102.27 l
+255.133 102.17 l
+255.343 102.11 l
+255.553 102.165 l
+255.972 102.145 l
+256.602 102.23 l
+256.811 102.245 l
+257.021 102.461 l
+257.231 102.38 l
+257.441 102.451 l
+258.07 102.501 l
+258.28 102.37 l
+258.489 102.511 l
+258.699 102.451 l
+258.909 102.375 l
+259.538 102.461 l
+259.748 102.451 l
+259.958 102.391 l
+260.168 102.416 l
+260.377 102.32 l
+261.007 102.315 l
+261.217 102.37 l
+261.426 102.325 l
+261.636 102.345 l
+262.475 102.265 l
+262.685 102.315 l
+262.895 102.29 l
+263.105 102.225 l
+263.314 102.205 l
+263.944 102.215 l
+264.153 102.26 l
+264.363 102.235 l
+264.573 102.22 l
+264.783 102.18 l
+265.412 102.24 l
+265.622 102.21 l
+265.832 102.235 l
+266.041 101.984 l
+266.251 101.914 l
+267.09 102.009 l
+267.3 101.844 l
+267.51 101.788 l
+267.72 101.688 l
+268.349 101.698 l
+268.559 101.864 l
+268.768 101.859 l
+268.978 101.909 l
+269.188 101.944 l
+269.817 101.989 l
+270.027 102.044 l
+270.237 102.079 l
+270.447 101.944 l
+270.656 102.009 l
+271.286 101.934 l
+271.495 101.969 l
+271.705 101.889 l
+271.915 101.884 l
+272.125 101.839 l
+272.754 101.859 l
+272.964 101.859 l
+273.174 101.793 l
+273.383 101.723 l
+273.593 101.643 l
+274.432 101.523 l
+274.642 101.507 l
+274.852 101.588 l
+275.062 101.533 l
+275.691 101.487 l
+275.901 101.543 l
+276.111 101.538 l
+276.32 101.492 l
+276.53 101.492 l
+277.159 101.638 l
+277.369 101.603 l
+277.579 101.558 l
+277.789 101.618 l
+277.998 101.452 l
+278.628 101.462 l
+278.838 101.367 l
+279.047 101.231 l
+279.257 101.186 l
+279.467 101.076 l
+280.096 101.021 l
+280.306 100.92 l
+280.516 101.011 l
+280.726 101.061 l
+281.565 101.021 l
+281.774 100.885 l
+281.984 101.001 l
+282.194 101.006 l
+282.404 100.981 l
+283.033 101.036 l
+283.243 101.151 l
+283.453 101.247 l
+283.662 101.457 l
+283.872 101.382 l
+284.502 101.392 l
+284.711 101.563 l
+284.921 101.427 l
+285.131 101.332 l
+285.341 101.146 l
+285.97 101.242 l
+286.18 101.231 l
+286.389 101.081 l
+286.599 101.543 l
+286.809 101.397 l
+287.438 101.402 l
+287.648 101.292 l
+287.858 101.402 l
+288.068 101.141 l
+288.277 101.553 l
+288.907 101.523 l
+289.117 101.583 l
+289.326 101.512 l
+289.536 101.523 l
+289.746 101.517 l
+290.375 101.462 l
+290.585 101.362 l
+290.795 101.367 l
+291.005 101.407 l
+291.214 101.553 l
+291.844 101.688 l
+292.053 101.673 l
+292.263 101.788 l
+292.473 101.894 l
+292.683 101.809 l
+293.312 101.859 l
+293.522 101.814 l
+293.732 101.793 l
+293.941 101.884 l
+294.151 101.969 l
+294.99 101.839 l
+295.2 101.844 l
+295.41 101.834 l
+295.62 101.658 l
+296.249 101.628 l
+296.459 101.698 l
+296.668 101.643 l
+296.878 101.698 l
+297.088 101.658 l
+297.717 101.598 l
+297.927 101.623 l
+298.137 101.573 l
+298.347 101.467 l
+298.556 101.467 l
+299.186 101.502 l
+299.395 101.523 l
+299.605 101.482 l
+299.815 101.598 l
+300.025 101.467 l
+300.654 101.472 l
+300.864 101.482 l
+301.074 101.492 l
+301.283 101.372 l
+301.493 101.307 l
+302.332 101.437 l
+302.542 101.302 l
+302.752 101.277 l
+302.962 101.492 l
+303.591 101.588 l
+303.801 101.743 l
+304.011 101.768 l
+304.22 101.919 l
+304.43 101.834 l
+305.059 101.713 l
+305.269 102.014 l
+305.479 102.024 l
+305.689 102.15 l
+305.898 101.778 l
+306.528 101.783 l
+306.738 101.708 l
+306.947 101.798 l
+307.157 101.814 l
+307.367 101.743 l
+307.996 101.894 l
+308.206 102.33 l
+308.416 102.541 l
+308.626 102.576 l
+308.835 102.792 l
+309.465 102.486 l
+309.674 102.591 l
+309.884 102.396 l
+310.094 102.551 l
+310.304 102.446 l
+310.933 102.521 l
+311.143 102.335 l
+311.353 102.436 l
+311.562 102.37 l
+311.772 102.325 l
+312.402 102.416 l
+312.611 102.396 l
+312.821 102.365 l
+313.031 102.476 l
+313.241 102.446 l
+313.87 102.531 l
+314.08 102.546 l
+314.289 102.646 l
+314.499 102.556 l
+314.709 102.471 l
+315.548 102.461 l
+315.758 102.386 l
+315.968 102.27 l
+316.177 102.255 l
+316.807 102.27 l
+317.017 102.205 l
+317.226 102.125 l
+317.436 102.105 l
+317.646 102.004 l
+318.275 101.974 l
+318.485 101.894 l
+318.695 101.723 l
+318.905 101.648 l
+319.114 101.613 l
+319.744 101.613 l
+319.953 101.648 l
+320.163 101.809 l
+320.373 101.944 l
+320.583 101.839 l
+321.212 101.728 l
+321.422 101.472 l
+321.632 101.322 l
+321.841 101.352 l
+322.051 101.282 l
+322.68 101.221 l
+322.89 101.196 l
+323.1 101.141 l
+323.31 101.282 l
+323.52 101.322 l
+324.149 101.252 l
+324.359 101.272 l
+324.568 101.528 l
+324.778 101.382 l
+324.988 101.377 l
+325.617 101.533 l
+325.827 101.497 l
+326.037 101.538 l
+326.247 101.412 l
+326.456 101.743 l
+327.086 101.824 l
+327.295 101.954 l
+327.505 102.195 l
+327.715 102.185 l
+327.925 102.295 l
+328.554 102.466 l
+328.764 102.486 l
+328.974 102.441 l
+329.183 102.506 l
+329.393 102.596 l
+330.023 102.641 l
+330.232 102.742 l
+330.442 102.862 l
+330.652 102.973 l
+330.862 103.023 l
+331.491 103.068 l
+331.701 102.942 l
+331.911 102.947 l
+332.33 102.872 l
+332.959 102.867 l
+333.169 102.832 l
+333.379 102.832 l
+333.589 102.932 l
+333.798 102.993 l
+334.428 102.912 l
+334.638 102.837 l
+334.847 102.867 l
+335.057 102.837 l
+335.267 102.847 l
+335.896 102.717 l
+336.106 102.561 l
+336.316 102.541 l
+336.526 102.461 l
+336.735 102.451 l
+337.365 102.416 l
+337.574 102.431 l
+337.784 102.365 l
+337.994 102.295 l
+338.204 102.32 l
+339.043 102.235 l
+339.253 102.2 l
+339.462 102.14 l
+339.672 102.084 l
+340.511 102.421 l
+340.721 102.486 l
+340.931 102.496 l
+341.141 102.456 l
+341.77 102.431 l
+341.98 102.501 l
+342.189 102.641 l
+342.399 102.566 l
+342.609 102.591 l
+343.448 102.496 l
+343.658 102.416 l
+343.868 102.506 l
+344.077 102.21 l
+344.707 102.18 l
+344.917 102.145 l
+345.126 102.205 l
+345.336 102.255 l
+345.546 102.887 l
+346.175 102.988 l
+346.385 103.063 l
+346.595 103.008 l
+346.805 102.832 l
+347.014 102.762 l
+347.644 102.581 l
+347.853 102.471 l
+348.063 102.456 l
+348.273 102.33 l
+348.483 102.345 l
+349.112 102.2 l
+349.322 102.325 l
+349.532 102.486 l
+349.741 102.451 l
+349.951 102.396 l
+350.79 102.315 l
+351 102.406 l
+351.21 102.375 l
+351.42 102.36 l
+352.049 102.566 l
+352.259 102.481 l
+352.468 102.611 l
+352.678 102.526 l
+352.888 102.511 l
+353.517 102.501 l
+353.727 102.571 l
+353.937 102.666 l
+354.147 102.541 l
+354.356 102.626 l
+354.986 102.596 l
+355.195 102.656 l
+355.405 102.722 l
+355.615 102.677 l
+355.825 102.787 l
+356.454 102.983 l
+356.664 102.907 l
+356.874 102.616 l
+357.083 102.471 l
+357.293 102.546 l
+357.923 102.546 l
+358.132 102.496 l
+358.342 102.551 l
+358.552 102.656 l
+358.762 102.646 l
+359.391 102.817 l
+359.601 102.857 l
+359.811 102.907 l
+360.02 102.817 l
+360.23 102.666 l
+360.859 102.687 l
+361.069 102.606 l
+361.279 102.641 l
+361.489 102.576 l
+362.328 102.466 l
+362.538 102.651 l
+362.747 102.556 l
+362.957 102.556 l
+363.167 102.616 l
+363.796 102.596 l
+364.006 102.596 l
+364.216 102.591 l
+364.426 102.666 l
+364.635 101.141 l
+365.265 101.211 l
+365.474 101.076 l
+365.684 100.66 l
+365.894 100.795 l
+366.104 100.971 l
+366.733 100.935 l
+366.943 100.885 l
+367.153 100.956 l
+367.362 100.685 l
+367.572 100.66 l
+368.202 100.695 l
+368.411 100.629 l
+368.621 100.489 l
+368.831 100.539 l
+369.041 100.404 l
+369.67 100.564 l
+369.88 100.519 l
+370.089 100.87 l
+370.299 100.986 l
+370.509 100.976 l
+371.348 100.695 l
+371.558 100.449 l
+371.768 100.534 l
+371.977 100.504 l
+372.607 100.374 l
+372.817 100.193 l
+373.026 100.148 l
+373.236 100.183 l
+373.446 100.088 l
+374.075 99.9872 l
+374.285 99.8868 l
+374.495 100.072 l
+374.705 100.163 l
+374.914 100.178 l
+375.544 100.399 l
+375.753 100.404 l
+375.963 100.66 l
+376.173 100.564 l
+376.383 100.374 l
+377.012 100.534 l
+377.222 100.554 l
+377.432 100.7 l
+377.641 100.855 l
+377.851 100.77 l
+378.48 100.966 l
+378.9 100.795 l
+379.11 100.86 l
+379.32 100.77 l
+379.949 100.87 l
+380.159 100.67 l
+380.368 100.444 l
+380.578 100.258 l
+380.788 100.273 l
+381.417 100.363 l
+381.627 100.494 l
+381.837 100.82 l
+382.047 100.549 l
+382.256 101.051 l
+382.886 101.116 l
+383.095 101.221 l
+383.305 101.297 l
+383.515 101.051 l
+383.725 101.237 l
+384.354 101.146 l
+384.564 101.111 l
+384.774 101.262 l
+384.983 101.221 l
+385.193 101.257 l
+385.823 101.221 l
+386.032 101.282 l
+386.242 101.332 l
+386.452 101.342 l
+386.662 101.327 l
+387.291 101.377 l
+387.501 101.467 l
+387.711 101.507 l
+387.92 101.507 l
+388.13 102.044 l
+388.759 102.21 l
+388.969 101.959 l
+389.179 101.984 l
+389.389 102.019 l
+389.598 102.074 l
+390.228 102.125 l
+390.438 102.069 l
+390.647 102.049 l
+390.857 101.999 l
+391.067 102.069 l
+391.906 101.954 l
+392.116 101.954 l
+392.326 101.869 l
+392.535 101.949 l
+393.165 102.105 l
+393.374 102.115 l
+393.584 102.14 l
+393.794 102.31 l
+394.004 102.571 l
+394.633 102.541 l
+394.843 102.576 l
+395.053 102.732 l
+395.262 102.596 l
+395.472 102.476 l
+396.102 102.621 l
+396.311 102.742 l
+396.521 102.862 l
+396.731 102.842 l
+396.941 102.817 l
+397.57 102.822 l
+397.78 102.827 l
+397.989 103.108 l
+398.199 103.098 l
+398.409 103.073 l
+399.038 103.003 l
+399.248 102.988 l
+399.458 102.912 l
+399.668 103.249 l
+399.877 103.324 l
+400.507 103.364 l
+400.717 103.359 l
+400.926 103.394 l
+401.136 103.284 l
+401.346 103.354 l
+401.975 103.364 l
+402.185 103.279 l
+402.395 103.294 l
+402.605 103.314 l
+402.814 103.309 l
+403.444 103.399 l
+403.653 103.489 l
+403.863 103.54 l
+404.073 103.519 l
+404.283 103.499 l
+404.912 103.555 l
+405.122 103.61 l
+405.332 103.625 l
+405.541 103.76 l
+405.751 103.75 l
+406.38 103.805 l
+406.59 103.795 l
+406.8 103.74 l
+407.01 103.916 l
+407.22 103.881 l
+407.849 104.127 l
+408.059 104.142 l
+408.268 104.142 l
+408.688 104.061 l
+409.317 103.921 l
+409.527 103.876 l
+409.737 103.966 l
+409.947 103.861 l
+410.156 103.74 l
+410.786 103.846 l
+410.995 103.745 l
+411.205 103.68 l
+411.415 103.61 l
+411.625 103.881 l
+412.254 103.951 l
+412.464 103.896 l
+412.674 103.956 l
+412.883 104.217 l
+413.093 104.272 l
+413.723 104.127 l
+413.932 104.177 l
+414.142 104.222 l
+414.352 104.172 l
+414.562 104.001 l
+415.401 104.177 l
+415.611 104.192 l
+415.82 104.172 l
+416.03 104.111 l
+417.079 104.111 l
+417.289 104.086 l
+417.498 104.001 l
+418.128 104.147 l
+418.338 104.162 l
+418.547 104.011 l
+418.757 104.528 l
+418.967 104.779 l
+419.806 104.754 l
+420.016 104.724 l
+420.226 104.678 l
+420.435 104.729 l
+421.065 104.538 l
+421.274 104.548 l
+421.484 104.719 l
+421.694 104.403 l
+421.904 104.478 l
+422.533 104.443 l
+422.743 104.418 l
+422.953 104.608 l
+423.162 104.458 l
+423.372 104.272 l
+424.002 103.986 l
+424.211 103.936 l
+424.421 103.866 l
+424.631 103.81 l
+424.841 103.675 l
+425.47 103.655 l
+425.68 103.74 l
+425.889 103.931 l
+426.099 103.961 l
+426.309 103.605 l
+427.148 103.65 l
+427.358 103.906 l
+427.568 103.926 l
+427.777 103.685 l
+428.407 103.765 l
+428.617 103.168 l
+428.826 103.319 l
+429.036 103.279 l
+429.246 103.113 l
+429.875 103.013 l
+430.085 103.148 l
+430.295 103.038 l
+430.505 102.897 l
+430.714 102.882 l
+431.344 102.957 l
+431.553 102.596 l
+431.763 102.937 l
+431.973 102.877 l
+432.183 102.902 l
+432.812 103.148 l
+433.022 103.153 l
+433.232 103.494 l
+433.441 103.369 l
+433.651 103.243 l
+434.28 103.344 l
+434.49 103.093 l
+434.7 103.053 l
+434.91 103.108 l
+435.12 103.168 l
+435.749 103.103 l
+435.959 103.168 l
+436.168 103.484 l
+436.378 103.509 l
+437.217 103.519 l
+437.427 103.434 l
+437.637 103.289 l
+437.847 103.504 l
+438.056 103.54 l
+438.686 103.6 l
+438.895 103.66 l
+439.105 103.534 l
+439.315 103.58 l
+439.525 103.745 l
+440.154 103.625 l
+440.364 103.63 l
+440.574 103.73 l
+440.783 103.78 l
+440.993 104.292 l
+441.623 104.202 l
+441.832 104.433 l
+442.042 104.533 l
+442.252 104.714 l
+442.462 104.508 l
+443.091 104.583 l
+443.301 104.603 l
+443.511 104.618 l
+443.72 104.518 l
+443.93 104.673 l
+444.559 104.714 l
+444.769 104.729 l
+444.979 104.814 l
+445.189 104.769 l
+445.398 104.694 l
+446.028 104.804 l
+446.238 104.623 l
+446.447 104.568 l
+446.657 104.362 l
+446.867 104.518 l
+447.706 104.673 l
+447.916 104.834 l
+448.126 104.623 l
+448.335 104.573 l
+448.965 104.638 l
+449.174 104.568 l
+449.384 104.423 l
+449.594 104.091 l
+449.804 104.307 l
+450.433 104.292 l
+450.643 104.207 l
+450.853 104.473 l
+451.062 104.538 l
+451.272 104.523 l
+451.902 104.533 l
+452.111 104.508 l
+452.321 104.287 l
+452.531 104.387 l
+452.741 104.026 l
+453.37 104.026 l
+453.58 104.041 l
+453.789 104.217 l
+453.999 104.197 l
+454.209 104.016 l
+454.838 104.152 l
+455.048 104.292 l
+455.468 104.277 l
+455.677 104.267 l
+456.307 104.217 l
+456.517 103.946 l
+456.726 104.026 l
+456.936 104.312 l
+457.146 104.192 l
+457.775 104.297 l
+457.985 104.668 l
+458.195 104.739 l
+458.405 105.035 l
+458.614 104.859 l
+459.244 104.874 l
+459.453 104.678 l
+459.663 104.633 l
+459.873 104.272 l
+460.083 103.976 l
+460.712 103.981 l
+460.922 103.775 l
+461.132 103.931 l
+461.341 104.041 l
+461.551 103.76 l
+462.18 104.051 l
+462.39 104.056 l
+462.6 104.282 l
+462.81 103.931 l
+463.02 103.635 l
+463.649 103.595 l
+463.859 103.464 l
+464.068 103.379 l
+464.278 103.233 l
+464.488 103.454 l
+465.117 103.459 l
+465.327 103.364 l
+465.537 103.439 l
+465.747 103.479 l
+465.956 103.735 l
+466.586 103.575 l
+466.795 103.294 l
+467.005 103.625 l
+467.215 103.555 l
+467.425 103.695 l
+468.264 103.735 l
+468.474 103.57 l
+468.683 103.785 l
+468.893 103.55 l
+469.523 103.57 l
+469.732 103.795 l
+469.942 103.795 l
+470.152 103.911 l
+470.362 103.851 l
+470.991 103.695 l
+471.201 103.795 l
+471.411 103.665 l
+471.62 103.54 l
+471.83 103.655 l
+472.459 103.871 l
+472.669 104.111 l
+472.879 104.081 l
+473.089 104.076 l
+473.298 104.061 l
+473.928 104.217 l
+474.138 104.182 l
+474.347 104.056 l
+474.557 104.187 l
+474.767 104.252 l
+475.396 104.252 l
+475.606 104.382 l
+475.816 104.448 l
+476.026 104.287 l
+476.235 104.418 l
+476.865 104.352 l
+477.074 104.493 l
+477.284 104.874 l
+477.494 104.914 l
+477.704 104.418 l
+stroke
+grestore
+1.000 0.000 0.000 setrgbcolor
+gsave
+446.4 345.6 72 43.2 clipbox
+110.389 100.8 m
+110.598 101.127 l
+111.228 101.677 l
+111.438 101.808 l
+111.647 101.559 l
+111.857 102.004 l
+112.067 102.371 l
+112.696 102.161 l
+112.906 102.175 l
+113.116 102.096 l
+113.326 101.559 l
+113.535 101.311 l
+114.374 101.009 l
+114.584 101.376 l
+114.794 101.769 l
+115.004 101.572 l
+115.633 101.14 l
+115.843 101.468 l
+116.053 101.599 l
+116.262 101.127 l
+116.472 101.193 l
+117.102 101.036 l
+117.311 100.905 l
+117.521 100.931 l
+117.731 101.023 l
+117.941 100.761 l
+118.57 101.009 l
+118.78 101.258 l
+118.989 101.18 l
+119.199 101.088 l
+119.409 101.651 l
+120.248 102.031 l
+120.458 101.965 l
+120.668 102.188 l
+120.877 102.253 l
+121.507 102.161 l
+121.717 102.371 l
+121.926 102.175 l
+122.136 102.423 l
+122.346 102.934 l
+122.975 102.319 l
+123.185 102.292 l
+123.395 102.305 l
+123.605 102.004 l
+123.814...
 
[truncated message content]

SF.net SVN: matplotlib: [3972] trunk/py4science/examples

From: <jd...@us...> - 2007-10-20 21:23:57

Revision: 3972
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3972&view=rev
Author:   jdh2358
Date:     2007-10-20 14:23:56 -0700 (Sat, 20 Oct 2007)

Log Message:
-----------
added stock records CSV example

Added Paths:
-----------
    trunk/py4science/examples/skel/stock_records_skel.py
    trunk/py4science/examples/stock_records.py

Added: trunk/py4science/examples/skel/stock_records_skel.py
===================================================================
--- trunk/py4science/examples/skel/stock_records_skel.py	                        (rev 0)
+++ trunk/py4science/examples/skel/stock_records_skel.py	2007-10-20 21:23:56 UTC (rev 3972)
@@ -0,0 +1,71 @@
+"""
+Download historical pricing record arrays for a universe of stocks
+from Yahoo Finance using urllib.  Load them into numpy record arrays
+using matplotlib.mlab.csv2rec, and do some batch processing -- make
+date vs price charts for each one, and compute the return since 2003
+for each stock.  Sort the returns and print out the tickers of the 4
+biggest winners
+"""
+import os, datetime, urllib
+import matplotlib.mlab as mlab  # contains csv2rec
+import numpy as npy
+import pylab as p
+
+def fetch_stock(ticker):
+    """
+    download the CSV file for stock with ticker and return a numpy
+    record array.  Save the CSV file as TICKER.csv where TICKER is the
+    stock's ticker symbol.
+
+    Extra credit for supporting a start date and end date, and
+    checking to see if the file already exists on the local file
+    system before re-downloading it
+    """
+    fname = '%s.csv'%ticker
+    url = XXX # create the url for this ticker
+
+    # the os.path module contains function for checking whether a file
+    # exists, and fetch it if not
+    XXX
+
+    # load the CSV file intoo a numpy record array
+    r = XXX
+
+    # note that the CSV file is sorted most recent date first, so you
+    # will probably want to sort the record array so most recent date
+    # is last
+    XXX
+    return r
+
+tickers = 'INTC', 'MSFT', 'YHOO', 'GOOG', 'GE', 'WMT', 'AAPL'
+
+# we want to compute returns since 2003, so define the start date as a
+# datetime.datetime instance
+startdate = XXX
+
+# we'll store a list of each return and ticker for analysis later
+data = []   # a list of (return, ticker) for each stock 
+fig = p.figure()
+for ticker in tickers:
+    print 'fetching', ticker
+    r = fetch_stock(ticker)
+    
+    # select the numpy records where r.date>=startdatre use numpy mask
+    # indexing to restrict r to just the dates > startdate
+    r = XXX
+    price = XXX   # set price equal to the adjusted close
+    returns = XXX # return is the (price-p0)/p0
+    XXX           # store the data
+
+    # plot the returns by date for each stock using pylab.plot, adding
+    # a label for the legend
+    XXX
+
+# use pylab legend command to build a legend
+XXX
+
+# now sort the data by returns and print the results for each stock
+XXX
+
+# show the figures
+p.show()

Added: trunk/py4science/examples/stock_records.py
===================================================================
--- trunk/py4science/examples/stock_records.py	                        (rev 0)
+++ trunk/py4science/examples/stock_records.py	2007-10-20 21:23:56 UTC (rev 3972)
@@ -0,0 +1,72 @@
+"""
+Download historical pricing record arrays for a universe of stocks
+from Yahoo Finance using urllib.  Load them into numpy record arrays
+using matplotlib.mlab.csv2rec, and do some batch processing -- make
+date vs price charts for each one, and compute the return since 2003
+for each stock.  Sort the returns and print out the tickers of the 4
+biggest winners
+"""
+import os, datetime, urllib
+import matplotlib.mlab as mlab  # contains csv2rec
+import numpy as npy
+import pylab as p
+
+def fetch_stock(ticker):
+    """
+    download the CSV file for stock with ticker and return a numpy
+    record array.  Save the CSV file as TICKER.csv where TICKER is the
+    stock's ticker symbol.
+
+    Extra credit for supporting a start date and end date, and
+    checking to see if the file already exists on the local file
+    system before re-downloading it
+    """
+    fname = '%s.csv'%ticker
+    url = 'http://ichart.finance.yahoo.com/table.csv?' +\
+   's=%s&d=9&e=20&f=2007&g=d&a=0&b=29&c=1993&ignore=.csv'%ticker
+
+    # the os.path module contains function for checking whether a file
+    # exists
+    if not os.path.exists(fname):
+        urllib.urlretrieve(url, fname)
+    r = mlab.csv2rec(fname)
+
+    # note that the CSV file is sorted most recent date first, so you
+    # will probably want to sort the record array so most recent date
+    # is last
+    r.sort()
+    return r
+
+tickers = 'INTC', 'MSFT', 'YHOO', 'GOOG', 'GE', 'WMT', 'AAPL'
+
+# we want to compute returns since 2003, so define the start date
+startdate = datetime.datetime(2003,1,1)
+
+# we'll store a list of each return and ticker for analysis later
+data = []   # a list of (return, ticker) for each stock 
+fig = p.figure()
+for ticker in tickers:
+    print 'fetching', ticker
+    r = fetch_stock(ticker)
+    
+    # select the numpy records where r.date>=startdatre
+
+    r = r[r.date>=startdate]
+    price = r.adj_close                 # set price equal to the adjusted close
+    returns = (price-price[0])/price[0] # return is the (price-p0)/p0
+    data.append((returns[-1], ticker))  # store the data
+
+    # plot the returns by date for each stock
+    p.plot(r.date, returns, label=ticker)
+
+p.legend(loc='upper left')
+
+# now sort the data by returns and print the results for each stock
+data.sort()
+for g, ticker in data:
+    print '%s: %1.1f%%'%(ticker, 100*g)
+
+
+p.savefig('fig/stock_records.png', dpi=100)
+p.savefig('fig/stock_records.eps')
+p.show()


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3971] trunk/py4science

From: <jd...@us...> - 2007-10-20 17:57:39

Revision: 3971
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3971&view=rev
Author:   jdh2358
Date:     2007-10-20 10:57:36 -0700 (Sat, 20 Oct 2007)

Log Message:
-----------
added files workbook

Added Paths:
-----------
    trunk/py4science/examples/skel/noisy_sine_skel.py
    trunk/py4science/workbook/fig/noisy_sine.eps
    trunk/py4science/workbook/fig/noisy_sine.png
    trunk/py4science/workbook/files_etc.tex

Added: trunk/py4science/examples/skel/noisy_sine_skel.py
===================================================================
--- trunk/py4science/examples/skel/noisy_sine_skel.py	                        (rev 0)
+++ trunk/py4science/examples/skel/noisy_sine_skel.py	2007-10-20 17:57:36 UTC (rev 3971)
@@ -0,0 +1,22 @@
+from scipy import arange, sin, pi, randn, zeros
+import pylab as p
+
+a = 2       # 2 volt amplitude
+f = 10      # 10 Hz frequency
+sigma = 0.5 # 0.5 volt standard deviation noise
+
+# create the t and v arrays; see the scipy commands arange, sin, and randn
+t = XXX # an evenly sampled time array
+v = XXX # a noisy sine wave
+
+# create a 2D array X and put t in the 1st column and v in the 2nd;
+# see the numpy command zeros
+X = XXX
+
+# save the output file as ASCII; see the pylab command save
+XXX
+
+# plot the arrays t vs v and label the x-axis, y-axis and title save
+# the output figure as noisy_sine.png.  See the pylab commands plot,
+# xlabel, ylabel, grid, show
+XXX

Added: trunk/py4science/workbook/fig/noisy_sine.eps
===================================================================
--- trunk/py4science/workbook/fig/noisy_sine.eps	                        (rev 0)
+++ trunk/py4science/workbook/fig/noisy_sine.eps	2007-10-20 17:57:36 UTC (rev 3971)
@@ -0,0 +1,954 @@
+%!PS-Adobe-3.0 EPSF-3.0
+%%Title: noisy_sine.eps
+%%Creator: matplotlib version 0.90.1, http://matplotlib.sourceforge.net/
+%%CreationDate: Sat Oct 20 11:42:38 2007
+%%Orientation: portrait
+%%BoundingBox: 18 180 594 612
+%%EndComments
+%%BeginProlog
+/mpldict 7 dict def
+mpldict begin
+/m { moveto } bind def
+/l { lineto } bind def
+/r { rlineto } bind def
+/box {
+m
+1 index 0 r
+0 exch r
+neg 0 r
+closepath
+} bind def
+/clipbox {
+box
+clip
+newpath
+} bind def
+/ellipse {
+newpath
+matrix currentmatrix 7 1 roll
+translate
+scale
+0 0 1 5 3 roll arc
+setmatrix
+closepath
+} bind def
+%!PS-Adobe-3.0 Resource-Font
+%%Title: Bitstream Vera Sans
+%%Copyright: Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved.
+%%Creator: Converted from TrueType by PPR
+25 dict begin
+/_d{bind def}bind def
+/_m{moveto}_d
+/_l{lineto}_d
+/_cl{closepath eofill}_d
+/_c{curveto}_d
+/_sc{7 -1 roll{setcachedevice}{pop pop pop pop pop pop}ifelse}_d
+/_e{exec}_d
+/FontName /BitstreamVeraSans-Roman def
+/PaintType 0 def
+/FontMatrix[.001 0 0 .001 0 0]def
+/FontBBox[-182 -235 1287 928]def
+/FontType 3 def
+/Encoding StandardEncoding def
+/FontInfo 10 dict dup begin
+/FamilyName (Bitstream Vera Sans) def
+/FullName (Bitstream Vera Sans) def
+/Notice (Copyright (c) 2003 by Bitstream, Inc. All Rights Reserved. Bitstream Vera is a trademark of Bitstream, Inc.) def
+/Weight (Roman) def
+/Version (Release 1.10) def
+/ItalicAngle 0.0 def
+/isFixedPitch false def
+/UnderlinePosition -213 def
+/UnderlineThickness 143 def
+end readonly def
+/CharStrings 25 dict dup begin
+/space{318 0 0 0 0 0 _sc
+}_d
+/parenleft{390 0 86 -131 310 759 _sc
+310 759 _m
+266 683 234 609 213 536 _c
+191 463 181 389 181 314 _c
+181 238 191 164 213 91 _c
+234 17 266 -56 310 -131 _c
+232 -131 _l
+183 -54 146 20 122 94 _c
+98 168 86 241 86 314 _c
+86 386 98 459 122 533 _c
+146 607 182 682 232 759 _c
+310 759 _l
+_cl}_d
+/parenright{390 0 80 -131 304 759 _sc
+80 759 _m
+158 759 _l
+206 682 243 607 267 533 _c
+291 459 304 386 304 314 _c
+304 241 291 168 267 94 _c
+243 20 206 -54 158 -131 _c
+80 -131 _l
+123 -56 155 17 177 91 _c
+198 164 209 238 209 314 _c
+209 389 198 463 177 536 _c
+155 609 123 683 80 759 _c
+_cl}_d
+/hyphen{361 0 49 234 312 314 _sc
+49 314 _m
+312 314 _l
+312 234 _l
+49 234 _l
+49 314 _l
+_cl}_d
+/period{318 0 107 0 210 124 _sc
+107 124 _m
+210 124 _l
+210 0 _l
+107 0 _l
+107 124 _l
+_cl}_d
+/zero{636 0 66 -13 570 742 _sc
+318 664 _m
+267 664 229 639 203 589 _c
+177 539 165 464 165 364 _c
+165 264 177 189 203 139 _c
+229 89 267 64 318 64 _c
+369 64 407 89 433 139 _c
+458 189 471 264 471 364 _c
+471 464 458 539 433 589 _c
+407 639 369 664 318 664 _c
+318 742 _m
+399 742 461 709 505 645 _c
+548 580 570 486 570 364 _c
+570 241 548 147 505 83 _c
+461 19 399 -13 318 -13 _c
+236 -13 173 19 130 83 _c
+87 147 66 241 66 364 _c
+66 486 87 580 130 645 _c
+173 709 236 742 318 742 _c
+_cl}_d
+/one{636 0 110 0 544 729 _sc
+124 83 _m
+285 83 _l
+285 639 _l
+110 604 _l
+110 694 _l
+284 729 _l
+383 729 _l
+383 83 _l
+544 83 _l
+544 0 _l
+124 0 _l
+124 83 _l
+_cl}_d
+/two{{636 0 73 0 536 742 _sc
+192 83 _m
+536 83 _l
+536 0 _l
+73 0 _l
+73 83 _l
+110 121 161 173 226 239 _c
+290 304 331 346 348 365 _c
+380 400 402 430 414 455 _c
+426 479 433 504 433 528 _c
+433 566 419 598 392 622 _c
+365 646 330 659 286 659 _c
+255 659 222 653 188 643 _c
+154 632 117 616 78 594 _c
+78 694 _l
+118 710 155 722 189 730 _c
+223 738 255 742 284 742 _c
+359 742 419 723 464 685 _c
+509 647 532 597 532 534 _c
+532 504 526 475 515 449 _c
+504 422 484 390 454 354 _c
+446 344 420 317 376 272 _c
+332 227 271 164 192 83 _c
+_cl}_e}_d
+/three{{636 0 76 -13 556 742 _sc
+406 393 _m
+453 383 490 362 516 330 _c
+542 298 556 258 556 212 _c
+556 140 531 84 482 45 _c
+432 6 362 -13 271 -13 _c
+240 -13 208 -10 176 -4 _c
+144 1 110 10 76 22 _c
+76 117 _l
+103 101 133 89 166 81 _c
+198 73 232 69 268 69 _c
+330 69 377 81 409 105 _c
+441 129 458 165 458 212 _c
+458 254 443 288 413 312 _c
+383 336 341 349 287 349 _c
+202 349 _l
+202 430 _l
+291 430 _l
+339 430 376 439 402 459 _c
+428 478 441 506 441 543 _c
+441 580 427 609 401 629 _c
+374 649 336 659 287 659 _c
+260 659 231 656 200 650 _c
+169 644 135 635 98 623 _c
+98 711 _l
+135 721 170 729 203 734 _c
+235 739 266 742 296 742 _c
+}_e{370 742 429 725 473 691 _c
+517 657 539 611 539 553 _c
+539 513 527 479 504 451 _c
+481 423 448 403 406 393 _c
+_cl}_e}_d
+/four{636 0 49 0 580 729 _sc
+378 643 _m
+129 254 _l
+378 254 _l
+378 643 _l
+352 729 _m
+476 729 _l
+476 254 _l
+580 254 _l
+580 172 _l
+476 172 _l
+476 0 _l
+378 0 _l
+378 172 _l
+49 172 _l
+49 267 _l
+352 729 _l
+_cl}_d
+/five{{636 0 77 -13 549 729 _sc
+108 729 _m
+495 729 _l
+495 646 _l
+198 646 _l
+198 467 _l
+212 472 227 476 241 478 _c
+255 480 270 482 284 482 _c
+365 482 429 459 477 415 _c
+525 370 549 310 549 234 _c
+549 155 524 94 475 51 _c
+426 8 357 -13 269 -13 _c
+238 -13 207 -10 175 -6 _c
+143 -1 111 6 77 17 _c
+77 116 _l
+106 100 136 88 168 80 _c
+199 72 232 69 267 69 _c
+323 69 368 83 401 113 _c
+433 143 450 183 450 234 _c
+450 284 433 324 401 354 _c
+368 384 323 399 267 399 _c
+241 399 214 396 188 390 _c
+162 384 135 375 108 363 _c
+108 729 _l
+_cl}_e}_d
+/A{684 0 8 0 676 729 _sc
+342 632 _m
+208 269 _l
+476 269 _l
+342 632 _l
+286 729 _m
+398 729 _l
+676 0 _l
+573 0 _l
+507 187 _l
+178 187 _l
+112 0 _l
+8 0 _l
+286 729 _l
+_cl}_d
+/V{684 0 8 0 676 729 _sc
+286 0 _m
+8 729 _l
+111 729 _l
+342 115 _l
+573 729 _l
+676 729 _l
+398 0 _l
+286 0 _l
+_cl}_d
+/a{{613 0 60 -13 522 560 _sc
+343 275 _m
+270 275 220 266 192 250 _c
+164 233 150 205 150 165 _c
+150 133 160 107 181 89 _c
+202 70 231 61 267 61 _c
+317 61 357 78 387 114 _c
+417 149 432 196 432 255 _c
+432 275 _l
+343 275 _l
+522 312 _m
+522 0 _l
+432 0 _l
+432 83 _l
+411 49 385 25 355 10 _c
+325 -5 287 -13 243 -13 _c
+187 -13 142 2 109 33 _c
+76 64 60 106 60 159 _c
+60 220 80 266 122 298 _c
+163 329 224 345 306 345 _c
+432 345 _l
+432 354 _l
+432 395 418 427 391 450 _c
+364 472 326 484 277 484 _c
+245 484 215 480 185 472 _c
+155 464 127 453 100 439 _c
+100 522 _l
+}_e{132 534 164 544 195 550 _c
+226 556 256 560 286 560 _c
+365 560 424 539 463 498 _c
+502 457 522 395 522 312 _c
+_cl}_e}_d
+/e{{615 0 55 -13 562 560 _sc
+562 296 _m
+562 252 _l
+149 252 _l
+153 190 171 142 205 110 _c
+238 78 284 62 344 62 _c
+378 62 412 66 444 74 _c
+476 82 509 95 541 113 _c
+541 28 _l
+509 14 476 3 442 -3 _c
+408 -9 373 -13 339 -13 _c
+251 -13 182 12 131 62 _c
+80 112 55 181 55 268 _c
+55 357 79 428 127 481 _c
+175 533 241 560 323 560 _c
+397 560 455 536 498 489 _c
+540 441 562 377 562 296 _c
+472 322 _m
+471 371 457 410 431 440 _c
+404 469 368 484 324 484 _c
+274 484 234 469 204 441 _c
+174 413 156 373 152 322 _c
+472 322 _l
+_cl}_e}_d
+/i{278 0 94 0 184 760 _sc
+94 547 _m
+184 547 _l
+184 0 _l
+94 0 _l
+94 547 _l
+94 760 _m
+184 760 _l
+184 646 _l
+94 646 _l
+94 760 _l
+_cl}_d
+/l{278 0 94 0 184 760 _sc
+94 760 _m
+184 760 _l
+184 0 _l
+94 0 _l
+94 760 _l
+_cl}_d
+/m{{974 0 91 0 889 560 _sc
+520 442 _m
+542 482 569 511 600 531 _c
+631 550 668 560 711 560 _c
+767 560 811 540 842 500 _c
+873 460 889 403 889 330 _c
+889 0 _l
+799 0 _l
+799 327 _l
+799 379 789 418 771 444 _c
+752 469 724 482 686 482 _c
+639 482 602 466 575 435 _c
+548 404 535 362 535 309 _c
+535 0 _l
+445 0 _l
+445 327 _l
+445 379 435 418 417 444 _c
+398 469 369 482 331 482 _c
+285 482 248 466 221 435 _c
+194 404 181 362 181 309 _c
+181 0 _l
+91 0 _l
+91 547 _l
+181 547 _l
+181 462 _l
+201 495 226 520 255 536 _c
+283 552 317 560 357 560 _c
+397 560 430 550 458 530 _c
+486 510 506 480 520 442 _c
+}_e{_cl}_e}_d
+/n{634 0 91 0 549 560 _sc
+549 330 _m
+549 0 _l
+459 0 _l
+459 327 _l
+459 379 448 417 428 443 _c
+408 469 378 482 338 482 _c
+289 482 251 466 223 435 _c
+195 404 181 362 181 309 _c
+181 0 _l
+91 0 _l
+91 547 _l
+181 547 _l
+181 462 _l
+202 494 227 519 257 535 _c
+286 551 320 560 358 560 _c
+420 560 468 540 500 501 _c
+532 462 549 405 549 330 _c
+_cl}_d
+/o{612 0 55 -13 557 560 _sc
+306 484 _m
+258 484 220 465 192 427 _c
+164 389 150 338 150 273 _c
+150 207 163 156 191 118 _c
+219 80 257 62 306 62 _c
+354 62 392 80 420 118 _c
+448 156 462 207 462 273 _c
+462 337 448 389 420 427 _c
+392 465 354 484 306 484 _c
+306 560 _m
+384 560 445 534 490 484 _c
+534 433 557 363 557 273 _c
+557 183 534 113 490 63 _c
+445 12 384 -13 306 -13 _c
+227 -13 165 12 121 63 _c
+77 113 55 183 55 273 _c
+55 363 77 433 121 484 _c
+165 534 227 560 306 560 _c
+_cl}_d
+/s{{521 0 54 -13 472 560 _sc
+443 531 _m
+443 446 _l
+417 458 391 468 364 475 _c
+336 481 308 485 279 485 _c
+234 485 200 478 178 464 _c
+156 450 145 430 145 403 _c
+145 382 153 366 169 354 _c
+185 342 217 330 265 320 _c
+296 313 _l
+360 299 405 279 432 255 _c
+458 230 472 195 472 151 _c
+472 100 452 60 412 31 _c
+372 1 316 -13 246 -13 _c
+216 -13 186 -10 154 -5 _c
+122 0 89 8 54 20 _c
+54 113 _l
+87 95 120 82 152 74 _c
+184 65 216 61 248 61 _c
+290 61 323 68 346 82 _c
+368 96 380 117 380 144 _c
+380 168 371 187 355 200 _c
+339 213 303 226 247 238 _c
+216 245 _l
+160 257 119 275 95 299 _c
+70 323 58 356 58 399 _c
+58 450 76 490 112 518 _c
+148 546 200 560 268 560 _c
+}_e{301 560 332 557 362 552 _c
+391 547 418 540 443 531 _c
+_cl}_e}_d
+/t{392 0 27 0 368 702 _sc
+183 702 _m
+183 547 _l
+368 547 _l
+368 477 _l
+183 477 _l
+183 180 _l
+183 135 189 106 201 94 _c
+213 81 238 75 276 75 _c
+368 75 _l
+368 0 _l
+276 0 _l
+206 0 158 13 132 39 _c
+106 65 93 112 93 180 _c
+93 477 _l
+27 477 _l
+27 547 _l
+93 547 _l
+93 702 _l
+183 702 _l
+_cl}_d
+/v{592 0 30 0 562 547 _sc
+30 547 _m
+125 547 _l
+296 88 _l
+467 547 _l
+562 547 _l
+357 0 _l
+235 0 _l
+30 547 _l
+_cl}_d
+/w{818 0 42 0 776 547 _sc
+42 547 _m
+132 547 _l
+244 120 _l
+356 547 _l
+462 547 _l
+574 120 _l
+686 547 _l
+776 547 _l
+633 0 _l
+527 0 _l
+409 448 _l
+291 0 _l
+185 0 _l
+42 547 _l
+_cl}_d
+/y{592 0 30 -207 562 547 _sc
+322 -50 _m
+296 -114 271 -157 247 -177 _c
+223 -197 191 -207 151 -207 _c
+79 -207 _l
+79 -132 _l
+132 -132 _l
+156 -132 175 -126 189 -114 _c
+203 -102 218 -75 235 -31 _c
+251 9 _l
+30 547 _l
+125 547 _l
+296 119 _l
+467 547 _l
+562 547 _l
+322 -50 _l
+_cl}_d
+end readonly def
+
+/BuildGlyph
+ {exch begin
+ CharStrings exch
+ 2 copy known not{pop /.notdef}if
+ true 3 1 roll get exec
+ end}_d
+
+/BuildChar {
+ 1 index /Encoding get exch get
+ 1 index /BuildGlyph get exec
+}_d
+
+FontName currentdict end definefont pop
+%%EOF
+end
+%%EndProlog
+mpldict begin
+18 180 translate
+576 432 0 0 clipbox
+1.000 setgray
+1.000 setlinewidth
+0 setlinejoin
+2 setlinecap
+[] 0 setdash
+0 0 m
+0 432 l
+576 432 l
+576 0 l
+closepath
+gsave
+fill
+grestore
+stroke
+0.000 setgray
+72 43.2 m
+72 388.8 l
+518.4 388.8 l
+518.4 43.2 l
+closepath
+gsave
+1.000 setgray
+fill
+grestore
+stroke
+0.000 0.000 1.000 setrgbcolor
+gsave
+446.4 345.6 72 43.2 clipbox
+72 192.08 m
+76.464 314.444 l
+80.928 238.206 l
+85.392 145.963 l
+89.856 52.5249 l
+94.32 177.605 l
+98.784 244.507 l
+103.248 225.898 l
+107.712 141.274 l
+112.176 101.132 l
+116.64 221.273 l
+121.104 220.387 l
+125.568 198.393 l
+130.032 110.626 l
+134.496 87.2167 l
+138.96 172.301 l
+143.424 288.57 l
+147.888 223.822 l
+152.352 109.895 l
+156.816 99.5877 l
+161.28 161.557 l
+165.744 327.85 l
+170.208 226.413 l
+174.672 119.61 l
+179.136 160.455 l
+183.6 170.923 l
+188.064 276.783 l
+192.528 252.279 l
+196.992 93.6217 l
+201.456 102.264 l
+205.92 231.631 l
+210.384 344.07 l
+214.848 237.692 l
+219.312 118.454 l
+223.776 88.4453 l
+228.24 156.313 l
+232.704 288.34 l
+237.168 265.415 l
+241.632 167.558 l
+246.096 89.9739 l
+250.56 176.91 l
+255.024 291.251 l
+259.488 263.848 l
+263.952 152.691 l
+268.416 113.887 l
+272.88 209.028 l
+277.344 335.703 l
+281.808 269.446 l
+286.272 94.2113 l
+290.736 103.596 l
+295.2 177.029 l
+299.664 270.441 l
+304.128 238.945 l
+308.592 118.646 l
+313.056 125.076 l
+317.52 184.406 l
+321.984 271.919 l
+326.448 271.253 l
+330.912 119.814 l
+335.376 72.1308 l
+339.84 129.271 l
+344.304 273.684 l
+348.768 291.815 l
+353.232 113.503 l
+357.696 77.032 l
+362.16 204.519 l
+366.624 272.078 l
+371.088 226.513 l
+375.552 141.138 l
+380.016 95.2778 l
+384.48 204.455 l
+388.944 287.641 l
+393.408 229.498 l
+397.872 126.356 l
+402.336 106.437 l
+406.8 210.134 l
+411.264 265.254 l
+415.728 240.776 l
+420.192 105.556 l
+424.656 141.974 l
+429.12 200.065 l
+433.584 290.119 l
+438.048 258.193 l
+442.512 168.972 l
+446.976 59.1563 l
+451.44 194.952 l
+455.904 311.614 l
+460.368 199.751 l
+464.832 132.967 l
+469.296 76.716 l
+473.76 232.12 l
+478.224 278.764 l
+482.688 217.446 l
+487.152 148.717 l
+491.616 86.2078 l
+496.08 175.329 l
+500.544 272.56 l
+505.008 227.057 l
+509.472 80.2823 l
+513.936 93.877 l
+stroke
+grestore
+0.000 setgray
+/BitstreamVeraSans-Roman findfont
+12.000 scalefont
+setfont
+63.25 30.122 m
+0 0.172 rmoveto
+(0.0) show
+0.500 setlinewidth
+0 setlinecap
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+183.6 43.2 m
+183.6 388.8 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+-0.5 0 m
+-0.5 4 l
+closepath
+stroke
+grestore } bind def
+183.6 43.2 o
+/o { gsave
+newpath
+translate
+-0.5 -4 m
+-0.5 0 l
+closepath
+stroke
+grestore } bind def
+183.6 388.8 o
+174.975 30.122 m
+0 0.172 rmoveto
+(0.5) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+295.2 43.2 m
+295.2 388.8 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+-0.5 0 m
+-0.5 4 l
+closepath
+stroke
+grestore } bind def
+295.2 43.2 o
+/o { gsave
+newpath
+translate
+-0.5 -4 m
+-0.5 0 l
+closepath
+stroke
+grestore } bind def
+295.2 388.8 o
+286.708 30.122 m
+0 0.172 rmoveto
+(1.0) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+406.8 43.2 m
+406.8 388.8 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+-0.5 0 m
+-0.5 4 l
+closepath
+stroke
+grestore } bind def
+406.8 43.2 o
+/o { gsave
+newpath
+translate
+-0.5 -4 m
+-0.5 0 l
+closepath
+stroke
+grestore } bind def
+406.8 388.8 o
+398.433 30.278 m
+0 0.172 rmoveto
+(1.5) show
+509.689 30.122 m
+0 0.172 rmoveto
+(2.0) show
+272.442 14.419 m
+0 1.578 rmoveto
+(time \(s\)) show
+57.594 38.661 m
+0 0.172 rmoveto
+(-3) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 92.5714 m
+518.4 92.5714 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 92.5714 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 92.5714 o
+57.828 88.118 m
+(-2) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 141.943 m
+518.4 141.943 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 141.943 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 141.943 o
+57.734 137.568 m
+(-1) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 191.314 m
+518.4 191.314 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 191.314 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 191.314 o
+61.953 186.775 m
+0 0.172 rmoveto
+(0) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 240.686 m
+518.4 240.686 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 240.686 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 240.686 o
+62.781 236.311 m
+(1) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 290.057 m
+518.4 290.057 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 290.057 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 290.057 o
+62.438 285.604 m
+(2) show
+[1 3] 0 setdash
+gsave
+446.4 345.6 72 43.2 clipbox
+72 339.429 m
+518.4 339.429 l
+stroke
+grestore
+[] 0 setdash
+/o { gsave
+newpath
+translate
+0 0.5 m
+4 0.5 l
+closepath
+stroke
+grestore } bind def
+72 339.429 o
+/o { gsave
+newpath
+translate
+-4 0.5 m
+0 0.5 l
+closepath
+stroke
+grestore } bind def
+518.4 339.429 o
+62.25 334.89 m
+0 0.172 rmoveto
+(3) show
+61.625 384.425 m
+(4) show
+52.594 191.453 m
+gsave
+90 rotate
+0 1.578 rmoveto
+(volts \(V\)) show
+grestore
+1.000 setlinewidth
+2 setlinecap
+72 43.2 m
+518.4 43.2 l
+518.4 388.8 l
+72 388.8 l
+72 43.2 l
+stroke
+/BitstreamVeraSans-Roman findfont
+14.000 scalefont
+setfont
+232.848 395.712 m
+0 2.906 rmoveto
+(A noisy sine wave) show
+
+end
+showpage

Added: trunk/py4science/workbook/fig/noisy_sine.png
===================================================================
(Binary files differ)


Property changes on: trunk/py4science/workbook/fig/noisy_sine.png
___________________________________________________________________
Name: svn:mime-type
   + application/octet-stream

Added: trunk/py4science/workbook/files_etc.tex
===================================================================
--- trunk/py4science/workbook/files_etc.tex	                        (rev 0)
+++ trunk/py4science/workbook/files_etc.tex	2007-10-20 17:57:36 UTC (rev 3971)
@@ -0,0 +1,117 @@
+\section{Working with files, the web, arrays, etc\dots}
+\label{sec:working_with_files}
+
+This section is a general overview to show how easy it is to load
+and manipulate data on the file system and over the web using python's
+built in data structures and numpy arrays.  The goal is to exercise
+basic programming skills like building filename or web addresses to
+automate certain tasks like loading a series of data files or
+downloading a bunch of related files off the web, as well as to
+illustrate basic numpy and pylab skills.
+
+\subsection{Loading and saving ASCII data}
+\label{sec:ascii_data}
+
+The simplest file format is a plain text ASCII file of numbers.
+Although there are many better formats out there for saveing and
+loading data, this format is extremely common because it has the
+advantages of being human readable, and thus will survive the test of
+time as the \textit{en vogue} programming languages, analysis
+applications and data formats come and go, it is easy to parse, and it
+is supported by almost all languages and applications.  
+
+In this exercise we will create a data set of two arrays, the first
+one regularly sampled time \textit{t} from 0..2 seconds with 20~ms
+time step , and the second one an array \texttt{v} of sinusoidal
+voltages corrupted by some noise.  Let's assume the sine wave has
+amplitude 2~V, frequency 10~Hz, and zero mean Gaussian distrubuted
+white noise with standard deviation 0.5~V.  Your task is to write two
+scripts.
+
+The first script should create the vectors \texttt{t} and \texttt{v},
+plot the time series of \texttt{t} versus \texttt{v}, save them in a
+two dimensional numpy array \texttt{X}, and then dump the array
+\texttt{X} to a plain text ASCII file called
+\texttt{'noisy_sine.dat'}.  The file will look like (not identical
+because of the noise)
+
+\begin{verbatim}
+0.000000000000000000e+00 1.550947826934816025e-02
+2.000000000000000042e-02 2.493944587057004725e+00
+4.000000000000000083e-02 9.497694074551737975e-01
+5.999999999999999778e-02 -9.185779287524413750e-01
+8.000000000000000167e-02 -2.811127590689064704e+00
+... and so on
+\end{verbatim}
+
+Here is the exercise skeleton of the script to create and plot the
+data file
+
+\lstinputlisting[label=code:noisy_sine_skel,caption={IGNORED}]{skel/noise_sine_skel.py}
+
+and the graph will look something like Figure~\ref{fig:noisy_sine}
+
+\begin{center}%
+\begin{figure}
+\begin{centering}\includegraphics[width=4in]{fig/noise_sine}\par\end{centering}
+
+
+\caption{\label{fig:noisy_sine}A 10~Hz sine wave corrupted by noise}
+\end{figure}
+\par\end{center}
+
+The second part of this exercise is to write a script which loads data
+from the data file into an array \texttt{X}, extracts the columns into
+arrays \texttt{t} and \texttt{v}, and computes the RMS
+(root-mean-square) intensity of the signal using the \textt{load}
+command.
+
+
+\subsection{Loading and saving binary data}
+\label{sec:binary_data}
+
+ASCII is bloated and slow for working with large arrays, and so binary
+data should be used if performance is a consideration.  To save the
+array \texttt{X} in binary form, use the numpy \texttt{tostring} method
+
+\begin{lstlisting}
+# open the file for writing binary and write the binary string
+file('../data/binary_data.dat', 'wb').write(X.tostring())
+\end{lstlisting}
+
+\noindent This data can later be loaded into a numpy array using
+\texttt{fromstring}.  This method takes two arguments, a string and a
+data type (note that numarray users can use \texttt{fromfile} which is
+more efficient for importing data directly from a file).  
+
+\lstinputlisting{code/load_binary_data.py}
+
+\noindent Note that although Numpy and numarray use different
+typecode arguments (Numeric uses strings whereas numarray uses type
+objects), the matplotlib.numpy compatibility layer provides symbols
+which will work with either \rc{numpy} rc setting.
+
+\subsection{Processing several data files}
+\label{sec:multiple_files}
+
+Since python is a programming language \textit{par excellence}, it is
+easy to process data in batch.  When I started the gradual transition
+from a full time \matlab\ user to a full time python user, I began
+processing my data in python and saving the results to data files for
+plotting in \matlab.  When that became too cumbersome, I decided to
+write matplotlib so I could have all the functionality I needed in one
+environment.  Here is a brief example showing how to iterate over
+several data files, named \fname{basename001.dat, basename002.dat,
+  basename003.dat, ... basename100.dat} and plot all of the traces to
+the same axes.  I'll assume for this example that each file is a 1D
+ASCII array, which I can load with the \texttt{load} command.
+
+\begin{lstlisting}
+hold(True)  # set the hold state to be on
+for i in range(1,101):  #start at 1, end at 100
+    fname = 'basename%03d.dat'%i  # %03d pads the integers with zeros
+    x = load(fname)
+    plot(x)
+\end{lstlisting}
+
+


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3970] trunk/py4science/examples/noisy_sine.py

From: <jd...@us...> - 2007-10-20 17:56:57

Revision: 3970
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3970&view=rev
Author:   jdh2358
Date:     2007-10-20 10:56:55 -0700 (Sat, 20 Oct 2007)

Log Message:
-----------
added files workbook

Added Paths:
-----------
    trunk/py4science/examples/noisy_sine.py

Added: trunk/py4science/examples/noisy_sine.py
===================================================================
--- trunk/py4science/examples/noisy_sine.py	                        (rev 0)
+++ trunk/py4science/examples/noisy_sine.py	2007-10-20 17:56:55 UTC (rev 3970)
@@ -0,0 +1,25 @@
+from scipy import arange, sin, pi, randn, zeros
+import pylab as p
+
+a = 2       # 2 volt amplitude
+f = 10      # 10 Hz frequency
+sigma = 0.5 # 0.5 volt standard deviation noise
+
+# create the t and v and store them a 2D array X 
+t = arange(0.0, 2.0, 0.02)                # an evenly sampled time array
+v = a*sin(2*f*pi*t) + sigma*randn(len(t)) # a noisy sine wave
+X = zeros((len(t),2))                     # an empty output array
+X[:,0] = t                                # add t to the first column 
+X[:,1] = v                                # add s to the 2nd column
+p.save('data/noisy_sine.dat', X)            # save the output file as ASCII
+
+# plot the arrays t vs v and label the x-axis, y-axis and title
+# save the output figure as noisy_sine.png
+p.plot(t, v, 'b-')
+p.xlabel('time (s)')
+p.ylabel('volts (V)')
+p.title('A noisy sine wave')
+p.grid()
+p.savefig('noisy_sine.png', dpi=150)
+p.savefig('noisy_sine.eps')
+p.show()


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3969] trunk/matplotlib/lib/matplotlib/__init__.py

From: <ds...@us...> - 2007-10-19 15:41:30

Revision: 3969
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3969&view=rev
Author:   dsdale
Date:     2007-10-19 08:41:25 -0700 (Fri, 19 Oct 2007)

Log Message:
-----------
whitespace cleanup

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/__init__.py

Modified: trunk/matplotlib/lib/matplotlib/__init__.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-19 15:37:41 UTC (rev 3968)
+++ trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-19 15:41:25 UTC (rev 3969)
@@ -149,13 +149,10 @@
     # --verbose-silent or --verbose-helpful
     _commandLineVerbose = None
 
-
     for arg in sys.argv[1:]:
         if not arg.startswith('--verbose-'): continue
         _commandLineVerbose = arg[10:]
 
-
-
     def __init__(self):
         self.set_level('silent')
         self.fileo = sys.stdout
@@ -195,8 +192,6 @@
             return True
         return False
 
-
-
     def wrap(self, fmt, func, level='helpful', always=True):
         """
         return a callable function that wraps func and reports it
@@ -225,6 +220,7 @@
 
 verbose=Verbose()
 
+
 def checkdep_dvipng():
     try:
         stdin, stdout = os.popen4('dvipng -version')


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3968] trunk/matplotlib/lib/matplotlib

From: <ds...@us...> - 2007-10-19 15:37:44

Revision: 3968
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3968&view=rev
Author:   dsdale
Date:     2007-10-19 08:37:41 -0700 (Fri, 19 Oct 2007)

Log Message:
-----------
changed dependency check for ghostscript, which was failing to identify svn 
versions

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/__init__.py
    trunk/matplotlib/lib/matplotlib/config/checkdep.py

Modified: trunk/matplotlib/lib/matplotlib/__init__.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-19 14:43:21 UTC (rev 3967)
+++ trunk/matplotlib/lib/matplotlib/__init__.py	2007-10-19 15:37:41 UTC (rev 3968)
@@ -55,7 +55,7 @@
 """
 from __future__ import generators
 
-NEWCONFIG = False
+NEWCONFIG = True
 
 __version__  = '0.90.1'
 __revision__ = '$Revision$'
@@ -243,7 +243,7 @@
             command = 'gs -v'
         stdin, stdout = os.popen4(command)
         line = stdout.readlines()[0]
-        v = line.split()[2]
+        v = line.split()[-2]
         vtest = '.'.join(v.split('.')[:2]) # deal with version numbers like '7.07.1'
         float(vtest)
         return vtest

Modified: trunk/matplotlib/lib/matplotlib/config/checkdep.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/config/checkdep.py	2007-10-19 14:43:21 UTC (rev 3967)
+++ trunk/matplotlib/lib/matplotlib/config/checkdep.py	2007-10-19 15:37:41 UTC (rev 3968)
@@ -1,4 +1,7 @@
-import os, re, sys
+import os
+import re
+import sys
+import warnings
 import distutils.version as version
 
 def dvipng():
@@ -19,7 +22,7 @@
             command = 'gs -v'
         stdin, stdout = os.popen4(command)
         line = stdout.readlines()[0]
-        v = line.split()[2]
+        v = line.split()[-2]
         vtest = '.'.join(v.split('.')[:2]) # deal with version numbers like '7.07.1'
         float(vtest)
         return vtest
@@ -130,4 +133,4 @@
                        'unless ghostscript-%s or later is '
                        'installed on your system') % gs_req)
 
-    return flag
\ No newline at end of file
+    return flag


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3967] trunk/matplotlib

From: <ds...@us...> - 2007-10-19 14:43:50

Revision: 3967
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3967&view=rev
Author:   dsdale
Date:     2007-10-19 07:43:21 -0700 (Fri, 19 Oct 2007)

Log Message:
-----------
removed a gsave/grestore pair surrounding _draw_ps

Modified Paths:
--------------
    trunk/matplotlib/CHANGELOG
    trunk/matplotlib/lib/matplotlib/backends/backend_ps.py

Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG	2007-10-19 14:23:48 UTC (rev 3966)
+++ trunk/matplotlib/CHANGELOG	2007-10-19 14:43:21 UTC (rev 3967)
@@ -1,3 +1,8 @@
+2007-10-19 Removed a gsave/grestore pair surrounding _draw_ps, which
+           was causing a loss graphics state info (see "EPS output
+           problem - scatter & edgecolors" on mpl-dev, 2007-10-29)
+           - DSD
+
 2007-10-15 Fixed a bug in patches.Ellipse that was broken for
            aspect='auto'.  Scale free ellipses now work properly for
            equal and auto on Agg and PS, and they fall back on a

Modified: trunk/matplotlib/lib/matplotlib/backends/backend_ps.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/backends/backend_ps.py	2007-10-19 14:23:48 UTC (rev 3966)
+++ trunk/matplotlib/lib/matplotlib/backends/backend_ps.py	2007-10-19 14:43:21 UTC (rev 3967)
@@ -915,7 +915,6 @@
         """
         # local variable eliminates all repeated attribute lookups
         write = self._pswriter.write
-        write('gsave\n')
 
         if debugPS and command:
             write("% "+command+"\n")
@@ -949,7 +948,6 @@
             write("stroke\n")
         if cliprect:
             write("grestore\n")
-        write('grestore\n')            
 
     def push_gc(self, gc, store=1):
         """


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3966] trunk/matplotlib/lib/matplotlib

From: <jd...@us...> - 2007-10-19 14:23:51

Revision: 3966
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3966&view=rev
Author:   jdh2358
Date:     2007-10-19 07:23:48 -0700 (Fri, 19 Oct 2007)

Log Message:
-----------
fixed a verbose report bug in patches

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/collections.py
    trunk/matplotlib/lib/matplotlib/patches.py

Modified: trunk/matplotlib/lib/matplotlib/collections.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/collections.py	2007-10-18 18:11:59 UTC (rev 3965)
+++ trunk/matplotlib/lib/matplotlib/collections.py	2007-10-19 14:23:48 UTC (rev 3966)
@@ -217,6 +217,7 @@
         ACCEPTS: float or sequence of floats
         """
         self._linewidths = self._get_value(lw)
+
     def set_linewidths(self, lw):
         self.set_linewidth(lw)
 
@@ -256,6 +257,7 @@
             self._linewidths = (0.0,)
         else:
             self._edgecolors = _colors.colorConverter.to_rgba_list(c)
+
     def set_edgecolors(self, c):
         self.set_edgecolor(c)
 
@@ -721,6 +723,7 @@
         return len(ind)>0,dict(ind=ind)
 
     def set_pickradius(self,pickradius): self.pickradius = 5
+
     def get_pickradius(self): return self.pickradius
 
     def get_transoffset(self):

Modified: trunk/matplotlib/lib/matplotlib/patches.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/patches.py	2007-10-18 18:11:59 UTC (rev 3965)
+++ trunk/matplotlib/lib/matplotlib/patches.py	2007-10-19 14:23:48 UTC (rev 3966)
@@ -849,7 +849,7 @@
 
 
         if not hasattr(renderer, 'draw_path'):
-            verbose.report('patches.Ellipse renderer does not support path drawing; falling back on vertex approximation for nonlinear transformation')
+            mpl.verbose.report('patches.Ellipse renderer does not support path drawing; falling back on vertex approximation for nonlinear transformation')
             renderer.draw_polygon(gc, rgbFace, self.get_verts())
             return
         


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3965] branches/transforms

From: <md...@us...> - 2007-10-18 18:12:03

Revision: 3965
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3965&view=rev
Author:   mdboom
Date:     2007-10-18 11:11:59 -0700 (Thu, 18 Oct 2007)

Log Message:
-----------
First pass at working PDF backend.

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/backends/backend_pdf.py
    branches/transforms/lib/matplotlib/backends/backend_ps.py
    branches/transforms/lib/matplotlib/projections/polar.py
    branches/transforms/lib/matplotlib/transforms.py
    branches/transforms/src/_backend_agg.cpp

Modified: branches/transforms/lib/matplotlib/backends/backend_pdf.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_pdf.py	2007-10-18 18:07:06 UTC (rev 3964)
+++ branches/transforms/lib/matplotlib/backends/backend_pdf.py	2007-10-18 18:11:59 UTC (rev 3965)
@@ -33,7 +33,10 @@
     LOAD_NO_HINTING, KERNING_UNFITTED
 from matplotlib.mathtext import MathTextParser
 from matplotlib.transforms import Bbox
+from matplotlib.path import Path
 from matplotlib import ttconv
+# MGDTODO: Move this stuff
+from matplotlib.backends._backend_agg import get_path_extents
 
 # Overview
 #
@@ -90,22 +93,26 @@
     """Make one string from sequence of strings, with whitespace
     in between. The whitespace is chosen to form lines of at most
     linelen characters, if possible."""
-
-    s, strings = [strings[0]], strings[1:]
-    while strings:
-        if len(s[-1]) + len(strings[0]) < linelen:
-            s[-1] += ' ' + strings[0]
+    currpos = 0
+    lasti = 0
+    result = []
+    for i, s in enumerate(strings):
+        length = len(s)
+        if currpos + length < linelen:
+            currpos += length + 1
         else:
-            s.append(strings[0])
-        strings = strings[1:]
-    return '\n'.join(s)
+            result.append(' '.join(strings[lasti:i]))
+            lasti = i
+            currpos = length
+    result.append(' '.join(strings[lasti:]))
+    return '\n'.join(result)
 
 
 def pdfRepr(obj):
     """Map Python objects to PDF syntax."""
 
     # Some objects defined later have their own pdfRepr method.
-    if 'pdfRepr' in dir(obj):
+    if hasattr(obj, 'pdfRepr'):
         return obj.pdfRepr()
 
     # Floats. PDF does not have exponential notation (1.0e-10) so we
@@ -164,6 +171,13 @@
         else: r += "-%02d'%02d'" % (z//3600, z%3600)
         return pdfRepr(r)
 
+    # A bounding box
+    elif isinstance(obj, Bbox):
+        r = ["["]
+        r.extend([pdfRepr(val) for val in obj.lbrt])
+        r.append("]")
+        return fill(r)
+    
     else:
         raise TypeError, \
             "Don't know a PDF representation for %s objects." \
@@ -379,7 +393,6 @@
 
         self.markers = {}
         self.two_byte_charprocs = {}
-        self.nextMarker = 1
 
         # The PDF spec recommends to include every procset
         procsets = [ Name(x)
@@ -409,8 +422,8 @@
                                for val in self.alphaStates.values()]))
         self.writeHatches()
         xobjects = dict(self.images.values())
-        for name, value in self.markers.items():
-            xobjects[name] = value[0]
+        for tup in self.markers.values():
+            xobjects[tup[0]] = tup[1]
         for name, value in self.two_byte_charprocs.items():
             xobjects[name] = value
         self.writeObject(self.XObjectObject, xobjects)
@@ -1009,71 +1022,64 @@
 
             img.flipud_out()
 
-    def markerObject(self, path, fillp, lw):
+    def markerObject(self, path, trans, fillp, lw):
         """Return name of a marker XObject representing the given path."""
-
-        name = Name('M%d' % self.nextMarker)
-        ob = self.reserveObject('marker %d' % self.nextMarker)
-        self.nextMarker += 1
-        self.markers[name] = (ob, path, fillp, lw)
+        key = (path, trans)
+        result = self.markers.get(key)
+        if result is None:
+            name = Name('M%d' % len(self.markers))
+            ob = self.reserveObject('marker %d' % len(self.markers))
+            self.markers[key] = (name, ob, path, trans, fillp, lw)
+        else:
+            name = result[0]
         return name
-
+    
     def writeMarkers(self):
-        for name, tuple in self.markers.items():
-            object, path, fillp, lw = tuple
+        for tup in self.markers.values():
+            name, object, path, trans, fillp, lw = tup
+            a, b, c, d = get_path_extents(path, trans)
+            bbox = Bbox.from_lbrt(*get_path_extents(path, trans))
+            bbox = bbox.padded(lw * 0.5)
             self.beginStream(
                 object.id, None,
                 {'Type': Name('XObject'), 'Subtype': Name('Form'),
-                 'BBox': self.pathBbox(path, lw) })
-            self.writePath(path, fillp)
+                 'BBox': bbox })
+            self.writePath(path, trans)
+            if fillp:
+                self.output(Op.fill_stroke)
+            else:
+                self.output(Op.stroke)
             self.endStream()
 
     #@staticmethod
-    def pathBbox(path, lw):
-        path.rewind(0)
-        x, y = [], []
-        while True:
-            code, xp, yp = path.vertex()
-            if code & agg.path_cmd_mask in \
-                    (agg.path_cmd_move_to, agg.path_cmd_line_to):
-                x.append(xp)
-                y.append(yp)
-            elif code == agg.path_cmd_stop:
-                break
-        return min(x)-lw, min(y)-lw, max(x)+lw, max(y)+lw
-    pathBbox = staticmethod(pathBbox)
-
-    #@staticmethod
-    def pathOperations(path):
-        path.rewind(0)
-        result = []
-        while True:
-            code, x, y = path.vertex()
-            code = code & agg.path_cmd_mask
-            if code == agg.path_cmd_stop:
-                break
-            elif code == agg.path_cmd_move_to:
-                result += (x, y, Op.moveto)
-            elif code == agg.path_cmd_line_to:
-                result += (x, y, Op.lineto)
-            elif code == agg.path_cmd_curve3:
-                pass # TODO
-            elif code == agg.path_cmd_curve4:
-                pass # TODO
-            elif code == agg.path_cmd_end_poly:
-                result += (Op.closepath,)
-            else:
-                print >>sys.stderr, "pathOperations", code, xp, yp
-        return result
+    def pathOperations(path, transform):
+        tpath = transform.transform_path(path)
+        
+        cmds = []
+        for points, code in tpath.iter_segments():
+            if code == Path.MOVETO:
+                cmds.extend(points)
+                cmds.append(Op.moveto)
+            elif code == Path.LINETO:
+                cmds.extend(points)
+                cmds.append(Op.lineto)
+            elif code == Path.CURVE3:
+                cmds.extend([points[0], points[1],
+                             points[0], points[1],
+                             points[2], points[3],
+                             Op.curveto])
+            elif code == Path.CURVE4:
+                cmds.extend(points)
+                cmds.append(Op.curveto)
+            elif code == Path.CLOSEPOLY:
+                cmds.append(Op.closepath)
+        return cmds
     pathOperations = staticmethod(pathOperations)
-
-    def writePath(self, path, fillp):
-        self.output(*self.pathOperations(path))
-        if fillp:
-            self.output(Op.fill_stroke)
-        else:
-            self.output(Op.stroke)
-
+            
+    def writePath(self, path, transform):
+        cmds = self.pathOperations(path, transform)
+        self.output(*cmds)
+        
     def reserveObject(self, name=''):
         """Reserve an ID for an indirect object.
         The name is used for debugging in case we forget to print out
@@ -1177,59 +1183,6 @@
                 stat_key, (realpath, Set()))
             used_characters[1].update(set)
 
-    def draw_arc(self, gcEdge, rgbFace, x, y, width, height,
-                 angle1, angle2, rotation):
-        """
-        Draw an arc using GraphicsContext instance gcEdge, centered at x,y,
-        with width and height and angles from 0.0 to 360.0
-        0 degrees is at 3-o'clock, rotated by `rotation` degrees
-        positive angles are anti-clockwise
-
-        If the color rgbFace is not None, fill the arc with it.
-        """
-        # source: agg_bezier_arc.cpp in agg23
-
-        def arc_to_bezier(cx, cy, rx, ry, angle1, sweep, rotation):
-            halfsweep = sweep / 2.0
-            x0, y0 = cos(halfsweep), sin(halfsweep)
-            tx = (1.0 - x0) * 4.0/3.0;
-            ty = y0 - tx * x0 / y0;
-            px =  x0, x0+tx, x0+tx, x0
-            py = -y0,   -ty,    ty, y0
-            sn, cs = sin(angle1 + halfsweep), cos(angle1 + halfsweep)
-            result = [ (rx * (pxi * cs - pyi * sn),
-                        ry * (pxi * sn + pyi * cs))
-                       for pxi, pyi in zip(px, py) ]
-            result = [ (cx + cos(rotation)*x - sin(rotation)*y,
-                        cy + sin(rotation)*x + cos(rotation)*y)
-                       for x, y in result ]
-            return reduce(lambda x, y: x + y, result)
-
-        epsilon = 0.01
-        angle1 *= pi/180.0
-        angle2 *= pi/180.0
-        rotation *= pi/180.0
-        sweep = angle2 - angle1
-        angle1 = angle1 % (2*pi)
-        sweep = min(max(-2*pi, sweep), 2*pi)
-
-        if sweep < 0.0:
-            sweep, angle1, angle2 = -sweep, angle2, angle1
-        bp = [ pi/2.0 * i
-               for i in range(4)
-               if pi/2.0 * i < sweep-epsilon ]
-        bp.append(sweep)
-        subarcs = [ arc_to_bezier(x, y, width/2.0, height/2.0,
-                                  bp[i], bp[i+1]-bp[i], rotation)
-                    for i in range(len(bp)-1) ]
-
-        self.check_gc(gcEdge, rgbFace)
-        self.file.output(subarcs[0][0], subarcs[0][1], Op.moveto)
-        for arc in subarcs:
-            self.file.output(*(arc[2:] + (Op.curveto,)))
-
-        self.file.output(self.gc.close_and_paint())
-
     def get_image_magnification(self):
         return self.image_magnification
 
@@ -1246,82 +1199,29 @@
         self.file.output(Op.gsave, w, 0, 0, h, x, y, Op.concat_matrix,
                          imob, Op.use_xobject, Op.grestore)
 
-    def draw_line(self, gc, x1, y1, x2, y2):
-        if npy.isnan(x1) or npy.isnan(x2) or npy.isnan(y1) or npy.isnan(y2):
-            return
-        self.check_gc(gc)
-        self.file.output(x1, y1, Op.moveto,
-                         x2, y2, Op.lineto, self.gc.paint())
-
-    def draw_lines(self, gc, x, y, transform=None):
-        self.check_gc(gc)
-        if transform is not None:
-            x, y = transform.seq_x_y(x, y)
-        nan_at = npy.isnan(x) | npy.isnan(y)
-        next_op = Op.moveto
-        for i in range(len(x)):
-            if nan_at[i]:
-                next_op = Op.moveto
-            else:
-                self.file.output(x[i], y[i], next_op)
-                next_op = Op.lineto
+    def draw_path(self, gc, path, transform, rgbFace=None):
+        self.check_gc(gc, rgbFace)
+        stream = self.file.writePath(path, transform)
         self.file.output(self.gc.paint())
 
-    def draw_point(self, gc, x, y):
-        print >>sys.stderr, "draw_point called"
-
-        self.check_gc(gc, gc._rgb)
-        self.file.output(x, y, 1, 1,
-                         Op.rectangle, Op.fill_stroke)
-
-    def draw_polygon(self, gcEdge, rgbFace, points):
-        # Optimization for axis-aligned rectangles
-        if len(points) == 4:
-            if points[0][0] == points[1][0] and points[1][1] == points[2][1] and \
-               points[2][0] == points[3][0] and points[3][1] == points[0][1]:
-                self.draw_rectangle(gcEdge, rgbFace,
-                                    min(points[0][0], points[2][0]),
-                                    min(points[1][1], points[3][1]),
-                                    abs(points[2][0] - points[0][0]),
-                                    abs(points[3][1] - points[1][1]))
-                return
-            elif points[0][1] == points[1][1] and points[1][0] == points[2][0] and \
-                 points[2][1] == points[3][1] and points[3][0] == points[0][0]:
-                self.draw_rectangle(gcEdge, rgbFace,
-                                    min(points[1][0], points[3][0]),
-                                    min(points[2][1], points[0][1]),
-                                    abs(points[1][0] - points[3][0]),
-                                    abs(points[2][1] - points[0][1]))
-                return
-
-        self.check_gc(gcEdge, rgbFace)
-        self.file.output(points[0][0], points[0][1], Op.moveto)
-        for x,y in points[1:]:
-            self.file.output(x, y, Op.lineto)
-        self.file.output(self.gc.close_and_paint())
-
-    def draw_rectangle(self, gcEdge, rgbFace, x, y, width, height):
-        self.check_gc(gcEdge, rgbFace)
-        self.file.output(x, y, width, height, Op.rectangle)
-        self.file.output(self.gc.paint())
-
-    def draw_markers(self, gc, path, rgbFace, x, y, trans):
+    def draw_markers(self, gc, marker_path, marker_trans, path, trans, rgbFace=None):
         self.check_gc(gc, rgbFace)
         fillp = rgbFace is not None
-        marker = self.file.markerObject(path, fillp, self.gc._linewidth)
-        x, y = trans.numerix_x_y(npy.asarray(x), npy.asarray(y))
-        nan_at = npy.isnan(x) | npy.isnan(y)
 
-        self.file.output(Op.gsave)
-        ox, oy = 0, 0
-        for i in range(len(x)):
-            if nan_at[i]: continue
-            dx, dy, ox, oy = x[i]-ox, y[i]-oy, x[i], y[i]
-            self.file.output(1, 0, 0, 1, dx, dy,
-                             Op.concat_matrix,
-                             marker, Op.use_xobject)
-        self.file.output(Op.grestore)
+        output = self.file.output
+        marker = self.file.markerObject(
+            marker_path, marker_trans, fillp, self.gc._linewidth)
+        tpath = trans.transform_path(path)
 
+        output(Op.gsave)
+        lastx, lasty = 0, 0
+        for x, y in tpath.vertices:
+            dx, dy = x - lastx, y - lasty
+            output(1, 0, 0, 1, dx, dy, Op.concat_matrix,
+                   marker, Op.use_xobject)
+            lastx, lasty = x, y
+        output(Op.grestore)
+        
     def _setup_textpos(self, x, y, angle, oldx=0, oldy=0, oldangle=0):
         if angle == oldangle == 0:
             self.file.output(x - oldx, y - oldy, Op.textpos)
@@ -1735,7 +1635,7 @@
 
     def hatch_cmd(self, hatch):
         if not hatch:
-            if self._fillcolor:
+            if self._fillcolor is not None:
                 return self.fillcolor_cmd(self._fillcolor)
             else:
                 return [Name('DeviceRGB'), Op.setcolorspace_nonstroke]
@@ -1757,7 +1657,7 @@
         if rgb[0] == rgb[1] == rgb[2]:
             return [rgb[0], Op.setgray_stroke]
         else:
-            return list(rgb) + [Op.setrgb_stroke]
+            return list(rgb[:3]) + [Op.setrgb_stroke]
 
     def fillcolor_cmd(self, rgb):
         if rgb is None or rcParams['pdf.inheritcolor']:
@@ -1765,7 +1665,7 @@
         elif rgb[0] == rgb[1] == rgb[2]:
             return [rgb[0], Op.setgray_nonstroke]
         else:
-            return list(rgb) + [Op.setrgb_nonstroke]
+            return list(rgb[:3]) + [Op.setrgb_nonstroke]
 
     def push(self):
         parent = GraphicsContextPdf(self.file)
@@ -1791,11 +1691,12 @@
         if (self._cliprect, self._clippath) != (cliprect, clippath):
             cmds.extend(self.push())
             if self._cliprect != cliprect:
-                cmds.extend([t for t in cliprect] + 
-                            [Op.rectangle, Op.clip, Op.endpath])
+                cmds.extend([cliprect, Op.rectangle, Op.clip, Op.endpath])
             if self._clippath != clippath:
-                cmds.extend(PdfFile.pathOperations(clippath) +
-                            [Op.clip, Op.endpath])
+                cmds.extend(
+                    PdfFile.pathOperations(
+                        *clippath.get_transformed_path_and_affine()) +
+                    [Op.clip, Op.endpath])
         return cmds
 
     commands = (
@@ -1821,7 +1722,11 @@
         for params, cmd in self.commands:
             ours = [ getattr(self, p) for p in params ] 
             theirs = [ getattr(other, p) for p in params ]
-            if ours != theirs:
+            try:
+                different = ours != theirs
+            except ValueError:
+                different = ours.shape != theirs.shape or npy.any(ours != theirs)
+            if ours is not theirs:
                 cmds.extend(cmd(self, *theirs))
                 for p in params:
                     setattr(self, p, getattr(other, p))

Modified: branches/transforms/lib/matplotlib/backends/backend_ps.py
===================================================================
--- branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-18 18:07:06 UTC (rev 3964)
+++ branches/transforms/lib/matplotlib/backends/backend_ps.py	2007-10-18 18:11:59 UTC (rev 3965)
@@ -1433,14 +1433,4 @@
       clip
       newpath
     } bind def""",
-    """/unitcircle {
-    newpath
--1. 0. moveto
--1.0 0.552284749831 -0.552284749831 1.0 0.0 1.0 curveto
-0.552284749831 1.0 1.0 0.552284749831 1.0 0.0 curveto
-1.0 -0.552284749831 0.552284749831 -1.0 0.0 -1.0 curveto
--0.552284749831 -1.0 -1.0 -0.552284749831 -1.0 0.0 curveto
-closepath
-    } bind def""",
-    
 ]

Modified: branches/transforms/lib/matplotlib/projections/polar.py
===================================================================
--- branches/transforms/lib/matplotlib/projections/polar.py	2007-10-18 18:07:06 UTC (rev 3964)
+++ branches/transforms/lib/matplotlib/projections/polar.py	2007-10-18 18:11:59 UTC (rev 3965)
@@ -41,13 +41,13 @@
             self._resolution = resolution
 
         def transform(self, tr):
-            xy = npy.zeros(tr.shape, npy.float_)
-            t = tr[:, 0:1]
-            r = tr[:, 1:2]
-            x = xy[:, 0:1]
-            y = xy[:, 1:2]
-            x += r * npy.cos(t)
-            y += r * npy.sin(t)
+            xy   = npy.zeros(tr.shape, npy.float_)
+            t    = tr[:, 0:1]
+            r    = tr[:, 1:2]
+            x    = xy[:, 0:1]
+            y    = xy[:, 1:2]
+            x[:] = r * npy.cos(t)
+            y[:] = r * npy.sin(t)
             return xy
         transform.__doc__ = Transform.transform.__doc__
 

Modified: branches/transforms/lib/matplotlib/transforms.py
===================================================================
--- branches/transforms/lib/matplotlib/transforms.py	2007-10-18 18:07:06 UTC (rev 3964)
+++ branches/transforms/lib/matplotlib/transforms.py	2007-10-18 18:11:59 UTC (rev 3965)
@@ -490,6 +490,14 @@
         a = npy.array([[-deltaw, -deltah], [deltaw, deltah]])
         return Bbox(self._points + a)
 
+    def padded(self, p):
+        """
+        Return a new Bbox that is padded on all four sides by the
+        given value.
+        """
+        points = self._points
+        return Bbox(points + [[-p, -p], [p, p]])
+    
     def translated(self, tx, ty):
         """
         Return a copy of the Bbox, translated by tx and ty.

Modified: branches/transforms/src/_backend_agg.cpp
===================================================================
--- branches/transforms/src/_backend_agg.cpp	2007-10-18 18:07:06 UTC (rev 3964)
+++ branches/transforms/src/_backend_agg.cpp	2007-10-18 18:11:59 UTC (rev 3965)
@@ -1573,12 +1573,12 @@
   curved_path.rewind(0);
 
   while ((code = curved_path.vertex(&x, &y)) != agg::path_cmd_stop) {
-    if (code & agg::path_cmd_end_poly == agg::path_cmd_end_poly)
-      continue;
     if (x < *x0) *x0 = x;
     if (y < *y0) *y0 = y;
     if (x > *x1) *x1 = x;
     if (y > *y1) *y1 = y;
+    if ((code & agg::path_cmd_end_poly) == agg::path_cmd_end_poly)
+      continue;
   }
 }
 


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3964] trunk/matplotlib/lib/matplotlib/backends/ backend_pdf.py

From: <md...@us...> - 2007-10-18 18:07:26

Revision: 3964
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3964&view=rev
Author:   mdboom
Date:     2007-10-18 11:07:06 -0700 (Thu, 18 Oct 2007)

Log Message:
-----------
Faster version of fill() for PDF writing

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py

Modified: trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py	2007-10-18 17:40:30 UTC (rev 3963)
+++ trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py	2007-10-18 18:07:06 UTC (rev 3964)
@@ -90,15 +90,19 @@
     """Make one string from sequence of strings, with whitespace
     in between. The whitespace is chosen to form lines of at most
     linelen characters, if possible."""
-
-    s, strings = [strings[0]], strings[1:]
-    while strings:
-        if len(s[-1]) + len(strings[0]) < linelen:
-            s[-1] += ' ' + strings[0]
+    currpos = 0
+    lasti = 0
+    result = []
+    for i, s in enumerate(strings):
+        length = len(s)
+        if currpos + length < linelen:
+            currpos += length + 1
         else:
-            s.append(strings[0])
-        strings = strings[1:]
-    return '\n'.join(s)
+            result.append(' '.join(strings[lasti:i]))
+            lasti = i
+            currpos = length
+    result.append(' '.join(strings[lasti:]))
+    return '\n'.join(result)
 
 
 def pdfRepr(obj):


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3963] trunk/matplotlib/lib/matplotlib/backends/ backend_pdf.py

From: <md...@us...> - 2007-10-18 17:40:31

Revision: 3963
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3963&view=rev
Author:   mdboom
Date:     2007-10-18 10:40:30 -0700 (Thu, 18 Oct 2007)

Log Message:
-----------
Major speedup in PDF backend by using hasattr() rather than 'in dir()'

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py

Modified: trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py	2007-10-18 15:06:49 UTC (rev 3962)
+++ trunk/matplotlib/lib/matplotlib/backends/backend_pdf.py	2007-10-18 17:40:30 UTC (rev 3963)
@@ -105,7 +105,7 @@
     """Map Python objects to PDF syntax."""
 
     # Some objects defined later have their own pdfRepr method.
-    if 'pdfRepr' in dir(obj):
+    if hasattr(obj, 'pdfRepr'):
         return obj.pdfRepr()
 
     # Floats. PDF does not have exponential notation (1.0e-10) so we


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

SF.net SVN: matplotlib: [3962] branches/transforms

From: <md...@us...> - 2007-10-18 15:06:51

Revision: 3962
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3962&view=rev
Author:   mdboom
Date:     2007-10-18 08:06:49 -0700 (Thu, 18 Oct 2007)

Log Message:
-----------
Merged revisions 3956-3961 via svnmerge from 
http://matplotlib.svn.sf.net/svnroot/matplotlib/trunk/matplotlib

........
  r3961 | jdh2358 | 2007-10-18 11:02:13 -0400 (Thu, 18 Oct 2007) | 3 lines
  
  Fixed collection.set_facecolor to respect alpha
........

Modified Paths:
--------------
    branches/transforms/lib/matplotlib/collections.py
    branches/transforms/lib/matplotlib/mlab.py

Property Changed:
----------------
    branches/transforms/


Property changes on: branches/transforms
___________________________________________________________________
Name: svnmerge-integrated
   - /trunk/matplotlib:1-3955
   + /trunk/matplotlib:1-3961

Modified: branches/transforms/lib/matplotlib/collections.py
===================================================================
--- branches/transforms/lib/matplotlib/collections.py	2007-10-18 15:02:13 UTC (rev 3961)
+++ branches/transforms/lib/matplotlib/collections.py	2007-10-18 15:06:49 UTC (rev 3962)
@@ -311,7 +311,8 @@
 
         ACCEPTS: matplotlib color arg or sequence of rgba tuples
         """
-        self._facecolors = _colors.colorConverter.to_rgba_list(c)
+        self._facecolors = _colors.colorConverter.to_rgba_list(c, self._alpha)
+
     set_facecolors = set_facecolor
 
     def set_edgecolor(self, c):

Modified: branches/transforms/lib/matplotlib/mlab.py
===================================================================
--- branches/transforms/lib/matplotlib/mlab.py	2007-10-18 15:02:13 UTC (rev 3961)
+++ branches/transforms/lib/matplotlib/mlab.py	2007-10-18 15:06:49 UTC (rev 3962)
@@ -1342,9 +1342,15 @@
     process_skiprows(reader)
 
 
+    def myfloat(x):
+        if x==missing:
+            return npy.nan
+        else:
+            return float(x)
+
     def get_func(item, func):
         # promote functions in this order
-        funcmap = {int:float, float:dateutil.parser.parse, dateutil.parser.parse:str}
+        funcmap = {int:myfloat, myfloat:dateutil.parser.parse, dateutil.parser.parse:str}
         try: func(item)
         except:
             if func==str:


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Flat | Threaded

<< < 1 .. 199 200 201 202 203 .. 219 > >> (Page 201 of 219)