[yt-svn] commit/yt: 4 new changesets

commits-noreply at bitbucket.org commits-noreply at bitbucket.org
Mon Aug 18 14:34:04 PDT 2014


4 new commits in yt:

https://bitbucket.org/yt_analysis/yt/commits/09e4a6cd0659/
Changeset:   09e4a6cd0659
Branch:      yt
User:        ngoldbaum
Date:        2014-08-15 20:39:41
Summary:     Fixing issues with TransferFunctions that are not log-scaled.
Affected #:  2 files

diff -r dee8cd4e2482c51ffeada18775df114dc3797073 -r 09e4a6cd0659e71c3b6b6884d35758c74e93442c yt/visualization/volume_rendering/transfer_function_helper.py
--- a/yt/visualization/volume_rendering/transfer_function_helper.py
+++ b/yt/visualization/volume_rendering/transfer_function_helper.py
@@ -154,7 +154,9 @@
             xmi, xma = np.log10(self.bounds[0]), np.log10(self.bounds[1])
         else:
             xfunc = np.linspace
-            xmi, xma = self.bounds
+            # Need to strip units off of the bounds to avoid a recursion error
+            # in matplotlib 1.3.1
+            xmi, xma = [np.float64(b) for b in self.bounds]
 
         x = xfunc(xmi, xma, tf.nbins)
         y = tf.funcs[3].y
@@ -166,7 +168,7 @@
         canvas = FigureCanvasAgg(fig)
         ax = fig.add_axes([0.2, 0.2, 0.75, 0.75])
         ax.bar(x, tf.funcs[3].y, w, edgecolor=[0.0, 0.0, 0.0, 0.0],
-               log=True, color=colors, bottom=[0])
+               log=self.log, color=colors, bottom=[0])
 
         if profile_field is not None:
             try:
@@ -177,10 +179,12 @@
             if profile_field not in prof.keys():
                 prof.add_fields([profile_field], fractional=False,
                                 weight=profile_weight)
-            ax.plot(prof[self.field], prof[profile_field]*tf.funcs[3].y.max() /
-                    prof[profile_field].max(), color='w', linewidth=3)
-            ax.plot(prof[self.field], prof[profile_field]*tf.funcs[3].y.max() /
-                    prof[profile_field].max(), color='k')
+            # Strip units, if any, for matplotlib 1.3.1
+            xplot = np.array(prof[self.field])
+            yplot = np.array(prof[profile_field]*tf.funcs[3].y.max() /
+                             prof[profile_field].max())
+            ax.plot(xplot, yplot, color='w', linewidth=3)
+            ax.plot(xplot, yplot, color='k')
 
         ax.set_xscale({True: 'log', False: 'linear'}[self.log])
         ax.set_xlim(x.min(), x.max())
@@ -200,7 +204,7 @@
 
     def setup_profile(self, profile_field=None, profile_weight=None):
         if profile_field is None:
-            profile_field = 'CellVolume'
+            profile_field = 'cell_volume'
         prof = BinnedProfile1D(self.ds.all_data(), 128, self.field,
                                self.bounds[0], self.bounds[1],
                                log_space=self.log,

diff -r dee8cd4e2482c51ffeada18775df114dc3797073 -r 09e4a6cd0659e71c3b6b6884d35758c74e93442c yt/visualization/volume_rendering/transfer_functions.py
--- a/yt/visualization/volume_rendering/transfer_functions.py
+++ b/yt/visualization/volume_rendering/transfer_functions.py
@@ -48,6 +48,8 @@
     def __init__(self, x_bounds, nbins=256):
         self.pass_through = 0
         self.nbins = nbins
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.x = np.linspace(x_bounds[0], x_bounds[1], nbins).astype('float64')
         self.y = np.zeros(nbins, dtype='float64')
@@ -353,6 +355,8 @@
     """
     def __init__(self, x_bounds, nbins=256, grey_opacity = False):
         MultiVariateTransferFunction.__init__(self)
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.nbins = nbins
         # This is all compatibility and convenience.
@@ -800,6 +804,8 @@
         if n_fields > 3:
             raise NotImplementedError
         MultiVariateTransferFunction.__init__(self)
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.nbins = 2
         self.linear_mapping = TransferFunction(x_bounds, 2)


https://bitbucket.org/yt_analysis/yt/commits/271f46ea8dac/
Changeset:   271f46ea8dac
Branch:      yt
User:        ngoldbaum
Date:        2014-08-15 23:06:01
Summary:     Fixing the volume rendering tests.
Affected #:  1 file

diff -r 09e4a6cd0659e71c3b6b6884d35758c74e93442c -r 271f46ea8dac7552e34507544b4c75711def4208 yt/visualization/volume_rendering/transfer_functions.py
--- a/yt/visualization/volume_rendering/transfer_functions.py
+++ b/yt/visualization/volume_rendering/transfer_functions.py
@@ -637,6 +637,7 @@
         >>> tf = ColorTransferFunction( (-10.0, -5.0) )
         >>> tf.sample_colormap(-7.0, 0.01, colormap='algae')
         """
+        v = np.float64(v)
         if col_bounds is None:
             rel = (v - self.x_bounds[0])/(self.x_bounds[1] - self.x_bounds[0])
         else:
@@ -684,7 +685,8 @@
         >>> tf.map_to_colormap(-6.0, -5.0, scale=10.0, colormap='algae',
         ...                    scale_func = linramp)
         """
-
+        mi = np.float64(mi)
+        ma = np.float64(ma)
         rel0 = int(self.nbins*(mi - self.x_bounds[0])/(self.x_bounds[1] -
                                                        self.x_bounds[0]))
         rel1 = int(self.nbins*(ma - self.x_bounds[0])/(self.x_bounds[1] -


https://bitbucket.org/yt_analysis/yt/commits/3aec01794a71/
Changeset:   3aec01794a71
Branch:      yt
User:        ngoldbaum
Date:        2014-08-17 20:01:09
Summary:     Fixing an incorrect comment.
Affected #:  1 file

diff -r 271f46ea8dac7552e34507544b4c75711def4208 -r 3aec01794a716071602928b53bd45f720d999ad0 doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
--- a/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
+++ b/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:f3e6416e4807e008a016ad8c7dfc8e78cab0d7519498458660554a4c88549c23"
+  "signature": "sha256:5a1547973517987ff047f1b2405277a0e98392e8fd5ffe04521cb2dc372d32d3"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -83,7 +83,7 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "# Build a transfer function that is a multivariate gaussian in Density\n",
+      "# Build a transfer function that is a multivariate gaussian in temperature\n",
       "tfh = yt.TransferFunctionHelper(ds)\n",
       "tfh.set_field('temperature')\n",
       "tfh.set_log(True)\n",
@@ -180,4 +180,4 @@
    "metadata": {}
   }
  ]
-}
+}
\ No newline at end of file


https://bitbucket.org/yt_analysis/yt/commits/2f242116a579/
Changeset:   2f242116a579
Branch:      yt
User:        MatthewTurk
Date:        2014-08-18 23:33:56
Summary:     Merged in ngoldbaum/yt (pull request #1149)

Fixing issues with TransferFunctions that are not log-scaled. Closes #880
Affected #:  3 files

diff -r 5c847041a74e8cd353617cc29da89048c62145ce -r 2f242116a579754330a95c7200eaa4dd7360a7e3 doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
--- a/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
+++ b/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:f3e6416e4807e008a016ad8c7dfc8e78cab0d7519498458660554a4c88549c23"
+  "signature": "sha256:5a1547973517987ff047f1b2405277a0e98392e8fd5ffe04521cb2dc372d32d3"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -83,7 +83,7 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "# Build a transfer function that is a multivariate gaussian in Density\n",
+      "# Build a transfer function that is a multivariate gaussian in temperature\n",
       "tfh = yt.TransferFunctionHelper(ds)\n",
       "tfh.set_field('temperature')\n",
       "tfh.set_log(True)\n",
@@ -180,4 +180,4 @@
    "metadata": {}
   }
  ]
-}
+}
\ No newline at end of file

diff -r 5c847041a74e8cd353617cc29da89048c62145ce -r 2f242116a579754330a95c7200eaa4dd7360a7e3 yt/visualization/volume_rendering/transfer_function_helper.py
--- a/yt/visualization/volume_rendering/transfer_function_helper.py
+++ b/yt/visualization/volume_rendering/transfer_function_helper.py
@@ -154,7 +154,9 @@
             xmi, xma = np.log10(self.bounds[0]), np.log10(self.bounds[1])
         else:
             xfunc = np.linspace
-            xmi, xma = self.bounds
+            # Need to strip units off of the bounds to avoid a recursion error
+            # in matplotlib 1.3.1
+            xmi, xma = [np.float64(b) for b in self.bounds]
 
         x = xfunc(xmi, xma, tf.nbins)
         y = tf.funcs[3].y
@@ -166,7 +168,7 @@
         canvas = FigureCanvasAgg(fig)
         ax = fig.add_axes([0.2, 0.2, 0.75, 0.75])
         ax.bar(x, tf.funcs[3].y, w, edgecolor=[0.0, 0.0, 0.0, 0.0],
-               log=True, color=colors, bottom=[0])
+               log=self.log, color=colors, bottom=[0])
 
         if profile_field is not None:
             try:
@@ -177,10 +179,12 @@
             if profile_field not in prof.keys():
                 prof.add_fields([profile_field], fractional=False,
                                 weight=profile_weight)
-            ax.plot(prof[self.field], prof[profile_field]*tf.funcs[3].y.max() /
-                    prof[profile_field].max(), color='w', linewidth=3)
-            ax.plot(prof[self.field], prof[profile_field]*tf.funcs[3].y.max() /
-                    prof[profile_field].max(), color='k')
+            # Strip units, if any, for matplotlib 1.3.1
+            xplot = np.array(prof[self.field])
+            yplot = np.array(prof[profile_field]*tf.funcs[3].y.max() /
+                             prof[profile_field].max())
+            ax.plot(xplot, yplot, color='w', linewidth=3)
+            ax.plot(xplot, yplot, color='k')
 
         ax.set_xscale({True: 'log', False: 'linear'}[self.log])
         ax.set_xlim(x.min(), x.max())
@@ -200,7 +204,7 @@
 
     def setup_profile(self, profile_field=None, profile_weight=None):
         if profile_field is None:
-            profile_field = 'CellVolume'
+            profile_field = 'cell_volume'
         prof = BinnedProfile1D(self.ds.all_data(), 128, self.field,
                                self.bounds[0], self.bounds[1],
                                log_space=self.log,

diff -r 5c847041a74e8cd353617cc29da89048c62145ce -r 2f242116a579754330a95c7200eaa4dd7360a7e3 yt/visualization/volume_rendering/transfer_functions.py
--- a/yt/visualization/volume_rendering/transfer_functions.py
+++ b/yt/visualization/volume_rendering/transfer_functions.py
@@ -48,6 +48,8 @@
     def __init__(self, x_bounds, nbins=256):
         self.pass_through = 0
         self.nbins = nbins
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.x = np.linspace(x_bounds[0], x_bounds[1], nbins).astype('float64')
         self.y = np.zeros(nbins, dtype='float64')
@@ -353,6 +355,8 @@
     """
     def __init__(self, x_bounds, nbins=256, grey_opacity = False):
         MultiVariateTransferFunction.__init__(self)
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.nbins = nbins
         # This is all compatibility and convenience.
@@ -633,6 +637,7 @@
         >>> tf = ColorTransferFunction( (-10.0, -5.0) )
         >>> tf.sample_colormap(-7.0, 0.01, colormap='algae')
         """
+        v = np.float64(v)
         if col_bounds is None:
             rel = (v - self.x_bounds[0])/(self.x_bounds[1] - self.x_bounds[0])
         else:
@@ -680,7 +685,8 @@
         >>> tf.map_to_colormap(-6.0, -5.0, scale=10.0, colormap='algae',
         ...                    scale_func = linramp)
         """
-
+        mi = np.float64(mi)
+        ma = np.float64(ma)
         rel0 = int(self.nbins*(mi - self.x_bounds[0])/(self.x_bounds[1] -
                                                        self.x_bounds[0]))
         rel1 = int(self.nbins*(ma - self.x_bounds[0])/(self.x_bounds[1] -
@@ -800,6 +806,8 @@
         if n_fields > 3:
             raise NotImplementedError
         MultiVariateTransferFunction.__init__(self)
+        # Strip units off of x_bounds, if any
+        x_bounds = [np.float64(xb) for xb in x_bounds]
         self.x_bounds = x_bounds
         self.nbins = 2
         self.linear_mapping = TransferFunction(x_bounds, 2)

Repository URL: https://bitbucket.org/yt_analysis/yt/

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