[Yt-svn] yt: An attempt to get the new multi variate to give exactly iden...

[hg at spacepope.org]

hg Repository: yt
details:   yt/rev/b409318f6420
changeset: 1512:b409318f6420
user:      Matthew Turk <matthewturk at gmail.com>
date:
Thu Apr 01 11:30:20 2010 -0700
description:
An attempt to get the new multi variate to give exactly identical results.  It
still doesn't quite work, because we're trying to replicate an old, ill-defined
result with a new, well-defined method.

diffstat:

 yt/_amr_utils/VolumeIntegrator.pyx                 |  11 +++++++++--
 yt/extensions/volume_rendering/TransferFunction.py |  14 ++++++++++----
 2 files changed, 19 insertions(+), 6 deletions(-)

diffs (82 lines):

diff -r b02c9c1919db -r b409318f6420 yt/_amr_utils/VolumeIntegrator.pyx
--- a/yt/_amr_utils/VolumeIntegrator.pyx	Thu Apr 01 01:03:30 2010 -0700
+++ b/yt/_amr_utils/VolumeIntegrator.pyx	Thu Apr 01 11:30:20 2010 -0700
@@ -82,11 +82,12 @@
     np.float64_t idbin
     int field_id
     int weight_field_id
+    int weight_table_id
     int nbins
 
 cdef void FIT_initialize_table(FieldInterpolationTable *fit, int nbins,
               np.float64_t *values, np.float64_t bounds1, np.float64_t bounds2,
-              int field_id, int weight_field_id = -1):
+              int field_id, int weight_field_id = -1, int weight_table_id = -1):
     fit.bounds[0] = bounds1; fit.bounds[1] = bounds2
     fit.nbins = nbins
     fit.dbin = (fit.bounds[1] - fit.bounds[0])/fit.nbins
@@ -95,6 +96,7 @@
     fit.values = values
     fit.field_id = field_id
     fit.weight_field_id = weight_field_id
+    fit.weight_table_id = weight_table_id
 
 cdef np.float64_t FIT_get_value(FieldInterpolationTable *fit,
                             np.float64_t *dvs):
@@ -153,7 +155,8 @@
                       <np.float64_t *> temp.data,
                       tf_obj.tables[i].x_bounds[0],
                       tf_obj.tables[i].x_bounds[1],
-                      tf_obj.field_ids[i], tf_obj.weight_field_ids[i])
+                      tf_obj.field_ids[i], tf_obj.weight_field_ids[i],
+                      tf_obj.weight_table_ids[i])
             self.my_field_tables.append((tf_obj.tables[i],
                                          tf_obj.tables[i].y))
             self.field_tables[i].field_id = tf_obj.field_ids[i]
@@ -185,6 +188,10 @@
                 break
         for i in range(self.n_field_tables):
             self.istorage[i] = FIT_get_value(&self.field_tables[i], dvs)
+        # We have to do this after the interpolation
+        for i in range(self.n_field_tables):
+            fid = self.field_tables[i].weight_table_id
+            if fid != -1: self.istorage[i] *= self.istorage[fid]
         for i in range(6):
             trgba[i] = self.istorage[self.field_table_ids[i]]
         # A few words on opacity.  We're going to be integrating equation 1.23
diff -r b02c9c1919db -r b409318f6420 yt/extensions/volume_rendering/TransferFunction.py
--- a/yt/extensions/volume_rendering/TransferFunction.py	Thu Apr 01 01:03:30 2010 -0700
+++ b/yt/extensions/volume_rendering/TransferFunction.py	Thu Apr 01 11:30:20 2010 -0700
@@ -87,11 +87,14 @@
         self.field_ids = [0] * 6 # This correlates fields with tables
         self.weight_field_ids = [-1] * 6 # This correlates 
         self.field_table_ids = [0] * 6
+        self.weight_table_ids = [-1] * 6
 
-    def add_field_table(self, table, field_id, weight_field_id = -1):
+    def add_field_table(self, table, field_id, weight_field_id = -1,
+                        weight_table_id = -1):
         self.tables.append(table)
         self.field_ids[self.n_field_tables] = field_id
         self.weight_field_ids[self.n_field_tables] = weight_field_id
+        self.weight_table_ids[self.n_field_tables] = weight_table_id
         self.n_field_tables += 1
 
     def link_channels(self, table_id, channels = 0):
@@ -113,10 +116,13 @@
 
         # Now we do the multivariate stuff
         # We assign to Density, but do not weight
-        for i,tf in enumerate(self.funcs[:-1]):
-            self.add_field_table(tf, 0)
+        for i,tf in enumerate(self.funcs):
+            self.add_field_table(tf, 0, weight_table_id = 3)
             self.link_channels(i, i)
-            self.link_channels(i, i+3)
+
+        self.alpha_two = TransferFunction(x_bounds, nbins)
+        self.add_field_table(self.alpha_two, 0)
+        self.link_channels(4, [3,4,5])
 
     def add_gaussian(self, location, width, height):
         for tf, v in zip(self.funcs, height):