Changeset 126

Timestamp:

03/26/09 11:10:43 (7 years ago)

Author:

mmckerns

Message:

added tutorial examples (see ticket #24);
commented out addModelNew (see ticket #30);
fixed formatting for printing 'x' in VerboseSow?

Location:

mystic

Files:

• README (modified) (1 diff)
• examples/Make.mm (modified) (1 diff)
• examples/example01.py (added)
• examples/example02.py (added)
• examples/example03.py (added)
• examples/example04.py (added)
• examples/example05.py (added)
• examples/example06.py (added)
• examples/example07.py (added)
• examples/example08.py (added)
• examples/example09.py (added)
• examples/example10.py (added)
• examples/example11.py (added)
• examples/example12.py (added)
• mystic/forward_model.py (modified) (2 diffs)
• mystic/tools.py (modified) (1 diff)

mystic/README

@@ -2 +2 @@
 
 Dependencies:
+ - All examples with prefix "example" should run without new dependencies, and are intended as a tutorial. (i.e. TRY THESE FIRST)
  - All examples with prefix "test_" should run without new dependencies.
  - All examples with prefix "scipy_" requires scipy to be installed. (tested on version 0.4.8).

mystic/examples/Make.mm

@@ -74 +74 @@
     rosetta_parabola_example.py \
     rosetta_mogi_example.py \
+    example01.py \
+    example02.py \
+    example03.py \
+    example04.py \
+    example05.py \
+    example06.py \
+    example07.py \
+    example08.py \
+    example09.py \
+    example10.py \
+    example11.py \
+    example12.py \
 
 

mystic/mystic/forward_model.py

@@ -68 +68 @@
         self._inputCheckers.append(inputChecker)
 
+    #XXX: addModelNew is a work in progress...
+    '''
     def addModelNew(self, model, name, outputFilter = Identity, inputChecker = NullChecker):
         """
@@ -87 +89 @@
         self._outputFilters.append(outputFilter)
         self._inputCheckers.append(inputChecker)
+    '''
 
     def getForwardEvaluator(self, evalpts):

mystic/mystic/tools.py

@@ -170 +170 @@
             print "Generation %d has best Chi-Squared: %f" % (self._step, y)
         if int(self._step % self._xinterval) == 0:
-            print "Generation %d has bet fit parameters: %s" % (self._step, x)
+            print "Generation %d has best fit parameters:\n %s" % (self._step, x)
         return
     pass