Addressing issue #18

Author: dokester

BayesicFitting/source/UserModel.py

@@ -11,7 +11,7 @@
 __author__ = "Do Kester"
 __year__ = 2022
 __license__ = "GPL3"
-__version__ = "3.0.0"
+__version__ = "3.0.1"
 __url__ = "https://www.bayesicfitting.nl"
 __status__ = "Perpetual Beta"
 
@@ -120,7 +120,7 @@ def __init__( self, npars, userResult, ndim=1, userPartial=None, userDeriv=None,
 
         self.setMethod( "userResult", userResult )
 
-        super( ).__init__( npars, copy=copy, **kwargs )
+        super( ).__init__( npars, ndim=ndim, copy=copy, **kwargs )
 
         if copy is not None :
             setatt( self, "userPartial", copy.userPartial )
@@ -133,7 +133,7 @@ def __init__( self, npars, userResult, ndim=1, userPartial=None, userDeriv=None,
 
     def copy( self ):
         """ Copy method.  """
-        return UserModel( self.npars, self.baseResult, copy=self )
+        return UserModel( self.npars, self.baseResult, ndim=self.ndim, copy=self )
 
     def setMethod( self, name, userMethod, numeric=None ) :
         if callable( userMethod ) :

BayesicFitting/test/TestUserModel.py

@@ -77,6 +77,10 @@ def etalonDer( xdata, params ) :
     dd *= dd
     return - 2 * math.pi * params[0] * params[1] * params[2] * sx * numpy.cos( x ) / dd
 
+def fitfunc(x, p):
+    return x[:,0]*p[0] + x[:,1]*p[1] + p[2]
+
+
 class Test( unittest.TestCase ):
     """
     Test harness for Models
@@ -120,6 +124,27 @@ def test2( self ):
         assertAE( m1.derivative( x, p ), m2.derivative( x, p ) )        
 
 
+    def test3( self ):
+        print( "******USER MODEL 2***********************" )
+
+        # Make 10 random 2-dimensional points
+        x = numpy.random.rand( 10, 2 )
+
+        # Make fake data + noise
+        p = numpy.array( [1,2,3] )
+        cleandata = fitfunc( x, p )
+        noisedata = cleandata * numpy.random.normal( 1, 0.05, x.shape[0] )
+
+        # Find model parameters from noisy data
+        model = UserModel( len(p), fitfunc, ndim=2 )
+        fitter = Fitter( x, model )
+        param = fitter.fit( noisedata )
+
+        self.assertTrue( model.ndim == 2 )
+        print( param )
+
+
+
 
     @classmethod
     def suite( cls ):

README.md

@@ -3,7 +3,7 @@
 A package for model fitting and Bayesian evidence calculation.
 
 We have a paper out in "Astronomy and Computing" about BayesicFitting.
-[Kester and Mueller (2021)](./references.md/#kester8).
+[Kester and Mueller (2021)](./docs/references.md/#kester8).
 
 (In case you are wondering what that is about take a 
 quick look at [this example.]
@@ -14,6 +14,9 @@ DOI: 10.5281/zenodo.2597200
 
 
 ## What's new.
+ + 05 Apr 2022 version 3.0.1
+   * Addressing issue #18: UserModel does not work for multiple dimensions.
+
  + 07 Feb 2022 version 3.0.0
    * New classes: AstropyModel and UserModel
    * New class: NeuralNetUtilities

setup.py

@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = '3.0.0'
+__version__ = '3.0.1'
 
 with open("README.md", "r") as fh:
     long_description = fh.read()