Merging

ch.py

@@ -280,12 +280,12 @@ def _compute_dr_wrt_sliced(self, wrt):
 
             try:
                 jac = wrt.compute_dr_wrt(inner).T
-            except:
+            except Exception as e:
                 import pdb; pdb.set_trace()
-        
+
             return self._superdot(result, jac)
 
-    
+
     @property
     def shape(self):
         return self.r.shape
@@ -331,7 +331,7 @@ def __setstate__(self, d):
         # This restores our unpickleable "_parents" attribute
         for k in set(self.dterms).intersection(set(self.__dict__.keys())):
             setattr(self, k, self.__dict__[k])
-        
+
     def __setattr__(self, name, value, itr=None):
         #print 'SETTING %s' % (name,)
 
@@ -471,7 +471,7 @@ def __setitem__(self, key, value, itr=None):
             #         kids.append(p)
             #     else:
             #         parents += [p.__dict__[k] for k in p.dterms]
-            # from body.ch.optimization import minimize_dogleg
+            # from ch.optimization import minimize_dogleg
             # minimize_dogleg(obj=self.__getitem__(key) - value, free_variables=kids, show_residuals=False)            
         else:
             inner = self
@@ -554,7 +554,7 @@ def _superdot(self, lhs, rhs):
 
             if isinstance(rhs, np.ndarray) and rhs.size==1:
                 rhs = rhs.ravel()[0]
-                
+
             if isinstance(lhs, numbers.Number) or isinstance(rhs, numbers.Number):
                 return lhs * rhs
 
@@ -740,8 +740,7 @@ def string_for(self, my_name):
                         result += ['%s [label="%s"];' % (dst, child_label)]
                         result += string_for(getattr(self, dterm), dterm)
             return result
-
-
+
         dot_file_contents = 'digraph G {\n%s\n}' % '\n'.join(list(set(string_for(self, 'root'))))
         dot_file = tempfile.NamedTemporaryFile()
         dot_file.write(dot_file_contents)

ch_ops.py

@@ -47,7 +47,7 @@
 import numpy as np
 import cPickle as pickle
 import scipy.sparse as sp
-from chumpy.utils import row, col
+from utils import row, col
 from copy import copy as copy_copy
 
 __all__ += ['pi', 'set_printoptions']
@@ -337,7 +337,7 @@ def on_changed(self, which):
             self.dr_cache = {}
 
     def compute_r(self):
-        return np.array(np.mean(self.x.r, axis=self.axis))
+        return np.array([np.mean(self.x.r, axis=self.axis)])
 
     def compute_dr_wrt(self, wrt):
         if wrt is not self.x:

extras.py

@@ -1,8 +1,8 @@
 __author__ = 'matt'
 
-import chumpy as ch
+import ch
 import numpy as np
-from .utils import row, col
+from utils import row, col
 import scipy.sparse as sp
 import scipy.special
 

linalg.py

@@ -8,7 +8,7 @@
 """
 
 
-__all__ = ['inv', 'svd', 'det', 'slogdet', 'pinv', 'lstsq']
+__all__ = ['inv', 'svd', 'det', 'slogdet', 'pinv', 'lstsq', 'norm']
 
 import numpy as np
 import scipy.sparse as sp
@@ -24,6 +24,11 @@
     __all__.append('tensorinv')
 except: pass
 
+def norm(x, ord=None, axis=None):
+    if ord is not None or axis is not None:
+        raise NotImplementedError("'ord' and 'axis' should be None for now.")
+
+    return ch.sqrt(ch.sum(x**2))
 
 def lstsq(a, b, rcond=-1):
     if rcond != -1:

logic.py

@@ -10,7 +10,7 @@
 __all__ = [] # added to incrementally below
 
 import ch
-from .ch import Ch
+from ch import Ch
 import numpy as np
 
 class LogicFunc(Ch):
@@ -34,6 +34,6 @@ def compute_dr_wrt(self, wrt):
 
 
 if __name__ == '__main__':
-    import chumpy as ch
+    import ch
     print all(np.array([1,2,3]))
-    print isinf(np.array([0,2,3]))
+    print isinf(np.array([0,2,3]))

optimization.py

@@ -15,8 +15,9 @@
 import numpy as np
 from numpy.linalg import norm
 
-from chumpy import ch
-from chumpy.utils import row, col
+import ch, utils
+from utils import row, col
+
 import scipy.sparse as sp
 import scipy.sparse
 import scipy.optimize
@@ -26,6 +27,7 @@
 vstack = lambda x : sp.vstack(x, format='csc') if any([sp.issparse(a) for a in x]) else np.vstack(x)
 hstack = lambda x : sp.hstack(x, format='csc') if any([sp.issparse(a) for a in x]) else np.hstack(x)
 
+
 # Nelder-Mead
 # Powell
 # CG
@@ -52,7 +54,7 @@ def minimize(fun, x0, method='dogleg', bounds=None, constraints=(), tol=None, ca
     free_variables = x0
 
 
-    from .ch import SumOfSquares
+    from ch import SumOfSquares
 
     hessp = None
     hess = None
@@ -206,8 +208,8 @@ def on_changed(self, which):
                     self.free_variables[idx].__setattr__('x', self.x.r[rng], _giter)
                 #self.free_variables[idx] = self.obj.replace(freevar, Ch(self.x.r[rng].copy()))
                 pos += sz
-
 
+
     @property
     def J(self):
         result = self.dr_wrt(self.x).copy()
@@ -272,7 +274,7 @@ def _minimize_dogleg(obj, free_variables, on_step=None,
     num_unique_ids = len(np.unique(np.array([id(freevar) for freevar in free_variables])))
     if num_unique_ids != len(free_variables):
         raise Exception('The "free_variables" param contains duplicate variables.')
-
+        
     obj = ChInputsStacked(obj=obj, free_variables=free_variables, x=np.concatenate([freevar.r.ravel() for freevar in free_variables]))
 
     def call_cb():
@@ -313,7 +315,7 @@ def call_cb():
     tm = time.time()
     pif('computing Jacobian...')
     J = obj.J
-        
+
     if sp.issparse(J):
         assert(J.nnz > 0)
     pif('Jacobian (%dx%d) computed in %.2fs' % (J.shape[0], J.shape[1], time.time() - tm))
@@ -464,8 +466,7 @@ def call_cb():
 
             # the following "collect" is very expensive.
             # please contact matt if you find situations where it actually helps things.
-            # collect()
-
+            #import gc; gc.collect()
             if stop or improvement_occurred or (fevals >= max_fevals):
                 break
         if k >= k_max:

reordering.py

@@ -6,7 +6,7 @@
 
 import ch
 import numpy as np
-from chumpy.utils import row, col
+from utils import row, col
 import scipy.sparse as sp
 import weakref
 
@@ -163,7 +163,7 @@ class Reshape(Permute):
     dterms = 'a',
     terms = 'newshape',
     term_order= 'a', 'newshape'
-    
+
     def compute_r(self):
         return self.a.r.reshape(self.newshape)
 
@@ -300,8 +300,8 @@ def on_changed(self, which):
 
 
 class AtleastNd(ch.Ch):
-    dterms = 'x',
-    terms = 'ndims',
+    dterms = 'x'
+    terms = 'ndims'
 
     def compute_r(self):
         xr = self.x.r