Merge branch 'pointwise' into pointwise_ng

demos/bernoulli_demo.py

@@ -52,7 +52,7 @@ if __name__ == '__main__':
     A = ift.create_power_operator(harmonic_space, sqrtpspec)
 
     # Set up a sky operator and instrumental response
-    sky = HT(A).ptw("sigmoid")
+    sky = ift.sigmoid(HT(A))
     GR = ift.GeometryRemover(position_space)
     R = GR
 

demos/getting_started_2.py

@@ -80,7 +80,7 @@ if __name__ == '__main__':
     A = pd(a)
 
     # Define sky operator
-    sky = HT(ift.makeOp(A)).ptw("exp")
+    sky = ift.exp(HT(ift.makeOp(A)))
 
     M = ift.DiagonalOperator(exposure)
     GR = ift.GeometryRemover(position_space)

demos/getting_started_3.py

@@ -85,7 +85,7 @@ if __name__ == '__main__':
     A = cfmaker.amplitude
 
     # Apply a nonlinearity
-    signal = correlated_field.ptw("sigmoid")
+    signal = ift.sigmoid(correlated_field)
 
     # Build the line-of-sight response and define signal response
     LOS_starts, LOS_ends = random_los(100) if mode == 0 else radial_los(100)
@@ -149,7 +149,7 @@ if __name__ == '__main__':
     filename_res = filename.format("results")
     plot = ift.Plot()
     plot.add(sc.mean, title="Posterior Mean")
-    plot.add(sc.var.ptw("sqrt"), title="Posterior Standard Deviation")
+    plot.add(ift.sqrt(sc.var), title="Posterior Standard Deviation")
 
     powers = [A.force(s + KL.position) for s in KL.samples]
     plot.add(

demos/getting_started_mf.py

@@ -84,7 +84,7 @@ if __name__ == '__main__':
     DC = SingleDomain(correlated_field.target, position_space)
 
     ## Apply a nonlinearity
-    signal = DC @ correlated_field.ptw("sigmoid")
+    signal = DC @ ift.sigmoid(correlated_field)
 
     # Build the line-of-sight response and define signal response
     LOS_starts, LOS_ends = random_los(100) if mode == 0 else radial_los(100)
@@ -170,7 +170,7 @@ if __name__ == '__main__':
     filename_res = filename.format("results")
     plot = ift.Plot()
     plot.add(sc.mean, title="Posterior Mean")
-    plot.add(sc.var.ptw("sqrt"), title="Posterior Standard Deviation")
+    plot.add(ift.sqrt(sc.var), title="Posterior Standard Deviation")
 
     powers1 = [A1.force(s + KL.position) for s in KL.samples]
     powers2 = [A2.force(s + KL.position) for s in KL.samples]

nifty6/field.py

@@ -686,9 +686,6 @@ class Field(Operator):
     def flexible_addsub(self, other, neg):
         return self-other if neg else self+other
 
-    def clip(self, a_min=None, a_max=None):
-        return self.ptw("clip", a_min, a_max)
-
     def _binary_op(self, other, op):
         # if other is a field, make sure that the domains match
         f = getattr(self._val, op)
@@ -700,20 +697,24 @@ class Field(Operator):
             return Field(self._domain, f(other))
         return NotImplemented
 
-    def ptw(self, op, *args, **kwargs):
-        from .pointwise import ptw_dict
+    def _prep_args(self, args, kwargs):
+        for arg in args + tuple(kwargs.values()):
+            if not (arg is None or np.isscalar(arg) or arg.jac is None):
+                raise TypeError("bad argument")
         argstmp = tuple(arg if arg is None or np.isscalar(arg) else arg._val
                         for arg in args)
         kwargstmp = {key: val if val is None or np.isscalar(val) else val._val
                      for key, val in kwargs.items()}
+        return argstmp, kwargstmp
+
+    def ptw(self, op, *args, **kwargs):
+        from .pointwise import ptw_dict
+        argstmp, kwargstmp = self._prep_args(args, kwargs)
         return Field(self._domain, ptw_dict[op][0](self._val, *argstmp, **kwargstmp))
 
     def ptw_with_deriv(self, op, *args, **kwargs):
         from .pointwise import ptw_dict
-        argstmp = tuple(arg if arg is None or np.isscalar(arg) else arg._val
-                        for arg in args)
-        kwargstmp = {key: val if val is None or np.isscalar(val) else val._val
-                     for key, val in kwargs.items()}
+        argstmp, kwargstmp = self._prep_args(args, kwargs)
         tmp = ptw_dict[op][1](self._val, *argstmp, **kwargstmp)
         return (Field(self._domain, tmp[0]), Field(self._domain, tmp[1]))
 

nifty6/library/correlated_fields.py

@@ -225,7 +225,7 @@ class _Normalization(Operator):
     def apply(self, x):
         self._check_input(x)
         amp = x.ptw("exp")
-        spec = amp*amp
+        spec = amp**2
         # FIXME This normalizes also the zeromode which is supposed to be left
         # untouched by this operator
         return self._specsum(self._mode_multiplicity(spec))**(-0.5)*amp

nifty6/linearization.py

@@ -294,15 +294,6 @@ class Linearization(Operator):
         t1, t2 = self._fld.ptw_with_deriv(op, *args, **kwargs)
         return self.new(t1, makeOp(t2)(self._jac))
 
-    def clip(self, a_min=None, a_max=None):
-        if a_min is None and a_max is None:
-            return self
-        if not (a_min is None or np.isscalar(a_min) or a_min.jac is None):
-            return NotImplemented
-        if not (a_max is None or np.isscalar(a_max) or a_max.jac is None):
-            return NotImplemented
-        return self.ptw("clip", a_min, a_max)
-
     def add_metric(self, metric):
         return self.new(self._fld, self._jac, metric)
 

nifty6/multi_field.py

@@ -314,25 +314,27 @@ class MultiField(Operator):
                 res[key] = -val if neg else val
         return MultiField.from_dict(res)
 
+    def _prep_args(self, args, kwargs, i):
+        for arg in args + tuple(kwargs.values()):
+            if not (arg is None or np.isscalar(arg) or arg.jac is None):
+                raise TypeError("bad argument")
+        argstmp = tuple(arg if arg is None or np.isscalar(arg) else arg._val[i]
+                        for arg in args)
+        kwargstmp = {key: val if val is None or np.isscalar(val) else val._val[i]
+                     for key, val in kwargs.items()}
+        return argstmp, kwargstmp
+
     def ptw(self, op, *args, **kwargs):
-#        _check_args(args, kwargs)
         tmp = []
         for i in range(len(self._val)):
-            argstmp = tuple(arg if arg is None or np.isscalar(arg) else arg._val[i]
-                            for arg in args)
-            kwargstmp = {key: val if val is None or np.isscalar(val) else val._val[i]
-                         for key, val in kwargs.items()}
+            argstmp, kwargstmp = self._prep_args(args, kwargs, i)
             tmp.append(self._val[i].ptw(op, *argstmp, **kwargstmp))
         return MultiField(self.domain, tuple(tmp))
 
     def ptw_with_deriv(self, op, *args, **kwargs):
-#        _check_args(args, kwargs)
         tmp = []
         for i in range(len(self._val)):
-            argstmp = tuple(arg if arg is None or np.isscalar(arg) else arg._val[i]
-                            for arg in args)
-            kwargstmp = {key: val if val is None or np.isscalar(val) else val._val[i]
-                         for key, val in kwargs.items()}
+            argstmp, kwargstmp = self._prep_args(args, kwargs, i)
             tmp.append(self._val[i].ptw_with_deriv(op, *argstmp, **kwargstmp))
         return (MultiField(self.domain, tuple(v[0] for v in tmp)),
                 MultiField(self.domain, tuple(v[1] for v in tmp)))

nifty6/operators/operator.py

@@ -18,6 +18,7 @@
 import numpy as np
 
 from ..utilities import NiftyMeta, indent
+from .. import pointwise
 
 
 class Operator(metaclass=NiftyMeta):
@@ -221,15 +222,6 @@ class Operator(metaclass=NiftyMeta):
             return NotImplemented
         return self.ptw("power", power)
 
-    def clip(self, a_min=None, a_max=None):
-        if a_min is None and a_max is None:
-            return self
-        if not (a_min is None or np.isscalar(a_min) or a_min.jac is None):
-            return NotImplemented
-        if not (a_max is None or np.isscalar(a_max) or a_max.jac is None):
-            return NotImplemented
-        return self.ptw("clip", a_min, a_max)
-
     def apply(self, x):
         """Applies the operator to a Field or MultiField.
 
@@ -292,6 +284,14 @@ class Operator(metaclass=NiftyMeta):
         return _OpChain.make((_FunctionApplier(self.target, op, *args, **kwargs), self))
 
 
+for f in pointwise.ptw_dict.keys():
+    def func(f):
+        def func2(self, *args, **kwargs):
+            return self.ptw(f, *args, **kwargs)
+        return func2
+    setattr(Operator, f, func(f))
+
+
 class _ConstCollector(object):
     def __init__(self):
         self._const = None

nifty6/pointwise.py

@@ -67,7 +67,7 @@ def _power_helper(v, expo):
     return (np.power(v, expo), expo*np.power(v, expo-1))
 
 
-def _clip_helper(v, a_min=None, a_max=None):
+def _clip_helper(v, a_min, a_max):
     if np.issubdtype(v.dtype, np.complexfloating):
         raise TypeError("Argument must not be complex")
     tmp = np.clip(v, a_min, a_max)

nifty6/sugar.py

@@ -33,13 +33,15 @@ from .operators.distributors import PowerDistributor
 from .operators.operator import Operator
 from .operators.scaling_operator import ScalingOperator
 from .plot import Plot
+from . import pointwise
+
 
 __all__ = ['PS_field', 'power_analyze', 'create_power_operator',
            'create_harmonic_smoothing_operator', 'from_random',
            'full', 'makeField',
            'makeDomain', 'get_signal_variance', 'makeOp', 'domain_union',
            'get_default_codomain', 'single_plot', 'exec_time',
-           'calculate_position']
+           'calculate_position'] + list(pointwise.ptw_dict.keys())
 
 
 def PS_field(pspace, func):
@@ -341,7 +343,7 @@ def makeOp(input, dom=None):
     if input is None:
         return None
     if np.isscalar(input):
-        if not isinstance(dom, (DomaiTuple, MultiDomain)):
+        if not isinstance(dom, (DomainTuple, MultiDomain)):
             raise TypeError("need proper `dom` argument")
         return SalingOperator(dom, input)
     if dom is not None:
@@ -373,8 +375,16 @@ def domain_union(domains):
     return MultiDomain.union(domains)
 
 
-def clip(a, a_min=None, a_max=None):
-    return a.clip(a_min, a_max)
+# Pointwise functions
+
+_current_module = sys.modules[__name__]
+
+for f in pointwise.ptw_dict.keys():
+    def func(f):
+        def func2(x, *args, **kwargs):
+           return x.ptw(f, *args, **kwargs)
+        return func2
+    setattr(_current_module, f, func(f))
 
 
 def get_default_codomain(domainoid, space=None):

test/test_field.py

@@ -193,8 +193,8 @@ def test_empty_domain():
 def test_trivialities():
     s1 = ift.RGSpace((10,))
     f1 = ift.Field.full(s1, 27)
-    assert_equal(f1.clip(a_min=29).val, 29.)
-    assert_equal(f1.clip(a_max=25).val, 25.)
+    assert_equal(f1.clip(a_min=29, a_max=50).val, 29.)
+    assert_equal(f1.clip(a_min=0, a_max=25).val, 25.)
     assert_equal(f1.val, f1.real.val)
     assert_equal(f1.val, (+f1).val)
     f1 = ift.Field.full(s1, 27. + 3j)