Introduce expm1 by wrapping the numpy function

nifty5/data_objects/distributed_do.py

@@ -32,7 +32,7 @@ __all__ = ["ntask", "rank", "master", "local_shape", "data_object", "full",
            "redistribute", "default_distaxis", "is_numpy", "absmax", "norm",
            "lock", "locked", "uniform_full", "transpose", "to_global_data_rw",
            "ensure_not_distributed", "ensure_default_distributed",
-           "tanh", "conjugate", "sin", "cos", "tan", "log10", "log1p",
+           "tanh", "conjugate", "sin", "cos", "tan", "log10", "log1p", "expm1",
            "sinh", "cosh", "sinc", "absolute", "sign", "clip"]
 
 _comm = MPI.COMM_WORLD
@@ -297,7 +297,8 @@ def _math_helper(x, function, out):
 _current_module = sys.modules[__name__]
 
 for f in ["sqrt", "exp", "log", "tanh", "conjugate", "sin", "cos", "tan",
-          "sinh", "cosh", "sinc", "absolute", "sign", "log10", "log1p"]:
+          "sinh", "cosh", "sinc", "absolute", "sign", "log10", "log1p",
+          "expm1"]:
     def func(f):
         def func2(x, out=None):
             return _math_helper(x, f, out)

nifty5/data_objects/numpy_do.py

@@ -22,7 +22,7 @@ from numpy import ndarray as data_object
 from numpy import empty, empty_like, ones, zeros, full
 from numpy import absolute, sign, clip, vdot
 from numpy import sin, cos, sinh, cosh, tan, tanh
-from numpy import exp, log, log10, sqrt, sinc, log1p
+from numpy import exp, log, log10, sqrt, sinc, log1p, expm1
 
 from .random import Random
 
@@ -35,8 +35,8 @@ __all__ = ["ntask", "rank", "master", "local_shape", "data_object", "full",
            "redistribute", "default_distaxis", "is_numpy", "absmax", "norm",
            "lock", "locked", "uniform_full", "to_global_data_rw",
            "ensure_not_distributed", "ensure_default_distributed",
-           "clip", "sin", "cos", "tan", "sinh",
-           "cosh", "absolute", "sign", "sinc", "log10", "log1p"]
+           "clip", "sin", "cos", "tan", "sinh", "cosh",
+           "absolute", "sign", "sinc", "log10", "log1p", "expm1"]
 
 ntask = 1
 rank = 0

nifty5/field.py

@@ -663,9 +663,8 @@ for op in ["__iadd__", "__isub__", "__imul__", "__idiv__",
         return func2
     setattr(Field, op, func(op))
 
-for f in ["sqrt", "exp", "log", "log10", "log1p", "tanh",
-          "sin", "cos", "tan", "cosh", "sinh",
-          "absolute", "sinc", "sign"]:
+for f in ["sqrt", "exp", "log", "sin", "cos", "tan", "sinh", "cosh", "tanh",
+          "absolute", "sinc", "sign", "log10", "log1p", "expm1"]:
     def func(f):
         def func2(self):
             return Field(self._domain, getattr(dobj, f)(self.val))

nifty5/linearization.py

@@ -341,6 +341,11 @@ class Linearization(object):
         jac = makeOp(1. / (1. + xval))
         return self.new(res, jac @ self.jac)
 
+    def expm1(self):
+        tmp = self._val.expm1()
+        tmp2 = self._val.exp()
+        return self.new(tmp, makeOp(tmp2)(self.jac))
+
     def sinh(self):
         tmp = self._val.sinh()
         tmp2 = self._val.cosh()

nifty5/multi_field.py

@@ -338,7 +338,7 @@ for op in ["__iadd__", "__isub__", "__imul__", "__idiv__",
     setattr(MultiField, op, func(op))
 
 
-for f in ["sqrt", "exp", "log", "log1p", "tanh"]:
+for f in ["sqrt", "exp", "log", "log1p", "expm1", "tanh"]:
     def func(f):
         def func2(self):
             fu = getattr(Field, f)

test/test_linearization.py

@@ -54,7 +54,7 @@ def test_special_gradients():
 
 @pmp('f', [
     'log', 'exp', 'sqrt', 'sin', 'cos', 'tan', 'sinc', 'sinh', 'cosh', 'tanh',
-    'absolute', 'one_over', 'sigmoid', 'log10', 'log1p'
+    'absolute', 'one_over', 'sigmoid', 'log10', 'log1p', "expm1"
 ])
 def test_actual_gradients(f):
     dom = ift.UnstructuredDomain((1,))