Add missing dtype aliases (#1309)

* Add missing type aliases

* Remove dpnp.object_ type alias

* Remove dpnp.longcomplex and dpnp.void

* Add dpnp.pi, dpnp.e, dpnp.inf constants

* Add remaining numpy constants

Author: antonwolfy

dpnp/dpnp_algo/dpnp_algo.pyx

@@ -233,11 +233,11 @@ cpdef dpnp_queue_is_cpu():
 Internal functions
 """
 cdef DPNPFuncType dpnp_dtype_to_DPNPFuncType(dtype):
-    dt_c = numpy.dtype(dtype).char
-    kind = numpy.dtype(dtype).kind
+    dt_c = dpnp.dtype(dtype).char
+    kind = dpnp.dtype(dtype).kind
     if isinstance(kind, int):
         kind = chr(kind)
-    itemsize = numpy.dtype(dtype).itemsize
+    itemsize = dpnp.dtype(dtype).itemsize
 
     if dt_c == 'd':
         return DPNP_FT_DOUBLE
@@ -266,19 +266,19 @@ cdef dpnp_DPNPFuncType_to_dtype(size_t type):
     TODO needs to use DPNPFuncType here
     """
     if type == <size_t > DPNP_FT_DOUBLE:
-        return numpy.float64
+        return dpnp.float64
     elif type == <size_t > DPNP_FT_FLOAT:
-        return numpy.float32
+        return dpnp.float32
     elif type == <size_t > DPNP_FT_LONG:
-        return numpy.int64
+        return dpnp.int64
     elif type == <size_t > DPNP_FT_INT:
-        return numpy.int32
+        return dpnp.int32
     elif type == <size_t > DPNP_FT_CMPLX64:
-        return numpy.complex64
+        return dpnp.complex64
     elif type == <size_t > DPNP_FT_CMPLX128:
-        return numpy.complex128
+        return dpnp.complex128
     elif type == <size_t > DPNP_FT_BOOL:
-        return numpy.bool_
+        return dpnp.bool
     else:
         utils.checker_throw_type_error("dpnp_DPNPFuncType_to_dtype", type)
 

dpnp/dpnp_algo/dpnp_algo_statistics.pyx

@@ -1,7 +1,7 @@
 # cython: language_level=3
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2020, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -129,7 +129,7 @@ cpdef dpnp_average(utils.dpnp_descriptor x1):
     array_sum = dpnp_sum(x1).get_pyobj()
 
     """ Numpy interface inconsistency """
-    return_type = numpy.float32 if (x1.dtype == numpy.float32) else numpy.float64
+    return_type = dpnp.float32 if (x1.dtype == dpnp.float32) else dpnp.float64
 
     return (return_type(array_sum / x1.size))
 

dpnp/dpnp_array.py

@@ -537,7 +537,7 @@ def conj(self):
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex_):
+        if not dpnp.issubsctype(self.dtype, dpnp.complex_):
             return self
         else:
             return dpnp.conjugate(self)
@@ -550,7 +550,7 @@ def conjugate(self):
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex_):
+        if not dpnp.issubsctype(self.dtype, dpnp.complex_):
             return self
         else:
             return dpnp.conjugate(self)

dpnp/dpnp_iface_linearalgebra.py

@@ -2,7 +2,7 @@
 # distutils: language = c++
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2020, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -269,7 +269,7 @@ def matmul(x1, x2, out=None, **kwargs):
                 array2_size = x2_desc.size
                 cost_size = 4096  # 2D array shape(64, 64)
 
-                if ((x1_desc.dtype == numpy.float64) or (x1_desc.dtype == numpy.float32)):
+                if ((x1_desc.dtype == dpnp.float64) or (x1_desc.dtype == dpnp.float32)):
                     """
                     Floating point types are handled via original math library better than SYCL math library
                     """

dpnp/dpnp_iface_logic.py

@@ -511,9 +511,8 @@ def isfinite(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([-numpy.inf, 0., numpy.inf])
+    >>> x = np.array([-np.inf, 0., np.inf])
     >>> out = np.isfinite(x)
     >>> [i for i in out]
     [False, True, False]
@@ -556,9 +555,8 @@ def isinf(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([-numpy.inf, 0., numpy.inf])
+    >>> x = np.array([-np.inf, 0., np.inf])
     >>> out = np.isinf(x)
     >>> [i for i in out]
     [True, False, True]
@@ -602,9 +600,8 @@ def isnan(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([numpy.inf, 0., np.nan])
+    >>> x = np.array([np.inf, 0., np.nan])
     >>> out = np.isnan(x)
     >>> [i for i in out]
     [False, False, True]

dpnp/dpnp_iface_manipulation.py

@@ -89,7 +89,7 @@ def asfarray(x1, dtype=None):
 
     x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
-        if dtype is None or not numpy.issubdtype(dtype, numpy.inexact):
+        if dtype is None or not numpy.issubdtype(dtype, dpnp.inexact):
             dtype = dpnp.default_float_type(sycl_queue=x1.sycl_queue)
 
         # if type is the same then same object should be returned

dpnp/dpnp_iface_trigonometric.py

@@ -2,7 +2,7 @@
 # distutils: language = c++
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2020, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -136,9 +136,8 @@ def arccosh(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([numpy.e, 10.0])
+    >>> x = np.array([np.e, 10.0])
     >>> out = np.arccosh(x)
     >>> [i for i in out]
     [1.65745445, 2.99322285]
@@ -205,9 +204,8 @@ def arcsinh(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([numpy.e, 10.0])
+    >>> x = np.array([np.e, 10.0])
     >>> out = np.arcsinh(x)
     >>> [i for i in out]
     [1.72538256, 2.99822295]
@@ -384,9 +382,8 @@ def cos(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([0, numpy.pi/2, numpy.pi])
+    >>> x = np.array([0, np.pi/2, np.pi])
     >>> out = np.cos(x)
     >>> [i for i in out]
     [1.0, 6.123233995736766e-17, -1.0]
@@ -464,9 +461,8 @@ def degrees(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> rad = np.arange(6.) * numpy.pi/6
+    >>> rad = np.arange(6.) * np.pi/6
     >>> out = np.degrees(rad)
     >>> [i for i in out]
     [0.0, 30.0, 60.0, 90.0, 120.0, 150.0]
@@ -652,9 +648,8 @@ def log(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([1.0, numpy.e, numpy.e**2, 0.0])
+    >>> x = np.array([1.0, np.e, np.e**2, 0.0])
     >>> out = np.log(x)
     >>> [i for i in out]
     [0.0, 1.0, 2.0, -inf]
@@ -867,9 +862,8 @@ def sin(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([0, numpy.pi/2, numpy.pi])
+    >>> x = np.array([0, np.pi/2, np.pi])
     >>> out = np.sin(x)
     >>> [i for i in out]
     [0.0, 1.0, 1.2246467991473532e-16]
@@ -897,9 +891,8 @@ def sinh(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([0, numpy.pi/2, numpy.pi])
+    >>> x = np.array([0, np.pi/2, np.pi])
     >>> out = np.sinh(x)
     >>> [i for i in out]
     [0.0, 2.3012989, 11.548739]
@@ -991,9 +984,8 @@ def tan(x1, out=None, **kwargs):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([-numpy.pi, numpy.pi/2, numpy.pi])
+    >>> x = np.array([-np.pi, np.pi/2, np.pi])
     >>> out = np.tan(x)
     >>> [i for i in out]
     [1.22460635e-16, 1.63317787e+16, -1.22460635e-16]
@@ -1021,9 +1013,8 @@ def tanh(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> x = np.array([-numpy.pi, numpy.pi/2, numpy.pi])
+    >>> x = np.array([-np.pi, np.pi/2, np.pi])
     >>> out = np.tanh(x)
     >>> [i for i in out]
     [-0.996272, 0.917152, 0.996272]
@@ -1055,11 +1046,10 @@ def unwrap(x1):
 
     Examples
     --------
-    >>> import numpy
     >>> import dpnp as np
-    >>> phase = np.linspace(0, numpy.pi, num=5)
+    >>> phase = np.linspace(0, np.pi, num=5)
     >>> for i in range(3, 5):
-    >>>     phase[i] += numpy.pi
+    >>>     phase[i] += np.pi
     >>> out = np.unwrap(phase)
     >>> [i for i in out]
     [0.0, 0.78539816, 1.57079633, 5.49778714, 6.28318531]