numpy-compatible histogram

python/mxnet/ndarray/numpy/_op.py

@@ -31,7 +31,7 @@
            'arctan2', 'sin', 'cos', 'tan', 'sinh', 'cosh', 'tanh', 'log10', 'sqrt', 'cbrt', 'abs',
            'absolute', 'exp', 'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log', 'degrees', 'log2',
            'log1p', 'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor',
-           'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'tensordot',
+           'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'tensordot', 'histogram',
            'linspace', 'expand_dims', 'tile', 'arange', 'split', 'concatenate', 'stack', 'vstack', 'mean',
            'maximum', 'minimum', 'swapaxes', 'clip', 'argmax', 'std', 'var', 'indices', 'copysign',
            'ravel', 'hanning', 'hamming', 'blackman', 'flip', 'around', 'hypot', 'rad2deg', 'deg2rad',
@@ -612,6 +612,53 @@ def tensordot(a, b, axes=2):
     return _npi.tensordot(a, b, a_axes_summed, b_axes_summed)
 
 
+@set_module('mxnet.ndarray.numpy')
+def histogram(a, bins=10, range=None, normed=None, weights=None, density=None):  # pylint: disable=too-many-arguments
+    """
+    Compute the histogram of a set of data.
+
+    Parameters
+    ----------
+    a : NDArray
+        Input data. The histogram is computed over the flattened array.
+    bins : int or NDArray
+        If `bins` is an int, it defines the number of equal-width
+        bins in the given range (10, by default). If `bins` is a
+        sequence, it defines a monotonically increasing array of bin edges,
+        including the rightmost edge, allowing for non-uniform bin widths.
+        .. versionadded:: 1.11.0
+        If `bins` is a string, it defines the method used to calculate the
+        optimal bin width, as defined by `histogram_bin_edges`.
+    range : (float, float)
+        The lower and upper range of the bins. Required when `bins` is an integer.
+        Values outside the range are ignored. The first element of the range must
+        be less than or equal to the second.
+    normed : bool, optional
+        Not supported yet, coming soon.
+    weights : array_like, optional
+        Not supported yet, coming soon.
+    density : bool, optional
+        Not supported yet, coming soon.
+    """
+    if normed is True:
+        raise NotImplementedError("normed is not supported yet...")
+    if weights is not None:
+        raise NotImplementedError("weights is not supported yet...")
+    if density is True:
+        raise NotImplementedError("density is not supported yet...")
+    if isinstance(bins, numeric_types):
+        if range is None:
+            raise NotImplementedError("automatic range is not supported yet...")
+        return _npi.histogram(a, bin_cnt=bins, range=range)
+    if isinstance(bins, (list, tuple)):
+        raise NotImplementedError("array_like bins is not supported yet...")
+    if isinstance(bins, str):
+        raise NotImplementedError("string bins is not supported yet...")
+    if isinstance(bins, NDArray):
+        return _npi.histogram(a, bins=bins)
+    raise ValueError("np.histogram fails with", locals())
+
+
 @set_module('mxnet.ndarray.numpy')
 def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, ctx=None):  # pylint: disable=too-many-arguments
     r"""

python/mxnet/numpy/multiarray.py

@@ -51,11 +51,12 @@
            'sqrt', 'cbrt', 'abs', 'absolute', 'exp', 'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log',
            'degrees', 'log2', 'log1p', 'rint', 'radians', 'reciprocal', 'square', 'negative',
            'fix', 'ceil', 'floor', 'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh',
-           'tensordot', 'linspace', 'expand_dims', 'tile', 'arange', 'split', 'concatenate',
+           'tensordot', 'histogram', 'linspace', 'expand_dims', 'tile', 'arange', 'split', 'concatenate',
            'stack', 'vstack', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip', 'argmax', 'std', 'var', 'indices',
            'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip', 'around', 'arctan2', 'hypot',
            'rad2deg', 'deg2rad', 'unique']
 
+
 # Return code for dispatching indexing function call
 _NDARRAY_UNSUPPORTED_INDEXING = -1
 _NDARRAY_BASIC_INDEXING = 0
@@ -3444,6 +3445,37 @@ def tensordot(a, b, axes=2):
     return _mx_nd_np.tensordot(a, b, axes)
 
 
+@set_module('mxnet.numpy')
+def histogram(a, bins=10, range=None, normed=None, weights=None, density=None):  # pylint-disable=too-many-arguments
+    """
+    Compute the histogram of a set of data.
+
+    Parameters
+    ----------
+    a : NDArray
+        Input data. The histogram is computed over the flattened array.
+    bins : int or NDArray
+        If `bins` is an int, it defines the number of equal-width
+        bins in the given range (10, by default). If `bins` is a
+        sequence, it defines a monotonically increasing array of bin edges,
+        including the rightmost edge, allowing for non-uniform bin widths.
+        .. versionadded:: 1.11.0
+        If `bins` is a string, it defines the method used to calculate the
+        optimal bin width, as defined by `histogram_bin_edges`.
+    range : (float, float)
+        The lower and upper range of the bins. Required when `bins` is an integer.
+        Values outside the range are ignored. The first element of the range must
+        be less than or equal to the second.
+    normed : bool, optional
+        Not supported yet, coming soon.
+    weights : array_like, optional
+        Not supported yet, coming soon.
+    density : bool, optional
+        Not supported yet, coming soon.
+    """
+    return _mx_nd_np.histogram(a, bins=bins, range=range, normed=normed, weights=weights, density=density)
+
+
 @set_module('mxnet.numpy')
 def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, ctx=None):  # pylint: disable=too-many-arguments
     r"""

python/mxnet/symbol/numpy/_symbol.py

@@ -33,7 +33,7 @@
            'sin', 'cos', 'tan', 'sinh', 'cosh', 'tanh', 'log10', 'sqrt', 'cbrt', 'abs', 'absolute', 'exp',
            'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log', 'degrees', 'log2', 'log1p',
            'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor',
-           'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'tensordot',
+           'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'tensordot', 'histogram',
            'linspace', 'expand_dims', 'tile', 'arange', 'split', 'concatenate', 'stack', 'vstack', 'mean',
            'maximum', 'minimum', 'swapaxes', 'clip', 'argmax', 'std', 'var', 'indices', 'copysign',
            'ravel', 'hanning', 'hamming', 'blackman', 'flip', 'around', 'hypot', 'rad2deg', 'deg2rad',
@@ -1134,6 +1134,53 @@ def tensordot(a, b, axes=2):
     return _npi.tensordot(a, b, a_axes_summed, b_axes_summed)
 
 
+@set_module('mxnet.symbol.numpy')
+def histogram(a, bins=10, range=None, normed=None, weights=None, density=None):  # pylint: disable= too-many-arguments
+    """
+    Compute the histogram of a set of data.
+
+    Parameters
+    ----------
+    a : Symbol
+        Input data. The histogram is computed over the flattened array.
+    bins : int or Symbol
+        If `bins` is an int, it defines the number of equal-width
+        bins in the given range (10, by default). If `bins` is a
+        sequence, it defines a monotonically increasing array of bin edges,
+        including the rightmost edge, allowing for non-uniform bin widths.
+        .. versionadded:: 1.11.0
+        If `bins` is a string, it defines the method used to calculate the
+        optimal bin width, as defined by `histogram_bin_edges`.
+    range : (float, float)
+        The lower and upper range of the bins. Required when `bins` is an integer.
+        Values outside the range are ignored. The first element of the range must
+        be less than or equal to the second.
+    normed : bool, optional
+        Not supported yet, coming soon.
+    weights : array_like, optional
+        Not supported yet, coming soon.
+    density : bool, optional
+        Not supported yet, coming soon.
+    """
+    if normed is True:
+        raise NotImplementedError("normed is not supported yet...")
+    if weights is not None:
+        raise NotImplementedError("weights is not supported yet...")
+    if density is True:
+        raise NotImplementedError("density is not supported yet...")
+    if isinstance(bins, numeric_types):
+        if range is None:
+            raise NotImplementedError("automatic range is not avaialble yet...")
+        return _npi.histogram(a, bin_cnt=bins, range=range)
+    if isinstance(bins, (list, tuple)):
+        raise NotImplementedError("array_like bins is not supported yet...")
+    if isinstance(bins, str):
+        raise NotImplementedError("string bins is not supported yet...")
+    if isinstance(bins, Symbol):
+        return _npi.histogram(a, bins)
+    raise ValueError("histogram fails with", locals())
+
+
 @set_module('mxnet.symbol.numpy')
 def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, ctx=None): # pylint: disable=too-many-arguments
     r"""

src/operator/tensor/histogram.cc

@@ -123,6 +123,7 @@ void HistogramForwardImpl<cpu>(const OpContext& ctx,
 DMLC_REGISTER_PARAMETER(HistogramParam);
 
 NNVM_REGISTER_OP(_histogram)
+.add_alias("_npi_histogram")
 .describe(R"code(This operators implements the histogram function.
 
 Example::

tests/python/unittest/test_numpy_op.py

@@ -1674,6 +1674,24 @@ def hybrid_forward(self, F, a):
                         assert_almost_equal(mx_out.asnumpy(), np_out, rtol=1e-3, atol=1e-5)
 
 
+@with_seed()
+@use_np
+def test_np_histogram():
+    shapes = [(), (3, 4), (3, 0)]
+
+    for shape in shapes:
+        mx_a = np.random.uniform(0.0, 10.0, size=shape)
+        np_a = mx_a.asnumpy()
+        mx_bins = np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5., 6., 7., 8., 9., 10.])
+        np_bins = mx_bins.asnumpy()
+        for bins, _range in [(20, (0.0, 10.0)), (mx_bins, None)]:
+            print(bins, _range)
+            mx_cnts, mx_bins = np.histogram(mx_a, bins=bins, range=_range)
+            np_cnts, np_bins = _np.histogram(np_a, bins=bins if isinstance(bins, mx.base.numeric_types) else bins.asnumpy(), range=_range)
+            assert_almost_equal(mx_cnts.asnumpy(), np_cnts, rtol=1e-3, atol=1e-5)
+            assert_almost_equal(mx_bins.asnumpy(), np_bins, rtol=1e-3, atol=1e-5)
+
+
 @with_seed()
 @use_np
 def test_np_choice():