[Numpy] add ediff1d

python/mxnet/ndarray/numpy/_op.py

@@ -44,7 +44,7 @@
  'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
  'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'rot90', 'einsum',
  'true_divide', 'nonzero', 'quantile', 'percentile', 'shares_memory', 'may_share_memory',
- 'diff', 'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
+ 'diff', 'ediff1d', 'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
  'where', 'bincount', 'pad']
 
 
@@ -6758,6 +6758,63 @@ def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable=redefin
  return _npi.diff(a, n=n, axis=axis)
 
 
+@set_module('mxnet.ndarray.numpy')
+def ediff1d(ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+
+ Parameters
+ ----------
+ ary : ndarray
+ If necessary, will be flattened before the differences are taken.
+ to_end : ndarray or scalar, optional
+ Number(s) to append at the end of the returned differences.
+ to_begin : ndarray or scalar, optional
+ Number(s) to prepend at the beginning of the returned differences.
+
+ Returns
+ -------
+ ediff1d : ndarray
+ The differences. Loosely, this is ``ary.flat[1:] - ary.flat[:-1]``.
+
+ Examples
+ --------
+ >>> x = np.array([1, 2, 4, 7, 0])
+ >>> np.ediff1d(x)
+ array([ 1., 2., 3., -7.])
+
+ >>> np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99]))
+ rray([-99., 1., 2., 3., -7., 88., 99.])
+
+ The returned array is always 1D.
+
+ >>> y = np.array([[1, 2, 4], [1, 6, 24]])
+ >>> np.ediff1d(y)
+ array([ 1., 2., -3., 5., 18.])
+
+ >>> np.ediff1d(x, to_begin=y)
+ array([ 1., 2., 4., 1., 6., 24., 1., 2., 3., -7.])
+ """
+ from ...numpy import ndarray as np_ndarray
+ input_type = (isinstance(to_begin, np_ndarray), isinstance(to_end, np_ndarray))
+ # case 1: when both `to_begin` and `to_end` are arrays
+ if input_type == (True, True):
+ return _npi.ediff1d(ary, to_begin, to_end, to_begin_arr_given=True, to_end_arr_given=True,
+ to_begin_scalar=None, to_end_scalar=None)
+ # case 2: only `to_end` is array but `to_begin` is scalar/None
+ elif input_type == (False, True):
+ return _npi.ediff1d(ary, to_end, to_begin_arr_given=False, to_end_arr_given=True,
+ to_begin_scalar=to_begin, to_end_scalar=None)
+ # case 3: only `to_begin` is array but `to_end` is scalar/None
+ elif input_type == (True, False):
+ return _npi.ediff1d(ary, to_begin, to_begin_arr_given=True, to_end_arr_given=False,
+ to_begin_scalar=None, to_end_scalar=to_end)
+ # case 4: both `to_begin` and `to_end` are scalar/None
+ else:
+ return _npi.ediff1d(ary, to_begin_arr_given=False, to_end_arr_given=False,
+ to_begin_scalar=to_begin, to_end_scalar=to_end)
+
+
 @set_module('mxnet.ndarray.numpy')
 def resize(a, new_shape):
  """

python/mxnet/numpy/multiarray.py

@@ -65,7 +65,7 @@
  'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad',
  'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal',
  'greater', 'less', 'greater_equal', 'less_equal', 'rot90', 'einsum', 'true_divide', 'nonzero',
- 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'resize', 'matmul',
+ 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'ediff1d', 'resize', 'matmul',
  'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite', 'polyval', 'where', 'bincount', 'pad']
 
 __all__ += fallback.__all__
@@ -8731,6 +8731,46 @@ def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable=redefin
  return _mx_nd_np.diff(a, n=n, axis=axis)
 
 
+@set_module('mxnet.numpy')
+def ediff1d(ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+
+ Parameters
+ ----------
+ ary : ndarray
+ If necessary, will be flattened before the differences are taken.
+ to_end : ndarray or scalar, optional
+ Number(s) to append at the end of the returned differences.
+ to_begin : ndarray or scalar, optional
+ Number(s) to prepend at the beginning of the returned differences.
+
+ Returns
+ -------
+ ediff1d : ndarray
+ The differences. Loosely, this is ``ary.flat[1:] - ary.flat[:-1]``.
+
+ Examples
+ --------
+ >>> x = np.array([1, 2, 4, 7, 0])
+ >>> np.ediff1d(x)
+ array([ 1., 2., 3., -7.])
+
+ >>> np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99]))
+ rray([-99., 1., 2., 3., -7., 88., 99.])
+
+ The returned array is always 1D.
+
+ >>> y = np.array([[1, 2, 4], [1, 6, 24]])
+ >>> np.ediff1d(y)
+ array([ 1., 2., -3., 5., 18.])
+
+ >>> np.ediff1d(x, to_begin=y)
+ array([ 1., 2., 4., 1., 6., 24., 1., 2., 3., -7.])
+ """
+ return _mx_nd_np.ediff1d(ary, to_end=to_end, to_begin=to_begin)
+
+
 @set_module('mxnet.numpy')
 def resize(a, new_shape):
  """

python/mxnet/numpy_dispatch_protocol.py

@@ -172,6 +172,7 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
  'quantile',
  'percentile',
  'diff',
+ 'ediff1d',
  'resize',
  'where',
  'full_like',

python/mxnet/symbol/numpy/_symbol.py

@@ -49,7 +49,7 @@
  'hypot', 'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm',
  'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
  'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'rot90', 'einsum',
- 'true_divide', 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff',
+ 'true_divide', 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'ediff1d',
  'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
  'where', 'bincount', 'pad']
 
@@ -6035,6 +6035,44 @@ def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable=redefin
  return _npi.diff(a, n=n, axis=axis)
 
 
+@set_module('mxnet.symbol.numpy')
+def ediff1d(ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+
+ Parameters
+ ----------
+ ary : _Symbol
+ If necessary, will be flattened before the differences are taken.
+ to_end : _Symbol or scalar, optional
+ Number(s) to append at the end of the returned differences.
+ to_begin : _Symbol or scalar, optional
+ Number(s) to prepend at the beginning of the returned differences.
+
+ Returns
+ -------
+ ediff1d : _Symbol
+ The differences. Loosely, this is ``ary.flat[1:] - ary.flat[:-1]``.
+ """
+ input_type = (isinstance(to_begin, _Symbol), isinstance(to_end, _Symbol))
+ # case 1: when both `to_begin` and `to_end` are arrays
+ if input_type == (True, True):
+ return _npi.ediff1d(ary, to_begin, to_end, to_begin_arr_given=True, to_end_arr_given=True,
+ to_begin_scalar=None, to_end_scalar=None)
+ # case 2: only `to_end` is array but `to_begin` is scalar/None
+ elif input_type == (False, True):
+ return _npi.ediff1d(ary, to_end, to_begin_arr_given=False, to_end_arr_given=True,
+ to_begin_scalar=to_begin, to_end_scalar=None)
+ # case 3: only `to_begin` is array but `to_end` is scalar/None
+ elif input_type == (True, False):
+ return _npi.ediff1d(ary, to_begin, to_begin_arr_given=True, to_end_arr_given=False,
+ to_begin_scalar=None, to_end_scalar=to_end)
+ # case 4: both `to_begin` and `to_end` are scalar/None
+ else:
+ return _npi.ediff1d(ary, to_begin_arr_given=False, to_end_arr_given=False,
+ to_begin_scalar=to_begin, to_end_scalar=to_end)
+
+
 @set_module('mxnet.symbol.numpy')
 def resize(a, new_shape):
  """

src/operator/numpy/np_diff.cc

@@ -43,8 +43,8 @@ inline TShape NumpyDiffShapeImpl(const TShape& ishape,
 }
 
 inline bool DiffShape(const nnvm::NodeAttrs& attrs,
-  std::vector<TShape>* in_attrs,
-  std::vector<TShape>* out_attrs) {
+ std::vector<TShape>* in_attrs,
+ std::vector<TShape>* out_attrs) {
  CHECK_EQ(in_attrs->size(), 1U);
  CHECK_EQ(out_attrs->size(), 1U);
  if (!shape_is_known(in_attrs->at(0))) {
@@ -57,8 +57,8 @@ inline bool DiffShape(const nnvm::NodeAttrs& attrs,
 }
 
 inline bool DiffType(const nnvm::NodeAttrs& attrs,
-  std::vector<int>* in_attrs,
-  std::vector<int>* out_attrs) {
+ std::vector<int>* in_attrs,
+ std::vector<int>* out_attrs) {
  CHECK_EQ(in_attrs->size(), 1U);
  CHECK_EQ(out_attrs->size(), 1U);