parameters: (a, axis=None, out=None, keepdims=np._NoValue, *, where=np._NoValue)
return_statement: return _wrapreduction(a, np.logical_and, 'all', axis, None, out,
                            keepdims=keepdims, where=where)
docstring: Test whether all array elements along a given axis evaluate to True.
  
      Parameters
      ----------
      a : array_like
          Input array or object that can be converted to an array.
      axis : None or int or tuple of ints, optional
          Axis or axes along which a logical AND reduction is performed.
          The default (``axis=None``) is to perform a logical AND over all
          the dimensions of the input array. `axis` may be negative, in
          which case it counts from the last to the first axis.
  
          .. versionadded:: 1.7.0
  
          If this is a tuple of ints, a reduction is performed on multiple
          axes, instead of a single axis or all the axes as before.
      out : ndarray, optional
          Alternate output array in which to place the result.
          It must have the same shape as the expected output and its
          type is preserved (e.g., if ``dtype(out)`` is float, the result
          will consist of 0.0's and 1.0's). See :ref:`ufuncs-output-type` for more
          details.
  
      keepdims : bool, optional
          If this is set to True, the axes which are reduced are left
          in the result as dimensions with size one. With this option,
          the result will broadcast correctly against the input array.
  
          If the default value is passed, then `keepdims` will not be
          passed through to the `all` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
  
      where : array_like of bool, optional
          Elements to include in checking for all `True` values.
          See `~numpy.ufunc.reduce` for details.
  
          .. versionadded:: 1.20.0
  
      Returns
      -------
      all : ndarray, bool
          A new boolean or array is returned unless `out` is specified,
          in which case a reference to `out` is returned.
  
      See Also
      --------
      ndarray.all : equivalent method
  
      any : Test whether any element along a given axis evaluates to True.
  
      Notes
      -----
      Not a Number (NaN), positive infinity and negative infinity
      evaluate to `True` because these are not equal to zero.
  
      Examples
      --------
      >>> np.all([[True,False],[True,True]])
      False
  
      >>> np.all([[True,False],[True,True]], axis=0)
      array([ True, False])
  
      >>> np.all([-1, 4, 5])
      True
  
      >>> np.all([1.0, np.nan])
      True
  
      >>> np.all([[True, True], [False, True]], where=[[True], [False]])
      True
  
      >>> o=np.array(False)
      >>> z=np.all([-1, 4, 5], out=o)
      >>> id(z), id(o), z
      (28293632, 28293632, array(True)) # may vary
docstring_summary: Test whether all array elements along a given axis evaluate to True.
docstring_tokens: Test whether all array elements along a given axis evaluate to True .
function: def all(a, axis=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):
      """
      Test whether all array elements along a given axis evaluate to True.
  
      Parameters
      ----------
      a : array_like
          Input array or object that can be converted to an array.
      axis : None or int or tuple of ints, optional
          Axis or axes along which a logical AND reduction is performed.
          The default (``axis=None``) is to perform a logical AND over all
          the dimensions of the input array. `axis` may be negative, in
          which case it counts from the last to the first axis.
  
          .. versionadded:: 1.7.0
  
          If this is a tuple of ints, a reduction is performed on multiple
          axes, instead of a single axis or all the axes as before.
      out : ndarray, optional
          Alternate output array in which to place the result.
          It must have the same shape as the expected output and its
          type is preserved (e.g., if ``dtype(out)`` is float, the result
          will consist of 0.0's and 1.0's). See :ref:`ufuncs-output-type` for more
          details.
  
      keepdims : bool, optional
          If this is set to True, the axes which are reduced are left
          in the result as dimensions with size one. With this option,
          the result will broadcast correctly against the input array.
  
          If the default value is passed, then `keepdims` will not be
          passed through to the `all` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
  
      where : array_like of bool, optional
          Elements to include in checking for all `True` values.
          See `~numpy.ufunc.reduce` for details.
  
          .. versionadded:: 1.20.0
  
      Returns
      -------
      all : ndarray, bool
          A new boolean or array is returned unless `out` is specified,
          in which case a reference to `out` is returned.
  
      See Also
      --------
      ndarray.all : equivalent method
  
      any : Test whether any element along a given axis evaluates to True.
  
      Notes
      -----
      Not a Number (NaN), positive infinity and negative infinity
      evaluate to `True` because these are not equal to zero.
  
      Examples
      --------
      >>> np.all([[True,False],[True,True]])
      False
  
      >>> np.all([[True,False],[True,True]], axis=0)
      array([ True, False])
  
      >>> np.all([-1, 4, 5])
      True
  
      >>> np.all([1.0, np.nan])
      True
  
      >>> np.all([[True, True], [False, True]], where=[[True], [False]])
      True
  
      >>> o=np.array(False)
      >>> z=np.all([-1, 4, 5], out=o)
      >>> id(z), id(o), z
      (28293632, 28293632, array(True)) # may vary
  
      """
      return _wrapreduction(a, np.logical_and, 'all', axis, None, out,
                            keepdims=keepdims, where=where)
function_tokens: def all ( a , axis = None , out = None , keepdims = np . _NoValue , * , where = np . _NoValue ) : return _wrapreduction ( a , np . logical_and , 'all' , axis , None , out , keepdims = keepdims , where = where )