#
# Created: 20140207
# Wirawan Purwanto
#

"""
wpylib.array_tools

Various tools for arrays (mainly, numpy array objects).

"""

import numpy

def array_indices_cond_1d(arr, cond):
  """Get the ordered list of array indices whose corresponding elements satisfy
  a given condition.
  Useful for conditional assignment or evaluation.

  The input `cond' argument can be an ufunc-like function that evaluates
  a logical expression in bulk for each of the arr's element.
  Or it can be an array of logical values that has the same length as arr.

  Example use case:

     r = numpy.linspace(1.97, 3.5, num=150)
     i_select = cond_indices_1d(r, r <= 2.5)
     # ... then we can do something with r[i_select]
     # for conditional assignment or value extraction.
  """
  arr = numpy.asarray(arr)
  assert len(arr.shape) == 1

  if callable(cond):
    cond = cond(arr)
  # otherwise, assume cond is already a good array
  return numpy.array(xrange(len(arr)))[ cond ]


def array_hstack(arrays):
  """Creates a 2D array by horizontally stacking many arrays together
  (along the array's second dimension).
  Each of the input arrays can be a 1D or 2D array.
  This function is similar to numpy.hstack.
  """
  from numpy import asarray, hstack
  stk = []

  for a1 in arrays:
    a = asarray(a1)
    dim = len(a.shape)
    if dim == 1:
      a = a.reshape((len(a),1))
    elif dim == 2:
      pass
    else:
      raise ValueError, "Won't take 3D, 4D, ... arrays"

    stk.append(a)

  return hstack(stk)


def array_vstack(arrays):
  """Creates a 2D array by vertically stacking many arrays together
  (along the array's first dimension).
  Each of the input arrays can be a 1D or 2D array.
  This function is similar to numpy.vstack.
  """
  from numpy import asarray, vstack
  stk = []

  for a1 in arrays:
    a = asarray(a1)
    dim = len(a.shape)
    if dim == 1:
      a = a.reshape((1,len(a)))
    elif dim == 2:
      pass
    else:
      raise ValueError, "Won't take 3D, 4D, ... arrays"

    stk.append(a)

  return vstack(stk)