# Jose Antonio Martin H.
# jamartinh <AT> fdi(DOT)ucm(DOT)es
# 29-Dec-2007

from numpy import *

def ndtuples(*dims):
   """Fast implementation of array(list(ndindex(*dims))).
	from an email from Jonathan Taylor
   """

   # Need a list because we will go through it in reverse popping
   # off the size of the last dimension.
   dims = list(dims)

   # N will keep track of the current length of the indices.
   N = dims.pop()

   # At the beginning the current list of indices just ranges over the
   # last dimension.
   cur = arange(N)
   cur = cur[:,newaxis]

   while dims != []:

       d = dims.pop()

       # This repeats the current set of indices d times.
       # e.g. [0,1,2] -> [0,1,2,0,1,2,...,0,1,2]
       cur = kron(ones((d,1)),cur)

       # This ranges over the new dimension and 'stretches' it by N.
       # e.g. [0,1,2] -> [0,0,...,0,1,1,...,1,2,2,...,2]
       front = arange(d).repeat(N)[:,newaxis]

       # This puts these two together.
       cur = column_stack((front,cur))
       N *= d

   return cur
    
def ndlinspace(input_ranges,nelems):
    """ ndlinspace: n-dimensional linspace function
        input_ranges = [[-1,1],[-0.07,0.07]]
        nelems = (5,5)
    """
    
    #x = array(list(ndindex(*nelems)),float)+1.0
    x = ndtuples(*nelems)+1.0
    
    lbounds = []
    ubounds = []
    from_b  = array(nelems,float)
    for r in input_ranges:
        lbounds.append(r[0])
        ubounds.append(r[1])
        
        
    lbounds = array(lbounds,float)
    ubounds = array(ubounds,float)

    y = (lbounds) + (((x-1)/(from_b-1))*((ubounds)-(lbounds)))

    
    return y    

input_ranges = [[-1,1],[-0.07,0.07]]
nelems = (5,5)
b = ndlinspace(input_ranges,nelems)
print b

# result
##[[-1.    -0.07 ]
## [-1.    -0.035]
## [-1.     0.   ]
## [-1.     0.035]
## [-1.     0.07 ]
## [-0.5   -0.07 ]
## [-0.5   -0.035]
## [-0.5    0.   ]
## [-0.5    0.035]
## [-0.5    0.07 ]
## [ 0.    -0.07 ]
## [ 0.    -0.035]
## [ 0.     0.   ]
## [ 0.     0.035]
## [ 0.     0.07 ]
## [ 0.5   -0.07 ]
## [ 0.5   -0.035]
## [ 0.5    0.   ]
## [ 0.5    0.035]
## [ 0.5    0.07 ]
## [ 1.    -0.07 ]
## [ 1.    -0.035]
## [ 1.     0.   ]
## [ 1.     0.035]
## [ 1.     0.07 ]]