Hi,
I've just whipped up my first cython-based code to try and speed up
some operations on some numpy-based code I'm writing. It works, but
I'd like to know how to make it go faster. It basically does something
like bincount (though bincount does not appear to work on more than
1-dimension).
I've looked at the resulting C code and cannot understand why (in some
cases) there are still some pythonic calls being made. Any help would
be appreciated. Some questions are in the code (and yes, it assumes
that bounds checking is done before the call)
import numpy as np
cimport numpy as np
cimport cython
@cython.boundscheck(False) # turn of bounds-checking for entire function
def table_bincount(int max_elements, np.ndarray[long, ndim=2] table):
cdef long rows = table.shape[0]
cdef long columns = table.shape[1]
cdef long i, j
cdef np.ndarray[double, ndim=2] retval = np.zeros(
(rows, max_elements), dtype=np.float64)
for 0 <= i < rows:
# Is there any way of typing these intermediate values so that they
# do not get turned into python code?
current_in_row = table[i]
current_out_row = retval[i]
for 0 <= j < columns:
current_out_row[current_in_row[j]] += 1
# Notice that even if do this instead :
# retval[i][table[i, j]] += 1
# ... it still generates some pythonic stuff like
# PyNumberAddInplace
return retval
Thanks in advance,
Brett Calcott
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