tpoisot/2Darray.py

## 2Darray.py
import numpy as np
import scipy as sp

from scipy.weave import inline

def along2Darray(rows,cols):
	arr = np.zeros((rows,cols))
	code = """
		int Pos;
		for(int Row = 0; Row < rows; Row++)
		{
			for(int Col = 0; Col < cols; Col++)
			{
				Pos = Row*cols + Col;
				arr[Pos] = Pos;
		return_val = 1;
	"""
	res = inline(code, ['arr','cols','rows'], headers = ['<math.h>'], compiler = 'gcc')
	return arr

newarr = along2Darray(10,10)

# Things to know
# 1 - Narr will have infos about the size of the array, so passing 'rows' and 'cols' is not necessary
# 2 - inline modifies the original array, so this is not a copy. Use np.copy if you want to keep the original array intact
# 3 - using the blitz library allows to of arr(Row,Col) instead of finding the position
	import numpy as np
	import scipy as sp

	from scipy.weave import inline

	def along2Darray(rows,cols):
	arr = np.zeros((rows,cols))
	code = """
	int Pos;
	for(int Row = 0; Row < rows; Row++)
	{
	for(int Col = 0; Col < cols; Col++)
	{
	Pos = Row*cols + Col;
	arr[Pos] = Pos;
	return_val = 1;
	"""
	res = inline(code, ['arr','cols','rows'], headers = ['<math.h>'], compiler = 'gcc')
	return arr

	newarr = along2Darray(10,10)

	# Things to know
	# 1 - Narr will have infos about the size of the array, so passing 'rows' and 'cols' is not necessary
	# 2 - inline modifies the original array, so this is not a copy. Use np.copy if you want to keep the original array intact
	# 3 - using the blitz library allows to of arr(Row,Col) instead of finding the position