On 2012-09-21 00:35, giuseppe.amatu...@gmail.com wrote:
Hi Ian and MRAB
thanks to you input i have improve the speed of my code. Definitely reading in
dic() is faster. I have one more question.
In the dic() I calculate the sum of the values, but i want count also the
number of observation, in
Hi Ian and MRAB
thanks to you input i have improve the speed of my code. Definitely reading in
dic() is faster. I have one more question.
In the dic() I calculate the sum of the values, but i want count also the
number of observation, in order to calculate the average in the end.
Should i creat
On Thu, Sep 20, 2012 at 1:28 PM, Ian Kelly wrote:
> Expanding on what MRAB wrote, since you probably have far fewer
> categories than pixels, you may be able to take better advantage of
> numpy's vectorized operations (which are pretty much the whole point
> of using numpy in the first place) by l
On Thu, Sep 20, 2012 at 1:09 PM, MRAB wrote:
> for col in range(cols):
> for row in range(rows):
> cat = valuesCategory[row, col]
> ras = valuesRaster[row, col]
> totals[cat] += ras
Expanding on what MRAB wrote, since you probably have far fewer
categories than pixels,
On 2012-09-20 19:31, giuseppe.amatu...@gmail.com wrote:
Hi,
I have this script in python that i need to apply for very large arrays (arrays
coming from satellite images).
The script works grate but i would like to speed up the process.
The larger computational time is in the for loop process.
Is
Hi,
I have this script in python that i need to apply for very large arrays (arrays
coming from satellite images).
The script works grate but i would like to speed up the process.
The larger computational time is in the for loop process.
Is there is a way to improve that part?
Should be better
