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other:python:jyp_steps [2016/01/29 15:41] jypeter Added the numpy for matlab users references |
other:python:jyp_steps [2016/02/09 15:32] jypeter Added the views side effect section |
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Where: [[http://docs.scipy.org/doc/|html and pdf documentation]] | Where: [[http://docs.scipy.org/doc/|html and pdf documentation]] | ||
- | How to get started? | + | ==== Getting started ==== |
- always remember that indices start at ''0'' and that the last element of an array is at index ''-1''!\\ First learn about //indexing// and //slicing// by manipulating strings, as shown in [[#part1|Part 1]] above (try '''This document by JY is awesome!'[::-1]'' and '''This document by JY is awesome!'[slice(None, None, -1)]'') 8-) | - always remember that indices start at ''0'' and that the last element of an array is at index ''-1''!\\ First learn about //indexing// and //slicing// by manipulating strings, as shown in [[#part1|Part 1]] above (try '''This document by JY is awesome!'[::-1]'' and '''This document by JY is awesome!'[slice(None, None, -1)]'') 8-) | ||
- if you are a Matlab user (but the references are interesting for others as well), you can read the following: | - if you are a Matlab user (but the references are interesting for others as well), you can read the following: | ||
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- Numpy Reference Guide | - Numpy Reference Guide | ||
- Scipy Reference Guide | - Scipy Reference Guide | ||
+ | |||
+ | ==== Beware of the array view side effects ==== | ||
+ | |||
+ | <note warning>When you take a slice of an array, you get a **//View//** : an array that has a new shape but that still shares its data with the first array. | ||
+ | |||
+ | That is not a problem when you only read the values, but **if you change the values of the //View//, you change the values of the first array** (and vice-versa)! If that is not what want, do not forget to **make a copy** of the data before working on it! | ||
+ | |||
+ | //Views// are a good thing most of the time, so only make a copy of your data when needed, because otherwise copying a big array will just be a waste of CPU and computer memory. Anyway, it is always better to understand what you are doing... :-P | ||
+ | |||
+ | Check the example below and the [[https://docs.scipy.org/doc/numpy-dev/user/quickstart.html#copies-and-views|copies and views]] part of the quickstart tutorial. | ||
+ | |||
+ | <code python> | ||
+ | >>> import numpy as np | ||
+ | >>> a = np.arange(30).reshape((3,10)) | ||
+ | >>> a | ||
+ | array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], | ||
+ | [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], | ||
+ | [20, 21, 22, 23, 24, 25, 26, 27, 28, 29]]) | ||
+ | |||
+ | >>> b = a[1, :] | ||
+ | >>> b | ||
+ | array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]) | ||
+ | |||
+ | >>> b[3:7] = 0 | ||
+ | >>> b | ||
+ | array([10, 11, 12, 0, 0, 0, 0, 17, 18, 19]) | ||
+ | |||
+ | >>> a | ||
+ | array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], | ||
+ | [10, 11, 12, 0, 0, 0, 0, 17, 18, 19], | ||
+ | [20, 21, 22, 23, 24, 25, 26, 27, 28, 29]]) | ||
+ | |||
+ | >>> a[:, 2:4] = -1 | ||
+ | >>> a | ||
+ | array([[ 0, 1, -1, -1, 4, 5, 6, 7, 8, 9], | ||
+ | [10, 11, -1, -1, 0, 0, 0, 17, 18, 19], | ||
+ | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
+ | |||
+ | >>> b | ||
+ | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
+ | |||
+ | >>> c = a[1, :].copy() | ||
+ | >>> c | ||
+ | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
+ | |||
+ | >>> c[:] = 9 | ||
+ | >>> c | ||
+ | array([9, 9, 9, 9, 9, 9, 9, 9, 9, 9]) | ||
+ | |||
+ | >>> b | ||
+ | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
+ | |||
+ | >>> a | ||
+ | array([[ 0, 1, -1, -1, 4, 5, 6, 7, 8, 9], | ||
+ | [10, 11, -1, -1, 0, 0, 0, 17, 18, 19], | ||
+ | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
+ | </code></note> | ||
===== cdms2 and netCDF4 ===== | ===== cdms2 and netCDF4 ===== |