Python科学计算入门与NumPy、Matplotlib教程

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本资源名为《PythonScientific.pdf》，是一份针对科学计算领域设计的Python教程讲义，由EuroSciPy团队编著，发布于2012年。作者包括Valentin Haenel、Emmanuelle Gouillart和Gaël Varoquaux，其目标是帮助科学家们利用Python进行高效的科研工作。该讲义分为五个主要部分： 1. **入门与工作流**：首先介绍了为何选择Python作为科学计算工具，强调了其易学、高效和丰富的库支持。讲解了Python的基本构建模块，如交互式工作流程，通过IPython和文本编辑器实现数据处理和分析。 2. **Python语言基础**：深入解析了Python语法，包括基本步骤、数据类型（如数字、字符串和列表）、赋值操作、控制流语句（if-else、for和while）、函数定义、代码重用（脚本和模块）以及输入输出处理和标准库的使用。还涉及了异常处理和面向对象编程（OOP）的概念。 3. **NumPy：数值数据处理**：核心内容是NumPy库，它提供了强大的数组对象（numpy.array），并演示了如何执行数值运算、创建和操作更复杂的数组。这部分还包括高级操作技巧。 4. **获取帮助与查找文档**：这部分教导读者如何有效地寻求Python和相关库的帮助，以及如何查找和理解官方文档，以便在遇到问题时能迅速找到解决方案。 5. **Matplotlib**：作为数据可视化的重要工具，讲解了Matplotlib的介绍、与IPython的集成、绘制简单图形的方法，以及如何设置图形属性和添加文本元素。这份讲义覆盖了Python在科学计算中的基础知识，适合对Python感兴趣或已在使用但希望进一步提升技能的科研人员，无论是初学者还是有一定经验的开发者，都能从中获得实用的指导和技巧。通过学习，读者可以更好地利用Python进行数据分析、可视化和实验过程中的各种计算任务。

Python Scientiﬁc lecture notes, Release 2012.2

In [1]: import demo

In [2]: demo.print_a()

In [3]: demo.print_b()

Importing the module gives access to its objects, using the module.object syntax. Don’t forget to put the

module’s name before the object’s name, otherwise Python won’t recognize the instruction.

Introspection

In [4]: demo ?

Type: module

Base Class: <type ’module’>

String Form: <module ’demo’ from ’demo.py’>

Namespace: Interactive

File: /home/varoquau/Projects/Python_talks/scipy_2009_tutorial/source/demo.py

Docstring:

A demo module.

In [5]: who

demo

In [6]: whos

Variable Type Data/Info

------------------------------

demo module <module ’demo’ from ’demo.py’>

In [7]: dir(demo)

Out[7]:

[’__builtins__’,

’__doc__’,

’__file__’,

’__name__’,

’__package__’,

’c’,

’d’,

’print_a’,

’print_b’]

In [8]: demo.

demo.__builtins__ demo.__init__ demo.__str__

demo.__class__ demo.__name__ demo.__subclasshook__

demo.__delattr__ demo.__new__ demo.c

demo.__dict__ demo.__package__ demo.d

demo.__doc__ demo.__reduce__ demo.print_a

demo.__file__ demo.__reduce_ex__ demo.print_b

demo.__format__ demo.__repr__ demo.py

demo.__getattribute__ demo.__setattr__ demo.pyc

demo.__hash__ demo.__sizeof__

Importing objects from modules into the main namespace

In [9]: from demo import print_a, print_b

In [10]: whos

Variable Type Data/Info

--------------------------------

2.6. Reusing code: scripts and modules 27

Python Scientiﬁc lecture notes, Release 2012.2

demo module <module ’demo’ from ’demo.py’>

print_a function <function print_a at 0xb7421534>

print_b function <function print_b at 0xb74214c4>

In [11]: print_a()

Warning: Module caching

Modules are cached: if you modify demo.py and re-import it in the old session, you will get the

old one.

Solution:

In [10]: reload(demo)

2.6.4 ‘__main__’ and module loading

File demo2.py:

import sys

def print_a():

"Prints a."

print ’a’

print sys.argv

if __name__ == ’__main__’:

print_a()

Importing it:

In [11]: import demo2

In [12]: import demo2

Running it:

In [13]: %run demo2

2.6.5 Scripts or modules? How to organize your code

Note: Rule of thumb

• Sets of instructions that are called several times should be written inside functions for better code reusability.

• Functions (or other bits of code) that are called from several scripts should be written inside a module,

so that only the module is imported in the different scripts (do not copy-and-paste your functions in the

different scripts!).

Note: How to import a module from a remote directory?

Many solutions exist, depending mainly on your operating system. When the import mymodule statement is

executed, the module mymodule is searched in a given list of directories. This list includes a list of installation-

dependent default path (e.g., /usr/lib/python) as well as the list of directories speciﬁed by the environment

variable PYTHONPATH.

2.6. Reusing code: scripts and modules 28

Python Scientiﬁc lecture notes, Release 2012.2

The list of directories searched by Python is given by the sys.path variable

In [1]: import sys

In [2]: sys.path

Out[2]:

[’’,

’/usr/bin’,

’/usr/local/include/enthought.traits-1.1.0’,

’/usr/lib/python2.6’,

’/usr/lib/python2.6/plat-linux2’,

’/usr/lib/python2.6/lib-tk’,

’/usr/lib/python2.6/lib-old’,

’/usr/lib/python2.6/lib-dynload’,

’/usr/lib/python2.6/dist-packages’,

’/usr/lib/pymodules/python2.6’,

’/usr/lib/pymodules/python2.6/gtk-2.0’,

’/usr/lib/python2.6/dist-packages/wx-2.8-gtk2-unicode’,

’/usr/local/lib/python2.6/dist-packages’,

’/usr/lib/python2.6/dist-packages’,

’/usr/lib/pymodules/python2.6/IPython/Extensions’,

u’/home/gouillar/.ipython’]

Modules must be located in the search path, therefore you can:

• write your own modules within directories already deﬁned in the search path (e.g.

‘/usr/local/lib/python2.6/dist-packages’). You may use symbolic links (on Linux) to keep the code

somewhere else.

• modify the environment variable PYTHONPATH to include the directories containing the user-deﬁned

modules. On Linux/Unix, add the following line to a ﬁle read by the shell at startup (e.g. /etc/proﬁle,

.proﬁle)

export PYTHONPATH=$PYTHONPATH:/home/emma/user_defined_modules

On Windows, http://support.microsoft.com/kb/310519 explains how to handle environment variables.

• or modify the sys.path variable itself within a Python script.

import sys

new_path = ’/home/emma/user_defined_modules’

if new_path not in sys.path:

sys.path.append(new_path)

This method is not very robust, however, because it makes the code less portable (user-dependent path) and because

you have to add the directory to your sys.path each time you want to import from a module in this directory.

See http://docs.python.org/tutorial/modules.html for more information about modules.

2.6.6 Packages

A directory that contains many modules is called a package. A package is a module with submodules (which can

have submodules themselves, etc.). A special ﬁle called __init__.py (which may be empty) tells Python that

the directory is a Python package, from which modules can be imported.

sd-2116 /usr/lib/python2.6/dist-packages/scipy $ ls

[17:07]

cluster/ io/ README.txt@ stsci/

__config__.py@ LATEST.txt@ setup.py@ __svn_version__.py@

__config__.pyc lib/ setup.pyc __svn_version__.pyc

constants/ linalg/ setupscons.py@ THANKS.txt@

fftpack/ linsolve/ setupscons.pyc TOCHANGE.txt@

__init__.py@ maxentropy/ signal/ version.py@

2.6. Reusing code: scripts and modules 29

Python Scientiﬁc lecture notes, Release 2012.2

__init__.pyc misc/ sparse/ version.pyc

INSTALL.txt@ ndimage/ spatial/ weave/

integrate/ odr/ special/

interpolate/ optimize/ stats/

sd-2116 /usr/lib/python2.6/dist-packages/scipy $ cd ndimage

[17:07]

sd-2116 /usr/lib/python2.6/dist-packages/scipy/ndimage $ ls

[17:07]

doccer.py@ fourier.pyc interpolation.py@ morphology.pyc setup.pyc

doccer.pyc info.py@ interpolation.pyc _nd_image.so

setupscons.py@

filters.py@ info.pyc measurements.py@ _ni_support.py@

setupscons.pyc

filters.pyc __init__.py@ measurements.pyc _ni_support.pyc tests/

fourier.py@ __init__.pyc morphology.py@ setup.py@

From Ipython:

In [1]: import scipy

In [2]: scipy.__file__

Out[2]: ’/usr/lib/python2.6/dist-packages/scipy/__init__.pyc’

In [3]: import scipy.version

In [4]: scipy.version.version

Out[4]: ’0.7.0’

In [5]: import scipy.ndimage.morphology

In [6]: from scipy.ndimage import morphology

In [17]: morphology.binary_dilation ?

Type: function

Base Class: <type ’function’>

String Form: <function binary_dilation at 0x9bedd84>

Namespace: Interactive

File: /usr/lib/python2.6/dist-packages/scipy/ndimage/morphology.py

Definition: morphology.binary_dilation(input, structure=None,

iterations=1, mask=None, output=None, border_value=0, origin=0,

brute_force=False)

Docstring:

Multi-dimensional binary dilation with the given structure.

An output array can optionally be provided. The origin parameter

controls the placement of the filter. If no structuring element is

provided an element is generated with a squared connectivity equal

to one. The dilation operation is repeated iterations times. If

iterations is less than 1, the dilation is repeated until the

result does not change anymore. If a mask is given, only those

elements with a true value at the corresponding mask element are

modified at each iteration.

2.6.7 Good practices

Note: Good practices

• Indentation: no choice!

Indenting is compulsory in Python. Every commands block following a colon bears an additional indentation level

2.6. Reusing code: scripts and modules 30

Python Scientiﬁc lecture notes, Release 2012.2

with respect to the previous line with a colon. One must therefore indent after def f(): or while:. At the

end of such logical blocks, one decreases the indentation depth (and re-increases it if a new block is entered, etc.)

Strict respect of indentation is the price to pay for getting rid of { or ; characters that delineate logical blocks in

other languages. Improper indentation leads to errors such as

------------------------------------------------------------

IndentationError: unexpected indent (test.py, line 2)

All this indentation business can be a bit confusing in the beginning. However, with the clear indentation, and in

the absence of extra characters, the resulting code is very nice to read compared to other languages.

• Indentation depth:

Inside your text editor, you may choose to indent with any positive number of spaces (1, 2, 3, 4, ...). However,

it is considered good practice to indent with 4 spaces. You may conﬁgure your editor to map the Tab key to a

4-space indentation. In Python(x,y), the editor Scite is already conﬁgured this way.

• Style guidelines

Long lines: you should not write very long lines that span over more than (e.g.) 80 characters. Long lines can be

broken with the \ character

>>> long_line = "Here is a very very long line \

... that we break in two parts."

Spaces

Write well-spaced code: put whitespaces after commas, around arithmetic operators, etc.:

>>> a = 1 # yes

>>> a=1 # too cramped

A certain number of rules for writing “beautiful” code (and more importantly using the same conventions as

anybody else!) are given in the Style Guide for Python Code.

• Use meaningful object names

2.7 Input and Output

To be exhaustive, here are some information about input and output in Python. Since we will use the Numpy

methods to read and write ﬁles, you may skip this chapter at ﬁrst reading.

We write or read strings to/from ﬁles (other types must be converted to strings). To write in a ﬁle:

>>> f = open(’workfile’, ’w’) # opens the workfile file

>>> type(f)

>>> f.write(’This is a test \nand another test’)

>>> f.close()

To read from a ﬁle

In [1]: f = open(’workfile’, ’r’)

In [2]: s = f.read()

In [3]: print(s)

This is a test

and another test

In [4]: f.close()

For more details: http://docs.python.org/tutorial/inputoutput.html

2.7. Input and Output 31

Python Scientiﬁc lecture notes, Release 2012.2

2.7.1 Iterating over a ﬁle

In [6]: f = open(’workfile’, ’r’)

In [7]: for line in f:

...: print line

...:

This is a test

and another test

In [8]: f.close()

File modes

• Read-only: r

• Write-only: w

– Note: Create a new ﬁle or overwrite existing ﬁle.

• Append a ﬁle: a

• Read and Write: r+

• Binary mode: b

– Note: Use for binary ﬁles, especially on Windows.

2.8 Standard Library

Note: Reference document for this section:

• The Python Standard Library documentation: http://docs.python.org/library/index.html

• Python Essential Reference, David Beazley, Addison-Wesley Professional

2.8.1 os module: operating system functionality

“A portable way of using operating system dependent functionality.”

Directory and ﬁle manipulation

Current directory:

In [17]: os.getcwd()

Out[17]: ’/Users/cburns/src/scipy2009/scipy_2009_tutorial/source’

List a directory:

In [31]: os.listdir(os.curdir)

Out[31]:

[’.index.rst.swo’,

’.python_language.rst.swp’,

’.view_array.py.swp’,

’_static’,

’_templates’,

’basic_types.rst’,

2.8. Standard Library 32

Python Scientiﬁc lecture notes, Release 2012.2

’conf.py’,

’control_flow.rst’,

’debugging.rst’,

...

Make a directory:

In [32]: os.mkdir(’junkdir’)

In [33]: ’junkdir’ in os.listdir(os.curdir)

Out[33]: True

Rename the directory:

In [36]: os.rename(’junkdir’, ’foodir’)

In [37]: ’junkdir’ in os.listdir(os.curdir)

Out[37]: False

In [38]: ’foodir’ in os.listdir(os.curdir)

Out[38]: True

In [41]: os.rmdir(’foodir’)

In [42]: ’foodir’ in os.listdir(os.curdir)

Out[42]: False

Delete a ﬁle:

In [44]: fp = open(’junk.txt’, ’w’)

In [45]: fp.close()

In [46]: ’junk.txt’ in os.listdir(os.curdir)

Out[46]: True

In [47]: os.remove(’junk.txt’)

In [48]: ’junk.txt’ in os.listdir(os.curdir)

Out[48]: False

os.path: path manipulations

os.path provides common operations on pathnames.

In [70]: fp = open(’junk.txt’, ’w’)

In [71]: fp.close()

In [72]: a = os.path.abspath(’junk.txt’)

In [73]: a

Out[73]: ’/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/junk.txt’

In [74]: os.path.split(a)

Out[74]: (’/Users/cburns/src/scipy2009/scipy_2009_tutorial/source’,

’junk.txt’)

In [78]: os.path.dirname(a)

Out[78]: ’/Users/cburns/src/scipy2009/scipy_2009_tutorial/source’

In [79]: os.path.basename(a)

Out[79]: ’junk.txt’

2.8. Standard Library 33

Python Scientiﬁc lecture notes, Release 2012.2

In [80]: os.path.splitext(os.path.basename(a))

Out[80]: (’junk’, ’.txt’)

In [84]: os.path.exists(’junk.txt’)

Out[84]: True

In [86]: os.path.isfile(’junk.txt’)

Out[86]: True

In [87]: os.path.isdir(’junk.txt’)

Out[87]: False

In [88]: os.path.expanduser(’~/local’)

Out[88]: ’/Users/cburns/local’

In [92]: os.path.join(os.path.expanduser(’~’), ’local’, ’bin’)

Out[92]: ’/Users/cburns/local/bin’

Running an external command

In [8]: os.system(’ls

’)

conf.py debug_file.py demo2.py~ demo.py demo.pyc my_file.py~

conf.py~ demo2.py demo2.pyc demo.py~ my_file.py pi_wallis_image.py

Walking a directory

os.path.walk generates a list of ﬁlenames in a directory tree.

In [10]: for dirpath, dirnames, filenames in os.walk(os.curdir):

....: for fp in filenames:

....: print os.path.abspath(fp)

....:

/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/.index.rst.swo

/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/.view_array.py.swp

/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/basic_types.rst

/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/conf.py

/Users/cburns/src/scipy2009/scipy_2009_tutorial/source/control_flow.rst

...

Environment variables:

In [9]: import os

In [11]: os.environ.keys()

Out[11]:

[’_’,

’FSLDIR’,

’TERM_PROGRAM_VERSION’,

’FSLREMOTECALL’,

’USER’,

’HOME’,

’PATH’,

’PS1’,

’SHELL’,

’EDITOR’,

’WORKON_HOME’,

’PYTHONPATH’,

2.8. Standard Library 34

Python Scientiﬁc lecture notes, Release 2012.2

...

In [12]: os.environ[’PYTHONPATH’]

Out[12]: ’.:/Users/cburns/src/utils:/Users/cburns/src/nitools:

/Users/cburns/local/lib/python2.5/site-packages/:

/usr/local/lib/python2.5/site-packages/:

/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5’

In [16]: os.getenv(’PYTHONPATH’)

Out[16]: ’.:/Users/cburns/src/utils:/Users/cburns/src/nitools:

/Users/cburns/local/lib/python2.5/site-packages/:

/usr/local/lib/python2.5/site-packages/:

/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5’

2.8.2 shutil: high-level ﬁle operations

The shutil provides useful ﬁle operations:

• shutil.rmtree: Recursively delete a directory tree.

• shutil.move: Recursively move a ﬁle or directory to another location.

• shutil.copy: Copy ﬁles or directories.

2.8.3 glob: Pattern matching on ﬁles

The glob module provides convenient ﬁle pattern matching.

Find all ﬁles ending in .txt:

In [18]: import glob

In [19]: glob.glob(’

.txt’)

Out[19]: [’holy_grail.txt’, ’junk.txt’, ’newfile.txt’]

2.8.4 sys module: system-speciﬁc information

System-speciﬁc information related to the Python interpreter.

• Which version of python are you running and where is it installed:

In [117]: sys.platform

Out[117]: ’darwin’

In [118]: sys.version

Out[118]: ’2.5.2 (r252:60911, Feb 22 2008, 07:57:53) \n

[GCC 4.0.1 (Apple Computer, Inc. build 5363)]’

In [119]: sys.prefix

Out[119]: ’/Library/Frameworks/Python.framework/Versions/2.5’

• List of command line arguments passed to a Python script:

In [100]: sys.argv

Out[100]: [’/Users/cburns/local/bin/ipython’]

sys.path is a list of strings that speciﬁes the search path for modules. Initialized from PYTHONPATH:

In [121]: sys.path

Out[121]:

[’’,

2.8. Standard Library 35

Python Scientiﬁc lecture notes, Release 2012.2

’/Users/cburns/local/bin’,

’/Users/cburns/local/lib/python2.5/site-packages/grin-1.1-py2.5.egg’,

’/Users/cburns/local/lib/python2.5/site-packages/argparse-0.8.0-py2.5.egg’,

’/Users/cburns/local/lib/python2.5/site-packages/urwid-0.9.7.1-py2.5.egg’,

’/Users/cburns/local/lib/python2.5/site-packages/yolk-0.4.1-py2.5.egg’,

’/Users/cburns/local/lib/python2.5/site-packages/virtualenv-1.2-py2.5.egg’,

...

2.8.5 pickle: easy persistence

Useful to store arbitrary objects to a ﬁle. Not safe or fast!

In [1]: import pickle

In [2]: l = [1, None, ’Stan’]

In [3]: pickle.dump(l, file(’test.pkl’, ’w’))

In [4]: pickle.load(file(’test.pkl’))

Out[4]: [1, None, ’Stan’]

Exercise

Write a program to search your PYTHONPATH for the module site.py.

path_site

2.9 Exception handling in Python

It is highly unlikely that you haven’t yet raised Exceptions if you have typed all the previous commands of the

tutorial. For example, you may have raised an exception if you entered a command with a typo.

Exceptions are raised by different kinds of errors arising when executing Python code. In your own code, you may

also catch errors, or deﬁne custom error types.

2.9.1 Exceptions

Exceptions are raised by errors in Python:

In [1]: 1/0

---------------------------------------------------------------------------

ZeroDivisionError: integer division or modulo by zero

In [2]: 1 + ’e’

---------------------------------------------------------------------------

TypeError: unsupported operand type(s) for +: ’int’ and ’str’

In [3]: d = {1:1, 2:2}

In [4]: d[3]

---------------------------------------------------------------------------

KeyError: 3

In [5]: l = [1, 2, 3]

In [6]: l[4]

---------------------------------------------------------------------------

2.9. Exception handling in Python 36

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