diff --git a/.gitignore b/.gitignore deleted file mode 100644 index 0a33c14..0000000 --- a/.gitignore +++ /dev/null @@ -1,10 +0,0 @@ -# ignore tex compilation files (created by emacs and latex) -*.aux -*.log -*.gz -index.html -sheet.html -template.html -github.css -auto/* - diff --git a/.travis.yml b/.travis.yml deleted file mode 100644 index c508a99..0000000 --- a/.travis.yml +++ /dev/null @@ -1,17 +0,0 @@ -language: python - -before_install: - - sudo apt-get install pandoc - -python: - - "2.7" - -install: - - pip install markdown - - pip install beautifulsoup4 - -script: - - python create-index-html.py - -after_success: - - bash deploy.sh \ No newline at end of file diff --git a/LICENSE b/LICENSE deleted file mode 100644 index 1eea43a..0000000 --- a/LICENSE +++ /dev/null @@ -1,395 +0,0 @@ -Attribution 4.0 International - -======================================================================= - -Creative Commons Corporation ("Creative Commons") is not a law firm and -does not provide legal services or legal advice. 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Except for the limited purpose of indicating that -material is shared under a Creative Commons public license or as -otherwise permitted by the Creative Commons policies published at -creativecommons.org/policies, Creative Commons does not authorize the -use of the trademark "Creative Commons" or any other trademark or logo -of Creative Commons without its prior written consent including, -without limitation, in connection with any unauthorized modifications -to any of its public licenses or any other arrangements, -understandings, or agreements concerning use of licensed material. For -the avoidance of doubt, this paragraph does not form part of the -public licenses. - -Creative Commons may be contacted at creativecommons.org . diff --git a/README.md b/README.md deleted file mode 100644 index 3ba0fe8..0000000 --- a/README.md +++ /dev/null @@ -1,48 +0,0 @@ -[](https://travis-ci.org/IPGP/scientific_python_cheat_sheet) - -# Scientific Python Cheat Sheet - -## Overview -This is an overview of python, numpy, scipy, matplotlib functions that are -useful for scientific work. It tries to keep examples as compact as possible. - -Chose one of the following layouts: -* [website](https://ipgp.github.io/scientific_python_cheat_sheet) -* [markdown](sheet.md) - -Or the print version (without pandas until there are enough commands for a -third page) - -* [high contrast pdf (2016-06-16)](https://github.com/IPGP/scientific_python_cheat_sheet/raw/master/print_version/high_contrast.pdf) -* [low contrast pdf (2016-06-16)](https://github.com/IPGP/scientific_python_cheat_sheet/raw/master/print_version/low_contrast.pdf) - -## Printing -Printing the last version is a bit complicated so far if you want to have the -same layout as on the webpage but possible: You can save the CSS layout as an -image in firefox: - -1. use `shift + f2` to open the web console. -2. Arange the page as you want to print it. We found that two columns is - suitable for printing on A3 pages. You can either resize your browser or use - the built-in zoom function for this (e.g. ctrl + mousewheel on firefox). -3. The command `screenshot out.png --fullpage` saves the current complete view - of the page to the download folder. -4. Print the long image on several papers or cut it in pieces with the image - software of your choice (e.g. gimp or inkscape). - -Hopefully this will be simpler in the future ! - -## Contributing -If you wish to contribute, you only need to edit the file [sheet.md](sheet.md) -and push it to the master branch (preferably via pull-request). The website -updates automatically. - -If, beyond your knowledge of Python, you also master HTML and CSS, you can also -contribute to the design of the website. You can submit your ideas via the -issues section or directly via pull-request. - -## Reference: -Authors: A few scientists - -## License: -[Creative Commons (CC-BY-4.0)](LICENSE) diff --git a/create-index-html.py b/create-index-html.py deleted file mode 100644 index 835b071..0000000 --- a/create-index-html.py +++ /dev/null @@ -1,151 +0,0 @@ -#!/usr/bin/env python - -""" -A script to generate a file named index.html from sheet.md and templace.html -""" - -from bs4 import BeautifulSoup -import markdown -import subprocess - - -top = """ - - -
- - - -
-
- a = {'red': 'rouge', 'blue': 'bleu'} # dictionary
b = a['red'] # translate item
+'red' in a # true if dictionary a contains key 'red'
c = [value for key, value in a.items()] # loop through contents
-d = a.get('yellow', 'no translation found') # return default
+d = a.get('yellow', 'no translation found') # return default
+a.setdefault('extra', []).append('cyan') # init key with default
+a.update({'green': 'vert', 'brown': 'brun'}) # update dictionary by data from another one
+a.keys() # get list of keys
+a.values() # get list of values
+a.items() # get list of key-value pairs
+del a['red'] # delete key and associated with it value
+a.pop('blue') # remove specified key and return the corresponding value
+a = {1, 2, 3} # initialize manually
+b = set(range(5)) # initialize from iteratable
+a.add(13) # add new element to set
+a.discard(13) # discard element from set
+a.update([21, 22, 23]) # update set with elements from iterable
+a.pop() # remove and return an arbitrary set element
+2 in {1, 2, 3} # true if 2 in set
+5 not in {1, 2, 3} # true if 5 not in set
+a.issubset(b) # test whether every element in a is in b
+a <= b # issubset in operator form
+a.issuperset(b) # test whether every element in b is in a
+a >= b # issuperset in operator form
+a.intersection(b) # return the intersection of two sets as a new set
+a.difference(b) # return the difference of two or more sets as a new set
+a - b # difference in operator form
+a.symmetric_difference(b) # return the symmetric difference of two sets as a new set
+a.union(b) # return the union of sets as a new set
+c = frozenset() # the same as set but immutable
<object>? # Information about the object
-<object>.<TAB> # tab completion
+console
+<object>? # Information about the object
+<object>.<TAB> # tab completion
-# measure runtime of a function:
-%timeit range(1000)
-100000 loops, best of 3: 7.76 us per loop
+# run scripts / profile / debug
+%run myscript.py
-# run scripts and debug
-%run
-%run -d # run in debug mode
-%run -t # measures execution time
-%run -p # runs a profiler
-%debug # jumps to the debugger after an exception
+%timeit range(1000) # measure runtime of statement
+%run -t myscript.py # measure script execution time
-%pdb # run debugger automatically on exception
+%prun <statement> # run statement with profiler
+%prun -s <key> <statement> # sort by key, e.g. "cumulative" or "calls"
+%run -p myfile.py # profile script
+
+%run -d myscript.py # run script in debug mode
+%debug # jumps to the debugger after an exception
+%pdb # run debugger automatically on exception
# examine history
%history
@@ -279,10 +320,13 @@ Python console
!make # prefix command with "!"
# clean namespace
-%reset
+%reset
+
+# run code from clipboard
+%paste
n # execute next line
b 42 # set breakpoint in the main file at line 42
b myfile.py:42 # set breakpoint in 'myfile.py' at line 42
@@ -295,6 +339,11 @@ Debugger commands
pp locals() # show all variables in local scope
pp globals() # show all variables in global scope
ipython --pdb -- myscript.py argument1 --option1 # debug after exception
+ipython -i -- myscript.py argument1 --option1 # console after finish
+import numpy as np)a = np.arange(100) # initialization with 0 - 99
a[:3] = 0 # set the first three indices to zero
a[2:5] = 1 # set indices 2-4 to 1
+a[:-3] = 2 # set all but last three elements to 2
a[start:stop:step] # general form of indexing/slicing
a[None, :] # transform to column vector
a[[1, 1, 3, 8]] # return array with values of the indices
@@ -334,11 +384,14 @@ array properties and operations
a.flatten() # collapse array to one dimension
a.conj() # return complex conjugate
a.astype(np.int16) # cast to integer
+a.tolist() # convert (possibly multidimensional) array to list
np.argmax(a, axis=1) # return index of maximum along a given axis
np.cumsum(a) # return cumulative sum
np.any(a) # True if any element is True
np.all(a) # True if all elements are True
-np.argsort(a, axis=1) # return sorted index array along axis
+np.argsort(a, axis=1) # return sorted index array along axis
+np.where(cond) # return indices where cond is True
+np.where(cond, x, y) # return elements from x or y depending on cond
np.dot(a, b) # inner product: a_mi b_in
np.einsum('ij,kj->ik', a, b) # einstein summation convention
np.sum(a, axis=1) # sum over axis 1
@@ -376,12 +429,19 @@ inner / outer products
np.sum(a * a.T) # matrix norm
evals, evecs = np.linalg.eig(a) # Find eigenvalues and eigenvectors
+evals, evecs = np.linalg.eigh(a) # np.linalg.eig for hermitian matrix
+
-np.fromfile(fname/fobject, dtype=np.float32, count=5) # binary data from file
np.loadtxt(fname/fobject, skiprows=2, delimiter=',') # ascii data from file
np.savetxt(fname/fobject, array, fmt='%.5f') # write ascii data
-np.tofile(fname/fobject) # write (C) binary data
+np.fromfile(fname/fobject, dtype=np.float32, count=5) # binary data from file
+np.tofile(fname/fobject) # write (C) binary data
+np.save(fname/fobject, array) # save as numpy binary (.npy)
+np.load(fname/fobject, mmap_mode='c') # load .npy file (memory mapped)
import mat
figures and axes
fig = plt.figure(figsize=(5, 2)) # initialize figure
-ax = fig.add_subplot(3, 2, 2) # add second subplot in a 3 x 2 grid
+fig.savefig('out.png') # save png image
fig, axes = plt.subplots(5, 2, figsize=(5, 5)) # fig and 5 x 2 nparray of axes
-ax = fig.add_axes([left, bottom, width, height]) # add custom axis
+ax = fig.add_subplot(3, 2, 2) # add second subplot in a 3 x 2 grid
+ax = plt.subplot2grid((2, 2), (0, 0), colspan=2) # multi column/row axis
+ax = fig.add_axes([left, bottom, width, height]) # add custom axis
figures and axes properties
@@ -453,7 +515,8 @@ plotting routines
ax.imshow(matrix, origin='lower',
extent=(x1, x2, y1, y2)) # show image
ax.specgram(y, FS=0.1, noverlap=128,
- scale='linear') # plot a spectrogram
+ scale='linear') # plot a spectrogram
+ax.text(x, y, string, fontsize=12, color='m') # write text
import scipy as sci)from scipy.ndimage import map_coordinates # interpolates data
-pts_new = map_coordinates(data, float_indices, # at index positions
- order=3)
+# interpolate data at index positions:
+from scipy.ndimage import map_coordinates
+pts_new = map_coordinates(data, float_indices, order=3)
+
+# simple 1d interpolator with axis argument:
+from scipy.interpolate import interp1d
+interpolator = interp1d(x, y, axis=2, fill_value=0., bounds_error=False)
+y_new = interpolator(x_new)
from scipy.integrate import quad # definite integral of python
value = quad(func, low_lim, up_lim) # function/method
from scipy import linalg
+evals, evecs = linalg.eig(a) # Find eigenvalues and eigenvectors
+evals, evecs = linalg.eigh(a) # linalg.eig for hermitian matrix
+b = linalg.expm(a) # Matrix exponential
+c = linalg.logm(a) # Matrix logarithm
+import pandas as pd)df = pd.read_csv("filename.csv") # read and load CSV file in a DataFrame
-print(df[:2]) # print first 2 lines of the DataFrame
-raw = df.values # get raw data out of DataFrame object
-cols = df.columns # get list of columns headers
+df = pd.read_csv("filename.csv") # read and load CSV file in a DataFrame
+raw = df.values # get raw data out of DataFrame object
+cols = df.columns # get list of columns headers
+df.dtypes # get data types of all columns
+df.head(5) # get first 5 rows
+df.describe() # get basic statisitics for all columns
+df.index # get index column range
+
+#column slicin
+# (.loc[] and .ix[] are inclusive of the range of values selected)
+df.col_name # select column values as a series by column name (not optimized)
+df[['col_name']] # select column values as a dataframe by column name (not optimized)
+df.loc[:, 'col_name'] # select column values as a series by column name
+df.loc[:, ['col_name']] # select column values as a dataframe by column name
+df.iloc[:, 0] # select by column index
+df.iloc[:, [0]] # select by column index, but as a dataframe
+df.ix[:, 'col_name'] # hybrid approach with column name
+df.ix[:, 0] # hybrid approach with column index
+
+# row slicin
+print(df[:2]) # print first 2 rows of the dataframe
+df.iloc[0:2, :] # select first 2 rows of the dataframe
+df.loc[0:2,'col_name'] # select first 3 rows of the dataframe
+df.loc[0:2, ['col_name1', 'col_name3', 'col_name6']] # select first 3 rows of the 3 different columns
+df.iloc[0:2,0:2] # select fisrt 3 rows and first 3 columns
+# Again, .loc[] and .ix[] are inclusive
+
+# Dicin
+df[ df.col_name < 7 ] # select all rows where col_name < 7
+df[ (df.col_name1 < 7) & (df.col_name2 == 0) ] # combine multiple boolean indexing conditionals using bit-wise logical operators.
+ # Regular Python boolean operators (and, or) cannot be used here.
+ # Be sure to encapsulate each conditional in parenthesis to make this work.
+df[df.recency < 7] = -100 # writing to slice