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python package/module/class

2021-07-01

LZN

technology

linux python
Module

A module is a file containing Python definitions and statements. The file name is the module name with the suffix .py appended. The __init__.py files are required to make Python treat directories containing the file as packages.

Naming

Modules should have short, all-lowercase names. Underscores can be used in the module name if it improves readability. When an extension module written in C or C++ has an accompanying Python module that provides a higher level (e.g. more object oriented) interface, the C/C++ module has a leading underscore (e.g. _socket).

Package

A package is a collection of modules. Packages are a way of structuring Python’s module namespace by using “dotted module names”. For example, the module name A.B designates a submodule named B in a package named A.

Naming

Python packages should also have short, all-lowercase names, although the use of underscores is discouraged.

Class

Naming

Class names should normally use the CapWords convention.

Instance

Naming
- Instance variable names should be all lower case
- Words in an instance variable name should be separated by an underscore
- Non-public instance variables should begin with a single underscore
- If an instance name needs to be mangled, two underscores may begin its name
Reference
- https://docs.python.org/3/tutorial/modules.html
- https://www.python.org/dev/peps/pep-0008/#package-and-module-names
- https://visualgit.readthedocs.io/en/latest/pages/naming_convention.html
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Coursera Machine Learning Recap: W1-2

2021-06-28

LZN

technology

cs229 coursera
W1

Notes
- “Batch” Gradient Descent: Each step use all training examples.
W2

Notes

Multivar linear regression
- learning rate alpha choices: 0.001, 0.003, 0.01, 0.03, 0.1, 0.3, 1… 3X test
- quadratic function / cubic function / third-order term
- polynomial regression
- Matrix inverse computational complexity O(n^3)
- Normal equation, use when feature numbers less than 10000 or so.
- Gradient descent complexity O(kn^2), where k is the number of iterations (epochs)
- Non-invertable matrix (singular/degenerate)
  - Cause 1: Redundent feature with linear relationship
  - Cause 2: Too many features (m«n)
- Clunkier 笨重的
Octave
- v= 1:0.1:2 arithmetic sequence
- ones(2,3) zeros(2,3) eye(3) rand(2,3)
- randn(2,3) % Guassian Distribution ~N(0,1)
- size(X), size(X,1), size(X,2)
- load(featureX.dat) % load a data file
- whos % command gives you variables in the current scope.
- clear X % delete X variable
- v = X(1:10) % slice
- save test.mat v % save v into test.mat file
- save test.txt v -ascii
- clear % clear all variables
- A=[A, [2; 4]] % matrix append a col vector to the rightmost position of A
- A(:) % squeeze nd data to 1d
- C = [A B]; C=[A;B] % right append and bottom append
- AB; A.B; % matrix multiplication and element-wise multiplication
- log(A); exp(A) % element-wise operation
- v + ones(length(v),1)
- [val, ind] = max(a)
- find(a<3) % return index
- [nrow, ncol]=find(A >= 7)
- sum(a); prod(a); % prod is the product of each element in a
- floor(a); ceil((a);
- max(A,[],1) % get max in each column
- max(A,[],2) % get max in each row
- sum(A, 1); sum(A,2); % column sum and row sum
- filpud(A) % FLIPUD Flip array in up/down direction.
- Plot
  - plot(t,y1); hold on; plot(t,y2); xlabel(‘time’); ylabel(‘val’); legend(‘sin’, ‘cos’)
  - print -dpng ‘myplot.png’
  - figure(1); plot(t,y1)
  - figure(2); plot(t,y2)
  - subplot(1,2,1); % divides canvas into 1x2 subdomain and access the first domain.
  - subplot(1,2,1); plot(t,y1); subplot(1,2,2); plot(t,y2)
  - axis([0.5 1 -1 1]) % set X axis from 0.5 to 1, and Y axis from -1 to 1
  - imagesc(A) % plot the matrix in heatmap
  - imagesc(A), colorbar, colormap gray; % in gray scale
  - comma chaining of commands would echo the result.
- Control
  - for i=1:10, v(i)=i^2; end;
  - ind = 1:10; for i=ind,
  - if elseif else
  - function y = f(x); y = x^2;
  - function y1, y2 = f(x) % multiple values return
- summation n. 求和
- reciprocal 倒数
- apostrophe 撇号
Programming

Carefully follow the matrix size after each vectorized operation, of particular caution is that matlab would perform add/subtract between 1-by-n and n-by-1 matrix by broadcasting the matrix to fit n-by-n size.
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echo in bashrc? No! bash_profile please.

2021-06-27

LZN

technology

linux python requriments.txt
- Reference
I tried to echo some message in the ~/.bashrc file, and then found scp does not work. In short, this is basically scp command try to parse these chars.

The scp command builds ssh connection first between the source and sink host, and ssh will execute source ~/.bashrc before full setup shell.

Therefore, put messages in ~/.bash_profile.

Reference
- https://chuacw.ath.cx/development/b/chuacw/archive/2019/02/04/how-the-scp-protocol-works.aspx
- https://huster.top/htmls/319.html (Chinese)
Updated 2021-06-27**
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Welcome to LZN's Blog!

python package/module/class

Module

Package

Class

Instance

Reference

Coursera Machine Learning Recap: W1-2

W1

Notes

W2

Notes

Multivar linear regression

Octave

Programming

echo in bashrc? No! bash_profile please.

Reference