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130 lines
2.9 KiB
130 lines
2.9 KiB
= LabInstance numpy!
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== Quickstart
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This is a quickstart guide of howto use this *LabInstance*
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=== Default Configuration
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- Working Directory
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> /home/docker/project
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- Default user
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> docker
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- Default password
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> docker
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- Default password4root
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> pass
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== LabInstance Info
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=== NumPy
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*NumPy* is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.
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=== SciPy
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*SciPy* is a free and open-source Python library used for scientific computing and technical computing.
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SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
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Available sub-packages include:
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* cluster: hierarchical clustering, vector quantization, K-means
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* constants: physical constants and conversion factors
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* fft: Discrete Fourier Transform algorithms
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* fftpack: Legacy interface for Discrete Fourier Transforms
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* integrate: numerical integration routines
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* interpolate: interpolation tools
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* io: data input and output
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* linalg: linear algebra routines
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* misc: miscellaneous utilities (e.g. example images)
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* ndimage: various functions for multi-dimensional image processing
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* ODR: orthogonal distance regression classes and algorithms
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* optimize: optimization algorithms including linear programming
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* signal: signal processing tools
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* sparse: sparse matrices and related algorithms
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* spatial: algorithms for spatial structures such as k-d trees, nearest neighbors, Convex hulls, etc.
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* special: special functions
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* stats: statistical functions
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* weave: tool for writing C/C++ code as Python multiline strings (now deprecated in favor of Cython)
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=== pandas
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*pandas* is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool,
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built on top of the Python programming language.
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== More info
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https://numpy.org/doc/stable/reference/index.html#reference[^]
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https://scipy.org/faq/[^]
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https://pandas.pydata.org/[^]
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== RUN INSTANCE
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Swarmlab services can be run in different ways.
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- You can run them **through the swarmlab hybrid environment** (http://docs.swarmlab.io/SwarmLab-HowTos/swarmlab/docs/swarmlab/docs/hybrid/start-microservices.html)
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- or use them individually at will on the **command line of your system**
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=== CLI
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> git clone ...
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> cd [DIRECTORY]
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=== help
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> make help
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==== create service
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> make create
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=== start service
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> make start
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=== stop service
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> make stop
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=== list service
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> make list
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=== clean service
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> make clean
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