1.Python常用库

本文由 简悦 SimpRead 转码， 原文地址 https://pyoceans.github.io/sea-py/

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A collaborative effort to organize and distribute

Python tools for the Atmospheric and Oceanographic Community

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A collaborative effort to organize Python tools for the Oceanographic Community

The bare minimum

  • Python: Needs no introduction.
  • IPython: An enhanced interactive Python shell.
  • NumPy: Support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays.
  • SciPy: Library of algorithms and mathematical tools for the Python programming language.
  • matplotlib: 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments.

Time Series Tools

  • UTide: UTide - A project (in its early development phase) to create a Python implementation of the Matlab-based UTide tidal analysis tools.
  • ttide: A direct conversion of T_Tide to Python.
  • pytides: Pytides is small Python package for the analysis and prediction of tides.
  • tappy: Tidal analysis package.
  • dateutil: Provides powerful extensions to the standard datetime module.
  • PyWavelets: Wavelet transform module.
  • wafo: Routines for statistical analysis and simulation of random waves and random loads.
  • pandas: Cross-section and time series data analysis toolkit
  • Currents: CODAS, Lowered ADCP

Numerical Modeling Tools

  • octant: Ocean C-grid model seTup and Analysis Toolkit. The toolkit contains general modeling tools for dealing with arrays, diagnosing standard properties, curvilinear grid generation, and interpolation. Specific tools are also included for ROMS and GETM.
  • pyroms: Collection of tools to help with input and output files from the Regional Ocean Modeling System (ROMS).
  • PySeidon: Suite of tools for the tidal energy community and FVCOM users
  • PyFVCOM: PyFVCOM is a collection of various tools and utilities which can be used to extract, analyse and plot input and output files from FVCOM.
  • TracPy: Fortran core of Tracmass + Python wrapping around the outside. TracPy is a toolbox for Lagrangian tracking on top of staggered C grid model output, and is currently set up to use directly with ROMS.
  • pygridgen: A Python interface to Pavel Sakov’s C-based Gridgen Orthogonal Grid Generation Package.
  • okean: Ocean modelling and analysis tools.

Mapping Tools

  • basemap: Matplotlib Basemap Toolkit.
  • cartopy: A library providing cartographic tools for python.
  • folium: Python Data. Leaflet.js Maps.
  • PySAL: Python Spatial Analysis Library.
  • sci-wms: A Python WMS service for geospatial gridded data.

Hydrographic Tools

  • python-ctd: Tools to load hydrographic data as pandas DataFrame with some handy methods for data pre-processing and analysis.
  • python-seawater: Python version of the CSIRO seawater toolbox (SEAWATER-3.3).
  • python-gsw: A oceanographic toolbox of the International Thermodynamic Equation Of Seawater - 2010, (TEOS-10).
  • pygsw: C-wrapped alternative to python-gsw.
  • cbsyst: Python module for calculating carbon and boron solution chem.
  • narwhal: Experimental tools to organize, analyze, and plot CTD data, including GSW wrappers.

Data Interface Tools

  • netcdf4-python: Python/numpy interface to netCDF
  • python-blosc: Wrapper for the Blosc compressor.
  • PyTables: Package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data.
  • h5py: Interface to the HDF5 library.
  • python-hdf4: Python-HDF4: Python interface to the NCSA HDF4 library.
  • PyNIO/PyNGL: File input/output
  • Pydap: Library implementing the Data Access Protocol.
  • pygrib: python GRIB (editions 1 and 2) reader.

Plotting (beyond matplotlib)

  • mayavi: Scripting for 3D plotting.
  • gnuplot-py: Package that interfaces to gnuplot, the popular open-source plotting program.
  • PyNGL: Scientific visualization.
  • ggplot: ggplot is a plotting system for Python based on R’s ggplot2 and the Grammar of Graphics. It is built for making professional looking, plots quickly with minimal code.
  • bokeh: Bokeh is a Python interactive visualization library that targets modern web browsers for presentation.
  • mpld3: The mpld3 project brings together Matplotlib, the popular Python-based graphing library, and D3js, the popular Javascript library for creating interactive data visualizations for the web.

CDMs

  • paegan: Processing and Analysis for Numerical Data.
  • Iris: A Python library for Meteorology and Climatology

Atmosphere

  • atmqty: Methods to calculate atmospheric quantities (on the Earth) that are directly derivative (i.e. not requiring time integration or modeling) from standard state variables.
  • airsea: Translation of the original AIR_SEA toolbox for Matlab.

Climate

  • PyClimate: Designed to accomplish some usual tasks needed during the analysis of climate variability. It provides functions to handle simple I/O operations, handling of COARDS-compliante netCDF files, EOF analysis, SVD and CCA analysis of coupled data sets, some linear digital filters, kernel based probability density function estimation and access to DCDFLIB.C library
  • climpy: climpy module.
  • CDAT: Climate Data Analysis Tools.
  • ccc-gistemp: Reimplementation of GISTEMP in Python for clarity.

Statistics

  • statsmodels: Statistical computations and models for use with SciPy.
  • scikit.learn: Module integrating classic machine learning algorithms in the tightly-knit world of scientific Python packages.
  • RPy: Interface to the R Programming Language.
  • pymc: Markov chain Monte Carlo for Python

Miscellaneous Other Tools

  • oceans: Misc functions for oceanographic data analysis.
  • OWSLib: OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models.
  • pyoos: A Python library for collecting Met/Ocean observations.
  • scitools: Contains many useful tools for scientific computing in Python. The package is built on top of other widely used packages such as NumPy, SciPy, ScientificPython, Matplotlib, Gnuplot, etc.
  • uncertainties: Transparent calculations with uncertainties on the quantities involved (aka “error propagation”) ; fast calculation of derivatives.
  • numexpr: Fast numerical array expression evaluator for Python and NumPy.
  • Bottleneck: Fast NumPy array functions written in Cython.
  • spyderlib: Spyder is the Scientific PYthon Development EnviRonment.
  • SciPy scikits: Scipy Toolkits are independent and separately installable projects hosted under a common namespace. Packages that are distributed in this way are here (instead of in monolithic scipy) for at least one of three general reasons. Each of these reasons use the same high-level namespace (scikits).
  • fwrap: Wraps FORTRAN code.
  • gmpy: A C-coded Python extension module that wraps the GMP library to provide to Python code fast multiprecision arithmetic (integer, rational, and float), random number generation, advanced number-theoretical functions, and more.
  • SymPy: Library for symbolic mathematics.
  • PyEphem: Scientific-grade astronomical computations.
  • Astropysics: Astrophysics utilities.
  • biopython: Tools for biological computation written in Python.
  • pytroll: Python modules for the reading, interpretation, and writing of weather satellite data.
  • Topical Software: SciPy Topical Software.
  • pyferret: Ferret is an interactive computer visualization and analysis environment designed to meet the needs of oceanographers and meteorologists.
  • openptv: OpenPTV is an open source particle tracking velocimetry consortium providing software and assistance with the 3D-PTV experiments, including the field deployments for oceanographers, limnologists and meteorologits.

Fun

  • slocum: A tool for ocean passage planning.
  • OceanSound: Get the music from oceancolor images, through MODIS satellite.

2.Python&ML书单

结合自己的阅读和使用经验，分享一些自认为还不错的Python、机器学习比较新的书籍。下载链接：气象家园

Book list

1.统计学习方法

2.Deep Learning-CN

3.TensorFlow实战-2017

4.机器学习_周志华

5.机器学习实战

6.Fluent Python-中文原版

7.Hands-On Machine Learning with Scikit-Learn and TensorFlow

8.Introduction Machine Learning with Python

9.Learning Python-5th

10.Python Cookbook（第3版）中文版

11.Python for Data Analysis Data Wrangling with Pandas, NumPy, and IPython

12.Python数据分析基础教程：NumPy学习指南（第2版）

13.Python科学计算第二版

14.Python编程：从入门到实践

15.Python语言及其应用

16.Scientific Computing with Python 3

17.Two Scoops of Django-1.11

18.如何阅读Python代码-The Hitchhiker’s Guide to Python

19.编写高质量代码 改善Python程序的91个建议

20.Introduction to Python for Engineers and Scientists

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