zapata

The zapata library (small z) is a collection of mapping and computational routines for handling atmospheric and ocean data. It is best used in conjunction with the Anaconda distribution and Jupyterlab Notebooks.

Submodules

• zapata.colormap module
  • Color control and choice
  • make_cmap()
  • load_xml()
  • plot_cmap()
  • viewcmap()
• zapata.computation module
  • zonal_var()
  • smooth_xarray()
  • anomaly()
  • Xmat
  • feature_to_input()
  • make_random_index()
• zapata.data module
  • A module to store and treat data
  • date_param()
  • DataGrid()
  • read_era5()
  • decode_period()
  • in_data()
  • read_ceres()
  • select_time()
• zapata.koopman module
  • Koopman Analysis
  • choose_eig()
  • reconstruct_koopman()
  • check_sim()
  • order_w()
  • expand_modes()
  • find_modes()
  • density_estimate()
  • one_over()
  • one_over_years()
  • Koop
  • KoopGen
  • KEig
• zapata.lib module
  • name_notebook()
  • get_values_from_dict()
  • remove_values_from_list()
  • makename()
  • makemm()
  • makefilename()
  • adddir()
  • makedir()
  • movefile()
  • copyfile()
  • chop()
  • year2date()
  • date2year()
  • putna()
  • go_to()
  • long_string()
  • lat_string()
  • get_environment_info()
• zapata.mapping module
  • Contouring, stremlines and vector plots
  • init_figure()
  • choose_projection()
  • xmap()
  • zonal_plot()
  • zonal_stream_plot()
  • choose_contour()
  • add_colorbar()
  • make_ticks()
  • set_titles_and_labels()
  • ocean_section_plot()
  • small_map()
  • adjust_data_centlon()
  • lon_sect()
  • lat_sect()
  • changelabel()
  • changebox()
  • label_equator()
  • zonal_streamfun_plot()
  • add_cyclic_lon()
  • xstmap()
  • vecmap()

Module contents

Zapata A revolutionary library for analysis and plotting of meteorological data.

It uses xarray as a basic data structure.

The module data contains the information on the data banks. The routine DataGrid in data must be modified to the location of the basic data for each installation.

Zapata contains computation modules and plotting modules. The plotting modules are based on matplotlib and cartopy. The computation modules are based on numpy and scipy.

computation :

Routines for averaging and various computations

data :

Information on data sets and routines to get data from the data sets

mapping :

Mapping routines based on Cartopy

lib :

Utilities for the rest of the modules.

colormap :

Routines to use colormap in xml format

koopman :

Routines for Koopman decomposition and eigenvalues handling

Version 2.1