Metadata-Version: 2.1
Name: ncvue
Version: 3.0
Summary: A minimal GUI for a quick view of netcdf files. Aiming to be a drop-in replacement for ncview.
Home-page: https://github.com/mcuntz/ncvue
Author: Matthias Cuntz
Author-email: mc@macu.de
Maintainer: Matthias Cuntz
Maintainer-email: mc@macu.de
License: MIT
Description: ncvue - A GUI to view netCDF files
        ==================================
        ..
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        A minimal GUI for a quick view of netCDF files. Aiming to be a drop-in
        replacement for ncview_.
        
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3893705.svg
           :alt: Zenodo DOI
           :target: https://doi.org/10.5281/zenodo.3893705
        
        .. image:: https://badge.fury.io/py/ncvue.svg
           :alt: PyPI version
           :target: https://badge.fury.io/py/ncvue
        
        .. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat
           :alt: License
           :target: https://github.com/mcuntz/ncvue/blob/master/LICENSE
        
        .. image:: https://travis-ci.org/mcuntz/ncvue.svg?branch=main
           :alt: Build status
           :target: https://travis-ci.org/mcuntz/ncvue
        
        About ncvue
        -----------
        
        ``ncvue`` is a minimal GUI for a quick view of netCDF files. It is aiming to be
        a drop-in replacement for ncview_, being slightly more general than ncview,
        which targets maps. If ``ncvue`` is used with maps, it supports mostly
        structured grids, more precisely the grids supported by cartopy_.
        
        ``ncvue`` is a Python script that can be called from within Python or as a
        command line tool. It is not supposed to produce publication-ready plots but
        rather provide a quick overview of the netcdf file.
        
        The complete documentation for ``ncvue`` is available from:
        
           https://mcuntz.github.io/ncvue/
        
        Quick usage guide
        -----------------
        
        ``ncvue`` can be run from the command line:
        
        .. code-block:: bash
        
           ncvue netcdf_file.nc
        
        or from within Python:
        
        .. code-block:: python
        
           from ncvue import ncvue
           ncvue('netcdf_file.nc')
        
        Note, ``ncvue`` uses the `TkAgg` backend of `matplotlib`. It must be called
        before any other call to `matplotlib`. This also means that you cannot launch it
        from within `iPython` if it was launched with `--pylab`. It can be called from
        within a standard `iPython`, though.
        
        General layout
        ^^^^^^^^^^^^^^
        
        On opening, ``ncvue`` presents three panels for different plotting types:
        Scatter or Line plots, Contour plots, and Maps. This is the look in macOS light
        mode (higher resolution images can be found in the documentation_):
        
        .. image:: docs/images/scatter_panel_light_small.png
           :width: 860 px
           :align: left
           :alt: Graphical documentation of ncvue layout
        
        ..
           :height: 462 px
        
        All three panes are organised in this fashion: the plotting canvas, the
        Matplotlib navigation toolbar and the pane, where one can choose the plotting
        variables and dimensions, as well as plotting options. You can always choose
        another panel on top, and open another, identical window for the same netCDF
        file with the button "New Window" on the top right.
        
        Map panel
        ^^^^^^^^^
        
        If ``ncvue`` detects latitude and longitude variables with a size greater than
        1, it opens the Map panel by default. This is the Map panel in macOS dark mode,
        describing all buttons, sliders, entry boxes, spinboxes, and menus:
        
        .. image:: docs/images/map_panel_dark_small.png
           :width: 860 px
           :align: left
           :alt: Graphical documentation of Map panel
        
        If it happens that the detection of latitudes and longitudes did not work
        automatically, you can choose the correct variables manually. Or you might use
        the empty entries on top of the dropdown menus of the latitudes and longitudes,
        which uses the index and one can hence display the matrix within the netCDF
        file. You might want to switch of the coastlines in this case.
        
        You might want to switch off the automatically detected "global" option
        sometimes if your data is on a rotated grid or excludes some regions such as
        below minus -60 °S.
        
        All dimensions can be set from 0 to the size of the dimension-1, to "all", or to
        any of the arithmetic operators "mean", "std" (standard deviation), "min",
        "max", "ptp" (point-to-point amplitude, i.e. max-min), "sum", "median", "var"
        (variance).
        
        Be aware that the underlying cartopy/matplotlib may (or may not) need a long
        time to plot the data (with the pseudocolor 'mesh' option) if you change the
        central longitude of the projection from the central longitude of your data,
        which is automatically detected if "central lon" is set to None. Setting
        "central lon" to the central longitude of the input data normally eliminates the
        problem.
        
        Scatter/Line panel
        ^^^^^^^^^^^^^^^^^^
        
        If ``ncvue`` does not detect latitude and longitude variables with a size
        greater than 1, it opens the Scatter/Line panel by default. This is the
        Scatter/Line panel in macOS dark mode, describing all buttons, sliders, entry
        boxes, spinboxes, and menus:
        
        .. image:: docs/images/scatter_panel_dark_small.png
           :width: 860 px
           :align: left
           :alt: Graphical documentation of Scatter/Line panel
        
        The default plot is a line plot with solid lines (line style 'ls' is '-'). One
        can set line style 'ls' to None and set a marker symbol, e.g. 'o' for circles, to
        get a scatter plot. A large variety of line styles, marker symbols and color
        notations are supported.
        
        ``ncvue`` builds automatically a `datetime` variable from the time axis. This is
        correctly interpreted by the underlying Matplotlib also when zooming into or
        panning the axes. But it is also much slower than using the index. Selecting the
        empty entry on top of the dropdown menu for `x` uses the index for the x-axis
        and is very fast. Plotting a line plot with 52608 time points takes about 2.2 s
        on my Macbook Pro using the `datetime` variable and about 0.3 s using the index
        (i.e. empty x-variable). This is especially true if one plots multiple lines
        with 'all' entries from a specific dimension. Plotting all 10 depths of soil
        water content for the 52608 time points, as in the example below, takes also
        about 0.3 s if using the index as x-variable but more than 11.1 s when using the
        `datetime` variable.
        
        .. image:: docs/images/scatter_panel_dark_multiline.png
           :width: 407 px
           :align: center
           :alt: Example of multiple lines in the Scatter/Line panel
        
        Contour panel
        ^^^^^^^^^^^^^
        
        The last panel provide by ``ncvue`` draws contour plots. This is the
        Contour panel in macOS dark mode, describing all buttons, sliders, entry
        boxes, spinboxes, and menus:
        
        .. image:: docs/images/contour_panel_dark_small.png
           :width: 860 px
           :align: left
           :alt: Graphical documentation of Contour panel
        
        This produces also either pseudocolor plots ('mesh' ticked) or filled
        contour plots ('mesh' unticked) just as the Map panel but without any map
        projection.
        
        Installation
        ------------
        
        The easiest way to install ``ncvue`` is via `pip` if you have cartopy_ installed already:
        
        .. code-block:: bash
        
           pip install ncvue
        
        `Cartopy` can, however, be more elaborate to install. The easiest way to install
        Cartopy is by Conda_ and then installing ``ncvue`` with `pip`:
        
        .. code-block:: bash
        
           conda install -c conda-forge cartopy
           pip install ncvue
        
        You would need an Anaconda_ or Miniconda_ environment for this, of course.
        
        See the installation instructions_ in the documentation_ for more information.
        
        License
        -------
        
        ``ncvue`` is distributed under the MIT License. See the LICENSE_ file for
        details.
        
        Copyright (c) 2020-2021 Matthias Cuntz
        
        The project structure is based on a template_ provided by Sebastian Müller_.
        
        .. _Anaconda: https://www.anaconda.com/products/individual
        .. _cartopy: https://scitools.org.uk/cartopy/docs/latest/
        .. _Conda: https://docs.conda.io/projects/conda/en/latest/
        .. _documentation: https://mcuntz.github.io/ncvue/
        .. _instructions: https://mcuntz.github.io/ncvue/install.htm
        .. _LICENSE: https://github.com/mcuntz/ncvue/blob/main/LICENSE
        .. _matplotlib: https://matplotlib.org/
        .. _Miniconda: https://docs.conda.io/en/latest/miniconda.html
        .. _Müller: https://github.com/MuellerSeb
        .. _ncview: http://meteora.ucsd.edu/~pierce/ncview_home_page.html
        .. _netcdf4: https://unidata.github.io/netcdf4-python/netCDF4/index.html
        .. _numpy: https://numpy.org/
        .. _template: https://github.com/MuellerSeb/template
        
Platform: Windows
Platform: Linux
Platform: Solaris
Platform: Mac OS-X
Platform: Unix
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Hydrology
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Description-Content-Type: text/x-rst
