Metadata-Version: 2.1
Name: ncvue
Version: 4.2
Summary: ncvue: A minimal GUI for a quick view of netcdf files, aiming to be a drop-in replacement for ncview and panoply
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
Project-URL: Documentation, https://mcuntz.github.io/ncvue/
Project-URL: Source, https://github.com/mcuntz/ncvue
Project-URL: Tracker, https://github.com/mcuntz/ncvue/issues
Project-URL: Changelog, https://github.com/mcuntz/ncvue/blob/main/CHANGELOG.rst
Platform: any
Classifier: Development Status :: 5 - Production/Stable
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 :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
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
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: netcdf4
Requires-Dist: cython
Requires-Dist: pyshp
Requires-Dist: six
Requires-Dist: shapely
Requires-Dist: matplotlib
Requires-Dist: pykdtree
Requires-Dist: cartopy
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ncvue - A GUI to view netCDF files
==================================
..
  pandoc -f rst -o README.html -t html README.rst
  As docs/src/readme.rst:
    replace _small.png with .png
    replace
      higher resolution images can be found in the documentation_
    with
      click on figures to open larger pictures
    remove section "Installation"

A minimal GUI for a quick view of netCDF files. Aiming to be a drop-in
replacement for ncview_ and panoply_.

.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4459598.svg
   :target: https://doi.org/10.5281/zenodo.4459598
   :alt: Zenodo DOI

.. image:: https://badge.fury.io/py/ncvue.svg
   :target: https://badge.fury.io/py/ncvue
   :alt: PyPI version

.. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat
   :target: https://github.com/mcuntz/ncvue/blob/master/LICENSE
   :alt: License

.. image:: https://github.com/mcuntz/ncvue/workflows/Continuous%20Integration/badge.svg?branch=main
   :target: https://github.com/mcuntz/ncvue/actions
   :alt: Build status

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_ and panoply_, being
slightly more general than ncview targeting maps but providing
animations, zooming and panning capabilities unlike panoply. 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')

where the netCDF file is optional. The latter can also be left out and
a netCDF file can be opened with the "Open File" button from within
``ncvue``.

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,
or using `ipython --gui tk`.

When using ``ncvue`` with `jupyter` notebooks, one has to set
`%matplotlib inline` before the import and call of ``ncvue``. You have
set `%matplotlib inline` again if you want to continue having inline
plots in `jupyter` afterwards.

.. code-block:: python

   %matplotlib inline
   from ncvue import ncvue
   ncvue('netcdf_file.nc')
   %matplotlib inline

One can also install standalone macOS or Windows applications that
come with everything needed to run ``ncvue`` including Python:

- `macOS app`_ (macOS > 10.13 [High Sierra] on Intel)
- `Windows executable`_ (Windows 10)

The macOS app should work from macOS 10.13 (High Sierra) onward on
Intel processors. There is no standalone application for macOS on
Apple Silicon (M1) chips because I do not have a paid Apple
Developer ID. Other installation options work, though.

A dialog box might pop up on macOS saying that the ``ncvue.app`` is
from an unidentified developer. This is because ``ncvue`` is an
open-source software.  Depending on the macOS version, it offers to
open it anyway. In later versions of macOS, this option is only given
if you right-click (or control-click) on the ``ncvue.app`` and choose
`Open`. You only have to do this once. It will open like any other
application the next times.

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:: https://mcuntz.github.io/ncvue/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:: https://mcuntz.github.io/ncvue/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:: https://mcuntz.github.io/ncvue/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:: https://mcuntz.github.io/ncvue/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:: https://mcuntz.github.io/ncvue/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
------------

``ncvue`` is an application written in Python. If you have Python
 installed, then the best is to install ``ncvue`` within the Python
 universe. The easiest way to install ``ncvue`` is thence 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` or directly ``ncvue`` is by using Conda_. After
installing, for example, Miniconda_:

.. code-block:: bash

   conda install -c conda-forge ncvue

We also provide a standalone `macOS app`_ and a `Windows executable`_
that come with everything needed to run ``ncvue`` including
Python. The macOS app should work from macOS 10.13 (High Sierra)
onward. It is, however, only tested on macOS 10.15 (Catalina). Drop me
a message if it does not work on newer operating systems.

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) 2020-2024 Matthias Cuntz

``ncvue`` uses the Azure_ 2.0 theme by rdbende_ on Linux and Windows.

Standalone applications are produced with `cx_Freeze`_, currently
maintained by `Marcelo Duarte`_.

The project structure of ``ncvue`` was very originally based on a
template_ provided by `Sebastian Müller`_ but has evolved
considerably.

Different netCDF test files were provided by `Juliane Mai`_.

.. _Anaconda: https://www.anaconda.com/products/individual
.. _macOS app: http://www.macu.de/extra/ncvue-4.0.dmg
.. _Azure: https://github.com/rdbende/Azure-ttk-theme
.. _cartopy: https://scitools.org.uk/cartopy/docs/latest/
.. _Conda: https://docs.conda.io/projects/conda/en/latest/
.. _cx_Freeze: https://cx-freeze.readthedocs.io/en/latest/
.. _documentation: https://mcuntz.github.io/ncvue/
.. _Marcelo Duarte: https://github.com/marcelotduarte
.. _Windows executable: http://www.macu.de/extra/ncvue-3.7-amd64.msi
.. _install: https://scitools.org.uk/cartopy/docs/latest/installing.html
.. _instructions: https://mcuntz.github.io/ncvue/html/install.html
.. _LICENSE: https://github.com/mcuntz/ncvue/blob/main/LICENSE
.. _matplotlib: https://matplotlib.org/
.. _Juliane Mai: https://github.com/julemai
.. _Miniconda: https://docs.conda.io/en/latest/miniconda.html
.. _Sebastian Müller: https://github.com/MuellerSeb
.. _Sun Valley: https://github.com/rdbende/Sun-Valley-ttk-theme
.. _ncview: http://meteora.ucsd.edu/~pierce/ncview_home_page.html
.. _netcdf4: https://unidata.github.io/netcdf4-python/netCDF4/index.html
.. _numpy: https://numpy.org/
.. _panoply: https://www.giss.nasa.gov/tools/panoply/
.. _rdbende: https://github.com/rdbende
.. _template: https://github.com/MuellerSeb/template
