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_.

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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 ncvue netcdf_file1.nc netcdf_file2.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. The netCDF has to be given in a list because several netcdf files can be given as in the second example from the command line.

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.

.. 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_light_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 on installing Cartopy and ncvue with pip.

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