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* implement conda package building
* paths
* need libtool
* PLATFORM check
* point to my PROJ feedstock for now
* point to PROJ repos
* plot building and artifact upload
* syntax
* add proj conda package for plotting
* retab
* no doxygen
* syntax
* update docs Makefile
* doc building
* needs
* consolidate doc/plots
* plot updates
* put updated plot output into docs
* register spelling module
* use v2 download-artifact
* artifact upload
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environment variable
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This commit adds five new projections to PROJ:
adams_hemi: Adams Hemisphere in a Square
adams_wsI: Adams World in a Square I
adams_wsII: Adams World in a Square II
guyou: Guyou
peirce_q: Pierce Quincuncial
The code originates from Gerry Evendens libproject and has been adapted
to work with modern PROJ. To ensure that the modified code works as
intended extensive test data has been created using libproject and
sproj so that no errors occured when porting from libproject to PROJ.
The test data is wrapped in a gie files. All test cases reproduce
results from libproject at the mm level.
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Added conda environment file too, hopefully making it simpler to get
started in the future.
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image to caption
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Use NumPy functions a bit more and avoid using np.append too much.
The previous code did not ensure that interpolated points were less than
the tolerance apart.
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Otherwise, it will try to use pre-installed data instead of a local
copy.
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Plotting script is now more flexible and makes it possible to do more
elaborate setup of each individual plot. This is done by adding a JSON
file that holds a record for each plot in the documentation. A plot
can now be restricted to a given bounding box, and there's a choice
between plotting as polygons or linestrings, as well as both low and
medium resolution data to go choose from.
Plots have not been added to the repository yet, they will show up in
a later commit although most of the work is done here. Most
plots are now done as polygons. Generally speaking the plots that are
still based on line data have show some problems when plotted as
polygons. There is still an unsolved wrap-around problem that should
eventually be fixed.
The land.geosjson dataset has been densified manually at the antartic
to make sure that the land mass is depicted correctly in projected
space.
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