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Brian's python workshop, where he keeps his tools, paint, and anything else useful.

Home Page: https://blaylockbk.github.io/Carpenter_Workshop/

License: BSD 3-Clause "New" or "Revised" License

Python 100.00%

cartopy matplotlib python tools

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carpenter_workshop's Issues

Easy map method to include global submap

Map of area of interest
In corner, put a map of the globe orthograpgic proj, with outline of area of interest.

modernize setup.py

Replace setup.py with setup.cfg and pyproject.toml, etc. etc.

Ocean and Land color doesn't plot for NorthPolarStereo

ax = EasyMap(figsize=10, dark=True, crs=ccrs.NorthPolarStereo()).OCEAN().LAND().ax

But for some reason the south pole does work...

ax = EasyMap(figsize=10, dark=True, crs=ccrs.SouthPolarStereo()).OCEAN().LAND().ax

TypeError when running code on Google Colab

I'm running code from HRRR Data. It works perfectly in a local Jupyter notebook, but runs into an error on Google Colab (with condacolab installed). Am I missing a library somewhere?

My code :


!pip install -q condacolab
import condacolab
condacolab.install()

!mamba install -q -c conda-forge cartopy metpy herbie-data
!pip install git+https://github.com/blaylockbk/Carpenter_Workshop.git

from herbie import Herbie
from toolbox import EasyMap, pc
from paint.standard2 import cm_tmp

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from metpy import units

H = Herbie(
    "2022-12-24",
    model="hrrr",
    product="sfc",
    fxx=0,
)

ds = H.xarray("TMP:2 m above")

ax = EasyMap("50m", crs=ds.herbie.crs, figsize=[20, 12]).STATES().ax
ax.set_extent([-125, -105, 35, 50])
p = ax.pcolormesh(
    ds.longitude,
    ds.latitude,
    ds.t2m.metpy.convert_units('degF'),
    transform=pc,
    **cm_tmp(units="F").cmap_kwargs,
)
plt.colorbar(
    p,
    ax=ax,
    orientation="horizontal",
    pad=0.01,
    shrink=0.8,
    **cm_tmp(units="F").cbar_kwargs,
)

ax.set_title(
    f"{ds.model.upper()}: {H.product_description}\nValid: {ds.valid_time.dt.strftime('%H:%M UTC %d %b %Y').item()}",
    loc="left",
)
ax.set_title(ds.t2m.GRIB_name, loc="right")

The resulting error on Colab:

TypeError                                 Traceback (most recent call last)
<ipython-input-9-5245a609d364> in <module>
     24     ds.t2m.metpy.convert_units('degF'),
     25     transform=pc,
---> 26     **cm_tmp(units="F").cmap_kwargs,
     27 )
     28 plt.colorbar(

1 frames
/usr/local/lib/python3.8/site-packages/paint/standard2.py in _segmented_cmap(name, colors, bounds, extend)
    101 def _segmented_cmap(name, colors, bounds, extend="neither"):
    102     cmap = mcolors.LinearSegmentedColormap.from_list(name, colors, N=len(bounds) + 1)
--> 103     norm = mcolors.BoundaryNorm(bounds, cmap.N, extend=extend)
    104     return cmap, norm
    105 

TypeError: __init__() got an unexpected keyword argument 'extend'

Add additional map backgrounds

https://predictablysunny.com/posts/inset_map_cartopy/

Plot terrain and bathymetry

I have always wanted to implement a way to plot terrain and bathymetry data.

This tweet reminded I still want to do this: https://twitter.com/DanJonesOcean/status/1448597935508369411?s=20

I could implement the example from here:
https://github.com/mattphysics/plot_bathymetry/blob/master/plot_bathymetry.ipynb

Any better methods and data sources for adding Bathymetry?
Could get data from:

Publish on conda-forge

Publish on Conda-forge since this is an optional dependency of Herbie and goes2go

Publish on PyPI

This should probably be published on PyPI since it is an optional dependency of Herbie and goes2go.

Update fig letters function

https://matplotlib.org/stable/tutorials/text/annotations.html#placing-artist-at-anchored-axes-locations

Does this make it cleaner to add fig letters and should I update my add_fig_letters function to use it

common_features: add terrain background map plotted from GFS

I would like to add this as a map background option for the cartopy_tools.common_features class...

Could be terrain field from GFS, HRRR, or another model

This would require Herbie being installed, and getting the data.

from herbie import Herbie

model = 'hrrr'

def TERRAIN2(self, date, model):
    H = Herbie(date, model)
    ds = H.terrain()

    # color the map background water
    self.ax.set_facecolor(water_color)

    # plot the terrain
    ax.pcolormesh(
        ds.longitude,
        ds.latitude,
        ds.orog,
        transform=pc,
        **cm_terrain(water=False, land_top=5500).cmap_kwargs
    )

Add hillshade map background given an array of surface height

Based on: http://willrudisill.net/coding/2023/04/10/make_dem_hillshademaps.html

Other references

blaylockbk / carpenter_workshop Goto Github PK

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