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earthkit-plots's Issues
How to generate line graph from numpy arrays
Is your feature request related to a problem? Please describe.
I tried to call "line()" in different ways but all failed. E.g.:
import earthkit.plots
import numpy as np
x = np.array([0,1,2,3])
y = np.array([5,6,7,8])
fig = earthkit.plots.line(x=x, y=y)
fig.show()
fails with:
Cannot find a wrapper for class: builtins.NoneType, returning unwrapped object
...
File ~/git/earthkit-plots/earthkit/plots/inputs.py:57, in xarray(self, data, args, kwargs)
55 else:
56 try:
---> 57 dataset = earthkit.data.from_object(data).to_xarray().squeeze()
58 except (NotImplementedError, ValueError):
59 return None
AttributeError: 'NoneType' object has no attribute 'to_xarray'
Describe the solution you'd like
No response
Describe alternatives you've considered
No response
Additional context
No response
Organisation
ECMWF
Bug when specifying regular latitude-longitude domains which wrap the dateline
What happened?
WHen plotting domains which wrap the dateline, the entire width of the globe is shown, rather than just the specified domain.
What are the steps to reproduce the bug?
chart = earthkit.plots.Map(domain=[170, 190, -10, 10], crs=ccrs.PlateCarree())
chart.borders()
chart.coastlines()
chart.gridlines()
chart.show()
Version
latest
Platform (OS and architecture)
MacOS
Relevant log output
No response
Accompanying data
No response
Organisation
No response
Plot tropical cyclone tracks from BUFR data
Is your feature request related to a problem? Please describe.
The BUFR file https://get.ecmwf.int/repository/test-data/earthkit-data/test-data/A_JSXX01ECEP251200_C_ECMP_20240625120000_tropical_cyclone_track_70W_132degE_6p4degN_bufr4.bin contains tropical cyclone track forecast for multiple ensemble members.
The following code extracts the minimum mslp locations for a given member into a pandas dataframe:
import earthkit.data
f_path = "A_JSXX01ECEP251200_C_ECMP_20240625120000_tropical_cyclone_track_70W_132degE_6p4degN_bufr4.bin"
ds = earthkit.data.from_source("file", f_path)
df = ds.to_pandas(columns=("latitude", "longitude", "pressureReducedToMeanSeaLevel"),
filters={"ensembleMemberNumber": 2, "meteorologicalAttributeSignificance": [1,4]},
required_columns=True)
df = df.dropna()
latitude longitude pressureReducedToMeanSeaLevel
0 6.7 132.8 100700.0
1 5.5 131.2 100600.0
2 6.5 130.0 100600.0
3 8.7 128.3 100400.0
6 11.9 122.9 100900.0
7 13.0 121.8 100800.0
The task is to generate a plot containing a singe track or multiple tracks.
The data also contains the maximum 10m wind locations, which can be extracted with the following code:
df = ds.to_pandas(columns=("latitude", "longitude", "windSpeedAt10M"),
filters={"ensembleMemberNumber": 2, "meteorologicalAttributeSignificance": 3},
required_columns=True)
df = df.dropna()
Describe the solution you'd like
No response
Describe alternatives you've considered
No response
Additional context
No response
Organisation
ECMWF
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