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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 823290488 | MDExOlB1bGxSZXF1ZXN0NTg1Nzc0MjY4 | 5003 | Add Dataset.plot.streamplot() method | johnomotani 3958036 | closed | 0 | 2 | 2021-03-05T17:41:49Z | 2021-03-30T16:41:08Z | 2021-03-30T16:41:07Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/5003 | Since @dcherian added Quiver plots in #4407, it's fairly simple to extend the functionality to For example (copying from @dcherian's unit test setup) ``` import xarray as xr from matplotlib import pyplot as plt das = [
xr.DataArray(
np.random.randn(3, 3),
dims=["x", "y"],
coords=[range(k) for k in [3, 3]],
)
for _ in [1, 2]
]
ds = xr.Dataset({"u": das[0], "v": das[1]})
ds["mag"] = np.hypot(ds.u, ds.v)
ds.plot.streamplot(x="x",y="y",u="u",v="v", hue="mag")
plt.show()
```
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xarray 13221727 | pull |
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