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xarray usage #1

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Mar 24, 2021
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xarray usage #1

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18 changes: 11 additions & 7 deletions src/plotting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,15 +14,19 @@ def plot_marginals(
true_values: pd.Series = None,
):
"""Plot marginal ability parameters against true values."""
qs = infd.posterior[var_name].to_series().unstack().quantile([0.1, 0.9]).T
qs["truth"] = true_values
qs["truth_in_interval"] = (qs["truth"] < qs[0.9]) & (qs["truth"] > qs[0.1])
qs = qs.sort_values(0.9)
y = np.linspace(*ax.get_ylim(), len(qs))
qs = infd.posterior[[var_name]].quantile([0.1, 0.9], dim=("chain", "draw"))
qs["truth"] = (("skater_name",), true_values)
qs["truth_in_interval"] = (
(qs["truth"] < qs[var_name].sel(quantile=0.9)) &
(qs["truth"] > qs[var_name].sel(quantile=0.1))
)
qs = qs.sortby(qs[var_name].sel(quantile=0.9))
y = np.linspace(*ax.get_ylim(), qs.dims["skater_name"])
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This is probably the piece that is more xarray specific and can be confusing. qs.dims["skater_name"] returns an the length of the dimension as integer. The key is in the difference between dimension and coordinate. Here both things have the same name, like in all ArviZ generated datasets but this is not a requirement in xarray. qs.skater_name or qs.coords.skater_name will return a DataArray with all the skater name values.

ax.set_yticks(y)
ax.set_yticklabels(qs.index)
ax.set_yticklabels(qs.skater_name)
ax.hlines(
y, qs[0.1], qs[0.9], color="tab:blue", label="90% marginal interval"
y, qs[var_name].sel(quantile=0.1), qs.sel(quantile=0.9),
color="tab:blue", label="90% marginal interval"
)
if true_values is not None:
ax.scatter(
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