remove deprecation warnings for credible_interval and include_circ (#…

…1548)

* remove deprecation warnings credible_interval and include_circ_vars

* add missing file and update changelog

* fix docstring

* black

CHANGELOG.md

@@ -11,6 +11,7 @@
 
 ### Deprecation
 * Removed Geweke diagnostic ([1545](https://github.com/arviz-devs/arviz/pull/1545))
+* Removed credible_interval and include_circ arguments ([1548](https://github.com/arviz-devs/arviz/pull/1548)) 
 
 ### Documentation
 

arviz/plots/__init__.py

@@ -9,7 +9,7 @@
 from .energyplot import plot_energy
 from .essplot import plot_ess
 from .forestplot import plot_forest
-from .hdiplot import plot_hdi, plot_hpd
+from .hdiplot import plot_hdi
 from .jointplot import plot_joint
 from .kdeplot import plot_kde
 from .khatplot import plot_khat
@@ -35,7 +35,6 @@
     "plot_ess",
     "plot_forest",
     "plot_hdi",
-    "plot_hpd",
     "plot_joint",
     "plot_kde",
     "plot_khat",

arviz/plots/backends/bokeh/loopitplot.py

@@ -34,7 +34,7 @@ def plot_loo_pit(
     y,
     color,
     textsize,
-    credible_interval,
+    hdi_prob,
     plot_kwargs,
     backend_kwargs,
     show,
@@ -96,9 +96,7 @@ def plot_loo_pit(
             fill_kwargs.setdefault(
                 "step", "mid" if plot_kwargs["drawstyle"] == "steps-mid" else None
             )
-            fill_kwargs.setdefault(
-                "legend_label", "{:.3g}% credible interval".format(credible_interval)
-            )
+            fill_kwargs.setdefault("legend_label", "{:.3g}% credible interval".format(hdi_prob))
     elif use_hdi:
         if hdi_kwargs is None:
             hdi_kwargs = {}

arviz/plots/backends/matplotlib/loopitplot.py

@@ -33,7 +33,7 @@ def plot_loo_pit(
     y,
     color,
     textsize,
-    credible_interval,
+    hdi_prob,
     plot_kwargs,
     backend_kwargs,
     show,
@@ -92,7 +92,7 @@ def plot_loo_pit(
             fill_kwargs.setdefault(
                 "step", "mid" if plot_kwargs["drawstyle"] == "steps-mid" else None
             )
-            fill_kwargs.setdefault("label", "{:.3g}% credible interval".format(credible_interval))
+            fill_kwargs.setdefault("label", "{:.3g}% credible interval".format(hdi_prob))
     elif use_hdi:
         if hdi_kwargs is None:
             hdi_kwargs = {}
@@ -129,7 +129,7 @@ def plot_loo_pit(
     ax.tick_params(labelsize=xt_labelsize)
     if legend:
         if not (use_hdi or (ecdf and ecdf_fill)):
-            label = "{:.3g}% credible interval".format(credible_interval) if ecdf else "Uniform"
+            label = "{:.3g}% credible interval".format(hdi_prob) if ecdf else "Uniform"
             ax.plot([], label=label, **plot_unif_kwargs)
         ax.legend()
 

arviz/plots/densityplot.py

@@ -3,7 +3,7 @@
 
 from ..data import convert_to_dataset
 from ..rcparams import rcParams
-from ..utils import _var_names, credible_interval_warning
+from ..utils import _var_names
 from .plot_utils import default_grid, get_plotting_function, make_label, xarray_var_iter
 
 
@@ -29,7 +29,6 @@ def plot_density(
     backend=None,
     backend_kwargs=None,
     show=None,
-    credible_interval=None,
 ):
     """Generate KDE plots for continuous variables and histograms for discrete ones.
 
@@ -102,13 +101,11 @@ def plot_density(
         check the plotting method of the backend.
     show : bool, optional
         Call backend show function.
-    credible_interval: float, optional
-        deprecated: Please see hdi_prob
+
     Returns
     -------
     axes : matplotlib axes or bokeh figures
 
-
     Examples
     --------
     Plot default density plot
@@ -163,9 +160,6 @@ def plot_density(
 
         >>> az.plot_density([centered, non_centered], var_names=["mu"], bw=.9)
     """
-    if credible_interval:
-        hdi_prob = credible_interval_warning(credible_interval, hdi_prob)
-
     if not isinstance(data, (list, tuple)):
         datasets = [convert_to_dataset(data, group=group)]
     else:

arviz/plots/forestplot.py

@@ -1,7 +1,7 @@
 """Forest plot."""
 from ..data import convert_to_dataset
 from ..rcparams import rcParams
-from ..utils import _var_names, credible_interval_warning, get_coords
+from ..utils import _var_names, get_coords
 from .plot_utils import get_plotting_function
 
 
@@ -34,7 +34,6 @@ def plot_forest(
     backend_config=None,
     backend_kwargs=None,
     show=None,
-    credible_interval=None,
 ):
     """Forest plot to compare HDI intervals from a number of distributions.
 
@@ -115,8 +114,6 @@ def plot_forest(
         check the plotting method of the backend.
     show: bool, optional
         Call backend show function.
-    credible_interval: float, optional
-        deprecated: Please see hdi_prob
 
     Returns
     -------
@@ -183,9 +180,6 @@ def plot_forest(
         >>>                            figsize=(9, 7))
         >>> axes[0].set_title('Estimated theta for 8 schools model')
     """
-    if credible_interval:
-        hdi_prob = credible_interval_warning(credible_interval, hdi_prob)
-
     if not isinstance(data, (list, tuple)):
         data = [data]
 

arviz/plots/hdiplot.py

@@ -8,7 +8,6 @@
 
 from ..rcparams import rcParams
 from ..stats import hdi
-from ..utils import credible_interval_warning
 from .plot_utils import get_plotting_function
 
 
@@ -29,7 +28,6 @@ def plot_hdi(
     backend=None,
     backend_kwargs=None,
     show=None,
-    credible_interval=None,
 ):
     r"""
     Plot HDI intervals for regression data.
@@ -76,8 +74,6 @@ def plot_hdi(
         These are kwargs specific to the backend being used. Passed to ::``
     show : bool, optional
         Call backend show function.
-    credible_interval : float, optional
-        Deprecated: Please see hdi_prob
 
     Returns
     -------
@@ -114,9 +110,6 @@ def plot_hdi(
         >>> az.plot_hdi(x_data, hdi_data=hdi_data[1], color="k", ax=ax, fill_kwargs={"alpha": .2})
 
     """
-    if credible_interval:
-        hdi_prob = credible_interval_warning(credible_interval, hdi_prob)
-
     if hdi_kwargs is None:
         hdi_kwargs = {}
 
@@ -189,8 +182,3 @@ def plot_hdi(
     plot = get_plotting_function("plot_hdi", "hdiplot", backend)
     ax = plot(**hdiplot_kwargs)
     return ax
-
-
-def plot_hpd(*args, **kwargs):  # noqa: D103
-    warnings.warn("plot_hpd has been deprecated, please use plot_hdi", DeprecationWarning)
-    return plot_hdi(*args, **kwargs)

arviz/plots/loopitplot.py

@@ -17,7 +17,7 @@ def plot_loo_pit(
     ecdf_fill=True,
     n_unif=100,
     use_hdi=False,
-    credible_interval=None,
+    hdi_prob=None,
     figsize=None,
     textsize=None,
     color="C0",
@@ -49,8 +49,8 @@ def plot_loo_pit(
     ecdf : bool, optional
         Plot the difference between the LOO-PIT Empirical Cumulative Distribution Function
         (ECDF) and the uniform CDF instead of LOO-PIT kde.
-        In this case, instead of overlaying uniform distributions, the beta ``credible_interval``
-        interval around the theoretical uniform CDF is shown. This approximation only holds
+        In this case, instead of overlaying uniform distributions, the beta ``hdi_prob``
+        around the theoretical uniform CDF is shown. This approximation only holds
         for large S and ECDF values not vary close to 0 nor 1. For more information, see
         `Vehtari et al. (2019)`, `Appendix G <https://avehtari.github.io/rhat_ess/rhat_ess.html>`_.
     ecdf_fill : bool, optional
@@ -60,8 +60,8 @@ def plot_loo_pit(
         Number of datasets to simulate and overlay from the uniform distribution.
     use_hdi : bool, optional
         Compute expected hdi values instead of overlaying the sampled uniform distributions.
-    credible_interval : float, optional
-        Theoretical credible interval. Works with ``use_hdi=True`` or ``ecdf=True``.
+    hdi_prob : float, optional
+        Probability for the highest density interval. Works with ``use_hdi=True`` or ``ecdf=True``.
     figsize : figure size tuple, optional
         If None, size is (8 + numvars, 8 + numvars)
     textsize: int, optional
@@ -139,11 +139,11 @@ def plot_loo_pit(
     unif = None
     x_vals = None
 
-    if credible_interval is None:
-        credible_interval = rcParams["stats.hdi_prob"]
+    if hdi_prob is None:
+        hdi_prob = rcParams["stats.hdi_prob"]
     else:
-        if not 1 >= credible_interval > 0:
-            raise ValueError("The value of credible_interval should be in the interval (0, 1]")
+        if not 1 >= hdi_prob > 0:
+            raise ValueError("The value of hdi_prob should be in the interval (0, 1]")
 
     if ecdf:
         loo_pit.sort()
@@ -152,20 +152,16 @@ def plot_loo_pit(
         # ideal unnormalized ECDF of uniform distribution with n_data_points points
         # it is used indistinctively as x or p(u<x) because for u~U(0,1) they are equal
         unif_ecdf = np.arange(n_data_points + 1)
-        p975 = stats.beta.ppf(
-            0.5 + credible_interval / 2, unif_ecdf + 1, n_data_points - unif_ecdf + 1
-        )
-        p025 = stats.beta.ppf(
-            0.5 - credible_interval / 2, unif_ecdf + 1, n_data_points - unif_ecdf + 1
-        )
+        p975 = stats.beta.ppf(0.5 + hdi_prob / 2, unif_ecdf + 1, n_data_points - unif_ecdf + 1)
+        p025 = stats.beta.ppf(0.5 - hdi_prob / 2, unif_ecdf + 1, n_data_points - unif_ecdf + 1)
         unif_ecdf = unif_ecdf / n_data_points
     else:
         x_vals, loo_pit_kde = kde(loo_pit)
 
         unif = np.random.uniform(size=(n_unif, loo_pit.size))
         if use_hdi:
             n_obs = loo_pit.size
-            hdi_ = stats.beta(n_obs / 2, n_obs / 2).ppf((1 - credible_interval) / 2)
+            hdi_ = stats.beta(n_obs / 2, n_obs / 2).ppf((1 - hdi_prob) / 2)
             hdi_odds = (hdi_ / (1 - hdi_), (1 - hdi_) / hdi_)
 
     loo_pit_kwargs = dict(
@@ -192,7 +188,7 @@ def plot_loo_pit(
         legend=legend,
         y_hat=y_hat,
         y=y,
-        credible_interval=credible_interval,
+        hdi_prob=hdi_prob,
         plot_kwargs=plot_kwargs,
         backend_kwargs=backend_kwargs,
         show=show,

arviz/plots/posteriorplot.py

@@ -1,7 +1,7 @@
 """Plot posterior densities."""
 from ..data import convert_to_dataset
 from ..rcparams import rcParams
-from ..utils import _var_names, credible_interval_warning, get_coords
+from ..utils import _var_names, get_coords
 from .plot_utils import default_grid, filter_plotters_list, get_plotting_function, xarray_var_iter
 
 
@@ -30,7 +30,6 @@ def plot_posterior(
     backend=None,
     backend_kwargs=None,
     show=None,
-    credible_interval=None,
     **kwargs
 ):
     """Plot Posterior densities in the style of John K. Kruschke's book.
@@ -110,8 +109,6 @@ def plot_posterior(
         check the plotting method of the backend.
     show: bool, optional
         Call backend show function.
-    credible_interval: float or str, optional
-        deprecated: Please see hdi_prob
     **kwargs
         Passed as-is to plt.hist() or plt.plot() function depending on the value of `kind`.
 
@@ -197,9 +194,6 @@ def plot_posterior(
 
         >>> az.plot_posterior(data, var_names=['mu'], hdi_prob=.75)
     """
-    if credible_interval:
-        hdi_prob = credible_interval_warning(credible_interval, hdi_prob)
-
     data = convert_to_dataset(data, group=group)
     if transform is not None:
         data = transform(data)

arviz/plots/violinplot.py

@@ -1,7 +1,7 @@
 """Plot posterior traces as violin plot."""
 from ..data import convert_to_dataset
 from ..rcparams import rcParams
-from ..utils import _var_names, credible_interval_warning
+from ..utils import _var_names
 from .plot_utils import default_grid, filter_plotters_list, get_plotting_function, xarray_var_iter
 
 
@@ -27,7 +27,6 @@ def plot_violin(
     backend=None,
     backend_kwargs=None,
     show=None,
-    credible_interval=None,
 ):
     """Plot posterior of traces as violin plot.
 
@@ -97,8 +96,6 @@ def plot_violin(
         check the plotting method of the backend.
     show: bool, optional
         Call backend show function.
-    credible_interval: float, optional
-        deprecated: Please see hdi_prob
 
     Returns
     -------
@@ -123,9 +120,6 @@ def plot_violin(
         >>> az.plot_violin(data, var_names="tau", transform=np.log)
 
     """
-    if credible_interval:
-        hdi_prob = credible_interval_warning(credible_interval, hdi_prob)
-
     data = convert_to_dataset(data, group="posterior")
     if transform is not None:
         data = transform(data)
@@ -141,7 +135,7 @@ def plot_violin(
         hdi_prob = rcParams["stats.hdi_prob"]
     else:
         if not 1 >= hdi_prob > 0:
-            raise ValueError("The value of credible_interval should be in the interval (0, 1]")
+            raise ValueError("The value of hdi_prob should be in the interval (0, 1]")
 
     violinplot_kwargs = dict(
         ax=ax,

arviz/stats/__init__.py

@@ -11,7 +11,6 @@
     "bfmi",
     "compare",
     "hdi",
-    "hpd",
     "kde",
     "loo",
     "loo_pit",