Adding MCSE Plot

docs/source/api/backend/none.rst

@@ -0,0 +1,48 @@
+============
+None backend
+============
+
+.. automodule:: arviz_plots.backend.none
+
+
+Object creation and I/O
+.......................
+
+.. autosummary::
+   :toctree: generated/
+
+   create_plotting_grid
+   show
+
+Geoms
+.....
+
+.. autosummary::
+   :toctree: generated/
+
+   line
+   scatter
+   text
+
+Plot appeareance
+................
+
+.. autosummary::
+   :toctree: generated/
+
+   title
+   ylabel
+   xlabel
+   xticks
+   yticks
+   ticklabel_props
+   remove_ticks
+   remove_axis
+
+Legend
+......
+
+.. autosummary::
+   :toctree: generated/
+
+   legend

docs/source/api/backend/plotly.rst

@@ -0,0 +1,48 @@
+==============
+Plotly backend
+==============
+
+.. automodule:: arviz_plots.backend.plotly
+
+
+Object creation and I/O
+.......................
+
+.. autosummary::
+   :toctree: generated/
+
+   create_plotting_grid
+   show
+
+Geoms
+.....
+
+.. autosummary::
+   :toctree: generated/
+
+   line
+   scatter
+   text
+
+Plot appeareance
+................
+
+.. autosummary::
+   :toctree: generated/
+
+   title
+   ylabel
+   xlabel
+   xticks
+   yticks
+   ticklabel_props
+   remove_ticks
+   remove_axis
+
+Legend
+......
+
+.. autosummary::
+   :toctree: generated/
+
+   legend

docs/source/gallery/backreferences.json

@@ -0,0 +1 @@
+{"plot_forest": [{"basename": "plot_forest_ess", "refname": "gallery_forest_ess", "title": "Forest plot with ESS", "description": "Multiple panel visualization with a forest plot and ESS information"}, {"basename": "plot_forest", "refname": "gallery_forest", "title": "Forest plot", "description": "Default forest plot with marginal distribution summaries"}, {"basename": "plot_forest_shade", "refname": "gallery_forest_shade", "title": "Forest plot with shading", "description": "Forest plot marginal summaries with row shading to enhance reading"}, {"basename": "plot_forest_models", "refname": "gallery_forest_models", "title": "Forest plot comparison", "description": "Forest plot summaries for 1D marginal distributions"}, {"basename": "plot_forest_pp_obs", "refname": "gallery_forest_pp_obs", "title": "Posterior predictive and observations forest plot", "description": "Overlay of forest plot for the posterior predictive samples and the actual observations"}], "plot_dist": [{"basename": "plot_dist_ecdf", "refname": "gallery_dist_ecdf", "title": "ECDF plot", "description": "Facetted ECDF plots for 1D marginals of the distribution"}, {"basename": "plot_dist_hist", "refname": "gallery_dist_hist", "title": "Histogram plot", "description": "Facetted histogram plots for 1D marginals of the distribution"}, {"basename": "plot_dist_kde", "refname": "gallery_dist_kde", "title": "KDE plot", "description": "Facetted KDE plots for 1D marginals of the distribution"}, {"basename": "plot_dist_models", "refname": "gallery_dist_models", "title": "Marginal distribution comparison plot", "description": "Full marginal distribution comparison between different models"}], "plot_mcse": [{"basename": "plot_mcse", "refname": "gallery_mcse", "title": "MCSE Quantile plot", "description": "Facetted quantile MCSE plot"}, {"basename": "plot_mcse_errorbar", "refname": "gallery_mcse_errorbar", "title": "MCSE Quantile plot with errorbars", "description": "Facetted quantile MCSE plot with errorbars"}, {"basename": "plot_mcse_models", "refname": "gallery_mcse_models", "title": "MCSE comparison plot", "description": "Full MCSE comparison between different models"}], "plot_trace": [{"basename": "plot_trace", "refname": "gallery_trace", "title": "Trace plot", "description": "Facetted plot with MCMC traces for each variable"}]}

docs/source/gallery/inference_diagnostics/plot_mcse.py

@@ -0,0 +1,24 @@
+"""
+# MCSE Quantile plot
+
+Facetted quantile MCSE plot
+
+---
+
+:::{seealso}
+API Documentation: {func}`~arviz_plots.plot_mcse`
+:::
+"""
+
+from arviz_base import load_arviz_data
+
+import arviz_plots as azp
+
+azp.style.use("arviz-clean")
+
+data = load_arviz_data("centered_eight")
+pc = azp.plot_mcse(
+    data,
+    backend="none",  # change to preferred backend
+)
+pc.show()

docs/source/gallery/inference_diagnostics/plot_mcse_errorbar.py

@@ -0,0 +1,25 @@
+"""
+# MCSE Quantile plot with errorbars
+
+Facetted quantile MCSE plot with errorbars
+
+---
+
+:::{seealso}
+API Documentation: {func}`~arviz_plots.plot_mcse`
+:::
+"""
+
+from arviz_base import load_arviz_data
+
+import arviz_plots as azp
+
+azp.style.use("arviz-clean")
+
+data = load_arviz_data("centered_eight")
+pc = azp.plot_mcse(
+    data,
+    errorbar=True,
+    backend="none",  # change to preferred backend
+)
+pc.show()

docs/source/gallery/inference_diagnostics/plot_mcse_models.py

@@ -0,0 +1,25 @@
+"""
+# MCSE comparison plot
+
+Full MCSE comparison between different models
+
+---
+
+:::{seealso}
+API Documentation: {func}`~arviz_plots.plot_mcse`
+:::
+"""
+
+from arviz_base import load_arviz_data
+
+import arviz_plots as azp
+
+azp.style.use("arviz-clean")
+
+c = load_arviz_data("centered_eight")
+n = load_arviz_data("non_centered_eight")
+pc = azp.plot_mcse(
+    {"Centered": c, "Non Centered": n},
+    backend="none",  # change to preferred backend
+)
+pc.show()

docs/source/gallery/inference_diagnostics/plot_mcse_models_errorbar.py

@@ -0,0 +1,26 @@
+"""
+# MCSE comparison plot with errorbars
+
+Full MCSE comparison between different models with errorbars
+
+---
+
+:::{seealso}
+API Documentation: {func}`~arviz_plots.plot_mcse`
+:::
+"""
+
+from arviz_base import load_arviz_data
+
+import arviz_plots as azp
+
+azp.style.use("arviz-clean")
+
+c = load_arviz_data("centered_eight")
+n = load_arviz_data("non_centered_eight")
+pc = azp.plot_mcse(
+    {"Centered": c, "Non Centered": n},
+    errorbar=True,
+    backend="none",  # change to preferred backend
+)
+pc.show()

pyproject.toml

@@ -27,7 +27,7 @@ classifiers = [
 dynamic = ["version", "description"]
 dependencies = [
   "arviz-base==0.2",
-  "arviz-stats[xarray]==0.2",
+  "arviz-stats[xarray] @ git+https://github.com/arviz-devs/arviz-stats",
 ]
 
 [tool.flit.module]

src/arviz_plots/backend/bokeh/__init__.py

@@ -298,6 +298,49 @@ def scatter(
     return target.scatter(np.atleast_1d(x), np.atleast_1d(y), **kwargs)
 
 
+def errorbar(
+    x,
+    y,
+    error,
+    target,
+    *,
+    size=unset,
+    marker=unset,
+    color=unset,
+    facecolor=unset,
+    edgecolor=unset,
+    width=unset,
+    **artist_kws,
+):
+    """Interface to bokeh for an errorbar plot."""
+    if color is not unset:
+        if facecolor is unset and edgecolor is unset:
+            facecolor = color
+            edgecolor = color
+        elif facecolor is unset:
+            facecolor = color
+        elif edgecolor is unset:
+            edgecolor = color
+    kwargs = {
+        "size": size,
+        "marker": marker,
+        "fill_color": facecolor,
+        "line_color": edgecolor,
+        "line_width": width,
+    }
+    kwargs = _filter_kwargs(kwargs, artist_kws)
+    if marker == "|":
+        kwargs["marker"] = "dash"
+        kwargs["angle"] = np.pi / 2
+
+    target.scatter(np.atleast_1d(x), np.atleast_1d(y), **kwargs)
+
+    x_err = list(zip(x, x))
+    y_err = [(y_i - err, y_i + err) for y_i, err in zip(y, error)]
+    target.multi_line(xs=x_err, ys=y_err, **kwargs)
+    return target
+
+
 def text(
     x,
     y,

src/arviz_plots/backend/matplotlib/__init__.py

@@ -274,6 +274,42 @@ def scatter(
     return target.scatter(x, y, **_filter_kwargs(kwargs, None, artist_kws))
 
 
+def errorbar(
+    x,
+    y,
+    error,
+    target,
+    *,
+    size=unset,
+    marker=unset,
+    color=unset,
+    facecolor=unset,
+    edgecolor=unset,
+    width=unset,
+    **artist_kws,
+):
+    """Interface to matplotlib for an errorbar plot."""
+    artist_kws.setdefault("zorder", 2)
+    fillable_marker = (marker is unset) or (marker in Line2D.filled_markers)
+    if color is not unset:
+        if facecolor is unset and edgecolor is unset:
+            facecolor = color
+            if fillable_marker:
+                edgecolor = color
+        elif facecolor is unset:
+            facecolor = color
+        elif edgecolor is unset and fillable_marker:
+            edgecolor = color
+    kwargs = {
+        "capsize": size,
+        "marker": marker,
+        "markerfacecolor": facecolor,
+        "markeredgecolor": edgecolor,
+        "elinewidth": width,
+    }
+    return target.errorbar(x, y, error, **_filter_kwargs(kwargs, None, artist_kws))
+
+
 def text(
     x,
     y,

src/arviz_plots/backend/none/__init__.py

@@ -271,6 +271,49 @@ def scatter(
     return artist_element
 
 
+def errorbar(
+    x,
+    y,
+    error,
+    target,
+    *,
+    size=unset,
+    marker=unset,
+    color=unset,
+    facecolor=unset,
+    edgecolor=unset,
+    width=unset,
+    **artist_kws,
+):
+    """Interface to an errorbar plot."""
+    if color is not unset:
+        if facecolor is unset and edgecolor is unset:
+            facecolor = color
+            edgecolor = color
+        elif facecolor is unset:
+            facecolor = color
+        elif edgecolor is unset:
+            edgecolor = color
+    kwargs = {
+        "capsize": size,
+        "marker": marker,
+        "markerfacecolor": facecolor,
+        "markeredgecolor": edgecolor,
+        "elinewidth": width,
+    }
+    if not ALLOW_KWARGS and artist_kws:
+        raise ValueError("artist_kws not empty")
+    artist_element = {
+        "function": "errorbar",
+        "x": np.atleast_1d(x),
+        "y": np.atleast_1d(y),
+        "error": np.atleast_1d(error),
+        **_filter_kwargs(kwargs, artist_kws),
+    }
+    target.append(artist_element)
+    return artist_element
+
+
 def text(
     x,
     y,

src/arviz_plots/plots/__init__.py

@@ -3,6 +3,7 @@
 from .compareplot import plot_compare
 from .distplot import plot_dist
 from .forestplot import plot_forest
+from .mcseplot import plot_mcse
 from .ridgeplot import plot_ridge
 from .tracedistplot import plot_trace_dist
 from .traceplot import plot_trace
@@ -14,4 +15,5 @@
     "plot_trace",
     "plot_trace_dist",
     "plot_ridge",
+    "plot_mcse",
 ]