finish labeling changes in summary

arviz/plots/backends/bokeh/essplot.py

@@ -7,9 +7,7 @@
 
 from . import backend_kwarg_defaults
 from .. import show_layout
-from ...plot_utils import (
-    _create_axes_grid,
-)
+from ...plot_utils import _create_axes_grid
 from ....sel_utils import make_label
 
 

arviz/plots/backends/bokeh/rankplot.py

@@ -7,9 +7,7 @@
 
 from . import backend_kwarg_defaults
 from .. import show_layout
-from ...plot_utils import (
-    _create_axes_grid,
-)
+from ...plot_utils import _create_axes_grid
 from ....sel_utils import make_label
 from ....stats.stats_utils import histogram
 

arviz/plots/backends/matplotlib/ppcplot.py

@@ -7,9 +7,7 @@
 
 from . import backend_show
 from ...kdeplot import plot_kde
-from ...plot_utils import (
-    _create_axes_grid,
-)
+from ...plot_utils import _create_axes_grid
 from ....sel_utils import make_label
 from ....numeric_utils import _fast_kde, histogram, get_bins
 

arviz/plots/backends/matplotlib/rankplot.py

@@ -4,9 +4,7 @@
 import scipy.stats
 
 from . import backend_show
-from ...plot_utils import (
-    _create_axes_grid,
-)
+from ...plot_utils import _create_axes_grid
 from ....sel_utils import make_label
 from ....stats.stats_utils import histogram
 

arviz/sel_utils.py

@@ -4,6 +4,7 @@
 import numpy as np
 import xarray as xr
 
+
 def selection_to_string(selection):
     """Convert dictionary of coordinates to a string for labels.
 
@@ -41,12 +42,14 @@ def make_label(var_name, selection, position="below"):
     if selection:
         sel = selection_to_string(selection)
         if position == "below":
-            sep = "\n"
+            base = "{}\n{}"
         elif position == "beside":
-            sep = " "
+            base = "{}[{}]"
     else:
-        sep = sel = ""
-    return "{}{}{}".format(var_name, sep, sel)
+        sel = ""
+        base = "{}{}"
+    return base.format(var_name, sel)
+
 
 def purge_duplicates(list_in):
     """Remove duplicates from list while preserving order.

arviz/stats/stats.py

@@ -984,7 +984,7 @@ def summary(
     stat_funcs=None,
     extend=True,
     hdi_prob=None,
-    order="C",
+    order=None,
     index_origin=None,
     skipna=False,
     coords: Optional[CoordSpec] = None,
@@ -1031,11 +1031,6 @@ def summary(
     hdi_prob: float, optional
         hdi interval to compute. Defaults to 0.94. This is only meaningful when ``stat_funcs`` is
         None.
-    order: {"C", "F"}
-        If fmt is "wide", use either C or F unpacking order. Defaults to C.
-    index_origin: int
-        If fmt is "wide, select n-based indexing for multivariate parameters.
-        Defaults to rcParam data.index.origin, which is 0.
     skipna: bool
         If true ignores nan values when computing the summary statistics, it does not affect the
         behaviour of the functions passed to ``stat_funcs``. Defaults to false.
@@ -1045,6 +1040,11 @@ def summary(
         Dimensions specification for the variables to be used if the ``fmt`` is ``'xarray'``.
     credible_interval: float, optional
         deprecated: Please see hdi_prob
+    order
+        deprecated: order is now ignored.
+    index_origin
+        deprecated: index_origin is now ignored, modify the coordinate values to change the
+        value used in summary.
 
     Returns
     -------
@@ -1112,7 +1112,12 @@ def summary(
         extra_args["coords"] = coords
     if dims is not None:
         extra_args["dims"] = dims
-    if index_origin is None:
+    if index_origin is not None:
+        warnings.warn(
+            "index_origin has been deprecated. summary now shows coordinate values, "
+            "to change the label shown, modify the coordinate values before calling sumary",
+            DeprecationWarning,
+        )
         index_origin = rcParams["data.index_origin"]
     if hdi_prob is None:
         hdi_prob = rcParams["stats.hdi_prob"]
@@ -1127,10 +1132,9 @@ def summary(
     if not isinstance(fmt, str) or (fmt.lower() not in fmt_group):
         raise TypeError("Invalid format: '{}'. Formatting options are: {}".format(fmt, fmt_group))
 
-    unpack_order_group = ("C", "F")
-    if not isinstance(order, str) or (order.upper() not in unpack_order_group):
-        raise TypeError(
-            "Invalid order: '{}'. Unpacking options are: {}".format(order, unpack_order_group)
+    if order is not None:
+        warnings.warn(
+            "order has been deprecated. summary now shows coordinate values.", DeprecationWarning
         )
 
     alpha = 1 - hdi_prob

arviz/tests/base_tests/test_rcparams.py

@@ -287,7 +287,7 @@ def test_stats_information_criterion(models):
     assert "loo" in df_comp.columns
 
 
-def test_http_type_request(models, monkeypatch):
+def test_http_type_request(monkeypatch):
     def _urlretrive(url, _):
         raise Exception("URL Retrieved: {}".format(url))
 

arviz/tests/base_tests/test_stats.py

@@ -229,40 +229,24 @@ def test_summary_fmt(centered_eight, fmt):
     assert summary(centered_eight, fmt=fmt) is not None
 
 
-@pytest.mark.parametrize("order", ["C", "F"])
-def test_summary_unpack_order(order):
-    data = from_dict({"a": np.random.randn(4, 100, 4, 5, 3)})
-    az_summary = summary(data, order=order, fmt="wide")
+def test_summary_labels():
+    coords1 = list("abcd")
+    coords2 = np.arange(1, 6)
+    data = from_dict(
+        {"a": np.random.randn(4, 100, 4, 5)},
+        coords={"dim1": coords1, "dim2": coords2},
+        dims={"a": ["dim1", "dim2"]},
+    )
+    az_summary = summary(data, fmt="wide")
     assert az_summary is not None
-    if order != "F":
-        first_index = 4
-        second_index = 5
-        third_index = 3
-    else:
-        first_index = 3
-        second_index = 5
-        third_index = 4
     column_order = []
-    for idx1 in range(first_index):
-        for idx2 in range(second_index):
-            for idx3 in range(third_index):
-                if order != "F":
-                    column_order.append("a[{},{},{}]".format(idx1, idx2, idx3))
-                else:
-                    column_order.append("a[{},{},{}]".format(idx3, idx2, idx1))
+    for coord1 in coords1:
+        for coord2 in coords2:
+            column_order.append("a[{}, {}]".format(coord1, coord2))
     for col1, col2 in zip(list(az_summary.index), column_order):
         assert col1 == col2
 
 
-@pytest.mark.parametrize("origin", [0, 1, 2, 3])
-def test_summary_index_origin(origin):
-    data = from_dict({"a": np.random.randn(2, 50, 10)})
-    az_summary = summary(data, index_origin=origin, fmt="wide")
-    assert az_summary is not None
-    for i, col in enumerate(list(az_summary.index)):
-        assert col == "a[{}]".format(i + origin)
-
-
 @pytest.mark.parametrize(
     "stat_funcs", [[np.var], {"var": np.var, "var2": lambda x: np.var(x) ** 2}]
 )
@@ -274,12 +258,12 @@ def test_summary_stat_func(centered_eight, stat_funcs):
 
 def test_summary_nan(centered_eight):
     centered_eight = deepcopy(centered_eight)
-    centered_eight.posterior.theta[:, :, 0] = np.nan
+    centered_eight.posterior["theta"].loc[{"school": "Deerfield"}] = np.nan
     summary_xarray = summary(centered_eight)
     assert summary_xarray is not None
-    assert summary_xarray.loc["theta[0]"].isnull().all()
+    assert summary_xarray.loc["theta[Deerfield]"].isnull().all()
     assert (
-        summary_xarray.loc[[ix for ix in summary_xarray.index if ix != "theta[0]"]]
+        summary_xarray.loc[[ix for ix in summary_xarray.index if ix != "theta[Deerfield]"]]
         .notnull()
         .all()
         .all()
@@ -288,7 +272,7 @@ def test_summary_nan(centered_eight):
 
 def test_summary_skip_nan(centered_eight):
     centered_eight = deepcopy(centered_eight)
-    centered_eight.posterior.theta[:, :10, 1] = np.nan
+    centered_eight.posterior["theta"].loc[{"draw": slice(10), "school": "Deerfield"}] = np.nan
     summary_xarray = summary(centered_eight)
     theta_1 = summary_xarray.loc["theta[Deerfield]"].isnull()
     assert summary_xarray is not None
@@ -302,10 +286,14 @@ def test_summary_bad_fmt(centered_eight, fmt):
         summary(centered_eight, fmt=fmt)
 
 
-@pytest.mark.parametrize("order", [1, "bad_order"])
-def test_summary_bad_unpack_order(centered_eight, order):
-    with pytest.raises(TypeError):
-        summary(centered_eight, order=order)
+def test_summary_order_deprecation(centered_eight):
+    with pytest.warns(DeprecationWarning, match="order"):
+        summary(centered_eight, order="C")
+
+
+def test_summary_index_origin_deprecation(centered_eight):
+    with pytest.warns(DeprecationWarning, match="index_origin"):
+        summary(centered_eight, index_origin=1)
 
 
 @pytest.mark.parametrize("scale", ["log", "negative_log", "deviance"])