Merge branch 'master' into fix-1536

.readthedocs.yml

@@ -27,3 +27,11 @@ python:
       path: .
       extra_requirements:
         - dev
+
+search:
+  ranking:
+
+    notebooks/*: 2
+    api_indicators.html: 1
+    indices.html: -1
+    _modules/*: -3

CHANGES.rst

@@ -19,12 +19,14 @@ New features and enhancements
 Bug fixes
 ^^^^^^^^^
 * Fixed a bug with ``n_escore=-1`` in ``xclim.sdba.adjustment.NpdfTransform`` (:issue:`1515`, :pull:`1515`).
+* In the documentaion, fix the tooltips in the indicator search results (:issue:`1524`, :pull:`1527`).
 * If chunked inputs are passed to indicators ``mean_radiant_temperature``  and ``potential_evapotranspiration``, subcalculations of the solar angle will also use the same chunks, instead of a single one of the same size as the data (:issue:`1536`, :pull:`1542`).
 
 Internal changes
 ^^^^^^^^^^^^^^^^
 * Pinned `cf-xarray` below v0.8.5 in Python3.8 installation to further extend legacy support. (:pull:`1519`).
 * `pip check` in conda builds in GitHub workflows have been temporarily set to always pass. (:pull:`1531`).
+* Configure RtD search rankings to emphasize notebooks and indicators over indices and raw source code. (:pull:`1526`).
 
 v0.46.0 (2023-10-24)
 --------------------

docs/_static/indsearch.js

@@ -30,15 +30,18 @@ fetch('indicators.json')
   });
 
 
-// Populate list of variables
-//function getVariables() {
-//    fetch('variables.json')
-//        .then((res) => {
-//            return res.json();
-//        })
-//}
-//const variables = getVariables();
-
+function escapeHTML(str){
+    /* Escape HTML characters in a string. */
+    var map =
+    {
+        '&': '&',
+        '<': '&lt;',
+        '>': '&gt;',
+        '"': '&quot;',
+        "'": '&#039;'
+    };
+    return str.replace(/[&<>"']/g, function(m) {return map[m];});
+}
 
 function makeKeywordLabel(ind) {
     /* Print list of keywords only if there is at least one. */
@@ -55,7 +58,10 @@ function makeKeywordLabel(ind) {
 function makeVariableList(ind) {
     /* Print list of variables and include mouse-hover tooltip with variable description. */
     return Object.entries(ind.vars).map((kv) => {
-        const tooltip = `<button class="indVarname" title="${kv[1]}" alt="${kv[1]}">${kv[0]}</button>`;
+        /* kv[0] is the variable name, kv[1] is the variable description. */
+        /* Convert kv[1] to a string literal */
+        const text = escapeHTML(kv[1]);
+        const tooltip = `<button class="indVarname" title="${text}" alt="${text}">${kv[0]}</button>`;
         return tooltip
     }).join('');
 }
@@ -66,13 +72,13 @@ function indTemplate(ind) {
   return `
     <div class="indElem" id="${ind.id}">
       <div class="indHeader">
-        <b class="indTitle">${ind.title}</b>
+        <b class="indTitle">${escapeHTML(ind.title)}</b>
         <a class="reference_internal indName" href="api_indicators.html#xclim.indicators.${ind.module}.${ind.name}" title="${ind.name}">
           <code>${ind.module}.${ind.name}</code>
         </a>
       </div>
       <div class="indVars">Uses: ${varlist}</div>
-      <div class="indDesc"><p>${ind.abstract}</p></div>
+      <div class="indDesc"><p>${escapeHTML(ind.abstract)}</p></div>
       ${makeKeywordLabel(ind)}
       <div class="indID">Yaml ID: <code>${ind.id}</code></div>
     </div>

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.46.5-beta
+current_version = 0.46.7-beta
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+).(?P<patch>\d+)(\-(?P<release>[a-z]+))?

tests/test_ensembles.py

@@ -743,8 +743,9 @@ def test_robustness_fractions_empty():
 
 
 def test_robustness_categories():
-    changed = xr.DataArray([0.5, 0.8, 1, 1])
-    agree = xr.DataArray([1, 0.5, 0.5, 1])
+    lat = xr.DataArray([1, 2, 3, 4], dims=("lat",), attrs={"axis": "Y"}, name="lat")
+    changed = xr.DataArray([0.5, 0.8, 1, 1], dims=("lat",), coords={"lat": lat})
+    agree = xr.DataArray([1, 0.5, 0.5, 1], dims=("lat",), coords={"lat": lat})
 
     categories = ensembles.robustness_categories(changed, agree)
     np.testing.assert_array_equal(categories, [2, 3, 3, 1])
@@ -753,6 +754,7 @@ def test_robustness_categories():
         categories.flag_meanings
         == "robust_signal no_change_or_no_signal conflicting_signal"
     )
+    assert categories.lat.attrs["axis"] == "Y"
 
 
 def test_robustness_coefficient():

xclim/__init__.py

@@ -15,7 +15,7 @@
 
 __author__ = """Travis Logan"""
 __email__ = "[email protected]"
-__version__ = "0.46.5-beta"
+__version__ = "0.46.7-beta"
 
 
 _module_data = _files("xclim.data")

xclim/ensembles/_robustness.py

@@ -262,6 +262,11 @@ def robustness_fractions(  # noqa: C901
         )
         out = out.assign(pvals=pvals)
 
+    # Keep attrs on non-modified coordinates
+    for ncrd, crd in fut.coords.items():
+        if ncrd in out.coords:
+            out[ncrd].attrs.update(crd.attrs)
+
     return out
 
 
@@ -370,16 +375,16 @@ def robustness_categories(
         Categorical (int) array following the flag variables CF conventions.
         99 is used as a fill value for points that do not fall in any category.
     """
-    if isinstance(changed_or_fractions, xr.Dataset):
+    src = changed_or_fractions.copy()  # Ensure no inplace changing of coords...
+    if isinstance(src, xr.Dataset):
         # Output of robustness fractions
-        changed = changed_or_fractions.changed
-        agree = changed_or_fractions.agree
+        changed = src.changed
+        agree = src.agree
     else:
-        changed = changed_or_fractions
+        changed = src
 
     # Initial map is all 99, same shape as change_frac
-    robustness = changed * 0 + 99
-
+    robustness = (changed.copy() * 0).astype(int) + 99
     # We go in reverse gear so that the first categories have precedence in the case of multiple matches.
     for i, ((chg_op, agr_op), (chg_thresh, agr_thresh)) in reversed(
         list(enumerate(zip(ops, thresholds), 1))
@@ -392,9 +397,9 @@ def robustness_categories(
             cond = compare(changed, chg_op, chg_thresh) & compare(
                 agree, agr_op, agr_thresh
             )
-        robustness = xr.where(cond, i, robustness)
+        robustness = xr.where(~cond, robustness, i, keep_attrs=True)
 
-    robustness = robustness.astype(np.uint8).assign_attrs(
+    robustness = robustness.assign_attrs(
         flag_values=list(range(1, len(categories) + 1)),
         _FillValue=99,
         flag_descriptions=categories,