Docs and testing for anchoring StdMean

pysal · Mar 30, 2023 · 8ef0947 · 8ef0947
1 parent b97c316
commit 8ef0947
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Showing 3 changed files with 68 additions and 33 deletions.
diff --git a/mapclassify/classifiers.py b/mapclassify/classifiers.py
@@ -1543,11 +1543,12 @@ class StdMean(MapClassifier):
     Notes
     -----
 
-    If anchor is True, the closed upper bound of the first class is set to
-    min(y)+std(y), while the open lower bound of the last class is set to
-    max(y)-std(y). k is ignored if anchor is True, and is determined
-    by the number of standar deviations required to span the range of
-    y. multiples is also ignored if anchor is True.
+    If anchor is True, one of the intervals will its closed upper bound equal to
+    the mean of y. Intermediate intervals will have widths equal to the standard
+    deviation of y. The first interval will be closed on the minimum value of
+    y, and the last interval will be closed on the maximum of y. The first and
+    last intervals may have widths different from the intermediate intervals.
+
 
     Examples
     --------

diff --git a/mapclassify/tests/test_mapclassify.py b/mapclassify/tests/test_mapclassify.py
@@ -623,13 +623,13 @@ def test_UserDefined_invariant(self):
         numpy.testing.assert_array_almost_equal(ud.counts, numpy.array([0, 3, 0, 0]))
 
 
-class TestStdMeanAnchor(unittest.TestCase):
-    def setUp(self):
+class TestStdMeanAnchor:
+    def setup_method(self):
         self.V = load_example()
 
     def test_StdMeanAnchor(self):
         sm = StdMean(self.V, anchor=True)
-        bins = np.array(
+        bins = numpy.array(
             [
                 125.92810345,
                 672.57333208,
@@ -642,9 +642,9 @@ def test_StdMeanAnchor(self):
                 4111.45,
             ]
         )
-        counts = np.array([50, 6, 1, 0, 0, 0, 0, 0, 1])
-        np.testing.assert_array_almost_equal(sm.bins, bins)
-        np.testing.assert_array_almost_equal(sm.counts, counts)
+        counts = numpy.array([50, 6, 1, 0, 0, 0, 0, 0, 1])
+        numpy.testing.assert_array_almost_equal(sm.bins, bins)
+        numpy.testing.assert_array_almost_equal(sm.counts, counts)
 
 
 class TestMaxP:

diff --git a/notebooks/06_api.ipynb b/notebooks/06_api.ipynb
@@ -23,7 +23,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.167785Z",
      "start_time": "2022-11-05T15:10:14.404320Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [],
    "source": [
@@ -46,13 +47,14 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.182165Z",
      "start_time": "2022-11-05T15:10:19.171353Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'2.4.2+78.gc62d2d7.dirty'"
+       "'2.4.2+107.gb97c316a.dirty'"
       ]
      },
      "execution_count": 2,
@@ -71,7 +73,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.586837Z",
      "start_time": "2022-11-05T15:10:19.187232Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -295,7 +298,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.595711Z",
      "start_time": "2022-11-05T15:10:19.589037Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -339,7 +343,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.603460Z",
      "start_time": "2022-11-05T15:10:19.598526Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -374,7 +379,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.611996Z",
      "start_time": "2022-11-05T15:10:19.608075Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -399,7 +405,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.619168Z",
      "start_time": "2022-11-05T15:10:19.614412Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -440,7 +447,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.627988Z",
      "start_time": "2022-11-05T15:10:19.621853Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -474,7 +482,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.634396Z",
      "start_time": "2022-11-05T15:10:19.629847Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -508,7 +517,8 @@
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.641115Z",
      "start_time": "2022-11-05T15:10:19.636017Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
@@ -537,18 +547,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-11-05T15:10:19.691302Z",
      "start_time": "2022-11-05T15:10:19.645124Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "StdMean               \n",
+       "StdMean\n",
        "\n",
        "   Interval      Count\n",
        "----------------------\n",
@@ -559,29 +570,30 @@
        "(75.37, 96.40] |     4"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "classify(y, 'Std_Mean')"
+    "mapclassify.classify(y, 'Std_Mean')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 15,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-10-26T03:01:45.977181Z",
      "start_time": "2022-10-26T03:01:45.931234Z"
-    }
+    },
+    "tags": []
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "StdMean               \n",
+       "StdMean\n",
        "\n",
        "   Interval      Count\n",
        "----------------------\n",
@@ -593,13 +605,35 @@
        "(93.83, 96.40] |     1"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mapclassify.classify(y, 'Std_Mean', anchor=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(38.43622446938775, 18.466069465206047, 17.9, 96.400002)"
+      ]
+     },
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "classify(y, 'Std_Mean', anchor=True)"
+    "y.mean(), y.std(), y.min(), y.max()"
    ]
   },
   {
@@ -626,7 +660,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.10"
   }
  },
  "nbformat": 4,