From b4b2b8b663fb8aa394dc1e713d515bba3afb5db1 Mon Sep 17 00:00:00 2001
From: Ivan Ogasawara <ivan.ogasawara@gmail.com>
Date: Mon, 11 Jan 2021 21:26:38 -0400
Subject: [PATCH] Add tests for ntile

---
 ibis_omniscidb/tests/test_window.py | 92 +++++++++++++++++++++++++++++
 1 file changed, 92 insertions(+)
 create mode 100644 ibis_omniscidb/tests/test_window.py

diff --git a/ibis_omniscidb/tests/test_window.py b/ibis_omniscidb/tests/test_window.py
new file mode 100644
index 0000000..4242977
--- /dev/null
+++ b/ibis_omniscidb/tests/test_window.py
@@ -0,0 +1,92 @@
+from typing import List, Union
+
+import ibis
+import pandas as pd
+import pytest
+from ibis.expr import types as ir
+
+# from ibis.expr import window as ww
+
+
+# ntile function version using pandas
+def _ntile(
+    data: Union[pd.Series, pd.core.groupby.generic.SeriesGroupBy], bucket: int
+):
+    """
+    NTILE divides given data set into a number of buckets.
+
+    It divides an ordered and grouped data set into a number of buckets
+    and assigns the appropriate bucket number to each row.
+    Return an integer ranging from 0 to `bucket - 1`, dividing the
+    partition as equally as possible.
+    Adapted from:
+    https://gist.github.com/xmnlab/2c1f93df1a6c6bde4e32c8579117e9cc
+
+    Parameters
+    ----------
+    data : pandas.core.groupby.generic.SeriesGroupBy or pandas.Series
+    bucket: int
+
+    Returns
+    -------
+    pandas.Series
+    """
+    if isinstance(data, pd.core.groupby.generic.SeriesGroupBy):
+        return pd.concat([_ntile(group, bucket) for name, group in data])
+
+    n = data.shape[0]
+    sub_n = n // bucket
+    diff = n - (sub_n * bucket)
+
+    result = []
+    for i in range(bucket):
+        sub_result = [i] * (sub_n + (1 if diff else 0))
+        result.extend(sub_result)
+        if diff > 0:
+            diff -= 1
+    return pd.Series(result, index=data.index)
+
+
+@pytest.mark.parametrize(
+    'column_name,group_by,order_by,buckets',
+    [('string_col', ['string_col'], 'id', 7)],
+)
+def test_ntile(
+    con: ibis.omniscidb.OmniSciDBClient,
+    alltypes: ibis.expr.types.TableExpr,
+    df_alltypes: pd.DataFrame,
+    column_name: str,
+    group_by: List[str],
+    order_by: List[str],
+    buckets: int,
+):
+    def prepare_expr(
+        t: ir.TableExpr,
+        column_name: str,
+        buckets: int,
+        group_by: List[str],
+        order_by: List[str],
+    ):
+        return t.mutate(
+            val=t[column_name]
+            .ntile(buckets=buckets)
+            .over(
+                ibis.window(
+                    following=0,
+                    group_by=group_by,
+                    order_by=order_by,
+                )
+            )
+        )
+
+    df_grouped = df_alltypes.sort_values(order_by).groupby(group_by)
+    result_pd = _ntile(df_grouped[column_name], buckets)
+
+    expr = prepare_expr(alltypes, column_name, buckets, group_by, order_by)
+
+    # result_pd = result_pd.sort_values(order_by).reset_index(drop=True)
+    result_expr = expr.execute().sort_values(order_by).reset_index(drop=True)
+
+    pd.testing.assert_series_equal(
+        result_pd.astype('int64'), result_expr.val.astype('int64')
+    )