From 00f1f0ae924463211b366c21fcc064b39a4786db Mon Sep 17 00:00:00 2001
From: aresnow1 <109642806+aresnow1@users.noreply.github.com>
Date: Wed, 4 Jan 2023 16:13:38 +0800
Subject: [PATCH] BUG: Fix `date_range` and pin sphinx<6.0.0 (#118)

---
 docs/requirements-doc.txt                     |  2 +-
 mars/dataframe/datasource/date_range.py       | 69 ++++++++++++++++++-
 .../tests/test_datasource_execution.py        |  5 ++
 .../stats/tests/test_stats_execution.py       | 18 ++++-
 4 files changed, 91 insertions(+), 3 deletions(-)

diff --git a/docs/requirements-doc.txt b/docs/requirements-doc.txt
index f2bf58f323..c4f0648a8b 100644
--- a/docs/requirements-doc.txt
+++ b/docs/requirements-doc.txt
@@ -10,7 +10,7 @@ pytest-cov>=2.5.0
 pytest-timeout>=1.2.0
 cloudpickle>=1.0.0
 sqlalchemy>=1.2.0
-sphinx>=3.0.0
+sphinx<6.0.0
 pydata-sphinx-theme>=0.3.0
 sphinx-intl>=0.9.9
 ipython>=4.0
diff --git a/mars/dataframe/datasource/date_range.py b/mars/dataframe/datasource/date_range.py
index 655f3a0e37..fca3b45ca6 100644
--- a/mars/dataframe/datasource/date_range.py
+++ b/mars/dataframe/datasource/date_range.py
@@ -17,6 +17,7 @@
 
 import numpy as np
 import pandas as pd
+from pandas import Timestamp, NaT
 from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import Tick
 from pandas._libs.tslibs import timezones
@@ -51,6 +52,72 @@ def normalize_date(dt):  # from pandas/_libs/tslibs/conversion.pyx
 _date_range_use_inclusive = pd_release_version[:2] >= (1, 4)
 
 
+# adapted from pandas.core.arrays.datetimes.generate_range
+def generate_range_count(
+    start=None, end=None, periods=None, offset=None
+):  # pragma: no cover
+    offset = to_offset(offset)
+
+    start = Timestamp(start)
+    start = start if start is not NaT else None
+    end = Timestamp(end)
+    end = end if end is not NaT else None
+
+    if start and not offset.is_on_offset(start):
+        start = offset.rollforward(start)
+
+    elif end and not offset.is_on_offset(end):
+        end = offset.rollback(end)
+
+    if periods is None and end < start and offset.n >= 0:
+        end = None
+        periods = 0
+
+    if end is None:
+        end = start + (periods - 1) * offset
+
+    if start is None:
+        start = end - (periods - 1) * offset
+
+    cur = start
+    count = 0
+    if offset.n >= 0:
+        while cur <= end:
+            count += 1
+
+            if cur == end:
+                # GH#24252 avoid overflows by not performing the addition
+                # in offset.apply unless we have to
+                break
+
+            # faster than cur + offset
+            try:
+                next_date = offset._apply(cur)
+            except AttributeError:
+                next_date = cur + offset
+            if next_date <= cur:
+                raise ValueError(f"Offset {offset} did not increment date")
+            cur = next_date
+    else:
+        while cur >= end:
+            count += 1
+
+            if cur == end:
+                # GH#24252 avoid overflows by not performing the addition
+                # in offset.apply unless we have to
+                break
+
+            # faster than cur + offset
+            try:
+                next_date = offset._apply(cur)
+            except AttributeError:
+                next_date = cur + offset
+            if next_date >= cur:
+                raise ValueError(f"Offset {offset} did not decrement date")
+            cur = next_date
+    return count
+
+
 class DataFrameDateRange(DataFrameOperand, DataFrameOperandMixin):
     _op_type_ = OperandDef.DATE_RANGE
 
@@ -511,7 +578,7 @@ def date_range(
             inclusive = "both"
     else:
         if periods is None:
-            periods = size = int((end - start) / freq + 1)
+            periods = size = generate_range_count(start, end, periods, freq)
         else:
             size = periods
         if inclusive in ("left", "right"):
diff --git a/mars/dataframe/datasource/tests/test_datasource_execution.py b/mars/dataframe/datasource/tests/test_datasource_execution.py
index 224b556970..9480cf570f 100644
--- a/mars/dataframe/datasource/tests/test_datasource_execution.py
+++ b/mars/dataframe/datasource/tests/test_datasource_execution.py
@@ -1007,6 +1007,11 @@ def test_date_range_execution(setup):
     expected = pd.date_range(start="1/1/2018", periods=5, freq="M")
     pd.testing.assert_index_equal(result, expected)
 
+    dr = md.date_range(start="2018/01/01", end="2018/07/01", freq="M")
+    result = dr.execute().fetch()
+    expected = pd.date_range(start="2018/01/01", end="2018/07/01", freq="M")
+    pd.testing.assert_index_equal(result, expected)
+
 
 parquet_engines = ["auto"]
 if pa is not None:
diff --git a/mars/tensor/stats/tests/test_stats_execution.py b/mars/tensor/stats/tests/test_stats_execution.py
index 69404b43ee..b820383d93 100644
--- a/mars/tensor/stats/tests/test_stats_execution.py
+++ b/mars/tensor/stats/tests/test_stats_execution.py
@@ -205,7 +205,6 @@ def test_t_test_execution(setup):
             functools.partial(mt_from_stats, equal_var=False),
             functools.partial(sp_from_stats, equal_var=False),
         ),
-        (ttest_1samp, sp_ttest_1samp),
     ]
 
     fa_raw = np.array([16, 18, 16, 14, 12, 12])
@@ -233,6 +232,23 @@ def test_t_test_execution(setup):
             np.testing.assert_almost_equal(expected[0], result[0])
             np.testing.assert_almost_equal(expected[1], result[1])
 
+    # second param size must be 1 for ttest_1samp
+    fb_raw = np.array([16])
+    fb = tensor(fb_raw)
+    for alt in alternatives:
+        if parse_version(scipy.__version__) >= parse_version("1.6.0"):
+            r = ttest_1samp(fa, fb, alternative=alt)
+        else:
+            r = ttest_1samp(fa, fb)
+        result = r.execute().fetch()
+
+        if parse_version(scipy.__version__) >= parse_version("1.6.0"):
+            expected = sp_ttest_1samp(fa_raw, fb_raw, alternative=alt)
+        else:
+            expected = sp_ttest_1samp(fa_raw, fb_raw)
+        np.testing.assert_almost_equal(expected[0], result[0])
+        np.testing.assert_almost_equal(expected[1], result[1])
+
 
 @pytest.mark.parametrize("chunk_size", [5, 15])
 @pytest.mark.parametrize(