DEV numpy prenan fn TST new numba file MAINT minor refactor BUG #690 …

…pivots

Makefile

@@ -14,6 +14,9 @@ init:
 test_metrics:
 	pytest -vv -s -l --cache-clear tests/test_metrics.py
 
+test_numba:
+	pytest -vv -s -l --cache-clear tests/test_numba.py
+
 test_studies:
 	pytest -vv -s -l --cache-clear tests/test_studies.py
 

README.md

@@ -197,7 +197,7 @@ $ pip install pandas_ta[full]
 
 Development Version
 -------------------
-The _development_ version, _0.3.95b_, includes _numerous_ bug fixes, speed improvements and better documentation since release, _0.3.14b_.
+The _development_ version, _0.3.96b_, includes _numerous_ bug fixes, speed improvements and better documentation since release, _0.3.14b_.
 ```sh
 $ pip install -U git+https://github.com/twopirllc/pandas-ta.git@development
 ```
@@ -538,7 +538,7 @@ df.ta.cores
 df.ta.ds
 
 # Set the Data Source (ds) so that df.ta.ticker() can download ohlcv data.
-# Available Data Sources: "yf", "polgon"
+# Available Data Sources: "yf", "polygon"
 df.ta.ds = "yf"
 ```
 

pandas_ta/core.py

@@ -1260,10 +1260,7 @@ def pivots(self, method=None, anchor=None, **kwargs: DictLike):
         high = self._get_column(kwargs.pop("high", "high"))
         low = self._get_column(kwargs.pop("low", "low"))
         close = self._get_column(kwargs.pop("close", "close"))
-        result = pivots(
-            open_=open_, high=high, low=low, close=close,
-            method=method, anchor=anchor, **kwargs,
-        )
+        result = pivots(open_=open_, high=high, low=low, close=close, method=method, anchor=anchor, **kwargs)
         return self._post_process(result, **kwargs)
 
     def pwma(self, length=None, offset=None, **kwargs: DictLike):

pandas_ta/overlap/pivots.py

@@ -165,13 +165,14 @@ def pivots(
     ]
     method = v_str(method, methods[0])
 
-    dt_index = close.index
-    if dt_index.size < 3:
+    if close.index.size < 3:
         return  # Emergency Break
 
     if not v_datetime_ordered(close):
-        dt_index = to_datetime(close.index, unit="ms")
+        print("[!] Pivots requires a datetime ordered index.")
+        return
 
+    dt_index = close.index
     freq = infer_freq(dt_index)
 
     if anchor and isinstance(anchor, str) and len(anchor) >= 1:
@@ -189,6 +190,7 @@ def pivots(
                 "close": close.resample(anchor).last()
             }
         )
+        df.dropna(inplace=True)
     else:
         df = DataFrame(
             data={"open": open_, "high": high, "low": low, "close": close},

pandas_ta/overlap/sma.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-from numpy import convolve, ndarray, ones
+from numpy import convolve, ones
 from numba import njit
 from pandas import Series
 from pandas_ta._typing import Array, DictLike, Int

pandas_ta/utils/_core.py

@@ -168,6 +168,9 @@ def _speed_group(
     result = []
     for i in group:
         r = df.ta(i, talib=talib, timed=True)
+        if r is None:
+            print(f"[S] {i} skipped due to returning None")
+            continue # ta.pivots() sometimes returns None
         ms = float(r.timed.split(" ")[0].split(" ")[0])
         result.append({index_name: i, "ms": ms, "secs": ms2secs(ms, p)})
     return result

pandas_ta/utils/_numba.py

@@ -5,13 +5,22 @@
 from pandas_ta._typing import Array, Int, IntFloat
 
 __all__ = [
+    "np_prenan",
     "np_prepend",
     "np_rolling",
     "np_shift",
 ]
 
 
-# Utilities
+@njit(cache=True)
+def np_prenan(x: Array, n: Int, value: IntFloat = nan) -> Array:
+    """Prepend n values, typically np.nan, to array x."""
+    if n > 0:
+        x[:n - 1] = value
+        return x
+    return x
+
+
 @njit(cache=True)
 def np_prepend(x: Array, n: Int, value: IntFloat = nan) -> Array:
     """Prepend n values, typically np.nan, to array x."""

pandas_ta/volatility/natr.py

@@ -66,8 +66,8 @@ def natr(
         from talib import NATR
         natr = NATR(high, low, close, length)
     else:
-        natr = scalar / close
-        natr *= atr(
+        natr = (scalar / close) * \
+        atr(
             high=high, low=low, close=close, length=length,
             mamode=mamode, drift=drift, talib=mode_tal,
             offset=offset, **kwargs

setup.py

@@ -20,7 +20,7 @@
         "pandas_ta.volatility",
         "pandas_ta.volume"
     ],
-    version=".".join(("0", "3", "95b")),
+    version=".".join(("0", "3", "96b")),
     description=long_description,
     long_description=long_description,
     author="Kevin Johnson",

tests/test_numba.py

@@ -0,0 +1,34 @@
+# -*- coding: utf-8 -*-
+import numpy as np
+import pandas_ta as ta
+
+from pytest import mark
+
+
+@mark.parametrize("array,n,result", [
+    (np.ones(5), 2, np.array([np.nan, 1.0, 1.0, 1.0, 1.0])),
+    (np.ones(5), -2, np.ones(5))
+])
+def test_np_prenan(array, n, result):
+    np.testing.assert_array_equal(ta.np_prenan(array, n), result)
+
+
+@mark.parametrize("array,n,result", [
+    (np.ones(5), 2, np.array([np.nan, np.nan, 1.0, 1.0, 1.0, 1.0, 1.0])),
+    (np.ones(5), -2, np.ones(5))
+])
+def test_np_prepend(array, n, result):
+    np.testing.assert_array_equal(ta.np_prepend(array, n), result)
+
+
+@mark.parametrize("array,n,fn,result", [(np.ones(5), 2, None, np.ones(5))])
+def test_np_rolling(array, n, fn, result):
+    np.testing.assert_array_equal(ta.np_rolling(array, n, fn), result)
+
+
+@mark.parametrize("array,n,result", [
+    (np.ones(5), 2, np.array([np.nan, np.nan, 1.0, 1.0, 1.0])),
+    (np.ones(5), -2, np.array([1.0, 1.0, 1.0, np.nan, np.nan]))
+])
+def test_np_shift(array, n, result):
+    np.testing.assert_array_equal(ta.np_shift(array, n), result)

tests/test_utils.py

@@ -277,27 +277,6 @@ def test_inv_norm_value(value, result):
     assert ta.utils.inv_norm(value) == result
 
 
-@mark.parametrize("array,window,result", [
-    (np.ones(5), 2, np.array([np.nan, np.nan, 1.0, 1.0, 1.0, 1.0, 1.0])),
-    (np.ones(5), -2, np.ones(5))
-])
-def test_np_prepend(array, window, result):
-    np.testing.assert_array_equal(ta.np_prepend(array, window), result)
-
-
-@mark.parametrize("array,window,fn,result", [(np.ones(5), 2, None, np.ones(5))])
-def test_np_rolling(array, window, fn, result):
-    np.testing.assert_array_equal(ta.np_rolling(array, window, fn), result)
-
-
-@mark.parametrize("array,window,result", [
-    (np.ones(5), 2, np.array([np.nan, np.nan, 1.0, 1.0, 1.0])),
-    (np.ones(5), -2, np.array([1.0, 1.0, 1.0, np.nan, np.nan]))
-])
-def test_np_shift(array, window, result):
-    np.testing.assert_array_equal(ta.np_shift(array, window), result)
-
-
 def test_symmetric_triangle():
     np.testing.assert_array_equal(ta.utils.symmetric_triangle(), np.array([1,1]))
     np.testing.assert_array_equal(ta.utils.symmetric_triangle(weighted=True), np.array([0.5, 0.5]))
@@ -399,5 +378,5 @@ def test_zero(value, result):
 @mark.parametrize("talib", [False, True])
 @mark.parametrize("verbose", [False, True])
 def test_indicator_speed_talib_verbose(df, talib, verbose):
-    resultdf =ta.speed_test(df, talib=talib, verbose=verbose)
+    resultdf = ta.speed_test(df, talib=talib, verbose=verbose)
     assert isinstance(resultdf, DataFrame)