MAINT remove unused imports

README.md

@@ -111,7 +111,7 @@ $ pip install pandas_ta
 
 Latest Version
 --------------
-Best choice! Version: *0.3.01b*
+Best choice! Version: *0.3.02b*
 * Includes all fixes and updates between **pypi** and what is covered in this README.
 ```sh
 $ pip install -U git+https://github.com/twopirllc/pandas-ta

pandas_ta/__init__.py

@@ -5,7 +5,6 @@ name = "pandas_ta"
 from importlib.util import find_spec
 from pathlib import Path
 from pkg_resources import get_distribution, DistributionNotFound
-import os.path
 
 
 _dist = get_distribution("pandas_ta")

pandas_ta/momentum/dm.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-from numpy import nan as npNaN
 from pandas import DataFrame
 from pandas_ta import Imports
 from pandas_ta.overlap import ma

pandas_ta/momentum/fisher.py

@@ -2,7 +2,7 @@
 from numpy import log as nplog
 from numpy import nan as npNaN
 from pandas import DataFrame, Series
-from pandas_ta.overlap import ema, hl2
+from pandas_ta.overlap import hl2
 from pandas_ta.utils import get_offset, high_low_range, verify_series, zero
 
 
@@ -33,10 +33,8 @@ def fisher(high, low, length=None, signal=None, offset=None, **kwargs):
     result = [npNaN for _ in range(0, length - 1)] + [0]
     for i in range(length, m):
         v = 0.66 * position.iloc[i] + 0.67 * v
-        if v < -0.99:
-            v = -0.999
-        if v > 0.99:
-            v = 0.999
+        if v < -0.99: v = -0.999
+        if v > 0.99: v = 0.999
         result.append(0.5 * (nplog((1 + v) / (1 - v)) + result[i - 1]))
     fisher = Series(result, index=high.index)
     signalma = fisher.shift(signal)

pandas_ta/momentum/ppo.py

@@ -2,7 +2,6 @@
 from pandas import DataFrame
 from pandas_ta import Imports
 from pandas_ta.overlap import ma
-from pandas_ta.overlap import ema, sma
 from pandas_ta.utils import get_offset, verify_series
 
 
@@ -31,7 +30,7 @@ def ppo(close, fast=None, slow=None, signal=None, scalar=None, mamode=None, offs
         ppo = scalar * (fastma - slowma)
         ppo /= slowma
 
-    signalma = ema(ppo, length=signal)
+    signalma = ma("ema", ppo, length=signal)
     histogram = ppo - signalma
 
     # Offset

pandas_ta/performance/drawdown.py

@@ -1,10 +1,7 @@
 # -*- coding: utf-8 -*-
-from sys import float_info as sflt
-
 from numpy import log as nplog
 from numpy import seterr
 from pandas import DataFrame
-
 from pandas_ta.utils import get_offset, verify_series
 
 

pandas_ta/performance/percent_return.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-from pandas import Series
 from pandas_ta.utils import get_offset, verify_series
 
 

pandas_ta/statistics/tos_stdevall.py

@@ -4,7 +4,6 @@ from numpy import arange as npArange
 from numpy import polyfit as npPolyfit
 from numpy import std as npStd
 from pandas import DataFrame, DatetimeIndex, Series
-# from pandas_ta import Imports
 from .stdev import stdev as stdev
 from pandas_ta.utils import get_offset, verify_series
 

pandas_ta/trend/psar.py

@@ -1,7 +1,6 @@
 # -*- coding: utf-8 -*-
 from numpy import nan as npNaN
 from pandas import DataFrame, Series
-from pandas_ta.momentum import dm
 from pandas_ta.utils import get_offset, verify_series, zero
 
 

pandas_ta/trend/vortex.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 from pandas import DataFrame
 from pandas_ta.volatility import true_range
-from pandas_ta.utils import get_drift, get_offset, verify_series, zero
+from pandas_ta.utils import get_drift, get_offset, verify_series
 
 
 def vortex(high, low, close, length=None, drift=None, offset=None, **kwargs):

pandas_ta/utils/_core.py

@@ -4,7 +4,6 @@ from pathlib import Path
 from sys import float_info as sflt
 
 from numpy import argmax, argmin
-from numpy import nan as npNaN
 from pandas import DataFrame, Series
 from pandas.api.types import is_datetime64_any_dtype
 

pandas_ta/utils/_math.py

@@ -12,7 +12,6 @@ from numpy import array as npArray
 from numpy import corrcoef as npCorrcoef
 from numpy import dot as npDot
 from numpy import fabs as npFabs
-from numpy import floor as npFloor
 from numpy import exp as npExp
 from numpy import log as npLog
 from numpy import nan as npNaN
@@ -64,7 +63,7 @@ def erf(x):
 
     # A&S formula 7.1.26
     t = 1.0 / (1.0 + p * x)
-    y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * math.exp(-x * x)
+    y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * npExp(-x * x)
     return sign * y # erf(-x) = -erf(x)
 
 

pandas_ta/utils/_metrics.py

@@ -9,7 +9,7 @@ from pandas import Series, Timedelta
 from ._core import verify_series
 from ._time import total_time
 from ._math import linear_regression, log_geometric_mean
-from pandas_ta import Imports, RATE
+from pandas_ta import RATE
 from pandas_ta.performance import drawdown, log_return, percent_return
 
 

pandas_ta/utils/_time.py

@@ -6,7 +6,6 @@ from typing import Tuple
 from pandas import DataFrame, Timestamp
 
 from pandas_ta import EXCHANGE_TZ, RATE
-from pandas_ta.utils import verify_series
 
 
 def df_dates(df: DataFrame, dates: Tuple[str, list] = None) -> DataFrame:

pandas_ta/volatility/ui.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 from numpy import sqrt as npsqrt
 from pandas_ta.overlap import sma
-from pandas_ta.utils import get_offset, non_zero_range, verify_series
+from pandas_ta.utils import get_offset, verify_series
 
 
 def ui(close, length=None, scalar=None, offset=None, **kwargs):

setup.py

@@ -19,7 +19,7 @@ setup(
         "pandas_ta.volatility",
         "pandas_ta.volume"
     ],
-    version=".".join(("0", "3", "01b")),
+    version=".".join(("0", "3", "02b")),
     description=long_description,
     long_description=long_description,
     author="Kevin Johnson",