58 lines
1.4 KiB
Python
58 lines
1.4 KiB
Python
|
"""Smoke tests: every public class can be constructed and emits the right shape."""
|
||
|
|
|
||
|
|
from __future__ import annotations
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import wickra as ta
|
||
|
|
|
||
|
|
|
||
|
|
def test_version_is_a_nonempty_string():
|
||
|
|
assert isinstance(ta.__version__, str)
|
||
|
|
assert ta.__version__
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"cls, args",
|
||
|
|
[
|
||
|
|
(ta.SMA, (14,)),
|
||
|
|
(ta.EMA, (14,)),
|
||
|
|
(ta.WMA, (14,)),
|
||
|
|
(ta.RSI, (14,)),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_scalar_batch_returns_same_length(cls, args, sine_prices):
|
||
|
|
out = cls(*args).batch(sine_prices)
|
||
|
|
assert out.shape == sine_prices.shape
|
||
|
|
assert out.dtype == np.float64
|
||
|
|
|
||
|
|
|
||
|
|
def test_macd_batch_returns_n_by_3(sine_prices):
|
||
|
|
out = ta.MACD().batch(sine_prices)
|
||
|
|
assert out.shape == (sine_prices.size, 3)
|
||
|
|
|
||
|
|
|
||
|
|
def test_bollinger_batch_returns_n_by_4(sine_prices):
|
||
|
|
out = ta.BollingerBands().batch(sine_prices)
|
||
|
|
assert out.shape == (sine_prices.size, 4)
|
||
|
|
|
||
|
|
|
||
|
|
def test_atr_batch_shape(ohlc_series):
|
||
|
|
high, low, close = ohlc_series
|
||
|
|
out = ta.ATR(14).batch(high, low, close)
|
||
|
|
assert out.shape == close.shape
|
||
|
|
|
||
|
|
|
||
|
|
def test_stochastic_batch_shape(ohlc_series):
|
||
|
|
high, low, close = ohlc_series
|
||
|
|
out = ta.Stochastic(14, 3).batch(high, low, close)
|
||
|
|
assert out.shape == (close.size, 2)
|
||
|
|
|
||
|
|
|
||
|
|
def test_obv_batch_shape(ohlc_series):
|
||
|
|
_, _, close = ohlc_series
|
||
|
|
volume = np.ones_like(close)
|
||
|
|
out = ta.OBV().batch(close, volume)
|
||
|
|
assert out.shape == close.shape
|