chore: import upstream snapshot with attribution
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wehub-resource-sync
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import numpy as np
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import pandas as pd
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from pathlib import Path
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import talipp
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from talipp.indicators import ZLEMA, McGinleyDynamic # SISO
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from talipp.ohlcv import OHLCVFactory
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from talipp.indicators import VWMA, ChaikinOsc, CHOP, ForceIndex, IBS, KVO, SOBV, RogersSatchell # MISO
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from talipp.indicators import StochRSI, KST # SIMO
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from talipp.indicators import ChandeKrollStop, SFX, TTM, VTX, ZigZag # MIMO
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def main():
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fname = "spy_ppo.txt"
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datetime_fmt = "%m/%d/%Y %I:%M:%S %p"
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df = pd.read_csv(fname)
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df["Date"] = pd.to_datetime(df["Date"], format=datetime_fmt)
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df = df.set_index("Date")
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def generate_reference_data_for_siso_indicator(
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indicator_type, parameters, output_name, fname_stem
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):
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df_in = df["Close"]
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indicator = indicator_type(**parameters, input_values=df["Close"].values)
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output_values = {output_name: list(indicator)}
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df_out = pd.concat([df_in, pd.DataFrame(output_values, index=df.index)], axis=1)
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df_out.index = df_out.index.strftime(datetime_fmt)
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df_out.to_csv(Path("out") / f"{fname_stem}.csv")
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def generate_reference_data_for_miso_indicator(
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indicator_type, parameters, output_name, fname_stem
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):
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df_in = df[["Open", "High", "Low", "Close", "Volume"]]
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input_values = OHLCVFactory.from_dict(
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{
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"open": df.Open,
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"high": df.High,
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"low": df.Low,
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"close": df.Close,
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"volume": df.Volume,
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}
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)
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indicator = indicator_type(**parameters, input_values=input_values)
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output_values = {output_name: list(indicator)}
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df_out = pd.concat([df_in, pd.DataFrame(output_values, index=df.index)], axis=1)
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df_out.index = df_out.index.strftime(datetime_fmt)
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df_out.to_csv(Path("out") / f"{fname_stem}.csv")
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def generate_reference_data_for_simo_indicator(
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indicator_type, parameters, output_names, fname_stem
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):
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df_in = df["Close"]
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indicator = indicator_type(**parameters, input_values=df["Close"].values)
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output_values = {output_name: [] for output_name in output_names}
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raw_output_values = list(indicator)
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for raw_output_value in raw_output_values:
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if raw_output_value is None:
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for output_name in output_names:
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output_value_for_name = np.nan
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output_values[output_name].append(output_value_for_name)
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else:
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for output_name in output_names:
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output_value_for_name = getattr(raw_output_value, output_name)
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output_values[output_name].append(output_value_for_name)
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df_out = pd.concat([df_in, pd.DataFrame(output_values, index=df.index)], axis=1)
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df_out.index = df_out.index.strftime(datetime_fmt)
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df_out.to_csv(Path("out") / f"{fname_stem}.csv")
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def generate_reference_data_for_mimo_indicator(
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indicator_type, parameters, output_names, fname_stem
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):
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df_in = df[["Open", "High", "Low", "Close", "Volume"]]
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input_values = OHLCVFactory.from_dict(
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{
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"open": df.Open,
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"high": df.High,
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"low": df.Low,
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"close": df.Close,
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"volume": df.Volume,
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}
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)
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indicator = indicator_type(**parameters, input_values=input_values)
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output_values = {output_name: [] for output_name in output_names}
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raw_output_values = list(indicator)
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for raw_output_value in raw_output_values:
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if raw_output_value is None:
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for output_name in output_names:
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output_value_for_name = np.nan
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output_values[output_name].append(output_value_for_name)
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else:
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for output_name in output_names:
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output_value_for_name = getattr(raw_output_value, output_name)
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output_values[output_name].append(output_value_for_name)
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df_out = pd.concat([df_in, pd.DataFrame(output_values, index=df.index)], axis=1)
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df_out.index = df_out.index.strftime(datetime_fmt)
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df_out.to_csv(Path("out") / f"{fname_stem}.csv")
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def generate_reference_data_for_zigzag_indicator(
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indicator_type, parameters, fname_stem
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):
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input_values = OHLCVFactory.from_dict(
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{
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"open": df.Open,
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"high": df.High,
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"low": df.Low,
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"close": df.Close,
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"volume": df.Volume,
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}
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)
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output_names = ["ohlcv", "type"]
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indicator = indicator_type(**parameters, input_values=input_values)
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output_values = {output_name: [] for output_name in output_names}
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raw_output_values = list(indicator)
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for raw_output_value in raw_output_values:
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if raw_output_value is None:
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for output_name in output_names:
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output_value_for_name = np.nan
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output_values[output_name].append(output_value_for_name)
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else:
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for output_name in output_names:
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output_value_for_name = getattr(raw_output_value, output_name)
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output_values[output_name].append(output_value_for_name)
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df_out = pd.DataFrame(output_values)
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df_out["open"] = df_out["ohlcv"].map(lambda cdl: cdl.open)
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df_out["high"] = df_out["ohlcv"].map(lambda cdl: cdl.high)
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df_out["low"] = df_out["ohlcv"].map(lambda cdl: cdl.low)
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df_out["close"] = df_out["ohlcv"].map(lambda cdl: cdl.close)
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df_out.index.name = "Id"
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del df_out["ohlcv"]
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df_out.to_csv(Path("out") / f"{fname_stem}.csv")
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# SISO
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generate_reference_data_for_siso_indicator(
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ZLEMA, {"period": 5}, "ZLEMA5", "spy_with_zlema"
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)
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generate_reference_data_for_siso_indicator(
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McGinleyDynamic, {"period": 14}, "McGinleyDynamic14", "spy_with_McGinleyDynamic"
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)
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# MISO
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generate_reference_data_for_miso_indicator(
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VWMA, {"period": 20}, "VWMA20", "spy_with_vwma"
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)
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generate_reference_data_for_miso_indicator(
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ChaikinOsc,
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{"fast_period": 5, "slow_period": 7},
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"ChaikinOsc5_7",
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"spy_with_ChaikinOsc",
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)
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generate_reference_data_for_miso_indicator(
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CHOP, {"period": 14}, "CHOP14", "spy_with_chop"
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)
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generate_reference_data_for_miso_indicator(
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ForceIndex, {"period": 20}, "ForceIndex20", "spy_with_ForceIndex"
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)
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generate_reference_data_for_miso_indicator(IBS, {}, "IBS", "spy_with_ibs")
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generate_reference_data_for_miso_indicator(
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KVO, {"fast_period": 5, "slow_period": 10}, "KVO5_10", "spy_with_kvo"
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)
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generate_reference_data_for_miso_indicator(
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SOBV, {"period": 20}, "SOBV20", "spy_with_sobv"
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)
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generate_reference_data_for_miso_indicator(
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RogersSatchell, {"period": 9}, "RSVolat9", "spy_with_rsvolat"
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)
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# SIMO
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generate_reference_data_for_simo_indicator(
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StochRSI,
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{
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"rsi_period": 14,
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"stoch_period": 14,
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"k_smoothing_period": 3,
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"d_smoothing_period": 3,
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},
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["k", "d"],
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"spy_with_StochRSI",
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)
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generate_reference_data_for_simo_indicator(
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KST,
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{
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"roc1_period": 5,
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"roc1_ma_period": 5,
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"roc2_period": 10,
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"roc2_ma_period": 5,
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"roc3_period": 15,
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"roc3_ma_period": 5,
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"roc4_period": 25,
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"roc4_ma_period": 10,
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"signal_period": 9,
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},
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["kst", "signal"],
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"spy_with_kst",
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)
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# MIMO
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generate_reference_data_for_mimo_indicator(
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ChandeKrollStop,
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{"atr_period": 5, "atr_mult": 2.0, "period": 3},
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["short_stop", "long_stop"],
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"spy_with_ChandeKrollStop",
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)
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generate_reference_data_for_mimo_indicator(
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SFX,
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{"atr_period": 12, "std_dev_period": 12, "std_dev_smoothing_period": 3},
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["atr", "std_dev", "ma_std_dev"],
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"spy_with_sfx",
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)
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generate_reference_data_for_mimo_indicator(
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TTM,
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{"period": 20, "bb_std_dev_mult": 2.0, "kc_atr_mult": 2.0},
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["squeeze", "histogram"],
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"spy_with_ttm",
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)
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generate_reference_data_for_mimo_indicator(
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VTX, {"period": 14}, ["plus_vtx", "minus_vtx"], "spy_with_vtx"
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)
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# Other MIMO (ZigZag)
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generate_reference_data_for_zigzag_indicator(
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ZigZag, {"sensitivity": 0.05, "min_trend_length": 3}, "spy_with_ZigZag"
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)
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if __name__ == "__main__":
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main()
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