<commit_before>import time
import pandas as pd
from pandas import DataFrame, Series
from zaifbot.modules.api.wrapper import BotPublicApi


def get_adx(currency_pair, period='1d', count=5, length=14, to_epoch_time=int(time.time())):
    public_api = BotPublicApi()
    second_api_params = {'period': period, 'count': count + 2 * length - 2, 'to_epoch_time': to_epoch_time}
    price_infos = DataFrame(public_api.everything('ohlc_data', currency_pair, second_api_params))
    return _get_adx(price_infos[['high', 'low', 'time', 'close']].copy(), length, count)


def _get_adx(df, length, count):
    def _create_dict(df, count):
        adxs = df.ix[len(df) - count:, ['time', 'ADX']].to_dict(orient='records')
        return {'success': 1, 'return': {'adxs': adxs}}

    df = pd.concat([df, _get_dm(df)], axis=1)
    df['TR'] = _get_tr(df)
    df = _get_di(df, length, count)
    df['DX'] = abs(df['+DI'] - df['-DI']) / (df['+DI'] + df['-DI']) * 100
    df['ADX'] = (df['DX']).rolling(window=length).mean()
    return _create_dict(df, count)


def _get_dm(df):
    """引数にはhigh,low, closeをカラム名に持つDataFrameをとる"""
    def _calc_dm(row):
        high_dff = max(row['high'], 0)
        low_diff = min(row['low'], 0)

        if abs(high_dff) > abs(low_diff):
            return Series({'+DM': high_dff, '-DM': 0})
        elif abs(high_dff) < abs(low_diff):
            return Series({'+DM': 0, '-DM': abs(low_diff)})
        else:
            return Series({'+DM': 0, '-DM': 0})

    return df.diff().fillna(0).apply(_calc_dm, axis=1)


def _get_tr(df):
    """引数にはhigh, low, closeをカラム名に持つDataFrameをとる"""
    new_row = list()
    new_row.append(0)
    for i in range(1, len(df)):
        tdy_high_minus_ystday_high = df.ix[i, 'high'] - df.ix[i, 'low']
        tdy_high_minus_ystday_close = df.ix[i, 'high'] - df.ix[i - 1, 'close']
        ystday_close_minus_tdy_low = df.ix[i - 1, 'close'] - df.ix[i, 'low']
        new_row.append(max(tdy_high_minus_ystday_high, tdy_high_minus_ystday_close, ystday_close_minus_tdy_low))
    return new_row


def _get_di(df, length, count):
    for i in range(count + length -1):
        df.ix[i + length - 1, '+DI'] = (df.ix[i:i + length - 1, '+DM'].sum() / df.ix[i:i + length - 1, 'TR'].sum()) * 100
        df.ix[i + length - 1, '-DI'] = (df.ix[i:i + length - 1, '-DM'].sum() / df.ix[i:i + length - 1, 'TR'].sum()) * 100
    return df.fillna(0)<commit_msg>fix feedback<commit_after>import time
import pandas as pd
from pandas import DataFrame, Series
from zaifbot.modules.api.wrapper import BotPublicApi


def get_adx(currency_pair, period='1d', count=5, length=14, to_epoch_time=int(time.time())):
    public_api = BotPublicApi()
    second_api_params = {'period': period, 'count': count + 2 * length - 2, 'to_epoch_time': to_epoch_time}
    price_infos = DataFrame(public_api.everything('ohlc_data', currency_pair, second_api_params))
    return _get_adx(price_infos[['high', 'low', 'time', 'close']].copy(), length, count)


def _get_adx(df, length, count):
    def _create_dict(df, count):
        adxs = df.ix[len(df) - count:, ['time', 'ADX']].to_dict(orient='records')
        return {'success': 1, 'return': {'adxs': adxs}}

    df = pd.concat([df, _get_dm(df)], axis=1)
    df['TR'] = _get_tr(df)
    df = _get_di(df, length, count)
    df['DX'] = abs(df['+DI'] - df['-DI']) / (df['+DI'] + df['-DI']) * 100
    df['ADX'] = (df['DX']).rolling(window=length).mean()
    return _create_dict(df, count)


def _get_dm(df):
    """引数にはhigh,low, closeをカラム名に持つDataFrameをとる"""
    def _calc_dm(row):
        high_dff = max(row['high'], 0)
        low_diff = min(row['low'], 0)

        if abs(high_dff) > abs(low_diff):
            return Series({'+DM': high_dff, '-DM': 0})
        elif abs(high_dff) < abs(low_diff):
            return Series({'+DM': 0, '-DM': abs(low_diff)})
        else:
            return Series({'+DM': 0, '-DM': 0})

    return df.diff().fillna(0).apply(_calc_dm, axis=1)


def _get_tr(df):
    """引数にはhigh, low, closeをカラム名に持つDataFrameをとる"""
    new_row = [0]
    for i in range(1, len(df)):
        tdy_high_minus_ystday_high = df.ix[i, 'high'] - df.ix[i, 'low']
        tdy_high_minus_ystday_close = df.ix[i, 'high'] - df.ix[i - 1, 'close']
        ystday_close_minus_tdy_low = df.ix[i - 1, 'close'] - df.ix[i, 'low']
        new_row.append(max(tdy_high_minus_ystday_high, tdy_high_minus_ystday_close, ystday_close_minus_tdy_low))
    return new_row


def _get_di(df, length, count):
    for i in range(count + length -1):
        df.ix[i + length - 1, '+DI'] = (df.ix[i:i + length - 1, '+DM'].sum() / df.ix[i:i + length - 1, 'TR'].sum()) * 100
        df.ix[i + length - 1, '-DI'] = (df.ix[i:i + length - 1, '-DM'].sum() / df.ix[i:i + length - 1, 'TR'].sum()) * 100
    return df.fillna(0)
{'fraction_non_alphanumeric': 0.19271272114574559, 'fraction_numerical': 0.015585509688289806, 'mean_word_length': 3.446629213483146, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '344883', 'n_tokens_mistral': 1961, 'n_tokens_neox': 1871, 'n_words': 385}