def gen_hour_macd_values(stk_code, source='jq', title=''):
if source == 'jq':
# df_30 = get_k_data_JQ(stk_code, start_date=add_date_str(get_current_date_str(), -20),
# end_date=add_date_str(get_current_date_str(), 1), freq='30m')
# df_60 = get_k_data_JQ(stk_code, start_date=add_date_str(get_current_date_str(), -20),
# end_date=add_date_str(get_current_date_str(), 1), freq='60m')
df_30 = get_k_data_JQ(stk_code, count=120,
end_date=add_date_str(get_current_date_str(), 1), freq='30m')
df_60 = get_k_data_JQ(stk_code, count=120,
end_date=add_date_str(get_current_date_str(), 1), freq='60m')
elif source == 'ts':
df_30 = my_pro_bar(stk_code, start=add_date_str(get_current_date_str(), -20), freq='30min')
df_60 = my_pro_bar(stk_code, start=add_date_str(get_current_date_str(), -20), freq='60min')
# 去掉volume为空的行
df_30 = df_30.loc[df_30.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_60 = df_60.loc[df_60.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_30['MACD'], _, _ = talib.MACD(df_30.close,
fastperiod=12, slowperiod=26,
signalperiod=9)
df_60['MACD'], _, _ = talib.MACD(df_60.close,
fastperiod=12, slowperiod=26,
signalperiod=9)
# 生成图片
df_30 = df_30.dropna()
df_60 = df_60.dropna()
if str(df_60.index[-1]) > get_current_datetime_str():
df_30 = df_30[:-1]
df_60 = df_60[:-1]
return df_30, df_60
# encoding=utf-8
# encoding=utf-8
# encoding=utf-8
def gen_Hour_MACD_Pic(stk_code, source='jq', title=''):
if source == 'jq':
df_30 = get_k_data_JQ(stk_code,
start_date=add_date_str(get_current_date_str(),
-20),
end_date=add_date_str(get_current_date_str(), 1),
freq='30m')
df_60 = get_k_data_JQ(stk_code,
start_date=add_date_str(get_current_date_str(),
-20),
end_date=add_date_str(get_current_date_str(), 1),
freq='60m')
elif source == 'ts':
df_30 = my_pro_bar(stk_code,
start=add_date_str(get_current_date_str(), -20),
freq='30min')
df_60 = my_pro_bar(stk_code,
start=add_date_str(get_current_date_str(), -20),
freq='60min')
# 去掉volume为空的行
df_30 = df_30.loc[df_30.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_60 = df_60.loc[df_60.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_30['MACD'], _, _ = talib.MACD(df_30.close,
fastperiod=12,
slowperiod=26,
signalperiod=9)
df_60['MACD'], _, _ = talib.MACD(df_60.close,
fastperiod=12,
slowperiod=26,
signalperiod=9)
# 生成图片
df_30 = df_30.dropna()
df_60 = df_60.dropna()
fig, ax = plt.subplots(ncols=1, nrows=4)
ax[0].plot(range(0, len(df_30)),
df_30['close'],
'g*--',
label='close_30min')
ax[1].bar(range(0, len(df_30)), df_30['MACD'], label='MACD_30min')
ax[2].plot(range(0, len(df_60)),
df_60['close'],
'g*--',
label='close_60min')
ax[3].bar(range(0, len(df_60)), df_60['MACD'], label='MACD_60min')
# 设置下标
ax[1] = addXticklabel_list(
ax[1],
list([str(x)[-11:-3] for x in df_30['datetime']]),
30,
rotation=45)
ax[3].set_xticks(list(range(0, len(df_60['datetime']))))
ax[3].set_xticklabels(list([str(x)[-11:-3] for x in df_60['datetime']]),
rotation=45)
for ax_sig in ax:
ax_sig.legend(loc='best')
plt.title(stk_code + title)
fig.tight_layout()
plt.subplots_adjust(wspace=0, hspace=1) # 调整子图间距
# plt.close()
return fig