From 538ef426f92d030dd7a03310365d6bb78fdc6d7b Mon Sep 17 00:00:00 2001 From: jingboyitiji Date: Wed, 6 Aug 2025 19:59:54 +0800 Subject: [PATCH] =?UTF-8?q?=E5=9B=BE=E7=89=87=E6=8A=A5=E5=91=8A=E7=9B=B8?= =?UTF-8?q?=E5=85=B3=E6=80=A7=E7=B3=BB=E6=95=B0=E4=BF=9D=E7=95=99=E4=B8=A4?= =?UTF-8?q?=E4=BD=8D=E5=B0=8F=E6=95=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lib/tools.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/tools.py b/lib/tools.py index 3536cce..5a4a043 100644 --- a/lib/tools.py +++ b/lib/tools.py @@ -959,7 +959,7 @@ def find_best_models(date='', global_config=None): ciridate = last_trading_day_str global_config['logger'].info(f'计算预测{last_trading_day}的次日{last_trading_day}最佳模型') global_config['logger'].info( - f'{date}真实价格：{true_price[true_price["ds"] == last_trading_day_str]["y"].values[0]}') + f'{date}真实价格：{true_price[true_price["ds"] == ciridate]["y"].values[0]}') price = df[['data_date', wd, 'model_id']] price = price[(price['data_date'] == ciridate) | (price['data_date'] == date)] @@ -1098,7 +1098,7 @@ def plot_pp_predict_result(y_hat, global_config,wd='yuedu'): y = pd.read_csv('juxitingdataset/指标数据.csv')[['ds', 'y']][-30:] xgx_df = pd.read_csv('juxitingdataset/相关系数.csv') xgx_df = xgx_df.rename(columns={xgx_df.columns[0]: '指标', xgx_df.columns[1]: '系数'}) - top_10_correlations = xgx_df.sort_values(by='系数', ascending=False)[1:11].round().astype({'系数': int}) + top_10_correlations = xgx_df.sort_values(by='系数', ascending=False)[1:11].round(2) y['ds'] = pd.to_datetime(y['ds']) y = y[y['ds'] < y_hat['ds'].iloc[0]] @@ -1138,7 +1138,7 @@ def plot_pp_predict_result(y_hat, global_config,wd='yuedu'): 'next_march_price': '次三月', 'next_april_price': '次四月', }, inplace=True) columns = y_hat.columns.tolist() - data = [round(num) for num in y_hat.values.ravel().tolist()] + data = [[round(num) for num in y_hat.values.ravel().tolist()]] # 将日期转换为字符串格式 for row in data: