Merge branch 'dev' of http://47.100.44.39:10001/pengxiong/fund_report into dev

app/service/portfolio_diagnose.py

@@ -1165,6 +1165,21 @@ class PortfolioDiagnose(object):
             radar_data.append(get_radar_data(fund))
         return radar_data
 
+    def original_fund_index_compare(self, total_fund_cnav_df):
+        compare_data = []
+        for fund in self.portfolio:
+            data_df = total_fund_cnav_df[[fund, "index"]].dropna()
+            data_df[fund + "_return_ratio"] = (data_df[fund] / data_df[fund].iloc[0] - 1)*100
+            data_df["index_return_ratio"] = (data_df["index"] / data_df["index"].iloc[0] - 1) * 100
+            xlabels = ["" for i in range(len(data_df))]
+
+            com_data = {
+                "xlabels": xlabels,
+                "index": {'name': '中证500', 'data': data_df["index_return_ratio"].values},
+                "fund": {'name': fund, 'data': data_df[fund + "_return_ratio"].values},
+            }
+            compare_data.append(com_data)
+        return compare_data
 
 # portfolio = ['HF00002JJ2', 'HF00005DBQ', 'HF0000681Q', 'HF00006693', 'HF00006AZF', 'HF00006BGS']
 # portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=portfolio, invest_amount=10000000)

app/utils/draw.py

@@ -342,6 +342,57 @@ def draw_combination_chart(xlabels, new_combination, origin_combination, index):
     return return_compare_img
 
 
+def draw_index_combination_chart(compare_data):
+    """基金和指数对比图"""
+    xlabels, origin_combination, index = compare_data["xlabels"], compare_data["fund"], compare_data["index"]
+    figsize = (20, 12)
+    # 标签文字大小
+    fontsize = 22
+    # 初始化
+    fig = plt.figure(figsize=figsize)
+    ax1 = fig.add_subplot(111)
+    ax3 = ax1.twiny()
+    ax1.spines['top'].set_visible(False)
+    ax1.spines['right'].set_visible(False)
+    ax1.spines['bottom'].set_visible(False)
+    ax1.spines['left'].set_visible(False)
+    ax3.spines['top'].set_visible(False)
+    ax3.spines['right'].set_visible(False)
+    ax3.spines['bottom'].set_visible(False)
+    ax3.spines['left'].set_visible(False)
+    # ax = plt.gca()  # gca:get current axis得到当前轴
+    # ax.spines['bottom'].set_position(('data', 0))  # data表示通过值来设置x轴的位置，将x轴绑定在y=0的位置
+    product_list = [origin_combination, index]
+    max_x_count = max([x['data'].size for x in product_list])
+    loc = np.arange(max_x_count)  # the x locations for the groups
+
+    # 坐标轴
+    ax1.tick_params(labelsize=fontsize)
+    ax3.tick_params(labelsize=fontsize)
+    ax1.set_xticks(loc)
+    ax1.set_xticklabels(xlabels)
+    # ax1.yaxis.set_major_formatter(FuncFormatter(to_percent))
+    ax1.set_yticks([])
+    ax3.set_yticks([])
+    ax3.set_xticks([])
+    ax1.axis('off')
+    ax3.axis('off')
+
+    # 基金折线图
+    ax1.plot(loc, origin_combination['data'], color='#D40000', marker='', linewidth=3)
+    ax1.legend(loc='upper left', fontsize=fontsize)
+
+    # 指数折线图
+    ax3.plot(loc, index['data'], color='grey', marker='', linewidth=3)
+    ax3.legend(loc='upper right', fontsize=fontsize)
+
+    # plt.show()
+    imgdata = BytesIO()
+    fig.savefig(imgdata, format='png', bbox_inches='tight')
+    imgdata.seek(0)  # rewind the data
+    return_compare_img = 'data:image/png;base64,' + base64.b64encode(imgdata.getvalue()).decode('utf-8')
+    return return_compare_img
+
 if __name__ == '__main__':
     # xlabels = ('2020-1', '2020-2', '2020-3', '2020-4', '2020-5', '2020-6', '2020-7', '2020-8', '2020-9', '2020-10', '2020-11', '2020-12')
     # product = {'name': '月度回报率', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}

app/utils/jinjia2html_v2.py

@@ -12,7 +12,7 @@ import os
 
 # 准备数据
 from app.utils.draw import draw_month_return_chart, draw_contribution_chart, draw_combination_chart, \
-    draw_old_combination_chart
+    draw_old_combination_chart, draw_index_combination_chart
 from app.utils.html_to_pdf import html_to_pdf
 from app.utils.radar_chart import gen_radar_chart
 
@@ -48,7 +48,15 @@ class DataIntegrate:
     def get_group_result(self):
         for group_name, group_result in self.d.items():
             portfolio_diagnose = self.get_portfolio_diagnose(group_result["fund_id_list"], invest_amount=group_result["total_cost"])
-            cur_group_portfolio_result = {}
+            cur_group_portfolio_result = {
+                'new_correlation': [],
+                'propose_fund_data_list': [],
+                'suggestions_result': {},
+                'suggestions_result_asset': {},
+                'return_compare_pic': [],
+                'indicator_compare': [],
+                'new_group_evaluation': []
+            }
 
             # 旧持仓组合点评
             self.comments_on_position_portfolio(portfolio_diagnose, group_name, cur_group_portfolio_result)
@@ -62,12 +70,12 @@ class DataIntegrate:
             self.get_old_compare_pic(cur_group_portfolio_result)
             # 旧相关性
             self.get_old_correlation(portfolio_diagnose, cur_group_portfolio_result)
-            # # 新增基金
-            self.propose_fund(portfolio_diagnose, cur_group_portfolio_result)
-            # # 新收益比较
-            self.get_transfer_suggestions(portfolio_diagnose, group_name, cur_group_portfolio_result)
-            # # 新相关性
-            self.get_new_correlation(portfolio_diagnose, cur_group_portfolio_result)
+            # # # 新增基金
+            # self.propose_fund(portfolio_diagnose, cur_group_portfolio_result)
+            # # # 新收益比较
+            # self.get_transfer_suggestions(portfolio_diagnose, group_name, cur_group_portfolio_result)
+            # # # 新相关性
+            # self.get_new_correlation(portfolio_diagnose, cur_group_portfolio_result)
 
             self.all_folio_result[group_name] = cur_group_portfolio_result
 
@@ -117,9 +125,12 @@ class DataIntegrate:
         """个基点评."""
         single_fund_data_list = []
         portfolio_evaluation = portfolio_diagnose.old_portfolio_evaluation()
-        radar_chart_data = portfolio_diagnose.single_fund_radar()
+        # radar_chart_data = portfolio_diagnose.single_fund_radar()
+        # with futures.ProcessPoolExecutor(os.cpu_count()) as executor:
+        #     res = executor.map(gen_radar_chart, radar_chart_data)
+        index_compare_chart_data = portfolio_diagnose.original_fund_index_compare(self.user_customer.fund_cnav_total)
         with futures.ProcessPoolExecutor(os.cpu_count()) as executor:
-            res = executor.map(gen_radar_chart, radar_chart_data)
+            res = executor.map(draw_index_combination_chart, index_compare_chart_data)
         res = list(res)
         for i in range(len(portfolio_evaluation)):
             if portfolio_evaluation[i]['status'] == '保留':