月度回报更新3

.idea/fund_report.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.6" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.7" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="TestRunnerService">

.idea/misc.xml

@@ -3,5 +3,5 @@
   <component name="JavaScriptSettings">
     <option name="languageLevel" value="ES6" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.6" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.7" project-jdk-type="Python SDK" />
 </project>
\ No newline at end of file

app/service/portfolio_diagnose.py

@@ -580,9 +580,10 @@ class PortfolioDiagnose(object):
         return result
 
 
+portfolio = ['HF00002JJ2', 'HF00005DBQ', 'HF0000681Q', 'HF00006693', 'HF00006AZF', 'HF00006BGS']
+portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=portfolio, invest_amount=10000000)
+portfolio_diagnose.optimize()
+
 if __name__ == '__main__':
-    portfolio = ['HF00002JJ2', 'HF00005DBQ', 'HF0000681Q', 'HF00006693', 'HF00006AZF', 'HF00006BGS']
-    portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=portfolio, invest_amount=10000000)
-    portfolio_diagnose.optimize()
     print(portfolio_diagnose.old_correlation)
     # print(portfolio_diagnose.propose_fund_evaluation())

app/service/result_service.py

@@ -143,7 +143,7 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
             col = list(month_earn.columns)
             col_ = {x: x.replace('_earn', '') for x in list(col)}
             month_earn.rename(columns=col_, inplace=True)
-            folio_report_data["contribution_decomposition"] = month_earn
+            # folio_report_data["contribution_decomposition"] = month_earn
 
             # 组合内单个基金净值数据  组合内基金持仓数据
             result_fund_nav_info, result_fund_hoding_info = self.group_fund_basic_info_data(cur_folio_order_data, cur_folio_result_cnav_data, cumulative_profit, total_cost)

app/templates/monthReport.html

@@ -2480,7 +2480,7 @@
           <div>
             <h4 class="item_title">【贡献分解】</h4>
             <div class="gongxianfenjie">
-              <img src="./img/logo-blue.png" alt="" class="contribute_img">
+              <img src={{contribution_decomposition}} alt="" class="contribute_img">
             </div>
           </div>
         </div>

app/utils/draw.py

@@ -105,7 +105,7 @@ def draw_contribution_chart(xlabels, product_list, cumulative):
     fontsize = 22
     # 初始化
     fig = plt.figure(figsize=figsize)
-    ax1 = fig.add_subplot()
+    ax1 = fig.add_subplot(111)
     ax2 = ax1.twiny()
     max_x_count = max([x['data'].size for x in product_list])
     loc = np.arange(max_x_count)  # the x locations for the groups
@@ -145,7 +145,12 @@ def draw_contribution_chart(xlabels, product_list, cumulative):
     ax2.plot(loc, cumulative['data'], color='#C6A774', marker='', linewidth=3, label=cumulative['name'])
     ax2.legend(loc='upper left', fontsize=fontsize)
 
-    plt.show()
+    # plt.show()
+    imgdata = BytesIO()
+    fig.savefig(imgdata, format='png')
+    imgdata.seek(0)  # rewind the data
+    month_return_img = 'data:image/png;base64,' + base64.b64encode(imgdata.getvalue()).decode('utf-8')
+    return month_return_img
 
 
 def draw_comment_chart(xlabels, source_prod, target_prod):

app/utils/radar_chart.py

+# -*- encoding: utf-8 -*-
+# -----------------------------------------------------------------------------
+# @File Name  : radar_chart.py
+# @Time       : 2020/12/1 下午4:50
+# @Author     : X. Peng
+# @Email      : acepengxiong@163.com
+# @Software   : PyCharm
+# -----------------------------------------------------------------------------
+
+import pyecharts.options as opts
+from pyecharts.charts import Radar, Bar
+from snapshot_phantomjs import snapshot
+from pyecharts.render import make_snapshot
+
+
+def gen_radar_chart():
+    """
+    Gallery 使用 pyecharts 1.1.0
+    参考地址: https://echarts.apache.org/examples/editor.html?c=radar
+    目前无法实现的功能:
+    1、雷达图周围的图例的 textStyle 暂时无法设置背景颜色
+    """
+    v1 = [[4300, 10000, 28000, 35000, 50000]]
+
+    (
+        Radar(
+            init_opts=opts.InitOpts(bg_color="#fff", animation_opts=opts.AnimationOpts(animation=False)))
+            .add_schema(
+            schema=[
+                opts.RadarIndicatorItem(name="绝对收益", max_=6500),
+                opts.RadarIndicatorItem(name="业绩持续性", max_=16000),
+                opts.RadarIndicatorItem(name="风险调整后收益", max_=30000),
+                opts.RadarIndicatorItem(name="极端风险", max_=38000),
+                opts.RadarIndicatorItem(name="抗风险能力", max_=52000),
+            ],
+            splitarea_opt=opts.SplitAreaOpts(
+                is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1, color=[
+                    'rgba(198, 167, 116, 0.5)',
+                    'rgba(198, 167, 116, 0.4)',
+                    'rgba(198, 167, 116, 0.3)',
+                    'rgba(198, 167, 116, 0.2)',
+                    'rgba(198, 167, 116, 0.1)',
+                ])
+            ),
+            textstyle_opts=opts.TextStyleOpts(color="#000", font_size=16),
+        )
+            .add(
+            series_name="预算分配（Allocated Budget）",
+            data=v1,
+            linestyle_opts=opts.LineStyleOpts(width=2, color="#C6A774"),
+            tooltip_opts=None
+        )
+            .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
+            .set_global_opts(
+            title_opts=opts.TitleOpts(
+                title="综合评分", subtitle="66.32", pos_top="center", pos_left="46%",
+                title_textstyle_opts={'color': '#333',
+                                      'fontSize': 18,
+                                      'lineHeight': 20,
+                                      'fontWeight': 'normal'
+                                      },
+                subtitle_textstyle_opts={'color': '#222A77',
+                                         'fontSize': 20,
+                                         'lineHeight': 23,
+                                         'fontWeight': 'bolder',
+                                         }),
+            legend_opts=opts.LegendOpts(selected_mode=False, is_show=False)
+        )
+            .render("basic_radar_chart.html")
+    )
+    make_snapshot(snapshot, "basic_radar_chart.html", "basic_radar_chart.png", delay=2)
+
+
+if __name__ == '__main__':
+    gen_radar_chart()
\ No newline at end of file

jinjia2html.py

@@ -3,7 +3,7 @@ from app.service.result_service import UserCustomerResultAdaptor
 
 
 # 准备数据
-from app.utils.draw import draw_month_return_chart
+from app.utils.draw import draw_month_return_chart, draw_contribution_chart
 
 ifa_id = 'USER_INFO15914346866762'
 customer_id = '202009281545001'
@@ -13,27 +13,33 @@ user_customer = UserCustomerResultAdaptor(ifa_id, customer_id)
 df = user_customer.calculate_total_data()
 d = user_customer.calculate_group_result_data()
 
-print(d)
+# print(d)
 
 # 几月综述部分
 
 total_cost = df["total_cost"]/10000
-now_yield = round((df['contribution_decomposition']-1)*100,2)
+now_yield = round((df['cumulative_return']-1)*100,2)
 index_yield = round((df["index_result"]["return_ratio"]-1)*100, 2)
 now_withdrawal = round(df["max_drawdown"][0]*100,2)
 index_withdrawal = round(df["index_result"]["max_drawdown"][0]*100, 2)
 # monthly_return_performance_pic = '_'.join((ifa_id, customer_id, '20201109', 'monthly_return_performance.png'))
 # image_dir = './img/'
 # monthly_return_performance_pic = image_dir + monthly_return_performance_pic
+# 月度回报
 xlabels, product_list, cumulative = user_customer.get_month_return_chart()
 monthly_return_performance_pic = draw_month_return_chart(xlabels, product_list, cumulative)
 
 # 组合数据
 group_result = d["default"]
+print(group_result)
+
+# 贡献分解
+g_data = group_result["contribution_decomposition"]
+contribution_decomposition = draw_contribution_chart(g_data['xlabels'], g_data['product_list'], g_data['cumulative'])
 
 now_month_income = int(group_result["cur_month_profit"])   # 本月收益
 now_year_income = int(group_result["cur_year_profit"])   # 今年累计收益
-totoal_rate_of_return = round((group_result['contribution_decomposition']-1)*100, 2)       # 累计收益率
+totoal_rate_of_return = round((group_result['cumulative_return']-1)*100, 2)       # 累计收益率
 month_rise = round(group_result["cur_month_profit_ratio"]*100, 2)       # 本月涨幅
 year_totoal_rate_of_return = round(group_result["cur_year_profit_ratio"]*100, 2)        # 今年累计收益率
 annualised_return = round(group_result["return_ratio_year"]*100, 2)     # 年化收益率
@@ -73,7 +79,8 @@ data = {'customer_name':'成龙', 'customer_gender':'女',
                             'volatility':index_volatility, 'max_withdrawal':index_max_withdrawal, 'sharpe_ratio':index_sharpe_ratio},
         'monthly_return_performance_pic':monthly_return_performance_pic,
         'group_nav_info': group_nav_info,
-        'group_hoding_info': group_hoding_info
+        'group_hoding_info': group_hoding_info,
+        'contribution_decomposition': contribution_decomposition
         }