456

app/utils/draw.py

@@ -89,7 +89,7 @@ def draw_month_return_chart(xlabels, product_list, cumulative):
 
     # plt.show()
     imgdata = BytesIO()
-    fig.savefig(imgdata, format='png')
+    fig.savefig(imgdata, format='png', bbox_inches='tight')
     imgdata.seek(0)  # rewind the data
     month_return_img = 'data:image/png;base64,' + base64.b64encode(imgdata.getvalue()).decode('utf-8')
     return month_return_img
@@ -100,7 +100,7 @@ def draw_contribution_chart(xlabels, product_list, cumulative):
 
     # plt.title('Scores by group and gender')
     # plt.ylabel('Scores')
-    figsize = (20, 12)
+    figsize = (25, 12)
     # 标签文字大小
     fontsize = 22
     # 初始化
@@ -117,12 +117,12 @@ def draw_contribution_chart(xlabels, product_list, cumulative):
     ax1.set_xticks(loc)
     ax1.set_xticklabels(xlabels)
     ax1.yaxis.set_major_formatter(FuncFormatter(to_percent))
-    temp_rate = np.zeros(max_x_count)
-    for i in range(len(product_list)):
-        temp_rate += product_list[i]['data']
-    max_rate = np.max(np.hstack((temp_rate, cumulative['data'])))
+    # temp_rate = np.zeros(max_x_count)
+    # for i in range(len(product_list)):
+    #     temp_rate += product_list[i]['data']
+    # max_rate = np.max(np.hstack((temp_rate, cumulative['data'])))
     ax2.set_xticks([])
-    ax2.set_ylim(0, max_rate + 10)
+    # ax2.set_ylim(0, max_rate + 10)
 
     # 堆叠柱状图
     prod_legend = []
@@ -139,18 +139,83 @@ def draw_contribution_chart(xlabels, product_list, cumulative):
             else:
                 ax = ax1.bar(loc, product_list[i]['data'], width, bottom=bottom, alpha=0.8)
         prod_legend.append(ax[0])
-    ax1.legend(prod_legend, [prod['name'] for prod in product_list], bbox_to_anchor=(0.8, -0.1), ncol=4, fontsize=fontsize)
+    ax1.legend(prod_legend, [prod['name'] for prod in product_list], bbox_to_anchor=(0.9, -0.1), ncol=4, fontsize=fontsize)
 
     # 画折线图
     ax2.plot(loc, cumulative['data'], color='#C6A774', marker='', linewidth=3, label=cumulative['name'])
     ax2.legend(loc='upper left', fontsize=fontsize)
 
-    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
+    imgdata = BytesIO()
+    fig.savefig(imgdata, format='png', bbox_inches='tight')
+    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_contribution_chart(xlabels, product_list, cumulative):
+#     """贡献分解图"""
+#
+#     # plt.title('Scores by group and gender')
+#     # plt.ylabel('Scores')
+#     figsize = (25, 12)
+#     # 标签文字大小
+#     fontsize = 22
+#     # 初始化
+#     fig = plt.figure(figsize=figsize)
+#     ax1 = fig.add_subplot()
+#     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
+#     width = 0.35  # the width of the bars: can also be len(x) sequence
+#     color_list = ['#222A77', '#6C71AA', '#E1BC95', '#F9DBB8']
+#
+#     # 坐标轴
+#     ax1.tick_params(labelsize=fontsize)
+#     ax1.set_xticks(loc)
+#     ax1.set_xticklabels(xlabels)
+#     ax1.yaxis.set_major_formatter(FuncFormatter(to_percent))
+#     # temp_rate = np.zeros(max_x_count)
+#     # for i in range(len(product_list)):
+#     #     temp_rate += product_list[i]['data']
+#     # max_rate = np.max(np.hstack((temp_rate, cumulative['data'])))
+#     ax2.set_xticks([])
+#     # ax2.set_ylim(0, max_rate + 10)
+#
+#     # 堆叠柱状图
+#     prod_legend = []
+#     for i in range(len(product_list)):
+#         ax = None
+#         for j in range(len(product_list[i]['data'])):
+#             product_list[i]['bottom'] = product_list[i].get('bottom', 0)
+#             product_list[i]['bottom_neg'] = product_list[i].get('bottom_neg', 0)
+#             if j > 0:
+#                 product_list[i]['bottom'] += product_list[i].get('bottom', 0)
+#                 product_list[i]['bottom_neg'] += product_list[i].get('bottom_neg', 0)
+#             if i < len(color_list):
+#                 for x in loc:
+#                     if product_list[i]['data'][x] >= 0:
+#                         ax = ax1.bar(x, product_list[i]['data'][x], width, bottom=product_list[i]['bottom'], color=color_list[i], alpha=0.8)
+#                     else:
+#                         ax = ax1.bar(x, product_list[i]['data'][x], width, bottom=product_list[i]['bottom_neg'],
+#                                      color=color_list[i], alpha=0.8)
+#             else:
+#                 for x in loc:
+#                     if product_list[i]['data'][x] >= 0:
+#                         ax = ax1.bar(x, product_list[i]['data'][x], width, bottom=product_list[i]['bottom'], alpha=0.8)
+#                     else:
+#                         ax = ax1.bar(x, product_list[i]['data'][x], width, bottom=product_list[i]['bottom_neg'], alpha=0.8)
+#         prod_legend.append(ax[0])
+#     # ax1.legend(prod_legend, [prod['name'] for prod in product_list], bbox_to_anchor=(0.9, -0.1), ncol=4, fontsize=fontsize)
+#
+#     # 画折线图
+#     ax2.plot(loc, cumulative['data'], color='#C6A774', marker='', linewidth=3, label=cumulative['name'])
+#     ax2.legend(loc='upper left', fontsize=fontsize)
+#
+#     plt.show()
+#     # imgdata = BytesIO()
+#     # fig.savefig(imgdata, format='png', bbox_inches='tight')
+#     # 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):
@@ -240,26 +305,26 @@ if __name__ == '__main__':
     # contrast = {'name': '同比上涨', 'data': np.array([10, 50, 120, 100, 36, 0, 50, 120, 100, 36, 23, 98])}
     # draw_month_return_chart(xlabels, [product], contrast)
 
-    # 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')
-    # product1 = {'name': '塞亚成长1号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product2 = {'name': '塞亚成长2号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product3 = {'name': '塞亚成长3号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product4 = {'name': '塞亚成长4号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product5 = {'name': '塞亚成长5号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product6 = {'name': '塞亚成长6号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product7 = {'name': '塞亚成长7号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product8 = {'name': '塞亚成长8号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    # product_list = [product1, product2, product3, product4, product5, product6, product7, product8]
-    # cumulative = {'name': '总收益', 'data': np.array([10, 50, 120, 100, 36, 0, 50, 120, 100, 36, 23, 98])}
-    # draw_contribution_chart(xlabels, product_list, cumulative)
+    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')
+    product1 = {'name': '塞亚成长1号', 'data': np.array([-10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product2 = {'name': '塞亚成长2号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product3 = {'name': '塞亚成长3号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product4 = {'name': '塞亚成长4号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product5 = {'name': '塞亚成长5号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product6 = {'name': '塞亚成长6号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product7 = {'name': '塞亚成长7号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product8 = {'name': '塞亚成长8号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    product_list = [product1, product2, product3, product4, product5, product6, product7, product8]
+    cumulative = {'name': '总收益', 'data': np.array([10, 50, 120, 100, 36, 0, 50, 120, 100, 36, 23, 98])}
+    draw_contribution_chart(xlabels, product_list, cumulative)
 
     # 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')
     # source_prod = {'name': '远澜银杏1号', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
     # target_prod = {'name': '上证指数', 'data': np.array([-10, 10, 5, 55, 24, 10, 20, 8, 10, 31, 40, 32])}
     # draw_comment_chart(xlabels, source_prod, target_prod)
 
-    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')
-    new_combination = {'name': '新组合', 'data': np.array([20, 30, 40, 50, 60, 20, 30, 40, 50, 60, 50, 60])}
-    origin_combination = {'name': '原组合', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
-    index = {'name': '上证指数', 'data': np.array([-10, 10, 5, 55, 24, 10, 20, 8, 10, 31, 40, 32])}
-    draw_combination_chart(xlabels, new_combination, origin_combination, index)
+    # 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')
+    # new_combination = {'name': '新组合', 'data': np.array([20, 30, 40, 50, 60, 20, 30, 40, 50, 60, 50, 60])}
+    # origin_combination = {'name': '原组合', 'data': np.array([10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 40, 50])}
+    # index = {'name': '上证指数', 'data': np.array([-10, 10, 5, 55, 24, 10, 20, 8, 10, 31, 40, 32])}
+    # draw_combination_chart(xlabels, new_combination, origin_combination, index)

app/utils/radar_chart.py

@@ -6,11 +6,14 @@
 # @Email      : acepengxiong@163.com
 # @Software   : PyCharm
 # -----------------------------------------------------------------------------
+from io import BytesIO, StringIO
+import imgkit
 
 import pyecharts.options as opts
 from pyecharts.charts import Radar, Bar
 from snapshot_phantomjs import snapshot
 from pyecharts.render import make_snapshot
+import cv2
 
 
 def gen_radar_chart():
@@ -21,11 +24,9 @@ def gen_radar_chart():
     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(
+    htmldata = StringIO()
+    radar = 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),
@@ -43,15 +44,12 @@ def gen_radar_chart():
                 ])
             ),
             textstyle_opts=opts.TextStyleOpts(color="#000", font_size=16),
-        )
-            .add(
+        ).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(
+        ).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',
@@ -66,10 +64,21 @@ def gen_radar_chart():
                                          }),
             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)
+    radar.render()
+    imgkit.from_file('render.html', "radar_chart.png")
+    # 读取图片
+    img = cv2.imread('radar_chart.png')
+    # 获取宽度和高度
+    height = len(img)
+    width = len(img[0])
+
+    img = img[height:height, 200:800]
 
+    height = len(img)
+    width = len(img[0])
+    print('图片大小%dX%d' % (width, height))
+    cv2.imshow('radar_chart.png', img)
+    cv2.waitKey(0)
 
 if __name__ == '__main__':
     gen_radar_chart()
\ No newline at end of file

jinjia2html.py

 from jinja2 import PackageLoader, Environment
 from app.service.result_service import UserCustomerResultAdaptor
-
+import numpy as np
 
 # 准备数据
 from app.utils.draw import draw_month_return_chart, draw_contribution_chart