Coverage for src/graphs/portfolio_graph.py: 0%
84 statements
« prev ^ index » next coverage.py v7.8.2, created at 2025-06-03 19:06 +0000
1import plotly.colors as pc
2import plotly.express as px
3import plotly.graph_objects as go
5from src.static.static_values_enum import Edition
7DEFAULT_HEIGHT = 800
10def plot_portfolio_total(portfolio_df, combined_users, theme):
11 portfolio_df.sort_values('date', inplace=True)
12 if 'total_investment_value' in portfolio_df.columns.tolist() \
13 and not portfolio_df['total_investment_value'].dropna().empty:
14 column_data = portfolio_df[['total_value', 'total_investment_value']].columns
16 # add last investment value to the last row for visual effect
17 last_investment_value = portfolio_df['total_investment_value'].dropna().tolist()[-1]
18 portfolio_df.loc[portfolio_df.index[-1], 'total_investment_value'] = last_investment_value
19 else:
20 column_data = portfolio_df[['total_value']].columns
22 fig = px.line(portfolio_df,
23 x='date',
24 y=column_data,
25 title='Total portfolio values of \'' + ','.join(combined_users) + '\' combined',
26 markers=True)
27 fig.update_traces(connectgaps=True)
28 fig.update_layout(
29 template=theme,
30 xaxis=dict(
31 showgrid=True,
32 gridwidth=1,
33 ),
34 )
35 return fig
38def plot_portfolio_all(df, theme, skip_zero=True):
39 fig = go.Figure()
41 temp_df = df.drop('account_name', axis=1)
43 if skip_zero:
44 temp_df = temp_df.drop('date', axis=1)
45 temp_df = temp_df.loc[:, (temp_df.sum(axis=0) != 0.0)]
46 temp_df['date'] = df[['date']]
48 temp_df = temp_df.set_index('date')
49 max_value = temp_df.loc[:, temp_df.columns.str.endswith('_value')].max().max()
50 max_qty = temp_df.loc[:, ~temp_df.columns.str.endswith('_value')].max().max()
52 # Get a discrete color palette from Plotly
53 color_palette = pc.qualitative.Plotly
54 color_index = 0 # Initialize the index for cycling colors
56 # Sort columns for legend
57 temp_df = temp_df.reindex(sorted(temp_df.columns), axis=1)
58 for column in temp_df.columns.tolist():
59 current_color = color_palette[color_index]
61 mode = 'lines' if temp_df[column].size > 1 else 'markers'
62 if '_value' in column:
63 trace = go.Scatter(x=temp_df.index,
64 y=temp_df[column],
65 mode=mode,
66 connectgaps=True,
67 # legendgroup=legend_group,
68 # showlegend=False,
69 line=dict(color=current_color),
70 name=column)
71 else:
72 trace = go.Scatter(x=temp_df.index,
73 y=temp_df[column],
74 mode=mode,
75 connectgaps=True,
76 # legendgroup=legend_group,
77 line=dict(color=current_color, dash='dash'),
78 name=column,
79 yaxis='y2')
80 fig.add_trace(trace)
81 color_index = (color_index + 1) % len(color_palette) # Move to the next color
83 fig.update_layout(
84 template=theme,
85 title_text='All',
86 legend=dict(
87 orientation='v',
88 x=1.1,
89 xanchor='left',
90 y=1,
91 font=dict(
92 size=10
93 ),
94 borderwidth=1,
95 ),
96 xaxis=dict(
97 title='date'
98 ),
100 yaxis2=dict(
101 overlaying='y',
102 side='right',
103 position=1.0, # Adjust the position of the secondary y-axis
104 range=[0, max_qty * 1.05],
105 title='qty/bcx/count',
106 ),
107 yaxis1=dict(
108 showgrid=False,
109 range=[0, max_value * 1.05],
110 title='value $',
111 ),
112 height=DEFAULT_HEIGHT,
113 )
115 return fig
118def get_editions_fig(editions_df, theme):
119 fig = go.Figure()
120 # max_value = editions_df.loc[:, editions_df.columns.str.endswith('_market_value')].max().max()
121 # max_bcx = editions_df.loc[:, editions_df.columns.str.endswith('_bcx')].max().max()
123 # Get a discrete color palette from Plotly
124 color_palette = pc.qualitative.Plotly
125 color_index = 0 # Initialize the index for cycling colors
127 for edition in Edition.list_names():
128 if str(edition) + '_bcx' in editions_df.columns.tolist():
129 legend_group = edition
130 current_color = color_palette[color_index]
132 mode = 'lines' if editions_df[str(edition) + '_market_value'].size > 1 else 'markers'
133 market_value_trace = go.Scatter(x=editions_df.index,
134 y=editions_df[str(edition) + '_market_value'],
135 mode=mode,
136 legendgroup=legend_group,
137 line=dict(color=current_color), # Set line color
138 name=str(edition))
139 fig.add_trace(market_value_trace)
140 mode = 'lines' if editions_df[str(edition) + '_bcx'].size > 1 else 'markers'
141 bcx__trace = go.Scatter(x=editions_df.index,
142 y=editions_df[str(edition) + '_bcx'],
143 mode=mode,
144 legendgroup=legend_group,
145 showlegend=False,
146 line=dict(color=current_color, dash='dash'),
147 name=str(edition) + ' bcx',
148 yaxis='y2')
149 fig.add_trace(bcx__trace)
150 color_index = (color_index + 1) % len(color_palette) # Move to the next color
152 current_color = color_palette[color_index]
153 temp_df = editions_df.copy()
154 temp_df['all_value'] = temp_df.loc[:, temp_df.columns.str.endswith('_market_value')].sum(axis=1)
155 temp_df['all_bcx'] = temp_df.loc[:, temp_df.columns.str.endswith('_bcx')].sum(axis=1)
156 legend_group = 'combined'
157 mode = 'lines' if temp_df.all_value.size > 1 else 'markers'
158 market_value_trace = go.Scatter(x=temp_df.index,
159 y=temp_df.all_value,
160 mode=mode,
161 legendgroup=legend_group,
162 line=dict(color=current_color), # Set line color
163 name=legend_group)
164 fig.add_trace(market_value_trace)
165 mode = 'lines' if temp_df.all_bcx.size > 1 else 'markers'
166 bcx__trace = go.Scatter(x=temp_df.index,
167 y=temp_df.all_bcx,
168 mode=mode,
169 legendgroup=legend_group,
170 showlegend=False,
171 line=dict(color=current_color, dash='dash'),
172 name=legend_group + ' bcx',
173 yaxis='y2')
174 fig.add_trace(bcx__trace)
176 fig.update_layout(
177 template=theme,
178 title_text='Editions',
179 hovermode='x unified',
180 margin=dict(l=10, r=10),
181 legend=dict(
182 orientation='h',
183 yanchor='bottom',
184 y=1.02,
185 xanchor='right',
186 x=1
187 ),
188 xaxis=dict(
189 title='date'
190 ),
192 yaxis2=dict(
193 overlaying='y',
194 side='right',
195 position=1.0, # Adjust the position of the secondary y-axis
196 # range=[0, max_bcx * 1.05],
197 title='bcx',
198 ),
199 yaxis1=dict(
200 showgrid=False,
201 # range=[0, max_value * 1.05],
202 title='value $',
203 ),
204 height=DEFAULT_HEIGHT,
206 )
208 return fig
211def get_sps_fig(sps_df, theme):
212 fig = go.Figure()
213 max_value = sps_df.loc[:, sps_df.columns.str.endswith('_value')].max().max()
214 max_qty = sps_df.loc[:, sps_df.columns.str.endswith('_qty')].max().max()
216 # Get a discrete color palette from Plotly
217 color_palette = pc.qualitative.Plotly
218 color_index = 0 # Initialize the index for cycling colors
220 for column in sps_df.columns.tolist():
221 current_color = color_palette[color_index]
222 legend_group = 'spsp' if 'spsp' in column else 'sps'
224 mode = 'lines' if sps_df[column].size > 1 else 'markers'
225 if '_qty' in column:
226 trace = go.Scatter(x=sps_df.index,
227 y=sps_df[column],
228 mode=mode,
229 legendgroup=legend_group,
230 showlegend=False,
231 line=dict(color=current_color, dash='dash'),
232 name=legend_group + ' qty ',
233 yaxis='y2')
234 else:
235 trace = go.Scatter(x=sps_df.index,
236 y=sps_df[column],
237 mode=mode,
238 legendgroup=legend_group,
239 line=dict(color=current_color), # Set line color
240 name=legend_group)
241 fig.add_trace(trace)
242 color_index = (color_index + 1) % len(color_palette) # Move to the next color
244 fig.update_layout(
245 template=theme,
246 title_text='SPS',
247 hovermode='x unified',
248 margin=dict(l=10, r=10),
249 legend=dict(
250 orientation='h',
251 yanchor='bottom',
252 y=1.02,
253 xanchor='right',
254 x=1
255 ),
256 xaxis=dict(
257 title='date'
258 ),
260 yaxis2=dict(
261 overlaying='y',
262 side='right',
263 position=1.0, # Adjust the position of the secondary y-axis
264 range=[0, max_qty * 1.05],
265 title='qty',
266 ),
267 yaxis1=dict(
268 showgrid=False,
269 range=[0, max_value * 1.05],
270 title='value $',
271 ),
272 height=DEFAULT_HEIGHT,
273 )
275 return fig