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- Fix: Fixed the bug when restore the object, some cross_test top tab…
…le was added to the GUI by wrong. - Change: Changed the "pixel_ratio" from 2 to 3 for the HTML plot to make the plot more clear.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,167 @@ | ||
| import pandas as pd | ||
| from pyecharts.charts import Sankey | ||
| from pyecharts import options as opts | ||
|
|
||
| class SankeyPlot: | ||
| def __init__(self, theme='white'): | ||
| self.font_size = 12 | ||
| self.show_legend = True | ||
| self.theme = theme | ||
|
|
||
| def df_to_sankey_df(self, df, value_col='value'): | ||
| df.index.name = 'index' | ||
| df['index'] = df.index | ||
| df = df[['index', value_col]] | ||
|
|
||
| if '<' in df['index'][0]: | ||
| index_str = df['index'].str.split("<", expand=True) | ||
| taxon_index, func_index = (0, 1) if '|' in index_str[0][0] else (1, 0) | ||
| df = df[[value_col]] | ||
| df['Taxon'] = index_str[taxon_index].str.replace(">", "") | ||
| df['Function'] = index_str[func_index].str.replace(">", "") | ||
| else: | ||
| df = df[[value_col]] | ||
| df['Taxon'] = df.index | ||
|
|
||
| df_t = df['Taxon'].str.split('|', expand=True) | ||
| if "Function" in df.columns: | ||
| df_t = df_t.join(df['Function']) | ||
|
|
||
| df_t = df_t.join(df[value_col]) | ||
| names = df_t.columns.tolist() | ||
| names[-1] = 'value' | ||
| df_t.columns = names | ||
| df_t = df_t[df_t['value'] != 0] | ||
|
|
||
| return df_t | ||
|
|
||
| def convert_df_by_group_for_sankey(self, df, plot_mean=False): | ||
| sample_list = df.columns.tolist() | ||
|
|
||
| if plot_mean is not None: | ||
| if plot_mean is None: | ||
| df = df.mean(axis=1).to_frame(name='mean') | ||
|
|
||
| group_dict = {col: col for col in df.columns} | ||
| else: | ||
| group_dict = {sample: sample for sample in sample_list} | ||
|
|
||
| df_dict = {} | ||
| if len(sample_list) > 1: | ||
| df['sum'] = df.sum(axis=1) | ||
| df_dict['All'] = self.df_to_sankey_df(df, value_col='sum') | ||
|
|
||
| for group, samples in group_dict.items(): | ||
| df_temp = df[samples] | ||
| if isinstance(df_temp, pd.Series): | ||
| df_temp = pd.DataFrame(df_temp) | ||
|
|
||
| df_temp['sum'] = df_temp.sum(axis=1) | ||
| df_temp = df_temp[df_temp['sum'] != 0] | ||
| df_temp = self.df_to_sankey_df(df_temp, value_col='sum') | ||
| df_dict[group] = df_temp | ||
|
|
||
| return df_dict | ||
|
|
||
| def create_nodes_links(self, df, value_col='value'): | ||
| lis = df.columns.tolist()[:-1] | ||
| lis1 = lis[:-1] | ||
| lis2 = lis[1:] | ||
|
|
||
| df2 = pd.DataFrame() | ||
| for i in zip(lis1, lis2): | ||
| dfi = df.pivot_table(value_col, index=list(i), aggfunc='sum').reset_index() | ||
| dfi.columns = [0, 1, 2] | ||
| df2 = pd.concat([df2, dfi]) | ||
|
|
||
| nodes = [] | ||
| ln = df2.iloc[:, 0].to_list() + df2.iloc[:, 1].to_list() | ||
| ln = list(set(ln)) | ||
| for i in ln: | ||
| dic = {'name': i} | ||
| nodes.append(dic) | ||
| print(f'Number of nodes: {len(nodes)}') | ||
|
|
||
| links = [] | ||
| for i in df2.values: | ||
| dic = {'source': i[0], 'target': i[1], 'value': i[2]} | ||
| links.append(dic) | ||
| print(f'Number of links: {len(links)}') | ||
|
|
||
| colors = GetDistinctColors().get_distinct_colors(20, convert=True) | ||
| node_colors = {} | ||
| for idx, node in enumerate(nodes): | ||
| available_colors = colors[:] | ||
| for link in links: | ||
| if link['source'] == node['name'] and link['target'] in node_colors: | ||
| if node_colors[link['target']] in available_colors: | ||
| available_colors.remove(node_colors[link['target']]) | ||
| if link['target'] == node['name'] and link['source'] in node_colors: | ||
| if node_colors[link['source']] in available_colors: | ||
| available_colors.remove(node_colors[link['source']]) | ||
| if not available_colors: | ||
| available_colors = colors[:] | ||
| chosen_color = available_colors[idx % len(available_colors)] | ||
| node_colors[node['name']] = chosen_color | ||
| node['itemStyle'] = {'color': chosen_color} | ||
|
|
||
| return nodes, links | ||
|
|
||
| def __plot_sankey(self, link_nodes_dict, width, height, title, subtitle=''): | ||
| pic = Sankey(init_opts=opts.InitOpts(width=f"{width*100}px", height=f"{height*100}px", theme=self.theme)) | ||
|
|
||
| for key, value in link_nodes_dict.items(): | ||
| nodes = value[0] | ||
| links = value[1] | ||
| num = value[2] | ||
| pic.add( | ||
| f'{key} ({num})', | ||
| nodes=nodes, | ||
| links=links, | ||
| node_align='justify', | ||
| layout_iterations=100, | ||
| node_width=25, | ||
| emphasis_opts=opts.EmphasisOpts(focus='adjacency'), | ||
| linestyle_opt=opts.LineStyleOpts(curve=0.5, opacity=0.3, color="gray"), | ||
| label_opts=opts.LabelOpts(position='right', font_size=self.font_size, color='white' if self.theme == 'dark' else 'black'), | ||
| itemstyle_opts=opts.ItemStyleOpts(border_width=1, border_color="black", opacity=0.7), | ||
| ) | ||
|
|
||
| pic.set_global_opts( | ||
| legend_opts=opts.LegendOpts(selected_mode='single', is_show=self.show_legend, type_="scroll", page_icon_size=8), | ||
| toolbox_opts=opts.ToolboxOpts( | ||
| is_show=True, | ||
| orient="vertical", | ||
| pos_left="left", | ||
| pos_top="bottom", | ||
| feature=opts.ToolBoxFeatureOpts( | ||
| save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(type_="png", background_color="black" if self.theme == 'dark' else "white", pixel_ratio=3, title="Save as PNG"), | ||
| restore=opts.ToolBoxFeatureRestoreOpts(title="Restore"), | ||
| data_zoom=opts.ToolBoxFeatureDataZoomOpts(zoom_title="Zoom", is_show=False, back_title="Back"), | ||
| data_view=opts.ToolBoxFeatureDataViewOpts(title="Data View"), | ||
| magic_type=opts.ToolBoxFeatureMagicTypeOpts(line_title="Line", bar_title="Bar", is_show=False, stack_title="Stack", tiled_title="Tiled"), | ||
| ), | ||
| ), | ||
| title_opts=opts.TitleOpts(title=title, subtitle=subtitle, title_textstyle_opts=opts.TextStyleOpts(font_size=self.font_size + 2)), | ||
| ) | ||
|
|
||
| return pic | ||
|
|
||
| def plot_intensity_sankey(self, df, width=12, height=8, title="Sankey Plot", subtitle="", font_size=12, show_legend=True, plot_mean=False): | ||
| df = df.copy() | ||
| self.font_size = font_size | ||
| self.show_legend = show_legend | ||
|
|
||
| df_sankey = self.convert_df_by_group_for_sankey(df, plot_mean=plot_mean) | ||
| link_nodes_dict = {} | ||
| for key, value in df_sankey.items(): | ||
| print(f'Creating nodes and links for {key}...') | ||
| nodes, links = self.create_nodes_links(value) | ||
| link_nodes_dict[key] = [nodes, links, len(value.index)] | ||
| pic = self.__plot_sankey(link_nodes_dict, width=width, height=height, title=title, subtitle=subtitle) | ||
| return pic | ||
|
|
||
| # df_sankey is a dataframe, index is "taxon" or "taxon < function>", columns are values | ||
| df_sankey = pd.read_csv('data.csv') | ||
| pic = SankeyPlot().plot_intensity_sankey(df_sankey, width=12, height=8, title="Sankey Plot", subtitle="", font_size=12, show_legend=False, plot_mean=False) | ||
| pic.render_notebook() |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,2 +1,2 @@ | ||
| __version__ = '1.109.8' | ||
| __version__ = '1.109.9' | ||
| API_version = '2' |