Source code for visualization.hdf5_vis

import sys
import os
root_dir = os.path.abspath(os.curdir)
sys.path.append(root_dir)

import h5py
import yaml

import numpy as np
import pandas as pd

from plotly.subplots import make_subplots
import plotly.graph_objects as go
import plotly.express as px
#import plotly.io as pio
from src.hdf5_ops import get_parent_child_relationships

 

[docs] def display_group_hierarchy_on_a_treemap(filename: str): """ filename (str): hdf5 file's filename""" with h5py.File(filename,'r') as file: nodes, parents, values = get_parent_child_relationships(file) metadata_list = [] metadata_dict={} for key in file.attrs.keys(): #if 'metadata' in key: if isinstance(file.attrs[key], str): # Check if the attribute is a string metadata_key = key[key.find('_') + 1:] metadata_value = file.attrs[key] metadata_dict[metadata_key] = metadata_value metadata_list.append(f'{metadata_key}: {metadata_value}') #metadata_dict[key[key.find('_')+1::]]= file.attrs[key] #metadata_list.append(key[key.find('_')+1::]+':'+file.attrs[key]) metadata = '<br>'.join(['<br>'] + metadata_list) customdata_series = pd.Series(nodes) customdata_series[0] = metadata fig = make_subplots(1, 1, specs=[[{"type": "domain"}]],) fig.add_trace(go.Treemap( labels=nodes, #formating_df['formated_names'][nodes], parents=parents,#formating_df['formated_names'][parents], values=values, branchvalues='remainder', customdata= customdata_series, #marker=dict( # colors=df_all_trees['color'], # colorscale='RdBu', # cmid=average_score), #hovertemplate='<b>%{label} </b> <br> Number of files: %{value}<br> Success rate: %{color:.2f}', hovertemplate='<b>%{label} </b> <br> Count: %{value} <br> Path: %{customdata}', name='', root_color="lightgrey" )) fig.update_layout(width = 800, height= 600, margin = dict(t=50, l=25, r=25, b=25)) fig.show() file_name, file_ext = os.path.splitext(filename) fig.write_html(file_name + ".html")
#pio.write_image(fig,file_name + ".png",width=800,height=600,format='png') #