+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")
