Open cshjin opened 1 year ago
Two options:
# global min over graph-level timestamps
ts_anchor = df['ready'].min()
tfs = ['ready', 'submit', 'execute_start', 'execute_end', 'post_script_start', 'post_script_end']
for attr in tfs[::-1]:
df[attr] -= ts_anchor
# local min over node level timestamps
ts_anchor = df['ready']
tfs = ['ready', 'submit', 'execute_start', 'execute_end', 'post_script_start', 'post_script_end']
for attr in tfs[::-1]:
df[attr] -= ts_anchor
Timestamp columns:
'ready', 'submit', 'execute_start', 'execute_end', 'post_script_start', 'post_script_end'
In general, they have the following condition per node
$$ \text{ready} \le \text{submit} \le \text{execute start} \le \text{execute end} \le \text{post script start} \le \text{post script end} $$