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Fake dataset generation #103

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42725cf
Added initial fake dataset generator and test
joshop Jul 14, 2023
17afcd6
MPI events, and some general realism changes
joshop Jul 19, 2023
f1cc393
Cleaned up code, removed pytest test and added top-level function
joshop Jul 27, 2023
62ca889
Clean up, CSV reader can be passed CSVs as strings
joshop Aug 9, 2023
4fada83
Slight cleanup
joshop Aug 29, 2023
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14 changes: 14 additions & 0 deletions pipit/trace.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,8 @@

import numpy as np
import pandas as pd
from ast import literal_eval
from io import StringIO


class Trace:
Expand Down Expand Up @@ -60,6 +62,10 @@ def from_nsight(filename):

@staticmethod
def from_csv(filename):
# detect if the input is a CSV as a string
if "," in filename:
# wrapping with StringIO allows pandas to read it
filename = StringIO(filename)
events_dataframe = pd.read_csv(filename, skipinitialspace=True)

# if timestamps are in seconds, convert them to nanoseconds
Expand All @@ -72,6 +78,14 @@ def from_csv(filename):
# ensure that ranks are ints
events_dataframe = events_dataframe.astype({"Process": "int32"})

# this next part is needed for fake test reading
# ensure that the attributes are a dict, not a string
if "Attributes" in events_dataframe.columns:
# use literal_eval so we're not running a security risk
events_dataframe["Attributes"] = events_dataframe["Attributes"].apply(
literal_eval
)

# make certain columns categorical
events_dataframe = events_dataframe.astype(
{
Expand Down
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