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Fix flatten_timepoint_specific_output_overrides
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... again.

Fixes an error when trying to apply re.sub to numeric values:

```
    petab.flatten_timepoint_specific_output_overrides(problem)
build/venv/lib/python3.9/site-packages/petab/core.py:290: in flatten_timepoint_specific_output_overrides
    observable[target] = re.sub(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

pattern = 'observableParameter([0-9]+)_obs_a'
repl = 'observableParameter\\1_obs_a__10__c0', string = 1, count = 0, flags = 0

    def sub(pattern, repl, string, count=0, flags=0):
        """Return the string obtained by replacing the leftmost
        non-overlapping occurrences of the pattern in string by the
        replacement repl.  repl can be either a string or a callable;
        if a string, backslash escapes in it are processed.  If it is
        a callable, it's passed the Match object and must return
        a replacement string to be used."""
>       return _compile(pattern, flags).sub(repl, string, count)
E       TypeError: cannot use a string pattern on a bytes-like object

/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/re.py:210: TypeError
```
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@dweindl
dweindl committed Dec 18, 2023
1 parent eb08318 commit f1a01be
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Showing 2 changed files with 41 additions and 13 deletions.
5 changes: 5 additions & 0 deletions petab/core.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@

import numpy as np
import pandas as pd
from pandas.api.types import is_string_dtype

from . import yaml
from .C import * # noqa: F403
Expand Down Expand Up @@ -282,6 +283,10 @@ def flatten_timepoint_specific_output_overrides(
if field not in measurements:
continue

if not is_string_dtype(type(observable[target])):
# if not a string, we don't have to substitute anything
continue

hyperparameter_replacement_id = get_hyperparameter_replacement_id(
hyperparameter_type=hyperparameter_type,
observable_replacement_id=observable_replacement_id,
Expand Down
49 changes: 36 additions & 13 deletions tests/test_petab.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -349,12 +349,14 @@ def test_flatten_timepoint_specific_output_overrides():
"""Test flatten_timepoint_specific_output_overrides"""
observable_df = pd.DataFrame(
data={
OBSERVABLE_ID: ["obs1"],
OBSERVABLE_ID: ["obs1", "obs2"],
OBSERVABLE_FORMULA: [
"observableParameter1_obs1 + observableParameter2_obs1"
"observableParameter1_obs1 + observableParameter2_obs1",
"x",
],
NOISE_FORMULA: [
"(observableParameter1_obs1 + observableParameter2_obs1) * noiseParameter1_obs1"
"(observableParameter1_obs1 + observableParameter2_obs1) * noiseParameter1_obs1",
1,
],
}
)
Expand All @@ -366,11 +368,17 @@ def test_flatten_timepoint_specific_output_overrides():
obs1_2_2_1 = "obs1__obsParOverride2_1_0__noiseParOverride2__condition1"
observable_df_expected = pd.DataFrame(
data={
OBSERVABLE_ID: [obs1_1_1_1, obs1_2_1_1, obs1_2_2_1],
OBSERVABLE_ID: [
obs1_1_1_1,
obs1_2_1_1,
obs1_2_2_1,
"obs2__condition1",
],
OBSERVABLE_FORMULA: [
f"observableParameter1_{obs1_1_1_1} + observableParameter2_{obs1_1_1_1}",
f"observableParameter1_{obs1_2_1_1} + observableParameter2_{obs1_2_1_1}",
f"observableParameter1_{obs1_2_2_1} + observableParameter2_{obs1_2_2_1}",
"x",
],
NOISE_FORMULA: [
f"(observableParameter1_{obs1_1_1_1} + observableParameter2_{obs1_1_1_1})"
Expand All @@ -379,6 +387,7 @@ def test_flatten_timepoint_specific_output_overrides():
f" * noiseParameter1_{obs1_2_1_1}",
f"(observableParameter1_{obs1_2_2_1} + observableParameter2_{obs1_2_2_1})"
f" * noiseParameter1_{obs1_2_2_1}",
1,
],
}
)
Expand All @@ -387,54 +396,66 @@ def test_flatten_timepoint_specific_output_overrides():
# Measurement table with timepoint-specific overrides
measurement_df = pd.DataFrame(
data={
OBSERVABLE_ID: ["obs1", "obs1", "obs1", "obs1"],
OBSERVABLE_ID: ["obs1", "obs1", "obs1", "obs1", "obs2"],
SIMULATION_CONDITION_ID: [
"condition1",
"condition1",
"condition1",
"condition1",
"condition1",
],
PREEQUILIBRATION_CONDITION_ID: ["", "", "", ""],
TIME: [1.0, 1.0, 2.0, 2.0],
MEASUREMENT: [0.1] * 4,
PREEQUILIBRATION_CONDITION_ID: ["", "", "", "", ""],
TIME: [1.0, 1.0, 2.0, 2.0, 3.0],
MEASUREMENT: [0.1] * 5,
OBSERVABLE_PARAMETERS: [
"obsParOverride1;1.0",
"obsParOverride2;1.0",
"obsParOverride2;1.0",
"obsParOverride2;1.0",
"",
],
NOISE_PARAMETERS: [
"noiseParOverride1",
"noiseParOverride1",
"noiseParOverride2",
"noiseParOverride2",
"",
],
}
)

measurement_df_expected = pd.DataFrame(
data={
OBSERVABLE_ID: [obs1_1_1_1, obs1_2_1_1, obs1_2_2_1, obs1_2_2_1],
OBSERVABLE_ID: [
obs1_1_1_1,
obs1_2_1_1,
obs1_2_2_1,
obs1_2_2_1,
"obs2__condition1",
],
SIMULATION_CONDITION_ID: [
"condition1",
"condition1",
"condition1",
"condition1",
"condition1",
],
PREEQUILIBRATION_CONDITION_ID: ["", "", "", ""],
TIME: [1.0, 1.0, 2.0, 2.0],
MEASUREMENT: [0.1] * 4,
PREEQUILIBRATION_CONDITION_ID: ["", "", "", "", ""],
TIME: [1.0, 1.0, 2.0, 2.0, 3.0],
MEASUREMENT: [0.1] * 5,
OBSERVABLE_PARAMETERS: [
"obsParOverride1;1.0",
"obsParOverride2;1.0",
"obsParOverride2;1.0",
"obsParOverride2;1.0",
"",
],
NOISE_PARAMETERS: [
"noiseParOverride1",
"noiseParOverride1",
"noiseParOverride2",
"noiseParOverride2",
"",
],
}
)
Expand Down Expand Up @@ -483,7 +504,9 @@ def test_flatten_timepoint_specific_output_overrides():
petab_problem=unflattened_problem,
)
# The unflattened simulation dataframe has the original observable IDs.
assert (unflattened_simulation_df[OBSERVABLE_ID] == "obs1").all()
assert (
unflattened_simulation_df[OBSERVABLE_ID] == ["obs1"] * 4 + ["obs2"]
).all()


def test_flatten_timepoint_specific_output_overrides_special_cases():
Expand Down

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