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[TODO] Resolves the chained assignment in level_populations.py #2933

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[TODO] Resolves the chained assignment in level_populations.py #2933

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55a190d
for test
Sonu0305 Jan 2, 2025
fee6b5f
Merge branch 'tardis-sn:master' into master
Sonu0305 Jan 6, 2025
b6ce897
Merge branch 'tardis-sn:master' into master
Sonu0305 Jan 9, 2025
b3ee193
Revert "for test"
Sonu0305 Jan 10, 2025
413edbe
resolves chained assignment
Sonu0305 Jan 10, 2025
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21 changes: 11 additions & 10 deletions tardis/plasma/equilibrium/level_populations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,18 +52,19 @@ def solve(self):
dtype=np.float64,
)

# try converting the set of vectors into a single 2D array and then applying index
for species_id in self.rates_matrices.index:
# TODO: resolve the chained assignment here. Maybe an intermediate df
# is needed
species_level_populations = pd.DataFrame(
index=self.levels.index,
columns=self.rates_matrices.columns,
dtype=np.float64,
)

for species_id in self.rates_matrices.index:
solved_matrices = self.rates_matrices.loc[species_id].apply(
lambda rates_matrix: self.__calculate_level_population(
rates_matrix
)
)
normalized_level_populations.loc[species_id, :].update(
np.vstack(solved_matrices.values).T
lambda rates_matrix: self.__calculate_level_population(rates_matrix)
)

species_level_populations.loc[species_id, :] = np.vstack(solved_matrices.values).T

normalized_level_populations.update(species_level_populations)

return normalized_level_populations
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