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Header-object attributes for column lookups in helpers and filters (#538) #542

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Merged
jepegit merged 1 commit into from
Jul 17, 2026
+49 −33
Merged

Header-object attributes for column lookups in helpers and filters (#538) #542

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8 changes: 8 additions & 0 deletions HISTORY.md
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,14 @@

## [Unreleased]

* Header column literals in `utils/helpers.py` and `filters/summary.py` use
header-object attributes (#538, native-headers Phase-0 prerequisite): the
base-name string-keyed `hdr_summary["charge_capacity"]`-style lookups become
attribute access, and `filter_summary`'s `rate_columns` default is resolved
from `HeadersSummary` (was a hard-coded `("charge_c_rate", "discharge_c_rate")`
tuple). Postfix/specific columns (`*_gravimetric`, `areal_*`) keep string-key
composition. Behavior-identical.

* Journal-page column literals use `HeadersJournal` attributes (#537, native-
headers Phase-0 prerequisite): the string-keyed `hdr_journal["mass"]`-style
lookups in `batch_plotters.py` and `helpers.py` become attribute access
Expand Down
10 changes: 9 additions & 1 deletion cellpy/filters/summary.py
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Expand Up @@ -29,6 +29,8 @@
from collections.abc import Mapping, Sequence
from typing import Any, Callable, Optional, Union

from cellpy.parameters.internal_settings import get_headers_summary

import pandas as pd

logger = logging.getLogger(__name__)
Expand Down Expand Up @@ -145,7 +147,7 @@ def filter_summary(
df: pd.DataFrame,
*,
rate: RangeArg = None,
rate_columns: ColumnsArg = ("charge_c_rate", "discharge_c_rate"),
rate_columns: ColumnsArg = None,
**extra_filters: Any,
) -> pd.DataFrame:
"""Filter rows of a cellpy summary DataFrame.
Expand All @@ -159,6 +161,8 @@ def filter_summary(
mapping ``{"value": v, "delta": d}`` (keep rows with
``v - d < value <= v + d``).
rate_columns: Which column(s) the ``rate`` filter applies to.
``None`` (default) resolves to the summary C-rate columns
(``HeadersSummary.charge_c_rate`` / ``.discharge_c_rate``).
A single string is coerced to a one-element tuple. With more
than one column the predicate is AND-ed across columns - a
row is kept only if *every* listed column lies in range.
Expand All @@ -176,6 +180,10 @@ def filter_summary(
argument is malformed.
TypeError: A range argument has an unsupported type.
"""
if rate_columns is None:
hdr_summary = get_headers_summary()
rate_columns = (hdr_summary.charge_c_rate, hdr_summary.discharge_c_rate)

range_kwargs = {k: v for k, v in extra_filters.items() if not k.endswith("_columns")}
column_kwargs = {k: v for k, v in extra_filters.items() if k.endswith("_columns")}

Expand Down
64 changes: 32 additions & 32 deletions cellpy/utils/helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,8 +37,8 @@ def _make_average_legacy(
):
if key_index_bounds is None:
key_index_bounds = [1, -2]
hdr_norm_cycle = hdr_summary["normalized_cycle_index"]
hdr_cum_charge = hdr_summary["cumulated_charge_capacity"]
hdr_norm_cycle = hdr_summary.normalized_cycle_index
hdr_cum_charge = hdr_summary.cumulated_charge_capacity
cell_id = ""
not_a_number = np.nan
new_frames = []
Expand Down Expand Up @@ -103,7 +103,7 @@ def _make_average(
skip_st_dev_for_equivalent_cycle_index=True,
average_method="mean",
):
hdr_norm_cycle = hdr_summary["normalized_cycle_index"]
hdr_norm_cycle = hdr_summary.normalized_cycle_index
not_a_number = np.nan
new_frames = []

Expand Down Expand Up @@ -225,7 +225,7 @@ def add_normalized_cycle_index(summary, nom_cap, column_name=None):
Returns:
data object now with normalized cycle index in its summary.
"""
hdr_norm_cycle = hdr_summary["normalized_cycle_index"]
hdr_norm_cycle = hdr_summary.normalized_cycle_index
hdr_cum_charge = hdr_summary["cumulated_charge_capacity_gravimetric"]

if column_name is None:
Expand Down Expand Up @@ -260,7 +260,7 @@ def add_c_rate(cell, nom_cap=None, column_name=None):
# now also included in step_table
# TODO: remove this function
if column_name is None:
column_name = hdr_steps["rate_avr"]
column_name = hdr_steps.rate_avr
if nom_cap is None:
nom_cap = cell.data.nom_cap

Expand All @@ -278,10 +278,10 @@ def add_areal_capacity(cell, cell_id, journal):
loading = journal.pages.loc[cell_id, hdr_journal.loading]

cell.data.summary[hdr_summary["areal_charge_capacity"]] = (
cell.data.summary[hdr_summary["charge_capacity"]] * loading / 1000
cell.data.summary[hdr_summary.charge_capacity] * loading / 1000
)
cell.data.summary[hdr_summary["areal_discharge_capacity"]] = (
cell.data.summary[hdr_summary["discharge_capacity"]] * loading / 1000
cell.data.summary[hdr_summary.discharge_capacity] * loading / 1000
)
return cell

Expand All @@ -303,7 +303,7 @@ def remove_outliers_from_summary_on_window(
):
"""Removes outliers based on neighbours"""
if col_name is None:
col = hdr_summary["charge_capacity"]
col = hdr_summary.charge_capacity

else:
col = hdr_summary[col_name]
Expand Down Expand Up @@ -344,8 +344,8 @@ def remove_outliers_from_summary_on_nn_distance(
"""
if filter_cols is None:
filter_cols = [
hdr_summary["charge_capacity"],
hdr_summary["discharge_capacity"],
hdr_summary.charge_capacity,
hdr_summary.discharge_capacity,
]

def neighbour_window(y):
Expand Down Expand Up @@ -391,8 +391,8 @@ def remove_outliers_from_summary_on_zscore(

if filter_cols is None:
filter_cols = [
hdr_summary["charge_capacity"],
hdr_summary["discharge_capacity"],
hdr_summary.charge_capacity,
hdr_summary.discharge_capacity,
]

s2 = s[filter_cols].copy()
Expand Down Expand Up @@ -424,8 +424,8 @@ def remove_outliers_from_summary_on_value(
"""
if filter_cols is None:
filter_cols = [
hdr_summary["charge_capacity"],
hdr_summary["discharge_capacity"],
hdr_summary.charge_capacity,
hdr_summary.discharge_capacity,
]

s2 = s[filter_cols].copy()
Expand Down Expand Up @@ -756,7 +756,7 @@ def concatenate_summaries(
group_nest.append(b.pages.group.to_list())

default_columns = [hdr_summary["charge_capacity_gravimetric"]]
hdr_norm_cycle = hdr_summary["normalized_cycle_index"]
hdr_norm_cycle = hdr_summary.normalized_cycle_index

if columns is None:
columns = []
Expand Down Expand Up @@ -786,16 +786,16 @@ def concatenate_summaries(

if normalize_capacity_on is not None:
normalize_capacity_headers = [
hdr_summary["normalized_charge_capacity"],
hdr_summary["normalized_discharge_capacity"],
hdr_summary.normalized_charge_capacity,
hdr_summary.normalized_discharge_capacity,
]
output_columns = [
col
for col in output_columns
if col
not in [
hdr_summary["charge_capacity"],
hdr_summary["discharge_capacity"],
hdr_summary.charge_capacity,
hdr_summary.discharge_capacity,
]
]
output_columns.extend(normalize_capacity_headers)
Expand Down Expand Up @@ -917,7 +917,7 @@ def _partition_summary_based_on_cv_steps(
import pandas as pd

if not x:
x = hdr_summary["cycle_index"]
x = hdr_summary.cycle_index

summary = c.data.summary.copy()

Expand Down Expand Up @@ -1081,7 +1081,7 @@ def concat_summaries(
group_nest.append(pages.group.to_list())

default_columns = [hdr_summary["charge_capacity_gravimetric"]]
hdr_norm_cycle = hdr_summary["normalized_cycle_index"]
hdr_norm_cycle = hdr_summary.normalized_cycle_index

if columns is None:
columns = []
Expand Down Expand Up @@ -1111,16 +1111,16 @@ def concat_summaries(

if normalize_capacity_on is not None:
normalize_capacity_headers = [
hdr_summary["normalized_charge_capacity"],
hdr_summary["normalized_discharge_capacity"],
hdr_summary.normalized_charge_capacity,
hdr_summary.normalized_discharge_capacity,
]
output_columns = [
col
for col in output_columns
if col
not in [
hdr_summary["charge_capacity"],
hdr_summary["discharge_capacity"],
hdr_summary.charge_capacity,
hdr_summary.discharge_capacity,
]
]
output_columns.extend(normalize_capacity_headers)
Expand Down Expand Up @@ -1462,18 +1462,18 @@ def select_summary_based_on_rate(
on = [on]

if rate_column is None:
rate_column = hdr_steps["rate_avr"]
rate_column = hdr_steps.rate_avr

if on:
on_column = hdr_steps["type"]
on_column = hdr_steps.type

if rate is None:
rate = 0.05

if rate_std is None:
rate_std = 0.1 * rate

cycle_number_header = hdr_summary["cycle_index"]
cycle_number_header = hdr_summary.cycle_index

step_table = cell.data.steps

Expand Down Expand Up @@ -1545,10 +1545,10 @@ def add_normalized_capacity(
if norm_cycles is None:
norm_cycles = [1, 2, 3, 4, 5]

col_name_charge = hdr_summary["charge_capacity"]
col_name_discharge = hdr_summary["discharge_capacity"]
col_name_norm_charge = hdr_summary["normalized_charge_capacity"]
col_name_norm_discharge = hdr_summary["normalized_discharge_capacity"]
col_name_charge = hdr_summary.charge_capacity
col_name_discharge = hdr_summary.discharge_capacity
col_name_norm_charge = hdr_summary.normalized_charge_capacity
col_name_norm_discharge = hdr_summary.normalized_discharge_capacity

try:
norm_val_charge = cell.data.summary.loc[norm_cycles, col_name_charge].mean()
Expand Down
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