neuralib.atlas.ccf.dataframe.RoiSubregionDataFrame

class neuralib.atlas.ccf.dataframe.RoiSubregionDataFrame

Bases: DataFrameWrapper

RoiSubregionDataFrame with each source per row, column shows the subregions

__init__(region, df, profile)

Parameters:

• region (str) – region name

• df (DataFrame) – subregion dataframe

• profile (DataFrame) – profile dataframe

Methods

__init__(region, df, profile)
clear([n])	See polars.DataFrame.clear.
clone()	Clone the wrapper.
dataframe([dataframe, may_inplace])	RoiSubregionDataFrame (VIS as example).
drop(*columns[, strict])	See polars.DataFrame.drop.
drop_nulls(subset)	See polars.DataFrame.drop_nulls.
fill_nan([value])	See polars.DataFrame.fill_nan.
fill_null([value, strategy, limit])	See polars.DataFrame.fill_null.
filter(*predicates, **constraints)	See polars.DataFrame.filter.
filter_overlap()	filter out overlap source
group_by(*by[, maintain_order])	See polars.DataFrame.group_by.
head([n])	See polars.DataFrame.head.
join(other, on[, how, left_on, right_on, ...])	See polars.DataFrame.join.
lazy()	Wrap dataframe in a lazy wrapper.
limit([n])	See polars.DataFrame.limit.
partition_by(by, *more_by[, as_dict])	See polars.DataFrame.partition_by.
pipe(function, *args, **kwargs)	See polars.DataFrame.pipe.
rename(mapping)	See polars.DataFrame.rename.
select(*exprs, **named_exprs)	See polars.DataFrame.select.
slice(offset[, length])	See polars.DataFrame.slice.
sort(by, *more_by[, descending, nulls_last, ...])	See polars.DataFrame.sort.
tail([n])	See polars.DataFrame.tail.
to_dict([as_series])	to subregion:value dict
to_numpy()	to value array.
with_animal_column(animal)	with animal id column
with_columns(*exprs, **named_exprs)	See polars.DataFrame.with_columns.
with_row_index([name, offset])	See polars.DataFrame.with_row_index.

Attributes

columns	See polars.DataFrame.columns.
n_subregion	number of subregion
profile	with channel-wise profile.
region	region name
schema	See polars.DataFrame.schema.
sources	list of source names
subregion	list of subregion names

__init__(region, df, profile)

Parameters:

• region (str) – region name

• df (DataFrame) – subregion dataframe

• profile (DataFrame) – profile dataframe

dataframe(dataframe=None, may_inplace=True)

RoiSubregionDataFrame (VIS as example):

┌─────────┬───────────┬───────────┬───────────┬───┬──────────┬──────────┬──────────┬──────────┐
│ source  ┆ VISam     ┆ VISp      ┆ VISpm     ┆ … ┆ VISal    ┆ VISpor   ┆ VISli    ┆ VISpl    │
│ ---     ┆ ---       ┆ ---       ┆ ---       ┆   ┆ ---      ┆ ---      ┆ ---      ┆ ---      │
│ str     ┆ f64       ┆ f64       ┆ f64       ┆   ┆ f64      ┆ f64      ┆ f64      ┆ f64      │
╞═════════╪═══════════╪═══════════╪═══════════╪═══╪══════════╪══════════╪══════════╪══════════╡
│ overlap ┆ 39.649682 ┆ 15.127389 ┆ 28.025478 ┆ … ┆ 3.025478 ┆ 2.707006 ┆ 1.592357 ┆ 0.159236 │
│ aRSC    ┆ 32.160414 ┆ 28.952135 ┆ 23.05304  ┆ … ┆ 6.080207 ┆ 1.293661 ┆ 2.069858 ┆ 0.07762  │
│ pRSC    ┆ 25.947955 ┆ 27.95539  ┆ 27.459727 ┆ … ┆ 3.122677 ┆ 2.973978 ┆ 1.982652 ┆ 1.016109 │
└─────────┴───────────┴───────────┴───────────┴───┴──────────┴──────────┴──────────┴──────────┘

Parameters:

• dataframe (DataFrame | None)

• may_inplace (bool)

Return type:

DataFrame | RoiSubregionDataFrame

property region: str

region name

property subregion: list[str]

list of subregion names

property n_subregion: int

number of subregion

property profile: DataFrame

with channel-wise profile:

┌─────────┬────────┬───────┬────────────────┐
│ source  ┆ counts ┆ total ┆ total_fraction │
│ ---     ┆ ---    ┆ ---   ┆ ---            │
│ str     ┆ u32    ┆ u32   ┆ f64            │
╞═════════╪════════╪═══════╪════════════════╡
│ overlap ┆ 628    ┆ 4027  ┆ 0.155947       │
│ aRSC    ┆ 3865   ┆ 30609 ┆ 0.12627        │
│ pRSC    ┆ 4035   ┆ 14442 ┆ 0.279393       │
└─────────┴────────┴───────┴────────────────┘

property sources: list[str]

list of source names

filter_overlap()

filter out overlap source

Return type:

Self

with_animal_column(animal)

with animal id column

Return type:

Self

to_dict(as_series=True)

to subregion:value dict

Parameters:

as_series (bool)

Return type:

dict[str, Any]

to_numpy()

to value array. Array[float, [n_source, n_subregion]]

Return type:

ndarray