neuralib.tracking.deeplabcut.core.DeepLabCutDataFrame

class neuralib.tracking.deeplabcut.core.DeepLabCutDataFrame[source]

Bases: DataFrameWrapper

DeepLabCut DataFrame

┌───────────┬───────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬──────────┐
│ Nose_x    ┆ Nose_y    ┆ Nose_like ┆ EarL_x    ┆ … ┆ TailMid_l ┆ TailEnd_x ┆ TailEnd_y ┆ TailEnd_ │
│ ---       ┆ ---       ┆ lihood    ┆ ---       ┆   ┆ ikelihood ┆ ---       ┆ ---       ┆ likeliho │
│ f64       ┆ f64       ┆ ---       ┆ f64       ┆   ┆ ---       ┆ f64       ┆ f64       ┆ od       │
│           ┆           ┆ f64       ┆           ┆   ┆ f64       ┆           ┆           ┆ ---      │
│           ┆           ┆           ┆           ┆   ┆           ┆           ┆           ┆ f64      │
╞═══════════╪═══════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪══════════╡
│ 57.907318 ┆ 512.54742 ┆ 0.999679  ┆ 77.701355 ┆ … ┆ 0.999904  ┆ 257.71426 ┆ 561.89660 ┆ 0.999961 │
│           ┆ 4         ┆           ┆           ┆   ┆           ┆ 4         ┆ 6         ┆          │
│ 57.907318 ┆ 516.79528 ┆ 0.999688  ┆ 77.701355 ┆ … ┆ 0.999923  ┆ 257.71426 ┆ 562.05725 ┆ 0.999954 │
│ …         ┆ …         ┆ …         ┆ …         ┆ … ┆ …         ┆ …         ┆ …         ┆ …        │
│ 94.259621 ┆ 43.849434 ┆ 0.973851  ┆ 106.33532 ┆ … ┆ 0.998977  ┆ 87.477776 ┆ 257.11996 ┆ 0.999937 │
│ 94.294357 ┆ 44.340511 ┆ 0.965436  ┆ 106.45220 ┆ … ┆ 0.999604  ┆ 87.223534 ┆ 258.46600 ┆ 0.999912 │
└───────────┴───────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴──────────┘

__init__(df, meta, *, filtered)[source]

Parameters:

df (DataFrame) – DeepLabCut result dataframe
meta (DeepLabCutMeta | None) – DeepLabCutMeta
filtered (bool) – whether the results has already been filtered

Methods

`__init__`(df, meta, *, filtered)
`clear`([n])	See polars.DataFrame.clear.
`clone`()	Clone the wrapper.
`dataframe`([dataframe, may_inplace])	Getter/setter for the internal Polars DataFrame.
`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.
`get_joint`(joint)	get specific joint
`group_by`(*by[, maintain_order])	See polars.DataFrame.group_by.
`head`([n])	See polars.DataFrame.head.
`join`(other, on, args, *kwargs)	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, *kwargs)	See polars.DataFrame.sort.
`tail`([n])	See polars.DataFrame.tail.
`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.
`default_filtered`	whether default filtered when running the deeplabcut
`fps`	frame per second, meta data required
`joints`	list of labelled joints
`meta`	`DeepLabCutMeta`
`model_config`	`DeepLabCutModelConfig`
`nframes`	number of frames
`schema`	See polars.DataFrame.schema.

__init__(df, meta, *, filtered)[source]

Parameters:

df (DataFrame) – DeepLabCut result dataframe
meta (DeepLabCutMeta | None) – DeepLabCutMeta
filtered (bool) – whether the results has already been filtered

dataframe(dataframe=None, may_inplace=True)[source]

Getter/setter for the internal Polars DataFrame.

Parameters:

dataframe (DataFrame | None) – Optional new dataframe to set.
may_inplace – If True, update current instance. Otherwise, return new instance.

Returns:

The current dataframe or a modified wrapper instance.

property default_filtered: bool: whether default filtered when running the deeplabcut

property meta: DeepLabCutMeta: DeepLabCutMeta

property model_config: DeepLabCutModelConfig: DeepLabCutModelConfig

property fps: float: frame per second, meta data required

property nframes: int: number of frames

property joints: list[str]: list of labelled joints

get_joint(joint)[source]

get specific joint

Parameters:: joint (str)
Return type:: JointDataFrame

clear(n=5)

See polars.DataFrame.clear.

Parameters:: n (int)
Return type:: Self

clone()

Clone the wrapper.

Return type:: Self

property columns: list[str]: See polars.DataFrame.columns.

drop(*columns, strict=True)

See polars.DataFrame.drop.

Parameters:

columns (pty.ColumnNameOrSelector | Iterable[pty.ColumnNameOrSelector])
strict (bool)

Return type:

Self

drop_nulls(subset)

See polars.DataFrame.drop_nulls.

Parameters:: subset (pty.ColumnNameOrSelector | Collection[pty.ColumnNameOrSelector])
Return type:: Self

fill_nan(value=None)

See polars.DataFrame.fill_nan.

Parameters:: value (pl.Expr | int | float | None)
Return type:: Self

fill_null(value=None, strategy=None, limit=None, **kwargs)

See polars.DataFrame.fill_null.

Parameters:

value (Any | pl.Expr | None)
strategy (pty.FillNullStrategy | None)
limit (int | None)

Return type:

Self

filter(*predicates, **constraints)

See polars.DataFrame.filter.

Parameters:

predicates (pty.IntoExprColumn | Iterable[pty.IntoExprColumn] | bool | list[bool] | np.ndarray)
constraints (Any)

Return type:

Self

group_by(*by, maintain_order=False, **named_by)

See polars.DataFrame.group_by.

Parameters:

by (pty.IntoExpr | Iterable[pty.IntoExpr])
maintain_order (bool)
named_by (pty.IntoExpr)

Return type:

GroupBy

head(n=5)

See polars.DataFrame.head.

Parameters:: n (int)
Return type:: Self

join(other, on, *args, **kwargs)

See polars.DataFrame.join.

Parameters:: other (pl.DataFrame | DataFrameWrapper)
Return type:: Self

lazy()

Wrap dataframe in a lazy wrapper.

Return type:: LazyDataFrameWrapper[Self]

limit(n=5)

See polars.DataFrame.limit.

Parameters:: n (int)
Return type:: Self

partition_by(by, *more_by, as_dict=False, **kwargs): See polars.DataFrame.partition_by.

pipe(function, *args, **kwargs)

See polars.DataFrame.pipe.

Parameters:

function (Callable[Concatenate[pl.DataFrame, P], pl.DataFrame])
args (P.args)
kwargs (P.kwargs)

Return type:

Self

rename(mapping)

See polars.DataFrame.rename.

Parameters:: mapping (dict[str, str] | Callable[[str], str])
Return type:: Self

property schema: Schema: See polars.DataFrame.schema.

select(*exprs, **named_exprs)

See polars.DataFrame.select.

Parameters:

exprs (pty.IntoExpr | Iterable[pty.IntoExpr])
named_exprs (pty.IntoExpr)

Return type:

Self

slice(offset, length=None)

See polars.DataFrame.slice.

Parameters:

offset (int)
length (int | None)

Return type:

Self

sort(by, *more_by, **kwargs)

See polars.DataFrame.sort.

Return type:: Self

tail(n=5)

See polars.DataFrame.tail.

Parameters:: n (int)
Return type:: Self

with_columns(*exprs, **named_exprs)

See polars.DataFrame.with_columns.

Parameters:

exprs (pty.IntoExpr | Iterable[pty.IntoExpr])
named_exprs (pty.IntoExpr)

Return type:

Self

with_row_index(name='index', offset=0)

See polars.DataFrame.with_row_index.

Parameters:

name (str)
offset (int)

Return type:

Self