neuralib.deeplabcut.core.DeepLabCutDataFrame

class neuralib.deeplabcut.core.DeepLabCutDataFrame

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)

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(-> ~polars.dataframe.frame.DataFrame)	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[, 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.
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)

Parameters:

• df (DataFrame) – DeepLabCut result dataframe

• meta (DeepLabCutMeta | None) – DeepLabCutMeta

• filtered (bool) – whether the results has already been filtered

dataframe() → DataFrame

dataframe(dataframe: DataFrame, may_inplace: bool = True) → Self

Getter/setter for the internal Polars DataFrame.

Parameters:

• dataframe (DataFrame | None) – Optional new dataframe to set.

• may_inplace (bool) – If True, update current instance. Otherwise, return new instance.

Returns:

The current dataframe or a modified wrapper instance.

Return type:

DataFrame | Self

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)

get specific joint

Parameters:

joint (str)

Return type:

JointDataFrame