cellrank.ul.models.FittedModel

class cellrank.ul.models.FittedModel(x_test, y_test, conf_int=None, x_all=None, y_all=None, w_all=None)

Class representing an already fitted model. Useful when the smoothed gene expression was computed externally.

Parameters

• x_test (Union[ndarray, spmatrix, List, Tuple]) – Independent variables of shape (n_samples, 1) used for prediction.

• y_test (Union[ndarray, spmatrix, List, Tuple]) – Prediction values of shape (n_samples,) for x_test.

• conf_int (Union[ndarray, spmatrix, List, Tuple, None]) – Array of shape (n_samples, 2) containing the lower and upper bounds of the confidence interval. If None, always set conf_int=False in cellrank.ul.models.BaseModel.plot().

• x_all (Union[ndarray, spmatrix, List, Tuple, None]) – Unfiltered independent variables of shape (n_cells, 1). If None, always sets hide_cells=True in cellrank.ul.models.BaseModel.plot().

• y_all (Union[ndarray, spmatrix, List, Tuple, None]) – Unfiltered dependent variables of shape (n_cells, 1). If None, always sets hide_cells=True` in cellrank.ul.models.BaseModel.plot().

• w_all (Union[ndarray, spmatrix, List, Tuple, None]) – Unfiltered weights of shape (n_cells,). If None and x_all and y_all are present, it will be set an array of 1.

Attributes

adata	Annotated data object.
conf_int	Array of shape (n_samples, 2) containing the lower and upper bounds of the confidence interval.
model	Underlying model.
prepared	Whether the model is prepared for fitting.
shape	Number of cells in adata.
w	Filtered weights of shape (n_filtered_cells,) used for fitting.
w_all	Unfiltered weights of shape (n_cells,).
x	Filtered independent variables of shape (n_filtered_cells, 1) used for fitting.
x_all	Unfiltered independent variables of shape (n_cells, 1).
x_hat	Filtered independent variables used when calculating default confidence interval, usually same as x.
x_test	Independent variables of shape (n_samples, 1) used for prediction.
y	Filtered dependent variables of shape (n_filtered_cells, 1) used for fitting.
y_all	Unfiltered dependent variables of shape (n_cells, 1).
y_hat	Filtered dependent variables used when calculating default confidence interval, usually same as y.
y_test	Prediction values of shape (n_samples,) for x_test.

Methods

confidence_interval([x_test])	Array of shape (n_samples, 2) containing the lower and upper bounds of the confidence interval.
copy()	Return a copy of self.
default_confidence_interval([x_test])	Array of shape (n_samples, 2) containing the lower and upper bounds of the confidence interval.
fit([x, y, w])	Do nothing and return self.
from_model(model)	Create a cellrank.ul.models.FittedModel instance from cellrank.ul.models.BaseModel.
plot([figsize, same_plot, hide_cells, perc, ...])	Plot the smoothed gene expression.
predict([x_test, key_added])	Prediction values of shape (n_samples,) for x_test.
prepare(*_args, **_kwargs)	Do nothing and return self.
read(fname[, adata, copy])	Deserialize self from a file.
write(fname[, write_adata, ext])	Serialize self to a file.