"""

Plotting of continuous features stored in adata.obs.

"""

from matplotlib import pyplot as plt

from PIL import Image

import pandas as pd

import matplotlib

import numpy as np

from typing import Optional, Union, Mapping # Special

from typing import Sequence, Iterable # ABCs

from typing import Tuple # Classes

from anndata import AnnData

import warnings

from stlearn.plotting.classes import FeaturePlot

from stlearn.plotting.classes_bokeh import BokehGenePlot

from stlearn.plotting._docs import doc_spatial_base_plot, doc_gene_plot

from stlearn.utils import Empty, _empty, _AxesSubplot, _docs_params

from bokeh.io import push_notebook, output_notebook

from bokeh.plotting import show

# @_docs_params(spatial_base_plot=doc_spatial_base_plot, gene_plot=doc_gene_plot)

def feat_plot(

adata: AnnData,

feature: str = None,

threshold: Optional[float] = None,

contour: bool = False,

step_size: Optional[int] = None,

title: Optional["str"] = None,

figsize: Optional[Tuple[float, float]] = None,

cmap: Optional[str] = "Spectral_r",

use_label: Optional[str] = None,

list_clusters: Optional[list] = None,

ax: Optional[matplotlib.axes._subplots.Axes] = None,

fig: Optional[matplotlib.figure.Figure] = None,

show_plot: Optional[bool] = True,

show_axis: Optional[bool] = False,

show_image: Optional[bool] = True,

show_color_bar: Optional[bool] = True,

color_bar_label: Optional[str] = "",

zoom_coord: Optional[float] = None,

crop: Optional[bool] = True,

margin: Optional[bool] = 100,

size: Optional[float] = 7,

image_alpha: Optional[float] = 1.0,

cell_alpha: Optional[float] = 0.7,

use_raw: Optional[bool] = False,

fname: Optional[str] = None,

dpi: Optional[int] = 120,

vmin: Optional[float] = None,

vmax: Optional[float] = None,

) -> Optional[AnnData]:

"""\

Allows the visualization of a continuous features stored in adata.obs

for Spatial transcriptomics array.

Parameters

-------------------------------------

{spatial_base_plot}

{feature_plot}

Examples

-------------------------------------

>>> import stlearn as st

>>> adata = st.datasets.example_bcba()

>>> st.pl.gene_plot(adata, 'dpt_pseudotime')

"""

FeaturePlot(

adata,

feature=feature,

threshold=threshold,

contour=contour,

step_size=step_size,

title=title,

figsize=figsize,

cmap=cmap,

use_label=use_label,

list_clusters=list_clusters,

ax=ax,

fig=fig,

show_plot=show_plot,

show_axis=show_axis,

show_image=show_image,

show_color_bar=show_color_bar,

color_bar_label=color_bar_label,

zoom_coord=zoom_coord,

crop=crop,

margin=margin,

size=size,

image_alpha=image_alpha,

cell_alpha=cell_alpha,

use_raw=use_raw,

fname=fname,

dpi=dpi,

vmin=vmin,

vmax=vmax,

)