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Eg. for a percentile of 85 the format would be 'p85'. Floats are accepted as p99.9 Alternatively, vmin/vmax could be a function that is applied to the list of color values (`color_vector`). E.g. def my_vmax(color_vector): np.percentile(color_vector, p=80) Parameters ---------- index This index of the plot color_vector List or values for the plot Returns ------- (vmin, vmax, vcenter, norm) containing None or float values for vmin, vmax, vcenter and matplotlib.colors.Normalize or None for norm. r\r[r]rorzThe parameter z# is not valid. If setting multiple z% values,check that the length of the z' list is equal to the number of plots. Np=z for plot number z? is not valid. Please check the correct format for percentiles.)qz%The return of the function given for z? is not valid. Please check that the function returns a number.z The given z is not valid. Please check that the value given is a valid number, a string starting with 'p' for percentiles or a valid function.)rrrerrorrr startswithrrrZ nanpercentilecallablertuple) r\r[r]r^rroutZv_namevZv_valuerrrrsJ#             $rcsddltj}|}|j}|d|d|d||fdd|D}|jj j k r|j|d<j t | |jd|_ ||_|S) Nrrmrrlcs&i|]\}}|jjjkr||jqSr) annotation Parameteremptyrkrinspectrr Osz'_wraps_plot_scatter..rn)return_annotation)r signaturer parametersrrupdateitemsr Signaturerrvalues __signature____annotations__)wrapperparamsZ wrapper_sigZwrapper_params annotationsrrr_wraps_plot_scatterCs&         r)rncKst|df|S)a Scatter plot in UMAP basis. Parameters ---------- {adata_color_etc} {edges_arrows} {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- .. plot:: :context: close-figs import scanpy as sc adata = sc.datasets.pbmc68k_reduced() sc.pl.umap(adata) Colour points by discrete variable (Louvain clusters). .. plot:: :context: close-figs sc.pl.umap(adata, color="louvain") Colour points by gene expression. .. plot:: :context: close-figs sc.pl.umap(adata, color="HES4") Plot muliple umaps for different gene expressions. .. plot:: :context: close-figs sc.pl.umap(adata, color=["HES4", "TNFRSF4"]) .. currentmodule:: scanpy See also -------- tl.umap umaprrlrrrrrbs;rcKst|df|S)a Scatter plot in tSNE basis. Parameters ---------- {adata_color_etc} {edges_arrows} {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- .. plot:: :context: close-figs import scanpy as sc adata = sc.datasets.pbmc68k_reduced() sc.tl.tsne(adata) sc.pl.tsne(adata, color='bulk_labels') .. currentmodule:: scanpy See also -------- tl.tsne tsnerrrrrrs&r)r3r4r5cKst|df|S)a Scatter plot in Diffusion Map basis. Parameters ---------- {adata_color_etc} {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- .. plot:: :context: close-figs import scanpy as sc adata = sc.datasets.pbmc68k_reduced() sc.tl.diffmap(adata) sc.pl.diffmap(adata, color='bulk_labels') .. currentmodule:: scanpy See also -------- tl.diffmap diffmaprrrrrrs$r)layout)rlrrncKsX|dkrt|jddd}d|}d||krJtdd||t||f|S)a Scatter plot in graph-drawing basis. Parameters ---------- {adata_color_etc} layout One of the :func:`~scanpy.tl.draw_graph` layouts. By default, the last computed layout is used. {edges_arrows} {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- .. plot:: :context: close-figs import scanpy as sc adata = sc.datasets.pbmc68k_reduced() sc.tl.draw_graph(adata) sc.pl.draw_graph(adata, color=['phase', 'bulk_labels']) .. currentmodule:: scanpy See also -------- tl.draw_graph N draw_graphrr draw_graph_X_z8Did not find {} in adata.obs. Did you compute layout {}?)runsZ obsm_keysrformatr)rlrrrmrrrrs+r)annotate_var_explainedrfrirg)rrfrirgrnc Ks|st|df|||d|Sd|jkrTd|jkrTtdt|jdddt|jddD}|d krt|dfd |i|}|jD]4}|||j | ||j q|St|dfd d d |} t| tr.| D]4}|||j | ||j qn0| || j | || j tjd||d |d kr|| Sd S)a] Scatter plot in PCA coordinates. Use the parameter `annotate_var_explained` to annotate the explained variance. Parameters ---------- {adata_color_etc} annotate_var_explained {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- .. plot:: :context: close-figs import scanpy as sc adata = sc.datasets.pbmc3k_processed() sc.pl.pca(adata) Colour points by discrete variable (Louvain clusters). .. plot:: :context: close-figs sc.pl.pca(adata, color="louvain") Colour points by gene expression. .. plot:: :context: close-figs sc.pl.pca(adata, color="CST3") .. currentmodule:: scanpy See also -------- tl.pca pp.pca pca)rfrirgZX_pcaz>Could not find entry in `obsm` for 'pca'. Available keys are: rrc Ss6i|].\}}d|dd|dt|ddqS)zPC{}roz PC{} ({}%)dr)rround)rirrrrrrs zpca..Zvariance_ratioTriFrN)robsmkeysKeyErrorrrrZaxesrZxaxisZ get_labelZget_textrZyaxisrrr) rlrrfrirgrZ label_dictrrhrrrrr(sD>   r)r3Zscatter_spatialr4r5spatial?)rmimgimg_key library_id crop_coord alpha_imgbwrTrN spot_sizerRrfrirg)rmrr r r r r rTrNrrRrfrirgrnc Ksrt|j|\}}t||||d\}}t|| } t||| d} t|| }t| |d} |r\d}nd}|| | d}t|f|| || ddd|}t|t s|g}|D]}t | | g}|dk r|j|||d n|d ||dk r||d |d ||d |dq||d |d ||d |dqtjd| |d| dksj| dkrn|SdS)u Scatter plot in spatial coordinates. This function allows overlaying data on top of images. Use the parameter `img_key` to see the image in the background And the parameter `library_id` to select the image. By default, `'hires'` and `'lowres'` are attempted. Use `crop_coord`, `alpha_img`, and `bw` to control how it is displayed. Use `size` to scale the size of the Visium spots plotted on top. As this function is designed to for imaging data, there are two key assumptions about how coordinates are handled: 1. The origin (e.g `(0, 0)`) is at the top left – as is common convention with image data. 2. Coordinates are in the pixel space of the source image, so an equal aspect ratio is assumed. If your anndata object has a `"spatial"` entry in `.uns`, the `img_key` and `library_id` parameters to find values for `img`, `scale_factor`, and `spot_size` arguments. Alternatively, these values be passed directly. Parameters ---------- {adata_color_etc} {scatter_spatial} {scatter_bulk} {show_save_ax} Returns ------- If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it. Examples -------- This function behaves very similarly to other embedding plots like :func:`~scanpy.pl.umap` >>> adata = sc.datasets.visium_sge("Targeted_Visium_Human_Glioblastoma_Pan_Cancer") >>> sc.pp.calculate_qc_metrics(adata, inplace=True) >>> sc.pl.spatial(adata, color="log1p_n_genes_by_counts") See Also -------- :func:`scanpy.datasets.visium_sge` Example visium data. :tutorial:`spatial/basic-analysis` Tutorial on spatial analysis. )r )r rNrgrayN?F)rmrNrTrRrfrg)rPrequalrror+rrfrT)_check_spatial_datar _check_img_check_spot_size_check_scale_factor_check_crop_coord_check_na_colorrrrrZ concatenateZget_xlimZget_ylimZimshowZ set_aspectZ invert_yaxisZset_xlimZset_ylimrr)rlrmrr r r r r rTrNrrRrfrirgr spatial_dataZcmap_imgZ circle_radiusrrhZ cur_coordsrrrrsTN      rq)rJrKrMrprncCsddd|}|dkr8|dkr8tddt|Dg}n|dk rP|dk rPtd|dkrlttt||}n&|dk rt|tr|g}d d |D}td d|Dr|g}|D](}t||kstd d|Dstq|S) z:Normalize components/ dimensions args for embedding plots.rr+rjNcss|] }|VqdSNr)rrrrr sz,_components_to_dimensions..z-Cannot provide both dimensions and componentsallcSs g|]}dd|dDqS)cSsg|]}t|dqSr)r)rdimrrrr!sz8_components_to_dimensions...,)splitrr}rrrr!sz-_components_to_dimensions..css|]}t|tVqdSrrr)relrrrr#scss|]}t|tVqdSrr!rrrrr's) rrangerrrrrrr)rJrKrMrpZndimsrrrrr s"  r)rQrXrSc  Cs6| rBt|rBd|kr"td|dd}|}||d<|j} |dkrv|} | | j | j | j d| j g|dkr| D]} |jgg|| | dq|jddd t| d krd nt| d krd nd|dn^|dkr2tj| ddgdj|dd}|D]&\} }}|j||| |dd||dq dS)z Add a legend to the passed Axes.ZNAzINo fallback for null labels has been defined if NA already in categories.TgQ?r:)r}labelFz center left)rorrorrr+)rUlocZbbox_to_anchorZncolfontsizezon dataxy)columns)Zobservedcenter)weightZverticalalignmentZhorizontalalignmentr'Z path_effectsN)rranyNotImplementedErroradd_categoriesfillnar categoriesZ get_positionZ set_positionZx0Zy0widthheightrZlegendrZ DataFramegroupbyZmedianZ sort_indexZ itertuplestext)rhrrQrXrWrVrYrrRrSrZcatsboxr$Zall_posZx_posZy_posrrrr-sN"   r)rlrmrncCsN||jkr|j|Sd||jkr4|jd|Std|d|ddS)z9Get array for basis from anndata. 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TrsNFcsi|]\}}||qSrrrrrrrsz!_color_vector..)rQ)rrrrr7r9rrrrr?mapZisnar-r/r0)rlr=rrQrRrOrrr@rrs  rcCsP|dkr dn>|dkrdn2|dkr$dn&|dkr0dnd |krH|d d n|}|S) z4 converts the 'basis' into the proper name. rZDCrZtSNErZUMAPrPCrrr{)replaceupper)rmZcomponent_namerrrrs r)rrrncCs6|dkr|dkrtdn|dkr.|ddS|SdS)zV Resolve spot_size value. This is a required argument for spatial plots. NzUWhen .uns['spatial'][library_id] does not exist, spot_size must be provided directly. scalefactorsZspot_diameter_fullres)r)rrrrrrs r)rr rNrncCs8|dk r |S|dk r0|dk r0|dd|dSdSdS)z$Resolve scale_factor, defaults to 1.NrEZtissue_Z_scalefrr)rr rNrrrrs r)rr rncCsx|di}|tkrZt|dkr8tdt|n"t|dkrVt|d}nd}|dk rl||}nd}||fS)z Given a mapping, try and extract a library id/ mapping with spatial data. Assumes this is `.uns` from how we parse visium data. rrozUFound multiple possible libraries in `.uns['spatial']. Please specify. 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