Update plotting

stlearn/plotting/QC_plot.py

@@ -17,7 +17,6 @@ def QC_plot(
         show_axis: bool = False,
         cropped: bool = True,
         margin: int = 100,
-        dpi: int = 192,
         output: str = None,
 ) -> Optional[AnnData]:
     """\
@@ -43,8 +42,6 @@ def QC_plot(
             Show axis or not.
         show_size_legend
             Show size legend or not.
-        dpi
-            Set dpi as the resolution for the plot.
         name
             Name of the output figure file.
         output
@@ -65,7 +62,7 @@ def QC_plot(
         reads_per_spot.to_numpy().reshape(-1, 1))
     genes_per_spot = adata.to_df().astype(bool).sum(axis=1)
 
-    plt.rcParams['figure.dpi'] = dpi
+    #plt.rcParams['figure.dpi'] = dpi
 
     # Option for turning off showing figure
     plt.ioff()
@@ -118,7 +115,7 @@ def QC_plot(
 
     # fig.tight_layout()
     if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
     plt.show()

stlearn/plotting/cci_plot.py

@@ -11,7 +11,6 @@ def het_plot(
     adata: AnnData,
     use_cluster: str = 'louvain',
     use_het: str = 'het',
-    dpi: int = 100,
     spot_size: Union[float,int] = 6.5,
     vmin: int = None,
     vmax: int = None,

stlearn/plotting/cluster_plot.py

@@ -24,7 +24,6 @@ def cluster_plot(
     spot_size: Union[float, int] = 6.5,
     show_axis: bool = False,
     show_legend: bool = True,
-    dpi: int = 180,
     show_trajectory: bool = False,
     reverse: bool = False,
     show_subcluster: bool = False,
@@ -61,8 +60,6 @@ def cluster_plot(
         Show axis or not.
     show_legend
         Show legend or not.
-    dpi
-        Set dpi as the resolution for the plot.
     show_trajectory
         Show the spatial trajectory or not. It requires stlearn.spatial.trajectory.pseudotimespace.
     show_subcluster
@@ -210,7 +207,7 @@ def cluster_plot(
         name = use_label
 
     if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
 

stlearn/plotting/deconvolution_plot.py

@@ -20,7 +20,6 @@ def deconvolution_plot(
     spot_size: Union[float, int] = 10,
     show_axis: bool = False,
     show_legend: bool = True,
-    dpi: int = 180,
     cropped: bool = True,
     margin: int = 100,
     name: str = None,
@@ -53,8 +52,6 @@ def deconvolution_plot(
         Show axis or not.
     show_legend
         Show legend or not.
-    dpi
-        Set dpi as the resolution for the plot.
     show_trajectory
         Show the spatial trajectory or not. It requires stlearn.spatial.trajectory.pseudotimespace.
     show_subcluster
@@ -151,7 +148,7 @@ def my_autopct(pct):
             name = use_label
 
     if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
 

stlearn/plotting/enrichment_analysis_plot.py

@@ -17,7 +17,6 @@ def enrichment_analysis_plot(
     save_plot: str = None,
     cmap: str = "plasma",
     title: str = None,
-    dpi: int = 192,
     store: bool = True,
     output: str = None,
     copy: bool = False,
@@ -51,11 +50,11 @@ def enrichment_analysis_plot(
 
     if output is not None:
         fig.savefig(output + "/enrich_plot_factor_" + str(factor) + "_" +
-                    gene_sets + ".png", dpi=dpi, bbox_inches='tight', pad_inches=0)
+                    gene_sets + ".png", dpi=plt.figure().dpi, bbox_inches='tight', pad_inches=0)
 
     if store:
 
-        fig_np = get_img_from_fig(fig, dpi)
+        fig_np = get_img_from_fig(fig, plt.figure().dpi)
 
         plt.close(fig)
 

stlearn/plotting/gene_plot.py

@@ -26,7 +26,6 @@ def gene_plot(
     show_axis: bool = False,
     cropped: bool = True,
     margin: int = 100,
-    dpi: int = 192,
     name: str = None,
     output: str = None,
     copy: bool = False,
@@ -60,8 +59,6 @@ def gene_plot(
         Show axis or not.
     show_legend
         Show legend or not.
-    dpi
-        Set dpi as the resolution for the plot.
     show_trajectory
         Show the spatial trajectory or not. It requires stlearn.spatial.trajectory.pseudotimespace.
     show_subcluster
@@ -121,12 +118,6 @@ def gene_plot(
     # Overlay the tissue image
     a.imshow(image, alpha=tissue_alpha, zorder=-1,)
 
-    if name is None:
-        name = method
-    if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
-                    bbox_inches='tight', pad_inches=0)
-
     if cropped:
         imagecol = adata.obs["imagecol"]
         imagerow = adata.obs["imagerow"]
@@ -138,17 +129,18 @@ def gene_plot(
                 imagerow.max() + margin)
 
         a.set_ylim(a.get_ylim()[::-1])
-        #plt.gca().invert_yaxis()
+
+    if name is None:
+        name = method
+    if output is not None:
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
+                    bbox_inches='tight', pad_inches=0)
+
+
+
 
     plt.show()
-    # Store figure
-    #fig_np = get_img_from_fig(fig,dpi)
-    # plt.close(fig)
-    # if "plots" not in adata.uns:
-    #    adata.uns['plots'] = {}
-    #adata.uns['plots'].update({str(', '.join(genes)):fig_np})
-    # print("The plot stored in adata.uns['plot']['" +
-    #    str(', '.join(genes)) + "']")
+
 
 
 def _gene_plot(adata, method, genes):

stlearn/plotting/microenv_plot.py

@@ -23,7 +23,6 @@ def microenv_plot(
     show_axis: bool = False,
     cropped: bool = True,
     margin: int = 100,
-    dpi: int = 192,
     name: str = None,
     output: str = None,
     copy: bool = False,
@@ -53,8 +52,6 @@ def microenv_plot(
         Show axis or not.
     show_legend
         Show legend or not.
-    dpi
-        Set dpi as the resolution for the plot.
     name
         Name of the output figure file.
     output
@@ -114,7 +111,7 @@ def microenv_plot(
             name = method
         if output is not None:
             fig.savefig(output + "/factor_" + str(i+1) + ".png",
-                        dpi=dpi, bbox_inches='tight', pad_inches=0)
+                        dpi=plt.figure().dpi, bbox_inches='tight', pad_inches=0)
 
         fig_np = get_img_from_fig(fig, dpi)
 

stlearn/plotting/non_spatial_plot.py

@@ -14,7 +14,6 @@
 def non_spatial_plot(
     adata: AnnData,
     use_label: str = "louvain",
-    dpi: int = 180
 ) -> Optional[AnnData]:
 
     """\

stlearn/plotting/subcluster_plot.py

@@ -23,7 +23,6 @@ def subcluster_plot(
     show_plot: bool = True,
     cropped: bool = True,
     margin: int = 100,
-    dpi: int = 192,
     name: str = None,
     output: str = None,
     copy: bool = False,
@@ -55,8 +54,6 @@ def subcluster_plot(
         Show axis or not.
     show_legend
         Show legend or not.
-    dpi
-        Set dpi as the resolution for the plot.
     name
         Name of the output figure file.
     output
@@ -153,7 +150,7 @@ def subcluster_plot(
         if name is None:
             print("The file name is not defined!")
             name = use_label
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
     # plt.close(fig)

stlearn/plotting/trajectory/local_plot.py

@@ -26,7 +26,6 @@ def local_plot(
     show_color_bar: bool = True,
     show_axis: bool = False,
     show_plot: bool = True,
-    dpi: int = 180,
     name: str = None,
     output: str = None,
     copy: bool = False,
@@ -163,7 +162,7 @@ def local_plot(
         if name is None:
             print("The file name is not defined!")
             name = use_label
-        fig.savefig(output + "/" + name, dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=matplotlib.pyplot.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
 

stlearn/plotting/trajectory/pseudotime_plot.py

@@ -30,7 +30,6 @@ def pseudotime_plot(
     margin: int = 100,
     output: str = None,
     name: str = None,
-    dpi: int = 180,
     copy: bool = False,
 ) -> Optional[AnnData]:
 
@@ -71,8 +70,6 @@ def pseudotime_plot(
         Show legend or not.
     show_plot
         Show plot or not
-    dpi
-        Set dpi as the resolution for the plot.
     output
         Save the figure as file or not.
     copy
@@ -175,7 +172,7 @@ def pseudotime_plot(
         #plt.gca().invert_yaxis()
 
     if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
     if show_plot == True:
         plt.show()

stlearn/plotting/trajectory/tree_plot.py

@@ -118,7 +118,7 @@ def tree_plot(
         name = use_label
 
     if output is not None:
-        fig.savefig(output + "/" + name + ".png", dpi=dpi,
+        fig.savefig(output + "/" + name, dpi=plt.figure().dpi,
                     bbox_inches='tight', pad_inches=0)
 
 

stlearn/spatials/trajectory/global_level.py

@@ -11,6 +11,7 @@ def global_level(
     list_cluster: list = [],
     return_graph: bool = False,
     w: float = None,
+    verbose: bool = True,
     copy: bool = False,
 ) -> Optional[AnnData]:
 
@@ -36,6 +37,8 @@ def global_level(
     Anndata
     """
 
+
+
     assert w <= 1, "w should be in range 0 to 1"
     # Get global graph
     G = adata.uns["global_graph"]
@@ -46,6 +49,9 @@ def global_level(
     query_nodes = list_cluster
     query_nodes = ordering_nodes(query_nodes, use_label,adata)
 
+    if verbose:
+        print("Start to construct the trajectory: " +  " -> ".join(np.array(query_nodes).astype(str)))
+
     query_dict = {}
     order_dict = {}