merged to the lastest code

.readthedocs.yml

@@ -2,7 +2,10 @@ version: 2
 formats: []
 
 build:
-    image: latest
+  os: ubuntu-22.04
+  tools:
+    python: "3.7"
+  # image: latest
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
@@ -14,7 +17,6 @@ sphinx:
 #         - requirements: docs/requirements.txt
 
 python:
-  version: 3.7
   install:
     - method: pip
       path: .

dynamo/dynamo_logger.py

@@ -152,19 +152,35 @@ def error(self, message, indent_level=1, *args, **kwargs):
         message = format_logging_message(message, logging.ERROR, indent_level=indent_level)
         return self.logger.error(message, *args, **kwargs)
 
-    def info_insert_adata(self, key, adata_attr="obsm", indent_level=1, *args, **kwargs):
+    def info_insert_adata(self, key, adata_attr="obsm", log_level=logging.NOTSET, indent_level=1, *args, **kwargs):
         message = "<insert> %s to %s in AnnData Object." % (key, adata_attr)
-        message = format_logging_message(message, logging.DEBUG, indent_level=indent_level)
-        return self.logger.debug(message, *args, **kwargs)
+        if log_level == logging.NOTSET or log_level == logging.DEBUG:
+            self.debug(message, indent_level=indent_level, *args, **kwargs)
+        elif log_level == logging.INFO:
+            self.info(message, indent_level=indent_level, *args, **kwargs)
+        elif log_level == logging.WARN:
+            self.warning(message, indent_level=indent_level, *args, **kwargs)
+        elif log_level == logging.ERROR:
+            self.error(message, indent_level=indent_level, *args, **kwargs)
+        elif log_level == logging.CRITICAL:
+            self.critical(message, indent_level=indent_level, *args, **kwargs)
+        else:
+            raise NotImplementedError
 
-    def info_insert_adata_var(self, key, indent_level=1, *args, **kwargs):
-        return self.info_insert_adata(self, key, adata_attr="var", indent_level=1, *args, **kwargs)
+    def info_insert_adata_var(self, key, log_level, indent_level, *args, **kwargs):
+        return self.info_insert_adata(
+            self, key, adata_attr="var", log_level=log_level, indent_level=indent_level, *args, **kwargs
+        )
 
-    def info_insert_adata_obsm(self, key, indent_level=1, *args, **kwargs):
-        return self.info_insert_adata(self, key, adata_attr="obsm", indent_level=1, *args, **kwargs)
+    def info_insert_adata_obsm(self, key, log_level, indent_level, *args, **kwargs):
+        return self.info_insert_adata(
+            self, key, adata_attr="obsm", log_level=log_level, indent_level=indent_level, *args, **kwargs
+        )
 
-    def info_insert_adata_uns(self, key, indent_level=1, *args, **kwargs):
-        return self.info_insert_adata(self, key, adata_attr="uns", indent_level=1, *args, **kwargs)
+    def info_insert_adata_uns(self, key, log_level, indent_level, *args, **kwargs):
+        return self.info_insert_adata(
+            self, key, adata_attr="uns", log_level=log_level, indent_level=indent_level, *args, **kwargs
+        )
 
     def log_time(self):
         now = time.time()

dynamo/external/__init__.py

@@ -3,22 +3,14 @@
 
 from .gseapy import enrichr
 from .hodge import ddhodge
-from .pearson_residual_recipe import (
-    normalize_layers_pearson_residuals,
-    select_genes_by_pearson_residuals,
-)
 from .scifate import scifate_glmnet
 from .scribe import coexp_measure, coexp_measure_mat, scribe
-from .sctransform import sctransform
 
 __all__ = [
     "enrichr",
     "ddhodge",
-    "normalize_layers_pearson_residuals",
-    "select_genes_by_pearson_residuals",
     "scifate_glmnet",
     "coexp_measure",
     "coexp_measure_mat",
     "scribe",
-    "sctransform",
 ]

dynamo/external/gseapy.py

@@ -70,7 +70,6 @@ def enrichr(
         gene_sets=gene_sets,  # GO_Biological_Process_2018
         organism=organism,  # don't forget to set organism to the one you desired! e.g. Yeast
         background=background,
-        description=description,
         outdir=outdir,
         no_plot=no_plot,
         cutoff=cutoff,  # test dataset, use lower value from range(0,1)

dynamo/external/scifate.py

@@ -169,7 +169,7 @@ def adata_processing_TF_link(
     total = adata.layers[nt_layers[1]]
 
     # recalculate size factor
-    from ..preprocessing import calc_sz_factor_legacy
+    from ..preprocessing.deprecated import calc_sz_factor_legacy
 
     adata = calc_sz_factor_legacy(
         adata,

dynamo/external/scribe.py

@@ -151,7 +151,7 @@ def scribe(
 
     if normalize:
         # recalculate size factor
-        from ..preprocessing import calc_sz_factor_legacy
+        from ..preprocessing.deprecated import calc_sz_factor_legacy
 
         adata = calc_sz_factor_legacy(
             adata,

dynamo/plot/__init__.py

@@ -32,6 +32,7 @@
 )
 from .scatters import scatters
 from .scPotential import show_landscape
+from .sctransform import sctransform_plot_fit, plot_residual_var
 from .scVectorField import (  # , plot_LIC_gray
     cell_wise_vectors,
     cell_wise_vectors_3d,
@@ -150,4 +151,6 @@
     "causality",
     "comb_logic",
     "hessian",
+    "sctransform_plot_fit",
+    "plot_residual_var",
 ]

dynamo/plot/cell_cycle.py

@@ -72,7 +72,7 @@ def cell_cycle_scores(
     # Heatmap returns an axes obj but you need to get a mappable obj (get_children)
     colorbar(ax.get_children()[0], cax=cax, ticks=[-0.9, 0, 0.9])
 
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "plot_direct_graph",
@@ -82,13 +82,17 @@ def cell_cycle_scores(
             "close": True,
             "verbose": True,
         }
+
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return ax
     else:
         raise NotImplementedError("Unavailable save_show_or_return flag: %s" % save_show_or_return)

dynamo/plot/connectivity.py

@@ -309,7 +309,7 @@ def connectivity_base(
 
     ax.set(xticks=[], yticks=[])
 
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "connectivity_base",
@@ -321,14 +321,16 @@ def connectivity_base(
         }
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return ax
-    else:
-        raise NotImplementedError("Unsupported save_show_or_return")
 
 
 docstrings.delete_params("con_base.parameters", "edge_df", "save_show_or_return", "save_kwargs")
@@ -578,7 +580,7 @@ def nneighbors(
                 ax.set_ylabel(cur_b + "_2")
                 ax.set_title(cur_c)
 
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "nneighbors",
@@ -590,11 +592,14 @@ def nneighbors(
         }
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return g
     else:
         raise NotImplementedError('Invalid "save_show_or_return".')

dynamo/plot/dimension_reduction.py

@@ -23,7 +23,7 @@ def pca(adata: AnnData, *args, **kwargs) -> Optional[Axes]:
         `save_show_or_return='return'` as a kwarg, the axes of the plot would be returned.
     """
 
-    scatters(adata, "pca", *args, **kwargs)
+    return scatters(adata, "pca", *args, **kwargs)
 
 
 def umap(adata: AnnData, *args, **kwargs) -> Optional[Axes]:

dynamo/plot/dynamics.py

@@ -1064,7 +1064,7 @@ def phase_portraits(
                 despline_all(ax6)
                 deaxis_all(ax6)
 
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "phase_portraits",
@@ -1076,18 +1076,19 @@ def phase_portraits(
         }
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+    if save_show_or_return in ["show", "both", "all"]:
 
         with warnings.catch_warnings():
             warnings.simplefilter("ignore")
             plt.tight_layout()
 
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return g
-    else:
-        raise NotImplementedError("Unsupported save_show_or_return")
 
 
 def dynamics(
@@ -2727,7 +2728,7 @@ def dynamics(
                 elif experiment_type == "coassay":
                     pass  # show protein velocity (steady state and the Gamma distribution model)
     # g.autofmt_xdate(rotation=-30, ha='right')
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "dynamics",
@@ -2738,11 +2739,15 @@ def dynamics(
             "verbose": True,
         }
         s_kwargs = update_dict(s_kwargs, save_kwargs)
+
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return g
 
 

dynamo/plot/fate.py

@@ -74,7 +74,7 @@ def fate_bias(
         fate_bias, col_cluster=True, row_cluster=True, figsize=figsize, yticklabels=False, **cluster_maps_kwargs
     )
 
-    if save_show_or_return == "save":
+    if save_show_or_return in ["save", "both", "all"]:
         s_kwargs = {
             "path": None,
             "prefix": "fate_bias",
@@ -86,11 +86,14 @@ def fate_bias(
         }
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         save_fig(**s_kwargs)
-    elif save_show_or_return == "show":
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return == "return":
+    if save_show_or_return in ["return", "all"]:
         return ax
 
 
@@ -154,11 +157,16 @@ def fate(
             "close": True,
             "verbose": True,
         }
+
+        # prevent the plot from being closed if the plot need to be shown or returned.
+        if save_show_or_return in ["both", "all"]:
+            s_kwargs["close"] = False
+
         s_kwargs = update_dict(s_kwargs, save_kwargs)
 
         save_fig(**s_kwargs)
-    elif save_show_or_return in ["show", "both", "all"]:
+    if save_show_or_return in ["show", "both", "all"]:
         plt.tight_layout()
         plt.show()
-    elif save_show_or_return in ["return", "all"]:
+    if save_show_or_return in ["return", "all"]:
         return ax