- Fix: Fixed the bug of when plot the heatmap of correlation, the rot…

…ation of x-axis and y-axis raise error.

Docs/ChangeLog.md

@@ -1,3 +1,9 @@
+# Version: 1.111.7
+## Date: 2024-09-06
+### Changes:
+- Fix: Fixed the bug of when plot the heatmap of correlation, the rotation of x-axis and y-axis raise error.
+
+
 # Version: 1.111.6
 ## Date: 2024-08-21
 ### Changes:

metax/gui/main_gui.py

@@ -4227,10 +4227,10 @@ def get_title_by_table_name(self, table_name):
                 if cluster:
                     df = self.delete_zero_columns(df)
                 self.show_message('Correlation is running, please wait...')
-                BasicPlot(self.tfa).plot_corr_sns(df=df, title_name=title_name, cluster= cluster, 
+                BasicPlot(self.tfa, **self.heatmap_params_dict).plot_corr_sns(df=df, title_name=title_name, cluster= cluster, 
                                                 width=width, height=height, font_size=font_size, 
                                                 show_all_labels=show_all_labels, theme=theme, cmap=cmap,
-                                                rename_sample = rename_sample, **self.heatmap_params_dict)
+                                                rename_sample = rename_sample)
 
             elif method == 'alpha_div':
                 self.show_message('Alpha diversity is running, please wait...')
@@ -5038,14 +5038,14 @@ def plot_co_expr(self, plot_type = 'network'):
                     self.checkBox_corr_hetatmap_show_all_labels_y.isChecked(),
                 )
                 cmap = self.comboBox_corr_hetatmap_cmap.currentText()
-                BasicPlot(self.tfa).plot_items_corr_heatmap(df=df,
+                BasicPlot(self.tfa, **self.heatmap_params_dict).plot_items_corr_heatmap(df=df,
                                                 title_name=f'Expression Correlation Heatmap({df_type})',
                                                 cluster=True,
                                                 cmap=cmap,
                                                 width=width, height=height, 
                                                 font_size=font_size, 
-                                                show_all_labels=show_all_labels,
-                                                **self.heatmap_params_dict)
+                                                show_all_labels=show_all_labels
+                                                )
 
             except Exception as e:
                 error_message = traceback.format_exc()

metax/peptide_annotator/pep_to_taxafunc.py

@@ -219,15 +219,16 @@ def proteins_to_taxa_func(self,protein_list: list ) -> dict:
 pep_null = 'MGYG000000137_01815;MGYG000001639_01406;MGYG000000236_03945'
 pep_no_species_level = "MGYG000000385;MGYG000002077;MGYG000003829"
 pep_mag_level = 'MGYG000003142_02726;MGYG000003142_02725'
+pep_t ='GCF_943193095.1-2283;concoct.103-megahit_28365_1'
 ### test data
 
 if __name__ == '__main__':
     import time
     t1 = time.time()
 
-    db_path = 'C:/Users/Qing/Desktop/MetaX_Suite/metaX_dev_files/MetaX-human-gut_20231211.db'
+    db_path = 'metax_db.db'
 
-    pep2taxafunc = Pep2TaxaFunc(db_path = db_path, threshold = 1, genome_mode = True)
+    pep2taxafunc = Pep2TaxaFunc(db_path = db_path, threshold = 1, genome_mode = True, protein_genome_separator= "_")
 
 
     # for i in [pep_no_species_level, pep_null, pep2, pep7, pep8, pep9, pep10, pep11]:

metax/taxafunc_ploter/basic_plot.py

@@ -10,16 +10,23 @@
 from .get_distinct_colors import GetDistinctColors
 
 class BasicPlot:
-    def __init__(self, tfobj):
+    def __init__(self, tfobj,
+                 linkage_method:str = 'average', distance_metric:str = 'correlation',
+                 x_labels_rotation:int = 90, y_labels_rotation:int = 0):
         self.tfa =  tfobj
         self.get_distinct_colors = GetDistinctColors().get_distinct_colors
         self.assign_colors = GetDistinctColors().assign_colors
+        # for heatmap
+        self.linkage_method = linkage_method
+        self.distance_metric = distance_metric
+        self.x_labels_rotation = x_labels_rotation
+        self.y_labels_rotation = y_labels_rotation
+
         # reset the style
         plt.style.use('default')
         sns.set_theme()
 
 
-
     def plot_taxa_stats_pie(self, theme:str = 'Auto', res_type = 'pic', font_size = 12):
         df = self.tfa.BasicStats.get_stats_peptide_num_in_taxa()
 
@@ -361,8 +368,6 @@ def plot_corr_sns(
         theme: str = None,
         cmap: str = "Auto",
         rename_sample: bool = False,
-        linkage_method: str = "average",
-        distance_metric: str = "euclidean",
     ):
         dft= df.copy()
         if rename_sample:
@@ -387,17 +392,29 @@ def plot_corr_sns(
             sns_params = {"linewidths":.01, "cmap":cmap, "cbar_kws":{ "shrink": 0.5},
                             'col_cluster':True if cluster else False,
                             'row_cluster':True if cluster else False,
-                            'method':linkage_method,
-                            'metric':distance_metric,
+                            'method':self.linkage_method,
+                            'metric':self.distance_metric,
                             "linecolor":(0/255, 0/255, 0/255, 0.01), "dendrogram_ratio":(.1, .2),"col_colors":color_list,
                             "figsize":(width, height), "xticklabels":True if show_all_labels[0] else "auto",
                             "yticklabels":True if show_all_labels[1] else 'auto'}
             fig = sns.clustermap(corr, **sns_params)
-
-            fig.ax_col_dendrogram.set_title(f'Correlation of {title_name}', fontsize=font_size+2, fontweight='bold')
             ax = fig.ax_heatmap
-            ax.set_xticklabels(ax.get_xticklabels(), fontsize=font_size, rotation=90)
-            ax.set_yticklabels(ax.get_yticklabels(), fontsize=font_size, rotation=0)
+
+            fig.ax_heatmap.set_xticklabels(
+                fig.ax_heatmap.get_xmajorticklabels(),
+                fontsize=font_size,
+                rotation=self.x_labels_rotation,
+                ha = self.get_x_labels_ha()
+            )
+            fig.ax_heatmap.set_yticklabels(
+                fig.ax_heatmap.get_ymajorticklabels(),
+                fontsize=font_size,
+                rotation=self.y_labels_rotation,
+                ha = 'left',
+                va = self.get_y_labels_va()
+            )
+
+            fig.ax_col_dendrogram.set_title(f'Correlation of {title_name}', fontsize=font_size+2, fontweight='bold')
 
             cbar = fig.ax_heatmap.collections[0].colorbar
             cbar.set_label('Intensity', rotation=90, labelpad=1)
@@ -594,8 +611,6 @@ def plot_items_corr_heatmap(
         height=8,
         font_size=10,
         show_all_labels=(False, False),
-        linkage_method: str = "average",
-        distance_metric: str = "euclidean",
     ):
         corr = df.copy()
         # mask = np.triu(np.ones_like(corr, dtype=bool))
@@ -609,17 +624,33 @@ def plot_items_corr_heatmap(
             sns_params = {"linewidths":.01, "cmap":cmap, "cbar_kws":{ "shrink": 0.5},
                             'col_cluster':True if cluster else False,
                             'row_cluster':True if cluster else False,
-                            'method':linkage_method,
-                            'metric':distance_metric,
+                            'method':self.linkage_method,
+                            'metric':self.distance_metric,
                             "linecolor":(0/255, 0/255, 0/255, 0.01), "dendrogram_ratio":(.1, .2),
                             "figsize":(width, height), "xticklabels":True if show_all_labels[0] else "auto",
                             "yticklabels":True if show_all_labels[1] else 'auto'}
             fig = sns.clustermap(corr, **sns_params)
-
-            fig.ax_col_dendrogram.set_title(f'Correlation of {title_name}', fontsize=font_size+2, fontweight='bold')
             ax = fig.ax_heatmap
-            ax.set_xticklabels(ax.get_xticklabels(), fontsize=font_size, rotation=90)
-            ax.set_yticklabels(ax.get_yticklabels(), fontsize=font_size, rotation=0)
+
+
+            fig.ax_col_dendrogram.set_title(f'Correlation of {title_name}', fontsize=font_size+2, fontweight='bold')
+            fig.ax_heatmap.set_xticklabels(
+                fig.ax_heatmap.get_xmajorticklabels(),
+                fontsize=font_size,
+                rotation=self.x_labels_rotation,
+                ha = self.get_x_labels_ha()
+            )
+            fig.ax_heatmap.set_yticklabels(
+                fig.ax_heatmap.get_ymajorticklabels(),
+                fontsize=font_size,
+                rotation=self.y_labels_rotation,
+                ha = 'left',
+                va = self.get_y_labels_va()
+            )
+
+            # hiend the x and y labels
+            fig.ax_heatmap.set_xlabel('')
+            fig.ax_heatmap.set_ylabel('')
 
             cbar = fig.ax_heatmap.collections[0].colorbar
             cbar.set_label("Correlation", rotation=90, labelpad=1)
@@ -634,3 +665,19 @@ def plot_items_corr_heatmap(
         except Exception as e:
             plt.close('all')
             raise e
+
+
+    def get_x_labels_ha(self):
+        x_rotation = self.x_labels_rotation
+        if x_rotation > 0:
+            return 'right'
+        elif x_rotation < 0:
+            return 'left'
+        else:
+            return 'center'
+    def get_y_labels_va(self):
+        y_rotation = self.y_labels_rotation
+        if y_rotation >= 0:
+            return 'baseline'
+        else:
+            return 'top'

metax/utils/version.py

@@ -1,2 +1,2 @@
-__version__ = '1.111.6'
+__version__ = '1.111.7'
 API_version = '2'

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "MetaXTools"
-version = "1.111.6"
+version = "1.111.7"
 description = "MetaXTools is a novel tool for linking peptide sequences with taxonomic and functional information in Metaproteomics."
 readme = "README_PyPi.md"
 license = { text = "NorthOmics" }