From f31302847c2aeb5df159322c682c64298e2e55f0 Mon Sep 17 00:00:00 2001 From: Qing <44231502+byemaxx@users.noreply.github.com> Date: Tue, 26 Nov 2024 13:57:32 -0500 Subject: [PATCH] - Fix: Resolved an issue where the option to rename sample names did not work when plotting the heatmap. - Change: Refactored the code to comply with PEP standards. --- Docs/ChangeLog.md | 7 ++ metax/gui/main_gui.py | 110 +++++++++--------- .../analyzer_utils/basic_stats.py | 2 +- metax/taxafunc_ploter/heatmap_plot.py | 6 +- metax/taxafunc_ploter/network_plot.py | 2 +- metax/utils/version.py | 2 +- pyproject.toml | 2 +- 7 files changed, 68 insertions(+), 63 deletions(-) diff --git a/Docs/ChangeLog.md b/Docs/ChangeLog.md index d21732d..8f99a51 100644 --- a/Docs/ChangeLog.md +++ b/Docs/ChangeLog.md @@ -1,3 +1,10 @@ +# Version: 1.118.4 +## Date: 2024-11-26 +### Changes: +- Fix: Resolved an issue where the option to rename sample names did not work when plotting the heatmap. +- Change: Refactored the code to comply with PEP standards. + + # Version: 1.118.3 ## Date: 2024-11-19 ### Changes: diff --git a/metax/gui/main_gui.py b/metax/gui/main_gui.py index cf0a19f..78d3b80 100644 --- a/metax/gui/main_gui.py +++ b/metax/gui/main_gui.py @@ -38,11 +38,10 @@ # import pyqt5 scripts from PyQt5 import QtWidgets, QtCore from PyQt5.QtWidgets import QFileDialog, QMessageBox, QTableWidgetItem -from PyQt5.QtWidgets import QApplication, QDesktopWidget, QListWidget, QListWidgetItem,QPushButton +from PyQt5.QtWidgets import QApplication, QListWidget, QListWidgetItem,QPushButton from PyQt5.QtWidgets import QDialog, QVBoxLayout, QTextBrowser from PyQt5.QtGui import QIcon, QCursor from PyQt5.QtCore import Qt, QTimer, QDir, QSettings -from PyQt5.QtWidgets import QToolBox, QGroupBox import qtawesome as qta # from qt_material import apply_stylesheet @@ -579,7 +578,7 @@ def get_table_by_df_type(self, df_type:str | None = None, dft = self.tfa.replace_if_two_index(dft) return dft - def get_list_by_df_type(self, df_type:str, remove_no_linked:bool=False, silent:bool=False) -> list|None: + def get_list_by_df_type(self, df_type:str, remove_no_linked:bool=False, silent:bool=False) -> list: ''' return the list of df_type, ignore capital case df_type: str, one of ['taxa', 'functions', 'taxa-functions', 'peptides', 'proteins', 'custom'] @@ -705,7 +704,7 @@ def change_event_comboBox_condition_group(comboBox, group_name): getattr(self, group_name).unselectAll() # unselect all items # select 1st item getattr(self, group_name).select_first() - except: + except Exception: pass except Exception as e: print(e) @@ -1761,7 +1760,7 @@ def run_db_builder(self): parm_kwargs = {'save_path': save_path, 'db_type': db_type, 'meta_path': meta_path, 'mgyg_dir': mgyg_dir, 'db_name': db_name} self.run_in_new_window(download_and_build_database, show_msg=True, **parm_kwargs) - except Exception as e: + except Exception: error_message = traceback.format_exc() QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2019,7 +2018,7 @@ def run_db_builder_own_table(self): parm_kwargs = {'anno_path': anno_path, 'taxa_path': taxa_path, 'db_path': save_path} self.run_in_new_window(build_db, show_msg=True,**parm_kwargs) - except Exception as e: + except Exception: error_message = traceback.format_exc() QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2064,7 +2063,7 @@ def run_db_updater(self): self.run_in_new_window(run_db_update, show_msg=True,**parm_kwargs) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'Error when run_db_updater: {error_message}', 'e') QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2138,7 +2137,7 @@ def metalab_main_wrapper(): return instance.main() self.run_in_new_window(metalab_main_wrapper, show_msg=True) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'Error when run_metalab_maxq_annotate: {error_message}', 'e') QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2359,7 +2358,7 @@ def set_taxaFuncAnalyzer(self): self.callback_after_set_taxafunc(self.tfa, True) - except: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'set_taxaFuncAnalyzer error: {error_message}', 'e') if "The OTF data must have Taxon_prop column!" in error_message: @@ -2550,7 +2549,7 @@ def update_GUI_after_tfobj(self): # go to original table tab self.tabWidget_TaxaFuncAnalyzer.setCurrentIndex(1) - except: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'update_after_tfobj error: {error_message}', 'e') QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2760,7 +2759,7 @@ def callback_after_set_multi_tables(result, success): # callback_after_set_multi_tables() - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'set_multi_table: {str(error_message)}', 'e') QMessageBox.warning(self.MainWindow, 'Error', error_message) @@ -2886,7 +2885,7 @@ def update_in_condition_combobox(self): for layout, combobox_name in combobox_layout_dict.items(): try: layout.itemAt(0).widget().deleteLater() - except Exception as e: + except Exception: pass new_combobox = CheckableComboBox() setattr(self, combobox_name, new_combobox) @@ -2921,7 +2920,7 @@ def enable_combobox_by_checkbox(checkbox, combobox_name): def update_group_and_sample_combobox(self, meta_name = None, update_group_list = True, update_sample_list = True): - if meta_name == None: + if meta_name is None: meta_name = self.tfa.meta_df.columns.tolist()[1] # set group list @@ -2966,7 +2965,7 @@ def update_group_and_sample_combobox(self, meta_name = None, update_group_list = for layout, combobox_name in group_layout_dict.items(): try: layout.itemAt(0).widget().deleteLater() - except Exception as e: + except Exception: pass new_combobox = CheckableComboBox() setattr(self, combobox_name, new_combobox) # Assign to the attribute @@ -2977,7 +2976,7 @@ def update_group_and_sample_combobox(self, meta_name = None, update_group_list = for layout, combobox_name in sample_layout_dict.items(): try: layout.itemAt(0).widget().deleteLater() - except Exception as e: + except Exception: pass new_combobox = CheckableComboBox(meta_df = self.tfa.meta_df) setattr(self, combobox_name, new_combobox) # Assign to the attribute @@ -3500,13 +3499,13 @@ def update_co_expr_list(self, str_selected=None, str_list=None): if str_selected == '': return None elif str_selected not in self.get_list_by_df_type(df_type): - QMessageBox.warning(self.MainWindow, 'Warning', f'Please select a valid item!') + QMessageBox.warning(self.MainWindow, 'Warning', 'Please select a valid item!') elif str_selected not in self.co_expr_focus_list: self.co_expr_focus_list.append(str_selected) self.listWidget_co_expr_focus_list.clear() self.listWidget_co_expr_focus_list.addItems(self.co_expr_focus_list) else: - QMessageBox.warning(self.MainWindow, 'Warning', f'This item has been added!') + QMessageBox.warning(self.MainWindow, 'Warning', 'This item has been added!') elif str_list is not None and str_selected is None: for i in str_list: if i not in self.co_expr_focus_list: @@ -3639,8 +3638,9 @@ def plot_basic_list(self, plot_type='heatmap'): try: if plot_type == 'heatmap': - df, sample_to_group_dict = self.tfa.BasicStats.get_df_by_mean_and_submeta(df = df, + df, sample_to_group_dict = self.tfa.BasicStats.prepare_dataframe_for_heatmap(df = df, sub_meta = sub_meta, + rename_sample = rename_sample, plot_mean = plot_mean) if row_cluster or (scale =='row'): df = self.delete_zero_rows(df) @@ -3693,7 +3693,7 @@ def plot_basic_list(self, plot_type='heatmap'): self.save_and_show_js_plot(pic, title) else: - ax = BarPlot(self.tfa, theme=self.html_theme).plot_intensity_bar_sns(df = df, width=width, height=height, + ax = BarPlot(self.tfa, theme=self.html_theme).plot_intensity_bar_sns(df = df, width=width, height=height, # noqa: F841 title= '', rename_taxa=rename_taxa, show_legend=show_legend, font_size=font_size, rename_sample=rename_sample, plot_mean = plot_mean, @@ -3735,7 +3735,7 @@ def plot_basic_list(self, plot_type='heatmap'): show_legend=self.checkBox_basic_bar_show_legend.isChecked()) self.save_and_show_js_plot(pic, title) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_basic_list error: {error_message}', 'e') self.logger.write_log(f'plot_basic_list: plot_type: {plot_type}, table_name: {table_name}, sample_list: {sample_list}, width: {width}, height: {height}, scale: {scale}, cmap: {cmap}, row_cluster: {row_cluster}, col_cluster: {col_cluster}, rename_taxa: {rename_taxa}', 'e') @@ -3946,7 +3946,7 @@ def plot_trends_cluster(self): self.pushButton_trends_get_trends_table.setEnabled(True) self.pushButton_trends_plot_interactive_line.setEnabled(True) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_trends_cluster error: {error_message}', 'e') self.logger.write_log(f'plot_trends_cluster: table_name: {table_name}, num_cluster: {num_cluster}, width: {width}, height: {height}, title: {title}, sample_list: {sample_list}, group_list: {group_list}, df: {df.shape}', 'e') @@ -3974,9 +3974,9 @@ def plot_trends_interactive_line(self): try: df = self.table_dict[save_table_name].copy() df = df[df['Cluster'] == cluster_num].drop('Cluster', axis=1) - self.show_message(f'Plotting interactive line plot...') - except: - QMessageBox.warning(self.MainWindow, 'Error', f'Please plot trends cluster first!') + self.show_message('Plotting interactive line plot...') + except Exception: + QMessageBox.warning(self.MainWindow, 'Error', 'Please plot trends cluster first!') return None if plot_samples or get_intensity: @@ -4005,19 +4005,19 @@ def plot_trends_interactive_line(self): extract_row = df.index.tolist() # extract_col = df.columns.tolist() extract_col = sample_list - df = dft.loc[extract_row, extract_col] + df = dft.loc[extract_row, extract_col] # type: ignore else: dft = self.tfa.BasicStats.get_stats_mean_df_by_group(dft, condition=condition) extract_row = df.index.tolist() # extract_col = df.columns.tolist() extract_col = group_list - df = dft.loc[extract_row, extract_col] + df = dft.loc[extract_row, extract_col] # type: ignore else: # plot_samples and not get_intensity dft = dft[sample_list] extract_row = df.index.tolist() # extract_col = df.columns.tolist() extract_col = sample_list - df = dft.loc[extract_row, extract_col] + df = dft.loc[extract_row, extract_col] # type: ignore try: @@ -4025,7 +4025,7 @@ def plot_trends_interactive_line(self): rename_taxa=rename_taxa, show_legend=show_legend, add_group_name = plot_samples, font_size=font_size) self.save_and_show_js_plot(pic, f'Cluster {cluster_num+1} of {table_name}') - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_trends_interactive_line error: {error_message}', 'e') self.logger.write_log(f'plot_trends_interactive_line: cluster_num: {cluster_num}, width: {width}, height: {height}, table_name: {table_name}, title: {title}, get_intensity: {get_intensity}, show_legend: {show_legend}, rename_taxa: {rename_taxa}, plot_samples: {plot_samples}', 'e') @@ -4046,8 +4046,8 @@ def get_trends_cluster_table(self): try: df_cluster = self.table_dict[save_table_name].copy() df_cluster = df_cluster[df_cluster['Cluster'] == cluster_num].drop('Cluster', axis=1) - except: - QMessageBox.warning(self.MainWindow, 'Error', f'Please plot trends cluster first!') + except Exception: + QMessageBox.warning(self.MainWindow, 'Error', 'Please plot trends cluster first!') return None if get_intensity: @@ -4104,7 +4104,7 @@ def save_and_show_js_plot(self, pic, title, width=None, height=None): self.web_list.append(web) web.show() - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'save_and_show_js_plot error: {error_message}', 'e') QMessageBox.warning(self.MainWindow, 'Error', f'{error_message}') @@ -4432,7 +4432,7 @@ def get_title_by_table_name(self, table_name): show_label = show_label, rename_sample = rename_sample, legend_col_num=legend_col_num, sub_meta = sub_meta) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_basic_info_sns error: {error_message}', 'e') QMessageBox.warning(self.MainWindow, 'Error', f'{error_message}') @@ -4471,7 +4471,7 @@ def plot_top_heatmap(self): try: width = int(width) length = int(length) - except: + except Exception: width = None length = None @@ -4566,7 +4566,7 @@ def plot_top_heatmap(self): error_message = traceback.format_exc() self.logger.write_log(f'plot_top_heatmap error: {error_message}') self.logger.write_log(f'plot_top_heatmap: table_name: {table_name}, top_num: {top_num}, value_type: {value_type}, fig_size: {fig_size}, pvalue: {pvalue}, sort_by: {sort_by}, cmap: {cmap}, scale: {scale}', 'e') - if 'No significant' in error_message: + if 'No significant' in str(e): QMessageBox.warning(self.MainWindow, 'Warning', f'No significant results. \n\n{error_message}') else: QMessageBox.warning(self.MainWindow, 'Error', f'{error_message}') @@ -4644,11 +4644,11 @@ def get_top_cross_table(self): self.logger.write_log( f"get_top_cross_table: table_name: {table_name}, top_num: {top_num}, value_type: {value_type}, pvalue: {pvalue}, sort_by: {sort_by}", "e", ) - if "No significant" in error_message: + if "No significant" in str(e): QMessageBox.warning( self.MainWindow, "Warning", - f"No significant results.\n\n{error_message}", + f"No significant results.\n\n{e}", ) else: QMessageBox.warning(self.MainWindow, "Error", f"{error_message}") @@ -4662,7 +4662,7 @@ def get_top_cross_table(self): else: self.update_table_dict(f'Cross_Test[{table_name}]', df_top_cross) self.show_table(df_top_cross, title=f'Cross_Test[{table_name}]') - except Exception as e: + except Exception: error_message = traceback.format_exc() QMessageBox.warning(self.MainWindow, 'Erro', error_message) return None @@ -4702,7 +4702,7 @@ def anova_test(self): anova_params = {'group_list': group_list, 'df_type': df_type, 'condition': condition} self.run_in_new_window(self.tfa.CrossTest.get_stats_anova, callback= self.callback_after_anova_test, **anova_params) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'anova_test error: {error_message}', 'e') self.logger.write_log(f'anova_test: group_list: {group_list}, df_type: {df_type}', 'e') @@ -4719,7 +4719,7 @@ def callback_after_anova_test(self, result, success): if success: - if type(result) == pd.DataFrame: + if type(result) is pd.DataFrame: df_anova = result self.show_table(df_anova, title=f'anova_test({df_type})') @@ -4727,7 +4727,7 @@ def callback_after_anova_test(self, result, success): table_names = [table_name] self.update_table_dict(table_name, df_anova) - elif type(result) == tuple: + elif type(result) is tuple: df_tuple = result table_name_1 = 'NonSigTaxa_SigFuncs(taxa-functions)' self.show_table(df_tuple[0], title=table_name_1) @@ -4897,7 +4897,7 @@ def tukey_test(self): self.pushButton_tukey_test.setEnabled(False) self.run_in_new_window(self.tfa.CrossTest.get_stats_tukey_test, callback= self.callback_after_tukey_test, taxon_name=taxa, func_name=func, sum_all=sum_all, condition=condition) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'tukey_test error: {error_message}', 'e') self.logger.write_log(f'tukey_test: taxa: {taxa}, func: {func}', 'e') @@ -4942,7 +4942,7 @@ def t_test(self): try: self.pushButton_ttest.setEnabled(False) group_list = [group1, group2] - table_names = [] # reset table_names as empty list + table_names = [] # reset table_names as empty list # noqa: F841 if df_type == 'Significant Taxa-Func'.lower(): p_value = self.doubleSpinBox_top_heatmap_pvalue.value() p_value = round(p_value, 4) @@ -4962,7 +4962,7 @@ def t_test(self): if str(e) == 'sample size must be more than 1 for t-test': QMessageBox.warning(self.MainWindow, 'Warning', 'The sample size of each group must be more than 1 for T-TEST!') return None - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f't_test error: {error_message}', 'e') self.logger.write_log(f't_test: group_list: {group_list}, df_type: {df_type}', 'e') @@ -5110,7 +5110,7 @@ def plot_deseq2_volcano(self): if log2fc_min > log2fc_max: QMessageBox.warning(self.MainWindow, 'Error', 'log2fc_min must be less than log2fc_max!') return None - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_deseq2_volcano error: {error_message}', 'e') self.logger.write_log(f'plot_deseq2_volcano: table_name: {table_name}, log2fc_min: {log2fc_min}, log2fc_max: {log2fc_max}, pvalue: {pvalue}, width: {width}, height: {height}, group1: {group1}, group2: {group2}, title_name: {title_name}', 'e') @@ -5134,7 +5134,7 @@ def plot_deseq2_volcano(self): width=width, height=height, dot_size=dot_size, theme = theme) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_deseq2_volcano error: {error_message}', 'e') self.logger.write_log(f'plot_deseq2_volcano: table_name: {table_name}, log2fc_min: {log2fc_min}, log2fc_max: {log2fc_max}, pvalue: {pvalue}, width: {width}, height: {height}, group1: {group1}, group2: {group2}, title_name: {title_name}', 'e') @@ -5199,7 +5199,7 @@ def plot_co_expr(self, plot_type = 'network'): show_all_labels=show_all_labels ) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_co_expr_heatmap error: {error_message}', 'e') self.logger.write_log(f'plot_co_expr_heatmap: df_type: {df_type}, corr_method: {corr_method}, corr_threshold: {corr_threshold}, width: {width}, height: {height}, focus_list: {focus_list}', 'e') @@ -5226,7 +5226,7 @@ def plot_co_expr(self, plot_type = 'network'): except ValueError as e: if 'sample_list should have at least 2' in str(e): QMessageBox.warning(self.MainWindow, 'Error', "At least 2 samples are required!") - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_co_expr_network error: {error_message}', 'e') self.logger.write_log(f'plot_co_expr_network: df_type: {df_type}, corr_method: {corr_method}, corr_threshold: {corr_threshold}, width: {width}, height: {height}, focus_list: {focus_list}', 'e') @@ -5472,7 +5472,7 @@ def plot_network(self): self.update_table_dict('taxa-func_network', network_df) self.update_table_dict('taxa-func_network_attributes', attributes_df) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_network error: {error_message}', 'e') self.logger.write_log(f'plot_network: sample_list:{sample_list}, focus_list:{focus_list}, plot_list_only:{plot_list_only}', 'e') @@ -5497,11 +5497,8 @@ def get_sample_list_tflink(self): sample_list = selected_samples return sample_list - def remove_no_linked_taxa_and_func_after_filter_tflink(self, check_list:list | None = None, type:str = 'taxa', silent:bool = False) -> list[str] | None: + def remove_no_linked_taxa_and_func_after_filter_tflink(self, check_list:list, type:str = 'taxa', silent:bool = False) -> list[str]: # keep taxa and func only in the taxa_func_linked_dict and remove others - if check_list is None: - print(f'check_list is {check_list}, return None') - return None if type == 'taxa' or type == 'functions': if type == 'taxa': @@ -5608,9 +5605,10 @@ def plot_tflink_heatmap(self, return_type = 'fig'): QMessageBox.warning(self.MainWindow, 'Warning', 'No data!, please reselect!') return None - df, sample_to_group_dict = self.tfa.BasicStats.get_df_by_mean_and_submeta(df = df, - sub_meta = sub_meta, - plot_mean = plot_mean) + df, sample_to_group_dict = self.tfa.BasicStats.prepare_dataframe_for_heatmap(df = df, + sub_meta = sub_meta, + rename_sample = rename_sample, + plot_mean = plot_mean) if row_cluster or (scale == 'row'): df = self.delete_zero_rows(df) @@ -5628,7 +5626,7 @@ def plot_tflink_heatmap(self, return_type = 'fig'): if return_type == 'table': self.show_table(fig_res, title=title.replace('\n', '-')) - except Exception as e: + except Exception: error_message = traceback.format_exc() self.logger.write_log(f'plot_others_heatmap error: {error_message}', 'e') self.logger.write_log(f'plot_others_heatmap: {params}', 'e') diff --git a/metax/taxafunc_analyzer/analyzer_utils/basic_stats.py b/metax/taxafunc_analyzer/analyzer_utils/basic_stats.py index b0fda3f..9dda064 100644 --- a/metax/taxafunc_analyzer/analyzer_utils/basic_stats.py +++ b/metax/taxafunc_analyzer/analyzer_utils/basic_stats.py @@ -262,7 +262,7 @@ def shapiro_test(self, df: pd.DataFrame, alpha=0.05) : - def get_df_by_mean_and_submeta(self, df, sub_meta:str = 'None', rename_sample:bool = True, plot_mean:bool = False): + def prepare_dataframe_for_heatmap(self, df, sub_meta:str = 'None', rename_sample:bool = True, plot_mean:bool = False): """ Prepares a DataFrame for baisc heatmap plotting. Parameters: diff --git a/metax/taxafunc_ploter/heatmap_plot.py b/metax/taxafunc_ploter/heatmap_plot.py index 6a46d5f..ce8205e 100644 --- a/metax/taxafunc_ploter/heatmap_plot.py +++ b/metax/taxafunc_ploter/heatmap_plot.py @@ -552,7 +552,7 @@ def plot_heatmap_of_all_condition_res(self, df, pvalue:float = 0.05,scale:str|N dft = self.scale_data(df = dft, scale_by = scale, method = scale_method) if cmap is None: - cmap = sns.color_palette("vlag", as_cmap=True, n_colors=30) + cmap = sns.color_palette("vlag", as_cmap=True, n_colors=30) # type: ignore # 标准化颜色映射以使 0 处为白色 from matplotlib.colors import TwoSlopeNorm @@ -695,7 +695,7 @@ def plot_heatmap_of_dunnett_test_res(self, df, pvalue:float = 0.05,scale:str|No if cmap is None: - cmap = sns.color_palette("vlag", as_cmap=True, n_colors=30) + cmap = sns.color_palette("vlag", as_cmap=True, n_colors=30) # type: ignore col_colors = self.get_distinct_colors(len(dft.columns)) # 标准化颜色映射以使 0 处为白色 @@ -868,7 +868,7 @@ def scale_data(self, df: pd.DataFrame, scale_by: str|None = None, method: str|No else: # 'maxmin' if scale_by == 'row': max_val = df.abs().max(axis=1) - df = pd.DataFrame([row / max_val.loc[index] if max_val.loc[index] != 0 else row for index, row in df.iterrows()], index=df.index, columns=df.columns) + df = pd.DataFrame([row / max_val.loc[index] if max_val.loc[index] != 0 else row for index, row in df.iterrows()], index=df.index, columns=df.columns) # type: ignore elif scale_by == 'col': max_val = df.abs().max() for col in df.columns: diff --git a/metax/taxafunc_ploter/network_plot.py b/metax/taxafunc_ploter/network_plot.py index 9c24810..55ce89e 100644 --- a/metax/taxafunc_ploter/network_plot.py +++ b/metax/taxafunc_ploter/network_plot.py @@ -258,7 +258,7 @@ def plot_tflink_network( focus_list: list = None, plot_list_only: bool = False, list_only_no_link: bool = False, - ) -> Tuple[Graph, pd.DataFrame]: + ) -> Tuple[Graph, pd.DataFrame, pd.DataFrame]: """ Creates a network graph of taxa and functions using Pyecharts. diff --git a/metax/utils/version.py b/metax/utils/version.py index 3db4266..be738a0 100644 --- a/metax/utils/version.py +++ b/metax/utils/version.py @@ -1,2 +1,2 @@ -__version__ = '1.118.3' +__version__ = '1.118.4' API_version = '3' \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 210fb39..f93cf8a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "MetaXTools" -version = "1.118.3" +version = "1.118.4" description = "MetaXTools is a novel tool for linking peptide sequences with taxonomic and functional information in Metaproteomics." readme = "README_PyPi.md" license = { text = "NorthOmics" }