Merge branch 'dev'

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:

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:

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:

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.
 

metax/utils/version.py

@@ -1,2 +1,2 @@
-__version__ = '1.118.3'
+__version__ = '1.118.4'
 API_version = '3'

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" }