Development

.bumpversion.cfg

@@ -0,0 +1,30 @@
+[bumpversion]
+current_version = 1.2.0
+commit = True
+tag = False
+parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<build>\d+))?
+serialize = 
+	{major}.{minor}.{patch}
+	{major}.{minor}.{patch}
+
+[bumpversion:part:release]
+
+[bumpversion:part:build]
+
+[bumpversion:file:./alphaviz/__init__.py]
+
+[bumpversion:file:./release/one_click_linux_gui/control]
+
+[bumpversion:file:./release/one_click_linux_gui/create_installer_linux.sh]
+
+[bumpversion:file:./release/one_click_macos_gui/distribution.xml]
+
+[bumpversion:file:./release/one_click_macos_gui/Info.plist]
+
+[bumpversion:file:./release/one_click_macos_gui/create_installer_macos.sh]
+
+[bumpversion:file:./release/one_click_windows_gui/create_installer_windows.sh]
+
+[bumpversion:file:./release/one_click_windows_gui/alphaviz_innoinstaller.iss]
+search = {current_version}
+replace = {new_version}

alphaviz/__init__.py

@@ -1,7 +1,7 @@
 #!python
 
 __project__ = "alphaviz"
-__version__ = "1.1.15"
+__version__ = "1.2.0"
 __license__ = "Apache"
 __description__ = "A interactive Dashboard to explore mass spectrometry data."
 __author__ = "Eugenia Voytik"

alphaviz/gui.py

@@ -541,10 +541,9 @@ def load_data(self, *args):
                 self.psm_df['instrument'] = 'timsTOF'
                 # trained on more Lumos files therefore should work better
                 # than 'timsTOF'
-                self.psm_df['spec_idx'] += 1
-                self.model_mgr.psm_num_to_tune_rt_ccs = 500
-                self.model_mgr.fine_tune_rt_model(self.psm_df)
-                # self.model_mgr.fine_tune_ccs_model(self.psm_df)
+                self.model_mgr.psm_num_to_train_rt_ccs = 500
+                self.model_mgr.train_rt_model(self.psm_df)
+                # self.model_mgr.train_ccs_model(self.psm_df)
 
         self.trigger_dependancy()
         self.upload_progress.active = False
@@ -2036,7 +2035,7 @@ def __init__(self, data, options):
             value=pd.DataFrame(
                 columns=['sequence', 'mods', 'mod_sites', 'charge']
             ),
-            hidden_columns=['frag_end_idx', 'frag_start_idx'],
+            hidden_columns=['frag_stop_idx', 'frag_start_idx'],
             widths={'index': 70},
             sizing_mode='stretch_width',
             layout='fit_data_table',
@@ -2382,7 +2381,7 @@ def run_prediction(self, *args):
                     print(f'cannot convert the column {col}')
             df.mod_sites = df.mod_sites.astype('str')
             df.mod_sites.replace('0', '', inplace=True)
-            df['nce'] = 30
+            df['nce'] = 30.0
             df['instrument'] = 'Lumos'
             self.predicted_dict = self.data.model_mgr.predict_all(
                 df,
@@ -2408,11 +2407,11 @@ def visualize_elution_plots_prediction(self, *args):
                         self.targeted_peptides_table_pred.value.loc[
                             self.targeted_peptides_table_pred.selection[0],
                             ['sequence', 'charge', 'precursor_mz',
-                                'rt_pred', 'mobility_pred', 'frag_start_idx', 'frag_end_idx']
+                                'rt_pred', 'mobility_pred', 'frag_start_idx', 'frag_stop_idx']
                         ].to_dict()
                     index_range = range(
                         self.peptide_prediction['frag_start_idx'],
-                        self.peptide_prediction['frag_end_idx']
+                        self.peptide_prediction['frag_stop_idx']
                     )
                     self.peptide_prediction['mz'] = \
                         self.peptide_prediction.pop('precursor_mz')
@@ -2476,7 +2475,7 @@ def visualize_elution_plots_prediction(self, *args):
                             align='center',
                             margin=(0, 10, 10, 10)
                         )
-                    except AttibuteError:
+                    except AttributeError:
                         self.layout_target_mode_predicted[2] = None
                     self.layout_target_mode_predicted[3] = self.export_svg_prediction_button
                     self.targeted_peptides_table_pred.loading = False

alphaviz/plotting.py

@@ -1220,7 +1220,7 @@ def plot_elution_profile_heatmap(
             )
     try:
         return common_plot.cols(n_cols)
-    except AttibuteError:
+    except AttributeError:
         return common_plot
 
 
@@ -1304,6 +1304,11 @@ def plot_elution_profile(
     title: str = "",
     # width: int = 900,
     height: int = 400,
+    hovermode:str = 'x unified',
+    theme_template:str = 'plotly_white',
+    include_precursor:bool = True,
+    include_ms1:bool = True,
+    row:int=None, col:int=None,
 ):
     """Plot an elution profile plot for the specified precursor and all
     his identified fragments.
@@ -1373,16 +1378,18 @@ def plot_elution_profile(
         'raw'
     ]
     fig = go.Figure()
-    fig.add_trace(
-        plot_elution_line(
-            raw_data,
-            precursor_indices,
-            remove_zeros=True,
-            # label=f"precursor ({round(peptide_info['mz'], 3)})",
-            label='precursor',
-            marker_color=dict(color=colors_set[0])
+    if include_precursor:
+        fig.add_trace(
+            plot_elution_line(
+                raw_data,
+                precursor_indices,
+                remove_zeros=True,
+                # label=f"precursor ({round(peptide_info['mz'], 3)})",
+                label='precursor',
+                marker_color=dict(color=colors_set[0])
+            ),
+            row=row, col=col
         )
-    )
     # create elution profiles for all fragments
     for ind, (frag, frag_mz) in enumerate(peptide_info['fragments'].items()):
         fragment_data_indices = raw_data[
@@ -1400,7 +1407,8 @@ def plot_elution_profile(
                     remove_zeros=True,
                     label=f"{frag} ({round(frag_mz, 3)})",
                     marker_color=dict(color=colors_set[ind+1])
-                )
+                ),
+                row=row, col=col
             )
 
     fig.update_layout(
@@ -1434,10 +1442,10 @@ def plot_elution_profile(
                 color='black'
             ),
         ),
-        template='plotly_white',
+        template=theme_template,
         # width=width,
         height=height,
-        hovermode='x unified',
+        hovermode=hovermode,
         showlegend=True
     )
     return fig