Merge branch 'master' into 182_precursor_request_patch

Author: kheal

corems/__init__.py

@@ -21,19 +21,22 @@
 
 
 
-def timeit(method):
-    def timed(*args, **kw):
-        ts = time.time()
-        result = method(*args, **kw)
-        te = time.time()
-        if "log_time" in kw:
-            name = kw.get("log_name", method.__name__.upper())
-            kw["log_time"][name] = int((te - ts) * 1000)
-        else:
-            print("%r  %2.2f ms" % (method.__name__, (te - ts) * 1000))
-        return result
-
-    return timed
+def timeit(print_time=True):
+    def decorator(method):
+        def timed(*args, **kw):
+            # Extract print_time from kwargs if provided
+            local_print_time = kw.pop('print_time', print_time)
+            ts = time.time()
+            result = method(*args, **kw)
+            te = time.time()
+            if "log_time" in kw:
+                name = kw.get("log_name", method.__name__.upper())
+                kw["log_time"][name] = int((te - ts) * 1000)
+            elif local_print_time:
+                print("%r  %2.2f ms" % (method.__name__, (te - ts) * 1000))
+            return result
+        return timed
+    return decorator
 
 
 class SuppressPrints:

corems/encapsulation/factory/parameters.py

@@ -13,6 +13,12 @@
 )
 from corems.encapsulation.factory.processingSetting import DataInputSetting
 
+def hush_output():
+    """Toggle all the verbose_processing flags to False on the MSParameters, GCMSParameters and LCMSParameters classes"""
+    MSParameters.molecular_search.verbose_processing = False
+    MSParameters.mass_spectrum.verbose_processing = False
+    GCMSParameters.gc_ms.verbose_processing = False
+    LCMSParameters.lc_ms.verbose_processing = False
 
 def reset_ms_parameters():
     """Reset the MSParameter class to the default values"""

corems/encapsulation/factory/processingSetting.py

@@ -816,7 +816,10 @@ class MolecularFormulaSearchSettings:
         m/z error average. Default is 0.0.
     used_atom_valences : dict, optional
         Dictionary of atoms and valences. Default is {'C': 4, '13C': 4, 'H': 1, 'O': 2, '18O': 2, 'N': 3, 'S': 2, '34S': 2, 'P': 3, 'Cl': 1, '37Cl': 1, 'Br': 1, 'Na': 1, 'F': 1, 'K': 0}.
+    verbose_processing: bool, optional
+        If True, print verbose processing information. Default is True.
     """
+    verbose_processing: bool = True    
 
     use_isotopologue_filter: bool = False
 

corems/mass_spectra/factory/GC_Class.py

@@ -201,6 +201,18 @@ def set_scans_number_from_data(self):
 
         self.scans_number = sorted(self._ms.keys())
 
+    @property
+    def parameters(self):
+        """GCMS Parameters"""
+        return self._parameters
+
+    @parameters.setter
+    def parameters(self, gcms_parameters_instance):
+        self._parameters = gcms_parameters_instance
+
+    # Note: maintaining `parameter` for backwards compatibility,
+    # but proper usage would reference `parameters` to conform
+    # to other classes.
     @property
     def parameter(self):
         """GCMS Parameters"""
@@ -213,20 +225,20 @@ def parameter(self, gcms_parameters_instance):
     @property
     def molecular_search_settings(self):
         """Molecular Search Settings"""
-        return self.parameter.molecular_search
+        return self.parameters.molecular_search
 
     @molecular_search_settings.setter
     def molecular_search_settings(self, settings_class_instance):
-        self.parameter.molecular_search = settings_class_instance
+        self.parameters.molecular_search = settings_class_instance
 
     @property
     def chromatogram_settings(self):
         """Chromatogram Settings"""
-        return self.parameter.gc_ms
+        return self.parameters.gc_ms
 
     @chromatogram_settings.setter
     def chromatogram_settings(self, settings_class_instance):
-        self.parameter.gc_ms = settings_class_instance
+        self.parameters.gc_ms = settings_class_instance
 
     @property
     def scans_number(self):

corems/mass_spectrum/calc/Calibration.py

@@ -65,7 +65,7 @@ def __init__(self, mass_spectrum, ref_masslist, mzsegment=None):
 
         # define reference mass list - bruker .ref format
         self.ref_mass_list_path = ref_masslist
-        if self.mass_spectrum.percentile_assigned()[0] != 0:
+        if self.mass_spectrum.percentile_assigned(mute_output=True)[0] != 0:
             warnings.warn(
                 "Warning: calibrating spectra which have already been assigned may yield erroneous results"
             )
@@ -77,10 +77,6 @@ def __init__(self, mass_spectrum, ref_masslist, mzsegment=None):
                 "MS Obj loaded - " + str(len(mass_spectrum.mspeaks)) + " peaks found."
             )
 
-            print(
-                "MS Obj loaded - " + str(len(mass_spectrum.mspeaks)) + " peaks found."
-            )
-
     def load_ref_mass_list(self):
         """Load reference mass list (Bruker format)
 
@@ -228,7 +224,7 @@ def find_calibration_points(
             cal_peaks_mz = list(tmpdf.values)
             cal_refs_mz = list(tmpdf.index)
         elif calibration_ref_match_method == "merged":
-            warnings.warn("Using experimental new reference mass list merging")
+            #warnings.warn("Using experimental new reference mass list merging")
             # This is a new approach (August 2024) which uses Pandas 'merged_asof' to find the peaks closest in m/z between
             # reference and measured masses. This is a quicker way to match, and seems to get more matches.
             # It may not work as well when the data are far from correc initial mass

corems/mass_spectrum/calc/MassErrorPrediction.py

@@ -90,12 +90,12 @@ def get_results(self):
 
     def calc_error_dist(self):
         """Calculate the error distribution."""
+        verbose = self.mass_spectrum_obj.parameters.mass_spectrum.verbose_processing
         results_list = []
 
         indexes_without_results = list(range(len(self.mass_spectrum_obj)))
         # loop trough mass spectrum
-
-        for peak_obj_idx, peak_obj in enumerate(tqdm(self.mass_spectrum_obj)):
+        for peak_obj_idx, peak_obj in enumerate(tqdm(self.mass_spectrum_obj), disable=not verbose):
             # access ms peaks triplets ( peak_obj_idx -1, peak_obj_idx, and peak_obj_idx + 1)
             # check lower and upper boundaries to not excesses mass spectrum range
 

corems/mass_spectrum/calc/MassSpectrumCalc.py

@@ -38,13 +38,16 @@ class MassSpecCalc(PeakPicking, NoiseThresholdCalc):
         Calculate the weight average molecular weight
     """
 
-    def percentile_assigned(self, report_error: bool = False):
+    def percentile_assigned(self, report_error: bool = False, mute_output: bool = False):
         """Percentage of peaks which are assigned
 
         Parameters
         -----------
         report_error: bool, optional
             Report the error of the assigned peaks. Default is False.
+        mute_output: bool, optional
+            Override the verbose setting. Default is False.
+            If True, the function will silence results
         """
         verbose = self.parameters.mass_spectrum.verbose_processing
         assign_abun = 0
@@ -68,15 +71,15 @@ def percentile_assigned(self, report_error: bool = False):
         total_relative_abundance = (assign_abun / (not_assign_abun + assign_abun)) * 100
         if report_error:
             rms_error = sqrt(mean(array(error) ** 2))
-            if verbose:
+            if verbose and not mute_output:
                 print(
                     "%i assigned peaks and %i unassigned peaks, total  = %.2f %%, relative abundance = %.2f %%, RMS error (best candidate) (ppm) = %.3f"
                     % (i, j, total_percent, total_relative_abundance, rms_error)
                 )
             return i, j, total_percent, total_relative_abundance, rms_error
 
         else:
-            if verbose:
+            if verbose and not mute_output:
                 print(
                     "%i assigned peaks and %i unassigned peaks , total  = %.2f %%, relative abundance = %.2f %%"
                     % (

corems/mass_spectrum/input/massList.py

@@ -175,7 +175,7 @@ def add_molecular_formula(self, mass_spec_obj, dataframe):
                     # Next, generate isotopologues from the parent
                     isos = list(
                         mono_mfobj.isotopologues(
-                            min_abundance=mass_spec_obj[df_index].abundance * 0.001,
+                            min_abundance=mass_spec_obj.abundance.min()*0.01,
                             current_mono_abundance=mass_spec_obj[mono_index].abundance,
                             dynamic_range=mass_spec_obj.dynamic_range,
                         )

corems/molecular_id/factory/MolecularLookupTable.py

@@ -364,14 +364,17 @@ def add_carbonsHydrogens(self, settings, existing_classes_objs):
                     self.sql_db.session.execute(insert_query)
                 self.sql_db.session.commit()
 
-    @timeit
-    def runworker(self, molecular_search_settings):
+    @timeit(print_time=True)
+    def runworker(self, molecular_search_settings, **kwargs):
         """Run the molecular formula lookup table worker.
 
         Parameters
         ----------
         molecular_search_settings : object
             An object containing user-defined settings.
+        kwargs : dict
+            A dictionary of keyword arguments.
+            Most notably, the print_time argument which is passed to the timeit decorator.
 
         Returns
         -------
@@ -380,6 +383,7 @@ def runworker(self, molecular_search_settings):
 
 
         """
+        verbose = molecular_search_settings.verbose_processing
 
         classes_list, class_to_create, existing_classes_objs = (
             self.check_database_get_class_list(molecular_search_settings)
@@ -412,7 +416,7 @@ def runworker(self, molecular_search_settings):
             self.even_ch_dbe = [obj.dbe for obj in even_ch_obj]
 
             all_results = list()
-            for class_tuple in tqdm(class_to_create):
+            for class_tuple in tqdm(class_to_create, disable = not verbose):
                 results = self.populate_combinations(class_tuple, settings)
                 all_results.extend(results)
                 if settings.db_jobs == 1:
@@ -438,8 +442,8 @@ def runworker(self, molecular_search_settings):
                 ]
                 p = multiprocessing.Pool(settings.db_jobs)
                 for class_list in tqdm(
-                    p.imap_unordered(insert_database_worker, worker_args)
-                ):
+                        p.imap_unordered(insert_database_worker, worker_args), disable= not verbose
+                        ):
                     pass
                 p.close()
                 p.join()

corems/molecular_id/factory/molecularSQL.py

@@ -473,6 +473,7 @@ def get_dict_by_classes(
         if the number of classes and nominal_m/zs are higher than 999 the query will fail
         Solution: use postgres or split query
         """
+        verbose = molecular_search_settings.verbose_processing
 
         def query_normal(class_list, len_adduct):
             """query for normal database
@@ -565,10 +566,7 @@ def nominal_mass_by_ion_type(formula_obj):
 
                 elif ion_type == Labels.adduct_ion and adduct_atom:
                     return int(formula_obj._adduct_mz(ion_charge, adduct_atom))
-
-            for formula_obj, ch_obj, classe_obj in tqdm.tqdm(
-                formulas, desc="Loading molecular formula database"
-            ):
+            for formula_obj, ch_obj, classe_obj in tqdm.tqdm(formulas, desc="Loading molecular formula database", disable = not verbose):
                 nominal_mz = nominal_mass_by_ion_type(formula_obj)
 
                 if self.type != "normal":