Merge pull request #82 from xomicsdatascience/dev

updated pyproject.toml version
xomicsdatascience · Jun 21, 2024 · 1ccd2e8 · 1ccd2e8
2 parents 4313beb + c05118e
commit 1ccd2e8
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Showing 6 changed files with 32 additions and 22 deletions.
diff --git a/pyproject.toml b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "zoDIAq"
-version = "2.0.0"
+version = "2.1.2"
 authors = [
   { name="Caleb Cranney", email="caleb.cranney.github@proton.me" },
 ]
@@ -22,7 +22,7 @@ dependencies = [
     'pyteomics>=4.4.1',
     'matplotlib>=3.3.4',
     'numba>=0.53.1',
-    'numpy>=1.20.1',
+    'numpy<2.0',
     'pandas>=1.2.2',
     'Bio>=0.4.1',
     'PyQt5>=5.15.4',

diff --git a/src/zodiaq/gui/windows/tabs/ScoringTabWindow.py b/src/zodiaq/gui/windows/tabs/ScoringTabWindow.py
@@ -18,9 +18,9 @@ def set_setting_layout(self, settingLayout):
     def set_args(self) -> list:
         args = ["score"]
         args.extend(self.get_arg_from_text_field_if_present(self.idOutputDir, "-i"))
-        args.extend(['-p', self.proteinQuantificationMethodComboBox.currentText()])
-        if self.proteinQuantificationMethodComboBox.currentText() == 'maxlfq':
-            args.extend(['-min', self.maxlfqMinNumMatchesComboBox.currentText()])
+        args.extend(["-p", self.proteinQuantificationMethodComboBox.currentText()])
+        if self.proteinQuantificationMethodComboBox.currentText() == "maxlfq":
+            args.extend(["-min", self.maxlfqMinNumMatchesComboBox.currentText()])
         return args
 
     def check_args_for_invalid_input(self, args):
@@ -49,16 +49,25 @@ def add_identification_output_directory_field(self, fileLayout):
         fileLayout.addRow(self.idOutputDir)
 
     def add_protein_quantification_method_combobox(self, settingLayout):
-        self.proteinQuantificationMethodText = QLabel("protein quantification method (if applicable):")
+        self.proteinQuantificationMethodText = QLabel(
+            "protein quantification method (if applicable):"
+        )
         self.proteinQuantificationMethodComboBox = QComboBox()
-        self.proteinQuantificationMethodComboBox.addItems(['maxlfq', 'sum'])
+        self.proteinQuantificationMethodComboBox.addItems(["maxlfq", "sum"])
 
-        self.maxlfqMinNumMatchesText = QLabel("minimum number of matching peptides between samples (only for 'maxlfq' method):")
+        self.maxlfqMinNumMatchesText = QLabel(
+            "minimum number of matching peptides between samples (only for 'maxlfq' method):"
+        )
         self.maxlfqMinNumMatchesComboBox = QComboBox()
-        self.maxlfqMinNumMatchesComboBox.addItems(['2', '1'])
+        self.maxlfqMinNumMatchesComboBox.addItems(["2", "1"])
 
-        settingLayout.addRow(self.proteinQuantificationMethodText, self.proteinQuantificationMethodComboBox)
-        settingLayout.addRow(self.maxlfqMinNumMatchesText, self.maxlfqMinNumMatchesComboBox)
+        settingLayout.addRow(
+            self.proteinQuantificationMethodText,
+            self.proteinQuantificationMethodComboBox,
+        )
+        settingLayout.addRow(
+            self.maxlfqMinNumMatchesText, self.maxlfqMinNumMatchesComboBox
+        )
 
     def add_no_setting_disclaimer_field(self, settingLayout):
         disclaimerText = QLabel("No settings currently implemented for the score step.")

diff --git a/src/zodiaq/identification/identifier.py b/src/zodiaq/identification/identifier.py
@@ -166,10 +166,11 @@ def _apply_correction_to_match_dataframe(self, matchDf):
             matchDf["ppmDifference"], self._commandLineArgs["correctionDegree"]
         )
         toleranceMinimumCutoff = 5
-        if not self._commandLineArgs["correctionDegree"] and tolerance < toleranceMinimumCutoff:
-            _, tolerance = calculate_ppm_offset_tolerance(
-                matchDf["ppmDifference"], 0.5
-            )
+        if (
+            not self._commandLineArgs["correctionDegree"]
+            and tolerance < toleranceMinimumCutoff
+        ):
+            _, tolerance = calculate_ppm_offset_tolerance(matchDf["ppmDifference"], 0.5)
         queryFile = self._queryContext.filePath.split("/")[-1]
         outFile = os.path.splitext(queryFile)[0] + "_correctionHistogram.png"
         if self._commandLineArgs["histogram"]:

diff --git a/src/zodiaq/scoring/idpickerFunctions.py b/src/zodiaq/scoring/idpickerFunctions.py
@@ -219,9 +219,9 @@ def reduce__identify_minimum_number_of_most_connected_proteins(
     """
     leadingProteins = set()
     for _, clusterDf in peptideProteinConnectionsDf.groupby("cluster"):
-        clusterDf[
-            "originalProteinCount"
-        ] = label_proteins_by_original_protein_count_for_breaking_ties(clusterDf)
+        clusterDf["originalProteinCount"] = (
+            label_proteins_by_original_protein_count_for_breaking_ties(clusterDf)
+        )
         (
             sortedClusterDf,
             initialAcceptedProteins,

diff --git a/tests/system/system_tests/scoring/testFileContentCreators/MaccScoresBreakdown.py b/tests/system/system_tests/scoring/testFileContentCreators/MaccScoresBreakdown.py
@@ -97,9 +97,9 @@ def _make_expected_protein_output(self, peptideDf):
         proteinDf = peptideDf.copy()
         proteinDf = proteinDf.reindex(list(proteinDf.index) + [1]).sort_index()
         leadingProteins = list(proteinDf["protein"])
-        leadingProteins[
-            : len(self.idPickerLeadingProteins)
-        ] = self.idPickerLeadingProteins
+        leadingProteins[: len(self.idPickerLeadingProteins)] = (
+            self.idPickerLeadingProteins
+        )
         proteinDf["leadingProtein"] = leadingProteins
         proteinDf["proteinCosine"] = proteinDf["cosine"]
         numUniqueLeadingProteins = len(set(self.idPickerLeadingProteins))

diff --git a/tests/unit/identification/test_outputFormattingFunctions.py b/tests/unit/identification/test_outputFormattingFunctions.py
@@ -48,7 +48,7 @@ def test__output_formatting_functions__format_output_line(identifierOutputData):
         "peaksCount": 5,
         "CV": 6,
         "windowWidth": 7,
-        "retentionTime":12,
+        "retentionTime": 12,
     }
     matchDict = {
         "cosineSimilarityScore": 8,