Merge branch 'dev' of github.com:Roestlab/massseer into patch/ui_rena…

…me_results_peak_boundaries

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,32 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Steps to reproduce the behavior:
+1. Go to '...'
+2. Click on '....'
+3. Scroll down to '....'
+4. See error
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots**
+If applicable, add screenshots to help explain your problem.
+
+**Desktop (please complete the following information):**
+ - OS: [e.g. iOS]
+ - Browser [e.g. chrome, safari]
+ - Version [e.g. 22]
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,20 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.

.github/PULL_REQUEST_TEMPLATE/pull_request_template.md

@@ -0,0 +1,36 @@
+# Description
+
+Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change.
+
+Fixes # (issue)
+
+## Type of change
+
+Please delete options that are not relevant.
+
+- [ ] Bug fix (non-breaking change which fixes an issue)
+- [ ] New feature (non-breaking change which adds functionality)
+- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
+- [ ] This change requires a documentation update
+
+# How Has This Been Tested?
+
+Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
+
+- [ ] Test A
+- [ ] Test B
+
+**Test Configuration**:
+* Firmware version:
+* Hardware:
+
+# Checklist:
+
+- [ ] My code follows the style guidelines of this project
+- [ ] I have performed a self-review of my code
+- [ ] I have commented my code, particularly in hard-to-understand areas
+- [ ] I have made corresponding changes to the documentation
+- [ ] My changes generate no new warnings
+- [ ] I have added tests that prove my fix is effective or that my feature works
+- [ ] New and existing unit tests pass locally with my changes
+- [ ] Any dependent changes have been merged and published in downstream modules

.github/pull_request_template.md

@@ -0,0 +1,36 @@
+# Description
+
+Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change.
+
+Fixes # (issue)
+
+## Type of change
+
+Please delete options that are not relevant.
+
+- [ ] Bug fix (non-breaking change which fixes an issue)
+- [ ] New feature (non-breaking change which adds functionality)
+- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
+- [ ] This change requires a documentation update
+
+# How Has This Been Tested?
+
+Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
+
+- [ ] Test A
+- [ ] Test B
+
+**Test Configuration**:
+* Firmware version:
+* Hardware:
+
+# Checklist:
+
+- [ ] My code follows the style guidelines of this project
+- [ ] I have performed a self-review of my code
+- [ ] I have commented my code, particularly in hard-to-understand areas
+- [ ] I have made corresponding changes to the documentation
+- [ ] My changes generate no new warnings
+- [ ] I have added tests that prove my fix is effective or that my feature works
+- [ ] New and existing unit tests pass locally with my changes
+- [ ] Any dependent changes have been merged and published in downstream modules

.github/workflows/auto-pr-desc.yml

@@ -6,25 +6,25 @@
 
 name: generate-pull-request-description
 
-on:
-  workflow_call:
-    secrets:
-      token:
-        required: true
+on: [pull_request]
 
 jobs:
   update:
     if: ${{ !contains(github.event.pull_request.body, '<!--- SKIP AUTOGENERATED NOTES --->') }}
     runs-on: ubuntu-latest
     steps:
-      - uses: octue/[email protected]
+      # Step 1: Use an action to generate the pull request description
+      - name: Generate PR Description
+        uses: octue/generate-pull-request-description@main
         id: pr-description
         with:
           pull_request_url: ${{ github.event.pull_request.url }}
-          api_token: ${{ secrets.token }}
+          api_token: ${{ secrets.GITHUB_TOKEN }}
 
+      # Step 2: Update the pull request body using the generated description
       - name: Update pull request body
         uses: riskledger/update-pr-description@v2
         with:
           body: ${{ steps.pr-description.outputs.pull_request_description }}
-          token: ${{ secrets.token }}
+          token: ${{ secrets.GITHUB_TOKEN }}
+

docs/conf.py

@@ -1,3 +1,8 @@
+"""
+docs/conf
+~~~~~~~~~
+"""
+
 # Configuration file for the Sphinx documentation builder.
 #
 # This file only contains a selection of the most common options. For a full

docs/plottingGallery/Heatmap Per Transition.ipynb

@@ -41,7 +41,7 @@
     "tags": []
    },
    "source": [
-    "By changing the ``type_of_heatmap`` in the `:py:class:~massseer.plotting.PlotConfig`, we can plot different axis against one another."
+    "By changing the ``type_of_heatmap`` in the `:py:class:~massdash.plotting.PlotConfig`, we can plot different axis against one another."
    ]
   },
   {

docs/python_docs/Advanced Plotting.ipynb

@@ -90,7 +90,7 @@
     "tags": []
    },
    "source": [
-    "MassSeer is also capable of generating many different other plot types. Since these plots are more complex, plotting is more involved. "
+    "MassDash is also capable of generating many different other plot types. Since these plots are more complex, plotting is more involved. "
    ]
   },
   {
@@ -317,7 +317,7 @@
    },
    "outputs": [],
    "source": [
-    "from massseer.plotting import PlotConfig\n",
+    "from massdash.plotting import PlotConfig\n",
     "plotConfig = PlotConfig()\n",
     "plotConfig.include_ms1 = True\n",
     "plotConfig.include_ms2 = True\n",
@@ -353,7 +353,7 @@
    },
    "outputs": [],
    "source": [
-    "from massseer.plotting import InteractivePlotter\n",
+    "from massdash.plotting import InteractivePlotter\n",
     "plotter = InteractivePlotter(plotConfig)"
    ]
   },

docs/python_docs/Loading Data.rst

@@ -3,7 +3,7 @@ Loading Data
 
 .. currentmodule:: massdash.loaders
 
-To load raw data into MassSeer, a loader object must be initiated. There are two types of loader classes
+To load raw data into MassDash, a loader object must be initiated. There are two types of loader classes
 
 
 1. :py:class:`Chromatogram Loaders<GenericChromatogramLoader>`: Chromatogram Loaders: Raw data stores chromatograms, this allows for faster loading however since extraction has already been performed by the upstream analysis tool. This includes :py:class:`SqMassLoader`
@@ -25,5 +25,5 @@ Since each loader type is linked with a results file each loader can be used to
    Loading Spectrum Data
    Loading Feature Information
 
-Have an idea for a loader you want to see? Create a issue `here <https://github.com/Roestlab/massseer/issues>`_.
+Have an idea for a loader you want to see? Create a issue `here <https://github.com/Roestlab/massdash/issues>`_.
 

docs/python_docs/Quick Start.ipynb

@@ -133,7 +133,7 @@
     "tags": []
    },
    "source": [
-    "Since the .sqMass file does not contain any metadata, to link chromatograms with their corresponding peptide sequence we must link an ``.osw`` file with the ``.sqMass`` file. In MassSeer this is done by initiating a :py:class:`~loaders.SqMassLoader` as shown below.  "
+    "Since the .sqMass file does not contain any metadata, to link chromatograms with their corresponding peptide sequence we must link an ``.osw`` file with the ``.sqMass`` file. In MassDash this is done by initiating a :py:class:`~loaders.SqMassLoader` as shown below.  "
    ]
   },
   {

manuscript/main_figures/Figure-5-Peak-Picking-Demonstration.ipynb

@@ -424,7 +424,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from massseer.plotting import InteractivePlotter, PlotConfig\n",
+    "from massdash.plotting import InteractivePlotter, PlotConfig\n",
     "\n",
     "plotConfig = PlotConfig()\n",
     "plotConfig.smoothing_dict = dict(type='none')\n",

massdash/__init__.py

@@ -1,5 +1,4 @@
 """
-=======
 massdash
 ~~~~~~~~
 TODO: ADD general documentation about how to use the auto API here

massdash/constants.py

@@ -1,6 +1,6 @@
 """
 massdash/constants
-~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~
 """
 
 import os
@@ -23,4 +23,5 @@
 URL_TEST_OSW = "https://github.com/Roestlab/massdash/raw/dev/test/test_data/example_dia/openswath/osw/test.osw"
 URL_TEST_PQP = "https://github.com/Roestlab/massdash/raw/dev/test/test_data/example_dia/openswath/lib/test.pqp"
 URL_TEST_RAW_MZML = "https://github.com/Roestlab/massdash/raw/dev/test/test_data/example_dia/raw/test_raw_1.mzML"
-URL_TEST_DREAMDIA_REPORT = "https://github.com/Roestlab/massdash/raw/dev/test/test_data/example_dia/dreamdia/test_dreamdia_report.tsv"
+URL_TEST_DREAMDIA_REPORT = "https://github.com/Roestlab/massdash/raw/dev/test/test_data/example_dia/dreamdia/test_dreamdia_report.tsv"
+URL_PRETRAINED_CONFORMER = "https://github.com/Roestlab/massdash/releases/download/v0.0.1-alpha/base_cape.onnx"

massdash/loaders/GenericChromatogramLoader.py

@@ -1,3 +1,8 @@
+"""
+massdash/loaders/GenericChromatogramLoader
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+
 from abc import abstractmethod
 import pandas as pd 
 from typing import Dict, List, Union, Literal

massdash/loaders/GenericSpectrumLoader.py

@@ -1,4 +1,7 @@
 '''
+massdash/loaders/GenericSpectrumLoader
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
 This is an abstract class for loading spectra from a file.
 '''
 

massdash/loaders/SqMassLoader.py

@@ -81,7 +81,7 @@ def loadTransitionGroups(self, pep_id: str, charge: int) -> Dict[str, Transition
             prec_chrom_ids = t.getPrecursorChromIDs(precursor_id)
             precursor_chroms = t.getDataForChromatograms(prec_chrom_ids['chrom_ids'], prec_chrom_ids['native_ids'])
 
-            out[t] = TransitionGroup(precursor_chroms, transition_chroms)
+            out[t] = TransitionGroup(precursor_chroms, transition_chroms, pep_id, charge)
         return out
 
     def loadTransitionGroupFeaturesDf(self, pep_id: str, charge: int) -> pd.DataFrame:

massdash/loaders/__init__.py

@@ -1,5 +1,8 @@
 """
-The :mod:`massseer.loaders` subpackage contains the structures for loading data into MassSeer
+massdash/loaders
+~~~~~~~~~~~~~~~~
+
+The :mod:`massdash.loaders` subpackage contains the structures for loading data into MassDash
 """
 
 from .GenericChromatogramLoader import GenericChromatogramLoader

massdash/loaders/access/MzMLDataAccess.py

@@ -420,7 +420,7 @@ def msExperimentToFeatureMap(self, msExperiment: po.MSExperiment, feature: Trans
         else:
             LOGGER.warn(f"No spectra found for peptide: {feature.sequence}{feature.precursor_charge}. Try adjusting the extraction parameters")
 
-        return FeatureMap(results_df, config)
+        return FeatureMap(results_df, feature.sequence, feature.precursor_charge, config)
 
     def _find_closest_reference_mz(self, given_mz: np.array, reference_mz_values: np.array, peptide_product_annotation_list: np.array) -> np.array:
         """

massdash/peakPickers/ConformerPeakPicker.py

@@ -11,8 +11,10 @@
 # Structs
 from ..structs.TransitionGroup import TransitionGroup
 from ..structs.TransitionGroupFeature import TransitionGroupFeature
+from ..loaders.SpectralLibraryLoader import SpectralLibraryLoader
 # Utils
 from ..util import check_package
+from ..util import LOGGER
 
 onnxruntime, ONNXRUNTIME_AVAILABLE = check_package("onnxruntime")
 
@@ -35,7 +37,7 @@ class ConformerPeakPicker:
         _convertConformerFeatureToTransitionGroupFeatures: Convert conformer predicted feature to TransitionGroupFeatures.
     """
 
-    def __init__(self, transition_group: TransitionGroup, pretrained_model_file: str, window_size: int = 175, prediction_threshold: float = 0.5, prediction_type: str = "logits"):
+    def __init__(self, library_file: str, pretrained_model_file: str, prediction_threshold: float = 0.5, prediction_type: str = "logits"):
         """
         Initialize the ConformerPeakPicker class.
 
@@ -46,14 +48,18 @@ def __init__(self, transition_group: TransitionGroup, pretrained_model_file: str
             prediction_threshold (float, optional): The prediction threshold for peak picking. Defaults to 0.5.
             prediction_type (str, optional): The prediction type for peak picking. Defaults to "logits".
         """
-        self.transition_group = transition_group
         self.pretrained_model_file = pretrained_model_file
-        self.window_size = window_size
         self.prediction_threshold = prediction_threshold
         self.prediction_type = prediction_type
-        self.onnx_session = None
+        self.library = SpectralLibraryLoader(library_file)
 
         self._validate_model()
+
+        ## set in load_model
+        self.onnx_session = None
+        self.window_size = None
+
+        LOGGER.name = __class__.__name__
 
     def _validate_model(self):
         """
@@ -73,8 +79,14 @@ def load_model(self):
             raise ImportError("onnxruntime is required for loading the pretrained Conformer model, but not installed.")
         # Load pretrained model
         self.onnx_session = onnxruntime.InferenceSession(self.pretrained_model_file)
+        if len(self.onnx_session.get_inputs()) == 0:
+            raise ValueError("Pretrained model does not have any inputs.")
+        elif len(self.onnx_session.get_inputs()[0].shape) != 3:
+            raise ValueError("First input to model must be a 3D numpy array, current shape: {}".format(len(self.onnx_session.get_inputs()[0].shape)))
+        else:
+            self.window_size = self.onnx_session.get_inputs()[0].shape[2]
 
-    def pick(self, max_int_transition: int=1000) -> List[TransitionGroupFeature]:
+    def pick(self, transition_group, max_int_transition: int=1000) -> List[TransitionGroupFeature]:
         """
         Perform peak picking.
 
@@ -85,19 +97,19 @@ def pick(self, max_int_transition: int=1000) -> List[TransitionGroupFeature]:
             List[TransitionGroupFeature]: The list of transition group features.
         """
         # Transform data into required input
-        print("Preprocessing data...")
-        conformer_preprocessor = ConformerPreprocessor(self.transition_group)
-        input_data = conformer_preprocessor.preprocess()
-        print("Loading model...")
+        LOGGER.info("Loading model...")
         self.load_model()
-        print("Predicting...")
+        LOGGER.info("Preprocessing data...")
+        conformer_preprocessor = ConformerPreprocessor(transition_group, self.window_size)
+        input_data = conformer_preprocessor.preprocess(self.library)
+        LOGGER.info("Predicting...")
         ort_input = {self.onnx_session.get_inputs()[0].name: input_data}
         ort_output = self.onnx_session.run(None, ort_input)
-        print("Getting predicted boundaries...")
+        LOGGER.info("Getting predicted boundaries...")
         peak_info = conformer_preprocessor.find_top_peaks(ort_output[0], ["precursor"], self.prediction_threshold, self.prediction_type)
         # Get actual peak boundaries
-        peak_info = conformer_preprocessor.get_peak_boundaries(peak_info, self.transition_group, self.window_size)
-        print(f"Peak info: {peak_info}")
+        peak_info = conformer_preprocessor.get_peak_boundaries(peak_info)
+        LOGGER.info(f"Peak info: {peak_info}")
         return self._convertConformerFeatureToTransitionGroupFeatures(peak_info, max_int_transition)
 
     def _convertConformerFeatureToTransitionGroupFeatures(self, peak_info: dict, max_int_transition: int=1000) -> List[TransitionGroupFeature]: