Plot Peptide Sequence with Matched Fragments (#53) #62
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WalkthroughThis update introduces a new peptide sequence display feature across multiple spectrum plot backends. The changes add an Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant SpectrumPlot
participant PlotBackend
User->>SpectrumPlot: plot(**kwargs)
SpectrumPlot->>SpectrumPlot: Check config.display_peptide_sequence
alt Peptide sequence provided
SpectrumPlot->>PlotBackend: add_peptide_sequence(peptide_sequence, matched_fragments)
Note right of PlotBackend: Implement or raise NotImplementedError
else
SpectrumPlot-->>User: Render standard plot
end
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Actionable comments posted: 1
🧹 Nitpick comments (2)
pyopenms_viz/_core.py (1)
814-820: Well integrated peptide sequence display logicThe conditional logic properly checks for configuration settings before attempting to display the peptide sequence, providing a clean integration with the existing plotting functionality.
Consider simplifying line 816-817 by removing the redundant
Nonedefault:- peptide_sequence = kwargs.get("peptide_sequence", None) - matched_fragments = kwargs.get("matched_fragments", []) + peptide_sequence = kwargs.get("peptide_sequence") + matched_fragments = kwargs.get("matched_fragments", [])The
getmethod already returnsNoneby default when the key is not found.🧰 Tools
🪛 Ruff (0.8.2)
816-816: Use
kwargs.get("peptide_sequence")instead ofkwargs.get("peptide_sequence", None)Replace
kwargs.get("peptide_sequence", None)withkwargs.get("peptide_sequence")(SIM910)
pyopenms_viz/_matplotlib/core.py (1)
651-669: Refactor nested if statements (SIM102).Currently, lines 664-665 use nested conditionals. Consolidate these into one statement:
if self._config.display_peptide_sequence: - if "sequence" in self.data.columns: - self.add_peptide_sequence(self.data["sequence"], self.data["matched_fragments"]) + if "sequence" in self.data.columns and "matched_fragments" in self.data.columns: + self.add_peptide_sequence( + self.data["sequence"], + self.data["matched_fragments"] + )🧰 Tools
🪛 Ruff (0.8.2)
664-665: Use a single
ifstatement instead of nestedifstatements(SIM102)
📜 Review details
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⛔ Files ignored due to path filters (13)
test/__snapshots__/test_spectrum/test_mirror_spectrum[ms_matplotlib].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_binning[ms_matplotlib-kwargs0].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_binning[ms_matplotlib-kwargs1].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_binning[ms_matplotlib-kwargs2].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_binning[ms_matplotlib-kwargs3].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_binning[ms_matplotlib-kwargs4].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_plot[ms_matplotlib-kwargs0].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_plot[ms_matplotlib-kwargs1].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_plot[ms_matplotlib-kwargs2].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_plot[ms_matplotlib-kwargs3].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_matplotlib-kwargs0].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_matplotlib-kwargs1].pngis excluded by!**/*.pngtest/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_matplotlib-kwargs2].pngis excluded by!**/*.png
📒 Files selected for processing (19)
pyopenms_viz/_bokeh/core.py(2 hunks)pyopenms_viz/_config.py(1 hunks)pyopenms_viz/_core.py(3 hunks)pyopenms_viz/_matplotlib/core.py(2 hunks)pyopenms_viz/_plotly/core.py(1 hunks)test/__snapshots__/test_spectrum/test_mirror_spectrum[ms_bokeh].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs0].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs1].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs2].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs3].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs4].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs0].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs1].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs2].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs3].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs0].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs1].html(1 hunks)test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs2].html(1 hunks)test/test_chromatogram.py(2 hunks)
🧰 Additional context used
🪛 Ruff (0.8.2)
pyopenms_viz/_core.py
816-816: Use kwargs.get("peptide_sequence") instead of kwargs.get("peptide_sequence", None)
Replace kwargs.get("peptide_sequence", None) with kwargs.get("peptide_sequence")
(SIM910)
pyopenms_viz/_matplotlib/core.py
664-665: Use a single if statement instead of nested if statements
(SIM102)
🔇 Additional comments (41)
pyopenms_viz/_plotly/core.py (1)
622-623: New method signature looks good but is not yet implemented for PlotlyThe
add_peptide_sequencemethod has been added to maintain a consistent interface across different backend implementations, correctly raisingNotImplementedErrorsince this functionality is only implemented for Matplotlib as mentioned in the PR summary.pyopenms_viz/_bokeh/core.py (2)
2-2: Good imports update to support new methodThe typing import has been properly updated to include List and Tuple for the type annotations needed in the new method.
544-545: New method signature looks good but is not yet implemented for BokehThe
add_peptide_sequencemethod has been added to maintain a consistent interface across different backend implementations, correctly raisingNotImplementedErroras mentioned in the PR summary.test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs4].html (2)
21-24: Updated test snapshot IDs are expectedThe changes to element IDs are expected when regenerating test snapshots after code changes. These are automatically generated by the testing framework and don't require specific review.
32-33: Updated document references are expectedThe modifications to document references and render items are consistent with the updated element IDs above and are expected when regenerating test snapshots.
test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs0].html (3)
21-21: Updated test snapshot IDs are expectedThe changes to element IDs are expected when regenerating test snapshots after code changes. These are automatically generated by the testing framework and don't require specific review.
23-24: Updated script references are expectedThe modifications to script ID and JSON content are consistent with the updated element IDs and are expected when regenerating test snapshots.
32-33: Updated document references are expectedThe modifications to document references and render items are consistent with the updated element IDs above and are expected when regenerating test snapshots.
test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs1].html (1)
21-21: Changes to element IDs and data references look appropriate.These changes update Bokeh element and data IDs which appear to be regenerated snapshots after implementing the new peptide sequence feature. The modifications maintain the proper structure required for Bokeh visualization rendering.
Also applies to: 23-24, 32-33
test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs1].html (1)
21-21: Updated Bokeh element and data IDs look correct.Similar to the previous file, these snapshot changes are expected when regenerating test files after implementing the new peptide sequence feature. The ID updates maintain proper Bokeh rendering structure.
Also applies to: 23-24, 32-33
test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs2].html (1)
21-21: Element and data ID updates maintain proper Bokeh structure.These are the expected changes when regenerating test snapshots after implementing the new peptide sequence feature. The modifications correctly maintain the relationship between DOM elements and Bokeh data references.
Also applies to: 23-24, 32-33
pyopenms_viz/_config.py (1)
360-364: New configuration options for peptide sequence display look good.The added configuration options properly support the new peptide sequence display feature:
display_peptide_sequenceis disabled by default (good for backward compatibility)- Font size, colors, and highlighting alpha values have sensible defaults
- The naming convention is consistent with the rest of the codebase
These additions align well with the PR objective to add peptide sequence visualization capabilities.
test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs0].html (3)
21-21: Regenerated Bokeh div element identifiers match updated implementation.The HTML div element has been updated with new identifiers, which is expected when the underlying Bokeh implementation changes.
23-24: Updated JSON script element with new identifiers.The script element containing the Bokeh visualization data has been appropriately updated with new IDs.
32-33: JavaScript references correctly updated to match new element IDs.The document embedding code has been properly synchronized with the new IDs defined above.
test/test_chromatogram.py (4)
5-6: Good addition of headless Matplotlib backend.Setting the Agg backend prevents GUI-related errors when running tests in environments without display capabilities.
59-71: Well-structured DummySpectrumPlot initialization.The class correctly implements a lightweight test double by manually setting only the essential attributes needed for testing rather than calling the parent constructor. The explicit comment about initialization strategy is helpful.
I particularly like that you're enabling the
display_peptide_sequenceflag in the dummy config to ensure the method will be called during tests.
96-107: Good implementation of test double pattern for renderer.The nested
DummyRendererclass efficiently simulates the behavior of a real renderer without actual rendering. This approach allows for testing the interaction with renderers without dependencies on the actual rendering implementation.
152-154: Appropriate NotImplementedError for unsupported backend.The
plot_peptide_sequencemethod correctly raises aNotImplementedErrorwith a clear message, which aligns with the PR objective to test behavior when a backend other than Matplotlib is used.test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs1].html (3)
21-21: Bokeh div element correctly updated with new identifiers.The div element has been updated with new identifiers, which is necessary to match the current implementation.
23-24: JSON data script updated with new identifiers.The script tag containing visualization data has been properly updated with new identifiers.
32-33: JavaScript initialization correctly uses updated element references.The embed_document function properly references the new script and div IDs, maintaining synchronization between the HTML structure and JavaScript.
test/__snapshots__/test_spectrum/test_spectrum_with_annotations[ms_bokeh-kwargs2].html (3)
21-21: Div element updated with appropriate new identifiers.The HTML div has been updated with new identifiers to match the current implementation.
23-24: JSON data script element properly updated.The script containing visualization data has been updated with appropriate new identifiers.
32-33: JavaScript element references correctly synchronized.The document initialization code has been properly updated to reference the new identifiers.
pyopenms_viz/_core.py (2)
692-704: Well implemented abstract method for peptide sequence visualizationThe addition of the
add_peptide_sequenceabstract method provides a clear interface for subclasses to implement peptide sequence visualization, with well-documented parameters and purpose.
764-764: Good modification to accept additional parametersUpdating the
plotmethod signature to accept**kwargsis a flexible approach that allows passing additional data to specialized plotting functions.test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs3].html (1)
21-33: Updated test snapshot IDsThe changes to element IDs and references in the test snapshot file are consistent with the implementation of the new feature. These updates are expected when regenerating test snapshots after code changes.
test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs0].html (1)
21-33: Updated test snapshot IDsThe changes to element IDs and references in the test snapshot file are consistent with the implementation of the new feature. These updates are expected when regenerating test snapshots after code changes.
test/__snapshots__/test_spectrum/test_spectrum_plot[ms_bokeh-kwargs3].html (1)
21-33: Updated test snapshot IDsThe changes to element IDs and references in the test snapshot file are consistent with the implementation of the new feature. These updates are expected when regenerating test snapshots after code changes.
test/__snapshots__/test_spectrum/test_mirror_spectrum[ms_bokeh].html (3)
21-21: No issues found.This updated div element ID and data-root-id appear consistent with the new Bokeh embedding references.
23-24: No issues found.The updated JSON script references for Bokeh rendering look correct.
32-33: No issues found.These revised references to the new script ID and render items align with the updated Bokeh document IDs.
pyopenms_viz/_matplotlib/core.py (5)
2-2: New import for typed hints is consistent.Importing
ListandTuplesupports better type annotations in the new method signatures.
582-582: Docstring update acknowledged.No functional changes introduced here; the updated docstring maintains clarity.
586-599: Figure creation logic looks good.This
_create_figureoverride cleanly handles fallback cases for width/height.
600-614: Main plot rendering is well-organized.Using a line renderer to draw the spectrum data is appropriate here.
615-649: Peptide sequence addition is well-structured.The method correctly places the sequence text above the main plot and highlights matched fragments. Consider boundary validation if negative (start, end) indices might occur in certain edge cases, though it's likely safe for normal usage.
test/__snapshots__/test_spectrum/test_spectrum_binning[ms_bokeh-kwargs2].html (3)
21-21: No issues found.The updated div element and data-root-id match the new Bokeh document structure.
23-24: No issues found.The JSON script ID update appears valid for the snapshot test.
32-33: No issues found.References to the new document and root IDs are consistent with the updated embed workflow.
| # Dummy backend to test missing peptide sequence implementation | ||
| class DummySpectrumPlot(SpectrumPlot): | ||
| def __init__(self, data): | ||
| # Instead of calling super().__init__(data) (which verifies required columns), | ||
| # we manually set minimal attributes needed to pass initialization. | ||
| self.data = data.copy() | ||
| # Set dummy column values so that _verify_column doesn't raise errors. | ||
| self.x = "dummy" | ||
| self.y = "dummy" | ||
| self.by = None | ||
| # Provide a dummy config with display_peptide_sequence enabled. | ||
| self._config = type("dummy_config", (), {"display_peptide_sequence": True})() | ||
|
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| def plot(self): | ||
| pass | ||
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| def load_config(self, **kwargs): | ||
| pass | ||
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| def _check_and_aggregate_duplicates(self): | ||
| pass | ||
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| def _prepare_data(self, data): | ||
| return data | ||
|
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| def _create_tooltips(self, entries, index): | ||
| return {}, {} | ||
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| def _get_annotations(self, data, x, y): | ||
| return [], [], [], [] | ||
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| def convert_for_line_plots(self, data, x, y): | ||
| return data | ||
|
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| def _get_colors(self, data, kind): | ||
| return "blue" | ||
|
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| def get_line_renderer(self, data, by=None, color=None, config=None): | ||
| # Return dummy object with required methods. | ||
| class DummyRenderer: | ||
| def generate(self, tooltips, custom_hover_data): | ||
| # Return a dummy canvas with a gca() method. | ||
| class DummyAxes: | ||
| def gca(self): | ||
| return self | ||
| return DummyAxes() | ||
| def _add_annotations(self, canvas, texts, xs, ys, colors): | ||
| pass | ||
| return DummyRenderer() | ||
|
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| # Provide stubs for all abstract methods from SpectrumPlot: | ||
| def _add_bounding_box_drawer(self): | ||
| pass | ||
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| def _add_bounding_vertical_drawer(self): | ||
| pass | ||
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| def _add_legend(self, legend): | ||
| pass | ||
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| def _add_tooltips(self, tooltips, custom_hover_data): | ||
| pass | ||
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| def _create_figure(self): | ||
| return None | ||
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| def _load_extension(self): | ||
| pass | ||
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| def _modify_x_range(self, x_range, padding=None): | ||
| pass | ||
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| def _modify_y_range(self, y_range, padding=None): | ||
| pass | ||
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| def _update_plot_aes(self): | ||
| pass | ||
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| def generate(self, tooltips, custom_hover_data): | ||
| return None | ||
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| def get_scatter_renderer(self, *args, **kwargs): | ||
| return None | ||
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| def get_vline_renderer(self, *args, **kwargs): | ||
| return None | ||
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| def plot_x_axis_line(self, canvas, line_width=2): | ||
| pass | ||
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| def show_default(self): | ||
| pass | ||
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| # Abstract method: raise error since it's not supported in this dummy backend. | ||
| def plot_peptide_sequence(self, ax, data): | ||
| raise NotImplementedError("Dummy backend does not support peptide sequence plotting") |
There was a problem hiding this comment.
💡 Verification agent
❓ Verification inconclusive
Consider adding a test that verifies the NotImplementedError is raised.
While the DummySpectrumPlot class is well implemented, I don't see an actual test that uses it to verify the NotImplementedError is raised when a non-Matplotlib backend is used. This would complete the testing of the feature described in the PR objectives.
🏁 Script executed:
#!/bin/bash
# Search for tests using DummySpectrumPlot to verify NotImplementedError
rg "DummySpectrumPlot" --type=python -A 10 -B 5 --no-headingLength of output: 91
Action Required: Add a Test for NotImplementedError in DummySpectrumPlot
It appears that no test currently verifies that the plot_peptide_sequence method in DummySpectrumPlot raises the expected NotImplementedError. Please add a test that imports DummySpectrumPlot, calls its plot_peptide_sequence method (using a dummy axis and data as needed), and asserts that the NotImplementedError with the message "Dummy backend does not support peptide sequence plotting" is raised.
- Verify in your test suite that:
- The dummy instance is created correctly.
- Calling
plot_peptide_sequenceon this instance triggers aNotImplementedError.
jcharkow
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jcharkow
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There was a problem hiding this comment.
Good start! This is a challenging PR since the Pyopenms_viz codebase can be difficult
to understand for new developers due to its many layers of abstraction. Please see comments above.
It cannot find where you placed the tests for the sequence plot? Also it seems that you modified a lot of the snapshots and the plots generated seem wonky (e.g. look at matplotlib .png files). The point of snapshot tests not to modify the snapshots as a failing snapshot means that the code is broken.
I think some of the issues of the failing tests are due to you implementing a new plot() function for matplotlibspectrum. I would recommend abstracting the plot() functionality to _core.py as suggested above.
| """ | ||
| Class for assembling a Bokeh spectrum plot | ||
| """ |
| """ | ||
| Class for assembling a Bokeh spectrum plot | ||
| """ | ||
| def add_peptide_sequence(self, peptide_sequence: str, matched_fragments: List[Tuple[int, int]]): |
There was a problem hiding this comment.
Please add a docstring here for good practice. Can be based on the docstring below and explain this is not implemented..
| Class for assembling a Bokeh spectrum plot | ||
| """ | ||
| def add_peptide_sequence(self, peptide_sequence: str, matched_fragments: List[Tuple[int, int]]): | ||
| raise NotImplementedError("Not implemented for Bokeh") |
There was a problem hiding this comment.
Be a bit more descriptive. Something like. "Plotting Peptide Sequences is not supported for the Bokeh backend"
| # Add peptide sequence if configured | ||
| if hasattr(self._config, "display_peptide_sequence") and self._config.display_peptide_sequence: | ||
| peptide_sequence = kwargs.get("peptide_sequence", None) | ||
| matched_fragments = kwargs.get("matched_fragments", []) | ||
| if peptide_sequence: | ||
| self.add_peptide_sequence(peptide_sequence, matched_fragments) |
There was a problem hiding this comment.
These variables should be stored automatically in the object. Thus you should be able to reference them using self.peptide_sequence and self.matched_fragments. This will remove the need for kwargs
| def _create_figure(self): | ||
| if self.width is None or self.height is None: | ||
| self.fig, self.ax = plt.subplots() | ||
| else: | ||
| self.fig, self.ax = plt.subplots(figsize=(self.width / 100, self.height / 100), dpi=100) | ||
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| self.ax.set_title(self.title) | ||
| self.ax.set_xlabel(self.xlabel) | ||
| self.ax.set_ylabel(self.ylabel) | ||
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| # Ensure `self.canvas` references the Axes, not the Figure | ||
| self.canvas = self.ax | ||
| return self.ax | ||
|
|
There was a problem hiding this comment.
This method is likely not needed as there is already this functionality in the MATPLOTLIBPLOT class
| def create_main_plot(self): | ||
| """ | ||
| Draw the main spectrum (e.g., peaks) on self.ax. | ||
| """ | ||
| # Example: use a line plot for the spectrum | ||
| linePlot = self.get_line_renderer( | ||
| data=self.data, | ||
| x=self._config.x, | ||
| y=self._config.y, | ||
| config=self._config, | ||
| canvas=self.canvas, | ||
| ) | ||
| ax = linePlot.generate(None, None) | ||
| return ax |
There was a problem hiding this comment.
I see that you structure this after the peakMap which is a little bit of an exception compared to other plots. Some of this can be abstracted more to prevent repeated code. I would recommend removing this function.
| if self.canvas is None: | ||
| self.canvas = self._create_figure() | ||
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| # Create the main spectrum plot | ||
| self.ax = self.create_main_plot() | ||
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| # Plot peptide sequence if set in config | ||
| if self._config.display_peptide_sequence: | ||
| if "sequence" in self.data.columns: | ||
| self.add_peptide_sequence(self.data["sequence"], self.data["matched_fragments"]) | ||
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| return self.ax |
There was a problem hiding this comment.
Would be best to add this instead to the _core.py SpectrumPlot's plot() function so that it can be shared across backends. I know only matplotlib is supported for now but it might be supported with other backends in the future.
| ) | ||
| return df | ||
| def add_peptide_sequence(self, peptide_sequence: str, matched_fragments: List[Tuple[int, int]]): | ||
| raise NotImplementedError("Not implemented for Plotly") |
There was a problem hiding this comment.
See above add docstring and make the NotImplementedErrror more descriptive
|
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||
| # Dummy backend to test missing peptide sequence implementation | ||
| class DummySpectrumPlot(SpectrumPlot): | ||
| def __init__(self, data): | ||
| # Instead of calling super().__init__(data) (which verifies required columns), | ||
| # we manually set minimal attributes needed to pass initialization. | ||
| self.data = data.copy() | ||
| # Set dummy column values so that _verify_column doesn't raise errors. | ||
| self.x = "dummy" | ||
| self.y = "dummy" | ||
| self.by = None | ||
| # Provide a dummy config with display_peptide_sequence enabled. | ||
| self._config = type("dummy_config", (), {"display_peptide_sequence": True})() | ||
|
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| def plot(self): | ||
| pass | ||
|
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| def load_config(self, **kwargs): | ||
| pass | ||
|
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| def _check_and_aggregate_duplicates(self): | ||
| pass | ||
|
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| def _prepare_data(self, data): | ||
| return data | ||
|
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| def _create_tooltips(self, entries, index): | ||
| return {}, {} | ||
|
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| def _get_annotations(self, data, x, y): | ||
| return [], [], [], [] | ||
|
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| def convert_for_line_plots(self, data, x, y): | ||
| return data | ||
|
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| def _get_colors(self, data, kind): | ||
| return "blue" | ||
|
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| def get_line_renderer(self, data, by=None, color=None, config=None): | ||
| # Return dummy object with required methods. | ||
| class DummyRenderer: | ||
| def generate(self, tooltips, custom_hover_data): | ||
| # Return a dummy canvas with a gca() method. | ||
| class DummyAxes: | ||
| def gca(self): | ||
| return self | ||
| return DummyAxes() | ||
| def _add_annotations(self, canvas, texts, xs, ys, colors): | ||
| pass | ||
| return DummyRenderer() | ||
|
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| # Provide stubs for all abstract methods from SpectrumPlot: | ||
| def _add_bounding_box_drawer(self): | ||
| pass | ||
|
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| def _add_bounding_vertical_drawer(self): | ||
| pass | ||
|
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| def _add_legend(self, legend): | ||
| pass | ||
|
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| def _add_tooltips(self, tooltips, custom_hover_data): | ||
| pass | ||
|
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| def _create_figure(self): | ||
| return None | ||
|
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| def _load_extension(self): | ||
| pass | ||
|
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| def _modify_x_range(self, x_range, padding=None): | ||
| pass | ||
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| def _modify_y_range(self, y_range, padding=None): | ||
| pass | ||
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| def _update_plot_aes(self): | ||
| pass | ||
|
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| def generate(self, tooltips, custom_hover_data): | ||
| return None | ||
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| def get_scatter_renderer(self, *args, **kwargs): | ||
| return None | ||
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| def get_vline_renderer(self, *args, **kwargs): | ||
| return None | ||
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| def plot_x_axis_line(self, canvas, line_width=2): | ||
| pass | ||
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| def show_default(self): | ||
| pass | ||
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| # Abstract method: raise error since it's not supported in this dummy backend. | ||
| def plot_peptide_sequence(self, ax, data): | ||
| raise NotImplementedError("Dummy backend does not support peptide sequence plotting") |
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Is this needed? Could you just test one of the backends where it is not supported?
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Hey @jcharkow , I hope you're doing well. I wanted to let you know that while I was working on the peptide sequence plotting updates, I was at college and didn’t realize I was working on a different fork . I only noticed this after completing the work. Thank you, |
2 participants
Hey @jcharkow !
This PR addresses issue #53 by integrating the feature to plot peptide sequences with matched fragments into the Matplotlib backend interface.
I have followed your instructions from the issue description.
The following changes have been made:
Abstract Method in _core.py:
Added an abstract method in SpectrumPlot class for adding peptide sequences to the plot. This method allows for flexible backend implementations (currently only matplotlib).
Matplotlib Backend Implementation:
Implemented the method for plotting the peptide sequence in the matplotlib backend (file _matplotlib/core.py). This implementation uses a simple text-based approach to display the peptide sequence on the plot.
Configuration Option:
Introduced a new configuration option in SpectrumConfig (in _config.py) called display_peptide_sequence. This option controls whether the peptide sequence should be shown on the plot. By default, this is set to False.
Testing:
Added tests in test_chromatogram.py to ensure that the peptide sequence is properly displayed when the configuration is enabled. Also, tests ensure that when a backend other than matplotlib is used, a NotImplementedError is raised, as expected.
Would appreciate it if you could review and provide any feedback or required changes. Thanks!
Summary by CodeRabbit
New Features
Tests