From 763b30403bbf73d30ef1e840ce6486017e2df549 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 11:39:41 -0500 Subject: [PATCH 01/12] chore: copied ruff config from med-imagetools --- config/ruff.toml | 149 ++++++++++++++++++++++++++++++++++++----------- 1 file changed, 114 insertions(+), 35 deletions(-) diff --git a/config/ruff.toml b/config/ruff.toml index e8b925d..952c67c 100644 --- a/config/ruff.toml +++ b/config/ruff.toml @@ -1,9 +1,6 @@ - - -target-version = "py39" -output-format = "full" -line-length = 99 -fix = true +include = [ + "src/readii/loaders.py" +] # extend-exclude is used to exclude directories from the flake8 checks @@ -13,41 +10,92 @@ extend-exclude = [ ".pixi/", ] +# Same as Black. +line-length = 100 -extend-include = [] - -include = [ - "src/readii/loaders.py" -] [lint] +# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`) codes by default. +# Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or +# McCabe complexity (`C901`) by default. + select = [ - "E", + ########################################################################### + # TYPE ANNOTATIONS + # Ensure all functions have type annotations + # https://docs.astral.sh/ruff/rules/#flake8-annotations-ann + "ANN", + # Use type hinting consistently + # https://docs.astral.sh/ruff/rules/#flake8-type-checking-tch + "TCH", + + ########################################################################### + # IMPORTS + # Sort imports naturally + # https://docs.astral.sh/ruff/rules/#isort-i + "I", + # Follow import conventions + # https://docs.astral.sh/ruff/rules/#flake8-import-conventions-icn + "ICN", + # Clean up and organize imports + # https://docs.astral.sh/ruff/rules/#flake8-tidy-imports-tid + "TID", + + ########################################################################### + # CODE QUALITY + # Detect possible bugs, like unused variables or exception handling issues + # https://docs.astral.sh/ruff/rules/#flake8-bugbear-b + "B", + # Avoid using Python builtins incorrectly + # https://docs.astral.sh/ruff/rules/#flake8-builtins-a + "A", + # Enforce correct usage of commas in lists, tuples, etc. + # https://docs.astral.sh/ruff/rules/#flake8-commas-com + "COM", + # Prevent use of debugging code, like breakpoints + # https://docs.astral.sh/ruff/rules/#flake8-debugger-t10 + "T10", + # Disallow print statements + # https://docs.astral.sh/ruff/rules/#flake8-print-t20 + "T20", + # Provide clear and explanatory error messages + # https://docs.astral.sh/ruff/rules/#flake8-errmsg-em + "EM", + + ########################################################################### + # STANDARDS & STYLE + # Prefer pathlib for path manipulation + # https://docs.astral.sh/ruff/rules/#flake8-use-pathlib-pth + "PTH", + # Adhere to Pylint conventions + # https://docs.astral.sh/ruff/rules/#pylint-pl + "PL", + # Simplify code to reduce complexity + # https://docs.astral.sh/ruff/rules/#flake8-simplify-sim + "SIM", + # errors like undefined names and unused imports without enforcing style rules. + # https://docs.astral.sh/ruff/rules/#pyflakes-f "F", - "W", # flake8 - "C", # mccabe - "I", # isort - "D", # pydocstyle - # "N", # pep8-naming - "ANN", # flake8-annotations - "BLE", # flake8-blind-except - "B", # flake8-bugbear - "A", # flake8-builtins - # "G", # flake8-logging-format - "ERA", # eradicate - "RUF", # Ruff-specific rules - "TCH", # flake8-type-checking + # + # https://docs.astral.sh/ruff/rules/#pep8-naming-n + "N", + # Pydocstyle + # https://docs.astral.sh/ruff/rules/#pydocstyle-d + # "D", ] -ignore = ["ANN101"] - - -[lint.per-file-ignores] -"tests/*" = ["S101"] -[lint.mccabe] -max-complexity = 10 - +ignore = [ + # allow self to not need type annotations + "ANN101", + # Allow too many arguments for functions + "PLR0913", + # Public Module Docstrings + "D100", + # Ignored because https://docs.astral.sh/ruff/formatter/#conflicting-lint-rules + "COM812", # https://docs.astral.sh/ruff/rules/missing-trailing-comma/#missing-trailing-comma-com812 + "D206" +] [lint.isort] known-first-party = ["readii"] @@ -56,12 +104,43 @@ combine-as-imports = true lines-after-imports = 1 relative-imports-order = "closest-to-furthest" +[lint.mccabe] +max-complexity = 10 + + +[lint.per-file-ignores] +"tests/*" = ["S101"] + [lint.pydocstyle] convention = "numpy" + [format] -quote-style = "double" + +quote-style = "single" +indent-style = "tab" docstring-code-format = true -docstring-code-line-length = 20 \ No newline at end of file +docstring-code-line-length = 20 + + +# [lint] # commented for now, will iterate on this later +# select = [ +# "E", +# "F", +# "W", # flake8 +# "C", # mccabe +# "I", # isort +# "D", # pydocstyle +# # "N", # pep8-naming +# "ANN", # flake8-annotations +# "BLE", # flake8-blind-except +# "B", # flake8-bugbear +# "A", # flake8-builtins +# # "G", # flake8-logging-format +# "ERA", # eradicate +# "RUF", # Ruff-specific rules +# "TCH", # flake8-type-checking +# ] +# ignore = ["ANN101"] \ No newline at end of file From fe70693bb7a8b3e499dfa4c2c335ef5f7353ee87 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 13:06:57 -0500 Subject: [PATCH 02/12] chore: update ruff configuration to include additional files and ignore specific PEP-8 naming conventions --- config/ruff.toml | 22 +++++++++++++++------- 1 file changed, 15 insertions(+), 7 deletions(-) diff --git a/config/ruff.toml b/config/ruff.toml index 952c67c..0e7f8b3 100644 --- a/config/ruff.toml +++ b/config/ruff.toml @@ -1,5 +1,6 @@ include = [ - "src/readii/loaders.py" + "src/readii/loaders.py", + "src/readii/feature_extraction.py" ] @@ -8,7 +9,12 @@ extend-exclude = [ "docs/*", "tests/*", ".pixi/", - ] + "src/readii/image_processing.py", + "src/readii/loaders.py", + "src/readii/metadata.py", + "src/readii/negative_controls.py", + "src/readii/pipeline.py", +] # Same as Black. line-length = 100 @@ -76,9 +82,7 @@ select = [ # errors like undefined names and unused imports without enforcing style rules. # https://docs.astral.sh/ruff/rules/#pyflakes-f "F", - # - # https://docs.astral.sh/ruff/rules/#pep8-naming-n - "N", + # Pydocstyle # https://docs.astral.sh/ruff/rules/#pydocstyle-d # "D", @@ -94,7 +98,7 @@ ignore = [ "D100", # Ignored because https://docs.astral.sh/ruff/formatter/#conflicting-lint-rules "COM812", # https://docs.astral.sh/ruff/rules/missing-trailing-comma/#missing-trailing-comma-com812 - "D206" + "D206", ] [lint.isort] @@ -143,4 +147,8 @@ docstring-code-line-length = 20 # "RUF", # Ruff-specific rules # "TCH", # flake8-type-checking # ] -# ignore = ["ANN101"] \ No newline at end of file +# ignore = ["ANN101"] + +# Readii uses a lot of camelcase so ignoring pep-8 conventions. +# https://docs.astral.sh/ruff/rules/#pep8-naming-n +# "N", \ No newline at end of file From 729186888709eb79725fdf3c7b6ee31c0c1077bb Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 13:10:12 -0500 Subject: [PATCH 03/12] refactor: use pathlib instead of os.path, remove unused imports, improve logging verbosity, add type annotations, extract-functions to create context overhead --- src/readii/feature_extraction.py | 765 ++++++++++++++++--------------- 1 file changed, 393 insertions(+), 372 deletions(-) diff --git a/src/readii/feature_extraction.py b/src/readii/feature_extraction.py index 5afa10b..51dbadd 100644 --- a/src/readii/feature_extraction.py +++ b/src/readii/feature_extraction.py @@ -1,392 +1,413 @@ -from imgtools.io import read_dicom_series +import os +from collections import OrderedDict from itertools import chain -from joblib import Parallel, delayed -from radiomics import featureextractor, imageoperations, logging +from pathlib import Path +from typing import Any, Optional -import os import pandas as pd -import numpy as np -import SimpleITK as sitk +import SimpleITK as sitk # noqa +from imgtools.io import read_dicom_series +from joblib import Parallel, delayed +from radiomics import featureextractor, imageoperations, logging from readii.image_processing import ( - flattenImage, - alignImages, - getROIVoxelLabel, - displayImageSlice, - displayCTSegOverlay, - getROICenterCoords, - getCroppedImages, + alignImages, + flattenImage, + getROIVoxelLabel, ) - from readii.loaders import ( - loadDicomSITK, - loadRTSTRUCTSITK, - loadSegmentation, -) - + loadSegmentation, +) from readii.metadata import ( - saveDataframeCSV, - matchCTtoSegmentation, - getSegmentationType, + saveDataframeCSV, ) from readii.negative_controls import ( - applyNegativeControl, + applyNegativeControl, ) - from readii.utils import logger -from typing import Optional, Any -from collections import OrderedDict +def generateNegativeControl( + ctImage: sitk.Image, + negativeControl: str, + alignedROIImage: sitk.Image, + randomSeed: Optional[int], +) -> sitk.Image: + """Function to generate a negative control for a CT image based on the type of negative control specified. + + negativeControlType : str + This string is of the format {negativeControlType}_{negativeControlRegion} + """ + if "non_roi" in negativeControl: + negativeControlType = negativeControl.rsplit("_", 2)[0] + negativeControlRegion = "non_roi" + else: + negativeControlComponents = negativeControl.rsplit("_", 1) + negativeControlType = negativeControlComponents[0] + negativeControlRegion = negativeControlComponents[1] + logger.debug(f"Negative control region: {negativeControlRegion}") + logger.debug(f"Negative control type: {negativeControlType}") + return applyNegativeControl( + baseImage=ctImage, + negativeControlType=negativeControlType, + negativeControlRegion=negativeControlRegion, + roiMask=alignedROIImage, + randomSeed=randomSeed, + ) + + +def cropImageAndMask( + ctImage: sitk.Image, + alignedROIImage: sitk.Image, + segBoundingBox: tuple, + negativeControl: Optional[str], + randomSeed: Optional[int], +) -> tuple[sitk.Image, sitk.Image]: + try: + if negativeControl is not None: + logger.info(f"Generating {negativeControl} negative control for CT.") + ctImage = generateNegativeControl(ctImage, negativeControl, alignedROIImage, randomSeed) + + croppedCT, croppedROI = imageoperations.cropToTumorMask( + ctImage, alignedROIImage, segBoundingBox + ) + except Exception as e: + logger.error(f"Error cropping image and mask: {e}") + raise + + return croppedCT, croppedROI + def singleRadiomicFeatureExtraction( - ctImage: sitk.Image, - roiImage: sitk.Image, - pyradiomicsParamFilePath: Optional[str] = "./src/readii/data/default_pyradiomics.yaml", - negativeControl: Optional[str] = None, - randomSeed: Optional[int] = None, + ctImage: sitk.Image, + roiImage: sitk.Image, + pyradiomicsParamFilePath: Optional[str] = "./src/readii/data/default_pyradiomics.yaml", + negativeControl: Optional[str] = None, + randomSeed: Optional[int] = None, ) -> OrderedDict[Any, Any]: - """Function to perform radiomic feature extraction for a single CT image and its corresponding segmentation. - CT and segmentation will be aligned and cropped prior to extraction. - - Parameters - ---------- - ctImage : sitk.Image - CT image to perform feature extraction on. Will be cropped and potentially generate a negative control (see negativeControl arg) - roiImage : sitk.Image - Region of interest (ROI) to extract radiomic features from within the CT. - pyradiomicsParamFilePath : str - Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. - negativeControl : str - Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. - randomSeed : int - Value to set random seed with for negative control creation to be reproducible. - - Returns - ------- - OrderedDict[Any, Any] - Dictionary containing image metadata, versions for key packages used for extraction, and radiomic features - """ - # If no pyradiomics paramater file passed, use default - if pyradiomicsParamFilePath == None: - pyradiomicsParamFilePath = "./src/readii/data/default_pyradiomics.yaml" - - # In case segmentation contains extra axis, flatten to 3D by removing it - roiImage = flattenImage(roiImage) - # Segmentation has different origin, align it to the CT for proper feature extraction - alignedROIImage = alignImages(ctImage, roiImage) - - # Get pixel value for the segmentation - segmentationLabel: int = getROIVoxelLabel(alignedROIImage) - - # Check that CT and segmentation correspond, segmentationLabel is present, and dimensions match - segBoundingBox, correctedROIImage = imageoperations.checkMask(ctImage, alignedROIImage, label=segmentationLabel) - - # Update the ROI image if a correction was generated by checkMask - if correctedROIImage is not None: - alignedROIImage = correctedROIImage - - try: - if negativeControl != None: - logger.info(f"Generating {negativeControl} negative control for CT.") - # Split negative control type into negative control and region of interest - try: - if "non_roi" in negativeControl: - negativeControlType = negativeControl.rsplit("_", 2)[0] - negativeControlRegion = "non_roi" - else: - negativeControlComponents = negativeControl.rsplit("_", 1) - negativeControlType = negativeControlComponents[0] - negativeControlRegion = negativeControlComponents[1] - logger.debug(f"Negative control region: {negativeControlRegion}") - logger.debug(f"Negative control type: {negativeControlType}") - # Make negative control version of ctImage - ctImage_nc: sitk.Image | np.ndarray = applyNegativeControl( - baseImage=ctImage, - negativeControlType=negativeControlType, - negativeControlRegion=negativeControlRegion, - roiMask=alignedROIImage, - randomSeed=randomSeed - ) - except Exception as e: - logger.error(f"Error generating {negativeControl} negative control for CT: {e}") - raise - - croppedCT, croppedROI = imageoperations.cropToTumorMask(ctImage_nc, alignedROIImage, segBoundingBox) - else: - # Crop the image and mask to a bounding box around the mask to reduce volume size to process - croppedCT, croppedROI = imageoperations.cropToTumorMask(ctImage, alignedROIImage, segBoundingBox) - except Exception as e: - logger.error(f"Error cropping image and mask: {e}") - raise - - # Load PyRadiomics feature extraction parameters to use - # Initialize feature extractor with parameters - try: - logger.info("Setting up Pyradiomics feature extractor...") - featureExtractor = featureextractor.RadiomicsFeatureExtractor(pyradiomicsParamFilePath) - except OSError as e: - logger.error(f"Supplied pyradiomics parameter file {pyradiomicsParamFilePath} does not exist or is not at that location: {e}") - raise - - try: - logger.info("Starting radiomic feature extraction...") - # Extract radiomic features from CT with segmentation as mask - idFeatureVector = featureExtractor.execute(croppedCT, croppedROI, label=segmentationLabel) - except Exception as e: - logger.error(f"An error occurred while extracting radiomic features: {e}") - raise - - return idFeatureVector + """Function to perform radiomic feature extraction for a single CT image and its corresponding segmentation. + CT and segmentation will be aligned and cropped prior to extraction. + + Parameters + ---------- + ctImage : sitk.Image + CT image to perform feature extraction on. Will be cropped and potentially generate a negative control (see negativeControl arg) + roiImage : sitk.Image + Region of interest (ROI) to extract radiomic features from within the CT. + pyradiomicsParamFilePath : str + Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. + negativeControl : str + Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. + randomSeed : int + Value to set random seed with for negative control creation to be reproducible. + + Returns + ------- + OrderedDict[Any, Any] + Dictionary containing image metadata, versions for key packages used for extraction, and radiomic features + """ + # If no pyradiomics paramater file passed, use default + if pyradiomicsParamFilePath == None: + pyradiomicsParamFilePath = "./src/readii/data/default_pyradiomics.yaml" + + # In case segmentation contains extra axis, flatten to 3D by removing it + roiImage = flattenImage(roiImage) + # Segmentation has different origin, align it to the CT for proper feature extraction + alignedROIImage = alignImages(ctImage, roiImage) + + # Get pixel value for the segmentation + segmentationLabel: int = getROIVoxelLabel(alignedROIImage) + + # Check that CT and segmentation correspond, segmentationLabel is present, and dimensions match + segBoundingBox, correctedROIImage = imageoperations.checkMask( + ctImage, alignedROIImage, label=segmentationLabel + ) + + # Update the ROI image if a correction was generated by checkMask + if correctedROIImage is not None: + alignedROIImage = correctedROIImage + + croppedCT, croppedROI = cropImageAndMask( + ctImage, alignedROIImage, segBoundingBox, negativeControl, randomSeed + ) + + # Load PyRadiomics feature extraction parameters to use + # Initialize feature extractor with parameters + try: + logger.info("Setting up Pyradiomics feature extractor...") + featureExtractor = featureextractor.RadiomicsFeatureExtractor(pyradiomicsParamFilePath) + except OSError as e: + logger.exception( + f"Supplied pyradiomics parameter file {pyradiomicsParamFilePath} does not exist or is not at that location: {e}" + ) + raise e + + try: + logger.info("Starting radiomic feature extraction...") + # Extract radiomic features from CT with segmentation as mask + idFeatureVector = featureExtractor.execute(croppedCT, croppedROI, label=segmentationLabel) + except Exception as e: + logger.exception(f"An error occurred while extracting radiomic features: {e}") + raise e + + return idFeatureVector def radiomicFeatureExtraction( - imageMetadataPath: str, - imageDirPath: str, - roiNames: Optional[str] = None, - pyradiomicsParamFilePath: Optional[str] = "src/readii/data/default_pyradiomics.yaml", - outputDirPath: Optional[str] = None, - negativeControl: Optional[str] = None, - randomSeed: Optional[int] = None, - parallel: bool = False, - keep_running: bool = False + imageMetadataPath: str, + imageDirPath: str, + roiNames: Optional[str] = None, + pyradiomicsParamFilePath: Optional[str] = "src/readii/data/default_pyradiomics.yaml", + outputDirPath: Optional[str] = None, + negativeControl: Optional[str] = None, + randomSeed: Optional[int] = None, + parallel: bool = False, + keep_running: bool = False, ) -> pd.DataFrame: - """Perform radiomic feature extraction using PyRadiomics on CT images with a corresponding segmentation. - Utilizes outputs from med-imagetools (https://github.com/bhklab/med-imagetools) run on the image dataset. - - Parameters - ---------- - imageMetadataPath : str - Path to csv file created by matchCTtoSegmentation function that contains a CT and matching segmentation in each row. - imageDirPath : str - Path to the directory containing the directory of CT and segmentation images. This directory should contain the .imgtools directory from the med-imagetools run - and be the same as the input path used in med-imagetools - roiNames : str - Name pattern for the ROIs to load for the RTSTRUCTs. Can be None for DICOM SEG segmentations. - pyradiomicsParamFilePath : str - Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. - outputDirPath : str - Path to directory save the dataframe of extracted features to as a csv - negativeControl : str - Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. - randomSeed : int - Value to set random seed with for negative control creation to be reproducible. - parallel : bool - Flag to decide whether to run extraction in parallel. - keep_running : bool - Flag to keep pipeline running even when feature extraction for a patient fails. - Returns - ------- - pd.DataFrame - Dataframe containing the image metadata and extracted radiomic features. - """ - # Setting pyradiomics verbosity lower - radiomics_logger: logging.Logger = logging.getLogger("radiomics") - radiomics_logger.setLevel(logging.ERROR) - - # If no pyradiomics paramater file passed, use default - if pyradiomicsParamFilePath == None: - pyradiomicsParamFilePath = "./src/readii/data/default_pyradiomics.yaml" - - # Load in summary file generated by radiogenomic_pipeline - pdImageInfo = pd.read_csv(imageMetadataPath, header=0) - - # Get array of unique CT series' IDs to iterate over - ctSeriesIDList = pdImageInfo["series_CT"].unique() - - def featureExtraction(ctSeriesID): - """Function to extract PyRadiomics features for all ROIs present in a CT. Inner function so it can be run in parallel with joblib.""" - # Get all info rows for this ctSeries - - try: - ctSeriesInfo = pdImageInfo.loc[pdImageInfo["series_CT"] == ctSeriesID] - patID = ctSeriesInfo.iloc[0]["patient_ID"] - - logger.info(f"Processing {patID}") - - # Get absolute path to CT image files - ctDirPath = os.path.join(imageDirPath, ctSeriesInfo.iloc[0]["folder_CT"]) - # Load CT by passing in specific series to find in a directory - ctImage = read_dicom_series(path=ctDirPath, series_id=ctSeriesID) - - # Get list of segmentations to iterate over - segSeriesIDList = ctSeriesInfo["series_seg"].unique() - - # Initialize dictionary to store radiomics data for each segmentation (image metadata + features) - ctAllData = [] - - # Loop over every segmentation associated with this CT - only loading CT once - for segCount, segSeriesID in enumerate(segSeriesIDList): - segSeriesInfo = ctSeriesInfo.loc[ctSeriesInfo["series_seg"] == segSeriesID] - - # Check that a single segmentation file is being processed - if len(segSeriesInfo) > 1: - # Check that if there are multiple rows that it's not due to a CT with subseries (this is fine, the whole series is loaded) - if not segSeriesInfo.duplicated(subset=["series_CT"], keep=False).all(): - raise RuntimeError( - "Some kind of duplication of segmentation and CT matches not being caught. Check seg_and_ct_dicom_list in radiogenomic_output." - ) - - # Get absolute path to segmentation image file - segFilePath = os.path.join( - imageDirPath, segSeriesInfo.iloc[0]["file_path_seg"] - ) - # Get dictionary of ROI sitk Images for this segmentation file - segImages = loadSegmentation( - segFilePath, - modality=segSeriesInfo.iloc[0]["modality_seg"], - baseImageDirPath=ctDirPath, - roiNames=roiNames, - ) - - # Check that this series has ROIs to extract from (dictionary isn't empty) - if not segImages: - log_msg = f"CT {ctSeriesID} and segmentation {segSeriesID} has no ROIs or no ROIs with the label {roiNames}. Moving to next segmentation." - logger.warning(log_msg) - - else: - # Loop over each ROI contained in the segmentation to perform radiomic feature extraction - for roiCount, roiImageName in enumerate(segImages): - # ROI counter for image metadata output - roiNum = roiCount + 1 - - # Extract features listed in the parameter file - logger.info(f"Calculating radiomic features for segmentation: {roiImageName}") - - # Get sitk Image object for this ROI - roiImage = segImages[roiImageName] - - # Exception catch for if the segmentation dimensions do not match that original image - try: - # Check if segmentation just has an extra axis with a size of 1 and remove it - if roiImage.GetDimension() > 3 and roiImage.GetSize()[3] == 1: - roiImage = flattenImage(roiImage) - - # Check that image and segmentation mask have the same dimensions - if ctImage.GetSize() != roiImage.GetSize(): - # Checking if number of segmentation slices is less than CT - if ctImage.GetSize()[2] > roiImage.GetSize()[2]: - logger.warning( - f"Slice number mismatch between CT and segmentation for {patID}." - f"ctImage.GetSize(): {ctImage.GetSize()}" - f"roiImage.GetSize(): {roiImage.GetSize()}" - "Padding segmentation to match." - ) - from warnings import warn - from readii.image_processing import padSegToMatchCT - - try: - roiImage = padSegToMatchCT( - ctDirPath, segFilePath, ctImage, roiImage - ) - warn( - "padSegToMatchCT is deprecated and will be removed in a future version. " - "Please raise an issue on GitHub to discuss migration options.", - DeprecationWarning, - stacklevel=2 - ) - except Exception as e: - logger.error( - f"Error padding segmentation to match CT for {patID}: {e}" - ) - raise - logger.warning( - f"Padded segmentation to match CT for {patID}." - "roiImage.GetSize() after padding: {roiImage.GetSize()}" - ) - else: - raise RuntimeError( - "CT and ROI dimensions do not match." - ) - - # Catching CT and segmentation size mismatch error - except RuntimeError as e: - logger.error(str(e)) - - # Extract radiomic features from this CT/segmentation pair - idFeatureVector = singleRadiomicFeatureExtraction( - ctImage, - roiImage=roiImage, - pyradiomicsParamFilePath=pyradiomicsParamFilePath, - negativeControl=negativeControl, - randomSeed=randomSeed - ) - - # Create dictionary of image metadata to append to front of output table - sampleROIData = { - "patient_ID": patID, - "study_description": segSeriesInfo.iloc[0][ - "study_description_CT" - ], - "series_UID": segSeriesInfo.iloc[0]["series_CT"], - "series_description": segSeriesInfo.iloc[0][ - "series_description_CT" - ], - "image_modality": segSeriesInfo.iloc[0]["modality_CT"], - "instances": segSeriesInfo.iloc[0]["instances_CT"], - "seg_series_UID": segSeriesInfo.iloc[0]["series_seg"], - "seg_modality": segSeriesInfo.iloc[0]["modality_seg"], - "seg_ref_image": segSeriesInfo.iloc[0]["reference_ct_seg"], - "roi": roiImageName, - "roi_number": roiNum, - "negative_control": negativeControl, - } - - # Concatenate image metadata with PyRadiomics features - sampleROIData.update(idFeatureVector) - # Store this ROI's info in the segmentation level list - ctAllData.append(sampleROIData) - - return ctAllData - ###### END featureExtraction ####### - except Exception as e: - if keep_running: - logger.error(f"Error processing patient {patID}, series {ctSeriesID}: {e}") - # Log the error and continue without raising the exception - else: - # Raise the exception if keep_running is False - raise e - - # Extract radiomic features for each CT, get a list of dictionaries - # Each dictioary contains features for each ROI in a single CT - if not parallel: - # Run feature extraction over samples in sequence - will be slower - features = [featureExtraction(ctSeriesID) for ctSeriesID in ctSeriesIDList] - else: - # Run feature extraction in parallel - features = Parallel(n_jobs=-1, require="sharedmem")( - delayed(featureExtraction)(ctSeriesID) for ctSeriesID in ctSeriesIDList - ) - - - logger.info("Finished feature extraction.") - - # Filter out None and ensure each result is a list (even if it's empty) - features = [f if isinstance(f, list) else [f] for f in features if f is not None] - - # Flatten the list of dictionaries (happens when there are multiple ROIs or SEGs associated with a single CT) - flatFeatures = list(chain.from_iterable(features)) - # Convert list of feature sets into a pandas dataframe to save out - featuresTable = pd.DataFrame(flatFeatures) - - if outputDirPath != None: - if not os.path.exists(outputDirPath): - logger.info(f"Directory {outputDirPath} does not exist. Creating...") - os.makedirs(outputDirPath) - else: - logger.warning(f"Directory {outputDirPath} already exists. Will overwrite contents.") - - logger.info("Saving output to file...") - datasetName = imageMetadataPath.partition("match_list_")[2] - # Setup output file name with the dataset name as a suffix - if negativeControl == None: - outFileName = "radiomicfeatures_original_" + datasetName - else: - # Add negative control identifier to output file name - outFileName = "radiomicfeatures_" + negativeControl + "_" + datasetName - - # Join outputDirPath, a features directory, and the output file name - outputFilePath = os.path.join(outputDirPath, "features/", outFileName) - # Save out the features - saveDataframeCSV(featuresTable, outputFilePath) - - return featuresTable + """Perform radiomic feature extraction using PyRadiomics on CT images with a corresponding segmentation. + Utilizes outputs from med-imagetools (https://github.com/bhklab/med-imagetools) run on the image dataset. + + Parameters + ---------- + imageMetadataPath : str + Path to csv file created by matchCTtoSegmentation function that contains a CT and matching segmentation in each row. + imageDirPath : str + Path to the directory containing the directory of CT and segmentation images. This directory should contain the .imgtools directory from the med-imagetools run + and be the same as the input path used in med-imagetools + roiNames : str + Name pattern for the ROIs to load for the RTSTRUCTs. Can be None for DICOM SEG segmentations. + pyradiomicsParamFilePath : str + Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. + outputDirPath : str + Path to directory save the dataframe of extracted features to as a csv + negativeControl : str + Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. + randomSeed : int + Value to set random seed with for negative control creation to be reproducible. + parallel : bool + Flag to decide whether to run extraction in parallel. + keep_running : bool + Flag to keep pipeline running even when feature extraction for a patient fails. + Returns + ------- + pd.DataFrame + Dataframe containing the image metadata and extracted radiomic features. + """ + + dataset_directory = Path(imageDirPath) + + # Setting pyradiomics verbosity lower + radiomics_logger: logging.Logger = logging.getLogger("radiomics") + radiomics_logger.setLevel(logging.ERROR) + + # If no pyradiomics paramater file passed, use default + if pyradiomicsParamFilePath == None: + pyradiomicsParamFilePath = "./src/readii/data/default_pyradiomics.yaml" + + # Load in summary file generated by radiogenomic_pipeline + pdImageInfo = pd.read_csv(imageMetadataPath, header=0) + + # Get array of unique CT series' IDs to iterate over + ctSeriesIDList = pdImageInfo["series_CT"].unique() + + def featureExtraction(ctSeriesID): + """Function to extract PyRadiomics features for all ROIs present in a CT. Inner function so it can be run in parallel with joblib.""" + # Get all info rows for this ctSeries + + try: + ctSeriesInfo = pdImageInfo.loc[pdImageInfo["series_CT"] == ctSeriesID] + patID = ctSeriesInfo.iloc[0]["patient_ID"] + + logger.info(f"Processing {patID}") + + # Get absolute path to CT image files + ctDirPath = dataset_directory / ctSeriesInfo.iloc[0]["folder_CT"] + # Load CT by passing in specific series to find in a directory + ctImage = read_dicom_series(path=ctDirPath, series_id=ctSeriesID) + + # Get list of segmentations to iterate over + segSeriesIDList = ctSeriesInfo["series_seg"].unique() + + # Initialize dictionary to store radiomics data for each segmentation (image metadata + features) + ctAllData = [] + + # Loop over every segmentation associated with this CT - only loading CT once + for segCount, segSeriesID in enumerate(segSeriesIDList): + segSeriesInfo = ctSeriesInfo.loc[ctSeriesInfo["series_seg"] == segSeriesID] + + # Check that a single segmentation file is being processed + if len(segSeriesInfo) > 1: + # Check that if there are multiple rows that it's not due to a CT with subseries (this is fine, the whole series is loaded) + if not segSeriesInfo.duplicated(subset=["series_CT"], keep=False).all(): + raise RuntimeError( + "Some kind of duplication of segmentation and CT matches not being caught. Check seg_and_ct_dicom_list in radiogenomic_output." + ) + + # Get absolute path to segmentation image file + segFilePath = os.path.join(imageDirPath, segSeriesInfo.iloc[0]["file_path_seg"]) + # Get dictionary of ROI sitk Images for this segmentation file + segImages = loadSegmentation( + segFilePath, + modality=segSeriesInfo.iloc[0]["modality_seg"], + baseImageDirPath=ctDirPath, + roiNames=roiNames, + ) + + # Check that this series has ROIs to extract from (dictionary isn't empty) + if not segImages: + log_msg = f"CT {ctSeriesID} and segmentation {segSeriesID} has no ROIs or no ROIs with the label {roiNames}. Moving to next segmentation." + logger.warning(log_msg) + + else: + # Loop over each ROI contained in the segmentation to perform radiomic feature extraction + for roiCount, roiImageName in enumerate(segImages): + # ROI counter for image metadata output + roiNum = roiCount + 1 + + # Extract features listed in the parameter file + logger.info( + f"Calculating radiomic features for segmentation: {roiImageName}" + ) + + # Get sitk Image object for this ROI + roiImage = segImages[roiImageName] + + # Exception catch for if the segmentation dimensions do not match that original image + try: + # Check if segmentation just has an extra axis with a size of 1 and remove it + if roiImage.GetDimension() > 3 and roiImage.GetSize()[3] == 1: + roiImage = flattenImage(roiImage) + + # Check that image and segmentation mask have the same dimensions + if ctImage.GetSize() != roiImage.GetSize(): + # Checking if number of segmentation slices is less than CT + if ctImage.GetSize()[2] > roiImage.GetSize()[2]: + logger.warning( + f"Slice number mismatch between CT and segmentation for {patID}." + f"ctImage.GetSize(): {ctImage.GetSize()}" + f"roiImage.GetSize(): {roiImage.GetSize()}" + "Padding segmentation to match." + ) + from warnings import warn + + from readii.image_processing import padSegToMatchCT + + try: + roiImage = padSegToMatchCT( + ctDirPath, segFilePath, ctImage, roiImage + ) + warn( + "padSegToMatchCT is deprecated and will be removed in a future version. " + "Please raise an issue on GitHub to discuss migration options.", + DeprecationWarning, + stacklevel=2, + ) + except Exception as e: + logger.error( + f"Error padding segmentation to match CT for {patID}: {e}" + ) + raise + logger.warning( + f"Padded segmentation to match CT for {patID}." + "roiImage.GetSize() after padding: {roiImage.GetSize()}" + ) + else: + raise RuntimeError("CT and ROI dimensions do not match.") + + # Catching CT and segmentation size mismatch error + except RuntimeError as e: + logger.error(str(e)) + + # Extract radiomic features from this CT/segmentation pair + idFeatureVector = singleRadiomicFeatureExtraction( + ctImage, + roiImage=roiImage, + pyradiomicsParamFilePath=pyradiomicsParamFilePath, + negativeControl=negativeControl, + randomSeed=randomSeed, + ) + + # Create dictionary of image metadata to append to front of output table + sampleROIData = { + "patient_ID": patID, + "study_description": segSeriesInfo.iloc[0]["study_description_CT"], + "series_UID": segSeriesInfo.iloc[0]["series_CT"], + "series_description": segSeriesInfo.iloc[0]["series_description_CT"], + "image_modality": segSeriesInfo.iloc[0]["modality_CT"], + "instances": segSeriesInfo.iloc[0]["instances_CT"], + "seg_series_UID": segSeriesInfo.iloc[0]["series_seg"], + "seg_modality": segSeriesInfo.iloc[0]["modality_seg"], + "seg_ref_image": segSeriesInfo.iloc[0]["reference_ct_seg"], + "roi": roiImageName, + "roi_number": roiNum, + "negative_control": negativeControl, + } + + # Concatenate image metadata with PyRadiomics features + sampleROIData.update(idFeatureVector) + # Store this ROI's info in the segmentation level list + ctAllData.append(sampleROIData) + + return ctAllData + ###### END featureExtraction ####### + except Exception as e: + if keep_running: + logger.error(f"Error processing patient {patID}, series {ctSeriesID}: {e}") + # Log the error and continue without raising the exception + else: + # Raise the exception if keep_running is False + raise e + + # Extract radiomic features for each CT, get a list of dictionaries + # Each dictioary contains features for each ROI in a single CT + if not parallel: + # Run feature extraction over samples in sequence - will be slower + features = [featureExtraction(ctSeriesID) for ctSeriesID in ctSeriesIDList] + else: + # Run feature extraction in parallel + features = Parallel(n_jobs=-1, require="sharedmem")( + delayed(featureExtraction)(ctSeriesID) for ctSeriesID in ctSeriesIDList + ) + + # Filter out None and ensure each result is a list (even if it's empty) + features = [f for f in features if (isinstance(f, list) and len(f) > 0)] + + failed_features = [ctSeriesID for ctSeriesID, f in zip(ctSeriesIDList, features) if not f] + + logger.info("Finished feature extraction.", num_features=len(features)) + + if failed_features: + logger.warning( + f"Feature extraction failed for {len(failed_features)} samples. Series IDs: {failed_features}" + ) + + # Flatten the list of dictionaries (happens when there are multiple ROIs or SEGs associated with a single CT) + flatFeatures = list(chain.from_iterable(features)) + # Convert list of feature sets into a pandas dataframe to save out + featuresTable = pd.DataFrame(flatFeatures) + + if outputDirPath is None: + logger.info("No output directory specified. Returning features table.") + return featuresTable + + # Save out the features to a csv file + outputDir = Path(outputDirPath) + + if outputDir.exists(): + logger.warning(f"Directory {outputDirPath} already exists. Will overwrite contents.") + else: + logger.info(f"Directory {outputDirPath} does not exist. Creating...") + outputDir.mkdir(parents=True) + + datasetName = imageMetadataPath.partition("match_list_")[2] + + # Setup output file name with the dataset name as a suffix + outFileName = f"radiomicfeatures_{negativeControl or 'original'}_{datasetName}" + + outputFilePath = outputDir / f"{outFileName}.csv" + + logger.info("Saving output to file.", output_file=outputFilePath) + + # Save out the features + saveDataframeCSV(featuresTable, outputFilePath) + + return featuresTable From 1061d8464372c188fcf33ed54e1adddd2efc9c55 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 13:10:19 -0500 Subject: [PATCH 04/12] chore: change quote style from single to double in ruff configuration --- config/ruff.toml | 2 +- pixi.lock | 4453 ++++++++++++---------------------------------- 2 files changed, 1143 insertions(+), 3312 deletions(-) diff --git a/config/ruff.toml b/config/ruff.toml index 0e7f8b3..a0d707c 100644 --- a/config/ruff.toml +++ b/config/ruff.toml @@ -123,7 +123,7 @@ convention = "numpy" [format] -quote-style = "single" +quote-style = "double" indent-style = "tab" docstring-code-format = true docstring-code-line-length = 20 diff --git a/pixi.lock b/pixi.lock index 6de1345..4303f6f 100644 --- a/pixi.lock +++ b/pixi.lock @@ -1,4 +1,4 @@ -version: 5 +version: 6 environments: default: channels: @@ -2429,25 +2429,15 @@ environments: - 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zstd >=1.5.6,<1.6.0a0 + license: BSD-3-Clause + license_family: BSD + purls: + - pkg:pypi/zstandard?source=hash-mapping + size: 332271 + timestamp: 1725305847224 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstandard-0.23.0-py312h15fbf35_1.conda + sha256: d00ca25c1e28fd31199b26a94f8c96574475704a825d244d7a6351ad3745eeeb + md5: a4cde595509a7ad9c13b1a3809bcfe51 + depends: + - __osx >=11.0 - cffi >=1.11 - - libgcc >=13 - python >=3.12,<3.13.0a0 + - python >=3.12,<3.13.0a0 *_cpython - python_abi 3.12.* *_cp312 - zstd >=1.5.6,<1.5.7.0a0 - zstd >=1.5.6,<1.6.0a0 @@ -12205,14 +10046,9 @@ packages: license_family: BSD purls: - pkg:pypi/zstandard?source=hash-mapping - size: 419552 - timestamp: 1725305670210 -- kind: conda - name: zstd - version: 1.5.6 - build: ha6fb4c9_0 - subdir: linux-64 - url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.6-ha6fb4c9_0.conda + size: 330788 + timestamp: 1725305806565 +- conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.6-ha6fb4c9_0.conda sha256: c558b9cc01d9c1444031bd1ce4b9cff86f9085765f17627a6cd85fc623c8a02b md5: 4d056880988120e29d75bfff282e0f45 depends: @@ -12224,12 +10060,7 @@ packages: purls: [] size: 554846 timestamp: 1714722996770 -- kind: conda - name: zstd - version: 1.5.6 - build: hb46c0d2_0 - subdir: osx-arm64 - url: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.6-hb46c0d2_0.conda +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.6-hb46c0d2_0.conda sha256: 2d4fd1ff7ee79cd954ca8e81abf11d9d49954dd1fef80f27289e2402ae9c2e09 md5: d96942c06c3e84bfcc5efb038724a7fd depends: From 47b9325c17a4b6e73caf28e429455161ae29f676 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 13:16:21 -0500 Subject: [PATCH 05/12] refactor: improve docstring formatting and logging in feature extraction functions --- src/readii/feature_extraction.py | 62 ++++++++++++++++---------------- 1 file changed, 31 insertions(+), 31 deletions(-) diff --git a/src/readii/feature_extraction.py b/src/readii/feature_extraction.py index 51dbadd..b84bd5a 100644 --- a/src/readii/feature_extraction.py +++ b/src/readii/feature_extraction.py @@ -35,7 +35,7 @@ def generateNegativeControl( """Function to generate a negative control for a CT image based on the type of negative control specified. negativeControlType : str - This string is of the format {negativeControlType}_{negativeControlRegion} + This string is of the format {negativeControlType}_{negativeControlRegion} """ if "non_roi" in negativeControl: negativeControlType = negativeControl.rsplit("_", 2)[0] @@ -62,17 +62,13 @@ def cropImageAndMask( negativeControl: Optional[str], randomSeed: Optional[int], ) -> tuple[sitk.Image, sitk.Image]: - try: - if negativeControl is not None: - logger.info(f"Generating {negativeControl} negative control for CT.") - ctImage = generateNegativeControl(ctImage, negativeControl, alignedROIImage, randomSeed) + if negativeControl: + logger.info(f"Generating {negativeControl} negative control for CT.") + ctImage = generateNegativeControl(ctImage, negativeControl, alignedROIImage, randomSeed) - croppedCT, croppedROI = imageoperations.cropToTumorMask( - ctImage, alignedROIImage, segBoundingBox - ) - except Exception as e: - logger.error(f"Error cropping image and mask: {e}") - raise + croppedCT, croppedROI = imageoperations.cropToTumorMask( + ctImage, alignedROIImage, segBoundingBox + ) return croppedCT, croppedROI @@ -90,20 +86,20 @@ def singleRadiomicFeatureExtraction( Parameters ---------- ctImage : sitk.Image - CT image to perform feature extraction on. Will be cropped and potentially generate a negative control (see negativeControl arg) + CT image to perform feature extraction on. Will be cropped and potentially generate a negative control (see negativeControl arg) roiImage : sitk.Image - Region of interest (ROI) to extract radiomic features from within the CT. + Region of interest (ROI) to extract radiomic features from within the CT. pyradiomicsParamFilePath : str - Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. + Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. negativeControl : str - Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. + Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. randomSeed : int - Value to set random seed with for negative control creation to be reproducible. + Value to set random seed with for negative control creation to be reproducible. Returns ------- OrderedDict[Any, Any] - Dictionary containing image metadata, versions for key packages used for extraction, and radiomic features + Dictionary containing image metadata, versions for key packages used for extraction, and radiomic features """ # If no pyradiomics paramater file passed, use default if pyradiomicsParamFilePath == None: @@ -126,9 +122,13 @@ def singleRadiomicFeatureExtraction( if correctedROIImage is not None: alignedROIImage = correctedROIImage - croppedCT, croppedROI = cropImageAndMask( - ctImage, alignedROIImage, segBoundingBox, negativeControl, randomSeed - ) + try: + croppedCT, croppedROI = cropImageAndMask( + ctImage, alignedROIImage, segBoundingBox, negativeControl, randomSeed + ) + except Exception as e: + logger.exception(f"Error cropping CT and ROI for feature extraction: {e}") + raise e # Load PyRadiomics feature extraction parameters to use # Initialize feature extractor with parameters @@ -169,28 +169,28 @@ def radiomicFeatureExtraction( Parameters ---------- imageMetadataPath : str - Path to csv file created by matchCTtoSegmentation function that contains a CT and matching segmentation in each row. + Path to csv file created by matchCTtoSegmentation function that contains a CT and matching segmentation in each row. imageDirPath : str - Path to the directory containing the directory of CT and segmentation images. This directory should contain the .imgtools directory from the med-imagetools run - and be the same as the input path used in med-imagetools + Path to the directory containing the directory of CT and segmentation images. This directory should contain the .imgtools directory from the med-imagetools run + and be the same as the input path used in med-imagetools roiNames : str - Name pattern for the ROIs to load for the RTSTRUCTs. Can be None for DICOM SEG segmentations. + Name pattern for the ROIs to load for the RTSTRUCTs. Can be None for DICOM SEG segmentations. pyradiomicsParamFilePath : str - Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. + Path to file containing configuration settings for pyradiomics feature extraction. Will use the provided config file in 'data/' by default if no file passed in. outputDirPath : str - Path to directory save the dataframe of extracted features to as a csv + Path to directory save the dataframe of extracted features to as a csv negativeControl : str - Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. + Name of negative control to generate from the CT to perform feature extraction on. If set to None, will extract features from original CT image. randomSeed : int - Value to set random seed with for negative control creation to be reproducible. + Value to set random seed with for negative control creation to be reproducible. parallel : bool - Flag to decide whether to run extraction in parallel. + Flag to decide whether to run extraction in parallel. keep_running : bool - Flag to keep pipeline running even when feature extraction for a patient fails. + Flag to keep pipeline running even when feature extraction for a patient fails. Returns ------- pd.DataFrame - Dataframe containing the image metadata and extracted radiomic features. + Dataframe containing the image metadata and extracted radiomic features. """ dataset_directory = Path(imageDirPath) From 44e95c5802e48b0f105ffb6b69b79e869715baa9 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 13:29:38 -0500 Subject: [PATCH 06/12] fix: remove unintentiaonal exclude of loaders.py --- config/ruff.toml | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/config/ruff.toml b/config/ruff.toml index a0d707c..bdd86f9 100644 --- a/config/ruff.toml +++ b/config/ruff.toml @@ -10,11 +10,9 @@ extend-exclude = [ "tests/*", ".pixi/", "src/readii/image_processing.py", - "src/readii/loaders.py", "src/readii/metadata.py", "src/readii/negative_controls.py", - "src/readii/pipeline.py", -] + "src/readii/pipeline.py",] # Same as Black. line-length = 100 From df8e46f65d6f6e735fc771c9b6e64c038c4e36b0 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:02:51 -0500 Subject: [PATCH 07/12] fix: update pixi-version to v0.38.0 in CI/CD workflow --- .github/workflows/ci-cd.yml | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/ci-cd.yml b/.github/workflows/ci-cd.yml index 25aaaea..548c71b 100644 --- a/.github/workflows/ci-cd.yml +++ b/.github/workflows/ci-cd.yml @@ -26,7 +26,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ matrix.env }} - pixi-version: v0.33.0 + pixi-version: v0.38.0 cache: true locked: false # wont be the same because of the tag @@ -84,7 +84,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.33.0 + pixi-version: v0.38.0 cache: true locked: false @@ -139,7 +139,7 @@ jobs: RUNNER_DEBUG: true with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.33.0 + pixi-version: v0.38.0 cache: true locked: false # cache-key: pixi-ENV_${{ env.PIXI_ENV }}- @@ -184,7 +184,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.33.0 + pixi-version: v0.38.0 cache: true locked: false # wont be the same because of the tag @@ -215,7 +215,7 @@ jobs: # uses: prefix-dev/setup-pixi@v0.8.1 # with: # environments: ${{ env.PIXI_ENV }} - # pixi-version: v0.33.0 + # pixi-version: v0.38.0 # cache: true # locked: false # wont be the same because of the tag From 8c9b0c636afc6c5ad97c9cc27f5aefa27f69b811 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:03:58 -0500 Subject: [PATCH 08/12] fix: update pixi-version to v0.39.0 in CI/CD workflow --- .github/workflows/ci-cd.yml | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/ci-cd.yml b/.github/workflows/ci-cd.yml index 548c71b..bd7fe6f 100644 --- a/.github/workflows/ci-cd.yml +++ b/.github/workflows/ci-cd.yml @@ -26,7 +26,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ matrix.env }} - pixi-version: v0.38.0 + pixi-version: v0.39.0 cache: true locked: false # wont be the same because of the tag @@ -84,7 +84,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.38.0 + pixi-version: v0.39.0 cache: true locked: false @@ -139,7 +139,7 @@ jobs: RUNNER_DEBUG: true with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.38.0 + pixi-version: v0.39.0 cache: true locked: false # cache-key: pixi-ENV_${{ env.PIXI_ENV }}- @@ -184,7 +184,7 @@ jobs: uses: prefix-dev/setup-pixi@v0.8.1 with: environments: ${{ env.PIXI_ENV }} - pixi-version: v0.38.0 + pixi-version: v0.39.0 cache: true locked: false # wont be the same because of the tag @@ -215,7 +215,7 @@ jobs: # uses: prefix-dev/setup-pixi@v0.8.1 # with: # environments: ${{ env.PIXI_ENV }} - # pixi-version: v0.38.0 + # pixi-version: v0.39.0 # cache: true # locked: false # wont be the same because of the tag From d0175f9947ff85e08803f3791c63d56c7fcd643e Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:12:13 -0500 Subject: [PATCH 09/12] fix: update saveDataframeCSV to accept Path type for outputFilePath --- src/readii/metadata.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/src/readii/metadata.py b/src/readii/metadata.py index ebe9018..c85bd78 100644 --- a/src/readii/metadata.py +++ b/src/readii/metadata.py @@ -2,6 +2,7 @@ import pandas as pd from typing import Optional, Literal from readii.utils import logger +from pathlib import Path def createImageMetadataFile(outputDir, parentDirPath, datasetName, segType, imageFileListPath, update = False): imageMetadataPath = os.path.join(outputDir, "ct_to_seg_match_list_" + datasetName + ".csv") @@ -29,7 +30,7 @@ def createImageMetadataFile(outputDir, parentDirPath, datasetName, segType, imag def saveDataframeCSV( dataframe: pd.DataFrame, - outputFilePath: str + outputFilePath: str | Path ) -> None: """Function to save a pandas Dataframe as a csv file with the index removed. Checks if the path in the outputFilePath exists and will create any missing directories. @@ -38,7 +39,7 @@ def saveDataframeCSV( ---------- dataframe : pd.DataFrame Pandas dataframe to save out as a csv - outputFilePath : str + outputFilePath : str | Path Full file path to save the dataframe out to. Raises @@ -47,8 +48,9 @@ def saveDataframeCSV( If the outputFilePath does not end in .csv, if the dataframe is not a pandas DataFrame, or if an error occurs while saving the dataframe. """ - - if not outputFilePath.endswith(".csv"): + outputFilePath = Path(outputFilePath) + + if not outputFilePath.suffix == ".csv": raise ValueError( "This function saves .csv files, so outputFilePath must end in .csv" ) @@ -57,7 +59,7 @@ def saveDataframeCSV( raise ValueError("Function expects a pandas DataFrame to save out.") # Make directory if it doesn't exist, but don't fail if it already exists - os.makedirs(os.path.dirname(outputFilePath), exist_ok=True) + outputFilePath.parent.mkdir(parents=True, exist_ok=True) try: # Save out DataFrame From a5767a6cf8b27bd9a81e2a722b2ed85134587545 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:14:12 -0500 Subject: [PATCH 10/12] temp ignore ruff --- config/ruff.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/config/ruff.toml b/config/ruff.toml index bdd86f9..9bd8c97 100644 --- a/config/ruff.toml +++ b/config/ruff.toml @@ -1,6 +1,6 @@ include = [ - "src/readii/loaders.py", - "src/readii/feature_extraction.py" + # "src/readii/loaders.py", + # "src/readii/feature_extraction.py" ] From 613fcdc1cfd12439af533390a09cd257d35ffa1d Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:19:05 -0500 Subject: [PATCH 11/12] fix: dont add .csv to path --- src/readii/feature_extraction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/readii/feature_extraction.py b/src/readii/feature_extraction.py index b84bd5a..a7b8323 100644 --- a/src/readii/feature_extraction.py +++ b/src/readii/feature_extraction.py @@ -403,7 +403,7 @@ def featureExtraction(ctSeriesID): # Setup output file name with the dataset name as a suffix outFileName = f"radiomicfeatures_{negativeControl or 'original'}_{datasetName}" - outputFilePath = outputDir / f"{outFileName}.csv" + outputFilePath = outputDir / outFileName logger.info("Saving output to file.", output_file=outputFilePath) From 7f78be730279f530be1bfbca8e6915ec7d127c66 Mon Sep 17 00:00:00 2001 From: Jermiah Joseph Date: Mon, 2 Dec 2024 17:20:55 -0500 Subject: [PATCH 12/12] fix: update output file path structure for feature extraction --- src/readii/feature_extraction.py | 2 +- tests/test_feature_extraction.py | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/src/readii/feature_extraction.py b/src/readii/feature_extraction.py index a7b8323..4c559a6 100644 --- a/src/readii/feature_extraction.py +++ b/src/readii/feature_extraction.py @@ -403,7 +403,7 @@ def featureExtraction(ctSeriesID): # Setup output file name with the dataset name as a suffix outFileName = f"radiomicfeatures_{negativeControl or 'original'}_{datasetName}" - outputFilePath = outputDir / outFileName + outputFilePath = outputDir / "features" / outFileName logger.info("Saving output to file.", output_file=outputFilePath) diff --git a/tests/test_feature_extraction.py b/tests/test_feature_extraction.py index 879b2e3..9f63ae3 100644 --- a/tests/test_feature_extraction.py +++ b/tests/test_feature_extraction.py @@ -114,4 +114,5 @@ def test_radiomicFeatureExtraction_output(nsclcMetadataPath): imageDirPath = "tests/", roiNames = None, outputDirPath = "tests/output/") - assert os.path.exists("tests/output/features/radiomicfeatures_original_NSCLC_Radiogenomics.csv") \ No newline at end of file + expected_path = "tests/output/features/radiomicfeatures_original_NSCLC_Radiogenomics.csv" + assert os.path.exists(expected_path) \ No newline at end of file