diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
new file mode 100644
index 0000000..71cda43
--- /dev/null
+++ b/.github/workflows/tests.yml
@@ -0,0 +1,41 @@
+name: pVACcompare tests
+
+on:
+ push:
+ branches:
+ - main
+ pull_request:
+ branches:
+ - main
+
+jobs:
+ test:
+ runs-on: ubuntu-latest
+ strategy:
+ matrix:
+ python-version: ['3.9', '3.10']
+
+ steps:
+ - name: Checkout code
+ uses: actions/checkout@v4
+
+ - name: Set up Python
+ uses: actions/setup-python@v4
+ with:
+ python-version: ${{ matrix.python-version }}
+
+ - name: Install dependencies
+ run: |
+ python -m pip install --upgrade pip
+ pip install -r requirements.txt
+ pip install coverage
+
+ - name: Change working directory and run tests with coverage
+ run: |
+ cd pvaccompare
+ coverage run -m unittest discover tests/
+
+ - name: Generate coverage report
+ run: |
+ cd pvaccompare
+ coverage report
\ No newline at end of file
diff --git a/README.md b/README.md
index 61e1a9d..7ac7e9d 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,36 @@
# pVACcompare
+pVACcompare is a file comparison suite built for comparing results generated by [pVACtools](https://github.com/griffithlab/pVACtools) or the [GriffithLab](https://github.com/griffithlab) immuno pipeline. Comparison can be specified for MHC Class I results, MHC Class II results, or both. In its current state the following files are included in the comparison:
+- log/inputs.yml
+- all_epitopes.tsv
+- all_epitopes.aggregated.tsv
+- all_epitopes.aggregated.tsv.reference_matches
+- all_epitopes.aggregated.metrics.json (inputs only)
+## Installation
+pVACcompare is written for Linux, other operating systems have not been tested. pVACcompare has been tested with Python 3.9 and 3.10. Other versions may work, but have not been tested.
+### Dependencies
+To install dependencies navigate inside the repository after cloning and run:
+```bash
+pip3 install -r requirements.txt
+```
+## Usage
+pVACcompare offers several parameters that allow the user to have control of the comparisons. Running the following in the terminal will display the help menu with all of the available parameters and options:
+```bash
+python3 run.py -h
+```
+An example of running the tool likes like the following:
+```bash
+python3 run.py --pvactools_release --output_dir path/to/output/directory --mhc_class 1 --aggregated_columns 'Best Peptide', 'Best Transcript' version1/result version2/result
+```
+**Note**: You must specify if the results are from pVACtools or the immuno pipeline. All columns specified must be in quotes and comma separated. If you do not specify MHC Class, the tool will include both in the report. A list of available columns is displayed in the help menu.
+The above command will perform a MHC Class I output comparison between two result folders generated by pVACtools only with the specified columns included in the aggregated tsv comparison. Columns for the unaggregated tsv comparison and reference match tsv comparison were not specified, so the default columns will be used. Results will be generated in the specified output directory. If an output directory is not specified, one will be created inside ```pvaccompare/```.
+## Viewing Results
+After completing a run, a results folder containing the JSON files generated by the tool will be created in the output directory. pVACcompare provides an organized HTML report for efficient parsing and visualization of results. To view the HTML report:
+1. Navigate to the ```pvaccompare/``` directory.
+2. Run the following command to start the local server:
+```bash
+python3 server.py
+```
+3. The server will output a link where you can access the report. Open this link in your browser to view the available results.
+Once on the report page:
+ - Select the results directory you'd like to explore.
+ - To return to the directory selection screen, click **pVACcompare** in the navigation bar.
\ No newline at end of file
diff --git a/pvaccompare/compare_tools/__init__.py b/pvaccompare/compare_tools/__init__.py
new file mode 100644
index 0000000..ad62453
--- /dev/null
+++ b/pvaccompare/compare_tools/__init__.py
@@ -0,0 +1,2 @@
+from .comparison_router import run_comparison, prepare_results_folder
+from .validators import *
diff --git a/pvaccompare/compare_tools/comparison_router.py b/pvaccompare/compare_tools/comparison_router.py
new file mode 100644
index 0000000..67b683a
--- /dev/null
+++ b/pvaccompare/compare_tools/comparison_router.py
@@ -0,0 +1,201 @@
+import glob
+import os
+import shutil
+import logging
+from datetime import datetime
+from runners import *
+
+
+def find_file(results_folder, subfolder, pattern):
+ """
+ Purpose: Attempts to locate the files needed for each comparison
+ Modifies: Nothing
+ Returns: A string of the file path
+ """
+ search_path = os.path.join(results_folder, subfolder, pattern)
+ files = glob.glob(search_path, recursive=True)
+ return files[0] if files else None
+
+
+def prepare_results_folder(classes, base_output_dir):
+ timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+ unique_output_dir = f"{base_output_dir}/results_{timestamp}"
+
+ os.makedirs(unique_output_dir)
+
+ if "1" in classes:
+ os.makedirs(f"{unique_output_dir}/mhc_class_i")
+ if "2" in classes:
+ os.makedirs(f"{unique_output_dir}/mhc_class_ii")
+
+ return unique_output_dir
+
+
+def run_comparison(
+ class_type,
+ prefix,
+ results_folder1,
+ results_folder2,
+ output_dir,
+ aggregated_columns,
+ unaggregated_columns,
+ reference_match_columns,
+):
+ """
+ Purpose: Runs all of the different comparisons
+ Modifies: Nothing
+ Returns: None
+ """
+ output_path = (
+ f'{output_dir}/{"mhc_class_i" if class_type == "1" else "mhc_class_ii"}'
+ )
+
+ if "pVACseq" not in prefix:
+ yml1_path = find_file(results_folder1, prefix + "/log", "inputs.yml")
+ yml2_path = find_file(results_folder2, prefix + "/log", "inputs.yml")
+ if yml1_path and yml2_path:
+ logging.info("Running the input YML comparison tool...")
+ run_compare_yml(yml1_path, yml2_path, output_path, class_type)
+ logging.info("\u2713 Comparison completed successfully.")
+ else:
+ if yml1_path:
+ logging.error(
+ "ERROR: Could not locate the input YML file in results folder 2 for %s.",
+ prefix,
+ )
+ elif yml2_path:
+ logging.error(
+ "ERROR: Could not locate the input YML file in results folder 1 for %s.",
+ prefix,
+ )
+ else:
+ logging.error(
+ "ERROR: Could not locate the input YML file in either results folder for %s.",
+ prefix,
+ )
+
+ logging.info("\u2716 Comparison skipped.")
+ else:
+ logging.info("Input YML files are not included in immuno pipeline results")
+ logging.info("\u2716 Comparison skipped.")
+
+ json1_path = find_file(
+ results_folder1, prefix + "/", "*all_epitopes.aggregated.metrics.json"
+ )
+ json2_path = find_file(
+ results_folder2, prefix + "/", "*all_epitopes.aggregated.metrics.json"
+ )
+ if json1_path and json2_path:
+ logging.info("\nRunning the metrics JSON comparison tool...")
+ run_compare_json(json1_path, json2_path, output_path, class_type)
+ logging.info("\u2713 Comparison completed successfully.")
+ else:
+ if json1_path:
+ logging.error(
+ "ERROR: Could not locate the metrics JSON file in results folder 2 for %s.",
+ prefix,
+ )
+ elif json2_path:
+ logging.error(
+ "ERROR: Could not locate the metrics JSON file in results folder 1 for %s.",
+ prefix,
+ )
+ else:
+ logging.error(
+ "ERROR: Could not locate the metrics JSON file in either results folder for %s.",
+ prefix,
+ )
+ logging.info("\u2716 Comparison skipped.")
+
+ agg_tsv1_path = find_file(
+ results_folder1, prefix + "/", "*all_epitopes.aggregated.tsv"
+ )
+ agg_tsv2_path = find_file(
+ results_folder2, prefix + "/", "*all_epitopes.aggregated.tsv"
+ )
+ if agg_tsv1_path and agg_tsv2_path:
+ logging.info("\nRunning the aggregated TSV comparison tool...")
+ run_compare_aggregated_tsv(
+ agg_tsv1_path, agg_tsv2_path, aggregated_columns, output_path, class_type
+ )
+ logging.info("\u2713 Comparison completed successfully.")
+ else:
+ if agg_tsv1_path:
+ logging.error(
+ "ERROR: Could not locate the aggregated TSV file in results folder 2 for %s.",
+ prefix,
+ )
+ elif agg_tsv2_path:
+ logging.error(
+ "ERROR: Could not locate the aggregated TSV file in results folder 1 for %s.",
+ prefix,
+ )
+ else:
+ logging.error(
+ "ERROR: Could not locate the aggregated TSV file in either results folder for %s.",
+ prefix,
+ )
+ logging.info("\u2716 Comparison skipped.")
+
+ unagg_tsv1_path = find_file(results_folder1, prefix + "/", "*all_epitopes.tsv")
+ unagg_tsv2_path = find_file(results_folder2, prefix + "/", "*all_epitopes.tsv")
+ if unagg_tsv1_path and unagg_tsv2_path:
+ logging.info("\nRunning the unaggregated TSV comparison tool...")
+ run_compare_unaggregated_tsv(
+ unagg_tsv1_path,
+ unagg_tsv2_path,
+ unaggregated_columns,
+ output_path,
+ class_type,
+ )
+ logging.info("\u2713 Comparison completed successfully.")
+ else:
+ if unagg_tsv1_path:
+ logging.error(
+ "ERROR: Could not locate the unaggregated TSV file in results folder 2 for %s.",
+ prefix,
+ )
+ elif unagg_tsv2_path:
+ logging.error(
+ "ERROR: Could not locate the unaggregated TSV file in results folder 1 for %s.",
+ prefix,
+ )
+ else:
+ logging.error(
+ "ERROR: Could not locate the unaggregated TSV file in either results folder for %s.",
+ prefix,
+ )
+ logging.info("\u2716 Comparison skipped.")
+
+ refmatch_tsv1_path = find_file(results_folder1, prefix + "/", "*.reference_matches")
+ refmatch_tsv2_path = find_file(results_folder2, prefix + "/", "*.reference_matches")
+ if refmatch_tsv1_path and refmatch_tsv2_path:
+ logging.info("\nRunning the reference match TSV comparison tool...")
+ run_compare_reference_matches_tsv(
+ refmatch_tsv1_path,
+ refmatch_tsv2_path,
+ reference_match_columns,
+ output_path,
+ class_type,
+ )
+ logging.info("\u2713 Comparison completed successfully.")
+ else:
+ if refmatch_tsv1_path:
+ logging.error(
+ "ERROR: Could not locate the reference match TSV file in results folder 2 for %s.",
+ prefix,
+ )
+ elif refmatch_tsv2_path:
+ logging.error(
+ "ERROR: Could not locate the reference match TSV file in results folder 1 for %s.",
+ prefix,
+ )
+ else:
+ logging.error(
+ "ERROR: Could not locate the reference match TSV file in either results folder for %s.",
+ prefix,
+ )
+ logging.info("\u2716 Comparison skipped.")
+ logging.info("\n" + "\u2500" * 55)
+ logging.info("Successfully generated %s comparison report.", prefix)
+ logging.info("\u2500" * 55)
diff --git a/pvaccompare/compare_tools/validators.py b/pvaccompare/compare_tools/validators.py
new file mode 100644
index 0000000..fe63d5e
--- /dev/null
+++ b/pvaccompare/compare_tools/validators.py
@@ -0,0 +1,121 @@
+def validate_aggregated_columns(aggregated_columns, parser):
+ """
+ Purpose: Makes sure the user inputs valid aggregated tsv columns
+ Modifies: Nothing
+ Returns: None
+ """
+ valid_aggregated_columns = [
+ "Gene",
+ "AA Change",
+ "Num Passing Transcripts",
+ "Best Peptide",
+ "Best Transcript",
+ "Num Passing Peptides",
+ "IC50 MT",
+ "IC50 WT",
+ "%ile MT",
+ "%ile WT",
+ "RNA Expr",
+ "RNA VAF",
+ "DNA VAF",
+ "Tier",
+ ]
+ for col in aggregated_columns:
+ if col not in valid_aggregated_columns:
+ parser.error(
+ f"Invalid aggregated column '{col}' specified.\nValid columns are: {', '.join(valid_aggregated_columns)}"
+ )
+
+
+def validate_unaggregated_columns(unaggregated_columns, parser):
+ """
+ Purpose: Makes sure the user inputs valid unaggregated tsv columns
+ Modifies: Nothing
+ Returns: None
+ """
+ valid_unaggregated_columns = [
+ "Biotype",
+ "Sub-peptide Position",
+ "Median MT IC50 Score",
+ "Median WT IC50 Score",
+ "Median MT Percentile",
+ "Median WT Percentile",
+ "WT Epitope Seq",
+ "Tumor DNA VAF",
+ "Tumor RNA Depth",
+ "Tumor RNA VAF",
+ "Gene Expression",
+ "BigMHC_EL WT Score",
+ "BigMHC_EL MT Score",
+ "BigMHC_IM WT Score",
+ "BigMHC_IM MT Score",
+ "MHCflurryEL Processing WT Score",
+ "MHCflurryEL Processing MT Score",
+ "MHCflurryEL Presentation WT Score",
+ "MHCflurryEL Presentation MT Score",
+ "MHCflurryEL Presentation WT Percentile",
+ "MHCflurryEL Presentation MT Percentile",
+ "MHCflurry WT IC50 Score",
+ "MHCflurry MT IC50 Score",
+ "MHCflurry WT Percentile",
+ "MHCflurry MT Percentile",
+ "MHCnuggetsI WT IC50 Score",
+ "MHCnuggetsI MT IC50 Score",
+ "MHCnuggetsI WT Percentile",
+ "MHCnuggetsI MT Percentile",
+ "NetMHC WT IC50 Score",
+ "NetMHC MT IC50 Score",
+ "NetMHC WT Percentile",
+ "NetMHC MT Percentile",
+ "NetMHCcons WT IC50 Score",
+ "NetMHCcons MT IC50 Score",
+ "NetMHCcons WT Percentile",
+ "NetMHCcons MT Percentile",
+ "NetMHCpan WT IC50 Score",
+ "NetMHCpan MT IC50 Score",
+ "NetMHCpan WT Percentile",
+ "NetMHCpan MT Percentile",
+ "NetMHCpanEL WT Score",
+ "NetMHCpanEL MT Score",
+ "NetMHCpanEL WT Percentile",
+ "NetMHCpanEL MT Percentile",
+ "PickPocket WT IC50 Score",
+ "PickPocket MT IC50 Score",
+ "PickPocket WT Percentile",
+ "PickPocket MT Percentile",
+ "SMM WT IC50 Score",
+ "SMM MT IC50 Score",
+ "SMM WT Percentile",
+ "SMM MT Percentile",
+ "SMMPMBEC WT IC50 Score",
+ "SMMPMBEC MT IC50 Score",
+ "SMMPMBEC WT Percentile",
+ "SMMPMBEC MT Percentile",
+ "DeepImmuno WT Score",
+ "DeepImmuno MT Score",
+ "Problematic Positions",
+ ]
+ for col in unaggregated_columns:
+ if col not in valid_unaggregated_columns:
+ parser.error(
+ f"Invalid unaggregated column '{col}' specified.\nValid columns are: {', '.join(valid_unaggregated_columns)}"
+ )
+
+
+def validate_reference_match_columns(reference_match_columns, parser):
+ """
+ Purpose: Makes sure the user inputs valid reference match tsv columns
+ Modifies: Nothing
+ Returns: None
+ """
+ valid_reference_match_columns = [
+ "Peptide",
+ "Hit Definition",
+ "Match Window",
+ "Match Sequence",
+ ]
+ for col in reference_match_columns:
+ if col not in valid_reference_match_columns:
+ parser.error(
+ f"Invalid reference match column '{col}' specified.\nValid columns are: {', '.join(valid_reference_match_columns)}"
+ )
diff --git a/pvaccompare/comparisons/__init__.py b/pvaccompare/comparisons/__init__.py
new file mode 100644
index 0000000..8c6ab8e
--- /dev/null
+++ b/pvaccompare/comparisons/__init__.py
@@ -0,0 +1,5 @@
+from .compare_aggregated_tsv import CompareAggregatedTSV
+from .compare_json import CompareJSON
+from .compare_reference_matches_tsv import CompareReferenceMatchesTSV
+from .compare_unaggregated_tsv import CompareUnaggregatedTSV
+from .compare_yml import CompareYML
diff --git a/pvaccompare/comparisons/compare_aggregated_tsv.py b/pvaccompare/comparisons/compare_aggregated_tsv.py
new file mode 100644
index 0000000..a3e17ac
--- /dev/null
+++ b/pvaccompare/comparisons/compare_aggregated_tsv.py
@@ -0,0 +1,52 @@
+from run_utils import *
+import logging
+
+
+class CompareAggregatedTSV:
+ def __init__(self, input_file1, input_file2, columns_to_compare):
+ self.input_file1 = input_file1
+ self.input_file2 = input_file2
+ self.df1, self.df2 = load_tsv_files(self.input_file1, self.input_file2)
+ self.contains_id = True
+ self.replaced_id = False
+ self.ID_replacement_cols = ["Gene", "AA Change"]
+ self.columns_to_compare = columns_to_compare
+
+ def check_id(self):
+ """
+ Purpose: Replace ID with Gene-AA_change if needed
+ Modifies: self.contains_id, self.replaced_id
+ Returns: None
+ """
+ if "ID" not in self.df1.columns or "ID" not in self.df2.columns:
+ self.contains_id = False
+ can_replace = True
+ for col in self.ID_replacement_cols:
+ if col not in self.df1.columns or col not in self.df2.columns:
+ can_replace = False
+ if can_replace:
+ self.combine_gene_and_AA_change()
+ logging.info("\u2022 Replaced ID with Gene and AA Change")
+ self.replaced_id = True
+
+ def combine_gene_and_AA_change(self):
+ """
+ Purpose: Combines Gene and AA_Change into a singular unique ID column in both dataframes
+ Modifies: df1 and df2
+ Returns: None
+ """
+ self.df1["ID"] = (
+ self.df1[self.ID_replacement_cols[0]].astype(str)
+ + " ("
+ + self.df1[self.ID_replacement_cols[1]].astype(str)
+ + ")"
+ )
+ self.df2["ID"] = (
+ self.df2[self.ID_replacement_cols[0]].astype(str)
+ + " ("
+ + self.df2[self.ID_replacement_cols[1]].astype(str)
+ + ")"
+ )
+
+ self.df1.drop(columns=self.ID_replacement_cols, inplace=True)
+ self.df2.drop(columns=self.ID_replacement_cols, inplace=True)
diff --git a/pvaccompare/comparisons/compare_json.py b/pvaccompare/comparisons/compare_json.py
new file mode 100644
index 0000000..04efa90
--- /dev/null
+++ b/pvaccompare/comparisons/compare_json.py
@@ -0,0 +1,70 @@
+import json
+
+
+class CompareJSON:
+ def __init__(self, input_file1, input_file2):
+ self.input_file1 = input_file1
+ self.input_file2 = input_file2
+ self.json1, self.json2 = self.load_files()
+ self.differences = {}
+
+ def load_files(self):
+ """
+ Purpose: Load the two json metrics files into dictionaries
+ Modifies: Nothing
+ Returns: Two dictionaries corresponding to the two input files
+ """
+ with open(self.input_file1) as f1, open(self.input_file2) as f2:
+ json1 = json.load(f1)
+ json2 = json.load(f2)
+ return json1, json2
+
+ @staticmethod
+ def filter_chr_keys(data):
+ """
+ Purpose: Filter the data to remove everything except the inputs
+ Modifies: Nothing
+ Returns: Filtered data
+ """
+ if isinstance(data, dict):
+ return {
+ k: CompareJSON.filter_chr_keys(v)
+ for k, v in data.items()
+ if not k.startswith("chr")
+ }
+ elif isinstance(data, list):
+ return [CompareJSON.filter_chr_keys(item) for item in data]
+ else:
+ return data
+
+ def compare_metric_data(self):
+ """
+ Purpose: Get and store all of the differences
+ Modifies: self.differences
+ Returns: None
+ """
+ filtered_data1 = self.filter_chr_keys(self.json1)
+ filtered_data2 = self.filter_chr_keys(self.json2)
+
+ differences = {
+ "Shared Fields": sorted(
+ k for k in filtered_data1.keys() if k in filtered_data2
+ ),
+ "Fields Unique to File 1": {
+ k: v
+ for k, v in sorted(filtered_data1.items())
+ if k not in filtered_data2
+ },
+ "Fields Unique to File 2": {
+ k: v
+ for k, v in sorted(filtered_data2.items())
+ if k not in filtered_data1
+ },
+ "Values Changed": {
+ k: f"{filtered_data1[k]} -> {filtered_data2[k]}"
+ for k in sorted(filtered_data1)
+ if k in filtered_data2 and filtered_data1[k] != filtered_data2[k]
+ },
+ }
+ if any(key != "Shared Fields" and differences[key] for key in differences):
+ self.differences = differences
diff --git a/pvaccompare/comparisons/compare_reference_matches_tsv.py b/pvaccompare/comparisons/compare_reference_matches_tsv.py
new file mode 100644
index 0000000..9a693f2
--- /dev/null
+++ b/pvaccompare/comparisons/compare_reference_matches_tsv.py
@@ -0,0 +1,85 @@
+from run_utils import *
+import logging
+
+
+class CompareReferenceMatchesTSV:
+ def __init__(self, input_file1, input_file2, columns_to_compare):
+ self.input_file1 = input_file1
+ self.input_file2 = input_file2
+ self.df1, self.df2 = load_tsv_files(self.input_file1, self.input_file2)
+ self.columns_to_compare = columns_to_compare
+ self.run_notes = []
+ self.hits_file1 = {}
+ self.hits_file2 = {}
+
+ def create_id_column(self):
+ """
+ Purpose: Combines multiple columns into a singular unique ID column in both dataframes
+ Modifies: df1 and df2
+ Returns: None
+ """
+ id_columns = [
+ "Chromosome",
+ "Start",
+ "Stop",
+ "Reference",
+ "Variant",
+ "Transcript",
+ "MT Epitope Seq",
+ "Hit ID",
+ "Match Start",
+ "Match Stop",
+ ]
+ self.df1["ID"] = self.df1[id_columns].apply(
+ lambda x: "-".join(map(str, x)), axis=1
+ )
+ self.df2["ID"] = self.df2[id_columns].apply(
+ lambda x: "-".join(map(str, x)), axis=1
+ )
+
+ self.df1.drop(columns=id_columns, inplace=True)
+ self.df2.drop(columns=id_columns, inplace=True)
+
+ def check_duplicate_ids(self):
+ """
+ Purpose: Checks if duplicate IDs exist in either dataframe
+ Modifies: Nothing
+ Returns: Boolean value
+ """
+ self.hits_file1 = self.df1["ID"].value_counts().to_dict()
+ self.hits_file2 = self.df2["ID"].value_counts().to_dict()
+
+ max_hits_file1 = max(self.hits_file1.values(), default=0)
+ max_hits_file2 = max(self.hits_file2.values(), default=0)
+
+ if max_hits_file1 > 1 or max_hits_file2 > 1:
+ if max_hits_file1 > 1 and max_hits_file2 > 1:
+ logging.error(
+ "ERROR: Duplicate unique records were found in both files. Writing number of hits only."
+ )
+ self.run_notes.append(
+ "ERROR: Duplicate unique records were found in both files. Writing number of hits only."
+ )
+ elif max_hits_file1 > 1:
+ logging.error(
+ "ERROR: Duplicate unique records were found in file 1. Writing number of hits only."
+ )
+ self.run_notes.append(
+ "ERROR: Duplicate unique records were found in file 1. Writing number of hits only."
+ )
+ else:
+ logging.error(
+ "ERROR: Duplicate unique records were found in file 2. Writing number of hits only."
+ )
+ self.run_notes.append(
+ "ERROR: Duplicate unique records were found in file 2. Writing number of hits only."
+ )
+ self.hits_file1 = dict(
+ sorted(self.hits_file1.items(), key=lambda x: extract_id_parts(x[0]))
+ )
+ self.hits_file2 = dict(
+ sorted(self.hits_file2.items(), key=lambda x: extract_id_parts(x[0]))
+ )
+ return True
+ else:
+ return False
diff --git a/pvaccompare/comparisons/compare_unaggregated_tsv.py b/pvaccompare/comparisons/compare_unaggregated_tsv.py
new file mode 100644
index 0000000..bf50b49
--- /dev/null
+++ b/pvaccompare/comparisons/compare_unaggregated_tsv.py
@@ -0,0 +1,36 @@
+from run_utils import *
+
+
+class CompareUnaggregatedTSV:
+ def __init__(self, input_file1, input_file2, columns_to_compare):
+ self.input_file1 = input_file1
+ self.input_file2 = input_file2
+ self.df1, self.df2 = load_tsv_files(self.input_file1, self.input_file2)
+ self.columns_to_compare = columns_to_compare
+
+ def create_id_column(self):
+ """
+ Purpose: Combines multiple columns into a singular unique ID column in both dataframes
+ Modifies: df1 and df2
+ Returns: None
+ """
+ id_columns = [
+ "Chromosome",
+ "Start",
+ "Stop",
+ "Reference",
+ "Variant",
+ "HLA Allele",
+ "Sub-peptide Position",
+ "MT Epitope Seq",
+ "Index",
+ ]
+ self.df1["ID"] = self.df1[id_columns].apply(
+ lambda x: "-".join(map(str, x)), axis=1
+ )
+ self.df2["ID"] = self.df2[id_columns].apply(
+ lambda x: "-".join(map(str, x)), axis=1
+ )
+
+ self.df1.drop(columns=id_columns, inplace=True)
+ self.df2.drop(columns=id_columns, inplace=True)
diff --git a/pvaccompare/comparisons/compare_yml.py b/pvaccompare/comparisons/compare_yml.py
new file mode 100644
index 0000000..daf6f72
--- /dev/null
+++ b/pvaccompare/comparisons/compare_yml.py
@@ -0,0 +1,118 @@
+import yaml
+from deepdiff import DeepDiff
+import re
+
+
+class CompareYML:
+ def __init__(self, input_file1, input_file2):
+ self.input_file1 = input_file1
+ self.input_file2 = input_file2
+ self.data1, self.data2 = self.load_files()
+ self.differences = DeepDiff(self.data1, self.data2, ignore_order=True)
+ self.output_mappings = {
+ "dictionary_item_added": "Fields Unique to File 2",
+ "dictionary_item_removed": "Fields Unique to File 1",
+ "values_changed": "Values Changed",
+ "iterable_item_added": "Values Added in File 2",
+ "iterable_item_removed": "Values Removed in File 2",
+ }
+
+ def load_files(self):
+ """
+ Purpose: Load the two input yml files into dictionaries
+ Modifies: Nothing
+ Returns: Two dictionaries corresponding to the two input files
+ """
+ with open(self.input_file1, "r") as f1, open(self.input_file2, "r") as f2:
+ data1 = yaml.safe_load(f1)
+ data2 = yaml.safe_load(f2)
+ return data1, data2
+
+ def convert_diff_to_dict(self):
+ """
+ Purpose: Convert the DeepDiff result to a categorized dictionary
+ Modifies: Nothing
+ Returns: Dictionary representation of the categorized DeepDiff result
+ """
+ differences = {}
+
+ pattern = r"root\['(.*?)'\]"
+
+ for change_type, changes in self.differences.items():
+ if change_type in ["dictionary_item_added", "dictionary_item_removed"]:
+ category = (
+ "Fields Unique to File 2"
+ if change_type == "dictionary_item_added"
+ else "Fields Unique to File 1"
+ )
+ if category not in differences:
+ differences[category] = []
+
+ if isinstance(changes, dict):
+ for change in changes.keys():
+ formatted_output = (
+ re.match(pattern, change)[1]
+ if re.match(pattern, change)
+ else change
+ )
+ differences[category].append(formatted_output)
+ elif isinstance(changes, list):
+ differences[category].extend(changes)
+ else:
+ changes = str(changes)
+ matched_fields = re.findall(pattern, changes)
+ differences[category].extend(matched_fields)
+
+ elif change_type == "values_changed":
+ if "Values Changed" not in differences:
+ differences["Values Changed"] = {}
+
+ for change, details in changes.items():
+ formatted_output = (
+ re.match(pattern, change)[1]
+ if re.match(pattern, change)
+ else change
+ )
+ differences["Values Changed"][
+ formatted_output
+ ] = f"{details['old_value']} -> {details['new_value']}"
+
+ elif change_type == "type_changes":
+ if "Type Changes" not in differences:
+ differences["Type Changes"] = {}
+
+ for change, details in changes.items():
+ formatted_output = (
+ re.match(pattern, change)[1]
+ if re.match(pattern, change)
+ else change
+ )
+ differences["Type Changes"][
+ formatted_output
+ ] = f"{details['old_type']} -> {details['new_type']}"
+
+ elif change_type == "iterable_item_added":
+ if "Values Added in File 2" not in differences:
+ differences["Values Added in File 2"] = {}
+
+ for change, details in changes.items():
+ formatted_output = (
+ re.match(pattern, change)[1]
+ if re.match(pattern, change)
+ else change
+ )
+ differences["Values Added in File 2"][formatted_output] = details
+
+ elif change_type == "iterable_item_removed":
+ if "Values Removed in File 2" not in differences:
+ differences["Values Removed in File 2"] = {}
+
+ for change, details in changes.items():
+ formatted_output = (
+ re.match(pattern, change)[1]
+ if re.match(pattern, change)
+ else change
+ )
+ differences["Values Removed in File 2"][formatted_output] = details
+
+ return differences
diff --git a/pvaccompare/html_report/favicon.ico b/pvaccompare/html_report/favicon.ico
new file mode 100644
index 0000000..1269f8f
Binary files /dev/null and b/pvaccompare/html_report/favicon.ico differ
diff --git a/pvaccompare/html_report/libs/bootstrap/bootstrap.bundle.min.js b/pvaccompare/html_report/libs/bootstrap/bootstrap.bundle.min.js
new file mode 100644
index 0000000..04e9185
--- /dev/null
+++ b/pvaccompare/html_report/libs/bootstrap/bootstrap.bundle.min.js
@@ -0,0 +1,7 @@
+/*!
+ * Bootstrap v5.3.3 (https://getbootstrap.com/)
+ * Copyright 2011-2024 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
+ */
+!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?module.exports=e():"function"==typeof define&&define.amd?define(e):(t="undefined"!=typeof globalThis?globalThis:t||self).bootstrap=e()}(this,(function(){"use strict";const t=new Map,e={set(e,i,n){t.has(e)||t.set(e,new Map);const s=t.get(e);s.has(i)||0===s.size?s.set(i,n):console.error(`Bootstrap doesn't allow more than one instance per element. 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t}))){T=O,E=!1;break}A.set(O,N)}if(E)for(var P=function(t){var e=v.find((function(e){var i=A.get(e);if(i)return i.slice(0,t).every((function(t){return t}))}));if(e)return T=e,"break"},j=p?3:1;j>0&&"break"!==P(j);j--);e.placement!==T&&(e.modifiersData[n]._skip=!0,e.placement=T,e.reset=!0)}},requiresIfExists:["offset"],data:{_skip:!1}};function oi(t,e,i){return void 0===i&&(i={x:0,y:0}),{top:t.top-e.height-i.y,right:t.right-e.width+i.x,bottom:t.bottom-e.height+i.y,left:t.left-e.width-i.x}}function ri(t){return[zt,qt,Rt,Vt].some((function(e){return t[e]>=0}))}const ai={name:"hide",enabled:!0,phase:"main",requiresIfExists:["preventOverflow"],fn:function(t){var 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m?m(Object.assign({},e.rects,{placement:e.placement})):m,O="number"==typeof C?{mainAxis:C,altAxis:C}:Object.assign({mainAxis:0,altAxis:0},C),x=e.modifiersData.offset?e.modifiersData.offset[e.placement]:null,k={x:0,y:0};if(A){if(o){var L,S="y"===y?zt:Vt,D="y"===y?Rt:qt,$="y"===y?"height":"width",I=A[y],N=I+g[S],P=I-g[D],j=f?-T[$]/2:0,M=b===Xt?E[$]:T[$],F=b===Xt?-T[$]:-E[$],H=e.elements.arrow,W=f&&H?Ce(H):{width:0,height:0},B=e.modifiersData["arrow#persistent"]?e.modifiersData["arrow#persistent"].padding:{top:0,right:0,bottom:0,left:0},z=B[S],R=B[D],q=Ne(0,E[$],W[$]),V=v?E[$]/2-j-q-z-O.mainAxis:M-q-z-O.mainAxis,K=v?-E[$]/2+j+q+R+O.mainAxis:F+q+R+O.mainAxis,Q=e.elements.arrow&&$e(e.elements.arrow),X=Q?"y"===y?Q.clientTop||0:Q.clientLeft||0:0,Y=null!=(L=null==x?void 0:x[y])?L:0,U=I+K-Y,G=Ne(f?ye(N,I+V-Y-X):N,I,f?ve(P,U):P);A[y]=G,k[y]=G-I}if(a){var J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const 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W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,jn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,Mn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,Mn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],dd:[],div:[],dl:[],dt:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:""},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'
',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'