From 9aee6bd1e7444907d66a29546ae6fe8e29b5cdc2 Mon Sep 17 00:00:00 2001 From: Eric Earl Date: Thu, 27 Jun 2019 09:32:32 -0700 Subject: [PATCH] Release version 1 from DCAN-Labs/abcd-dicom2bids (#1) * Documentation and bug fixes: First commit * Minor changes to README * Added step 5 (BIDS validator) to README * Added options to (1) good_bad_series_parser and (2) nda_aws_token_maker letting them accept (1) NDA data download target/location and (2) NDA credentials as CLI args instead of being hardcoded. * Added almost-complete Python abcd2bids wrapper, slight change to unpack_and_setup to let the wrapper send it an output directory as a CLI arg, and added (not yet working) compiled MATLAB data_gatherer script in /bin/. * Added untracked files which were changed as of the last commit. * Finishing up abcd2bids.py wrapper, compiled data_gatherer script, and modified unpack_and_setup to get args from abcd2bids.py * Wrapper functionality seems complete, so it should be ready for testing from start to finish even though it has not yet. * Minor changes to README.md. * More minor changes to the README. * Fixed minor typo in abcd2bids.py * Minor README change: Added FSL 5.0 as a dependency. * Reorganized directory structure, updated paths to files now in ./src/ folder, and added 'config' functionality to abcd2bids.py * Minor changes to make scripts work with new folder organization, and to make config file only accessible by its owner by default. * Updated README and added necessary JSONs to ./data/ * Minor change to README. * Added READMEs to other folders, fixed a bug preventing nda_aws_token_maker from working, updated main README, changed config functionality to save config.ini to ~/.abcd2bids/, and deleted unneeded MATLAB compiler file. * Added raw/ directory and its README file. * Fix src/nda_aws_token_maker.py Fixed a small bug in nda_aws_token_maker.py, updated the src/README.md doc, removed some extraneous files, and fixed a broken link in data/README.md. * Updated README to add AWS dependency/troubleshooting Added AWS CLI as a dependency, then added description of error caused by incorrect AWS CLI file and how to fix it by installing the latest AWS CLI version and setting it in user's PATH variable. * Updated abcd2bids.py its README, added temp dir and its README abcd2bids.py will now delete all temp files even if it crashes. It will also overwrite an old config file if new NDA credentials are entered as CLI args. I updated its README accordingly. I also added temp dir with a README to the git, since it should be empty. Finally, I made nda_aws_token_maker.py less likely to crash by failing to import nda_aws_token_generator.py * Updated README file in spreadsheets folder * Fix UNPACK_ANCD_SETUP logic in abcd2bids.py * Small file rename to data/README for BIDS compatibility * Updated README and added raw data cleanup functionality Added warning to main README.md, added option to delete the raw data for each subject session after that subject session is processed; also a few minor changes to abcd2bids.py * Updated 'last updated' label in abcd2bids.py * Minor updates to abcd2bids.py and main README.md * Finished first version of wrapper so it runs without error - Added functionality to start the process from any step. - Updated README to include new functionality. - Fixed a bug caused by relative instead of absolute paths in unpack_and_setup. - Minor updates/cleanup. * Minor docstring fix in abcd2bids.py * Fixed 'last updated' tag on abcd2bids.py * Very minor fix: Changed 'pathlib.Path.absolute' to 'pathlib.Path.resolve' in abcd2bids.py * Completed last minor fix (absolute to resolve) * Added detail to main README.md The temp, output, and download folders will be created by abcd2bids.py if they do not already exist * Finalized wrapper - Simplified abcd2bids.py start_at usage by having user enter the name, instead of the number, of the step to start at. - Minor updates to README: Added --temp to advanced usage example, and changed 'processed' to 'converted' for more accurate language * Minor edit: Added names of steps to argparse help * Minor edit: Instead of overwriting start_at with the step number, iterate over the steps * Minor edit to abcd2bids.py start_at argparse help message --- .gitignore | 13 + README.md | 124 +++-- abcd2bids.py | 559 +++++++++++++++++++++ data/CHANGES | 2 + data/README | 3 + data/dataset_description.json | 41 ++ data/task-MID_bold.json | 5 + data/task-SST_bold.json | 5 + data/task-nback_bold.json | 6 + data/task-rest_bold.json | 6 + raw/README.md | 3 + spreadsheets/README.md | 4 +- src/FSL_identity_transformation_matrix.mat | 4 + src/README.md | 28 ++ src/__init__.py | 2 + src/bin/data_gatherer | Bin 0 -> 96083 bytes src/bin/readme.txt | 115 +++++ src/bin/run_data_gatherer.sh | 36 ++ src/correct_jsons.py | 115 +++++ src/eta_squared | Bin 0 -> 7516984 bytes src/good_bad_series_parser.py | 224 +++++++++ src/mapping.mat | Bin 0 -> 8444 bytes src/nda_aws_token_generator.py | 123 +++++ src/nda_aws_token_maker.py | 61 +++ src/run_eta_squared.sh | 40 ++ src/run_order_fix.py | 266 ++++++++++ src/sefm_eval_and_json_editor.py | 336 +++++++++++++ src/unpack_and_setup.sh | 167 ++++++ temp/README.md | 5 + 29 files changed, 2260 insertions(+), 33 deletions(-) create mode 100644 .gitignore mode change 100644 => 100755 README.md create mode 100644 abcd2bids.py create mode 100644 data/CHANGES create mode 100644 data/README create mode 100644 data/dataset_description.json create mode 100644 data/task-MID_bold.json create mode 100644 data/task-SST_bold.json create mode 100644 data/task-nback_bold.json create mode 100644 data/task-rest_bold.json create mode 100644 raw/README.md create mode 100755 src/FSL_identity_transformation_matrix.mat create mode 100644 src/README.md create mode 100644 src/__init__.py create mode 100755 src/bin/data_gatherer create mode 100644 src/bin/readme.txt create mode 100755 src/bin/run_data_gatherer.sh create mode 100755 src/correct_jsons.py create mode 100755 src/eta_squared create mode 100755 src/good_bad_series_parser.py create mode 100755 src/mapping.mat create mode 100644 src/nda_aws_token_generator.py create mode 100755 src/nda_aws_token_maker.py create mode 100755 src/run_eta_squared.sh create mode 100755 src/run_order_fix.py create mode 100755 src/sefm_eval_and_json_editor.py create mode 100755 src/unpack_and_setup.sh create mode 100644 temp/README.md diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..6d102e1 --- /dev/null +++ b/.gitignore @@ -0,0 +1,13 @@ +.idea/ +__pycache__/ +abcd_download_log.csv +src/abcd_download_log.csv +src/config.ini +spreadsheets/ABCD_good_and_bad_series_table.csv +spreadsheets/image03.txt +spreadsheets/DAL_ABCD_QC_merged_pcqcinfo.csv +temp/*/ +raw/*/ +data/*/ +*.pyc +*.txt diff --git a/README.md b/README.md old mode 100644 new mode 100755 index c1414e7..1c321ab --- a/README.md +++ b/README.md @@ -4,16 +4,19 @@ Written by the OHSU ABCD site for selectively downloading ABCD Study imaging DIC ## Installation -Clone this repository and save it somewhere on the Linux system you want to do ABCD DICOM downloads and conversions to BIDS. +Clone this repository and save it somewhere on the Linux system you want to do ABCD DICOM downloads and conversions to BIDS on. ## Dependencies -1. [MathWorks MATLAB (R2016b and newer)](https://www.mathworks.com/products/matlab.html) -1. [Python 2.7](https://www.python.org/download/releases/2.7/) -1. [NIMH Data Archive (NDA) `nda_aws_token_generator`](https://github.com/NDAR/nda_aws_token_generator) +1. [Python 3.5.2](https://www.python.org/downloads/release/python-352/) +1. [MathWorks MATLAB Runtime Environment (MRE) version 9.1 (R2016b)](https://www.mathworks.com/products/compiler/matlab-runtime.html) 1. [cbedetti Dcm2Bids](https://github.com/cbedetti/Dcm2Bids) (`export` into your BASH `PATH` variable) 1. [Rorden Lab dcm2niix](https://github.com/rordenlab/dcm2niix) (`export` into your BASH `PATH` variable) 1. [zlib's pigz-2.4](https://zlib.net/pigz) (`export` into your BASH `PATH` variable) +1. Docker (see documentation for [Docker Community Edition for Ubuntu](https://docs.docker.com/install/linux/docker-ce/ubuntu/)) +1. [FMRIB Software Library (FSL) v5.0](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation) +1. [Python `cryptography` package](https://cryptography.io/en/latest/) +1. [AWS CLI (Amazon Web Services Command Line Interface) v19.0.0](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html) ## Spreadsheets (not included) @@ -41,65 +44,122 @@ To download images for ABCD you must have two spreadsheets downloaded to this re - Click **Create Package** 1. Download and use the **Package Manager** to download your package -## Setup +## Usage -You will also need to reach into the `nda_aws_token_maker.py` in this repository and update it with your NDA USERNAME and PASSWORD. Make sure the file is locked down to only your own read and write privileges so no one else can read your username and password in there: +The DICOM to BIDS process can be done by running the `abcd2bids.py` wrapper from within the directory cloned from this repo. `abcd2bids.py` requires two positional arguments and can take several optional arguments. Those positional arguments are file paths to the FSL directory and the MATLAB Runtime Environment. Here is an example of a valid call of this wrapper: ``` -chmod 600 nda_aws_token_maker.py +python3 abcd2bids.py ``` -We don't have a better solution for securing your credentials while automating downloads right now. +The first time that a user uses this wrapper, the user will have to enter their NDA credentials. If the user does not include them as command-line arguments, then the wrapper will prompt the user to enter them. The wrapper will then create a `config.ini` file with the user's username and (encrypted) password, so the user will not have to enter their NDA credentials any subsequent times running this wrapper. -## Usage +If the user already has a `config.ini` file, then the wrapper can use that, so the user does not need to enter their NDA credentials again. However, to make another `config.ini` file or overwrite the old one, the user can enter their NDA credentials as command-line args. + +### Disk Space Usage Warnings + +This wrapper will download NDA data (into the `raw/` subdirectory by default) and then copy it (into the `data/` subdirectory by default) to convert it without deleting the downloaded data, unless the `--remove` flag is added. The downloaded and converted data will take up a large amount of space on the user's filesystem, especially for converting many subjects. About 3 to 7 GB of data or more will be produced by downloading and converting one subject session, not counting the temporary files in the `temp/` subdirectory. + +This wrapper will create a temporary folder (`temp/` by default) with hundreds of thousands of files (about 7 GB or more) per subject session. These files are used in the process of preparing the BIDS data. The wrapper will delete that temporary folder once it finishes running, even if it crashes. Still, it is probably a good idea to double-check that the temporary folder has no subdirectories before and after running this wrapper. Otherwise, this wrapper might leave an extremely large set of unneeded files on the user's filesystem. + +### Optional arguments + +`--username` and `--password`: Include one of these to pass the user's NDA credentials from the command line into a `config.ini` file. This will create a new config file if one does not already exist, or overwrite the existing file. If only one of these flags is included, the user will be prompted for the other. They can be passed into the wrapper from the command line like so: `--username my_nda_username --password my_nda_password`. + +`--config`: By default, the wrapper will look for a `config.ini` file in a hidden subdirectory of the user's home directory (`~/.abcd2bids/`). Use `--config` to enter a different (non-default) path to the config file, e.g. `--config ~/Documents/config.ini`. + +`--temp`: By default, the temporary files will be created in the `temp/` subdirectory of the clone of this repo. If the user wants to place the temporary files anywhere else, then they can do so using the optional `--temp` flag followed by the path at which to create the directory containing temp files, e.g. `--temp /usr/home/abcd2bids-temporary-folder`. A folder will be created at the given path if one does not already exist. -This repo's usage is broken out into four distinct scripting sections. You will need to run them in order, each independently of the next waiting for the first to complete. +`--download`: By default, the wrapper will download the ABCD data to the `raw/` subdirectory of the cloned folder. If the user wants to download the ABCD data to a different directory, they can use the `--download` flag, e.g. `--download ~/abcd-dicom2bids/ABCD-Data-Download`. A folder will be created at the given path if one does not already exist. + +`--remove`: By default, the wrapper will download the ABCD data to the `raw/` subdirectory of the cloned folder. If the user wants to delete the raw downloaded data for each subject after that subject's data is finished converting, the user can use the `--remove` flag without any additional parameters. + +`--output`: By default, the wrapper will place the finished/converted data into the `data/` subdirectory of the cloned folder. If the user wants to put the finished data anywhere else, they can do so using the optional `--output` flag followed by the path at which to create the directory, e.g. `--output ~/abcd-dicom2bids/Finished-Data`. A folder will be created at the given path if one does not already exist. + +`--start_at`: By default, this wrapper will run every step listed under "Explanation of Process" below. Use this flag to start at one step and skip all of the previous ones. To do so, enter the name of the step, e.g. `--start_at correct_jsons` to skip every step before JSON correction. + +For more information including the shorthand flags of each option, use the `--help` command: `python3 abcd2bids.py --help`. + +Here is the format for a call to the wrapper with more options added: + +``` +python3 abcd2bids.py --username --download --output --temp --remove +``` + +## Explanation of Process + +`abcd2bids.py` is a wrapper for five distinct scripts, which previously needed to be run on their own in sequential order: 1. (MATLAB) `data_gatherer.m` 2. (Python) `good_bad_series_parser.py` 3. (BASH) `unpack_and_setup.sh` 4. (Python) `correct_jsons.py` +5. (Docker) Official BIDS validator -The MATLAB portion is for producing a download list for the Python & BASH portion to download, convert, select, and prepare. +The DICOM 2 BIDS conversion process can be done by running `python3 abcd2bids.py ` without any other options. First, the wrapper will try to create an NDA token with the user's NDA credentials. It does this by calling `src/nda_aws_token_maker.py`, which calls `src/nda_aws_token_generator` ([taken from the NDA](https://github.com/NDAR/nda_aws_token_generator)). If the wrapper cannot find a `config.ini` file with those credentials, and they are not entered as command line args, then the user will be prompted to enter them. -## 1. (MATLAB) `data_gatherer.m` +### 1. (MATLAB) `data_gatherer` -The two spreadsheets referenced above are used in the `data_gatherer.m` to create the `ABCD_good_and_bad_series_table.csv` which gets used to actually download the images. +The MATLAB portion is for producing a download list for the Python & BASH portion to download, convert, select, and prepare. The two spreadsheets referenced above are used in the `data_gatherer` compiled MATLAB script to create the `ABCD_good_and_bad_series_table.csv` which gets used to actually download the images. `data_gatherer` depends on a mapping file (`mapping.mat`), which maps the SeriesDescriptions to known OHSU descriptors that classify each TGZ file into T1, T2, task-rest, task-nback, etc. -`data_gatherer.m` depends on a mapping file (`mapping.mat`), which maps the SeriesDescriptions to known OHSU descriptors that classify each TGZ file into T1, T2, task-rest, task-nback, etc. +As its first step, the wrapper will run `data_gatherer` with this repository's cloned folder as the clone of this repo. If successful, it will create the file `ABCD_good_and_bad_series_table.csv` in the `spreadsheets/` subdirectory. -## 2. (Python) `good_bad_series_parser.py` +**NOTE:** This step can take over two hours to complete. -The download is done like this: +### 2. (Python) `good_bad_series_parser.py` -``` -./good_bad_series_parser.py -``` +Once `ABCD_good_and_bad_series_table.csv` is successfully created, the wrapper will run `src/good_bad_series_parser.py` with this repository's cloned folder as the present working directory to download the ABCD data from the NDA website. It requires the `ABCD_good_and_bad_series_table.csv` spreadsheet under a `spreadsheets` subdirectory of this repository's cloned folder. -This only requires the `ABCD_good_and_bad_series_table.csv` spreadsheet present under a `spreadsheets` folder inside this repository's cloned folder. +`src/good_bad_series_parser.py` also requires a `.aws` folder in the user's `home` directory, which will contain the NDA token. The `nda_aws_token_maker.py` is called before running the wrapper. If successful, `nda_aws_token_maker` will create a `credentials` file in `.aws`. If the download crashes and shows errors about `awscli`, try making sure you have the [latest AWS CLI installed](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html), and that the [`aws` executable is in your BASH `PATH` variable](https://docs.aws.amazon.com/cli/latest/userguide/install-linux.html#install-linux-path). -**Note:** The `nda_aws_token_maker.py` is called before each attempted DICOM series TGZ download. +If successful, this will download the ABCD data from the NDA site into the `raw/` subdirectory of the clone of this repo. -## 3. (BASH) `unpack_and_setup.sh` +### 3. (BASH) `unpack_and_setup.sh` -`unpack_and_setup.sh` should be called in a loop to do the DICOM to BIDS conversion and spin echo field map selection. It takes three arguments: +The wrapper will call `unpack_and_setup.sh` in a loop to do the DICOM to BIDS conversion and spin echo field map selection, taking seven arguments: ``` SUB=$1 # Full BIDS formatted subject ID (sub-SUBJECTID) VISIT=$2 # Full BIDS formatted session ID (ses-SESSIONID) TGZDIR=$3 # Path to directory containing all TGZ files for SUB/VISIT +ROOTBIDSINPUT=$4 Path to output folder which will be created to store unpacked/setup files +ScratchSpaceDir=$5 Path to folder which will be created to store temporary files that will be deleted once the wrapper finishes +FSL_DIR=$6 Path to FSL directory +MRE_DIR=$7 Path to MATLAB Runtime Environment (MRE) directory ``` -Here is an example: +By default, the wrapper will put the unpacked/setup data in the `data/` subdirectory of this repository's cloned folder. This step will also create and fill the `temp/` subdirectory of the user's home directory containing temporary files used for the download. If the user enters other locations for the temp directory or output data directory as optional command line args, then those will be used instead. -``` -./unpack_and_setup.sh sub-NDARINVABCD1234 ses-baselineYear1Arm1 ./new_download/sub-NDARINVABCD1234/ses-baseline_year_1_arm_1 -``` +### 4. (Python) `correct_jsons.py` -## 4. (Python) `correct_jsons.py` +Next, the wrapper runs `correct_jsons.py` on the whole BIDS directory (`data/` by default) to correct/prepare all BIDS sidecar JSON files to comply with the BIDS specification standard version 1.2.0. -Finally at the end `correct_jsons.py` is run on the whole BIDS input directory to correct/prepare all BIDS sidecar JSON files to comply with the BIDS specification standard version 1.2.0. +### 5. (Docker) Run official BIDS validator -``` -./correct_jsons.py ./ABCD-HCP -``` +Finally, the wrapper will run the [official BIDS validator](https://github.com/bids-standard/bids-validator) using Docker to validate the final dataset created by this process in the `data/` subdirectory. + +## Inside the `data` subdirectory + +The following files belong in the `data` subdirectory to run `abcd2bids.py`: + +1. `CHANGES` +2. `dataset_description.json` +3. `task-MID_bold.json` +4. `task-nback_bold.json` +5. `task-rest_bold.json` +6. `task-SST_bold.json` + +Without these files, the output of `abcd2bids.py` will fail BIDS validation. They should be downloaded from the GitHub repo by cloning it. + +This folder is where the output of `abcd2bids.py` will be placed by default. So, after running `abcd2bids.py`, this folder will have subdirectories for each subject session. Those subdirectories will be correctly formatted according to the [official BIDS specification standard v1.2.0](https://github.com/bids-standard/bids-specification/releases/tag/v1.2.0). + +The resulting ABCD Study dataset here is made up of all the ABCD Study participants' imaging data that passed initial acquisition quality control (MRI QC). + +## Attributions + +This wrapper relies on the following other projects: +- [cbedetti Dcm2Bids](https://github.com/cbedetti/Dcm2Bids) +- [Rorden Lab dcm2niix](https://github.com/rordenlab/dcm2niix) +- [zlib's pigz-2.4](https://zlib.net/pigz) +- [Official BIDS validator](https://github.com/bids-standard/bids-validator) +- [NDA AWS token generator](https://github.com/NDAR/nda_aws_token_generator) diff --git a/abcd2bids.py b/abcd2bids.py new file mode 100644 index 0000000..db32a28 --- /dev/null +++ b/abcd2bids.py @@ -0,0 +1,559 @@ +#! /usr/bin/env python3 + +""" +ABCD to BIDS CLI Wrapper +Greg Conan: conan@ohsu.edu +Created 2019-05-29 +Last Updated 2019-06-26 +""" + +################################## +# +# Wrapper for ABCD DICOM to BIDS pipeline that can be run from the command line +# 1. Runs data_gatherer to create ABCD_good_and_bad_series_table.csv +# 2. Runs good_bad_series_parser to download ABCD data using that .csv table +# 3. Runs unpack_and_setup to unpack/setup the downloaded ABCD data +# 4. Runs correct_jsons to conform data to official BIDS standards +# 5. Runs BIDS validator on unpacked/setup data using Docker +# +################################## + +import argparse +import configparser +from cryptography.fernet import Fernet +from getpass import getpass +import os +from pathlib import Path +import shutil +import signal +import subprocess +import sys + +# Constant: List of function names of steps 1-5 in the list above +STEP_NAMES = ["create_good_and_bad_series_table", "download_nda_data", + "unpack_and_setup", "correct_jsons", "run_bids_validator"] + +# Constants: Default paths to scripts to call from this wrapper, and default +# paths to folders in which to manipulate data +CONFIG_FILEPATH = os.path.expanduser("~/.abcd2bids/config.ini") +CORRECT_JSONS = "./src/correct_jsons.py" +DATA_GATHERER = "./src/bin/run_data_gatherer.sh" +DOWNLOAD_FOLDER = "./raw/" +GOOD_BAD_SERIES_PARSER = "./src/good_bad_series_parser.py" +NDA_AWS_TOKEN_MAKER = "./src/nda_aws_token_maker.py" +TEMP_FILES_DIR = "./temp" +UNPACK_AND_SETUP = "./src/unpack_and_setup.sh" +UNPACKED_FOLDER = "./data/" + + +def main(): + """ + Run entire process of downloading ABCD data from NDA website, transforming + it to meet BIDS standards, and validating that it meets those standards. + :return: N/A + """ + cli_args = cli() + print("\nRunning ABCD to BIDS wrapper. Started at: ") + subprocess.check_call("date") + + # Set cleanup function to delete all temporary files if script crashes + set_to_cleanup_on_crash(cli_args.temp) + + # Before running any different scripts, validate user's NDA credentials and + # use them to make NDA token + make_nda_token(cli_args) + + # Run the steps sequentially, starting at the one specified by the user + started = False + for step in STEP_NAMES: + if step == cli_args.start_at: + started = True + if started: + eval(step + "(cli_args)") + + # Finally, delete temporary files and end script with success exit code + cleanup(cli_args.temp, 0) + + +def cli(): + """ + Get and validate all args from command line using argparse. + :return: Namespace containing all validated inputted command line arguments + """ + # Create arg parser + parser = argparse.ArgumentParser( + description="Wrapper to download, parse, and validate QC'd ABCD data." + ) + + # Required: Get path to FSL directory + parser.add_argument( + "fsl_dir", + type=str, + help=("Required: Path to FSL directory. This positional argument must " + "be a valid path to an existing folder.") + ) + + # Required: Get path to MRE / MCR root to run compiled MATLAB script + parser.add_argument( + "mre_dir", + type=str, + help=("Required: Path to directory containing MATLAB Runtime " + "Environment (MRE) version 9.1 or newer. This is used to run " + "a compiled MATLAB script. This positional argument must be a " + "valid path to an existing folder.") + ) + + # Optional: Get NDA username and password + parser.add_argument( + "-u", + "--username", + type=str, + help=("Optional: NDA username. Adding this will create a new config " + "file or overwrite an old one. Unless this is added or a config " + "file exists with the user's NDA credentials, the user will be " + "prompted for them. If this is added and --password is not, " + "then the user will be prompted for their NDA password.") + ) + parser.add_argument( + "-p", + "--password", + type=str, + help=("Optional: NDA password. Adding this will create a new config " + "file or overwrite an old one. Unless this is added or a config " + "file exists with the user's NDA credentials, the user will be " + "prompted for them. If this is added and --username is not, " + "then the user will be prompted for their NDA username.") + ) + + # Optional: Get path to already-existing config file with NDA credentials + parser.add_argument( + "-c", + "--config", + default=CONFIG_FILEPATH, + help=("Optional: Path to config file with NDA credentials. If no " + "config file exists at this path yet, then one will be created. " + "Unless this option or --username and --password is added, the " + "user will be prompted for their NDA username and password. " + "By default, the config file will be located at " + + os.path.abspath(CONFIG_FILEPATH)) + ) + + # Optional: Get download folder path from user as CLI arg + parser.add_argument( + "-d", + "--download", + default=DOWNLOAD_FOLDER, + help=("Optional: Path to folder which NDA data will be downloaded " + "into. By default, data will be downloaded into the " + + os.path.abspath(DOWNLOAD_FOLDER) + " folder. A folder will be " + "created at the given path if one does not already exist.") + ) + + # Optional: Get folder to unpack NDA data into from download folder + parser.add_argument( + "-o", + "--output", + default=UNPACKED_FOLDER, + help=("Optional: Folder path into which NDA data will be unpacked and " + "setup once downloaded. By default, this script will put the " + "data into the " + os.path.abspath(UNPACKED_FOLDER) + " folder. " + "A folder will be created at the given path if one does not " + "already exist.") + ) + + # Optional: Get folder to place temp data into during unpacking + parser.add_argument( + "-t", + "--temp", + default=TEMP_FILES_DIR, + help=("Optional: Path to the directory to be created and filled with " + "temporary files during unpacking and setup. By default, the " + "folder will be created at " + os.path.abspath(TEMP_FILES_DIR) + + " and deleted once the script finishes. A folder will be " + "created at the given path if one does not already exist.") + ) + + # Optional: During unpack_and_setup, remove unprocessed data + parser.add_argument( + "-r", + "--remove", + action="store_true", + help=("Optional: After each subject's data has finished conversion, " + "removed that subject's unprocessed data.") + ) + + # Optional: Pick a step to start at, ignore previous ones, and then run + # that function and all subsequent ones sequentially + parser.add_argument( + "-s", + "--start_at", + choices=STEP_NAMES, + default=STEP_NAMES[0], + help=("Optional: Give the name of the step in the wrapper to start " + "at, then run that step and every step after it. Here are the " + "names of each step, in order from first to last: " + + ", ".join(STEP_NAMES)) + ) + + # Parse, validate, and return all CLI args + return validate_cli_args(parser.parse_args(), parser) + + +def validate_cli_args(args, parser): + """ + Check that all command line arguments will allow this script to work. + :param args: argparse namespace with all command-line arguments + :param parser: argparse ArgumentParser to raise error if anything's invalid + :return: Validated command-line arguments argparse namespace + """ + # Validate FSL and MRE directories + validate_dir_path(args.fsl_dir, parser) + validate_dir_path(args.mre_dir, parser) + + # Validate and create config file's parent directory + try: + Path(os.path.dirname(args.config)).mkdir(parents=True, exist_ok=True) + except (OSError, TypeError): + parser.error("Could not create folder to contain config file.") + + # Validate other dirs: check if they exist; if not, try to create them; and + # move important files in the default dir(s) to the new dir(s) + try_to_create_and_prep_directory_at(args.download, DOWNLOAD_FOLDER, parser) + try_to_create_and_prep_directory_at(args.output, UNPACKED_FOLDER, parser) + try_to_create_and_prep_directory_at(args.temp, TEMP_FILES_DIR, parser) + + # Ensure that the folder paths are formatted correctly: download and output + # should have trailing slashes, but temp should not + if args.download[-1] != "/": + args.download += "/" + print(args.download) + if args.output[-1] != "/": + args.output += "/" + print(args.output) + if args.temp[-1] == "/": + args.temp = args.temp[:-1] + print(args.temp) + + return args + + +def validate_dir_path(dir_path, parser): + """ + Validate that a given path refers to an existing directory; if it doesn't, + then raise an argparse error + :param dir_path: Path to validate + :param parser: argparse ArgumentParser to raise error if path is invalid + :return: N/A + """ + if not Path(dir_path).is_dir(): + parser.error(dir_path + " is not an existing directory.") + + +def try_to_create_and_prep_directory_at(folder_path, default_path, parser): + """ + Validate file path of folder, and if it doesn't exist, create it. If a + non-default path is given, then move the file(s) in the default folder(s) + to the new folder(s) without copying any subdirectories (which have data). + :param folder_path: Path of folder that either exists or should be created + :param default_path: The default value of folder_path. The folder here + has some files which will be copied to the new directory at folder_path. + :param parser: argparse ArgumentParser to raise error if path is invalid + :return: N/A + """ + try: + Path(folder_path).mkdir(exist_ok=True, parents=True) + except (OSError, TypeError): + parser.error("Could not create folder at " + folder_path) + + # If user gave a different directory than the default, then copy the + # required files into that directory and nothing else + default = Path(default_path) + if Path(folder_path).resolve() != default.resolve(): + for file in default.iterdir(): + if not file.is_dir(): + shutil.copy2(str(file), folder_path) + + +def set_to_cleanup_on_crash(temp_dir): + """ + Make it so that if the script crashes, all of the temporary files that it + generated are deleted. signal.signal() checks if the script has crashed, + and cleanup() deletes all of the temporary files. + :return: N/A + """ + # Use local function as an intermediate because the signal module does + # not allow the signal handler (the second parameter of signal.signal) to + # take the parameter (temp_dir) needed by the cleanup function. Run cleanup + # function and exit with exit code 1 (failure) + def call_cleanup_function(_signum, _frame): + cleanup(temp_dir, 1) + + # If this wrapper crashes, delete all temporary files + signal.signal(signal.SIGINT, call_cleanup_function) + signal.signal(signal.SIGTERM, call_cleanup_function) + + +def cleanup(temp_dir, exit_code): + """ + Function to delete all temp files created while running this script. This + function will always run right before the wrapper terminates, whether or + not the wrapper ran successfully. + :param temp_dir: Path to folder containing temporary files to delete. + :param exit_code: Code for this wrapper to return on exit. If cleanup() is + called when wrapper finishes successfully, then 0; otherwise 1. + :return: N/A + """ + # Delete all temp folder subdirectories, but not the README in temp folder + for temp_dir_subdir in Path(temp_dir).iterdir(): + if temp_dir_subdir.is_dir(): + shutil.rmtree(str(temp_dir_subdir)) + + # Inform user that temporary files were deleted, then terminate wrapper + print("\nTemporary files in " + temp_dir + " deleted. ABCD to BIDS " + "wrapper terminated.") + sys.exit(exit_code) + + +def make_nda_token(args): + """ + Create NDA token by getting credentials from config file. If no config file + exists yet, or user specified to make a new one by entering their NDA + credentials as CLI args, then create one to store NDA credentials. + :param args: argparse namespace containing all CLI arguments. The specific + arguments used by this function are --username, --password, and --config. + :return: N/A + """ + # If config file with NDA credentials exists, then get credentials from it, + # unless user entered other credentials to make a new config file + if not args.username and not args.password and Path(args.config).exists(): + username, password = get_nda_credentials_from(args.config) + + # Otherwise get NDA credentials from user & save them in a new config file, + # overwriting the existing config file if user gave credentials as cli args + else: + + # If NDA username was a CLI arg, use it; otherwise prompt user for it + if args.username: + username = args.username + else: + username = input("\nEnter your NIMH Data Archives username: ") + + # If NDA password was a CLI arg, use it; otherwise prompt user for it + if args.password: + password = args.password + else: + password = getpass("Enter your NIMH Data Archives password: ") + + make_config_file(args.config, username, password) + + # Try to make NDA token + token_call_exit_code = subprocess.call([ + "python3", + NDA_AWS_TOKEN_MAKER, + username, + password + ]) + + # If NDA credentials are invalid, tell user so without printing password. + # Manually catch error instead of using try-except to avoid trying to + # catch another file's exception. + if token_call_exit_code is not 0: + print("Failed to create NDA token using the username and decrypted " + "password from " + str(Path(args.config).resolve())) + sys.exit(1) + + +def get_nda_credentials_from(config_file_path): + """ + Given the path to a config file, returns user's NDA credentials. + :param config_file_path: Path to file containing user's NDA username, + encrypted form of user's NDA password, and key to that encryption. + :return: Two variables: user's NDA username and password. + """ + # Object to read/write config file containing NDA credentials + config = configparser.ConfigParser() + config.read(config_file_path) + + # Get encrypted password and encryption key from config file + encryption_key = config["NDA"]["key"] + encrypted_password = config["NDA"]["encrypted_password"] + + # Decrypt password to get user's NDA credentials + username = config["NDA"]["username"] + password = ( + Fernet(encryption_key.encode("UTF-8")) + .decrypt(token=encrypted_password.encode("UTF-8")) + .decode("UTF-8") + ) + + return username, password + + +def make_config_file(config_filepath, username, password): + """ + Create a config file to save user's NDA credentials. + :param config_filepath: Name and path of config file to create. + :param username: User's NDA username to save in config file. + :param password: User's NDA password to encrypt then save in config file. + :return: N/A + """ + # Object to read/write config file containing NDA credentials + config = configparser.ConfigParser() + + # Encrypt user's NDA password by making an encryption key + encryption_key = Fernet.generate_key() + encrypted_password = ( + Fernet(encryption_key).encrypt(password.encode("UTF-8")) + ) + + # Save the encryption key and encrypted password to a new config file + config["NDA"] = { + "username": username, + "encrypted_password": encrypted_password.decode("UTF-8"), + "key": encryption_key.decode("UTF-8") + } + with open(config_filepath, "w") as configfile: + config.write(configfile) + + # Change permissions of the config file to prevent other users accessing it + subprocess.check_call(["chmod", "700", config_filepath]) + + +def create_good_and_bad_series_table(cli_args): + """ + Create good_and_bad_series_table.csv using compiled MATLAB data_gatherer. + :param cli_args: argparse namespace containing all CLI arguments. This + function only uses the --mre_dir argument. + :return: N/A + """ + print("\ndata_gatherer to create good_and_bad_series_table started at:") + subprocess.check_call("date") + try: + subprocess.check_call([DATA_GATHERER, cli_args.mre_dir]) + + # If user does not have the right spreadsheets in the right location, then + # inform the user instead of spitting out an unhelpful stack trace + except subprocess.CalledProcessError: + print("Error: data_gatherer failed. Please check that the " + "./spreadsheets/ folder contains image03.txt and " + "DAL_ABCD_QC_merged_pcqcinfo.csv, then run this script again.") + sys.exit(1) + + print("\ndata_gatherer finished at:") + subprocess.check_call('date') + + +def download_nda_data(cli_args): + """ + Download NDA data by making NDA token and parsing the + good_and_bad_series_table.csv spreadsheet. + :param cli_args: argparse namespace containing all CLI arguments. This + function only uses the --download argument, the path to the folder to fill + with downloaded NDA data. + :return: N/A + """ + # Call Python script to parse good_and_bad_series_table and download data + print("\nDownloading ABCD data from NDA. Download started at:") + subprocess.check_call("date") + subprocess.check_call([ + "python3", + GOOD_BAD_SERIES_PARSER, + cli_args.download + ]) + print("\nABCD data download finished at:") + subprocess.check_call("date") + + +def unpack_and_setup(args): + """ + Run unpack_and_setup.sh script to unpack and setup the newly downloaded + NDA data files. + :param args: All arguments entered by the user from the command line. The + specific arguments used by this function are fsl_dir, mre_dir, --output, + --download, --temp, and --remove. + :return: N/A + """ + print("\nData unpacking and setup started at:") + subprocess.check_call("date") + + # Get name of NDA data folder newly downloaded from download_nda_data + download_folder = Path(args.download) + + # Unpack and setup every .tgz file descendant of the NDA data folder + for subject in download_folder.iterdir(): + if subject.is_dir(): + for session_dir in subject.iterdir(): + if session_dir.is_dir(): + for tgz in session_dir.iterdir(): + if tgz: + + # Get session ID from some (arbitrary) .tgz file in + # session folder + session_name = tgz.name.split("_")[1] + + # Unpack/setup the data for this subject/session + subprocess.check_call([ + UNPACK_AND_SETUP, + subject.name, + "ses-" + session_name, + str(session_dir.resolve()), + args.output, + args.temp, + args.fsl_dir, + args.mre_dir + ]) + + # If user said to, delete all the raw downloaded + # files for each subject after that subject's data + # has been converted and copied + if args.remove: + shutil.rmtree(args.download + subject.name) + + break + + print("\nUnpacking and setup finished at:") + subprocess.check_call("date") + + +def correct_jsons(cli_args): + """ + Correct ABCD BIDS input data to conform to official BIDS Validator. + :param cli_args: argparse namespace containing all CLI arguments. This + function only uses the --output argument, the path to the folder containing + corrected NDA data to validate. + :return: N/A + """ + print("\nJSON correction started at:") + subprocess.check_call("date") + subprocess.check_call([CORRECT_JSONS, cli_args.output]) + print("\nJSON correction finished at:") + subprocess.check_call("date") + + +def run_bids_validator(cli_args): + """ + Run the official BIDS validator on the corrected ABCD BIDS data. + :param cli_args: argparse namespace containing all CLI arguments. This + function only uses the --output argument, the path to the folder containing + corrected NDA data to validate. + :return: N/A + """ + + print("\nBIDS validation started at:") + subprocess.check_call("date") + try: + subprocess.check_call(["docker", "run", "-ti", "--rm", "-v", + os.path.abspath(cli_args.output) + ":/data:ro", + "bids/validator", "/data"]) + + # If BIDS validation is successful, then delete directory/ies holding + # temporary files which were generated by unpack_and_setup + print("\nBIDS validation finished at:") + subprocess.check_call("date") + + except subprocess.CalledProcessError: + print("Error: BIDS validation failed.") + + +if __name__ == '__main__': + main() diff --git a/data/CHANGES b/data/CHANGES new file mode 100644 index 0000000..b75354c --- /dev/null +++ b/data/CHANGES @@ -0,0 +1,2 @@ +0.0.0 2018-08-22 + - Initial collection. diff --git a/data/README b/data/README new file mode 100644 index 0000000..0a87bb5 --- /dev/null +++ b/data/README @@ -0,0 +1,3 @@ +This data collection from the Oregon Health & Science University (OHSU) Developmental Cognition and Neuroimaging (DCAN) Labs contains a regularly updated dataset of ABCD Brain Imaging Data Structure (BIDS) version 1.2.0 pipeline inputs and derivatives. Source data are currently comprised of all the ABCD Study participants baseline year 1 arm 1 DICOM imaging data that passed initial acquisition quality control from the ABCD Data Analysis and Informatics Center (DAIC) and were processed by OHSU DCAN Labs. + +The input DICOM data to this BIDS version 1.2.0 (https://www.nature.com/articles/sdata201644) data collection were retrieved from the NIMH Data Archive (NDA) share of ABCD fast-track data (https://nda.nih.gov/edit_collection.html?id=2573) and were last accessed on May 1, 2019. BIDS input data were converted from DICOMs using Dcm2Bids (https://github.com/cbedetti/Dcm2Bids). BIDS derivatives data were derived from the OHSU DCAN Labs ABCD-BIDS MRI processing pipeline which outputs Human Connectome Project (HCP) Minimal Preprocessing Pipelines-style data in both volume and surface spaces (https://doi.org/10.5281/zenodo.2587210, https://doi.org/10.1016/j.neuroimage.2013.04.127). This collection is independent from ABCD Data Collection 2573. Users may access ABCD DICOM files via the ABCD fast-track imaging data release in Collection 2573. diff --git a/data/dataset_description.json b/data/dataset_description.json new file mode 100644 index 0000000..7581b0a --- /dev/null +++ b/data/dataset_description.json @@ -0,0 +1,41 @@ +{ + "Name": "OHSU DCAN Labs ABCD-BIDS MRI processing pipeline inputs and derivatives", + "BIDSVersion": "1.2.0", + "Authors": [ + "Eric Earl", + "Anders Perrone", + "Darrick Sturgeon", + "Kathy Snider", + "Anthony Galassi", + "Damien A. Fair, Ph.D.", + "Hauke Bartsch, Ph.D.", + "Donald J. Hagler, Ph.D.", + "Feng Xue, Ph.D.", + "Octavio Ruiz, Ph.D." + ], + "Acknowledgements": "The many other ABCD Study researchers who helped acquire and prepare this data. Full site listing here: https://abcdstudy.org/sites/abcd-sites.html", + "HowToAcknowledge": "Please cite this paper: B.J. Casey, Tariq Cannonier, May I. Conley, Alexandra O. Cohen, Deanna M. Barch, Mary M. Heitzeg, Mary E. Soules, Theresa Teslovich, Danielle V. Dellarco, Hugh Garavan, Catherine A. Orr, Tor D. Wager, Marie T. Banich, Nicole K. Speer, Matthew T. Sutherland, Michael C. Riedel, Anthony S. Dick, James M. Bjork, Kathleen M. Thomas, Bader Chaarani, Margie H. Mejia, Donald J. Hagler, M. Daniela Cornejo, Chelsea S. Sicat, Michael P. Harms, Nico U.F. Dosenbach, Monica Rosenberg, Eric Earl, Hauke Bartsch, Richard Watts, Jonathan R. Polimeni, Joshua M. Kuperman, Damien A. Fair, Anders M. Dale, The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites, Developmental Cognitive Neuroscience, Volume 32, 2018, Pages 43-54, ISSN 1878-9293, https://doi.org/10.1016/j.dcn.2018.03.001.", + "Funding": [ + "K01 DA037819 (MTS)", + "NSF Graduate Research Fellowship (AOC)", + "R00 MH091238 (DAF)", + "R01 MH096773 (DAF)", + "R01 MH115357 (DAF, JTN)", + "U01 DA041106 (MMH, MES)", + "U01 DA041120 (MTB, DMB, JMB, MH, NUFD, NKS, KMT)", + "U01 DA041148 (HG, RW, DAF, BN, SFE)", + "U01 DA041156 (ASD, MCR, ARL)", + "U01 DA041174 (BJC, TC, DVD, MIC, MR, TT, TDW)", + "U24 DA041123 (BJC, MDC, ASD, HB, DJH, JMK, JRP, CSS, DAF)", + "U24 DA041147 (HG, MHM)" + ], + "ReferencesAndLinks": [ + "https://abcdstudy.org/scientists-publications.html", + "The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Casey BJ, Cannonier T, Conley MI, Cohen AO, Barch DM, Heitzeg MM, Soules ME, Teslovich T, Dellarco DV, Garavan H, Orr CA, Wager TD, Banich MT, Speer NK, Sutherland MT, Riedel MC, Dick AS, Bjork JM, Thomas KM, Chaarani B, Mejia MH, Hagler DJ Jr, Daniela Cornejo M, Sicat CS, Harms MP, Dosenbach NUF, Rosenberg M, Earl E, Bartsch H, Watts R, Polimeni JR, Kuperman JM, Fair DA, Dale AM, ABCD Imaging Acquisition Workgroup. Dev Cogn Neurosci. 2018 Aug. doi: 10.1016/j.dcn.2018.03.001. Epub 2018 Mar 14. Review. PMID: 29567376.", + "Heritability of the human connectome: A connectotyping study. Miranda-Dominguez O, Feczko E, Grayson DS, Walum H, Nigg JT, Fair DA. Netw Neurosci. 2018 Jun 1. doi: 10.1162/netn_a_00029. eCollection 2018. PMID: 30215032.", + "ADHD and attentional control: Impaired segregation of task positive and task negative brain networks. Mills BD, Miranda-Dominguez O, Mills KL, Earl E, Cordova M, Painter J, Karalunas SL, Nigg JT, Fair DA. Netw Neurosci. 2018 Jun 1. doi: 10.1162/netn_a_00034. eCollection 2018. PMID: 30215033.", + "Individual differences in functional brain connectivity predict temporal discounting preference in the transition to adolescence. Anandakumar J, Mills KL, Earl EA, Irwin L, Miranda-Dominguez O, Demeter DV, Walton-Weston A, Karalunas S, Nigg J, Fair DA. Dev Cogn Neurosci. 2018 Nov. doi: 10.1016/j.dcn.2018.07.003. Epub 2018 Jul 30. PMID: 30121543.", + "Fair, Damien A; Miranda-Dominguez, Oscar; Snyder, Abraham Z; Perrone, Anders A; Earl, Eric A; Van, Andrew N; Koller, Jonathan M; Feczko, Eric; Klein, Rachel L; Mirro, Amy E. Correction of respiratory artifacts in MRI head motion estimates. bioRxiv. 2018." + ] +} + diff --git a/data/task-MID_bold.json b/data/task-MID_bold.json new file mode 100644 index 0000000..36343d7 --- /dev/null +++ b/data/task-MID_bold.json @@ -0,0 +1,5 @@ +{ + "TaskName": "Monetary Incentive Delay", + "CogAtlasID": "http://www.cognitiveatlas.org/task/id/trm_4f23fc8c42d28/", + "CogPOID": "http://wiki.cogpo.org/index.php?title=Delay_Discounting_Task_Paradigm" +} diff --git a/data/task-SST_bold.json b/data/task-SST_bold.json new file mode 100644 index 0000000..6a6468b --- /dev/null +++ b/data/task-SST_bold.json @@ -0,0 +1,5 @@ +{ + "TaskName": "Stop-Signal Task", + "TaskDescription": "See https://www.psytoolkit.org/experiment-library/stopsignal.html", + "CogAtlasID": "http://www.cognitiveatlas.org/task/id/tsk_4a57abb949e1a/" +} diff --git a/data/task-nback_bold.json b/data/task-nback_bold.json new file mode 100644 index 0000000..2eb8495 --- /dev/null +++ b/data/task-nback_bold.json @@ -0,0 +1,6 @@ +{ + "TaskName": "n-back", + "TaskDescription": "See https://en.wikipedia.org/wiki/N-back", + "CogAtlasID": "http://www.cognitiveatlas.org/task/id/tsk_4a57abb949bcd/", + "CogPOID": "http://wiki.cogpo.org/index.php?title=N-back_Paradigm" +} diff --git a/data/task-rest_bold.json b/data/task-rest_bold.json new file mode 100644 index 0000000..23d40bf --- /dev/null +++ b/data/task-rest_bold.json @@ -0,0 +1,6 @@ +{ + "TaskName": "Resting State (eyes open)", + "TaskDescription": "See http://www.cognitiveatlas.org/task/id/tsk_4a57abb949e1a/", + "CogAtlasID": "http://www.cognitiveatlas.org/task/id/trm_4c8a834779883/", + "CogPOID": "http://wiki.cogpo.org/index.php?title=Rest_Paradigm" +} diff --git a/raw/README.md b/raw/README.md new file mode 100644 index 0000000..0bc9863 --- /dev/null +++ b/raw/README.md @@ -0,0 +1,3 @@ +# `raw` folder + +This folder will contain all of the raw files downloaded directly from the NDA website after `abcd2bids.py` is run. Other than this README, it does not need to contain anything before running `abcd2bids.py`. After running `abcd2bids.py`, this folder will contain one subdirectory for each ABCD subject session downloaded from the NDA. \ No newline at end of file diff --git a/spreadsheets/README.md b/spreadsheets/README.md index fd097af..8e4c568 100644 --- a/spreadsheets/README.md +++ b/spreadsheets/README.md @@ -4,4 +4,6 @@ This is where the spreadsheets belong: 1. `DAL_ABCD_merged_pcqcinfo.csv` (the DAIC QC info) 1. `image03.txt` (the NDA DICOM imaging data info) -1. `ABCD_good_bad_series_table.csv` (generated after `data_gatherer.m` is run) +1. `ABCD_good_bad_series_table.csv` (generated after `data_gatherer` is run) + +The `DAL_ABCD_merged_pcqcinfo.csv` is currently only available from the ABCD DAIC. So, it is only accessible for someone within the ABCD consortium (who can access ABCD data on the NDA website). However, the MRI QC scores will soon be uploaded to NDA. Afterwards, this script will be updated to download that file and read from it instead of requiring the user to manually get the `DAL_ABCD_merged_pcqcinfo.csv` spreadsheet. diff --git a/src/FSL_identity_transformation_matrix.mat b/src/FSL_identity_transformation_matrix.mat new file mode 100755 index 0000000..00451f0 --- /dev/null +++ b/src/FSL_identity_transformation_matrix.mat @@ -0,0 +1,4 @@ +1.000000 0.000000 0.000000 0.000000 +0.000000 1.000000 0.000000 0.000000 +0.000000 0.000000 1.000000 0.000000 +0.000000 0.000000 0.000000 1.000000 diff --git a/src/README.md b/src/README.md new file mode 100644 index 0000000..cbcef9d --- /dev/null +++ b/src/README.md @@ -0,0 +1,28 @@ +# `src` folder + +This folder contains all of the scripts used by the `abcd2bids.py` wrapper. There should be 13 files in this folder, as well as a `bin` subdirectory. + +## Files belonging in this folder + +#### Metadata: +1. `__init__.py` +1. `README.md` + +#### Scripts used to create NDA token to download NDA data: +1. `nda_aws_token_generator.py` +1. `nda_aws_token_maker.py` + +#### Scripts used to download NDA data: +1. `FSL_identity_transformation_matrix.mat` +1. `good_bad_series_parser.py` +1. `mapping.mat` + +#### Scripts used to unpack and setup NDA data: +1. `eta_squared` +1. `run_eta_squared.sh` +1. `run_order_fix.py` +1. `sefm_eval_and_json_editor.py` +1. `unpack_and_setup.sh` + +#### Scripts used to make NDA data meet BIDS standards: +1. `correct_jsons.py` diff --git a/src/__init__.py b/src/__init__.py new file mode 100644 index 0000000..e0f06e7 --- /dev/null +++ b/src/__init__.py @@ -0,0 +1,2 @@ +from src.nda_aws_token_maker import * +from src.nda_aws_token_generator import * diff --git a/src/bin/data_gatherer b/src/bin/data_gatherer new file mode 100755 index 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Prerequisites for Deployment + +. Verify the MATLAB Runtime is installed and ensure you + have installed version 9.2 (R2017a). + +. If the MATLAB Runtime is not installed, do the following: + (1) enter + + >>mcrinstaller + + at MATLAB prompt. The MCRINSTALLER command displays the + location of the MATLAB Runtime installer. + + (2) run the MATLAB Runtime installer. + +Or download the Linux 64-bit version of the MATLAB Runtime for R2017a +from the MathWorks Web site by navigating to + + http://www.mathworks.com/products/compiler/mcr/index.html + + +For more information about the MATLAB Runtime and the MATLAB Runtime installer, see +Package and Distribute in the MATLAB Compiler documentation +in the MathWorks Documentation Center. + + +2. Files to Deploy and Package + +Files to package for Standalone +================================ +-data_gatherer +-run_data_gatherer.sh (shell script for temporarily setting environment variables and + executing the application) + -to run the shell script, type + + ./run_data_gatherer.sh + + at Linux or Mac command prompt. is the directory + where version 9.2 of the MATLAB Runtime is installed or the directory where + MATLAB is installed on the machine. is all the + arguments you want to pass to your application. For example, + + If you have version 9.2 of the MATLAB Runtime installed in + /mathworks/home/application/v92, run the shell script as: + + ./run_data_gatherer.sh /mathworks/home/application/v92 + + If you have MATLAB installed in /mathworks/devel/application/matlab, + run the shell script as: + + ./run_data_gatherer.sh /mathworks/devel/application/matlab +-MCRInstaller.zip + -if end users are unable to download the MATLAB Runtime using the above + link, include it when building your component by clicking + the "Runtime downloaded from web" link in the Deployment Tool +-This readme file + +3. Definitions + +For information on deployment terminology, go to +http://www.mathworks.com/help. Select MATLAB Compiler > +Getting Started > About Application Deployment > +Deployment Product Terms in the MathWorks Documentation +Center. + + +4. Appendix + +A. Linux x86-64 systems: +In the following directions, replace MCR_ROOT by the directory where the MATLAB Runtime + is installed on the target machine. + +(1) Set the environment variable XAPPLRESDIR to this value: + + MCR_ROOT/v92/X11/app-defaults + + +(2) If the environment variable LD_LIBRARY_PATH is undefined, set it to the concatenation + of the following strings: + + MCR_ROOT/v92/runtime/glnxa64: + MCR_ROOT/v92/bin/glnxa64: + MCR_ROOT/v92/sys/os/glnxa64: + MCR_ROOT/v92/sys/opengl/lib/glnxa64 + + If it is defined, set it to the concatenation of these strings: + + ${LD_LIBRARY_PATH}: + MCR_ROOT/v92/runtime/glnxa64: + MCR_ROOT/v92/bin/glnxa64: + MCR_ROOT/v92/sys/os/glnxa64: + MCR_ROOT/v92/sys/opengl/lib/glnxa64 + + For more detail information about setting the MATLAB Runtime paths, see Package and + Distribute in the MATLAB Compiler documentation in the MathWorks Documentation Center. + + + + NOTE: To make these changes persistent after logout on Linux + or Mac machines, modify the .cshrc file to include this + setenv command. + NOTE: The environment variable syntax utilizes forward + slashes (/), delimited by colons (:). + NOTE: When deploying standalone applications, it is possible + to run the shell script file run_data_gatherer.sh + instead of setting environment variables. See + section 2 "Files to Deploy and Package". + + + + + + diff --git a/src/bin/run_data_gatherer.sh b/src/bin/run_data_gatherer.sh new file mode 100755 index 0000000..591d3d1 --- /dev/null +++ b/src/bin/run_data_gatherer.sh @@ -0,0 +1,36 @@ +#!/bin/sh +# script for execution of deployed applications +# +# Sets up the MATLAB Runtime environment for the current $ARCH and executes +# the specified command. +# +exe_name=$0 +exe_dir=`dirname "$0"` +echo "------------------------------------------" +if [ "x$1" = "x" ]; then + echo Usage: + echo $0 \ args +else + echo Setting up environment variables + MCRROOT="$1" + echo --- + LD_LIBRARY_PATH=.:${MCRROOT}/runtime/glnxa64 ; + LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${MCRROOT}/bin/glnxa64 ; + LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${MCRROOT}/sys/os/glnxa64; + LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${MCRROOT}/sys/opengl/lib/glnxa64; + export LD_LIBRARY_PATH; + echo LD_LIBRARY_PATH is ${LD_LIBRARY_PATH}; + shift 1 + RANDHASH=`cat /dev/urandom | tr -cd "a-f0-9" | head -c 8` + export MCR_CACHE_ROOT=$TMPDIR/$USER/$RANDHASH + mkdir -p $MCR_CACHE_ROOT + args= + while [ $# -gt 0 ]; do + token=$1 + args="${args} \"${token}\"" + shift + done + eval "\"${exe_dir}/data_gatherer\"" $args +fi +exit + diff --git a/src/correct_jsons.py b/src/correct_jsons.py new file mode 100755 index 0000000..958a414 --- /dev/null +++ b/src/correct_jsons.py @@ -0,0 +1,115 @@ +#! /usr/bin/env python3 + +import json,os,sys,argparse,re + +__doc__ = \ +""" +This scripts is meant to correct ABCD BIDS input data to +conform to the Official BIDS Validator. +""" +__version__ = "1.0.0" + +def read_json_field(json_path, json_field): + + with open(json_path, 'r') as f: + data = json.load(f) + + if json_field in data: + return data[json_field] + else: + return None + +def remove_json_field(json_path, json_field): + + with open(json_path, 'r+') as f: + data = json.load(f) + + if json_field in data: + del data[json_field] + f.seek(0) + json.dump(data, f, indent=4) + f.truncate() + flag = True + else: + flag = False + + return flag + +def update_json_field(json_path, json_field, value): + + with open(json_path, 'r+') as f: + data = json.load(f) + + if json_field in data: + flag = True + else: + flag = False + + data[json_field] = value + f.seek(0) + json.dump(data, f, indent=4) + f.truncate() + + return flag + +def main(argv=sys.argv): + parser = argparse.ArgumentParser( + prog='correct_jsons.py', + description=__doc__, + usage='%(prog)s BIDS_DIR' + ) + parser.add_argument( + 'BIDS_DIR', + help='Path to the input BIDS dataset root directory. Read more ' + 'about the BIDS standard in the link in the description. It is ' + 'recommended to use Dcm2Bids to convert from participant dicoms ' + 'into BIDS format.' + ) + parser.add_argument( + '--version', '-v', action='version', version='%(prog)s ' + __version__ + ) + + args = parser.parse_args() + + for root, dirs, files in os.walk(args.BIDS_DIR): + for filename in files: + fn, ext = os.path.splitext(filename) + + if ext == '.json': + json_path = os.path.join(root, filename) + + with open(json_path, 'r') as f: + data = json.load(f) + + # If TotalReadoutTime is missing from fmap JSON + if ('fmap' in root or 'func' in root) and 'TotalReadoutTime' not in data: + # Then check for EffectiveEchoSpacing and ReconMatrixPE + if 'EffectiveEchoSpacing' in data and 'ReconMatrixPE' in data: + # If both are present then update the JSON with a calculated TotalReadoutTime + EffectiveEchoSpacing = data['EffectiveEchoSpacing'] + ReconMatrixPE = data['ReconMatrixPE'] + # Calculated TotalReadoutTime = EffectiveEchoSpacing * (ReconMatrixPE - 1) + TotalReadoutTime = EffectiveEchoSpacing * (ReconMatrixPE - 1) + update_json_field(json_path, 'TotalReadoutTime', TotalReadoutTime) + + # If EffectiveEchoSpacing is missing print error + if 'EffectiveEchoSpacing' not in data: + print(json_path + ': No EffectiveEchoSpacing') + + # If ReconMatrixPE is missing print error + if 'ReconMatrixPE' not in data: + print(json_path + ': No ReconMatrixPE') + + # Find the IntendedFor field that is a non-empty list + if 'fmap' in root and 'IntendedFor' in data and len(data['IntendedFor']) > 0: + # Regular expression replace all paths in that list with a relative path to ses-SESSION + intended_list = data['IntendedFor'] + corrected_intended_list = [re.sub(r'.*(ses-.*_ses-.+)','\g<1>',entry) for entry in intended_list] + update_json_field(json_path, 'IntendedFor', corrected_intended_list) + + # Remove SliceTiming field from func JSONs + if 'func' in root and 'SliceTiming' in data: + remove_json_field(json_path, 'SliceTiming') + +if __name__ == "__main__": + 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