bb_pipeline_func.py

#!/bin/env python
#
# Script name: bb_pipeline_func.py
#
# Description: Script with the functional pipeline.
# 			   This script will call the rest of functional functions.
#
# Authors: Fidel Alfaro-Almagro, Stephen M. Smith & Mark Jenkinson
#
# Copyright 2017 University of Oxford
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import bb_pipeline_tools.bb_logging_tool as LT
import os.path


def bb_pipeline_func(subject, jobHold, fileConfiguration):

    logger = LT.initLogging(__file__, subject)
    logDir = logger.logDir
    baseDir = logDir[0 : logDir.rfind("/logs/")]

    jobsToWaitFor = ""

    subname = subject.replace("/", "_")

    st = (
        # '${FSLDIR}/bin/fsl_sub -T 5 -N "bb_postprocess_struct_'
        '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_postprocess_struct_'
        + subname
        + '" -l '
        + logDir
        + " -j "
        + str(jobHold)
        + " $BB_BIN_DIR/bb_functional_pipeline/bb_postprocess_struct "
        + subject
    )

    # print(st)

    jobPOSTPROCESS = LT.runCommand(
        logger,
        #'${FSLDIR}/bin/fsl_sub -T 5 -N "bb_postprocess_struct_'
        '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_postprocess_struct_'
        + subname
        + '" -l '
        + logDir
        + " -j "
        + str(jobHold)
        + " $BB_BIN_DIR/bb_functional_pipeline/bb_postprocess_struct "
        + subject,
    )

    # TODO: Embed the checking of the fieldmap inside the independent steps -- Every step should check if the previous one has ended.
    rfMRI_nums = [k.split("_")[-1] for k in fileConfiguration.keys() if "rfMRI" in k]
    print(f"FILE CONFIG IN FUNC: {fileConfiguration}")
    # if ("rfMRI" in fileConfiguration) and (fileConfiguration["rfMRI"] != ""):
    for i in range(len(rfMRI_nums)):

        jobGEFIELDMAP = LT.runCommand(
            logger,
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_STANDARD} -N "tvb_prepare_gradEchoFieldMap_'
            + subname
            + '" -l '
            + logDir
            + " -j "
            + jobPOSTPROCESS
            + " $$BB_BIN_DIR/bb_functional_pipeline/tvb_prepare_gradEchoFieldMap "
            + subject
        )
        jobPREPARE_R = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T 15   -N "bb_prepare_rfMRI_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM}   -N "bb_prepare_rfMRI_'
            + subname
            + '"  -l '
            + logDir
            + " -j "
            + jobGEFIELDMAP
            + " $BB_BIN_DIR/bb_functional_pipeline/bb_prepare_rfMRI "
            + subject
            + f" {rfMRI_nums[i]}",
        )
        jobFEAT_R = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T 1200 -N "bb_feat_rfMRI_ns_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_feat_rfMRI_ns_'
            + subname
            + '"  -l '
            + logDir
            + " -j "
            + jobPREPARE_R
            + " feat "
            + baseDir
            #
            + f"/fMRI/rfMRI_{i}.fsf " + subject,
        )
        jobFIX = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T 175  -N "bb_fix_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MAX_MEM}  -N "bb_fix_'
            + subname
            + '"  -l '
            + logDir
            + " -j "
            + jobFEAT_R
            + " $BB_BIN_DIR/bb_functional_pipeline/bb_fix "
            + subject
            + f" {rfMRI_nums[i]}",
        )
        ### compute FC using parcellation
        jobFC = LT.runCommand(
            logger,
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_FC_'
            + subname
            + '"  -l '
            + logDir
            + " -j "
            + jobFIX
            + " $BB_BIN_DIR/bb_functional_pipeline/bb_FC "
            + subject
            + f" {rfMRI_nums[i]}",
        )
        ### don't generate group-ICA RSNs
        # jobDR = LT.runCommand(
        # logger,
        ##'${FSLDIR}/bin/fsl_sub -T 120  -N "bb_ICA_dr_'
        #'${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM}  -N "bb_ICA_dr_'
        # + subname
        # + '"  -l '
        # + logDir
        # + " -j "
        # + jobFIX
        # + " $BB_BIN_DIR/bb_functional_pipeline/bb_ICA_dual_regression "
        # + subject,
        # )
        jobCLEAN = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T 5  -N "bb_rfMRI_clean_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM}  -N "bb_rfMRI_clean_'
            + subname
            + '"  -l '
            + logDir
            + " -j "
            # + jobDR
            + jobFC
            + " $BB_BIN_DIR/bb_functional_pipeline/bb_clean_fix_logs "
            + subject
            + f" {rfMRI_nums[i]}",
        )

        jobsToWaitFor = jobCLEAN

    else:
        logger.error(
            "There is no rFMRI info. Thus, the Resting State part will not be run"
        )

    if jobsToWaitFor != "":
        jobsToWaitFor += ","
    tfMRI_nums = [
        k.split("_")[-1]
        for k in fileConfiguration.keys()
        if "tfMRI" in k and k != "tfMRI_SBREF"
    ]
    # if ("rfMRI" in fileConfiguration) and (fileConfiguration["rfMRI"] != ""):
    for i in range(len(tfMRI_nums)):
        # if ("tfMRI" in fileConfiguration) and (fileConfiguration["tfMRI"] != ""):
        jobPREPARE_T = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T  15 -N "bb_prepare_tfMRI_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_prepare_tfMRI_'
            + subname
            + '" -l '
            + logDir
            + " -j "
            + jobPOSTPROCESS
            + " $BB_BIN_DIR/bb_functional_pipeline/bb_prepare_tfMRI "
            + subject
            + f" {rfMRI_nums[i]}",
        )
        jobFEAT_T = LT.runCommand(
            logger,
            #'${FSLDIR}/bin/fsl_sub -T 400 -N "bb_feat_tfMRI_'
            '${FSLDIR}/bin/fsl_sub -q ${QUEUE_MORE_MEM} -N "bb_feat_tfMRI_'
            + subname
            + '" -l '
            + logDir
            + " -j "
            + jobPREPARE_T
            + " feat  "
            + baseDir
            + f"/fMRI/tfMRI_{i}.fsf",
        )

        if jobsToWaitFor != "":
            # jobsToWaitFor = jobsToWaitFor + "," + jobFEAT_T
            jobsToWaitFor += f",{jobFEAT_T}"
        else:
            jobsToWaitFor = jobFEAT_T

    else:
        logger.error(
            "There is no tFMRI info. Thus, the Task Functional part will not be run"
        )

    if jobsToWaitFor == "":
        jobsToWaitFor = "-1"

    print("SUBMITTED FUNCTIONAL")

    return jobsToWaitFor