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settings_template.py
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settings_template.py
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class local_settings():
def __init__(self):
self.remote_path = "/data/imagen/2.7" #the remote path on the sftp server
self.local_path ="/my/local/datapath/" #your local path where the data will be downloaded
self.log_path ="/my/local/download_logs" #give a path where logs can be saved
class dl_settings():
def __init__(self, description, mode, time_dirs, overall_dirs, intermed_dir1, subjs, dirs, subj_files):
self.description = description
# string, short description what the given settings will do
# e.g. "download available data from all timepoints and subjects for imaging/spm_first_level/.../EPI_short_MID/",
self.mode = mode # string, "files" or "dirs" or "subjects" or "overall"
# the folder structure of the server is: remote_path/{time_dirs}/intermed_dirs/
# some of the intermed_dirs (e.g. imaging/spm*) are organised as follows: remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}
# the "mode" setting provides several ways of downloading parts of the data, using different hierarchies
# "overall": download all directories, subdirectories and files within the given folders remote_path/{time_dirs}/{overall_dirs}
# "dirs": download n directories per subject within remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}
# "files": download n files from folder remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}/{subj_files}
# dirs should have only one entry in this case, because files are expected to be present within each dir
# "subjects": dowload n subject folders from: remote_path/{time_dirs}/intermed_dir/
self.time_dirs = time_dirs
# list of strings, example: ["BL","FU1","FU2","FU3"]
self.overall_dirs = overall_dirs
# list of strings, e.g. ["dawba/", "geolocation/", "cantab/", "meta_data/", "psytools/"]
self.intermed_dir1 = intermed_dir1
# string, e.g. "imaging/spm_first_level"
self.subjs = subjs
# list of strings, e.g. ["000099616225", "000085724167"]
# leave empty (self.subjs = [])to download all available subj-subdirectories within intermed_dir1
self.dirs = dirs
# list of strings, e.g. ["EPI_stop_signal/", "EPI_short_MID/"]
self.subj_files = subj_files
# list of strings, e.g. ["con_0006_stop_failure_-_stop_success.nii.gz",
# "con_0005_stop_success_-_stop_failure.nii.gz"]
# if mode = "dir" subj_files is ignored
dl_fMRI_MID = dl_settings(
## commented example
description = "download available data from baseline of all subjects for imaging/spm_first_level/.../EPI_short_MID/, just contrast images",
mode = "files", # string, "files" or "dirs" or "subjects" or "overall"
# the folder structure of the server is: remote_path/{time_dirs}/intermed_dirs/
# some of the intermed_dirs (e.g. imaging/spm*) are organised as follows: remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}
# the "mode" setting provides several ways of downloading parts of the data, using different hierarchies
# "overall": download all directories, subdirectories and files within the given folders remote_path/{time_dirs}/{overall_dirs}
# "dirs": download n directories per subject within remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}
# "files": download n files from folder remote_path/{time_dirs}/intermed_dir/{subjs}/{dirs}/{subj_files}
# Unix-style wildcards can be used
# "subjects": download n subject folders from: remote_path/{time_dirs}/intermed_dir/
time_dirs = ["BL"],
# list of strings, example: ["BL","FU1","FU2","FU3"]
overall_dirs = [],
# list of strings, e.g. ["dawba/", "geolocation/", "cantab/", "meta_data/", "psytools/"]
intermed_dir1 = "imaging/spm_first_level",
# string, e.g. "imaging/spm_first_level"
subjs = [],
# list of strings, e.g. ["000099616225", "000085724167"]
# leave empty (self.subjs = [])to download all available subj-subdirectories within intermed_dir1
dirs = ["EPI_short_MID/"],
# list of strings, e.g. ["EPI_stop_signal/", "EPI_short_MID/"]
subj_files = ['con*'],
#subj_files = ["rp_nuisance_extended.txt"]
# list of strings, e.g. ["con_0006_stop_failure_-_stop_success.nii.gz",
# "con_0005_stop_success_-_stop_failure.nii.gz"]
# UNIX-style wildcards can be used to download all matching files (e.g. ['con*','*.txt*']
# if mode = "dir" subj_files is ignored
)
#further examples
dl_fMRI_all_FU2 = dl_settings(
description = "download available data from all subjects at FU2 for imaging/spm_first_level/",
mode = "subjects",
time_dirs = ["FU2"],
overall_dirs = [],
intermed_dir1 = "imaging/spm_first_level",
subjs = [],
dirs = [],
subj_files = []
)
dl_fMRI_Face = dl_settings(
description = "download data of subjects 000099616225, 000085724167 from all timepoints for imaging/spm_first_level/EPI_faces",
mode = "dirs",
time_dirs = ["BL","FU1"],
overall_dirs = [],
intermed_dir1 = "imaging/spm_first_level",
subjs = ["000099616225", "000085724167"],
dirs = ["EPI_faces"],
subj_files = []
)
dl_overall_data = dl_settings(
description = "download available data from overall folders (dawba,geolocation,cantab,meta_data,psytools)",
mode = "overall",
time_dirs = ["BL","FU1","FU2","FU3"],
overall_dirs = ["dawba/", "geolocation/", "cantab/", "meta_data/", "psytools/"],
intermed_dir1 = "",
subjs = [],
dirs = [],
subj_files = []
)
#put all definitions here into a list named dl_tasks, and they will be downloaded sequentially
dl_tasks = [
dl_fMRI_MID,
dl_overall_data
]
#dl_tasks = [
# dl_overall_data
#]
#dl_tasks =[
# dl_fMRI_all_FU2
#]
#dl_tasks =[
# dl_fMRI_Face
#]