prepare_tutorial.py

# import sys
# sys.path.insert(0, "./") # add path for import
import tigress_read  # scripts for reading data

# Master directory where the data is stored
dir_master = "./data/"
# Snapshot number
num = 300

# A snapshot can be downloaded using `download` method.
# dataset can be one of
# ["MHD", "MHD_PI", "chem", "CO_lines", "history", "input", "all"]

## R8_4pc MHD
while True:
    download_ok = input("Download 4pc MHD data [750MB]? (y/n):")
    if download_ok.lower() in ["y", "n"]:
        break
if download_ok.lower() == "y":
    # read the model information
    model_4pc = tigress_read.Model("R8_4pc", dir_master=dir_master)
    # download data
    model_4pc.download(num, dataset="history")
    model_4pc.download(num, dataset="input")
    model_4pc.download(num, dataset="MHD")

## R8_4pc MHD_PI
while True:
    download_ok = input("Download 4pc MHD_PI data [3.9GB]? (y/n):")
    if download_ok.lower() in ["y", "n"]:
        break
if download_ok.lower() == "y":
    # read the model information
    model_4pc = tigress_read.Model("R8_4pc", dir_master=dir_master)
    # download data
    model_4pc.download(num, dataset="history")
    model_4pc.download(num, dataset="input")
    model_4pc.download(num, dataset="MHD_PI")


while True:
    download_ok = input("Download 2pc MHD/CO data [6GB]? (y/n):")
    if download_ok.lower() in ["y", "n"]:
        break
if download_ok.lower() == "y":
    model_id_2pc = "R8_2pc"  # name of the simulation model
    model_2pc = tigress_read.Model(model_id_2pc, dir_master=dir_master)
    # reading the model information
    model_2pc.download(num, dataset="history")
    model_2pc.download(num, dataset="input")
    model_2pc.download(num, dataset="MHD")
    model_2pc.download(num, dataset="CO_lines", iline=1)  # CO(J=1-0)
    model_2pc.download(num, dataset="CO_lines", iline=2)  # CO(J=2-1)

while True:
    download_ok = input("Download 2pc full chemistry data [15GB]? (y/n):")
    if download_ok.lower() in ["y", "n"]:
        break

if download_ok.lower() == "y":
    model_2pc.download(num, dataset="chem")  # large file 15GB