1. JHTD(Johns Hopkins Turbulence Database) module

This module is developed to handle data from JHTD. Details: Parse parameters required to get a cutout of the JHTD data. By default, it downloads a cutout of isotropic turbulence (coarse).

1.1. Overview

Specify

1.2. Example Usage

Example:

python cutout.py -dir '~/Desktop/' -t0 0 -x0 0 -y0 0 -z0 512 -tl 10 -xl 10 -yl 10 -zl 10 -verbose False

1.3. Functions and Classes

cutout.get_big_cutout(filename='./test', t0=0, tl=1, x0=0, xl=32, y0=0, yl=32, z0=0, zl=32, chunk_xdim=16, chunk_ydim=16, chunk_zdim=16, data_set='isotropic1024coarse', data_type='u', auth_token='edu.uchicago.tmatsuzawa-5e4905e2', base_website='dsp033.pha.jhu.edu')

Recommended to use this method in case of downloading large data from JHTD. This splits the large data into small chunks, and downloads them. Construct a large hdf5 at the end. If connection gets lost, run the method again with the same parameters to resume.

Parameters:

filename: str, full path where data will be stored

t0: int, starting time. Choose from [0,5023]. def:0

tl: int, duration to download. Must be less than 5024-t0. tl=1 corresponds to 10DNS steps for isotropic1024coarse data. def:1

x0: int, starting x-coordinate. Choose from [0,1023]. def:32

xl: int, length in x to download. Choose from [1,1024]

y0: int, starting y-coordinate. Choose from [0,1023]. def:32

yl: int, length in y to download. Choose from [1,1024]

z0: int, starting z-coordinate. Choose from [0,1023]. def:32

zl: int, length in z to download. Choose from [1,1024]

chunk_xdim: int, length in x of a small chunk to download every trial. def: 16

chunk_ydim: int, length in y of a small chunk to download every trial. def: 16

chunk_zdim: int, length in z of a small chunk to download every trial. def: 16

data_set: str, name of dataset registered on JHTD. def: ‘isotropic1024coarse’

data_type: str, name of data to download. choices are ‘u’, ‘p’, ‘a’, ‘b’. def: ‘u’

auth_token: str, token registed on JHTD. def: ‘edu.uchicago.tmatsuzawa-5e4905e2’

base_website: str, website where data lies. def: ‘dsp033.pha.jhu.edu’

Returns:

None

cutout.convert_dict(dset, delimiter='_')

Converts a dictionary to a string e.g. {“key0”: 0, “key1”: 1} -> “key0_0_key1_1”

Parameters:

dset: dict

delimiter: str, default is _

Returns:

string

cutout.date()

Returns the date in the format “year_month_day” Returns ——- date: str, “year_month_day”

cutout.recover(log_file)

From a log file containing the dset information to download, try again to download data

cutout.write_header(f, keys)

Writes keys as a header of a file Parameters ———- f: file keys: list/tuple

cutout.write_line(f, list0, delimiter='\t')

Writes elements in a list in a file Parameters ———- f: file list0: list delimiter

cutout.read_dataFile(file, Hdelimiter=', ', Ddelimiter=', ', Oneline=False)

Basic function for reading a .txt dataFile

The data file format has to be as following: Header of one or more lines containing the title of each dataset in the last Header line. Data are presented into columns, separated by a given character Ddelimiter