Read & Write a DataCube

The hsi-wizard module provides basic functions for reading and writing a DataCube. For more information visit loader chapter.

Supported DataCube File Formats

Extension	Read Supported	Write Supported
.csv	✅	✅
.xlsx	✅	✅
.tdms	✅	❌
.fsm	✅	❌
.folder	✅	❌
.nrrd	✅	❌
.image	✅	❌
.hdr	✅	✅

Note

The wizard.read() function serves as the main entry point for users. It abstracts the file handling process and automatically determines the appropriate handler based on the file type.

Writing a DataCube

csv

This snippet shows how to generate a random DataCube, write it to a .csv file using the wizard._utils._loader.csv module, and read it back into a new DataCube, preserving the original data shape and structure.

"""
Demonstrate DataCube CSV serialization and deserialization.
"""

import wizard
import numpy as np
from wizard._utils._loader import csv

# generate a random DataCube with 22 spectral bands and a 10×8 spatial grid
dc = wizard.DataCube(np.random.rand(22, 10, 8))

# write the DataCube to 'test.csv'
csv._write_csv(dc, filename='test.csv')

# load DataCube directly using wizard.read
new_dc = wizard.read('test.csv')
# csv._read_csv also works
# new_dc = csv._read_csv('test.csv')

# confirm that the read-back DataCube matches the original shape
print(new_dc.shape)

Output:

(22, 10, 8)

xlsx

Similar to the snippet above, this example shows how to generate a random DataCube, write it to a .xlsx file using the wizard._utils._loader.xlsx module, and read it back into a new DataCube.

"""
Demonstrate DataCube XLSX serialization and deserialization.
"""

import os
import wizard
import numpy as np
from wizard._utils._loader import xlsx

# generate a random DataCube with 22 spectral bands and a 10×8 spatial grid
dc = wizard.DataCube(np.random.rand(22, 10, 8))

# write the DataCube to 'test.xlsx'
xlsx._write_xlsx(dc, filename='test.xlsx')

# load DataCube directly from the xlsx file
new_dc = xlsx._read_xlsx('test.xlsx')

# confirm that the read-back DataCube matches the original shape
print(new_dc.shape)

Output:

(22, 10, 8)