Convertire USGS Spectral LIbrary in formato Envi

 

 

import os

import pandas as pd

import numpy as np

import spectral.io.envi as envi

def create_envi_library(input_folder, output_filename):

spectra_data = []

names = []

wavelengths = None

files = sorted([f for f in os.listdir(input_folder) if f.endswith('.txt')])

if not files:

print("No .txt files found in the directory!")

return

for file in files:

file_path = os.path.join(input_folder, file)

try:

df = pd.read_csv(file_path, sep=r'\s+', comment='#', header=None, engine='python')

# Clean up: ensure we only have numeric rows

df = df[pd.to_numeric(df[0], errors='coerce').notnull()]

df = df.astype(float)

if wavelengths is None:

wavelengths = df[0].values

spectra_data.append(df[1].values)

names.append(os.path.splitext(file)[0])

print(f"Processed: {file}")

except Exception as e:

print(f"Skipping {file}: {e}")

lib_array = np.array(spectra_data).astype(np.float32)

lib_array = lib_array.reshape((lib_array.shape[0], 1, lib_array.shape[1]))

lib_array[lib_array < -100] = 0

metadata = {

'file type': 'ENVI Spectral Library',

'wavelength': list(wavelengths.astype(str)),

'wavelength units': 'Micrometers',

'spectra names': names,

'data type': 4, # Float32

'interleave': 'bsq'

}

output_path = output_filename if output_filename.endswith('.sli') else output_filename + '.sli'

envi.save_image(output_path + '.hdr', lib_array, metadata=metadata, force=True)

print(f"\nSuccess! Created {output_path} and associated header.")

# Usage

input_dir = '/home/luca/Downloads/ASCIIdata/ASCIIdata_splib07b_cvASD/ChapterM_Minerals'

output_name = 'USGS_splib07b_ASD_Library'

create_envi_library(input_dir, output_name)