def test_spc_file(filename, spectrum_shape, wavelength_shape):
spec = specread(filename)
if isinstance(spec, list):
# in '-xy.spc', there is two different wavelength size: we are checking
# each of them
for wi in range(1):
assert spec[wi].spectrum.shape == spectrum_shape[wi]
assert spec[wi].wavelength.shape == wavelength_shape[wi]
else:
assert spec.spectrum.shape == spectrum_shape
assert spec.wavelength.shape == wavelength_shape
def test_spectrum_to_csv(filename):
spec = specread(filename)
tmp_dir = mkdtemp()
filename = os.path.join(tmp_dir, 'spectra.csv')
try:
spec.to_csv(filename)
df = pd.read_csv(filename, index_col=0)
df.columns = df.columns.astype(float)
assert_allclose(df.values, spec.to_dataframe().values)
assert_allclose(df.columns.values, spec.to_dataframe().columns.values)
assert_array_equal(df.index.values, spec.to_dataframe().index.values)
finally:
rmtree(tmp_dir)
def test_specread(filename, filename_cmp, spectrum_shape, wavelength_shape):
spec = specread(filename)
if isinstance(spec, Spectrum):
_check_spectra(spec, filename, filename_cmp, spectrum_shape,
wavelength_shape)
elif isinstance(spec, list):
assert all([isinstance(sp, Spectrum) for sp in spec])
sp = spec[0]
_check_spectra(sp, filename, filename_cmp, spectrum_shape,
wavelength_shape)
else:
raise AssertionError('specread should return either a Spectrum '
'instance or a list of Spectrum. '
'Got {!r}.'.format(spec))
def test_specread_consitent_wavelength(side_effect, tol_wavelength,
spectra_type, spectra_shape, mocker):
# emulate that we read several file
mocker.patch('specio.core.functions._validate_filenames',
return_value=['filename' for _ in range(10)])
mocker.patch('specio.core.functions._get_reader_get_data',
side_effect=side_effect)
# emulate the spectrum reading
spectra = specread('', tol_wavelength=tol_wavelength)
assert isinstance(spectra, spectra_type)
if isinstance(spectra, Spectrum):
assert spectra.amplitudes.shape == spectra_shape
assert spectra.wavelength.shape == (spectra_shape[1], )
assert spectra.meta == tuple({} for _ in range(spectra_shape[0]))
elif isinstance(spectra, list):
assert len(spectra) == spectra_shape
""" ==================================================== Read SPC Galactic Industries Corporation binary file ==================================================== This example shows how to read SPC file and plot the results. """ from __future__ import print_function import matplotlib.pyplot as plt from specio import specread from specio.datasets import load_spc_path # Find the path to the SPC toy data spc_filename = load_spc_path() print(spc_filename) # Read the data spectra = specread(spc_filename) # Plot the first spectra plt.plot(spectra.wavelength, spectra.spectrum[0]) plt.xlabel(spectra.meta['xlabel']) plt.ylabel(spectra.meta['ylabel']) plt.show()
def test_spc_xy():
filename = join(DATA_PATH, 'data', 'gxy.spc')
spec = specread(filename)
assert spec.spectrum.shape == (151, )
assert spec.wavelength.shape == (151, )
import sys
import matplotlib.pyplot as plt
from specio import specread
print(__doc__)
# Get the path to the data relatively to this example
DATA_PATH = os.path.dirname(sys.argv[0])
spc_filenames = os.path.join(DATA_PATH, 'data', '*.spc')
print('The SPC files will be search in: {}'.format(spc_filenames))
# Read the data
spectra = specread(spc_filenames)
# Plot the first spectra
plt.figure()
plt.plot(spectra.wavelength,
spectra.amplitudes.T)
# We get the axis information by using the meta data of the first file read.
plt.xlabel(spectra.meta[0]['xlabel'])
plt.ylabel(spectra.meta[0]['ylabel'])
plt.title('Spectra extracted from the SPC files')
# Export all spectrum into csv
spectra.to_csv('spectra.csv')
# We can open the exported file
"""
==============================================
Read FSM Perkin Elmer Spotlight IR binary file
==============================================
This example shows how to read FSM file and plot the results.
"""
from __future__ import print_function
import matplotlib.pyplot as plt
from specio import specread
from specio.datasets import load_fsm_path
# Find the path to the FSM toy data
fsm_filename = load_fsm_path()
print(fsm_filename)
# Read the data
spectra = specread(fsm_filename)
# Plot the first spectra
plt.plot(spectra.wavelength,
spectra.spectrum[0])
plt.show()
This example shows how to read CSV file and plot the results. Note that this
format is the format used when using :func:`specio.core.Spectrum.to_csv`
"""
# Authors: Guillaume Lemaitre <*****@*****.**>
# License: BSD3
from __future__ import print_function
import matplotlib.pyplot as plt
from specio import specread
from specio.datasets import load_csv_path
print(__doc__)
# Find the path to the CSV toy data
csv_filename = load_csv_path()
print(csv_filename)
# Read the data
spectra = specread(csv_filename)
# Plot the first spectra
plt.plot(spectra.wavelength, spectra.amplitudes.T)
plt.xlabel('Amplitude')
plt.ylabel('Wavelength')
plt.show()
This example illustrates how to export a spectrum into a dataframe which can be useful for some later processing. """ # Authors: Guillaume Lemaitre <*****@*****.**> # License: BSD3 import matplotlib.pyplot as plt from specio.datasets import load_csv_path from specio import specread # read the spectrum spectra = specread(load_csv_path()) # convert to a dataframe df_spectra = spectra.to_dataframe() # print the head of dataframe print(df_spectra.head()) # plot the five first spectra df_spectra.head().T.plot() # or on different plots df_spectra.head().T.plot(subplots=True) plt.show()
