Import Data in SpectroChemPy

This tutorial shows how to import data in SpectroChemPy (SCPy) .

First, let’s import spectrochempy as scp in the current namespace, so that all spectrochempy commands will be called as scp.method(<method parameters>) .

[1]:

import spectrochempy as scp

SpectroChemPy's API - v.0.8.2.dev7
©Copyright 2014-2025 - A.Travert & C.Fernandez @ LCS

Generic read command

To read a file containing spectrocopic data or similar, the read method can be used. This method will try to guess the file format based on the file extension.

[2]:

X = scp.read("wodger.spg")

Running on GitHub Actions
MPL Configuration directory: /home/runner/.config/matplotlib
Stylelib directory: /home/runner/.config/matplotlib/stylelib

The above command will extract the data from the file wodger.spg and store it in a NDDataset object named X. To display information about the dataset, simply type X in a cell and run it.

[3]:

[3]:

NDDataset: [float64] a.u. (shape: (y:2, x:5549))[wodger]

Summary

name

:

wodger

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

Omnic title: wodger.spg
Omnic filename: /home/runner/work/spectrochempy/spectrochempy/docs/sources/userguide/importexport/wodger.spg

history

:

2025-04-27 01:45:33+00:00> Imported from spg file
/home/runner/work/spectrochempy/spectrochempy/docs/sources/userguide/importexport/wodger.spg.
2025-04-27 01:45:33+00:00> Sorted by date

Data

title

:

absorbance

values

:

...

[[ 2.005 2.003 ... 1.826 1.831]
[ 1.983 1.984 ... 1.698 1.704]] a.u.

shape

:

(y:2, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

2

title

:

acquisition timestamp (GMT)

coordinates

:

[1.468e+09 1.468e+09] s

labels

:

...

[[ vz0470.spa, Wed Jul 06 21:40:37 2016 (GMT+02:00) 2016-07-06 19:43:13+00:00]
[ vz0468.spa, Wed Jul 06 21:20:38 2016 (GMT+02:00) 2016-07-06 19:23:14+00:00]]

In this case, the data were in an OMNIC file format, and the read method guessed it correctly using the file name extension. The read method can also read other file formats, such as OPUS, JCAMP-DX, CSV, MATLAB, TOPSPIN, etc. or even a directory.

Using a specific reader

Instead of using the generic read method, you can also use a specific reader, such as read_omnic, read_opus, read_csv, read_jcamp, etc. These methods are more specific and will only read the file format they are. For example, read_omnic will only read OMNIC files.

The following table lists the available file readers in SCPy along with the corresponding file formats and extensions they support:

Reader	File Formats	Extensions
read_omnic,read_spa,read_spg,read_srs	Thermo Scientific/Nicolet OMNIC files	.spa, .spg, .srs
read_opus	Bruker OPUS files	.0, .1, .000, …
read_csv	Comma-Separated Values (CSV) files	.csv
read_jcamp, read_dx	JCAMP-DX spectral data files	.dx, .jdx
read_matlab,read_mat	MATLAB files	.mat, .dso
read_topspin	Bruker TopSpin NMR files	fid, ser, 1r, 1i, 2rr…
read_labspec	LABSPEC6 spectral data files	.txt
read_wire,read_wdf	Renishaw Wire files	.wdf
read_scp	SpectroChemPy-specific files	.scp
read_soc,read_ddr,read_hdr,read_sdr	Surface Optics Corporation files	.ddr, .hdr, .sdr
read_galactic	Galactic spectral files	.spc
read_quadera	Pfeiffer Vacuum QUADERA mass spectrometer files	.txt
read	Generic reader (automatically detects format)
read_dir	Reads all supported files in a directory
read_zip	Reads files from a ZIP archive	.zip
read_carroucell	Reads files from a carrousel experiment directory

The read_dir function scans a directory and reads all supported files, returning a list of NDDataset objects.

Other reader functions return either a single NDDataset or multiple NDDataset objects, depending on the file type and content.

Further details on specific cases are provided below. See the section Reading directories.

Using relative or absolute pathnames

In the above examples, the file wodger.spg was read from the current working directory.

If the file is located in another directory, the full path to the file can be provided. For example:

X = scp.read('/users/Brian/s/Life/wodger.spg')

or, for Windows:

X = scp.read(r'C:\users\Brian\s\Life\wodger.spg')

Notes:

The path separator is a backslash \ on Windows, but in many contexts, backslash is also used as an escape character to represent non-printable characters. To avoid problems, either it has to be escaped itself, a double backslash \\, or one can also use raw string literals to represent Windows paths. These are string literals that have an r prepended to them. In raw string literals, the \\ represents a literal backslash: r'C:\users\Brian'.
In python, the slash / is used as the path separator in all systems (Windows, Linux, OSX, …). So it can be used in all cases. For exemple:
```
X = scp.read('C:/users/Brian/s/Life/wodger.spg')
```
The use of relative pathnames is a good practice. SpectroChemPy readers use relative paths. If the given path is not absolute, then SpectroChemPy will search relative to the current directory or to a directory specified using the directorykeywords.

For example:
```
X = scp.read('wodger.spg', directory='C:/users/Brian/s/Life')
X = scp.read('Life/wodger.spg', directory='C:\\users\\Brian\\s')
```
The os or pathlib modules can be used to work with pathnames. See the section Good practice:Use of os or pathlib packages.
The preferences.datadir variable can be used to set a default directory where to look for data. See the section Another default search directory: datadir.

Good practices

Use relative paths

As path are system dependent, it is a good practice to use relative pathnames in scripts and notebooks.

If, for instance, Brian has a project organised in a folder (s ) with a directory dedicated to input data (Life ) and a notebook for preprocessing (welease.ipynb ) as illustrate below:

C:\users
|    +-- Brian
|    |    +-- s
|    |    |   +-- Life
|    |    |   |   +-- wodger.spg
|    |    |   +-- welease.ipynb

Then running this project in John’s Linux computer (e.g. in /home/john/s_copy ) will certainly result in execution errors if absolute paths are used in the notebook:

OSError: Can't find this filename C:\users\Brian\s\life\wodger.spg

Fortunately, SpectroChemPy readers use relative paths. If the given path is not absolute, then SpectroChemPy will search in the current directory. Hence, the opening of the spg file from scripts in welease.ipynb can be made by the command:

X = scp.read('Life/wodger.spg')

or:

X = scp.read('wodger.spg', directory='Life')

Use os or pathlib packages

In python, working with pathnames is classically done with dedicated modules such as os or pathlib python modules. With os we mention the following methods that can be particularly useful:

import os
os.getcwd()              # returns the absolute path of the current working directory
                         # preferences.datadir
os.path.expanduser("~")  # returns the home directory of the user
os.path.join('path1','path2','path3', ...)
                         # intelligently concatenates path components
                         # using the system separator (`/` or `\\` )

Using Pathlib is even simpler:

from pathlib import Path
Path.cwd()               # returns the absolute path of the current working directory
Path.home()              # returns the home directory of the user
Path('path1') / 'path2' / 'path3' / '...'   # intelligently concatenates path
components

The interested readers will find more details on the use of these modules here:

os
pathlib

Another default search directory: datadir

Spectrochempy also comes with the definition of a second default directory path where to look at the data: the datadir directory. It is defined in the variable preferences.datadir which is imported at the same time as spectrochempy. By default, datadir points in the ‘$HOME/.spectrochempy/tesdata’ directory.:

[4]:

DATADIR = scp.preferences.datadir
DATADIR

[4]:

PosixPath('/home/runner/.spectrochempy/testdata')

DATADIR is already a pathlib object and so can be used easily

[5]:

scp.read_omnic(DATADIR / "wodger.spg")

[5]:

NDDataset: [float64] a.u. (shape: (y:2, x:5549))[wodger]

Summary

name

:

wodger

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

Omnic title: wodger.spg
Omnic filename: /home/runner/.spectrochempy/testdata/wodger.spg

history

:

2025-04-27 01:45:33+00:00> Imported from spg file /home/runner/.spectrochempy/testdata/wodger.spg.
2025-04-27 01:45:33+00:00> Sorted by date

Data

title

:

absorbance

values

:

...

[[ 2.005 2.003 ... 1.826 1.831]
[ 1.983 1.984 ... 1.698 1.704]] a.u.

shape

:

(y:2, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

2

title

:

acquisition timestamp (GMT)

coordinates

:

[1.468e+09 1.468e+09] s

labels

:

...

[[ vz0470.spa, Wed Jul 06 21:40:37 2016 (GMT+02:00) 2016-07-06 19:43:13+00:00]
[ vz0468.spa, Wed Jul 06 21:20:38 2016 (GMT+02:00) 2016-07-06 19:23:14+00:00]]

It can be set to another pathname permanently (i.e., even after computer restart) by a new assignment:

scp.preferences.datadir = 'C:/users/Brian/s/Life'

This will change the default value in the SCPy preference file located in the hidden folder .spectrochempy/ at the root of the user home directory.

Finally, by default, the import functions used in Spectrochempy will search the data files using this order of precedence:

try absolute path
try in current working directory
try in datadir
if none of these works: generate an OSError (file or directory not found)

Reading directories

The read_dir function is designed to read an entire directory, create NDDatasets for each file, and finally merge all compatible datasets. Let’s see an example:

Here is a list of the files presents in DATADIR/irdata/subdir/

[6]:

folder = DATADIR / "irdata" / "subdir"
[str(item.relative_to(DATADIR)) for item in folder.glob("*.*")]

[6]:

['irdata/subdir/7_CZ0-100_Pd_102.SPA',
 'irdata/subdir/TGAIR-unreadable.srs',
 'irdata/subdir/7_CZ0-100_Pd_101.SPA',
 'irdata/subdir/7_CZ0-100_Pd_104.SPA',
 'irdata/subdir/7_CZ0-100_Pd_103.SPA']

Now read all files in the DATADIR/irdata/subdir/ directory (i.e.,, four .spa files and one .srs file). Any file in unknown format will be ignored silently:

[7]:

scp.read_dir(folder)

[7]:

List (len=2, type=NDDataset)

0: NDDataset: [float64] a.u. (shape: (y:335, x:1868))[dd_6.6_19039_538]

Summary

name

:

dd_6.6_19039_538

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

Concatenation of 1 datasets:
( dd_6.6_19039_538 )

history

:

2025-04-27 01:45:33+00:00> Created by concatenate
2025-04-27 01:45:33+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[-0.007524 -0.0003661 ... 8.291e-05 9.239e-05]
[-0.009306 -0.002252 ... 0.0001051 0.000107]
...
[ 0.02474 0.02814 ... 0.002962 0.002967]
[ 0.02663 0.02899 ... 0.002907 0.002916]] a.u.

shape

:

(y:335, x:1868)

Dimension `x`

size

:

1868

title

:

wavenumbers

coordinates

:

[ 4000 3998 ... 401.1 399.2] cm⁻¹

Dimension `y`

size

:

335

title

:

Time

coordinates

:

[ 0.26 0.52 ... 86.76 87.02] min

labels

:

...

[ Verknüpftes Spektrum bei 0,260 Min.
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±ºð¹¯ºqHºIKº Verknüpftes Spektrum bei 0,519 Min.
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Verknüpftes Spektrum bei 86,756 Min.
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Verknüpftes Spektrum bei 87,016 Min.
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0+@
+1Ú<9}í< B <µ*<;µÖ;ÓÆ" <½²ò;ç<àP<ãâ;4Å;vüö;ÑMà;·S;M;HÃà;¾cö;M¶ü;C;Ö[#;3Ó;*Ûæ;6;ýH;R±Ã;ÍN;í;j7;oÚ;ú;]

1: NDDataset: [float64] a.u. (shape: (y:4, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

Concatenation of 1 datasets:
( 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:33+00:00> Created by concatenate
2025-04-27 01:45:33+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.544 1.543 ... 2.1 2.091]
[ 1.552 1.553 ... 2.161 2.109]
[ 1.461 1.46 ... 2.087 2.088]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:4, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

4

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09 1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-30 07:10:57+00:00 2018-11-30 07:22:52+00:00 2018-11-30 07:34:49+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_101.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_102.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_103.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

The above command have read all files in the DATADIR/irdata/subdir/ directory and merged them into two groups of compatible NDDatasets:

a first NDDataset object (id: 0, shape [335,1868]) comes from the single .srs file.
a second NDDataset object (id: 1, shape [335,1868]) comes from the merging of four .spa files.

Merging compatible NDDataset is the default behavior of read_dir (or equivalently read). If you want to read the files separately, you can use the merge=False keyword:

[8]:

scp.read_dir(folder, merge=False)

[8]:

List (len=5, type=NDDataset)

0: NDDataset: [float64] a.u. (shape: (y:1, x:5549))[7_CZ0-100 Pd_101]

Summary

name

:

7_CZ0-100 Pd_101

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

# Omnic name: 7_CZ0-100 Pd_101
# Filename: 7_CZ0-100_Pd_101.SPA

history

:

2025-04-27 01:45:33+00:00> Imported from spa file(s)
2025-04-27 01:45:33+00:00> Data processing history from Omnic :
------------------------------------
Acquisition échantillon

<br/> Background acquis le Ven Nov 30 08:03:45 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:12:56 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:24:51 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:36:47 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

As expected the result is a list of 5 NDDataset objects, one for each file in the directory.

Additional options for reading directories

The read_dir/read function has additional options to control the behavior of the reading process:

recursive: if True, the function will scan the directory recursively and read all supported files in all subdirectories.
pattern: a string or a list of strings that can be used to filter the files to be read. Only files whose name matches the pattern will be read.

Let’s see an example with the recursive option:

First we list files in all directories under DATADIR/irdata/subdir/:

[9]:

[str(item.relative_to(DATADIR)) for item in folder.glob("**/*.*")]

[9]:

['irdata/subdir/7_CZ0-100_Pd_102.SPA',
 'irdata/subdir/TGAIR-unreadable.srs',
 'irdata/subdir/7_CZ0-100_Pd_101.SPA',
 'irdata/subdir/7_CZ0-100_Pd_104.SPA',
 'irdata/subdir/7_CZ0-100_Pd_103.SPA',
 'irdata/subdir/1-20/7_CZ0-100_Pd_3.SPA',
 'irdata/subdir/1-20/7_CZ0-100_Pd_5.SPA',
 'irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA',
 'irdata/subdir/20-50/7_CZ0-100_Pd_21.SPA']

the ìrdata/subdir/directory contains two subdirectory1-20and20-50with two additional.spa` files.

Now we read all files (a total of 9) in the DATADIR/irdata/subdir/ directory and its subdirectories:

[10]:

scp.read_dir(folder, recursive=True, merge=False)

[10]:

List (len=9, type=NDDataset)

0: NDDataset: [float64] a.u. (shape: (y:1, x:5549))[7_CZ0-100 Pd_3]

Summary

name

:

7_CZ0-100 Pd_3

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:33+00:00

description

:

# Omnic name: 7_CZ0-100 Pd_3
# Filename: 7_CZ0-100_Pd_3.SPA

history

:

2025-04-27 01:45:33+00:00> Imported from spa file(s)
2025-04-27 01:45:33+00:00> Data processing history from Omnic :
------------------------------------
Acquisition échantillon

<br/> Background acquis le Jeu Nov 29 17:13:06 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Jeu Nov 29 17:25:03 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Jeu Nov 29 17:36:59 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Jeu Nov 29 20:48:01 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:03:45 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:12:56 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:24:51 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

<br/> Background acquis le Ven Nov 30 08:36:47 2018 (GMT+01:00) <br/> Format Final : Absorbance <br/> Résolution: 4,000 de 649,9207 à 5999,7134 <br/> Roue de validation: 0 <br/> Roue porte écran atténuation: Vide <br/> Numéro Série du banc:ALK1100494</div></div></div></details></div>

and we allow merging them:

[11]:

scp.read_dir(folder, recursive=True)

[11]:

List (len=2, type=NDDataset)

0: NDDataset: [float64] a.u. (shape: (y:335, x:1868))[dd_6.6_19039_538]

Summary

name

:

dd_6.6_19039_538

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 1 datasets:
( dd_6.6_19039_538 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[-0.007524 -0.0003661 ... 8.291e-05 9.239e-05]
[-0.009306 -0.002252 ... 0.0001051 0.000107]
...
[ 0.02474 0.02814 ... 0.002962 0.002967]
[ 0.02663 0.02899 ... 0.002907 0.002916]] a.u.

shape

:

(y:335, x:1868)

Dimension `x`

size

:

1868

title

:

wavenumbers

coordinates

:

[ 4000 3998 ... 401.1 399.2] cm⁻¹

Dimension `y`

size

:

335

title

:

Time

coordinates

:

[ 0.26 0.52 ... 86.76 87.02] min

labels

:

...

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îÂ@
y¼»¾¯^¹¸:¸4êº=x»ØÃ1»¼-øºÿÉºÓÅº[L»×

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ºó(
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Verknüpftes Spektrum bei 86,756 Min.
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ã!@
¡Ê r <«><
é;òÙ;\
<â½Ä;²;ÿÐæ;¤ññ;°Í¹;¡´;ÛYÎ;?å;Þ¦ò;²ø§;hAe;°TÉ;ó÷Ì;dK;úºY;ÛýÀ;j8;ïkª;#G;¸Û;Öþ;
Verknüpftes Spektrum bei 87,016 Min.
Ë
ÁØsúË
t/ä
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0+@
+1Ú<9}í< B <µ*<;µÖ;ÓÆ" <½²ò;ç<àP<ãâ;4Å;vüö;ÑMà;·S;M;HÃà;¾cö;M¶ü;C;Ö[#;3Ó;*Ûæ;6;ýH;R±Ã;ÍN;í;j7;oÚ;ú;]

1: NDDataset: [float64] a.u. (shape: (y:8, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 1 datasets:
( 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.311 1.307]
[ 1.245 1.245 ... 1.302 1.299]
...
[ 1.461 1.46 ... 2.087 2.088]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:8, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

8

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09 ... 1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:23:05+00:00 2018-11-29 16:35:00+00:00 ... 2018-11-30 07:34:49+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_3.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA ...
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_103.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

As the 8 .spa files are compatible, they are merged into a single NDDataset object. The .srs file is read separately.

Specific reader can equivalently read folder recursively:

[12]:

scp.read_omnic(folder, recursive=True)

[12]:

List (len=2, type=NDDataset)

0: NDDataset: [float64] a.u. (shape: (y:335, x:1868))[dd_6.6_19039_538]

Summary

name

:

dd_6.6_19039_538

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 1 datasets:
( dd_6.6_19039_538 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[-0.007524 -0.0003661 ... 8.291e-05 9.239e-05]
[-0.009306 -0.002252 ... 0.0001051 0.000107]
...
[ 0.02474 0.02814 ... 0.002962 0.002967]
[ 0.02663 0.02899 ... 0.002907 0.002916]] a.u.

shape

:

(y:335, x:1868)

Dimension `x`

size

:

1868

title

:

wavenumbers

coordinates

:

[ 4000 3998 ... 401.1 399.2] cm⁻¹

Dimension `y`

size

:

335

title

:

Time

coordinates

:

[ 0.26 0.52 ... 86.76 87.02] min

labels

:

...

[ Verknüpftes Spektrum bei 0,260 Min.
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ÁØsúË
t/ä
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±½@
ö»Îö¿¹·j»D»t4»*
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»[ýéºùH|»
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º¹¶:»ñ&Rº*
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ºB'ÆºP|_º)ïQ9OÌºÜìº-ºÁrï¹ç
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t/ä
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îÂ@
y¼»¾¯^¹¸:¸4êº=x»ØÃ1»¼-øºÿÉºÓÅº[L»×

»£Êp»Õ@»¤(»ëð¢¹±w 95ºÍ9ÔºÓà³ºOuºÔ
Ü¹ºm¼BºâÞå7ÛÍ9Mº,ºJq:ò49 jZºLÛº¬ëºÃi¹;ý:ì) º)vÂº¡ê¹xÕ½·?³º©ëÁºÀ
ºó(
¹ ...
Verknüpftes Spektrum bei 86,756 Min.
Ë
ÁØsúË
t/ä
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ã!@
¡Ê r <«><
é;òÙ;\
<â½Ä;²;ÿÐæ;¤ññ;°Í¹;¡´;ÛYÎ;?å;Þ¦ò;²ø§;hAe;°TÉ;ó÷Ì;dK;úºY;ÛýÀ;j8;ïkª;#G;¸Û;Öþ;
Verknüpftes Spektrum bei 87,016 Min.
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ÁØsúË
t/ä
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0+@
+1Ú<9}í< B <µ*<;µÖ;ÓÆ" <½²ò;ç<àP<ãâ;4Å;vüö;ÑMà;·S;M;HÃà;¾cö;M¶ü;C;Ö[#;3Ó;*Ûæ;6;ýH;R±Ã;ÍN;í;j7;oÚ;ú;]

1: NDDataset: [float64] a.u. (shape: (y:8, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 1 datasets:
( 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.311 1.307]
[ 1.245 1.245 ... 1.302 1.299]
...
[ 1.461 1.46 ... 2.087 2.088]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:8, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

8

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09 ... 1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:23:05+00:00 2018-11-29 16:35:00+00:00 ... 2018-11-30 07:34:49+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_3.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA ...
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_103.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

Let’s see an example with the pattern option:

We read all files in the DATADIR/irdata/subdir/ directory and its subdirectories, but only those with the .spa extension and whose name contains the string 4:

[13]:

scp.read_dir(folder, recursive=True, pattern="*4*")

[13]:

NDDataset: [float64] a.u. (shape: (y:2, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 2 datasets:
( 7_CZ0-100 Pd_4, 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.302 1.299]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:2, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

2

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:35:00+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

The above pattern “*4*” match only two files which are then merged and returned as a single NDDataset object.

This pattern option is obviously interesting to select only a type of extension:

[14]:

scp.read_dir(folder, recursive=True, pattern="*.spa")

[14]:

NDDataset: [float64] a.u. (shape: (y:8, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 8 datasets:
( 7_CZ0-100 Pd_3, 7_CZ0-100 Pd_4, 7_CZ0-100 Pd_5, 7_CZ0-100 Pd_21, 7_CZ0-100 Pd_101, 7_CZ0-100 Pd_102, 7_CZ0-100 Pd_103, 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.311 1.307]
[ 1.245 1.245 ... 1.302 1.299]
...
[ 1.461 1.46 ... 2.087 2.088]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:8, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

8

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09 ... 1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:23:05+00:00 2018-11-29 16:35:00+00:00 ... 2018-11-30 07:34:49+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_3.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA ...
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_103.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

[15]:

scp.read(folder, recursive=True, pattern="*.spa")  # equivalent

[15]:

NDDataset: [float64] a.u. (shape: (y:8, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 8 datasets:
( 7_CZ0-100 Pd_3, 7_CZ0-100 Pd_4, 7_CZ0-100 Pd_5, 7_CZ0-100 Pd_21, 7_CZ0-100 Pd_101, 7_CZ0-100 Pd_102, 7_CZ0-100 Pd_103, 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.311 1.307]
[ 1.245 1.245 ... 1.302 1.299]
...
[ 1.461 1.46 ... 2.087 2.088]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:8, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

8

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09 ... 1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:23:05+00:00 2018-11-29 16:35:00+00:00 ... 2018-11-30 07:34:49+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_3.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA ...
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_103.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

[16]:

scp.read_omnic(folder, recursive=True, pattern="*4.spa")  # equivalent

[16]:

NDDataset: [float64] a.u. (shape: (y:2, x:5549))[7_CZ0-100 Pd_104]

Summary

name

:

7_CZ0-100 Pd_104

author

:

runner@fv-az2211-104

created

:

2025-04-27 01:45:34+00:00

description

:

Concatenation of 2 datasets:
( 7_CZ0-100 Pd_4, 7_CZ0-100 Pd_104 )

history

:

2025-04-27 01:45:34+00:00> Created by concatenate
2025-04-27 01:45:34+00:00> Merged from several files

Data

title

:

absorbance

values

:

...

[[ 1.245 1.245 ... 1.302 1.299]
[ 1.448 1.447 ... 2.071 2.065]] a.u.

shape

:

(y:2, x:5549)

Dimension `x`

size

:

5549

title

:

wavenumbers

coordinates

:

[ 6000 5999 ... 650.9 649.9] cm⁻¹

Dimension `y`

size

:

2

title

:

acquisition timestamp (GMT)

coordinates

:

[1.544e+09 1.544e+09] s

labels

:

...

[[ 2018-11-29 16:35:00+00:00 2018-11-30 07:46:44+00:00]
[ /home/runner/.spectrochempy/testdata/irdata/subdir/1-20/7_CZ0-100_Pd_4.SPA
/home/runner/.spectrochempy/testdata/irdata/subdir/7_CZ0-100_Pd_104.SPA]]

This way the “.srs” file is ignored.

Reading files from a ZIP archive

The read_zip function is designed to read files from a ZIP archive. It can be used to read a single file or all files in the archive. As usual, by default all files are merged. The merge keyword can be used to read the files separately.

[17]:

scp.read(
    "https://eigenvector.com/wp-content/uploads/2019/06/corn.mat_.zip", merge=False
)

 The mat file contains an array of strings named 'information' which will not be converted to NDDataset

[17]:

List (len=7, type=NDDataset)

0: NDDataset: [float64] unitless (shape: (y:3, x:700))[m5nbs]

Summary

name

:

m5nbs

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> M5nbs.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ 0.134 0.132 ... 0.09665 0.09771]
[ 0.1374 0.1354 ... 0.09898 0.09999]
[ 0.1437 0.1416 ... 0.1037 0.1048]]

shape

:

(y:3, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

3

title

:

index

coordinates

:

[ 0 1 2]

1: NDDataset: [float64] unitless (shape: (y:4, x:700))[mp5nbs]

Summary

name

:

mp5nbs

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> Mp5nbs.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ 0.06679 0.0645 ... 0.03636 0.03724]
[ 0.06031 0.05819 ... 0.02807 0.02892]
[ 0.06189 0.05965 ... 0.03215 0.03299]
[ 0.06115 0.05901 ... 0.03013 0.03099]]

shape

:

(y:4, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

4

title

:

index

coordinates

:

[ 0 1 2 3]

2: NDDataset: [float64] unitless (shape: (y:4, x:700))[mp6nbs]

Summary

name

:

mp6nbs

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> Mp6nbs.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ 0.05404 0.0524 ... 0.02147 0.02236]
[ 0.05388 0.05223 ... 0.02187 0.02277]
[ 0.05238 0.05069 ... 0.02207 0.02295]
[ 0.05311 0.05144 ... 0.02195 0.02284]]

shape

:

(y:4, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

4

title

:

index

coordinates

:

[ 0 1 2 3]

3: NDDataset: [float64] unitless (shape: (y:80, x:4))[propvals]

Summary

name

:

propvals

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> Propvals.label{2,1}=proplbls; %class char 4x8
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ 10.45 3.687 8.746 64.84]
[ 10.41 3.72 8.658 64.85]
...
[ 10.59 3.176 8.132 65.21]
[ 10.98 3.328 8.428 64.85]]

shape

:

(y:80, x:4)

Dimension `x`

size

:

4

title

:

labels

:

[ Moisture Oil Protein Starch ]

Dimension `y`

size

:

80

title

:

index

coordinates

:

[ 0 1 ... 78 79]

4: NDDataset: [float64] unitless (shape: (y:80, x:700))[m5spec]

Summary

name

:

m5spec

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> M5spec.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ 0.04449 0.04438 ... 0.7309 0.7306]
[ 0.0465 0.04635 ... 0.7275 0.727]
...
[ 0.05944 0.05932 ... 0.7362 0.7357]
[ 0.05009 0.04993 ... 0.7289 0.7282]]

shape

:

(y:80, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

80

title

:

index

coordinates

:

[ 0 1 ... 78 79]

5: NDDataset: [float64] unitless (shape: (y:80, x:700))[mp5spec]

Summary

name

:

mp5spec

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> Mp5spec.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[-0.01244 -0.01251 ... 0.6849 0.6844]
[-0.01419 -0.01425 ... 0.6924 0.6919]
...
[0.005116 0.00504 ... 0.6979 0.6976]
[-0.003701 -0.003818 ... 0.7128 0.7121]]

shape

:

(y:80, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

80

title

:

index

coordinates

:

[ 0 1 ... 78 79]

6: NDDataset: [float64] unitless (shape: (y:80, x:700))[mp6spec]

Summary

name

:

mp6spec

author

:

*unknown*

created

:

2025-04-27 01:45:35+00:00

history

:

2025-04-27 01:45:35+00:00> Mp6spec.axisscale{2,1}=freqs; %class double 1x700
2025-04-27 01:45:35+00:00> Imported by spectrochempy.

Data

title

:

values

:

...

[[ -0.0227 -0.0228 ... 0.6747 0.6741]
[-0.02192 -0.02206 ... 0.6826 0.6822]
...
[-0.006796 -0.006888 ... 0.6899 0.6891]
[-0.01526 -0.01538 ... 0.7028 0.7021]]

shape

:

(y:80, x:700)

Dimension `x`

size

:

700

title

:

coordinates

:

[ 1100 1102 ... 2496 2498]

Dimension `y`

size

:

80

title

:

index

coordinates

:

[ 0 1 ... 78 79]