A set of Python utilities for reading JCAMP-DX files.
The following features are supported:
x
values are normalized to wavelength values (in microns)y
values are interpreted (optional)A few example datasets are provided.
You can download and install the latest version of this software from the Python package index (PyPI) as follows:
pip install --upgrade jcamp
The jcamp_reader()
function takes a filename as input, and returns a dictionary containing the data found in the file.
Specifically, the keys contained in the dictionary are:
x
and y
, giving the scaled values of the data points (scaled according to the xfactor
and yfactor
fields in the header, if they exist).The units of x
and y
are whatever are indicated in the header fields xunits
and yunits
, if these exist.
If the input is a compound file, then the returned dictionary will contain a children
field.
This field is an array of dictionaries that each represent a block.
The jcamp_calc_xsec()
function is intended to takes as input the result of the jcamp_reader()
function and to convert the x
data to wavelength in microns, and the y
data to cross-section in units of m^2 for gas concentration of 1ppm at standard atmospheric pressure and temperature, across a path length of 1 meter.
The jcamp_calc_xsec()
function takes as input the data dictionary jcamp_dict
, and manipulates that dictionary directly without having a separate return value.
Changes to the dictionary may including adding the fields:
and modifying the fields:
The optional arguments wavemin
, wavemax
are used if the user wishes to truncate the data to only a desired spectral range.
For example, setting wavemin=8.0
and wavemax=12.0
means that the returned data arrays will only contain data corresponding to those wavlengths.
If the skip_nonquant
optional input argument is used, then any input spectrum that does not have the complete path_length
and partial_pressure
fields in its dictionary will be passed without modification (That is, no conversion to quantitative cross-section will be attempted).
If this option is set to True, then if the code finds missing data, it will attempt to generate a quantitative cross-section by guessing the missing values.
Based upon NIST's infrared database, typical values for guessing here are partial_pressure = 150.0 mmHg
and path length = 0.1 m
.
You can view a notebook demo in the doc folder to see how you can produce a series of plots showing spectra.
The repository comes with four folders containing JCAMP-format files: infrared_spectra/
, mass_spectra/
, raman_spectra/
, and uvvis_spectra
.
These were downloaded from freely-available internet databases, and can be used as example format files.
In order to use jcamp
for online queries rather than static text files, we can use the following procedure with the requests
package:
response = requests.get(something)
content = response.content.splitlines()
content = [line.decode("utf-8") for line in content]
data_dict = jcamp_read(content)
The jcamp_writefile()
function is used to write out a file given an input data dictionary. Note that the dictionary must have two required entries: x
and y
, giving the primary data to write. The remainder of the dictionary is written into the file header.
The core of the jcamp_writefile()
function is the jcamp_write()
function, which converts the input data dictionary to a long string, while the jcamp_writefile()
function simply takes that string an writes it to a file. The reason for separating the two here is that it allows one to use the writing functions independent of files, or of directly exporting JCAMP-DX formats to software tools that take such strings as input.
Your contributions and hints are welcome.
See CONTRIBUTING.md for details.
jcamp
is licensed under the MIT License - see the LICENSE.txt file for details