colorSpec objects from files. In case of ERROR, they return NULL.
There are 5 different file formats supported; see Details.readSpectra( pathvec, ... )
readSpectraXYY( path )
readSpectraSpreadsheet( path )
readSpectrumScope( path )readSpectraCGATS( path )
readSpectraControl( path )XYY, Spreadsheet, Scope,
CGATS, or Control. See Details.
If the function cannot recognize the format, it returns NULL.readSpectra returns a single colorSpec object or NULL in case of ERROR.
If there are multiple files in pathvec and they cannot be combined using bind because
their wavelengths are different, it is an ERROR.
To avoid this ERROR, the wavelength argument can be used for resampling to a common wavelength.
If there are multiple files, the organization of the returned object is
"df.row" and the first column is the path from which the spectrum was read.
The functions readSpectraXYY, readSpectraSpreadsheet,
and readSpectraScope, return a single colorSpec object,
or NULL in case of ERROR.
The functions readSpectraCGATS and readSpectraControl are more complicated.
These 2 file formats can contain multiple spectra with different wavelength vectors
so both functions return a list of colorSpec objects.
When readSpectra is called with a wavelength argument,
these multiple spectra are resampled using resample and combined using bind
into a single colorSpec object, which makes it much more convenient to read such files.XYY
There is a column header line matching ^(wave|wl) (not case sensitive) followed by the the names of the spectra.
All lines above this one are taken to be metadata.
The separarator on this header line can be space, tab, or comma;
the line is examined and the separator found there is used in the lines with data below.
The organization of the returned object is 'df.col'.
This is probably the most common file format; see the sample file ciexyz31_1.csv.
Spreadsheet
There is a line matching "^(ID|SAMPLE|Time)". This line and lines below must be tab-separated. Fields matching '^[A-Z]+([0-9.]+)nm$' are taken to be spectral data and other fields are taken to be extradata. All lines above this one are taken to be metadata.
The organization of the returned object is 'df.row'.
This is a good format for automated acquisition, using a spectrometer, of many spectra.
See the sample file N130501.txt from Wolf Faust.
Scope
This is a file format used by Ocean Optics spectrometer software.
There is a line
>>>>>Begin Processed Spectral Data<<<<< followed by wavelength and power
separated by a tab. There is only 1 spectrum per file.
The organization of the returned object is 'vector'.
See the sample file pos1-20x.scope.
CGATS
This is a complex format that is best understood by looking at some samples,
such as extdata/filters/Rosco.txt;
see also CGATS.17.
The fields with spectral data match the pattern "^(nm|SPEC_|SPECTRAL_)[0-9.]+"
and other fields are considered extradata.
The organization of the returned object is 'df.row'.
Control
This is a personal format used for digitizing images of plots from manufacturer
datasheets and academic papers. It is structured like a .INI file.
There is a [Control]
section establishing a simple linear map from pixels to the wavelength and spectrum quantities.
Only 3 points are really necessary.
It is OK for there to be a little rotation of the plot axes relative to the image.
This is followed by a section for each spectrum, in XY pixel units only.
Conversion to wavelength and spectral quantities happens on-the-fly.
Extrapolation can be a problem, especially when the value is near 0.
To force constant extrapolation, repeat the control point (knot) at the endpoint.
See the sample file Lumencor-SpectraX.txt.
The organization of the returned objects is 'vector'.wavelength,
quantity,
metadata,
resample,
bind# read file with header declaring the quantity to be photons->neural
bird = readSpectra( system.file( "extdata/eyes/BirdEyes.txt", package='colorSpec' ) )
quantity(bird) # [1] "photons->neural"Run the code above in your browser using DataLab