Generate Spectroscopic Data

These functions generate hyper-spectral datasets that are mainly used for exploring and testing functionality of hyperSpec.

• generate_hy_spectra() generates several spectra.

• generate_hy_profile() generates depth, concentration, time-series profiles at a single wavelength.

• generate_hy_map() generates hyper-spectral map.

generate_hy_spectra(n_wl = 50, n = 20)

generate_hy_profile(n = 20, wavelength = 550)

generate_hy_map(n_wl = 5, n_xy = 7, k = 5)

Arguments

n_wl	(integer) Number of wavelengths (points per spectrum).
n	(integer) Number of spectra.
wavelength	(numeric) A single numeric value for wavelength.
n_xy	(integer)number of pixels in x and y directions of hyper-spectral map.
k	integer not larger than n_xy. If k = n_xy, there are no empty pixels in the map. Otherwise, some pixels are empty.

Value

A hyperSpec object.

See also

generate_faux_cell()

Author

V. Gegzna

Examples

# Generate spectra
hy_spectra <- generate_hy_spectra()
hy_spectra
#> hyperSpec object
#>    20 spectra
#>    5 data columns
#>    50 data points / spectrum
#> wavelength: lambda, nm [numeric] 400.0000 406.1224 ... 700 
#> data:  (20 rows x 5 columns)
#>    1. gr:  [character] A B ... B 
#>    2. x: l, cm [numeric] 0.25 0.50 ... 5 
#>    3. c:  [numeric] 12.64911 12.31601 ... 1.414214 
#>    4. t:  [numeric] 0.0000000 0.1578947 ... 3 
#>    5. spc: I, a.u. [matrix, array50] 1.638282 1.243157 ... 0.1831655 

plot(hy_spectra)


# Generate profiles
hy_profile <- generate_hy_profile()
hy_profile
#> hyperSpec object
#>    20 spectra
#>    4 data columns
#>    1 data points / spectrum
#> wavelength: lambda, nm [numeric] 550 
#> data:  (20 rows x 4 columns)
#>    1. z: z, mm [numeric] 0.0000000 0.6931472 ... 2.995732 
#>    2. c: Concentration, mol/l [numeric] 0.8414710 0.9092974 ... 0.9129453 
#>    3. t: t, s [numeric] 0.00000 21.05263 ... 400 
#>    4. spc: I, a.u. [matrix, array1] 0.9497657 0.8041098 ... 0.9965564 

plotc(hy_profile, model = spc ~ t)
plotc(hy_profile, model = spc ~ z)
plotc(hy_profile, model = spc ~ c)


# Generate hyper-spectral map
hy_map <- generate_hy_map()
hy_map
#> hyperSpec object
#>    35 spectra
#>    4 data columns
#>    5 data points / spectrum
#> wavelength: k, 1/cm [numeric] 5000 5750 6500 7250 8000 
#> data:  (35 rows x 4 columns)
#>    1. x: x, px [integer] 1 1 ... 7 
#>    2. y: y, px [integer] 1 2 ... 7 
#>    3. gr:  [factor] A B ... B 
#>    4. spc: I, a.u. [matrix, array5] 1 2 ... 1 

plotmap(hy_map)
plotmap(hy_map[, , 8000])