Calculate spectral values at a different set of wavelengths

Interpolate/re-express spectral irradiance (or other spectral quantity) values at new wavelengths values. This is a low-level function operating on numeric vectors and called by higher level functions in the package, such as mathematical operators for classes for spectral data.

Usage

interpolate_spectrum(
  w.length.in,
  s.irrad,
  w.length.out,
  fill = NA,
  method = "approx",
  ...
)

Arguments

w.length.in

numeric vector of wavelengths (nm).

s.irrad

a numeric vector of spectral values.

w.length.out

numeric vector of wavelengths (nm).

fill

a numeric value to be assigned to out of range wavelengths.

method

character string One of "auto", "approx", "spline", "skip".

...

additional arguments passed to spline().

Value

a numeric vector of interpolated spectral values.

Details

Depending on method natural spline interpolation or linear interpolation are used. With method = spline a call to spline with method = "natural" is used and with method = "approx" a call to approx is used. If method = "auto" or method = NULL when 100 or fewer distinct wavelengths are available as input and/or the maximum wavelength step size in w.length.in is more than three times the minimum wavelength step size in w.length.out "spline" is used and "approx" otherwise. Finally, with method = "skip" the input is returned unchanged.

If w.length.out is a numeric vector and length.out = NULL, it directly gives the target wavelengths for interpolation. If it is NULL, and length.out is an integer value evenly spaced wavelength values covering the same wavelength range as in the input are generated. If w.length.out is a numeric vector and length.out is an integer value, length.out evenly spaced wavelengths covering the wavelength range of w.length.out are generated. Extrapolation is not supported.

With default fill = NA if the output exceeds the wavelength range of the input, extrapolated values are filled with NA values. With fill = NULL wavelengths outside the wavelength range of input data are discarded. A numerical value can be also be provided as fill. While interpolate_spectrum supports interpolation of a single numeric vector, interpolate_wl applies, one at a time, interpolation to all numeric columns found in x.

See also

spline() and approx().

Other low-level functions operating on numeric vectors.: as_energy(), as_quantum_mol(), calc_multipliers(), div_spectra(), energy_irradiance(), energy_ratio(), insert_hinges(), integrate_xy(), irradiance(), l_insert_hinges(), oper_spectra(), photon_irradiance(), photon_ratio(), photons_energy_ratio(), prod_spectra(), s_e_irrad2rgb(), split_energy_irradiance(), split_photon_irradiance(), subt_spectra(), sum_spectra(), trim_tails(), v_insert_hinges(), v_replace_hinges()

Examples

my.w.length <- 300:700
with(sun.data, interpolate_spectrum(w.length, s.e.irrad, my.w.length))
#>   [1] 0.001264554 0.002623718 0.003922583 0.008974134 0.011655666 0.017991275
#>   [7] 0.020761658 0.030591580 0.039978542 0.041639084 0.048712392 0.078527559
#>  [13] 0.080367380 0.094289456 0.105412629 0.112790138 0.102058726 0.148768985
#>  [19] 0.141391876 0.156969197 0.174169122 0.182203132 0.178721531 0.168053318
#>  [25] 0.207550771 0.216805488 0.277441571 0.285109584 0.264857263 0.299874513
#>  [31] 0.329518958 0.289551009 0.300071827 0.295150124 0.293696227 0.312925259
#>  [37] 0.271243302 0.260976992 0.290466940 0.310840376 0.335235319 0.305328678
#>  [43] 0.322195009 0.338005240 0.267587832 0.306027900 0.305130505 0.320791837
#>  [49] 0.305603819 0.298168712 0.345357201 0.341556702 0.323414777 0.330504697
#>  [55] 0.375862487 0.373763892 0.344165845 0.282222836 0.254490689 0.291694468
#>  [61] 0.370706830 0.307170911 0.324516952 0.360841632 0.368125255 0.366179060
#>  [67] 0.449189842 0.429468010 0.398062052 0.416799402 0.439323261 0.409285405
#>  [73] 0.378833546 0.357683807 0.326005743 0.338741381 0.394624218 0.418970286
#>  [79] 0.496971381 0.413149791 0.397674856 0.436211050 0.322994378 0.261431030
#>  [85] 0.300153524 0.391544645 0.354681256 0.374841506 0.365555284 0.396362059
#>  [91] 0.453539598 0.482210468 0.437234060 0.242202287 0.297644222 0.469988640
#>  [97] 0.405450284 0.254182717 0.503564422 0.586119023 0.608104877 0.626174220
#> [103] 0.649738778 0.620728707 0.637048946 0.626378620 0.599643955 0.595122643
#> [109] 0.625620917 0.661542103 0.560550458 0.650713476 0.674249832 0.645636462
#> [115] 0.663252803 0.647460864 0.676181832 0.644650255 0.633474327 0.644604654
#> [121] 0.598841551 0.670126933 0.666837734 0.611819108 0.602692194 0.606191811
#> [127] 0.638887302 0.595463601 0.592769703 0.547992196 0.457037071 0.413689966
#> [133] 0.646453175 0.652784601 0.629833249 0.662687445 0.733660742 0.726669733
#> [139] 0.645321225 0.602850221 0.643647639 0.673426029 0.718858063 0.705562936
#> [145] 0.706734749 0.696689331 0.665201654 0.737180964 0.769608965 0.744430705
#> [151] 0.775153602 0.820463342 0.769963708 0.697267409 0.732363421 0.765381427
#> [157] 0.774125663 0.798493545 0.761838948 0.769424580 0.769551282 0.771127687
#> [163] 0.761229358 0.760866657 0.760967158 0.745359011 0.758114649 0.742989105
#> [169] 0.766531175 0.766383174 0.748045520 0.742406604 0.769335685 0.751494433
#> [175] 0.745485216 0.772463397 0.768368987 0.764061376 0.786977343 0.753697541
#> [181] 0.771487291 0.763996666 0.783275921 0.773039789 0.749263417 0.733195569
#> [187] 0.652902130 0.651165424 0.716398516 0.702688375 0.772811081 0.735604670
#> [193] 0.689661134 0.738208076 0.733300961 0.789987227 0.760024838 0.753378017
#> [199] 0.712262795 0.725017333 0.724098235 0.709001697 0.691629553 0.730127374
#> [205] 0.725668867 0.737184608 0.770173714 0.736361219 0.701330220 0.746655664
#> [211] 0.742732159 0.738493353 0.751087598 0.712607287 0.700402655 0.693310040
#> [217] 0.730273261 0.617665218 0.644963708 0.637494891 0.698323787 0.715079946
#> [223] 0.730263301 0.695705698 0.736290334 0.737608845 0.692562308 0.649207176
#> [229] 0.721373613 0.731504253 0.730562857 0.760329660 0.724632351 0.646047102
#> [235] 0.672727894 0.708475517 0.742924836 0.715776953 0.736209227 0.722175087
#> [241] 0.675629939 0.668424621 0.709732364 0.717384896 0.724795825 0.727246427
#> [247] 0.699304126 0.711901259 0.693656490 0.702085310 0.704655110 0.703140897
#> [253] 0.717886336 0.692071644 0.707215385 0.711759892 0.699776245 0.687500598
#> [259] 0.691690903 0.676546347 0.682997060 0.697282697 0.667644497 0.699158988
#> [265] 0.689760552 0.691030049 0.650160315 0.669408771 0.675091491 0.650802622
#> [271] 0.651739716 0.644368480 0.657513818 0.671338953 0.665265926 0.653900084
#> [277] 0.659179593 0.664428699 0.657354465 0.647434024 0.664121163 0.670127970
#> [283] 0.685373604 0.683998192 0.679381371 0.672798245 0.652057679 0.655352889
#> [289] 0.630464328 0.565875951 0.570424859 0.606160550 0.598629221 0.610659840
#> [295] 0.616150651 0.602827712 0.617006037 0.625627153 0.623827236 0.624741526
#> [301] 0.637276746 0.629583712 0.630589004 0.636032911 0.657813967 0.661432277
#> [307] 0.655703462 0.649912648 0.654486861 0.649440349 0.639000522 0.639132824
#> [313] 0.646843646 0.635169215 0.628622299 0.630445405 0.610374752 0.600743827
#> [319] 0.636397425 0.642854444 0.637355531 0.646409857 0.634972528 0.627126608
#> [325] 0.611598268 0.609424964 0.600836444 0.606918172 0.589678938 0.603312874
#> [331] 0.599971460 0.598354254 0.584174618 0.604107069 0.599413654 0.608921081
#> [337] 0.600507257 0.611388086 0.623351017 0.613681790 0.599770051 0.604088763
#> [343] 0.613891791 0.612283890 0.600603360 0.592575244 0.577735916 0.561086580
#> [349] 0.554740369 0.556987470 0.566359186 0.579913525 0.568615701 0.581916331
#> [355] 0.578714123 0.561770580 0.498295902 0.516005449 0.568161191 0.576024010
#> [361] 0.578000613 0.596081660 0.599538267 0.596802361 0.591356846 0.590886447
#> [367] 0.589367045 0.585655836 0.597708872 0.596728172 0.592550463 0.589076157
#> [373] 0.581766939 0.584407549 0.587988463 0.585766359 0.585039960 0.583209758
#> [379] 0.580927455 0.579854155 0.576914450 0.572616242 0.572064144 0.569409041
#> [385] 0.568592243 0.565028736 0.532775954 0.474612718 0.475584826 0.473902623
#> [391] 0.489913869 0.502197202 0.502920107 0.487091273 0.472551439 0.477816556
#> [397] 0.490539390 0.516479856 0.505073328 0.483381678 0.475801560