Blood
4 datasets, together covering 0.4–14.99 µm. Default: Rowe et al. 2017: n,k 2–15 µm.
Compare datasets
Tick datasets in the list to add them to the plot (up to 12).
Datasets
Whole blood
Blood components
Use it in Lightsmith
Load this data in Python, simulate in one more line
pip install lightsmith
import lightsmith as ls
# Blood: Rowe et al. 2017: n,k 2–15 µm
blood = ls.fetch_refractiveindex("other", "blood", "Rowe", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(blood.range_nm) # (2000.6, 14987.2) nm
eps = blood.eps([5480]) # complex permittivity
Downloads the original record once (pinned to the imported snapshot) and caches it.
import json, urllib.request
import lightsmith as ls
url = "https://materials.lightsmith.dev/v1/datasets/ds_d3e63730ebdb/lightsmith"
blood = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(blood.source) # citation and provenance travel with the data
Any dataset here, as the library's Tabulated material (blood/rowe-2017).
# ... load blood as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=blood)],
medium_index=1.0,
wavelengths=ls.WavelengthRange(start_nm=2001, stop_nm=14990, num=81),
)
res = ls.solve(sim) # exact Mie for a sphere
print(res.q_ext) # extinction efficiency at each wavelength
Same spec runs with DDA, FDTD, BEM or T-matrix: ls.compare(sim, ["mie", "dda"]).
Lightsmith is open source (MIT): Mie, T-matrix, BEM, DDA, FDTD, RCWA, TMM, mode solvers and inverse design behind one spec, on CPU or GPU. GitHub.
About Blood
Other names: Blood (Human body)
API: /v1/materials/mat_4068c6a8a357 · slug blood