def spectra_to_melanopic_irradiance(spectra, binwidth):
# get melanopsin sensitivity
sss = get_CIES026(asdf=True, binwidt=binwidth)
mel = sss['Mel']
# aggregate to melanopic irradiance
mi = spectra.groupby(
by=['led', 'intensity'])['flux'].agg(lambda x: x.dot(mel.values.T))
return mi
def create_alphaopic_irradiances_table(self):
'''Using the CIE026 spectral sensetivities, calculate alphaopic
irradiances (S, M, L, Rhod and Melanopic) for every spectrum in
`self.lkp`.
Returns
-------
pd.DataFrame
Alphaopic irradiances.
'''
sss = get_CIES026(asdf=True, binwidth=self.binwidth)
sss = sss.fillna(0)
return self.lkp.dot(sss)
red_led = 9
target_lux = 800
# find the required intensity setting of the blue led for 800 lux
blue_intensity = (
cc.lux.loc[blue_led].sub(target_lux).abs().idxmin().values[0])
# find the intensity setting of the red led for 800 lux
red_intensity = cc.match(match_led=blue_led,
match_led_intensity=blue_intensity,
target_led=red_led,
match_type='irrad')[1]
# plot stims
fig, ax = plt.subplots()
sss = get_CIES026(asdf=True, binwidth=1)
ax.plot(cc.lkp.loc[(blue_led, blue_intensity)], c='blue')
ax.plot(cc.lkp.loc[(red_led, red_intensity)], c='red')
ax2 = ax.twinx()
ax2.plot(sss['Mel'], ls='dashed', c='steelblue')
ax2.set_ylabel('Melanopsin spectral sensitivity', c='steelblue')
ax.set_xlabel('Wavelength (nm)')
ax.set_ylabel('W/m2/nm')
fig.savefig('./pipr_stims.png')
# make video files
blue_spec, red_spec = [0] * 10, [0] * 10
blue_spec[blue_led] = blue_intensity
red_spec[red_led] = red_intensity
# In[4]:
import sys
sys.path.insert(0, '../../../PyPlr')
import numpy as np
import pandas as pd
from pyplr.CIE import get_CIES026
# # Spectral sensitivities
# In[5]:
_, sss = get_CIES026(asdf=True)
#sss = sss[::5] # downsample to 5nm bins
sss.plot()
# # Spectral mesurements (STLAB)
# In[18]:
stlspec = pd.read_csv(
'/Users/jtm/OneDrive - Nexus365/spectrometer_data/stlab_led_intensity_spectra_08-17-20-14-31.csv'
)
stlspec
# In[19]:
stlinfo = pd.read_csv(