def normalize(self, norm_type=None, norm_f=1, cieobs=_CIEOBS):
"""
Normalize spectral power distributions in SPD instance.
Args:
:norm_type:
| None, optional
| - 'lambda': make lambda in norm_f equal to 1
| - 'area': area-normalization times norm_f
| - 'max': max-normalization times norm_f
| - 'ru': to :norm_f: radiometric units
| - 'pu': to :norm_f: photometric units
| - 'pusa': to :norm_f: photometric units (with Km corrected
| to standard air, cfr. CIE TN003-2015)
| - 'qu': to :norm_f: quantal energy units
:norm_f:
| 1, optional
| Determines size of normalization for 'max' and 'area'
or which wavelength is normalized to 1 for 'lambda' option.
:cieobs:
| _CIEOBS or str, optional
| Type of cmf set to use for normalization using photometric
units (norm_type == 'pu')
"""
self.value = spd_normalize(self.get_(),
norm_type=norm_type,
norm_f=norm_f,
cieobs=cieobs)[1:]
return self
def test_spd_normalize(self, getvars):
# check spd_normalize:
S, spds, rfls, xyz, xyzw = getvars
rfls_np_cp = rfls.copy()
rfls_norm = lx.spd_normalize(rfls)
rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='area', norm_f=2)
rfls_norm = lx.spd_normalize(rfls_np_cp,
norm_type='lambda',
norm_f=560)
rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='max', norm_f=1)
rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='pu', norm_f=1)
rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='ru', norm_f=1)
rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='qu', norm_f=1)
def spd_to_aopicE(sid, Ee = None, E = None, Q = None, cieobs = _CIEOBS, sid_units = 'W/m2', out = 'Eeas,Eas'):
"""
Calculate alpha-opic irradiance (Ee,α) and equivalent luminance (Eα) values
for the l-cone, m-cone, s-cone, rod and iprgc (α) photoreceptor cells
following CIE technical note TN 003:2015.
Args:
:sid:
| numpy.ndarray with retinal spectral irradiance in :sid_units:
| (if 'uW/cm2', sid will be converted to SI units 'W/m2')
:Ee:
| None, optional
| If not None: normalize :sid: to an irradiance of :Ee:
:E:
| None, optional
| If not None: normalize :sid: to an illuminance of :E:
| Note that E is calculate using a Km factor corrected to standard air.
:Q:
| None, optional
| If not None: nNormalize :sid: to a quantal energy of :Q:
:cieobs:
| _CIEOBS or str, optional
| Type of cmf set to use for photometric units.
:sid_units:
| 'W/m2', optional
| Other option 'uW/m2', input units of :sid:
:out:
| 'Eeas, Eas' or str, optional
| Determines values to return.
Returns:
:returns:
| (Eeas, Eas) with Eeas and Eas resp. numpy.ndarrays with the
α-opic irradiance and equivalent illuminance values
of all spectra in :sid: in SI-units.
| (other choice can be set using :out:)
"""
outlist = out.split(',')
# Convert to Watt/m²:
if sid_units == 'uW/cm2':
sid[1:] = sid[1:]/100
elif sid_units == 'W/m2':
pass
else:
raise Exception("spd_to_aopicE(): {} unsupported units for SID.".format(sid_units))
# Normalize sid to Ee:
if Ee is not None:
sid = spd_normalize(sid, norm_type = 'ru', norm_f = Ee)
elif E is not None:
sid = spd_normalize(sid, norm_type = 'pusa', norm_f = E)
elif Q is not None:
sid = spd_normalize(sid, norm_type = 'qu', norm_f = Q)
# Get sid irradiance (W/m²):
if 'Ee' in outlist:
Ee = spd_to_power(sid, cieobs = cieobs, ptype = 'ru')
# Get sid illuminance (lx):
if 'E' in outlist:
E = spd_to_power(sid, cieobs = cieobs, ptype = 'pusa') #photometric units (Km corrected to standard air)
# Get sid quantal energy (photons/m²/s):
if 'Q' in outlist:
Q = spd_to_power(sid, cieobs = cieobs, ptype = 'qu')
# get SI actinic action spectra, sa:
sa = spd(_ACTIONSPECTRA, wl = sid[0], interpolation = 'cmf', norm_type = 'max')
# get wavelength spacing:
dl = getwld(sid[0])
# Calculate all alpha-opics Ee's:
Eeas = (np.dot((sa[1:]*dl),sid[1:].T)).T
# Calculate equivalent alpha-opic E's:
Vl, Km = vlbar(cieobs = cieobs, wl_new = sid[0], out = 2)
Eas = Km*Km_correction_factor*Eeas*(Vl[1].sum()/sa[1:].sum(axis = 1))
#Prepare output:
if out == 'Eeas,Eas':
return Eeas,Eas
elif out == 'Eeas':
return Eeas
elif out == 'Eas':
return Eas
else:
eval(out)
.. codeauthor:: Kevin A.G. Smet (ksmet1977 at gmail.com) """ import luxpy as lx # get some spectral data: spds = lx._IESTM30['S']['data'][:5] rfls = lx._IESTM30['R']['99']['5nm'][:6] # check getdata(): rfls_df = lx.getdata(rfls, kind='df') rfls_np = lx.getdata(rfls_df, kind='np') # check spd_normalize: rfls_norm = lx.spd_normalize(rfls_np) rfls_np_cp = rfls_np.copy() rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='area', norm_f=2) rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='lambda', norm_f=560) rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='max', norm_f=1) rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='pu', norm_f=1) rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='ru', norm_f=1) rfls_norm = lx.spd_normalize(rfls_np_cp, norm_type='qu', norm_f=1) # check spd_to_xyz: xyz = lx.spd_to_xyz(spds) xyz = lx.spd_to_xyz(spds, relative=False) xyz = lx.spd_to_xyz(spds, rfl=rfls) xyz, xyzw = lx.spd_to_xyz(spds, rfl=rfls, cieobs='1931_2', out=2) # check xyz_to_cct():
def plot_tm30_spd(spd, cri_type = 'ies-tm30', axh = None,
font_size = _TM30_FONT_SIZE, **kwargs):
"""
Plot test SPD and reference illuminant, both normalized to the same luminous power.
Args:
:spd:
| ndarray or dict
| If ndarray: single spectral power distribution.
| If dict: dictionary with pre-computed parameters (using _tm30_process_spd()).
| required keys:
| 'Rf','Rg','cct','duv','Sr','cri_type','xyzri','xyzrw',
| 'hbinnrs','Rfi','Rfhi','Rcshi','Rhshi',
| 'jabt_binned','jabr_binned',
| 'nhbins','start_hue','normalize_gamut','normalized_chroma_ref'
| see cri.spd_to_cri() for more info on parameters.
:cri_type:
| _CRI_TYPE_DEFAULT or str or dict, optional
| -'str: specifies dict with default cri model parameters
| (for supported types, see luxpy.cri._CRI_DEFAULTS['cri_types'])
| - dict: user defined model parameters
| (see e.g. luxpy.cri._CRI_DEFAULTS['cierf']
| for required structure)
| Note that any non-None input arguments (in kwargs)
| to the function will override default values in cri_type dict.
:axh:
| None, optional
| If None: create new figure with single axes, else plot on specified axes.
:font_size:
| _TM30_FONT_SIZE, optional
| Font size of text, axis labels and axis values.
:kwargs:
| Additional optional keyword arguments,
| the same as in cri.spd_to_cri()
Returns:
:axh:
| handle to figure axes.
:data:
| dictionary with required parameters for plotting functions.
"""
data = _tm30_process_spd(spd, cri_type = 'ies-tm30',**kwargs)
# Normalize Sr to same luminous power as spd:
Phiv_spd = spd_to_power(data['spd'], ptype = 'pu', cieobs = data['cri_type']['cieobs']['cct'])
#Phiv_Sr = spd_to_power(data['Sr'], ptype = 'pu', cieobs = data['cri_type']['cieobs']['cct'])
data['Sr'] = spd_normalize(data['Sr'], norm_type = 'pu', norm_f = Phiv_spd, cieobs = data['cri_type']['cieobs']['cct'])
# Plot test and ref SPDs:
if axh is None:
fig, axh = plt.subplots(nrows = 1, ncols = 1)
axh.plot(data['Sr'][0,:], data['Sr'][1,:],'k-', label = 'Reference')
axh.plot(data['spd'][0,:], data['spd'][1,:],'r-', label = 'Test')
axh.set_xlabel('Wavelength (nm)', fontsize = font_size)
axh.set_ylabel('Radiant power\n(Equal Luminous Flux)', fontsize = font_size)
axh.set_xlim([360,830])
axh.set_yticklabels([])
axh.legend(loc = 'upper right', fontsize = font_size)
return axh, data