Cls for fields generated with synalm disagree with input Cls and Cls for fields generated using synfast
I am generating random healpix maps from an input angular power spectrum Cl. If I use healpy.synalm, then healpy.alm2map, and finally test the map by running healpy.anafast on the generated map, the output and input power spectra do not agree, especially at high l, the output power spectrum is above the input (See plot produced by code below). If I directly use healpy.synfast, I get an output power spectrum that agrees with the input. The same applies if I use the alms from healpy.synfast and generate a map from the synfast alms using healpy.alm2map. When I look into the source code of synfast, it seems to just call synalm and alm2map, so I don't understand, why their results disagree. My test code looks like this:
import numpy as np
import matplotlib.pyplot as plt
import classy
import healpy as hp
NSIDE = 32
A_s=2.3e-9
n_s=0.9624
h=0.6711
omega_b=0.022068
omega_cdm=0.12029
params = {
'output': 'dCl, mPk',
'A_s': A_s,
'n_s': n_s,
'h': h,
'omega_b': omega_b,
'omega_cdm': omega_cdm,
'selection_mean': '0.55',
'selection_magnification_bias_analytic': 'yes',
'selection_bias_analytic': 'yes',
'selection_dNdz_evolution_analytic': 'yes'}
cosmo = classy.Class()
cosmo.set(params)
cosmo.compute()
theory_cl=cosmo.density_cl()['dd']
data_map,data_alm=hp.synfast(theory_cl[0],NSIDE,alm=True)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast")
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast using alm")
data_alm=hp.synalm(theory_cl[0])
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synalm")
plt.plot(np.arange(min(len(data_cl),len(theory_cl[0]))),theory_cl[0][:len(data_cl)],label="Theory")
plt.xlabel(r'$ell$')
plt.ylabel(r'$C_ell$')
plt.legend()
plt.show()
The offset becomes larger for lower NSIDE.
Thank you very much for your help.
healpy
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
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I am generating random healpix maps from an input angular power spectrum Cl. If I use healpy.synalm, then healpy.alm2map, and finally test the map by running healpy.anafast on the generated map, the output and input power spectra do not agree, especially at high l, the output power spectrum is above the input (See plot produced by code below). If I directly use healpy.synfast, I get an output power spectrum that agrees with the input. The same applies if I use the alms from healpy.synfast and generate a map from the synfast alms using healpy.alm2map. When I look into the source code of synfast, it seems to just call synalm and alm2map, so I don't understand, why their results disagree. My test code looks like this:
import numpy as np
import matplotlib.pyplot as plt
import classy
import healpy as hp
NSIDE = 32
A_s=2.3e-9
n_s=0.9624
h=0.6711
omega_b=0.022068
omega_cdm=0.12029
params = {
'output': 'dCl, mPk',
'A_s': A_s,
'n_s': n_s,
'h': h,
'omega_b': omega_b,
'omega_cdm': omega_cdm,
'selection_mean': '0.55',
'selection_magnification_bias_analytic': 'yes',
'selection_bias_analytic': 'yes',
'selection_dNdz_evolution_analytic': 'yes'}
cosmo = classy.Class()
cosmo.set(params)
cosmo.compute()
theory_cl=cosmo.density_cl()['dd']
data_map,data_alm=hp.synfast(theory_cl[0],NSIDE,alm=True)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast")
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast using alm")
data_alm=hp.synalm(theory_cl[0])
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synalm")
plt.plot(np.arange(min(len(data_cl),len(theory_cl[0]))),theory_cl[0][:len(data_cl)],label="Theory")
plt.xlabel(r'$ell$')
plt.ylabel(r'$C_ell$')
plt.legend()
plt.show()
The offset becomes larger for lower NSIDE.
Thank you very much for your help.
healpy
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
I am generating random healpix maps from an input angular power spectrum Cl. If I use healpy.synalm, then healpy.alm2map, and finally test the map by running healpy.anafast on the generated map, the output and input power spectra do not agree, especially at high l, the output power spectrum is above the input (See plot produced by code below). If I directly use healpy.synfast, I get an output power spectrum that agrees with the input. The same applies if I use the alms from healpy.synfast and generate a map from the synfast alms using healpy.alm2map. When I look into the source code of synfast, it seems to just call synalm and alm2map, so I don't understand, why their results disagree. My test code looks like this:
import numpy as np
import matplotlib.pyplot as plt
import classy
import healpy as hp
NSIDE = 32
A_s=2.3e-9
n_s=0.9624
h=0.6711
omega_b=0.022068
omega_cdm=0.12029
params = {
'output': 'dCl, mPk',
'A_s': A_s,
'n_s': n_s,
'h': h,
'omega_b': omega_b,
'omega_cdm': omega_cdm,
'selection_mean': '0.55',
'selection_magnification_bias_analytic': 'yes',
'selection_bias_analytic': 'yes',
'selection_dNdz_evolution_analytic': 'yes'}
cosmo = classy.Class()
cosmo.set(params)
cosmo.compute()
theory_cl=cosmo.density_cl()['dd']
data_map,data_alm=hp.synfast(theory_cl[0],NSIDE,alm=True)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast")
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast using alm")
data_alm=hp.synalm(theory_cl[0])
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synalm")
plt.plot(np.arange(min(len(data_cl),len(theory_cl[0]))),theory_cl[0][:len(data_cl)],label="Theory")
plt.xlabel(r'$ell$')
plt.ylabel(r'$C_ell$')
plt.legend()
plt.show()
The offset becomes larger for lower NSIDE.
Thank you very much for your help.
healpy
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
I am generating random healpix maps from an input angular power spectrum Cl. If I use healpy.synalm, then healpy.alm2map, and finally test the map by running healpy.anafast on the generated map, the output and input power spectra do not agree, especially at high l, the output power spectrum is above the input (See plot produced by code below). If I directly use healpy.synfast, I get an output power spectrum that agrees with the input. The same applies if I use the alms from healpy.synfast and generate a map from the synfast alms using healpy.alm2map. When I look into the source code of synfast, it seems to just call synalm and alm2map, so I don't understand, why their results disagree. My test code looks like this:
import numpy as np
import matplotlib.pyplot as plt
import classy
import healpy as hp
NSIDE = 32
A_s=2.3e-9
n_s=0.9624
h=0.6711
omega_b=0.022068
omega_cdm=0.12029
params = {
'output': 'dCl, mPk',
'A_s': A_s,
'n_s': n_s,
'h': h,
'omega_b': omega_b,
'omega_cdm': omega_cdm,
'selection_mean': '0.55',
'selection_magnification_bias_analytic': 'yes',
'selection_bias_analytic': 'yes',
'selection_dNdz_evolution_analytic': 'yes'}
cosmo = classy.Class()
cosmo.set(params)
cosmo.compute()
theory_cl=cosmo.density_cl()['dd']
data_map,data_alm=hp.synfast(theory_cl[0],NSIDE,alm=True)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast")
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synfast using alm")
data_alm=hp.synalm(theory_cl[0])
data_map=hp.alm2map(data_alm,NSIDE)
data_cl=hp.anafast(data_map)
plt.plot(np.arange(len(data_cl)),data_cl,label="synalm")
plt.plot(np.arange(min(len(data_cl),len(theory_cl[0]))),theory_cl[0][:len(data_cl)],label="Theory")
plt.xlabel(r'$ell$')
plt.ylabel(r'$C_ell$')
plt.legend()
plt.show()
The offset becomes larger for lower NSIDE.
Thank you very much for your help.
healpy
healpy
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
asked Jan 18 at 16:00
Benedict KalusBenedict Kalus
61
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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1 Answer
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Sorry, I missed that synfast knows about NSIDE, so the lmax is by default based on NSIDE, whereas synalm does not know about it, so it takes the maximum l of the input spectrum as lmax. Setting lmax to 3 * NSIDE -1 in synalm resolves the discrepancy.
answered yesterday
Benedict KalusBenedict Kalus
61
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Sorry, I missed that synfast knows about NSIDE, so the lmax is by default based on NSIDE, whereas synalm does not know about it, so it takes the maximum l of the input spectrum as lmax. Setting lmax to 3 * NSIDE -1 in synalm resolves the discrepancy.
answered yesterday
Benedict KalusBenedict Kalus
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Sorry, I missed that synfast knows about NSIDE, so the lmax is by default based on NSIDE, whereas synalm does not know about it, so it takes the maximum l of the input spectrum as lmax. Setting lmax to 3 * NSIDE -1 in synalm resolves the discrepancy.
answered yesterday
Benedict KalusBenedict Kalus
61
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Sorry, I missed that synfast knows about NSIDE, so the lmax is by default based on NSIDE, whereas synalm does not know about it, so it takes the maximum l of the input spectrum as lmax. Setting lmax to 3 * NSIDE -1 in synalm resolves the discrepancy.
answered yesterday
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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Sorry, I missed that synfast knows about NSIDE, so the lmax is by default based on NSIDE, whereas synalm does not know about it, so it takes the maximum l of the input spectrum as lmax. Setting lmax to 3 * NSIDE -1 in synalm resolves the discrepancy.
answered yesterday
Benedict KalusBenedict Kalus
61
New contributor
Benedict Kalus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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answered yesterday
Benedict KalusBenedict Kalus
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answered yesterday
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answered yesterday
Benedict KalusBenedict Kalus
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