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commit c3dfd854d05e201f2c4c34c85f2de336c3e70a24 0 parents
@zonca authored
27 README.txt
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+Python package for dealing with Planck satellite data
+part of the US Planck Test Environment
+license: GPL v3
+author: Andrea Zonca
+Access to Planck Data is needed to make use of this package, this
+software does not include any performance number or any other
+information covered by the Planck Data Agreement.
+If you are in the Planck collaboration and interested in using
+and contributing to the software please contact me.
+* planck, LFI, HFI: metadata classes for LFI and HFI channels
+created dynamically from the Reduced Instrument Model (RIMO),
+not publicly available, not even channel names are available in
+this package.
+* pointing: pointing library which builds detector pointing from
+satellite quaternions, it is based on quaternionarray
+* utils, ps, hitmap: utilities for date conversion, angular power spectra
+and hitmaps
674 gplv3.txt
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+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library. If this is what you want to do, use the GNU Lesser General
+Public License instead of this License. But first, please read
27 planck/
@@ -0,0 +1,27 @@
+#!/usr/bin/env python
+# Generic python class for dealing with Planck HFI
+# by
+import planck
+import private
+class HFIChannel(planck.Channel):
+ @property
+ def centralfreq(self):
+ return self.f.freq
+ def Planck_to_RJ(self, data):
+ return data / private.mKRJ_2_mKcmb[self.f.freq]
+class HFI(planck.Instrument):
+ Channel = HFIChannel
+ def __init__(self, name = 'HFI', rimo =private.HFI_rimo):
+ super(HFI, self).__init__(name,rimo)
+ @staticmethod
+ def freq_from_tag(tag):
+ return int(tag[:3])
99 planck/
@@ -0,0 +1,99 @@
+#!/usr/bin/env python
+# Generic python class for dealing with Planck LFI
+# by
+import numpy as np
+import planck
+import private
+def flatten_d(chlist):
+ return [d for ch in chlist for d in ch.d]
+class LFIChannel(planck.Channel):
+ MS = { 0 : 'M', 1 : 'S' }
+ fromMS = { 'M' : 0, 'S' : 1}
+ def __init__(self, data, inst=None):
+ super(LFIChannel, self).__init__(data, inst)
+ self.d = [Detector(self, 0), Detector(self, 1)]
+ @property
+ def RCA(self):
+ return LFI.RCA_from_tag(self.tag)
+ @property
+ def arm(self):
+ return self.tag[-1]
+ @property
+ def n(self):
+ return self.fromMS[self.arm]
+ @property
+ def centralfreq(self):
+ return self.inst.instrument_db(self).field('nu_cen')
+ @property
+ def wn(self):
+ return self.inst.instrument_db(self).field('NET_KCMB')
+ def __getitem__(self, n):
+ return self.d[n]
+ def Planck_to_RJ(self, data):
+ import dipole
+ return dipole.Planck_to_RJ(data, self.centralfreq)
+class LFIFrequencySet(planck.FrequencySet):
+ @property
+ def d(self):
+ return flatten_d(
+class LFI(planck.Instrument):
+ Channel = LFIChannel
+ FrequencySet = LFIFrequencySet
+ def __init__(self, name = 'LFI', rimo = private.LFI_rimo):
+ super(LFI, self).__init__(name,rimo)
+ @classmethod
+ def freq_from_tag(cls, tag):
+ RCA = cls.RCA_from_tag(tag)
+ if RCA <= 23:
+ return 70
+ elif RCA <= 26:
+ return 44
+ elif RCA <= 28:
+ return 30
+ else:
+ return None
+ @staticmethod
+ def RCA_from_tag(tag):
+ return int(tag[3:5])
+ def instrument_db(self,ch):
+ if not hasattr(self,'_instrument_db'):
+ import pyfits
+ self._instrument_db =[1].data
+ det_index, = np.where(self._instrument_db.field('RADIOMETER').rfind(ch.tag)== 0)
+ return self._instrument_db[det_index]
+ @property
+ def d(self):
+ return flatten_d(
+class Detector(planck.ChannelBase):
+ def __init__(self, ch, n):
+ self.n = n
+ = ch
+ self.tag = '%s-%s%s' % (ch.tag,, self.n)
+ def savfilename(self, od):
+ return private.savfilename % (od,,, self.n)
+ @property
+ def cdstag(self):
+ return 'RCA%s%s%s' % (,, self.n)
0  planck/
No changes.
17 planck/
@@ -0,0 +1,17 @@
+result = command_line_args(count=count)
+lat = float(result[0])
+lon = float(result[1])
+radius = float(result[2])
+nside = float(result[3])
+;glon_glat = [lon 33.75, lat -40.33] ; Jupiter
+;radius = 1.5d ; deg
+;nside = 512
+ang2vec, lat , lon ,vector,/astro
+print, listpix
+exit, status = 0
68 planck/
@@ -0,0 +1,68 @@
+import matplotlib
+import healpy
+import cPickle
+import logging as l
+import numpy as np
+from LFI import LFI
+from pointing import Pointing
+from remix import read_exchange
+import glob
+def testBit(int_type, offset):
+ mask = 1 << offset
+ return(int_type & mask)
+def concat_hitmaps(folder = 'pkl/'):
+ files = glob.iglob(folder + '*pkl')
+ for f in files:
+ print(f)
+ odhitmap = cPickle.load(open(f,'rb'))
+ try:
+ hitmap += odhitmap
+ except:
+ hitmap = odhitmap
+ return hitmap
+class HitMap(object):
+ def __init__(self, freq, od, nside=512, use_flag=True):
+ LOG_FILENAME = '/u/zonca/p/issues/hitmap/full.log'
+ l.basicConfig(filename=LOG_FILENAME,level=l.DEBUG)
+ self.freq = freq
+ self.od = od
+ self.use_flag = use_flag
+ self.lfi = LFI()
+ self.f = self.lfi.f[self.freq]
+ self.nside = nside
+'%s ready' % self)
+ def __repr__(self):
+ return 'HitMap %d GHz, od %d' % (self.freq, self.od)
+ def run(self):
+ l.debug('Reading data')
+ read_exchange_obt_flag(self.freq, [self.f.r[0]], ods = [self.od], discard_flag = False,type='R')
+ obt =,0)!=0,self.f.obtx)
+ l.debug('Preparing pointing')
+ self.pnt = Pointing(obt.compressed(),coord='G')
+ self.hitmap = np.zeros(healpy.nside2npix(self.nside))
+ for rad in self.f.r:
+ l.debug('Processing rad %s' % rad)
+ vec = self.pnt.get(rad)
+ ids = np.bincount(healpy.vec2pix(self.nside, vec[:,0], vec[:,1], vec[:,2]))
+ self.hitmap[:len(ids)] += ids
+ l.debug('Writing to file')
+ cPickle.dump(self.hitmap, open('/u/zonca/p/issues/hitmap/pkl/%d_%d.pkl' % (self.freq,self.od),'wb'),protocol=-1)
+def pix2hitmap(pix, nside):
+ pix = pix.astype(
+ ids = np.bincount(pix)
+ hitmap = np.zeros(healpy.nside2npix(nside))
+ hitmap[:len(ids)] += ids
+ hitmap =,0)
+ hitmap.fill_value = healpy.UNSEEN
+ return hitmap
88 planck/
@@ -0,0 +1,88 @@
+import pyfits
+import numpy as np
+from exceptions import KeyError
+import itertools
+class ChannelBase(object):
+ '''Base for Channel, frequencyset and detector'''
+ def __repr__(self):
+ return self.tag
+class Channel(ChannelBase):
+ '''Abstract channel class for LFI and HFI channels'''
+ def __init__(self, data, inst=None):
+ self.tag = data[0]
+ self.rimo = data
+ self.inst = inst
+ @property
+ def sampling_freq(self):
+ return self.rimo['F_SAMP']
+class FrequencySet(ChannelBase):
+ def __init__(self, freq, ch, inst=None):
+ self.freq = freq
+ = ch
+ self.inst = inst
+ for ch in
+ ch.f = self
+ self.tag = '%d' % self.freq
+ def __repr__(self):
+ return '%d GHz' % self.freq
+ @property
+ def sampling_freq(self):
+ return[0].sampling_freq
+ @property
+ def wn(self):
+ return np.mean([ch.wn for ch in])
+class Instrument(object):
+ '''Common base class for LFI and HFI'''
+ Channel = Channel
+ FrequencySet = FrequencySet
+ def __init__(self, name, rimo):
+ '''Rimo is full path to Reduced Instrument Model FITS file'''
+ = name
+ self.rimo = rimo
+ rimo_file =[1].data
+ rimo_file.sort()
+ self.rimo_fields = rimo_file.dtype.names
+ = map(self.Channel, rimo_file, [self]*len(rimo_file))
+ self.chdict = dict( (ch.tag, ch) for ch in
+ self.f = self.create_frequency_sets()
+ def create_frequency_sets(self):
+ freqs = [self.freq_from_tag(ch.tag) for ch in]
+ f = {}
+ for freq in set(freqs):
+ chlist = [[i] for i,chfreq in enumerate(freqs) if chfreq == freq]
+ f[freq] = self.FrequencySet(freq, chlist, self)
+ return f
+ def __getitem__(self, key):
+ return self.chdict[key]
+import LFI
+import HFI
+class Planck(object):
+ '''Planck class, gives an iterator .ch for all LFI and HFI channels'''
+ def __init__(self):
+ self.inst = {'LFI':LFI.LFI(), 'HFI':HFI.HFI()}
+ = [ch for inst in self.inst.values() for ch in]
+ self.f = dict((freq,f) for inst in self.inst.values() for freq,f in inst.f.iteritems())
+ def __getitem__(self, key):
+ try:
+ return self.inst['LFI'][key]
+ except KeyError:
+ return self.inst['HFI'][key]
219 planck/
@@ -0,0 +1,219 @@
+from __future__ import division
+import math
+import operator
+import pyfits
+import logging as l
+import csv
+import glob
+from itertools import *
+from Quaternion import Quat as quat
+import numpy as np
+from LFI import LFI
+#from IPython.Debugger import Tracer; debug_here = Tracer()
+import re
+import cmb.quaternionarray as qarray
+from utils import grouper
+import planck
+import private
+from cgkit.cgtypes import *
+QECL2GAL = np.array((-0.37382079227204573, 0.33419217216073838, 0.64478939348298625, 0.57690575088960561))
+def ahf_limits(odrange = range(90,481 +1), folder = private.AHF_limits):
+ from IPython.kernel import client
+ tc = client.TaskClient()
+ files = [glob.glob(folder + '/%04d/att_hist_high*' % od)[0] for od in odrange]
+ lims =, files)
+ outfile = open('/u/zonca/p/remix/AHF-limits.txt','w')
+ out = csv.writer(outfile)
+ for f,l in zip(files,lims):
+ out.writerow([f,'%f' % l[0],'%f' % l[1]])
+ outfile.close()
+def get_ahf_lim(AHF):
+ import pyfits
+ f =
+ return f[1].data.field('OBT_SPL')[[0,-1]]/2.**16
+class Siam(object):
+ def __init__(self):
+ siamfile = private.siam
+ l.debug('using SIAM %s' % siamfile)
+ f = open(siamfile)
+ lines = f.readlines()
+ self.siam = {}
+ for line in grouper(4,lines[1:]):
+ chtag = line[0].split()[0]
+ m = np.matrix(';'.join(line[1:])).T
+ self.siam[chtag] = m
+ def get(self, ch):
+ if == 'HFI':
+ return self.siam[ch.tag]
+ else:
+ l.warning('For LFI using instrument DB angles')
+ return SiamAngles().get(ch)
+class SiamAngles(object):
+ def __init__(self):
+ pass
+ def get(self, ch):
+ mat_spin2boresight=mat3.rotation(np.pi/2-self.SPIN2BORESIGHT/180.*np.pi,vec3(0,1,0))
+ theta = ch.rimo['THETA_UV']/180.*np.pi
+ phi = ch.rimo['PHI_UV']/180.*np.pi
+ psi = ch.rimo['PSI_UV']/180.*np.pi
+ mat_theta_phi = mat3.rotation(theta,vec3(-math.sin(phi),math.cos(phi),0))
+ mat_psi = mat3.rotation(psi,vec3(0,0,1))
+ # detector points to X axis
+ total = mat_spin2boresight * (mat_theta_phi * mat_psi)
+ total_mat = np.matrix(np.split(np.array(total.toList(rowmajor=True)),3))
+ # siam is defined as pointing to Z axis
+ return total_mat * np.matrix([[0,0,1],[0,1,0],[1,0,0]])
+def AHF_filename2od(filename):
+ return int(re.findall('/(\d{4})/',filename)[0])
+def get_AHF_limits(filenames = True):
+ limitsfile = private.limitsfile
+ if filenames:
+ dt=np.dtype({'names':['filename','start','end'],'formats':['S100',np.float,np.float]})
+ return np.loadtxt(open(limitsfile),delimiter=',',dtype=dt)
+ else:
+ dt=np.dtype({'names':['od','start','end'],'formats':[,np.float,np.float]})
+ return np.loadtxt(open(limitsfile),delimiter=',',dtype=dt, converters={0: AHF_filename2od})
+def AHF_btw_OBT(obt):
+ limits = get_AHF_limits()
+ first_file_index = limits['start'].searchsorted(obt[0]) - 1
+ last_file_index = limits['end'].searchsorted(obt[-1])
+ if first_file_index == -1:
+ first_file_index = 0
+ if last_file_index > len(limits) -1:
+ last_file_index -= 1
+ files = limits['filename'][first_file_index:last_file_index + 1]
+ l.debug('Opening %s' % files)
+ return files
+def generate_repointing_flag(obt):
+ flag = np.zeros_like(obt)
+ files = [[1].data for file in AHF_btw_OBT(obt)]
+ files[-1] = files[-1][:(files[-1].field('OBT_SPL')/2.**16).searchsorted(obt[-1])+1]
+ files[0] = files[0][(files[0].field('OBT_SPL')/2.**16).searchsorted(obt[0])-1:]
+ AHF = np.concatenate(files)
+ i_start_repointing, = np.nonzero(np.diff(AHF['OBT_BEG']))
+ start_repointing = AHF['OBT_SPL'][i_start_repointing+1]/2.**16
+ end_repointing = AHF['OBT_BEG'][i_start_repointing+1]/2.**16
+ for start, end in zip(start_repointing,end_repointing):
+ flag[obt.searchsorted(start):obt.searchsorted(end)] = 1
+ return flag
+def quaternion_ecl2gal(qsat):
+ '''Convert array of quaternions from Ecliptic to Galactic'''
+'Rotating to Galactic frame')
+ qsatgal = qarray.mult(QECL2GAL ,qsat)
+ # renormalizing to unity
+ qsatgal = qarray.norm(qsatgal)
+ return qsatgal
+def vector_ecl2gal(vecl):
+ '''Convert arrays from Ecliptic to Galactic'''
+'Rotating to Galactic frame')
+ return qarray.rotate(QECL2GAL ,vecl)
+class Pointing(object):
+ '''Pointing interpolation and rotation class
+ usage:
+ >>> ch= Planck()['100-1a']
+ >>> pnt = Pointing(obt, coord='G') #interpolates AHF to obt
+ >>> vec = pnt.get(ch) #rotates to detector frame and gives x,y,z vector
+ >>> pix = pnt.get_pix(ch, 2048, nest=True) #healpix pixel number nside 2048
+ '''
+ def __init__(self,obt,coord='G', AHF_d=None, nointerp=False):
+ '''AHF_d is the pyfits AHF data if already loaded in the main file
+ nointerp to use the AHF OBT stamps'''
+ l.warning('Pointing setup, coord:%s' % coord)
+ #get ahf limits
+ if AHF_d is None:
+ AHF_data_iter = ([1].data for file in AHF_btw_OBT(obt))
+ else:
+ AHF_data_iter = [AHF_d]
+ ahfobt = np.array([])
+ qsat = None
+ for AHF_data in AHF_data_iter:
+ obt_spl = AHF_data.field('OBT_SPL')/2.**16
+ i_start = max(obt_spl.searchsorted(obt[0])-1,0)
+ i_end = min(obt_spl.searchsorted(obt[-1])+1,len(obt_spl)-1)
+ AHF = AHF_data[i_start:i_end]
+ allquat = np.hstack([AHF.field('QUATERNION_X')[:,np.newaxis], AHF.field('QUATERNION_Y')[:,np.newaxis], AHF.field('QUATERNION_Z')[:,np.newaxis], AHF.field('QUATERNION_S')[:,np.newaxis]])
+ if qsat is None:
+ qsat = allquat
+ else:
+ qsat = np.vstack([qsat,allquat])
+ ahfobt = np.concatenate([ahfobt, AHF.field('OBT_SPL')/2.**16])
+ if coord == 'E':
+ qsatgal = qsat
+ elif coord == 'G':
+ hfobt = np.array([])
+ qsatgal = quaternion_ecl2gal(qsat)
+ if nointerp:
+ self.qsatgal_interp = qsatgal
+ else:
+'Interpolating quaternions')
+ #nlerp
+ self.qsatgal_interp = qarray.nlerp(obt, ahfobt, qsatgal)
+'Quaternions interpolated')
+ self.siam = Siam()
+ self.ahfobt = ahfobt
+ self.obt = obt
+ def interp_get(self, rad):
+ '''Interpolation after rotation to gal frame'''
+ from Quaternion import Quat
+'Rotating to detector %s' % rad)
+ siam_quat = Quat(self.siam.get(rad)).q
+ totquat = qarray.mult(self.qsatgal_interp, siam_quat)
+ totquat_interp = qarray.nlerp(self.obt, self.ahfobt, totquat)
+ x = np.array([[1, 0, 0]]).T
+ x = np.array(x).flatten()
+ vec = qarray.rotate(totquat_interp, x)
+'Rotated to detector %s' % rad)
+ return vec
+ def get(self, rad):
+'Rotating to detector %s' % rad)
+ x = self.siam.get(rad) * np.array([[1, 0, 0]]).T
+ x = np.array(x).flatten()
+ vec = qarray.rotate(self.qsatgal_interp, x)
+'Rotated to detector %s' % rad)
+ return vec
+ def get_pix(self, rad, nside=1024, nest=True):
+ from healpy import vec2pix
+ vec = self.get(rad)
+ return vec2pix(nside, vec[:,0], vec[:,1], vec[:,2], nest)
+ def get_ang(self, rad):
+ from healpy import vec2ang
+ vec = self.get(rad)
+ return vec2ang(vec)
96 planck/
@@ -0,0 +1,96 @@
+import subprocess
+import pkgutil
+import numpy as np
+import os
+import pyfits
+from configobj import ConfigObj
+import math
+import healpy
+from cluster import run_serial
+def apply_mask(mask, m):
+ m[mask == 0] = healpy.UNSEEN
+ return m
+def sum_diff_maps(a, b):
+ '''Returns half-sum and half-difference of input maps on common pixels
+ '''
+ valid_pixels = np.logical_and(a != healpy.UNSEEN, b != healpy.UNSEEN)
+ jackmaps = np.zeros_like([a,b])
+ jackmaps[:] = healpy.UNSEEN
+ jackmaps[0][valid_pixels] = ( a[valid_pixels] + b[valid_pixels]) / 2
+ jackmaps[1][valid_pixels] = ( a[valid_pixels] - b[valid_pixels]) / 2
+ return jackmaps
+def smooth(m, arcmin, lmax = None):
+ '''Utility to smooth a map with smooting by Healpix
+ '''
+ unseen = m == healpy.UNSEEN
+ healpy.write_map('tempmap.fits', m, nest = False)
+ config_filename = 'config_smooth.txt'
+ config = ConfigObj()
+ config.filename = config_filename
+ config['simul_type'] = 1
+ if lmax:
+ config['nlmax'] = lmax
+ config['infile'] = 'tempmap.fits'
+ config['outfile'] = 'tempmap_smoothed.fits'
+ config['fwhm_arcmin'] = arcmin
+ config.write()
+ if os.path.exists('tempmap_smoothed.fits'):
+ os.remove('tempmap_smoothed.fits')
+ callstring = 'smoothing --double %s' % config_filename
+, shell=True)
+ smoothed_m = healpy.read_map('tempmap_smoothed.fits')
+ smoothed_m[unseen] = healpy.UNSEEN
+ return smoothed_m
+def remove_dipole(m, gal_cut = 30):
+ #module abs path
+ abspath = os.path.dirname(__file__)
+ if os.path.exists('tempmap.fits'):
+ os.remove('tempmap.fits')
+ healpy.write_map('tempmap.fits',m,nest = False)
+ callstring = 'idl %s/ -IDL_QUIET 1 -quiet -args tempmap.fits %d' % (abspath,gal_cut)
+, shell=True)
+ out = healpy.read_map('no_dipole_tempmap.fits', nest=True)
+ os.remove('no_dipole_tempmap.fits')
+ return out
+def anafast(m, gal_cut = 30, lmax = None):
+ '''Utility to run anafast by Healpix'''
+ healpy.write_map('tempmap.fits', m, nest = False)
+ config_filename = 'anafastconfig.txt'
+ config = ConfigObj()
+ config.filename = config_filename
+ config['simul_type'] = 1
+ if gal_cut:
+ config['theta_cut_deg'] = gal_cut
+ if lmax:
+ config['nlmax'] = lmax
+ config['infile'] = 'tempmap.fits'
+ config['outfile'] = 'tempcl.fits'
+ config['won'] = 0
+ config.write()
+ if os.path.exists('tempcl.fits'):
+ os.remove('tempcl.fits')
+ callstring = 'anafast --double %s' % config_filename
+, shell=True)
+ cl ='tempcl.fits')[1].data.field('TEMPERATURE')
+ os.remove('tempcl.fits')
+ return cl
+def cut_planet(lat, lon, radius = 1.5, nside = 512):
+ '''Cut planet
+ Example:
+ Jupiter [lat -40.33,lon 33.75] radius = 1.5 deg'''
+ callstring = 'idl -IDL_QUIET 1 -quiet -args %f %f %f %f' % (lat, lon, radius, nside)
+ popen = subprocess.Popen(callstring, shell=True, stdout=subprocess.PIPE, cwd = os.path.dirname(__file__))
+ output = popen.communicate()[0]
+ return map(float, output.strip().split())
1  planck/
@@ -0,0 +1 @@
+contains sensitive data, NOT PUBLISHED
79 planck/
@@ -0,0 +1,79 @@
+from __future__ import division
+import numpy as np
+from itertools import *
+import ephem
+import datetime
+OBTSTARTDATE = datetime.datetime(1958,1,1,0,0,0)
+LAUNCH = datetime.datetime(2009, 5, 13, 13, 11, 57, 565826)
+SECONDSPERDAY = 3600 * 24
+def grouper(n, iterable, padvalue=None):
+ "grouper(3, 'abcdefg', 'x') --> ('a','b','c'), ('d','e','f'), ('g','x','x')"
+ return izip(*[chain(iterable, repeat(padvalue, n-1))]*n)
+def ahfdate2obt(ahfdate):
+ jd = ephem.Date(ahfdate.replace('T',' ').replace('-','/')) - ephem.Date('-4713/1/1 12:00:0')
+ return jd2obt(jd)
+def time2sample(freq, time):
+ if freq == 30:
+ return int((time - 1621174818.021514892578125) * 32.5079365079365)
+ elif freq == 44:
+ return int((time - 1621174818.012481689453125) * 46.5454545454545)
+ elif freq == 70:
+ return int((time - 1621174818.008087158203125) * 78.7692307692308)
+ else:
+ return None
+def ndsample2time(freq, sample):
+ if freq == 30:
+ time_flat = 1621174818.021514892578125 + (sample / 32.5079365079365)
+ BREAK98 = 1629377124.0625305
+ BREAK98LEN = 3.573974609375
+ afterbreak, = np.where(time_flat >= BREAK98)
+ correction = np.zeros_like(time_flat)
+ correction[afterbreak] = BREAK98LEN
+ time_corrected = time_flat + correction
+ return time_corrected
+def sample2time(freq, sample):
+ if freq == 30:
+ return 1621174818.021514892578125 + (sample / 32.5079365079365)
+ elif freq == 44:
+ return 1621174818.012481689453125 + (sample / 46.5454545454545)
+ elif freq == 70:
+ return 1621174818.008087158203125 + (sample / 78.7692307692308)
+ else:
+ return None
+def timedelta2seconds(diff):
+ return diff.days * 24 * 3600 + diff.seconds + diff.microseconds * 1e-3
+def obt2utc(obt):
+ '''Convert OBT (s) to UTC'''
+ return OBTSTARTDATE + datetime.timedelta(0,obt)
+def utc2obt(utc):
+ '''Convert UTC (datetime object) to OBT (s)'''
+ return timedelta2seconds(utc - OBTSTARTDATE)
+def approxod2utc(od):
+ return LAUNCH + datetime.timedelta(od)
+def utc2approxod(utc):
+ return timedelta2seconds(utc - LAUNCH) / SECONDSPERDAY
+def approxod2obt(od):
+ return utc2obt(approxod2utc(od))
+def obt2approxod(obt):
+ return utc2approxod(obt2utc(obt))
+def powerspectrum(s, Fs):
+ import matplotlib.pyplot as plt
+ Pxx, freqs = plt.mlab.psd(s, NFFT=len(s), Fs = Fs)
+ return freqs, Pxx
+def whitenoise(lenght):
+ return np.random.standard_normal(size=lenght)
@@ -0,0 +1,25 @@
+from setuptools import setup, find_packages
+ name = "planck",
+ version = "0.3",
+ packages = ['planck'],
+ # Project uses reStructuredText, so ensure that the docutils get
+ # installed or upgraded on the target machine
+ install_requires = ['docutils>=0.3'],
+ package_data = {
+ # If any package contains *.txt or *.rst files, include them:
+ '': ['*.txt', '*.rst'],
+ },
+ # metadata for upload to PyPI
+ author = "Andrea Zonca",
+ author_email = "",
+ description = "Python package for working with Planck data",
+ license = "PSF",
+ keywords = "Planck science data",
+ url = "", # project home page, if any
+ # could also include long_description, download_url, classifiers, etc.
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