Merge pull request #10 from kadrlica/cleanup

Ok, this is probably enough for right now.
DarkEnergySurvey · May 7, 2018 · 17d78e2 · 17d78e2
2 parents 349d82f + 41e51b5
commit 17d78e2
Show file tree

Hide file tree

Showing 16 changed files with 533 additions and 871 deletions.
diff --git a/ugali/analysis/kernel.py b/ugali/analysis/kernel.py
@@ -9,11 +9,10 @@
 from collections import OrderedDict as odict
 import copy
 
-import numpy
 import numpy as np
+import healpy as hp
 import scipy.integrate
 import scipy.interpolate
-import healpy
 
 import ugali.utils.projector
 from ugali.utils.projector import Projector, angsep
@@ -69,7 +68,7 @@ def projector(self):
         else:
             return Projector(self.lon, self.lat, self.proj)
 
-    def integrate(self, rmin=0, rmax=numpy.inf):
+    def integrate(self, rmin=0, rmax=np.inf):
         """
         Calculate the 2D integral of the 1D surface brightness profile 
         (i.e, the flux) between rmin and rmax (elliptical radii). 
@@ -84,7 +83,7 @@ def integrate(self, rmin=0, rmax=numpy.inf):
         integral : Solid angle integral (deg^2)
         """
         if rmin < 0: raise Exception('rmin must be >= 0')
-        integrand = lambda r: self._pdf(r) * 2*numpy.pi * r
+        integrand = lambda r: self._pdf(r) * 2*np.pi * r
         return scipy.integrate.quad(integrand,rmin,rmax,full_output=True,epsabs=0)[0]
 
 class ToyKernel(Kernel):
@@ -101,7 +100,7 @@ class ToyKernel(Kernel):
         ])
 
     def _cache(self, name=None):
-        pixel_area = healpy.nside2pixarea(self.nside,degrees=True)
+        pixel_area = hp.nside2pixarea(self.nside,degrees=True)
         vec = ang2vec(self.lon, self.lat)
         self.pix = query_disc(self.nside,vec,self.extension)
         self._norm = 1./(len(self.pix)*pixel_area)
@@ -190,7 +189,7 @@ def sample_radius(self, n):
         cdf = np.cumsum(pdf)
         cdf /= cdf[-1]
         fn = scipy.interpolate.interp1d(cdf, list(range(0, len(cdf))))
-        index = numpy.floor(fn(numpy.random.uniform(size=n))).astype(int)
+        index = np.floor(fn(np.random.uniform(size=n))).astype(int)
         return radius[index]
 
     def sample_lonlat(self, n):
@@ -206,7 +205,7 @@ def sample_lonlat(self, n):
         radius = self.sample_radius(n)
         a = radius; b = self.jacobian * radius
 
-        t = 2. * np.pi * numpy.random.rand(n)
+        t = 2. * np.pi * np.random.rand(n)
         cost,sint = np.cos(t),np.sin(t)
         phi = np.pi/2. - np.deg2rad(self.theta)
         cosphi,sinphi = np.cos(phi),np.sin(phi)
@@ -326,7 +325,7 @@ class EllipticalPlummer(EllipticalKernel):
         ])
 
     def _kernel(self, radius):
-        return 1./(numpy.pi*self.r_h**2 * (1.+(radius/self.r_h)**2)**2)
+        return 1./(np.pi*self.r_h**2 * (1.+(radius/self.r_h)**2)**2)
 
     def _cache(self, name=None):
         if name in [None,'extension','ellipticity','truncate']:

diff --git a/ugali/candidate/associate.py b/ugali/candidate/associate.py
@@ -4,10 +4,9 @@
 import inspect
 from collections import OrderedDict as odict
 
-import numpy
 import numpy as np
-import fitsio
 from numpy.lib.recfunctions import stack_arrays
+import fitsio
 
 import ugali.utils.projector
 from ugali.utils.projector import gal2cel, cel2gal
@@ -16,7 +15,7 @@
 from ugali.utils.shell import get_ugali_dir
 from ugali.utils.logger import logger
 
-#class Catalog(numpy.recarray):
+#class Catalog(np.recarray):
 # 
 #    DATADIR=os.path.join(os.path.split(os.path.abspath(__file__))[0],"../data/catalogs/")
 # 
@@ -27,23 +26,23 @@
 #               ('dec',float),
 #               ('glon',float),
 #               ('glat',float)]
-#        self = numpy.recarray(0,dtype=dtype).view(cls)
+#        self = np.recarray(0,dtype=dtype).view(cls)
 #        self._load(filename)
 #        return self
 # 
 #    def __add__(self, other):
-#        return numpy.concatenate([self,other])
+#        return np.concatenate([self,other])
 # 
 #    def __getitem__(self, key):
 #        """ 
 #        Support indexing, slicing and direct access.
 #        """
 #        try:
-#            return numpy.recarray.__getitem__(key)
+#            return np.recarray.__getitem__(key)
 #        except ValueError, message:
 #            if key in self.name:
 #                idx = (self.name == key)
-#                return numpy.recarray.__getitem__(idx)
+#                return np.recarray.__getitem__(idx)
 #            else:
 #                raise ValueError(message)
 # 
@@ -75,7 +74,7 @@ def __init__(self, filename=None):
                    ('dec',float),
                    ('glon',float),
                    ('glat',float)]
-        self.data = numpy.recarray(0,dtype=columns)
+        self.data = np.recarray(0,dtype=columns)
         self._load(filename)
         if np.isnan([self.data['glon'],self.data['glat']]).any():
             raise ValueError("Incompatible values")
@@ -94,7 +93,7 @@ def __getitem__(self, key):
 
     def __add__(self, other):
         ret = SourceCatalog()
-        ret.data = numpy.concatenate([self.data,other.data])
+        ret.data = np.concatenate([self.data,other.data])
         return ret
 
     def __len__(self):
@@ -126,10 +125,10 @@ def _load(self,filename):
             filename = os.path.join(self.DATADIR,"J_AJ_144_4/NearbyGalaxies2012.dat")
         self.filename = filename
 
-        raw = numpy.genfromtxt(filename,delimiter=[19,3,3,5,3,3,3],usecols=range(7),dtype=['|S19']+6*[float],skip_header=36)
+        raw = np.genfromtxt(filename,delimiter=[19,3,3,5,3,3,3],usecols=range(7),dtype=['|S19']+6*[float],skip_header=36)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.strip(raw['f0'])
+        self.data['name'] = np.char.strip(raw['f0'])
 
         ra = raw[['f1','f2','f3']].view(float).reshape(len(raw),-1)
         dec = raw[['f4','f5','f6']].view(float).reshape(len(raw),-1)
@@ -152,7 +151,7 @@ def _load(self,filename):
             filename = os.path.join(self.DATADIR,"J_AJ_144_4/NearbyGalaxies.dat")
         self.filename = filename
 
-        raw = numpy.genfromtxt(filename,delimiter=[19,3,3,5,3,3,3],usecols=list(range(7)),dtype=['|S19']+6*[float],skip_header=36)
+        raw = np.genfromtxt(filename,delimiter=[19,3,3,5,3,3,3],usecols=list(range(7)),dtype=['|S19']+6*[float],skip_header=36)
 
         self.data.resize(len(raw))
         self.data['name'] = np.char.lstrip(np.char.strip(raw['f0']),'*')
@@ -180,7 +179,7 @@ def _load(self, filename):
         raw = fitsio.read(filename,lower=True)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.mod("RedMaPPer %d",raw['mem_match_id'])
+        self.data['name'] = np.char.mod("RedMaPPer %d",raw['mem_match_id'])
         self.data['ra'] = raw['ra']
         self.data['dec'] = raw['dec']
         glon,glat = cel2gal(raw['ra'],raw['dec'])
@@ -203,10 +202,10 @@ def _load(self,filename):
         self.filename = filename
 
         kwargs = dict(delimiter=[12,12,3,3,6,5,3,6,8,8,6],dtype=2*['S12']+7*[float],skip_header=72,skip_footer=363)
-        raw = numpy.genfromtxt(filename,**kwargs)
+        raw = np.genfromtxt(filename,**kwargs)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.strip(raw['f0'])
+        self.data['name'] = np.char.strip(raw['f0'])
 
         ra = raw[['f2','f3','f4']].view(float).reshape(len(raw),-1)
         dec = raw[['f5','f6','f7']].view(float).reshape(len(raw),-1)
@@ -228,18 +227,18 @@ def _load(self,filename):
             for basename in ['VII_239A/ngcpos.dat','VII_239A/icpos.dat']:
                 filename = os.path.join(self.DATADIR,basename)
                 raw.append(np.genfromtxt(filename,**kwargs))
-            raw = numpy.concatenate(raw)
+            raw = np.concatenate(raw)
         else:
-            raw = numpy.genfromtxt(filename,**kwargs)
+            raw = np.genfromtxt(filename,**kwargs)
         self.filename = filename
 
         # Some entries are missing...
-        raw['f4'] = numpy.where(numpy.isnan(raw['f4']),0,raw['f4'])
-        raw['f7'] = numpy.where(numpy.isnan(raw['f7']),0,raw['f7'])
+        raw['f4'] = np.where(np.isnan(raw['f4']),0,raw['f4'])
+        raw['f7'] = np.where(np.isnan(raw['f7']),0,raw['f7'])
 
         self.data.resize(len(raw))
-        names = numpy.where(raw['f0'] == 'N', 'NGC %04i', 'IC %04i')
-        self.data['name'] = numpy.char.mod(names,raw['f1'])
+        names = np.where(raw['f0'] == 'N', 'NGC %04i', 'IC %04i')
+        self.data['name'] = np.char.mod(names,raw['f1'])
 
         ra = raw[['f2','f3','f4']].view(float).reshape(len(raw),-1)
         dec = raw[['f5','f6','f7']].view(float).reshape(len(raw),-1)
@@ -258,16 +257,16 @@ def _load(self,filename):
 #        if filename is None: 
 #            filename = os.path.join(self.DATADIR,"NI2013.csv")
 # 
-#        raw = numpy.genfromtxt(filename,delimiter=',',usecols=[5,6]+range(13,20),dtype=['S1',int]+3*[float]+['S1']+3*[float])
+#        raw = np.genfromtxt(filename,delimiter=',',usecols=[5,6]+range(13,20),dtype=['S1',int]+3*[float]+['S1']+3*[float])
 # 
 #        self.data.resize(len(raw))
-#        names = numpy.where(raw['f0'] == 'N', 'NGC %04i', 'IC %04i')
-#        self.data['name'] = numpy.char.mod(names,raw['f1'])
+#        names = np.where(raw['f0'] == 'N', 'NGC %04i', 'IC %04i')
+#        self.data['name'] = np.char.mod(names,raw['f1'])
 # 
-#        sign = numpy.where(raw['f5'] == '-',-1,1)
+#        sign = np.where(raw['f5'] == '-',-1,1)
 #        ra = raw[['f2','f3','f4']].view(float).reshape(len(raw),-1)
 #        dec = raw[['f6','f7','f8']].view(float).reshape(len(raw),-1)
-#        dec[:,0] = numpy.copysign(dec[:,0], sign)
+#        dec[:,0] = np.copysign(dec[:,0], sign)
 # 
 #        self.data['ra'] = ugali.utils.projector.hms2dec(ra)
 #        self.data['dec'] = ugali.utils.projector.dms2dec(dec)
@@ -288,7 +287,7 @@ def _load(self,filename):
         raw = np.genfromtxt(filename,delimiter=[3,7,2,4,3,2],dtype=['S3']+['S7']+4*[float])
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.mod('UGC %s',numpy.char.strip(raw['f1']))
+        self.data['name'] = np.char.mod('UGC %s',np.char.strip(raw['f1']))
 
         ra = raw[['f2','f3']].view(float).reshape(len(raw),-1)
         ra = np.vstack([ra.T,np.zeros(len(raw))]).T
@@ -318,7 +317,7 @@ def _load(self,filename):
             for basename in ['VII_151/table1a.dat','VII_151/table1c.dat']:
                 filename = os.path.join(self.DATADIR,basename)
                 raw.append(np.genfromtxt(filename,**kwargs))
-            raw = numpy.concatenate(raw)
+            raw = np.concatenate(raw)
         else:
             raw = np.genfromtxt(filename,**kwargs)
         self.filename = filename
@@ -355,7 +354,7 @@ def _load(self,filename):
         raw = np.genfromtxt(filename,**kwargs)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.strip(raw['f0'])
+        self.data['name'] = np.char.strip(raw['f0'])
 
         self.data['glon'] = raw['f1']
         self.data['glat'] = raw['f2']
@@ -378,7 +377,7 @@ def _load(self,filename):
         raw = np.genfromtxt(filename,**kwargs)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.strip(raw['f0'])
+        self.data['name'] = np.char.strip(raw['f0'])
 
         ra = raw[['f1','f2','f3']].view(float).reshape(len(raw),-1)
         dec = raw[['f4','f5','f6']].view(float).reshape(len(raw),-1)
@@ -402,7 +401,7 @@ def _load(self,filename):
         raw = np.genfromtxt(filename,**kwargs)
 
         self.data.resize(len(raw))
-        self.data['name'] = numpy.char.strip(raw['f0'])
+        self.data['name'] = np.char.strip(raw['f0'])
 
         self.data['glon'] = raw['f1']
         self.data['glat'] = raw['f2']

diff --git a/ugali/isochrone/model.py b/ugali/isochrone/model.py
@@ -37,7 +37,6 @@
 import glob
 from functools import wraps
 
-import numpy
 import numpy as np
 import scipy.interpolate
 import scipy.stats
@@ -163,7 +162,7 @@ def sample(self, mode='data', mass_steps=1000, mass_min=0.1, full_data_range=Fal
         # ADW: Assume that the isochrones are pre-sorted by mass_init
         # This avoids some numerical instability from points that have the same
         # mass_init value (discontinuities in the isochrone).
-        # ADW: Might consider using numpy.interp for speed
+        # ADW: Might consider using np.interp for speed
         mass_act_interpolation = scipy.interpolate.interp1d(mass_init, mass_act,assume_sorted=True)
         mag_1_interpolation = scipy.interpolate.interp1d(mass_init, mag_1,assume_sorted=True)
         mag_2_interpolation = scipy.interpolate.interp1d(mass_init, mag_2,assume_sorted=True)
@@ -406,12 +405,12 @@ def sumMag(mag_1, mag_2):
         # Analytic part
         mass_init, mass_pdf, mass_act, mag_1, mag_2 = self.sample(mass_steps = steps)
         g,r = (mag_1,mag_2) if self.band_1 == 'g' else (mag_2,mag_1)
-        #cut = numpy.logical_not((g > mag_bright) & (g < mag_faint) & (r > mag_bright) & (r < mag_faint))
+        #cut = np.logical_not((g > mag_bright) & (g < mag_faint) & (r > mag_bright) & (r < mag_faint))
         cut = ((g + self.distance_modulus) > mag_faint) if self.band_1 == 'g' else ((r + self.distance_modulus) > mag_faint)
         mag_unobs = visual(g[cut], r[cut], richness * mass_pdf[cut])
 
         # Stochastic part
-        abs_mag_obs_array = numpy.zeros(n_trials)
+        abs_mag_obs_array = np.zeros(n_trials)
         for ii in range(0, n_trials):
             if ii%100==0: logger.debug('%i absolute magnitude trials'%ii)
             g, r = self.simulate(richness * self.stellar_mass())
@@ -421,11 +420,11 @@ def sumMag(mag_1, mag_2):
             abs_mag_obs_array[ii] = sumMag(mag_obs, mag_unobs)
 
         # ADW: This shouldn't be necessary
-        #abs_mag_obs_array = numpy.sort(abs_mag_obs_array)[::-1]
+        #abs_mag_obs_array = np.sort(abs_mag_obs_array)[::-1]
 
         # ADW: Careful, fainter abs mag is larger (less negative) number
         q = [100*alpha/2., 50, 100*(1-alpha/2.)]
-        hi,med,lo = numpy.percentile(abs_mag_obs_array,q)
+        hi,med,lo = np.percentile(abs_mag_obs_array,q)
         return ugali.utils.stats.interval(med,lo,hi)
 
     def simulate(self, stellar_mass, distance_modulus=None, **kwargs):