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celinelee
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python_fn_calls

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engines.run(ten_distance, store={'b': Point(10, 10)
print(results)
is_near(results['distance'], 0.0)
engines.run(ten_distance)
print(results)
antpcf(dat,datR,bins,parmetric,permetric)
poserr(xi,DD)
returns (1.0+xi)
np.sqrt(DD)
atpcf(datfile, binspar, binsper, **kwargs)
bins (in $c/H_0$ units)
np.arange(0.002,0.06,0.002)
file (both ascii and fits files are supported)
atpcf('/path/to/datfile.dat',binspar, binsper, randfile='/path/to/randomfile.dat', vtype='sigpi', weights=True)
catalog (default 2x size)
atpcf('/path/to/datfile.dat', binspar, binsper, maskfile='/path/to/maskfile.ply', vtype='smu', weights='eq', randfact=3)
file (Mandatory)
option (must to obtain accurate results)
binspar (Mandatory)
units (for distances)
binsper (Mandatory)
units (for distances)
file (semi-Optional)
n(z)
file (semi-Optional)
format (with column title **radial_weight** or **WEIGHT_SYSTOT** )
choice (ref: https://arxiv.org/pdf/1312.0003.pdf)
estimator (default - fastest)
np.zeros((len(binspar)
len(binsper)
kwargs.items()
print (key, value)
key.lower()
key.lower()
key.lower()
value.lower()
value.lower()
value.lower()
value.lower()
key.lower()
value.lower()
value.lower()
print("Incorrect Cosmology provided! Using 'lcdm' as default")
key.lower()
value.lower()
value.lower()
key.lower()
value.lower()
value.lower()
print("Incorrect estimator provided! Using 'dp' as default")
key.lower()
key.lower()
isinstance(value, str)
value.lower()
print ("key argument `%s` not valid" % key)
print ("Refer documentation to enter valid keyword arguments")
max(np.sqrt(binsparv**2 + binsperv**2)
max(binsparv)
max(binsparv+binsperv)
print ("No valid valuation method provided. Using 'smu' as default")
print("Calculating Anisotropic Correlation function with the following parameters")
print("data file=")
print(datfile)
print("random file=")
print(randfile)
print("Random catalog size factor(if random file is None)
print(randcatfact)
print("mask/window file=")
print(maskfile)
print ("Cosmology=")
print(cosmology)
print ("Geometry=")
print (geometry)
print("Weights=")
print(weightsflag)
print ("Using ones as weights?=")
print (useones)
print("perpendicular metric=")
print(permetric)
print("parallel metric=")
print(parmetric)
print("Correl estimator=")
print(estimator)
print("Valuation type=")
print(vtype)
print ("binsparv=")
print (binsparv)
print ("binsperv=")
print (binsperv)
print("---------------------------------------------------------------------------")
datprepz(datfile, 'data', cosmology)
len(dat)
print ("Mask file compulsory. Please provide mask='maskfilepath.ply'")
randcatprepz(datfile, randcatsize, maskfile, cosmology)
datprepz(randfile, 'random', cosmology)
datprep(datfile, 'data', cosmology)
len(dat)
print ("Mask file compulsory. Please provide mask='maskfilepath.ply'")
randcatprep(datfile, randcatsize, maskfile, cosmology)
datprep(randfile, 'random', cosmology)