Source code for rail.estimation.algos.naiveStack

"""
A summarizer that simple makes a histogram of a point estimate
"""

import numpy as np
from ceci.config import StageParameter as Param
from rail.estimation.summarizer import PZSummarizer
from rail.core.data import QPHandle
import qp


[docs]class NaiveStack(PZSummarizer): """Summarizer which simply histograms a point estimate """ name = 'NaiveStack' config_options = PZSummarizer.config_options.copy() config_options.update(zmin=Param(float, 0.0, msg="The minimum redshift of the z grid"), zmax=Param(float, 3.0, msg="The maximum redshift of the z grid"), nzbins=Param(int, 301, msg="The number of gridpoints in the z grid"), seed=Param(int, 87, msg="random seed"), nsamples=Param(int, 1000, msg="Number of sample distributions to create")) outputs = [('output', QPHandle), ('single_NZ', QPHandle)] def __init__(self, args, comm=None): PZSummarizer.__init__(self, args, comm=comm) self.zgrid = None
[docs] def run(self): rng = np.random.default_rng(seed=self.config.seed) test_data = self.get_data('input') self.zgrid = np.linspace(self.config.zmin, self.config.zmax, self.config.nzbins + 1) pdf_vals = test_data.pdf(self.zgrid) yvals = np.expand_dims(np.sum(np.where(np.isfinite(pdf_vals), pdf_vals, 0.), axis=0), 0) qp_d = qp.Ensemble(qp.interp, data=dict(xvals=self.zgrid, yvals=yvals)) bvals = np.empty((self.config.nsamples, len(self.zgrid))) for i in range(self.config.nsamples): bootstrap_draws = rng.integers(low=0, high=test_data.npdf, size=test_data.npdf) bvals[i] = np.sum(pdf_vals[bootstrap_draws], axis=0) sample_ens = qp.Ensemble(qp.interp, data=dict(xvals=self.zgrid, yvals=bvals)) self.add_data('output', sample_ens) self.add_data('single_NZ', qp_d)