lgarrison

swot: https://github.com/jcoupon/swot/
corrfunc: https://github.com/manodeep/Corrfunc

To test the speed and agreement of swot vs corrfuc, we generated random
datasets of increasing size and measured the w(theta) autocorrelation function.

Swot has an approximation parameter 'OA' (opening angle) that critically impacts its runtime.
We tried OA=0.03 and OA='no'.  However, even the conservative value of OA=0.03
caused >10% errors in wtheta for this randomized configuration.  Thus, it should
be used with caution.

lgarrison

lgarrison

# Note: this function uses the term 'radius', but the histogramming is completely general

import numpy as np

def RadialBin(radii, values, bin_edges, bin_indices=None):
    """
    Radial histogramming that supports fast re-evaluation
    for the same `radii` with new `values` by passing back `bin_indices`.
    
    Parameters

lgarrison

lgarrison

lgarrison

lgarrison

/*

This is a "minimal" reproducer for an apparent GCC-7 bug related to AVX-512.
It has a 100% reproduction rate on my machine (Cascade Lake).

A simple loop that copies the values from a double array to a float array
sometimes gives the wrong answer in the first few elements (zero, nan, or garbage).

The bug seems correlated with alignment values of the input and output
arrays, but it's not a one-to-one relationship.

lgarrison

#!/usr/bin/env python3

'''
This script facilitates Globus transfers of Abacus simulation data.
In particular, for AbacusSummit we want to transfer particle data and
halo catalogs from OLCF to NERSC after each simulation is done.
Both sites already have Globus endpoints, so the job of this script
is to initiate a transfer between the two, saving the transfer ID
number so we can query the transfer status later.
The intention of this script is primarily to do disk-to-disk

lgarrison

'''
A simple multi-threaded Python file writer.

Author: Lehman Garrison (lgarrison.github.io)
'''

import threading
import queue

import numpy as np

lgarrison

import numba as nb
import numpy as np

def nb_ecdf(X,Rmax,ngrid=64,nthreads=1):
    '''Compute the empirical CDF of points X (shape (N,D))
    in domain [0,Rmax) using a histogram with `ngrid` cells
    per dimension.
    
    Rmax and ngrid can also be length D arrays.
    '''