dkirkby

# https://stackoverflow.com/a/37977222/4726728
# Requires numpy >= 1.7

c = np.divide(a, b, out=np.zeros_like(a), where=b!=0)

# Another method that maps all inexact values with finite ones.
# Unlike the method above, this also works inside @jax.jit
c = np.nan_to_num(a / b, posinf=0., neginf=0.)

dkirkby

# Given ellipticity parameters (e1, e2) and size s = det(Q)**(1/4)
# https://github.com/dkirkby/desietcimg/blob/master/desietcimg/plot.py
def draw_ellipse_se1e2(ax, x0, y0, s, g1, g2, nsigmas=1, **ellipseopts):
    g = np.sqrt(g1 ** 2 + g2 ** 2)
    if g > 1:
        raise ValueError('g1 ** 2 + g2 ** 2 > 1')
    center = np.array([x0, y0])
    angle = np.rad2deg(0.5 * np.arctan2(g2, g1))
    ratio = np.sqrt((1 + g) / (1 - g))
    width = 2 * s * ratio * nsigmas

dkirkby

def downsample(data, downsampling, summary=np.sum, allow_trim=False):
    """Downsample a 2D array.
    
    Parameters
    ----------
    data : array
        Two dimensional array of values to downsample.
    downsampling : int
        Downsampling factor to use along both dimensions. Must evenly divide the
        data dimensions when allow_trim is False.

dkirkby

'''
Save this file to scripts/myprog.py then add these lines to setup.py:

    entry_points = {
        'console_scripts': [
            'myprog=fpoffline.scripts.myprog:main',
        ],
    }
'''
import argparse

dkirkby

# See https://stackoverflow.com/questions/6910641/how-do-i-get-indices-of-n-maximum-values-in-a-numpy-array
# argpartition requires numpy >= 1.8.0
# See also http://seanlaw.github.io/2020/01/03/finding-top-or-bottom-k-in-a-numpy-array/

def argkmax1(a, k, axis=-1):
    """Return the indices of the k largest elements of a.
    
    With k=1, this is identical to argmax except that it
    returns an array of length 1 instead of a scalar.
    """

dkirkby

%reload_ext autoreload
%autoreload 1
%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt

# Modules imported by devpkg must also be listed here to get the same treatment.
%aimport devpkg
%aimport devpkg.util

dkirkby

# Get the latest name using tab completion or check sys.prefix from within jupyterhub
#module load python/3.8-anaconda-2020.11
module load python/3.9-anaconda-2021.11

# Create a new env. Only list the pkgs you need since they will be downloaded into ~/.conda/pkgs/
#conda create -n desi pip ipython jupyter ipykernel numpy scipy matplotlib pyyaml
conda create -n desi39 pip ipython jupyter ipykernel numpy scipy matplotlib pyyaml astropy pandas

# conda activate <env> *was* not supported at NERSC yet but is now
conda activate desi39

dkirkby

import time, sys
import IPython.display

class ProgressBar(object):
    """Replace existing contents of the current output cell with a progress bar.
    """
    def __init__(self, maxval=1., label='Progress', width=40):
        self.maxval = maxval
        self.label = label
        self.width = width

dkirkby

## DESI
conda create -n desi python=3.8 pip ipython jupyter jupyterlab ipykernel numpy scipy pandas matplotlib pyyaml requests psycopg2 astropy
conda activate desi
conda install -c conda-forge galsim fitsio

dkirkby

# Reuse the automatically selected color from a plot
line2d = plt.plot([0, 1], [0, 1], ':')
plt.scatter([0, 1], [0, 1], c=line2d[0].get_color())

# Reuse the automatically selected color from a scatter
pathcol = plt.scatter([0, 1], [0, 1])
plt.plot([0, 1], [0, 1], c=pathcol.get_fc()[0], ls=':')

# Use the j-th default color
c = plt.rcParams['axes.prop_cycle'].by_key()['color'][j]