astrodendro-viewer Macro for plot sorting tests

gistfile1.py

import numpy as np

plot_sort_name = "npix"

cube_view.z = 212

set_color_map("bone")

highlighters = [create_highlighter(c) for c in ["purple", "green", "orange", "brown"]]

coords = [(51,69,213), (69,7,214), (3,14,212), (96,32,212)]

fig_num = 1

def generate(min_flux,min_npix,min_delta, desc=""):
    global fig_num
    make_dendrogram(min_flux=min_flux, min_npix=min_npix, min_delta=min_delta)
    for i in range(0,4):
        highlighters[i].highlight_coords(coords[i])
    title="Sorting by {method}, Fig. {num}".format(method=plot_sort_name, num=fig_num)
    if desc:
	    desc += " "
    desc=desc+"flux {f} npix {n} delta {d}".format(f=min_flux, n=min_npix, d=min_delta)
    filename="{method}_{fig:02}_{desc}.pdf".format(method=plot_sort_name, fig=fig_num, desc=desc.replace(" ", "_"))
    export_pdf(filename, title=title, subtitle=desc)
    fig_num += 1

# Now, run the following one-by-one to generate the plots:

generate(min_flux=1.4, min_npix=10, min_delta=0.3) #1

generate(min_flux=1.4, min_npix=10, min_delta=0.2) #2

generate(min_flux=1.4, min_npix=10, min_delta=0.4) #3

generate(min_flux=1.6, min_npix=10, min_delta=0.3) #4

generate(min_flux=1.4, min_npix=10, min_delta=0.4) #5

generate(min_flux=1.6, min_npix=30, min_delta=0.3) #6

generate(min_flux=1.0, min_npix=5, min_delta=0.15) #7

# Now, some noise tests:

orig_data = cube.data

set_data(orig_data + np.random.normal(scale=0.1, size=cube.data.shape))
generate(min_flux=1.4, min_npix=10, min_delta=0.3, desc="noise 0.1 A"); # 8

set_data(orig_data + np.random.normal(scale=0.1, size=cube.data.shape))
generate(min_flux=1.4, min_npix=10, min_delta=0.3, desc="noise 0.1 B"); # 9

set_data(orig_data + np.random.normal(scale=0.2, size=cube.data.shape))
generate(min_flux=1.4, min_npix=10, min_delta=0.3, desc="noise 0.2"); # 10

set_data(orig_data + np.random.normal(scale=0.3, size=cube.data.shape))
generate(min_flux=1.4, min_npix=10, min_delta=0.3, desc="noise 0.3"); # 11