christopherlovell

for filename in IMG_38*; do heif-convert $filename ${filename}.png; done
for filename in IMG_38*.png; do mogrify -resize 50% $filename; done

christopherlovell

import numpy as np
import matplotlib.pyplot as plt

from synthesizer.filters import Filter, FilterCollection


filter_codes = ["JWST/NIRCam.F444W", "JWST/NIRCam.F480M"]
filtcoll = FilterCollection(filter_codes=filter_codes)

fig, ax = filtcoll.plot_transmission_curves(show=False, linestyle='solid')

christopherlovell

"""
PCA visualisation based on the example here:
https://gist.github.com/anonymous/7d888663c6ec679ea65428715b99bfdd
"""

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

plt.style.use('dark_background')

christopherlovell

from swiftsimio import Writer
from swiftsimio.units import cosmo_units

import unyt
import numpy as np
import h5py
import glob
  
files = glob.glob('ics*.hdf5')

christopherlovell

import sys
import os
import numpy as np
import matplotlib
# matplotlib.use('agg')
from matplotlib import pyplot as plt
# from IPython.display import clear_output
import tensorflow as tf
# physical_devices = tf.config.experimental.list_physical_devices('GPU')
# assert len(physical_devices) > 0, "Not enough GPU hardware devices available"

christopherlovell

def weighted_quantile(values, quantiles, sample_weight=None, 
                      values_sorted=False, old_style=False):
    """ 
    Taken from From https://stackoverflow.com/a/29677616/1718096
    
    Very close to numpy.percentile, but supports weights.
    NOTE: quantiles should be in [0, 1]!
    :param values: numpy.array with data
    :param quantiles: array-like with many quantiles needed

christopherlovell

"""
Script for creating subsets of particles from gizmo sims

Authors: 
- Sydney Lower
- Chris Lovell
"""

import h5py
import caesar

christopherlovell

"""
A tutorial introduction to Schwimmbad

https://github.com/adrn/schwimmbad

To install the requirements:

    > cat requirements.txt | xargs pip install

"""

christopherlovell

import numpy as np
import h5py
import glob

files = glob.glob('snap*')


coods = [None] * len(files)
ages = [None] * len(files)
metals = [None] * len(files)

christopherlovell

import numpy as np

# dimensions (age,metallicity,wavelength)
a = 2
Z = 3
wl = 4

weights = np.random.rand(a,Z,1)
grid = np.random.randint(1,10,(a,Z,wl))