Milad Pourrahmani Miladiouss
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University of California, Irvine
- Irvine, CA
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View pix2world_timing.py
from time import sleep, time | |
import numpy as np | |
from astropy import wcs | |
w = wcs.WCS(naxis=2) | |
w.wcs.ctype = ["RA---SIN","DEC--SIN"] | |
w.wcs.cdelt = (6.2/3600, 6.2/3600) | |
w.wcs.crval = (30, 60) | |
w.wcs.crota = (0, 15) | |
# ---------------------------------------- |
View matplotlibTemplate.py
""" | |
Author: Miladious | |
Latest Modification Date: Oct 11, 2019 | |
About: | |
Creating a publication quality figure using matplotlib requires a lot of tweaks. | |
In this gist, I show the main tweaks for creating publication quality plots. | |
This is an example how one would plot astronomical images in python. | |
Feel free to modify to your field's standards. | |
""" |
View IPythonAppetizer.py
# https://gist.github.com/Miladiouss/332b21e3c9d82ca2085b1396641cc80d | |
#----------------------------------------------------------- | |
# IPython | |
from IPython.core.interactiveshell import InteractiveShell | |
from IPython.display import clear_output | |
InteractiveShell.ast_node_interactivity = "all" | |
from IPython import display | |
#----------------------------------------------------------- | |
# Scientific |
View HSC-Cat-Selection.sql
-- An HSC-PDR2 SQL query to extract RA, Dec, tract, patch of clean galaxies with a magnitude cut. | |
-- Useful Links: | |
-- /https://hsc-release.mtk.nao.ac.jp/hscMap-pdr2/app/#/?_=%7B%22view%22%3A%7B%22a%22%3A5.770914805732617,%22d%22%3A-0.019535944017082533,%22fovy%22%3A0.0002503311005562077,%22roll%22%3A0%7D,%22sspParams%22%3A%7B%22type%22%3A%22SDSS_TRUE_COLOR%22,%22filter%22%3A%5B%22HSC-I%22,%22HSC-R%22,%22HSC-G%22%5D,%22simpleRgb%22%3A%7B%22beta%22%3A22026.465794806718,%22a%22%3A1,%22bias%22%3A0.05,%22b0%22%3A0%7D,%22sdssTrueColor%22%3A%7B%22beta%22%3A26003.369421497522,%22a%22%3A1,%22bias%22%3A0.14439999999999995,%22b0%22%3A0%7D%7D%7D | |
-- https://hsc-release.mtk.nao.ac.jp/schema/#pdr2.pdr2_wide.forced | |
SELECT | |
object_id | |
, tract |
View Ordinality.py
def appendOrdinality(df, columns, ascending, strictlyIncreasing=False): | |
""" | |
Appends absolute and relative ordinality to a dataframe. | |
Oridinality is the normalized position of a row in a sorted dataframe. | |
df: | |
Pandas DataFrame | |
columns: | |
List of column names for to be used for sorting (e.g. ['prob_1']) | |
ascending: |
View Stamp.py
from datetime import datetime | |
timeFormat = '%a %b %d %Y at %H:%M:%S' | |
import socket | |
deviceName = socket.gethostname() | |
import getpass | |
userName = getpass.getuser() | |
t1 = datetime.now() | |
print(t1.strftime(timeFormat) + ' on ' + deviceName + ' by ' + userName) |
View GPU Detection Test in Python and PyTorch.py
# GPU Detection Tests | |
from torch.cuda import device_count | |
import gpustat | |
print(""" | |
If pytorch raises "RuntimeError: cuda runtime error (30)" after suspension, | |
run the following commands in linux terminal: | |
sudo rmmod nvidia_uvm | |
sudo rmmod nvidia |
View logistic_map.py
# Library import for plotting | |
import matplotlib.pyplot as plt | |
%matplotlib inline | |
# Define Logistic Map | |
def f(x, r): | |
return r * x * (1 - x) | |
# Define history and parameters | |
history = [0.5] |
View Python_FITS_Handler.py
import numpy as np | |
from pathlib import Path | |
# AstroPy | |
from astropy import units as u | |
from astropy.io import fits | |
from astropy.wcs import WCS | |
from astropy.coordinates import SkyCoord, Angle | |
from astropy.nddata import Cutout2D |
View histogramTransform.py
import numpy as np | |
from matplotlib import pyplot as plt | |
import torch | |
class HistogramTransform(object): | |
""" | |
Transforms the distribution of the input tensor to match that | |
of the list of template histograms corresponding to each channel. | |
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