avivajpeyi

trigger-time=1268431094.157825
channel-dict={ H1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01, L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01,V1:Hrec_hoft_16384Hz }
coherence-test=False
detectors=['H1', 'L1', 'V1']
duration=16.0
psd-dict={ H1:/home/daniel.williams/events/O3/event_repos/S200316a/C01_offline/psds/4096/H1-psd.dat, L1:/home/daniel.williams/events/O3/event_repos/S200316a/C01_offline/psds/4096/L1-psd.dat, V1:/home/daniel.williams/events/O3/event_repos/S200316a/C01_offline/psds/4096/V1-psd.dat }
psd-fractional-overlap=0.5
post-trigger-duration=2.0
sampling-frequency=4096.0
psd-length=16

avivajpeyi

""" Plots total number of CPU hours used	
To create a "jobstats.txt" run somthing like the following:	
> sacct -S 2020-01-01 -E 2021-10-06 -u avajpeyi -X -o "jobname%-40,cputimeraw,start" --parsable2 > jobstats.txt	
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from humanize import intword
from matplotlib import ticker
from datetime import timedelta, datetime, date

avivajpeyi

avivajpeyi

""" Plots total number of CPU hours used	
To create a "jobstats.txt" run somthing like the following:	
> sacct -S 2020-01-01 -E 2021-10-06 -u avajpeyi -X -o "jobname%-40,cputimeraw,start" --parsable2 > jobstats.txt	
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from humanize import intword
from matplotlib import ticker

avivajpeyi

#%% md

# Plot signal 

#%%


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

avivajpeyi

### FIGURE
figure.facecolor: white
figure.dpi: 300
figure.titlesize: x-large  # fontsize of the axes title
figure.titleweight: bold

### LINES
lines.linewidth: 1.5

### PATCHES

avivajpeyi

"""Demo of Matched Filtering"""
from typing import Callable, Dict, Optional

import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
import scipy.signal
from plotly.subplots import make_subplots

N_POINTS = 1000

avivajpeyi

from typing import List, Optional
import seaborn as sns

def get_colors(num_colors: int, alpha: Optional[float]=1) -> List[List[float]]:
    """Get a list of colorblind colors,

    :param num_colors: Number of colors.
    :param alpha: The transparency
    :return: List of colors. Each color is a list of [r, g, b, alpha].
    """

avivajpeyi

"""
Completed backtracking code for week11, demonstrating bike-lock combos

Author: Gavin
Modifed by: Avi

"""
import itertools
from typing import List

avivajpeyi

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits import mplot3d


# Defining the functions and its first derivative
def f(x):
    return x ** 3 - 2 * x ** 2 - 11 * x + 12