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import cv2
from matplotlib import pyplot as plt
import numpy as np
from skimage import draw
from scipy.signal import find_peaks

w = int(3648/4)
h = int(2736/4)
# Actual mouse callback function
def print_coords(event, x, y, flags, param):

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import PyDAQmx as daq
import numpy as np
import time
from ctypes import *
import matplotlib.pyplot as plt
from pyvcam import pvc
from pyvcam.camera import Camera
# device = 'dev1'
# try:
#     daq.DAQmxResetDevice(device)

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#!/usr/bin/env python
# Fit equations of state (EOS) to energy vs volume curves and optionally plot the results
# Davide Ceresoli <dceresoli@gmail.com>, 03/22/2011
# Inspired by ase.utils.eosase2
# TODO: Keane

import sys, numpy, math
from scipy.optimize import leastsq

# Murnaghan equation of state

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#!/usr/bin/env python
# Fit polynomial equations of state (EOS) to energy vs volume curves
# and optionally plot the results
# Davide Ceresoli <dceresoli@gmail.com>, 10/03/2012
# Inspired by ase.utils.eosase2

import sys, numpy, math
from scipy.optimize import leastsq
import numpy.polynomial.polynomial as poly

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import numpy as np
import math

# function to calculate LCM
def lcm(a):
  lcm = a[0]
  for i in range(1,len(a)):
    lcm = lcm*a[i]//math.gcd(lcm, a[i])
  return lcm

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import numpy as np
import matplotlib.pyplot as plt
from scipy.fftpack import fft, fftfreq
from scipy import signal
import glob
from scipy import constants
import pandas as pd
import glob
import matplotlib
matplotlib.style.use('seaborn-poster')

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