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calc_peak_2_peak.py
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import glob
import numpy as np
import matplotlib.pyplot
from scipy.signal import find_peaks
import matplotlib.pyplot as plt
no_laser_files = glob.glob('Documents/graphene_hackathon/real_data/train/clean_Al*.csv')
no_laser_data = np.zeros((300,247))
for i,file in enumerate(no_laser_files):
data = np.genfromtxt(file,delimiter=',')
no_laser_data[i,::] = data
no_laser_avg_peak_2_peak = np.zeros((300))
for i in range(300):
peaks, _ = find_peaks(no_laser_data[i,::], height=0)
inv_peaks, _ = find_peaks(-no_laser_data[i,::], height=0)
inv_values = -no_laser_data[0,::][inv_peaks]
values = no_laser_data[0,::][peaks]
peak_2_peak = values + inv_values
no_laser_avg_peak_2_peak[i] = np.mean(peak_2_peak)
green_laser_files = glob.glob('Documents/graphene_hackathon/real_data/train/laser_Al*.csv')
green_laser_data = np.zeros((300,247))
for i,file in enumerate(green_laser_files):
data = np.genfromtxt(file,delimiter=',')
green_laser_data[i,::] = data
green_laser_avg_peak_2_peak = np.zeros((300))
for i in range(300):
peaks, _ = find_peaks(green_laser_data[i,::], height=0)
inv_peaks, _ = find_peaks(-green_laser_data[i,::], height=0)
inv_values = -green_laser_data[0,::][inv_peaks]
values = green_laser_data[0,::][peaks]
peak_2_peak = values + inv_values
green_laser_avg_peak_2_peak[i] = np.mean(peak_2_peak)
blue_laser_files = glob.glob('Documents/graphene_hackathon/real_data/train/laser_blue_Al*.csv')
blue_laser_data = np.zeros((300,247))
for i,file in enumerate(blue_laser_files):
data = np.genfromtxt(file,delimiter=',')
blue_laser_data[i,::] = data
blue_laser_avg_peak_2_peak = np.zeros((300))
for i in range(300):
peaks, _ = find_peaks(blue_laser_data[i,::], height=0)
inv_peaks, _ = find_peaks(-blue_laser_data[i,::], height=0)
inv_values = -blue_laser_data[0,::][inv_peaks]
values = blue_laser_data[0,::][peaks]
peak_2_peak = values + inv_values
blue_laser_avg_peak_2_peak[i] = np.mean(peak_2_peak)
cleaned_no_laser_peak_2_peak = no_laser_avg_peak_2_peak[no_laser_avg_peak_2_peak>np.mean(no_laser_avg_peak_2_peak)]
cleaned_green_laser_peak_2_peak = green_laser_avg_peak_2_peak[green_laser_avg_peak_2_peak>np.mean(green_laser_avg_peak_2_peak)]
cleaned_blue_laser_peak_2_peak = blue_laser_avg_peak_2_peak[blue_laser_avg_peak_2_peak>np.mean(blue_laser_avg_peak_2_peak)]
cleaned_cleaned_no_laser_peak_2_peak = cleaned_no_laser_peak_2_peak[cleaned_no_laser_peak_2_peak>np.mean(cleaned_no_laser_peak_2_peak)]
plt.figure(figsize=(12,8))
plt.plot(np.arange(0,len(cleaned_cleaned_no_laser_peak_2_peak[:140])),cleaned_cleaned_no_laser_peak_2_peak[:140],'ko',label='Without laser')
plt.plot(np.arange(0,len(cleaned_green_laser_peak_2_peak[:140])),cleaned_green_laser_peak_2_peak[:140],'go',label='Green laser')
plt.plot(np.arange(0,len(cleaned_blue_laser_peak_2_peak[:140])),cleaned_blue_laser_peak_2_peak[:140],'bo',label='Blue laser')
plt.xlabel('Number of runs')
plt.ylabel("Average peak to peak (V)")
plt.legend()
plt.title('Graphene/Aluminium/Graphene')
plt.show()