Fig_19b.ipynb

Kernel: Python 3 (system-wide)

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

plt.style.use('../jfm.mplstyle')

!find ../Experimental_Dataset -type f -name "elevation.csv.gz" | xargs dirname | sort | grep "undular" | tee "data_directories.txt" > /dev/null

def find_idx_nearest(x,v):
    return np.argmin(np.abs(x-v))

with open("data_directories.txt","r") as data_directories_file:
    data_directories = data_directories_file.read().splitlines()

data_directories = sorted([data_dir for data_dir in data_directories if 'x=-100.0cm' in data_dir])

h0, a0, g = 50, 5, 9810
c0 = np.sqrt(g*h0)
t0 = h0/c0

data_dir = data_directories[-1]

fig, ax = plt.subplots(figsize=(5.0/2,2.0),layout='constrained',dpi=600)

linestyles = ['-','--','-.']
yvalues = [0, 8, 12]

for yval, linestyle in zip(yvalues,linestyles):
    time  = np.loadtxt(f"{data_dir}/time.csv",delimiter=',',dtype=int)
    space = np.loadtxt(f"{data_dir}/space.csv",delimiter=',',dtype=int)
    elev  = np.loadtxt(f"{data_dir}/elevation.csv",delimiter=',')

    y   = (space*0.3)/h0
    t   = (time/125)/t0
    eta = elev/h0

    y_idx = find_idx_nearest(y,yval)

    ax.plot(t,eta[:,y_idx],color='k',linestyle=linestyle,label=f"{yval}")


ax.set_xlim(45,80)
ax.set_ylim(0,0.2)

ax.set_xlabel(r'$t$')
ax.set_ylabel(r'$\eta$')

plt.savefig('Fig_19b.pdf',dpi=600)
plt.show()