Fig_16.ipynb

Kernel: Python 3 (system-wide)

import os

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms

import scipy.integrate as integrate
from scipy import signal

from scipy.signal import find_peaks
from matplotlib.lines import Line2D

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

rainbow = np.loadtxt("../rainbow.tsv")

def array2cmpa(X):
    from matplotlib import colors
    # Assuming array is Nx3, where x3 gives RGB values
    # Append 1's for the alpha channel, to make X Nx4
    X = np.c_[X,np.ones(len(X))]

    return colors.LinearSegmentedColormap.from_list('my_colormap', X)

rainbow_map = array2cmpa(rainbow)

colormap = rainbow_map #'coolwarm' #'plasma' #rainbow_map

!find ../Experimental_Dataset -type f -name "elevation.csv.gz" | xargs dirname | sort | grep "sol3rd" | tee "data_directories.txt" > /dev/null

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

amp = 'a1.5cm'
locs = ['x=-02.54cm','x=+00.00cm','x=+02.54cm','x=+07.62cm']

xlim = (-2,2)
ylim = (57,80)

dx,dt,h,g = 0.3,1/125,50,9810
t0 = np.sqrt(h/g)

fig, axes = plt.subplots(ncols=4,nrows=2,figsize=(5.0,3.5),sharey='all',sharex='all',layout='constrained')

kwargs = {'vmin':-0.07,'vmax':0.50,'cmap':colormap}
vmin,vmax = kwargs['vmin'],kwargs['vmax']
levels = np.arange(vmin,vmax,0.03)

for axcol, loc in zip(axes.T,locs):
    data_dirs = [d for d in data_directories if loc in d and amp in d]
    
    for data_dir, ax in zip(data_dirs,axcol):
        time  = np.loadtxt(f"{data_dir}/time.csv",delimiter=',',dtype=int)
        t_off = np.loadtxt(f"{data_dir}/time_offset.csv")
        space = np.loadtxt(f"{data_dir}/space.csv",delimiter=',',dtype=int)
        elev  = np.loadtxt(f"{data_dir}/elevation.csv",delimiter=',')
        
        space = space*dx/h
        time  = (time*dt - t_off)/t0
        elev  = elev/h
        
        X,T = np.meshgrid(space,time)
        
        cmp = ax.pcolormesh(X,T,elev,shading='nearest',**kwargs)
        ctl = ax.contour(X,T,elev,levels=levels,colors='k',linewidths=0.25)
        ax.set_xlim(*xlim)
        ax.set_ylim(*ylim)

for ax in axes[:,0]:
    ax.set_ylabel(r'$t$')

for ax in axes[1,:]:
     ax.set_xlabel(r'$y$')

titles = [r'$x=-0.508$',r'$x=0^+$',r'$x=0.508$',r'$x=1.52$']
for ax,title in zip(axes[0,:],titles):
    ax.set_title(title)

cbar = fig.colorbar(cmp, ax=axes.ravel().tolist(),location='right',shrink=0.70)
cbar.ax.set_title(r'$\eta$')
cbar.add_lines(ctl)

#labels = ['a)', 'b)', 'c)', 'd)', 'e)', 'f)', 'g)', 'h)']
#for label, ax in zip(labels, axes[:,0]):
#    trans = mtransforms.ScaledTranslation(-29/72, 7/72, fig.dpi_scale_trans)
#    ax.text(0.0, 1.0, label, transform=ax.transAxes + trans,
#            fontsize='9.0', verticalalignment='top', fontfamily='Times New Roman',
#            bbox=dict(facecolor='1.0', edgecolor='none', pad=2.0))

plt.savefig('Fig_16.jpg')
plt.show()