Fig_21.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

# have to do some memory management on cocalc servers
from tempfile import mkdtemp
import os.path as path

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 "undular" | tee "data_directories.txt" > /dev/null

with open("data_directories.txt","r") as data_directories_file:
    data_directories = data_directories_file.read().splitlines()
    
amp = 'a0.5cm'
loc = 'y=+00.00cm'

xlim = (-20,20)
ylim = (50,130)

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

fig, axes = plt.subplots(ncols=2,nrows=1,figsize=(5.0,2.5),sharey='all',sharex='all',layout='constrained',dpi=300)

kwargs = {'vmin':-0.03,'vmax':0.27,'cmap':colormap}
vmin,vmax = kwargs['vmin'],kwargs['vmax']
levels = np.arange(vmin,vmax,0.018)
data_dirs = [d for d in data_directories if loc in d and amp in d]

# no-flow in the top row, with-flow in the bottom row
for ax, data_dir in zip(axes.flat,data_dirs):
    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)
    # work with elev from disk instead of memory
    elev = np.memmap('elev.dat', dtype=float, mode='w+', shape=(time.size,space.size))
    elev[:] = np.loadtxt(f"{data_dir}/elevation.csv",delimiter=',')
    
    space = space*dx/h
    time  = (time*dt)/t0
    elev  /= h
    
    #print(np.amin(elev),np.amax(elev))
    
    # work with X,T from disk instead of memory
    X = np.memmap('X.dat', dtype=float, mode='w+', shape=(time.size,space.size))
    T = np.memmap('T.dat', dtype=float, mode='w+', shape=(time.size,space.size))
    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)
    #title = 'with-flow' if 'with_flow' in data_dir else 'no-flow'
    #ax.set_title(title)

# some more memory management for cocalc
X,T,space,time,elev = None, None, None, None, None
# some disk management
os.remove('elev.dat')
os.remove('X.dat')
os.remove('T.dat')

axes[0].set_ylabel(r'$t$')

for ax in axes.flat:
     ax.set_xlabel(r'$x$')

#axes[0].set_title(r'no-flow')
#axes[1].set_title(r'with-flow')

cbar = fig.colorbar(cmp, ax=axes.ravel().tolist(),location='right',shrink=0.90)
cbar.ax.set_title(r'$\eta$')
cbar.add_lines(ctl)

#for label, ax in zip(['a)', 'b)'], axes):
#    ax.set_title(label,loc='left',fontfamily='Times New Roman',fontsize='9.0')

# some more memory management
cmp, ctl = None, None

plt.savefig('Fig_21.jpg')

plt.show()