/
spec_view.py
executable file
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/
spec_view.py
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#!/usr/bin/env python
# This script plots spectra for vorticity, divergence and acceleration
# divergence from data in spectra.asc.
# Further options can be found using spec_view -h
#=====perform the various imports========
#=======needed by the main code==========
import sys,os,warnings
# Define main hydra tree locations:
uname=os.getlogin()
homedir=os.getenv('HOME')
rootdir=os.path.join(homedir,'hydra','scripts')
moddir=os.path.join(rootdir,'modules')
graphicsdir=os.path.join(rootdir,'graphics')
sys.path.append(moddir)
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as clrs
# Set default plot save resolution to a large value:
mpl.rcParams['savefig.dpi'] = 200
# Set label size:
mpl.rcParams['xtick.labelsize'] = 30
mpl.rcParams['ytick.labelsize'] = 30
mpl.rcParams['axes.linewidth'] = 3
import argparse
warnings.simplefilter("ignore",DeprecationWarning)
#========================================
#=====various function definitions=======
#========================================
def parse_args():
# Define a parser and read in the command line arguments passed when the script is run.
parser = argparse.ArgumentParser(prog='spec-view')
# Argument list:
# Default limits for the spectra are -12, 0.
# this can be over-ridden with this option:
parser.add_argument('-xlims', metavar='x_lim' , type=float , nargs=2, default='0.0 2.25'.split(),help='Lower and upper limits for x range of the plot')
parser.add_argument('-ylims', metavar='y_lim' , type=float , nargs=2, default='-12.0 0.0'.split(),help='Lower and upper limits for y range of the plot')
args = parser.parse_args()
# Return a parsed argument object:
return args
def running(args):
# Main code opening and controlling a plotting window.
# Open input file:
in_file=open('spectra.asc','r')
# Read the first header line to get kmax:
first_line=in_file.readline()
kmax=int(first_line.split()[-1])
in_file.seek(0)
nx=kmax
# Read in the full data to a 1d array and close input file:
raw_data = np.fromfile(file=in_file,dtype=float,sep='\n')
in_file.close()
# Set the number of frames:
nframes = int(len(raw_data)/(4*kmax+2))
print 'Number of frames found %i' %nframes
# Shape the data array into a useful shape for plotting:
frames=range(0,nframes)
time=[raw_data[i*(4*kmax+2)] for i in frames]
tim_eles = [i*(4*kmax+2)+j for i in frames for j in range(2)]
shaped_data = np.delete(raw_data,tim_eles)[0:(4*kmax+2)*nframes].reshape((nframes,kmax,4))
k=np.zeros((nframes,nx))
z=np.zeros((nframes,nx))
d=np.zeros((nframes,nx))
g=np.zeros((nframes,nx))
for i in frames:
k[i,:]=shaped_data[i].transpose()[0][0:nx]
z[i,:]=shaped_data[i].transpose()[1][0:nx]
d[i,:]=shaped_data[i].transpose()[2][0:nx]
g[i,:]=shaped_data[i].transpose()[3][0:nx]
global ic
# Grab the correct sub-array for plotting (ic is the current frame)
ic = 0
# Initiate a plotting window and plot relevant data into it:
fig = plt.figure(1,figsize=[12.5,12])
fig.subplots_adjust(left=0.15)
ax = fig.add_subplot(111)
im = ax.plot(k[ic],z[ic],'b-',lw=3,label='$\\zeta$')
im2 = ax.plot(k[ic],d[ic],'r-',lw=3,label='$\\delta$')
im3 = ax.plot(k[ic],g[ic],'m-',lw=3,label='$\\gamma$')
# Set plot title, legend and limits of the plot:
ax.set_title('Spectra at $t =$'+str('%.2f'%time[ic]), fontsize=40)
ax.set_xlabel('$\log_{10}\,k$', fontsize=40)
ax.set_ylabel('$\log_{10}\,|\hat{a}|^2$', fontsize=40)
ax.tick_params(length=10, width=3)
ax.legend(loc='lower left',prop={'size':30}, shadow=True)
xlimits=[float(x) for x in args.xlims]
ax.set_xlim(xlimits)
ylimits=[float(y) for y in args.ylims]
ax.set_ylim(ylimits)
def on_press(event):
# Routine to deal with re-plotting the window on keypress.
# The keys -/= (ie. -/+ without the shift key) cycle through frames
# forward and backwards.
global ic
if event.key=='=':
axes=event.canvas.figure.get_axes()[0]
ic = (ic+1+nframes) % nframes
xlim=axes.get_xlim()
ylim=axes.get_ylim()
# Clear the axes for replot:
axes.clear()
# Replot the relevant data:
axes.plot(k[ic],z[ic],'b-',lw=3,label='$\\zeta$')
axes.plot(k[ic],d[ic],'r-',lw=3,label='$\\delta$')
axes.plot(k[ic],g[ic],'m-',lw=3,label='$\\gamma$')
# Set the title, legend and plot limits:
axes.set_title('Spectra at $t =$'+str('%.2f'%time[ic]), fontsize=40)
axes.set_xlabel('$\log_{10}\,k$', fontsize=40)
axes.set_ylabel('$\log_{10}\,|\hat{a}|^2$', fontsize=40)
axes.tick_params(length=10, width=3)
axes.legend(loc='lower left',prop={'size':30}, shadow=True)
axes.set_xlim(xlim)
axes.set_ylim(ylim)
plt.draw()
if event.key=='-':
axes=event.canvas.figure.get_axes()[0]
ic = (ic-1+nframes) % nframes
xlim=axes.get_xlim()
ylim=axes.get_ylim()
# Clear the axes for replot:
axes.clear()
# Replot the relevant data:
axes.plot(k[ic],z[ic],'b-',lw=3,label='$\\zeta$')
axes.plot(k[ic],d[ic],'r-',lw=3,label='$\\delta$')
axes.plot(k[ic],g[ic],'m-',lw=3,label='$\\gamma$')
# Set the title, legend and plot limits:
axes.set_title('Spectra at $t =$'+str('%.2f'%time[ic]), fontsize=40)
axes.set_xlabel('$\log_{10}\,k$', fontsize=40)
axes.set_ylabel('$\log_{10}\,|\hat{a}|^2$', fontsize=40)
axes.tick_params(length=10, width=3)
axes.legend(loc='lower left',prop={'size':30}, shadow=True)
axes.set_xlim(xlim)
axes.set_ylim(ylim)
# Finally redraw the plot:
plt.draw()
# Begin the plot and link keypress events to the above handler:
cid=fig.canvas.mpl_connect('key_press_event',on_press)
plt.show()
if __name__ == '__main__':
# Main code to drive the above routines:
args = parse_args()
running(args)