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#!/usr/bin/python
# the Scientific Python netCDF 3 interface
from Scientific.IO.NetCDF import NetCDFFile as Dataset
import matplotlib
matplotlib.use("Agg") # to avoid some DISPLAY issues on compute nodes, we do not need display anyways
from pylab import*
import pylab
import numpy
import scipy.interpolate
import matplotlib.colors
import sys
import matplotlib.pyplot as plt
import matplotlib.animation as animation
# Time to start...
# What figures to plot:
lfig1 = True
lfig2 = True
lfig3 = True
params2 = {'backend': 'eps',
'axes.labelsize': 10,
'text.fontsize': 20,
'xtick.labelsize': 26,
'ytick.labelsize': 26,
'text.fontsize': 20,
'xtick.labelsize': 12,
'ytick.labelsize': 12,
'legend.pad': 0.5, # empty space around the legend box
'legend.fontsize': 16,
'lines.markersize': 3,
'font.size': 10,
'figure.figsize': (9,6)}
rcParams.update(params2)
rcParams['text.usetex']=True
rcParams['ps.usedistiller']='xpdf'
# Getting netcdf files to read from command-line arguments
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
nb_arg = len(sys.argv) ; # number of "command-line" arguments
if nb_arg < 2 or nb_arg > 3:
print 'Usage: '+sys.argv[0]+' <file_to_be_read.nc> (<land_sea_mask.nc>) \n'
sys.exit(0)
cf_in = sys.argv[1] ; # the file we read temperature from
# if 3rd argument present that must be the land-sea mask file:
cf_lsm = ''
if nb_arg == 3: cf_lsm = sys.argv[2]
# Opening the Netcdf file for reading relevant variables
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
vlin3 = np.zeros((163,141))
vlin4 = np.zeros((163,141))
vlin5 = np.zeros((163,141))
tmpvlin5 = np.zeros((163,141))
vlin6 = np.zeros((163,141))
id_in = Dataset(cf_in)
print 'File ', cf_in, 'is open...\n'
vlon1 = id_in.variables['vz'][:][:][:]; # extracting longitude 3D array
vlon2 = id_in.variables['vy'][:][:][:]; # extracting longitude 3D array
vlon3 = id_in.variables['G1'][:][:][:]; # extracting longitude 3D array
vlon4 = id_in.variables['G2'][:][:][:]; # extracting longitude 3D array
#vlon3 =id_in.variables['Fi_low2'][:][:];
tt0=495
# Plot data
fig1 = figure()
#manage axis
extraticks=[-0.5, 0.5]
plt.xticks(list(plt.xticks()[0]) + extraticks)
axis([-0.5, 0.5, 0,1.0]) ; # X-Y axis bound:
xlabel('$z/ \delta$',fontsize=15)
ylabel(' $y/ \delta$',fontsize=15)
u= np.linspace(-0.15, 0.15, num=141)/0.3 #horizontal
v=np.linspace(0, 0.3, num=163)/0.3
vlin3 = np.zeros((163,141))
vlin4 = np.zeros((163,141))
tt =tt0
dt = 1
for l in range(141):
for l2 in range(163):
if l%2==0:
if l2%2==0:
vlin3[l2,l] = vlon1[l,l2,tt]
vlin4[l2,l] = vlon2[l,l2,tt]
Q = quiver(u, v, vlin3, vlin4, scale=2.5)
nt =0;
def updatefig(nt):
global Q
for l in range(141):
for l2 in range(163):
if l%2==0:
if l2%2==0:
vlin3[l2,l] = vlon1[l,l2,tt+nt]
vlin4[l2,l] = vlon2[l,l2,tt+nt]
Q.set_UVC(vlin3,vlin4)
ani = animation.FuncAnimation(fig1, updatefig, frames=10)
ani.save('movie.mp4')
print 'end', |
Quiver animation avec matplotlib
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