vx = 0
vy = 1
vz = 2
pr = 3
ro = 4
bx = 5
by = 6
bz = 7
ps = 8
# reading the data ...
# x,y,t,data = openmhd.data_read("data/field-%05d.dat" % 15)
# reading the data (partial domain: [ix1,ix2] x [jx1,jx2])
x, y, t, data = openmhd.data_read("data/field-%05d.dat" % 15,
ix1=0,
ix2=301,
jx1=0,
jx2=51)
# 2D mirroring (This depends on the BC)
ix = x.size
jx = 2 * y.size - 2
jxh = y.size - 1
tmp = data
data = np.ndarray((ix, jx, 9), np.double)
data[:, jxh:, :] = tmp[:, 1:, :]
data[:, 0:jxh, :] = tmp[:, -1:-jxh - 1:-1, :]
data[:, 0:jxh, vy] = -tmp[:, -1:-jxh - 1:-1, vy]
data[:, 0:jxh, vz] = -tmp[:, -1:-jxh - 1:-1, vz]
data[:, 0:jxh, bx] = -tmp[:, -1:-jxh - 1:-1, bx]
data[:, 0:jxh, ps] = -tmp[:, -1:-jxh - 1:-1, ps]
bx = 5
by = 6
bz = 7
ps = 8
# ---- for movies --------------------
# NOTE: "import os" is necessary
if not os.path.exists('movie'):
print('This routine outputs image files in "./movie/".')
os.mkdir('./movie/')
# ---- loop for movies ---------------
for ii in range(0, 41):
# reading the data ...
x, y, t, data = openmhd.data_read("data/field-%05d.dat" % ii)
# clearing the current figure, if any
plt.clf()
# extent: [left, right, bottom, top]
extent = [x[0], x[-1], y[0], y[-1]]
# 2D plot (vmin/mymin: minimum value, vmax/mymax: max value)
# Note: ().T is necessary for 2-D plot routines (imshow/pcolormesh...)
tmp = np.ndarray((x.size, y.size), np.double)
tmp[:, :] = data[:, :, pr]
mymax = max(tmp.max(), -tmp.min()) if (tmp.max() > 0.0) else 0.0
mymin = min(tmp.min(), -tmp.max()) if (tmp.min() < 0.0) else 0.0
myimg = plt.imshow(tmp.T,
origin='lower',
vmin=mymin,
vmax=mymax,
import matplotlib.pyplot as plt
import numpy as np
import openmhd
# dummy index
vx = 0
vy = 1
vz = 2
pr = 3
ro = 4
bx = 5
by = 6
bz = 7
ps = 8
# reading the data ...
x, y, t, data = openmhd.data_read(15)
# x,y,t,data = openmhd.data_read(15,ix1=300,ix2=901,jx1=150,jx2=451)
# preparing the canvas
fig = plt.figure(figsize=(10, 5), dpi=80)
# fig.clear()
plt.clf()
# extent: [left, right, bottom, top]
extent = [x[0], x[-1], y[0], y[-1]]
# 2D plot
myimg = plt.imshow(data[:, :, vx].T,
origin='lower',
cmap='jet',
extent=extent,
aspect='auto')
import openmhd # dummy index vx = 0 vy = 1 vz = 2 pr = 3 ro = 4 bx = 5 by = 6 bz = 7 ps = 8 # reading the data ... #x,y,t,data = openmhd.data_read(8) # reading the data (partial domain: [ix1,ix2] x [jx1,jx2]) x, y, t, data = openmhd.data_read(10, ix1=0, ix2=1301, jx1=0, jx2=151) # 2D mirroring (This depends on the BC) ix = x.size jx = 2 * y.size - 2 jxh = y.size - 1 tmp = data data = np.ndarray((ix, jx, 9), np.double) data[:, jxh:, :] = tmp[:, 1:, :] data[:, 0:jxh, :] = tmp[:, -1:-jxh - 1:-1, :] data[:, 0:jxh, vy] = -tmp[:, -1:-jxh - 1:-1, vy] data[:, 0:jxh, vz] = -tmp[:, -1:-jxh - 1:-1, vz] data[:, 0:jxh, bx] = -tmp[:, -1:-jxh - 1:-1, bx] data[:, 0:jxh, ps] = -tmp[:, -1:-jxh - 1:-1, ps] tmp = y y = np.ndarray((jx), np.double)
import matplotlib.pyplot as plt
import numpy as np
import openmhd
import gc
# dummy index
vx=0;vy=1;vz=2;pr=3;ro=4;bx=5;by=6;bz=7;ps=8
# reading the data ...
# x,y,t,data = openmhd.data_read("data/field-%05d.dat" % 8)
# reading the data (partial domain: [ix1,ix2] x [jx1,jx2])
x,y,t,data = openmhd.data_read("data/field-%05d.dat" % 10,ix1=0,ix2=1301,jx1=0,jx2=151)
# 2D mirroring (This depends on the BC)
ix = x.size
jx = 2*y.size-2
jxh= y.size-1
tmp = data
data = np.ndarray((ix,jx,9),np.double)
data[:,jxh:,:] = tmp[:,1:,:]
data[:,0:jxh, :] = tmp[:,-1:-jxh-1:-1, :]
data[:,0:jxh,vy] = -tmp[:,-1:-jxh-1:-1,vy]
data[:,0:jxh,vz] = -tmp[:,-1:-jxh-1:-1,vz]
data[:,0:jxh,bx] = -tmp[:,-1:-jxh-1:-1,bx]
data[:,0:jxh,ps] = -tmp[:,-1:-jxh-1:-1,ps]
# releasing the memory, because this tmp could be large
del tmp
gc.collect()
tmp = y
y = np.ndarray((jx),np.double)
y[jxh:] = tmp[1:]
import matplotlib.pyplot as plt
import numpy as np
import openmhd
# dummy index
vx=0;vy=1;vz=2;pr=3;ro=4;bx=5;by=6;bz=7;ps=8
# reading the data ...
x,y,t,data = openmhd.data_read("data/field-%05d.dat" % 15)
# reading the data (partial domain: [ix1,ix2] x [jx1,jx2])
# x,y,t,data = openmhd.data_read("data/field-%05d.dat" % 15,ix1=300,ix2=901,jx1=150,jx2=451)
# preparing the canvas
fig = plt.figure(figsize=(10, 5), dpi=80)
# fig.clear()
plt.clf()
# extent: [left, right, bottom, top]
extent=[x[0],x[-1],y[0],y[-1]]
# 2D plot (vmin/mymin: minimum value, vmax/mymax: max value)
# Note: ().T is necessary, because the imshow routine uses the image coordinates
tmp = np.ndarray((x.size,y.size),np.double)
tmp[:,:] = data[:,:,vx]
mymax = max(tmp.max(), -tmp.min()) if( tmp.max() > 0.0 ) else 0.0
mymin = min(tmp.min(), -tmp.max()) if( tmp.min() < 0.0 ) else 0.0
myimg = plt.imshow(tmp.T,origin='lower',vmin=mymin,vmax=mymax,cmap='jet',extent=extent,aspect='auto')
# image operations (e.g. colormaps)
# myimg.set_cmap('jet')
# myimg.set_cmap('RdBu_r') # colortable(70,/reverse) in IDL
# myimg.set_cmap('seismic')
# myimg.set_cmap('bwr')
