def onclick(event):
# Check if user clicked inside the plot
if event.xdata is None:
return
# Find closest data point, but stretch axes so
# real and imaginary components are weighted equally
dist = ((eigs_r - event.xdata)/range_r)**2 + ((eigs_i - event.ydata)/range_i)**2
ind = argmin(dist)
# Update the highlight plot
overplot.set_data([eigs_r[ind]], [eigs_i[ind]])
print("Eigenvalue number: %d (%e,%e)" % (ind, eigs_r[ind], eigs_i[ind]))
if data is not None:
# Draw the vtk file
# Set the variables up
var_r = data[2*ind,:]
var_i = data[2*ind+1,:]
nx,ny,nz = visual.dimd(name)
# Interpolate the variables
var_r2,ny3 = visual.zshift_interp3d(nx,ny,nz,zshift,z_tol,var_r)
var_i2,ny3 = visual.zshift_interp3d(nx,ny,nz,zshift,z_tol,var_i)
#c reate the vtk variables
vrbl_r = visual.vtk_var(var_r2,nx,ny2,nz)
vrbl_i = visual.vtk_var(var_i2,nx,ny2,nz)
#W rite the vtk file
vtk_path = visual.write_vtk_2(name,pts,vrbl_r,vrbl_i,ind)
print "Eigenvalue %d written to vtk" % ind
fig.canvas.draw()
def cylinder(name, time, step = 0.5, path = None):
#Get the working dir
if path == None:
work_dir = os.getcwd()
if path != None:
work_dir = os.chdir(path)
work_dir = os.getcwd()
# Prompt for grid file name
grid_file = visual.get("BOUT.inp","grid")
# grid_file = str(raw_input('Enter the filename of the gridfile: '))
if os.path.exists(work_dir + '/' + grid_file + '.nc'):
grid_path = work_dir + '/' + grid_file + '.nc'
if os.path.exists(work_dir + '/' + grid_file + '.grd.nc'):
grid_path = work_dir + '/' + grid_file + '.grd.nc'
# Find dimensions of data
max_t, var_0, nx, ny, nz = visual.dim_all(name)
# Import coordinates from gridfile
r = visual.nc_var(grid_path,'Rxy') # toroidal coordinates
z = visual.nc_var(grid_path,'Zxy') # toroidal coordinates
# pts = visual.cylinder(r, z, nx, ny, nz) # vtk grid points
#Interpolate setup
#Get number of new points
ny_new = len(np.arange(0,(ny-1),step))
#Define empty array with increased number of y values
var_new = np.empty((nx,ny_new,nz),dtype=float)
pts = visual.cylinder(r, z, nx, ny_new, nz) # vtk grid points
#Set time from input
t = time
# Set t to max_t, if user desires entire dataset
if t == -1:
t = max_t
#If t is outside time dim of data set to max_t
if t >= max_t:
t = max_t
### Make dir for storing vtk files and image files
#Check if dir for storing vtk files exsists if not make that dir
if not os.path.exists("batch"):
os.makedirs("batch")
#Make dir for storing images
if not os.path.exists("images"):
os.makedirs("images")
#Initial max and min values
var_x, var_y, var_z = var_0[:,0,0], var_0[0,:,0], var_0[0,0,:]
max_x, max_y, max_z = np.amax(var_x), np.amax(var_y), np.amax(var_z)
min_x, min_y, min_z = np.amin(var_x), np.amin(var_y),np.amin(var_z)
max = np.amax((max_x, max_y, max_z))
min = np.amin((min_x, min_y, min_z))
q = 0
#For the entire t range import the spacial values, find min max values, interpolate y, coordinate transform, write to vtk
for q in range(t):
var = visual.var3d(name,q) # collect variable
#Find the min and max values
var_x, var_y, var_z = var[:,0,0], var[0,:,0], var[0,0,:]
max_x, max_y, max_z = np.amax(var_x), np.amax(var_y), np.amax(var_z)
min_x, min_y, min_z = np.amin(var_x), np.amin(var_y), np.amin(var_z)
max_i = np.amax(np.array((max_x,max_y,max_z)))
min_i = np.amin(np.array((min_x,min_y,min_z)))
if max_i >= max:
max = max_i
if min_i <= min:
min = min_i
#Interpolate section for all y values
for i in range(nx):
for k in range(nz):
var_y = var[i,:,k]
y = np.arange(0,ny) # Arrange y values in array
f = interpolate.interp1d(y,var_y) # Interpolate the data
y_new = np.arange(0,(ny-1),step) # Arrange new y values
var_y_new = f(y_new) # interpolate y values
var_new[i,:,k] = var_y_new # Store values in new variable
#Convert coordinate section
# vrbl = visual.vtk_var(var, nx, ny, nz)
vrbl = visual.vtk_var(var_new,nx,ny_new,nz) # vtk variable
vtk_path = visual.write_vtk(name,pts,vrbl,q,nx,ny,nz) # write vtk file
print "At t = %d, %d Steps remaining" % (q,t-(q+1)) # Progress indicator
#Write the Max and min values to file
mm_array = np.array((max,min))
np.savetxt('max_min_' + name + '.txt',mm_array)
return
def elm(name ,time ,zShf_int_p = 0.25, path = None):
#Add error for zShf_int_p > 1
#Get the working dir
if path == None:
work_dir = os.getcwd()
if path != None:
work_dir = os.chdir(path)
work_dir = os.getcwd()
grid_file = visual.get("BOUT.inp","grid")
# grid_file = str(raw_input('Enter the filename of the gridfile: '))
grid_dir = work_dir + '/' + grid_file + '.nc'
# Get the dimensions and initial value of the variable data.
max_t, var_0, nx, ny, nz = visual.dim_all(name)
#ELM
#Import r,z and zshift from grid file
r = visual.nc_var(grid_dir,'Rxy') # ELM Coordinates
z = visual.nc_var(grid_dir,'Zxy') # ELM Coordinates
zshift = visual.nc_var(grid_dir,'zShift') #ELM Coordinates
max_z,min_z = visual.z_shift_mm(nx,ny,zshift) #Find the max and minimum zshift values
z_tol = min_z + (max_z * zShf_int_p) # Set tolerance value ##CHANGE TO IMPORT PERCENT !!##
#Interpolate the Rxy and Zxy values
r2,ny2 = visual.zshift_interp2d(nx,ny,zshift,z_tol,r)
z2,ny2 = visual.zshift_interp2d(nx,ny,zshift,z_tol,z)
zshift2,ny2 = visual.zshift_interp2d(nx,ny,zshift,z_tol,zshift)
#Create points for ELM
pts2 = visual.elm(r2,z2,zshift2,nx,ny2,nz)
## Set time
t = time
# Set t to max_t, if user desires entire dataset
if t == -1:
t = max_t
#If t is greater than number of slices then set to max_t
if t >= max_t:
t = max_t
### Make dir for storing vtk files and image files
#Check if dir for storing vtk files exsists if not make that dir
if not os.path.exists("batch"):
os.makedirs("batch")
#Make dir for storing images
if not os.path.exists("images"):
os.makedirs("images")
#Initial max and min values
var_x, var_y, var_z = var_0[:,0,0], var_0[0,:,0], var_0[0,0,:]
max_x, max_y, max_z = np.amax(var_x), np.amax(var_y), np.amax(var_z)
min_x, min_y, min_z = np.amin(var_x), np.amin(var_y),np.amin(var_z)
max = np.amax((max_x, max_y, max_z))
min = np.amin((min_x, min_y, min_z))
#If the variable is pressure, import and add the P0 variable to this
if name == 'P':
p0 = visual.collect("P0") #Import P0
add_p = True
#For the entire t range import the spacial values, find min max values, interpolate y, coordinate transform, write to vtk
for q in range(t):
var = visual.var3d(name,q) # collect variable
#Find the min and max values
var_x, var_y, var_z = var[:,0,0], var[0,:,0], var[0,0,:]
max_x, max_y, max_z = np.amax(var_x), np.amax(var_y), np.amax(var_z)
min_x, min_y, min_z = np.amin(var_x), np.amin(var_y), np.amin(var_z)
max_i = np.amax(np.array((max_x,max_y,max_z)))
min_i = np.amin(np.array((min_x,min_y,min_z)))
if max_i >= max:
max = max_i
if min_i <= min:
min = min_i
#Adding p0
if add_p == True:#Adding P0
for i in range (nx): # X value
for j in range(ny): # Y Value
var[i,j,:] = var[i,j,:] + p0[i,j]
var2,ny3 = visual.zshift_interp3d(nx,ny,nz,zshift,z_tol,var)
#Convert coordinate section
vrbl = visual.vtk_var(var2,nx,ny2,nz) #vtk variable
# vrbl = visual.vtk_var(var,nx,ny,nz) # vtk variable
vtk_path = visual.write_vtk(name,pts2,vrbl,q,nx,ny2,nz) # write vtk file
print "At t = %d, %d Steps remaining" % (q,t-(q+1)) # Progress indicator
#Write the Max and min values to file
mm_array = np.array((max,min))
np.savetxt('max_min_' + name + '.txt',mm_array)
return