Python save_general_mesh 예제들

예제 #1

파일: meso_touch.py 프로젝트: jgd10/Python_Scripts

zcr     *= GRIDSPC
radii   *= GRIDSPC
MAT      = pss.mat_assignment(mats,xcr,ycr)
DMY      = np.zeros_like(xcoords)


A,B = pss.part_distance(xcr,ycr,radii,MAT,False)
print "The Contacts Measure, A = {}".format(A)
print "Avg Contacts Between the Same Materials, B = {}".format(B)
print 'Total contacts between same materials = {}, Total particles = {}'.format(B*J,J)
ALL = np.column_stack((MAT,xcr,ycr,radii))

pss.populate_materials(I_shape,XINT,YINT,MAT,J,TRACERS=True,ON=J_shape)      # Now populate the materials meshes (NB these are different to the 'mesh' and are
pss.save_spherical_parts(xcr,ycr,radii,MAT,A)
print 'save to meso_A-{:3.4f}.iSALE'.format(A)
pss.save_general_mesh(tracers=True)
A2, contact_matrix = pss.discrete_contacts_number(I_shape,XINT,YINT,J,J_shape)
print '\n'
print "A and A2 are:", A, A2
print '\n'


timestr = time.strftime('%d-%m-%Y_%H-%M-%S')
#np.savetxt('{}cppr_{}vfrlim_A{:1.3f}_{}.iSALE'.format(cppr,vfraclimit,A,timestr),ALL)
placed_part_area = np.array(placed_part_area)
print "total particles placed: {}".format(J)
vol_frac_calc = np.sum(placed_part_area)/(pss.meshx*pss.meshy)

if abs(vol_frac_calc - pss.vol_frac) <= 0.02:
    print "GREAT SUCCESS! Volume Fraction = {:3.3f}%".format(vol_frac_calc*100.)
else:

예제 #2

파일: wave_partial_geom.py 프로젝트: jgd10/Python_Scripts

pss.fill_rectangle(Sip_L1, Sip_T1, Sip_L2, Sip_T2, mats[2])


"""
PMMA_T1 = 0.e-3
PMMA_T2 = 10.e-3
PMMA_L1 = 8.6e-3
PMMA_L2 = 10.e-3
pss.fill_rectangle(PMMA_L1,PMMA_T1,PMMA_L2,PMMA_T2,mats[3])
"""
# pss.mesh_Shps[0,:,:],part_area = pss.gen_circle(r)

i = np.where(abs(pss.yh - 12.7e-3) < pss.GS / 2.0)
j = np.where(abs(pss.xh - 4.51e-3) < pss.GS / 2.0)
I, J, M = i[0], j[0], mats[4]
# pss.place_shape(pss.mesh_Shps[0,:,:],J,I,M)
plt.figure()
# plt.imshow(pss.mesh,interpolation='nearest',cmap='binary')
view_mesh = np.zeros_like((pss.materials[0, :, :]))
for item in mats:
    view_mesh += pss.materials[item - 1, :, :] * item
plt.imshow(view_mesh, interpolation="nearest", cmap="viridis")
# plt.imshow(pss.materials[0,:,:],interpolation='nearest',cmap='copper_r')
# plt.imshow(pss.materials[1,:,:],interpolation='nearest',cmap='BuPu')
# plt.imshow(pss.materials[2,:,:],interpolation='nearest',cmap='viridis')
# plt.imshow(pss.materials[3,:,:],interpolation='nearest',cmap='binary')
# plt.imshow(pss.materials[4,:,:],interpolation='nearest',cmap='Reds_r')
plt.show()

pss.save_general_mesh(mixed=True)

예제 #3

MAT = pss.mat_assignment(mats, xcr, ycr)
DMY = np.zeros_like(xcoords)

A, B = pss.part_distance(xcr, ycr, radii, MAT, False)
print "The Contacts Measure, A = {}".format(A)
print "Avg Contacts Between the Same Materials, B = {}".format(B)
print 'Total contacts between same materials = {}, Total particles = {}'.format(
    B * J, J)
ALL = np.column_stack((MAT, xcr, ycr, radii))

pss.populate_materials(
    I_shape, XINT, YINT, MAT, J, TRACERS=True, ON=J_shape
)  # Now populate the materials meshes (NB these are different to the 'mesh' and are
#pss.save_spherical_parts(xcr,ycr,radii,MAT,A)
print 'save to meso_A-{:3.4f}.iSALE'.format(A)
pss.save_general_mesh(tracers=True)
A2, contact_matrix = pss.discrete_contacts_number(I_shape, XINT, YINT, J,
                                                  J_shape)
print '\n'
print "A and A2 are:", A, A2
print '\n'

timestr = time.strftime('%d-%m-%Y_%H-%M-%S')
#np.savetxt('{}cppr_{}vfrlim_A{:1.3f}_{}.iSALE'.format(cppr,vfraclimit,A,timestr),ALL)
placed_part_area = np.array(placed_part_area)
print "total particles placed: {}".format(J)
vol_frac_calc = np.sum(placed_part_area) / (pss.meshx * pss.meshy)

if abs(vol_frac_calc - pss.vol_frac) <= 0.02:
    print "GREAT SUCCESS! Volume Fraction = {:3.3f}%".format(vol_frac_calc *
                                                             100.)

예제 #4

Sip_L2 = 8.6e-3
pss.fill_rectangle(Sip_L1,Sip_T1,Sip_L2,Sip_T2,mats[2])


PMMA_T1 = 0.e-3
PMMA_T2 = 10.e-3
PMMA_L1 = 8.6e-3
PMMA_L2 = 10.e-3
pss.fill_rectangle(PMMA_L1,PMMA_T1,PMMA_L2,PMMA_T2,mats[3])

#pss.mesh_Shps[0,:,:],part_area = pss.gen_circle(r)

i = np.where(abs(pss.yh-12.7e-3)<pss.GS/2.)
j = np.where(abs(pss.xh-4.51e-3)<pss.GS/2.)
I, J, M = i[0],j[0],mats[4]
#pss.place_shape(pss.mesh_Shps[0,:,:],J,I,M)
pss.save_general_mesh(mixed=True)
plt.figure()
#plt.imshow(pss.mesh,interpolation='nearest',cmap='binary')
view_mesh = np.zeros_like((pss.materials[0,:,:]))
for item in mats:
    view_mesh += pss.materials[item-1,:,:]*item
plt.imshow(view_mesh,interpolation='nearest',cmap = 'Reds')
#plt.imshow(pss.materials[0,:,:],interpolation='nearest',cmap='copper_r')
#plt.imshow(pss.materials[1,:,:],interpolation='nearest',cmap='BuPu')
#plt.imshow(pss.materials[2,:,:],interpolation='nearest',cmap='viridis')
#plt.imshow(pss.materials[3,:,:],interpolation='nearest',cmap='binary')
#plt.imshow(pss.materials[4,:,:],interpolation='nearest',cmap='Reds_r')
plt.show()

예제 #5

파일: meso_chond-matrix_EXAMPLE.py 프로젝트: jgd10/Python_Scripts

    pass                
I_shape = np.array(I_)                                              # Convert the lists of index, shape number, and coordinates to arrays
J_shape = np.array(J_)

xcSI = np.array(xc)
ycSI = np.array(yc)
xcSI*= GRIDSPC                                                      # Turn the coordinates into physical units
ycSI*= GRIDSPC
MAT  = pss.mat_assignment(pss.mats[1:],xcSI,ycSI)                   # Assign materials to the particles. This returns an array that is the same shape as xc, 
                                                                    # and contains the optimum corresponding material number for each particle
pss.populate_materials(I_,xc,yc,MAT,J)                              # Now populate the materials meshes (NB these are different to the 'mesh' and are
                                                                    # the ones used in the actual iSALE input file)

pss.fill_rectangle(0,0,pss.meshx*GRIDSPC,pss.meshy*GRIDSPC,pss.mats[0])
                                                                    # pySALESetup prioritises material placed sooner. So later things will NOT overwrite previous ones
pss.save_general_mesh()                                             # Save the mesh as meso_m.iSALE (default)

plt.figure()                                                        # plot the resulting mesh. Skip this bit if you do not need to.
for KK in range(pss.Ms):
    matter = np.copy(pss.materials[KK,:,:])*(KK+1)
    matter = np.ma.masked_where(matter==0.,matter)
    plt.imshow(matter, cmap='viridis',vmin=0,vmax=pss.Ms,interpolation='nearest')

matter = np.copy(pss.materials[pss.Ms-1,:,:])*(pss.Ms)
matter = np.ma.masked_where(matter==0.,matter)


#plt.axis('equal')
plt.xlim(0,pss.meshx)
plt.ylim(0,pss.meshy)
plt.show()

예제 #6

xcSI = np.array(xc)
ycSI = np.array(yc)
xcSI *= GRIDSPC  # Turn the coordinates into physical units
ycSI *= GRIDSPC
MAT = pss.mat_assignment(
    pss.mats[1:], xcSI, ycSI
)  # Assign materials to the particles. This returns an array that is the same shape as xc,
# and contains the optimum corresponding material number for each particle
pss.populate_materials(
    I_, xc, yc, MAT, J
)  # Now populate the materials meshes (NB these are different to the 'mesh' and are
# the ones used in the actual iSALE input file)

pss.fill_rectangle(0, 0, pss.meshx * GRIDSPC, pss.meshy * GRIDSPC, pss.mats[0])
# pySALESetup prioritises material placed sooner. So later things will NOT overwrite previous ones
pss.save_general_mesh()  # Save the mesh as meso_m.iSALE (default)

plt.figure()  # plot the resulting mesh. Skip this bit if you do not need to.
for KK in range(pss.Ms):
    matter = np.copy(pss.materials[KK, :, :]) * (KK + 1)
    matter = np.ma.masked_where(matter == 0., matter)
    plt.imshow(matter,
               cmap='viridis',
               vmin=0,
               vmax=pss.Ms,
               interpolation='nearest')

matter = np.copy(pss.materials[pss.Ms - 1, :, :]) * (pss.Ms)
matter = np.ma.masked_where(matter == 0., matter)

#plt.axis('equal')

예제 #7

파일: triangular_block.py 프로젝트: jgd10/Python_Scripts

Y  = np.append(Y1,Y2)

Y += 37.5

assert np.size(X) == np.size(Y)

p = 1.
N = np.size(X)
for i in range(N):
	if i%2==0:
		pass
	else:
		Y[i] += p*2.5
		p  *= -1.

X  = np.append(X,(X[-1],X[0])) 
Y  = np.append(Y,([0.,0.])) 
X /= (GRIDSPC/1.e-6)
Y /= (GRIDSPC/1.e-6)

pss.fill_arbitrary_shape_p(Y,X,mats[0])

#pss.fill_plate(0.,300.,mats[1])

pss.save_general_mesh()

fig, ax = plt.subplots()
cax = ax.imshow(pss.mesh,cmap='Greys',interpolation='nearest',vmin=0,vmax=1)
cbar = fig.colorbar(cax, orientation='horizontal')
plt.show()

예제 #8

import numpy as np
import scipy.spatial as scsp
import scipy as sc
import random
import matplotlib.pyplot as plt
import time

T_length = .5e-3
L_length = 1.e-3
GRIDSPC = 2.e-5
T_cells = int(T_length / GRIDSPC)
L_cells = int(L_length / GRIDSPC)  # T - Transverse, L - Longitudinal

pss.generate_mesh(L_cells, T_cells, mat_no=1, GS=GRIDSPC)
pss.mesh_Shps[0, :, :], part_area = pss.gen_circle(r)
mats = pss.mats

l1 = 0.5 * L_length
l2 = 0.9 * L_length
t1 = 0.1 * T_length
t2 = 0.9 * T_length

pss.fill_rectangle(l1, t1, l2, t2, mats[0])

plt.figure()
#plt.imshow(pss.mesh,interpolation='nearest',cmap='binary')
plt.imshow(pss.materials[0, :, :], interpolation='nearest', cmap='binary')
plt.show()

pss.save_general_mesh()

예제 #9

파일: full_setup.py 프로젝트: tmdavison/Python_Scripts

Al4_L1 = 1.3e-3
Al4_L2 = 2.5e-3
pss.fill_rectangle(Al4_L1, Al4_T1, Al4_L2, Al4_T2, mats[1])

Sip_T1 = 7.7e-3
Sip_T2 = 17.7e-3
Sip_L1 = 2.6e-3
Sip_L2 = 8.6e-3
pss.fill_rectangle(Sip_L1, Sip_T1, Sip_L2, Sip_T2, mats[2])

PMMA_T1 = 7.7e-3
PMMA_T2 = 17.7e-3
PMMA_L1 = 8.6e-3
PMMA_L2 = 14.6e-3
pss.fill_rectangle(PMMA_L1, PMMA_T1, PMMA_L2, PMMA_T2, mats[3])

plt.figure()
#plt.imshow(pss.mesh,interpolation='nearest',cmap='binary')
view_mesh = np.zeros_like((pss.materials[0, :, :]))
for item in mats:
    view_mesh += pss.materials[item - 1, :, :] * item
plt.imshow(view_mesh, interpolation='nearest', cmap='Reds')
#plt.imshow(pss.materials[0,:,:],interpolation='nearest',cmap='copper_r')
#plt.imshow(pss.materials[1,:,:],interpolation='nearest',cmap='BuPu')
#plt.imshow(pss.materials[2,:,:],interpolation='nearest',cmap='viridis')
#plt.imshow(pss.materials[3,:,:],interpolation='nearest',cmap='binary')
#plt.imshow(pss.materials[4,:,:],interpolation='nearest',cmap='Reds_r')
plt.show()

pss.save_general_mesh(mixed=False)

예제 #10

파일: meso_small.py 프로젝트: tmdavison/Python_Scripts

dX = 2*cppr*np.sin(ANG)
dY = 2*cppr*np.cos(ANG) 
pss.place_shape(pss.mesh_Shps[0,:,:],16+dY,28+dX,2)
pss.place_shape(pss.mesh_Shps[0,:,:],32+dY,28+dX,3)
pss.place_shape(pss.mesh_Shps[0,:,:],32+dY,28+dX-16,4)

#pss.place_shape(pss.mesh_Shps[0,:,:],50,25,3)
#pss.place_shape(pss.mesh_Shps[0,:,:],50,41,4)
#pss.place_shape(pss.mesh_Shps[0,:,:],50,9,2)






plt.figure()
plt.imshow(pss.materials[0,:,:],interpolation='nearest',cmap='binary')
plt.imshow(pss.materials[1,:,:],interpolation='nearest',cmap='binary',alpha=.5)
plt.imshow(pss.materials[2,:,:],interpolation='nearest',cmap='binary',alpha=.5)
plt.imshow(pss.materials[3,:,:],interpolation='nearest',cmap='binary',alpha=.5)
plt.imshow(pss.materials[4,:,:],interpolation='nearest',cmap='binary',alpha=.5)
plt.show()

#S = float(np.sum(UC)-4*3)#There are 4 particles and 3 cells overlap per particle
#print "Approximate Volume Fraction = {:3.1f}".format(S/float(lx*ly))

pss.save_general_mesh(fname='meso_m_test-{:3.1f}.iSALE'.format(ANGLE),mixed=False)

예제 #11

파일: full_setup.py 프로젝트: jgd10/Python_Scripts

Al4_L2 = 2.5e-3
pss.fill_rectangle(Al4_L1,Al4_T1,Al4_L2,Al4_T2,mats[1])

Sip_T1 = 7.7e-3
Sip_T2 = 17.7e-3
Sip_L1 = 2.6e-3
Sip_L2 = 8.6e-3
pss.fill_rectangle(Sip_L1,Sip_T1,Sip_L2,Sip_T2,mats[2])

PMMA_T1 = 7.7e-3
PMMA_T2 = 17.7e-3
PMMA_L1 = 8.6e-3
PMMA_L2 = 14.6e-3
pss.fill_rectangle(PMMA_L1,PMMA_T1,PMMA_L2,PMMA_T2,mats[3])


plt.figure()
#plt.imshow(pss.mesh,interpolation='nearest',cmap='binary')
view_mesh = np.zeros_like((pss.materials[0,:,:]))
for item in mats:
    view_mesh += pss.materials[item-1,:,:]*item
plt.imshow(view_mesh,interpolation='nearest',cmap = 'Reds')
#plt.imshow(pss.materials[0,:,:],interpolation='nearest',cmap='copper_r')
#plt.imshow(pss.materials[1,:,:],interpolation='nearest',cmap='BuPu')
#plt.imshow(pss.materials[2,:,:],interpolation='nearest',cmap='viridis')
#plt.imshow(pss.materials[3,:,:],interpolation='nearest',cmap='binary')
#plt.imshow(pss.materials[4,:,:],interpolation='nearest',cmap='Reds_r')
plt.show()

pss.save_general_mesh(mixed=False)