Merge branch 'development' of magit1.mpie.de:damask/DAMASK into development
This commit is contained in:
Philip Eisenlohr
commit
61777647df
|
|
@ -517,21 +517,25 @@ class ASCIItable():
|
|||
|
||||
# ------------------------------------------------------------------
|
||||
def microstructure_read(self,
|
||||
grid):
|
||||
grid,
|
||||
type = 'i'):
|
||||
"""read microstructure data (from .geom format)"""
|
||||
N = grid.prod() # expected number of microstructure indices in data
|
||||
microstructure = np.zeros(N,'i') # initialize as flat array
|
||||
def datatype(item):
|
||||
return int(item) if type.lower() == 'i' else float(item)
|
||||
|
||||
N = grid.prod() # expected number of microstructure indices in data
|
||||
microstructure = np.zeros(N,type) # initialize as flat array
|
||||
|
||||
i = 0
|
||||
while i < N and self.data_read():
|
||||
items = self.data
|
||||
if len(items) > 2:
|
||||
if items[1].lower() == 'of': items = [int(items[2])]*int(items[0])
|
||||
elif items[1].lower() == 'to': items = range(int(items[0]),1+int(items[2]))
|
||||
else: items = map(int,items)
|
||||
else: items = map(int,items)
|
||||
if items[1].lower() == 'of': items = np.ones(datatype(items[0]))*datatype(items[2])
|
||||
elif items[1].lower() == 'to': items = np.arange(datatype(items[0]),1+datatype(items[2]))
|
||||
else: items = map(datatype,items)
|
||||
else: items = map(datatype,items)
|
||||
|
||||
s = min(len(items), N-i) # prevent overflow of microstructure array
|
||||
s = min(len(items), N-i) # prevent overflow of microstructure array
|
||||
microstructure[i:i+s] = items[:s]
|
||||
i += s
|
||||
|
||||
|
|
|
|||
|
|
@ -10,40 +10,35 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
|||
scriptID = ' '.join([scriptName,damask.version])
|
||||
|
||||
def curlFFT(geomdim,field):
|
||||
N = grid.prod() # field size
|
||||
n = np.array(np.shape(field)[3:]).prod() # data size
|
||||
grid = np.array(np.shape(field)[2::-1])
|
||||
N = grid.prod() # field size
|
||||
n = np.array(np.shape(field)[3:]).prod() # data size
|
||||
|
||||
if n == 3:
|
||||
dataType = 'vector'
|
||||
elif n == 9:
|
||||
dataType = 'tensor'
|
||||
if n == 3: dataType = 'vector'
|
||||
elif n == 9: dataType = 'tensor'
|
||||
|
||||
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
|
||||
curl_fourier = np.zeros(field_fourier.shape,'c16')
|
||||
|
||||
# differentiation in Fourier space
|
||||
k_s = np.zeros([3],'i')
|
||||
TWOPIIMG = (0.0+2.0j*math.pi)
|
||||
TWOPIIMG = 2.0j*math.pi
|
||||
for i in xrange(grid[2]):
|
||||
k_s[0] = i
|
||||
if(grid[2]%2==0 and i == grid[2]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[0]=0
|
||||
elif (i > grid[2]//2):
|
||||
k_s[0] = k_s[0] - grid[2]
|
||||
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif i > grid[2]//2: k_s[0] -= grid[2]
|
||||
|
||||
for j in xrange(grid[1]):
|
||||
k_s[1] = j
|
||||
if(grid[1]%2==0 and j == grid[1]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[1]=0
|
||||
elif (j > grid[1]//2):
|
||||
k_s[1] = k_s[1] - grid[1]
|
||||
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif j > grid[1]//2: k_s[1] -= grid[1]
|
||||
|
||||
for k in xrange(grid[0]//2+1):
|
||||
k_s[2] = k
|
||||
if(grid[0]%2==0 and k == grid[0]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[2]=0
|
||||
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
|
||||
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order
|
||||
|
||||
xi = np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
|
||||
if dataType == 'tensor':
|
||||
for l in xrange(3):
|
||||
curl_fourier[i,j,k,0,l] = ( field_fourier[i,j,k,l,2]*xi[1]\
|
||||
|
|
@ -100,10 +95,8 @@ if options.vector is None and options.tensor is None:
|
|||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,buffered = False)
|
||||
except:
|
||||
continue
|
||||
try: table = damask.ASCIItable(name = name,buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
|
@ -161,9 +154,10 @@ for name in filenames:
|
|||
stack = [table.data]
|
||||
for type, data in items.iteritems():
|
||||
for i,label in enumerate(data['active']):
|
||||
stack.append(curlFFT(size[::-1], # we need to reverse order here, because x
|
||||
table.data[:,data['column'][i]:data['column'][i]+data['dim']]. # is fastest,ie rightmost, but leftmost in
|
||||
reshape([grid[2],grid[1],grid[0]]+data['shape']))) # our x,y,z notation
|
||||
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
|
||||
stack.append(curlFFT(size[::-1],
|
||||
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
|
||||
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
|
||||
|
||||
# ------------------------------------------ output result -----------------------------------------
|
||||
|
||||
|
|
|
|||
|
|
@ -10,39 +10,35 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
|||
scriptID = ' '.join([scriptName,damask.version])
|
||||
|
||||
def divFFT(geomdim,field):
|
||||
N = grid.prod() # field size
|
||||
n = np.array(np.shape(field)[3:]).prod() # data size
|
||||
grid = np.array(np.shape(field)[2::-1])
|
||||
N = grid.prod() # field size
|
||||
n = np.array(np.shape(field)[3:]).prod() # data size
|
||||
|
||||
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
|
||||
div_fourier = np.zeros(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
|
||||
div_fourier = np.zeros(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
|
||||
|
||||
# differentiation in Fourier space
|
||||
k_s=np.zeros([3],'i')
|
||||
TWOPIIMG = (0.0+2.0j*math.pi)
|
||||
TWOPIIMG = 2.0j*math.pi
|
||||
for i in xrange(grid[2]):
|
||||
k_s[0] = i
|
||||
if(grid[2]%2==0 and i == grid[2]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[0]=0
|
||||
elif (i > grid[2]//2):
|
||||
k_s[0] = k_s[0] - grid[2]
|
||||
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif i > grid[2]//2: k_s[0] -= grid[2]
|
||||
|
||||
for j in xrange(grid[1]):
|
||||
k_s[1] = j
|
||||
if(grid[1]%2==0 and j == grid[1]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[1]=0
|
||||
elif (j > grid[1]//2):
|
||||
k_s[1] = k_s[1] - grid[1]
|
||||
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif j > grid[1]//2: k_s[1] -= grid[1]
|
||||
|
||||
for k in xrange(grid[0]//2+1):
|
||||
k_s[2] = k
|
||||
if(grid[0]%2==0 and k == grid[0]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
k_s[2]=0
|
||||
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
|
||||
xi=np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
|
||||
if n == 9: # tensor, 3x3 -> 3
|
||||
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order
|
||||
if n == 9: # tensor, 3x3 -> 3
|
||||
for l in xrange(3):
|
||||
div_fourier[i,j,k,l] = sum(field_fourier[i,j,k,l,0:3]*xi) *TWOPIIMG
|
||||
elif n == 3: # vector, 3 -> 1
|
||||
elif n == 3: # vector, 3 -> 1
|
||||
div_fourier[i,j,k] = sum(field_fourier[i,j,k,0:3]*xi) *TWOPIIMG
|
||||
|
||||
return np.fft.fftpack.irfftn(div_fourier,axes=(0,1,2)).reshape([N,n/3])
|
||||
|
|
@ -80,15 +76,13 @@ parser.set_defaults(coords = 'ipinitialcoord',
|
|||
if options.vector is None and options.tensor is None:
|
||||
parser.error('no data column specified.')
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
# --- loop over input files ------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,buffered = False)
|
||||
except:
|
||||
continue
|
||||
try: table = damask.ASCIItable(name = name,buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
|
@ -140,16 +134,17 @@ for name in filenames:
|
|||
maxcorner = np.array(map(max,coords))
|
||||
grid = np.array(map(len,coords),'i')
|
||||
size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
|
||||
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 set to smallest among other spacings
|
||||
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
|
||||
|
||||
# ------------------------------------------ process value field -----------------------------------
|
||||
|
||||
stack = [table.data]
|
||||
for type, data in items.iteritems():
|
||||
for i,label in enumerate(data['active']):
|
||||
stack.append(divFFT(size[::-1], # we need to reverse order here, because x
|
||||
table.data[:,data['column'][i]:data['column'][i]+data['dim']]. # is fastest,ie rightmost, but leftmost in
|
||||
reshape([grid[2],grid[1],grid[0]]+data['shape']))) # our x,y,z notation
|
||||
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
|
||||
stack.append(divFFT(size[::-1],
|
||||
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
|
||||
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
|
||||
|
||||
# ------------------------------------------ output result -----------------------------------------
|
||||
|
||||
|
|
@ -158,4 +153,4 @@ for name in filenames:
|
|||
|
||||
# ------------------------------------------ output finalization -----------------------------------
|
||||
|
||||
table.close() # close input ASCII table (works for stdin)
|
||||
table.close() # close input ASCII table (works for stdin)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,158 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,sys,math
|
||||
import numpy as np
|
||||
from optparse import OptionParser
|
||||
import damask
|
||||
|
||||
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
||||
scriptID = ' '.join([scriptName,damask.version])
|
||||
|
||||
def gradFFT(geomdim,field):
|
||||
grid = np.array(np.shape(field)[2::-1])
|
||||
N = grid.prod() # field size
|
||||
n = np.array(np.shape(field)[3:]).prod() # data size
|
||||
if n == 3: dataType = 'vector'
|
||||
elif n == 1: dataType = 'scalar'
|
||||
|
||||
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
|
||||
grad_fourier = np.zeros(field_fourier.shape+(3,),'c16')
|
||||
|
||||
# differentiation in Fourier space
|
||||
k_s = np.zeros([3],'i')
|
||||
TWOPIIMG = 2.0j*math.pi
|
||||
for i in xrange(grid[2]):
|
||||
k_s[0] = i
|
||||
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif i > grid[2]//2: k_s[0] -= grid[2]
|
||||
|
||||
for j in xrange(grid[1]):
|
||||
k_s[1] = j
|
||||
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
elif j > grid[1]//2: k_s[1] -= grid[1]
|
||||
|
||||
for k in xrange(grid[0]//2+1):
|
||||
k_s[2] = k
|
||||
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
|
||||
|
||||
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field order
|
||||
|
||||
grad_fourier[i,j,k,0,:] = field_fourier[i,j,k,0]*xi *TWOPIIMG # vector field from scalar data
|
||||
|
||||
if dataType == 'vector':
|
||||
grad_fourier[i,j,k,1,:] = field_fourier[i,j,k,1]*xi *TWOPIIMG # tensor field from vector data
|
||||
grad_fourier[i,j,k,2,:] = field_fourier[i,j,k,2]*xi *TWOPIIMG
|
||||
|
||||
return np.fft.fftpack.irfftn(grad_fourier,axes=(0,1,2)).reshape([N,3*n])
|
||||
|
||||
|
||||
# --------------------------------------------------------------------
|
||||
# MAIN
|
||||
# --------------------------------------------------------------------
|
||||
|
||||
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
|
||||
Add column(s) containing gradient of requested column(s).
|
||||
Operates on periodic ordered three-dimensional data sets.
|
||||
Deals with both vector- and scalar fields.
|
||||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-c','--coordinates',
|
||||
dest = 'coords',
|
||||
type = 'string', metavar='string',
|
||||
help = 'column heading for coordinates [%default]')
|
||||
parser.add_option('-v','--vector',
|
||||
dest = 'vector',
|
||||
action = 'extend', metavar = '<string LIST>',
|
||||
help = 'heading of columns containing vector field values')
|
||||
parser.add_option('-s','--scalar',
|
||||
dest = 'scalar',
|
||||
action = 'extend', metavar = '<string LIST>',
|
||||
help = 'heading of columns containing scalar field values')
|
||||
|
||||
parser.set_defaults(coords = 'ipinitialcoord',
|
||||
)
|
||||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
if options.vector is None and options.scalar is None:
|
||||
parser.error('no data column specified.')
|
||||
|
||||
# --- loop over input files ------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try: table = damask.ASCIItable(name = name,buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
||||
table.head_read()
|
||||
|
||||
# ------------------------------------------ sanity checks ----------------------------------------
|
||||
|
||||
items = {
|
||||
'scalar': {'dim': 1, 'shape': [1], 'labels':options.scalar, 'active':[], 'column': []},
|
||||
'vector': {'dim': 3, 'shape': [3], 'labels':options.vector, 'active':[], 'column': []},
|
||||
}
|
||||
errors = []
|
||||
remarks = []
|
||||
column = {}
|
||||
|
||||
if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
|
||||
else: colCoord = table.label_index(options.coords)
|
||||
|
||||
for type, data in items.iteritems():
|
||||
for what in (data['labels'] if data['labels'] is not None else []):
|
||||
dim = table.label_dimension(what)
|
||||
if dim != data['dim']: remarks.append('column {} is not a {}.'.format(what,type))
|
||||
else:
|
||||
items[type]['active'].append(what)
|
||||
items[type]['column'].append(table.label_index(what))
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
# ------------------------------------------ assemble header --------------------------------------
|
||||
|
||||
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
||||
for type, data in items.iteritems():
|
||||
for label in data['active']:
|
||||
table.labels_append(['{}_gradFFT({})'.format(i+1,label) for i in xrange(3 * data['dim'])]) # extend ASCII header with new labels
|
||||
table.head_write()
|
||||
|
||||
# --------------- figure out size and grid ---------------------------------------------------------
|
||||
|
||||
table.data_readArray()
|
||||
|
||||
coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)]
|
||||
mincorner = np.array(map(min,coords))
|
||||
maxcorner = np.array(map(max,coords))
|
||||
grid = np.array(map(len,coords),'i')
|
||||
size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
|
||||
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1]))
|
||||
|
||||
# ------------------------------------------ process value field -----------------------------------
|
||||
|
||||
stack = [table.data]
|
||||
for type, data in items.iteritems():
|
||||
for i,label in enumerate(data['active']):
|
||||
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
|
||||
stack.append(gradFFT(size[::-1],
|
||||
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
|
||||
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
|
||||
|
||||
# ------------------------------------------ output result -----------------------------------------
|
||||
|
||||
if len(stack) > 1: table.data = np.hstack(tuple(stack))
|
||||
table.data_writeArray('%.12g')
|
||||
|
||||
# ------------------------------------------ output finalization -----------------------------------
|
||||
|
||||
table.close() # close input ASCII table (works for stdin)
|
||||
|
|
@ -28,24 +28,32 @@ parser.add_option('-o', '--offset',
|
|||
help = 'a,b,c offset from old to new origin of grid [%default]')
|
||||
parser.add_option('-f', '--fill',
|
||||
dest = 'fill',
|
||||
type = 'int', metavar = 'int',
|
||||
type = 'float', metavar = 'float',
|
||||
help = '(background) canvas grain index. "0" selects maximum microstructure index + 1 [%default]')
|
||||
parser.add_option('--float',
|
||||
dest = 'real',
|
||||
action = 'store_true',
|
||||
help = 'input data is float [%default]')
|
||||
|
||||
parser.set_defaults(grid = ['0','0','0'],
|
||||
offset = (0,0,0),
|
||||
fill = 0,
|
||||
real = False,
|
||||
)
|
||||
|
||||
(options, filenames) = parser.parse_args()
|
||||
|
||||
datatype = 'f' if options.real else 'i'
|
||||
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
buffered = False, labeled = False)
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False,
|
||||
labeled = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
|
|
@ -71,7 +79,7 @@ for name in filenames:
|
|||
|
||||
# --- read data ------------------------------------------------------------------------------------
|
||||
|
||||
microstructure = table.microstructure_read(info['grid']).reshape(info['grid'],order='F') # read microstructure
|
||||
microstructure = table.microstructure_read(info['grid'],datatype).reshape(info['grid'],order='F') # read microstructure
|
||||
|
||||
# --- do work ------------------------------------------------------------------------------------
|
||||
|
||||
|
|
@ -85,8 +93,8 @@ for name in filenames:
|
|||
else int(n) for o,n in zip(info['grid'],options.grid)],'i')
|
||||
newInfo['grid'] = np.where(newInfo['grid'] > 0, newInfo['grid'],info['grid'])
|
||||
|
||||
microstructure_cropped = np.zeros(newInfo['grid'],'i')
|
||||
microstructure_cropped.fill(options.fill if options.fill > 0 else microstructure.max()+1)
|
||||
microstructure_cropped = np.zeros(newInfo['grid'],datatype)
|
||||
microstructure_cropped.fill(options.fill if options.real or options.fill > 0 else microstructure.max()+1)
|
||||
xindex = list(set(xrange(options.offset[0],options.offset[0]+newInfo['grid'][0])) & \
|
||||
set(xrange(info['grid'][0])))
|
||||
yindex = list(set(xrange(options.offset[1],options.offset[1]+newInfo['grid'][1])) & \
|
||||
|
|
@ -152,9 +160,9 @@ for name in filenames:
|
|||
|
||||
# --- write microstructure information ------------------------------------------------------------
|
||||
|
||||
formatwidth = int(math.floor(math.log10(microstructure_cropped.max())+1))
|
||||
format = '%g' if options.real else '%{}i'.format(int(math.floor(math.log10(microstructure_cropped.max())+1)))
|
||||
table.data = microstructure_cropped.reshape((newInfo['grid'][0],newInfo['grid'][1]*newInfo['grid'][2]),order='F').transpose()
|
||||
table.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
|
||||
table.data_writeArray(format,delimiter=' ')
|
||||
|
||||
# --- output finalization --------------------------------------------------------------------------
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue