adopted new ASCIItable API. some polishing.
This commit is contained in:
Philip Eisenlohr
parent
4ed56a8ba6
commit
a4772343b0
|
|
@ -18,35 +18,56 @@ Produces a binned grid of two columns from an ASCIItable, i.e. a two-dimensional
|
|||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-d','--data', dest='data', nargs=2, type='string', metavar='string string',
|
||||
help='column labels containing x and y ')
|
||||
parser.add_option('-w','--weight', dest='weight', metavar='string', type='string',
|
||||
help='column label containing weight of (x,y) point')
|
||||
parser.add_option('-b','--bins', dest='bins', nargs=2, type='int', metavar='int int',
|
||||
help='number of bins in x and y direction [%default]')
|
||||
parser.add_option('-t','--type', dest='type', nargs=3, metavar='string string string',
|
||||
help='type (linear/log) of x, y, and z axis [%default]')
|
||||
parser.add_option('-x','--xrange', dest='xrange', nargs=2, type='float', metavar='float float',
|
||||
help='min max value in x direction [autodetect]')
|
||||
parser.add_option('-y','--yrange', dest='yrange', nargs=2, type='float', metavar='float float',
|
||||
help='min max value in y direction [autodetect]')
|
||||
parser.add_option('-z','--zrange', dest='zrange', nargs=2, type='float', metavar='float float',
|
||||
help='min max value in z direction [autodetect]')
|
||||
parser.add_option('-i','--invert', dest='invert', action='store_true',
|
||||
help='invert probability density [%default]')
|
||||
parser.add_option('-r','--rownormalize', dest='normRow', action='store_true',
|
||||
help='normalize probability density in each row [%default]')
|
||||
parser.add_option('-c','--colnormalize', dest='normCol', action='store_true',
|
||||
help='normalize probability density in each column [%default]')
|
||||
parser.add_option('-d','--data',
|
||||
dest = 'data',
|
||||
type='string', nargs = 2, metavar = 'string string',
|
||||
help = 'column labels containing x and y ')
|
||||
parser.add_option('-w','--weight',
|
||||
dest = 'weight',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label containing weight of (x,y) point')
|
||||
parser.add_option('-b','--bins',
|
||||
dest = 'bins',
|
||||
type = 'int', nargs = 2, metavar = 'int int',
|
||||
help = 'number of bins in x and y direction [%default]')
|
||||
parser.add_option('-t','--type',
|
||||
dest = 'type',
|
||||
type = 'string', nargs = 3, metavar = 'string string string',
|
||||
help = 'type (linear/log) of x, y, and z axis [%default]')
|
||||
parser.add_option('-x','--xrange',
|
||||
dest = 'xrange',
|
||||
type = 'float', nargs = 2, metavar = 'float float',
|
||||
help = 'min max value in x direction [autodetect]')
|
||||
parser.add_option('-y','--yrange',
|
||||
dest = 'yrange',
|
||||
type = 'float', nargs = 2, metavar = 'float float',
|
||||
help = 'min max value in y direction [autodetect]')
|
||||
parser.add_option('-z','--zrange',
|
||||
dest = 'zrange',
|
||||
type = 'float', nargs = 2, metavar = 'float float',
|
||||
help = 'min max value in z direction [autodetect]')
|
||||
parser.add_option('-i','--invert',
|
||||
dest = 'invert',
|
||||
action = 'store_true',
|
||||
help = 'invert probability density [%default]')
|
||||
parser.add_option('-r','--rownormalize',
|
||||
dest = 'normRow',
|
||||
action = 'store_true',
|
||||
help = 'normalize probability density in each row [%default]')
|
||||
parser.add_option('-c','--colnormalize',
|
||||
dest = 'normCol',
|
||||
action = 'store_true',
|
||||
help = 'normalize probability density in each column [%default]')
|
||||
|
||||
parser.set_defaults(bins = (10,10))
|
||||
parser.set_defaults(type = ('linear','linear','linear'))
|
||||
parser.set_defaults(xrange = (0.0,0.0))
|
||||
parser.set_defaults(yrange = (0.0,0.0))
|
||||
parser.set_defaults(zrange = (0.0,0.0))
|
||||
parser.set_defaults(invert = False)
|
||||
parser.set_defaults(normRow = False)
|
||||
parser.set_defaults(normCol = False)
|
||||
parser.set_defaults(bins = (10,10),
|
||||
type = ('linear','linear','linear'),
|
||||
xrange = (0.0,0.0),
|
||||
yrange = (0.0,0.0),
|
||||
zrange = (0.0,0.0),
|
||||
invert = False,
|
||||
normRow = False,
|
||||
normCol = False,
|
||||
)
|
||||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
|
|
@ -56,37 +77,36 @@ minmax = np.array([np.array(options.xrange),
|
|||
grid = np.zeros(options.bins,'f')
|
||||
result = np.zeros((options.bins[0],options.bins[1],3),'f')
|
||||
|
||||
datainfo = { # list of requested labels per datatype
|
||||
'scalar': {'len':1,
|
||||
'label':[]},
|
||||
}
|
||||
if options.data == None: parser.error('no data columns specified.')
|
||||
|
||||
if options.data != None: datainfo['scalar']['label'] += options.data
|
||||
if options.weight != None: datainfo['scalar']['label'] += [options.weight] # prevent character splitting of single string value
|
||||
labels = options.data
|
||||
|
||||
# --- loop over input files ------------------------------------------------------------------------
|
||||
if options.weight != None: labels += [options.weight] # prevent character splitting of single string value
|
||||
|
||||
if filenames == []:
|
||||
filenames = ['STDIN']
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = ['STDIN']
|
||||
|
||||
for name in filenames:
|
||||
if name == 'STDIN':
|
||||
file = {'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr}
|
||||
file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
|
||||
else:
|
||||
if not os.path.exists(name): continue
|
||||
file = {'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr}
|
||||
file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
|
||||
if not (name == 'STDIN' or os.path.exists(name)): continue
|
||||
table = damask.ASCIItable(name = name,
|
||||
outname = os.path.join(os.path.dirname(name),
|
||||
'binned-%s-%s_'%(options.data[0],options.data[1])+ \
|
||||
('weighted-%s_'%(options.weight) if options.weight != None else '') + \
|
||||
os.path.basename(name))
|
||||
buffered = False)
|
||||
table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name != 'STDIN' else ''))
|
||||
|
||||
table = damask.ASCIItable(file['input'],file['output'],buffered = False) # make unbuffered ASCII_table
|
||||
table.head_read() # read ASCII header info
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
||||
# --- process data ---------------------------------------------------------------------------------
|
||||
table.head_read()
|
||||
|
||||
missing_labels = table.data_readArray(datainfo['scalar']['label'])
|
||||
# ------------------------------------------ sanity checks ----------------------------------------
|
||||
|
||||
missing_labels = table.data_readArray(labels)
|
||||
|
||||
if len(missing_labels) > 0:
|
||||
file['croak'].write('column%s %s not found...\n'%('s' if len(missing_labels) > 1 else '',', '.join(missing_labels)))
|
||||
table.croak('column{} {} not found.'.format('s' if len(missing_labels) > 1 else '',', '.join(missing_labels)))
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
|
|
@ -120,7 +140,7 @@ for name in filenames:
|
|||
minmax[2,0] -= 1.
|
||||
minmax[2,1] += 1.
|
||||
if (minmax[2] == 0.0).all(): # no data in grid?
|
||||
file['croak'].write('no data found on grid...\n')
|
||||
table.croak('no data found on grid...')
|
||||
minmax[2,:] = np.array([0.0,1.0]) # making up arbitrary z minmax
|
||||
if options.type[2].lower() == 'log':
|
||||
grid = np.log(grid)
|
||||
|
|
@ -148,10 +168,7 @@ for name in filenames:
|
|||
|
||||
# --- output result ---------------------------------------------------------------------------------
|
||||
|
||||
prefix = 'binned-%s-%s_'%(options.data[0],options.data[1])+ \
|
||||
('weighted-%s_'%(options.weight) if options.weight != None else '')
|
||||
np.savetxt(file['output'],result.reshape(options.bins[0]*options.bins[1],3))
|
||||
table.output_close() # close output ASCII table
|
||||
if file['name'] != 'STDIN':
|
||||
os.rename(file['name']+'_tmp',\
|
||||
os.path.join(os.path.dirname(file['name']),prefix+os.path.basename(file['name'])))
|
||||
table.data = result.reshape(options.bins[0]*options.bins[1],3)
|
||||
table.data_writeArray()
|
||||
|
||||
table.close()
|
||||
|
|
|
|||
Loading…
Reference in New Issue