class WDumpSegs(WESTTool):
prog = 'w_dumpsegs'
description = '''\
Dump segment data as text. This is very inefficient, so this tool should be used
as a last resort (use hdfview/h5ls to look at data, and access HDF5 directly for
significant analysis tasks).
'''
def __init__(self):
super(WDumpSegs, self).__init__()
self.data_reader = WESTDataReader()
self.n_iter = None
self.output_file = None
self.print_pcoords = False
def add_args(self, parser):
self.data_reader.add_args(parser)
parser.add_argument(
'-p',
'--print-pcoords',
dest='print_pcoords',
action='store_true',
help='print initial and final progress coordinates for each segment'
)
parser.add_argument(
'-i',
'--iteration',
dest='n_iter',
type=int,
help=
'Use data from iteration N_ITER (default: last complete iteration)'
)
parser.add_argument(
'-o',
'--output',
dest='output_file',
help=
'Store output in OUTPUT_FILE (default: write to standard output).')
def process_args(self, args):
self.data_reader.process_args(args)
self.data_reader.open()
self.n_iter = args.n_iter or self.data_reader.current_iteration - 1
self.output_file = open(args.output_file,
'wt') if args.output_file else sys.stdout
self.print_pcoords = args.print_pcoords
def go(self):
segments = self.data_reader.get_segments(self.n_iter)
max_seg_id_len = len(str(max(segment.seg_id for segment in segments)))
max_status_name_len = max(
list(map(len, iter(Segment.status_names.values()))))
max_endpoint_type_len = max(
list(map(len, iter(Segment.endpoint_type_names.values()))))
max_n_parents_len = len(
str(max(len(segment.wtg_parent_ids) for segment in segments)))
report_line = (
'{segment.n_iter:d} {segment.seg_id:{max_seg_id_len}d} {segment.weight:20.14g}'
+ ' {status_name:{max_status_name_len}s} ({segment.status})' +
' {segment.walltime:<12.6g} {segment.cputime:<12.6g}' +
' {endpoint_type_name:{max_endpoint_type_len}s} ({segment.endpoint_type})'
+
' {n_parents:{max_n_parents_len}d} {segment.parent_id:{max_seg_id_len}d} {parents_str}'
+ '\n')
pcoord_lines = (
' pcoord[0] = {init_pcoord}\n pcoord[-1] = {final_pcoord}' +
'\n')
for (_seg_id, segment) in enumerate(segments):
parents_str = '[' + ', '.join(
map(str, sorted(segment.wtg_parent_ids))) + ']'
init_pcoord_str = '[' + ', '.join(
'{pcval:<12.6g}'.format(pcval=float(pce))
for pce in segment.pcoord[0]) + ']'
final_pcoord_str = '[' + ', '.join(
'{pcval:<12.6g}'.format(pcval=float(pce))
for pce in segment.pcoord[-1]) + ']'
self.output_file.write(
report_line.format(
segment=segment,
status_name=segment.status_names[segment.status],
endpoint_type_name=segment.endpoint_type_names[
segment.endpoint_type],
parents_str=parents_str,
n_parents=len(segment.wtg_parent_ids),
max_seg_id_len=max_seg_id_len,
max_status_name_len=max_status_name_len,
max_endpoint_type_len=max_endpoint_type_len,
max_n_parents_len=max_n_parents_len))
if self.print_pcoords:
self.output_file.write(
pcoord_lines.format(init_pcoord=init_pcoord_str,
final_pcoord=final_pcoord_str))
class WDumpSegs(WESTTool):
prog='w_dumpsegs'
description = '''\
Dump segment data as text. This is very inefficient, so this tool should be used
as a last resort (use hdfview/h5ls to look at data, and access HDF5 directly for
significant analysis tasks).
'''
def __init__(self):
super(WDumpSegs,self).__init__()
self.data_reader = WESTDataReader()
self.n_iter = None
self.output_file = None
self.print_pcoords = False
def add_args(self, parser):
self.data_reader.add_args(parser)
parser.add_argument('-p', '--print-pcoords', dest='print_pcoords', action='store_true',
help='print initial and final progress coordinates for each segment')
parser.add_argument('-i', '--iteration', dest='n_iter', type=int,
help='Use data from iteration N_ITER (default: last complete iteration)')
parser.add_argument('-o', '--output', dest='output_file',
help='Store output in OUTPUT_FILE (default: write to standard output).')
def process_args(self, args):
self.data_reader.process_args(args)
self.data_reader.open()
self.n_iter = args.n_iter or self.data_reader.current_iteration-1
self.output_file = open(args.output_file, 'wt') if args.output_file else sys.stdout
self.print_pcoords = args.print_pcoords
def go(self):
segments = self.data_reader.get_segments(self.n_iter)
max_seg_id_len = len(str(max(segment.seg_id for segment in segments)))
max_status_name_len = max(map(len,Segment.status_names.itervalues()))
max_endpoint_type_len = max(map(len,Segment.endpoint_type_names.itervalues()))
max_n_parents_len = len(str(max(len(segment.wtg_parent_ids) for segment in segments)))
report_line = ( '{segment.n_iter:d} {segment.seg_id:{max_seg_id_len}d} {segment.weight:20.14g}'
+' {status_name:{max_status_name_len}s} ({segment.status})'
+' {segment.walltime:<12.6g} {segment.cputime:<12.6g}'
+' {endpoint_type_name:{max_endpoint_type_len}s} ({segment.endpoint_type})'
+' {n_parents:{max_n_parents_len}d} {segment.parent_id:{max_seg_id_len}d} {parents_str}'
+'\n')
pcoord_lines = (' pcoord[0] = {init_pcoord}\n pcoord[-1] = {final_pcoord}'
+'\n')
for (_seg_id, segment) in enumerate(segments):
parents_str = '['+', '.join(map(str,sorted(segment.wtg_parent_ids)))+']'
init_pcoord_str = '[' + ', '.join('{pcval:<12.6g}'.format(pcval=float(pce)) for pce in segment.pcoord[0]) + ']'
final_pcoord_str = '[' + ', '.join('{pcval:<12.6g}'.format(pcval=float(pce)) for pce in segment.pcoord[-1]) + ']'
self.output_file.write(report_line.format(segment=segment,
status_name = segment.status_names[segment.status],
endpoint_type_name = segment.endpoint_type_names[segment.endpoint_type],
parents_str = parents_str,
n_parents = len(segment.wtg_parent_ids),
max_seg_id_len=max_seg_id_len,
max_status_name_len=max_status_name_len,
max_endpoint_type_len=max_endpoint_type_len,
max_n_parents_len=max_n_parents_len))
if self.print_pcoords:
self.output_file.write(pcoord_lines.format(init_pcoord = init_pcoord_str,final_pcoord = final_pcoord_str))
