def stringify(self, record_or_index, fields=None, exclude=[]):
"""
Return element, passed in as a record or index, as the string that
would be output by the output() method.
"""
record = record_or_index
if type(record_or_index) != numpy.void:
record = self[record_or_index]
if fields is None: fields = [s[0] for s in self.spec]
for skip_field in exclude:
if skip_field in fields: fields.remove(skip_field)
strings = []
for field in fields:
strings.append(self.field_spec[field][2] % record[field])
return ' '.join(strings)
def output(self, indices=None, fields=None, exclude=[], rename=[],
select_values=None, skip_values=None,
sort=None, reverse=False, sliced=None, unique=None,
filename=None, append=False, fh=None, stringify=False,
print_spec=None, print_header=None, line_space=0, delimiter=' '):
"""
Print to screen, or file filename or file handle fh, the records
given by indices (default all).
File format is as follows --
#fields symbol average_volume liquidity days min_close min_volume
#types |S14 <f8 <f8 <i8 <f8 <f8
#formats %-14s %9.0f %8.2f %3d %9.4f %9.0f
AA+ 1190 0.08 31 56.0000 100
ABL 6415 0.09 48 12.8750 200
fields:
list of fields, to selectively print, in that order.
exclude:
list of fields to exclude from printing.
rename:
list of (field, new_name) pairs to rename fields in header of output
sort:
sort records by this field before printing.
reverse:
reverse records to be printed.
sliced:
select records based on this slice tuple.
unique:
print only the first occurrence for each unique value for this field.
filename:
print to this file.
fh:
print to this filehandle.
stringify:
return output as string.
append:
append to file if file already exists.
print_spec:
Whether to print a three-line header or not. Defaults to true if writing
to a new file, false otherwise.
print_header:
Whether to print a one-line header or not. Defaults to true if printing
to standard output, false otherwise.
select_values:
(<field>, set([str1, str2, ...])) where rows are to be printed only if
the value for <field> is in [str1, str2, ...]
skip_values:
(<field>, set([str1, str2, ...])) where rows are to be printed only if
the value for <field> is not in [str1, str2, ...]
line_space:
Print an empty line every these many lines.
"""
if filename:
mode = 'w'
if append and os.path.exists(filename):
mode = 'a'
elif print_spec is None and print_header is None: print_spec = True
if filename[-3:] == '.gz':
if mode == 'a': raise AssertionError('Can not append to .gz file ' + filename)
fh = gzip.open(filename, 'wb')
else: fh = open(filename, mode)
elif fh is None and print_header is None and print_spec is None:
print_header = True
if stringify:
assert filename is None and fh is None, 'Too many output options.'
fh = cStringIO.StringIO()
field_format = dict([(field, spec[2]) \
for field, spec in self.field_spec.items()])
if fields is None: fields = [s[0] for s in self.spec]
elif numpy.isscalar(fields): fields = [fields]
if exclude is not None:
if numpy.isscalar(exclude): exclude = [exclude]
for skip_field in exclude:
if skip_field in fields: fields.remove(skip_field)
if print_spec or print_header:
print >>fh, self.header(fields=fields, spec=print_spec, rename=rename, delimiter=delimiter)
if indices is None: records = self
else: records = self[indices]
if sort is not None:
srt_idx = arrays.argsort(records, order=sort, reverse=reverse)
records = records[srt_idx]
elif reverse: records = records[::-1]
if sliced is not None:
if numpy.isscalar(sliced): sliced = [sliced]
records = records[slice(*sliced)]
uniques = {}
line_count = 0
for record in records:
if select_values and record[select_values[0]] not in select_values[1]: continue
if skip_values and record[skip_values[0]] in skip_values[1]: continue
if unique:
if record[unique] in uniques: continue
uniques[record[unique]] = True
strings = []
for field in fields:
if record[field] == '': record[field] = '#NA'
strings.append(field_format[field] % record[field])
if line_space and line_count and line_count % line_space == 0: print ''
print >>fh, delimiter.join(strings)
line_count += 1
if stringify: return fh.getvalue()
if fh is not None: fh.flush()
if filename: fh.close()
