def _install_row_cases(row, values):
"""Installs row case names, based on values entries."""
# First define base testers that add row constraints and safety checks.
constraint_rows_map = values.get('constraint_rows')
if constraint_rows_map:
base_row = _filter_test_row(row, with_rules=False)
values['base_test_case'] = (
'Case%s' % constraint_rows_map[dgen_core.neutral_repr(base_row)])
else:
values['base_test_case'] = ''
# Add test decoders associated with the row in the table.
decoder_rows_map = values.get('decoder_rows')
if decoder_rows_map:
decoder_row = _filter_test_row(row)
values['test_case'] = (
'Case%s' % decoder_rows_map[dgen_core.neutral_repr(decoder_row)])
else:
values['test_case'] = ''
# Encorporate patterns with each row.
pattern_rows_map = values.get('test_rows')
if pattern_rows_map:
pattern_row = _filter_test_row(row, with_patterns=True)
values['test_pattern'] = (
'Case%s' % pattern_rows_map[dgen_core.neutral_repr(pattern_row)])
else:
values['test_pattern'] = ''
def _install_row_cases(row, values):
"""Installs row case names, based on values entries."""
# First define base testers that add row constraints and safety checks.
constraint_rows_map = values.get('constraint_rows')
if constraint_rows_map:
base_row = _filter_test_row(row)
values['base_test_case'] = (
'Case%s' % constraint_rows_map[dgen_core.neutral_repr(base_row)])
else:
values['base_test_case'] = ''
# Add test decoders associated with the row in the table.
decoder_rows_map = values.get('decoder_rows')
if decoder_rows_map:
decoder_row = _filter_test_row(row)
values['test_case'] = (
'Case%s' % decoder_rows_map[dgen_core.neutral_repr(decoder_row)])
else:
values['test_case'] = ''
# Encorporate patterns with each row.
pattern_rows_map = values.get('test_rows')
if pattern_rows_map:
pattern_row = _filter_test_row(row)
values['test_pattern'] = (
'Case%s' % pattern_rows_map[dgen_core.neutral_repr(pattern_row)])
else:
values['test_pattern'] = ''
def _index_neutral_map(values):
"""Returns a dictionary from each neutral_repr(value) in list
values, to its corresponding index. This is done to reduce the
number of compares to find the index, speeding up code
generation.
"""
lookup_map = {}
index = 0
for v in values:
lookup_map[dgen_core.neutral_repr(v)] = index
index += 1
return lookup_map
def _index_neutral_map(values):
"""Returns a dictionary from each neutral_repr(value) in list
values, to its corresponding index. This is done to reduce the
number of compares to find the index, speeding up code
generation.
"""
lookup_map = {}
index = 0
for v in values:
lookup_map[dgen_core.neutral_repr(v)] = index
index += 1
return lookup_map
def _install_test_row(row, decoder, values,
with_patterns=False, with_rules=True):
"""Installs data associated with the given row into the values map.
Installs the baseline class, rule name, and constraints associated
with the row. If with_patterns is specified, then pattern information and
actual class information is also inserted.
"""
action = _filter_test_action(row.action, with_patterns, with_rules)
values['row_comment'] = (dgen_core.neutral_repr(row.copy_with_action(action)).
replace(NEWLINE_STR, COMMENTED_NEWLINE_STR))
values['row_rep_comment'] = repr(
row.copy_with_action(action)).replace(NEWLINE_STR, COMMENTED_NEWLINE_STR)
_install_action(decoder, action, values)
return action
def DefineDecoder(action, decoder_name, out):
"""Generates the C++ class definition for the given action.
action: The decoder action to define.
decoder_name: The name for the C++ decoder class.
out: The output stream to write the class declation to.
"""
values = {'decoder_name': decoder_name}
for method in METHODS:
if _IsMethodDefined(action, method):
method_body = _FindMethodBody(action, method)
values['neutral_rep'] = (
'%s: %s' % (method, dgen_output.commented_string(
repr(dgen_core.neutral_repr(method_body)), ' ')))
DefineMethodFcn(method)(out, method_body, values)
def _rows_to_test(decoder, values):
"""Returns the rows of the decoder that define enough information
that testing can be done.
"""
generated_names = set()
rows = []
for table in decoder.tables():
for row in table.rows():
if (isinstance(row.action, dgen_core.DecoderAction) and
row.action.pattern()):
new_row = row.copy_with_action(_install_test_row(row, decoder, values))
constraint_tester = dgen_core.neutral_repr(new_row)
if constraint_tester not in generated_names:
generated_names.add(constraint_tester)
rows.append(new_row)
return sorted(rows)
def _rows_to_test(decoder, values):
"""Returns the rows of the decoder that define enough information
that testing can be done.
"""
generated_names = set()
rows = []
for table in decoder.tables():
for row in table.rows():
if (isinstance(row.action, dgen_core.DecoderAction) and
row.action.pattern()):
new_row = row.copy_with_action(_install_test_row(row, decoder, values))
constraint_tester = dgen_core.neutral_repr(new_row)
if constraint_tester not in generated_names:
generated_names.add(constraint_tester)
rows.append(new_row)
return sorted(rows)