def update_schema(self, tablename, mappings):
"""
mappings is a dict of column name to 'continuous', 'multinomial', 'ignore', or 'key'.
TODO: can we get rid of cctypes?
"""
metadata_full = self.get_metadata_full(tablename)
cctypes_full = metadata_full['cctypes_full']
M_c_full = metadata_full['M_c_full']
raw_T_full = metadata_full['raw_T_full']
colnames_full = utils.get_all_column_names_in_original_order(M_c_full)
# Now, update cctypes_full (cctypes updated later, after removing ignores).
mapping_set = 'continuous', 'multinomial', 'ignore', 'key'
for col, mapping in mappings.items():
if col.lower() not in M_c_full['name_to_idx']:
raise utils.BayesDBError('Error: column %s does not exist.' % col)
elif mapping not in mapping_set:
raise utils.BayesDBError('Error: datatype %s is not one of the valid datatypes: %s.' % (mapping, str(mapping_set)))
cidx = M_c_full['name_to_idx'][col.lower()]
# If the column's current type is key, don't allow the change.
if cctypes_full[cidx] == 'key':
raise utils.BayesDBError('Error: %s is already set as the table key. To change its type, reload the table using CREATE BTABLE and choose a different key column.' % col.lower())
# If the user tries to change a column to key, it's easier to reload the table, since at this point
# there aren't models anyways. Eventually we can build this in if it's desirable.
elif mapping == 'key':
raise utils.BayesDBError('Error: key column already exists. To choose a different key, reload the table using CREATE BTABLE')
cctypes_full[cidx] = mapping
# Make sure there isn't more than one key.
assert len(filter(lambda x: x=='key', cctypes_full)) == 1
T_full, M_r_full, M_c_full, _ = data_utils.gen_T_and_metadata(colnames_full, raw_T_full, cctypes=cctypes_full)
# Variables without "_full" don't include ignored columns.
raw_T, cctypes, colnames = data_utils.remove_ignore_cols(raw_T_full, cctypes_full, colnames_full)
T, M_r, M_c, _ = data_utils.gen_T_and_metadata(colnames, raw_T, cctypes=cctypes)
# Now, put cctypes, T, M_c, and M_r back into the DB
self.update_metadata(tablename, M_r, M_c, T, cctypes)
self.update_metadata_full(tablename, M_r_full, M_c_full, T_full, cctypes_full)
return self.get_metadata_full(tablename)
def update_schema(self, tablename, mappings):
"""
mappings is a dict of column name to 'cyclic', 'numerical', 'categorical', 'ignore', or
'key'.
TODO: can we get rid of cctypes?
"""
metadata_full = self.get_metadata_full(tablename)
cctypes_full = metadata_full['cctypes_full']
M_c_full = metadata_full['M_c_full']
raw_T_full = metadata_full['raw_T_full']
colnames_full = utils.get_all_column_names_in_original_order(M_c_full)
try:
parameters_full = [x['parameters'] for x in M_c_full['column_metadata']]
except KeyError:
print('WARNING: resetting parameters to defaults. Please check these values with '
'DESCRIBE and adjust them manually if necessary.')
parameters_full = []
for md in M_c_full['column_metadata']:
if 'dirichlet' in md['modeltype']:
params = {
'cardinality': len(md['value_to_code'])
}
elif'vonmises' in md['modeltype']:
params = {
'min': 0.0,
'max': 2.0*3.14159265358979323846264338328
}
else:
params = None
parameters_full.append(params)
parameters_full = [None for _ in range(len(M_c_full['column_metadata']))]
# Now, update cctypes_full (cctypes updated later, after removing ignores).
mapping_set = 'numerical', 'categorical', 'ignore', 'key', 'cyclic'
for colname, mapping in mappings.items():
cctype = mapping['cctype']
parameters = mapping['parameters']
if colname.lower() not in M_c_full['name_to_idx']:
raise utils.BayesDBError('Error: column %s does not exist.' % colname)
elif cctype not in mapping_set:
raise utils.BayesDBError('Error: datatype %s is not one of the valid datatypes: %s.'
% (mapping, str(mapping_set)))
cidx = M_c_full['name_to_idx'][colname.lower()]
# If the column's current type is key, don't allow the change.
if cctypes_full[cidx] == 'key':
raise utils.BayesDBError('Error: %s is already set as the table key. To change its '
'type, reload the table using CREATE BTABLE and choose a '
'different key column.' % colname.lower())
# If the user tries to change a column to key, it's easier to reload the table, since at
# this point there aren't models anyways. Eventually we can build this in if it's
# desirable.
elif cctype == 'key':
raise utils.BayesDBError('Error: key column already exists. To choose a different '
'key, reload the table using CREATE BTABLE')
cctypes_full[cidx] = cctype
parameters_full[cidx] = parameters
# Make sure there isn't more than one key.
assert len(filter(lambda x: x == 'key', cctypes_full)) == 1
T_full, M_r_full, M_c_full, _ = data_utils.gen_T_and_metadata(colnames_full, raw_T_full,
cctypes=cctypes_full,
parameters=parameters_full)
# Variables without "_full" don't include ignored columns.
raw_T, cctypes, colnames, parameters = data_utils.remove_ignore_cols(raw_T_full,
cctypes_full,
colnames_full,
parameters_full)
T, M_r, M_c, _ = data_utils.gen_T_and_metadata(colnames, raw_T, cctypes=cctypes,
parameters=parameters)
# Now, put cctypes, T, M_c, and M_r back into the DB
self.update_metadata(tablename, M_r, M_c, T, cctypes)
self.update_metadata_full(tablename, M_r_full, M_c_full, T_full, cctypes_full)
return self.get_metadata_full(tablename)
def update_schema(self, tablename, mappings):
"""
mappings is a dict of column name to 'cyclic', 'numerical', 'categorical', 'ignore', or
'key'.
TODO: can we get rid of cctypes?
"""
metadata_full = self.get_metadata_full(tablename)
cctypes_full = metadata_full['cctypes_full']
M_c_full = metadata_full['M_c_full']
raw_T_full = metadata_full['raw_T_full']
colnames_full = utils.get_all_column_names_in_original_order(M_c_full)
try:
parameters_full = [x['parameters'] for x in M_c_full['column_metadata']]
except KeyError:
print('WARNING: resetting parameters to defaults. Please check these values with '
'DESCRIBE and adjust them manually if necessary.')
parameters_full = []
for md in M_c_full['column_metadata']:
if 'dirichlet' in md['modeltype']:
params = {
'cardinality': len(md['value_to_code'])
}
elif'vonmises' in md['modeltype']:
params = {
'min': 0.0,
'max': 2.0*3.14159265358979323846264338328
}
else:
params = None
parameters_full.append(params)
parameters_full = [None for _ in range(len(M_c_full['column_metadata']))]
# Now, update cctypes_full (cctypes updated later, after removing ignores).
mapping_set = 'numerical', 'categorical', 'ignore', 'key', 'cyclic'
for colname, mapping in mappings.items():
cctype = mapping['cctype']
parameters = mapping['parameters']
if colname.lower() not in M_c_full['name_to_idx']:
raise utils.BayesDBError('Error: column %s does not exist.' % colname)
elif cctype not in mapping_set:
raise utils.BayesDBError('Error: datatype %s is not one of the valid datatypes: %s.'
% (mapping, str(mapping_set)))
cidx = M_c_full['name_to_idx'][colname.lower()]
# If the column's current type is key, don't allow the change.
if cctypes_full[cidx] == 'key':
raise utils.BayesDBError('Error: %s is already set as the table key. To change its '
'type, reload the table using CREATE BTABLE and choose a '
'different key column.' % colname.lower())
# If the user tries to change a column to key, it's easier to reload the table, since at
# this point there aren't models anyways. Eventually we can build this in if it's
# desirable.
elif cctype == 'key':
raise utils.BayesDBError('Error: key column already exists. To choose a different '
'key, reload the table using CREATE BTABLE')
cctypes_full[cidx] = cctype
parameters_full[cidx] = parameters
# Make sure there isn't more than one key.
assert len(filter(lambda x: x == 'key', cctypes_full)) == 1
T_full, M_r_full, M_c_full, _ = data_utils.gen_T_and_metadata(colnames_full, raw_T_full,
cctypes=cctypes_full,
parameters=parameters_full)
# Variables without "_full" don't include ignored columns.
raw_T, cctypes, colnames, parameters = data_utils.remove_ignore_cols(raw_T_full,
cctypes_full,
colnames_full,
parameters_full)
T, M_r, M_c, _ = data_utils.gen_T_and_metadata(colnames, raw_T, cctypes=cctypes,
parameters=parameters)
# Now, put cctypes, T, M_c, and M_r back into the DB
self.update_metadata(tablename, M_r, M_c, T, cctypes)
self.update_metadata_full(tablename, M_r_full, M_c_full, T_full, cctypes_full)
return self.get_metadata_full(tablename)