def _get_layers(self):
self.layers = []
for table_name, table in DATA_TABLES_ORIGINAL.iteritems():
select_statement = select([table]).where(
and_(
table.c.galaxy_id == self._galaxy_id,
table.c.galaxy_id == MASK_POINT.c.galaxy_id,
table.c.x == MASK_POINT.c.x,
table.c.y == MASK_POINT.c.y,
table.c.x >= self._from_x,
table.c.x <= self._to_x,
table.c.y >= self._from_y,
table.c.y <= self._to_y,
table.c.value > 0.0
)
)
count = 0
numpy_table = numpy.zeros((self._width, self._height))
for entry in self._connection.execute(select_statement):
corrected_x = entry[table.c.x] - self._from_x
corrected_y = entry[table.c.y] - self._from_y
numpy_table[corrected_x, corrected_y] = entry[table.c.value]
count += 1
if count > 0:
self.layers.append(numpy_table)
def get_tables_required(steps_done):
data_required = []
for table_name, table in DATA_TABLES_SED.iteritems():
step_done = [STEP_DONE_ID_BUILD_GALAXY_DETAILS, table_name]
if step_done not in steps_done:
data_required.append(table)
for table_name, table in DATA_TABLES_ORIGINAL.iteritems():
step_done = [STEP_DONE_ID_BUILD_GALAXY_DETAILS, table_name]
if step_done not in steps_done:
data_required.append(table)
return data_required
def get_tables_required(steps_done):
data_required = []
for table_name, table in DATA_TABLES_SED.iteritems():
step_done = [STEP_DONE_ID_MEAN_STANDARD_DEVIATION, table_name]
if step_done not in steps_done:
data_required.append(table)
for table_name, table in DATA_TABLES_ORIGINAL.iteritems():
step_done = [STEP_DONE_ID_MEAN_STANDARD_DEVIATION, table_name]
if step_done not in steps_done:
data_required.append(table)
return data_required
def get_tables_required(steps_done):
data_required = []
for table_name, table in DATA_TABLES_SED.iteritems():
step_done1 = [STEP_DONE_ID_BUILD_GALAXY_DETAILS, table_name]
step_done2 = [STEP_DONE_ID_NORMALISE_Z_MIN_MAX, table_name]
if step_done1 in steps_done and step_done2 not in steps_done:
data_required.append(table)
for table_name, table in DATA_TABLES_ORIGINAL.iteritems():
step_done1 = [STEP_DONE_ID_BUILD_GALAXY_DETAILS, table_name]
step_done2 = [STEP_DONE_ID_NORMALISE_Z_MIN_MAX, table_name]
if step_done1 in steps_done and step_done2 not in steps_done:
data_required.append(table)
return data_required
