def fetch(self, ert, key, parameter, data, comparison_fs):
data.x_data_type = "time"
fs = ert.enkf.enkf_main_get_fs(ert.main)
config_node = ert.enkf.ensemble_config_get_node(ert.ensemble_config, key)
node = ert.enkf.enkf_node_alloc(config_node)
comp_node = ert.enkf.enkf_node_alloc(config_node)
num_realizations = ert.enkf.enkf_main_get_ensemble_size(ert.main)
user_data = parameter.getUserData()
if user_data is None:
return False
key_index = None
if user_data.has_key("key_index"):
key_index = user_data["key_index"]
if parameter.getType() == FieldModel.TYPE:
field_position = user_data["field_position"]
field_config = ert.enkf.enkf_config_node_get_ref(config_node)
if ert.enkf.field_config_ijk_active(
field_config, field_position[0] - 1, field_position[1] - 1, field_position[2] - 1
):
key_index = "%i,%i,%i" % (field_position[0], field_position[1], field_position[2])
data.setKeyIndexIsIndex(True)
else:
return False
elif parameter.getType() == DataModel.TYPE:
data_index = user_data["data_index"]
key_index = "KEY:%d" % data_index
data.setKeyIndexIsIndex(True)
data.setKeyIndex(key_index)
state_list = [user_data["state"]]
if state_list[0] == enums.ert_state_enum.BOTH:
state_list = [enums.ert_state_enum.FORECAST, enums.ert_state_enum.ANALYZED]
for member in range(0, num_realizations):
data.x_data[member] = []
data.y_data[member] = []
x_time = data.x_data[member]
y = data.y_data[member]
if not comparison_fs is None:
data.x_comp_data[member] = []
data.y_comp_data[member] = []
x_comp_time = data.x_comp_data[member]
y_comp = data.y_comp_data[member]
member_config = ert.enkf.enkf_main_iget_member_config(ert.main, member)
stop_time = ert.enkf.enkf_main_get_history_length(ert.main)
for step in range(0, stop_time + 1):
for state in state_list:
if ert.enkf.enkf_fs_has_node(fs, config_node, step, member, state.value()):
sim_time = ert.enkf.member_config_iget_sim_time(member_config, step, fs)
ert.enkf.enkf_fs_fread_node(fs, node, step, member, state.value())
valid = ertwrapper.c_int()
value = ert.enkf.enkf_node_user_get(node, key_index, ertwrapper.byref(valid))
if valid.value == 1:
data.checkMaxMin(sim_time)
data.checkMaxMinY(value)
x_time.append(sim_time)
y.append(value)
# else:
# print "Not valid: ", key, member, step, key_index
if not comparison_fs is None:
if ert.enkf.enkf_fs_has_node(comparison_fs, config_node, step, member, state.value()):
sim_time = ert.enkf.member_config_iget_sim_time(member_config, step, comparison_fs)
ert.enkf.enkf_fs_fread_node(comparison_fs, comp_node, step, member, state.value())
valid = ertwrapper.c_int()
value = ert.enkf.enkf_node_user_get(comp_node, key_index, ertwrapper.byref(valid))
if valid.value == 1:
# data.checkMaxMin(sim_time)
# data.checkMaxMinY(value)
x_comp_time.append(sim_time)
y_comp.append(value)
# else:
# print "Not valid: ", key, member, step, key_index
data.x_data[member] = numpy.array([t.datetime() for t in x_time])
data.y_data[member] = numpy.array(y)
if not comparison_fs is None:
data.x_comp_data[member] = numpy.array([t.datetime() for t in x_comp_time])
data.y_comp_data[member] = numpy.array(y_comp)
self._getObservations(ert, key, key_index, data)
self._getRefCase(ert, key, data)
ert.enkf.enkf_node_free(node)
ert.enkf.enkf_node_free(comp_node)
data.inverted_y_axis = False
def fetch(self, ert, key, parameter, data, comparison_fs):
data.x_data_type = "time"
fs = ert.main.get_fs
config_node = ert.main.ensemble_config.get_node(key)
node = config_node.alloc_node
comp_node = config_node.alloc_node
num_realizations = ert.main.ens_size
var_type_set = False
user_data = parameter.getUserData()
if user_data is None:
return False
key_index = None
if user_data.has_key("key_index"):
key_index = user_data["key_index"]
if parameter.getType() == FieldModel.TYPE:
var_type = enums.enkf_var_type.PARAMETER
var_type_set = True
field_position = user_data["field_position"]
field_config = config_node.field_model
if field_config.ijk_active(field_position[0] - 1, field_position[1] - 1, field_position[2] - 1):
key_index = "%i,%i,%i" % (field_position[0], field_position[1], field_position[2])
data.setKeyIndexIsIndex(True)
else:
return False
elif parameter.getType() == DataModel.TYPE:
var_type = enums.enkf_var_type.PARAMETER
var_type_set = True
data_index = user_data["data_index"]
key_index = "KEY:%d" % data_index
data.setKeyIndexIsIndex(True)
if not var_type_set:
var_type = enums.enkf_var_type.DYNAMIC_RESULT
data.setKeyIndex(key_index)
state_list = [user_data["state"]]
if state_list[0] == enums.ert_state_enum.BOTH:
state_list = [enums.ert_state_enum.FORECAST, enums.ert_state_enum.ANALYZED]
for member in range(0, num_realizations):
data.x_data[member] = []
data.y_data[member] = []
x_time = data.x_data[member]
y = data.y_data[member]
if not comparison_fs is None:
data.x_comp_data[member] = []
data.y_comp_data[member] = []
x_comp_time = data.x_comp_data[member]
y_comp = data.y_comp_data[member]
stop_time = ert.main.get_history_length
for state in state_list:
start_time = 0
if config_node.get_impl_type == SummaryModel.TYPE:
start_time = 1
for step in range(start_time, stop_time):
time_map = fs.get_time_map
sim_time_as_c_int = time_map.iget(step)
sim_time_as_time_t = time_t(sim_time_as_c_int)
sim_time_as_ordinal = sim_time_as_time_t.datetime().toordinal()
valid = ertwrapper.c_double()
value = node.user_get(fs, key_index, step, member, state.value(), ertwrapper.byref(valid))
if value == True:
data.checkMaxMin(sim_time_as_time_t)
data.checkMaxMinY(valid.value)
x_time.append(sim_time_as_ordinal)
y.append(valid.value)
# else:
# print "Not valid: ", key, member, step, key_index, value, state.value()
if not comparison_fs is None:
time_map = comparison_fs.get_time_map
sim_time_as_c_int = time_map.iget(step)
sim_time_as_time_t = time_t(sim_time_as_c_int)
sim_time_as_ordinal = sim_time_as_time_t.datetime().toordinal()
valid = ertwrapper.c_double()
value = node.user_get(comparison_fs, key, step, member, state.value(), ertwrapper.byref(valid))
if value == 1:
data.checkMaxMin(sim_time_as_time_t)
data.checkMaxMinY(valid.value)
x_comp_time.append(sim_time_as_ordinal)
y_comp.append(valid.value)
# else:
# print "Not valid: ", key, member, step, key_index
data.x_data[member] = numpy.array(x_time) # [t.datetime() for t in x_time])
data.y_data[member] = numpy.array(y)
if not comparison_fs is None:
data.x_comp_data[member] = numpy.array(x_comp_time) # [t.datetime() for t in x_comp_time])
data.y_comp_data[member] = numpy.array(y_comp)
self._getObservations(ert, key, key_index, data)
self._getRefCase(ert, key, data)
# node.__del__
# comp_node.__del__
data.inverted_y_axis = False
