def fetchData(self, key, case=None):
key, keyword = key.split(":")
ensemble_config_node = self.getEnsembleConfigNode(key)
enkf_fs = self.ert().getEnkfFsManager().getFileSystem(case)
ensemble_plot_gen_kw = EnsemblePlotGenKW(ensemble_config_node, enkf_fs)
keyword_index = ensemble_plot_gen_kw.getIndexForKeyword(keyword)
use_log_scale = ensemble_plot_gen_kw.shouldUseLogScale(keyword_index)
data = {"x": [0], "y": [], "min_y": None, "max_y": None, "min_x": 0, "max_x": 0, "use_log_scale": use_log_scale}
for vector in ensemble_plot_gen_kw:
y = []
data["y"].append(y)
if len(vector) > keyword_index:
value = vector.getValue(keyword_index)
y.append(value)
if data["min_y"] is None or data["min_y"] > value:
data["min_y"] = value
if data["max_y"] is None or data["max_y"] < value:
data["max_y"] = value
return data
def loadAllGenKwData(ert, case_name, keys=None):
"""
@type ert: EnKFMain
@type case_name: str
@type keys: list of str
@rtype: DataFrame
"""
fs = ert.getEnkfFsManager().getFileSystem(case_name)
realizations = GenKwCollector.createActiveList(ert, fs)
gen_kw_keys = GenKwCollector.getAllGenKwKeys(ert)
if keys is not None:
gen_kw_keys = [key for key in keys if key in gen_kw_keys
] # ignore keys that doesn't exist
gen_kw_array = numpy.empty(shape=(len(gen_kw_keys), len(realizations)),
dtype=numpy.float64)
gen_kw_array.fill(numpy.nan)
for column_index, key in enumerate(gen_kw_keys):
key, keyword = key.split(":")
use_log_scale = False
if key.startswith("LOG10_"):
key = key[6:]
use_log_scale = True
ensemble_config_node = ert.ensembleConfig().getNode(key)
ensemble_data = EnsemblePlotGenKW(ensemble_config_node, fs)
keyword_index = ensemble_data.getIndexForKeyword(keyword)
for realization_index, realization_number in enumerate(
realizations):
realization_vector = ensemble_data[realization_number]
value = realization_vector[keyword_index]
if use_log_scale:
value = math.log10(value)
gen_kw_array[column_index][realization_index] = value
gen_kw_data = DataFrame(data=numpy.transpose(gen_kw_array),
index=realizations,
columns=gen_kw_keys)
gen_kw_data.index.name = "Realization"
return gen_kw_data
class EnsembleGenKWFetcher(DataFetcher):
def __init__(self, ert):
super(EnsembleGenKWFetcher, self).__init__(ert)
def fetchSupportedKeys(self):
gen_kw_keys = self.ert().ensembleConfig().getKeylistFromImplType(
ErtImplType.GEN_KW)
gen_kw_list = []
for key in gen_kw_keys:
enkf_config_node = self.ert().ensembleConfig().getNode(key)
model_config = enkf_config_node.getModelConfig()
assert isinstance(model_config, GenKwConfig)
model_keys = model_config.getKeyWords()
for key_word in model_keys:
gen_kw_list.append("%s:%s" % (key, key_word))
return gen_kw_list
def getEnsembleConfigNode(self, key):
""" @rtype: EnsembleConfig """
ensemble_config = self.ert().ensembleConfig()
assert key in ensemble_config
return ensemble_config.getNode(key)
def fetchData(self, key, case=None):
key, keyword = key.split(":")
ensemble_config_node = self.getEnsembleConfigNode(key)
enkf_fs = self.ert().getEnkfFsManager().getFileSystem(case)
ensemble_plot_gen_kw = EnsemblePlotGenKW(ensemble_config_node, enkf_fs)
keyword_index = ensemble_plot_gen_kw.getIndexForKeyword(keyword)
use_log_scale = ensemble_plot_gen_kw.shouldUseLogScale(keyword_index)
data = {
"x": [0],
"y": [],
"min_y": None,
"max_y": None,
"min_x": 0,
"max_x": 0,
"use_log_scale": use_log_scale
}
for vector in ensemble_plot_gen_kw:
y = []
data["y"].append(y)
if len(vector) > keyword_index:
value = vector.getValue(keyword_index)
y.append(value)
if data["min_y"] is None or data["min_y"] > value:
data["min_y"] = value
if data["max_y"] is None or data["max_y"] < value:
data["max_y"] = value
return data
def loadAllGenKwData(ert, case_name, keys=None):
"""
@type ert: EnKFMain
@type case_name: str
@type keys: list of str
@rtype: DataFrame
"""
fs = ert.getEnkfFsManager().getFileSystem(case_name)
realizations = GenKwCollector.createActiveList(ert, fs)
gen_kw_keys = GenKwCollector.getAllGenKwKeys(ert)
if keys is not None:
gen_kw_keys = [key for key in keys if key in gen_kw_keys] # ignore keys that doesn't exist
gen_kw_array = numpy.empty(shape=(len(gen_kw_keys), len(realizations)), dtype=numpy.float64)
gen_kw_array.fill(numpy.nan)
for column_index, key in enumerate(gen_kw_keys):
key, keyword = key.split(":")
use_log_scale = False
if key.startswith("LOG10_"):
key = key[6:]
use_log_scale = True
ensemble_config_node = ert.ensembleConfig().getNode(key)
ensemble_data = EnsemblePlotGenKW(ensemble_config_node, fs)
keyword_index = ensemble_data.getIndexForKeyword(keyword)
for realization_index, realization_number in enumerate(realizations):
realization_vector = ensemble_data[realization_number]
value = realization_vector[keyword_index]
if use_log_scale:
value = math.log10(value)
gen_kw_array[column_index][realization_index] = value
gen_kw_data = DataFrame(data=numpy.transpose(gen_kw_array), index=realizations, columns=gen_kw_keys)
gen_kw_data.index.name = "Realization"
return gen_kw_data
