def fetchSummaryData(self, observation_data_fetcher, key, cases):
plot_data = PlotData(key)
observation_data = observation_data_fetcher.fetchData(key)
observation_plot_data = ObservationPlotData(key)
observation_plot_data.setObservationData(observation_data["x"], observation_data["y"], observation_data["std"], observation_data["continuous"])
observation_plot_data.updateBoundaries(observation_data["min_x"], observation_data["max_x"], observation_data["min_y"], observation_data["max_y"])
plot_data.setObservationData(observation_plot_data)
refcase_data = RefcaseDataFetcher(self.ert()).fetchData(key)
refcase_plot_data = RefcasePlotData(key)
refcase_plot_data.setRefcaseData(refcase_data["x"], refcase_data["y"])
refcase_plot_data.updateBoundaries(refcase_data["min_x"], refcase_data["max_x"], refcase_data["min_y"], refcase_data["max_y"])
plot_data.setRefcaseData(refcase_plot_data)
for case in cases:
ensemble_data = EnsembleDataFetcher(self.ert()).fetchData(key, case)
ensemble_plot_data = EnsemblePlotData(key, case)
ensemble_plot_data.setEnsembleData(ensemble_data["x"], ensemble_data["y"], ensemble_data["min_y_values"], ensemble_data["max_y_values"])
ensemble_plot_data.updateBoundaries(ensemble_data["min_x"], ensemble_data["max_x"], ensemble_data["min_y"], ensemble_data["max_y"])
plot_data.addEnsembleData(ensemble_plot_data)
return plot_data
def fetchPcaData(self, key, cases):
""" @rtype: PlotData """
if key.startswith("PCA:"):
pca_name = key
else:
pca_name ="PCA:%s" % key
pca_data_fetcher = PcaDataFetcher(self.ert())
pca_plot_data = PlotData(pca_name)
if DataTypeKeysModel().isCustomPcaKey(key):
obs_keys = DataTypeKeysModel().getCustomPcaKeyObsKeys(key)
else:
obs_keys = pca_data_fetcher.getObsKeys(key)
for case in cases:
pca_data = pca_data_fetcher.fetchData(obs_keys, case)
if pca_data["x"] is not None:
if not pca_plot_data.hasObservationData():
pca_observation_plot_data = ObservationPlotData(pca_name)
pca_observation_plot_data.setObservationData(pca_data["x"], pca_data["obs_y"], [0.0 for x in pca_data["x"]], False)
pca_observation_plot_data.updateBoundaries(pca_data["min_x"], pca_data["max_x"], pca_data["min_y"], pca_data["max_y"])
pca_plot_data.setObservationData(pca_observation_plot_data)
pca_ensemble_plot_data = EnsemblePlotData(key, case)
pca_ensemble_plot_data.setEnsembleData(pca_data["x"], pca_data["y"], [], [])
pca_ensemble_plot_data.updateBoundaries(pca_data["min_x"], pca_data["max_x"], pca_data["min_y"], pca_data["max_y"])
pca_plot_data.addEnsembleData(pca_ensemble_plot_data)
return pca_plot_data
def fetchBlockObservationData(self, block_observation_data_fetcher, key, cases):
plot_data = PlotData(key)
data = block_observation_data_fetcher.fetchData(key)
block_observation_plot_data = ObservationPlotData(key)
selected_report_step_index = 0
if len(data) > 0:
data = data[selected_report_step_index]
block_observation_plot_data.setObservationData(data["x"], data["y"], data["std"], False, histogram_support=False)
block_observation_plot_data.updateBoundaries(data["min_x"], data["max_x"], data["min_y"], data["max_y"])
plot_data.setObservationData(block_observation_plot_data)
for case in cases:
ensemble_data = EnsembleBlockDataFetcher(self.ert()).fetchData(key, case)
if len(ensemble_data) > 0:
ensemble_data = ensemble_data[selected_report_step_index]
ensemble_plot_data = EnsemblePlotData(key, case)
ensemble_plot_data.setEnsembleData(ensemble_data["x"], ensemble_data["y"], ensemble_data["min_x_values"], ensemble_data["max_x_values"], histogram_support=False)
ensemble_plot_data.updateBoundaries(ensemble_data["min_x"], ensemble_data["max_x"], ensemble_data["min_y"], ensemble_data["max_y"])
plot_data.addEnsembleData(ensemble_plot_data)
return plot_data
def addObservationData(self, plot_data, key, fetcher, histogram_factory=None):
observation_data = fetcher.fetchData(key)
observation_plot_data = ObservationPlotData(key)
observation_plot_data.setObservationData(observation_data["x"], observation_data["y"], observation_data["std"], observation_data["continuous"])
observation_plot_data.updateBoundaries(observation_data["min_x"], observation_data["max_x"], observation_data["min_y"], observation_data["max_y"])
plot_data.setObservationData(observation_plot_data)
if histogram_factory is not None:
histogram_factory.setObservations(observation_data["x"], observation_data["y"], observation_data["std"], observation_data["min_y"], observation_data["max_y"])
def fetchPcaData(self, key, cases):
""" @rtype: PlotData """
if key.startswith("PCA:"):
pca_name = key
else:
pca_name = "PCA:%s" % key
pca_data_fetcher = PcaDataFetcher(self.ert())
pca_plot_data = PlotData(pca_name)
if DataTypeKeysModel().isCustomPcaKey(key):
obs_keys = DataTypeKeysModel().getCustomPcaKeyObsKeys(key)
else:
obs_keys = pca_data_fetcher.getObsKeys(key)
for case in cases:
pca_data = pca_data_fetcher.fetchData(obs_keys, case)
if pca_data["x"] is not None:
if not pca_plot_data.hasObservationData():
pca_observation_plot_data = ObservationPlotData(pca_name)
pca_observation_plot_data.setObservationData(
pca_data["x"], pca_data["obs_y"],
[0.0 for x in pca_data["x"]], False)
pca_observation_plot_data.updateBoundaries(
pca_data["min_x"], pca_data["max_x"],
pca_data["min_y"], pca_data["max_y"])
pca_plot_data.setObservationData(pca_observation_plot_data)
pca_ensemble_plot_data = EnsemblePlotData(key, case)
pca_ensemble_plot_data.setEnsembleData(pca_data["x"],
pca_data["y"], [], [])
pca_ensemble_plot_data.updateBoundaries(
pca_data["min_x"], pca_data["max_x"], pca_data["min_y"],
pca_data["max_y"])
pca_plot_data.addEnsembleData(pca_ensemble_plot_data)
return pca_plot_data
def fetchGenData(self, gen_data_fetcher, key, cases):
plot_data = PlotData(key)
ensemble_data = ObservationGenDataFetcher(self.ert()).fetchData(key, cases)
if len(ensemble_data) > 0:
observation_plot_data = ObservationPlotData(key)
observation_plot_data.setObservationData(ensemble_data["x"], ensemble_data["y"], ensemble_data["std"], ensemble_data["continuous"])
observation_plot_data.updateBoundaries(ensemble_data["min_x"], ensemble_data["max_x"], ensemble_data["min_y"], ensemble_data["max_y"])
plot_data.setObservationData(observation_plot_data)
for case in cases:
ensemble_data = gen_data_fetcher.fetchData(key, case)
if len(ensemble_data) > 0:
ensemble_plot_data = EnsemblePlotData(key, case)
ensemble_plot_data.setEnsembleData(ensemble_data["x"], ensemble_data["y"], ensemble_data["min_y_values"], ensemble_data["max_y_values"])
ensemble_plot_data.updateBoundaries(ensemble_data["min_x"], ensemble_data["max_x"], ensemble_data["min_y"], ensemble_data["max_y"])
plot_data.addEnsembleData(ensemble_plot_data)
return plot_data
def addObservationData(self,
plot_data,
key,
fetcher,
histogram_factory=None):
observation_data = fetcher.fetchData(key)
observation_plot_data = ObservationPlotData(key)
observation_plot_data.setObservationData(
observation_data["x"], observation_data["y"],
observation_data["std"], observation_data["continuous"])
observation_plot_data.updateBoundaries(observation_data["min_x"],
observation_data["max_x"],
observation_data["min_y"],
observation_data["max_y"])
plot_data.setObservationData(observation_plot_data)
if histogram_factory is not None:
histogram_factory.setObservations(observation_data["x"],
observation_data["y"],
observation_data["std"],
observation_data["min_y"],
observation_data["max_y"])