def getPlotDataForKeyAndCases(self, key, cases):
observation_data_fetcher = ObservationDataFetcher(self.ert())
block_observation_data_fetcher = BlockObservationDataFetcher(
self.ert())
gen_kw_fetcher = EnsembleGenKWFetcher(self.ert())
gen_data_fetcher = EnsembleGenDataFetcher(self.ert())
if self.isBlockObservationKey(key):
return self.fetchBlockObservationData(
block_observation_data_fetcher, key, cases)
elif self.isSummaryKey(key):
return self.fetchSummaryData(observation_data_fetcher, key, cases)
elif self.isGenKWKey(key):
return self.fetchGenKWData(gen_kw_fetcher, key, cases)
elif self.isGenDataKey(key):
return self.fetchGenData(gen_data_fetcher, key, cases)
elif self.isPcaDataKey(key):
plot_data = PlotData(key)
pca_plot_data = self.fetchPcaData(key, cases)
plot_data.setUserData("PCA", pca_plot_data)
return plot_data
else:
raise NotImplementedError("Key %s not supported." % key)
def getPlotDataForKeyAndCases(self, key, cases):
observation_data_fetcher = ObservationDataFetcher(self.ert())
block_observation_data_fetcher = BlockObservationDataFetcher(self.ert())
gen_kw_fetcher = EnsembleGenKWFetcher(self.ert())
gen_data_fetcher = EnsembleGenDataFetcher(self.ert())
if self.isBlockObservationKey(key):
return self.fetchBlockObservationData(block_observation_data_fetcher, key, cases)
elif self.isSummaryKey(key):
return self.fetchSummaryData(observation_data_fetcher, key, cases)
elif self.isGenKWKey(key):
return self.fetchGenKWData(gen_kw_fetcher, key, cases)
elif self.isGenDataKey(key):
return self.fetchGenData(gen_data_fetcher, key, cases)
elif self.isPcaDataKey(key):
plot_data = PlotData(key)
pca_plot_data = self.fetchPcaData(key, cases)
plot_data.setUserData("PCA", pca_plot_data)
return plot_data
else:
raise NotImplementedError("Key %s not supported." % key)
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 fetchGenKWData(self, gen_kw_fetcher, key, cases):
plot_data = PlotData(key)
histogram_factory = ReportStepLessHistogramPlotDataFactory(key)
self.addEnsembleData(plot_data, key, cases, gen_kw_fetcher, histogram_factory)
plot_data.setHistogramFactory(histogram_factory)
return plot_data
def fetchGenKWData(self, gen_kw_fetcher, key, cases):
plot_data = PlotData(key)
histogram_factory = ReportStepLessHistogramPlotDataFactory(key)
self.addEnsembleData(plot_data, key, cases, gen_kw_fetcher,
histogram_factory)
plot_data.setHistogramFactory(histogram_factory)
return plot_data
def fetchBlockObservationData(self, block_observation_data_fetcher, key, cases):
plot_data = PlotData(key)
plot_data.setUnitY(self.ert().eclConfig().getDepthUnit())
plot_data.setUnitX(self.ert().eclConfig().getPressureUnit())
if block_observation_data_fetcher.hasData(key):
block_observation_data_fetcher.setSelectedReportStepIndex(0)
self.addObservationData(plot_data, key, block_observation_data_fetcher)
ensemble_block_data_fetcher = EnsembleBlockDataFetcher(self.ert())
ensemble_block_data_fetcher.setSelectedReportStepIndex(0)
self.addEnsembleData(plot_data, key, cases, ensemble_block_data_fetcher)
self.addPcaData(plot_data, key, cases)
return plot_data
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 fetchGenKWData(self, gen_kw_fetcher, key, cases):
plot_data = PlotData(key)
histogram_factory = ReportStepLessHistogramPlotDataFactory(key)
for case in cases:
ensemble_data = gen_kw_fetcher.fetchData(key, case)
ensemble_plot_data = EnsemblePlotData(key, case)
ensemble_plot_data.setEnsembleData(ensemble_data["x"], ensemble_data["y"], None, None)
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)
histogram_factory.addEnsembleData(case, ensemble_data["x"], ensemble_data["y"], ensemble_data["min_y"], ensemble_data["max_y"])
plot_data.setHistogramFactory(histogram_factory)
return plot_data
def fetchGenData(self, gen_data_fetcher, key, cases):
plot_data = PlotData(key)
gen_data_observation_fetcher = ObservationGenDataFetcher(self.ert())
if gen_data_observation_fetcher.hasData(key):
self.addObservationData(plot_data, key,
gen_data_observation_fetcher)
self.addEnsembleData(plot_data, key, cases, gen_data_fetcher)
self.addPcaData(plot_data, key, cases)
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 fetchSummaryData(self, observation_data_fetcher, key, cases):
plot_data = PlotData(key)
histogram_factory = HistogramPlotDataFactory(key)
refcase_fetcher = RefcaseDataFetcher(self.ert())
self.addObservationData(plot_data, key, observation_data_fetcher,
histogram_factory)
self.addRefcaseData(plot_data, key, refcase_fetcher, histogram_factory)
self.addEnsembleData(plot_data, key, cases,
EnsembleDataFetcher(self.ert()),
histogram_factory)
self.addPcaData(plot_data, key, cases)
if refcase_fetcher.hasRefcase():
unit = refcase_fetcher.getRefCase().unit(key)
if unit != "":
plot_data.setUnitY(unit)
plot_data.setHistogramFactory(histogram_factory)
return plot_data
def fetchSummaryData(self, observation_data_fetcher, key, cases):
plot_data = PlotData(key)
histogram_factory = HistogramPlotDataFactory(key)
refcase_fetcher = RefcaseDataFetcher(self.ert())
self.addObservationData(plot_data, key, observation_data_fetcher, histogram_factory)
self.addRefcaseData(plot_data, key, refcase_fetcher, histogram_factory)
self.addEnsembleData(plot_data, key, cases, EnsembleDataFetcher(self.ert()), histogram_factory)
self.addPcaData(plot_data, key, cases)
if refcase_fetcher.hasRefcase():
unit = refcase_fetcher.getRefCase().unit(key)
if unit != "":
plot_data.setUnitY(unit)
plot_data.setHistogramFactory(histogram_factory)
return 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 __init__(self, web_page, plot_url):
QObject.__init__(self)
assert isinstance(web_page, QWebPage)
self.__web_page = web_page
self.__ready = False
self.__html_ready = False
self.__data = PlotData("invalid", parent=self)
self.__size = None
self.__temporary_data_object = None
self.applyContextObject()
root_path = os.getenv("ERT_SHARE_PATH")
path = os.path.join(root_path, plot_url)
self.__web_page.mainFrame().load(QUrl("file://%s" % path))
self.__web_page.loadFinished.connect(self.loadFinished)
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)
plot_data.setUnitY(self.ert().eclConfig().getDepthUnit())
plot_data.setUnitX(self.ert().eclConfig().getPressureUnit())
if block_observation_data_fetcher.hasData(key):
block_observation_data_fetcher.setSelectedReportStepIndex(0)
self.addObservationData(plot_data, key,
block_observation_data_fetcher)
ensemble_block_data_fetcher = EnsembleBlockDataFetcher(self.ert())
ensemble_block_data_fetcher.setSelectedReportStepIndex(0)
self.addEnsembleData(plot_data, key, cases,
ensemble_block_data_fetcher)
self.addPcaData(plot_data, key, cases)
return plot_data
def addPcaData(self, plot_data, key, cases):
if plot_data.hasObservationData() and plot_data.hasEnsembleData():
plot_data.setUserData("PCA", self.fetchPcaData(key, cases))
else:
plot_data.setUserData(
"PCA", PlotData("No ensemble data available for %s" % key))
