Python ParameterContext.description方法代码示例

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_grt_qc(self, name, data_product):
        pfunc_id, pfunc = self.find_grt() 
        grt_min_id, grt_min_name = self.get_lookup_value('LV_grt_$designator_%s||grt_min_value' % data_product)
        grt_max_id, grt_max_name = self.get_lookup_value('LV_grt_$designator_%s||grt_max_value' % data_product)

        pmap = {'dat':name, 'dat_min':grt_min_name,'dat_max':grt_max_name}
        pfunc.param_map = pmap
        pfunc.lookup_values = [grt_min_id, grt_max_id]
        dp_name = self.dp_name(data_product)
        pc = ParameterContext(name='%s_glblrng_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = '%s_GLBLRNG_QC' % dp_name
        pc.display_name = '%s Global Range Test Quality Control Flag' % dp_name
        pc.description = "The OOI Global Range quality control algorithm generates a QC flag for the input data point indicating whether it falls within a given range."
        ctxt_id = self.dataset_management.create_parameter_context(name='%s_glblrng_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_stuckvalue_qc(self, name, data_product):
        pfunc_id, pfunc = self.find_stuck_value()

        reso_id, reso_name = self.get_lookup_value('LV_svt_$designator_%s||svt_resolution' % data_product)
        n_id, n_name = self.get_lookup_value('LV_svt_$designator_%s||svt_n' % data_product)

        pmap = {'x' : name, 'reso': reso_name, 'num': n_name}
        pfunc.param_map = pmap
        pfunc.lookup_values = [reso_id, n_id]
        dp_name = self.dp_name(data_product)
        pc = ParameterContext(name='%s_stuckvl_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = '%s_STUCKVL_QC' % dp_name
        pc.display_name = '%s Stuck Value Test Quality Control Flag' % dp_name
        pc.description =  'The OOI Stuck Value Test quality control algorithm generates a flag for repeated occurrence of one value in a time series.'

        ctxt_id = self.dataset_management.create_parameter_context(name='%s_stuckvl_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_propagate_qc(self,inputs):

        pfunc_id, pfunc = self.find_propagate_test()
        pmap = {"strict_validation":False}
        arg_list = ['strict_validation']
        for i,val in enumerate(inputs):
            if i >= 100:
                break
            pmap['array%s' % i] = val
            arg_list.append('array%s' % i)
        pfunc.param_map = pmap
        pfunc.arg_list = arg_list
        pc = ParameterContext(name='cmbnflg_qc', param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = 'CMBNFLG_QC' 
        pc.display_name = 'Combined Data Quality Control Flag' 
        pc.description = 'The purpose of this computation is to produce a single merged QC flag from a set of potentially many flags.'
        ctxt_id = self.dataset_management.create_parameter_context(name='cmbnflg_qc', parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_trendtest_qc(self, name, data_product):

        pfunc_id, pfunc = self.find_trend_test()

        order_id, order_name = self.get_lookup_value('LV_trend_$designator_%s||polynomial_order' % data_product)
        dev_id, dev_name = self.get_lookup_value('LV_trend_$designator_%s||standard_deviation' % data_product)

        pmap = {"dat":name ,"t":'time',"ord_n":order_name,"ntsd":dev_name}

        pfunc.param_map = pmap
        pfunc.lookup_values = [order_id, dev_id]
        dp_name = self.dp_name(data_product)
        pc = ParameterContext(name='%s_trndtst_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc,value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = '%s_TRNDTST_QC' % dp_name
        pc.display_name = '%s Trend Test Test Quality Control Flag' % dp_name
        pc.description = 'The OOI Trend Test quality control algorithm generates flags on data values within a time series where a significant fraction of the variability in the time series can be explained by a drift, where the drift is assumed to be a polynomial of specified order.'
        ctxt_id = self.dataset_management.create_parameter_context(name='%s_trndtst_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_spike_qc(self, name, data_product):
        pfunc_id, pfunc = self.find_spike()
        spike_acc_id, spike_acc_name = self.get_lookup_value('LV_spike_$designator_%s||acc' % data_product)
        spike_n_id, spike_n_name = self.get_lookup_value('LV_spike_$designator_%s||spike_n' % data_product)
        spike_l_id, spike_l_name = self.get_lookup_value('LV_spike_$designator_%s||spike_l' % data_product)

        pmap = {'dat':name, 'acc':spike_acc_name, 'N':spike_n_name, 'L':spike_l_name}
        pfunc.param_map = pmap
        pfunc.lookup_values = [spike_acc_id, spike_n_id, spike_l_id]
        dp_name = self.dp_name(data_product)
        pc = ParameterContext(name='%s_spketst_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom='1'
        pc.ooi_short_name = '%s_SPKETST_QC' % dp_name
        pc.display_name = '%s Spike Test Quality Control Flag' % dp_name

        pc.description = "The OOI Spike Test quality control algorithm generates a flag for individual data values that deviate significantly from surrounding data values."

        ctxt_id = self.dataset_management.create_parameter_context(name='%s_spketst_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_localrange_qc(self, name, data_product):

        pfunc_id, pfunc = self.find_localrange_test()

        datlim_id, datlim = self.get_array_lookup_value('LV_lrt_$designator_%s||datlim' % data_product)
        datlimz_id, datlimz = self.get_array_lookup_value('LV_lrt_$designator_%s||datlimz' % data_product)
        dims_id, dims = self.get_string_array_lookup_value('LV_lrt_$designator_%s||dims' % data_product)

        pmap = {"dat":name, "dims*":dims, "datlim*":datlim, "datlimz*":datlimz}
        pfunc.param_map = pmap
        pfunc.lookup_values = [datlim_id, datlimz_id, dims_id]
        dp_name = self.dp_name(data_product)

        pc = ParameterContext(name='%s_loclrng_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = '%s_LOCLRNG_QC' % dp_name
        pc.display_name = '%s Local Range Test Quality Control Flag' % dp_name
        pc.description = 'The OOI Local Range Test is the computation to test whether a given data point falls within pre-defined ranges.'
        ctxt_id = self.dataset_management.create_parameter_context(name='%s_loclrng_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc

# 需要导入模块: from coverage_model import ParameterContext [as 别名]
# 或者: from coverage_model.ParameterContext import description [as 别名]
    def make_gradienttest_qc(self, name, data_product):

        pfunc_id, pfunc = self.find_gradient_test()

        ddatdx_id, ddatdx = self.get_lookup_value('LV_grad_$designator_%s_time||d_dat_dx' % data_product)
        mindx_id, mindx = self.get_lookup_value('LV_grad_$designator_%s_time||min_dx' % data_product)
        startdat_id, startdat = self.get_lookup_value('LV_grad_$designator_%s_time||start_dat' % data_product)
        toldat_id, toldat = self.get_lookup_value('LV_grad_$designator_%s_time||tol_dat' % data_product)

        pmap = {"dat":name, "x": 'time', 'ddatdx': ddatdx, 'mindx':mindx, 'startdat': startdat, 'toldat':toldat}
        pfunc.param_map = pmap
        pfunc.lookup_values = [ddatdx_id, mindx_id, startdat_id, toldat_id]
        dp_name = self.dp_name(data_product)

        pc = ParameterContext(name='%s_gradtst_qc' % dp_name.lower(), param_type=ParameterFunctionType(pfunc, value_encoding='|i1'))
        pc.uom = '1'
        pc.ooi_short_name = '%s_GRADTST_QC' % dp_name
        pc.display_name = '%s Gradient Test Quality Control Flag' % dp_name
        pc.description = 'The OOI Gradient Test is an automated quality control algorithm used on various OOI data products. This automated algorithm generates flags for data points according to whether changes between successive points are within a pre-determined range.'
        ctxt_id = self.dataset_management.create_parameter_context(name='%s_gradtst_qc' % dp_name.lower(), parameter_type='function', parameter_context=pc.dump(), parameter_function_id=pfunc_id, ooi_short_name=pc.ooi_short_name, units='1', value_encoding='int8', display_name=pc.display_name, description=pc.description)
        return ctxt_id, pc