Source code for src.toolbox.steps.custom.qc.impossible_range_qc

# This file is part of the NOC Autonomy Toolbox.
#
# Copyright 2025-2026 National Oceanography Centre and The Contributors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""QC test(s) for flagging based on value ranges."""

#### Mandatory imports ####
import numpy as np
from toolbox.steps.base_qc import BaseQC, register_qc, flag_cols

#### Custom imports ####
import matplotlib.pyplot as plt
import xarray as xr
import matplotlib


@register_qc
[docs] class impossible_range_qc(BaseQC): """ Target Variable: Any Flag Number: Any Variables Flagged: Any Checks that a meausurement is within a reasonable range. EXAMPLE ------- - name: "Apply QC" parameters: qc_settings: { "impossible range qc": { "variable_ranges": {"PRES": {3: [-2, 0], 4: [-999, -2]}, "LATITUDE": {4: [-90, 90]}}, "also_flag": {"PRES": ["CNDC", "TEMP"], "LATITUDE": ["LONGITUDE"]}, "plot": ["PRES", "LATITUDE"] "test_depth_range": [-100, 0] # OPTIONAL } } diagnostics: true """
[docs] qc_name = "impossible range qc"
# Specify if test target variable is user-defined (if True, __init__ has to be redefined)
[docs] dynamic = True
def __init__(self, data, **kwargs): # Check the necessary kwargs are available required_kwargs = {"variable_ranges", "also_flag", "plot"} if not required_kwargs.issubset(set(kwargs.keys())): raise KeyError( f"{required_kwargs - set(kwargs.keys())} are missing from {self.qc_name} settings" ) # Specify the tests paramters from kwargs (config)
[docs] self.expected_parameters = { k: v for k, v in kwargs.items() if k in required_kwargs }
[docs] self.required_variables = list( set(self.expected_parameters["variable_ranges"].keys()) )
[docs] self.tested_variables = self.required_variables.copy()
if "test_depth_range" in kwargs.keys(): self.required_variables.append("DEPTH") self.test_depth_range = kwargs["test_depth_range"]
[docs] self.qc_outputs = list( set(f"{var}_QC" for var in self.tested_variables) | set( f"{var}_QC" for var in sum(self.expected_parameters["also_flag"].values(), []) ) )
if data is not None: self.data = data.copy(deep=True) for k, v in self.expected_parameters.items(): setattr(self, k, v)
[docs] self.flags = None
[docs] def return_qc(self): # Subset the data self.data = self.data[self.required_variables] # If the user specified a depth range, limit the checks to that range if hasattr(self, "test_depth_range"): # TODO: -DEPTH depth_range_mask = (self.data["DEPTH"] >= self.test_depth_range[0]) & ( self.data["DEPTH"] <= self.test_depth_range[1] ) else: depth_range_mask = True # Make the empty QC columns for var in self.tested_variables: self.data[f"{var}_QC"] = ( ["N_MEASUREMENTS"], np.full(len(self.data[var]), 0), ) # Generate the variable-specific flags for var, meta in self.variable_ranges.items(): for flag, bounds in meta.items(): self.data[f"{var}_QC"] = xr.where( ( depth_range_mask & (self.data[var] > bounds[0]) & (self.data[var] < bounds[1]) & (self.data[f"{var}_QC"] == 0) ), flag, 0, ) # Replace all remaining 0s (unchecked) with 1s (good) self.data[f"{var}_QC"] = xr.where( depth_range_mask & (self.data[f"{var}_QC"] == 0), 1, self.data[f"{var}_QC"], ) # Broadcast the QC found for var into variables specified by "also_flag" if extra_vars := self.also_flag.get(var): for extra_var in extra_vars: self.data[f"{extra_var}_QC"] = self.data[f"{var}_QC"] # Select just the flags self.flags = self.data[ [var_qc for var_qc in self.data.data_vars if "_QC" in var_qc] ] return self.flags
[docs] def plot_diagnostics(self): matplotlib.use("tkagg") # If not plots were specified if len(self.plot) == 0: print( "WARNING: In 'range test' diagnostics were called but no plots were specified." ) return # Plot the QC output fig, axs = plt.subplots(nrows=len(self.plot), figsize=(8, 6), dpi=200) if len(self.plot) == 1: axs = [axs] for ax, var in zip(axs, self.plot): # Check that the user specified var exists in the test set if f"{var}_QC" not in self.qc_outputs: print( f"WARNING: Cannot plot {var}_QC as it was not included in this test." ) continue for i in range(10): # Plot by flag number plot_data = self.data[[var, "N_MEASUREMENTS"]].where( self.data[f"{var}_QC"] == i, drop=True ) if len(plot_data[var]) == 0: continue # Plot the data ax.plot( plot_data["N_MEASUREMENTS"], plot_data[var], c=flag_cols[i], ls="", marker="o", label=f"{i}", ) for bounds in self.variable_ranges[var].values(): for bound in bounds: ax.axhline(bound, ls="--", c="k") ax.set( xlabel="Index", ylabel=var, title=f"{var} Range Test", ) ax.legend(title="Flags", loc="upper right") fig.tight_layout() plt.show(block=True)