Merge branch 'main' of https://github.com/mgrover1/pyart

pyart/xradar/accessor.py

@@ -4,9 +4,176 @@
 """
 
 
+import copy
+from collections.abc import Hashable, Mapping
+from typing import Any, overload
+
+import numpy as np
+import pandas as pd
+from datatree import DataTree, formatting, formatting_html
+from datatree.treenode import NodePath
+from xarray import DataArray, Dataset, concat
+from xarray.core import utils
+
+
 class Xradar:
-    def __init__(self, xradar):
+    def __init__(self, xradar, default_sweep="sweep_0"):
         self.xradar = xradar
+        self.scan_type = "ppi"
+        self.combined_sweeps = self._combine_sweeps(self.xradar)
+        self.fields = self._find_fields(self.combined_sweeps)
+        self.scan_type = None
+        self.time = dict(
+            data=(self.combined_sweeps.time - self.combined_sweeps.time.min()).astype(
+                "int64"
+            )
+            / 1e9,
+            units=f"seconds since {pd.to_datetime(self.combined_sweeps.time.min().values).strftime('%Y-%m-%d %H:%M:%S.0')}",
+            calendar="gregorian",
+        )
+        self.range = dict(data=self.combined_sweeps.range.values)
+        self.azimuth = dict(data=self.combined_sweeps.azimuth.values)
+        self.elevation = dict(data=self.combined_sweeps.elevation.values)
+        self.fixed_angle = dict(data=self.combined_sweeps.sweep_fixed_angle.values)
+        self.antenna_transition = None
+        self.latitude = dict(data=self.xradar["latitude"].values)
+        self.longitude = dict(data=self.xradar["longitude"].values)
+        self.sweep_end_ray_index = dict(
+            data=self.combined_sweeps.ngates.groupby("sweep_number").max().values
+        )
+        self.sweep_start_ray_index = dict(
+            data=self.combined_sweeps.ngates.groupby("sweep_number").min().values
+        )
+        self.metadata = dict(**self.xradar.attrs)
+        self.ngates = len(self.range["data"])
+        self.nrays = len(self.azimuth["data"])
+        self.nsweeps = len(self.xradar.sweep_group_name)
+        self.instrument_parameters = dict(**self.xradar["radar_parameters"].attrs)
+
+    def __repr__(self):
+        return formatting.datatree_repr(self.xradar)
+
+    def _repr_html_(self):
+        return formatting_html.datatree_repr(self.xradar)
+
+    @overload
+    def __getitem__(self, key: Mapping) -> Dataset:  # type: ignore[misc]
+        ...
+
+    @overload
+    def __getitem__(self, key: Hashable) -> DataArray:  # type: ignore[misc]
+        ...
+
+    @overload
+    def __getitem__(self, key: Any) -> Dataset:
+        ...
+
+    def __getitem__(self: DataTree, key: str) -> DataTree | DataArray:
+        """
+        Access child nodes, variables, or coordinates stored anywhere in this tree.
+
+        Returned object will be either a DataTree or DataArray object depending on whether the key given points to a
+        child or variable.
+
+        Parameters
+        ----------
+        key : str
+            Name of variable / child within this node, or unix-like path to variable / child within another node.
+
+        Returns
+        -------
+        Union[DataTree, DataArray]
+        """
+
+        # Either:
+        if utils.is_dict_like(key):
+            # dict-like indexing
+            raise NotImplementedError("Should this index over whole tree?")
+        elif isinstance(key, str):
+            # path-like: a name of a node/variable, or path to a node/variable
+            path = NodePath(key)
+            return self.xradar._get_item(path)
+        elif utils.is_list_like(key):
+            # iterable of variable names
+            raise NotImplementedError(
+                "Selecting via tags is deprecated, and selecting multiple items should be "
+                "implemented via .subset"
+            )
+        else:
+            raise ValueError(f"Invalid format for key: {key}")
+
+        # Iterators
+
+    def iter_start(self):
+        """Return an iterator over the sweep start indices."""
+        return (s for s in self.sweep_start_ray_index["data"])
+
+    def iter_end(self):
+        """Return an iterator over the sweep end indices."""
+        return (s for s in self.sweep_end_ray_index["data"])
+
+    def iter_start_end(self):
+        """Return an iterator over the sweep start and end indices."""
+        return ((s, e) for s, e in zip(self.iter_start(), self.iter_end()))
+
+    def iter_slice(self):
+        """Return an iterator which returns sweep slice objects."""
+        return (slice(s, e + 1) for s, e in self.iter_start_end())
+
+    def iter_field(self, field_name):
+        """Return an iterator which returns sweep field data."""
+        self.check_field_exists(field_name)
+        return (self.fields[field_name]["data"][s] for s in self.iter_slice())
+
+    def iter_azimuth(self):
+        """Return an iterator which returns sweep azimuth data."""
+        return (self.azimuth["data"][s] for s in self.iter_slice())
+
+    def iter_elevation(self):
+        """Return an iterator which returns sweep elevation data."""
+        return (self.elevation["data"][s] for s in self.iter_slice())
+
+    def add_field(self, field_name, dic, replace_existing=False):
+        """
+        Add a field to the object.
+
+        Parameters
+        ----------
+        field_name : str
+            Name of the field to add to the dictionary of fields.
+        dic : dict
+            Dictionary contain field data and metadata.
+        replace_existing : bool, optional
+            True to replace the existing field with key field_name if it
+            exists, loosing any existing data. False will raise a ValueError
+            when the field already exists.
+
+        """
+        # check that the field dictionary to add is valid
+        if field_name in self.fields and replace_existing is False:
+            err = "A field with name: %s already exists" % (field_name)
+            raise ValueError(err)
+        if "data" not in dic:
+            raise KeyError("dic must contain a 'data' key")
+        if dic["data"].shape != (self.nrays, self.ngates):
+            t = (self.nrays, self.ngates)
+            err = "'data' has invalid shape, should be (%i, %i)" % t
+            raise ValueError(err)
+        # add the field
+        self.fields[field_name] = dic
+        for sweep in range(self.nsweeps):
+            sweep_ds = (
+                self.xradar[f"sweep_{sweep}"].to_dataset().drop_duplicates("azimuth")
+            )
+            sweep_ds[field_name] = (
+                ("azimuth", "range"),
+                self.fields[field_name]["data"][self.get_slice(sweep)],
+            )
+            attrs = dic.copy()
+            del attrs["data"]
+            sweep_ds[field_name].attrs = attrs
+            self.xradar[f"sweep_{sweep}"].ds = sweep_ds
+        return
 
     def get_field(self, sweep, field_name, copy=False):
         """
@@ -39,6 +206,22 @@ def get_field(self, sweep, field_name, copy=False):
         else:
             return data
 
+    def check_field_exists(self, field_name):
+        """
+        Check that a field exists in the fields dictionary.
+
+        If the field does not exist raise a KeyError.
+
+        Parameters
+        ----------
+        field_name : str
+            Name of field to check.
+
+        """
+        if field_name not in self.fields:
+            raise KeyError("Field not available: " + field_name)
+        return
+
     def get_gate_x_y_z(self, sweep, edges=False, filter_transitions=False):
         """
         Return the x, y and z gate locations in meters for a given sweep.
@@ -75,8 +258,141 @@ def get_gate_x_y_z(self, sweep, edges=False, filter_transitions=False):
 
         """
         # Check to see if the data needs to be georeferenced
-        if "x" not in self.xradar[f"sweep_{0}"].coords:
+        if "x" not in self.xradar[f"sweep_{sweep}"].coords:
             self.xradar = self.xradar.xradar.georeference()
 
         data = self.xradar[f"sweep_{sweep}"].xradar.georeference()
         return data["x"].values, data["y"].values, data["z"].values
+
+    def _combine_sweeps(self, radar):
+        # Loop through and extract the different datasets
+        ds_list = []
+        for sweep in radar.sweep_group_name.values:
+            ds_list.append(radar[sweep].ds.drop_duplicates("azimuth"))
+
+        # Merge based on the sweep number
+        merged = concat(ds_list, dim="sweep_number")
+
+        # Stack the sweep number and azimuth together
+        stacked = merged.stack(gates=["sweep_number", "azimuth"]).transpose()
+
+        # Drop the missing gates
+        cleaned = stacked.where(stacked.time == stacked.time.dropna("gates"))
+
+        # Add in number of gates variable
+        cleaned["ngates"] = ("gates", np.arange(len(cleaned.gates)))
+
+        # Return the non-missing times, ensuring valid data is returned
+        return cleaned
+
+    def add_filter(self, gatefilter, replace_existing=False, include_fields=None):
+        """
+        Updates the radar object with an applied gatefilter provided
+        by the user that masks values in fields within the radar object.
+
+        Parameters
+        ----------
+        gatefilter : GateFilter
+            GateFilter instance. This filter will exclude equal to
+            the conditions provided in the gatefilter and mask values
+            in fields specified or all fields if include_fields is None.
+        replace_existing : bool, optional
+            If True, replaces the fields in the radar object with
+            copies of those fields with the applied gatefilter.
+            False will return new fields with the appended 'filtered_'
+            prefix.
+        include_fields : list, optional
+            List of fields to have filtered applied to. If none, all
+            fields will have applied filter.
+
+        """
+        # If include_fields is None, sets list to all fields to include.
+        if include_fields is None:
+            include_fields = [*self.fields.keys()]
+
+        try:
+            # Replace current fields with masked versions with applied gatefilter.
+            if replace_existing:
+                for field in include_fields:
+                    self.fields[field]["data"] = np.ma.masked_where(
+                        gatefilter.gate_excluded, self.fields[field]["data"]
+                    )
+            # Add new fields with prefix 'filtered_'
+            else:
+                for field in include_fields:
+                    field_dict = copy.deepcopy(self.fields[field])
+                    field_dict["data"] = np.ma.masked_where(
+                        gatefilter.gate_excluded, field_dict["data"]
+                    )
+                    self.add_field(
+                        "filtered_" + field, field_dict, replace_existing=True
+                    )
+
+        # If fields don't match up throw an error.
+        except KeyError:
+            raise KeyError(
+                field + " not found in the original radar object, "
+                "please check that names in the include_fields list "
+                "match those in the radar object."
+            )
+        return
+
+    def get_nyquist_vel(self, sweep, check_uniform=True):
+        """
+        Return the Nyquist velocity in meters per second for a given sweep.
+
+        Raises a LookupError if the Nyquist velocity is not available, an
+        Exception is raised if the velocities are not uniform in the sweep
+        unless check_uniform is set to False.
+
+        Parameters
+        ----------
+        sweep : int
+            Sweep number to retrieve data for, 0 based.
+        check_uniform : bool
+            True to check to perform a check on the Nyquist velocities that
+            they are uniform in the sweep, False will skip this check and
+            return the velocity of the first ray in the sweep.
+
+        Returns
+        -------
+        nyquist_velocity : float
+            Array containing the Nyquist velocity in m/s for a given sweep.
+
+        """
+        s = self.get_slice(sweep)
+        try:
+            nyq_vel = self.instrument_parameters["nyquist_velocity"]["data"][s]
+        except TypeError:
+            raise LookupError("Nyquist velocity unavailable")
+        if check_uniform:
+            if np.any(nyq_vel != nyq_vel[0]):
+                raise Exception("Nyquist velocities are not uniform in sweep")
+        return float(nyq_vel[0])
+
+    def get_start(self, sweep):
+        """Return the starting ray index for a given sweep."""
+        return int(self.combined_sweeps.ngates.sel(sweep_number=sweep).min())
+
+    def get_end(self, sweep):
+        """Return the ending ray for a given sweep."""
+        return self.sweep_end_ray_index["data"][sweep]
+
+    def get_start_end(self, sweep):
+        """Return the starting and ending ray for a given sweep."""
+        return self.get_start(sweep), self.get_end(sweep)
+
+    def get_slice(self, sweep):
+        """Return a slice for selecting rays for a given sweep."""
+        start, end = self.get_start_end(sweep)
+        return slice(start, end + 1)
+
+    def _find_fields(self, ds):
+        fields = {}
+        for field in self.combined_sweeps.variables:
+            if self.combined_sweeps[field].dims == ("gates", "range"):
+                fields[field] = {
+                    "data": self.combined_sweeps[field].values,
+                    **self.combined_sweeps[field].attrs,
+                }
+        return fields

tests/xradar/test_accessor.py

@@ -9,7 +9,6 @@
 def test_get_field(filename=filename):
     dtree = xd.io.open_cfradial1_datatree(
         filename,
-        first_dim="time",
         optional=False,
     )
     radar = pyart.xradar.Xradar(dtree)
@@ -20,11 +19,22 @@ def test_get_field(filename=filename):
 def test_get_gate_x_y_z(filename=filename):
     dtree = xd.io.open_cfradial1_datatree(
         filename,
-        first_dim="time",
         optional=False,
     )
     radar = pyart.xradar.Xradar(dtree)
     x, y, z = radar.get_gate_x_y_z(0)
     assert x.shape == (483, 996)
     assert y.shape == (483, 996)
     assert z.shape == (483, 996)
+
+
+def test_add_field(filename=filename):
+    dtree = xd.io.open_cfradial1_datatree(
+        filename,
+        optional=False,
+    )
+    radar = pyart.xradar.Xradar(dtree)
+    new_field = radar.fields["DBZ"]
+    radar.add_field("reflectivity", new_field)
+    assert "reflectivity" in radar.fields
+    assert radar["sweep_0"]["reflectivity"].shape == radar["sweep_0"]["DBZ"].shape