The Py-ART Radar object and indexing

# The Py-ART radar object has functions and attributes that allow for a more
# in depth look of the data and the radar object.

# Import needed modules
import numpy as np
import pyart

## You are using the Python ARM Radar Toolkit (Py-ART), an open source
## library for working with weather radar data. Py-ART is partly
## supported by the U.S. Department of Energy as part of the Atmospheric
## Radiation Measurement (ARM) Climate Research Facility, an Office of
## Science user facility.
##
## If you use this software to prepare a publication, please cite:
##
##     JJ Helmus and SM Collis, JORS 2016, doi: 10.5334/jors.119

# Load the radar file
radar = pyart.io.read("KATX20130717_195021_V06")

# For a detailed print of the Py-ART radar object, use radar.info()
radar.info()

altitude:
	data: <ndarray of type: float64 and shape: (1,)>
	long_name: Altitude
	standard_name: Altitude
	units: meters
	positive: up
altitude_agl: None
antenna_transition: None
azimuth:
	data: <ndarray of type: float64 and shape: (7200,)>
	units: degrees
	standard_name: beam_azimuth_angle
	long_name: azimuth_angle_from_true_north
	axis: radial_azimuth_coordinate
	comment: Azimuth of antenna relative to true north
elevation:
	data: <ndarray of type: float32 and shape: (7200,)>
	units: degrees
	standard_name: beam_elevation_angle
	long_name: elevation_angle_from_horizontal_plane
	axis: radial_elevation_coordinate
	comment: Elevation of antenna relative to the horizontal plane
fields:
	differential_reflectivity:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: dB
		standard_name: log_differential_reflectivity_hv
		long_name: log_differential_reflectivity_hv
		valid_max: 7.9375
		valid_min: -7.875
		coordinates: elevation azimuth range
		_FillValue: -9999.0
	differential_phase:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: degrees
		standard_name: differential_phase_hv
		long_name: differential_phase_hv
		valid_max: 360.0
		valid_min: 0.0
		coordinates: elevation azimuth range
		_FillValue: -9999.0
	reflectivity:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: dBZ
		standard_name: equivalent_reflectivity_factor
		long_name: Reflectivity
		valid_max: 94.5
		valid_min: -32.0
		coordinates: elevation azimuth range
		_FillValue: -9999.0
	cross_correlation_ratio:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: ratio
		standard_name: cross_correlation_ratio_hv
		long_name: Cross correlation_ratio (RHOHV)
		valid_max: 1.0
		valid_min: 0.0
		coordinates: elevation azimuth range
		_FillValue: -9999.0
	spectrum_width:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: meters_per_second
		standard_name: doppler_spectrum_width
		long_name: Spectrum Width
		valid_max: 63.0
		valid_min: -63.5
		coordinates: elevation azimuth range
		_FillValue: -9999.0
	velocity:
		data: <ndarray of type: float32 and shape: (7200, 1832)>
		units: meters_per_second
		standard_name: radial_velocity_of_scatterers_away_from_instrument
		long_name: Mean doppler Velocity
		valid_max: 95.0
		valid_min: -95.0
		coordinates: elevation azimuth range
		_FillValue: -9999.0
fixed_angle:
	data: <ndarray of type: float32 and shape: (16,)>
	long_name: Target angle for sweep
	units: degrees
	standard_name: target_fixed_angle
instrument_parameters:
	unambiguous_range:
		data: <ndarray of type: float32 and shape: (7200,)>
		units: meters
		comments: Unambiguous range
		meta_group: instrument_parameters
		long_name: Unambiguous range
	nyquist_velocity:
		data: <ndarray of type: float32 and shape: (7200,)>
		units: meters_per_second
		comments: Unambiguous velocity
		meta_group: instrument_parameters
		long_name: Nyquist velocity
latitude:
	data: <ndarray of type: float64 and shape: (1,)>
	long_name: Latitude
	standard_name: Latitude
	units: degrees_north
longitude:
	data: <ndarray of type: float64 and shape: (1,)>
	long_name: Longitude
	standard_name: Longitude
	units: degrees_east
nsweeps: 16
ngates: 1832
nrays: 7200
radar_calibration: None
range:
	data: <ndarray of type: float32 and shape: (1832,)>
	units: meters
	standard_name: projection_range_coordinate
	long_name: range_to_measurement_volume
	axis: radial_range_coordinate
	spacing_is_constant: true
	comment: Coordinate variable for range. Range to center of each bin.
	meters_to_center_of_first_gate: 2125.0
	meters_between_gates: 250.0
scan_rate: None
scan_type: ppi
sweep_end_ray_index:
	data: <ndarray of type: int32 and shape: (16,)>
	long_name: Index of last ray in sweep, 0-based
	units: count
sweep_mode:
	data: <ndarray of type: |S20 and shape: (16,)>
	units: unitless
	standard_name: sweep_mode
	long_name: Sweep mode
	comment: Options are: "sector", "coplane", "rhi", "vertical_pointing", "idle", "azimuth_surveillance", "elevation_surveillance", "sunscan", "pointing", "manual_ppi", "manual_rhi"
sweep_number:
	data: <ndarray of type: int32 and shape: (16,)>
	units: count
	standard_name: sweep_number
	long_name: Sweep number
sweep_start_ray_index:
	data: <ndarray of type: int32 and shape: (16,)>
	long_name: Index of first ray in sweep, 0-based
	units: count
target_scan_rate: None
time:
	data: <ndarray of type: float64 and shape: (7200,)>
	units: seconds since 2013-07-17T19:50:21Z
	standard_name: time
	long_name: time_in_seconds_since_volume_start
	calendar: gregorian
	comment: Coordinate variable for time. Time at the center of each ray, in fractional seconds since the global variable time_coverage_start
metadata:
	Conventions: CF/Radial instrument_parameters
	version: 1.3
	title: 
	institution: 
	references: 
	source: 
	history: 
	comment: 
	instrument_name: KATX
	original_container: NEXRAD Level II
	vcp_pattern: 11

# Let's view the elevation parameter. Py-ART stores all fields as 2D masked arrays
# of dimensions (number of rays) x (number of gates). Therefore, as the elevation can change with
# each ray, the data in the elevation array is a 1D array of dimension (number of rays)
radar.elevation

{'units': 'degrees',
 'standard_name': 'beam_elevation_angle',
 'long_name': 'elevation_angle_from_horizontal_plane',
 'axis': 'radial_elevation_coordinate',
 'comment': 'Elevation of antenna relative to the horizontal plane',
 'data': array([ 0.7470703,  0.7196045,  0.6893921, ..., 19.511719 , 19.511719 ,
        19.511719 ], dtype=float32)}

# If we just want the elevations of one sweep, we can use the get_slice() function
# of the Radar object to just get the elevations from one slice.
sweep_1 = radar.get_slice(1)
print(radar.elevation["data"][sweep_1])

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# All of the radar fields are stored in a dictionary called radar.fields. This dictionary
# contains entries that correspond to the field names in the file.
radar.fields["reflectivity"]

{'units': 'dBZ',
 'standard_name': 'equivalent_reflectivity_factor',
 'long_name': 'Reflectivity',
 'valid_max': 94.5,
 'valid_min': -32.0,
 'coordinates': 'elevation azimuth range',
 '_FillValue': -9999.0,
 'data': masked_array(
   data=[[10.5, 7.5, --, ..., --, --, --],
         [--, --, --, ..., --, --, --],
         [9.5, --, --, ..., --, --, --],
         ...,
         [-10.5, -15.0, -9.5, ..., --, --, --],
         [-14.0, -13.5, -13.5, ..., --, --, --],
         [-11.0, -15.0, 0.5, ..., --, --, --]],
   mask=[[False, False,  True, ...,  True,  True,  True],
         [ True,  True,  True, ...,  True,  True,  True],
         [False,  True,  True, ...,  True,  True,  True],
         ...,
         [False, False, False, ...,  True,  True,  True],
         [False, False, False, ...,  True,  True,  True],
         [False, False, False, ...,  True,  True,  True]],
   fill_value=1e+20,
   dtype=float32)}

# This shows entries such as the data itself, coordinates, long name, and units. You can
# access the array with the reflectivity data itself using radar.fields['reflectivity']['data'].
# This is stored as a 2D masked array with dimensions (number of rays) x (number of gates)
radar.fields["reflectivity"]["data"]

masked_array(
  data=[[10.5, 7.5, --, ..., --, --, --],
        [--, --, --, ..., --, --, --],
        [9.5, --, --, ..., --, --, --],
        ...,
        [-10.5, -15.0, -9.5, ..., --, --, --],
        [-14.0, -13.5, -13.5, ..., --, --, --],
        [-11.0, -15.0, 0.5, ..., --, --, --]],
  mask=[[False, False,  True, ...,  True,  True,  True],
        [ True,  True,  True, ...,  True,  True,  True],
        [False,  True,  True, ...,  True,  True,  True],
        ...,
        [False, False, False, ...,  True,  True,  True],
        [False, False, False, ...,  True,  True,  True],
        [False, False, False, ...,  True,  True,  True]],
  fill_value=1e+20,
  dtype=float32)

# If you just want the data from one slice, you can get the indicies for the
# slice using radar.get_slice()
slice_indices = radar.get_slice(0)
print(radar.fields["reflectivity"]["data"][slice_indices])

[[10.5 7.5 -- ... -- -- --]
 [-- -- -- ... -- -- --]
 [9.5 -- -- ... -- -- --]
 ...
 [-- 6.0 11.0 ... -- -- --]
 [-- -- -- ... -- -- --]
 [-- -- -- ... -- -- --]]

# You can also iterate over each slice by using radar.iter_slice() This example
# returns the mean reflectivity of each sweep.
reflectivity = [
    radar.fields["reflectivity"]["data"][x].mean() for x in radar.iter_slice()
]
print(reflectivity)

[-2.9066728410400056, -3.478547577741713, -6.587792083929423, -6.871031288639269, -10.971692217963673, -11.830616390843327, -12.108188248095756, -12.483419908190385, -12.88976917057903, -11.852766685681688, -12.410455582269897, -12.66444787446138, -12.997862391449566, -13.172098402018502, -13.489752513534416, -13.712565619531706]

# You can also view the important radar instrument parameters. One commonly used parameter
# is the nyquist velocity, which is the maximum magnitude of the velocity the radar is
# capable of recording before a phenomena known as aliasing occurs.
radar.instrument_parameters["nyquist_velocity"]["data"]

array([ 8.81,  8.81,  8.81, ..., 32.33, 32.33, 32.33], dtype=float32)