# Source code for pyart.filters.gatefilter

```
"""
Functions for creating gate filters (masks) which can be used it various
corrections routines in Py-ART.
"""
from copy import deepcopy
import numpy as np
from ..config import get_field_name, get_metadata
from ..util import texture_along_ray
[docs]def moment_based_gate_filter(
radar,
ncp_field=None,
rhv_field=None,
refl_field=None,
min_ncp=0.5,
min_rhv=None,
min_refl=-20.0,
max_refl=100.0,
):
"""
Create a filter which removes undesired gates based on moments.
Creates a gate filter in which the following gates are excluded:
* Gates where the instrument is transitioning between sweeps.
* Gates where the reflectivity is outside the interval min_refl, max_refl.
* Gates where the normalized coherent power is below min_ncp.
* Gates where the cross correlation ratio is below min_rhi. Using the
default parameter this filtering is disabled.
* Gates where any of the above three fields are masked or contain
invalid values (NaNs or infs).
* If any of these three fields do not exist in the radar that fields filter
criteria is not applied.
Parameters
----------
radar : Radar
Radar object from which the gate filter will be built.
refl_field, ncp_field, rhv_field : str
Names of the radar fields which contain the reflectivity, normalized
coherent power (signal quality index) and cross correlation ratio
(RhoHV) from which the gate filter will be created using the above
criteria. A value of None for any of these parameters will use the
default field name as defined in the Py-ART configuration file.
min_ncp, min_rhv : float
Minimum values for the normalized coherence power and cross
correlation ratio. Gates in these fields below these limits as well as
gates which are masked or contain invalid values will be excluded and
not used in calculation which use the filter. A value of None will
disable filtering based upon the given field including removing
masked or gates with an invalid value. To disable the thresholding
but retain the masked and invalid filter set the parameter to a value
below the lowest value in the field.
min_refl, max_refl : float
Minimum and maximum values for the reflectivity. Gates outside
of this interval as well as gates which are masked or contain invalid
values will be excluded and not used in calculation which use this
filter. A value or None for one of these parameters will disable the
minimum or maximum filtering but retain the other. A value of None
for both of these values will disable all filtering based upon the
reflectivity including removing masked or gates with an invalid value.
To disable the interval filtering but retain the masked and invalid
filter set the parameters to values above and below the lowest and
greatest values in the reflectivity field.
Returns
-------
gatefilter : :py:class:`GateFilter`
A gate filter based upon the described criteria. This can be
used as a gatefilter parameter to various functions in pyart.correct.
"""
# parse the field parameters
if refl_field is None:
refl_field = get_field_name("reflectivity")
if ncp_field is None:
ncp_field = get_field_name("normalized_coherent_power")
if rhv_field is None:
rhv_field = get_field_name("cross_correlation_ratio")
# filter gates based upon field parameters
gatefilter = GateFilter(radar)
gatefilter.exclude_transition()
if (min_ncp is not None) and (ncp_field in radar.fields):
gatefilter.exclude_below(ncp_field, min_ncp)
gatefilter.exclude_masked(ncp_field)
gatefilter.exclude_invalid(ncp_field)
if (min_rhv is not None) and (rhv_field in radar.fields):
gatefilter.exclude_below(rhv_field, min_rhv)
gatefilter.exclude_masked(rhv_field)
gatefilter.exclude_invalid(rhv_field)
if refl_field in radar.fields:
if min_refl is not None:
gatefilter.exclude_below(refl_field, min_refl)
gatefilter.exclude_masked(refl_field)
gatefilter.exclude_invalid(refl_field)
if max_refl is not None:
gatefilter.exclude_above(refl_field, max_refl)
gatefilter.exclude_masked(refl_field)
gatefilter.exclude_invalid(refl_field)
return gatefilter
[docs]def moment_and_texture_based_gate_filter(
radar,
zdr_field=None,
rhv_field=None,
phi_field=None,
refl_field=None,
textzdr_field=None,
textrhv_field=None,
textphi_field=None,
textrefl_field=None,
wind_size=7,
max_textphi=20.0,
max_textrhv=0.3,
max_textzdr=2.85,
max_textrefl=8.0,
min_rhv=0.6,
):
"""
Create a filter which removes undesired gates based on texture of moments.
Creates a gate filter in which the following gates are excluded:
* Gates where the instrument is transitioning between sweeps.
* Gates where RhoHV is below min_rhv
* Gates where the PhiDP texture is above max_textphi.
* Gates where the RhoHV texture is above max_textrhv.
* Gates where the ZDR texture is above max_textzdr
* Gates where the reflectivity texture is above max_textrefl
* If any of the thresholds is not set or the field (RhoHV, ZDR, PhiDP,
reflectivity) do not exist in the radar the filter is not applied.
Parameters
----------
radar : Radar
Radar object from which the gate filter will be built.
zdr_field, rhv_field, phi_field, refl_field : str
Names of the radar fields which contain the differential reflectivity,
cross correlation ratio, differential phase and reflectivity from
which the textures will be computed. A value of None for any of these
parameters will use the default field name as defined in the Py-ART
configuration file.
textzdr_field, textrhv_field, textphi_field, textrefl_field : str
Names of the radar fields given to the texture of the
differential reflectivity, texture of the cross correlation ratio,
texture of differential phase and texture of reflectivity. A value
of None for any of these parameters will use the default field name
as defined in the Py-ART configuration file.
wind_size : int
Size of the moving window used to compute the ray texture.
max_textphi, max_textrhv, max_textzdr, max_textrefl : float
Maximum value for the texture of the differential phase, texture of
RhoHV, texture of Zdr and texture of reflectivity. Gates in these
fields above these limits as well as gates which are masked or contain
invalid values will be excluded and not used in calculation which use
the filter. A value of None will disable filtering based upon the
given field including removing masked or gates with an invalid value.
To disable the thresholding but retain the masked and invalid filter
set the parameter to a value above the highest value in the field.
min_rhv : float
Minimum value for the RhoHV. Gates below this limits as well as gates
which are masked or contain invalid values will be excluded and not
used in calculation which use the filter. A value of None will disable
filtering based upon the given field including removing masked or
gates with an invalid value. To disable the thresholding but retain
the masked and invalid filter set the parameter to a value below the
lowest value in the field.
Returns
-------
gatefilter : :py:class:`GateFilter`
A gate filter based upon the described criteria. This can be
used as a gatefilter parameter to various functions in pyart.correct.
"""
# parse the field parameters
if refl_field is None:
refl_field = get_field_name("reflectivity")
if zdr_field is None:
zdr_field = get_field_name("differential_reflectivity")
if rhv_field is None:
rhv_field = get_field_name("cross_correlation_ratio")
if phi_field is None:
phi_field = get_field_name("uncorrected_differential_phase")
if textrefl_field is None:
textrefl_field = get_field_name("reflectivity_texture")
if textzdr_field is None:
textzdr_field = get_field_name("differential_reflectivity_texture")
if textrhv_field is None:
textrhv_field = get_field_name("cross_correlation_ratio_texture")
if textphi_field is None:
textphi_field = get_field_name("differential_phase_texture")
# make deepcopy of input radar (we do not want to modify the original)
radar_aux = deepcopy(radar)
# compute the textures of the moments and add them into radar object
if (max_textphi is not None) and (phi_field in radar_aux.fields):
textphi = texture_along_ray(radar_aux, phi_field, wind_size=wind_size)
tphi = get_metadata(textphi_field)
tphi["data"] = textphi
radar_aux.add_field(textphi_field, tphi)
if (max_textrhv is not None) and (rhv_field in radar_aux.fields):
textrho = texture_along_ray(radar_aux, rhv_field, wind_size=wind_size)
trhv = get_metadata(textrhv_field)
trhv["data"] = textrho
radar_aux.add_field(textrhv_field, trhv)
if (max_textzdr is not None) and (zdr_field in radar_aux.fields):
textzdr = texture_along_ray(radar_aux, zdr_field, wind_size=wind_size)
tzdr = get_metadata(textzdr_field)
tzdr["data"] = textzdr
radar_aux.add_field(textzdr_field, tzdr)
if (max_textrefl is not None) and (refl_field in radar_aux.fields):
textrefl = texture_along_ray(radar_aux, refl_field, wind_size=wind_size)
trefl = get_metadata(textrefl_field)
trefl["data"] = textrefl
radar_aux.add_field(textrefl_field, trefl)
# filter gates based upon field parameters
gatefilter = GateFilter(radar_aux)
gatefilter.exclude_transition()
if (min_rhv is not None) and (rhv_field in radar_aux.fields):
gatefilter.exclude_below(rhv_field, min_rhv)
gatefilter.exclude_masked(rhv_field)
gatefilter.exclude_invalid(rhv_field)
if (max_textphi is not None) and (textphi_field in radar_aux.fields):
gatefilter.exclude_above(textphi_field, max_textphi)
gatefilter.exclude_masked(textphi_field)
gatefilter.exclude_invalid(textphi_field)
if (max_textrhv is not None) and (textrhv_field in radar_aux.fields):
gatefilter.exclude_above(textrhv_field, max_textrhv)
gatefilter.exclude_masked(textrhv_field)
gatefilter.exclude_invalid(textrhv_field)
if (max_textzdr is not None) and (textzdr_field in radar_aux.fields):
gatefilter.exclude_above(textzdr_field, max_textzdr)
gatefilter.exclude_masked(textzdr_field)
gatefilter.exclude_invalid(textzdr_field)
if (max_textrefl is not None) and (textrefl_field in radar_aux.fields):
gatefilter.exclude_above(textrefl_field, max_textrefl)
gatefilter.exclude_masked(textrefl_field)
gatefilter.exclude_invalid(textrefl_field)
return gatefilter
[docs]def temp_based_gate_filter(
radar, temp_field=None, min_temp=0.0, thickness=400.0, beamwidth=None
):
"""
Create a filter which removes undesired gates based on temperature. Used
primarily to filter out the melting layer and gates above it.
Parameters
----------
radar : Radar
Radar object from which the gate filter will be built.
temp_field : str
Name of the radar field which contains the temperature.
A value of None for will use the default field name as defined in
the Py-ART configuration file.
min_temp : float
Minimum value for the temperature in degrees. Gates below this limits
as well as gates which are masked or contain invalid values will be
excluded and not used in calculation which use the filter. A value of
None will disable filtering based upon the field including removing
masked or gates with an invalid value. To disable the thresholding but
retain the masked and invalid filter set the parameter to a value
below the lowest value in the field.
thickness : float
The estimated thickness of the melting layer in m.
beamwidth : float
The radar antenna 3 dB beamwidth [deg].
Returns
-------
gatefilter : :py:class:`GateFilter`
A gate filter based upon the described criteria. This can be
used as a gatefilter parameter to various functions in pyart.correct.
"""
# parse the field parameters
if temp_field is None:
temp_field = get_field_name("temperature")
# make deepcopy of input radar (we do not want to modify the original)
radar_aux = deepcopy(radar)
# filter gates based upon field parameters
gatefilter = GateFilter(radar_aux)
if (min_temp is not None) and (temp_field in radar_aux.fields):
gatefilter.exclude_below(temp_field, min_temp)
gatefilter.exclude_masked(temp_field)
gatefilter.exclude_invalid(temp_field)
deltar = radar.range["data"][1] - radar.range["data"][0]
if beamwidth is not None:
beam_rad = beamwidth * np.pi / 180.0
if thickness is not None:
temp = radar_aux.fields[temp_field]
temp["data"] = np.ma.masked_where(gatefilter.gate_excluded == 1, temp["data"])
for ray in range(radar_aux.nrays):
gate_h_ray = radar_aux.gate_altitude["data"][ray, :]
# index of first excluded gate
ind_r = np.where(gatefilter.gate_excluded[ray, :] == 1)[0]
if ind_r.size > 0:
# some gates are excluded: find the maximum height
ind_r = ind_r[0]
if beamwidth is None:
hmax = gate_h_ray[ind_r] - thickness
else:
# consider also the radar volume
# maximum altitude at the end of the volume
if ind_r < radar_aux.ngates - 2:
hmax = (
gate_h_ray[ind_r] + gate_h_ray[ind_r + 1]
) / 2.0 - thickness
else:
hmax = gate_h_ray[ind_r] - thickness
beam_radius = (
(radar.range["data"][ind_r] + deltar / 2.0) * beam_rad / 2.0
)
delta_h = beam_radius * np.cos(
radar.elevation["data"][ray] * np.pi / 180.0
)
hmax -= delta_h
ind_hmax = np.where(radar_aux.gate_altitude["data"][ray, :] > hmax)[0]
if ind_hmax.size > 0:
ind_hmax = ind_hmax[0]
temp["data"][ray, ind_hmax:] = np.ma.masked
radar_aux.add_field(temp_field, temp, replace_existing=True)
gatefilter = GateFilter(radar_aux)
gatefilter.exclude_masked(temp_field)
return gatefilter
[docs]def iso0_based_gate_filter(
radar, iso0_field=None, max_h_iso0=0.0, thickness=400.0, beamwidth=None
):
"""
Create a filter which removes undesired gates based height over the iso0.
Used primarily to filter out the melting layer and gates above it.
Parameters
----------
radar : Radar
Radar object from which the gate filter will be built.
iso0_field : str
Name of the radar field which contains the height relative to the
iso0. A value of None for will use the default field name as defined
in the Py-ART configuration file.
max_h_iso0 : float
Maximum height relative to the iso0 in m. Gates below this limits
as well as gates which are masked or contain invalid values will be
excluded and not used in calculation which use the filter. A value of
None will disable filtering based upon the field including removing
masked or gates with an invalid value. To disable the thresholding but
retain the masked and invalid filter set the parameter to a value
below the lowest value in the field.
thickness : float
The estimated thickness of the melting layer in m.
beamwidth : float
The radar antenna 3 dB beamwidth [deg].
Returns
-------
gatefilter : :py:class:`GateFilter`
A gate filter based upon the described criteria. This can be
used as a gatefilter parameter to various functions in pyart.correct.
"""
# parse the field parameters
if iso0_field is None:
iso0_field = get_field_name("height_over_iso0")
# make deepcopy of input radar (we do not want to modify the original)
radar_aux = deepcopy(radar)
# filter gates based upon field parameters
gatefilter = GateFilter(radar_aux)
if (max_h_iso0 is not None) and (iso0_field in radar_aux.fields):
gatefilter.exclude_above(iso0_field, max_h_iso0)
gatefilter.exclude_masked(iso0_field)
gatefilter.exclude_invalid(iso0_field)
deltar = radar.range["data"][1] - radar.range["data"][0]
if beamwidth is not None:
beam_rad = beamwidth * np.pi / 180.0
if thickness is not None:
iso0 = radar_aux.fields[iso0_field]
iso0["data"] = np.ma.masked_where(gatefilter.gate_excluded == 1, iso0["data"])
for ray in range(radar_aux.nrays):
gate_h_ray = radar_aux.gate_altitude["data"][ray, :]
# index of first excluded gate
ind_r = np.where(gatefilter.gate_excluded[ray, :] == 1)[0]
if ind_r.size > 0:
# some gates are excluded: find the maximum height
ind_r = ind_r[0]
if beamwidth is None:
hmax = gate_h_ray[ind_r] - thickness
else:
# consider also the radar volume
# maximum altitude at the end of the volume
if ind_r < radar_aux.ngates - 2:
hmax = (
gate_h_ray[ind_r] + gate_h_ray[ind_r + 1]
) / 2.0 - thickness
else:
hmax = gate_h_ray[ind_r] - thickness
beam_radius = (
(radar.range["data"][ind_r] + deltar / 2.0) * beam_rad / 2.0
)
delta_h = beam_radius * np.cos(
radar.elevation["data"][ray] * np.pi / 180.0
)
hmax -= delta_h
ind_hmax = np.where(radar_aux.gate_altitude["data"][ray, :] > hmax)[0]
if ind_hmax.size > 0:
ind_hmax = ind_hmax[0]
iso0["data"][ray, ind_hmax:] = np.ma.masked
radar_aux.add_field(iso0_field, iso0, replace_existing=True)
gatefilter = GateFilter(radar_aux)
gatefilter.exclude_masked(iso0_field)
return gatefilter
[docs]class GateFilter:
"""
A class for building a boolean arrays for filtering gates based on
a set of condition typically based on the values in the radar fields.
These filter can be used in various algorithms and calculations within
Py-ART.
See :py:func:`pyart.correct.GateFilter.exclude_below` for method
parameter details.
Parameters
----------
radar : Radar
Radar object from which gate filter will be build.
exclude_based : bool, optional
True, the default and suggested method, will begin with all gates
included and then use the exclude methods to exclude gates based on
conditions. False will begin with all gates excluded from which
a set of gates to include should be set using the include methods.
Examples
--------
>>> import pyart
>>> radar = pyart.io.read('radar_file.nc')
>>> gatefilter = pyart.correct.GateFilter(radar)
>>> gatefilter.exclude_below('reflectivity', 10)
>>> gatefilter.exclude_below('normalized_coherent_power', 0.75)
"""
def __init__(self, radar, exclude_based=True):
"""initialize"""
self._radar = radar
shape = (radar.nrays, radar.ngates)
if exclude_based:
# start with all gates included, exclude gates based on a set
# of rules using the exclude_ methods.
self._gate_excluded = np.zeros(shape, dtype=np.bool_)
else:
# start with all gates excluded, include gates based on a set
# of rules using the include_ methods.
self._gate_excluded = np.ones(shape, dtype=np.bool_)
# Implemetation is based on marking excluded gates stored in the private
# _gate_excluded attribute. The gate_included attribute can be found
# by taking the ones complement of gates_included.
[docs] def copy(self):
"""Return a copy of the gatefilter."""
a = GateFilter(self._radar)
a._gate_excluded = self._gate_excluded.copy()
return a
@property
def gate_included(self):
"""
Boolean array indicating if a gate should be included in a
calculation. Elements marked True indicate the corresponding gate
should be include. Those marked False should be excluded.
This is read-only attribute, any changes to the array will NOT
be reflected in gate_excluded and will be lost when the attribute is
accessed again.
"""
return ~self._gate_excluded.copy()
@property
def gate_excluded(self):
"""
Boolean array indicating if a gate should be excluded from a
calculation. Elements marked True indicate the corresponding gate
should be excluded. Those marked False should be included.
This is read-only attribute, any changes to the array will NOT
be reflected in gate_included and will be lost when the attribute is
accessed again.
"""
return self._gate_excluded.copy()
def _get_fdata(self, field):
"""Check that the field exists and retrieve field data."""
self._radar.check_field_exists(field)
return self._radar.fields[field]["data"]
def _merge(self, marked, op, exclude_masked):
"""Merge an array of marked gates with the exclude array."""
# exclude masked elements in marked by replacing them with the value
# of the exclude_masked flag. This does nothing if marked is a
# non-masked array.
if exclude_masked not in [True, False]:
raise ValueError("exclude_masked must be 'True' or 'False'")
marked = np.ma.filled(marked, exclude_masked)
# merge array of marked gates with existing excluded gates
# using the specified operation.
if op == "or":
self._gate_excluded = np.logical_or(self._gate_excluded, marked)
elif op == "and":
self._gate_excluded = np.logical_and(self._gate_excluded, marked)
elif op == "new":
self._gate_excluded = marked
else:
raise ValueError("invalid 'op' parameter: ", op)
return
###################
# exclude methods #
###################
[docs] def exclude_transition(self, trans_value=1, exclude_masked=True, op="or"):
"""
Exclude all gates in rays marked as in transition between sweeps.
Exclude all gates in rays marked as "in transition" by the
antenna_transition attribute of the radar used to construct the filter.
If no antenna transition information is available no gates are
excluded.
Parameters
----------
trans_value : int, optional
Value used in the antenna transition data to indicate that the
instrument was between sweeps (in transition) during the collection
of a specific ray. Typically a value of 1 is used to indicate this
transition and the default can be used in these cases.
exclude_masked : bool, optional
True to filter masked values in antenna_transition if the data is
a masked array, False to include any masked values.
op : {'and', 'or', 'new'}
Operation to perform when merging the existing set of excluded
gates with the excluded gates from the current operation.
'and' will perform a logical AND operation, 'or' a logical OR,
and 'new' will replace the existing excluded gates with the one
generated here. 'or', the default for exclude methods, is
typically desired when building up a set of conditions for
excluding gates where the desired effect is to exclude gates which
meet any of the conditions. 'and', the default for include
methods, is typically desired when building up a set of conditions
where the desired effect is to include gates which meet any of the
conditions. Note that the 'and' method MAY results in including
gates which have previously been excluded because they were masked
or invalid.
"""
marked = np.zeros_like(self._gate_excluded)
if self._radar.antenna_transition is not None:
transition_data = self._radar.antenna_transition["data"]
in_transition = transition_data == trans_value
marked[in_transition] = True
return self._merge(marked, op, exclude_masked)
[docs] def exclude_below(
self, field, value, exclude_masked=True, op="or", inclusive=False
):
"""
Exclude gates where a given field is below a given value.
Parameters
----------
field : str
Name of field compared against the value.
value : float
Gates with a value below this value in the specified field will
be marked for exclusion in the filter.
exclude_masked : bool, optional
True to filter masked values in the specified field if the data is
a masked array, False to include any masked values.
op : {'and', 'or', 'new'}
Operation to perform when merging the existing set of excluded
gates with the excluded gates from the current operation.
'and' will perform a logical AND operation, 'or' a logical OR,
and 'new' will replace the existing excluded gates with the one
generated here. 'or', the default for exclude methods, is
typically desired when building up a set of conditions for
excluding gates where the desired effect is to exclude gates which
meet any of the conditions. 'and', the default for include
methods, is typically desired when building up a set of conditions
where the desired effect is to include gates which meet any of the
conditions. Note that the 'and' method MAY results in including
gates which have previously been excluded because they were masked
or invalid.
inclusive : bool
Indicates whether the specified value should also be excluded.
"""
if inclusive:
marked = self._get_fdata(field) <= value
else:
marked = self._get_fdata(field) < value
return self._merge(marked, op, exclude_masked)
[docs] def exclude_above(
self, field, value, exclude_masked=True, op="or", inclusive=False
):
"""Exclude gates where a given field is above a given value."""
if inclusive:
marked = self._get_fdata(field) >= value
else:
marked = self._get_fdata(field) > value
return self._merge(marked, op, exclude_masked)
[docs] def exclude_inside(
self, field, v1, v2, exclude_masked=True, op="or", inclusive=True
):
"""Exclude gates where a given field is inside a given interval."""
if v2 < v1:
(v1, v2) = (v2, v1)
fdata = self._get_fdata(field)
if inclusive:
marked = (fdata >= v1) & (fdata <= v2)
else:
marked = (fdata > v1) & (fdata < v2)
return self._merge(marked, op, exclude_masked)
[docs] def exclude_outside(
self, field, v1, v2, exclude_masked=True, op="or", inclusive=False
):
"""Exclude gates where a given field is outside a given interval."""
if v2 < v1:
(v1, v2) = (v2, v1)
fdata = self._get_fdata(field)
if inclusive:
marked = (fdata <= v1) | (fdata >= v2)
else:
marked = (fdata < v1) | (fdata > v2)
return self._merge(marked, op, exclude_masked)
[docs] def exclude_equal(self, field, value, exclude_masked=True, op="or"):
"""Exclude gates where a given field is equal to a value."""
marked = self._get_fdata(field) == value
return self._merge(marked, op, exclude_masked)
[docs] def exclude_not_equal(self, field, value, exclude_masked=True, op="or"):
"""Exclude gates where a given field is not equal to a value."""
marked = self._get_fdata(field) != value
return self._merge(marked, op, exclude_masked)
[docs] def exclude_all(self):
"""Exclude all gates."""
self._gate_excluded = np.ones_like(self._gate_excluded)
return
[docs] def exclude_none(self):
"""Exclude no gates, include all gates."""
self._gate_excluded = np.zeros_like(self._gate_excluded)
return
[docs] def exclude_masked(self, field, exclude_masked=True, op="or"):
"""Exclude gates where a given field is masked."""
marked = np.ma.getmaskarray(self._get_fdata(field))
return self._merge(marked, op, exclude_masked)
[docs] def exclude_invalid(self, field, exclude_masked=True, op="or"):
"""
Exclude gates where an invalid value occurs in a field (NaNs or infs).
"""
marked = ~np.isfinite(self._get_fdata(field))
return self._merge(marked, op, exclude_masked)
[docs] def exclude_last_gates(self, field, n_gates=10, exclude_masked=True, op="or"):
"""
Excludes a number of gates at the end of each ray. This is useful
for when trying to exclude "ring artifacts" in some datasets.
"""
marked = np.full(self._get_fdata(field).shape, False)
marked[:, -n_gates:] = True
return self._merge(marked, op, exclude_masked)
[docs] def exclude_gates(self, mask, exclude_masked=True, op="or"):
"""
Exclude gates where a given mask is equal True.
Parameters
----------
mask : numpy array
Boolean numpy array with same shape as a field array.
exclude_masked : bool, optional
True to filter masked values in the specified mask if it is
a masked array, False to include any masked values.
op : {'and', 'or', 'new'}
Operation to perform when merging the existing set of excluded
gates with the excluded gates from the current operation.
'and' will perform a logical AND operation, 'or' a logical OR,
and 'new' will replace the existing excluded gates with the one
generated here. 'or', the default for exclude methods, is
typically desired when building up a set of conditions for
excluding gates where the desired effect is to exclude gates which
meet any of the conditions. 'and', the default for include
methods, is typically desired when building up a set of conditions
where the desired effect is to include gates which meet any of the
conditions. Note that the 'and' method MAY results in including
gates which have previously been excluded because they were masked
or invalid.
"""
fdata = next(iter(self._radar.fields.values()))["data"]
if mask.shape != fdata.shape:
raise ValueError("mask array must be the same size as a field.")
marked = np.array(mask, dtype="bool")
return self._merge(marked, op, exclude_masked)
####################
# include_ methods #
####################
[docs] def include_not_transition(self, trans_value=0, exclude_masked=True, op="and"):
"""
Include all gates in rays not marked as in transition between sweeps.
Include all gates in rays not marked as "in transition" by the
antenna_transition attribute of the radar used to construct the filter.
If no antenna transition information is available all gates are
included.
Parameters
----------
trans_value : int, optional
Value used in the antenna transition data to indicate that the
instrument is not between sweeps (in transition) during the
collection of a specific ray. Typically a value of 0 is used to
indicate no transition and the default can be used in these cases.
exclude_masked : bool, optional
True to filter masked values in antenna_transition if the data is
a masked array, False to include any masked values.
op : {'and', 'or', 'new'}
Operation to perform when merging the existing set of excluded
gates with the excluded gates from the current operation.
'and' will perform a logical AND operation, 'or' a logical OR,
and 'new' will replace the existing excluded gates with the one
generated here. 'or', the default for exclude methods, is
typically desired when building up a set of conditions for
excluding gates where the desired effect is to exclude gates which
meet any of the conditions. 'and', the default for include
methods, is typically desired when building up a set of conditions
where the desired effect is to include gates which meet any of the
conditions. Note that the 'or' method MAY results in excluding
gates which have previously been included.
"""
if self._radar.antenna_transition is None:
include = np.ones_like(self._gate_excluded) # include all gates
else:
include = np.zeros_like(self._gate_excluded)
transition_data = self._radar.antenna_transition["data"]
not_in_transition = transition_data == trans_value
include[not_in_transition] = True
return self._merge(~include, op, exclude_masked)
[docs] def include_below(
self, field, value, exclude_masked=True, op="and", inclusive=False
):
"""Include gates where a given field is below a given value."""
if inclusive:
marked = self._get_fdata(field) <= value
else:
marked = self._get_fdata(field) < value
self._merge(~marked, op, exclude_masked)
[docs] def include_above(
self, field, value, exclude_masked=True, op="and", inclusive=False
):
"""Include gates where a given field is above a given value."""
if inclusive:
marked = self._get_fdata(field) >= value
else:
marked = self._get_fdata(field) > value
self._merge(~marked, op, exclude_masked)
[docs] def include_inside(
self, field, v1, v2, exclude_masked=True, op="and", inclusive=True
):
"""Include gates where a given field is inside a given interval."""
if v2 < v1:
(v1, v2) = (v2, v1)
fdata = self._get_fdata(field)
if inclusive:
marked = (fdata >= v1) & (fdata <= v2)
else:
marked = (fdata > v1) & (fdata < v2)
return self._merge(~marked, op, exclude_masked)
[docs] def include_outside(
self, field, v1, v2, exclude_masked=True, op="and", inclusive=False
):
"""Include gates where a given field is outside a given interval."""
if v2 < v1:
(v1, v2) = (v2, v1)
fdata = self._get_fdata(field)
if inclusive:
marked = (fdata <= v1) | (fdata >= v2)
else:
marked = (fdata < v1) | (fdata > v2)
return self._merge(~marked, op, exclude_masked)
[docs] def include_equal(self, field, value, exclude_masked=True, op="and"):
"""Include gates where a given field is equal to a value."""
marked = self._get_fdata(field) == value
return self._merge(~marked, op, exclude_masked)
[docs] def include_not_equal(self, field, value, exclude_masked=True, op="and"):
"""Include gates where a given field is not equal to a value."""
marked = self._get_fdata(field) != value
return self._merge(~marked, op, exclude_masked)
[docs] def include_all(self):
"""Include all gates."""
self._gate_excluded = np.zeros_like(self._gate_excluded)
[docs] def include_none(self):
"""Include no gates, exclude all gates."""
self._gate_excluded = np.ones_like(self._gate_excluded)
[docs] def include_not_masked(self, field, exclude_masked=True, op="and"):
"""Include gates where a given field in not masked."""
marked = np.ma.getmaskarray(self._get_fdata(field))
return self._merge(marked, op, exclude_masked)
[docs] def include_valid(self, field, exclude_masked=True, op="and"):
"""
Include gates where a valid value occurs in a field (not NaN or inf).
"""
marked = np.isfinite(self._get_fdata(field))
return self._merge(~marked, op, exclude_masked)
[docs] def include_gates(self, mask, exclude_masked=True, op="and"):
"""
Include gates where a given mask is equal True.
Parameters
----------
mask : numpy array
Boolean numpy array with same shape as a field array.
exclude_masked : bool, optional
True to filter masked values in the specified mask if it is
a masked array, False to include any masked values.
op : {'and', 'or', 'new'}
Operation to perform when merging the existing set of excluded
gates with the excluded gates from the current operation.
'and' will perform a logical AND operation, 'or' a logical OR,
and 'new' will replace the existing excluded gates with the one
generated here. 'or', the default for exclude methods, is
typically desired when building up a set of conditions for
excluding gates where the desired effect is to exclude gates which
meet any of the conditions. 'and', the default for include
methods, is typically desired when building up a set of conditions
where the desired effect is to include gates which meet any of the
conditions. Note that the 'or' method MAY results in excluding
gates which have previously been included.
"""
fdata = next(iter(self._radar.fields.values()))["data"]
if mask.shape != fdata.shape:
raise ValueError("Mask array must be the same size as a field.")
marked = ~np.array(mask, dtype="bool")
return self._merge(marked, op, exclude_masked)
```