def get_values(
self, unit="SI", is_oneperiod=False, is_antiperiod=False, is_smallestperiod=False
):
"""Returns the vector 'axis' by rebuilding the linspace, symmetries and unit included.
Parameters
----------
self: DataLinspace
a DataLinspace object
unit: str
requested unit
is_oneperiod: bool
return values on a single period
is_antiperiod: bool
return values on a semi period (only for antiperiodic signals)
Returns
-------
Vector of axis values
"""
initial = self.initial
if self.number == None:
final = self.final
number = (final - initial + self.step) / self.step
elif self.final == None:
number = self.number
final = self.initial + (number - 1) * self.step
else:
number = self.number
final = self.final
values = linspace(initial, final, int(number), endpoint=self.include_endpoint)
# Unit conversion
if unit != "SI" and unit != self.unit:
values = convert(values, self.unit, unit)
# Ignore symmetries if fft axis
if self.name == "freqs" or self.name == "wavenumber":
is_smallestperiod = True
# Rebuild symmetries
if is_smallestperiod:
return values
elif is_antiperiod:
if "antiperiod" in self.symmetries:
return values
else:
raise AxisError("ERROR: axis has no antiperiodicity")
elif is_oneperiod:
if "antiperiod" in self.symmetries:
nper = self.symmetries["antiperiod"]
self.symmetries["antiperiod"] = 2
values = rebuild_symmetries_axis(values, self.symmetries)
self.symmetries["antiperiod"] = nper
return values
elif "period" in self.symmetries:
return values
else:
return values
else:
values = rebuild_symmetries_axis(values, self.symmetries)
return values
def get_values(self,
unit="SI",
is_oneperiod=False,
is_antiperiod=False,
is_smallestperiod=False):
"""Returns the vector 'axis' taking symmetries into account.
Parameters
----------
self: Data1D
a Data1D object
unit: str
requested unit
is_oneperiod: bool
return values on a single period
is_antiperiod: bool
return values on a semi period (only for antiperiodic signals)
Returns
-------
Vector of axis values
"""
values = self.values
# Unit conversion
if unit != "SI" and unit != self.unit:
values = convert(values, self.unit, unit)
# Ignore symmetries if fft axis
if self.name == "freqs" or self.name == "wavenumber":
is_smallestperiod = True
# Rebuild symmetries
if is_smallestperiod:
return values
elif is_antiperiod:
if "antiperiod" in self.symmetries:
return values
else:
raise AxisError("ERROR: axis has no antiperiodicity")
elif is_oneperiod:
if "antiperiod" in self.symmetries:
nper = self.symmetries["antiperiod"]
self.symmetries["antiperiod"] = 2
values = rebuild_symmetries_axis(values, self.symmetries)
self.symmetries["antiperiod"] = nper
return values
elif "period" in self.symmetries:
return values
else:
return values
else:
values = rebuild_symmetries_axis(values, self.symmetries)
return values
def get_values(self):
"""Returns the vector 'axis' taking symmetries into account (no units).
Parameters
----------
self: Data1D
a Data1D object
Returns
-------
Vector of axis values
"""
values = self.values
# Rebuild symmetries
if self.name in self.symmetries:
values = rebuild_symmetries_axis(values, self.symmetries.get(self.name))
return values
def get_axis(self, axis, is_real):
"""Computes the vector 'axis' in the unit required, using conversions and symmetries if needed.
Parameters
----------
self: RequestedAxis
a RequestedAxis object
axis: Axis
an Axis object
"""
if self.operation is not None:
module = import_module("SciDataTool.Functions.conversions")
func = getattr(module, self.operation) # Conversion function
if isinstance(axis, DataPattern):
self.is_pattern = True
self.rebuild_indices = axis.rebuild_indices
self.is_step = axis.is_step
is_components = getattr(axis, "is_components", False)
if is_components:
values = axis.get_values()
if not self.extension in ["sum", "rss", "mean", "rms", "integrate"]:
self.extension = "list"
if self.indices is not None:
self.values = values[self.indices]
else:
self.values = values
else:
if self.extension == "pattern":
if not self.is_pattern:
raise AxisError(
"ERROR: [pattern] cannot be called with non DataPattern axis"
)
else:
is_smallestperiod = True
is_oneperiod = False
is_antiperiod = False
self.extension = "smallestperiod"
elif self.extension == "smallestperiod":
if isinstance(axis, DataPattern):
raise AxisError(
"ERROR: [smallestperiod] cannot be called with DataPattern axis"
)
else:
is_smallestperiod = True
is_oneperiod = False
is_antiperiod = False
elif self.extension == "antiperiod":
if isinstance(axis, DataPattern):
raise AxisError(
"ERROR: [antiperiod] cannot be called with DataPattern axis"
)
else:
is_smallestperiod = False
is_oneperiod = False
is_antiperiod = True
elif self.extension == "oneperiod" or self.transform == "fft":
if isinstance(axis, DataPattern):
raise AxisError(
"ERROR: [oneperiod] cannot be called with DataPattern axis"
)
else:
is_smallestperiod = False
is_oneperiod = True
is_antiperiod = False
elif self.extension in ["sum", "rss", "mean", "rms", "integrate"]:
is_smallestperiod = False
is_oneperiod = False
is_antiperiod = False
# Ignore symmetries if fft axis
elif self.name == "freqs" or self.name == "wavenumber":
is_smallestperiod = True
is_oneperiod = False
is_antiperiod = False
else:
if self.input_data is not None and not self.is_step:
# Check if symmetries need to be reconstructed to match input_data
if self.operation is not None:
axis_values = func(
axis.get_values(is_smallestperiod=True, ),
is_real=is_real,
)
else:
axis_values = axis.get_values(is_smallestperiod=True, )
if min(self.input_data) >= min(axis_values) and max(
self.input_data) <= max(axis_values):
is_smallestperiod = True
is_oneperiod = False
is_antiperiod = False
else:
if self.operation is not None:
axis_values = func(
axis.get_values(is_oneperiod=True, ),
is_real=is_real,
)
else:
axis_values = axis.get_values(is_oneperiod=True, )
if min(self.input_data) >= min(axis_values) and max(
self.input_data) <= max(axis_values):
is_smallestperiod = False
is_oneperiod = True
is_antiperiod = False
self.extension = "oneperiod"
else:
is_smallestperiod = False
is_oneperiod = False
is_antiperiod = False
if not self.is_pattern:
self.extension = "interval"
elif self.transform == "ifft": # Ignore symmetries in ifft case
is_smallestperiod = True
is_oneperiod = False
is_antiperiod = False
else:
is_smallestperiod = False
is_oneperiod = False
is_antiperiod = False
# Get original values of the axis
if self.operation is not None:
values = array(
func(
axis.get_values(
is_oneperiod=is_oneperiod,
is_antiperiod=is_antiperiod,
is_smallestperiod=is_smallestperiod,
),
is_real=is_real,
))
# Store original values
self.corr_values = array(
axis.get_values(
is_oneperiod=is_oneperiod,
is_antiperiod=is_antiperiod,
is_smallestperiod=is_smallestperiod,
))
else:
values = array(
axis.get_values(
is_oneperiod=is_oneperiod,
is_antiperiod=is_antiperiod,
is_smallestperiod=is_smallestperiod,
))
# Unit conversions and normalizations
unit = self.unit
if unit == self.corr_unit or unit == "SI":
pass
elif unit in axis.normalizations:
if axis.normalizations.get(unit) == "indices":
values = array([i for i in range(len(values))])
elif isinstance(axis.normalizations.get(unit), ndarray):
values = axis.normalizations.get(unit)
else:
values = values / axis.normalizations.get(unit)
else:
values = convert(values, self.corr_unit, unit)
# Rebuild symmetries in fft case
if self.transform == "fft":
if "period" in axis.symmetries:
if axis.name != "time":
values = values * axis.symmetries["period"]
elif "antiperiod" in axis.symmetries:
if axis.name != "time":
values = values * axis.symmetries["antiperiod"] / 2
# Rebuild symmetries in ifft case
if self.transform == "ifft":
# if "antiperiod" in axis.symmetries:
# axis.symmetries["antiperiod"] = int(axis.symmetries["antiperiod"]/2)
if (self.extension != "smallestperiod"
and self.extension != "oneperiod"
and self.extension != "antiperiod"):
values = rebuild_symmetries_axis(values, axis.symmetries)
# if "period" in axis.symmetries:
# if axis.name != "freqs":
# values = values * axis.symmetries["period"]
# elif "antiperiod" in axis.symmetries:
# if axis.name != "freqs":
# values = values * axis.symmetries["antiperiod"] / 2
# Interpolate axis with input data
if self.input_data is None:
self.values = values
else:
# if self.is_step:
# values = values[axis.rebuild_indices]
if len(self.input_data) == 2 and self.extension != "axis_data":
indices = [
i for i, x in enumerate(values)
if x >= self.input_data[0] and x <= self.input_data[-1]
]
if self.indices is None:
self.indices = indices
else:
indices_new = []
for i in self.indices:
if i in indices:
indices_new.append(i)
self.indices = indices_new
self.input_data = None
else:
self.values = values
if self.indices is not None:
self.values = values[self.indices]
if self.extension in ["sum", "rss", "mean", "rms", "integrate"]:
self.indices = None