Source code for skrf.frequency

.. currentmodule:: skrf.frequency

frequency (:mod:`skrf.frequency`)

Provides a frequency object and related functions.

Most of the functionality is provided as methods and properties of the
:class:`Frequency` Class.

Frequency Class
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.. autosummary::
    :toctree: generated/



.. autosummary::
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# from matplotlib.pyplot import gca,plot, autoscale
from typing import List
import warnings

from numbers import Number
from .constants import NumberLike, ZERO
from typing import Union
from numpy import pi, linspace, geomspace
import numpy as npy
from numpy import gradient  # used to center attribute `t` at 0
import re
from .util import slice_domain, find_nearest_index, axes_kwarg, Axes

[docs] class InvalidFrequencyWarning(UserWarning): """Thrown if frequency values aren't monotonously increasing """ pass
[docs] class Frequency: """ A frequency band. The frequency object provides a convenient way to work with and access a frequency band. It contains a frequency vector as well as a frequency unit. This allows a frequency vector in a given unit to be available (:attr:`f_scaled`), as well as an absolute frequency axis in 'Hz' (:attr:`f`). A Frequency object can be created from either (start, stop, npoints) using the default constructor, :func:`__init__`. Or, it can be created from an arbitrary frequency vector by using the class method :func:`from_f`. Internally, the frequency information is stored in the `f` property combined with the `unit` property. All other properties, `start` `stop`, etc are generated from these. """ unit_dict = { 'hz': 'Hz', 'khz': 'kHz', 'mhz': 'MHz', 'ghz': 'GHz', 'thz': 'THz' } """ Dictionary to convert unit string with correct capitalization for display. """ multiplier_dict={ 'hz': 1, 'khz': 1e3, 'mhz': 1e6, 'ghz': 1e9, 'thz': 1e12 } """ Frequency unit multipliers. """
[docs] def __init__(self, start: float = 0, stop: float = 0, npoints: int = 0, unit: str = None, sweep_type: str = 'lin') -> None: """ Frequency initializer. Creates a Frequency object from start/stop/npoints and a unit. Alternatively, the class method :func:`from_f` can be used to create a Frequency object from a frequency vector instead. Parameters ---------- start : number, optional start frequency in units of `unit`. Default is 0. stop : number, optional stop frequency in units of `unit`. Default is 0. npoints : int, optional number of points in the band. Default is 0. unit : string, optional Frequency unit of the band: 'hz', 'khz', 'mhz', 'ghz', 'thz'. This is used to create the attribute :attr:`f_scaled`. It is also used by the :class:`` class for plots vs. frequency. Default is 'hz'. sweep_type : string, optional Type of the sweep: 'lin' or 'log'. 'lin' for linear and 'log' for logarithmic. Default is 'lin'. Note ---- The attribute `unit` sets the frequency multiplier, which is used to scale the frequency when `f_scaled` is referenced. Note ---- The attribute `unit` is not case sensitive. Hence, for example, 'GHz' or 'ghz' is the same. See Also -------- from_f : constructs a Frequency object from a frequency vector instead of start/stop/npoints. :attr:`unit` : frequency unit of the band Examples -------- >>> wr1p5band = Frequency(start=500, stop=750, npoints=401, unit='ghz') >>> logband = Frequency(1, 1e9, 301, sweep_type='log') """ if unit is None: warnings.warn(''' Frequency unit not passed: uses 'Hz' per default. ''', DeprecationWarning, stacklevel=2) unit = 'hz' self._unit = unit.lower() start = self.multiplier * start stop = self.multiplier * stop if sweep_type.lower() == 'lin': self._f = linspace(start, stop, npoints) elif sweep_type.lower() == 'log' and start > 0: self._f = geomspace(start, stop, npoints) else: raise ValueError('Sweep Type not recognized')
def __str__(self) -> str: """ """ try: output = \ '%s-%s %s, %i pts' % \ (self.f_scaled[0], self.f_scaled[-1], self.unit, self.npoints) except (IndexError): output = "[no freqs]" return output def __repr__(self) -> str: """ """ return self.__str__() def __getitem__(self, key: Union[str, int, slice]) -> 'Frequency': """ Slices a Frequency object based on an index, or human readable string. Parameters ---------- key : str, int, or slice if int, then it is interpreted as the index of the frequency if str, then should be like '50.1-75.5ghz', or just '50'. If the frequency unit is omitted then :attr:`unit` is used. Examples -------- >>> b = rf.Frequency(50, 100, 101, 'ghz') >>> a = b['80-90ghz'] >>> a.plot_s_db() """ output = self.copy() if isinstance(key, str): # they passed a string try and do some interpretation re_hyphen = re.compile(r'\s*-\s*') re_letters = re.compile('[a-zA-Z]+') freq_unit = re.findall(re_letters,key) if len(freq_unit) == 0: freq_unit = self.unit else: freq_unit = freq_unit[0] key_nounit = re.sub(re_letters,'',key) edges = re.split(re_hyphen,key_nounit) edges_freq = Frequency.from_f([float(k) for k in edges], unit = freq_unit) if len(edges_freq) ==2: slicer=slice_domain(output.f, edges_freq.f) elif len(edges_freq)==1: key = find_nearest_index(output.f, edges_freq.f[0]) slicer = slice(key,key+1,1) else: raise ValueError() try: output._f = npy.array(output.f[slicer]).reshape(-1) return output except(IndexError): raise IndexError('slicing frequency is incorrect') if output.f.shape[0] > 0: output._f = npy.array(output.f[key]).reshape(-1) else: output._f = npy.empty(shape=(0)) return output
[docs] @classmethod def from_f(cls, f: NumberLike, *args,**kwargs) -> 'Frequency': """ Construct Frequency object from a frequency vector. The unit is set by kwarg 'unit' Parameters ---------- f : scalar or array-like frequency vector *args, **kwargs : arguments, keyword arguments passed on to :func:`__init__`. Returns ------- myfrequency : :class:`Frequency` object the Frequency object Raises ------ InvalidFrequencyWarning: If frequency points are not monotonously increasing Examples -------- >>> f = npy.linspace(75,100,101) >>> rf.Frequency.from_f(f, unit='ghz') """ if npy.isscalar(f): f = [f] temp_freq = cls(0,0,0,*args, **kwargs) temp_freq._f = npy.asarray(f) * temp_freq.multiplier temp_freq.check_monotonic_increasing() return temp_freq
def __eq__(self, other: object) -> bool: #return (list(self.f) == list(other.f)) # had to do this out of practicality if not isinstance(other, self.__class__): return False if len(self.f) != len(other.f): return False elif len(self.f) == len(other.f) == 0: return True else: return (max(abs(self.f-other.f)) < ZERO) def __ne__(self,other: object) -> bool: return (not self.__eq__(other)) def __len__(self) -> int: """ The number of frequency points """ return self.npoints def __mul__(self,other: 'Frequency') -> 'Frequency': out = self.copy() out.f = self.f*other return out def __rmul__(self,other: 'Frequency') -> 'Frequency': out = self.copy() out.f = self.f*other return out def __div__(self,other: 'Frequency') -> 'Frequency': out = self.copy() out.f = self.f/other return out
[docs] def check_monotonic_increasing(self) -> None: """Validate the frequency values Raises ------ InvalidFrequencyWarning: If frequency points are not monotonously increasing """ increase = npy.diff(self.f) > 0 if not increase.all(): warnings.warn("Frequency values are not monotonously increasing!\n" "To get rid of the invalid values call `drop_non_monotonic_increasing`", InvalidFrequencyWarning)
[docs] def drop_non_monotonic_increasing(self) -> List[int]: """Drop duplicate and invalid frequency values and return the dropped indices Returns: list[int]: The dropped indices """ invalid = npy.diff(self.f, prepend=self.f[0]-1) <= 0 self._f = self._f[~invalid] return list(npy.flatnonzero(invalid))
@property def start(self) -> float: """ Starting frequency in Hz. """ return self.f[0] @property def start_scaled(self) -> float: """ Starting frequency in :attr:`unit`'s. """ return self.f_scaled[0] @property def stop_scaled(self) -> float: """ Stop frequency in :attr:`unit`'s. """ return self.f_scaled[-1] @property def stop(self) -> float: """ Stop frequency in Hz. """ return self.f[-1] @property def npoints(self) -> int: """ Number of points in the frequency. """ return len(self.f) @property def center(self) -> float: """ Center frequency in Hz. Returns ------- center : number the exact center frequency in units of Hz """ return self.start + (self.stop-self.start)/2. @property def center_idx(self) -> int: """ Closes idx of :attr:`f` to the center frequency. """ return self.npoints // 2 @property def center_scaled(self) -> float: """ Center frequency in :attr:`unit`'s. Returns ------- center : number the exact center frequency in units of :attr:`unit`'s """ return self.start_scaled + (self.stop_scaled-self.start_scaled)/2. @property def step(self) -> float: """ The inter-frequency step size (in Hz) for evenly-spaced frequency sweeps See Also -------- df : for general case """ return self.span/(self.npoints-1.) @property def step_scaled(self) -> float: """ The inter-frequency step size (in :attr:`unit`) for evenly-spaced frequency sweeps. See Also -------- df : for general case """ return self.span_scaled/(self.npoints-1.) @property def span(self) -> float: """ The frequency span. """ return abs(self.stop-self.start) @property def span_scaled(self) -> float: """ The frequency span. """ return abs(self.stop_scaled-self.start_scaled) @property def f(self) -> npy.ndarray: """ Frequency vector in Hz. Returns ---------- f : :class:`numpy.ndarray` The frequency vector in Hz See Also ---------- f_scaled : frequency vector in units of :attr:`unit` w : angular frequency vector in rad/s """ return self._f @property def f_scaled(self) -> npy.ndarray: """ Frequency vector in units of :attr:`unit`. Returns ------- f_scaled : numpy.ndarray A frequency vector in units of :attr:`unit` See Also -------- f : frequency vector in Hz w : frequency vector in rad/s """ return self.f/self.multiplier @property def w(self) -> npy.ndarray: r""" Angular frequency in radians/s. Angular frequency is defined as :math:`\omega=2\pi f` [#]_ Returns ------- w : :class:`numpy.ndarray` Angular frequency in rad/s References ---------- .. [#] See Also -------- f_scaled : frequency vector in units of :attr:`unit` f : frequency vector in Hz """ return 2*pi*self.f @property def df(self) -> npy.ndarray: """ The gradient of the frequency vector. Note ---- The gradient is calculated using:: `gradient(self.f)` """ return gradient(self.f) @property def df_scaled(self) -> npy.ndarray: """ The gradient of the frequency vector (in unit of :attr:`unit`). Note ---- The gradient is calculated using:: `gradient(self.f_scaled)` """ return gradient(self.f_scaled) @property def dw(self) -> npy.ndarray: """ The gradient of the frequency vector (in radians). Note ---- The gradient is calculated using:: `gradient(self.w)` """ return gradient(self.w) @property def unit(self) -> str: """ Unit of this frequency band. Possible strings for this attribute are: 'Hz', 'kHz', 'MHz', 'GHz', 'THz' Setting this attribute is not case sensitive. Returns ------- unit : string String representing the frequency unit """ return self.unit_dict[self._unit] @unit.setter def unit(self, unit: str) -> None: self._unit = unit.lower() @property def multiplier(self) -> float: """ Multiplier for formatting axis. This accesses the internal dictionary `multiplier_dict` using the value of :attr:`unit` Returns ------- multiplier : number multiplier for this Frequencies unit """ return self.multiplier_dict[self._unit]
[docs] def copy(self) -> 'Frequency': """ Returns a new copy of this frequency. """ freq = Frequency.from_f(self.f, unit='hz') freq.unit = self.unit return freq
@property def t(self) -> npy.ndarray: """ Time vector in s. t_period = 2*(n-1)/f_step """ return npy.fft.fftshift(npy.fft.fftfreq(self.npoints, self.step)) @property def t_ns(self) -> npy.ndarray: """ Time vector in ns. t_period = 2*(n-1)/f_step """ return self.t*1e9
[docs] def round_to(self, val: Union[str, Number] = 'hz') -> None: """ Round off frequency values to a specified precision. This is useful for dealing with finite precision limitations of VNA's and/or other software Parameters ---------- val : string or number if val is a string it should be a frequency :attr:`unit` (ie 'hz', 'mhz',etc). if its a number, then this returns f = f-f%val Examples -------- >>> f = skrf.Frequency.from_f([.1,1.2,3.5],unit='hz') >>> f.round_to('hz') """ if isinstance(val, str): val = self.multiplier_dict[val.lower()] self.f = npy.round_(self.f/val)*val
[docs] def overlap(self,f2: 'Frequency') -> 'Frequency': """ Calculates overlapping frequency between self and f2. See Also -------- overlap_freq """ return overlap_freq(self, f2)
@property def sweep_type(self) -> str: """ Frequency sweep type. Returns ------- sweep_type: str 'lin' if linearly increasing, 'log' or 'unknown'. """ if npy.allclose(self.f, linspace(self.f[0], self.f[-1], self.npoints), rtol=0.05): sweep_type = 'lin' elif self.f[0] and npy.allclose(self.f, geomspace(self.f[0], self.f[-1], self.npoints), rtol=0.05): sweep_type = 'log' else: sweep_type = 'unknown' return sweep_type
[docs] @axes_kwarg def labelXAxis(self, ax: Axes = None): """ Label the x-axis of a plot. Sets the labels of a plot using :func:`matplotlib.x_label` with string containing the frequency unit. Parameters ---------- ax : :class:`matplotlib.Axes` or None, optional Axes on which to label the plot. Defaults is None, for the current axe returned by :func:`matplotlib.gca()` """ ax.set_xlabel('Frequency (%s)' % self.unit)
[docs] @axes_kwarg def plot(self, y: NumberLike, *args, ax: Axes=None, **kwargs): """ Plot something vs this frequency. This plots whatever is given vs. `self.f_scaled` and then calls `labelXAxis`. """ from .plotting import scale_frequency_ticks try: if len(npy.shape(y)) > 2: # perhaps the dimensions are empty, try to squeeze it down y = y.squeeze() if len(npy.shape(y)) > 2: # the dimensions are full, so lets loop and plot each for m in range(npy.shape(y)[1]): for n in range(npy.shape(y)[2]): self.plot(y[:, m, n], *args, **kwargs) return if len(y) == len(self): pass else: raise IndexError(['thing to plot doesn\'t have same' ' number of points as f']) except(TypeError): y = y * npy.ones(len(self)) # plt.plot(self.f_scaled, y, *args, **kwargs) ax.plot(self.f, y, *args, **kwargs) scale_frequency_ticks(ax, self.unit) ax.autoscale(axis='x', tight=True) self.labelXAxis()
[docs] def overlap_freq(f1: 'Frequency',f2: 'Frequency') -> Frequency: """ Calculates overlapping frequency between f1 and f2. Or, put more accurately, this returns a Frequency that is the part of f1 that is overlapped by f2. The resultant start frequency is the smallest f1.f that is greater than f2.f.start, and the stop frequency is the largest f1.f that is smaller than f2.f.stop. This way the new frequency overlays onto f1. Parameters ---------- f1 : :class:`Frequency` a frequency object f2 : :class:`Frequency` a frequency object Returns ------- f3 : :class:`Frequency` part of f1 that is overlapped by f2 """ if f1.start > f2.stop: raise ValueError('Out of bounds. f1.start > f2.stop') elif f2.start > f1.stop: raise ValueError('Out of bounds. f2.start > f1.stop') start = max(f1.start, f2.start) stop = min(f1.stop, f2.stop) f = f1.f[(f1.f>=start) & (f1.f<=stop)] freq = Frequency.from_f(f, unit = 'hz') freq.unit = f1.unit return freq