rompy.core.spectrum.LogFrequency#
- pydantic model rompy.core.spectrum.LogFrequency[source]#
Logarithmic wave frequencies.
Frequencies are defined according to:
\(f_{i+1} = \gamma * f_{i}\)
Note
The number of frequency bins nbin is always kept unchanged when provided. This implies other parameters may be adjusted so nbin bins can be defined. Specify f0, f1 and finc and let nbin be calculated to avoid those values changing.
Note
Choose finc=0.1 for a 10% increment between frequencies that satisfies the DIA.
Examples
In [1]: from rompy.core.spectrum import LogFrequency In [2]: LogFrequency(f0=0.04, f1=1.0, nbin=34) Out[2]: LogFrequency(model_type='log', f0=np.float64(0.04), f1=np.float64(1.0), finc=np.float64(0.0992991258103799), nbin=34) In [3]: LogFrequency(f0=0.04, f1=1.0, finc=0.1) Out[3]: LogFrequency(model_type='log', f0=np.float64(0.04), f1=np.float64(1.0), finc=np.float64(0.0992991258103799), nbin=34) In [4]: LogFrequency(f0=0.04, nbin=34, finc=0.1) Out[4]: LogFrequency(model_type='log', f0=np.float64(0.04), f1=np.float64(1.0219067944750664), finc=np.float64(0.1000000000000006), nbin=34) In [5]: LogFrequency(f1=1.0, nbin=34, finc=0.1) Out[5]: LogFrequency(model_type='log', f0=np.float64(0.03914251301220403), f1=np.float64(1.0), finc=np.float64(0.10000000000000035), nbin=34)
- Fields:
- Validators:
init_options
»all fields
- field f0: float | None = None#
Lower frequency boundary (Hz)
- Constraints:
gt = 0.0
- Validated by:
- field f1: float | None = None#
Upper frequency boundary (Hz)
- Validated by:
- field finc: float | None = None#
Log frequency increment
- Constraints:
gt = 0.0
- Validated by:
- field model_type: Literal['log', 'LOG'] = 'log'#
Model type discriminator
- Validated by:
- field nbin: int | None = None#
Number of frequency bins, one less the size of frequency array
- Constraints:
gt = 0
- Validated by:
- property flen#
- property gamma#
- property nf#