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jan 2025-12-29 23:22:07 -08:00
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blowback/LICENSE.md Symbolic link
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../LICENSE.md

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blowback/README.md Symbolic link
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../README.md

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blowback/__init__.py Normal file
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from .obr import OBRData
__version__ = '0.1'

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blowback/obr.py Normal file
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from typing import IO, Self
from dataclasses import dataclass
from pathlib import Path
import logging
import numpy
from numpy.typing import NDArray
from numpy.fft import fftshift, fftfreq
from .utils import C0
logger = logging.getLogger(__name__)
@dataclass
class OBRData:
te: NDArray[numpy.complex128] # time domain complex amplitude, polarization 1
tm: NDArray[numpy.complex128] # time domain complex amplitude, polarization 2
t0half: float # t0 / 2
dt_ns: float # delta between time points
max_freq_GHz: float # sweep's max frequency (shortest wavelength)
freq_windowed: bool # was frequency windowing enabled (altered content of te/tm data)
gain_dB: int # sensor gain (normalized away, for info only)
ng_setting: float | None # set by user (for info only)
meas_date: NDArray[numpy.int16] # 8 items: year month [week?] day hour min sec ms
calib_date: NDArray[numpy.int16] # 8 items: year month [week?] day hour min sec ms
_wip_metadata: NDArray[numpy.float64] | None # unknown metadata values
_raw_sweep_rate: NDArray[numpy.int8] | None # values not totally clear yet
@property
def time_ns(self) -> NDArray[numpy.float64]:
"""
Time delay (x-axis) for `te` and `tm` data
"""
tt = numpy.arange(self.tee.size) * self.dt_ns + self.t0half * 2
return tt
@property
def wl_range_nm(self) -> NDArray[numpy.float64]:
freq_range = numpy.asarray([
self.max_freq_GHz - 1 / (2 * self.dt_ns),
welf.max_freq_GHz,
])
return C0 / freq_range
@property
def ctr_freq_GHz(self) -> float:
return self.max_freq_GHz - 1 / (4 * self.dt_ns)
def freqs(self, size: int) -> NDArray[numpy.float64]:
# To be used with spectrum generated with e.g. fft(fftshift(data.te))
frq_GHz = fftshift(fftfreq(size, d=self.dt_ns)) + self.ctr_freq_GHz
return frq_GHz
def wls(self, size: int) -> NDArray[numpy.float64]:
# To be used with spectrum generated with e.g. fft(fftshift(data.te))
return C0 / self.freqs(size)
def window(self, size: int) -> NDArray[numpy.float64]:
# Approximation of the generalized Hamming window used when freq_windowed==True
nn = numpy.linspace(0, 1, size)
alpha = 0.572
scale = 1.5 # likely related to "incoherent power gain compensation" for Hamming window (=1.54)
# 1.50 seems to fit the data better though
ham = alpha - (1 - alpha) * numpy.cos(2 * numpy.pi * nn)
return scale * ham
@staticmethod
def read(file: str | IO[bytes] | Path) -> Self:
def fromfile(*args, **kwargs) -> NDArray:
if not isinstance(file, str | Path):
file.seek(0)
return numpy.fromfile(file, *args, **kwargs)
magic = fromfile(dtype=numpy.uint8, offset=0x00, count=12)
if (magic != [0, 0, 0x60, 0x40] + [ord(cc) for cc in 'OBR/OFDR']).any():
logger.warning(f'Unexpected magic bytes: {magic}')
metadata = fromfile(dtype=numpy.float64, offset=0x0c, count=4)
ng = fromfile(dtype=numpy.float64, offset=0x2e, count=1)
gain_dB = fromfile(dtype=numpy.int16, offset=0x36, count=1)
dates = fromfile(dtype=numpy.int16, offset=0x46, count=2)
t0half = fromfile(dtype=numpy.float64, offset=0x96, count=1)
freq_windowed = fromfile(dtype=numpy.int8, offset=0xb6, count=1).any()
arr = fromfile(dtype=numpy.float64, offset=0x800)
max_freq_GHz = metadata[0]
dt_ns = metadata[3] / 2
arrs = numpy.split(arr, 4)
te = arrs[0] + 1j * arrs[1]
tm = arrs[2] + 1j * arrs[3]
meas_date, calib_date = numpy.split(dates, 2)
tt = numpy.arange(arrs[0].size) * dt_ns + t0half * 2
result = OBRData(
te = te,
tm = tm,
t0half = t0half,
dt_ns = dt_ns,
gain_dB = gain_dB,
max_freq_GHz = max_freq_GHz,
ng_setting = ng,
freq_windowed = freq_windowed,
meas_date = meas_date,
calib_date = calib_date,
_wip_metadata = metadata[1:3],
)
"""
Notes on file format
====================
Little endian
Magic bytes: 00 00 60 40 then 'OBR/OFDR' (4 + 8 bytes)
4 floats: (229012, 1.2434e-3, -68.4366, 3.07e-3)
max_freq_GHz ?? ?? 2 * dt
| always same??
changes for extd. range
then two 00 bytes
then ng
0x20: 00 00 00 00
| f64--
0x30: 00 00 00 00 10 40 0c 00 00 00 23 57 00 00 08 00
group index -------| gain | | resolution | data size (i.e. 8 byte float)
res: 05723, 015c8c, 057232; 0025ab for ext rng
equivalent to data length
0x40: 00 00 00 00 04 00
| data bytecount? |
0x40.00.00, may be 2x for extd. range
E7 04 08 00 05 00 19 00 03 00
|year month week? day hour # measurement time
0x50: 12 00 04 00 3F 01 E7 04 08 00 05 00 19 00 03 00
mm ss ms |year month week? day hour # calibration time
0x60: 12 00 04 00 3F 01
mm ss ms |
00 00 00 00 00 00 00 00 00 00
| f64 = -0.80319 ??
0x60: 00 80 F8 A4 E9 BF 00 00 [zeros...]
-------------------|
...
0x90: [...zeros] 00 00 00 40 08 AC 1A C0 00 00
| f64 = -6.668 = t0/2 -----|
0xa0: [all zeros]
0xb0: 00 00 00 00 00 00 01 00 00 C8 41 20 20 20 20 20
|---| | |
| | |sweep rate?
| frequency windowing enabled
[fill with 20 until 0x800]
0x800: [4x arrays of float64: real, imag, real, imag for two polarizations]
"""

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blowback/py.typed Normal file
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blowback/utils.py Normal file
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C0 = 299_792_458 # Speed of light in m/s