Fix typo & add 2024_06_07 observation

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linarphy 2024-08-28 18:59:47 +02:00
parent 3bbcc3bbed
commit 03d704b97a
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4 changed files with 266 additions and 1 deletions

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@ -0,0 +1,186 @@
#!/usr/bin/env python3
from gettext import install
from backscattering_analyzer.display import show_projection # type: ignore[reportMissingTypeStubs]
from backscattering_analyzer.experiment import AcquisitionType, Experiment # type: ignore[reportMissingTypeStubs]
from logging import basicConfig, getLogger
from rich.console import Console
from rich.theme import Theme
from rich.logging import RichHandler
from warnings import filterwarnings
from command_parser.flag import Flag # type: ignore[reportMissingTypeStubs]
from command_parser.value import Value # type: ignore[reportMissingTypeStubs]
from command_parser.parser import parse # type: ignore[reportMissingTypeStubs]
from sys import argv
from importlib.metadata import version
install(__name__)
filterwarnings("error")
flags = [
Flag("help"),
Flag("version", single_char="V"),
Flag("verbose"),
Flag("full"),
]
values = [
Value("date", "2023_03_24"),
Value("bench", "SDB1"),
Value("file", "values.toml", single_char="F"),
Value("vibration-frequency", "0.2"),
]
parse(" ".join(argv[1:]), flags, values)
if flags[0].value:
theme = Theme(
{
"main": "white bold",
"option": "grey50 italic",
"argument": "red",
"description": "green italic",
}
)
console = Console(theme=theme)
help = (
"[main]display[/main] [option]\\[options][/option]"
"\n [argument]-b --bench[/argument] [description]bench of the experiment[/description]"
"\n [argument]-d --date[/argument] [description]date of the experiment[/description]"
"\n [argument]-h --help[/argument] [description]print this help and exit[/description]"
"\n [argument]-f --full[/argument] [description]run experiment with all benches with all dates[/description]"
"\n [argument]-F --file[/argument] [description]file containing all the parameters values (toml file)[/description]"
"\n [argument]-v --verbose[/argument] [description]be verbose[/description]"
"\n [argument]-V --version[/argument] [description]print version number and exit[/description]"
)
console.print(help)
exit(0)
if flags[1].value:
version = (
"Versions\n"
"numpy {numpy}\n"
"scipy {scipy}\n"
"matplotlib {matplotlib}\n"
"science_signal {science_signal}\n"
"backscattering_analyzer {backscattering_analyzer}\n"
"command_parser {command_parser}\n"
"script 0.1.0\n"
).format(
numpy=version("numpy"),
scipy=version("scipy"),
matplotlib=version("matplotlib"),
science_signal=version("science_signal"),
backscattering_analyzer=version("backscattering_analyzer"),
command_parser=version("command_parser"),
)
console = Console()
console.print(version)
exit(0)
if flags[2].value:
level = "DEBUG"
else:
level = "INFO"
basicConfig(
level=level,
format="%(message)s",
datefmt="[%X]",
handlers=[RichHandler()],
)
logger = getLogger(__name__)
if flags[3].value:
logger.debug(_("loading every experiments"))
experiments: list[Experiment] = []
results: dict[str, float | None] = dict({})
for bench in ["SDB1", "SDB2", "SNEB", "SWEB"]:
if bench in ["SDB1", "SDB2"]:
experiment = Experiment(
bench,
"2023_03_24",
values[2].value,
float(values[3].value),
)
if bench == "SDB1":
start_frequency, end_frequency = 12.5, 30
else:
start_frequency, end_frequency = 40, 50
experiment.factors = experiment.fit_factors(
start_frequency=start_frequency,
end_frequency=end_frequency,
)
results[
"{bench}-{date}".format(
bench=bench,
date="2023_03_24",
)
] = experiment.factors["true"]
elif bench == "SNEB":
for date in ["2023_03_24", "2024_01_21"]:
experiment = Experiment(
bench,
date,
values[2].value,
float(values[3].value),
)
experiment.factors = experiment.fit_factors(
start_frequency=15,
end_frequency=100,
)
results["{bench}-{date}".format(bench=bench, date=date)] = (
experiment.factors["true"]
)
else: # bench == SWEB
for date in ["2023_03_24", "2023_12_20"]:
experiment = Experiment(
bench,
date,
values[2].value,
float(values[3].value),
)
experiment.factors = experiment.fit_factors(
start_frequency=15,
end_frequency=100,
)
results["{bench}-{date}".format(bench=bench, date=date)] = (
experiment.factors["true"]
)
console = Console()
console.print(results)
else:
experiment = Experiment(
values[1].value, values[0].value, values[2].value, float(values[3].value)
)
if experiment.bench == "SDB1":
start_frequency, end_frequency = 12.5, 30
elif experiment.bench == "SDB2":
start_frequency, end_frequency = 40, 50
else:
start_frequency, end_frequency = 15, 100
try:
experiment.factors = experiment.fit_factors(
start_frequency=start_frequency,
end_frequency=end_frequency,
)
experiment.projection_reference = experiment.compute_projection(
AcquisitionType.REFERENCE
)
experiment.projection_excited = experiment.compute_projection(
AcquisitionType.EXCITED
)
except AttributeError:
pass
#show_projection(experiment, start_frequency, end_frequency)
import matplotlib.pyplot as plt
plt.loglog(experiment.coupling[0].x, experiment.coupling[0].y)
plt.loglog(experiment.coupling[1].x, experiment.coupling[1].y)
plt.show()
exit(0)

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@ -93,7 +93,7 @@ basicConfig(
logger = getLogger(__name__)
if flags[3].value:
logger.debug(_("loading every experiments"))
logger.debug(_("loading every experiments")) # type: ignore[reportUnknownArgumentType]
experiments: list[Experiment] = []
results: dict[str, float | None] = dict({})
for bench in ["SDB1", "SDB2", "SNEB", "SWEB"]:

74
figure_overleaf.py Executable file
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@ -0,0 +1,74 @@
#!/usr/bin/env python3
from gettext import install
from logging import basicConfig, getLogger
from warnings import filterwarnings
from backscattering_analyzer.acquisition import AcquisitionType
from backscattering_analyzer.experiment import Experiment
from rich.logging import RichHandler
from matplotlib.pyplot import figure, show
install(__name__)
filterwarnings("error")
basicConfig(
level = "INFO",
format = "%(message)s",
datefmt = "[%X]",
handlers = [RichHandler()],
)
logger = getLogger(__name__)
date = "2024_06_07"
bancs = [
"SNEB",
"SWEB",
"SDB1",
"SDB2",
]
experiment = Experiment(
bench = bancs[0],
date = date,
values_file = "values-coupling.toml",
)
reference = experiment.data.reference.sensibility.psd().sqrt()
projections = [experiment.compute_projection(
type = AcquisitionType.REFERENCE,
)]
for banc in bancs[1:]:
experiment = Experiment(
bench = banc,
date = date,
values_file = "values-coupling.toml",
)
projections.append(experiment.compute_projection( # type: ignore[reportUnknownVariable]
type = AcquisitionType.REFERENCE,
))
fig = figure()
axes = fig.add_subplot(1, 1, 1) # type: ignore[reportUnknownVariable]
axes.loglog( # type: ignore[reportUnknownVariable]
reference.x,
reference.y,
)
for index in range(len(bancs)):
axes.loglog( # type: ignore[reportUnknownVariable]
projections[index].x,
projections[index].y,
label = _("{bench} projection").format(bench = bancs[index]) # type: ignore[reportUnknownVariable]
)
axes.set_xlabel(_("frequencies")) # type: ignore[reportUnknownVariable]
axes.set_ylabel(_("sensibility ($\\frac{1}{\\sqrt{Hz}}$)")) # type: ignore[reportUnknownVariable]
axes.set_title(_("Projection pour un interféromètre dans une condition nominale")) # type: ignore[reportUnknownVariable]
temp = axes.set_xlim(5, 100)
temp = axes.set_ylim(10e-28, 10e-18)
temp = axes.legend() # type: ignore[reportUnknownVariable]
axes.grid(True, "both") # type: ignore[reportUnknownVariable]
show()

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@ -49,3 +49,8 @@
dark_fringe = 4.445e-3
modelisation = "scatterCoupling_dec_jan.mat"
correct-power = false
[dates.2024_06_07]
laser = 12.1
dark_fringe = 4.445e-3
modelisation = "scatterCoupling_dec_jan.mat"
correct-power = false