AUX_ISR_1B
Contents
AUX_ISR_1B¶
Abstract: Access to auxiliary ISR product
%load_ext watermark
%watermark -i -v -p viresclient,pandas,xarray,matplotlib
Python implementation: CPython
Python version : 3.9.7
IPython version : 8.0.1
viresclient: 0.11.0
pandas : 1.4.1
xarray : 0.21.1
matplotlib : 3.5.1
from viresclient import AeolusRequest
import datetime as dt
import matplotlib.pyplot as plt
request = AeolusRequest()
Product information¶
Description of product.
Documentation:
request.set_collection('AUX_ISR_1B')
request.set_fields(fields=[
"time",
"freq_mie_USR_closest_to_rayleigh_filter_centre",
"frequency_rayleigh_filter_centre",
"num_of_valid_mie_results",
"num_of_valid_rayleigh_results",
"laser_frequency_offset",
"mie_valid",
"rayleigh_valid",
"fizeau_transmission",
"mie_response",
"rayleigh_channel_A_response",
"rayleigh_channel_B_response",
"num_of_raw_reference_pulses",
"num_of_mie_reference_pulses",
"num_of_rayleigh_reference_pulses",
"accumulated_laser_energy_mie",
"mean_laser_energy_mie",
"accumulated_laser_energy_rayleigh",
"mean_laser_energy_rayleigh",
"laser_energy_drift",
"downhill_simplex_used",
"num_of_iterations_mie_core_1",
"last_peak_difference_mie_core_1",
"FWHM_mie_core_2",
"num_of_iterations_mie_core_2",
"downhill_simplex_quality_flag",
"rayleigh_spectrometer_temperature_9",
"rayleigh_spectrometer_temperature_10",
"rayleigh_spectrometer_temperature_11",
"rayleigh_thermal_hood_temperature_1",
"rayleigh_thermal_hood_temperature_2",
"rayleigh_thermal_hood_temperature_3",
"rayleigh_thermal_hood_temperature_4",
"rayleigh_optical_baseplate_avg_temperature"
])
data = request.get_between(
start_time="2020-06-01T03:00:58Z",
end_time="2020-06-01T03:30:22Z",
filetype="nc",
asynchronous=False
)
ds = data.as_xarray()
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
plt.rcParams["figure.figsize"] = (25,12)
fig, ax = plt.subplots()
ax.plot(
ds.laser_frequency_offset.values,
ds.rayleigh_channel_A_response.values,
label="rayleigh_channel_A_response",
color="b"
)
ax.scatter(
ds.laser_frequency_offset.values,
ds.rayleigh_channel_A_response.values,
s=30, facecolors='none', edgecolors='b',
)
ax.plot(
ds.laser_frequency_offset.values,
ds.rayleigh_channel_B_response.values,
label="rayleigh_channel_B_response",
color="r"
)
ax.scatter(
ds.laser_frequency_offset.values,
ds.rayleigh_channel_B_response.values,
s=30, facecolors='none', edgecolors='r', marker="s",
)
plt.legend()
<matplotlib.legend.Legend at 0x7fd522506100>
