Basic usage: Array1DScanAnalyzer¶
Array1DScanAnalyzer is the 1D analog of Array2DScanAnalyzer. Same shape of workflow — wrap an ImageAnalyzer that produces 1D (x vs y) data, run it across every shot in a scan, render results — but the output rendering produces a waterfall plot (one trace per bin) instead of a montage of averaged images.
Same Mode-2 / Mode-1 split as the 2D wrapper: a unified diagnostic YAML drives the common case, in-code construction handles ad-hoc tweaks.
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import logging
import time
from IPython.display import Image, display
from geecs_data_utils import ScanPaths, ScanTag
from geecs_data_utils.config_roots import image_analysis_config
from image_analysis.config import load_diagnostic, load_line_config
from scan_analysis.config import create_scan_analyzer
from scan_analysis.analyzers.common.array1d_scan_analysis import Array1DScanAnalyzer
from image_analysis.analyzers.standard_1d_analyzer import Standard1DAnalyzer
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
logging.getLogger("image_analysis").setLevel(logging.WARNING)
logging.getLogger("scan_analysis").setLevel(logging.WARNING)
logging.getLogger("geecs_data_utils").setLevel(logging.WARNING)
# Required for Mode 1's load_line_config; Mode 2 falls back to
# ScanPaths.paths_config.scan_analysis_configs_path automatically.
image_analysis_config.set_base_dir(ScanPaths.paths_config.image_analysis_configs_path)
import logging
import time
from IPython.display import Image, display
from geecs_data_utils import ScanPaths, ScanTag
from geecs_data_utils.config_roots import image_analysis_config
from image_analysis.config import load_diagnostic, load_line_config
from scan_analysis.config import create_scan_analyzer
from scan_analysis.analyzers.common.array1d_scan_analysis import Array1DScanAnalyzer
from image_analysis.analyzers.standard_1d_analyzer import Standard1DAnalyzer
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
logging.getLogger("image_analysis").setLevel(logging.WARNING)
logging.getLogger("scan_analysis").setLevel(logging.WARNING)
logging.getLogger("geecs_data_utils").setLevel(logging.WARNING)
# Required for Mode 1's load_line_config; Mode 2 falls back to
# ScanPaths.paths_config.scan_analysis_configs_path automatically.
image_analysis_config.set_base_dir(ScanPaths.paths_config.image_analysis_configs_path)
Out[1]:
PosixPath('/Users/samuelbarber/Desktop/Code/Github_repos/GEECS-Plugins-Configs/scan_analysis_configs/analyzers')
Mode 2 — Load from a unified diagnostic YAML¶
The YAML declares everything: the analyzer class, the line-config pipeline (data loading, ROI, background, filtering, interpolation), and the scan-side runtime config (priority, file_tail, renderer kwargs).
create_scan_analyzer picks the right wrapper class from the type of diag.image. A Line1DConfig routes to Array1DScanAnalyzer; the file_tail / renderer_kwargs / save flags come straight from the YAML's scan: block.
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test_tag = ScanTag(year=2025, month=11, day=13, number=1, experiment="Undulator")
diag = load_diagnostic("U_BCaveICT")
scan_analyzer = create_scan_analyzer(diag)
t0 = time.monotonic()
result = scan_analyzer.run_analysis(scan_tag=test_tag)
print(f"execution time: {time.monotonic() - t0:.2f}s")
display(Image(filename=str(result[0]), width=500))
test_tag = ScanTag(year=2025, month=11, day=13, number=1, experiment="Undulator")
diag = load_diagnostic("U_BCaveICT")
scan_analyzer = create_scan_analyzer(diag)
t0 = time.monotonic()
result = scan_analyzer.run_analysis(scan_tag=test_tag)
print(f"execution time: {time.monotonic() - t0:.2f}s")
display(Image(filename=str(result[0]), width=500))
Mode 1 — In-code construction with notebook-time tweaks¶
Useful when you want to override an ROI, change the renderer's colormap, or use a different analysis_mode (per_shot vs per_bin) than the YAML declares.
Below: same scan, but built imperatively with an explicit analysis_mode="per_shot" and a custom renderer_kwargs for diverging scope traces.
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line_config = load_line_config("U_BCaveICT")
# Notebook-time tweak — narrow the ROI on the fly
# (line_config.roi.x_min = 0.0e-6 ; line_config.roi.x_max = 10.0e-6)
image_analyzer = Standard1DAnalyzer(line_config=line_config)
scan_analyzer_m1 = Array1DScanAnalyzer(
image_analyzer=image_analyzer,
device_name="U_BCaveICT",
analysis_mode="per_shot",
file_tail=".tdms",
renderer_kwargs={
"colormap_mode": "diverging",
"cmap": "RdBu_r",
},
)
result = scan_analyzer_m1.run_analysis(scan_tag=test_tag)
display(Image(filename=str(result[0]), width=500))
line_config = load_line_config("U_BCaveICT")
# Notebook-time tweak — narrow the ROI on the fly
# (line_config.roi.x_min = 0.0e-6 ; line_config.roi.x_max = 10.0e-6)
image_analyzer = Standard1DAnalyzer(line_config=line_config)
scan_analyzer_m1 = Array1DScanAnalyzer(
image_analyzer=image_analyzer,
device_name="U_BCaveICT",
analysis_mode="per_shot",
file_tail=".tdms",
renderer_kwargs={
"colormap_mode": "diverging",
"cmap": "RdBu_r",
},
)
result = scan_analyzer_m1.run_analysis(scan_tag=test_tag)
display(Image(filename=str(result[0]), width=500))
A line analyzer with ROI tweak — LineAnalyzer on MagSpec data¶
The same pattern works for any 1D analyzer. Here LineAnalyzer (a general-purpose 1D pipeline) processes BCave MagSpec interpolated-spectrum files. Mode 1 again, to demonstrate touching the line config in code.
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from image_analysis.analyzers.line_analyzer import LineAnalyzer
mag_tag = ScanTag(year=2026, month=2, day=12, number=22, experiment="Undulator")
dev = "U_BCaveMagSpec-interpSpec"
line_config = load_line_config("BcaveMagSpecStitcherSpec")
line_config.roi.x_min = 60
line_config.roi.x_max = 200
image_analyzer = LineAnalyzer(line_config=line_config)
scan_analyzer_mag = Array1DScanAnalyzer(
image_analyzer=image_analyzer,
device_name=dev,
file_tail=".txt",
)
result = scan_analyzer_mag.run_analysis(scan_tag=mag_tag)
display(Image(filename=str(result[0]), width=500))
from image_analysis.analyzers.line_analyzer import LineAnalyzer
mag_tag = ScanTag(year=2026, month=2, day=12, number=22, experiment="Undulator")
dev = "U_BCaveMagSpec-interpSpec"
line_config = load_line_config("BcaveMagSpecStitcherSpec")
line_config.roi.x_min = 60
line_config.roi.x_max = 200
image_analyzer = LineAnalyzer(line_config=line_config)
scan_analyzer_mag = Array1DScanAnalyzer(
image_analyzer=image_analyzer,
device_name=dev,
file_tail=".txt",
)
result = scan_analyzer_mag.run_analysis(scan_tag=mag_tag)
display(Image(filename=str(result[0]), width=500))
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test_tag = ScanTag(year=2026, month=5, day=13, number=8, experiment="Undulator")
diag = load_diagnostic("U_FROG_Grenouille-SpectralPhase")
scan_analyzer = create_scan_analyzer(diag)
t0 = time.monotonic()
result = scan_analyzer.run_analysis(scan_tag=test_tag)
print(f"execution time: {time.monotonic() - t0:.2f}s")
display(Image(filename=str(result[0]), width=500))
test_tag = ScanTag(year=2026, month=5, day=13, number=8, experiment="Undulator")
diag = load_diagnostic("U_FROG_Grenouille-SpectralPhase")
scan_analyzer = create_scan_analyzer(diag)
t0 = time.monotonic()
result = scan_analyzer.run_analysis(scan_tag=test_tag)
print(f"execution time: {time.monotonic() - t0:.2f}s")
display(Image(filename=str(result[0]), width=500))
2026-05-28 19:15:54,806 - scan_analysis.analyzers.common.single_device_scan_analyzer - WARNING - No file found for shot 1
2026-05-28 19:16:03,202 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,203 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,203 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,204 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,206 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,207 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,207 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,208 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,209 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,209 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,210 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,211 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,213 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,214 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,214 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,215 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 15 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,217 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,217 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,218 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,219 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,221 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,221 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,221 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,222 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,224 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,224 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,224 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,225 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(122,), (123,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,226 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 15 shots: inhomogeneous shapes [(122,), (123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,226 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 15 shots: inhomogeneous shapes [(122,), (123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,227 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 15 shots: inhomogeneous shapes [(122,), (123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,227 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 15 shots: inhomogeneous shapes [(122,), (123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,228 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,228 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,229 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,229 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,231 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(123,), (245,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,231 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(123,), (245,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,231 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(123,), (245,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,232 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(123,), (245,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,233 - image_analysis.types - WARNING - Cannot average render_data['fit_valid_mask'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,233 - image_analysis.types - WARNING - Cannot average render_data['raw_spectral_phase'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,234 - image_analysis.types - WARNING - Cannot average render_data['fit_normalized_reference'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:03,234 - image_analysis.types - WARNING - Cannot average render_data['raw_wavelength_nm'] across 16 shots: inhomogeneous shapes [(123,), (245,), (246,)]. Skipping this field in the averaged result.
2026-05-28 19:16:10,966 - scan_analysis.base - WARNING - append_to_sfile: columns already exist in s-file: {'U_FROG_Grenouille-SpectralPhase_tod_fs3', 'U_FROG_Grenouille-SpectralPhase_gdd_fs2', 'U_FROG_Grenouille-SpectralPhase_flipped', 'U_FROG_Grenouille-SpectralPhase_phi0_rad', 'U_FROG_Grenouille-SpectralPhase_gd_fs'} (will overwrite)
2026-05-28 19:16:11,335 - scan_analysis.base - WARNING - append_to_sfile: 1 shot(s) missing in update for U_FROG_Grenouille-Temporal; existing rows will be kept unchanged
execution time: 26.86s
Note: Array1DScanAnalyzer can consume 2D source data¶
When an ImageAnalyzer is designed to convert a 2D source image into 1D data (e.g., a homebuilt optical spectrometer that uses a CCD), it returns the x-vs-y data on the ImageAnalyzerResult.return_lineouts field and leaves processed_image blank. Array1DScanAnalyzer consumes the lineouts and renders a waterfall plot exactly as it would for native 1D data — no special wiring needed on the wrapper side.
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scan_analyzer.binned_data[10]
scan_analyzer.binned_data[10]
Out[11]:
{'value': 41649.92375,
'result': ImageAnalyzerResult(data_type='1d', processed_image=None, line_data=array([[ 7.97150578e+02, 6.20192675e-01],
[ 7.97230164e+02, 6.00501726e-01],
[ 7.97309767e+02, 5.81071061e-01],
[ 7.97389387e+02, 5.61899444e-01],
[ 7.97469024e+02, 5.42985643e-01],
[ 7.97548678e+02, 5.24328421e-01],
[ 7.97628348e+02, 5.05926543e-01],
[ 7.97708035e+02, 4.87778777e-01],
[ 7.97787739e+02, 4.69883885e-01],
[ 7.97867460e+02, 4.52240635e-01],
[ 7.97947198e+02, 4.34847792e-01],
[ 7.98026953e+02, 4.17704119e-01],
[ 7.98106724e+02, 4.00808384e-01],
[ 7.98186513e+02, 3.84159352e-01],
[ 7.98266318e+02, 3.67755786e-01],
[ 7.98346140e+02, 3.51596454e-01],
[ 7.98425979e+02, 3.35680121e-01],
[ 7.98505835e+02, 3.20005550e-01],
[ 7.98585708e+02, 3.04571509e-01],
[ 7.98665597e+02, 2.89376762e-01],
[ 7.98745504e+02, 2.74420075e-01],
[ 7.98825427e+02, 2.59700213e-01],
[ 7.98905368e+02, 2.45215941e-01],
[ 7.98985325e+02, 2.30966025e-01],
[ 7.99065299e+02, 2.16949230e-01],
[ 7.99145290e+02, 2.03164321e-01],
[ 7.99225298e+02, 1.89610064e-01],
[ 7.99305323e+02, 1.76285223e-01],
[ 7.99385365e+02, 1.63188565e-01],
[ 7.99465424e+02, 1.50318855e-01],
[ 7.99545500e+02, 1.37674857e-01],
[ 7.99625593e+02, 1.25255338e-01],
[ 7.99705702e+02, 1.13059063e-01],
[ 7.99785829e+02, 1.01084796e-01],
[ 7.99865973e+02, 8.93313040e-02],
[ 7.99946133e+02, 7.77973514e-02],
[ 8.00026311e+02, 6.64817038e-02],
[ 8.00106506e+02, 5.53831264e-02],
[ 8.00186717e+02, 4.45003847e-02],
[ 8.00266946e+02, 3.38322439e-02],
[ 8.00347192e+02, 2.33774694e-02],
[ 8.00427455e+02, 1.31348265e-02],
[ 8.00507734e+02, 3.10308058e-03],
[ 8.00588031e+02, -6.71900308e-03],
[ 8.00668345e+02, -1.63326591e-02],
[ 8.00748676e+02, -2.57391222e-02],
[ 8.00829024e+02, -3.49396271e-02],
[ 8.00909388e+02, -4.39354083e-02],
[ 8.00989770e+02, -5.27277006e-02],
[ 8.01070170e+02, -6.13177386e-02],
[ 8.01150586e+02, -6.97067570e-02],
[ 8.01231019e+02, -7.78959905e-02],
[ 8.01311469e+02, -8.58866738e-02],
[ 8.01391936e+02, -9.36800414e-02],
[ 8.01472421e+02, -1.01277328e-01],
[ 8.01552922e+02, -1.08679769e-01],
[ 8.01633441e+02, -1.15888597e-01],
[ 8.01713977e+02, -1.22905049e-01],
[ 8.01794530e+02, -1.29730359e-01],
[ 8.01875100e+02, -1.36365761e-01],
[ 8.01955687e+02, -1.42812490e-01],
[ 8.02036291e+02, -1.49071781e-01],
[ 8.02116912e+02, -1.55144869e-01],
[ 8.02197551e+02, -1.61032987e-01],
[ 8.02278207e+02, -1.66737371e-01],
[ 8.02358879e+02, -1.72259256e-01],
[ 8.02439569e+02, -1.77599876e-01],
[ 8.02520277e+02, -1.82760465e-01],
[ 8.02601001e+02, -1.87742259e-01],
[ 8.02681742e+02, -1.92546492e-01],
[ 8.02762501e+02, -1.97174399e-01],
[ 8.02843277e+02, -2.01627214e-01],
[ 8.02924070e+02, -2.05906173e-01],
[ 8.03004880e+02, -2.10012509e-01],
[ 8.03085708e+02, -2.13947457e-01],
[ 8.03166552e+02, -2.17712253e-01],
[ 8.03247414e+02, -2.21308130e-01],
[ 8.03328293e+02, -2.24736324e-01],
[ 8.03409190e+02, -2.27998069e-01],
[ 8.03490103e+02, -2.31094600e-01],
[ 8.03571034e+02, -2.34027151e-01],
[ 8.03651982e+02, -2.36796958e-01],
[ 8.03732948e+02, -2.39405254e-01],
[ 8.03813930e+02, -2.41853274e-01],
[ 8.03894930e+02, -2.44142254e-01],
[ 8.03975947e+02, -2.46273428e-01],
[ 8.04056982e+02, -2.48248030e-01],
[ 8.04138033e+02, -2.50067295e-01],
[ 8.04219102e+02, -2.51732458e-01],
[ 8.04300188e+02, -2.53244753e-01],
[ 8.04381292e+02, -2.54605416e-01],
[ 8.04462413e+02, -2.55815680e-01],
[ 8.04543551e+02, -2.56876781e-01],
[ 8.04624706e+02, -2.57789953e-01],
[ 8.04705879e+02, -2.58556431e-01],
[ 8.04787069e+02, -2.59177449e-01],
[ 8.04868277e+02, -2.59654242e-01],
[ 8.04949502e+02, -2.59988046e-01],
[ 8.05030744e+02, -2.60180093e-01],
[ 8.05112003e+02, -2.60231620e-01],
[ 8.05193280e+02, -2.60143861e-01],
[ 8.05274574e+02, -2.59918050e-01],
[ 8.05355886e+02, -2.59555422e-01],
[ 8.05437215e+02, -2.59057213e-01],
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