Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summary
notebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics
notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "176" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 62 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 60 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2459876 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.379149 | 0.187480 | -0.693824 | -0.454092 | 1.482383 | 4.297396 | 0.681969 | 15.670508 | 0.6669 | 0.6557 | 0.4008 | nan | nan |
2459875 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.066395 | -0.281978 | -0.771162 | -0.813221 | -0.009594 | 0.872557 | -0.248877 | 8.410875 | 0.6799 | 0.6877 | 0.4070 | nan | nan |
2459874 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.233536 | 0.106617 | -0.769292 | -0.861573 | -0.005392 | 0.782835 | 0.324060 | 17.389756 | 0.6680 | 0.6532 | 0.3924 | nan | nan |
2459873 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.279639 | -0.103433 | -0.840130 | -0.746674 | -0.108676 | 0.440143 | -0.411568 | 9.472733 | 0.6722 | 0.6513 | 0.3909 | nan | nan |
2459872 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
2459871 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.001637 | -0.283517 | -0.869239 | -0.750196 | 0.323529 | 1.408811 | -0.279864 | 6.048384 | 0.6761 | 0.6545 | 0.3953 | nan | nan |
2459870 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 360.857563 | 355.082176 | inf | inf | 4145.517215 | 4176.761478 | 12940.395420 | 15241.904457 | nan | nan | nan | nan | nan |
2459869 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
2459868 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 389.855492 | 390.318100 | inf | inf | 7950.066361 | 7331.066870 | 18020.907095 | 15933.948173 | nan | nan | nan | nan | nan |
2459867 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.645356 | -0.265587 | -0.845943 | -0.592229 | -0.130009 | 0.171190 | -0.071029 | 16.693071 | 0.6777 | 0.6581 | 0.4161 | nan | nan |
2459866 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.584176 | -0.294205 | -0.698753 | -0.719443 | 0.724756 | 0.774566 | 2.216063 | 8.580348 | 0.6793 | 0.6614 | 0.4062 | nan | nan |
2459865 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.262619 | -0.353558 | 3.888895 | 3.233300 | 0.365043 | 0.666660 | 6.263123 | 9.450850 | 0.6938 | 0.6735 | 0.3793 | nan | nan |
2459864 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.263251 | -1.213412 | -1.038925 | -1.408006 | -0.131997 | 0.613299 | 0.794938 | 26.887941 | 0.6732 | 0.6513 | 0.4277 | nan | nan |
2459863 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.795996 | 0.040108 | -0.484040 | -0.204464 | -0.344866 | 0.588781 | -0.504288 | 11.572826 | 0.6688 | 0.6436 | 0.4166 | nan | nan |
2459862 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.316588 | 0.384265 | -0.472307 | -1.258647 | 0.605261 | 0.653327 | 0.064035 | 8.604601 | 0.6511 | 0.6685 | 0.4290 | nan | nan |
2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.098479 | 0.195107 | -0.456826 | 0.012602 | -0.249464 | 0.443008 | -0.300465 | 10.759001 | 0.6800 | 0.6519 | 0.4320 | nan | nan |
2459860 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.212697 | 0.306219 | -0.186830 | -0.797995 | 0.264663 | 1.063761 | -0.206850 | 6.521951 | 0.6865 | 0.6538 | 0.4287 | nan | nan |
2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.045654 | -0.128511 | -0.597396 | -0.046849 | -0.434888 | 0.532131 | -0.485663 | 3.757085 | 0.6939 | 0.6603 | 0.4233 | nan | nan |
2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.127152 | 0.175805 | -0.582420 | -0.139417 | -0.441158 | 0.737299 | -0.464343 | 9.572915 | 0.7018 | 0.6647 | 0.4384 | 3.668550 | 3.308617 |
2459857 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.262465 | 0.574799 | -0.179308 | -0.137831 | 1.755094 | 0.558939 | 0.044749 | 2.098259 | 0.0292 | 0.0262 | 0.0017 | nan | nan |
2459856 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.533027 | 0.387499 | 0.137347 | -0.457126 | -0.301851 | 0.949113 | 0.189988 | 5.100789 | 0.6931 | 0.6816 | 0.4189 | 3.324141 | 3.036270 |
2459855 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.077171 | 0.739321 | -0.091206 | -0.657413 | -0.252589 | -0.174690 | -0.122063 | 5.380692 | 0.6656 | 0.6934 | 0.4569 | 3.133653 | 2.776734 |
2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.612961 | -0.447383 | 0.847797 | 1.287229 | -0.526010 | -0.404802 | 0.332160 | 8.793452 | 0.6793 | 0.7130 | 0.4547 | 3.657472 | 3.215022 |
2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.272202 | -0.346315 | 1.014359 | 1.770538 | -0.187058 | -0.014225 | -0.099336 | 11.720701 | 0.7106 | 0.6635 | 0.4455 | 4.173223 | 3.623369 |
2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 7.03% | -0.086863 | 0.444695 | 0.838442 | 1.466492 | 0.239862 | 0.781921 | 3.817055 | 3.765744 | 0.7920 | 0.8023 | 0.2722 | 3.426526 | 3.082228 |
2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.219035 | 0.597027 | 1.215826 | 1.971871 | 0.838204 | 2.719312 | 1.110223 | 14.293929 | 0.7227 | 0.7112 | 0.3619 | 2.652084 | 2.473749 |
2459850 | digital_ok | 0.00% | 0.00% | 0.00% | 0.58% | 18.02% | 0.00% | 0.112142 | -0.793950 | -0.531877 | -0.550425 | -0.744141 | 0.012005 | -0.231538 | 1.177992 | 0.7156 | 0.7364 | 0.3733 | 1.571310 | 1.337187 |
2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.311076 | -1.333282 | 0.903225 | -0.940802 | -1.057707 | 0.412929 | 0.932892 | 6.047691 | 0.7113 | 0.7279 | 0.3770 | 4.112619 | 4.125902 |
2459848 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 30.15% | 0.00% | 0.019938 | -0.927477 | -0.667225 | 1.062761 | -0.980853 | 0.721898 | -0.191841 | 0.774745 | 0.6849 | 0.7251 | 0.3991 | 1.353896 | 1.276229 |
2459847 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.00% | 0.112506 | -0.813003 | -0.295650 | 1.269340 | -0.460462 | 0.376908 | -0.252259 | 0.473354 | 0.6930 | 0.6551 | 0.4483 | 1.452204 | 1.319766 |
2459845 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.02% | 1.66% | 0.704930 | -0.246480 | -0.384592 | 0.892915 | -0.762799 | 0.045981 | -0.030173 | 1.162628 | 0.6875 | 0.7102 | 0.4036 | 1.245382 | 1.245763 |
2459844 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.413933 | 0.799427 | -0.880951 | 1.257057 | -0.585882 | -1.368157 | -0.822268 | -1.167015 | 0.0284 | 0.0258 | 0.0015 | nan | nan |
2459843 | digital_ok | 100.00% | 1.20% | 0.66% | 0.00% | 100.00% | 0.00% | -0.147985 | -0.147978 | -0.662569 | 7.155118 | -0.715549 | 9.468118 | -0.087289 | 1.314207 | 0.7036 | 0.6905 | 0.4119 | 4.474779 | 3.750483 |
2459840 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 268.305142 | 212.345338 | 93.968541 | 61.669659 | 1122.260800 | 829.619845 | 2240.567094 | 1745.346277 | 0.0208 | 0.0173 | 0.0015 | nan | nan |
2459839 | digital_ok | 100.00% | - | - | - | - | - | 43.921364 | 65.598114 | 192.364359 | 219.529336 | 387.397587 | 516.084762 | 2441.405231 | 4165.788922 | nan | nan | nan | nan | nan |
2459838 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 99.39% | 0.61% | 0.108678 | -0.868400 | -0.904010 | -0.043431 | -0.032051 | 1.437968 | -0.683774 | 0.158466 | 0.6515 | 0.6195 | 0.4002 | 0.000000 | 0.000000 |
2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0345 | 0.0317 | 0.0016 | nan | nan |
2459835 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.251288 | 0.316854 | -0.162538 | -0.015552 | 0.641165 | -1.212492 | -1.054547 | -1.881725 | 0.0365 | 0.0316 | 0.0010 | nan | nan |
2459833 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.706788 | 0.672461 | -0.595514 | -0.730533 | -1.288177 | -1.786156 | -0.681339 | -1.473423 | 0.0349 | 0.0317 | 0.0022 | nan | nan |
2459832 | digital_ok | 0.00% | 0.00% | 2.69% | 0.00% | 2.63% | 0.00% | 0.811136 | -0.847920 | -1.069357 | -0.342776 | -0.614230 | 0.394954 | -0.515027 | -0.061096 | 0.7493 | 0.4321 | 0.5729 | 1.619823 | 1.347814 |
2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.289039 | 0.756456 | -0.250774 | -0.458538 | -1.523768 | -1.987317 | -0.816392 | -1.382628 | 0.0386 | 0.0297 | 0.0018 | nan | nan |
2459830 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 2.63% | 0.00% | 0.670234 | -0.902378 | -0.926552 | 0.239614 | 0.015795 | -0.015795 | -0.439446 | 1.609854 | 0.7501 | 0.4462 | 0.5568 | 1.608069 | 1.314350 |
2459829 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.65% | 99.35% | 1.049615 | -0.460621 | -0.909602 | 0.223768 | -0.493882 | 0.513220 | -0.010411 | 3.177897 | 0.6747 | 0.5817 | 0.4116 | 6.713401 | 28.812654 |
2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.700245 | -0.884160 | -0.763922 | -0.051525 | 0.432563 | 0.517416 | 0.858279 | 9.661708 | 0.7452 | 0.4494 | 0.5388 | 0.000000 | 0.000000 |
2459827 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.505548 | -0.297552 | -0.364924 | 1.094200 | -0.718478 | 0.252076 | -0.064967 | 1.591698 | 0.0569 | 0.0728 | 0.0049 | 15.351949 | 41.057445 |
2459826 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.621108 | -0.446415 | -0.460702 | 0.821804 | -0.120189 | 0.666029 | -0.376210 | 1.952170 | 0.0428 | 0.0684 | 0.0055 | 18.669294 | 18.911151 |
2459825 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.053400 | -0.970229 | -0.993976 | 0.039915 | 0.017221 | 0.218181 | -0.333459 | 0.758886 | 0.0426 | 0.0618 | 0.0041 | 0.000000 | 0.000000 |
2459824 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.125205 | -0.063646 | -0.906707 | 0.095574 | -0.980206 | 1.064147 | -0.191677 | 0.087345 | 0.0669 | 0.0726 | 0.0071 | 7.701315 | 22.045517 |
2459823 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.283350 | -0.017149 | -0.313364 | 0.999755 | 0.159393 | 0.517547 | -0.258183 | 3.981721 | 0.0528 | 0.0648 | 0.0077 | 219.337532 | 100.126732 |
2459822 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.152784 | -0.788094 | -0.494150 | 0.637869 | 0.049549 | -0.002923 | -0.042345 | -0.036795 | 0.0526 | 0.0686 | 0.0107 | 1.236582 | 1.237240 |
2459821 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 364.940315 | 365.150607 | inf | inf | 726.073916 | 919.716499 | 1095.723916 | 1326.666179 | nan | nan | nan | 0.000000 | 0.000000 |
2459820 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.455195 | -0.665599 | -0.376955 | 0.902056 | -0.055985 | 1.675831 | -0.694271 | -0.606118 | 0.0570 | 0.0667 | 0.0078 | 0.887608 | 0.886776 |
2459817 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.224189 | -0.852810 | -0.636670 | 0.537542 | -0.782006 | -0.828412 | -0.603303 | -0.698305 | 0.0555 | 0.0662 | 0.0076 | 1.237482 | 1.231811 |
2459816 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.718341 | -0.498855 | -1.096652 | -0.075920 | -0.755124 | -0.871004 | -0.327792 | -0.997452 | 0.8456 | 0.5479 | 0.6318 | 1.828548 | 1.445884 |
2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.089380 | -0.674291 | -1.026684 | 0.373720 | -0.155130 | -0.097269 | -0.661615 | -0.647945 | 0.7880 | 0.6177 | 0.5498 | 1.688523 | 1.327031 |
2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics
notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics
notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 15.670508 | 0.379149 | 0.187480 | -0.693824 | -0.454092 | 1.482383 | 4.297396 | 0.681969 | 15.670508 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 8.410875 | -0.066395 | -0.281978 | -0.771162 | -0.813221 | -0.009594 | 0.872557 | -0.248877 | 8.410875 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 17.389756 | 0.233536 | 0.106617 | -0.769292 | -0.861573 | -0.005392 | 0.782835 | 0.324060 | 17.389756 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 9.472733 | -0.279639 | -0.103433 | -0.840130 | -0.746674 | -0.108676 | 0.440143 | -0.411568 | 9.472733 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 6.048384 | -0.283517 | -0.001637 | -0.750196 | -0.869239 | 1.408811 | 0.323529 | 6.048384 | -0.279864 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Power | inf | 360.857563 | 355.082176 | inf | inf | 4145.517215 | 4176.761478 | 12940.395420 | 15241.904457 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Power | inf | 389.855492 | 390.318100 | inf | inf | 7950.066361 | 7331.066870 | 18020.907095 | 15933.948173 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 16.693071 | 0.645356 | -0.265587 | -0.845943 | -0.592229 | -0.130009 | 0.171190 | -0.071029 | 16.693071 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 8.580348 | -0.294205 | 0.584176 | -0.719443 | -0.698753 | 0.774566 | 0.724756 | 8.580348 | 2.216063 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 9.450850 | 0.262619 | -0.353558 | 3.888895 | 3.233300 | 0.365043 | 0.666660 | 6.263123 | 9.450850 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 26.887941 | -1.213412 | -0.263251 | -1.408006 | -1.038925 | 0.613299 | -0.131997 | 26.887941 | 0.794938 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 11.572826 | 0.795996 | 0.040108 | -0.484040 | -0.204464 | -0.344866 | 0.588781 | -0.504288 | 11.572826 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 8.604601 | 0.316588 | 0.384265 | -0.472307 | -1.258647 | 0.605261 | 0.653327 | 0.064035 | 8.604601 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 10.759001 | 0.195107 | 0.098479 | 0.012602 | -0.456826 | 0.443008 | -0.249464 | 10.759001 | -0.300465 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 6.521951 | 0.212697 | 0.306219 | -0.186830 | -0.797995 | 0.264663 | 1.063761 | -0.206850 | 6.521951 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 3.757085 | 0.045654 | -0.128511 | -0.597396 | -0.046849 | -0.434888 | 0.532131 | -0.485663 | 3.757085 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 9.572915 | 0.175805 | 0.127152 | -0.139417 | -0.582420 | 0.737299 | -0.441158 | 9.572915 | -0.464343 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 2.098259 | 0.574799 | -0.262465 | -0.137831 | -0.179308 | 0.558939 | 1.755094 | 2.098259 | 0.044749 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 5.100789 | 0.533027 | 0.387499 | 0.137347 | -0.457126 | -0.301851 | 0.949113 | 0.189988 | 5.100789 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 5.380692 | 0.739321 | 0.077171 | -0.657413 | -0.091206 | -0.174690 | -0.252589 | 5.380692 | -0.122063 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 8.793452 | -0.447383 | -0.612961 | 1.287229 | 0.847797 | -0.404802 | -0.526010 | 8.793452 | 0.332160 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 11.720701 | -0.346315 | -0.272202 | 1.770538 | 1.014359 | -0.014225 | -0.187058 | 11.720701 | -0.099336 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Temporal Discontinuties | 3.817055 | -0.086863 | 0.444695 | 0.838442 | 1.466492 | 0.239862 | 0.781921 | 3.817055 | 3.765744 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 14.293929 | 0.219035 | 0.597027 | 1.215826 | 1.971871 | 0.838204 | 2.719312 | 1.110223 | 14.293929 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 1.177992 | 0.112142 | -0.793950 | -0.531877 | -0.550425 | -0.744141 | 0.012005 | -0.231538 | 1.177992 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 6.047691 | 0.311076 | -1.333282 | 0.903225 | -0.940802 | -1.057707 | 0.412929 | 0.932892 | 6.047691 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 1.062761 | -0.927477 | 0.019938 | 1.062761 | -0.667225 | 0.721898 | -0.980853 | 0.774745 | -0.191841 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 1.269340 | -0.813003 | 0.112506 | 1.269340 | -0.295650 | 0.376908 | -0.460462 | 0.473354 | -0.252259 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 1.162628 | -0.246480 | 0.704930 | 0.892915 | -0.384592 | 0.045981 | -0.762799 | 1.162628 | -0.030173 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 1.257057 | 0.413933 | 0.799427 | -0.880951 | 1.257057 | -0.585882 | -1.368157 | -0.822268 | -1.167015 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Variability | 9.468118 | -0.147978 | -0.147985 | 7.155118 | -0.662569 | 9.468118 | -0.715549 | 1.314207 | -0.087289 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Temporal Discontinuties | 2240.567094 | 268.305142 | 212.345338 | 93.968541 | 61.669659 | 1122.260800 | 829.619845 | 2240.567094 | 1745.346277 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 4165.788922 | 65.598114 | 43.921364 | 219.529336 | 192.364359 | 516.084762 | 387.397587 | 4165.788922 | 2441.405231 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Variability | 1.437968 | -0.868400 | 0.108678 | -0.043431 | -0.904010 | 1.437968 | -0.032051 | 0.158466 | -0.683774 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Temporal Variability | 0.641165 | 0.316854 | 0.251288 | -0.015552 | -0.162538 | -1.212492 | 0.641165 | -1.881725 | -1.054547 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Shape | 0.672461 | 0.672461 | -0.706788 | -0.730533 | -0.595514 | -1.786156 | -1.288177 | -1.473423 | -0.681339 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Shape | 0.811136 | 0.811136 | -0.847920 | -1.069357 | -0.342776 | -0.614230 | 0.394954 | -0.515027 | -0.061096 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Shape | 0.756456 | -0.289039 | 0.756456 | -0.250774 | -0.458538 | -1.523768 | -1.987317 | -0.816392 | -1.382628 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 1.609854 | 0.670234 | -0.902378 | -0.926552 | 0.239614 | 0.015795 | -0.015795 | -0.439446 | 1.609854 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 3.177897 | -0.460621 | 1.049615 | 0.223768 | -0.909602 | 0.513220 | -0.493882 | 3.177897 | -0.010411 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 9.661708 | -0.884160 | 0.700245 | -0.051525 | -0.763922 | 0.517416 | 0.432563 | 9.661708 | 0.858279 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 1.591698 | 0.505548 | -0.297552 | -0.364924 | 1.094200 | -0.718478 | 0.252076 | -0.064967 | 1.591698 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 1.952170 | -0.446415 | 0.621108 | 0.821804 | -0.460702 | 0.666029 | -0.120189 | 1.952170 | -0.376210 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 0.758886 | -0.970229 | -0.053400 | 0.039915 | -0.993976 | 0.218181 | 0.017221 | 0.758886 | -0.333459 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Shape | 1.125205 | 1.125205 | -0.063646 | -0.906707 | 0.095574 | -0.980206 | 1.064147 | -0.191677 | 0.087345 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Discontinuties | 3.981721 | -0.017149 | -0.283350 | 0.999755 | -0.313364 | 0.517547 | 0.159393 | 3.981721 | -0.258183 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 0.637869 | -0.152784 | -0.788094 | -0.494150 | 0.637869 | 0.049549 | -0.002923 | -0.042345 | -0.036795 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | inf | 365.150607 | 364.940315 | inf | inf | 919.716499 | 726.073916 | 1326.666179 | 1095.723916 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Temporal Variability | 1.675831 | 0.455195 | -0.665599 | -0.376955 | 0.902056 | -0.055985 | 1.675831 | -0.694271 | -0.606118 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 0.537542 | -0.224189 | -0.852810 | -0.636670 | 0.537542 | -0.782006 | -0.828412 | -0.603303 | -0.698305 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | ee Shape | 0.718341 | -0.498855 | 0.718341 | -0.075920 | -1.096652 | -0.871004 | -0.755124 | -0.997452 | -0.327792 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Power | 0.373720 | -0.674291 | -0.089380 | 0.373720 | -1.026684 | -0.097269 | -0.155130 | -0.647945 | -0.661615 |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
176 | N12 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |