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 = "75" 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 61 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 59 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 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 11.889235 | 19.418012 | 7.480354 | 53.967781 | 12.840063 | 44.153537 | 17.669786 | 9.591419 | 0.6793 | 0.0474 | 0.4835 | nan | nan |
2459875 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 11.558605 | 20.858599 | 11.209935 | 70.182786 | 2.900374 | 20.863005 | 5.379735 | 10.133696 | 0.6907 | 0.0487 | 0.4831 | nan | nan |
2459874 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 16.804186 | 29.310225 | 6.255818 | 36.880942 | 4.338246 | 27.635482 | 13.566033 | 6.716314 | 0.6726 | 0.0482 | 0.4928 | nan | nan |
2459873 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 14.062913 | 21.818642 | 14.977476 | 47.713866 | 3.483865 | 11.351267 | 21.050572 | 3.695685 | 0.6707 | 0.0496 | 0.4918 | nan | nan |
2459872 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 11.187351 | 19.357381 | 18.789440 | 61.184736 | 2.568852 | 31.597250 | 5.121333 | 4.659987 | 0.6646 | 0.0424 | 0.4545 | nan | nan |
2459871 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 8.523065 | 15.874706 | 17.321110 | 65.328505 | 2.920174 | 26.106220 | 7.665922 | 2.350122 | 0.6753 | 0.0462 | 0.4680 | nan | nan |
2459870 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 15.294214 | 26.122959 | 13.227508 | 49.268116 | 7.231399 | 18.434555 | 8.756722 | 8.064046 | 0.6837 | 0.0482 | 0.5100 | nan | nan |
2459869 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 12.260863 | 20.847008 | 11.228710 | 48.918489 | 4.193957 | 23.244857 | 6.161294 | 6.830817 | 0.6987 | 0.0488 | 0.5244 | nan | nan |
2459868 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 14.346831 | 24.097205 | 17.397890 | 74.249961 | 5.319025 | 17.271944 | 27.903217 | 7.090421 | 0.6726 | 0.0447 | 0.5167 | nan | nan |
2459867 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 9.509385 | 17.254943 | 16.063512 | 58.764815 | 5.161859 | 10.128420 | 6.967244 | 4.225110 | 0.6838 | 0.0458 | 0.5167 | nan | nan |
2459866 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 13.003806 | 19.546483 | 29.132183 | 55.563197 | 10.232414 | 11.472394 | 32.130160 | 2.978468 | 0.6481 | 0.0496 | 0.4854 | nan | nan |
2459865 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 14.827380 | 22.039832 | 55.019746 | 67.795928 | 14.323690 | 24.259274 | 5.904876 | 13.555564 | 0.5611 | 0.0383 | 0.3806 | nan | nan |
2459864 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 16.681248 | 26.815301 | 15.797967 | 27.735403 | 12.386974 | 13.564428 | 13.180912 | 8.224753 | 0.6175 | 0.0399 | 0.4640 | nan | nan |
2459863 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 9.213375 | 16.248153 | 4.368814 | 8.950616 | 9.593398 | 5.268518 | 17.768001 | 3.734233 | 0.6321 | 0.0405 | 0.4798 | nan | nan |
2459862 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 8.303082 | 16.388167 | 16.496422 | 31.869062 | 5.757722 | 19.076544 | 10.933530 | 2.684330 | 0.6141 | 0.0453 | 0.4217 | nan | nan |
2459861 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 5.749152 | 12.169708 | 4.562258 | 9.172729 | 2.318989 | 3.358461 | 8.206161 | 3.208180 | 0.6477 | 0.0394 | 0.4495 | nan | nan |
2459860 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 6.067678 | 13.487518 | 9.634345 | 26.549770 | 8.627753 | 21.895899 | 4.294399 | 2.524476 | 0.6814 | 0.0431 | 0.5213 | nan | nan |
2459859 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 4.831101 | 11.464360 | 4.206063 | 9.847207 | 2.178777 | 2.942173 | 32.871604 | 1.685724 | 0.6766 | 0.0463 | 0.5231 | nan | nan |
2459858 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.351118 | 12.142110 | 4.203990 | 10.100037 | 2.296421 | 3.149960 | 18.185435 | 3.222800 | 0.6882 | 0.0437 | 0.5243 | 2.471111 | 1.190067 |
2459857 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 2.610896 | 6.133375 | 1.199603 | 1.761502 | 3.273839 | 2.063818 | 7.682261 | 10.599466 | 0.0296 | 0.0260 | 0.0017 | nan | nan |
2459856 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 8.816939 | 18.507416 | 9.976172 | 24.836309 | 4.293590 | 12.466155 | 19.315108 | 5.274052 | 0.6809 | 0.0447 | 0.5139 | 2.582176 | 1.194919 |
2459855 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.916255 | 17.977874 | 10.243546 | 25.740906 | 2.627492 | 4.349958 | 11.496590 | 1.884996 | 0.6582 | 0.0462 | 0.4931 | 2.592180 | 1.220981 |
2459854 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.922374 | 16.353781 | 6.826775 | 19.642591 | 2.174714 | 4.247551 | 12.453086 | 4.676018 | 0.6907 | 0.0487 | 0.5290 | 2.506775 | 1.167549 |
2459853 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.169239 | 16.060238 | 9.573397 | 27.216504 | 2.656685 | 11.220745 | 19.539174 | 4.879669 | 0.7057 | 0.0472 | 0.5398 | 2.569465 | 1.154282 |
2459852 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.955408 | 16.360006 | 9.180905 | 28.483119 | 5.540399 | 20.081930 | 9.652394 | 16.542264 | 0.8212 | 0.0534 | 0.5343 | 5.513551 | 1.178749 |
2459851 | digital_maintenance | 100.00% | 0.00% | 89.15% | 0.00% | 100.00% | 0.00% | 4.677536 | 21.234729 | 6.159952 | 30.418326 | 4.839390 | 43.607358 | 5.866765 | 22.005824 | 0.7405 | 0.1244 | 0.5175 | 0.000000 | 0.000000 |
2459850 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.459026 | 19.017984 | 6.245003 | 25.317887 | 5.511748 | 19.969526 | 6.496170 | 17.519660 | 0.0432 | 0.0304 | 0.0218 | 1.183670 | 1.155179 |
2459849 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 8.006732 | 17.504476 | 12.091952 | 49.975579 | 3.667885 | 13.130384 | 20.193274 | 6.913560 | 0.0537 | 0.0296 | 0.0230 | 1.209753 | 1.178484 |
2459848 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.654769 | 15.564891 | 7.901019 | 32.669232 | 7.987541 | 21.929326 | 3.377312 | 4.864104 | 0.0452 | 0.0298 | 0.0231 | 1.213057 | 1.180830 |
2459847 | digital_maintenance | 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 |
2459846 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.694334 | 26.793148 | 8.911259 | 35.810377 | 1.574871 | 21.226094 | 8.271986 | 4.969622 | 0.0392 | 0.0314 | 0.0317 | 0.967350 | 0.925661 |
2459845 | digital_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.123022 | 19.931788 | 14.221943 | 42.140894 | 6.072763 | 16.803081 | 19.322635 | 2.472191 | 0.7210 | 0.0555 | 0.5859 | 0.000000 | 0.000000 |
2459844 | digital_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 4.951943 | 14.825428 | 4.103232 | 9.204592 | 8.546905 | 4.031350 | 12.883975 | 13.973882 | 0.0302 | 0.0266 | 0.0018 | nan | nan |
2459843 | digital_maintenance | 100.00% | 0.66% | 100.00% | 0.00% | 100.00% | 0.00% | 11.174636 | 20.374579 | 7.631271 | 20.791966 | 11.980539 | 71.001240 | 12.007850 | 3.092790 | 0.7177 | 0.0544 | 0.5758 | 2.600041 | 1.234678 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | RF_maintenance | nn Power | 53.967781 | 11.889235 | 19.418012 | 7.480354 | 53.967781 | 12.840063 | 44.153537 | 17.669786 | 9.591419 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | RF_maintenance | nn Power | 70.182786 | 11.558605 | 20.858599 | 11.209935 | 70.182786 | 2.900374 | 20.863005 | 5.379735 | 10.133696 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 36.880942 | 16.804186 | 29.310225 | 6.255818 | 36.880942 | 4.338246 | 27.635482 | 13.566033 | 6.716314 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 47.713866 | 14.062913 | 21.818642 | 14.977476 | 47.713866 | 3.483865 | 11.351267 | 21.050572 | 3.695685 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 61.184736 | 19.357381 | 11.187351 | 61.184736 | 18.789440 | 31.597250 | 2.568852 | 4.659987 | 5.121333 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 65.328505 | 15.874706 | 8.523065 | 65.328505 | 17.321110 | 26.106220 | 2.920174 | 2.350122 | 7.665922 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 49.268116 | 15.294214 | 26.122959 | 13.227508 | 49.268116 | 7.231399 | 18.434555 | 8.756722 | 8.064046 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 48.918489 | 12.260863 | 20.847008 | 11.228710 | 48.918489 | 4.193957 | 23.244857 | 6.161294 | 6.830817 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 74.249961 | 14.346831 | 24.097205 | 17.397890 | 74.249961 | 5.319025 | 17.271944 | 27.903217 | 7.090421 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 58.764815 | 9.509385 | 17.254943 | 16.063512 | 58.764815 | 5.161859 | 10.128420 | 6.967244 | 4.225110 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 55.563197 | 19.546483 | 13.003806 | 55.563197 | 29.132183 | 11.472394 | 10.232414 | 2.978468 | 32.130160 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 67.795928 | 14.827380 | 22.039832 | 55.019746 | 67.795928 | 14.323690 | 24.259274 | 5.904876 | 13.555564 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 27.735403 | 26.815301 | 16.681248 | 27.735403 | 15.797967 | 13.564428 | 12.386974 | 8.224753 | 13.180912 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | ee Temporal Discontinuties | 17.768001 | 9.213375 | 16.248153 | 4.368814 | 8.950616 | 9.593398 | 5.268518 | 17.768001 | 3.734233 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 31.869062 | 8.303082 | 16.388167 | 16.496422 | 31.869062 | 5.757722 | 19.076544 | 10.933530 | 2.684330 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Shape | 12.169708 | 12.169708 | 5.749152 | 9.172729 | 4.562258 | 3.358461 | 2.318989 | 3.208180 | 8.206161 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 26.549770 | 6.067678 | 13.487518 | 9.634345 | 26.549770 | 8.627753 | 21.895899 | 4.294399 | 2.524476 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | ee Temporal Discontinuties | 32.871604 | 4.831101 | 11.464360 | 4.206063 | 9.847207 | 2.178777 | 2.942173 | 32.871604 | 1.685724 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | ee Temporal Discontinuties | 18.185435 | 12.142110 | 5.351118 | 10.100037 | 4.203990 | 3.149960 | 2.296421 | 3.222800 | 18.185435 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Temporal Discontinuties | 10.599466 | 6.133375 | 2.610896 | 1.761502 | 1.199603 | 2.063818 | 3.273839 | 10.599466 | 7.682261 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 24.836309 | 8.816939 | 18.507416 | 9.976172 | 24.836309 | 4.293590 | 12.466155 | 19.315108 | 5.274052 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 25.740906 | 17.977874 | 9.916255 | 25.740906 | 10.243546 | 4.349958 | 2.627492 | 1.884996 | 11.496590 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 19.642591 | 16.353781 | 9.922374 | 19.642591 | 6.826775 | 4.247551 | 2.174714 | 4.676018 | 12.453086 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 27.216504 | 16.060238 | 7.169239 | 27.216504 | 9.573397 | 11.220745 | 2.656685 | 4.879669 | 19.539174 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 28.483119 | 3.955408 | 16.360006 | 9.180905 | 28.483119 | 5.540399 | 20.081930 | 9.652394 | 16.542264 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Temporal Variability | 43.607358 | 4.677536 | 21.234729 | 6.159952 | 30.418326 | 4.839390 | 43.607358 | 5.866765 | 22.005824 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 25.317887 | 6.459026 | 19.017984 | 6.245003 | 25.317887 | 5.511748 | 19.969526 | 6.496170 | 17.519660 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 49.975579 | 8.006732 | 17.504476 | 12.091952 | 49.975579 | 3.667885 | 13.130384 | 20.193274 | 6.913560 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 32.669232 | 15.564891 | 7.654769 | 32.669232 | 7.901019 | 21.929326 | 7.987541 | 4.864104 | 3.377312 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 35.810377 | 6.694334 | 26.793148 | 8.911259 | 35.810377 | 1.574871 | 21.226094 | 8.271986 | 4.969622 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Power | 42.140894 | 19.931788 | 10.123022 | 42.140894 | 14.221943 | 16.803081 | 6.072763 | 2.472191 | 19.322635 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Shape | 14.825428 | 4.951943 | 14.825428 | 4.103232 | 9.204592 | 8.546905 | 4.031350 | 12.883975 | 13.973882 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | N05 | digital_maintenance | nn Temporal Variability | 71.001240 | 20.374579 | 11.174636 | 20.791966 | 7.631271 | 71.001240 | 11.980539 | 3.092790 | 12.007850 |