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 = "243" csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H5C_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 253 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_ Found 247 auto_metrics notebooks in /home/obs/src/H5C_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/H5C_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/H5C_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) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2459810 | RF_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
2459809 | RF_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 |
2459808 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 14.352558 | 13.695185 | 127.280149 | 142.004240 | 2956.952109 | 2956.805846 | 12893.387118 | 12894.356975 | nan | nan | nan | 0.000000 | 0.000000 |
2459807 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 14.220693 | 14.112448 | inf | inf | 2842.224377 | 2842.155787 | 40696.481426 | 40699.063338 | nan | nan | nan | 0.000000 | 0.000000 |
2459806 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.345725 | 12.112099 | 96.963869 | 89.907015 | 3446.448534 | 3529.783144 | 30201.329481 | 30195.058153 | nan | nan | nan | 0.000000 | 0.000000 |
2459805 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.222036 | 9.981063 | 119.022439 | 115.615303 | 2743.116763 | 2743.216769 | 9791.026756 | 9790.224836 | nan | nan | nan | 0.000000 | 0.000000 |
2459804 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.196791 | 12.787670 | inf | inf | 3151.639508 | 3151.584107 | 6887.722579 | 6886.985208 | nan | nan | nan | 0.000000 | 0.000000 |
2459803 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.063915 | 12.021235 | 141.026086 | 149.079808 | 3582.346696 | 3582.458463 | 21859.422192 | 21861.813562 | nan | nan | nan | 0.000000 | 0.000000 |
2459802 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 15.898267 | 17.139394 | 120.491111 | 128.204436 | 4366.339354 | 4366.349909 | 16260.445623 | 16261.091514 | nan | nan | nan | 0.000000 | 0.000000 |
2459801 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 14.922276 | 15.195961 | 107.525721 | 108.918330 | 4494.737933 | 4494.512319 | 29114.534210 | 29114.677672 | nan | nan | nan | 0.000000 | 0.000000 |
2459800 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.912344 | 12.425341 | 102.781058 | 97.027558 | 3632.537598 | 3632.303933 | 33128.646518 | 33125.759723 | nan | nan | nan | 0.000000 | 0.000000 |
2459799 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 8.454554 | 10.837189 | 87.110453 | 79.431882 | 4220.208404 | 4262.945656 | 11182.422533 | 11313.701533 | nan | nan | nan | 0.000000 | 0.000000 |
2459798 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.572457 | 4.294236 | 102.077062 | 109.562985 | 2704.644926 | 2704.736942 | 22905.960644 | 22908.507112 | nan | nan | nan | 0.000000 | 0.000000 |
2459797 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.323321 | 9.125842 | inf | inf | 3385.389773 | 3385.036546 | 30002.191239 | 29999.043545 | nan | nan | nan | 0.000000 | 0.000000 |
2459796 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.338063 | 3.986831 | inf | inf | 2689.398231 | 2689.339855 | 30962.312084 | 30963.937075 | nan | nan | nan | 0.000000 | 0.000000 |
2459795 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 24.639854 | 26.698159 | inf | inf | 2779.878504 | 2779.359523 | 29625.668753 | 29627.102117 | nan | nan | nan | 0.000000 | 0.000000 |
2459794 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.286938 | 12.159095 | inf | inf | 3383.496372 | 3382.941891 | 48796.528391 | 48787.697222 | nan | nan | nan | 0.000000 | 0.000000 |
2459793 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.001662 | 9.157050 | 104.707899 | 98.933975 | 3465.714731 | 3465.276571 | 23974.377379 | 23969.621078 | nan | nan | nan | 0.000000 | 0.000000 |
2459792 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 8.215203 | 10.969054 | 90.160729 | 81.644661 | 2801.541889 | 2830.190952 | 11837.414111 | 11834.570659 | nan | nan | nan | 0.000000 | 0.000000 |
2459791 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.474323 | 11.879043 | inf | inf | 3081.024629 | 3092.934255 | 6725.959434 | 6740.204130 | nan | nan | nan | 0.000000 | 0.000000 |
2459790 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.641685 | 17.467494 | inf | inf | 4473.497856 | 4473.472752 | 20427.790071 | 20422.173257 | nan | nan | nan | 0.000000 | 0.000000 |
2459789 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.153375 | 18.011082 | inf | inf | 4560.928044 | 4560.759962 | 46561.614197 | 46557.937606 | nan | nan | nan | 0.000000 | 0.000000 |
2459788 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.509730 | 13.680563 | 138.290493 | 128.436900 | 5162.217641 | 5162.029463 | 21278.327748 | 21273.075516 | nan | nan | nan | 0.000000 | 0.000000 |
2459787 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.859256 | 12.769674 | 113.421740 | 105.056463 | 3450.337212 | 3450.394593 | 21398.483153 | 21395.214306 | nan | nan | nan | 0.000000 | 0.000000 |
2459786 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.419346 | 15.249826 | inf | inf | 5391.331152 | 5390.940612 | 31512.405289 | 31507.511435 | nan | nan | nan | 0.000000 | 0.000000 |
2459785 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.858105 | 12.621210 | 152.562807 | 125.514189 | 3111.783136 | 3205.437528 | 8326.784647 | 8324.047962 | nan | nan | nan | 0.000000 | 0.000000 |
2459784 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.225956 | 18.274707 | 143.306272 | 123.599095 | 5280.203590 | 5279.727067 | 2929.998607 | 2928.932088 | nan | nan | nan | 0.000000 | 0.000000 |
2459783 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 13.024173 | 15.793007 | inf | inf | 3001.218345 | 3001.238523 | 18445.055835 | 18444.485482 | nan | nan | nan | 0.000000 | 0.000000 |
2459782 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 13.564694 | 15.757005 | inf | inf | 1863.926310 | 1864.098517 | 13271.574716 | 13271.462818 | nan | nan | nan | 0.000000 | 0.000000 |
2459781 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.486881 | 1.368820 | 12.011190 | 11.884024 | 535.545115 | 559.216531 | 6700.225726 | 6699.748213 | nan | nan | nan | 0.000000 | 0.000000 |
2459778 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.652027 | 7.072381 | 24.779638 | 25.430327 | 1841.091668 | 1926.043721 | 18788.591220 | 18784.422529 | nan | nan | nan | 0.000000 | 0.000000 |
2459776 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 25.339161 | 7.299739 | 34.189464 | 26.738228 | 8874.822911 | 8863.344602 | 26222.785144 | 26203.024328 | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 12894.356975 | 13.695185 | 14.352558 | 142.004240 | 127.280149 | 2956.805846 | 2956.952109 | 12894.356975 | 12893.387118 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 14.112448 | 14.220693 | inf | inf | 2842.155787 | 2842.224377 | 40699.063338 | 40696.481426 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 30201.329481 | 10.345725 | 12.112099 | 96.963869 | 89.907015 | 3446.448534 | 3529.783144 | 30201.329481 | 30195.058153 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 9791.026756 | 9.222036 | 9.981063 | 119.022439 | 115.615303 | 2743.116763 | 2743.216769 | 9791.026756 | 9790.224836 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 12.787670 | 10.196791 | inf | inf | 3151.584107 | 3151.639508 | 6886.985208 | 6887.722579 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 21861.813562 | 11.063915 | 12.021235 | 141.026086 | 149.079808 | 3582.346696 | 3582.458463 | 21859.422192 | 21861.813562 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 16261.091514 | 17.139394 | 15.898267 | 128.204436 | 120.491111 | 4366.349909 | 4366.339354 | 16261.091514 | 16260.445623 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 29114.677672 | 15.195961 | 14.922276 | 108.918330 | 107.525721 | 4494.512319 | 4494.737933 | 29114.677672 | 29114.534210 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 33128.646518 | 12.425341 | 6.912344 | 97.027558 | 102.781058 | 3632.303933 | 3632.537598 | 33125.759723 | 33128.646518 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 11313.701533 | 10.837189 | 8.454554 | 79.431882 | 87.110453 | 4262.945656 | 4220.208404 | 11313.701533 | 11182.422533 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Temporal Discontinuties | 22908.507112 | 7.572457 | 4.294236 | 102.077062 | 109.562985 | 2704.644926 | 2704.736942 | 22905.960644 | 22908.507112 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 9.125842 | 6.323321 | inf | inf | 3385.036546 | 3385.389773 | 29999.043545 | 30002.191239 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Power | inf | 7.338063 | 3.986831 | inf | inf | 2689.398231 | 2689.339855 | 30962.312084 | 30963.937075 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 26.698159 | 24.639854 | inf | inf | 2779.359523 | 2779.878504 | 29627.102117 | 29625.668753 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Power | inf | 7.286938 | 12.159095 | inf | inf | 3383.496372 | 3382.941891 | 48796.528391 | 48787.697222 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 23974.377379 | 5.001662 | 9.157050 | 104.707899 | 98.933975 | 3465.714731 | 3465.276571 | 23974.377379 | 23969.621078 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 11837.414111 | 8.215203 | 10.969054 | 90.160729 | 81.644661 | 2801.541889 | 2830.190952 | 11837.414111 | 11834.570659 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Power | inf | 6.474323 | 11.879043 | inf | inf | 3081.024629 | 3092.934255 | 6725.959434 | 6740.204130 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 17.467494 | 9.641685 | inf | inf | 4473.472752 | 4473.497856 | 20422.173257 | 20427.790071 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 18.011082 | 11.153375 | inf | inf | 4560.759962 | 4560.928044 | 46557.937606 | 46561.614197 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 21278.327748 | 13.680563 | 9.509730 | 128.436900 | 138.290493 | 5162.029463 | 5162.217641 | 21273.075516 | 21278.327748 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 21398.483153 | 9.859256 | 12.769674 | 113.421740 | 105.056463 | 3450.337212 | 3450.394593 | 21398.483153 | 21395.214306 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 15.249826 | 11.419346 | inf | inf | 5390.940612 | 5391.331152 | 31507.511435 | 31512.405289 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 8326.784647 | 12.621210 | 7.858105 | 125.514189 | 152.562807 | 3205.437528 | 3111.783136 | 8324.047962 | 8326.784647 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Variability | 5280.203590 | 9.225956 | 18.274707 | 143.306272 | 123.599095 | 5280.203590 | 5279.727067 | 2929.998607 | 2928.932088 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 15.793007 | 13.024173 | inf | inf | 3001.238523 | 3001.218345 | 18444.485482 | 18445.055835 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | nn Power | inf | 15.757005 | 13.564694 | inf | inf | 1864.098517 | 1863.926310 | 13271.462818 | 13271.574716 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 6700.225726 | 1.486881 | 1.368820 | 12.011190 | 11.884024 | 535.545115 | 559.216531 | 6700.225726 | 6699.748213 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 18788.591220 | 7.072381 | 7.652027 | 25.430327 | 24.779638 | 1926.043721 | 1841.091668 | 18784.422529 | 18788.591220 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
243 | N19 | RF_ok | ee Temporal Discontinuties | 26222.785144 | 25.339161 | 7.299739 | 34.189464 | 26.738228 | 8874.822911 | 8863.344602 | 26222.785144 | 26203.024328 |