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 = "207" 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% | 6.344246 | 4.811994 | 17.039031 | 14.079808 | 20.709002 | 13.154029 | -0.872782 | -1.918343 | 0.0551 | 0.0537 | 0.0071 | 0.000000 | 0.000000 |
2459808 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 12.392086 | 9.989697 | 18.132815 | 15.219042 | 17.228741 | 13.840410 | 6.765527 | 5.335436 | 0.0579 | 0.0608 | 0.0056 | 1.115665 | 1.104854 |
2459807 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 12.871128 | 10.683996 | 12.287838 | 10.429714 | 14.919926 | 12.712773 | 23.411474 | 19.568754 | 0.0565 | 0.0578 | 0.0051 | 1.329647 | 1.331398 |
2459806 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 12.176126 | 8.944152 | 19.948293 | 16.316951 | 27.332616 | 25.880955 | 21.085373 | 18.522057 | 0.0533 | 0.0536 | 0.0050 | 0.000000 | 0.000000 |
2459805 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.461933 | 9.609488 | 16.163920 | 14.165949 | 12.378838 | 11.314141 | 4.556014 | 3.520751 | 0.0530 | 0.0567 | 0.0046 | 1.329796 | 1.329727 |
2459804 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 13.846431 | 11.108954 | 15.248141 | 12.743136 | 13.523887 | 11.930587 | 2.981134 | 2.326274 | 0.0551 | 0.0521 | 0.0045 | 1.139933 | 1.141918 |
2459803 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 17.138676 | 13.873013 | 20.763211 | 17.626958 | 14.265367 | 12.581140 | 10.026037 | 8.642479 | 0.0603 | 0.0619 | 0.0061 | 0.973488 | 0.970341 |
2459802 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 14.340037 | 11.365266 | 18.203234 | 14.984312 | 24.726803 | 18.999344 | 5.356102 | 4.130143 | 0.0587 | 0.0599 | 0.0061 | 0.000000 | 0.000000 |
2459801 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 13.587382 | 11.399441 | 14.958784 | 12.656195 | 24.616591 | 20.993720 | 15.788465 | 13.212024 | 0.0610 | 0.0615 | 0.0058 | 0.852593 | 0.850340 |
2459800 | RF_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 14.511892 | 12.044655 | 14.014888 | 11.936042 | 14.383616 | 12.055209 | 15.390113 | 12.196290 | 0.0668 | 0.0635 | 0.0073 | 1.168812 | 1.163681 |
2459799 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.641999 | 8.791069 | 18.104087 | 14.855483 | 35.422843 | 27.794681 | 7.859908 | 5.111628 | 0.7082 | 0.6133 | 0.4012 | 4.213687 | 3.410638 |
2459798 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 13.902816 | 11.186781 | 14.680800 | 12.311447 | 11.747782 | 9.389074 | 9.132382 | 4.036286 | 0.6660 | 0.6502 | 0.4144 | 6.326331 | 6.234163 |
2459797 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.723365 | 9.650864 | 14.146332 | 12.120262 | 16.012652 | 13.401203 | 19.563355 | 18.650977 | 0.6534 | 0.6395 | 0.4151 | 8.115338 | 10.574607 |
2459796 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 12.939003 | 10.259814 | 19.447477 | 15.950122 | 13.794774 | 11.004666 | 13.466385 | 12.224021 | 0.6502 | 0.6384 | 0.3992 | 0.000000 | 0.000000 |
2459795 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 14.407464 | 11.419240 | 15.292130 | 12.372019 | 15.808400 | 12.651703 | 18.939743 | 17.790266 | 0.6238 | 0.6107 | 0.4135 | 5.821645 | 5.279639 |
2459794 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 13.843184 | 11.040640 | 15.875565 | 13.224244 | 18.964142 | 15.225631 | 19.498215 | 17.572774 | 0.6442 | 0.6354 | 0.3899 | 1.190562 | 1.187761 |
2459793 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.073093 | 9.099018 | 15.055782 | 12.362343 | 19.683932 | 15.675409 | 9.109954 | 8.129122 | 0.6285 | 0.6295 | 0.3872 | 0.000000 | 0.000000 |
2459792 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.555069 | 9.094335 | 18.284426 | 15.829319 | 23.675416 | 19.372021 | 8.097230 | 7.209955 | 0.7046 | 0.6114 | 0.3965 | 10.842047 | 8.588111 |
2459791 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 13.298959 | 10.973120 | 20.762723 | 17.824944 | 21.246199 | 17.699906 | 3.112719 | 2.428077 | 0.6198 | 0.6208 | 0.3765 | 5.681177 | 6.120765 |
2459790 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 20.692002 | 17.516300 | 19.018280 | 16.724378 | 28.573640 | 24.404526 | 7.981260 | 6.728917 | 0.5996 | 0.6049 | 0.3728 | 0.000000 | 0.000000 |
2459789 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 17.885940 | 23.522841 | 20.022465 | 26.497286 | 30.003718 | 37.855343 | 17.942743 | 19.902150 | 0.5781 | 0.5633 | 0.3659 | 0.000000 | 0.000000 |
2459788 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 15.293754 | 17.428804 | 20.858462 | 24.470195 | 31.921647 | 35.059770 | 7.591773 | 8.310237 | 0.5856 | 0.5819 | 0.3552 | 0.870131 | 0.857420 |
2459787 | RF_ok | 100.00% | 8.06% | 8.06% | 0.00% | 100.00% | 0.00% | 14.803697 | 19.737071 | 17.225542 | 23.383307 | 20.698388 | 25.905366 | 8.122829 | 8.794044 | 0.5469 | 0.5301 | 0.3530 | -0.000000 | -0.000000 |
2459786 | RF_ok | 100.00% | 5.38% | 8.06% | 0.00% | 100.00% | 0.00% | 15.955783 | 20.977831 | 21.635889 | 28.060185 | 32.124613 | 39.471240 | 12.999110 | 13.915152 | 0.5498 | 0.5358 | 0.3377 | 1.136486 | 1.127508 |
2459785 | RF_ok | 100.00% | 2.15% | 1.61% | 0.00% | 100.00% | 0.00% | 12.843809 | 12.075175 | 41.871665 | 40.560361 | 37.758620 | 34.320336 | 5.083691 | 4.403854 | 0.6936 | 0.6056 | 0.3869 | 0.000000 | 0.000000 |
2459784 | RF_ok | 100.00% | 16.13% | 10.75% | 0.00% | 100.00% | 0.00% | 19.476895 | 18.117823 | 31.762263 | 31.385816 | 41.977384 | 36.226029 | 1.961403 | 1.288426 | 0.5093 | 0.5162 | 0.3066 | 4.136896 | 4.902717 |
2459783 | RF_ok | 100.00% | 2.70% | 0.00% | 0.00% | 100.00% | 0.00% | 16.952768 | 15.093114 | 9.297127 | 8.416136 | 20.259830 | 16.691083 | 8.807294 | 4.244832 | 0.5087 | 0.5151 | 0.3021 | 3.290062 | 3.416518 |
2459782 | RF_ok | 100.00% | 21.51% | 8.06% | 0.00% | 100.00% | 0.00% | 15.717787 | 14.212363 | 4.742821 | 4.235319 | 11.367646 | 9.646678 | 6.438199 | 2.930906 | 0.4862 | 0.4958 | 0.2889 | 4.710386 | 5.681303 |
2459781 | RF_ok | 0.00% | 10.43% | 9.13% | 0.00% | 100.00% | 0.00% | 2.255449 | 1.642361 | 0.998111 | 0.719582 | 0.112547 | 0.035707 | -2.068591 | -1.952926 | 0.6651 | 0.6201 | 0.3414 | 7.334525 | 7.585301 |
2459778 | RF_ok | 100.00% | 4.30% | 0.00% | 0.00% | 100.00% | 0.00% | 10.109078 | 7.889864 | 7.183918 | 5.736839 | 19.395744 | 17.502236 | 12.230989 | 8.437075 | 0.6714 | 0.5898 | 0.3828 | 7.662634 | 6.450161 |
2459776 | RF_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 9.512394 | 6.423398 | 7.927208 | 6.892906 | 28.797349 | 18.705239 | 20.296968 | 22.855083 | 0.7175 | 0.6193 | 0.3941 | 10.115597 | 8.022342 |
2459774 | RF_ok | - | 3.12% | 0.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.6827 | 0.5958 | 0.3817 | nan | nan |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 20.709002 | 4.811994 | 6.344246 | 14.079808 | 17.039031 | 13.154029 | 20.709002 | -1.918343 | -0.872782 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 18.132815 | 9.989697 | 12.392086 | 15.219042 | 18.132815 | 13.840410 | 17.228741 | 5.335436 | 6.765527 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Discontinuties | 23.411474 | 10.683996 | 12.871128 | 10.429714 | 12.287838 | 12.712773 | 14.919926 | 19.568754 | 23.411474 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 27.332616 | 12.176126 | 8.944152 | 19.948293 | 16.316951 | 27.332616 | 25.880955 | 21.085373 | 18.522057 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 16.163920 | 11.461933 | 9.609488 | 16.163920 | 14.165949 | 12.378838 | 11.314141 | 4.556014 | 3.520751 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 15.248141 | 11.108954 | 13.846431 | 12.743136 | 15.248141 | 11.930587 | 13.523887 | 2.326274 | 2.981134 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 20.763211 | 17.138676 | 13.873013 | 20.763211 | 17.626958 | 14.265367 | 12.581140 | 10.026037 | 8.642479 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 24.726803 | 11.365266 | 14.340037 | 14.984312 | 18.203234 | 18.999344 | 24.726803 | 4.130143 | 5.356102 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 24.616591 | 11.399441 | 13.587382 | 12.656195 | 14.958784 | 20.993720 | 24.616591 | 13.212024 | 15.788465 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Discontinuties | 15.390113 | 12.044655 | 14.511892 | 11.936042 | 14.014888 | 12.055209 | 14.383616 | 12.196290 | 15.390113 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 35.422843 | 8.791069 | 11.641999 | 14.855483 | 18.104087 | 27.794681 | 35.422843 | 5.111628 | 7.859908 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 14.680800 | 13.902816 | 11.186781 | 14.680800 | 12.311447 | 11.747782 | 9.389074 | 9.132382 | 4.036286 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Discontinuties | 19.563355 | 9.650864 | 11.723365 | 12.120262 | 14.146332 | 13.401203 | 16.012652 | 18.650977 | 19.563355 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 19.447477 | 12.939003 | 10.259814 | 19.447477 | 15.950122 | 13.794774 | 11.004666 | 13.466385 | 12.224021 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Discontinuties | 18.939743 | 11.419240 | 14.407464 | 12.372019 | 15.292130 | 12.651703 | 15.808400 | 17.790266 | 18.939743 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Discontinuties | 19.498215 | 13.843184 | 11.040640 | 15.875565 | 13.224244 | 18.964142 | 15.225631 | 19.498215 | 17.572774 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 19.683932 | 11.073093 | 9.099018 | 15.055782 | 12.362343 | 19.683932 | 15.675409 | 9.109954 | 8.129122 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 23.675416 | 11.555069 | 9.094335 | 18.284426 | 15.829319 | 23.675416 | 19.372021 | 8.097230 | 7.209955 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 21.246199 | 13.298959 | 10.973120 | 20.762723 | 17.824944 | 21.246199 | 17.699906 | 3.112719 | 2.428077 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 28.573640 | 17.516300 | 20.692002 | 16.724378 | 19.018280 | 24.404526 | 28.573640 | 6.728917 | 7.981260 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | nn Temporal Variability | 37.855343 | 23.522841 | 17.885940 | 26.497286 | 20.022465 | 37.855343 | 30.003718 | 19.902150 | 17.942743 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | nn Temporal Variability | 35.059770 | 17.428804 | 15.293754 | 24.470195 | 20.858462 | 35.059770 | 31.921647 | 8.310237 | 7.591773 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | nn Temporal Variability | 25.905366 | 14.803697 | 19.737071 | 17.225542 | 23.383307 | 20.698388 | 25.905366 | 8.122829 | 8.794044 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | nn Temporal Variability | 39.471240 | 20.977831 | 15.955783 | 28.060185 | 21.635889 | 39.471240 | 32.124613 | 13.915152 | 12.999110 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Power | 41.871665 | 12.075175 | 12.843809 | 40.560361 | 41.871665 | 34.320336 | 37.758620 | 4.403854 | 5.083691 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 41.977384 | 19.476895 | 18.117823 | 31.762263 | 31.385816 | 41.977384 | 36.226029 | 1.961403 | 1.288426 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 20.259830 | 15.093114 | 16.952768 | 8.416136 | 9.297127 | 16.691083 | 20.259830 | 4.244832 | 8.807294 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Shape | 15.717787 | 14.212363 | 15.717787 | 4.235319 | 4.742821 | 9.646678 | 11.367646 | 2.930906 | 6.438199 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Shape | 2.255449 | 2.255449 | 1.642361 | 0.998111 | 0.719582 | 0.112547 | 0.035707 | -2.068591 | -1.952926 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 19.395744 | 7.889864 | 10.109078 | 5.736839 | 7.183918 | 17.502236 | 19.395744 | 8.437075 | 12.230989 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
207 | N19 | RF_ok | ee Temporal Variability | 28.797349 | 9.512394 | 6.423398 | 7.927208 | 6.892906 | 28.797349 | 18.705239 | 20.296968 | 22.855083 |