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<h3>
Gary E. Miller pushed to branch master
at <a href="https://gitlab.com/NTPsec/ntpsec">NTPsec / ntpsec</a>
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Commits:
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<strong><a href="https://gitlab.com/NTPsec/ntpsec/commit/1cd3645e389016584c2ccb39627c09b7b52bb05a">1cd3645e</a></strong>
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<span>by Gary E. Miller</span>
<i>at 2016-08-31T18:51:31-07:00</i>
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<pre class="commit-message" style="margin: 0; white-space: pre-wrap">Define sigma.
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<strong><a href="https://gitlab.com/NTPsec/ntpsec/commit/dba694c1810ee720263a85125060c36c399657fe">dba694c1</a></strong>
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<span>by Gary E. Miller</span>
<i>at 2016-08-31T19:16:17-07:00</i>
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<pre class="commit-message" style="margin: 0; white-space: pre-wrap">Add standard deviation functions, print mean in histogram.
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<h4>1 changed file:</h4>
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ntpstats/ntpviz
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<h4>Changes:</h4>
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<a href="https://gitlab.com/NTPsec/ntpsec/compare/5a919794afc25f5a2368fad8f3a688f374304002...dba694c1810ee720263a85125060c36c399657fe#diff-0"><strong>ntpstats/ntpviz</strong></a>
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<td class="line_content match " style="background: #fafafa; color: rgba(0,0,0,0.3); padding-left: 0.5em; padding-right: 0.5em" bgcolor="#fafafa">@@ -24,6 +24,33 @@ from __future__ import print_function, division</td>
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<pre style="margin: 0"> <span id="LC24" class="line">import os, sys, getopt, socket, binascii, collections, time</span>
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<pre style="margin: 0"> <span id="LC25" class="line">from ntp.statfiles import *</span>
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<pre style="margin: 0"> <span id="LC26" class="line"></span>
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<pre style="margin: 0"> <span id="LC27" class="line"># standard deviation functions</span>
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<pre style="margin: 0"> <span id="LC28" class="line"># use this until we can guarantee Python 3.4 and the statistics module</span>
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<pre style="margin: 0"> <span id="LC29" class="line"># http://stackoverflow.com/questions/15389768/standard-deviation-of-a-list#21505523</span>
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<pre style="margin: 0"> <span id="LC30" class="line"></span>
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<pre style="margin: 0"> <span id="LC31" class="line">def mean(data):</span>
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<pre style="margin: 0"> <span id="LC32" class="line"> """Return the sample arithmetic mean of data."""</span>
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<pre style="margin: 0"> <span id="LC33" class="line"> n = len(data)</span>
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<pre style="margin: 0"> <span id="LC34" class="line"> if n <span class="nt" style="color: navy">< 1:</span></span>
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<pre style="margin: 0"> <span id="LC35" class="line"> <span class="na" style="color: teal">raise</span> <span class="na" style="color: teal">ValueError</span><span class="err" style="background: #e3d2d2; color: #a61717">('</span><span class="na" style="color: teal">mean</span> <span class="na" style="color: teal">requires</span> <span class="na" style="color: teal">at</span> <span class="na" style="color: teal">least</span> <span class="na" style="color: teal">one</span> <span class="na" style="color: teal">data</span> <span class="na" style="color: teal">point</span><span class="err" style="background: #e3d2d2; color: #a61717">')</span></span>
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<pre style="margin: 0"> <span id="LC36" class="line"> <span class="na" style="color: teal">return</span> <span class="na" style="color: teal">sum</span><span class="err" style="background: #e3d2d2; color: #a61717">(</span><span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">)/</span><span class="na" style="color: teal">n</span> <span class="err" style="background: #e3d2d2; color: #a61717">#</span> <span class="na" style="color: teal">in</span> <span class="na" style="color: teal">Python</span> <span class="na" style="color: teal">2</span> <span class="na" style="color: teal">use</span> <span class="na" style="color: teal">sum</span><span class="err" style="background: #e3d2d2; color: #a61717">(</span><span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">)/</span><span class="na" style="color: teal">float</span><span class="err" style="background: #e3d2d2; color: #a61717">(</span><span class="na" style="color: teal">n</span><span class="err" style="background: #e3d2d2; color: #a61717">)</span></span>
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<pre style="margin: 0"> <span id="LC37" class="line"></span>
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<pre style="margin: 0"> <span id="LC38" class="line"><span class="na" style="color: teal">def</span> <span class="na" style="color: teal">_ss</span><span class="err" style="background: #e3d2d2; color: #a61717">(</span><span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">)</span><span class="na" style="color: teal">:</span></span>
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<pre style="margin: 0"> <span id="LC39" class="line"> <span class="err" style="background: #e3d2d2; color: #a61717">"""</span><span class="na" style="color: teal">Return</span> <span class="na" style="color: teal">sum</span> <span class="na" style="color: teal">of</span> <span class="na" style="color: teal">square</span> <span class="na" style="color: teal">deviations</span> <span class="na" style="color: teal">of</span> <span class="na" style="color: teal">sequence</span> <span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">."""</span></span>
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<pre style="margin: 0"> <span id="LC40" class="line"> <span class="na" style="color: teal">c =</span><span class="err" style="background: #e3d2d2; color: #a61717"> </span><span class="s" style="color: #d14">mean(data)</span></span>
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<pre style="margin: 0"> <span id="LC41" class="line"> <span class="na" style="color: teal">ss =</span><span class="err" style="background: #e3d2d2; color: #a61717"> </span><span class="s" style="color: #d14">sum((x-c)**2</span> <span class="na" style="color: teal">for</span> <span class="na" style="color: teal">x</span> <span class="na" style="color: teal">in</span> <span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">)</span></span>
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<pre style="margin: 0"> <span id="LC42" class="line"> <span class="na" style="color: teal">return</span> <span class="na" style="color: teal">ss</span></span>
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<pre style="margin: 0"> <span id="LC43" class="line"></span>
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<pre style="margin: 0"> <span id="LC44" class="line"><span class="na" style="color: teal">def</span> <span class="na" style="color: teal">pstdev</span><span class="err" style="background: #e3d2d2; color: #a61717">(</span><span class="na" style="color: teal">data</span><span class="err" style="background: #e3d2d2; color: #a61717">)</span><span class="na" style="color: teal">:</span></span>
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<pre style="margin: 0"> <span id="LC45" class="line"> <span class="err" style="background: #e3d2d2; color: #a61717">"""</span><span class="na" style="color: teal">Calculates</span> <span class="na" style="color: teal">the</span> <span class="na" style="color: teal">population</span> <span class="na" style="color: teal">standard</span> <span class="na" style="color: teal">deviation</span><span class="err" style="background: #e3d2d2; color: #a61717">."""</span></span>
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<pre style="margin: 0"> <span id="LC46" class="line"> <span class="na" style="color: teal">n =</span><span class="err" style="background: #e3d2d2; color: #a61717"> </span><span class="s" style="color: #d14">len(data)</span></span>
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<pre style="margin: 0"> <span id="LC47" class="line"> <span class="na" style="color: teal">if</span> <span class="na" style="color: teal">n</span> <span class="err" style="background: #e3d2d2; color: #a61717"><</span> <span class="na" style="color: teal">2:</span></span>
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<pre style="margin: 0"> <span id="LC48" class="line"> <span class="na" style="color: teal">raise</span> <span class="na" style="color: teal">ValueError</span><span class="err" style="background: #e3d2d2; color: #a61717">('</span><span class="na" style="color: teal">variance</span> <span class="na" style="color: teal">requires</span> <span class="na" style="color: teal">at</span> <span class="na" style="color: teal">least</span> <span class="na" style="color: teal">two</span> <span class="na" style="color: teal">data</span> <span class="na" style="color: teal">points</span><span class="err" style="background: #e3d2d2; color: #a61717">')</span></span>
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<pre style="margin: 0"> <span id="LC49" class="line"> <span class="na" style="color: teal">ss =</span><span class="err" style="background: #e3d2d2; color: #a61717"> </span><span class="s" style="color: #d14">_ss(data)</span></span>
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<pre style="margin: 0"> <span id="LC50" class="line"> <span class="na" style="color: teal">pvar =</span><span class="err" style="background: #e3d2d2; color: #a61717"> </span><span class="s" style="color: #d14">ss/n</span> <span class="err" style="background: #e3d2d2; color: #a61717">#</span> <span class="na" style="color: teal">the</span> <span class="na" style="color: teal">population</span> <span class="na" style="color: teal">variance</span></span>
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<pre style="margin: 0"> <span id="LC51" class="line"> <span class="na" style="color: teal">return</span> <span class="na" style="color: teal">pvar</span><span class="err" style="background: #e3d2d2; color: #a61717">**</span><span class="na" style="color: teal">0</span><span class="err" style="background: #e3d2d2; color: #a61717">.</span><span class="na" style="color: teal">5</span></span>
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<pre style="margin: 0"> <span id="LC52" class="line"></span>
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<pre style="margin: 0"> <span id="LC53" class="line"><span class="err" style="background: #e3d2d2; color: #a61717">#</span> <span class="na" style="color: teal">end</span> <span class="na" style="color: teal">standard</span> <span class="na" style="color: teal">deviation</span> <span class="na" style="color: teal">functions</span></span>
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<pre style="margin: 0"> <span id="LC54" class="line"><span class="err" style="background: #e3d2d2; color: #a61717">#</span> <span class="na" style="color: teal">RMS</span> <span class="na" style="color: teal">frequency</span> <span class="na" style="color: teal">jitter</span> <span class="na" style="color: teal">-</span> <span class="na" style="color: teal">Deviation</span> <span class="na" style="color: teal">from</span> <span class="na" style="color: teal">a</span> <span class="na" style="color: teal">root-mean-square</span> <span class="na" style="color: teal">linear</span> <span class="na" style="color: teal">approximation</span><span class="err" style="background: #e3d2d2; color: #a61717">?</span></span>
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<pre style="margin: 0"> <span id="LC55" class="line"><span class="err" style="background: #e3d2d2; color: #a61717">#</span> <span class="na" style="color: teal">Investigate</span><span class="err" style="background: #e3d2d2; color: #a61717">.</span></span>
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<pre style="margin: 0"> <span id="LC56" class="line"></span>
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<td class="line_content match " style="background: #fafafa; color: rgba(0,0,0,0.3); padding-left: 0.5em; padding-right: 0.5em" bgcolor="#fafafa">@@ -75,6 +102,8 @@ set rmargin 12</td>
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<pre style="margin: 0"> <span id="LC102" class="line"> period=period, starttime=starttime, endtime=endtime)</span>
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<pre style="margin: 0"> <span id="LC103" class="line"> if self.sitename is None:</span>
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<pre style="margin: 0"> <span id="LC104" class="line"> self.sitename = os.path.basename(statsdir)</span>
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<pre style="margin: 0"> <span id="LC105" class="line"></span>
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106
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<pre style="margin: 0"> <span id="LC106" class="line"></span>
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78
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107
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<pre style="margin: 0"> <span id="LC107" class="line"> def local_offset_gnuplot(self):</span>
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79
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108
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<pre style="margin: 0"> <span id="LC108" class="line"> "Generate GNUPLOT code graphing local clock loop statistics"</span>
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80
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109
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<pre style="margin: 0"> <span id="LC109" class="line"> if not len( self.loopstats):</span>
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<td class="diff-line-num unfold js-unfold new_line" data-linenumber="358" style="background: #fafafa; border-right-color: #f0f0f0; border-right-style: solid; border-right-width: 1px; color: rgba(0,0,0,0.3); padding: 0 5px; text-align: right; width: 35px" align="right" bgcolor="#fafafa">...</td>
<td class="line_content match " style="background: #fafafa; color: rgba(0,0,0,0.3); padding-left: 0.5em; padding-right: 0.5em" bgcolor="#fafafa">@@ -329,6 +358,11 @@ plot \</td>
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329
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358
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<pre style="margin: 0"> <span id="LC358" class="line"> for line in self.loopstats:</span>
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330
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359
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<pre style="margin: 0"> <span id="LC359" class="line"> # put into 100 nSec buckets</span>
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331
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360
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<pre style="margin: 0"> <span id="LC360" class="line"> cnt[ round( float(line.split()[1]), 7)] += 1</span>
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361
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<pre style="margin: 0"> <span id="LC361" class="line"></span>
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362
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<pre style="margin: 0"> <span id="LC362" class="line"> values = [float(line.split()[1]) for line in self.loopstats]</span>
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363
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<pre style="margin: 0"> <span id="LC363" class="line"> values.sort()</span>
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364
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<pre style="margin: 0"> <span id="LC364" class="line"> values_mean = mean( values ) * 1000000</span>
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365
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<pre style="margin: 0"> <span id="LC365" class="line"></span>
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332
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366
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<pre style="margin: 0"> <span id="LC366" class="line"> ninetynine = self.percentile(2, 99, self.loopstats) * 1000000</span>
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333
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367
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<pre style="margin: 0"> <span id="LC367" class="line"> seventyfive = self.percentile(2, 75, self.loopstats) * 1000000</span>
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334
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368
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<pre style="margin: 0"> <span id="LC368" class="line"> twentyfive = self.percentile(2, 25, self.loopstats) * 1000000</span>
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<td class="diff-line-num unfold js-unfold old_line" data-linenumber="354" style="background: #fafafa; border-right-color: #f0f0f0; border-right-style: solid; border-right-width: 1px; color: rgba(0,0,0,0.3); padding: 0 5px; text-align: right; width: 35px" align="right" bgcolor="#fafafa">...</td>
<td class="diff-line-num unfold js-unfold new_line" data-linenumber="388" style="background: #fafafa; border-right-color: #f0f0f0; border-right-style: solid; border-right-width: 1px; color: rgba(0,0,0,0.3); padding: 0 5px; text-align: right; width: 35px" align="right" bgcolor="#fafafa">...</td>
<td class="line_content match " style="background: #fafafa; color: rgba(0,0,0,0.3); padding-left: 0.5em; padding-right: 0.5em" bgcolor="#fafafa">@@ -354,6 +388,7 @@ set arrow from %(seventyfive)s,0 to %(seventyfive)s,graph 0.7 as 4</td>
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354
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388
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<pre style="margin: 0"> <span id="LC388" class="line">set key off</span>
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355
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389
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<pre style="margin: 0"> <span id="LC389" class="line">set lmargin 12</span>
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356
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390
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<pre style="margin: 0"> <span id="LC390" class="line">set rmargin 12</span>
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391
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<pre style="margin: 0"> <span id="LC391" class="line">set label 1 gprintf("mean = %(values_mean)s μs",50) at graph 0.01,0.3 left front</span>
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357
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392
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<pre style="margin: 0"> <span id="LC392" class="line">plot \</span>
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358
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393
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<pre style="margin: 0"> <span id="LC393" class="line"> "-" using ($1 * 1000000):2 title "histogram" with boxes</span>
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359
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394
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<pre style="margin: 0"> <span id="LC394" class="line">''' % locals()</span>
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<td class="line_content match " style="background: #fafafa; color: rgba(0,0,0,0.3); padding-left: 0.5em; padding-right: 0.5em" bgcolor="#fafafa">@@ -710,6 +745,12 @@ system clock frequency (usually in parts per million, ppm)</dd></td>
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<pre style="margin: 0"> <span id="LC745" class="line"><span class="nt" style="color: navy"><dt></span>upstream clock:<span class="nt" style="color: navy"></dt></span></span>
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<pre style="margin: 0"> <span id="LC746" class="line"><span class="nt" style="color: navy"><dd></span>Any remote clock or reference clock used as a source of time.<span class="nt" style="color: navy"></dd></span></span>
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<pre style="margin: 0"> <span id="LC747" class="line"></span>
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<pre style="margin: 0"> <span id="LC748" class="line"><span class="nt" style="color: navy"><dt></span>σ, sigma:<span class="nt" style="color: navy"></dt></span></span>
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<pre style="margin: 0"> <span id="LC749" class="line"><span class="nt" style="color: navy"><dd></span>Sigma denotes the standard distribution. One sigma is the band of</span>
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<pre style="margin: 0"> <span id="LC750" class="line">values centered on the mean value enclosing 68.27% of the samples. Two</span>
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<pre style="margin: 0"> <span id="LC751" class="line">sigma is 95.45%. Three Sigma is 99.73%. Two sigma is considered a</span>
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<pre style="margin: 0"> <span id="LC752" class="line">sgignificant confidence level.<span class="nt" style="color: navy"></dd></span></span>
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<pre style="margin: 0"> <span id="LC753" class="line"></span>
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<pre style="margin: 0"> <span id="LC754" class="line"><span class="nt" style="color: navy"><dt></span>µs, us, microsecond:<span class="nt" style="color: navy"></dt></span></span>
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<pre style="margin: 0"> <span id="LC755" class="line"><span class="nt" style="color: navy"><dd></span>One millionth of a second, also one thousandth of a millisecond,</span>
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<pre style="margin: 0"> <span id="LC756" class="line">0.0000001s.<span class="nt" style="color: navy"></dd></span></span>
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