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docs/pyerrors/obs.html
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@ -879,7 +879,7 @@
<span class="sd"> Returns</span> <span class="sd"> Returns</span>
<span class="sd"> -------</span> <span class="sd"> -------</span>
<span class="sd"> np.ndarray</span> <span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span> <span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span> <span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span> <span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
@ -2460,7 +2460,7 @@
<span class="sd"> Returns</span> <span class="sd"> Returns</span>
<span class="sd"> -------</span> <span class="sd"> -------</span>
<span class="sd"> np.ndarray</span> <span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span> <span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span> <span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span> <span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
@ -3629,7 +3629,7 @@ specifies a custom path for the file (default '.')</li>
<span class="sd"> Returns</span> <span class="sd"> Returns</span>
<span class="sd"> -------</span> <span class="sd"> -------</span>
<span class="sd"> np.ndarray</span> <span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span> <span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span> <span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span> <span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
@ -3659,7 +3659,7 @@ specifies a custom path for the file (default '.')</li>
<h6 id="returns">Returns</h6> <h6 id="returns">Returns</h6>
<ul> <ul>
<li><strong>np.ndarray</strong>: Returns a numpy array of length N + 1 where N is the number of samples <li><strong>numpy.ndarray</strong>: Returns a numpy array of length N + 1 where N is the number of samples
for the given ensemble and replicum. The zeroth entry of the array contains for the given ensemble and replicum. The zeroth entry of the array contains
the mean value of the Obs, entries 1 to N contain the N jackknife samples the mean value of the Obs, entries 1 to N contain the N jackknife samples
derived from the Obs. The current implementation only works for observables derived from the Obs. The current implementation only works for observables

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docs/search.js
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