--- /srv/reproducible-results/rbuild-debian/r-b-build.0EolXhxo/b1/lmfit-py_1.3.3-1_arm64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.0EolXhxo/b2/lmfit-py_1.3.3-1_arm64.changes
├── Files
│ @@ -1,3 +1,3 @@
│  
│ - 7c09d1a71d4ecdf21a0197e5ffb32f3c 6379724 doc optional python-lmfit-doc_1.3.3-1_all.deb
│ + 19a27f1b80c93ffa4c9b2de11140819a 6379644 doc optional python-lmfit-doc_1.3.3-1_all.deb
│   ff3152741293e9cc00373343ffa4e68f 82296 python optional python3-lmfit_1.3.3-1_all.deb
├── python-lmfit-doc_1.3.3-1_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2025-03-28 16:45:54.000000 debian-binary
│ │ --rw-r--r--   0        0        0     9032 2025-03-28 16:45:54.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  6370500 2025-03-28 16:45:54.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0     9040 2025-03-28 16:45:54.000000 control.tar.xz
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│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./md5sums
│ │ │ │ ├── ./md5sums
│ │ │ │ │┄ Files differ
│ ├── data.tar.xz
│ │ ├── data.tar
│ │ │ ├── file list
│ │ │ │ @@ -320,15 +320,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    25955 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    24473 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/installation.html
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│ │ │ │  -rw-r--r--   0 root         (0) root         (0)     8794 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/support.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    71045 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/whatsnew.html
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-03-28 16:45:54.000000 ./usr/share/doc-base/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)      305 2025-03-28 16:44:14.000000 ./usr/share/doc-base/python-lmfit-doc.python-lmfit-doc
│ │ │ │  lrwxrwxrwx   0 root         (0) root         (0)        0 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/_static/doctools.js -> ../../../../javascript/sphinxdoc/1.0/doctools.js
│ │ │ │  lrwxrwxrwx   0 root         (0) root         (0)        0 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/_static/language_data.js -> ../../../../javascript/sphinxdoc/1.0/language_data.js
│ │ │ │  lrwxrwxrwx   0 root         (0) root         (0)        0 2025-03-28 16:45:54.000000 ./usr/share/doc/python3-lmfit/html/_static/searchtools.js -> ../../../../javascript/sphinxdoc/1.0/searchtools.js
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_Model_interface.rst.txt
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_basinhopping.rst.txt
│ │ │ │ @@ -146,15 +146,15 @@
│ │ │ │      plt.plot(x, result.best_fit, '-', label=method2)
│ │ │ │      plt.legend()
│ │ │ │      plt.show()
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_brute.rst.txt
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_complex_resonator_model.rst.txt
│ │ │ │ @@ -291,15 +291,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_confidence_interval.rst.txt
│ │ │ │ @@ -275,15 +275,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_detect_outliers.rst.txt
│ │ │ │ @@ -261,15 +261,15 @@
│ │ │ │  
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_diffev.rst.txt
│ │ │ │ @@ -184,15 +184,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_expression_model.rst.txt
│ │ │ │ @@ -139,15 +139,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_jacobian_benchmark.rst.txt
│ │ │ │ @@ -238,26 +238,26 @@
│ │ │ │  
│ │ │ │   .. code-block:: none
│ │ │ │  
│ │ │ │      The "true" parameters are: a = 2.500, b = 1.300, c = 0.800
│ │ │ │  
│ │ │ │      | Method                  | Avg. time (ms) | # func. (+ Jac.) calls | Chi-squared | a     | b     | c     |
│ │ │ │      |-------------------------|----------------|------------------------|-------------|-------|-------|-------|
│ │ │ │ -    | leastsq                 | 7.19           | 39                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -    | leastsq with Jac.       | 4.86           | 12 (+10)               | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -    | least_squares           | 12.93          | 38                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -    | least_squares with Jac. | 11.26          | 11 (+9)                | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +    | leastsq                 | 1.79           | 39                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +    | leastsq with Jac.       | 1.55           | 12 (+10)               | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +    | least_squares           | 3.89           | 38                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +    | least_squares with Jac. | 2.71           | 11 (+9)                | 1.092       | 2.564 | 1.359 | 0.824 |
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_multi_datasets.rst.txt
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_multi_datasets_Model-interface.rst.txt
│ │ │ │ @@ -230,15 +230,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_with_algebraic_constraint.rst.txt
│ │ │ │ @@ -121,15 +121,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_with_bounds.rst.txt
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_with_derivfunc.rst.txt
│ │ │ │ @@ -175,15 +175,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_fit_with_inequality.rst.txt
│ │ │ │ @@ -163,15 +163,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_reduce_fcn.rst.txt
│ │ │ │ @@ -199,15 +199,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_sympy.rst.txt
│ │ │ │ @@ -189,15 +189,15 @@
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_two_dimensional_peak.rst.txt
│ │ │ │ @@ -368,15 +368,15 @@
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│ │ │ │  .. _sphx_glr_download_examples_example_two_dimensional_peak.py:
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_uncertainties_y_and_x.rst.txt
│ │ │ │ @@ -198,15 +198,15 @@
│ │ │ │      plt.show()
│ │ │ │  
│ │ │ │      # # <end examples/doc_uncertainties_in_x_and_y.py>
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│ │ │ │  .. rst-class:: sphx-glr-timing
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│ │ │ │  .. _sphx_glr_download_examples_example_uncertainties_y_and_x.py:
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/_sources/examples/example_use_pandas.rst.txt
│ │ │ │ @@ -123,15 +123,15 @@
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│ │ │ │  .. _sphx_glr_download_examples_example_use_pandas.py:
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│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_Model_interface.html
│ │ │ │ @@ -337,15 +337,15 @@
│ │ │ │  <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[Variables]]
│ │ │ │      N:    7.11270194 +/- 0.24334895 (3.42%) (init = 10)
│ │ │ │      tau:  2.92065227 +/- 0.13488230 (4.62%) (init = 1)
│ │ │ │  [[Correlations]] (unreported correlations are &lt; 0.100)
│ │ │ │      C(N, tau) = -0.9320
│ │ │ │  </pre></div>
│ │ │ │  </div>
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│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-model-interface-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/a69966d88009a9341e88bfe1935158a7/example_Model_interface.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_Model_interface.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/8b2fe0a32f4790de5b0465c00682a37b/example_Model_interface.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_Model_interface.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -179,15 +179,15 @@
│ │ │ │ │  result = model.fit(truncated_data_with_holes, params, t=t)
│ │ │ │ │  report_fit(result.params)
│ │ │ │ │  [[Variables]]
│ │ │ │ │      N:    7.11270194 +/- 0.24334895 (3.42%) (init = 10)
│ │ │ │ │      tau:  2.92065227 +/- 0.13488230 (4.62%) (init = 1)
│ │ │ │ │  [[Correlations]] (unreported correlations are < 0.100)
│ │ │ │ │      C(N, tau) = -0.9320
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.757 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.404 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___M_o_d_e_l___i_n_t_e_r_f_a_c_e_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___M_o_d_e_l___i_n_t_e_r_f_a_c_e_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___M_o_d_e_l___i_n_t_e_r_f_a_c_e_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_basinhopping.html
│ │ │ │ @@ -235,15 +235,15 @@
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">ydat</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;data&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">result0</span><span class="o">.</span><span class="n">best_fit</span><span class="p">,</span> <span class="s1">&#39;+&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;leastsq&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">result</span><span class="o">.</span><span class="n">best_fit</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">method2</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 7.247 seconds)</p>
│ │ │ │ +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.761 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-basinhopping-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/ae6f08d1acd42b44f92003d3b671ff34/example_basinhopping.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_basinhopping.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/165816e6cae13bf96b2272527b6d1d2b/example_basinhopping.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_basinhopping.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -124,15 +124,15 @@
│ │ │ │ │  
│ │ │ │ │  # plot comparison
│ │ │ │ │  plt.plot(x, ydat, 'o', label='data')
│ │ │ │ │  plt.plot(x, result0.best_fit, '+', label='leastsq')
│ │ │ │ │  plt.plot(x, result.best_fit, '-', label=method2)
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 7.247 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 2.761 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___b_a_s_i_n_h_o_p_p_i_n_g_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___b_a_s_i_n_h_o_p_p_i_n_g_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___b_a_s_i_n_h_o_p_p_i_n_g_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_brute.html
│ │ │ │ @@ -649,15 +649,15 @@
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>and finally, to generated the figure:</p>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plot_results_brute</span><span class="p">(</span><span class="n">result_brute</span><span class="p">,</span> <span class="n">best_vals</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">varlabels</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_brute_004.png" srcset="../_images/sphx_glr_example_brute_004.png, ../_images/sphx_glr_example_brute_004_3_00x.png 3.00x" alt="example brute" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 47.945 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_brute_004.png" srcset="../_images/sphx_glr_example_brute_004.png, ../_images/sphx_glr_example_brute_004_3_00x.png 3.00x" alt="example brute" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 17.693 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-brute-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/9254f2af7eef00978dc5823dc5418985/example_brute.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_brute.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/c004866ac6395edd2609ff96cecdc255/example_brute.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_brute.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -476,15 +476,15 @@
│ │ │ │ │  
│ │ │ │ │      if output is not None:
│ │ │ │ │          plt.savefig(output)
│ │ │ │ │  and finally, to generated the figure:
│ │ │ │ │  plot_results_brute(result_brute, best_vals=True, varlabels=None)
│ │ │ │ │  plt.show()
│ │ │ │ │  [example brute]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 47.945 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 17.693 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___b_r_u_t_e_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___b_r_u_t_e_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___b_r_u_t_e_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _p_r_e_v_i_o_u_s |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_complex_resonator_model.html
│ │ │ │ @@ -278,15 +278,15 @@
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;MHz&#39;</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="sphx-glr-horizontal">
│ │ │ │  <li><img src="../_images/sphx_glr_example_complex_resonator_model_002.png" srcset="../_images/sphx_glr_example_complex_resonator_model_002.png, ../_images/sphx_glr_example_complex_resonator_model_002_3_00x.png 3.00x" alt="example complex resonator model" class = "sphx-glr-multi-img"/></li>
│ │ │ │  <li><img src="../_images/sphx_glr_example_complex_resonator_model_003.png" srcset="../_images/sphx_glr_example_complex_resonator_model_003.png, ../_images/sphx_glr_example_complex_resonator_model_003_3_00x.png 3.00x" alt="example complex resonator model" class = "sphx-glr-multi-img"/></li>
│ │ │ │  </ul>
│ │ │ │ -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.134 seconds)</p>
│ │ │ │ +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.738 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-complex-resonator-model-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/3dcc7459227dbd4ba1982949be8491e1/example_complex_resonator_model.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_complex_resonator_model.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/3805fc8171e8a0686d5cf65be55085ee/example_complex_resonator_model.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_complex_resonator_model.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -158,15 +158,15 @@
│ │ │ │ │  plt.plot(f, 20*np.log10(np.abs(fit_s21)), '.-', label='best fit')
│ │ │ │ │  plt.plot(f, 20*np.log10(np.abs(guess_s21)), '--', label='initial fit')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.ylabel('|S21| (dB)')
│ │ │ │ │  plt.xlabel('MHz')
│ │ │ │ │      * [example complex resonator model]
│ │ │ │ │      * [example complex resonator model]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 2.134 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.738 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___c_o_m_p_l_e_x___r_e_s_o_n_a_t_o_r___m_o_d_e_l_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___c_o_m_p_l_e_x___r_e_s_o_n_a_t_o_r___m_o_d_e_l_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___c_o_m_p_l_e_x___r_e_s_o_n_a_t_o_r___m_o_d_e_l_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_confidence_interval.html
│ │ │ │ @@ -291,15 +291,15 @@
│ │ │ │              <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;prob&#39;</span><span class="p">)</span>
│ │ │ │              <span class="n">ax</span><span class="o">.</span><span class="n">tick_params</span><span class="p">(</span><span class="n">labelleft</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_confidence_interval_002.png" srcset="../_images/sphx_glr_example_confidence_interval_002.png, ../_images/sphx_glr_example_confidence_interval_002_3_00x.png 3.00x" alt="example confidence interval" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 46.494 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_confidence_interval_002.png" srcset="../_images/sphx_glr_example_confidence_interval_002.png, ../_images/sphx_glr_example_confidence_interval_002_3_00x.png 3.00x" alt="example confidence interval" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 15.538 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-confidence-interval-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/2c0316848a8a5e58fdf5c1bd1978018e/example_confidence_interval.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_confidence_interval.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/b6a243851aa5b1d7362705005c5ed3b1/example_confidence_interval.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_confidence_interval.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -171,15 +171,15 @@
│ │ │ │ │              plt.plot(xn, f(xn), lw=1)
│ │ │ │ │              plt.ylabel('prob')
│ │ │ │ │              ax.tick_params(labelleft=True)
│ │ │ │ │  
│ │ │ │ │  plt.tight_layout()
│ │ │ │ │  plt.show()
│ │ │ │ │  [example confidence interval]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 46.494 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 15.538 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___c_o_n_f_i_d_e_n_c_e___i_n_t_e_r_v_a_l_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___c_o_n_f_i_d_e_n_c_e___i_n_t_e_r_v_a_l_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___c_o_n_f_i_d_e_n_c_e___i_n_t_e_r_v_a_l_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_detect_outliers.html
│ │ │ │ @@ -240,15 +240,15 @@
│ │ │ │  <span class="n">axs</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">stderrs</span><span class="p">[</span><span class="s1">&#39;b&#39;</span><span class="p">])</span>
│ │ │ │  <span class="n">axs</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">idx</span><span class="p">],</span> <span class="n">stderrs</span><span class="p">[</span><span class="s1">&#39;b&#39;</span><span class="p">][</span><span class="n">idx</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;r&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;outlier&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">axs</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;err b change&#39;</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="n">axs</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_detect_outliers_003.png" srcset="../_images/sphx_glr_example_detect_outliers_003.png, ../_images/sphx_glr_example_detect_outliers_003_3_00x.png 3.00x" alt="example detect outliers" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 3.484 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_detect_outliers_003.png" srcset="../_images/sphx_glr_example_detect_outliers_003.png, ../_images/sphx_glr_example_detect_outliers_003_3_00x.png 3.00x" alt="example detect outliers" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.124 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-detect-outliers-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/a4a9bd70fc277eac0b5a505f48c84a99/example_detect_outliers.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_detect_outliers.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/997bd062873174254128e513e48dc191/example_detect_outliers.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_detect_outliers.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -117,15 +117,15 @@
│ │ │ │ │  
│ │ │ │ │  axs[3].plot(x, stderrs['b'])
│ │ │ │ │  axs[3].scatter(x[idx], stderrs['b'][idx], color='r', label='outlier')
│ │ │ │ │  axs[3].set_ylabel('err b change')
│ │ │ │ │  
│ │ │ │ │  axs[3].set_xlabel('x')
│ │ │ │ │  [example detect outliers]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 3.484 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.124 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___d_e_t_e_c_t___o_u_t_l_i_e_r_s_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___d_e_t_e_c_t___o_u_t_l_i_e_r_s_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___d_e_t_e_c_t___o_u_t_l_i_e_r_s_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_diffev.html
│ │ │ │ @@ -223,15 +223,15 @@
│ │ │ │  </div>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;data&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="o">+</span><span class="n">o1</span><span class="o">.</span><span class="n">residual</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;leastsq&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="o">+</span><span class="n">o2</span><span class="o">.</span><span class="n">residual</span><span class="p">,</span> <span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;diffev&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_diffev_001.png" srcset="../_images/sphx_glr_example_diffev_001.png, ../_images/sphx_glr_example_diffev_001_3_00x.png 3.00x" alt="example diffev" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.396 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_diffev_001.png" srcset="../_images/sphx_glr_example_diffev_001.png, ../_images/sphx_glr_example_diffev_001_3_00x.png 3.00x" alt="example diffev" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.402 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-diffev-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/b14ecb1d89648d4116095890700c90a4/example_diffev.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_diffev.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/9be2a6edec6597f9b4fc9ae817df3c9e/example_diffev.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_diffev.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -105,15 +105,15 @@
│ │ │ │ │      amp:     1.80253519 (init = 2.5)
│ │ │ │ │      decay:   5.76281241 (init = 1)
│ │ │ │ │  plt.plot(x, yn, 'o', label='data')
│ │ │ │ │  plt.plot(x, yn+o1.residual, '-', label='leastsq')
│ │ │ │ │  plt.plot(x, yn+o2.residual, '--', label='diffev')
│ │ │ │ │  plt.legend()
│ │ │ │ │  [example diffev]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.396 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.402 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___d_i_f_f_e_v_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___d_i_f_f_e_v_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___d_i_f_f_e_v_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_expression_model.html
│ │ │ │ @@ -181,15 +181,15 @@
│ │ │ │  </div>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">result</span><span class="o">.</span><span class="n">init_fit</span><span class="p">,</span> <span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;initial fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">result</span><span class="o">.</span><span class="n">best_fit</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;best fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_expression_model_001.png" srcset="../_images/sphx_glr_example_expression_model_001.png, ../_images/sphx_glr_example_expression_model_001_3_00x.png 3.00x" alt="example expression model" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.701 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_expression_model_001.png" srcset="../_images/sphx_glr_example_expression_model_001.png, ../_images/sphx_glr_example_expression_model_001_3_00x.png 3.00x" alt="example expression model" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.254 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-expression-model-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/18a51e50a47e90524ad3b8de0632b714/example_expression_model.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_expression_model.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/dd61d0d99d106be1eecc4533c0a813be/example_expression_model.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_expression_model.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -65,15 +65,15 @@
│ │ │ │ │  [[Correlations]] (unreported correlations are < 0.100)
│ │ │ │ │      C(amp, wid) = +0.5774
│ │ │ │ │  plt.plot(x, y, 'o')
│ │ │ │ │  plt.plot(x, result.init_fit, '--', label='initial fit')
│ │ │ │ │  plt.plot(x, result.best_fit, '-', label='best fit')
│ │ │ │ │  plt.legend()
│ │ │ │ │  [example expression model]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.701 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.254 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___e_x_p_r_e_s_s_i_o_n___m_o_d_e_l_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___e_x_p_r_e_s_s_i_o_n___m_o_d_e_l_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___e_x_p_r_e_s_s_i_o_n___m_o_d_e_l_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_jacobian_benchmark.html
│ │ │ │ @@ -305,21 +305,21 @@
│ │ │ │  <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <img src="../_images/sphx_glr_example_fit_jacobian_benchmark_001.png" srcset="../_images/sphx_glr_example_fit_jacobian_benchmark_001.png, ../_images/sphx_glr_example_fit_jacobian_benchmark_001_3_00x.png 3.00x" alt="example fit jacobian benchmark" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>The &quot;true&quot; parameters are: a = 2.500, b = 1.300, c = 0.800
│ │ │ │  
│ │ │ │  | Method                  | Avg. time (ms) | # func. (+ Jac.) calls | Chi-squared | a     | b     | c     |
│ │ │ │  |-------------------------|----------------|------------------------|-------------|-------|-------|-------|
│ │ │ │ -| leastsq                 | 7.19           | 39                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -| leastsq with Jac.       | 4.86           | 12 (+10)               | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -| least_squares           | 12.93          | 38                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ -| least_squares with Jac. | 11.26          | 11 (+9)                | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +| leastsq                 | 1.79           | 39                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +| leastsq with Jac.       | 1.55           | 12 (+10)               | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +| least_squares           | 3.89           | 38                     | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │ +| least_squares with Jac. | 2.71           | 11 (+9)                | 1.092       | 2.564 | 1.359 | 0.824 |
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.838 seconds)</p>
│ │ │ │ +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.371 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-jacobian-benchmark-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/9db45352ed3b7a40b0471b4137f67079/example_fit_jacobian_benchmark.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_jacobian_benchmark.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/42b143772ac94b1e24f82c78c37f8727/example_fit_jacobian_benchmark.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_jacobian_benchmark.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -197,23 +197,23 @@
│ │ │ │ │  [example fit jacobian benchmark]
│ │ │ │ │  The "true" parameters are: a = 2.500, b = 1.300, c = 0.800
│ │ │ │ │  
│ │ │ │ │  | Method                  | Avg. time (ms) | # func. (+ Jac.) calls | Chi-
│ │ │ │ │  squared | a     | b     | c     |
│ │ │ │ │  |-------------------------|----------------|------------------------|----------
│ │ │ │ │  ---|-------|-------|-------|
│ │ │ │ │ -| leastsq                 | 7.19           | 39                     | 1.092
│ │ │ │ │ +| leastsq                 | 1.79           | 39                     | 1.092
│ │ │ │ │  | 2.564 | 1.359 | 0.824 |
│ │ │ │ │ -| leastsq with Jac.       | 4.86           | 12 (+10)               | 1.092
│ │ │ │ │ +| leastsq with Jac.       | 1.55           | 12 (+10)               | 1.092
│ │ │ │ │  | 2.564 | 1.359 | 0.824 |
│ │ │ │ │ -| least_squares           | 12.93          | 38                     | 1.092
│ │ │ │ │ +| least_squares           | 3.89           | 38                     | 1.092
│ │ │ │ │  | 2.564 | 1.359 | 0.824 |
│ │ │ │ │ -| least_squares with Jac. | 11.26          | 11 (+9)                | 1.092
│ │ │ │ │ +| least_squares with Jac. | 2.71           | 11 (+9)                | 1.092
│ │ │ │ │  | 2.564 | 1.359 | 0.824 |
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 4.838 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.371 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___j_a_c_o_b_i_a_n___b_e_n_c_h_m_a_r_k_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___j_a_c_o_b_i_a_n___b_e_n_c_h_m_a_r_k_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___j_a_c_o_b_i_a_n___b_e_n_c_h_m_a_r_k_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_multi_datasets.html
│ │ │ │ @@ -229,15 +229,15 @@
│ │ │ │  <p>Plot the data sets and fits</p>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
│ │ │ │  <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span>
│ │ │ │      <span class="n">y_fit</span> <span class="o">=</span> <span class="n">gauss_dataset</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">params</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
│ │ │ │      <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="p">:],</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y_fit</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_fit_multi_datasets_001.png" srcset="../_images/sphx_glr_example_fit_multi_datasets_001.png, ../_images/sphx_glr_example_fit_multi_datasets_001_3_00x.png 3.00x" alt="example fit multi datasets" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.414 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_fit_multi_datasets_001.png" srcset="../_images/sphx_glr_example_fit_multi_datasets_001.png, ../_images/sphx_glr_example_fit_multi_datasets_001_3_00x.png 3.00x" alt="example fit multi datasets" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.267 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-multi-datasets-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/e9797dfaa256c029a43c2a364328ed36/example_fit_multi_datasets.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_multi_datasets.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/5c7aecfc832cba8709209d4aee80c638/example_fit_multi_datasets.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_multi_datasets.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -110,15 +110,15 @@
│ │ │ │ │      C(amp_2, amp_5) = +0.1092
│ │ │ │ │  Plot the data sets and fits
│ │ │ │ │  plt.figure()
│ │ │ │ │  for i in range(5):
│ │ │ │ │      y_fit = gauss_dataset(out.params, i, x)
│ │ │ │ │      plt.plot(x, data[i, :], 'o', x, y_fit, '-')
│ │ │ │ │  [example fit multi datasets]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.414 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.267 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_multi_datasets_Model-interface.html
│ │ │ │ @@ -240,15 +240,15 @@
│ │ │ │  <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">y</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
│ │ │ │      <span class="n">components</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">eval_components</span><span class="p">(</span><span class="n">params</span><span class="o">=</span><span class="n">out</span><span class="o">.</span><span class="n">params</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">)</span>
│ │ │ │      <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">components</span><span class="p">[</span><span class="sa">f</span><span class="s1">&#39;n</span><span class="si">{</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s1">_&#39;</span><span class="p">],</span> <span class="s1">&#39;-&#39;</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001.png" srcset="../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001.png, ../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001_3_00x.png 3.00x" alt="example fit multi datasets Model interface" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.514 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001.png" srcset="../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001.png, ../_images/sphx_glr_example_fit_multi_datasets_Model-interface_001_3_00x.png 3.00x" alt="example fit multi datasets Model interface" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.328 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-multi-datasets-model-interface-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/6bd1774e2b7de7f7c5a9bb78e91a173a/example_fit_multi_datasets_Model-interface.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_multi_datasets_Model-interface.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/9cc433d73a3c54edbac87a2639bd6858/example_fit_multi_datasets_Model-interface.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_multi_datasets_Model-interface.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -123,15 +123,15 @@
│ │ │ │ │  plt.figure()
│ │ │ │ │  for i, y in enumerate(data):
│ │ │ │ │      components = model.eval_components(params=out.params, x=x)
│ │ │ │ │      plt.plot(x, y, 'o', x, components[f'n{i+1}_'], '-')
│ │ │ │ │  
│ │ │ │ │  plt.show()
│ │ │ │ │  [example fit multi datasets Model interface]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.514 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.328 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s___M_o_d_e_l_-_i_n_t_e_r_f_a_c_e_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s___M_o_d_e_l_-_i_n_t_e_r_f_a_c_e_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___m_u_l_t_i___d_a_t_a_s_e_t_s___M_o_d_e_l_-_i_n_t_e_r_f_a_c_e_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_with_algebraic_constraint.html
│ │ │ │ @@ -210,15 +210,15 @@
│ │ │ │      C(g_sigma, total_amplitude)        = -0.4115
│ │ │ │      C(g_center, line_intercept)        = +0.3868
│ │ │ │      C(g_amplitude, line_intercept)     = +0.1834
│ │ │ │      C(g_amplitude, line_slope)         = +0.1825
│ │ │ │      C(g_sigma, line_slope)             = +0.1739
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.975 seconds)</p>
│ │ │ │ +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.283 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-with-algebraic-constraint-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/795f02254c8fb4ff85239a1247e0cdb3/example_fit_with_algebraic_constraint.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_with_algebraic_constraint.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/cb6735e259aa0fe1e9993a89862af987/example_fit_with_algebraic_constraint.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_with_algebraic_constraint.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -106,15 +106,15 @@
│ │ │ │ │      C(g_amplitude, total_amplitude)    = -0.6115
│ │ │ │ │      C(line_intercept, total_amplitude) = -0.5883
│ │ │ │ │      C(g_sigma, total_amplitude)        = -0.4115
│ │ │ │ │      C(g_center, line_intercept)        = +0.3868
│ │ │ │ │      C(g_amplitude, line_intercept)     = +0.1834
│ │ │ │ │      C(g_amplitude, line_slope)         = +0.1825
│ │ │ │ │      C(g_sigma, line_slope)             = +0.1739
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.975 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.283 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___a_l_g_e_b_r_a_i_c___c_o_n_s_t_r_a_i_n_t_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___a_l_g_e_b_r_a_i_c___c_o_n_s_t_r_a_i_n_t_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___a_l_g_e_b_r_a_i_c___c_o_n_s_t_r_a_i_n_t_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_with_bounds.html
│ │ │ │ @@ -208,15 +208,15 @@
│ │ │ │  </div>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;data&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">fit</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;best fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_fit_with_bounds_001.png" srcset="../_images/sphx_glr_example_fit_with_bounds_001.png, ../_images/sphx_glr_example_fit_with_bounds_001_3_00x.png 3.00x" alt="example fit with bounds" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.082 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_fit_with_bounds_001.png" srcset="../_images/sphx_glr_example_fit_with_bounds_001.png, ../_images/sphx_glr_example_fit_with_bounds_001_3_00x.png 3.00x" alt="example fit with bounds" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.273 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-with-bounds-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/fd01b33f1731fe67d0f89a803067a496/example_fit_with_bounds.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_with_bounds.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/27b87cac9cd9afd7fa73c15f10211608/example_fit_with_bounds.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_with_bounds.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -91,15 +91,15 @@
│ │ │ │ │    | decay    | +0.5757  | -0.0404  | -0.0502  | +1.0000  |
│ │ │ │ │    +----------+----------+----------+----------+----------+
│ │ │ │ │  plt.plot(x, data, 'o', label='data')
│ │ │ │ │  plt.plot(x, fit, label='best fit')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │  [example fit with bounds]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.082 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.273 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___b_o_u_n_d_s_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___b_o_u_n_d_s_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___b_o_u_n_d_s_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_with_derivfunc.html
│ │ │ │ @@ -214,15 +214,15 @@
│ │ │ │  both methods:</p>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;data&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">fit1</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;with analytical derivative&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">fit2</span><span class="p">,</span> <span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;without analytical derivative&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_fit_with_derivfunc_001.png" srcset="../_images/sphx_glr_example_fit_with_derivfunc_001.png, ../_images/sphx_glr_example_fit_with_derivfunc_001_3_00x.png 3.00x" alt="example fit with derivfunc" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.570 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_fit_with_derivfunc_001.png" srcset="../_images/sphx_glr_example_fit_with_derivfunc_001.png, ../_images/sphx_glr_example_fit_with_derivfunc_001_3_00x.png 3.00x" alt="example fit with derivfunc" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.257 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-with-derivfunc-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/a48b6f5c2c4202cb67d15a117c5eb6bc/example_fit_with_derivfunc.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_with_derivfunc.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/34710c8e386116e372179d0463d53c6a/example_fit_with_derivfunc.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_with_derivfunc.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -100,15 +100,15 @@
│ │ │ │ │  and the best-fit to the synthetic data (with added noise) is the same for both
│ │ │ │ │  methods:
│ │ │ │ │  plt.plot(x, data, 'o', label='data')
│ │ │ │ │  plt.plot(x, fit1, label='with analytical derivative')
│ │ │ │ │  plt.plot(x, fit2, '--', label='without analytical derivative')
│ │ │ │ │  plt.legend()
│ │ │ │ │  [example fit with derivfunc]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.570 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.257 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___d_e_r_i_v_f_u_n_c_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___d_e_r_i_v_f_u_n_c_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___d_e_r_i_v_f_u_n_c_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_fit_with_inequality.html
│ │ │ │ @@ -200,15 +200,15 @@
│ │ │ │  <p>and figure:</p>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="s1">&#39;o&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">best_fit</span><span class="p">,</span> <span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;best fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_fit_with_inequality_001.png" srcset="../_images/sphx_glr_example_fit_with_inequality_001.png, ../_images/sphx_glr_example_fit_with_inequality_001_3_00x.png 3.00x" alt="example fit with inequality" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.780 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_fit_with_inequality_001.png" srcset="../_images/sphx_glr_example_fit_with_inequality_001.png, ../_images/sphx_glr_example_fit_with_inequality_001_3_00x.png 3.00x" alt="example fit with inequality" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.270 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-fit-with-inequality-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/8cc2f5f768207b7533d24c7fd6035d90/example_fit_with_inequality.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_fit_with_inequality.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/0372b8f3b0b615eb40855b665c11d339/example_fit_with_inequality.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_fit_with_inequality.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -84,15 +84,15 @@
│ │ │ │ │      C(cen_g, wid_g)      = +0.1546
│ │ │ │ │  and figure:
│ │ │ │ │  plt.plot(x, data, 'o')
│ │ │ │ │  plt.plot(x, best_fit, '--', label='best fit')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │  [example fit with inequality]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.780 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.270 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___i_n_e_q_u_a_l_i_t_y_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___i_n_e_q_u_a_l_i_t_y_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___f_i_t___w_i_t_h___i_n_e_q_u_a_l_i_t_y_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_reduce_fcn.html
│ │ │ │ @@ -237,15 +237,15 @@
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="p">,</span> <span class="s1">&#39;--*&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;with noise+outliers&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="o">+</span><span class="n">o1</span><span class="o">.</span><span class="n">residual</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;sum of squares fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">yn</span><span class="o">+</span><span class="n">o2</span><span class="o">.</span><span class="n">residual</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;robust fit&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_reduce_fcn_001.png" srcset="../_images/sphx_glr_example_reduce_fcn_001.png, ../_images/sphx_glr_example_reduce_fcn_001_3_00x.png 3.00x" alt="example reduce fcn" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.192 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_reduce_fcn_001.png" srcset="../_images/sphx_glr_example_reduce_fcn_001.png, ../_images/sphx_glr_example_reduce_fcn_001_3_00x.png 3.00x" alt="example reduce fcn" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.308 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-reduce-fcn-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/5d125e1fb5f23aa5a5473c67a4699244/example_reduce_fcn.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_reduce_fcn.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/d0e8e1e708ca0de18639372a3ff96a6a/example_reduce_fcn.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_reduce_fcn.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -118,15 +118,15 @@
│ │ │ │ │  plt.plot(x, y, 'o', label='true function')
│ │ │ │ │  plt.plot(x, yn, '--*', label='with noise+outliers')
│ │ │ │ │  plt.plot(x, yn+o1.residual, '-', label='sum of squares fit')
│ │ │ │ │  plt.plot(x, yn+o2.residual, '-', label='robust fit')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │  [example reduce fcn]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.192 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.308 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___r_e_d_u_c_e___f_c_n_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___r_e_d_u_c_e___f_c_n_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___r_e_d_u_c_e___f_c_n_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_sympy.html
│ │ │ │ @@ -196,15 +196,15 @@
│ │ │ │  <span class="n">res2</span> <span class="o">=</span> <span class="n">lm_mod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">yn</span><span class="p">,</span> <span class="o">**</span><span class="n">param2_values</span><span class="p">)</span>
│ │ │ │  <span class="n">res2</span><span class="o">.</span><span class="n">plot_fit</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;true&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_sympy_003.png" srcset="../_images/sphx_glr_example_sympy_003.png, ../_images/sphx_glr_example_sympy_003_3_00x.png 3.00x" alt="Model(_lambdifygenerated)" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 3.821 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_sympy_003.png" srcset="../_images/sphx_glr_example_sympy_003.png, ../_images/sphx_glr_example_sympy_003_3_00x.png 3.00x" alt="Model(_lambdifygenerated)" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.138 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-sympy-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/6069607ae016c4f4f055d1c8dfd4bfa7/example_sympy.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_sympy.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/ecc08a53d28f5c81caa3656731ba5657/example_sympy.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_sympy.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -80,15 +80,15 @@
│ │ │ │ │  param2_values = dict(x=x, A1=2, sigma1=1, xc1=2, xc2=5, xw=4, B=5)
│ │ │ │ │  res2 = lm_mod.fit(data=yn, **param2_values)
│ │ │ │ │  res2.plot_fit()
│ │ │ │ │  plt.plot(x, y, label='true')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │  [Model(_lambdifygenerated)]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 3.821 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 1.138 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___s_y_m_p_y_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___s_y_m_p_y_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___s_y_m_p_y_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_two_dimensional_peak.html
│ │ │ │ @@ -350,15 +350,15 @@
│ │ │ │  <span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">axs</span><span class="o">.</span><span class="n">ravel</span><span class="p">():</span>
│ │ │ │      <span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>
│ │ │ │      <span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;y&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">remove</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_two_dimensional_peak_004.png" srcset="../_images/sphx_glr_example_two_dimensional_peak_004.png, ../_images/sphx_glr_example_two_dimensional_peak_004_3_00x.png 3.00x" alt="Data, Fit, Data - Fit" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 7.257 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_two_dimensional_peak_004.png" srcset="../_images/sphx_glr_example_two_dimensional_peak_004.png, ../_images/sphx_glr_example_two_dimensional_peak_004_3_00x.png 3.00x" alt="Data, Fit, Data - Fit" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 3.183 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-two-dimensional-peak-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/ee6bdfefbd3fee18a7b2cb99c291f27e/example_two_dimensional_peak.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_two_dimensional_peak.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/87be2ee5d3294a608face2290f955fe3/example_two_dimensional_peak.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_two_dimensional_peak.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -219,15 +219,15 @@
│ │ │ │ │  
│ │ │ │ │  for ax in axs.ravel():
│ │ │ │ │      ax.set_xlabel('x')
│ │ │ │ │      ax.set_ylabel('y')
│ │ │ │ │  axs[1, 1].remove()
│ │ │ │ │  plt.show()
│ │ │ │ │  [Data, Fit, Data - Fit]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 7.257 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 3.183 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___t_w_o___d_i_m_e_n_s_i_o_n_a_l___p_e_a_k_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___t_w_o___d_i_m_e_n_s_i_o_n_a_l___p_e_a_k_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___t_w_o___d_i_m_e_n_s_i_o_n_a_l___p_e_a_k_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_uncertainties_y_and_x.html
│ │ │ │ @@ -288,15 +288,15 @@
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">xdat</span><span class="p">,</span> <span class="n">bestfit2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;fit, with x error&#39;</span><span class="p">)</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
│ │ │ │  <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="c1"># # &lt;end examples/doc_uncertainties_in_x_and_y.py&gt;</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.773 seconds)</p>
│ │ │ │ +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.261 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-uncertainties-y-and-x-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/2588677a1a505d9f24402b03894d5bfd/example_uncertainties_y_and_x.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_uncertainties_y_and_x.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/dba681f3439dfa9f72e79de3389e77d7/example_uncertainties_y_and_x.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_uncertainties_y_and_x.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -177,15 +177,15 @@
│ │ │ │ │  plt.plot(xtrue, ytrue, '-+', label='true data')
│ │ │ │ │  plt.plot(xdat, bestfit1, label='fit, no x error')
│ │ │ │ │  plt.plot(xdat, bestfit2, label='fit, with x error')
│ │ │ │ │  plt.legend()
│ │ │ │ │  plt.show()
│ │ │ │ │  
│ │ │ │ │  # # <end examples/doc_uncertainties_in_x_and_y.py>
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.773 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.261 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___u_n_c_e_r_t_a_i_n_t_i_e_s___y___a_n_d___x_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___u_n_c_e_r_t_a_i_n_t_i_e_s___y___a_n_d___x_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___u_n_c_e_r_t_a_i_n_t_i_e_s___y___a_n_d___x_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/examples/example_use_pandas.html
│ │ │ │ @@ -175,15 +175,15 @@
│ │ │ │      C(amplitude, sigma) = +0.7087
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>and plot below:</p>
│ │ │ │  <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">result</span><span class="o">.</span><span class="n">plot_fit</span><span class="p">()</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │ -<img src="../_images/sphx_glr_example_use_pandas_001.png" srcset="../_images/sphx_glr_example_use_pandas_001.png, ../_images/sphx_glr_example_use_pandas_001_3_00x.png 3.00x" alt="Model(lorentzian)" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.782 seconds)</p>
│ │ │ │ +<img src="../_images/sphx_glr_example_use_pandas_001.png" srcset="../_images/sphx_glr_example_use_pandas_001.png, ../_images/sphx_glr_example_use_pandas_001_3_00x.png 3.00x" alt="Model(lorentzian)" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.291 seconds)</p>
│ │ │ │  <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-use-pandas-py">
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/5adbaff47e6aef0917d3da79f59fba26/example_use_pandas.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">example_use_pandas.ipynb</span></code></a></p>
│ │ │ │  </div>
│ │ │ │  <div class="sphx-glr-download sphx-glr-download-python docutils container">
│ │ │ │  <p><a class="reference download internal" download="" href="../_downloads/67e6ee8d13b1ad43c31b4b2dc6d01d54/example_use_pandas.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">example_use_pandas.py</span></code></a></p>
│ │ │ │  </div>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -61,15 +61,15 @@
│ │ │ │ │      height:     10.7899571 +/- 0.17160652 (1.59%) == '0.3183099*amplitude/max
│ │ │ │ │  (1e-15, sigma)'
│ │ │ │ │  [[Correlations]] (unreported correlations are < 0.100)
│ │ │ │ │      C(amplitude, sigma) = +0.7087
│ │ │ │ │  and plot below:
│ │ │ │ │  result.plot_fit()
│ │ │ │ │  [Model(lorentzian)]
│ │ │ │ │ -TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.782 seconds)
│ │ │ │ │ +TToottaall rruunnnniinngg ttiimmee ooff tthhee ssccrriipptt:: (0 minutes 0.291 seconds)
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _J_u_p_y_t_e_r_ _n_o_t_e_b_o_o_k_:_ _e_x_a_m_p_l_e___u_s_e___p_a_n_d_a_s_._i_p_y_n_b
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _P_y_t_h_o_n_ _s_o_u_r_c_e_ _c_o_d_e_:_ _e_x_a_m_p_l_e___u_s_e___p_a_n_d_a_s_._p_y
│ │ │ │ │  _D_o_w_n_l_o_a_d_ _z_i_p_p_e_d_:_ _e_x_a_m_p_l_e___u_s_e___p_a_n_d_a_s_._z_i_p
│ │ │ │ │  _G_a_l_l_e_r_y_ _g_e_n_e_r_a_t_e_d_ _b_y_ _S_p_h_i_n_x_-_G_a_l_l_e_r_y
│ │ │ │ │  ******** NNaavviiggaattiioonn ********
│ │ │ │ │      * _i_n_d_e_x
│ │ │ │ │      * _n_e_x_t |
│ │ │ ├── ./usr/share/doc/python3-lmfit/html/searchindex.js
│ │ │ │ ├── js-beautify {}
│ │ │ │ │ @@ -1436,15 +1436,14 @@
│ │ │ │ │          "0708269": 9,
│ │ │ │ │          "07083": 9,
│ │ │ │ │          "0726e": 9,
│ │ │ │ │          "0737250": 24,
│ │ │ │ │          "07382999": 15,
│ │ │ │ │          "07386098": 14,
│ │ │ │ │          "07744386": 15,
│ │ │ │ │ -        "082": 17,
│ │ │ │ │          "08260274": 14,
│ │ │ │ │          "08261146": 15,
│ │ │ │ │          "0834e": 15,
│ │ │ │ │          "08533642": 8,
│ │ │ │ │          "0870": 17,
│ │ │ │ │          "08937623": 10,
│ │ │ │ │          "08992736": 16,
│ │ │ │ │ @@ -1498,15 +1497,15 @@
│ │ │ │ │          "120": 16,
│ │ │ │ │          "1208": 7,
│ │ │ │ │          "12156": 9,
│ │ │ │ │          "12156317": 9,
│ │ │ │ │          "1223": 22,
│ │ │ │ │          "123": [8, 9],
│ │ │ │ │          "12345": 17,
│ │ │ │ │ -        "124": 7,
│ │ │ │ │ +        "124": [7, 10],
│ │ │ │ │          "12464389": 17,
│ │ │ │ │          "12499965": 7,
│ │ │ │ │          "12499997": 7,
│ │ │ │ │          "125": 7,
│ │ │ │ │          "12528141463621": 8,
│ │ │ │ │          "12633327": 23,
│ │ │ │ │          "1266": 22,
│ │ │ │ │ @@ -1518,20 +1517,21 @@
│ │ │ │ │          "130": 20,
│ │ │ │ │          "13089969": 7,
│ │ │ │ │          "1309": 7,
│ │ │ │ │          "1324": 1,
│ │ │ │ │          "133": [8, 23],
│ │ │ │ │          "13340536": 24,
│ │ │ │ │          "1338": 10,
│ │ │ │ │ -        "134": [7, 8],
│ │ │ │ │ +        "134": 7,
│ │ │ │ │          "13481789": 5,
│ │ │ │ │          "13488230": 5,
│ │ │ │ │          "135": [1, 20],
│ │ │ │ │          "1359": 23,
│ │ │ │ │          "136": 11,
│ │ │ │ │ +        "138": 21,
│ │ │ │ │          "1381": 23,
│ │ │ │ │          "14": [4, 6, 9, 13, 15, 16, 17, 28, 29],
│ │ │ │ │          "1415926": 3,
│ │ │ │ │          "1418": 6,
│ │ │ │ │          "142": 8,
│ │ │ │ │          "1436": 1,
│ │ │ │ │          "146": [11, 23],
│ │ │ │ │ @@ -1555,51 +1555,52 @@
│ │ │ │ │          "16": [1, 6, 7, 9, 15, 22, 35],
│ │ │ │ │          "1630": 23,
│ │ │ │ │          "1647": 9,
│ │ │ │ │          "1651": 19,
│ │ │ │ │          "1655": 23,
│ │ │ │ │          "1670": 9,
│ │ │ │ │          "1674767": 20,
│ │ │ │ │ -        "17": [5, 12, 23, 35],
│ │ │ │ │ +        "17": [5, 7, 12, 23, 35],
│ │ │ │ │          "1715": 23,
│ │ │ │ │          "17160652": 24,
│ │ │ │ │          "1720": 11,
│ │ │ │ │          "1731192": 23,
│ │ │ │ │          "1739": 16,
│ │ │ │ │          "175": 1,
│ │ │ │ │          "1762e": 23,
│ │ │ │ │          "1774": 22,
│ │ │ │ │          "17809725": 7,
│ │ │ │ │          "18": [5, 7, 11, 15, 23, 35],
│ │ │ │ │          "180": 22,
│ │ │ │ │          "1811577": 23,
│ │ │ │ │          "1812e": 15,
│ │ │ │ │          "1825": 16,
│ │ │ │ │ +        "183": 22,
│ │ │ │ │          "1834": 16,
│ │ │ │ │          "1841": 12,
│ │ │ │ │          "1851": 12,
│ │ │ │ │          "1858429": 23,
│ │ │ │ │          "1870": 23,
│ │ │ │ │          "18749997": 7,
│ │ │ │ │          "1875": 7,
│ │ │ │ │          "18756": 17,
│ │ │ │ │          "1877635": 16,
│ │ │ │ │          "18965087": 6,
│ │ │ │ │ -        "19": [1, 4, 13, 14, 16, 17, 23, 29],
│ │ │ │ │ +        "19": [1, 4, 14, 16, 17, 23, 29],
│ │ │ │ │          "19011498": 6,
│ │ │ │ │ -        "192": [7, 20, 24],
│ │ │ │ │ +        "192": [7, 24],
│ │ │ │ │          "1924": 23,
│ │ │ │ │          "1936": 19,
│ │ │ │ │          "19401928": 11,
│ │ │ │ │          "19580": 12,
│ │ │ │ │          "199": 7,
│ │ │ │ │          "1d": [2, 14, 15, 35],
│ │ │ │ │          "1e": [2, 15, 16, 22, 24, 28],
│ │ │ │ │          "1j": 8,
│ │ │ │ │ -        "2": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33],
│ │ │ │ │ +        "2": [0, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33],
│ │ │ │ │          "20": [1, 6, 8, 9, 14, 15, 16, 17, 19, 22, 24, 28, 35],
│ │ │ │ │          "200": [1, 2, 5, 8, 14, 15, 24, 26, 33],
│ │ │ │ │          "2000": 28,
│ │ │ │ │          "200000": 28,
│ │ │ │ │          "2001": 30,
│ │ │ │ │          "2002": 30,
│ │ │ │ │          "2003": 30,
│ │ │ │ │ @@ -1649,51 +1650,58 @@
│ │ │ │ │          "242": 7,
│ │ │ │ │          "24259071": 5,
│ │ │ │ │          "24334895": 5,
│ │ │ │ │          "24410753": 17,
│ │ │ │ │          "2460": 23,
│ │ │ │ │          "24638": 9,
│ │ │ │ │          "2464": 22,
│ │ │ │ │ -        "247": [6, 8],
│ │ │ │ │ +        "247": 8,
│ │ │ │ │          "2474265369565": 8,
│ │ │ │ │          "24998843": 7,
│ │ │ │ │          "24999772": 7,
│ │ │ │ │          "24999999": 7,
│ │ │ │ │          "25": [1, 6, 7, 9, 14, 15, 22, 23, 24, 32],
│ │ │ │ │          "250": [9, 17, 20, 26],
│ │ │ │ │          "2500": 9,
│ │ │ │ │          "25332": 6,
│ │ │ │ │          "25370110": 6,
│ │ │ │ │          "25370113": 6,
│ │ │ │ │ +        "254": 12,
│ │ │ │ │          "2542": 15,
│ │ │ │ │          "256760": 23,
│ │ │ │ │ -        "257": 22,
│ │ │ │ │ +        "257": 18,
│ │ │ │ │          "25743367": 15,
│ │ │ │ │          "2575": 14,
│ │ │ │ │          "25755570": 14,
│ │ │ │ │ -        "26": [7, 13, 14, 15, 16, 17, 22],
│ │ │ │ │ +        "26": [7, 14, 15, 16, 17, 22],
│ │ │ │ │ +        "261": 23,
│ │ │ │ │          "26179939": 7,
│ │ │ │ │          "263": 10,
│ │ │ │ │          "26503": 16,
│ │ │ │ │          "26606": 22,
│ │ │ │ │          "2664": 14,
│ │ │ │ │ +        "267": 14,
│ │ │ │ │          "268": 10,
│ │ │ │ │          "2696": 15,
│ │ │ │ │          "27": [4, 9, 19, 22, 29],
│ │ │ │ │ +        "270": 19,
│ │ │ │ │          "2722842": 19,
│ │ │ │ │ +        "273": 17,
│ │ │ │ │          "2735": 23,
│ │ │ │ │          "2761": 19,
│ │ │ │ │          "2776438": 23,
│ │ │ │ │          "27s_t": 1,
│ │ │ │ │          "28": [5, 23],
│ │ │ │ │          "28002384": 5,
│ │ │ │ │ +        "283": 16,
│ │ │ │ │          "28588": 12,
│ │ │ │ │          "2887": 16,
│ │ │ │ │          "28904676": 22,
│ │ │ │ │          "29": 19,
│ │ │ │ │ +        "291": 24,
│ │ │ │ │          "2913": 16,
│ │ │ │ │          "2919": 14,
│ │ │ │ │          "2922": 15,
│ │ │ │ │          "294636": 8,
│ │ │ │ │          "295": 1,
│ │ │ │ │          "2951": 19,
│ │ │ │ │          "2968": 14,
│ │ │ │ │ @@ -1710,14 +1718,15 @@
│ │ │ │ │          "301": 7,
│ │ │ │ │          "30195609": 15,
│ │ │ │ │          "3037": 17,
│ │ │ │ │          "3040": 15,
│ │ │ │ │          "3046": 22,
│ │ │ │ │          "3055": 16,
│ │ │ │ │          "3058": 17,
│ │ │ │ │ +        "308": 20,
│ │ │ │ │          "30899694": 7,
│ │ │ │ │          "31": 6,
│ │ │ │ │          "310": 26,
│ │ │ │ │          "31007541": 24,
│ │ │ │ │          "3117": 8,
│ │ │ │ │          "31249964": 7,
│ │ │ │ │          "3146": 8,
│ │ │ │ │ @@ -1726,14 +1735,15 @@
│ │ │ │ │          "3183099": [16, 24],
│ │ │ │ │          "32": [14, 20],
│ │ │ │ │          "3200": 32,
│ │ │ │ │          "32078443": 15,
│ │ │ │ │          "32192128": 16,
│ │ │ │ │          "32715193": 23,
│ │ │ │ │          "32742010": 14,
│ │ │ │ │ +        "328": 15,
│ │ │ │ │          "329": 6,
│ │ │ │ │          "32980958": 9,
│ │ │ │ │          "32981": 9,
│ │ │ │ │          "33": [9, 14, 20],
│ │ │ │ │          "33162347": 20,
│ │ │ │ │          "3342": 22,
│ │ │ │ │          "34": 23,
│ │ │ │ │ @@ -1751,38 +1761,38 @@
│ │ │ │ │          "3585": 18,
│ │ │ │ │          "359": 13,
│ │ │ │ │          "36": 14,
│ │ │ │ │          "3646": 17,
│ │ │ │ │          "36481425": 16,
│ │ │ │ │          "3688": 15,
│ │ │ │ │          "37": [6, 14, 17, 22],
│ │ │ │ │ +        "371": 13,
│ │ │ │ │          "3742": 14,
│ │ │ │ │          "375000": 7,
│ │ │ │ │          "3796": 19,
│ │ │ │ │          "38": [13, 22, 23],
│ │ │ │ │          "3823": 22,
│ │ │ │ │          "3868": 16,
│ │ │ │ │          "39": [13, 18, 23, 24],
│ │ │ │ │          "39269908": 7,
│ │ │ │ │ -        "396": 11,
│ │ │ │ │          "3989423": [15, 16],
│ │ │ │ │          "3f": [13, 18],
│ │ │ │ │          "4": [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 26, 29, 30, 32, 33],
│ │ │ │ │          "40": [6, 21],
│ │ │ │ │          "401856": 10,
│ │ │ │ │ -        "404": 33,
│ │ │ │ │ +        "402": 11,
│ │ │ │ │ +        "404": [5, 33],
│ │ │ │ │          "40552155": 15,
│ │ │ │ │          "40625133": 12,
│ │ │ │ │          "406586": 23,
│ │ │ │ │          "41": [5, 8, 9, 23],
│ │ │ │ │          "411487": 11,
│ │ │ │ │          "4115": 16,
│ │ │ │ │          "41261441": 16,
│ │ │ │ │          "4131e": 15,
│ │ │ │ │ -        "414": 14,
│ │ │ │ │          "416": 28,
│ │ │ │ │          "41851637": 16,
│ │ │ │ │          "4195833": 22,
│ │ │ │ │          "42": 5,
│ │ │ │ │          "43": 23,
│ │ │ │ │          "4321": 17,
│ │ │ │ │          "436569": 20,
│ │ │ │ │ @@ -1794,28 +1804,26 @@
│ │ │ │ │          "4411385": 6,
│ │ │ │ │          "44210577": 23,
│ │ │ │ │          "44581423": 23,
│ │ │ │ │          "45": [9, 23],
│ │ │ │ │          "450": 11,
│ │ │ │ │          "4526504": 6,
│ │ │ │ │          "4572e": 7,
│ │ │ │ │ -        "46": [5, 8, 9],
│ │ │ │ │ +        "46": [5, 8],
│ │ │ │ │          "46229147": 10,
│ │ │ │ │          "46504173": 19,
│ │ │ │ │ -        "47": [7, 16],
│ │ │ │ │ +        "47": 16,
│ │ │ │ │          "478231": 22,
│ │ │ │ │          "48": [6, 23],
│ │ │ │ │          "48130689": 22,
│ │ │ │ │ -        "484": 10,
│ │ │ │ │          "486": 35,
│ │ │ │ │          "489": 35,
│ │ │ │ │          "491": 35,
│ │ │ │ │          "492": 35,
│ │ │ │ │          "493": 35,
│ │ │ │ │ -        "494": 9,
│ │ │ │ │          "49516158": 22,
│ │ │ │ │          "496": 35,
│ │ │ │ │          "496119": 24,
│ │ │ │ │          "49692376": 22,
│ │ │ │ │          "497": 35,
│ │ │ │ │          "4972": 8,
│ │ │ │ │          "499": 35,
│ │ │ │ │ @@ -1839,15 +1847,15 @@
│ │ │ │ │          "508878": 7,
│ │ │ │ │          "51074241": 22,
│ │ │ │ │          "51171730": 9,
│ │ │ │ │          "512": 35,
│ │ │ │ │          "512493": 6,
│ │ │ │ │          "51298991": 10,
│ │ │ │ │          "51399": 22,
│ │ │ │ │ -        "514": [15, 35],
│ │ │ │ │ +        "514": 35,
│ │ │ │ │          "5150": 8,
│ │ │ │ │          "5151": 8,
│ │ │ │ │          "5175": 8,
│ │ │ │ │          "5178641": 22,
│ │ │ │ │          "52": [6, 11, 12, 16],
│ │ │ │ │          "521": 35,
│ │ │ │ │          "52163544": 19,
│ │ │ │ │ @@ -1861,28 +1869,28 @@
│ │ │ │ │          "52896805": 23,
│ │ │ │ │          "529": 35,
│ │ │ │ │          "533": 35,
│ │ │ │ │          "534": 35,
│ │ │ │ │          "535": 35,
│ │ │ │ │          "536": 35,
│ │ │ │ │          "537781821432": 8,
│ │ │ │ │ -        "538": 8,
│ │ │ │ │ +        "538": [8, 9],
│ │ │ │ │          "539": 35,
│ │ │ │ │          "540": 35,
│ │ │ │ │          "542": 35,
│ │ │ │ │          "543": 35,
│ │ │ │ │          "545": 35,
│ │ │ │ │          "547": 35,
│ │ │ │ │          "54740777": 22,
│ │ │ │ │          "548": 35,
│ │ │ │ │          "54820333": 23,
│ │ │ │ │          "54866058": 6,
│ │ │ │ │          "54866141": 6,
│ │ │ │ │          "549": 35,
│ │ │ │ │ -        "55": [10, 16],
│ │ │ │ │ +        "55": [10, 13, 16],
│ │ │ │ │          "550": 35,
│ │ │ │ │          "552": 35,
│ │ │ │ │          "553": 35,
│ │ │ │ │          "554": 35,
│ │ │ │ │          "55438813": 17,
│ │ │ │ │          "556": 35,
│ │ │ │ │          "558": 35,
│ │ │ │ │ @@ -1894,15 +1902,15 @@
│ │ │ │ │          "5625": 7,
│ │ │ │ │          "5626e": 15,
│ │ │ │ │          "5635": 18,
│ │ │ │ │          "564": [13, 35],
│ │ │ │ │          "565": 35,
│ │ │ │ │          "567": 35,
│ │ │ │ │          "569": 35,
│ │ │ │ │ -        "570": [18, 35],
│ │ │ │ │ +        "570": 35,
│ │ │ │ │          "57079633": 7,
│ │ │ │ │          "571": [7, 35],
│ │ │ │ │          "572": 35,
│ │ │ │ │          "573": 35,
│ │ │ │ │          "574": 35,
│ │ │ │ │          "575": 35,
│ │ │ │ │          "5757": 17,
│ │ │ │ │ @@ -2024,31 +2032,32 @@
│ │ │ │ │          "6848e": 12,
│ │ │ │ │          "685": 35,
│ │ │ │ │          "687": 35,
│ │ │ │ │          "6875": 7,
│ │ │ │ │          "688": 35,
│ │ │ │ │          "689": 35,
│ │ │ │ │          "69": 16,
│ │ │ │ │ -        "693": 35,
│ │ │ │ │ +        "693": [7, 35],
│ │ │ │ │          "694": 35,
│ │ │ │ │          "6952": 16,
│ │ │ │ │          "696": 35,
│ │ │ │ │          "699": 35,
│ │ │ │ │          "69977011": 20,
│ │ │ │ │ -        "7": [1, 2, 4, 5, 6, 7, 8, 10, 13, 14, 15, 16, 17, 20, 21, 22, 26, 28, 29, 30],
│ │ │ │ │ +        "7": [1, 2, 4, 5, 7, 8, 10, 14, 15, 16, 17, 20, 21, 26, 28, 29, 30],
│ │ │ │ │          "70": 22,
│ │ │ │ │          "700": [5, 27, 35],
│ │ │ │ │          "70062332": 10,
│ │ │ │ │          "70099": 8,
│ │ │ │ │ -        "701": [12, 35],
│ │ │ │ │ +        "701": 35,
│ │ │ │ │          "702": 35,
│ │ │ │ │          "7056": 23,
│ │ │ │ │          "706": 35,
│ │ │ │ │          "707": 35,
│ │ │ │ │          "7087": 24,
│ │ │ │ │ +        "71": 13,
│ │ │ │ │          "710": 35,
│ │ │ │ │          "711": 35,
│ │ │ │ │          "712": 35,
│ │ │ │ │          "713": 35,
│ │ │ │ │          "7144": 16,
│ │ │ │ │          "718": 35,
│ │ │ │ │          "7182818": 3,
│ │ │ │ │ @@ -2066,14 +2075,15 @@
│ │ │ │ │          "7281": 22,
│ │ │ │ │          "729": 35,
│ │ │ │ │          "73": [9, 16, 22],
│ │ │ │ │          "730": 35,
│ │ │ │ │          "732": 35,
│ │ │ │ │          "73300589": 22,
│ │ │ │ │          "737": 35,
│ │ │ │ │ +        "738": 8,
│ │ │ │ │          "739": 35,
│ │ │ │ │          "74": 7,
│ │ │ │ │          "740": 35,
│ │ │ │ │          "745": 35,
│ │ │ │ │          "746": 1,
│ │ │ │ │          "747": 35,
│ │ │ │ │          "7475": 23,
│ │ │ │ │ @@ -2086,42 +2096,39 @@
│ │ │ │ │          "753": 35,
│ │ │ │ │          "7533": 5,
│ │ │ │ │          "754": 35,
│ │ │ │ │          "7542": 5,
│ │ │ │ │          "755": 35,
│ │ │ │ │          "7550": 11,
│ │ │ │ │          "756": 35,
│ │ │ │ │ -        "757": [5, 35],
│ │ │ │ │ +        "757": 35,
│ │ │ │ │          "758": 35,
│ │ │ │ │          "759": 35,
│ │ │ │ │          "76": [7, 11, 17],
│ │ │ │ │          "7603": 23,
│ │ │ │ │ -        "761": 35,
│ │ │ │ │ +        "761": [6, 35],
│ │ │ │ │          "76279753": 11,
│ │ │ │ │          "76281241": 11,
│ │ │ │ │          "768": 35,
│ │ │ │ │          "769692": 8,
│ │ │ │ │          "77": 7,
│ │ │ │ │          "770": 35,
│ │ │ │ │          "771": 35,
│ │ │ │ │ -        "773": 23,
│ │ │ │ │          "77327762": 20,
│ │ │ │ │          "777": 35,
│ │ │ │ │          "777681": 8,
│ │ │ │ │          "78": 14,
│ │ │ │ │ -        "780": 19,
│ │ │ │ │          "780924": 7,
│ │ │ │ │ -        "782": 24,
│ │ │ │ │          "7825": 24,
│ │ │ │ │          "78539816": 7,
│ │ │ │ │          "7855": 7,
│ │ │ │ │          "787": 35,
│ │ │ │ │          "788": 35,
│ │ │ │ │          "7899571": 24,
│ │ │ │ │ -        "79": [7, 17],
│ │ │ │ │ +        "79": [7, 13, 17],
│ │ │ │ │          "790": 35,
│ │ │ │ │          "7909094": 23,
│ │ │ │ │          "794": 35,
│ │ │ │ │          "795": 35,
│ │ │ │ │          "7955e": 23,
│ │ │ │ │          "7961792": 11,
│ │ │ │ │          "798": 35,
│ │ │ │ │ @@ -2141,26 +2148,25 @@
│ │ │ │ │          "8125": 7,
│ │ │ │ │          "813": 35,
│ │ │ │ │          "815": 35,
│ │ │ │ │          "816": 35,
│ │ │ │ │          "8188": 23,
│ │ │ │ │          "82": 7,
│ │ │ │ │          "820": 35,
│ │ │ │ │ -        "821": [21, 35],
│ │ │ │ │ +        "821": 35,
│ │ │ │ │          "824": 13,
│ │ │ │ │          "8241": 18,
│ │ │ │ │          "826": 35,
│ │ │ │ │          "830": 35,
│ │ │ │ │          "8319533": 15,
│ │ │ │ │          "832": 35,
│ │ │ │ │          "83231374": 20,
│ │ │ │ │          "8332836": 22,
│ │ │ │ │          "837": 35,
│ │ │ │ │          "83703275": 16,
│ │ │ │ │ -        "838": 13,
│ │ │ │ │          "839": 35,
│ │ │ │ │          "84": [16, 28],
│ │ │ │ │          "840": 35,
│ │ │ │ │          "841": 35,
│ │ │ │ │          "842": 35,
│ │ │ │ │          "844": 35,
│ │ │ │ │          "844705": 23,
│ │ │ │ │ @@ -2172,15 +2178,15 @@
│ │ │ │ │          "852": 35,
│ │ │ │ │          "853": 35,
│ │ │ │ │          "855": 35,
│ │ │ │ │          "856": 35,
│ │ │ │ │          "8570e": 12,
│ │ │ │ │          "859": 35,
│ │ │ │ │          "85940121": 22,
│ │ │ │ │ -        "86": [7, 13],
│ │ │ │ │ +        "86": 7,
│ │ │ │ │          "860": 35,
│ │ │ │ │          "864": 35,
│ │ │ │ │          "865": 35,
│ │ │ │ │          "8653514": 7,
│ │ │ │ │          "866": 35,
│ │ │ │ │          "8662": 16,
│ │ │ │ │          "87": [7, 22, 28],
│ │ │ │ │ @@ -2192,14 +2198,15 @@
│ │ │ │ │          "87508800": 22,
│ │ │ │ │          "8758308": 22,
│ │ │ │ │          "87992": 22,
│ │ │ │ │          "883": 35,
│ │ │ │ │          "884": 35,
│ │ │ │ │          "888": 35,
│ │ │ │ │          "888888": 32,
│ │ │ │ │ +        "89": 13,
│ │ │ │ │          "8904759": 17,
│ │ │ │ │          "892": 35,
│ │ │ │ │          "8923637137222027": 7,
│ │ │ │ │          "89285089": 5,
│ │ │ │ │          "893": 35,
│ │ │ │ │          "894": 35,
│ │ │ │ │          "89425": 8,
│ │ │ │ │ @@ -2231,15 +2238,14 @@
│ │ │ │ │          "92065227": 5,
│ │ │ │ │          "921": 35,
│ │ │ │ │          "923": 35,
│ │ │ │ │          "92503564": 5,
│ │ │ │ │          "92657076": 15,
│ │ │ │ │          "927": 35,
│ │ │ │ │          "928": 35,
│ │ │ │ │ -        "93": 13,
│ │ │ │ │          "9311": 5,
│ │ │ │ │          "93162": 22,
│ │ │ │ │          "932": 35,
│ │ │ │ │          "9320": 5,
│ │ │ │ │          "933": 35,
│ │ │ │ │          "934": 35,
│ │ │ │ │          "935": 7,
│ │ │ │ │ @@ -2247,15 +2253,14 @@
│ │ │ │ │          "937": 35,
│ │ │ │ │          "94": 7,
│ │ │ │ │          "940": 35,
│ │ │ │ │          "94011531": 23,
│ │ │ │ │          "940764": 22,
│ │ │ │ │          "941": 35,
│ │ │ │ │          "9426e": 14,
│ │ │ │ │ -        "945": 7,
│ │ │ │ │          "948": 7,
│ │ │ │ │          "949": 35,
│ │ │ │ │          "95": [2, 8, 9],
│ │ │ │ │          "950": 35,
│ │ │ │ │          "951": 35,
│ │ │ │ │          "952": 35,
│ │ │ │ │          "952483": 7,
│ │ │ │ │ @@ -2274,15 +2279,14 @@
│ │ │ │ │          "96333168": 11,
│ │ │ │ │          "967": 35,
│ │ │ │ │          "97": [7, 9, 16, 20, 22],
│ │ │ │ │          "970": 35,
│ │ │ │ │          "97268236": 5,
│ │ │ │ │          "973": 35,
│ │ │ │ │          "97313427": 20,
│ │ │ │ │ -        "975": 16,
│ │ │ │ │          "976": 7,
│ │ │ │ │          "9760872": 20,
│ │ │ │ │          "97663118": 5,
│ │ │ │ │          "97868751": 6,
│ │ │ │ │          "98": 7,
│ │ │ │ │          "982": 35,
│ │ │ │ │          "98224427": 20,