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@ -116,6 +116,7 @@ |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"m.fixed[\"c\"] = True\n", |
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"m.migrad()" |
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] |
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}, |
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@ -154,13 +155,6 @@ |
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"m.covariance" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"Copy covariance information to numpy arrays" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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@ -192,7 +186,7 @@ |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"m.draw_mncontour('a', 'b')" |
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"m.draw_mncontour('a', 'b', cl=[1,2,3,4])" |
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] |
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}, |
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{ |
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@ -209,6 +203,9 @@ |
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"outputs": [], |
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"source": [ |
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"print(m.values,m.errors)\n", |
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"print (m.merrors['a'])\n", |
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"print (m.merrors['a'].lower)\n", |
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"print (m.merrors['a'].upper)\n", |
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"a_fit = m.values[\"a\"]\n", |
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"b_fit = m.values[\"b\"]\n", |
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"c_fit = m.values[\"c\"]" |
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@ -251,20 +248,13 @@ |
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"plt.xlim(-0.1, 4.1)\n", |
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"plt.show()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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} |
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], |
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"metadata": { |
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"kernelspec": { |
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"display_name": "Python 3 (ipykernel)", |
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"display_name": "Python [conda env:ML]", |
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"language": "python", |
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"name": "python3" |
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"name": "conda-env-ML-py" |
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}, |
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"language_info": { |
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"codemirror_mode": { |
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@ -276,7 +266,7 @@ |
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"name": "python", |
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"nbconvert_exporter": "python", |
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"pygments_lexer": "ipython3", |
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"version": "3.8.16" |
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"version": "3.10.9" |
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} |
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}, |
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"nbformat": 4, |
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