prepare data

.idea/workspace.xml

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source/backend/calc.py

@@ -1,2 +1,25 @@
-def g():
-    print("f")
+import numpy as np
+
+
+def prepare_data(freq, re, im):
+    """the function takes raw data and gives vectors of eq (8)"""
+    fl = freq[re.index(max(re))]
+    # fl is the frequency of loaded resonance
+    f0 = fl
+    # f0 is the frequency of unloaded resonance
+    e1, e2, e3, gamma, p = [], [], [], [], []
+    for i in range(0, len(freq)):
+        # filling vectors
+        t = 2*(freq[i] - fl)/f0
+        g = re[i] + im[i] * j
+        e1.append(t)
+        e2.append(1)
+        e3.append(-t*g)
+        gamma.append(g)
+        p.append(1/(1 + t**2*(1 + re[i]**2 + im[i]**2)))
+    data = np.array([e1, e2, e3, gamma, p], dtype=complex)
+    return data
+
+def scalar_product ():
+    pass
+

source/other/article_research/notebook.ipynb

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+{
+ "cells": [],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  },
+  "pycharm": {
+   "stem_cell": {
+    "cell_type": "raw",
+    "source": [
+     "\n",
+     "\n"
+    ],
+    "metadata": {
+     "collapsed": false
+    }
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}