diff --git a/notebooks/annotation_analysis.ipynb b/notebooks/annotation_analysis.ipynb
deleted file mode 100644
index 28e4f3a..0000000
--- a/notebooks/annotation_analysis.ipynb
+++ /dev/null
@@ -1,87 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import common\n",
-    "import matplotlib.pyplot as plt\n",
-    "import glob\n",
-    "import numpy\n",
-    "\n",
-    "paths = []\n",
-    "for csv_path in glob.glob('outs/*.csv'):\n",
-    "    _, p = common.import_csv_data(csv_path)\n",
-    "    paths.append(p)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1440x2160 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(20, 30))\n",
-    "for path in paths:\n",
-    "    plt.plot(path[0], path[1])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/bezier.py b/notebooks/bezier.py
deleted file mode 100644
index 4f05a2c..0000000
--- a/notebooks/bezier.py
+++ /dev/null
@@ -1,18 +0,0 @@
-from __future__ import print_function
-from numpy import *
-
-
-# evaluates cubic bezier at t, return point
-def q(ctrlPoly, t):
-    return (1.0-t)**3 * ctrlPoly[0] + 3*(1.0-t)**2 * t * ctrlPoly[1] + 3*(1.0-t)* t**2 * ctrlPoly[2] + t**3 * ctrlPoly[3]
-
-
-# evaluates cubic bezier first derivative at t, return point
-def qprime(ctrlPoly, t):
-    return 3*(1.0-t)**2 * (ctrlPoly[1]-ctrlPoly[0]) + 6*(1.0-t) * t * (ctrlPoly[2]-ctrlPoly[1]) + 3*t**2 * (ctrlPoly[3]-ctrlPoly[2])
-
-
-# evaluates cubic bezier second derivative at t, return point
-def qprimeprime(ctrlPoly, t):
-    return 6*(1.0-t) * (ctrlPoly[2]-2*ctrlPoly[1]+ctrlPoly[0]) + 6*(t) * (ctrlPoly[3]-2*ctrlPoly[2]+ctrlPoly[1])
-
diff --git a/notebooks/common.py b/notebooks/common.py
deleted file mode 100644
index 541d3ba..0000000
--- a/notebooks/common.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import numpy as np
-import csv
-import matplotlib.pyplot as plt
-
-def import_csv_data(filename):
-    stylus_x = []
-    stylus_y = []
-    stylus_pressure = []
-    time = []
-    with open(filename) as csv_fp:
-        reader = csv.reader(csv_fp)
-        next(reader) # skip header
-        for row in reader:
-            for i, v in enumerate([stylus_x, stylus_y]): #, stylus_pressure, time]):
-                v.append(float(row[i]))
-    stylus_pos = np.array([stylus_x, stylus_y])
-    time = np.array(time)
-    return time, stylus_pos
\ No newline at end of file
diff --git a/notebooks/entries_per_sec.txt b/notebooks/entries_per_sec.txt
deleted file mode 100644
index a53209d..0000000
--- a/notebooks/entries_per_sec.txt
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-(1821361778-1820009777)*10**-6 = 1.352001 (seconds)
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diff --git a/notebooks/fast_data.csv b/notebooks/fast_data.csv
deleted file mode 100644
index 14b7764..0000000
--- a/notebooks/fast_data.csv
+++ /dev/null
@@ -1,217 +0,0 @@
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diff --git a/notebooks/fitCurves.py b/notebooks/fitCurves.py
deleted file mode 100644
index 19bf0fc..0000000
--- a/notebooks/fitCurves.py
+++ /dev/null
@@ -1,162 +0,0 @@
-""" Python implementation of
-    Algorithm for Automatically Fitting Digitized Curves
-    by Philip J. Schneider
-    "Graphics Gems", Academic Press, 1990
-"""
-from __future__ import print_function
-from numpy import *
-import bezier
-
-
-# Fit one (ore more) Bezier curves to a set of points
-def fitCurve(points, maxError):
-    leftTangent = normalize(points[1] - points[0])
-    rightTangent = normalize(points[-2] - points[-1])
-    return fitCubic(points, leftTangent, rightTangent, maxError)
-
-
-def fitCubic(points, leftTangent, rightTangent, error):
-    # Use heuristic if region only has two points in it
-    if (len(points) == 2):
-        dist = linalg.norm(points[0] - points[1]) / 3.0
-        bezCurve = [points[0], points[0] + leftTangent * dist, points[1] + rightTangent * dist, points[1]]
-        return [bezCurve]
-
-    # Parameterize points, and attempt to fit curve
-    u = chordLengthParameterize(points)
-    bezCurve = generateBezier(points, u, leftTangent, rightTangent)
-    # Find max deviation of points to fitted curve
-    maxError, splitPoint = computeMaxError(points, bezCurve, u)
-    if maxError < error:
-        return [bezCurve]
-
-    # If error not too large, try some reparameterization and iteration
-    if maxError < error**2:
-        for i in range(20):
-            uPrime = reparameterize(bezCurve, points, u)
-            bezCurve = generateBezier(points, uPrime, leftTangent, rightTangent)
-            maxError, splitPoint = computeMaxError(points, bezCurve, uPrime)
-            if maxError < error:
-                return [bezCurve]
-            u = uPrime
-
-    # Fitting failed -- split at max error point and fit recursively
-    beziers = []
-    centerTangent = normalize(points[splitPoint-1] - points[splitPoint+1])
-    beziers += fitCubic(points[:splitPoint+1], leftTangent, centerTangent, error)
-    beziers += fitCubic(points[splitPoint:], -centerTangent, rightTangent, error)
-
-    return beziers
-
-
-def generateBezier(points, parameters, leftTangent, rightTangent):
-    bezCurve = [points[0], None, None, points[-1]]
-
-    # compute the A's
-    A = zeros((len(parameters), 2, 2))
-    for i, u in enumerate(parameters):
-        A[i][0] = leftTangent  * 3*(1-u)**2 * u
-        A[i][1] = rightTangent * 3*(1-u)    * u**2
-
-    # Create the C and X matrices
-    C = zeros((2, 2))
-    X = zeros(2)
-
-    for i, (point, u) in enumerate(zip(points, parameters)):
-        C[0][0] += dot(A[i][0], A[i][0])
-        C[0][1] += dot(A[i][0], A[i][1])
-        C[1][0] += dot(A[i][0], A[i][1])
-        C[1][1] += dot(A[i][1], A[i][1])
-
-        tmp = point - bezier.q([points[0], points[0], points[-1], points[-1]], u)
-
-        X[0] += dot(A[i][0], tmp)
-        X[1] += dot(A[i][1], tmp)
-
-    # Compute the determinants of C and X
-    det_C0_C1 = C[0][0] * C[1][1] - C[1][0] * C[0][1]
-    det_C0_X  = C[0][0] * X[1] - C[1][0] * X[0]
-    det_X_C1  = X[0] * C[1][1] - X[1] * C[0][1]
-
-    # Finally, derive alpha values
-    alpha_l = 0.0 if det_C0_C1 == 0 else det_X_C1 / det_C0_C1
-    alpha_r = 0.0 if det_C0_C1 == 0 else det_C0_X / det_C0_C1
-
-    # If alpha negative, use the Wu/Barsky heuristic (see text) */
-    # (if alpha is 0, you get coincident control points that lead to
-    # divide by zero in any subsequent NewtonRaphsonRootFind() call. */
-    segLength = linalg.norm(points[0] - points[-1])
-    epsilon = 1.0e-6 * segLength
-    if alpha_l < epsilon or alpha_r < epsilon:
-        # fall back on standard (probably inaccurate) formula, and subdivide further if needed.
-        bezCurve[1] = bezCurve[0] + leftTangent * (segLength / 3.0)
-        bezCurve[2] = bezCurve[3] + rightTangent * (segLength / 3.0)
-
-    else:
-        # First and last control points of the Bezier curve are
-        # positioned exactly at the first and last data points
-        # Control points 1 and 2 are positioned an alpha distance out
-        # on the tangent vectors, left and right, respectively
-        bezCurve[1] = bezCurve[0] + leftTangent * alpha_l
-        bezCurve[2] = bezCurve[3] + rightTangent * alpha_r
-
-    return bezCurve
-
-
-def reparameterize(bezier, points, parameters):
-    return [newtonRaphsonRootFind(bezier, point, u) for point, u in zip(points, parameters)]
-
-
-def newtonRaphsonRootFind(bez, point, u):
-    """
-       Newton's root finding algorithm calculates f(x)=0 by reiterating
-       x_n+1 = x_n - f(x_n)/f'(x_n)
-
-       We are trying to find curve parameter u for some point p that minimizes
-       the distance from that point to the curve. Distance point to curve is d=q(u)-p.
-       At minimum distance the point is perpendicular to the curve.
-       We are solving
-       f = q(u)-p * q'(u) = 0
-       with
-       f' = q'(u) * q'(u) + q(u)-p * q''(u)
-
-       gives
-       u_n+1 = u_n - |q(u_n)-p * q'(u_n)| / |q'(u_n)**2 + q(u_n)-p * q''(u_n)|
-    """
-    d = bezier.q(bez, u)-point
-    numerator = (d * bezier.qprime(bez, u)).sum()
-    denominator = (bezier.qprime(bez, u)**2 + d * bezier.qprimeprime(bez, u)).sum()
-
-    if denominator == 0.0:
-        return u
-    else:
-        return u - numerator/denominator
-
-
-def chordLengthParameterize(points):
-    u = [0.0]
-    for i in range(1, len(points)):
-        u.append(u[i-1] + linalg.norm(points[i] - points[i-1]))
-
-    for i, _ in enumerate(u):
-        u[i] = u[i] / u[-1]
-
-    return u
-
-
-def computeMaxError(points, bez, parameters):
-    maxDist = 0.0
-    splitPoint = len(points)/2
-    for i, (point, u) in enumerate(zip(points, parameters)):
-        dist = linalg.norm(bezier.q(bez, u)-point)**2
-        if dist > maxDist:
-            maxDist = dist
-            splitPoint = i
-
-    return maxDist, splitPoint
-
-
-def normalize(v):
-    return v / linalg.norm(v)
-
-
diff --git a/notebooks/frequency_analysis.ipynb b/notebooks/frequency_analysis.ipynb
deleted file mode 100644
index 64708a0..0000000
--- a/notebooks/frequency_analysis.ipynb
+++ /dev/null
@@ -1,136 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import common\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from scipy import fft\n",
-    "\n",
-    "time, pos = common.import_csv_data('fast_data.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Average time delta [s] = 0.007605088372093023\n",
-      "Min time delta [s] = 0.0009239999999999999\n",
-      "Estimated sampling frequency [Hz] = 131.49091122589894\n",
-      "Frequency upper bound [Hz] 1082.2510822510824\n"
-     ]
-    }
-   ],
-   "source": [
-    "time_deltas = (time[1:] - time[:-1])*1e-6\n",
-    "print('Average time delta [s] =', np.mean(time_deltas))\n",
-    "print('Min time delta [s] =', np.min(time_deltas))\n",
-    "print('Estimated sampling frequency [Hz] =', 1/np.mean(time_deltas))\n",
-    "print('Frequency upper bound [Hz]', 1/np.min(time_deltas))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f912f709710>]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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BosqgBTADKSKkiHSlhtKWyK3VdZFDZ6LKoAV4ngGQJtKBprQlDREbUu+1M1Fl0AJcZqTIhIlUGShtiG5Up6gyaAEuM1IpQjpFanUpbUloozrtox2JKoMW4DKQIuicgdK2SCNFd9btTFQZtADHZaSJkCK1upT2JPTSmSqDjkSVwQJjrSwiQipFanUpbYmGiRRVBguMHVjpFOlqIqVtCYeJFrEgyqKhymCBsWMsRZ53oEaX0o6oZ6CoMlhg7FJSbzWRruFW2hPdtVRRZbDA2IGVNm8gq9WltCOqDBRVBguMHWS6HYXSzoS3sF7EgiiLhiqDBcafM0gRUim1upT2RDeqU2ZVBkR0ExENEdEzIu2TRHSIiLaZv8vFbx8jogEi2kNEbxfpl5q0ASK6TqSfTUSPmvTvEVFuPh9wsXF9z8ALFelAU9oRJ7QdhfbRTmQunsG3AVwak/4lZr7Q/G0CACI6H8A7AVxgrvkqEaWJKA3gKwAuA3A+gHeZcwHgcyavVwEYBXDVyTxQu+HPGaR0zkBpXxz1DDqeWZUBM/8cwMgc87sCwO3MXGXmFwAMAHiL+Rtg5n3MXANwO4AriIgAvBXA9831NwN4x8t8hrbGaXrpbJELpCgxuDpn0PGczJzBB4louwkjLTNpawAcEOccNGlJ6SsAjDFzI5IeCxFdTURbiWjr8PDwSRS9dVjhr9tRKO1M+Etn2kc7kRNVBjcAOAfAhQCOAPjCvJVoBpj5RmbeyMwb+/v7W3HLk8YRcwYpnTNQ2hRdWqpkTuQiZh60x0T0dQD3mP8eArBOnLrWpCEh/TiApUSUMd6BPP+0QL50pspAaVdCbyBrH+1ITsgzIKLV4r9/BMCuNLobwDuJKE9EZwM4F8BjAB4HcK5ZOZSDN8l8N3u7tj0I4E/M9VcCuOtEytSu2I+GpMh8z0DHmdKGhD2DRSyIsmjM6hkQ0W0AfhfASiI6COATAH6XiC4EwABeBPB+AGDmnUR0B4BdABoArmFmx+TzQQD3AkgDuImZd5pbXAvgdiL6DICnAHxz3p6uDQhWE0HnDJS2xdU5g45nVmXAzO+KSU4U2Mz8WQCfjUnfBGBTTPo+eKuNTkusy50yq4naPUw0Vq7hi5ufw8cvfy26sunFLo7SInSjOkXfQF5gWCqDU2DO4FfPH8ctj+zHs0cnF7soSgtxdQK541FlsMA4cs6AKPTh8XZkYroOAGjoYvOOQl86U1QZLDByzoCo/VdqTFQ8ZVB32rucyvwS3o5i8cqhLB6qDBYYG38ls5qo3T97OTHtvf/XaHcXRplXXGakyDvWOYPORJXBAhN+A7n99yaynkFDPYOOouEwsmlPHOhqos5ElcEC468mSsGsJlrkAs2CP2fQ7gVV5hWXGTmrDLTpOxJVBguMG1pN1P6TcxMVEybSCeSOwnEZmbQXJ2r3eS1lYVBlsMC44ktnp8L3DCbtBLKahx2Fw4x0ikCEtp/XUhYGVQYLjJWp3kCjtt8e2J9AbveCKvOK63rKIH0KzGspC4MqgwUmWE3kLS9td6tLJ5A7E8flYJFDm/dRZWFQZbDAWOF/yqwmmrZhIvUMOgmH2f9Ot+qCzkSVwQLjyC2s23xvoobjolRzAOha805Dw0SKKoMFxo6rYG+ixS3PTExWGv6xvoHcWTREmKidDRZl4VBlsMAEq4mAdJsvLZXKQCeQOwvXDxORvnTWoagyWGCCvYnaf87ATh4D+tJZpxFMIOt7Bp2KKoMFxhHvGaRS1NaTc3byGADq6hl0FI7rzWvp1/g6F1UGC0x4zqC9J2ZDnoHOGXQULrP5Gp+GiToVVQYLjCv2Jkq3+Woi+8IZoGGiTsNxGelUSieQOxhVBguMK94zoDYfaGHPQMNEnYTLjDR5Bos2fWcy6zeQlZMj9D2DNl9aOlFpgAgo5jLqGXQYjhvsTdTOBouycMzqGRDRTUQ0RETPiLTlRLSZiPaaf5eZdCKi64logIi2E9GbxDVXmvP3EtGVIv3NRLTDXHM9EdF8P+Ri4n/PIHUKzBlM11HMZ5DLpHQCucNouOxtptjmoUxl4ZhLmOjbAC6NpF0H4H5mPhfA/eb/AHAZgHPN39UAbgA85QHgEwAuAvAWAJ+wCsSc8z5xXfRebcfhsWkcHa/M6VxHvGeQ9Aby7iMTODw2DcALz8zn/kUTlXpTfiOlGm5/7KXYc/u6ssikaV4mkO/bNYhH9x0/6XxmY3Bibm1xKlOpOwuav76BrMyqDJj55wBGIslXALjZHN8M4B0i/Rb22AJgKRGtBvB2AJuZeYSZRwFsBnCp+a2PmbewJ7FuEXktCLc88iLu2X4YAPDgniEMTVTAzLh1y35MVuqoNhzc9thLcF3G0EQFdz55sCmP//X9p/FXP9wBAHjk+eM4OFoGANy17RBGSzUwM/594BiYOfI9g2Clxu4jE3hi/ygA4L/f9hT+6Wd74LqM//CPD+COrQdC96s2HPzbU4eahHqp2sDxqSoAT/D++8AxAMBjL4xgcKKCiUodF332fty7cxAjpRqu+vbjGCnVcM/2w7juzh0YmqjgqZdG8a1/fwGAN4Hc151FJpUK7U204+A4StUGXJdx22MvoVJ3UKo28K9b9oOZMTA0hZt+6eXx3Udfwmfu2QUA+Py9e/C1h58HAHzqR7vwq4FjcF3G5376LI6OVzBaquF/fm+bv222ZbJS9+tU8rOdR7Hn6CQcl/Hfb3sKT700in3DU7j4H+7HE/tHsf3gGP7TFx/GZKWOwYkKHtozBAAYn65jeLIa1x18XjhWgusymBnPHp1o+v2xF0bwr1v2AwA+dud2/O1dnqP88HPD2H+8lJhv3XHxzKFxAMD+4yX8ZMcRUzfP4iN3PA0AePDZIf+cH28/giPj02g4Lv7hJ7sxUqrhyZdG8Wuf/BmOjE9j5+Fx/P2m3WBmbDsw5vflgaFJvHjMK8fTB8ZwzPSL3UcmUGu4GCvX8IHvPIGxcg2Hx6bxxc3PgZmx4+A4bt2yP7KFdfgZpqoNX0GMlWsAvD23XjD3Ozw2jR897ZVjx8FxPPDsIADgxWMlHBn3jJwHnh302/SR54+jUncwNFnBe7/1GMbKNYxP13HvzqMAgONTVew+4rXBrsMTft1Ivvf4SxicqMBxGTf98gVU6g6YGYeMUXVobNqv66cPjOFB0xeGJisYL3v97Yubn8O2A2NgZtyx9QBKVW8BhXzW+3YNNt37keeP+0bO8akqKnUHDcfF1bdsxbYDYwCAJ18aBTOH2v/gaBn37/by23N0Ek++5I3/p14a9evygWcHMTTpPdc/3/ccxso1TFbquP7+vQs+j3eiE8irmPmIOT4KYJU5XgNASrKDJm2m9IMx6bEQ0dVEtJWItg4PD59Qwb+z5SX86OnDcF3G+27eilu37Me+YyX8zb89g5/tHMTPnzuGj925A88cHscPnjyE/3nH06GJVQA4PlXDsZI3KK757pP4+s/34fhUFR+6fRvu2nYITx8cx3/+xqN49IURsZqIkEmTv83DP927B5+42xMoY+Uaxst1lOsOhiareOFYWBA++OwQPvy9bXj26CReOFbCN36xD4AnbN/9zccAAF+67zl89aEBAMBVNz9uylTDdN3BwdEyth8cw/1G6Ng3jaeqDfzgyYP43E+fNf+vo5hPI5sOrMNqw8H/fcOvcNtjL2HXkQl87M4deGjPEO7bPYi//rdnsHdoCj986iA+dc8uVBsOHtwzhJ884w3qUq2BUs0bpN/+1QvYvHsQL42UccNDz+O+3YN4Yv8o7nzqEHYcGsfjL47gz7++BXXHxZcfGMA7b9zS1HYf/+Ez+MYv9mGsXMOPnj6MXz1/HEfHK2AGjoxP45lDExgYmsLhsQpufWQ/3nfLVjAzPvWjXXj/rVsBAN9/4iAefs7rOz96+jAOjJQxOFHB277wEO7bPYgt+0Zw6T//AnsHJ0P3vv2xl/DFzc8BALYfHPcH+P/43jZ8/Rf74LqMT9z1DAaGJjE4UcF/+uLDODBSxqYdR/CHX/4lhia9Mn3oe9sAAE8fGMe2A54w+OSPduKGh59HreHig7c9idsfO4A9g5P4l4f34aE9Q3jxWAk1x8WR8Qo27xrEjT/fh1LNwbf+/QV85p7dAIBrf7ADnzZK+L3fegz/8vDzGC3V8Af/55f40dOHse3AGDbtOIqnD47jZzuP4vr79+LIeAV3bD2Av//xbrgiTCQ9g7rj4rc/9wC+/8QBHBqbxps/cx8ef3EEDz03jLd+4SEcGpvG7Y8fwP9z+1OoNVx87eHn8cm7vXJ8+Hvb8Kkfeccf+M6TuOWR/RicqOBdX9+CTTuOYPuBcTy0Zxi7Dk/gh08exPtvfQIjpRq+/OAA3vstr19/dtMuPw/L+HQd1/5gB+588hC2HxzDp+7ZhZ8/N4z7dw/hd/73gxiaqOC7j+7HB297Cq7L+MqDA76B8v5bn8Cn7tkFx2Vcf/9ebNpxBC8eL+P//f52/PSZo9h5eByv/Zuf4uBoGd9/4iD+6y1bm4yVz9/7LL5g+sKffO0RXH//Xhwv1fCzXYPYsu84njk0jj/+6q/w+IujQftPVHDLI/vxl995EsyMz9+7B3/9Q2/8f/T/expf2vwcGo6L/3rzVnz30Zewd2gS/3zfXjzw7BB+/twxfHHzc9h5uNlImU9OejWRsehb4lcy843MvJGZN/b3959QHoV8GuWag1KtgYbLmJiuh4SjbfjJSgNTVe/YWgyWqWoD5WoDzN714yKPyUoDIyXPKhsp1VCpe9q8K5NCIZdBzXFRd1xMVOr+Us5S1StP2dynXAvfb9y8DDYxXcdd2w7hMz/ejVK14YWrTIhkqtpAqerAcRmTlQbGp+t+uUtVB2WzAV251vDzL9cclKsOKnUXjsso1xwU8hmkU0GYqFR1UHNcjJRqoWeUx6Wql/d0zUG51kBJ5l9roNpw4TJQrjqYEs/on1d18PiLI/jV88dxfKqGwYlKrCU/Wan7z+k/s32uquM/V6nmPX/dYUwbC3Rwwsvvyw/sxa2PvAjHZXzo9qdw22MvYXiyCpe9cNPQpFef0fuXag2/Pss1B6Wq47f/xHQDw1NV3PzIfjzw7BCeG5zEwNAUdh+ZwPBkFczAaMkre63hotZwvT5kyj5VaWCq4rULM0K/lWqO/4yVmoNpEy4qVb3y2DocLdcwWq7BdRmj5TpGy3WMlGtwXMbwVDVof1FnNo/puoO6w8Fb8sI1KFcdjJbrODjqhUYdl3FgpOwr4eHJKqYqXrnLtQYmqw2/jUdKNYyUaqg1XFTqLiYrdYwaz2KkVPPLXqo5/hf2Jit1/zrb98enw8LY5j9VrYvjBo6MT8NxGUOTVUxMe97MdN3rc/a8oYkqhiYr/r3DY76OF4ziPTAy7d9XbtNir5kyaYfGpnFkvBL0jWrD98qOTVVxbKoGZmDEWPi1houa43r9xtx33ByXqg5c9jz0YOyK44hcmG9OVBkMmhAPzL9DJv0QgHXivLUmbab0tTHpC0Yhn2kabGVR2SXRuazQiSoDT8h5QrLhMkq1QMhN1cLCyqYX8hkU8t7iLU8oesLLdtiyGPT2eotfjlrQCUtGmE75ncYL3UiBGAgv+VxO6LkCwe3lVchlkE0HE8hR4TPTsfe8noKxv3mCM6ibsnhG+Vyheq85qDbckFvccFxUG64RjsHACz9voBh8QVMNCwN7XKo14LJVZoFQmhLH0Ta3ZbL15rd/KH8nNHhDbSfqTLaJfX75u680q4GRMF13UBGCfMrUPTObdnBQrgulX3Wa8ivVnNDz2nqarNb9UKYMR1YaNj8H07WZ+4I1kkK/JfQ9q1Cb8/PS6w6j1nBDBoQlfK58luZ+XTL9qRwZk+VqoBxj60aM/6hxVjJjt+54il2eWxLPNRV5rqmq6PtNYyE6FoP8gr6wsPNGJ6oM7gZgVwRdCeAukf4es6roYgDjJpx0L4BLiGiZmTi+BMC95rcJIrrYrCJ6j8hrQSjkMqEOFh2EvqVZCzekJBjMYaEHGEEUyTubJuQzKRRyaQBWKHq/JQnb6P0AM5hq4UFTa3ieRiB4gw4WKLywYvA9g7r0GLwBU8invQlkEyqYrsXcWwy8sujUZaNYa46LSt0TnmXplVTjy4MGOwgAACAASURBVBFSDNX4eo9as345hHAp1wKhFBVWVmj6yiAisGZrAykwrDHgC9taI9Lmsg2kApDne3k0HM9qjgqRshQu5rrpeuAZ2DK4DL+erTC295aGQrkaUw5xPDHdQCbVHCayE9eewdIs1KeqUog5IUVuDSqpvJMs3qBvResy+M3vCyEjJ65fRPuIlwcz+0pSKu+woogzUCLjvxYxemqRPpTQn8qRZ7dzMdN1p0mxhdurNZ7BrO8ZENFtAH4XwEoiOghvVdA/AriDiK4CsB/An5nTNwG4HMAAgDKAvwAAZh4hok8DeNyc9ylmtpPSH4C3YqkbwE/M34LRk083DTapoVNmZWtY8AaNYC1UFulRi2Iq0uiFfAZEJDwDL926zkAwuL38Ip1fDF7rsoYsskrDd4fjOqVnKUurpFlx2Wt7chlvAtlY5TK8JAdeteH69SStbnu+DbOEB0pQp1NVB4UZ6sxeu6Qn698/eK7mkFfUsooK3oYJg1XqricoRWhQCjby2z/iDUa8qbqTCgnbqZh2CT9XWDjbMOXYdD2Ur63zOKU0XXMwXbf1HtxnsuJdm05Tk/cRrbOohzLl51H3lz/LxUQ2zDkdCVHV/P4R9aa944mK10dKkfqVCrvbGEfliDEQ9W6j26lLg0cqmrCXLPKrNvzwS93hUDnKtfCY6c6mg/YSeYfv30A2nfJ/t16+V+aId1GL6QtmLq3WcP39wKLtIsdrXYRsHZeRImAhVuDPqgyY+V0JP70t5lwGcE1CPjcBuCkmfSuA181WjvmimM8kDohSteErg7LoxKWag4efG8buIxP484teAQCoNVw/pigbPRQLNgKgkMv497bn2HtaoWnnMeyx6zK+9vPn8V8uXh9rTcmBNzxl8whbRNJyCVmowrKSVqKnuLwJZDtnMF1rHshRYeAPLCHwbNx0OhSWiHoGQX3Icsv2ePDZITguY8PKHr9uytVgEIY8gxjXWgqMQTG/MhVTplD71xp45tA4vvPofnz2Ha/3zz9uYsDVhuvHfGUfCuUdtQyFkLNlDdo/GioL6slSqQehGqmcj5eq/pxMKaYOpmS9R+ZWbDlcjv8AU0WEnWRfsO0/FTEubN527iWq5KZEe8Va8lHjou6A2RtvuUzKTw+uC8ZabFhMHNsyNXsUgeDtzjaPk6lqAwdGyjgyXsGF65ai7jDqTmAAeIpoZs81anRGx27UY5P9pu6k/ONv/GIfPn/vHmz/5CXoyc3vO8Mdtx1FjwkThd33eItMHt/55EH8y8PPhyw1K/DC4Y/mPKwS6DGW0GSl4VtcUhjIzrz76AT+90/34P7dgxEF0Nzhh8zkaN3xJg/9e4eeS7q0YkCac46XanAZ/gSyDRWURVhChkqmqoFgmIpROva5Gi5jTJYpZtDYkFnQHkHeX3lwAP/nwYHY5w7NGUQGU1wIx062h63VSDhFWHsPPDuE2x47gNFyrUnIee1fC9olJjQgBaUUXOPlui9MbT3Jto2GKP0J+rqD6brMO9z+Ncf1J2iThEu4D4Xj8WlC0zbrQZjITRRWMu9onyzX470mOfkfKquop2OTNX+Za6nawH/+xhZ87eHnwx6P7EMhg0woPJP3kPVWo3MNMYojVE81rx9+8LtPxo5/qThKkeeKMwwmK3W/TIN+n3TCSq4WfzxZaYAB34OZTzpuO4piPm0GjXTPZJgA5jg8kL3Z/0aoMwzFDOSoZThV9axtAH6YSK5UsXnUHcbYtDeQyzXHX2k0MR0WNJPSavI7eSCghkICL0bhJViGtkx2Anmq4Z1TiRuwVW9VTDTvsXLNd2mtxSPzDg88B9KDihMo5ZqDiUrdn6T1yywm/32FV4/EpmPK5Asok2/0uaaqDaRSgWdo+4JcMRVqO1HXsg/FC83gGWV72fwqdelphCdDbTmma27sJO5QTH+SCkWGCcOKJmg7wGxhHdk/q9KwYSIxv1UL2r8snneyUveNHFsOZiE0IyEZaxxFvUFfyYl6mqo2sO2lMSzryeGis5eLeooT6oECHSnV/fkvm1/Ncf3wnOwrpVoDXdXACpfhzZFSDWPlekh52vyifVb25XKMULdGBBD0yem644eAo/OO0jOoNlz0dmUWJ0x0umFdK98ij0yuGVnQNGgmK95kj2zIUIhHWChSuExVHSzp9uLeVhnIwTscc1yuNXzBMGmWnHn5BfcZLdX8Tm6XTcq8mz0AYb1bS1MIU3vvnlwaGbG0NPwswcCr+vHjYOANyXJMxDxXtRESSlOizuI8hqlqAxPTDX/FFmCEph3I4lmkUJKCQZZDvqkcpzTLtQbSpgOUag3Y9+6Ol2q+JR9qu6lAydm5n9AcSi3egh6KaS9ZT+GwWQMEr0yeZ+CVY8R4cl4e4rkmA0szdlVLqC8Ex4C3mWIqBYj3DUMTyNNCedcazZ6VNADCZYq3yHtCbRdTT6JuJip1lGqOt2Q6ZmGE9AZl35LlCI8TuSQ7yCOfCRRUdPzbJdZ+HhNy/MeFnaLhoxjjLbH9gzay47xU89qgt2thxHbHKYOiL5BFZxDWhbUMwzHywJKU21DIUMiI755H3L1qA2uWdgGA7yHEDV6ZX6kaWAkTlfhJqMHJeCEXsjTF5FRIKNWsu9ocrirmM8jELC2Nhr+kZxA3eEOegRCa9t2NqWoDxZjnOi6EnFWK0jMI5RdpOynUrcCQZToq6unoRDDw5MoSEgsI7NLWkBKJaS953BRCkXMupi4Thaa5j5yvKgthXak7vnAeCim2ZiXsWZqi/WvNgne8XPPbEQi+xtfgIK0SWb1knyvkGcYpuZjjUkTp92Sl4LXzH0H7y3q3405651EPKryQYW5lkvMYpaqDrqzsk4FAtuPfvlHtlS8Y/354LjQvFvFW4soUIwvkyjjpGZSNUurrymIh6Dhl0OMLZK9Bqg1XvPwlPYOw62qF8xGpDEKDutmqs5Z8dAI5zmqWx9N1x3/tfyL08phQBjEKwCuHjGlL70dMZFWThVJPPuNNILvNE8hyIFthMFkJwgdxzxI9PjYZhMLilifK5xovB7HVOIus+WU673isXPfLJ/OLO44Kb7/9q8GKqSMxBoBXZzECrxofJz42VfXj30ntH3h1gdKUSnC6FljnSQol1C9iY9rNk5cW+6Uz+dJZNWk1UUOsaqrN3P62fKGQUbXhL7UOh4bi6/ewaYPJ6SBU43mGMnxoQ4P1IFyZMDbCc1rB3E9XNgjJSIEcKIN4wyDkkcm5i5j2T+xDwquXYSfrpU8ZI1E9g3nCj9vHhTFEmGBiOoh/lmqOb2UfFZZBqPNPBHlErRV7z+5sGkQzuIkxykXGq8emAyGX1MnjQhByolgOvGMxg7eQSyOTSvlWsRUA0WVwthzHYjyAaPqxGMEVDs8ECkqW/0jIkm8eeNP14M1VOReSNNikV2ePXfasUVumlD9nFCg52eZDMW0OhFcqSWMgCFfMLJSi59hwZKnqBHMG4j2DRIs3VkFFvdXmPAD5zY0gzb505oWJAiHn98M5KKVYL6HawJSYM/ANlIn4+rUbOY5P10U4KBxnt5Z8kieX1AZynmXKzBlMirBjudbwDcawMoj3fmJXMiV4A3HP6ynNQEHl0qmgHJU61i3vwULQccogGiYCgEERMrJhAinAbLwSCHeGYzGdq+4IS6MSXk1ERCjkMrGdCAgLhsAtrsdazeEOP7MwkJNTMtYcp3wK+Yw3Z+CG5wzkM5arjm81z0XIJVm//vxHOYjJD042C2wgeRAeE9ZUEJONv7eMGQ/GKFDZ/jK/wwmegaw/m181suQ4+t7FTOWLtTRrDdipwpAySLQu45Wm3D4kLg8AZtdShD57OVuYaDYrN/m5gjmD8bKck4kX5EeMMpio1P1VQ0AwTqUSHkwytmYpX6nqIJ+xK5mC373tV7w2tUopKT9mb/mxzS8IV8aXaTDhef1+XW2gkQm8FQ0TzSN2BUOc0PQ8gXrT74PSokwMzzRbiXb9d1G4dYV8OtaVj+bnKwMRJkoabIkxbZG33d30WML9bB0UcpnQFtZy62TfW6k2/DmFJK9kNmXgiHmWJCtXKoAjYwnWuRUGISHXHIefqaxSkLN9CbAqvcEkazBpctI7HinV/GWaQwnKO1FZCQvavvsghXCS0BxMaoOY9pfXAUYZNL2B7N3P7qcEeIK3EfdcibHwmdt/LgrFKuS6wxEjLPCgbfsPJnlNiSFD7xxvlVEtthy2SkJ9IdEDCca/3/5J4zXJqxNevR1rNkKxUGGijnvPwFrp0uKdFgLPdn75+5GY8AIAf5ln9Hybh41b2jAR4Alb+zuA0AReVRwf9RVKsDRSnmvX7sv7RY/l+dZCkW9zyg24bB305NPIpFNouMFLZdFnrDVcP/4p71dNeBa5YkWWyV4rz5VL95I8A5mHP5EZU//RdPns8j6yLmUs3NbP0YR7Jz2X3Phw1nPFOXHP5XLwPWo5bzKXNp+oNOcd108t3hbW8S+dyfvXHQ7W/88yjqL3LMfUQynh9/AYnBbHlaZz5L1lHcj0pD4S1yfn0g+T8rPHSXUg02X55Dny/rbfTlW8dyn6VBnMD/KtPblUd6bjqCVv5xWiyOsy4pxiPnhBRCoGS1x+VhnYe2cS7mlJJZQ/6bKk9GI+g2wq2Gp7OiIw5lJnM6VF05PqEggPwsGJSuJzzWXJtb3PXNqOKBK6Mm1gz0nNoX6TmK3OZnouu2IlLr+5lCPpnCCPmPcMRPtLZRQtX9zxXPrKXMsdne+ZS/vPds5c2pFo5n4okX1rrrIlqWzR9BR5socZ6OtemDBRxymDohDGKwo5cZxPSM+FvgfMDCzpziKb9lpKammZR39vcFwQCsiGqQBgmdl3Z2UxuN9yc29rrVihLPOz18myLuvJ+R06VP5iwnUivdfUSYqAfCbleQZ2All4Bk15z1J/y3uC35fGlDn67NHnqsldS10O30OUX95neSH++AxTf/3iuiXd8n750LH0Imz723LbT4NGyyGfJbme5PPatgvKsbIYLodktBTeylme432UiJrusTyhL8S1XToF7z2DmAlkoFkZJI8ZL122S2J9yHaMOSeXSaGYz4Tao+a4MzzLzM+bVNcrZ8gv2g+L+Qzypv3D+c2l/Zv7bWJ7Rfq7DTlpmGie6MqmfKHZ39vlp5/RKwV5V+yxpSeX9j0MKaRlHmf0BdfJOQO5NUVvl1UG4t7FsACIy29Vnyyfd77cIjtU/qIsX5AeumefySPnvdmYSRHqYgJZvvqeVDf22YmAFWZQLOnJ+ishZDnC1838XKE66I2vJ3muHJD2/HSK/EG2rJDzheaZoTrNxx5LbLkL+Yy/LFKWSZb/jIRjm0dPLu33hVAf6ovvTz25tC+UrCCS5xRysv0T+mRvfJ359RT5Gh8QDhM1XPYNh+b8mtuurzvrl3W2ftN0bOqsmM+EDDg/j6T+1Necd4oCIbuimPfHf6iu++LrJm78y7o+I6Evz/a8+UzKt/BXFmdvL3m8UBPIHacM7IoeINr5Zm8Eaw0WQ8JAdkQhGMR1sjMXfGWQ8b2Evq5g0Mg8pOsaN1AyKfKty55cetbn6k8QBnZg2bJlxJfOpuvOyxIuPdlAyBVyGX9nyrnUb5IAte73yqTyz3Lck0v7z9abz/jKeU5tng6GiFU0ScbAqhhBlHRcyAftXxTHSf0pzorNpAjLClk/D9snk5RqkjKwxzO9Z+DfO/S8zXl3ZVO+5VrIB31hLkIurqyFfNB2MgwTd++kY2koyeOQITKLQgGCUK1Xprn361UxSqeYz/h59HVlfYNrLoZBryqD+cO+eDaXDiqP1yzt9q7PpdFjOtTyQs7vpElCODSBnLcCQAjNfNoXBtLiWb2k2z+WHerMvuZOLjtXkqeRZEH7QtNcn0ml4JjvAU/XnFhrO+m4R5TJU1DNz5XU4a0CzaVTWGqspt6ujB/O6e2SQjPhGWM8IWldFvKB0lyV4G3J47OWBpZ8IOQyoh2DMiV5F3ECryAUlKcYMjNet0K0wUop5HLiuWI9g3jLNc5L9D0DoQzkBCcQrt84pROq61xmDmOtuUzZNPlhRWmF27aIXtefIHht+Qo5UU9zMJpWJZT1LDP+i6Lel/UEnmZSOeL6qmzzHqFc5qK8NUw0j9jOtTKpUya4j6uXNIcJPOHSbNVJSyPkGeSEAAh5Cc0D2SqfaH5hIRdsgudbv0Jozta5pHdhy2bnQ+xnI0Nu7CyutRSO8hmXdGd9zypJkPuDVwi2vq6s3/mLop6SPB5r1REBK3tzTXVT7Mr67RG22OKtwTXLuoNnyQkhJ45jLc2+5v6Uy6R8xSY9Qy9k1Kw0ZX4yfryyYNtLGhTh9rdv0ia1lz0uCCWXStkwkX8aKnXHbzdg9hBUTy5ihZt6WipChnF1EypTkyXv1c26ZT3x18V4Z5kUYant10LYyvyWFXKxIeOk8gXGYJKnEa8o7XEunfKVXE9C2yUpbJmfTiDPI3J7iEJsGKM55l7MZ0IhGV+r5wJL6IwYqwQIewZWOBZyUpAHnXVJTzARaAWRzLsrKwVK4KFIi7eYj1cucaGhnpCFajwDM2gbrrdt8Ypizl/ZENdZu7JB/FOGq7qFZ9CTEGfvjxl4Utn2dmX8GGlPPl5oxnlCPdm0H9+WQrOYT/thor6ubCA0E8JVVgCEBW/QXj3Cw0ucM7BzDaKupXUpFYqMs4fDRHJiNFBy1vL28gi8lbmGZ3qE8s74H7cJzxnIieCQl2iFnFByYUMpKEePKN9soZVCTl4X9KflhVysZxivlNJhQ0mO+XzzcVwoBwj6U3c2Ha53+4xy7meWMKE0cuS9C0KeLBNKMzlMpJ7BvBFy8WcYNN3ZYJK3rysThAlExy7k40NGdlKWCP6GXN49xXVCofSEBLl3jvQM5ISatEqkSx4WUM3eSjhM1Cx47YCxyqjuMCo1B93ZYDAlDV6ZRyCg0v6cgezwcVa4ZzUFq3WkcOzrblZyS3tyweR0XBhGWvLCgwoJg65MrCBfFVIGnjUatuTD7WXrfbmYnI4LNci67smHw0SFXHObJoaJioEgT8oj3hiID+vImHzcS2fLCs0hRVk+OY7CCi8YG7Lt4jxUb+FBIDTlfEpR9gU7HkNKs1kJh4VtNHQZFzKa2cjp6874x3IuJORpCEMubgK5R4SrpHEk+2dPPj60JvNTZTCP+A0itHpcKERagL1d2cD6jQjycOzXxI99azDj74Rqz/HyyMR2KJlfyDMITYYJwZaTecQJzaCDnuF3ynRocPSIMgGBMmg4Lsp1x3hCMVZdrFufFvWbCR3b510h3HNpNfkDQrRLX1cGvflsUx5euZNDYYWm+p1ZMcTN/WRSFJnwk88o2ivG6gyHBoIwXFhAScUQPHvcc8VNIEthFhVQsZPT5lnymVTgbQnvLUUxXzprOFheCMISSRP0YSs8qJtiyEAJFLkNRcqFB72hNmpuuyXd2cADycUrzZCRI+sjps17Iorc9slVMW3e2xUoorChkUZPzBj0Q4MiNBT2StKRviDS41Yqiraz22zPN52pDEJCMxD2dkb/DKnJfask479TEB1s0iqOhoxsZ/PvbQVHLuxq9ghrJeoZpCjo5NJS8oR6vKcRJxiCwRtvldh/bZhouu59c7VbusLFQMgt6Y4Jm0UHSl4eN7vtZ/jzBGFL3p7b1yU9g3R4UEcGTbopThwXJop4UzEemZ1L6hPCp0coAM/7iRPCzSGjcLw6IvRjwkTRyUmroOT689AEcpzCS4hH9ycISukZRL+BXK27fp0CwTs2cml0MdLmcRPjxXw0pBW2yMOhl0gIJaYv9OSblWZ3Nu2P0Z6QoZRGMSSwY7xEWU+hcRIYJfbehYjyC/en8Iou2SfCSj88BkMGlHjefMZbCm/fRViolURAB+5NBAQCOuxme52YwbEWgPQMCrkM6g1vxERj7nLisyub8v8f3Ft2jGaXUZbpjL48smlCVyZ+cEdDRnYZoBSa1m2fqDRECEWGbzIhJQIEE8h2W4XurHD9zeR0PpMKDaqiGLyyw9sQWZOCyqcxVWv4MWiZRzQ0ECzpi7fqVhalhRo8S0j5xNSZDBPZa13zUpHX5pnQCiLpQdk5lKgg972fomdpNgleKZTEBHJcmMgaGo7LoTfn5QSyzaOYz/gWvSyrNVCGJ6uRpbbh/gEEXzqLfvZySXcWRN4Ll12mL2TTqaa6s/cLQkPh9oiu6JqsNPwQVNS7lIsQrJG2RISJpNJc2u2FDMPtHJ407hFljQsZ2WeoO64IBwnB3B32DDJpNyiHUPC+p2lWGTUbjnFjNyhrXBi41nDFeFg4kX1SngERvUhEO4hoGxFtNWnLiWgzEe01/y4z6URE1xPRABFtJ6I3iXyuNOfvJaIrT+6RZidokPBgsp1UCtJQuKJLdqhmt9haBtk0+W9Oypd0vPPjPAphQQvPwFtJkzVhKW/76/Ayyfi4aFRo9uTSSJH3DJkURUJbYcEAeEtLAfgbtXXn5OBM+zHz0D2kAhADLBDI4TwKeU9R5DPppoEslbBnkQVholCd+YraWz0j2y6xnqLCNjIIZXv2ydBASODJ0IAYyF1efrlMCln7TMK6LETqvSehHaPpPUIgZtMUEVZCmAlBU4zUe08uja6s1zej4UXbLsEW1mFl0J1Nh5S6VTBS2UrhXRR9IeQVReZZCrkg35CHlYtvu3DcXva/NGyYMXY8RJRmXHjWtn94Yj9s3Nl7h73zSHg2n0GK4BuCUU8+GCfpkMKWY0b2F+sByXDVQjEfaub3mPmY+P91AO5n5n8kouvM/68FcBmAc83fRQBuAHARES0H8AkAGwEwgCeI6G5mHp2HssXSE9OQtpMzA9l0CrlMKtTJo5aBfT0+7BlkQp1UHlvC7qC8d3MM2ltJ48052JflooNAuqtVs3WAzK+YCzo4EfnCrifmfjbfTMQzsFZTJkXIpVMo5j0h7g/kXPNAt88aN39g03vycjDL68JzNbY8UatJCl7rCYQGnlDSVil7AjteSRTynmeQSafMG6IRz0B4b9YziNZfU9hAhgakN5gQqpNzJ91Z7xm8UJ2noLuy0f4W5GFluFSmvkIR7RDqs0LwplNeqCj0BnLDRVc2he5cxtt22rRNNp0Ktae0+sOLIcKCzdafLVcqRX7ILM6Tk4o3OmfQk4u0f0LopdnQiPGKjXKqOxmkU+QL85Ai6grqMJ1y/Oct5MLj0R9rpg/GGSLhNg8bKEE/8/LKpl0/XLRQm9QBCxMmugLA75rjmwE8BE8ZXAHgFmZmAFuIaCkRrTbnbmbmEQAgos0ALgVw2wKUDUAQG7daO+cL/3TgauestSEEs1g+abeVbXb3gk64YUUhNAnsnSPd2OYBZC3GFHmdta876w/ydct7sH55T2DNiM5czKdRbTS7oN3RgWY6Z1yMN5hANp6B2c7ZCqBC3uvkPbkM8llvD6Ng0IQ7sD2OxomJAiEXtgTTkYESDEJbHpl3ITL4rUVlB03YAkzjvNW9OH91H157Zh+qZlJ8RTEXav++rgxsZXteXTg0KNvOLgko5DNY1dflK9zerkg4JJ8JCcdEb1AKePNcqRSZ0AWjKxsoiDhlW8xnwKLvRq3sYqT9QyEUk0eKwm8g1x0XjsvoyqRDymhJdxaZVArpFPkhRGlgxbWjPLZvqYeUWnSeI0aQe2GioG7jQotBn4zUU0jZhtsnmybkM+mQkSe9FyDsGRTyad9AiS4KiHsHoTvbrHyi3qVUlMV8JuRdZhuub8gt1FYUwMkrAwbwMyJiAP/CzDcCWMXMR8zvRwGsMsdrABwQ1x40aUnpTRDR1QCuBoBXvOIVJ1zo887sw5ql3VhZzOO8M3vx2rP6AAAXrlvqbx17Tn8R5/QX0duVwYYVPXjt6j6c01/Ea1b14oKzlmDbgTEAXud/VX8Ra5Z2ozubxu+8uh9rjQL4+ns2Nu2GeNbSLpy/ug+vX7vUH7xn9nX5nbU7l/YVTypF+PUNy/0Y7g/+8jeQNZO7r15VxAVr+vCaVb148/pleN2aJRgt1fGaVb1Ys6wbr17Vi1euLPhKzp9s7etCf28+5BnY+La/iiYdfO3NOyeN88/q8zcqO+/MXv9FpF9buxTnr+7D8kLO1FUh7ApnAyXxmjM9gZxKEVYv6fKt62svOw+rl3ShO5vGH79pDX773H6sXdaDlcUczjuzD13ZNDas6MGGFQWcf1YfXnVGEcWuDFYWc/7EqrUUiQirl3TjzCXec65Z2o3zzuzD6iXd2PSh3wYAvL3vTDz68ZXo7crizeuX+buSfvSS1/jbab9+7RK8bk0flnRnsaKQw4aVBZy1tBvpFGHdsh4cMt9XKOYzePdvrMfbLzgT6RThfb/9Sn9//D/duA7LzSTweWf24txVvTijrwuFXBqv7C/6BkVPLoPfPGcl/q/Xr8aKQg6/de5Kv7+cuaQLDYd9gdKd84Tx0p4s1q/owTlnFPHqVUWcv7oPhXwGf/m7Zbyyv4iVRtF1ZVP4wzes9rdeXlHMY0XBi7GvXtKF9St6sHpJF3pyaaxb3oOB4Sl/AtnuS9SVTaMnG3hcf/sHF/htd/5ZfXjNmUUs78lhaU8W5/QXcN6Zvdi4fplff2uWeu1x3pl9uOAsr/1/7zVn+N9WWFHIYWUxj+5sGhvXL8OF65bgFct78Mp+r703rCjg45efhwvOWgLA++JfMZ/B+hUF/7l+be0SP4Ty0UtegzetX4aVxTz6ujI454wCzl5ZRD6TwoYVBeQzaaxd1o3+3jw2rl+GYfP9gff+hw3+G9cXnb0CF65bimI+g7OWdOHVq3rxmlW9uOx1Z+LXNyzH4EQFvfkM1izrxuvXeH2lO5vGBWf1+cbbu39jPZb443gZXr92CVYv6cI5/QW8bs0SrCjmsaovj1f2F1FruDij12ub/r68P9n/B7+22v+2yNkrC3hlfwELBjOf8B+ANebfMwA8DeB3AIxFzhk1/94D4LdEooPgwgAACZ9JREFU+v3wQkMfBfDXIv1vAHx0tnu/+c1v5oXEdV12XTfx9/3HSnzVtx/ncrVxUvd56XiJmZmfH5rkv//xLnZdlweGJvm+XUdPKl/JfbuO8u2P7Wdm5qPj0zxaqrLruvzmT2/mb/5iHzMz7x2cYMfxnvf+3Ud5/bX38PX3Pcfrr72HH3/h+JzuM11rsOu6XK42+JN3P8OTlTr/cu8wv+Hv7uWJ6Vro3PHpGh+fqp7Ucw1PVvj5oUlmZr7uB9v57zft8tOnayfXLpJKveH3hbGy9xyTlTp/65f7ZuwjSTQcr2+NlWr8kTu28WSlnnjuWLnGY+UaHx4r8/pr7+G3f+lhZvbq2rZXHFOVOu8dnGxKf/HYFA+OTzflYf/93E928zkf+zEzMw9NVHj9tffwLb96ga/48i95/bX38Ggpuc3sc71c9h8r8fBk5WVfV284s7bzbOO4HZmYrvlyQVJrONyYoc3nCoCtHCNTT8ozYOZD5t8hIvohgLcAGCSi1cx8xISBhszphwCsE5evNWmHEISVbPpDJ1Ou+YCSNhk3vGJFD75x5caTvo/9nukr+4v42OWvBRB4JfPF2167yj+WL1Td/5H/6LvBrzqj10+3YRn74RW78mg2uoT1+ok/vAAA8JuvWoltf3tJ07nz4e6uLOb9lUT/8MevD6XPJ3Jd9xIxifje3zz7hPKzy0WX9GTxT3/6hhnPtfdjY27aOrb/JlHIZ/CqM5r70PoVgWUp87Dvwsi9iaxnkM+mfc9kpvvO9G2KmXjFihP7pm8mncJsS+5nG8ftSK9ZOBIlm17YNwFOOHciKhBRrz0GcAmAZwDcDcCuCLoSwF3m+G4A7zGrii4GMM5eOOleAJcQ0TKz8ugSk6YsMEu6s/47BZJgAtmsJppF8CgLj5wzWEi8l8485WMXJHSZOR77vQvl9ORkPINVAH5oNG8GwHeZ+adE9DiAO4joKgD7AfyZOX8TgMsBDAAoA/gLAGDmESL6NIDHzXmfYjOZrCwO1gKZmLariRZuBYMyN/KZlLe1yRy9tBMlbSxpl4OvnHVlUv5ChFPR0lbmxgmPcmbeB6DJx2Xm4wDeFpPOAK5JyOsmADedaFmU+cW6+xPqGbQNRN7Kna4FVgY20uMyhyaQe7uCFTnK6YmafEoTWTNncHyq5r3otoBrm5W5051No2uB9qWx2LkDx+XAM8im8d/+4zn4wzectaD3VhYXHeVKE3bOYGiyiqXd2ROeGFTml//x+6/Ga87snf3EkyBlwkDMcmlpCutXFEKTz8rphyoDpQm7N9HxUhWvXKkCoF34LxevX/B72PUEDjMqYgJZOf3RpQFKE3ZpKXN4t0zl9Md6Bo7rffIU0DmjTkGVgdKEDAupMugsgjARo2Lexs5nVUx0AtrKShPy5Zblhfl9gUtpb9JyArmmYaJOQpWB0oSdQAYQ+sqVcvoTLC0FBicq6MqmmrZhV05PVBkoTdilpYB6Bp2GXVrqMuPw+DTOWtqtL5p1CKoMlCakZ7BC5ww6irSYQD40Ou1/elU5/VFloDQhlcEyVQYdRYoCz+DQmCqDTkKVgdJERoSJ1DPoLGyYaLrm4NhUTZVBB6HKQGkinSL/4yW6tLSzsBPIB0e9j/ecpcqgY1BloMRiJ5FVGXQWdmnpgdEyADR9tlU5fdE1Y0osmTQhk07rGvMOw84ZHBgxykA9g45BlYESSyZF/gfAlc4hUAbTIPK+wax0BhomUmLJpFM6edyB2JfPD4yWsaq3a8E/tai0D9rSSiyZFOmy0g6ERJhI5ws6C1UGSiwri3ls0P3rOw770tlEpYF1qgw6Cp0zUGK59aq3oHuBP7GotB8bNyzDn1/0CqxZ2o0rLtQvm3USqgyUWFYUdU+iTmRpTw5//0evX+xiKItA24SJiOhSItpDRANEdN1il0dRFKWTaAtlQERpAF8BcBmA8wG8i4jOX9xSKYqidA5toQwAvAXAADPvY+YagNsBXLHIZVIURekY2kUZrAFwQPz/oEkLQURXE9FWIto6PDzcssIpiqKc7rSLMpgTzHwjM29k5o39/f2LXRxFUZTThnZRBocArBP/X2vSFEVRlBbQLsrgcQDnEtHZRJQD8E4Ady9ymRRFUTqGtnjPgJkbRPRBAPcCSAO4iZl3LnKxFEVROgZi5sUuwwlBRMMA9p/g5SsBHJvH4pxOaN0ko3WTjNZNMu1WN+uZuWnS9ZRVBicDEW1l5o2LXY52ROsmGa2bZLRukjlV6qZd5gwURVGURUSVgaIoitKxyuDGxS5AG6N1k4zWTTJaN8mcEnXTkXMGiqIoSphO9QwURVEUgSoDRVEUpbOUgX4zoRkiepGIdhDRNiLaatKWE9FmItpr/l222OVsBUR0ExENEdEzIi22LsjjetOXthPRmxav5AtPQt18kogOmb6zjYguF799zNTNHiJ6++KUujUQ0ToiepCIdhHRTiL6kEk/pfpOxygD/WbCjPweM18o1kJfB+B+Zj4XwP3m/53AtwFcGklLqovLAJxr/q4GcEOLyrhYfBvNdQMAXzJ950Jm3gQAZly9E8AF5pqvmvF3utIA8BFmPh/AxQCuMXVwSvWdjlEG0G8mvByuAHCzOb4ZwDsWsSwtg5l/DmAkkpxUF1cAuIU9tgBYSkSrW1PS1pNQN0lcAeB2Zq4y8wsABuCNv9MSZj7CzE+a40kAu+FtwX9K9Z1OUgZz+mZCB8IAfkZETxDR1SZtFTMfMcdHAaxanKK1BUl1of3J44Mm1HGTCCd2bN0Q0QYAbwTwKE6xvtNJykCJ57eY+U3wXNdriOh35I/srT3W9cfQuojhBgDnALgQwBEAX1jc4iwuRFQE8AMAH2bmCfnbqdB3OkkZ6DcTYmDmQ+bfIQA/hOfOD1q31fw7tHglXHSS6qLj+xMzDzKzw8wugK8jCAV1XN0QURaeIvgOM99pkk+pvtNJykC/mRCBiApE1GuPAVwC4Bl49XKlOe1KAHctTgnbgqS6uBvAe8zKkIsBjIuQQEcQiXP/Eby+A3h1804iyhPR2fAmSh9rdflaBRERgG8C2M3MXxQ/nVp9h5k75g/A5QCeA/A8gL9a7PIs9h+AVwJ42vzttHUCYAW81Q97AdwHYPlil7VF9XEbvHBHHV4c96qkugBA8FanPQ9gB4CNi13+RaibW82zb4cn4FaL8//K1M0eAJctdvkXuG5+C14IaDuAbebv8lOt7+h2FIqiKEpHhYkURVGUBFQZKIqiKKoMFEVRFFUGiqIoClQZKIqiKFBloCiKokCVgaIoigLg/wc4MdZaLM/diQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(time_deltas)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f912b796890>]"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "x_ft = fft.fft(pos[0])\n",
-    "freqs = np.linspace(0, )\n",
-    "plt.plot(np.abs(x_ft)/len(pos[0]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/outs/out.0.csv b/notebooks/outs/out.0.csv
deleted file mode 100644
index be6bf4d..0000000
--- a/notebooks/outs/out.0.csv
+++ /dev/null
@@ -1,11 +0,0 @@
-coord_x,coord_y
-54.7409,336.133
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-54.6441,337.052
-54.6925,337.197
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diff --git a/notebooks/outs/out.1.csv b/notebooks/outs/out.1.csv
deleted file mode 100644
index 5432dc6..0000000
--- a/notebooks/outs/out.1.csv
+++ /dev/null
@@ -1,17 +0,0 @@
-coord_x,coord_y
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-129.756,375.164
-130.168,375.285
-130.579,375.454
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diff --git a/notebooks/outs/out.10.csv b/notebooks/outs/out.10.csv
deleted file mode 100644
index 7f26e7a..0000000
--- a/notebooks/outs/out.10.csv
+++ /dev/null
@@ -1,12 +0,0 @@
-coord_x,coord_y
-49.2962,365.485
-49.0059,365.823
-48.9333,366.114
-48.8849,366.307
-48.8849,366.404
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diff --git a/notebooks/outs/out.100.csv b/notebooks/outs/out.100.csv
deleted file mode 100644
index cdb8a87..0000000
--- a/notebooks/outs/out.100.csv
+++ /dev/null
@@ -1,32 +0,0 @@
-coord_x,coord_y
-22.8714,262.763
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-23.065,263.15
-23.2586,263.344
-23.4522,263.44
-23.5732,263.489
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diff --git a/notebooks/outs/out.101.csv b/notebooks/outs/out.101.csv
deleted file mode 100644
index 3855d74..0000000
--- a/notebooks/outs/out.101.csv
+++ /dev/null
@@ -1,34 +0,0 @@
-coord_x,coord_y
-78.8427,264.311
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-78.1893,261.384
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-78.8911,261.166
-79.3267,260.996
-79.5929,260.875
-79.8348,260.633
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8.9664 356.41142 440.6281 Tm&#10;[&#40;z&#41;] TJ&#10;ET&#10;BT&#10;/T1_9 1 Tf&#10;5.9776 0 0 5.9776 361.132 439.631 Tm&#10;[&#40;i&#41;] TJ&#10;ET&#10;BT&#10;/T1_10 1 Tf&#10;8.9664 0 0 8.9664 364.293 440.6281 Tm&#10;[&#40;&#92;&#41;&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;8.9664 0 0 8.9664 367.87956 440.6281 Tm&#10;[&#40;.&#41;-378&#40;&#141;PCA&#41;58&#40;&#142;&#41;-249&#40;stands&#41;-249&#40;f&#41;27&#40;or&#41;-249&#40;&#141;principal&#41;-249&#40;com&#41;13&#40;ponents&#41;] TJ&#10;ET&#10;BT&#10;8.9664 0 0 8.9664 130.78104 429.67116 Tm&#10;[&#40;analy&#41;22&#40;sis&#41;10&#40;&#142;.&#41;-403&#40;&#141;ICA&#41;58&#40;&#142;&#41;-325&#40;stands&#41;-325&#40;f&#41;27&#40;or&#41;-325&#40;&#141;indepedendent&#41;-325&#40;com&#41;13&#40;ponents&#41;-325&#40;analy&#41;22&#40;sis&#41;10&#40;&#142;.&#41;] TJ&#10;ET&#10;1 0 0 1 163.121 311.567 cm&#10;0 0 0 1 K&#10;0.2 w&#10;1 j&#10;0 0 m&#10;130.673 0 l&#10;S&#10;0 0 m&#10;0 103.096 l&#10;S&#10;1 0 0 1 12.569 0 cm&#10;0 0 m&#10;0 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307.922 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;q&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 202.817 307.922 Tm&#10;[&#40;3&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 215.762 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -215.762 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 213.675 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -215.762 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 215.352 307.922 Tm&#10;[&#40;.4&#41;] TJ&#10;ET&#10;1 0 0 1 229.111 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -229.111 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 227.024 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -229.111 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 228.701 307.922 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;q&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 229.54 307.922 Tm&#10;[&#40;5&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 242.46 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -242.46 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 240.373 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -242.46 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 242.05 307.922 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;q&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 242.889 307.922 Tm&#10;[&#40;6&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 255.834 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -255.834 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 253.747 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -255.834 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 255.424 307.922 Tm&#10;[&#40;.7&#41;] TJ&#10;ET&#10;1 0 0 1 269.183 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -269.183 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 267.096 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -269.183 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 268.773 307.922 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;q&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 269.612 307.922 Tm&#10;[&#40;8&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 282.532 311.567 cm&#10;0 0 m&#10;0 1.308 l&#10;S&#10;q&#10;1 0 0 1 -282.532 -311.567 cm&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 280.445 307.922 Tm&#10;[&#40;0&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 -282.532 -311.567 cm&#10;BT&#10;3.0167 0 0 3.0167 282.122 307.922 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;q&#10;158.068 307.897 136.983 107.797 re&#10;W&#10;n&#10;BT&#10;3.0167 0 0 3.0167 282.961 307.922 Tm&#10;[&#40;9&#41;] TJ&#10;ET&#10;Q&#10;1 0 0 1 163.121 315.389 cm&#10;0 0 m&#10;1.282 0 l&#10;S&#10;1 0 0 1 -163.121 -315.389 cm&#10;BT&#10;3.0167 0 0 3.0167 158.068 314.282 Tm&#10;[&#40;0.2&#41;] 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c&#10;17.748 -8.648 l&#10;17.999 -9 l&#10;22.365 -15.433 27.616 -26.232 26.874 -34.089 c&#10;26.773 -34.743 l&#10;26.622 -35.371 l&#10;26.622 -35.396 l&#10;26.396 -36.025 l&#10;22.717 -43.898 11.537 -30.928 9.301 -27.326 c&#10;9.075 -27.025 l&#10;8.874 -26.723 l&#10;4.413 -20.209 -0.65 -9.9 -0.302 -1.911 c&#10;-0.227 -1.282 l&#10;-0.126 -0.629 l&#10;0 0 l&#10;S&#10;1 0 0 1 2.966 -3.52 cm&#10;0 0 m&#10;0.126 0.327 l&#10;0.427 0.905 l&#10;0.453 0.956 l&#10;3.921 5.459 11.699 -3.848 13.525 -6.611 c&#10;13.626 -6.762 l&#10;13.953 -7.24 l&#10;17.392 -12.293 21.424 -20.539 21.016 -26.723 c&#10;20.941 -27.351 l&#10;20.79 -28.005 l&#10;20.69 -28.331 l&#10;20.589 -28.658 l&#10;17.679 -34.468 9.399 -25.012 7.542 -22.223 c&#10;7.19 -21.72 l&#10;7.09 -21.569 l&#10;3.451 -16.407 -0.682 -8.016 -0.327 -1.609 c&#10;-0.251 -0.98 l&#10;-0.1 -0.326 l&#10;0 0 l&#10;S&#10;1 0 0 1 3.369 -4.072 cm&#10;0 0 m&#10;0.352 0.528 l&#10;0.427 0.628 l&#10;2.735 2.615 6.814 -1.883 8.044 -3.419 c&#10;8.472 -3.947 l&#10;8.472 -3.972 l&#10;10.206 -6.242 11.559 -8.646 12.695 -11.263 c&#10;12.871 -11.715 l&#10;13.097 -12.343 l&#10;13.122 -12.343 l&#10;13.349 -12.997 l&#10;13.525 -13.575 l&#10;16.346 -22.894 11.393 -23.335 6.335 -17.271 c&#10;5.983 -16.843 l&#10;5.933 -16.768 l&#10;2.908 -13.144 -1.116 -5.459 -0.252 -0.754 c&#10;-0.05 -0.126 l&#10;0 0 l&#10;S&#10;1 0 0 1 5.933 -8.07 cm&#10;0 0 m&#10;0.402 -0.075 l&#10;0.829 -0.352 l&#10;0.905 -0.402 l&#10;1.257 -0.83 l&#10;1.433 -1.056 l&#10;1.684 -1.433 l&#10;1.835 -1.709 l&#10;2.111 -2.262 l&#10;2.136 -2.338 l&#10;2.338 -2.991 l&#10;2.388 -3.645 l&#10;2.111 -4.047 l&#10;1.684 -3.972 l&#10;1.257 -3.695 l&#10;1.206 -3.645 l&#10;0.829 -3.218 l&#10;0.678 -2.991 l&#10;0.402 -2.614 l&#10;0.276 -2.338 l&#10;0 -1.785 l&#10;-0.0509999 -1.709 l&#10;-0.227 -1.056 l&#10;-0.277 -0.402 l&#10;0 0 l&#10;S&#10;1 0 0 1 -264.13 -373.108 cm&#10;/CS0 cs&#10;1 scn&#10;BT&#10;/T1_1 1 Tf&#10;7.9701 0 0 7.9701 222.705 295.741 Tm&#10;[&#40;&#92;&#40;a&#92;&#41;&#41;] TJ&#10;ET&#10;q&#10;318.935 415.697 164.161 -65.189 re&#10;W&#10;n&#10;q&#10;165.426 0 0 65.676 318.357 350.472 cm&#10;/X1 Do&#10;Q&#10;Q&#10;q&#10;318.935 350.508 164.161 -42.812 re&#10;W&#10;n&#10;q&#10;165.426 0 0 43.476 318.357 307.092 cm&#10;/X2 Do&#10;Q&#10;Q&#10;BT&#10;7.9701 0 0 7.9701 397.129 295.741 Tm&#10;[&#40;&#92;&#40;b&#92;&#41;&#41;] TJ&#10;ET&#10;BT&#10;/T1_7 1 Tf&#10;8.9664 0 0 8.9664 130.78 272.435 Tm&#10;[&#40;F&#41;30&#40;igur&#41;20&#40;e&#41;-377&#40;11.3&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;8.9664 0 0 8.9664 180.10417 272.435 Tm&#10;[&#40;A&#41;-377&#40;mixtur&#41;29&#40;e&#41;-377&#40;o&#41;15&#40;f&#41;-377&#40;3&#41;-377&#40;Gaussians&#41;-377&#40;in&#41;-377&#40;2d.&#41;-558&#40;&#92;&#40;a&#92;&#41;&#41;-377&#40;W&#41;65&#40;e&#41;-377&#40;sho&#41;16&#40;w&#41;-377&#40;the&#41;-377&#40;cont&#41;30&#40;our&#41;14&#40;s&#41;-377&#40;o&#41;15&#40;f&#41;-377&#40;constant&#41;-377&#40;pr&#41;28&#40;obability&#41;-377&#40;f&#41;27&#40;or&#41;-377&#40;each&#41;] TJ&#10;ET&#10;BT&#10;8.9664 0 0 8.9664 130.78 261.47806 Tm&#10;[&#40;com&#41;13&#40;ponent&#41;-295&#40;in&#41;-294&#40;the&#41;-295&#40;mixtur&#41;29&#40;e.&#41;-392&#40;&#92;&#40;b&#92;&#41;&#41;-295&#40;A&#41;-295&#40;sur&#41;-11&#40;f&#41;15&#40;ace&#41;-294&#40;plo&#41;12&#40;t&#41;-295&#40;o&#41;15&#40;f&#41;-294&#40;the&#41;-295&#40;o&#41;20&#40;v&#41;29&#40;e&#41;12&#40;r&#41;13&#40;all&#41;-294&#40;density&#41;53&#40;.&#41;-393&#40;Based&#41;-295&#40;on&#41;-294&#40;Figur&#41;29&#40;e&#41;-295&#40;2.23&#41;-294&#40;o&#41;15&#40;f&#41;-295&#40;&#92;&#40;Bishop&#41;-295&#40;2006a&#92;&#41;.&#41;] TJ&#10;ET&#10;BT&#10;1.222 TL&#10;8.9664 0 0 8.9664 130.78 250.52112 Tm&#10;[&#40;Figur&#41;29&#40;e&#41;-325&#40;g&#41;19&#40;ene&#41;12&#40;r&#41;13&#40;a&#41;20&#40;t&#41;28&#40;ed&#41;-325&#40;b&#41;20&#40;y&#41;] TJ&#10;ET&#10;BT&#10;0.0001 Tc&#10;/T1_15 1 Tf&#10;8.9664 0 0 8.9664 204.06239 250.52112 Tm&#10;[&#40;mixGaussPlotDemo&#41;] TJ&#10;ET&#10;BT&#10;0 Tc&#10;/T1_1 1 Tf&#10;8.9664 0 0 8.9664 279.36221 250.52112 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;BT&#10;/T1_7 1 Tf&#10;10.9091 0 0 10.9091 93.494 213.631 Tm&#10;[&#40;11.2.1&#41;-1370&#40;Mixtur&#41;20&#40;es&#41;-325&#40;o&#41;14&#40;f&#41;-325&#40;G&#41;13&#40;aussians&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 130.78 195.235 Tm&#10;[&#40;The&#41;-251&#40;most&#41;-251&#40;widely&#41;-252&#40;used&#41;-251&#40;mixtur&#41;29&#40;e&#41;-252&#40;model&#41;-251&#40;is&#41;-252&#40;the&#41;] TJ&#10;ET&#10;BT&#10;/T1_7 1 Tf&#10;9.9626 0 0 9.9626 303.02339 195.235 Tm&#10;[&#40;mixtur&#41;20&#40;e&#41;-252&#40;o&#41;14&#40;f&#41;-251&#40;G&#41;13&#40;aussians&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 394.97819 195.235 Tm&#10;[&#40;&#92;&#40;MOG&#92;&#41;,&#41;-252&#40;also&#41;-251&#40;called&#41;-252&#40;a&#41;] TJ&#10;ET&#10;BT&#10;/T1_7 1 Tf&#10;9.9626 0 0 9.9626 475.00776 195.235 Tm&#10;[&#40;G&#41;13&#40;aussian&#41;] TJ&#10;ET&#10;BT&#10;9.9626 0 0 9.9626 130.78 183.27988 Tm&#10;[&#40;mixtur&#41;20&#40;e&#41;-345&#40;mod&#41;13&#40;el&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 197.62905 183.27988 Tm&#10;[&#40;or&#41;] TJ&#10;ET&#10;BT&#10;/T1_7 1 Tf&#10;9.9626 0 0 9.9626 209.36499 183.27988 Tm&#10;[&#40;GMM&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 231.13327 183.27988 Tm&#10;[&#40;.&#41;-345&#40;In&#41;-345&#40;this&#41;-345&#40;model,&#41;-350&#40;each&#41;-345&#40;base&#41;-345&#40;dist&#41;-12&#40;ribution&#41;-345&#40;in&#41;-345&#40;the&#41;-345&#40;mixtur&#41;29&#40;e&#41;-345&#40;is&#41;-345&#40;a&#41;-345&#40;multiv&#41;24&#40;aria&#41;20&#40;t&#41;28&#40;e&#41;] TJ&#10;ET&#10;BT&#10;9.9626 0 0 9.9626 130.78 171.32476 Tm&#10;[&#40;Gaussian&#41;-325&#40;with&#41;-325&#40;mean&#41;] TJ&#10;ET&#10;BT&#10;/T1_16 1 Tf&#10;9.9626 0 0 9.9626 215.29274 171.32476 Tm&#10;[&#40;&#181;&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 222.345 168.889 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 230.484 171.325 Tm&#10;[&#40;and&#41;-325&#40;co&#41;20&#40;v&#41;24&#40;ariance&#41;-325&#40;ma&#41;20&#40;t&#41;-12&#40;rix&#41;] TJ&#10;ET&#10;BT&#10;/T1_4 1 Tf&#10;9.9626 0 0 9.9626 322.53842 171.325 Tm&#10;[&#40;&#92;003&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 330.813 169.83 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 335.715 171.325 Tm&#10;[&#40;.&#41;-403&#40;Thus&#41;-325&#40;the&#41;-325&#40;model&#41;-325&#40;has&#41;-325&#40;the&#41;-325&#40;f&#41;27&#40;orm&#41;] TJ&#10;ET&#10;BT&#10;/T1_2 1 Tf&#10;9.9626 0 0 9.9626 143.7357 141.70619 Tm&#10;[&#40;p&#41;] TJ&#10;ET&#10;BT&#10;/T1_3 1 Tf&#10;9.9626 0 0 9.9626 148.74689 141.70619 Tm&#10;[&#40;&#92;&#40;&#41;] TJ&#10;ET&#10;BT&#10;/T1_4 1 Tf&#10;9.9626 0 0 9.9626 152.62234 141.70619 Tm&#10;[&#40;x&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 158.665 140.213 Tm&#10;[&#40;i&#41;] TJ&#10;ET&#10;BT&#10;/T1_6 1 Tf&#10;9.9626 0 0 9.9626 161.982 141.7081 Tm&#10;[&#40;|&#41;] TJ&#10;ET&#10;BT&#10;/T1_16 1 Tf&#10;9.9626 0 0 9.9626 164.7516 141.7081 Tm&#10;[&#40;&#92;002&#41;] TJ&#10;ET&#10;BT&#10;0.2789 Tc&#10;/T1_3 1 Tf&#10;9.9626 0 0 9.9626 170.66939 141.7081 Tm&#10;[&#40;&#92;&#41;=&#41;] TJ&#10;ET&#10;BT&#10;0 Tc&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 191.476 154.161 Tm&#10;[&#40;K&#41;] TJ&#10;ET&#10;BT&#10;/T1_17 1 Tf&#10;9.9626 0 0 9.9626 187.872 151.172 Tm&#10;[&#40;&#92;002&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 187.822 129.725 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_18 1 Tf&#10;6.9738 0 0 6.9738 192.22247 129.725 Tm&#10;[&#40;=1&#41;] TJ&#10;ET&#10;BT&#10;/T1_2 1 Tf&#10;9.9626 0 0 9.9626 203.973 141.7081 Tm&#10;[&#40;&#92;013&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 209.652 140.213 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_6 1 Tf&#10;9.9626 0 0 9.9626 214.554 141.7081 Tm&#10;[&#40;N&#41;] TJ&#10;ET&#10;BT&#10;/T1_3 1 Tf&#10;9.9626 0 0 9.9626 224.1978 141.7081 Tm&#10;[&#40;&#92;&#40;&#41;] TJ&#10;ET&#10;BT&#10;/T1_4 1 Tf&#10;9.9626 0 0 9.9626 228.07325 141.7081 Tm&#10;[&#40;x&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 234.117 140.213 Tm&#10;[&#40;i&#41;] TJ&#10;ET&#10;BT&#10;/T1_6 1 Tf&#10;9.9626 0 0 9.9626 237.434 141.7081 Tm&#10;[&#40;|&#41;] TJ&#10;ET&#10;BT&#10;/T1_16 1 Tf&#10;9.9626 0 0 9.9626 240.2036 141.7081 Tm&#10;[&#40;&#181;&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 247.254 139.273 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_2 1 Tf&#10;9.9626 0 0 9.9626 252.156 141.7081 Tm&#10;[&#40;,&#41;] TJ&#10;ET&#10;BT&#10;/T1_4 1 Tf&#10;9.9626 0 0 9.9626 256.58936 141.7081 Tm&#10;[&#40;&#92;003&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 264.858 140.213 Tm&#10;[&#40;k&#41;] TJ&#10;ET&#10;BT&#10;/T1_3 1 Tf&#10;9.9626 0 0 9.9626 269.76 141.7081 Tm&#10;[&#40;&#92;&#41;&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 495.81139 141.7081 Tm&#10;[&#40;&#92;&#40;11.2&#92;&#41;&#41;] TJ&#10;ET&#10;BT&#10;9.9626 0 0 9.9626 130.78173 112.61731 Tm&#10;[&#40;Figur&#41;29&#40;e&#41;-341&#40;11.3&#41;-340&#40;sho&#41;16&#40;w&#41;19&#40;s&#41;-341&#40;a&#41;-340&#40;mixtur&#41;29&#40;e&#41;-341&#40;o&#41;15&#40;f&#41;-341&#40;3&#41;-340&#40;Gaussians&#41;-341&#40;in&#41;-341&#40;2D.&#41;-340&#40;Each&#41;-341&#40;mixtur&#41;29&#40;e&#41;-341&#40;com&#41;13&#40;ponent&#41;-340&#40;is&#41;-341&#40;r&#41;29&#40;epr&#41;29&#40;esent&#41;28&#40;ed&#41;-340&#40;b&#41;20&#40;y&#41;-341&#40;a&#41;] TJ&#10;ET&#10;BT&#10;1.2 TL&#10;9.9626 0 0 9.9626 130.78173 100.66219 Tm&#10;[&#40;di&#92;002e&#41;12&#40;r&#41;29&#40;ent&#41;-378&#40;se&#41;10&#40;t&#41;-378&#40;o&#41;15&#40;f&#41;-377&#40;elip&#41;11&#40;tical&#41;-378&#40;cont&#41;30&#40;our&#41;14&#40;s.&#41;-562&#40;Giv&#41;29&#40;en&#41;-377&#40;a&#41;-378&#40;su&#92;003ciently&#41;-378&#40;lar&#41;15&#40;g&#41;19&#40;e&#41;-378&#40;numbe&#41;12&#40;r&#41;-377&#40;o&#41;15&#40;f&#41;-378&#40;mixtur&#41;29&#40;e&#41;-378&#40;com&#41;13&#40;ponents,&#41;-391&#40;a&#41;] TJ&#10;ET&#10;BT&#10;9.9626 0 0 9.9626 130.78173 88.70707 Tm&#10;[&#40;GMM&#41;-325&#40;can&#41;-325&#40;be&#41;-325&#40;used&#41;-325&#40;t&#41;30&#40;o&#41;-325&#40;appr&#41;28&#40;o&#41;29&#40;xima&#41;20&#40;t&#41;28&#40;e&#41;-325&#40;an&#41;29&#40;y&#41;-325&#40;density&#41;-325&#40;de&#147;ned&#41;-325&#40;on&#41;] TJ&#10;ET&#10;BT&#10;/T1_19 1 Tf&#10;9.9626 0 0 9.9626 364.89287 88.70707 Tm&#10;[&#40;R&#41;] TJ&#10;ET&#10;BT&#10;/T1_5 1 Tf&#10;6.9738 0 0 6.9738 372.086 92.324 Tm&#10;[&#40;D&#41;] TJ&#10;ET&#10;BT&#10;/T1_1 1 Tf&#10;9.9626 0 0 9.9626 379.313 88.709 Tm&#10;[&#40;.&#41;] TJ&#10;ET&#10;Q&#10;</data>
-</stream>
diff --git a/notebooks/shape_analysis.ipynb b/notebooks/shape_analysis.ipynb
deleted file mode 100644
index 2a9cafe..0000000
--- a/notebooks/shape_analysis.ipynb
+++ /dev/null
@@ -1,115 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import common\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "time, pos = common.import_csv_data('w_data.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7f7fb0145390>"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.scatter(pos[0], -pos[1], s=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'pos' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-2-85aa0823d467>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m: name 'pos' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "pos[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "216"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/shape_bezier_fit.ipynb b/notebooks/shape_bezier_fit.ipynb
deleted file mode 100644
index 1a25f09..0000000
--- a/notebooks/shape_bezier_fit.ipynb
+++ /dev/null
@@ -1,122 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import common\n",
-    "import fitCurves\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from matplotlib.path import Path\n",
-    "from math import inf\n",
-    "import matplotlib.patches as patches\n",
-    "import glob\n",
-    "import rdp\n",
-    "#time, pos = common.import_csv_data('w_data.csv')\n",
-    "#pos[1]=-pos[1]\n",
-    "#paths=[pos]\n",
-    "paths = []\n",
-    "for csv_path in glob.glob('outs/*.csv'):\n",
-    "    _, p = common.import_csv_data(csv_path)\n",
-    "    paths.append(p)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def fit_bezier_to_points(points):\n",
-    "    filtered_points = rdp.rdp(np.stack((points[0], points[1]), axis=1))\n",
-    "    control_points = fitCurves.fitCurve(filtered_points, 1e0)\n",
-    "    return [(s[0],s[1]) for s in np.concatenate(control_points)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1440x2160 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "def generate_bezier_patch(control_points):\n",
-    "    codes = [\n",
-    "        Path.MOVETO,\n",
-    "        Path.CURVE4,\n",
-    "        Path.CURVE4,\n",
-    "        Path.CURVE4,\n",
-    "    ] * (len(control_points)//4)\n",
-    "\n",
-    "    path = Path(control_points, codes)\n",
-    "    return patches.PathPatch(path, facecolor='none', lw=2)\n",
-    "\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(20, 30))\n",
-    "min_x = min_y = inf\n",
-    "max_x = max_y = -inf\n",
-    "for points in paths:\n",
-    "    control_points = fit_bezier_to_points(points)\n",
-    "    patch = generate_bezier_patch(control_points)\n",
-    "    ax.add_patch(patch)\n",
-    "    min_x = min(min_x, min(points[0]))\n",
-    "    min_y = min(min_y, min(points[1]))\n",
-    "    max_x = max(max_x, max(points[0]))\n",
-    "    max_y = max(max_y, max(points[1]))\n",
-    "ax.set_xlim(min_x, max_x)\n",
-    "ax.set_ylim(min_y, max_y)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/w_data.csv b/notebooks/w_data.csv
deleted file mode 100644
index cfebcf6..0000000
--- a/notebooks/w_data.csv
+++ /dev/null
@@ -1,205 +0,0 @@
-x,y,pressure,time_usec
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