Fixed import errors.
This commit is contained in:
Roger Labbe committed
1 parent
bb36ee299f
commit
6871e55e78
1 file changed
+27
-22
+27
-22
@@ -53,7 +53,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@@ -61,9 +61,9 @@
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"outputs": [
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{
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"data": {
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"image/png": 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truncated
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAARAAAAEoCAYAAACQI67VAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
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"text/plain": [
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"<matplotlib.figure.Figure at 0x7407940>"
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"<matplotlib.figure.Figure at 0x71f6828>"
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]
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},
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"metadata": {},
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@@ -111,11 +111,11 @@
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" plt.ylabel('velocity')\n",
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" \n",
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"interact(plot_FPFT, \n",
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" F00=widgets.IntSliderWidget(value=1, min=0, max=2.), \n",
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" F01=widgets.FloatSliderWidget(value=1, min=0., max=2., description='F01(dt)'),\n",
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" F10=widgets.FloatSliderWidget(value=0, min=0., max=2.),\n",
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" F11=widgets.FloatSliderWidget(value=1, min=0., max=2.),\n",
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" covar=widgets.FloatSliderWidget(value=0, min=0, max=1.));"
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" F00=widgets.IntSlider(value=1, min=0, max=2.), \n",
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" F01=widgets.FloatSlider(value=1, min=0., max=2., description='F01(dt)'),\n",
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" F10=widgets.FloatSlider(value=0, min=0., max=2.),\n",
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" F11=widgets.FloatSlider(value=1, min=0., max=2.),\n",
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" covar=widgets.FloatSlider(value=0, min=0, max=1.));"
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]
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},
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{
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@@ -131,7 +131,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 2,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
@@ -140,7 +140,7 @@
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7754cc0>"
|
||||
"<matplotlib.figure.Figure at 0x7427588>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -148,14 +148,19 @@
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"%matplotlib inline\n",
|
||||
"from IPython.html.widgets import interact, interactive, fixed\n",
|
||||
"from IPython.html.widgets import FloatSlider\n",
|
||||
"from math import cos, sin, pi\n",
|
||||
"from math import cos, sin, pi, atan2, sqrt\n",
|
||||
"import numpy.linalg as linalg\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"from matplotlib.patches import Ellipse\n",
|
||||
"\n",
|
||||
"def plot_covariance_ellipse(P):\n",
|
||||
" U,s,v = linalg.svd(P)\n",
|
||||
" angle = math.atan2(U[1,0],U[0,0])\n",
|
||||
" width = math.sqrt(s[0]) * 2\n",
|
||||
" height = math.sqrt(s[1]) * 2\n",
|
||||
" angle = atan2(U[1,0],U[0,0])\n",
|
||||
" width = sqrt(s[0]) * 2\n",
|
||||
" height = sqrt(s[1]) * 2\n",
|
||||
"\n",
|
||||
" ax = plt.gca()\n",
|
||||
" e = Ellipse(xy=(0, 0), width=width, height=height, angle=angle,\n",
|
||||
@@ -191,16 +196,16 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"execution_count": 3,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEACAYAAABRQBpkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x6e3cc18>"
|
||||
"<matplotlib.figure.Figure at 0x7e26358>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -244,10 +249,10 @@
|
||||
" plt.show()\n",
|
||||
"\n",
|
||||
"interact (interactive_gh, \n",
|
||||
" x=widgets.FloatSliderWidget(value=0., min=-50, max=50.), \n",
|
||||
" dx=widgets.FloatSliderWidget(value=5., min=-50., max=50.), \n",
|
||||
" g=widgets.FloatSliderWidget(value=0.1, min=0.01, max=2, step=.02), \n",
|
||||
" h=widgets.FloatSliderWidget(value=0.02, min=0.0, max=0.5, step=0.01));"
|
||||
" x=widgets.FloatSlider(value=0., min=-50, max=50.), \n",
|
||||
" dx=widgets.FloatSlider(value=5., min=-50., max=50.), \n",
|
||||
" g=widgets.FloatSlider(value=0.1, min=0.01, max=2, step=.02), \n",
|
||||
" h=widgets.FloatSlider(value=0.02, min=0.0, max=0.5, step=0.01));"
|
||||
]
|
||||
}
|
||||
],
|
||||
@@ -267,7 +272,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.4.1"
|
||||
"version": "3.5.0"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
Reference in new issue
Block a user