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133 lines
3.1 KiB
133 lines
3.1 KiB
{
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"cells": [
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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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"Exercise 1b: Read a binary file which contains pixel data and apply\n",
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"transformations"
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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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"import numpy as np\n",
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"import matplotlib.pyplot as plt"
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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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"# load figure as 2D array \n",
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"data = np.load('horse.npy')\n",
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"print(data.shape)"
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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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"# just scale the data by a factor and shift by trans\n",
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"trans = np.ones(data.shape)\n",
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"trans[0,:] *=0.6\n",
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"trans[1,:] *=0.4\n",
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"factor = 0.5 \n",
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"data_scale = data * factor + trans"
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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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"#compression in x and y \n",
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"sx = 0.4\n",
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"sy = 0.9\n",
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"t = np.array([[sx,0],[0,sy]])\n",
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"data_comp = t@data"
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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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"#rotation by an angle theta\n",
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"theta = 0.5\n",
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"data_rot = np.array([[np.cos(theta),-np.sin(theta)],[np.sin(theta), np.cos(theta)]])@data"
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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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"#spiegelung an der x Achse\n",
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"tx = np.array([[1,0],[0,-1]]) # mirror x axis\n",
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"ty = np.array([[-1,0],[0,1]]) # mirror y axis\n",
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"tp = np.array([[-1,0],[0,-1]]) # mirror (0,0)\n",
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"data_mirror = tp@data"
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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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"# create figure for the transformations\n",
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"plt.figure(figsize=(10.0,10.0),dpi=100,facecolor='lightgrey')\n",
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"plt.suptitle('Plot Transformations')\n",
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"plt.subplot(2,2,1)\n",
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"plt.title('original picture')\n",
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"plt.plot(data[0,:],data[1,:],'.')\n",
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"plt.axis([-1.2,1.2,-1.2,1.2])\n",
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"plt.subplot(2,2,2)\n",
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"plt.title('scaling and translation')\n",
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"plt.plot(data_scale[0,:],data_scale[1,:],'.')\n",
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"plt.axis([-1.2,1.2,-1.2,1.2])\n",
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"plt.subplot(2,2,3)\n",
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"plt.title('compression')\n",
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"plt.plot(data_comp[0,:],data_comp[1,:],'.')\n",
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"plt.axis([-1.2,1.2,-1.2,1.2])\n",
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"plt.subplot(2,2,4)\n",
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"plt.title('rotation and mirror at p(0,0)')\n",
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"plt.plot(data_rot[0,:],data_rot[1,:],'.')\n",
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"plt.plot(data_mirror[0,:],data_mirror[1,:],'.')\n",
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"plt.axis([-1.2,1.2,-1.2,1.2])"
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]
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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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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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