{ "cells": [ { "cell_type": "code", "execution_count": 326, "metadata": { "ExecuteTime": { "end_time": "2018-10-26T08:39:33.004450Z", "start_time": "2018-10-26T08:39:32.891153Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "from noise import pnoise1, pnoise3\n", "import matplotlib.pyplot as plt\n", "import matplotlib.gridspec as gridspec\n", "from scipy import interpolate\n", "from jupyterthemes import jtplot\n", "jtplot.style(grid=False, fscale=0.6)\n", "#jtplot.reset()\n", "\n", "layer_thickness = 5.0 #in nm, we will use this throughout\n", "num_layers = 200 # this give us a 1um thick sample \n", "uni = np.linspace(0, num_layers, num_layers, endpoint=False)\n", "\n", "d_array = np.array(num_layers*[layer_thickness])\n", "\n", "\n", "samps = int(np.random.uniform(70, 180, 1))\n", "scales = np.random.uniform(0.05, 0.5, 1)\n", "\n", "\n", "\n", "\n", "\n", "s = np.linspace(-1,201, samps)\n", "fr = np.clip(np.random.normal(loc=0.5, scale=scales, size=samps), 0, 1)\n", "fr_p = s - s\n", "for ctr, x in enumerate(s):\n", " octa = np.random.uniform(1,4,1)\n", " pers = np.random.uniform(0.5, 2.2, 1)\n", " fr_p[ctr] = np.clip((0.5 + pnoise1(x, octaves=octa, persistence=pers)), 0,1)\n", "\n", "if np.random.randint(2):\n", " f = interpolate.interp1d(s, fr, kind='quadratic', assume_sorted=True)\n", "else:\n", " f = interpolate.interp1d(s, fr_p, kind='quadratic', assume_sorted=True)\n", "\n", "q_x = np.clip( f(uni), 0, 1)\n", "\n", "\n", "\n", "bins = np.array([-0.02, 0.2, 0.4, 0.6, 0.8, 1.01])\n", "dig = (np.digitize(q_x, bins, right=True)) - 1\n", "act_r = np.linspace(0, 1, 5, endpoint=True)\n", "q_xd = act_r[dig]\n", "\n", "\n", "fig = plt.subplots(2,1, figsize=(4,2))\n", "\n", "ax = plt.subplot(211)\n", "gratim = np.tile(q_xd, (5,1))\n", "#ax.axis('tight')\n", "ax.axis('off')\n", "ax.set_axis_off()\n", "ax.set_xlim(0,num_layers)\n", "ax.xaxis.set_label_position('top') \n", "ax.xaxis.tick_top()\n", "ax.imshow(gratim, cmap='binary_r')\n", "\n", "ax1 = plt.subplot(212)\n", "#ax1.imshow(gratim, cmap='binary_r')\n", "ax1.plot(uni*5.0, q_x, linewidth=0.3 )\n", "ax1.plot(uni*5.0, q_xd, linewidth=0.5 )\n", "ax1.set_ylim(-0.1,1.1)\n", "ax1.set_xlim(0,num_layers*layer_thickness)\n", "ax1.set_xlabel('Distance (nm)')\n", "#ax1.xaxis.set_label_position('top') \n", "#ax1.xaxis.tick_top()\n", "plt.subplots_adjust(wspace=0, hspace=0)\n", "plt.tight_layout()\n", "#f(uni)" ] }, { "cell_type": "code", "execution_count": 373, "metadata": { "ExecuteTime": { "end_time": "2018-10-26T09:02:35.209374Z", "start_time": "2018-10-26T09:02:35.123645Z" } }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 373, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "num_layers = 200\n", "\n", "def bet01(x):\n", " x = x - np.amin(x)\n", " x = x/np.amax(x)\n", " return x\n", " \n", "\n", "\n", "xs = np.linspace(0, num_layers, num_layers)\n", "poses = np.ones_like(xs)\n", "\n", "poses[0] = 0 #np.random.uniform(-50, +50, 1)\n", "\n", "p = random.random()\n", "pos_counter = 0\n", "#Start the random walk.\n", "for i in range(1,num_layers):\n", " \n", " test = random.random()\n", " \n", " if test >= p:\n", " pos_counter += np.random.uniform(1,100)\n", " else:\n", " pos_counter -= np.random.uniform(1,100)\n", "\n", " #Fill the current position array index with the current value of the position counter from the loop.\n", " poses[i] = pos_counter\n", "\n", "poses = bet01(poses)\n", "\n", "plt.plot(xs, poses)\n", "\n" ] }, { "cell_type": "code", "execution_count": 325, "metadata": { "ExecuteTime": { "end_time": "2018-10-26T08:38:26.139462Z", "start_time": "2018-10-26T08:38:26.043349Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/hegder/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:86: MatplotlibDeprecationWarning: pyplot.hold is deprecated.\n", " Future behavior will be consistent with the long-time default:\n", " plot commands add elements without first clearing the\n", " Axes and/or Figure.\n", "/home/hegder/anaconda3/lib/python3.7/site-packages/matplotlib/__init__.py:910: MatplotlibDeprecationWarning: axes.hold is deprecated. Please remove it from your matplotlibrc and/or style files.\n", " mplDeprecation)\n", "/home/hegder/anaconda3/lib/python3.7/site-packages/matplotlib/rcsetup.py:156: MatplotlibDeprecationWarning: axes.hold is deprecated, will be removed in 3.0\n", " mplDeprecation)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#The following code describes a simple 1D random walk\n", "#where the walker can move either forwards or backwards. There is an\n", "#equal probability to move either forwards or backwards with each step.\n", "\n", "\n", "\n", "#Numeric Python library\n", "import numpy as np\n", "import random\n", "from matplotlib import pyplot as plt\n", "\n", "\n", "#Number of steps. Chosen as 50 in this case.\n", "N_steps = 1000\n", "prob = 0.5\n", "\n", "def SimpleRandomWalk(N, p, line):\n", "\n", " #Create an array of positions for the walker. And initialize the first position\n", " #to be the origin (zero). The array will be the same size as the number of steps.\n", " #A position counter variable is also used, which is initialized to zero as well.\n", " position = np.empty(N)\n", " position[0] = 0\n", " pos_counter = 0\n", "\n", " #Array containing the full range of the number of possible steps taken.\n", " steps = np.arange(N)\n", "\n", "\n", " #Start the random walk.\n", " for i in range(1,N):\n", "\n", "\n", " #Generate a random probability value between 0 and 1.\n", " test = random.random()\n", "\n", "\n", " #Chechk the value of the probability generated. If it is > or equal to 0.5, increment the step forwards.\n", " #If it is less than 0.5, increment a step backwards instead. Keep track of the position counter after\n", " #updating it.\n", " if test >= p:\n", " pos_counter += 1\n", " else:\n", " pos_counter -= 1\n", "\n", " #Fill the current position array index with the current value of the position counter from the loop.\n", " position[i] = pos_counter\n", "\n", "\n", "\n", " #Generate a plot of walker position vs. the number of steps taken. Line is a string that will describe the\n", " #markers and line type used to plot the random walk.\n", " plt.plot(steps, position/np.amax(position), line)\n", " plt.xlabel('Steps taken')\n", " plt.ylabel('Distance from Starting Position')\n", "\n", "\n", " return None\n", "\n", "\n", "#Create a new figure to plot the random walk.\n", "plt.figure()\n", "\n", "#Function call to generate and plot the first random walk with circular markers and a dotted line.\n", "SimpleRandomWalk(N_steps, prob, line = 'o--')\n", "\n", "\n", "#Hold the first random walk on the plot.\n", "plt.hold(True)\n", "\n", "\n", "#Function call to generate and plot a second random walk using a full line.\n", "SimpleRandomWalk(N_steps, prob, line = '-')\n", "\n", "\n", "#Show both random walks on the plot.\n", "plt.show()" ] }, { "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": "3.7.0" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 2 }