{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Testing 1-D random walk turbulence jittering for vertical particle distribution" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# imports modules and renames them short names\n", "import numpy as np\n", "import os\n", "from matplotlib import pyplot as plt, animation\n", "from datetime import datetime, timedelta\n", "from dateutil.parser import parse\n", "from IPython.display import HTML\n", "from scipy.stats import skewnorm, gamma\n", "import seaborn as sns\n", "\n", "# makes the plots show up below the code cells\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Sets the default font size of matplotlib plots\n", "plt.rcParams['font.size'] = 12" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Create a 1D random walk turbulence model to jitter particles in the vertical" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Define parameters for the walk\n", "\n", "dims = 1 # just 1 dimension, in my case it represents depth\n", "step_n = 10000 # number of timesteps - when implementing this in parcels, divide your \"duration\" (days) variable by your timestep variable \"dt\" \n", "#(seconds) to get the total number of timesteps. It would look like this: (duration*24*60*60)/dt\n", "step_set = [-1, 0, 1] # these are the random step choices, the particles can either go backwards (-1 increment, could be up in my case if depth\n", "# variable is positive for increasing depth), not move at all (0), or go forwards (1 increment). Need to define increments somehow\n", "origin = np.zeros((1,dims)) # this creates a new array, of x dimensions, filled with zeroes. The first 1 I think is basically the number of particles\n", "# if I want to assign an initial depth distribution the array I would create would not be filled with zeroes, but would be all the particles\n", "# and their starting depths" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Simulate steps in 1D\n", "\n", "step_shape = (step_n,dims)\n", "steps = np.random.choice(a=step_set, size=step_shape)\n", "path = np.concatenate([origin, steps]).cumsum(0)\n", "start = path[:1]\n", "stop = path[-1:]\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[-1, 0, 1]\n" ] } ], "source": [ "print()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the path\n", "\n", "fig = plt.figure(figsize=(8,4),dpi=200)\n", "ax = fig.add_subplot(111)\n", "#ax.scatter(np.arange(step_n+1), path, c='blue', alpha=0.5, s=0.05);\n", "ax.plot(path, c='blue', alpha=0.5, lw=0.5, ls='-',);\n", "ax.plot(0, start, c='red', marker='+')\n", "ax.plot(step_n, stop, c='black', marker='o')\n", "\n", "# The red + is the particles start, black circle is end. Blue line is its path along the 1 dimension over the timesteps" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(4, 4))\n", "l = ax.plot(path, c='black', marker='o')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Try to animate this" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%capture\n", "\n", "fig, ax = plt.subplots(figsize=(4, 4))\n", "l = ax.plot(path, c='black', marker='o')\n", "\n", "# Init function\n", "def init():\n", " l.set_offsets(np.empty((0, 2)))\n", " l.set_array(np.empty(0))\n", " return l,\n", "\n", "# Animate function\n", "def animate(hour):\n", " l.set_offsets(np.vstack([data.lon[:, hour], data.z[:, hour]]).T)\n", " l.set_array(data.z[:, hour])\n", " return l,\n", "\n", "# Build animation\n", "anim = animation.FuncAnimation(fig, animate, init_func=init, frames=73, interval=100, blit=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Render animation\n", "HTML(anim.to_html5_video())" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Create skewed Gaussian distribution modelled after my pteropod vertical distributions" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_1146955/2064641501.py:5: UserWarning: \n", "\n", "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", "\n", "Please adapt your code to use either `displot` (a figure-level function with\n", "similar flexibility) or `histplot` (an axes-level function for histograms).\n", "\n", "For a guide to updating your code to use the new functions, please see\n", "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", "\n", " ax = sns.distplot(data, kde_kws={'label':'kde of given data'}, label='histogram')\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# create some random data from a skewnorm\n", "data = skewnorm.rvs(5, loc=10, scale=70, size=1000).astype(np.int_)\n", "\n", "# draw a histogram and kde of the given data\n", "ax = sns.distplot(data, kde_kws={'label':'kde of given data'}, label='histogram')\n", "\n", "# find parameters to fit a skewnorm to the data\n", "params = skewnorm.fit(data, 5, loc=10, scale=70)\n", "\n", "# draw the pdf of the fitted skewnorm\n", "x = np.linspace(0, 255, 500)\n", "ax.plot(x, skewnorm.pdf(x, *params), label='approximated skewnorm')\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(5.378448039731417, 47.758016157226024, 67.34594006680516)\n" ] } ], "source": [ "print(params)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "\n", "# Calculate the first four moments:\n", "a = 2 # a is the input the scipy.stats.gamma takes as the shape parameter\n", "#mean, var, skew, kurt = gamma.stats(a, moments='mvsk')" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Display the probability density function (pdf):\n", "fig, ax = plt.subplots(1, 1)\n", "x = np.linspace(gamma.ppf(0, a), gamma.ppf(300, a), 1000)\n", "ax.plot(x, gamma.pdf(x, a, loc = 10, scale = 100), 'r-', lw=5, alpha=0.6, label='gamma pdf')" ] } ], "metadata": { "kernelspec": { "display_name": "analysis-matt", "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": "3.10.9" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "b0820408f94f9adab353dd622003a8ca360cea5172f3643d18b5213ac85f01b3" } } }, "nbformat": 4, "nbformat_minor": 2 }