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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "955e0f44",
+ "metadata": {},
+ "source": [
+ "### Example code for computing CIV distance."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "2da2635f",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/trevormccaffrey/anaconda3/lib/python3.6/_collections_abc.py:841: MatplotlibDeprecationWarning: Support for setting the 'text.latex.preamble' or 'pgf.preamble' rcParam to a list of strings is deprecated since 3.3 and will be removed two minor releases later; set it to a single string instead.\n",
+ " self[key] = other[key]\n"
+ ]
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib.patches as patches\n",
+ "import numpy as np\n",
+ "import richardsplot as rplot\n",
+ "from sklearn.preprocessing import scale\n",
+ "\n",
+ "from CIVfunctions import project, CIV_distance"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "80b6d000",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Basic implementation\n",
+ "\n",
+ "Load in example file with CIV EW+Blueshift already computed."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "70c80012",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " SDSS_NAME_1a | \n",
+ " RA_1a | \n",
+ " DEC_1a | \n",
+ " REDSHIFT | \n",
+ " PLATE_1a | \n",
+ " FIBER_1a | \n",
+ " MJD_1a | \n",
+ " TARGET_FLAG_TARGET | \n",
+ " NSPECOBS | \n",
+ " UNIFORM_TARGET | \n",
+ " ... | \n",
+ " Separation_2 | \n",
+ " CIV_blue | \n",
+ " CIV_EW | \n",
+ " good | \n",
+ " z_paul | \n",
+ " SDSS_NAME_2 | \n",
+ " Separation_Amy | \n",
+ " CIV_DIST_021721 | \n",
+ " Separation | \n",
+ " CIV_DIST_041921 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 104446.00+521742.8 | \n",
+ " 161.191681 | \n",
+ " 52.295242 | \n",
+ " 1.7513 | \n",
+ " 1010 | \n",
+ " 182 | \n",
+ " 52649 | \n",
+ " 3 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.015827 | \n",
+ " 87.889379 | \n",
+ " 37.666121 | \n",
+ " True | \n",
+ " 1.75054 | \n",
+ " 104446.00+521742.8 | \n",
+ " 0.015827 | \n",
+ " 2.522933 | \n",
+ " 0.002494 | \n",
+ " 2.124091 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 104547.58+551853.8 | \n",
+ " 161.448257 | \n",
+ " 55.314972 | \n",
+ " 1.8896 | \n",
+ " 906 | \n",
+ " 462 | \n",
+ " 52368 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.008950 | \n",
+ " 142.521789 | \n",
+ " 44.743671 | \n",
+ " True | \n",
+ " 1.88758 | \n",
+ " 104547.58+551853.8 | \n",
+ " 0.008950 | \n",
+ " 2.422896 | \n",
+ " 0.003449 | \n",
+ " 1.985659 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 104718.64+541917.8 | \n",
+ " 161.827698 | \n",
+ " 54.321629 | \n",
+ " 1.8288 | \n",
+ " 906 | \n",
+ " 55 | \n",
+ " 52368 | \n",
+ " 3145739 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.013102 | \n",
+ " 832.307354 | \n",
+ " 49.698713 | \n",
+ " True | \n",
+ " 1.83249 | \n",
+ " 104718.64+541917.8 | \n",
+ " 0.013102 | \n",
+ " 2.791469 | \n",
+ " 0.005172 | \n",
+ " 2.129244 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 104829.97+550819.0 | \n",
+ " 162.124893 | \n",
+ " 55.138630 | \n",
+ " 2.0671 | \n",
+ " 906 | \n",
+ " 518 | \n",
+ " 52368 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.012861 | \n",
+ " 1798.550056 | \n",
+ " 22.573777 | \n",
+ " True | \n",
+ " 2.07342 | \n",
+ " 104829.97+550819.0 | \n",
+ " 0.012861 | \n",
+ " 3.848747 | \n",
+ " 0.003931 | \n",
+ " 3.199583 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 104852.00+530747.2 | \n",
+ " 162.216675 | \n",
+ " 53.129780 | \n",
+ " 1.6792 | \n",
+ " 1010 | \n",
+ " 509 | \n",
+ " 52649 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.007413 | \n",
+ " 872.211364 | \n",
+ " 51.004578 | \n",
+ " True | \n",
+ " 1.68111 | \n",
+ " 104852.00+530747.2 | \n",
+ " 0.007413 | \n",
+ " 2.801772 | \n",
+ " 0.002967 | \n",
+ " 2.110882 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
5 rows × 342 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " SDSS_NAME_1a RA_1a DEC_1a REDSHIFT PLATE_1a FIBER_1a \\\n",
+ "0 104446.00+521742.8 161.191681 52.295242 1.7513 1010 182 \n",
+ "1 104547.58+551853.8 161.448257 55.314972 1.8896 906 462 \n",
+ "2 104718.64+541917.8 161.827698 54.321629 1.8288 906 55 \n",
+ "3 104829.97+550819.0 162.124893 55.138630 2.0671 906 518 \n",
+ "4 104852.00+530747.2 162.216675 53.129780 1.6792 1010 509 \n",
+ "\n",
+ " MJD_1a TARGET_FLAG_TARGET NSPECOBS UNIFORM_TARGET ... Separation_2 \\\n",
+ "0 52649 3 1 1 ... 0.015827 \n",
+ "1 52368 1048578 1 1 ... 0.008950 \n",
+ "2 52368 3145739 1 1 ... 0.013102 \n",
+ "3 52368 1048578 1 1 ... 0.012861 \n",
+ "4 52649 1048578 1 1 ... 0.007413 \n",
+ "\n",
+ " CIV_blue CIV_EW good z_paul SDSS_NAME_2 Separation_Amy \\\n",
+ "0 87.889379 37.666121 True 1.75054 104446.00+521742.8 0.015827 \n",
+ "1 142.521789 44.743671 True 1.88758 104547.58+551853.8 0.008950 \n",
+ "2 832.307354 49.698713 True 1.83249 104718.64+541917.8 0.013102 \n",
+ "3 1798.550056 22.573777 True 2.07342 104829.97+550819.0 0.012861 \n",
+ "4 872.211364 51.004578 True 1.68111 104852.00+530747.2 0.007413 \n",
+ "\n",
+ " CIV_DIST_021721 Separation CIV_DIST_041921 \n",
+ "0 2.522933 0.002494 2.124091 \n",
+ "1 2.422896 0.003449 1.985659 \n",
+ "2 2.791469 0.005172 2.129244 \n",
+ "3 3.848747 0.003931 3.199583 \n",
+ "4 2.801772 0.002967 2.110882 \n",
+ "\n",
+ "[5 rows x 342 columns]"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dat = pd.read_csv(\"data/LOFAR_from8403colorselected_all388_CIV.csv\")\n",
+ "dat.iloc[:,10:].head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "7f6eb57e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ew = dat[[\"CIV_EW\"]].values.flatten()\n",
+ "blue = dat[[\"CIV_blue\"]].values.flatten()\n",
+ "\n",
+ "#Best-fit line -- this part could be improved\n",
+ "bestfit = np.load(\"data/RM_CIV_bestFitLine_noScale.npy\")[65000:,:]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "928bfdf1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig = plt.figure(figsize=(9,9))\n",
+ "\n",
+ "#Visualize increasing CIV distance\n",
+ "style = \"Simple, tail_width=1.25, head_width=20, head_length=20\"\n",
+ "kw = dict(arrowstyle=style, color=\"k\")\n",
+ "a1 = patches.FancyArrowPatch((2000, 105), (4900, 45),\n",
+ " connectionstyle=\"arc3,rad=.35\", **kw)\n",
+ "plt.gca().add_patch(a1)\n",
+ "plt.text(x=2800,y=95,s=\"Increasing\", fontsize=42.5, weight='extra bold')\n",
+ "plt.text(x=2535,y=82,s=\"C$_\\mathrm{IV}$ Distance\", fontsize=42.5)\n",
+ "\n",
+ "plt.plot(bestfit[:,0], bestfit[:,1])\n",
+ "plt.scatter(blue, ew)\n",
+ "plt.xlabel(\"CIV Blueshift (km\\,s$^{-1}$)\", fontsize=20)\n",
+ "plt.ylabel(\"CIV EW (Å)\", fontsize=20)\n",
+ "plt.xlim(-850,5650)\n",
+ "plt.ylim(-1,148)\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "09c85b3c",
+ "metadata": {},
+ "source": [
+ "Note: points with EW $\\gtrsim105$ Angstroms will be projected onto the top of the curve."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "7f045079",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from time import time\n",
+ "\n",
+ "start = time()\n",
+ "data = np.array([blue, ew]).T\n",
+ "dist = CIV_distance(data, bestfit) #compute CIV distances like this\n",
+ "end = time()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1d191190",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Save time with the ``step`` parameter\n",
+ "\n",
+ "``CIV_distance()`` function has an optional \"step\" parameter. How it's normally set up is to project each data point onto the best-fit curve, then travel along the best-fit line--point-by-point--checking when you've passed a point on the line. The default argument ``step=1`` will check every point along the curve, ``step=100`` will check every hundredth point etc. Since the curve is so dense, you can often get away with a much higher step size than 1, increasing your runtime dramatically; for example, ``step=100`` will result in 100 times less iterations of the for loop inside ``CIV_distance()``.\n",
+ "\n",
+ "Visualize accuracy as a function of step size. Will consider \"correct\" to be the distances corresponding to ``step=1``."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "be76e288",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from functools import reduce\n",
+ "\n",
+ "#Get all factors of input number- use this function to find valid step sizes\n",
+ "def factors(n): \n",
+ " return set(reduce(list.__add__, \n",
+ " ([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "927faef6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "step_list = np.sort(list(factors(98000)))[0:-15:2]\n",
+ "diff_list = [0]\n",
+ "dt_list = [end - start]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "3f93e7de",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 1, 4, 7, 10, 16, 25, 35, 49, 56, 80, 100,\n",
+ " 125, 175, 200, 250, 350, 400, 500, 700, 875, 1000, 1400,\n",
+ " 1960])"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "step_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "d9db150a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for step_size in step_list[1:]:\n",
+ " start_time = time()\n",
+ " idist = CIV_distance(data, bestfit, step=step_size)\n",
+ " diff_list.append(np.median(np.abs((dist-idist)/dist)))\n",
+ " end_time = time()\n",
+ " dt_list.append(end_time - start_time)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "47b637d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.subplots?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "946351e7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax1 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax1.set_xlabel('Step size')\n",
+ "ax1.set_ylabel('fractional error', color=color)\n",
+ "ax1.plot(step_list, diff_list, color=color)\n",
+ "ax1.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax2.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax2.plot(step_list, dt_list, color=color)\n",
+ "ax2.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "plt.show()\n",
+ "\n",
+ "fig, ax11 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax11.set_xlabel('Step size')\n",
+ "ax11.set_ylabel('fractional error', color=color)\n",
+ "ax11.plot(step_list, diff_list, color=color)\n",
+ "ax11.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax22 = ax11.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax22.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax22.plot(step_list, dt_list, color=color)\n",
+ "ax22.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "ax22.set_ylim(0,5)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9c37d66e",
+ "metadata": {},
+ "source": [
+ "Plot showing both the time saved and median error in C IV distance as a function of step size. Lesson learned: use a non-unity step size for lots of data! Roughly ``step=200`` looks like a good choice. **Use the step parameter when testing big datasets.**"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "110f6932",
+ "metadata": {},
+ "source": [
+ "----\n",
+ "\n",
+ "make plots"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "2eead24e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "proj = project(data, bestfit)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "9bade62a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "xscale = scale(np.concatenate((bestfit[:,0], data[:,0]))) #add ``good`` mask to lofar to remove \"bad\" reconstructions\n",
+ "yscale = scale(np.concatenate((bestfit[:,1], data[:,1])))\n",
+ "bestfit_scale = np.array([xscale[0:len(bestfit)], yscale[0:len(bestfit)]]).T\n",
+ "data_scale = np.array([xscale[len(bestfit):len(bestfit)+len(data)], yscale[len(bestfit):len(bestfit)+len(data)]]).T"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "85d64bee",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from matplotlib.patches import ConnectionPatch\n",
+ "\n",
+ "fig, [ax1,ax2] = plt.subplots(1, 2, figsize=(15,5))\n",
+ "plt.subplots_adjust(wspace=1.0)\n",
+ "\n",
+ "ax1.plot(bestfit[:,0], bestfit[:,1])\n",
+ "ax1.scatter(data[::2,0], data[::2,1])\n",
+ "ax1.set_xlim(-850,5650)\n",
+ "ax1.set_ylim(-1,108)\n",
+ "ax1.set_xlabel(\"CIV Blueshift (km\\,s$^{-1}$)\")\n",
+ "ax1.set_ylabel(\"CIV EW ($Å$)\")\n",
+ "\n",
+ "con1 = ConnectionPatch(\n",
+ " xyA=(1.08,0.5), coordsA=ax1.transAxes,\n",
+ " xyB=(-0.30, 0.5), coordsB=ax2.transAxes,\n",
+ " arrowstyle=\"->, head_width=1.7, head_length=1.7\", color=\"black\", linewidth=8.0)\n",
+ "fig.add_artist(con1)\n",
+ "\n",
+ "ax2.plot(bestfit_scale[:,0], bestfit_scale[:,1])\n",
+ "ax2.scatter(data_scale[::2,0], data_scale[::2,1])\n",
+ "ax2.set_xlim(-1.3,3.1)\n",
+ "ax2.set_ylim(-1.95,1.85)\n",
+ "ax2.set_xlabel(\"CIV Blueshift (Scaled)\")\n",
+ "ax2.set_ylabel(\"CIV EW (Scaled)\")\n",
+ "ax2.set_aspect(\"equal\")\n",
+ "\n",
+ "plt.savefig(\"imgs/scale_data.png\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "bc7919ab",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "proj_scale = project(data_scale, bestfit_scale)\n",
+ "\n",
+ "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "87f6b2ed",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, [ax1,ax2] = plt.subplots(1, 2, figsize=(15,5))\n",
+ "plt.subplots_adjust(wspace=1.0)\n",
+ "\n",
+ "con1 = ConnectionPatch(\n",
+ " xyA=(1.08,0.5), coordsA=ax1.transAxes,\n",
+ " xyB=(-0.30, 0.5), coordsB=ax2.transAxes,\n",
+ " arrowstyle=\"->, head_width=1.7, head_length=1.7\", color=\"black\", linewidth=8.0)\n",
+ "fig.add_artist(con1)\n",
+ "\n",
+ "ax1.plot(bestfit_scale[:,0], bestfit_scale[:,1])\n",
+ "ax1.scatter(data_scale[::2,0], data_scale[::2,1])\n",
+ "ax1.set_xlim(-1.3,3.1)\n",
+ "ax1.set_ylim(-2.0,1.9)\n",
+ "ax1.set_xlabel(\"CIV Blueshift (Scaled)\")\n",
+ "ax1.set_ylabel(\"CIV EW (Scaled)\")\n",
+ "ax1.set_aspect(\"equal\")\n",
+ "\n",
+ "ax2.scatter(data_scale[::2,0], data_scale[::2,1], alpha=0.2, color=colors[0])\n",
+ "ax2.scatter(proj_scale[::2,0], proj_scale[::2,1], color=colors[0])\n",
+ "ax2.plot(bestfit_scale[:,0], bestfit_scale[:,1], color=colors[0])\n",
+ "\n",
+ "for i in range(len(proj_scale[::2,0])):\n",
+ " ax2.plot([data_scale[::2,0][i], proj_scale[::2,0][i]], [data_scale[::2,1][i], proj_scale[::2,1][i]], alpha=0.2, color=colors[0])\n",
+ "\n",
+ "ax2.set_xlim(-1.3,3.1)\n",
+ "ax2.set_ylim(-2.0,1.9)\n",
+ "ax2.set_xlabel(\"CIV Blueshift (Scaled)\")\n",
+ "ax2.set_ylabel(\"CIV EW (Scaled)\")\n",
+ "ax2.set_aspect(\"equal\")\n",
+ "\n",
+ "xticks_scaled = ax2.get_xticks()\n",
+ "yticks_scaled = ax2.get_yticks()\n",
+ "\n",
+ "plt.savefig(\"imgs/project_scaled.png\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2107587d",
+ "metadata": {},
+ "source": [
+ "Example plot of CIV distance increments."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "4dc14114",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "98000"
+ ]
+ },
+ "execution_count": 17,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(bestfit[::1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "8736bd1b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dist_line = CIV_distance(bestfit, bestfit, step=200)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "455eed7f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([0, 1, 2, 3, 4, 5])"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.arange(0,6,1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "0db08bc4",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(97800,)"
+ ]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dist_line.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "4e39b33c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([624.7071514, 51.199 ])"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bestfit[np.argmin(abs(dist_line-2)),:]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "dd23cb0f",
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax1 = plt.subplots(figsize=(9,9))\n",
+ "\n",
+ "ax1.scatter(proj[::2,0], proj[::2,1], color=colors[0])\n",
+ "ax1.plot(bestfit[:,0], bestfit[:,1], color=colors[0])\n",
+ "\n",
+ "ax1.plot([-580, 450], [104.7, 105.3], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(580, 103.05, \"0\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "#ax1.plot([-520, 630], [77, 77], linestyle=\"--\", color=colors[2])\n",
+ "ax1.plot([-520, 630], [75.2, 78.8], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(720, 78.5, \"1\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "ax1.plot([136, 996], [43.4, 59.4], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(1076, 60, \"2\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "ax1.plot([1244, 2044], [24, 44], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(2094, 45, \"3\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "ax1.plot([2770, 3370], [10, 32], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(3390, 32.5, \"4\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "ax1.plot([4170, 4770], [0.2, 25.2], linestyle=\"--\", color=colors[2])\n",
+ "ax1.text(4800, 26, \"5\", fontsize=35, color=colors[2])\n",
+ "\n",
+ "#Add starting line\n",
+ "ax1.text(-530, 109, \"Start\", fontsize=35, color=colors[2], family=\"monospace\")\n",
+ "\n",
+ "#Arrow goes out of frame without this for some reason?\n",
+ "ax1.set_xlim(-850,5800)\n",
+ "ax1.set_ylim(-3,118)\n",
+ "\n",
+ "#Visualize increasing CIV distance\n",
+ "style = \"Simple, tail_width=1.25, head_width=20, head_length=20\"\n",
+ "kw = dict(arrowstyle=style, color=\"k\")\n",
+ "a1 = patches.FancyArrowPatch((2000, 105), (4900, 45),\n",
+ " connectionstyle=\"arc3,rad=.35\", **kw)\n",
+ "ax1.add_patch(a1)\n",
+ "\n",
+ "#ax1.title(\"CIV Distance Path\", fontsize=20)\n",
+ "ax1.set_xlabel(\"CIV Blueshift (km\\,s$^{-1}$)\", fontsize=25, color=color)\n",
+ "ax1.set_ylabel(\"CIV EW ($Å$)\", fontsize=25, color=color)\n",
+ "\n",
+ "ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "color = \"k\"\n",
+ "ax2.set_ylabel('CIV EW (Scaled)', color=color, fontsize=25) \n",
+ "ax2.plot(bestfit_scale[:,0], bestfit_scale[:,1], alpha=0, color=color)\n",
+ "ax2.tick_params(axis='y', which=\"both\", color=color, labelcolor=color, labelsize=20)\n",
+ "ax2.yaxis.set_label_position(\"left\")\n",
+ "ax2.yaxis.tick_left()\n",
+ "ax2.set_ylim(-2.3,2.1)\n",
+ "\n",
+ "ax22 = ax1.twiny() # instantiate a second axes that shares the same x-axis\n",
+ "ax22.set_xlabel('CIV Blueshift (Scaled)', color=color, fontsize=25)\n",
+ "ax22.plot(bestfit_scale[:,0], bestfit_scale[:,1], alpha=0, color=color)\n",
+ "ax22.tick_params(axis='x', which=\"both\", color=color, labelcolor=color, labelsize=20)\n",
+ "ax22.xaxis.set_label_position('bottom')\n",
+ "ax22.xaxis.tick_bottom()\n",
+ "ax22.set_xlim(-1.4,3.15)\n",
+ "\n",
+ "color = colors[7]\n",
+ "ax1.xaxis.set_label_position('top')\n",
+ "ax1.xaxis.tick_top()\n",
+ "ax1.yaxis.set_label_position(\"right\")\n",
+ "ax1.yaxis.tick_right()\n",
+ "ax1.tick_params(axis='both', which=\"both\", color=color, labelcolor=color, labelsize=20)\n",
+ "\n",
+ "plt.savefig(\"imgs/distance_path.png\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "ad6526a5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.Axes.tick_params?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "d7da552c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ax2.xaxis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "01a031c2",
+ "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": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/.ipynb_checkpoints/example-Copy2-checkpoint.ipynb b/.ipynb_checkpoints/example-Copy2-checkpoint.ipynb
new file mode 100644
index 0000000..731be62
--- /dev/null
+++ b/.ipynb_checkpoints/example-Copy2-checkpoint.ipynb
@@ -0,0 +1,534 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "955e0f44",
+ "metadata": {},
+ "source": [
+ "### Example code for computing CIV distance."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "2da2635f",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/trevormccaffrey/anaconda3/lib/python3.6/_collections_abc.py:841: MatplotlibDeprecationWarning: Support for setting the 'text.latex.preamble' or 'pgf.preamble' rcParam to a list of strings is deprecated since 3.3 and will be removed two minor releases later; set it to a single string instead.\n",
+ " self[key] = other[key]\n"
+ ]
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib.patches as patches\n",
+ "import numpy as np\n",
+ "import richardsplot as rplot\n",
+ "from sklearn.preprocessing import scale\n",
+ "\n",
+ "from CIVfunctions import project, CIV_distance"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "80b6d000",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Basic implementation\n",
+ "\n",
+ "Load in example file with CIV EW+Blueshift already computed."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "70c80012",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " SDSS_NAME_1a | \n",
+ " RA_1a | \n",
+ " DEC_1a | \n",
+ " REDSHIFT | \n",
+ " PLATE_1a | \n",
+ " FIBER_1a | \n",
+ " MJD_1a | \n",
+ " TARGET_FLAG_TARGET | \n",
+ " NSPECOBS | \n",
+ " UNIFORM_TARGET | \n",
+ " ... | \n",
+ " Separation_2 | \n",
+ " CIV_blue | \n",
+ " CIV_EW | \n",
+ " good | \n",
+ " z_paul | \n",
+ " SDSS_NAME_2 | \n",
+ " Separation_Amy | \n",
+ " CIV_DIST_021721 | \n",
+ " Separation | \n",
+ " CIV_DIST_041921 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 104446.00+521742.8 | \n",
+ " 161.191681 | \n",
+ " 52.295242 | \n",
+ " 1.7513 | \n",
+ " 1010 | \n",
+ " 182 | \n",
+ " 52649 | \n",
+ " 3 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.015827 | \n",
+ " 87.889379 | \n",
+ " 37.666121 | \n",
+ " True | \n",
+ " 1.75054 | \n",
+ " 104446.00+521742.8 | \n",
+ " 0.015827 | \n",
+ " 2.522933 | \n",
+ " 0.002494 | \n",
+ " 2.124091 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 104547.58+551853.8 | \n",
+ " 161.448257 | \n",
+ " 55.314972 | \n",
+ " 1.8896 | \n",
+ " 906 | \n",
+ " 462 | \n",
+ " 52368 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.008950 | \n",
+ " 142.521789 | \n",
+ " 44.743671 | \n",
+ " True | \n",
+ " 1.88758 | \n",
+ " 104547.58+551853.8 | \n",
+ " 0.008950 | \n",
+ " 2.422896 | \n",
+ " 0.003449 | \n",
+ " 1.985659 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 104718.64+541917.8 | \n",
+ " 161.827698 | \n",
+ " 54.321629 | \n",
+ " 1.8288 | \n",
+ " 906 | \n",
+ " 55 | \n",
+ " 52368 | \n",
+ " 3145739 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.013102 | \n",
+ " 832.307354 | \n",
+ " 49.698713 | \n",
+ " True | \n",
+ " 1.83249 | \n",
+ " 104718.64+541917.8 | \n",
+ " 0.013102 | \n",
+ " 2.791469 | \n",
+ " 0.005172 | \n",
+ " 2.129244 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 104829.97+550819.0 | \n",
+ " 162.124893 | \n",
+ " 55.138630 | \n",
+ " 2.0671 | \n",
+ " 906 | \n",
+ " 518 | \n",
+ " 52368 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.012861 | \n",
+ " 1798.550056 | \n",
+ " 22.573777 | \n",
+ " True | \n",
+ " 2.07342 | \n",
+ " 104829.97+550819.0 | \n",
+ " 0.012861 | \n",
+ " 3.848747 | \n",
+ " 0.003931 | \n",
+ " 3.199583 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 104852.00+530747.2 | \n",
+ " 162.216675 | \n",
+ " 53.129780 | \n",
+ " 1.6792 | \n",
+ " 1010 | \n",
+ " 509 | \n",
+ " 52649 | \n",
+ " 1048578 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " ... | \n",
+ " 0.007413 | \n",
+ " 872.211364 | \n",
+ " 51.004578 | \n",
+ " True | \n",
+ " 1.68111 | \n",
+ " 104852.00+530747.2 | \n",
+ " 0.007413 | \n",
+ " 2.801772 | \n",
+ " 0.002967 | \n",
+ " 2.110882 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
5 rows × 342 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " SDSS_NAME_1a RA_1a DEC_1a REDSHIFT PLATE_1a FIBER_1a \\\n",
+ "0 104446.00+521742.8 161.191681 52.295242 1.7513 1010 182 \n",
+ "1 104547.58+551853.8 161.448257 55.314972 1.8896 906 462 \n",
+ "2 104718.64+541917.8 161.827698 54.321629 1.8288 906 55 \n",
+ "3 104829.97+550819.0 162.124893 55.138630 2.0671 906 518 \n",
+ "4 104852.00+530747.2 162.216675 53.129780 1.6792 1010 509 \n",
+ "\n",
+ " MJD_1a TARGET_FLAG_TARGET NSPECOBS UNIFORM_TARGET ... Separation_2 \\\n",
+ "0 52649 3 1 1 ... 0.015827 \n",
+ "1 52368 1048578 1 1 ... 0.008950 \n",
+ "2 52368 3145739 1 1 ... 0.013102 \n",
+ "3 52368 1048578 1 1 ... 0.012861 \n",
+ "4 52649 1048578 1 1 ... 0.007413 \n",
+ "\n",
+ " CIV_blue CIV_EW good z_paul SDSS_NAME_2 Separation_Amy \\\n",
+ "0 87.889379 37.666121 True 1.75054 104446.00+521742.8 0.015827 \n",
+ "1 142.521789 44.743671 True 1.88758 104547.58+551853.8 0.008950 \n",
+ "2 832.307354 49.698713 True 1.83249 104718.64+541917.8 0.013102 \n",
+ "3 1798.550056 22.573777 True 2.07342 104829.97+550819.0 0.012861 \n",
+ "4 872.211364 51.004578 True 1.68111 104852.00+530747.2 0.007413 \n",
+ "\n",
+ " CIV_DIST_021721 Separation CIV_DIST_041921 \n",
+ "0 2.522933 0.002494 2.124091 \n",
+ "1 2.422896 0.003449 1.985659 \n",
+ "2 2.791469 0.005172 2.129244 \n",
+ "3 3.848747 0.003931 3.199583 \n",
+ "4 2.801772 0.002967 2.110882 \n",
+ "\n",
+ "[5 rows x 342 columns]"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dat = pd.read_csv(\"data/LOFAR_from8403colorselected_all388_CIV.csv\")\n",
+ "dat.iloc[:,10:].head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "7f6eb57e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ew = dat[[\"CIV_EW\"]].values.flatten()\n",
+ "blue = dat[[\"CIV_blue\"]].values.flatten()\n",
+ "\n",
+ "#Best-fit line -- this part could be improved\n",
+ "bestfit = np.load(\"data/RM_CIV_bestFitLine_noScale.npy\")[65000:,:]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "928bfdf1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig = plt.figure(figsize=(9,9))\n",
+ "\n",
+ "#Visualize increasing CIV distance\n",
+ "style = \"Simple, tail_width=1.25, head_width=20, head_length=20\"\n",
+ "kw = dict(arrowstyle=style, color=\"k\")\n",
+ "a1 = patches.FancyArrowPatch((2000, 105), (4900, 45),\n",
+ " connectionstyle=\"arc3,rad=.35\", **kw)\n",
+ "plt.gca().add_patch(a1)\n",
+ "plt.text(x=2800,y=95,s=\"Increasing\", fontsize=42.5, weight='extra bold')\n",
+ "plt.text(x=2535,y=82,s=\"C$_\\mathrm{IV}$ Distance\", fontsize=42.5)\n",
+ "\n",
+ "plt.plot(bestfit[:,0], bestfit[:,1])\n",
+ "plt.scatter(blue, ew)\n",
+ "plt.xlabel(\"CIV Blueshift (km\\,s$^{-1}$)\", fontsize=20)\n",
+ "plt.ylabel(\"CIV EW (Å)\", fontsize=20)\n",
+ "plt.xlim(-850,5650)\n",
+ "plt.ylim(-1,148)\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "09c85b3c",
+ "metadata": {},
+ "source": [
+ "Note: points with EW $\\gtrsim105$ Angstroms will be projected onto the top of the curve."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "7f045079",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from time import time\n",
+ "\n",
+ "start = time()\n",
+ "data = np.array([blue, ew]).T\n",
+ "dist = CIV_distance(data, bestfit) #compute CIV distances like this\n",
+ "end = time()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1d191190",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Save time with the ``step`` parameter\n",
+ "\n",
+ "``CIV_distance()`` function has an optional \"step\" parameter. How it's normally set up is to project each data point onto the best-fit curve, then travel along the best-fit line--point-by-point--checking when you've passed a point on the line. The default argument ``step=1`` will check every point along the curve, ``step=100`` will check every hundredth point etc. Since the curve is so dense, you can often get away with a much higher step size than 1, increasing your runtime dramatically; for example, ``step=100`` will result in 100 times less iterations of the for loop inside ``CIV_distance()``.\n",
+ "\n",
+ "Visualize accuracy as a function of step size. Will consider \"correct\" to be the distances corresponding to ``step=1``."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "be76e288",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from functools import reduce\n",
+ "\n",
+ "#Get all factors of input number- use this function to find valid step sizes\n",
+ "def factors(n): \n",
+ " return set(reduce(list.__add__, \n",
+ " ([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "927faef6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "step_list = np.sort(list(factors(98000)))[0:-15:2]\n",
+ "diff_list = [0]\n",
+ "dt_list = [end - start]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "3f93e7de",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 1, 4, 7, 10, 16, 25, 35, 49, 56, 80, 100,\n",
+ " 125, 175, 200, 250, 350, 400, 500, 700, 875, 1000, 1400,\n",
+ " 1960])"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "step_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "d9db150a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for step_size in step_list[1:]:\n",
+ " start_time = time()\n",
+ " idist = CIV_distance(data, bestfit, step=step_size)\n",
+ " diff_list.append(np.median(np.abs((dist-idist)/dist)))\n",
+ " end_time = time()\n",
+ " dt_list.append(end_time - start_time)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "47b637d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.subplots?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "946351e7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax1 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax1.set_xlabel('Step size')\n",
+ "ax1.set_ylabel('fractional error', color=color)\n",
+ "ax1.plot(step_list, diff_list, color=color)\n",
+ "ax1.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax2.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax2.plot(step_list, dt_list, color=color)\n",
+ "ax2.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "plt.show()\n",
+ "\n",
+ "fig, ax11 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax11.set_xlabel('Step size')\n",
+ "ax11.set_ylabel('fractional error', color=color)\n",
+ "ax11.plot(step_list, diff_list, color=color)\n",
+ "ax11.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax22 = ax11.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax22.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax22.plot(step_list, dt_list, color=color)\n",
+ "ax22.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "ax22.set_ylim(0,5)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9c37d66e",
+ "metadata": {},
+ "source": [
+ "Plot showing both the time saved and median error in C IV distance as a function of step size. Lesson learned: use a non-unity step size for lots of data! Roughly ``step=200`` looks like a good choice. **Use the step parameter when testing big datasets.**"
+ ]
+ }
+ ],
+ "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": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/.ipynb_checkpoints/example-checkpoint.ipynb b/.ipynb_checkpoints/example-checkpoint.ipynb
index 7e067fc..731be62 100644
--- a/.ipynb_checkpoints/example-checkpoint.ipynb
+++ b/.ipynb_checkpoints/example-checkpoint.ipynb
@@ -10,10 +10,19 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"id": "2da2635f",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/trevormccaffrey/anaconda3/lib/python3.6/_collections_abc.py:841: MatplotlibDeprecationWarning: Support for setting the 'text.latex.preamble' or 'pgf.preamble' rcParam to a list of strings is deprecated since 3.3 and will be removed two minor releases later; set it to a single string instead.\n",
+ " self[key] = other[key]\n"
+ ]
+ }
+ ],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
@@ -32,12 +41,14 @@
"source": [
"---\n",
"\n",
+ "#### Basic implementation\n",
+ "\n",
"Load in example file with CIV EW+Blueshift already computed."
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"id": "70c80012",
"metadata": {},
"outputs": [
@@ -243,7 +254,7 @@
"[5 rows x 342 columns]"
]
},
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@@ -255,7 +266,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"id": "7f6eb57e",
"metadata": {},
"outputs": [],
@@ -269,7 +280,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"id": "928bfdf1",
"metadata": {},
"outputs": [
@@ -313,18 +324,189 @@
"id": "09c85b3c",
"metadata": {},
"source": [
- "Note: points with EW $\\gtrsim105Å$ will be projected onto the top of the curve."
+ "Note: points with EW $\\gtrsim105$ Angstroms will be projected onto the top of the curve."
]
},
{
"cell_type": "code",
- "execution_count": 6,
- "id": "946351e7",
+ "execution_count": 5,
+ "id": "7f045079",
"metadata": {},
"outputs": [],
"source": [
+ "from time import time\n",
+ "\n",
+ "start = time()\n",
"data = np.array([blue, ew]).T\n",
- "dist = CIV_distance(data, bestfit) #compute CIV distances like this"
+ "dist = CIV_distance(data, bestfit) #compute CIV distances like this\n",
+ "end = time()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1d191190",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Save time with the ``step`` parameter\n",
+ "\n",
+ "``CIV_distance()`` function has an optional \"step\" parameter. How it's normally set up is to project each data point onto the best-fit curve, then travel along the best-fit line--point-by-point--checking when you've passed a point on the line. The default argument ``step=1`` will check every point along the curve, ``step=100`` will check every hundredth point etc. Since the curve is so dense, you can often get away with a much higher step size than 1, increasing your runtime dramatically; for example, ``step=100`` will result in 100 times less iterations of the for loop inside ``CIV_distance()``.\n",
+ "\n",
+ "Visualize accuracy as a function of step size. Will consider \"correct\" to be the distances corresponding to ``step=1``."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "be76e288",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from functools import reduce\n",
+ "\n",
+ "#Get all factors of input number- use this function to find valid step sizes\n",
+ "def factors(n): \n",
+ " return set(reduce(list.__add__, \n",
+ " ([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "927faef6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "step_list = np.sort(list(factors(98000)))[0:-15:2]\n",
+ "diff_list = [0]\n",
+ "dt_list = [end - start]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "3f93e7de",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 1, 4, 7, 10, 16, 25, 35, 49, 56, 80, 100,\n",
+ " 125, 175, 200, 250, 350, 400, 500, 700, 875, 1000, 1400,\n",
+ " 1960])"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "step_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "d9db150a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for step_size in step_list[1:]:\n",
+ " start_time = time()\n",
+ " idist = CIV_distance(data, bestfit, step=step_size)\n",
+ " diff_list.append(np.median(np.abs((dist-idist)/dist)))\n",
+ " end_time = time()\n",
+ " dt_list.append(end_time - start_time)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "47b637d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.subplots?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "946351e7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax1 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax1.set_xlabel('Step size')\n",
+ "ax1.set_ylabel('fractional error', color=color)\n",
+ "ax1.plot(step_list, diff_list, color=color)\n",
+ "ax1.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax2.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax2.plot(step_list, dt_list, color=color)\n",
+ "ax2.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "plt.show()\n",
+ "\n",
+ "fig, ax11 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax11.set_xlabel('Step size')\n",
+ "ax11.set_ylabel('fractional error', color=color)\n",
+ "ax11.plot(step_list, diff_list, color=color)\n",
+ "ax11.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax22 = ax11.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax22.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax22.plot(step_list, dt_list, color=color)\n",
+ "ax22.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "ax22.set_ylim(0,5)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9c37d66e",
+ "metadata": {},
+ "source": [
+ "Plot showing both the time saved and median error in C IV distance as a function of step size. Lesson learned: use a non-unity step size for lots of data! Roughly ``step=200`` looks like a good choice. **Use the step parameter when testing big datasets.**"
]
}
],
diff --git a/CIVfunctions.py b/CIVfunctions.py
index 44a4f27..32c0285 100644
--- a/CIVfunctions.py
+++ b/CIVfunctions.py
@@ -19,7 +19,7 @@ def project(data, fit):
return np.array(locs)
-def CIV_distance(data_original, fit_original):
+def CIV_distance(data_original, fit_original, step=1):
#fit: N-by-2 array containing coordinates of points along best fit line
#data: N-by-2 [[x,y]] array of data
#NOTE: This really just caters to this situation (assumes monotonically decreasing fit_original)
@@ -38,12 +38,13 @@ def CIV_distance(data_original, fit_original):
#3) Loop through each data point- start at tip of line and sum dist traveled until passing data point
for scat in data:
d = 0 #start at beginning of the line
- for i in range(fit.shape[0]-1):
- xp, x = fit[i,0], fit[i+1,0]
- yp, y = fit[i,1], fit[i+1,1]
+ for i in range(0, fit.shape[0]-step, step):
+ xp, x = fit[i,0], fit[i+step,0]
+ yp, y = fit[i,1], fit[i+step,1]
+ dp = d
d += np.sqrt((x-xp)**2 + (y-yp)**2)
if yp >= scat[1] > y: #if we pass the projected y-coord, save the distance traveled
- darr.append(d)
+ darr.append((d+dp)/2) #save the average between dprevious and d
break
return np.array(darr)
diff --git a/__pycache__/CIVfunctions.cpython-36.pyc b/__pycache__/CIVfunctions.cpython-36.pyc
index 52eabb2..16ee8e1 100644
Binary files a/__pycache__/CIVfunctions.cpython-36.pyc and b/__pycache__/CIVfunctions.cpython-36.pyc differ
diff --git a/data/.DS_Store b/data/.DS_Store
new file mode 100644
index 0000000..5008ddf
Binary files /dev/null and b/data/.DS_Store differ
diff --git a/example.ipynb b/example.ipynb
index 7e067fc..731be62 100644
--- a/example.ipynb
+++ b/example.ipynb
@@ -10,10 +10,19 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"id": "2da2635f",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/trevormccaffrey/anaconda3/lib/python3.6/_collections_abc.py:841: MatplotlibDeprecationWarning: Support for setting the 'text.latex.preamble' or 'pgf.preamble' rcParam to a list of strings is deprecated since 3.3 and will be removed two minor releases later; set it to a single string instead.\n",
+ " self[key] = other[key]\n"
+ ]
+ }
+ ],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
@@ -32,12 +41,14 @@
"source": [
"---\n",
"\n",
+ "#### Basic implementation\n",
+ "\n",
"Load in example file with CIV EW+Blueshift already computed."
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"id": "70c80012",
"metadata": {},
"outputs": [
@@ -243,7 +254,7 @@
"[5 rows x 342 columns]"
]
},
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@@ -255,7 +266,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"id": "7f6eb57e",
"metadata": {},
"outputs": [],
@@ -269,7 +280,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"id": "928bfdf1",
"metadata": {},
"outputs": [
@@ -313,18 +324,189 @@
"id": "09c85b3c",
"metadata": {},
"source": [
- "Note: points with EW $\\gtrsim105Å$ will be projected onto the top of the curve."
+ "Note: points with EW $\\gtrsim105$ Angstroms will be projected onto the top of the curve."
]
},
{
"cell_type": "code",
- "execution_count": 6,
- "id": "946351e7",
+ "execution_count": 5,
+ "id": "7f045079",
"metadata": {},
"outputs": [],
"source": [
+ "from time import time\n",
+ "\n",
+ "start = time()\n",
"data = np.array([blue, ew]).T\n",
- "dist = CIV_distance(data, bestfit) #compute CIV distances like this"
+ "dist = CIV_distance(data, bestfit) #compute CIV distances like this\n",
+ "end = time()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1d191190",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "#### Save time with the ``step`` parameter\n",
+ "\n",
+ "``CIV_distance()`` function has an optional \"step\" parameter. How it's normally set up is to project each data point onto the best-fit curve, then travel along the best-fit line--point-by-point--checking when you've passed a point on the line. The default argument ``step=1`` will check every point along the curve, ``step=100`` will check every hundredth point etc. Since the curve is so dense, you can often get away with a much higher step size than 1, increasing your runtime dramatically; for example, ``step=100`` will result in 100 times less iterations of the for loop inside ``CIV_distance()``.\n",
+ "\n",
+ "Visualize accuracy as a function of step size. Will consider \"correct\" to be the distances corresponding to ``step=1``."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "be76e288",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from functools import reduce\n",
+ "\n",
+ "#Get all factors of input number- use this function to find valid step sizes\n",
+ "def factors(n): \n",
+ " return set(reduce(list.__add__, \n",
+ " ([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "927faef6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "step_list = np.sort(list(factors(98000)))[0:-15:2]\n",
+ "diff_list = [0]\n",
+ "dt_list = [end - start]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "3f93e7de",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 1, 4, 7, 10, 16, 25, 35, 49, 56, 80, 100,\n",
+ " 125, 175, 200, 250, 350, 400, 500, 700, 875, 1000, 1400,\n",
+ " 1960])"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "step_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "d9db150a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for step_size in step_list[1:]:\n",
+ " start_time = time()\n",
+ " idist = CIV_distance(data, bestfit, step=step_size)\n",
+ " diff_list.append(np.median(np.abs((dist-idist)/dist)))\n",
+ " end_time = time()\n",
+ " dt_list.append(end_time - start_time)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "47b637d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.subplots?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "946351e7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax1 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax1.set_xlabel('Step size')\n",
+ "ax1.set_ylabel('fractional error', color=color)\n",
+ "ax1.plot(step_list, diff_list, color=color)\n",
+ "ax1.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax2.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax2.plot(step_list, dt_list, color=color)\n",
+ "ax2.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "plt.show()\n",
+ "\n",
+ "fig, ax11 = plt.subplots()\n",
+ "\n",
+ "color = 'tab:red'\n",
+ "ax11.set_xlabel('Step size')\n",
+ "ax11.set_ylabel('fractional error', color=color)\n",
+ "ax11.plot(step_list, diff_list, color=color)\n",
+ "ax11.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "ax22 = ax11.twinx() # instantiate a second axes that shares the same x-axis\n",
+ "\n",
+ "color = 'tab:blue'\n",
+ "ax22.set_ylabel('runtime (seconds)', color=color) # we already handled the x-label with ax1\n",
+ "ax22.plot(step_list, dt_list, color=color)\n",
+ "ax22.tick_params(axis='y', labelcolor=color)\n",
+ "\n",
+ "fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
+ "ax22.set_ylim(0,5)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9c37d66e",
+ "metadata": {},
+ "source": [
+ "Plot showing both the time saved and median error in C IV distance as a function of step size. Lesson learned: use a non-unity step size for lots of data! Roughly ``step=200`` looks like a good choice. **Use the step parameter when testing big datasets.**"
]
}
],
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