{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The autoreload extension is already loaded. To reload it, use:\n", " %reload_ext autoreload\n" ] } ], "source": [ "%matplotlib notebook\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from scipy.interpolate import interp1d\n", "from scipy.interpolate import UnivariateSpline\n", "from matplotlib.patches import Circle\n", "from scipy.special import gamma\n", "import numpy as np\n", "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", "from numpy import exp, sqrt\n", "from scipy.integrate import quad, dblquad, nquad, simps\n", "from scipy.stats import rv_continuous\n", "from scipy.special import gamma\n", "from scipy.interpolate import interp1d\n", "from scipy.integrate import quad\n", "import scipy.optimize as optimize\n", "import matplotlib.patches as patches\n", "from itertools import product\n", "from scipy.integrate import quad\n", "import scipy.optimize as optimize\n", "from scipy.interpolate import interp1d\n", "from scipy.misc import derivative\n", "import matplotlib.pyplot as plt\n", "import matplotlib as mpl\n", "from sklearn.neighbors import KDTree\n", "import sys\n", "import glob\n", "from unsio import *\n", "import os\n", "import wkbl\n", "from wkbl.astro.halo_info import *\n", "from mpl_toolkits.mplot3d import axes3d\n", "from mpl_toolkits.mplot3d import proj3d\n", "from matplotlib import cm\n", "import wkbl.astro.nbody_essentials as nbe\n", "from iminuit import Minuit, describe, Struct\n", "import probfit\n", "import cfalcon\n", "CF =cfalcon.CFalcon()\n", "from matplotlib.colors import LogNorm\n", "from matplotlib.ticker import FormatStrFormatter\n", "from matplotlib import rc\n", "import datetime\n", "from scipy.misc import derivative\n", "rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n", "## for Palatino and other serif fonts use:\n", "#rc('font',**{'family':'serif','serif':['Palatino']})\n", "rc('text', usetex=True)\n", "labelsize = 30\n", "tickssize = 19\n", "textsize = 15\n", "hydro = HALOBHydro()\n", "dmo = HALOBdmo()\n", "center_in_pot=True" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# DMO" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "loading Dark matter..\n" ] } ], "source": [ "\n", "simname = dmo.name\n", "pathsim = dmo.path\n", "#path = \"/media/arturo/ARTUROTECA/OUTPUTS/HaloB/output_00417\"\n", "myDMO = wkbl.Galaxy_Hound(pathsim)\n", "zoomreg = np.where(myDMO.dm.mass==myDMO.dm.mass.min())\n", "centro = nbe.real_center(myDMO.dm.pos3d[zoomreg],myDMO.dm.mass[zoomreg])\n", "\n", "myDMO.center_shift(centro)\n", "myDMO.r_virial(600,n=2.5)\n", "myDMO.r200\n", "myDMO.redefine(2.5)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[-0.01847012 -0.01124173 0.00994932]]\n" ] } ], "source": [ "if (center_in_pot):\n", " myGkpc = 6.673e-11*((1e-3/myDMO.p.kpctokm)**3)*myDMO.p.msuntokg#kpc^ 3 Msun^-1 s^-2\n", " pos = np.array(myDMO.dm.pos3d.reshape(len(myDMO.dm.pos3d)*3),dtype=np.float32)#*myDMO.p.kpctokm\n", " ok, acc, Phy = CF.getGravity(pos,myDMO.dm.mass,0.190,G=myGkpc)\n", " center_pot = myDMO.dm.pos3d[np.where(Phy==Phy.min())]\n", " print center_pot\n", " myDMO.center_shift(center_pot)\n", " myDMO.r_virial(600,n=2.5)\n", " myDMO.r200\n", " myDMO.redefine(2.5)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "9393588 9393588\n" ] } ], "source": [ "pos = np.array(myDMO.dm.pos3d.reshape(len(myDMO.dm.pos3d)*3),dtype=np.float32)\n", "phi_cord =myDMO.dm.phi\n", "\n", "mass = myDMO.dm.mass\n", "v = myDMO.dm.v\n", "print len(mass)*3, len(pos)\n", "r2 = myDMO.dm.pos3d[:,0]**2 + myDMO.dm.pos3d[:,1]**2 +myDMO.dm.pos3d[:,2]**2" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "ok,myDMO.dm.rho,_= CF.getDensity(np.array(myDMO.dm.pos3d.reshape(len(myDMO.dm.pos3d)*3),dtype=np.float32), myDMO.dm.mass)\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def abg_logprofile(x,p_s,r_s,al,be,ga):\n", " x = 10**x\n", " power = (be - ga) / (al)\n", " denominator = ((x/(r_s))**ga) * ((1 + (x / (r_s))**al)**power)\n", " return np.log10(10**p_s / denominator)\n", "\n", "def abg_profile(x,po,r_s,al,be,ga):\n", " power = (be - ga) / al\n", " denominator = ((x/r_s)**ga) * ((1 + (x / r_s)**al)**power)\n", " return (10**po) / denominator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Mass fit" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.024097491898402\n", "0.2 1.024097491898402\n" ] } ], "source": [ "Pcrit = myDMO.dm._p.rho_crit\n", "Mdm = myDMO.dm.mass.min()\n", "myradiuses = myDMO.dm.r[np.argsort(myDMO.dm.r)]\n", "tabN = np.cumsum(np.ones(len(myradiuses)))[1:]\n", "myradiuses = myradiuses[1:]\n", "Rp03 = np.sqrt(200/64.) * np.sqrt(4 * np.pi * Pcrit * tabN / 3. / Mdm ) * (myradiuses**1.5)/ np.log(tabN) \n", "val =0.6\n", "R_P03 = myradiuses[ np.where(Rp03 > val) ][0]\n", "\n", "\n", "print R_P03\n", "hsml= 0.2# R_P03\n", "print hsml,R_P03\n", "# R array logarithmic Bining\n", "r_p = np.logspace(np.log10(0.2*hsml),np.log10(hsml),15)\n", "# histogram of dm particles per logarithmic bin\n", "n_dm,r = np.histogram(myDMO.dm.r,bins=r_p)\n", "# edges of bins\n", "r1,r2 =r[:-1],r[1:]\n", "# shell's volume\n", "vol = 4.* np.pi * ((r2**3)-(r1**3)) / 3.\n", "r_size = r_p[1:]-r_p[:-1]\n", "# density per shell\n", "profileDMO_in = n_dm*myDMO.dm.mass.min()/vol\n", "# center of bins\n", "r_in = (r_p[:-1]+r_p[1:])/2.\n", "\n", "\n", "# R array logarithmic Bining\n", "r_p = np.logspace(np.log10(3*hsml),np.log10(2.5*myDMO.r200),150)\n", "# histogram of dm particles per logarithmic bin\n", "n_dm,r = np.histogram(myDMO.dm.r,bins=r_p)\n", "# edges of bins\n", "r1,r2 =r[:-1],r[1:]\n", "# shell's volume\n", "vol = 4.* np.pi * ((r2**3)-(r1**3)) / 3.\n", "r_size = r_p[1:]-r_p[:-1]\n", "# density per shell\n", "profileDMO = n_dm*myDMO.dm.mass.min()/vol\n", "# center of bins\n", "r = (r_p[:-1]+r_p[1:])/2.\n", "bin_size= (r_p[:-1]-r_p[1:])/2.\n", "rr = r\n", "\n", "\n", "Delta_rho = (myDMO.dm.mass.min() /vol) + (4*np.pi*(r**2)* (n_dm*myDMO.dm.mass.min()) * r_size / vol**2)\n", "Delta_rho2 = np.sqrt((myDMO.dm.mass.min()/np.sqrt(n_dm) /vol)**2 + (4*np.pi*(r**2)* (n_dm*myDMO.dm.mass.min()) * r_size / vol**2)**2)\n", "Delta_rho3 =(4*np.pi*(r**2)* (n_dm*myDMO.dm.mass.min()) * r_size / vol**2)\n", "Delta_rho4 =(myDMO.dm.mass.min() /vol)\n", "\n", "# extra estatistics from Cfalcon density\n", "mean = std = n = stdlog = np.array([])\n", "for i in range(len(r_p)-1):\n", " shell = np.where((myDMO.dm.r > r_p[i])&(myDMO.dm.r < r_p[i+1])&(myDMO.dm.r > hsml))\n", " n = np.append(n,len(shell[0]))\n", " mean = np.append(mean,np.mean(myDMO.dm.rho[shell]))\n", " std = np.append(std,np.std(myDMO.dm.rho[shell]))\n", " stdlog = np.append(stdlog,np.std(np.log10(myDMO.dm.rho[shell])))\n", " \n", "n_dm_bin = n\n", "m_obs = n_dm*myDMO.dm.mass.min()\n", "n = np.array([len(myDMO.dm.mass[myDMO.dm.r" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FCN = 1.32202099592TOTAL NCALL = 170NCALLS = 170
EDM = 7.13603007169e-05GOAL EDM = 1e-05\n", " UP = 1.0
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+NameValueHesse ErrorMinos Error-Minos Error+Limit-Limit+Fixed?
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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "chi_rho = 1.32, chi_bin = 0.10\n" ] } ], "source": [ "\n", "\n", "m_rho = Minuit(chi2_rho_log, al=1., fix_al=True,\n", " po=7.0, error_po=0.01, limit_po =(2.,11.),\n", " r_s=7.3, error_r_s=0.1, limit_r_s=(1.,30),\n", " be=3., error_be=0.1, limit_be =(2.5,3.5),\n", " ga=1., error_ga=0.1, limit_ga =(.5,1.5))\n", "m_rho.migrad();\n", "chirhorho = chi2_rho_log(m_rho.values['po'] ,m_rho.values['r_s'],m_rho.values['al'],m_rho.values['be'],m_rho.values['ga'])\n", "chibinrho= chi2_mass_bin_log(m_rho.values['po'] ,m_rho.values['r_s'],m_rho.values['al'],m_rho.values['be'],m_rho.values['ga'])\n", "print \"chi_rho = {0:1.2f}, chi_bin = {1:1.2f}\".format(chirhorho,chibinrho)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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FCN = 0.101171430934TOTAL NCALL = 195NCALLS = 195
EDM = 6.73380771015e-05GOAL EDM = 1e-05\n", " UP = 1.0
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ValidValid ParamAccurate CovarPosDefMade PosDef
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+NameValueHesse ErrorMinos Error-Minos Error+Limit-Limit+Fixed?
0po7.060861.87888411No
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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "chi_rho = 1.35, chi_bin = 0.10\n" ] } ], "source": [ "m_bin = Minuit(chi2_mass_bin_log, al=1., fix_al=True,\n", " po=5.0, error_po=0.01, limit_po =(4.,11.),\n", " r_s=7.3, error_r_s=0.1, limit_r_s=(1.,30),\n", " be=3., error_be=0.01, limit_be =(2.5,3.5),\n", " ga=1., error_ga=0.01, limit_ga =(.5,1.5))\n", "m_bin.migrad();\n", "\n", "chirhobin = chi2_rho_log(m_bin.values['po'] ,m_bin.values['r_s'],m_bin.values['al'],m_bin.values['be'],m_bin.values['ga'])\n", "chibinbin= chi2_mass_bin_log(m_bin.values['po'] ,m_bin.values['r_s'],m_bin.values['al'],m_bin.values['be'],m_bin.values['ga'])\n", "print \"chi_rho = {0:1.2f}, chi_bin = {1:1.2f}\".format(chirhobin,chibinbin)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chi_rho = 3.22, chi_bin = 0.28\n" ] } ], "source": [ "#polfit\n", "chirhopol = chi2_rho_log(7.663,5.552,1,2.636,0.819)\n", "chibinpol= chi2_mass_bin_log(7.663,5.552,1,2.636,0.819)\n", "print \"chi_rho = {0:1.2f}, chi_bin = {1:1.2f}\".format(chirhopol,chibinpol)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false, "hide_input": false, "scrolled": true }, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
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');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "\n", "fig, ax = plt.subplots(4,1,figsize=[8,12])\n", "for i in range(4):\n", " ax[i].set_xscale('log')\n", " ax[i].set_yscale('log')\n", "\n", "#ax[0].yaxis.get_major_formatter().set_powerlimits((0, 2))\n", "#ax[1].yaxis.get_major_formatter().set_powerlimits((0, 2))\n", "#ax[2].yaxis.get_major_formatter().set_powerlimits((0, 2))\n", "#ax[3].yaxis.get_major_formatter().set_powerlimits((0, 2))\n", "\n", "\n", "ax[3].set_xlabel(r'$\\rm r\\, [kpc]$',fontsize=18)\n", "ax[0].set_ylabel(r'$\\langle v^{-2} \\rangle$$\\rm \\, [km/s]^{-2}$',fontsize=18)\n", "ax[1].set_ylabel(r'$\\langle v^{-1} \\rangle$$\\rm \\,[km/s]^{-1}$',fontsize=18)\n", "ax[2].set_ylabel(r'$\\langle v \\rangle$$\\rm \\,[km/s]$',fontsize=18)\n", "ax[3].set_ylabel(r'$\\langle v^{2} \\rangle$$\\rm \\,[km/s]^2$',fontsize=18)\n", "\n", "\n", "\n", "#ax[0].set_ylim([0,1.4*np.nanmax(m_2)])\n", "#ax[1].set_ylim([0,1.4*np.nanmax(m_1)])\n", "#ax[2].set_ylim([0,1.4*np.nanmax(m1)])\n", "#ax[3].set_ylim([0,1.4*np.nanmax(m2)])\n", "\n", "ax[0].set_ylim([0.5*m_2.min(),2*m_2.max()])\n", "ax[1].set_ylim([0.5*m_1.min(),2*m_1.max()])\n", "ax[2].set_ylim([0.5*m1.min(),2*m1.max()])\n", "ax[3].set_ylim([0.5*m2.min(),2*m2.max()])\n", "\n", "r_v_c = (r_v[:-1]+r_v[1:])/2.\n", "\n", "ax[0].set_xlim([r_v_c.min(),v_av[:,0].max()])\n", "ax[1].set_xlim([r_v_c.min(),v_av[:,0].max()])\n", "ax[2].set_xlim([r_v_c.min(),v_av[:,0].max()])\n", "ax[3].set_xlim([r_v_c.min(),v_av[:,0].max()])\n", "\n", "ax[0].axvline(x=myDMO.r200,color='k',linestyle='--')\n", "ax[1].axvline(x=myDMO.r200,color='k',linestyle='--')\n", "ax[2].axvline(x=myDMO.r200,color='k',linestyle='--')\n", "ax[3].axvline(x=myDMO.r200,color='k',linestyle='--')\n", "\n", "\n", "alpha=0.2\n", "\n", "ax[0].plot(r_v_c,m_2,lw=2)\n", "#ax[0].fill_between(r_v_c,m_2-std_2,m_2+std_2,alpha=alpha)\n", "ax[0].plot(v_2_av[:,0],v_2_av[:,1],\"k\",lw=1.5)\n", "ax[0].plot(v_2_av_m[:,0],v_2_av_m[:,1],\"r\",lw=1.5)\n", "fig.text(0.3,.9,r\"$\\rm\"+ hydro.name +\" $\",fontsize=30)\n", "fig.text(0.35,.87,r\"$\\rm DMO $\",fontsize=25)\n", "\n", "\n", "ax[1].plot(r_v_c,m_1,lw=2,label=r\"$\\rm Data$\")\n", "#ax[1].fill_between(r_v_c,m_1-std_1,m_1+std_1,alpha=alpha)\n", "\n", "ax[1].plot(v_1_av[:,0],v_1_av[:,1],\"k\",lw=1.5,label=r\"$\\rm Eddington$\")\n", "ax[1].plot(v_1_av_m[:,0],v_1_av_m[:,1],\"r\",lw=1.5,label=r\"$\\rm Maxwellian$\")\n", "\n", "ax[2].plot(r_v_c,m1,lw=2)\n", "#ax[2].fill_between(r_v_c,m1-std1,m1+std1,alpha=alpha)\n", "\n", "ax[2].plot(v_av[:,0],v_av[:,1],\"k\",lw=1.5)\n", "ax[2].plot(v_av_m[:,0],v_av_m[:,1],\"r\",lw=1.5)\n", "\n", "ax[3].plot(r_v_c,m2,lw=2,label=r\"$\\rm Data$\")\n", "#ax[3].fill_between(r_v_c,m2-std2,m2+std2,alpha=alpha)\n", "\n", "\n", "ax[3].plot(v2_av[:,0],v2_av[:,1],\"k\",lw=1.5,label=r\"$\\rm Eddington$\")\n", "ax[3].plot(v2_av_m[:,0],v2_av_m[:,1],\"r\",lw=1.5,label=r\"$\\rm Maxwellian$\")\n", "\n", "legend = ax[1].legend(loc='upper right', ncol=2, shadow=False, fontsize=textsize)\n", "frame = legend.get_frame()\n", "\n", "fig.tight_layout(h_pad=-1.5)\n", "ax[2].text(170,1e7,r'R$_{200}$',fontsize=17)\n", "\n", "\n", "ax[0].tick_params(axis='y', which='major', labelsize=15, size=5,width=1.2)\n", "ax[0].tick_params(axis='x', which='major', labelsize=0, size=5,width=1.2)\n", "ax[0].tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n", "ax[1].tick_params(axis='y', which='major', labelsize=15, size=5,width=1.2)\n", "ax[1].tick_params(axis='x', which='major', labelsize=0, size=5,width=1.2)\n", "ax[1].tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n", "ax[2].tick_params(axis='y', which='major', labelsize=15, size=5,width=1.2)\n", "ax[2].tick_params(axis='x', which='major', labelsize=0, size=5,width=1.2)\n", "ax[2].tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n", "ax[3].tick_params(axis='both', which='major', labelsize=15, size=5,width=1.2)\n", "ax[3].tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n", "fig.tight_layout(h_pad=-1.5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" }, "latex_envs": { "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 0 } }, "nbformat": 4, "nbformat_minor": 1 }