{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Catmull-Rom splines ##" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Definition of this class of curves ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Catmull-Rom interpolation problem defined in [Catmull, E. and R. Rom, *A Class of Local Interpolationg Splines*, in Barnhill R.E. and R.F. Riesenfeld (eds.), Computer Aided Geometric Design, Academic Press, New York, 1974.] is formulated as follows:\n", "\n", "Given $n+1$ points, $P_0, P_1, \\ldots, P_n$, $n\\geq 3$, find a piecewise cubic curve, parameterized by\n", "$c:[1, n-1]\\to\\mathbb{R}^d$ (usually, d=2,3) such \n", "that $c(i)=P_{i}$, for $i\\in\\{1,2\\ldots, n-1\\}$, and the tangent vector at each interpolatory point, $P_i$, $i=\\overline{1, n-1}$, to be colinear with the vector $\\overrightarrow{P_{i-1}P_{i+1}}$:\n", "\n", "$$\\vec{\\dot{c}}(i)=s\\overrightarrow{P_{i-1}P_{i+1}},\n", "$$ where $s\\in(0,1]$. Usually one takes s=0.5.\n", "\n", "Hence given n+1 points, $P_0, P_1, \\ldots, P_n$, a CR curve interporlates only the points $P_1, P_2, \\ldots, P_{n-1}$.\n", "The first and the last point influence only the direction of tangent at $P_1$, respectively, $P_{n-1}$.\n", "\n", "\n", "\n", "Since the distance between two consecutive knots, $t_i=i$, $t_{i+1}=i+1$ is constant, such a curve is called uniform parameterized Catmull-Rom curve.\n", "\n", "Being a cubic above each interval $[i, i+1]$, an arc of CR curve on such an interval can be defined\n", "as a Bézier curve of control points ${\\bf b}_0, {\\bf b}_1, {\\bf b}_2, {\\bf b}_3$,\n", "with\n", "${\\bf b}_0=P_i, {\\bf b}_3=P_{i+1}$.\n", "\n", "But the tangent at end points, ${\\bf b}_0$ and ${\\bf b}_3$, of a Bézier curve, is\n", " $3\\overrightarrow{{\\bf b}_0{\\bf b}_1}$, respectively $3\\overrightarrow{{\\bf b}_2{\\bf b}_3}$.\n", "Thus we get:\n", "\n", "$${\\bf b}_1=P_i+s(P_{i+1}-P_{i-1})/3, \\:\\: {\\bf b}_2=P_{i+1}-s(P_{i+2}-P_{i})/3$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "Below we illustrate the above stated properties of a CR curve, defined by 7 points. Attached to the third arc, joining the points $P_3, P_4$,\n", "is the Bézier control polygon defining that arc of curve. The tangent at $P_2$ is obviously parallel to \n", "$\\overrightarrow{P_1P_3}$." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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FgSVLllj//v1t9OjRsagvlYQABCBQCgIIiI8yAuLgh4A44FEUAhCIBYGnn37a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"text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import Image\n", "Image(filename='Imag/Catmull-Rom-curve.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Catmull-Rom interpolating curves can be evaluated\n", "at a point using a recursive scheme similar to the [de Boor algorithm](http://nbviewer.jupyter.org/github/empet/geom_modeling/blob/master/FP-Bezier-Bspline.ipynb) for B-spline curves.\n", "\n", "Usually a cubic spline curve is $C^2$ at knots. Although the CR curves are only $C^1$ at each knot, \n", "they are sometimes called Catmull Rom spline curves, due to the similarities of the algorithms of\n", "evaluation, and other common properties.\n" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Let us point out the drawback of the uniform parameterization, that led to defining CR splines with\n", "non-uniform knots.\n", "\n", "A $C^1$-parameterization, $c:[a,b]\\to\\mathbb{R}^d$, of a curve can be interpreted as defining the motion of the point c(t), along the trace of $c$, during the time from a to b.\n", "\n", "When the parameterization of a CR curve is uniform, the point $c(t)$ spends the same amount of time on each arc of ends $P_i, P_{i+1}$, $i=1,2, ...n-1$, irrespective of the distance between $P_i, P_{i+1}$.\n", "\n", "If the distance between two data points is large, the point c(t)\n", "moves with a high speed. If the next two interpolatory points, $P_{i+1}, P_{i+2}$, are closer, then the moving point will overshoot since it cannot abruptly change its speed.\n", "\n", "Barry and Goldman [P. J. Barry, R. N. Goldman, *A recursive evaluation algorithm for a class of Catmullâ€“Rom splines*, SIGGRAPH Computer Graphics, 22(4):199-204, 1988] extended the definition of uniform parameterized CR splines to curves whose parameterization incorporates the\n", "distance between any two adjacent interpolatory points. \n", "\n", "Namely, given the points $P_0, P_1, \\ldots, P_n$, one defines a knot sequence, $t_0, t_1, \\ldots, t_{n}$ as follows:\n", " \n", "$$\\begin{array}{lll}t_0&=&0\\\\\n", " t_i&=&t_{i-1}+||\\overrightarrow{P_{i-1}P_i}||^\\alpha, \\quad \\alpha\\in[0,1]\\end{array}$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " A $C^1$-piecewise cubic, that interpolates the given points, i.e. $c(t_i)=P_i$, $i=1,2, \\ldots, n-1$, is defined at any $u\\in[t_i, t_{i+1}]$ through a recursive scheme in which are involved only four points, $P_{i-1}, P_i, P_{i+1}, P_{i+2}$\n", " and the knots $t_{i-1}, t_i, t_{i+1}, t_{i+2}$:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$$P_j^r=(1-\\omega^{r-1}_j)P^{r-1}_j+\\omega^{r-1}_jP^{r-1}_{j+1}, \\quad r=1,2,\\quad j=i-1, i, i+1, i+2,\n", "$$\n", "\n", "with $\\omega^r_j(u)=\\displaystyle\\frac{u-t_j}{t_{j+1+r}-t_j}$. The superscript $r$ points out the level of recursion. $P_j^0=P_j$.\n", "\n", "\n", "The last two points, $P^2_{i-1}$, $P^2_{i}$, are finally interpolated linearly, to get $c(u)$, the point on the CR curve corresponding to the parameter $u\\in[t_i, t_{i+1}]$:\n", "\n", "$$c(u)=\\left(1-\\displaystyle\\frac{u-t_i}{t_{i+1}-t_i}\\right) P^2_{i-1}+\\displaystyle\\frac{u-t_i}{t_{i+1}-t_i} P^2_{i}$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We note that in the first two steps, the points $P_j^r$, $r=1,2$, are computed via de Boor algorithm for B-splines, while in the last step, $c(u)$ is computed according to the [Neville algorithm](https://en.wikipedia.org/wiki/Neville%27s_algorithm) for evaluating Lagrange polynomials." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The parameter $\\alpha$ in the definition of knots controls the geometry of the interpolating CR curve.\n", "For $\\alpha=0.5$ the corresponding CR curve is called centripetal Catmull-Rom curve, for $\\alpha=1$, chordal Catmull\n", "Rom curve, while for $\\alpha=0$ we get the initial uniform parameterized CR spline.\n", "\n", "For $\\alpha$ close to $0$ the corresponding CR curve can exhibit singular points (self intersections or cusps) within short curve segments(with small distance between $P_i, P_{i+1}$).\n", "\n", "In [C Yuksel, S Schaefer, J Keyser,\n", "*Parameterization and Applications of Catmull-Rom Curves*,\n", "Computer Aided Design, 43, 7, 2011] it was deduced that the optimal parameter that corresponds to CR splines with no singular points is $\\alpha=0.5$.\n", "Moreover a centripetal CR curve follows more tightly the interpolatory points than CR curves corresponding to $\\alpha$ close to 0 or to 1.\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "That is why centripetal Catmull-Rom splines are now widely used in interactive generation of interpolating curves." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Python implementation of the Catmull-Rom spline generation ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Instead of the above mixture of the de Boor and Neville algorithm we generate each segment of CR curve,\n", "as a Bezier curve.\n", "\n", "Over each interval $[t_i, t_{i+1}]$, the CR curve is a cubic polynomial curve, hence it can be defined as\n", "a Bézier curve, parameterized over $[0,1]$. Theoretically, the standard polynomial parameterization\n", "is obtained applying (using a Computer Algebra System) the two steps of de Boor algorithm defined above, and a step of the Neville algo.\n", "Then this parameterization is converted to one in which the polynomial components are expressed \n", "in Bernstein basis, to get the Bézier form of that polynomial segment of curve.\n", "\n", "The expression of the Bézier control points as combinations of four consecutive interpolatory \n", "points, $P_{0}, P_1, P_{2}, P_{3}$, involved in the definition of a CR segment, is given in the function ctrl_bezier(P, d). d is a list of values involved in knot definition, $d_j=||\\overrightarrow{P_{j}P_{j+1}}||^\\alpha$, $j=0,1,2$." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define the function knot_interval, that computes the values \n", "$d_j=||\\overrightarrow{P_{j}P_{j+1}}||^\\alpha$, $j=\\overline{0, n-1}$. If we want define a closed curve, then we extend the list of points $P_0, P_1, \\ldots, P_n$ with $P_0, P_1, P_2$:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def knot_interval(i_pts, alpha=0.5, closed=False):\n", " if len(i_pts)<4:\n", " raise ValueError('CR-curves need at least 4 interpolatory points')\n", " #i_pts is the list of interpolatory points P[0], P[1], ... P[n]\n", " if closed:\n", " i_pts+=[i_pts[0], i_pts[1], i_pts[2]]\n", " i_pts=np.array(i_pts)\n", " dist=np.linalg.norm(i_pts[1:, :]-i_pts[:-1,:], axis=1)\n", " return dist**alpha\n", " \n", "\n", "def ctrl_bezier(P, d):\n", " #Associate to 4 consecutive interpolatory points and the corresponding three d-values, \n", " #the Bezier control points\n", " if len(P)!=len(d)+1!=4:\n", " raise ValueError('The list of points and knot intervals have inappropriate len ')\n", " P=np.array(P) \n", " bz=[0]*4\n", " bz[0]=P[1]\n", " bz[1]=(d[0]**2*P[2]-d[1]**2*P[0] +(2*d[0]**2+3*d[0]*d[1]+d[1]**2)*P[1])/(3*d[0]*(d[0]+d[1]))\n", " bz[2]=(d[2]**2*P[1]-d[1]**2*P[3] +(2*d[2]**2+3*d[2]*d[1]+d[1]**2)*P[2])/(3*d[2]*(d[1]+d[2]))\n", " bz[3]=P[2]\n", " return bz\n", "\n", "def Bezier_curve(bz, nr=100):\n", " #implements the de Casteljau algorithm to compute nr points on a Bezier curve\n", " \n", " t=np.linspace(0,1, nr)\n", " N=len(bz) \n", " points=[]# the list of points to be computed on the Bezier curve\n", " for i in range(nr):#for each parameter t[i] evaluate a point on the Bezier curve \n", " #via De Casteljau algorithm\n", " aa=np.copy(bz) \n", " for r in range(1,N):\n", " aa[:N-r,:]=(1-t[i])*aa[:N-r,:]+t[i]*aa[1:N-r+1,:]# convex combination\n", " points.append(aa[0,:]) \n", " return points \n", "\n", "def Catmull_Rom(i_pts, alpha=0.5, closed=False):\n", " #returns the list of points computed on the interpolating CR curve\n", " #i_pts the list of interpolatory points P[0], P[1], ...P[n]\n", " curve_pts=[]#the list of all points to be computed on the CR curve\n", " d=knot_interval(i_pts, alpha=alpha, closed=closed)\n", " for k in range(len(i_pts)-3):\n", " cb=ctrl_bezier(i_pts[k:k+4], d[k:k+3])\n", " curve_pts.extend(Bezier_curve(cb, nr=100))\n", " \n", " return np.array(curve_pts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we give a list of points and define the CR curve corresponding to $\\alpha=0,0.5,1$:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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mk5oz9qWx5MwQYaXl/v1uamfcuBu2xsba8uUUy52bHfsLxv1evua/o4P79IEG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\nJiKSrCmgSLL177+upP3SpZZ2y6pTddm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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "P=[[-0.72, -0.3], [0,0], [1., 0.8], [1.1, 0.5], [2.7, 1.2], [3.4, 0.27]]\n", "\n", "curve0=Catmull_Rom(P, alpha=0, closed=False)\n", "curve1=Catmull_Rom(P, alpha=0.5, closed=False)\n", "curve2=Catmull_Rom(P, alpha=1.0, closed=False)\n", "xp, yp=zip(*P)\n", "\n", "fig=plt.figure(figsize=(9,6))\n", "plt.plot(curve0[:,0], curve0[:,1], 'r', xp, yp, 'go' )\n", "plt.plot(curve1[:,0], curve1[:,1], 'g')\n", "plt.plot(curve2[:,0], curve2[:,1], 'b')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The green curve is the centripetal CR spline interpolating the central 4 from 6 points. It folows closely\n", "the given interpolatory points." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In order to get more insights into CR curves properties we give the possibility to generate them interactively.\n", "Choose the interpolatory points, by clicking the left mouse button at the desired position. When the right button is pressed, the corresponding curve is generated:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#enable interactivity in notebook:\n", "%matplotlib notebook " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def curve_plot(i_pts, alpha=0.5, closed=False):\n", " curve_pts=Catmull_Rom(i_pts, alpha, closed=closed)\n", " # plot the interpolating curve\n", " plt.plot(curve_pts[:,0], curve_pts[:,1], 'b') " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class catrom(object): \n", " \n", " def __init__(self, alpha=0.5, closed=False):\n", " self.interp_pts=[] # list of interpolating points\n", " self.alpha=alpha\n", " self.closed=closed# boolean value\n", " def callback(self, event): #select interpolating points with left mouse button click\n", " if event.button==1 and event.inaxes:\n", " x,y = event.xdata, event.ydata\n", " self.interp_pts.append([x,y]) \n", " plt.plot(x, y, 'bo') \n", " \n", " elif event.button==3: #press right button to plot the curve\n", " curve_plot(self.interp_pts, self.alpha, self.closed)\n", " plt.draw() \n", " \n", " else: pass\n", " \n", " def caxis(self):#define axes for plot\n", " fig = plt.figure(figsize=(8, 6))\n", " ax = fig.add_subplot(111)\n", " \n", " ax.set_xlim(0,10)\n", " ax.set_ylim(0,10)\n", " ax.grid('on') \n", " ax.set_autoscale_on(False)\n", " fig.canvas.mpl_connect('button_press_event', self.callback)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\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 â‰¥ 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 = $(' ');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", "$(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " this.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " ' ');\n", " var titletext =$(\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 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);\n", " canvas.attr('height', height);\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": [ "cv=catrom(closed=True)\n", "cv.caxis()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\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 â‰¥ 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 = $(' ');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", "$(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " this.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " ' ');\n", " var titletext =$(\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 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);\n", " canvas.attr('height', height);\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 = $(' ')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button =$('