Created
January 30, 2015 21:26
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ipython_3d_scatter_widget
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| { | |
| "metadata": { | |
| "name": "", | |
| "signature": "sha256:06246424bcbad603fff82c9486defe01de3ff31ab0b8afef346af09e651cc87e" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "heading", | |
| "level": 1, | |
| "metadata": {}, | |
| "source": [ | |
| "Dots on a helix" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 5, | |
| "metadata": {}, | |
| "source": [ | |
| "IPython widgets with 3d Plotly graphs" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "import plotly.plotly as py\n", | |
| "from plotly.graph_objs import *\n", | |
| "from plotly.widgets import GraphWidget\n", | |
| "from IPython.display import display, HTML, Image\n", | |
| "import numpy as np\n", | |
| "import math\n", | |
| "from IPython.html import widgets\n", | |
| "import colorlover as cl" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 51 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 5, | |
| "metadata": {}, | |
| "source": [ | |
| "Widgets can't be displayed on nbviewer, but this is what you'll see if you download the notebook:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "Image(url='http://i.imgur.com/CzMRuMo.gif')" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<img src=\"http://i.imgur.com/CzMRuMo.gif\"/>" | |
| ], | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 53, | |
| "text": [ | |
| "<IPython.core.display.Image at 0x1074e9310>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 53 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "z = np.arange(1,20,0.1)\n", | |
| "x = np.cos(4*z)*( np.power(z+1,3) )\n", | |
| "y = np.sin(4*z)*( np.power(z+1,3) )" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 26 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "colors = cl.interp( cl.scales['11']['div']['RdYlBu'], z)\n", | |
| "HTML( cl.to_html( colors ) )" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
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| ], | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 33, | |
| "text": [ | |
| "<IPython.core.display.HTML at 0x1074db0d0>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 33 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "class shifter:\n", | |
| " def __init__(self):\n", | |
| " self.x = np.cos(4*z)*( np.power(z+1,3) )\n", | |
| " self.y = np.sin(4*z)*( np.power(z+1,3) )\n", | |
| " self.colors = cl.interp( cl.scales['11']['div']['RdYlBu'], z)\n", | |
| " \n", | |
| " def on_phase_change(self, name, old_value, new_value):\n", | |
| " self.x = np.cos(4*z+new_value)*( np.power(z+1,3) )\n", | |
| " self.y = np.sin(4*z+new_value)*( np.power(z+1,3) )\n", | |
| " self.replot()\n", | |
| " \n", | |
| " def replot(self):\n", | |
| " g.restyle({ 'x': [self.x], 'y': [self.y] })\n", | |
| "\n", | |
| "p_slider = widgets.FloatSliderWidget(min=0,max=10,value=1,step=0.05)\n", | |
| "p_slider.description = 'Phase shift'\n", | |
| "p_slider.value = 1\n", | |
| "\n", | |
| "p_state = shifter()\n", | |
| "p_slider.on_trait_change(p_state.on_phase_change, 'value')" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 42 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": [ | |
| "Create an empty graph - load only once in the beginning" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 5, | |
| "metadata": {}, | |
| "source": [ | |
| "(This graph won't load in nbviewer because it uses widgets, you have to download the notebook)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "g.restyle( { 'x':[x],\n", | |
| " 'y':[y],\n", | |
| " 'z':[z], \n", | |
| " 'marker':{'size':np.power(z,1.2),'opacity':0.9,'color':colors}, \n", | |
| " 'type':'scatter3d' } )" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 46 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "g = GraphWidget()\n", | |
| "display(p_slider)\n", | |
| "display(g)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 45 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": [ | |
| "Reference" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "help(Scatter3d)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": [ | |
| "Help on class Scatter3d in module plotly.graph_objs.graph_objs:\n", | |
| "\n", | |
| "class Scatter3d(PlotlyTrace)\n", | |
| " | A dictionary-like object for representing a 3D scatter trace in plotly.\n", | |
| " | \n", | |
| " | Quick method reference:\n", | |
| " | \n", | |
| " | Scatter3d.update(changes)\n", | |
| " | Scatter3d.strip_style()\n", | |
| " | Scatter3d.get_data()\n", | |
| " | Scatter3d.to_graph_objs()\n", | |
| " | Scatter3d.validate()\n", | |
| " | Scatter3d.to_string()\n", | |
| " | Scatter3d.force_clean()\n", | |
| " | \n", | |
| " | Valid keys:\n", | |
| " | \n", | |
| " | x [required=True] (value=list or 1d numpy array of numbers, strings,\n", | |
| " | datetimes or list of lists or 2d numpy array of numbers) (streamable):\n", | |
| " | Sets the x coordinates of the points of this 3D scatter trace. If\n", | |
| " | 'x' is linked to a list or 1d numpy array of strings, then the x\n", | |
| " | coordinates are integers, 0, 1, 2, 3, ..., labeled on the x-axis by\n", | |
| " | the list or 1d numpy array of strings linked to 'x'.\n", | |
| " | \n", | |
| " | y [required=True] (value=list or 1d numpy array of numbers, strings,\n", | |
| " | datetimes or list of lists or 2d numpy array of numbers) (streamable):\n", | |
| " | Sets the y coordinates of the points of this 3D scatter trace. If\n", | |
| " | 'y' is linked to a list or 1d numpy array of strings, then the y\n", | |
| " | coordinates are integers, 0, 1, 2, 3, ..., labeled on the y-axis by\n", | |
| " | the list or 1d numpy array of strings linked to 'y'.\n", | |
| " | \n", | |
| " | z [required=True] (value=list or 1d numpy array of numbers, strings,\n", | |
| " | datetimes or list of lists or 2d numpy array of numbers) (streamable):\n", | |
| " | Sets the z coordinates of the points of this scatter trace. If 'z'\n", | |
| " | is linked to a list or 1d numpy array of strings, then the z\n", | |
| " | coordinates are integers, 0, 1, 2, 3, ..., labeled on the z-axis by\n", | |
| " | the list or 1d numpy array of strings linked to 'z'.\n", | |
| " | \n", | |
| " | mode [required=False] (value='lines' | 'markers' | 'text' |\n", | |
| " | 'lines+markers' | 'lines+text' | 'markers+text' | 'lines+markers+text'):\n", | |
| " | Plotting mode for this 3D scatter trace. If the mode includes 'text'\n", | |
| " | then the 'text' will appear at the (x,y) points, otherwise it will\n", | |
| " | appear on hover.\n", | |
| " | \n", | |
| " | name [required=False] (value=a string):\n", | |
| " | The label associated with this trace. This name will appear in the\n", | |
| " | column header in the online spreadsheet.\n", | |
| " | \n", | |
| " | text [required=False] (value=list or 1d numpy array of strings)\n", | |
| " | (streamable):\n", | |
| " | The text elements associated with each (x,y,z) pair in this 3D\n", | |
| " | scatter trace. If the scatter 'mode' does not include 'text' then\n", | |
| " | elements linked to 'text' will appear on hover only. In contrast, if\n", | |
| " | 'text' is included in 'mode', the elements in 'text' will be\n", | |
| " | rendered on the plot at the locations specified in part by their\n", | |
| " | corresponding (x,y,z) coordinate pair and the 'textposition' key.\n", | |
| " | \n", | |
| " | error_z [required=False] (value=ErrorZ object | dictionary-like object)\n", | |
| " | (streamable):\n", | |
| " | Links a dictionary-like object describing the z-axis error bars that\n", | |
| " | can be drawn from the (x,y,z) coordinates of this 3D scatter trace.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.ErrorZ)`\n", | |
| " | \n", | |
| " | error_y [required=False] (value=ErrorY object | dictionary-like object)\n", | |
| " | (streamable):\n", | |
| " | Links a dictionary-like object describing the y-axis error bars that\n", | |
| " | can be drawn from the (x,y,z) coordinates of this 3D scatter trace.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.ErrorY)`\n", | |
| " | \n", | |
| " | error_x [required=False] (value=ErrorX object | dictionary-like object)\n", | |
| " | (streamable):\n", | |
| " | Links a dictionary-like object describing the x-axis error bars that\n", | |
| " | can be drawn from the (x,y,z) coordinates of this 3D scatter trace.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.ErrorX)`\n", | |
| " | \n", | |
| " | marker [required=False] (value=Marker object | dictionary-like object)\n", | |
| " | (streamable):\n", | |
| " | Links a dictionary-like object containing marker style parameters\n", | |
| " | for this 3D scatter trace. Has an effect only if 'mode' contains\n", | |
| " | 'markers'.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.Marker)`\n", | |
| " | \n", | |
| " | line [required=False] (value=Line object | dictionary-like object)\n", | |
| " | (streamable):\n", | |
| " | Links a dictionary-like object containing line parameters for this\n", | |
| " | 3D scatter trace. Has an effect only if 'mode' contains 'lines'.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.Line)`\n", | |
| " | \n", | |
| " | textposition [required=False] (value='top left' | 'top' (or 'top\n", | |
| " | center')| 'top right' | 'left' (or 'middle left') | '' (or 'middle\n", | |
| " | center') | 'right' (or 'middle right') | 'bottom left' | 'bottom' (or\n", | |
| " | 'bottom center') | 'bottom right'):\n", | |
| " | Sets the position of the text elements in the 'text' key with\n", | |
| " | respect to the data points. By default, the text elements are\n", | |
| " | plotted directly at the (x,y,z) coordinates.\n", | |
| " | \n", | |
| " | scene [required=False] (value='scene1' | 'scene2' | 'scene3' | etc.):\n", | |
| " | This key determines the scene on which this trace will be plotted\n", | |
| " | in.\n", | |
| " | \n", | |
| " | stream [required=False] (value=Stream object | dictionary-like object):\n", | |
| " | Links a dictionary-like object that initializes this trace as a\n", | |
| " | writable-stream, for use with the streaming API.\n", | |
| " | \n", | |
| " | For more, run `help(plotly.graph_objs.Stream)`\n", | |
| " | \n", | |
| " | visible [required=False] (value=a boolean: True | False):\n", | |
| " | Toggles whether or not this object will be visible on the rendered\n", | |
| " | figure.\n", | |
| " | \n", | |
| " | type [required=False] (value='scatter3d'):\n", | |
| " | Plotly identifier for this data's trace type.\n", | |
| " | \n", | |
| " | Method resolution order:\n", | |
| " | Scatter3d\n", | |
| " | PlotlyTrace\n", | |
| " | PlotlyDict\n", | |
| " | __builtin__.dict\n", | |
| " | __builtin__.object\n", | |
| " | \n", | |
| " | Methods inherited from PlotlyTrace:\n", | |
| " | \n", | |
| " | __init__(self, *args, **kwargs)\n", | |
| " | \n", | |
| " | to_string(self, level=0, indent=4, eol='\\n', pretty=True, max_chars=80)\n", | |
| " | Returns a formatted string showing graph_obj constructors.\n", | |
| " | \n", | |
| " | Example:\n", | |
| " | \n", | |
| " | print(obj.to_string())\n", | |
| " | \n", | |
| " | Keyword arguments:\n", | |
| " | level (default = 0) -- set number of indentations to start with\n", | |
| " | indent (default = 4) -- set indentation amount\n", | |
| " | eol (default = '\\n') -- set end of line character(s)\n", | |
| " | pretty (default = True) -- curtail long list output with a '...'\n", | |
| " | max_chars (default = 80) -- set max characters per line\n", | |
| " | \n", | |
| " | ----------------------------------------------------------------------\n", | |
| " | Methods inherited from PlotlyDict:\n", | |
| " | \n", | |
| " | __setitem__(self, key, value)\n", | |
| " | \n", | |
| " | force_clean(self, caller=True)\n", | |
| " | Attempts to convert to graph_objs and call force_clean() on values.\n", | |
| " | \n", | |
| " | Calling force_clean() on a PlotlyDict will ensure that the object is\n", | |
| " | valid and may be sent to plotly. This process will also remove any\n", | |
| " | entries that end up with a length == 0.\n", | |
| " | \n", | |
| " | Careful! This will delete any invalid entries *silently*.\n", | |
| " | \n", | |
| " | get_data(self)\n", | |
| " | Returns the JSON for the plot with non-data elements stripped.\n", | |
| " | \n", | |
| " | get_ordered(self, caller=True)\n", | |
| " | \n", | |
| " | strip_style(self)\n", | |
| " | Strip style from the current representation.\n", | |
| " | \n", | |
| " | All PlotlyDicts and PlotlyLists are guaranteed to survive the\n", | |
| " | stripping process, though they made be left empty. This is allowable.\n", | |
| " | \n", | |
| " | Keys that will be stripped in this process are tagged with\n", | |
| " | `'type': 'style'` in graph_objs_meta.json.\n", | |
| " | \n", | |
| " | This process first attempts to convert nested collections from dicts\n", | |
| " | or lists to subclasses of PlotlyList/PlotlyDict. This process forces\n", | |
| " | a validation, which may throw exceptions.\n", | |
| " | \n", | |
| " | Then, each of these objects call `strip_style` on themselves and so\n", | |
| " | on, recursively until the entire structure has been validated and\n", | |
| " | stripped.\n", | |
| " | \n", | |
| " | to_graph_objs(self, caller=True)\n", | |
| " | Walk obj, convert dicts and lists to plotly graph objs.\n", | |
| " | \n", | |
| " | For each key in the object, if it corresponds to a special key that\n", | |
| " | should be associated with a graph object, the ordinary dict or list\n", | |
| " | will be reinitialized as a special PlotlyDict or PlotlyList of the\n", | |
| " | appropriate `kind`.\n", | |
| " | \n", | |
| " | update(self, dict1=None, **dict2)\n", | |
| " | Update current dict with dict1 and then dict2.\n", | |
| " | \n", | |
| " | This recursively updates the structure of the original dictionary-like\n", | |
| " | object with the new entries in the second and third objects. This\n", | |
| " | allows users to update with large, nested structures.\n", | |
| " | \n", | |
| " | Note, because the dict2 packs up all the keyword arguments, you can\n", | |
| " | specify the changes as a list of keyword agruments.\n", | |
| " | \n", | |
| " | Examples:\n", | |
| " | # update with dict\n", | |
| " | obj = Layout(title='my title', xaxis=XAxis(range=[0,1], domain=[0,1]))\n", | |
| " | update_dict = dict(title='new title', xaxis=dict(domain=[0,.8]))\n", | |
| " | obj.update(update_dict)\n", | |
| " | obj\n", | |
| " | {'title': 'new title', 'xaxis': {'range': [0,1], 'domain': [0,.8]}}\n", | |
| " | \n", | |
| " | # update with list of keyword arguments\n", | |
| " | obj = Layout(title='my title', xaxis=XAxis(range=[0,1], domain=[0,1]))\n", | |
| " | obj.update(title='new title', xaxis=dict(domain=[0,.8]))\n", | |
| " | obj\n", | |
| " | {'title': 'new title', 'xaxis': {'range': [0,1], 'domain': [0,.8]}}\n", | |
| " | \n", | |
| " | This 'fully' supports duck-typing in that the call signature is\n", | |
| " | identical, however this differs slightly from the normal update\n", | |
| " | method provided by Python's dictionaries.\n", | |
| " | \n", | |
| " | validate(self, caller=True)\n", | |
| " | Recursively check the validity of the keys in a PlotlyDict.\n", | |
| " | \n", | |
| " | The valid keys constitute the entries in each object\n", | |
| " | dictionary in graph_objs_meta.json\n", | |
| " | \n", | |
| " | The validation process first requires that all nested collections be\n", | |
| " | converted to the appropriate subclass of PlotlyDict/PlotlyList. Then,\n", | |
| " | each of these objects call `validate` and so on, recursively,\n", | |
| " | until the entire object has been validated.\n", | |
| " | \n", | |
| " | ----------------------------------------------------------------------\n", | |
| " | Data descriptors inherited from PlotlyDict:\n", | |
| " | \n", | |
| " | __dict__\n", | |
| " | dictionary for instance variables (if defined)\n", | |
| " | \n", | |
| " | __weakref__\n", | |
| " | list of weak references to the object (if defined)\n", | |
| " | \n", | |
| " | ----------------------------------------------------------------------\n", | |
| " | Methods inherited from __builtin__.dict:\n", | |
| " | \n", | |
| " | __cmp__(...)\n", | |
| " | x.__cmp__(y) <==> cmp(x,y)\n", | |
| " | \n", | |
| " | __contains__(...)\n", | |
| " | D.__contains__(k) -> True if D has a key k, else False\n", | |
| " | \n", | |
| " | __delitem__(...)\n", | |
| " | x.__delitem__(y) <==> del x[y]\n", | |
| " | \n", | |
| " | __eq__(...)\n", | |
| " | x.__eq__(y) <==> x==y\n", | |
| " | \n", | |
| " | __ge__(...)\n", | |
| " | x.__ge__(y) <==> x>=y\n", | |
| " | \n", | |
| " | __getattribute__(...)\n", | |
| " | x.__getattribute__('name') <==> x.name\n", | |
| " | \n", | |
| " | __getitem__(...)\n", | |
| " | x.__getitem__(y) <==> x[y]\n", | |
| " | \n", | |
| " | __gt__(...)\n", | |
| " | x.__gt__(y) <==> x>y\n", | |
| " | \n", | |
| " | __iter__(...)\n", | |
| " | x.__iter__() <==> iter(x)\n", | |
| " | \n", | |
| " | __le__(...)\n", | |
| " | x.__le__(y) <==> x<=y\n", | |
| " | \n", | |
| " | __len__(...)\n", | |
| " | x.__len__() <==> len(x)\n", | |
| " | \n", | |
| " | __lt__(...)\n", | |
| " | x.__lt__(y) <==> x<y\n", | |
| " | \n", | |
| " | __ne__(...)\n", | |
| " | x.__ne__(y) <==> x!=y\n", | |
| " | \n", | |
| " | __repr__(...)\n", | |
| " | x.__repr__() <==> repr(x)\n", | |
| " | \n", | |
| " | __sizeof__(...)\n", | |
| " | D.__sizeof__() -> size of D in memory, in bytes\n", | |
| " | \n", | |
| " | clear(...)\n", | |
| " | D.clear() -> None. Remove all items from D.\n", | |
| " | \n", | |
| " | copy(...)\n", | |
| " | D.copy() -> a shallow copy of D\n", | |
| " | \n", | |
| " | fromkeys(...)\n", | |
| " | dict.fromkeys(S[,v]) -> New dict with keys from S and values equal to v.\n", | |
| " | v defaults to None.\n", | |
| " | \n", | |
| " | get(...)\n", | |
| " | D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.\n", | |
| " | \n", | |
| " | has_key(...)\n", | |
| " | D.has_key(k) -> True if D has a key k, else False\n", | |
| " | \n", | |
| " | items(...)\n", | |
| " | D.items() -> list of D's (key, value) pairs, as 2-tuples\n", | |
| " | \n", | |
| " | iteritems(...)\n", | |
| " | D.iteritems() -> an iterator over the (key, value) items of D\n", | |
| " | \n", | |
| " | iterkeys(...)\n", | |
| " | D.iterkeys() -> an iterator over the keys of D\n", | |
| " | \n", | |
| " | itervalues(...)\n", | |
| " | D.itervalues() -> an iterator over the values of D\n", | |
| " | \n", | |
| " | keys(...)\n", | |
| " | D.keys() -> list of D's keys\n", | |
| " | \n", | |
| " | pop(...)\n", | |
| " | D.pop(k[,d]) -> v, remove specified key and return the corresponding value.\n", | |
| " | If key is not found, d is returned if given, otherwise KeyError is raised\n", | |
| " | \n", | |
| " | popitem(...)\n", | |
| " | D.popitem() -> (k, v), remove and return some (key, value) pair as a\n", | |
| " | 2-tuple; but raise KeyError if D is empty.\n", | |
| " | \n", | |
| " | setdefault(...)\n", | |
| " | D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D\n", | |
| " | \n", | |
| " | values(...)\n", | |
| " | D.values() -> list of D's values\n", | |
| " | \n", | |
| " | viewitems(...)\n", | |
| " | D.viewitems() -> a set-like object providing a view on D's items\n", | |
| " | \n", | |
| " | viewkeys(...)\n", | |
| " | D.viewkeys() -> a set-like object providing a view on D's keys\n", | |
| " | \n", | |
| " | viewvalues(...)\n", | |
| " | D.viewvalues() -> an object providing a view on D's values\n", | |
| " | \n", | |
| " | ----------------------------------------------------------------------\n", | |
| " | Data and other attributes inherited from __builtin__.dict:\n", | |
| " | \n", | |
| " | __hash__ = None\n", | |
| " | \n", | |
| " | __new__ = <built-in method __new__ of type object>\n", | |
| " | T.__new__(S, ...) -> a new object with type S, a subtype of T\n", | |
| "\n" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 9 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 1, | |
| "metadata": {}, | |
| "source": [ | |
| "Custom styling" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "from IPython.core.display import HTML\n", | |
| "import urllib2\n", | |
| "HTML(urllib2.urlopen('http://bit.ly/1Bf5Hft').read())" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<style>\n", | |
| "\n", | |
| "html {\n", | |
| " font-size: 62.5% !important; }\n", | |
| "body {\n", | |
| " font-size: 1.5em !important; /* currently ems cause chrome bug misinterpreting rems on body element */\n", | |
| " line-height: 1.6 !important;\n", | |
| " font-weight: 400 !important;\n", | |
| " font-family: \"Raleway\", \"HelveticaNeue\", \"Helvetica Neue\", Helvetica, Arial, sans-serif !important;\n", | |
| " color: #222 !important; }\n", | |
| "\n", | |
| "div{ border-radius: 0px !important; }\n", | |
| "div.CodeMirror-sizer{ background: rgb(244, 244, 248) !important; }\n", | |
| "div.input_area{ background: rgb(244, 244, 248) !important; }\n", | |
| "\n", | |
| "div.out_prompt_overlay:hover{ background: rgb(244, 244, 248) !important; }\n", | |
| "div.input_prompt:hover{ background: rgb(244, 244, 248) !important; }\n", | |
| "\n", | |
| "h1, h2, h3, h4, h5, h6 {\n", | |
| " color: #333 !important;\n", | |
| " margin-top: 0 !important;\n", | |
| " margin-bottom: 2rem !important;\n", | |
| " font-weight: 300 !important; }\n", | |
| "h1 { font-size: 4.0rem !important; line-height: 1.2 !important; letter-spacing: -.1rem !important;}\n", | |
| "h2 { font-size: 3.6rem !important; line-height: 1.25 !important; letter-spacing: -.1rem !important; }\n", | |
| "h3 { font-size: 3.0rem !important; line-height: 1.3 !important; letter-spacing: -.1rem !important; }\n", | |
| "h4 { font-size: 2.4rem !important; line-height: 1.35 !important; letter-spacing: -.08rem !important; }\n", | |
| "h5 { font-size: 1.8rem !important; line-height: 1.5 !important; letter-spacing: -.05rem !important; }\n", | |
| "h6 { font-size: 1.5rem !important; line-height: 1.6 !important; letter-spacing: 0 !important; }\n", | |
| "\n", | |
| "@media (min-width: 550px) {\n", | |
| " h1 { font-size: 5.0rem !important; }\n", | |
| " h2 { font-size: 4.2rem !important; }\n", | |
| " h3 { font-size: 3.6rem !important; }\n", | |
| " h4 { font-size: 3.0rem !important; }\n", | |
| " h5 { font-size: 2.4rem !important; }\n", | |
| " h6 { font-size: 1.5rem !important; }\n", | |
| "}\n", | |
| "\n", | |
| "p {\n", | |
| " margin-top: 0 !important; }\n", | |
| " \n", | |
| "a {\n", | |
| " color: #1EAEDB !important; }\n", | |
| "a:hover {\n", | |
| " color: #0FA0CE !important; }\n", | |
| " \n", | |
| "code {\n", | |
| " padding: .2rem .5rem !important;\n", | |
| " margin: 0 .2rem !important;\n", | |
| " font-size: 90% !important;\n", | |
| " white-space: nowrap !important;\n", | |
| " background: #F1F1F1 !important;\n", | |
| " border: 1px solid #E1E1E1 !important;\n", | |
| " border-radius: 4px !important; }\n", | |
| "pre > code {\n", | |
| " display: block !important;\n", | |
| " padding: 1rem 1.5rem !important;\n", | |
| " white-space: pre !important; }\n", | |
| " \n", | |
| "button{ border-radius: 0px !important; }\n", | |
| ".navbar-inner{ background-image: none !important; }\n", | |
| "select, textarea{ border-radius: 0px !important; }\n", | |
| "\n", | |
| "</style>" | |
| ], | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 118, | |
| "text": [ | |
| "<IPython.core.display.HTML at 0x1076c5d90>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 118 | |
| } | |
| ], | |
| "metadata": {} | |
| } | |
| ] | |
| } |
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