{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"inputHidden": false,
"outputHidden": false
},
"source": [
"#### New to Plotly?\n",
"Plotly's Python library is free and open source! [Get started](https://plotly.com/python/getting-started/) by downloading the client and [reading the primer](https://plotly.com/python/getting-started/).\n",
"
You can set up Plotly to work in [online](https://plotly.com/python/getting-started/#initialization-for-online-plotting) or [offline](https://plotly.com/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plotly.com/python/getting-started/#start-plotting-online).\n",
"
We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Version Check\n",
"Plotly's python package is updated frequently. Run `pip install plotly --upgrade` to use the latest version."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"inputHidden": false,
"outputHidden": false
},
"outputs": [
{
"data": {
"text/plain": [
"'2.4.1'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly\n",
"plotly.__version__"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Basic Carpet Plot\n",
"\n",
"Set the `x` and `y` coorindates, using `x` and `y` attributes. If `x` coorindate values are ommitted a cheater plot will be created. To save parameter values use `a` and `b` attributes. To make changes to the axes, use `aaxis` or `baxis` attributes. For a more detailed list of axes attributes refer to [python reference](https://plotly.com/python/reference/#carpet-aaxis)."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly.graph_objs as go\n",
"import plotly.plotly as py\n",
"\n",
"trace1 = go.Carpet(\n",
" a = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3],\n",
" b = [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6],\n",
" x = [2, 3, 4, 5, 2.2, 3.1, 4.1, 5.1, 1.5, 2.5, 3.5, 4.5],\n",
" y = [1, 1.4, 1.6, 1.75, 2, 2.5, 2.7, 2.75, 3, 3.5, 3.7, 3.75],\n",
" aaxis = dict(\n",
" tickprefix = 'a = ',\n",
" smoothing = 0,\n",
" minorgridcount = 9,\n",
" type = 'linear'\n",
" ),\n",
" baxis = dict(\n",
" tickprefix = 'b = ',\n",
" smoothing = 0,\n",
" minorgridcount = 9,\n",
" type = 'linear'\n",
" )\n",
")\n",
"\n",
"data = [trace1]\n",
"\n",
"layout = go.Layout(\n",
" margin = dict(\n",
" \tt = 40,\n",
" r = 30,\n",
" b = 30,\n",
" l = 30\n",
" ),\n",
" yaxis = dict(\n",
" range = [0.388,4.361]\n",
" ),\n",
" xaxis = dict(\n",
" \trange = [0.667,5.932]\t\n",
" )\n",
")\n",
"\n",
"fig = go.Figure(data = data, layout = layout)\n",
"py.iplot(fig, filename = \"contourcarpet/basic\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Add Contours"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"inputHidden": false,
"outputHidden": false
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly.graph_objs as go\n",
"import plotly.plotly as py\n",
"\n",
"trace1 = go.Contourcarpet(\n",
" a = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3],\n",
" b = [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6],\n",
" z = [1, 1.96, 2.56, 3.0625, 4, 5.0625, 1, 7.5625, 9, 12.25, 15.21, 14.0625],\n",
" autocontour = False,\n",
" contours = dict(\n",
" \tstart = 1,\n",
" end = 14,\n",
" size = 1\n",
" ),\n",
" line = dict(\n",
" \twidth = 2,\n",
" \tsmoothing = 0\n",
" ),\n",
" colorbar = dict(\n",
" \tlen = 0.4,\n",
" y = 0.25\n",
" )\n",
")\n",
"\n",
"trace2 = go.Carpet(\n",
" a = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3],\n",
" b = [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6],\n",
" x = [2, 3, 4, 5, 2.2, 3.1, 4.1, 5.1, 1.5, 2.5, 3.5, 4.5],\n",
" y = [1, 1.4, 1.6, 1.75, 2, 2.5, 2.7, 2.75, 3, 3.5, 3.7, 3.75],\n",
" aaxis = dict(\n",
" tickprefix = 'a = ',\n",
" smoothing = 0,\n",
" minorgridcount = 9,\n",
" type = 'linear'\n",
" ),\n",
" baxis = dict(\n",
" tickprefix = 'b = ',\n",
" smoothing = 0,\n",
" minorgridcount = 9,\n",
" type = 'linear'\n",
" )\n",
")\n",
"\n",
"data = [trace1, trace2]\n",
"\n",
"layout = go.Layout(\n",
" margin = dict(\n",
" \tt = 40,\n",
" r = 30,\n",
" b = 30,\n",
" l = 30\n",
" ),\n",
" yaxis = dict(\n",
" range = [0.388,4.361]\n",
" ),\n",
" xaxis = dict(\n",
" \trange = [0.667,5.932]\t\n",
" )\n",
")\n",
"\n",
"fig = go.Figure(data = data, layout = layout)\n",
"py.iplot(fig, filename = \"contourcarpet/add-contours\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Add Multiple Traces"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"inputHidden": false,
"outputHidden": false
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly.graph_objs as go\n",
"import plotly.plotly as py\n",
"\n",
"import urllib, json\n",
"\n",
"url = \"https://raw.githubusercontent.com/bcdunbar/datasets/master/airfoil_data.json\"\n",
"response = urllib.urlopen(url)\n",
"data = json.loads(response.read())\n",
" \n",
"trace1 = go.Carpet(\n",
" a = data[0]['a'],\n",
" b = data[0]['b'],\n",
" x = data[0]['x'],\n",
" y = data[0]['y'],\n",
" baxis = dict(\n",
" startline = False,\n",
" endline = False,\n",
" showticklabels = \"none\",\n",
" smoothing = 0,\n",
" showgrid = False\n",
" ),\n",
" aaxis = dict(\n",
" startlinewidth = 2,\n",
" startline = True,\n",
" showticklabels = \"none\",\n",
" endline = True,\n",
" showgrid = False,\n",
" endlinewidth = 2,\n",
" smoothing = 0\n",
" )\n",
")\n",
"\n",
"trace2 = go.Contourcarpet(\n",
" z = data[1]['z'],\n",
" autocolorscale = False,\n",
" zmax = 1,\n",
" name = \"Pressure\",\n",
" colorscale = \"Viridis\",\n",
" zmin = -8,\n",
" colorbar = dict(\n",
" y = 0,\n",
" yanchor = \"bottom\",\n",
" titleside = \"right\",\n",
" len = 0.75,\n",
" title = \"Pressure coefficient, cp\"\n",
" ),\n",
" contours = dict(\n",
" start = -1,\n",
" size = 0.025,\n",
" end = 1.000,\n",
" showlines = False\n",
" ),\n",
" line = dict(\n",
" smoothing = 0\n",
" ),\n",
" autocontour = False,\n",
" zauto = False\n",
")\n",
"\n",
"trace3 = go.Contourcarpet(\n",
" z = data[2]['z'],\n",
" opacity = 0.300,\n",
" showlegend = True,\n",
" name = \"Streamlines\",\n",
" autocontour = True,\n",
" ncontours = 50,\n",
" contours = dict(\n",
" coloring = \"none\"\n",
" ),\n",
" line = dict(\n",
" color = \"white\",\n",
" width = 1\n",
" )\n",
")\n",
"\n",
"trace4 = go.Contourcarpet(\n",
" z = data[3]['z'],\n",
" showlegend = True,\n",
" name = \"Pressure
contours\",\n",
" autocontour = False,\n",
" line = dict(\n",
" color = \"rgba(0, 0, 0, 0.5)\",\n",
" smoothing = 1\n",
" ),\n",
" contours = dict(\n",
" size = 0.250,\n",
" start = -4,\n",
" coloring = \"none\",\n",
" end = 1.000,\n",
" showlines = True\n",
" )\n",
")\n",
"\n",
"trace5 = go.Scatter(\n",
" x = data[4]['x'],\n",
" y = data[4]['y'],\n",
" legendgroup = \"g1\",\n",
" name = \"Surface
pressure\",\n",
" mode = \"lines\",\n",
" hoverinfo = \"skip\",\n",
" line = dict(\n",
" color = \"rgba(255, 0, 0, 0.5)\",\n",
" width = 1,\n",
" shape = \"spline\",\n",
" smoothing = 1\n",
" ),\n",
" fill = \"toself\",\n",
" fillcolor = \"rgba(255, 0, 0, 0.2)\"\n",
")\n",
"\n",
"trace6 = go.Scatter(\n",
" x = data[5]['x'],\n",
" y = data[5]['y'],\n",
" showlegend = False,\n",
" legendgroup = \"g1\",\n",
" mode = \"lines\",\n",
" hoverinfo = \"skip\",\n",
" line = dict(\n",
" color = \"rgba(255, 0, 0, 0.3)\",\n",
" width = 1\n",
" )\n",
")\n",
"\n",
"trace7 = go.Scatter(\n",
" x = data[6]['x'],\n",
" y = data[6]['y'],\n",
" showlegend = False,\n",
" legendgroup = \"g1\",\n",
" name = \"cp\",\n",
" text = data[6]['text'],\n",
" hoverinfo = \"text\",\n",
" mode = \"lines\",\n",
" line = dict(\n",
" color = \"rgba(255, 0, 0, 0.2)\",\n",
" width = 0\n",
" )\n",
")\n",
"\n",
"data = [trace1,trace2,trace3,trace4,trace5,trace6,trace7]\n",
"\n",
"layout = go.Layout(\n",
" yaxis = dict(\n",
" zeroline = False,\n",
" range = [-1.800,1.800],\n",
" showgrid = False\n",
" ),\n",
" dragmode = \"pan\",\n",
" height = 700,\n",
" xaxis = dict(\n",
" zeroline = False,\n",
" scaleratio = 1,\n",
" scaleanchor = 'y',\n",
" range = [-3.800,3.800],\n",
" showgrid = False\n",
" ),\n",
" title = \"Flow over a Karman-Trefftz airfoil\",\n",
" hovermode = \"closest\",\n",
" margin = dict(\n",
" r = 60,\n",
" b = 40,\n",
" l = 40,\n",
" t = 80\n",
" ),\n",
" width = 900\n",
")\n",
"\n",
"fig = go.Figure(data=data,layout=layout)\n",
"py.iplot(fig, filename = \"contourcarpet/airfoil\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reference"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"See https://plotly.com/python/reference/#contourcarpet for more information and chart attribute options!"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting git+https://github.com/plotly/publisher.git\n",
" Cloning https://github.com/plotly/publisher.git to /private/var/folders/tc/bs9g6vrd36q74m5t8h9cgphh0000gn/T/pip-req-build-kJPbmE\n",
"Building wheels for collected packages: publisher\n",
" Running setup.py bdist_wheel for publisher ... \u001b[?25ldone\n",
"\u001b[?25h Stored in directory: /private/var/folders/tc/bs9g6vrd36q74m5t8h9cgphh0000gn/T/pip-ephem-wheel-cache-ClMTFO/wheels/99/3e/a0/fbd22ba24cca72bdbaba53dbc23c1768755fb17b3af0f33966\n",
"Successfully built publisher\n",
"Installing collected packages: publisher\n",
" Found existing installation: publisher 0.11\n",
" Uninstalling publisher-0.11:\n",
" Successfully uninstalled publisher-0.11\n",
"Successfully installed publisher-0.11\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/nbconvert.py:13: ShimWarning:\n",
"\n",
"The `IPython.nbconvert` package has been deprecated since IPython 4.0. You should import from nbconvert instead.\n",
"\n",
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/publisher/publisher.py:53: UserWarning:\n",
"\n",
"Did you \"Save\" this notebook before running this command? Remember to save, always save.\n",
"\n"
]
}
],
"source": [
"from IPython.display import display, HTML\n",
"\n",
"display(HTML(''))\n",
"display(HTML(''))\n",
"\n",
"! pip install git+https://github.com/plotly/publisher.git --upgrade\n",
"import publisher\n",
"publisher.publish(\n",
" 'contourcarpet.ipynb', 'python/carpet-contour/', 'Carpet Contour Plot',\n",
" 'How to make carpet contour plots in Python with Plotly.',\n",
" title = 'Carpet Contour Plots | Plotly',\n",
" has_thumbnail='true', thumbnail='thumbnail/contourcarpet.jpg', \n",
" language='python', \n",
" # page_type='example_index', // note this is only if you want the tutorial to appear on the main page: plot.ly/python\n",
" display_as='scientific', order=27,\n",
" ipynb= '~notebook_demo/145')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernel_info": {
"name": "python2"
},
"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"
}
},
"nbformat": 4,
"nbformat_minor": 4
}