def _set_axis(self,traces,on=None,side='right',title=''):
"""
Sets the axis in which each trace should appear
If the axis doesn't exist then a new axis is created
Parameters:
-----------
traces : list(str)
List of trace names
on : string
The axis in which the traces should be placed.
If this is not indicated then a new axis will be
created
side : string
Side where the axis will be placed
'left'
'right'
title : string
Sets the title of the axis
Applies only to new axis
"""
fig=Figure(self.copy())
if not isinstance(traces,list):
traces=[traces]
def update_data(trace,y):
anchor=fig.axis['def'][y]['anchor'] if 'anchor' in fig.axis['def'][y] else 'x1'
idx=fig.trace_dict[trace] if isinstance(trace,str) else trace
fig['data'][idx]['xaxis']=anchor
fig['data'][idx]['yaxis']=y
for trace in traces:
if on:
if on not in fig.axis['def']:
raise Exception('"on" axis does not exists: {0}'.format(on))
update_data(trace,y=on)
else:
curr_x,curr_y=fig.axis['ref'][trace]
domain='[0.0, 1.0]' if 'domain' not in fig.axis['def'][curr_y] else str(fig.axis['def'][curr_y]['domain'])
try:
new_axis=fig.axis['dom']['y'][domain][side]
except KeyError:
axis=YAxis(fig.axis['def'][curr_y].copy())
### check overlaying values
axis.update(title=title,overlaying=curr_y,side=side,anchor=curr_x)
axis_idx=str(fig.axis['len']['y']+1)
fig['layout']['yaxis{0}'.format(axis_idx)]=axis
new_axis='y{0}'.format(axis_idx)
update_data(trace,y=new_axis)
for k in fig.axis['def'].keys():
id='{0}axis{1}'.format(k[0],k[-1:])
if k not in fig.axis['ref_axis']:
try:
del fig['layout'][id]
except KeyError:
pass
return fig
def init_plotly():
"""
Prepares authenticate tokens for each trace, prepares layout and streams with corresponding scatter graph traces.
:return: Returns initialized stream IDs for each trace
"""
logger = logging.getLogger(sys._getframe().f_code.co_name)
# pull in Plotly authentication data
plotly_creds = plotly.tools.get_credentials_file()
username = plotly_creds['username']
api_key = plotly_creds['api_key']
token_cpu, token_temp, token_humidity, token_pressure, token_wu = plotly_creds['stream_ids'][0:5]
plotly.plotly.sign_in(username, api_key)
# create Stream structures with proper tokens and maximum preserved graph points
my_stream_cpu = Stream(token=token_cpu, maxpoints=MAX_POINTS)
my_stream_temp = Stream(token=token_temp, maxpoints=MAX_POINTS)
my_stream_humidity = Stream(token=token_humidity, maxpoints=MAX_POINTS)
my_stream_pressure = Stream(token=token_pressure, maxpoints=MAX_POINTS)
my_stream_wu = Stream(token=token_wu, maxpoints=MAX_POINTS)
# create Scatter-type structures with appropriate names; don't provide sample data as we'll provide it live in
# Stream mode
my_scatter_cpu = Scatter(x=[], y=[], stream=my_stream_cpu, name='CPU temperature', mode=TRACE_MODE)
my_scatter_temp = Scatter(x=[], y=[], stream=my_stream_temp,
name='Environment temperature', mode=TRACE_MODE)
my_scatter_humidity = Scatter(x=[], y=[], stream=my_stream_humidity,
name='Environment humidity', mode=TRACE_MODE)
my_scatter_pressure = Scatter(x=[], y=[], stream=my_stream_pressure,
name='Barometric pressure', yaxis='y2',
mode=TRACE_MODE)
my_scatter_wu = Scatter(x=[], y=[], stream=my_stream_wu, name='Outdoor temperature (Weather Underground)',
mode=TRACE_MODE)
# prepare Data structure
my_data = Data([my_scatter_cpu, my_scatter_temp, my_scatter_humidity,
my_scatter_pressure, my_scatter_wu])
# create Layout structure where we have one shared X axis (time series) and two Y axis, one left side (temperature
# and humidity) and one right side (pressure)
my_layout = Layout(title='Raspberry PI Sensors',
xaxis=XAxis(title='Time'), yaxis=YAxis(title='Temperature [C] / Humidity [%]'),
yaxis2=YAxis(title='Pressure [hPa]',
overlaying='y', side='right',
titlefont=Font(color='rgb(148, 103, 189)'),
tickfont=Font(color='rgb(148, 103, 189)')))
# prepare Figure structure
my_fig = Figure(data=my_data, layout=my_layout)
try:
# overwrite existing data on creating the new figure
plotly.plotly.plot(my_fig, filename=PLOTLY_CHART_NAME, auto_open=False, fileopt=GRAPH_MODE)
except requests.exceptions.ConnectionError, e:
logger.error('Cannot connect to PlotLy to create chart: %s. Exiting...' % e)
sys.exit(1)
def test_two_row():
expected = Figure(data=Data(),
layout=Layout(xaxis1=XAxis(domain=[0.0, 1.0],
anchor='y1'),
xaxis2=XAxis(domain=[0.0, 1.0],
anchor='y2'),
yaxis1=YAxis(domain=[0.0, 0.425],
anchor='x1'),
yaxis2=YAxis(domain=[0.575, 1.0],
anchor='x2')))
assert tls.get_subplots(2) == expected
def dataPlotlyHandler():
configuration = ConfigParser.ConfigParser()
configuration.read('credentials.config')
username = configuration.get('plotly', 'username')
apikey = configuration.get('plotly', 'apikey')
streamtokentx = configuration.get('plotly', 'streamtokentx')
streamtokenrx = configuration.get('plotly', 'streamtokenrx')
py.sign_in(username, apikey)
trace_network_tx = Scatter(x=[],
y=[],
stream=Stream(token=streamtokentx, ),
yaxis='tx')
trace_network_rx = Scatter(x=[],
y=[],
stream=Stream(token=streamtokenrx, ),
yaxis='rx')
layout = Layout(title='IoT Lab Network Health System',
yaxis=YAxis(title='Bytes'),
yaxis2=YAxis(title='%', side='right', overlaying="y"))
data = Data([trace_network_tx, trace_network_rx])
fig = Figure(data=data, layout=layout)
print py.plot(fig,
filename='IoT Lab Network Health System',
auto_open=False)
stream_network_tx = py.Stream(streamtokentx)
stream_network_tx.open()
stream_network_rx = py.Stream(streamtokenrx)
stream_network_rx.open()
counter = 0
while True:
output = psutil.net_io_counters()
randoma = randint(0, 1000)
randomb = randint(0, 1000)
stream_network_tx.write({'x': counter, 'y': randoma})
stream_network_rx.write({'x': counter, 'y': randomb})
counter += 1
time.sleep(0.25)
stream_network_tx.close()
stream_network_rx.close()
def createLayout(title=None,
xLabel="Date",
yLabel="Metric",
fontSize=12,
width=800,
height=500):
"""Return plotly Layout object."""
layoutArgs = {
"title": title,
"font": {
"size": fontSize
},
"showlegend": False,
"width": width,
"height": height,
"xaxis": XAxis(title=xLabel, ),
"yaxis": YAxis(
title=yLabel,
domain=[0, 1],
autorange=True,
autotick=True,
),
"barmode": "stack",
"bargap": 0
}
margins = {"l": 70, "r": 30, "b": 50, "t": 90, "pad": 4}
layoutArgs["margin"] = margins
return Layout(**layoutArgs)
def plot_explained_variance(pca):
explained_var = pca.explained_variance_ratio_
cum_var_exp = np.cumsum(explained_var)
py.iplot(Figure(
data=[
Bar(y=explained_var, name='individual explained variance'),
Scatter(y=cum_var_exp, name='cumulative explained variance'),
],
layout=\
Layout(xaxis=XAxis(title='Principal components'),
yaxis=YAxis(title='Explained variance ratio'),
shapes=[{
'type': 'line',
'xref': 'paper',
'x0': 0,
'y0': 1 / len(explained_var), # use absolute value or variable here
'x1': 1,
'y1': 1 / len(explained_var), # ditto
'line': {
'color': 'rgb(50, 171, 96)',
'width': 2,
'dash': 'dash',
},}]
)
))
def plot_ly(subgraph, title, data, measure, colorscale='Hot'):
'''
Function to get a plotly figure object to be plotted
Args:
subgraph (NetworkX Graph): the graph to be plotted
title (str): the title for the plot
data (dict): the measured data to be plotted
measure (str): the measure being plotted
colorscale (str): colorscale for the data measure
ColorScale options
'Greys' | 'Greens' | 'Bluered' | 'Hot' | 'Picnic' | 'Portland' |
Jet' | 'RdBu' | 'Blackbody' | 'Earth' | 'Electric' | 'YIOrRd' |
'YIGnBu'
'''
pos = nx.spring_layout(subgraph, k=.12)
nodes = list(subgraph.node.keys())
nodes.sort()
labels = []
for node in subgraph.nodes():
author_name = subgraph.node[node]['data']['author']['name'].title()
label = "{}<br>{} = {}".format(author_name, measure, str(data[node]))
labels.append(label)
trace1 = scatter_edges(subgraph, pos)
trace2 = scatter_nodes(pos=pos,
labels=labels,
title=title,
data=data,
nodes=nodes,
colorscale=colorscale)
width = 800
height = 600
axis = dict(showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
layout = Layout(title=title,
font=Font(),
showlegend=False,
autosize=False,
width=width,
height=height,
xaxis=dict(title='',
titlefont=dict(size=14, color='#7f7f7f'),
showline=False,
showticklabels=False,
zeroline=False),
yaxis=YAxis(axis),
margin=Margin(
l=40,
r=40,
b=85,
t=100,
pad=0,
),
hovermode='closest',
plot_bgcolor='#EFECEA')
data = Data([trace1, trace2])
fig = Figure(data=data, layout=layout)
return fig
def plotSharpVSOthers(dictParam, fileNameParam, extOfInterest="cSharpCount"):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
cSharpList = dictParam[extOfInterest]
otherList = [100.0 - float(x) for x in cSharpList]
cSharpTrace_ = go.Box(y=cSharpList, name="C# Files")
otherTrace_ = go.Box(y=otherList, name="Other Files")
dataToPlot = [cSharpTrace_, otherTrace_]
layoutToUse = Layout(
title='Distribution of File Types : ' + fileNameParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Values',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
#plot_url = py.plot(dataToPlot, filename=fileNameParam)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plot-session-info/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
def init_layout(self, key, element, ranges):
l, b, zmin, r, t, zmax = self.get_extents(element, ranges)
xd, yd, zd = (element.get_dimension(i) for i in range(3))
xaxis = dict(range=[l, r], title=str(xd))
if self.logx:
xaxis['type'] = 'log'
yaxis = dict(range=[b, t], title=str(yd))
if self.logy:
yaxis['type'] = 'log'
zaxis = dict(range=[zmin, zmax], title=str(zd))
if self.logz:
zaxis['type'] = 'log'
opts = {}
if self.aspect == 'cube':
opts['aspectmode'] = 'cube'
else:
opts['aspectmode'] = 'manual'
opts['aspectratio'] = self.aspect
scene = Scene(xaxis=XAxis(xaxis),
yaxis=YAxis(yaxis),
zaxis=ZAxis(zaxis),
**opts)
return dict(width=self.width,
height=self.height,
title=self._format_title(key, separator=' '),
plot_bgcolor=self.bgcolor,
scene=scene)
def plotDistForThreeGroups(group1, group2, group3, fileNameParam):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
#from plotly.graph_objs import Bar, Marker, Data, Layout, XAxis, YAxis, Figure, Margin, Font
dataToPlot = []
g1Trace_ = go.Box(y=group1, name="Corr >=0.50")
g2Trace_ = go.Box(y=group2, name="Corr >=0.0 AND Corr <=0.499")
g3Trace_ = go.Box(y=group3, name="Corr < 0.0")
dataToPlot = [g1Trace_, g2Trace_, g3Trace_]
layoutToUse = Layout(
title='Distribution of : ' + fileNameParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Values',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
#plot_url = py.plot(dataToPlot, filename=fileNameParam)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plot-session-info/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
def _createLayout(title=None,
xLabel="Date",
yLabel="Metric",
fontSize=12,
width=WIDTH,
height=HEIGHT):
"""Return plotly Layout object."""
layoutArgs = {
"title": title,
"font": {
"size": fontSize
},
"showlegend": False,
"width": width,
"height": height,
"xaxis": XAxis(title=xLabel, ),
"yaxis": YAxis(
title=yLabel,
domain=[0, 1],
autorange=True,
),
"barmode": "stack",
"bargap": 0
}
margins = {"l": 70, "r": 30, "b": 50, "t": 90, "pad": 4}
if title is None:
margins["t"] -= 70
if fontSize > 12:
margins["l"] += (fontSize - 12) * 3
margins["b"] += (fontSize - 12) * 3
layoutArgs["margin"] = margins
return Layout(**layoutArgs)
def plotTwoGroups(group1Param, group2Param, yAxisParam, titleParam,
fileNameParam):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
group1Trace_ = go.Box(y=group1Param, name="High Productivity Sessions")
group2Trace_ = go.Box(y=group2Param, name="Low Productivity Sessions")
dataToPlot = [group1Trace_, group2Trace_]
layoutToUse = Layout(
title='Summary of 84030 Sessions : ' + titleParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title=yAxisParam,
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plot-session-info/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
return "DONE!"
def results(symbol, trend1, trend2):
data = web.DataReader(symbol, data_source='yahoo')
#Guardamos la data en formato HDF5
# filename = 'data'+'_'+symbol+'_'+trend1+'_'+trend2+'.h5'
filename = 'data.h5'
store = {}
store['symbol'] = data
h5 = pd.HDFStore(filename, 'w')
h5['symbol'] = store['symbol']
h5.close()
#Mandamos la data al correo
#os.system("python send_email.py")
data['Tendencia 1'] = pd.rolling_mean(data['Adj Close'],
window=int(trend1))
data['Tendencia 2'] = pd.rolling_mean(data['Adj Close'],
window=int(trend2))
layout = Layout(xaxis=XAxis(showgrid=True,
gridcolor='#bdbdbd',
gridwidth=2),
yaxis=YAxis(showgrid=True,
gridcolor='#bdbdbd',
gridwidth=2))
fig = Figure(data=df_to_plotly(
data[['Adj Close', 'Tendencia 1', 'Tendencia 2']]),
layout=layout)
plot = ply.plot(fig, auto_open=False)
table = data.tail().to_html()
return render_template('plotly.html',
symbol=symbol,
plot=plot,
table=table)
def compareViaBoxPlot(posGroupParam, zeroGroupParam, negGroupParam,
fileNameParam):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
#from plotly.graph_objs import Bar, Marker, Data, Layout, XAxis, YAxis, Figure, Margin, Font
posGroup = go.Box(y=posGroupParam, name='Corr. >= 0.50')
zeroGroup = go.Box(y=zeroGroupParam, name='Corr. within 0.0 & 0.499')
negGroup = go.Box(y=negGroupParam, name='Corr. < 0.0')
layoutToUse = Layout(
title='Distribution of Three Groups: ' + fileNameParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Values',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
dataToPlot = [posGroup, zeroGroup, negGroup]
#plot_url = py.plot(dataToPlot, filename=fileNameParam)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plots/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
def test_get_single_plot():
expected = Figure(data=Data(),
layout=Layout(xaxis1=XAxis(domain=[0.0, 1.0],
anchor='y1'),
yaxis1=YAxis(domain=[0.0, 1.0],
anchor='x1')))
assert tls.get_subplots() == expected
def plot_linear_prediction(results, data, filename):
x_transform = (add_month(data[0][-1]) - min(data[0])).days
x_val = add_month(data[0][-1])
prediction = results.params["x"] * x_transform + results.params["Intercept"]
trace1 = Scatter(x=data[0],
y=data[1],
mode='lines',
marker=Marker(color='rgb(255, 127, 14)'),
name='Data')
trace2 = Scatter(x=[x_val],
y=[prediction],
mode='markers',
marker=Marker(color='rgb(31, 119, 180)'),
name='Fit')
layout = Layout(title='Linear Fit in Python',
plot_bgcolor='rgb(229, 229, 229)',
xaxis=XAxis(zerolinecolor='rgb(255,255,255)',
gridcolor='rgb(255,255,255)'),
yaxis=YAxis(zerolinecolor='rgb(255,255,255)',
gridcolor='rgb(255,255,255)'))
to_scatter = [trace1, trace2]
plotly.offline.plot({"data": to_scatter, "layout": layout})
shutil.move("temp-plot.html", filename)
def plotConfusionMatrix(self, dataFrame, name):
"""
@param data (pandas DF) The confusion matrix.
@param name (str)
"""
labels = dataFrame.columns.values.tolist()
values = map(list, dataFrame.values)
data = Data(
[Heatmap(z=values, x=labels, y=labels, colorscale='YIGnBu')])
layout = Layout(
title='Confusion Matrix for ' + name,
xaxis=XAxis(title='',
side='top',
titlefont=Font(family='Courier New, monospace',
size=18,
color='#7f7f7f')),
yaxis=YAxis(title='',
titlefont=Font(family='Courier New, monospace',
size=18,
color='#7f7f7f'),
autorange='reversed'),
barmode='overlay',
autosize=True,
width=1000,
height=1000,
margin=Margin(l=80, r=80, b=120, t=140))
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig)
print "Confusion matrix URL: ", plot_url
def compareFileExtViaBarPlots(dictParam, fileNameParam, listParam):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
import numpy as np
xList = []
yList = []
for it_ in listParam:
xList.append(it_)
yList.append(np.mean(dictParam[it_]))
dataToPlot = [go.Bar(x=xList, y=yList)]
layoutToUse = Layout(
title='Distribution of File Types (Average) : ' + fileNameParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Values',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
#plot_url = py.plot(dataToPlot, filename=fileNameParam)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plot-session-info/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
def compareFileExtViaBoxPlots(dictParam, fileNameParam, extList):
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font
#from plotly.graph_objs import Bar, Marker, Data, Layout, XAxis, YAxis, Figure, Margin, Font
dataToPlot = []
for it_ in extList:
trace_ = go.Box(y=dictParam[it_], name=it_)
dataToPlot.append(trace_)
layoutToUse = Layout(
title='Distribution of File Types : ' + fileNameParam,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Values',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
#plot_url = py.plot(dataToPlot, filename=fileNameParam)
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
fileNameParam = "plot-session-info/" + fileNameParam + ".png"
py.image.save_as(figToPlot, fileNameParam)
def plot_df(df, title):
ax = ['x', 'y', 'z']
data = [Scatter(y=df[a], name=a) for a in ax]
layout = Layout(title=title,
xaxis=XAxis(title='Timestep'),
yaxis=YAxis(title='{x, y, z} coordinates in Gs'))
plot({'data': data, 'layout': layout}, show_link=False)
def setUp(self):
super(TestToDataframe, self).setUp()
self.fig = Figure(data=Data([
Scatter(x=[52698, 43117],
y=[53, 31],
mode='markers',
name='North America',
text=['United States', 'Canada'],
marker=Marker(color='rgb(164, 194, 244)',
size=12,
line=Line(color='white', width=0.5))),
Scatter(x=[
39317, 37236, 35650, 30066, 29570, 27159, 23557, 21046, 18007
],
y=[33, 20, 13, 19, 27, 19, 49, 44, 38],
mode='markers',
name='Europe',
text=[
'Germany', 'Britain', 'France', 'Spain', 'Italy',
'Czech Rep.', 'Greece', 'Poland'
],
marker=Marker(color='rgb(255, 217, 102)',
size=12,
line=Line(color='white', width=0.5))),
Scatter(x=[42952, 37037, 33106, 17478, 9813, 5253, 4692, 3899],
y=[23, 42, 54, 89, 14, 99, 93, 70],
mode='markers',
name='Asia/Pacific',
text=[
'Australia', 'Japan', 'South Korea', 'Malaysia',
'China', 'Indonesia', 'Philippines', 'India'
],
marker=Marker(color='rgb(234, 153, 153)',
size=12,
line=Line(color='white', width=0.5))),
Scatter(x=[19097, 18601, 15595, 13546, 12026, 7434, 5419],
y=[43, 47, 56, 80, 86, 93, 80],
mode='markers',
name='Latin America',
text=[
'Chile', 'Argentina', 'Mexico', 'Venezuela',
'Venezuela', 'El Salvador', 'Bolivia'
],
marker=Marker(color='rgb(142, 124, 195)',
size=12,
line=Line(color='white', width=0.5)))
]),
layout=Layout(title='Quarter 1 Growth',
autosize=False,
width=500,
height=500,
xaxis=XAxis(title='GDP per Capita',
showgrid=False,
zeroline=False),
yaxis=YAxis(title='Percent',
showline=False),
margin=Margin(l=65, r=50, b=65, t=90)))
def graph(self):
trace_network_tx = Scatter(x=[],
y=[],
stream=Stream(token=self.streamtokentx, ),
yaxis='tx')
trace_network_rx = Scatter(x=[],
y=[],
stream=Stream(token=self.streamtokenrx, ),
yaxis='rx')
layout = Layout(title='IoTPy Network Health System',
yaxis=YAxis(title='Bytes'),
yaxis2=YAxis(title='%', side='right', overlaying="y"))
data = Data([trace_network_tx, trace_network_rx])
fig = Figure(data=data, layout=layout)
print py.plot(fig,
filename='IoTPy Network Health System',
auto_open=False)
stream_network_tx = py.Stream(self.streamtokentx)
stream_network_tx.open()
stream_network_rx = py.Stream(self.streamtokenrx)
stream_network_rx.open()
time.sleep(5)
counter = 0
while True:
output = psutil.net_io_counters()
print "Network Bytes Tx %s" % output.bytes_sent
print "Network Bytes Rx %s" % output.bytes_recv
stream_network_tx.write({'x': counter, 'y': output.bytes_sent})
stream_network_rx.write({'x': counter, 'y': output.bytes_recv})
counter += 1
time.sleep(0.25)
stream_network_tx.close()
stream_network_rx.close()
def scatter_df_plotly(df,
x,
y,
z,
text_fnct=hover_all,
streaming=True,
filename=None):
"""
a wrapper function for `plotlyi.graph_objs.Scatter` on `pandas.Dataframe`
usage:
=====
d
"""
layout = Layout(
title='colour map: %s' % z,
hovermode='closest', # (!) hover -> closest data pt
showlegend=False, # remove legend (info in hover)
autosize=False, # turn off autosize
width=650, # plot width
height=500, # plot height
xaxis=XAxis(title=x,
titlefont=Font(family='Courier New, monospace',
size=14,
color='#7f7f7f')),
yaxis=YAxis(title=y,
titlefont=Font(family='Courier New, monospace',
size=14,
color='#7f7f7f')))
# print('marker sizes:')
# print(rescale_marker(df[z], square = True))
SC = Scatter(x=df[x],
y=df[y],
mode='markers',
marker=Marker(size=rescale_marker(df[z], square=True),
color=df[z],
colorscale='Jet',
sizeref=1,
sizemode='area'))
FIG = Figure(data=Data([SC]), layout=layout)
#FIG['layout'].update( )
if text_fnct is not None:
FIG['data'][0].update(text = \
df.apply(lambda ds: text_fnct(ds, x=x, y=y,z=z), axis = 1).tolist() )
if not streaming:
if filename is not None:
return py.plot(FIG, filename=filename)
else:
return py.plot(FIG)
else:
return py.iplot(FIG)
def _createLayout(title):
"""Return plotly Layout object."""
return Layout(title=title,
showlegend=False,
width=1000,
height=600,
xaxis=XAxis(
title="Date"
),
yaxis=YAxis(
title="Metric",
domain=[0, 1],
autorange=True,
autotick=True
),
yaxis2=YAxis(
overlaying="y",
side="right"
),
barmode="stack",
bargap=0)
def test_append_scatter():
expected = Figure(
data=Data([Scatter(x=[1, 2, 3], y=[2, 3, 4], xaxis='x5', yaxis='y5')]),
layout=Layout(
xaxis1=XAxis(domain=[0.0, 0.2888888888888889], anchor='y1'),
xaxis2=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor='y2'),
xaxis3=XAxis(domain=[0.7111111111111111, 1.0], anchor='y3'),
xaxis4=XAxis(domain=[0.0, 0.2888888888888889], anchor='y4'),
xaxis5=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor='y5'),
xaxis6=XAxis(domain=[0.7111111111111111, 1.0], anchor='y6'),
yaxis1=YAxis(domain=[0.575, 1.0], anchor='x1'),
yaxis2=YAxis(domain=[0.575, 1.0], anchor='x2'),
yaxis3=YAxis(domain=[0.575, 1.0], anchor='x3'),
yaxis4=YAxis(domain=[0.0, 0.425], anchor='x4'),
yaxis5=YAxis(domain=[0.0, 0.425], anchor='x5'),
yaxis6=YAxis(domain=[0.0, 0.425], anchor='x6')))
trace = Scatter(x=[1, 2, 3], y=[2, 3, 4])
fig = tls.make_subplots(rows=2, cols=3)
fig.append_trace(trace, 2, 2)
d1, d2 = strip_dict_params(fig['data'][0], expected['data'][0])
assert d1 == d2
d1, d2 = strip_dict_params(fig['layout'], expected['layout'])
assert d1 == d2
def test_append_scatter():
expected = Figure(
data=Data([Scatter(x=[1, 2, 3], y=[2, 3, 4], xaxis="x5", yaxis="y5")]),
layout=Layout(
xaxis1=XAxis(domain=[0.0, 0.2888888888888889], anchor="y1"),
xaxis2=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor="y2"),
xaxis3=XAxis(domain=[0.7111111111111111, 1.0], anchor="y3"),
xaxis4=XAxis(domain=[0.0, 0.2888888888888889], anchor="y4"),
xaxis5=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor="y5"),
xaxis6=XAxis(domain=[0.7111111111111111, 1.0], anchor="y6"),
yaxis1=YAxis(domain=[0.575, 1.0], anchor="x1"),
yaxis2=YAxis(domain=[0.575, 1.0], anchor="x2"),
yaxis3=YAxis(domain=[0.575, 1.0], anchor="x3"),
yaxis4=YAxis(domain=[0.0, 0.425], anchor="x4"),
yaxis5=YAxis(domain=[0.0, 0.425], anchor="x5"),
yaxis6=YAxis(domain=[0.0, 0.425], anchor="x6"),
),
)
trace = Scatter(x=[1, 2, 3], y=[2, 3, 4])
fig = tls.make_subplots(rows=2, cols=3)
fig.append_trace(trace, 2, 2)
d1, d2 = strip_dict_params(fig["data"][0], expected["data"][0])
assert d1 == d2
d1, d2 = strip_dict_params(fig["layout"], expected["layout"])
assert d1 == d2
def create_plot(username, api_key,
weather_token,
sensor_tokens, sensor_names,
title, units,
max_points):
py.sign_in(username, api_key)
traces = [
Scatter(
x=[],
y=[],
name=n,
stream={
'token': t,
# 'maxpoints': max_points,
}
)
for t, n in zip(sensor_tokens, sensor_names)
]
traces.append(
Scatter(
x=[],
y=[],
name='Outside Temperature',
stream={
'token': weather_token,
# 'maxpoints': max_points,
}
)
)
layout = Layout(
title=title,
yaxis=YAxis(
title='Degrees %s' % units.title(),
),
showlegend=True,
)
fig = Figure(data=traces, layout=layout)
plot_url = py.plot(fig, filename=title, extend=True, auto_open=False)
LOG.info('Output graph visible at %s', plot_url)
sensor_streams = {
t: py.Stream(t)
for t in sensor_tokens
}
for s in sensor_streams.values():
s.open()
weather_stream = py.Stream(weather_token)
weather_stream.open()
return sensor_streams, weather_stream
def results(symbol, trend1, trend2):
data = web.DataReader(symbol, data_source='yahoo')
data['Trend 1'] = pd.rolling_mean(data['Adj Close'], window=int(trend1))
data['Trend 2'] = pd.rolling_mean(data['Adj Close'], window=int(trend2))
layout = Layout(
xaxis=XAxis(showgrid=True, gridcolor='#bdbdbd', gridwidth=2),
yaxis=YAxis(showgrid=True, gridcolor='#bdbdbd', gridwidth=2)
)
fig = Figure(data=df_to_plotly(data[['Adj Close', 'Trend 1', 'Trend 2']]),
layout=layout)
plot = ply.plot(fig, auto_open=False)
table = data.tail().to_html()
return render_template('plotly.html', symbol=symbol,
plot=plot, table=table)
def fig1():
trace1 = Scatter(
x=df['LifeExpectancy'],
y=df['GNP'],
text=country_names,
mode='markers'
)
layout = Layout(
xaxis=XAxis(title='Life Expectancy'),
yaxis=YAxis(type='log', title='GNP')
)
data = Data([trace1])
fig = Figure(data=data, layout=layout)
py.iplot(fig, filename='world GNP vs life expectancy')
def plot_explained_variance(pca):
import plotly
from plotly.graph_objs import Scatter, Marker, Layout, XAxis, YAxis, Bar, Line
plotly.offline.init_notebook_mode() # run at the start of every notebook
explained_var = pca.explained_variance_ratio_
cum_var_exp = np.cumsum(explained_var)
plotly.offline.iplot({
"data": [Bar(y=explained_var, name='individual explained variance'),
Scatter(y=cum_var_exp, name='cumulative explained variance')
],
"layout": Layout(xaxis=XAxis(title='Principal components'), yaxis=YAxis(title='Explained variance ratio'))
})
def plotly_create_stream(data):
api_key = os.environ.get("PLOTLY_KEY_API")
stream_token = os.environ.get("PULSE_STREAM_TOKEN")
x, y = process_data_for_pulse(data)
py.sign_in('SergeyParamonov', api_key)
data = Data([Scatter(x=x, y=y, stream=dict(token=stream_token))])
layout = Layout(
title="Пульс Хабра — изменение просмотров статей в Новом (в минуту)",
xaxis=XAxis(title=u"Московское время"), # x-axis title
yaxis=YAxis(title=u"Просмотры"), # y-axis title
showlegend=False, # remove legend (info in hover)
hovermode='closest', # N.B hover -> closest data pt
)
plotly_fig = Figure(data=data, layout=layout)
unique_url = py.plot(plotly_fig, filename="pulse")
return unique_url
def make_YAxis(y_in):
yaxis = YAxis(range=[y_in.min(),y_in.max()])
yaxis.update(axis_style)
return yaxis