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 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 kamervragen_reply_time_per_year(years, kamervraag_durations):
fig = ff.create_distplot(
kamervraag_durations,
years,
# colors=colors,
bin_size=1,
show_curve=True,
show_hist=False,
show_rug=False)
xaxis = XAxis(range=[0, 60])
fig['layout'].update(xaxis=xaxis)
# fig['layout'].update(title="Kamervraag Antwoordtijd per Ministerie tijdens Rutte-II (KDE probability distributie)")
fig['layout'].update(xaxis=dict(title='Antwoordtijd [dagen]'))
# fig['layout'].update(yaxis=dict(title=''))
fig['layout'].update(height=700)
fig['layout'].update(margin=Margin(t=20))
legend = dict(
# x=0.01,
# y=1,
bordercolor='#E2E2E2',
bgcolor='#FFFFFF',
borderwidth=2)
fig['layout'].update(legend=legend)
return Plot.create_plot_html_default(figure_or_data=fig)
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 test_to_string():
fig = Figure(data=Data([
Scatter(x=[1, 2, 3, 4], y=[10, 15, 13, 17]),
Scatter(x=[1, 2, 3, 4], y=[16, 5, 11, 9])
]),
layout=Layout(autosize=False,
width=500,
height=500,
margin=Margin(l=65, r=50, b=65, t=65)))
fig_string = fig.to_string(pretty=False)
comp_string = ('Figure(\n'
' data=Data([\n'
' Scatter(\n'
' x=[1, 2, 3, 4],\n'
' y=[10, 15, 13, 17]\n'
' ),\n'
' Scatter(\n'
' x=[1, 2, 3, 4],\n'
' y=[16, 5, 11, 9]\n'
' )\n'
' ]),\n'
' layout=Layout(\n'
' autosize=False,\n'
' width=500,\n'
' height=500,\n'
' margin=Margin(\n'
' l=65,\n'
' r=50,\n'
' b=65,\n'
' t=65\n'
' )\n'
' )\n'
')')
assert fig_string == comp_string
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 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 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 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 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 create_layout(self):
return Layout(
# title="Kamervraag Antwoordtijd vs Tijd",
xaxis=dict(title='Kamervraag Ingediend [tijd]'),
yaxis=dict(title='Antwoordtijd [dagen]'),
autosize=False,
width=1000,
height=500,
margin=Margin(t=20))
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 create_layout(self):
return Layout(
yaxis=dict(title='Kamervragen per maand'),
margin=Margin(t=20, b=30),
legend=dict(
# x=0.01,
# y=1,
bordercolor='#E2E2E2',
bgcolor='#FFFFFF',
borderwidth=2))
def create_layout(self):
return Layout(title=self.plot_title,
xaxis=dict(title='Tijd'),
yaxis=dict(title='Kamervragen per week'),
margin=Margin(t=20),
legend=dict(x=0.01,
y=1,
bordercolor='#E2E2E2',
bgcolor='#FFFFFF',
borderwidth=2))
def compare_runs(self,
column,
loc=(),
iloc=(),
subsample=1,
marker=False,
reference=None,
verbose=True) -> None:
mode = 'lines' if (not marker) else 'lines+markers'
if isinstance(iloc, int):
iloc = [i for i in range(iloc)
] if (iloc > 0) else [i for i in range(iloc, 0, 1)]
data = []
def _add(entry, name):
x, y = zip(*entry[column])
x, y = arr(x)[::subsample], arr(y)[::subsample]
data.append(Scatter(x=x, y=y, name=name, mode=mode))
for idx in loc:
try:
entry = self.df.loc[idx].logs
_add(entry, name=f'loc_({idx})')
except Exception as e:
if verbose:
print(f'Exception for loc idx={idx} e={e}')
for idx in iloc:
try:
entry = self.df.iloc[idx].logs
_add(entry, name=f'ix_({idx})')
except Exception as e:
if verbose:
print(f'Exception for ix idx={idx} e={e}')
ref = reference or []
for i, (x, y) in enumerate(ref):
data.append(Scatter(x=x, y=y, name=f'ref_{i}', mode=mode))
plotly.offline.iplot({
'data':
data,
'layout':
Layout(autosize=False,
width=1000,
height=250,
margin=Margin(l=35, r=35, b=35, t=35, pad=0))
})
def create_layout(self):
return Layout(
# title="Kamervragen per Week",
xaxis=dict(title='Tijd'),
yaxis=dict(title='Zetels per partij'),
margin=Margin(t=20),
legend=dict(
# x=0.01,
# y=1,
bordercolor='#E2E2E2',
bgcolor='#FFFFFF',
borderwidth=2))
def get_context_data(self, **kwargs):
import plotly.offline
from plotly.graph_objs import Layout, Bar, Margin
context = super().get_context_data(**kwargs)
domains = self.get_domains()
x = []
y = []
domains_selection = []
min_mentions = 10
for domain in domains:
if domain[1] < min_mentions:
break
domains_selection.append(domain)
for domain in reversed(domains):
if domain[1] < 20:
continue
if domain[0] == 'zoek.officielebekendmakingen.nl':
continue
x.append(domain[0])
y.append(domain[1])
data = [Bar(
x=y,
y=x,
orientation='h'
)]
plot_html = plotly.offline.plot(
figure_or_data={
"data": data,
"layout": Layout(
title="Vermeldingen per website",
autosize=True,
height=1200,
margin=Margin(
l=200,
r=50,
b=40,
t=40,
pad=4
),
)
},
show_link=False,
output_type='div',
include_plotlyjs=False,
auto_open=False,
)
context['plot_html'] = mark_safe(plot_html)
context['domains'] = domains_selection
context['min_mentions'] = min_mentions
return context
def _plotly_3d_scatter(coords, partition=None):
""" _plotly_3d_scatter(coords, partition=None)
Make a scatterplot of treeCl.CoordinateMatrix using the Plotly
plotting engine
"""
from plotly.graph_objs import Scatter3d, Data, Figure, Layout, Line, Margin, Marker
# auto sign-in with credentials or use py.sign_in()
colourmap = {
'A': '#1f77b4',
'B': '#ff7f0e',
'C': '#2ca02c',
'D': '#d62728',
'E': '#9467bd',
1: '#1f77b4',
2: '#ff7f0e',
3: '#2ca02c',
4: '#d62728',
5: '#9467bd'
}
df = coords.df
if partition:
assert len(partition.partition_vector) == df.shape[0]
labels = [x + 1 for x in partition.partition_vector]
else:
labels = [1 for _ in range(df.shape[0])]
x, y, z = df.columns[:3]
df['Label'] = labels
colours = [colourmap[lab] for lab in df['Label']]
trace = Scatter3d(x=df[x],
y=df[y],
z=df[z],
mode='markers',
marker=Marker(size=9,
color=colours,
line=Line(color=colours, width=0.5),
opacity=0.8),
text=[str(ix) for ix in df.index])
data = Data([trace])
layout = Layout(
margin=Margin(l=0, r=0, b=0, t=0),
hovermode='x',
)
fig = Figure(data=data, layout=layout)
return fig
def graphRes():
conn = sqlite3.connect("test.db")
sq = "SELECT title as Post_Title, sent as Sentiment_Analysis FROM merge;"
df = pd.read_sql(sq, conn)
plotly.offline.plot({
"data": [Bar(x=df.Post_Title, y=df.Sentiment_Analysis)],
"layout":
Layout(
title=
"Comment Sentiment Analysis on Top 25 /r/worldnews Posts (from Last 24 Hrs)",
margin=Margin(b=200))
})
#close connection
conn.close()
def plotConfusionMatrix(self, data, normalize=True):
"""
Plots the confusion matrix of the input dataframe.
@param data (pandas DF) The confusion matrix.
@param normalize (bool) True will normalize the confusion matrix
values for the total number of actual classifications per label. Thus
the cm values are 0.0 to 1.0.
"""
xyzData = self.interpretConfusionMatrixData(data, normalize)
data = Data([
Heatmap(z=xyzData["z"],
x=xyzData["x"],
y=xyzData["y"],
colorscale='YIGnBu')
])
layout = Layout(
title='Confusion matrix for ' + self.experimentName,
xaxis=XAxis(title='Predicted label',
side='top',
titlefont=Font(family='Courier New, monospace',
size=18,
color='#7f7f7f')),
yaxis=YAxis(title='True label',
titlefont=Font(family='Courier New, monospace',
size=18,
color='#7f7f7f'),
autorange='reversed'),
barmode='overlay',
autosize=True,
width=1000,
height=1000,
margin=Margin(l=200, r=80, b=80, t=450))
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig)
print "Confusion matrix URL: ", plot_url
x2=[0, 1, 2, 3, 4, 5, 6],
y2=[1, 4, 8, 16, 32, 64, 128])
SIMPLE_LINE = Figure(data=Data([
Scatter(x=[0.0, 1.0, 2.0, 3.0, 4.0, 5.0],
y=[10.0, 20.0, 50.0, 80.0, 100.0, 200.0],
name='simple',
mode='lines',
line=Line(dash='solid', color='rgba (0, 0, 255, 1)', width=1.0),
xaxis='x1',
yaxis='y1')
]),
layout=Layout(width=640,
height=480,
autosize=False,
margin=Margin(l=80, r=63, b=47, t=47,
pad=0),
hovermode='closest',
showlegend=False,
xaxis1=XAxis(domain=[0.0, 1.0],
range=[0.0, 5.0],
type='linear',
showline=True,
ticks='inside',
nticks=6,
showgrid=False,
zeroline=False,
tickfont=Font(size=12.0),
anchor='y1',
side='bottom',
mirror='ticks'),
yaxis1=YAxis(domain=[0.0, 1.0],
def draw_igraph(self, title, colors=None):
(Xn, Yn, Zn), (Xe, Ye, Ze) = self.get_3d_position()
trace1 = Scatter3d(x=Xe,
y=Ye,
z=Ze,
mode='lines',
line=Line(color='rgb(125,125,125)',
width=1,
dash=True),
hoverinfo='none')
trace2 = Scatter3d(
x=Xn,
y=Yn,
z=Zn,
mode='markers',
name='callers',
marker=Marker(
symbol='dot',
size=[100 * x + 5 for x in list(self.betweenness.values())],
color=self.colors,
colorscale='Rainbow',
opacity=0.5),
text=self.nodes,
hoverinfo='text')
axis = dict(showbackground=False,
showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
layout = Layout(
title=title,
width=1000,
height=1000,
showlegend=False,
scene=Scene(
xaxis=XAxis(axis),
yaxis=YAxis(axis),
zaxis=ZAxis(axis),
),
margin=Margin(t=100),
hovermode='closest',
annotations=Annotations([
Annotation(showarrow=False,
text="Data source: ???",
xref='paper',
yref='paper',
x=0,
y=0.1,
xanchor='left',
yanchor='bottom',
font=Font(size=14))
]),
)
data = Data([trace1, trace2])
fig = Figure(data=data, layout=layout)
iplot(fig, filename='Call Network')
from plotly import __version__
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from plotly.graph_objs import Scatter, Figure, Layout, Bar, Margin
import pandas as pd
df = pd.read_csv('data/recipeData.csv', index_col='BeerID', encoding='latin-1')
print(df.head())
print(df.info(verbose=False))
data = [
Bar(
x=df['Name'], # assign x as the dataframe column 'x'
y=df['OG'])
]
#url = plot(data, filename='graph/plot.html')
top_n_types = 15
recipe_popularity_as_perc = 100 * df['Style'].value_counts(
)[:top_n_types] / len(df)
data = [
Bar(x=recipe_popularity_as_perc.index, y=recipe_popularity_as_perc.values)
]
layout = Layout(title='Most popular beer styles',
xaxis={'title': 'Style'},
yaxis={'title': 'Proportion of recipes (%)'},
margin=Margin(l=50, r=50, b=150, t=50, pad=4))
fig = Figure(data=data, layout=layout)
plot(fig, filename='graph/popular.html')
BLANK_SUBPLOTS = Figure(
data=Data([
Scatter(x=[0.0, 1.0],
y=[1.0, 2.0],
name='_line0',
mode='lines',
line=Line(dash='solid', color='#0000FF', width=1.0),
xaxis='x1',
yaxis='y1')
]),
layout=Layout(
width=640,
height=480,
autosize=False,
margin=Margin(l=168, r=63, b=47, t=47, pad=0),
hovermode='closest',
showlegend=False,
xaxis1=XAxis(domain=[0.0, 0.13513513513513517],
range=[0.0, 1.0],
type='linear',
showline=True,
ticks='inside',
nticks=6,
showgrid=False,
zeroline=False,
tickfont=Font(size=12.0),
anchor='y1',
side='bottom',
mirror='ticks'),
xaxis2=XAxis(domain=[0.0, 0.13513513513513517],
def draw3Dnx(graph=None,
out_path=None,
perc_threshold=None,
positions_array=None,
positions_dict=None,
plot_title='',
plot_description='',
colorscale='Set3',
notebook_mode=True,
auto_open=False):
"""Draws a given graph in 3D"""
if graph is None or nx.is_empty(graph):
raise ValueError('input graph can not be empty!')
# graph = nx.random_geometric_graph(200, 0.05)
if notebook_mode:
init_notebook_mode()
marker_size = 7
marker_edge_width = 2
link_width = 2
colorbar_title = 'Node Connections'
hover_description = '# connections: '
position_attr = ['x', 'y', 'z']
if positions_array is not None:
for node in graph.nodes():
for ix, attr in enumerate(position_attr):
graph.nodes[node][attr] = positions_array[node][ix]
elif positions_dict is not None:
for node in graph.nodes():
for attr in position_attr:
graph.nodes[node][attr] = positions_array[node][attr]
for attr in position_attr:
if not nx.get_node_attributes(graph, attr):
raise ValueError(
'Position attribute {} missing. '
'Add it to graph or supply with one of the position inputs'.
format(attr))
edge_threshold = -np.Inf
if perc_threshold is not None:
eval_distr = np.array(
list(nx.get_edge_attributes(graph, 'weight').values()))
try:
edge_threshold = np.percentile(eval_distr, perc_threshold)
except:
print('threshold to prune edges can not be determined.')
traceback.print_exc()
return
edge_trace = Scatter3d(
x=[],
y=[],
z=[],
mode='lines',
line=Line(width=marker_edge_width, color='#888'),
hoverinfo='none',
)
def get_position(gnode):
"""Helper to retun the x, y, z coords of a node"""
return gnode['x'], gnode['y'], gnode['z']
for src, dest in graph.edges():
# adding only the strongest edges
if perc_threshold is None or graph.get_edge_data(
src, dest)['weight'] > edge_threshold:
x0, y0, z0 = get_position(graph.nodes[src]) # ['position']
x1, y1, z1 = get_position(graph.nodes[dest]) # ['position']
edge_trace['x'].extend([x0, x1, None])
edge_trace['y'].extend([y0, y1, None])
edge_trace['z'].extend([z0, z1, None])
# empty lists here will be appended with data to be plotted
node_trace = Scatter3d(x=[],
y=[],
z=[],
text=[],
mode='markers',
hoverinfo='text',
marker=Marker(
symbol='dot',
showscale=True,
colorscale=colorscale,
reversescale=True,
color=[],
size=marker_size,
colorbar=dict(thickness=15,
title=colorbar_title,
xanchor='left',
titleside='right'),
))
# setting nodal positions and info
for ix, node in enumerate(graph.nodes()):
x, y, z = get_position(graph.nodes[node])
node_trace['x'].append(x)
node_trace['y'].append(y)
node_trace['z'].append(z)
node_trace['text'].append(node)
node_trace['marker']['color'].append(ix)
axis = dict(showbackground=False,
showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
scene = Scene(xaxis=XAxis(axis), yaxis=YAxis(axis), zaxis=ZAxis(axis))
annotations = Annotations([
Annotation(
showarrow=False,
text=plot_description,
xref='paper',
yref='paper',
x=0,
y=0.1, # z=0.05,
xanchor='left',
yanchor='bottom', # zanchor='bottom',
font=Font(size=14))
])
layout = Layout(
title=plot_title,
titlefont=dict(size=16),
# width=1000,
# height=1000,
showlegend=False,
hovermode='closest',
scene=scene,
margin=Margin(t=100),
# margin=dict(b=20,l=5,r=5,t=40),
annotations=annotations,
)
fig_data = Data([edge_trace, node_trace])
fig = Figure(data=fig_data, layout=layout)
if out_path is None and auto_open is False:
auto_open = True
if notebook_mode:
iplot(fig, filename=out_path)
else:
plot(fig, filename=out_path, auto_open=auto_open)
return fig
showticklabels=False,
title=''
)
layout = Layout(
title="Link Structure for Delhi University - Academics",
width=1000,
height=1000,
showlegend=False,
scene=Scene(
xaxis=XAxis(axis),
yaxis=YAxis(axis),
zaxis=ZAxis(axis),
),
margin=Margin(
t=100
),
hovermode='closest',
annotations=Annotations([
Annotation(
showarrow=False,
text="",
xref='paper',
yref='paper',
x=0,
y=0.1,
xanchor='left',
yanchor='bottom',
font=Font(
size=14
)
def create_layout(self):
return Layout(
# title="Dagen tot Antwoord",
xaxis=dict(title='Antwoordtijd [dagen]'),
yaxis=dict(title='Aantal Kamervragen'),
margin=Margin(t=20))
def plotCorrelations(fileNameP, listP):
import plotly.plotly as py
#import plotly
from plotly.graph_objs import Bar, Marker, Data, Layout, XAxis, YAxis, Figure, Margin, Font
#import plotly.graph_objs as gObjLib
### authentication stuff ....
#py = plotly.plotly(username='******', key='9ebth53cdo')
#barSize = 5
fileTrace = [listP[0], listP[1], listP[2]]
projectTrace = [listP[3], listP[4], listP[5]]
stateTrace = [listP[6], listP[7], listP[8]]
namespaceTrace = [listP[9], listP[10], listP[11]]
fileCorrTrace = Bar(
x=['Corr. >= 0.50', 'Corr. within 0.0 & 0.499', 'Corr. < 0.0'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=fileTrace,
name='FileInterleaving')
projCorrTrace = Bar(
x=['Corr. >= 0.50', 'Corr. within 0.0 & 0.499', 'Corr. < 0.0'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=projectTrace,
name='ProjetInterleaving')
nspaceCorrTrace = Bar(
x=['Corr. >= 0.50', 'Corr. within 0.0 & 0.499', 'Corr. < 0.0'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=namespaceTrace,
name='NamespaceInterleaving')
stateTrace = Bar(
x=['Corr. >= 0.50', 'Corr. within 0.0 & 0.499', 'Corr. < 0.0'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=stateTrace,
name='StateInterleaving')
#fileCorrTrace['marker'] = Marker(color='blue', size=barSize)
#projCorrTrace['marker'] = Marker(color='green', size=barSize)
#nspaceCorrTrace['marker'] = Marker(color='yellow', size=barSize)
#stateTrace['marker'] = Marker(color='red', size=barSize)
fileCorrTrace['marker'] = Marker(color='blue')
projCorrTrace['marker'] = Marker(color='green')
nspaceCorrTrace['marker'] = Marker(color='yellow')
stateTrace['marker'] = Marker(color='red')
dataToPlot = Data(
[fileCorrTrace, projCorrTrace, nspaceCorrTrace, stateTrace])
layoutToUse = Layout(
title='Distribution of Correlation for 339 Datasets : ' + fileNameP,
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
barmode='group',
xaxis=XAxis(showgrid=True,
showline=True,
title='Interleaving Correlations',
titlefont=Font(family='Times New Roman',
size=12,
color='#000000'),
tickwidth=1.5),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Count',
#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),
)
fileToSave = 'plots/' + fileNameP + '.png'
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
py.image.save_as(figToPlot, fileToSave)
def plotLinesForBaseline(fileNameParam):
import csv
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.graph_objs import Layout, YAxis, Figure, Margin, Font, XAxis
xList = []
baselineAct = []
optimizedAct = []
baselinePass = []
optimizedPass = []
fileToRead = open(fileNameParam, "rU")
try:
fileReader = csv.reader(fileToRead,
delimiter=',',
dialect=csv.excel_tab)
next(fileReader, None)
for rowVar in fileReader:
xList.append(rowVar[0])
baselineAct.append(rowVar[1])
optimizedAct.append(rowVar[3])
baselinePass.append(rowVar[2])
optimizedPass.append(rowVar[4])
finally:
fileToRead.close()
baselineActTrace = go.Scatter(x=xList,
y=baselineAct,
mode='lines+markers',
name='Baseline-Undetected Active Errors')
optimizedActTrace = go.Scatter(x=xList,
y=optimizedAct,
mode='lines+markers',
name='Optimized-Undetected Active Errors')
baselinePassTrace = go.Scatter(x=xList,
y=baselinePass,
mode='lines+markers',
name='Baseline-Undetected Passive Errors')
optimizedPassTrace = go.Scatter(x=xList,
y=optimizedPass,
mode='lines+markers',
name='Optimized-Undetected Passive Errors')
ActTraces = [baselineActTrace, optimizedActTrace]
PassTraces = [baselinePassTrace, optimizedPassTrace]
layout_ActError = Layout(
title=
'Comparing Optimized Values with Baseline Values : Undetected Active Errors',
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
xaxis=XAxis(showgrid=True,
showline=True,
title='Iterations of DE',
autorange=False,
range=[0, 1100],
titlefont=Font(family='Times New Roman',
size=12,
color='#000000')),
yaxis=YAxis(showgrid=True,
showline=True,
title='Optimized Value',
range=[0, 1500],
autorange=False,
titlefont=Font(family='Times New Roman',
size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
layout_PassError = Layout(
title=
'Comparing Optimized Values with Baseline Values : Undetected Passive Errors',
titlefont=Font(family='Times New Roman', size=18, color='#000000'),
xaxis=XAxis(showgrid=True,
showline=True,
title='Iterations of DE',
autorange=False,
range=[0, 1100],
titlefont=Font(family='Times New Roman',
size=12,
color='#000000')),
yaxis=YAxis(showgrid=True,
showline=True,
title='Optimized Value',
range=[0, 5],
autorange=False,
titlefont=Font(family='Times New Roman',
size=12,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
fig_UnActErr = Figure(data=ActTraces, layout=layout_ActError)
fileNameParam = "UnActError.png"
py.image.save_as(fig_UnActErr, fileNameParam)
fig_UnPassErr = Figure(data=PassTraces, layout=layout_PassError)
fileNameParam = "UnPassError.png"
py.image.save_as(fig_UnPassErr, fileNameParam)
return "DONE!"
def plotAllStates(fileNameP, dictP):
import plotly.plotly as py
from plotly.graph_objs import Bar, Marker, Data, Layout, XAxis, YAxis, Figure, Margin, Font
#import plotly.graph_objs as gObjLib
#####
dirToSave = "plotsesscat/"
#barSize = 6
listForNormalTrace = []
listForHeavyTrace = []
listForSuperHeavyTrace = []
allCatList = ['None', 'Idle', 'System', 'Code', 'Debug', 'Build', 'Navi']
for it_ in allCatList:
#print "ZZZZZZZ", dictP[it_]
listForNormalTrace.append(dictP[it_][0])
listForHeavyTrace.append(dictP[it_][1])
listForSuperHeavyTrace.append(dictP[it_][2])
#print "length - Normal ... ", listForNormalTrace
#print "length - Heavy ... ", listForHeavyTrace
#print "length - SuperHeavy ... ", listForSuperHeavyTrace
normalTrace = Bar(
x=['None', 'Idle', 'System', 'Code', 'Debug', 'Build', 'Navi'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=listForNormalTrace,
name='Normal')
heavyTrace = Bar(
x=['None', 'Idle', 'System', 'Code', 'Debug', 'Build', 'Navi'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=listForHeavyTrace,
name='Heavy')
superHeavyTrace = Bar(
x=['None', 'Idle', 'System', 'Code', 'Debug', 'Build', 'Navi'],
#x=[ 'Idle', 'System', 'Code', 'Debug', 'Build'],
y=listForSuperHeavyTrace,
name='Super Heavy')
normalTrace['marker'] = Marker(color='green')
heavyTrace['marker'] = Marker(color='yellow')
superHeavyTrace['marker'] = Marker(color='red')
dataToPlot = Data([normalTrace, heavyTrace, superHeavyTrace])
layoutToUse = Layout(
title='Distribution of Different Session Categories',
titlefont=Font(family='Times New Roman', size=22, color='#000000'),
barmode='group',
xaxis=XAxis(showgrid=True,
showline=True,
title='Types of Sessions',
titlefont=Font(family='Times New Roman',
size=18,
color='#000000'),
tickwidth=1.5),
yaxis=YAxis(
showgrid=True,
showline=True,
title='Count',
#range=[0, 35],
autorange=True,
titlefont=Font(family='Times New Roman', size=18,
color='#000000')),
width=800,
height=600,
margin=Margin(l=140, r=40, b=50, t=80),
)
fileToSave = dirToSave + fileNameP + '.png'
figToPlot = Figure(data=dataToPlot, layout=layoutToUse)
#plot_url = py.plot(figToPlot, filename=fileToSave)
py.image.save_as(figToPlot, fileToSave)
