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Commit 69f8e465 authored by DylanKruyff's avatar DylanKruyff
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Initial commit: ABC, SAX, random vector notebooks + web-app prototype

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.gitattributes 0 → 100644
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ABC-Hashing/.idea/ABC-Hashing.iml 0 → 100644
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ABC-Hashing/.ipynb_checkpoints/ABC-LSH-checkpoint.ipynb 0 → 100644
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%% Cell type:code id: tags:
``` python
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv("DailyDelhiClimateTrain.csv", index_col=0)
df.index = pd.to_datetime(df.index)
df.sort_index(inplace=True)
meantemp = df.loc[:, 'meantemp'].copy()
meantemp.head()
meantemp.plot(figsize = (10, 8));
plt.ylabel('Temperature'); plt.title('Mean Temperature');
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
from network_discovery import *
import numpy as np
window_size = 180
values = meantemp.values
data = []
for index in range(len(values)-window_size):
data.append(values[index:index+window_size])
data = np.array(data)
k, r, b = 5, 5, 10
data = binarize(data)
n = data.shape[1]
indices = [random.sample(range(n - k + 1), r) for _ in range(b)]
tables = [defaultdict(list) for _ in range(b)]
all_pairs = set()
for t in range(len(tables)):
table = tables[t]
current = indices[t]
for x in range(len(data)):
row = data[x, :]
signature = tuple([str(row[index:index + k]) for index in current])
table[signature].append(x)
print(tables[1])
print(len(values))
```
%%%% Output: stream
defaultdict(<class 'list'>, {('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]', '[0 0 0 0 0]'): [0, 358, 719, 1093], ('[0 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 0]', '[0 0 0 0 0]'): [1], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]', '[0 0 0 0 0]'): [2], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]', '[0 0 0 0 1]'): [3], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 1 1 1]', '[0 0 0 1 0]'): [4], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]', '[0 0 1 0 1]'): [5], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 0 0 1]'): [6], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 1 1]'): [7, 38], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 0]'): [8, 367, 392, 1105], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 0 0]'): [9, 368, 748, 1106], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 0]'): [10, 389, 422, 749, 1107], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 0 0]'): [11, 423, 750, 1108], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]'): [12, 13, 14, 15, 16, 17, 18, 19, 20, 363, 364, 374, 375, 424, 751, 752, 753, 1100, 1101, 1102], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 1]'): [21, 400, 425, 754, 1103, 1109], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 1 1]'): [22, 391, 762, 1104, 1110], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]'): [23, 39, 386, 763, 1111], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]'): [24, 40, 764, 1112, 1122], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 41, 42, 43, 44, 45, 46, 60, 411, 412, 418, 419, 420, 765, 777, 778, 779, 785, 786, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1123, 1124, 1125, 1126, 1127, 1134, 1135, 1136, 1137], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]'): [35, 47, 421], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 0]'): [36, 388], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 1]'): [37], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]'): [48], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]'): [49, 1120], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]', '[1 1 1 1 1]', '[1 0 1 1 1]'): [50], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 0]', '[1 1 1 1 1]', '[0 1 1 1 1]'): [51], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [52, 1130], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [53, 1131], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [54, 1132, 1162], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [55], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [56, 414, 1139], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [57, 415], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [58, 416], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [59, 417, 1133], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [61, 413, 1128, 1138], ('[1 1 1 1 1]', '[1 1 0 1 1]', '[1 1 1 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [62], ('[1 1 1 1 1]', '[1 0 1 1 0]', '[1 1 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [63], ('[1 1 1 1 1]', '[0 1 1 0 0]', '[1 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [64], ('[1 1 1 1 1]', '[1 1 0 0 0]', '[0 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [65], ('[1 1 1 1 1]', '[1 0 0 0 0]', '[0 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [66], ('[1 1 1 1 0]', '[0 0 0 0 1]', '[1 1 1 0 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [67], ('[1 0 1 0 0]', '[0 0 0 1 1]', '[1 1 0 0 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): 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'[0 0 0 0 0]', '[0 1 1 1 1]', '[0 0 0 0 1]', '[0 0 0 0 0]'): [1218], ('[1 1 0 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 0 0 1 1]', '[0 0 0 0 0]'): [1219], ('[1 0 1 1 0]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 0 1 1 1]', '[0 0 0 0 1]'): [1220], ('[0 1 1 0 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 1 1 1 0]', '[0 0 0 1 1]'): [1221], ('[1 1 0 1 0]', '[0 0 0 0 0]', '[1 1 1 1 0]', '[1 1 1 0 1]', '[0 0 1 1 1]'): [1222], ('[1 0 1 0 0]', '[0 0 0 0 1]', '[1 1 1 0 0]', '[1 1 0 1 1]', '[0 1 1 1 1]'): [1223], ('[0 1 0 0 0]', '[0 0 0 1 1]', '[1 1 0 0 0]', '[1 0 1 1 0]', '[1 1 1 1 1]'): [1224], ('[1 0 0 0 0]', '[0 0 1 1 0]', '[1 0 0 0 0]', '[0 1 1 0 1]', '[1 1 1 1 0]'): [1225], ('[0 0 0 0 1]', '[0 1 1 0 1]', '[0 0 0 0 0]', '[1 1 0 1 0]', '[1 1 1 0 1]'): [1226], ('[0 0 0 1 0]', '[1 1 1 1 0]', '[0 0 0 0 0]', '[1 1 1 0 0]', '[1 1 0 1 0]'): [1227], ('[0 0 1 0 0]', '[1 1 1 0 0]', '[0 0 0 0 0]', '[1 1 0 0 0]', '[1 0 1 0 0]'): [1228], ('[0 1 0 0 0]', '[1 1 1 0 1]', '[0 0 0 0 0]', '[1 0 0 0 0]', '[0 1 0 0 0]'): [1229], ('[1 0 0 0 1]', '[1 1 0 1 0]', '[0 0 0 0 0]', '[0 0 0 0 1]', '[1 0 0 0 0]'): [1230], ('[1 0 0 1 1]', '[1 0 1 0 1]', '[0 0 0 0 0]', '[0 0 0 1 1]', '[0 0 0 0 0]'): [1231], ('[0 0 1 1 1]', '[0 1 1 1 1]', '[0 0 0 0 0]', '[0 0 1 1 0]', '[0 0 0 0 0]'): [1232], ('[0 1 1 1 1]', '[1 1 1 1 0]', '[0 0 0 0 0]', '[0 1 1 0 0]', '[0 0 0 0 0]'): [1233], ('[1 1 1 1 1]', '[1 1 1 0 0]', '[0 0 0 0 0]', '[1 1 0 0 1]', '[0 0 0 0 0]'): [1234], ('[1 1 1 1 0]', '[1 1 0 0 0]', '[0 0 0 0 0]', '[1 0 0 1 1]', '[0 0 0 0 1]'): [1235], ('[1 1 1 0 1]', '[1 0 0 0 0]', '[0 0 0 0 0]', '[0 0 1 1 1]', '[0 0 0 1 1]'): [1236], ('[1 1 0 1 1]', '[0 0 0 0 0]', '[0 0 0 0 0]', '[0 1 1 1 1]', '[0 0 1 1 1]'): [1237], ('[1 0 1 1 1]', '[0 0 0 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 1 1 1 0]'): [1238], ('[0 1 1 1 1]', '[0 0 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 0]', '[1 1 1 0 1]'): [1239], ('[1 1 1 1 0]', '[0 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 0 1]', '[1 1 0 1 1]'): [1240], ('[1 1 1 0 0]', '[1 1 1 1 0]', '[0 0 0 0 0]', '[1 1 0 1 1]', '[1 0 1 1 1]'): [1241], ('[1 1 0 0 0]', '[1 1 1 0 1]', '[0 0 0 0 0]', '[1 0 1 1 1]', '[0 1 1 1 1]'): [1242], ('[1 0 0 0 0]', '[1 1 0 1 1]', '[0 0 0 0 0]', '[0 1 1 1 1]', '[1 1 1 1 0]'): [1243], ('[0 0 0 0 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 0]', '[1 1 1 0 0]'): [1244], ('[0 0 0 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 0 0]', '[1 1 0 0 1]'): [1245], ('[0 0 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 0 0 0]', '[1 0 0 1 0]'): [1246], ('[0 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 0 0 0 0]', '[0 0 1 0 1]'): [1247], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 0 0 1]', '[0 1 0 1 1]'): [1248], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 0 1 1]', '[1 0 1 1 0]'): [1249], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 1 1 1]', '[0 1 1 0 0]'): [1250], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[1 0 0 1 1]'): [1266], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 0 1 1 1]'): [1267]})
1462
%% Cell type:code id: tags:
``` python
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot
from ipywidgets import VBox, HBox
fig = go.FigureWidget()
fig.add_trace(
go.Scatter(
x=list(range(len(meantemp.values))),
y=meantemp.values,
mode='markers'
)
)
main_trace = fig.data[0]
colors = ['#a3a7e4'] * len(values)
sizes = [10] * len(values)
main_trace.marker.color = colors.copy()
main_trace.marker.size = sizes.copy()
fig.layout.hovermode = 'closest'
# create our callback function
def update_point(trace, points, selector):
for i in points.point_inds:
image.children = (fig,)
table_hash_value = []
table_cluster = []
neighbours = [];
for t in range(len(tables)):
table = tables[t]
hsh = indices[t]
row = data[i]
signature = tuple([str(row[index:index + k]) for index in hsh])
neighbours.extend(table[signature])
table_hash_value.append(str(signature))
table_cluster.append(str(table[signature]))
neighbours = set(neighbours)
c = colors.copy()
s = sizes.copy()
for index in neighbours:
c[index] = '#bae2be'
s[index] = 20
fig2 = go.FigureWidget(data=[go.Table(header=dict(values=['Hash function', 'Hash value', 'Cluster']),
cells=dict(values=[indices,table_hash_value, table_cluster]))
])
image.children += (fig2,)
i = 0
for neighbour in neighbours:
i = i + 1
if i == 5:
break
f = go.FigureWidget()
f.add_trace(
go.Scatter(x=meantemp.index[neighbour: neighbour + window_size], y=meantemp.values[neighbour: neighbour + window_size])
)
image.children += (f,)
with fig.batch_update():
main_trace.marker.color = c
main_trace.marker.size = s
main_trace.on_click(update_point)
image = VBox([fig])
image
```
%%%% Output: display_data
ABC-Hashing/ABC-LSH.ipynb 0 → 100644
View file @ 69f8e465
%% Cell type:code id: tags:
``` python
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv("DailyDelhiClimateTrain.csv", index_col=0)
df.index = pd.to_datetime(df.index)
df.sort_index(inplace=True)
meantemp = df.loc[:, 'meantemp'].copy()
meantemp.head()
meantemp.plot(figsize = (10, 8));
plt.ylabel('Temperature'); plt.title('Mean Temperature');
```
%%%% Output: display_data
![](data:image/png;base64,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)
%% Cell type:code id: tags:
``` python
from network_discovery import *
import numpy as np
window_size = 180
values = meantemp.values
data = []
for index in range(len(values)-window_size):
data.append(values[index:index+window_size])
data = np.array(data)
k, r, b = 5, 5, 10
data = binarize(data)
n = data.shape[1]
indices = [random.sample(range(n - k + 1), r) for _ in range(b)]
tables = [defaultdict(list) for _ in range(b)]
all_pairs = set()
for t in range(len(tables)):
table = tables[t]
current = indices[t]
for x in range(len(data)):
row = data[x, :]
signature = tuple([str(row[index:index + k]) for index in current])
table[signature].append(x)
print(tables[1])
print(len(values))
```
%%%% Output: stream
defaultdict(<class 'list'>, {('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]', '[0 0 0 0 0]'): [0, 358, 719, 1093], ('[0 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 0]', '[0 0 0 0 0]'): [1], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]', '[0 0 0 0 0]'): [2], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]', '[0 0 0 0 1]'): [3], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 1 1 1]', '[0 0 0 1 0]'): [4], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]', '[0 0 1 0 1]'): [5], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 0 0 1]'): [6], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 1 1]'): [7, 38], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 0]'): [8, 367, 392, 1105], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 0 0]'): [9, 368, 748, 1106], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 0]'): [10, 389, 422, 749, 1107], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 0 0]'): [11, 423, 750, 1108], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]'): [12, 13, 14, 15, 16, 17, 18, 19, 20, 363, 364, 374, 375, 424, 751, 752, 753, 1100, 1101, 1102], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 1]'): [21, 400, 425, 754, 1103, 1109], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 1 1]'): [22, 391, 762, 1104, 1110], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]'): [23, 39, 386, 763, 1111], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]'): [24, 40, 764, 1112, 1122], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 41, 42, 43, 44, 45, 46, 60, 411, 412, 418, 419, 420, 765, 777, 778, 779, 785, 786, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1123, 1124, 1125, 1126, 1127, 1134, 1135, 1136, 1137], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]'): [35, 47, 421], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 0]'): [36, 388], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 1]'): [37], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]'): [48], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]'): [49, 1120], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]', '[1 1 1 1 1]', '[1 0 1 1 1]'): [50], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 0]', '[1 1 1 1 1]', '[0 1 1 1 1]'): [51], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [52, 1130], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [53, 1131], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [54, 1132, 1162], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [55], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [56, 414, 1139], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [57, 415], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [58, 416], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [59, 417, 1133], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [61, 413, 1128, 1138], ('[1 1 1 1 1]', '[1 1 0 1 1]', '[1 1 1 0 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [62], ('[1 1 1 1 1]', '[1 0 1 1 0]', '[1 1 0 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [63], ('[1 1 1 1 1]', '[0 1 1 0 0]', '[1 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [64], ('[1 1 1 1 1]', '[1 1 0 0 0]', '[0 0 1 1 1]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [65], ('[1 1 1 1 1]', '[1 0 0 0 0]', '[0 1 1 1 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [66], ('[1 1 1 1 0]', '[0 0 0 0 1]', '[1 1 1 0 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): [67], ('[1 0 1 0 0]', '[0 0 0 1 1]', '[1 1 0 0 0]', '[1 1 1 1 1]', '[1 1 1 1 1]'): 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[1229], ('[1 0 0 0 1]', '[1 1 0 1 0]', '[0 0 0 0 0]', '[0 0 0 0 1]', '[1 0 0 0 0]'): [1230], ('[1 0 0 1 1]', '[1 0 1 0 1]', '[0 0 0 0 0]', '[0 0 0 1 1]', '[0 0 0 0 0]'): [1231], ('[0 0 1 1 1]', '[0 1 1 1 1]', '[0 0 0 0 0]', '[0 0 1 1 0]', '[0 0 0 0 0]'): [1232], ('[0 1 1 1 1]', '[1 1 1 1 0]', '[0 0 0 0 0]', '[0 1 1 0 0]', '[0 0 0 0 0]'): [1233], ('[1 1 1 1 1]', '[1 1 1 0 0]', '[0 0 0 0 0]', '[1 1 0 0 1]', '[0 0 0 0 0]'): [1234], ('[1 1 1 1 0]', '[1 1 0 0 0]', '[0 0 0 0 0]', '[1 0 0 1 1]', '[0 0 0 0 1]'): [1235], ('[1 1 1 0 1]', '[1 0 0 0 0]', '[0 0 0 0 0]', '[0 0 1 1 1]', '[0 0 0 1 1]'): [1236], ('[1 1 0 1 1]', '[0 0 0 0 0]', '[0 0 0 0 0]', '[0 1 1 1 1]', '[0 0 1 1 1]'): [1237], ('[1 0 1 1 1]', '[0 0 0 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 1 1 1 0]'): [1238], ('[0 1 1 1 1]', '[0 0 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 0]', '[1 1 1 0 1]'): [1239], ('[1 1 1 1 0]', '[0 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 0 1]', '[1 1 0 1 1]'): [1240], ('[1 1 1 0 0]', '[1 1 1 1 0]', '[0 0 0 0 0]', '[1 1 0 1 1]', '[1 0 1 1 1]'): [1241], ('[1 1 0 0 0]', '[1 1 1 0 1]', '[0 0 0 0 0]', '[1 0 1 1 1]', '[0 1 1 1 1]'): [1242], ('[1 0 0 0 0]', '[1 1 0 1 1]', '[0 0 0 0 0]', '[0 1 1 1 1]', '[1 1 1 1 0]'): [1243], ('[0 0 0 0 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 0]', '[1 1 1 0 0]'): [1244], ('[0 0 0 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 0 0]', '[1 1 0 0 1]'): [1245], ('[0 0 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 0 0 0]', '[1 0 0 1 0]'): [1246], ('[0 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 0 0 0 0]', '[0 0 1 0 1]'): [1247], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 0 0 1]', '[0 1 0 1 1]'): [1248], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 0 1 1]', '[1 0 1 1 0]'): [1249], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[0 0 1 1 1]', '[0 1 1 0 0]'): [1250], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[1 0 0 1 1]'): [1266], ('[1 1 1 1 1]', '[1 1 1 1 1]', '[0 0 0 0 0]', '[1 1 1 1 1]', '[0 0 1 1 1]'): [1267]})
1462
%% Cell type:code id: tags:
``` python
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot
from ipywidgets import VBox, HBox
fig = go.FigureWidget()
fig.add_trace(
go.Scatter(
x=list(range(len(meantemp.values))),