I'm having trouble getting the color_map to work with my networkx graph. It's fairly simply code but won't seem to work. I've looked through other similar threads but no the solutions don't seem to work.
I have data that look like this:
edgelist_manual = [{'source': 'ABE', 'target': 'ATL', 'value': 851},
{'source': 'ABE', 'target': 'BHM', 'value': 1},
{'source': 'ABE', 'target': 'CLE', 'value': 805}]
edgelist = pd.DataFrame(edgelist_manual)
nodelist_manual = [{'source': 'ABE', 'value': '4807', 'group': 0},
{'source': 'ABI', 'value': '2660', 'group': 4},
{'source': 'ABQ', 'value': '41146', 'group': 2}]
nodelist = pd.DataFrame(nodelist_manual)
I run the code below, but my color_map keep screwing up. I just get a key error on the 'group' reference.
import itertools
import copy
import networkx as nx
import pandas as pd
import matplotlib.pyplot as plt
nodelist = pd.read_csv('final_nodes.csv')
edgelist = pd.read_csv('final_edges.csv')
g = nx.Graph()
for i, elrow in edgelist.iterrows():
g.add_edge(elrow[0], elrow[1], attr_dict=elrow[2:].to_dict())
for i, nlrow in nodelist.iterrows():
g.node[nlrow['source']].update(nlrow[1:].to_dict())
color_map = {0: 'r', 1:'b', 2:'r', 3:'b', 4:'r', 5:'b'}
colors = [color_map[g.node[node]['group']] for node in g]
nx.draw(g, node_color=colors)
ax = plt.gca()
ax.collections[0].set_edgecolor("#555555")
plt.show()
The only difference from this and my code is that rather than creating the data manually I'm loading it from .csv. I've checked for trailing whitespaces on the feature labels but nothing. I don't understand indices well so I wonder if those are messing it up. Any ideas?
Thanks!
Related
I am working to adapt a python2.7 code that uses keras and tensorflow to implement a CNN but looks like the keras API has changed a little bit since when the original code was idealized. I keep getting an error about "Negative dimension after subtraction" and I can not find out what is causing it.
Unfortunately I am not able to provide an executable piece of code because I was not capable of make the original code works, but the repository containing all the source files can be found here.
The piece of code:
from keras.callbacks import EarlyStopping
from keras.layers.containers import Sequential
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.layers.core import Reshape, Flatten, Dropout, Dense
from keras.layers.embeddings import Embedding
from keras.models import Graph
from keras.preprocessing import sequence
filter_lengths = [3, 4, 5]
self.model = Graph()
'''Embedding Layer'''
self.model.add_input(name='input', input_shape=(max_len,), dtype=int)
self.model.add_node(Embedding(
max_features, emb_dim, input_length=max_len), name='sentence_embeddings', input='input')
'''Convolution Layer & Max Pooling Layer'''
for i in filter_lengths:
model_internal = Sequential()
model_internal.add(
Reshape(dims=(1, self.max_len, emb_dim), input_shape=(self.max_len, emb_dim))
)
model_internal.add(Convolution2D(
nb_filters, i, emb_dim, activation="relu"))
model_internal.add(
MaxPooling2D(pool_size=(self.max_len - i + 1, 1))
)
model_internal.add(Flatten())
self.model.add_node(model_internal, name='unit_' + str(i), input='sentence_embeddings')
What I have tried:
m = tf.keras.Sequential()
m.add(tf.keras.Input(shape=(max_len, ), name="input"))
m.add(tf.keras.layers.Embedding(max_features, emb_dim, input_length=max_len))
filter_lengths = [ 3, 4, 5 ]
for i in filter_lengths:
model_internal = tf.keras.Sequential(name=f'unit_{i}')
model_internal.add(
tf.keras.layers.Reshape(( 1, max_len, emb_dim ), input_shape=( max_len, emb_dim ))
)
model_internal.add(
tf.keras.layers.Convolution2D(100, i, emb_dim, activation="relu")
)
model_internal.add(
tf.keras.layers.MaxPooling2D(pool_size=( max_len - i + 1, 1 ))
)
model_internal.add(
tf.keras.layers.Flatten()
)
m.add(model_internal)
I do not expect a complete solution, what I am really trying to understand is what is the cause to the following error:
Negative dimension size caused by subtracting 3 from 1 for '{{node conv2d_5/Conv2D}} = Conv2D[T=DT_FLOAT, data_format="NHWC", dilations=[1, 1, 1, 1], explicit_paddings=[], padding="VALID", strides=[1, 200, 200, 1], use_cudnn_on_gpu=true](Placeholder, conv2d_5/Conv2D/ReadVariableOp)' with input shapes: [?,1,300,200], [3,3,200,100].
My Altair plots are no longer displaying in VS Code. Is anyone else having this issue? Matplotlib / pandas plots still show normally.
I used the simple bar chart example:
source = pd.DataFrame({
'a': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],
'b': [28, 55, 43, 91, 81, 53, 19, 87, 52]
})
I can plot a pandas bar chart and get it to display:
source.plot.bar()
But I get no output when using Altair:
alt.Chart(source).mark_bar().encode(
x='a',
y='b'
)
I think that you need to call the chart, so first you need to save the chart as a variable and then call.
Chart1=alt.Chart(source).mark_bar().encode(
x='a',
y='b'
)
Chart1
I have two different Python Dashboards, both of which visualize different types of financial data. I would like to have both figures on one single dashboard, one above the other. Would you happen to know if that is possible? If so, I'm sure one has to extend the entire app structure, including the layout and, more importantly, callback part. Has anyone any experience with merging two apps into one dashboard? Below you'll find my code I've assembled so far.
First Dashboard:
# import relevant packages
import pandas as pd
import numpy as np
import matplotlib as mpl
import plotly
import dash
import pyodbc
import plotly.express as px
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
data = [['2020-01-31', 100, 100, 100], ['2020-02-28', 101, 107, 99], ['2020-03-31', 104, 109, 93], ['2020-04-30', 112, 115, 94], ['2020-05-31', 112, 120, 89]]
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['DATE', 'A', 'B', 'C'])
df = df.set_index('DATE')
df
# create the Dash app
app = dash.Dash()
# Set up the app layout
app.layout = html.Div(children=[
html.H1(children='Index Dashboard'),
html.P('''Pick one or more stocks from the dropdown below.'''),
dcc.Dropdown(id='index-dropdown',
options=[{'label': x, 'value': x}
for x in df.columns],
value='A',
multi=True, clearable=True),
dcc.Graph(id='price-graph')
])
# Set up the callback function
#app.callback(
Output(component_id='price-graph', component_property='figure'),
[Input(component_id='index-dropdown', component_property='value')],
)
def display_time_series(selected_index):
dff = df[selected_index] # Only columns selected in dropdown
fig = px.line(dff, x=df.index, y=selected_index, labels={'x': 'x axis label'})
fig.update_layout(
title="Price Index Development",
xaxis_title="Month",
yaxis_title="Price",
font=dict(size=13))
return fig
# Run local server
if __name__ == '__main__':
app.run_server(debug=True, use_reloader=False)
Second Dashboard:
data2 = [['A', 'B', 0.4], ['A', 'C', 0.5], ['A', 'D', 0.1], ['X', 'Y', 0.15], ['X', 'Z', 0.85]]
df2 = pd.DataFrame(data2, columns = ['BM_NAME', 'INDEX_NAME', 'WEIGHT'])
df2
barchart = px.bar(
data_frame=df2,
x=df2.BM_NAME,
y="WEIGHT",
color="INDEX_NAME",
opacity=0.9,
barmode='group')
barchart
# create the Dash app
app = dash.Dash()
# set up app layout
app.layout = html.Div(children=[
html.H1(children='BM Composition'),
dcc.Dropdown(id='BM-dropdown',
options=[{'label': x, 'value': x}
for x in df2.BM_NAME.unique()],
value='A',
multi=False, clearable=True),
dcc.Graph(id='bar-chart')
])
# set up the callback function
#app.callback(
Output(component_id="bar-chart", component_property="figure"),
[Input(component_id="BM-dropdown", component_property="value")],
)
def display_BM_composition(selected_BM):
filtered_BM = df2[df2.BM_NAME == selected_BM] # Only use unique values in column "BM_NAME" selected in dropdown
barchart = px.bar(
data_frame=filtered_BM,
x="BM_NAME",
y="WEIGHT",
color="INDEX_NAME",
opacity=0.9,
barmode='group')
return barchart
# Run local server
if __name__ == '__main__':
app.run_server(debug=True, use_reloader=False)
Many thanks in advance!
I'd like to remove a specific edge (specific color) from a MultiGraph.
How can I do that?
Following code does not work.
#!/usr/bin/env python
import matplotlib.pyplot as plt
import networkx as nx
G = nx.MultiGraph()
# the_colored_graph.add_edge(v1, v2, "red")
G.add_edge(1, 2, color="red")
G.add_edge(2, 3, color="red")
G.add_edge(4, 2, color="green")
G.add_edge(2, 4, color="blue")
print (G.edges(data=True))
# G.remove_edge(2, 4, color="green")
#
selected_edge = [(u,v) for u,v,e in G.edges(data=True) if e['color'] == 'green']
print (selected_edge)
G.remove_edge(selected_edge[0][0], selected_edge[0][1])
print (G.edges(data=True))
nx.draw(G)
plt.show()
When constructing the multigraph, assign a "key" attribute to each edge (the key could be anything that disambiguates the parallel edges - say, the color):
G.add_edge(1, 2, color="red", key='red')
Remove an edges by specifying the end nodes and the key:
G.remove_edge(1, 2, key='red')
I am attempting to write a simple code to simply plot a bar graph of some fruit names in the x-axis vs corresponding sales units. The aim of this code is just to understand how to query postgres results from heroku hosted database through a dash app.
Below is the code,
from dash import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import psycopg2
import os
DATABASE_URL = os.environ['DATABASE_URL']
conn = psycopg2.connect(DATABASE_URL, sslmode='require')
cur = conn.cursor()
cur.execute("SELECT fruits FROM pgrt_table")
fruits1=cur.fetchall()
#print(fruits1)
cur.execute("SELECT sales FROM pgrt_table")
sales1=cur.fetchall()
app = dash.Dash()
app.layout = html.Div(children=[
html.H1(
children='Hello Dash'
),
html.Div(
children='''Dash: A web application framework for Python.'''
),
dcc.Graph(
id='example-graph',
figure=go.Figure(
data=[
go.Bar(
x=fruits1, y=sales1, name='SF'),
#{'x': [1, 2, 3], 'y': [2, 4, 5], 'type': 'bar', 'name': u'Montréal'},
],
#'layout':{
# 'title': 'Dash Data Visualization'
#}
)
)
])
if __name__ == '__main__':
app.run_server(debug=True)
The output is below,
Output to the above code
The corresponding output is just the axes with no bar graphs. The connection with the db is working since printing fruits1 or sales1 gives me the values from the columns in postgres. The only issue is the plotting.
NOTE: This question has been heavily modified since the previous draft was extremely vague without any code to show for.
Example:
fruits1 = [('apple',), ('banana',),
('mango',), ('pineapple',),
('peach',), ('watermelon',)]
The output of your database cannot be used directly:
xData = [fruit[0] for fruit in fruits1]
# gives ['apple', 'banana', 'mango', 'pineapple', 'peach', 'watermelon']
yData = [sales[0] for sales in sales1]
You have to assign your data to the go.Bar object:
go.Bar(x=xData, y=yData, name='SF')