while changed:
changed = False
for edge in edges:
source = edge.node_source
dest = edge.node_dest
if source in connected and dest not in connected:
current.append(dest)
changed = True
if dest in connected and source not in connected:
current.append(source)
changed = True
current = indirect
connected.extend(current)
return direct, indirect
if __name__ == '__main__':
import sys
app = QApplication(sys.argv)
app.setAttribute(Qt.AA_UseHighDpiPixmaps)
from glue.core.state import load
dc = load('links.glu')
widget = DataGraphWidget(dc)
widget.show()
sys.exit(app.exec_())
while changed:
changed = False
for edge in edges:
source = edge.node_source
dest = edge.node_dest
if source in connected and dest not in connected:
current.append(dest)
changed = True
if dest in connected and source not in connected:
current.append(source)
changed = True
current = indirect
connected.extend(current)
return direct, indirect
if __name__ == '__main__':
import sys
app = QApplication(sys.argv)
app.setAttribute(Qt.AA_UseHighDpiPixmaps)
from glue.core.state import load
dc = load('links.glu')
widget = DataGraphWidget(dc)
widget.show()
sys.exit(app.exec_())
# This script was produced by glue and can be used to further customize a
# particular plot.
### Package imports
from glue.core.state import load
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
plt.ion()
#matplotlib.use('Agg')
### Set up data
data_collection = load('make_plot.py.data')
### Set up viewer
# Initialize figure
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, aspect='auto')
### Set up layers
## Layer 1: coelho14_model_paa[HDU1]
layer_data = data_collection[0]
# Get main data values
x = layer_data['mag_paa_m_high']
y = layer_data['mag_paa_m_low']
# This script was produced by glue and can be used to further customize a
# particular plot.
### Package imports
from glue.core.state import load
import matplotlib.pyplot as plt
import numpy as np
### Set up data
data_collection = load('Documents/GitHub/Wells_by_County_Histogram.py.data')
### Set up viewer
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, aspect='auto')
### Set up layers
## Layer 1: fracfocus_registry_texas
layer_data = data_collection[0]
# Get main data values
x = layer_data['col16']
# Set up histogram bins
hist_n_bin = 30
hist_x_min = np.nanmin(x)
hist_x_max = 52.5