Develop Reference

Position the radio button and label (div) of dcc.RadioItems to be next to each other inside a flexbox

In the layout of my Dash app, I have flexible container containing a dcc.RadioItems component. I want all of the labels and their corresponding radio buttons to be next to each other, however I want each button-label pair to be vertically stacked. This works fine until I want to change the label to not just be text, but another Dash component (an html.Div exactly, so I can format its margins properties).
Here's the part of the layout responsible for the dcc.RadioItems and its parent container:
dbc.Container([
dcc.RadioItems([
{'label': html.Div(['Label 1'],
style={'margin-bottom': '20px'}), 'value': 'l1'},
{'label': html.Div(['Label 2'],
style={'margin-bottom': '20px'}), 'value': 'l2'},
{'label': html.Div(['Label 3'],
style={'margin-bottom': '20px'}), 'value': 'l3'}],
id="radio-items", inline=False, labelStyle={'display': 'block'})
], id="container-radio", style={"display": "flex", "flex-direction": "column",
"justify-content": "center", "align-items": "center"}),
This version makes the button-label pair appear under each other like this
o
label1
o
label2
o
label3
whereas I want it to be positioned like
o label1
o label2
o label3
I also want the RadioItems position to be centered in the parent container, both horizontally and vertically, thus the parent container style has justify-content and align-items attributes, but I assume that has little to do with my problem (might be wrong, as I am not a web-dev developer). I have tested all possible combinations of flex-direction, labelStyle and inline but were not able to get the positioning I desire. I have a feeling this problem has to do something with the underlying css classes and I am just not experienced in front-end enough to solve it.

Python folium synchronizing 2 markerclusters

I have a situation, where I decided to distinguish my markers slightly by adding the MarkerCluster to the existing Marker.
The clustering works, although isn't synchronized. It means, that if I switch one layer off, just the first markercluster disappears, whereas the second criterion defined as CircleMarker still appears like shown below.
My code is:
df = pd.read_csv("or_geo.csv")
fo=FeatureGroup(name="OR",overlay = True)
openreach_cluster = MarkerCluster(name="OR").add_to(map)
openreach_status = MarkerCluster(control=False,
visible=True
).add_to(map)
for i,row in df.iterrows():
lat =df.at[i, 'lat']
lng = df.at[i, 'lng']
sp = df.at[i, 'sp']
stat = df.at[i,'status']
popup = df.at[i,'sp'] +'<br>' + str(df.at[i, 'street']) + '<br>' + str(df.at[i, 'post code']) + '<br>{}'.format(style)
or_marker = folium.Marker(location=[lat,lng], tooltip='<strong>Job details</strong>', popup=popup, icon = folium.Icon(
color='blue', icon='glyphicon-calendar'))
or_stat_marker = folium.CircleMarker(
location=[lat,lng],
radius=10,
color=or_color(stat),
fill_color=or_color(stat),
fill_opacity=0.5)
openreach_cluster.add_child(or_marker)
openreach_status.add_child(or_stat_marker)
Is there any way to combine these markerClusters together or sync them?
UPDATE:
The first approach from the answer below, unfortunately, doubles the jobs up and the user can't see them until clicks on any of them shown below:
This option would be fantastic if the behavior could be the same as in the image above.
UPDATE II:
The second approach is still not what I am looking for, because the clusters are doubled again and after clicking the circlemarker falls almost in the opposite direction as presented in the image above.
I need to have the behaviors exactly like those displayed on the top-left image. The circlemarker should be integrated with the point marker.

If I got you right, I think there are two possibilities:
Use the same cluster
Add your markers from or_stat_marker to the openreach_cluster and not to another cluster to de-/activate them at the same time with the same button
# was
openreach_cluster.add_child(or_marker)
openreach_status.add_child(or_stat_marker)
# try this
openreach_cluster.add_child(or_marker)
openreach_cluster.add_child(or_stat_marker)
Use marker subgroups
In this case you will have three checkmarks, one parent and two childs for each markercluster which gives full control to visibility
UPDATE: If you add the control=False option to the subgroup you will only see the parent group in LayerControl which then show/hide both groups. But the matter of markers "spreading for visibility" still is a problem I think
Another UPDATE: You are able to deactivate the clustering according to the map zoom level or even at all by using disableClusteringAtZoom option (use True or an int number for zoom level). See here for reference
# markergroups in layercontrol
mc = folium.plugins.MarkerCluster(name='OR',
overlay=True,
control=True,
show=True,
disableClusteringAtZoom=15) # choose zoom lvl to your needs
mc.add_to(map)
sub1 = folium.plugins.FeatureGroupSubGroup(mc, name='openreach_cluster', control=False, show=True) # False --> deactivated at start
sub1.add_to(map)
sub2 = folium.plugins.FeatureGroupSubGroup(mc, name='openreach_status', control=False)
sub2.add_to(map)
# the layercontrol itself
lc = folium.map.LayerControl(collapsed=False)
lc.add_to(map)
# ...
for i, row in df.iterrows():
# ...
or_marker = folium.Marker(...)
or_marker.add_to(sub1)
or_stat_marker = folium.CircleMarker(...)
or_stat_marker.add_to(sub2)
My Result:
By following the second approach described I get a map shown here. There is one checkmark "Segment Markers" which shows/hides the markers including the circles. They don't move around when clicked and are fully shown when zoomed in to a specific lvl by using disableClusteringAtZoom.
Sorry this didn't work for your problem, I really don't know why ..

How to get rid of this popup when hovering over a label in the Chord Diagram (Holoviews - Python)

Exactly like the title says, I've used some code that I collected from multiple places to build up this Chord diagram, but unfortunately one last thing that's kind of going to hinder that 100% perfection is this popup that shows up whenever I hover over the label. The pop up remains there even when the mouse is moving elsewhere...
By the way, I'm using Python and Holoviews for plotting the chord.
I'm pretty sure this is due to a bug or something... however, I'd love to find a way to bypass it...
Example here : bug example
Code :
%%opts Chord [height=600 width=600 title="Transactions from 2000 to 2021" ]
#plot
#edit links = moves[moves['Transactions'] > x] // x refers to the number of transactions minimum for the diagram display
moves = moves[moves['Transactions']>5]
links = moves
chord = hv.Chord(links)
chord
nodesl = []
c = []
for i, row in moves.iterrows():
c.append(row[0])
c.append(row[1])
c = pd.DataFrame(c)
c.drop_duplicates(inplace=True)
c.reset_index(inplace=True)
c.drop(columns='index', inplace=True)
c
nodes = []
for i, row in c.iterrows():
nodes.append({'name':row[0]})
nodes = pd.DataFrame(nodes)
# nodes
nodes = hv.Dataset(nodes, 'name')
nodes.data.head()
%%opts Chord [height=800 width=800 bgcolor="black"]
%%opts Chord [title="Transactions from 2000 to 2021 (Countries with over 5 moves)\nTip: Please do not hover over the label as it might produce a bug, else refresh the page" ]
chord = hv.Chord((links, nodes)).select(value=(5, None))
#this function allows text to fit perfectly on the screen
def rotate_label(plot, element):
text_cds = plot.handles['text_1_source']
length = len(text_cds.data['angle'])
text_cds.data['angle'] = [0]*length
xs = text_cds.data['x']
text = np.array(text_cds.data['text'])
xs[xs<0] -= np.array([len(t)*0.019 for t in text[xs<0]])
chord.opts(
opts.Chord(cmap='Category10',
edge_color=dim('Target').str(),
node_color=dim('name').str(),
labels='name',
label_text_color="white",
hooks=[rotate_label]
))
chord

The ??? usually indicates that some field it's trying to display isn't available; not sure why that would be in this case. You can always override the default tools HoloViews uses for Bokeh by setting default_tools=[] and then specify whatever tools you do want, without 'hover', e.g. tools=['save', 'pan', 'wheel_zoom', 'box_zoom', 'reset'].

canvasObjects; found PartInstance, expecting tuple in Abaqus/CAE

I'm developening an Abaqus/CAE plug-in, in this plug-in i'm using the gui toolkit, and i have a button that uses the PickStep, on click the button i can select a PartInstance in the viewport.
Then i want to export the selected PartInstance to an .obj file but when i try it, abaqus displays an error.
This is an example of my PICK BUTTON:
# PICK BUTTON 1
pickHf = FXHorizontalFrame(p=col2, opts=0, x=0, y=0, w=0, h=0, pl=0, pr=0, pt=0, pb=0, hs=DEFAULT_SPACING,
vs=DEFAULT_SPACING)
# Note: Set the selector to indicate that this widget should not be
# colored differently from its parent when the 'Color layout managers'
# button is checked in the RSG Dialog Builder dialog.
pickHf.setSelector(99)
label1 = FXLabel(p=pickHf, text='' + ' (None)', ic=None, opts=LAYOUT_CENTER_Y | JUSTIFY_LEFT)
pickHandler1 = DBPickHandler(form, form.uper, 'Select a 3D, discrete and dependent meshed instance', INSTANCES,
1, label1)
icon = afxGetIcon('select', AFX_ICON_SMALL)
FXButton(p=pickHf, text='\tPick Items in Viewport', ic=icon, tgt=pickHandler1, sel=AFXMode.ID_ACTIVATE,
opts=BUTTON_NORMAL | LAYOUT_CENTER_Y, x=0, y=0, w=0, h=0, pl=2, pr=2, pt=1, pb=1)
I save the value in an ObjectKeyword:
self.uper = AFXObjectKeyword(self.cmd, 'uper', True, pickedDefault)
This is how i export the PartInstance to .obj:
print 'Uper - ' + uper[0].name
f.write('Uper - '+uper[0].name+'\n')
session.writeOBJFile(fileName='C:/temp/Uper.obj', canvasObjects=(uper[0]))
That displays and error, and i also tried this:
print 'Fixed - ' + fixed[0].name
f.write(fixed[0].name+'\n')
fixedobj = open('Fixed.obj', 'w')
pickle.dump(fixed[0], fixedobj)
fixedobj.close()
But that does not work either.
I get this error:
canvasObjects;found PartInstance, expecting tuple

This answer will help you. On your call to session.writeOBJFile you are trying to create a one element tuple for the canvasObjects argument. Simply wrapping the item in parentheses won't achieve that. You need to add a comma to make it a tuple:
session.writeOBJFile(fileName='C:/temp/Uper.obj', canvasObjects=(uper[0],))
The Abaqus documentation says this about canvasObjects:
canvasObjects
A sequence of canvas objects to export.
I'm not sure if PartInstance is considered a canvas object or not, but you may still have problems even after correcting the argument to be a tuple. If so, make sure the items of the tuple are proper canvas objects.

dynamic plotting in wxpython

I have been developing a GUI for reading continuous data from a serial port. After reading the data, some calculations are made and the results will be plotted and refreshed (aka dynamic plotting). I use the wx backend provided in the matplotlib for this purposes. To do this, I basically use an array to store my results, in which I keep appending it to, after each calculation, and replot the whole graph. To make it "dynamic", I just set the x-axis lower and upper limits for each iteration. Something like found in:
http://eli.thegreenplace.net/2008/08/01/matplotlib-with-wxpython-guis/
The problem, however, is that since the data is continuous, and if I keep plotting it, eventually the system memory will run out and system will crash. Is there any other way I can plot my result continuously?

To do this, I basically use an array
to store my results, in which I keep
appending it to
Try limiting the size of this array, either by deleting old data or by deleting every n-th entry (the screen resolution will prevent all entries to be displayed anyway). I assume you write all the data to disk so you won't lose anything.
Also, analise your code for memory leaks. Stuff you use and don't need anymore but that doesn't get garbage-collected because you still have a reference to it.

I have created such a component with pythons Tkinter. The source is here.
Basically, you have to keep the plotted data somewhere. You cannot keep an infinite amount of data points in memory, so you either have to save it to disk or you have to overwrite old data points.

Data and representation of data are two different things. You might want to store your data to disk if it's important data to be analyzed later, but only keep a fixed period of time or the last N points for display purposes. You could even let the user pick the time frame to be displayed.

I actually ran into this problem (more of a mental block, actually...).
First of all I copy-pasted some wx Plot code from wx Demo Code.
What I do is keep a live log of a value, and compare it to two markers (min and max, shown as red and green dotted lines) (but I will make these 2 markers optional - hence the optional parameters).
In order to implement the live log, I first wanted to use the deque class, but since the data is in tuple mode (x,y coordinates) I gave up and just tried to rewrite the entire parameter list of tuples: see _update_coordinates.
It works just fine for keeping track of the last 100-10,000 plots. Would have also included a printscreen, but I'm too much of a noob at stackoverflow to be allowed :))
My live parameter is updated every 0.25 seconds over a 115kbps UART.
The trick is at the end, in the custom refresh method!
Here is most of the code:
class DefaultPlotFrame(wx.Frame):
def __init__(self, ymin=0, ymax=MAXIMUM_PLOTS, minThreshold=None,
maxThreshold=None, plotColour='blue',
title="Default Plot Frame",
position=(10,10),
backgroundColour="yellow", frameSize=(400,300)):
self.minThreshold = minThreshold
self.maxThreshold = maxThreshold
self.frame1 = wx.Frame(None, title="wx.lib.plot", id=-1, size=(410, 340), pos=position)
self.panel1 = wx.Panel(self.frame1)
self.panel1.SetBackgroundColour(backgroundColour)
self.ymin = ymin
self.ymax = ymax
self.title = title
self.plotColour = plotColour
self.lines = [None, None, None]
# mild difference between wxPython26 and wxPython28
if wx.VERSION[1] < 7:
self.plotter = plot.PlotCanvas(self.panel1, size=frameSize)
else:
self.plotter = plot.PlotCanvas(self.panel1)
self.plotter.SetInitialSize(size=frameSize)
# enable the zoom feature (drag a box around area of interest)
self.plotter.SetEnableZoom(False)
# list of (x,y) data point tuples
self.coordinates = []
for x_item in range(MAXIMUM_PLOTS):
self.coordinates.append((x_item, (ymin+ymax)/2))
self.queue = deque(self.coordinates)
if self.maxThreshold!=None:
self._update_max_threshold()
#endif
if self.lockThreshold!=None:
self._update_min_threshold()
#endif
self.line = plot.PolyLine(self.coordinates, colour=plotColour, width=1)
self.lines[0] = (self.line)
self.gc = plot.PlotGraphics(self.lines, title, 'Time', 'Value')
self.plotter.Draw(self.gc, xAxis=(0, MAXIMUM_PLOTS), yAxis=(ymin, ymax))
self.frame1.Show(True)
def _update_max_threshold(self):
if self.maxThreshold!=None:
self.maxCoordinates = []
for x_item in range(MAXIMUM_PLOTS):
self.maxCoordinates.append((x_item, self.maxThreshold))
#endfor
self.maxLine = plot.PolyLine(self.maxCoordinates, colour="green", width=1)
self.maxMarker = plot.PolyMarker(self.maxCoordinates, colour="green", marker='dot')
self.lines[1] = self.maxMarker
#endif
def _update_live_param(self, liveParam, minParam, maxParam):
if minParam!=None:
self.minThreshold = int(minParam)
self._update_min_threshold()
#endif
if maxParam!=None:
self.maxThreshold = int(maxParam)
self._update_max_threshold()
#endif
if liveParam!=None:
self._update_coordinates(int(liveParam))
#endif
def _update_coordinates(self, newValue):
newList = []
for x,y in self.coordinates[1:]:
newList.append((x-1, y))
#endfor
newList.append((x, newValue))
print "New list", newList
self.line = (plot.PolyLine(newList, colour=self.plotColour, width=1))
self.lines[0] = self.line
self.coordinates = newList
def _MyLIVE_MAGIC_refresh__(self, liveParam=None, minParam=None, maxParam=None):
self._update_live_param(liveParam, minParam, maxParam)
self.gc = plot.PlotGraphics(self.lines, self.title, 'Time', 'Value')
self.plotter.Draw(self.gc, xAxis=(0, MAXIMUM_PLOTS), yAxis=(self.ymin, self.ymax))
self.plotter.Refresh()
self.frame1.Refresh()