We Keep Coding

Using a for loop to plot arrays from dictionaries

I have a dictionary with multiple key defined as (arbitrary inputs):
colors = {}
colors['red'] = {}
colors['blue'] = {}
colors['red'][clustname] = np.array([])
colors['blue'][clustname] = np.array([])
basically I want to plot a red v blue graph for each 'cluster'. I have 13 'clusters' in total with differing color values for each. The names in my code are different from the arbitrary ones above, but I figured it would be easier to understand with basic values then to look at the overall code:
colpath = '/home/jacob/PHOTOMETRY/RESTFRAME_COLOURS/' #This is the path to the restframe colors
goodcolindx = {}
colfiledat = {}
colors = {}
colors['UMINV'] = {}
colors['VMINJ'] = {}
colors['NUVMINV'] = {}
colors['id'] = {}
for iclust in range(len(clustname)):
colors['UMINV'][clustname[iclust]] = np.array([])
colors['VMINJ'][clustname[iclust]] = np.array([])
colors['id'][clustname[iclust]] = np.array([])
colors['NUVMINV'][clustname[iclust]] = np.array([])
filepath = catpath + clustname[iclust] + "_totalall_" + extname[iclust] + ".cat"
photdat[clustname[iclust]] = ascii.read(filepath)
filepath = zpath + "compilation_" + clustname[iclust] + ".dat"
zdat[clustname[iclust]] = ascii.read(filepath)
colfilepath = colpath + 'RESTFRAME_MASTER_' + clustname[iclust] + '_indivredshifts.cat'
colfiledat[clustname[iclust]] = ascii.read(colfilepath)
goodcolindx[clustname[iclust]] = np.where((colfiledat[clustname[iclust]]['REDSHIFTUSED'] > 0.9) & \
(colfiledat[clustname[iclust]]['REDSHIFTUSED'] < 1.5) & \
(photdat[clustname[iclust]]['totmask'] == 0) & \
(photdat[clustname[iclust]]['K_flag'] == 0) & \
((zdat[clustname[iclust]]['quality'] == 3) | (zdat[clustname[iclust]]['quality'] == 4)))
goodcolindx[clustname[iclust]] = goodcolindx[clustname[iclust]][0]
for igood in range(len(goodcolindx[clustname[iclust]])):
idstring = str(photdat[clustname[iclust]]['id'][goodcolindx[clustname[iclust]][igood]])
colors['NUVMINV'][clustname[iclust]] = np.append(colors['NUVMINV'][clustname[iclust]], -2.5 *
np.log10(colfiledat[clustname[iclust]]['NUV'][goodcolindx[clustname[iclust]][igood]]
/ colfiledat[clustname[iclust]]['V'][goodcolindx[clustname[iclust]][igood]]))'SpARCS-0035'
colors['UMINV'][clustname[iclust]] = np.append(colors['UMINV'][clustname[iclust]], colfiledat[clustname[iclust]]['UMINV'][goodcolindx[clustname[iclust]][igood]])
colors['id'][clustname[iclust]] = np.append(colors['id'][clustname[iclust]], photdat[clustname[iclust]]['id'][goodcolindx[clustname[iclust]][igood]])
colors['VMINJ'][clustname[iclust]] = np.append(colors['VMINJ'][clustname[iclust]], colfiledat[clustname[iclust]]['VMINJ'][goodcolindx[clustname[iclust]][igood]])
for iclustc in colors:
plt.plot(colors['VMINJ'][clustname[iclustc]], colors['UMINV'][clustname[iclustc]], 'ko')
plt.show()
So in this case, my 'red' is the VMINJ and my 'blue' is the UMINV. I am trying to use a for loop to cycle through all the cluster names that I have, but I keep getting the error back 'String indices must be integers'. I understand the basics of that, but don't know how to fix my code to make plots for each 'red' v 'blue' for each cluster. Any help would be awesome, let me know if you have questions

I figured it out. I changed the for loop to:
for iclust in range(len(clustname)):
plt.plot(colors['UMINV'][clustname[iclust]]....
and that worked

Vertical positioning of nodes in Sankey diagram to avoid collision with links

I'm trying to make a Sankey-plot using Plotly, which follows the filtering of certain documents into either being in scope or out of scope, i.e. 1 source, 2 targets, however some documents are filtered during step 1, some during step 2 etc. This leads to the following Sankey-plot:
Current output
Now what I would ideally like is for it to look something like this:
Ideal output
I've already tried to look through the documentation on : https://plot.ly/python/reference/#sankey but I fail to find what I'm looking for, ideally I would like to implement a feature to prevent the plot from overlapping nodes and links.
This is the code I'm using the generate the plot object:
def genSankeyPlotObject(df, cat_cols=[], value_cols='', visible = False):
### COLORPLATTE TO USE
colorPalette = ['472d3c', '5e3643', '7a444a', 'a05b53', 'bf7958', 'eea160', 'f4cca1', 'b6d53c', '71aa34', '397b44',
'3c5956', '302c2e', '5a5353', '7d7071', 'a0938e', 'cfc6b8', 'dff6f5', '8aebf1', '28ccdf', '3978a8',
'394778', '39314b', '564064', '8e478c', 'cd6093', 'ffaeb6', 'f4b41b', 'f47e1b', 'e6482e', 'a93b3b',
'827094', '4f546b']
### CREATES LABELLIST FROM DEFINED COLUMNS
labelList = []
for catCol in cat_cols:
labelListTemp = list(set(df[catCol].values))
labelList = labelList + labelListTemp
labelList = list(dict.fromkeys(labelList))
### DEFINES THE NUMBER OF COLORS IN THE COLORPALLET
colorNum = len(df[cat_cols[0]].unique()) + len(df[cat_cols[1]].unique()) + len(df[cat_cols[2]].unique())
TempcolorPallet = colorPalette * math.ceil(len(colorPalette)/colorNum)
shuffle(TempcolorPallet)
colorList = TempcolorPallet[0:colorNum]
### TRANSFORMS DF INTO SOURCE -> TARGET PAIRS
for i in range(len(cat_cols)-1):
if i==0:
sourceTargetDf = df[[cat_cols[i],cat_cols[i+1],value_cols]]
sourceTargetDf.columns = ['source','target','count']
else:
tempDf = df[[cat_cols[i],cat_cols[i+1],value_cols]]
tempDf.columns = ['source','target','count']
sourceTargetDf = pd.concat([sourceTargetDf,tempDf])
sourceTargetDf = sourceTargetDf.groupby(['source','target']).agg({'count':'sum'}).reset_index()
### ADDING INDEX TO SOURCE -> TARGET PAIRS
sourceTargetDf['sourceID'] = sourceTargetDf['source'].apply(lambda x: labelList.index(x))
sourceTargetDf['targetID'] = sourceTargetDf['target'].apply(lambda x: labelList.index(x))
### CREATES THE SANKEY PLOT OBJECT
data = go.Sankey(node = dict(pad = 15,
thickness = 20,
line = dict(color = "black",
width = 0.5),
label = labelList,
color = colorList),
link = dict(source = sourceTargetDf['sourceID'],
target = sourceTargetDf['targetID'],
value = sourceTargetDf['count']),
valuesuffix = ' ' + value_cols,
visible = visible)
return data

How to use vispy to generate a rolling image?

Some context:
I was looking into the vispy module to plot in realtime (or as close as possible to) data coming from an instrument. My attempt follow.
from vispy.plot import Fig
from vispy import app,scene
from vispy.visuals import TextVisual
import numpy as np
import Queue
FONT_SIZE = 14
MIN = 0
MAX = 1.1
w_size = 100
N = 5000
M = 2500
color_map = 'cubehelix'
q_size = 1000
Nb = 5
#generate (empty) initial data to fill the plot
data = np.zeros(N*M)
data = np.reshape(data, (N,M))
#setup the plot
fig = Fig(show = False,size = (16*w_size,9*w_size),bgcolor='black')
fig.title = 'my plot'
main_plot = fig[0,0].image(data = data,fg_color='w',cmap=color_map,clim=(MIN,MAX))
fig[0,0].view.camera.aspect = N/float(M) * 16./9.
title = scene.Label("someoutput", font_size=FONT_SIZE, color = 'w')
fig[0,0].grid.add_widget(title, row=0, col=4)
fig[0,0].grid[2,4].border_color = 'black'
fig[0,0].grid[2,4].bgcolor = 'black'
xlabel_title = scene.Label("x_axis [unit]", font_size=FONT_SIZE, color = 'w')
fig[0,0].grid.add_widget(xlabel_title, row=4, col=4)
ylabel_title = scene.Label("y_axis [unit]", font_size=FONT_SIZE,rotation=-90, color='w')
fig[0,0].grid.add_widget(ylabel_title, row=2, col=2)
scale = scene.ColorBarWidget(orientation='left',
cmap=color_map,
label='Some value',
clim=(MIN,MAX),
border_color = 'w',
border_width = 1,
label_color = 'w'
)
fig[0,0].grid.add_widget(scale, row=2, col=6)
fig[0,0].cbar_right.width_max = \
fig[0,0].cbar_right.width_min = 50
#fill a queue so to excude the generation time from the plotting time
q = Queue.Queue()
for i in range(q_size):
new_data = (np.abs(0.5*np.random.randn(Nb*M)[:])).astype('float32')
new_data = np.reshape(new_data, (Nb,M))
q.put(new_data[:])
#update function
def update(ev):
global main_plot, q, data, Nb,M,fig,index
#acquire
new_data = q.get()
#roll the plot data
data[Nb:, :] = data[:-Nb, :]
data[:Nb,:] = new_data
#recycle the new data
q.put(new_data)
#update the plot
main_plot.set_data(data)
main_plot.update()
# setup timer
interv = 0.01
timer = app.Timer(interval = interv)
timer.connect(update)
timer.start(interval = interv)
if __name__ == '__main__':
fig.show(run=True)
app.run()
This code currently works but it's much slower than the data rate. In the vispy gallery, as well as in some examples, I saw much more points being plotted and updated. I think that the main problem is that I completely set each time all the data of the plot instead of shifting them and inserting new points.
I also had a look at this example:
https://github.com/vispy/vispy/blob/master/examples/demo/scene/oscilloscope.py
However I don't know how to generalize the update function that rolls the data (I have no knowledge of OpenGL) and I cannot use the example as is because I need a quantitative color scale (that seems well implemented in vispy.plot).
The question:
Is there a way to write a function that rolls the data of a plot generated with the vispy.plot class?
Thanks.

Select and zoom features of a layer using PyQgis

I want to select features and to zoom on them and do all these steps using PyQgis.
And I'm able to do both of them separatly but it doesn't seems to work when I try to mix the two of them.
Both of the codes I use for them are from the internet. Here's what I use to select features of a layer :
from qgis.core import *
import qgis.utils
lyrMap = QgsVectorLayer('C:/someplace', 'MapName', 'ogr')
QgsMapLayerRegistry.instance().addMapLayer(lyrMap)
expr = QgsExpression("'Attribute' IS NOT NULL")
it = lyrMap.getFeatures(QgsFeatureRequest(expr))
ids = [i.id() for i in it] #select only the features for which the expression is true
lyrMap.setSelectedFeatures(ids)
And it seems to do the trick as features appear selected on QGis.
In order to zoom the code is much more simple, it's just :
canvas = qgis.utils.iface.mapCanvas()
canvas.zoomToSelected(lyrMap)
But it seems that canvas doesn't consider that there's a selection on lyrMap and simply do nothing. I've tried to do the selection manually in QGis, and then zoom using zoomToSelected, and it worked.
But my objective is to do it without needing to do the selection manually...
Note : I don't think that's the issue, but the attribute I'm doing the selection on is from a join between lyrMap and another layer (I didn't put the code here because I don't think it's linked).
Thanks in advances for answers, clues or anything really :) !

This is working for my plugin. I am using python 2.7 and QGIS 1.8 and 2.0.1.You can use this code after including using vector file and adding it to the registry.
self.rubberBand = None
#create vertex marker for point..older versons..
self.vMarker = None
#add rubberbands
self.crossRb = QgsRubberBand(iface.mapCanvas(),QGis.Line)
self.crossRb.setColor(Qt.black)
def pan(self):
print "pan button clicked!"
x = self.dlg.ui.mTxtX.text()
y = self.dlg.ui.mTxtY.text()
if not x:
return
if not y:
return
print x + "," + y
canvas = self.canvas
currExt = canvas.extent()
canvasCenter = currExt.center()
dx = float(x) - canvasCenter.x()
dy = float(y) - canvasCenter.y()
xMin = currExt.xMinimum() + dx
xMax = currExt.xMaximum() + dx
yMin = currExt.yMinimum() + dy
yMax = currExt.yMaximum() + dy
newRect = QgsRectangle(xMin,yMin,xMax,yMax)
canvas.setExtent(newRect)
pt = QgsPoint(float(x),float(y))
self.zoom(pt)
canvas.refresh()
def zoom(self,point):
canvas = self.canvas
currExt = canvas.extent()
leftPt = QgsPoint(currExt.xMinimum(),point.y())
rightPt = QgsPoint(currExt.xMaximum(),point.y())
topPt = QgsPoint(point.x(),currExt.yMaximum())
bottomPt = QgsPoint(point.x(),currExt.yMinimum())
horizLine = QgsGeometry.fromPolyline( [ leftPt , rightPt ] )
vertLine = QgsGeometry.fromPolyline( [ topPt , bottomPt ] )
self.crossRb.reset(QGis.Line)
self.crossRb.addGeometry(horizLine,None)
self.crossRb.addGeometry(vertLine,None)
if QGis.QGIS_VERSION_INT >= 10900:
rb = self.rubberBand
rb.reset(QGis.Point)
rb.addPoint(point)
else:
self.vMarker = QgsVertexMarker(self.canvas)
self.vMarker.setIconSize(10)
self.vMarker.setCenter(point)
self.vMarker.show()
# wait .5 seconds to simulate a flashing effect
QTimer.singleShot(500,self.resetRubberbands)
def resetRubberbands(self):
print "resetting rubberbands.."
canvas = self.canvas
if QGis.QGIS_VERSION_INT >= 10900:
self.rubberBand.reset()
else:
self.vMarker.hide()
canvas.scene().removeItem(self.vMarker)
self.crossRb.reset()
print "completed resetting.."

Tkinter: get data from a Entry widget

I am workin with Python 2.7. This is the initial part of a longer programme. What I want to do is to add a new username, together with is height and weight. I use a .txt file to store user data,
example userlist3.txt:
add_new_user 1 1
unknown_user 170 70
monthy 185 83
[empty line]
This is the code:
from Tkinter import *
user_list = Tk()
user_list.title('Users')
def add_new_user():
global select
global height
global weight
select = name.get()
height = h.get()
weight = w.get()
f = ' '
us=open("userlist3.txt","a")
print name, height, weight
us.write(select + f + str(height) + f + str(weight) + "\n")
us.close()
# add_user.destroy() # it doesn't work
user_list.destroy()
def onSelect(ev): # (10)
global select
select=listb.get(listb.curselection()) # (12)
lab.configure(text=select) # (14)
global name
global h
global w
if select == 'add_new_user':
add_user = Tk()
add_user.title('New user')
a=Label(add_user,text="Your username").pack()
name = StringVar()
NAME = Entry(add_user,textvariable = name).pack()
b=Label(add_user,text="Your height (in cm)").pack()
h = IntVar()
H = Entry(add_user,textvariable = h).pack()
c=Label(add_user,text="Your weight (in kg)").pack()
w = IntVar()
W = Entry(add_user,textvariable = w).pack()
Add_New_User=Button(add_user,text="Add new user data",command=add_new_user).pack()
add_user.mainloop()
else:
user_list.destroy()
a=open("userlist3.txt","r")
b =[]
for linea in a:
b.append(linea)
a.close()
e = []
for i in range(len(b)):
e.append(b[i].split())
userlist = []
heightlist = []
weightlist = []
for i in range(len(e)):
userlist.append(e[i][0])
heightlist.append(e[i][1])
weightlist.append(e[i][2])
sbar = Scrollbar(user_list, orient=VERTICAL) # (20)
listb = Listbox(user_list, width=30, height=4) # (22)
sbar.config(command=listb.yview) # (30)
listb.config(yscrollcommand=sbar.set) # (32)
sbar.pack(side=RIGHT, fill=Y) # (40)
listb.pack() # (42)
lab=Label(user_list,text="Double Click on User") # (50)
lab.pack()
for c in userlist: listb.insert(END,c)
listb.bind('<Double-1>',onSelect) # (70)
user_list.mainloop()
for d in range(1,len(userlist)):
if userlist[d] == select:
height = int(heightlist[d])
weight = int(weightlist[d])
print "Selected user is: ",select
print height
print weight
It works with user already present in the txt file, but not if I want to add a new one. When I try, I got 'PY_VAR0 0 0' printed on the shell and '' 0 0 added in a new line in the txt file. Obviously these data are of no use in the following steps of my software.I'm probably missing a .get() somewhere.

When you see something like PY_VAR0, that means you are printing out the instance of a StringVar (or IntVar or whatever), rather than printing out the value of the variable. If you are using one of the special vars, you must call the get() method to get the value.
In your specific case, change this:
print name, width, height
To this:
print name.get(), width, height

Thanks Fiver for your advice!
metaphy's solution works, I solved the problem modifying line 28 in
add_user = Toplevel(user_list)