I have a series of x coordinates (e.g.: 1,2,3,4) and y coordinates (e.g.: 10,20,30,40). I would like pyplot to draw a line between two consecutive points, while skipping every other line (e.g.: draw a line between (1,10) and (2,20), and a line between (3,30) and (4,40).)
How can this be done?
Do you mean something like this?
x = [1,2,3,4,5,6]
y = [10,20,30,40,50,60]
for n in np.arange(0,len(x),2):
plt.plot(x[n:n+2],y[n:n+2])
(Copied from #Floris' comment above)
The quick and dirty trick would be to insert NaN values in the arrays at every third position (both X and Y).
Related
I'm fairly new to python so bare with me. I have plotted a histogram using some generated data. This data has many many points. I have defined it with the variable vals. I have then plotted a histogram with these values, though I have limited it so that only values between 104 and 155 are taken into account. This has been done as follows:
bin_heights, bin_edges = np.histogram(vals, range=[104, 155], bins=30)
bin_centres = (bin_edges[:-1] + bin_edges[1:])/2.
plt.errorbar(bin_centres, bin_heights, np.sqrt(bin_heights), fmt=',', capsize=2)
plt.xlabel("$m_{\gamma\gamma} (GeV)$")
plt.ylabel("Number of entries")
plt.show()
Giving the above plot:
My next step is to take into account values from vals which are less than 120. I have done this as follows:
background_data=[j for j in vals if j <= 120] #to avoid taking the signal bump, upper limit of 120 MeV set
I need to plot a curve on the same plot as the histogram, which follows the form B(x) = Ae^(-x/λ)
I then estimated a value of λ using the maximum likelihood estimator formula:
background_data=[j for j in vals if j <= 120] #to avoid taking the signal bump, upper limit of 120 MeV set
#print(background_data)
N_background=len(background_data)
print(N_background)
sigma_background_data=sum(background_data)
print(sigma_background_data)
lamb = (sigma_background_data)/(N_background) #maximum likelihood estimator for lambda
print('lambda estimate is', lamb)
where lamb = λ. I got a value of roughly lamb = 27.75, which I know is correct. I now need to get an estimate for A.
I have been advised to do this as follows:
Given a value of λ, find A by scaling the PDF to the data such that the area beneath
the scaled PDF has equal area to the data
I'm not quite sure what this means, or how I'd go about trying to do this. PDF means probability density function. I assume an integration will have to take place, so to get the area under the data (vals), I have done this:
data_area= integrate.cumtrapz(background_data, x=None, dx=1.0)
print(data_area)
plt.plot(background_data, data_area)
However, this gives me an error
ValueError: x and y must have same first dimension, but have shapes (981555,) and (981554,)
I'm not sure how to fix it. The end result should be something like:
See the cumtrapz docs:
Returns: ... If initial is None, the shape is such that the axis of integration has one less value than y. If initial is given, the shape is equal to that of y.
So you are either to pass an initial value like
data_area = integrate.cumtrapz(background_data, x=None, dx=1.0, initial = 0.0)
or discard the first value of the background_data:
plt.plot(background_data[1:], data_area)
How can I find or generate data points form a shape in 2D in MATLAB ? For example, the letters A, B, and C.
You can use fill()
An example for an octogon, provided by
See https://www.mathworks.com/help/matlab/ref/fill.html
% Generate the points required for the fill.
t = (1/16:1/8:1)'*2*pi; % using 1/8 steps we get an 8 sided object.
x = cos(t);
y = sin(t);
% fill the data
fill(x,y,'r')
axis square % prevent skewing the result.
An example of generating the x y coordinates of a rectangle with an offset of (5,5):
x=[5 5 25 25 5]
y=[5 15 15 5 5]
You have 5 points because you need to include the final point to complete the path ( I believe ) Follow the blue path when collecting the x coordinates and the y coordinates. You can see we start at 5,5 then move to 5,15 --- so the first part of the path is
x=[5 5 ...
y=[5 15 ...
If you want to generate the coordinates automatically, you could use a program like InkScape (vector program) to help you convert a character to paths, but here is a simple example drawn with the pen tool:
The points are given by
m 0,1052.3622 5,-10 5,0 5,10 z
which 1052.3622 is VERY large, but is ultimately because I placed my shape at the bottom of the page. if we set this to be 0,0 it would go to the top of the page.
I want to estimate the point of fracture (x_F) (red circle) via ternary operator to restrict the range of my plot to it.
Example plot
To achieve a restriction to the X(Y_max)-value the stats command in combination with ternary-operator seems to be sufficient:
stats 'foo.csv' u 5 nooutput name 'Y_'
stats 'foo.csv' u 4 every ::Y_index_max::Y_index_max nooutput
X_max = STATS_max
plot 'foo.csv' u 4:(($4 <= X_max) ? $5 : 1/0) w l notitle
I cannot use the X_max-variable, because there a several points beyond the point of fracture (x_n > x_F) due to measurement errors. My idea was to compare the x-entries $4 to one another and to save the first point which satisfies $4_prev > $4_curr and to save it as x_F=$4_prev.
A simple delta-function seems to do the trick: delta(x)=(D=x-old_D,old_D=x,D) and old_D=NaN in combination with the ternary operator (delta($4)>0 ? $5 : 1/0) whereas $5 is the y-value, which will be plotted as long as the difference of two sequent x-values is positive.
You want to discard any data point after dx has become negative for the first time, right? You'll need a flag variable, i called it broken, which is set after the first occurrence of dx < 0:
broken = 0
plot dataf us (lastx=thisx, thisx=$4): \
(broken ? 1/0 :($4 < lastx) ? $5 : (broken=1, 1/0))
This uses the comma as "serial evaluator", same as in C, etc.
(Not tested now, as i don't have a suitable data set at hand and was too lazy to create one.)
Update: You can put the assignment broken=0 into the plot
plot broken=0, dataf us ....
, to be able to replot, zoom that plot etc.
I am trying to understand how I can go about finding or calculating the intersection points of a straight line and a diagonal scatter plot. Just to give a better idea, on an X,Y plot, if I have a straight horizontal line at y= # (any number), that crosses an array of scatters points (which form a diagonal line), how can I calculate points of intersection the two lines?
The problem that I am having is that the scattered array has multiple points around my horizontal line, what I would like to do is find the point that hits the horizontal line first, and the point that hits the horizontal line the last.
please refer to the image for a better understanding. The two points that are annotated are the ones that I am trying to extract with VBA. Is this possible? The image shows two sets of scattered arrays, I am only interested in figuring out the method for 1 of the arrays. If I can extract this for 1 scattered array, I can replicate the method for the next one.
http://imgur.com/9YTNeco
It's hard to give you any specifics without knowing the structure of your Data. But this is the approach I'd use.
I'll assume your data looks like this (for both of the plots)
A B
x1 y1
x2 y2
x3 y3
Loop through the axis like so:
'the y values need to be as high as the black axis you've got there
'I'll assume that's zero
i = 0
k = .Cells(1,1)
'we begin at the first x-value in your column
for i = 0 to Worksheets("Sheet name").UsedRange.Rows.Count
'now we are looking for the lowest value of x, k will be this value
if .Cells(i,1) < k Then
if .cells(i,2) = 0 Then '0 = y-value of the "black" axis
k = .Cells(i,1)
End If
End If
'every time we find a lower value than our existing k
'we will assign it to k
Next
The lowest value will be your "low limit"-point.
You can use that same kind of algorithm for the highest value of the same scatter plot (just change the "<" to ">" or the lowest and highest value for the one, just change the Column ID.
HTH
I'm overplotting multicolored lines on an image, the color of the lines is supposed to represent a given parameter that varies between roughtly -1 and 3.
The following portion of code is the one that builds these lines :
x = self._tprun.r[0,p,::100] # x coordinate
y = self._tprun.r[1,p,::100] # y coordinate
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
# 'color' is the parameter that will color the line
vmin = self._color[p,:].min()
vmax = self._color[p,:].max()
lc = LineCollection(segments,
cmap=plt.get_cmap('jet'),
norm=plt.Normalize(vmin=vmin,vmax=vmax))
lc.set_array(self._color[p,:])
lc.set_linewidth(1)
self._ax.add_collection(lc)
This code is inside a loop on 'p' and so it will create several lines at locations given by the arrays 'x' and 'y' and for which the color should be given by the value of 'self._color[p,:]'.
As I said, '_color[p,:]' roughly varies between -1 and 3. Here is an example of what '_color[p,:]' may be :
My problem is that the lines that are created appear without much variation of the color, they all look kind of monochrome dark blue whereas _color[p,:] varies much and I ask for the normalization to take its min/max values.
here is an example of such a line (look at the oscillating dark blue line, other black lines are a contour of another value) :
Is there something I'm missing in the way these functions work?
Got it!
Answer to the question is here :
x = self._tprun.r[0,p,::100] # re-sample every 100 values !!
y = self._tprun.r[1,p,::100] #
# [...]
#lc.set_array(self._color[p,:]) # self._color[p,:] is not resampled
lc.set_array(self._color[p,::100]) # this works because resampled
meaning that the 'color' array was actually much larger than the arrays used for position of the line segments.... only the first values of '_color' where used where its values do not vary that much.