I've written a program which reads measurements from an impedance analyzer as it sweeps over a range of frequencies or voltages, saves the data to a text file, and also creates a scatter plot. In one type of measurement, I obtain x and y values for complex impedance, neither of which are the independent parameter. Now when plotting this graph, it appears that it simply puts each x value to the right of the previous one at regular spacings resulting in x axis labels looking like, from left to right, [45000, 43000, 40000,... etc.].
I've tried forcing the x-axis to start from zero which did not change anything and haven't been able to find much else on this. Is there a way to make sure the plot reflects the actual x values of each point?
Here's my current method of creating the chart,which pulls the data from the already created table:
For Each row In table.Rows
Chart1.Series("series1").Points.AddXY(row(0), row(1))
Next
Related
Application used: everycircuit
Example circuits used (the book icon in the left sidebar):
: "LED Array", "RC step response"
So,
the image is of a parametric plot of some quantities on vertical axis (legend indicated by #3 in image), and one quantity on horizontal axis (legend indicated by #2)
in this, there's one parameter with respect to which all values are changing (which is time)
in the plot, the trail of values is kept for some time then it is erased - the keeping behaviour helps when the system is stable, and the erasing helps a lot to declutter the plot and zoom into the new relevant area/scale when the system changes its characteristics
How to do this animation in other code based data analysis software? like python/octave/julia etc?
Animation i.e.
the values changing with change in the parameter (i.e. the normal plot),
but the trail shown for only some time (hence, non-static)
while still retaining some way to change the parameter, and see which point corresponds to that (also known as "track" the plot)
I am working on a image search algorithm that finds certain shapes of certain colors; to save time I only register half of the shape's perimeter in 2 distinct sets, one for the rows and one for the columns used by the shape. The idea is that whenever I find a point which has the target color, I then check if this point's row and column are in a master set (which have both the previous sets); if they are I skip it, if they are not then I initialize 2 recursive fuctions that register the first row and the first column of the shape.
Since it's for a school project, my images are specially tailored
and the code would be
for y in range(height):
for x in range(width):
if img[y][x] == target:
if y in master_set and x in master_set:
continue
else:
row = set()
column = set()
flood_fillv2_y(img,x,y,target,column)
flood_fillv2_x(img,x,y,target,row)
row=frozenset(row)
column=frozenset(column)
master_set.add(row)
master_set.add(column)
The idea then is to check the len of master_set to see how many shapes I have, but as I said what I get is that y and x are never in the master set so it keeps doing it for all points of the shape, resulting in a wrong number.
It's hard to give a good answer without seeing the whole code, but I can give a guess:
master_set.add(row) literally adds the frozenset row to the master_set, but you probably want all elements from the set to be added to master_set. Take a look at the update() method of sets.
Does this help?
I have a matrix of data, which is an output of automatic music transcription program. I want to plot it using gnuplot, assigning appropriate labels. Here's my dropbox with some data, where Intensity.dat is actual data, example.stn is a column of string values, some of which are to be displayed on y axis and example.all is just a result of paste example.stn Intensity.dat > example.all Script:
reset
set title "Intensity detection"
set palette negative grayscale
set cbrange [0.01:1]
set xlabel "Time [s]"
set ylabel "Musical note"
set terminal qt font "Verdana,16"
set logscale cb
xincr=0.04644
yincr=1
plot 'example.all' u (($1+0.5)*xincr):($2*yincr):3 matrix with image
produces
plot produced by script 1. Everything's OK, now just tic labels...
After I change the last line to plot 'example.all' u (($1+0.5)*xincr):($2*yincr):3 matrix rowheaders with image, the y-axis becomes too densly populated (It's plot2.jpg from my dropbox, link on top. Sorry guys, I'm new and it doesn't allow me to post more than 2 links).
What I want is a way to present only the labels I want (or hide others, whatever), not all at a time (because it looks unreadable). I'd also like to be able to quickly change them to the others when I need to do so. Supposingly, I want to display every 12th label, but still keep entire matrix with all rows plotted. Or every 12th starting from 2nd label AND every 12th starting from 6th. I've already tried many ways but I'm stuck. Functions like :ytics() or :yticlabels() can't make it, at least for me. And yes, I need this Verdana 16, and removing labels completely is out of question.
I'll be extra grateful if the method applies also for x-axis, as I have an analogical problem with x-axis in other plot, but I generally appreciate any help.
You can separate plotting the image from plotting the ytics like this:
condition(n) = (ceil(n)%12-2 == 0) || (ceil(n)%12-6 == 0)
plot 'Intensity.dat' u (($1+0.5)*xincr):($2*yincr):3 matrix with image ,\
'example.stn' u (NaN):0:ytic(condition($0) ? strcol(1) : "") notitle
The function condition checks whether the label should be plotted or not. I have used ceil to convert from a real number to an integer which is required by the modulo operator (%). The condition function is called with the linenumber $0. The NaN while plotting 'example.stn' avoids plotting data points while keeping the chance for setting the labels. If the condition is met (12th label starting from 2nd or 12th starting from 6th), we use the actual label, else an empty string is used.
Trying to implement EKG style "heartbeat" chart from a design and I'm having a hard time getting D3 to draw a path like I need.
The design spec states that the graph needs to return to nuetral/zero point between each and every data point, and that the curved path from the zero point should be close to the data point itself and rise sharply. See the attached images below
Here is the design....
And here is my attempt to match the curve with dummy data (black circle data points)...
The graph has a time scale X axis and a linear Y axis that ranges from 0 to 2 (my data points are 0,1, or 2 respectively). The line is using 'monotone' interpolation which is the least terrible looking.
Question:
Is there a better way to get this appearance without dummy data points?
Question-behind-the-question:
What is the best way to get D3 draw a custom paths (e.g. from a function)?
Sub-question:
Why does the monotone interpolation curve the path inward so sharply between the last 2 data points?
Any help is appreciated! The designers and client won't budge on this one, so I have to get it as close possible :(
Let's say I have a list of values and I have already chunked them into groups to make a histogram.
Since Excel doesn't have histograms, I made a bar plot using the groups I developed. Specifically, I have the frequencies 2 6 12 10 2 and it produces the bar plot you see below.
Next, I want to add a normal distribution (line plot) with a mean of 0.136 and standard deviation of 0.497 on top of this histogram. How can I do this in excel? I need the axis to line up such that it takes up the width of the bar plot. Otherwise, you get something like I've attached.
But...the normal should be overlayed on the bar plot. How can I get this effect?
There are two main part to this answer:
First, I reverse-engineered the grouped data to come up with an appropriate mean and standard deviation on this scale.
Second, I employed some chart trickery to make the normal distribution curve look right when superimposed on the column chart. I used Excel 2007 for this; hopefully you have the same options available in your version.
Part 1: Reverse-Engineer
The column B formulae are:
Last Point =MAX(A2:A6)
Mean =SUMPRODUCT(B2:B6,A2:A6)/SUM(B2:B6)
E(x^2f) =SUMPRODUCT(A2:A6^2,B2:B6)
E(xf)^2 =SUMPRODUCT(A2:A6,B2:B6)^2
E(f) =SUM(B2:B6)
Variance =B10-B11/B12
StDev =SQRT(B13/(B12-1))
Part 2: Chart Trickery
Data table:
Column D is just an incremental counter. This will be the number of data points in the normal distribution curve.
E2 =D2/$B$8 etc.
F2 =NORMDIST(E2,$B$9,$B$14,FALSE) etc.
Chart:
Now, add Columns E:F to the chart. You will need to massage a few things:
Change the series to be an X-Y plot. This might require some editing of the chart series to force a single series to use your desired X and Y values.
Change the series to use the secondary axes (both X and Y).
Change the secondary X-axis range to 0.5-5.5 (i.e., 0.5 on either side of the column chart category values). This will effectively align the primary and secondary X-axes.
Change the secondary Y-axis range to 0-1
Format the X-Y series appearance to taste (I suggest removing value markers).
The result so far:
Lastly, you can remove the tick marks and labels on the secondary axes to clean up the look.
Postscript: Thanks to John Peltier for innumerable charting inspirations over the years.