I would like to create a barplot in TIBCO Spotfire with frequency on Y axis based on two factors: Stage and Genotype.
This is the standard expression that I have from Spotfire:
Count() THEN [Value] / Sum([Value]) OVER (All([Axis.X]))
It turns out, I do not want the frequency over ALL the data, but within Stage. In a way that the sum of the frequency within each is stage it will be 100%.
I watched some videos and I still did not figured out.
I tried to find a solution to your problem but could't find a working expression. This can still help you :
What I would have done in your case is :
remove the Genotype from the X Axis
set the visualization as a 100% stacked bars (with right click)
add the Genotype as a color by parameter (in the visualization options)
Related
I am trying to set up a simple Kibana line chart with these conditions -
I'm trying to set up a Power vs Timestamp chart. In elastic, I have the metrics Current and Voltage. I'll calculate the Power from that. Problem is, I need to show the visual ONLY if the current is decreasing.
So at time t, the current value should be less than the last reported current value.
Cannot figure out how to do this in Lens. If it can't be done in Lens, any help with Vega is appreciated.
Thanks
So it sounds like you want a graph that only shows the values of current for when the previous value is greater. This is not doable in lens, but definitely doable in Vega.
Since you haven't provided an example I will just point you in the right direction. You will need a series of transforms to get the data in a plottable form.
sort the data by timestamp (collect transform)
run a window transform that stores the previous value (window transform)
calculate the difference between these values (formula transform)
filter values with a negative/positive difference (filter transform)
From here you can build the marks etc. if Vega is new to you I would start by looking at the Vega Documentation, Vega Gallery and the Kibana-Vega Documentation (for data ingest).
I‘m working on a visual data logger for my DMM, it writes every measurement to RS232 inteface. There I connect a Teensy 3.6 and collect the data points.
For each point I have the timestamp and the measured value. I will collect 10.000 readings.
I want to display the measured data on a display (800x480) in two ways. First as a rolling graph, that scrolls from right to left and shows the last minute or so. This is working fine.
Second, I want to display all collected measurements in total (max. 10k points). So I have to shrink or compress the data, but I want to preserve the shape of the curve.
To give you an idea how it should look like, please watch the video from Dave on EEV at YT (https://youtu.be/SObqPuUozNo) and skip to 41:20. There you see how another DMM is shrinking the incomming data and displays it. At about 1:01:05 10k measurements are shown on the display area of only 400px wide.
Question is, how is this done?
I’ve heard about Douglas-Pucker algorithm, but have no idea if this is the right way and how to use it on the Arduino/ Teensy platform.
Any help is very welcome, thank you....
I cannot just display all data points, because I‘m using an FT81x as display controller, and this can take only up to 2000 drawing commands per frame. And it takes more time.
Anyway, I solved the problem using the simple way.
I create bins and calculate the min and max values in this bin. Then simply draw a line between these points. Works fine!
BTW, I‘m the TO :-)
For cases where you got many more samples than pixels in x axis instead of LineTo like graph use vertical lines graph instead...
So depending on the number of samples per rendered time frame and x resolution you should compute ymin and ymax for eaxch x and render vertical line ...
something like:
xs=800;
for (x0=x,i=sample_left,y0=y1=sample[i],i<sample_right;i++)
{
x = (i-sample_left)*xs/(sample_right-sample_left);
y = sample[i]; // here add y scaling and offset
if (x0!=x) { line(x0,y0,x0,y1); x0=x; y0=y; y1=y; }
if (y0>y) y0=y;
if (y1<y) y1=y;
}
where sample[] are your stored values , sample_left,sample_right is the range to render and xs is graph x resolution. To speed up you can pre-compute the y0,y1 for each x and render that (recompute only on range or samples change) ... So as you can see you will use just xs line commands which shoul dbe fast enough. The x linear interpolation can be done without multiplication nor division if you rewrite it to integer DDA style ...
These QAs might interest you:
plotting real time Data on (qwt )Oscillocope
i don't really understand FFT and sample rates
[note]
After a second look The deleted answer is with the same approach as this (got deleted by review probably before the edit which transformed it from not an answer (comment) to the correct answer) so I voted for undelete even if it is considerably lower quality than mine but was posted sooner.
I'm using DC.JS scatterplots to let users select points of interest. If you use elastic axis you cannot select the highest value point. Look at the DC.JS example (https://dc-js.github.io/dc.js/examples/scatter-brushing.html). You cannot select the highest point in the left or right plot.
In several cases, the highest or lowest point(s) is exactly what people need to be able to select because those are the outliers we care about. If you disable elastic axis and make sure you specify a range that is higher than the max value, you can select the point.
Is there another solution besides setting the axis domain based on current min/max and expanding them little bit? This is sometimes ugly when the minimum=0 and now your domain needs to include some small negative number.
--Nico
Always when I face this issue, I increase the y domain by 5% manually.
For instance:
var balanceDomain = d3.scale.linear().domain([0, s.balanceDimension.top(1)[0].balance + (s.balanceDimension.top(1)[0].balance*0.05)]);
s.amountOverallScore
.width(400)
.height(400)
.x(someDomain)
.y(balanceDomain)
...
Maybe this is not the best solution, but always work for me.
Hope it helps (=.
In my application the values were always positive and I used the following to get correct behavior:
// using reductio on the all_grp to get easy access to filtered min,max,avg,etc.
totalTimeMinValue = all_grp.top(1)[0].value.min;
totalTimeMaxValue = all_grp.top(1)[0].value.max;
// now use it to scale the charts we want
detail1_chart.y(d3.scale.linear().domain([totalTimeMinValue-1, totalTimeMaxValue+1]));
detail3_chart.y(d3.scale.linear().domain([totalTimeMinValue-1, totalTimeMaxValue+1]));
This keeps both charts in sink. An additional benefit was that my rather large dots (symbolsize=15) are no longer being clipped.
Thanks Roger.
I am drawing charts using dc.js.The following is a frequency VS Day Chart
I am using the following line to generate the titles:
..something.yAxisLabel("Frequency").xAxisLabel('Day');
But the problem is as you see when the frequency is so large the Y axis title is colliding with the frequency numbers. So is there any simple way to move the Y axis title left?
The layout of auxiliary elements such as axes and legends is not completely automatic in dc.js; use .margins() to adjust where necessary.
https://github.com/dc-js/dc.js/blob/master/web/docs/api-latest.md#marginsmargins
It would be great to figure this out automatically but it is difficult to calculate, and easy to work around, so I guess no one has gotten annoyed enough to submit a fix. :)
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.