Is there an easy way to create a difference chart using dimple? I'm looking to create something similar to this example: http://bl.ocks.org/mbostock/3894205/.
Thanks
I know this was asked 2 years ago, maybe someone is still interested :-)
A way to do this with dimple is to transform your 2 series (say A and B) into 3 series:
a serie that draws the lower line: its values are min(A,B)
a serie that draws the upper line when A > B and fills with green: its values are max(A-B,0)
a serie that draws the upper line when A < B and fills with red: its values are max(B-A,0)
Then you stack all 3 and use dimple.plot.area for the last 2 to have the fill-in effect.
We can make a working example if you provide your code and data.
Related
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)
I want to plot only one simple set of data. For example, my plot command could be :
x = (1:10);
y = ones[1,10];
plot(x,y);
In fact, the y data set could have been generated by a previous code, depending on several parameters. I want to print the name of every parameters and there values outside the graph, at the right of it, as if it were a legend. My problem is that I have several parameters to print, but only one set of data.
I tried to do this by the text or legend functions, but it never fit completly my needs.
Could you help me please ?
I think this code should help you out. Its probably easiest to split your figure into two axes, the right one just to hold text:
x = rand(1,10);
y = rand(1,10);
figure % makes your figure
axes('Position', [0.05,0.05,0.45,.9]) % makes axes on left side of your figure
scatter(x,y)
axes('Position', [0.55,0,1,1],'ytick',[],'xtick',[]) %make axes on left side of your figure, turns of ticks
text(0.05,0.85,{'Parameter 1: blah blah';'Parameter 2: bloop bloop';'Parameter 3: ....'},'Interpreter','Latex')
Play around with the numbers in the brackets to resize things as you like.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Detecting thin lines in blurry image
So as the title says, I am trying to detect boundaries of patterns. In the images attached, you can basically see three different patterns.
Close stripe lines
One thick L shaped line
The area between 1 & 2
I am trying to separate these three, in say 3 separate images. Depend on where the answers go, I will upload more images if needed. Both idea or code will be helpful.
You can solve (for some values of "solve") this problem using morphology. First, to make the image more uniform, remove irrelevant minima. One way to do this is using the h-dome transform for regional minima, which suppresses minima of height < h. Now, we want to join the thin lines. That is accomplished by a morphological opening with a horizontal line of length l. If the lines were merged, then the regional minima of the current image is the background. So we can fill holes to obtain the relevant components. The following code summarizes these tasks:
f = rgb2gray(imread('http://i.stack.imgur.com/02X9Z.jpg'));
hm = imhmin(f, h);
o = imopen(hm, strel('line', l, 0));
result = imfill(~imregionalmin(o), 'holes');
Now, you need to determine h and l. The parameter h is expected to be easier since it is not related to the scale of the input, and in your example, values in the range [10, 30] work fine. To determine l maybe a granulometry analysis could help. Another way is to check if the result contains two significant connected components, corresponding to the bigger L shape and the region of the thin lines. There is no need to increase l one by one, you could perform something that resembles a binary search.
Here are the hm, o and result images with h = 30 and l = 15 (l in [13, 19] works equally good here). This approach gives flexibility on parameter choosing, making it easier to pick/find good values.
To calculate the area in the space between the two largest components, we could merge them and simply count the black pixels inside the new connected component.
You can pass a window (10x10 pixels?) and collect features for that window. The features could be something as simple as the cumulative gradients (edges) within that window. This would distinguish the various areas as long as the window is big enough.
Then using each window as a data point, you can do some clustering, or if the patterns don't vary that much you can do some simple thresholds to determine which data points belong to which patterns (the larger gradient sums belong to the small lines: more edges, while the smallest gradient sums belong to the thickest lines: only one edge, and those in between belong to the other "in-between" pattern .
Once you have this classification, you can create separate images if need be.
Just throwing out ideas. You can binarize the image and do connected component labelling. Then perform some analysis on the connected components such as width to discriminate between the regions.
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.
I need to write an application in VB6 which makes a scatter plot out of a series of data points.
The current workflow:
User inputs info.
A bunch of calculations go down.
The output data is displayed in a series of 10 list boxes.
Each time the "calculate" button is clicked, 2 to 9 entries are entered into the list boxes.
One list box contains x coordinates.
One list box contains the y coordinates.
I need to:
Scan through those list boxes, and select my x's and y's.
Another list box field will change from time to time, varying between 0 and 100, and that field is what needs to differentiate which series on the eventual graph the x's and y's go into. So I will have Series 1 with six (x,y) data points, Series 26 with six data points, Series 99 with six data points, etc. Or eight data points. Or two data points. The user controls how many x's there are.
Ideally, I'll have a graph with multiple series displaying all this info.
I am not allowed to use a 3rd party solution (e.g. Excel). This all has to be contained in a VB6 application.
I'm currently trying to do this with MS Chart, as there seems to be the most documentation for that. However, this seems to focus on pie charts and other unrelated visualizations.
I'm totally open to using MS Graph but I don't know the tool and can't find good documentation.
A 2D array is, I think, a no go, since it would need to be of a constantly dynamically changing size, and that can't be done (or so I've been told). I would ideally cull through the runs, sort the data by that third series parameter, and then plug in the x's and y's, but I'm finding the commands and structure for MS Chart to be so dense that I'm just running around in very small circles.
Edit: It would probably help if you can visualize what my data looks like. (S for series, made up numbers.)
S X Y
1 0 1000000
1 2 500000
1 4 250000
1 6 100000
2 0 1000000
2 2 6500
2 4 5444
2 6 1111
I don't know MSGraph, but I'm sure there is some sort of canvas element in VB6 which you can use to easily draw dots yourself. Scatter plots are an easy graph to make on your own, so long as you don't need to calculate a line of best fit.
I would suggest looking into the canvas element and doing it by hand if you can't find a tool that does it for you.
Conclusion: MSChart and MSGraph can both go suck a lemon. I toiled and toiled and got a whole pile of nothing out of either one. I know they can do scatter plots, but I sure as heck can't make them do 'em well.
#BlackBear! After finding out that my predecessor had the same problems and just used Pset and Line to make some really impressive graphs, I did the same thing - even if it's not reproducible and generic in the future as was desired. The solution that works, albeit less functionally >> the solution with great functionality that exists only in myth.
If anyone is reading this down the line and has an actual answer about scatter plots and MSChart/Graph, I'd still love to know.