Is is possible to create a scale-location plot in SPSS?
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Is it possible to change the scatter plot point from the usual circle to something else. And more specifically can this be linked to a Dimension?
I know I can change the colour but we are already using a Master Item colour, and need to and another dimension.
We are also using the marker size for a measure so we cant co-opt that either
We are using Qlik Sense (SaaS).
From experience, no, you can't, I have ended up creating my own extension to create my own scatter plots to have donuts instead of dots using chart.js
Thanks,
I would like to implement a scatterplot over timeline using plotly.js, similar to the image below.
Plotly takes in x and y values to plot the chart. But I will be plotting x-values(time) without any y-values. Is it possible to do so ? Or can I generate random values for y-axis ? Any suggestion or idea would be great.
I intend to draw maps using d3.js and geoJson.
I need to plot circles on this map.These circles when hovered should get bigger and display some data inside that.
Also,i need to create a time line scale which will increase and decrease the circles in the map based on the data for that particular time frame.
I am able to draw map with the help of geo JSON file but the problem is how to plot the circles such that when map is moved in the canvass the circle remains at same position inside the map.I mean the circles should be relative to map not relative to canvass.
Secondly I am not able to understand how the coordinate system of maps work.
Any help Please..
I'm a bit new to D3, so I apologize if this is trivial.
I want to create a histogram that allows a user to brush over parts of a histogram and display all of the selected data points in a table separate of the histogram. Basically, I want to create (http://square.github.com/crossfilter/) in D3 using a "brush". All of the examples that I've seen have bar charts instead of histograms. I couldn't get anything to work by creating the brush in a histogram visualization. Is this possible or should I just re-tool a bar graph into a pseudo-histogram?
Thank you!
I am attempting to create a content based image retrieval system (CBIR) in MATLAB for colour images, and am using a k-means algorithm to extract the feature vectors for images in my database. Each image has four clusters, and each cluster has information about the colour (R,G,B) and position (X,Y).
I am now trying to add a texture feature to my clusters, and need to use grey level co-occurrence matrices (GLCM) for this. I know that GLCM is just an indicator of probability that a certain grey level will appear next to another, and have created the GLCM for my images.
I am unclear about how to map the GLCM to the original image (and thus its clusters), since GLCM talks about pairs of pixels, and I would like each X,Y position to have texture information. How does one go about translating GLCM to pixels?
The output of GLCM seems to be a T-by-T matrix where T is the number of distinct grayscale levels in the image. Therefore, the size of this matrix does not really depend on the size of your image. The matrix also describes the texture of the whole image, so it isn't especially meaningful to associate GLCM data with a single pixel.
It sounds like you could compute GLCM for the individual clusters, since this would describe the texture within that cluster? I think graycomatrix requires a rectangular image, but you could find the bounding box for each cluster and extract GLCM from them separately.
If you wanted to get some more meaningful information out of a GLCM matrix (i.e. something that is appropriate as a 'feature'), you could use graycoprops which returns 4 summary statistics.