How do i only show data points for the low and high? Every other data point can be hovered over to get their value but by default just the low and high should always show with custom tooltip
I was able to find a solution in case this helps anyone else out.
as i generate my xData and yData from api, i then grab min/max value from array
then i loop thru yData array and pull out the index of the min/max
as i'm initializing line chart, i used a function for pointRadius in the datasets that sets the dot to 10 if it's low or high, if not set it to 0 so it doesn't show
I set up Color Scale no color from lowest value to red color for highest value.
But if I filter data and column "Losses" have values $0 then for some reason the whole column becomes red.
Is any way how can it make it with "No color" if all the values are 0's?
in order to fix the problem I also have to indicate max value. So I used maximum value as $1,000,000 which is fit for my dataset.
i have a chart that fills itself with values, however currently i am limited on how many values i can display by the amount of label values i insert.
$scope.AxirsLabels = [1,2,3,4,5,6,7,8,9,10];
for example with the above label value i can only display 10 different values on the chart.
is it possible to set an unlimited amount of values based on the values of data?
each data value is an integer like 10 or 20 etc.
everytime the user clicks a button values are added to the data of the chart and the X axis needs to adjust.
Fixed it by using the function i use for adding data to the chart for the label values as well. this adds label values based on the amount of data values there are.
$scope.AxirsLabels = getDataProp('values');
I am trying to reverse the Y Axis in MSChart
The scale from left to right would be 5 - 1
So if a bar has a value of 2 it will fill from 5 until 2 on the scale with the score to the right of the filled bar.
This link shows exactly what I am trying to achieve
http://www.hfi.com/images/graph.png
Is this possible with MS Chart?
Thanks
Have you tried using IsReversed property on the Y axis.
I am using letter_regcog example from OpenCV, it used dataset from UCI which have structure like this:
Attribute Information:
1. lettr capital letter (26 values from A to Z)
2. x-box horizontal position of box (integer)
3. y-box vertical position of box (integer)
4. width width of box (integer)
5. high height of box (integer)
6. onpix total # on pixels (integer)
7. x-bar mean x of on pixels in box (integer)
8. y-bar mean y of on pixels in box (integer)
9. x2bar mean x variance (integer)
10. y2bar mean y variance (integer)
11. xybar mean x y correlation (integer)
12. x2ybr mean of x * x * y (integer)
13. xy2br mean of x * y * y (integer)
14. x-ege mean edge count left to right (integer)
15. xegvy correlation of x-ege with y (integer)
16. y-ege mean edge count bottom to top (integer)
17. yegvx correlation of y-ege with x (integer)
example:
T,2,8,3,5,1,8,13,0,6,6,10,8,0,8,0,8
I,5,12,3,7,2,10,5,5,4,13,3,9,2,8,4,10
now I have segmented image of letter and want to transform it into data like this to put recognize it but I don't understand the mean of all value like "6. onpix total # on pixels" what is it mean ? Can you please explain the mean of these value. thanks.
I am not familiar with OpenCV's letter_recog example, but this appears to be a feature vector, or set of statistics about the image of a letter that is used to classify the future occurrences of the letter. The results of your segmentation should leave you with a binary mask with 1's on the letter and 0's everywhere else. onpix is simply the total count of pixels that fall on the letter, or in other words, the sum of your binary mask.
Most of the rest values in the list need to be calculated based on the set of pixels with a value of 1 in your binary mask. x and y are just the position of the pixel. For instance, x-bar is just the sample mean of all of the x positions of all pixels that have a 1 in the mask. You should be able to easily find references on the web for mathematical definitions of mean, variance, covariance and correlation.
14-17 are a little different since they are based on edge pixels, but the calculations should be similar, just over a different set of pixels.
My name is Antonio Bernal.
In page 3 of this article you will find a good description for each value.
Letter Recognition Using Holland-Style Adaptive Classifiers.
If you have any doubt let me know.
I am trying to make this algorithm work, but my problem is that I do not know how to scale the values to fit them to the range 0-15.
Do you have any idea how to do this?
Another Link from Google scholar -> Letter Recognition Using Holland-Style Adaptive Classifiers