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<shape xmlns:android="http://schemas.android.com/apk/res/android" | |
android:shape="rectangle"> | |
<gradient | |
android:angle="90" | |
android:endColor="@android:color/transparent" | |
android:startColor="#66000000"/> | |
</shape> |
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/** | |
* In-place algorithm that rotates an NxN integer matrix array by 90 degrees. | |
* @param array - input array to rotate | |
* @return - array rotated 90 degrees | |
*/ | |
public static int[][] rotate90(int[][] array) { | |
int topLeftTemp; | |
for(int i = 0; i < array.length - i; i++) { | |
int arrayBound = array.length - 1; | |
for(int j = i; j < arrayBound-i; j++) { |
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# Scalable Kalman Filter written in python 3 that takes in multiple matrixes and outputs both a predicted state estimate and predicted estimate covariance. | |
# NOTE: matrixes passed into the Kalman filter MUST adhear to linear algebra matrix multiplication rules. | |
# Uncomment import if matrix has not been imported yet. | |
# from Matrix import matrix | |
# inputs: | |
# measurements: Sensor world data. | |
# x: Initial state. | |
# P: Initial uncertainty. |