ludennis

$ rosrun cartographer_ros cartographer_rosbag_validate -bag_filename $PWD/e2w-patched.bag

I1030 22:02:45.935303 14457 rosbag_validate_main.cc:398] Time delta histogram for consecutive messages on topic "/imu/data" (frame_id: "base_imu"):
Count: 26499  Min: 0.000612  Max: 0.023971  Mean: 0.010000
[0.000612, 0.002948)	                    	Count: 6 (0.022642%)	Total: 6 (0.022642%)
[0.002948, 0.005284)	                    	Count: 43 (0.162270%)	Total: 49 (0.184913%)
[0.005284, 0.007620)	                    	Count: 20 (0.075475%)	Total: 69 (0.260387%)
[0.007620, 0.009956)	                  ##	Count: 3036 (11.457036%)	Total: 3105 (11.717423%)
[0.009956, 0.012292)	  ##################	Count: 23324 (88.018417%)	Total: 26429 (99.735840%)
[0.012292, 0.014627)	                    	Count: 55 (0.207555%)	Total: 26484 (99.943398%)

ludennis

$rosrun cartographer_ros cartographer_rosbag_validate -bag_filename $PWD/shuttle_route-patched.bag

I1030 21:58:40.303122 14001 rosbag_validate_main.cc:398] Time delta histogram for consecutive messages on topic "/imu/data" (frame_id: "base_imu"):
Count: 92264  Min: 0.000462  Max: 0.027200  Mean: 0.010000
[0.000462, 0.003136)	                    	Count: 126 (0.136565%)	Total: 126 (0.136565%)
[0.003136, 0.005810)	                    	Count: 305 (0.330573%)	Total: 431 (0.467138%)
[0.005810, 0.008483)	                    	Count: 1290 (1.398162%)	Total: 1721 (1.865300%)
[0.008483, 0.011157)	 ###################	Count: 88652 (96.085144%)	Total: 90373 (97.950447%)
[0.011157, 0.013831)	                    	Count: 1451 (1.572661%)	Total: 91824 (99.523109%)
[0.013831, 0.016505)	                    	Count: 301 (0.326238%)	Total: 92125 (99.849342%)

ludennis

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#Deep Learning (Neural Networks)
A day prior to my Deep Learning nanodegree foundation begins, I try to prep myself as much as possible for the topics that are to be covered. And I stumbled upon Welch Labs YouTube Channel with 7 parts of their videos to explain and code Deep Learning Neural Networks in Python with a simple case.


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Coding a neural network to learn it
So I thought of how I, as a kinesthetic learner, can learn neural network, and I thought of just trying to work out the same example given in the first part of neural networks from Welch Labs: