> You don't have to take my word for this. Look up the history of what happened to the energy hedge fund Amaranth. Amaranths positions were sold to Citadel and JP to wind down gently. That's pretty different from forced…
Not quite neutral. You return -0.0 only when needed. >>> 0.0+0.0 0.0 >>> 0.0+(-0.0) 0.0 >>> (-0.0)+0.0 0.0 >>> (-0.0)+(-0.0) -0.0
Discussion 3 days ago: https://news.ycombinator.com/item?id=25278128
I don't know if this comment is serious, but I'd suggest you explore the idea that you don't know, what you don't know. With a few years of experience, you can feel comfortable in a technology stack and seen and learnt…
It doesn't quite seem fair to compare numpy to one of the most famous K code golf's ever created, but here is my attempt, 140 characters compared to Arthur's 30, so 5 times longer. Not worry about padding the edges…
This 100 character version is probably the cleanest. M = np.reshape(np.arange(16),(4,4)) np.array([np.roll(M,(i,j),(0,1)) for i in [1,0,-1] for j in [1,0,-1]])
> You don't have to take my word for this. Look up the history of what happened to the energy hedge fund Amaranth. Amaranths positions were sold to Citadel and JP to wind down gently. That's pretty different from forced…
Not quite neutral. You return -0.0 only when needed. >>> 0.0+0.0 0.0 >>> 0.0+(-0.0) 0.0 >>> (-0.0)+0.0 0.0 >>> (-0.0)+(-0.0) -0.0
Discussion 3 days ago: https://news.ycombinator.com/item?id=25278128
I don't know if this comment is serious, but I'd suggest you explore the idea that you don't know, what you don't know. With a few years of experience, you can feel comfortable in a technology stack and seen and learnt…
It doesn't quite seem fair to compare numpy to one of the most famous K code golf's ever created, but here is my attempt, 140 characters compared to Arthur's 30, so 5 times longer. Not worry about padding the edges…
This 100 character version is probably the cleanest. M = np.reshape(np.arange(16),(4,4)) np.array([np.roll(M,(i,j),(0,1)) for i in [1,0,-1] for j in [1,0,-1]])