A Great Wyrm of Chaos has a chance of 1 in 3 to use a spell or breath attack; with 5 spells and 2 breaths to chose from, that's a 2 in 21 chance of a breath attack each turn. Now you have speed +34 when hasted; the dragon has +10. So in your 10 rounds of melee, he gets 5 actions. Chance of no breath attack within your 10 turns is 60%, no matter where you are.
Damage vs Accuracy
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Well, I guess I've been disabused of a fantasy that I thoroughly enjoyed, pooh!
That rather nasty bug has not been fixed in 4.0.5. I tested on an Istar with average 1800 HP and it took 8 charges from the Wand of Annihilation to bring it down. Seven times 250 plus 50 from the eighth charge. Any thoughts on a backport for the fix? 4.1 seems to be a whole different game.
Thanks for the info on @'s weight. I didn't know what an Angband stone was, so I just assumed that 13lb was the equivalent of 3 stone. It did seem rather ridiculously low.
Regarding archery, @ did recently find a Sling of Buckland (x4) (+18, +17) <+5, +2> that I've been thinking about giving a try. Trouble is, I've been passing up high grade sling ammo all game, so I'd need to start accumulating it from scratch. Also, up until now, I've needed the stats from the bow @ is currently wielding. That is no longer the case though.
One other thing. When I was looking for a monster to try the Wand of Annihilation on, I ran into Ariel, Queen of Air. Seeing as I knew that the wand wouldn't work on her, I cast Mana Storm instead. It failed five times in a row. With @'s current 14% chance of failure for this spell, the probability of that happening by chance is 1 in 18593. Has anyone checked the RNG used for spell failure for correlation?Last edited by Gordon; March 28, 2018, 21:04.Comment
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One other thing. When I was looking for a monster to try the Wand of Annihilation on, I ran into Ariel, Queen of Air. Seeing as I knew that the wand wouldn't work on her, I cast Mana Storm instead. It failed five times in a row. With @'s current 14% chance of failure for this spell, the probability of that happening by chance is 1 in 18593. Has anyone checked the RNG used for spell failure for correlation?Comment
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I beleive the Angband RNG is random in the mathematical and statistical sense; but often it seems "unfair" or "streaky" to humans.Playing roguelikes on and off since 1984.
rogue, hack, moria, nethack, angband & zangband.Comment
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Well, 1 in 18593 is slightly less probable than flipping a coin and having it come up heads 14 times in a row. I think any intelligent being would look upon that coin with suspicion. That said, I was glad to hear that this RNG had been tested for correlation. Serial correlation analysis is just as important as uniformity analysis when evaluating a RNG and is often neglected.Comment
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When evaluating likelihood of an event like repeated fails on a 5% throw, it's better to ignore the first failure, as you are looking at a case where there is at least one failure. So the first failure should be considered a prior. 1 in 18000 isn't all that unlikely when integrated over all games and players.Comment
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One other thing. When I was looking for a monster to try the Wand of Annihilation on, I ran into Ariel, Queen of Air. Seeing as I knew that the wand wouldn't work on her, I cast Mana Storm instead. It failed five times in a row. With @'s current 14% chance of failure for this spell, the probability of that happening by chance is 1 in 18593. Has anyone checked the RNG used for spell failure for correlation?
I skipped the formulas, of course (maybe Nick can verify them ). But there are also some human language examplanations and even some code. So I played a bit with it on my machine. If you cast mana storm 100 times, you'll get a streak of 5 or more failures in a row with about 1% probability. 18000 casts give you more than 50% chance of getting a bad run.
I guess there is a useful lesson here - always be prepared for the worstComment
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Here is a prettied up version of a python script for calculating this that I found on a link on that site.
Code:import argparse argparser = argparse.ArgumentParser(description='Calculate the probability of run of n events in m trials where p is the probabilty of an event') argparser.add_argument('-n', type=int, required=True, help='run length') argparser.add_argument('-m', type=int, required=True, help='number of trials') argparser.add_argument('-p', type=float, required=True, help='probability of an event') args = argparser.parse_args() N = args.n M = args.m p = args.p q = 1-p #probability of failure #setting up P_i (P[i] will be the probability that we see a run of length n in i flips) P = [None for i in range(0,M+1)] #initialize list to all Nones for i in range(0,N): #set boundary conditions, (not including P_N (r) P[i] = 0 P[N] =p**N #P_N (r) is now equal to p^N #now for main recursion (using a loop here instead) for i in range(N,M): P[i +1] = P[i] + (1-P[i-N]) * q * P[N] print 'A run of',N, 'events of probability',p, 'has a chance of 1 in',1.0 / P[M], 'of occuring in',M, 'trials'
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The other thing people often lose track of (or don't think about in the first place) is just how many trials are really being run in a typical game. I'll bet it's a *lot* more than most people realize, so when you do the math and come up with a 1 in 18,000 chance of something, you think "come on, that'll never happen" when in fact there are so many trials that it's to be expected a lot more than you think.Comment
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