i noticed the faces of human repeated or similar,
and would like to prove whether evolution a several generations will
return to the original intelligence of ancester
On Friday, November 18, 2016 at 1:55:31 PM UTC+8, meInvent bbird wrote:
> how to simulate the situation in DNA evolution for finding the minimum
> population needed and minimum samples selected to mating in order to no
> extinction in any one of original species and new species
>
> assume mating are randomly selected to become a couple,
> how to keep species good which means no extinction in original species
>
> i use i+j to get new species,
> but i do not know whether there is limit in evolution, i assume
> limit is 7, then extra evolution will go back to past species and
> cycle again
>
> import matplotlib.pyplot as plt
> import random
> dict = {}
> dist = {}
> maxnum = 5
> allowedmax = 7
> for i in range(1,allowedmax+1):
> dist[str(i)] = 0
>
> rr = range (1,maxnum)
> for i in range (1,maxnum):
> for j in range (1,maxnum):
> if i < j:
> print("(" +str(i) + "," + str(j) + ")");
> dict[str(i) + str(j)] = 1;
> dist[str(i+j)] = dist[str(i+j)] + 1
> if i+j > max(rr or [0]):
> rr = rr + [i+j];
>
> original = rr;
> for numberofevolutions in range(1,10):
> rr2 = []
> samples = random.sample(original, len(original)-2)
> print("total rr")
> print(str(rr))
> print("samples")
> print(str(samples))
> for i in samples:
> for j in samples:
> if i < j:
> print("(" +str(i) + "," + str(j) + ")");
> if i+j > allowedmax:
> dict[str(i) + str(j)] = (i+j) % allowedmax;
> dist[str((i+j) % allowedmax)] = dist[str((i+j) %
> allowedmax)] + 1
> if ((i+j) % allowedmax) > max(rr2 or [0]):
> rr2 = rr2 + [((i+j) % allowedmax)];
> else:
> dict[str(i) + str(j)] = i+j;
> dist[str(i+j)] = dist[str(i+j)] + 1
> if i+j > max(rr2 or [0]):
> rr2 = rr2 + [i+j];
> temp = rr
> rr = rr2
> rr2 = temp
>
> plt.bar(range(len(dist)), dist.values(), align='center')
> plt.xticks(range(len(dist)), dist.keys())
> plt.show()
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