ConwayLife.com

shouldsee wrote:The fixed "mutate.py" takes the current rulestring and flips a random hensel configuration. It depends on the messy collection "KBs.py" and please place them in the same folder.

mutate.py

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## Written by Feng (shouldsee.gem@gmail.com) March 2018.
import golly
import KBs

import random


# rulestr=golly.getstring('NTCA number',golly.getclipstr()).split('_')[-1];
kb = KBs.kb_2dntca()
# alias = golly.getrule()
curr=golly.getrule().split(':')
if len(curr)==1:
	curr+=['']
alias,suffix = curr

rulestr = kb.alias2rulestr(alias)
bitstr = KBs.hex2bin(rulestr,102)
# assert KBs.bin2hex(bitstr)==rulestr
bitlst = list(bitstr)

idx =  random.randint(0,102)
flip = {'0':'1','1':'0'}
bitlst[idx] = flip[bitlst[idx]]
rulestr = KBs.bin2hex(''.join(bitlst))
alias = kb.rulestr2alias(rulestr)


golly.note(alias)
golly.setclipstr(alias)

golly.setrule('%s:%s'%(alias,suffix))

KBs.py

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import numpy as np
import pickle
import itertools, collections, re
import copy
import random
import collections 
count = collections.Counter
identity = lambda x:x
# import collections
base2bin=lambda data,scale,num_of_bits: bin(int(data, scale))[2:].zfill(num_of_bits);
hex2bin=lambda hexdata,num_of_bits: base2bin(hexdata,16,num_of_bits);
bin2hex = lambda bitstr:hex(int(bitstr,2)).lstrip('0x').rstrip('L')

# from astropy.convolution import convolve
# convolve_int=lambda a,fir,method:np.around(convolve(a,fir,method)).astype(np.int);
import scipy.ndimage
convolve_int=lambda a,fir,method,**kwargs:scipy.ndimage.filters.convolve(a,fir,mode = method,**kwargs)

hensellist=['b0_','b1c','b1e','b2a','b2c','b3i','b2e','b3a','b2k','b3n','b3j','b4a','s0_','s1c','s1e','s2a','s2c','s3i','s2e','s3a','s2k','s3n','s3j','s4a','b2i','b3r','b3e','b4r','b4i','b5i','s2i','s3r','s3e','s4r','s4i','s5i','b2n','b3c','b3q','b4n','b4w','b5a','s2n','s3c','s3q','s4n','s4w','s5a','b3y','b3k','b4k','b4y','b4q','b5j','b4t','b4j','b5n','b4z','b5r','b5q','b6a','s3y','s3k','s4k','s4y','s4q','s5j','s4t','s4j','s5n','s4z','s5r','s5q','s6a','b4e','b5c','b5y','b6c','s4e','s5c','s5y','s6c','b5k','b6k','b6n','b7c','s5k','s6k','s6n','s7c','b4c','b5e','b6e','s4c','s5e','s6e','b6i','b7e','s6i','s7e','b8_','s8_',];
rca2ntca=[0, 1, 2, 3, 1, 4, 3, 5, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 13, 16, 15, 17, 14, 15, 18, 19, 20, 21, 22, 23, 2, 8, 6, 10, 3, 9, 7, 11, 24, 25, 26, 27, 25, 28, 27, 29, 14, 20, 18, 22, 15, 21, 19, 23, 30, 31, 32, 33, 31, 34, 33, 35, 1, 4, 8, 9, 36, 37, 38, 39, 3, 5, 10, 11, 38, 39, 40, 41, 13, 16, 20, 21, 42, 43, 44, 45, 15, 17, 22, 23, 44, 45, 46, 47, 8, 48, 49, 50, 38, 51, 52, 53, 25, 54, 55, 56, 57, 58, 59, 60, 20, 61, 62, 63, 44, 64, 65, 66, 31, 67, 68, 69, 70, 71, 72, 73, 2, 8, 24, 25, 8, 48, 25, 54, 6, 10, 26, 27, 49, 50, 55, 56, 14, 20, 30, 31, 20, 61, 31, 67, 18, 22, 32, 33, 62, 63, 68, 69, 6, 49, 26, 55, 10, 50, 27, 56, 26, 55, 74, 75, 55, 76, 75, 77, 18, 62, 32, 68, 22, 63, 33, 69, 32, 68, 78, 79, 68, 80, 79, 81, 3, 9, 25, 28, 38, 51, 57, 58, 7, 11, 27, 29, 52, 53, 59, 60, 15, 21, 31, 34, 44, 64, 70, 71, 19, 23, 33, 35, 65, 66, 72, 73, 10, 50, 55, 76, 40, 82, 59, 83, 27, 56, 75, 77, 59, 83, 84, 85, 22, 63, 68, 80, 46, 86, 72, 87, 33, 69, 79, 81, 72, 87, 88, 89, 1, 36, 8, 38, 4, 37, 9, 39, 8, 38, 49, 52, 48, 51, 50, 53, 13, 42, 20, 44, 16, 43, 21, 45, 20, 44, 62, 65, 61, 64, 63, 66, 3, 38, 10, 40, 5, 39, 11, 41, 25, 57, 55, 59, 54, 58, 56, 60, 15, 44, 22, 46, 17, 45, 23, 47, 31, 70, 68, 72, 67, 71, 69, 73, 4, 37, 48, 51, 37, 90, 51, 91, 9, 39, 50, 53, 51, 91, 82, 92, 16, 43, 61, 64, 43, 93, 64, 94, 21, 45, 63, 66, 64, 94, 86, 95, 9, 51, 50, 82, 39, 91, 53, 92, 28, 58, 76, 83, 58, 96, 83, 97, 21, 64, 63, 86, 45, 94, 66, 95, 34, 71, 80, 87, 71, 98, 87, 99, 3, 38, 25, 57, 9, 51, 28, 58, 10, 40, 55, 59, 50, 82, 76, 83, 15, 44, 31, 70, 21, 64, 34, 71, 22, 46, 68, 72, 63, 86, 80, 87, 7, 52, 27, 59, 11, 53, 29, 60, 27, 59, 75, 84, 56, 83, 77, 85, 19, 65, 33, 72, 23, 66, 35, 73, 33, 72, 79, 88, 69, 87, 81, 89, 5, 39, 54, 58, 39, 91, 58, 96, 11, 41, 56, 60, 53, 92, 83, 97, 17, 45, 67, 71, 45, 94, 71, 98, 23, 47, 69, 73, 66, 95, 87, 99, 11, 53, 56, 83, 41, 92, 60, 97, 29, 60, 77, 85, 60, 97, 85, 100, 23, 66, 69, 87, 47, 95, 73, 99, 35, 73, 81, 89, 73, 99, 89, 101];
henseldict={'0': ['_'],
 '1': ['c', 'e'],
 '2': ['a', 'c', 'e', 'k', 'i', 'n'],
 '3': ['i', 'a', 'n', 'j', 'r', 'e', 'c', 'q', 'y', 'k'],
 '4': ['a', 'r', 'i', 'n', 'w', 'k', 'y', 'q', 't', 'j', 'z', 'e', 'c'],
 '5': ['i', 'a', 'j', 'n', 'r', 'q', 'c', 'y', 'k', 'e'],
 '6': ['a', 'c', 'k', 'n', 'e', 'i'],
 '7': ['c', 'e'],
 '8': ['_']}


rca2ntca=np.array(rca2ntca,np.int);
henselidx={k: v for v, k in enumerate(hensellist)};
subconf='_cekainyqjrtwz';
p_NOTnumletter = re.compile(r'[^\da-zA-Z\-]')    

try:
    from data import *
    with open('tp','rb') as f:  # Python 3: open(..., 'rb')
       hdist, tst_data = pickle.load(f)
       hdist = np.array(hdist).reshape([512,512]);
except:
    print('[WARN]Not finding data.py')




def invert(s):
    num = s[0]
    conf = henseldict[num]
    return ''.join([num]+[x for x in conf if x not in s])

def ntuple(lst,n):
    """ntuple([0,3,4,10,2,3], 2) => [(0,3), (4,10), (2,3)]
    
    Group a list into consecutive n-tuples. Incomplete tuples are
    discarded e.g.
    
    >>> group(range(10), 3)
    [(0, 1, 2), (3, 4, 5), (6, 7, 8)]
    """    
    return zip(*[lst[i::n] for i in range(n)])

def add_all(s,prime,sold,neg=0):
    for c in subconf:
        conf=prime+sold+c;
        try:
            s[henselidx[conf]]=str(1-neg);
        except KeyError:
            pass
class kb_2dntca():
    def __init__(self):
        self.familyname='2dntca'
        pass
    def rulestr2alias(self, rulestr):
        OUT = ''
        # rulestr =  '000000000060031c61c67f86a0'
        r=hex2bin(rulestr,102);
        r=r[::-1];
        rule=[i for i,x in enumerate(r) if x=='1'];
#         print r
        lst = [hensellist[i] for i in rule]
        lst.sort()
        
        #### group by B/S
        d = collections.OrderedDict((('b',{}),('s',{}))) ### set default
#         d = {'b':{},'s':{}}   ### set default
        d.update(
            {k:list(gp) for k,gp in itertools.groupby(lst, lambda x:x[0])}        
        )
        for k,lst in d.items():
            d[k] = {k:list(gp) for k,gp in itertools.groupby(lst, lambda x:x[1])}
            
        for bs, dd in d.items():
            OUT += bs
            for k,lst in dd.items():
                OUT += k + ''.join( conf[-1] for conf in lst)
        OUT = OUT.replace('_','')
        alias = OUT
        return alias


    def alias2rulestr(self,alias): 
    # alias.replace('-','')
        alias = re.sub('(\d-[a-zA-Z]+)',lambda o:invert(o.group()),alias)
        alias = p_NOTnumletter.sub( '', alias).lower()
        OUT = ['0']*102
        d = collections.OrderedDict((('b',{}),('s',{}))) ### set default
        # d.update()
        # alias.split('s')
        s = alias
        lst = [x for x  in re.split("([bs])", s) if x]
        if len(lst) % 2: #### Padding to even length
            lst += ['']
        d  = dict(ntuple(lst,2))
        idxs = []
        for k, v in d.items():
            s = v
            lst = [x for x in re.split("(\d)", s) if x]
            L  = len(lst)
            v_old = ''
            for i,v in enumerate(lst):
                if v.isdigit():
                    if v_old.isdigit():
                        idx = [henselidx.get( k + v_old + c,None) for c in subconf]
                        idxs.extend(idx)
                    if i + 1 == L:
                        idx = [henselidx.get( k + v + c,None) for c in subconf]
                        idxs.extend(idx)
                    num = v
                else:
                    idx = [henselidx[ k + num + v_i]  for v_i in v ]
                    idxs.extend(idx)
                v_old = v
        idxs = [ x for x in idxs if x is not None] 
        for i in idxs:
            if not i is None:
                OUT[i] = '1'
        bitstr=''.join(OUT[::-1]);
        hexstr=hex(int(bitstr,2)).lstrip('0x').rstrip('L').zfill(26)
        return hexstr
#     def alias2rulestr(self, alias):
#         alias = p_NOTnumletter.sub( '', alias).lower()
#         OUT = ['0']*102
#         # print alias
#         d = collections.OrderedDict((('b',{}),('s',{}))) ### set default
#         # d.update()
#         # alias.split('s')
#         s = alias
#         lst = [x for x  in re.split("([bs])", s) if x]
#         if len(lst) % 2: #### Padding to even length
#             lst += ['']
#         d  = dict(ntuple(lst,2))
#         idxs = []
#         for k, v in d.items():
#             s = v
#             lst = [x for x in re.split("(\d)", s) if x]
#             L  = len(lst)
#             v_old = ''
#             for i,v in enumerate(lst):
#                 if v.isdigit():
#                     if v_old.isdigit():
#                         idx = [henselidx.get( k + v_old + c,None) for c in subconf]
#                         idxs.extend(idx)
#                     if i + 1 == L:
#                         idx = [henselidx.get( k + v + c,None) for c in subconf]
#                         idxs.extend(idx)
#                     num = v
#                 else:
#                     idx = [henselidx[ k + num + v_i]  for v_i in v ]
#                     idxs.extend(idx)
#                 v_old = v
#         idxs = [ x for x in idxs if x is not None] 
#         for i in idxs:
#             if not i is None:
#                 OUT[i] = '1'
#         bitstr=''.join(OUT[::-1]);
#         hexstr=hex(int(bitstr,2)).lstrip('0x').rstrip('L').zfill(26)
#         return hexstr
    def rulestr2adv(self,rulestr):
        ruleprj=np.array( 
            list(hex2bin(rulestr,102)[::-1]),
            np.int);
        adv = self.bin2adv(ruleprj)
#         ruleprj=np.array(list(hex2bin(rulestr,102)[::-1]));
#         fir=(2**np.arange(0,9)).reshape([1,3,3]);
#         pj=rca2ntca;
#         def adv(a,horizon):
#             return ruleprj[pj[convolve_int(a,fir,'wrap').astype(np.int)]]
#         # adv=lambda a, horizon: ruleprj[pj[convolve_int(a,fir,'wrap').astype(np.int)]]
        return adv 
    def conv(self,a):
        fir=(2**np.arange(0,9)).reshape([1,3,3]);
        pj=rca2ntca;
        return pj[convolve_int(a,fir,'wrap').astype(np.int)]
    def bin2adv(self, ruleprj):
        if isinstance(ruleprj,str):
            ruleprj = list(ruleprj)
        ruleprj = np.array(ruleprj,np.int)
        def adv(a,horizon=0):
            return ruleprj[self.conv(a)]
        return adv
    def rstr(self,callback=(lambda x:bin2hex(x).zfill(26)) ):
        r = '{:0102b}'.format(random.randrange(2**102))
        if callback is not None:
            r = callback(r)
        return r
    def randadv(self):
        return self.bin2adv(self.rstr(None))
    def bulk_rstr(self,seed = 0,bsize=2**18,**kwargs):
        random.seed(seed)
        lst = [{'family':self.familyname,
                'rulestr':self.rstr(**kwargs)} for x in range(bsize)]
        return lst    
    
    
class kb_2dtca():
#     def rulestr2alias(rulestr):
#         r=base2bin(int(rulestr),18,2);
#         r=r[:1:-1];
#         r+='0'*(18-len(r));
#         rule=[i for x,i in zip(r,range(len(r))) if x=='1'];
#         alias='b';
#         ps=1;
#         for a in rule:
#             if a>8 and ps:
#                 alias+='s';
#                 ps=0;
#             alias+=str((a)%9)
#         if ps==1:
#             alias+='s';
#         return alias        
    def alias2rulestr(self, ali):
        rule=['0']*18;
        ali=ali.replace('/','').lower().lstrip('b');
        (b,s)=ali.split('s');
        lst=list(str(int(i)+9) for i in s);
        bs=list(b)+(lst)
        for i in bs:
            rule[int(i)]='1';
        rnum=(''.join(rule[::-1]),2);
        return(rnum);
    def rulestr2adv(self,rulestr):
        #take an numpy array and convolution across the axis=[1,2];
        # project the convolved array back to value space according to the rule
        # 
        hex2bin(rulestr)
                                       
class CA_sys():
    def __init__(self,familyname = None,rulestr=None,dimsiz=None,adv=None,rdf=None):
#         siz=[600,100,400];
        if dimsiz is None:
            dimsiz = [128,128,32**2]
        if rulestr is None:
            rulestr = '0c83820e0060061941946a68f0'
        if familyname is None:
            familyname = '2dntca'
        self.familyname=familyname;
        self.rulestr=rulestr;
        self.adv=adv;
        self.dimsiz=dimsiz;
        self.change_size();
#         self.family = globals().get('familyname')
        self.family=eval('kb_%s()'%self.familyname);
        self.rulestr2alias()
#         self.
        if rdf==None:
            self.rdf=lambda:(np.random.random(self.siz)<=0.5).astype(np.int);

    def change_size(self,dimsiz=None):
        if dimsiz==None:
            dimsiz=self.dimsiz;
        N,hmax,ksq=dimsiz
        self.N=N;
        self.hmax=hmax;
        dd=int(ksq**0.5);
        self.siz = (N,dd,dd);
        
    def rulestr2alias(self):
#         kb=eval('kb_%s()'%self.familyname);
        # kb=eval('kb_%s'%self.familyname);
        self.alias=self.family.rulestr2alias(self.rulestr);
        self.adv=self.family.rulestr2adv(self.rulestr);
    def alias2rulestr(self):
#         kb=eval('kb_%s()'%self.familyname);
        # kb=eval('kb_%s'%self.familyname);
        self.rulestr=self.family.alias2rulestr(self.alias)
        self.adv    =self.family.rulestr2adv(self.rulestr)            
    def as_config(self):
        conf = {'family':self.family.familyname,
               'rulestr':self.rulestr,
                'alias':self.alias,}
        return conf
#     def change_adv(familyname,rulestr):

kb=kb_2dntca();
# kb.rulestr2alias('000000000060031c61c67f86a0')
kb.alias2rulestr('b3/s23')

    
# @function

# @function
def measure_temperature(sys0=None,hdist=None,*args,**kwargs):
#     varargin = measure_temperature.varargin
#     nargin = measure_temperature.nargin
    sysX=copy.copy(sys0)
    jmax=sysX.N;
    avi=sysX.rdf().astype(np.int)
    siz=avi.shape
    siz=(sysX.hmax,)+siz;
    tmp=np.zeros(siz)
    smtmp=np.zeros(siz)

    avc=avi
    i=0
    fir=np.reshape(2 ** (np.arange(0,9)),[1,3,3])
    trans=6
    mtp=0
    stp=0
    while i+1 < sysX.hmax:

        i=i + 1
        avcnew=(sysX.adv(avc,i))
        cavc=convolve_int(avc,fir,'wrap').astype(np.int);
        cavcnew=convolve_int(avcnew,fir,'wrap').astype(np.int);
        idx=np.ravel_multi_index((cavc,cavcnew),[2**9,2**9]);
        tmp[i,:,:,:]=np.expand_dims(hdist.flat[idx],0)
        if i >= trans:
            smtmpnow=np.mean(tmp[i - trans:i,:,:,:],axis=0)
            smtmp[i - trans,:,:,:]=smtmpnow
            if i >= trans + 10:
                mtp=np.mean(smtmpnow.flat)
                stpmat=((smtmp[i - trans,:,:,:] - smtmp[i - trans - trans,:,:,:]))
                a=np.mean(np.abs(stpmat.flat))
                b=abs(np.mean(stpmat.flat))
                stp=a - b
                stp1=np.mean(avcnew.flat)
                stp1=min(stp1,1 - stp1)
        avc=avcnew;
        #     im1=[avc(1,:,:)];
        if mtp < 0.02 and i > 20:
            break
    
    fam_alias=sys0.familyname+'_'+sys0.alias;
# /home/shouldsee/Documents/repos/CA_tfmat/custom_function/measure_temperature.m:55
    # s=sprintf('%s\\t%s\\t%d\\t%f\\t%f\\t%f\\n',fam_alias,num2str(sys0.od),i,mtp,stp,stp1)
    s='{}\t{}\t{:d}\t{:f}\t{:f}\t{:f}\n'.format(fam_alias,sysX.rulestr,i,mtp,stp,stp1)
# /home/shouldsee/Documents/repos/CA_tfmat/custom_function/measure_temperature.m:56
    return s
    
# if __name__ == '__main__':
#     pass
    


### Profiling loop
### Profiling loop
def profile(input_list, log = []):
    # global log
    output_data=[];    
    repeat=2;
    # input_list=[input_rulestr];
    ipt_list=input_list*repeat;
    # for i in range(5):
    l_ipt=len(input_list)
    log += ['Log of the process:'];
    logs='Starting to profile {:d} rules at {:d} replicates,\n totaling {:d} instances'.format(l_ipt,repeat,l_ipt*repeat);
    log += [logs];
    # print('Starting to profile {:d} rules at {:d} replicates,\n totaling {:d} instances'.format(l_ipt,repeat,l_ipt*repeat))

    for num,rulestr in enumerate(ipt_list):
        ca1=CA_sys(familyname,rulestr,[400,100,400]);
        ca1.rulestr2alias();
        s=measure_temperature(ca1,hdist);
        output_data+=[s];
    #     print('{:d} of {:d}'.format(num,len(ipt_list)))
        logs =('{:d} of {:d} '.format(num,len(ipt_list)));
        log += [logs];
    temp_data=[];
    # sample_data=[]
    for line in output_data:
        temp_data+=[line.rstrip('\n').split('\t')];
    sample_data=np.array(temp_data)
    # print('data is succesfully generated at {:d} replicates'.format(repeat))
    logs=('data is succesfully generated at {:d} replicates'.format(repeat))

    log  += [logs];

    # print('\n Detail of the input:')
    logs='\n Detail of the input:';
    log+=[logs];
    for k,v in ca1.__dict__.items():
        if not callable(v):
    #         print(k+str(v).ljust(-10))
    #         print("{:5} {:<15} {:<10}".format('',k, str(v)))

            logs=("{:5} {:<15} {:<10}".format('',k, str(v)));
            log+=[logs];
    return( [sample_data,log]);
    
if __name__ == '__main__':
    INPUT = "B345678/S012678"
    exp = "3f9fbe3e001fff07e07e15fea0"
    act = kb.alias2rulestr(INPUT)
    assert act == exp,'expected:%s, actual:%s' %(exp,act)
#     pass

def guess(i=None,sysX=None,dct=None):
    dimsiz = (256,2**7,24**2)
    if i is not None:
        rstr = tst_data[i][1]
        familyname='2dntca'
    if dct is not None:
        familyname = dct['family']
        rstr = dct['rulestr']
    if sysX is None:
        sysX = CA_sys(familyname,rstr,dimsiz)
        # sysX = KBs.CA_sys('2dntca',tst_data[i][1],(200,2**7,400))
        sysX.rulestr2alias()
    else:
        sysX.dimsiz = dimsiz
        sysX.change_size()# spspa.distance
    return sysX


import IPython.display as ipd
def lview(self):
    fmt = 'http://newflaw.com/view.php?rule_alias={:}'
    uri = fmt.format(self.alias)
    print uri
    ele = '<iframe src="{}" width=600 height=500></iframe>'.format(uri)
    ipd.display(ipd.HTML(ele))
    return uri


def sample(self,ini=None,adv = None):
    '''
    Sample an iterator ('CA_sys' object)
    '''
    if adv is None:
        adv = self.adv
    if ini is None:
        ini=self.rdf().astype(int)
    avc = ini
    hist = np.zeros((self.hmax,)+avc.shape,dtype=np.int)
    for i in range(self.hmax):
        hist[i]=avc
        avc=(adv(avc)) 
    return hist
def fill_ber(arr,p=0.5):
    '''
    Create bernouli using shape of arr
    '''
    return np.random.random(arr.shape) < p
def mix_adv(fA,fB,pa=0):
    '''
    Mixing two iterator
    '''
    if pa==1:
        adv = lambda arr:fA(arr)
    elif pa==0:
        adv = lambda arr:fB(arr)
    else:
        def adv(arr):
            mask = np.random.random(arr.shape)<pa
            A = fA(arr)
            B = fB(arr)
#             arr[mask] = A
#             arr[~mask] = B
            out = A*mask + B*(1-mask)
            return out
#             return arr
    return adv
def cov2cor(COV):
    D = np.diag(COV)
    COR = COV /  np.sqrt(D[:,None]*D[None,:])
    return COR


# Fast run length encoding
def rle (img):
    '''
    Source:https://www.kaggle.com/hackerpoet/even-faster-run-length-encoder
    '''
    x = np.ravel(img)
#     flat_img = img.flatten()
#     flat_img = np.where(flat_img > 0.5, 1, 0).astype(np.uint8)
    ### startswith 0->1
    ### endswith 1->0
    starts = np.array((x[:-1] == 0) & (x[1:] == 1))
    ends = np.array((x[:-1] == 1) & (x[1:] == 0))
    starts_ix = np.where(starts)[0] + 1
    ends_ix = np.where(ends)[0] + 1
    if x[0] == 1:
        starts_ix = np.insert(starts_ix,0,0)
    if x[-1] == 1:
        ends_ix = np.append(ends_ix,len(x))
    lengths = ends_ix - starts_ix
    
    return starts_ix, lengths
def _gollyrle(x):
    sl = rle(x)
    sym='bo$'
    S = 0
    out = ''
    L = 0
#     if s
    if sl[0].size!=0:
        for s,l1 in zip(*sl):
            l0 = s-S-L
            if l0>0:        
                inc = '%d%s'%(l0,sym[0]) ### number of zeros
                out = '%s%s'%(out,inc)
            inc = '%d%s'%(l1,sym[1])
            out = '%s%s'%(out,inc)
            S = s
            L = l1
    l0 = len(x)-S-L
    if l0>0:        
        inc = '%d%s'%(l0,sym[0]) ### number of zeros
        out = '%s%s'%(out,inc)
#     out='%s%s'%(out,sym[-1])
    return out
_gollyrle(map(int,list('010001001010')))
def gollyrle(arr):
    return '$'.join(map(_gollyrle,arr))
def hill(x):
    return 1-abs(2*x-1)
def sflatten(arr):
    return np.reshape(arr,(len(arr),-1))
def sexpand(arr,d=2):
    S = arr.shape
    root = int(round(S[1]**(1./d)) )
    out = np.reshape(arr,(S[0],)+(root,)*d)
    return out


def showsptime(arr,ax=None,**kwargs):
    if ax is None:
        fig,ax = plt.subplots(1,1,figsize=[12,4])    
    return ax.pcolormesh(sflatten(arr),**kwargs)
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import IPython.display as ipd
def animate(arr,html = 1,nFrame=20):
    '''
    Animate a list of 2d-array
    '''
    fig, ax = plt.subplots()
    im = ax.imshow(arr[0])
    ax.grid()
    data_gen = arr

    def run(data):
        im.set_data(data)
        return im,

    ani = animation.FuncAnimation(fig, run, 
                                  data_gen, 
                                  blit=False,
                                  interval=1000./nFrame,
                                  repeat=1, init_func=None)
    plt.close()
    if html:
        ani = ipd.HTML(ani.to_html5_video())
    return ani

KittyTac wrote:Can anyone tell me the solution to my problem?

KittyTac wrote:Can anyone tell me the solution to my problem?

pip install numpy

KittyTac wrote:

Code: Select all

>>> pip install numpy
  File "<stdin>", line 1
    pip install numpy
              ^
SyntaxError: invalid syntax

Help.

KittyTac wrote:Wait, how did you do that? It says that it is not a cmd command or something along those lines. I'm on Windows 8.1 if that's any help.

py -m pip install numpy
Worked for me!

what about py -m makes it work, and what do they do? Please explain your answer!

'py' is the python command line alias for windows that for one reason or another is sometimes set as a default during python installation. '-m' is mod option which allows you to run a library module as a script. 'py -m' instructs python to run the pip module as a script, passing the install and numpy keywords.

KittyTac wrote:I'm Russian, and the message is in Russian. So I won't be able to search StackOverflow with it.

C:\Users\{username}>pip install numpy
'pip' is not recognized as an internal or external command,
operable program or batch file.

dvgrn wrote:

KittyTac wrote:I'm Russian, and the message is in Russian. So I won't be able to search StackOverflow with it.

Okay, in that case it's definitely not worth messing with Windows' language settings to get a searchable chunk of text for that particular error message. Sometimes that might be useful, but here you're probably just seeing the equivalent of

C:\Users\{username}>pip install numpy
'pip' is not recognized as an internal or external command,
operable program or batch file.

Does that seem right? If so, you might just need to change directories to where pip actually is on your system, and run the command from there.

KittyTac wrote:It worked! Thanks! But mutate.py still does not work. It doesn't even open.

It depends on the messy collection "KBs.py" and please place them in the same folder.

dvgrn wrote:

KittyTac wrote:It worked! Thanks! But mutate.py still does not work. It doesn't even open.

It depends on the messy collection "KBs.py" and please place them in the same folder.

Where did you put the two Python files, and what are their names? (Just checking.)

Do other Python scripts work now?

If mutate.py just flips a random isotropic bit, you don't need either numpy or Python to do that in Golly 3.x. There's an equivalent Lua script.

KittyTac wrote:

dvgrn wrote:

KittyTac wrote:It worked! Thanks! But mutate.py still does not work. It doesn't even open.

It depends on the messy collection "KBs.py" and please place them in the same folder.

Where did you put the two Python files, and what are their names? (Just checking.)
...
If mutate.py just flips a random isotropic bit, you don't need either numpy or Python to do that in Golly 3.x. There's an equivalent Lua script.

Wait, there is?

KittyTac wrote:Yeah, I ran like 50 iterations of it and soups started exploding. Took 20 more to un-explodify it.

pip install numpy
pip install scipy
pip install IPython
pip install matplotlib