import numpy as np
def calc_period_entire(matt):
if matt.shape[0]==0:
return -1
for divi in divisors(matt.shape[0])[:-1]:
this_one = True
for i in range(1,matt.shape[0]/divi):
if not np.all(matt[0:divi]==matt[i*divi:(i+1)*divi]):
this_one = False
break
if this_one:
return divi
return -1
def calc_period(matt):
periodicities = []
for i in range(1,matt.shape[0]/2):
still_checking = True
check_dist = 1
while still_checking:
if matt.shape[0]-1-i-i*check_dist<0:
return i
still_checking = False
periodicities.append([i,check_dist])
else:
if np.all(matt[matt.shape[0]-1-i:matt.shape[0]-1]==matt[matt.shape[0]-1-i-i*check_dist:matt.shape[0]-1-i*check_dist]):
check_dist += 1
else:
if i*check_dist>matt.shape[0]/2:
return i
still_checking = False
periodicities.append([i,check_dist])
return -1
print(periodicities)
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def generate_sum_free(initial,pattern,length):
decision = format(initial,"b")[1:]
repetition = format(pattern,"b")[1:]
if "1" in repetition:
num = 1
i = 0
list_g = []
unavailable = []
difference_counts = np.zeros((length))
while num < length:
if num not in unavailable:
include = False
if len(decision)<=i:
if repetition[(i+len(repetition)*10-len(decision))%len(repetition)]=='1':
include = True
else:
if decision[i%len(decision)]=='1':
include = True
if include:
list_g.append(num)
for j in list_g:
difference_counts[num-j] += 1
unavailable.append(j+num)
i+=1
num += 1
matt = np.zeros((length))
for a in range(length):
if a in list_g:
matt[a] = 1
return matt,difference_counts
else:
return np.zeros((length)),np.zeros((length))
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period = [20,10]
periods_a = []
periods_b = []
difference_count_list = np.zeros((1000,period[0]*period[1]))
aperiodic_i = []
for i in range(10):
#print(format(i,"b")[1:]+" "+str(calc_period_entire( np.array([int(a) for a in format(i,"b")[1:]]) )))
if calc_period_entire( np.array([int(a) for a in format(i,"b")[1:]]) ) == -1:
sum_free,difference_count_list[i,:] = generate_sum_free(0,i,period[0]*period[1])
print(format(i,"b")[1:]+" "+str(calc_period(sum_free)))
periods_a.append([i,calc_period(sum_free)])
if periods_a[len(periods_a)-1][1] == -1:
aperiodic_i.append(i)
periods_b.append([i,calc_period_entire(sum_free)])
A = scatter_plot(periods_a, strokecolor='red', facecolor='red')
B = scatter_plot(periods_b, strokecolor='blue', facecolor='blue')
show(A)
1
1
0 1
1 2
01 3
10 3
001 4
verbose 0 (163: primitive.py, options) WARNING: Ignoring option
'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points
are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation
of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
verbose 0 (163: primitive.py, options) WARNING: Ignoring option
'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points
are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation
of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
verbose 0 (163: primitive.py, options) WARNING: Ignoring option
'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points
are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation
of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
1
1
0 1
1 2
01 3
10 3
001 4
verbose 0 (163: primitive.py, options) WARNING: Ignoring option 'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
verbose 0 (163: primitive.py, options) WARNING: Ignoring option 'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
verbose 0 (163: primitive.py, options) WARNING: Ignoring option 'strokecolor'=red
verbose 0 (163: primitive.py, options)
The allowed options for Scatter plot graphics primitive on 7 data points are:
alpha How transparent the marker border is.
clip Whether or not to clip.
edgecolor The color of the marker border.
facecolor The color of the marker face.
hue The color given as a hue.
marker What shape to plot the points. See the documentation of plot() for the full list of markers.
markersize the size of the markers.
rgbcolor The color as an RGB tuple.
zorder The layer level in which to draw.
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print(aperiodic_i)
[] [] |
import colorsys
color_i = 0
A = list_plot([], color='black')
pattern_i = 107
sum_free,difference_count = generate_sum_free(0,pattern_i,4000)
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lumpy = 4
A = list_plot([], color='black')
color_i = 0
for eee in range(lumpy):
rgb = colorsys.hsv_to_rgb(1/lumpy*eee, 1, 0.8)
color_i += 1
plotty = [[i,difference_count[i]*(1.0/(1.0-float(i)/difference_count.shape[0]))] for i in range(eee,difference_count.shape[0]/2,lumpy)]
list_plot(plotty, color=rgb)
A = A+list_plot(plotty, color=rgb)
   
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show(A)
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format(107,"b")[1:]
'101011' '101011' |
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