int_main_list = [int(N) for N in main_list] int_main_list_2 = [int(N) for N in main_string_2[2:]] #print(intlist_main_string) avg = sum(int_main_list) / ( len(int_main_list) -1) print(avg) avgg = sum(int_main_list_2) / ( len(int_main_list_2) -1) print(avgg) ##CODE #1: the quickest/ Python-est: values_0 = [N for N in range(10)] distr_values_0 = [ sbm( str(N) , main_string_2[2:]).counter() for N in values_0 ] num = 0 for L in range(len(values_0)): num += values_0[L] * distr_values_0[L] avgg = float(num)/ float(sum(distr_values_0)) print(avgg) #exit() ## CODE #2: The longest/ C++-est: s = time.time()
for n in range( len_filenames ): with open(filenames[n]) as f: lines[n] = f.readlines() pi_str[n] = strconvert(lines[n])[0:1] + strconvert(lines[n])[2:-1] # NOTE: below n = 0, 1, 2 indexes the three lengths of Pi being considered, and # x = 0, 1, 2, ..., 9 are the input values to be plotted against. E.g. x vs. F_n(x). domain = range(0,10) #Defines an array of Class Instantiations: CL[n][x] CL = [ [] ] * len_filenames for n in range(len_filenames): CL[n] = [ sbm(x, pi_str[n] ) for x in domain ] #Defines an array of Methodized classes: freq[n][x] freq = [ [] ] * len_filenames for n in range(len_filenames): freq[n] = [ element.jcount() for element in CL[n] ] #freq[n] = [ CL[n][x].jcount() for x in domain ] norm_freq = [ [] ] * len_filenames for n in range(len_filenames): norm_freq[n] = [ 100*element/sum(freq[n]) for element in freq[n] ] # From their uses inside the for loops AT a given n: CL[n], freq[n] and norm_freq[n]
snippet_str[n] = strconvert(lines[n])[0:-1]
# NOTE: below n = 0, 1 indexes the two lengths of Pi being considered, and
# x = 0, 1, 2, ..., 9 are the input values to be plotted against. E.g. x vs. F_n(x).
domain = range(0, 10)
# Defines an array of Class Instantiations, CL[n][x],
# as made clear in the body of the for loop
CL = [[]] * len_filenames # = [ [], [] ] since len_filenames == 2.
# This list has two elements, Cl[0] = CL[1] = [],
# each of which are empty LISTS, but will soon take form.
for n in range(len_filenames):
CL[n] = [sbm(x, str_lines[n]) for x in domain]
#Defines an array of Methodized classes: freq[n][x]
freq = [[]] * len_filenames
for n in range(len_filenames):
freq[n] = [element.jcount() for element in CL[n]]
norm_freq = [[]] * len_filenames
for n in range(len_filenames):
norm_freq[n] = [100 * element / sum(freq[n]) for element in freq[n]]
hist = pygal.Bar(style=custom_0, legend_at_bottom=True)
hist1 = pygal.Line()
#hist = pygal.Bar(Style = blue)
lines = [] for item in filenames: with open(item) as f: lines_item = f.readlines() lines.append(lines_item ) str_lines = [] for item in lines: str_lines_item = strconvert(item)[0:1] + strconvert(item)[2:-1] str_lines.append(str_lines_item) CL = [] for item in str_lines: CL_item = [ sbm(x, item ) for x in domain ] CL.append(CL_item) freq = [] for CL_n in CL: freq_n = [ element.jcount() for element in CL_n ] freq.append(freq_n) norm_freq = [ ] for freq_n in freq: norm_freq_n = [ 100*element/sum(freq_n) for element in freq_n ] norm_freq.append(norm_freq_n)
len_filenames = len(filenames) lines = [''] * len_filenames pi_str = [''] * len_filenames for n in range( len_filenames ): with open(filenames[n]) as f: lines[n] = f.readlines() pi_str[n] = strconvert(lines[n])[0:1] + strconvert(lines[n])[2:-1] R = range(0,10) # D = [0,1,2,..,9] V_0 = [ sbm(r, pi_str[0] ) for r in R ] V_1 = [ sbm(r, pi_str[1] ) for r in R ] #V_2 = [ sbm(r, pi_str[2] ) for r in R ] freq_0 = [ element.jcount() for element in V_0 ] freq_1 = [ element.jcount() for element in V_1 ] #freq_2 = [ element.jcount() for element in V_2 ] norm_freq_0 = [100*element/sum(freq_0) for element in freq_0] norm_freq_1 = [100*element/sum(freq_1) for element in freq_1] #norm_freq_2 = [100*element/sum(freq_2) for element in freq_2]
from jonmodule import Sub_in_main as sbm
import time
filename = 'pi_1000000.txt'
with open(filename) as f:
lines = f.readlines()
main_string = ''.join(line.strip() for line in lines)
#main_string = main_string[2:]
sub_string = '121391'
#sub_string = '151087'
#sub_string = '052380'
#sub_string = '6666'
v = sbm(sub_string, main_string)
start = time.time()
print(v.location())
v.counter()
end = time.time()
delta_t_1 = (end - start)
start = time.time()
v.locationn()
v.counterr()
end = time.time()
delta_t_2 = (end - start)