def graph_pts(table, percent=True, axes=True, zeroes=True, exact=False):
'''returns graph pts for a table.
axes=True returns (x_axis, y_axis). axes=False returns [(x,y), (x,y)...]
zeroes includes zero freq values from the min_val to max_val of the table
percent=True converts y values into percent of total y values.
exact=True/False only works with pct. exact=False only good to ten decimal
places, but much much faster.
percent=False leaves as raw long ints, which will often be too large for
graphing functions to handle. for that case, graph_pts_overflow(table) is
reccommended.'''
if not table.values():
raise ValueError('empty table')
if zeroes:
the_pts = table.frequency_range(table.values_min(),
table.values_max() + 1)
else:
the_pts = table.frequency_all()
if percent:
temp = []
total_freq = table.total_frequency()
if exact:
for value, freq in the_pts:
temp.append((value, li_div(100 * freq, total_freq)))
else:
factor = 10**50
for value, freq in the_pts:
y_val = (freq * factor) // total_freq
temp.append((value, (y_val*100.)/factor))
the_pts = temp[:]
if axes:
return [tuple([pair[0] for pair in the_pts]),
tuple([pair[1] for pair in the_pts])]
else:
return the_pts
def stats(table, values):
'''table is a LongIntTable. values is a list. returns tuple of strings
(string of input values, combinations from input values, total combos,
1 in how many chance, percent chance)'''
total_freq = table.total_frequency()
lst_freq = 0
no_copies = set(values)
for value in no_copies:
lst_freq += table.frequency(value)[1]
if lst_freq == 0:
chance = 'infinity'
pct = scinote(0)
else:
chance = scinote(li_div(total_freq, lst_freq))
pct = scinote(100 * li_div(lst_freq, total_freq))
return (list_to_string(values),
scinote(lst_freq),
scinote(total_freq),
chance,
pct)
def ascii_graph_helper(table):
'''table is a LongIntTable. makes a list of tuples which
[(value, x's representing value), ...]'''
output_list = []
max_frequency = table.frequency_highest()[1]
max_graph_height = 80
divisor = 1
add_s = ''
if max_frequency > max_graph_height:
divisor = li_div(max_frequency, max_graph_height)
add_s = 's'
val_len = len(str(table.values_max()))
for value, frequency in table.frequency_all():
num_of_xs = int(round(li_div(frequency, divisor)))
output_list.append((value,
'{0:>{1}}:{2}'.format(value, val_len, num_of_xs*'x')
))
output_list.append((None,
'each x represents {} occurence{}'.format(
scinote(divisor), add_s
)
))
return output_list
