PythonCode/loops.py at master · PaulSpence/PythonCode · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
import numpy as np
import glob
import test
from matplotlib import pyplot

fdata='/Users/johnspence/Documents/CarpentryBootcamp/teaching/swc-python/novice/'

fname=fdata+'inflammation-01.csv'

data=np.loadtxt(fname, delimiter=',')


#for loops
def print_characters(element):
    for char in element:
        print char

print_characters(fdata)


def rescale(a):
    result=(a[:]-a.max())/(a.max()-a.min())
    return result

a=np.random.rand(3,2)

#range creates a list not an array
a=range(0,100,5)

#np creates arrays
a=np.arange(0,100,5)

b=rescale(a)


odds=[1,3,4,5]
type(odds)
odds[-1]

#show attributes
dir(odds)

def sign(num):
    if num > 0:
        return 1
    elif num == 0:
        return 0
    else:
        return -1

print 'sign of -3:', sign(-3)

if (1 > 0) and (-1 > 0):
    print 'both parts are true'
else:
    print 'one part is not true'

if (1 < 0) or ('left' < 'right'):
    print 'at least one test is true'

def near(first,second):
    value=(first*1.0)/(second*1.0)
    if (value >= .9) and (value <= 1.1):
        return 'TRUE'
    else:
        return 'FALSE'

data=np.loadtxt(fname, delimiter=',')
width, height = data.shape
heatmap=data

for x in range(width):
    for y in range(height):
        if data[x,y] < data.mean():
            heatmap[x,y] = -1
        elif data[x,y] == data.mean():
            heatmap[x,y] = 0
        else:
            heatmap[x,y] = 1

pyplot.imshow(heatmap)
pyplot.show()

numbers = [1.5, 2.3, 0.7, 0.001, 4.4]
total = 0.0

for n in numbers:
    assert n>=0.0, 'Data should only contain +ve values'
    total += n

print 'total is:', total

def normalize_rectangle(rect):
    assert len(rect) == 4, 'Rectangles must contain 4 coordinates'
    x0, y0, x1, y1 = rect
    assert x0 < x1, 'Invalid X coordinates'
    assert y0 < y1, 'Invalid Y coordinates'

    dx = x1 - x0
    dy = y1 - y0
    if dx > dy:
        scaled = float(dy) / dx
        upper_x, upper_y = 1.0, scaled
    else:
        scaled = float(dx) / dy
        upper_x, upper_y = scaled, 1.0

    assert 0 < upper_x <= 1.0, 'Calculated upper X coordinate invalid'
    assert 0 < upper_y <= 1.0, 'Calculated upper Y coordinate invalid'

    return (0, 0, upper_x, upper_y)


#print normalize_rectangle( (4.0, 2.0, 1.0, 5.0) )
print normalize_rectangle( (0.0, 0.0, 1.0, 5.0) )

def average(array):
    assert array.size>0, 'At least 1 value required'
    #return array.mean()
    sum=0.0
    for n in array:
        print 'n index: ',  n
        sum+=n
    if sum > 0:
        return sum/array.size
    else:
        return 0

#for loops work as lists - cycles thru number of elements in list

fglob=fdata+'*.csv'
print glob.glob(fglob)
filenames=glob.glob(fglob)
filenames=filenames[0:3]

filenames = filenames[0:3]
for f in filenames:
    print f
    test.analyze(f)