Example #1
0
 def clr_grad(color):
     if color.startswith('rgba('):
         r, g, b, a = rgba(color)
         return  '%d' % int(a*100000)
     elif 'opacity' in keys:
         return '%d' % int(float(e.get('opacity')) * 100000)
     else:
         return '%d' % 100000
Example #2
0
 def clr_grad(color):
     if color.startswith('rgba('):
         r, g, b, a = rgba(color)
         return '%d' % int(a * 100000)
     elif 'opacity' in keys:
         return '%d' % int(float(e.get('opacity')) * 100000)
     else:
         return '%d' % 100000
Example #3
0
def msclr(color):
    r, g, b, a = rgba(color)
    return '%02x%02x%02x' % (255*r, 255*g, 255*b)
Example #4
0
def msclr(color):
    r, g, b, a = rgba(color)
    return '%02x%02x%02x' % (255 * r, 255 * g, 255 * b)
reader = csv.DictReader(open('daily-rainfall-data.csv'), delimiter='\t')
fields = reader.fieldnames[3:]
W = len(fields)

HI = 5.7    # 99% = 49.1, 95% = 14.3, 90% = 5.7, 80% = 0.6
STARTYEAR = 1971
ENDYEAR = 2005
YEARS = ENDYEAR - STARTYEAR + 1     # Number of years
ROWS = 65                           # Number of latitude grids each day

im = Image.new('RGBA', (W * 366, YEARS * ROWS))
for key, rows in itertools.groupby(reader, lambda v: (v['Year'], v['Day'])):
    print key
    rows = list(rows)
    X0 = W * (int(key[1]) - 1)
    Y0 = ROWS * (int(key[0]) - STARTYEAR)
    for y, row in enumerate(rows):
        for x, field in enumerate(fields):
            try:
                cell = float(row[field])
            except:
                cell = -999
            if cell < 0:
                color = (0, 0, 0, 0)
            else:
                color = tuple(int(255 * v) for v in _color.rgba(
                    _color.gradient(cell / HI, _color.Greens)))
            im.putpixel((x + X0, y + Y0), color)

im.save('rainfall.png')