ENH: Enhanced the problem set building on the image handing and arrays.
Illustrated dtypes, casting and their importance along with an example
using RGBA images. Also introduce edge detection.
import math
def linspace(a, b, N):
lns = []
step = (float(b) - float(a)) / float(N - 1)
print step
for i in range(N):
lns.append(a + i*step)
return lns
def sinsin_func():
x = linspace(0, 5, 11)
sin_list = []
for i in x:
sin_list.append(math.sin(i) + math.sin(10*i))
return sin_list
def find_root_range():
sin_list = sinsin_func()
for i, sins in enumerate(sin_list):
if (sin_list[i] > 0 and sin_list[i+1] < 0) or (sin_list[i] > 0 and sin_list[i+1] < 0):
print "Roots lie between: %f and %f" % (sin_list[i], sin_list[i+1])
if sin_list[i] == 0:
print "%f is the root" % sin_list[i]
find_root_range()