def myfunc(x,y):
if (x>0.5*y and y<0.3):
return (sn(x-y))
elif (x<0.5*y):
return 0
elif (x>0.2*y):
return (2*sn(x+2*y))
else:
return (sn(y+x))
def myfunc(x, y):
if (x > 0.5 * y and y < 0.3):
return (sn(x - y))
elif (x < 0.5 * y):
return 0
elif (x > 0.2 * y):
return (2 * sn(x + 2 * y))
else:
return (
sn(y + x)
) # List of stored elements, generated from a Normal distribution
def targetting(self, event=0):
if event:
self.angle = math.atan((event.y - 450) / (event.x - 20))
if self.f2_on:
canv.itemconfig(self.id, fill='skyblue')
else:
canv.itemconfig(self.id, fill='grey')
canv.coords(self.id, 20, 450,
20 + max(self.f2_power, 20) * math.cos(self.angle),
450 + max(self.f2_power, 20) * math.sn(self.angle))
return 0
elif (x>0.2*y):
return (2*sn(x+2*y))
else:
return (sn(y+x))
lst_x = np.random.randn(N_point)
lst_y = np.random.randn(N_point)
lst_result = []
tic=time.time()
for i in range(len(lst_x)):
x = lst_x[i]
y = lst_y[i]
if (x>0.5*y and y<0.3):
lst_result.append(sn(x-y))
elif (x<0.5*y):
lst_result.append(0)
elif (x>0.2*y):
lst_result.append(2*sn(x+2*y))
else:
lst_result.append(sn(y+x))
toc=time.time()
print("\nTime taken by the plain vanilla for-loop\n----------------------------------------------\n{} us".format(1000000*(toc-tic)))
# List comprehension
print("\nTime taken by list comprehension and zip\n"+'-'*40)
%timeit lst_result = [myfunc(x,y) for x,y in zip(lst_x,lst_y)]
# Map() function
def sin(k, x):
return float(((-1) ** (k - 1)) * (x ** (2 * k - 1))) / float(factorial(2 * k - 1))
sin_approx = []
Number = []
Exponent = []
sin_error = []
sin_first_neglected_term = []
for x in [pi, 30 * pi]:
for N in [5, 10, 20]:
Tsin = Sum(f=sin, M=1, N=N)
Exponent.append(N)
Number.append(x)
sin_approx.append(Tsin(x))
sin_error.append(sn(x) - Tsin(x))
sin_first_neglected_term.append(Tsin.first_neglected_term)
print "Results for Taylor Expansion of sin(x):\n%10s %10s %40s %40s %40s" % (
"x",
"N",
"Value",
"Error",
"First Neglected Term",
)
for i in range(len(Number)):
print "%10.5f %10.0f %40.4f %40.5f %40.5f" % (
Number[i],
Exponent[i],
sin_approx[i],
sin_error[i],