import numpy as np
import calc_prism as cp
y = 10.0
v = 10.0
ys = np.arange(0.001,10.0,0.001)
p_trap = {}
p_trap['y'] = 22.0
p_trap['g'] = 32.2
p_trap['Q'] = 12600.0
p_trap['m'] = 2.0
p_trap['b'] = 75.0
a_trap = cp.area_trap(p_trap)
print a_trap
b_trap = cp.width_trap(p_trap)
print b_trap
p_trap['v'] = 12600.0/a_trap
f_trap = cp.f_trap(p_trap)
print f_trap
u_star = (p_dict['g'] * rh * s)**0.5
ratio = u_star / u_c_star
if ratio <= 1.0:
a, b = 0.15, 1.85
elif ratio > 1.0 and ratio <= 1.5:
a, b = 0.2, 2.7
elif ratio > 1.5 and ratio <= 2.5:
a, b = 0.28, 3.08
else:
a, b = 0.29, 3.5
print a, b
n_term1 = kn / ((8.0 * p_dict['g'])**0.5)
n_term2 = ((rh / k)**(1.0 / 6.0) / (a + (b * math.log10(rh / k))))
n = n_term1 * n_term2 * k**(1.0 / 6.0)
area = cp.area_trap(p_dict)
print area
Q = (kn / n) * cp.area_trap(p_dict) * rh**(2.0 / 3.0) * s**0.5
print Q, p_dict['y'], rh, tao, k, n
#
#Y = np.arange(0.001,10.0,0.001)
#r = 1.0e+20
#correct_y1 = -999
#correct_n = -999
#correct_tao = -999
#correct_v = -999
#for y in Y:
# p_dict['y'] = y
# rh = y
# tao = gamma * y * s
# u_star = (p_dict['g'] * rh * s)**0.5
import numpy as np
import calc_prism as cp
y = 10.0
v = 10.0
ys = np.arange(0.001, 10.0, 0.001)
p_trap = {}
p_trap['y'] = 22.0
p_trap['g'] = 32.2
p_trap['Q'] = 12600.0
p_trap['m'] = 2.0
p_trap['b'] = 75.0
a_trap = cp.area_trap(p_trap)
print a_trap
b_trap = cp.width_trap(p_trap)
print b_trap
p_trap['v'] = 12600.0 / a_trap
f_trap = cp.f_trap(p_trap)
print f_trap
p_rect['b'] = 49.0
p_rect['Q'] = 12600.0
p_trap = {}
p_trap['g'] = 32.2
p_trap['m'] = 2.0
p_trap['b'] = 75.0
p_trap['Q'] = 12600.0
p_trap['y'] = 22.0
delta_z = 1.0
k_loss = 0.5
#--energy downstream
e_trap = cp.e_trap(p_trap)
print e_trap
#--energy upstream = e_dwn + delta_z + head_loss
e_trap -= delta_z
#--add parameters to p_rect for depth finding
p_rect['area2'] = cp.area_trap(p_trap)
p_rect['k_loss'] = k_loss
y = np.arange(0.001,100.0,0.001)
#y = np.array([19.88])
alt_depths = cp.find_depths(e_trap,y,p_rect,e_rect_mod)
print alt_depths
p_dict['y'] = y
rh = cp.r_trap(p_dict)
tao = gamma * y * s
u_star = (p_dict['g'] * rh * s)**0.5
ratio = u_star/u_c_star
if ratio <= 1.0:
a,b = 0.15,1.85
elif ratio > 1.0 and ratio <= 1.5:
a,b = 0.2,2.7
elif ratio > 1.5 and ratio <=2.5:
a,b = 0.28,3.08
else:
a,b = 0.29,3.5
k = avg_hgt * 0.14 * (((mei/tao)**0.25)/avg_hgt)**1.59
n_term1 = kn /((8.0*p_dict['g'])**0.5)
n_term2 = ((rh/k)**(1.0/6.0)/(a + (b * math.log10(rh/k))))
n = n_term1 * n_term2 * k**(1.0/6.0)
#print n
rhs = (n * p_dict['Q']) / (kn * (s**0.5))
lhs = (cp.area_trap(p_dict)**(5.0/3.0)) / (cp.p_trap(p_dict)**(2.0/3.0))
this_r = abs(lhs-rhs)
if this_r < r:
r = this_r
correct_y1 = y
correct_n = n
correct_tao = tao
print 'y',correct_y1
print 'n',correct_n
tao_bot_max = gamma * correct_y1 * s
print 'tao_perm,tao_max',tao_perm,correct_tao
p_dict['m'] = 1.0 / (3.0)**0.5
p_dict['Q'] = 1500.0
#nm_2_lbft = 47.9
n = 0.015
kn = 1.49
s = 0.0005
Y = np.arange(0.001, 20.0, 0.001)
r = 1.0e+20
correct_y1 = -999
correct_n = -999
correct_b = -999
for y in Y:
p_dict['y'] = y
p_dict['b'] = (2.0 / 3.0) * y * (3.0)**0.5
rh = cp.r_trap(p_dict)
rhs = (n * p_dict['Q']) / (kn * (s**0.5))
lhs = (cp.area_trap(p_dict)**(5.0 / 3.0)) / (cp.p_trap(p_dict)
**(2.0 / 3.0))
this_r = abs(lhs - rhs)
if this_r < r:
r = this_r
correct_y1 = y
correct_n = n
correct_b = p_dict['b']
print 'y', correct_y1
p_dict['y'] = correct_y1
print 'f', cp.f_trap(p_dict)
print 'n', correct_n
print 'b', correct_b
p_rect = {}
p_rect['g'] = 32.2
p_rect['b'] = 49.0
p_rect['Q'] = 12600.0
p_trap = {}
p_trap['g'] = 32.2
p_trap['m'] = 2.0
p_trap['b'] = 75.0
p_trap['Q'] = 12600.0
p_trap['y'] = 22.0
delta_z = 1.0
k_loss = 0.5
#--energy downstream
e_trap = cp.e_trap(p_trap)
print e_trap
#--energy upstream = e_dwn + delta_z + head_loss
e_trap -= delta_z
#--add parameters to p_rect for depth finding
p_rect['area2'] = cp.area_trap(p_trap)
p_rect['k_loss'] = k_loss
y = np.arange(0.001, 100.0, 0.001)
#y = np.array([19.88])
alt_depths = cp.find_depths(e_trap, y, p_rect, e_rect_mod)
print alt_depths
u_star = (p_dict['g'] * rh * s)**0.5
ratio = u_star/u_c_star
if ratio <= 1.0:
a,b = 0.15,1.85
elif ratio > 1.0 and ratio <= 1.5:
a,b = 0.2,2.7
elif ratio > 1.5 and ratio <=2.5:
a,b = 0.28,3.08
else:
a,b = 0.29,3.5
print a,b
n_term1 = kn /((8.0*p_dict['g'])**0.5)
n_term2 = ((rh/k)**(1.0/6.0)/(a + (b * math.log10(rh/k))))
n = n_term1 * n_term2 * k**(1.0/6.0)
area = cp.area_trap(p_dict)
print area
Q = (kn/n) * cp.area_trap(p_dict) * rh**(2.0/3.0) * s**0.5
print Q,p_dict['y'],rh,tao,k,n
#
#Y = np.arange(0.001,10.0,0.001)
#r = 1.0e+20
#correct_y1 = -999
#correct_n = -999
#correct_tao = -999
#correct_v = -999
#for y in Y:
# p_dict['y'] = y
# rh = y
# tao = gamma * y * s
# u_star = (p_dict['g'] * rh * s)**0.5
