def rotate_by_pivot(p, pivot, angle):
result = [None] * 2
result[0] = (p[0] - pivot[0]) * np.cos(angle) + (
p[1] - pivot[1]) * np.sin(angle) + pivot[0]
result[1] = (p[0] - pivot[0]) * -np.sin(angle) + (
p[1] - pivot[1]) * np.cos(angle) + pivot[1]
return result
def ltfree(lK, Rg, alpha, beta, delta, omegat):
ltx = np.cos(alpha) * np.cos(np.radians(omegat) + delta) + np.cos(
beta) * lK - np.cos(np.radians(omegat)) * Rg
lty = np.sin(np.radians(omegat) + delta) - np.sin(np.radians(omegat)) * Rg
ltz = -np.sin(alpha) * np.cos(np.radians(omegat) +
delta) + np.sin(beta) * lK
return np.sqrt(ltx * ltx + lty * lty + ltz * ltz)
def ek(alpha, betas):
ca = np.cos(alpha)
sa = np.sin(alpha)
cbs = np.cos(betas)
sbs = np.sin(betas)
return np.array([[ca * cbs, -sbs, sa * cbs], [ca * sbs, cbs, sa * sbs],
[-sa, 0, ca]])
def Mgrz(lK, Rg, alpha, betas, beta, delta, omegat, ot):
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cbs = np.cos(betas)
sbs = np.sin(betas)
cot = np.cos(np.radians(omegat) + ot)
sot = np.sin(np.radians(omegat) + ot)
cotd = np.cos(np.radians(omegat) + ot + delta)
sotd = np.sin(np.radians(omegat) + ot + delta)
#
ekxx = ca * cbs
ekxy = ca * sbs
ekxz = -sa
#
ekyx = -sbs
ekyy = cbs
ekyz = 0
#
ekzx = sa * cbs
ekzy = sa * sbs
ekzz = ca
#
eaxx = ekxx * cotd + ekyx * sotd
eaxy = ekxy * cotd + ekyy * sotd
eaxz = ekxz * cotd
#
ltx = eaxx + cb * lK - cot * Rg
lty = eaxy - sot * Rg
ltz = eaxz + sb * lK
#
vcz = cot * lty - sot * ltx
#
return vcz / (ltx * ekzx + lty * ekzy + ltz * ekzz)
def Ftry(lK, Rg, alpha, betas, beta, delta, omegat, ot):
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cbs = np.cos(betas)
sbs = np.sin(betas)
cot = np.cos(np.radians(omegat) + ot)
sot = np.sin(np.radians(omegat) + ot)
cotd = np.cos(np.radians(omegat) + ot + delta)
sotd = np.sin(np.radians(omegat) + ot + delta)
#
ekxx = ca * cbs
ekxy = ca * sbs
ekxz = -sa
#
ekyx = -sbs
ekyy = cbs
ekyz = 0
#
ekzx = sa * cbs
ekzy = sa * sbs
ekzz = ca
#
ltx = ekxx * cotd + ekyx * sotd + cb * lK - cot * Rg
lty = ekxy * cotd + ekyy * sotd - sot * Rg
ltz = ekxz * cotd + sb * lK
#
return (ltx * ekyx + lty * ekyy + ltz * ekyz) / (ltx * ekzx + lty * ekzy +
ltz * ekzz)
def rotate_arrow_and_text(BarNo):
alpha = p*(BarNo-1)*alpha_c / 180 * np.pi
x = x_ori* np.cos(alpha) + y_ori*-np.sin(alpha)
y = x_ori* np.sin(alpha) + y_ori* np.cos(alpha)
pu.pyx_arrow((x,y))
pu.pyx_text(( np.sign(x)*(abs(x)-1),
np.sign(y)*(abs(y)-1)
), rf'${BarNo}$', scale=1.5)
print(f'alpha={alpha/np.pi*180}')
def rA(lK, R, alpha, betas, beta, delta, omegat):
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cbs = np.cos(betas)
sbs = np.sin(betas)
cotd = np.cos(np.radians(omegat) + delta)
sotd = np.sin(np.radians(omegat) + delta)
rAx = (ca * cbs * cotd - sbs * sotd) * R + cb * lK
rAy = (ca * sbs * cotd + cbs * sotd) * R
rAz = (-sa * cotd) * R + sb * lK
return np.array([rAx, rAy, rAz])
def rB(R, omegat):
cot = np.cos(np.radians(omegat))
sot = np.sin(np.radians(omegat))
rBx = cot * R
rBy = sot * R
rBz = 0
return np.array([rBx, rBy, rBz])
def derive_mm_w_pm(GP, SD):
GP["mm_w_pm"].value = (
GP['mm_r_os'].value - GP["mm_d_bg_air"].value -
(GP['mm_r_ri'].value + GP['mm_d_ri'].value)) / np.cos(
GP['deg_alpha_vspm'].value) - GP['mm_d_pm'].value * np.tan(
GP['deg_alpha_vspm'].value)
return GP["mm_w_pm"].value
def rK(lK, beta):
cb = np.cos(beta)
sb = np.sin(beta)
rKx = cb * lK
rKy = 0
rKz = sb * lK
return np.array([rKx, rKy, rKz])
def cosgammag(lK, Rg, beta, delta, omegat):
alpha = 0.5*np.pi-beta
cb = np.cos(beta)
sb = np.sin(beta)
cot = np.cos(np.radians(omegat))
sot = np.sin(np.radians(omegat))
cotd = np.cos(np.radians(omegat)+delta)
sotd = np.sin(np.radians(omegat)+delta)
ltx = np.cos(alpha)*cotd + cb*lK - cot*Rg
lty = sotd - sot*Rg
ltz = -np.sin(alpha)*cotd + sb*lK
Rwx = cot*Rg
Rwy = sot*Rg
Rwz = 0
lt = np.sqrt(ltx*ltx+lty*lty+ltz*ltz)
return (Rwx*lty-Rwy*ltx)/(lt*Rg)
def cosgammak(lK, Rg, beta, delta, omegat):
alpha = 0.5*np.pi-beta
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cot = np.cos(np.radians(omegat))
sot = np.sin(np.radians(omegat))
cotd = np.cos(np.radians(omegat)+delta)
sotd = np.sin(np.radians(omegat)+delta)
Rax = ca*cotd
Ray = sotd
Raz = -sa*cotd
ltx = Rax + cb*lK - cot*Rg
lty = Ray - sot*Rg
ltz = Raz + sb*lK
lt = np.sqrt(ltx*ltx+lty*lty+ltz*ltz)
return (sa*(Ray*ltz-Raz*lty) + ca*(Rax*lty-Ray*ltx))/lt
def vt(lK, Rg, beta, delta, omegat):
alpha = 0.5*np.pi-beta
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cot = np.cos(np.radians(omegat))
sot = np.sin(np.radians(omegat))
cotd = np.cos(np.radians(omegat)+delta)
sotd = np.sin(np.radians(omegat)+delta)
ltx = ca*cotd + cb*lK - cot*Rg
lty = sotd - sot*Rg
ltz = -sa*cotd + sb*lK
lt = np.sqrt(ltx*ltx+lty*lty+ltz*ltz)
dltxdt = -ca*sotd + sot*Rg
dltydt = cotd - cot*Rg
dltzdt = sa*sotd
return (ltx*dltxdt+lty*dltydt+ltz*dltzdt)/lt
def wall(xvals, parms):
#position=p[0]; intensity=p[1]; slit=p[2]; stth=p[3]; background=p[4]; thickness=p[5]; absorption=p[6]
midpoint = parms[0]
i0 = parms[1]
w = parms[2]
theta = parms[3]
ib = parms[4]
thick = parms[5]
u = parms[6]
midpoint = parms[0]
x0 = midpoint - thick / 2.0
th = np.deg2rad(theta)
p = w * np.cos(th)
Atot = w * w / np.sin(2.0 * th)
out = []
for x in xvals:
if (x <= (x0 - p)):
val = ib
#elif ((x0-p) >= (x-thick)) and ((x0+p) >= x): #Gauge volume is smaller than thickness
if ((x > (x0 - p)) and (x0 - p > (x - thick)) and (x <= x0)):
val = ib + i0 * ((x - (x0 - p)) * ((x -
(x0 - p)) * np.tan(th))) / Atot
elif ((x > x0) and (x <= x0 + p) and (x0 - p > (x - thick))):
val = ib + i0 * (Atot - (x0 + p - x) *
(x0 + p - x) * np.tan(th)) / Atot
elif (x0 - p > (x - thick)
and (x0 + p < x)): #Gauge volume is smaller than thickness
val = ib + i0
elif (x0 - p < (x - thick)
and (x0 + p > x)): #Gauge volume is larger than thickness
A2 = (x0 + p - x) * (x0 + p - x) * np.tan(th)
A3 = ((x - thick) - (x0 - p)) * (((x - thick) -
(x0 - p)) * np.tan(th))
val = ib + i0 * (Atot - A2 - A3) / Atot
elif ((x0 - p) < (x - thick)) and ((x0 + p) < x) and (x0 >=
(x - thick)):
A3 = ((x - thick) - (x0 - p)) * (((x - thick) -
(x0 - p)) * np.tan(th))
val = ib + i0 * (Atot - A3) / Atot
elif (x0 < (x - thick) and ((x0 + p >= (x - thick)))):
A2 = (x0 + p - (x - thick)) * ((x0 + p) - (x - thick)) * np.tan(th)
val = ib + i0 * (A2 / Atot)
elif (x0 + p < (x - thick)):
val = ib
#elif ((x0-p) < (x-thick)) and ((x0+p) >= x): #Gauge volume is larger than thickness
# A2 = (x0+p-x)*(x0+p-x)*np.tan(th)
# A3 = ((x-thick)-(x0-p))*(((x-thick)-(x0-p))*np.tan(th))
# val = ib + i0*(Atot-A2-A3)/Atot
out = out + [val]
return np.array(out)
def arc(r0, R, e, n, phi0, phi):
e1 = e / np.sqrt(np.sum(e * e)) # normalize
en = n / np.sqrt(np.sum(n * n)) # normalize
ip = np.argmax(phi > phi0) # find end index
e2 = np.cross(en, e1)
cp = np.cos(np.radians(phi[:ip]))
sp = np.sin(np.radians(phi[:ip]))
# r = cp*e1+sp*e2
r = np.zeros((3, ip))
r[0, :] = r0[0] + R * (cp * e1[0] + sp * e2[0])
r[1, :] = r0[1] + R * (cp * e1[1] + sp * e2[1])
r[2, :] = r0[2] + R * (cp * e1[2] + sp * e2[2])
return r
def Marz(lK, Rg, alpha, betas, beta, delta, omegat, ot):
cb = np.cos(beta)
sb = np.sin(beta)
ca = np.cos(alpha)
sa = np.sin(alpha)
cbs = np.cos(betas)
sbs = np.sin(betas)
cot = np.cos(np.radians(omegat) + ot)
sot = np.sin(np.radians(omegat) + ot)
cotd = np.cos(np.radians(omegat) + ot + delta)
sotd = np.sin(np.radians(omegat) + ot + delta)
#
ekxx = ca * cbs
ekxy = ca * sbs
ekxz = -sa
#
ekyx = -sbs
ekyy = cbs
ekyz = 0
#
ekzx = sa * cbs
ekzy = sa * sbs
ekzz = ca
#
eaxx = ekxx * cotd + ekyx * sotd
eaxy = ekxy * cotd + ekyy * sotd
eaxz = ekxz * cotd
#
ltx = eaxx + cb * lK - cot * Rg
lty = eaxy - sot * Rg
ltz = eaxz + sb * lK
#
vcx = eaxy * ltz - eaxz * lty
vcy = eaxz * ltx - eaxx * ltz
vcz = eaxx * lty - eaxy * ltx
#
d = ltx * ekzx + lty * ekzy + ltz * ekzz
#
return np.where(d > dmin, (vcx * ekzx + vcy * ekzy + vcz * ekzz) / d, 0.0)
def transformCoords(self, points, deg_addTheta=0):
# This function takes in an nx2 array of coordinates of the form
# [x,y] and returns rotated and translated coordinates. The
# translation and rotation are described by obj.anchor_xy and
# obj.theta. The optional "addTheta" argument adds an
# additional angle of "addTheta" to the obj.theta attribute.
transCoords = []
for point in points:
# 旋转方向和eMach是反一下的，我是Park变换。
cosT = np.cos(self.theta + (deg_addTheta * np.pi / 180))
sinT = np.sin(self.theta + (deg_addTheta * np.pi / 180))
transCoords.append([
points[0] * cosT + points[1] * sinT,
points[0] * -sinT + points[1] * cosT
])
return np.array(transCoords)
def transmission(xvals, parms):
#position=p[0]; intensity=p[1]; slit=p[2]; stth=p[3]; background=p[4]; thickness=p[5]; absorption=p[6]
#x0=p[0]; i0=p[1]; w=p[2]; theta=p[3]; ib=p[4]; thick=p[5]; u=p[6];
#th = np.deg2rad(theta)
#p0 = w * np.cos(th)/np.cos(2*th)
#out = []
#for x in xvals:
# if x < (x0 - p0):
# val = ib
# elif ((x>=x0-p0) and (x < x0)):
# val = i0*(x-x0+p0)*(x-x0+p0)+ib
# elif ((x>=x0) and (x<(x0+p0))):
# val = i0*(2.0*p0*p0-(x0+p0-x)*(x0+p0-x))+ib
# elif (x>=x0+p0):
# val=2*i0*p0*p0 +ib
# out = out + [val]
x0 = parms[0]
i0 = parms[1]
w = parms[2]
theta = parms[3]
ib = parms[4]
thick = parms[5]
u = parms[6]
th = np.deg2rad(theta)
p = w * np.cos(th)
Atot = w * w / np.sin(2.0 * th)
out = []
for x in xvals:
if (x <= (x0 - p)):
val = ib
elif ((x > (x0 - p)) and (x <= x0)):
val = ib + i0 * ((x - (x0 - p)) * ((x -
(x0 - p)) * np.tan(th))) / Atot
elif ((x > x0) and (x <= x0 + p)):
val = ib + i0 * (Atot - (x0 + p - x) *
(x0 + p - x) * np.tan(th)) / Atot
elif (x > x0 + p):
val = ib + i0
out = out + [val]
return np.array(out)
def gammak2(lK, Rg, beta, delta, omegat):
alpha = 0.5 * np.pi - beta
cb = np.cos(beta)
sb = np.sin(beta)
cot = np.cos(np.radians(omegat))
sot = np.sin(np.radians(omegat))
cotd = np.cos(np.radians(omegat) + delta)
sotd = np.sin(np.radians(omegat) + delta)
cotdt = np.cos(np.radians(omegat + 90) + delta)
sotdt = np.sin(np.radians(omegat + 90) + delta)
ltx = np.cos(alpha) * cotd + cb * lK - cot * Rg
lty = sotd - sot * Rg
ltz = -np.sin(alpha) * cotd + sb * lK
eyrx = np.cos(alpha) * cotdt
eyry = sotdt
eyrz = -np.sin(alpha) * cotdt
lt = np.sqrt(ltx * ltx + lty * lty + ltz * ltz)
return np.degrees(np.arccos((eyrx * ltx + eyry * lty + eyrz * ltz) / lt))
def iPark(P, theta):
return [
P[0] * np.cos(theta) + P[1] * -np.sin(theta),
P[0] * np.sin(theta) + P[1] * np.cos(theta)
]
def ModifiedBianchi2006(self, fea_config_dict, SD, GP, OP):
air_gap_flux_density_B = SD['guess_air_gap_flux_density_B']
# air_gap_flux_density_B = 0.9
stator_tooth_flux_density_B_ds = SD[
'guess_stator_tooth_flux_density_B_ds']
# stator_tooth_flux_density_B_ds = 1.5
stator_yoke_flux_density_Bys = SD['guess_stator_yoke_flux_density_Bys']
if SD['p'] >= 2:
ROTOR_STATOR_YOKE_HEIGHT_RATIO = 0.75
alpha_rm_over_alpha_rp = 1.0
# stator_yoke_flux_density_Bys = 1.2
else:
# penalty for p=1 motor, i.e., large yoke height
ROTOR_STATOR_YOKE_HEIGHT_RATIO = 0.5
alpha_rm_over_alpha_rp = 0.75
# stator_yoke_flux_density_Bys = 1.5
stator_outer_diameter_Dse = 0.128 # m
stator_outer_radius_r_os = 0.5 * stator_outer_diameter_Dse
speed_rpm = SD['ExcitationFreqSimulated'] * 60 / SD['p'] # rpm
split_ratio = 0.5 # refer to 2020-MLMS-0953@Fig. 5
stator_inner_radius_r_is = stator_outer_radius_r_os * split_ratio
stator_inner_diameter_Dis = stator_inner_radius_r_is * 2
mm_sleeve_length = 0.5
mm_airgap_plus_sleeve_length = SD[
'minimum_mechanical_air_gap_length_mm'] + mm_sleeve_length
rotor_outer_radius_r_or = stator_inner_radius_r_is - mm_airgap_plus_sleeve_length * 1e-3 # m
rotor_outer_diameter_Dr = rotor_outer_radius_r_or * 2
# Bianchi2006@(1)--(3)
stator_yoke_height_h_ys = air_gap_flux_density_B * np.pi * stator_inner_diameter_Dis * alpha_rm_over_alpha_rp / (
2 * stator_yoke_flux_density_Bys * 2 * SD['p'])
stator_tooth_height_h_ds = (
stator_outer_diameter_Dse -
stator_inner_diameter_Dis) / 2 - stator_yoke_height_h_ys
stator_slot_height_h_ss = stator_tooth_height_h_ds
stator_tooth_width_b_ds = air_gap_flux_density_B * np.pi * stator_inner_diameter_Dis / (
stator_tooth_flux_density_B_ds * SD['Qs'])
# Bianchi2006@(4)
OP['stator_slot_area'] = stator_slot_area = np.pi / (4 * SD['Qs']) * (
(stator_outer_diameter_Dse - 2 * stator_yoke_height_h_ys)**2 -
stator_inner_diameter_Dis**
2) - stator_tooth_width_b_ds * stator_tooth_height_h_ds
# Bianchi2006@(5)
slot_pitch_pps = np.pi * (stator_inner_diameter_Dis +
stator_slot_height_h_ss) / SD['Qs']
kov = 1.8 # \in [1.6, 2.0]
OP['end_winding_length_Lew'] = end_winding_length_Lew = np.pi * 0.5 * (
slot_pitch_pps + stator_tooth_width_b_ds
) + slot_pitch_pps * kov * (SD['coil_pitch_y'] - 1)
Q = SD['Qs']
p = SD['p']
# STATOR
GP['deg_alpha_st'].value = 360 / Q - 2 # deg
GP['deg_alpha_so'].value = GP[
'deg_alpha_st'].value / 2 # im_template uses alpha_so as 0.
GP['mm_r_si'].value = 1e3 * stator_inner_radius_r_is # mm
GP['mm_r_os'].value = 1e3 * stator_outer_diameter_Dse / 2 # mm
GP['mm_d_so'].value = 1 # mm
GP['mm_d_sp'].value = 1.5 * GP['mm_d_so'].value
GP['mm_d_st'].value = 1e3 * (
0.5 * stator_outer_diameter_Dse - stator_yoke_height_h_ys
) - GP['mm_r_si'].value - GP['mm_d_sp'].value # mm
GP['mm_d_sy'].value = 1e3 * stator_yoke_height_h_ys # mm
GP['mm_w_st'].value = 1e3 * stator_tooth_width_b_ds # mm
# ROTOR
GP['mm_d_sleeve'].value = mm_sleeve_length
GP['mm_d_fixed_air_gap'].value = SD[
'minimum_mechanical_air_gap_length_mm']
GP['split_ratio'].value = split_ratio
GP['mm_d_pm'].value = 4 # mm
GP['mm_d_ri'].value = 1e3 * ROTOR_STATOR_YOKE_HEIGHT_RATIO * stator_yoke_height_h_ys # TODO：This ratio (0.75) is randomly specified
GP['mm_r_or'].value = 1e3 * rotor_outer_radius_r_or
GP['mm_r_ri'].value = 1e3 * stator_inner_radius_r_is - GP[
'mm_d_pm'].value - GP['mm_d_ri'].value - GP[
'mm_d_sleeve'].value - GP['mm_d_fixed_air_gap'].value
# Vernier specific
GP["deg_alpha_vspm"].value = 20.3
GP["mm_d_bg_air"].value = 1.5
GP["mm_d_bg_magnet"].value = 1.5
GP["mm_w_pm"].value = (
GP['mm_r_os'].value - GP["mm_d_bg_air"].value -
(GP['mm_r_ri'].value + GP['mm_d_ri'].value)) / np.cos(
GP['deg_alpha_vspm'].value) - GP['mm_d_pm'].value * np.tan(
GP['deg_alpha_vspm'].value)
def hide_annotations(self):
for ann in self.annotations:
ann.set_visible(False)
# ---------------------------------------------------------------------
t = np.linspace(0.0, 1.0, 11)
s1 = t
s2 = -t
s3 = t**2
s4 = -(t**2)
s5 = np.sin(t * 2 * np.pi)
s6 = np.cos(t * 2 * np.pi)
fig = figure()
ax1 = fig.add_subplot(321)
ax1.plot(t, s1)
ax1.scatter(t, s1)
ax2 = fig.add_subplot(322)
ax2.plot(t, s2)
ax2.scatter(t, s2)
ax3 = fig.add_subplot(323)
ax3.plot(t, s3)
ax3.scatter(t, s3)
plt.xlabel('Smarts')
plt.ylabel('Probability')
# 添加标题
plt.title('Histogram of IQ')
# 添加文字
plt.text(60, .025, r'$\mu=100,\ \sigma=15$')
plt.axis([40, 160, 0, 0.03])
plt.grid(True)
plt.show()
'==========================================='
ax = plt.subplot(111)
t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2 * np.pi * t)
line, = plt.plot(t, s, lw=2)
plt.annotate(
'local max',
xy=(2, 1),
xytext=(3, 1.5),
arrowprops=dict(facecolor='black', shrink=0.05),
)
plt.ylim(-2, 2)
plt.show()
'==========================================='
# 导入 matplotlib 的所有内容（nympy 可以用 np 这个名字来使用）
RgRk = Rg / Rk vtip = omega * Rko lam = omega * Rko / vw Ma = Pnom / omega S = np.pi * (Rko * Rko - Rk * Rk) alpha = np.radians(60) # Initial value betas = np.radians(0) # Initial value a, b, c, d = Marzmean(lKRk, RgRk, alpha, betas, beta, delta) alpha = a betas = b MaRF = c MgRF = d Fakz = Ma / (MaRF * Rk) sa = np.sin(alpha) ca = np.cos(alpha) sb = np.sin(betas) cb = np.cos(betas) L = Fakz * np.sqrt(sb * sb * sa * sa + ca * ca) D = Fakz * cb * sa LoD = L / D CL = 2 * L / (rho * S * vw * vw) CD = 2 * D / (rho * S * vw * vw) CM = 2 * Ma / (rho * Rko * S * vw * vw) Cp = lam * CM aeff = np.arccos(cb * ca) Ftrxam = Ftrxminmax(lKRk, RgRk, alpha, betas, beta, delta) Ftryam = Ftryminmax(lKRk, RgRk, alpha, betas, beta, delta) h = np.sin(beta) * lK - sa * Rko print "Pnom : ", Pnom
import PyX_classes, PyX_Utility
import os, pyx
from pylab import np
''' TEC-ISMB-2021 鼠笼相量图
'''
if __name__ == '__main__':
pu = PyX_Utility.PyX_Utility()
PyX_Utility.global_settings['linewidth'] = pyx.style.linewidth.THIck
Q_r_prime = 8
alpha_c = 2 * np.pi / Q_r_prime
for i in range(Q_r_prime):
radius = 10
x = radius * np.cos(i * alpha_c)
y = radius * -np.sin(i * alpha_c)
pu.pyx_arrow((x, y))
radius = 9
x = radius * np.cos(i * alpha_c + 15 / 180 * np.pi)
y = radius * -np.sin(i * alpha_c + 15 / 180 * np.pi)
pu.pyx_text((x, y),
r'$\bar U_{r%d,n}$' % (i + 1),
settings=['blue'],
scale=1.5)
radius = 11
x = radius * np.cos(i * alpha_c + 0 / 180 * np.pi)
y = radius * -np.sin(i * alpha_c + 0 / 180 * np.pi)
pu.pyx_text((x, y), str(i + 1), settings=[], scale=1.5)
radius = 3
x = radius * np.cos(i * alpha_c)
def rotate(_, x, y):
return np.cos(_) * x + np.sin(_) * y, -np.sin(_) * x + np.cos(_) * y
def my_3d_plot_non_dominated_fronts(pop,
paretoPoints,
fea_config_dict,
az=180,
comp=[0, 1, 2],
plot_option=1):
"""
Plots solutions to the DTLZ problems in three dimensions. The Pareto Front is also
visualized if the problem id is 2,3 or 4.
Args:
pop (:class:`~pygmo.population`): population of solutions to a dtlz problem
az (``float``): angle of view on which the 3d-plot is created
comp (``list``): indexes the fitness dimension for x,y and z axis in that order
Returns:
``matplotlib.axes.Axes``: the current ``matplotlib.axes.Axes`` instance on the current figure
Raises:
ValueError: if *pop* does not contain a DTLZ problem (veryfied by its name only) or if *comp* is not of length 3
Examples:
>>> import pygmo as pg
>>> udp = pg.dtlz(prob_id = 1, fdim =3, dim = 5)
>>> pop = pg.population(udp, 40)
>>> udp.plot(pop) # doctest: +SKIP
"""
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
# from pylab import mpl
# mpl.rcParams['font.family'] = ['Times New Roman']
# mpl.rcParams['font.size'] = 16.0
# if (pop.problem.get_name()[:-1] != "DTLZ"):
# raise(ValueError, "The problem seems not to be from the DTLZ suite")
if (len(comp) != 3):
raise (
ValueError,
"The kwarg *comp* needs to contain exactly 3 elements (ids for the x,y and z axis)"
)
# Create a new figure
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111, projection='3d')
# plot the points
fits = np.transpose(pop.get_f())
try:
pass
# ax.plot(fits[comp[0]], fits[comp[1]], fits[comp[2]], 'ro')
except IndexError:
print('Error. Please choose correct fitness dimensions for printing!')
if False:
# Plot pareto front for dtlz 1
if plot_option == 1: # (pop.problem.get_name()[-1] in ["1"]):
X, Y = np.meshgrid(np.linspace(0, 0.5, 100),
np.linspace(0, 0.5, 100))
Z = -X - Y + 0.5
# remove points not in the simplex
for i in range(100):
for j in range(100):
if X[i, j] < 0 or Y[i, j] < 0 or Z[i, j] < 0:
Z[i, j] = float('nan')
ax.set_xlim(0, 1.)
ax.set_ylim(0, 1.)
ax.set_zlim(0, 1.)
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.plot([0, 0.5], [0.5, 0], [0, 0])
# Plot pareto fronts for dtlz 2,3,4
if plot_option == 2: # (pop.problem.get_name()[-1] in ["2", "3", "4"]):
# plot the wireframe of the known optimal pareto front
thetas = np.linspace(0, (np.pi / 2.0), 30)
# gammas = np.linspace(-np.pi / 4, np.pi / 4, 30)
gammas = np.linspace(0, (np.pi / 2.0), 30)
x_frame = np.outer(np.cos(thetas), np.cos(gammas))
y_frame = np.outer(np.cos(thetas), np.sin(gammas))
z_frame = np.outer(np.sin(thetas), np.ones(np.size(gammas)))
ax.set_autoscalex_on(False)
ax.set_autoscaley_on(False)
ax.set_autoscalez_on(False)
ax.set_xlim(0, 1.8)
ax.set_ylim(0, 1.8)
ax.set_zlim(0, 1.8)
ax.plot_wireframe(x_frame, y_frame, z_frame)
# https://stackoverflow.com/questions/37000488/how-to-plot-multi-objectives-pareto-frontier-with-deap-in-python
# def simple_cull(inputPoints, dominates):
# paretoPoints = set()
# candidateRowNr = 0
# dominatedPoints = set()
# while True:
# candidateRow = inputPoints[candidateRowNr]
# inputPoints.remove(candidateRow)
# rowNr = 0
# nonDominated = True
# while len(inputPoints) != 0 and rowNr < len(inputPoints):
# row = inputPoints[rowNr]
# if dominates(candidateRow, row):
# # If it is worse on all features remove the row from the array
# inputPoints.remove(row)
# dominatedPoints.add(tuple(row))
# elif dominates(row, candidateRow):
# nonDominated = False
# dominatedPoints.add(tuple(candidateRow))
# rowNr += 1
# else:
# rowNr += 1
# if nonDominated:
# # add the non-dominated point to the Pareto frontier
# paretoPoints.add(tuple(candidateRow))
# if len(inputPoints) == 0:
# break
# return paretoPoints, dominatedPoints
# def dominates(row, candidateRow):
# return sum([row[x] >= candidateRow[x] for x in range(len(row))]) == len(row)
# import random
# print(inputPoints)
# inputPoints = [[random.randint(70,100) for i in range(3)] for j in range(500)]
# print(inputPoints)
# quit()
# inputPoints = [(x,y,z) for x,y,z in zip(fits[comp[0]], fits[comp[1]], fits[comp[2]])]
# paretoPoints, dominatedPoints = simple_cull(inputPoints, dominates)
x = [coords[0] / 1000 for coords in paretoPoints]
y = [coords[1] for coords in paretoPoints]
z = [coords[2] for coords in paretoPoints]
# from surface_fitting import surface_fitting
# surface_fitting(x,y,z)
# quit()
if False:
pass
else:
import pandas as pd
from pylab import cm
print(dir(cm))
df = pd.DataFrame({'x': x, 'y': y, 'z': z})
# 只有plot_trisurf这一个函数，输入是三个以为序列的，其他都要meshgrid得到二维数组的(即ndim=2的数组)
# # https://jakevdp.github.io/PythonDataScienceHandbook/04.12-three-dimensional-plotting.html
# surf = ax.plot_trisurf(df.x, df.y, df.z, cmap=cm.magma, linewidth=0.1, edgecolor='none')
# surf = ax.plot_trisurf(x, y, z, cmap='viridis', edgecolor='none')
# surf = ax.plot_trisurf(df.x, df.y, df.z, cmap=cm.magma, linewidth=0.1)
surf = ax.plot_trisurf(df.x,
df.y * 100,
df.z,
cmap=cm.Spectral,
linewidth=0.1)
with open('./%s_PF_points.txt' % (fea_config_dict['run_folder'][:-1]),
'w') as f:
f.write('TRV,eta,OC\n')
f.writelines([
'%g,%g,%g\n' % (a, b, c)
for a, b, c in zip(df.x, df.y * 100, df.z)
])
# quit()
fig.colorbar(surf, shrink=0.5, aspect=5)
ax.set_xlabel(' \n$\\rm -TRV$ [$\\rm kNm/m^3$]')
ax.set_ylabel(' \n$-\\eta$ [%]')
ax.set_yticks(np.arange(-96, -93.5, 0.5))
ax.set_zlabel(r'$O_C$ [1]')
# Try to export data from plot_trisurf # https://github.com/WoLpH/numpy-stl/issues/19
# print(surf.get_vector())
# plt.savefig('./plots/avgErrs_vs_C_andgamma_type_%s.png'%(k))
# plt.show()
# # rotate the axes and update
# for angle in range(0, 360):
# ax.view_init(30, angle)
# plt.draw()
# plt.pause(.001)
ax.view_init(azim=245, elev=15)
# fig.tight_layout()
# Y730
# fig.savefig(r'C:\Users\horyc\Desktop/3D-plot.png', dpi=300, layout='tight')
# ax.view_init(azim=az)
# ax.set_xlim(0, 1.)
# ax.set_ylim(0, 1.)
# ax.set_zlim(0, 10.)
return ax
def hide_annotations(self):
for ann in self.annotations:
ann.set_visible(False)
# ---------------------------------------------------------------------
t = np.linspace(0.0, 1.0, 11)
s1 = t
s2 = -t
s3 = t**2
s4 = -(t**2)
s5 = np.sin(t*2*np.pi)
s6 = np.cos(t*2*np.pi)
fig = figure()
ax1 = fig.add_subplot(321)
ax1.plot(t, s1)
ax1.scatter(t, s1)
ax2 = fig.add_subplot(322)
ax2.plot(t, s2)
ax2.scatter(t, s2)
ax3 = fig.add_subplot(323)
ax3.plot(t, s3)
ax3.scatter(t, s3)
plt.plot([1.732, 1.732], [0.0, 3.0], color='0.6', linestyle='--')
# high-resolution limit calculation with delta_omega = 0.1
x = [
1.00, 1.10, 1.20, 1.30, 1.40, 1.50, 1.60, 1.70, 1.80, 1.90, 2.00, 2.20,
2.40, 2.60
]
y = [
1.15, 1.28, 1.38, 1.50, 1.61, 1.73, 1.84, 1.96, 2.07, 2.19, 2.31, 2.54,
2.77, 2.99
]
M = [
1.52, 1.50, 1.42, 0.97, 1.34, 0.98, 1.27, 1.25, 1.22, 1.21, 1.20, 1.67,
1.14, 1.12
]
plt.plot(x, y, color='k', linestyle='-')
plt.plot([0.0, 3.0], [0.0, 3.0 / np.cos(beta)], color='r', linestyle='--')
plt.plot([1.732, 1.732], [0.0, 3.0], color='0.6', linestyle='--')
plt.scatter(5,
1.25,
marker='o',
s=80,
linewidth=1.2,
edgecolor='k',
facecolor='w')
plt.xlim(1.0, 5.0)
plt.ylim(0.0, 3.0)
plt.xticks(np.arange(1.0, 5.01, 1.0))
plt.yticks(np.arange(0.0, 3.01, 1.0))
minorLocator = MultipleLocator(0.5)
ax.xaxis.set_minor_locator(minorLocator)
ax.yaxis.set_minor_locator(minorLocator)
def walltransmission(xvals, parms):
#position=p[0]; intensity=p[1]; slit=p[2]; stth=p[3]; background=p[4]; thickness=p[5]; absorption=p[6]
midpoint = parms[0]
i0 = parms[1]
w = parms[2]
theta = parms[3]
ib = parms[4]
thick = parms[5]
u = parms[6]
midpoint = parms[0]
x0 = midpoint - thick / 2.0
th = np.deg2rad(theta)
p = w * np.cos(th)
t = thick
Atot1 = w * w / np.sin(2.0 * th)
Atot = 2 * w * np.sin(th) * w * np.cos(th)
out = []
baselength = 2 * p
Gvol_area = 2 * w * w * np.sin(th) * np.cos(th)
if baselength > thick:
Ar = 0.5 * (p - thick / 2.0) * (p - thick / 2.0) * np.tan(th)
maxbeam = Gvol_area - 4.0 * Ar
else:
maxbeam = Gvol_area
for x in xvals:
x1 = x
x2 = x - thick
if (x1 <= (x0 - p)) and (x2 <= x0 - p):
val = ib
elif (x0 - p) >= x2 and (x0 - p <= x1) and (x0 > x1):
A = (x1 - (x0 - p))
val = ib + A * A * np.tan(th) / maxbeam * i0
elif (x0 - p <= x2) and (x0 >= x1):
C = (x1 - (x0 - p))
B = (x2 - (x0 - p))
val = ib + (C * C * np.tan(th) - B * B * np.tan(th)) / maxbeam * i0
elif (x2 <= (x0 - p)) and (x0 >= x2) and (x0 <= x1) and (x1 <=
(x0 + p)):
A = (x1 - (x0 + p))
val = ib + (Gvol_area - A * A * np.tan(th)) / maxbeam * i0
elif (x2 <= (x0 - p)) and (x0 >= x2) and (x0 <= x1) and (x1 >=
(x0 + p)):
val = ib + i0
elif (x2 >= (x0 - p)) and (x0 >= x2) and (x0 <= x1) and (x1 <=
(x0 + p)):
A = (x1 - (x0 + p))
B = (x2 - (x0 - p))
val = ib + (Gvol_area - A * A * np.tan(th) -
B * B * np.tan(th)) / maxbeam * i0
elif (x2 >= (x0 - p)) and (x0 >= x2) and (x0 <= x1) and (x1 >=
(x0 + p)):
B = (x2 - (x0 - p))
val = ib + (Gvol_area - B * B * np.tan(th)) / maxbeam * i0
elif (x0 + p >= x1) and (x0 <= x2):
A = (x1 - (x0 + p))
C = (x2 - (x0 + p))
val = ib + (C * C * np.tan(th) - A * A * np.tan(th)) / maxbeam * i0
elif (x2 >= (x0 - p)) and (x0 <= x2) and (x0 <= x1) and (
x1 >= (x0 + p)) and (x2 <= (x0 + p)):
A = (x0 + p - x2)
val = ib + A * A * np.tan(th) / maxbeam * i0
elif (x0 - p) >= x2 and (x0 + p) <= x2:
val = ib
out = out + [val]
return np.array(out)
def redraw_cross_section_outline_with_pyx(tool_tikz, no_repeat_stator,
no_repeat_rotor,
mm_rotor_outer_radius,
mm_air_gap_length,
mm_rotor_outer_steel_radius,
mm_rotor_inner_radius):
# PyX
tool_tikz.c = pyx.canvas.canvas(
) # clear the canvas because we want to redraw 90 deg with the data tool_tikz.track_path
print('Index | Path data')
p_stator = None #pyx.path.path()
p_rotor = None #pyx.path.path()
for index, path in enumerate(
tool_tikz.track_path
): # track_path is passed by reference and is changed by mirror
# Failed to fill the closed path, because there is no arc-like path available.
# p = pyx.path.line(4, 0, 5, 0) << pyx.path.line(5, 0, 5, 1) << pyx.path.line(5, 1, 4, 1)
# p.append(path.closepath())
# tool_tikz.c.stroke(p)
# tool_tikz.c.stroke(path.rect(0, 0, 1, 1), [pyx.style.linewidth.Thick,
# pyx.color.rgb.red,
# pyx.deco.filled([pyx.color.rgb.green])])
path_mirror = deepcopy(path)
# for mirror copy (along x-axis)
path_mirror[1] = path[1] * -1
path_mirror[3] = path[3] * -1
# for mirror copy (along y-axis)
# path_mirror[0] = path[0]*-1
# path_mirror[2] = path[2]*-1
bool_exclude_path = False
# rotate path and plot
if is_at_stator(path, mm_rotor_outer_radius, mm_air_gap_length):
Q = no_repeat_stator
else:
Q = no_repeat_rotor * 2
EPS = 1e-6
if is_at_stator(path, mm_rotor_outer_radius, mm_air_gap_length):
# 按照Eric的要求，把不必要的线给删了。
if abs(path[1] + path[3]) < EPS: # 镜像对称线
bool_exclude_path = True
if abs(path[0] - path[2]) + np.cos(
2 * np.pi / Q / 2) < EPS: # 旋转对称线（特别情况，tan(90°) = ∞
bool_exclude_path = True
else:
if abs(
abs((path[1] - path[3]) / (path[0] - path[2])) -
abs(np.tan(2 * np.pi / Q / 2))) < EPS: # 旋转对称线
bool_exclude_path = True
if not is_at_stator(path, mm_rotor_outer_radius,
mm_air_gap_length):
# 按照Eric的要求，把不必要的线给删了。
if (abs(np.sqrt(path[0]**2+path[1]**2) - mm_rotor_inner_radius)<EPS or abs(np.sqrt(path[2]**2+path[3]**2) - mm_rotor_inner_radius)<EPS) \
and (len(path)==4): # 转子铁芯内径到外径的直线(len(path)==4)
bool_exclude_path = True
# # 特别的是，画永磁体的时候，边界要闭合哦。
# if abs(np.sqrt(path[0]**2+path[1]**2) - mm_rotor_outer_steel_radius) < EPS or abs(np.sqrt(path[2]**2+path[3]**2) - mm_rotor_outer_steel_radius) < EPS:
# bool_exclude_path = False
# A trick that makes sure models with different outer diameters have the same scale.
# tool_tikz.draw_arc([125,0], [-125,0], relangle=sign*180, untrack=True)
tool_tikz.c.fill(
pyx.path.circle(0, 0, 125), [pyx.color.transparency(1)]
) # use this if THICK is used. <- Warn: Transparency not available in PostScript, proprietary ghostscript extension code inserted. (save as eps format)
# tool_tikz.c.fill(pyx.path.circle(0, 0, 125), [pyx.color.rgb.white]) # use this if THICK is used. <- this will over-write everthing... how to change zorder?
_ = 2 * np.pi / Q
if True: # full model
for counter in range(Q):
# 转子：旋转复制
if not is_at_stator(path, mm_rotor_outer_radius,
mm_air_gap_length):
path[0], path[1] = rotate(_, path[0], path[1])
path[2], path[3] = rotate(_, path[2], path[3])
路径 = tool_tikz.pyx_draw_path(
path,
sign=1,
bool_exclude_path=bool_exclude_path,
bool_stroke=True)
if 路径 is not None:
if p_rotor is None:
p_rotor = 路径
else:
p_rotor = p_rotor << 路径
# 定子：镜像+旋转复制
if is_at_stator(path, mm_rotor_outer_radius,
mm_air_gap_length):
path[0], path[1] = rotate(_, path[0], path[1])
path[2], path[3] = rotate(_, path[2], path[3])
路径 = tool_tikz.pyx_draw_path(
path,
sign=1,
bool_exclude_path=bool_exclude_path,
bool_stroke=True)
# print(index, '\t|', ',\t'.join(['%g'%(el) for el in path]))
if 路径 is not None:
if p_stator is None:
p_stator = 路径
else:
p_stator = p_stator << 路径
path_mirror[0], path_mirror[1] = rotate(
_, path_mirror[0], path_mirror[1])
path_mirror[2], path_mirror[3] = rotate(
_, path_mirror[2], path_mirror[3])
路径 = tool_tikz.pyx_draw_path(
path_mirror,
sign=-1,
bool_exclude_path=bool_exclude_path,
bool_stroke=True)
if 路径 is not None:
if p_stator is None:
p_stator = 路径
else:
p_stator = p_stator << 路径
# break
else: # backup
# 转子：旋转复制
if not is_at_stator(path, mm_rotor_outer_radius,
mm_air_gap_length):
path[0], path[1] = rotate(0.5 * np.pi - 0.5 * 0.5 * _,
path[0], path[1])
path[2], path[3] = rotate(0.5 * np.pi - 0.5 * 0.5 * _,
path[2], path[3])
pyx_draw_path(tool_tikz,
path,
sign=1,
bool_exclude_path=bool_exclude_path)
# print(index, '\t|', ',\t'.join(['%g'%(el) for el in path]))
# path[0], path[1] = rotate(0.5*np.pi - 0*0.5*_, path[0], path[1])
# path[2], path[3] = rotate(0.5*np.pi - 0*0.5*_, path[2], path[3])
# pyx_draw_path(tool_tikz, path, sign=1, bool_exclude_path=bool_exclude_path)
# 定子：镜像+旋转复制
if is_at_stator(path, mm_rotor_outer_radius,
mm_air_gap_length):
path[0], path[1] = rotate(0.5 * np.pi - 0.5 * _, path[0],
path[1])
path[2], path[3] = rotate(0.5 * np.pi - 0.5 * _, path[2],
path[3])
pyx_draw_path(tool_tikz,
path,
sign=1,
bool_exclude_path=bool_exclude_path)
# print(index, '\t|', ',\t'.join(['%g'%(el) for el in path]))
path_mirror[0], path_mirror[1] = rotate(
0.5 * np.pi - 0.5 * _, path_mirror[0], path_mirror[1])
path_mirror[2], path_mirror[3] = rotate(
0.5 * np.pi - 0.5 * _, path_mirror[2], path_mirror[3])
pyx_draw_path(tool_tikz,
path_mirror,
sign=-1,
bool_exclude_path=bool_exclude_path)
# 注意，所有 tack_path 中的 path 都已经转动了90度了！
# for mirror copy (along y-axis)
path[0] *= -1
path[2] *= -1
pyx_draw_path(tool_tikz,
path,
sign=-1,
bool_exclude_path=bool_exclude_path)
path_mirror[0] *= -1
path_mirror[2] *= -1
pyx_draw_path(tool_tikz,
path_mirror,
sign=1,
bool_exclude_path=bool_exclude_path)
