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![And here’s the code itself; you can paste this directly into Google Colab and it generates the plot:
import numpy as np, matplotlib.pyplot as plt
R=10.0; P=34.0; q=2*np.pi/P
nz,nk=720,560; kz_max,kp_max=2.0,2.0
sigma_z=0.04; mmax=20; delta_phi=np.pi; delta_z=P/2.0
h=3.4; N_bp=400; beta=0.25
kz=np.linspace(-kz_max,kz_max,nz); kp=np.linspace(0,kp_max,nk)
n_tau=512; tau=np.linspace(0,np.pi,n_tau); s_tau=np.sin(tau)
def Jv(m,x):
x=np.asarray(x); ph=m*tau[None,:]-x[:,None]*s_tau[None,:]
return np.trapz(np.cos(ph),tau,axis=1)/np.pi
I=np.zeros((nz,nk),dtype=np.float64)
for m in range(-mmax,mmax+1):
Jm=Jv(abs(m),kp*R); L=np.exp(-0.5*((kz-m*q)/sigma_z)**2)[:,None]
A2=2.0+2.0*np.cos(m*delta_phi+kz[:,None]*delta_z)
I+=(Jm*Jm)[None,:]*L*A2
eps=1e-9
S=(np.sin(0.5*N_bp*h*kz)**2)/((np.sin(0.5*h*kz)**2)+eps); S=(S/(S.max()+eps))[:,None]
I*=1.0+beta*S
I/=I.max()+1e-12; I=np.log1p(12*I)
I_full=np.concatenate([I[:,::-1],I],axis=1)
extent=[-kp_max,kp_max,-kz_max,kz_max]
plt.figure(figsize=(6,8))
plt.imshow(I_full,extent=extent,origin='lower',aspect='auto')
plt.axis('off')
plt.savefig('photo51_like.png',dpi=220,bbox_inches='tight',pad_inches=0.02)
https://t.co/HDadZBCvO4()](/_next/image?url=https%3A%2F%2Fpbs.twimg.com%2Fprofile_images%2F1225476100547063809%2F53jSWs7z_400x400.jpg&w=3840&q=75 "And here’s the code itself; you can paste this directly into Google Colab and it generates the plot:
import numpy as np, matplotlib.pyplot as plt
R=10.0; P=34.0; q=2*np.pi/P
nz,nk=720,560; kz_max,kp_max=2.0,2.0
sigma_z=0.04; mmax=20; delta_phi=np.pi; delta_z=P/2.0
h=3.4; N_bp=400; beta=0.25
kz=np.linspace(-kz_max,kz_max,nz); kp=np.linspace(0,kp_max,nk)
n_tau=512; tau=np.linspace(0,np.pi,n_tau); s_tau=np.sin(tau)
def Jv(m,x):
x=np.asarray(x); ph=m*tau[None,:]-x[:,None]*s_tau[None,:]
return np.trapz(np.cos(ph),tau,axis=1)/np.pi
I=np.zeros((nz,nk),dtype=np.float64)
for m in range(-mmax,mmax+1):
Jm=Jv(abs(m),kp*R); L=np.exp(-0.5*((kz-m*q)/sigma_z)**2)[:,None]
A2=2.0+2.0*np.cos(m*delta_phi+kz[:,None]*delta_z)
I+=(Jm*Jm)[None,:]*L*A2
eps=1e-9
S=(np.sin(0.5*N_bp*h*kz)**2)/((np.sin(0.5*h*kz)**2)+eps); S=(S/(S.max()+eps))[:,None]
I*=1.0+beta*S
I/=I.max()+1e-12; I=np.log1p(12*I)
I_full=np.concatenate([I[:,::-1],I],axis=1)
extent=[-kp_max,kp_max,-kz_max,kz_max]
plt.figure(figsize=(6,8))
plt.imshow(I_full,extent=extent,origin='lower',aspect='auto')
plt.axis('off')
plt.savefig('photo51_like.png',dpi=220,bbox_inches='tight',pad_inches=0.02)
https://t.co/HDadZBCvO4()")
And here’s the code itself; you can paste this directly into Google Colab and it generates the plot: import numpy as np, matplotlib.pyplot as plt R=10.0; P=34.0; q=2*np.pi/P nz,nk=720,560; kz_max,kp_max=2.0,2.0 sigma_z=0.04; mmax=20; delta_phi=np.pi; delta_z=P/2.0 h=3.4; N_bp=400; beta=0.25 kz=np.linspace(-kz_max,kz_max,nz); kp=np.linspace(0,kp_max,nk) n_tau=512; tau=np.linspace(0,np.pi,n_tau); s_tau=np.sin(tau) def Jv(m,x): x=np.asarray(x); ph=m*tau[None,:]-x[:,None]*s_tau[None,:] return np.trapz(np.cos(ph),tau,axis=1)/np.pi I=np.zeros((nz,nk),dtype=np.float64) for m in range(-mmax,mmax+1): Jm=Jv(abs(m),kp*R); L=np.exp(-0.5*((kz-m*q)/sigma_z)**2)[:,None] A2=2.0+2.0*np.cos(m*delta_phi+kz[:,None]*delta_z) I+=(Jm*Jm)[None,:]*L*A2 eps=1e-9 S=(np.sin(0.5*N_bp*h*kz)**2)/((np.sin(0.5*h*kz)**2)+eps); S=(S/(S.max()+eps))[:,None] I*=1.0+beta*S I/=I.max()+1e-12; I=np.log1p(12*I) I_full=np.concatenate([I[:,::-1],I],axis=1) extent=[-kp_max,kp_max,-kz_max,kz_max] plt.figure(figsize=(6,8)) plt.imshow(I_full,extent=extent,origin='lower',aspect='auto') plt.axis('off') plt.savefig('photo51_like.png',dpi=220,bbox_inches='tight',pad_inches=0.02) https://t.co/HDadZBCvO4()
Here’s the final image straight from python.