for data in reader:
x2.append(int(data[0]))
y2.append(int(data[1]))
##############################################################################
# Plot some figures
##############################################################################
# fig1 = plt.figure('fig1', figsize=(5, 5))
# ax1 = fig1.add_subplot(1, 1, 1)
# fig1.patch.set_facecolor(cs['mdk_dgrey'])
# ax1.set_xlabel('x axis')
# ax1.set_ylabel('y axis')
# plt.imshow(im, extent=prd.extents(x) + prd.extents(y))
fig2 = plt.figure('fig2', figsize=(5, 3))
ax2 = fig2.add_subplot(1, 1, 1)
fig2.patch.set_facecolor(cs['mdk_dgrey'])
ax2.set_xlabel('Year')
ax2.xaxis.set_major_locator(MaxNLocator(integer=True))
ax2.set_ylabel('# of publications')
plt.plot(x2, y2, '.:', label='free space')
plt.plot(x0, y0, '.:', label='fibre')
plt.plot(x1, y1, '.:', label='satellite')
plt.legend(fancybox=True, framealpha=0.0)
os.chdir(r"D:\Python\Misc Plots")
plt.tight_layout()
plt.show()
prd.PPT_save_2d(fig2, ax2, 'plot1.png')
# cm = plt.get_cmap('binary')
# surf0 = ax0.plot_surface(X[:, 0:a], Y[:, 0:a], Z1[
# :, 0:a], cmap='gray', alpha=0.6)
# wire0 = ax0.plot_wireframe(X[:, 0:a], Y[:, 0:a], Z1[
# :, 0:a], color=cs['mdk_dgrey'], lw=0.5, alpha=1)
fig1 = plt.figure('fig1')
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mdk_dgrey'])
ax1.set_xlabel('x axis')
ax1.set_ylabel('y axis')
ax1.set_aspect(1)
plt.imshow(Gtot, extent=(x[0], x[-1], y[0], y[-1]), origin='lower')
# surffit = ax1.contour(*coords, G, 5 , cmap=cm.jet)
plt.plot(xc, yc)
# im3 = plt.figure('im3')
# ax3 = im3.add_subplot(1, 1, 1)
# im3.patch.set_facecolor(cs['mdk_dgrey'])
# ax3.set_xlabel('x axis')
# ax3.set_ylabel('y axis')
# plt.imshow(im)
# cb2 = plt.colorbar()
# plt.legend()
plt.tight_layout()
plt.show()
prd.PPT_save_2d(fig1, ax1, 'Hex pack.png')
# plt.plot(H1[0, :], 'o:')
# plt.plot(H2[0, :], 'o:')
# plt.ylim(0, 255)
# plt.plot(ϕ1, 'o:')
# plt.plot(Z12_mod[0, :] / π, 'o:')
# plt.ylim(-1, 2)
# plt.imshow(Z12_mod, extent=prd.extents(X) + prd.extents(Y))
# plt.imshow(H2, extent=prd.extents(X) + prd.extents(Y),
# cmap='gray', vmin=0, vmax=255)
# plt.colorbar()
plt.plot(X, H2[0, :] / π, 'o:')
# plt.plot(H2[0, :], Z_HR_mod[0, :] / π)
ax1.set_xlabel('x axis - px')
# ax1.set_ylabel('y axis - phase/π')
# ax1.set_ylabel('y axis - phase (ϕ)')
# im3 = plt.figure('im3')
# ax3 = im3.add_subplot(1, 1, 1)
# im3.patch.set_facecolor(cs['mdk_dgrey'])
# ax3.set_xlabel('x axis')
# ax3.set_ylabel('y axis')
# plt.imshow(im)
# cb2 = plt.colorbar()
# plt.legend()
plt.tight_layout()
plt.show()
os.chdir(f2)
prd.PPT_save_2d(fig1, ax1, 'plot1.png')
'P$_{sat}$ = ' + str(P_sat) + 'μW'
##############################################################################
# Plot some figures
##############################################################################
fig2 = plt.figure('fig2', figsize=(6, 4))
prd.ggplot()
ax2 = fig2.add_subplot(1, 1, 1)
fig2.patch.set_facecolor(cs['mnk_dgrey'])
ax2.set_xlabel('Inferred power (mW)')
ax2.set_ylabel('kcounts per secound')
plt.plot(Ps, kcps, 'o:', label='data')
plt.plot(Ps_fit, Isat_fit, '-', label=lb0)
plt.plot(Ps_fit,
prd.I_sat(Ps_fit, popt[0], popt[1], 0, popt[3]),
'--',
label=lb1)
plt.plot(Ps_fit,
prd.I_sat(Ps_fit, 0, popt[1], popt[2], popt[3]),
'--',
label=lb2)
ax2.legend(loc='upper left', fancybox=True, framealpha=1)
os.chdir(p0)
plt.title(lb3)
plt.tight_layout()
plt.show()
ax2.legend(loc='upper left', fancybox=True, facecolor=(1.0, 1.0, 1.0, 0.0))
prd.PPT_save_2d(fig2, ax2, 'Sat curve.png')
x1 = -τ * np.log(y1) + τ
##############################################################################
# Plot some figures
##############################################################################
prd.ggplot()
# fig1 = plt.figure('fig1', figsize=(5, 5))
# ax1 = fig1.add_subplot(1, 1, 1)
# fig1.patch.set_facecolor(cs['mnk_dgrey'])
# ax1.set_xlabel('x axis')
# ax1.set_ylabel('y axis')
# plt.imshow(im, extent=prd.extents(x) + prd.extents(y))
size = 2
fig2 = plt.figure('fig2', figsize=(size * np.sqrt(2), size))
ax2 = fig2.add_subplot(1, 1, 1)
fig2.patch.set_facecolor(cs['mnk_dgrey'])
ax2.set_xlabel('x axis')
ax2.set_ylabel('y axis')
plt.plot(x1, y1, '.', alpha=0.4, color=cs['gglred'], label='')
plt.plot(x1, y1, alpha=1, color=cs['ggdred'], lw=0.5, label='decay')
plt.plot(x2, y2, '.', alpha=0.4, color=cs['gglblue'], label='')
plt.plot(x2, y2, alpha=1, color=cs['ggblue'], lw=0.5, label='excite')
ax2.legend(loc='upper right', fancybox=True, framealpha=0.5)
# os.chdir(p0)
plt.tight_layout()
plt.show()
ax2.legend(loc='upper right', fancybox=True, facecolor=(1.0, 1.0, 1.0, 0.0))
plot_file_name = p0 + r'\plot1.png'
prd.PPT_save_2d(fig2, ax2, plot_file_name)
for i0, val0 in enumerate(datafiles[4:]):
x, y, img = prd.load_SCM_F5L10(val0)
print(y)
lb = os.path.basename(val0)
print(lb, np.shape(img))
img_name = os.path.splitext(lb)[0] + '_img.png'
profile_name = os.path.splitext(lb)[0] + '_prof.png'
fig1 = plt.figure('fig1', figsize=(4, 4))
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mnk_dgrey'])
ax1.set_xlabel('x dimension (px)')
ax1.set_ylabel('y dimension (px)')
plt.imshow(img, label=lb)
plt.gca().invert_yaxis()
ax1.legend(loc='upper right', fancybox=True, framealpha=1)
fig2 = plt.figure('fig2', figsize=(8, 4))
ax2 = fig2.add_subplot(1, 1, 1)
fig2.patch.set_facecolor(cs['mnk_dgrey'])
ax2.set_xlabel('x dimension (V)')
ax2.set_ylabel('counts')
plt.plot(img[10, :], '.:', label='y V = ' + str(round(y[-10], 4)))
ax2.legend(loc='upper right', fancybox=True, framealpha=1)
plt.show()
os.chdir(p0)
prd.PPT_save_2d(fig1, ax1, img_name)
prd.PPT_save_2d(fig2, ax2, profile_name)
XT = d3 - d2
fig1 = plt.figure('fig1')
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mdk_dgrey'])
ax1.set_xlabel('P1 - sin(ϕ) offset')
ax1.set_ylabel('P0 - sin(ϕ) amplitude')
plt.imshow(XT,
aspect='auto',
interpolation='none',
extent=prd.extents(x) + prd.extents(y),
origin='lower')
plt.colorbar()
fig2 = plt.figure('fig2')
ax2 = fig2.add_subplot(1, 1, 1)
fig2.patch.set_facecolor(cs['mdk_dgrey'])
ax2.set_xlabel('P1 - sin(ϕ) offset')
ax2.set_ylabel('P0 - sin(ϕ) amplitude')
plt.imshow(d3,
aspect='auto',
interpolation='none',
extent=prd.extents(x) + prd.extents(y),
origin='lower')
plt.colorbar()
plt.show()
os.chdir(p0)
prd.PPT_save_2d(fig1, ax1, 'figure1')
sys.path.insert(0, r"D:\Python\Local Repo\library")
import useful_defs_prd as prd
cs = prd.palette()
##############################################################################
# Do some stuff
##############################################################################
p0 = (r"D:\Experimental Data\Oscilloscope (F5 L10)\SPAD outputs" r"\SPAD2.csv")
lb = os.path.basename(p0)
name = os.path.splitext(p0)[0]
csv = np.genfromtxt(p0, delimiter=",")
t = 1e6 * csv[:, 3]
V = csv[:, 4]
# plot each data set and save (close pop-up to save each time)
prd.ggplot()
fig1 = plt.figure('fig1', figsize=(6, 4))
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mnk_dgrey'])
ax1.set_xlabel('time / μs')
ax1.set_ylabel('Voltage / V')
ax1.plot(t, V, lw=0.5)
ax1.plot(t, V, '.', markersize=0.3, alpha=0.5, label=lb)
plt.title('time trace')
plt.tight_layout()
ax1.legend(loc='upper left', fancybox=True, framealpha=0.5)
plt.show()
ax1.legend(loc='upper left', fancybox=True, facecolor=(1.0, 1.0, 1.0, 0.0))
prd.PPT_save_2d(fig1, ax1, name)
im2.patch.set_facecolor(cs['mdk_dgrey'])
ax2.set_xlabel('x axis')
ax2.set_ylabel('y axis')
plt.imshow(H5, cmap='gray')
# im3 = plt.figure('im3')
# ax3 = im3.add_subplot(1, 1, 1)
# im3.patch.set_facecolor(cs['mdk_dgrey'])
# ax3.set_xlabel('x axis')
# ax3.set_ylabel('y axis')
# plt.imshow(H6, cmap='gray')
# cb3 = plt.colorbar()
# fig2 = plt.figure('fig2')
# ax2 = Axes3D(fig2)
# fig2.patch.set_facecolor(cs['mdk_dgrey'])
# ax2.w_xaxis.set_pane_color(cs['mdk_dgrey'])
# ax2.w_yaxis.set_pane_color(cs['mdk_dgrey'])
# ax2.w_zaxis.set_pane_color(cs['mdk_dgrey'])
# ax2.set_xlabel('x axis')
# ax2.set_ylabel('y axis')
# ax2.set_zlabel('z axis')
# scat2 = ax2.scatter(X, Y, Z0,
# '.', cmap='gray', s=16, c=Z0)
# surf2 = ax2.plot_surface(X, Y, Z0, cmap='gray', alpha=0.1, edgecolor=ggred)
plt.show()
prd.PPT_save_2d(fig1, ax1, 'pixel row grey.png')
for i1, val1 in enumerate(files[0:]):
print('file name = ', val1)
data = io.loadmat(val1)
if int(data['fibre']) > 4:
fibre = str(int(data['fibre']))
else:
fibre = str(int(data['fibre']))
label = 'Port ' + fibre
fibre_c = 'fibre9d_' + fibre
print(fibre)
print(np.transpose(np.shape(data['Ps'])))
plt.plot(np.transpose(data['lambdas']), np.transpose(data['Ps']), '-',
lw=1, label=label, c=cs[fibre_c])
leg1 = plt.legend(prop={'size': 6})
leg1.get_frame().set_alpha(0.0)
for text in leg1.get_texts():
text.set_color("black")
##############################################################################
# Plot some figures
##############################################################################
os.chdir(p2)
plt.show()
prd.PPT_save_2d(fig1, ax1, 'Port2')
ax2.set_xlabel('Count rate')
ax2.set_ylabel('Freq (#)')
lb1 = 'kcps 1 = ' + str(np.round(Cts1_μ/1e3,1))
lb2 = 'kcps 2 = ' + str(np.round(Cts2_μ/1e3,1))
lb3 = 'kcps$_{tot}$ = ' + str(np.round((Cts1_μ + Cts2_μ)/1e3,1))
Cts1_n, Cts1_bins, Cts1_patches = plt.hist(Cts1, bins=10, label=lb1,
alpha=0.5, edgecolor=cs['mnk_dgrey'])
Cts2_n, Cts2_bins, Cts2_patches = plt.hist(Cts2, bins=10, label=lb2,
alpha=0.5, edgecolor=cs['mnk_dgrey'])
Cts3_n, Cts3_bins, Cts3_patches = plt.hist(Cts2 + Cts1, bins=10, label=lb3,
alpha=0.5, edgecolor=cs['mnk_dgrey'])
x1, y1 = prd.Gauss_hist(Cts1)
x2, y2 = prd.Gauss_hist(Cts2)
x3, y3 = prd.Gauss_hist(Cts1 + Cts2)
plt.plot(x1, y1, '-', linewidth=2, color=cs['ggred'])
plt.plot(x2, y2, '-', linewidth=2, color=cs['ggblue'])
plt.plot(x3, y3, '-', linewidth=2, color=cs['ggpurple'])
ax2.legend(loc='upper left', fancybox=True, framealpha=0.2)
os.chdir(p0)
plt.tight_layout()
plt.show()
ax2.legend(loc='upper left', fancybox=True, facecolor=(1.0, 1.0, 1.0, 0.3))
prd.PPT_save_2d(fig2, ax2, 'hists.png')
# Optimized parameters
print(res.x)
scale = res.x[0]
angle = res.x[1]
ex = res.x[2]
ey = res.x[3]
print('Scale =', np.round(scale, 3))
print('Angle =', np.round(angle * 180 / pi, 2))
print('ex =', np.round(ex, 3))
print('ey =', np.round(ey, 3))
# Calculate theoretical positions
x_theory, y_theory, error = calculate(scale, angle, ex, ey, x, y)
print('error = ', np.round(error, 3))
# Plot data
fig1 = plt.figure('fig1')
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mdk_dgrey'])
ax1.set_xlabel('x axis')
ax1.set_ylabel('y axis')
plt.plot(x, y, 'o')
plt.plot(x_theory, y_theory, '+')
show()
prd.PPT_save_2d(fig1, ax1, '2D array fit 1')
fig3 = plt.figure('fig3', figsize=(4, 4))
ax3 = fig3.add_subplot(1, 1, 1)
fig3.patch.set_facecolor(cs['mdk_dgrey'])
plt.plot(Profile1/π, '.:', c=cs[fibre_c])
ax3.set_ylabel('phase - / π')
ax3.set_xlabel('x axis - px')
plt.tight_layout()
fig4 = plt.figure('fig4', figsize=(4, 4))
ax4 = fig4.add_subplot(1, 1, 1)
fig4.patch.set_facecolor(cs['mdk_dgrey'])
ax4.set_ylabel('y axis - px')
ax4.set_xlabel('x axis - px')
l5 = plt.imshow(H2[:, :], cmap='binary')
# l6 = plt.plot(ϕ1 / π, g_ϕ1(ϕ1), '.')
# l6 = plt.plot(ϕ1 / π, g_ϕ3(ϕ1))
# datacursor(l1, bbox=dict(fc=cs['mdk_yellow'], alpha=1))
# datacursor(l4, bbox=dict(fc=cs['mdk_yellow'], alpha=1))
plt.tight_layout()
plt.show()
os.chdir(p1)
prd.PPT_save_2d(fig1, ax1, 'plot1.png')
prd.PPT_save_2d(fig2, ax2, 'plot2.png')
prd.PPT_save_2d(fig3, ax3, 'plot3.png')
prd.PPT_save_2d(fig4, ax4, 'plot4.png')
ax5.set_ylabel('y axis - μm')
ax5.set_xlabel('x axis - μm')
fig6 = plt.figure('fig6', figsize=(4, 4))
fig6.patch.set_facecolor(cs['mdk_dgrey'])
ax6 = fig6.add_subplot(1, 1, 1)
ax6.set_ylabel('y axis - μm')
ax6.set_xlabel('x axis - μm')
fig7 = plt.figure('fig7', figsize=(4, 4))
fig7.patch.set_facecolor(cs['mdk_dgrey'])
ax7 = fig7.add_subplot(1, 1, 1)
ax7.set_ylabel('y axis - μm')
ax7.set_xlabel('x axis - μm')
I, x, y = prd.holo_replay_file(files[1], p1)
np.savetxt(p0 + r'\I.csv', I, delimiter=',')
np.savetxt(p0 + r'\x.csv', x, delimiter=',')
np.savetxt(p0 + r'\y.csv', y, delimiter=',')
plt.show()
os.chdir(p0)
prd.PPT_save_2d(fig1, ax1, 'plot1.png')
prd.PPT_save_2d(fig2, ax2, 'plot2.png')
prd.PPT_save_2d(fig3, ax3, 'plot3.png')
prd.PPT_save_2d(fig4, ax4, 'plot4.png')
prd.PPT_save_2d(fig5, ax5, 'plot5.png')
prd.PPT_save_2d(fig6, ax6, 'plot6.png')
prd.PPT_save_2d(fig7, ax7, 'plot7.png')
##############################################################################
# Plot some figures
##############################################################################
prd.ggplot()
plot_path = r"D:\Python\Plots\\"
plot_label = 'Gaussian wavepacket b'
plot_file_name = plot_path + plot_label
# fig1 = plt.figure('fig1', figsize=(5, 5))
# ax1 = fig1.add_subplot(1, 1, 1)
# fig1.patch.set_facecolor(cs['mdk_dgrey'])
# ax1.set_xlabel('x axis')
# ax1.set_ylabel('y axis')
# plt.imshow(im, extent=prd.extents(x) + prd.extents(y))
###
fig1 = plt.figure('fig1', figsize=(5, 5))
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mnk_dgrey'])
ax1.set_xlabel('x axis')
ax1.set_ylabel('y axis')
plt.plot(ts, Es, '-')
plt.tight_layout()
plt.axis('off')
###
plt.savefig(plot_file_name + '.svg')
plt.show()
prd.PPT_save_2d(fig1, ax1, plot_file_name + '.png')
##############################################################################
p1 = r"C:\Users\Philip\Documents\Powerpoints\IEEE Yangzhou"
p2 = (r"C:\Users\Philip\Documents\Technical Stuff\Hologram optimisation"
r"\High frequency sin term\180228\Sin amp values")
f1 = p2 + r'\*.csv'
files = glob.glob(f1)
data_all = np.array([])
print(files)
for i1, val1 in enumerate(files[:]):
print(i1)
data = np.genfromtxt(val1, delimiter=',')
print(np.shape(data))
fig1 = plt.figure('fig1')
ax1 = fig1.add_subplot(1, 1, 1)
fig1.patch.set_facecolor(cs['mdk_dgrey'])
ax1.set_xlabel('Frequency (GHz)')
ax1.set_ylabel('Signal (dB)')
plt.plot(1.0 * data[0, :], data[1, :], '-', lw=1, c=cs['ggred'])
ax1.set_ylim([-70, -25])
plt.show()
os.chdir(p2)
prd.PPT_save_2d(fig1, ax1, str(i1))
# leg1 = plt.legend()
# leg1.get_frame().set_alpha(0.0)
##############################################################################
# Plot some figures
##############################################################################
