for ii in range(19,20):
fig = plt.figure(figsize=(16,10),constrained_layout=False)
# gs0 = fig.add_gridspec(1,2,width_ratios=[1.5,3],right=0.93,left=0.01,top=0.99,bottom=0.03)
# ax_video = fig.add_subplot(gs0[0])
# gs1 = gs0[1].subgridspec(2, 1,hspace=0.02)
# ax_green = fig.add_subplot(gs1[0])
# ax_red = fig.add_subplot(gs1[1])
gs_left = 0.01
gs_right = 0.93
gs_top = 0.95
gs_bottom = 0.06
gs = fig.add_gridspec(nrows=10, ncols=4, left=gs_left, right=gs_right,bottom=gs_bottom,top=gs_top,
hspace=0.08)
ax_video = fig.add_subplot(gs[:, :1])
ax_green = fig.add_subplot(gs[:5, 1:])
ax_red = fig.add_subplot(gs[5:, 1:])
ax_video.imshow(video_frame_cube[:,:,:,ii])
ax_video.axvline(slit_pos,color="red",lw=2,alpha=0.7)
ax_video.text(0.5,1.02,"i={:03d} {}".format(ii,video_time_array[ii]),transform=ax_video.transAxes,fontsize=14,ha="center",va="bottom")
ax_video.axis("scaled")
ax_video.tick_params(left=False,bottom=False,labelleft=False,labelbottom=False)
green_nearest_fname = totality_green_df.loc[(totality_green_df['date-obs']
- video_time_array[ii]).abs().idxmin(),"file"]
red_nearest_fname = totality_red_df.loc[(totality_red_df['date-obs']
- video_time_array[ii]).abs().idxmin(),"file"]
green_frame = CCDData.read(os.path.join(green_path,green_nearest_fname),unit="adu")
red_frame = CCDData.read(os.path.join(red_path,red_nearest_fname),unit="adu")
green_image = green_frame.data[300:750,:]/green_frame.header["EXPTIME"]
red_image = red_frame.data[300:750,:]/red_frame.header["EXPTIME"]
norm_green = ImageNormalize(green_image,stretch=LogStretch())
norm_red = ImageNormalize(red_image,stretch=LogStretch())
im_green = ax_green.pcolormesh(np.arange(green_frame.header["NAXIS1"]),np.arange(450)+300,
green_image,cmap=cmcm.lajolla,norm=norm_green,shading='auto',rasterized=True)
im_red = ax_red.pcolormesh(np.arange(red_frame.header["NAXIS1"]),np.arange(450)+300,
red_image,cmap=cmcm.lajolla,
norm=norm_red,shading='auto',rasterized=True)
ax_green.text(0.5,1.02,"Green Detector {}\n{}".format(green_frame.header["DATE-OBS"],green_nearest_fname),
transform=ax_green.transAxes,va="bottom",ha="center",fontsize=14)
ax_red.text(0.5,1.02,"Red Detector {}\n{}".format(red_frame.header["DATE-OBS"],red_nearest_fname),
transform=ax_red.transAxes,va="bottom",ha="center",fontsize=14)
clb_green_ax = inset_axes(ax_green,width="3%",height= "100%",loc='lower left',
bbox_to_anchor=(1.02, 0., 1, 1),
bbox_transform=ax_green.transAxes,
borderpad=0)
clb_green = plt.colorbar(im_green,pad = 0.05,orientation='vertical',
ax=ax_green,cax=clb_green_ax)
clb_red_ax = inset_axes(ax_red,width="3%",height= "100%",loc='lower left',
bbox_to_anchor=(1.02, 0., 1, 1),
bbox_transform=ax_red.transAxes,
borderpad=0)
clb_red = plt.colorbar(im_red,pad = 0.05,orientation='vertical',
ax=ax_red,cax=clb_red_ax)
for ax_ in (ax_green, ax_red):
ax_.axis("scaled")
ax_.tick_params(labelsize=14)
for ax_ in (clb_green_ax, clb_red_ax):
ax_.yaxis.set_major_locator(FixedLocator([1e2,1e3,1e4,1e5]))
ax_.yaxis.set_major_formatter(FixedFormatter((r"10^2",r"$10^3$",r"$10^4$",r"$10^5$")))
y_minor = LogLocator(base = 10.0, subs = np.arange(1.0, 10.0) * 0.1, numticks = 10)
ax_.yaxis.set_minor_locator(y_minor)
# ax_.yaxis.set_minor_locator(AutoMinorLocator(10))
ax_.tick_params(labelsize=14)
ax_green.set_ylabel("CCD-Y [Pixel]",fontsize=14)
ax_red.set_xlabel("CCD-X [Pixel]",fontsize=14)
ax_red.set_ylabel("CCD-Y [Pixel]",fontsize=14)
plt.tight_layout()
plt.savefig(fname=os.path.join("../../sav/Eclipse/Video_Comb/","Video_Comb_test.png".format(ii)),format="png",
dpi=120)