get_camera3d_from_world() got an unexpected keyword argument 'phi' about deepdrr HOT 11 CLOSED

volume = deepdrr.Volume.from_nifti(path,
                                  materials ='Bone')

camera_intrinsics = deepdrr.geo.CameraIntrinsicTransform.from_sizes(
    sensor_size = 512,
    pixel_size = 0.5,
    source_to_detector_distance = 1118.38
)
center = volume.world_from_ijk @ deepdrr.geo.point(160,160,160)
carm = deepdrr.MobileCArm(isocenter=center,
                          source_to_detector_distance = 689.1,
                         min_alpha = -40,
                         max_alpha = 40,
                         # note that this would collide with the patient. Suggested to limit to +/- 45
                         min_beta = -45,
                         max_beta = 45,
                         pixel_size =0.5,
                         sensor_height =320,
                         sensor_width =320,)

alphas,betas = utils.generate_uniform_angles(
    (-40,40,40),
    (-45,45,45)
)

output_dir = Path("/root/autodl-tmp/drr_result")
output_dir.mkdir(exist_ok = True)
with deepdrr.Projector(
    volume=volume,
    carm=carm,
    step=0.1,  # stepsize along projection ray, measured in voxels
    spectrum="90KV_AL40", # energy spectrum
    photon_count=100000, # number of photons to simulate
    scatter_num=0, # number of scatter events to simulate
    neglog=True, # apply negative log transform to image (convenient for visualization)
    intensity_upper_bound=3, # Good default for windowing
    
) as projector:
    images = projector.project_over_carm_range(
          (-40,40,40),
          (-45,45,45))
    for i,image in enumerate(images):
        plt.imshow(image,cmap ='gray')
        plt.title(f'alpha,beta ={alphas[i],betas[i]}')
        display(Image.fromarray((image * 255).astype(np.uint8)))
print("###               finish               ###")

seg_array = nib.load('/root/autodl-tmp/datasets/DeepDRR_Data/CTPelvic1K_dataset6_CLINIC_0001/dataset6_CLINIC_0001_mask_4label_1.nii.gz')
print(seg_array.shape)
seg_array = seg_array.get_fdata()
volume = deepdrr.Volume.from_nifti(path,
                                   materials=dict(bone=seg_array))             
volume.supine()
carm = deepdrr.MobileCArm(isocenter=volume.center_in_world, alpha=0, beta=0, degrees=True)

with deepdrr.Projector(
    volume=volume,
    carm=carm,
    step=0.2,  # stepsize along projection ray, measured in voxels
    spectrum="90KV_AL40", # energy spectrum
    photon_count=10000, # number of photons to simulate
    scatter_num=0, # number of catter events to simulate
    collected_energy =False, # apply negative log transform to image (convenient for visualization)
    intensity_upper_bound=2, # Good default for windowing
) as projector:
    for z in range(-500, -100, 50):
        carm.move_to(isocenter_in_world=volume.center_in_world + geo.v(0, 0, z))
        print(f"Projecting at z={z}")
        image = projector.project()
        display(Image.fromarray((image * 255).astype(np.uint8)))
print("######          finish          ######")