def get_rfs(inputs, voxels, mods, approx_n = GRAD_APPROX_N):
manager, grads = backprop_fields.gradients_raw_fullbatch(
model, inputs, voxels, mods = mods,
approx_n = approx_n)
estimated = backprop_fields.parameter_estimates_grads(grads, voxels)
params = estimates_to_params(estimated)
return manager, grads, params
full.to_csv(filename)
def load_bbox_csv(filename):
df = pd.read_csv(filename)
voxels = vx.VoxelIndex.from_serial(df['unit'])
bboxes = {}
layer_strs = map(df['unit'], lambda s: s.split(';')[1])
for l_str, group in df.groupby(layer_strs):
layer = tuple(int(i) for i in l_str.split('.'))
# bboxes[layer] is expected to have shape ([left, top, w, h], n_vox)
bboxes[layer] = group[['x', 'y', 'var', 'amp']].as_matrix()
return bboxes
if __name__ == '__main__':
model, ckpt = cornet.load_cornet("Z")
inputs = backprop_fields.noise_video(11, 3, 256, 256, numpy=False)
manager = nm.NetworkManager.assemble(model, inputs)
voxel = {(0, 1, 0): vx.VoxelIndex((0, 1, 0), ([1], [50], [30]))}
_, grads = backprop_fields.gradients_raw_fullbatch(model, inputs, voxel)
rfbb = trace_rf(sequential_leaves(manager, stop=(0, 1, 0)), manager)
rfbb = (30 * rfbb[0][1] - rfbb[1][1], 50 * rfbb[0][0] - rfbb[1][0],
rfbb[1][1] * 2 + 1, rfbb[1][0] * 2 + 1)
backprop_fields.grad_plot(grads, [(0, 1, 0)], 0, 0, bbox=rfbb)
video_gen.rf_slider_check(frame, check_widths=[50, 30, 5], speed=8),
'color':
video_gen.color_rotation(frame, 128),
'orientation':
video_gen.sine_rotation(frame, 64, freqs=[5, 20])
}
# ---- Compute Receptive fields, etc. ----
results = {}
for k, inp in inputs.items():
manager = nm.NetworkManager.assemble(model, inp)
bboxes = possible_fields.rf_bboxes(voxels, manager)
print("\n[ Gradients: {} ]".format(k))
_, grads = bf.gradients_raw_fullbatch(model, inp, voxels, approx_n=30)
params = bf.parameter_estimates_grads(grads, voxels)
true_acts, pred_acts = lsq_fields.voxel_activity(
voxels, manager, inp.numpy(), params)
results[k] = {
'grad': grads,
'params': params,
'true_acts': true_acts,
'pred_acts': pred_acts,
}
# ---- Saving & Plotting RF Diagnostics ----
print("Saving and Plotting")