npac_detector.machine_learning.load_model

Attributes

chemin
folder_path
file_paths
layer_nb
X_events
df_event
images
images
images
images
input_shape
latent_dim
image_input
image_input
model
reconstructed
reconstructed
im1
cbar1
im2
cbar2

Functions

event_hits_to_image(→ numpy.array)

Converts the hits of a dataframe into a 3D numpy array

Module Contents

npac_detector.machine_learning.load_model.chemin

npac_detector.machine_learning.load_model.folder_path = '/data/pion_1Gev_noShower/'

npac_detector.machine_learning.load_model.file_paths

npac_detector.machine_learning.load_model.layer_nb = 0

npac_detector.machine_learning.load_model.event_hits_to_image(df: pandas.DataFrame, n_layers=7, x_size=400, y_size=400) → numpy.array

Converts the hits of a dataframe into a 3D numpy array

Parameters:

• df – Input dataframe

• n_layers (int) – Number of layers in the detector

• x_size (int) – Number of pixels along x

• y_size (int) – Number of pixel along y

Returns:

Array of dimension (n_layers,x_size,y_size) with take the energy as the value

npac_detector.machine_learning.load_model.X_events = []

npac_detector.machine_learning.load_model.df_event = None

npac_detector.machine_learning.load_model.images

npac_detector.machine_learning.load_model.images

npac_detector.machine_learning.load_model.images

npac_detector.machine_learning.load_model.images

npac_detector.machine_learning.load_model.input_shape

npac_detector.machine_learning.load_model.latent_dim = 32

npac_detector.machine_learning.load_model.image_input

npac_detector.machine_learning.load_model.image_input

npac_detector.machine_learning.load_model.model

npac_detector.machine_learning.load_model.reconstructed

npac_detector.machine_learning.load_model.reconstructed

npac_detector.machine_learning.load_model.im1

npac_detector.machine_learning.load_model.cbar1

npac_detector.machine_learning.load_model.im2

npac_detector.machine_learning.load_model.cbar2