from pynet import NetParameters from pynet.datasets import DataManager, fetch_registration from pynet.utils import setup_logging from pynet.interfaces import (VoxelMorphNetRegister, ADDNetRegister, VTNetRegister, RCNetRegister) import pynet from pynet.models.voxelmorphnet import FlowRegularizer from pynet.models.vtnet import ADDNetRegularizer from torch.optim import lr_scheduler from pynet.plotting import plot_history from pynet.history import History from pynet.losses import MSELoss, NCCLoss, RCNetLoss, PCCLoss from pynet.plotting import Board, update_board import matplotlib.pyplot as plt setup_logging(level="debug") logger = logging.getLogger("pynet") losses = pynet.get_tools(tool_name="losses") outdir = "/neurospin/nsap/tmp/registration" data = fetch_registration(datasetdir=outdir) manager = DataManager(input_path=data.input_path, metadata_path=data.metadata_path, number_of_folds=2, batch_size=8, sampler="random", stratify_label="studies", projection_labels={"studies": ["abide"]}, test_size=0.1, add_input=True, sample_size=0.1)
from pynet.utils import setup_logging from pynet.metrics import SKMetrics from pynet.plotting import Board, update_board from mne.viz import circular_layout, plot_connectivity_circle import collections import torch import torch.nn as nn from torch.optim import lr_scheduler import scipy from scipy.stats.stats import pearsonr import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt setup_logging(level="info") logger = logging.getLogger("pynet") # Load the data outdir = "/tmp/graph_connectome" (injury, x_train, y_train, x_test, y_test, x_valid, y_valid) = get_fetchers()["fetch_connectome"](outdir) labels = [str(idx) for idx in range(1, x_train.shape[-1] + 1)] for name, (x, y) in (("train", (x_train, y_train)), ("test", (x_test, y_test)), ("validation", (x_valid, y_valid))): print("{0}: x {1} - y {2}".format(name, x.shape, y.shape)) # View the realistic base connectome and the injury signatures. plt.figure(figsize=(16, 4)) plt.subplot(1, 3, 1) plt.imshow(injury.X_mn, interpolation="None")