ae_toolbox_torch/viz/viz_map.py
2019-09-13 13:36:13 +02:00

51 lines
1.3 KiB
Python

from dataset import *
# Plotting
# import matplotlib as mlp
from matplotlib import pyplot as plt
from matplotlib.patches import Polygon
from matplotlib.collections import LineCollection, PatchCollection
import matplotlib.colors as mcolors
import matplotlib.cm as cmaps
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
import seaborn as sns
from argparse import ArgumentParser
from viz.utils import search_for_weights
from run_models import *
sns.set()
arguments = ArgumentParser()
arguments.add_argument('--data', default=os.path.join('data', 'validation'))
dataset = DataContainer(os.path.join(os.pardir, 'data', 'validation'), 9, 6).to(device)
dataloader = DataLoader(dataset, shuffle=True, batch_size=len(dataset))
def viz_map(self, base_map: MapContainer):
# Base Map Plotting
# filled Triangle
patches = [Polygon(base_map.get_triangle_by_key(i), True, color='k') for i in range(len(base_map))]
patch_collection = PatchCollection(patches, color='k')
self.ax.add_collection(patch_collection)
print('Basemap Plotted')
patches = [Polygon(base_map.get_triangle_by_key(i), True, color='k') for i in range(len(base_map))]
return PatchCollection(patches, color='k')
def load_and_predict(folder):
pass
if __name__ == '__main__':
search_for_weights(load_and_predict, arguments.data)
# ToDo: THIS