Move plotting code to folder

benchmarking.py

@@ -1,8 +1,4 @@
-from pyro.infer.autoguide import AutoNormal
-from DataGenModel import DataGenModel
-from data.synthetic import generate_wty_linear_scalar_data, generate_wty_linear_multi_w_data
-from data.whynot_simulators import generate_lalonde_random_outcome
-from models import linear_gaussian_full_model, linear_gaussian_outcome_model, linear_multi_w_outcome_model, VAE
+from data.synthetic import generate_wty_linear_multi_w_data
 import numpy as np
 import pandas as pd
 import whynot as wn
@@ -11,7 +7,7 @@
 
 import seaborn as sns; sns.set()
 import matplotlib.pyplot as plt
-from plotting import save_and_show
+from plotting.plotting import save_and_show
 
 ATE_ESTS = 'ate_ests'
 COVERAGE_COUNT = 'coverage_count'

models/base.py

@@ -7,9 +7,8 @@
 from typing import Type
 
 from models.preprocess import Preprocess, PlaceHolderTransform
-from plotting import compare_joints, compare_bivariate_marginals
-from utils import T, Y, to_np_vectors, to_np_vector, to_torch_variable, permutation_test, regular_round, get_duplicates
-
+from plotting.plotting import compare_joints, compare_bivariate_marginals
+from utils import T, Y, to_np_vectors, to_np_vector, to_torch_variable, permutation_test, regular_round
 
 MODEL_LABEL = "model"
 TRUE_LABEL = "true"

models/nonlinear.py

@@ -7,7 +7,7 @@
 from torch import nn
 from torch.utils import data
 from itertools import chain
-from plotting import fig2img
+from plotting.plotting import fig2img
 from tqdm import tqdm
 from contextlib import contextmanager
 

plotting.py → plotting/plotting.py

@@ -10,7 +10,7 @@
 
 FIGSIZE = [12, 5]
 SINGLE_FIGSIZE = [5.5, 5]
-DIR = 'plots'
+DIR = '../plots'
 DPI = 300