Merge pull request #10 from XanaduAI/improvements-to-plots

Improvements to plots while polishing the paper

Author: mariaschuld

README.md

@@ -176,10 +176,10 @@ generate results for a hyperparameter search for any model and dataset. The scri
 can be run as
 
 ```
-python run_hyperparameter_search.py --classifier-name "DataReuploadingClassifier" --dataset-path "dataset.csv"
+python run_hyperparameter_search.py --classifier-name "DataReuploadingClassifier" --dataset-path "my_dataset.csv"
 ```
 
-where `dataset.csv` is a CSV file containing the training data, where each column is a feature
+where `my_dataset.csv` is a CSV file containing the training data such that each column is a feature
 and the last column is the target.
 
 Unless otherwise specified, the hyperparameter grid is loaded from `qml_benchmarks/hyperparameter_settings.py`.
@@ -190,7 +190,7 @@ For example, for the `DataReuploadingClassifier` we can run:
 ```
 python run_hyperparameter_search.py \
     --classifier-name DataReuploadingClassifier \
-    --dataset-path "../paper/benchmarks/hidden_manifold/hidden_manifold-6manifold-2d_train.csv" \
+    --dataset-path "my_dataset.csv" \
     --n_layers 1 2 \
     --observable_type "single" "full"\
     --learning_rate 0.001 \

paper/benchmarks/generate_two_curves.py

@@ -21,7 +21,7 @@
 
 np.random.seed(3)
 
-os.makedirs("two_curves", exist_ok=True)
+os.makedirs("two_curves_diff", exist_ok=True)
 
 n_samples = 300
 degree = 5
@@ -32,11 +32,11 @@
     X, y = generate_two_curves(n_samples, n_features, degree, offset, noise)
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
 
-    name_train = f"two_curves/two_curves-5degree-0.1offset-{n_features}d_train.csv"
+    name_train = f"two_curves_diff/two_curves-5degree-0.1offset-{n_features}d_train.csv"
     data_train = np.c_[X_train, y_train]
     np.savetxt(name_train, data_train, delimiter=",")
 
-    name_test = f"two_curves/two_curves-5degree-0.1offset-{n_features}d_test.csv"
+    name_test = f"two_curves_diff/two_curves-5degree-0.1offset-{n_features}d_test.csv"
     data_test = np.c_[X_test, y_test]
     np.savetxt(name_test, data_test, delimiter=",")
 

paper/plots/datasets-for-plots/hidden_manifold_model/hidden_manifold-6manifold-10d_test.csv

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