Simplify testing file

hawk/processes/simulation_interactive.py

@@ -1,46 +1,21 @@
-import numpy as np
-import pandas as pd
 from birdy import WPSClient
 
-# ----------- Generate some data -----------
-np.random.seed(0)
-n = 1000  # number of samples
-m = 15  # number of features
-
-data = {}
-for i in range(1, m + 1):
-    data[f"x{i}"] = np.random.normal(size=n)
-
-target_name = "target"
-data[target_name] = sum(data.values()) + np.random.normal(size=n)
-
-data = pd.DataFrame(data)
-
-n_test = int(0.20 * n)
-n_train = n - n_test
-data_test = data[n_train:]
-data = data[:n_train]
-
-data.head()
-
-
-train_file_path = "./train_dataset.csv"
-test_file_path = "./test_dataset.csv"
-data.to_csv(train_file_path, index=False)
-data_test.to_csv(test_file_path, index=False)
+train_file_path = "Emiliani1_train.csv"
+test_file_path = "Emiliani1_test.csv"
+target_column_name = "cyclostationary_mean_rr_4w_1"
 
 # ----------------- WPS -----------------
 
-wps = WPSClient("http://localhost:5000/wps", verify=False)
+wps = WPSClient("http://localhost:5002/wps", verify=False)
 help(wps)
 
 # Input some data for the causal process
 resp = wps.causal(
-    dataset_train=train_file_path,
-    dataset_test=test_file_path,
-    target_column_name=target_name,
+    dataset_train=open(train_file_path),
+    dataset_test=open(test_file_path),
+    target_column_name=target_column_name,
     pcmci_test_choice="ParCorr",
-    pcmci_max_lag="1",
+    pcmci_max_lag="0",
     tefs_direction="both",
     tefs_use_contemporary_features="Yes",
     tefs_max_lag_features="1",