fix download instruction from LUDB database

data/ludb/download_ludb.py

@@ -4,10 +4,8 @@
 The database consists of 200 10-second 12-lead ECG signal records representing different morphologies of the ECG signal. The ECGs were collected from healthy volunteers and patients, which had various cardiovascular diseases. The boundaries of P, T waves and QRS complexes were manually annotated by cardiologists for all 200 records.
 
 Steps:
-    1. In the command line, run 'pip install gsutil'
-    2. Then, 'gsutil -m cp -r gs://ludb-1.0.0.physionet.org D:/YOURPATH/NeuroKit/data/ludb'
-    This will download all the files in a folder named 'ludb-1.0.0.physionet.org' at the
-    destination you entered.
+    1. Download zipped data base from https://physionet.org/content/ludb/1.0.1/ 
+    2. Unzip the folder so that you have a `lobachevsky-university-electrocardiography-database-1.0.1/` folder'
     3. Run this script.
 """
 import pandas as pd
@@ -16,31 +14,33 @@
 import os
 
 
-files = os.listdir("./ludb-1.0.0.physionet.org/")
-
 dfs_ecg = []
 dfs_rpeaks = []
 
 
 for participant in range(200):
     filename = str(participant + 1)
 
-    data, info = wfdb.rdsamp("./ludb-1.0.0.physionet.org/" + filename)
+    data, info = wfdb.rdsamp(
+        "./lobachevsky-university-electrocardiography-database-1.0.1/data/" + filename
+    )
 
     # Get signal
     data = pd.DataFrame(data, columns=info["sig_name"])
     data = data[["i"]].rename(columns={"i": "ECG"})
-    data["Participant"] = "LUDB_%.2i" %(participant + 1)
+    data["Participant"] = "LUDB_%.2i" % (participant + 1)
     data["Sample"] = range(len(data))
-    data["Sampling_Rate"] = info['fs']
+    data["Sampling_Rate"] = info["fs"]
     data["Database"] = "LUDB"
 
     # Get annotations
-    anno = wfdb.rdann("./ludb-1.0.0.physionet.org/" + filename, 'atr_i')
+    anno = wfdb.rdann(
+        "./lobachevsky-university-electrocardiography-database-1.0.1/data/" + filename, "i"
+    )
     anno = anno.sample[np.where(np.array(anno.symbol) == "N")[0]]
     anno = pd.DataFrame({"Rpeaks": anno})
-    anno["Participant"] = "LUDB_%.2i" %(participant + 1)
-    anno["Sampling_Rate"] = info['fs']
+    anno["Participant"] = "LUDB_%.2i" % (participant + 1)
+    anno["Sampling_Rate"] = info["fs"]
     anno["Database"] = "LUDB"
 
     # Store with the rest