diff --git a/Neural_Network_Analysis.py b/Neural_Network_Analysis.py
index 9fb53b8..9f6aaf8 100644
--- a/Neural_Network_Analysis.py
+++ b/Neural_Network_Analysis.py
@@ -11,7 +11,7 @@ import matplotlib.pyplot as plt
# path to json file that stores MFCCs and subject labels for each processed sample
DATA_PATH = str(Path.cwd()) + "/mfcc_data.json"
-def load_data(data_path):
+def load_data_from_json(data_path):
with open(data_path, "r") as fp:
data = json.load(fp)
@@ -30,6 +30,7 @@ def load_data(data_path):
return X, y
+
def plot_history(history):
"""Plots accuracy/loss for training/validation set as a function of the epochs
:param history: Training history of model
diff --git a/README.md b/README.md
index 7391d0c..e5f246e 100644
--- a/README.md
+++ b/README.md
@@ -23,10 +23,15 @@ Scripts to handle CSV files composed by 2 * 8 EMG sensors(left & right) devided
## Table of Contents
-| File and classes | Description and help functions |
-|-----------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Handle_emg_data.py: - Data_container - CSV_handler - NN_handler | Handles, manipulates, and stores data for analysis. - Data_container is a class that describes the data for each subject in the experiment. Use __init__. - CSV_handler takes data from CSV files and places it in Data_container for each subject. Use load_data() to load csv data into data containers and add the containers to the CSV_handler's 'data_container_dict', indexed by subject number. Use get_data() to retrieve specific data. - NN_handler prepares data for further analysis in Neural Networks. This class has storage for this data and/or can save it to a json file. |
-| Signal_prep.py | |
-| Present_data.py | |
-| Neural_Network_Analysis.py | |
+| File and classes | Description and help functions |
+|---|---|
+| Handle_emg_data.py:
* Data_container
* CSV_handler
* NN_handler | Handles, manipulates, and stores data for analysis.
* Data_container is a class that describes the data for each subject in the experiment.
* CSV_handler takes data from CSV files and places it in Data_container for each subject.
Use load_data() to load csv data into data containers and add the containers to the
CSV_handler's 'data_container_dict', indexed by subject number. Use get_data() to retrieve
specific data.
* NN_handler prepares data for further analysis in Neural Networks. This class has storage
for this data and/or can save it to a json file. |
+| Signal_prep.py | Does mapping to data and contains various functions. Among others, this contains wavelet,
MFCC, cepstrum and normalization. |
+| Present_data.py | Contains plot and case functions. Case functions combines many elements from the code and
presents some results described. |
+| Neural_Network_Analysis.py | Contains functions to load, build and execute analysis with Neural Networks. Main functions are
load_data_from_json(), build_model(), and main() |
+
+
+
+
+