latest fits

Author: dil-shana

example/predict/AR/comp_norm/Rplots.pdf

@@ -9,12 +9,12 @@ data <- read.csv("predict_data_AR.csv")
 ggplot(data, aes(x = AR, y = predicted)) +
   geom_point(color = 'blue', alpha = 0.6) +  # Adds points with some transparency
   geom_abline(intercept = 0, slope = 1, color = 'red', linetype = "dashed") +  # Adds the y=x reference line
-  labs(title = "Comparison of AR values and Predicted values",
-       x = "AR values (Real)",
+  labs(
+       x = "Actual Values",
        y = "Predicted values") +
   theme_minimal() +
   theme(plot.title = element_text(hjust = 0.5))
 
 # Save the plot as a PNG file
-ggsave("ar_vs_predicted_comparison_plot.png")
+ggsave("ar_comp.png")
 

example/predict/AR/comp_norm/ar_comp.png

@@ -9,12 +9,12 @@ data <- read.csv("predict_data_AR.csv")
 ggplot(data, aes(x = AR, y = predicted)) +
   geom_point(color = 'blue', alpha = 0.6) +  # Adds points with some transparency
   geom_abline(intercept = 0, slope = 1, color = 'red', linetype = "dashed") +  # Adds the y=x reference line
-  labs(title = "Comparison of AR values and Predicted values",
-       x = "AR values (Real)",
+  labs(
+       x = "Actual Values",
        y = "Predicted values") +
   theme_minimal() +
   theme(plot.title = element_text(hjust = 0.5))
 
 # Save the plot as a PNG file
-ggsave("ar_vs_predicted_comparison_plot.png")
+ggsave("ar_uncomp.png")
 

example/predict/AR/comp_norm/plot_ar_vs_predicted.R

@@ -0,0 +1,20 @@
+
+# Load necessary libraries
+library(ggplot2)
+
+# Load the data
+data <- read.csv("predict_data_AR.csv")
+
+# Create the plot
+ggplot(data, aes(x = AR, y = predicted)) +
+  geom_point(color = 'blue', alpha = 0.6) +  # Adds points with some transparency
+  geom_abline(intercept = 0, slope = 1, color = 'red', linetype = "dashed") +  # Adds the y=x reference line
+  labs(
+       x = "Actual Values",
+       y = "Predicted values") +
+  theme_minimal() +
+  theme(plot.title = element_text(hjust = 0.5))
+
+# Save the plot as a PNG file
+ggsave("reg_comp.png")
+

example/predict/AR/uncomp_norm/Rplots.pdf

@@ -0,0 +1,11 @@
+2024-08-22 19:34:22,528 - root - INFO - The following arguments are received or filled with default values:
+Namespace(method='predict', configFile='/home/shanavas/PycharmProjects/deepFPlearn/example/success_jsonfile/regtransc_predict.json')
+2024-08-22 19:34:22,910 - tensorflow - WARNING - No training configuration found in save file, so the model was *not* compiled. Compile it manually.
+2024-08-22 19:34:22,911 - root - INFO - Adding compressed fingerprints
+2024-08-22 19:34:22,917 - root - INFO - Using input matrix of shape (5988, 2048) with type bool
+2024-08-22 19:34:22,917 - root - INFO - Compressed fingerprints are added to input dataframe.
+2024-08-22 19:34:24,293 - root - INFO - Compressed FP matrix with shape (5988, 256) and type float32
+2024-08-22 19:34:24,763 - root - INFO - Loading scaler from example/reg_transc/comp_normal/scaler.pkl
+2024-08-22 19:34:24,763 - root - INFO - Applying inverse transformation to get pre-normalized values
+2024-08-22 19:34:24,764 - root - INFO - Saving normalized predictions to /home/shanavas/PycharmProjects/deepFPlearn/example/predict/reg/reg_comp_norm_1/normalized_predictions.csv
+2024-08-22 19:34:29,010 - root - INFO - Prediction successful. Results written to '/home/shanavas/PycharmProjects/deepFPlearn/example/predict/reg/reg_comp_norm_1/predict_data_AR.csv'