charmm force field develeopment based on Monte Carlo simulation

Author: asaminewbiochem

2D_generate_histogram.py

@@ -0,0 +1,70 @@
+#!/usr/bin/python
+"""
+Script: 2D_generate_histogram.py
+Author: Asaminew Aytenfisu
+Description: This script generates a histogram from data points.
+"""
+
+import argparse
+import sys
+import math
+import numpy as np
+
+def read_angles(line):
+    tokens = line.split()
+    x = float(tokens[0])
+    y = float(tokens[1])
+    return [x, y]
+
+def main(args):
+    try:
+        data_file = args.data_file
+        histogram_file = args.histogram_file
+        x_min = args.x_min
+        x_max = args.x_max
+        y_min = args.y_min
+        y_max = args.y_max
+        x_resolution = args.x_resolution
+        y_resolution = args.y_resolution 
+
+        points = [read_angles(line) for line in open(data_file)]
+        count = len(points)
+        histogram = np.zeros([x_resolution, y_resolution])
+        x_interval_length = (x_max - x_min) / x_resolution
+        y_interval_length = (y_max - y_min) / y_resolution
+        interval_surface = x_interval_length * y_interval_length
+        increment =  count / interval_surface
+
+        for i in points:
+            x = int((i[0] - x_min) / x_interval_length)
+            y = int((i[1] - y_min) / y_interval_length)
+            histogram[x,y] += increment
+
+        x_intervals = np.arange(x_min, x_max, (x_max - x_min) / x_resolution)
+        y_intervals = np.arange(y_min, y_max, (y_max - y_min) / y_resolution)
+
+        with open(histogram_file, 'w') as o:
+            for i, x in enumerate(x_intervals):
+                for j, y in enumerate(y_intervals):
+                    if histogram[i,j] != 0.0:
+                        o.write('%f %f %f \n' % (x, y,  -0.001982923700*298.0*math.log(histogram[i,j]/histogram.max())))
+                    else:
+                        o.write('%f %f %f \n' % (x, y,  99999.0))
+                o.write('\n')
+
+    except Exception as e:
+        print("Error:", e)
+        sys.exit(1)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Generate a histogram from data points")
+    parser.add_argument("data_file", help="input data file")
+    parser.add_argument("histogram_file", help="output histogram file")
+    parser.add_argument("x_min", type=float, help="minimum x value")
+    parser.add_argument("x_max", type=float, help="maximum x value")
+    parser.add_argument("y_min", type=float, help="minimum y value")
+    parser.add_argument("y_max", type=float, help="maximum y value")
+    parser.add_argument("x_resolution", type=int, help="x resolution")
+    parser.add_argument("y_resolution", type=int, help="y resolution")
+    args = parser.parse_args()
+    main(args)

README.md

@@ -1,2 +1,37 @@
-# RNA-structure
-Will be used for RNA and related structure prediction
+# RNA and related tools and codes
+
+
+## Table of Contents
+
+- [Project Name](#project-name)
+  - [Table of Contents](#table-of-contents)
+  - [About](#about)
+  - [Features](#features)
+  - [Installation](#installation)
+  - [Usage](#usage)
+  - [Contributing](#contributing)
+  - [License](#license)
+
+## About
+
+Provide more detailed information about the project. What is its purpose? Why was it created? Who is the intended audience?
+
+## Features
+
+List the key features of the project. What functionalities does it offer? What problems does it solve?
+
+## Installation
+
+Provide step-by-step instructions on how to install and set up the project. Include any prerequisites or dependencies.
+
+## Usage
+
+Explain how to use the project. Provide examples, code snippets, or screenshots if applicable.
+
+## Contributing
+
+Outline guidelines for contributing to the project. How can others contribute? What types of contributions are welcome?
+
+## License
+
+Specify the license under which the project is distributed. Include any terms and conditions.