updating README.me and including some missing scripts

README.md

@@ -5,7 +5,7 @@
       
 ## What is roost?
 
-The Python Library roost is a software package developed by UC3M. The roost is a tool for robust flight planning within the currently structured airspace. The main features of roost are: 1) integrates horizontal and vertical decision-making, 2) fast performance thanks to GPU-based parallelization, 3) considers climb, cruise, and descent phases
+The Python Library roost is a software package developed by UC3M. It is a tool for robust flight planning within the currently structured airspace. The main features of roost are: 1) integrates horizontal and vertical decision-making, 2) fast performance thanks to GPU-based parallelization, 3) considers climb, cruise, and descent phases
 4) incorporate uncertainty in meteorological variables, as well as initial flight time and initial flight mass. 
 
 **License:** roost is released under GNU Lesser General Public License v3.0 (LGPLv3). 
@@ -24,15 +24,15 @@ The installation is the first step to working with roost. In the following, the
 conda create -n env_roost
 conda activate env_roost
 ```
-1. Clone or download the repository. The roost source code is available on a public GitHub repository: XXX. The easiest way to obtain it is to clone the repository using git: git clone XXX.
+1. Clone or download the repository. The roost source code is available on a public GitHub repository: https://github.com/Abolfazl-Simorgh/roost. The easiest way to obtain it is to clone the repository using git: git clone https://github.com/Abolfazl-Simorgh/roost.git.
 
 2. Locate yourself in the roost (library folder) path, and run the following line, using terminal (MacOS and Linux) or cmd (Windows), which will install all dependencies:
 ```python
 python setup.py install
 ```
-it will install all required dependency.
+it will install all the required dependencies.
 
 ## How to use it
-There is a script in the roost (library folder) path, *main_run.py*, which provides a sample to get started with the library. This sample file contains some comments explaining the required inputs, problem configurations, selection of objective function (which includes flight planning objectives), optimization configurations, running, and output files. Notice that, in order to use roost for optimizing aircraft trajectories, the BADA4.0 license is required, and the script bada4.py needs to be included in the directory of the library.
+There is a script in the roost (library folder) path, *main_run.py*, which provides a sample to get started with the library. This sample file contains comments explaining the required inputs, problem configurations, objective function selection (which includes flight planning objectives), optimization configurations, running, and output files. Notice that we use BADA4.0 to represent the aerodynamic and propulsive performance of the aircraft. Due to restrictions imposed by the BADA license, the current version in GitHub is incomplete, as three python scripts related to the used aircraft performance model have been excluded (i.e., bada4.py, apm.py, and badalib.cu). We are currently assessing the existing open-source aircraft performance models in order to make the complete library available to the public. 
 
 

main_run.py

@@ -16,7 +16,7 @@
 # Filter the dataset to the required variables
 dsc = ds[['t', 'u', 'v', 'z', 'r', 'pv', 'C1', 'C2', 'olr', 'aCCF_CH4']]
 
-# Information of the considered aircraft (notice that the user needs to input s .xml file)
+# Input Aircraft Performance Datasets:
 apm = BADA4_jet_CR('A320-214', full_path='A320-214.xml')
 
 # New coordinates for processing the input meteorological data
@@ -61,7 +61,7 @@
 # If yes, the climate impact is considered as an objective in the objective function to be optimized
 problem_config['compute_accf'] = True
 
-# # If yes, the NOx emission is considered as an objective in the objective function to be optimized
+# If yes, the NOx emission is considered as an objective in the objective function to be optimized
 problem_config['compute_emissions'] = True
 
 
@@ -80,10 +80,10 @@
 # Weights ATR of H2O in the objective function 
 problem_config['CI_h2o'] = 1
 
-# Weights ATR of Contrails in the objective function 
+# Weights ATR of contrails in the objective function
 problem_config['CI_contrail'] = 1
 
-# Weights distance flown in persistent contrails formation areas in the objective function 
+# Weights the distance flown in persistent contrails formation areas in the objective function 
 problem_config['CI_contrail_dis'] = 0
 
 

roost/airspace.py

@@ -3,7 +3,7 @@
 
 import pandas as pd
 from typing import Sequence
-from roc3.geometry import *
+from roost.geometry import *
 import networkx as nx
 import matplotlib.pyplot as plt
 import networkx.readwrite as rw

roost/codegen.py

@@ -3,7 +3,7 @@
 
 import os
 import re
-from roc3.bada4 import BADA4_jet_CR as jet
+from roost.bada4 import BADA4_jet_CR as jet
 from jinja2 import Template, Environment, StrictUndefined, UndefinedError
 from pathlib import Path
 

roost/constants.py

@@ -0,0 +1,97 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import numpy as np
+# Unless specified otherwise, all units are SI
+
+#: :obj:`float` :
+#: kappa = 1.4
+kappa = 1.4
+
+#: :obj:`float` :
+#: Rg = 287.05287
+Rg = 287.05287
+
+#: :obj:`float` :
+#: ft = 0.3048
+ft = 0.3048
+
+#: :obj:`float` :
+#: m2ft = ft**-1
+m2ft = ft**-1
+
+#: :obj:`float` :
+#: T0_MSL = 288.15
+T0_MSL = 288.15
+
+#: :obj:`float` :
+#: P0_MSL = 101325.0
+P0_MSL = 101325.0
+
+#: :obj:`float` :
+#: rho0_MSL = 1.225
+rho0_MSL = 1.225
+
+#: :obj:`float` :
+#: a0_MSL = 340.294
+a0_MSL = 340.294
+
+#: :obj:`float` :
+#: nmi = 1852.0
+nmi = 1852.0
+
+#: :obj:`float` :
+#: kt = nmi/3600
+kt = nmi/3600
+
+#: :obj:`float` :
+#: ms2kt = 1/kt
+ms2kt = 1/kt
+
+#: :obj:`float` :
+#: g0 = g = 9.80665
+g0 = g = 9.80665
+
+#: :obj:`float` :
+#: lapse_rate_troposphere = -0.0065
+lapse_rate_troposphere = -0.0065
+
+#: :obj:`float` :
+#: R_mean = 6356.8e3
+R_mean = 6356.8e3
+
+#: :obj:`float` :
+#: d2r = np.pi/180
+d2r = np.pi/180
+
+#: :obj:`float` :
+#: flattening = 1/298.257223563
+flattening = 1/298.257223563
+
+#: :obj:`float` :
+#: first_eccentricity = (flattening*(2 - flattening))**0.5
+first_eccentricity = (flattening*(2 - flattening))**0.5
+
+#: :obj:`float` :
+#: R_a = 6378.137e3
+R_a = 6378.137e3
+
+#: :obj:`float` :
+#: R_b = 6356.752
+R_b = 6356.752
+
+#: :obj:`float` :
+#: h_tropopause = 11e3
+h_tropopause = 11e3
+
+#: :obj:`float` :
+#: T_tropopause = 216.65
+T_tropopause = 216.65
+
+#: :obj:`float` :
+#: minute = np.timedelta64(1, 'm').astype('timedelta64[ns]')
+minute = np.timedelta64(1, 'm').astype('timedelta64[ns]')
+
+#: :obj:`float` :
+#: hour = np.timedelta64(1, 'h').astype('timedelta64[ns]')
+hour = np.timedelta64(1, 'h').astype('timedelta64[ns]')