Tabulated Data Added

README.md

@@ -5,12 +5,14 @@ Contents:
   - Atmospheric Model up to 110km
   - Accurate Calculations for Temperature, Pressure and Density
   - Custom defined atmospheric conditions
+  - Tabulate your data to save future computation time
+  - Save tabulated data in .csv or .xlsx files
 
 
 With this module, it is possible to calculate, using the 1976 standard atmosphere model, the Temperature,
 Density and Pressure at any point in the atmosphere from 0 up to 110,000 [m].
 
-This package is useful for Aerospace and Aeronautical Engineers who wish to run simulations.
+This package is useful for Aerospace and Aeronautical Engineers who wish to run simulations using atmospheric data.
 
 To use this package, follow these steps:
 

isacalc/__init__.py

@@ -1 +1,2 @@
 from isacalc.main_executable import calculate_at_h, get_atmosphere
+from isacalc.table_maker import tabulate

isacalc/src/atmosphere.py

@@ -34,17 +34,35 @@ def __init__(self, *args, **kwargs):
         self.__layers = []
         self.__build()
 
+    def get_height_boundaries(self):
+        """
+        Method to calculate for which range the atmosphere model can be used
+        :return: Min, Max Height
+        """
+        return self.__Hn[0], self.__Hn[-1]
 
     @staticmethod
     def __get_lapse(Hn, Tn) -> list:
+        """
+        Static Method to calculate the layer types of all layers
+        :param Hn: Heights
+        :param Tn: Temperatures
+        :return: Layer Types
+        """
 
         types = []
 
         for i in range(len(Hn)-1):
-            lapse = (Tn[i+1] - Tn[i])/(Hn[i+1] - Hn[i])
+            delta_T = Tn[i+1] - Tn[i]
+
+            lapse = delta_T/(Hn[i+1] - Hn[i])
 
             if lapse != 0:
-                types.append(1)
+                if abs(delta_T) > 0.5:
+                    types.append(1)
+
+                else:
+                    types.append(0)
 
             elif lapse == 0:
                 types.append(0)
@@ -95,9 +113,12 @@ def calculate(self, h) -> list:
             if h == self.__Hn[idx+1]:
                 return self.__layers[idx].get_ceiling_values()
 
+            elif h == self.__Hn[idx]:
+                return self.__layers[idx].get_base_values()
+
             elif self.__Hn[idx] < h < self.__Hn[idx + 1]:
                 return self.__layers[idx].get_intermediate_values(h)
 
-            elif h >= self.__Hn[idx + 1]:
+            elif h > self.__Hn[idx + 1]:
                 continue
 

isacalc/src/layers.py

@@ -7,7 +7,7 @@ class Layer(object):
     """
 
     def __init__(self, base_height: float, base_temperature: float, base_pressure: float, base_density: float,
-                 max_height: float, name: str = ''):
+                 max_height: float, name: str = '', **kwargs):
         """
         All Properties of a layer, excluding its type, which will be expressed
         by making separate objects for the different layers
@@ -18,9 +18,21 @@ def __init__(self, base_height: float, base_temperature: float, base_pressure: f
         :param max_height:          Height up to which the layer extends
         """
 
-        self.g0 = 9.80665
-        self.R = 287.0
-        self.gamma = 1.4
+        if kwargs:
+            try:
+                self.g0 = kwargs['g0']
+                self.R = kwargs['R']
+                self.gamma = kwargs['gamma']
+
+            except KeyError:
+                self.g0 = 9.80665
+                self.R = 287.0
+                self.gamma = 1.4
+
+        else:
+            self.g0 = 9.80665
+            self.R = 287.0
+            self.gamma = 1.4
 
         self.__h0 = base_height
         self.__T0 = base_temperature
@@ -99,14 +111,16 @@ def __init__(self, base_height: float,
                  base_pressure: float,
                  base_density: float,
                  max_height: float,
-                 name: str = ''):
+                 name: str = '',
+                 **kwargs):
 
         super().__init__(base_height=base_height,
                          base_temperature=base_temperature,
                          base_pressure=base_pressure,
                          base_density=base_density,
                          max_height=max_height,
-                         name=name)
+                         name=name,
+                         **kwargs)
 
     def get_ceiling_values(self) -> list:
         """
@@ -160,14 +174,16 @@ def __init__(self, base_height: float,
                  base_density: float,
                  max_height: float,
                  top_temperature: float,
-                 name: str = ''):
+                 name: str = '',
+                 **kwargs):
 
         super().__init__(base_height=base_height,
                          base_temperature=base_temperature,
                          base_pressure=base_pressure,
                          base_density=base_density,
                          max_height=max_height,
-                         name=name)
+                         name=name,
+                         **kwargs)
 
         self.__T_top = top_temperature
 

isacalc/table_maker.py

@@ -0,0 +1,98 @@
+import numpy as np
+import pandas as pd
+from isacalc.main_executable import get_atmosphere, calculate_at_h
+
+
+def __extract_desired_params(boolean_list: list, parameter_list: list):
+    """
+    Function which takes 2 lists, one with booleans and one with any other data types.
+    Returns a list with all values of the parameter list which had the same indices as
+    the True booleans in the boolean list
+    :param boolean_list:    List of True or False
+    :param parameter_list:  List of parameters
+    :return: List of parameters that coincide with True items in boolean list
+    """
+
+    if len(boolean_list) != len(parameter_list):
+        raise IndexError("Input sizes do not match")
+
+    result = []
+
+    for boolean, item in zip(boolean_list, parameter_list):
+        if boolean is True:
+            result.append(item)
+
+    return result
+
+
+def tabulate(height_range: tuple, atmosphere_model=get_atmosphere(), export_as: str = '', params: list = []):
+    """
+    Function to tabulate all the calculated data.
+    For large projects where the ISA data needs to be calculated and accessed a lot, this will be
+    a beneficial tradeoff of space against time. Storing in a csv or xlsx file is optional
+    :param height_range:        Range of heights, (start, stop, step) format is required
+    :param atmosphere_model:    Model on which the computations need to be performed
+    :param export_as:           If left blank, will not be saved to file
+    :param params:              List of all desired parameters to be recorded
+    :return:                    Numpy Array of all values calculated [Height, Temp, Press, Dens, SOS, Visc]
+    """
+
+    param_names = ['Temperature [K]',
+                   'Pressure [Pa]',
+                   'Density [kg/m^3]',
+                   'Speed of Sound [m/s]',
+                   'Dynamic Viscosity [kg/(m*s)]']
+
+    start, stop, step = height_range
+    heights = np.arange(start=start, stop=stop+step, step=step)
+
+    params = [a.lower() for a in params if type(a) == str and len(params) != 0]
+
+    boolean_record_list = [True]*5
+
+    if params:
+        if 't' not in params:
+            boolean_record_list[0] = False
+
+        if 'p' not in params:
+            boolean_record_list[1] = False
+
+        if 'd' not in params:
+            boolean_record_list[2] = False
+
+        if 'a' not in params:
+            boolean_record_list[3] = False
+
+        if 'mu' not in params:
+            boolean_record_list[4] = False
+
+    table_shape = (len(heights), sum(boolean_record_list)+1)
+    result = np.zeros(table_shape, dtype=float)
+
+    for idx, height in enumerate(heights):
+
+        parameters = __extract_desired_params(boolean_record_list, list(calculate_at_h(height, atmosphere_model=atmosphere_model)))
+        result[idx,:] = [height] + parameters
+
+    if export_as:
+
+        param_names = __extract_desired_params(boolean_record_list, param_names)
+
+        extension = export_as.split('.')[-1]
+
+        df_result = pd.DataFrame(data=result,
+                                 index=range(0, table_shape[0]),
+                                 columns=['Height [m]']+param_names)
+
+        if extension == 'csv':
+            df_result.to_csv(export_as)
+
+        else:
+            df_result.to_excel(export_as)
+
+    return result
+
+
+if __name__ == "__main__":
+
+    table = tabulate((0, 110000, 100), export_as=r'test1.csv', params=['T', 'mu', 'p'])

setup.py

@@ -9,17 +9,17 @@ def readme():
 setup(
   name = 'isacalc',         # How you named your package folder (MyLib)
   packages = ['isacalc'],   # Chose the same as "name"
-  version = 'v1.2.0',      # Start with a small number and increase it with every change you make
+  version = 'v1.2.1',      # Start with a small number and increase it with every change you make
   license='GNU GPLv3',        # Chose a license from here: https://help.github.com/articles/licensing-a-repository
   description = 'Standard International Atmosphere Calculator',   # Give a short description about your library
   long_description=readme(),
   author = 'Luke de Waal',                   # Type in your name
   author_email = '[email protected]',      # Type in your E-Mail
   url = 'https://github.com/LukeDeWaal/ISA_Calculator',   # Provide either the link to your github or to your website
-  download_url = 'https://github.com/LukeDeWaal/ISA_Calculator/archive/v1.2.0.tar.gz',    # I explain this later on
+  download_url = 'https://github.com/LukeDeWaal/ISA_Calculator/archive/v1.2.1.tar.gz',    # I explain this later on
   keywords = ['ISA','Aerospace','Aeronautical','Atmosphere'],   # Keywords that define your package best
   install_requires=[            # I get to this in a second
-          'numpy',
+          'numpy', 'pandas'
       ],
   classifiers=[
     'Development Status :: 3 - Alpha',      # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package