Defined alternative constructor for EquationSystem

equpy.py

@@ -1,30 +1,59 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import warnings
-from typing import List, Tuple
+from typing import List, Tuple, Union, Optional, Dict
 from utils import eq_system_builder
 
+
 class EquationSystem:
- """
- Assembles an object including the equations defining the systems reactions and mass conservations
- Parameters:
- - equations: set of reactions, either list of Str or list of numerical lists
- - mass_conservation: set of mass conservations, either list of Str or list of numerical lists
- - species: optional argument. If reactions in Str form are passed the species names are automatically generated.
- Custom species names can be passed when input is in matrix form as a dictionary of species, such as: 
- {'A':0, 'B':1, 'C':2} for a system involving three species (n=3) named A, B, C.
- """
- def __init__(self, equations, mass_conservation, species = None):
- self.stoichiometry, self.mass_conservation, self.species = equations, mass_conservation, species
- if isinstance(self.stoichiometry[0], str): #assuming the user is passing reactions in textual form
- self.stoichiometry, self.mass_conservation, self.species = eq_system_builder(self.stoichiometry, self.mass_conservation)
+ def __init__(
+ self,
+ equations: Union[List[List[float]], np.ndarray],
+ mass_conservation: Union[List[List[float]], np.ndarray],
+ species: Optional[Dict[str, int]] = None,
+ ):
+ """
+ Assembles an object including the equations defining the systems reactions and mass conservations
+ Parameters:
+ - equations: set of reactions, either list of list of numbers or bidimensional numpy.ndarray
+ - mass_conservation: set of mass conservations, either list of list of numbers or bidimensional numpy.ndarray
+ - species: optional argument. Custom species names can be passed when input is in matrix form as a dictionary of species, such as:
+ {'A':0, 'B':1, 'C':2} for a system involving three species (n=3) named A, B, C.
+ """
+ self.stoichiometry = (
+ equations if isinstance(equations, np.ndarray) else np.array(equations)
+ )
+ self.mass_conservation = (
+ mass_conservation
+ if isinstance(mass_conservation, np.ndarray)
+ else np.array(mass_conservation)
+ )
+ self.species = (
+ species
+ if species is not None
+ else {i: i for i in range(np.shape(self.stoichiometry)[1])}
+ ) # placeholder for species name if not specified
+
+ @classmethod
+ def from_literal_equations(
+ cls, equations: List[str], mass_conservation: List[str]
+ ) -> None:
+ """
+ Alternative constructor that assembles an object including the equations defining the systems reactions and mass conservations,
+ passed as text
+ Parameters:
+ - equations: set of reactions, expressed as a list of strings
+ - mass_conservation: set of mass conservations, expressed as a list of strings
+ """
+ _stoichiometry, _mass_conservation, _species = eq_system_builder(
+ equations, mass_conservation
+ )
+ return cls(_stoichiometry, _mass_conservation, _species)
 
- if self.species == None:
- self.species = {i:i for i in range(np.shape(self.stoichiometry)[1])} #placeholder for species name if not specified
 
 class ChemicalReaction:
  """
- Assembles an object with the equations defining the systems reactions and mass conservations 
+ Assembles an object with the equations defining the systems reactions and mass conservations
  plus equilibrium constants and total masses.
  Parameters:
  - equation_system: EquationSystem object as defined in the respective Class
@@ -34,6 +63,7 @@ class ChemicalReaction:
  IMPORTANT: for equpy's result to be meaningful the unit of measurement have to be matching: if the equilibrium constants
  are given in (1/micromolar) units, the concentrations have to be given in micromolar units.
  """
+
  def __init__(
  self,
  equation_system: EquationSystem,
@@ -69,6 +99,7 @@ def __init__(
  such as 0.5 or 1.0 grealy improve code stability for more difficult tasks, but will cause a slower
  approach to convergence.
  """
+
  def solve(
  self, iter: int, tolerance: float, w: float
  ) -> Tuple[np.ndarray, List[np.ndarray]]:
@@ -99,24 +130,28 @@ def solve(
  """
  plotter method relies on matplotlib to generate a graph showing algorithm's progress to convergence and final results.
  """
+
  def plotter(self):
  f, (ax1, ax2) = plt.subplots(1, 2, sharey=False, figsize=(15, 5))
  ax1.plot(np.arange(len(self.residuals)), self.residuals, lw=3, color="black")
  ax1.scatter(
  np.arange(len(self.residuals)), self.residuals, s=120, color="black"
  )
 
- ax1.set_xlabel("steps", fontsize=14, fontname = 'Arial')
- ax1.set_ylabel("||r||", fontsize=14, fontname = 'Arial')
- ax1.set_title('Algorithm Progress', fontsize=16, fontname = 'Arial')
+ ax1.set_xlabel("steps", fontsize=14, fontname="Arial")
+ ax1.set_ylabel("||r||", fontsize=14, fontname="Arial")
+ ax1.set_title("Algorithm Progress", fontsize=16, fontname="Arial")
  ax1.set_yscale("linear")
 
  ax2.bar(np.arange(0, len(self.result)), self.result)
- ax2.set_ylabel("concentration", fontsize=14, fontname = 'Arial')
+ ax2.set_ylabel("concentration", fontsize=14, fontname="Arial")
  ax2.set_xticks(np.arange(0, len(self.result)))
- ax2.set_title('Equilibrium Concentrations', fontsize=16, fontname = 'Arial')
+ ax2.set_title("Equilibrium Concentrations", fontsize=16, fontname="Arial")
  ax2.set_xticklabels(
- sorted(self.s, key=lambda x: self.s[x]), fontsize=12, rotation=90, fontname = 'Arial'
+ sorted(self.s, key=lambda x: self.s[x]),
+ fontsize=12,
+ rotation=90,
+ fontname="Arial",
  )