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restructured functions
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@alexjamesgarza
alexjamesgarza committed Apr 2, 2024
1 parent 4d4f1ef commit 4e1d991
Showing 1 changed file with 71 additions and 65 deletions.
136 changes: 71 additions & 65 deletions src/music_box_evolving_conditions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,72 +85,18 @@ def from_UI_JSON(cls, UI_JSON, species_list, reaction_list):
@classmethod
def from_config_JSON(cls, path_to_json ,config_JSON, species_list, reaction_list):
# Initialize empty lists for times and conditions
times = []
conditions = []


evolving_conditions = EvolvingConditions()

# Check if 'evolving conditions' is a key in the JSON config
if 'evolving conditions' in config_JSON:
# Construct the path to the evolving conditions file
evolving_conditions_path = os.path.dirname(path_to_json) + "/" + list(config_JSON['evolving conditions'].keys())[0]
print(evolving_conditions_path)

# Open the evolving conditions file and read it as a CSV
with open(evolving_conditions_path, 'r') as csv_file:
evolving_conditions = list(csv.reader(csv_file))

# The first row of the CSV contains headers
headers = evolving_conditions[0]

# Iterate over the remaining rows of the CSV
for i in range(1, len(evolving_conditions)):
# The first column of each row is a time value
times.append(float(evolving_conditions[i][0]))

# Initialize pressure and temperature as None
pressure = None
temperature = None

# If pressure and temperature headers are present in the CSV, extract their values
if 'ENV.pressure.Pa' in headers:
pressure = float(evolving_conditions[i][headers.index('ENV.pressure.Pa')])
if 'ENV.temperature.K' in headers:
temperature = float(evolving_conditions[i][headers.index('ENV.temperature.K')])

# Initialize concentrations list and extract concentration headers
concentrations = []
concentration_headers = list(filter(lambda x: 'CONC' in x, headers))

# For each concentration header, find the matching species and append its concentration to the list
for j in range(len(concentration_headers)):
match = filter(lambda x: x.name == concentration_headers[j].split('.')[1], species_list.species)
species = next(match, None)
concentration = float(evolving_conditions[i][headers.index(concentration_headers[j])])

concentrations.append(SpeciesConcentration(species, concentration))


# Initialize rates list and extract rate headers
rates = []
rate_headers = list(filter(lambda x: 's-1' in x, headers))

# For each rate header, find the matching reaction and append its rate to the list
for k in range(len(rate_headers)):
name_to_match = rate_headers[k].split('.')

if name_to_match[0] == 'LOSS' or name_to_match[0] == 'EMIS':
name_to_match = name_to_match[0] + '_' + name_to_match[1]
else:
name_to_match = name_to_match[1]
match = filter(lambda x: x.name == name_to_match, reaction_list.reactions)
reaction = next(match, None)
rate = float(evolving_conditions[i][headers.index(rate_headers[k])])
rates.append(ReactionRate(reaction, rate))

# Append the conditions for this time point to the conditions list
conditions.append(Conditions(pressure, temperature, concentrations, rates))

# Return a new instance of the class with the times and conditions
return cls(times, conditions)
evolving_conditions = EvolvingConditions.read_conditions_from_file( evolving_conditions_path, species_list, reaction_list)

return evolving_conditions


def add_condition(self, time_point, conditions):
"""
Expand All @@ -163,16 +109,76 @@ def add_condition(self, time_point, conditions):
self.time.append(time_point)
self.conditions.append(conditions)

def read_conditions_from_file(self, file_path):
@classmethod
def read_conditions_from_file(cls, file_path, species_list, reaction_list):
"""
TODO: Read conditions from a file and update the evolving conditions.
Args:
file_path (str): The path to the file containing conditions UI_JSON.
"""
# TODO: Implement the logic to read conditions from the specified file.
# This method is a placeholder, and the actual implementation is required.
pass

times = []
conditions = []

# Open the evolving conditions file and read it as a CSV
with open(file_path, 'r') as csv_file:
evolving_conditions = list(csv.reader(csv_file))

# The first row of the CSV contains headers
headers = evolving_conditions[0]

# Iterate over the remaining rows of the CSV
for i in range(1, len(evolving_conditions)):
# The first column of each row is a time value
times.append(float(evolving_conditions[i][0]))

# Initialize pressure and temperature as None
pressure = None
temperature = None

# If pressure and temperature headers are present in the CSV, extract their values
if 'ENV.pressure.Pa' in headers:
pressure = float(evolving_conditions[i][headers.index('ENV.pressure.Pa')])
if 'ENV.temperature.K' in headers:
temperature = float(evolving_conditions[i][headers.index('ENV.temperature.K')])

# Initialize concentrations list and extract concentration headers
concentrations = []
concentration_headers = list(filter(lambda x: 'CONC' in x, headers))

# For each concentration header, find the matching species and append its concentration to the list
for j in range(len(concentration_headers)):
match = filter(lambda x: x.name == concentration_headers[j].split('.')[1], species_list.species)
species = next(match, None)
concentration = float(evolving_conditions[i][headers.index(concentration_headers[j])])

concentrations.append(SpeciesConcentration(species, concentration))


# Initialize rates list and extract rate headers
rates = []
rate_headers = list(filter(lambda x: 's-1' in x, headers))

# For each rate header, find the matching reaction and append its rate to the list
for k in range(len(rate_headers)):
name_to_match = rate_headers[k].split('.')

if name_to_match[0] == 'LOSS' or name_to_match[0] == 'EMIS':
name_to_match = name_to_match[0] + '_' + name_to_match[1]
else:
name_to_match = name_to_match[1]
match = filter(lambda x: x.name == name_to_match, reaction_list.reactions)
reaction = next(match, None)
rate = float(evolving_conditions[i][headers.index(rate_headers[k])])
rates.append(ReactionRate(reaction, rate))

# Append the conditions for this time point to the conditions list
conditions.append(Conditions(pressure, temperature, concentrations, rates))

# Return a new instance of the class with the times and conditions
return cls(times, conditions)


#allows len overload for this class
def __len__(self):
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