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treat_runtimeparams fix optimization_time_step timedelta #396

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merged 4 commits into from
Dec 24, 2024
Merged

treat_runtimeparams fix optimization_time_step timedelta #396

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a1d8423
treat_runtimeparams fix optimization_time_step timedelta
GeoDerp Dec 23, 2024
90f97a5
Merge branch 'master' of github.com:davidusb-geek/emhass into patch-21
GeoDerp Dec 24, 2024
906240b
webserver remove logger duplicate
GeoDerp Dec 24, 2024
a88f6ef
treat_runtimeparams add missing passed_data, move forecast_methods
GeoDerp Dec 24, 2024
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118 changes: 64 additions & 54 deletions src/emhass/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -308,7 +308,7 @@ def treat_runtimeparams(
runtimeparams.get("optimization_time_step", runtimeparams.get("freq"))
)
params["retrieve_hass_conf"]["optimization_time_step"] = pd.to_timedelta(
optimization_time_step
optimization_time_step, "minutes"
)
else:
optimization_time_step = int(
Expand Down Expand Up @@ -338,59 +338,6 @@ def treat_runtimeparams(
optimization_time_step, delta_forecast, time_zone
)

# Treat passed forecast data lists
list_forecast_key = [
"pv_power_forecast",
"load_power_forecast",
"load_cost_forecast",
"prod_price_forecast",
"outdoor_temperature_forecast",
]
forecast_methods = [
"weather_forecast_method",
"load_forecast_method",
"load_cost_forecast_method",
"production_price_forecast_method",
"outdoor_temperature_forecast_method",
]

# Loop forecasts, check if value is a list and greater than or equal to forecast_dates
for method, forecast_key in enumerate(list_forecast_key):
if forecast_key in runtimeparams.keys():
if isinstance(runtimeparams[forecast_key], list) and len(
runtimeparams[forecast_key]
) >= len(forecast_dates):
params["passed_data"][forecast_key] = runtimeparams[forecast_key]
params["optim_conf"][forecast_methods[method]] = "list"
else:
logger.error(
f"ERROR: The passed data is either not a list or the length is not correct, length should be {str(len(forecast_dates))}"
)
logger.error(
f"Passed type is {str(type(runtimeparams[forecast_key]))} and length is {str(len(runtimeparams[forecast_key]))}"
)
# Check if string contains list, if so extract
if isinstance(runtimeparams[forecast_key], str):
if isinstance(ast.literal_eval(runtimeparams[forecast_key]), list):
runtimeparams[forecast_key] = ast.literal_eval(
runtimeparams[forecast_key]
)
list_non_digits = [
x
for x in runtimeparams[forecast_key]
if not (isinstance(x, int) or isinstance(x, float))
]
if len(list_non_digits) > 0:
logger.warning(
f"There are non numeric values on the passed data for {forecast_key}, check for missing values (nans, null, etc)"
)
for x in list_non_digits:
logger.warning(
f"This value in {forecast_key} was detected as non digits: {str(x)}"
)
else:
params["passed_data"][forecast_key] = None

# Add runtime exclusive (not in config) parameters to params
# regressor-model-fit
if set_type == "regressor-model-fit":
Expand Down Expand Up @@ -447,6 +394,16 @@ def treat_runtimeparams(
soc_final = runtimeparams["soc_final"]
params["passed_data"]["soc_final"] = soc_final

params["passed_data"]["operating_hours_of_each_deferrable_load"] = params[
"optim_conf"
].get("operating_hours_of_each_deferrable_load", None)
params["passed_data"]["start_timesteps_of_each_deferrable_load"] = params[
"optim_conf"
].get("start_timesteps_of_each_deferrable_load", None)
params["passed_data"]["end_timesteps_of_each_deferrable_load"] = params[
"optim_conf"
].get("end_timesteps_of_each_deferrable_load", None)

forecast_dates = copy.deepcopy(forecast_dates)[0:prediction_horizon]

# Load the default config
Expand Down Expand Up @@ -480,6 +437,59 @@ def treat_runtimeparams(
params["passed_data"]["soc_init"] = None
params["passed_data"]["soc_final"] = None

# Treat passed forecast data lists
list_forecast_key = [
"pv_power_forecast",
"load_power_forecast",
"load_cost_forecast",
"prod_price_forecast",
"outdoor_temperature_forecast",
]
forecast_methods = [
"weather_forecast_method",
"load_forecast_method",
"load_cost_forecast_method",
"production_price_forecast_method",
"outdoor_temperature_forecast_method",
]

# Loop forecasts, check if value is a list and greater than or equal to forecast_dates
for method, forecast_key in enumerate(list_forecast_key):
if forecast_key in runtimeparams.keys():
if isinstance(runtimeparams[forecast_key], list) and len(
runtimeparams[forecast_key]
) >= len(forecast_dates):
params["passed_data"][forecast_key] = runtimeparams[forecast_key]
params["optim_conf"][forecast_methods[method]] = "list"
else:
logger.error(
f"ERROR: The passed data is either not a list or the length is not correct, length should be {str(len(forecast_dates))}"
)
logger.error(
f"Passed type is {str(type(runtimeparams[forecast_key]))} and length is {str(len(runtimeparams[forecast_key]))}"
)
# Check if string contains list, if so extract
if isinstance(runtimeparams[forecast_key], str):
if isinstance(ast.literal_eval(runtimeparams[forecast_key]), list):
runtimeparams[forecast_key] = ast.literal_eval(
runtimeparams[forecast_key]
)
list_non_digits = [
x
for x in runtimeparams[forecast_key]
if not (isinstance(x, int) or isinstance(x, float))
]
if len(list_non_digits) > 0:
logger.warning(
f"There are non numeric values on the passed data for {forecast_key}, check for missing values (nans, null, etc)"
)
for x in list_non_digits:
logger.warning(
f"This value in {forecast_key} was detected as non digits: {str(x)}"
)
else:
params["passed_data"][forecast_key] = None

# Treat passed data for forecast model fit/predict/tune at runtime
if (
params["passed_data"].get("historic_days_to_retrieve", None) is not None
Expand Down
11 changes: 2 additions & 9 deletions src/emhass/web_server.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@

import yaml
from flask import Flask, make_response, request
from flask import logging as log
from jinja2 import Environment, PackageLoader
from waitress import serve

Expand Down Expand Up @@ -384,7 +385,6 @@ def action_call(action_name):

ActionStr = " >> Setting input data dict"
app.logger.info(ActionStr)
app.logger.warning(costfun)
input_data_dict = set_input_data_dict(
emhass_conf, costfun, params, runtimeparams, action_name, app.logger
)
Expand Down Expand Up @@ -652,37 +652,30 @@ def action_call(action_name):
raise Exception("missing: " + str(emhass_conf["data_path"]))

# Define loggers
ch = logging.StreamHandler()
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
ch.setFormatter(formatter)
log.default_handler.setFormatter(formatter)
# Action file logger
fileLogger = logging.FileHandler(str(emhass_conf["data_path"] / "actionLogs.txt"))
formatter = logging.Formatter("%(levelname)s - %(name)s - %(message)s")
fileLogger.setFormatter(formatter) # add format to Handler
if logging_level == "DEBUG":
app.logger.setLevel(logging.DEBUG)
ch.setLevel(logging.DEBUG)
fileLogger.setLevel(logging.DEBUG)
elif logging_level == "INFO":
app.logger.setLevel(logging.INFO)
ch.setLevel(logging.INFO)
fileLogger.setLevel(logging.INFO)
elif logging_level == "WARNING":
app.logger.setLevel(logging.WARNING)
ch.setLevel(logging.WARNING)
fileLogger.setLevel(logging.WARNING)
elif logging_level == "ERROR":
app.logger.setLevel(logging.ERROR)
ch.setLevel(logging.ERROR)
fileLogger.setLevel(logging.ERROR)
else:
app.logger.setLevel(logging.DEBUG)
ch.setLevel(logging.DEBUG)
fileLogger.setLevel(logging.DEBUG)
app.logger.propagate = False
app.logger.addHandler(ch)
app.logger.addHandler(fileLogger)
# Clear Action File logger file, ready for new instance
clearFileLog()
Expand Down
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