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Address warnings + remove warning suppression #69

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merged 4 commits into from
May 12, 2024
Merged

Address warnings + remove warning suppression #69

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183db25
workflow tutorial always returns the acf /= acf[0] divide by zero err…
twallema May 12, 2024
0ab5319
omit warning suppression in influenza 1718 tutorial
twallema May 12, 2024
d3bc26f
fix date parsing warning in influenza 1718 tutorial
twallema May 12, 2024
a904c00
remove suppression of warnings in SIR_SI tutorial
twallema May 12, 2024
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6 changes: 1 addition & 5 deletions tutorials/SIR/workflow_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,10 +20,6 @@
from pySODM.optimization.mcmc import perturbate_theta, run_EnsembleSampler, emcee_sampler_to_dictionary
from pySODM.optimization.objective_functions import log_posterior_probability, ll_negative_binomial

# Suppress warnings
import warnings
warnings.filterwarnings("ignore")

######################################################
## Generate a synthetic dataset with overdispersion ##
######################################################
Expand Down Expand Up @@ -107,7 +103,7 @@ def integrate(t, S, I, R, beta, gamma):
# Calibated parameters and bounds
pars = ['beta',]
labels = ['$\\beta$',]
bounds = [(1e-6,1),]
bounds = [(0,10),]
# Setup objective function (no priors --> uniform priors based on bounds)
objective_function = log_posterior_probability(model, pars, bounds, data, states, log_likelihood_fnc, log_likelihood_fnc_args, labels=labels)
# Extract start- and enddate
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4 changes: 0 additions & 4 deletions tutorials/SIR_SI/calibration.py
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Expand Up @@ -21,10 +21,6 @@
from pySODM.optimization.mcmc import perturbate_theta, run_EnsembleSampler, emcee_sampler_to_dictionary
from pySODM.optimization.objective_functions import log_posterior_probability, ll_negative_binomial, ll_poisson

# Suppress warnings
import warnings
warnings.filterwarnings("ignore")

##################
## Define model ##
##################
Expand Down
7 changes: 2 additions & 5 deletions tutorials/influenza_1718/calibration.py
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Expand Up @@ -25,9 +25,6 @@
from pySODM.optimization.objective_functions import log_posterior_probability, ll_negative_binomial
# pySODM dependecies
import corner
# Suppress warnings
import warnings
warnings.filterwarnings("ignore")

##############
## Settings ##
Expand All @@ -52,10 +49,10 @@
###############

# Load case data
data = pd.read_csv(os.path.join(os.path.dirname(__file__),'data/interim/data_influenza_1718_format.csv'), index_col=[0,1], parse_dates=True)
data = pd.read_csv(os.path.join(os.path.dirname(__file__),'data/interim/data_influenza_1718_format.csv'), index_col=[0,1], parse_dates=True, date_format='%Y-%m-%d')
data = data.squeeze()
# Load case data per 100K
data_100K = pd.read_csv(os.path.join(os.path.dirname(__file__),'data/interim/data_influenza_1718_format_100K.csv'), index_col=[0,1], parse_dates=True)
data_100K = pd.read_csv(os.path.join(os.path.dirname(__file__),'data/interim/data_influenza_1718_format_100K.csv'), index_col=[0,1], parse_dates=True, date_format='%Y-%m-%d')
data_100K = data_100K.squeeze()
# Re-insert pd.IntervalIndex (pd.IntervalIndex is always loaded as a string..)
age_groups = pd.IntervalIndex.from_tuples([(0,5),(5,15),(15,65),(65,120)], closed='left')
Expand Down
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