From 81e0e2243dbee2b8ffce15d4dbc23dcba264587f Mon Sep 17 00:00:00 2001
From: Stefano Serafin <serafin@jet01.img.univie.ac.at>
Date: Wed, 26 Feb 2025 12:22:39 +0100
Subject: [PATCH] minor bug fixes
---
ENDA.py | 16 +++++++++-------
1 file changed, 9 insertions(+), 7 deletions(-)
diff --git a/ENDA.py b/ENDA.py
index 6852981..1b07e81 100644
--- a/ENDA.py
+++ b/ENDA.py
@@ -136,7 +136,7 @@ def eakf(xb,o,var_o,xcoord,ocoord,dist,\
# Store innovation wrt to ensemble mean
if return_covariances_increments_and_innovations:
- innovations_mean[i] = o[i]-yp[i].mean()
+ innovations_mean[i] = o[i]-yp[i,:].mean()
# Determine analysis increments in observation space
# weight_p is a scalar
@@ -295,12 +295,12 @@ class cycle:
backgrounds = np.zeros((ncycles,state_vector_length,nens)) + np.nan
analyses = np.zeros((ncycles,state_vector_length,nens)) + np.nan
model_equivalents = np.zeros((ncycles,nobs,nens)) + np.nan
- if cbl_settings['do_parameter_estimation'] and cbl_settings['return_covariances_increments_and_innovations']:
- increments = np.zeros((ncycles,nobs,npar)) + np.nan
+ if cbl_settings['return_covariances_increments_and_innovations']:
cov_py = np.zeros((ncycles,nobs,npar)) + np.nan
cov_pp = np.zeros((ncycles,nobs,npar)) + np.nan
cov_yy = np.zeros((ncycles,nobs)) + np.nan
innov = np.zeros((ncycles,nobs)) + np.nan
+ increments = np.zeros((ncycles,nobs,npar)) + np.nan
# Turn inflation coefficients into an array
inflation_coefficients_rtps = np.ones(state_vector_length)*inflation_rtps_alpha
@@ -473,7 +473,7 @@ class cycle:
self.zt = nr.zt
self.nens = nens
self.initial_perturbed_parameters = model.initial_perturbed_parameters
- if cbl_settings['do_parameter_estimation'] and cbl_settings['return_covariances_increments_and_innovations']:
+ if cbl_settings['return_covariances_increments_and_innovations']:
self.cov_py = cov_py
self.cov_pp = cov_pp
self.cov_yy = cov_yy
@@ -505,13 +505,15 @@ class experiment:
self.truths = deepcopy(exp.truths)
self.observations = deepcopy(exp.observations)
self.obs_coordinates = deepcopy(exp.obs_coordinates)
+ self.obs_error_sdev_generate = np.ones(self.nobs)*self.obs_error_sdev_generate
+ self.obs_error_sdev_assimilate = np.ones(self.nobs)*self.obs_error_sdev_assimilate
if not self.do_parameter_estimation:
self.nr.do_parameter_estimation = False
# Get CBL settings from file
- assert os.path.isfile(self.cbl_settings_file),\
- f'CBL settings file {self.cbl_settings_file} does not exist'
- with open(self.cbl_settings_file, 'r') as fp:
+ assert os.path.isfile(self.path+self.cbl_settings_file),\
+ f'CBL settings file {self.path+self.cbl_settings_file} does not exist'
+ with open(self.path+self.cbl_settings_file, 'r') as fp:
self.cbl_settings = dict(json.load(fp))
# Propagate parameter estimation settings to CBL model
--
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