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Chris Jewell
covid19uk
Commits
62f9ec37
Commit
62f9ec37
authored
Apr 23, 2021
by
Chris Jewell
Browse files
Merge branch 'fix-prediction-weekday' into 'master'
Fix for weekday effect in prediction See merge request
!37
parents
45a79675
3df0dd34
Changes
1
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Inline
Side-by-side
covid/tasks/predict.py
View file @
62f9ec37
...
@@ -3,6 +3,7 @@
...
@@ -3,6 +3,7 @@
import
numpy
as
np
import
numpy
as
np
import
xarray
import
xarray
import
pickle
as
pkl
import
pickle
as
pkl
import
pandas
as
pd
import
tensorflow
as
tf
import
tensorflow
as
tf
from
covid
import
model_spec
from
covid
import
model_spec
...
@@ -75,11 +76,17 @@ def predict(data, posterior_samples, output_file, initial_step, num_steps):
...
@@ -75,11 +76,17 @@ def predict(data, posterior_samples, output_file, initial_step, num_steps):
origin_date
=
np
.
array
(
cases
.
coords
[
"time"
][
0
])
origin_date
=
np
.
array
(
cases
.
coords
[
"time"
][
0
])
dates
=
np
.
arange
(
dates
=
np
.
arange
(
origin_date
+
np
.
timedelta64
(
initial_step
,
"D"
)
,
origin_date
,
origin_date
+
np
.
timedelta64
(
initial_step
+
num_steps
,
"D"
),
origin_date
+
np
.
timedelta64
(
initial_step
+
num_steps
,
"D"
),
np
.
timedelta64
(
1
,
"D"
),
np
.
timedelta64
(
1
,
"D"
),
)
)
covar_data
[
"weekday"
]
=
xarray
.
DataArray
(
(
pd
.
to_datetime
(
dates
).
weekday
<
5
).
astype
(
model_spec
.
DTYPE
),
coords
=
[
dates
],
dims
=
[
"prediction_time"
],
)
estimated_init_state
,
predicted_events
=
predicted_incidence
(
estimated_init_state
,
predicted_events
=
predicted_incidence
(
samples
,
initial_state
,
covar_data
,
initial_step
,
num_steps
samples
,
initial_state
,
covar_data
,
initial_step
,
num_steps
)
)
...
@@ -89,7 +96,7 @@ def predict(data, posterior_samples, output_file, initial_step, num_steps):
...
@@ -89,7 +96,7 @@ def predict(data, posterior_samples, output_file, initial_step, num_steps):
coords
=
[
coords
=
[
np
.
arange
(
predicted_events
.
shape
[
0
]),
np
.
arange
(
predicted_events
.
shape
[
0
]),
covar_data
.
coords
[
"location"
],
covar_data
.
coords
[
"location"
],
dates
,
dates
[
initial_step
:]
,
np
.
arange
(
predicted_events
.
shape
[
3
]),
np
.
arange
(
predicted_events
.
shape
[
3
]),
],
],
dims
=
(
"iteration"
,
"location"
,
"time"
,
"event"
),
dims
=
(
"iteration"
,
"location"
,
"time"
,
"event"
),
...
...
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