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create_database(
file_name,
age_list,
time_list,
integrand_table,
node_table,
subgroup_table,
weight_table,
covariate_table,
avgint_table,
data_table,
prior_table,
smooth_table,
nslist_table,
rate_table,
mulcov_table,
option_table
)
dismod_at database
with all of its input
tables.
This is only meant for small example and testing cases and is not efficient.
age_list[i]
corresponds to the i-th row
of the age table which has
primary key
value
age_id = i
.
table_name_name
in the table
table_name
.
str containing the name of the file where the data base
is stored.
If this file already exists, it is deleted and a database is created.
list of float that
specify age values by indices.
list of float that
specify time values by indices.
dict
that define the rows of the integrand_table
.
The dictionary
integrand_table[i]
has the following:
| Key |
Value Type | Description |
| name | str |
name for the i-th integrand |
| minimum_meas_cv | str | minimum measurement cv for this integrand |
minimum_meas_cv is optional.
If it is not present, 0.0 is used for the corresponding value.
dict
that define the rows of the node_table
.
The dictionary
node_table[i]
has the following:
| Key |
Value Type | Description |
| name | str |
name for the i-th node |
| parent | str |
name of parent of the i-th node
|
dict
that define the rows of the subgroup_table
.
The dictionary
node_table[i]
has the following:
| Key |
Value Type | Description |
| subgroup | str |
name for the i-th subgroup |
| group | str | name of group that subgroup is in |
create_database call
(just after the
node_table
):
subgroup_table = [ { 'subgroup':'world', 'group':'world' } ]
create_database call should be necessary
(for backward compatibility).
dict
that define the rows of the weight_table
and
weight_grid_table
.
The dictionary
weight_table[i]
has the following:
| Key |
Value Type | Description |
| name | str |
name of i-th weighting |
| age_id | list of int | indices for age grid |
| time_id | list of int | indices for time grid |
| fun | function |
w=fun(a, t)
|
w
is the value of this weighting a the corresponding
float age
a
and float time
t
.
Note that there is an
i
,
j
such that
a = age_list[age_id[i]]
and
t = time_list[time_id[j]]
.
dict
that define the rows of the covariate_table
.
The dictionary
covariate_table[i]
has the following:
| Key |
Value Type | Description |
| name | str |
name for the i-th covariate |
| reference | float |
reference value for i-th covariate
|
| max_difference | float |
maximum difference for i-th covariate
|
max_difference
is None, the corresponding table entry
is null and this corresponds to an infinite maximum difference.
If
max_difference
does not appear, null is written for the
corresponding covariate entry.
dict
that define the rows of the avgint_table
.
The dictionary
avgint_table[i]
has the following:
| Key |
Value Type | Description |
| integrand | str |
integrand for i-th data |
| node | str | name of node in graph |
| subgroup | str | name of subgroup |
| weight | str | weighting function name |
| age_lower | float | lower age limit |
| age_upper | float | upper age limit |
| time_lower | float | lower time limit |
| time_lower | float | upper time limit |
c_0
| float | value of first covariate |
| ... | ... | ... |
c_J
| float | value of last covariate |
subgroup key is not present, the first subgroup in
subgroup_table
is used
and a warning is printed.
name
. If
weight
is the empty string,
the constant weighting is used.
J = len(covariate_table) - 1
and for
j = 0 , ... , J
,
c_j = covariate_table[j]['name']
avgint_table
.
row
of
option_table
has
row['name']
equal to 'avgint_extra_columns', the corresponding
row['value'].split()
is the list of extra avgint table columns.
Otherwise the list of extra avgint table columns is empty.
dict
that define the rows of the data_table
.
It has all the columns required for the
avgint_table
.
In addition, the dictionary
data_table[i]
has the following:
| Key |
Value Type | Description |
| hold_out | bool | hold out flag |
| density | str | density_name |
| meas_value | float | measured value |
| meas_std | float | standard deviation |
| eta | float | offset in log-transform |
| nu | float | Student's-t degrees of freedom |
meas_std, eta, and nu
are optional. If they are not present, the value null is used
for the corresponding row of the data table.
subgroup key is not present, the first subgroup in
subgroup_table
is used
and a warning is printed.
row
of
option_table
has
row['name']
equal to 'data_extra_columns', the corresponding
row['value'].split()
is the list of extra data table columns.
Otherwise the list of extra data table columns is empty.
dict
that define the rows of the prior_table
.
The dictionary
prior_table[i]
has the following:
| Key |
Value Type | Description |
| name | str |
name of i-th prior |
| lower | float | lower limit |
| upper | float | upper limit |
| std | float | standard deviation |
| density | str | density_name |
| eta | float | offset in log densities |
| nu | float | degrees of freed in Student densities |
lower, upper, std, eta, and nu
are optional. If they are not present, the value null is used
for the corresponding row of the prior table.
dict
that define the rows of the smooth_table
and
smooth_grid_table
.
The dictionary
smooth_table[i]
has the following keys:
str specifying the name used to reference the i-th smoothing.
int specifying the age values for this smoothing
as indices in age_list
.
int specifying the time values for this smoothing
as indices in time_list
.
str specifying the prior used for the value multiplier
for the i-th smoothing; see
mulstd_value_prior_id
This key is optional and its default value is None which corresponds
to null in the database.
str specifying the prior used for the age difference multiplier
for the i-th smoothing; see
mulstd_dage_prior_id
This key is optional and its default value is None which corresponds
to null in the database.
str specifying the prior used for the time difference multiplier
for the i-th smoothing; see
mulstd_dtime_prior_id
This key is optional and its default value is None which corresponds
to null in the database.
(v, da, dt) = fun(a, t)
str results
v
,
da
, and
dt
are the names for the value prior, age difference prior,
and time difference prior corresponding to the i-th smoothing.
The value
da
is not used,
when age
a = age_id[-1]
.
The value
dt
is not used,
when time
t = time_id[-1]
.
Note that there is an
i
,
j
such that
a = age_list[age_id[i]]
and
t = time_list[time_id[j]]
.
fun
return value
v
may be a float.
In this case, the value of the smoothing, at the corresponding age and time,
is constrained to be
v
using the
const_value
column in the
smooth_grid table.
dict that specifies the
nslist_table
and the nslist_pair_table
.
For each nslist_name
,
nslist_table[nslist_name] = [ (node_name, smooth_name), ... ]
tuple:
| Variable |
Value Type | Description |
| nslist_name | str | name of one list of node,smoothing pairs |
| node_name | str | name of the node for this pair |
| smooth_name | str | name of the smoothing for this pair |
dict
that define the rows of the rate_table
.
The dictionary
rate_table[i]
has the following:
| Key |
Value Type | Description |
| name | str | pini, iota, rho, chi, or omega |
| parent_smooth | str | parent smoothing |
| child_smooth | str | a single child smoothing |
| child_nslist | str | list of child smoothings |
None is used to represent a null value for
the parent and child smoothings.
If a key name does not appear, null is used for the corresponding value.
If a
name
; e.g. rho, does not appear, the value
null is used for the parent and child smoothings for the corresponding rate.
dict
that define the rows of the mulcov_table
.
The dictionary
mulcov_table[i]
has the following:
| Key |
Value Type | Description |
| covariate | str | is the covariate column |
| type | str |
rate_value, meas_value, or meas_noise |
| effected | str | integrand or rate affected |
| group | str | the group that is affected |
| smooth | str | smoothing at group level |
| subsmooth | str | smoothing at subgroup level |
type
is rate_value,
effected
is a rate.
Otherwise it is an integrand.
group key is not present, the first group in
subgroup_table
is used.
subsmooth key is not present, the value null is used for
the subgroup smoothing in the corresponding row and a warning is printed.
dict
that define the values
option_name
,
option_value
in the option table.
The i-th row of the table will have
option_name = option_table[i]['name']
option_value = option_table[i]['value']
| create_database.py | create_database: Example and Test |
create_database.