csv.module¶

The at_cascade.csv Python Module¶

Interface Example¶

The python code that implements this interface to the at_cascade module can be used as an example for other interfaces.

Notation¶

Demographer¶

None of the data is in demographer notation. For example, time 1990 means the beginning of 1990, not the time interval from 1990 to 1991.

Rectangular Grid¶

Define a selection subset of a csv file as those rows with the same value in column select. For each value in select , a csv file is said to have a rectangular grid in age and time if the following holds:

Define \(( a_1 , \ldots , a_M )\) to be the vector of values in the age column for this selection subset.
Define \(( t_1 , \ldots , t_N )\) to be the vector of values in the time column for this selection subset.
For \(m = 1 , \ldots , M\), \(n = 1, \ldots , N\) , there is one and only one row in this selection subset with age equal to \(a_m\), and time equal to \(t_n\).

Data Type¶

The actual data type for each entry in a csv file is a string; i.e., an arbitrary sequence of characters. Certain columns have further restrictions as described below

Integer¶

An integer value is a string represents of an integer.

Float¶

A float value is a string that represents a floating point number.

Sex¶

A sex, or sex_name, is one of the following: female , both, or male.

Boolean¶

A boolean value is either true or false .

Index Column¶

An index column for a csv file is an integer column that has the row number corresponding to each row. It starts with zero at the first row below the header row. If a column name is an index column for two or more files, rows with the same index value in the different files correspond to each other.

Distributions¶

Unless other wise specified, the mean and standard deviations that simulate refers to are for a normal distribution.

sex_name2value¶

The following dictionary maps each sex name to the corresponding sex value

sex_name2value = { 'female' : -0.5, 'both' : 0.0, 'male' : 0.5 }

split_reference_table¶

The split_covariate_name is sex and the split_reference_table has the following values for csv.fit, csv.simulate and csv.predict :

split_reference_table = [
   { 'split_reference_name' : 'female' , 'split_reference_value' : -0.5 },
   { 'split_reference_name' : 'both'   , 'split_reference_value' :  0.0 },
   { 'split_reference_name' : 'male'   , 'split_reference_value' : +0.5 },
]

Routines¶

Name	Title
csv.ancestor_fit	Determine Closet Ancestor With Fit and Samples
csv.check_table	Check Columns in a CSV File
csv.covariate_avg	Compute Covariate Averages for One Node
csv.covariate_both	Add both Sex to csv Covariate Table
csv.covariate_same	Determine Which Covariates in covariate.csv Are the Same
csv.covariate_spline	Create Spline Functions For Covariates
csv.empty_str	Create A Table from a CSV File
csv.fit	Fit a CSV Specified Cascade
csv.get_header	Get the Header from a CSV File
csv.join_file	Join The Tables In Two Csv Files
csv.pre_one_job	Calculate the predictions for One Fit
csv.pre_one_process	Predict Using One Process
csv.pre_parallel	Predict With Specified Maximum Number of Processes
csv.pre_user	Convert Prediction Csv Files From dismod_at Notation to User csv.fit Notation
csv.predict	Prediction for a CSV Fit
csv.read_table	Create A Table from a CSV File
csv.set_truth	Set the Truth Table for a Fitted Database
csv.simulate	Simulate A Cascade Data Set
csv.write_table	Create A CSV File from a Table