smile.io

Interface Read

public interface Read

Interface to read data from external storage systems.

Method Summary

Modifier and Type	Method and Description
static smile.data.DataFrame	arff(java.nio.file.Path path) Reads an ARFF file.
static smile.data.DataFrame	arff(java.lang.String path) Reads an ARFF file.
static smile.data.DataFrame	arrow(java.nio.file.Path path) Reads an Apache Arrow file.
static smile.data.DataFrame	arrow(java.lang.String path) Reads an Apache Arrow file.
static smile.data.DataFrame	avro(java.nio.file.Path path, java.io.InputStream schema) Reads an Apache Avro file.
static smile.data.DataFrame	avro(java.nio.file.Path path, java.nio.file.Path schema) Reads an Apache Avro file.
static smile.data.DataFrame	avro(java.lang.String path, java.io.InputStream schema) Reads an Apache Avro file.
static smile.data.DataFrame	avro(java.lang.String path, java.lang.String schema) Reads an Apache Avro file.
static smile.data.DataFrame	csv(java.nio.file.Path path) Reads a CSV file.
static smile.data.DataFrame	csv(java.nio.file.Path path, org.apache.commons.csv.CSVFormat format) Reads a CSV file.
static smile.data.DataFrame	csv(java.nio.file.Path path, org.apache.commons.csv.CSVFormat format, smile.data.type.StructType schema) Reads a CSV file.
static smile.data.DataFrame	csv(java.lang.String path) Reads a CSV file.
static smile.data.DataFrame	csv(java.lang.String path, org.apache.commons.csv.CSVFormat format) Reads a CSV file.
static smile.data.DataFrame	csv(java.lang.String path, org.apache.commons.csv.CSVFormat format, smile.data.type.StructType schema) Reads a CSV file.
static smile.data.DataFrame	json(java.nio.file.Path path) Reads a JSON file.
static smile.data.DataFrame	json(java.nio.file.Path path, JSON.Mode mode, smile.data.type.StructType schema) Reads a JSON file.
static smile.data.DataFrame	json(java.lang.String path) Reads a JSON file.
static smile.data.DataFrame	json(java.lang.String path, JSON.Mode mode, smile.data.type.StructType schema) Reads a JSON file.
static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>>	libsvm(java.io.BufferedReader reader) Reads a libsvm sparse dataset.
static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>>	libsvm(java.nio.file.Path path) Reads a libsvm sparse dataset.
static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>>	libsvm(java.lang.String path) Reads a libsvm sparse dataset.
static smile.data.DataFrame	parquet(java.nio.file.Path path) Reads an Apache Parquet file.
static smile.data.DataFrame	parquet(java.lang.String path) Reads an Apache Parquet file.
static smile.data.DataFrame	sas(java.nio.file.Path path) Reads a SAS7BDAT file.
static smile.data.DataFrame	sas(java.lang.String path) Reads a SAS7BDAT file.

Method Detail

csv

static smile.data.DataFrame csv(java.lang.String path)
                         throws java.io.IOException,
                                java.net.URISyntaxException

Reads a CSV file.

Throws:

java.io.IOException

java.net.URISyntaxException

csv

static smile.data.DataFrame csv(java.lang.String path,
                                org.apache.commons.csv.CSVFormat format)
                         throws java.io.IOException,
                                java.net.URISyntaxException

Reads a CSV file.

Throws:

java.io.IOException

java.net.URISyntaxException

csv

static smile.data.DataFrame csv(java.lang.String path,
                                org.apache.commons.csv.CSVFormat format,
                                smile.data.type.StructType schema)
                         throws java.io.IOException,
                                java.net.URISyntaxException

Reads a CSV file.

Throws:

java.io.IOException

java.net.URISyntaxException

csv

static smile.data.DataFrame csv(java.nio.file.Path path)
                         throws java.io.IOException

Reads a CSV file.

Throws:

java.io.IOException

csv

static smile.data.DataFrame csv(java.nio.file.Path path,
                                org.apache.commons.csv.CSVFormat format)
                         throws java.io.IOException

Reads a CSV file.

Throws:

java.io.IOException

csv

static smile.data.DataFrame csv(java.nio.file.Path path,
                                org.apache.commons.csv.CSVFormat format,
                                smile.data.type.StructType schema)
                         throws java.io.IOException

Reads a CSV file.

Throws:

java.io.IOException

json

static smile.data.DataFrame json(java.lang.String path)
                          throws java.io.IOException,
                                 java.net.URISyntaxException

Reads a JSON file.

Throws:

java.io.IOException

java.net.URISyntaxException

json

static smile.data.DataFrame json(java.lang.String path,
                                 JSON.Mode mode,
                                 smile.data.type.StructType schema)
                          throws java.io.IOException,
                                 java.net.URISyntaxException

Reads a JSON file.

Throws:

java.io.IOException

java.net.URISyntaxException

json

static smile.data.DataFrame json(java.nio.file.Path path)
                          throws java.io.IOException

Reads a JSON file.

Throws:

java.io.IOException

json

static smile.data.DataFrame json(java.nio.file.Path path,
                                 JSON.Mode mode,
                                 smile.data.type.StructType schema)
                          throws java.io.IOException

Reads a JSON file.

Throws:

java.io.IOException

arff

static smile.data.DataFrame arff(java.lang.String path)
                          throws java.io.IOException,
                                 java.text.ParseException,
                                 java.net.URISyntaxException

Reads an ARFF file. Weka ARFF (attribute relation file format) is an ASCII text file format that is essentially a CSV file with a header that describes the meta-data. ARFF was developed for use in the Weka machine learning software.

A dataset is firstly described, beginning with the name of the dataset (or the relation in ARFF terminology). Each of the variables (or attribute in ARFF terminology) used to describe the observations is then identified, together with their data type, each definition on a single line. The actual observations are then listed, each on a single line, with fields separated by commas, much like a CSV file.

Missing values in an ARFF dataset are identified using the question mark '?'.

Comments can be included in the file, introduced at the beginning of a line with a '%', whereby the remainder of the line is ignored.

A significant advantage of the ARFF data file over the CSV data file is the meta data information.

Also, the ability to include comments ensure we can record extra information about the data set, including how it was derived, where it came from, and how it might be cited.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.text.ParseException

java.net.URISyntaxException

arff

static smile.data.DataFrame arff(java.nio.file.Path path)
                          throws java.io.IOException,
                                 java.text.ParseException

Reads an ARFF file. Weka ARFF (attribute relation file format) is an ASCII text file format that is essentially a CSV file with a header that describes the meta-data. ARFF was developed for use in the Weka machine learning software.

A dataset is firstly described, beginning with the name of the dataset (or the relation in ARFF terminology). Each of the variables (or attribute in ARFF terminology) used to describe the observations is then identified, together with their data type, each definition on a single line. The actual observations are then listed, each on a single line, with fields separated by commas, much like a CSV file.

Missing values in an ARFF dataset are identified using the question mark '?'.

Comments can be included in the file, introduced at the beginning of a line with a '%', whereby the remainder of the line is ignored.

A significant advantage of the ARFF data file over the CSV data file is the meta data information.

Also, the ability to include comments ensure we can record extra information about the data set, including how it was derived, where it came from, and how it might be cited.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.text.ParseException

sas

static smile.data.DataFrame sas(java.lang.String path)
                         throws java.io.IOException,
                                java.net.URISyntaxException

Reads a SAS7BDAT file.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.net.URISyntaxException

sas

static smile.data.DataFrame sas(java.nio.file.Path path)
                         throws java.io.IOException

Reads a SAS7BDAT file.

Parameters:

path - the input file path.

Throws:

java.io.IOException

arrow

static smile.data.DataFrame arrow(java.lang.String path)
                           throws java.io.IOException,
                                  java.net.URISyntaxException

Reads an Apache Arrow file. Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.net.URISyntaxException

arrow

static smile.data.DataFrame arrow(java.nio.file.Path path)
                           throws java.io.IOException

Reads an Apache Arrow file. Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware.

Parameters:

path - the input file path.

Throws:

java.io.IOException

avro

static smile.data.DataFrame avro(java.lang.String path,
                                 java.io.InputStream schema)
                          throws java.io.IOException,
                                 java.net.URISyntaxException

Reads an Apache Avro file.

Parameters:

path - the input data file path.

schema - the input stream of schema.

Throws:

java.io.IOException

java.net.URISyntaxException

avro

static smile.data.DataFrame avro(java.lang.String path,
                                 java.lang.String schema)
                          throws java.io.IOException,
                                 java.net.URISyntaxException

Reads an Apache Avro file.

Parameters:

path - the input data file path.

schema - the input schema file path.

Throws:

java.io.IOException

java.net.URISyntaxException

avro

static smile.data.DataFrame avro(java.nio.file.Path path,
                                 java.io.InputStream schema)
                          throws java.io.IOException

Reads an Apache Avro file.

Parameters:

path - the input data file path.

schema - the input stream of schema.

Throws:

java.io.IOException

avro

static smile.data.DataFrame avro(java.nio.file.Path path,
                                 java.nio.file.Path schema)
                          throws java.io.IOException

Reads an Apache Avro file.

Parameters:

path - the input data file path.

schema - the input schema file path.

Throws:

java.io.IOException

parquet

static smile.data.DataFrame parquet(java.lang.String path)
                             throws java.io.IOException,
                                    java.net.URISyntaxException

Reads an Apache Parquet file.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.net.URISyntaxException

parquet

static smile.data.DataFrame parquet(java.nio.file.Path path)
                             throws java.io.IOException

Reads an Apache Parquet file.

Parameters:

path - the input file path.

Throws:

java.io.IOException

libsvm

static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>> libsvm(java.lang.String path)
                                                                       throws java.io.IOException,
                                                                              java.net.URISyntaxException

Reads a libsvm sparse dataset. The format of libsvm file is:

<label> <index1>:<value1> <index2>:<value2> ...

where <label> is the target value of the training data. For classification, it should be an integer which identifies a class (multi-class classification is supported). For regression, it's any real number. For one-class SVM, it's not used so can be any number. <index> is an integer starting from 1, and <value> is a real number. The indices must be in an ascending order. The labels in the testing data file are only used to calculate accuracy or error. If they are unknown, just fill this column with a number.

Parameters:

path - the input file path.

Throws:

java.io.IOException

java.net.URISyntaxException

libsvm

static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>> libsvm(java.nio.file.Path path)
                                                                       throws java.io.IOException

Reads a libsvm sparse dataset. The format of libsvm file is:

<label> <index1>:<value1> <index2>:<value2> ...

where <label> is the target value of the training data. For classification, it should be an integer which identifies a class (multi-class classification is supported). For regression, it's any real number. For one-class SVM, it's not used so can be any number. <index> is an integer starting from 1, and <value> is a real number. The indices must be in an ascending order. The labels in the testing data file are only used to calculate accuracy or error. If they are unknown, just fill this column with a number.

Parameters:

path - the input file path.

Throws:

java.io.IOException

libsvm

static smile.data.Dataset<smile.data.Instance<smile.util.SparseArray>> libsvm(java.io.BufferedReader reader)
                                                                       throws java.io.IOException

Reads a libsvm sparse dataset. The format of libsvm file is:

<label> <index1>:<value1> <index2>:<value2> ...

where <label> is the target value of the training data. For classification, it should be an integer which identifies a class (multi-class classification is supported). For regression, it's any real number. For one-class SVM, it's not used so can be any number. <index> is an integer starting from 1, and <value> is a real number. The indices must be in an ascending order. The labels in the testing data file are only used to calculate accuracy or error. If they are unknown, just fill this column with a number.

Parameters:

reader - the input reader.

Throws:

java.io.IOException