[mlpack-svn] r10671 - in mlpack/trunk/src/mlpack: core/io methods/emst methods/gmm methods/hmm methods/kmeans methods/linear_regression methods/naive_bayes methods/nca methods/neighbor_search
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Thu Dec 8 14:29:04 EST 2011
Author: mamidon
Date: 2011-12-08 14:29:03 -0500 (Thu, 08 Dec 2011)
New Revision: 10671
Modified:
mlpack/trunk/src/mlpack/core/io/cli.cpp
mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp
mlpack/trunk/src/mlpack/methods/gmm/gmm_main.cpp
mlpack/trunk/src/mlpack/methods/hmm/train.cpp
mlpack/trunk/src/mlpack/methods/kmeans/kmeans_main.cpp
mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cpp
mlpack/trunk/src/mlpack/methods/nca/nca_main.cpp
mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cpp
Log:
Did some more formatting of output.
Added more shortcuts to methods.
Need to complete formatting.
Modified: mlpack/trunk/src/mlpack/core/io/cli.cpp
===================================================================
--- mlpack/trunk/src/mlpack/core/io/cli.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/core/io/cli.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -429,9 +429,9 @@
for(iter = gmap.begin(); iter != gmap.end(); iter++) {
std::string key = iter->first;
std::string alias = AliasReverseLookup(key);
- alias = alias.length() ? ", " + alias : alias;
+ alias = alias.length() ? ", -" + alias : alias;
- Log::Info << "\t" << key << alias << " : ";
+ Log::Info << " --" << key << alias << " : ";
//Now, figure out what type it is, and print it.
//We can handle strings, ints, bools, floats, doubles.
@@ -481,10 +481,10 @@
if (param != "" && gmap.count(param)) {
ParamData data = gmap[param];
std::string alias = AliasReverseLookup(param);
- alias = alias.length() ? ", "+alias:alias;
+ alias = alias.length() ? ", -"+alias:alias;
- Log::Info << param << alias << " info: " << std::endl;
- Log::Info << "\t" << HyphenateString(data.desc, 8) << std::endl;
+ Log::Info << " --" << param << alias << " info: ";
+ Log::Info << HyphenateString(data.desc, 4) << std::endl;
return;
} else if(param != "") {
//User passed a single variable, but it doesn't exist.
@@ -493,8 +493,8 @@
// Print out the descriptions.
if(docs.programName != "") {
- Log::Info << "Program: " << docs.programName << std::endl;
- Log::Info << "\t" << HyphenateString(docs.documentation,8) << std::endl;
+ Log::Info << docs.programName << std::endl;
+ Log::Info << " " << HyphenateString(docs.documentation,2) << std::endl;
}
else
Log::Info << "Undocumented Program" << std::endl;
@@ -506,11 +506,11 @@
ParamData data = iter->second;
std::string desc = data.desc;
std::string alias = AliasReverseLookup(key);
- alias = alias.length() ? ", "+alias:alias;
+ alias = alias.length() ? ", -"+alias:alias;
//Now, print the descriptions.
- Log::Info << "\t" << key << alias << std::endl;
- Log::Info << "\t\t" << HyphenateString(desc,16) << std::endl;
+ Log::Info << " --" << key << alias << ": ";
+ Log::Info << HyphenateString(desc,4) << std::endl;
Log::Info << std::endl;
}
Modified: mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -16,13 +16,13 @@
#include <mlpack/core.hpp>
-PARAM_STRING_REQ("input_file", "Data input file.", "");
-PARAM_STRING("output_file", "Data output file. Stored as an edge list.", "emst", "emst_output.csv");
+PARAM_STRING_REQ("input_file", "Data input file.", "I");
+PARAM_STRING("output_file", "Data output file. Stored as an edge list.", "O", "emst_output.csv");
PARAM_FLAG("do_naive", "Compute the MST using .", "");
-PARAM_STRING("naive_output_file", "Naive data output file.", "",
+PARAM_STRING("naive_output_file", "Naive data output file.", "N",
"naive_output.csv");
-PARAM_INT("leaf_size", "Leaf size in the kd-tree. Singleton leaves give the empirically best performance at the cost of greater memory requirements.", "", 1);
-PARAM_DOUBLE("total_squared_length", "Squared length of the computed tree.", "", 0.0);
+PARAM_INT("leaf_size", "Leaf size in the kd-tree. Singleton leaves give the empirically best performance at the cost of greater memory requirements.", "L", 1);
+PARAM_DOUBLE("total_squared_length", "Squared length of the computed tree.", "T", 0.0);
using namespace mlpack;
using namespace mlpack::emst;
Modified: mlpack/trunk/src/mlpack/methods/gmm/gmm_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/gmm/gmm_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/gmm/gmm_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -11,8 +11,8 @@
" using the EM algorithm to find the maximum likelihood estimate.");
PARAM_STRING_REQ("data", "A file containing the data on which the model has to "
- "be fit.", "");
-PARAM_INT("gaussians", "g", "", 1);
+ "be fit.", "D");
+PARAM_INT("gaussians", "g", "G", 1);
using namespace mlpack;
using namespace mlpack::gmm;
Modified: mlpack/trunk/src/mlpack/methods/hmm/train.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/hmm/train.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/hmm/train.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -26,22 +26,20 @@
bool train_viterbi();
void usage();
-PARAM_STRING_REQ("type", "HMM type : discrete | gaussian | mixture.", "");
-PARAM_STRING_REQ("profile", "A file containing HMM profile.", "");
-PARAM_STRING_REQ("seqfile", "Output file for the generated sequences.", "");
-PARAM_STRING("algorithm", "Training algorithm: baumwelch | viterbi.", "",
+PARAM_STRING_REQ("type", "HMM type : discrete | gaussian | mixture.", "T");
+PARAM_STRING_REQ("profile", "A file containing HMM profile.", "P");
+PARAM_STRING_REQ("seqfile", "Output file for the generated sequences.", "S");
+PARAM_STRING("algorithm", "Training algorithm: baumwelch | viterbi.", "A",
"baumwelch");
-PARAM_STRING("guess", "File containing guessing HMM model profile.", "",
+PARAM_STRING("guess", "File containing guessing HMM model profile.", "G",
"");
PARAM(double, "tolerance",
- "Error tolerance on log-likelihood as a stopping criteria.", "", 1e-3, false);
-PARAM_INT("maxiter", "Maximum number of iterations, default = 500.", "", 500);
-PARAM_INT("numstate", "If no guessing profile specified, at least provide the number of states.", "", 10);
+ "Error tolerance on log-likelihood as a stopping criteria.", "R", 1e-3, false);
+PARAM_INT("maxiter", "Maximum number of iterations, default = 500.", "M", 500);
+PARAM_INT("numstate", "If no guessing profile specified, at least provide the number of states.", "N", 10);
-PARAM_MODULE("hmm", "This is a program generating sequences from HMM models.");
-
void usage() {
Log::Warn << "Usage:" << std::endl;
Log::Warn << " train --type=={discrete|gaussian|mixture} OPTCLIN" << std::endl;
Modified: mlpack/trunk/src/mlpack/methods/kmeans/kmeans_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/kmeans/kmeans_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/kmeans/kmeans_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -21,19 +21,19 @@
"becomes empty, the point furthest from the centroid of the cluster with "
"maximum variance is taken to fill that cluster.");
-PARAM_STRING_REQ("input_file", "Input dataset to perform clustering on.", "");
-PARAM_INT_REQ("clusters", "Number of clusters to find.", "");
+PARAM_STRING_REQ("input_file", "Input dataset to perform clustering on.", "I");
+PARAM_INT_REQ("clusters", "Number of clusters to find.", "C");
PARAM_FLAG("in_place", "If specified, a column of the learned cluster "
"assignments will be added to the input dataset file. In this case "
- "--output_file is not necessary.", "");
-PARAM_STRING("output_file", "File to write output labels to.", "", "");
-PARAM_FLAG("allow_empty_clusters", "Allow empty clusters to be created.", "");
-PARAM_FLAG("labels_only", "Only output labels into output file.", "");
+ "--output_file is not necessary.", "P");
+PARAM_STRING("output_file", "File to write output labels to.", "O", "");
+PARAM_FLAG("allow_empty_clusters", "Allow empty clusters to be created.", "E");
+PARAM_FLAG("labels_only", "Only output labels into output file.", "L");
PARAM_DOUBLE("overclustering", "Finds (overclustering * clusters) clusters, "
"then merges them together until only the desired number of clusters are "
- "left.", "", 1.0);
+ "left.", "C", 1.0);
PARAM_INT("max_iterations", "Maximum number of iterations before K-Means "
- "terminates.", "", 1000);
+ "terminates.", "M", 1000);
int main(int argc, char** argv)
{
Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -9,12 +9,12 @@
using namespace mlpack;
-PARAM_STRING_REQ("train", "A file containing X", "");
+PARAM_STRING_REQ("train", "A file containing X", "X");
PARAM_STRING_REQ("test", "A file containing data points to predict on",
- "");
+ "T");
PARAM_STRING("responses", "A file containing the y values for X; if not "
"present, it is assumed the last column of train contains these values.",
- "", "");
+ "", "R");
PROGRAM_INFO("Simple Linear Regression", "An implementation of simple linear "
"regression using ordinary least squares.");
Modified: mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -27,12 +27,12 @@
#include "simple_nbc.hpp"
-PARAM_INT_REQ("classes", "The number of classes present in the data.", "")
+PARAM_INT_REQ("classes", "The number of classes present in the data.", "C")
-PARAM_STRING_REQ("train", "A file containing the training set", "");
-PARAM_STRING_REQ("test", "A file containing the test set", "");
+PARAM_STRING_REQ("train", "A file containing the training set", "R");
+PARAM_STRING_REQ("test", "A file containing the test set", "T");
PARAM_STRING("output", "The file in which the output of the test would "
- "be written, defaults to 'output.csv')", "", "output.csv");
+ "be written, defaults to 'output.csv')", "O", "output.csv");
PROGRAM_INFO("Parametric Naive Bayes", "This program test drives the Parametric"
" Naive Bayes Classifier assuming that the features are sampled from a "
Modified: mlpack/trunk/src/mlpack/methods/nca/nca_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/nca/nca_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/nca/nca_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -13,8 +13,8 @@
PROGRAM_INFO("Neighborhood Components Analysis",
"documentation not done yet");
-PARAM_STRING_REQ("input_file", "Input dataset to run NCA on.", "");
-PARAM_STRING_REQ("output_file", "Output file for learned distance matrix.", "");
+PARAM_STRING_REQ("input_file", "Input dataset to run NCA on.", "I");
+PARAM_STRING_REQ("output_file", "Output file for learned distance matrix.", "O");
using namespace mlpack;
using namespace mlpack::nca;
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cpp 2011-12-08 19:20:11 UTC (rev 10670)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cpp 2011-12-08 19:29:03 UTC (rev 10671)
@@ -40,15 +40,15 @@
// Define our input parameters that this program will take.
PARAM_STRING_REQ("reference_file", "File containing the reference dataset.",
- "");
-PARAM_STRING("query_file", "File containing query points (optional).", "", "");
-PARAM_STRING_REQ("distances_file", "File to output distances into.", "");
-PARAM_STRING_REQ("neighbors_file", "File to output neighbors into.", "");
+ "R");
+PARAM_STRING("query_file", "File containing query points (optional).", "Q", "");
+PARAM_STRING_REQ("distances_file", "File to output distances into.", "D");
+PARAM_STRING_REQ("neighbors_file", "File to output neighbors into.", "N");
-PARAM_INT("leaf_size", "Leaf size for tree building.", "", 20);
-PARAM_FLAG("naive", "If true, O(n^2) naive mode is used for computation.", "");
+PARAM_INT("leaf_size", "Leaf size for tree building.", "L", 20);
+PARAM_FLAG("naive", "If true, O(n^2) naive mode is used for computation.", "N");
PARAM_FLAG("single_mode", "If true, single-tree search is used (as opposed to "
- "dual-tree search.", "");
+ "dual-tree search.", "S");
PARAM_INT_REQ("k", "Number of furthest neighbors to find.", "");
int main(int argc, char *argv[])
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