# This file is part of NIT ( http://www.nitlanguage.org ).
#
# Copyright 2012 Jean Privat <jean@pryen.org>
+# Copyright 2014 Alexandre Terrasa <alexandre@moz-code.org>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
module metrics_base
import modelbuilder
+import csv
+import counter
+import console
redef class ToolContext
+ # --all
+ var opt_all = new OptionBool("Compute all metrics", "--all")
+
+ # --mmodules
+ var opt_mmodules = new OptionBool("Compute metrics about mmodules", "--mmodules")
+ # --mclassses
+ var opt_mclasses = new OptionBool("Compute metrics about mclasses", "--mclasses")
+ # --mendel
+ var opt_mendel = new OptionBool("Compute mendel metrics", "--mendel")
+ # --inheritance
+ var opt_inheritance = new OptionBool("Compute metrics about inheritance usage", "--inheritance")
+ # --genericity
+ var opt_refinement = new OptionBool("Compute metrics about refinement usage", "--refinement")
+ # --self
+ var opt_self = new OptionBool("Compute metrics about the usage of explicit and implicit self", "--self")
+ # --ast
+ var opt_ast = new OptionBool("Compute metrics about the usage of nodes and identifiers in the AST", "--ast")
+ # --nullables
+ var opt_nullables = new OptionBool("Compute metrics on nullables send", "--nullables")
# --static-types
var opt_static_types = new OptionBool("Compute explicit static types metrics", "--static-types")
# --tables
var opt_tables = new OptionBool("Compute tables metrics", "--tables")
# --rta
var opt_rta = new OptionBool("Compute RTA metrics", "--rta")
+ # --generate-csv
+ var opt_csv = new OptionBool("Export metrics in CSV format", "--csv")
# --generate_hyperdoc
var opt_generate_hyperdoc = new OptionBool("Generate Hyperdoc", "--generate_hyperdoc")
-
+ # --poset
+ var opt_poset = new OptionBool("Complete metrics on posets", "--poset")
+ # --no-colors
+ var opt_nocolors = new OptionBool("Disable colors in console outputs", "--no-colors")
+ # --dir
var opt_dir = new OptionString("Directory where some statistics files are generated", "-d", "--dir")
+
+ # Output directory for metrics files.
var output_dir: String = "."
redef init
do
super
+ self.option_context.add_option(opt_all)
+ self.option_context.add_option(opt_mmodules)
+ self.option_context.add_option(opt_mclasses)
+ self.option_context.add_option(opt_mendel)
+ self.option_context.add_option(opt_inheritance)
+ self.option_context.add_option(opt_refinement)
+ self.option_context.add_option(opt_self)
+ self.option_context.add_option(opt_ast)
+ self.option_context.add_option(opt_nullables)
self.option_context.add_option(opt_static_types)
self.option_context.add_option(opt_tables)
self.option_context.add_option(opt_rta)
+ self.option_context.add_option(opt_csv)
self.option_context.add_option(opt_generate_hyperdoc)
+ self.option_context.add_option(opt_poset)
self.option_context.add_option(opt_dir)
+ self.option_context.add_option(opt_nocolors)
end
- redef fun process_options
+ redef fun process_options(args)
do
super
var val = self.opt_dir.value
self.output_dir = val
end
end
+
+ # Format and colorize a string heading of level 1 for console output.
+ #
+ # Default style is yellow and bold.
+ fun format_h1(str: String): String do
+ if opt_nocolors.value then return str
+ return str.yellow.bold
+ end
+
+ # Format and colorize a string heading of level 2 for console output.
+ #
+ # Default style is white and bold.
+ fun format_h2(str: String): String do
+ if opt_nocolors.value then return str
+ return str.bold
+ end
+
+ # Format and colorize a string heading of level 3 for console output.
+ #
+ # Default style is white and nobold.
+ fun format_h3(str: String): String do
+ if opt_nocolors.value then return str
+ return str
+ end
+
+ # Format and colorize a string heading of level 4 for console output.
+ #
+ # Default style is green.
+ fun format_h4(str: String): String do
+ if opt_nocolors.value then return str
+ return str.green
+ end
+
+ # Format and colorize a string heading of level 5 for console output.
+ #
+ # Default style is light gray.
+ fun format_p(str: String): String do
+ if opt_nocolors.value then return str
+ return str.light_gray
+ end
+
end
-# A counter counts occurence of things
-# Use this instead of a HashMap[E, Int]
-class Counter[E: Object]
- # Total number of counted occurences
- var total: Int = 0
+# A Metric is used to collect data about things
+#
+# The concept is reified here for a better organization and documentation
+interface Metric
- private var map = new HashMap[E, Int]
+ # Type of elements measured by this metric.
+ type ELM: Object
- # The number of counted occurences of `e'
- fun [](e: E): Int
- do
- var map = self.map
- if map.has_key(e) then return map[e]
- return 0
+ # Type of values used to measure elements.
+ type VAL: Object
+
+ # Type of data representation used to associate elements and values.
+ type RES: Map[ELM, VAL]
+
+ # The name of this metric (generally an acronym about the metric).
+ fun name: String is abstract
+
+ # A long and understandable description about what is measured by this metric.
+ fun desc: String is abstract
+
+ # Clear all results for this metric
+ fun clear is abstract
+
+ # Values for each element
+ fun values: RES is abstract
+
+ # Collect metric values on elements
+ fun collect(elements: Set[ELM]) is abstract
+
+ # The value calculated for the element
+ fun [](element: ELM): VAL do return values[element]
+
+ # Does the element have a value for this metric?
+ fun has_element(element: ELM): Bool do return values.has_key(element)
+
+ # The values average
+ fun avg: Float is abstract
+
+ # Pretty print the metric results in console
+ fun to_console(indent: Int, colors: Bool) do
+ if values.is_empty then
+ if colors then
+ print "{"\t" * indent}{name}: {desc} -- nothing".green
+ else
+ print "{"\t" * indent}{name}: {desc} -- nothing"
+ end
+ return
+ end
+
+ var max = self.max
+ var min = self.min
+ if colors then
+ print "{"\t" * indent}{name}: {desc}".green
+ print "{"\t" * indent} avg: {avg}".light_gray
+ print "{"\t" * indent} max: {max} ({self[max]})".light_gray
+ print "{"\t" * indent} min: {min} ({self[min]})".light_gray
+ print "{"\t" * indent} std: {std_dev}".light_gray
+ else
+ print "{"\t" * indent}{name}: {desc}"
+ print "{"\t" * indent} avg: {avg}"
+ print "{"\t" * indent} max: {max} ({self[max]})"
+ print "{"\t" * indent} min: {min} ({self[min]})"
+ print "{"\t" * indent} std: {std_dev}"
+ end
end
- # Count one more occurence of `e'
- fun inc(e: E)
- do
- self.map[e] = self[e] + 1
- total += 1
+ # The sum of all the values.
+ fun sum: VAL is abstract
+
+ # The values standard derivation
+ fun std_dev: Float is abstract
+
+ # The element with the highest value
+ fun max: ELM is abstract
+
+ # The element with the lowest value
+ fun min: ELM is abstract
+
+ # The value threshold above what elements are considered as 'interesting'
+ fun threshold: Float do return avg + std_dev
+
+ # The set of element above the threshold
+ fun above_threshold: Set[ELM] is abstract
+
+ # Sort the metric keys by values
+ fun sort: Array[ELM] do
+ return values.keys_sorted_by_values(default_reverse_comparator)
end
+end
- # Return an array of elements sorted by occurences
- fun sort: Array[E]
- do
- var res = map.keys.to_a
- var sorter = new CounterSorter[E](self)
- sorter.sort(res)
- #res.sort !cmp a, b = map[a] <=> map[b]
- return res
+# A Metric that collects integer data
+#
+# Used to count things
+class IntMetric
+ super Metric
+
+ redef type VAL: Int
+ redef type RES: Counter[ELM]
+
+ # `IntMetric` uses a Counter to store values in intern.
+ protected var values_cache = new Counter[ELM]
+
+ redef fun values do return values_cache
+
+ redef fun clear do values_cache.clear
+
+ redef fun sum do return values_cache.sum
+
+ redef fun max do
+ assert not values_cache.is_empty
+ return values_cache.max.as(not null)
+ end
+
+ redef fun min do
+ assert not values_cache.is_empty
+ return values_cache.min.as(not null)
+ end
+
+ # Values average
+ redef fun avg do return values_cache.avg
+
+ redef fun std_dev do return values_cache.std_dev
+
+ redef fun above_threshold do
+ var above = new HashSet[ELM]
+ var threshold = threshold
+ for element, value in values do
+ if value.to_f > threshold then above.add(element)
+ end
+ return above
+ end
+
+ redef fun to_console(indent, colors) do
+ super
+ if colors then
+ print "{"\t" * indent} sum: {sum}".light_gray
+ else
+ print "{"\t" * indent} sum: {sum}"
+ end
end
end
-private class CounterSorter[E: Object]
- super AbstractSorter[E]
- var counter: Counter[E]
- redef fun compare(a,b) do return self.counter.map[a] <=> self.counter.map[b]
+# A Metric that collects float datas
+#
+# Used sor summarization
+class FloatMetric
+ super Metric
+
+ redef type VAL: Float
+
+ # `FloatMetric` uses a Map to store values in intern.
+ protected var values_cache = new HashMap[ELM, VAL]
+
+ redef fun values do return values_cache
+
+ redef fun clear do values_cache.clear
+
+
+ redef fun sum do
+ var sum = 0.0
+ for v in values.values do
+ if v.is_nan then continue
+ sum += v
+ end
+ return sum
+ end
+
+ redef fun max do
+ assert not values.is_empty
+ var max: nullable Float = null
+ var elem: nullable ELM = null
+ for e, v in values do
+ if max == null or v > max then
+ max = v
+ elem = e
+ end
+ end
+ return elem.as(not null)
+ end
+
+ redef fun min do
+ assert not values.is_empty
+ var min: nullable Float = null
+ var elem: nullable ELM = null
+ for e, v in values do
+ if min == null or v < min then
+ min = v
+ elem = e
+ end
+ end
+ return elem.as(not null)
+ end
+
+ redef fun avg do
+ if values.is_empty then return 0.0
+ return sum / values.length.to_f
+ end
+
+ redef fun std_dev do
+ var sum = 0.0
+ for value in values.values do
+ if value.is_nan then continue
+ sum += (value - avg).pow(2.to_f)
+ end
+ return (sum / values.length.to_f).sqrt
+ end
+
+ redef fun above_threshold do
+ var above = new HashSet[ELM]
+ var threshold = threshold
+ for element, value in values do
+ if value > threshold then above.add(element)
+ end
+ return above
+ end
+
+ redef fun to_console(indent, colors) do
+ super
+ if colors then
+ print "{"\t" * indent} sum: {sum}".light_gray
+ else
+ print "{"\t" * indent} sum: {sum}"
+ end
+ end
end
-# Helper function to display n/d and handle division by 0
-fun div(n: Int, d: Int): String
-do
- if d == 0 then return "na"
- return ((100*n/d).to_f/100.0).to_precision(2)
+# A MetricSet is a metric holder
+#
+# It purpose is to be extended with a metric collect service
+class MetricSet
+
+ # Type of element measured by this `MetricSet`.
+ type ELM: Object
+
+ # Metrics to compute
+ var metrics: Set[Metric] = new HashSet[Metric]
+
+ # Add a metric to the set
+ fun register(metrics: Metric...) do for metric in metrics do self.metrics.add(metric)
+
+ # Clear all results for all metrics
+ fun clear do for metric in metrics do metric.clear
+
+ # Collect all metrics for this set of class
+ fun collect(elements: Set[ELM]) do
+ for metric in metrics do metric.collect(elements)
+ end
+
+ # Pretty print the resuls in console
+ fun to_console(indent: Int, colors: Bool) do
+ for metric in metrics do metric.to_console(indent, colors)
+ end
+
+ # Export the metric set in CSV format
+ fun to_csv: CsvDocument do
+ var csv = new CsvDocument
+
+ csv.format = new CsvFormat('"', ';', "\n")
+
+ # set csv headers
+ csv.header.add("entry")
+ for metric in metrics do csv.header.add(metric.name)
+
+ # collect all entries to merge metric results
+ var entries = new HashSet[ELM]
+ for metric in metrics do
+ for entry in metric.values.keys do entries.add(entry)
+ end
+
+ # collect results
+ for entry in entries do
+ var line = [entry.to_s]
+ for metric in metrics do
+ if metric.has_element(entry) then
+ line.add(metric[entry].to_s)
+ else
+ line.add("n/a")
+ end
+ end
+ csv.records.add(line)
+ end
+ return csv
+ end
end
nitlanguage / nit.git / blobdiff