In Files

  • minitest/benchmark.rb
  • minitest/unit.rb

MiniTest::Unit::TestCase

Subclass TestCase to create your own tests. Typically you’ll want a TestCase subclass per implementation class.

See MiniTest::Assertions

Public Class Methods

bench_exp(min, max, base = 10) click to toggle source

Returns a set of ranges stepped exponentially from min to max by powers of base. Eg:

bench_exp(2, 16, 2) # => [2, 4, 8, 16]
 
               # File minitest/benchmark.rb, line 26
def self.bench_exp min, max, base = 10
  min = (Math.log10(min) / Math.log10(base)).to_i
  max = (Math.log10(max) / Math.log10(base)).to_i

  (min..max).map { |m| base ** m }.to_a
end
            
bench_linear(min, max, step = 10) click to toggle source

Returns a set of ranges stepped linearly from min to max by step. Eg:

bench_linear(20, 40, 10) # => [20, 30, 40]
 
               # File minitest/benchmark.rb, line 39
def self.bench_linear min, max, step = 10
  (min..max).step(step).to_a
rescue LocalJumpError # 1.8.6
  r = []; (min..max).step(step) { |n| r << n }; r
end
            
bench_range() click to toggle source

Specifies the ranges used for benchmarking for that class. Defaults to exponential growth from 1 to 10k by powers of 10. Override if you need different ranges for your benchmarks.

See also: ::bench_exp and ::bench_linear.

 
               # File minitest/benchmark.rb, line 67
def self.bench_range
  bench_exp 1, 10_000
end
            
benchmark_suites() click to toggle source

Returns all test suites that have benchmark methods.

 
               # File minitest/benchmark.rb, line 56
def self.benchmark_suites
  TestCase.test_suites.reject { |s| s.benchmark_methods.empty? }
end
            
i_suck_and_my_tests_are_order_dependent!() click to toggle source

Call this at the top of your tests when you absolutely positively need to have ordered tests. In doing so, you’re admitting that you suck and your tests are weak.

 
               # File minitest/unit.rb, line 1367
def self.i_suck_and_my_tests_are_order_dependent!
  class << self
    undef_method :test_order if method_defined? :test_order
    define_method :test_order do :alpha end
  end
end
            
make_my_diffs_pretty!() click to toggle source

Make diffs for this TestCase use pretty_inspect so that diff in assert_equal can be more details. NOTE: this is much slower than the regular inspect but much more usable for complex objects.

 
               # File minitest/unit.rb, line 1380
def self.make_my_diffs_pretty!
  require 'pp'

  define_method :mu_pp do |o|
    o.pretty_inspect
  end
end
            
parallelize_me!() click to toggle source

Call this at the top of your tests when you want to run your tests in parallel. In doing so, you’re admitting that you rule and your tests are awesome.

 
               # File minitest/unit.rb, line 1393
def self.parallelize_me!
  class << self
    undef_method :test_order if method_defined? :test_order
    define_method :test_order do :parallel end
  end
end
            

Public Instance Methods

assert_performance(validation, &work) click to toggle source

Runs the given work, gathering the times of each run. Range and times are then passed to a given validation proc. Outputs the benchmark name and times in tab-separated format, making it easy to paste into a spreadsheet for graphing or further analysis.

Ranges are specified by ::bench_range.

Eg:

def bench_algorithm
  validation = proc { |x, y| ... }
  assert_performance validation do |n|
    @obj.algorithm(n)
  end
end
 
               # File minitest/benchmark.rb, line 89
def assert_performance validation, &work
  range = self.class.bench_range

  io.print "#{__name__}"

  times = []

  range.each do |x|
    GC.start
    t0 = Time.now
    instance_exec(x, &work)
    t = Time.now - t0

    io.print "\t%9.6f" % t
    times << t
  end
  io.puts

  validation[range, times]
end
            
assert_performance_constant(threshold = 0.99, &work) click to toggle source

Runs the given work and asserts that the times gathered fit to match a constant rate (eg, linear slope == 0) within a given threshold. Note: because we’re testing for a slope of 0, R^2 is not a good determining factor for the fit, so the threshold is applied against the slope itself. As such, you probably want to tighten it from the default.

See www.graphpad.com/curvefit/goodness_of_fit.htm for more details.

Fit is calculated by fit_linear.

Ranges are specified by ::bench_range.

Eg:

def bench_algorithm
  assert_performance_constant 0.9999 do |n|
    @obj.algorithm(n)
  end
end
 
               # File minitest/benchmark.rb, line 133
def assert_performance_constant threshold = 0.99, &work
  validation = proc do |range, times|
    a, b, rr = fit_linear range, times
    assert_in_delta 0, b, 1 - threshold
    [a, b, rr]
  end

  assert_performance validation, &work
end
            
assert_performance_exponential(threshold = 0.99, &work) click to toggle source

Runs the given work and asserts that the times gathered fit to match a exponential curve within a given error threshold.

Fit is calculated by fit_exponential.

Ranges are specified by ::bench_range.

Eg:

def bench_algorithm
  assert_performance_exponential 0.9999 do |n|
    @obj.algorithm(n)
  end
end
 
               # File minitest/benchmark.rb, line 159
def assert_performance_exponential threshold = 0.99, &work
  assert_performance validation_for_fit(:exponential, threshold), &work
end
            
assert_performance_linear(threshold = 0.99, &work) click to toggle source

Runs the given work and asserts that the times gathered fit to match a straight line within a given error threshold.

Fit is calculated by fit_linear.

Ranges are specified by ::bench_range.

Eg:

def bench_algorithm
  assert_performance_linear 0.9999 do |n|
    @obj.algorithm(n)
  end
end
 
               # File minitest/benchmark.rb, line 179
def assert_performance_linear threshold = 0.99, &work
  assert_performance validation_for_fit(:linear, threshold), &work
end
            
assert_performance_power(threshold = 0.99, &work) click to toggle source

Runs the given work and asserts that the times gathered curve fit to match a power curve within a given error threshold.

Fit is calculated by fit_power.

Ranges are specified by ::bench_range.

Eg:

def bench_algorithm
  assert_performance_power 0.9999 do |x|
    @obj.algorithm
  end
end
 
               # File minitest/benchmark.rb, line 199
def assert_performance_power threshold = 0.99, &work
  assert_performance validation_for_fit(:power, threshold), &work
end
            
fit_error(xys) click to toggle source

Takes an array of x/y pairs and calculates the general R^2 value.

See: en.wikipedia.org/wiki/Coefficient_of_determination

 
               # File minitest/benchmark.rb, line 208
def fit_error xys
  y_bar  = sigma(xys) { |x, y| y } / xys.size.to_f
  ss_tot = sigma(xys) { |x, y| (y    - y_bar) ** 2 }
  ss_err = sigma(xys) { |x, y| (yield(x) - y) ** 2 }

  1 - (ss_err / ss_tot)
end
            
fit_exponential(xs, ys) click to toggle source

To fit a functional form: y = ae^(bx).

Takes x and y values and returns [a, b, r^2].

See: mathworld.wolfram.com/LeastSquaresFittingExponential.html

 
               # File minitest/benchmark.rb, line 223
def fit_exponential xs, ys
  n     = xs.size
  xys   = xs.zip(ys)
  sxlny = sigma(xys) { |x,y| x * Math.log(y) }
  slny  = sigma(xys) { |x,y| Math.log(y)     }
  sx2   = sigma(xys) { |x,y| x * x           }
  sx    = sigma xs

  c = n * sx2 - sx ** 2
  a = (slny * sx2 - sx * sxlny) / c
  b = ( n * sxlny - sx * slny ) / c

  return Math.exp(a), b, fit_error(xys) { |x| Math.exp(a + b * x) }
end
            
fit_linear(xs, ys) click to toggle source

Fits the functional form: a + bx.

Takes x and y values and returns [a, b, r^2].

See: mathworld.wolfram.com/LeastSquaresFitting.html

 
               # File minitest/benchmark.rb, line 245
def fit_linear xs, ys
  n   = xs.size
  xys = xs.zip(ys)
  sx  = sigma xs
  sy  = sigma ys
  sx2 = sigma(xs)  { |x|   x ** 2 }
  sxy = sigma(xys) { |x,y| x * y  }

  c = n * sx2 - sx**2
  a = (sy * sx2 - sx * sxy) / c
  b = ( n * sxy - sx * sy ) / c

  return a, b, fit_error(xys) { |x| a + b * x }
end
            
fit_power(xs, ys) click to toggle source

To fit a functional form: y = ax^b.

Takes x and y values and returns [a, b, r^2].

See: mathworld.wolfram.com/LeastSquaresFittingPowerLaw.html

 
               # File minitest/benchmark.rb, line 267
def fit_power xs, ys
  n       = xs.size
  xys     = xs.zip(ys)
  slnxlny = sigma(xys) { |x, y| Math.log(x) * Math.log(y) }
  slnx    = sigma(xs)  { |x   | Math.log(x)               }
  slny    = sigma(ys)  { |   y| Math.log(y)               }
  slnx2   = sigma(xs)  { |x   | Math.log(x) ** 2          }

  b = (n * slnxlny - slnx * slny) / (n * slnx2 - slnx ** 2);
  a = (slny - b * slnx) / n

  return Math.exp(a), b, fit_error(xys) { |x| (Math.exp(a) * (x ** b)) }
end
            
io() click to toggle source

Return the output IO object

 
               # File minitest/unit.rb, line 1344
def io
  @__io__ = true
  MiniTest::Unit.output
end
            
io?() click to toggle source

Have we hooked up the IO yet?

 
               # File minitest/unit.rb, line 1352
def io?
  @__io__
end
            
passed?() click to toggle source

Returns true if the test passed.

 
               # File minitest/unit.rb, line 1434
def passed?
  @passed
end
            
run(runner) click to toggle source

Runs the tests reporting the status to runner

 
               # File minitest/unit.rb, line 1281
def run runner
  trap "INFO" do
    runner.report.each_with_index do |msg, i|
      warn "\n%3d) %s" % [i + 1, msg]
    end
    warn ''
    time = runner.start_time ? Time.now - runner.start_time : 0
    warn "Current Test: %s#%s %.2fs" % [self.class, self.__name__, time]
    runner.status $stderr
  end if SUPPORTS_INFO_SIGNAL

  start_time = Time.now

  result = ""
  begin
    @passed = nil
    self.before_setup
    self.setup
    self.after_setup
    self.run_test self.__name__
    result = "." unless io?
    time = Time.now - start_time
    runner.record self.class, self.__name__, self._assertions, time, nil
    @passed = true
  rescue *PASSTHROUGH_EXCEPTIONS
    raise
  rescue Exception => e
    @passed = false
    time = Time.now - start_time
    runner.record self.class, self.__name__, self._assertions, time, e
    result = runner.puke self.class, self.__name__, e
  ensure
    %w{ before_teardown teardown after_teardown }.each do |hook|
      begin
        self.send hook
      rescue *PASSTHROUGH_EXCEPTIONS
        raise
      rescue Exception => e
        @passed = false
        result = runner.puke self.class, self.__name__, e
      end
    end
    trap 'INFO', 'DEFAULT' if SUPPORTS_INFO_SIGNAL
  end
  result
end
            
setup() click to toggle source

Runs before every test. Use this to set up before each test run.

 
               # File minitest/unit.rb, line 1442
def setup; end
            
sigma(enum, &block) click to toggle source

Enumerates over enum mapping block if given, returning the sum of the result. Eg:

sigma([1, 2, 3])                # => 1 + 2 + 3 => 7
sigma([1, 2, 3]) { |n| n ** 2 } # => 1 + 4 + 9 => 14
 
               # File minitest/benchmark.rb, line 288
def sigma enum, &block
  enum = enum.map(&block) if block
  enum.inject { |sum, n| sum + n }
end
            
teardown() click to toggle source

Runs after every test. Use this to clean up after each test run.

 
               # File minitest/unit.rb, line 1448
def teardown; end
            
validation_for_fit(msg, threshold) click to toggle source

Returns a proc that calls the specified fit method and asserts that the error is within a tolerable threshold.

 
               # File minitest/benchmark.rb, line 297
def validation_for_fit msg, threshold
  proc do |range, times|
    a, b, rr = send "fit_#{msg}", range, times
    assert_operator rr, :>=, threshold
    [a, b, rr]
  end
end
            

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