EZ Stats

EZ Stats simplifies your statistics needs by offering the following global functions via a sole, auto-loaded singleton script:

sanitize() - Ingests an Array with elements of any type, sanitizes non-integers/floats, and returns an Array[float]

mean() - Calculates the statistical mean (average) of a dataset

median() - Calculates the statistical median of a dataset

spread() - Calculates the statistical range of a dataset

minima() - Calculates the statistical minima of a dataset

maxima() - Calculates the statistical maxima of a dataset

variance() - Calculates the mean-based variance of a dataset

standev() - Calculates the mean-based standard deviation of a dataset

mad() - Calculates the median absolute deviation of a dataset

all() - Calculates all summary statistics above and returns them in a Dictionary

Badges

Installation

Install from the Godot editor's AssetLib

  1.) Click on "AssetLib" at the top-middle of the editor
  2.) Search for "EZ Stats" without double-quotes
  3.) Click on "EZ Stats"
  4.) Click "Download"
  5.) Click "Install"
  6.) Navigate to Project -> Project Settings -> Plugins and check the "On" box 
  7.) Call the EZ Stats functions anywhere in the rest of your project's GDScript scripts via:
    7.1.) EZSTATS.sanitize()
    7.2.) EZSTATS.mean()
    7.3.) EZSTATS.median()
    7.4.) EZSTATS.spread()
    7.5.) EZSTATS.minima()
    7.6.) EZSTATS.maxima()
    7.7.) EZSTATS.variance()
    7.8.) EZSTATS.standev()
    7.9.) EZSTATS.mad()
    7.10.) EZSTATS.all()

Install from the .zip file

  1.) Download and un-zip the addons folder from this repo
  2.) If your project doesn't yet have an addons folder, paste the addons folder as-is into the root of res://
    2.1.) res:// structure should be res://addons/ez_stats/$contents
    2.2.) If you already have an addons folder, just paste the ez_stats folder into it
  3.) Navigate to Project -> Project Settings -> Plugins and check the "On" box
  4.) Call the EZ Stats functions anywhere in the rest of your project's GDScript scripts via:
    4.1.) EZSTATS.sanitize()
    4.2.) EZSTATS.mean()
    4.3.) EZSTATS.median()
    4.4.) EZSTATS.spread()
    4.5.) EZSTATS.minima()
    4.6.) EZSTATS.maxima()
    4.7.) EZSTATS.variance()
    4.8.) EZSTATS.standev()
    4.9.) EZSTATS.mad()
    4.10.) EZSTATS.all()

Usage

EZSTATS.sanitize()

  EZSTATS.sanitize(sources: Array) -> Array[float]

  ##e.g. Sanitize a sample Array of integers and floats:

  var sample_source: Array = [1, 2.5, 3, false, "test"]
  var sanitized_source: Array[float] = EZSTATS.sanitize(sample_source)
  print(str(sanitize_source)) ##Will show [1.0, 2.5, 3.0]

Parameters	Type	Description
sources	Array	Required. Source data values in an Array

Returns	Type	Description
sanitized	Array[float]	A float array containing all sanitized, integer or float only, values

EZSTATS.mean()

  EZSTATS.mean(data: Array[float], dof: float) -> float

  ##e.g. Find the mean of a sample sanitized source array

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var mean: float = EZSTATS.mean(sanitized_source, 0.001)
  print(str(mean)) ##Will return 4.625

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
mean	float	A float representative of the mean of the data values

EZSTATS.median()

  EZSTATS.median(data: Array[float], dof: float) -> float

  ##e.g. Find the median of a sample sanitized source array

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var median: float = EZSTATS.median(sanitized_source, 0.01)
  print(str(median)) ##Will return 3.75

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
median	float	A float representative of the median of the data values

EZSTATS.spread()

  EZSTATS.spread(data: Array[float], dof: float) -> void

  ##e.g. Find the spread of a sample sanitized source array

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var spread: float = EZSTATS.spread(sanitized_source, 0.1)
  print(str(spread)) ##Will return 9

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
mean	float	A float representative of the spread of the data values

EZSTATS.minima()

  EZSTATS.minima(data: Array[float], dof: float) -> void

  ##e.g. Find the minima, smallest value, of a sample sanitized source array
  
  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var minima: float = EZSTATS.minima(sanitized_source, 0.1)
  print(str(minima)) ##Will return 1

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
mean	float	A float representative of the minima data value

EZSTATS.maxima()

  EZSTATS.maxima(data: Array[float], dof: float) -> void

  ##e.g. Find the maxima, largest value, of a sample sanitized source array
  
  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var maxima: float = EZSTATS.maxima(sanitized_source, 0.1)
  print(str(maxima)) ##Will return 10

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
mean	float	A float representative of the maxima data value

EZSTATS.variance()

  variance(data: Array[float], dof: float) -> float

  ##e.g Find the variance of a sample sanitized source dataset

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var variance: float = EZSTATS.variance(sanitized_source, 0.0001)
  print(str(variance)) ##Will return 15.5625

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
variance	float	A float representative of the data's variance

EZSTATS.standev()

  standev(data: Array[float], dof: float) -> float

  ##e.g Find the standard deviation of a sample sanitized source dataset

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var standev: float = EZSTATS.standev(sanitized_source, 0.01)
  print(str(standev)) ##Will return 3.54

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
standev	float	A float representative of the data's standard deviation

EZSTATS.mad()

  mad(data: Array[float], dof: float) -> float

  ##e.g Find the median absolute deviation of a sample sanitized source dataset

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var mad: float = EZSTATS.mad(sanitized_source, 0.001)
  print(str(mad)) ##Will return 2.875

Parameters	Type	Description
data	Array[float]	Required. Sanitized source data values in an Array[float]
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
mad	float	A float representative of the data's median absolute deviation

EZSTATS.all()

  all(sources: Array, dof: float) -> Dictionary

  ##e.g Calculate all summary statistics

  var sanitized_source: Array[float] = [1, 2.5, 5, 10]
  var all: Dictionary = EZSTATS.all(sanitized_source, 0.01)
  print(str(all)) ##Will return all values rounded to the 0.01 (hundredths) place
  ##{
        ##"Mean": 4.63,
        ##"Median": 3.75,
        ##"Spread": 9.0,
        ##"Minima": 1.0,
        ##"Maxima": 10.0,
        ##"Variance": 15.56,
        ##"Standev": 3.54,
        ##"Mad": 2.88
    ##}

Parameters	Type	Description
sources	Array	Required. Source data values, will be sanitized for you
dof	float	Required. Degrees of Freedom, 10^n-th place

Returns	Type	Description
results	Dictionary	A dictionary containing all summary statistics

Documentation

• Snapped()

Acknowledgements

• Awesome README
• Godot Foundation
• Shields.io Badges
• Opensource.org License Templates

Authors

Tundra Peaks Studios

@aaron-tundrapeaksstudios

License

MIT