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Keep calm and carry on #56

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merged 4 commits into from
Jun 2, 2017
Merged

Keep calm and carry on #56

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0b78ee2
Keep calm and carry on
michiel-de-muynck Jun 2, 2017
971d9ce
Ran rustfmt
michiel-de-muynck Jun 2, 2017
52d9906
Update changelog
michiel-de-muynck Jun 2, 2017
7fe9e9f
Add test case for Chi distribution with high degree of freedom
michiel-de-muynck Jun 2, 2017
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12 changes: 0 additions & 12 deletions src/distribution/bernoulli.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -127,10 +127,6 @@ impl Univariate<u64, f64> for Bernoulli {
/// Calculates the cumulative distribution
/// function for the bernoulli distribution at `x`.
///
/// # Panics
///
/// If `x < 0.0` or `x > 1.0`
///
/// # Formula
///
/// ```ignore
Expand Down Expand Up @@ -277,10 +273,6 @@ impl Discrete<u64, f64> for Bernoulli {
/// Calculates the probability mass function for the
/// bernoulli distribution at `x`.
///
/// # Panics
///
/// If `x > 1`
///
/// # Formula
///
/// ```ignore
Expand All @@ -294,10 +286,6 @@ impl Discrete<u64, f64> for Bernoulli {
/// Calculates the log probability mass function for the
/// bernoulli distribution at `x`.
///
/// # Panics
///
/// If `x > 1`
///
/// # Formula
///
/// ```ignore
Expand Down
57 changes: 23 additions & 34 deletions src/distribution/beta.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -136,10 +136,6 @@ impl Univariate<f64, f64> for Beta {
/// Calculates the cumulative distribution function for the beta distribution
/// at `x`
///
/// # Panics
///
/// If `x < 0.0` or `x > 1.0`
///
/// # Formula
///
/// ```ignore
Expand All @@ -149,9 +145,9 @@ impl Univariate<f64, f64> for Beta {
/// where `α` is shapeA, `β` is shapeB, and `I_x` is the regularized
/// lower incomplete beta function
fn cdf(&self, x: f64) -> f64 {
assert!(x >= 0.0 && x <= 1.0,
format!("{}", StatsError::ArgIntervalIncl("x", 0.0, 1.0)));
if x == 1.0 {
if x < 0.0 {
0.0
} else if x >= 1.0 {
1.0
} else if self.shape_a == f64::INFINITY && self.shape_b == f64::INFINITY {
if x < 0.5 { 0.0 } else { 1.0 }
Expand Down Expand Up @@ -348,10 +344,6 @@ impl Mode<f64> for Beta {
impl Continuous<f64, f64> for Beta {
/// Calculates the probability density function for the beta distribution at `x`.
///
/// # Panics
///
/// If `x < 0.0` or `x > 1.0`
///
/// # Formula
///
/// ```ignore
Expand All @@ -362,9 +354,9 @@ impl Continuous<f64, f64> for Beta {
///
/// where `α` is shapeA, `β` is shapeB, and `Γ` is the gamma function
fn pdf(&self, x: f64) -> f64 {
assert!(x >= 0.0 && x <= 1.0,
format!("{}", StatsError::ArgIntervalIncl("x", 0.0, 1.0)));
if self.shape_a == f64::INFINITY && self.shape_b == f64::INFINITY {
if x < 0.0 || x > 1.0 {
0.0
} else if self.shape_a == f64::INFINITY && self.shape_b == f64::INFINITY {
if x == 0.5 { f64::INFINITY } else { 0.0 }
} else if self.shape_a == f64::INFINITY {
if x == 1.0 { f64::INFINITY } else { 0.0 }
Expand All @@ -383,10 +375,6 @@ impl Continuous<f64, f64> for Beta {

/// Calculates the log probability density function for the beta distribution at `x`.
///
/// # Panics
///
/// If `x < 0.0` or `x > 1.0`
///
/// # Formula
///
/// ```ignore
Expand All @@ -397,9 +385,9 @@ impl Continuous<f64, f64> for Beta {
///
/// where `α` is shapeA, `β` is shapeB, and `Γ` is the gamma function
fn ln_pdf(&self, x: f64) -> f64 {
assert!(x >= 0.0 && x <= 1.0,
format!("{}", StatsError::ArgIntervalIncl("x", 0.0, 1.0)));
if self.shape_a == f64::INFINITY && self.shape_b == f64::INFINITY {
if x < 0.0 || x > 1.0 {
f64::NEG_INFINITY
} else if self.shape_a == f64::INFINITY && self.shape_b == f64::INFINITY {
if x == 0.5 {
f64::INFINITY
} else {
Expand Down Expand Up @@ -443,6 +431,7 @@ mod test {
use std::f64;
use statistics::*;
use distribution::{Univariate, Continuous, Beta};
use distribution::internal::*;

fn try_create(shape_a: f64, shape_b: f64) -> Beta {
let n = Beta::new(shape_a, shape_b);
Expand Down Expand Up @@ -612,15 +601,13 @@ mod test {
}

#[test]
#[should_panic]
fn test_pdf_input_lt_zero() {
get_value(1.0, 1.0, |x| x.pdf(-1.0));
test_case(1.0, 1.0, 0.0, |x| x.pdf(-1.0));
}

#[test]
#[should_panic]
fn test_pdf_input_gt_one() {
get_value(1.0, 1.0, |x| x.pdf(2.0));
test_case(1.0, 1.0, 0.0, |x| x.pdf(2.0));
}

#[test]
Expand All @@ -646,15 +633,13 @@ mod test {
}

#[test]
#[should_panic]
fn test_ln_pdf_input_lt_zero() {
get_value(1.0, 1.0, |x| x.ln_pdf(-1.0));
test_case(1.0, 1.0, f64::NEG_INFINITY, |x| x.ln_pdf(-1.0));
}

#[test]
#[should_panic]
fn test_ln_pdf_input_gt_one() {
get_value(1.0, 1.0, |x| x.ln_pdf(2.0));
test_case(1.0, 1.0, f64::NEG_INFINITY, |x| x.ln_pdf(2.0));
}

#[test]
Expand All @@ -680,14 +665,18 @@ mod test {
}

#[test]
#[should_panic]
fn test_cdf_input_lt_zero() {
get_value(1.0, 1.0, |x| x.cdf(-1.0));
test_case(1.0, 1.0, 0.0, |x| x.cdf(-1.0));
}

#[test]
#[should_panic]
fn test_cdf_input_gt_zero() {
get_value(1.0, 1.0, |x| x.cdf(2.0));
}
test_case(1.0, 1.0, 1.0, |x| x.cdf(2.0));
}

#[test]
fn test_continuous() {
test::check_continuous_distribution(&try_create(1.2, 3.4), 0.0, 1.0);
test::check_continuous_distribution(&try_create(4.5, 6.7), 0.0, 1.0);
}
}
47 changes: 21 additions & 26 deletions src/distribution/binomial.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -135,10 +135,6 @@ impl Univariate<u64, f64> for Binomial {
/// Calulcates the cumulative distribution function for the
/// binomial distribution at `x`
///
/// # Panics
///
/// If `x < 0.0` or `x > n`
///
/// # Formula
///
/// ```ignore
Expand All @@ -147,11 +143,11 @@ impl Univariate<u64, f64> for Binomial {
///
/// where `I_(x)(a, b)` is the regularized incomplete beta function
fn cdf(&self, x: f64) -> f64 {
assert!(x >= 0.0 && x <= self.n as f64,
format!("{}", StatsError::ArgIntervalIncl("x", 0.0, self.n as f64)));
if x == self.n as f64 {
1.0
} else {
if x < 0.0 {
0.0
} else if x >= self.n as f64 {
1.0
} else {
let k = x.floor();
beta::beta_reg(self.n as f64 - k, k + 1.0, 1.0 - self.p)
}
Expand Down Expand Up @@ -293,18 +289,15 @@ impl Discrete<u64, f64> for Binomial {
/// Calculates the probability mass function for the binomial
/// distribution at `x`
///
/// # Panics
///
/// If `x > n`
///
/// # Formula
///
/// ```ignore
/// (n choose k) * p^k * (1 - p)^(n - k)
/// ```
fn pmf(&self, x: u64) -> f64 {
assert!(x <= self.n,
format!("{}", StatsError::ArgLte("x", 1.0)));
if x > self.n {
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can we put this into the match statement? same with the ln_pmf method below

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No, the opposite should happen: the match should go away. Matching on floating-point values is deprecated. It's currently only a warning but it will become a hard error in the future.

return 0.0;
}
match self.p {
0.0 if x == 0 => 1.0,
0.0 => 0.0,
Expand All @@ -321,18 +314,15 @@ impl Discrete<u64, f64> for Binomial {
/// Calculates the log probability mass function for the binomial
/// distribution at `x`
///
/// # Panics
///
/// If `x > n`
///
/// # Formula
///
/// ```ignore
/// ln((n choose k) * p^k * (1 - p)^(n - k))
/// ```
fn ln_pmf(&self, x: u64) -> f64 {
assert!(x <= self.n,
format!("{}", StatsError::ArgLte("x", 1.0)));
if x > self.n {
return f64::NEG_INFINITY;
}
match self.p {
0.0 if x == 0 => 0.0,
0.0 => f64::NEG_INFINITY,
Expand All @@ -353,6 +343,7 @@ mod test {
use std::f64;
use statistics::*;
use distribution::{Univariate, Discrete, Binomial};
use distribution::internal::*;

fn try_create(p: f64, n: u64) -> Binomial {
let n = Binomial::new(p, n);
Expand Down Expand Up @@ -548,14 +539,18 @@ mod test {
}

#[test]
#[should_panic]
fn test_cdf_lower_bound() {
get_value(0.5, 3, |x| x.cdf(-1.0));
test_case(0.5, 3, 0.0, |x| x.cdf(-1.0));
}

#[test]
#[should_panic]
fn test_cdf_upper_bound() {
get_value(0.5, 3, |x| x.cdf(5.0));
}
test_case(0.5, 3, 1.0, |x| x.cdf(5.0));
}

#[test]
fn test_discrete() {
test::check_discrete_distribution(&try_create(0.3, 5), 5);
test::check_discrete_distribution(&try_create(0.7, 10), 10);
}
}
48 changes: 22 additions & 26 deletions src/distribution/categorical.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -123,11 +123,6 @@ impl Univariate<u64, f64> for Categorical {
/// Calculates the cumulative distribution function for the categorical
/// distribution at `x`
///
/// # Panics
///
/// If `x < 0.0` or `x > k` where `k` is the number of categories
/// (i.e. the length of the `prob_mass` slice passed to the constructor)
///
/// # Formula
///
/// ```ignore
Expand All @@ -136,12 +131,11 @@ impl Univariate<u64, f64> for Categorical {
///
/// where `p_j` is the probability mass for the `j`th category
fn cdf(&self, x: f64) -> f64 {
assert!(x >= 0.0 && x <= self.cdf.len() as f64,
format!("{}",
StatsError::ArgIntervalIncl("x", 0.0, self.cdf.len() as f64)));
if x == self.cdf.len() as f64 {
1.0
} else {
if x < 0.0 {
0.0
} else if x >= self.cdf.len() as f64 {
1.0
} else {
unsafe { self.cdf.get_unchecked(x as usize) / self.cdf_max() }
}
}
Expand Down Expand Up @@ -269,19 +263,17 @@ impl Discrete<u64, f64> for Categorical {
/// Calculates the probability mass function for the categorical
/// distribution at `x`
///
/// # Panics
///
/// If `x >= k` where `k` is the number of categories
///
/// # Formula
///
/// ```ignore
/// p_x
/// ```
fn pmf(&self, x: u64) -> f64 {
assert!(x < self.norm_pmf.len() as u64,
format!("{}", StatsError::ArgLtArg("x", "k")));
unsafe { *self.norm_pmf.get_unchecked(x as usize) }
if x >= self.norm_pmf.len() as u64 {
0.0
} else {
unsafe { *self.norm_pmf.get_unchecked(x as usize) }
}
}

/// Calculates the log probability mass function for the categorical
Expand Down Expand Up @@ -373,9 +365,11 @@ fn test_binary_index() {
#[cfg_attr(rustfmt, rustfmt_skip)]
#[cfg(test)]
mod test {
use std::f64;
use std::fmt::Debug;
use statistics::*;
use distribution::{Univariate, Discrete, InverseCDF, Categorical};
use distribution::internal::*;

fn try_create(prob_mass: &[f64]) -> Categorical {
let n = Categorical::new(prob_mass);
Expand Down Expand Up @@ -466,9 +460,8 @@ mod test {
}

#[test]
#[should_panic]
fn test_pmf_x_too_high() {
get_value(&[4.0, 2.5, 2.5, 1.0], |x| x.pmf(4));
test_case(&[4.0, 2.5, 2.5, 1.0], 0.0, |x| x.pmf(4));
}

#[test]
Expand All @@ -479,9 +472,8 @@ mod test {
}

#[test]
#[should_panic]
fn test_ln_pmf_x_too_high() {
get_value(&[4.0, 2.5, 2.5, 1.0], |x| x.ln_pmf(4));
test_case(&[4.0, 2.5, 2.5, 1.0], f64::NEG_INFINITY, |x| x.ln_pmf(4));
}

#[test]
Expand All @@ -494,15 +486,13 @@ mod test {
}

#[test]
#[should_panic]
fn test_cdf_input_low() {
get_value(&[4.0, 2.5, 2.5, 1.0], |x| x.cdf(-1.0));
test_case(&[4.0, 2.5, 2.5, 1.0], 0.0, |x| x.cdf(-1.0));
}

#[test]
#[should_panic]
fn test_cdf_input_high() {
get_value(&[4.0, 2.5, 2.5, 1.0], |x| x.cdf(4.5));
test_case(&[4.0, 2.5, 2.5, 1.0], 1.0, |x| x.cdf(4.5));
}

#[test]
Expand All @@ -526,4 +516,10 @@ mod test {
fn test_inverse_cdf_input_high() {
get_value(&[4.0, 2.5, 2.5, 1.0], |x| x.inverse_cdf(1.0));
}

#[test]
fn test_discrete() {
test::check_discrete_distribution(&try_create(&[1.0, 2.0, 3.0, 4.0]), 4);
test::check_discrete_distribution(&try_create(&[0.0, 1.0, 2.0, 3.0, 4.0]), 5);
}
}
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