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Batuhan Osman TASKAYA
cpython
Commits
a933f6a5
Kaydet (Commit)
a933f6a5
authored
Nis 20, 1998
tarafından
Guido van Rossum
Dosyalara gözat
Seçenekler
Dosyalara Gözat
İndir
Eposta Yamaları
Sade Fark
Fix vonmisesvariate() -- it now returns an angle between 0 and *two*
times pi. Got rid of $math$ here and in one other place.
üst
9a34523e
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2 changed files
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8 additions
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8 deletions
+8
-8
librandom.tex
Doc/lib/librandom.tex
+4
-4
librandom.tex
Doc/librandom.tex
+4
-4
No files found.
Doc/lib/librandom.tex
Dosyayı görüntüle @
a933f6a5
...
@@ -30,7 +30,7 @@ Returned values will range between 0 and 1.
...
@@ -30,7 +30,7 @@ Returned values will range between 0 and 1.
Circular uniform distribution.
\var
{
mean
}
is the mean angle, and
Circular uniform distribution.
\var
{
mean
}
is the mean angle, and
\var
{
arc
}
is the range of the distribution, centered around the mean
\var
{
arc
}
is the range of the distribution, centered around the mean
angle. Both values must be expressed in radians, and can range
angle. Both values must be expressed in radians, and can range
between 0 and
$
\pi
$
. Returned values will range between
between 0 and
pi
. Returned values will range between
\code
{
\var
{
mean
}
-
\var
{
arc
}
/2
}
and
\code
{
\var
{
mean
}
+
\var
{
arc
}
/2
}
.
\code
{
\var
{
mean
}
-
\var
{
arc
}
/2
}
and
\code
{
\var
{
mean
}
+
\var
{
arc
}
/2
}
.
\end{funcdesc}
\end{funcdesc}
...
@@ -65,11 +65,11 @@ standard deviation.
...
@@ -65,11 +65,11 @@ standard deviation.
\end{funcdesc}
\end{funcdesc}
\begin{funcdesc}
{
vonmisesvariate
}{
mu, kappa
}
\begin{funcdesc}
{
vonmisesvariate
}{
mu, kappa
}
\var
{
mu
}
is the mean angle, expressed in radians between 0 and pi,
\var
{
mu
}
is the mean angle, expressed in radians between 0 and
2*
pi,
and
\var
{
kappa
}
is the concentration parameter, which must be greater
and
\var
{
kappa
}
is the concentration parameter, which must be greater
th
e
n or equal to zero. If
\var
{
kappa
}
is equal to zero, this
th
a
n or equal to zero. If
\var
{
kappa
}
is equal to zero, this
distribution reduces to a uniform random angle over the range 0 to
distribution reduces to a uniform random angle over the range 0 to
$
2
\pi
$
.
2*pi
.
\end{funcdesc}
\end{funcdesc}
\begin{funcdesc}
{
paretovariate
}{
alpha
}
\begin{funcdesc}
{
paretovariate
}{
alpha
}
...
...
Doc/librandom.tex
Dosyayı görüntüle @
a933f6a5
...
@@ -30,7 +30,7 @@ Returned values will range between 0 and 1.
...
@@ -30,7 +30,7 @@ Returned values will range between 0 and 1.
Circular uniform distribution.
\var
{
mean
}
is the mean angle, and
Circular uniform distribution.
\var
{
mean
}
is the mean angle, and
\var
{
arc
}
is the range of the distribution, centered around the mean
\var
{
arc
}
is the range of the distribution, centered around the mean
angle. Both values must be expressed in radians, and can range
angle. Both values must be expressed in radians, and can range
between 0 and
$
\pi
$
. Returned values will range between
between 0 and
pi
. Returned values will range between
\code
{
\var
{
mean
}
-
\var
{
arc
}
/2
}
and
\code
{
\var
{
mean
}
+
\var
{
arc
}
/2
}
.
\code
{
\var
{
mean
}
-
\var
{
arc
}
/2
}
and
\code
{
\var
{
mean
}
+
\var
{
arc
}
/2
}
.
\end{funcdesc}
\end{funcdesc}
...
@@ -65,11 +65,11 @@ standard deviation.
...
@@ -65,11 +65,11 @@ standard deviation.
\end{funcdesc}
\end{funcdesc}
\begin{funcdesc}
{
vonmisesvariate
}{
mu, kappa
}
\begin{funcdesc}
{
vonmisesvariate
}{
mu, kappa
}
\var
{
mu
}
is the mean angle, expressed in radians between 0 and pi,
\var
{
mu
}
is the mean angle, expressed in radians between 0 and
2*
pi,
and
\var
{
kappa
}
is the concentration parameter, which must be greater
and
\var
{
kappa
}
is the concentration parameter, which must be greater
th
e
n or equal to zero. If
\var
{
kappa
}
is equal to zero, this
th
a
n or equal to zero. If
\var
{
kappa
}
is equal to zero, this
distribution reduces to a uniform random angle over the range 0 to
distribution reduces to a uniform random angle over the range 0 to
$
2
\pi
$
.
2*pi
.
\end{funcdesc}
\end{funcdesc}
\begin{funcdesc}
{
paretovariate
}{
alpha
}
\begin{funcdesc}
{
paretovariate
}{
alpha
}
...
...
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