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Remove unecessary utf8 chars from docs that make t/pod.t fail on some…

… systems
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1 parent cd231fe commit 82f62a7a75fd12c1d347e53b37396e53b76af50c @leto committed Jun 6, 2012
Showing with 6 additions and 6 deletions.
  1. +1 −1 pod/DHT.pod
  2. +2 −2 pod/NTuple.pod
  3. +1 −1 pod/RNG.pod
  4. +1 −1 pod/Randist.pod
  5. +1 −1 pod/Roots.pod
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@@ -34,7 +34,7 @@ Here is a list of all the functions included in this module :
=item C<gsl_dht_x_sample($t, $n)> - This function returns the value of the $n-th sample point in the unit interval, (j_{\nu,n+1}/j_{\nu,M}) X. These are the points where the function f(t) is assumed to be sampled.
-=item C<gsl_dht_k_sample($t, $n)> - This function returns the value of the $n-th sample point in k-space, j_{\nu,n+1}/X.
+=item C<gsl_dht_k_sample($t, $n)> - This function returns the value of the $n-th sample point in "k-space", j_{\nu,n+1}/X.
=item C<gsl_dht_free($t)> - This function frees the transform $t.
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@@ -46,9 +46,9 @@ sub raw
{
return (shift)->{_ntuple};
}
-=item * <gsl_ntuple_open($filename, $ntuple_data, $size)> - This function opens an existing ntuple file $filename for reading and returns a pointer to a corresponding ntuple struct. The ntuples in the file must have size $size. A pointer to memory for the current ntuple row $ntuple_data, which is an array reference, must be suppliedthis is used to copy ntuples in and out of the file.
+=item * <gsl_ntuple_open($filename, $ntuple_data, $size)> - This function opens an existing ntuple file $filename for reading and returns a pointer to a corresponding ntuple struct. The ntuples in the file must have size $size. A pointer to memory for the current ntuple row $ntuple_data, which is an array reference, must be supplied -- this is used to copy ntuples in and out of the file.
-=item * <gsl_ntuple_create > - This function creates a new write-only ntuple file $filename for ntuples of size $size and returns a pointer to the newly created ntuple struct. Any existing file with the same name is truncated to zero length and overwritten. A pointer to memory for the current ntuple row $ntuple_data, which is an array reference, must be suppliedthis is used to copy ntuples in and out of the file.
+=item * <gsl_ntuple_create > - This function creates a new write-only ntuple file $filename for ntuples of size $size and returns a pointer to the newly created ntuple struct. Any existing file with the same name is truncated to zero length and overwritten. A pointer to memory for the current ntuple row $ntuple_data, which is an array reference, must be supplied -- this is used to copy ntuples in and out of the file.
=item * <gsl_ntuple_write($ntuple)> - This function writes the current $ntuple $ntuple->{ntuple_data} of size $ntuple->{size} to the corresponding file.
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@@ -196,7 +196,7 @@ __END__
=item $gsl_rng_fishman20
-=item $gsl_rng_fishman2x - This is the L'EcuyerFishman random number generator. It is taken from Knuth's Seminumerical Algorithms, 3rd Ed., page 108. Its sequence is, z_{n+1} = (x_n - y_n) mod m with m = 2^31 - 1. x_n and y_n are given by the fishman20 and lecuyer21 algorithms. The seed specifies the initial value, x_1.
+=item $gsl_rng_fishman2x - This is the L'Ecuyer-Fishman random number generator. It is taken from Knuth's Seminumerical Algorithms, 3rd Ed., page 108. Its sequence is, z_{n+1} = (x_n - y_n) mod m with m = 2^31 - 1. x_n and y_n are given by the fishman20 and lecuyer21 algorithms. The seed specifies the initial value, x_1.
=item $gsl_rng_gfsr4
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@@ -422,7 +422,7 @@ This function computes the probability p($k) of obtaining $k from a geometric di
=item gsl_ran_hypergeometric($r, $n1, $n2, $t)
-This function returns a random integer from the hypergeometric distribution. The probability distribution for hypergeometric random variates is, p(k) = C(n_1, k) C(n_2, t - k) / C(n_1 + n_2, t) where C(a,b) = a!/(b!(a-b)!) and t <= n_1 + n_2. The domain of k is max(0,t-n_2), ..., min(t,n_1). If a population contains n_1 elements of “type 1” and n_2 elements of “type 2” then the hypergeometric distribution gives the probability of obtaining k elements of “type 1” in t samples from the population without replacement. $r is a gsl_rng structure.
+This function returns a random integer from the hypergeometric distribution. The probability distribution for hypergeometric random variates is, p(k) = C(n_1, k) C(n_2, t - k) / C(n_1 + n_2, t) where C(a,b) = a!/(b!(a-b)!) and t <= n_1 + n_2. The domain of k is max(0,t-n_2), ..., min(t,n_1). If a population contains n_1 elements of "type 1" and n_2 elements of "type 2" then the hypergeometric distribution gives the probability of obtaining k elements of "type 1" in t samples from the population without replacement. $r is a gsl_rng structure.
=item gsl_ran_hypergeometric_pdf($k, $n1, $n2, $t)
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@@ -213,7 +213,7 @@ The false position algorithm is a method of finding roots based on linear
interpolation. Its convergence is linear, but it is usually faster than
bisection. On each iteration a line is drawn between the endpoints (a,f(a)) and
(b,f(b)) and the point where this line crosses the x-axis taken as a
-midpoint. The value of the function at this point is calculated and its sign
+"midpoint". The value of the function at this point is calculated and its sign
is used to determine which side of the interval does not contain a root. That
side is discarded to give a new, smaller interval containing the root. This
procedure can be continued indefinitely until the interval is sufficiently

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