version_string:

Pointer to a string pointer. If not null, it is set to the igraph version string, e.g. "0.9.11" or "0.10.0". This string must not be modified or deallocated.

major:

If not a null pointer, then it is set to the major igraph version. E.g. for version "0.9.11" this is 0.

minor:

If not a null pointer, then it is set to the minor igraph version. E.g. for version "0.9.11" this is 11.

subminor:

If not a null pointer, then it is set to the subminor igraph version. E.g. for version "0.9.11" this is 11.

data:

The vector containing the data.

res:

The vector containing the result. This should be initialized before calling this function and will be resized.

binwidth:

Integer giving the width of the bin for the running mean calculation.

Error code.

res:

Pointer to an initialized vector. This will hold the result. It will be resized to the proper size.

l:

The lower limit of the generation interval (inclusive). This must be less than or equal to the upper limit, and it must be integral.

h:

The upper limit of the generation interval (inclusive). This must be greater than or equal to the lower limit, and it must be integral.

length:

The number of random integers to generate.

The error codeIGRAPH_EINVAL is returned in each of the following cases: (1) The given lower limit is greater than the given upper limit, i.e.l >h. (2) Assuming thatl <h and N is the sample size, the above error code is returned if N > |h -l|, i.e. the sample size exceeds the size of the candidate pool.

dim:

The dimension of the random vectors.

n:

The number of vectors to sample.

radius:

Radius of the sphere, it must be positive.

positive:

Whether to restrict sampling to the positive orthant.

res:

Pointer to an initialized matrix, the result is stored here, each column will be a sampled vector. The matrix is resized, as needed.

Error code.

igraph_sample_sphere_volume(),igraph_sample_dirichlet() for other similar samplers.

dim:

The dimension of the random vectors.

n:

The number of vectors to sample.

radius:

Radius of the sphere, it must be positive.

positive:

Whether to restrict sampling to the positive orthant.

res:

Pointer to an initialized matrix, the result is stored here, each column will be a sampled vector. The matrix is resized, as needed.

Error code.

igraph_sample_sphere_surface(),igraph_sample_dirichlet() for other similar samplers.

n:

The number of vectors to sample.

alpha:

The parameters of the Dirichlet distribution. They must be positive. The length of this vector gives the dimension of the generated samples.

res:

Pointer to an initialized matrix, the result is stored here, one sample in each column. It will be resized, as needed.

Error code.

igraph_sample_sphere_surface() andigraph_sample_sphere_volume() for other methods to samplelatent vectors.

data:

vector containing the coordinates. The length of the vector must be even, since it contains X-Y coordinate pairs.

resverts:

the vector containing the result, e.g. the vector of vertex indices used as the corners of the convex hull. SupplyNULL here if you are only interested in the coordinates of the convex hull corners.

rescoords:

the matrix containing the coordinates of the selected corner vertices. SupplyNULL here if you are only interested in the vertex indices.

Error code:IGRAPH_ENOMEM: not enough memory

continuous:

Whether the fitted power-law distribution was continuous or discrete.

alpha:

The exponent of the fitted power-law distribution.

xmin:

The minimum value from which the power-law distribution was fitted. In other words, only the values larger thanxmin were used from the input vector.

L:

The log-likelihood of the fitted parameters; in other words, the probability of observing the input vector given the parameters.

D:

The test statistic of a Kolmogorov-Smirnov test that compares the fitted distribution with the input vector. Smaller scores denote better fit.

p:

The p-value of the Kolmogorov-Smirnov test;NaN if it has not been calculated yet. Small p-values (less than 0.05) indicate that the test rejected the hypothesis that the original data could have been drawn from the fitted power-law distribution.

data:

The vector containing the original input data. May not be valid any more if the caller already destroyed the vector.

data:

vector containing the samples for which a power-law distribution is to be fitted. Note that you have to provide thesamples, not the probability density function or the cumulative distribution function. For example, if you wish to fit a power-law to the degrees of a graph, you can use the output ofigraph_degree directly as an input argument toigraph_power_law_fit

result:

the result of the fitting algorithm. Seeigraph_plfit_result_t for more details. Note that the p-value of the fit isnot calculated by default as it is time-consuming; you need to calligraph_plfit_result_calculate_p_value() to calculate the p-value itself

xmin:

the minimum value in the sample vector where the power-law behaviour is expected to kick in. Samples smaller thanxmin will be ignored by the algorithm. Pass zero here if you want to include all the samples. Ifxmin is negative, the algorithm will attempt to determine its best value automatically.

force_continuous:

assume that the samples in thedata argument come from a continuous distribution even if the sample vector contains integer values only (by chance). If this argument is false, igraph will assume a continuous distribution if at least one sample is non-integer and assume a discrete distribution otherwise.

Error code:IGRAPH_ENOMEM: not enough memoryIGRAPH_EINVAL: one of the arguments is invalidIGRAPH_EOVERFLOW: overflow during the fitting processIGRAPH_EUNDERFLOW: underflow during the fitting processIGRAPH_FAILURE: the underlying algorithm signaled a failure without returning a more specific error code

model:

The fitted power-law model from theigraph_power_law_fit() function

result:

The calculated p-value is returned here

precision:

The desired precision of the p-value. Higher values correspond to longer calculation time.

Error code.

a:

The first float.

b:

The second float.

eps:

The level of tolerance on the relative error. The relative error is defined asabs(a-b) / (abs(a) + abs(b)). The two numbers are considered equal if this is less thaneps. Negative epsilon values are not allowed; the returned value will be undefined in this case. Zero means to do an exact comparison without tolerance.

Zero if the two floats are nearly equal to each other within the given level of tolerance, positive number if the first float is larger, negative number if the second float is larger.

a:

The first float.

b:

The second float.

eps:

The level of tolerance on the relative error. The relative error is defined asabs(a-b) / (abs(a) + abs(b)). The two numbers are considered equal if this is less thaneps.

True if the two floats are nearly equal to each other within the given level of tolerance, false otherwise.

a:

The first complex number.

b:

The second complex number.

eps:

The level of tolerance on the relative error. The relative error is defined asabs(a-b) / (abs(a) + abs(b)). The two numbers are considered equal if this is less thaneps.

True if the two complex numbers are nearly equal to each other within the given level of tolerance, false otherwise.

data:

vector containing the coordinates. The length of the vector must be even, since it contains X-Y coordinate pairs.

resverts:

the vector containing the result, e.g. the vector of vertex indices used as the corners of the convex hull. SupplyNULL here if you are only interested in the coordinates of the convex hull corners.

rescoords:

the matrix containing the coordinates of the selected corner vertices. SupplyNULL here if you are only interested in the vertex indices.

Error code:IGRAPH_ENOMEM: not enough memory