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Module gwy :: Class DataField |
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DataField
struct contains private
data only and should be accessed using the functions below.
Method Summary | |
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Creates a new data field. | |
Transforms all rows or columns in a data field with Fast Fourier Transform. | |
Transforms all rows or columns in a data field with Fast Fourier Transform. | |
Calculates two-dimensional autocorrelation function of a data field. | |
Calculates 2D Fast Fourier Transform of a rectangular a data field. | |
Rearranges 2D FFT output back from the human-friendly form. | |
Rearranges 2D FFT output to a human-friendly form. | |
Calculates 2D Fast Fourier Transform of a data field. | |
Calculates one-dimensional autocorrelation function of a data field. | |
Adds given value to all values in a data field. | |
Transforms all rows or columns in a rectangular part of a data field with Fast Fourier Transform. | |
Calculates two-dimensional autocorrelation function of a data field area. | |
Calculates 2D Fast Fourier Transform of a rectangular area of a data field. | |
Calculates one-dimensional autocorrelation function of a rectangular part of a data field. | |
Adds given value to all values in a rectangular part of a data field. | |
Calculates cumulative distribution of slopes in a rectangular part of data field. | |
Calculates cumulative distribution of heights in a rectangular part of data field. | |
Limits values in a rectangular part of a data field to a range. | |
Fills a rectangular part of a data field with zeroes. | |
Convolves a rectangular part of a data field with given kernel. | |
Convolves a rectangular part of a data field with given linear kernel. | |
Copies a rectangular area from one data field to another. | |
Counts data samples in given range. | |
Calculates distribution of slopes in a rectangular part of data field. | |
Calculates distribution of heights in a rectangular part of data field. | |
Extracts a rectangular part of a data field to a new data field. | |
Fills a rectangular part of a data field with given value. | |
Filters a rectangular part of a data field with conservative denoise filter. | |
Filters a rectangular part of a data field with 5x5 checker pattern removal filter. | |
Filters a rectangular part of a data field with a Gaussian filter. | |
Filters a rectangular part of a data field with a Kuwahara (edge-preserving smoothing) filter. | |
Filters a rectangular part of a data field with Laplacian filter. | |
Filters a rectangular part of a data field with maximum filter. | |
Filters a rectangular part of a data field with mean filter of size size . | |
Filters a rectangular part of a data field with median filter. | |
Filters a rectangular part of a data field with minimum filter. | |
Filters a rectangular part of a data field with Prewitt filter. | |
Filters a rectangular part of a data field with RMS filter of size size . | |
Filters a rectangular part of a data field with Sobel filter. | |
Fits a plane through a rectangular part of a data field. | |
Fit a given set of polynomial terms to a rectangular part of a data field. | |
Fits a two-dimensional polynomial to a rectangular part of a data field. | |
Sums or averages values in reactangular areas around each sample in a data field. | |
Computes average value of a rectangular part of a data field. | |
Calculates the inclination of the image (polar and azimuth angle). | |
Calculates a line quantity for each row or column in a data field area. | |
Finds the maximum value in a rectangular part of a data field. | |
Computes median value of a data field area. | |
Finds the minimum value in a rectangular part of a data field. | |
Computes root mean square value of a rectangular part of a data field. | |
Computes basic statistical quantities of a rectangular part of a data field. | |
Sums values of a rectangular part of a data field. | |
Computes surface area of a rectangular part of a data field. | |
Computes volume of a rectangular part of a data field. | |
Calculates threshold grain number distribution. | |
Calculates one-dimensional autocorrelation function of a rectangular part of a data field. | |
Convenience function to get just one quantity from DataField.area_fit_local_planes (). | |
Calculates Minkowski boundary functional of a rectangular part of a data field. | |
Calculates Minkowski connectivity functional (Euler characteristics) of a rectangular part of a data field. | |
Calculates Minkowski volume functional of a rectangular part of a data field. | |
Multiplies values in a rectangular part of a data field by given value | |
Calculates one-dimensional power spectrum density function of a rectangular part of a data field. | |
Calculates radial power spectrum density function of a rectangular part of a data field. | |
Subtracts a two-dimensional Legendre polynomial fit from a rectangular part of a data field. | |
Subtract a given set of polynomial terms from a rectangular part of a data field. | |
Subtracts a two-dimensional polynomial with limited total degree from a rectangular part of a data field. | |
Subtracts a two-dimensional polynomial from a rectangular part of a data field. | |
Tresholds values of a rectangular part of a data field. | |
Calculates cumulative distribution of slopes in a data field. | |
Calculates cumulative distribution of heights in a data field. | |
Checks whether two data fields are compatible. | |
Extracts values from a circular region of a data field. | |
Fills an elliptic region of a data field with given value. | |
Puts values back to a circular region of a data field. | |
Limits data field values to a range. | |
Fills a data field with zeroes. | |
Convolves a data field with given kernel. | |
Convolves a data field with given linear kernel. | |
Copies the contents of an already allocated data field to a data field of the same size. | |
Sets lateral and value units of a data line to match a data field. | |
Fills data under mask with average value. | |
Performs one interation of Laplace data correction. | |
Computes correlation score for all positions in a data field. | |
create_full_mask()
| |
Algorithm for matching two different images of the same object under changes. | |
Calculates distribution of slopes in a data field. | |
Emits signal "data-changed" on a data field. | |
Calculates distribution of heights in a data field. | |
Divides one data field with another. | |
Duplicate datafield | |
Performs steps of the 2D image wavelet decomposition. | |
dwt_mark_anisotropy(mask,
wt_coefs,
ratio,
lowlimit)
| |
Extracts values from an elliptic region of a data field. | |
Fills an elliptic region of a data field with given value. | |
Puts values back to an elliptic region of a data field. | |
Performs 1D FFT filtering of a data field. | |
Fills a data field with given value. | |
Filters a rectangular part of a data field with canny edge detector filter. | |
Filters a data field with conservative denoise filter. | |
Filters a data field with 5x5 checker pattern removal filter. | |
Filters a data field with a Gaussian filter. | |
filter_harris(y_gradient,
result,
neighbourhood,
alpha)
| |
Filters a data field with Kuwahara filter. | |
Filters a data field with Laplacian filter. | |
Filters a data field with maximum filter. | |
Filters a data field with mean filter of size size . | |
Filters a data field with median filter. | |
Filters a data field with minimum filter. | |
Filters a data field with Prewitt filter. | |
Filters a data field with RMS filter. | |
Filters a data field with Sobel filter. | |
Independently levels profiles on each row/column in a data field. | |
Fits a plane through a data field. | |
Fit a given set of polynomial terms to a data field. | |
Fits a two-dimensional polynomial to a data field. | |
Replaces data under mask with interpolated values using fractal interpolation. | |
Computes data for log-log plot by cube counting. | |
Computes data for log-log plot by partitioning. | |
Computes data for log-log plot by spectral density method. | |
Computes data for log-log plot by triangulation. | |
Computes derivative in direction specified by given angle. | |
Computes average value of a data field. | |
Extracts a data field column into a data line. | |
Extracts part of a data field column into a data line. | |
Calculates a correlation score in one point. | |
Create a tuple of data which the datafield contains. | |
Gets interpolated value at arbitrary data field point indexed by pixel coordinates. | |
Gets interpolated value at arbitrary data field point indexed by real coordinates. | |
Calculates a line quantity for each row or column of a data field. | |
Finds the maximum value of a data field. | |
Computes median value of a data field. | |
Finds the minimum value of a data field. | |
Finds minimum and maximum values of a data field. | |
Computes average normal vector of a data field. | |
Extracts a possibly averaged profile from data field to a data line. | |
Computes root mean square value of a data field. | |
Extracts a data field row into a data line. | |
Extracts part of a data field row into a data line. | |
Returns: SI unit corresponding to the lateral (XY) dimensions of the data | |
Returns: SI unit corresponding to the "height" (Z) dimension of the data | |
Computes basic statistical quantities of a data field. | |
Sums all values in a data field. | |
Computes surface area of a data field. | |
Gets value at given position in a data field. | |
Computes central derivative in X direction. | |
Gets the X offset of data field origin. | |
Gets the X real (physical) size of a data field. | |
Gets X resolution (number of columns) of a data field. | |
Computes central derivative in Y direction. | |
Gets the Y offset of data field origin. | |
Gets the Y real (physical) size of a data field. | |
Gets Y resolution (number of rows) of the field. | |
Adds add_field grains to
grain_field . | |
Removes all grains except that one at given position. | |
Performs intersection betweet two grain fields, result is stored in grain_field . | |
Marks data that are above/below curvature threshold. | |
Marks data that are above/below height threshold. | |
Marks data that are above/below slope threshold. | |
Performs watershed algorithm. | |
Removes grains that are higher/lower than given threshold value. | |
Removes all grain below specified area. | |
Removes one grain at given position. | |
grains_splash_water(minima,
locate_steps,
locate_dropsize)
| |
Calculates one-dimensional autocorrelation function of a data field. | |
hough_circle(x_gradient,
y_gradient,
result,
radius)
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hough_circle_strenghten(x_gradient,
y_gradient,
radius,
threshold)
| |
hough_line(x_gradient,
y_gradient,
result,
hwidth,
overlapping)
| |
hough_line_strenghten(x_gradient,
y_gradient,
hwidth,
threshold)
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hough_polar_line_to_datafield(rho,
theta,
px1,
px2,
py1,
py2)
| |
Reflects amd/or inverts a data field. | |
Transforms vertical pixel coordinate to real (physical) Y coordinate. | |
Transforms horizontal pixel coordinate to real (physical) X coordinate. | |
Convenience function to get just one quantity from DataField.fit_local_planes (). | |
Creates mask of data that are above or below thresh *sigma from average height. | |
Finds point-wise minima of two data fields. | |
Finds point-wise maxima of two data fields. | |
Calculates Minkowski boundary functional of a data field. | |
Calculates Minkowski connectivity functional (Euler characteristics) of a data field. | |
Calculates Minkowski volume functional of a data field. | |
Multiplies all values in a data field by given value. | |
Multiplies two data fields. | |
Creates a new data field similar to an existing one. | |
Creates a new data field by resampling an existing one. | |
Normalizes data in a data field to range 0.0 to 1.0. | |
Subtracts plane from a data field. | |
Performs rotation of plane along x and y axis. | |
Calculates one-dimensional power spectrum density function of a data field. | |
Transforms data in a data field with first linear function to given range. | |
Resamples a data field using given interpolation method | |
Resizes (crops) a data field. | |
Rotates a data field by a given angle. | |
Calculates radial power spectrum density function of a data field. | |
Transforms real (physical) Y coordinate to row. | |
Transforms real (physical) X coordinate to column. | |
Sets a column in the data field to values of a data line. | |
Puts a data line into data field column. | |
Sets a row in the data field to values of a data line. | |
Puts a data line into a data field row. | |
Sets the SI unit corresponding to the lateral (XY) dimensions of a data field. | |
Sets the SI unit corresponding to the "height" (Z) dimension of a data field. | |
Sets value at given position in a data field. | |
Sets the X offset of a data field origin. | |
Sets X real (physical) size value of a data field. | |
Sets the Y offset of a data field origin. | |
Sets Y real (physical) size value of a data field. | |
Shades a data field. | |
Computes angular slope distribution. | |
Subtracts one data field from another. | |
Subtracts a two-dimensional Legendre polynomial fit from a data field. | |
Subtract a given set of polynomial terms from a data field. | |
Subtracts a two-dimensional polynomial with limited total degree from a data field. | |
Subtracts a two-dimensional polynomial from a data field. | |
Sums two data fields. | |
Tresholds values of a data field. | |
Fits two-dimensional Legendre polynomial to a rectangular part of a data field. | |
Fits a plane through neighbourhood of each sample in a rectangular part of a data field. | |
Fits two-dimensional polynomial with limited total degree to a rectangular part of a data field. | |
Finds minimum and maximum values in a rectangular part of a data field. | |
Computes average normal vector of an area of a data field. | |
Extracts values with positions from a circular region of a data field. | |
Creates a new correlation iterator. | |
Initializes a cross-correlation iterator. | |
Computes a continuous wavelet transform (CWT) at given scale and using given wavelet. | |
Distorts a data field in the horizontal plane. | |
Fits two-dimensional Legendre polynomial to a data field. | |
Fits a plane through neighbourhood of each sample in a data field. | |
Fits two-dimensional polynomial with limited total degree to a data field. | |
Computes value range with outliers cut-off. | |
Find bounding boxes of all grains. | |
Calculates the inclination of the image (polar and azimuth angle). | |
UNIMPLEMENTED_get_local_maxima_list(xdata,
ydata,
zdata,
ndata,
skip,
threshold,
subpixel)
| |
Finds value format good for displaying coordinates of a data field. | |
Finds value format good for displaying values of a data field. | |
Computes distribution of requested grain characteristics. | |
Calculates characteristics of grains. | |
Initializes the watershed algorithm. | |
UNIMPLEMENTED_mark_scars(data_field,
scar_field,
threshold_high,
threshold_low,
min_scar_len,
max_scar_width,
negative)
| |
UNIMPLEMENTED_normalize_rows(dfield)
| |
Numbers grains in a mask data field. | |
Performs steps of the X-direction image wavelet decomposition. | |
Performs steps of the Y-direction image wavelet decomposition. |
Method Details |
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__init__(xres,
yres,
xreal,
yreal,
nullme)
Creates a new data field.
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a_1dfft(iin, rout, iout, orientation, windowing, direction, interpolation, preserverms, level)Transforms all rows or columns in a data field with Fast Fourier Transform. If requested a windowing and/or leveling is applied to preprocess data to obtain reasonable results.
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a_1dfft_raw(iin, rout, iout, orientation, direction)Transforms all rows or columns in a data field with Fast Fourier Transform. No leveling, windowing nor scaling is performed. Since 2.8 the dimensions need not to be from the set of sizes
returned by
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a_2dacf(target_field)Calculates two-dimensional autocorrelation function of a data field. See
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a_2dfft(iin, rout, iout, windowing, direction, interpolation, preserverms, level)Calculates 2D Fast Fourier Transform of a rectangular a data field. If requested a windowing and/or leveling is applied to preprocess data to obtain reasonable results.
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a_2dfft_dehumanize()Rearranges 2D FFT output back from the human-friendly form. Top-left, top-right, bottom-left and bottom-right sub-rectangles are swapped to reshuffle a humanized 2D FFT output back into the natural positions. See L{DataField.2dfft_humanize}() for discussion. Since: 2.8 |
a_2dfft_humanize()Rearranges 2D FFT output to a human-friendly form. Top-left, top-right, bottom-left and bottom-right sub-rectangles are swapped to obtain a humanized 2D FFT output with (0,0) in the centre. More precisely, for even field dimensions the equally-sized blocks starting with the Nyquist frequency and with the zero frequency (constant component) will exchange places. For odd field dimensions, the block containing the zero frequency is one item larger and the constant component will actually end up in the exact centre. Also note if both dimensions are even, this function is involutory and identical to L{DataField.2dfft_dehumanize}(). However, if any dimension is odd, L{DataField.2dfft_humanize}() and L{DataField.2dfft_dehumanize}() are different, therefore they must be paired properly. |
a_2dfft_raw(iin, rout, iout, direction)Calculates 2D Fast Fourier Transform of a data field. No leveling, windowing nor scaling is performed. Since 2.8 the dimensions need not to be from the set of sizes
returned by
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acf(target_line, orientation, interpolation, nstats)Calculates one-dimensional autocorrelation function of a data field.
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add(value)Adds given value to all values in a data field.
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area_1dfft(iin, rout, iout, col, row, width, height, orientation, windowing, direction, interpolation, preserverms, level)Transforms all rows or columns in a rectangular part of a data field with Fast Fourier Transform. If requested a windowing and/or leveling is applied to preprocess data to obtain reasonable results.
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area_2dacf(target_field, col, row, width, height, xrange, yrange)Calculates two-dimensional autocorrelation function of a data field area. The resulting data field has the correlation corresponding to (0,0) in the centre. The maximum possible values of
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area_2dfft(iin, rout, iout, col, row, width, height, windowing, direction, interpolation, preserverms, level)Calculates 2D Fast Fourier Transform of a rectangular area of a data field. If requested a windowing and/or leveling is applied to preprocess data to obtain reasonable results.
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area_acf(target_line, col, row, width, height, orientation, interpolation, nstats)Calculates one-dimensional autocorrelation function of a rectangular part of a data field.
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area_add(col, row, width, height, value)Adds given value to all values in a rectangular part of a data field.
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area_cda(target_line, col, row, width, height, orientation, nstats)Calculates cumulative distribution of slopes in a rectangular part of data field.
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area_cdh(mask, target_line, col, row, width, height, nstats)Calculates cumulative distribution of heights in a rectangular part of data field.
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area_clamp(col, row, width, height, bottom, top)Limits values in a rectangular part of a data field to a range.
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area_clear(col, row, width, height)Fills a rectangular part of a data field with zeroes.
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area_convolve(kernel_field, col, row, width, height)Convolves a rectangular part of a data field with given kernel.
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area_convolve_1d(kernel_line, orientation, col, row, width, height)Convolves a rectangular part of a data field with given linear kernel. For large separable kernels it can be more efficient to use a sequence of horizontal and vertical convolutions instead one 2D convolution. Since: 2.4
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area_copy(dest, col, row, width, height, destcol, destrow)Copies a rectangular area from one data field to another. The area starts at ( The source area has to be completely contained in
src is equal to dest , the
areas may not overlap.
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area_count_in_range(mask, col, row, width, height, below, above, nbelow, nabove)Counts data samples in given range. No assertion is made about the values of DataField.area_count_in_range (data_field,
NULL, col, row, width, height, 0.0, 0.0, &count, NULL); count =
width*height - count;
</programlisting></informalexample>
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area_da(target_line, col, row, width, height, orientation, nstats)Calculates distribution of slopes in a rectangular part of data field.
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area_dh(mask, target_line, col, row, width, height, nstats)Calculates distribution of heights in a rectangular part of data field.
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area_extract(col, row, width, height)Extracts a rectangular part of a data field to a new data field.
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area_fill(col, row, width, height, value)Fills a rectangular part of a data field with given value.
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area_filter_conservative(size, col, row, width, height)Filters a rectangular part of a data field with conservative denoise filter.
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area_filter_dechecker(col, row, width, height)Filters a rectangular part of a data field with 5x5 checker pattern removal filter. Since: 2.1
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area_filter_gaussian(sigma, col, row, width, height)Filters a rectangular part of a data field with a Gaussian filter. The Gausian is normalized, i.e. it is sum-preserving. Since: 2.4
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area_filter_kuwahara(col, row, width, height)Filters a rectangular part of a data field with a Kuwahara (edge-preserving smoothing) filter.
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area_filter_laplacian(col, row, width, height)Filters a rectangular part of a data field with Laplacian filter.
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area_filter_maximum(size, col, row, width, height)Filters a rectangular part of a data field with maximum filter. This operation is often called dilation filter.
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area_filter_mean(size, col, row, width, height)Filters a rectangular part of a data field with mean filter of size
DataField.area_gather () wrapper.
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area_filter_median(size, col, row, width, height)Filters a rectangular part of a data field with median filter.
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area_filter_minimum(size, col, row, width, height)Filters a rectangular part of a data field with minimum filter. This operation is often called erosion filter.
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area_filter_prewitt(orientation, col, row, width, height)Filters a rectangular part of a data field with Prewitt filter.
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area_filter_rms(size, col, row, width, height)Filters a rectangular part of a data field with RMS filter of size
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area_filter_sobel(orientation, col, row, width, height)Filters a rectangular part of a data field with Sobel filter.
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area_fit_plane(mask, col, row, width, height, pa, pbx, pby)Fits a plane through a rectangular part of a data field. The coefficients can be used for plane leveling using the same relation as inDataField.fit_plane (), counting indices
from area top left corner.
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area_fit_poly(mask_field, col, row, width, height, nterms, term_powers, exclude, coeffs)Fit a given set of polynomial terms to a rectangular part of a data field.
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area_fit_polynom(col, row, width, height, col_degree, row_degree)Fits a two-dimensional polynomial to a rectangular part of a data field. The coefficients are stored by row into col_degree =
row_degree = 6.
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area_gather(result, buffer, hsize, vsize, average, col, row, width, height)Sums or averages values in reactangular areas around each sample in a data field. When the gathered area extends out of calculation area, only samples from their intersection are taken into the local sum (or average). There are no restrictions on values of width +
hsize )*(height +
vsize ) instead of
width *hsize *height *vsize .
On the other hand it means absolute rounding errors of all output
values are given by the largest input values, that is relative
precision of results small in absolute value may be poor.
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area_get_avg(mask, col, row, width, height)Computes average value of a rectangular part of a data field.
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area_get_inclination(col, row, width, height, theta, phi)Calculates the inclination of the image (polar and azimuth angle).
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area_get_line_stats(mask, target_line, col, row, width, height, quantity, orientation)Calculates a line quantity for each row or column in a data field area. Since: 2.2
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area_get_max(mask, col, row, width, height)Finds the maximum value in a rectangular part of a data field.
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area_get_median(mask, col, row, width, height)Computes median value of a data field area.
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area_get_min(mask, col, row, width, height)Finds the minimum value in a rectangular part of a data field.
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area_get_rms(mask, col, row, width, height)Computes root mean square value of a rectangular part of a data field.
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area_get_stats(mask, col, row, width, height, avg, ra, rms, skew, kurtosis)Computes basic statistical quantities of a rectangular part of a data field.
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area_get_sum(mask, col, row, width, height)Sums values of a rectangular part of a data field.
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area_get_surface_area(mask, col, row, width, height)Computes surface area of a rectangular part of a data field. This quantity makes sense only if the lateral dimensions and values ofdata_field are the same physical quantities.
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area_get_volume(basis, mask, col, row, width, height)Computes volume of a rectangular part of a data field.
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area_grains_tgnd(target_line, col, row, width, height, below, nstats)Calculates threshold grain number distribution. This is the number of grains for each ofnstats
equidistant height threshold levels. For large
nstats this function is much faster than the
equivalent number of DataField.grains_mark_height ().
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area_hhcf(target_line, col, row, width, height, orientation, interpolation, nstats)Calculates one-dimensional autocorrelation function of a rectangular part of a data field.
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area_local_plane_quantity(size, col, row, width, height, type, result)Convenience function to get just one quantity fromDataField.area_fit_local_planes ().
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area_minkowski_boundary(target_line, col, row, width, height, nstats)Calculates Minkowski boundary functional of a rectangular part of a data field. Boundary functional is calculated as the number of boundaries for each threshold value (the number of pixel sides where of neighouring pixels is ,white` and the other ,black`) divided by the total number of samples in the area.
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area_minkowski_euler(target_line, col, row, width, height, nstats)Calculates Minkowski connectivity functional (Euler characteristics) of a rectangular part of a data field. Connectivity functional is calculated as the number connected areas of pixels above threhsold (,white`) minus the number of connected areas of pixels below threhsold (,black`) for each threshold value, divided by the total number of samples in the area.
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area_minkowski_volume(target_line, col, row, width, height, nstats)Calculates Minkowski volume functional of a rectangular part of a data field. Volume functional is calculated as the number of values above each threshold value (,white pixels`) divided by the total number of samples in the area. Is it's equivalent to 1-CDH.
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area_multiply(col, row, width, height, value)Multiplies values in a rectangular part of a data field by given value
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area_psdf(target_line, col, row, width, height, orientation, interpolation, windowing, nstats)Calculates one-dimensional power spectrum density function of a rectangular part of a data field.
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area_rpsdf(target_line, col, row, width, height, interpolation, windowing, nstats)Calculates radial power spectrum density function of a rectangular part of a data field. Since: 2.7
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area_subtract_legendre(col, row, width, height, col_degree, row_degree, coeffs)Subtracts a two-dimensional Legendre polynomial fit from a rectangular part of a data field. Due to the transform of coordinates to [-1,1] x [-1,1], this method can be used on an area of dimensions different than the area the coefficients were calculated for.
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area_subtract_poly(col, row, width, height, nterms, term_powers, coeffs)Subtract a given set of polynomial terms from a rectangular part of a data field. Since: 2.11
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area_subtract_poly_max(col, row, width, height, max_degree, coeffs)Subtracts a two-dimensional polynomial with limited total degree from a rectangular part of a data field. Due to the transform of coordinates to [-1,1] x [-1,1], this method can be used on an area of dimensions different than the area the coefficients were calculated for.
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area_subtract_polynom(col, row, width, height, col_degree, row_degree, coeffs)Subtracts a two-dimensional polynomial from a rectangular part of a data field.
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area_threshold(col, row, width, height, threshval, bottom, top)Tresholds values of a rectangular part of a data field. Values smaller thanthreshold are set to value
bottom , values higher than
threshold or equal to it are set to value
top
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cda(target_line, orientation, nstats)Calculates cumulative distribution of slopes in a data field.
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cdh(target_line, nstats)Calculates cumulative distribution of heights in a data field.
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check_compatibility(data_field2, check)Checks whether two data fields are compatible.
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circular_area_extract(col, row, radius)Extracts values from a circular region of a data field.
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circular_area_fill(col, row, radius, value)Fills an elliptic region of a data field with given value.
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circular_area_unextract(col, row, radius, data)Puts values back to a circular region of a data field. This method does the reverse ofDataField.circular_area_extract ()
allowing to implement pixel-wise filters on circular areas. Values from
data are put back to the same positions DataField.circular_area_extract () took
them from.
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clamp(bottom, top)Limits data field values to a range.
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clear()Fills a data field with zeroes. |
convolve(kernel_field)Convolves a data field with given kernel.
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convolve_1d(kernel_line, orientation)Convolves a data field with given linear kernel. Since: 2.4
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copy(dest, nondata_too)Copies the contents of an already allocated data field to a data field of the same size.
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copy_units_to_data_line(data_line)Sets lateral and value units of a data line to match a data field.
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correct_average(mask_field)Fills data under mask with average value. Simply puts average value of all thedata_field
values into points in data_field lying under points
where mask_field values are nonzero.
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correct_laplace_iteration(mask_field, buffer_field, corrfactor, error)Performs one interation of Laplace data correction. Tries to remove all the points in mask off the data by using iterative method similar to solving heat flux equation. Use this function repeatedly until reasonableerror is reached.
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correlate(kernel_field, score, method)Computes correlation score for all positions in a data field. Correlation score is compute for all points in data field
score correspond to centers of
kernel. More precisely, the point ((kxres -1)/2,
(kyres -1)/2) in score
corresponds to kernel field top left corner coincident with data field
top left corner. Points outside the area where the kernel field fits
into the data field completely are set to -1 for
CORRELATION_NORMAL .
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crosscorrelate(data_field2, x_dist, y_dist, score, search_width, search_height, window_width, window_height)Algorithm for matching two different images of the same object under changes. It does not use any special features for matching. It simply searches for all points (with their neighbourhood) ofdata_field1 within data_field2 .
Parameters search_width and
search_height determine maimum area where to search
for points. The area is cenetered in the
data_field2 at former position of points at
data_field1 .
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da(target_line, orientation, nstats)Calculates distribution of slopes in a data field.
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data_changed()Emits signal "data-changed" on a data field. |
dh(target_line, nstats)Calculates distribution of heights in a data field.
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divide_fields(operand1, operand2)Divides one data field with another. |
duplicate()Duplicate datafield
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dwt(wt_coefs, direction, minsize)Performs steps of the 2D image wavelet decomposition. The smallest low pass coefficients block is equal tominsize . Run with minsize =
dfield ->xres/2 to perform one step of
decomposition or minsize = 4 to perform full
decomposition (or anything between).
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elliptic_area_extract(col, row, width, height)Extracts values from an elliptic region of a data field. The elliptic region is defined by its bounding box which must be completely contained in the data field.
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elliptic_area_fill(col, row, width, height, value)Fills an elliptic region of a data field with given value. The elliptic region is defined by its bounding box which must be completely contained in the data field.
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elliptic_area_unextract(col, row, width, height, data)Puts values back to an elliptic region of a data field. The elliptic region is defined by its bounding box which must be completely contained in the data field. This method does the reverse ofDataField.elliptic_area_extract ()
allowing to implement pixel-wise filters on elliptic areas. Values from
data are put back to the same positions DataField.elliptic_area_extract () took
them from.
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fft_filter_1d(result_field, weights, orientation, interpolation)Performs 1D FFT filtering of a data field.
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fill(value)Fills a data field with given value.
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filter_canny(threshold)Filters a rectangular part of a data field with canny edge detector filter.
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filter_conservative(size)Filters a data field with conservative denoise filter.
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filter_dechecker()Filters a data field with 5x5 checker pattern removal filter. Since: 2.1 |
filter_gaussian(sigma)Filters a data field with a Gaussian filter. Since: 2.4
|
filter_kuwahara()Filters a data field with Kuwahara filter. |
filter_laplacian()Filters a data field with Laplacian filter. |
filter_maximum(size)Filters a data field with maximum filter.
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filter_mean(size)Filters a data field with mean filter of sizesize .
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filter_median(size)Filters a data field with median filter.
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filter_minimum(size)Filters a data field with minimum filter.
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filter_prewitt(orientation)Filters a data field with Prewitt filter.
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filter_rms(size)Filters a data field with RMS filter.
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filter_sobel(orientation)Filters a data field with Sobel filter.
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fit_lines(col, row, width, height, degree, exclude, orientation)Independently levels profiles on each row/column in a data field. Lines that have no intersection with area selected byulcol , ulrow ,
brcol , brrow are always leveled
as a whole. Lines that have intersection with selected area, are
leveled using polynomial coefficients computed only from data inside
(or outside for exclude = True )
the area.
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fit_plane(pa, pbx, pby)Fits a plane through a data field. The coefficients can be used for plane leveling using relation data[i] := data[i] - (pa + pby*i + pbx*j);
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fit_poly(mask_field, nterms, term_powers, exclude, coeffs)Fit a given set of polynomial terms to a data field.
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fit_polynom(col_degree, row_degree)Fits a two-dimensional polynomial to a data field.
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fractal_correction(mask_field, interpolation)Replaces data under mask with interpolated values using fractal interpolation.
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fractal_cubecounting(xresult, yresult, interpolation)Computes data for log-log plot by cube counting. Data linesxresult and
yresult will be resized to the output size and they
will contain corresponding values at each position.
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fractal_partitioning(xresult, yresult, interpolation)Computes data for log-log plot by partitioning. Data linesxresult and
yresult will be resized to the output size and they
will contain corresponding values at each position.
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fractal_psdf(xresult, yresult, interpolation)Computes data for log-log plot by spectral density method. Data linesxresult and
yresult will be resized to the output size and they
will contain corresponding values at each position.
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fractal_triangulation(xresult, yresult, interpolation)Computes data for log-log plot by triangulation. Data linesxresult and
yresult will be resized to the output size and they
will contain corresponding values at each position.
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get_angder(col, row, theta)Computes derivative in direction specified by given angle.
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get_avg()Computes average value of a data field. This quantity is cached.
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get_column(data_line, col)Extracts a data field column into a data line.
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get_column_part(data_line, col, _from, to)Extracts part of a data field column into a data line.
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get_correlation_score(kernel_field, col, row, kernel_col, kernel_row, kernel_width, kernel_height)Calculates a correlation score in one point. Correlation window size is given by
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get_data()Create a tuple of data which the datafield contains. Content of the tuple is NOT reference to original datafield but its copy.
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get_dval(x, y, interpolation)Gets interpolated value at arbitrary data field point indexed by pixel coordinates. Note pixel values are centered in pixels, so to get the same value
as DataField.get_dval_real () that does the
same, but takes real coordinates.
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get_dval_real(x, y, interpolation)Gets interpolated value at arbitrary data field point indexed by real coordinates. See alsoDataField.get_dval () that does the same,
but takes pixel coordinates.
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get_line_stats(target_line, quantity, orientation)Calculates a line quantity for each row or column of a data field. Since: 2.2
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get_max()Finds the maximum value of a data field. This quantity is cached.
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get_median()Computes median value of a data field. This quantity is cached.
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get_min()Finds the minimum value of a data field. This quantity is cached.
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get_min_max(min, max)Finds minimum and maximum values of a data field.
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get_normal_coeffs(nx, ny, nz, normalize1)Computes average normal vector of a data field.
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get_profile(scol, srow, ecol, erow, res, thickness, interpolation)Extracts a possibly averaged profile from data field to a data line.
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get_rms()Computes root mean square value of a data field. This quantity is cached.
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get_row(data_line, row)Extracts a data field row into a data line.
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get_row_part(data_line, row, _from, to)Extracts part of a data field row into a data line.
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get_si_unit_xy()Returns: SI unit corresponding to the lateral (XY) dimensions of the data
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get_si_unit_z()Returns: SI unit corresponding to the "height" (Z) dimension of the data
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get_stats(avg, ra, rms, skew, kurtosis)Computes basic statistical quantities of a data field.
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get_sum()Sums all values in a data field. This quantity is cached.
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get_surface_area()Computes surface area of a data field. This quantity is cached.
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get_val(col, row)Gets value at given position in a data field. Do not access data with this function inside inner loops, it's slow. Get raw data buffer withDataField.get_data_const () and
access it directly instead.
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get_xder(col, row)Computes central derivative in X direction. On border points, one-side derivative is returned.
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get_xoffset()Gets the X offset of data field origin.
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get_xreal()Gets the X real (physical) size of a data field.
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get_xres()Gets X resolution (number of columns) of a data field.
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get_yder(col, row)Computes central derivative in Y direction. On border points, one-side derivative is returned. Note the derivative is for legacy reasons calulcated for the opposite y direction than is usual elsewhere in Gwyddion, i.e. if values increase with increasing row number, the returned value is negative.
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get_yoffset()Gets the Y offset of data field origin.
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get_yreal()Gets the Y real (physical) size of a data field.
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get_yres()Gets Y resolution (number of rows) of the field.
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grains_add(add_field)Adds DataField.max_of_fields (grain_field,
grain_field, add_field);</literal> and it will be probably
removed someday.
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grains_extract_grain(col, row)Removes all grains except that one at given position. If there is no grain at (col ,
row ), all grains are removed.
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grains_intersect(intersect_field)Performs intersection betweet two grain fields, result is stored in
DataField.min_of_fields (grain_field,
grain_field, intersect_field);</literal> and it will be probably
removed someday.
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grains_mark_curvature(grain_field, threshval, below)Marks data that are above/below curvature threshold.
|
grains_mark_height(grain_field, threshval, below)Marks data that are above/below height threshold.
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grains_mark_slope(grain_field, threshval, below)Marks data that are above/below slope threshold.
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grains_mark_watershed(grain_field, locate_steps, locate_thresh, locate_dropsize, wshed_steps, wshed_dropsize, prefilter, below)Performs watershed algorithm.
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grains_remove_by_height(grain_field, threshval, below)Removes grains that are higher/lower than given threshold value.
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grains_remove_by_size(size)Removes all grain below specified area.
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grains_remove_grain(col, row)Removes one grain at given position.
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hhcf(target_line, orientation, interpolation, nstats)Calculates one-dimensional autocorrelation function of a data field.
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invert(x, y, z)Reflects amd/or inverts a data field. In the case of value reflection, it's inverted about the mean value.
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itor(row)Transforms vertical pixel coordinate to real (physical) Y coordinate. That is it maps range [0..y-resolution] to range [0..real-y-size]. It is not suitable for conversion of matrix indices to physical coordinates, you have to useDataField.itor (data_field ,
row + 0.5) for that.
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jtor(col)Transforms horizontal pixel coordinate to real (physical) X coordinate. That is it maps range [0..x-resolution] to range [0..real-x-size]. It is not suitable for conversion of matrix indices to physical coordinates, you have to useDataField.jtor (data_field ,
col + 0.5) for that.
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local_plane_quantity(size, type, result)Convenience function to get just one quantity fromDataField.fit_local_planes ().
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mask_outliers(mask_field, thresh)Creates mask of data that are above or below
thresh = 3.
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max_of_fields(operand1, operand2)Finds point-wise minima of two data fields. |
min_of_fields(operand1, operand2)Finds point-wise maxima of two data fields. |
minkowski_boundary(target_line, nstats)Calculates Minkowski boundary functional of a data field. SeeDataField.area_minkowski_boundary () for
details.
|
minkowski_euler(target_line, nstats)Calculates Minkowski connectivity functional (Euler characteristics) of a data field. SeeDataField.area_minkowski_euler () for
details.
|
minkowski_volume(target_line, nstats)Calculates Minkowski volume functional of a data field. SeeDataField.area_minkowski_volume () for
details.
|
multiply(value)Multiplies all values in a data field by given value.
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multiply_fields(operand1, operand2)Multiplies two data fields. |
new_alike(nullme)Creates a new data field similar to an existing one. UseDataField.duplicate () if you want to copy
a data field including data.
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new_resampled(xres, yres, interpolation)Creates a new data field by resampling an existing one. This method is equivalent toDataField.duplicate () followed by DataField.resample (), but it is more
efficient.
|
normalize()Normalizes data in a data field to range 0.0 to 1.0. It is equivalent to data_field is filled with only one value, it
is changed to 0.0.
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plane_level(a, bx, by)Subtracts plane from a data field. SeeDataField.fit_plane () for details.
|
plane_rotate(xangle, yangle, interpolation)Performs rotation of plane along x and y axis.
|
psdf(target_line, orientation, interpolation, windowing, nstats)Calculates one-dimensional power spectrum density function of a data field.
|
renormalize(range, offset)Transforms data in a data field with first linear function to given range. When range is zero, this method is equivalent to
DataField.fill (data_field ,
offset ).
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resample(xres, yres, interpolation)Resamples a data field using given interpolation method This method may invalidate raw data buffer returned byDataField.get_data ().
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resize(ulcol, ulrow, brcol, brrow)Resizes (crops) a data field. Crops a data field to a rectangle between upper-left and bottom-right points, recomputing real size. This method may invalidate raw data buffer returned byDataField.get_data ().
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rotate(angle, interpolation)Rotates a data field by a given angle. Values that get outside of data field by the rotation are lost. Undefined values from outside of data field that get inside are set to data field minimum value.
|
rpsdf(target_line, interpolation, windowing, nstats)Calculates radial power spectrum density function of a data field. Since: 2.7
|
rtoi(realy)Transforms real (physical) Y coordinate to row. That is it maps range [0..real-y-size] to range [0..y-resolution].
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rtoj(realx)Transforms real (physical) X coordinate to column. That is it maps range [0..real-x-size] to range [0..x-resolution].
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set_column(data_line, col)Sets a column in the data field to values of a data line. Data line length must be equal to height of data field.
|
set_column_part(data_line, col, _from, to)Puts a data line into data field column. If data line length differs fromto -from , it is resampled to
this length.
|
set_row(data_line, row)Sets a row in the data field to values of a data line. Data line length must be equal to width of data field.
|
set_row_part(data_line, row, _from, to)Puts a data line into a data field row. If data line length differs fromto -from , it is resampled to
this length.
|
set_si_unit_xy(si_unit)Sets the SI unit corresponding to the lateral (XY) dimensions of a data field. It does not assume a reference onsi_unit ,
instead it adds its own reference.
|
set_si_unit_z(si_unit)Sets the SI unit corresponding to the "height" (Z) dimension of a data field. It does not assume a reference onsi_unit ,
instead it adds its own reference.
|
set_val(col, row, value)Sets value at given position in a data field. Do not set data with this function inside inner loops, it's slow. Get raw data buffer withDataField.get_data () and write to it
directly instead.
|
set_xoffset(xoff)Sets the X offset of a data field origin. Note offsets don't affect any calculation, nor functions likeDataField.rotj ().
|
set_xreal(xreal)Sets X real (physical) size value of a data field.
|
set_yoffset(yoff)Sets the Y offset of a data field origin. Note offsets don't affect any calculation, nor functions likeDataField.rtoi ().
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set_yreal(yreal)Sets Y real (physical) size value of a data field.
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shade(target_field, theta, phi)Shades a data field.
|
slope_distribution(derdist, kernel_size)Computes angular slope distribution.
|
subtract_fields(operand1, operand2)Subtracts one data field from another. |
subtract_legendre(col_degree, row_degree, coeffs)Subtracts a two-dimensional Legendre polynomial fit from a data field.
|
subtract_poly(nterms, term_powers, coeffs)Subtract a given set of polynomial terms from a data field. Since: 2.11
|
subtract_poly_max(max_degree, coeffs)Subtracts a two-dimensional polynomial with limited total degree from a data field.
|
subtract_polynom(col_degree, row_degree, coeffs)Subtracts a two-dimensional polynomial from a data field.
|
sum_fields(operand1, operand2)Sums two data fields. |
threshold(threshval, bottom, top)Tresholds values of a data field. Values smaller thanthreshold are set to value
bottom , values higher than
threshold or equal to it are set to value
top
|
UNIMPLEMENTED_area_fit_legendre(col, row, width, height, col_degree, row_degree, coeffs)Fits two-dimensional Legendre polynomial to a rectangular part of a data field. The The coefficients are organized exactly like in
|
UNIMPLEMENTED_area_fit_local_planes(size, col, row, width, height, nresults, types, results)Fits a plane through neighbourhood of each sample in a rectangular part of a data field. The sample is always in the origin of its local (x,y) coordinate system, even if the neighbourhood is not centered about it (e.g. because sample is on the edge of data field). Z-coordinate is however not centered, that isPLANE_FIT_A is normal mean
value.
|
UNIMPLEMENTED_area_fit_poly_max(col, row, width, height, max_degree, coeffs)Fits two-dimensional polynomial with limited total degree to a rectangular part of a data field. SeeDataField.area_fit_legendre () for description. This
function differs by limiting the total maximum degree, while
DataField.area_fit_legendre () limits the maximum degrees
in horizontal and vertical directions independently.
|
UNIMPLEMENTED_area_get_min_max(mask, col, row, width, height, min, max)Finds minimum and maximum values in a rectangular part of a data field.
|
UNIMPLEMENTED_area_get_normal_coeffs(col, row, width, height, nx, ny, nz, normalize1)Computes average normal vector of an area of a data field.
|
UNIMPLEMENTED_circular_area_extract_with_pos(col, row, radius, data, xpos, ypos)Extracts values with positions from a circular region of a data field. The row and column indices stored toxpos and
ypos are relative to the area centre, i.e. to
(col , row ). The central pixel
will therefore have 0 at the corresponding position in both
xpos and ypos .
|
UNIMPLEMENTED_correlate_init(kernel_field, score)Creates a new correlation iterator. This iterator reports its state asComputationStateType .
|
UNIMPLEMENTED_crosscorrelate_init(data_field2, x_dist, y_dist, score, search_width, search_height, window_width, window_height)Initializes a cross-correlation iterator. This iterator reports its state asComputationStateType .
|
UNIMPLEMENTED_cwt(interpolation, scale, wtype)Computes a continuous wavelet transform (CWT) at given scale and using given wavelet.
|
UNIMPLEMENTED_distort(dest, invtrans, user_data, interp, exterior, fill_value)Distorts a data field in the horizontal plane. Note the transform function
|
UNIMPLEMENTED_fit_legendre(col_degree, row_degree, coeffs)Fits two-dimensional Legendre polynomial to a data field. SeeDataField.area_fit_legendre () for details.
|
UNIMPLEMENTED_fit_local_planes(size, nresults, types, results)Fits a plane through neighbourhood of each sample in a data field. SeeDataField.area_fit_local_planes () for details.
|
UNIMPLEMENTED_fit_poly_max(max_degree, coeffs)Fits two-dimensional polynomial with limited total degree to a data field. SeeDataField.area_fit_poly_max () for details.
|
UNIMPLEMENTED_get_autorange(_from, to)Computes value range with outliers cut-off. The purpose of this function is to find a range is suitable for false color mapping. The precise method how it is calculated is unspecified and may be subject to changes. However, it is guaranteed minimum <=
|
UNIMPLEMENTED_get_grain_bounding_boxes(ngrains, grains, bboxes)Find bounding boxes of all grains.
|
UNIMPLEMENTED_get_inclination(theta, phi)Calculates the inclination of the image (polar and azimuth angle).
|
UNIMPLEMENTED_get_value_format_xy(style, format)Finds value format good for displaying coordinates of a data field.
|
UNIMPLEMENTED_get_value_format_z(style, format)Finds value format good for displaying values of a data field.
|
UNIMPLEMENTED_grains_get_distribution(grain_field, distribution, ngrains, grains, quantity, nstats)Computes distribution of requested grain characteristics. Puts number of grains vs. grain value data intodistribution , units, scales and offsets of
distribution are updated accordingly.
|
UNIMPLEMENTED_grains_get_values(values, ngrains, grains, quantity)Calculates characteristics of grains. This is a bit low-level function, see also
The array values .
Therefore as long as the same grains is used, the
same position in values corresponds to the same
particular grain. This enables one for instance to calculate grain
sizes and grain heights and then correlate them.
|
UNIMPLEMENTED_grains_watershed_init(grain_field, locate_steps, locate_thresh, locate_dropsize, wshed_steps, wshed_dropsize, prefilter, below)Initializes the watershed algorithm. This iterator reports its state asWatershedStateType .
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UNIMPLEMENTED_number_grains(grains)Numbers grains in a mask data field.
|
xdwt(wt_coefs, direction, minsize)Performs steps of the X-direction image wavelet decomposition. The smallest low pass coefficients block is equal tominsize . Run with minsize =
dfield ->xres/2 to perform one step of
decomposition or minsize = 4 to perform full
decomposition (or anything between).
|
ydwt(wt_coefs, direction, minsize)Performs steps of the Y-direction image wavelet decomposition. The smallest low pass coefficients block is equal tominsize . Run with minsize =
dfield ->yres/2 to perform one step of
decomposition or minsize = 4 to perform full
decomposition (or anything between).
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