garnet.plots package#

Submodules#

garnet.plots.base module#

class BasePlot[source]#

Bases: object

Methods

save_plot(filename)

Save plot.

close
close()[source]#
save_plot(filename)[source]#

Save plot.

Parameters:
filenamestr

Path to file.

class Pages(filename)[source]#

Bases: object

Methods

add_plot

close
add_plot(fig)[source]#
close()[source]#

garnet.plots.colors module#

Atom color map for plotting (shared module).

garnet.plots.crystal module#

class CrystalStructurePlot(sites, cell, space_group=None)[source]#

Bases: object

Methods

get_crystal_structure

matrices

params

plot

wrap
get_crystal_structure()[source]#
matrices()[source]#
params(a, b, c, alpha, beta, gamma)[source]#
plot(filename)[source]#
wrap(val)[source]#

garnet.plots.monitor module#

class SlicePlot(UB, W)[source]#

Bases: object

Plotly version of the reciprocal-space slice plot.

This version resamples the oblique slice grid onto a rectangular display grid and draws it with a standard Plotly Heatmap.

Parameters:
UBndarray, shape (3, 3)

UB matrix.

Wndarray, shape (3, 3)

Basis or transform matrix used to construct the metric tensor in the slice frame.

Methods

calculate_transforms(axes, labels, normal[, ...])

Precompute the display transform and build the Plotly heatmap.

make_slice(data_signal, norm_signal, value)

Update the figure to show the slice nearest the requested value.
MAX_DISPLAY_BINS = 201[source]#
calculate_transforms(axes, labels, normal, oversample=1.0, interpolation='nearest')[source]#

Precompute the display transform and build the Plotly heatmap.

Parameters:
axessequence of ndarray

Axis arrays for the 3 dimensions.

labelssequence of str

Axis labels for the 3 dimensions.

normalarray-like of length 3

Slice normal selector. This follows the same convention as the original code: the dimension with value 1 is taken as the sliced dimension.

oversamplefloat, optional

Display oversampling factor for the rectangular grid. A value of 1.0 is usually fine.

interpolation{“nearest”, “linear”}, optional

Interpolation used when resampling onto the display grid.

make_slice(data_signal, norm_signal, value)[source]#

Update the figure to show the slice nearest the requested value.

Counts and normalization are resampled onto the display grid separately, then divided – resampling their ratio directly produces artifacts near masked/zero-exposure bins, since a single missing/zero normalization value would otherwise corrupt the interpolated ratio in its whole interpolation neighborhood.

Parameters:
data_signalndarray, shape (n0, n1, n2)

3D raw-counts signal array.

norm_signalndarray, shape (n0, n1, n2)

3D normalization signal array, matching data_signal’s shape.

valuefloat

Requested slice coordinate.

garnet.plots.peaks module#

class PeakCentroidPlot(c0, c1, c2, Q, r_cut, d_min)[source]#

Bases: BasePlot

Methods

save_plot(filename)

Save plot.

close
class PeakEstimatePlot(zs, ys, es)[source]#

Bases: BasePlot

Methods

save_plot(filename)

Save plot.

close

plot_peak_bins
plot_peak_bins(ax, z, y)[source]#
class PeakPlot[source]#

Bases: BasePlot

Methods

add_ellipsoid(c, S)

Draw ellipsoid envelopes.

add_ellipsoid_fit(xye_fit)

Three-dimensional ellipsoids.

add_estimated_ellipsoid(c, S)

Draw estimated ellipsoid envelopes on ROI views.

add_peak_info(hkl, d, wavelength, angles, gon)

Add peak information.

add_peak_stats(reddev, intensity, sigma)

Add peak statistics.

save_plot(filename)

Save the current peak figure without rebuilding it.

update_envelope(x0, x1, x2, pk, bkg)

Draw region-of-interest.

add_data_norm_fit

add_profile_bkg

add_profile_fit

add_profile_iterations

add_projection_fit

close
add_data_norm_fit(xye, params)[source]#
add_ellipsoid(c, S)[source]#

Draw ellipsoid envelopes.

Parameters:
c1d-array

3 component center.

S2d-array

3x3 covariance matrix.

add_ellipsoid_fit(xye_fit)[source]#

Three-dimensional ellipsoids.

Parameters:
x0, x1, x2, y, e, fit3d-array

Bins, signal, error, and fit.

add_estimated_ellipsoid(c, S)[source]#

Draw estimated ellipsoid envelopes on ROI views.

Parameters:
c1d-array

3 component center.

S2d-array

3x3 covariance matrix.

add_peak_info(hkl, d, wavelength, angles, gon)[source]#

Add peak information.

Parameters:
hkllist

Miller indices.

dfloat,

Interplanar d-spacing.

wavelengthfloat

Wavelength.

angleslist

Scattering and azimuthal angles.

gonlist

Goniometer Euler angles.

add_peak_stats(reddev, intensity, sigma)[source]#

Add peak statistics.

Parameters:
reddevlist

Reduced Poisson deviance D/dof per mode.

intensitylist

Integrated intensity.

sigmalist

Integrated intensity uncertainty.

add_profile_bkg(bkg_prof)[source]#
add_profile_fit(xye_fit)[source]#
add_profile_iterations(result)[source]#
add_projection_fit(xye_fit)[source]#
save_plot(filename)[source]#

Save the current peak figure without rebuilding it.

PeakPlot mutators update existing artists in place, so repeated saves can reuse the same figure instead of recreating the entire layout for each peak.

update_envelope(x0, x1, x2, pk, bkg)[source]#

Draw region-of-interest. mask =

Parameters:
pk3d-array

Peak region.

bkg3d-array

Background shell.

class PeakProfilePlot(x, y, e, vol, r, r_cut)[source]#

Bases: BasePlot

Methods

save_plot(filename)

Save plot.

close

draw_boundary

plot_peak_bins

plot_peaks
draw_boundary(res, params)[source]#
plot_peak_bins(x0, x1, x2, y0, y1, y2, e0, e1, e2)[source]#
plot_peaks(x0, x1, x2, y0, y1, y2, e0, e1, e2, r_cut)[source]#
class ScanPlot(thresholds, max_peaks, indexed_peaks, cutoff)[source]#

Bases: BasePlot

Methods

save_plot(filename)

Save plot.

close

garnet.plots.volume module#

class SlicePlot(UB, W)[source]#

Bases: BasePlot

Methods

save_plot(filename)

Save plot.

calculate_transforms

close

make_slice
calculate_transforms(axes, labels, normal)[source]#
make_slice(signal, value)[source]#

Module contents#