edtools.find_cell
Functions:
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Perform hierarchical cluster analysis on a list of cells. |
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Helper function for unit_cell_lcv_distance |
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Takes a linkage object z from scipy.cluster.hierarchy.linkage and displays a dendrogram. |
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Opens a plot with 6 subplots in which the cell parameter histogram is displayed. |
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order cell parameters in order to eliminate difference in cell distance because of parameter order |
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convert all angles in unit cell parameter list to radians cells: the cell parameters that are parsed from cells.yaml as np array |
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convert all angles in unit cell parameter list to sine cells: the cell parameters that are parsed from cells.yaml as np array |
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Implements Linear Cell Volume from Acta Cryst. |
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Return the absolute difference in volumes between two unit cells |
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Returns weighted mean and standard deviation |
- edtools.find_cell.cluster_cell(cells: list, distance: Optional[float] = None, method: str = 'average', metric: str = 'euclidean', use_radian: bool = False, use_sine: bool = False)
Perform hierarchical cluster analysis on a list of cells.
method: lcv, volume, euclidean distance: cutoff distance, if it is not given, pop up a dendrogram to
interactively choose a cutoff distance
use_radian: Use radian instead of degrees to downweight difference use_sine: Use sine for unit cell clustering (to disambiguousize the difference in angles)
- edtools.find_cell.d_calculator(cell: list) tuple
Helper function for unit_cell_lcv_distance
- edtools.find_cell.distance_from_dendrogram(z, ylabel: str = '', initial_distance: Optional[float] = None) float
Takes a linkage object z from scipy.cluster.hierarchy.linkage and displays a dendrogram. The cutoff distance can be picked interactively, and is returned ylabel: sets the label for the y-axis initial_distance: initial cutoff distsance to display
- edtools.find_cell.find_cell(cells, weights, binsize=0.5)
Opens a plot with 6 subplots in which the cell parameter histogram is displayed. It will calculate the weighted mean of the unit cell parameters. The ranges can be adjusted by dragging on the plots.
- edtools.find_cell.get_clusters(z, cells, distance=0.5)
- edtools.find_cell.main()
- edtools.find_cell.parse_cellparm(fn)
- edtools.find_cell.put_in_order(cells)
order cell parameters in order to eliminate difference in cell distance because of parameter order
- edtools.find_cell.to_radian(cells)
convert all angles in unit cell parameter list to radians cells: the cell parameters that are parsed from cells.yaml as np array
- edtools.find_cell.to_sin(cells)
convert all angles in unit cell parameter list to sine cells: the cell parameters that are parsed from cells.yaml as np array
- edtools.find_cell.unit_cell_lcv_distance(cell1: list, cell2: list) float
Implements Linear Cell Volume from Acta Cryst. (2013). D69, 1617-1632
- edtools.find_cell.volume_difference(cell1: list, cell2: list)
Return the absolute difference in volumes between two unit cells
- edtools.find_cell.weighted_average(values, weights=None)
Returns weighted mean and standard deviation