plot_func module¶
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plot_func.
closefig
()¶
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plot_func.
closegraph
()¶
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plot_func.
get_color
(v, v_minmax=None, colorscale=’jet’, return_r=False)¶
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class
plot_func.
legendScale
(data=None, n=None, scale_type=’linear’, perc_bnd=[0, 100], colorscale=’jet’)¶ Bases:
dict
Methods
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copy
()¶
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getBoundaries
()¶
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getCmap
()¶
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getColorscale
()¶
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getFrm
()¶
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getImodLabels
()¶
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getLabels
()¶
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getRgba
()¶
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getTicks
()¶
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make_figure
(labels=False)¶
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putBoundaries
(boundaries)¶
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putImodLabels
(imodlabels)¶
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putLabels
(labels)¶
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putRgba
(rgba)¶
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putTicks
(ticks)¶
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setBoundaries
(data, n=None, scale_type=’linear’, perc_bnd=[0, 100])¶ Method to set suitable boundary values (intervals) for classification of the data.
The boundaries may be used for classification into legends (colour scales), histogram bins etc.
Parameters: data : numpy array (ndarray or MaskedArray) or array_like
The data to base the boundaries on. Masked values will not be included in the determination of the boundaries.
n : int or None (optional)
Number of intervals. This is an initial number; the final number of intervals may differ depending on the determined interval width.
If n is None then the initial number of intervals will be 8.
scale_type : str (optional)
Two types are supported: ‘linear’ and ‘histogram’.
If scale_type is ‘linear’ then the intervals will have equal widths.
If scale_type is ‘histogram’ then the interval widths will be based on the distribution of values (percentiles).
perc_bnd : numpy array or array_like (optional)
Lower and upper percentiles to be used as initial minimum and maximum boundary values.
Returns: boundaries : numpy ndarray
Boundaries values.
frm : str
String format (% format) to format the boundaries values.
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setImodLabels
()¶
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setLabels
()¶
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setLegend
(colorscale=None, alfa=1)¶
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setOver
(rgba=None)¶
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setTicks
()¶
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setUnder
(rgba=None)¶
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write_imod_leg
(f_leg)¶
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plot_func.
read_imod_leg
(f_leg)¶