plotting module¶
Classes:
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Represents the Ramsay deformation plot. |
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Represents the Hsu fabric plot. |
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Represents the Ramsay deformation plot. |
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The class to store values with associated uniformly positions. |
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Plot features on stereographic projection |
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Represents the triangular fabric plot (Vollmer, 1989). |
Functions:
|
Function to quickly show or save |
- class apsg.plotting.FlinnPlot(*args, **kwargs)¶
Bases:
FabricPlot
Represents the Ramsay deformation plot.
- path(*args, **kwargs)¶
Plot EllipsoidSet as path
- point(*args, **kwargs)¶
Plot Ellipsoid as point
- class apsg.plotting.HsuPlot(*args, **kwargs)¶
Bases:
FabricPlot
Represents the Hsu fabric plot.
- path(*args, **kwargs)¶
Plot EllipsoidSet as path
- point(*args, **kwargs)¶
Plot Ellipsoid as point
- class apsg.plotting.RamsayPlot(*args, **kwargs)¶
Bases:
FabricPlot
Represents the Ramsay deformation plot.
- path(*args, **kwargs)¶
Plot EllipsoidSet as path
- point(*args, **kwargs)¶
Plot ellipsoid as point
- class apsg.plotting.RosePlot(**kwargs)¶
Bases:
object
RosePlot
class for rose histogram plotting.- Keyword Arguments:
title (str) – figure title. Default None
bins (int) – Number of bins. Default 36
axial (bool) – Directional data are axial. Defaut True
density (bool) – Use density instead of counts. Default False
pdf (bool) – Plot Von Mises density function instead histogram. Default False
pdf_res (int) – Resolution of pdf. Default 901
kappa (float) – Shape parameter of Von Mises pdf. Default 250
scaled (bool) – Bins scaled by area instead value. Default False
ticks (bool) – show ticks. Default True
grid (bool) – show grid lines. Default False
grid_kw (dict) – Dict passed to Axes.grid. Default {}
plot. (Other keyword arguments are passed to matplotlib) –
Examples
>>> v = vec2set.random_vonmises(position=120) >>> p = RosePlot(grid=False) >>> p.pdf(v) >>> p.bar(v, fc='none', ec='k', lw=1) >>> p.muci(v) >>> p.show()
- bar(*args, **kwargs)¶
Plot rose histogram of angles
- clear()¶
Clear plot
- classmethod from_json(json_dict)¶
Create rose plot from JSON dict
- classmethod load(filename)¶
Load stereonet from pickle file
- Parameters:
filename (str) – name of picke file
- muci(*args, **kwargs)¶
Plot circular mean with confidence interval
- pdf(*args, **kwargs)¶
Plot rose histogram of angles
- render2fig(fig)¶
Plot stereonet to already existing figure or subfigure
- Parameters:
fig (Figure) – A mtplotlib Figure artist
- save(filename)¶
Save stereonet to pickle file
- Parameters:
filename (str) – name of picke file
- savefig(filename='roseplot.png', **kwargs)¶
Save rose plot figure to graphics file
- Keyword Arguments:
filename (str) – filename
All others kwargs are passed to matplotlib Figure.savefig
- show()¶
Show rose plot
- to_json()¶
Return rose plot as JSON dict
- class apsg.plotting.StereoGrid(**kwargs)¶
Bases:
object
The class to store values with associated uniformly positions.
StereoGrid
is used to calculate continous functions on sphere e.g. density distribution.- Keyword Arguments:
kind (str) – Equal area (“equal-area”, “schmidt” or “earea”) or equal angle (“equal-angle”, “wulff” or “eangle”) projection. Default is “equal-area”
hemisphere (str) – “lower” or “upper”. Default is “lower”
overlay_position (tuple or Pair) – Position of overlay X, Y, Z given by Pair. X is direction of linear element, Z is normal to planar. Default is (0, 0, 0, 0)
rotate_data (bool) – Whether plotted data should be rotated together with overlay. Default False
minor_ticks (None or float) – Default None
major_ticks (None or float) – Default None
overlay (bool) – Whether to show overlay. Default is True
overlay_step (float) – Grid step of overlay. Default 15
overlay_resolution (float) – Resolution of overlay. Default 181
clip_pole (float) – Clipped cone around poles. Default 15
grid_type (str) – Type of contouring grid “gss” or “sfs”. Default “gss”
grid_n (int) – Number of counting points in grid. Default 3000
Note: Euclidean norms are used as weights. Normalize data if you dont want to use weigths.
- angmech(faults, **kwargs)¶
Implementation of Angelier-Mechler dihedra method
- Parameters:
faults –
FaultSet
of data
- Kwargs:
method: ‘probability’ or ‘classic’. Classic method assigns +/-1 to individual positions, while ‘probability’ returns maximum likelihood estimate. Other kwargs are passed to contourf
- apply_func(func, *args, **kwargs)¶
Calculate values of user-defined function on sphere.
Function must accept Vector3 like (or 3 elements array) as first argument and return scalar value.
- Parameters:
func (function) – function used to calculate values
*args – passed to function func as args
**kwargs – passed to function func as kwargs
- calculate_density(features, **kwargs)¶
Calculate density distribution of vectors from
FeatureSet
object.The modified Kamb contouring technique with exponential smoothing is used.
- Parameters:
sigma (float) – if none sigma is calculated automatically. Default None
sigmanorm (bool) – If True counting is normalized to sigma multiples. Default True
trimzero – if True, zero contour is not drawn. Default True
- contour(*args, **kwargs)¶
Draw contour lines of values using tricontour.
- Keyword Arguments:
levels (int or list) – number or values of contours. Default 6
cmap – matplotlib colormap used for filled contours. Default “Greys”
colorbar (bool) – Show colorbar. Default False
alpha (float) – transparency. Default None
antialiased (bool) – Default True
linewidths (float) – contour lines width
linestyles (str) – contour lines style
- contourf(*args, **kwargs)¶
Draw filled contours of values using tricontourf.
- Keyword Arguments:
levels (int or list) – number or values of contours. Default 6
cmap – matplotlib colormap used for filled contours. Default “Greys”
colorbar (bool) – Show colorbar. Default False
alpha (float) – transparency. Default None
antialiased (bool) – Default True
- density_lookup(v)¶
Calculate density distribution value at position given by vector
Note: you need to calculate density before using this method
- Parameters:
v – Vector3 like object
- Keyword Arguments:
p (int) – power. Default 2
- max()¶
Returns maximum value of the grid
- max_at()¶
Returns position of maximum value of the grid as
Lineation
- min()¶
Returns minimum value of the grid
- min_at()¶
Returns position of minimum value of the grid as
Lineation
- plotcountgrid(**kwargs)¶
Show counting grid.
- class apsg.plotting.StereoNet(**kwargs)¶
Bases:
object
Plot features on stereographic projection
- Keyword Arguments:
title (str) – figure title. Default None.
tight_layout (bool) – Matplotlib figure tight_layout. Default False
kind (str) – Equal area (“equal-area”, “schmidt” or “earea”) or equal angle (“equal-angle”, “wulff” or “eangle”) projection. Default is “equal-area”
hemisphere (str) – “lower” or “upper”. Default is “lower”
overlay_position (tuple or Pair) – Position of overlay X, Y, Z given by Pair. X is direction of linear element, Z is normal to planar. Default is (0, 0, 0, 0)
rotate_data (bool) – Whether plotted data should be rotated together with overlay. Default False
minor_ticks (None or float) – Default None
major_ticks (None or float) – Default None
overlay (bool) – Whether to show overlay. Default is True
overlay_step (float) – Grid step of overlay. Default 15
overlay_resolution (float) – Resolution of overlay. Default 181
clip_pole (float) – Clipped cone around poles. Default 15
grid_type (str) – Type of contouring grid “gss” or “sfs”. Default “gss”
grid_n (int) – Number of counting points in grid. Default 3000
Examples
>>> l = linset.random_fisher(position=lin(120, 40)) >>> s = StereoNet(title="Random linear features") >>> s.contour(l) >>> s.line(l) >>> s.show()
- arc(*args, **kwargs)¶
Plot arc bewtween two vectors along great circle(s)
- arrow(*args, **kwargs)¶
Plot arrows at position of first argument and oriented in direction of second
- clear()¶
Clear plot
- cone(*args, **kwargs)¶
Plot small circle(s) with given angle(s)
- contour(*args, **kwargs)¶
Plot filled contours using modified Kamb contouring technique with exponential smoothing
- Keyword Arguments:
levels (int or list) – number or values of contours. Default 6
cmap – matplotlib colormap used for filled contours. Default “Greys”
colorbar (bool) – Show colorbar. Default False
alpha (float) – transparency. Default None
antialiased (bool) – Default True
sigma (float) – If None it is automatically calculated
sigmanorm (bool) – If True scaled counts are normalized by sigma. Default True
trimzero (bool) – Remove values equal to 0. Default True
clines (bool) – Show contour lines instead filled contours. Default False
linewidths (float) – contour lines width
linestyles (str) – contour lines style
show_data (bool) – Show data as points. Default False
data_kwargs (dict) – arguments passed to point factory
- fault(*args, **kwargs)¶
Plot fault feature(s) as great circle and point
- format_coord(x, y)¶
Format stereonet coordinates
- classmethod from_json(json_dict)¶
Create stereonet from JSON dict
- great_circle(*args, **kwargs)¶
Plot planar feature(s) as great circle(s)
- hoeppner(*args, **kwargs)¶
Plot a fault-and-striae as in tangent lineation plot - Hoeppner plot.
- line(*args, **kwargs)¶
Plot linear feature(s) as point(s)
- classmethod load(filename)¶
Load stereonet from pickle file
- Parameters:
filename (str) – name of picke file
- pair(*args, **kwargs)¶
Plot pair feature(s) as great circle and point
- pole(*args, **kwargs)¶
Plot pole of planar feature(s) as point(s)
- render2fig(fig)¶
Plot stereonet to already existing figure or subfigure
- Parameters:
fig (Figure) – A mtplotlib Figure artist
- save(filename)¶
Save stereonet to pickle file
- Parameters:
filename (str) – name of picke file
- savefig(filename='stereonet.png', **kwargs)¶
Save stereonet figure to graphics file
- Keyword Arguments:
filename (str) – filename
All others kwargs are passed to matplotlib Figure.savefig
- scatter(*args, **kwargs)¶
Plot vector-like feature(s) as point(s) using scatter
- show()¶
Show stereonet
- to_json()¶
Return stereonet as JSON dict
- vector(*args, **kwargs)¶
Plot vector feature(s) as point(s), filled on lower and open on upper hemisphere.
- class apsg.plotting.VollmerPlot(*args, **kwargs)¶
Bases:
FabricPlot
Represents the triangular fabric plot (Vollmer, 1989).
- Keyword Arguments:
title (str) – figure title. Default None.
ticks (bool) – Show ticks. Default True
n_ticks (int) – Number of ticks. Default 10
tick_size (float) – Size of ticks. Default 0.2
margin (float) – Size of margin. Default 0.05
grid (bool) – Show grid. Default is True
grid_color (str) – Matplotlib color of the grid. Default “k”
grid_style (str) – Matplotlib style of the grid. Default “:”
Examples
>>> l = linset.random_fisher(position=lin(120, 40)) >>> ot = l.ortensor() >>> s = VollmerPlot(title="Point distribution") >>> s.point(ot) >>> s.show()
- path(*args, **kwargs)¶
Plot EllipsoidSet as path
- point(*args, **kwargs)¶
Plot ellipsoid as point
- apsg.plotting.quicknet(*args, **kwargs)¶
Function to quickly show or save
StereoNet
from args- Parameters:
args – object(s) to be plotted. Instaces of
Vector3
,Foliation
,Lineation
,Pair
,Fault
,Cone
,Vector3Set
,FoliationSet
,LineationSet
,PairSet
orFaultSet
.- Keyword Arguments:
savefig (bool) – True to save figure. Default False
filename (str) – filename for figure. Default stereonet.png
savefig_kwargs (dict) – dict passed to
plt.savefig
fol_as_pole (bool) – True to plot planar features as poles, False for plotting as great circle. Default True
Example
>>> l = linset.random_fisher(position=lin(120, 50)) >>> f = folset.random_fisher(position=lin(300, 40)) >>> quicknet(f, l, fol_as_pole=False)