Pynoddy modules, classes and functions

Basic modules (low-level access)

The modules in this section provide low-level access to the functionality in Noddy. Basically, these modules provide parsers for Noddy input and output files and class definitions for suitable Noddy elements.

Main module

Package initialization file for pynoddy

pynoddy.compute_model(history, output_name, **kwds)

Call Noddy and compute the history file

Arguments:

• history = string : filename of history file
• output_name = string : basename for output files

Optional Keywords:

• sim_type = ‘BLOCK’, ‘GEOPHYSICS’, ‘SURFACES’, ‘BLOCK_GEOPHYS’,

‘TOPOLOGY’, ‘BLOCK_SURFACES’, ‘ALL’:

type of Noddy simulation (default: ‘BLOCK’)

• program_name = string : name of program

  (default: noddy.exe or noddy, both checked)

• verbose = bool: verbose mode, print out information for debugging (default = False)

Returns:

-Returns any text outputted by the noddy executable.

pynoddy.compute_topology(rootname, **kwds)

Call the topology executable to compute a models topology.

Arguments:

• rootname = string : rootname of the noddy model to calculate topology for

Optional Keywords:

• ensure_discrete_volumes = True if topological units are broken down into

  separate, spatially continuous volumes. Otherwise some topological units may represent two separate rock volumes (eg. if a folded unit has been truncated by an unconformity). Default is True, though this is a global variable (pynoddy.ensure_discrete_volumes) so it can be changed during runtime.

• null_volume_threshold = The smallest non-null volume. volumes smaller than this are

  ignored by the topology algorithm (as they represent pixelation artefacts). The default is 20 voxels, though this is a global variable and can be changed with pynoddy.null_volume_threshold.

Returns

-Returns any text outputted by the topology executable, including errors.

History file parser: pynoddy.history

Noddy history file wrapper Created on 24/03/2014

@author: Florian Wellmann

class pynoddy.history.NoddyHistory(history=None, **kwds)

Bases: object

Class container for Noddy history files

add_event(event_type, event_options, **kwds)

Add an event type to history

Arguments:

• event_type = string : type of event, legal options to date are:

‘stratigraphy’, ‘fault’, ‘fold’, ‘unconformity’ - event_options = list : required options to create event (event dependent)

Optional keywords:

• event_num = int : event number (default: implicitly defined with increasing counter)

change_cube_size(cube_size, **kwds)

Change the model cube size (isotropic)

Arguments:

• cube_size = float : new model cube size

change_event_params(changes_dict)

Change multiple event parameters according to settings in changes_dict

Arguments:

• changes_dict = dictionary : entries define relative changes for (multiple) parameters

Per default, the values in the dictionary are added to the event parameters.

copy_events()

Create a copy of the current event state

create_footer_from_template()

Create model footer (with all settings) from template

create_new_history()

Methods to create a Noddy model

determine_events(**kwds)

Determine events and save line numbers

Note

Parsing of the history file is based on a fixed Noddy output order.

If this is, for some reason (e.g. in a changed version of Noddy) not the case, then this parsing might fail!

Optional Keywords:

• verbose = True if this function is should write to the print bufffer, otherwise False. Default is False.

determine_model_stratigraphy()

Determine stratigraphy of entire model from all events

get_cube_size(**kwds)

Determine cube size for model export Optional Args

-type: choose geology or geophysics cube size to return. Should be either ‘Geology’ (default) or ‘Geophysics’

get_date_saved()

Determine the last savepoint of the file

get_drillhole_data(x, y, **kwds)

Get geology values along 1-D profile at position x,y with a 1 m resolution

The following steps are performed: 1. creates a copy of the entire object, 2. sets values of origin, extent and geology cube size, 3. saves model to a temporary file, 4. runs Noddy on that file 5. opens and analyses output 6. deletes temporary files

Note: this method only works if write access to current directory is enabled and noddy can be executed!

Arguments:

• x = float: x-position of drillhole
• y = float: y-position of drillhole

Optional Arguments:

• z_min = float : minimum depth of drillhole (default: model range)
• z_max = float : maximum depth of drillhole (default: model range)
• resolution = float : resolution along profile (default: 1 m)

get_ev_counter()

Event counter for implicit and continuous definition of events

get_event_param(event_number, name)

Returns the value of a given parameter for a given event.

Arguments:

• event_number = the event to get a parameter for (integer)
• name = the name of the parameter to retreive (string)

Returns

• Returns the value of the request parameter, or None if it does not exists.

get_event_params(event_number)

Returns the parameter dictionary for a given event.

Arguments:

• event_number = the event to get a parameter for (integer)

Returns

• Returns the parameter dictionary for the requested event

get_extent()

Get model extent and return and store in local variables

Returns: (extent_x, extent_y, extent_z)

get_filename()

Determine model filename from history file/ header

get_footer_lines()

Get the footer lines from self.history_lines

The footer contains everything below events (all settings, etc.)

get_info_string(**kwds)

Get model information as string

Optional keywords:

• events_only = bool : only information on events

get_origin()

Get coordinates of model origin and return and store in local variables

Returns: (origin_x, origin_y, origin_z)

info(**kwds)

Print out model information

Optional keywords:

• events_only = bool : only information on events

load_history(history)

Load Noddy history

Arguments:

• history = string : Name of Noddy history file

load_history_from_url(url)

Directly load a Noddy history from a URL

This method is useful to load a model from the Structural Geophysics Atlas on the pages of the Virtual Explorer. See: http://tectonique.net/asg

Arguments:

• url : url of history file

reorder_events(reorder_dict)

Reorder events accoring to assignment in reorder_dict

Arguments:

• reorder_dict = dict : for example {1 : 2, 2 : 3, 3 : 1}

set_event_params(params_dict)

set multiple event parameters according to settings in params_dict

Arguments:

• params_dict = dictionary : entries to set (multiple) parameters

set_extent(extent_x, extent_y, extent_z)

Set model extent and update local variables

Arguments:

• extent_x = float : extent in x-direction
• extent_y = float : extent in y-direction
• extent_z = float : extent in z-direction

set_origin(origin_x, origin_y, origin_z)

Set coordinates of model origin and update local variables

Arguments:

• origin_x = float : x-location of model origin
• origin_y = float : y-location of model origin
• origin_z = float : z-location of model origin

swap_events(event_num_1, event_num_2)

Swap two geological events in the timeline

Arguments:

• event_num_1/2 = int : number of events to be swapped (“order”)

update_all_event_properties()

Update properties of all events - in case changes were made

update_event_numbers()

Update event numbers in ‘Event #’ line in noddy history file

write_history(filename)

Write history to new file

Arguments:

• filename = string : filename of new history file

Hint

Just love it how easy it is to ‘write history’ with Noddy ;-)

Output file parser: pynoddy.output

Noddy output file analysis Created on 24/03/2014

@author: Florian Wellmann, Sam Thiele

class pynoddy.output.NoddyGeophysics(output_name)

Bases: object

Definition to read, analyse, and visualise calculated geophysical responses

read_gravity()

Read calculated gravity response

read_magnetics()

Read caluclated magnetic field response

class pynoddy.output.NoddyOutput(output_name)

Bases: object

Class definition for Noddy output analysis

compare_dimensions_to(other)

Compare model dimensions to another model

determine_unit_volumes()

Determine volumes of geological units in the discretized block model

export_to_vtk(**kwds)

Export model to VTK

Export the geology blocks to VTK for visualisation of the entire 3-D model in an external VTK viewer, e.g. Paraview.

..Note:: Requires pyevtk, available for free on: https://github.com/firedrakeproject/firedrake/tree/master/python/evtk

Optional keywords:

• vtk_filename = string : filename of VTK file (default: output_name)
• data = np.array : data array to export to VKT (default: entire block model)

get_section_lines(direction='y', position='center', **kwds)

Create and returns a list of lines representing a section block through the model

Arguments:

• direction = ‘x’, ‘y’, ‘z’ : coordinate direction of section plot (default: ‘y’)

• position = int or ‘center’ : cell position of section as integer value

  or identifier (default: ‘center’)

Returns: A tuple of lists of dictionaries.... ie: ( [ dictionary of x coordinates, with lithology pairs as keys, separated by an underscore],

[ dictionary of y coordinates, with lithology pairs as keys, separated by an underscore], [ dictionary of z coordinates, with lithology pairs as keys, separated by an underscore], [ dictionary of colours, with lithologies as keys])

For example: get_section_lines()[0][“1_2”] returns a list of all the x coordinates from the contact between lithology 1 and lithology 2. Note that the smaller lithology index always comes first in the code.

get_section_voxels(direction='y', position='center', **kwds)

Create and returns section block through the model

Arguments:

• direction = ‘x’, ‘y’, ‘z’ : coordinate direction of section plot (default: ‘y’)

• position = int or ‘center’ : cell position of section as integer value

  or identifier (default: ‘center’)

Optional Keywords:

• data = np.array : data to plot, if different to block data itself
• litho_filter = a list of lithologies to draw. All others will be ignored.

get_surface_grid(lithoID, **kwds)

Returns a grid of lines that define a grid on the specified surface. Note that this cannot handle layers that are repeated in the z direction...

Arguments:

• lithoID - the top surface of this lithology will be calculated. If a list is passed,

  the top surface of each lithology in the list is calculated.

Keywords:

• res - the resolution to sample at. Default is 2 (ie. every second voxel is sampled).

Returns:

a tuple containing lists of tuples of x, y and z coordinate dictionaries and colour dictionaries, one containing the east-west lines and one the north-south lines: ((x,y,z,c),(x,y,z,c)). THe dictionary keys are the lithoID’s passed in the lithoID parameter.

load_geology()

Load block geology ids from .g12 output file

load_model_info()

Load information about model discretisation from .g00 file

plot_section(direction='y', position='center', **kwds)

Create a section block through the model

Arguments:

• direction = ‘x’, ‘y’, ‘z’ : coordinate direction of section plot (default: ‘y’)

• position = int or ‘center’ : cell position of section as integer value

  or identifier (default: ‘center’)

Optional Keywords:

• ax = matplotlib.axis : append plot to axis (default: create new plot)

• figsize = (x,y) : matplotlib figsize

• colorbar = bool : plot colorbar (default: True)

• colorbar_orientation = ‘horizontal’ or ‘vertical’ : orientation of colorbar

  (default: ‘vertical’)

• title = string : plot title

• savefig = bool : save figure to file (default: show directly on screen)

• cmap = matplotlib.cmap : colormap (default: YlOrRd)

• fig_filename = string : figure filename

• ve = float : vertical exaggeration

• layer_labels = list of strings: labels for each unit in plot

• layers_from = noddy history file : get labels automatically from history file

• data = np.array : data to plot, if different to block data itself

• litho_filter = a list of lithologies to draw. All others will be ignored.

set_basename(name)

Set model basename

class pynoddy.output.NoddyTopology(noddy_model, **kwds)

Bases: object

Definition to read, analyse, and visualise calculated voxel topology

calculate_difference(G2, data=False)

Calculates the difference between this NoddyTopology and another NoddyTopology or networkX graph

Arguments

• G2 = a valid NoddyTopology object or NetworkX graph that this topology is to be compared with

Returns

A tuple containing: - The number of different edges - a list of these edges

calculate_overlap(G2)

Calculates the overlap between this NoddyTopology and another NoddyTopology or networkX graph

Arguments

• G2 = a valid NoddyTopology object or NetworkX graph that this topology is to be compared with

Returns

• The number of overlapping edges
• A list of these edges

static calculate_unique_topologies(topology_list, **kwds)

Calculates the number of unique topologies in a list of NoddyTopologies

Arguments:

• topology_list = The list of NoddyTopologies to search through.

Optional Keywords:

• output = A File or list to write cumulative observed topologies distribution. Default is None (nothing written).

• ids = A list to write the unique topology id’s for each topology in the provided topology_list (in that

  order). Default is None.

• frequency = A list to write frequency counts to.

Returns:

• Returns a list of unique topologies.

collapse_stratigraphy()

Collapses all stratigraphic edges in this network to produce a network that only contains structurally bound rock volumes. Essentially this is a network built only with Topology codes and ignoring lithology

Returns

• a new NoddyTopology object containing the collapsed graph. The original object is not modified.

collapse_structure(verbose=False)

Collapses all topology codes down to the last (most recent) difference. Information regarding specific model topology is generalised, eg. lithology A has a fault and stratigrappic contact with B (regardless of how many different faults are involved).

Optional Arguments:

• verbose = True if this function should write to the print buffer. Default is False.

Returns

• a new NoddyTopology object containing the collapsed graph. The original object is not modified.

static combine_topologies(topology_list)

Combines a list of topology networks into a weighted ‘super-network’. This is designed for estimating the likelyhood of a given edge occuring using a series of networks generated in a Monte-Carlo type analysis.

Arguments

• topology_list = A list of networkX graphs or NoddyTopology objects to build supernetwork from.

Returns

• A NetworkX graph object containing all edges from the input graphs and weighted (‘weight’ parameter) according to their observed frequency.

draw_3d_network(**kwds)

Draws a 3D network using matplotlib.

Optional Keywords:

• show = If True, the 3D network is displayed immediatly on-screen in an

  interactive matplotlib viewer. Default is True.

• output = If defined an image of the network is saved to this location.

• node_size = The size of the nodes. Default is 40.

• geology = a NoddyOutput object to draw with the network

• res = resolution to draw geology at. Default is 4 (ie 1/4 of all voxels are drawn)

• horizons = a list of geology surfaces to draw. Default is nothing (none drawn). Slow!

  See NoddyOutput.get_surface_grid for details.

• sections = draw geology sections. Default is True.

draw_adjacency_matrix(**kwds)

Draws an adjacency matrix representing this topology object.

Keywords:

• path = The path to save this image to. If not provided, the image is drawn to the screen
• dpi = The resolution to save this image. Default is 300
• size = The size of the image to save (in inches). This value will be used as the width and the height

draw_difference_matrix(G2, **kwds)

Draws an adjacency matrix containing the difference between this topology and the provided topology

Arguments:

• G2 = A different NoddyTopology or NetworkX Graph to compare to

Optional Keywords:

• strat = A dictionary linking node names to stratigraphic heights and names. Should be as follows { node_name : (height,name) }.
• path = The path to save this image to. If not provided, the image is drawn to the screen
• dpi = The resolution to save this image. Default is 300
• size = The size of the image to save (in inches). This value will be used as the width and the height

static draw_graph_matrix(G, **kwds)

Draws an adjacency matrix representing the specified graph object. Equivalent to NoddyTopology.draw_matrix_image() but for a networkX graph object.

Keywords:

• strat = A dictionary linking node names to stratigraphic heights and names. Should be as follows { node_name : (height,name) }.
• path = The path to save this image to. If not provided, the image is drawn to the screen
• dpi = The resolution to save this image. Default is 300
• size = The size of the image to save (in inches). This value will be used as the width and the height

draw_mayavi(**kwds)

Draws this network with mayavi. This requires the Mayavi python library (mayavi.mlab)

Optional Keywords:

• node_size = The size of the nodes. Default is 40.
• edge_thickness = The thickness of the edges. Default is 4
• show = If true, the model is displayed in the mayavi viewer after exporting. Default is True
• path = A path to save the mayavi vtk file to after generating it.

static draw_mayavi_graph(G, **kwds)

Draws the provided network with mayavi. This requires the Mayavi python library (mayavi.mlab)

Optional Keywords:

• node_size = The size of the nodes. Default is 40.
• edge_thickness = The thickness of the edges. Default is 4
• show = If true, the model is displayed in the mayavi viewer after exporting. Default is True
• path = A path to save the mayavi vtk file to after generating it.

draw_network_hive(**kwds)

Draws a network hive plot (see https://github.com/ericmjl/hiveplot). The axes of the hive are: node lithology, edge age & edge area.

ie. the top axis lists the nodes in stratigraphic order. The second axis lists edges in structural age & thrid axis lists edges by surface area.

Nodes are joined to edge-nodes by lines on the graph if they are topologically linked (ie. if an edge has that node as an end point).

Optional Keywords - path = the path to save this figure - dpi = the resolution of the figure - bg = the background color. Default is black. - axes = The color of the axes and labels.

draw_network_image(outputname='', **kwds)

Draws a network diagram of this NoddyTopology to the specified image

Arguments

• outputname = the path of the image being written. If left as ‘’ the image is written to the same directory as the basename.

Optional Keywords

• dimension = ‘2D’ for a 2D network diagram or ‘3D’ for a 3D network diagram. Default is ‘2D’.

• axis = the axis to view on for 3D network diagrams

• perspective = True to use perspective projection, or False for orthographic projection. Default is False.

• node_size = The size that nodes are drawn. Default is 1500.

• layout = The layout algorithm used in 2D. Options are ‘spring_layout’ (default), ‘shell_layout’, ‘circular_layout’

  and ‘spectral_layout’.

• verbose = True if this function is allowed to write to the print buffer, otherwise false. Default is False.

filter_node_volumes(min_volume=50)

Removes all nodes with volumes less than the specified size

Arguments:

• min_volume = the threshold volume. Nodes with smaller volumes are deleted.

Returns

• returns the number of deleted nodes

find_first_match(known)

Identical to is_unique, except that the index of the first match is returned if this matches, otherwise -1 is returned. Arguments:

-known = a list of valid NoddyTopology objects or NetworkX graphs to compare with.

Returns:

• Returns the index of the first matching topology object, or -1

find_matching(known)

Finds the first matching NoddyTopology (or NetworkX graph) in the specified list

Arguments:

-known = a list of valid NoddyTopology objects or NetworkX graphs to compare with.

Returns:

• Returns the first matching object (jaccard coefficient = 1), or otherwise None

is_unique(known)

Returns True if the topology of this model is different (ie. forms a different network) to a list of models.

Arguments:

-known = a list of valid NoddyTopology objects or NetworkX graphs to compare with.

Returns:

• Returns true if this topology is unique, otherwise false

jaccard_coefficient(G2)

Calculates the Jaccard Coefficient (ratio between the intersection & union) of the graph representing this NOddyTopology and G2.

Arguments

• G2 = a valid NoddyTopology object or NetworkX graph that this topology is to be compared with

Returns

• The jaccard_coefficient

loadNetwork()

Loads the topology network into a NetworkX datastructure

read_adjacency_matrix()

DEPRECIATED Read max number of lithologies aross all models

read_properties()

write_summary_file(path, append=True)

Writes summary information about this network to a file

Optional Arguments

• append = True if summary information should be appended to the file. If so the file is written as a csv spreadsheet.

  Default is true. If False is passed, a single, detailed summary is written for this network.

Additional useful classes

pynoddy.events

Module for reading and manipulating geological events Created on Mar 26, 2014

@author: Florian Wellmann

class pynoddy.events.Dyke(**kwds)

Bases: pynoddy.events.Event

Dyke event

parse_event_lines(lines)

Read specific event lines from history file Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Event(**kwds)

Bases: object

Main class container for geological events

Include here all elements that events have in common (position, etc. - possibly even things like color and other aspects that are defined in the history... Parse for equal settings and include here!)

set_event_lines(lines)

Explicitly define event lines

set_event_number(num)

Set number in ‘Event #’ line to num

update_properties(**kwds)

Update properties (required if self.properties assignment changed!)

class pynoddy.events.Fault(**kwds)

Bases: pynoddy.events.Event

Fault event

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Fold(**kwds)

Bases: pynoddy.events.Event

Folding event

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Plug(**kwds)

Bases: pynoddy.events.Event

Plug event

parse_event_lines(lines)

Read specific event lines from history file Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Shear(**kwds)

Bases: pynoddy.events.Event

Shear zone event

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Strain(**kwds)

Bases: pynoddy.events.Event

Strain event

parse_event_lines(lines)

Read specific event lines from history file Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Stratigraphy(**kwds)

Bases: pynoddy.events.Event

Sedimentary pile with defined stratigraphy

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Tilt(**kwds)

Bases: pynoddy.events.Event

Tilt event

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

class pynoddy.events.Unconformity(**kwds)

Bases: pynoddy.events.Event

Unconformity event

change_height(val)

Change the vertical position (i.e. height) of the entire stratigraphic pile above the unconformity

Note

This is not identical to changing only the ‘Z’ property as the height of all layers has to be adjusted for (geological) consistency

Arguments:

• val = float : value added to current z-values

parse_event_lines(lines)

Read specific event lines from history file

Arguments:

• lines = list of lines : lines with event information (as stored in .his file)

Modules for Kinematic experiments

The modules described in this section are designed to provide a high-level access to the kinematic modelling functionality in Noddy. The modules encapsulate the required aspects of complete experiments, including input file generation, adaptation of parameters, random number generation, model computation, and postprocessing.

Base classes for pynoddy experiments

The base class for any type of experiments is defined in the pynoddy.experiment module.

Base class from which PyNoddy experiments should inherit.

Much basic functionality (random perturbation, plotting etc. is defined here).

Thought: perhaps drawing functions etc. should be moved into NoddyOutput class?

@author: flohorovicic, samthiele

class pynoddy.experiment.Experiment(history=None, **kwds)

Bases: pynoddy.history.NoddyHistory, pynoddy.output.NoddyOutput

Noddy experiment container, inheriting from both noddy history and output methods

export_to_vtk(**kwds)

Export model to VTK

Export the geology blocks to VTK for visualisation of the entire 3-D model in an external VTK viewer, e.g. Paraview.

..Note:: Requires pyevtk, available for free on: https://github.com/firedrakeproject/firedrake/tree/master/python/evtk

Optional keywords:

• vtk_filename = string : filename of VTK file (default: output_name)
• data = np.array : data array to export to VKT (default: entire block model)
• recompute = bool : recompute the block model (default: True)
• model_type = ‘current’, ‘base’ : model type (base “freezed” model can be plotted for comparison)

..Note:: If data is defined, the model is not recomputed and the data from this array is plotted

freeze(**kwds)

Freeze the current model state: store the event settings for later comparison

get_sampling_line_data(xyz_from, xyz_to)

Get computed model along a line, for example as a drillhole position

Arguments:

• xyz_from = [x, y, z] : list of float values for starting position
• xyz_to = [x, y, z] : list of float values for starting position

get_section(direction='y', position='center', **kwds)

Get geological section of the model (re-computed at required resolution) as noddy object

Arguments:

• direction = ‘x’, ‘y’, ‘z’ : coordinate direction of section plot (default: ‘y’)

• position = int or ‘center’ : cell position of section as integer value

  or identifier (default: ‘center’)

Optional arguments:

• resolution = float : set resolution for section (default: self.cube_size)
• model_type = ‘current’, ‘base’ : model type (base “freezed” model can be plotted for comparison)
• compute_output = bool : provide output from command line call (default: True)

get_up_to_date()

Get model state

is_up_to_date

Model state

load_parameter_file(filename, **kwds)

Load parameter statistics from external csv file

The csv file should contain a header row with the relevant keywords identifying columns. In order to be read in correctly, the header should contain the labels:

• ‘event’ : event id
• ‘parameter’ : Noddy parameter (‘Dip’, ‘Dip Direction’, etc.)
• ‘mean’ : mean parameter value
• ‘type’ = ‘normal’, ‘vonmises’ or ‘uniform’.

In addition, it is necessary to define PDF type and parameters. For now, the following settings are supported: - ‘+-‘ = Defines the 2.5th and 97.5th percentiles of the distribution,

similar to a 95% confidence interval.

• ‘stdev’ = standard deviation. Only works if type=’normal’.
• ‘min’ = The minimum value of a uniform distribution (if type=’uniform’)
• ‘max’ = The maximum value of a uniform distribution (if type=’uniform’)

Arguments:

• filename = string : filename

Optional arguments:

• delim = string : delimiter (default: ‘,’ or ‘;’, both checked)

plot_section(direction='y', position='center', **kwds)

Extended version of plot_section method from pynoddy.output class

Arguments:

• direction = ‘x’, ‘y’, ‘z’ : coordinate direction of section plot (default: ‘y’)

• position = int or ‘center’ : cell position of section as integer value

  or identifier (default: ‘center’)

Optional Keywords:

• ax = matplotlib.axis : append plot to axis (default: create new plot)

• figsize = (x,y) : matplotlib figsize

• colorbar = bool : plot colorbar (default: True)

• colorbar_orientation = ‘horizontal’ or ‘vertical’ : orientation of colorbar

  (default: ‘vertical’)

• title = string : plot title

• savefig = bool : save figure to file (default: show directly on screen)

• cmap = matplotlib.cmap : colormap (default: YlOrRd)

• fig_filename = string : figure filename

• ve = float : vertical exaggeration

• layer_labels = list of strings: labels for each unit in plot

• layers_from = noddy history file : get labels automatically from history file

• resolution = float : set resolution for section (default: self.cube_size)

• model_type = ‘current’, ‘base’ : model type (base “freezed” model can be plotted for comparison)

• data = np.array : data to plot, if different to block data itself

random_draw(**kwds)

Perform a random draw for parameter distributions as defined, and calculate model

This method is based on the model “base-state”, and not the current state (as opposed to the self.random_perturbation() method).

Optional Keywords:

• verbose = bool: print out parameter changes as they happen (default: False)
• store_params = bool : store random parameter set (default: True)

random_perturbation(**kwds)

Perform a random perturbation of the model according to parameter statistics defined in self.param_stats.

Note that by default, this function is identical to random_draw. If model_type is set to ‘current’, then parameters are varied according using the current values as distribution means - this allows ‘random walk’ away from the initial model state, which is usually not desired.

Optional arguments:

• store_params = bool : store random parameter set (default: True)

• verbose = bool: print out parameter changes as they happen (default: False)

• model_type = ‘base’, ‘current’ : perturb on basis of current model,

  or use base model (default: ‘base’ model)

reset_base()

Set events back to base model (stored in self.base_events)

reset_random_seed()

Reset random seed to defined value (stored in self.seed, set with self.set_random_seed)

set_parameter_statistics(param_stats)

Define parameter statistics for uncertainty simulation and sensitivity analysis

param_stats = list : list with relevant statistics defined for event parameters list is organised as: param_stats[event_id][parameter_name][stats_type] = value

Example: param_stats[2][“Dip”][“min”] = 200.

Possible statistics are:

• min = float : minimum bound
• max = float : maximum bound
• type = ‘normal’, ‘uniform’ : distribution type
• stdev = float : standard deviation (if normal distribution)

set_random_seed(random_seed)

Set random seed for reproducible experiments

Arguments:

• random_seed = int (or array-like) : define seed

set_up_to_date()

Set boolean variable for valid object

shuffle_event_order(event_ids)

Randomly shuffle order of events

Arguments:

• event_ids = [list of event ids] : event ids to be randomly shuffeled

update()

Update model computation

write_parameter_changes(filepath)

MonteCarlo class

This class provides the basic functionality to perform MonteCarlo error propagation experiments with Noddy.

SensitivityAnalysis class