Data

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@Data_Class Module describing a Data Set where values are associated with an xyz co-ordinate

class geobipy.src.classes.data.dataset.Data.Data(components=None, channels_per_system=1, x=None, y=None, z=None, elevation=None, data=None, std=None, predictedData=None, fiducial=None, lineNumber=None, units=None, channel_names=None, **kwargs)

Class defining a set of Data.

Data(channels_per_system, x, y, z, data, std, predictedData, dataUnits, channel_names)

Parameters:

nPoints (int) – Number of points in the data.
channels_per_system (int or array_like) – Number of data channels in the data * If int, a single acquisition system is assumed. * If array_like, each item describes the number of points per acquisition system.
x (geobipy.StatArray or array_like, optional) – The x co-ordinates. Default is zeros of size nPoints.
y (geobipy.StatArray or array_like, optional) – The y co-ordinates. Default is zeros of size nPoints.
z (geobipy.StatArrayor array_like, optional) – The z co-ordinates. Default is zeros of size nPoints.
data (geobipy.StatArrayor array_like, optional) – The values of the data. * If None, zeroes are assigned
std (geobipy.StatArrayor array_like, optional) – The uncertainty estimates of the data. * If None, ones are assigned if data is None, else 0.1*data
predictedData (geobipy.StatArrayor array_like, optional) – The predicted data. * If None, zeros are assigned.
dataUnits (str) – Units of the data.
channel_names (list of str, optional) – Names of each channel of length sum(channels_per_system)

Returns:

out – Data class

Return type:

Data

Bcast(world, root=0)

Broadcast a Data object using MPI

Parameters:

world (mpi4py.MPI.COMM_WORLD) – MPI communicator
root (int, optional) – The MPI rank to broadcast from. Default is 0.

Returns:

out – Data broadcast to each core in the communicator

Return type:

geobipy.Data

Scatterv(starts, chunks, world, root=0)

Scatterv a Data object using MPI

Parameters:

starts (array of ints) – 1D array of ints with size equal to the number of MPI ranks. Each element gives the starting index for a chunk to be sent to that core. e.g. starts[0] is the starting index for rank = 0.
chunks (array of ints) – 1D array of ints with size equal to the number of MPI ranks. Each element gives the size of a chunk to be sent to that core. e.g. chunks[0] is the chunk size for rank = 0.
world (mpi4py.MPI.Comm) – The MPI communicator over which to Scatterv.
root (int, optional) – The MPI rank to broadcast from. Default is 0.

Returns:

out – The Data distributed amongst ranks.

Return type:

geobipy.Data

property active

Logical array whether the channel is active or not.

An inactive channel is one where channel values are NaN for all points.

Returns:: out – Indices of non-NaN columns.
Return type:: bools

addToVTK(vtk, prop=['data', 'predicted', 'std'], system=None)

Adds a member to a VTK handle.

Parameters:

vtk (pyvtk.VtkData) – vtk handle returned from self.vtkStructure()
prop (str or list of str, optional) – List of the member to add to a VTK handle, either “data”, “predicted”, or “std”.
system (int, optional) – The system for which to add the data

property additive_error: The data.

append(other)

Append pointclouds together

Parameters:: other (geobipy.PointCloud3D) – 3D pointcloud

channel_index(channel, system)

Gets the data in the specified channel

Parameters:

channel (int) – Index of the channel to return * If system is None, 0 <= channel < self.nChannels else 0 <= channel < self.nChannelsPerSystem[system]
system (int, optional) – The system to obtain the channel from.

Returns:

out – The index of the channel

Return type:

int

createHdf(parent, myName, withPosterior=True, fillvalue=None): Create the hdf group metadata in file parent: HDF object to create a group inside myName: Name of the group

property data: The data.

data_misfit(squared=False)

Compute the \(L_{2}\) norm squared misfit between the observed and predicted data

\[\| \mathbf{W}_{d} (\mathbf{d}^{obs}-\mathbf{d}^{pre})\|_{2}^{2},\]

where \(\mathbf{W}_{d}\) are the reciprocal data errors.

Parameters:: squared (bool) – Return the squared misfit.
Returns:: out – The misfit value.
Return type:: float64

datapoint(i)

Get the ith data point from the data set

Parameters:: i (int) – The data point to get
Returns:: out – The data point
Return type:: geobipy.DataPoint

property deltaD

Get the difference between the predicted and observed data,

\[\delta \mathbf{d} = \mathbf{d}^{pre} - \mathbf{d}^{obs}.\]

Returns:: out – The residual between the active observed and predicted data.
Return type:: StatArray

classmethod fromHdf(grp, **kwargs): Reads the object from a HDF group

line(line): Get the data from the given line number

mapData(channel, system=None, *args, **kwargs)

Interpolate the data channel between the x, y co-ordinates.

Parameters:

channel (int) – Index of the channel to return * If system is None, 0 <= channel < self.nChannels else 0 <= channel < self.nChannelsPerSystem[system]
system (int, optional) – The system to obtain the channel from.

mapPredictedData(channel, system=None, *args, **kwargs)

Interpolate the predicted data channel between the x, y co-ordinates.

Parameters:

channel (int) – Index of the channel to return * If system is None, 0 <= channel < self.nChannels else 0 <= channel < self.nChannelsPerSystem[system]
system (int, optional) – The system to obtain the channel from.

mapStd(channel, system=None, *args, **kwargs)

Interpolate the standard deviation channel between the x, y co-ordinates.

Parameters:

channel (int) – Index of the channel to return * If system is None, 0 <= channel < self.nChannels else 0 <= channel < self.nChannelsPerSystem[system]
system (int, optional) – The system to obtain the channel from.

nPointsPerLine()

Gets the number of points in each line.

Returns:: out – Number of points in each line
Return type:: ints

plot_data(x='index', channels=None, system=None, **kwargs)

Plots the specifed channels as a line plot.

Plots the channels along a specified co-ordinate e.g. ‘x’. A legend is auto generated.

Parameters:

xAxis (str) – If xAxis is ‘index’, returns numpy.arange(self.nPoints) If xAxis is ‘x’, returns self.x If xAxis is ‘y’, returns self.y If xAxis is ‘z’, returns self.z If xAxis is ‘r2d’, returns cumulative distance along the line in 2D using x and y. If xAxis is ‘r3d’, returns cumulative distance along the line in 3D using x, y, and z.
channels (ints, optional) – Indices of the channels to plot. All are plotted if None * If system is None, 0 <= channel < self.nChannels else 0 <= channel < self.nChannelsPerSystem[system]
values (arraylike, optional) – Specifies values to plot against the chosen axis. Takes precedence over channels.
system (int, optional) – The system to obtain the channel from.
legend (bool) – Attach a legend to the plot. Default is True.

Returns:

ax (matplotlib.axes) – Plot axes handle
legend (matplotlib.legend.Legend) – The attached legend.