swprocess

https://swprocess.readthedocs.io/en/stable/
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swprocess is a Python package for surface wave processing, supporting MASW data processing,...
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### Install swprocess

Source: https://swprocess.readthedocs.io/en/stable/install.html

Use pip to install or upgrade the swprocess library.

```bash
pip install swprocess

```

```bash
pip install swprocess --upgrade

```

--------------------------------

### trim Method

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Method to trim time series data within specified start and end times.

```python
trim(start_time, end_time)
Parameters:
start_time, end_time (float) – Desired start time and end time in seconds measured from the point the acquisition system was triggered.
Returns:
None – Updates internal attributes.
```

--------------------------------

### AbstractRegistry.create_instance

Source: https://swprocess.readthedocs.io/en/stable/register.html

Creates an instance by name.

```python
@classmethod
def _create_instance(_name_ , _* args_, _** kwargs_):
    pass
```

--------------------------------

### AbstractRegistry.create_class

Source: https://swprocess.readthedocs.io/en/stable/register.html

Creates a class by name.

```python
@classmethod
def _create_class(_name_):
    pass
```

--------------------------------

### AbstractRegistry

Source: https://swprocess.readthedocs.io/en/stable/register.html

Registry class definition.

```python
class _AbstractRegistry(ABC):
    pass
```

--------------------------------

### Masw.create_settings_dict

Source: https://swprocess.readthedocs.io/en/stable/masw.html

Create settings dict using function arguments. See Masw.create_settings_file() for details.

```python
static _create_settings_dict(_workflow ='time-domain'_, _trim =False_, _trim_begin =0.0_, _trim_end =1.0_, _mute =False_, _method ='interactive'_, _window_kwargs =None_, _pad =False_, _df =1.0_, _transform ='fdbf'_, _fmin =5_, _fmax =100_, _vmin =100_, _vmax =1000_, _nvel =200_, _vspace ='linear'_, _weighting ='sqrt'_, _steering ='cylindrical'_, _snr =False_, _noise_begin =-0.5_, _noise_end =0.0_, _signal_begin =0.0_, _signal_end =0.5_, _pad_snr =True_, _df_snr =1.0_, _min_offset =0_, _max_offset =inf_)
```

--------------------------------

### Array1D Initialization Parameters

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Parameters for initializing an Array1D object, including detrending and normalization options.

```python
detrend (bool, optional) – Boolean to control whether a linear detrending operation is performed, default is False so no detrending is performed.
normalize ({"none", "each", "all"}, optional) – Enable different normalizations to be performed. "each" normalizes each traces by its maximum. "all" normalizes all traces by the same maximum. Default is "none" so no normalization is performed.
```

--------------------------------

### Allow for interactive picking of first arrivals

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Allow for interactive picking of first arrivals.

```python
def manual_pick_first_arrivals(_waterfall_kwargs =None_):
    """Allow for interactive picking of first arrivals."""
    pass
```

--------------------------------

### SourceWithSignal Class

Source: https://swprocess.readthedocs.io/en/stable/source.html

Contains source position and signal information.

```python
class SourceWithSignal(Source, TimeSeries):
    """Contains source position and signal information."""
    def __init__(self, x, y, z, amp, dt):
        """Create from spatial and signal information."""
        pass
```

--------------------------------

### MaswWorkflowRegistry

Source: https://swprocess.readthedocs.io/en/stable/register.html

Registry for Masw workflows.

```python
class _MaswWorkflowRegistry(
    AbstractRegistry
):
    pass
```

--------------------------------

### WavefieldTransformRegistry

Source: https://swprocess.readthedocs.io/en/stable/register.html

Registry for wavefield transforms.

```python
class _WavefieldTransformRegistry(
    AbstractRegistry
):
    pass
```

--------------------------------

### Sensor1C Initialization

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

Initializes a Sensor1C object with amplitude, time delta, and spatial coordinates.

```python
__init__(_amplitude_ , _dt_ , _x_ , _y_ , _z_ , _nstacks =1_, _delay =0_):
    """Initialize Sensor1C."""
    pass
```

--------------------------------

### Masw.run

Source: https://swprocess.readthedocs.io/en/stable/masw.html

Run an MASW workflow from SU or SEGY files. Create an instance of an Masw object for a specific Masw workflow. Note that each file should contain multiple traces where each trace corresponds to a single receiver. The header information for these files must be correct and readable. Currently supported file types are SEGY and SU.

```python
static _run(_fnames_ , _settings_ , _map_x= <function Masw.<lambda>>_, _map_y= <function Masw.<lambda>>_)
```

--------------------------------

### Interactively select source window boundary

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Interactively select source window boundary.

```python
def interactive_mute(_mute_location ='both'_, _window_kwargs =None_, _waterfall_kwargs =None_):
    """Interactively select source window boundary."""
    pass
```

--------------------------------

### get_all()

Source: https://swprocess.readthedocs.io/en/stable/regex.html

Compile regular expression to identify peaks from a .max file.

```python
get_all(_wavetype ='rayleigh'_, _time ='(\\\d+\\.?\\[d]*)'_){
    
    Compile regular expression to identify peaks from a .max file. 

    Parameters:
        
      * **wavetype** (_{‘rayleigh’, ‘love’, ‘vertical’, ‘radial’, ‘transverse’}, optional_) – Define a specific wavetype to extract, default is ‘rayleigh’.
      * **time** (_str, optional_) – Define a specific time of interest, default is “(d+.?d*)”), a generic regular expression which will match all time.



    Returns:
        
      _Compiled Regular Expression_ – To identify peaks from a .max file. 

```

--------------------------------

### zero_pad Method

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Method to append zeros to sensors to achieve a desired frequency step.

```python
zero_pad(df)
Parameters:
df (float) – Desired linear frequency step in Hertz.
Returns:
None – Instead modifies sensors.
```

--------------------------------

### Initialize an Array1D object from one or more data files

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Initialize an Array1D object from one or more data files. This classmethod creates an Array1D object by reading the header information in the provided file(s). Each file should contain multiple traces where each trace corresponds to a single receiver. Currently supported file types are SEG2 and SU.

```python
@classmethod
def from_files(_fnames_ , _map_x= <function Array1D.<lambda>>_, _map_y= <function Array1D.<lambda>>_, _obspy_read_kwargs=None_):
    """Initialize an Array1D object from one or more data files."""
    pass
```

--------------------------------

### MaswXcorr.run

Source: https://swprocess.readthedocs.io/en/stable/masw.html

Run an MASW workflow from SU or SEGY files. Create an instance of an Masw object for a specific Masw workflow. Note that each file should contain multiple traces where each trace corresponds to a single receiver. The header information for these files must be correct and readable. Currently supported file types are SEGY and SU.

```python
_run(_fnames_rec_ , _fnames_src_ , _src_channel_ , _settings_ , _map_x= <function MaswXcorr.<lambda>>_, _map_y= <function MaswXcorr.<lambda>>_)
```

--------------------------------

### get_spac_ratio()

Source: https://swprocess.readthedocs.io/en/stable/regex.html

TODO (jpv): Finish docstring.

```python
get_spac_ratio(_time ='(-?\\[d]+.?\\[d]*[eE]?[+-]?\\[d]*)'_, _component ='(0)'_, _ring ='(\\\d+)'_){
    
    TODO (jpv): Finish docstring. 

    Parameters:
        
      * **component** (_{“0”, “1”, “2”}, optional_) – Component vertical=”0”, radial=”1”, and transverse=”2” to be read, default is “0”.
      * **ring** (_str_) – Desired ring, default is “d+” so all rings will be exported.



    Returns:
        
      _Compiled regular expression_ – To read lines from SPAC-style .max file. 

```

--------------------------------

### Array1DwSource Classmethod from_files

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Classmethod to initialize an Array1D object from one or more data files.

```python
_classmethod _from_files(fnames_rec, fnames_src, src_channel, map_x=<function Array1DwSource.<lambda>>, map_y=<function Array1DwSource.<lambda>>)
Initialize an Array1D object from one or more data files.
This classmethod creates an Array1D object by reading the header information in the provided file(s). Each file should contain multiple traces where each trace corresponds to a single receiver. Currently supported file types are SEG2 and SU.
Parameters:
fnames (str or iterable) – File name or iterable of file names. If multiple files are provided the traces are stacked.
map_x, map_y (function, optional) – Convert x and y coordinates using some function, default is not transformation. Can be useful for converting between coordinate systems.
obspy_read_kwargs (dict, optional) – Keyword arguments to be passed to the obspy.read().
Returns:
Array1D – Initialized Array1d object.
Raises:
TypeError – If fnames is not of type str or iterable.
```

--------------------------------

### Array1DwSource Class Initialization

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Initialization of the Array1DwSource class, inheriting from Array1D.

```python
_class _Array1DwSource(sensors, source)
Bases: `Array1D`
```

--------------------------------

### Initialize Array1D

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Initialize from an iterable of Sensor1C's and a Source.

```python
def __init__(_sensors_ , _source_):
    """Initialize from an iterable of Sensor1C's and a Source."""
    pass
```

--------------------------------

### Initialize from a SEG2 Trace object

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Initializes an ActiveTimeSeries from a SEG2 Trace object, extracting additional header information.

```python
def _from_trace_seg2(_trace_):
    """Initialize from a SEG2 Trace object."""
    pass
```

--------------------------------

### Create Sensor1C from Trace

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

Class method to create a Sensor1C object from a Trace object, with options for header reading and coordinate mapping.

```python
classmethod _from_trace(_trace_ , _read_header=True_ , _map_x= <function Sensor1C.<lambda>>_, _map_y= <function Sensor1C.<lambda>>_, _nstacks=1_ , _delay=0_ , _x=0_ , _y=0_ , _z=0_ , _format=None_):
    """Create a Sensor1C object from a Trace object."""
    pass
```

--------------------------------

### FK

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

FK transform class.

```python
class FK(_frequencies_ , _velocities_ , _power_):
    Bases: `FDBF` 

    _classmethod _from_array(_array_ , _settings_):
         
```

--------------------------------

### Create Sensor1C from Sensor1C

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

Class method to create a deep copy of an existing Sensor1C object.

```python
classmethod _from_sensor1c(_sensor1c_):
    """Create deep copy of an existing Sensor1C object."""
    pass
```

--------------------------------

### PhaseShift

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

Perform the Phase-Shift Transform.

```python
class PhaseShift(_frequencies_ , _velocities_ , _power_):
    Bases: `AbstractWavefieldTransform` 

    _classmethod _transform(_array_ , _velocities_ , _settings_):
        Perform the Phase-Shift Transform. 

        Parameters:
            
          * **array** (_Array1D_) – Instance of Array1D.
          * **velocities** (_ndarray_) – Vector of trial velocities.
          * **settings** (_dict_) – dict with processing settings.



        Returns:
            
        _tuple_ – Of the form (frequencies, power). 
```

--------------------------------

### Array's sensor positions as list

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Array's sensor positions as list.

```python
def position(_normalize =False_):
    """Array’s sensor positions as list."""
    pass
```

--------------------------------

### Source Class

Source: https://swprocess.readthedocs.io/en/stable/source.html

A Source class for storing information about an active-source.

```python
class Source(object):
    """A Source class for storing information about an active-source."""
    def __init__(self, x, y, z):
        """Initialize a Source class object."""
        pass

    @classmethod
    def from_source(cls, other):
        pass

    @property
    def x(self):
        pass

    @property
    def y(self):
        pass

    @property
    def z(self):
        pass
```

--------------------------------

### ActiveTimeSeries constructor

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Initializes an ActiveTimeSeries object with amplitude, time step, number of stacks, and delay.

```python
def __init__(_amplitude_, _dt_, _nstacks=1, _delay=0_):
    """Initialize an ActiveTimeSeries object."""
    pass
```

--------------------------------

### Create a deep copy of an existing Array1D object

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Create a deep copy of an existing Array1D object.

```python
@classmethod
def from_array1d(_array1d_):
    """Create a deep copy of an existing Array1D object."""
    pass
```

--------------------------------

### Sensor amplitudes as 2D ndarray

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Sensor amplitudes as 2D ndarray.

```python
def timeseriesmatrix(_detrend =False_, _normalize ='none'_):
    """Sensor amplitudes as 2D ndarray."""
    pass
```

--------------------------------

### FDBF

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

Perform Frequency-Domain Beamforming.

```python
class FDBF(_frequencies_ , _velocities_ , _power_):
    Bases: `AbstractWavefieldTransform` 

    _classmethod _transform(_array_ , _velocities_ , _settings_):
        Perform Frequency-Domain Beamforming. 

        Parameters:
            
          * **array** (_Array1D_) – Instance of Array1D.
          * **velocities** (_ndarray_) – Vector of trial velocities.
          * **settings** (_dict_) – dict with processing settings.



        Returns:
            
        _tuple_ – Of the form (frequencies, power). 
```

--------------------------------

### EmptyWavefieldTransform

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

Empty transform method.

```python
class EmptyWavefieldTransform(_frequencies_ , _velocities_ , _power_):
    Bases: `AbstractWavefieldTransform` 

    _classmethod _from_array(_array_ , _settings_):
         

    stack(_other_):
         

    _classmethod _transform(_array_ , _velocities_ , _settings_):
        Empty transform method. 
```

--------------------------------

### AbstractWavefieldTransform

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

Wavefield transformation of an Array1D.

```python
class AbstractWavefieldTransform(_frequencies_ , _velocities_ , _power_):
    Bases: `ABC`
    Wavefield transformation of an Array1D. 

    __init__(_frequencies_ , _velocities_ , _power_):
        Define AbstractWavefieldTransform. 

    find_peak_power(_by ='frequency-maximum'_, _** kwargs_):
        Find maximum WavefieldTransform power. 

        Parameters:
            
          * **by** (_{“frequency-maximum”, “find_peaks”}, optional_) – Determines how the maximum surface wave dispersion power is selected, default is ‘frequency-maximum’. frequency-maximum as the name indicates simply returns the single maximum power point’s velocity at each frequency. find_peaks uses the function by the same name from the scipy package, keyword arguments can be entered as kwargs.
          * **kwargs** (_kwargs, optional_) – Keyword arguments, different for each search method.



        Returns:
            
        _ndarray_ – Containing the peak velocity at each frequency. 

    _classmethod _from_array(_array_ , _settings_):
         

    normalize(_by ='frequency-maximum'_):
        Normalize WavefieldTransform power. 

        Parameters:
            
          **by** (_{“none”, “absolute-maximum”, “frequency-maximum”}, optional_) – Determines how the surface wave dispersion power is normalized, default is ‘frequency-maximum’. 

        Returns:
            
        _None_ – Update the internal state of power. 

    plot(_fig =None_, _ax =None_, _cax =None_, _normalization ='frequency-maximum'_, _peaks ='frequency-maximum'_, _nearfield =None_, _cmap ='jet'_, _peak_kwargs =None_, _colorbar_kwargs =None_, _rasterize =False_):
        Plot the WavefieldTransform’s dispersion image. 

        Parameters:
            
          * **ax** (_Axes, optional_) – Axes object on which to plot the dispersion image, default is None so an Axes will be created on-the-fly.
          * **cax** (_Axes, optional_) – Axes object on which to plot the colorbar for the disperison image, default is None so an Axes will be created from ax.
          * **normalization** (_{“none”, “absolute-maximum”, “frequency-maximum”}, optional_) – Determines how the surface wave dispersion power is normalized, default is ‘frequency-maximum’.
          * **peaks** (_{“none”, “frequency-maximum”}, optional_) – Determines if the spectral peaks are shown and if so how they will be determined, default is ‘frequency-maximum’.
          * **nearfield** (_int, optional_) – Number of array center distances per wavelength following Yoon and Rix (2009), default is None so nearfield criteria will not be plotted. A value of 1 corresponds to ~15% error and 2 ~5% error.
          * **peak_kwargs** (_dict, optional_) – Keyword arguments to control the appearance of the spectral peaks, default is None so the default settings will be used.



        Returns:
            
        _tuple or None_ – tuple of the form (fig, ax) if ax=None, None otherwise. 

    plot_snr(_ax =None_, _plot_kwargs =None_):
         

    _abstract classmethod _transform(_array_ , _velocities_ , _settings_):
        Abstract transform method. 
```

--------------------------------

### Mute traces outside of a narrow signal window

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Mute traces outside of a narrow signal window.

```python
def mute(_signal_start =None_, _signal_end =None_, _window_kwargs =None_):
    """Mute traces outside of a narrow signal window."""
    pass
```

--------------------------------

### Create Sensor1C from ActiveTimeSeries

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

Class method to create a Sensor1C object from an ActiveTimeSeries object.

```python
classmethod _from_activetimeseries(_activetimeseries_ , _x_ , _y_ , _z_):
    pass
```

--------------------------------

### Array1D class definition

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Class definition for Array1D.

```python
class _Array1D(_sensors_ , _source_):
    """A class to organize the information for a 1D (linear) array."""
    pass
```

--------------------------------

### AbstractRegistry.register

Source: https://swprocess.readthedocs.io/en/stable/register.html

Register a virtual subclass of an ABC. Returns the subclass, to allow usage as a class decorator.

```python
@classmethod
def _register(_name_):
    """Register a virtual subclass of an ABC.
    Returns the subclass, to allow usage as a class decorator.
    """
    pass
```

--------------------------------

### SlantStack

Source: https://swprocess.readthedocs.io/en/stable/wavefieldtransforms.html

Perform a slant-stack on the given wavefield data.

```python
class SlantStack(_frequencies_ , _velocities_ , _power_):
    Bases: `AbstractWavefieldTransform` 

    _classmethod _slant_stack(_array_ , _velocities_):
        Perform a slant-stack on the given wavefield data. 

        Parameters:
            
          * **array** (_Array1d_) – One-dimensional array object.
          * **velocities** (_ndarray_) – One-dimensional array of trial velocities.



        Returns:
            
        _tuple_ – Of the form (tau, slant_stack) where tau is an ndarray of the attempted intercept times and slant_stack are the slant-stacked waveforms. 

    _classmethod _transform(_array_ , _velocities_ , _settings_):
        Perform the Slant-Stack transform. 

        Parameters:
            
          * **array** (_Array1D_) – Instance of Array1D.
          
```

--------------------------------

### Sensor1C Properties

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

Properties for accessing the x, y, and z spatial coordinates of the sensor.

```python
property _x:
    pass

property _y:
    pass

property _z:
    pass
```

--------------------------------

### Create ActiveTimeSeries from cross-correlation

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Creates an ActiveTimeSeries by cross-correlating and stacking a second TimeSeries onto a first.

```python
def _from_cross_stack(_a_, _b_):
    """Create ActiveTimeSeries from cross-correlation."""
    pass
```

--------------------------------

### extract_mseed() function signature

Source: https://swprocess.readthedocs.io/en/stable/utils.html

Extract specific time blocks from a set of miniseed files. Reads a large set of miniseed files, trims out specified time block(s), and writes the trimmed block(s) to disk. Useful for condensing a large dataset consisting of miniseed files written at the end of each hour to a single file that spans several hours. Stations which share an array name will appear in a common directory.

```python
extract_mseed(_startend_fname_ , _network_ , _data_dir ='./'_, _output_dir ='./'_, _extension ='mseed'_)
```

--------------------------------

### get_peak_from_max()

Source: https://swprocess.readthedocs.io/en/stable/regex.html

Compile regular expression to extract peaks from a .max file.

```python
get_peak_from_max(_time ='\\[d]+\\.?\\[d]*'_, _frequency ='-?\\[d]+.?\\[d]*[eE]?[+-]?\\[d]*'_, _wavetype ='rayleigh'_){
    
    Compile regular expression to extract peaks from a .max file. 

    Parameters:
        
      * **wavetype** (_{‘rayleigh’, ‘love’, ‘vertical’, ‘radial’, ‘transverse’}, optional_) – Define a specific wavetype to extract, default is ‘rayleigh’.
      * **time** (_str, optional_) – Define a specific time of interest, default is “(d+.?d*)”), a generic regular expression which will match all time.



    Returns:
        
      _Compiled Regular Expression_ – To extract peaks from a .max file. 

```

--------------------------------

### Create ActiveTimeSeries from a Trace object

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Creates an ActiveTimeSeries from a Trace object, without extracting metadata.

```python
def _from_trace(_trace_, _nstacks=1_, _delay=0_):
    """Create ActiveTimeSeries from a Trace object."""
    pass
```

--------------------------------

### xcorrelate Method

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Method for cross-correlation, with optional vmin and vmax parameters.

```python
xcorrelate(vmin=None, vmax=None)
```

--------------------------------

### waterfall Plot Parameters

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Parameters for creating a waterfall plot, including options for axes, detrending, normalization, and scaling.

```python
waterfall(ax=None, time_ax='y', amplitude_detrend=True, amplitude_normalization='each', amplitude_scale=None, position_normalization=False, plot_kwargs=None)
Parameters:
ax (Axes, optional) – Axes on which to plot, default is None indicating a Figure and Axes will be generated on-the-fly.
time_ax ({'x', 'y'}, optional) – Denotes the time axis, ‘y’ is the default.
amplitude_detrend (bool, optional) – Boolean to control whether a linear detrending operation is performed, default is False so no detrending is performed.
amplitude_normalization ({“none”, “each”, “all”}, optional) – Enable different normalizations including: “each” which normalizes each traces by its maximum, “all” which normalizes all traces by the same maximum, and “none” which perform no normalization, default is “each”.
amplitude_scale (float, optional) – Factor by which each trace is multiplied, default is None which uses a factor equal to half the average receiver receiver spacing.
position_normalization (bool, optional) – Determines whether the array positions are shifted such that the first sensor is located at x=0.
plot_kwargs (None, dict, optional) – Kwargs for matplotlib.pyplot.plot to control the style of each trace, default is None.
Returns:
Tuple – Of the form (fig, ax) where fig is the figure object and ax the axes object on which the schematic is plotted, if ax=None.
```

--------------------------------

### to_json Method

Source: https://swprocess.readthedocs.io/en/stable/peaks.html

Writes Peaks data to a JSON file. Allows overwriting or appending to an existing file.

```python
to_json(_fname_ , _append =False_)
    
Write Peaks to json file. 

Parameters:
    
  * **fname** (_str_) – Output file name, can include a relative or the full path. 
  * **append** (_bool, optional_) – Controls whether fname (if it exists) should be appended to or overwritten, default is False indicating fname will be overwritten.


Returns:
    
_None_ – Instead writes file to disk.
```

--------------------------------

### Check if other is similar to self

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Check if other is similar to self.

```python
def is_similar(_other_):
    """Check if other is similar to self."""
    pass
```

--------------------------------

### trim_offsets Method

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Method to remove sensors outside of specified offset ranges.

```python
trim_offsets(min_offset, max_offset)
Parameters:
min_offset, max_offset (float) – Specify the minimum and maximum allowable offset in meters.
Returns:
None – Updates internal attributes.
```

--------------------------------

### Plot a schematic of the Array1D object

Source: https://swprocess.readthedocs.io/en/stable/array1d.html

Plot a schematic of the Array1D object. The schematic shows the position of the receivers and source and lists the total number of receivers and their spacing.

```python
def plot(_ax =None_, _sensor_kwargs =None_, _source_kwargs =None_):
    """Plot a schematic of the Array1D object."""
    pass
```

--------------------------------

### SignaltoNoiseRatio class definition

Source: https://swprocess.readthedocs.io/en/stable/snr.html

The SignaltoNoiseRatio class is defined with its bases and a class method.

```python
class SignaltoNoiseRatio(_frequencies_ , _snr_):
    
    Bases: object 

    classmethod from_array1ds(_signal_ , _noise_ , _fmin =3_, _fmax =75_, _pad_snr =False_, _df_snr =None_):
        
```

--------------------------------

### Stack a new timeseries onto the current one

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Appends and averages a new timeseries onto the current ActiveTimeSeries object.

```python
def stack_append(_timeseries_):
    """Stack (i.e., average) a new timeseries onto the current one."""
    pass
```

--------------------------------

### Sensor1C Class Definition

Source: https://swprocess.readthedocs.io/en/stable/sensor1c.html

The Sensor1C class is a base class for single-component sensor objects, inheriting from ActiveTimeSeries.

```python
class _Sensor1C(_amplitude_ , _dt_ , _x_ , _y_ , _z_ , _nstacks =1_, _delay =0_):
    """Bases: `ActiveTimeSeries`
    Class for single component sensor objects. """
    pass
```

--------------------------------

### Shift b for maximal correlation with a

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Shifts a second ActiveTimeSeries object (b) so that it is maximally correlated with a first ActiveTimeSeries object (a).

```python
def _crosscorr_shift(_a_, _b_, _exclude=None_):
    """Shift b so that it is maximally corrlated with a."""
    pass
```

--------------------------------

### Time vector for ActiveTimeSeries

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Property to access the time vector for the ActiveTimeSeries.

```python
def _time(self):
    """Time vector for ActiveTimeSeries."""
    pass
```

--------------------------------

### ActiveTimeSeries class definition

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

The definition of the ActiveTimeSeries class, inheriting from TimeSeries.

```python
class ActiveTimeSeries(TimeSeries):
    """A class for working with active-source TimeSeries."""
    pass
```

--------------------------------

### Cross-correlation of two ActiveTimeSeries objects

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Calculates the cross-correlation between two ActiveTimeSeries objects.

```python
def _crosscorr(_a_, _b_, _correlate_kwargs=None_, _exclude='nsamples'_):
    """Cross correlation of two ActiveTimeSeries objects."""
    pass
```

--------------------------------

### Trim ActiveTimeSeries

Source: https://swprocess.readthedocs.io/en/stable/activetimeseries.html

Trims the ActiveTimeSeries within a specified time interval.

```python
def trim(_start_time_, _end_time_):
    """Trim in the interval [start_time, end_time]."""
    pass
```
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