period Module¶
- average_rectified_sections(data)¶
Returns a slice of an oscillating data vector based on the max and min of the mean of the sections created by retifiying the data.
- Parameters:
- datandarray, shape(n,)
- Returns:
- datandarray, shape(m,)
A slice where m is typically less than n.
Notes
This is a function to try to handle the fact that some of the data from the torsional pendulum had a beating like phenomena and we only want to select a section of the data that doesn’t seem to exhibit the phenomena.
- calc_periods_for_files(directory, filenames, forkIsSplit)¶
Calculates the period for all filenames in directory.
- Parameters:
- directorystring
This is the path to the RawData directory.
- filenameslist
List of all the mat file names in the RawData directory.
- forkIsSplitboolean
True if the fork is broken into a handlebar and fork and false if the fork and handlebar was measured together.
- Returns:
- periodsdictionary
Contains all the periods for the mat files in the RawData directory.
- check_for_period(mp, forkIsSplit)¶
Returns whether the fork is split into two pieces and whether the period calculations need to happen again.
- Parameters:
- mpdictionary
Dictionary the measured parameters.
- forkIsSplitboolean
True if the fork is broken into a handlebar and fork and false if the fork and handlebar was measured together.
- Returns:
- forcePeriodCalcboolean
True if there wasn’t enough period data in mp, false if there was.
- forkIsSplitboolean
True if the fork is broken into a handlebar and fork and false if the fork and handlebar was measured together.
- fit_goodness(ym, yp)¶
Calculate the goodness of fit.
- Parameters:
- ymndarray, shape(n,)
The vector of measured values.
- ypndarry, shape(n,)
The vector of predicted values.
- Returns:
- rsqfloat
The r squared value of the fit.
- SSEfloat
The error sum of squares.
- SSTfloat
The total sum of squares.
- SSRfloat
The regression sum of squares.
- get_period(data, sample_rate_or_time, pathToPlotFile)¶
Returns the period and uncertainty for data resembling a decaying oscillation.
- Parameters:
- dataarray_like, shape(n,)
A time series that resembles a decaying oscillation.
- sample_rate_or_timeint or array_like, shape(n,)
Either the frequency in Hertz that data was sampled at or a time array that corresponds to
data.- pathToPlotFilestring
A path to the file to print the plots.
- Returns:
- Tufloat
The period of oscillation and its uncertainty.
- get_period_from_truncated(data, sampleRate, pathToPlotFile)¶
- get_period_key(matData, forkIsSplit)¶
Returns a dictionary key for the period entries.
- Parameters:
- matDatadictionary
The data imported from a pendulum mat file.
- forkIsSplitboolean
True if the fork is broken into a handlebar and fork and false if the fork and handlebar was measured together.
- Returns:
- keystring
A key of the form ‘T[pendulum][part][orientation]’. For example, if it is the frame that was hung as a torsional pendulum at the second orientation angle then the key would be ‘TtB2’.
- get_sample_rate(matData)¶
Returns the sample rate for the data.
- jac_fitfunc(p, t)¶
Calculate the Jacobian of a decaying oscillation function.
Uses the analytical formulations of the partial derivatives.
- Parameters:
- pthe five parameters of the equation
- ttime vector
- Returns:
- jacThe jacobian, the partial of the vector function with respect to the
- parameters vector. A 5 x N matrix where N is the number of time steps.
- make_guess(data, sampleRate)¶
Returns a decent starting point for fitting the decaying oscillation function.
- plot_osfit(t, ym, yf, p, rsq, T, m=None, fig=None)¶
Plot fitted data over the measured
- Parameters:
- tndarray (n,)
Measurement time in seconds
- ymndarray (n,)
The measured voltage
- yfndarray (n,)
- pndarray (5,)
The fit parameters for the decaying oscillation function.
- rsqfloat
The r squared value of y (the fit)
- Tfloat
The period
- mfloat
The maximum value to plot
- Returns:
- figthe figure
- select_good_data(data, percent)¶
Returns a slice of the data from the index at maximum value to the index at a percent of the maximum value.
- Parameters:
- datandarray, shape(n,)
This should be a decaying function.
- percentfloat
The percent of the maximum to clip.
- This basically snips of the beginning and end of the data so that the super
- damped tails are gone and also any weirdness at the beginning.