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API Reference

class physerror.Data(user_x_data: ~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]] | ~numpy._typing._nested_sequence._NestedSequence[~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]]] | bool | int | float | complex | str | bytes | ~numpy._typing._nested_sequence._NestedSequence[bool | int | float | complex | str | bytes] = , user_y_data: ~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]] | ~numpy._typing._nested_sequence._NestedSequence[~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]]] | bool | int | float | complex | str | bytes | ~numpy._typing._nested_sequence._NestedSequence[bool | int | float | complex | str | bytes] = , data_type: str = )

An initializer and container dataclass that is initialized and reused by the user and other classes, as well as their methods. There are many attributes that calculate common statistical errors, constants, and general error propagation methods, and two class methods.

delta

[]

  • Type: float

A

[]

  • Type: float

B

[]

  • Type: float

x_mean

[]

  • Type: float

x_best

[]

  • Type: float

y_mean

[]

  • Type: float

y_best

[]

  • Type: float

sigma_y

[]

  • Type: float

sigma_A

[]

  • Type: float

sigma_B

[]

  • Type: float

sigma_x

[]

  • Type: float

sigma_x_best

[]

  • Type: float

sigma_y_best

[]

  • Type: float

sigma_x_mean

[]

  • Type: float

sigma_y_mean

[]

  • Type: float

sigma_frac

[]

  • Type: float

  • Parameters:

    • user_x_data (ArrayLike = [1, 2, 3, 4, 5]) – []
    • user_y_data (ArrayLike = [1, 2, 3, 4, 5]) – []
    • data_type (str = 'manual') – []

NOTE

Will update this soon-ish

export()

Exports error analysis calculations to either an Excel workbook or JSON file based on user’s choice.

outlier()

A method that creates two empty arrays then searches the cls.x_data and cls.y_data arrays for values that are outside the standard 2 * sigma outlier “limit”.

  • Returns:
    • np.ndarray – An array that contains either the outliers that were found in the user’s x_data, or a string stating no outliers were found.
    • np.ndarray – An array that contains either the outliers that were found in the user’s y_data, or a string stating no outliers were found.

class physerror.FileReaders

Container class for methods that read in and parse data files.

csvreader()

Reads in a csv file selected via a tkinter file explorer window. Assumes there is no index column. Data should be organized into columns rather than rows.

  • Returns:
    • ndarray – A NumPy array containing the data in the leftmost column of the passed in data file.
    • ndarray – A NumPy array containing the data in the second column of the passed in data file.

excelreader()

Reads in an Excel Workbook selected via a tkinter file explorer window. Assumes there is no index column. Data should be organized into columns rather than rows.

  • Returns:
    • ndarray – A NumPy array containing the data in the leftmost column of the passed in data file.
    • ndarray – A NumPy array containing the data in the second column of the passed in data file.

class physerror.Graphs

Allows the user to create various graphs from the user_data pulled from Data.

graph_title

String used as the title for any graphing function that is run. Defaults to “Graph”.

  • Type: str = “Graph”

title_size

Numerical value used as the title font size for any graphing function that is run. Defaults to 11.

  • Type: int = 11 | float

x_label

String used as the x-axis label for any graphing function with points that is run. Defaults to “x label”

  • Type: str = “x label”

y_label

String used as the y-axis label for any graphing function with points that is run. Defaults to “y label”.

  • Type: str = “y label”

p_color

Either a single string, list, or ArrayLike of strings that is used to color the points in any graphing function with points that is run. Defaults to “cyan”.

  • Type: str = “cyan” | list[str] | ArrayLike[str]

line_color

A string used to color the line in the linreg and resid functions. Defaults to “black”.

  • Type: str = “black”

errbar_color

A string used to color the error bars in the errbargraph function. Defaults to “red”.

  • Type: str = “red”

dist_check

A string used to determine if the datahist function will generate normal distrbution histograms. Only accepts “Yes” and “No”, and defaults to “No”.

  • Type: str = “Yes” | “No”

dataset_check

An integer used to determine how many datasets will be generated from the datahist function. Only accepts 1 and 2, and defaults to 1.

  • Type: int = 1 | 2

hist_color

Either a single string, list, or ArrayLike of strings to determine the color of the the histogram(s) from the datahist function. Defaults to “green”.

  • Type: str = “green” | list[str] | ArrayLike[str]

dbl_pend_line

A string used to change the color of specifically the double pendulum function’s line color. Defaults to “lime”.

  • Type: str = “lime”

dbl_pend_trace

A string used to change the color of specifically the double pendulum function’s trace line color. Defaults to “black”.

  • Type: str = “black”

datahist(user_data: Data)

Generates a histogram of one or two sets of data pulled from the Data class using pandas’ DataFrame.hist method.

  • Parameters: user_data (Data) – Requires the user to pass in an instance of Data to make use of the user’s data.

dbl_pend(theta_0: float, phi_0: float, theta_dot_0=0, phi_dot_0=0, anim_type=0)

Generates either a point mass or bar mass double pendulum animation based on the pass in initial values. Angles are read as the angle between the bar/string and an imaginary horizontal line going through the point.

Point mass calculations and animation code were taken from matplotlib’s documentation: https://matplotlib.org/stable/gallery/animation/double_pendulum.html

  • Parameters:
    • theta_0 (float) – Initial angle of the top bar/string.
    • phi_0 (float) – Initial angle of the bottom bar/string.
    • theta_dot_0 (int = 0 *(*optional )) – Initial velocity of the top bar/string. Defaults to 0.
    • phi_dot_0 (int = 0 *(*optional )) – Initial velocity of the bottom bar/string. Defaults to 0.
    • anim_type (int = 0 | 1 *(*optional )) – Optional variable that determines the type of double pendulum that will be used. Defaults to 0 for Point Mass, accepts 1 for Bar Mass.

errbargraph(user_data: Data)

Uses the x data and y data from Data to create a point-based with error bars on each point. Error size is the sigma_x value calculated in Data.

  • Parameters: user_data (Data) – Requires the user to pass in an instance of Data to make use of the user’s data.

linreg(user_data: Data)

Uses the given x_data and y_data arrays to create a linear regression plot.

  • Parameters: user_data (Data) – Requires the user to pass in an instance of Data to make use of the user’s data.

resid(user_data: Data)

Uses user_data._df to create a residuals scatter plot via the seaborn sns.residplot method. The graph’s title can optionally be customized.

  • Parameters: user_data (Data) – Requires the user to pass in an instance of Data to make use of the user’s data.

sctrplot(user_data: Data)

Uses the given x_data and y_data to create a scatter plot via matplot.pyplot’s scatter method. Customization options are available, similar to the original pyplot method.

  • Parameters: user_data (Data) – Requires the user to pass in an instance of Data to make use of the user’s data.