labtex 0.4.0

Lab report data analysis and LaTeX file generation

labtex

Purpose

This package provides a single solution to repetitive analysis tasks in a lab environment. If you are doing error propagation, linear regression or LaTeX tables/figures manually, this package automates the process.

Features

• Measurement and MeasurementList classes with automatic:
  • Error propagation
  • Printing to correct significant figures
  • Unit parsing, propagation and conversion
• Linear regression
• Automatic table generation in three styles
• Automatic plot generation with matplotlib
• Template LaTeX file output with the generated figures and tables included

Installation

Using pip or pip3 the latest release can be installed with

pip3 install labtex

Usage

For ease of use, you can import the package into your file's global namespace with

from labtex import *

The rest of this section will assume the package is imported in this way. Alternatively do import labtex as lt.

Single measurements can be instantiated with Measurement(value,uncertainty,unit) where unit is a string that will be parsed.

x = Measurement(1.1,0.3,"m")
y = Measurement(2.22,0.4,"m")
z = M(314,10,"V")

where M is an equivalent shorthand for Measurement. Note that the unit parsing supports all combinations of common units, prefixes and powers of units, eg. any of "nm^2", "C^-1", "kg m^2 s^-2", "J^3" etc. are supported.

Measurement instances support all operations (+-*/ and **) as well as math functions with the error and units automatically propagated. Some examples are shown below.

print(x)
# 1.1 ± 0.3 m

print(x + y)
# 3.3 ± 0.5 m

print(x * z)
# (35 ± 9) × 10^{1} V m

print(x ** 2)
# 1.2 ± 0.7 m^2

print(Measurement.tan(x / y))
# 0.5 ± 0.2  

Notice also that Measurements are rounded to the significant figures as dictated by the uncertainty.

For a list of measurements, the MeasurementList class functions identically to the Measurement class, only now taking a list of values. The uncertainty can be a list or a single value for all measurements.

heights = MeasurementList([185,183,182,194,184,177],5,"cm")

print(heights)
# [185 ± 5, 183 ± 5, 182 ± 5, 194 ± 5, 184 ± 5, 177 ± 5] cm

print(200 - heights)
# [15 ± 5, 17 ± 5, 18 ± 5, 6 ± 5, 16 ± 5, 23 ± 5] cm

MeasurementLists also support all operations (+-*/ and **) with themselves and with Measurements.

With two MeasurementList instances, they can be linearly regressed with the LinearRegression class.

voltages = MeasurementList([1.3,3,5,7,8.5,10],1,"V")
temperatures = MeasurementList([23,55,67,82,88,96],[5,3,7,10,5,6],"C")

lobf = LinearRegression(voltages,temperatures)

print(lobf)
# m = 7 ± 1 V^{-1} C
# c = 27 ± 7 C

Observe that printing all Measurement and MeasurementList instances rounds the value to the largest significant figure of the error, as is convention.

For LaTeX template file output, the Document class can be used. Argument names are not required, they are shown here only for demonstration.

doc = Document(title="Lab Report Template",author="CianLM")

Once doc has been instantiated, tables and graphs may be added to the document with their respective methods. Once again argument names are for demonstration and most are optional anyway.

doc.table(
    nameandsymbol = ["Voltage, V","Temperature, T"],
    data = [voltages,temperatures],
    caption = "Voltage and Temperature Correlation"
)

This inserts the following into the doc instance.

\begin{table}[ht]
    \centering
    \caption{Voltage and Temperature Correlation}
    \label{tab:1}
    \begin{tabular}{c|cccccc}
        \toprule
            Voltage, V, ($\pm 1$ V) & 1 & 3 & 5 & 7 & 8 & 10 \\ 
            Temperature, T& $23 \pm 5 $ & $55 \pm 3 $ & $67 \pm 7 $ & $(8 \pm 1) \times 10^{1} $ & $88 \pm 5 $ & $96 \pm 6 $ \\ 
        \bottomrule
    \end{tabular}
\end{table}

which results in

Alternatively if an upright table is preferred, this may be specified through the style argument.

doc.table(
    nameandsymbol = ["Voltage, V", "Temperature, T"],
    data = [voltages,temperatures**2],
    caption = "Voltage and Temperature Sqaured Correlation",
    style = "upright"
)

Once again this inserts the following into the doc instance.

\begin{table}[ht]
    \centering
    \caption{Voltage and Temperature Sqaured Correlation}
    \label{tab:2}
    \begin{tabular}{*{2}c}
        \toprule
        Voltage, V, ($\pm 1$ V)  & Temperature, T \\ 
            \midrule
              1 & $(5 \pm 2) \times 10^{2} $  \\
              3 & $(30 \pm 3) \times 10^{2} $  \\
              5 & $(45 \pm 9) \times 10^{2} $  \\
              7 & $(7 \pm 2) \times 10^{3} $  \\
              8 & $(77 \pm 9) \times 10^{2} $  \\
              10& $(9 \pm 1) \times 10^{3} $ \\
        \bottomrule
    \end{tabular}
\end{table}

which results in

For a graph, a similar process occurs.

doc.graph(
    data = [voltages,temperatures],
    title = "Voltage Temperature Correlation",
    xnameandsymbol = "Voltage, V",
    ynameandsymbol = "Temperature, T",
    caption = "Linear Regression of Voltage and Temperature"
)
# labtex: Wrote to 'figures/graph1.png'.

This generates the graph below and saves it to figures/graph1.png. If you want your graphs elsewhere than figures/, you may change Document.graphfolder at your convenience.

Once you have added all your tables and graphs to the doc object, you may save this file as shown below. The default write directory is tex/ relative to root. This directory is also customisable with Document.texfolder.

doc.save("test")
# labtex: Wrote to 'tex/test.tex'.

Contributions

This package is under active development. Feel free to submit a pull request or reach out with feature suggestions.