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+# Differential Amplifier for mV/V Instrumentation
+
+## Overview
+
+This project showcases the design and calibration of a differential amplifier for mV/V instrumentation, such as load cells. The amplifier provides a gain of approximately 100 and shifts the output so that 2.5V corresponds to 0 differential voltage. This configuration makes it compatible with analog-to-digital converters (ADCs) that have an input range of 0 to 5V, such as those used in Arduino.
+
+## Key Features
+
+- **High Gain**: The amplifier provides a gain of around 100, making it suitable for millivolt-range signals from load cells and other precision sensors.
+- **Offset Shifting**: Shifts the output to 2.5V when the differential input voltage is 0, allowing for full utilization of ADCs with a 0-5V range.
+- **Calibration via Analog Discovery 3**: Uses the Analog Discovery 3's signal generator and scope to calibrate the amplifier across a range of input voltages.
+
+## Calibration Process
+
+The calibration of the amplifier is automated using the Analog Discovery 3 and Python. Here's how the calibration is carried out:
+
+### 1. **Signal Injection**
+
+- The Analog Discovery 3 generates small differential voltages to simulate the load cell signals, sweeping from -20mV to +20mV in custom increments (e.g., 0.5mV steps).
+- It logs the generated input signal and the amplifier's output using its own scope.
+
+### 2. **Sampling and Logging**
+
+- Over a 1-second period, the system samples both the input signal and the amplifier's output.
+- It calculates the average value of each during this period.
+
+### 3. **Multiple Sweeps**
+
+- The system performs multiple sweeps through the input range (e.g., -20mV to +20mV), repeating this process for a specified number of loops to ensure consistent data.
+
+### 4. **Linear Regression and Analysis**
+
+- Once the data is collected, Python performs a linear regression on each sweep to calculate:
+  - **Average Amplification**: The gain of the amplifier.
+  - **Offset**: Any static offset in the output.
+- The results include both the average amplification and offset, along with their uncertainties, providing a thorough calibration of the system.
+
+## Python Script Overview
+
+The Python script used for calibration automates the process of sweeping, logging, and analyzing data from the Analog Discovery 3. Key functions include:
+
+- **Signal Generation**: Customizable step sizes, voltage range, and number of sweeps.
+- **Data Collection**: Logs both input and output voltages during each sweep.
+- **Linear Regression**: Fits a line to the data for each sweep to calculate the amplifier's gain and offset.
+- **Uncertainty Analysis**: Reports uncertainties in both the amplification and offset.
+
+### Example Workflow:
+
+1. **Run the script** to initiate the calibration process.
+2. **Set the input sweep parameters**: range, step size, and number of loops.
+3. **Log the data**: Input and output values are sampled and averaged.
+4. **Perform regression**: Python analyzes the data, calculates gain and offset, and reports results with uncertainties.