🔬

Generate, acquire and plot a signal in Jupyter Notebooks

Documentation and Examples for Jupyter Notebooks:

2.3.3. Jupyter Lab — Red Pitaya 2.00-30 documentation
JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. A modular design invites extensions to expand and enrich functionality.
2.3.3. Jupyter Lab — Red Pitaya 2.00-30 documentation
https://redpitaya.readthedocs.io/en/latest/appsFeatures/remoteControl/jupyter/Jupyter.html

Jupyter Notebooks file:

💡
When you have opened the Jupyter notebook app, drag the .ipynb file into the window.
 

Code Explanation

import time
import numpy as np
from matplotlib import pyplot as plt
from rp_overlay import overlay
import rp
  • Imports: The code starts by importing necessary libraries. time for sleep functions, numpy for numerical operations, matplotlib.pyplot for plotting the acquired signals, and rp for interfacing with the Red Pitaya hardware.
# Initialize Red Pitaya overlay
fpga = overlay()
rp.rp_Init()
  • Initialization: Initializes the Red Pitaya overlay and the Red Pitaya library to set up the device for signal generation and acquisition.
# Constants for the experiment
frequency = 1000  # Hz
ampl = 1          # Amplitude
N = 16384         # Number of samples for acquisition
dec = rp.RP_DEC_128  # Decimation
sampling_rate = 125e6 / dec  # Adjusted for decimation
  • Constants: Defines constants used in the experiment:
    • frequency: The frequency of the generated sine wave signal.
    • ampl: The amplitude of the generated signal.
    • N: The number of samples to acquire.
    • dec: Decimation factor for reducing the sampling rate.
    • sampling_rate: Calculated sampling rate based on the decimation factor.
# Acquisition settings
trig_lvl = 0.5
trig_dly = 0
acq_trig_sour = rp.RP_TRIG_SRC_AWG_PE
  • Acquisition Settings: Defines the settings for the acquisition process:
    • trig_lvl: Trigger level voltage.
    • trig_dly: Trigger delay.
    • acq_trig_sour: Trigger source set to the Arbitrary Waveform Generator (AWG).
###### Generation #####
rp.rp_GenReset()
rp.rp_AcqReset()
print(f"Generating {frequency} Hz signal")
rp.rp_GenWaveform(rp.RP_CH_1, rp.RP_WAVEFORM_SINE)
rp.rp_GenFreqDirect(rp.RP_CH_1, frequency)
rp.rp_GenAmp(rp.RP_CH_1, ampl)
rp.rp_GenOutEnable(rp.RP_CH_1)
rp.rp_GenTriggerOnly(rp.RP_CH_1)
  • Signal Generation:
    • Resets the signal generator and acquisition settings.
    • Configures the signal generator to produce a sine wave at the specified frequency and amplitude.
    • Enables the output channel and triggers the signal generation.
##### Acquisition #####
rp.rp_AcqSetDecimation(dec)
rp.rp_AcqSetTriggerLevel(rp.RP_T_CH_1, trig_lvl)
rp.rp_AcqSetTriggerDelay(trig_dly)
rp.rp_AcqSetGain(rp.RP_CH_2, rp.RP_HIGH)
rp.rp_AcqStart()
rp.rp_AcqSetTriggerSrc(acq_trig_sour)
  • Acquisition Configuration:
    • Sets the decimation factor to reduce the sampling rate.
    • Configures the trigger level and delay.
    • Sets the gain for the acquisition channel.
    • Starts the acquisition process and sets the trigger source.
time.sleep(1)  # Wait to ensure acquisition is ready
rp.rp_GenTriggerOnly(rp.RP_CH_1)  # Trigger generation
  • Wait and Trigger:
    • Waits for 1 second to ensure the acquisition system is ready.
    • Triggers the signal generation.
# Wait for acquisition trigger
while rp.rp_AcqGetTriggerState()[1] != rp.RP_TRIG_STATE_TRIGGERED:
    pass

# Wait until buffer is full
while not rp.rp_AcqGetBufferFillState()[1]:
    pass
  • Wait for Acquisition:
    • Waits until the acquisition system is triggered.
    • Waits until the acquisition buffer is full.
### Get data ###
fbuff_ch1 = rp.fBuffer(N)
rp.rp_AcqGetOldestDataV(rp.RP_CH_1, N, fbuff_ch1)
fbuff_ch2 = rp.fBuffer(N)
rp.rp_AcqGetOldestDataV(rp.RP_CH_2, N, fbuff_ch2)

# Convert the buffer data to numpy arrays
data_V_ch1 = np.array([fbuff_ch1[i] for i in range(N)])
data_V_ch2 = np.array([fbuff_ch2[i] for i in range(N)])
  • Data Acquisition:
    • Allocates buffers to store the acquired data.
    • Retrieves the oldest data from both input (CH_1) and output (CH_2) channels.
    • Converts the buffer data to numpy arrays for further processing or plotting.
# Plotting the signals
plt.figure(figsize=(10, 5))
plt.plot(data_V_ch1, label='Input Signal (Vin)')
plt.plot(data_V_ch2, label='Output Signal (Vout)')
plt.title(f'Signals at {frequency} Hz')
plt.xlabel('Sample Number')
plt.ylabel('Voltage (V)')
plt.legend()
plt.grid(True)
plt.show()
  • Plotting:
    • Plots the acquired input and output signals.
    • Labels the plots and adds a legend for clarity.
    • Displays the plot using plt.show().
# Release resources
rp.rp_Release()
  • Resource Release: Releases the resources used by the Red Pitaya to ensure proper cleanup after the experiment.
This code generates a sine wave signal, acquires the input and output signals, and plots them for visualization. It is a basic template that can be expanded or modified for more complex experiments.
import time
import numpy as np
from matplotlib import pyplot as plt
from rp_overlay import overlay
import rp

# Initialize Red Pitaya overlay
fpga = overlay()
rp.rp_Init()

# Constants for the experiment
frequency = 1000  # Hz
ampl = 1          # Amplitude
N = 16384         # Number of samples for acquisition
dec = rp.RP_DEC_128  # Decimation
sampling_rate = 125e6 / dec  # Adjusted for decimation

# Acquisition settings
trig_lvl = 0.5
trig_dly = 0
acq_trig_sour = rp.RP_TRIG_SRC_AWG_PE

###### Generation #####
rp.rp_GenReset()
rp.rp_AcqReset()
print(f"Generating {frequency} Hz signal")
rp.rp_GenWaveform(rp.RP_CH_1, rp.RP_WAVEFORM_SINE)
rp.rp_GenFreqDirect(rp.RP_CH_1, frequency)
rp.rp_GenAmp(rp.RP_CH_1, ampl)
rp.rp_GenOutEnable(rp.RP_CH_1)
rp.rp_GenTriggerOnly(rp.RP_CH_1)

##### Acquisition #####
rp.rp_AcqSetDecimation(dec)
rp.rp_AcqSetTriggerLevel(rp.RP_T_CH_1, trig_lvl)
rp.rp_AcqSetTriggerDelay(trig_dly)
rp.rp_AcqSetGain(rp.RP_CH_2, rp.RP_HIGH)
rp.rp_AcqStart()
rp.rp_AcqSetTriggerSrc(acq_trig_sour)

time.sleep(1)  # Wait to ensure acquisition is ready
rp.rp_GenTriggerOnly(rp.RP_CH_1)  # Trigger generation

# Wait for acquisition trigger
while rp.rp_AcqGetTriggerState()[1] != rp.RP_TRIG_STATE_TRIGGERED:
    pass

# Wait until buffer is full
while not rp.rp_AcqGetBufferFillState()[1]:
    pass

### Get data ###
fbuff_ch1 = rp.fBuffer(N)
rp.rp_AcqGetOldestDataV(rp.RP_CH_1, N, fbuff_ch1)
fbuff_ch2 = rp.fBuffer(N)
rp.rp_AcqGetOldestDataV(rp.RP_CH_2, N, fbuff_ch2)

# Convert the buffer data to numpy arrays
data_V_ch1 = np.array([fbuff_ch1[i] for i in range(N)])
data_V_ch2 = np.array([fbuff_ch2[i] for i in range(N)])

# Plotting the signals
plt.figure(figsize=(10, 5))
plt.plot(data_V_ch1, label='Input Signal (Vin)')
plt.plot(data_V_ch2, label='Output Signal (Vout)')
plt.title(f'Signals at {frequency} Hz')
plt.xlabel('Sample Number')
plt.ylabel('Voltage (V)')
plt.legend()
plt.grid(True)
plt.show()

# Release resources
rp.rp_Release()