Documentation and Examples for Jupyter Notebooks:

2.3.3. Jupyter Lab — Red Pitaya 2.00-30 documentation

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redpitaya.readthedocs.io

Jupyter Notebooks file:

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()