Moku:Pro can be configured to save high resolution data at a rate of 5 GSa/s with certain channel configuration settings. Details on how to configure these settings can be found in this knowledge base.

When high resolution data files are downloaded, the data format is in 5 columns, where column 1 is time and columns 2-5 are 1.25 GSa/s data arrays. The four data columns should be interleaved to form the single 5 GSa/s data array. Since each row has a 800 ps timespan, the time vector should be interpolated for each data column in 200 ps increments (i.e. If the first row of the time column is 0 ps, then Column 1 time = 0 ps, Column 2 time = 0 ps + 200 ps, Column 3 time = 0 ps + 400 ps, Column 4 time = 0 + 600 ps). An example of how the data gets reshaped is shown in the following two tables:

Table 1: Raw high resolution output data

Table 2: Reshaped high resolution output data

Examples of how to reshape and plot downloaded high resolution data files in Python and MATLAB are below:

Python:

import numpy as np
import matplotlib.pyplot as plt

# Load the structured array
data = np.load('high_res_data.npy')  # Change to your .npy filename

# Convert to regular ndarray
if data.dtype.names:
    data = np.vstack([data[name] for name in data.dtype.names]).T

# Extract time and signal channels
time = data[:, 0]          # First column = time
signals = data[:, 1:5]     # Remaining 4 columns = signal channels

# Interleave signals row-wise (4 x N) → 1 x (4N)
data_reshaped = signals.T.reshape(-1)

# Apply 200 ps offsets across columns
offsets = np.array([0, 200e-12, 400e-12, 600e-12])
time_offsets = time[:, np.newaxis] + offsets       # shape (N, 4)
time_interleaved = time_offsets.T.reshape(-1)      # shape (4N, )

# Sort by time
sorted_indices = np.argsort(time_interleaved)
time_sorted = time_interleaved[sorted_indices]
data_sorted = data_reshaped[sorted_indices]

# Plot
plt.figure(figsize=(10, 4))
plt.plot(time_sorted, data_sorted)

plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.grid(True)
plt.tight_layout()
plt.show()

MATLAB:

load('high_res_data.mat');  % Change to your .mat filename
data = moku.data;
time = data(:, 1);       % Time column
signals = data(:, 2:5);  % Extract the 4 data columns

% Interleave signals row-wise (4 x N) -> 1 x (4*N)
data_reshaped = reshape(signals.', 1, []);        

% Define 200 ps offset pattern for each column (same for every row)
offsets = [0, 200e-12, 400e-12, 600e-12];  % seconds

time_offsets_matrix = time + offsets;         % size: N x 4
time_interleaved = reshape(time_offsets_matrix.', [], 1);  % (4*N x 1)

% Plot
figure
plot(time_interleaved, data_reshaped);
xlabel('Time (s)');
ylabel('Amplitude');