Log and download .li file

To stream to a file (log and convert within a single script) instead of logging to a file, please refer to this article:

API streaming and stream_to_file | Python

First, start a logging session and download your file. For more detailed information on the API's please visit our API Reference:

Datalogger | API Reference       download_file       Datalogger Examples for Python

# moku example: Basic Datalogger
# (c) 2025 Liquid Instruments Pty. Ltd.
import os
import time
from moku.instruments import Datalogger

# Connect to your Moku
i = Datalogger('192.168.###.###', force_connect=False)
try:
    # Set-up the Datalogger
    i.set_samplerate(100)
    i.set_acquisition_mode(mode='Precision')
    i.generate_waveform(channel=1, type='Sine', amplitude=1, frequency=10e3)

    # Start a logging session
    logFile = i.start_logging(duration=10)

    # Track progress percentage of the data logging session
    complete = False
    while complete is False:
        time.sleep(0.5)
        progress = i.logging_progress()
        complete = progress['complete']
        if 'time_remaining' in progress:
            print(f"Remaining time {progress['time_remaining']} seconds")

    # Download the .li log from Moku
    i.download(logFile['location'], logFile['file_name'],
               os.path.join(os.getcwd(), logFile['file_name']))
    print(f"Downloaded log file to local directory. {logFile['file_name']}")

except Exception as e:
    print(f'Exception occurred: {e}')
finally:
    # Close the connection to the Moku device
    i.relinquish_ownership()

Example output:

{'sample_rate': 100.0}
{'mode': 'Precision'}
{'amplitude': 1.0, 'frequency': 10000.0, 'offset': 0.0, 'phase': 0.0, 'type': 'Sine'}
...
Remaining time 0 seconds
Downloaded log file to local directory. MokuDataLoggerData_20250116_102402.li

Mokucli method

Ensure you have mokucli installed, you can download it from the Utilities page.

From your command line, you can convert to your desired file type; csv, npy, mat, or hdf5. We'll be converting to csv for this example. Change directories to where the file is located or use the full file path:

C:\Users\user\Downloads>mokucli convert MokuDataLoggerData_20250116_102402.li --format=csv
[===========================================================================]
Done.

Another method would be to call mokucli from within the script, ideally in this use case, streaming and stream_to_file would be used, see this article: 

API streaming and stream_to_file | Python

Calling mokucli from within the script is not best practice, but it is available as an option:

import subprocess
sp = subprocess.run(f'mokucli convert --format=csv {logFile['file_name']}', capture_output=True, text=True)
print(sp.stdout)
file_name = logFile['file_name'][:-2] + 'csv'

LI File Converter method

Alternatively, you can convert the file using the LI File Converter GUI, this can be accessed from the Moku: App or downloaded from the Utilities page

You can choose the file type, then drag and drop the file to the converter, or open the file from the converter using “File | Open file” or "Ctrl/Cmd + O"

Loading data from file

You can then use the converted file to load and analyze your data.

import os
import csv
import numpy as np
import matplotlib.pyplot as plt

file_name = "MokuDataLoggerData_20250116_102402.csv"
channels = 2
print(file_name)

assert os.path.isfile(file_name), "Streaming failed, no file received"
data = {'time':[], 'ch1':[]}
with open(file_name, 'r') as f:
    load = csv.reader(f)
    file = np.array([[float(row[0])] + [float(row[i]) for i in range(1, channels+1)] for row in load if row[0][0] != '%'])
    f.close()
data['time'] = file[:,0]
for i in range(1, channels+1):
    data[f'ch{i}'] = file[:,i]

keys = data.keys()
for key in keys:
    print(f"'{key}': {str(data[key][:3])[:-1]} ... {data[key][-1]}]")

fig = plt.figure(figsize=(10, 3))
for i in range(1, channels+1):
    plt.plot(data['time'], data[f'ch{i}'], label=f'Channel {i}')
plt.title("Logged Data")
plt.grid(True)
plt.xlabel("Time (s)")
plt.ylabel("Voltage (V)")
plt.legend(loc=0)
plt.show()

Example output:

MokuDataLoggerData_20250116_102402.csv
'time': [0.   0.01 0.02 ... 9.99]
'ch1': [0.00063297 0.00077466 0.00071688 ... 0.00067479823461]
'ch2': [0.01406568 0.01389566 0.014152   ... 0.014421103911]

Other file type conversions and reading methods for Python

Here is a cheat-sheet style summary of the file type conversions and how to read them in Python, adjust the file_name and channels parameters to match your experiment.

.mat

C:\Users\LItes\Downloads>mokucli convert MokuDataLoggerData_20250116_102402.li --format=mat
[===========================================================================]
Done.

import os
from scipy.io import loadmat

file_name = "MokuDataLoggerData_20250116_102402.mat"
channels = 2
print(file_name)

assert os.path.isfile(file_name), "Convert failed, no file received"
data = {'time':[], 'ch1':[]}
file = loadmat(file_name)
data['time'] = file['moku']['data'][0, 0][:,0]
for i in range(1, channels+1):
    data[f'ch{i}'] = file['moku']['data'][0, 0][:,i]

keys = data.keys()
for key in keys:
    print(f"'{key}': {str(data[key][:3])[:-1]} ... {data[key][-1]}]")

.npy

C:\Users\LItes\Downloads>mokucli convert MokuDataLoggerData_20250116_102402.li --format=npy
[===========================================================================]
Done.

import os
import numpy as np

file_name = "MokuDataLoggerData_20250116_102402.npy"
channels = 2
print(file_name)

assert os.path.isfile(file_name), "Convert failed, no file received"
data = {'time':[], 'ch1':[]}
load = np.load(file_name)
file = np.array([[load[i][0]] + [load[i][j] for j in range(1, channels+1)] for i in range(len(load))])
data['time'] = file[:,0]
for i in range(1, channels+1):
    data[f'ch{i}'] = file[:,i]

keys = data.keys()
for key in keys:
    print(f"'{key}': {str(data[key][:3])[:-1]} ... {data[key][-1]}]")

.hdf5

C:\Users\LItes\Downloads>mokucli convert MokuDataLoggerData_20250116_102402.li --format=hdf5
[===========================================================================]
Done.

import os
import numpy as np
import h5py

file_name = "MokuDataLoggerData_20250116_102402.hdf5"
channels = 2
print(file_name)

assert os.path.isfile(file_name), "Convert failed, no file received"
data = {'time':[], 'ch1':[]}
load = h5py.File(file_name, 'r')
file = np.array(list(load['moku']),dtype=np.dtype('float'+',float'*channels))
file.dtype.names=['time'] + [f'ch{i}' for i in range(1, channels+1)]
data['time'] = file['time']
for i in range(1, channels+1):
    data[f'ch{i}'] = file[f'ch{i}']

keys = data.keys()
for key in keys:
    print(f"'{key}': {str(data[key][:3])[:-1]} ... {data[key][-1]}]")