Daisy Process

Command Set

Always start your automation scripts by setting up the interface to the Daisy instruments. Assuming your Daisy Process is the first instrument in the first group:

process = self.my_interface.groups[0].inst[0]

The run command format is:

[<param1>, <param2>, <param3>] = process.measure_parameters(<channel #>)

There are four MODBUS channels available on each Daisy Process instrument. Simply specify the channel number that your target probe is connected to in the command, and measurement parameters will be returned. For instance, to read pH, mV and temperature values simultaneously from the Polylite Plus ARC probe from Hamilton connected to channel 3 of a Daisy Process module, use:

[pH, mV, T] = process.measure_parameters(3)

Application Example: Real-Time pH Control
The script segment below uses a Daisy Peri T (peristaltic pump) and a Daisy Multi Val (selector valve) to set up a cell perfusion assay. The Peri T provides continuous, long-term flow of reagents into the perfusion chamber, while the Multi Val switches between various input reagents/buffers (up to 12 different inputs) to feed to the pump. The example below uses a time-of-day based scheduling to switch between the different reagents.

from datetime import datetime

g1 = self.my_interface.groups[0]
peri_pump = g1.inst[0]  # first instrument in the chain is the Daisy Peri T
multi_val = g1.inst[1]  # second instrument in the chain is Daisy Multi Val

# Start by homing the selector valve
multi_val.home()  # waits automatically to finish. Defaults to port 1

# Next, calibrate the peristaltic pump according to the tubing used
calibration_speed = 7.54  # ml/min @ 60 rpm; using 1.6/4.8 ID/OD (mm) tubing
peri_pump.calibrate(calibration_speed)

# Finally, start the peri pump at 10 ml/min perfusion speed, choosing
# different reagents at different times. For simplicity, let's assume
# the cells are in an artificial muscle environment, reacting to
# simulated glucose level increases with every meal. Breakfast at 
# 08:00, Lunch at 12:00 and dinner at 18:00. This is just an example; 
# the reagent schedule could be anything your application needs.

current_time = datetime.now().time()

# Define meal times and the duration of glucose spike from each meal
breakfast_time = current_time.replace(hour=8, minute=0, second=0, microsecond=0)
breakfast_digest_time = current_time.replace(hour=9, minute=30, second=0, microsecond=0)
lunch_time = current_time.replace(hour=12, minute=0, second=0, microsecond=0)
lunch_digest_time = current_time.replace(hour=14, minute=0, second=0, microsecond=0)
dinner_time = current_time.replace(hour=18, minute=0, second=0, microsecond=0)
dinner_digest_time = current_time.replace(hour=20, minute=15, second=0, microsecond=0)

check_interval = 60 # seconds
one_hour = check_interval*60

# start the peri pump
peri_pump.run(10.0, 10*60*24*10, wait=False) # run at 10 ml/min for 10 days
while True:
    current_time = datetime.now().time()
    if (current_time >= breakfast_time):
        multi.select_port(3, wait=False) # breakfast spike on port 3
    if (current_time >= breakfast_digest_time):
        multi.select_port(1, wait=False)
    if (current_time >= lunch_time):
        multi.select_port(4, wait=False) # lunch spike on port 4
    if (current_time >= lunch_digest_time):
        multi.select_port(1, wait=False)
    if (current_time >= dinner_time):
        multi.select_port(5, wait=False) # dinner spike on port 5
    if (current_time >= dinner_digest_time):
        multi.select_port(1, wait=False)
    time.sleep(60)  # next check 1 min later