def command_button_analyze(self):
logger = logging.getLogger('gui_multiples.command_button_analyze')
logger.setLevel(logging.INFO)
file_counter = 0
for filename in self.filepath_open:
file_counter += 1
logger.info("Analyzing data of the file #%d of %d: %s." % (file_counter, len(self.filepath_open), filename))
data_analyzer.analyze_data(filename, self.filepath_save)
def run(self):
# Initialize networktables
team = ""
while team == "":
team = input("Enter team number or 'sim': ")
if team == "sim":
NetworkTables.initialize(server="localhost")
else:
NetworkTables.startClientTeam(int(team))
# Use listeners to receive the data
NetworkTables.addConnectionListener(self.connectionListener,
immediateNotify=True)
NetworkTables.addEntryListener(self.valueChanged)
# Wait for a connection notification, then continue on the path
print("Waiting for NT connection..")
while True:
if self.queue.get() == "connected":
break
print("Connected!")
print()
autonomous = [
# name, initial speed, ramp
("slow-forward", 0, 0.001),
("slow-backward", 0, -0.001),
("fast-forward", abs(ROBOT_FAST_SPEED), 0),
("fast-backward", -abs(ROBOT_FAST_SPEED), 0),
]
stored_data = {}
#
# Wait for the user to cycle through the 4 autonomus modes
#
for i, (name, initial_speed, ramp) in enumerate(autonomous):
# Initialize the robot commanded speed to 0
self.autospeed = 0
self.discard_data = True
print()
print("Autonomous %d/%d: %s" % (i + 1, len(autonomous), name))
print()
print("Please enable the robot in autonomous mode.")
print()
print(
"WARNING: It will not automatically stop moving, so disable the robot"
)
print("before it hits something!")
print("")
# Wait for robot to signal that it entered autonomous mode
with self.lock:
self.lock.wait_for(lambda: self.mode == "auto")
data = self.wait_for_stationary()
if data is not None:
if data in ("connected", "disconnected"):
print(
"ERROR: NT disconnected, results won't be reliable. Giving up."
)
return
else:
print(
"Robot exited autonomous mode before data could be sent?"
)
break
# Ramp the voltage at the specified rate
data = self.ramp_voltage_in_auto(initial_speed, ramp)
if data in ("connected", "disconnected"):
print(
"ERROR: NT disconnected, results won't be reliable. Giving up."
)
return
# output sanity check
if len(data) < 3:
print(
"WARNING: There wasn't a lot of data received during that last run"
)
else:
left_distance = data[-1][L_ENCODER_P_COL] - data[0][
L_ENCODER_P_COL]
right_distance = data[-1][R_ENCODER_P_COL] - data[0][
R_ENCODER_P_COL]
print()
print("The robot reported traveling the following distance:")
print()
print("Left: %.3f ft" % left_distance)
print("Right: %.3f ft" % right_distance)
print()
print(
"If that doesn't seem quite right... you should change the encoder calibration"
)
print("in the robot program or fix your encoders!")
stored_data[name] = data
# In case the user decides to re-enable autonomous again..
self.autospeed = 0
#
# We have data! Do something with it now
#
# Write it to disk first, in case the processing fails for some reason
# -> Using JSON for simplicity, maybe add csv at a later date
now = time.strftime("%Y%m%d-%H%M-%S")
fname = "%s-data.json" % now
print()
print("Data collection complete! saving to %s..." % fname)
with open(fname, "w") as fp:
json.dump(stored_data, fp, indent=4, separators=(",", ": "))
analyze_data(stored_data)
def command_button_analyze(self):
data_analyzer.analyze_data(self.filepath_open, self.filepath_save)
import pandas as pd
import numpy as np
from sklearn.tree import DecisionTreeRegressor
from data_analyzer import analyze_data
x = []
y = []
for i in range(100):
x.append(i)
y.append(i)
# X = np.array(x)
# Y = np.array(y)
# X = X.reshape(-1, 1)
X = analyze_data()
Y = X.iloc[:, 12]
cc = list(combinations(X.iloc[0:11], 11))
print(len(cc))
indexes = []
indexes.append(cc[0][0])
indexes.append(cc[0][0])
x_smol = X[indexes]
# print(x_smol)
cross_val = KFold(10, True, 1)
print(cross_val)
