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2 changes: 1 addition & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,7 @@ Follow the steps below to contribute to this project.

Install the required dependencies from the `requirements.txt` file.

If using `pip` then `pip install requirements.txt`.
If using `pip` then `pip install -r requirements.txt`.

If using `conda` then follow these steps to create an environment with the right dependencies:

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55 changes: 54 additions & 1 deletion src/VPPMod.py
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
from src.HydroMod import HydroMod
from src.UtilsMod import KNOTS_TO_MPS, json_write, polar_plot, sail_chart
from src.YachtMod import Yacht as YachtClass
from rich.progress import track # For progress bar

logger = logging.getLogger(__name__)
debug_mode = logging.getLogger().getEffectiveLevel() == logging.DEBUG
Expand Down Expand Up @@ -202,7 +203,7 @@ def run(self, verbose=False):
if not self.upToDate:
raise "VPP run stop: no analysis set!"

for i, tws in enumerate(self.tws_range):
for i, tws in track(enumerate(self.tws_range), description="Analysing...", total=len(self.tws_range)):
logging.debug("Sailing in TWS : %.1f" % (tws / KNOTS_TO_MPS))

for n in range(self.Nsails):
Expand Down Expand Up @@ -329,6 +330,58 @@ def results(self):

def write(self, fname):
json_write(self.results(), fname)

def write_csv(self, fname):
import csv

# Init a counter for how many values have been used to average the boat speed for a given wind direction and speed:
avg_counter = np.zeros((37, 20))

with open(fname, mode="w", newline="") as file:
writer = csv.writer(file, delimiter=";")
# Write header with TWS in knots
writer.writerow(["TWA\TWS", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20", "22", "24", "26", "28", "30", "32", "34", "36", "38", "40"])
# Loop through every degree from 0°to 180° in 5° increments
for angle in range(0, 181, 5):
# Init row to write
row = [None] * 21
# Set angle
row[0] = angle
# Go through each TWS and get the corresponding boat speed for the current angle
for i, tws in enumerate(self.tws_range):
# Change tws to knots
tws = tws / KNOTS_TO_MPS
for j, twa in enumerate(self.twa_range):
# Get closest wind speed and find column in openCPN. Note we are stuck using these until this issue (https://github.com/rgleason/polar_pi/issues/34) gets dealt with
closest_wind_speed_column = round(tws/2)
# If closest wind speed column is zero, increment by one so we don't overwrite the angle column.
if closest_wind_speed_column == 0:
closest_wind_speed_column += 1
# Get closest angle and find see if it matches the current angle we are looking for
closest_angle = round(twa/5)*5
# If the closest_angle matches the angle we're currently working with then get the speeds, otherwise, skip to next entry
if closest_angle == angle:
# Get boat speed for give wind angle and speed
boat_speed = self.store[i, j, 0, 0]
# Get row number
row_number = int(angle/5)

# Update the row with the boat speed for this angle and wind speed
# If there has not been a value used yet, set the value to the boat speed, otherwise, average the current value with the new boat speed
if row[closest_wind_speed_column] is None:
row[closest_wind_speed_column] = boat_speed
else:
# Find out how many values have been used to make this average
num_values = avg_counter[row_number, closest_wind_speed_column]
# Average the current boat speed with the already logged average boat speed
row[closest_wind_speed_column] = (row[closest_wind_speed_column] * num_values + boat_speed) / (num_values + 1)

# Update the average counter for this angle and wind speed
avg_counter[row_number, closest_wind_speed_column] += 1
# Print out the speed of the vessel given the angle and wind speed

# Write the row to the csv file
writer.writerow(row)

def polar(self, n=1, save=False, fname="Polars.png"):
polar_plot([self], n, save, fname)
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