def _get_rows_of_plants(types):
"""
Types is array of (row, spacing, plant) tuples
"""
plants = []
for row, spacing, plant_type in types:
for col in range(spacing // 2 + 2, NUM_X_STEPS - spacing // 2,
spacing):
plants.append(Plant.from_preset(plant_type, col, row))
return plants
def _get_random_plants_of_type(types):
plants = []
for plant_type, num in types:
x_locations = np.random.randint(3, NUM_X_STEPS - 3, (num, 1))
y_locations = np.random.randint(3, NUM_Y_STEPS - 3, (num, 1))
locations = np.hstack((x_locations, y_locations))
plants.extend([
Plant.from_preset(plant_type, row, col) for row, col in locations
])
return plants
def _get_grid_of_plants(types):
count = 0
plants = []
for row in range(0, NUM_Y_STEPS - 1, 10):
for col in range(0, NUM_X_STEPS - 1, 10):
plants.append(Plant.from_preset(types[0][0], col, row))
count += 1
if count >= types[0][1]:
types.pop(0)
count = 0
return plants
def _get_random_plants(plant_types, plants_per_color, seed=None):
if seed is not None:
np.random.seed(seed)
plants = []
for name in plant_types:
x_locations = np.random.randint(1, NUM_X_STEPS - 1,
(plants_per_color, 1))
y_locations = np.random.randint(1, NUM_Y_STEPS - 1,
(plants_per_color, 1))
locations = np.hstack((x_locations, y_locations))
plants.extend(
[Plant.from_preset(name, row, col) for row, col in locations])
return plants
def _read_plants_from_csv(path):
plants = []
with open(path) as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for row in csv_reader:
if line_count == 0:
line_count += 1
else:
coord = literal_eval(row[2])
x = round(coord[0] * NUM_X_STEPS / 1920)
y = round(NUM_Y_STEPS - coord[1] * NUM_Y_STEPS / 1080)
plants.append(Plant.from_preset(row[1], x, y))
line_count += 1
return plants
