本文整理汇总了Python中gnome.outputters.Renderer.save_foreground方法的典型用法代码示例。如果您正苦于以下问题：Python Renderer.save_foreground方法的具体用法？Python Renderer.save_foreground怎么用？Python Renderer.save_foreground使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类gnome.outputters.Renderer的用法示例。
在下文中一共展示了Renderer.save_foreground方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_render_beached_elements
# 需要导入模块: from gnome.outputters import Renderer [as 别名]
# 或者: from gnome.outputters.Renderer import save_foreground [as 别名]
def test_render_beached_elements():
"""
Should this test be in map_canvas?
"""
input_file = os.path.join(data_dir,
r"MapBounds_2Spillable2Islands2Lakes.bna")
r = Renderer(input_file, output_dir, image_size=(800, 600))
BB = r.map_BB
(min_lon, min_lat) = BB[0]
(max_lon, max_lat) = BB[1]
N = 100
# create some random particle positions:
lon = random.uniform(min_lon, max_lon, (N, ))
lat = random.uniform(min_lat, max_lat, (N, ))
# create a sc
sc = sample_sc_release(num_elements=N)
sc['positions'][:, 0] = lon
sc['positions'][:, 1] = lat
# make half of them on land
sc['status_codes'][::2] = oil_status.on_land
r.create_foreground_image()
r.draw_elements(sc)
# create an uncertainty sc
lon = random.uniform(min_lon, max_lon, (N, ))
lat = random.uniform(min_lat, max_lat, (N, ))
sc = sample_sc_release(num_elements=N, uncertain=True)
sc['positions'][:, 0] = lon
sc['positions'][:, 1] = lat
# make half of them on land
sc['status_codes'][::2] = oil_status.on_land
r.draw_elements(sc)
# save the image
r.save_foreground(os.path.join(output_dir, 'foreground2.png'))
assert True示例2: test_render_elements
# 需要导入模块: from gnome.outputters import Renderer [as 别名]
# 或者: from gnome.outputters.Renderer import save_foreground [as 别名]
def test_render_elements(output_dir):
"""
Should this test be in map_canvas?
"""
# put in current dir for now:
output_dir = './'
r = Renderer(bna_sample, output_dir, image_size=(800, 600))
BB = r.map_BB
(min_lon, min_lat) = BB[0]
(max_lon, max_lat) = BB[1]
N = 1000
# create some random particle positions:
lon = random.uniform(min_lon, max_lon, (N, ))
lat = random.uniform(min_lat, max_lat, (N, ))
# create a sc
sc = sample_sc_release(num_elements=N)
sc['positions'][:, 0] = lon
sc['positions'][:, 1] = lat
r.create_foreground_image()
r.draw_elements(sc)
# create an uncertainty sc
lon = random.uniform(min_lon, max_lon, (N, ))
lat = random.uniform(min_lat, max_lat, (N, ))
sc = sample_sc_release(num_elements=N, uncertain=True)
sc['positions'][:, 0] = lon
sc['positions'][:, 1] = lat
r.draw_elements(sc)
# save the image
r.save_foreground(os.path.join(output_dir, 'foreground1.png'))
assert True