mirror of
https://github.com/AtsushiSakai/PythonRobotics.git
synced 2026-04-22 03:00:41 -04:00
remove cover alls (#357)
* remove cover alls * add codecov * try coverage * try coverage * try coverage
This commit is contained in:
Atsushi Sakai
2
.github/workflows/Linux_CI.yml
vendored
2
.github/workflows/Linux_CI.yml
vendored
@@ -45,6 +45,8 @@ jobs:
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run: bash rundiffstylecheck.sh
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- name: do all unit tests
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run: bash runtests.sh
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- name: Codecov
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uses: codecov/codecov-action@v1.0.10
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35
.travis.yml
35
.travis.yml
@@ -1,35 +0,0 @@
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language: python
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matrix:
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include:
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- os: linux
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python:
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- 3.8
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before_install:
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- sudo apt-get update
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- wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
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- chmod +x miniconda.sh
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- bash miniconda.sh -b -p $HOME/miniconda
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- export PATH="$HOME/miniconda/bin:$PATH"
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- hash -r
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- conda config --set always_yes yes --set changeps1 no
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- conda config --append channels conda-forge
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- conda update -q conda
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# Useful for debugging any issues with conda
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- conda info -a
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install:
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- conda install numpy
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- conda install scipy
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- conda install matplotlib
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- conda install pandas
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- conda install cvxpy
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- conda install coveralls
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script:
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- python --version
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after_success:
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- coveralls
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@@ -12,33 +12,31 @@ import sys
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import matplotlib.pyplot as plt
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import numpy as np
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from scipy import ndimage
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do_animation = True
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def transform(
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gridmap, src, distance_type='chessboard',
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transform_type='path', alpha=0.01
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grid_map, src, distance_type='chessboard',
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transform_type='path', alpha=0.01
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):
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"""transform
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calculating transform of transform_type from src
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in given distance_type
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:param gridmap: 2d binary map
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:param grid_map: 2d binary map
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:param src: distance transform source
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:param distance_type: type of distance used
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:param transform_type: type of transform used
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:param alpha: weight of Obstacle Transform usedwhen using path_transform
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:param alpha: weight of Obstacle Transform used when using path_transform
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"""
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nrows, ncols = gridmap.shape
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n_rows, n_cols = grid_map.shape
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if nrows == 0 or ncols == 0:
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sys.exit('Empty gridmap.')
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if n_rows == 0 or n_cols == 0:
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sys.exit('Empty grid_map.')
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inc_order = [[0, 1], [1, 1], [1, 0], [1, -1],
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[0, -1], [-1, -1], [-1, 0], [-1, 1]]
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@@ -49,30 +47,30 @@ def transform(
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else:
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sys.exit('Unsupported distance type.')
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transform_matrix = float('inf') * np.ones_like(gridmap, dtype=np.float)
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transform_matrix = float('inf') * np.ones_like(grid_map, dtype=np.float)
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transform_matrix[src[0], src[1]] = 0
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if transform_type == 'distance':
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eT = np.zeros_like(gridmap)
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eT = np.zeros_like(grid_map)
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elif transform_type == 'path':
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eT = ndimage.distance_transform_cdt(1-gridmap, distance_type)
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eT = ndimage.distance_transform_cdt(1 - grid_map, distance_type)
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else:
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sys.exit('Unsupported transform type.')
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# set obstacle transform_matrix value to infinity
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for i in range(nrows):
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for j in range(ncols):
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if gridmap[i][j] == 1.0:
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for i in range(n_rows):
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for j in range(n_cols):
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if grid_map[i][j] == 1.0:
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transform_matrix[i][j] = float('inf')
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is_visited = np.zeros_like(transform_matrix, dtype=bool)
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is_visited[src[0], src[1]] = True
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traversal_queue = [src]
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calculated = [(src[0]-1)*ncols + src[1]]
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calculated = [(src[0] - 1) * n_cols + src[1]]
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def is_valid_neighbor(i, j):
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return ni >= 0 and ni < nrows and nj >= 0 and nj < ncols \
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and not gridmap[ni][nj]
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def is_valid_neighbor(g_i, g_j):
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return 0 <= g_i < n_rows and 0 <= g_j < n_cols \
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and not grid_map[g_i][g_j]
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while traversal_queue != []:
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while traversal_queue:
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i, j = traversal_queue.pop(0)
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for k, inc in enumerate(inc_order):
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ni = i + inc[0]
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@@ -83,16 +81,35 @@ def transform(
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# update transform_matrix
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transform_matrix[i][j] = min(
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transform_matrix[i][j],
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transform_matrix[ni][nj] + cost[k] + alpha*eT[ni][nj])
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transform_matrix[ni][nj] + cost[k] + alpha * eT[ni][nj])
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if not is_visited[ni][nj] \
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and ((ni-1)*ncols + nj) not in calculated:
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and ((ni - 1) * n_cols + nj) not in calculated:
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traversal_queue.append((ni, nj))
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calculated.append((ni-1)*ncols + nj)
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calculated.append((ni - 1) * n_cols + nj)
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return transform_matrix
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def get_search_order_increment(start, goal):
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if start[0] >= goal[0] and start[1] >= goal[1]:
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order = [[1, 0], [0, 1], [-1, 0], [0, -1],
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[1, 1], [1, -1], [-1, 1], [-1, -1]]
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elif start[0] <= goal[0] and start[1] >= goal[1]:
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order = [[-1, 0], [0, 1], [1, 0], [0, -1],
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[-1, 1], [-1, -1], [1, 1], [1, -1]]
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elif start[0] >= goal[0] and start[1] <= goal[1]:
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order = [[1, 0], [0, -1], [-1, 0], [0, 1],
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[1, -1], [-1, -1], [1, 1], [-1, 1]]
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elif start[0] <= goal[0] and start[1] <= goal[1]:
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order = [[-1, 0], [0, -1], [0, 1], [1, 0],
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[-1, -1], [-1, 1], [1, -1], [1, 1]]
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else:
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sys.exit('get_search_order_increment: cannot determine \
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start=>goal increment order')
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return order
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def wavefront(transform_matrix, start, goal):
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"""wavefront
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@@ -104,32 +121,14 @@ def wavefront(transform_matrix, start, goal):
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"""
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path = []
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nrows, ncols = transform_matrix.shape
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n_rows, n_cols = transform_matrix.shape
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def get_search_order_increment(start, goal):
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if start[0] >= goal[0] and start[1] >= goal[1]:
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order = [[1, 0], [0, 1], [-1, 0], [0, -1],
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[1, 1], [1, -1], [-1, 1], [-1, -1]]
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elif start[0] <= goal[0] and start[1] >= goal[1]:
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order = [[-1, 0], [0, 1], [1, 0], [0, -1],
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[-1, 1], [-1, -1], [1, 1], [1, -1]]
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elif start[0] >= goal[0] and start[1] <= goal[1]:
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order = [[1, 0], [0, -1], [-1, 0], [0, 1],
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[1, -1], [-1, -1], [1, 1], [-1, 1]]
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elif start[0] <= goal[0] and start[1] <= goal[1]:
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order = [[-1, 0], [0, -1], [0, 1], [1, 0],
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[-1, -1], [-1, 1], [1, -1], [1, 1]]
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else:
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sys.exit('get_search_order_increment: cannot determine \
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start=>goal increment order')
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return order
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def is_valid_neighbor(i, j):
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is_i_valid_bounded = i >= 0 and i < nrows
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is_j_valid_bounded = j >= 0 and j < ncols
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def is_valid_neighbor(g_i, g_j):
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is_i_valid_bounded = 0 <= g_i < n_rows
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is_j_valid_bounded = 0 <= g_j < n_cols
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if is_i_valid_bounded and is_j_valid_bounded:
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return not is_visited[i][j] and \
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transform_matrix[i][j] != float('inf')
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return not is_visited[g_i][g_j] and \
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transform_matrix[g_i][g_j] != float('inf')
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return False
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inc_order = get_search_order_increment(start, goal)
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@@ -146,7 +145,7 @@ def wavefront(transform_matrix, start, goal):
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i_max = (-1, -1)
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i_last = 0
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for i_last in range(len(path)):
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current_node = path[-1 - i_last] # get lastest node in path
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current_node = path[-1 - i_last] # get latest node in path
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for ci, cj in inc_order:
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ni, nj = current_node[0] + ci, current_node[1] + cj
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if is_valid_neighbor(ni, nj) and \
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@@ -168,10 +167,10 @@ def wavefront(transform_matrix, start, goal):
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return path
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def visualize_path(grid_map, start, goal, path, resolution):
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def visualize_path(grid_map, start, goal, path): # pragma: no cover
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oy, ox = start
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gy, gx = goal
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px, py = np.transpose(np.flipud(np.fliplr((path))))
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px, py = np.transpose(np.flipud(np.fliplr(path)))
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if not do_animation:
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plt.imshow(grid_map, cmap='Greys')
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@@ -207,12 +206,12 @@ def main():
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# distance transform wavefront
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DT = transform(img, goal, transform_type='distance')
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DT_path = wavefront(DT, start, goal)
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visualize_path(img, start, goal, DT_path, 1)
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visualize_path(img, start, goal, DT_path)
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# path transform wavefront
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PT = transform(img, goal, transform_type='path', alpha=0.01)
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PT_path = wavefront(PT, start, goal)
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visualize_path(img, start, goal, PT_path, 1)
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visualize_path(img, start, goal, PT_path)
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if __name__ == "__main__":
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@@ -6,7 +6,7 @@
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[](https://travis-ci.org/AtsushiSakai/PythonRobotics)
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[](https://pythonrobotics.readthedocs.io/en/latest/?badge=latest)
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[](https://ci.appveyor.com/project/AtsushiSakai/pythonrobotics)
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[](https://coveralls.io/github/AtsushiSakai/PythonRobotics?branch=master)
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[](https://codecov.io/gh/AtsushiSakai/PythonRobotics)
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[](https://lgtm.com/projects/g/AtsushiSakai/PythonRobotics/context:python)
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[](https://www.codefactor.io/repository/github/atsushisakai/pythonrobotics/overview/master)
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[](https://github.com/AtsushiSakai/PythonRobotics)
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