def _generate_content(*args, **kwargs):
grid = tpl.subplot_grid((2, 3), *args, **kwargs)
grid[0, 0].aprint("Some text")
grid[0, 1].aprint("Some more text\nand more")
grid[0, 2].aprint("Some more text\nand more\neven more")
grid[1, 0].aprint("Some more text\nand more\neven more")
grid[1, 1].aprint("Some more text\nand more")
grid[1, 2].aprint("Some text")
return grid
def test_subplot_custom_border():
grid = tpl.subplot_grid((1, 2), border_style="x", width=20)
grid[0, 0].aprint("Some text")
grid[0, 1].aprint("Some more text")
string = grid.get_string()
assert (string == """xxxxxxxxxxxxxxxxxxxx
x x x
x Some x Some x
x x x
xxxxxxxxxxxxxxxxxxxx""")
return
def test_subplot():
grid = tpl.subplot_grid((1, 2), width=20)
grid[0, 0].aprint("Some text")
grid[0, 1].aprint("Some more text")
string = grid.get_string()
assert (string == """┌─────────┬────────┐
│ │ │
│ Some │ Some │
│ │ │
└─────────┴────────┘""")
return
def test_subplot2():
grid = tpl.subplot_grid((1, 2), width=20, border_style="thick")
grid[0, 0].aprint("Some text")
grid[0, 1].aprint("Some more text\nand more")
string = grid.get_string()
assert (string == """┏━━━━━━━━━┳━━━━━━━━┓
┃ ┃ ┃
┃ Some ┃ Some ┃
┃ ┃ and ┃
┃ ┃ ┃
┗━━━━━━━━━┻━━━━━━━━┛""")
return
def test_subplot_padding():
grid = tpl.subplot_grid((1, 2), width=20, padding=2, border_style="double")
grid[0, 0].aprint("Some text")
grid[0, 1].aprint("Some more text\nand more")
string = grid.get_string()
assert (string == """╔═════════╦════════╗
║ ║ ║
║ ║ ║
║ Some ║ Some ║
║ ║ and ║
║ ║ ║
║ ║ ║
╚═════════╩════════╝""")
return
def print_stats(mesh):
import termplotlib
q = mesh.q_radius_ratio
q_hist, q_bin_edges = numpy.histogram(q,
bins=numpy.linspace(0.0,
1.0,
num=41,
endpoint=True))
grid = termplotlib.subplot_grid((1, 2),
column_widths=None,
border_style=None)
grid[0, 0].hist(q_hist, q_bin_edges, bar_width=1, strip=True)
grid[0, 1].aprint("min quality: {:5.3f}".format(numpy.min(q)))
grid[0, 1].aprint("avg quality: {:5.3f}".format(numpy.average(q)))
grid[0, 1].aprint("max quality: {:5.3f}".format(numpy.max(q)))
grid.show()
def print_stats_2d(quality,
method="not specified",
elapsed=0.0,
num_verts=0.0,
num_cells=0.0):
"""https://github.com/nschloe/optimesh/blob/master/optimesh/helpers.py
NTS: terminal dimension: 286x93, font size 11, Menlo Regular, Line spacing 0.8, Char. spacing 1.044
"""
q = quality
q_hist, q_bin_edges = numpy.histogram(q,
bins=numpy.linspace(0.0,
1.0,
num=41,
endpoint=True))
grid = tpl.subplot_grid((2, 1))
grid[0, 0].aprint(method)
grid[0, 0].aprint("Mesh creation time (sec.): {:7.2f}".format(elapsed))
grid[0, 0].aprint("Mesh creation speed (vertices/sec.): {:7.2f}".format(
num_verts / elapsed))
grid[0, 0].aprint("Number of vertices: {:7.0f}".format(num_verts))
grid[0, 0].aprint("Number of cells: {:7.0f}".format(num_cells))
grid[1, 0].aprint("min quality: {:5.3f}".format(numpy.min(q)))
grid[1, 0].aprint("avg quality: {:5.3f}".format(numpy.average(q)))
grid[1, 0].aprint("max quality: {:5.3f}".format(numpy.max(q)))
grid[1, 0].hist(q_hist, q_bin_edges, grid=[15, 25])
grid.show()
stats = numpy.array([
elapsed,
num_verts / elapsed,
num_verts,
num_cells,
numpy.min(q),
numpy.average(q),
numpy.max(q),
])
numpy.savetxt(method + "_2d.txt", stats, delimiter=",")
def print_stats(mesh, extra_cols=None):
extra_cols = [] if extra_cols is None else extra_cols
angles = mesh.angles / numpy.pi * 180
angles_hist, angles_bin_edges = numpy.histogram(angles,
bins=numpy.linspace(
0.0,
180.0,
num=73,
endpoint=True))
q = mesh.cell_quality
q_hist, q_bin_edges = numpy.histogram(q,
bins=numpy.linspace(0.0,
1.0,
num=41,
endpoint=True))
grid = tpl.subplot_grid((1, 4 + len(extra_cols)),
column_widths=None,
border_style=None)
grid[0, 0].hist(angles_hist,
angles_bin_edges,
grid=[24],
bar_width=1,
strip=True)
grid[0, 1].aprint("min angle: {:7.3f}".format(numpy.min(angles)))
grid[0, 1].aprint("avg angle: {:7.3f}".format(60))
grid[0, 1].aprint("max angle: {:7.3f}".format(numpy.max(angles)))
grid[0, 1].aprint("std dev angle: {:7.3f}".format(numpy.std(angles)))
grid[0, 2].hist(q_hist, q_bin_edges, bar_width=1, strip=True)
grid[0, 3].aprint("min quality: {:5.3f}".format(numpy.min(q)))
grid[0, 3].aprint("avg quality: {:5.3f}".format(numpy.average(q)))
grid[0, 3].aprint("max quality: {:5.3f}".format(numpy.max(q)))
for k, col in enumerate(extra_cols):
grid[0, 4 + k].aprint(col)
grid.show()
return
def print_stats_3d(angles,
quality,
method="not specified",
elapsed=0.0,
num_verts=0.0,
num_cells=0.0):
"""https://github.com/nschloe/optimesh/blob/master/optimesh/helpers.py
NTS: terminal dimension: 286x93, font size 11, Menlo Regular, Line spacing 0.8, Char. spacing 1.044
"""
# convert to dihedral angles in radians
const = 2 * math.sqrt(2) / 3
angles = numpy.arcsin(const * angles)
# convert to degrees
angles = 180 * angles / numpy.pi
angles_hist, angles_bin_edges = numpy.histogram(angles,
bins=numpy.linspace(
0.0,
180.0,
num=73,
endpoint=True))
q = quality
q_hist, q_bin_edges = numpy.histogram(q,
bins=numpy.linspace(0.0,
1.0,
num=41,
endpoint=True))
grid = tpl.subplot_grid((2, 2))
grid[0, 0].aprint(method)
grid[0, 0].aprint("Mesh creation time (sec.): {:7.2f}".format(elapsed))
grid[0, 0].aprint("Mesh creation speed (vertices/sec.): {:7.2f}".format(
num_verts / elapsed))
grid[0, 1].aprint("Number of vertices: {:7.0f}".format(num_verts))
grid[0, 1].aprint("Number of cells: {:7.0f}".format(num_cells))
grid[1, 0].aprint("min. dihedral angles: {:7.3f}".format(
numpy.min(angles)))
grid[1, 0].aprint("avg. dihedral angles: {:7.3f}".format(
numpy.mean(angles)))
grid[1, 0].aprint("max dihedral angles: {:7.3f}".format(
numpy.max(angles)))
grid[1, 0].aprint("std dev. dihedral angles: {:7.3f}".format(
numpy.std(angles)))
grid[1, 0].hist(angles_hist, angles_bin_edges, grid=[15, 25])
grid[1, 1].aprint("min quality: {:5.3f}".format(numpy.min(q)))
grid[1, 1].aprint("avg quality: {:5.3f}".format(numpy.average(q)))
grid[1, 1].aprint("max quality: {:5.3f}".format(numpy.max(q)))
grid[1, 1].hist(q_hist, q_bin_edges, grid=[15, 25])
grid.show()
stats = numpy.array([
elapsed,
num_verts / elapsed,
num_verts,
num_cells,
numpy.min(angles),
numpy.mean(angles),
numpy.max(angles),
numpy.std(angles),
numpy.min(q),
numpy.average(q),
numpy.max(q),
])
numpy.savetxt(method + ".txt", stats, delimiter=",")
