def build_matrix(cls, vnames, matrix, latex_map=None):
"""build latex correlation matrix"""
# ret_link = '<a onclick="$(\'#%s\').toggle()" href="#">Show Latex</a>'%uid
headers = [""] + list(vnames)
data = []
color = {}
grad = Gradient(
(-1.0, 120.0, 120.0, 250.0),
(0.0, 250.0, 250.0, 250.0),
(1.0, 250.0, 100.0, 100.0),
)
for i, v1 in enumerate(vnames):
tmp = [v1]
for j in range(len(vnames)):
m = matrix[i][j]
tmp.append(m)
color[(i + 1, j + 1)] = grad(m)
# +1 for header on the side and top
data.append(tmp)
table = LatexTable(headers=headers,
data=data,
rotate_header=True,
latex_map=latex_map)
table.float_format = "%.2g"
for (i, j), c in color.items():
table.set_cell_color(i, j, c)
return table
def test_color_3():
g = Gradient((-1, 50, 50, 250), (0, 100, 100, 100), (1, 250, 50, 50))
assert g.rgb(-1) == "rgb(50,50,250)"
assert g.rgb(-0.5) == "rgb(75,75,175)"
assert g.rgb(0) == "rgb(100,100,100)"
assert g.rgb(0.5) == "rgb(175,75,75)"
assert g.rgb(1) == "rgb(250,50,50)"
def test_color_2():
g = Gradient((-1, 10, 10, 20), (2, 20, 20, 10))
assert g.rgb(-1) == "rgb(10,10,20)"
assert g.rgb(2) == "rgb(20,20,10)"
assert g.rgb(-1.00001) == "rgb(10,10,20)"
assert g.rgb(1.99999) == "rgb(20,20,10)"
assert g.rgb(0.5) == "rgb(15,15,15)"
def matrix(m):
is_correlation = True
for i in range(len(m)):
if m[i][i] != 1.0:
is_correlation = False
break
if not is_correlation:
n = len(m)
args = []
for mi in m:
for mj in mi:
args.append(mj)
nums = matrix_format(*args)
grad = Gradient(
(-1.0, 120.0, 120.0, 250.0),
(0.0, 250.0, 250.0, 250.0),
(1.0, 250.0, 100.0, 100.0),
)
s = Html()
with table(s):
with tr(s):
s += "<td/>\n"
for v in m.names:
with th(s):
s += v
for i, v in enumerate(m.names):
with tr(s):
with th(s):
s += v
for j in range(len(m.names)):
val = m[i][j]
if is_correlation:
if i == j:
with td(s):
s += " 1.00"
else:
color = grad.rgb(val)
with td(s, style="background-color:" + color):
s += "%5.2f" % val
else:
if i == j:
with td(s):
s += nums[n * i + j]
else:
color = grad.rgb(val / (m[i][i] * m[j][j])**0.5)
with td(s, style="background-color:" + color):
s += nums[n * i + j]
return str(s)
def matrix(m):
is_correlation = True
for i in range(len(m)):
if m[i][i] != 1.0:
is_correlation = False
break
if not is_correlation:
n = len(m)
args = []
for mi in m:
for mj in mi:
args.append(mj)
nums = matrix_format(*args)
grad = Gradient(
(-1.0, 120.0, 120.0, 250.0),
(0.0, 250.0, 250.0, 250.0),
(1.0, 250.0, 100.0, 100.0),
)
rows = []
for i, v in enumerate(m.names):
cols = [th(v)]
for j in range(len(m.names)):
val = m[i][j]
if is_correlation:
if i == j:
t = td("1.00")
else:
color = grad.rgb(val)
t = td(
"%5.2f" % val,
style="background-color:" + color + ";color:black",
)
else:
if i == j:
t = td(nums[n * i + j])
else:
num = m[i][i] * m[j][j]
color = grad.rgb(val / num**0.5 if num > 0 else 0)
t = td(
nums[n * i + j],
style="background-color:" + color + ";color:black",
)
cols.append(t)
rows.append(tr(*cols))
return to_str(table(tr(td(), *[th(v) for v in m.names]), *rows))
