def generate_entries():
fc_format = r"--format=%{file}\n%{family}\n%{slant}\n%{weight}\n%{width}\n"
vendored_fonts_dir = Path(mpl.get_data_path(), "fonts/ttf")
vendored_fonts = [*map(str, vendored_fonts_dir.glob("*.ttf"))]
vendored_fonts = subprocess.check_output(["fc-query", fc_format] +
vendored_fonts,
universal_newlines=True)
system_fonts = subprocess.check_output(["fc-list", fc_format],
universal_newlines=True)
entries = []
lines = vendored_fonts.splitlines() + system_fonts.splitlines()
while lines:
fc_file, fc_family, fc_slant, fc_weight, fc_width, *lines = lines
file = fc_file
families = fc_family.split(",")
if re.match("\A\[.*\]\Z", fc_weight): # Variable weight, unsupported.
print(f"Skipping {fc_file} (unsupported variable weight)")
continue
style = {"0": "normal", "100": "italic", "110": "oblique"}[fc_slant]
# See FcWeightToOpenType.
# Note that 215 ("EXTRABLACK") does not appear in the docs, but in the
# header...
fc_weights = [0, 40, 50, 55, 75, 80, 100, 180, 200, 205, 210, 215]
css_weights = [
100, 200, 300, 350, 380, 400, 500, 600, 700, 800, 900, 1000
]
weight = int(np.interp(float(fc_weight), fc_weights, css_weights) + .5)
# The old version from pango_fc_weight_to_pango was:
# weight = (
# 100 if fc_weight <= 20
# else 200 if fc_weight <= 45
# else 300 if fc_weight <= 62
# else 380 if fc_weight <= 77
# else 400 if fc_weight <= 90
# else 500 if fc_weight <= 140
# else 600 if fc_weight <= 190
# else 700 if fc_weight <= 202
# else 800 if fc_weight <= 207
# else 900 if fc_weight <= 212
# else 1000)
stretch = {
"50": "ultra-condensed",
"63": "extra-condensed",
"75": "condensed",
"87": "semi-condensed",
"100": "normal",
"113": "semi-expanded",
"125": "expanded",
"150": "extra-expanded",
"200": "ultra-expanded",
}[fc_width]
variant = "normal" # Small caps not supported.
size = "scalable"
entries.extend(
fm.FontEntry(file, family, style, variant, weight, stretch, size)
for family in families)
entries.sort(key=lambda entry: entry.fname)
return entries
def line2img(line, scores, filename, maxwidth=50, img_width=800):
'''
Outputs an image containing text with green/red background highlights to indicate the importance of words in the text.
Arguments:
line (str): the text that should be printed
scores (Tensor): a vector of size len(line), where each index contains the "weight" of the corresponding letter in the line string; positive values will be colored green, and negative values red.
filename (str): the name of the output file
'''
import matplotlib
import matplotlib.colors as colors
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import math
import matplotlib.font_manager as font_manager
import os
font_manager.FontEntry(
fname=os.path.expanduser('~/project/fonts/ipag.ttf'))
fp = matplotlib.font_manager.FontProperties(
fname=os.path.expanduser('~/project/fonts/ipag.ttf'))
plt.rcParams['font.family'] = fp.get_name()
im_height = 1 + len(line) // maxwidth
im = np.zeros([maxwidth, im_height])
for i in range(scores.shape[0]):
im[i % maxwidth, im_height - i // maxwidth - 1] = scores[i]
cmap = matplotlib.colors.LinearSegmentedColormap.from_list(
"", ["red", "white", "green"])
scores_max = torch.max(scores)
norm = plt.Normalize(-scores_max, scores_max)
dpi = 96
fig, ax = plt.subplots(figsize=(img_width / dpi, 300 / dpi), dpi=dpi)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.set_xlim(-0.5, -0.5 + maxwidth)
ax.set_ylim(-0.5, 0.5 + i // maxwidth)
ax.imshow(im.transpose(), cmap=cmap, norm=norm)
#,fontproperties= fp
for i, c in enumerate(line):
ax.text(i % maxwidth - 0.25,
im_height - i // maxwidth - 0.25 - 1,
c,
fontsize=12,
fontproperties=fp)
plt.tight_layout()
plt.savefig(filename, bbox_inches='tight')
def set_font(path, name):
fe = fm.FontEntry(fname=path, name=name)
fm.fontManager.ttflist.insert(0, fe)
pp.rcParams["font.family"] = fe.name
import platform
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
os = platform.system()
if os == "Darwin":
plt.rc('font', family="AppleGothic")
else:
fe = fm.FontEntry(
fname="pykrx/NanumBarunGothic.ttf",
name='NanumBarunGothic'
)
fm.fontManager.ttflist.insert(0, fe)
plt.rc('font', family=fe.name)
plt.rcParams['axes.unicode_minus'] = False
count_stats, METRICS_TO_INVERT as invertible_metrics,
POSITIONS_DICT as pos_dict, POSITIONS_FBREF_DICT as
fbref_pos_dict, POSITIONS_COLORS_DICT as col_dict, SEASON)
warnings.filterwarnings("ignore")
TEXT_COLOR = "k"
LINE_COLOR = "k"
SCATTER_COLOR = "k"
LABEL_FILL_COLOR = "0.7"
MIN_90s = 4 ##for the player comparison pool, not the queried player themself
font_name = 'Source-Sans-Pro'
font_dirs = ['../Source_Sans_Pro/']
font_file = sorted(font_manager.findSystemFonts(fontpaths=font_dirs))[1]
font_list = [font_manager.FontEntry(font_file, name=font_name)]
font_manager.fontManager.ttflist.extend(font_list)
plt.rcParams['font.family'] = font_name
font_prop_italic = font_manager.FontProperties(
fname="../Source_Sans_Pro/SourceSansPro-Italic.ttf", size=8)
font_prop_bold = font_manager.FontProperties(
fname="../Source_Sans_Pro/SourceSansPro-SemiBold.ttf", size=16)
def plot_sonar(fig, ax, position, df, player_name, minutes, team_name, season,
age):
"""Creates the pizza plot for a player """
# fig, ax = plt.subplots(figsize=(6,8), subplot_kw={"projection":"polar"})
TP = 98
TC = 109
fname_cats = {AK: 'is_predicted_', AL: 'is_exp_known_', AS: 'is_similar_',
K: 'only_predicted_', L: 'only_exp_known_', S: 'only_similar_',
LK: 'known_predicted_', SK: 'similar_predicted_'}
flav_ids = ['AGI', 'BUN', 'KXN', 'HWB', 'EKXN', 'EGT', 'ERD', 'GKXN', 'GEN',
'HCC', 'KMP', 'LU2', 'MYC', 'NAR', 'QUE']
names = {'AGI': 'Apigenin', 'BUN': 'Butein', 'KXN': 'Catechin', 'HWB': 'Cyanidin',
'EKXN': 'Epicatechin', 'EGT': 'Epigallocatechin', 'ERD': 'Eriodictyol',
'GKXN': 'Gallocatechin', 'GEN': 'Genistein', 'HCC': 'Isoliquiritigenin',
'KMP': 'Kaempferol', 'LU2': 'Luteolin', 'MYC': 'Myricetin', 'NAR': 'Naringenin',
'QUE': 'Quercetin'}
fe = fm.FontEntry(fname='nunito/NunitoSans-SemiBold.ttf', name='NunitoSans-Bold')
fm.fontManager.ttflist.insert(0, fe)
plt.rcParams['font.family'] = fe.name
ftype = '.png'
def main():
rd = pd.read_excel('kegg-data.xlsx')
df = rd[['Name'] + flav_ids]
df = df.set_index('Name')
mk_tables(df)
# vennd(df)
def mk_tables(df):
try: os.mkdir('pics')
except (FileExistsError, OSError) as e: pass
try: os.mkdir('csv')