def generate_report():
report = MdUtils(file_name=f'./report.md')
report.new_header(level=1, title='Выделение признаков символов')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
report.new_line(text=f'Алфавит - {ALPHABET}')
for letter in ALPHABET:
letter_folder_path = f'./{folder_helper.IMAGES_FOLDER_PATH}/letter_{letter}'
os.makedirs(letter_folder_path, exist_ok=True)
letter_image_path = f'{letter_folder_path}/{letter}.png'
letter_image = Image.new(mode=constants.GRAYSCALE_MODE, size=(FONT_SIZE, FONT_SIZE), color=WHITE)
result = ImageDraw.Draw(im=letter_image, mode=constants.GRAYSCALE_MODE)
result.text(xy=(0, 0), text=letter, font=FONT, fill=0, anchor='lt')
letter_image = cut_empty_rows_and_cols(letter_image)
letter_image.save(letter_image_path)
report.new_header(level=2, title=f'Буква {letter}')
report.new_line(report.new_inline_image(text=letter, path=letter_image_path))
thresholded = simple_threshold(letter_image, 100)
report.new_line(text=f'Вес черного - {black_weight(thresholded)}')
report.new_line(text=f'Удельный вес черного - {normalized_black_weight(thresholded)}')
center = gravity_center(thresholded)
report.new_line(text=f'Координаты центра масс - ({center[0]}, {center[1]})')
normalized_center = normalized_gravity_center(thresholded)
report.new_line(text=f'Нормированные координаты центра масс - ({normalized_center[0]}, {normalized_center[1]})')
report.new_line(text=f'Центральный горизонтальный осевой момент - {central_horizontal_axial_moment(thresholded)}')
report.new_line(text=f'Центральный вертикальный осевой момент - {central_vertical_axial_moment(thresholded)}')
report.new_line(text=f'Нормированный центральный горизонтальный осевой момент -'
f'{normalized_central_horizontal_axial_moment(thresholded)}')
report.new_line(text=f'Нормированный центральный вертикальный осевой момент -'
f'{normalized_central_vertical_axial_moment(thresholded)}')
h_levels, h_projections = horizontal_projection(thresholded)
pyplot.plot(h_levels, h_projections)
pyplot.title(f'Horizontal projection {letter}')
path = f'{letter_folder_path}/horizontal_projection_{letter}.png'
pyplot.savefig(path)
pyplot.close()
report.new_line(report.new_inline_image(text=letter, path=path))
v_levels, v_projections = vertical_projection(thresholded)
pyplot.plot(v_levels, v_projections)
pyplot.title(f'Vertical projection {letter}')
path = f'{letter_folder_path}/vertical_projection_{letter}.png'
pyplot.savefig(path)
pyplot.close()
report.new_line(report.new_inline_image(text=letter, path=path))
report.new_line()
report.create_md_file()
def generate_report():
df_final = predictionsPerSecond()
explode = (0.1, 0.1, 0.1)
plt.pie(df_final.Label.value_counts(),
explode=explode,
labels=df_final.Label.value_counts().index.to_list(),
autopct='%1.1f%%',
shadow=True,
startangle=90)
plt.title('Tiempo de uso de mascarilla')
plt.savefig('predictions.png')
mdFile = MdUtils(
file_name='report',
title='Reporte de predicción de uso correcto de mascarilla')
mdFile.new_line(
mdFile.new_inline_image(text='Predicciones', path='predictions.png'))
mdFile.new_header(title='Tablas de resultados', level=1)
mdFile.new_line('Juan Pablo Carranza Hurtado')
mdFile.new_line('José Alberto Ligorría Taracena')
mdFile.create_md_file()
f = open("report.html", "w")
f.write(markdown2.markdown_path('report.md'))
f.write(pd.crosstab(df_final.Time, df_final.Label).to_html())
f.write('<h1> Cantidad de segundos de utilización de mascarilla </h1>')
f.write(pd.DataFrame(df_final.Label.value_counts()).to_html())
f.close()
def test_new_inline_image(self):
md_file = MdUtils(file_name="Test_file", title="")
expected_image = ''
created_image = md_file.new_inline_image(text='image',
path='../image.png')
self.assertEqual(expected_image, created_image)
def img_to_markdown(path: str) -> str:
"""
Creates a Markdown Image.
Parameters
----------
path: str
The image path.
"""
return MdUtils.new_inline_image(text=path, path=path)
link = "https://github.com/raymiranda/actions-craps/issues/new?title=Roll%20Some%20Dice&body=https://api.github.com/repos/raymiranda/action-craps/issues?title=Let%27s%20Roll%20Some%20Dice&body=Add%20your%20own%20comments"
text = "--> We need a new shooter! <--"
mdFile.new_line(mdFile.new_inline_link(link=link, text=text))
else:
d = last_line.strip().replace(" ", "").split("|")
point = d[2]
dice = d[1].split(",")
dice1 = './images/' + str(dice[0]) + '.png'
dice2 = './images/' + str(dice[1]) + '.png'
last_roll = re.sub("[^0-9]", "", d[0])
if "lets try to hit that" in last_saying:
mdFile.new_header(level=2,
title="The point is now " + str(last_roll) +
"! Let's go shooter!")
else:
mdFile.new_header(level=2,
title="Last roll was a " + str(last_roll) +
"! The point is " + str(point))
mdFile.new_line(mdFile.new_inline_image(text='Dice 1', path=dice1))
mdFile.new_line(mdFile.new_inline_image(text='Dice 2', path=dice2))
link = "https://github.com/raymiranda/actions-craps/issues/new?title=Roll%20Some%20Dice&body=https://api.github.com/repos/raymiranda/action-craps/issues?title=Let%27s%20Roll%20Some%20Dice&body=Add%20your%20own%20comments"
text = "--> The Dice Are Hot - Keep It Going! <-- "
mdFile.new_line(mdFile.new_inline_link(link=link, text=text))
# Create a table of contents
mdFile.new_table_of_contents(table_title='Contents', depth=2)
mdFile.create_md_file()
under_config = {**user_yaml, **yaml.load(static, Loader=yaml.FullLoader)}
with open(f"{submod}/_config.yml", 'w') as dest:
documents = yaml.dump(under_config, dest)
return documents
def find_recent_resume(url)->str:
import glob
season = {'W': 4, 'F': 3, 'X': 2, 'S': 1}
recent_sort = lambda r: (r[-7], r[-6], season.get(r[-5], 0))
s = max((r.split("/docs/")[1] for r in glob.glob(f"./{url}/docs/Resume_*.pdf")), key=recent_sort)
return s
# Generate markdowns
if updategithub:
mdReadMe = MdUtils(file_name='README') #include some flags
mdReadMe.new_line(mdReadMe.new_inline_image(text='image', path='https://github.com/kevinfjiang/kevinfjiang/blob/master/hello_world.png'))
# Read existing yamls
# Intro and config
logger.debug("Opening user.yml")
with open(PATH+"user.yml") as user:
user_info = yaml.load(user, Loader=yaml.FullLoader)
submod = user_info['url']
logger.debug(f"submod path is {submod}")
alt_badges = [button_templates[key].format(user_info[key])
for key in ["github_username", "spotify_username"]]
if not keep_resume:
import googleapiclient
from oauth2client.service_account import ServiceAccountCredentials
def neuron2md(nt, neuron, doc_path):
"""
name: str (analyzers or responders)
neuron: str
doc_path: str
"""
# Title
neuron_path = path.join(nt, neuron)
mdFile = MdUtils(file_name="{}.md".format(neuron), title="")
mdFile.new_header(level=1, title=neuron)
# add README.md file in description
mdFile.new_line()
if 'README.md' in listdir(neuron_path):
readme = open("{}/README.md".format(neuron_path), 'r')
mdFile.new_line("!!! abstract \"README\"")
mdFile.new_paragraph(" {}".format(readme.read().replace(
'\n', '\n ')))
readme.close
#print(neuron)
# Analyzers or Responders flavors
for f in listdir(path.join(nt, neuron)):
if nt in ["analyzers", "responders"] and f.endswith(".json"):
with open(path.join(neuron_path, f), 'r') as fc:
config = json.load(fc)
# Title
mdFile.new_header(level=2, title=config.get('name'))
# Logo
if config.get('service_logo'):
logo_path = config.get('service_logo').get('path')
logo_src_path = path.join(neuron_path, logo_path)
if path.exists(logo_src_path) and logo_path != "":
logo_filename = path.basename(logo_path)
ext = logo_filename.split('.')[-1]
logo_filename = logo_filename.split('.')[0]
logo_filename = "{}_logo.{}".format(
f.split('.')[0], ext)
logo_md_path = path.join("assets", logo_filename)
logo_dest_path = path.join(doc_path, nt, logo_md_path)
copy(logo_src_path, logo_dest_path)
logo_md_path = path.join(
"../",
logo_md_path) ## trick to make Html.image work
mdFile.new_paragraph(
Html.image(path=logo_md_path,
size='150',
align='center'))
mdFile.new_line()
# Identity
mdFile.new_line("!!! note \"\"")
mdFile.new_line(" **Author**: _{}_".format(
config.get('author')))
mdFile.new_line(" **License**: _{}_".format(
config.get('license')))
mdFile.new_line(" **Version**: _{}_".format(
config.get('version')))
if nt == "analyzers":
mdFile.new_line(" **Supported observables types**:")
else:
mdFile.new_line(" **Supported data types**:")
for item in config.get('dataTypeList'):
mdFile.new_line(" - {}".format(item))
mdFile.new_line(" **Registration required**: \
_{}_".format(config.get('registration_required', 'N/A')))
mdFile.new_line(" **Subscription required**: \
_{}_".format(config.get('subscription_required', 'N/A')))
mdFile.new_line(" **Free subscription**: \
_{}_".format(config.get('free_subscription', 'N/A')))
mdFile.new_line(' **Third party service**: '+\
mdFile.new_inline_link(link=config.get('service_homepage', 'N/A'), text=config.get('service_homepage', 'N/A')))
# Description
mdFile.new_line()
mdFile.new_header(level=3, title='Description')
mdFile.new_paragraph(config.get('description', 'N/A'))
# Configuration
mdFile.new_line()
mdFile.new_header(level=3, title='Configuration')
if config.get('configurationItems') and len(
config.get('configurationItems')) > 0:
for c in config.get('configurationItems'):
configuration_items = [
"**{}**".format(c.get('name')),
c.get('description', 'No description')
]
configuration_items.extend([
"**Default value if not configured**",
"_{}_".format(c.get('defaultValue', 'N/A'))
])
configuration_items.extend([
"**Type of the configuration item**",
"_{}_".format(c.get('type'))
])
configuration_items.extend([
"**The configuration item can contain multiple values**",
"_{}_".format(c.get('multi'))
])
configuration_items.extend([
"**Is required**", "_{}_".format(c.get('required'))
])
mdFile.new_line()
mdFile.new_table(columns=2,
rows=5,
text=configuration_items,
text_align='left')
else:
mdFile.new_paragraph("No specific configuration required.")
# Notes.md file
if 'notes.md' in listdir(neuron_path):
notes = open("{}/notes.md".format(neuron_path), 'r')
mdFile.new_line("!!! tip \"Developer notes\"")
mdFile.new_paragraph(" {}".format(notes.read().replace(
'\n', '\n ')))
notes.close
# Analysers report samples
if nt == "analyzers" and f.endswith(".json"):
# Templates for TheHive
mdFile.new_line()
mdFile.new_header(level=3, title='Templates samples for TheHive')
## Copy images files to destination folder
base_neuronname = f.split('.')[0]
if config.get('screenshots'):
for idx, sc in enumerate(config.get('screenshots')):
sc_path = sc.get('path')
sc_src_path = path.join(neuron_path, sc.get('path'))
if path.exists(sc_src_path):
sc_filename = path.basename(sc.get('path'))
ext = sc_filename.split('.')[-1]
sc_filename = path.basename(f).split('.')[0]
sc_filename = "{}_{}.{}".format(sc_filename, idx, ext)
sc_md_path = path.join("assets", sc_filename)
sc_dest_path = path.join(doc_path, nt, sc_md_path)
copy(sc_src_path, sc_dest_path)
mdFile.new_paragraph(
mdFile.new_inline_image(text=sc.get(
'caption', 'screenshot'),
path=sc_md_path))
else:
mdFile.new_paragraph("No template samples to display.")
# Save md file
dest_dir = path.join(doc_path, nt)
if not path.exists(dest_dir):
makedirs(dest_dir)
olddir = path.abspath(path.curdir)
chdir(dest_dir)
mdFile.create_md_file()
chdir(olddir)
class DataAnalyzer(object):
def __init__(self, data_path):
self._images_path = os.path.join(data_path, 'images')
self._parser = Parser(data_path)
self._results = MdUtils(file_name='results', title='Overview')
self._num_images = None
self._counts = None
self._image_shape = None
self._image_shape_mean = None
def _compute_stats(self):
self._num_images = self._parser.data.shape[1]
self._counts = self._parser.data.loc['anomaly_class'].value_counts(
).to_dict()
def _plot_random_image(self):
random_image_file = f'{random.randint(0, self._num_images)}.jpg'
image = img.imread(os.path.join(self._images_path, random_image_file))
self._image_shape = image.shape
fig = plt.figure()
plt.tight_layout()
plt.imshow(image)
plt.xticks([]), plt.yticks([])
plt.tight_layout()
plt.title('Random Image')
plt.savefig('random_image.png')
plt.close(fig)
plt.figure()
plt.tight_layout()
plt.hist(image.flatten())
plt.xlabel('Pixel Value')
plt.ylabel('Counts')
plt.title('Histogram')
plt.savefig('random_image_histogram.png')
plt.close(fig)
def _compute_mean_shape(self):
h, w = [], []
for im in self._parser.image_list:
print(f'Reading image: {im}')
image = img.imread(os.path.join(self._images_path, im))
h.append(image.shape[0])
w.append(image.shape[1])
self._image_shape_mean = (np.mean(h), np.mean(w))
def _plot_image_each_class(self):
fig = plt.figure(figsize=(10, 10))
plt.tight_layout()
plt.title('Random Image In Each Class')
i = 1
for label in self._parser.labels:
image_list = self._parser.get_label_images(label)
random_selection = random.choice(image_list)
image_path = self._parser.data.loc['image_filepath'].tolist(
)[random_selection]
image = img.imread(os.path.join(self._images_path, image_path[7:]))
plt.subplot(4, 3, i)
i += 1
plt.subplots_adjust(hspace=1, wspace=1)
plt.title(f'Class: {label}')
cur_axes = plt.gca()
cur_axes.axes.get_xaxis().set_ticks([])
cur_axes.axes.get_yaxis().set_ticks([])
plt.imshow(np.uint8(image))
plt.savefig('random_image_each_class.png')
plt.close(fig)
def analyze(self):
self._parser.parse()
self._compute_stats()
self._plot_random_image()
self._compute_mean_shape()
self._plot_image_each_class()
def save_results(self):
self._results.new_paragraph(f'Number of images: {self._num_images}')
self._results.new_paragraph(
f'Number of unique classes: {len(self._parser.labels)}')
self._results.new_paragraph(f'Class names:')
self._results.new_list(items=self._parser.labels)
self._results.new_paragraph(f'Number of images per class: ')
self._results.new_list(
items=[f'{k}: {v}' for k, v in self._counts.items()])
self._results.new_paragraph(f'Image shape: {self._image_shape}')
self._results.new_paragraph(
f'Mean Image shape: {self._image_shape_mean}')
self._results.new_paragraph(
self._results.new_inline_image(text='Random Image',
path='random_image.png'))
self._results.new_paragraph(
self._results.new_inline_image(text='Histogram',
path='random_image_histogram.png'))
self._results.new_paragraph(
self._results.new_inline_image(text='Classes',
path='random_image_each_class.png'))
self._results.create_md_file()
def main():
#-----Getting parser-----#
args = get_parser()
ProducedIsotopes = []
if args.Energy is not None:
ProducedIsotopes = data_extractor(args.Infile, args.Energy)
else:
print(colored('ERROR :', 'red'), ' Energy not provided')
raise SystemExit
try:
os.mkdir(args.Outfolder)
except:
print(colored('WARNING :', 'yellow'),
" Output folder already exist. All content will be replaced")
finally:
os.system('rm -r ' + args.Outfolder)
os.mkdir(args.Outfolder)
os.mkdir(args.Outfolder + '/Images')
Primary = PrimaryProduction(args.XsecTh, ProducedIsotopes)
Second = NextProduction(Primary)
Third = NextProduction(Second)
# print(Primary)
# print(Second)
# print(Third)
mdFile = MdUtils(file_name=args.Outfolder + '/Resume',
title='ENSDF Resume')
blacklist = []
for iso in Primary:
E = []
M = []
HL = []
flag = args.Levels
levelflag = True
nucleon = iso['A']
proton = iso['Z']
try:
E, M, HL = list_levels(nucleons=nucleon, protons=proton)
levelflag = level_scheme(nucleons=nucleon,
protons=proton,
filename=args.Outfolder + '/Images/' +
str(proton) + str(nucleon) + '.png')
except:
flag = False
El = element(proton)
title = str(nucleon) + El.symbol
blacklist.append(title)
mdFile.new_header(3, title)
mdFile.new_line("Element " + title +
" direct production cross section -> " +
str(iso['Xsec']) + " mb")
x = checkisopresence(iso['Z'], iso['A'], Second)
y = checkisopresence(iso['Z'], iso['A'], Third)
if x != -1:
Z, A = decayreverse(Second[x]['Z'], Second[x]['A'],
Second[x]['Prev'])
El2 = element(Z)
title2 = str(A) + El2.symbol
mdFile.new_line("Second generation production cross section -> " +
str(Second[x]['Xsec']) + " mb")
mdFile.new_line("Coming from " + Second[x]['Prev'] + " decay of " +
title2)
if y != -1:
Z, A = decayreverse(Third[y]['Z'], Third[y]['A'], Third[y]['Prev'])
El2 = element(Z)
title2 = str(A) + El2.symbol
mdFile.new_line("Third generation production cross section -> " +
str(Third[y]['Xsec']) + " mb")
mdFile.new_line("Coming from " + Third[y]['Prev'] + " decay of " +
title2)
if flag:
list_of_levels = ["Energy", "Jπ", "λ"]
for index in range(len(E)):
list_of_levels.extend(
[f"{E[index]}", f"{M[index]}", HL[index]])
mdFile.new_line()
mdFile.new_table(columns=3,
rows=len(E) + 1,
text=list_of_levels,
text_align='left')
# if levelflag :
# mdFile.new_line(mdFile.new_inline_image(text=title, path='Images/'+Isotope[1]+'.png'))
for iso in Second:
E = []
M = []
HL = []
flag = args.Levels
levelflag = True
nucleon = iso['A']
proton = iso['Z']
El = element(proton)
title = str(nucleon) + El.symbol
if title not in blacklist:
blacklist.append(title)
try:
E, M, HL = list_levels(nucleons=nucleon, protons=proton)
levelflag = level_scheme(nucleons=nucleon,
protons=proton,
filename=args.Outfolder + '/Images/' +
str(proton) + str(nucleon) + '.png')
except:
flag = False
mdFile.new_header(3, title)
Z, A = decayreverse(iso['Z'], iso['A'], iso['Prev'])
El2 = element(Z)
title2 = str(A) + El2.symbol
mdFile.new_line("Second generation production cross section -> " +
str(iso['Xsec']) + " mb")
mdFile.new_line("Coming from " + iso['Prev'] + " decay of " +
title2)
if flag:
list_of_levels = ["Energy", "Jπ", "λ"]
for index in range(len(E)):
list_of_levels.extend(
[f"{E[index]}", f"{M[index]}", HL[index]])
mdFile.new_line()
mdFile.new_table(columns=3,
rows=len(E) + 1,
text=list_of_levels,
text_align='left')
# if levelflag :
# mdFile.new_line(mdFile.new_inline_image(text=title, path='Images/'+Isotope[1]+'.png'))
for iso in Third:
E = []
M = []
HL = []
flag = args.Levels
levelflag = True
nucleon = iso['A']
proton = iso['Z']
El = element(proton)
title = str(nucleon) + El.symbol
if title not in blacklist:
blacklist.append(title)
try:
E, M, HL = list_levels(nucleons=nucleon, protons=proton)
levelflag = level_scheme(nucleons=nucleon,
protons=proton,
filename=args.Outfolder + '/Images/' +
str(proton) + str(nucleon) + '.png')
except:
flag = False
mdFile.new_header(3, title)
Z, A = decayreverse(iso['Z'], iso['A'], iso['Prev'])
El2 = element(Z)
title2 = str(A) + El2.symbol
mdFile.new_line("Third generation production cross section -> " +
str(iso['Xsec']) + " mb")
mdFile.new_line("Coming from " + iso['Prev'] + " decay of " +
title2)
if flag:
list_of_levels = ["Energy", "Jπ", "λ"]
for index in range(len(E)):
list_of_levels.extend(
[f"{E[index]}", f"{M[index]}", HL[index]])
mdFile.new_line()
mdFile.new_table(columns=3,
rows=len(E) + 1,
text=list_of_levels,
text_align='left')
# if levelflag :
# mdFile.new_line(mdFile.new_inline_image(text=title, path='Images/'+Isotope[1]+'.png'))
cmdstr = ''
for el in blacklist:
cmdstr += ' --Produced ' + el
os.system('python ChartDrawer.py --n 129 148 --z 85 97 nubase16.xml ' +
args.Outfolder + '/chart.svg ' + cmdstr)
os.system('inkscape ' + args.Outfolder + '/chart.svg --export-filename ' +
args.Outfolder + '/chart.pdf')
mdFile.new_line(
mdFile.new_inline_image(text="Production Nuclide Chart",
path=args.Outfolder + '/chart.png'))
mdFile.create_md_file()
os.system('grip -b ' + args.Outfolder + '/Resume.md')
os.system('xdg-open ' + args.Outfolder + '/chart.pdf')
mdFile.new_header(2, "Add images")
# *********************************************** Inline Image *******************************************************
image_text = "snow trees"
path = "./doc/source/images/photo-of-snow-covered-trees.jpg"
mdFile.new_header(3, "Inline Images")
mdFile.new_paragraph(
"You can add inline images using ``new_inline_image`` method. Method will return: "
"``[image](../path/to/your/image.png)``. Check the following example: ")
mdFile.insert_code(
"mdFile.new_line(mdFile.new_inline_image(text='{}', path='{}'))".format(
image_text, path))
mdFile.new_line(mdFile.new_inline_image(text=image_text, path=path))
# *********************************************** Reference Image ****************************************************
mdFile.new_header(3, "Reference Images")
mdFile.new_paragraph(
"You can add inline images using ``new_reference_image`` method. Method will return: "
"``[image][im]``. Check the following example: ")
mdFile.insert_code(
"mdFile.new_line(mdFile.new_reference_image(text='{}', path='{}', reference_tag='im'))"
.format(image_text, path))
mdFile.new_line(
mdFile.new_reference_image(text=image_text, path=path, reference_tag='im'))
# ************************************************* Html Image *******************************************************
mdFile.new_header(2, "Add HTML images")
