def import_andalusian_catalog(request):
message=""
if request.method == 'POST':
form = forms.CsvAndalusianCatalogForm(request.POST, request.FILES)
if form.is_valid():
transliterator = ALA_LC_Transliterator()
vocalizer=TashkeelClass()
omited = 0
csv_file = form.cleaned_data['csv_file']
reader = csv.reader(csv_file.read().splitlines())
next(reader)
for row in reader:
genre = row[0]
rec_mbid = row[11]
nawba = row[14]
tab = row[15]
form = row[16]
mizan = row[17]
if rec_mbid:
section_start = row[18]
section_end = row[19]
genre, created = andalusian.models.Genre.objects.get_or_create(name = genre.decode('utf8'))
rec = andalusian.models.Recording.objects.get(mbid = rec_mbid)
sec, created = andalusian.models.Section.objects.get_or_create(recording=rec, start_time=section_start, end_time=section_end)
tab = andalusian.models.Tab.objects.get(name=tab.decode('utf8'))
form = andalusian.models.Form.objects.get(name=form.decode('utf8'))
nawba = andalusian.models.Nawba.objects.get(name=nawba.decode('utf8'))
mizan = andalusian.models.Mizan.objects.get(name=mizan.decode('utf8'))
voc = vocalizer.tashkeel(row[0].decode('utf8'))
tr = transliterator.do(voc.strip())
genre.transliterated_name = arabic_reshaper.reshape(tr)
genre.save()
voc = vocalizer.tashkeel(rec.title)
tr = transliterator.do(voc.strip())
rec.transliterated_title = arabic_reshaper.reshape(tr)
rec.genre = genre
rec.save()
sec.mizan = mizan
sec.tab = tab
sec.form = form
sec.nawba = nawba
sec.save()
else:
omited += 1
message = "The elements has been successfully loaded"
if omited:
message += "(%d rows omited)" % omited
else:
form = forms.CsvAndalusianCatalogForm()
params = {"form": form, "message": message}
return render(request, "dashboard/load_catalog_csv.html", params)
def import_andalusian_elements(request):
message=""
if request.method == 'POST':
form = forms.CsvAndalusianForm(request.POST, request.FILES)
if form.is_valid():
transliterator = ALA_LC_Transliterator()
vocalizer=TashkeelClass()
csv_file = form.cleaned_data['csv_file']
reader = csv.reader(csv_file.read().splitlines())
klass = None
if form.cleaned_data['elem_type'] == 'tabs':
klass = andalusian.models.Tab
elif form.cleaned_data['elem_type'] == 'nawbas':
klass = andalusian.models.Nawba
elif form.cleaned_data['elem_type'] == 'forms':
klass = andalusian.models.Form
elif form.cleaned_data['elem_type'] == 'mizans':
klass = andalusian.models.Mizan
if klass:
for row in reader:
elem, created = klass.objects.get_or_create(name = row[0].decode('utf8'))
voc = vocalizer.tashkeel(row[0].decode('utf8'))
tr = transliterator.do(voc.strip())
elem.transliterated_name = arabic_reshaper.reshape(tr)
elem.save()
message = "The elements has been successfully loaded"
else:
form = forms.CsvAndalusianForm()
params = {"form": form, "message": message}
return render(request, "dashboard/load_csv.html", params)
def text(self, text):
"""The text to be rendered. Use \\\\n to make new lines.
Issues: May be slow, and pyglet has a memory leak when setting text.
For these reasons, this function checks so that it only updates the
text if it has changed. So scripts can safely set the text on every
frame, with no need to check if it has actually altered.
"""
if text == self.text: # only update for a change
return
if text is not None:
text = str(text) # make sure we have unicode object to render
# deal with some international text issues. Only relevant for Python:
# online experiments use web technologies and handle this seamlessly.
style = self.languageStyle.lower() # be flexible with case
if style == 'arabic' and haveArabic:
# reshape Arabic characters from their isolated form so that
# they flow and join correctly to their neighbours:
text = arabic_reshaper.reshape(text)
if style == 'rtl' or style == 'arabic' and haveArabic:
# deal with right-to-left text presentation by applying the
# bidirectional algorithm:
text = bidi_algorithm.get_display(text)
# no action needed for default 'ltr' (left-to-right) option
self.__dict__['text'] = text
if self.useShaders:
self._setTextShaders(text)
else:
self._setTextNoShaders(text)
self._needSetText = False
def reshape(text):
"""Reshapes arabic in order to display characters from right to left
"""
if platform.system() == "Darwin":
return text
else:
reshaped_text = arabic_reshaper.reshape(text)
bidi_text = get_display(reshaped_text)
return bidi_text
def get_dictionary():
arabicWords = [
arabic_reshaper.reshape(u"وزارة"),
arabic_reshaper.reshape(u"الشؤون"),
arabic_reshaper.reshape(u"الخارجيّة"),
arabic_reshaper.reshape(u"شمس"),
arabic_reshaper.reshape(u"الله"),
arabic_reshaper.reshape(u"نبي"),
arabic_reshaper.reshape(u"عام"),
arabic_reshaper.reshape(u"مليون"),
]
return arabicWords
def create_images(label,count=100,font_size = 17):
# here we want to create count images of label with
# different filters/rotations etc..
img = Image.new("L", (100, 100),200)
draw=ImageDraw.Draw(img)
font=ImageFont.truetype("/Library/Fonts/Arial Unicode.ttf", font_size)
label_correct = arabic_reshaper.reshape(label)
label_correct = get_display(label_correct)
draw.text((22,22),label_correct,font=font)
img.save('pics/' +label + '.png')
img.close()
def renderImage(word, label):
reshaped = arabic_reshaper.reshape(u"%s" % word)
bidi = get_display(reshaped)
for f in fList:
#print(f)
font = ImageFont.truetype(fFolder+f, fntSize)
width, height = font.getsize(reshaped)
img = Image.new('RGB', (width, height), "white")
d = ImageDraw.Draw(img)
d.text((0, 0), bidi, fill="black", font=font)
img.save(iFolder+"%s_%s_%s.png" % (label, str(fntSize), f[:-4]))
def process_single_image(word, label, size, fontsize = 50, loc = (25,25)):
if not os.path.exists('pics/' + label):
os.makedirs('pics/' + label)
img = Image.new("L", size ,256) # greyscale and white background
draw = ImageDraw.Draw(img)
font = ImageFont.truetype("/Library/Fonts/Arial Unicode.ttf", fontsize)
label_correct = arabic_reshaper.reshape(word)
label_correct = get_display(label_correct)
draw.text(loc,label_correct,font=font)
direc = 'pics/'+label
img.save(direc + '/original.png')
img.close()
# now we've created the base picture - now we can process it a bit more
create_copies(direc, '/original.png')
def _formatText(self, text):
"Generates PDF text output operator(s)"
canv = self._canvas
font = pdfmetrics.getFont(self._fontname)
R = []
# Adding Unicode BiDirection Support
# Refer to http://github.com/barsi/openerp-rtl
# for more info
try:
text = type(text) == type(u"") and text or text.decode("utf8")
reshaped_text = arabic_reshaper.reshape(text)
text = get_display(reshaped_text)
except UnicodeDecodeError, e:
i, j = e.args[2:4]
raise UnicodeDecodeError(
*(
e.args[:4]
+ ("%s\n%s==[%s]==%s" % (e.args[4], text[max(i - 10, 0) : i], text[i:j], text[j : j + 10]),)
)
)
def draw_text_using_font(text, font_path):
reshaped_text = arabic_reshaper.reshape(text)
bidi_text = get_display(reshaped_text)
image = Image.new("RGBA", (700, 500), (255, 255, 255))
draw = ImageDraw.Draw(image)
font = ImageFont.truetype(font_path, 100)
draw.text((0, 0), bidi_text, (0, 0, 0), font=font)
width, height = draw.textsize(bidi_text, font=font)
image_frames = []
for i in xrange(len(bidi_text)):
line = bidi_text[:i + 1]
symbol = bidi_text[i:i + 1]
w, _ = draw.textsize(line, font=font)
line_frame = [(0, 0), (w, height)]
symbol_width, _ = draw.textsize(symbol, font=font)
symbol_frame = [(w - symbol_width, 0), (symbol_width, height)]
image_frames.append({'symbol': symbol,
'frame' : symbol_frame})
draw.rectangle(line_frame, outline=(0, 0, 0))
return image, image_frames
def Camera():
camera = cv2.VideoCapture(0)
while True:
value, frame = camera.read()
frame = cv2.resize(frame, (600, 500))
blob = cv2.dnn.blobFromImage(frame,
0.00392, (416, 416), (0, 0, 0),
True,
crop=False)
net.setInput(blob)
layer_names = net.getLayerNames()
output_layers = [
layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()
]
output_layers = net.forward(output_layers)
class_ids = []
confidences = []
boxes = []
key = cv2.waitKey(1)
for out in output_layers:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
center_x = int(detection[0] * frame.shape[1])
center_y = int(detection[1] * frame.shape[0])
w = int(detection[2] * frame.shape[1])
h = int(detection[3] * frame.shape[0])
x = center_x - w / 2
y = center_y - h / 2
class_ids.append(class_id)
confidences.append(float(confidence))
boxes.append([x, y, w, h])
indices = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
for i in indices:
i = i[0]
box = boxes[i]
x = box[0]
y = box[1]
w = box[2]
h = box[3]
text = str(classes[class_ids[i]][1])
font = ImageFont.truetype("font.ttf", 35)
reshaped_text = arabic_reshaper.reshape(text)
arabic_text = get_display(reshaped_text)
#print(arabic_text)
image_pil = Image.fromarray(frame)
draw = ImageDraw.Draw(image_pil)
draw.text((round(x), round(y) - 50),
arabic_text, (255, 255, 255),
font=font)
frame = np.array(image_pil)
cv2.rectangle(frame, (round(x), round(y)),
(round(x + w), round(y + h)), (255, 255, 255), 2)
#cv2.putText(frame, "{:.0f}%".format(confidences[i]*100), (round(x),round(y)-40), cv2.FONT_HERSHEY_SIMPLEX, 1,(0,0,0), 2)
cv2.imshow("Object Detection Using YOLOv3", frame)
if key == 27:
break
cv2.destroyAllWindows()
camera.release()
def reshape_arabic_text(text):
return get_display(arabic_reshaper.reshape(text))
def __init__(self, **kwargs):
super(Ar_text, self).__init__(**kwargs)
self.text = get_display(arabic_reshaper.reshape(""))
def drawTextAtMiddle(imageWidth, draw, text, y, fontSize, color):
font = ImageFont.truetype('IRANSansWeb (1).ttf', size=fontSize)
reshaped_text = arabic_reshaper.reshape(text)
bidi_text = get_display(reshaped_text)
w, h = font.getsize(bidi_text)
draw.text((((imageWidth - w) / 2), y), bidi_text, fill=color, font=font)
# -*- coding: UTF-8 -*-
import arabic_reshaper
from bidi.algorithm import get_display
from reportlab.platypus import SimpleDocTemplate, Paragraph
from reportlab.pdfbase import pdfmetrics
from reportlab.lib.styles import ParagraphStyle
from reportlab.lib.enums import TA_RIGHT
from reportlab.lib.pagesizes import A4
from reportlab.pdfbase.ttfonts import TTFont
arabic_text = u'تلفون'
new_word = ''
for i in arabic_text[::-1]:
new_word = new_word+i
arabic_text = arabic_reshaper.reshape(arabic_text)
new_word = arabic_reshaper.reshape(new_word) # join characters
# arabic_text = get_display(arabic_text) # change orientation by using bidi
pdf_file=open('disclaimer.pdf','w')
pdf_doc = SimpleDocTemplate(pdf_file, pagesize=A4)
pdfmetrics.registerFont(TTFont('Arabic-normal', 'KacstOne.ttf'))
style = ParagraphStyle(name='Normal', fontName='Arabic-normal', fontSize=12, leading=12. * 1.2)
style.alignment=TA_RIGHT
pdf_doc.build([Paragraph(arabic_text, style)])
pdf_doc.build([Paragraph(arabic_text[::-1], style)])
pdf_file.close()
def get_arabic_string(string):
reshaped_text = arabic_reshaper.reshape(string)
bidi_text = get_display(reshaped_text)
return bidi_text
def Processing_Image(Image, destination):
test = Image
large = cv2.imread(test)
large = cv2.resize(large, (800, 850))
large = cv2.fastNlMeansDenoisingColored(large, None, 10, 10, 7, 21)
rgb = cv2.pyrDown(large)
small = cv2.cvtColor(rgb, cv2.COLOR_BGR2GRAY)
k = small
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (4, 2))
grad = cv2.morphologyEx(small, cv2.MORPH_GRADIENT, kernel)
_, bw = cv2.threshold(grad, 0.0, 255.0,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (4, 1))
connected = cv2.morphologyEx(bw, cv2.MORPH_CLOSE, kernel)
_, contours, _ = cv2.findContours(connected.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_NONE)
mask = np.zeros(bw.shape, dtype=np.uint8)
translator = Translator()
pytesseract.pytesseract.tesseract_cmd = "C:\\Program Files (x86)\\Tesseract-OCR\\tesseract.exe"
for idx in range(len(contours)):
x, y, w, h = cv2.boundingRect(contours[idx])
mask[y:y + h, x:x + w] = 0
cv2.drawContours(mask, contours, idx, (255, 255, 255), -1)
r = float(cv2.countNonZero(mask[y:y + h, x:x + w])) / (w * h)
if r > 0.45 and w > 20 and h > 10:
temp = k[y:y + 3 + h, x:x + 3 + w]
#_, bw = cv2.threshold(temp, 0.0, 255.0, cv2.ADAPTIVE_THRESH_GAUSSIAN_C | cv2.THRESH_OTSU)
#cv2.imshow('rects', bw)
#cv2.waitKey(0)
text = pytesseract.image_to_string(temp, lang='eng+deu')
if (text != ''):
#rgb[y:y + 3 + h, x:x + 3 + w]=temp[5,5]
print("The text is: ", text)
file = open("test.txt", "w", encoding="utf-8")
pass
file.write(str(text))
file.close()
c = detect_forth_tested("test.txt")
if (c == "eng"):
c = 'English'
elif (c == "fre"):
c = "French"
else:
c = "German"
cv2.rectangle(rgb, (x - 3, y), (x + w, y + h), (0, 255, 0), 1)
print('the language is: ', c)
try:
t = translator.translate(text, dest=destination, src=c)
except:
print(
"Translation Error ... Check the internet connection")
exit()
print('the translation is: ', t.text)
h1 = t.text
h1 = h1.replace('\n', ' ')
d = ImageDraw.Draw(rgb)
reshaped_text = arabic_reshaper.reshape(t.text)
bidi_text = get_display(reshaped_text)
font = cv2.FONT_HERSHEY_SIMPLEX
if (temp[0, 0] >= 240):
rgb[y:y + 3 + h, x:x + 3 + w] = temp[0, 0]
#cv2.putText(rgb, bidi_text, (x, y +13), font, 0.5, (0, 0, 0), 2, cv2.LINE_AA)
d.text((x, y + 13),
bidi_text,
font=font,
fill=(0, 255, 255, 255))
else:
#cv2.putText(rgb, bidi_text, (x, y -3), font, 0.5, (255, 255, 255), 2, cv2.LINE_AA)
d.text((x, y + 13),
bidi_text,
font=font,
fill=(0, 255, 255, 255))
else:
cv2.rectangle(rgb, (x, y), (x + w, y + h), (0, 0, 255), 1)
if (float(time.time() - start_time) >= 60):
print("%.2f minutes" % (float(time.time() - start_time) / 60))
else:
print("%.2f seconds" % (time.time() - start_time))
cv2.imshow('rects', rgb)
cv2.waitKey(0)
import arabic_reshaper
text_to_be_reshaped = 'اللغة العربية رائعة'
reshaped_text = arabic_reshaper.reshape(text_to_be_reshaped)
print(reshaped_text)
from arabic_reshaper import ArabicReshaper
configuration = {
'delete_harakat': False,
'support_ligatures': True,
'RIAL SIGN': True, # Replace ر ي ا ل with ﷼
}
reshaper = ArabicReshaper(configuration=configuration)
l1='ل'
l2='ا'
l3='ر'
l4='ي'
text_to_be_reshaped = 'ب ﺭ ﻱ ﺕ' # had to split the string for display
reshaped_text = reshaper.reshape(text_to_be_reshaped.replace(' ',''))
print(reshaped_text)
def CleanMOJUsingSVM(data, lands, villas, save_svm_plots, save_aqar_plots,
cityName):
if len(villas) == 0:
TransactionsTemp = []
for item in data:
tempr = []
for i, ele in enumerate(item):
tempr.append(ele)
tempr.append(0)
tempr.append(1.0)
TransactionsTemp.append(tempr)
return np.array(TransactionsTemp)
directory = "MOHplots/"
if not os.path.exists(directory + ""):
os.mkdir(directory + "/")
if save_svm_plots: os.mkdir(directory + "/SVM Plots/")
if save_aqar_plots: os.mkdir(directory + "/Aqar Plots/")
city = cityName
if save_svm_plots and not os.path.exists(directory + "/SVM Plots/" + city +
"/"):
os.mkdir(directory + "/SVM Plots/" + city + "/")
if save_aqar_plots and not os.path.exists(directory + "/Aqar Plots/" +
city + "/"):
os.mkdir(directory + "/Aqar Plots/" + city + "/")
aqar = read_aqar_data(city, lands, villas)
ranked2 = sorted([(len(values), key) for key, values in aqar.items()],
reverse=True)
names = {}
if city in merge:
for nameList in merge[city]:
name = min(nameList, key=len)
for n in nameList:
names[n] = name
for neigh in aqar:
if neigh not in names: names[neigh] = neigh
X = []
index = {neigh: i for i, neigh in enumerate(aqar)}
for count, neigh in ranked2:
for x, y, c in aqar[neigh]:
if not (np.isnan(x) or np.isnan(y)):
c2 = 0 if c == 'Land' else 1
X.append(
[c2, x, y] +
[1 if i == index[neigh] else 0 for i in range(len(aqar))])
random.shuffle(X)
X_train = [x[1:] for x in X]
X_label = [x[0] for x in X]
clf = svm.SVC(kernel='rbf', probability=True)
clf.fit(X_train, X_label)
nbh = {}
#with open(directory + "Data/" + city + "-Final-MOJ.csv", 'r') as f:
#data = [ row.split(',') for row in f.read().splitlines() ]
#MOJ data
columns = {n: i for i, n in enumerate(data[0])}
if "NewNeighborhood" in columns: name = columns["NewNeighborhood"]
elif "OriginalName" in columns: name = columns["OriginalName"]
else: name = columns["Neighborhood"]
#name = 13
data2 = [[names[unicode(d[name])],
float(d[9]),
float(d[10]), i] for i, d in enumerate(data)
if i > 0 and unicode(d[name]) in names and len(d) > 10
] #and d[0] == '1437' ]
for neigh, area, ppm, i in data2:
if neigh not in nbh: nbh[neigh] = []
nbh[neigh].append([np.log(area), np.log(ppm), i])
for n in nbh:
nbh[n] = [(a, p, i) for a, p, i in nbh[n]
if np.isfinite(a) and np.isfinite(p)]
colors = [
'aliceblue', 'antiquewhite', 'aqua', 'aquamarine', 'azure', 'beige',
'bisque', 'blanchedalmond', 'blue', 'blueviolet', 'brown', 'burlywood',
'cadetblue', 'chartreuse', 'chocolate', 'coral', 'cornflowerblue',
'cornsilk', 'crimson', 'cyan', 'darkcyan', 'darkgoldenrod',
'darkkhaki', 'darkmagenta', 'darkorange', 'darkorchid', 'darkred',
'darksalmon', 'darkturquoise', 'deeppink', 'deepskyblue', 'dimgray',
'dodgerblue', 'firebrick', 'floralwhite', 'forestgreen', 'fuchsia',
'gainsboro', 'ghostwhite', 'gold', 'goldenrod', 'gray', 'green',
'greenyellow', 'honeydew', 'hotpink', 'indianred', 'khaki', 'lavender',
'lavenderblush', 'lawngreen', 'lemonchiffon', 'lightblue',
'lightcoral', 'lightcyan', 'lightgoldenrodyellow', 'lightgreen',
'lightgray', 'lightpink', 'lightsalmon', 'lightseagreen',
'lightskyblue', 'lightslategray', 'lightsteelblue', 'lightyellow',
'lime', 'limegreen', 'linen', 'magenta', 'maroon', 'mediumaquamarine',
'mediumblue', 'mediumorchid', 'mediumpurple', 'mediumseagreen',
'mediumslateblue', 'mediumspringgreen', 'mediumturquoise',
'mediumvioletred', 'mintcream', 'mistyrose', 'moccasin', 'navajowhite',
'oldlace', 'olive', 'olivedrab', 'orange', 'orangered', 'orchid',
'palegoldenrod', 'palegreen', 'paleturquoise', 'palevioletred',
'papayawhip', 'peachpuff', 'peru', 'pink', 'plum', 'powderblue',
'purple', 'red', 'rosybrown', 'royalblue', 'saddlebrown', 'salmon',
'sandybrown', 'seagreen', 'seashell', 'sienna', 'silver', 'skyblue',
'slateblue', 'slategray', 'snow', 'springgreen', 'steelblue', 'tan',
'teal', 'thistle', 'tomato', 'turquoise', 'violet', 'wheat', 'white',
'whitesmoke', 'yellow', 'yellowgreen'
]
random.shuffle(colors)
ranked = sorted([(len(values), key) for key, values in nbh.items()],
reverse=True)
for count, neigh in ranked[:]:
if neigh not in aqar: continue
X_train = []
for x, y, i in nbh[neigh]:
X_train.append(
[x, y] +
[1 if i == index[neigh] else 0 for i in range(len(aqar))])
X_labels = clf.predict(X_train)
X_prob = clf.predict_proba(X_train)
for i, label in enumerate(X_labels):
#Final_Labels.append([data[int(nbh[neigh][i][2])][7],label, max(X_prob[i]) ])
data[int(nbh[neigh][i][2])] += [label, max(X_prob[i])]
if save_svm_plots:
colors2 = [
'red', 'blue', 'green', 'orange', 'purple'
'brown', 'yellow', 'lime', 'lightsteelblue', 'darksalmon',
'cyan', 'teal', 'tan', 'slategray'
] + colors
labels_found = list(set([c for c in X_labels]))
x, y, c = [r[0] for r in X_train], [r[1] for r in X_train], [
'blue' if c == labels_found[0] else 'red' for c in X_labels
]
plt.scatter(x, y, c=c, lw=0)
prop = FontProperties("Arabic Typesetting")
test = neigh.decode("utf-8")
reshaped_text = arabic_reshaper.reshape(test)
bidi_text = get_display(reshaped_text)
plt.title('SVM Classification for ' + bidi_text + ' (' + city +
')',
fontproperties=prop,
fontsize=32)
plt.axis('tight')
#plt.show()
plt.xlim(4, 10)
plt.ylim(4, 10)
plt.savefig(directory + "/SVM Plots/" + city + "/" +
neigh.decode("utf-8") + ".pdf")
plt.clf()
if save_aqar_plots:
for count, neigh in ranked[:]:
if neigh in aqar:
colors2 = [
'red', 'blue', 'green', 'orange', 'purple'
'brown', 'yellow', 'lime', 'lightsteelblue',
'darksalmon', 'cyan', 'teal', 'tan', 'slategray'
] + colors
labels_found = list(set([c for c in X_labels]))
x, y, c = [r[0] for r in aqar[neigh]
], [r[1] for r in aqar[neigh]], [
'blue' if r[2] == 'Land' else 'red'
for r in aqar[neigh]
]
plt.scatter(x, y, c=c, lw=0)
prop = FontProperties("Arabic Typesetting")
test = neigh.decode("utf-8")
reshaped_text = arabic_reshaper.reshape(test)
bidi_text = get_display(reshaped_text)
plt.title('Aqar Distribution for ' + bidi_text + ' (' +
city + ')',
fontproperties=prop,
fontsize=32)
plt.axis('tight')
#plt.show()
plt.xlim(4, 10)
plt.ylim(4, 10)
plt.savefig(directory + "/Aqar Plots/" + city + "/" +
neigh.decode("utf-8") + ".pdf")
plt.clf()
return data
# with open(directory + "Results/"+city+" Labels.csv", "w+") as f:
# for i, row in enumerate(data):
# if i > 0: f.write("\n")
# for j, col in enumerate(row):
# f.write(col if j==0 else ","+str(col))
# if i == 0: f.write(",label")
"""
textNewsubOld += (' ' + item) * freqNewsubOld[word]
# old (label2) - new (lable 1)
freqOldsubNew = {}
for word in freqold:
if word in freqnew:
if (freqold[word] > freqnew[word]):
freqOldsubNew[word] = int((freqold[word] - freqnew[word]) * 100000)
else:
freqOldsubNew[word] = int(freqold[word] * 100000)
for item in freqOldsubNew:
textOldsubNew += (' ' + item) * freqOldsubNew[word]
#creating clouds
textnew = arabic_reshaper.reshape(textnew)
textnew = get_display(textnew)
textold = arabic_reshaper.reshape(textold)
textold = get_display(textold)
textNewsubOld = arabic_reshaper.reshape(textNewsubOld)
textNewsubOld = get_display(textNewsubOld)
textOldsubNew = arabic_reshaper.reshape(textOldsubNew)
textOldsubNew = get_display(textOldsubNew)
WordCloudnew = WordCloud(font_path='WordCloud/src/BNazanin.ttf',
background_color='white',
height=2000,
width=2000)
WordCloudnew.generate(textnew)
plt.imshow(WordCloudnew)
plt.axis("off")
- bidi.algorithm
- arabic_reshaper
Dependencies installation:
pip install python-bidi arabic_reshape
"""
import os
import codecs
from textcloud import TextCloud
import arabic_reshaper
from bidi.algorithm import get_display
# get data directory (using getcwd() is needed to support running example in generated IPython notebook)
d = os.path.dirname(__file__) if "__file__" in locals() else os.getcwd()
# Read the whole text.
f = codecs.open(os.path.join(d, 'arabicwords.txt'), 'r', 'utf-8')
# Make text readable for a non-Arabic library like wordcloud
text = arabic_reshaper.reshape(f.read())
text = get_display(text)
# Generate a word cloud image
wordcloud = TextCloud(
font_path='fonts/NotoNaskhArabic/NotoNaskhArabic-Regular.ttf').generate(
text)
# Export to an image
wordcloud.to_file("arabic_example.png")
def word_process(self, x):
reshaped_text = arabic_reshaper.reshape(x)
return get_display(reshaped_text)
def arabic(str):
reshaped_text = arabic_reshaper.reshape(str)
return get_display(reshaped_text)
def myFirstPage(canvas, doc):
canvas.saveState()
canvas.setFont('Arabic-3', 10)
# canvas.drawCentredString(PAGE_WIDTH/2.0, PAGE_HEIGHT-108, Title)
# canvas.drawString(PAGE_WIDTH, 1*mm, "First Page / %s" % pageinfo)
arabic_text = get_display(
arabic_reshaper.reshape(u'طبقا لمقتضيات الظهير الشريف'))
canvas.drawCentredString(PAGE_WIDTH - 320, PAGE_HEIGHT - 15, arabic_text)
arabic_text = get_display(
arabic_reshaper.reshape(u'الصادر في 03 اكتوبر 2002'))
canvas.drawCentredString(PAGE_WIDTH - 320, PAGE_HEIGHT - 30, arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'المملكة المغربية'))
canvas.drawRightString(PAGE_WIDTH - 70, PAGE_HEIGHT - 15, arabic_text)
arabic_text = get_display(
arabic_reshaper.reshape(
u'وزارة الداخلية '
))
canvas.drawRightString(PAGE_WIDTH - 70, PAGE_HEIGHT - 30, arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'عمالة او اقليم:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 60,
"field 1 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'جماعة:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 75,
"field 2 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'مكتب الحالة المدنية:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 90,
"field 3 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'رسم رقم:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 105,
"field 4 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'لسنة:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 120,
"field 5 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'هجرية'))
canvas.drawRightString(PAGE_WIDTH - 130, PAGE_HEIGHT - 120, arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u' '))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 135,
"field 6 " + arabic_text)
arabic_text = get_display(arabic_reshaper.reshape(u'ميلادية'))
canvas.drawRightString(PAGE_WIDTH - 130, PAGE_HEIGHT - 135, arabic_text)
canvas.setFont('Arabic-2', 36)
arabic_text = get_display(
arabic_reshaper.reshape(u'نسخة موجزة من رسم الولادة'))
canvas.drawCentredString(PAGE_WIDTH / 2.0, PAGE_HEIGHT - 165, arabic_text)
canvas.setFont('Arabic-3', 10)
arabic_text = get_display(arabic_reshaper.reshape(u'الاسم الشخصي:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 190,
"field 7 " + arabic_text)
canvas.drawString(PAGE_WIDTH - 380, PAGE_HEIGHT - 190,
"Prénom: " + "field 7 bis")
arabic_text = get_display(arabic_reshaper.reshape(u'الاسم العائلي:'))
canvas.drawRightString(PAGE_WIDTH - 30, PAGE_HEIGHT - 210,
"field 8 " + arabic_text)
canvas.drawString(PAGE_WIDTH - 380, PAGE_HEIGHT - 210,
"Nom: " + "field 8 bis")
canvas.restoreState()
def visualization(tweets,y_predicted,noOfSearchTerms):
# Create and generate a word cloud image:
words_in_tweet_strings = " "
weridPatterns = re.compile("["
u"\U0001F600-\U0001F64F" # emoticons
u"\U0001F300-\U0001F5FF" # symbols & pictographs
u"\U0001F680-\U0001F6FF" # transport & map symbols
u"\U0001F1E0-\U0001F1FF" # flags (iOS)
u"\U00002702-\U000027B0"
u"\U000024C2-\U0001F251"
u"\U0001f926-\U0001f937"
u'\U00010000-\U0010ffff'
u"\u200d"
u"\u2640-\u2642"
u"\u2600-\u2B55"
u"\u23cf"
u"\u23e9"
u"\u231a"
u"\u3030"
u"\ufe0f"
u"\u2069"
u"\u2066"
u"\u200c"
u"\u2068"
u"\u2067"
"]+", flags=re.UNICODE)
for tweet in tweets:
words_in_tweet_strings += tweet.full_text
clean_text = weridPatterns.sub(r'', words_in_tweet_strings)
data = arabic_reshaper.reshape(clean_text)
data = get_display(data) # add this line
wordcloud = WordCloud(font_path='arial', background_color='white',
mode='RGB', width=2000, height=1000).generate(data)
# Display the generated image:
#fig1 = plt.figure(1)
plt.subplot(2,1,1)
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
#plt.show()
#fig1.savefig('words.png')
####### Visualization
n_all = len(y_predicted)
n_pos = 0
n_neg = 0
for y in y_predicted:
if y == 'pos':
n_pos += 1
if y == 'neg':
n_neg += 1
positive = percentage(n_pos, n_all)
negative = percentage(n_neg, n_all)
positive = format(positive,'.2f')
negative = format(negative, '.2f')
labels = ['Positive [' + str(positive) + '%]', 'Negative [' + str(negative) + '%]']
sizes = [positive, negative]
colors = ['yellowgreen', 'red']
#fig2 = plt.figure(2)
plt.subplot(2, 1, 2)
patches, texts = plt.pie(sizes, colors=colors, startangle=90)
plt.legend(patches, labels, loc="best")
plt.title(" by analyzing " + str(noOfSearchTerms) + " Tweets.")
plt.axis('equal')
plt.tight_layout()
plt.show()
def _generate_mit_pe_certificate(self, student_name, download_dir, verify_dir, filename='Certificate.pdf'):
"""
Generate the BigDataX certs
"""
# 8.5x11 page size 279.4mm x 215.9mm
WIDTH = 279 # width in mm (8.5x11)
HEIGHT = 216 # height in mm (8.5x11)
download_uuid = uuid.uuid4().hex
verify_uuid = uuid.uuid4().hex
download_url = "{base_url}/{cert}/{uuid}/{file}".format(
base_url=settings.CERT_DOWNLOAD_URL,
cert=S3_CERT_PATH, uuid=download_uuid, file=filename
)
filename = os.path.join(download_dir, download_uuid, filename)
# This file is overlaid on the template certificate
overlay_pdf_buffer = StringIO.StringIO()
c = canvas.Canvas(overlay_pdf_buffer)
c.setPageSize((WIDTH * mm, HEIGHT * mm))
# register all fonts in the fonts/ dir,
# there are more fonts in here than we need
# but the performance hit seems minimal
for font_file in glob('{0}/fonts/*.ttf'.format(self.template_dir)):
font_name = os.path.basename(os.path.splitext(font_file)[0])
pdfmetrics.registerFont(TTFont(font_name, font_file))
#### STYLE: grid/layout
LEFT_INDENT = 10 # mm from the left side to write the text
MAX_WIDTH = 260 # maximum width on the content in the cert, used for wrapping
#### STYLE: template-wide typography settings
style_type_name_size = 36
style_type_name_leading = 53
style_type_name_med_size = 22
style_type_name_med_leading = 27
style_type_name_small_size = 18
style_type_name_small_leading = 21
#### STYLE: template-wide color settings
style_color_name = colors.Color(0.000000, 0.000000, 0.000000)
#### STYLE: positioning
pos_name_y = 137
pos_name_med_y = 142
pos_name_small_y = 140
pos_name_no_wrap_offset_y = 2
#### HTML Parser ####
# Since the final string is HTML in a PDF we need to un-escape the html
# when calculating the string width.
html = HTMLParser()
####### ELEM: Student Name
# default is to use Garamond for the name,
# will fall back to Arial if there are
# unusual characters
y_offset_name = pos_name_y
y_offset_name_med = pos_name_med_y
y_offset_name_small = pos_name_small_y
styleUnicode = ParagraphStyle(name="arial", leading=10,
fontName='Arial Unicode')
styleGaramondStudentName = ParagraphStyle(name="garamond", fontName='Garamond-Bold')
styleGaramondStudentName.leading = style_type_name_small_size
style = styleGaramondStudentName
html_student_name = html.unescape(student_name)
larger_width = stringWidth(html_student_name.decode('utf-8'),
'Garamond-Bold', style_type_name_size) / mm
smaller_width = stringWidth(html_student_name.decode('utf-8'),
'Garamond-Bold', style_type_name_small_size) / mm
paragraph_string = arabic_reshaper.reshape(student_name.decode('utf-8'))
paragraph_string = get_display(paragraph_string)
# Garamond only supports Latin-1
# if we can't use it, use Gentium
if self._use_unicode_font(student_name):
style = styleUnicode
larger_width = stringWidth(html_student_name.decode('utf-8'),
'Arial Unicode', style_type_name_size) / mm
# if the name is too long, shrink the font size
if larger_width < MAX_WIDTH:
style.fontSize = style_type_name_size
style.leading = style_type_name_leading
y_offset = y_offset_name
elif smaller_width < MAX_WIDTH:
y_offset = y_offset_name_med + pos_name_no_wrap_offset_y
style.fontSize = style_type_name_med_size
style.leading = style_type_name_med_leading
else:
y_offset = y_offset_name_small
style.fontSize = style_type_name_small_size
style.leading = style_type_name_small_leading
style.textColor = style_color_name
style.alignment = TA_CENTER
paragraph = Paragraph(paragraph_string, style)
paragraph.wrapOn(c, MAX_WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
## Generate the final PDF
c.showPage()
c.save()
# Merge the overlay with the template, then write it to file
output = PdfFileWriter()
overlay = PdfFileReader(overlay_pdf_buffer)
# We need a page to overlay on.
# So that we don't have to open the template
# several times, we open a blank pdf several times instead
# (much faster)
blank_pdf = PdfFileReader(
file("{0}/blank-letter.pdf".format(self.template_dir), "rb")
)
final_certificate = blank_pdf.getPage(0)
final_certificate.mergePage(self.template_pdf.getPage(0))
final_certificate.mergePage(overlay.getPage(0))
output.addPage(final_certificate)
self._ensure_dir(filename)
outputStream = file(filename, "wb")
output.write(outputStream)
outputStream.close()
return (download_uuid, verify_uuid, download_url)
import arabic_reshaper
import sys
file_path = sys.argv[1]
with open(file_path, "r") as myfile:
text = ''.join(myfile.readlines())
text_to_be_reshaped = 'اللغة العربية رائعة'
reshaped_text = arabic_reshaper.reshape(text)
output_file = open(file_path, "w")
output_file.write(reshaped_text)
output_file.close()
def reshaper(self, text): reshaped_text = arabic_reshaper.reshape(text) return get_display(reshaped_text)
image_area = height * width
serial_width, serial_height, serial_font_size = generate_random_coordinates(
height, width, start_point)
if serial_width == False:
index = index - 1
continue
serial_width = serial_width * 0.7
end_point = (round(start_point[0] + serial_width),
round(start_point[1] - serial_height))
serial_area = serial_height * serial_width
font = cv2.FONT_HERSHEY_SIMPLEX
# print(serial_height , " " , serial_width)
print("Image Num #", str(index), "start at :", start_point)
original_text = get_shuffle_serial(7)
text = original_text
reshaped_text = arabic_reshaper.reshape(text) # correct its shape
text = get_display(reshaped_text)
# cv2.putText(image,text,start_point, font, serial_font_size,(0,0,0),random.randint(0,3),cv2.LINE_AA)
# cv2.rectangle(image,start_point,(round(start_point[0]+serial_width),round(start_point[1]-serial_height)),(0,255,0),0)
# cv2.circle(image,start_point,2, (0,0,255), -1)
# cv2.circle(image,end_point, 2, (0,0,255), -1)
# cv2.imwrite("test.png",image)
fontpath = "Mirza/Mirza-Regular.ttf"
font = ImageFont.truetype(fontpath, round(serial_height * 1.7))
img_pil = Image.fromarray(image)
draw = ImageDraw.Draw(img_pil)
d = (start_point[0], start_point[1] - serial_height)
draw.text(d, text, font=font, fill=(0, 0, 0))
# draw.rectangle((start_point,end_point))
image = np.array(img_pil)
cv2.imwrite("dataset/" + str(index) + ".png", image)
def to_arabic(self, text):
a = get_display(arabic_reshaper.reshape(str(text)))
return(a)
def main():
reshaped_text = arabic_reshaper.reshape(sys.argv[1].decode('utf-8'))
print reshaped_text.encode('utf-8')
def do_backspace(self, from_undo=True, mode='bkspc'):
self.str = self.str[0:len(self.str)-1]
self.text = get_display(arabic_reshaper.reshape(self.str))
def reportP(pid, dates, is_true):
import datetime
import pandas as pd
import numpy as np
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
from firebase_admin import storage
import pyrebase
from datetime import date, timedelta
import urllib.request, json
import time
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
import os
import csv
from IPython.display import display
from Model import trainData
import random
from matplotlib.patches import Ellipse
import matplotlib.patches as mpatches
import seaborn as sns
# signal processing
from scipy import signal
from scipy.ndimage import label
from scipy.stats import zscore
from scipy.interpolate import interp1d
from scipy.integrate import trapz
# misc
import warnings
#generate pdf
from reportlab.pdfgen import canvas
from reportlab.lib.colors import Color, lightblue, black
# In[2]:
if not firebase_admin._apps:
cred = credentials.Certificate("serene-firebase-adminsdk.json")
app = firebase_admin.initialize_app(
cred, {
'storageBucket': 'serene-2dfd6.appspot.com',
},
name='[DEFAULT]')
else:
app = firebase_admin.get_app()
db = firestore.client()
# In[3]:
userID = pid
GoogleCalendar = is_true
# In[4]:
today = datetime.datetime.now()
timestamp = today.strftime("%Y-%m-%d %H:%M:%S")
bucket = storage.bucket(app=app)
# ## Get data from storage and get list of dates
# In[5]:
df = pd.DataFrame()
notAvailableDates = []
# loop through the storage and get the data
sleep = []
for x in range(0, len(dates)):
#Sleep
blob = bucket.blob(userID + "/fitbitData/" + dates[x] + "/" +
dates[x] + "-sleep.json")
#download the file
u = blob.generate_signed_url(datetime.timedelta(seconds=300),
method='GET')
try:
with urllib.request.urlopen(u) as url:
data = json.loads(url.read().decode())
sleepMinutes = data['summary']["totalMinutesAsleep"]
except:
notAvailableDates.append(dates[x])
pass
#Activity (Steps)
blob = bucket.blob(userID + "/fitbitData/" + dates[x] + "/" +
dates[x] + "-activity.json")
#download the file
u = blob.generate_signed_url(datetime.timedelta(seconds=300),
method='GET')
try:
with urllib.request.urlopen(u) as url:
data = json.loads(url.read().decode())
steps = data['summary']["steps"]
except:
notAvailableDates.append(dates[x])
pass
#heartrate
blob = bucket.blob(userID + "/fitbitData/" + dates[x] + "/" +
dates[x] + "-heartrate.json")
u = blob.generate_signed_url(datetime.timedelta(seconds=300),
method='GET')
try:
with urllib.request.urlopen(u) as url:
data = json.loads(url.read().decode())
df_heartrate = pd.DataFrame(
data['activities-heart-intraday']['dataset'])
df_heartrate.time.apply(str)
df_heartrate['time'] = pd.to_datetime(df_heartrate['time'])
df_heartrate['hour'] = df_heartrate['time'].apply(
lambda time: time.strftime('%H'))
df_heartrate.drop(['time'], axis=1, inplace=True)
heart_rate = df_heartrate.groupby(["hour"], as_index=False).mean()
heart_rate['sleepMin'] = sleepMinutes
heart_rate['TotalSteps'] = steps
heart_rate['date'] = dates[x]
heart_rate = heart_rate.astype({"hour": int})
except:
notAvailableDates.append(dates[x])
pass
#append dataframe
df = df.append(heart_rate, ignore_index=True)
notAvailableDates
notSyncedDates = pd.DataFrame()
notSyncedDates['date'] = notAvailableDates
# In[16]:
notSyncedDates = notSyncedDates.drop_duplicates()
# ### Get user location
# In[17]:
# get location from database
loc_df = pd.DataFrame()
locID = []
locations = db.collection(u'PatientLocations').where(
u'patientID', u'==', userID).stream()
for location in locations:
loc = location.to_dict()
locID.append(location.id)
loc_df = loc_df.append(pd.DataFrame(loc, index=[0]), ignore_index=True)
loc_df['id'] = locID
# In[18]:
loc_df.drop(['anxietyLevel', 'lat', 'lng', 'patientID'],
axis=1,
inplace=True)
# In[19]:
loc_df.time.apply(str)
loc_df['time'] = pd.to_datetime(loc_df['time'])
loc_df['date'] = pd.to_datetime(loc_df['time'], format='%Y:%M:%D').dt.date
loc_df['hour'] = loc_df['time'].apply(lambda time: time.strftime('%H'))
loc_df.drop(['time'], axis=1, inplace=True)
loc_df.hour = loc_df.hour.astype(int)
loc_df.date = loc_df.date.astype(str)
df.date = df.date.astype(str)
# In[20]:
dfinal = pd.merge(left=df,
right=loc_df,
how='left',
left_on=['hour', 'date'],
right_on=['hour', 'date']).ffill()
# ### Test data into model
# In[23]:
#test model
train_df = dfinal.rename(columns={'value': 'Heartrate'})
# In[24]:
Labeled_df = pd.DataFrame()
Labeled_df = trainData(train_df)
# In[25]:
Labeled_df.drop(['lon'], axis=1, inplace=True)
# In[26]:
# Replace missing values because it doesn't exist
Labeled_df['name'].fillna("Not given", inplace=True)
Labeled_df['id'].fillna("Not given", inplace=True)
#Labeled_df['anxiety_assigned'].fillna('Not given', inplace = True)
# In[27]:
# In[28]:
# Update firebase with the user anxiety level
for row in Labeled_df.itertuples():
if row.id != 'Not given':
if row.Label == 'Low' or row.Label == 'LowA':
anxietyLevel = '1'
elif row.Label == 'Meduim':
anxietyLevel = '2'
else:
anxietyLevel = '3'
if ((row.anxiety_assigned == False)
or (row.anxiety_assigned == 'Not given')):
doc_ref = db.collection(u'PatientLocations').document(row.id)
doc_ref.update({
u'anxietyLevel': anxietyLevel,
u'anxiety_assigned': True
})
# ### Show the places with highest anxiety level
# In[29]:
# Show the highest level
df_high = pd.DataFrame()
df_high = Labeled_df[Labeled_df.Label == 'High']
# # Recommendation
# In[30]:
docDf = pd.DataFrame()
doc_ref = db.collection(u'Patient').document(userID)
doc = doc_ref.get().to_dict()
docDf = docDf.append(pd.DataFrame(doc, index=[0]), ignore_index=True)
# In[31]:
age1 = docDf['age'].values
name1 = docDf['name'].values
emp1 = docDf['employmentStatus'].values
mar1 = docDf['maritalStatus'].values
income1 = docDf['monthlyIncome'].values
chronicD1 = docDf['chronicDiseases'].values
smoke1 = docDf['smokeCigarettes'].values
gad1 = docDf['GAD-7ScaleScore'].values
gender1 = docDf['gender'].values
age = age1[0]
name = name1[0]
emp = emp1[0]
mar = mar1[0]
income = income1[0]
chronicD = chronicD1[0]
smoke = smoke1[0]
gad = gad1[0]
gender = gender1[0]
compareAge = int(age)
# In[32]:
sleepMin = Labeled_df['sleepMin'].mean()
totalSteps = Labeled_df['TotalSteps'].astype(float).mean()
sleepRecomendation = False
stepsRecomendation = False
recomendedSteps = 'No recomendation'
if sleepMin < 360:
sleepRecomendation = True
if compareAge < 20 and compareAge > 11:
if totalSteps < 6000:
stepsRecomendation = True
recomendedSteps = '6000'
if compareAge < 66 and compareAge > 19:
if totalSteps < 3000:
stepsRecomendation = True
recomendedSteps = '3000'
sleepMin = sleepMin / 60
sleepMin = float("{:.1f}".format(sleepMin))
totalSteps = int(totalSteps)
# ## Storage intilization
# In[33]:
firebaseConfig = {
"apiKey": "AIzaSyBoxoXwFm9TuFysjQYag0GB1NEPyBINlTU",
"authDomain": "serene-2dfd6.firebaseapp.com",
"databaseURL": "https://serene-2dfd6.firebaseio.com",
"projectId": "serene-2dfd6",
"storageBucket": "serene-2dfd6.appspot.com",
"messagingSenderId": "461213981433",
"appId": "1:461213981433:web:62428e3664182b3e58e028",
"measurementId": "G-J66VP2Y3CR"
}
firebase = pyrebase.initialize_app(firebaseConfig)
storage = firebase.storage()
# # AL
# In[34]:
sns.set(rc={'axes.facecolor': '#fcfeff'})
# In[35]:
# Change Label values to num, to represent them in a barchart
nums = []
for row in Labeled_df.itertuples():
if row.Label == 'Low' or row.Label == 'LowA':
nums.append(1)
elif row.Label == 'Meduim':
nums.append(2)
else:
nums.append(3)
Labeled_df['numLabel'] = nums
# In[36]:
# Get anxiety level by day and store it in a new data frame
plot_df = pd.DataFrame()
avgAnxiety = []
totalAnxiety = 0
rowCount = 1
for x in range(0, len(dates)):
totalAnxiety = 0
rowCount = 1
for row in Labeled_df.itertuples():
if (row.date == dates[x]):
rowCount += 1
totalAnxiety += row.numLabel
avgAnxiety.append(totalAnxiety / rowCount)
plot_df['date'] = dates
plot_df['Anxiety'] = avgAnxiety
# In[37]:
#divide dataframe into 15 rows (2 weeks) max is 3 months
df1 = pd.DataFrame()
df2 = pd.DataFrame()
df3 = pd.DataFrame()
df4 = pd.DataFrame()
df5 = pd.DataFrame()
df6 = pd.DataFrame()
dfarray = []
count = 0
if (len(plot_df) > 15):
df1 = plot_df[:15]
df2 = plot_df[15:]
dfarray.append(df1)
dfarray.append(df2)
if (len(df2) > 15):
count = (df2.last_valid_index() - (len(df2) - 15))
df3 = df2[count:]
dfarray.append(df3)
if (len(df3) > 15):
count = (df3.last_valid_index() - (len(df3) - 15))
df4 = df3[count:]
dfarray.append(df4)
if (len(df4) > 15):
count = (df4.last_valid_index() - (len(df4) - 15))
df5 = df4[count:]
dfarray.append(df5)
if (len(df5) > 15):
count = (df5.last_valid_index() - (len(df5) - 15))
df6 = df5[count:]
dfarray.append(df6)
# In[38]:
# Plot AL
if (len(plot_df) <= 15):
fig, ax = plt.subplots()
c1 = '#9dd6f5'
c2 = '#4ba0d1'
c3 = '#23495f'
bar_width = 0.25
for t, y in zip(plot_df["date"], plot_df["Anxiety"]):
c = ""
if (y <= 1):
c = c1
elif (1 < y <= 2):
c = c2
elif (y > 2):
c = c3
plt.bar([t, t], [0, y], bar_width, color=c)
colors = [[c1, c1], [c2, c2], [c3, c3]]
categories = ['Low', 'Meduim', 'High']
#create dict
legend_dict = dict(zip(categories, colors))
#create patches
patchList = []
for key in legend_dict:
data_key = mpatches.Patch(facecolor=legend_dict[key][0],
edgecolor=legend_dict[key][1],
label=key)
patchList.append(data_key)
ax.legend(handles=patchList, ncol=len(categories), fontsize=12)
plt.tick_params(axis='x', rotation=70)
# Start the graph at 0
ax.set_ylim(0, 3)
#fig.set_size_inches(15.5, 10)
plt.tight_layout()
plt.xlabel('Date')
ax.yaxis.set_label_coords(-0.02, 0.48)
fig.savefig('AL0.png', dpi=None)
imagePath = 'AL0.png'
link = storage.child(
userID + "/lastGeneratedPatientReport/AL0.png").put('AL0.png')
os.remove('AL0.png')
else:
links = []
for x in range(0, len(dfarray)):
fig, ax = plt.subplots()
c1 = '#9dd6f5'
c2 = '#4ba0d1'
c3 = '#23495f'
bar_width = 0.25
for t, y in zip(dfarray[x]["date"], dfarray[x]["Anxiety"]):
c = ""
if (y <= 1):
c = c1
elif (1 < y <= 2):
c = c2
elif (y > 2):
c = c3
plt.bar([t, t], [0, y], bar_width, color=c)
colors = [[c1, c1], [c2, c2], [c3, c3]]
categories = ['Low', 'Meduim', 'High']
#create dict
legend_dict = dict(zip(categories, colors))
#create patches
patchList = []
for key in legend_dict:
data_key = mpatches.Patch(facecolor=legend_dict[key][0],
edgecolor=legend_dict[key][1],
label=key)
patchList.append(data_key)
ax.legend(handles=patchList, ncol=len(categories), fontsize=12)
plt.tick_params(axis='x', rotation=70)
# Start the graph at 0
ax.set_ylim(0, 3)
#fig.set_size_inches(15.5, 10)
plt.tight_layout()
plt.xlabel('Date')
ax.yaxis.set_label_coords(-0.02, 0.48)
fig.savefig('AL' + str(x) + '.png', dpi=None)
imagePath = 'AL' + str(x) + '.png'
link = storage.child(userID + "/lastGeneratedPatientReport/AL" +
str(x) + '.png').put('AL' + str(x) + '.png')
links.append(link)
os.remove('AL' + str(x) + '.png')
# ### save file to database first
# In[39]:
if (len(plot_df) <= 15):
linkDF = pd.DataFrame()
linkDF = linkDF.append(pd.DataFrame(link, index=[0]),
ignore_index=True)
token1 = linkDF['downloadTokens'].values
token = token1[0]
AlLink = storage.child(
userID + "/lastGeneratedPatientReport/AL0.png").get_url(token)
doc_rec = db.collection(u'LastGeneratePatientReport').document(
'report' + userID)
doc_rec.set({
u'average_steps': totalSteps,
u'patient_id': userID,
u'average_sleep_hours': sleepMin,
u'sleepRecomendation': sleepRecomendation,
u'stepsRecomendation': stepsRecomendation,
u'recommended_steps': recomendedSteps,
u'number_of_AL_graphs': 1,
u'AL_graph_0': AlLink,
u'recommended_sleep_hours': '7-9'
})
else:
firebase_links = []
for x in range(0, len(links)):
linkDF = pd.DataFrame()
linkDF = linkDF.append(pd.DataFrame(link, index=[0]),
ignore_index=True)
token1 = linkDF['downloadTokens'].values
token = token1[0]
AlLink = storage.child(userID + "/lastGeneratedPatientReport/AL" +
str(x) + '.png').get_url(token)
firebase_links.append(AlLink)
doc_rec = db.collection(u'LastGeneratePatientReport').document(
'report' + userID)
doc_rec.set({
u'average_steps': totalSteps,
u'patient_id': userID,
u'average_sleep_hours': sleepMin,
u'sleepRecomendation': sleepRecomendation,
u'stepsRecomendation': stepsRecomendation,
u'recommended_steps': recomendedSteps,
u'number_of_AL_graphs': len(links),
u'recommended_sleep_hours': '7-9'
})
for x in range(0, len(links)):
doc_rec = db.collection(u'LastGeneratePatientReport').document(
'report' + userID)
doc_rec.update({u'AL_graph_' + str(x): firebase_links[x]})
# ## To generate graphs for PDF report
# In[40]:
fig, ax = plt.subplots()
c1 = '#9dd6f5'
c2 = '#4ba0d1'
c3 = '#23495f'
bar_width = 0.25
for t, y in zip(plot_df["date"], plot_df["Anxiety"]):
c = ""
if (y <= 1):
c = c1
elif (1 < y <= 2):
c = c2
elif (y > 2):
c = c3
plt.bar([t, t], [0, y], bar_width, color=c)
colors = [[c1, c1], [c2, c2], [c3, c3]]
categories = ['Low', 'Meduim', 'High']
#create dict
legend_dict = dict(zip(categories, colors))
#create patches
patchList = []
for key in legend_dict:
data_key = mpatches.Patch(facecolor=legend_dict[key][0],
edgecolor=legend_dict[key][1],
label=key)
patchList.append(data_key)
ax.legend(handles=patchList, ncol=len(categories), fontsize=12)
plt.tick_params(axis='x', rotation=70)
# Start the graph at 0
ax.set_ylim(0, 3)
fig.set_size_inches(15.5, 10)
plt.tight_layout()
plt.xlabel('Date')
ax.yaxis.set_label_coords(-0.02, 0.48)
fig.savefig('ALpdf.png', dpi=None)
# # Location Analysis
# In[41]:
# get location from database
new_loc = pd.DataFrame()
locID = []
locations = db.collection(u'PatientLocations').where(
u'patientID', u'==', userID).stream()
for location in locations:
loc = location.to_dict()
locID.append(location.id)
new_loc = new_loc.append(pd.DataFrame(loc, index=[0]),
ignore_index=True)
new_loc['id'] = locID
# In[42]:
new_loc.time.apply(str)
new_loc['time'] = pd.to_datetime(new_loc['time'])
new_loc['date'] = pd.to_datetime(new_loc['time'],
format='%Y:%M:%D').dt.date
new_loc.drop(['time'], axis=1, inplace=True)
new_loc.date = new_loc.date.astype(str)
# In[43]:
new_loc = new_loc[(new_loc.date >= dates[0])
& (new_loc.date <= dates[len(dates) - 1])]
# In[44]:
names = []
Name = ""
for row in new_loc.itertuples():
Name = row.nearestLoc
names.append(Name)
# In[45]:
new_name = pd.DataFrame()
new_name['name'] = names
# In[46]:
new_name = new_name.drop_duplicates()
new_name.dropna()
# In[47]:
fnames = []
fName = ""
for row in new_name.itertuples():
fName = row.name
fnames.append(fName)
# In[48]:
analysis_EN = pd.DataFrame()
analysis_AR = pd.DataFrame()
count = 0
i = 0
#label = ""
locationName = ""
near = ''
nearLocs = []
counts = []
labels = []
locationNames = []
for x in range(0, len(fnames)):
count = 0
locName = fnames[i]
for row in new_loc.itertuples():
if (locName == row.nearestLoc):
if (row.anxietyLevel == '3'):
count += 1
label = row.anxietyLevel
locationName = row.name
near = row.nearestLoc
i += 1
counts.append(count)
#labels.append(label)
locationNames.append(locationName)
nearLocs.append(near)
analysis_EN['Location'] = locationNames
analysis_EN['Number of occurrences'] = counts
#analysis_EN ['Anxiety Level'] = labels
analysis_EN['Nearest Location'] = nearLocs
analysis_AR['الموقع'] = locationNames
analysis_AR['عدد مرات الزيارة'] = counts
#analysis_AR ['مستوى القلق'] = labels
analysis_AR['أقرب موقع'] = nearLocs
# In[49]:
newEn = analysis_EN.drop(
analysis_EN[analysis_EN['Number of occurrences'] == 0].index,
inplace=True)
newAr = analysis_AR.drop(
analysis_AR[analysis_AR['عدد مرات الزيارة'] == 0].index, inplace=True)
# In[50]:
#analysis_EN ['Anxiety Level'] = 'High'
#analysis_AR ['مستوى القلق'] = 'مرتفع'
# In[51]:
import six
import arabic_reshaper
from googletrans import Translator
from bidi.algorithm import get_display
from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.ttfonts import TTFont
# In[52]:
def render_mpl_table(data,
col_width=5.0,
row_height=0.625,
font_size=14,
tran='',
header_color='#23495f',
row_colors=['#e1eff7', 'w'],
edge_color='#23495f',
bbox=[0, 0, 1, 1],
header_columns=0,
ax=None,
**kwargs):
if ax is None:
size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array(
[col_width, row_height])
fig, ax = plt.subplots(figsize=size)
ax.axis('off')
mpl_table = ax.table(cellText=data.values,
bbox=bbox,
colLabels=data.columns,
cellLoc='center',
**kwargs)
mpl_table.auto_set_font_size(False)
mpl_table.set_fontsize(font_size)
for k, cell in six.iteritems(mpl_table._cells):
cell.set_edgecolor(edge_color)
if k[0] == 0 or k[1] < header_columns:
cell.set_text_props(weight='bold', color='w')
cell.set_facecolor(header_color)
else:
cell.set_facecolor(row_colors[k[0] % len(row_colors)])
cell.alignment = 'center'
fig.savefig(tran + '.png', dpi=100)
return ax
# In[53]:
if (len(analysis_EN) > 0):
for ind, row in analysis_EN.iterrows():
analysis_EN.loc[ind, 'Nearest Location'] = get_display(
arabic_reshaper.reshape(analysis_EN.loc[ind,
'Nearest Location']))
if (len(analysis_AR) > 0):
for ind, row in analysis_AR.iterrows():
analysis_AR.loc[ind, 'أقرب موقع'] = get_display(
arabic_reshaper.reshape(analysis_AR.loc[ind, 'أقرب موقع']))
# analysis_AR.loc[ind,'مستوى القلق']=get_display(arabic_reshaper.reshape(analysis_AR.loc[ind,'مستوى القلق']))
analysis_AR = analysis_AR.rename(
columns={'الموقع': get_display(arabic_reshaper.reshape('الموقع'))})
analysis_AR = analysis_AR.rename(
columns={
'التكرار': get_display(arabic_reshaper.reshape('التكرار'))
})
#analysis_AR = analysis_AR.rename(columns={'مستوى القلق': get_display(arabic_reshaper.reshape('مستوى القلق')) })
analysis_AR = analysis_AR.rename(
columns={
'أقرب موقع': get_display(arabic_reshaper.reshape('أقرب موقع'))
})
# In[54]:
if (len(analysis_EN) > 0):
render_mpl_table(analysis_EN,
header_columns=0,
col_width=6,
tran='Location-EN')
if (len(analysis_AR) > 0):
render_mpl_table(analysis_AR,
header_columns=0,
col_width=6,
tran='Location-AR')
# # Events with highest level of anxiety
# In[59]:
from dateutil.parser import parse
# In[60]:
if GoogleCalendar == 'true':
events_df = pd.DataFrame()
finalEvents_EN = pd.DataFrame()
finalEvents_AR = pd.DataFrame()
eventID = []
events = db.collection(u'PatientEvents').where(u'patientID', u'==',
userID).stream()
for event in events:
ev = event.to_dict()
eventID.append(event.id)
events_df = events_df.append(pd.DataFrame(ev, index=[0]),
ignore_index=True)
events_df['idEvent'] = eventID
# In[61]:
if len(events_df) > 0:
newDates = []
for row in events_df.itertuples():
newDate = parse(row.date)
newDates.append(newDate)
events_df['newDate'] = newDates
events_df = events_df.rename(columns={'name': 'eventName'})
events_df.newDate.apply(str)
events_df['date'] = pd.to_datetime(events_df['newDate'],
format='%Y:%M:%D').dt.date
events_df['hour'] = events_df['newDate'].apply(
lambda time: time.strftime('%H'))
events_df.hour = events_df.hour.astype(int)
events_df.date = events_df.date.astype(str)
Test = Labeled_df
merge_df = pd.merge(left=Test,
right=events_df,
how='left',
left_on=['hour', 'date'],
right_on=['hour', 'date']).ffill()
merge_df['eventName'].fillna("Not given", inplace=True)
merge_df = merge_df[merge_df.eventName != 'Not given']
#finalEvents_EN = pd.DataFrame()
#finalEvents_AR = pd.DataFrame()
ev_name = ''
evNames = []
#evLabels = []
evDate = []
for row in merge_df.itertuples():
if row.eventName != ev_name:
if row.Label == 'High':
ev_name = row.eventName
#ev_label = row.Label
ev_date = row.date
if (ev_name != ''):
evNames.append(ev_name)
#evLabels.append(ev_label)
evDate.append(ev_date)
finalEvents_EN['Event Name'] = evNames
#finalEvents_EN['Anxiety Level'] = evLabels
finalEvents_EN['Date'] = evDate
finalEvents_AR['اسم الحدث'] = evNames
#finalEvents_AR['مستوى القلق'] = evLabels
finalEvents_AR['تاريخ الحدث'] = evDate
finalEvents_EN = finalEvents_EN.drop_duplicates()
finalEvents_AR = finalEvents_AR.drop_duplicates()
Final_duplicated = pd.DataFrame()
eventId = ''
eventIds = []
event_Labels = []
event_names = []
hours = []
for row in merge_df.itertuples():
if eventId != row.idEvent:
eventId = row.idEvent
if eventId != '':
eventIds.append(eventId)
event_Labels.append(row.Label)
event_names.append(row.eventName)
hours.append(row.hour)
Final_duplicated['id'] = eventIds
Final_duplicated['Label'] = event_Labels
Final_duplicated['name'] = event_names
Final_duplicated['hour'] = hours
Final_duplicated = Final_duplicated.drop_duplicates(subset='id')
# Update firebase with the user anxiety level
for row in Final_duplicated.itertuples():
if row.Label == 'High':
doc_ref = db.collection(u'PatientEvents').document(row.id)
doc_ref.update({u'anxietyLevel': '3'})
else:
doc_ref = db.collection(u'PatientEvents').document(row.id)
doc_ref.delete()
checkEvents_df = pd.DataFrame()
cEventsID = []
checkEvents = db.collection(u'PatientEvents').where(
u'patientID', u'==', userID).stream()
for event in checkEvents:
cEv = event.to_dict()
cEventsID.append(event.id)
checkEvents_df = checkEvents_df.append(pd.DataFrame(cEv,
index=[0]),
ignore_index=True)
checkEvents_df['id'] = cEventsID
checkEvents_df.fillna("Not given", inplace=True)
if len(checkEvents_df) > 0:
checkEvents_df = checkEvents_df[checkEvents_df.anxietyLevel ==
'Not given']
for row in checkEvents_df.itertuples():
doc_ref = db.collection(u'PatientEvents').document(row.id)
doc_ref.delete()
# In[62]:
if (len(finalEvents_EN) > 0):
finalEvents_EN = finalEvents_EN.drop_duplicates()
finalEvents_AR = finalEvents_AR.drop_duplicates()
# In[63]:
if (len(finalEvents_EN) > 0):
for ind, row in finalEvents_EN.iterrows():
try:
finalEvents_EN.loc[ind, 'Event Name'] = get_display(
arabic_reshaper.reshape(
finalEvents_EN.loc[ind, 'Event Name']))
except:
pass
if (len(finalEvents_AR) > 0):
#finalEvents_AR['مستوى القلق'] = 'مرتفع'
for ind, row in finalEvents_AR.iterrows():
try:
finalEvents_AR.loc[ind, 'اسم الحدث'] = get_display(
arabic_reshaper.reshape(
finalEvents_AR.loc[ind, 'اسم الحدث']))
#finalEvents_AR.loc[ind,'مستوى القلق']=get_display(arabic_reshaper.reshape(finalEvents_AR.loc[ind,'مستوى القلق']))
except:
pass
finalEvents_AR = finalEvents_AR.rename(columns={
'اسم الحدث':
get_display(arabic_reshaper.reshape('اسم الحدث'))
})
#finalEvents_AR = finalEvents_AR.rename(columns={'مستوى القلق': get_display(arabic_reshaper.reshape('مستوى القلق')) })
finalEvents_AR = finalEvents_AR.rename(
columns={
'تاريخ الحدث':
get_display(arabic_reshaper.reshape('تاريخ الحدث'))
})
# In[64]:
if (len(finalEvents_EN) > 0):
render_mpl_table(finalEvents_EN,
header_columns=0,
col_width=4,
tran='Events-EN')
if (len(finalEvents_AR) > 0):
render_mpl_table(finalEvents_AR,
header_columns=0,
col_width=4,
tran='Events-AR')
# In[ ]:
# # Genertate patient report and save it in storage
# In[65]:
from reportlab.lib import colors
# In[66]:
pdfmetrics.registerFont(TTFont('Arabic', 'traditional-arabic/tradbdo.TTF'))
# In[67]:
pdf = canvas.Canvas('Patient-EN.pdf')
pdf.setTitle('Patient report')
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 620, 485, 50, 4, fill=1, stroke=0)
pdf.setFont("Helvetica-Bold", 16)
pdf.setFillColor(colors.HexColor('#23495f'))
pdf.drawString(
115, 638,
"Report Duration From: " + dates[0] + " To: " + dates[len(dates) - 1])
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 400, 485, 200, 4, fill=1, stroke=0)
pdf.setFont("Helvetica-Bold", 20)
pdf.setFillColor(colors.HexColor('#23495f'))
pdf.drawString(100, 570, "Patient Information")
pdf.setFont("Helvetica-Bold", 15)
pdf.drawString(150, 550, "Name: ")
pdf.drawString(150, 530, "Age: ")
pdf.drawString(150, 510, "Employment Status: ")
pdf.drawString(150, 490, "Martial Status: ")
pdf.drawString(150, 470, "Monthly Income: ")
pdf.drawString(150, 450, "Chronic Diseases: ")
pdf.drawString(150, 430, "Cigarette Smoker: ")
pdf.drawString(150, 410, "Gender: ")
pdf.setFont("Helvetica", 15)
pdf.setFillColor(black)
pdf.drawString(210, 550, name)
pdf.drawString(210, 530, age)
pdf.drawString(310, 510, emp)
pdf.drawString(260, 490, mar)
pdf.drawString(290, 470, income)
pdf.drawString(290, 450, chronicD)
pdf.drawString(290, 430, smoke)
pdf.drawString(220, 410, gender)
pdf.setFillColor(colors.HexColor('#bfbfbf'))
pdf.roundRect(370, 560, 125, 30, 4, fill=1, stroke=0)
pdf.setFillColorRGB(1, 1, 1)
pdf.drawString(375, 570, "GAD-7 Score = ")
pdf.setFont("Helvetica-Bold", 15)
pdf.drawString(480, 570, gad)
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 160, 485, 200, 4, fill=1, stroke=0)
pdf.setFont("Helvetica-Bold", 16)
pdf.setFillColor(colors.HexColor('#23495f'))
pdf.drawString(80, 330, "Recommendations: ")
pdf.drawString(100, 300, "Sleep Recomendation: ")
pdf.drawString(100, 220, "Steps Recomendation: ")
pdf.setFont("Helvetica", 11)
pdf.setFillColor(black)
if (sleepRecomendation == True):
t = pdf.beginText(100, 280)
text = [
"It is recommended to sleep at least 7-9 hours per day to get lower chance of anxiety.",
"Getting a good night’s sleep can improve your mental well-being and help you to better",
"manage your anxiety."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
else:
t = pdf.beginText(100, 280)
text = [
"Good News! It seems you're getting enough sleep!",
"Getting a good night’s sleep can improve your mental well-being and help you to better",
"manage your anxiety."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
if (stepsRecomendation == True):
t = pdf.beginText(100, 200)
text = [
"It is recommended to walk at least " + recomendedSteps +
" steps per day to get lower chance of anxiety.",
"Keep in mind that active people have lower rates of anxiety than sedentary people."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
else:
t = pdf.beginText(100, 200)
text = [
"Great Work! You're considered an active person based on your average steps per day.",
"Keep in mind that active people have lower rates of anxiety than sedentary people."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
pdf.showPage()
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFont("Helvetica-Bold", 20)
pdf.setFillColor(colors.HexColor('#808080'))
pdf.drawString(100, 650, "Anxiety Level")
pdf.drawImage("ALpdf.png", 57, 400, width=485, height=200)
pdf.drawString(100, 320, "Locations With Highest Level of Anxiety")
if (len(analysis_EN) > 0):
pdf.drawImage("Location-EN.png", 30, 200, width=570, height=100)
else:
pdf.setFont("Helvetica", 15)
pdf.setFillColor(colors.HexColor('#23495f'))
t = pdf.beginText(130, 250)
text = [
name + " condition was stable through this period,",
"no locations with high anxiety level were detected."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
pdf.showPage()
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFont("Helvetica-Bold", 20)
pdf.setFillColor(colors.HexColor('#808080'))
pdf.drawString(100, 650, "Events With Highest Level of Anxiety")
if (GoogleCalendar == 'true' and len(finalEvents_EN) > 0):
pdf.drawImage("Events-EN.png", 30, 500, width=550, height=100)
elif (GoogleCalendar == 'true' and len(finalEvents_EN) < 0):
pdf.setFont("Helvetica", 15)
pdf.setFillColor(colors.HexColor('#23495f'))
t = pdf.beginText(130, 550)
text = ["No events found associated with high anxiety level"]
for line in text:
t.textLine(line)
pdf.drawText(t)
else:
pdf.setFont("Helvetica", 15)
pdf.setFillColor(colors.HexColor('#23495f'))
t = pdf.beginText(130, 550)
text = [
name + " have not synced Google Calendar events,",
"with thier account."
]
for line in text:
t.textLine(line)
pdf.drawText(t)
if (len(notSyncedDates) != 0):
pdf.setFont("Helvetica", 12)
pdf.setFillColor(colors.HexColor('#d40027'))
pdf.drawString(
75, 95,
"Note: Below dates are missing, because they were not synced correctly:"
)
i = 70
for row in notSyncedDates.itertuples():
pdf.drawString(85, i, '- ' + row.date)
i = i - 20
pdf.save()
# In[68]:
def translate(text):
reshaped_text = arabic_reshaper.reshape(text)
bidi_text = get_display(reshaped_text)
return bidi_text
# In[69]:
def from_en_to_ar(text):
translator = Translator()
result = translator.translate(text, dest='ar')
return result.text
# In[70]:
pdf = canvas.Canvas('Patient-AR.pdf')
pdf.setTitle('تقرير المريض')
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 620, 485, 50, 4, fill=1, stroke=0)
pdf.setFont("Arabic", 22)
pdf.setFillColor(colors.HexColor('#23495f'))
reportDuration = translate(u'مدة التقرير من')
to = translate(u'إلى')
pdf.drawString(
125, 638, dates[len(dates) - 1] + ' ' + to + ' ' + dates[0] + ' ' +
reportDuration)
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 400, 485, 200, 4, fill=1, stroke=0)
pdf.setFont("Arabic", 22)
pdf.setFillColor(colors.HexColor('#23495f'))
patient = translate(u'معلومات المريض')
pdf.drawString(400, 570, patient)
na = translate(u'الاسم:')
ag = translate(u'العمر:')
Es = translate(u'الحالة الوظيفية:')
Ms = translate(u'الحالة الإجتماعية:')
Mi = translate(u'الدخل الشهري:')
Cd = translate(u'الأمراض المزمنة:')
Cs = translate(u'مدخن:')
ge = translate(u'الجنس:')
pdf.setFont("Arabic", 18)
pdf.drawString(445, 550, na)
pdf.drawString(446, 530, ag)
pdf.drawString(400, 510, Es)
pdf.drawString(390, 490, Ms)
pdf.drawString(400, 470, Mi)
pdf.drawString(395, 450, Cd)
pdf.drawString(445, 430, Cs)
pdf.drawString(446, 410, ge)
pdf.setFont("Arabic", 15)
pdf.setFillColor(black)
pdf.drawString(400, 550, name)
pdf.drawString(420, 530, age)
pdf.drawString(350, 510, translate(from_en_to_ar(emp)))
pdf.drawString(355, 490, translate(from_en_to_ar(mar)))
pdf.drawString(360, 470, income)
pdf.drawString(360, 450, translate(from_en_to_ar(chronicD)))
pdf.drawString(420, 430, translate(from_en_to_ar(smoke)))
pdf.drawString(420, 410, translate(from_en_to_ar(gender)))
pdf.setFillColor(colors.HexColor('#bfbfbf'))
pdf.roundRect(100, 560, 120, 30, 4, fill=1, stroke=0)
ga = translate(u'مقياس GAD-7 =')
pdf.setFillColorRGB(1, 1, 1)
pdf.drawString(120, 570, ga)
pdf.setFont("Helvetica-Bold", 15)
pdf.drawString(105, 570, gad)
pdf.setFillColor(colors.HexColor('#e1eff7'))
pdf.roundRect(57, 160, 485, 200, 4, fill=1, stroke=0)
pdf.setFont("Arabic", 22)
pdf.setFillColor(colors.HexColor('#23495f'))
rec = translate(u' التوصيات:')
stepRec = translate(u'توصيات النشاط:')
sleepRec = translate(u'توصيات النوم:')
pdf.drawString(420, 330, rec)
pdf.drawString(380, 300, sleepRec)
pdf.drawString(360, 220, stepRec)
pdf.setFont("Arabic", 15)
pdf.setFillColor(black)
if (sleepRecomendation == True):
text = translate(
u'يوصى بالنوم لمدة تتراوح بين ٧-٩ ساعات في اليوم للحصول على أقل معدل قلق.'
)
text2 = translate(
u'يمكن أن يحسن النوم الجيد ليلاً من صحتك العقلية ويساعدك على إدارة قلقك بشكل أفضل.'
)
pdf.drawString(120, 280, text)
pdf.drawString(80, 260, text2)
else:
text = translate(u'أخبار جيدة! يبدو أنك تحصل على قسط كافٍ من اليوم.')
text2 = translate(
u'يمكن أن يحسن النوم الجيد ليلاً من صحتك العقلية ويساعدك على إدارة قلقك بشكل أفضل.'
)
pdf.drawString(230, 280, text)
pdf.drawString(80, 260, text2)
if (stepsRecomendation == True):
btwnText = translate(u'خطوة في اليوم للحصول على أقل معدل قلق. ')
text = translate(u'يوصى بالمشي على الأقل')
text2 = translate(
u'تذكر أن الأشخاص الأكثر نشاطاً لديهم معدلات قلق أقل من أولئك الغير نشطين.'
)
pdf.drawString(130, 200, btwnText + recomendedSteps + text)
pdf.drawString(120, 180, text2)
else:
text = translate(
u'عمل رائع! بناءاً على معدل خطواتك في اليوم الواحد، أنت تعتبر من الأشخاص النشطين.'
)
text2 = translate(
u'تذكر أن الأشخاص الأكثر نشاطاً لديهم معدلات قلق أقل من أولئك الغير نشطين.'
)
pdf.drawString(100, 200, text)
pdf.drawString(130, 180, text2)
pdf.showPage()
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFont("Arabic", 28)
pdf.setFillColor(colors.HexColor('#808080'))
AL = translate(u'مستوى القلق')
pdf.drawString(400, 650, AL)
loc = translate(u'تحليل المواقع ذات مستوى قلق مرتفع ')
pdf.drawImage("ALpdf.png", 57, 400, width=485, height=200)
pdf.drawString(210, 320, loc)
if (len(analysis_AR) > 0):
pdf.drawImage("Location-AR.png", 10, 200, width=570, height=100)
else:
pdf.setFont("Arabic", 18)
pdf.setFillColor(colors.HexColor('#23495f'))
text = translate(
u'كانت الحالة مستقرة خلال هذه الفترة, لم يتم الكشف عن أي مواقع ذات مستوى قلق مرتفع.'
)
pdf.drawString(50, 250, text)
pdf.showPage()
pdf.drawImage("serene .png", 150, 730, width=300, height=130, mask='auto')
pdf.setFont("Arabic", 28)
pdf.setFillColor(colors.HexColor('#808080'))
EV = translate(u'تحليل الأحداث ذات مستوى قلق مرتفع ')
pdf.drawString(200, 650, EV)
if (GoogleCalendar == 'true' and len(finalEvents_AR) > 0):
pdf.drawImage("Events-AR.png", 20, 500, width=550, height=100)
elif (GoogleCalendar == 'true' and len(finalEvents_EN) < 0):
pdf.setFont("Arabic", 18)
pdf.setFillColor(colors.HexColor('#23495f'))
text = translate(u' لم يتم الكشف أي أحداث ذات مستوى قلق مرتفع.')
pdf.drawString(250, 550, text)
else:
pdf.setFont("Arabic", 18)
pdf.setFillColor(colors.HexColor('#23495f'))
text = translate(
u'المستخدم لم يقم بمزامنة أحداث تقويم قوقل بحساب سيرين.')
pdf.drawString(210, 550, text)
if (len(notSyncedDates) != 0):
pdf.setFont("Arabic", 15)
pdf.setFillColor(colors.HexColor('#d40027'))
note = translate(
u'.ملاحظة: التواريخ المذكورة أدناه غير متضمنة في التحليل لعدم مزامنة البيانات'
)
pdf.drawString(200, 95, note)
i = 70
for row in notSyncedDates.itertuples():
pdf.setFont("Helvetica", 12)
pdf.drawString(450, i, row.date + ' -')
i = i - 20
pdf.save()
# In[71]:
#new method
doct = storage.child(userID +
"/lastGeneratedPatientReport/patientReport-EN").put(
'Patient-EN.pdf')
doct = storage.child(userID +
"/lastGeneratedPatientReport/patientReport-AR").put(
'Patient-AR.pdf')
# In[72]:
os.remove('Patient-EN.pdf')
os.remove('Patient-AR.pdf')
if (len(plot_df) <= 90):
os.remove('ALpdf.png')
else:
for x in range(0, len(dfarray)):
os.remove('AL' + str(x) + 'pdf.png')
if (GoogleCalendar == 'true' and len(finalEvents_AR) > 0):
os.remove('Events-AR.png')
os.remove('Events-EN.png')
if (len(analysis_AR) > 0):
os.remove('Location-AR.png')
os.remove('Location-EN.png')
to_json = plot_df[['date', 'Anxiety']].to_json()
return to_json
def _draw_time_series(indicator, indicator_name, indicator_hat_fourier,
indicator_hat_lstsq, indicator_hat_sindy, node_labels,
test_index):
for node_id in range(indicator.shape[1]):
# Time Series plot
data_frame = pd.DataFrame({
'index': np.arange(indicator.shape[0]),
indicator_name: indicator[:, node_id],
'Fourier': indicator_hat_fourier[:, node_id],
# 'Least_Squares': indicator_hat_lstsq[:, node_id],
'SINDy': indicator_hat_sindy[:, node_id],
})
melted_data_frame = pd.melt(
data_frame,
id_vars=['index'],
value_vars=[
indicator_name,
'Fourier',
# 'Least-Squares',
'SINDy',
])
rc('font', weight=600)
plt.subplots(figsize=(20, 10))
ax = sns.lineplot(x='index',
y='value',
hue='variable',
style='variable',
data=melted_data_frame,
linewidth=4)
node_instrument_id, node_name = node_labels[node_id].split('_')
ax.set_title(get_display(arabic_reshaper.reshape(node_name)),
fontsize=28,
fontweight=500)
ax.set_xlabel(get_display(arabic_reshaper.reshape('روزها')),
fontsize=20,
fontweight=500)
ax.set_ylabel(indicator_name, fontsize=20, fontweight=500)
for axis in ['top', 'bottom', 'left', 'right']:
ax.spines[axis].set_linewidth(3)
ax.tick_params(width=3, length=10, labelsize=16)
plt.savefig(
os.path.join(
OUTPUT_DIR, 'node_%d_%s_%s.png' %
(node_id, node_instrument_id, indicator_name)))
plt.close('all')
# Signal Plot
lag = 5
threshold = 1
influence = 1
indicator_signal = thresholding_alg(indicator[:, node_id], lag,
threshold, influence)[test_index:]
indicator_hat_sindy_signal = \
thresholding_alg(indicator_hat_sindy[:, node_id], lag, threshold, influence)[test_index:]
data_frame = pd.DataFrame({
'index':
np.arange(len(indicator_signal)),
'%s' % indicator_name + get_display(
arabic_reshaper.reshape('قلههای')):
indicator_signal,
'SINDy' + get_display(arabic_reshaper.reshape('قلههای')):
indicator_hat_sindy_signal,
})
melted_data_frame = pd.melt(
data_frame,
id_vars=['index'],
value_vars=[
'%s' % indicator_name +
get_display(arabic_reshaper.reshape('قلههای')),
'SINDy' + get_display(arabic_reshaper.reshape('قلههای')),
])
rc('font', weight=600)
plt.subplots(figsize=(20, 10))
ax = sns.lineplot(x='index',
y='value',
hue='variable',
style='variable',
data=melted_data_frame,
linewidth=4)
node_instrument_id, node_name = node_labels[node_id].split('_')
ax.set_title(get_display(arabic_reshaper.reshape(node_name)),
fontsize=28,
fontweight=500)
ax.set_xlabel(get_display(
arabic_reshaper.reshape('روزهای پیشبینی شده')),
fontsize=20,
fontweight=500)
ax.set_ylabel(get_display(
arabic_reshaper.reshape('قلههای تشخیص داده شده')),
fontsize=20,
fontweight=500)
for axis in ['top', 'bottom', 'left', 'right']:
ax.spines[axis].set_linewidth(3)
ax.tick_params(width=3, length=10, labelsize=16)
plt.savefig(
os.path.join(
OUTPUT_DIR, 'node_%d_%s_%s_peaks.png' %
(node_id, node_instrument_id, indicator_name)))
plt.close('all')
def to_persion_text(text):
return get_display(ar.reshape(text))
a = cv2.waitKey(1)
if frame_counter % 5 == 0:
score = 0
res = ''
try:
proba = model.predict(process_image(img_cropped))[0]
mx = np.argmax(proba)
score = proba[mx] * 100
res = categories[mx][0]
sequence = categories[mx][1]
except:
continue
reshaped_text = arabic_reshaper.reshape(sequence)
bidi_text = get_display(reshaped_text)
frame_counter += 1
img_pil = Image.fromarray(img)
draw = ImageDraw.Draw(img_pil)
draw.text((50, 600), bidi_text, (255, 255, 255), font=font)
img = np.array(img_pil)
#cv2.putText(img, '%s' % (res.upper()), (100,400), cv2.FONT_HERSHEY_SIMPLEX, 4, (255,255,255), 4)
cv2.putText(img, '(score = %.5f)' % (float(score)), (100, 450),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255))
cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
cv2.imshow("img", img)
if a == 27: # when `esc` is pressed
break
def OnConvert(self, evt):
self.tc2.Clear()
reshaped_text = arabic_reshaper.reshape(self.tc1.GetValue())
bidi_text = get_display(reshaped_text)
self.tc2.WriteText(bidi_text)
def print_receipt():
receipt_from_tailpos = loads(request.get_data(as_text=True))
for_printing = receipt_from_tailpos['data']
print(for_printing)
port_serial = "/dev/rfcomm0"
bluetoothSerial = serial.Serial(port_serial, baudrate=115200, timeout=1)
#fontPath = "/home/jiloysss/Documents/spiceco/aljazeera-font/FontAljazeeraColor-lzzD.ttf"
fontPath = "/home/pi/FontAljazeeraColor-lzzD.ttf"
tmpImage = 'receipt.png'
#printWidth = 375
printWidth = 570
height = 600
draw = wDrawing()
draw.font = fontPath
#COMPANY ==============
draw.font_size = 34
draw.text(x=180,y=75,body=for_printing['company'])
#DATE ==================
split_date = for_printing['date'].split()
draw.font_size = 26
draw.text(x=5,y=110,body=split_date[0])
draw.text(x=260,y=110,body=split_date[1])
#ORDER TYPE ==============
draw.font_size = 26
draw.text(x=5,y=145,body="Order Type: " + for_printing['ordertype'])
y_value = 145
#HEADER ==========
if for_printing['header']:
header_value = 160
for x in for_printing['header'].split("\n"):
y_value = y_value + 35
header_value = header_value + 25
draw.text_alignment = "center"
draw.text(x=180,y=header_value,body=x)
draw.text_alignment = "undefined"
draw.text(x=5,y=y_value + 35 ,body="=====================================")
#ITEM PURCHASES
y_value = y_value + 30
for idx,i in enumerate(for_printing['lines']):
if idx != 0:
height += 35
draw.gravity = "north_east"
draw.text(x=5,y=y_value + 10,body=format(float(i['qty'] * i['price']), '.2f'))
draw.gravity = "forget"
if len(i['item_name']) > 22:
quotient = len(i['item_name']) / 22
for xxx in range(0,int(quotient)):
if idx != 0:
height += 35
y_value = y_value + 35
draw.text(x=5,y=y_value,body=i['item_name'][xxx * 22: (xxx+1) * 22])
translation_text = ""
if i['translation_text']:
textReshaped = arabic_reshaper.reshape(i['translation_text'])
textDisplay = get_display(textReshaped)
translation_text = "(" + textReshaped + ")"
y_value = y_value + 35
draw.text(x=5,y=y_value,body=i['item_name'][(int(quotient)*22): len(i['item_name'])] + translation_text )
else:
translation_text = ""
if i['translation_text']:
textReshaped = arabic_reshaper.reshape(i['translation_text'])
textDisplay = get_display(textReshaped)
translation_text = "(" + textReshaped + ")"
y_value = y_value + 35
draw.text(x=5,y=y_value,body=i['item_name'] )
y_value = y_value + 35
draw.text(x=5,y=y_value,body= translation_text)
draw.text(x=5,y=y_value+35,body="=====================================")
y_value = y_value + 35
#SUBTOTAL
draw.text(x=5,y=y_value + 35,body="Subtotal")
draw.gravity = "north_east"
draw.text(x=5,y=y_value + 5,body=for_printing['subtotal'])
draw.gravity = "forget"
y_value = y_value + 35
#DISCOUNT
draw.text(x=5,y=y_value + 35,body="Discount")
draw.gravity = "north_east"
draw.text(x=5,y=y_value + 5,body=for_printing['discount'])
draw.gravity = "forget"
#TAXES VALUES
if len(for_printing['taxesvalues']) > 0:
y_value = y_value + 35
for idx,iii in enumerate(for_printing['taxesvalues']):
if idx != 0:
height += 35
y_value = y_value + 35
draw.text(x=5,y=y_value,body=iii['name'])
draw.gravity = "north_east"
draw.text(x=5,y=y_value - 25,body=str(format(round(float(iii['totalAmount']),2), '.2f')))
draw.gravity = "forget"
#MODE OF PAYMENT
for idx, ii in enumerate(loads(for_printing['mop'])):
if idx != 0:
height += 35
y_value = y_value + 70
type = ii['type']
if ii['translation_text']:
textReshaped = arabic_reshaper.reshape(ii['translation_text'])
textDisplay = get_display(textReshaped)
type += "(" + textReshaped + ")"
draw.text(x=5,y=y_value,body=type)
draw.gravity = "north_east"
draw.text(x=5,y=y_value - 25,body=str(format(float(ii['amount']), '.2f')))
draw.gravity = "forget"
#TOTAL AMOUNT
draw.text(x=5,y=y_value + 35,body="Total Amount")
draw.gravity = "north_east"
draw.text(x=5,y=y_value + 5,body=str(format(float(for_printing['total_amount']), '.2f')))
draw.gravity = "forget"
#CHANGE
draw.text(x=5,y=y_value + 70,body="Change")
draw.gravity = "north_east"
draw.text(x=5,y=y_value + 43,body=str(format(float(for_printing['change']), '.2f')))
draw.gravity = "forget"
draw.text(x=5,y=y_value+105,body="=====================================")
#FOOTER ==========
if for_printing['footer']:
header_value = y_value+105
for x in for_printing['footer'].split("\n"):
y_value = y_value + 35
header_value = header_value + 25
draw.text_alignment = "center"
draw.text(x=180,y=header_value,body=x)
im = wImage(width=printWidth, height=height, background=wColor('#ffffff'))
draw(im)
im.save(filename=tmpImage)
# Print an image with your printer library
printertest = printer.File(port_serial)
printertest.set(align="left")
printertest.image(tmpImage)
printertest.cut()
print("SAMOKA GYUD Oi")
bluetoothSerial.close()
return {}
def bidiRegion(region, view, edit):
txt = view.substr(region)
reshaped_text = arabic_reshaper.reshape(txt)
view.replace(edit, region, reshaped_text)
def Upload_Image():
file = asfile = askopenfile(title='Upload Image',
filetypes=[('Image Files', [
'.jpeg', '.jpg', '.png', '.gif', '.tiff',
'.tif', '.bmp'
])])
if file is not None:
#print(file.name)
image = cv2.imread(file.name)
text = ''
image = cv2.resize(image, (600, 500))
blob = cv2.dnn.blobFromImage(image,
0.00392, (416, 416), (0, 0, 0),
True,
crop=False)
net.setInput(blob)
layer_names = net.getLayerNames()
output_layers = [
layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()
]
output_layers = net.forward(output_layers)
class_ids = []
confidences = []
boxes = []
for out in output_layers:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
center_x = int(detection[0] * image.shape[1])
center_y = int(detection[1] * image.shape[0])
w = int(detection[2] * image.shape[1])
h = int(detection[3] * image.shape[0])
x = center_x - w / 2
y = center_y - h / 2
class_ids.append(class_id)
confidences.append(float(confidence))
boxes.append([x, y, w, h])
indices = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
for i in indices:
i = i[0]
box = boxes[i]
x = box[0]
y = box[1]
w = box[2]
h = box[3]
text = str(classes[class_ids[i]][1])
font = ImageFont.truetype("font.ttf", 35)
reshaped_text = arabic_reshaper.reshape(text)
arabic_text = get_display(reshaped_text)
#print(arabic_text)
image_pil = Image.fromarray(image)
draw = ImageDraw.Draw(image_pil)
draw.text((round(x), round(y) - 50),
arabic_text, (255, 255, 255),
font=font)
image = np.array(image_pil)
cv2.rectangle(image, (round(x), round(y)),
(round(x + w), round(y + h)), (255, 255, 255), 2)
#cv2.putText(image, "{:.0f}%".format(confidences[i]*100), (round(x),round(y)-40), cv2.FONT_HERSHEY_SIMPLEX, 1,(0,0,0), 2)
cv2.imshow("Object Detection Using YOLOv3", image)
cv2.waitKey()
cv2.destroyAllWindows()
def getPicture(poem, poet):
allBGs = glob.glob('/home/ali/Pictures/background/*.*')
selected = randint(0, len(allBGs) - 1)
pic = allBGs[selected]
img = Image.open(pic)
img = img.resize((800, 300))
offset = 200
draw = ImageDraw.Draw(img)
sentences = poem
maxSize = 0
boundingSize = (550, 300)
for sent in sentences:
if (len(sent) > maxSize):
maxSize = len(sent)
maxSent = sent
t1 = arabic_reshaper.reshape(maxSent.decode('utf-8'))
maxSent = get_display(t1)
fontSize = 2
fontAddress = "/home/ali/Fonts/Mj_Sandbad.ttf"
while (1):
font = ImageFont.truetype(fontAddress, fontSize)
draw.setfont(font)
width = draw.textsize(maxSent)[0]
height = len(sentences) * draw.textsize(maxSent)[1]
if (width < boundingSize[0] and height < boundingSize[1]):
fontSize = fontSize + 1
continue
else:
break
font = ImageFont.truetype(fontAddress, fontSize - 1)
draw.setfont(font)
i = 0
W, H = boundingSize
color = (255, 255, 255)
for sent in sentences:
t1 = arabic_reshaper.reshape(sent.decode('utf-8'))
text = get_display(t1)
size = draw.textsize(text)
## draw.text((x, y),"Sample Text",(r,g,b))
draw.text(
(W / 2 - size[0] / 2 + offset,
H / 2 - len(sentences) * size[1] / 2 - size[1] / 4 + i * size[1]),
text, color)
i = i + 1
font = ImageFont.truetype(fontAddress, 25)
draw.setfont(font)
t1 = arabic_reshaper.reshape(poet.decode('utf-8'))
ppoet = get_display(t1)
size = draw.textsize(ppoet)
position = (W / 2 - size[0] / 2, H - size[1] - 20)
#pixel = img.getpixel(position)
#hsv = colorsys.rgb_to_hsv(float(pixel[0])/255,float(pixel[1])/255,float(pixel[2])/255)
#rgb = colorsys.hsv_to_rgb(((hsv[0]-.5)*360%360)/360,1-hsv[1],1-hsv[2])
rgb = (1, 1, 1)
draw.text(position, ppoet,
(int(255 * rgb[0]), int(255 * rgb[1]), int(255 * rgb[2])))
avatar = getAvatar(poet)
avatar = avatar.resize([offset, offset])
img.paste(avatar, (0, img.size[1] - offset), avatar)
return img
def printit_ar(pname, ti, ofc, tnu, tas, cticket, lang=None):
def fsizeit(text, t, f):
ltxt = "A" * len(t)
return f.getsize(t)
def center(text, t, f):
fs1, fs2 = fsizeit(text, t, f)
return ((text.size[0] - fs1) / 2, (text.size[1] - fs2) / 2)
if name == 'nt':
fpath = absolute_path('static\\gfonts\\arial.ttf')
else:
fpath = absolute_path('static/gfonts/arial.ttf')
fonts = [
ImageFont.truetype(fpath, 50),
ImageFont.truetype(fpath, 30),
ImageFont.truetype(fpath, 25)
]
logo = 'FQM ' + VERSION[:4]
title = u'نظام إدارة الحشود الحر'
title = arabic_reshaper.reshape(title)
title = get_display(title)
link = 'http://fqms.github.io'
border = "#" * 20
ticket = str(ti)
officet = u'المكتب : ' + ofc
office = arabic_reshaper.reshape(officet)
office = get_display(office)
try:
taskt = u'المهمة : ' + tas
except Exception:
taskt = tas
task = arabic_reshaper.reshape(taskt)
task = get_display(task)
datet = u'الوقت : '
datet += str(datetime.now())[:-7]
date = arabic_reshaper.reshape(datet)
date = get_display(date)
aheadt = u'تذاكر قبلك : '
aheadt += str(tnu)
ahead = arabic_reshaper.reshape(aheadt)
ahead = get_display(ahead)
cutit = u'التذكرة الحالية : '
cutit += str(cticket)
cuti = arabic_reshaper.reshape(cutit)
cuti = get_display(cuti)
w = 400
bt_1 = Image.new('RGB', (w, 60), "white")
bt_2 = Image.new('RGB', (w, 60), "white")
bt_3 = Image.new('RGB', (w, 60), "white")
st_1 = Image.new('RGB', (w, 50), "white")
st_2 = Image.new('RGB', (w, 50), "white")
st_3 = Image.new('RGB', (w, 50), "white")
st_4 = Image.new('RGB', (w, 50), "white")
st_5 = Image.new('RGB', (w, 50), "white")
st_6 = Image.new('RGB', (w, 50), "white")
st_7 = Image.new('RGB', (w, 50), "white")
st_8 = Image.new('RGB', (w, 50), "white")
tt = 50 * 8
tt += 60 * 3
mt = Image.new('RGB', (w, tt), "white")
bd_1 = ImageDraw.Draw(bt_1)
bd_2 = ImageDraw.Draw(bt_2)
bd_3 = ImageDraw.Draw(bt_3)
sd_1 = ImageDraw.Draw(st_1)
sd_2 = ImageDraw.Draw(st_2)
sd_3 = ImageDraw.Draw(st_3)
sd_4 = ImageDraw.Draw(st_4)
sd_5 = ImageDraw.Draw(st_5)
sd_6 = ImageDraw.Draw(st_6)
sd_7 = ImageDraw.Draw(st_7)
sd_8 = ImageDraw.Draw(st_8)
md = ImageDraw.Draw(mt)
b = "black"
bd_1.text(center(bt_1, logo, fonts[0]), logo, font=fonts[0], fill=b)
bd_2.text(center(bt_2, title, fonts[1]), title, font=fonts[1], fill=b)
bd_3.text(center(bt_3, ticket, fonts[0]), ticket, font=fonts[0], fill=b)
sd_1.text(center(st_1, link, fonts[2]), link, font=fonts[2], fill=b)
sd_2.text(center(st_2, border, fonts[2]), border, font=fonts[2], fill=b)
sd_3.text(center(st_3, border, fonts[2]), border, font=fonts[2], fill=b)
sd_4.text(center(st_4, office, fonts[2]), office, font=fonts[2], fill=b)
sd_5.text(center(st_5, task, fonts[2]), task, font=fonts[2], fill=b)
sd_6.text(center(st_6, date, fonts[2]), date, font=fonts[2], fill=b)
sd_7.text(center(st_7, ahead, fonts[2]), ahead, font=fonts[2], fill=b)
sd_8.text(center(st_8, cuti, fonts[2]), cuti, font=fonts[2], fill=b)
tts = 0
mt.paste(bt_1, (0, 0))
tts += bt_1.size[1]
mt.paste(bt_2, (0, tts))
tts += bt_2.size[1]
mt.paste(st_1, (0, tts))
tts += st_1.size[1]
mt.paste(st_2, (0, tts))
tts += st_2.size[1]
mt.paste(bt_3, (0, tts))
tts += bt_3.size[1]
mt.paste(st_3, (0, tts))
tts += st_3.size[1]
mt.paste(st_4, (0, tts))
tts += st_4.size[1]
mt.paste(st_8, (0, tts))
tts += st_8.size[1]
mt.paste(st_7, (0, tts))
tts += st_7.size[1]
mt.paste(st_5, (0, tts))
tts += st_5.size[1]
mt.paste(st_6, (0, tts))
iname = 'dummy.jpg'
finame = path.join(getcwd(), iname)
mt.save(iname, format="JPEG")
pname.image(iname, fragment_height=tt, high_density_vertical=True)
pname.cut()
pname.close()
if path.isfile(finame):
remove(finame)
def normalize_text(text):
text = reverse_transcription(text)
text = arabic_reshaper.reshape(text)
text = reverse_transcription(text)
return text
def _generate_v2_certificate(self, student_name, download_dir,
verify_dir, filename='Certificate.pdf'):
"""
We have a new set of certificates that we want to generate which means brand new generation of certs
"""
# 8.5x11 page size 279.4mm x 215.9mm
WIDTH = 279 # width in mm (8.5x11)
HEIGHT = 216 # height in mm (8.5x11)
verify_uuid = uuid.uuid4().hex
download_uuid = uuid.uuid4().hex
download_url = "{base_url}/{cert}/{uuid}/{file}".format(
base_url=settings.CERT_DOWNLOAD_URL,
cert=S3_CERT_PATH, uuid=download_uuid, file=filename
)
filename = os.path.join(download_dir, download_uuid, filename)
# This file is overlaid on the template certificate
overlay_pdf_buffer = StringIO.StringIO()
c = canvas.Canvas(overlay_pdf_buffer)
c.setPageSize((WIDTH * mm, HEIGHT * mm))
# register all fonts in the fonts/ dir,
# there are more fonts in here than we need
# but the performance hit seems minimal
for font_file in glob('{0}/fonts/*.ttf'.format(self.template_dir)):
font_name = os.path.basename(os.path.splitext(font_file)[0])
pdfmetrics.registerFont(TTFont(font_name, font_file))
styleOpenSans = ParagraphStyle(name="opensans-regular", leading=10,
fontName='OpenSans-Regular')
styleArial = ParagraphStyle(name="arial", leading=10,
fontName='Arial Unicode')
# Text is overlayed top to bottom
# * Issued date (top right corner)
# * "This is to certify that"
# * Student's name
# * "successfully completed"
# * Course name
# * "a course of study.."
# * honor code url at the bottom
########
#
# New things below
#
########
#### STYLE: typeface assets
addMapping('AvenirNext-Regular', 0, 0, 'AvenirNext-Regular')
addMapping('AvenirNext-DemiBold', 1, 0, 'AvenirNext-DemiBold')
#### STYLE: grid/layout
LEFT_INDENT = 23 # mm from the left side to write the text
MAX_WIDTH = 150 # maximum width on the content in the cert, used for wrapping
#### STYLE: template-wide typography settings
style_type_metacopy_size = 13
style_type_metacopy_leading = 10
style_type_footer_size = 8
style_type_name_size = 36
style_type_name_leading = 53
style_type_name_med_size = 28
style_type_name_med_leading = 41
style_type_name_small_size = 22
style_type_name_small_leading = 27
style_type_course_size = 24
style_type_course_leading = 28
style_type_course_small_size = 16
style_type_course_small_leading = 20
#### STYLE: template-wide color settings
style_color_metadata = colors.Color(0.541176, 0.509804, 0.560784)
style_color_name = colors.Color(0.000000, 0.000000, 0.000000)
#### STYLE: positioning
pos_metacopy_title_y = 120
pos_metacopy_achivement_y = 88
pos_metacopy_org_y = 50
pos_name_y = 94
pos_name_med_y = 95
pos_name_small_y = 95
pos_name_no_wrap_offset_y = 2
pos_course_y = 68
pos_course_small_y = 66
pos_course_no_wrap_offset_y = 5
pos_footer_url_x = 83
pos_footer_url_y = 20
pos_footer_date_x = LEFT_INDENT
pos_footer_date_y = 20
#### STYLE: verified settings
v_style_color_course = colors.Color(0.701961, 0.231373, 0.400000)
#### HTML Parser ####
# Since the final string is HTML in a PDF we need to un-escape the html
# when calculating the string width.
html = HTMLParser()
#### ================== ####
#### ELEM: Metacopy
styleAvenirNext = ParagraphStyle(name="avenirnext-regular", fontName='AvenirNext-Regular')
styleAvenirNext.alignment = TA_LEFT
styleAvenirNext.fontSize = style_type_metacopy_size
styleAvenirNext.leading = style_type_metacopy_leading
styleAvenirNext.textColor = style_color_metadata
#### ELEM: Metacopy - Title: This is to certify that
if self.template_type == 'verified':
y_offset = pos_metacopy_title_y
paragraph_string = 'This is to certify that'
paragraph = Paragraph(paragraph_string, styleAvenirNext)
paragraph.wrapOn(c, WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
#### ================== ####
####### ELEM: Student Name
# default is to use Avenir for the name,
# will fall back to Arial if there are
# unusual characters
y_offset_name = pos_name_y
y_offset_name_med = pos_name_med_y
y_offset_name_small = pos_name_small_y
styleAvenirStudentName = ParagraphStyle(name="avenirnext-demi", fontName='AvenirNext-DemiBold')
styleAvenirStudentName.leading = style_type_name_small_size
style = styleAvenirStudentName
html_student_name = html.unescape(student_name)
larger_width = stringWidth(html_student_name.decode('utf-8'),
'AvenirNext-DemiBold', style_type_name_size) / mm
smaller_width = stringWidth(
html_student_name.decode('utf-8'),
'AvenirNext-DemiBold', style_type_name_small_size) / mm
#TODO: get all strings working reshaped and handling bi-directional strings
paragraph_string = arabic_reshaper.reshape(student_name.decode('utf-8'))
paragraph_string = get_display(paragraph_string)
# Avenir only supports Latin-1
# Switch to using OpenSans if we can
if self._use_non_latin(student_name):
style = styleOpenSans
larger_width = stringWidth(html_student_name.decode('utf-8'),
'OpenSans-Regular', style_type_name_size) / mm
# if we can't use OpenSans, use Arial
if self._use_unicode_font(student_name):
style = styleArial
larger_width = stringWidth(html_student_name.decode('utf-8'),
'Arial Unicode', style_type_name_size) / mm
# if the name is too long, shrink the font size
if larger_width < MAX_WIDTH:
style.fontSize = style_type_name_size
style.leading = style_type_name_leading
y_offset = y_offset_name
elif smaller_width < MAX_WIDTH:
y_offset = y_offset_name_med + pos_name_no_wrap_offset_y
style.fontSize = style_type_name_med_size
style.leading = style_type_name_med_leading
else:
y_offset = y_offset_name_small
style.fontSize = style_type_name_small_size
style.leading = style_type_name_small_leading
style.textColor = style_color_name
style.alignment = TA_LEFT
paragraph = Paragraph(paragraph_string, style)
paragraph.wrapOn(c, MAX_WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
#### ================== ####
##### ELEM: Metacopy - Achievement: successfully completed and received a passing grade in
y_offset = pos_metacopy_achivement_y
paragraph_string = 'successfully completed and received a passing grade in'
paragraph = Paragraph("{0}".format(paragraph_string), styleAvenirNext)
paragraph.wrapOn(c, WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
#### ================== ####
##### ELEM: Course Name
y_offset_larger = pos_course_y
y_offset_smaller = pos_course_small_y
styleAvenirCourseName = ParagraphStyle(name="avenirnext-demi", fontName='AvenirNext-DemiBold')
styleAvenirCourseName.textColor = style_color_name
if self.template_type == 'verified':
styleAvenirCourseName.textColor = v_style_color_course
paragraph_string = "{0}: {1}".format(self.course, self.long_course)
html_paragraph_string = html.unescape(paragraph_string)
larger_width = stringWidth(html_paragraph_string.decode('utf-8'),
'AvenirNext-DemiBold', style_type_course_size) / mm
smaller_width = stringWidth(html_paragraph_string.decode('utf-8'),
'AvenirNext-DemiBold', style_type_course_small_size) / mm
if larger_width < MAX_WIDTH:
styleAvenirCourseName.fontSize = style_type_course_size
styleAvenirCourseName.leading = style_type_course_leading
y_offset = y_offset_larger
elif smaller_width < MAX_WIDTH:
styleAvenirCourseName.fontSize = style_type_course_small_size
styleAvenirCourseName.leading = style_type_course_small_leading
y_offset = y_offset_smaller + pos_course_no_wrap_offset_y
else:
styleAvenirCourseName.fontSize = style_type_course_small_size
styleAvenirCourseName.leading = style_type_course_small_leading
y_offset = y_offset_smaller
styleAvenirCourseName.alignment = TA_LEFT
paragraph = Paragraph(paragraph_string, styleAvenirCourseName)
paragraph.wrapOn(c, MAX_WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
#### ================== ####
#### ELEM: Metacopy - Org: a course of study...
y_offset = pos_metacopy_org_y
paragraph_string = "{2} offered by {0}" \
", an online learning<br /><br />initiative of " \
"{1} through edX.".format(
self.org, self.long_org, self.course_association_text)
paragraph = Paragraph(paragraph_string, styleAvenirNext)
paragraph.wrapOn(c, WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
#### ================== ####
##### ELEM: Footer
styleAvenirFooter = ParagraphStyle(name="avenirnext-demi", fontName='AvenirNext-DemiBold')
styleAvenirFooter.alignment = TA_LEFT
styleAvenirFooter.fontSize = style_type_footer_size
##### ELEM: Footer - Issued on Date
x_offset = pos_footer_date_x
y_offset = pos_footer_date_y
paragraph_string = "Emitido {0}".format(self.issued_date) # Issued
# Right justified so we compute the width
paragraph = Paragraph("{0}".format(
paragraph_string), styleAvenirFooter)
paragraph.wrapOn(c, WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, LEFT_INDENT * mm, y_offset * mm)
########
#### ================== ####
##### ELEM: Footer - Verify Authenticity URL
y_offset = pos_footer_url_y
x_offset = pos_footer_url_x
paragraph_string = "<a href='https://{bucket}/{verify_path}/{verify_uuid}'>" \
"https://{bucket}/{verify_path}/{verify_uuid}</a>"
paragraph_string = paragraph_string.format(bucket=BUCKET,
verify_path=S3_VERIFY_PATH,
verify_uuid=verify_uuid)
paragraph = Paragraph(paragraph_string, styleAvenirFooter)
paragraph.wrapOn(c, WIDTH * mm, HEIGHT * mm)
paragraph.drawOn(c, x_offset * mm, y_offset * mm)
c.showPage()
c.save()
# Merge the overlay with the template, then write it to file
output = PdfFileWriter()
overlay = PdfFileReader(overlay_pdf_buffer)
# We need a page to overlay on.
# So that we don't have to open the template
# several times, we open a blank pdf several times instead
# (much faster)
blank_pdf = PdfFileReader(
file("{0}/blank-letter.pdf".format(self.template_dir), "rb")
)
final_certificate = blank_pdf.getPage(0)
final_certificate.mergePage(self.template_pdf.getPage(0))
final_certificate.mergePage(overlay.getPage(0))
output.addPage(final_certificate)
self._ensure_dir(filename)
outputStream = file(filename, "wb")
output.write(outputStream)
outputStream.close()
self._generate_verification_page(
student_name,
filename,
verify_dir,
verify_uuid,
download_url
)
return (download_uuid, verify_uuid, download_url)
def parse_link(self, response):
item = ArticleItem()
title = ""
try:
title = get_display(
arabic_reshaper.reshape(u'' + self.cleanhtml(
response.xpath("//*[@class='background_title']/h1/text()").
extract_first()).strip()))
except (RuntimeError, TypeError, NameError):
pass
item["title"] = title
author = ""
try:
author = get_display(
arabic_reshaper.reshape(u'' + self.cleanhtml(
response.xpath("//h4[@class='gold']/text()").extract_first(
)).strip()))
except (RuntimeError, TypeError, NameError):
pass
item["author"] = author
item["link"] = response.url
description = list()
try:
description.extend([
get_display(arabic_reshaper.reshape(u'' + self.cleanhtml(d)))
for d in response.xpath(
"//*[@class='fontstyleDivBody detailedBody']/div/div/div").
extract()
])
except (RuntimeError, TypeError, NameError):
pass
item["description"] = description
comment = list()
names = list()
feeds = list()
try:
comment.extend([
get_display(arabic_reshaper.reshape(u'' + self.cleanhtml(d)))
for d in response.xpath(
"//*[@class='comment-text']/text()").extract()
])
names.extend([
get_display(arabic_reshaper.reshape(u'' + self.cleanhtml(d)))
for d in response.xpath(
"//*[@class='commenter']/text()").extract()
])
feeds.extend(
map(add, [
int(self.cleanhtml(d)) for d in response.xpath(
"//*[@class='comments-like clsLike clicked']/text()").
extract()
], [
int(self.cleanhtml(d)) for d in response.xpath(
"//*[@class='comments-unlike clsLike clicked']/text()"
).extract()
]))
except (RuntimeError, TypeError, NameError):
pass
item["comments"] = comment
item["names"] = names
item["feedbacks"] = feeds
yield item
def order_and_shape(wc):
return bidi.algorithm.get_display(arabic_reshaper.reshape(wc[0])), wc[1]
# a 1080x1920 jpg file
imageFile = "./assets/images/input/tweetNegar.jpg"
# load the profile photo
urllib.request.urlretrieve(profile, "./assets/user/profile0.jpg") # Save Profile Photo from twitter
user_profile = Image.open("./assets/user/profile0.jpg") # load profile photo
profile = user_profile.resize((180, 180))
# load the font and theme image
font = ImageFont.truetype(fontFile, 50)
image = Image.open(imageFile)
# firts you must prepare your text (you dont need this for english text)
username = user_name
reshaped_text = arabic_reshaper.reshape(username) # correct its shape
bidi_name = get_display(reshaped_text)
# tweet content
# Content Should Wrap in a Better Way, this is just for test!!
my_wrap = textwrap.TextWrapper(width = 30)
wrap_list = my_wrap.wrap(text=tweet_content)
text = ''
reshaped_text = arabic_reshaper.reshape(text) # correct its shape
bidi_text = get_display(reshaped_text) # correct its direction
# get image size
(w, h) = image.size
# text location
def save(self, name):
reshaped_text = arabic_reshaper.reshape(name)
config_file = open("config.cfg", "a")
config_file.write(self.id + " " + self.gp + " " + reshaped_text + "\n")
config_file.close()
def make_farsi_text(x):
reshaped_text = arabic_reshaper.reshape(x)
farsi_text = get_display(reshaped_text)
return farsi_text
def getPicture(poem,poet):
allBGs = glob.glob('/home/ali/Pictures/background/*.*')
selected = randint(0,len(allBGs)-1)
pic = allBGs[selected]
img = Image.open(pic)
img= img.resize((800,300))
offset = 200;
draw = ImageDraw.Draw(img)
sentences = poem
maxSize = 0
boundingSize = (550,300)
for sent in sentences:
if(len(sent) > maxSize):
maxSize = len(sent)
maxSent = sent
t1 = arabic_reshaper.reshape(maxSent.decode('utf-8'))
maxSent = get_display(t1)
fontSize =2
fontAddress = "/home/ali/Fonts/Mj_Sandbad.ttf"
while(1):
font = ImageFont.truetype(fontAddress, fontSize)
draw.setfont(font)
width = draw.textsize(maxSent)[0]
height = len(sentences)* draw.textsize(maxSent)[1]
if(width<boundingSize[0] and height < boundingSize[1]):
fontSize = fontSize+1
continue
else:
break
font = ImageFont.truetype(fontAddress, fontSize-1)
draw.setfont(font)
i=0
W,H = boundingSize
color = (255,255,255)
for sent in sentences:
t1 = arabic_reshaper.reshape(sent.decode('utf-8'))
text = get_display(t1)
size = draw.textsize(text)
## draw.text((x, y),"Sample Text",(r,g,b))
draw.text((W/2-size[0]/2+offset, H/2-len(sentences)*size[1]/2-size[1]/4+i*size[1]),text, color)
i=i+1
font = ImageFont.truetype(fontAddress, 25)
draw.setfont(font)
t1 = arabic_reshaper.reshape(poet.decode('utf-8'))
ppoet = get_display(t1)
size = draw.textsize(ppoet)
position = (W/2-size[0]/2,H-size[1]-20)
#pixel = img.getpixel(position)
#hsv = colorsys.rgb_to_hsv(float(pixel[0])/255,float(pixel[1])/255,float(pixel[2])/255)
#rgb = colorsys.hsv_to_rgb(((hsv[0]-.5)*360%360)/360,1-hsv[1],1-hsv[2])
rgb = (1,1,1)
draw.text(position,ppoet,(int(255*rgb[0]),int(255*rgb[1]),int(255*rgb[2])))
avatar = getAvatar(poet)
avatar = avatar.resize([offset,offset])
img.paste(avatar, (0, img.size[1]-offset), avatar)
return img
def run(self, edit): region = sublime.Region(0, self.view.size()) txt = self.view.substr(region) reshaped_text = arabic_reshaper.reshape(txt) bdiText = get_display(reshaped_text) self.view.replace(edit, region, bdiText)
