def createGui(self):
# self.chatBox = self.createChatBox()
self.messageWindow = self.createMessageWindow()
headerDiv = Div(text="<link rel='stylesheet' type='text/css' href='templates/styles.css'>")
self.createKeyboardCoordinates()
self.englishInput = AutocompleteInput(value = "",title = "English:",completions = ["bath","bathtub"])
self.englishInput.on_change("value",self.englishBoxCallback)
self.text_input = TextInput(value="", title="Message:",width = self.keyboardWidth - 300)
self.text_input.on_change("value",self.textBoxcallback)
sendButton = Button(label="↩",button_type = "primary")
sendButton.on_click(self.sendMessage)
self.suggestedCategoryRow = self.createEmojiFigure("Row","Suggested")
self.suggestedCategoryRow.on_event(Tap,self.suggestedSelectCallback)
self.suggestedCategoryRow.title.text = "💡"
self.suggestedCategoryRow.title.text_font_size = "20pt"
mainCategoryFigure = self.createEmojiFigure("Column","Main")
mainCategoryFigure.title.text = "🐘📦"
mainCategoryFigure.title.text_font_size = "30pt"
mainCategoryFigure.on_event(Tap,self.mainCategorySelectCallback)
mainCategoryFigure.js_on_event(DoubleTap,self.playSound)
subCategoryFigure = self.createEmojiFigure("Column","Sub")
subCategoryFigure.title.text = "🥖📦"
subCategoryFigure.title.text_font_size = "30pt"
subCategoryFigure.name = "sub"
subCategoryFigure.on_event(Tap,self.subCategorySelectCallback)
self.emojiKeyboard = self.createMainEmojiWindow()
self.emojiKeyboard.title.text = "⌨"
self.emojiKeyboard.title.text_font_size = "30pt"
self.gui = column(
headerDiv,
self.messageWindow,
row(self.englishInput,self.text_input,sendButton),
self.suggestedCategoryRow,
row(self.emojiKeyboard,subCategoryFigure,mainCategoryFigure)
)
split = Dropdown(label="Split button", button_type="danger", menu=split_menu)
checkbox_group = CheckboxGroup(labels=["Option 1", "Option 2", "Option 3"],
active=[0, 1])
radio_group = RadioGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
checkbox_button_group = CheckboxButtonGroup(
labels=["Option 1", "Option 2", "Option 3"], active=[0, 1])
radio_button_group = RadioButtonGroup(
labels=["Option 1", "Option 2", "Option 3"], active=0)
text_input = TextInput(placeholder="Enter value ...")
autocomplete_input = AutocompleteInput()
select = Select(options=["Option 1", "Option 2", "Option 3"])
multi_select = MultiSelect(options=["Option %d" % (i + 1) for i in range(16)],
size=6)
slider = Slider(value=10, start=0, end=100)
range_slider = RangeSlider()
#date_range_slider = DateRangeSlider(value=(date(2016, 1, 1), date(2016, 12, 31)))
date_picker = DatePicker()
paragraph = Paragraph(text="some text")
RadioButtonGroup(
labels=["Radio Option 1", "Radio Option 2", "Radio Option 3"],
button_type="default",
active=0),
RadioButtonGroup(
labels=["Radio Option 4", "Radio Option 5", "Radio Option 6"],
button_type="primary",
active=1),
RadioButtonGroup(
labels=["Radio Option 7", "Radio Option 8", "Radio Option 9"],
button_type="success",
active=2),
TextInput(placeholder="TextInput 1"),
TextInput(placeholder="TextInput 2"),
TextInput(placeholder="TextInput 3"),
AutocompleteInput(placeholder="AutocompleteInput 1 ...",
completions=["aaa", "aab", "aac", "baa", "caa"]),
AutocompleteInput(placeholder="AutocompleteInput 2 ...",
completions=["AAA", "AAB", "AAC", "BAA", "CAA"]),
AutocompleteInput(placeholder="AutocompleteInput 3 ...",
completions=["000", "001", "002", "100", "200"]),
DatePicker(value=date(2018, 9, 1)),
DatePicker(value=date(2018, 9, 2)),
DatePicker(value=date(2018, 9, 3)),
)
#Slider(value=10, start=0, end=100, step=0.5),
#RangeSlider(value=[20, 30], start=0, end=100, step=0.5),
#DateSlider(value=date(2018, 9, 1), start=date(2018, 1, 1), end=date(2018, 12, 31)),
#DateRangeSlider(value=(date(2018, 9, 1), date(2018, 9, 30)), start=date(2018, 1, 1), end=date(2018, 12, 31)),
#CheckboxGroup(labels=["Checkbox Option 1", "Checkbox Option 2", "Checkbox Option 3"], active=[0, 1]),
def mapping_sentences_words(input_file):
output_file(filename="../dashboards/sentences_words.html", title="Intermediate representations")
###################################################
# PREPARING DATA
###################################################
index = 0
id_sentence = list()
id_word = list()
x = list()
y = list()
sentences = list()
language_sentence = list()
language_word = list()
words = list()
x_words = list()
y_words = list()
links = dict()
with open(input_file, 'r') as file:
array = json.load(file)
data = array['content']
for idx, translations in data.items():
nbr_lang = len(translations)
for lang, info in translations.items():
id_sentence.append(idx)
language_sentence.append(lang)
sentences.append(info['sentence'])
x.append(info['embedding'][0])
y.append(info['embedding'][1])
for word, emb in info['words'].items():
id_word.append(idx)
language_word.append(lang)
words.append(word)
x_words.append(emb[0])
y_words.append(emb[1])
for i in range(nbr_lang):
links[index + i] = [index + j for j in range(nbr_lang) if j != i]
index += nbr_lang
source_sentence_dict = {
"id": id_sentence,
"x": x,
"y": y,
"lang": language_sentence,
"sentence": sentences
}
source_word_dict = {
"id": id_word,
"x": x_words,
"y": y_words,
"lang": language_word,
"word": words
}
source_sentences = ColumnDataSource(source_sentence_dict)
source_words = ColumnDataSource(source_word_dict)
source_words_visible = ColumnDataSource(source_word_dict)
###################################################
# SET UP SENTENCE FIGURE
###################################################
tools = "hover, tap, box_select, reset, help"
p = figure(plot_width=800, plot_height=700, tools=tools, title='Intermediate representations')
cr = p.circle('x', 'y',
size=6, alpha=0.6,
hover_color='yellow', hover_alpha=1.0,
source=source_sentences,
color=factor_cmap('lang',
palette=['red', 'blue', 'green'],
factors=['en', 'fr', 'es']),
legend='lang',
name="sentences")
###################################################
# SET UP LINKS BETWEEN TRANSLATIONS
###################################################
source = ColumnDataSource({'x0': [], 'y0': [], 'x1': [], 'y1': []})
sr = p.segment(x0='x0', y0='y0', x1='x1', y1='y1', color='black', alpha=0.6, line_width=1, source=source)
code = """
var links = %s;
var data = {'x0': [], 'y0': [], 'x1': [], 'y1': []};
var cdata = circle.data;
var indices = cb_data.index['1d'].indices;
for (var i = 0; i < indices.length; i++) {
var ind0 = indices[i]
for (var j = 0; j < links[ind0].length; j++) {
var ind1 = links[ind0][j];
data['x0'].push(cdata.x[ind0]);
data['y0'].push(cdata.y[ind0]);
data['x1'].push(cdata.x[ind1]);
data['y1'].push(cdata.y[ind1]);
}
}
segment.data = data;
""" % links
###################################################
# ADD LINKS IN HOVERTOOL
###################################################
callback = CustomJS(args={'circle': cr.data_source,
'segment': sr.data_source}, code=code)
p.add_tools(HoverTool(callback=callback, renderers=[cr]))
hover = p.select(dict(type=HoverTool))
hover.tooltips = [
("sentence", "@sentence"),
]
hover.names = [
"sentences"
]
###################################################
# SET UP WORD FIGURE
###################################################
p_w = figure(title='Words', tools="reset")
p_w.circle('x', 'y',
size=6, alpha=0.6,
hover_color='yellow', hover_alpha=1.0,
selection_color='yellow',
nonselection_color='white',
source=source_words_visible,
color=factor_cmap('lang',
palette=['red', 'blue', 'green'],
factors=['en', 'fr', 'es']),
legend='lang',
name="words")
hover_word = HoverTool(tooltips=[('word', '@word')],
names=['words'])
p_w.add_tools(hover_word)
source_sentences.selected.js_on_change('indices', CustomJS(args=dict(sentences=source_sentences,
words=source_words,
words_visible=source_words_visible),
code="""
var inds = cb_obj.indices;
var sentences = sentences.data;
var words = words.data;
var words_visible = words_visible.data
words_visible.id = []
words_visible.x = []
words_visible.y = []
words_visible.lang = []
words_visible.word = []
console.log(sentences.id[inds])
for (var i = 0; i < words.x.length; i++) {
if (words.id[i] == sentences.id[inds]) {
words_visible.id.push(words.id[i])
words_visible.x.push(words.x[i])
words_visible.y.push(words.y[i])
words_visible.lang.push(words.lang[i])
words_visible.word.push(words.word[i])
}
}
words_visible.change.emit();
""")
)
text_input = AutocompleteInput(title='Search a sentence', completions=sentences)
###################################################
# CREATION OF THE LAYOUT
###################################################
# window = layout([p, words], sizing_mode='stretch_both')
window = row(p, column(p_w, text_input))
show(window)
source_words_visible_dict['lang'].append(
source_words.data['lang'][idx])
source_words_visible_dict['word'].append(
source_words.data['word'][idx])
source_words_visible.data = source_words_visible_dict
# source_words_visible.selected.indices = indices
source_sentences.selected.on_change('indices', update_words)
###################################################
# ADD TEXT INPUT
###################################################
text_input = AutocompleteInput(title='Select a sentence',
completions=sentences)
def update_sentences(attr, old, new):
sentence = text_input.value
ind = [
j for j, sent in enumerate(source_sentences.data['sentence'])
if sent == sentence
]
source_sentences.selected.indices = ind
text_input.on_change('value', update_sentences)
###################################################
# ADD RESET BUTTON
of "minus line" will be returned first. Result will be used for unpacking values to line figures.
:param provider: str in ["emhi", "yrno"]
:return: [{"y": ..., "x": ..., "source": ..., "color": ...}, same]
"""
global source
defaults = {"x": "start", "source": source}
y_and_color_based_on_plus_dominance = {
True: {"1y": "minus", "1c": "#48AFE8", "2y": "plus", "2c": "firebrick"}, # True if plus dominates
False: {"1y": "plus", "1c": "firebrick", "2y": "minus", "2c": "#48AFE8"}, # False if plus does not dominate
}
vmap = y_and_color_based_on_plus_dominance[temp_plus_dominates[provider]]
return [{"y": "temp_{}_{}".format(provider, vmap["1y"]), "color": vmap["1c"], **defaults},
{"y": "temp_{}_{}".format(provider, vmap["2y"]), "color": vmap["2c"], **defaults}]
city_picker = AutocompleteInput(value="Tartu", title="\n",
completions=list(CITY_MAP))
city_picker.on_change("value", lambda attr, old, new: update())
source = ColumnDataSource(
data=dict(
start=[], # Python datetime objects
temp_emhi=[], # All EMHI temperatures - needed for the positioning of cloud-symbols.
temp_emhi_plus=[], # EMHI temperatures above 0.
temp_emhi_minus=[], # EMHI temperatures below 0.
precipitation_emhi=[],
temp_yrno=[],
temp_yrno_plus=[],
temp_yrno_minus=[],
precipitation_yrno=[],
symbol_yrno=[], # Cloud-symbols
symbol_emhi=[]
class emojiPicker:
def __init__(self):
self.setupVariables()
self.createGui()
self.loadEmojis()
def setupVariables(self):
self.keyboardHeight = 650
self.keyboardWidth = 1200
self.categoryClickIndex = 0
self.colWidth = 100
self.colHeight = self.keyboardHeight
self.rowHeight = 120
self.rowWidth = self.keyboardWidth + 2 * self.colWidth
#keyboard spacing variables
self.midRowXOffset = .2
self.keyboardYOffset = .5
self.keyboardYSpacing = 1
self.keyBoardXSpacing = 1
self.TOOLTIPS = """<div>@names</div>"""
self.TOOLTIPS = """<div class="btn-group">
<button>@names 🔊</button>
<button>Schadenfreude 🔊</button>
<button>⻄⻇ 🔊</button>
</div> """
# var audio = new Audio('emojiMessenger/static/audio.mp3');
self.filename = "audio.mp3"
self.playSound = CustomJS(args=dict(filename = self.filename), code =
"""
var audio = new Audio('emojiMessenger/static/'.concat(filename));
audio.play();
"""
)
def loadEmojis(self):
self.sessionId = emojiDber.getSessionId()
self.friendId = emojiDber.checkForUnmatchedFriendId(self.sessionId)
#main category
self.mainCategoryNames = emojiDber.getMasterCategories()[1:]
mainCategoryIcons = emojiDber.getSubCategoriesIcons("MASTER",self.mainCategoryNames)
self.updateEmojiFigure("Main","Column",mainCategoryIcons)
#pick the first main category
self.activeMainCategory = self.mainCategoryNames[0]
subCategories = emojiDber.getSubCategories(self.activeMainCategory)
subCategoryIcons = emojiDber.getSubCategoriesIcons(self.activeMainCategory,subCategories)
self.updateEmojiFigure("Sub","Column",subCategoryIcons)
#pick the first subcategory
self.activeSubCategory = subCategories[0]
#get suggested emojis
suggestedEmojis = emojiDber.getRelevantEmojis(self.activeMainCategory)
self.updateEmojiFigure("Suggested","Row",suggestedEmojis)
#get emojis to display on the keyboars
subCategoryEmojis = emojiDber.getCategoryTopEmojis(self.activeSubCategory)
#fill in the difference with main cateogry emojis
numSubEmojis = len(subCategoryEmojis)
mainCategoryEmojies = emojiDber.getCategoryTopEmojis(self.activeMainCategory,NUM_TO_GET = 26 - numSubEmojis)
keyboardEmojisDict = {**subCategoryEmojis,**mainCategoryEmojies}
self.updateKeyboardFigure(keyboardEmojisDict)
def updateEmojiFigure(self,figureName,figureType,emojisDict):
newData = self.createCategoryGlyphSource(emojisDict,figureType)
self.gui.select_one({"name":figureName}).data = newData
def updateKeyboardFigure(self,emojisDict):
newNames = list(emojisDict.keys())
newEmojis = list(emojisDict.values())
numEmojis = len(newNames)
if numEmojis < 26:
diff = 26 - numEmojis
newNames += [""] * diff
newEmojis += [""] * diff
keyboardSourceDict = (self.emojiKeyboard.select_one({"name":"emojis"})).data_source.data
keyboardSourceDict["names"] = newNames
keyboardSourceDict["text"] = newEmojis
(self.emojiKeyboard.select_one({"name":"emojis"})).data_source.data = keyboardSourceDict
def createCategoryGlyphSource(self,categoriesDict,figureType):
categoryEmojies = list(categoriesDict.values())
categoryNames = list(categoriesDict.keys())
numCategories = len(categoriesDict.keys())
indices = range(1,1+numCategories)
categoryFills = [0] * numCategories
categoryXs = [0] * numCategories
categoryYs = range(numCategories)
if figureType == "Row":
categoryXs, categoryYs = categoryYs,categoryXs
else:
categoryFills[-1] = 1
categoryGlyphSourceDict = dict(x=categoryXs, y=categoryYs, text=categoryEmojies,names = categoryNames,fills = categoryFills,indices=indices)
return categoryGlyphSourceDict
def createEmojiFigure(self,figureType,name):
#creates either a row or column to display emojies in
numCategories = 10
if figureType == "Column":
height = self.colHeight
width = self.colWidth
xRange = (-.5,.5)
yRange = (-.5,numCategories-.5)
yOffset = 20
else:
height = self.rowHeight
width = self.rowWidth
xRange = (-.5,numCategories-.5)
yRange = (-.4,.6)
yOffset = 20
categoriesFigure = figure(title = "Title",
plot_height = height, plot_width = width,
x_range=xRange,y_range=yRange,
toolbar_location = None,tools = "")
categoriesFigure.axis.visible = False
categoriesFigure.grid.visible = False
categorySourceDict = dict(x=[], y=[], text=[],names = [],fills = [],indices=[])
# categorySourceDict = self.createCategoryGlyphSource(categoriesDict,figureType)
categorySource = ColumnDataSource(categorySourceDict,name = name)
#text glyph to display emojies
categoriesGlyph = Text(x="x", y="y", text="text", angle=0,y_offset=yOffset,
text_color="black",text_alpha = 1,
text_font_size='35pt',text_align = "center")
categoriesFigure.add_glyph(categorySource, categoriesGlyph)
if figureType == "Row":
categoryIndexText = Text(x="x", y="y", text="indices", angle=0,y_offset=-10,x_offset= -50,
text_color="black",text_alpha = 1,
text_font_size='20pt',text_align = "center")
categoriesFigure.add_glyph(categorySource,categoryIndexText)
#hidden circle glyph used to allow hovertool to work to show tooltips
categoryCircleGlyph = Circle(x="x", y="y",radius=.45,fill_alpha = 0,line_alpha = "fills")
circleGlyph = categoriesFigure.add_glyph(categorySource, categoryCircleGlyph, name = "circles")
#create hover tool and add it to figure
categoryHoverer = HoverTool(renderers=[circleGlyph], tooltips=self.TOOLTIPS)
categoriesFigure.add_tools(categoryHoverer)
return categoriesFigure
def mainCategorySelectCallback(self,event):
self.categoryClickIndex += 1
x,y = (event.x, event.y)
index = int(y)
selectedCategory = self.mainCategoryNames[index]
self.activeMainCategory = selectedCategory
#update the selected category indicator
newFills = [0] * len(self.mainCategoryNames)
newFills[index] = 1
self.gui.select_one({"name":"Main"}).data["fills"] = newFills
#update sub categories
subCategories = emojiDber.getSubCategories(self.activeMainCategory)
subCategoryIcons = emojiDber.getSubCategoriesIcons(selectedCategory,subCategories)
self.updateEmojiFigure("Sub","Column",subCategoryIcons)
#pick the first new subcategory
self.activeSubCategory = subCategories[0]
subCategoryEmojis = emojiDber.getCategoryTopEmojis(self.activeSubCategory)
#fill in the difference with main cateogry emojis
numSubEmojis = len(subCategoryEmojis)
mainCategoryEmojies = emojiDber.getCategoryTopEmojis(self.activeMainCategory,NUM_TO_GET = 26 - numSubEmojis)
keyboardEmojisDict = {**subCategoryEmojis,**mainCategoryEmojies}
self.updateKeyboardFigure(keyboardEmojisDict)
def subCategorySelectCallback(self,event):
#keep track of how many categories clicked throiugh until an answer found
self.categoryClickIndex += 1
x,y = (event.x, event.y)
index = int(y)
subCategoryDict = self.gui.select_one({"name":"Sub"}).data
#update the selected category indicator
newFills = [0] * len(subCategoryDict["fills"])
newFills[index] = 1
self.gui.select_one({"name":"Sub"}).data["fills"] = newFills
#change the active categroy abd get the emojis belonging to it
self.activeSubCategory = subCategoryDict["names"][index]
subCategoryEmojis = emojiDber.getCategoryTopEmojis(self.activeSubCategory)
numSubEmojis = len(subCategoryEmojis.keys())
mainCategoryEmojies = emojiDber.getCategoryTopEmojis(self.activeMainCategory,NUM_TO_GET = 26 - numSubEmojis)
keyboardEmojisDict = {**subCategoryEmojis,**mainCategoryEmojies}
self.updateKeyboardFigure(keyboardEmojisDict)
def suggestedSelectCallback(self,event):
x,y = (event.x, event.y)
index = int(x)
suggestedEmojis = self.gui.select_one({"name":"Suggested"}).data["text"]
clickedEmoji = suggestedEmojis[index]
self.text_input.remove_on_change("value",self.textBoxcallback)
self.text_input.value += (clickedEmoji)
self.text_input.on_change("value",self.textBoxcallback)
self.analyzeNgram(self.text_input.value,"tapped")
def xyCoordsToKeyboardKey(self,x,y):
"""given an (X,Y) cooridnate, returns the key pressed
on a qwerty keyboard"""
rowIndex = int(y/(self.keyboardYSpacing))
colIndex = (x-(rowIndex*self.midRowXOffset))/self.keyBoardXSpacing
clickedLetter = self.letters[int(rowIndex)][int(colIndex)]
return clickedLetter
def emojiDoubleTapCallback(self,event):
#called when an emoji keyboard is double tapped
#updates the suggested categories, but doesn't add it to the textbox
print (1)
def emojiTapCallback(self,event):
#called when an emoji on the keyboard window is single tapped
x,y = (event.x, event.y)
index = int(x) + int(y)
selectedChar = self.xyCoordsToKeyboardKey(x,y)
emojiSourceData = (self.emojiKeyboard.select_one({"name":"emojis"})).data_source.data
letterIndex = emojiSourceData["letters"].index(selectedChar)
selectedEmoji = emojiSourceData["text"][letterIndex]
self.text_input.remove_on_change("value",self.textBoxcallback)
self.text_input.value += (selectedEmoji)
self.text_input.on_change("value",self.textBoxcallback)
self.filename = "cats.wav"
self.analyzeNgram(self.text_input.value,"tapped")
def analyzeNgram(self,ngram,methodOfEntry):
#get the current category structure
heirarchy = [self.activeMainCategory,self.activeSubCategory]
emojiDber.addEnteredString(
ENTERED_STRING = ngram,
ENTRY_METHOD = methodOfEntry,
CLICK_INDEX = self.categoryClickIndex,
CATEGORY_STRUCTURE = heirarchy,
SESSION_ID = self.sessionId)
#reset category click index
self.categoryClickIndex = 0
#get new suggestions
#split the currently entered string
splitNgram = list(ngram)
newSuggestionsDict = {}
for emoji in splitNgram:
suggestions = emojiDber.getRelevantEmojisFromEmoji(emoji)
newSuggestionsDict = {**newSuggestionsDict,**suggestions}
#get suggested emojis
self.updateEmojiFigure("Suggested","Row",newSuggestionsDict)
def createMainEmojiWindow(self):
plot = figure(title="", plot_width=self.keyboardWidth, plot_height=self.keyboardHeight,
x_range= (-.5,10-.5),y_range = (0,3*self.keyboardYSpacing),
h_symmetry=False, v_symmetry=False, min_border=0,
toolbar_location=None,tools = "")
plot.grid.visible = False
plot.axis.visible = False
emojiGlyph = Text(x="x", y="y", text="text", angle=0,
text_color="black",text_alpha = 1,text_font_size='65pt',text_align = "center")
source = self.createKeyboardCoordinates()
plot.add_glyph(source, emojiGlyph,name = "emojis")
circleGlyph = Circle(x="x", y="y",radius=.5,fill_alpha = 0,line_alpha = 0)
circGlypher = plot.add_glyph(source, circleGlyph)
emojiLetterText = Text(x="x", y="y", text="letters", angle=0,y_offset=-80,x_offset= -40,
text_color="black",text_alpha = 1,
text_font_size='20pt',text_align = "center")
plot.add_glyph(source,emojiLetterText)
hoverer = HoverTool(renderers=[circGlypher], tooltips=self.TOOLTIPS)
plot.add_tools(hoverer)
plot.on_event(Tap,self.emojiTapCallback)
# plot.on_event(DoubleTap,self.emojiDoubleTapCallback)
return plot
def englishBoxCallback(self,attr,old,new):
#called when someone types something into the english box,
#gets the suggested emojis and updates the list
#check if the new value is drastically longer than the old one (indicating autocomplete)
if (len(new) - len(old)) > 4:
print ("CLICKED")
clickedEmoji = new[-1]
self.text_input.value += (clickedEmoji)
self.englishInput.value = ""
return
suggestedEmojis = emojiDber.getRelevantEmojis(new)
emojisList = []
for name,emoji in suggestedEmojis.items():
entry = name.replace("_"," ") + " " + emoji
emojisList.append(entry)
self.englishInput.completions = emojisList
def textBoxcallback(self,attr,old,new):
if (len(old) > len(new)):
return
if not new:
return
newChar = new[-1]
if newChar == " ":
return
if newChar.isdigit():
newEmojiIndex = int(newChar)-1
newEmoji = (self.gui.select_one({"name":"Suggested"})).data["text"][newEmojiIndex]
self.text_input.remove_on_change("value",self.textBoxcallback)
self.text_input.value = new[:-1] + newEmoji
self.text_input.on_change("value",self.textBoxcallback)
if newChar.isalpha():
newCharStr = newChar.lower()
emojiSourceData = (self.gui.select_one({"name":"emojis"})).data_source.data
typedEmojiIndex = emojiSourceData["letters"].index(newCharStr)
newEmoji = emojiSourceData["text"][typedEmojiIndex]
self.text_input.remove_on_change("value",self.textBoxcallback)
self.text_input.value = new[:-1] + newEmoji
self.text_input.on_change("value",self.textBoxcallback)
self.analyzeNgram(self.text_input.value,"typed")
def createKeyboardCoordinates(self):
#rectangle window
topRowXs, topRowYs = list(range(10)),[2*self.keyboardYSpacing + self.keyboardYOffset]*10
topRowLetters = ["q","w","e","r","t","y","u","i","o","p"]
midRowXs, midRowYs = list(np.linspace(self.midRowXOffset,9-self.midRowXOffset,9)), [self.keyboardYSpacing + self.keyboardYOffset]*9
midRowLetters = ["a","s","d","f","g","h","j","k","l"]
lowRowXs, lowRowYs = list(np.linspace(2*self.midRowXOffset,7-3*self.midRowXOffset,7)),[self.keyboardYOffset]*7
lowRowLetters = ["z","x","c","v","b","n","m"]
self.letters = [lowRowLetters,midRowLetters,topRowLetters]
xCoords = topRowXs + midRowXs + lowRowXs
yCoords = topRowYs + midRowYs + lowRowYs
letters = topRowLetters + midRowLetters + lowRowLetters
self.numCoords = len(xCoords)
emojis = [""] * self.numCoords
names = [""] * self.numCoords
source = ColumnDataSource(dict(x=xCoords, y=yCoords, text=emojis,names = names,letters = letters))
return source
###CHAT BOX
def createChatBox(self):
#creates a datatable to show messages
data = dict(sender=[],message=[])
source = ColumnDataSource(data)
columns = [
TableColumn(field="sender", title="From"),
TableColumn(field="message", title="Message"),
]
chatBox = DataTable(source=source, columns=columns,
width=self.keyboardWidth, height=200)
return chatBox
def createMessageWindow(self):
messageWindow = column([],css_classes=["message-box"],width = self.keyboardWidth - 300,height = 400)
return messageWindow
def sendMessage(self):
#posts a message to the db and clears the text box, updates the chat window
currentMessage = self.text_input.value
emojiDber.postEnteredMessage(MESSAGE = currentMessage,SESSION_ID = self.sessionId)
self.updateChatBox("You",currentMessage)
def createSentDiv(self,message):
return Div(text=message,height=30,width=self.keyboardWidth-400,css_classes = ["sent-speech-bubble"])
def createReceivedDiv(self,message):
return Div(text=message,height=30,width=self.keyboardWidth-400,css_classes = ["received-speech-bubble"])
def updateChatBox(self,sender,newMessage):
if sender == "You":
newDiv = self.createSentDiv(newMessage)
else:
newDiv = self.createReceivedDiv(newMessage)
self.messageWindow.children.append(newDiv)
# chatBoxSource = self.chatBox.source.data
# chatBoxSource["sender"].append(sender)
# chatBoxSource["message"].append(newMessage)
# self.chatBox.source.data = chatBoxSource
self.text_input.value = ""
def getReceivedMessages(self):
#check if there's a friend id
self.friendId = emojiDber.checkForUnmatchedFriendId(self.sessionId)
#if its not found, return and try again later
if not self.friendId: return
unreadMessages = emojiDber.getUnreadMessages(SESSION_ID = self.friendId)
for message in unreadMessages:
messageText = message["MESSAGE"]
messageTime = message["TIMESTAMP"]
self.updateChatBox("Them",messageText)
emojiDber.incrementMessageRead(SESSION_ID=self.friendId,TIMESTAMP = messageTime)
def createGui(self):
# self.chatBox = self.createChatBox()
self.messageWindow = self.createMessageWindow()
headerDiv = Div(text="<link rel='stylesheet' type='text/css' href='templates/styles.css'>")
self.createKeyboardCoordinates()
self.englishInput = AutocompleteInput(value = "",title = "English:",completions = ["bath","bathtub"])
self.englishInput.on_change("value",self.englishBoxCallback)
self.text_input = TextInput(value="", title="Message:",width = self.keyboardWidth - 300)
self.text_input.on_change("value",self.textBoxcallback)
sendButton = Button(label="↩",button_type = "primary")
sendButton.on_click(self.sendMessage)
self.suggestedCategoryRow = self.createEmojiFigure("Row","Suggested")
self.suggestedCategoryRow.on_event(Tap,self.suggestedSelectCallback)
self.suggestedCategoryRow.title.text = "💡"
self.suggestedCategoryRow.title.text_font_size = "20pt"
mainCategoryFigure = self.createEmojiFigure("Column","Main")
mainCategoryFigure.title.text = "🐘📦"
mainCategoryFigure.title.text_font_size = "30pt"
mainCategoryFigure.on_event(Tap,self.mainCategorySelectCallback)
mainCategoryFigure.js_on_event(DoubleTap,self.playSound)
subCategoryFigure = self.createEmojiFigure("Column","Sub")
subCategoryFigure.title.text = "🥖📦"
subCategoryFigure.title.text_font_size = "30pt"
subCategoryFigure.name = "sub"
subCategoryFigure.on_event(Tap,self.subCategorySelectCallback)
self.emojiKeyboard = self.createMainEmojiWindow()
self.emojiKeyboard.title.text = "⌨"
self.emojiKeyboard.title.text_font_size = "30pt"
self.gui = column(
headerDiv,
self.messageWindow,
row(self.englishInput,self.text_input,sendButton),
self.suggestedCategoryRow,
row(self.emojiKeyboard,subCategoryFigure,mainCategoryFigure)
)
def showGui(self):
curdoc().add_root(self.gui)
curdoc().add_periodic_callback(self.getReceivedMessages,1000)
curdoc().on_session_destroyed(self.destroySession)
curdoc().title = "Emoji Messenger"
show(self.gui)
def destroySession(self,session_context):
emojiDber.deactivateSessionId(self.sessionId,self.friendId)
print ("Session closed")
def create_widget(self, dim, holomap=None, editable=False):
""""
Given a Dimension creates bokeh widgets to select along that
dimension. For numeric data a slider widget is created which
may be either discrete, if a holomap is supplied or the
Dimension.values are set, or a continuous widget for
DynamicMaps. If the slider is discrete the returned mapping
defines a mapping between values and labels making it possible
sync the two slider and label widgets. For non-numeric data
a simple dropdown selection widget is generated.
"""
label, mapping = None, None
if holomap is None:
if dim.values:
if dim.default is None:
default = dim.values[0]
elif dim.default not in dim.values:
raise ValueError(
"%s dimension default %r is not in dimension values: %s"
% (dim, dim.default, dim.values))
else:
default = dim.default
value = dim.values.index(default)
if all(isnumeric(v) for v in dim.values):
values = sorted(dim.values)
labels = [unicode(dim.pprint_value(v)) for v in values]
if editable:
label = AutocompleteInput(value=labels[value],
completions=labels,
title=dim.pprint_label)
else:
label = Div(text='<b>%s</b>' %
dim.pprint_value_string(labels[value]))
widget = Slider(value=value,
start=0,
end=len(dim.values) - 1,
title=None,
step=1)
mapping = list(enumerate(zip(values, labels)))
else:
values = [(v, dim.pprint_value(v)) for v in dim.values]
widget = Select(title=dim.pprint_label,
value=values[value][0],
options=values)
else:
start = dim.soft_range[0] if dim.soft_range[0] else dim.range[0]
end = dim.soft_range[1] if dim.soft_range[1] else dim.range[1]
dim_range = end - start
int_type = isinstance(dim.type, type) and issubclass(
dim.type, int)
if dim.step is not None:
step = dim.step
elif isinstance(dim_range, int) or int_type:
step = 1
else:
step = 10**((round(math.log10(dim_range)) - 3))
if dim.default is None:
default = start
elif (dim.default < start or dim.default > end):
raise ValueError(
"%s dimension default %r is not in the provided range: %s"
% (dim, dim.default, (start, end)))
else:
default = dim.default
if editable:
label = TextInput(value=str(default),
title=dim.pprint_label)
else:
label = Div(text='<b>%s</b>' %
dim.pprint_value_string(default))
widget = Slider(value=default,
start=start,
end=end,
step=step,
title=None)
else:
values = (dim.values if dim.values else list(
unique_array(holomap.dimension_values(dim.name))))
if dim.default is None:
default = values[0]
elif dim.default not in values:
raise ValueError(
"%s dimension default %r is not in dimension values: %s" %
(dim, dim.default, values))
else:
default = dim.default
if isinstance(values[0], np.datetime64) or isnumeric(values[0]):
values = sorted(values)
labels = [dim.pprint_value(v) for v in values]
value = values.index(default)
if editable:
label = AutocompleteInput(value=labels[value],
completions=labels,
title=dim.pprint_label)
else:
label = Div(text='<b>%s</b>' %
(dim.pprint_value_string(labels[value])))
widget = Slider(value=value,
start=0,
end=len(values) - 1,
title=None,
step=1)
else:
labels = [dim.pprint_value(v) for v in values]
widget = Select(title=dim.pprint_label,
value=default,
options=list(zip(values, labels)))
mapping = list(enumerate(zip(values, labels)))
return widget, label, mapping
"#c7c7c7",
"#1CE6FF",
"#336600",
] # these last ones were added
# load data
anndat = load_h5ad()
#pca = anndat.obsm['X_pca']
pca = anndat.obsm['X_draw_graph_fa']
tsne = anndat.obsm['X_tsne']
umap = anndat.obsm['X_umap']
# set up widgets
#stats = PreText(text='', width=500)
symbol = AutocompleteInput(completions=anndat.var_names.tolist(),
title="Enter Gene Name (e.g. POU5F1 ):",
value="AFP")
select = Select(title="Legend:",
value="stage_group",
options=[
"clusters", "stage", "stage_group", "donor", "Donor",
"group", "res.0.6"
]) #options=anndat.obs_keys())
# message box
message = Div(text="""Input Gene Name:\n Legend Option: """,
width=200,
height=100)
## setup data
dd = select.value
umis = get_umi(anndat, symbol.value)
groups = widgetbox(Paragraph(text="The bokeh groups"), checkbox_group, radio_group, checkbox_button_group, radio_button_group, sizing_mode=sizing_mode)
# Markups
div = Div(text="Some custom <strong>bold</strong> text")
paragraph = Paragraph(text="this is a paragraph")
pretext_1 = PreText(text="This is pre. I could put a bunch of code in here perhaps\nOr maybe something else")
pretext_2 = PreText(text="This is pre")
pretext_3 = PreText(text="This is pre it's a bit longer and i'm going to constrict it.", width=150)
markups = widgetbox(Paragraph(text="The bokeh markups"), div, paragraph, pretext_1, pretext_2, pretext_3, sizing_mode=sizing_mode)
# Inputs
#daterangeslider = DateRangeSlider() # Known broken
slider = Slider(title="Slider", start=0, end=10, width=100)
multiselect = MultiSelect(options=['1', '2', '3'])
select = Select(options=['1', '2', '3'])
textinput = TextInput()
autocomplete = AutocompleteInput(completions=['one', 'two', 'three'])
#datepicker = DatePicker()
inputs = widgetbox(Paragraph(text="The bokeh inputs"), slider, multiselect, select, textinput, autocomplete, sizing_mode=sizing_mode)
plot = figure(sizing_mode=sizing_mode)
plot.circle(x=[1, 2], y=[2, 3])
l = layout([
[buttons, groups],
[markups, inputs],
[plot],
], sizing_mode=sizing_mode)
show(l)
def update_simulation_sample_size(attr, old, new):
update()
# configure Bokeh Inputs, data sources, and plots
autocomplete_station_names = list(STATIONS_DF['Station Name'])
peak_source = ColumnDataSource(data=dict())
peak_flagged_source = ColumnDataSource(data=dict())
distribution_source = ColumnDataSource(data=dict())
qq_source = ColumnDataSource(data=dict())
station_name_input = AutocompleteInput(
completions=autocomplete_station_names, title='Enter Station Name (ALL CAPS)',
value=IDS_TO_NAMES['08MH016'], min_characters=3)
simulation_number_input = Spinner(
high=1000, low=1, step=1, value=50, title="Number of Simulations",
)
sample_size_input = Spinner(
high=200, low=2, step=1, value=10, title="Sample Size for Simulations"
)
ffa_info = Div(
text="Mean of {} simulations of a sample size {}.".format('x', 'y'))
error_info = Div(text="", style={'color': 'red'})
options=[x[0] for x in collections.Counter(ptree.leaf_cds.data['superkingdom']).most_common()],\
width=200,height=70)
kms.on_change('value',lambda attr,old,new:kmsfunc())
sfms=MultiSelect(title='Subfams',\
options=[x[0] for x in collections.Counter(ptree.leaf_cds.data['subfamstr']).most_common()],\
width=150,height=70)
sfms.on_change('value',lambda attr,old,new:sfmsfunc())
tcb=Button(label='CalcTC',width=80,height=40)
tcb.on_click(tcbfunc)
#splist=list(set(ptree.leaf_cds.data['species']))
#splist.sorted(key=ptree.leaf_cds.data['species'])
#acw=AutocompleteInput(title='Organism name',completions=list(set(ptree.leaf_cds.data['species'])),width=200,height=50)
acw=AutocompleteInput(title='Organism name',\
completions=[x[0] for x in collections.Counter(ptree.leaf_cds.data['species']).most_common()],\
width=200,height=50)
acw.on_change('value',lambda attr,old,new:acfunc())
accacw=AutocompleteInput(title='Accession',\
completions=ptree.leaf_cds.data['gbacc'][:],width=200,height=50)
accacw.on_change('value',lambda attr,old,new:accacfunc())
if len(sys.argv)>3:
preselfpath=os.path.join(os.environ['SCIENCEDIR'],'GHSeqs',ghfam.upper(),sys.argv[3])
with open(preselfpath,'r') as f:
preselections=[x.strip() for x in f.readlines()]
print(preselections)
else:
preselections=[]
def bokehGUI(ScoreBoard,
MakerDictionary,
offlineboard='None',
curMeme="sustainability",
curInfluencer='zbattiz',
ApiRequest=False):
MD = MakerDictionary
SB = ScoreBoard
if offlineboard: SB.import_board(offlineboard)
BI = BokehControler(SB, MD)
names = [k for k, v in SB.get_names().items()]
category_codes = MD.categories.values()
print(category_codes)
# make this more generic:
if not curInfluencer: curInfluencer = 'zbattiz'
if not curMeme: curMeme = 'sustainability'
BI.populateInfluencers(names, category_codes)
BI.populateBoards(category_codes)
BI.setActiveBoard(curMeme, BI.Boards.data.keys())
BI.setActiveInfluencer(curInfluencer, BI.Influencers.data.keys())
boards = BI.Boards
board = BI.ActiveBoard
influencers = BI.Influencers
influencer = BI.ActiveInfluencer
boardatr = ColumnDataSource(data=dict(legend=[curMeme]))
influenceratr = ColumnDataSource(data=dict(legend=[curInfluencer]))
#for k in BI.Boards.data.keys(): print(k, BI.Boards.data[k])
# Drawing:::::::::::::
## Commom Tools::
TOOLS = "tap,pan,wheel_zoom,reset,save"
## The Influencer Canvas::
title = "Influencer"
fig_influencer = figure(plot_width=700,
plot_height=500,
title=title,
tools=TOOLS,
toolbar_location="above",
toolbar_sticky=True,
active_drag="pan",
active_tap='tap',
active_scroll='wheel_zoom',
responsive=True)
fig_influencer.axis.visible = False
fig_influencer.border_fill_color = "whitesmoke"
fig_influencer.border_fill_alpha = 0.3
fig_influencer.min_border_top = 30
fig_influencer.outline_line_width = 4
fig_influencer.outline_line_alpha = 0.2
fig_influencer.outline_line_color = "navy"
fig_influencer.xgrid.visible = False
fig_influencer.ygrid.visible = False
### Legend:::
fig_influencer.circle(0,
0,
alpha=0.8,
color='olive',
legend='legend',
source=influenceratr)
fig_influencer.legend.location = "top_left"
fig_influencer.legend.label_text_font_size = "8pt"
fig_influencer.legend.label_text_color = "red"
### Data:::
fig_influencer.multi_line('xsegments',
'ysegments',
color="colors",
alpha=0.5,
line_width=2,
line_dash="dashed",
source=influencer)
fig_influencer.circle('x',
'y',
color='colors',
size='sizes',
alpha=1,
source=influencer)
labels = LabelSet(x='x',
y='y',
text='memes',
text_font_size='9pt',
level='glyph',
x_offset="offsets",
y_offset=0,
source=influencer,
render_mode='canvas')
fig_influencer.add_layout(labels)
### Hover Tool:::
infhover = HoverTool(
tooltips=[("Score",
"@scores{0,0.000}"), ("Type",
"per_tweet"), ("Ntweets", "@tweets")])
fig_influencer.add_tools(infhover)
## The Board Canvas:::
#for k in BI.ActiveBoard.data.keys(): print(k, BI.ActiveBoard.data[k])
title_board = "Community Spirometer"
fig_board = figure(plot_width=900,
plot_height=550,
title=title_board,
tools=TOOLS,
toolbar_location="above",
toolbar_sticky=True,
active_drag="pan",
active_tap='tap',
active_scroll='wheel_zoom',
responsive=True)
fig_board.axis.visible = False
fig_board.border_fill_color = "whitesmoke"
fig_board.border_fill_alpha = 0.2
fig_board.min_border_top = 30
fig_board.outline_line_width = 6
fig_board.outline_line_alpha = 0.2
fig_board.outline_line_color = "navy"
### Legend:::
fig_board.circle(0,
0,
alpha=0.8,
color='turquoise',
legend='legend',
source=boardatr)
fig_board.legend.location = "top_left"
fig_board.legend.label_text_font_size = "9pt"
fig_board.legend.label_text_color = "red"
### Data:::
fig_board.line('x',
'y',
alpha=0.4,
line_width=1,
line_dash="dashed",
source=board)
fig_board.circle('x',
'y',
color='black',
size='levels',
alpha=1,
source=board)
fig_board.circle('x',
'y',
color='colors',
size='sizes',
alpha=0.8,
source=board)
labels = LabelSet(x='x',
y='y',
text='names',
text_font_size='7pt',
level='glyph',
x_offset='offsets',
y_offset=0,
source=board,
render_mode='canvas')
fig_board.add_layout(labels)
### Hover Tool:::
boardhover = HoverTool(tooltips=[("Name", "@names"), (
"Phase",
"@clusters"), ("Score",
"@scores{0,0.000}"), (
"Scoring type",
"per_tweet"), ("Number of tweets probed",
"@tweets")])
fig_board.add_tools(boardhover)
# JavaScript Callbacks:::
board.callback = CustomJS(args=dict(source=influencers,
display=influencer,
atr=influenceratr),
code="""
var inds = cb_obj.selected['1d'].indices;
var d1 = cb_obj.data;
var d2 = source.data;
var d3 = display.data;
var d4 = atr.data;
var ind = inds[0];
console.log(ind);
if (ind != null){
d3['x'] = [];
d3['y'] = [];
d3['sizes'] = [];
d3['scores'] = [];
d3['names'] = [];
d3['memes'] = [];
d3['colors'] = [];
d3['offsets'] = [];
d3['xsegments'] = [];
d3['ysegments'] = [];
d3['tweets'] = [];
d3_tags = [];
var name = d1['names'][ind];
console.log(name);
d4['legend'] = [];
d4['legend'].push(name);
var start = d2['names'].indexOf(name);
var end = d2['names'].lastIndexOf(name);
console.log(start);
console.log(end);
for (var i = start; i <= end; i++) {
d3['x'].push(d2['x'][i]);
d3['y'].push(d2['y'][i]);
d3['sizes'].push(d2['sizes'][i]);
d3['scores'].push(d2['scores'][i]);
d3['names'].push(d2['names'][i]);
d3['memes'].push(d2['memes'][i]);
d3['offsets'].push(d2['offsets'][i]);
d3['colors'].push(d2['colors'][i]);
d3['tweets'].push(d2['tweets'][i]);
d3['xsegments'].push(d2['xsegments'][i]);
d3['ysegments'].push(d2['ysegments'][i]);
}
}
display.change.emit();
atr.change.emit();
""")
influencer.callback = CustomJS(args=dict(source=boards,
display=board,
atr=boardatr),
code="""
var inds = cb_obj.selected['1d'].indices;
var d1 = cb_obj.data;
var d2 = source.data;
var d3 = display.data;
var d4 = atr.data;
var ind = inds[0];
console.log(ind)
if (ind != null){
d3['x'] = [];
d3['y'] = [];
d3['sizes'] = [];
d3['scores'] = [];
d3['levels'] = [];
d3['clusters'] = [];
d3['names'] = [];
d3['memes'] = [];
d3['offsets'] = [];
d3['colors'] = [];
d3['tweets'] = [];
var meme = d1['memes'][ind];
d4['legend'] = [];
d4['legend'].push(meme)
console.log(meme)
var name = d1['names'][ind];
var color = d1['colors'][ind]
var start = d2['memes'].indexOf(meme);
var end = d2['memes'].lastIndexOf(meme);
console.log(start);
console.log(end);
for (var i = start; i <= end; i++) {
d3['x'].push(d2['x'][i]);
d3['y'].push(d2['y'][i]);
d3['sizes'].push(d2['sizes'][i]);
d3['scores'].push(d2['scores'][i]);
d3['levels'].push(d2['levels'][i]);
d3['clusters'].push(d2['clusters'][i]);
d3['names'].push(d2['names'][i]);
d3['memes'].push(d2['memes'][i]);
d3['offsets'].push(d2['offsets'][i]);
d3['tweets'].push(d2['tweets'][i]);
if (d2['names'][i] == name){
d3['colors'].push(color);
}
else {
d3['colors'].push(d2['colors'][i]);
}
}
}
display.change.emit();
atr.change.emit();
""")
# Adding additional Widgets and their events:::::
## Info Box::
div_title = Div(text="""
<h2> Sustainable Finance Spirometer</h2>
<p><b>This Sprirometer infographics is one of the ways to observe opionion leaders and influencers,
those who promote or debate on issues relevant to sustainable finance. </b>
<p>Influential actors are placed rather outer branches of the spiral. See the lower interactive panel.
An infleuncer's spiral profile, as of his/her contribution to the related debates,
can be seen via the upper interactive panel.</p>
<p>The data is collected from the tweets that are in the public domain.
The latest tweets in English of an infleuncer is used for the analysis and visualizations.
The nodes on the spirometer (the lower panel) are resized according to the number of tweets
by the corresponding influencer.</p>
<p>Influencers are clustered according to their sphere of influence.
There are 4 or more distinct clusters/phases on each spiral.
Number of clusters and cluster membership is algorithmically generated from the data.
The sequence of nodes with/without an inner circle denotes membership to the same cluster.
<br/> <br/>
</p>
""",
width=850,
height=220)
title_box = widgetbox(div_title, sizing_mode='scale_both', responsive=True)
## Tips Box::
div_tips = Div(text="""
<p>Hover over the nodes in order to see the details. <b>Ntweets</b>
denotes the number of tweeters collected for the profiling, <b>per_tweet</b>
denotes that scores are computed per tweet.</p>
<p>A new influencer can be added. Address bar can be used to query an influencer
whose profile is not analyzed yet. Note that a twitter user name is the part after @ sign.
For instance, the Twitter user <i>@bulentozel</i> can be added by appending <b>bulentozel</b> to the URL:
<i>BASE_URL/gui/bulentozel</i>
</p>
<p>To query the users whose profiling has already been included, the search bar below can be used. </p>
""",
width=200,
height=350)
tips_box = widgetbox(div_tips, sizing_mode='scale_both', responsive=True)
## Query Box::
callback_search = CustomJS(args=dict(boardWin=board,
infList=influencers,
infWin=influencer,
atr=influenceratr),
code="""
var bWin = boardWin.data;
var iWin = infWin.data;
var iL = infList.data;
var query = cb_obj.value;
var d4 = atr.data;
console.log(query);
var ind = iL['names'].indexOf(query);
if (ind >= 0){
var start = ind;
var end = iL['names'].lastIndexOf(query);
iWin['x'] = [];
iWin['y'] = [];
iWin['sizes'] = [];
iWin['scores'] = [];
iWin['names'] = [];
iWin['memes'] = [];
iWin['colors'] = [];
iWin['offsets'] = [];
iWin['xsegments'] = [];
iWin['ysegments'] = [];
iWin['tweets'] = [];
for (var i = start; i <= end; i++) {
iWin['x'].push(iL['x'][i]);
iWin['y'].push(iL['y'][i]);
iWin['sizes'].push(iL['sizes'][i]);
iWin['scores'].push(iL['scores'][i]);
iWin['names'].push(iL['names'][i]);
iWin['memes'].push(iL['memes'][i]);
iWin['offsets'].push(iL['offsets'][i]);
iWin['colors'].push(iL['colors'][i]);
iWin['tweets'].push(iL['tweets'][i]);
iWin['xsegments'].push(iL['xsegments'][i]);
iWin['ysegments'].push(iL['ysegments'][i]);
}
ind = bWin['names'].indexOf(query);
if (ind > 0){
var blength = bWin['colors'].length;
bWin['colors'] = []
for (i = 0; i < blength; i++) {
bWin['colors'].push('turquoise');
}
bWin['colors'][ind] = 'olive'
}
d4['legend'] = [];
d4['legend'].push(query);
}
boardWin.change.emit();
infWin.change.emit();
atr.change.emit();
""")
text_input = AutocompleteInput(completions=names,
title="Search an influencer:")
text_input.js_on_change('value', callback_search)
query_box = widgetbox(text_input,
sizing_mode='stretch_both',
responsive=True)
# Tabular Data
## Info Box::
div_scorebord_info = Div(text="""
<h3>Spirometer Details</h3>
<p>Tap to column names in order to sort accordingly.
</p>
""",
width=750,
height=50)
title_table = widgetbox(div_scorebord_info,
sizing_mode='scale_both',
responsive=True)
Nformatter = NumberFormatter()
Nformatter.format = "0,0.000"
columns = [
TableColumn(field="names", title="Name"),
TableColumn(field="memes", title="Category"),
TableColumn(field="scores", title="Score", formatter=Nformatter),
TableColumn(field="tweets", title="Number of Tweets")
]
data_table = DataTable(source=boards,
columns=columns,
width=820,
height=500)
table_box = widgetbox(data_table,
sizing_mode='stretch_both',
responsive=True)
# Figures only layout::::
if ApiRequest:
layoutAPI = column(fig_influencer, fig_board)
return (layoutAPI)
# Overall Layout::::
layout = column(title_box, row(fig_influencer,
column(tips_box, query_box)), fig_board,
title_table, table_box)
return (layout)
def cHow():
if byButton:
return rs_update()
else:
return byRow(source.data['ID'].iloc[source.selected.indices[0]])
menu = [('Publication Paper', 'pub'), ('Dataset', 'data'), ('All', '')]
nmenu = RadioButtonGroup(labels=['Publication', 'Dataset', 'Keyword'], active=0)
how = ['Jaccard', 'Cosine', 'Hopcroft', 'Adamic-Adar']
nhow = RadioButtonGroup(labels=['Jaccard', 'Cosine', 'Hopcroft', 'Adamic-Adar'], active=0)
nhow.on_change('active', lambda attr, old, new: cHow())
search = TextInput(title="Search Archive")
rs_search = AutocompleteInput(title="Recommend by Keyword", completions=all_keywords)
button = Button(label="Search", button_type="warning")
button.on_event(ButtonClick, update)
rs_button = Button(label="Recommend", button_type="success")
rs_button.on_event(ButtonClick, rs_update)
columns = [
TableColumn(field="ID", title="ID", width=20),
TableColumn(field="title", title="Title", width=300, formatter=HTMLTemplateFormatter(template=template)),
TableColumn(field="description", title="Description", width=200, formatter=HTMLTemplateFormatter(template=template))
]
data_table = DataTable(source=source, columns=columns, width=800)
rs_columns = [
TableColumn(field="data_set_id", title="Data ID", width=20),
TableColumn(field="rs_score", title="RS Score", width=20),
def recommender_tab_simple(recommender):
# create a list of divs
def make_div_list(textlist, max_lines, fmt_str="""%s""", **attribs):
"""create a list of divs containing text to display"""
divs = []
for i in range(max_lines):
if len(textlist) > i:
divs.append(Div(text=fmt_str % (textlist[i]), **attribs))
else:
divs.append(Div(text=fmt_str % (' '), **attribs))
return divs
def make_rec_list(titles, max_lines):
"""create a recommendation list of games,
with a thumbnail, game title, info and Amazon buy links"""
global games_by_title
fmt_str1 = """
<div class="rec-post-container">
<div class="rec-post-thumb"><img src="%s" /></div>
<div class="rec-post-content">
<h3 class="rec-post-title">%s<br>
<a href="%s" target="_blank">Info</a><span> </span>
<a href="%s" target="_blank">Buy on Amazon</a> </h3>
</div>
</div>"""
fmt_str2 = """"""
divs = []
for i in range(max_lines):
# there is a title available for this list slot
if len(titles) > i:
divs.append(
Div(text=fmt_str1 %
(games_by_title['pic_url'].loc[titles[i]], titles[i],
'https://boardgamegeek.com/boardgame/' +
str(games_by_title['id'].loc[titles[i]]),
'https://www.amazon.com/s?k=' +
titles[i].replace(' ', '+') + '&i=toys-and-games')))
# there no title available for this list slot
else:
divs.append(Div(text=fmt_str2))
return divs
# update the 'liked games' list UI elements
def update_liked_list(titlelist):
global max_liked
ctl_liked_games.children = make_div_list(titlelist,
max_liked,
fmt_str=liked_list_fmt,
render_as_text=False)
# update the 'recommended games' list UI elements
def update_recommended_list(titlelist):
global n_recommendations
ctl_recommended_games.children = make_rec_list(titlelist,
n_recommendations)
def show_searching_message():
ctl_recommended_games.children = [
Div(text='<h1>Searching for recommendations...</h1>')
]
# called when a control widget is changed
def update_preflist(attr, old, new):
global liked_games
liked_games.append(ctl_game_entry.value)
liked_games = list(filter(None, set(liked_games)))
# get control values
update_liked_list(liked_games)
ctl_game_entry.value = ''
# clear out the list of preferred games
def reset_preferred_games():
global liked_games
liked_games = []
update_liked_list(liked_games)
# user wants some recommendations (clicked the rec button)
def recommend_games():
global liked_games, recommended_games
global games_all, n_recommendations, title_list
global title_list_lower
# display a "Searching for recommendations..." message
# Note: Bokeh doesn't do redraw while inside handlers
show_searching_message()
# get some default filter parameters:
weight = []
minrating = 6.5
categories = ['Any category']
mechanics = ['Any mechanism']
for title in liked_games:
idx = (np.array(title_list_lower) == title.lower()).nonzero()[0][0]
info = games_all.iloc[idx, :]
weight.append(info['weight'])
categories += info['categories'].split(',')
mechanics += info['mechanics'].split(',')
# select a range of weights around the liked game weights
weightrange = [
max(1,
np.min(weight) - 0.25),
min(5,
np.max(weight) + 0.25)
]
# get game IDs for titles
liked_ids = recommender.get_item_title_id(liked_games)
# select games to search from based on filters:
recommended_games = recommender.recommend_items_by_pref_list(
liked_ids,
num2rec=n_recommendations,
weightrange=weightrange,
minrating=minrating,
categories_include=categories,
categories_exclude=['Expansion for Base-game'],
mechanics_include=mechanics,
mechanics_exclude=[])
update_recommended_list(recommended_games)
# NOTE: I'm using globals because I'm running into variable scope
# problems with the bokeh handlers. Easiest to declare globals
global liked_games, recommended_games, games_all
global n_recommendations, max_liked, title_list, title_list_lower
global games_by_title
# layout params
n_recommendations = 10
max_liked = 8
# Format to use for liked list.
# This needs to be changed to work like rec list
liked_list_fmt = """<div style="font-size : 14pt; line-height:14pt;">%s</div>"""
# variables used by the tab
liked_games = []
recommended_games = []
weight_range = [1, 5]
games_all = recommender.item_data # use all games for search
games_by_title = recommender.item_data.set_index('name')
# list of all game titles
title_list = games_all['name']
title_list_lower = [s.lower() for s in title_list]
# preferred game entry text control
ctl_game_entry = AutocompleteInput(completions=list(title_list) +
list(title_list_lower),
min_characters=1,
title='Enter some game names you like:')
ctl_game_entry.on_change('value', update_preflist)
# reset liked game list button
ctl_reset_prefs = Button(label='Reset game list',
width_policy='min',
align='end')
ctl_reset_prefs.on_click(reset_preferred_games)
# liked list title
ctl_liked_list_title = Div(
text=
"""<div style="font-size : 18pt; line-height:16pt;">Games you like:</div>"""
)
# liked game entries
ctl_liked_games = WidgetBox(
children=make_div_list(liked_games, max_liked, fmt_str=liked_list_fmt))
# recommended list title
ctl_recommended_list_title = Div(
text=
"""<div style="font-size : 18pt; line-height:16pt;">Games we recommend:</div>"""
)
# recommended games list widget
ctl_recommended_games = WidgetBox(
children=make_rec_list(recommended_games, n_recommendations))
# Recommend games button
ctl_recommend = Button(label='Recommend some games!', width_policy='min')
ctl_recommend.on_click(recommend_games)
# controls to select preferred games
pref_controls = WidgetBox(ctl_liked_list_title, ctl_liked_games,
Spacer(min_height=20),
ctl_game_entry, ctl_reset_prefs,
Spacer(min_height=40), ctl_recommend)
# recommendation results
results_controls = WidgetBox(ctl_recommended_list_title,
ctl_recommended_games)
# Create a row layout
layout = row(pref_controls, results_controls)
# Make a tab with the layout
tab = Panel(child=layout, title='Simple Game Recommender')
return tab
def update_simulated_msmt_error(val):
update()
# configure Bokeh Inputs, data sources, and plots
autocomplete_station_names = list(STATIONS_DF['Station Name'])
peak_source = ColumnDataSource(data=dict())
peak_flagged_source = ColumnDataSource(data=dict())
distribution_source = ColumnDataSource(data=dict())
qq_source = ColumnDataSource(data=dict())
datatable_source = ColumnDataSource(data=dict())
hist_source = ColumnDataSource(data=dict())
station_name_input = AutocompleteInput(
completions=autocomplete_station_names,
title='Enter Water Survey of Canada STATION NAME (USE ALL CAPS)',
value=IDS_TO_NAMES['08MH016'],
min_characters=3)
simulation_number_input = Spinner(
high=5000,
low=100,
step=1,
value=500,
title="Number of Simulations",
)
sample_size_input = Spinner(high=200,
low=2,
step=1,
value=10,
menu = [("Item 1", "item_1_value"), ("Item 2", "item_2_value"), None, ("Item 3", "item_3_value")]
dropdown = Dropdown(label="Dropdown button", button_type="warning", menu=menu)
dropdown_split = Dropdown(label="Split button", button_type="danger", menu=menu, split=True)
checkbox_group = CheckboxGroup(labels=["Option 1", "Option 2", "Option 3"], active=[0, 1])
radio_group = RadioGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
checkbox_button_group = CheckboxButtonGroup(labels=["Option 1", "Option 2", "Option 3"], active=[0, 1])
radio_button_group = RadioButtonGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
text_input = TextInput(placeholder="Enter value ...")
completions = ["aaa", "aab", "aac", "baa", "caa"]
autocomplete_input = AutocompleteInput(placeholder="Enter value (auto-complete) ...", completions=completions)
select = Select(options=["Option 1", "Option 2", "Option 3"])
multi_select = MultiSelect(options=["Option %d" % (i+1) for i in range(16)], size=6)
slider = Slider(value=10, start=0, end=100, step=0.5)
range_slider = RangeSlider(value=[10, 90], start=0, end=100, step=0.5)
date_slider = DateSlider(value=date(2016, 1, 1), start=date(2015, 1, 1), end=date(2017, 12, 31))
date_range_slider = DateRangeSlider(value=(date(2016, 1, 1), date(2016, 12, 31)), start=date(2015, 1, 1), end=date(2017, 12, 31))
spinner = Spinner(value=100)
index_select = Select(value='000001', title='指数代码', options=sorted(index_codes), height=50)
index_type_select = Select(value='牛熊股比', title='数据类型', options=sorted(index_type_list), height=50)
# DatePciekr
dt_pckr_start = DatePicker(title='开始日期', value = date.today() - timedelta(days = 200), min_date = date(2004,1,1), max_date = date.today())
dt_pckr_end = DatePicker(title='结束日期', value = date.today(), min_date = date(2004,1,1), max_date = date.today())
index_select_row = row(index_select, index_type_select, dt_pckr_start, dt_pckr_end)
index_layout = column(index_select_row, create_index_figure_column(index_select.value, index_type_select.value, dt_pckr_start.value, dt_pckr_end.value))
index_select.on_change('value', update_index)
index_type_select.on_change('value', update_index)
dt_pckr_start.on_change('value', update_index)
dt_pckr_end.on_change('value', update_index)
# Add Stock Analysis
stock_auto_input = AutocompleteInput(value = '601318', completions = initializer.update_code_list(), title = '股票代码')
# DatePciekr
stock_pckr_start = DatePicker(title='开始日期', value = date.today() - timedelta(days = 100), min_date = date(2000,1,1), max_date = date.today())
stock_pckr_end = DatePicker(title='股票日期', value = date.today(), min_date = date(2000,1,1), max_date = date.today())
stock_select_row = row(stock_auto_input, stock_pckr_start, stock_pckr_end)
stock_layout = column(stock_select_row, create_stock_figure_column(stock_auto_input.value, stock_pckr_start.value, stock_pckr_end.value))
stock_auto_input.on_change('value', update_stock)
stock_pckr_start.on_change('value', update_stock)
stock_pckr_end.on_change('value', update_stock)
# Market Data
# DatePciekr
market_title = Div(text="整体市场概况", width=120, height=40, margin=[25, 0, 0, 0], style={'font-size': '150%', 'color': 'blue'})
market_pckr_start = DatePicker(title='开始日期', value = date.today() - timedelta(days = 100), min_date = date(2000,1,1), max_date = date.today())
def recommender_tab_advanced(recommender):
def make_div_list(textlist, max_lines, fmt_str="""%s""", **attribs):
"""create a list of divs containing text to display"""
divs = []
for i in range(max_lines):
if len(textlist) > i:
divs.append(Div(text=fmt_str % (textlist[i]), **attribs))
else:
divs.append(Div(text=fmt_str % (' '), **attribs))
return divs
def make_rec_list(titles, max_lines):
"""create a recommendation list of games,
with a thumbnail, game title, info and Amazon buy links"""
global games_by_title
fmt_str1 = """
<div class="rec-post-container">
<div class="rec-post-thumb"><img src="%s" /></div>
<div class="rec-post-content">
<h3 class="rec-post-title">%s<br>
<a href="%s" target="_blank">Info</a><span> </span>
<a href="%s" target="_blank">Buy on Amazon</a> </h3>
</div>
</div>"""
fmt_str2 = """"""
divs = []
for i in range(max_lines):
# there is a title available for this list slot
if len(titles) > i:
divs.append(
Div(text=fmt_str1 %
(games_by_title['pic_url'].loc[titles[i]], titles[i],
'https://boardgamegeek.com/boardgame/' +
str(games_by_title['id'].loc[titles[i]]),
'https://www.amazon.com/s?k=' +
titles[i].replace(' ', '+') + '&i=toys-and-games')))
# no title, so fill with blank
else:
divs.append(Div(text=fmt_str2))
return divs
# update the 'liked games' list UI elements
def update_liked_list(titlelist):
global max_liked
ctl_liked_games.children = make_div_list(titlelist,
max_liked,
fmt_str=liked_list_fmt,
render_as_text=False)
# update the 'recommended games' list UI elements
def update_recommended_list(titlelist):
global n_recommendations
ctl_recommended_games.children = make_rec_list(titlelist,
n_recommendations)
# called when a control widget is changed
def update_filters(attr, old, new):
global category_includes, mechanics_includes
global category_excludes, mechanics_excludes
category_includes = [
ctl_category_selection1.labels[i]
for i in ctl_category_selection1.active
]
category_includes += [
ctl_category_selection2.labels[i]
for i in ctl_category_selection2.active
]
mechanics_includes = [
ctl_mechanics_selection1.labels[i]
for i in ctl_mechanics_selection1.active
]
mechanics_includes += [
ctl_mechanics_selection2.labels[i]
for i in ctl_mechanics_selection2.active
]
# NOTE: this will need to be changed if I ever implement exclude selections!
if ctl_include_expansions.active:
category_excludes = []
else:
category_excludes = ['Expansion for Base-game']
# called when a control widget is changed
def update_preflist(attr, old, new):
global liked_games
liked_games.append(ctl_game_entry.value)
liked_games = list(filter(None, set(liked_games)))
# get control values
update_liked_list(liked_games)
ctl_game_entry.value = ''
# reset preferred games list
def reset_preferred_games():
global liked_games
liked_games = []
update_liked_list(liked_games)
# recommend some games
def recommend_games():
global liked_games, recommended_games
global games_all, n_recommendations, title_list
global category_includes, mechanics_includes
# get game IDs for titles
liked_ids = recommender.get_item_title_id(liked_games)
# select games to search from based on filters:
recommended_games = recommender.recommend_items_by_pref_list(
liked_ids,
num2rec=n_recommendations,
weightrange=ctl_game_weight.value,
minrating=ctl_game_min_rating.value,
categories_include=category_includes,
categories_exclude=category_excludes,
mechanics_include=mechanics_includes,
mechanics_exclude=mechanics_excludes)
# show the recommended games
update_recommended_list(recommended_games)
# NOTE: I'm using globals because I'm running into variable scope
# problems with the bokeh handlers. Easiest to declare globals
global liked_games, recommended_games, games_all
global n_recommendations, max_liked, title_list, title_list_lower
global category_includes, mechanics_includes
global category_excludes, mechanics_excludes
global games_by_title
# layout params
n_recommendations = 10
max_liked = 8
num_check_options = 20
# Format to use for liked list.
# This needs to be changed to work like rec list
liked_list_fmt = """<div style="font-size : 14pt; line-height:14pt;">%s</div>"""
# variables used by the tab
games_all = recommender.item_data # use all games for search
liked_games = []
recommended_games = []
weight_range = [1, 5]
category_includes = []
mechanics_includes = []
category_excludes = []
mechanics_excludes = []
# list of all game titles
title_list = games_all['name']
title_list_lower = [s.lower() for s in title_list]
games_by_title = recommender.item_data.set_index('name')
# preferred game entry text control
ctl_game_entry = AutocompleteInput(completions=list(title_list) +
list(title_list_lower),
min_characters=1,
title='Enter some game names you like:')
ctl_game_entry.on_change('value', update_preflist)
# reset liked game list button
ctl_reset_prefs = Button(label='Reset game list',
width_policy='min',
align='end')
ctl_reset_prefs.on_click(reset_preferred_games)
# liked list title
ctl_liked_list_title = Div(
text=
"""<div style="font-size : 18pt; line-height:16pt;">Games you like:</div>"""
)
# liked game entries
ctl_liked_games = WidgetBox(
children=make_div_list(liked_games, max_liked, fmt_str=liked_list_fmt))
# recommended list title
ctl_recommended_list_title = Div(
text=
"""<div style="font-size : 18pt; line-height:16pt;">Games we recommend:</div>"""
)
# recommended games list widget
ctl_recommended_games = WidgetBox(
children=make_rec_list(recommended_games, n_recommendations))
# Recommend games button
ctl_recommend = Button(label='Recommend some games!',
width_policy='min',
align='center')
ctl_recommend.on_click(recommend_games)
# game weight slider
ctl_game_weight = RangeSlider(
start=1,
end=5,
value=(1, 5),
step=.1,
title='Game weight range',
width_policy='min',
)
ctl_game_weight.on_change('value', update_filters)
# min game rating slider
ctl_game_min_rating = Slider(start=1,
end=10,
value=7,
step=.1,
title='Minimum average rating',
width_policy='min')
ctl_game_min_rating.on_change('value', update_filters)
# collect all category and mechanics labels from recommender data
categories, mechanics = recommender.get_categories_and_mechanics()
# game category selection
category_list = ['Any category'] + list(categories['tag'].values)
ctl_category_selection1 = CheckboxGroup(
labels=category_list[:int(num_check_options / 2)],
width_policy='min',
active=[0])
ctl_category_selection1.on_change('active', update_filters)
ctl_category_selection2 = CheckboxGroup(
labels=category_list[int(num_check_options / 2):num_check_options],
width_policy='min')
ctl_category_selection2.on_change('active', update_filters)
# game mechanism checkbox group
mechanics_list = ['Any mechanism'] + list(mechanics['tag'].values)
ctl_mechanics_selection1 = CheckboxGroup(
labels=mechanics_list[:int(num_check_options / 2)],
width_policy='min',
active=[0])
ctl_mechanics_selection1.on_change('active', update_filters)
ctl_mechanics_selection2 = CheckboxGroup(
labels=mechanics_list[int(num_check_options / 2):num_check_options],
width_policy='min')
ctl_mechanics_selection2.on_change('active', update_filters)
# select whether to include expansions
ctl_include_expansions = CheckboxGroup(labels=['Include game expansions'],
width_policy='min')
ctl_include_expansions.on_change('active', update_filters)
# controls to select preferred games
pref_controls = WidgetBox(
ctl_liked_list_title,
ctl_liked_games,
Spacer(min_height=20),
ctl_game_entry,
ctl_reset_prefs,
Spacer(min_height=5),
)
ctl_liked_list_title = Div(
text=
"""<div style="font-size : 18pt; line-height:16pt;">Game Categories:</div>"""
)
filter_controls = WidgetBox(
row(ctl_game_weight, Spacer(min_width=50), ctl_game_min_rating),
row(ctl_include_expansions),
column(
row(
Div(text=
"""<div style="font-size : 18pt; line-height:16pt;">Game Categories:</div>"""
), Spacer(min_width=50), ctl_recommend),
row(ctl_category_selection1, ctl_category_selection2),
Spacer(min_height=5),
Div(text=
"""<div style="font-size : 18pt; line-height:16pt;">Game Mechanics:</div>"""
),
row(ctl_mechanics_selection1, ctl_mechanics_selection2),
))
# recommendation results
results_controls = WidgetBox(
ctl_recommended_list_title,
ctl_recommended_games,
Spacer(min_height=10),
)
# Create a row layout
layout = row(column(pref_controls, filter_controls), Spacer(min_width=50),
results_controls)
# Make a tab with the layout
tab = Panel(child=layout, title='Advanced Game Recommender')
return tab
plot_height=PLOT_HEIGHT,
plot_width=PLOT_WIDTH,
tools=TOOLS,
x_range=[1, 50],
y_range=[0, 1],
)
plot.yaxis.axis_label = "Transmission fraction"
plot.xaxis.axis_label = "Energy [keV]"
plot.line("x", "y", source=source, line_width=3, line_alpha=0.6)
plot.title.text = f"{response}"
plot.add_tools(custom_hover)
# Set up the inputs
ylog_checkbox = CheckboxGroup(labels=["y-log"], active=[0])
# materials in the path
material_input = AutocompleteInput(title="Material (lowercase)",
value=DEFAULT_MATERIAL[0])
material_input.completions = all_materials
material_thickness_input = TextInput(title="thickness",
value=str(DEFAULT_THICKNESS[0]))
material_density_input = TextInput(title="density",
value=str(this_material.density.value))
air_thickness_input = TextInput(title="air path length",
value=str(DEFAULT_AIR_THICKNESS))
air_pressure_input = TextInput(title='air pressure',
value=str(DEFAULT_AIR_PRESSURE))
air_temperature_input = TextInput(title='air temperature',
value=str(DEFAULT_AIR_TEMPERATURE))
detector_material_input = AutocompleteInput(title='Detector',
value=DEFAULT_DETECTOR_MATERIAL)
def beliebtheitsermittler(df,actorList, productionList , directorList, writersList, genreList,df_merged, ratingQuantile ):
text = "Füllen Sie die Felder aus und drücken auf den Start-Button um den Film zu bewerten."
actorList = list(set(actorList))
productionList = list(set(productionList))
directorList = list(set(directorList))
writersList = list(set(writersList))
genreList = list(set(genreList))
output_notebook()
# Set up widgets
actor1 = AutocompleteInput(completions=actorList, placeholder = 'Required',title='Schauspieler 1')
actor2 = AutocompleteInput(completions=actorList, placeholder = 'Required', title='Schauspieler 2')
actor3 = AutocompleteInput(completions=actorList, placeholder = 'Required', title='Schauspieler 3')
actor4 = AutocompleteInput(completions=actorList, placeholder = 'Required', title='Schauspieler 4')
production = AutocompleteInput(completions=productionList, placeholder = 'Required', title='Production')
director = AutocompleteInput(completions= directorList, placeholder = 'Required', title='Regie')
autor = AutocompleteInput(completions= writersList, placeholder = 'Required', title='Autor')
genre = Select(title = 'Auswahl des Hauptgenre',height = 50,value = 'Comedy', options = genreList)
select = Select(title = 'Auswahl der Metric',height = 50,value = 'Metascore', options = ['Metascore', 'imdbRating', 'TomatoRating'])
answer = Button(height = 100, width = 600,disabled = True,margin = [10,10,10,10],background = 'white', label = text)
button = Button(margin = [23,0,0,200], width = 100, button_type = 'primary', label = 'Start')
paragraph2 = Paragraph(margin = [40,0,0,10])
paragraph2.text = "Ergebnis:"
def doOnClick():
metric = select.value
columns = df_merged.columns.tolist()
columns.remove('Category')
if (actor1.value in actorList) and (actor2.value in actorList) and (actor3.value in actorList) and (actor4.value in actorList) and (production.value in productionList) and (director.value in directorList) and (autor.value in writersList):
filename = 'models/'+ metric + '_model.sav'
model = pickle.load(open(filename, 'rb'))
d = pd.DataFrame(0,index=np.arange(1), columns=columns)
d['Actors_' + actor1.value] = 1
d['Actors_' + actor2.value] = 1
d['Actors_' + actor3.value] = 1
d['Actors_' + actor4.value] = 1
d['Genre_' + genre.value] = 1
d['Director_' + director.value] = 1
d['Writer_' + autor.value] = 1
d['Production__'+ production.value] = 1
result = model.predict(d)[0]
if ('Gut' in result):
answer.background = 'green'
elif('Schlecht' in result):
answer.background = 'red'
else:
answer.background = 'yellow'
answer.label = result
else:
answer.label = text
answer.background = 'white'
button.on_click(doOnClick)
layout = [row(widgetbox(actor1 , actor2, actor3, actor4, genre),
widgetbox( production, director,autor, select, button ))]
def modify_doc(doc):
doc.add_root(row(layout))
doc.add_root(column(widgetbox(paragraph2,answer)))
handler = FunctionHandler(modify_doc)
app = Application(handler)
show(app)