{% extends "en/base.html" %}
{% block title %}{{query}}{% endblock %}

{% block nav %}
<div id="print" class="blink {{ connection }}">
	<a href="?q={{ query }}&print=now&results_count={{ results_count }}"><img src="/static/images/epson.png"></a>
</div>
<script>
	(function () {
		var printing = false,
			button = document.querySelector('#print a');
			
		button.addEventListener('click', function (e) {
			if (!printing) {
				printing = true;
				button.classList.add('printing');
			}
			else {
				e.preventDefault();
				alert('Already printing ...');
			}
		})
	})();
</script>
{% endblock %}

{% block results %}
{% if results == {} %}
	<div id="notused">This word could not be found.</div>
{% else %}
	<div class="cross">
		<p class="note">[Note on the search results]</p>
		<p class="tfidf">Once a search query is submitted, the <em>TF-IDF</em> starts to go through all the manifestos in the dataset, to see if a word is used, and if yes, to put it in the list of search results. The list is sorted according to the importance of the word <strong>{{ query }} </strong> to each manifesto. </p>
		<p class="techfem">The search results are snippets, statements, quotes or questions, threaded together by one single word, create a cross-reading index. The occurances of <strong> {{ query }}</strong> in the different manifestos, become eachother complexifiers. </p>
		<br>
		<br>
	</div>
	<div id="results">
		<h1>Cross-reading through the manifestos along the axes of <strong class="query">{{ query }}</strong>:</h1>
		<div class="results">
			{% for x, manifesto in results.items() %}
				{% for sentence in manifesto.html %}
					<div id="{{ x }}_{{ loop.index }}" class="result">
						<div class="title">
							{{ manifesto.name }}
						</div>
						<div class="sentence">{{ sentence }}</div>
					</div>
				{% endfor %}
			{% endfor %}
		</div>	
	</div>
{% endif %}
{% endblock %}

{% block suggestions %}
<div id="suggestions">
	<h1>SUGGESTIONS</h1>

	{% if analytics %}
		{% if analytics.stemmer %}
			<div id="similars" class="analytics stemmer">
				<h2>Similar but not the same to <em>{{ query }}</em>:</h2>
				{% for word in analytics.stemmer %}
					<strong class="word"><a href="/{{ lang}}/?q={{ word }}">{{ word }}</a></strong>
				{% endfor%}
			</div>
			<br>
		{% endif%}	
	{% endif%}

	<div class="suggestions techfem">
		<h1>Cross-reading suggestions (manual selection):</h1>
		{% for word in suggestions %}
			<strong class="query"><a href="?q={{word}}">{{ word.strip() }}</a></strong>
		{% endfor %}
	</div>
	{% if analytics.mappings %}
	<br>

	<div class="suggestions tfidf">
		<h1>Cross-reading suggestions (algorithmic selection) through <em>{{ results[0]['name']}}</em>: <br></h1>
		<div class="">
			{% for tfidf, word in analytics.mappings[:50] %}
				{% if word == query %}
					<strong class="word">{{ word }}</strong>
				{% else %}
					<strong class="word"><a href="/{{ lang}}/?q={{ word }}">{{ word }}</a></strong>
				{% endif%}
			{% endfor%}
		</div>
		<br>
		<div><a class="contrast" href="/{{ lang}}/mappings/{{ results[0]['filename'].strip() | replace('.txt','') }}">Read more ◐</a></div>
	</div>
	{% endif%}
</div>

<div class="cross">
	<p class="note">[Note on activating]</p>
	<p class="tfidf">
		The <em>TF-IDF algorithm</em> is an activator. Activating non-linear threads through a dataset of words. 
		<br><br>
		As a navigator the algorithm is a provider of order, deciding on the importance of the search term for a manifesto.
	</p>
	<p class="techfem">
		The <em>cyber- and technofeminist manifesto</em> are written and published to activate. Declaring intentions, motives or specific views on technology. Their writing styles, different as they are, are often statement-based, short and sometimes militant.
		<br><br>
		<em>&quot;Nothing should be accepted as fixed, permanent, or 'given' -- neither material conditions nor social forms..&quot;</em> (Xenofeminist manifesto), <br>
		<em>&quot;So that is why no revolution should be without her.&quot;</em> (The Manifesto of Futurist Woman)
	</p>
</div>
{% endblock %}