diff --git a/README.md b/README.md
index 499cc73047f58096bc46ba407cec3cad3f54ad17..a2e97e1307f5c3845c1477d7c6c1391ecb1674b1 100755
--- a/README.md
+++ b/README.md
@@ -31,7 +31,11 @@ Next, to install the database, run the MongoDB server and execute this command (
./mongorestore --archive=/path/to/dump-iris.bin
```
-where `/path/to/` is the path to the dump file of the IRIS collection (provided with the package mongiris in `mongiris/data/dump-iris.bin`).
+where `/path/to/` is the path to the dump file of the IRIS collection (provided with the package mongiris in `mongiris/data/dump-iris.bin`).
+You may have to create two folders for Mongodb: `data/db` under `PATH/TO/MONGODB/bin`. A tip is to move the dump into that folder and use the hollowing steps:
+
+1. In a first terminal: `./mongod --dbpath=./data/db` (to run mongodb),
+2. In a second terminal: `./mongorestore --archive=./data/db/dump-dbinsee.bin` (to restore data from the dump).
### Run Predihood
diff --git a/predihood/__init__.py b/predihood/__init__.py
index b22478b7c702aba8e96c2a06009250a37cb23920..b85fb43366971f6c9024513fa238df2f7c2a8cc4 100644
--- a/predihood/__init__.py
+++ b/predihood/__init__.py
@@ -1,4 +1,3 @@
import logging
-import sys
logging.basicConfig(level=logging.DEBUG)
\ No newline at end of file
diff --git a/predihood/classifiers_list.py b/predihood/classifiers_list.py
index d1971991e9d133645ec23814659961ce73a88d9d..052708daac65dbc5ac5e3b7960d4049f63281431 100644
--- a/predihood/classifiers_list.py
+++ b/predihood/classifiers_list.py
@@ -1,7 +1,6 @@
# define available classifiers for the algorithmic interface
import os
import re
-import sys
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
from sklearn.neighbors import KNeighborsClassifier
@@ -12,7 +11,7 @@ from sklearn.tree import DecisionTreeClassifier
import importlib
tree = os.listdir('algorithms')
regex = re.compile(r'__[^_]*__')
-tree_filtered = [i for i in tree if not regex.match(i)] # remove undesirable files such as __pycache__
+tree_filtered = [i for i in tree if not regex.match(i)] # remove undesirable files such as __pycache__
AVAILABLE_CLASSIFIERS = {
"Random Forest Classifier": RandomForestClassifier,
diff --git a/predihood/static/js/carto.js b/predihood/static/js/carto.js
index b13931a0b8d47885a6831748d74763b4f2243c0e..df7e98ae0edf57705b12806ce1370f44e605686f 100644
--- a/predihood/static/js/carto.js
+++ b/predihood/static/js/carto.js
@@ -104,87 +104,34 @@ function displayPopup(e) {
divInformation.append(moreInfosLink);
}
-
- if($("#assessmentMode").is(":checked")) {
- // alert("assessment mode");
-
- for(let env in environment_variables) {
- let env_values = environment_variables[env]
- let div_container = $("<div>").prop("id", "assessment"+env)
- let list_values = $("<select>");
- for(let value in env_values) { list_values.append($("<option>").prop("value", env_values[value]).text(env_values[value])) }
- div_container.append(env).append(list_values)
- divInformation.append(div_container)
- }
-
- if($("#addAssessmentButton").length > 0) {
- $("#addAssessmentButton").removeAttr("id"); // remove id to avoid duplicates (fix the miss of event on button)
- }
-
- let to_csv_button = $("<button>").prop("id", "addAssessmentButton");
- if(preferred_language_carto === "french") {
- to_csv_button.text("Ajouter au jeu de données");
- } else {
- to_csv_button.text("Add to dataset");
- }
-
- let messageTooltip = divInformation[0].outerHTML + to_csv_button[0].outerHTML;
- layer.bindPopup(messageTooltip)
- layer.bringToFront();
- layer.openPopup();
-
- $("#addAssessmentButton").on("click", function() {
- let data_param = {}
- for(let env in environment_variables) {
- data_param[env] = $("#assessment"+env)[0].children[0].value
- }
- data_param["code_iris"] = code_iris
- console.log(data_param)
- $.ajax({
- type: "GET",
- url: "/add_iris_to_csv",
- data: data_param,
- "async": false,
- contentType: 'application/json;charset=UTF-8',
- success: function(result) {
- alert(result)
- },
- error: function(result, textStatus, errorThrown) {
- console.log(errorThrown);
- }
- });
- });
+ if (selected_algorithm !== "undefined" && selected_algorithm !== undefined) {
+ predictions = predict(code_iris, selected_algorithm)
+ console.log(predictions)
}
- else {
- if (selected_algorithm !== "undefined" && selected_algorithm !== undefined) {
- predictions = predict(code_iris, selected_algorithm)
- console.log(predictions)
- }
- let selectAlgorithm = $("<select>")
- selectAlgorithm
- .prop("id", "selectAlgorithmTooltip")
- .append($("<option>").prop("value", "undefined").text("---"))
+ let selectAlgorithm = $("<select>")
+ selectAlgorithm
+ .prop("id", "selectAlgorithmTooltip")
+ .append($("<option>").prop("value", "undefined").text("---"))
- for(let algorithm of classifiers) {
- selectAlgorithm.append($("<option>").prop("value", algorithm).text(algorithm));
- }
- previously_selected_algorithm = selected_algorithm;
+ for(let algorithm of classifiers) {
+ selectAlgorithm.append($("<option>").prop("value", algorithm).text(algorithm));
+ }
+ previously_selected_algorithm = selected_algorithm;
- let divPredictions = $("<div>").prop("id", "divPredictions")
- if(predictions !== undefined) {
- for(let key in predictions) { divPredictions.append(capitalizeFirstLetter(key.split("_").join(" "))+': ' + predictions[key]["most_frequent"] + " (" + predictions[key]["count_frequent"] + "/7)").append($('<br>')); }
- }
+ let divPredictions = $("<div>").prop("id", "divPredictions")
+ if(predictions !== undefined) {
+ for(let key in predictions) { divPredictions.append(capitalizeFirstLetter(key.split("_").join(" "))+': ' + predictions[key]["most_frequent"] + " (" + predictions[key]["count_frequent"] + "/7)").append($('<br>')); }
+ }
- let messageTooltip = divInformation[0].outerHTML + selectAlgorithm[0].outerHTML + divPredictions[0].outerHTML;
- console.log(messageTooltip)
- layer.bindPopup(messageTooltip)
- layer.bringToFront();
- layer.openPopup();
+ let messageTooltip = divInformation[0].outerHTML + selectAlgorithm[0].outerHTML + divPredictions[0].outerHTML;
+ console.log(messageTooltip)
+ layer.bindPopup(messageTooltip)
+ layer.bringToFront();
+ layer.openPopup();
- $("#selectAlgorithmTooltip").val(previously_selected_algorithm); // must be after binding the popup to be effective
- $("#selectAlgorithmTooltip").on("click", function() { displayPopup(e)}) // update popup (env variables) when click on an algorithm
- }
+ $("#selectAlgorithmTooltip").val(previously_selected_algorithm); // must be after binding the popup to be effective
+ $("#selectAlgorithmTooltip").on("click", function() { displayPopup(e)}) // update popup (env variables) when click on an algorithm
}
/**
diff --git a/predihood/temp.py b/predihood/temp.py
deleted file mode 100644
index 3ea63a13d49acebd0cda3eecd1802d3aaec977b4..0000000000000000000000000000000000000000
--- a/predihood/temp.py
+++ /dev/null
@@ -1,89 +0,0 @@
-import pandas as pd
-from sklearn.cluster import KMeans
-
-from predihood.classes.Data import Data
-from predihood.classes.Dataset import Dataset
-from predihood.classes.Method import Method
-from predihood.config import ENVIRONMENT_VALUES
-
-
-def geo_position():
- file = pd.read_csv("generated_files/cleaned_data.csv")
- north, south, east, west, southEast, northEast, southWest, northWest, centre, problem = 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
-
- for index, line in file.iterrows():
- # print(line)
- # print(line["old_landscape"])
- if isinstance(line["old_geographical_position"], str):
- old_val = line["old_geographical_position"].split()[0].upper()
- if old_val == "NORD":
- north += 1
- elif old_val == "SUD":
- south += 1
- elif old_val == "EST":
- east += 1
- elif old_val == "OUEST":
- west += 1
- elif old_val == "CENTRE":
- centre += 1
- elif old_val == "NORD-EST":
- northEast += 1
- elif old_val == "NORD-OUEST":
- northWest += 1
- elif old_val == "SUD-EST":
- southEast += 1
- elif old_val == "SUD-OUEST":
- southWest += 1
- else:
- problem += 1
- print(line["old_geographical_position"])
- else:
- print(line["old_geographical_position"])
- problem += 1
-
- if isinstance(line["new_geographical_position"], str):
- new_val = line["new_geographical_position"].split()[0].upper()
- if new_val == "NORD":
- north += 1
- elif new_val == "SUD":
- south += 1
- elif new_val == "EST":
- east += 1
- elif new_val == "OUEST":
- west += 1
- elif new_val == "CENTRE":
- centre += 1
- elif new_val == "NORD-EST":
- northEast += 1
- elif new_val == "NORD-OUEST":
- northWest += 1
- elif new_val == "SUD-EST":
- southEast += 1
- elif new_val == "SUD-OUEST":
- southWest += 1
- else:
- problem += 1
- print(line["new_geographical_position"])
- else:
- print(line["new_geographical_position"])
- problem += 1
-
- print(north, south, east, west, southEast, northEast, southWest, northWest, centre, " - ", problem)
-
-
-def k_means_v1():
- data = Data()
- data.init_all_in_one()
- for env in ENVIRONMENT_VALUES:
- dataset = Dataset(data, env, "unsupervised")
- # dataset.selected_indicators =
- nb_clust = len(ENVIRONMENT_VALUES[env])
- print(dataset.selected_indicators)
-
- estimator = Method("kmeans", dataset, KMeans(n_clusters=nb_clust))
- estimator.fit()
-
-
-if __name__ == '__main__':
- # k_means_v1()
- geo_position()
diff --git a/predihood/templates/algorithmic-interface.html b/predihood/templates/algorithmic-interface.html
index 9b4c6e52351dedf555b59e0a368f15ef2c94bd4a..1c0f0d2aae2e824f661611816c6ec3dc2c9d59db 100644
--- a/predihood/templates/algorithmic-interface.html
+++ b/predihood/templates/algorithmic-interface.html
@@ -33,7 +33,7 @@
{% if language == "french" %}
<h6>Paramètres spécifiques<i id="specificParametersTitle" class="fas fa-angle-double-up"></i></h6>
<ul id="specificParameters" class="nav flex-column bg-white mb-0" style="display: block"></ul>
- <h6>Paramèteres communs<i id="commonParametersTitle" class="fas fa-angle-double-up"></i></h6>
+ <h6>Paramètres communs<i id="commonParametersTitle" class="fas fa-angle-double-up"></i></h6>
<ul id="commonParameters" class="nav flex-column bg-white mb-0" style="display: block"></ul>
{% else %}
<h6>Specific parameters<i id="specificParametersTitle" class="fas fa-angle-double-up"></i></h6>
diff --git a/predihood/templates/form.html b/predihood/templates/form.html
index 2f114f0f862f1835162f0b4213ae25565ee624cd..84d99687daace27c7db28553f41250fadc1f9333 100644
--- a/predihood/templates/form.html
+++ b/predihood/templates/form.html
@@ -55,14 +55,6 @@
<br>
</div>
-<div>
- {% if language == "french" %}
- Expertise manuelle: <input type="checkbox" id="assessmentMode"/>
- {% else %}
- Manual assessment: <input type="checkbox" id="assessmentMode"/>
- {% endif %}
-</div>
-
<div class="input-group mb-3">
<button class="btn" type="button" id="boutonEffacer">
{% if language == "french" %}
diff --git a/predihood/tests.py b/predihood/tests.py
index 97fb69451af178d245f8b8078decbbf8b4d59b55..d445c260b8588caf9c8ed0ae29b84f39f6cfb8ad 100644
--- a/predihood/tests.py
+++ b/predihood/tests.py
@@ -54,7 +54,7 @@ class TestCase(unittest.TestCase):
classifier_name = "KNeighbors Classifier"
classifier = get_classifier(classifier_name)
# classifier == KNeighborsClassifier() fails because they are different objects
- assert type(classifier) == type(KNeighborsClassifier())
+ assert classifier.isistance(type(KNeighborsClassifier()))
def test_set_classifier(self):
# test if setting the parameters of a classifier changes its internal parameters
@@ -150,4 +150,3 @@ class TestCase(unittest.TestCase):
if __name__ == "__main__":
unittest.main(verbosity=2) # run all tests with verbose mode
-