Merge branch 'branche_base_lorys' into 'master'

Branche base lorys

See merge request !1

main.py

 """File to execute to show results"""
+#Data
+from parameters import SESSION
+
+#Basics
+import re
+from datetime import datetime, timedelta
+import matplotlib.dates as mdates
 import numpy as np
 import matplotlib.pyplot as plt
-from datetime import datetime, timedelta
-from parameters import SESSION
+from pandas.plotting import register_matplotlib_converters
+register_matplotlib_converters()
+#Stats
+import statsmodels.graphics as stm_graphs
+import pandas as pd 
+import statsmodels.api as stm
+#Graph map
+from mpl_toolkits.basemaps import Basemap
+
 
 
 def execute_query(query):
@@ -16,6 +30,28 @@ def ask_q(possibilities, text=">>> "):
         answer = input(text)
     return answer
 
+def ask_d(text=">>> "):
+    t = input(text)
+    done = False
+
+    date_parser = re.compile(
+        r"(?P<year>\d+)-(?P<month>\d+)-(?P<day>\d+) (?P<hour>\d+):(?P<minute>\d+)"
+    )
+    match = False
+    result = None
+
+
+
+    while(match == False):
+        match = date_parser.match(t)
+        if not match:
+            print("Veuillez suivre le format demandé")
+            continue
+        m = match.groupdict()
+        result = (int(m['year']), int(m['month']), int(m['day']), int(m['hour']), int(m['minute']))
+           
+            
+    return result
 
 class Manager:
     table = None  # table name use by the function
@@ -61,80 +97,83 @@ class Manager:
             print("\t-", text, ":", code)
         attr = ask_q(decision.keys())
 
-        x = []
-        y = []
-        saisons = {
-            'spring': {
-                'n': 0,
-                'somme': 0,
-                'month': [3, 4, 5],  # March - May
-                'end': lambda dt: datetime(dt.year, 6, 1) - timedelta(days=1),
-                'legend': False,
-                'color': 'r'
-            },
-            'summer': {
-                'n': 0,
-                'somme': 0,
-                'month': [6, 7, 8],  # June - August
-                'end': lambda dt: datetime(dt.year, 9, 1) - timedelta(days=1),
-                'legend': False,
-                'color': 'y'
-            },
-            'automne': {
-                'n': 0,
-                'somme': 0,
-                'month': [9, 10, 11],  # September - November
-                'end': lambda dt: datetime(dt.year, 12, 1) - timedelta(days=1),
-                'legend': False,
-                'color': 'm'
-            },
-            'winter': {
-                'n': 0,
-                'somme': 0,
-                'month': [12, 1, 2],  # December - Febrarie
-                'end': lambda dt: datetime(dt.year + 1, 3, 1) - timedelta(days=1),
-                'legend': False,
-                'color': 'k'
-            }
-        }
-        query = "SELECT * FROM {} WHERE station={}".format(self.table, station.__repr__())
+        ts = pd.Series()
+        query = "SELECT time,{} FROM {} WHERE station={}".format(attr,self.table, station.__repr__())
         for row in execute_query(query):
             value = getattr(row, attr)
             if value is None:
                 continue
-            x.append(datetime(*list(row.time)))
-            y.append(value)
-            # For saison
-            for saison, d in saisons.items():
-                if row.time[1] in d['month']:
-                    d['n'] += 1
-                    d['somme'] += value
-                    break
-
-        date, last_date = x[0], x[-1]  # first date and last date, initialisation
-        x = np.array(x)
-        y = np.array(y)
-        plt.plot(x, y, label=attr)
-
-        # Mark saison
-        while date < last_date:
-            for saison, d in saisons.items():
-                if date.month in d['month']:
-                    next_date = min(last_date, d['end'](date))
-                    moyenne = d['somme'] / d['n']
-                    if d['legend']:
-                        plt.plot([date, next_date], [moyenne, moyenne], d['color'], linewidth=4)
-                    else:
-                        plt.plot([date, next_date], [moyenne, moyenne], d['color'], label=saison, linewidth=4)
-                        d['legend'] = True
-                    date = next_date + timedelta(days=1)
-                    break
-        plt.title(station)
+            ts.loc[datetime(*list(row.time))] = value
+
+        figure = plt.figure(figsize=(25,16))
+        axes = plt.subplot()
+        axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M'))
+        _=plt.xticks(rotation=90) 
+        
+        
+        plt.plot(ts, label=attr)
+        plt.title("Donnees de " + str(attr) + " pour la station : " + station )
         plt.legend()
         plt.show()
+        plt.savefig('./out/graph_'+station+'_'+ str(attr) +'.png')
+
+        res = stm.tsa.seasonal_decompose(ts, freq=15, extrapolate_trend= 'freq')
+        res.plot()
+        plt.show()
+        plt.savefig('./out/decompose_'+station+'_'+ str(attr) +'.png')
+        
+
+        ACF = stm_graphs.tsaplots.plot_acf(ts,lags=30)
+        plt.show()
+        plt.savefig('./out/acf_'+station+'_'+ str(attr) +'.png')
 
     def map(self):
-        print("Cette fonction n'est pas implémentée")
+        self.table = "TABLE_TIME"
+
+        #Ask Date
+        print("Entrez une date sous la forme YYYY-MM-DD HH:mm")
+        date = ask_d()
+
+        # Search element
+        decision = {
+            "tmpf": "La témparature",
+            "relh": "L'humidité"
+        }
+        print("Choisissez un élément parmis les suivant :")
+        for code, text in decision.items():
+            print("\t-", text, ":", code)
+        attr = ask_q(decision.keys())
+
+
+        df = pd.DataFrame()
+        query = "SELECT station,lon,lat,{} FROM {} WHERE time={}".format(attr,self.table, date)
+        print(query)
+        for row in execute_query(query):
+            if getattr(row, "station") is None:
+                continue
+            print(getattr(row,"station"))
+            df = df.append({"station": getattr(row, "station"),
+                        "lon":getattr(row,"lon"),
+                        "lat":getattr(row,"lat"),
+                        "val":getattr(row,attr)},
+                        ignore_index=True)
+
+        
+        map = Basemap(projection='mill',lat_0=26.281898,lon_0=-16.42,lat_1 = 43.08,lon_1 =7.35, resolution='l')
+        # draw coastlines, country boundaries, fill continents.
+        map.drawcoastlines(linewidth=0.25)
+        map.drawcountries(linewidth=0.25)
+        map.fillcontinents(color='coral',lake_color='aqua')
+        # draw the edge of the map projection region (the projection limb)
+        map.drawmapboundary(fill_color='aqua')
+        # draw lat/lon grid lines every 30 degrees.
+        map.drawmeridians(np.arange(0,360,30))
+        map.drawparallels(np.arange(-90,90,30))
+
+        plt.title('Map')
+        plt.show()
+        plt.savefig('./out/map.png')
+
 
     def cluster(self):
         print("Cette fonction n'est pas implémentée")

parameters.py

@@ -7,7 +7,7 @@ from collections import OrderedDict
 import os
 import datetime
 # Can be specified
-KEY_SPACE = "nf26"
+KEY_SPACE = "lhamadac_projet"
 TABLE = "Spain"
 
 # Don't change
@@ -22,12 +22,17 @@ COLUMNS = OrderedDict([
     ('lon', float),
     ('lat', float),
     ('tmpf', float),
+    ('tmpc',float),
     ('dwpf', float),
+    ('dwpc',float),
     ('relh', float),
     ('drct', float),
     ('sknt', float),
+    ('sped',float),
     ('alti', float),
     ('mslp', float),
+    # ('p01m',float), all null
+    # ('p01i',float), all null
     ('vsby', float),
     ('gust', float),
     ('skyc1', str),
@@ -45,8 +50,7 @@ COLUMNS = OrderedDict([
     # ('peak_wind_gust', ), all null
     # ('peak_wind_drct', ), all null
     # ('peak_wind_time', ), all null
-    ('feel', float),
-    ('metar', str)
+    ('feel', float)
 ])
 # Name of table -> Primary key
 TABLES = {