Upload map_viz_pred.py

src/map_viz_pred.py

@@ -0,0 +1,99 @@
+from __future__ import division, print_function
+from six import StringIO
+from svgpath2mpl import parse_path
+from collections import defaultdict
+import xml.etree.ElementTree as etree
+import re
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
+import requests
+import pandas as pd
+import datetime
+
+def calling_pred_map_viz():
+    r = "snazzy-image-01.svg"
+    tree = etree.parse(r)
+    root = tree.getroot()
+    path_elems = root.findall('.//{http://www.w3.org/2000/svg}path')
+
+    paths = [parse_path(elem.attrib['d']) for elem in path_elems]
+    facecolors = []
+    edgecolors = []
+    linewidths = []
+    for elem in path_elems:
+        facecolors.append(dict(item.split(":") for item in elem.attrib.get('style', 'none').split(";")).get("fill", "none"))
+        edgecolors.append(dict(item.split(":") for item in elem.attrib.get('style', 'none').split(";")).get("stroke", "none"))
+        linewidths.append(dict(item.split(":") for item in elem.attrib.get('style', 'none').split(";")).get("stroke-width", "none").replace("px", ""))
+
+    path_id = defaultdict(int)
+    for i, elem in enumerate(path_elems):
+        try:
+            #print(i, elem.attrib['id'])
+            path_id[elem.attrib['id']] = i
+        except:
+            continue
+
+
+    counts_df1 = merge_volumes(counts_df)
+    counts_df1.loc[:,'date_time'] = pd.to_datetime(counts_df1.loc[:,'date'] + " "+ counts_df1.loc[:,'time'], format='%Y-%m-%d %H:%M:%S')
+    counts_df1.loc[:,'hour'] = counts_df1.loc[:,'date_time'].apply(hour_rounder)
+    counts_df1.loc[:,'day_name'] = counts_df1.loc[:,'date_time'].dt.day_name()
+    filtered_date = counts_df1.iloc[-1]['date']
+    filtered_time = counts_df.iloc[-1]['time']
+    filtered_day = counts_df1.iloc[-1]['day_name']
+    filtered_hour = counts_df1.iloc[-1]['hour']
+
+
+    day_hour_view_group = counts_df1.groupby(by=['view', 'day_name', 'hour'])['total'].mean().reset_index()
+    count_max = day_hour_view_group['total'].max()
+    count_min = day_hour_view_group['total'].min()
+
+
+    count_dict = {"woodlands_to_sg" :date_view_group.loc[(date_view_group['view'] == 'Woodlands - to SG') & (date_view_group['day_name'] == filtered_day) & (date_view_group['hour'] == filtered_hour), "total" ].iloc[0],
+                  "woodlands_to_jh" :date_view_group.loc[(date_view_group['view'] == 'Woodlands - to Johor') & (date_view_group['day_name'] == filtered_day) & (date_view_group['hour'] == filtered_hour), "total" ].iloc[0],
+                  "tuas_to_sg" :date_view_group.loc[(date_view_group['view'] == 'Tuas - to SG') & (date_view_group['day_name'] == filtered_day) & (date_view_group['hour'] == filtered_hour), "total" ].iloc[0],
+                  "tuas_to_jh" :date_view_group.loc[(date_view_group['view'] == 'Tuas - to Johor') & (date_view_group['day_name'] == filtered_day) & (date_view_group['hour'] == filtered_hour), "total" ].iloc[0]
+                  }
+
+    values = np.array([0., 0.5, 1.])
+    values = np.sort(np.array(values))
+    values = np.interp(values, (values.min(), values.max()), (0., 1.))
+    colors = ["#539f6b", "#ffc835", "#bf0000"]
+    cmap = mpl.colors.LinearSegmentedColormap.from_list("custom", list(zip(values, colors)))
+
+    norm = mpl.colors.Normalize(vmin=count_min, vmax=count_max)
+
+
+
+    hex_dict = {k: mpl.colors.to_hex(cmap(norm(v))) for k, v in count_dict.items()}
+    color_dict = defaultdict(str)
+
+    for k, i in path_id.items():
+        #print(k, i)
+        color_dict[i] = hex_dict[k]
+
+    for k, i in color_dict.items():
+        #print(k,i)
+        facecolors[k] = i
+
+    collection = mpl.collections.PathCollection(paths, 
+                                          edgecolors=edgecolors, 
+                                          linewidths=[int(i)/100 for i in linewidths if i != 'none'],
+                                          facecolors=[i.strip() for i in facecolors])
+
+
+
+    fig = plt.figure(figsize=(10,10))
+    ax = fig.add_subplot(111)
+    # ax.close()
+    collection.set_transform(ax.transData)
+    ax.add_artist(collection)
+    ax.set_xlim([100, 1900])
+    ax.set_ylim([1800, 0])
+    ax.text(200, 100, '1,000,000', color='r', size='large', name = 'Georgia')
+    ax.set_title(datetime.datetime.strptime(last_date, '%Y-%m-%d').strftime('%a, %d %B %Y') + " | " + last_time + " SGT", fontname = 'Georgia')
+    plt.show()
+
+
+calling_map_viz()