Add script that create static html page from yaml files

.gitignore

+*.html
 binario.txt
 output.txt
 current.yaml
@@ -8,4 +9,4 @@ ensalador
 schedules.yaml
 rooms.yaml
 Makefile
-munkres-cpp
\ No newline at end of file
+munkres-cpp

plots/.gitignore

+*.html

plots/README.md

+# ensalador_plots.py
+
+## How to use
+
+RUN: 
+```bash
+python3 ensalador_plots.py rooms.yaml schedules.yaml current.yaml
+```
+
+The yaml files is the files used and generated by ensalador algorithm.
+
+
+If the program works, the program will generate the follow files:
+
+- not_scheduled.html: Page that contains the schedules that has no rooms assigned
+
+- capacity_use.html: Page that contains a chart for every block and the relation between this use and this maximum room capacity
+
+- ensalamento_graph-bar.html: Page that contains a chart with relation between the use and maximum capacity of all blocks used on ensalamento
+
+- X_heatmap.html: For every sector, we have a file (with X = name of sector) that contains the relation of every room use by days of week
\ No newline at end of file

plots/ensalador_plots.py

+from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
+import plotly.graph_objs as go
+from plotly import tools
+
+import numpy as np
+import datetime
+
+import yaml
+import io
+from collections import defaultdict
+
+import sys
+
+WEEK_DAYS = ["Domingo", "Segunda", "Terça", "Quarta", "Quinta", "Sexta", "Sábado"]
+# WEEK_DAYS = ["Segunda", "Terça", "Quarta", "Quinta", "Sexta", "Sábado"]
+
+MIN_HOUR_DAY = 7
+MAX_HOUR_DAY = 23
+
+# Every room that has this strings in name will be disconsidered
+BANNED_LIST_ROOMS = [
+    "palotina",
+    "dp2",
+    "dp1",
+]
+
+# Every schedule that has this strings on blocks names will be disconsidered
+BANNED_SCHEDULE_BLOCKS = [
+    "palotina",
+]
+
+
+SECTORS = [
+    "politecnico",
+    "humanas",
+    "biologicas",
+    "palotina",
+]
+
+BLOCK_2_SECTOR = {
+    'humanas-dp1-11': 'humanas',
+    'humanas-dp1-09': 'humanas',
+    'humanas-dp2-05': 'humanas',
+    'humanas-dp1-12': 'humanas',
+    'humanas-dp1-10': 'humanas',
+    'humanas-dp1-01': 'humanas',
+    'humanas-dp2-03': 'humanas',
+    'humanas-dp2-04': 'humanas',
+    'humanas-dp1-06': 'humanas',
+    'humanas-dp2-06': 'humanas',
+    'dp1': 'humanas',
+    'dp2': 'humanas',
+
+    'palotina-bl-5': 'palotina',
+    'palotina-bl-1': 'palotina',
+    'palotina-bl-3': 'palotina',
+    'palotina-bl-4': 'palotina',
+    'palotina-bl-2': 'palotina',
+    
+    'bl_anexo_i': 'biologicas',
+    'bl': 'biologicas',
+    
+    'pf': 'politecnico',
+    'pm': 'politecnico',
+    'pd': 'politecnico',
+    'pg': 'politecnico',
+    'eq': 'politecnico',
+    'pk': 'politecnico',
+    'pa': 'politecnico',
+    'ph': 'politecnico',
+    'ct': 'politecnico',
+    'pc': 'politecnico',
+    'pl': 'politecnico',
+    'pq': 'politecnico',
+}
+
+
+MARGIN_PLOTS = go.layout.Margin(
+    l=50,
+    r=50,
+    b=200,
+    t=150,
+    pad=0
+)
+
+def pretty(d, indent=0):
+   for key, value in d.items():
+      print('\t' * indent + str(key))
+      if isinstance(value, dict):
+         pretty(value, indent+1)
+      else:
+         print('\t' * (indent+1) + str(value))
+
+def plot_matrix_heatmap(x_axis_labels, y_axis_labels, z_axis_labels, title="", filename="ensalament-heatmap"):
+
+    my_colorsc=[[0, 'rgb(255,255,255)'],#white
+        # [0.08, 'rgb(255,255,255'], 
+        [0.2, 'rgb(0,0,255)'],
+        [0.6, 'rgb(255,165,0)'],#orange
+        [0.8, 'rgb(255,165,0)'],
+        # [0.4, 'rgb(255,0,0'], #red
+        [1.0, 'rgb(255,0,0)']
+        # [0.999, 'rgb(255,0,0)'],
+        # [1.0, 'rgb(0,255,0)']
+    ]
+        # [0.8, 'rgb(0,0,255)'], #blue
+
+    data = [
+        go.Heatmap(
+            z=z_axis_labels,
+            x=x_axis_labels,
+            y=y_axis_labels,
+            # colorscale='Viridis',
+            colorscale = my_colorsc,
+            colorbar= {
+                # "x": -2,
+                "y": 1,
+                "yanchor": "top",
+                # "width": 30,
+                "tickmode": "array",
+                "lenmode": "pixels",
+                "len": 500,
+            }
+        )
+    ]
+
+    layout = go.Layout(
+        title=title,
+        xaxis = dict(ticks='', nticks=24, side='top'),
+        yaxis = dict(ticks='' ),
+        autosize = True,
+        height = len(y_axis_labels)*30,
+        margin=MARGIN_PLOTS,
+    )
+
+    fig = go.Figure(data=data, layout=layout)
+    plot(fig, filename=filename)
+
+
+
+def daily_use(rooms_uses, blocks):
+
+    for sector in SECTORS: 
+        data_heat_map = []
+        y_axis_labels = []
+        x_axis_labels = WEEK_DAYS
+        for room in rooms_uses:
+            room_block = get_block_of_room(room, blocks)
+            if(room_block != "" and BLOCK_2_SECTOR[room_block] != sector):
+                continue
+            y_axis_labels.append(room)
+            heat_map_line = []
+            
+            for day in rooms_uses[room]:
+                used_times_per_day = len( [ 1 for x in rooms_uses[room][day] if rooms_uses[room][day][x] != None] )
+                heat_map_line.append(used_times_per_day)
+            
+            data_heat_map.append(heat_map_line)
+        
+        if(len(data_heat_map) == 0):
+            continue
+        
+        plot_matrix_heatmap(
+            x_axis_labels,
+            y_axis_labels,
+            data_heat_map,
+            "Uso (horas) diário de cada sala não reestrita. <br>As cores próximas de azul representam baixos usos das salas e as próximas do vermelho um alto uso (cores brancas indicam o não uso da sala em um determinado dia da semana).<br> Destaca-se o uso das salas PM.<br>",
+            sector+"_heatmap"
+        )
+
+
+def create_axis_schedules():
+    x_axis_labels = []
+    
+    for i in range(7):
+        for j in range(1,25):
+            init_hour_str = str(j%24)+":30"
+            end_hour_str = str((j+1)%24)+":30"
+            
+            time_str = init_hour_str+" - "+end_hour_str
+
+            x_axis_labels.append(WEEK_DAYS[i]+" "+time_str)
+    return x_axis_labels
+
+def rooms_uses_by_time(rooms_uses):
+
+    total_rooms = len(rooms_uses)
+
+    x_axis_labels = create_axis_schedules()
+    
+    y_data = [0 for i in range(24*7)]
+    for room in rooms_uses:
+        for day in rooms_uses[room]:
+            for use_room_time in rooms_uses[room][day]:
+                course_code = rooms_uses[room][day][use_room_time]
+                if course_code:
+                    y_data[(day-1)*24 + (use_room_time-1)] += 1
+        
+
+    # print(y_data)
+    data = [
+        go.Bar(
+            x=x_axis_labels,
+            y=y_data,
+            name='Salas usadas neste horário',
+        ),
+        # go.Bar(
+        #     x=x_axis_labels,
+        #     y=[total_rooms-x for x in y_data],
+        #     name='Salas não usadas neste horário',
+        # ),
+        go.Scatter(
+            x=x_axis_labels,
+            y=[str(total_rooms) for x in range(len(x_axis_labels))],
+            name="Capacidade",
+        )
+
+    ]
+
+    layout = go.Layout(
+        title="Quantidade de salas não restritas usadas por horários.<br> Observa-se um pico no uso das salas nas segundas das 13:30 às 15:30. <br>Total de salas não restritas: "+str(total_rooms),
+        autosize = True,
+        barmode='stack',
+        margin=MARGIN_PLOTS,
+        xaxis={
+            "title": "Horários",
+        },
+        yaxis={
+            "title": "Quantidade de salas utilizadas",
+        },
+    )
+
+    fig = go.Figure(data=data, layout=layout)
+    plot(fig, filename='ensalamento-graph-bar')
+
+
+def get_block_of_room(room, blocks):
+    for block in blocks:
+        rooms = blocks[block]
+        if(room in rooms):
+            return block
+    return None
+
+def get_block_of_schedule(schedule_code, to_schedule):
+    for ts in to_schedule:
+        if(ts["code"] == schedule_code):
+            return ts["block"]
+    return None
+
+def merge_room_uses(rooms):
+    block_use = {}
+    for i in range(1,8):
+        block_use[i] = {}
+        for j in range(1,25):
+            block_use[i][j] = 0
+    
+    for room in rooms:
+        for i in range(1,8):
+            for j in range(1,25):
+                if(room[i][j] != None):
+                    block_use[i][j] += 1
+    return block_use
+
+def dict_uses_in_week_to_array(dic):
+    array = np.zeros(7*24)
+    for i in range(1,8):
+        for j in range(1,25):
+            array[i*7 + j] = dic[i][j]
+    
+    return array
+
+
+def overflow_block_capacity(rooms_uses, blocks_capacities, blocks_not_restricts):
+    
+
+    blocks_uses = {}
+    
+    for block_name in blocks_capacities:
+        blocks_uses[block_name] = merge_room_uses(
+            [rooms_uses[x] for x in rooms_uses if get_block_of_room(x, blocks_not_restricts) == block_name ]
+        )
+
+    x_data = create_axis_schedules()
+
+    plot_titles = ["Uso do bloco "+x for x in blocks_uses]
+    fig = tools.make_subplots(rows=len(blocks_uses), cols=1, subplot_titles=plot_titles)
+
+    for i,block_name in enumerate(blocks_uses):
+        y_data = [0 for i in range(24*7)]
+        for day in blocks_uses[block_name]:
+            for use_room_time in blocks_uses[block_name][day]:
+                block_use = blocks_uses[block_name][day][use_room_time]
+                y_data[(day-1)*24 + (use_room_time-1)] += block_use
+
+        trace_data = go.Bar(
+            x=x_data,
+            y=y_data,
+            name="Salas usadas",
+        )
+        
+        trace_limiar = go.Scatter(
+            x=x_data,
+            y=[blocks_capacities[block_name] for x in range(len(x_data))],
+            name="Capacidade",
+        )
+
+        
+        fig.append_trace(trace_data, i+1, 1)
+        fig.append_trace(trace_limiar, i+1, 1)
+
+        fig['layout']['xaxis'+str(i+1)].update(title='Horários')
+
+        fig['layout']['yaxis'+str(i+1)].update(title='Quantidade de salas utilizadas')
+
+    fig['layout'].update(title='Uso dos blocos por horários. As retas indicam a capacidade máxima de cada bloco.')
+    fig['layout'].update(autosize = True)
+    fig['layout'].update(height=len(blocks_uses)*400)
+    fig['layout'].update(margin=MARGIN_PLOTS)
+
+    plot(fig, filename='capacity_use')
+
+def plot_schedules_by_day(schedules):
+    MIN_TIME = 5
+    days = [["" for x in range(MIN_TIME,24)] for i in WEEK_DAYS]
+    days = [[str(x)+":30" for x in range(MIN_TIME,24)]] + days
+
+    for schedule in schedules:
+        day = schedule["day"]
+        ini = (schedule["ini"] - MIN_TIME) % 24
+        end = (schedule["end"] - MIN_TIME) % 24
+        code= schedule["code"]
+
+        text = code
+        if("suggested" in schedule):
+            text+="<br>Sala sugerida: <b>"+schedule["suggested"]+"</b>"
+
+        for i in range(ini,end):
+            days[day][i]+="<br> <b>"+text+"</b><br>" 
+    
+    trace = go.Table(
+        header=dict(values=["Horários"]+WEEK_DAYS,
+                    fill = dict(color='#C2D4FF'),
+                    align = ['left'] * 5),
+        cells=dict(values=days,
+                fill = dict(color='#F5F8FF'),
+                align = ['left'] * 5),
+                columnwidthsrc = "-PB - Sala sugerida: pm-4 &nbsp-PB - Sala sugerida: pm-4 &nbsp"
+                )
+                
+
+    data = [trace] 
+
+    layout = go.Layout(
+        title="Turmas que não receberam salas. As turmas que possuem ; representam diferentes turmas que foram consideradas aptas a serem juntadas",
+        autosize = True,
+        margin=MARGIN_PLOTS,
+    )
+    fig = go.Figure(data=data, layout=layout)
+    plot(fig, filename = 'not_scheduled')
+
+
+
+def get_rooms_uses(rooms, schedules):
+    rooms_uses = {}
+
+    for room in rooms:
+        room_use = {}
+        for i in range(1,8):
+            room_use[i] = {}
+            for j in range(1,25):
+                room_use[i][j] = None
+        rooms_uses[room["code"]] = room_use
+
+    for schedule in schedules:
+        ini = schedule["ini"]
+        end = schedule["end"]
+        day = schedule["day"]
+        course_code = schedule["code"]
+        assigned = schedule["assigned"]
+
+        for i in range(ini,end):
+            if(assigned in rooms_uses.keys()):
+                rooms_uses[assigned][day][i] = course_code
+
+    return rooms_uses
+
+if __name__ == "__main__":
+    if(len(sys.argv) < 4):
+        print("Fail. Use: \"python3 ensalador_plots.py rooms.yaml schedules.yaml current.yaml")
+        exit()
+    with open(sys.argv[1], 'r') as stream:
+        rooms = yaml.load(stream)["rooms"]
+    with open(sys.argv[2], 'r') as stream:
+        to_schedule = yaml.load(stream)["schedules"]
+    with open(sys.argv[3], 'r') as stream:
+        schedules = yaml.load(stream)["schedules"]
+
+    # Some schedules, like CELIN and Idioma sem fronteiras has no blocks
+    # Then, add empty strings to its objects
+    for x in to_schedule:
+        if(not "block" in x):
+            x["block"] = ""
+    for x in schedules:
+        if(not "block" in x):
+            x["block"] = ""
+    
+    # Filter schedules by banned blocks
+    schedules = [x for x in schedules if len([True for y in BANNED_SCHEDULE_BLOCKS if y in x["block"] ]) == 0 ]
+    to_schedule = [x for x in to_schedule if len([True for y in BANNED_SCHEDULE_BLOCKS if y in x["block"] ]) == 0 ]
+
+    filtered_rooms = [x for x in rooms if len([True for y in BANNED_LIST_ROOMS if y in x["code"] ]) == 0 ]
+    rooms = filtered_rooms
+
+    restrict_rooms = [r for r in rooms if "restrict" in r]
+    not_restrict_rooms = [r for r in rooms if not ("restrict" in r)]
+
+    not_schedules = [x for x in schedules if not "assigned" in x]
+    schedules = [x for x in schedules if "assigned" in x]
+
+    
+
+    blocks_not_restricts = defaultdict(list)
+    blocks = defaultdict(list)
+
+    # Define if is filtered or any rooms
+    for room in rooms:
+        blocks[room["block"]].append(room["code"])
+    for room in not_restrict_rooms:
+        blocks_not_restricts[room["block"]].append(room["code"])
+
+    blocks_capacities = defaultdict(lambda: 0)
+
+    for block in blocks_not_restricts:
+        blocks_capacities[block] = len(blocks_not_restricts[block])
+
+    rooms_uses = get_rooms_uses(not_restrict_rooms,schedules)
+
+    rooms_uses_by_time( rooms_uses )
+    daily_use( rooms_uses, blocks )
+    overflow_block_capacity(rooms_uses, blocks_capacities, blocks)
+
+
+    plot_schedules_by_day(not_schedules)