Add a completion visualization

estimage/visualize/completion.py

@@ -0,0 +1,64 @@
+import typing
+import datetime
+
+import numpy as np
+
+from . import utils
+from .. import utilities
+
+
+class MPLCompletionPlot:
+    width = 2
+
+    def __init__(self, todo_estimation, perweek_velocity_mean_std):
+        dom, pdf = todo_estimation.divide_by_gauss_pdf(200, * perweek_velocity_mean_std)
+        self.distribution = utilities.get_random_variable(dom, pdf)
+        DAYS_IN_WEEK = 7
+        lower_bound = self.distribution.ppf(0.02)
+        upper_bound = self.distribution.ppf(0.98)
+        self.dom = np.arange(
+                int(np.floor(lower_bound * DAYS_IN_WEEK)),
+                int(np.ceil(upper_bound * DAYS_IN_WEEK)) + 1)
+        self.probs = self.distribution.cdf(self.dom / DAYS_IN_WEEK)
+        self.probs -= self.probs[0]
+        self.probs /= self.probs[-1]
+        self.probs *= 100
+
+    def _calculate_plan_wrt_day(self, ax, start):
+        ax.plot(self.dom, self.probs, color="green",
+                linewidth=self.width, label="prob of completion")
+        utils.x_axis_weeks_and_months(ax, start, start + utils.ONE_DAY * self.dom[-1])
+
+    def get_figure(self):
+        plt = utils.get_standard_pyplot()
+
+        fig, ax = plt.subplots()
+        ax.grid(True)
+
+        self._calculate_plan_wrt_day(ax, datetime.datetime.today())
+        ax.legend(loc="upper left")
+
+        ax.set_ylabel("percents")
+
+        return fig
+
+    def get_small_figure(self):
+        plt = utils.get_standard_pyplot()
+
+        fig, ax = plt.subplots()
+
+        self._prepare_plots()
+        self._plot_prepared_arrays(ax)
+        self._show_plan(ax)
+        self._show_today(ax)
+
+        ax.set_axis_off()
+        fig.subplots_adjust(0, 0, 1, 1)
+
+        return fig
+
+    def plot_stuff(self):
+        plt = utils.get_standard_pyplot()
+        self.get_figure()
+
+        plt.show()

estimage/visualize/utils.py

@@ -29,10 +29,10 @@ def x_axis_weeks_and_months(ax, start, end):
     ax.set_xlabel("time / weeks")
 
 
-def set_week_ticks_to_mondays(ticks, start, end):
-    week_index = 0
+def set_week_ticks_to_mondays(ticks, start, end, week_index_start=0):
+    week_index = week_index_start
     if start.weekday != 0:
-        week_index = 1
+        week_index = week_index_start + 1
     for day in range((end - start).days + 1):
         if (start + day * ONE_DAY).weekday() == 0:
             ticks[day] = str(week_index)

estimage/webapp/vis/routes.py

@@ -4,13 +4,14 @@
 
 import flask
 import flask_login
+import numpy as np
 
 from . import bp
 from .. import web_utils
 from ... import utilities
 from ... import simpledata as webdata
 from ... import history
-from ...visualize import utils, velocity, burndown, pert
+from ...visualize import utils, velocity, burndown, pert, completion
 
 import matplotlib
 
@@ -52,6 +53,38 @@ def get_pert_in_figure(estimation, task_name):
     return fig
 
 
+@bp.route('/completion.svg')
+@flask_login.login_required
+def visualize_completion():
+    user = flask_login.current_user
+    user_id = user.get_id()
+    all_events = webdata.EventManager()
+    all_events.load()
+
+    all_targets_by_id, model = web_utils.get_all_tasks_by_id_and_user_model("retro", user_id)
+    all_targets = list(all_targets_by_id.values())
+    targets_tree_without_duplicates = utilities.reduce_subsets_from_sets([t for t in all_targets if t.tier == 0])
+    model = web_utils.get_user_model(user_id, targets_tree_without_duplicates)
+    todo = model.remaining_point_estimate
+
+    start, end = flask.current_app.config["RETROSPECTIVE_PERIOD"]
+    aggregation = history.Aggregation.from_targets(targets_tree_without_duplicates, start, end)
+    aggregation.process_event_manager(all_events)
+
+    velocity_array = aggregation.get_velocity_array()
+    velocity_array = velocity_array[velocity_array > 0] * 7
+    velocity_mean = velocity_array.mean()
+    velocity_array = np.convolve(velocity_array, np.ones(7) / 7, "same")
+    velocity_stdev = velocity_array.var()**0.5
+
+    matplotlib.use("svg")
+    print(f"{velocity_mean=}, {velocity_stdev=}")
+    print(f"{velocity_array=}")
+    fig = completion.MPLCompletionPlot(todo, (velocity_mean, velocity_stdev)).get_figure()
+    fig.set_size_inches(* NORMAL_FIGURE_SIZE)
+    return send_figure_as_svg(fig, "completion.svg")
+
+
 @bp.route('/<epic_name>-velocity.svg')
 @flask_login.login_required
 def visualize_velocity(epic_name):