matplotlib annotate explain

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches


fig, axs = plt.subplots(2, 2)
x1, y1 = 0.3, 0.3
x2, y2 = 0.7, 0.7

ax = axs.flat[0]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",
            xy=(x1, y1), xycoords='data',
            xytext=(x2, y2), textcoords='data',
            arrowprops=dict(arrowstyle="-",
                            color="0.5",
                            patchB=None,
                            shrinkB=0,
                            connectionstyle="arc3,rad=0.3",
                            ),
            )
ax.text(.05, .95, "connect", transform=ax.transAxes, ha="left", va="top")

ax = axs.flat[1]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",
            xy=(x1, y1), xycoords='data',
            xytext=(x2, y2), textcoords='data',
            arrowprops=dict(arrowstyle="-",
                            color="0.5",
                            patchB=el,
                            shrinkB=0,
                            connectionstyle="arc3,rad=0.3",
                            ),
            )
ax.text(.05, .95, "clip", transform=ax.transAxes, ha="left", va="top")

ax = axs.flat[2]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",
            xy=(x1, y1), xycoords='data',
            xytext=(x2, y2), textcoords='data',
            arrowprops=dict(arrowstyle="-",
                            color="0.5",
                            patchB=el,
                            shrinkB=5,
                            connectionstyle="arc3,rad=0.3",
                            ),
            )
ax.text(.05, .95, "shrink", transform=ax.transAxes, ha="left", va="top")

ax = axs.flat[3]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",
            xy=(x1, y1), xycoords='data',
            xytext=(x2, y2), textcoords='data',
            arrowprops=dict(arrowstyle="fancy",
                            color="0.5",
                            patchB=el,
                            shrinkB=5,
                            connectionstyle="arc3,rad=0.3",
                            ),
            )
ax.text(.05, .95, "mutate", transform=ax.transAxes, ha="left", va="top")

for ax in axs.flat:
    ax.set(xlim=(0, 1), ylim=(0, 1), xticks=[], yticks=[], aspect=1)

plt.show()

matplotlib anchored box04

from matplotlib.patches import Ellipse import matplotlib.pyplot as plt from matplotlib.offsetbox import (AnchoredOffsetbox, DrawingArea, HPacker, TextArea)

sanic request stream

from sanic import Sanic from sanic.blueprints import Blueprint from sanic.response import stream, text from sanic.views import HTTPMethodView from sanic.views import stream as stream_decorator

amending request object

from random import randint from sanic import Sanic from sanic.response import text app = Sanic("Example")

authorized sanic

# -*- coding: utf-8 -*- from functools import wraps from sanic import Sanic from sanic.response import json

sanic blueprints

from sanic import Blueprint, Sanic from sanic.response import file, json app = Sanic("Example") blueprint = Blueprint("bp_example", url_prefix="/my_blueprint") blueprint2 = Blueprint("bp_example2", url_prefix="/my_blueprint2")

fastapi request directly

from fastapi import FastAPI, Request app = FastAPI() @app.get("/items/{item_id}") def read_root(item_id: str, request: Request):

fastapi websockets

from fastapi import FastAPI, WebSocket from fastapi.responses import HTMLResponse app = FastAPI()

simple fastapi wsgi

from fastapi import FastAPI from fastapi.middleware.wsgi import WSGIMiddleware from flask import Flask, escape, request

matplotlib multicursor

Showing a cursor on multiple plots simultaneously. This example generates three axes split over two different figures.  On hovering the cursor over data in one subplot, the values of that datapoint are shown in all axes

polygon selector

import matplotlib.pyplot as plt from matplotlib.widgets import PolygonSelector # To create the polygon programmatically fig, ax = plt.subplots() fig.show() selector = PolygonSelector(ax, lambda *args: None)