#%% [markdown]
# # Visualization of WMS layers
# 
# If we work with trajectory data, we often want to visualize information from a
# so called <em>birds eye view</em> on some digital layers, such as ortophotos.
# Typically, those layers are provided by some Web Map Service (WMS). `tasi` is
# equipped with classes that allows to query such WMS servers and visualize
# them. 
#
# To achieve this, we extend the
# [tilemapbase](https://github.com/MatthewDaws/TileMapBase) library to also
# support other WMS servers than [OSM](https://www.openstreetmap.org). In the
# following, we demonstrate how to visualize a orthophoto of the DLR AIM
# Research intersection where the [DLR Urban Traffic
# Dataset](https://zenodo.org/records/14025010) was collected.  
#
# ## Tiles and Plotter
# 
# In `tilemapbase`, visualization of images provided by a WMS server is managed
# by two entities, a `Tile` and a `Plotter`. The `Tile` is the interface to the
# WMS server and, originally, requires a center position and a zoom level since
# this is the interface by [OSM](https://www.openstreetmap.org). In `tasi` a
# customized version is available that allows to query WMS servers that
# requires to specify a boundingbox using a 2-point definition (boundingbox tile). 
#
# In `tasi` there is already a custom `Tile`, the `LowerSaxonyOrthophotoTile`
# that provides access to the  orthophoto of Lower Saxony which is provided by
# the [Landesamt für Geoinformation und Landesvermessung
# Niedersachsen](https://ni-lgln-opengeodata.hub.arcgis.com/). 
#
# Since in `tilemapbase`, the interface to the WMS server requires to specify a
# center position and a zoom level, we have to adapt the original `Plotter`
# since it would not work with a boundingbox tile. In `tasi`, the
# `BoundingboxPlotter` is available that is a custom plotter that works with
# these tiles.
#%%
from tasi.plotting import LowerSaxonyOrthophotoTile, BoundingboxPlotter

#%% [markdown]
# ## Plotting using Matplotlib
# 
# To visualize a layer from a WMS server, `tilemapbase` uses `matplotlib`. Thus,
# let's create an `Figure` and `Axes` where we want to visualize the layer.
# Furthermore, we need to specify the extend of the region that we want to
# visualize.  
#%%
import matplotlib.pyplot as plt 
import numpy as np 

f, ax = plt.subplots(figsize=(8, 8))

roi = np.array([604725, 5792760, 604810, 5792830]).reshape(-1, 2)

plotter = BoundingboxPlotter(roi, LowerSaxonyOrthophotoTile())
plotter.plot(ax)
#%% [markdown]
# The location of the attribution changes based on the shape of the region of
# interest, while the font size is fixed. You can change via the
# `attribution_kwargs` argument.
# %%

f, ax = plt.subplots(figsize=(8, 8))

plotter.plot(ax, attribution_kwargs={'fontsize' : 12})
#%% [markdown]
# That's it for now but there is more to come. We plan to add several other
# tile variants that provide access to various WMS servers. If you want to add
# your own WMS server, have a look into the definition of the
# `LowerSaxonyOrthophotoTile` tile. Adding a new `Tile` is straightforward 😉.