#!/usr/bin/env python
# coding: utf-8

# In[3]:


# Install prettymaps using pip:
get_ipython().system('pip install prettymaps')


# # prettymaps
# 
# A minimal Python library to draw customized maps from [OpenStreetMap](https://www.openstreetmap.org/#map=12/11.0733/106.3078) created using the [osmnx](https://github.com/gboeing/osmnx), [matplotlib](https://matplotlib.org/), [shapely](https://shapely.readthedocs.io/en/stable/index.html) and [vsketch](https://github.com/abey79/vsketch) packages.
# 
# ![](https://github.com/marceloprates/prettymaps/raw/main/prints/heerhugowaard.png)
# 
# 
# This work is [licensed](LICENSE) under a GNU Affero General Public License v3.0 (you can make commercial use, distribute and modify this project, but must **disclose** the source code with the license and copyright notice)
# 
# ## Note about crediting and NFTs:
# - Please keep the printed message on the figures crediting my repository and OpenStreetMap ([mandatory by their license](https://www.openstreetmap.org/copyright)).
# - I am personally **against** NFTs for their [environmental impact](https://earth.org/nfts-environmental-impact/), the fact that they're a [giant money-laundering pyramid scheme](https://twitter.com/smdiehl/status/1445795667826208770) and the structural incentives they create for [theft](https://twitter.com/NFTtheft) in the open source and generative art communities.
# - **I do not authorize in any way this project to be used for selling NFTs**, although I cannot legally enforce it. **Respect the creator**.
# - The [AeternaCivitas](https://magiceden.io/marketplace/aeterna_civitas) and [geoartnft](https://www.geo-nft.com/) projects have used this work to sell NFTs and refused to credit it. See how they reacted after being exposed: [AeternaCivitas](etc/NFT_theft_AeternaCivitas.jpg), [geoartnft](etc/NFT_theft_geoart.jpg).
# - **I have closed my other generative art projects on Github and won't be sharing new ones as open source to protect me from the NFT community**.
# 
# <a href='https://ko-fi.com/marceloprates_' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
# 
# ## As seen on [Hacker News](https://web.archive.org/web/20210825160918/https://news.ycombinator.com/news):
# ![](https://github.com/marceloprates/prettymaps/raw/main/prints/hackernews-prettymaps.png)
# 
# ## [prettymaps subreddit](https://www.reddit.com/r/prettymaps_/)
# ## [Google Colaboratory Demo](https://colab.research.google.com/github/marceloprates/prettymaps/blob/master/notebooks/examples.ipynb)

# # Installation
# 
# OBS. I'm trying to solve a dependency issue with [vsketch](https://vsketch.readthedocs.io/en/latest/install.html) before publishing prettymaps v0.1.3, so, for now, please install directly from GitHub.

# ### Install locally:
# Install prettymaps with:
# 
# ```
# pip install git+https://github.com/marceloprates/prettymaps
# ```

# ### Install on Google Colaboratory:
# 
# Install prettymaps with:
# 
# ```
# !pip install -e "git+https://github.com/marceloprates/prettymaps#egg=prettymaps"
# ```
# 
# Then **restart the runtime** (Runtime -> Restart Runtime) before importing prettymaps

# # Tutorial

# Plotting with prettymaps is very simple. Run:
# ```python
# prettymaps.plot(your_query)
# ```
# 
# **your_query** can be:
# 1. An address (Example: "Porto Alegre"),
# 2. Latitude / Longitude coordinates (Example: (-30.0324999, -51.2303767))
# 3. A custom boundary in GeoDataFrame format

# In[1]:


import prettymaps

plot = prettymaps.plot('Stad van de Zon, Heerhugowaard, Netherlands')


# You can also choose from different "presets" (parameter combinations saved in JSON files)
# 
# See below an example using the "minimal" preset

# In[2]:


plot = prettymaps.plot(
    'Stad van de Zon, Heerhugowaard, Netherlands',
    preset = 'minimal'
)


# Run
# 
# ```python
# prettymaps.presets()
# ```
# 
# to list all available presets:

# In[3]:


prettymaps.presets()


# To examine a specific preset, run:

# In[4]:


prettymaps.preset('default')


# 
# Insted of using the default configuration you can customize several parameters. The most important are:
# 
# - layers: A dictionary of OpenStreetMap layers to fetch.
#     - Keys: layer names (arbitrary)
#     - Values: dicts representing OpenStreetMap queries
# - style: Matplotlib style parameters
#     - Keys: layer names (the same as before)
#     - Values: dicts representing Matplotlib style parameters
# 
# ```python
# plot = prettymaps.plot(
#     # Your query. Example: "Porto Alegre" or (-30.0324999, -51.2303767) (GPS coords)
#     your_query,
#     # Dict of OpenStreetMap Layers to plot. Example:
#     # {'building': {'tags': {'building': True}}, 'water': {'tags': {'natural': 'water'}}}
#     # Check the /presets folder for more examples
#     layers,
#     # Dict of style parameters for matplotlib. Example:
#     # {'building': {'palette': ['#f00','#0f0','#00f'], 'edge_color': '#333'}}
#     style,
#     # Preset to load. Options include:
#     # ['default', 'minimal', 'macao', 'tijuca']
#     preset,
#     # Save current parameters to a preset file.
#     # Example: "my-preset" will save to "presets/my-preset.json"
#     save_preset,
#     # Whether to update loaded preset with additional provided parameters. Boolean
#     update_preset,
#     # Plot with circular boundary. Boolean
#     circle,
#     # Plot area radius. Float
#     radius,
#     # Dilate the boundary by this amount. Float
#     dilate
# )
# ```
# 
# **plot** is a python dataclass containing:
# 
# ```python
# @dataclass
# class Plot:
#     # A dictionary of GeoDataFrames (one for each plot layer)
#     geodataframes: Dict[str, gp.GeoDataFrame]
#     # A matplotlib figure
#     fig: matplotlib.figure.Figure
#     # A matplotlib axis object
#     ax: matplotlib.axes.Axes
# ```
# 
# Here's an example of running prettymaps.plot() with customized parameters:

# In[5]:


plot = prettymaps.plot(
    'Praça Ferreira do Amaral, Macau',
    circle = True,
    radius = 1100,
    layers = {
        "green": {
            "tags": {
                "landuse": "grass",
                "natural": ["island", "wood"],
                "leisure": "park"
            }
        },
        "forest": {
            "tags": {
                "landuse": "forest"
            }
        },
        "water": {
            "tags": {
                "natural": ["water", "bay"]
            }
        },
        "parking": {
            "tags": {
                "amenity": "parking",
                "highway": "pedestrian",
                "man_made": "pier"
            }
        },
        "streets": {
            "width": {
                "motorway": 5,
                "trunk": 5,
                "primary": 4.5,
                "secondary": 4,
                "tertiary": 3.5,
                "residential": 3,
            }
        },
        "building": {
            "tags": {"building": True},
        },
    },
    style = {
        "background": {
            "fc": "#F2F4CB",
            "ec": "#dadbc1",
            "hatch": "ooo...",
        },
        "perimeter": {
            "fc": "#F2F4CB",
            "ec": "#dadbc1",
            "lw": 0,
            "hatch": "ooo...",
        },
        "green": {
            "fc": "#D0F1BF",
            "ec": "#2F3737",
            "lw": 1,
        },
        "forest": {
            "fc": "#64B96A",
            "ec": "#2F3737",
            "lw": 1,
        },
        "water": {
            "fc": "#a1e3ff",
            "ec": "#2F3737",
            "hatch": "ooo...",
            "hatch_c": "#85c9e6",
            "lw": 1,
        },
        "parking": {
            "fc": "#F2F4CB",
            "ec": "#2F3737",
            "lw": 1,
        },
        "streets": {
            "fc": "#2F3737",
            "ec": "#475657",
            "alpha": 1,
            "lw": 0,
        },
        "building": {
            "palette": [
                "#FFC857",
                "#E9724C",
                "#C5283D"
            ],
            "ec": "#2F3737",
            "lw": 0.5,
        }
    }
)


# In order to plot an entire region and not just a rectangular or circular area, set
# 
# ```python
# radius = False
# ```

# In[6]:


plot = prettymaps.plot(
    'Bom Fim, Porto Alegre, Brasil', radius = False,
)


# You can access layers's GeoDataFrames directly like this:

# In[7]:


# Run prettymaps in show = False mode (we're only interested in obtaining the GeoDataFrames)
plot = prettymaps.plot('Centro Histórico, Porto Alegre', show = False)
plot.geodataframes['building']


# Search a building by name and display it:

# In[8]:


plot.geodataframes['building'][
        plot.geodataframes['building'].name == 'Catedral Metropolitana Nossa Senhora Mãe de Deus'
].geometry[0]


# Plot mosaic of building footprints

# In[9]:


import numpy as np
import osmnx as ox
from matplotlib import pyplot as plt
from matplotlib.font_manager import FontProperties

# Run prettymaps in show = False mode (we're only interested in obtaining the GeoDataFrames)
plot = prettymaps.plot('Porto Alegre', show = False)
# Get list of buildings from plot's geodataframes dict
buildings = plot.geodataframes['building']
# Project from lat / long
buildings = ox.project_gdf(buildings)
buildings = [b for b in buildings.geometry if b.area > 0]

# Draw Matplotlib mosaic of n x n building footprints
n = 6
fig,axes = plt.subplots(n,n, figsize = (7,6))
# Set background color
fig.patch.set_facecolor('#5cc0eb')
# Figure title
fig.suptitle(
    'Buildings of Porto Alegre',
    size = 25,
    color = '#fff'
)
# Draw each building footprint on a separate axis
for ax,building in zip(np.concatenate(axes),buildings):
    ax.plot(*building.exterior.xy, c = '#ffffff')
    ax.autoscale(); ax.axis('off'); ax.axis('equal')


# Access plot.ax or plot.fig to add new elements to the matplotlib plot: 

# In[10]:


from matplotlib.font_manager import FontProperties

plot = prettymaps.plot(
    (41.39491,2.17557),
    preset = 'barcelona',
)

# Change background color
plot.fig.patch.set_facecolor('#F2F4CB')
# Add title
plot.ax.set_title(
    'Barcelona',
    size = 50
)

plt.show()


# Use **plotter** mode to export a pen plotter-compatible SVG (thanks to abey79's amazing [vsketch](https://github.com/abey79/vsketch) library)

# In[11]:


plot = prettymaps.plot(
    (41.39491,2.17557),
    mode = 'plotter',
    layers = dict(perimeter = {}),
    preset = 'barcelona-plotter',
    scale_x = .6,
    scale_y = -.6,
)


# Some other examples

# In[12]:


plot = prettymaps.plot(
    # City name
    'Barra da Tijuca',
    dilate = 0,
    figsize = (22,10),
    preset = 'tijuca',
)


# In[13]:


plot = prettymaps.plot(
    'Stad van de Zon, Heerhugowaard, Netherlands',
    preset = 'heerhugowaard',
)


# Use prettymaps.create_preset() to create a preset:

# In[14]:


prettymaps.create_preset(
    "my-preset",
    layers = {
        "building": {
            "tags": {
                "building": True,
                "leisure": [
                    "track",
                    "pitch"
                ]
            }
        },
        "streets": {
            "width": {
                "trunk": 6,
                "primary": 6,
                "secondary": 5,
                "tertiary": 4,
                "residential": 3.5,
                "pedestrian": 3,
                "footway": 3,
                "path": 3
            }
        },
    },
    style = {
        "perimeter": {
            "fill": False,
            "lw": 0,
            "zorder": 0
        },
        "streets": {
            "fc": "#F1E6D0",
            "ec": "#2F3737",
            "lw": 1.5,
            "zorder": 3
        },
        "building": {
            "palette": [
                "#fff"
            ],
            "ec": "#2F3737",
            "lw": 1,
            "zorder": 4
        }
    }
)

prettymaps.preset('my-preset')


# Use prettymaps.delete_preset() to delete presets:

# In[15]:


# Show presets before deletion
print('Before deletion:')
display(prettymaps.presets())
# Delete 'my-preset'
prettymaps.delete_preset('my-preset')
# Show presets after deletion
print('After deletion:')
display(prettymaps.presets())


# Use **prettymaps.multiplot** and **prettymaps.Subplot** to draw multiple regions on the same canvas

# In[16]:


# Draw several regions on the same canvas
prettymaps.multiplot(
    prettymaps.Subplot(
        'Cidade Baixa, Porto Alegre',
        style={'building': {'palette': ['#49392C', '#E1F2FE', '#98D2EB']}}
    ),
    prettymaps.Subplot(
        'Bom Fim, Porto Alegre',
        style={'building': {'palette': ['#BA2D0B', '#D5F2E3', '#73BA9B', '#F79D5C']}}
    ),
    prettymaps.Subplot(
        'Farroupilha, Porto Alegre',
        style={'building': {'palette': ['#EEE4E1', '#E7D8C9', '#E6BEAE']}}
    ),
    # Load a global preset
    preset='cb-bf-f',
    # Figure size
    figsize=(12, 12)
)