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

# # New Zealand DEM remake
# 
# See the original notebook [here](https://nbviewer.org/github/royalosyin/Work-with-DEM-data-using-Python-from-Simple-to-Complicated/blob/master/Sup03-Ridgelines%20Map%20of%20DEM.ipynb).

# In[1]:


import pandas as pd

from lets_plot import *


# In[2]:


LetsPlot.setup_html()


# In[3]:


def dataset_array_to_dataframe(dataset_array):
    df = pd.DataFrame.from_records([
        (j, i, a)
        for i, r in enumerate(dataset_array)
        for j, a in enumerate(r)
    ], columns=["x", "y", "h"])
    return df


# In[4]:


raw_data_array = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/new_zealand.csv", header=None).to_numpy()
df = dataset_array_to_dataframe(raw_data_array)
df = df[df.h > 0]
print(df.shape)
df.head()


# In[5]:


ggplot(df) + \
    geom_area_ridges(aes("x", "y", height="h"), \
                     stat='identity', scale=.002, \
                     color="#08519c", fill="#bdd7e7",
                     sampling=sampling_pick(df.shape[0]), \
                     tooltips='none') + \
    geom_text(x=140, y=65, label="New Zealand", size=20, family="Cinzel") + \
    scale_y_continuous(trans='reverse') + \
    ggsize(600, 600) + \
    theme_minimal() + theme(axis='blank', panel_grid='blank', \
                            plot_background=element_rect(color='black', fill='#e6e6e6', size=1))