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

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get_ipython().run_line_magic('matplotlib', 'inline')
from datetime import timedelta, datetime
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import matplotlib

from matplotlib.animation import FuncAnimation
import matplotlib.animation as animation

from IPython.display import HTML

import cartopy
import cartopy.crs as ccrs
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import matplotlib.ticker as mticker
import cartopy.feature as cfeature


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get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')
get_ipython().run_line_magic('load_ext', 'version_information')
get_ipython().run_line_magic('version_information', 'numpy, matplotlib, xarray, cartopy')


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rootdir = "/Users/Gomez023/src/git/"


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filedir = "parcels_gallery/data/"

ds_subregion = xr.open_dataset(rootdir + filedir + 'Particle_AZO_grid100000p_wtides_0601_hourly_MONTH_subregion.nc')


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ds_subregion


# # Simulation:

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outputdt = timedelta(hours=1)
timerange = np.arange(np.nanmin(ds_subregion['time'].values),
                      (np.datetime64('2010-06-29T00:30:00.000000000'))+np.timedelta64(outputdt), 
                      outputdt)  # timerange in nanoseconds


# # Just tidal:

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get_ipython().run_cell_magic('capture', '', "\nfig = plt.figure(figsize=(12, 8))#, constrained_layout=True)\n\nax1 = plt.subplot(111, projection=ccrs.PlateCarree())\n\nax1.set_xlim([-32, -18])\nax1.set_ylim([30, 40])\n\nresol = '10m'  # use data at this scale\nland = cartopy.feature.NaturalEarthFeature('physical', 'land', \\\n    scale=resol, edgecolor='k', facecolor=cfeature.COLORS['land'])\nocean = cartopy.feature.NaturalEarthFeature('physical', 'ocean', \\\n    scale=resol, edgecolor='none', facecolor=cfeature.COLORS['water'])\n\nax1.add_feature(land, facecolor='burlywood', zorder=50) #beige\nax1.add_feature(ocean, linewidth=0.2 )\n\ngl = ax1.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,\n                  linewidth=2, color='gray', alpha=0.5, linestyle='-')\ngl.xlabels_top = False\ngl.ylabels_right = False\ngl.xlines = False\ngl.ylines = False\ngl.xlocator = mticker.FixedLocator([-35, -30., -25., -20.])\ngl.ylocator = mticker.FixedLocator([30., 33., 36., 39.]) #np.arange(30., 42, 3)\ngl.xformatter = LONGITUDE_FORMATTER\ngl.yformatter = LATITUDE_FORMATTER\ngl.ylabel_style = {'size': 12}#, 'color': 'gray'}\ngl.xlabel_style = {'size': 12}\n\n\ntime_id = np.where(ds_subregion['time'] == timerange[0]) # Indices of the data where time = 0\n\nscatter_subregion = ax1.scatter(ds_subregion['lon'].values[time_id], ds_subregion['lat'].values[time_id], s=1, c='r', transform=ccrs.PlateCarree(), zorder=20)\n\nt = str(timerange[0]) \ntitle = plt.suptitle('Particles at t = ' + str(t[0:10]) + ' ' + str(t[11:16]), size=24)\n\ndef animate(i):\n    t = str(timerange[i])\n    title.set_text('Particles at t = ' + str(t[0:10]) + ' ' + str(t[11:16]))\n    \n    time_id = np.where(ds_subregion['time'] == timerange[i])\n    scatter_subregion.set_offsets(np.c_[ds_subregion['lon'].values[time_id], ds_subregion['lat'].values[time_id]])\n\nax1.set_title('Tidal', size=20)\n\nanim = FuncAnimation(fig, animate, frames = len(timerange), interval=500)\n")


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# Set up formatting for the movie files
Writer = animation.writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)

anim.save(rootdir + 'parcels_gallery/images/anim_June_s1_TIDAL_all_subregion.mp4', writer=writer, dpi=500)


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pwd


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