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

# # DataArray - Dfs123 plotting
# 
# A DataArray with gridded data, can be plotted in many different ways.

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import matplotlib.pyplot as plt
import mikeio


# ## Dfs1

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ds = mikeio.read("../tests/testdata/vu_tide_hourly.dfs1")
ds = ds.rename({"Tidal current component (geographic East)":"Tidal current u-comp"})
da = ds["Tidal current u-comp"]
da


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da.geometry


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da[0:10:2].plot();


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da[0:10:2].plot.line()
plt.legend(da.time[0:10:2]);


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# plot all points on line as time series
da.plot.timeseries();


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# first 48 hours...  
da[:49].plot.pcolormesh();


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# single point on line as timeseries
da.sel(x=0.5).sel(time=slice("2021-08-01","2021-08-03")).plot();


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# all data as histogram
da.plot.hist(bins=40);


# ## Dfs2

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da = mikeio.read("../tests/testdata/gebco_sound.dfs2")[0]
da


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da.geometry


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da.plot(figsize=(10,6));


# It is also possible to customize the labels of the axes as well as the color bar, e.g. for localized adaption.

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da.plot.contourf(figsize=(10,6), levels=4, label="Højde (m)")
plt.xlabel("Længdekreds (°)")
plt.ylabel("Breddekreds (°)")


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ax = da.plot.contour(figsize=(8,8), cmap="plasma")
ax.set_xlim([12.5, 12.9])
ax.set_ylim([55.8, 56]);


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da.plot.hist(bins=20);


# ## Dfs3

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fn = "../tests/testdata/test_dfs3.dfs3"
dfs = mikeio.open(fn)
dfs


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dfs.geometry


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ds=dfs.read()
ds


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ds.Temperature.plot();


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ax = ds.Temperature[:,0,:,:].plot.contourf()
ax.grid()


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ds.Temperature[:,0,:,0].plot();


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ds=dfs.read(layers=0)
ds


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ds.Temperature.plot();


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