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

# # Combining Datasets
# 
# Datasets can be combined along the items and time axis

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import matplotlib.pyplot as plt
import mikeio


# ## Concatenate Datasets (along the time axis)

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ds1 = mikeio.read("../tests/testdata/tide1.dfs1")
ds1


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ds2 = mikeio.read("../tests/testdata/tide2.dfs1") + 0.5  # add offset
ds2


# Concatenating data along the time axis can be done with `Dataset.concat`

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ds3 = mikeio.Dataset.concat([ds1, ds2])
ds3


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plt.plot(ds1.time, ds1[0].to_numpy()[:,1], 'ro', label="Dataset 1")
plt.plot(ds2.time, ds2[0].to_numpy()[:,1], 'k+', label="Dataset 2")
plt.plot(ds3.time, ds3[0].to_numpy()[:,1], 'g-', label="Dataset 3")
plt.title("Notice the offset...")
plt.legend();


# ## Merging datasets

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dsA = mikeio.read("../tests/testdata/tide1.dfs1")
dsA


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dsB = dsA.copy()
dsB = dsB.rename({"Level":"Other_level"})
dsB = dsB + 2
dsB


# Merge datasets with different items can be done like this:

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dsC = mikeio.Dataset.merge([dsA, dsB])
dsC


# Which in this simple case with a single item in each dataset is equivalent to:

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daA = dsA[0]
daA


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daB = dsB[0]
daB


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mikeio.Dataset([daA, daB])


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