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

# # PFS 
# 
# The support for PFS files have been extended with MIKE IO release 1.2. It was previously only possible to *read* PFS files. It is now also possible to *modify* and *create* new PFS files. 

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import mikeio


# ## Read

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pfs = mikeio.read_pfs("../tests/testdata/pfs/lake.sw")
pfs


# The "target" (root section) is in this case called FemEngineSW. `pfs.FemEngineSW` is a PfsSection object that contains other PfsSection objects. Let's print the names of it's subsections:

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pfs.FemEngineSW.keys()


# It is possible to navigate to each section and keyword in the pfs file:

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pfs.FemEngineSW.DOMAIN.file_name


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pfs.FemEngineSW.MODULE_SELECTION


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pfs.FemEngineSW.MODULE_SELECTION.mode_of_spectral_wave_module


# If you are unsure the name of a section, it is also possible to search for a specific string in the file, to find the name of a specific section.
# 
# In the example below we do an case-insensitive search for the string 'charnock', which occurs at 6 different places in this file.

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pfs.search("charnock")


# The same search can be done at any level of the hierarchy, i.e. to search only within the OUTPUTS section:

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pfs.FemEngineSW.SPECTRAL_WAVE_MODULE.OUTPUTS.search("charnock")


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pfs.FemEngineSW.SPECTRAL_WAVE_MODULE.WIND.search("charnock")


# MIKE FM PFS files has a specific structure and active FM modules can be accessed by an alias on the Pfs object. In this case, `pfs.SW` can be used as a short-hand for `pfs.FemEngineSW.SPECTRAL_WAVE_MODULE`.

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pfs.SW.SPECTRAL.number_of_directions


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pfs.SW.SPECTRAL.maximum_threshold_frequency


# Enumerated sections (e.g. [OUTPUT_1], [OUTPUT_2], ...) can be outputted in tabular form (dataframe).

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df = pfs.SW.OUTPUTS.to_dataframe()
df


# ## Modify
# 
# The PfsSection object can be modified. Existing values can be changes, new key-value pairs can be added, subsections can added or removed. 

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pfs.SW.SPECTRAL.number_of_directions = 32


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pfs.SW.SPECTRAL


# ### Add a new keyword

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pfs.SW.SPECTRAL["new_keyword"] = "new_value"


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pfs.SW.SPECTRAL


# ### Add a section
# 
# Let's create an additional output, by copying OUTPUT_4 and modifying some parameters.

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pfs.SW.OUTPUTS.number_of_outputs += 1


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new_output = pfs.SW.OUTPUTS.OUTPUT_4.copy()


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new_output.file_name = 'spectrum_x10km_y40km.dfsu'
new_output.POINT_1.x = 10000
new_output.POINT_1.y = 40000


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pfs.SW.OUTPUTS["OUTPUT_5"] = new_output


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pfs.SW.OUTPUTS.keys()


# ## Output
# 
# The Pfs object can be written to pfs file, but can also be exported to a dictionary (which in turn can be written to a yaml or json file).

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pfs.write("lake_modified.pfs")


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pfs.to_dict()


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# write to yaml file
import yaml
yaml.dump(pfs.to_dict(), open('lake_modified.yaml', 'w+'))


# ## Create
# 
# A PFS file can also be created from a dictionary, like this:

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setup = {
    "Name": "Extract that",
    "InputFileName": "|random.dfs1|",
    "FirstTimeStep": 0,
    "LastTimeStep": 99,
    "X": 2,
    "OutputFileName": "|.\\out2.dfs0|",
}
t1_t0 = {"CLSID": "t1_t0.dll", "TypeName": "t1_t0", "Setup": setup}
t1_t0


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pfs = mikeio.PfsDocument({"t1_t0": t1_t0})
pfs


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pfs.write("extract_point.mzt")


# ## Clean up

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import os
os.remove("lake_modified.pfs")
os.remove('lake_modified.yaml')
os.remove("extract_point.mzt")