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

# # Res1D - Strategies for handling large files

# In[1]:


import mikeio1d


# All static network data is loaded into memory by default. Dynamic result data is only loaded when required.

# In[2]:


res = mikeio1d.open("../tests/testdata/network.res1d")
loaded_time_steps = res.data.NumberOfTimeSteps
loaded_time_steps


# Calling read() loads dynamic data for the entire network.

# In[3]:


res.read()
loaded_time_steps = res.data.NumberOfTimeSteps
loaded_time_steps


# All network dynamic data is loaded into memory regardless of how read() is called. In the future, it would nice to make this work lazily.

# In[4]:


res = mikeio1d.open("../tests/testdata/network.res1d")
# this still reads all network data, but only creates a DataFrame with the requested data
res.nodes["1"].WaterLevel.read().head()


# To avoid loading the entire network's dynamic data into memory, you can specify which IDs to load when opening the file.

# In[5]:


res = mikeio1d.open("../tests/testdata/network.res1d", nodes=["1"], reaches=["100l1"])
res.nodes


# In[6]:


res.reaches


# In[7]:


res.read()


# Similarly, you can also specify the time range to read.

# In[8]:


start, end = "1994-08-07 18:30:07.967", "1994-08-07 18:33:07.967"
res = mikeio1d.open(
    "../tests/testdata/network.res1d", nodes=["1"], reaches=["100l1"], time=(start, end)
)
loaded_time_steps = res.data.NumberOfTimeSteps
loaded_time_steps


# In[9]:


res.read()
loaded_time_steps = res.data.NumberOfTimeSteps
loaded_time_steps


# In[10]:


res.read().head()


# It's also possible to load every 'nth' time step with the 'step_every' parameter.

# In[42]:


# First plot the full time series for a comparison
res = mikeio1d.open(
    "../tests/testdata/network.res1d", reaches=["100l1"]
)
ax = res.reaches['100l1'][0].WaterLevel.plot(linestyle='-', marker='x')

# Then plot with every 5th time step

res = mikeio1d.open(
    "../tests/testdata/network.res1d", reaches=["100l1"], step_every=5,
)
ax = res.reaches['100l1'][0].WaterLevel.plot(ax=ax, linestyle='--', marker='o', color='g')

ax.legend(["all steps", "step_every=5"])
ax.set_xlim("1994-08-07 17:15", "1994-08-07 17:50")


# In[43]:


res.data.NumberOfTimeSteps


# Lastly you can also specify which quantities to include.

# In[45]:


res = mikeio1d.open(
    "../tests/testdata/network.res1d", nodes=["1"], reaches=["100l1"], step_every=10, quantities=["Discharge"]
)
res.read()