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

# # Lucid local development notebook
# 
# This notebook allows you to use your development version of the lucid codebase.
# It is meant to only be used during development of lucid, not when using it.
# 
# Instead, see "usage_example.ipynb" in this folder for an example of how to use lucid in a notebook.

# ## Setup
# 
# ### Add local package to search path

# In[5]:


import os
import sys

module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path:
    sys.path.append(module_path)


# Now we should be able to import it directly, just like if we installed it using `pip`:
# 
# ```python
# import lucid
# ```
# 
# However, we will use `autoreload` so we can quickly iterate on local code changes:
# 
# ### Enable autoreload

# In[6]:


get_ipython().run_line_magic('load_ext', 'autoreload')


# In[7]:


get_ipython().run_line_magic('aimport', 'lucid')
get_ipython().run_line_magic('aimport', '-tensorflow')
get_ipython().run_line_magic('aimport', '-numpy')
get_ipython().run_line_magic('aimport', '-sklearn')


# In[8]:


get_ipython().run_line_magic('aimport', '')


# Let's check that we're actually seeing the local version, not a package installed in site-packages.
# Th next cell should show the path at which you cloned the lucid repo, not a system path:

# In[9]:


module_path = lucid.__path__[0]
print("Lucid was loaded from {}.".format(module_path))
assert os.path.abspath("..") in module_path
del module_path


# ## Example usage

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import numpy as np


# In[7]:


image = np.random.normal(loc=.5, scale=.1, size=(200,200))


# In[15]:


# this is how you set log levels globally:

import logging
logging.getLogger('lucid').setLevel(logging.DEBUG)

# or per module:
# logging.getLogger('lucid.misc.io').setLevel(logging.INFO)


# In[16]:


get_ipython().run_line_magic('autoreload', '')

from lucid.misc.io import load, save, show

image = load('../tests/fixtures/noise.jpeg')

print(image.dtype)
show(image)


# In[10]:


get_ipython().run_line_magic('autoreload', '')

array = load("../tests/fixtures/noise.jpeg")
print(array.dtype, array.shape)
show(array, domain=None)
array


# In[11]:


show(load("https://www.google.com/images/branding/googlelogo/2x/googlelogo_color_272x92dp.png"))


# ## Optvis Usage

# In[12]:


from lucid.optvis import objectives, param, transform, render
from lucid.modelzoo.vision_models import InceptionV1


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model = InceptionV1()
model.load_graphdef()


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_ = render.render_vis(model, "mixed3b_pre_relu:470", thresholds=(32, 256, 1024))


# In[12]:


import os
repr(os.urandom(16))


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import numpy as np
from lucid.misc.channel_reducer import ChannelReducer


# In[98]:


array = np.zeros((100,100,10), dtype=np.float32)
for d in range(array.shape[-1]):
    array[:,:,d] = np.eye(100,100)


# In[104]:


array += 0.1 * np.random.uniform(size=array.shape)


# In[106]:


reducer = ChannelReducer(3, reduction_alg='PCA')


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reducer.fit(array)


# In[108]:


reducer._reducer.components_


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reduced = reducer.transform(array)


# In[110]:


show(np.dsplit(reduced, reduced.shape[-1]))


# In[105]:


from lucid.misc.io import load, save, show

show(np.dsplit(array, array.shape[-1]))