Make edits to the docs to handle the lowercaseness of cdtools now

This commit is contained in:
Abe Levitan
2022-06-08 13:30:49 -07:00
parent 672096085b
commit 858d8f3b2a
5 changed files with 19 additions and 15 deletions
+1 -1
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@@ -24,6 +24,6 @@ model.compare(dataset) # See how the simulated and measured patterns compare
plt.show()
```
Full installation instructions and documentation can be found [here](https://github.mit.edu/pages/Scattering/CDTools/).
Full installation instructions and documentation can be found [here](https://github.mit.edu/pages/Scattering/cdtools/).
Have a wonderful day!
+1 -1
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@@ -71,7 +71,7 @@ master_doc = 'index'
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
language = 'en'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
+2
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@@ -1,3 +1,5 @@
:orphan:
.. toctree::
:maxdepth: 1
+9 -9
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@@ -13,7 +13,7 @@ Our first step will be creating the file and filling out the boilerplate: All th
.. code-block:: python
import CDTools
import cdtools
from matplotlib import pyplot as plt
from scipy import io
@@ -24,7 +24,7 @@ You can always import more libraries, like numpy, or pytorch, or pandas, or what
.. code-block:: python
filename = 'example_data/lab_ptycho_data.cxi'
dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
dataset = cdtools.datasets.Ptycho2DDataset.from_cxi(filename)
dataset.inspect()
plt.show()
@@ -35,7 +35,7 @@ Now that we know we have the data loaded and it looks good, we can go ahead and
.. code-block:: python
model = CDTools.models.FancyPtycho.from_dataset(dataset)
model = cdtools.models.FancyPtycho.from_dataset(dataset)
model.to(device='cuda')
dataset.get_as(device='cuda')
@@ -62,7 +62,7 @@ Once we run this, we can take a look at the result. What we see is pretty good,
.. code-block:: python
model = CDTools.models.FancyPtycho.from_dataset(dataset, oversampling=2)
model = cdtools.models.FancyPtycho.from_dataset(dataset, oversampling=2)
And secondly, we note that there don't seem to be any errors with the positioning. So we can just not reconstruct the probe positions, knowing that the initial guesses are already accurate enough. We can do this by writing the following line, just before we run the reconstruction for loop.
@@ -77,7 +77,7 @@ After running this reconstruction, we can see that we're getting a little improv
.. code-block:: python
model = CDTools.models.FancyPtycho.from_dataset(dataset, oversampling=2,
model = cdtools.models.FancyPtycho.from_dataset(dataset, oversampling=2,
probe_support_radius=90)
@@ -129,8 +129,8 @@ We can start with the basic skeleton for this file. In addition to our standard
import numpy as np
import torch as t
from matplotlib import pyplot as plt
from CDTools.datasets import CDataset
from CDTools.tools import data as cdtdata
from cdtools.datasets import CDataset
from cdtools.tools import data as cdtdata
__all__ = ['BasicPtychoDataset']
@@ -288,8 +288,8 @@ Once again, we start with the basic skeleton
import numpy as np
import torch as t
from CDTools.models import CDIModel
from CDTools import tools
from cdtools.models import CDIModel
from cdtools import tools
__all__ = ['SimplePtycho']
+6 -4
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@@ -10,10 +10,7 @@ implemented by default in pytorch (such as drawing data in a random order,
drawing minibatches, etc.)
New Datasets can be defined a subclass of the main CDataset class defined
in the base.py file. Example implementations of all these functions
can be found in the code for the Ptycho2DDataset class. In addition, it is
recommended to read through the tutorial section on defining a new CDI
dataset before attempting to do so
in the base.py file, and should define the following functions:
* __init__
* __len__
@@ -23,6 +20,11 @@ dataset before attempting to do so
* to_cxi
* inspect
Example implementations of all these functions can be found in the code
for the Ptycho2DDataset class. In addition, it is recommended to read
through the tutorial section on defining a new CDI dataset before
attempting to do so
"""
# I don't believe that __all__ really needed, but it's nice to define it