André F. Rendeiro afrendeiro

## quantization_experiments.py
"""
Run the experiments for the quantization speedup and plot results.
"""

import subprocess

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

## fix_indica_tiff.py
"""
Convert a TIFF file generated by IndicaLabs (HALO) to a usable TIFF file.
"""

import typing as tp
from pathlib import Path
from xml.etree import ElementTree

import tifffile
from tifffile.tiffcomment import tiffcomment

## macsima_liver.py
from pathlib import Path
import tifffile
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from stardist.models import StarDist2D
from csbdeep.utils import normalize

_dir = Path("HumanLiverH35")
files = list(

## markers_to_cell_type_labels.yaml
# This annotation of cell type markers is tailored for surface proteins
# normally profilid with multiplexed imaging (IMC, CODEX).
# It is a simple reference for myself and may be more detailed in some parts than others.
# This reference is hierarchical.
# This annotation is generally pan-tissue.
# Author: Andre Rendeiro
# License: CC BY-SA 2.0

cell_types:
    structural:

## mask_to_labelme_json.py
import pathlib

import numpy as np

def mask_to_labelme(
    labeled_image: np.ndarray,
    filename: pathlib.Path,
    overwrite: bool = False,
    simplify: bool = True,
    simplification_threshold: float = 5.0,

## triangular_clustermap.py
import string

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# generate some data
n_groups = 4
n_per_group = 5

## interactive_volume_viewer.py
#!/usr/bin/env python

"""
An example program to display a volumetric image from the command line.
"""

import sys
import typing as tp
from urlpath import URL
from functools import partial

## upload_zipfiles_to_box.py
#!/usr/bin/env python

"""
Upload images inside zip files to box.com.
"""

import sys, time, webbrowser, json, zipfile, tempfile, urllib3
from argparse import ArgumentParser
from pathlib import Path
from typing import Dict, List, Generator

## dog_ex.py
from skimage import data, feature, color, filters, img_as_float
from matplotlib import pyplot as plt


original_image = img_as_float(data.chelsea())
img = color.rgb2gray(original_image)

k = 1.6

plt.subplot(2,3,1)

## nih_grant_link_eracommons.md

      
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              December 28, 2020 20:30
            
              
                Linking NIH grant number to publications in NCBI/eRA Commons
              
          
      View nih_grant_link_eracommons.md
  
      
An important first step is to link the era commons and the NCBI accounts. Check if linked here: https://www.ncbi.nlm.nih.gov/account/settings/ and link accounts here: https://www.ncbi.nlm.nih.gov/account/settings/linked-accounts/.
One that is done, go to your bibliography page of NCBI (https://www.ncbi.nlm.nih.gov/myncbi/collections/mybibliography/).
In there should be your publications, if not, search and add it manually with "Add citations".
For each citation there is a panel on the right that has the grant awards mentioned in the work or a "Add Award" button to add manually.
	"""
	Run the experiments for the quantization speedup and plot results.
	"""

	import subprocess

	import numpy as np
	import pandas as pd
	import matplotlib.pyplot as plt
	import seaborn as sns
	"""
	Convert a TIFF file generated by IndicaLabs (HALO) to a usable TIFF file.
	"""

	import typing as tp
	from pathlib import Path
	from xml.etree import ElementTree

	import tifffile
	from tifffile.tiffcomment import tiffcomment
	# This annotation of cell type markers is tailored for surface proteins
	# normally profilid with multiplexed imaging (IMC, CODEX).
	# It is a simple reference for myself and may be more detailed in some parts than others.
	# This reference is hierarchical.
	# This annotation is generally pan-tissue.
	# Author: Andre Rendeiro
	# License: CC BY-SA 2.0

	cell_types:
	structural:
	import pathlib

	import numpy as np

	def mask_to_labelme(
	labeled_image: np.ndarray,
	filename: pathlib.Path,
	overwrite: bool = False,
	simplify: bool = True,
	simplification_threshold: float = 5.0,
	import string

	import numpy as np
	import pandas as pd
	import matplotlib.pyplot as plt
	import seaborn as sns

	# generate some data
	n_groups = 4
	n_per_group = 5
	#!/usr/bin/env python

	"""
	An example program to display a volumetric image from the command line.
	"""

	import sys
	import typing as tp
	from urlpath import URL
	from functools import partial
	#!/usr/bin/env python

	"""
	Upload images inside zip files to box.com.
	"""

	import sys, time, webbrowser, json, zipfile, tempfile, urllib3
	from argparse import ArgumentParser
	from pathlib import Path
	from typing import Dict, List, Generator
	from skimage import data, feature, color, filters, img_as_float
	from matplotlib import pyplot as plt


	original_image = img_as_float(data.chelsea())
	img = color.rgb2gray(original_image)

	k = 1.6

	plt.subplot(2,3,1)