Microarrayer layout generator

quanterix2470_custom_layout.py

HEADER = """\
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<IndirectPrinting>
"""

FOOTER = """\
   <Attributes>
      <PrintName>CustomPrint</PrintName>
      <Originals>4</Originals>
      <Replicants>{Replicants}</Replicants>
      <maxInXDir>{maxInXDir}</maxInXDir>
      <maxInYDir>{maxInYDir}</maxInYDir>
   </Attributes>
   <integrity>Lnu0jwyG1z2wa9ReqqU3lHDT36vkrLmFErBTt00iBTMDHn916BMMCA..</integrity>
</IndirectPrinting>
"""

SAMPLE = """\
   <Sample>
      <SampleNumber>{SampleNumber}</SampleNumber>
      <SpotNumber>{SpotNumber}</SpotNumber>
      <SpotRow>{SpotRow}</SpotRow>
      <SpotCol>{SpotCol}</SpotCol>
      <SampleLabel>{SampleNumber}:{SpotNumber}</SampleLabel>
      <Depositions>1</Depositions>
   </Sample>
"""

data = dict(SampleNumber=1, SpotNumber=0, SpotRow=3, SpotCol=4)


samples = ""

ROWS = 20
COLS = 5

cell_size = 80  # um
spot2spot = 2  # cells
fov2fov = 5  # cells

maxInXDir = COLS * fov2fov
maxInYDir = ROWS * fov2fov

for SampleNumber in range(1, 5):
    SpotNumber = 0
    i = (0 if SampleNumber <= 2 else 1) * spot2spot
    j = ((SampleNumber - 1) % 2) * spot2spot
    for SpotRow in range(i, i + maxInYDir, fov2fov):
        for SpotCol in range(j, j + maxInXDir, fov2fov):
            samples += SAMPLE.format(
                SampleNumber=SampleNumber,
                SpotNumber=SpotNumber,
                SpotRow=SpotRow,
                SpotCol=SpotCol,
            )
            SpotNumber += 1


with open("out.xml", "w") as output_file:
    output_file.write(HEADER)
    output_file.write(samples)
    output_file.write(
        FOOTER.format(
            Replicants=ROWS * COLS,
            maxInXDir=maxInXDir - spot2spot,
            maxInYDir=maxInYDir - spot2spot,
        )
    )

quanterix2470_custom_layout_test.py

FNAME = "5um distance test 120-170.xml"

HEADER = """\
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<IndirectPrinting>
"""

FOOTER = """\
   <Attributes>
      <PrintName>CustomPrint</PrintName>
      <Originals>4</Originals>
      <Replicants>{Replicants}</Replicants>
      <maxInXDir>{maxInXDir}</maxInXDir>
      <maxInYDir>{maxInYDir}</maxInYDir>
   </Attributes>
   <integrity>Lnu0jwyG1z2wa9ReqqU3lHDT36vkrLmFErBTt00iBTMDHn916BMMCA..</integrity>
</IndirectPrinting>
"""

SAMPLE = """\
   <Sample>
      <SampleNumber>{SampleNumber}</SampleNumber>
      <SpotNumber>{SpotNumber}</SpotNumber>
      <SpotRow>{SpotRow}</SpotRow>
      <SpotCol>{SpotCol}</SpotCol>
      <SampleLabel>{SampleNumber}:{SpotNumber}</SampleLabel>
      <Depositions>1</Depositions>
   </Sample>
"""

import numpy as np

data = dict(SampleNumber=1, SpotNumber=0, SpotRow=3, SpotCol=4)


samples = ""

cell_size = 5  # um
dMIN = 120
dMAX = 170

XREPS = 3

xgrid = np.arange(dMIN / cell_size, (dMAX + cell_size) / cell_size).astype(int)


maxInXDir = 0
maxInYDir = 0
SpotNumber = 0
for rep in range(XREPS):
    x_origin = int(rep * dMAX * 3 / cell_size)
    for row, N in enumerate(reversed(xgrid)):
        samples += SAMPLE.format(
            SampleNumber=1,
            SpotNumber=SpotNumber,
            SpotRow=row,
            SpotCol=x_origin,
        )
        SpotNumber += 1
        samples += SAMPLE.format(
            SampleNumber=1,
            SpotNumber=SpotNumber,
            SpotRow=row,
            SpotCol=x_origin + N,
        )
        SpotNumber += 1
        maxInXDir = max(maxInXDir, row)
        maxInYDir = max(maxInYDir, x_origin + N)


with open(FNAME, "w") as output_file:
    output_file.write(HEADER)
    output_file.write(samples)
    output_file.write(
        FOOTER.format(
            Replicants=SpotNumber,
            maxInXDir=maxInXDir,
            maxInYDir=maxInYDir,
        )
    )


print(
    f"""Spacing: x={cell_size}um, y={dMAX*3}
Array size: W={maxInXDir*cell_size/1000}mm, H={dMAX*3*len(xgrid)}mm"""
)


import xml.etree.ElementTree as ET
import pandas as pd
import matplotlib.pyplot as plt

# Parse the XML file
tree = ET.parse(FNAME)
root = tree.getroot()

# Extract data and store in a list of dictionaries
samples = []
for sample in root.findall("Sample"):
    sample_data = {
        "SampleNumber": int(sample.find("SampleNumber").text),
        "SpotNumber": int(sample.find("SpotNumber").text),
        "SpotRow": int(sample.find("SpotRow").text),
        "SpotCol": int(sample.find("SpotCol").text),
        "SampleLabel": sample.find("SampleLabel").text,
        "Depositions": int(sample.find("Depositions").text),
    }
    samples.append(sample_data)

# Convert to DataFrame
df = pd.DataFrame(samples)

# Print the DataFrame
print(df)

# Visualize spot positions on a grid
plt.figure(figsize=(8, 6))
plt.scatter(df["SpotCol"], df["SpotRow"], s=100, c=df["SampleNumber"], marker="o")

# Annotate spots with their labels
for i, label in enumerate(df["SampleLabel"]):
    plt.annotate(
        label,
        (df["SpotCol"][i], df["SpotRow"][i]),
        textcoords="offset points",
        xytext=(0, 10),
        ha="center",
    )

plt.gca().invert_yaxis()  # Invert y-axis to match typical grid layout
plt.xlabel("SpotCol")
plt.ylabel("SpotRow")
plt.title("Spot Positions on Grid")

# Set up major and minor ticks
plt.gca().xaxis.set_major_locator(plt.MultipleLocator(10 * cell_size))
plt.gca().yaxis.set_major_locator(plt.MultipleLocator(10))
plt.gca().xaxis.set_minor_locator(plt.MultipleLocator(cell_size))
plt.gca().yaxis.set_minor_locator(plt.MultipleLocator(1))

# Show grid lines
plt.grid(which="major", color="black", linestyle="-", linewidth=0.75)
plt.grid(which="minor", color="gray", linestyle=":", linewidth=0.5)

plt.grid(True)
# plt.gca().set_aspect("equal", adjustable="box")
plt.show()

show_spots.py

import xml.etree.ElementTree as ET
import pandas as pd
import matplotlib.pyplot as plt

# Parse the XML file
tree = ET.parse('4spots 160um 400um 6x20.xml')
root = tree.getroot()

# Extract data and store in a list of dictionaries
samples = []
for sample in root.findall('Sample'):
    sample_data = {
        'SampleNumber': int(sample.find('SampleNumber').text),
        'SpotNumber': int(sample.find('SpotNumber').text),
        'SpotRow': int(sample.find('SpotRow').text),
        'SpotCol': int(sample.find('SpotCol').text),
        'SampleLabel': sample.find('SampleLabel').text,
        'Depositions': int(sample.find('Depositions').text)
    }
    samples.append(sample_data)

# Convert to DataFrame
df = pd.DataFrame(samples)

# Print the DataFrame
print(df)

# Visualize spot positions on a grid
plt.figure(figsize=(8, 6))
plt.scatter(df['SpotCol'], df['SpotRow'], s=100, c=df['SampleNumber'], marker='o')

# Annotate spots with their labels
for i, label in enumerate(df['SampleLabel']):
    plt.annotate(label, (df['SpotCol'][i], df['SpotRow'][i]), textcoords="offset points", xytext=(0,10), ha='center')

plt.gca().invert_yaxis()  # Invert y-axis to match typical grid layout
plt.xlabel('SpotCol')
plt.ylabel('SpotRow')
plt.title('Spot Positions on Grid')
plt.grid(True)
plt.gca().set_aspect('equal', adjustable='box')
plt.show()