import numpy as np
from PIL import Image, ImageDraw, ImageFont
from stimupy.utils import pad_dict_to_visual_size, resolution
__all__ = [
"text",
]
[docs]def text(
text,
visual_size=None,
ppd=None,
shape=None,
intensity_text=0.0,
intensity_background=0.5,
fontsize=36,
align="center",
# direction="ltr",
):
"""Draw given text into a (numpy) image-array
If no shape is provided / can be resolved,
tightly fits the bounding box of the drawn text.
Parameters
----------
text : str
Text to draw
visual_size : Sequence[Number, Number], Number, or None (default)
visual size [height, width] of image, in degrees visual angle
ppd : Sequence[Number, Number], Number, or None (default)
pixels per degree [vertical, horizontal]
shape : Sequence[Number, Number], Number, or None (default)
shape [height, width] of image, in pixels
intensity_text : float, optional
intensity of text in range (0.0; 1.0), by default 0.0
intensity_background : float, optional
intensity value of background in range (0.0; 1.0), by default 0.5
fontsize : int, optional
font size, by default 36
align : "left", "center" (default), "right"
alignment of text, by default "center"
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img"),
mask with integer index for the text (key: "text_mask"),
and additional keys containing stimulus parameters
"""
# Try to resolve resolution
try:
shape, visual_size, ppd = resolution.resolve(shape=shape, visual_size=visual_size, ppd=ppd)
except resolution.TooManyUnknownsError:
shape = resolution.validate_shape(shape)
visual_size = resolution.validate_visual_size(visual_size)
ppd = resolution.validate_ppd(ppd)
# Get font
font = ImageDraw.ImageDraw.font
if not font:
try:
# Not all machines will have Arial installed...
font = ImageFont.truetype(
"arial.ttf",
fontsize,
encoding="unic",
)
except OSError:
font = ImageFont.load_default()
# Determine dimensions of total text
n_lines = len(text.split("\n"))
max_length = 0
for line in text.split("\n"):
max_length = max(int(font.getlength(line)), max_length)
_, top, _, bottom = font.getbbox(text)
text_width = max_length
text_height = int(top + bottom) * n_lines
text_shape = (text_height, text_width)
# Instantiate grayscale image of correct shape (in pixels)
img = Image.new("L", (text_width, text_height), 0)
draw = ImageDraw.Draw(img)
# Draw text into this image
draw.text(
(0, 0),
text,
fill=1,
font=font,
align=align,
# direction=direction
)
# Turn into mask-array
mask = np.array(img)
img = np.where(mask, intensity_text, intensity_background)
# Package as dict
stim = {
"img": img,
"text_mask": mask,
"text_shape": text_shape,
}
# Resolve resolution
if not shape or shape == (None, None):
shape = text_shape
shape, visual_size, ppd = resolution.resolve(shape=shape, visual_size=visual_size, ppd=ppd)
# Pad
stim = pad_dict_to_visual_size(stim, visual_size=visual_size, ppd=ppd, pad_value=0.5)
# Output
return stim
def overview(**kwargs):
"""Generate example stimuli from this module
Returns
-------
stims : dict
dict with all stimuli containing individual stimulus dicts.
"""
default_params = {
"visual_size": (10, 10),
"ppd": 32,
}
default_params.update(kwargs)
# fmt: off
stimuli = {
"text(), single line": text(text="hello world", **default_params),
"text(), multiline": text(text="hello\nworld", **default_params)
}
# fmt: on
return stimuli
if __name__ == "__main__":
from stimupy.utils import plot_stimuli
stims = overview()
plot_stimuli(stims, mask=False, save=None)
