def _pixel_coordinate(line: list,
x_1d: np.array,
y_1d: np.array,
k: int = None):
"""Gets the pixel coordinate of the value x or y, in order to get posterior
conditional probability given a KDE.
:param line: Coordinates of the line we'd like to sample along [(x1, y1), (x2, y2)]
:param x_1d: List of x coordinates along the axis
:param y_1d: List of y coordinates along the axis
:param k: Used to set number of rows/columns
:return: (rows, columns)
"""
if k is None:
num = 200
else:
num = k
# https://stackoverflow.com/questions/18920614/plot-cross-section-through-heat-map
# Convert the line to pixel/index coordinates
x_world, y_world = np.array(list(zip(*line)))
col = y_1d.shape * (x_world - min(x_1d)) / x_1d.ptp()
row = x_1d.shape * (y_world - min(y_1d)) / y_1d.ptp()
# Interpolate the line at "num" points...
row, col = [np.linspace(item[0], item[1], num) for item in [row, col]]
return row, col
def qpixmap_from(image: np.array):
dwidth, dheight = image.shape
# map the data range to 0 - 255
img_8bit = ((image - image.min()) / (image.ptp() / 255.0)).astype(np.uint8)
# qimg = QImage(img_8bit.repeat(4), dwidth, dheight, QImage.Format_RGB32)
qimg = QImage(img_8bit.repeat(3), dwidth, dheight, QImage.Format_RGB888)
return QPixmap(qimg)
def find_pctile(self, data: np.array, terminal_days: int,
spline_knots_type: str) -> Tuple[float, float]:
data = np.sort(data)
if spline_knots_type == 'domain':
#start_boundary_pctile = (data[terminal_days - 1] - data[0]) / data.ptp()
end_boundary_pctile = (data[-terminal_days] - data[0]) / data.ptp()
elif spline_knots_type == 'frequency':
#start_boundary_pctile = terminal_days / data.size
end_boundary_pctile = 1. - terminal_days / data.size
return end_boundary_pctile # start_boundary_pctile,
