atompy.load_2d_from_txt#

atompy.load_2d_from_txt(fname, output_format='pcolormesh', xyz_indices=(1, 0, 2), permuting='x', xmin=None, xmax=None, ymin=None, ymax=None, origin=None, **loadtxt_kwargs)[source]#

Load 2D data stored in a text file.

Three columns in the file should specify the x, y, and corresponding z values of the data. E.g.,

y0 x0 z00
y0 x1 z01
y0 x2 z02
...
y0 xN z0N
y1 x0 z10
...
yM xN zMN

You can specify which value is permuting first (in the example above x) with the permuting keyword. The assignment of the columns (here, y, x, z) is specified by the xyz_indices keyword.

Parameters:

fnamestr

Filename, including filetype.

output_format{"imshow", "pcolormesh", "Hist2d" }, default "pcolormesh"

Change output format. See Returns.

xyz_indices(int, int, int), default (1, 0, 2)

Specify which column in the file corresponds to x, y, z.

The default corresponds to the output format of the default ROOT macro of the Atomic Physics group that exports 2D data to a text file (hist2ascii).

permuting{"x", "y"}, default "x"

Specify if the x- or y-column permutes through the values first.

xmin, yminfloat, optional

Specify the lower x (y) limit of the data in fname. Only necessary if the x (y) values in fname are not equally spaced. Alternatively, specify xmax (ymax.

xmax, ymaxfloat, optional

Specify the upper x (y) limit of the data in fname. Only necessary if the x (y) values in fname are not equally spaced. Alternatively, specify xmin (ymin). If xmin (ymin) and xmax (ymin) are specified, xmax (ymax) is not used.

origin{"lower", "upper"}, optional

Specify the origin of the imshow-image. If None, use plt.rcParams["image.origin"].

**loadtxt_kwargs

Other numpy.loadtxt() keyword arguments. Useful if, e.g., you want to skip a certain number of lines in the text file.

Returns:

outputPcolormeshData, ImshowData or Hist2d

Depends on output_format.

output_format == "pcolormesh": Return PcolormeshData.
output_format == "imshow": Return ImshowData.
output_format == "Hist2d": Return a Hist2d.

Examples

Load data such that it can be plotted using matplotlib.pyplot.pcolormesh().

data = ap.load_2d_from_txt("data.txt", output_format="pcolormesh")
plt.pcolormesh(data.x, data.y, data.z)

Load data such that it can be plotted using matplotlib.pyplot.imshow().

data = ap.load_2d_from_txt("data.txt", output_format="imshow")
plt.imshow(data.image, extent=data.extent)

Alternatively, immediately unpack the loaded data into their respective numpy.ndarray.

x, y, z = ap.load_2d_from_txt("data.txt", output_format="pcolormesh")
plt.pcolormesh(x, y, z)

image, extent = ap.load_2d_from_txt("data.txt", output_format="imshow")
plt.imshow(image, extent=extent)

Load data as a Hist2d".

hist = ap.load_2d_from_txt("data.txt", output_format="Hist2d")
data = hist.column_normalized_to_sum.for_pcolormesh
plt.pcolormesh(data.x, data.y, data.z)

atompy.load_2d_from_txt#

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