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Python Multi-core / GPU Digital Phosphor Rendering of Huge Waveform Data

Most modern oscilloscopes are marketed as Digital Phosphor Oscilloscope (DPO) because the waveform shown on those scopes looks night-and-day compared to their old counterparts.   DPO vs DSO, from Tektronix TDS784D marketing materials This is because although the traditional DSO can capture data at a blazling fast speed, they lacked the processing bandwidth to show them on the display: It may be able to capture 100 million waveform data for one trigger point and store it in the sample memory, but the monitor only has say 1024 pixels wide. DSO simply throw away most of the points, resulting in an ugly aliased apperarance with 1bit per pixel.   To achieve the nice and smooth look of a DPO, what we want to do is to down sample the 100 million points to 1024 pixels wide with a correct down sampling algorithm.  Recently I've been working with some huge waveform captures with more than 1G points. Plotting such data with the beloved matplotlib will result in an ugl...

Color Profiles


I bought a Spyder 5 Elite display calibrator. Then, it's inevitable that I will start benchmarking and calibrating all the devices I own. I think it would be nice to share the generated color profiles so owners of those (poorly factory-calibrated) devices can use them to hopefully get a better color reproduction. 

As a rule of thumb, without any calibrator or color palettes on hand, you can compare your device with an Apple device (which usually has a good factory calibration and does not have the "vibrant enhancement" BS) to get a sense of its color accuracy.

All calibrations are done with the default settings (50% brightness, Gamma 2.2, 6500K)

I do not provide any guarantee on the quality of those profiles. Use it at your own risk.

Device Name

Serial Numbers

Profile

Coverage

Device

Panel

sRGB

aRGB

DCI-P3

Wacom DTH-W1310 

6CAH000337-715

EDID

 ICC

 95%

75% 

80% 

Panasonic CF-RZ6

CF-RZ6RFDVS; 7HKSA16768 

EDID

ICC

76% 

62% 

61% 

Panasonic CF-XZ

CF-XZ6RD4VS; 9FKSC77747     

EDID 

ICC 

82% 

62% 

62% 

Thinkpad X1 Carbon Gen 10

PF4A0P83

-

-

100%

97%

100%

 LG Ultrafine 4K 

27UP600-W.AUM; 205NTZNJH957

EDID

ICC

100%

90%

100%

Wacom MobileStudio (Gen1) 16 Inch

 -

 -

ICC

98%

92%

93%

Huion Kamvas 22 Plus

-

-

ICC

100%

97% 

100%

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 A simple way to visualize the color space supported by the ICC file is to use the Color Space Browser tool provided by Krita:



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