Tóm tắt trực quan một mớ hỗn độn của các đoạn đường có hướng

Tôi có một bộ dữ liệu gồm hàng triệu phân đoạn dòng được định hướng. Các phân đoạn dòng là tuần tự - đó là một biến khí hậu (nhiệt độ hợp lý), với các giá trị được quan sát và mô phỏng trong khoảng thời gian nửa giờ. Tôi đang cố gắng tìm kiếm các mẫu trong cách mô phỏng đang thực hiện. Tôi đang xem xét một biểu đồ phân tán các giá trị mô phỏng và mô phỏng và liên kết chúng với các phân đoạn dòng (mũi tên chỉ hướng thời gian). Nếu tôi vẽ chúng, tôi sẽ nhận được một mớ hỗn độn không thể diễn giải, như thế này:

Đây là tập hợp con gồm 10000 dòng, được vẽ tốt và có độ mờ thấp:

ggplot(d, aes(x=Qh_obs, xend=lead(Qh_obs), y=Qh_sim, yend=lead(Qh_sim))) +
  geom_segment(size=0.1, alpha=0.2, arrow=arrow(length=unit(2, units='mm')))

dput() trong số 700 hàng dữ liệu đầu tiên (giới hạn bởi độ dài bài đăng):

structure(
    list(
        Qh_sim = c( 56.401439666748, 33.9568634033203, 16.2147789001465, 0.797790050506592, -3.19529962539673, -10.3250732421875, -11.6082448959351, -21.5074787139893, -21.5963478088379, -21.4389324188232, -19.8912830352783, -18.5908279418945, -19.2523441314697, -19.663516998291, -19.1126575469971, -18.4237308502197, -16.6181221008301, -14.7601175308228, -14.5604763031006, -14.3527803421021, -14.6219816207886, -14.791407585144, -15.452392578125, -15.8962726593018, -11.9349966049194, -7.97028636932373, 12.4507570266724, 32.1654815673828, 56.9330673217773, 82.0748443603516, 110.501235961914, 138.745697021484, 150.787033081055, 161.838928222656, 172.895263671875, 184.098617553711, 187.657043457031, 192.906372070312, 193.122268676758, 192.274002075195, 179.315124511719, 164.562591552734, 163.265823364258, 161.703796386719, 133.756286621094, 105.635498046875, 97.0240097045898, 87.8632583618164, 58.3389205932617, 33.2009048461914, 23.2682571411133, 13.6356563568115, 1.51271843910217, 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Tôi quan tâm đến việc cố gắng tóm tắt trực quan dòng chảy của những dòng này. Có cách nào phổ biến để tóm tắt loại thông tin này không? Tôi chỉ có thể thực hiện một âm mưu trường vectơ, nhưng tôi nghĩ rằng tôi sẽ mất một số thông tin có liên quan - đặc biệt, một số khu vực dày đặc hơn có thể có nhiều nhóm phân khúc. Tôi đang xem xét phân cụm các phân đoạn (sử dụng bốn biến làm tính năng), và sau đó vẽ sơ đồ trung bình, hoặc có thể thực hiện một vectơ hoa hồng gió, nhưng tôi muốn xem liệu có cách nào tốt hơn về nó không.

Bạn cũng có thể chia thành các khối thời gian và thực hiện các âm mưu. Điều này sẽ giúp nếu dòng chảy trở lại và chuyển tiếp qua chính nó một vài lần.

Có thể có thể làm mịn các phân đoạn để có cảm giác về dòng chảy, nhưng tôi nghĩ rằng việc tạo mặt sẽ là bước đầu tiên.

Một khả năng sẽ là trung bình qua các ngày, để có được một hoặc một vài chu kỳ "trung bình" hàng ngày thay vì hơn 1000 ngày riêng lẻ.

Một ý tưởng khác có thể là một đại diện 3D như trong Tominski, Schumann, Andrienko và Andrienko (2012) .

Tài liệu tham khảo:

Tominski, C., Schumann, H., Andrienko, G., Andrienko, N. (2012). Trực quan hóa dựa trên xếp chồng dữ liệu thuộc tính quỹ đạo. Trực quan hóa và Đồ họa máy tính, Giao dịch theo chuẩn IEEE , tập 18, số 12, tr.2565,2574, tháng 12 năm 2012. doi: 10.1109 / TVCG.2012.265. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6327262&isnumber=6327196