Remove unused path offset learner

* loggerd: use services.h

* don't need yaml-cpp anymore

* forgot that

.dir-locals.el

@@ -0,0 +1,3 @@
+((c++-mode (flycheck-gcc-language-standard . "c++11")
+           (flycheck-clang-language-standard . "c++11")
+           ))

.dockerignore

@@ -0,0 +1,24 @@
+.git
+.DS_Store
+notebooks
+phone
+massivemap
+neos
+installer
+chffr/app2
+chffr/backend/env
+selfdrive/nav
+selfdrive/baseui
+chffr/lib/vidindex/vidindex
+chffr/lib/index_log/index_log
+selfdrive/test/simulator2
+**/cache_data
+xx/chffr/lib/index_log/index_log
+xx/chffr/lib/vidindex/vidindex
+xx/plus
+xx/community
+xx/projects
+!xx/projects/eon_testing_master
+!xx/projects/map3d
+xx/ops
+xx/junk

.editorconfig

@@ -0,0 +1,11 @@
+root = true
+
+[*]
+end_of_line = lf
+insert_final_newline = true
+trim_trailing_whitespace = true
+
+[{*.py, *.pyx, *pxd}]
+charset = utf-8
+indent_style = space
+indent_size = 2

.gitattributes

@@ -0,0 +1,27 @@
+*.keras filter=lfs diff=lfs merge=lfs -text
+*.dlc filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.apk filter=lfs diff=lfs merge=lfs -text
+*.ipynb filter=nbstripout -diff
+external/ffmpeg/bin/ffmpeg_cuda filter=lfs diff=lfs merge=lfs -text
+models/segnet.keras filter=lfs diff=lfs merge=lfs -text
+external/zmq/lib/libzmq.a filter=lfs diff=lfs merge=lfs -text
+external/zmq/lib/libczmq.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/x64/lib/libacado_toolkit.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/x64/lib/libacado_toolkit_s.so.1.2.2beta filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/x64/lib/libacado_casadi.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/x64/lib/libacado_csparse.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/x64/lib/libacado_qpoases.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/aarch64/lib/libacado_toolkit.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/aarch64/lib/libacado_toolkit_s.so.1.2.2beta filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/aarch64/lib/libacado_casadi.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/aarch64/lib/libacado_csparse.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/acado/aarch64/lib/libacado_qpoases.a filter=lfs diff=lfs merge=lfs -text
+phonelibs/fastcv/aarch64/libfastcvopt.so filter=lfs diff=lfs merge=lfs -text
+phonelibs/fastcv/aarch64/libfastcvadsp_stub.so filter=lfs diff=lfs merge=lfs -text
+external/mac/MP4Box filter=lfs diff=lfs merge=lfs -text
+models/segnet2.keras filter=lfs diff=lfs merge=lfs -text
+external/opencl/*.deb filter=lfs diff=lfs merge=lfs -text
+phonelibs/zmq/aarch64-linux/lib/libzmq.a filter=lfs diff=lfs merge=lfs -text
+external/azcopy/azcopy filter=lfs diff=lfs merge=lfs -text

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,25 @@
+---
+name: Bug report
+about: Create a report to help us improve openpilot
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**How to reproduce or log data**
+Steps to reproduce the behavior, or a explorer/cabana link to the exact drive and timestamp of when the bug occurred.
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Device/Version information (please complete the following information):**
+ - Device: [e.g. EON/EON Gold]
+ - Version: [e.g. 0.6.4], or commit hash when on devel
+ - Car make/model [e.g. Toyota Prius 2016]
+
+**Additional context**
+Add any other context about the problem here.

.github/workflows/test.yaml

@@ -0,0 +1,125 @@
+name: Openpilot Tests
+on: [push, pull_request]
+
+env:
+  RUN: docker run --shm-size 1G --rm tmppilot /bin/sh -c
+  LOAD: docker load -i tmppilot.tar.gz/tmppilot.tar.gz
+  UNIT_TEST: cd /tmp/openpilot && python -m unittest discover
+
+jobs:
+  build:
+    name: build
+    runs-on: ubuntu-16.04
+    steps:
+    - uses: actions/checkout@v2
+    - name: Checkout submodules
+      run: |
+        git submodule update --init
+    - run: |
+        docker pull $(grep -ioP '(?<=^from)\s+\S+' Dockerfile.openpilot) || true
+        docker pull docker.io/commaai/openpilot:latest || true
+
+        docker build --cache-from docker.io/commaai/openpilot:latest -t tmppilot -f Dockerfile.openpilot .
+        docker save tmppilot:latest | gzip > tmppilot.tar.gz
+    - uses: actions/upload-artifact@v1
+      with:
+        name: tmppilot.tar.gz
+        path: tmppilot.tar.gz
+
+  linter:
+    name: linter
+    runs-on: ubuntu-16.04
+    needs: build
+    steps:
+      - uses: actions/download-artifact@v1
+        with:
+          name: tmppilot.tar.gz
+      - name: Load image
+        run: $LOAD
+      - name: flake8
+        run: $RUN "cd /tmp/openpilot/ && ./flake8_openpilot.sh"
+      - name: pylint
+        run: $RUN "cd /tmp/openpilot/ && ./pylint_openpilot.sh"
+
+  unit_tests:
+    name: unit tests
+    runs-on: ubuntu-16.04
+    needs: build
+    steps:
+      - uses: actions/download-artifact@v1
+        with:
+          name: tmppilot.tar.gz
+      - name: Load image
+        run: $LOAD
+      - name: Run unit tests
+        run: |
+          $RUN cd /tmp/openpilot/selfdrive/test/test_fingerprints.py
+          $RUN "$UNIT_TEST common"
+          $RUN "$UNIT_TEST opendbc/can"
+          $RUN "$UNIT_TEST selfdrive/boardd"
+          $RUN "$UNIT_TEST selfdrive/controls"
+          $RUN "$UNIT_TEST selfdrive/loggerd"
+          $RUN "$UNIT_TEST selfdrive/car"
+          $RUN "$UNIT_TEST selfdrive/locationd"
+          $RUN "$UNIT_TEST selfdrive/athena"
+
+  process_replay:
+    name: process replay
+    runs-on: ubuntu-16.04
+    needs: build
+    timeout-minutes: 30
+    steps:
+      - uses: actions/download-artifact@v1
+        with:
+          name: tmppilot.tar.gz
+      - name: Load image
+        run: $LOAD
+      - name: Run replay
+        run: |
+          CONTAINER_NAME="tmppilot_${GITHUB_SHA}"
+          docker run --shm-size 1G --name ${CONTAINER_NAME} tmppilot /bin/sh -c "cd /tmp/openpilot/selfdrive/test/process_replay && CI=1 ./test_processes.py"
+          docker cp $CONTAINER_NAME:/tmp/openpilot/selfdrive/test/process_replay/diff.txt diff.txt
+          docker rm $CONTAINER_NAME
+      - uses: actions/upload-artifact@v1
+        if: always()
+        with:
+          name: process_replay_diff.txt
+          path: diff.txt
+
+  test_longitudinal:
+    name: longitudinal
+    runs-on: ubuntu-16.04
+    needs: build
+    timeout-minutes: 30
+    steps:
+      - uses: actions/download-artifact@v1
+        with:
+          name: tmppilot.tar.gz
+      - name: Load image
+        run: $LOAD
+      - name: Test longitudinal
+        run: |
+          CONTAINER_NAME="tmppilot_${GITHUB_SHA}"
+          docker run --shm-size 1G --name ${CONTAINER_NAME} tmppilot /bin/sh -c "cd /tmp/openpilot/selfdrive/test/longitudinal_maneuvers && OPTEST=1 ./test_longitudinal.py"
+          mkdir out
+          docker cp $CONTAINER_NAME:/tmp/openpilot/selfdrive/test/longitudinal_maneuvers/out/longitudinal/ out/
+          docker rm $CONTAINER_NAME
+      - uses: actions/upload-artifact@v1
+        if: always()
+        with:
+          name: longitudinal
+          path: out
+
+  test_car_models:
+    name: test car models
+    runs-on: ubuntu-16.04
+    needs: build
+    timeout-minutes: 30
+    steps:
+      - uses: actions/download-artifact@v1
+        with:
+          name: tmppilot.tar.gz
+      - name: Load image
+        run: $LOAD
+      - name: Test car models
+        run: $RUN "mkdir -p /data/params && cd /tmp/openpilot/selfdrive/test/ && ./test_car_models.py"

.gitignore

@@ -1,10 +1,16 @@
+venv/
 .DS_Store
 .tags
 .ipynb_checkpoints
 .idea
+.overlay_init
+.overlay_consistent
+.sconsign.dblite
+.vscode
 model2.png
 a.out
 
+*.dylib
 *.DSYM
 *.d
 *.pyc
@@ -12,7 +18,9 @@ a.out
 .*.swp
 .*.swo
 .*.un~
+*.tmp
 *.o
+*.os
 *.so
 *.a
 *.clb
@@ -22,11 +30,30 @@ a.out
 config.json
 clcache
 
+persist
 board/obj/
 selfdrive/boardd/boardd
 selfdrive/logcatd/logcatd
+selfdrive/mapd/default_speeds_by_region.json
 selfdrive/proclogd/proclogd
-selfdrive/ui/ui
+selfdrive/ui/_ui
+selfdrive/test/longitudinal_maneuvers/out
+selfdrive/visiond/visiond
+selfdrive/loggerd/loggerd
+selfdrive/sensord/_gpsd
+selfdrive/sensord/_sensord
+selfdrive/camerad/camerad
+selfdrive/modeld/_modeld
+selfdrive/modeld/_dmonitoringmodeld
 /src/
 
 one
+openpilot
+notebooks
+xx
+panda_jungle
+
+.coverage*
+htmlcov
+pandaextra
+

.gitmodules

@@ -0,0 +1,16 @@
+[submodule "panda"]
+	path = panda
+	url = ../../commaai/panda.git
+[submodule "opendbc"]
+	path = opendbc
+	url = ../../commaai/opendbc.git
+[submodule "laika_repo"]
+	path = laika_repo
+	url = ../../commaai/laika.git
+[submodule "apks"]
+	path = apks
+	url = ../../commaai/openpilot-apks.git
+[submodule "cereal"]
+	path = cereal
+	url = ../../commaai/cereal.git
+

.pylintrc

@@ -0,0 +1,585 @@
+[MASTER]
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code
+extension-pkg-whitelist=scipy
+
+# Add files or directories to the blacklist. They should be base names, not
+# paths.
+ignore=CVS
+
+# Add files or directories matching the regex patterns to the blacklist. The
+# regex matches against base names, not paths.
+ignore-patterns=
+
+# Python code to execute, usually for sys.path manipulation such as
+# pygtk.require().
+#init-hook=
+
+# Use multiple processes to speed up Pylint.
+jobs=4
+
+# List of plugins (as comma separated values of python modules names) to load,
+# usually to register additional checkers.
+load-plugins=
+
+# Pickle collected data for later comparisons.
+persistent=yes
+
+# Specify a configuration file.
+#rcfile=
+
+# When enabled, pylint would attempt to guess common misconfiguration and emit
+# user-friendly hints instead of false-positive error messages
+suggestion-mode=yes
+
+# Allow loading of arbitrary C extensions. Extensions are imported into the
+# active Python interpreter and may run arbitrary code.
+unsafe-load-any-extension=no
+
+
+[MESSAGES CONTROL]
+
+# Only show warnings with the listed confidence levels. Leave empty to show
+# all. Valid levels: HIGH, INFERENCE, INFERENCE_FAILURE, UNDEFINED
+confidence=
+
+# Disable the message, report, category or checker with the given id(s). You
+# can either give multiple identifiers separated by comma (,) or put this
+# option multiple times (only on the command line, not in the configuration
+# file where it should appear only once).You can also use "--disable=all" to
+# disable everything first and then reenable specific checks. For example, if
+# you want to run only the similarities checker, you can use "--disable=all
+# --enable=similarities". If you want to run only the classes checker, but have
+# no Warning level messages displayed, use"--disable=all --enable=classes
+# --disable=W"
+disable=print-statement,
+        parameter-unpacking,
+        unpacking-in-except,
+        old-raise-syntax,
+        backtick,
+        long-suffix,
+        old-ne-operator,
+        old-octal-literal,
+        import-star-module-level,
+        non-ascii-bytes-literal,
+        raw-checker-failed,
+        bad-inline-option,
+        locally-disabled,
+        locally-enabled,
+        file-ignored,
+        suppressed-message,
+        useless-suppression,
+        deprecated-pragma,
+        apply-builtin,
+        basestring-builtin,
+        buffer-builtin,
+        cmp-builtin,
+        coerce-builtin,
+        execfile-builtin,
+        file-builtin,
+        long-builtin,
+        raw_input-builtin,
+        reduce-builtin,
+        standarderror-builtin,
+        unicode-builtin,
+        xrange-builtin,
+        coerce-method,
+        delslice-method,
+        getslice-method,
+        setslice-method,
+        no-absolute-import,
+        old-division,
+        dict-iter-method,
+        dict-view-method,
+        next-method-called,
+        metaclass-assignment,
+        indexing-exception,
+        raising-string,
+        reload-builtin,
+        oct-method,
+        hex-method,
+        nonzero-method,
+        cmp-method,
+        input-builtin,
+        round-builtin,
+        intern-builtin,
+        unichr-builtin,
+        map-builtin-not-iterating,
+        zip-builtin-not-iterating,
+        range-builtin-not-iterating,
+        filter-builtin-not-iterating,
+        using-cmp-argument,
+        eq-without-hash,
+        div-method,
+        idiv-method,
+        rdiv-method,
+        exception-message-attribute,
+        invalid-str-codec,
+        sys-max-int,
+        bad-python3-import,
+        deprecated-string-function,
+        deprecated-str-translate-call,
+        deprecated-itertools-function,
+        deprecated-types-field,
+        next-method-defined,
+        dict-items-not-iterating,
+        dict-keys-not-iterating,
+        dict-values-not-iterating,
+        bad-indentation,
+        line-too-long,
+        missing-docstring,
+        multiple-statements,
+        bad-continuation,
+        invalid-name,
+        too-many-arguments,
+        too-many-locals,
+        superfluous-parens,
+        bad-whitespace,
+        too-many-instance-attributes,
+        wrong-import-position,
+        ungrouped-imports,
+        wrong-import-order,
+        protected-access,
+        trailing-whitespace,
+        too-many-branches,
+        too-few-public-methods,
+        too-many-statements,
+        trailing-newlines,
+        attribute-defined-outside-init,
+        too-many-return-statements,
+        too-many-public-methods,
+        unused-argument,
+        old-style-class,
+        no-init,
+        len-as-condition,
+        unneeded-not,
+        no-self-use,
+        multiple-imports,
+        no-else-return,
+        logging-not-lazy,
+        fixme,
+        redefined-outer-name,
+        unused-variable,
+        unsubscriptable-object,
+        expression-not-assigned,
+        too-many-boolean-expressions,
+        consider-using-ternary,
+        invalid-unary-operand-type,
+        relative-import,
+        deprecated-lambda
+
+
+# Enable the message, report, category or checker with the given id(s). You can
+# either give multiple identifier separated by comma (,) or put this option
+# multiple time (only on the command line, not in the configuration file where
+# it should appear only once). See also the "--disable" option for examples.
+enable=c-extension-no-member
+
+
+[REPORTS]
+
+# Python expression which should return a note less than 10 (10 is the highest
+# note). You have access to the variables errors warning, statement which
+# respectively contain the number of errors / warnings messages and the total
+# number of statements analyzed. This is used by the global evaluation report
+# (RP0004).
+evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)
+
+# Template used to display messages. This is a python new-style format string
+# used to format the message information. See doc for all details
+#msg-template=
+
+# Set the output format. Available formats are text, parseable, colorized, json
+# and msvs (visual studio).You can also give a reporter class, eg
+# mypackage.mymodule.MyReporterClass.
+output-format=text
+
+# Tells whether to display a full report or only the messages
+reports=no
+
+# Activate the evaluation score.
+score=yes
+
+
+[REFACTORING]
+
+# Maximum number of nested blocks for function / method body
+max-nested-blocks=5
+
+# Complete name of functions that never returns. When checking for
+# inconsistent-return-statements if a never returning function is called then
+# it will be considered as an explicit return statement and no message will be
+# printed.
+never-returning-functions=optparse.Values,sys.exit
+
+
+[LOGGING]
+
+# Logging modules to check that the string format arguments are in logging
+# function parameter format
+logging-modules=logging
+
+
+[SPELLING]
+
+# Limits count of emitted suggestions for spelling mistakes
+max-spelling-suggestions=4
+
+# Spelling dictionary name. Available dictionaries: none. To make it working
+# install python-enchant package.
+spelling-dict=
+
+# List of comma separated words that should not be checked.
+spelling-ignore-words=
+
+# A path to a file that contains private dictionary; one word per line.
+spelling-private-dict-file=
+
+# Tells whether to store unknown words to indicated private dictionary in
+# --spelling-private-dict-file option instead of raising a message.
+spelling-store-unknown-words=no
+
+
+[MISCELLANEOUS]
+
+# List of note tags to take in consideration, separated by a comma.
+notes=FIXME,
+      XXX,
+      TODO
+
+
+[SIMILARITIES]
+
+# Ignore comments when computing similarities.
+ignore-comments=yes
+
+# Ignore docstrings when computing similarities.
+ignore-docstrings=yes
+
+# Ignore imports when computing similarities.
+ignore-imports=no
+
+# Minimum lines number of a similarity.
+min-similarity-lines=4
+
+
+[TYPECHECK]
+
+# List of decorators that produce context managers, such as
+# contextlib.contextmanager. Add to this list to register other decorators that
+# produce valid context managers.
+contextmanager-decorators=contextlib.contextmanager
+
+# List of members which are set dynamically and missed by pylint inference
+# system, and so shouldn't trigger E1101 when accessed. Python regular
+# expressions are accepted.
+generated-members=capnp.* cereal.* pygame.* zmq.* setproctitle.* smbus2.* usb1.* serial.* cv2.*
+
+# Tells whether missing members accessed in mixin class should be ignored. A
+# mixin class is detected if its name ends with "mixin" (case insensitive).
+ignore-mixin-members=yes
+
+# This flag controls whether pylint should warn about no-member and similar
+# checks whenever an opaque object is returned when inferring. The inference
+# can return multiple potential results while evaluating a Python object, but
+# some branches might not be evaluated, which results in partial inference. In
+# that case, it might be useful to still emit no-member and other checks for
+# the rest of the inferred objects.
+ignore-on-opaque-inference=yes
+
+# List of class names for which member attributes should not be checked (useful
+# for classes with dynamically set attributes). This supports the use of
+# qualified names.
+ignored-classes=optparse.Values,thread._local,_thread._local
+
+# List of module names for which member attributes should not be checked
+# (useful for modules/projects where namespaces are manipulated during runtime
+# and thus existing member attributes cannot be deduced by static analysis. It
+# supports qualified module names, as well as Unix pattern matching.
+ignored-modules=flask setproctitle usb1 flask.ext.socketio smbus2 usb1.*
+
+# Show a hint with possible names when a member name was not found. The aspect
+# of finding the hint is based on edit distance.
+missing-member-hint=yes
+
+# The minimum edit distance a name should have in order to be considered a
+# similar match for a missing member name.
+missing-member-hint-distance=1
+
+# The total number of similar names that should be taken in consideration when
+# showing a hint for a missing member.
+missing-member-max-choices=1
+
+
+[VARIABLES]
+
+# List of additional names supposed to be defined in builtins. Remember that
+# you should avoid to define new builtins when possible.
+additional-builtins=
+
+# Tells whether unused global variables should be treated as a violation.
+allow-global-unused-variables=yes
+
+# List of strings which can identify a callback function by name. A callback
+# name must start or end with one of those strings.
+callbacks=cb_,
+          _cb
+
+# A regular expression matching the name of dummy variables (i.e. expectedly
+# not used).
+dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
+
+# Argument names that match this expression will be ignored. Default to name
+# with leading underscore
+ignored-argument-names=_.*|^ignored_|^unused_
+
+# Tells whether we should check for unused import in __init__ files.
+init-import=no
+
+# List of qualified module names which can have objects that can redefine
+# builtins.
+redefining-builtins-modules=six.moves,past.builtins,future.builtins
+
+
+[FORMAT]
+
+# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
+expected-line-ending-format=
+
+# Regexp for a line that is allowed to be longer than the limit.
+ignore-long-lines=^\s*(# )?<?https?://\S+>?$
+
+# Number of spaces of indent required inside a hanging  or continued line.
+indent-after-paren=4
+
+# String used as indentation unit. This is usually "    " (4 spaces) or "\t" (1
+# tab).
+indent-string='  '
+
+# Maximum number of characters on a single line.
+max-line-length=100
+
+# Maximum number of lines in a module
+max-module-lines=1000
+
+# List of optional constructs for which whitespace checking is disabled. `dict-
+# separator` is used to allow tabulation in dicts, etc.: {1  : 1,\n222: 2}.
+# `trailing-comma` allows a space between comma and closing bracket: (a, ).
+# `empty-line` allows space-only lines.
+no-space-check=trailing-comma,
+               dict-separator
+
+# Allow the body of a class to be on the same line as the declaration if body
+# contains single statement.
+single-line-class-stmt=no
+
+# Allow the body of an if to be on the same line as the test if there is no
+# else.
+single-line-if-stmt=no
+
+
+[BASIC]
+
+# Naming style matching correct argument names
+argument-naming-style=snake_case
+
+# Regular expression matching correct argument names. Overrides argument-
+# naming-style
+#argument-rgx=
+
+# Naming style matching correct attribute names
+attr-naming-style=snake_case
+
+# Regular expression matching correct attribute names. Overrides attr-naming-
+# style
+#attr-rgx=
+
+# Bad variable names which should always be refused, separated by a comma
+bad-names=foo,
+          bar,
+          baz,
+          toto,
+          tutu,
+          tata
+
+# Naming style matching correct class attribute names
+class-attribute-naming-style=any
+
+# Regular expression matching correct class attribute names. Overrides class-
+# attribute-naming-style
+#class-attribute-rgx=
+
+# Naming style matching correct class names
+class-naming-style=PascalCase
+
+# Regular expression matching correct class names. Overrides class-naming-style
+#class-rgx=
+
+# Naming style matching correct constant names
+const-naming-style=UPPER_CASE
+
+# Regular expression matching correct constant names. Overrides const-naming-
+# style
+#const-rgx=
+
+# Minimum line length for functions/classes that require docstrings, shorter
+# ones are exempt.
+docstring-min-length=-1
+
+# Naming style matching correct function names
+function-naming-style=snake_case
+
+# Regular expression matching correct function names. Overrides function-
+# naming-style
+#function-rgx=
+
+# Good variable names which should always be accepted, separated by a comma
+good-names=i,
+           j,
+           k,
+           ex,
+           Run,
+           _
+
+# Include a hint for the correct naming format with invalid-name
+include-naming-hint=no
+
+# Naming style matching correct inline iteration names
+inlinevar-naming-style=any
+
+# Regular expression matching correct inline iteration names. Overrides
+# inlinevar-naming-style
+#inlinevar-rgx=
+
+# Naming style matching correct method names
+method-naming-style=snake_case
+
+# Regular expression matching correct method names. Overrides method-naming-
+# style
+#method-rgx=
+
+# Naming style matching correct module names
+module-naming-style=snake_case
+
+# Regular expression matching correct module names. Overrides module-naming-
+# style
+#module-rgx=
+
+# Colon-delimited sets of names that determine each other's naming style when
+# the name regexes allow several styles.
+name-group=
+
+# Regular expression which should only match function or class names that do
+# not require a docstring.
+no-docstring-rgx=^_
+
+# List of decorators that produce properties, such as abc.abstractproperty. Add
+# to this list to register other decorators that produce valid properties.
+property-classes=abc.abstractproperty
+
+# Naming style matching correct variable names
+variable-naming-style=snake_case
+
+# Regular expression matching correct variable names. Overrides variable-
+# naming-style
+#variable-rgx=
+
+
+[DESIGN]
+
+# Maximum number of arguments for function / method
+max-args=5
+
+# Maximum number of attributes for a class (see R0902).
+max-attributes=7
+
+# Maximum number of boolean expressions in a if statement
+max-bool-expr=5
+
+# Maximum number of branch for function / method body
+max-branches=12
+
+# Maximum number of locals for function / method body
+max-locals=15
+
+# Maximum number of parents for a class (see R0901).
+max-parents=7
+
+# Maximum number of public methods for a class (see R0904).
+max-public-methods=20
+
+# Maximum number of return / yield for function / method body
+max-returns=6
+
+# Maximum number of statements in function / method body
+max-statements=50
+
+# Minimum number of public methods for a class (see R0903).
+min-public-methods=2
+
+
+[CLASSES]
+
+# List of method names used to declare (i.e. assign) instance attributes.
+defining-attr-methods=__init__,
+                      __new__,
+                      setUp
+
+# List of member names, which should be excluded from the protected access
+# warning.
+exclude-protected=_asdict,
+                  _fields,
+                  _replace,
+                  _source,
+                  _make
+
+# List of valid names for the first argument in a class method.
+valid-classmethod-first-arg=cls
+
+# List of valid names for the first argument in a metaclass class method.
+valid-metaclass-classmethod-first-arg=mcs
+
+
+[IMPORTS]
+
+# Allow wildcard imports from modules that define __all__.
+allow-wildcard-with-all=no
+
+# Analyse import fallback blocks. This can be used to support both Python 2 and
+# 3 compatible code, which means that the block might have code that exists
+# only in one or another interpreter, leading to false positives when analysed.
+analyse-fallback-blocks=no
+
+# Deprecated modules which should not be used, separated by a comma
+deprecated-modules=regsub,
+                   TERMIOS,
+                   Bastion,
+                   rexec
+
+# Create a graph of external dependencies in the given file (report RP0402 must
+# not be disabled)
+ext-import-graph=
+
+# Create a graph of every (i.e. internal and external) dependencies in the
+# given file (report RP0402 must not be disabled)
+import-graph=
+
+# Create a graph of internal dependencies in the given file (report RP0402 must
+# not be disabled)
+int-import-graph=
+
+# Force import order to recognize a module as part of the standard
+# compatibility libraries.
+known-standard-library=
+
+# Force import order to recognize a module as part of a third party library.
+known-third-party=enchant
+
+
+[EXCEPTIONS]
+
+# Exceptions that will emit a warning when being caught. Defaults to
+# "Exception"
+overgeneral-exceptions=Exception

.travis.yml

@@ -1,12 +0,0 @@
-sudo: required
-
-services:
-  - docker
-
-install:
-  - docker build -t tmppilot -f Dockerfile.openpilot .
-
-script:
-  - docker run --rm
-      -v "$(pwd)"/selfdrive/test/tests/plant/out:/tmp/openpilot/selfdrive/test/tests/plant/out
-      tmppilot /bin/sh -c 'cd /tmp/openpilot/selfdrive/test/tests/plant && OPTEST=1 ./test_longitudinal.py'

CONTRIBUTING.md

@@ -2,17 +2,39 @@
 
 Our software is open source so you can solve your own problems without needing help from others. And if you solve a problem and are so kind, you can upstream it for the rest of the world to use.
 
-Most open source development activity is coordinated through our [slack](https://slack.comma.ai). A lot of documentation is available on our [medium](https://medium.com/@comma_ai/)
+Most open source development activity is coordinated through our [Discord](https://discord.comma.ai). A lot of documentation is available on our [medium](https://medium.com/@comma_ai/)
 
 ## Getting Started
 
- * Join our slack [slack.comma.ai](https://slack.comma.ai)
+ * Join our [Discord](https://discord.comma.ai)
  * Make sure you have a [GitHub account](https://github.com/signup/free)
- * Fork the repository on GitHub
+ * Fork [our repositories](https://github.com/commaai) on GitHub
+
+## Testing
+
+### Local Testing
+
+You can test your changes on your machine by running `run_docker_tests.sh`. This will run some automated tests in docker against your code. 
+
+### Automated Testing
+
+All PRs are automatically checked by travis. Check out `.travis.yml` for what travis runs. Any new tests sould be added to travis.
+
+### Code Style and Linting
+
+Code is automatically check for style by travis as part of the automated tests. You can also run these yourself by running `check_code_quality.sh`. 
 
 ## Car Ports (openpilot)
 
-We've released a guide for porting to Toyota cars [here](https://medium.com/@comma_ai/openpilot-port-guide-for-toyota-models-e5467f4b5fe6)
+We've released a [Model Port guide](https://medium.com/@comma_ai/openpilot-port-guide-for-toyota-models-e5467f4b5fe6) for porting to Toyota/Lexus models.
 
-If you port openpilot to a substantially new car, you might be eligible for a bounty. See our bounties at [comma.ai/bounties.html](https://comma.ai/bounties.html)
+If you port openpilot to a substantially new car brand, see this more generic [Brand Port guide](https://medium.com/@comma_ai/how-to-write-a-car-port-for-openpilot-7ce0785eda84). You might also be eligible for a bounty. See our bounties at [comma.ai/bounties.html](https://comma.ai/bounties.html)
 
+## Pull Requests
+
+Pull requests should be against the master branch. Before running master on in-car hardware, you'll need to run
+```
+git submodule init
+git submodule update
+```
+in order to pull down the submodules, such as `panda` and `opendbc`.

Dockerfile.openpilot

@@ -1,19 +1,88 @@
 FROM ubuntu:16.04
 ENV PYTHONUNBUFFERED 1
 
-RUN apt-get update && apt-get install -y build-essential clang vim screen wget bzip2 git libglib2.0-0 python-pip capnproto libcapnp-dev libzmq5-dev libffi-dev libusb-1.0-0
-RUN pip install numpy==1.11.2 scipy==0.18.1 matplotlib
+RUN apt-get update && apt-get install -y \
+    autoconf \
+    build-essential \
+    bzip2 \
+    clang \
+    cmake \
+    curl \
+    ffmpeg \
+    git \
+    libarchive-dev \
+    libbz2-dev \
+    libcurl4-openssl-dev \
+    libeigen3-dev \
+    libffi-dev \
+    libglew-dev \
+    libgles2-mesa-dev \
+    libglfw3-dev \
+    libglib2.0-0 \
+    liblzma-dev \
+    libmysqlclient-dev \
+    libomp-dev \
+    libopencv-dev \
+    libssl-dev \
+    libsqlite3-dev \
+    libtool \
+    libusb-1.0-0-dev \
+    libzmq5-dev \
+    locales \
+    ocl-icd-libopencl1 \
+    ocl-icd-opencl-dev \
+    opencl-headers \
+    python-dev \
+    python-pip \
+    screen \
+    sudo \
+    vim \
+    wget
 
-COPY requirements_openpilot.txt /tmp/
-RUN pip install -r /tmp/requirements_openpilot.txt
 
-ENV PYTHONPATH /tmp/openpilot:$PYTHONPATH
+RUN sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen && locale-gen
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US:en
+ENV LC_ALL en_US.UTF-8
 
+RUN curl -L https://github.com/pyenv/pyenv-installer/raw/master/bin/pyenv-installer | bash
+
+ENV PATH="/root/.pyenv/bin:/root/.pyenv/shims:${PATH}"
+RUN pyenv install 3.7.3
+RUN pyenv global 3.7.3
+RUN pyenv rehash
+
+RUN pip install pipenv==2018.11.26
+
+COPY Pipfile /tmp/
+COPY Pipfile.lock /tmp/
+
+RUN python --version
+RUN cd /tmp && pipenv install --system --deploy
+
+# Install subset of dev dependencies needed for CI
+RUN pip install matplotlib==3.1.1 dictdiffer==0.8.0 fastcluster==1.1.25 aenum==2.2.1 scipy==1.3.1 lru-dict==1.1.6 tenacity==5.1.1 azure-common==1.1.23 azure-nspkg==3.0.2 azure-storage-blob==2.1.0 azure-storage-common==2.1.0 azure-storage-nspkg==3.1.0 pycurl==7.43.0.3
+
+ENV PATH="/tmp/openpilot/external/bin:${PATH}"
+ENV PYTHONPATH /tmp/openpilot:${PYTHONPATH}
+
+RUN mkdir -p /tmp/openpilot
+COPY ./flake8_openpilot.sh /tmp/openpilot/
+COPY ./pylint_openpilot.sh /tmp/openpilot/
+COPY ./.pylintrc /tmp/openpilot/
+
+COPY ./release /tmp/openpilot/release
 COPY ./common /tmp/openpilot/common
 COPY ./cereal /tmp/openpilot/cereal
 COPY ./opendbc /tmp/openpilot/opendbc
 COPY ./selfdrive /tmp/openpilot/selfdrive
 COPY ./phonelibs /tmp/openpilot/phonelibs
 COPY ./pyextra /tmp/openpilot/pyextra
+COPY ./panda /tmp/openpilot/panda
+COPY ./external /tmp/openpilot/external
+COPY ./tools /tmp/openpilot/tools
+
+COPY SConstruct /tmp/openpilot/SConstruct
 
 RUN mkdir -p /tmp/openpilot/selfdrive/test/out
+RUN cd /tmp/openpilot && scons -j$(nproc)

Jenkinsfile

@@ -0,0 +1,23 @@
+pipeline {
+  agent {
+    docker {
+      image 'python:3.7.3'
+      args '--user=root'
+    }
+
+  }
+  stages {
+    stage('EON Build/Test') {
+      steps {
+        lock(resource: "", label: 'eon', inversePrecedence: true, variable: 'eon_name', quantity: 1){
+          timeout(time: 30, unit: 'MINUTES') {
+            dir(path: 'release') {
+              sh 'pip install paramiko'
+              sh 'python remote_build.py'
+            }
+          }
+        }
+      }
+    }
+  }
+}

Makefile

@@ -1,9 +0,0 @@
-
-code_dir := $(shell pwd)
-
-# TODO: Add a global build system
-
-.PHONY: all
-all:
-	cd selfdrive && PYTHONPATH=$(code_dir) PREPAREONLY=1 ./manager.py
-

Pipfile

@@ -0,0 +1,130 @@
+[[source]]
+name = "pypi"
+url = "https://pypi.org/simple"
+verify_ssl = true
+
+[dev-packages]
+opencv-python= "==3.4.2.17"
+PyQt5 = "*"
+ipython = "*"
+networkx = "==2.3"
+azure-core = "==1.1.1"
+azure-common = "==1.1.24"
+azure-nspkg = "==3.0.2"
+azure-storage-blob = "==2.1.0"
+azure-storage-common = "==2.1.0"
+azure-storage-nspkg = "==3.1.0"
+boto = "*"
+"boto3" = "*"
+control = "*"
+datadog = "*"
+dlib = "*"
+elasticsearch = "*"
+future = "*"
+futures = "*"
+pycocotools = {git = "https://github.com/cocodataset/cocoapi.git",subdirectory = "PythonAPI"}
+gunicorn = "*"
+"h5py" = "*"
+hexdump = "*"
+"html5lib" = "*"
+imageio = "*"
+ipykernel = "*"
+joblib = "*"
+json-logging-py = "*"
+jupyter = "*"
+libarchive = "*"
+lru-dict = "*"
+"mpld3" = "*"
+msgpack-python = "*"
+nbstripout = "*"
+numpy = "*"
+osmium = "*"
+pbr = "*"
+percache = "*"
+pprofile = "*"
+pycurl = "*"
+git-pylint-commit-hook = "*"
+pymongo = "*"
+"pynmea2" = "*"
+pypolyline = "*"
+python-logstash = "*"
+redis = "*"
+"s2sphere" = "*"
+scikit-image = "*"
+"subprocess32" = "*"
+tenacity = "*"
+tensorflow-gpu = "==2.0"
+PyJWT = "==1.4.1"
+PyMySQL = "==0.9.2"
+Werkzeug = "*"
+"backports.lzma" = "*"
+Flask-Cors = "*"
+Flask-SocketIO = "*"
+"GeoAlchemy2" = "*"
+Pygments = "*"
+PyNaCl = "*"
+"PySDL2" = "*"
+reverse_geocoder = "*"
+Shapely = "*"
+SQLAlchemy = "*"
+scipy = "*"
+fastcluster = "*"
+backports-abc = "*"
+pygame = "*"
+simplejson = "*"
+python-logstash-async = "*"
+seaborn = "*"
+pyproj = "*"
+mock = "*"
+matplotlib = "*"
+dictdiffer = "*"
+aenum = "*"
+coverage = "*"
+azure-cli-core = "*"
+paramiko = "*"
+aiohttp = "*"
+
+[packages]
+overpy = {git = "https://github.com/commaai/python-overpy.git",ref = "f86529af402d4642e1faeb146671c40284007323"}
+atomicwrites = "*"
+cffi = "*"
+crcmod = "*"
+hexdump = "*"
+libusb1 = "*"
+numpy = "*"
+psutil = "*"
+pycapnp = "*"
+cryptography = "*"
+pyserial = "*"
+python-dateutil = "*"
+pyzmq = "*"
+raven = "*"
+requests = "*"
+setproctitle = "*"
+six = "*"
+smbus2 = "*"
+sympy = "*"
+tqdm = "*"
+Cython = "*"
+PyYAML = "*"
+websocket_client = "*"
+Logentries = {git = "https://github.com/commaai/le_python.git",ref = "feaeacb48f7f4bdb02c0a8fc092326d4e101b7f2"}
+urllib3 = "*"
+chardet = "*"
+idna = "*"
+gunicorn = "*"
+utm = "*"
+json-rpc = "*"
+Flask = "*"
+PyJWT = "*"
+"Jinja2" = "*"
+nose = "*"
+flake8 = "*"
+pylint = "*"
+pycryptodome = "*"
+pillow = "*"
+scons = "*"
+cysignals = "*"
+
+[requires]
+python_version = "3.7.3"

README.md

@@ -1,193 +1,306 @@
-Welcome to openpilot
-======
+[![](https://i.imgur.com/UelUjKAh.png)](#)
 
-[openpilot](http://github.com/commaai/openpilot) is an open source driving agent.
+Table of Contents
+=======================
 
-Currently it performs the functions of Adaptive Cruise Control (ACC) and Lane Keeping Assist System (LKAS) for Hondas, Acuras and Toyotas. It's about on par with Tesla Autopilot at launch, and better than [all other manufacturers](http://www.thedrive.com/tech/5707/the-war-for-autonomous-driving-part-iii-us-vs-germany-vs-japan).
+* [What is openpilot?](#what-is-openpilot)
+* [Integration with Stock Features](#integration-with-stock-features)
+* [Supported Hardware](#supported-hardware)
+* [Supported Cars](#supported-cars)
+* [Community Maintained Cars and Features](#community-maintained-cars-and-features)
+* [Installation Instructions](#installation-instructions)
+* [Limitations of openpilot ALC and LDW](#limitations-of-openpilot-alc-and-ldw)
+* [Limitations of openpilot ACC and FCW](#limitations-of-openpilot-acc-and-fcw)
+* [Limitations of openpilot DM](#limitations-of-openpilot-dm)
+* [User Data and comma Account](#user-data-and-comma-account)
+* [Safety and Testing](#safety-and-testing)
+* [Testing on PC](#testing-on-pc)
+* [Community and Contributing](#community-and-contributing)
+* [Directory Structure](#directory-structure)
+* [Licensing](#licensing)
 
-The openpilot codebase has been written to be concise and enable rapid prototyping. We look forward to your contributions - improving real vehicle automation has never been easier.
+---
 
-Here are [some](https://www.youtube.com/watch?v=9OwTJFuDI7g) [videos](https://www.youtube.com/watch?v=64Wvt5pYQmE) [of](https://www.youtube.com/watch?v=6IW7Nejsr3A) [it](https://www.youtube.com/watch?v=-VN1YcC83nA) [running](https://www.youtube.com/watch?v=EQJZvVeihZk). And a really cool [tutorial](https://www.youtube.com/watch?v=PwOnsT2UW5o).
-
-Community
+What is openpilot?
 ------
 
-openpilot is supported by [comma.ai](https://comma.ai/)
+[openpilot](http://github.com/commaai/openpilot) is an open source driver assistance system. Currently, openpilot performs the functions of Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW) and Lane Departure Warning (LDW) for a growing variety of supported [car makes, models and model years](#supported-cars). In addition, while openpilot is engaged, a camera based Driver Monitoring (DM) feature alerts distracted and asleep drivers.
 
-We have a [Twitter you should follow](https://twitter.com/comma_ai).
+<table>
+  <tr>
+    <td><a href="https://www.youtube.com/watch?v=mgAbfr42oI8" title="YouTube" rel="noopener"><img src="https://i.imgur.com/kAtT6Ei.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=394rJKeh76k" title="YouTube" rel="noopener"><img src="https://i.imgur.com/lTt8cS2.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=1iNOc3cq8cs" title="YouTube" rel="noopener"><img src="https://i.imgur.com/ANnuSpe.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=Vr6NgrB-zHw" title="YouTube" rel="noopener"><img src="https://i.imgur.com/Qypanuq.png"></a></td>
+  </tr>
+  <tr>
+    <td><a href="https://www.youtube.com/watch?v=Ug41KIKF0oo" title="YouTube" rel="noopener"><img src="https://i.imgur.com/3caZ7xM.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=NVR_CdG1FRg" title="YouTube" rel="noopener"><img src="https://i.imgur.com/bAZOwql.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=tkEvIdzdfUE" title="YouTube" rel="noopener"><img src="https://i.imgur.com/EFINEzG.png"></a></td>
+    <td><a href="https://www.youtube.com/watch?v=_P-N1ewNne4" title="YouTube" rel="noopener"><img src="https://i.imgur.com/gAyAq22.png"></a></td>
+  </tr>
+</table>
 
-Also, we have a 3500+ person [community on slack](https://slack.comma.ai).
-
-Hardware
+Integration with Stock Features
 ------
 
-Right now openpilot supports the [EON Dashcam DevKit](https://shop.comma.ai/products/eon-dashcam-devkit). We'd like to support other platforms as well.
+In all supported cars:
+* Stock Lane Keep Assist (LKA) and stock ALC are replaced by openpilot ALC, which only functions when openpilot is engaged by the user.
+* Stock LDW is replaced by openpilot LDW.
 
-Install openpilot on a neo device by entering ``https://openpilot.comma.ai`` during NEOS setup.
+Additionally, on specific supported cars (see ACC column in [supported cars](#supported-cars)):
+* Stock ACC is replaced by openpilot ACC.
+* openpilot FCW operates in addition to stock FCW.
+
+openpilot should preserve all other vehicle's stock features, including, but are not limited to: FCW, Automatic Emergency Braking (AEB), auto high-beam, blind spot warning, and side collision warning.
+
+Supported Hardware
+------
+
+At the moment, openpilot supports the [EON DevKit](https://comma.ai/shop/products/eon-dashcam-devkit) and the [comma two](https://comma.ai/shop/products/comma-two-devkit). A [car harness](https://comma.ai/shop/products/car-harness) is recommended to connect the EON or comma two to the car. In the future, we'd like to support other platforms as well, like gaming PCs.
 
 Supported Cars
 ------
 
-### Honda + Acura ###
+| Make      | Model (US Market Reference)   | Supported Package | ACC              | No ACC accel below | No ALC below |
+| ----------| ------------------------------| ------------------| -----------------| -------------------| -------------|
+| Acura     | ILX 2016-18                   | AcuraWatch Plus   | openpilot        | 25mph<sup>5</sup>  | 25mph        |
+| Acura     | RDX 2016-18                   | AcuraWatch Plus   | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Chrysler  | Pacifica 2017-18              | Adaptive Cruise   | Stock            | 0mph               | 9mph         |
+| Chrysler  | Pacifica Hybrid 2017-18       | Adaptive Cruise   | Stock            | 0mph               | 9mph         |
+| Chrysler  | Pacifica Hybrid 2019-20       | Adaptive Cruise   | Stock            | 0mph               | 39mph        |
+| Honda     | Accord 2018-19                | All               | Stock            | 0mph               | 3mph         |
+| Honda     | Accord Hybrid 2018-19         | All               | Stock            | 0mph               | 3mph         |
+| Honda     | Civic Hatchback 2017-19       | Honda Sensing     | Stock            | 0mph               | 12mph        |
+| Honda     | Civic Sedan/Coupe 2016-18     | Honda Sensing     | openpilot        | 0mph               | 12mph        |
+| Honda     | Civic Sedan/Coupe 2019        | Honda Sensing     | Stock            | 0mph               | 2mph         |
+| Honda     | CR-V 2015-16                  | Touring           | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Honda     | CR-V 2017-19                  | Honda Sensing     | Stock            | 0mph               | 12mph        |
+| Honda     | CR-V Hybrid 2017-2019         | Honda Sensing     | Stock            | 0mph               | 12mph        |
+| Honda     | Fit 2018-19                   | Honda Sensing     | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Honda     | Odyssey 2018-20               | Honda Sensing     | openpilot        | 25mph<sup>5</sup>  | 0mph         |
+| Honda     | Passport 2019                 | All               | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Honda     | Pilot 2016-18                 | Honda Sensing     | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Honda     | Pilot 2019                    | All               | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Honda     | Ridgeline 2017-19             | Honda Sensing     | openpilot        | 25mph<sup>5</sup>  | 12mph        |
+| Hyundai   | Elantra 2017-19<sup>1</sup>   | SCC + LKAS        | Stock            | 19mph              | 34mph        |
+| Hyundai   | Genesis 2018<sup>1</sup>      | All               | Stock            | 19mph              | 34mph        |
+| Hyundai   | Santa Fe 2019<sup>1</sup>     | All               | Stock            | 0mph               | 0mph         |
+| Jeep      | Grand Cherokee 2016-18        | Adaptive Cruise   | Stock            | 0mph               | 9mph         |
+| Jeep      | Grand Cherokee 2019           | Adaptive Cruise   | Stock            | 0mph               | 39mph        |
+| Kia       | Optima 2019<sup>1</sup>       | SCC + LKAS        | Stock            | 0mph               | 0mph         |
+| Kia       | Sorento 2018<sup>1</sup>      | All               | Stock            | 0mph               | 0mph         |
+| Kia       | Stinger 2018<sup>1</sup>      | SCC + LKAS        | Stock            | 0mph               | 0mph         |
+| Lexus     | CT Hybrid 2017-18             | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Lexus     | ES 2019                       | All               | openpilot        | 0mph               | 0mph         |
+| Lexus     | ES Hybrid 2019                | All               | openpilot        | 0mph               | 0mph         |
+| Lexus     | IS 2017-2019                  | All               | Stock            | 22mph              | 0mph         |
+| Lexus     | IS Hybrid 2017                | All               | Stock            | 0mph               | 0mph         |
+| Lexus     | RX 2016-17                    | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Lexus     | RX 2020                       | All               | openpilot        | 0mph               | 0mph         |
+| Lexus     | RX Hybrid 2016-19             | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Subaru    | Crosstrek 2018-19             | EyeSight          | Stock            | 0mph               | 0mph         |
+| Subaru    | Impreza 2019-20               | EyeSight          | Stock            | 0mph               | 0mph         |
+| Toyota    | Avalon 2016                   | TSS-P             | Stock<sup>4</sup>| 20mph<sup>5</sup>  | 0mph         |
+| Toyota    | Avalon 2017-18                | All               | Stock<sup>4</sup>| 20mph<sup>5</sup>  | 0mph         |
+| Toyota    | Camry 2018-19                 | All               | Stock            | 0mph<sup>2</sup>   | 0mph         |
+| Toyota    | Camry Hybrid 2018-19          | All               | Stock            | 0mph<sup>2</sup>   | 0mph         |
+| Toyota    | C-HR 2017-19                  | All               | Stock            | 0mph               | 0mph         |
+| Toyota    | C-HR Hybrid 2017-19           | All               | Stock            | 0mph               | 0mph         |
+| Toyota    | Corolla 2017-19               | All               | Stock<sup>4</sup>| 20mph<sup>5</sup>  | 0mph         |
+| Toyota    | Corolla 2020                  | All               | openpilot        | 0mph               | 0mph         |
+| Toyota    | Corolla Hatchback 2019-20     | All               | openpilot        | 0mph               | 0mph         |
+| Toyota    | Corolla Hybrid 2020           | All               | openpilot        | 0mph               | 0mph         |
+| Toyota    | Highlander 2017-19            | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Highlander Hybrid 2017-19     | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Prius 2016                    | TSS-P             | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Prius 2017-19                 | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Prius Prime 2017-20           | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Rav4 2016                     | TSS-P             | Stock<sup>4</sup>| 20mph<sup>5</sup>  | 0mph         |
+| Toyota    | Rav4 2017-18                  | All               | Stock<sup>4</sup>| 20mph<sup>5</sup>  | 0mph         |
+| Toyota    | Rav4 2019                     | All               | openpilot        | 0mph               | 0mph         |
+| Toyota    | Rav4 Hybrid 2016              | TSS-P             | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Rav4 Hybrid 2017-18           | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Toyota    | Rav4 Hybrid 2019-20           | All               | openpilot        | 0mph               | 0mph         |
+| Toyota    | Sienna 2018                   | All               | Stock<sup>4</sup>| 0mph               | 0mph         |
+| Volkswagen| Golf 2016-19<sup>3</sup>      | Driver Assistance | Stock            | 0mph               | 0mph         |
 
-- Honda Accord 2018 with Honda Sensing (alpha!)
-  - Uses stock Honda Sensing for longitudinal control
+<sup>1</sup>Requires a [panda](https://comma.ai/shop/products/panda-obd-ii-dongle) and open sourced [Hyundai giraffe](https://github.com/commaai/neo/tree/master/giraffe/hyundai), designed for the 2019 Sante Fe; pinout may differ for other Hyundai and Kia models. <br />
+<sup>2</sup>28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control. <br />
+<sup>3</sup>Requires a [custom connector](https://community.comma.ai/wiki/index.php/Volkswagen#Integration_at_R242_Camera) for the [car harness](https://comma.ai/shop/products/car-harness) <br />
 
-- Honda Civic 2016+ with Honda Sensing
-  - Due to limitations in steering firmware, steering is disabled below 12 mph
-  - Note that the hatchback model is not supported
-
-- Honda Civic Hatchback 2017+ with Honda Sensing (alpha!)
-  - Due to limitations in steering firmware, steering is disabled below 12 mph
-  - Uses stock Honda Sensing for longitudinal control
-
-- Honda CR-V 2017-2018 with Honda Sensing (alpha!)
-  - Due to limitations in steering firmware, steering is disabled below 12 mph
-  - Uses stock Honda Sensing for longitudinal control
-
-- Honda CR-V Touring 2015-2016
-  - Can only be enabled above 25 mph
-
-- Honda Odyssey 2018 with Honda Sensing (alpha!)
-  - Can only be enabled above 25 mph
-
-- Honda Pilot 2017 with Honda Sensing (alpha!)
-  - Can only be enabled above 27 mph
-
-- Honda Ridgeline 2017 with Honda Sensing (alpha!)
-  - Can only be enabled above 27 mph
-
-- Acura ILX 2016 with AcuraWatch Plus
-  - Due to use of the cruise control for gas, it can only be enabled above 25 mph
-
-- Acura RDX 2018 with AcuraWatch Plus (alpha!)
-  - Can only be enabled above 25 mph
-
-### Toyota + Lexus ###
-
-- Toyota RAV-4 2016+ non-hybrid with TSS-P
-  - By default it uses stock Toyota ACC for longitudinal control
-  - openpilot longitudinal control available after unplugging the [Driving Support ECU](https://community.comma.ai/wiki/index.php/Toyota#Rav4_.28for_openpilot.29) and can be enabled above 20 mph
-
-- Toyota Prius 2017+
-  - By default it uses stock Toyota ACC for longitudinal control
-  - openpilot longitudinal control available after unplugging the [Driving Support ECU](https://community.comma.ai/wiki/index.php/Toyota#Prius_.28for_openpilot.29)
-  - Lateral control needs improvements
-
-- Toyota RAV-4 2017+ hybrid
-  - By default it uses stock Toyota ACC for longitudinal control
-  - openpilot longitudinal control available after unplugging the [Driving Support ECU](https://community.comma.ai/wiki/index.php/Toyota#Rav4_.28for_openpilot.29) and can do stop and go
-
-- Toyota Corolla 2017+
-  - By default it uses stock Toyota ACC for longitudinal control
-  - openpilot longitudinal control available after unplugging the [Driving Support ECU](https://community.comma.ai/wiki/index.php/Toyota#Corolla_.28for_openpilot.29) and can be enabled above 20 mph
-
-- Lexus RX 2017+ hybrid (alpha!)
-  - By default it uses stock Lexus ACC for longitudinal control
-  - openpilot longitudinal control available after unplugging the [Driving Support ECU](https://community.comma.ai/wiki/index.php/Toyota#Lexus_RX_hybrid)
-
-### GM (Chevrolet + Cadillac) ###
-
-- Chevrolet Volt Premier 2017+
-  - Driver Confidence II package (adaptive cruise control) required
-  - Can only be enabled above 18 mph
-  - Read the [installation guide](https://www.zoneos.com/volt.htm)
-
-- Cadillac CT6
-  - Uses stock ACC for longitudinal control
-  - Requires multiple panda for proxying the ASCMs
-
-In Progress Cars
-------
-- All TSS-P Toyota with Steering Assist.
-  - 'Full Speed Range Dynamic Radar Cruise Control' is required to enable stop-and-go. Only the Prius, Camry and C-HR have this option.
-  - Even though the Tundra, Sequoia and the Land Cruiser have TSS-P, they don't have Steering Assist and are not supported.
-- All LSS-P Lexus with Steering Assist or Lane Keep Assist.
-  - 'All-Speed Range Dynamic Radar Cruise Control' is required to enable stop-and-go. Only the GS, GSH, GS, F, RX, RXH, LX, NX, NXH, LC, LCH, LS, LSH have this option.
-  - Even though the LX have TSS-P, it does not have Steering Assist and is not supported.
-
-Community Maintained Cars
+Community Maintained Cars and Features
 ------
 
-- [Classic Tesla Model S (pre-AP)](https://github.com/commaai/openpilot/pull/246)
+| Make      | Model (US Market Reference)   | Supported Package | ACC              | No ACC accel below | No ALC below |
+| ----------| ------------------------------| ------------------| -----------------| -------------------| -------------|
+| Buick     | Regal 2018<sup>6</sup>        | Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
+| Cadillac  | ATS 2018<sup>6</sup>          | Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
+| Chevrolet | Malibu 2017<sup>6</sup>       | Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
+| Chevrolet | Volt 2017-18<sup>6</sup>      | Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
+| GMC       | Acadia Denali 2018<sup>6</sup>| Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
+| Holden    | Astra 2017<sup>6</sup>        | Adaptive Cruise   | openpilot        | 0mph               | 7mph         |
 
-How can I add support for my car?
+<sup>4</sup>When disconnecting the Driver Support Unit (DSU), openpilot ACC will replace stock ACC. For DSU locations, see [Toyota Wiki page](https://community.comma.ai/wiki/index.php/Toyota). ***NOTE: disconnecting the DSU disables Automatic Emergency Braking (AEB).*** <br />
+<sup>5</sup>[Comma Pedal](https://community.comma.ai/wiki/index.php/Comma_Pedal) is used to provide stop-and-go capability to some of the openpilot-supported cars that don't currently support stop-and-go. Here is how to [build a Comma Pedal](https://medium.com/@jfrux/comma-pedal-building-with-macrofab-6328bea791e8). ***NOTE: The Comma Pedal is not officially supported by [comma](https://comma.ai).*** <br />
+<sup>6</sup>Requires a [panda](https://comma.ai/shop/products/panda-obd-ii-dongle) and [community built giraffe](https://zoneos.com/volt/). ***NOTE: disconnecting the ASCM disables Automatic Emergency Braking (AEB).*** <br />
+
+Community Maintained Cars and Features are not verified by comma to meet our [safety model](SAFETY.md). Be extra cautious using them. They are only available after enabling the toggle in `Settings->Developer->Enable Community Features`.
+
+Installation Instructions
 ------
 
-If your car has adaptive cruise control and lane keep assist, you are in luck. Using a [panda](https://panda.comma.ai) and [cabana](https://community.comma.ai/cabana/), you can understand how to make your car drive by wire.
+Install openpilot on a EON by entering ``https://openpilot.comma.ai`` during the installer setup.
 
-We've written a [porting guide](https://medium.com/@comma_ai/openpilot-port-guide-for-toyota-models-e5467f4b5fe6) for Toyota that might help you after you have the basics figured out.
+Follow this [video instructions](https://youtu.be/3nlkomHathI) to properly mount the EON on the windshield. Note: openpilot features an automatic pose calibration routine and openpilot performance should not be affected by small pitch and yaw misalignments caused by imprecise EON mounting.
 
-Sadly, BMW, Audi, Volvo, and Mercedes all use [FlexRay](https://en.wikipedia.org/wiki/FlexRay) and are unlikely to be supported any time soon. We also put time into a Ford port, but the steering has a 10 second cutout limitation that makes it unusable.
+Before placing the device on your windshield, check the state and local laws and ordinances where you drive. Some state laws prohibit or restrict the placement of objects on the windshield of a motor vehicle.
 
-Directory structure
+You will be able to engage openpilot after reviewing the onboarding screens and finishing the calibration procedure.
+
+Limitations of openpilot ALC and LDW
 ------
 
-- cereal        -- The messaging spec used for all logs on the phone
-- common        -- Library like functionality we've developed here
-- opendbc       -- Files showing how to interpret data from cars
-- panda         -- Code used to communicate on CAN and LIN
-- phonelibs     -- Libraries used on the phone
-- selfdrive     -- Code needed to drive the car
-  - assets        -- Fonts for ui
-  - boardd        -- Daemon to talk to the board
-  - car           -- Code that talks to the car and implements CarInterface
-  - common        -- Shared C/C++ code for the daemons
-  - controls      -- Python controls (PID loops etc) for the car
-  - debug         -- Tools to help you debug and do car ports
-  - logcatd       -- Android logcat as a service
-  - loggerd       -- Logger and uploader of car data
-  - orbd          -- Service generating ORB features from road camera
-  - proclogd      -- Logs information from proc
-  - sensord       -- IMU / GPS interface code
-  - test/plant    -- Car simulator running code through virtual maneuvers
-  - ui            -- The UI
-  - visiond       -- embedded vision pipeline
+openpilot ALC and openpilot LDW do not automatically drive the vehicle or reduce the amount of attention that must be paid to operate your vehicle. The driver must always keep control of the steering wheel and be ready to correct the openpilot ALC action at all times.
 
-To understand how the services interact, see `selfdrive/service_list.yaml`
+While changing lanes, openpilot is not capable of looking next to you or checking your blind spot. Only nudge the wheel to initiate a lane change after you have confirmed it's safe to do so.
+
+Many factors can impact the performance of openpilot ALC and openpilot LDW, causing them to be unable to function as intended. These include, but are not limited to:
+
+* Poor visibility (heavy rain, snow, fog, etc.) or weather conditions that may interfere with sensor operation.
+* The road facing camera is obstructed, covered or damaged by mud, ice, snow, etc.
+* Obstruction caused by applying excessive paint or adhesive products (such as wraps, stickers, rubber coating, etc.) onto the vehicle.
+* The EON is mounted incorrectly.
+* When in sharp curves, like on-off ramps, intersections etc...; openpilot is designed to be limited in the amount of steering torque it can produce.
+* In the presence of restricted lanes or construction zones.
+* When driving on highly banked roads or in presence of strong cross-wind.
+* Extremely hot or cold temperatures.
+* Bright light (due to oncoming headlights, direct sunlight, etc.).
+* Driving on hills, narrow, or winding roads.
+
+The list above does not represent an exhaustive list of situations that may interfere with proper operation of openpilot components. It is the driver's responsibility to be in control of the vehicle at all times.
+
+Limitations of openpilot ACC and FCW
+------
+
+openpilot ACC and openpilot FCW are not systems that allow careless or inattentive driving. It is still necessary for the driver to pay close attention to the vehicle’s surroundings and to be ready to re-take control of the gas and the brake at all times.
+
+Many factors can impact the performance of openpilot ACC and openpilot FCW, causing them to be unable to function as intended. These include, but are not limited to:
+
+* Poor visibility (heavy rain, snow, fog, etc.) or weather conditions that may interfere with sensor operation.
+* The road facing camera or radar are obstructed, covered, or damaged by mud, ice, snow, etc.
+* Obstruction caused by applying excessive paint or adhesive products (such as wraps, stickers, rubber coating, etc.) onto the vehicle.
+* The EON is mounted incorrectly.
+* Approaching a toll booth, a bridge or a large metal plate.
+* When driving on roads with pedestrians, cyclists, etc...
+* In presence of traffic signs or stop lights, which are not detected by openpilot at this time.
+* When the posted speed limit is below the user selected set speed. openpilot does not detect speed limits at this time.
+* In presence of vehicles in the same lane that are not moving.
+* When abrupt braking maneuvers are required. openpilot is designed to be limited in the amount of deceleration and acceleration that it can produce.
+* When surrounding vehicles perform close cut-ins from neighbor lanes.
+* Driving on hills, narrow, or winding roads.
+* Extremely hot or cold temperatures.
+* Bright light (due to oncoming headlights, direct sunlight, etc.).
+* Interference from other equipment that generates radar waves.
+
+The list above does not represent an exhaustive list of situations that may interfere with proper operation of openpilot components. It is the driver's responsibility to be in control of the vehicle at all times.
+
+Limitations of openpilot DM
+------
+
+openpilot DM should not be considered an exact measurements of the status of alertness of the driver.
+
+Many factors can impact the performance of openpilot DM, causing it to be unable to function as intended. These include, but are not limited to:
+
+* Low light conditions, such as driving at night or in dark tunnels.
+* Bright light (due to oncoming headlights, direct sunlight, etc.).
+* The driver face is partially or completely outside field of view of the driver facing camera.
+* Right hand driving vehicles.
+* The driver facing camera is obstructed, covered, or damaged.
+
+The list above does not represent an exhaustive list of situations that may interfere with proper operation of openpilot components. A driver should not rely on openpilot DM to assess their level of attention.
+
+User Data and comma Account
+------
+
+By default, openpilot uploads the driving data to our servers. You can also access your data by pairing with the comma connect app ([iOS](https://apps.apple.com/us/app/comma-connect/id1456551889), [Android](https://play.google.com/store/apps/details?id=ai.comma.connect&hl=en_US)). We use your data to train better models and improve openpilot for everyone.
+
+openpilot is open source software: the user is free to disable data collection if they wish to do so.
+
+openpilot logs the road facing camera, CAN, GPS, IMU, magnetometer, thermal sensors, crashes, and operating system logs.
+The driver facing camera is only logged if you explicitly opt-in in settings. The microphone is not recorded.
+
+By using openpilot, you agree to [our Privacy Policy](https://my.comma.ai/privacy). You understand that use of this software or its related services will generate certain types of user data, which may be logged and stored at the sole discretion of comma. By accepting this agreement, you grant an irrevocable, perpetual, worldwide right to comma for the use of this data.
+
+Safety and Testing
+----
+
+* openpilot observes ISO26262 guidelines, see [SAFETY.md](SAFETY.md) for more detail.
+* openpilot has software in the loop [tests](run_docker_tests.sh) that run on every commit.
+* The safety model code lives in panda and is written in C, see [code rigor](https://github.com/commaai/panda#code-rigor) for more details.
+* panda has software in the loop [safety tests](https://github.com/commaai/panda/tree/master/tests/safety).
+* Internally, we have a hardware in the loop Jenkins test suite that builds and unit tests the various processes.
+* panda has additional hardware in the loop [tests](https://github.com/commaai/panda/blob/master/Jenkinsfile).
+* We run the latest openpilot in a testing closet containing 10 EONs continuously replaying routes.
 
 Testing on PC
 ------
 
-There is rudimentary infrastructure to run a basic simulation and generate a report of openpilot's behavior in different scenarios.
+Check out the tools directory in master: lots of tools you can use to replay driving data, test and develop openpilot from your pc.
 
-```bash
-# Requires working docker
-./run_docker_tests.sh
-```
-
-The results are written to `selfdrive/test/plant/out/index.html`
-
-More extensive testing infrastructure and simulation environments are coming soon.
-
-User Data / chffr Account / Crash Reporting
+Community and Contributing
 ------
 
-By default openpilot creates an account and includes a client for chffr, our dashcam app. We use your data to train better models and improve openpilot for everyone.
+openpilot is developed by [comma](https://comma.ai/) and by users like you. We welcome both pull requests and issues on [GitHub](http://github.com/commaai/openpilot). Bug fixes and new car ports are encouraged.
 
-It's open source software, so you are free to disable it if you wish.
+You can add support for your car by following guides we have written for [Brand](https://medium.com/@comma_ai/how-to-write-a-car-port-for-openpilot-7ce0785eda84) and [Model](https://medium.com/@comma_ai/openpilot-port-guide-for-toyota-models-e5467f4b5fe6) ports. Generally, a car with adaptive cruise control and lane keep assist is a good candidate. [Join our Discord](https://discord.comma.ai) to discuss car ports: most car makes have a dedicated channel.
 
-It logs the road facing camera, CAN, GPS, IMU, magnetometer, thermal sensors, crashes, and operating system logs.
-It does not log the user facing camera or the microphone.
+Want to get paid to work on openpilot? [comma is hiring](https://comma.ai/jobs/). We also have a [bounty program](https://comma.ai/bounties.html).
 
-By using it, you agree to [our privacy policy](https://beta.comma.ai/privacy.html). You understand that use of this software or its related services will generate certain types of user data, which may be logged and stored at the sole discretion of comma.ai. By accepting this agreement, you grant an irrevocable, perpetual, worldwide right to comma.ai for the use of this data.
+And [follow us on Twitter](https://twitter.com/comma_ai).
 
-Contributing
+Directory Structure
 ------
+    .
+    ├── apk                 # The apk files used for the UI
+    ├── cereal              # The messaging spec and libs used for all logs on EON
+    ├── common              # Library like functionality we've developed here
+    ├── installer/updater   # Manages auto-updates of openpilot
+    ├── opendbc             # Files showing how to interpret data from cars
+    ├── panda               # Code used to communicate on CAN
+    ├── phonelibs           # Libraries used on EON
+    ├── pyextra             # Libraries used on EON
+    └── selfdrive           # Code needed to drive the car
+        ├── assets          # Fonts and images for UI
+        ├── athena          # Allows communication with the app
+        ├── boardd          # Daemon to talk to the board
+        ├── camerad         # Driver to capture images from the camera sensors
+        ├── car             # Car specific code to read states and control actuators
+        ├── common          # Shared C/C++ code for the daemons
+        ├── controls        # Perception, planning and controls
+        ├── debug           # Tools to help you debug and do car ports
+        ├── locationd       # Soon to be home of precise location
+        ├── logcatd         # Android logcat as a service
+        ├── loggerd         # Logger and uploader of car data
+        ├── modeld          # Driving and monitoring model runners
+        ├── proclogd        # Logs information from proc
+        ├── sensord         # IMU / GPS interface code
+        ├── tests           # Unit tests, system tests and a car simulator
+        └── ui              # The UI
 
-We welcome both pull requests and issues on
-[github](http://github.com/commaai/openpilot). See the TODO file for a list of
-good places to start.
-
-Want to get paid to work on openpilot? [comma.ai is hiring](http://comma.ai/positions.html)
+To understand how the services interact, see `cereal/service_list.yaml`.
 
 Licensing
 ------
 
 openpilot is released under the MIT license. Some parts of the software are released under other licenses as specified.
 
-Any user of this software shall indemnify and hold harmless Comma.ai, Inc. and its directors, officers, employees, agents, stockholders, affiliates, subcontractors and customers from and against all allegations, claims, actions, suits, demands, damages, liabilities, obligations, losses, settlements, judgments, costs and expenses (including without limitation attorneys’ fees and costs) which arise out of, relate to or result from any use of this software by user.
+Any user of this software shall indemnify and hold harmless comma.ai, Inc. and its directors, officers, employees, agents, stockholders, affiliates, subcontractors and customers from and against all allegations, claims, actions, suits, demands, damages, liabilities, obligations, losses, settlements, judgments, costs and expenses (including without limitation attorneys’ fees and costs) which arise out of, relate to or result from any use of this software by user.
 
 **THIS IS ALPHA QUALITY SOFTWARE FOR RESEARCH PURPOSES ONLY. THIS IS NOT A PRODUCT.
 YOU ARE RESPONSIBLE FOR COMPLYING WITH LOCAL LAWS AND REGULATIONS.
 NO WARRANTY EXPRESSED OR IMPLIED.**
+
+---
+
+<img src="https://d1qb2nb5cznatu.cloudfront.net/startups/i/1061157-bc7e9bf3b246ece7322e6ffe653f6af8-medium_jpg.jpg?buster=1458363130" width="75"></img> <img src="https://cdn-images-1.medium.com/max/1600/1*C87EjxGeMPrkTuVRVWVg4w.png" width="225"></img>

README_chffrplus.md

@@ -1,36 +0,0 @@
-Welcome to chffrplus
-======
-
-[chffrplus](https://github.com/commaai/chffrplus) is an open source dashcam.
-
-This is the shipping reference software for the comma EON Dashcam DevKit. It keeps many of the niceities of [openpilot](https://github.com/commaai/openpilot), like high quality sensors, great camera, and good autostart and stop. Though unlike openpilot, it cannot control your car. chffrplus can interface with your car through a [panda](https://shop.comma.ai/products/panda-obd-ii-dongle), but just like our dashcam app [chffr](https://getchffr.com/), it is read only.
-
-It integrates with the rest of the comma ecosystem, so you can view your drives on the [chffr](https://getchffr.com/) app for Android or iOS, and reverse engineer your car with [cabana](https://community.comma.ai/cabana/?demo=1).
-
-
-Hardware
-------
-
-Right now chffrplus supports the [EON Dashcam DevKit](https://shop.comma.ai/products/eon-dashcam-devkit) for hardware to run on.
-
-Install chffrplus on a EON device by entering ``https://chffrplus.comma.ai`` during NEOS setup.
-
-
-User Data / chffr Account / Crash Reporting
-------
-
-By default chffrplus creates an account and includes a client for chffr, our dashcam app.
-
-It's open source software, so you are free to disable it if you wish. 
-
-It logs the road facing camera, CAN, GPS, IMU, magnetometer, thermal sensors, crashes, and operating system logs.
-It does not log the user facing camera or the microphone.
-
-By using it, you agree to [our privacy policy](https://beta.comma.ai/privacy.html). You understand that use of this software or its related services will generate certain types of user data, which may be logged and stored at the sole discretion of comma.ai. By accepting this agreement, you grant an irrevocable, perpetual, worldwide right to comma.ai for the use of this data.
-
-
-Licensing
-------
-
-chffrplus is released under the MIT license.
-

RELEASES.md

@@ -1,3 +1,271 @@
+Version 0.7.2 (2020-02-07)
+========================
+ * ECU firmware version based fingerprinting for Honda & Toyota
+ * New driving model: improved path prediction during turns and lane changes and better lead speed tracking
+ * Improve driver monitoring under extreme lighting and add low accuracy alert
+ * Support for 2019 Rav4 Hybrid thanks to illumiN8i!
+ * Support for 2016, 2017 and 2020 Lexus RX thanks to illumiN8i!
+ * Support for 2020 Chrysler Pacifica Hybrid thanks to adhintz!
+
+Version 0.7.1 (2020-01-20)
+========================
+ * comma two support!
+ * Lane Change Assist above 45 mph!
+ * Replace zmq with custom messaging library, msgq!
+ * Supercombo model: calibration and driving models are combined for better lead estimate
+ * More robust updater thanks to jyoung8607! Requires NEOS update
+ * Improve low speed ACC tuning
+
+Version 0.7 (2019-12-13)
+========================
+ * Move to SCons build system!
+ * Add Lane Departure Warning (LDW) for all supported vehicles!
+ * NEOS update: increase wifi speed thanks to jyoung8607!
+ * Adaptive driver monitoring based on scene
+ * New driving model trained end-to-end: improve lane lines and lead detection
+ * Smarter torque limit alerts for all cars
+ * Improve GM longitudinal control: proper computations for 15Hz radar
+ * Move GM port, Toyota with DSU removed, comma pedal in community features; toggle switch required
+ * Remove upload over cellular toggle: only upload qlog and qcamera files if not on wifi
+ * Refactor Panda code towards ISO26262 and SIL2 compliancy
+ * Forward stock FCW for Honda Nidec
+ * Volkswagen port now standard: comma Harness intercepts stock camera
+
+Version 0.6.6 (2019-11-05)
+========================
+ * Volkswagen support thanks to jyoung8607!
+ * Toyota Corolla Hybrid with TSS 2.0 support thanks to u8511049!
+ * Lexus ES with TSS 2.0 support thanks to energee!
+ * Fix GM ignition detection and lock safety mode not required anymore
+ * Log panda firmware and dongle ID thanks to martinl!
+ * New driving model: improve path prediction and lead detection
+ * New driver monitoring model, 4x smaller and running on DSP
+ * Display an alert and don't start openpilot if panda has wrong firmware
+ * Fix bug preventing EON from terminating processes after a drive
+ * Remove support for Toyota giraffe without the 120Ohm resistor
+
+Version 0.6.5 (2019-10-07)
+========================
+ * NEOS update: upgrade to Python3 and new installer!
+ * comma Harness support!
+ * New driving model: improve path prediction
+ * New driver monitoring model: more accurate face and eye detection
+ * Redesign offroad screen to display updates and alerts
+ * Increase maximum allowed acceleration
+ * Prevent car 12V battery drain by cutting off EON charge after 3 days of no drive
+ * Lexus CT Hybrid support thanks to thomaspich!
+ * Louder chime for critical alerts
+ * Add toggle to switch to dashcam mode
+ * Fix "invalid vehicle params" error on DSU-less Toyota
+
+Version 0.6.4 (2019-09-08)
+========================
+ * Forward stock AEB for Honda Nidec
+ * Improve lane centering on banked roads
+ * Always-on forward collision warning
+ * Always-on driver monitoring, except for right hand drive countries
+ * Driver monitoring learns the user's normal driving position
+ * Honda Fit support thanks to energee!
+ * Lexus IS support
+
+Version 0.6.3 (2019-08-12)
+========================
+ * Alert sounds from EON: requires NEOS update
+ * Improve driver monitoring: eye tracking and improved awareness logic
+ * Improve path prediction with new driving model
+ * Improve lane positioning with wide lanes and exits
+ * Improve lateral control on RAV4
+ * Slow down for turns using model
+ * Open sourced regression test to verify outputs against reference logs
+ * Open sourced regression test to sanity check all car models
+
+Version 0.6.2 (2019-07-29)
+========================
+ * New driving model!
+ * Improve lane tracking with double lines
+ * Strongly improve stationary vehicle detection
+ * Strongly reduce cases of braking due to false leads
+ * Better lead tracking around turns
+ * Improve cut-in prediction by using neural network
+ * Improve lateral control on Toyota Camry and C-HR thanks to zorrobyte!
+ * Fix unintended openpilot disengagements on Jeep thanks to adhintz!
+ * Fix delayed transition to offroad when car is turned off
+
+Version 0.6.1 (2019-07-21)
+========================
+ * Remote SSH with comma prime and [ssh.comma.ai](https://ssh.comma.ai)
+ * Panda code Misra-c2012 compliance, tested against cppcheck coverage
+ * Lockout openpilot after 3 terminal alerts for driver distracted or unresponsive
+ * Toyota Sienna support thanks to wocsor!
+
+Version 0.6 (2019-07-01)
+========================
+ * New model, with double the pixels and ten times the temporal context!
+ * Car should not take exits when in the right lane
+ * openpilot uses only ~65% of the CPU (down from 75%)
+ * Routes visible in connect/explorer after only 0.2% is uploaded (qlogs)
+ * loggerd and sensord are open source, every line of openpilot is now open
+ * Panda safety code is MISRA compliant and ships with a signed version on release2
+ * New NEOS is 500MB smaller and has a reproducible usr/pipenv
+ * Lexus ES Hybrid support thanks to wocsor!
+ * Improve tuning for supported Toyota with TSS 2.0
+ * Various other stability improvements
+
+Version 0.5.13 (2019-05-31)
+==========================
+ * Reduce panda power consumption by 70%, down to 80mW, when car is off (not for GM)
+ * Reduce EON power consumption by 40%, down to 1100mW, when car is off
+ * Reduce CPU utilization by 20% and improve stability
+ * Temporarily remove mapd functionalities to improve stability
+ * Add openpilot record-only mode for unsupported cars
+ * Synchronize controlsd to boardd to reduce latency
+ * Remove panda support for Subaru giraffe
+
+Version 0.5.12 (2019-05-16)
+==========================
+ * Improve lateral control for the Prius and Prius Prime
+ * Compress logs before writing to disk
+ * Remove old driving data when storage reaches 90% full
+ * Fix small offset in following distance
+ * Various small CPU optimizations
+ * Improve offroad power consumption: require NEOS Update
+ * Add default speed limits for Estonia thanks to martinl!
+ * Subaru Crosstrek support thanks to martinl!
+ * Toyota Avalon support thanks to njbrown09!
+ * Toyota Rav4 with TSS 2.0 support thanks to wocsor!
+ * Toyota Corolla with TSS 2.0 support thanks to wocsor!
+
+Version 0.5.11 (2019-04-17)
+========================
+ * Add support for Subaru
+ * Reduce panda power consumption by 60% when car is off
+ * Fix controlsd lag every 6 minutes. This would sometimes cause disengagements
+ * Fix bug in controls with new angle-offset learner in MPC
+ * Reduce cpu consumption of ubloxd by rewriting it in C++
+ * Improve driver monitoring model and face detection
+ * Improve performance of visiond and ui
+ * Honda Passport 2019 support
+ * Lexus RX Hybrid 2019 support thanks to schomems!
+ * Improve road selection heuristic in mapd
+ * Add Lane Departure Warning to dashboard for Toyota thanks to arne182
+
+Version 0.5.10 (2019-03-19)
+========================
+ * Self-tuning vehicle parameters: steering offset, tire stiffness and steering ratio
+ * Improve longitudinal control at low speed when lead vehicle harshly decelerates
+ * Fix panda bug going unexpectedly in DCP mode when EON is connected
+ * Reduce white panda power consumption by 500mW when EON is disconnected by turning off WIFI
+ * New Driver Monitoring Model
+ * Support QR codes for login using comma connect
+ * Refactor comma pedal FW and use CRC-8 checksum algorithm for safety. Reflashing pedal is required.
+   Please see `#hw-pedal` on [discord](discord.comma.ai) for assistance updating comma pedal.
+ * Additional speed limit rules for Germany thanks to arne182
+ * Allow negative speed limit offsets
+
+Version 0.5.9 (2019-02-10)
+========================
+ * Improve calibration using a dedicated neural network
+ * Abstract planner in its own process to remove lags in controls process
+ * Improve speed limits with country/region defaults by road type
+ * Reduce mapd data usage with gzip thanks to eFiniLan
+ * Zip log files in the background to reduce disk usage
+ * Kia Optima support thanks to emmertex!
+ * Buick Regal 2018 support thanks to HOYS!
+ * Comma pedal support for Toyota thanks to wocsor! Note: tuning needed and not maintained by comma
+ * Chrysler Pacifica and Jeep Grand Cherokee support thanks to adhintz!
+
+Version 0.5.8 (2019-01-17)
+========================
+ * Open sourced visiond
+ * Auto-slowdown for upcoming turns
+ * Chrysler/Jeep/Fiat support thanks to adhintz!
+ * Honda Civic 2019 support thanks to csouers!
+ * Improve use of car display in Toyota thanks to arne182!
+ * No data upload when connected to Android or iOS hotspots and "Enable Upload Over Cellular" setting is off
+ * EON stops charging when 12V battery drops below 11.8V
+
+Version 0.5.7 (2018-12-06)
+========================
+ * Speed limit from OpenStreetMap added to UI
+ * Highlight speed limit when speed exceeds road speed limit plus a delta
+ * Option to limit openpilot max speed to road speed limit plus a delta
+ * Cadillac ATS support thanks to vntarasov!
+ * GMC Acadia support thanks to CryptoKylan!
+ * Decrease GPU power consumption
+ * NEOSv8 autoupdate
+
+Version 0.5.6 (2018-11-16)
+========================
+ * Refresh settings layout and add feature descriptions
+ * In Honda, keep stock camera on for logging and extra stock features; new openpilot giraffe setting is 0111!
+ * In Toyota, option to keep stock camera on for logging and extra stock features (e.g. AHB); 120Ohm resistor required on giraffe.
+ * Improve camera calibration stability
+ * More tuning to Honda positive accelerations
+ * Reduce brake pump use on Hondas
+ * Chevrolet Malibu support thanks to tylergets!
+ * Holden Astra support thanks to AlexHill!
+
+Version 0.5.5 (2018-10-20)
+========================
+ * Increase allowed Honda positive accelerations
+ * Fix sporadic unexpected braking when passing semi-trucks in Toyota
+ * Fix gear reading bug in Hyundai Elantra thanks to emmertex!
+
+Version 0.5.4 (2018-09-25)
+========================
+ * New Driving Model
+ * New Driver Monitoring Model
+ * Improve longitudinal mpc in mid-low speed braking
+ * Honda Accord hybrid support thanks to energee!
+ * Ship mpc binaries and sensibly reduce build time
+ * Calibration more stable
+ * More Hyundai and Kia cars supported thanks to emmertex!
+ * Various GM Volt improvements thanks to vntarasov!
+
+Version 0.5.3 (2018-09-03)
+========================
+ * Hyundai Santa Fe support!
+ * Honda Pilot 2019 support thanks to energee!
+ * Toyota Highlander support thanks to daehahn!
+ * Improve steering tuning for Honda Odyssey
+
+Version 0.5.2 (2018-08-16)
+========================
+ * New calibration: more accurate, a lot faster, open source!
+ * Enable orbd
+ * Add little endian support to CAN packer
+ * Fix fingerprint for Honda Accord 1.5T
+ * Improve driver monitoring model
+
+Version 0.5.1 (2018-08-01)
+========================
+ * Fix radar error on Civic sedan 2018
+ * Improve thermal management logic
+ * Alpha Toyota C-HR and Camry support!
+ * Auto-switch Driver Monitoring to 3 min counter when inaccurate
+
+Version 0.5 (2018-07-11)
+========================
+ * Driver Monitoring (beta) option in settings!
+ * Make visiond, loggerd and UI use less resources
+ * 60 FPS UI
+ * Better car parameters for most cars
+ * New sidebar with stats
+ * Remove Waze and Spotify to free up system resources
+ * Remove rear view mirror option
+ * Calibration 3x faster
+
+Version 0.4.7.2 (2018-06-25)
+==========================
+ * Fix loggerd lag issue
+ * No longer prompt for updates
+ * Mitigate right lane hugging for properly mounted EON (procedure on wiki)
+
+Version 0.4.7.1 (2018-06-18)
+==========================
+ * Fix Acura ILX steer faults
+ * Fix bug in mock car
+
 Version 0.4.7 (2018-06-15)
 ==========================
  * New model!

SAFETY.md

@@ -1,13 +1,26 @@
 openpilot Safety
 ======
 
-openpilot is an Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA) system. 
-Like other ACC and LKA systems, openpilot requires the driver to be alert and to 
-pay attention at all times. We repeat, **driver alertness is necessary, but not 
-sufficient, for openpilot to be used safely**.
+openpilot is an Adaptive Cruise Control (ACC) and Automated Lane Centering (ALC) system. 
+Like other ACC and ALC systems, openpilot is a failsafe passive system and it requires the
+driver to be alert and to pay attention at all times.
 
-Even with an attentive driver, we must make further efforts for the system to be
-safe. We have designed openpilot with two other safety considerations.
+In order to enforce driver alertness, openpilot includes a driver monitoring feature
+that alerts the driver when distracted.
+
+However, even with an attentive driver, we must make further efforts for the system to be
+safe. We repeat, **driver alertness is necessary, but not sufficient, for openpilot to be
+used safely** and openpilot is provided with no warranty of fitness for any purpose.
+
+openpilot is developed in good faith to be compliant with FMVSS requirements and to follow
+industry standards of safety for Level 2 Driver Assistance Systems. In particular, we observe
+ISO26262 guidelines, including those from [pertinent documents](https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/13498a_812_573_alcsystemreport.pdf)
+released by NHTSA. In addition, we impose strict coding guidelines (like [MISRA C : 2012](https://www.misra.org.uk/MISRAHome/MISRAC2012/tabid/196/Default.aspx))
+on parts of openpilot that are safety relevant. We also perform software-in-the-loop,
+hardware-in-the-loop and in-vehicle tests before each software release.
+
+Following Hazard and Risk Analysis and FMEA, at a very high level, we have designed openpilot
+ensuring two main safety requirements.
 
 1. The driver must always be capable to immediately retake manual control of the vehicle, 
    by stepping on either pedal or by pressing the cancel button.
@@ -15,59 +28,7 @@ safe. We have designed openpilot with two other safety considerations.
    react. This means that while the system is engaged, the actuators are constrained
    to operate within reasonable limits.
 
-Following are details of the car specific safety implementations:
+For vehicle specific implementation of the safety concept, refer to `panda/board/safety/`.
 
-Honda/Acura
-------
-
-  - While the system is engaged, gas, brake and steer limits are subject to the same limits used by
-    the stock system.
-
-  - Without an interceptor, the gas is controlled by the Powertrain Control Module (PCM). 
-    The PCM limits acceleration to what is reasonable for a cruise control system.  With an
-    interceptor, the gas is clipped to 60%.
-
-  - The brake is controlled by the 0x1FA CAN message. This message allows full
-    braking, although the board and the software clip it to 1/4th of the max.
-    This is around .3g of braking.
-
-  - Steering is controlled by the 0xE4 CAN message. The Electronic Power Steering (EPS) 
-    controller in the car limits the torque to a very small amount, so regardless of the 
-    message, the controller cannot jerk the wheel.
-
-  - Brake and gas pedal pressed signals are contained in the 0x17C CAN message. A rising edge of
-    either signal triggers a disengagement, which is enforced by the board and in software. The
-    green led on the board signifies if the board is allowing control messages.
-
-  - Honda CAN uses both a counter and a checksum to ensure integrity and prevent
-    replay of the same message.
-
-Toyota/Lexus
-------
-
-  - While the system is engaged, gas, brake and steer limits are subject to the same limits used by
-    the stock system.
-
-  - With the stock Driving Support Unit (DSU) enabled, the acceleration is controlled 
-    by the stock system and is subject to the stock adaptive cruise control limits. Without the
-    stock DSU connected, the acceleration command is controlled by the 0x343 CAN message and its
-    value is limited by the board and the software to between .3g of deceleration and .15g of
-    acceleration. The acceleration command is ignored by the Engine Control Module (ECM) while the
-    cruise control system is disengaged.
-
-  - Steering torque is controlled through the 0x2E4 CAN message and it's limited by the board and in
-    software to a value of -1500 and 1500. In addition, the vehicle EPS unit will not respond to
-    commands outside these limits.  A steering torque rate limit is enforced by the board and in
-    software so that the commanded steering torque must rise from 0 to max value no faster than
-    1.5s. Commanded steering torque is limited by the board and in software to be no more than 350
-    units above the actual EPS generated motor torque to ensure limited differences between
-    commanded and actual torques.
-
-  - Brake and gas pedal pressed signals are contained in the 0x224 and 0x1D2 CAN messages,
-    respectively. A rising edge of either signal triggers a disengagement, which is enforced by the
-    board and in software. Additionally, the cruise control system disengages on the rising edge of
-    the brake pedal pressed signal.
-
-  - The cruise control system state is contained in the 0x1D2 message. No control messages are
-    allowed if the cruise control system is not active. This is enforced by the software and the
-    board. The green led on the board signifies if the board is allowing control messages.
+**Extra note**: comma.ai strongly discourages the use of openpilot forks with safety code either missing or
+  not fully meeting the above requirements.

SConstruct

@@ -0,0 +1,232 @@
+import os
+import subprocess
+import sys
+import platform
+
+AddOption('--test',
+          action='store_true',
+          help='build test files')
+
+AddOption('--asan',
+          action='store_true',
+          help='turn on ASAN')
+
+arch = subprocess.check_output(["uname", "-m"], encoding='utf8').rstrip()
+if platform.system() == "Darwin":
+  arch = "Darwin"
+
+if arch == "aarch64":
+  lenv = {
+    "LD_LIBRARY_PATH": '/data/data/com.termux/files/usr/lib',
+    "PATH": os.environ['PATH'],
+    "ANDROID_DATA": os.environ['ANDROID_DATA'],
+    "ANDROID_ROOT": os.environ['ANDROID_ROOT'],
+  }
+
+  cpppath = [
+    "#phonelibs/opencl/include",
+  ]
+  libpath = [
+    "#phonelibs/snpe/aarch64-android-clang3.8",
+    "/usr/lib",
+    "/data/data/com.termux/files/usr/lib",
+    "/system/vendor/lib64",
+    "/system/comma/usr/lib",
+    "#phonelibs/nanovg",
+    "#phonelibs/libyuv/lib",
+  ]
+
+  cflags = ["-DQCOM", "-mcpu=cortex-a57"]
+  cxxflags = ["-DQCOM", "-mcpu=cortex-a57"]
+
+  rpath = ["/system/vendor/lib64"]
+else:
+  lenv = {
+    "PATH": "#external/bin:" + os.environ['PATH'],
+  }
+  cpppath = [
+    "#phonelibs/capnp-cpp/include",
+    "#phonelibs/capnp-c/include",
+    "#phonelibs/zmq/x64/include",
+    "#external/tensorflow/include",
+  ]
+
+  if arch == "Darwin":
+    libpath = [
+      "#phonelibs/capnp-cpp/mac/lib",
+      "#phonelibs/capnp-c/mac/lib",
+      "#phonelibs/libyuv/mac/lib",
+      "#cereal",
+      "#selfdrive/common",
+      "/usr/local/lib",
+      "/System/Library/Frameworks/OpenGL.framework/Libraries",
+    ]
+  else:
+    libpath = [
+      "#phonelibs/capnp-cpp/x64/lib",
+      "#phonelibs/capnp-c/x64/lib",
+      "#phonelibs/snpe/x86_64-linux-clang",
+      "#phonelibs/zmq/x64/lib",
+      "#phonelibs/libyuv/x64/lib",
+      "#external/zmq/lib",
+      "#external/tensorflow/lib",
+      "#cereal",
+      "#selfdrive/common",
+      "/usr/lib",
+      "/usr/local/lib",
+    ]
+
+  rpath = ["phonelibs/capnp-cpp/x64/lib",
+           "phonelibs/zmq/x64/lib",
+           "external/tensorflow/lib",
+           "cereal",
+           "selfdrive/common"]
+
+  # allows shared libraries to work globally
+  rpath = [os.path.join(os.getcwd(), x) for x in rpath]
+
+  cflags = []
+  cxxflags = []
+
+ccflags_asan = ["-fsanitize=address", "-fno-omit-frame-pointer"] if GetOption('asan') else []
+ldflags_asan = ["-fsanitize=address"] if GetOption('asan') else []
+
+# change pythonpath to this
+lenv["PYTHONPATH"] = Dir("#").path
+
+env = Environment(
+  ENV=lenv,
+  CCFLAGS=[
+    "-g",
+    "-fPIC",
+    "-O2",
+    "-Werror=implicit-function-declaration",
+    "-Werror=incompatible-pointer-types",
+    "-Werror=int-conversion",
+    "-Werror=return-type",
+    "-Werror=format-extra-args",
+  ] + cflags + ccflags_asan,
+
+  CPPPATH=cpppath + [
+    "#",
+    "#selfdrive",
+    "#phonelibs/bzip2",
+    "#phonelibs/libyuv/include",
+    "#phonelibs/openmax/include",
+    "#phonelibs/json/src",
+    "#phonelibs/json11",
+    "#phonelibs/eigen",
+    "#phonelibs/curl/include",
+    "#phonelibs/opencv/include",
+    "#phonelibs/libgralloc/include",
+    "#phonelibs/android_frameworks_native/include",
+    "#phonelibs/android_hardware_libhardware/include",
+    "#phonelibs/android_system_core/include",
+    "#phonelibs/linux/include",
+    "#phonelibs/snpe/include",
+    "#phonelibs/nanovg",
+    "#selfdrive/common",
+    "#selfdrive/camerad",
+    "#selfdrive/camerad/include",
+    "#selfdrive/loggerd/include",
+    "#selfdrive/modeld",
+    "#cereal/messaging",
+    "#cereal",
+    "#opendbc/can",
+  ],
+
+  CC='clang',
+  CXX='clang++',
+  LINKFLAGS=ldflags_asan,
+
+  RPATH=rpath,
+
+  CFLAGS=["-std=gnu11"] + cflags,
+  CXXFLAGS=["-std=c++14"] + cxxflags,
+  LIBPATH=libpath +
+  [
+    "#cereal",
+    "#selfdrive/common",
+    "#phonelibs",
+  ]
+)
+
+if os.environ.get('SCONS_CACHE'):
+  CacheDir('/tmp/scons_cache')
+
+node_interval = 5
+node_count = 0
+def progress_function(node):
+  global node_count
+  node_count += node_interval
+  sys.stderr.write("progress: %d\n" % node_count)
+
+if os.environ.get('SCONS_PROGRESS'):
+  Progress(progress_function, interval=node_interval)
+
+SHARED = False
+
+def abspath(x):
+  if arch == 'aarch64':
+    pth = os.path.join("/data/pythonpath", x[0].path)
+    env.Depends(pth, x)
+    return File(pth)
+  else:
+    # rpath works elsewhere
+    return x[0].path.rsplit("/", 1)[1][:-3]
+
+#zmq = 'zmq'
+# still needed for apks
+zmq = FindFile("libzmq.a", libpath)
+Export('env', 'arch', 'zmq', 'SHARED')
+
+# cereal and messaging are shared with the system
+SConscript(['cereal/SConscript'])
+if SHARED:
+  cereal = abspath([File('cereal/libcereal_shared.so')])
+  messaging = abspath([File('cereal/libmessaging_shared.so')])
+else:
+  cereal = [File('#cereal/libcereal.a')]
+  messaging = [File('#cereal/libmessaging.a')]
+Export('cereal', 'messaging')
+
+SConscript(['selfdrive/common/SConscript'])
+Import('_common', '_visionipc', '_gpucommon', '_gpu_libs')
+
+if SHARED:
+  common, visionipc, gpucommon = abspath(common), abspath(visionipc), abspath(gpucommon)
+else:
+  common = [_common, 'json']
+  visionipc = _visionipc
+  gpucommon = [_gpucommon] + _gpu_libs
+
+Export('common', 'visionipc', 'gpucommon')
+
+SConscript(['opendbc/can/SConscript'])
+
+SConscript(['common/SConscript'])
+SConscript(['common/kalman/SConscript'])
+SConscript(['phonelibs/SConscript'])
+
+if arch != "Darwin":
+  SConscript(['selfdrive/camerad/SConscript'])
+  SConscript(['selfdrive/modeld/SConscript'])
+
+SConscript(['selfdrive/controls/lib/cluster/SConscript'])
+SConscript(['selfdrive/controls/lib/lateral_mpc/SConscript'])
+SConscript(['selfdrive/controls/lib/longitudinal_mpc/SConscript'])
+
+SConscript(['selfdrive/boardd/SConscript'])
+SConscript(['selfdrive/proclogd/SConscript'])
+
+SConscript(['selfdrive/ui/SConscript'])
+SConscript(['selfdrive/loggerd/SConscript'])
+
+if arch == "aarch64":
+  SConscript(['selfdrive/logcatd/SConscript'])
+  SConscript(['selfdrive/sensord/SConscript'])
+  SConscript(['selfdrive/clocksd/SConscript'])
+
+SConscript(['selfdrive/locationd/SConscript'])
+
+# TODO: finish cereal, dbcbuilder, MPC

apk/README

@@ -0,0 +1,3 @@
+Place apks here that you want to be installed with the name <app>.apk
+
+These won't be committed into one, but for now baseui will ship with openpilot.

apk/external/.gitignore

@@ -1,2 +0,0 @@
-src/*
-out/*

apk/external/patcher.py

@@ -1,122 +0,0 @@
-#!/usr/bin/env python2.7
-
-import os
-import sys
-import glob
-import shutil
-import urllib2
-import hashlib
-import subprocess
-
-
-EXTERNAL_PATH = os.path.dirname(os.path.abspath(__file__))
-
-if os.path.exists("/init.qcom.rc"):
-  # android
-  APKPATCH = os.path.join(EXTERNAL_PATH, 'tools/apkpatch_android')
-  SIGNAPK = os.path.join(EXTERNAL_PATH, 'tools/signapk_android')
-else:
-  APKPATCH = os.path.join(EXTERNAL_PATH, 'tools/apkpatch')
-  SIGNAPK = os.path.join(EXTERNAL_PATH, 'tools/signapk')
-
-APKS = {
-  'com.waze': {
-    'src': 'https://apkcache.s3.amazonaws.com/com.waze_1021278.apk',
-    'src_sha256': 'f00957e93e2389f9e30502ac54994b98ac769314b0963c263d4e8baa625ab0c2',
-    'patch': 'com.waze.apkpatch',
-    'out_sha256': 'fee880a91a44c738442cd05fd1b6d9b5817cbf755aa61c86325ada2bc443d5cf'
-  },
-  'com.spotify.music': {
-    'src': 'https://apkcache.s3.amazonaws.com/com.spotify.music_24382006.apk',
-    'src_sha256': '0610fea68ee7ba5f8e4e0732ad429d729dd6cbb8bc21222c4c99db6cb09fbff4',
-    'patch': 'com.spotify.music.apkpatch',
-    'out_sha256': '5a3d6f478c7e40403a98ccc8906d7e0ae12b06543b41f5df52149dd09c647c11'
-  },
-}
-
-def sha256_path(path):
-  with open(path, 'rb') as f:
-    return hashlib.sha256(f.read()).hexdigest()
-
-def remove(path):
-  try:
-    os.remove(path)
-  except OSError:
-    pass
-
-def process(download, patch):
-  # clean up any junk apks
-  for out_apk in glob.glob(os.path.join(EXTERNAL_PATH, 'out/*.apk')):
-    app = os.path.basename(out_apk)[:-4]
-    if app not in APKS:
-      print "remove junk", out_apk
-      remove(out_apk)
-
-  complete = True
-  for k,v in APKS.iteritems():
-    apk_path = os.path.join(EXTERNAL_PATH, 'out', k+'.apk')
-    print "checking", apk_path
-    if os.path.exists(apk_path) and sha256_path(apk_path) == v['out_sha256']:
-      # nothing to do
-      continue
-
-    complete = False
-
-    remove(apk_path)
-
-    src_path = os.path.join(EXTERNAL_PATH, 'src', v['src_sha256'])
-    if not os.path.exists(src_path) or sha256_path(src_path) != v['src_sha256']:
-      if not download:
-        continue
-
-      print "downloading", v['src'], "to", src_path
-      # download it
-      resp = urllib2.urlopen(v['src'])
-      data = resp.read()
-      with open(src_path, 'wb') as src_f:
-        src_f.write(data)
-
-      if sha256_path(src_path) != v['src_sha256']:
-        print "download was corrupted..."
-        continue
-
-    if not patch:
-      continue
-
-    # ignoring lots of TOCTTOU here...
-
-    apk_temp = "/tmp/"+k+".patched"
-    remove(apk_temp)
-    apk_temp2 = "/tmp/"+k+".signed"
-    remove(apk_temp2)
-
-    try:
-      print "patching", v['patch']
-      subprocess.check_call([APKPATCH, 'apply', src_path, apk_temp, os.path.join(EXTERNAL_PATH, v['patch'])])
-      print "signing", apk_temp
-      subprocess.check_call([SIGNAPK,
-        os.path.join(EXTERNAL_PATH, 'tools/certificate.pem'), os.path.join(EXTERNAL_PATH, 'tools/key.pk8'),
-        apk_temp, apk_temp2])
-
-      out_sha256 = sha256_path(apk_temp2) if os.path.exists(apk_temp2) else None
-
-      if out_sha256 == v['out_sha256']:
-        print "done", apk_path
-        shutil.move(apk_temp2, apk_path)
-      else:
-        print "patch was corrupted", apk_temp2, out_sha256
-    finally:
-      remove(apk_temp)
-      remove(apk_temp2)
-
-  return complete
-
-if __name__ == "__main__":
-  ret = True
-  if len(sys.argv) == 2 and sys.argv[1] == "download":
-    ret = process(True, False)
-  elif len(sys.argv) == 2 and sys.argv[1] == "patch":
-    ret = process(False, True)
-  else:
-    ret = process(True, True)
-  sys.exit(0 if ret else 1)

apk/external/tools/apkpatch_android

@@ -1,7 +0,0 @@
-#!/system/bin/sh
-
-DIR="$(cd "$(dirname "$0")" && pwd)"
-
-export LD_LIBRARY_PATH=/system/lib64
-export CLASSPATH="$DIR"/ApkPatch.android.jar
-exec app_process "$DIR" ApkPatch "$@"

apk/external/tools/certificate.pem

@@ -1,17 +0,0 @@
------BEGIN CERTIFICATE-----
-MIICtTCCAh4CCQDm79UqF+Dc5zANBgkqhkiG9w0BAQUFADCBnjELMAkGA1UEBhMC
-SUQxEzARBgNVBAgTCkphd2EgQmFyYXQxEDAOBgNVBAcTB0JhbmR1bmcxEjAQBgNV
-BAoTCUxvbmRhdGlnYTETMBEGA1UECxMKQW5kcm9pZERldjEaMBgGA1UEAxMRTG9y
-ZW5zaXVzIFcuIEwuIFQxIzAhBgkqhkiG9w0BCQEWFGxvcmVuekBsb25kYXRpZ2Eu
-bmV0MB4XDTEwMDUwNTA5MjEzOFoXDTEzMDEyODA5MjEzOFowgZ4xCzAJBgNVBAYT
-AklEMRMwEQYDVQQIEwpKYXdhIEJhcmF0MRAwDgYDVQQHEwdCYW5kdW5nMRIwEAYD
-VQQKEwlMb25kYXRpZ2ExEzARBgNVBAsTCkFuZHJvaWREZXYxGjAYBgNVBAMTEUxv
-cmVuc2l1cyBXLiBMLiBUMSMwIQYJKoZIhvcNAQkBFhRsb3JlbnpAbG9uZGF0aWdh
-Lm5ldDCBnzANBgkqhkiG9w0BAQEFAAOBjQAwgYkCgYEAy2oWtbdVXMHGiS6cA3qi
-3VfZt5Vz9jTlux+TEcGx5h18ZKwclyo+z2B0L/p5bYdnrTdFEiD7IxvX+h3lu0JV
-B9rdXZdyrzXNOw5YFrsn2k7hKvB8KEBaga1gZEwodlc6N14H3FbZdZkIA9V716Pu
-e5CWBZ2VqU03lUJmKnpH8c8CAwEAATANBgkqhkiG9w0BAQUFAAOBgQBpNgXh8dw9
-uMjZxzLUXovV5ptHd61jAcZlQlffqPsz6/2QNfIShVdGH9jkm0IudfKkbvvOKive
-a77t9c4sDh2Sat2L/rx6BfTuS1+y9wFr1Ee8Rrr7wGHhRkx2qqGrXGVWqXn8aE3E
-P6e7BTPF0ibS+tG8cdDPEisqGFxw36nTNQ==
------END CERTIFICATE-----

apk/external/tools/signapk_android

@@ -1,7 +0,0 @@
-#!/system/bin/sh
-
-DIR="$(cd "$(dirname "$0")" && pwd)"
-
-export LD_LIBRARY_PATH=/system/lib64
-export CLASSPATH="$DIR"/signapk.android.jar
-exec app_process "$DIR" com.android.signapk.SignApk "$@"

cereal/.gitignore

@@ -1,3 +0,0 @@
-gen
-node_modules
-package-lock.json

cereal/Makefile

@@ -1,59 +0,0 @@
-PWD := $(shell pwd)
-
-SRCS := log.capnp car.capnp
-
-GENS := gen/cpp/car.capnp.c++ gen/cpp/log.capnp.c++
-JS := gen/js/car.capnp.js gen/js/log.capnp.js
-
-UNAME_M ?= $(shell uname -m)
-
-# only generate C++ for docker tests
-ifneq ($(OPTEST),1)
-	GENS += gen/c/car.capnp.c gen/c/log.capnp.c gen/c/include/c++.capnp.h gen/c/include/java.capnp.h
-
-	ifeq ($(UNAME_M),x86_64)
-		GENS += gen/java/Car.java gen/java/Log.java
-	endif
-
-endif
-
-ifeq ($(UNAME_M),aarch64)
-	CAPNPC=PATH=$(PWD)/../phonelibs/capnp-cpp/aarch64/bin/:$$PATH capnpc
-else
-	CAPNPC=capnpc
-endif
-
-.PHONY: all
-all: $(GENS)
-js: $(JS)
-
-.PHONY: clean
-clean:
-	rm -rf gen
-	rm -rf node_modules
-	rm -rf package-lock.json
-
-gen/c/%.capnp.c: %.capnp
-	@echo "[ CAPNPC C ] $@"
-	mkdir -p gen/c/
-	$(CAPNPC) '$<' -o c:gen/c/
-
-gen/js/%.capnp.js: %.capnp
-	@echo "[ CAPNPC JavaScript ] $@"
-	mkdir -p gen/js/
-	sh ./generate_javascript.sh
-
-gen/cpp/%.capnp.c++: %.capnp
-	@echo "[ CAPNPC C++ ] $@"
-	mkdir -p gen/cpp/
-	$(CAPNPC) '$<' -o c++:gen/cpp/
-
-gen/java/Car.java gen/java/Log.java: $(SRCS)
-	@echo "[ CAPNPC java ] $@"
-	mkdir -p gen/java/
-	$(CAPNPC) $^ -o java:gen/java
-
-# c-capnproto needs some empty headers
-gen/c/include/c++.capnp.h gen/c/include/java.capnp.h:
-	mkdir -p gen/c/include
-	touch '$@'

cereal/__init__.py

@@ -1,8 +0,0 @@
-import os
-import capnp
-
-CEREAL_PATH = os.path.dirname(os.path.abspath(__file__))
-capnp.remove_import_hook()
-
-log = capnp.load(os.path.join(CEREAL_PATH, "log.capnp"))
-car = capnp.load(os.path.join(CEREAL_PATH, "car.capnp"))

cereal/car.capnp

@@ -1,345 +0,0 @@
-using Cxx = import "./include/c++.capnp";
-$Cxx.namespace("cereal");
-
-using Java = import "./include/java.capnp";
-$Java.package("ai.comma.openpilot.cereal");
-$Java.outerClassname("Car");
-
-@0x8e2af1e708af8b8d;
-
-# ******* events causing controls state machine transition *******
-
-struct CarEvent @0x9b1657f34caf3ad3 {
-  name @0 :EventName;
-  enable @1 :Bool;
-  noEntry @2 :Bool;
-  warning @3 :Bool;
-  userDisable @4 :Bool;
-  softDisable @5 :Bool;
-  immediateDisable @6 :Bool;
-  preEnable @7 :Bool;
-  permanent @8 :Bool;
-
-  enum EventName @0xbaa8c5d505f727de {
-    # TODO: copy from error list
-    commIssue @0;
-    steerUnavailable @1;
-    brakeUnavailable @2;
-    gasUnavailable @3;
-    wrongGear @4;
-    doorOpen @5;
-    seatbeltNotLatched @6;
-    espDisabled @7;
-    wrongCarMode @8;
-    steerTempUnavailable @9;
-    reverseGear @10;
-    buttonCancel @11;
-    buttonEnable @12;
-    pedalPressed @13;
-    cruiseDisabled @14;
-    radarCommIssue @15;
-    dataNeeded @16;
-    speedTooLow @17;
-    outOfSpace @18;
-    overheat @19;
-    calibrationInProgress @20;
-    calibrationInvalid @21;
-    controlsMismatch @22;
-    pcmEnable @23;
-    pcmDisable @24;
-    noTarget @25;
-    radarFault @26;
-    modelCommIssue @27;
-    brakeHold @28;
-    parkBrake @29;
-    manualRestart @30;
-    lowSpeedLockout @31;
-    plannerError @32;
-    ipasOverride @33;
-    debugAlert @34;
-    steerTempUnavailableMute @35;
-    resumeRequired @36;
-  }
-}
-
-# ******* main car state @ 100hz *******
-# all speeds in m/s
-
-struct CarState {
-  errorsDEPRECATED @0 :List(CarEvent.EventName);
-  events @13 :List(CarEvent);
-
-  # car speed
-  vEgo @1 :Float32;         # best estimate of speed
-  aEgo @16 :Float32;        # best estimate of acceleration
-  vEgoRaw @17 :Float32;     # unfiltered speed from CAN sensors
-  yawRate @22 :Float32;     # best estimate of yaw rate
-  standstill @18 :Bool;
-  wheelSpeeds @2 :WheelSpeeds;
-
-  # gas pedal, 0.0-1.0
-  gas @3 :Float32;        # this is user + computer
-  gasPressed @4 :Bool;    # this is user pedal only
-
-  # brake pedal, 0.0-1.0
-  brake @5 :Float32;      # this is user pedal only
-  brakePressed @6 :Bool;  # this is user pedal only
-  brakeLights @19 :Bool;
-
-  # steering wheel
-  steeringAngle @7 :Float32;   # deg
-  steeringRate @15 :Float32;   # deg/s
-  steeringTorque @8 :Float32;  # TODO: standardize units
-  steeringPressed @9 :Bool;    # if the user is using the steering wheel
-
-  # cruise state
-  cruiseState @10 :CruiseState;
-
-  # gear
-  gearShifter @14 :GearShifter;
-
-  # button presses
-  buttonEvents @11 :List(ButtonEvent);
-  leftBlinker @20 :Bool;
-  rightBlinker @21 :Bool;
-  genericToggle @23 :Bool;
-
-  # lock info
-  doorOpen @24 :Bool;
-  seatbeltUnlatched @25 :Bool;
-
-  # which packets this state came from
-  canMonoTimes @12: List(UInt64);
-
-  struct WheelSpeeds {
-    # optional wheel speeds
-    fl @0 :Float32;
-    fr @1 :Float32;
-    rl @2 :Float32;
-    rr @3 :Float32;
-  }
-
-  struct CruiseState {
-    enabled @0 :Bool;
-    speed @1 :Float32;
-    available @2 :Bool;
-    speedOffset @3 :Float32;
-    standstill @4 :Bool;
-  }
-
-  enum GearShifter {
-    unknown @0;
-    park @1;
-    drive @2;
-    neutral @3;
-    reverse @4;
-    sport @5;
-    low @6;
-    brake @7;
-  }
-
-
-  # send on change
-  struct ButtonEvent {
-    pressed @0 :Bool;
-    type @1 :Type;
-
-    enum Type {
-      unknown @0;
-      leftBlinker @1;
-      rightBlinker @2;
-      accelCruise @3;
-      decelCruise @4;
-      cancel @5;
-      altButton1 @6;
-      altButton2 @7;
-      altButton3 @8;
-    }
-  }
-}
-
-# ******* radar state @ 20hz *******
-
-struct RadarState {
-  errors @0 :List(Error);
-  points @1 :List(RadarPoint);
-
-  # which packets this state came from
-  canMonoTimes @2 :List(UInt64);
-
-  enum Error {
-    commIssue @0;
-    fault @1;
-  }
-
-  # similar to LiveTracks
-  # is one timestamp valid for all? I think so
-  struct RadarPoint {
-    trackId @0 :UInt64;  # no trackId reuse
-
-    # these 3 are the minimum required
-    dRel @1 :Float32; # m from the front bumper of the car
-    yRel @2 :Float32; # m
-    vRel @3 :Float32; # m/s
-
-    # these are optional and valid if they are not NaN
-    aRel @4 :Float32; # m/s^2
-    yvRel @5 :Float32; # m/s
-
-    # some radars flag measurements VS estimates
-    measured @6 :Bool;
-  }
-}
-
-# ******* car controls @ 100hz *******
-
-struct CarControl {
-  # must be true for any actuator commands to work
-  enabled @0 :Bool;
-  active @7 :Bool;
-
-  gasDEPRECATED @1 :Float32;
-  brakeDEPRECATED @2 :Float32;
-  steeringTorqueDEPRECATED @3 :Float32;
-
-  actuators @6 :Actuators;
-
-  cruiseControl @4 :CruiseControl;
-  hudControl @5 :HUDControl;
-
-  struct Actuators {
-    # range from 0.0 - 1.0
-    gas @0: Float32;
-    brake @1: Float32;
-    # range from -1.0 - 1.0
-    steer @2: Float32;
-    steerAngle @3: Float32;
-  }
-
-  struct CruiseControl {
-    cancel @0: Bool;
-    override @1: Bool;
-    speedOverride @2: Float32;
-    accelOverride @3: Float32;
-  }
-
-  struct HUDControl {
-    speedVisible @0: Bool;
-    setSpeed @1: Float32;
-    lanesVisible @2: Bool;
-    leadVisible @3: Bool;
-    visualAlert @4: VisualAlert;
-    audibleAlert @5: AudibleAlert;
-
-    enum VisualAlert {
-      # these are the choices from the Honda
-      # map as good as you can for your car
-      none @0;
-      fcw @1;
-      steerRequired @2;
-      brakePressed @3;
-      wrongGear @4;
-      seatbeltUnbuckled @5;
-      speedTooHigh @6;
-    }
-
-    enum AudibleAlert {
-      # these are the choices from the Honda
-      # map as good as you can for your car
-      none @0;
-      beepSingle @1;
-      beepTriple @2;
-      beepRepeated @3;
-      chimeSingle @4;
-      chimeDouble @5;
-      chimeRepeated @6;
-      chimeContinuous @7;
-    }
-  }
-}
-
-# ****** car param ******
-
-struct CarParams {
-  carName @0 :Text;
-  radarNameDEPRECATED @1 :Text;
-  carFingerprint @2 :Text;
-
-  enableSteerDEPRECATED @3 :Bool;
-  enableGasInterceptor @4 :Bool;
-  enableBrakeDEPRECATED @5 :Bool;
-  enableCruise @6 :Bool;
-  enableCamera @26 :Bool;
-  enableDsu @27 :Bool; # driving support unit
-  enableApgs @28 :Bool; # advanced parking guidance system
-
-  minEnableSpeed @17 :Float32;
-  safetyModel @18 :Int16;
-  safetyParam @41 :Int16;
-
-  steerMaxBP @19 :List(Float32);
-  steerMaxV @20 :List(Float32);
-  gasMaxBP @21 :List(Float32);
-  gasMaxV @22 :List(Float32);
-  brakeMaxBP @23 :List(Float32);
-  brakeMaxV @24 :List(Float32);
-
-  longPidDeadzoneBP @32 :List(Float32);
-  longPidDeadzoneV @33 :List(Float32);
-
-  enum SafetyModels {
-    # does NOT match board setting
-    noOutput @0;
-    honda @1;
-    toyota @2;
-    elm327 @3;
-    gm @4;
-    hondaBosch @5;
-    ford @6;
-    cadillac @7;
-  }
-
-  # things about the car in the manual
-  mass @7 :Float32;             # [kg] running weight
-  wheelbase @8 :Float32;        # [m] distance from rear to front axle
-  centerToFront @9 :Float32;   # [m] GC distance to front axle
-  steerRatio @10 :Float32;       # [] ratio between front wheels and steering wheel angles
-  steerRatioRear @11 :Float32;  # [] rear steering ratio wrt front steering (usually 0)
-
-  # things we can derive
-  rotationalInertia @12 :Float32;    # [kg*m2] body rotational inertia
-  tireStiffnessFront @13 :Float32;   # [N/rad] front tire coeff of stiff
-  tireStiffnessRear @14 :Float32;    # [N/rad] rear tire coeff of stiff
-
-  # Kp and Ki for the lateral control
-  steerKpBP @42 :List(Float32);
-  steerKpV @43 :List(Float32);
-  steerKiBP @44 :List(Float32);
-  steerKiV @45 :List(Float32);
-  steerKpDEPRECATED @15 :Float32;
-  steerKiDEPRECATED @16 :Float32;
-  steerKf @25 :Float32;
-
-  # Kp and Ki for the longitudinal control
-  longitudinalKpBP @36 :List(Float32);
-  longitudinalKpV @37 :List(Float32);
-  longitudinalKiBP @38 :List(Float32);
-  longitudinalKiV @39 :List(Float32);
-
-  steerLimitAlert @29 :Bool;
-
-  vEgoStopping @30 :Float32; # Speed at which the car goes into stopping state
-  directAccelControl @31 :Bool; # Does the car have direct accel control or just gas/brake
-  stoppingControl @34 :Bool; # Does the car allows full control even at lows speeds when stopping
-  startAccel @35 :Float32; # Required acceleraton to overcome creep braking
-  steerRateCost @40 :Float32; # Lateral MPC cost on steering rate
-  steerControlType @46 :SteerControlType;
-  radarOffCan @47 :Bool; # True when radar objects aren't visible on CAN
-
-  steerActuatorDelay @48 :Float32; # Steering wheel actuator delay in seconds
-
-  enum SteerControlType {
-    torque @0;
-    angle @1;
-  }
-}

cereal/include/java.capnp

@@ -1,28 +0,0 @@
-# Copyright (c) 2013-2015 Sandstorm Development Group, Inc. and contributors
-# Licensed under the MIT License:
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in
-# all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
-# THE SOFTWARE.
-
-@0xc5f1af96651f70ea;
-
-annotation package @0x9ee4c8f803b3b596 (file) : Text;
-# Name of the package, such as "org.example.foo", in which the generated code will reside.
-
-annotation outerClassname @0x9b066bb4881f7cd3 (file) : Text;
-# Name of the outer class that will wrap the generated code.

common/.gitignore

@@ -0,0 +1 @@
+*.cpp

common/SConscript

@@ -0,0 +1,6 @@
+Import('env')
+
+# parser
+env.Command(['common_pyx.so'],
+  ['common_pyx_setup.py', 'clock.pyx'],
+  "cd common && python3 common_pyx_setup.py build_ext --inplace")

common/android.py

@@ -0,0 +1,130 @@
+import os
+import binascii
+import itertools
+import re
+import struct
+import subprocess
+import random
+from cereal import log
+
+NetworkType = log.ThermalData.NetworkType
+
+ANDROID = os.path.isfile('/EON')
+
+def getprop(key):
+  if not ANDROID:
+    return ""
+  return subprocess.check_output(["getprop", key], encoding='utf8').strip()
+
+def get_imei(slot):
+  slot = str(slot)
+  if slot not in ("0", "1"):
+    raise ValueError("SIM slot must be 0 or 1")
+
+  ret = parse_service_call_string(service_call(["iphonesubinfo", "3" ,"i32", str(slot)]))
+  if not ret:
+    # allow non android to be identified differently
+    ret = "%015d" % random.randint(0, 1<<32)
+  return ret
+
+def get_serial():
+  ret = getprop("ro.serialno")
+  if ret == "":
+    ret = "cccccccc"
+  return ret
+
+def get_subscriber_info():
+  ret = parse_service_call_string(service_call(["iphonesubinfo", "7"]))
+  if ret is None or len(ret) < 8:
+    return ""
+  return ret
+
+def reboot(reason=None):
+  if reason is None:
+    reason_args = ["null"]
+  else:
+    reason_args = ["s16", reason]
+
+  subprocess.check_output([
+    "service", "call", "power", "16", # IPowerManager.reboot
+    "i32", "0", # no confirmation,
+    *reason_args,
+    "i32", "1" # wait
+  ])
+
+def service_call(call):
+  if not ANDROID:
+    return None
+
+  ret = subprocess.check_output(["service", "call", *call], encoding='utf8').strip()
+  if 'Parcel' not in ret:
+    return None
+
+  return parse_service_call_bytes(ret)
+
+def parse_service_call_unpack(r, fmt):
+  try:
+    return struct.unpack(fmt, r)[0]
+  except Exception:
+    return None
+
+def parse_service_call_string(r):
+  try:
+    r = r[8:] # Cut off length field
+    r = r.decode('utf_16_be')
+
+    # All pairs of two characters seem to be swapped. Not sure why
+    result = ""
+    for a, b, in itertools.zip_longest(r[::2], r[1::2], fillvalue='\x00'):
+        result += b + a
+
+    result = result.replace('\x00', '')
+
+    return result
+  except Exception:
+    return None
+
+def parse_service_call_bytes(ret):
+  try:
+    r = b""
+    for hex_part in re.findall(r'[ (]([0-9a-f]{8})', ret):
+      r += binascii.unhexlify(hex_part)
+    return r
+  except Exception:
+    return None
+
+def get_network_type():
+  if not ANDROID:
+    return NetworkType.none
+
+  wifi_check = parse_service_call_string(service_call(["connectivity", "2"]))
+  if wifi_check is None:
+    return NetworkType.none
+  elif 'WIFI' in wifi_check:
+    return NetworkType.wifi
+  else:
+    cell_check = parse_service_call_unpack(service_call(['phone', '59']), ">q")
+    # from TelephonyManager.java
+    cell_networks = {
+      0: NetworkType.none,
+      1: NetworkType.cell2G,
+      2: NetworkType.cell2G,
+      3: NetworkType.cell3G,
+      4: NetworkType.cell2G,
+      5: NetworkType.cell3G,
+      6: NetworkType.cell3G,
+      7: NetworkType.cell3G,
+      8: NetworkType.cell3G,
+      9: NetworkType.cell3G,
+      10: NetworkType.cell3G,
+      11: NetworkType.cell2G,
+      12: NetworkType.cell3G,
+      13: NetworkType.cell4G,
+      14: NetworkType.cell4G,
+      15: NetworkType.cell3G,
+      16: NetworkType.cell2G,
+      17: NetworkType.cell3G,
+      18: NetworkType.cell4G,
+      19: NetworkType.cell4G
+    }
+    return cell_networks.get(cell_check, NetworkType.none)

common/api/__init__.py

@@ -1,7 +1,34 @@
+import jwt
 import requests
-
+from datetime import datetime, timedelta
+from common.basedir import PERSIST
 from selfdrive.version import version
 
+class Api():
+  def __init__(self, dongle_id):
+    self.dongle_id = dongle_id
+    with open(PERSIST+'/comma/id_rsa') as f:
+      self.private_key = f.read()
+
+  def get(self, *args, **kwargs):
+    return self.request('GET', *args, **kwargs)
+
+  def post(self, *args, **kwargs):
+    return self.request('POST', *args, **kwargs)
+
+  def request(self, method, endpoint, timeout=None, access_token=None, **params):
+    return api_get(endpoint, method=method, timeout=timeout, access_token=access_token, **params)
+
+  def get_token(self):
+    now = datetime.utcnow()
+    payload = {
+      'identity': self.dongle_id,
+      'nbf': now,
+      'iat': now,
+      'exp': now + timedelta(hours=1)
+    }
+    return jwt.encode(payload, self.private_key, algorithm='RS256').decode('utf8')
+
 def api_get(endpoint, method='GET', timeout=None, access_token=None, **params):
   backend = "https://api.commadotai.com/"
 

common/apk.py

@@ -0,0 +1,99 @@
+import os
+import subprocess
+import glob
+import hashlib
+import shutil
+from common.basedir import BASEDIR
+from selfdrive.swaglog import cloudlog
+
+android_packages = ("ai.comma.plus.offroad", "ai.comma.plus.frame")
+
+def get_installed_apks():
+  dat = subprocess.check_output(["pm", "list", "packages", "-f"], encoding='utf8').strip().split("\n")
+  ret = {}
+  for x in dat:
+    if x.startswith("package:"):
+      v,k = x.split("package:")[1].split("=")
+      ret[k] = v
+  return ret
+
+def install_apk(path):
+  # can only install from world readable path
+  install_path = "/sdcard/%s" % os.path.basename(path)
+  shutil.copyfile(path, install_path)
+
+  ret = subprocess.call(["pm", "install", "-r", install_path])
+  os.remove(install_path)
+  return ret == 0
+
+def start_frame():
+  set_package_permissions()
+  system("am start -n ai.comma.plus.frame/.MainActivity")
+
+def set_package_permissions():
+  pm_grant("ai.comma.plus.offroad", "android.permission.ACCESS_FINE_LOCATION")
+  pm_grant("ai.comma.plus.offroad", "android.permission.READ_PHONE_STATE")
+  appops_set("ai.comma.plus.offroad", "SU", "allow")
+  appops_set("ai.comma.plus.offroad", "WIFI_SCAN", "allow")
+  appops_set("ai.comma.plus.offroad", "READ_EXTERNAL_STORAGE", "allow")
+  appops_set("ai.comma.plus.offroad", "WRITE_EXTERNAL_STORAGE", "allow")
+
+def appops_set(package, op, mode):
+  system(f"LD_LIBRARY_PATH= appops set {package} {op} {mode}")
+
+def pm_grant(package, permission):
+  system(f"pm grant {package} {permission}")
+
+def system(cmd):
+  try:
+    cloudlog.info("running %s" % cmd)
+    subprocess.check_output(cmd, stderr=subprocess.STDOUT, shell=True)
+  except subprocess.CalledProcessError as e:
+    cloudlog.event("running failed",
+      cmd=e.cmd,
+      output=e.output[-1024:],
+      returncode=e.returncode)
+
+# *** external functions ***
+
+def update_apks():
+  # install apks
+  installed = get_installed_apks()
+
+  install_apks = glob.glob(os.path.join(BASEDIR, "apk/*.apk"))
+  for apk in install_apks:
+    app = os.path.basename(apk)[:-4]
+    if app not in installed:
+      installed[app] = None
+
+  cloudlog.info("installed apks %s" % (str(installed), ))
+
+  for app in installed.keys():
+    apk_path = os.path.join(BASEDIR, "apk/"+app+".apk")
+    if not os.path.exists(apk_path):
+      continue
+
+    h1 = hashlib.sha1(open(apk_path, 'rb').read()).hexdigest()
+    h2 = None
+    if installed[app] is not None:
+      h2 = hashlib.sha1(open(installed[app], 'rb').read()).hexdigest()
+      cloudlog.info("comparing version of %s  %s vs %s" % (app, h1, h2))
+
+    if h2 is None or h1 != h2:
+      cloudlog.info("installing %s" % app)
+
+      success = install_apk(apk_path)
+      if not success:
+        cloudlog.info("needing to uninstall %s" % app)
+        system("pm uninstall %s" % app)
+        success = install_apk(apk_path)
+
+      assert success
+
+def pm_apply_packages(cmd):
+  for p in android_packages:
+    system("pm %s %s" % (cmd, p))
+
+if __name__ == "__main__":
+  update_apks()
+

common/basedir.py

@@ -1,4 +1,11 @@
 import os
 BASEDIR = os.path.abspath(os.path.join(os.path.dirname(os.path.realpath(__file__)), "../"))
 
+from common.android import ANDROID
+if ANDROID:
+  PERSIST = "/persist"
+  PARAMS = "/data/params"
+else:
+  PERSIST = os.path.join(BASEDIR, "persist")
+  PARAMS = os.path.join(BASEDIR, "persist", "params")
 

common/clock.pyx

@@ -0,0 +1,22 @@
+from posix.time cimport clock_gettime, timespec, CLOCK_MONOTONIC_RAW, clockid_t
+
+IF UNAME_SYSNAME == "Darwin":
+  # Darwin doesn't have a CLOCK_BOOTTIME
+  CLOCK_BOOTTIME = CLOCK_MONOTONIC_RAW
+ELSE:
+  from posix.time cimport CLOCK_BOOTTIME
+
+cdef double readclock(clockid_t clock_id):
+  cdef timespec ts
+  cdef double current
+
+  clock_gettime(clock_id, &ts)
+  current = ts.tv_sec + (ts.tv_nsec / 1000000000.)
+  return current
+
+def monotonic_time():
+  return readclock(CLOCK_MONOTONIC_RAW)
+
+def sec_since_boot():
+  return readclock(CLOCK_BOOTTIME)
+

common/column_store.py

@@ -0,0 +1,150 @@
+import os
+import numpy as np
+import collections
+from contextlib import closing
+
+from common.file_helpers import mkdirs_exists_ok
+
+class ColumnStoreReader():
+  def __init__(self, path, mmap=False, allow_pickle=False, direct_io=False):
+    if not (path and os.path.isdir(path)):
+      raise ValueError("Not a column store: {}".format(path))
+
+    self._path = os.path.realpath(path)
+    self._keys = os.listdir(self._path)
+    self._mmap = mmap
+    self._allow_pickle = allow_pickle
+    self._direct_io = direct_io
+
+  @property
+  def path(self):
+    return self._path
+
+  def close(self):
+    pass
+
+  def get(self, key):
+    try:
+      return self[key]
+    except KeyError:
+      return None
+
+  def keys(self):
+    return list(self._keys)
+
+  def iteritems(self):
+    for k in self:
+      yield (k, self[k])
+
+  def itervalues(self):
+    for k in self:
+      yield self[k]
+
+  def get_npy_path(self, key):
+    """Gets a filesystem path for an npy file containing the specified array,
+       or none if the column store does not contain key.
+    """
+    if key in self:
+      return os.path.join(self._path, key)
+    else:
+      return None
+
+  def __getitem__(self, key):
+    try:
+      path = os.path.join(self._path, key)
+
+      # TODO(mgraczyk): This implementation will need to change for zip.
+      if os.path.isdir(path):
+        return ColumnStoreReader(path)
+      else:
+        if self._mmap:
+          # note that direct i/o does nothing for mmap since file read/write interface is not used
+          ret = np.load(path, mmap_mode='r', allow_pickle=self._allow_pickle, fix_imports=False)
+        else:
+          if self._direct_io:
+            opener = lambda path, flags: os.open(path, os.O_RDONLY | os.O_DIRECT)
+            with open(path, 'rb', buffering=0, opener=opener) as f:
+              ret = np.load(f, allow_pickle=self._allow_pickle, fix_imports=False)
+          else:
+            ret = np.load(path, allow_pickle=self._allow_pickle, fix_imports=False)
+        if type(ret) == np.lib.npyio.NpzFile:
+          # if it's saved as compressed, it has arr_0 only in the file. deref this
+          return ret['arr_0']
+        else:
+          return ret
+    except IOError:
+      raise KeyError(key)
+
+  def __contains__(self, item):
+    try:
+      self[item]
+      return True
+    except KeyError:
+      return False
+
+  def __len__(self):
+    return len(self._keys)
+
+  def __bool__(self):
+    return bool(self._keys)
+
+  def __iter__(self):
+    return iter(self._keys)
+
+  def __str__(self):
+    return "ColumnStoreReader({})".format(str({k: "..." for k in self._keys}))
+
+  def __enter__(self): return self
+  def __exit__(self, type, value, traceback): self.close()
+
+class ColumnStoreWriter():
+  def __init__(self, path, allow_pickle=False):
+    self._path = path
+    self._allow_pickle = allow_pickle
+    mkdirs_exists_ok(self._path)
+
+  def map_column(self, path, dtype, shape):
+    npy_path = os.path.join(self._path, path)
+    mkdirs_exists_ok(os.path.dirname(npy_path))
+    return np.lib.format.open_memmap(npy_path, mode='w+', dtype=dtype, shape=shape)
+
+  def add_column(self, path, data, dtype=None, compression=False, overwrite=False):
+    npy_path = os.path.join(self._path, path)
+    mkdirs_exists_ok(os.path.dirname(npy_path))
+
+    if overwrite:
+      f = open(npy_path, "wb")
+    else:
+      f = os.fdopen(os.open(npy_path, os.O_WRONLY | os.O_CREAT | os.O_EXCL), "wb")
+
+    with closing(f) as f:
+      data2 = np.array(data, copy=False, dtype=dtype)
+      if compression:
+        np.savez_compressed(f, data2)
+      else:
+        np.save(f, data2, allow_pickle=self._allow_pickle, fix_imports=False)
+
+  def add_group(self, group_name):
+    # TODO(mgraczyk): This implementation will need to change if we add zip or compression.
+    return ColumnStoreWriter(os.path.join(self._path, group_name))
+
+  def close(self):
+    pass
+
+  def __enter__(self): return self
+  def __exit__(self, type, value, traceback): self.close()
+
+
+def _save_dict_as_column_store(values, writer):
+  for k, v in values.items():
+    if isinstance(v, collections.Mapping):
+      _save_dict_as_column_store(v, writer.add_group(k))
+    else:
+      writer.add_column(k, v)
+
+
+def save_dict_as_column_store(values, output_path):
+  with ColumnStoreWriter(output_path) as writer:
+    _save_dict_as_column_store(values, writer)
+
+

common/common_pyx_setup.py

@@ -0,0 +1,20 @@
+from distutils.core import Extension, setup  # pylint: disable=import-error,no-name-in-module
+from Cython.Build import cythonize
+
+from common.cython_hacks import BuildExtWithoutPlatformSuffix
+
+sourcefiles = ['clock.pyx']
+extra_compile_args = ["-std=c++11"]
+
+setup(name='Common',
+      cmdclass={'build_ext': BuildExtWithoutPlatformSuffix},
+      ext_modules=cythonize(
+        Extension(
+          "common_pyx",
+          language="c++",
+          sources=sourcefiles,
+          extra_compile_args=extra_compile_args,
+        )
+      ),
+      nthreads=4,
+)

common/compat.py

@@ -0,0 +1,3 @@
+# py2,3 compatiblity helpers
+
+basestring = (str, bytes)

common/cython_hacks.py

@@ -0,0 +1,23 @@
+import os
+import sysconfig
+from Cython.Distutils import build_ext
+
+def get_ext_filename_without_platform_suffix(filename):
+  name, ext = os.path.splitext(filename)
+  ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
+
+  if ext_suffix == ext:
+    return filename
+
+  ext_suffix = ext_suffix.replace(ext, '')
+  idx = name.find(ext_suffix)
+
+  if idx == -1:
+    return filename
+  else:
+    return name[:idx] + ext
+
+class BuildExtWithoutPlatformSuffix(build_ext):
+  def get_ext_filename(self, ext_name):
+    filename = super().get_ext_filename(ext_name)
+    return get_ext_filename_without_platform_suffix(filename)

common/dbc.py

@@ -1,220 +0,0 @@
-import re
-import os
-import struct
-import bitstring
-import sys
-import numbers
-from collections import namedtuple
-
-def int_or_float(s):
-  # return number, trying to maintain int format
-  try:
-    return int(s)
-  except ValueError:
-    return float(s)
-
-DBCSignal = namedtuple(
-  "DBCSignal", ["name", "start_bit", "size", "is_little_endian", "is_signed",
-                "factor", "offset", "tmin", "tmax", "units"])
-
-class dbc(object):
-  def __init__(self, fn):
-    self.name, _ = os.path.splitext(os.path.basename(fn))
-    with open(fn) as f:
-      self.txt = f.read().split("\n")
-    self._warned_addresses = set()
-
-    # regexps from https://github.com/ebroecker/canmatrix/blob/master/canmatrix/importdbc.py
-    bo_regexp = re.compile(r"^BO\_ (\w+) (\w+) *: (\w+) (\w+)")
-    sg_regexp = re.compile(r"^SG\_ (\w+) : (\d+)\|(\d+)@(\d+)([\+|\-]) \(([0-9.+\-eE]+),([0-9.+\-eE]+)\) \[([0-9.+\-eE]+)\|([0-9.+\-eE]+)\] \"(.*)\" (.*)")
-    sgm_regexp = re.compile(r"^SG\_ (\w+) (\w+) *: (\d+)\|(\d+)@(\d+)([\+|\-]) \(([0-9.+\-eE]+),([0-9.+\-eE]+)\) \[([0-9.+\-eE]+)\|([0-9.+\-eE]+)\] \"(.*)\" (.*)")
-
-    # A dictionary which maps message ids to tuples ((name, size), signals).
-    #   name is the ASCII name of the message.
-    #   size is the size of the message in bytes.
-    #   signals is a list signals contained in the message.
-    # signals is a list of DBCSignal in order of increasing start_bit.
-    self.msgs = {}
-
-    # lookup to bit reverse each byte
-    self.bits_index = [(i & ~0b111) + ((-i-1) & 0b111) for i in xrange(64)]
-
-    for l in self.txt:
-      l = l.strip()
-
-      if l.startswith("BO_ "):
-        # new group
-        dat = bo_regexp.match(l)
-
-        if dat is None:
-          print "bad BO", l
-        name = dat.group(2)
-        size = int(dat.group(3))
-        ids = int(dat.group(1), 0) # could be hex
-        if ids in self.msgs:
-          sys.exit("Duplicate address detected %d %s" % (ids, self.name))
-
-        self.msgs[ids] = ((name, size), [])
-
-      if l.startswith("SG_ "):
-        # new signal
-        dat = sg_regexp.match(l)
-        go = 0
-        if dat is None:
-          dat = sgm_regexp.match(l)
-          go = 1
-        if dat is None:
-          print "bad SG", l
-
-        sgname = dat.group(1)
-        start_bit = int(dat.group(go+2))
-        signal_size = int(dat.group(go+3))
-        is_little_endian = int(dat.group(go+4))==1
-        is_signed = dat.group(go+5)=='-'
-        factor = int_or_float(dat.group(go+6))
-        offset = int_or_float(dat.group(go+7))
-        tmin = int_or_float(dat.group(go+8))
-        tmax = int_or_float(dat.group(go+9))
-        units = dat.group(go+10)
-
-        self.msgs[ids][1].append(
-          DBCSignal(sgname, start_bit, signal_size, is_little_endian,
-                    is_signed, factor, offset, tmin, tmax, units))
-
-    for msg in self.msgs.viewvalues():
-      msg[1].sort(key=lambda x: x.start_bit)
-
-    self.msg_name_to_address = {}
-    for address, m in self.msgs.items():
-      name = m[0][0]
-      self.msg_name_to_address[name] = address
-
-  def lookup_msg_id(self, msg_id):
-    if not isinstance(msg_id, numbers.Number):
-      msg_id = self.msg_name_to_address[msg_id]
-    return msg_id
-
-  def encode(self, msg_id, dd):
-    """Encode a CAN message using the dbc.
-
-       Inputs:
-        msg_id: The message ID.
-        dd: A dictionary mapping signal name to signal data.
-    """
-    msg_id = self.lookup_msg_id(msg_id)
-
-    # TODO: Stop using bitstring, which is super slow.
-    msg_def = self.msgs[msg_id]
-    size = msg_def[0][1]
-
-    bsf = bitstring.Bits(hex="00"*size)
-    for s in msg_def[1]:
-      ival = dd.get(s.name)
-      if ival is not None:
-        ival = (ival / s.factor) - s.offset
-        ival = int(round(ival))
-
-        # should pack this
-        if s.is_little_endian:
-          ss = s.start_bit
-        else:
-          ss = self.bits_index[s.start_bit]
-
-
-        if s.is_signed:
-          tbs = bitstring.Bits(int=ival, length=s.size)
-        else:
-          tbs = bitstring.Bits(uint=ival, length=s.size)
-
-        lpad = bitstring.Bits(bin="0b"+"0"*ss)
-        rpad = bitstring.Bits(bin="0b"+"0"*(8*size-(ss+s.size)))
-        tbs = lpad+tbs+rpad
-
-        bsf |= tbs
-    return bsf.tobytes()
-
-  def decode(self, x, arr=None, debug=False):
-    """Decode a CAN message using the dbc.
-
-       Inputs:
-        x: A collection with elements (address, time, data), where address is
-           the CAN address, time is the bus time, and data is the CAN data as a
-           hex string.
-        arr: Optional list of signals which should be decoded and returned.
-        debug: True to print debugging statements.
-
-       Returns:
-        A tuple (name, data), where name is the name of the CAN message and data
-        is the decoded result. If arr is None, data is a dict of properties.
-        Otherwise data is a list of the same length as arr.
-
-        Returns (None, None) if the message could not be decoded.
-    """
-
-    if arr is None:
-      out = {}
-    else:
-      out = [None]*len(arr)
-
-    msg = self.msgs.get(x[0])
-    if msg is None:
-      if x[0] not in self._warned_addresses:
-        #print("WARNING: Unknown message address {}".format(x[0]))
-        self._warned_addresses.add(x[0])
-      return None, None
-
-    name = msg[0][0]
-    if debug:
-      print name
-
-    blen = 8*len(x[2])
-
-    st = x[2].rjust(8, '\x00')
-    le, be = None, None
-
-    for s in msg[1]:
-      if arr is not None and s[0] not in arr:
-        continue
-
-      # big or little endian?
-      #   see http://vi-firmware.openxcplatform.com/en/master/config/bit-numbering.html
-      if s[3] is False:
-        ss = self.bits_index[s[1]]
-        if be is None:
-          be = struct.unpack(">Q", st)[0]
-        x2_int = be
-        data_bit_pos = (blen - (ss + s[2]))
-      else:
-        if le is None:
-          le = struct.unpack("<Q", st)[0]
-        x2_int = le
-        ss = s[1]
-        data_bit_pos = ss
-
-      if data_bit_pos < 0:
-        continue
-      ival = (x2_int >> data_bit_pos) & ((1 << (s[2])) - 1)
-
-      if s[4] and (ival & (1<<(s[2]-1))): # signed
-        ival -= (1<<s[2])
-
-      # control the offset
-      ival = (ival * s[5]) + s[6]
-      #if debug:
-      #  print "%40s  %2d %2d  %7.2f %s" % (s[0], s[1], s[2], ival, s[-1])
-
-      if arr is None:
-        out[s[0]] = ival
-      else:
-        out[arr.index(s[0])] = ival
-    return name, out
-
-  def get_signals(self, msg):
-    msg = self.lookup_msg_id(msg)
-    return [sgs.name for sgs in self.msgs[msg][1]]
-
-if __name__ == "__main__":
-   from opendbc import DBC_PATH
-
-   dbc_test = dbc(os.path.join(DBC_PATH, sys.argv[1]))
-   print dbc_test.get_signals(0xe4)

common/ffi_wrapper.py

@@ -0,0 +1,55 @@
+import os
+import sys
+import fcntl
+import hashlib
+import platform
+from cffi import FFI
+
+def suffix():
+  if platform.system() == "Darwin":
+    return ".dylib"
+  else:
+    return ".so"
+
+def ffi_wrap(name, c_code, c_header, tmpdir="/tmp/ccache", cflags="", libraries=None):
+  if libraries is None:
+    libraries = []
+
+  cache = name + "_" + hashlib.sha1(c_code.encode('utf-8')).hexdigest()
+  try:
+    os.mkdir(tmpdir)
+  except OSError:
+    pass
+
+  fd = os.open(tmpdir, 0)
+  fcntl.flock(fd, fcntl.LOCK_EX)
+  try:
+    sys.path.append(tmpdir)
+    try:
+      mod = __import__(cache)
+    except Exception:
+      print("cache miss {0}".format(cache))
+      compile_code(cache, c_code, c_header, tmpdir, cflags, libraries)
+      mod = __import__(cache)
+  finally:
+    os.close(fd)
+
+  return mod.ffi, mod.lib
+
+
+def compile_code(name, c_code, c_header, directory, cflags="", libraries=None):
+  if libraries is None:
+    libraries = []
+
+  ffibuilder = FFI()
+  ffibuilder.set_source(name, c_code, source_extension='.cpp', libraries=libraries)
+  ffibuilder.cdef(c_header)
+  os.environ['OPT'] = "-fwrapv -O2 -DNDEBUG -std=c++11"
+  os.environ['CFLAGS'] = cflags
+  ffibuilder.compile(verbose=True, debug=False, tmpdir=directory)
+
+
+def wrap_compiled(name, directory):
+  sys.path.append(directory)
+  mod = __import__(name)
+  return mod.ffi, mod.lib

common/file_helpers.py

@@ -0,0 +1,109 @@
+import os
+import shutil
+import tempfile
+from atomicwrites import AtomicWriter
+
+def mkdirs_exists_ok(path):
+  try:
+    os.makedirs(path)
+  except OSError:
+    if not os.path.isdir(path):
+      raise
+
+def rm_not_exists_ok(path):
+  try:
+    os.remove(path)
+  except OSError:
+    if os.path.exists(path):
+      raise
+
+def rm_tree_or_link(path):
+  if os.path.islink(path):
+    os.unlink(path)
+  elif os.path.isdir(path):
+    shutil.rmtree(path)
+
+def get_tmpdir_on_same_filesystem(path):
+  normpath = os.path.normpath(path)
+  parts = normpath.split("/")
+  if len(parts) > 1 and parts[1] == "scratch":
+    return "/scratch/tmp"
+  elif len(parts) > 2 and parts[2] == "runner":
+    return "/{}/runner/tmp".format(parts[1])
+  return "/tmp"
+
+class AutoMoveTempdir():
+  def __init__(self, target_path, temp_dir=None):
+    self._target_path = target_path
+    self._path = tempfile.mkdtemp(dir=temp_dir)
+
+  @property
+  def name(self):
+    return self._path
+
+  def close(self):
+    os.rename(self._path, self._target_path)
+
+  def __enter__(self): return self
+
+  def __exit__(self, type, value, traceback):
+    if type is None:
+      self.close()
+    else:
+      shutil.rmtree(self._path)
+
+class NamedTemporaryDir():
+  def __init__(self, temp_dir=None):
+    self._path = tempfile.mkdtemp(dir=temp_dir)
+
+  @property
+  def name(self):
+    return self._path
+
+  def close(self):
+    shutil.rmtree(self._path)
+
+  def __enter__(self): return self
+
+  def __exit__(self, type, value, traceback):
+    self.close()
+
+def _get_fileobject_func(writer, temp_dir):
+  def _get_fileobject():
+    file_obj = writer.get_fileobject(dir=temp_dir)
+    os.chmod(file_obj.name, 0o644)
+    return file_obj
+  return _get_fileobject
+
+def atomic_write_on_fs_tmp(path, **kwargs):
+  """Creates an atomic writer using a temporary file in a temporary directory
+     on the same filesystem as path.
+  """
+  # TODO(mgraczyk): This use of AtomicWriter relies on implementation details to set the temp
+  #                 directory.
+  writer = AtomicWriter(path, **kwargs)
+  return writer._open(_get_fileobject_func(writer, get_tmpdir_on_same_filesystem(path)))
+
+
+def atomic_write_in_dir(path, **kwargs):
+  """Creates an atomic writer using a temporary file in the same directory
+     as the destination file.
+  """
+  writer = AtomicWriter(path, **kwargs)
+  return writer._open(_get_fileobject_func(writer, os.path.dirname(path)))
+
+def atomic_write_in_dir_neos(path, contents, mode=None):
+  """
+  Atomically writes contents to path using a temporary file in the same directory
+  as path. Useful on NEOS, where `os.link` (required by atomic_write_in_dir) is missing.
+  """
+
+  f = tempfile.NamedTemporaryFile(delete=False, prefix=".tmp", dir=os.path.dirname(path))
+  f.write(contents)
+  f.flush()
+  if mode is not None:
+    os.fchmod(f.fileno(), mode)
+  os.fsync(f.fileno())
+  f.close()
+
+  os.rename(f.name, path)

common/filter_simple.py

@@ -0,0 +1,10 @@
+class FirstOrderFilter():
+  # first order filter
+  def __init__(self, x0, ts, dt):
+    self.k = (dt / ts) / (1. + dt / ts)
+    self.x = x0
+
+  def update(self, x):
+    self.x = (1. - self.k) * self.x + self.k * x
+
+

common/fingerprints.py

@@ -1,64 +0,0 @@
-import os
-from common.basedir import BASEDIR
-
-def get_fingerprint_list():
-  # read all the folders in selfdrive/car and return a dict where:
-  # - keys are all the car models for which we have a fingerprint
-  # - values are lists dicts of messages that constitute the unique 
-  #   CAN fingerprint of each car model and all its variants
-  fingerprints = {}
-  for car_folder in [x[0] for x in os.walk(BASEDIR + '/selfdrive/car')]:
-    try:
-      car_name = car_folder.split('/')[-1]
-      values = __import__('selfdrive.car.%s.values' % car_name, fromlist=['FINGERPRINTS'])
-      if hasattr(values, 'FINGERPRINTS'):
-        car_fingerprints = values.FINGERPRINTS
-      else:
-        continue
-      for f, v in car_fingerprints.iteritems():
-        fingerprints[f] = v
-    except (ImportError, IOError):
-      pass
-  return fingerprints
-
-
-_FINGERPRINTS = get_fingerprint_list()
-
-_DEBUG_ADDRESS = {1880: 8}   # reserved for debug purposes
-
-def is_valid_for_fingerprint(msg, car_fingerprint):
-  adr = msg.address
-  bus = msg.src
-  # ignore addresses that are more than 11 bits
-  return (adr in car_fingerprint and car_fingerprint[adr] == len(msg.dat)) or \
-         bus != 0 or adr >= 0x800
-
-
-def eliminate_incompatible_cars(msg, candidate_cars):
-  """Removes cars that could not have sent msg.
-
-     Inputs:
-      msg: A cereal/log CanData message from the car.
-      candidate_cars: A list of cars to consider.
-
-     Returns:
-      A list containing the subset of candidate_cars that could have sent msg.
-  """
-  compatible_cars = []
-
-  for car_name in candidate_cars:
-    car_fingerprints = _FINGERPRINTS[car_name]
-
-    for fingerprint in car_fingerprints:
-      fingerprint.update(_DEBUG_ADDRESS)  # add alien debug address
-
-      if is_valid_for_fingerprint(msg, fingerprint):
-        compatible_cars.append(car_name)
-        break
-
-  return compatible_cars
-
-
-def all_known_cars():
-  """Returns a list of all known car strings."""
-  return _FINGERPRINTS.keys()

common/geocode/reverse.py

@@ -0,0 +1,24 @@
+import numpy as np
+import os
+import csv
+path = os.path.dirname(os.path.abspath(__file__))
+# locally cache cities from
+# https://github.com/thampiman/reverse-geocoder
+csv_file_name = path + '/rg_cities1000.csv'
+
+# right hand drive is when the steering wheel is on the right of the car
+# left hand traffic is when cars driver on the left side of the road
+LHT_COUNTRIES = ['AU', 'IN', 'IE', 'JP', 'MU', 'MY', 'NZ', 'UK', 'ZA']
+
+
+def get_city(lat, lon):
+  cities = np.array(list(csv.reader(open(csv_file_name))))[1:]
+  positions = cities[:,:2].astype(np.float32)
+  idx = np.argmin(np.linalg.norm((positions - np.array([lat, lon])), axis=1))
+  return cities[idx]
+
+
+def is_lht(lat, lon):
+  city = get_city(lat, lon)
+  country = city[-1]
+  return country in LHT_COUNTRIES

common/kalman/.gitignore

@@ -0,0 +1 @@
+simple_kalman_impl.c

common/kalman/SConscript

@@ -0,0 +1,6 @@
+Import('env')
+
+env.Command(['simple_kalman_impl.so'],
+  ['simple_kalman_impl.pyx', 'simple_kalman_impl.pxd', 'simple_kalman_setup.py'],
+  "cd common/kalman && python3 simple_kalman_setup.py build_ext --inplace")
+

common/kalman/ekf.py

@@ -1,252 +0,0 @@
-# pylint: skip-file
-import abc
-import numpy as np
-# The EKF class contains the framework for an Extended Kalman Filter, but must be subclassed to use.
-# A subclass must implement:
-#   1) calc_transfer_fun(); see bottom of file for more info.
-#   2) __init__() to initialize self.state, self.covar, and self.process_noise appropriately
-
-# Alternatively, the existing implementations of EKF can be used (e.g. EKF2D)
-
-# Sensor classes are optionally used to pass measurement information into the EKF, to keep
-#   sensor parameters and processing methods for a each sensor together.
-# Sensor classes have a read() method which takes raw sensor data and returns
-#   a SensorReading object, which can be passed to the EKF update() method.
-
-# For usage, see run_ekf1d.py in selfdrive/new for a simple example.
-# ekf.predict(dt) should be called between update cycles with the time since it was last called.
-# Ideally, predict(dt) should be called at a relatively constant rate.
-# update() should be called once per sensor, and can be called multiple times between predict steps.
-# Access and set the state of the filter directly with ekf.state and ekf.covar.
-
-
-class SensorReading:
-  # Given a perfect model and no noise, data = obs_model * state
-  def __init__(self, data, covar, obs_model):
-    self.data = data
-    self.obs_model = obs_model
-    self.covar = covar
-
-  def __repr__(self):
-    return "SensorReading(data={}, covar={}, obs_model={})".format(
-      repr(self.data), repr(self.covar), repr(self.obs_model))
-
-
-# A generic sensor class that does no pre-processing of data
-class SimpleSensor:
-  # obs_model can be
-  #   a full observation model matrix, or
-  #   an integer or tuple of indices into ekf.state, indicating which variables are being directly observed
-  # covar can be
-  #   a full covariance matrix
-  #   a float or tuple of individual covars for each component of the sensor reading
-  # dims is the number of states in the EKF
-  def __init__(self, obs_model, covar, dims):
-    # Allow for integer covar/obs_model
-    if not hasattr(obs_model, "__len__"):
-      obs_model = (obs_model, )
-    if not hasattr(covar, "__len__"):
-      covar = (covar, )
-
-    # Full observation model passed
-    if dims in np.array(obs_model).shape:
-      self.obs_model = np.asmatrix(obs_model)
-      self.covar = np.asmatrix(covar)
-    # Indices of unit observations passed
-    else:
-      self.obs_model = np.matlib.zeros((len(obs_model), dims))
-      self.obs_model[:, list(obs_model)] = np.identity(len(obs_model))
-      if np.asarray(covar).ndim == 2:
-        self.covar = np.asmatrix(covar)
-      elif len(covar) == len(obs_model):
-        self.covar = np.matlib.diag(covar)
-      else:
-        self.covar = np.matlib.identity(len(obs_model)) * covar
-
-  def read(self, data, covar=None):
-    if covar:
-      self.covar = covar
-    return SensorReading(data, self.covar, self.obs_model)
-
-
-class EKF:
-  __metaclass__ = abc.ABCMeta
-
-  def __init__(self, debug=False):
-    self.DEBUG = debug
-
-
-  def __str__(self):
-    return "EKF(state={}, covar={})".format(self.state, self.covar)
-
-  # Measurement update
-  # Reading should be a SensorReading object with data, covar, and obs_model attributes
-  def update(self, reading):
-    # Potential improvements:
-    # deal with negative covars
-    # add noise to really low covars to ensure stability
-    # use mahalanobis distance to reject outliers
-    # wrap angles after state updates and innovation
-
-    # y = z - H*x
-    innovation = reading.data - reading.obs_model * self.state
-
-    if self.DEBUG:
-      print "reading:\n",reading.data
-      print "innovation:\n",innovation
-
-    # S = H*P*H' + R
-    innovation_covar = reading.obs_model * self.covar * reading.obs_model.T + reading.covar
-
-    # K = P*H'*S^-1
-    kalman_gain = self.covar * reading.obs_model.T * np.linalg.inv(
-      innovation_covar)
-
-    if self.DEBUG:
-      print "gain:\n", kalman_gain
-      print "innovation_covar:\n", innovation_covar
-      print "innovation: ", innovation
-      print "test: ", self.covar * reading.obs_model.T * (
-        reading.obs_model * self.covar * reading.obs_model.T + reading.covar *
-        0).I
-
-    # x = x + K*y
-    self.state += kalman_gain*innovation
-
-    # print "covar", np.diag(self.covar)
-    #self.state[(roll_vel, yaw_vel, pitch_vel),:] = reading.data
-
-    # Standard form: P = (I - K*H)*P
-    # self.covar = (self.identity - kalman_gain*reading.obs_model) * self.covar
-
-    # Use the Joseph form for numerical stability: P = (I-K*H)*P*(I - K*H)' + K*R*K'
-    aux_mtrx = (self.identity - kalman_gain * reading.obs_model)
-    self.covar = aux_mtrx * self.covar * aux_mtrx.T + kalman_gain * reading.covar * kalman_gain.T
-
-    if self.DEBUG:
-      print "After update"
-      print "state\n", self.state
-      print "covar:\n",self.covar
-
-  def update_scalar(self, reading):
-    # like update but knowing that measurement is a scalar
-    # this avoids matrix inversions and speeds up (surprisingly) drived.py a lot
-
-    # innovation = reading.data - np.matmul(reading.obs_model, self.state)
-    # innovation_covar = np.matmul(np.matmul(reading.obs_model, self.covar), reading.obs_model.T) + reading.covar
-    # kalman_gain = np.matmul(self.covar, reading.obs_model.T)/innovation_covar
-    # self.state += np.matmul(kalman_gain, innovation)
-    # aux_mtrx = self.identity - np.matmul(kalman_gain, reading.obs_model)
-    # self.covar =  np.matmul(aux_mtrx, np.matmul(self.covar, aux_mtrx.T)) + np.matmul(kalman_gain, np.matmul(reading.covar, kalman_gain.T))
-
-    # written without np.matmul
-    es = np.einsum
-    ABC_T = "ij,jk,lk->il"
-    AB_T = "ij,kj->ik"
-    AB = "ij,jk->ik"
-    innovation = reading.data - es(AB, reading.obs_model, self.state)
-    innovation_covar = es(ABC_T, reading.obs_model, self.covar,
-                          reading.obs_model) + reading.covar
-    kalman_gain = es(AB_T, self.covar, reading.obs_model) / innovation_covar
-
-    self.state += es(AB, kalman_gain, innovation)
-    aux_mtrx = self.identity - es(AB, kalman_gain, reading.obs_model)
-    self.covar = es(ABC_T, aux_mtrx, self.covar, aux_mtrx) + \
-                 es(ABC_T, kalman_gain, reading.covar, kalman_gain)
-
-  # Prediction update
-  def predict(self, dt):
-    es = np.einsum
-    ABC_T = "ij,jk,lk->il"
-    AB = "ij,jk->ik"
-
-    # State update
-    transfer_fun, transfer_fun_jacobian = self.calc_transfer_fun(dt)
-
-    # self.state = np.matmul(transfer_fun, self.state)
-    # self.covar = np.matmul(np.matmul(transfer_fun_jacobian, self.covar), transfer_fun_jacobian.T) + self.process_noise * dt
-
-    # x = f(x, u), written in the form x = A(x, u)*x
-    self.state = es(AB, transfer_fun, self.state)
-
-    # P = J*P*J' + Q
-    self.covar = es(ABC_T, transfer_fun_jacobian, self.covar,
-                    transfer_fun_jacobian) + self.process_noise * dt  #!dt
-
-    #! Clip covariance to avoid explosions
-    self.covar = np.clip(self.covar,-1e10,1e10)
-
-  @abc.abstractmethod
-  def calc_transfer_fun(self, dt):
-    """Return a tuple with the transfer function and transfer function jacobian
-    The transfer function and jacobian should both be a numpy matrix of size DIMSxDIMS
-
-    The transfer function matrix A should satisfy the state-update equation
-      x_(k+1) = A * x_k
-
-    The jacobian J is the direct jacobian A*x_k. For linear systems J=A.
-
-    Current implementations calculate A and J as functions of state. Control input
-      can be added trivially by adding a control parameter to predict() and calc_tranfer_update(),
-      and using it during calculation of A and J
-    """
-
-
-class FastEKF1D(EKF):
-  """Fast version of EKF for 1D problems with scalar readings."""
-
-  def __init__(self, dt, var_init, Q):
-    super(FastEKF1D, self).__init__(False)
-    self.state = [0, 0]
-    self.covar = [var_init, var_init, 0]
-
-    # Process Noise
-    self.dtQ0 = dt * Q[0]
-    self.dtQ1 = dt * Q[1]
-
-  def update(self, reading):
-    raise NotImplementedError
-
-  def update_scalar(self, reading):
-    # TODO(mgraczyk): Delete this for speed.
-    # assert np.all(reading.obs_model == [1, 0])
-
-    rcov = reading.covar[0, 0]
-
-    x = self.state
-    S = self.covar
-
-    innovation = reading.data - x[0]
-    innovation_covar = S[0] + rcov
-
-    k0 = S[0] / innovation_covar
-    k1 = S[2] / innovation_covar
-
-    x[0] += k0 * innovation
-    x[1] += k1 * innovation
-
-    mk = 1 - k0
-    S[1] += k1 * (k1 * (S[0] + rcov) - 2 * S[2])
-    S[2] = mk * (S[2] - k1 * S[0]) + rcov * k0 * k1
-    S[0] = mk * mk * S[0] + rcov * k0 * k0
-
-  def predict(self, dt):
-    # State update
-    x = self.state
-
-    x[0] += dt * x[1]
-
-    # P = J*P*J' + Q
-    S = self.covar
-    S[0] += dt * (2 * S[2] + dt * S[1]) + self.dtQ0
-    S[2] += dt * S[1]
-    S[1] += self.dtQ1
-
-    # Clip covariance to avoid explosions
-    S = max(-1e10, min(S, 1e10))
-
-  def calc_transfer_fun(self, dt):
-    tf = np.identity(2)
-    tf[0, 1] = dt
-    tfj = tf
-    return tf, tfj

common/kalman/simple_kalman.py

@@ -1,23 +1,3 @@
-import numpy as np
-
-
-class KF1D:
-  # this EKF assumes constant covariance matrix, so calculations are much simpler
-  # the Kalman gain also needs to be precomputed using the control module
-
-  def __init__(self, x0, A, C, K):
-    self.x = x0
-    self.A = A
-    self.C = C
-    self.K = K
-
-    self.A_K = self.A - np.dot(self.K, self.C)
-
-    # K matrix needs to  be pre-computed as follow:
-    # import control
-    # (x, l, K) = control.dare(np.transpose(self.A), np.transpose(self.C), Q, R)
-    # self.K = np.transpose(K)
-
-  def update(self, meas):
-    self.x = np.dot(self.A_K, self.x) + np.dot(self.K, meas)
-    return self.x
+# pylint: skip-file
+from common.kalman.simple_kalman_impl import KF1D as KF1D
+assert KF1D

common/kalman/simple_kalman_impl.pxd

@@ -0,0 +1,16 @@
+cdef class KF1D:
+  cdef public:
+    double x0_0
+    double x1_0
+    double K0_0
+    double K1_0
+    double A0_0
+    double A0_1
+    double A1_0
+    double A1_1
+    double C0_0
+    double C0_1
+    double A_K_0
+    double A_K_1
+    double A_K_2
+    double A_K_3

common/kalman/simple_kalman_impl.pyx

@@ -0,0 +1,36 @@
+# cython: language_level=3
+
+cdef class KF1D:
+  def __init__(self, x0, A, C, K):
+    self.x0_0 = x0[0][0]
+    self.x1_0 = x0[1][0]
+    self.A0_0 = A[0][0]
+    self.A0_1 = A[0][1]
+    self.A1_0 = A[1][0]
+    self.A1_1 = A[1][1]
+    self.C0_0 = C[0]
+    self.C0_1 = C[1]
+    self.K0_0 = K[0][0]
+    self.K1_0 = K[1][0]
+
+    self.A_K_0 = self.A0_0 - self.K0_0 * self.C0_0
+    self.A_K_1 = self.A0_1 - self.K0_0 * self.C0_1
+    self.A_K_2 = self.A1_0 - self.K1_0 * self.C0_0
+    self.A_K_3 = self.A1_1 - self.K1_0 * self.C0_1
+
+  def update(self, meas):
+    cdef double x0_0 = self.A_K_0 * self.x0_0 + self.A_K_1 * self.x1_0 + self.K0_0 * meas
+    cdef double x1_0 = self.A_K_2 * self.x0_0 + self.A_K_3 * self.x1_0 + self.K1_0 * meas
+    self.x0_0 = x0_0
+    self.x1_0 = x1_0
+
+    return [self.x0_0, self.x1_0]
+
+  @property
+  def x(self):
+    return [[self.x0_0], [self.x1_0]]
+
+  @x.setter
+  def x(self, x):
+    self.x0_0 = x[0][0]
+    self.x1_0 = x[1][0]

common/kalman/simple_kalman_old.py

@@ -0,0 +1,23 @@
+import numpy as np
+
+
+class KF1D:
+  # this EKF assumes constant covariance matrix, so calculations are much simpler
+  # the Kalman gain also needs to be precomputed using the control module
+
+  def __init__(self, x0, A, C, K):
+    self.x = x0
+    self.A = A
+    self.C = C
+    self.K = K
+
+    self.A_K = self.A - np.dot(self.K, self.C)
+
+    # K matrix needs to  be pre-computed as follow:
+    # import control
+    # (x, l, K) = control.dare(np.transpose(self.A), np.transpose(self.C), Q, R)
+    # self.K = np.transpose(K)
+
+  def update(self, meas):
+    self.x = np.dot(self.A_K, self.x) + np.dot(self.K, meas)
+    return self.x

common/kalman/simple_kalman_setup.py

@@ -0,0 +1,9 @@
+from distutils.core import Extension, setup
+
+from Cython.Build import cythonize
+
+from common.cython_hacks import BuildExtWithoutPlatformSuffix
+
+setup(name='Simple Kalman Implementation',
+      cmdclass={'build_ext': BuildExtWithoutPlatformSuffix},
+      ext_modules=cythonize(Extension("simple_kalman_impl", ["simple_kalman_impl.pyx"])))

common/kalman/tests/test_simple_kalman.py

@@ -0,0 +1,85 @@
+import unittest
+import random
+import timeit
+import numpy as np
+
+from common.kalman.simple_kalman import KF1D
+from common.kalman.simple_kalman_old import KF1D as KF1D_old
+
+
+class TestSimpleKalman(unittest.TestCase):
+  def setUp(self):
+    dt = 0.01
+    x0_0 = 0.0
+    x1_0 = 0.0
+    A0_0 = 1.0
+    A0_1 = dt
+    A1_0 = 0.0
+    A1_1 = 1.0
+    C0_0 = 1.0
+    C0_1 = 0.0
+    K0_0 = 0.12287673
+    K1_0 = 0.29666309
+
+    self.kf_old = KF1D_old(x0=np.matrix([[x0_0], [x1_0]]),
+                           A=np.matrix([[A0_0, A0_1], [A1_0, A1_1]]),
+                           C=np.matrix([C0_0, C0_1]),
+                           K=np.matrix([[K0_0], [K1_0]]))
+
+    self.kf = KF1D(x0=[[x0_0], [x1_0]],
+                   A=[[A0_0, A0_1], [A1_0, A1_1]],
+                   C=[C0_0, C0_1],
+                   K=[[K0_0], [K1_0]])
+
+  def test_getter_setter(self):
+    self.kf.x = [[1.0], [1.0]]
+    self.assertEqual(self.kf.x, [[1.0], [1.0]])
+
+  def update_returns_state(self):
+      x = self.kf.update(100)
+      self.assertEqual(x, self.kf.x)
+
+  def test_old_equal_new(self):
+    for _ in range(1000):
+      v_wheel = random.uniform(0, 200)
+
+      x_old = self.kf_old.update(v_wheel)
+      x = self.kf.update(v_wheel)
+
+      # Compare the output x, verify that the error is less than 1e-4
+      self.assertAlmostEqual(x_old[0], x[0])
+      self.assertAlmostEqual(x_old[1], x[1])
+
+
+  def test_new_is_faster(self):
+    setup = """
+import numpy as np
+
+from common.kalman.simple_kalman import KF1D
+from common.kalman.simple_kalman_old import KF1D as KF1D_old
+
+dt = 0.01
+x0_0 = 0.0
+x1_0 = 0.0
+A0_0 = 1.0
+A0_1 = dt
+A1_0 = 0.0
+A1_1 = 1.0
+C0_0 = 1.0
+C0_1 = 0.0
+K0_0 = 0.12287673
+K1_0 = 0.29666309
+
+kf_old = KF1D_old(x0=np.matrix([[x0_0], [x1_0]]),
+                  A=np.matrix([[A0_0, A0_1], [A1_0, A1_1]]),
+                  C=np.matrix([C0_0, C0_1]),
+                  K=np.matrix([[K0_0], [K1_0]]))
+
+kf = KF1D(x0=[[x0_0], [x1_0]],
+          A=[[A0_0, A0_1], [A1_0, A1_1]],
+          C=[C0_0, C0_1],
+          K=[[K0_0], [K1_0]])
+    """
+    kf_speed = timeit.timeit("kf.update(1234)", setup=setup, number=10000)
+    kf_old_speed = timeit.timeit("kf_old.update(1234)", setup=setup, number=10000)
+    self.assertTrue(kf_speed < kf_old_speed / 4)

common/lazy_property.py

@@ -0,0 +1,12 @@
+class lazy_property():
+  """Defines a property whose value will be computed only once and as needed.
+
+     This can only be used on instance methods.
+  """
+  def __init__(self, func):
+    self._func = func
+
+  def __get__(self, obj_self, cls):
+    value = self._func(obj_self)
+    setattr(obj_self, self._func.__name__, value)
+    return value

common/loader.py

@@ -0,0 +1,284 @@
+import os
+import struct
+import bisect
+import numpy as np
+import _io
+
+import capnp
+from cereal import log as capnp_log
+
+class RawData():
+  def __init__(self, f):
+    self.f = _io.FileIO(f, 'rb')
+    self.lenn = struct.unpack("I", self.f.read(4))[0]
+    self.count = os.path.getsize(f) / (self.lenn+4)
+
+  def read(self, i):
+    self.f.seek((self.lenn+4)*i + 4)
+    return self.f.read(self.lenn)
+
+def yuv420_to_rgb(raw, image_dim=None, swizzled=False):
+  def expand(x):
+    x = np.repeat(x, 2, axis=0)
+    return np.repeat(x, 2, axis=1)
+
+  if image_dim is None:
+    image_dim = (raw.shape[1]*2, raw.shape[2]*2)
+    swizzled = True
+
+  if not swizzled:
+    img_data = np.array(raw, copy=False, dtype=np.uint8)
+    uv_len = (image_dim[0]/2)*(image_dim[1]/2)
+    img_data_u = expand(img_data[image_dim[0]*image_dim[1]: \
+                                 image_dim[0]*image_dim[1]+uv_len]. \
+                                 reshape(image_dim[0]/2, image_dim[1]/2))
+
+    img_data_v = expand(img_data[image_dim[0]*image_dim[1]+uv_len: \
+                                 image_dim[0]*image_dim[1]+2*uv_len]. \
+                                 reshape(image_dim[0]/2, image_dim[1]/2))
+    img_data_y = img_data[0:image_dim[0]*image_dim[1]].reshape(image_dim)
+  else:
+    img_data_y = np.zeros(image_dim, dtype=np.uint8)
+    img_data_y[0::2, 0::2] = raw[0]
+    img_data_y[1::2, 0::2] = raw[1]
+    img_data_y[0::2, 1::2] = raw[2]
+    img_data_y[1::2, 1::2] = raw[3]
+    img_data_u = expand(raw[4])
+    img_data_v = expand(raw[5])
+
+  yuv = np.stack((img_data_y, img_data_u, img_data_v)).swapaxes(0,2).swapaxes(0,1)
+  yuv = yuv.astype(np.int16)
+
+  # http://maxsharabayko.blogspot.com/2016/01/fast-yuv-to-rgb-conversion-in-python-3.html
+  # according to ITU-R BT.709
+  yuv[:,:, 0] = yuv[:,:, 0].clip(16, 235).astype(yuv.dtype) - 16
+  yuv[:,:,1:] = yuv[:,:,1:].clip(16, 240).astype(yuv.dtype) - 128
+
+  A = np.array([[1.164,  0.000,  1.793],
+                [1.164, -0.213, -0.533],
+                [1.164,  2.112,  0.000]])
+
+  # our result
+  img = np.dot(yuv, A.T).clip(0, 255).astype('uint8')
+  return img
+
+
+class YuvData():
+  def __init__(self, f, dim=(160,320)):
+    self.f = _io.FileIO(f, 'rb')
+    self.image_dim = dim
+    self.image_size = self.image_dim[0]/2 * self.image_dim[1]/2 * 6
+    self.count = os.path.getsize(f) / self.image_size
+
+  def read_frame(self, frame):
+    self.f.seek(self.image_size*frame)
+    raw = self.f.read(self.image_size)
+    return raw
+
+  def read_frames(self, range_start, range_len):
+    self.f.seek(self.image_size*range_start)
+    raw = self.f.read(self.image_size*range_len)
+    return raw
+
+  def read_frames_into(self, range_start, buf):
+    self.f.seek(self.image_size*range_start)
+    return self.f.readinto(buf)
+
+  def read(self, frame):
+    return yuv420_to_rgb(self.read_frame(frame), self.image_dim)
+
+  def close(self):
+    self.f.close()
+
+  def __enter__(self):
+    return self
+
+  def __exit__(self, type, value, traceback):
+    self.close()
+
+
+
+class OneReader():
+  def __init__(self, base_path, goofy=False, segment_range=None):
+    self.base_path = base_path
+
+    route_name = os.path.basename(base_path)
+
+    self.rcamera_size = (304, 560)
+
+    if segment_range is None:
+      parent_path = os.path.dirname(base_path)
+      self.segment_nums = []
+      for p in os.listdir(parent_path):
+        if not p.startswith(route_name+"--"):
+          continue
+        self.segment_nums.append(int(p.rsplit("--", 1)[-1]))
+      if not self.segment_nums:
+        raise Exception("no route segments found")
+      self.segment_nums.sort()
+      self.segment_range = (self.segment_nums[0], self.segment_nums[-1])
+    else:
+      self.segment_range = segment_range
+      self.segment_nums = range(segment_range[0], segment_range[1]+1)
+      for i in self.segment_nums:
+        if not os.path.exists(base_path+"--"+str(i)):
+          raise Exception("missing segment in provided range")
+
+    # goofy data is broken with discontinuous logs
+    if goofy and (self.segment_range[0] != 0
+        or self.segment_nums != range(self.segment_range[0], self.segment_range[1]+1)):
+      raise Exception("goofy data needs all the segments for a route")
+
+    self.cur_seg = None
+    self.cur_seg_f = None
+
+    # index the frames
+    print("indexing frames {}...".format(self.segment_nums))
+
+    self.rcamera_encode_map = {} # frame_id -> (segment num, segment id, frame_time)
+    last_frame_id = -1
+
+    if goofy:
+      # goofy is goofy
+
+      frame_size = self.rcamera_size[0]*self.rcamera_size[1]*3/2
+
+      # find the encode id ranges for each segment by using the rcamera file size
+      segment_encode_ids = []
+      cur_encode_id = 0
+      for n in self.segment_nums:
+        camera_path = os.path.join(self.seg_path(n), "rcamera")
+        if not os.path.exists(camera_path):
+          # for goofy, missing camera files means a bad route
+          raise Exception("Missing camera file {}".format(camera_path))
+        camera_size = os.path.getsize(camera_path)
+        assert (camera_size % frame_size) == 0
+
+        num_frames = camera_size / frame_size
+        segment_encode_ids.append(cur_encode_id)
+        cur_encode_id += num_frames
+
+      last_encode_id = -1
+      # use the segment encode id map and frame events to build the frame index
+      for n in self.segment_nums:
+        log_path = os.path.join(self.seg_path(n), "rlog")
+        if os.path.exists(log_path):
+          with open(log_path, "rb") as f:
+            for evt in capnp_log.Event.read_multiple(f):
+              if evt.which() == 'frame':
+
+                if evt.frame.frameId < last_frame_id:
+                  # a non-increasing frame id is bad route (eg visiond was restarted)
+                  raise Exception("non-increasing frame id")
+                last_frame_id = evt.frame.frameId
+
+                seg_i = bisect.bisect_right(segment_encode_ids, evt.frame.encodeId)-1
+                assert seg_i >= 0
+                seg_num = self.segment_nums[seg_i]
+                seg_id = evt.frame.encodeId-segment_encode_ids[seg_i]
+                frame_time = evt.logMonoTime / 1.0e9
+
+                self.rcamera_encode_map[evt.frame.frameId] = (seg_num, seg_id,
+                                                              frame_time)
+
+                last_encode_id = evt.frame.encodeId
+
+      if last_encode_id-cur_encode_id > 10:
+        # too many missing frames is a bad route (eg route from before encoder rotating worked)
+        raise Exception("goofy route is missing frames: {}, {}".format(
+          last_encode_id, cur_encode_id))
+
+    else:
+      # for harry data, build the index from encodeIdx events
+      for n in self.segment_nums:
+        log_path = os.path.join(self.seg_path(n), "rlog")
+        if os.path.exists(log_path):
+          with open(log_path, "rb") as f:
+            for evt in capnp_log.Event.read_multiple(f):
+              if evt.which() == 'encodeIdx' and evt.encodeIdx.type == 'bigBoxLossless':
+                frame_time = evt.logMonoTime / 1.0e9
+                self.rcamera_encode_map[evt.encodeIdx.frameId] = (
+                  evt.encodeIdx.segmentNum, evt.encodeIdx.segmentId,
+                  frame_time)
+
+    print("done")
+
+    # read the first event to find the start time
+    self.reset_to_seg(self.segment_range[0])
+    for evt in self.events():
+      if evt.which() != 'initData':
+        self.start_mono = evt.logMonoTime
+        break
+    self.reset_to_seg(self.segment_range[0])
+
+
+  def seg_path(self, num):
+    return self.base_path+"--"+str(num)
+
+  def reset_to_seg(self, seg):
+    self.cur_seg = seg
+    if self.cur_seg_f:
+      self.cur_seg_f.close()
+      self.cur_seg_f = None
+
+  def seek_ts(self, ts):
+    seek_seg = int(ts/60)
+    if seek_seg < self.segment_range[0] or seek_seg > self.segment_range[1]:
+      raise ValueError
+
+    self.reset_to_seg(seek_seg)
+    target_mono = self.start_mono + int(ts*1e9)
+    for evt in self.events():
+      if evt.logMonoTime >= target_mono:
+        break
+
+  def read_event(self):
+    while True:
+      if self.cur_seg > self.segment_range[1]:
+        return None
+      if self.cur_seg_f is None:
+        log_path = os.path.join(self.seg_path(self.cur_seg), "rlog")
+        if not os.path.exists(log_path):
+          print("missing log file!", log_path)
+          self.cur_seg += 1
+          continue
+        self.cur_seg_f = open(log_path, "rb")
+
+      try:
+        return capnp_log.Event.read(self.cur_seg_f)
+      except capnp.lib.capnp.KjException as e:
+        if 'EOF' in str(e): # dumb, but pycapnp does this too
+          self.cur_seg_f.close()
+          self.cur_seg_f = None
+          self.cur_seg += 1
+        else:
+          raise
+
+  def events(self):
+    while True:
+      r = self.read_event()
+      if r is None:
+        break
+      yield r
+
+  def read_frame(self, frame_id):
+    encode_idx = self.rcamera_encode_map.get(frame_id)
+    if encode_idx is None:
+      return None
+
+    seg_num, seg_id, _ = encode_idx
+    camera_path = os.path.join(self.seg_path(seg_num), "rcamera")
+    if not os.path.exists(camera_path):
+      return None
+    with YuvData(camera_path, self.rcamera_size) as data:
+      return data.read_frame(seg_id)
+
+  def close(self):
+    if self.cur_seg_f is not None:
+      self.cur_seg_f.close()
+
+  def __enter__(self):
+    return self
+
+  def __exit__(self, type, value, traceback):
+    self.close()

common/log_compressor.py

@@ -0,0 +1,92 @@
+import sys
+import json
+# pip2 install msgpack-python
+import msgpack
+import zlib
+import os
+import logging
+
+from Crypto.Cipher import AES
+
+ext = ".gz"
+SWAG = '\xde\xe2\x11\x15VVC\xf2\x8ep\xd7\xe4\x87\x8d,9'
+
+def compress_json(in_file, out_file):
+  logging.debug("compressing %s -> %s", in_file, out_file)
+
+  errors = 0
+
+  good = []
+  last_can_time = 0
+  with open(in_file, 'r') as inf:
+    for ln in inf:
+      ln = ln.rstrip()
+      if not ln: continue
+      try:
+        ll = json.loads(ln)
+      except ValueError:
+        errors += 1
+        continue
+      if ll is None or ll[0] is None:
+        continue
+      if ll[0][1] == 1:
+        # no CAN in hex
+        ll[1][2] = ll[1][2].decode("hex")
+        # relativize the CAN timestamps
+        this_can_time = ll[1][1]
+        ll[1] = [ll[1][0], this_can_time - last_can_time, ll[1][2]]
+        last_can_time = this_can_time
+      good.append(ll)
+
+  logging.debug("compressing %s -> %s, read done", in_file, out_file)
+  data = msgpack.packb(good)
+  data_compressed = zlib.compress(data)
+  # zlib doesn't care about this
+  data_compressed += "\x00" * (16 - len(data_compressed)%16)
+  aes = AES.new(SWAG, AES.MODE_CBC, "\x00"*16)
+  data_encrypted = aes.encrypt(data_compressed)
+  with open(out_file, "wb") as outf:
+    outf.write(data_encrypted)
+
+  logging.debug("compressing %s -> %s, write done", in_file, out_file)
+
+  return errors
+
+def decompress_json_internal(data_encrypted):
+  aes = AES.new(SWAG, AES.MODE_CBC, "\x00"*16)
+  data_compressed = aes.decrypt(data_encrypted)
+  data = zlib.decompress(data_compressed)
+  msgs = msgpack.unpackb(data)
+  good = []
+  last_can_time = 0
+  for ll in msgs:
+    if ll[0][1] == 1:
+      # back into hex
+      ll[1][2] = ll[1][2].encode("hex")
+      # derelativize CAN timestamps
+      last_can_time += ll[1][1]
+      ll[1] = [ll[1][0], last_can_time, ll[1][2]]
+    good.append(ll)
+  return good
+
+def decompress_json(in_file, out_file):
+  logging.debug("decompressing %s -> %s", in_file, out_file)
+  f = open(in_file)
+  data_encrypted = f.read()
+  f.close()
+
+  good = decompress_json_internal(data_encrypted)
+  out = '\n'.join(map(lambda x: json.dumps(x), good)) + "\n"
+  logging.debug("decompressing %s -> %s, writing", in_file, out_file)
+  f = open(out_file, 'w')
+  f.write(out)
+  f.close()
+  logging.debug("decompressing %s -> %s, write finished", in_file, out_file)
+
+if __name__ == "__main__":
+  for dat in sys.argv[1:]:
+    print(dat)
+    compress_json(dat, "/tmp/out"+ext)
+    decompress_json("/tmp/out"+ext, "/tmp/test")
+    os.system("diff "+dat+" /tmp/test")
+

common/logging_extra.py

@@ -1,9 +1,11 @@
+import io
 import os
 import sys
 import copy
 import json
 import socket
 import logging
+import traceback
 from threading import local
 from collections import OrderedDict
 from contextlib import contextmanager
@@ -78,28 +80,6 @@ class SwagLogger(logging.Logger):
     self.log_local = local()
     self.log_local.ctx = {}
 
-  def findCaller(self):
-    """
-      Find the stack frame of the caller so that we can note the source
-      file name, line number and function name.
-      """
-    # f = currentframe()
-    f = sys._getframe(3)
-    #On some versions of IronPython, currentframe() returns None if
-    #IronPython isn't run with -X:Frames.
-    if f is not None:
-      f = f.f_back
-    rv = "(unknown file)", 0, "(unknown function)"
-    while hasattr(f, "f_code"):
-      co = f.f_code
-      filename = os.path.normcase(co.co_filename)
-      if filename in (logging._srcfile, _srcfile):
-        f = f.f_back
-        continue
-      rv = (co.co_filename, f.f_lineno, co.co_name)
-      break
-    return rv
-
   def local_ctx(self):
     try:
       return self.log_local.ctx
@@ -132,11 +112,50 @@ class SwagLogger(logging.Logger):
     if args:
       evt['args'] = args
     evt.update(kwargs)
+    ctx = self.get_ctx()
+    if ctx:
+      evt['ctx'] = self.get_ctx()
     if 'error' in kwargs:
       self.error(evt)
     else:
       self.info(evt)
 
+  def findCaller(self, stack_info=False, stacklevel=1):
+    """
+    Find the stack frame of the caller so that we can note the source
+    file name, line number and function name.
+    """
+    f = sys._getframe(3)
+    #On some versions of IronPython, currentframe() returns None if
+    #IronPython isn't run with -X:Frames.
+    if f is not None:
+        f = f.f_back
+    orig_f = f
+    while f and stacklevel > 1:
+        f = f.f_back
+        stacklevel -= 1
+    if not f:
+        f = orig_f
+    rv = "(unknown file)", 0, "(unknown function)", None
+    while hasattr(f, "f_code"):
+        co = f.f_code
+        filename = os.path.normcase(co.co_filename)
+        if filename == _srcfile:
+            f = f.f_back
+            continue
+        sinfo = None
+        if stack_info:
+            sio = io.StringIO()
+            sio.write('Stack (most recent call last):\n')
+            traceback.print_stack(f, file=sio)
+            sinfo = sio.getvalue()
+            if sinfo[-1] == '\n':
+                sinfo = sinfo[:-1]
+            sio.close()
+        rv = (co.co_filename, f.f_lineno, co.co_name, sinfo)
+        break
+    return rv
+
 if __name__ == "__main__":
   log = SwagLogger()
 

common/numpy_fast.py

@@ -12,7 +12,10 @@ def interp(x, xp, fp):
       hi += 1
     low = hi - 1
     return fp[-1] if hi == N and xv > xp[low] else (
-      fp[0] if hi == 0 else 
+      fp[0] if hi == 0 else
       (xv - xp[low]) * (fp[hi] - fp[low]) / (xp[hi] - xp[low]) + fp[low])
   return [get_interp(v) for v in x] if hasattr(
     x, '__iter__') else get_interp(x)
+
+def mean(x):
+  return sum(x) / len(x)

common/numpy_helpers.py

@@ -0,0 +1,66 @@
+import bisect
+import numpy as np
+from scipy.interpolate import interp1d
+
+
+def deep_interp_0_fast(dx, x, y):
+  FIX = False
+  if len(y.shape) == 1:
+    y = y[:, None]
+    FIX = True
+  ret = np.zeros((dx.shape[0], y.shape[1]))
+  index = list(x)
+  for i in range(dx.shape[0]):
+    idx = bisect.bisect_left(index, dx[i])
+    if idx == x.shape[0]:
+      idx = x.shape[0] - 1
+    ret[i] = y[idx]
+
+  if FIX:
+    return ret[:, 0]
+  else:
+    return ret
+
+
+def running_mean(x, N):
+  cumsum = np.cumsum(np.insert(x, [0]*(int(N/2)) + [-1]*(N-int(N/2)), [x[0]]*int(N/2) + [x[-1]]*(N-int(N/2))))
+  return (cumsum[N:] - cumsum[:-N]) / N
+
+
+def deep_interp_np(x, xp, fp):
+  x = np.atleast_1d(x)
+  xp = np.array(xp)
+  if len(xp) < 2:
+    return np.repeat(fp, len(x), axis=0)
+  if min(np.diff(xp)) < 0:
+    raise RuntimeError('Bad x array for interpolation')
+  j = np.searchsorted(xp, x) - 1
+  j = np.clip(j, 0, len(xp)-2)
+  d = np.divide(x - xp[j], xp[j + 1] - xp[j], out=np.ones_like(x, dtype=np.float64), where=xp[j + 1] - xp[j] != 0)
+  vals_interp = (fp[j].T*(1 - d)).T + (fp[j + 1].T*d).T
+  if len(vals_interp) == 1:
+    return vals_interp[0]
+  else:
+    return vals_interp
+
+
+def clipping_deep_interp(x, xp, fp):
+  if len(xp) < 2:
+    return deep_interp_np(x, xp, fp)
+  bad_idx = np.where(np.diff(xp) < 0)[0]
+  if len(bad_idx) > 0:
+    if bad_idx[0] ==1:
+      return np.zeros([] + list(fp.shape[1:]))
+    return deep_interp_np(x, xp[:bad_idx[0]], fp[:bad_idx[0]])
+  else:
+    return deep_interp_np(x, xp, fp)
+
+
+def deep_interp(dx, x, y, kind="slinear"):
+  return interp1d(
+    x, y,
+    axis=0,
+    kind=kind,
+    bounds_error=False,
+    fill_value="extrapolate",
+    assume_sorted=True)(dx)

common/params.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python
+#!/usr/bin/env python3
 """ROS has a parameter server, we have files.
 
 The parameter store is a persistent key value store, implemented as a directory with a writer lock.
@@ -27,7 +27,9 @@ import sys
 import shutil
 import fcntl
 import tempfile
+import threading
 from enum import Enum
+from common.basedir import PARAMS
 
 def mkdirs_exists_ok(path):
   try:
@@ -36,50 +38,72 @@ def mkdirs_exists_ok(path):
     if not os.path.isdir(path):
       raise
 
+
 class TxType(Enum):
   PERSISTENT = 1
   CLEAR_ON_MANAGER_START = 2
-  CLEAR_ON_CAR_START = 3
+  CLEAR_ON_PANDA_DISCONNECT = 3
+
 
 class UnknownKeyName(Exception):
   pass
 
+
 keys = {
-# written: manager
-# read:    loggerd, uploaderd, offroad
-  "DongleId": TxType.PERSISTENT,
-  "AccessToken": TxType.PERSISTENT,
-  "Version": TxType.PERSISTENT,
-  "TrainingVersion": TxType.PERSISTENT,
-  "GitCommit": TxType.PERSISTENT,
-  "GitBranch": TxType.PERSISTENT,
-  "GitRemote": TxType.PERSISTENT,
-# written: baseui
-# read:    ui, controls
-  "IsMetric": TxType.PERSISTENT,
-  "IsRearViewMirror": TxType.PERSISTENT,
-  "IsFcwEnabled": TxType.PERSISTENT,
-  "HasAcceptedTerms": TxType.PERSISTENT,
-  "CompletedTrainingVersion": TxType.PERSISTENT,
-  "IsUploadVideoOverCellularEnabled": TxType.PERSISTENT,
-# written: visiond
-# read:    visiond, controlsd
-  "CalibrationParams": TxType.PERSISTENT,
-# written: visiond
-# read:    visiond, ui
-  "CloudCalibration": TxType.PERSISTENT,
-# written: controlsd
-# read:    radard
-  "CarParams": TxType.CLEAR_ON_CAR_START,
-
-  "Passive": TxType.PERSISTENT,
-  "DoUninstall": TxType.CLEAR_ON_MANAGER_START,
-  "ShouldDoUpdate": TxType.CLEAR_ON_MANAGER_START,
-  "IsUpdateAvailable": TxType.PERSISTENT,
-
-  "RecordFront": TxType.PERSISTENT,
+  "AccessToken": [TxType.PERSISTENT],
+  "AthenadPid": [TxType.PERSISTENT],
+  "CalibrationParams": [TxType.PERSISTENT],
+  "CarParams": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "CarParamsCache": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "CarVin": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "CommunityFeaturesToggle": [TxType.PERSISTENT],
+  "CompletedTrainingVersion": [TxType.PERSISTENT],
+  "ControlsParams": [TxType.PERSISTENT],
+  "DoUninstall": [TxType.CLEAR_ON_MANAGER_START],
+  "DongleId": [TxType.PERSISTENT],
+  "GitBranch": [TxType.PERSISTENT],
+  "GitCommit": [TxType.PERSISTENT],
+  "GitRemote": [TxType.PERSISTENT],
+  "GithubSshKeys": [TxType.PERSISTENT],
+  "HasAcceptedTerms": [TxType.PERSISTENT],
+  "HasCompletedSetup": [TxType.PERSISTENT],
+  "IsLdwEnabled": [TxType.PERSISTENT],
+  "IsGeofenceEnabled": [TxType.PERSISTENT],
+  "IsMetric": [TxType.PERSISTENT],
+  "IsOffroad": [TxType.CLEAR_ON_MANAGER_START],
+  "IsRHD": [TxType.PERSISTENT],
+  "IsTakingSnapshot": [TxType.CLEAR_ON_MANAGER_START],
+  "IsUpdateAvailable": [TxType.CLEAR_ON_MANAGER_START],
+  "IsUploadRawEnabled": [TxType.PERSISTENT],
+  "LastUpdateTime": [TxType.PERSISTENT],
+  "LimitSetSpeed": [TxType.PERSISTENT],
+  "LimitSetSpeedNeural": [TxType.PERSISTENT],
+  "LiveParameters": [TxType.PERSISTENT],
+  "LongitudinalControl": [TxType.PERSISTENT],
+  "OpenpilotEnabledToggle": [TxType.PERSISTENT],
+  "PandaFirmware": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "PandaFirmwareHex": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "PandaDongleId": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "Passive": [TxType.PERSISTENT],
+  "RecordFront": [TxType.PERSISTENT],
+  "ReleaseNotes": [TxType.PERSISTENT],
+  "ShouldDoUpdate": [TxType.CLEAR_ON_MANAGER_START],
+  "SpeedLimitOffset": [TxType.PERSISTENT],
+  "SubscriberInfo": [TxType.PERSISTENT],
+  "TermsVersion": [TxType.PERSISTENT],
+  "TrainingVersion": [TxType.PERSISTENT],
+  "UpdateAvailable": [TxType.CLEAR_ON_MANAGER_START],
+  "Version": [TxType.PERSISTENT],
+  "Offroad_ChargeDisabled": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "Offroad_ConnectivityNeeded": [TxType.CLEAR_ON_MANAGER_START],
+  "Offroad_ConnectivityNeededPrompt": [TxType.CLEAR_ON_MANAGER_START],
+  "Offroad_TemperatureTooHigh": [TxType.CLEAR_ON_MANAGER_START],
+  "Offroad_PandaFirmwareMismatch": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
+  "Offroad_InvalidTime": [TxType.CLEAR_ON_MANAGER_START],
+  "Offroad_IsTakingSnapshot": [TxType.CLEAR_ON_MANAGER_START],
 }
 
+
 def fsync_dir(path):
   fd = os.open(path, os.O_RDONLY)
   try:
@@ -88,7 +112,7 @@ def fsync_dir(path):
     os.close(fd)
 
 
-class FileLock(object):
+class FileLock():
   def __init__(self, path, create):
     self._path = path
     self._create = create
@@ -104,7 +128,7 @@ class FileLock(object):
       self._fd = None
 
 
-class DBAccessor(object):
+class DBAccessor():
   def __init__(self, path):
     self._path = path
     self._vals = None
@@ -265,57 +289,112 @@ class DBWriter(DBAccessor):
       self._lock = None
 
 
+def read_db(params_path, key):
+  path = "%s/d/%s" % (params_path, key)
+  try:
+    with open(path, "rb") as f:
+      return f.read()
+  except IOError:
+    return None
 
-class JSDB(object):
-  def __init__(self, fn):
-    self._fn = fn
+def write_db(params_path, key, value):
+  if isinstance(value, str):
+    value = value.encode('utf8')
 
-  def begin(self, write=False):
+  prev_umask = os.umask(0)
+  lock = FileLock(params_path+"/.lock", True)
+  lock.acquire()
+
+  try:
+    tmp_path = tempfile.mktemp(prefix=".tmp", dir=params_path)
+    with open(tmp_path, "wb") as f:
+      f.write(value)
+      f.flush()
+      os.fsync(f.fileno())
+
+    path = "%s/d/%s" % (params_path, key)
+    os.rename(tmp_path, path)
+    fsync_dir(os.path.dirname(path))
+  finally:
+    os.umask(prev_umask)
+    lock.release()
+
+class Params():
+  def __init__(self, db=PARAMS):
+    self.db = db
+
+    # create the database if it doesn't exist...
+    if not os.path.exists(self.db+"/d"):
+      with self.transaction(write=True):
+        pass
+
+  def clear_all(self):
+    shutil.rmtree(self.db, ignore_errors=True)
+    with self.transaction(write=True):
+      pass
+
+  def transaction(self, write=False):
     if write:
-      return DBWriter(self._fn)
+      return DBWriter(self.db)
     else:
-      return DBReader(self._fn)
-
-class Params(object):
-  def __init__(self, db='/data/params'):
-    self.env = JSDB(db)
+      return DBReader(self.db)
 
   def _clear_keys_with_type(self, tx_type):
-    with self.env.begin(write=True) as txn:
+    with self.transaction(write=True) as txn:
       for key in keys:
-        if keys[key] == tx_type:
+        if tx_type in keys[key]:
           txn.delete(key)
 
   def manager_start(self):
     self._clear_keys_with_type(TxType.CLEAR_ON_MANAGER_START)
 
-  def car_start(self):
-    self._clear_keys_with_type(TxType.CLEAR_ON_CAR_START)
+  def panda_disconnect(self):
+    self._clear_keys_with_type(TxType.CLEAR_ON_PANDA_DISCONNECT)
 
   def delete(self, key):
-    with self.env.begin(write=True) as txn:
+    with self.transaction(write=True) as txn:
       txn.delete(key)
 
-  def get(self, key, block=False):
+  def get(self, key, block=False, encoding=None):
     if key not in keys:
       raise UnknownKeyName(key)
 
     while 1:
-      with self.env.begin() as txn:
-        ret = txn.get(key)
+      ret = read_db(self.db, key)
       if not block or ret is not None:
         break
       # is polling really the best we can do?
       time.sleep(0.05)
+
+    if ret is not None and encoding is not None:
+      ret = ret.decode(encoding)
+
     return ret
 
   def put(self, key, dat):
+    """
+    Warning: This function blocks until the param is written to disk!
+    In very rare cases this can take over a second, and your code will hang.
+
+    Use the put_nonblocking helper function in time sensitive code, but
+    in general try to avoid writing params as much as possible.
+    """
+
     if key not in keys:
       raise UnknownKeyName(key)
 
-    with self.env.begin(write=True) as txn:
-      txn.put(key, dat)
-    print "set", key
+    write_db(self.db, key, dat)
+
+
+def put_nonblocking(key, val):
+  def f(key, val):
+    params = Params()
+    params.put(key, val)
+
+  t = threading.Thread(target=f, args=(key, val))
+  t.start()
+  return t
+
 
 if __name__ == "__main__":
   params = Params()
@@ -325,11 +404,11 @@ if __name__ == "__main__":
     for k in keys:
       pp = params.get(k)
       if pp is None:
-        print k, "is None"
+        print("%s is None" % k)
       elif all(ord(c) < 128 and ord(c) >= 32 for c in pp):
-        print k, pp
+        print("%s = %s" % (k, pp))
       else:
-        print k, pp.encode("hex")
+        print("%s = %s" % (k, pp.encode("hex")))
 
   # Test multiprocess:
   # seq 0 100000 | xargs -P20 -I{} python common/params.py DongleId {} && sleep 0.05

common/peakdetect.py

@@ -0,0 +1,163 @@
+#!/usr/bin/env python3
+
+
+# Copyright (C) 2016 Sixten Bergman
+# License WTFPL
+#
+# This program is free software. It comes without any warranty, to the extent
+# permitted by applicable law.
+# You can redistribute it and/or modify it under the terms of the Do What The
+# Fuck You Want To Public License, Version 2, as published by Sam Hocevar. See
+# http://www.wtfpl.net/ for more details.
+#
+# note that the function peakdetect is derived from code which was released to
+# public domain see: http://billauer.co.il/peakdet.html
+#
+
+from math import log
+import numpy as np
+
+__all__ = ["peakdetect"]
+
+
+
+def _datacheck_peakdetect(x_axis, y_axis):
+    if x_axis is None:
+        x_axis = range(len(y_axis))
+
+    if len(y_axis) != len(x_axis):
+        raise ValueError("Input vectors y_axis and x_axis must have same length")
+
+    #needs to be a numpy array
+    y_axis = np.array(y_axis)
+    x_axis = np.array(x_axis)
+    return x_axis, y_axis
+
+
+def _pad(fft_data, pad_len):
+    """
+    Pads fft data to interpolate in time domain
+
+    keyword arguments:
+    fft_data -- the fft
+    pad_len --  By how many times the time resolution should be increased by
+
+    return: padded list
+    """
+    length = len(fft_data)
+    n = _n(length * pad_len)
+    fft_data = list(fft_data)
+
+    return fft_data[:length // 2] + [0] * (2**n-length) + fft_data[length // 2:]
+
+
+def _n(x):
+    """
+    Find the smallest value for n, which fulfils 2**n >= x
+
+    keyword arguments:
+    x -- the value, which 2**n must surpass
+      return: the integer n
+    """
+    return int(log(x)/log(2)) + 1
+
+
+def peakdetect(y_axis, x_axis=None, lookahead=200, delta=0):
+    """
+    Converted from/based on a MATLAB script at:
+    http://billauer.co.il/peakdet.html
+      function for detecting local maxima and minima in a signal.
+    Discovers peaks by searching for values which are surrounded by lower
+    or larger values for maxima and minima respectively
+      keyword arguments:
+    y_axis -- A list containing the signal over which to find peaks
+      x_axis -- A x-axis whose values correspond to the y_axis list and is used
+        in the return to specify the position of the peaks. If omitted an
+        index of the y_axis is used.
+        (default: None)
+      lookahead -- distance to look ahead from a peak candidate to determine if
+        it is the actual peak
+        (default: 200)
+        '(samples / period) / f' where '4 >= f >= 1.25' might be a good value
+      delta -- this specifies a minimum difference between a peak and
+        the following points, before a peak may be considered a peak. Useful
+        to hinder the function from picking up false peaks towards to end of
+        the signal. To work well delta should be set to delta >= RMSnoise * 5.
+        (default: 0)
+            When omitted delta function causes a 20% decrease in speed.
+            When used Correctly it can double the speed of the function
+        return: two lists [max_peaks, min_peaks] containing the positive and
+        negative peaks respectively. Each cell of the lists contains a tuple
+        of: (position, peak_value)
+        to get the average peak value do: np.mean(max_peaks, 0)[1] on the
+        results to unpack one of the lists into x, y coordinates do:
+        x, y = zip(*max_peaks)
+    """
+    max_peaks = []
+    min_peaks = []
+    dump = []   # Used to pop the first hit which almost always is false
+    # check input data
+    x_axis, y_axis = _datacheck_peakdetect(x_axis, y_axis)
+    # store data length for later use
+    length = len(y_axis)
+    #perform some checks
+    if lookahead < 1:
+        raise ValueError("Lookahead must be '1' or above in value")
+    if not (np.isscalar(delta) and delta >= 0):
+        raise ValueError("delta must be a positive number")
+      #maxima and minima candidates are temporarily stored in
+    #mx and mn respectively
+    mn, mx = np.Inf, -np.Inf
+    #Only detect peak if there is 'lookahead' amount of points after it
+    for index, (x, y) in enumerate(zip(x_axis[:-lookahead],
+                                       y_axis[:-lookahead])):
+        if y > mx:
+            mx = y
+            mxpos = x
+        if y < mn:
+            mn = y
+            mnpos = x
+        ####look for max####
+        if y < mx-delta and mx != np.Inf:
+            #Maxima peak candidate found
+            #look ahead in signal to ensure that this is a peak and not jitter
+            if y_axis[index:index+lookahead].max() < mx:
+                max_peaks.append([mxpos, mx])
+                dump.append(True)
+                #set algorithm to only find minima now
+                mx = np.Inf
+                mn = np.Inf
+                if index+lookahead >= length:
+                    #end is within lookahead no more peaks can be found
+                    break
+                continue
+            #else:  #slows shit down this does
+            #    mx = ahead
+            #    mxpos = x_axis[np.where(y_axis[index:index+lookahead]==mx)]
+              ####look for min####
+        if y > mn+delta and mn != -np.Inf:
+            #Minima peak candidate found
+            #look ahead in signal to ensure that this is a peak and not jitter
+            if y_axis[index:index+lookahead].min() > mn:
+                min_peaks.append([mnpos, mn])
+                dump.append(False)
+                #set algorithm to only find maxima now
+                mn = -np.Inf
+                mx = -np.Inf
+                if index+lookahead >= length:
+                    #end is within lookahead no more peaks can be found
+                    break
+            #else:  #slows shit down this does
+            #    mn = ahead
+            #    mnpos = x_axis[np.where(y_axis[index:index+lookahead]==mn)]
+        #Remove the false hit on the first value of the y_axis
+    try:
+        if dump[0]:
+            max_peaks.pop(0)
+        else:
+            min_peaks.pop(0)
+        del dump
+    except IndexError:
+        #no peaks were found, should the function return empty lists?
+        pass
+    return [max_peaks, min_peaks]

common/profiler.py

@@ -1,6 +1,6 @@
 import time
 
-class Profiler(object):
+class Profiler():
   def __init__(self, enabled=False):
     self.enabled = enabled
     self.cp = {}
@@ -36,11 +36,11 @@ class Profiler(object):
     if not self.enabled:
       return
     self.iter += 1
-    print "******* Profiling *******"
+    print("******* Profiling *******")
     for n, ms in sorted(self.cp.items(), key=lambda x: -x[1]):
       if n in self.cp_ignored:
-        print "%30s: %7.2f   percent: %3.0f" % (n, ms*1000.0, ms/self.tot*100), "  IGNORED"
+        print("%30s: %7.2f   percent: %3.0f   IGNORED" % (n, ms*1000.0, ms/self.tot*100))
       else:
-        print "%30s: %7.2f   percent: %3.0f" % (n, ms*1000.0, ms/self.tot*100)
-    print "Iter clock: %2.6f   TOTAL: %2.2f" % (self.tot/self.iter, self.tot)
+        print("%30s: %7.2f   percent: %3.0f" % (n, ms*1000.0, ms/self.tot*100))
+    print("Iter clock: %2.6f   TOTAL: %2.2f" % (self.tot/self.iter, self.tot))
 

common/realtime.py

@@ -2,58 +2,25 @@
 import os
 import time
 import platform
-import threading
 import subprocess
 import multiprocessing
-
 from cffi import FFI
+
+from common.common_pyx import sec_since_boot  # pylint: disable=no-name-in-module, import-error
+
+
+# time step for each process
+DT_CTRL = 0.01  # controlsd
+DT_MDL = 0.05  # model
+DT_DMON = 0.1  # driver monitoring
+DT_TRML = 0.5  # thermald and manager
+
+
 ffi = FFI()
-ffi.cdef("""
-
-typedef int clockid_t;
-struct timespec {
-    long tv_sec;   /* Seconds.  */
-    long tv_nsec;  /* Nanoseconds.  */
-};
-int clock_gettime (clockid_t clk_id, struct timespec *tp);
-
-long syscall(long number, ...);
-
-"""
-)
+ffi.cdef("long syscall(long number, ...);")
 libc = ffi.dlopen(None)
 
 
-# see <linux/time.h>
-CLOCK_MONOTONIC_RAW = 4
-CLOCK_BOOTTIME = 7
-
-if platform.system() != 'Darwin' and hasattr(libc, 'clock_gettime'):
-  c_clock_gettime = libc.clock_gettime
-
-  tlocal = threading.local()
-  def clock_gettime(clk_id):
-    if not hasattr(tlocal, 'ts'):
-      tlocal.ts = ffi.new('struct timespec *')
-
-    ts = tlocal.ts
-
-    r = c_clock_gettime(clk_id, ts)
-    if r != 0:
-      raise OSError("clock_gettime")
-    return ts.tv_sec + ts.tv_nsec * 1e-9
-else:
-  # hack. only for OS X < 10.12
-  def clock_gettime(clk_id):
-    return time.time()
-
-def monotonic_time():
-  return clock_gettime(CLOCK_MONOTONIC_RAW)
-
-def sec_since_boot():
-  return clock_gettime(CLOCK_BOOTTIME)
-
-
 def set_realtime_priority(level):
   if os.getuid() != 0:
     print("not setting priority, not root")
@@ -69,7 +36,7 @@ def set_realtime_priority(level):
   return subprocess.call(['chrt', '-f', '-p', str(level), str(tid)])
 
 
-class Ratekeeper(object):
+class Ratekeeper():
   def __init__(self, rate, print_delay_threshold=0.):
     """Rate in Hz for ratekeeping. print_delay_threshold must be nonnegative."""
     self._interval = 1. / rate
@@ -99,12 +66,9 @@ class Ratekeeper(object):
     lagged = False
     remaining = self._next_frame_time - sec_since_boot()
     self._next_frame_time += self._interval
-    if remaining < -self._print_delay_threshold:
+    if self._print_delay_threshold is not None and remaining < -self._print_delay_threshold:
       print("%s lagging by %.2f ms" % (self._process_name, -remaining * 1000))
       lagged = True
     self._frame += 1
     self._remaining = remaining
     return lagged
-
-if __name__ == "__main__":
-  print sec_since_boot()

common/sampling_buffer.py

@@ -0,0 +1,78 @@
+import os
+import numpy as np
+import random
+
+class SamplingBuffer():
+  def __init__(self, fn, size, write=False):
+    self._fn = fn
+    self._write = write
+    if self._write:
+      self._f = open(self._fn, "ab")
+    else:
+      self._f = open(self._fn, "rb")
+    self._size = size
+    self._refresh()
+
+  def _refresh(self):
+    self.cnt = os.path.getsize(self._fn) / self._size
+
+  @property
+  def count(self):
+    self._refresh()
+    return self.cnt
+
+  def _fetch_one(self, x):
+    assert self._write == False
+    self._f.seek(x*self._size)
+    return self._f.read(self._size)
+
+  def sample(self, count, indices = None):
+    if indices == None:
+      cnt = self.count
+      assert cnt != 0
+      indices = map(lambda x: random.randint(0, cnt-1), range(count))
+    return map(self._fetch_one, indices)
+
+  def write(self, dat):
+    assert self._write == True
+    assert (len(dat) % self._size) == 0
+    self._f.write(dat)
+    self._f.flush()
+
+class NumpySamplingBuffer():
+  def __init__(self, fn, size, dtype, write=False):
+    self._size = size
+    self._dtype = dtype
+    self._buf = SamplingBuffer(fn, len(np.zeros(size, dtype=dtype).tobytes()), write)
+
+  @property
+  def count(self):
+    return self._buf.count
+
+  def write(self, dat):
+    self._buf.write(dat.tobytes())
+
+  def sample(self, count, indices = None):
+    return np.fromstring(''.join(self._buf.sample(count, indices)), dtype=self._dtype).reshape([count]+list(self._size))
+
+# TODO: n IOPS needed where n is the Multi
+class MultiNumpySamplingBuffer():
+  def __init__(self, fn, npa, write=False):
+    self._bufs = []
+    for i,n in enumerate(npa):
+      self._bufs.append(NumpySamplingBuffer(fn + ("_%d" % i), n[0], n[1], write))
+
+  def write(self, dat):
+    for b,x in zip(self._bufs, dat):
+      b.write(x)
+
+  @property
+  def count(self):
+    return min(map(lambda x: x.count, self._bufs))
+
+  def sample(self, count):
+    cnt = self.count
+    assert cnt != 0
+    indices = map(lambda x: random.randint(0, cnt-1), range(count))
+    return map(lambda x: x.sample(count, indices), self._bufs)
+

common/spinner.py

@@ -0,0 +1,63 @@
+import os
+import subprocess
+from common.basedir import BASEDIR
+
+
+class Spinner():
+  def __init__(self):
+    try:
+      self.spinner_proc = subprocess.Popen(["./spinner"],
+                                           stdin=subprocess.PIPE,
+                                           cwd=os.path.join(BASEDIR, "selfdrive", "ui", "spinner"),
+                                           close_fds=True)
+    except OSError:
+      self.spinner_proc = None
+
+  def __enter__(self):
+    return self
+
+  def update(self, spinner_text):
+    if self.spinner_proc is not None:
+      self.spinner_proc.stdin.write(spinner_text.encode('utf8') + b"\n")
+      try:
+        self.spinner_proc.stdin.flush()
+      except BrokenPipeError:
+        pass
+
+  def close(self):
+    if self.spinner_proc is not None:
+      try:
+        self.spinner_proc.stdin.close()
+      except BrokenPipeError:
+        pass
+      self.spinner_proc.terminate()
+      self.spinner_proc = None
+
+  def __del__(self):
+    self.close()
+
+  def __exit__(self, type, value, traceback):
+    self.close()
+
+
+class FakeSpinner():
+  def __init__(self):
+    pass
+
+  def __enter__(self):
+    return self
+
+  def update(self, _):
+    pass
+
+  def __exit__(self, type, value, traceback):
+    pass
+
+
+if __name__ == "__main__":
+  import time
+  with Spinner() as s:
+    s.update("Spinner text")
+    time.sleep(5.0)
+  print("gone")
+  time.sleep(5.0)

common/stat_live.py

@@ -0,0 +1,73 @@
+import numpy as np
+
+class RunningStat():
+  # tracks realtime mean and standard deviation without storing any data
+  def __init__(self, priors=None, max_trackable=-1):
+    self.max_trackable = max_trackable
+    if priors is not None:
+      # initialize from history
+      self.M = priors[0]
+      self.S = priors[1]
+      self.n = priors[2]
+      self.M_last = self.M
+      self.S_last = self.S
+
+    else:
+      self.reset()
+
+  def reset(self):
+    self.M = 0.
+    self.S = 0.
+    self.M_last = 0.
+    self.S_last = 0.
+    self.n = 0
+
+  def push_data(self, new_data):
+    # short term memory hack
+    if self.max_trackable < 0 or self.n < self.max_trackable:
+      self.n += 1
+    if self.n == 0:
+      self.M_last = new_data
+      self.M = self.M_last
+      self.S_last = 0.
+    else:
+      self.M = self.M_last + (new_data - self.M_last) / self.n
+      self.S = self.S_last + (new_data - self.M_last) * (new_data - self.M);
+      self.M_last = self.M
+      self.S_last = self.S
+
+  def mean(self):
+    return self.M
+
+  def variance(self):
+    if self.n >= 2:
+      return self.S / (self.n - 1.)
+    else:
+      return 0
+
+  def std(self):
+    return np.sqrt(self.variance())
+
+  def params_to_save(self):
+    return [self.M, self.S, self.n]
+
+class RunningStatFilter():
+  def __init__(self, raw_priors=None, filtered_priors=None, max_trackable=-1):
+    self.raw_stat = RunningStat(raw_priors, max_trackable)
+    self.filtered_stat = RunningStat(filtered_priors, max_trackable)
+
+  def reset(self):
+    self.raw_stat.reset()
+    self.filtered_stat.reset()
+
+  def push_and_update(self, new_data):
+    _std_last = self.raw_stat.std()
+    self.raw_stat.push_data(new_data)
+    _delta_std = self.raw_stat.std() - _std_last
+    if _delta_std<=0:
+      self.filtered_stat.push_data(new_data)
+    else:
+      pass
+      # self.filtered_stat.push_data(self.filtered_stat.mean())
+
+# class SequentialBayesian():

common/stat_tracker.py

@@ -0,0 +1,94 @@
+import numpy as np
+
+_DESC_FMT = """
+{} (n={}):
+MEAN={}
+VAR={}
+MIN={}
+MAX={}
+"""
+
+class StatTracker():
+  def __init__(self, name):
+    self._name = name
+    self._mean = 0.
+    self._var = 0.
+    self._n = 0
+    self._min = -float("-inf")
+    self._max = -float("inf")
+
+  @property
+  def mean(self):
+    return self._mean
+
+  @property
+  def var(self):
+    return (self._n * self._var) / (self._n - 1.)
+
+  @property
+  def min(self):
+    return self._min
+
+  @property
+  def max(self):
+    return self._max
+
+  def update(self, samples):
+    # https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
+    data = samples.reshape(-1)
+    n_a = data.size
+    mean_a = np.mean(data)
+    var_a = np.var(data, ddof=0)
+
+    n_b = self._n
+    mean_b = self._mean
+
+    delta = mean_b - mean_a
+    m_a = var_a * (n_a - 1)
+    m_b = self._var * (n_b - 1)
+    m2 = m_a + m_b + delta**2 * n_a * n_b / (n_a + n_b)
+
+    self._var = m2 / (n_a + n_b)
+    self._mean = (n_a * mean_a + n_b * mean_b) / (n_a + n_b)
+    self._n = n_a + n_b
+
+    self._min = min(self._min, np.min(data))
+    self._max = max(self._max, np.max(data))
+
+  def __str__(self):
+    return _DESC_FMT.format(self._name, self._n, self._mean, self.var, self._min,
+                            self._max)
+
+# FIXME(mgraczyk): The variance computation does not work with 1 sample batches.
+class VectorStatTracker(StatTracker):
+  def __init__(self, name, dim):
+    self._name = name
+    self._mean = np.zeros((dim, ))
+    self._var = np.zeros((dim, dim))
+    self._n = 0
+    self._min = np.full((dim, ), -float("-inf"))
+    self._max = np.full((dim, ), -float("inf"))
+
+  @property
+  def cov(self):
+    return self.var
+
+  def update(self, samples):
+    n_a = samples.shape[0]
+    mean_a = np.mean(samples, axis=0)
+    var_a = np.cov(samples, ddof=0, rowvar=False)
+
+    n_b = self._n
+    mean_b = self._mean
+
+    delta = mean_b - mean_a
+    m_a = var_a * (n_a - 1)
+    m_b = self._var * (n_b - 1)
+    m2 = m_a + m_b + delta**2 * n_a * n_b / (n_a + n_b)
+
+    self._var = m2 / (n_a + n_b)
+    self._mean = (n_a * mean_a + n_b * mean_b) / (n_a + n_b)
+    self._n = n_a + n_b
+
+    self._min = np.minimum(self._min, np.min(samples, axis=0))
+    self._max = np.maximum(self._max, np.max(samples, axis=0))

common/string_helpers.py

@@ -0,0 +1,6 @@
+def replace_right(s, old, new, occurrence):
+  # replace_right('1232425', '2', ' ', 1) -> '12324 5'
+  # replace_right('1232425', '2', ' ', 2) -> '123 4 5'
+
+  split = s.rsplit(old, occurrence)
+  return new.join(split)

common/sympy_helpers.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+import sympy as sp
+import numpy as np
+
+def cross(x):
+  ret = sp.Matrix(np.zeros((3,3)))
+  ret[0,1], ret[0,2] = -x[2], x[1]
+  ret[1,0], ret[1,2] = x[2], -x[0]
+  ret[2,0], ret[2,1] = -x[1], x[0]
+  return ret
+
+def euler_rotate(roll, pitch, yaw):
+  # make symbolic rotation matrix from eulers
+  matrix_roll =  sp.Matrix([[1, 0, 0],
+                            [0, sp.cos(roll), -sp.sin(roll)],
+                            [0, sp.sin(roll), sp.cos(roll)]])
+  matrix_pitch =  sp.Matrix([[sp.cos(pitch), 0, sp.sin(pitch)],
+                             [0, 1, 0],
+                             [-sp.sin(pitch), 0, sp.cos(pitch)]])
+  matrix_yaw =  sp.Matrix([[sp.cos(yaw), -sp.sin(yaw), 0],
+                           [sp.sin(yaw), sp.cos(yaw), 0],
+                           [0, 0, 1]])
+  return matrix_yaw*matrix_pitch*matrix_roll
+
+def quat_rotate(q0, q1, q2, q3):
+  # make symbolic rotation matrix from quat
+  return sp.Matrix([[q0**2 + q1**2 - q2**2 - q3**2, 2*(q1*q2 + q0*q3), 2*(q1*q3 - q0*q2)],
+                    [2*(q1*q2 - q0*q3), q0**2 - q1**2 + q2**2 - q3**2, 2*(q2*q3 + q0*q1)],
+                    [2*(q1*q3 + q0*q2), 2*(q2*q3 - q0*q1), q0**2 - q1**2 - q2**2 + q3**2]]).T
+
+def quat_matrix_l(p):
+  return sp.Matrix([[p[0], -p[1], -p[2], -p[3]],
+                    [p[1],  p[0], -p[3],  p[2]],
+                    [p[2],  p[3],  p[0], -p[1]],
+                    [p[3], -p[2],  p[1],  p[0]]])
+
+def quat_matrix_r(p):
+  return sp.Matrix([[p[0], -p[1], -p[2], -p[3]],
+                    [p[1],  p[0],  p[3], -p[2]],
+                    [p[2], -p[3],  p[0],  p[1]],
+                    [p[3],  p[2], -p[1],  p[0]]])
+
+
+def sympy_into_c(sympy_functions):
+  from sympy.utilities import codegen
+  routines = []
+  for name, expr, args in sympy_functions:
+    r = codegen.make_routine(name, expr, language="C99")
+
+    # argument ordering input to sympy is broken with function with output arguments
+    nargs = []
+    # reorder the input arguments
+    for aa in args:
+      if aa is None:
+        nargs.append(codegen.InputArgument(sp.Symbol('unused'), dimensions=[1,1]))
+        continue
+      found = False
+      for a in r.arguments:
+        if str(aa.name) == str(a.name):
+          nargs.append(a)
+          found = True
+          break
+      if not found:
+        # [1,1] is a hack for Matrices
+        nargs.append(codegen.InputArgument(aa, dimensions=[1,1]))
+    # add the output arguments
+    for a in r.arguments:
+      if type(a) == codegen.OutputArgument:
+        nargs.append(a)
+
+    #assert len(r.arguments) == len(args)+1
+    r.arguments = nargs
+
+    # add routine to list
+    routines.append(r)
+
+  [(c_name, c_code), (h_name, c_header)] = codegen.get_code_generator('C', 'ekf', 'C99').write(routines, "ekf")
+  c_code = '\n'.join(x for x in c_code.split("\n") if len(x) > 0 and x[0] != '#')
+  c_header = '\n'.join(x for x in  c_header.split("\n") if len(x) > 0 and x[0] != '#')
+
+  return c_header, c_code

common/tests/test_file_helpers.py

@@ -0,0 +1,28 @@
+import os
+import unittest
+from uuid import uuid4
+
+from common.file_helpers import atomic_write_on_fs_tmp
+from common.file_helpers import atomic_write_in_dir
+
+
+class TestFileHelpers(unittest.TestCase):
+  def run_atomic_write_func(self, atomic_write_func):
+    path = "/tmp/tmp{}".format(uuid4())
+    with atomic_write_func(path) as f:
+      f.write("test")
+
+    with open(path) as f:
+      self.assertEqual(f.read(), "test")
+    self.assertEqual(os.stat(path).st_mode & 0o777, 0o644)
+    os.remove(path)
+
+  def test_atomic_write_on_fs_tmp(self):
+    self.run_atomic_write_func(atomic_write_on_fs_tmp)
+
+  def test_atomic_write_in_dir(self):
+    self.run_atomic_write_func(atomic_write_in_dir)
+
+
+if __name__ == "__main__":
+  unittest.main()

common/tests/test_numpy_fast.py

@@ -0,0 +1,27 @@
+import numpy as np
+import unittest
+import timeit
+
+from common.numpy_fast import interp
+
+
+class InterpTest(unittest.TestCase):
+  def test_correctness_controls(self):
+    _A_CRUISE_MIN_BP = np.asarray([0., 5., 10., 20., 40.])
+    _A_CRUISE_MIN_V = np.asarray([-1.0, -.8, -.67, -.5, -.30])
+    v_ego_arr = [-1, -1e-12, 0, 4, 5, 6, 7, 10, 11, 15.2, 20, 21, 39,
+                 39.999999, 40, 41]
+
+    expected = np.interp(v_ego_arr, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+    actual = interp(v_ego_arr, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+
+    np.testing.assert_equal(actual, expected)
+
+    for v_ego in v_ego_arr:
+      expected = np.interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+      actual = interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+      np.testing.assert_equal(actual, expected)
+
+
+if __name__ == "__main__":
+  unittest.main()

common/tests/test_params.py

@@ -0,0 +1,63 @@
+from common.params import Params, UnknownKeyName
+import threading
+import time
+import tempfile
+import shutil
+import unittest
+
+
+class TestParams(unittest.TestCase):
+  def setUp(self):
+    self.tmpdir = tempfile.mkdtemp()
+    print("using", self.tmpdir)
+    self.params = Params(self.tmpdir)
+
+  def tearDown(self):
+    shutil.rmtree(self.tmpdir)
+
+  def test_params_put_and_get(self):
+    self.params.put("DongleId", "cb38263377b873ee")
+    assert self.params.get("DongleId") == b"cb38263377b873ee"
+
+  def test_params_non_ascii(self):
+    st = b"\xe1\x90\xff"
+    self.params.put("CarParams", st)
+    assert self.params.get("CarParams") == st
+
+  def test_params_get_cleared_panda_disconnect(self):
+    self.params.put("CarParams", "test")
+    self.params.put("DongleId", "cb38263377b873ee")
+    assert self.params.get("CarParams") == b"test"
+    self.params.panda_disconnect()
+    assert self.params.get("CarParams") is None
+    assert self.params.get("DongleId") is not None
+
+  def test_params_get_cleared_manager_start(self):
+    self.params.put("CarParams", "test")
+    self.params.put("DongleId", "cb38263377b873ee")
+    assert self.params.get("CarParams") == b"test"
+    self.params.manager_start()
+    assert self.params.get("CarParams") is None
+    assert self.params.get("DongleId") is not None
+
+  def test_params_two_things(self):
+    self.params.put("DongleId", "bob")
+    self.params.put("AccessToken", "knope")
+    assert self.params.get("DongleId") == b"bob"
+    assert self.params.get("AccessToken") == b"knope"
+
+  def test_params_get_block(self):
+    def _delayed_writer():
+      time.sleep(0.1)
+      self.params.put("CarParams", "test")
+    threading.Thread(target=_delayed_writer).start()
+    assert self.params.get("CarParams") is None
+    assert self.params.get("CarParams", True) == b"test"
+
+  def test_params_unknown_key_fails(self):
+    with self.assertRaises(UnknownKeyName):
+      self.params.get("swag")
+
+
+if __name__ == "__main__":
+  unittest.main()

common/timeout.py

@@ -0,0 +1,28 @@
+import signal
+
+class TimeoutException(Exception):
+  pass
+
+class Timeout:
+  """
+  Timeout context manager.
+  For example this code will raise a TimeoutException:
+  with Timeout(seconds=5, error_msg="Sleep was too long"):
+    time.sleep(10)
+  """
+  def __init__(self, seconds, error_msg=None):
+    if error_msg is None:
+      error_msg = 'Timed out after {} seconds'.format(seconds)
+    self.seconds = seconds
+    self.error_msg = error_msg
+
+  def handle_timeout(self, signume, frame):
+    raise TimeoutException(self.error_msg)
+
+  def __enter__(self):
+    signal.signal(signal.SIGALRM, self.handle_timeout)
+    signal.alarm(self.seconds)
+
+  def __exit__(self, exc_type, exc_val, exc_tb):
+    signal.alarm(0)
+

common/transformations/README.md

@@ -0,0 +1,61 @@
+
+Reference Frames
+------
+Many reference frames are used throughout. This
+folder contains all helper functions needed to
+transform between them. Generally this is done
+by generating a rotation matrix and multiplying.
+
+
+| Name | [x, y, z] | Units | Notes |
+| :-------------: |:-------------:| :-----:| :----: |
+| Geodetic | [Latitude, Longitude, Altitude] | geodetic coordinates | Sometimes used as [lon, lat, alt], avoid this frame. |
+| ECEF | [x, y, z] | meters | We use **ITRF14 (IGS14)**, NOT NAD83. <br> This is the global Mesh3D frame. |
+| NED | [North, East, Down] | meters | Relative to earth's surface, useful for vizualizing. |
+| Device | [Forward, Right, Down] | meters | This is the Mesh3D local frame. <br> Relative to camera, **not imu.** <br> ![img](http://upload.wikimedia.org/wikipedia/commons/thumb/2/2f/RPY_angles_of_airplanes.png/440px-RPY_angles_of_airplanes.png)|
+| Road | [Forward, Left, Up] | meters | On the road plane aligned to the vehicle. <br> ![img](https://upload.wikimedia.org/wikipedia/commons/f/f5/RPY_angles_of_cars.png) |
+| View | [Right, Down, Forward] | meters | Like device frame, but according to camera conventions. |
+| Camera | [u, v, focal] | pixels | Like view frame, but 2d on the camera image.|
+| Normalized Camera | [u / focal, v / focal, 1] | / | |
+| Model | [u, v, focal] | pixels | The sampled rectangle of the full camera frame the model uses. |
+| Normalized Model | [u / focal, v / focal, 1] | / | |
+
+
+
+
+Orientation Conventations
+------
+Quaternions, rotation matrices and euler angles are three 
+equivalent representations of orientation and all three are
+used throughout the code base.
+
+For euler angles the preferred convention is [roll, pitch, yaw]
+which corresponds to rotations around the [x, y, z] axes. All
+euler angles should always be in radians or radians/s unless
+for plotting or display purposes. For quaternions the hamilton 
+notations is preferred which is [q<sub>w</sub>, q<sub>x</sub>, q<sub>y</sub>, q<sub>z</sub>]. All quaternions
+should always be normalized with a strictly positive q<sub>w</sub>. **These
+quaternions are a unique representation of orientation whereas euler angles
+or rotation matrices are not.**
+
+To rotate from one frame into another with euler angles the
+convention is to rotate around roll, then pitch and then yaw,
+while rotating around the rotated axes, not the original axes.
+
+
+Calibration
+------
+EONs are not all mounted in the exact same way. To compensate for the effects of this the vision model takes in an image that is "calibrated". This means the image is aligned so the direction of travel of the car when it is going straight and the road is flat is always in the location on the image. This calibration is defined by a pitch and yaw angle that describe the direction of travel vector in device frame.
+
+Example
+------
+To transform global Mesh3D positions and orientations (positions_ecef, quats_ecef) into the local frame described by the 
+first position and orientation from Mesh3D one would do:
+```
+ecef_from_local = rot_from_quat(quats_ecef[0])
+local_from_ecef = ecef_from_local.T
+positions_local = np.einsum('ij,kj->ki', local_from_ecef, postions_ecef - positions_ecef[0])
+rotations_global = rot_from_quat(quats_ecef)
+rotations_local = np.einsum('ij,kjl->kil', local_from_ecef, rotations_global)
+eulers_local = euler_from_rot(rotations_local)
+```

common/transformations/camera.py

@@ -0,0 +1,227 @@
+import numpy as np
+import common.transformations.orientation as orient
+import math
+
+FULL_FRAME_SIZE = (1164, 874)
+W, H = FULL_FRAME_SIZE[0], FULL_FRAME_SIZE[1]
+eon_focal_length = FOCAL = 910.0
+
+# aka 'K' aka camera_frame_from_view_frame
+eon_intrinsics = np.array([
+  [FOCAL,   0.,   W/2.],
+  [  0.,  FOCAL,  H/2.],
+  [  0.,    0.,     1.]])
+
+
+leon_dcam_intrinsics = np.array([
+  [650,   0,   816//2],
+  [  0,  650,  612//2],
+  [  0,    0,     1]])
+
+eon_dcam_intrinsics = np.array([
+  [860,   0,   1152//2],
+  [  0,  860,  864//2],
+  [  0,    0,     1]])
+
+# aka 'K_inv' aka view_frame_from_camera_frame
+eon_intrinsics_inv = np.linalg.inv(eon_intrinsics)
+
+
+# device/mesh : x->forward, y-> right, z->down
+# view : x->right, y->down, z->forward
+device_frame_from_view_frame = np.array([
+  [ 0.,  0.,  1.],
+  [ 1.,  0.,  0.],
+  [ 0.,  1.,  0.]
+])
+view_frame_from_device_frame = device_frame_from_view_frame.T
+
+
+def get_calib_from_vp(vp):
+  vp_norm = normalize(vp)
+  yaw_calib = np.arctan(vp_norm[0])
+  pitch_calib = -np.arctan(vp_norm[1]*np.cos(yaw_calib))
+  roll_calib = 0
+  return roll_calib, pitch_calib, yaw_calib
+
+
+# aka 'extrinsic_matrix'
+# road : x->forward, y -> left, z->up
+def get_view_frame_from_road_frame(roll, pitch, yaw, height):
+  device_from_road = orient.rot_from_euler([roll, pitch, yaw]).dot(np.diag([1, -1, -1]))
+  view_from_road = view_frame_from_device_frame.dot(device_from_road)
+  return np.hstack((view_from_road, [[0], [height], [0]]))
+
+
+def vp_from_ke(m):
+  """
+  Computes the vanishing point from the product of the intrinsic and extrinsic
+  matrices C = KE.
+
+  The vanishing point is defined as lim x->infinity C (x, 0, 0, 1).T
+  """
+  return (m[0, 0]/m[2,0], m[1,0]/m[2,0])
+
+
+def vp_from_rpy(rpy):
+  e = get_view_frame_from_road_frame(rpy[0], rpy[1], rpy[2], 1.22)
+  ke = np.dot(eon_intrinsics, e)
+  return vp_from_ke(ke)
+
+
+def roll_from_ke(m):
+  # note: different from calibration.h/RollAnglefromKE: i think that one's just wrong
+  return np.arctan2(-(m[1, 0] - m[1, 1] * m[2, 0] / m[2, 1]),
+                    -(m[0, 0] - m[0, 1] * m[2, 0] / m[2, 1]))
+
+
+def normalize(img_pts, intrinsics=eon_intrinsics):
+  # normalizes image coordinates
+  # accepts single pt or array of pts
+  intrinsics_inv = np.linalg.inv(intrinsics)
+  img_pts = np.array(img_pts)
+  input_shape = img_pts.shape
+  img_pts = np.atleast_2d(img_pts)
+  img_pts = np.hstack((img_pts, np.ones((img_pts.shape[0],1))))
+  img_pts_normalized = img_pts.dot(intrinsics_inv.T)
+  img_pts_normalized[(img_pts < 0).any(axis=1)] = np.nan
+  return img_pts_normalized[:,:2].reshape(input_shape)
+
+
+def denormalize(img_pts, intrinsics=eon_intrinsics):
+  # denormalizes image coordinates
+  # accepts single pt or array of pts
+  img_pts = np.array(img_pts)
+  input_shape = img_pts.shape
+  img_pts = np.atleast_2d(img_pts)
+  img_pts = np.hstack((img_pts, np.ones((img_pts.shape[0],1))))
+  img_pts_denormalized = img_pts.dot(intrinsics.T)
+  img_pts_denormalized[img_pts_denormalized[:,0] > W] = np.nan
+  img_pts_denormalized[img_pts_denormalized[:,0] < 0] = np.nan
+  img_pts_denormalized[img_pts_denormalized[:,1] > H] = np.nan
+  img_pts_denormalized[img_pts_denormalized[:,1] < 0] = np.nan
+  return img_pts_denormalized[:,:2].reshape(input_shape)
+
+
+def device_from_ecef(pos_ecef, orientation_ecef, pt_ecef):
+  # device from ecef frame
+  # device frame is x -> forward, y-> right, z -> down
+  # accepts single pt or array of pts
+  input_shape = pt_ecef.shape
+  pt_ecef = np.atleast_2d(pt_ecef)
+  ecef_from_device_rot = orient.rotations_from_quats(orientation_ecef)
+  device_from_ecef_rot = ecef_from_device_rot.T
+  pt_ecef_rel = pt_ecef - pos_ecef
+  pt_device = np.einsum('jk,ik->ij', device_from_ecef_rot, pt_ecef_rel)
+  return pt_device.reshape(input_shape)
+
+
+def img_from_device(pt_device):
+  # img coordinates from pts in device frame
+  # first transforms to view frame, then to img coords
+  # accepts single pt or array of pts
+  input_shape = pt_device.shape
+  pt_device = np.atleast_2d(pt_device)
+  pt_view = np.einsum('jk,ik->ij', view_frame_from_device_frame, pt_device)
+
+  # This function should never return negative depths
+  pt_view[pt_view[:,2] < 0] = np.nan
+
+  pt_img = pt_view/pt_view[:,2:3]
+  return pt_img.reshape(input_shape)[:,:2]
+
+
+def get_camera_frame_from_calib_frame(camera_frame_from_road_frame):
+  camera_frame_from_ground = camera_frame_from_road_frame[:, (0, 1, 3)]
+  calib_frame_from_ground = np.dot(eon_intrinsics,
+                                     get_view_frame_from_road_frame(0, 0, 0, 1.22))[:, (0, 1, 3)]
+  ground_from_calib_frame = np.linalg.inv(calib_frame_from_ground)
+  camera_frame_from_calib_frame = np.dot(camera_frame_from_ground, ground_from_calib_frame)
+  return camera_frame_from_calib_frame
+
+
+def pretransform_from_calib(calib):
+  roll, pitch, yaw, height = calib
+  view_frame_from_road_frame = get_view_frame_from_road_frame(roll, pitch, yaw, height)
+  camera_frame_from_road_frame = np.dot(eon_intrinsics, view_frame_from_road_frame)
+  camera_frame_from_calib_frame = get_camera_frame_from_calib_frame(camera_frame_from_road_frame)
+  return np.linalg.inv(camera_frame_from_calib_frame)
+
+
+def transform_img(base_img,
+                 augment_trans=np.array([0,0,0]),
+                 augment_eulers=np.array([0,0,0]),
+                 from_intr=eon_intrinsics,
+                 to_intr=eon_intrinsics,
+                 output_size=None,
+                 pretransform=None,
+                 top_hacks=False,
+                 yuv=False,
+                 alpha=1.0,
+                 beta=0,
+                 blur=0):
+  import cv2  # pylint: disable=import-error
+  cv2.setNumThreads(1)
+
+  if yuv:
+    base_img = cv2.cvtColor(base_img, cv2.COLOR_YUV2RGB_I420)
+
+  size = base_img.shape[:2]
+  if not output_size:
+    output_size = size[::-1]
+
+  cy = from_intr[1,2]
+  def get_M(h=1.22):
+    quadrangle = np.array([[0, cy + 20],
+                           [size[1]-1, cy + 20],
+                           [0, size[0]-1],
+                           [size[1]-1, size[0]-1]], dtype=np.float32)
+    quadrangle_norm = np.hstack((normalize(quadrangle, intrinsics=from_intr), np.ones((4,1))))
+    quadrangle_world = np.column_stack((h*quadrangle_norm[:,0]/quadrangle_norm[:,1],
+                                        h*np.ones(4),
+                                        h/quadrangle_norm[:,1]))
+    rot = orient.rot_from_euler(augment_eulers)
+    to_extrinsics = np.hstack((rot.T, -augment_trans[:,None]))
+    to_KE = to_intr.dot(to_extrinsics)
+    warped_quadrangle_full = np.einsum('jk,ik->ij', to_KE, np.hstack((quadrangle_world, np.ones((4,1)))))
+    warped_quadrangle = np.column_stack((warped_quadrangle_full[:,0]/warped_quadrangle_full[:,2],
+                                         warped_quadrangle_full[:,1]/warped_quadrangle_full[:,2])).astype(np.float32)
+    M = cv2.getPerspectiveTransform(quadrangle, warped_quadrangle.astype(np.float32))
+    return M
+
+  M = get_M()
+  if pretransform is not None:
+    M = M.dot(pretransform)
+  augmented_rgb = cv2.warpPerspective(base_img, M, output_size, borderMode=cv2.BORDER_REPLICATE)
+
+  if top_hacks:
+    cyy = int(math.ceil(to_intr[1,2]))
+    M = get_M(1000)
+    if pretransform is not None:
+      M = M.dot(pretransform)
+    augmented_rgb[:cyy] = cv2.warpPerspective(base_img, M, (output_size[0], cyy), borderMode=cv2.BORDER_REPLICATE)
+
+  # brightness and contrast augment
+  augmented_rgb = np.clip((float(alpha)*augmented_rgb + beta), 0, 255).astype(np.uint8)
+
+  # gaussian blur
+  if blur > 0:
+    augmented_rgb = cv2.GaussianBlur(augmented_rgb,(blur*2+1,blur*2+1),cv2.BORDER_DEFAULT)
+
+  if yuv:
+    augmented_img = cv2.cvtColor(augmented_rgb, cv2.COLOR_RGB2YUV_I420)
+  else:
+    augmented_img = augmented_rgb
+  return augmented_img
+
+
+def yuv_crop(frame, output_size, center=None):
+  # output_size in camera coordinates so u,v
+  # center in array coordinates so row, column
+  import cv2  # pylint: disable=import-error
+  rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
+  if not center:
+    center = (rgb.shape[0]/2, rgb.shape[1]/2)
+  rgb_crop = rgb[center[0] - output_size[1]/2: center[0] + output_size[1]/2,
+                 center[1] - output_size[0]/2: center[1] + output_size[0]/2]
+  return cv2.cvtColor(rgb_crop, cv2.COLOR_RGB2YUV_I420)

common/transformations/coordinates.py

@@ -12,12 +12,14 @@ esq = 6.69437999014 * 0.001
 e1sq = 6.73949674228 * 0.001
 
 
-def geodetic2ecef(geodetic):
+def geodetic2ecef(geodetic, radians=False):
   geodetic = np.array(geodetic)
   input_shape = geodetic.shape
   geodetic = np.atleast_2d(geodetic)
-  lat = (np.pi/180)*geodetic[:,0]
-  lon = (np.pi/180)*geodetic[:,1]
+
+  ratio = 1.0 if radians else (np.pi / 180.0)
+  lat = ratio*geodetic[:,0]
+  lon = ratio*geodetic[:,1]
   alt = geodetic[:,2]
 
   xi = np.sqrt(1 - esq * np.sin(lat)**2)
@@ -28,42 +30,42 @@ def geodetic2ecef(geodetic):
   return ecef.reshape(input_shape)
 
 
-def ecef2geodetic(ecef):
+def ecef2geodetic(ecef, radians=False):
   """
   Convert ECEF coordinates to geodetic using ferrari's method
   """
-  def ferrari(x, y, z):
-    # ferrari's method
-    r = np.sqrt(x * x + y * y)
-    Esq = a * a - b * b
-    F = 54 * b * b * z * z
-    G = r * r + (1 - esq) * z * z - esq * Esq
-    C = (esq * esq * F * r * r) / (pow(G, 3))
-    S = np.cbrt(1 + C + np.sqrt(C * C + 2 * C))
-    P = F / (3 * pow((S + 1 / S + 1), 2) * G * G)
-    Q = np.sqrt(1 + 2 * esq * esq * P)
-    r_0 =  -(P * esq * r) / (1 + Q) + np.sqrt(0.5 * a * a*(1 + 1.0 / Q) - \
-          P * (1 - esq) * z * z / (Q * (1 + Q)) - 0.5 * P * r * r)
-    U = np.sqrt(pow((r - esq * r_0), 2) + z * z)
-    V = np.sqrt(pow((r - esq * r_0), 2) + (1 - esq) * z * z)
-    Z_0 = b * b * z / (a * V)
-    h = U * (1 - b * b / (a * V))
-    lat = (180/np.pi)*np.arctan((z + e1sq * Z_0) / r)
-    lon = (180/np.pi)*np.arctan2(y, x)
-    return lat, lon, h
-
-  geodetic = []
-  ecef = np.array(ecef)
+  # Save shape and export column
+  ecef = np.atleast_1d(ecef)
   input_shape = ecef.shape
   ecef = np.atleast_2d(ecef)
-  for p in ecef:
-    geodetic.append(ferrari(*p))
-  geodetic = np.array(geodetic)
+  x, y, z = ecef[:, 0], ecef[:, 1], ecef[:, 2]
+
+  ratio = 1.0 if radians else (180.0 / np.pi)
+
+  # Conver from ECEF to geodetic using Ferrari's methods
+  # https://en.wikipedia.org/wiki/Geographic_coordinate_conversion#Ferrari.27s_solution
+  r = np.sqrt(x * x + y * y)
+  Esq = a * a - b * b
+  F = 54 * b * b * z * z
+  G = r * r + (1 - esq) * z * z - esq * Esq
+  C = (esq * esq * F * r * r) / (pow(G, 3))
+  S = np.cbrt(1 + C + np.sqrt(C * C + 2 * C))
+  P = F / (3 * pow((S + 1 / S + 1), 2) * G * G)
+  Q = np.sqrt(1 + 2 * esq * esq * P)
+  r_0 =  -(P * esq * r) / (1 + Q) + np.sqrt(0.5 * a * a*(1 + 1.0 / Q) - \
+        P * (1 - esq) * z * z / (Q * (1 + Q)) - 0.5 * P * r * r)
+  U = np.sqrt(pow((r - esq * r_0), 2) + z * z)
+  V = np.sqrt(pow((r - esq * r_0), 2) + (1 - esq) * z * z)
+  Z_0 = b * b * z / (a * V)
+  h = U * (1 - b * b / (a * V))
+  lat = ratio*np.arctan((z + e1sq * Z_0) / r)
+  lon = ratio*np.arctan2(y, x)
+
+  # stack the new columns and return to the original shape
+  geodetic = np.column_stack((lat, lon, h))
   return geodetic.reshape(input_shape)
 
-
-
-class LocalCoord(object):
+class LocalCoord():
   """
    Allows conversions to local frames. In this case NED.
    That is: North East Down from the start position in

common/transformations/model.py

@@ -0,0 +1,150 @@
+import numpy as np
+
+from common.transformations.camera import (FULL_FRAME_SIZE, eon_focal_length,
+                                           get_view_frame_from_road_frame,
+                                           vp_from_ke)
+
+# segnet
+
+SEGNET_SIZE = (512, 384)
+
+segnet_frame_from_camera_frame = np.array([
+  [float(SEGNET_SIZE[0])/FULL_FRAME_SIZE[0],    0.,          ],
+  [     0.,          float(SEGNET_SIZE[1])/FULL_FRAME_SIZE[1]]])
+
+
+# model
+
+MODEL_INPUT_SIZE = (320, 160)
+MODEL_YUV_SIZE = (MODEL_INPUT_SIZE[0], MODEL_INPUT_SIZE[1] * 3 // 2)
+MODEL_CX = MODEL_INPUT_SIZE[0]/2.
+MODEL_CY = 21.
+
+model_zoom = 1.25
+model_height = 1.22
+
+# canonical model transform
+model_intrinsics = np.array(
+  [[ eon_focal_length / model_zoom,    0. ,  MODEL_CX],
+   [   0. ,  eon_focal_length / model_zoom,  MODEL_CY],
+   [   0. ,                            0. ,   1.]])
+
+
+# MED model
+MEDMODEL_INPUT_SIZE = (512, 256)
+MEDMODEL_YUV_SIZE = (MEDMODEL_INPUT_SIZE[0], MEDMODEL_INPUT_SIZE[1] * 3 // 2)
+MEDMODEL_CY = 47.6
+
+medmodel_zoom = 1.
+medmodel_intrinsics = np.array(
+  [[ eon_focal_length / medmodel_zoom,    0. ,  0.5 * MEDMODEL_INPUT_SIZE[0]],
+   [   0. ,  eon_focal_length / medmodel_zoom,  MEDMODEL_CY],
+   [   0. ,                            0. ,   1.]])
+
+
+# BIG model
+
+BIGMODEL_INPUT_SIZE = (864, 288)
+BIGMODEL_YUV_SIZE = (BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1] * 3 // 2)
+
+bigmodel_zoom = 1.
+bigmodel_intrinsics = np.array(
+  [[ eon_focal_length / bigmodel_zoom,    0. , 0.5 * BIGMODEL_INPUT_SIZE[0]],
+   [   0. ,  eon_focal_length / bigmodel_zoom,  0.2 * BIGMODEL_INPUT_SIZE[1]],
+   [   0. ,                            0. ,   1.]])
+
+
+bigmodel_border = np.array([
+    [0,0,1],
+    [BIGMODEL_INPUT_SIZE[0], 0, 1],
+    [BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1], 1],
+    [0, BIGMODEL_INPUT_SIZE[1], 1],
+])
+
+
+model_frame_from_road_frame = np.dot(model_intrinsics,
+  get_view_frame_from_road_frame(0, 0, 0, model_height))
+
+bigmodel_frame_from_road_frame = np.dot(bigmodel_intrinsics,
+  get_view_frame_from_road_frame(0, 0, 0, model_height))
+
+medmodel_frame_from_road_frame = np.dot(medmodel_intrinsics,
+  get_view_frame_from_road_frame(0, 0, 0, model_height))
+
+model_frame_from_bigmodel_frame = np.dot(model_intrinsics, np.linalg.inv(bigmodel_intrinsics))
+
+# 'camera from model camera'
+def get_model_height_transform(camera_frame_from_road_frame, height):
+  camera_frame_from_road_ground = np.dot(camera_frame_from_road_frame, np.array([
+      [1, 0, 0],
+      [0, 1, 0],
+      [0, 0, 0],
+      [0, 0, 1],
+  ]))
+
+  camera_frame_from_road_high = np.dot(camera_frame_from_road_frame, np.array([
+      [1, 0, 0],
+      [0, 1, 0],
+      [0, 0, height - model_height],
+      [0, 0, 1],
+  ]))
+
+  road_high_from_camera_frame = np.linalg.inv(camera_frame_from_road_high)
+  high_camera_from_low_camera = np.dot(camera_frame_from_road_ground, road_high_from_camera_frame)
+
+  return high_camera_from_low_camera
+
+
+# camera_frame_from_model_frame aka 'warp matrix'
+# was: calibration.h/CalibrationTransform
+def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height=model_height):
+  vp = vp_from_ke(camera_frame_from_road_frame)
+
+  model_camera_from_model_frame = np.array([
+    [model_zoom,         0., vp[0] - MODEL_CX * model_zoom],
+    [        0., model_zoom, vp[1] - MODEL_CY * model_zoom],
+    [        0.,         0.,                            1.],
+  ])
+
+  # This function is super slow, so skip it if height is very close to canonical
+  # TODO: speed it up!
+  if abs(height - model_height) > 0.001: #
+    camera_from_model_camera = get_model_height_transform(camera_frame_from_road_frame, height)
+  else:
+    camera_from_model_camera = np.eye(3)
+
+  return np.dot(camera_from_model_camera, model_camera_from_model_frame)
+
+
+def get_camera_frame_from_medmodel_frame(camera_frame_from_road_frame):
+  camera_frame_from_ground = camera_frame_from_road_frame[:, (0, 1, 3)]
+  medmodel_frame_from_ground = medmodel_frame_from_road_frame[:, (0, 1, 3)]
+
+  ground_from_medmodel_frame = np.linalg.inv(medmodel_frame_from_ground)
+  camera_frame_from_medmodel_frame = np.dot(camera_frame_from_ground, ground_from_medmodel_frame)
+
+  return camera_frame_from_medmodel_frame
+
+
+def get_camera_frame_from_bigmodel_frame(camera_frame_from_road_frame):
+  camera_frame_from_ground = camera_frame_from_road_frame[:, (0, 1, 3)]
+  bigmodel_frame_from_ground = bigmodel_frame_from_road_frame[:, (0, 1, 3)]
+
+  ground_from_bigmodel_frame = np.linalg.inv(bigmodel_frame_from_ground)
+  camera_frame_from_bigmodel_frame = np.dot(camera_frame_from_ground, ground_from_bigmodel_frame)
+
+  return camera_frame_from_bigmodel_frame
+
+
+def get_model_frame(snu_full, camera_frame_from_model_frame, size):
+  idxs = camera_frame_from_model_frame.dot(np.column_stack([np.tile(np.arange(size[0]), size[1]),
+                                                            np.tile(np.arange(size[1]), (size[0],1)).T.flatten(),
+                                                            np.ones(size[0] * size[1])]).T).T.astype(int)
+  calib_flat = snu_full[idxs[:,1], idxs[:,0]]
+  if len(snu_full.shape) == 3:
+    calib = calib_flat.reshape((size[1], size[0], 3))
+  elif len(snu_full.shape) == 2:
+    calib = calib_flat.reshape((size[1], size[0]))
+  else:
+    raise ValueError("shape of input img is weird")
+  return calib

common/transformations/orientation.py

@@ -0,0 +1,295 @@
+import numpy as np
+from numpy import dot, inner, array, linalg
+from common.transformations.coordinates import LocalCoord
+
+
+'''
+Vectorized functions that transform between
+rotation matrices, euler angles and quaternions.
+All support lists, array or array of arrays as inputs.
+Supports both x2y and y_from_x format (y_from_x preferred!).
+'''
+
+def euler2quat(eulers):
+  eulers = array(eulers)
+  if len(eulers.shape) > 1:
+    output_shape = (-1,4)
+  else:
+    output_shape = (4,)
+  eulers = np.atleast_2d(eulers)
+  gamma, theta, psi = eulers[:,0],  eulers[:,1],  eulers[:,2]
+
+  q0 = np.cos(gamma / 2) * np.cos(theta / 2) * np.cos(psi / 2) + \
+       np.sin(gamma / 2) * np.sin(theta / 2) * np.sin(psi / 2)
+  q1 = np.sin(gamma / 2) * np.cos(theta / 2) * np.cos(psi / 2) - \
+       np.cos(gamma / 2) * np.sin(theta / 2) * np.sin(psi / 2)
+  q2 = np.cos(gamma / 2) * np.sin(theta / 2) * np.cos(psi / 2) + \
+       np.sin(gamma / 2) * np.cos(theta / 2) * np.sin(psi / 2)
+  q3 = np.cos(gamma / 2) * np.cos(theta / 2) * np.sin(psi / 2) - \
+       np.sin(gamma / 2) * np.sin(theta / 2) * np.cos(psi / 2)
+
+  quats = array([q0, q1, q2, q3]).T
+  for i in range(len(quats)):
+    if quats[i,0] < 0:
+      quats[i] = -quats[i]
+  return quats.reshape(output_shape)
+
+
+def quat2euler(quats):
+  quats = array(quats)
+  if len(quats.shape) > 1:
+    output_shape = (-1,3)
+  else:
+    output_shape = (3,)
+  quats = np.atleast_2d(quats)
+  q0, q1, q2, q3 = quats[:,0], quats[:,1], quats[:,2], quats[:,3]
+
+  gamma = np.arctan2(2 * (q0 * q1 + q2 * q3), 1 - 2 * (q1**2 + q2**2))
+  theta = np.arcsin(2 * (q0 * q2 - q3 * q1))
+  psi = np.arctan2(2 * (q0 * q3 + q1 * q2), 1 - 2 * (q2**2 + q3**2))
+
+  eulers = array([gamma, theta, psi]).T
+  return eulers.reshape(output_shape)
+
+
+def quat2rot(quats):
+  quats = array(quats)
+  input_shape = quats.shape
+  quats = np.atleast_2d(quats)
+  Rs = np.zeros((quats.shape[0], 3, 3))
+  q0 = quats[:, 0]
+  q1 = quats[:, 1]
+  q2 = quats[:, 2]
+  q3 = quats[:, 3]
+  Rs[:, 0, 0] = q0 * q0 + q1 * q1 - q2 * q2 - q3 * q3
+  Rs[:, 0, 1] = 2 * (q1 * q2 - q0 * q3)
+  Rs[:, 0, 2] = 2 * (q0 * q2 + q1 * q3)
+  Rs[:, 1, 0] = 2 * (q1 * q2 + q0 * q3)
+  Rs[:, 1, 1] = q0 * q0 - q1 * q1 + q2 * q2 - q3 * q3
+  Rs[:, 1, 2] = 2 * (q2 * q3 - q0 * q1)
+  Rs[:, 2, 0] = 2 * (q1 * q3 - q0 * q2)
+  Rs[:, 2, 1] = 2 * (q0 * q1 + q2 * q3)
+  Rs[:, 2, 2] = q0 * q0 - q1 * q1 - q2 * q2 + q3 * q3
+
+  if len(input_shape) < 2:
+    return Rs[0]
+  else:
+    return Rs
+
+
+def rot2quat(rots):
+  input_shape = rots.shape
+  if len(input_shape) < 3:
+    rots = array([rots])
+  K3 = np.empty((len(rots), 4, 4))
+  K3[:, 0, 0] = (rots[:, 0, 0] - rots[:, 1, 1] - rots[:, 2, 2]) / 3.0
+  K3[:, 0, 1] = (rots[:, 1, 0] + rots[:, 0, 1]) / 3.0
+  K3[:, 0, 2] = (rots[:, 2, 0] + rots[:, 0, 2]) / 3.0
+  K3[:, 0, 3] = (rots[:, 1, 2] - rots[:, 2, 1]) / 3.0
+  K3[:, 1, 0] = K3[:, 0, 1]
+  K3[:, 1, 1] = (rots[:, 1, 1] - rots[:, 0, 0] - rots[:, 2, 2]) / 3.0
+  K3[:, 1, 2] = (rots[:, 2, 1] + rots[:, 1, 2]) / 3.0
+  K3[:, 1, 3] = (rots[:, 2, 0] - rots[:, 0, 2]) / 3.0
+  K3[:, 2, 0] = K3[:, 0, 2]
+  K3[:, 2, 1] = K3[:, 1, 2]
+  K3[:, 2, 2] = (rots[:, 2, 2] - rots[:, 0, 0] - rots[:, 1, 1]) / 3.0
+  K3[:, 2, 3] = (rots[:, 0, 1] - rots[:, 1, 0]) / 3.0
+  K3[:, 3, 0] = K3[:, 0, 3]
+  K3[:, 3, 1] = K3[:, 1, 3]
+  K3[:, 3, 2] = K3[:, 2, 3]
+  K3[:, 3, 3] = (rots[:, 0, 0] + rots[:, 1, 1] + rots[:, 2, 2]) / 3.0
+  q = np.empty((len(rots), 4))
+  for i in range(len(rots)):
+    _, eigvecs = linalg.eigh(K3[i].T)
+    eigvecs = eigvecs[:,3:]
+    q[i, 0] = eigvecs[-1]
+    q[i, 1:] = -eigvecs[:-1].flatten()
+    if q[i, 0] < 0:
+      q[i] = -q[i]
+
+  if len(input_shape) < 3:
+    return q[0]
+  else:
+    return q
+
+
+def euler2rot(eulers):
+  return rotations_from_quats(euler2quat(eulers))
+
+
+def rot2euler(rots):
+  return quat2euler(quats_from_rotations(rots))
+
+
+quats_from_rotations = rot2quat
+quat_from_rot = rot2quat
+rotations_from_quats = quat2rot
+rot_from_quat= quat2rot
+rot_from_quat= quat2rot
+euler_from_rot = rot2euler
+euler_from_quat = quat2euler
+rot_from_euler = euler2rot
+quat_from_euler = euler2quat
+
+
+
+
+
+
+'''
+Random helpers below
+'''
+
+
+def quat_product(q, r):
+  t = np.zeros(4)
+  t[0] = r[0] * q[0] - r[1] * q[1] - r[2] * q[2] - r[3] * q[3]
+  t[1] = r[0] * q[1] + r[1] * q[0] - r[2] * q[3] + r[3] * q[2]
+  t[2] = r[0] * q[2] + r[1] * q[3] + r[2] * q[0] - r[3] * q[1]
+  t[3] = r[0] * q[3] - r[1] * q[2] + r[2] * q[1] + r[3] * q[0]
+  return t
+
+
+def rot_matrix(roll, pitch, yaw):
+  cr, sr = np.cos(roll), np.sin(roll)
+  cp, sp = np.cos(pitch), np.sin(pitch)
+  cy, sy = np.cos(yaw), np.sin(yaw)
+  rr = array([[1,0,0],[0, cr,-sr],[0, sr, cr]])
+  rp = array([[cp,0,sp],[0, 1,0],[-sp, 0, cp]])
+  ry = array([[cy,-sy,0],[sy, cy,0],[0, 0, 1]])
+  return ry.dot(rp.dot(rr))
+
+
+def rot(axis, angle):
+  # Rotates around an arbitrary axis
+  ret_1 = (1 - np.cos(angle)) * array([[axis[0]**2, axis[0] * axis[1], axis[0] * axis[2]], [
+    axis[1] * axis[0], axis[1]**2, axis[1] * axis[2]
+  ], [axis[2] * axis[0], axis[2] * axis[1], axis[2]**2]])
+  ret_2 = np.cos(angle) * np.eye(3)
+  ret_3 = np.sin(angle) * array([[0, -axis[2], axis[1]], [axis[2], 0, -axis[0]],
+                              [-axis[1], axis[0], 0]])
+  return ret_1 + ret_2 + ret_3
+
+
+def ecef_euler_from_ned(ned_ecef_init, ned_pose):
+  '''
+  Got it from here:
+  Using Rotations to Build Aerospace Coordinate Systems
+  -Don Koks
+  '''
+  converter = LocalCoord.from_ecef(ned_ecef_init)
+  x0 = converter.ned2ecef([1, 0, 0]) - converter.ned2ecef([0, 0, 0])
+  y0 = converter.ned2ecef([0, 1, 0]) - converter.ned2ecef([0, 0, 0])
+  z0 = converter.ned2ecef([0, 0, 1]) - converter.ned2ecef([0, 0, 0])
+
+  x1 = rot(z0, ned_pose[2]).dot(x0)
+  y1 = rot(z0, ned_pose[2]).dot(y0)
+  z1 = rot(z0, ned_pose[2]).dot(z0)
+
+  x2 = rot(y1, ned_pose[1]).dot(x1)
+  y2 = rot(y1, ned_pose[1]).dot(y1)
+  z2 = rot(y1, ned_pose[1]).dot(z1)
+
+  x3 = rot(x2, ned_pose[0]).dot(x2)
+  y3 = rot(x2, ned_pose[0]).dot(y2)
+  #z3 = rot(x2, ned_pose[0]).dot(z2)
+
+  x0 = array([1, 0, 0])
+  y0 = array([0, 1, 0])
+  z0 = array([0, 0, 1])
+
+  psi = np.arctan2(inner(x3, y0), inner(x3, x0))
+  theta = np.arctan2(-inner(x3, z0), np.sqrt(inner(x3, x0)**2 + inner(x3, y0)**2))
+  y2 = rot(z0, psi).dot(y0)
+  z2 = rot(y2, theta).dot(z0)
+  phi = np.arctan2(inner(y3, z2), inner(y3, y2))
+
+  ret = array([phi, theta, psi])
+  return ret
+
+
+def ned_euler_from_ecef(ned_ecef_init, ecef_poses):
+  '''
+  Got the math from here:
+  Using Rotations to Build Aerospace Coordinate Systems
+  -Don Koks
+
+  Also accepts array of ecef_poses and array of ned_ecef_inits.
+  Where each row is a pose and an ecef_init.
+  '''
+  ned_ecef_init = array(ned_ecef_init)
+  ecef_poses = array(ecef_poses)
+  output_shape = ecef_poses.shape
+  ned_ecef_init = np.atleast_2d(ned_ecef_init)
+  if ned_ecef_init.shape[0] == 1:
+    ned_ecef_init = np.tile(ned_ecef_init[0], (output_shape[0], 1))
+  ecef_poses = np.atleast_2d(ecef_poses)
+
+  ned_poses = np.zeros(ecef_poses.shape)
+  for i, ecef_pose in enumerate(ecef_poses):
+    converter = LocalCoord.from_ecef(ned_ecef_init[i])
+    x0 = array([1, 0, 0])
+    y0 = array([0, 1, 0])
+    z0 = array([0, 0, 1])
+
+    x1 = rot(z0, ecef_pose[2]).dot(x0)
+    y1 = rot(z0, ecef_pose[2]).dot(y0)
+    z1 = rot(z0, ecef_pose[2]).dot(z0)
+
+    x2 = rot(y1, ecef_pose[1]).dot(x1)
+    y2 = rot(y1, ecef_pose[1]).dot(y1)
+    z2 = rot(y1, ecef_pose[1]).dot(z1)
+
+    x3 = rot(x2, ecef_pose[0]).dot(x2)
+    y3 = rot(x2, ecef_pose[0]).dot(y2)
+    #z3 = rot(x2, ecef_pose[0]).dot(z2)
+
+    x0 = converter.ned2ecef([1, 0, 0]) - converter.ned2ecef([0, 0, 0])
+    y0 = converter.ned2ecef([0, 1, 0]) - converter.ned2ecef([0, 0, 0])
+    z0 = converter.ned2ecef([0, 0, 1]) - converter.ned2ecef([0, 0, 0])
+
+    psi = np.arctan2(inner(x3, y0), inner(x3, x0))
+    theta = np.arctan2(-inner(x3, z0), np.sqrt(inner(x3, x0)**2 + inner(x3, y0)**2))
+    y2 = rot(z0, psi).dot(y0)
+    z2 = rot(y2, theta).dot(z0)
+    phi = np.arctan2(inner(y3, z2), inner(y3, y2))
+    ned_poses[i] = array([phi, theta, psi])
+
+  return ned_poses.reshape(output_shape)
+
+
+def ecef2car(car_ecef, psi, theta, points_ecef, ned_converter):
+  """
+  TODO: add roll rotation
+  Converts an array of points in ecef coordinates into
+  x-forward, y-left, z-up coordinates
+  Parameters
+  ----------
+  psi: yaw, radian
+  theta: pitch, radian
+  Returns
+  -------
+  [x, y, z] coordinates in car frame
+  """
+
+  # input is an array of points in ecef cocrdinates
+  # output is an array of points in car's coordinate (x-front, y-left, z-up)
+
+  # convert points to NED
+  points_ned = []
+  for p in points_ecef:
+    points_ned.append(ned_converter.ecef2ned_matrix.dot(array(p) - car_ecef))
+
+  points_ned = np.vstack(points_ned).T
+
+  # n, e, d -> x, y, z
+  # Calculate relative postions and rotate wrt to heading and pitch of car
+  invert_R = array([[1., 0., 0.], [0., -1., 0.], [0., 0., -1.]])
+
+  c, s = np.cos(psi), np.sin(psi)
+  yaw_R = array([[c, s, 0.], [-s, c, 0.], [0., 0., 1.]])
+
+  c, s = np.cos(theta), np.sin(theta)
+  pitch_R = array([[c, 0., -s], [0., 1., 0.], [s, 0., c]])
+
+  return dot(pitch_R, dot(yaw_R, dot(invert_R, points_ned)))

common/transformations/tests/test_coordinates.py

@@ -0,0 +1,122 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import unittest
+
+import common.transformations.coordinates as coord
+
+geodetic_positions = np.array([[37.7610403, -122.4778699, 115],
+                                 [27.4840915, -68.5867592, 2380],
+                                 [32.4916858, -113.652821, -6],
+                                 [15.1392514, 103.6976037, 24],
+                                 [24.2302229, 44.2835412, 1650]])
+
+geodetic_positions_radians = np.array([[0.65905448, -2.13764209, 115],
+                                       [0.47968789, -1.19706477, 2380],
+                                       [0.5670869, -1.98361593, -6],
+                                       [0.26422978, 1.80986461, 24],
+                                       [0.42289717, 0.7728936, 1650]])
+
+ecef_positions = np.array([[-2711076.55270557, -4259167.14692758,  3884579.87669935],
+                          [ 2068042.69652729, -5273435.40316622,  2927004.89190746],
+                          [-2160412.60461669, -4932588.89873832,  3406542.29652851],
+                          [-1458247.92550567,  5983060.87496612,  1654984.6099885 ],
+                          [ 4167239.10867871,  4064301.90363223,  2602234.6065749 ]])
+
+ecef_positions_offset = np.array([[-2711004.46961115, -4259099.33540613,  3884605.16002147],
+                                  [ 2068074.30639499, -5273413.78835412,  2927012.48741131],
+                                  [-2160344.53748176, -4932586.20092211,  3406636.2962545 ],
+                                  [-1458211.98517094,  5983151.11161276,  1655077.02698447],
+                                  [ 4167271.20055269,  4064398.22619263,  2602238.95265847]])
+
+
+ned_offsets = np.array([[78.722153649976391, 24.396208657446344, 60.343017506838436],
+                       [10.699003365155221, 37.319278617604269, 4.1084100025050407],
+                       [95.282646251726959, 61.266689955574428, -25.376506058505054],
+                       [68.535769283630003, -56.285970011848889, -100.54840137956515],
+                       [-33.066609321880179, 46.549821994306861, -84.062540548335591]])
+
+ecef_init_batch = np.array([2068042.69652729, -5273435.40316622,  2927004.89190746])
+ecef_positions_offset_batch = np.array([[ 2068089.41454771, -5273434.46829148,  2927074.04783672],
+                                        [ 2068103.31628647, -5273393.92275431,  2927102.08725987],
+                                        [ 2068108.49939636, -5273359.27047121,  2927045.07091581],
+                                        [ 2068075.12395611, -5273381.69432566,  2927041.08207992],
+                                        [ 2068060.72033399, -5273430.6061505,  2927094.54928305]])
+
+ned_offsets_batch = np.array([[  53.88103168,   43.83445935,  -46.27488057],
+                              [  93.83378995,   71.57943024,  -30.23113187],
+                              [  57.26725796,   89.05602684,   23.02265814],
+                              [  49.71775195,   49.79767572,   17.15351015],
+                              [  78.56272609,   18.53100158,  -43.25290759]])
+
+
+
+class TestNED(unittest.TestCase):
+  def test_small_distances(self):
+    start_geodetic = np.array([33.8042184, -117.888593, 0.0])
+    local_coord = coord.LocalCoord.from_geodetic(start_geodetic)
+
+    start_ned = local_coord.geodetic2ned(start_geodetic)
+    np.testing.assert_array_equal(start_ned, np.zeros(3,))
+
+    west_geodetic = start_geodetic + [0, -0.0005, 0]
+    west_ned = local_coord.geodetic2ned(west_geodetic)
+    self.assertLess(np.abs(west_ned[0]), 1e-3)
+    self.assertLess(west_ned[1], 0)
+
+    southwest_geodetic = start_geodetic + [-0.0005, -0.002, 0]
+    southwest_ned = local_coord.geodetic2ned(southwest_geodetic)
+    self.assertLess(southwest_ned[0], 0)
+    self.assertLess(southwest_ned[1], 0)
+
+  def test_ecef_geodetic(self):
+    # testing single
+    np.testing.assert_allclose(ecef_positions[0], coord.geodetic2ecef(geodetic_positions[0]), rtol=1e-9)
+    np.testing.assert_allclose(geodetic_positions[0,:2], coord.ecef2geodetic(ecef_positions[0])[:2], rtol=1e-9)
+    np.testing.assert_allclose(geodetic_positions[0,2], coord.ecef2geodetic(ecef_positions[0])[2], rtol=1e-9, atol=1e-4)
+
+    np.testing.assert_allclose(geodetic_positions[:,:2], coord.ecef2geodetic(ecef_positions)[:,:2], rtol=1e-9)
+    np.testing.assert_allclose(geodetic_positions[:,2], coord.ecef2geodetic(ecef_positions)[:,2], rtol=1e-9, atol=1e-4)
+    np.testing.assert_allclose(ecef_positions, coord.geodetic2ecef(geodetic_positions), rtol=1e-9)
+
+    np.testing.assert_allclose(geodetic_positions_radians[0], coord.ecef2geodetic(ecef_positions[0], radians=True), rtol=1e-5)
+    np.testing.assert_allclose(geodetic_positions_radians[:,:2], coord.ecef2geodetic(ecef_positions, radians=True)[:,:2], rtol=1e-7)
+    np.testing.assert_allclose(geodetic_positions_radians[:,2], coord.ecef2geodetic(ecef_positions, radians=True)[:,2], rtol=1e-7, atol=1e-4)
+
+
+
+  def test_ned(self):
+    for ecef_pos in ecef_positions:
+      converter = coord.LocalCoord.from_ecef(ecef_pos)
+      ecef_pos_moved = ecef_pos + [25, -25, 25]
+      ecef_pos_moved_double_converted = converter.ned2ecef(converter.ecef2ned(ecef_pos_moved))
+      np.testing.assert_allclose(ecef_pos_moved, ecef_pos_moved_double_converted, rtol=1e-9)
+
+    for geo_pos in geodetic_positions:
+      converter = coord.LocalCoord.from_geodetic(geo_pos)
+      geo_pos_moved = geo_pos + np.array([0, 0, 10])
+      geo_pos_double_converted_moved = converter.ned2geodetic(converter.geodetic2ned(geo_pos) + np.array([0,0,-10]))
+      np.testing.assert_allclose(geo_pos_moved[:2], geo_pos_double_converted_moved[:2], rtol=1e-9, atol=1e-6)
+      np.testing.assert_allclose(geo_pos_moved[2], geo_pos_double_converted_moved[2], rtol=1e-9, atol=1e-4)
+
+
+  def test_ned_saved_results(self):
+    for i, ecef_pos in enumerate(ecef_positions):
+      converter = coord.LocalCoord.from_ecef(ecef_pos)
+      np.testing.assert_allclose(converter.ned2ecef(ned_offsets[i]),
+                                 ecef_positions_offset[i],
+                                 rtol=1e-9, atol=1e-4)
+      np.testing.assert_allclose(converter.ecef2ned(ecef_positions_offset[i]),
+                                 ned_offsets[i],
+                                 rtol=1e-9, atol=1e-4)
+
+  def test_ned_batch(self):
+    converter = coord.LocalCoord.from_ecef(ecef_init_batch)
+    np.testing.assert_allclose(converter.ecef2ned(ecef_positions_offset_batch),
+                                                           ned_offsets_batch,
+                                                           rtol=1e-9, atol=1e-7)
+    np.testing.assert_allclose(converter.ned2ecef(ned_offsets_batch),
+                                                           ecef_positions_offset_batch,
+                                                           rtol=1e-9, atol=1e-7)
+if __name__ == "__main__":
+  unittest.main()

common/transformations/tests/test_orientation.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import unittest
+
+from common.transformations.orientation import euler2quat, quat2euler, euler2rot, rot2euler, \
+                                               rot2quat, quat2rot, \
+                                               ned_euler_from_ecef
+
+eulers = np.array([[ 1.46520501,  2.78688383,  2.92780854],
+       [ 4.86909526,  3.60618161,  4.30648981],
+       [ 3.72175965,  2.68763705,  5.43895988],
+       [ 5.92306687,  5.69573614,  0.81100357],
+       [ 0.67838374,  5.02402037,  2.47106426]])
+
+quats = np.array([[ 0.66855182, -0.71500939,  0.19539353,  0.06017818],
+       [ 0.43163717,  0.70013301,  0.28209145,  0.49389021],
+       [ 0.44121991, -0.08252646,  0.34257534,  0.82532207],
+       [ 0.88578382, -0.04515356, -0.32936046,  0.32383617],
+       [ 0.06578165,  0.61282835,  0.07126891,  0.78424163]])
+
+ecef_positions = np.array([[-2711076.55270557, -4259167.14692758,  3884579.87669935],
+                          [ 2068042.69652729, -5273435.40316622,  2927004.89190746],
+                          [-2160412.60461669, -4932588.89873832,  3406542.29652851],
+                          [-1458247.92550567,  5983060.87496612,  1654984.6099885 ],
+                          [ 4167239.10867871,  4064301.90363223,  2602234.6065749 ]])
+
+ned_eulers = np.array([[ 0.46806039, -0.4881889 ,  1.65697808],
+                    [-2.14525969, -0.36533066,  0.73813479],
+                    [-1.39523364, -0.58540761, -1.77376356],
+                    [-1.84220435,  0.61828016, -1.03310421],
+                    [ 2.50450101,  0.36304151,  0.33136365]])
+
+
+class TestOrientation(unittest.TestCase):
+  def test_quat_euler(self):
+    for i, eul in enumerate(eulers):
+      np.testing.assert_allclose(quats[i], euler2quat(eul), rtol=1e-7)
+      np.testing.assert_allclose(quats[i], euler2quat(quat2euler(quats[i])), rtol=1e-6)
+    for i, eul in enumerate(eulers):
+      np.testing.assert_allclose(quats[i], euler2quat(list(eul)), rtol=1e-7)
+      np.testing.assert_allclose(quats[i], euler2quat(quat2euler(list(quats[i]))), rtol=1e-6)
+    np.testing.assert_allclose(quats, euler2quat(eulers), rtol=1e-7)
+    np.testing.assert_allclose(quats, euler2quat(quat2euler(quats)), rtol=1e-6)
+
+  def test_rot_euler(self):
+    for eul in eulers:
+      np.testing.assert_allclose(euler2quat(eul), euler2quat(rot2euler(euler2rot(eul))), rtol=1e-7)
+    for eul in eulers:
+      np.testing.assert_allclose(euler2quat(eul), euler2quat(rot2euler(euler2rot(list(eul)))), rtol=1e-7)
+    np.testing.assert_allclose(euler2quat(eulers), euler2quat(rot2euler(euler2rot(eulers))), rtol=1e-7)
+
+  def test_rot_quat(self):
+    for quat in quats:
+      np.testing.assert_allclose(quat, rot2quat(quat2rot(quat)), rtol=1e-7)
+    for quat in quats:
+      np.testing.assert_allclose(quat, rot2quat(quat2rot(list(quat))), rtol=1e-7)
+    np.testing.assert_allclose(quats, rot2quat(quat2rot(quats)), rtol=1e-7)
+
+  def test_euler_ned(self):
+    for i in range(len(eulers)):
+      np.testing.assert_allclose(ned_eulers[i], ned_euler_from_ecef(ecef_positions[i], eulers[i]), rtol=1e-7)
+      #np.testing.assert_allclose(eulers[i], ecef_euler_from_ned(ecef_positions[i], ned_eulers[i]), rtol=1e-7)
+    np.testing.assert_allclose(ned_eulers, ned_euler_from_ecef(ecef_positions, eulers), rtol=1e-7)
+
+
+
+if __name__ == "__main__":
+  unittest.main()