xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

8ca4305bf27ee3867690505a7764b93195be5977

30

py

Python

stepik/3559/66578/step_5/script.py

tshemake/Software-Development

e6dff82dffa49e66dc5fa5650af775437ebb6a9b

[ "Unlicense" ]

null

stepik/3559/66578/step_5/script.py

tshemake/Software-Development

e6dff82dffa49e66dc5fa5650af775437ebb6a9b

[ "Unlicense" ]

null

stepik/3559/66578/step_5/script.py

tshemake/Software-Development

e6dff82dffa49e66dc5fa5650af775437ebb6a9b

[ "Unlicense" ]

null

print(241.90263432641407 / 77)

30

0.8

4

30

6

1

0

0.678571

0.066667

30

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30

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true

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null

0

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1

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8ca65b9706dc95450bd40aa7ed91ab64422e8e46

30,008

py

Python

test_gitstatus.py

ksomf/zsh-git-prompt

fba95921f9545d6ffc6bf7a13548331a77e72a1a

[ "MIT" ]

64

2018-05-31T02:28:18.000Z

2022-02-10T14:27:20.000Z

test_gitstatus.py

ksomf/zsh-git-prompt

fba95921f9545d6ffc6bf7a13548331a77e72a1a

[ "MIT" ]

36

2018-05-25T13:01:14.000Z

2020-01-06T18:07:35.000Z

test_gitstatus.py

ksomf/zsh-git-prompt

fba95921f9545d6ffc6bf7a13548331a77e72a1a

[ "MIT" ]

19

2018-06-02T13:35:19.000Z

2022-01-18T23:56:35.000Z

""" Test module for gitstatus Fixtures used to to setup git repo scenarios on the fly. Tests are short and at the end of this file. """ from __future__ import absolute_import, print_function import os import re import shlex import shutil import subprocess as sub import tempfile import pytest import gitstatus GIT_STATUS = os.path.join(os.path.dirname(__file__), 'gitstatus.py') def run_gitstatus(): """ Helper to simply run gitstatus in the current directory. Returns: The output of gitstatus.py in the CWD. """ return sub.check_output(['python', GIT_STATUS]).decode('utf-8', errors='ignore') @pytest.yield_fixture(scope="function") def empty_working_directory(): """ Run a test inside an empty temporary directory. """ cwd = os.getcwd() try: folder = tempfile.mkdtemp() os.chdir(folder) yield finally: os.chdir(cwd) try: shutil.rmtree(folder) except (OSError, IOError): pass @pytest.yield_fixture(scope="function") def git_repo_initial_commit(): """ Create a fake git repo with the following properties: - No commits beyond initialization. """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_find_git_root(): """ Create a fake git repo with the following properties: - 1 commit - nested folders called, first/second/third """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", ] try: subs = os.path.join(folder, 'd_one', 'd_two', 'd_three') os.makedirs(subs) os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_with_worktree(): """ Create a fake git repo with the following properties: - main repo has 3 commits - upstream repo has 3 commits - main repo has upstream set and is has diverged by 1 commit each way """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_tree = folder + "_worktree" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:Second line", "git add first", "git commit -m 'second commit'", "git branch tree", "git checkout tree", "first:third line", "git add first", "git commit -m 'third commit'", "git checkout master", "git worktree add --detach %s tree" % (folder_tree), ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) os.chdir(folder_tree) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_tree) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_parse_stats(): """ Create a fake git repo with the following properties: - upstream set to another local git repo - 3 staged files (1 changed, 2 additions) - 1 changed file unstaged - 2 untracked files - 1 stashed change set """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "second:A single line", "third:A single line", "touch untracked1 untracked2", "git add first", "git commit -m 'first commit'", "first:Changes to stash", "git stash", "first:Changes to stage", "git add first second third", "first:Changes but unstaged", "cp -R %s %s" % (folder, folder_up), "git remote add -f up %s" % folder_up, "git branch --set-upstream-to=up/master", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_parse_stats_only_conflicts(): """ Create a fake git repo with the following properties: - upstream set to another local git repo - edit the same file and create a merge conflict """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line\nsecond line\third line", "git add first", "git commit -m 'first commit'", "first:fourth line\nfifth line\n", "git add first", "git commit -m 'second commit'", "cp -R %s %s" % (folder, folder_up), "git reset --hard HEAD~1", "first:ninth line\ntenth line\n", "git add first", "git commit -m 'new second commit'", "git remote add -f up %s" % folder_up, "git branch --set-upstream-to=up/master", "git fetch up", "git merge up/master", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: try: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) except sub.CalledProcessError: pass yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_branch_on_hash(): """ Create a fake git repo with the following properties: - 3 commits made - yield when on checkout hash """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:A second line", "git add first", "git commit -m 'second commit'", "git checkout HEAD~1", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_branch_on_master(): """ Create a fake git repo with the following properties: - 3 commits made - yield when on checkout hash """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:A second line", "git add first", "git commit -m 'second commit'", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_branch_local_only(): """ Create a fake git repo with the following properties: - 1 commit - no upstream copy or set value """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_remote_ahead(): """ Create a fake git repo with the following properties: - main repo has 3 commits - upstream repo has 2 commits - main repo has upstream set and is AHEAD by 1 commit """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:Second line", "git add first", "git commit -m 'second commit'", "cp -R %s %s" % (folder, folder_up), "first:third line", "git add first", "git commit -m 'third commit'", "git remote add -f up %s" % folder_up, "git branch --set-upstream-to=up/master", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_remote_behind(): """ Create a fake git repo with the following properties: - main repo has 2 commits - upstream repo has 3 commits - main repo has upstream set and is BEHIND by 1 commit """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:Second line", "git add first", "git commit -m 'second commit'", "first:third line", "git add first", "git commit -m 'third commit'", "cp -R %s %s" % (folder, folder_up), "git remote add -f up %s" % folder_up, "git branch --set-upstream-to=up/master", "git reset --hard HEAD~1", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_remote_diverged(): """ Create a fake git repo with the following properties: - main repo has 3 commits - upstream repo has 4 commits - main repo has upstream set and is has diverged 2 behind, 1 ahead """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:Second line", "git add first", "git commit -m 'second commit'", "first:third line", "git add first", "git commit -m 'third commit'", "first:fourth line", "git add first", "git commit -m 'fourth commit'", "cp -R %s %s" % (folder, folder_up), "git remote add -f up %s" % folder_up, "git branch --set-upstream-to=up/master", "git reset --hard HEAD~2", "first:different third line", "git add first", "git commit -m 'different third commit'", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_in_merge(): """ Create a fake git repo with the following properties: - master branch with 2 commits - dev branch that has 2 commits, last one differs from master - dev branch is merging master into it """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "git branch dev", "first:the second master line here", "git add first", "git commit -m 'second master commit'", "git checkout dev", "first:Second line for dev", "git add first", "git commit -m 'second dev commit'", "git merge master", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: proc = sub.Popen(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) proc.wait() yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_in_rebase(): """ Create a fake git repo with the following properties: - master branch with 3 commits - dev branch that has 3 commits, last two differ from master - dev is rebasing master, 2 commits need resolving """ cwd = os.getcwd() folder = tempfile.mkdtemp() cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "git branch dev", "first:the second master line here", "git add first", "git commit -m 'second master commit'", "first:there is also a third master", "git add first", "git commit -m 'third master commit'", "git checkout dev", "first:Second line", "git add first", "git commit -m 'second dev commit'", "first:Third line\nForuth line", "git add first", "git commit -m 'third dev commit'", "git rebase master", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: proc = sub.Popen(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) proc.wait() yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass os.chdir(cwd) @pytest.yield_fixture(scope="function") def git_repo_upstream_gone(): """ Create a fake git repo with the following properties: - create a repo with 2 commits and a 'dev' branch - copy repo to create an upstream - set 'dev' branch to track 'up/dev' - delete upstream dev """ cwd = os.getcwd() folder = tempfile.mkdtemp() folder_up = folder + "_upstream" cmds = [ "git init", "git config user.email 'you@example.com'", "git config user.name 'Your Name'", "first:A single line", "git add first", "git commit -m 'first commit'", "first:Second line", "git add first", "git commit -m 'second commit'", "cp -R %s %s" % (folder, folder_up), "git remote add -f up %s" % folder_up, "git branch dev", "git checkout dev", "git push -u up dev", "git fetch up", "git push up :dev", ] try: os.chdir(folder) for cmd in cmds: if re.match(r'\S+:', cmd): assert len(cmd.split(":")) == 2 fname, text = cmd.split(":") with open(os.path.join(folder, fname), 'a') as fout: fout.write(text + '\n') else: with open(os.devnull, 'w') as devnull: sub.check_call(shlex.split(cmd), stdout=devnull, stderr=sub.STDOUT) yield finally: try: shutil.rmtree(folder) except (OSError, IOError): pass try: shutil.rmtree(folder_up) except (OSError, IOError): pass os.chdir(cwd) # ---------- # Unit Tests # ---------- def test_find_git_root(git_repo_find_git_root): """ A unit test for gitstatus. """ expect = os.path.join(os.getcwd(), '.git') sub_d = os.path.join(os.getcwd(), 'd_one', 'd_two', 'd_three') assert os.path.isdir(sub_d) os.chdir(sub_d) assert gitstatus.find_git_root() == expect def test_find_git_root_fail(empty_working_directory): """ A unit test for gitstatus. """ with pytest.raises(IOError): gitstatus.find_git_root() def test_git_paths_in_normal_repo(git_repo_initial_commit): """ A unit test for gitstatus. """ head_file, stash_file, merge_file, rebase_dir = gitstatus.git_paths(gitstatus.find_git_root()) assert head_file == os.path.join(os.getcwd(), '.git', 'HEAD') assert stash_file == os.path.join(os.getcwd(), '.git', 'logs', 'refs', 'stash') assert merge_file == os.path.join(os.getcwd(), '.git', 'MERGE_HEAD') assert rebase_dir == os.path.join(os.getcwd(), '.git', 'rebase-apply') def test_git_paths_in_working_tree(git_repo_with_worktree): """ A unit test for gitstatus. """ repo_root = os.getcwd().replace('_worktree', '') tree_root = os.path.join(repo_root, '.git', 'worktrees', os.path.basename(repo_root) + '_worktree') head_file, stash_file, merge_file, rebase_dir = gitstatus.git_paths(gitstatus.find_git_root()) assert head_file == os.path.join(tree_root, 'HEAD') assert stash_file == os.path.join(repo_root, '.git', 'logs', 'refs', 'stash') assert merge_file == os.path.join(tree_root, 'MERGE_HEAD') assert rebase_dir == os.path.join(tree_root, 'rebase-apply') def test_parse_stats(): """ A unit test for gitstatus. """ status_input = """?? untracked1 ?? untracked2 ?? untracked3 AA conflicts1 AU conflicts2 DD conflicts3 DU conflicts4 UA conflicts5 UD conflicts6 UD conflicts7 A_ staged1 C_ staged2 D_ staged3 M_ staged4 R_ staged5 _C changed1 _D changed2 _M changed3 _R changed4""" assert gitstatus.parse_stats(status_input.splitlines()) == (5, 7, 4, 3) def test_parse_ahead_behind_only_ahead(): """ A unit test for gitstatus. """ assert gitstatus.parse_ahead_behind("## master...up/master [ahead 2]") == (2, 0) def test_parse_ahead_behind_only_behind(): """ A unit test for gitstatus. """ assert gitstatus.parse_ahead_behind("## master...up/master [behind 1]") == (0, 1) def test_parse_ahead_behind_both(): """ A unit test for gitstatus. """ assert gitstatus.parse_ahead_behind("## master...up/master [ahead 2, behind 1]") == (2, 1) def test_parse_branch_on_local_branch(): """ A unit test for gitstatus. """ branch_line = "## master" assert gitstatus.parse_branch(branch_line, None) == ('master', '..', 1) def test_parse_branch_has_upstream(): """ A unit test for gitstatus. """ branch_line = "## master...up/master [ahead 2, behind 1]" assert gitstatus.parse_branch(branch_line, None) == ('master', 'up/master', 0) def test_parse_branch_out_on_hash(git_repo_branch_on_hash): """ A unit test for gitstatus. """ actual_hash = sub.check_output(shlex.split('git rev-parse --short HEAD')) actual_hash = actual_hash.decode('utf-8', errors='ignore').strip() head_file = os.path.join(os.getcwd(), '.git', 'HEAD') branch_line = "## HEAD (no branch)" assert gitstatus.parse_branch(branch_line, head_file) == (':' + actual_hash, '..', 0) def test_stash_count_one_stash(git_repo_parse_stats): """ A unit test for gitstatus. """ stash_file = os.path.join(os.getcwd(), '.git', 'logs', 'refs', 'stash') assert gitstatus.stash_count(stash_file) == 1 def test_stash_count_no_stash(git_repo_initial_commit): """ A unit test for gitstatus. """ stash_file = os.path.join(os.getcwd(), 'logs', 'refs', 'stash') assert gitstatus.stash_count(stash_file) == 0 def test_rebase_progress_active_rebase(git_repo_in_rebase): rebase_dir = os.path.join(os.getcwd(), '.git', 'rebase-apply') assert gitstatus.rebase_progress(rebase_dir) == '1/2' def test_rebase_progress_no_rebase(git_repo_initial_commit): rebase_dir = os.path.join(os.getcwd(), '.git', 'rebase-apply') assert gitstatus.rebase_progress(rebase_dir) == '0' # ---------------- # Functional Tests # ---------------- def test_gitstatus_no_repo(empty_working_directory): """ A unit test for gitstatus. """ assert run_gitstatus() == '' def test_gitstatus_initial_commit(git_repo_initial_commit): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 0 0 0 0 0 0 0 1 {} 0 0'.format(gitstatus.SYM_NOUPSTREAM) def test_gitstatus_local_branch(git_repo_branch_on_master): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 0 0 0 0 0 0 0 1 {} 0 0'.format(gitstatus.SYM_NOUPSTREAM) def test_gitstatus_on_hash(git_repo_branch_on_hash): """ A unit test for gitstatus. """ actual_hash = sub.check_output(shlex.split('git rev-parse --short HEAD')) actual_hash = actual_hash.decode('utf-8', errors='ignore').strip() assert run_gitstatus() == ':{} 0 0 0 0 0 0 0 0 {} 0 0'.format(actual_hash, gitstatus.SYM_NOUPSTREAM) def test_gitstatus_parse_stats_no_conflicts(git_repo_parse_stats): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 0 0 3 0 1 2 1 0 up/master 0 0' def test_gitstatus_parse_stats_only_conflicts(git_repo_parse_stats_only_conflicts): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 1 1 0 1 0 0 0 0 up/master 1 0' def test_gitstatus_remote_ahead(git_repo_remote_ahead): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 1 0 0 0 0 0 0 0 up/master 0 0' def test_gitstatus_remote_behind(git_repo_remote_behind): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 0 1 0 0 0 0 0 0 up/master 0 0' def test_gitstatus_remote_diverged(git_repo_remote_diverged): """ A unit test for gitstatus. """ assert run_gitstatus() == 'master 1 2 0 0 0 0 0 0 up/master 0 0' def test_gitstatus_stdin(git_repo_parse_stats): """ A unit test for gitstatus. """ std_input = sub.check_output(['git', 'status', '--branch', '--porcelain']) with tempfile.TemporaryFile() as finput: finput.write(std_input) finput.seek(0) out = sub.check_output(['python', GIT_STATUS], stdin=finput).decode('utf-8') assert out == 'master 0 0 3 0 1 2 1 0 up/master 0 0' def test_gitstatus_merging(git_repo_in_merge): """ A unit test for gitstatus. """ assert run_gitstatus() == 'dev 0 0 0 1 0 0 0 1 .. 1 0' def test_gitstatus_rebasing(git_repo_in_rebase): """ A unit test for gitstatus. """ actual_hash = sub.check_output(shlex.split('git rev-parse --short HEAD')) actual_hash = actual_hash.decode('utf-8', errors='ignore').strip() assert run_gitstatus() == ':{} 0 0 0 1 0 0 0 0 .. 0 1/2'.format(actual_hash) def test_gitstatus_upstream_gone(git_repo_upstream_gone): """ A unit test for gitstatus. """ assert run_gitstatus() == 'dev 0 0 0 0 0 0 0 0 up/dev 0 0'

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50a958e3b16c7cd9237a78942c721421f767ff80

940

py

Python

evaluation/regression_metrics.py

rupakc/DriftGAN

acd2ebbed96d0b4d3ede38b01d7d6620f9b0f426

[ "Apache-2.0" ]

null

evaluation/regression_metrics.py

rupakc/DriftGAN

acd2ebbed96d0b4d3ede38b01d7d6620f9b0f426

[ "Apache-2.0" ]

null

evaluation/regression_metrics.py

rupakc/DriftGAN

acd2ebbed96d0b4d3ede38b01d7d6620f9b0f426

[ "Apache-2.0" ]

null

from sklearn.metrics.regression import mean_squared_error, median_absolute_error, mean_absolute_error from sklearn.metrics.regression import r2_score, mean_squared_log_error, explained_variance_score def get_mean_squared_error(gold_values, predicted_values): return mean_squared_error(gold_values, predicted_values) def get_median_absolute_error(gold_values, predicted_values): return median_absolute_error(gold_values, predicted_values) def get_mean_absolute_error(gold_values, predicted_values): return mean_absolute_error(gold_values, predicted_values) def get_r2_score(gold_values, predicted_values): return r2_score(gold_values, predicted_values) def get_mean_squared_log_error(gold_values, predicted_values): return mean_squared_log_error(gold_values, predicted_values) def get_explained_variance_score(gold_values, predicted_values): return explained_variance_score(gold_values, predicted_values)

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null

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7

50b40fc09dbcb8024f993618e62657bbcf5d806b

157

py

Python

src/lk_db/ents/both/census/EntMaritalStatusOfPopulation.py

nuuuwan/lk_db

ac0abfa47ba31b0d4c2c8566b3101b83749bd45d

[ "MIT" ]

null

src/lk_db/ents/both/census/EntMaritalStatusOfPopulation.py

nuuuwan/lk_db

ac0abfa47ba31b0d4c2c8566b3101b83749bd45d

[ "MIT" ]

null

src/lk_db/ents/both/census/EntMaritalStatusOfPopulation.py

nuuuwan/lk_db

ac0abfa47ba31b0d4c2c8566b3101b83749bd45d

[ "MIT" ]

null

# Auto Generated - DO NOT EDIT! from lk_db.ents.both.EntCensusResult import EntCensusResult class EntMaritalStatusOfPopulation(EntCensusResult): pass

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py

Python

src/LLS_search_patterns.py

frankeverdij/logic-life-search

0e6bf5f6b7a8fbbf838f4a65dbcff18e01a5c8a8

[ "MIT" ]

null

src/LLS_search_patterns.py

frankeverdij/logic-life-search

0e6bf5f6b7a8fbbf838f4a65dbcff18e01a5c8a8

[ "MIT" ]

null

src/LLS_search_patterns.py

frankeverdij/logic-life-search

0e6bf5f6b7a8fbbf838f4a65dbcff18e01a5c8a8

[ "MIT" ]

null

import copy from . import LLS_files from . import LLS_formatting from . import LLS_rules from . import LLS_defaults from .SearchPattern import SearchPattern from .LLS_messages import print_message from .LLS_literal_manipulation import neighbours_from_coordinates, variable_from_literal, negate def search_pattern_from_string(input_string, indent = 0, verbosity = 0): """Create the grid and ignore_transitionof a search pattern from the given string""" grid, ignore_transition = LLS_formatting.parse_input_string(input_string, indent = indent, verbosity = verbosity) print_message( "Pattern parsed as:\n" + LLS_formatting.make_csv(grid, ignore_transition) + "\n", 3, indent = indent, verbosity = verbosity ) for t, generation in enumerate(grid): for y, row in enumerate(generation): for x, cell in enumerate(row): if cell not in ["0", "1", "*"]: variable, negated = variable_from_literal(cell) grid[t][y][x] = negate("user_input_" + variable, negated) return grid, ignore_transition def blank_search_pattern(width, height, duration, indent = 0, verbosity = 0): print_message('Creating spaceship search pattern...', 3, indent = indent, verbosity = verbosity) grid = [[["*" for i in range(width)] for j in range(height)] for k in range(duration)] print_message("Pattern created:\n" + LLS_formatting.make_csv(grid) + "\n", 3, indent = indent+1, verbosity = verbosity) print_message('Done\n', 3, indent = indent, verbosity = verbosity) return grid def check_orphan(file_name, number_of_generations, indent = 0, verbosity = 0): print_message( 'Creating search pattern to see if file "' + file_name + '" contains an orphan...', 3, indent = indent, verbosity = verbosity ) input_string = LLS_files.string_from_file(file_name, indent = indent + 1, verbosity = verbosity) grid, _ = LLS_formatting.parse_input_string(input_string, indent = indent + 1, verbosity = verbosity) assert len(grid) == 1, "More than one generation in input" print_message( "Pattern parsed as:\n" + LLS_formatting.make_csv(grid) + "\n", 3, indent = indent+1, verbosity = verbosity ) pattern = grid[0] width = len(pattern[0]) height = len(pattern) padding = number_of_generations pattern = [["*" for columns in range(padding)] + row + ["*" for columns in range(padding)] for row in [["*" for cell in range( width)] for rows in range(padding)] + pattern + [["*" for cell in range(width)] for rows in range(padding)]] width = len(pattern[0]) height = len(pattern) duration = number_of_generations + 1 grid = [[["0" for cell in range(width)] for row in range( height)] for generation in range(number_of_generations)] + [pattern] ignore_transition = [[[True for cell in range(width)] for row in range( height)] for generation in range(number_of_generations)] + [[[False for cell in range(width)] for row in range( height)]] for t in range(number_of_generations - 1, -1, -1): for y in range(height): for x in range(width): if t == number_of_generations - 1: neighbours = neighbours_from_coordinates(grid,x,y,t,t_offset=1,background_grid=[[["*"]]]) nonempties = ["0", "1"] else: neighbours = neighbours_from_coordinates(grid,x,y,t,t_offset=1) nonempties = ["*"] if any(nonempty in neighbours for nonempty in nonempties): grid[t][y][x] = "*" ignore_transition[t][y][x] = False for y in range(height): for x in range(width): if grid[-1][y][x] not in ["0", "1"]: grid[-1][y][x] = "0" ignore_transition[-1][y][x] = True print_message("Search pattern:\n" + LLS_formatting.make_csv(grid, ignore_transition) + "\n", 3, indent = indent+1, verbosity = verbosity) print_message('Done\n', 3, indent = indent, verbosity = verbosity) return grid, ignore_transition def glider_eater_search_pattern(width,height,digestion_time,symmetry="C1",indent = 0, verbosity = 0): print_message('Creating eater search pattern...', 3, indent = indent, verbosity = verbosity) glider_in = [ [["1","0","0","0","0"], ["0","1","1","0","0"], ["1","1","0","0","0"], ["0","0","0","0","0"], ["0","0","0","0","0"]], [["0","1","0","0","0"], ["0","0","1","0","0"], ["1","1","1","0","0"], ["0","0","0","0","0"], ["0","0","0","0","0"]], [["0","0","0","0","0"], ["1","0","1","0","0"], ["0","1","1","0","0"], ["0","1","0","0","0"], ["0","0","0","0","0"]], [["0","0","0","0","0"], ["0","0","1","0","0"], ["1","0","1","0","0"], ["0","1","1","0","0"], ["0","0","0","0","0"]], [["0","0","0","0","0"], ["0","1","0","0","0"], ["0","0","1","1","0"], ["0","1","1","0","0"], ["0","0","0","0","0"]], [["0","0","0","0","0"], ["0","0","1","0","0"], ["0","0","0","1","0"], ["0","1","1","1","0"], ["0","0","0","0","0"]] ] width = width + 2 height = height + 2 duration = digestion_time + 6 grid = [[["0" for i in range(width)] for j in range(height)] for k in range(duration)] for y in range(1,height-1): for x in range(1,width-1): grid[-1][y][x] = "*" search_pattern = SearchPattern(grid) search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) for x in range(5): for y in range(5): search_pattern.grid[-1][y][x] = "0" search_pattern.force_symmetry(symmetry) for t, generation in enumerate(glider_in): search_pattern.grid[t] = copy.deepcopy(search_pattern.grid[-1]) for t, generation in enumerate(glider_in): for y, row in enumerate(generation): for x, cell in enumerate(row): search_pattern.grid[t][y][x] = cell for t in range(6,duration-1): for y in range(1,height-1): for x in range(1,width-1): search_pattern.grid[t][y][x] = "*" search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) print_message("Pattern created:\n" + search_pattern.make_string(pattern_output_format = "csv") + "\n", 3, indent = indent+1, verbosity = verbosity) print_message('Done\n', 3, indent = indent, verbosity = verbosity) return search_pattern.grid, search_pattern.ignore_transition def lwss_eater_search_pattern(width,height,digestion_time,symmetry="C1",indent = 0, verbosity = 0): print_message('Creating lwss search pattern...', 3, indent = indent, verbosity = verbosity) assert height % 2 == 1, "Height must be odd" lwss_in = [ [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["1","1","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["0","1","0","0","0","0","0"], ["0","1","0","0","0","0","0"], ["1","1","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["1","1","0","0","0","0","0"], ["0","1","1","0","0","0","0"], ["1","1","0","0","0","0","0"], ["1","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["1","1","1","0","0","0","0"], ["0","0","1","0","0","0","0"], ["0","0","1","0","0","0","0"], ["0","1","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["1","1","0","0","0","0","0"], ["1","1","1","0","0","0","0"], ["1","0","1","1","0","0","0"], ["0","1","1","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","1","0","0","0","0"], ["0","0","0","1","0","0","0"], ["0","0","0","1","0","0","0"], ["1","1","1","1","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","0","1","1","0","0","0"], ["1","1","0","1","1","0","0"], ["1","1","1","1","0","0","0"], ["0","1","1","0","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"], ["0","1","1","1","1","0","0"], ["1","0","0","0","1","0","0"], ["0","0","0","0","1","0","0"], ["1","0","0","1","0","0","0"], ["0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0"], ["0","0","1","1","0","0","0"], ["0","1","1","1","1","0","0"], ["0","1","1","0","1","1","0"], ["0","0","0","1","1","0","0"], ["0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0"]] ] in_time = len(lwss_in) width = width + 2 height = height + 2 duration = digestion_time + in_time grid = [[["0" for i in range(width)] for j in range(height)] for k in range(duration)] for y in range(1,height-1): for x in range(1,width-1): grid[-1][y][x] = "*" search_pattern = SearchPattern(grid) search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) for x in range(7): for y in range(height/2 - 3, height/2 + 4): search_pattern.grid[-1][y][x] = "0" search_pattern.force_symmetry(symmetry) for t, generation in enumerate(lwss_in): search_pattern.grid[t] = copy.deepcopy(search_pattern.grid[-1]) for t, generation in enumerate(lwss_in): for y, row in enumerate(generation): if y not in [0, len(generation) - 1]: search_pattern.ignore_transition[t][height/2 - 3 + y][0] = True for x, cell in enumerate(row): search_pattern.grid[t][height/2 - 3 + y][x] = cell for t in range(in_time,duration-1): for y in range(1,height-1): for x in range(1,width-1): search_pattern.grid[t][y][x] = "*" search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) print_message("Pattern created:\n" + search_pattern.make_string(pattern_output_format = "csv") + "\n", 3, indent = indent+1, verbosity = verbosity) print_message('Done\n', 3, indent = indent, verbosity = verbosity) return search_pattern.grid, search_pattern.ignore_transition def hwss_eater_search_pattern(width,height,digestion_time,symmetry="C1",indent = 0, verbosity = 0): print_message('Creating lwss search pattern...', 3, indent = indent, verbosity = verbosity) assert height % 2 == 1, "Height must be odd" hwss_in = [ [["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"]], [["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["1","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], 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["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"], ["0","0","0","0","0","0","0","0","0"]] ] in_time = len(hwss_in) width = width + 2 height = height + 2 duration = digestion_time + in_time grid = [[["0" for i in range(width)] for j in range(height)] for k in range(duration)] for y in range(1,height-1): for x in range(1,width-1): grid[-1][y][x] = "*" search_pattern = SearchPattern(grid) search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) for x in range(9): for y in range(height/2 - 4, height/2 + 5): search_pattern.grid[-1][y][x] = "0" search_pattern.force_symmetry(symmetry) for t, generation in enumerate(hwss_in): search_pattern.grid[t] = copy.deepcopy(search_pattern.grid[-1]) for t, generation in enumerate(hwss_in): for y, row in enumerate(generation): if y not in [0, len(generation) - 1]: search_pattern.ignore_transition[t][height/2 - 4 + y][0] = True for x, cell in enumerate(row): search_pattern.grid[t][height/2 - 4 + y][x] = cell for t in range(in_time,duration-1): for y in range(1,height-1): for x in range(1,width-1): search_pattern.grid[t][y][x] = "*" search_pattern.standardise_varaibles_names(indent = indent + 1, verbosity = verbosity) print_message("Pattern created:\n" + search_pattern.make_string(pattern_output_format = "csv") + "\n", 3, indent = indent+1, verbosity = verbosity) print_message('Done\n', 3, indent = indent, verbosity = verbosity) return search_pattern.grid, search_pattern.ignore_transition def stator_search_pattern(pattern, rule=None, background_grid=None, indent=0, verbosity=0): if rule == None: rule = LLS_rules.rule_from_rulestring(LLS_defaults.rulestring) if background_grid == None: ( background_grid, _ ) = LLS_formatting.parse_input_string( LLS_files.string_from_file( "backgrounds/" + LLS_defaults.background, ) ) width = len(pattern[0]) height = len(pattern) grid = [pattern] duration = 1 print_message('Creating oscillator...', 3, indent = indent, verbosity = verbosity) while True: print_message('Generation: ' + str(duration), 3, indent = indent + 1, verbosity = verbosity) grid.append([["0" for x in range(width)] for y in range(height)]) duration += 1 for x in range(width): for y in range(height): BS_letter = "S" if grid[-2][y][x] == "1" else "B" grid[-1][y][x] = rule[BS_letter + LLS_rules.transition_from_cells(neighbours_from_coordinates(grid,x,y,-1, background_grid = background_grid))] if grid[0] == grid[-1]: break number_of_variables = 0 for x in range(width): for y in range(height): if all(grid[t][y][x] == grid[0][y][x] for t in range(duration)): for t in range(duration): grid[t][y][x] = "stator_cell_" + str(number_of_variables) number_of_variables += 1 grid = [[["0" for x in range(width)]] + generation + [["0" for x in range(width)]] for generation in grid] grid = [[["0"] + row + ["0"] for row in generation] for generation in grid] print_message('Done\n', 3, indent = indent, verbosity = verbosity) return grid

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50e8cf525998f3838566d57c8a177c902eacb06a

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py

Python

core/variance_predictor.py

carankt/FastSpeech2-1

42c06e4fbdf741a0719154d1cb4617b7d3f15a5c

[ "Apache-2.0" ]

1

2021-12-08T09:07:09.000Z

core/variance_predictor.py

carankt/FastSpeech2-1

42c06e4fbdf741a0719154d1cb4617b7d3f15a5c

[ "Apache-2.0" ]

null

core/variance_predictor.py

carankt/FastSpeech2-1

42c06e4fbdf741a0719154d1cb4617b7d3f15a5c

[ "Apache-2.0" ]

null

import torch import torch.nn.functional as F from typing import Optional from core.modules import LayerNorm import pycwt as wavelet import numpy as np from sklearn import preprocessing class VariancePredictor(torch.nn.Module): def __init__( self, idim: int, n_layers: int = 2, n_chans: int = 256, out: int = 1, kernel_size: int = 3, dropout_rate: float = 0.5, offset: float = 1.0, ): super(VariancePredictor, self).__init__() self.offset = offset self.conv = torch.nn.ModuleList() for idx in range(n_layers): in_chans = idim if idx == 0 else n_chans self.conv += [ torch.nn.Sequential( torch.nn.Conv1d( in_chans, n_chans, kernel_size, stride=1, padding=(kernel_size - 1) // 2, ), torch.nn.ReLU(), LayerNorm(n_chans), torch.nn.Dropout(dropout_rate), ) ] self.linear = torch.nn.Linear(n_chans, out) def _forward( self, xs: torch.Tensor, is_inference: bool = False, is_log_output: bool = False, alpha: float = 1.0, ) -> torch.Tensor: xs = xs.transpose(1, -1) # (B, idim, Tmax) for f in self.conv: xs = f(xs) # (B, C, Tmax) # NOTE: calculate in log domain xs = self.linear(xs.transpose(1, -1)).squeeze(-1) # (B, Tmax) if is_inference and is_log_output: # # NOTE: calculate in linear domain xs = torch.clamp( torch.round(xs.exp() - self.offset), min=0 ).long() # avoid negative value xs = xs * alpha return xs def forward( self, xs: torch.Tensor, x_masks: Optional[torch.Tensor] = None ) -> torch.Tensor: """Calculate forward propagation. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: Tensor: Batch of predicted durations in log domain (B, Tmax). """ xs = self._forward(xs) if x_masks is not None: xs = xs.masked_fill(x_masks, 0.0) return xs def inference( self, xs: torch.Tensor, is_log_output: bool = False, alpha: float = 1.0 ) -> torch.Tensor: """Inference duration. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: LongTensor: Batch of predicted durations in linear domain (B, Tmax). """ return self._forward( xs, is_inference=True, is_log_output=is_log_output, alpha=alpha ) class EnergyPredictor(torch.nn.Module): def __init__( self, idim, n_layers=2, n_chans=256, kernel_size=3, dropout_rate=0.1, offset=1.0, min=0, max=0, n_bins=256, out = 10 ): """Initilize Energy predictor module. Args: idim (int): Input dimension. n_layers (int, optional): Number of convolutional layers. n_chans (int, optional): Number of channels of convolutional layers. kernel_size (int, optional): Kernel size of convolutional layers. dropout_rate (float, optional): Dropout rate. offset (float, optional): Offset value to avoid nan in log domain. """ super(EnergyPredictor, self).__init__() # self.bins = torch.linspace(min, max, n_bins - 1).cuda() self.register_buffer("energy_bins", torch.linspace(min, max, n_bins - 1)) self.predictor = VariancePredictor(idim) self.conv = torch.nn.ModuleList() for idx in range(n_layers): in_chans = idim if idx == 0 else n_chans self.conv += [ torch.nn.Sequential( torch.nn.Conv1d( in_chans, n_chans, kernel_size, stride=1, padding=(kernel_size - 1) // 2, ), torch.nn.ReLU(), LayerNorm(n_chans), torch.nn.Dropout(dropout_rate), ) ] self.spectrogram_out = torch.nn.Linear(n_chans, out) self.mean = torch.nn.Linear(n_chans, 1) self.std = torch.nn.Linear(n_chans, 1) self.out = out def forward(self, xs: torch.Tensor, olens: torch.Tensor, x_masks: torch.Tensor): """Calculate forward propagation. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: Tensor: Batch of predicted durations in log domain (B, Tmax). """ xs = xs.transpose(1, -1) # (B, idim, Tmax) for f in self.conv: xs = f(xs) # (B, C, Tmax) # NOTE: calculate in log domain xs = xs.transpose(1, -1) f0_spec = self.spectrogram_out(xs) # (B, Tmax, 10) if x_masks is not None: # print("olen:", olens) #f0_spec = f0_spec.transpose(1, -1) # print("F0 spec dimension:", f0_spec.shape) # print("x_masks dimension:", x_masks.shape) f0_spec = f0_spec.masked_fill(x_masks, 0.0) #f0_spec = f0_spec.transpose(1, -1) # print("F0 spec dimension:", f0_spec.shape) #xs = xs.transpose(1, -1) xs = xs.masked_fill(x_masks, 0.0) #xs = xs.transpose(1, -1) # print("xs dimension:", xs.shape) x_avg = xs.sum(dim=1).squeeze(1) # print(x_avg) # print("xs dim :", x_avg.shape) # print("olens ;", olens.shape) if olens is not None: x_avg = x_avg / olens.unsqueeze(1) # print(x_avg) f0_mean = self.mean(x_avg).squeeze(-1) f0_std = self.std(x_avg).squeeze(-1) # if x_masks is not None: # f0_spec = f0_spec.masked_fill(x_masks, 0.0) #print(f0_spec.shape, f0_mean.shape, f0_std.shape, "Energy Predictor Output") return f0_spec, f0_mean, f0_std def inference(self, xs: torch.Tensor, olens = None, alpha: float = 1.0): """Inference duration. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: LongTensor: Batch of predicted durations in linear domain (B, Tmax). """ f0_spec, f0_mean, f0_std = self.forward(xs, olens, x_masks=None) # (B, Tmax, 10) #print(f0_spec) f0_reconstructed = self.inverse(f0_spec, f0_mean, f0_std) #print(f0_reconstructed) return self.to_one_hot(f0_reconstructed) def to_one_hot(self, x): # e = de_norm_mean_std(e, hp.e_mean, hp.e_std) # For pytorch > = 1.6.0 quantize = torch.bucketize(x, self.energy_bins).to(device=x.device) # .cuda() return F.one_hot(quantize.long(), 256).float() def inverse(self, Wavelet_lf0, f0_mean, f0_std): mother = wavelet.MexicanHat() dt = 0.005 dj = 2 s0 = dt*2 J = self.out - 1 _, scales, _, _, _, _ = wavelet.cwt(np.ones([10]), dt, dj, s0, J, mother) #scales = np.array([0.01, 0.02, 0.04, 0.08, 0.16]) #np.arange(1,11) #print(Wavelet_lf0.shape) Wavelet_lf0 = Wavelet_lf0.squeeze(0).cpu().numpy() lf0_rec = np.zeros([Wavelet_lf0.shape[0], len(scales)]) for i in range(0,len(scales)): lf0_rec[:,i] = Wavelet_lf0[:,i]*((i+200+2.5)**(-2.5)) lf0_rec_sum = np.sum(lf0_rec,axis = 1) lf0_rec_sum_norm = preprocessing.scale(lf0_rec_sum) f0_reconstructed = (torch.Tensor(lf0_rec_sum_norm).cuda()*f0_std) + f0_mean f0_reconstructed = torch.exp(f0_reconstructed) #print(f0_reconstructed.shape) #print(f0_reconstructed.shape) return f0_reconstructed.reshape(1,-1) class PitchPredictor(torch.nn.Module): def __init__( self, idim, n_layers=2, n_chans=384, kernel_size=3, dropout_rate=0.1, offset=1.0, min=0, max=0, n_bins=256, out=10, ): """Initilize pitch predictor module. Args: idim (int): Input dimension. n_layers (int, optional): Number of convolutional layers. n_chans (int, optional): Number of channels of convolutional layers. kernel_size (int, optional): Kernel size of convolutional layers. dropout_rate (float, optional): Dropout rate. offset (float, optional): Offset value to avoid nan in log domain. """ super(PitchPredictor, self).__init__() # self.bins = torch.exp(torch.linspace(torch.log(torch.tensor(min)), torch.log(torch.tensor(max)), n_bins - 1)).cuda() self.register_buffer( "pitch_bins", torch.exp( torch.linspace( torch.log(torch.tensor(min)), torch.log(torch.tensor(max)), n_bins - 1, ) ), ) self.offset = offset self.conv = torch.nn.ModuleList() for idx in range(n_layers): in_chans = idim if idx == 0 else n_chans self.conv += [ torch.nn.Sequential( torch.nn.Conv1d( in_chans, n_chans, kernel_size, stride=1, padding=(kernel_size - 1) // 2, ), torch.nn.ReLU(), LayerNorm(n_chans), torch.nn.Dropout(dropout_rate), ) ] self.spectrogram_out = torch.nn.Linear(n_chans, out) self.mean = torch.nn.Linear(n_chans, 1) self.std = torch.nn.Linear(n_chans, 1) self.out = out def forward(self, xs: torch.Tensor, olens: torch.Tensor, x_masks: torch.Tensor): """Calculate forward propagation. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: Tensor: Batch of predicted durations in log domain (B, Tmax). """ xs = xs.transpose(1, -1) # (B, idim, Tmax) for f in self.conv: xs = f(xs) # (B, C, Tmax) # NOTE: calculate in log domain xs = xs.transpose(1, -1) f0_spec = self.spectrogram_out(xs) # (B, Tmax, 10) if x_masks is not None: # print("olen:", olens) #f0_spec = f0_spec.transpose(1, -1) # print("F0 spec dimension:", f0_spec.shape) # print("x_masks dimension:", x_masks.shape) f0_spec = f0_spec.masked_fill(x_masks, 0.0) #f0_spec = f0_spec.transpose(1, -1) # print("F0 spec dimension:", f0_spec.shape) #xs = xs.transpose(1, -1) xs = xs.masked_fill(x_masks, 0.0) #xs = xs.transpose(1, -1) # print("xs dimension:", xs.shape) x_avg = xs.sum(dim=1).squeeze(1) # print(x_avg) # print("xs dim :", x_avg.shape) # print("olens ;", olens.shape) if olens is not None: x_avg = x_avg / olens.unsqueeze(1) # print(x_avg) f0_mean = self.mean(x_avg).squeeze(-1) f0_std = self.std(x_avg).squeeze(-1) # if x_masks is not None: # f0_spec = f0_spec.masked_fill(x_masks, 0.0) #print(f0_spec.shape, f0_mean.shape, f0_std.shape, "Pitch Predictor Output") return f0_spec, f0_mean, f0_std def inference(self, xs: torch.Tensor, olens = None, alpha: float = 1.0): """Inference duration. Args: xs (Tensor): Batch of input sequences (B, Tmax, idim). x_masks (ByteTensor, optional): Batch of masks indicating padded part (B, Tmax). Returns: LongTensor: Batch of predicted durations in linear domain (B, Tmax). """ f0_spec, f0_mean, f0_std = self.forward(xs, olens, x_masks=None) # (B, Tmax, 10) #print(f0_spec) f0_reconstructed = self.inverse(f0_spec, f0_mean, f0_std) #print(f0_reconstructed) #f0_reconstructed = torch.from_numpy(np.load("/results/chkpts/LJ/Fastspeech2_V2/data/pitch/LJ001-0001.npy").reshape(1,-1)).cuda() #print(f0_reconstructed, "Pitch coef output") return self.to_one_hot(f0_reconstructed) def to_one_hot(self, x: torch.Tensor): # e = de_norm_mean_std(e, hp.e_mean, hp.e_std) # For pytorch > = 1.6.0 quantize = torch.bucketize(x, self.pitch_bins).to(device=x.device) # .cuda() return F.one_hot(quantize.long(), 256).float() def inverse(self, Wavelet_lf0, f0_mean, f0_std): mother = wavelet.MexicanHat() dt = 0.005 dj = 2 s0 = dt*2 J = self.out - 1 _, scales, _, _, _, _ = wavelet.cwt(np.ones([10]), dt, dj, s0, J, mother) #scales = np.array([0.01, 0.02, 0.04, 0.08, 0.16]) #np.arange(1,11) #print(Wavelet_lf0.shape) Wavelet_lf0 = Wavelet_lf0.squeeze(0).cpu().numpy() lf0_rec = np.zeros([Wavelet_lf0.shape[0], len(scales)]) for i in range(0,len(scales)): lf0_rec[:,i] = Wavelet_lf0[:,i]*((i+200+2.5)**(-2.5)) lf0_rec_sum = np.sum(lf0_rec,axis = 1) lf0_rec_sum_norm = preprocessing.scale(lf0_rec_sum) f0_reconstructed = (torch.Tensor(lf0_rec_sum_norm).cuda()*f0_std) + f0_mean f0_reconstructed = torch.exp(f0_reconstructed) #print(f0_reconstructed.shape) #print(f0_reconstructed.shape) return f0_reconstructed.reshape(1,-1) class PitchPredictorLoss(torch.nn.Module): """Loss function module for duration predictor. The loss value is Calculated in log domain to make it Gaussian. """ def __init__(self, offset=1.0): """Initilize duration predictor loss module. Args: offset (float, optional): Offset value to avoid nan in log domain. """ super(PitchPredictorLoss, self).__init__() self.criterion = torch.nn.MSELoss() self.offset = offset def forward(self, outputs, targets): """Calculate forward propagation. Args: outputs (Tensor): Batch of prediction durations in log domain (B, T) targets (LongTensor): Batch of groundtruth durations in linear domain (B, T) Returns: Tensor: Mean squared error loss value. Note: `outputs` is in log domain but `targets` is in linear domain. """ # NOTE: We convert the output in log domain low error value # print("Output :", outputs[0]) # print("Before Output :", targets[0]) # targets = torch.log(targets.float() + self.offset) # print("Before Output :", targets[0]) # outputs = torch.log(outputs.float() + self.offset) loss = self.criterion(outputs, targets) # print(loss) return loss class EnergyPredictorLoss(torch.nn.Module): """Loss function module for duration predictor. The loss value is Calculated in log domain to make it Gaussian. """ def __init__(self, offset=1.0): """Initilize duration predictor loss module. Args: offset (float, optional): Offset value to avoid nan in log domain. """ super(EnergyPredictorLoss, self).__init__() self.criterion = torch.nn.MSELoss() self.offset = offset def forward(self, outputs, targets): """Calculate forward propagation. Args: outputs (Tensor): Batch of prediction durations in log domain (B, T) targets (LongTensor): Batch of groundtruth durations in linear domain (B, T) Returns: Tensor: Mean squared error loss value. Note: `outputs` is in log domain but `targets` is in linear domain. """ # NOTE: outputs is in log domain while targets in linear # targets = torch.log(targets.float() + self.offset) loss = self.criterion(outputs, targets) return loss

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0

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0

1

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null

0

7

50f75c338e0bc24cd380ba90a26460b67bdadd3f

4,824

py

Python

function/set_ops.py

facebookresearch/task_bench

1a75797d635d2b2e79336b5c02af654f1bec7013

[ "CC0-1.0" ]

1

2022-03-20T22:09:25.000Z

function/set_ops.py

facebookresearch/task_bench

1a75797d635d2b2e79336b5c02af654f1bec7013

[ "CC0-1.0" ]

null

function/set_ops.py

facebookresearch/task_bench

1a75797d635d2b2e79336b5c02af654f1bec7013

[ "CC0-1.0" ]

null

# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. from function import Function, FUNCTION_REGISTRY, WordFunction class SetIntersect(WordFunction): """ Maps set -> set """ def __init__(self, fn_tree, inner_fns, **kwargs): super().__init__(fn_tree=fn_tree, inner_fns=inner_fns) assert len(self.inner_fns) <= 2 @classmethod def get_func_name(cls): return ['intersection'] def to_nl(self): inner_nls = [inner_fn.to_nl() for inner_fn in self.inner_fns] assert len(inner_nls) == 2 return f"{inner_nls[0]} and {inner_nls[1]}" def __call__(self, inputs: list=None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 2 return {'out': set(inputs[0]).intersection(set(inputs[1])), 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(fn_tree=fn_tree, inner_fns=inner_fns, **kwargs) class SetUnion(WordFunction): """ Maps set -> set """ def __init__(self, fn_tree, inner_fns, **kwargs): super().__init__(fn_tree=fn_tree, inner_fns=inner_fns) assert len(self.inner_fns) <= 2 @classmethod def get_func_name(cls): return ['union'] def to_nl(self): inner_nls = [inner_fn.to_nl() for inner_fn in self.inner_fns] assert len(inner_nls) == 2 return f"{inner_nls[0]} or {inner_nls[1]}" def __call__(self, inputs: list=None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 2 return {'out': set(inputs[0]).union(set(inputs[1])), 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(fn_tree=fn_tree, inner_fns=inner_fns, **kwargs) class SetComplement(WordFunction): """ Maps set -> set """ def __init__(self, fn_tree, inner_fns, **kwargs): super().__init__(fn_tree=fn_tree, inner_fns=inner_fns) self.inner_fns = inner_fns @classmethod def get_func_name(cls): return ['complement'] def __call__(self, inputs: list=None): breakpoint() inputs = self.compute_inner_fns(inputs) assert len(inputs) == 1 return {'out': (self.get_universe() - set(inputs[0])), 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(fn_tree=fn_tree, inner_fns=inner_fns, **kwargs) class Subset(Function): """ Maps [set, set] -> bool """ def __init__(self, inner_fns, **kwargs): self.inner_fns = inner_fns @classmethod def get_func_name(cls): return ['subset'] def __call__(self, inputs: list = None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 2 return {'out': {set(inputs[0]).issubset(set(inputs[1]))}, 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(inner_fns) class SetEquals(Function): """ Maps [set, set] -> bool """ def __init__(self, inner_fns, **kwargs): self.inner_fns = inner_fns @classmethod def get_func_name(cls): return ['eq'] def __call__(self, inputs: list = None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 2 return {'out': {set(inputs[0]) == set(inputs[1])}, 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(inner_fns) class IsIn(Function): """ Maps [element, set] -> bool """ def __init__(self, fn_tree, inner_fns, **kwargs): super().__init__(fn_tree=fn_tree, inner_fns=inner_fns) @classmethod def get_func_name(cls): return ['in'] def to_nl(self): inner_nls = [inner_fn.to_nl() for inner_fn in self.inner_fns] assert len(inner_nls) == 2 return f"{inner_nls[1]} include {inner_nls[0]}" def __call__(self, inputs: list = None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 2 assert len(inputs[0]) == 1 for el in inputs[0]: break return {'out': el in inputs[1], 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(fn_tree=fn_tree, inner_fns=inner_fns) class IsEmpty(Function): """ Maps set -> bool """ def __init__(self, inner_fns, **kwargs): self.inner_fns = inner_fns @classmethod def get_func_name(cls): return ['empty'] def __call__(self, inputs: list=None): inputs = self.compute_inner_fns(inputs) assert len(inputs) == 1 return {'out': len(inputs[0]) == 0, 'inner': inputs} @classmethod def build(cls, fn_tree, inner_fns, **kwargs): return cls(inner_fns)

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1

0

null

0

1

0

1

0

10

0faffdbb6ebebbe7b50afac21592165fe57f89f1

30,754

py

Python

google-datacatalog-qlik-connector/src/google/datacatalog_connectors/qlik/prepare/datacatalog_tag_template_factory.py

anugrah86/datacatalog-connectors-bi

58cc57e12632cbd1e237b3d6930e519333c51f4e

[ "Apache-2.0" ]

27

2020-04-27T21:55:49.000Z

2022-02-18T22:09:13.000Z

google-datacatalog-qlik-connector/src/google/datacatalog_connectors/qlik/prepare/datacatalog_tag_template_factory.py

anugrah86/datacatalog-connectors-bi

58cc57e12632cbd1e237b3d6930e519333c51f4e

[ "Apache-2.0" ]

36

2020-05-01T15:26:14.000Z

2022-03-26T00:09:19.000Z

google-datacatalog-qlik-connector/src/google/datacatalog_connectors/qlik/prepare/datacatalog_tag_template_factory.py

anugrah86/datacatalog-connectors-bi

58cc57e12632cbd1e237b3d6930e519333c51f4e

[ "Apache-2.0" ]

18

2020-04-30T22:14:09.000Z

2022-01-13T10:28:03.000Z

#!/usr/bin/python # # Copyright 2021 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from google.cloud import datacatalog from google.datacatalog_connectors.commons import prepare from google.datacatalog_connectors.qlik.prepare import \ constants, dynamic_properties_helper as dph class DataCatalogTagTemplateFactory(prepare.BaseTagTemplateFactory): __ASCII_CHARACTER_ENCODING = 'ASCII' __BOOL_TYPE = datacatalog.FieldType.PrimitiveType.BOOL __DOUBLE_TYPE = datacatalog.FieldType.PrimitiveType.DOUBLE __STRING_TYPE = datacatalog.FieldType.PrimitiveType.STRING __TIMESTAMP_TYPE = datacatalog.FieldType.PrimitiveType.TIMESTAMP def __init__(self, project_id, location_id): self.__project_id = project_id self.__location_id = location_id def make_tag_template_for_app(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_APP) tag_template.display_name = 'Qlik App Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=16) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_username', field_type=self.__STRING_TYPE, display_name='Owner username', order=15) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_name', field_type=self.__STRING_TYPE, display_name='Owner name', order=14) self._add_primitive_type_field(tag_template=tag_template, field_id='modified_by_username', field_type=self.__STRING_TYPE, display_name='Username who modified it', order=13) self._add_primitive_type_field(tag_template=tag_template, field_id='published', field_type=self.__BOOL_TYPE, display_name='Published', is_required=True, order=12) self._add_primitive_type_field(tag_template=tag_template, field_id='publish_time', field_type=self.__TIMESTAMP_TYPE, display_name='Publish time', order=11) self._add_primitive_type_field(tag_template=tag_template, field_id='last_reload_time', field_type=self.__TIMESTAMP_TYPE, display_name='Last reload time', order=10) self._add_primitive_type_field(tag_template=tag_template, field_id='stream_id', field_type=self.__STRING_TYPE, display_name='Stream Id', is_required=True, order=9) self._add_primitive_type_field(tag_template=tag_template, field_id='stream_name', field_type=self.__STRING_TYPE, display_name='Stream name', is_required=True, order=8) self._add_primitive_type_field( tag_template=tag_template, field_id='stream_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the Stream', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='file_size', field_type=self.__STRING_TYPE, display_name='File size', order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='thumbnail', field_type=self.__STRING_TYPE, display_name='Thumbnail', order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='saved_in_product_version', field_type=self.__STRING_TYPE, display_name='Saved in product version', order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='migration_hash', field_type=self.__STRING_TYPE, display_name='Migration hash', order=3) self._add_primitive_type_field(tag_template=tag_template, field_id='availability_status', field_type=self.__DOUBLE_TYPE, display_name='Availability status', order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_custom_property_definition(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_CUSTOM_PROPERTY_DEFINITION) tag_template.display_name = 'Qlik Custom Property Definition Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='modified_by_username', field_type=self.__STRING_TYPE, display_name='Username who modified it', order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='value_type', field_type=self.__STRING_TYPE, display_name='Value type', order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='choice_values', field_type=self.__STRING_TYPE, display_name='Choice values', order=3) self._add_primitive_type_field(tag_template=tag_template, field_id='object_types', field_type=self.__STRING_TYPE, display_name='Object types', order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_custom_property_value(self, definition_metadata, value): tag_template = datacatalog.TagTemplate() template_id = dph.DynamicPropertiesHelper\ .make_id_for_custom_property_value_tag_template( definition_metadata, value) tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=template_id) tag_template.display_name = dph.DynamicPropertiesHelper\ .make_display_name_for_custom_property_value_tag_template( definition_metadata, value) self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=9) self._add_primitive_type_field(tag_template=tag_template, field_id='created_date', field_type=self.__TIMESTAMP_TYPE, display_name='Created date', order=8) self._add_primitive_type_field(tag_template=tag_template, field_id='modified_date', field_type=self.__TIMESTAMP_TYPE, display_name='Modified date', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='modified_by_username', field_type=self.__STRING_TYPE, display_name='Username who modified it', order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='value', field_type=self.__STRING_TYPE, display_name='Value', is_required=True, order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='property_definition_id', field_type=self.__STRING_TYPE, display_name='Property Definition Id', is_required=True, order=4) # According to the Qlik Analytics Platform Architecture Team, there was # no way of searching assets by the Custom Property values using Qlik # when this feature was implemented (Dec, 2020), which means the # catalog search might be helpful to address such a use case. Hence the # 'definition_' part was supressed from this Tag Field Id to turn seach # queries more intuitive, e.g. tag:property_name:<PROPERTY-NAME>. self._add_primitive_type_field(tag_template=tag_template, field_id='property_name', field_type=self.__STRING_TYPE, display_name='Property Definition name', is_required=True, order=3) self._add_primitive_type_field( tag_template=tag_template, field_id='property_definition_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the Property Definition', is_required=True, order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_dimension(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_DIMENSION) tag_template.display_name = 'Qlik Dimension Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=9) self._add_enum_type_field( tag_template=tag_template, field_id='grouping', values=[ constants.DIMENSION_GROUPING_SINGLE_TAG_FIELD, constants.DIMENSION_GROUPING_DRILL_DOWN_TAG_FIELD ], display_name='Grouping', order=8) self._add_primitive_type_field(tag_template=tag_template, field_id='fields', field_type=self.__STRING_TYPE, display_name='Fields', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='field_labels', field_type=self.__STRING_TYPE, display_name='Field labels', order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='tags', field_type=self.__STRING_TYPE, display_name='Qlik tags', order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='app_id', field_type=self.__STRING_TYPE, display_name='App Id', is_required=True, order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='app_name', field_type=self.__STRING_TYPE, display_name='App name', is_required=True, order=3) self._add_primitive_type_field( tag_template=tag_template, field_id='app_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the App', is_required=True, order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_measure(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_MEASURE) tag_template.display_name = 'Qlik Measure Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', order=9) self._add_primitive_type_field(tag_template=tag_template, field_id='expression', field_type=self.__STRING_TYPE, display_name='Expression', order=8) self._add_primitive_type_field(tag_template=tag_template, field_id='label_expression', field_type=self.__STRING_TYPE, display_name='Label expression', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='is_custom_formatted', field_type=self.__BOOL_TYPE, display_name='Is custom formatted', order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='tags', field_type=self.__STRING_TYPE, display_name='Qlik tags', order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='app_id', field_type=self.__STRING_TYPE, display_name='App Id', is_required=True, order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='app_name', field_type=self.__STRING_TYPE, display_name='App name', is_required=True, order=3) self._add_primitive_type_field( tag_template=tag_template, field_id='app_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the App', is_required=True, order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_sheet(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_SHEET) tag_template.display_name = 'Qlik Sheet Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=12) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_username', field_type=self.__STRING_TYPE, display_name='Owner username', order=11) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_name', field_type=self.__STRING_TYPE, display_name='Owner name', order=10) self._add_primitive_type_field(tag_template=tag_template, field_id='published', field_type=self.__BOOL_TYPE, display_name='Published', order=9) self._add_primitive_type_field(tag_template=tag_template, field_id='publish_time', field_type=self.__TIMESTAMP_TYPE, display_name='Publish time', order=8) self._add_primitive_type_field(tag_template=tag_template, field_id='approved', field_type=self.__BOOL_TYPE, display_name='Approved', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='app_id', field_type=self.__STRING_TYPE, display_name='App Id', is_required=True, order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='app_name', field_type=self.__STRING_TYPE, display_name='App name', is_required=True, order=5) self._add_primitive_type_field( tag_template=tag_template, field_id='app_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the App', is_required=True, order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='source_object', field_type=self.__STRING_TYPE, display_name='Source object', order=3) self._add_primitive_type_field(tag_template=tag_template, field_id='draft_object', field_type=self.__STRING_TYPE, display_name='Draft object', order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_stream(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_STREAM) tag_template.display_name = 'Qlik Stream Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_username', field_type=self.__STRING_TYPE, display_name='Owner username', order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='owner_name', field_type=self.__STRING_TYPE, display_name='Owner name', order=3) self._add_primitive_type_field(tag_template=tag_template, field_id='modified_by_username', field_type=self.__STRING_TYPE, display_name='Username who modified it', order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template def make_tag_template_for_visualization(self): tag_template = datacatalog.TagTemplate() tag_template.name = datacatalog.DataCatalogClient.tag_template_path( project=self.__project_id, location=self.__location_id, tag_template=constants.TAG_TEMPLATE_ID_VISUALIZATION) tag_template.display_name = 'Qlik Visualization Metadata' self._add_primitive_type_field(tag_template=tag_template, field_id='id', field_type=self.__STRING_TYPE, display_name='Unique Id', is_required=True, order=10) self._add_primitive_type_field(tag_template=tag_template, field_id='title', field_type=self.__STRING_TYPE, display_name='Title', order=9) self._add_primitive_type_field(tag_template=tag_template, field_id='subtitle', field_type=self.__STRING_TYPE, display_name='Subtitle', order=8) self._add_primitive_type_field(tag_template=tag_template, field_id='footnote', field_type=self.__STRING_TYPE, display_name='Footnote', order=7) self._add_primitive_type_field(tag_template=tag_template, field_id='type', field_type=self.__STRING_TYPE, display_name='Type', order=6) self._add_primitive_type_field(tag_template=tag_template, field_id='tags', field_type=self.__STRING_TYPE, display_name='Qlik tags', order=5) self._add_primitive_type_field(tag_template=tag_template, field_id='app_id', field_type=self.__STRING_TYPE, display_name='App Id', is_required=True, order=4) self._add_primitive_type_field(tag_template=tag_template, field_id='app_name', field_type=self.__STRING_TYPE, display_name='App name', is_required=True, order=3) self._add_primitive_type_field( tag_template=tag_template, field_id='app_entry', field_type=self.__STRING_TYPE, display_name='Data Catalog Entry for the App', is_required=True, order=2) self._add_primitive_type_field(tag_template=tag_template, field_id='site_url', field_type=self.__STRING_TYPE, display_name='Qlik Sense site url', is_required=True, order=1) return tag_template

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7

0fcf1a0bafc2912fd8f2447451e119fd9ee771d9

201

py

Python

model/model_helper/__init__.py

IDNatte/mygamelist

6b40f56b84e2246793e26da9aecc800b6698e1ba

[ "CNRI-Python", "RSA-MD" ]

null

model/model_helper/__init__.py

IDNatte/mygamelist

6b40f56b84e2246793e26da9aecc800b6698e1ba

[ "CNRI-Python", "RSA-MD" ]

null

model/model_helper/__init__.py

IDNatte/mygamelist

6b40f56b84e2246793e26da9aecc800b6698e1ba

[ "CNRI-Python", "RSA-MD" ]

null

""" Model Helper function """ import random import string def random_id_generator(): return ''.join((random.choice(string.ascii_letters + string.digits + string.punctuation) for x in range(50)))

20.1

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Python

tests/image_window_dataset_test.py

Min-Sheng/NiftyNet

13ff54018d3ea282b94af94b6bce7bd67c0d7cc5

[ "Apache-2.0" ]

2

2019-03-25T18:50:47.000Z

2019-10-10T01:45:02.000Z

tests/image_window_dataset_test.py

Min-Sheng/NiftyNet

13ff54018d3ea282b94af94b6bce7bd67c0d7cc5

[ "Apache-2.0" ]

null

tests/image_window_dataset_test.py

Min-Sheng/NiftyNet

13ff54018d3ea282b94af94b6bce7bd67c0d7cc5

[ "Apache-2.0" ]

1

2018-11-11T09:49:38.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import, print_function import os import numpy as np import tensorflow as tf from niftynet.io.image_reader import ImageReader from niftynet.contrib.dataset_sampler.image_window_dataset import \ ImageWindowDataset IMAGE_PATH_2D_1 = os.path.join('.', 'example_volumes', 'gan_test_data') IMAGE_PATH_3D = os.path.join('.', 'testing_data') def get_2d_reader(): data_param = {'mr': {'path_to_search': IMAGE_PATH_2D_1}} reader = ImageReader().initialise(data_param) return reader def get_3d_reader(): data_param = {'mr': {'path_to_search': IMAGE_PATH_3D, 'filename_contains': 'FLAIR', 'interp_order': 1}} reader = ImageReader().initialise(data_param) return reader class ImageWindowDataset_2D_Test(tf.test.TestCase): def assert_window(self, window): self.assertEqual(window['mr'].shape[1:3], (120, 160)) self.assertEqual(window['mr_location'][0, 1:].tolist(), [0, 0, 0, 120, 160, 1]) self.assertEqual(window['mr'].dtype, np.float32) self.assertEqual(window['mr_location'].dtype, np.int32) def assert_tf_window(self, sampler): with self.test_session() as sess: sampler.run_threads(sess) window = sess.run(sampler.pop_batch_op()) self.assert_window(window) def test_simple(self): sampler = ImageWindowDataset(reader=get_2d_reader()) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_batch_size(self): # batch size doesn't change the numpy interface sampler = ImageWindowDataset(reader=get_2d_reader(), batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_window_size(self): sampler = ImageWindowDataset(reader=get_2d_reader(), window_sizes=(0, 0, 0), batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_window_size_dict(self): sampler = ImageWindowDataset(reader=get_2d_reader(), window_sizes={'mr': (0, 0, 0)}, batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) # sampler layer_op()'s output shape is not checked #def test_wrong_window_size_dict(self): # sampler = ImageWindowDataset(reader=get_2d_reader(), # batch_size=2, # window_sizes=(3,3,0)) # self.assert_tf_window(sampler) def test_windows_per_image(self): with self.assertRaisesRegexp(AssertionError, ''): sampler = ImageWindowDataset(reader=get_2d_reader(), batch_size=2, windows_per_image=2) self.assert_window(sampler()) def test_epoch(self): reader = get_2d_reader() batch_size = 3 sampler = ImageWindowDataset(reader=reader, batch_size=batch_size, epoch=1) with self.test_session() as sess: sampler.run_threads(sess) iters = 0 try: for _ in range(400): window = sess.run(sampler.pop_batch_op()) iters = iters + 1 except tf.errors.OutOfRangeError: pass # batch size 2, 40 images in total self.assertEqual(np.ceil(reader.num_subjects/np.float(batch_size)), iters) class ImageWindowDataset_3D_Test(tf.test.TestCase): def assert_window(self, window): self.assertEqual(window['mr'].shape[1:4], (256, 168, 256)) self.assertEqual(window['mr_location'][0, 1:].tolist(), [0, 0, 0, 256, 168, 256]) self.assertEqual(window['mr'].dtype, np.float32) self.assertEqual(window['mr_location'].dtype, np.int32) def assert_tf_window(self, sampler): with self.test_session() as sess: sampler.run_threads(sess) window = sess.run(sampler.pop_batch_op()) self.assert_window(window) def test_simple(self): sampler = ImageWindowDataset(reader=get_3d_reader()) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_batch_size(self): # batch size doesn't change the numpy interface sampler = ImageWindowDataset(reader=get_3d_reader(), batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_window_size(self): sampler = ImageWindowDataset(reader=get_3d_reader(), window_sizes=(0, 0, 0), batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_window_size_dict(self): sampler = ImageWindowDataset(reader=get_3d_reader(), window_sizes={'mr': (0, 0, 0)}, batch_size=2) self.assert_tf_window(sampler) self.assert_window(sampler()) def test_windows_per_image(self): with self.assertRaisesRegexp(AssertionError, ''): sampler = ImageWindowDataset(reader=get_3d_reader(), batch_size=2, windows_per_image=2) self.assert_window(sampler()) def test_epoch(self): reader = get_3d_reader() batch_size = 3 sampler = ImageWindowDataset(reader=reader, batch_size=batch_size, epoch=1) with self.test_session() as sess: sampler.run_threads(sess) iters = 0 try: for _ in range(400): window = sess.run(sampler.pop_batch_op()) iters = iters + 1 except tf.errors.OutOfRangeError: pass # batch size 2, 40 images in total self.assertEqual(np.ceil(reader.num_subjects/np.float(batch_size)), iters) if __name__ == "__main__": tf.test.main()

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68,578

py

Python

benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/SystemIPC/cmp_lu.cont/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/SystemIPC/cmp_lu.cont/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/SystemIPC/cmp_lu.cont/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

power = {'BUSES': {'Area': 1.33155, 'Bus/Area': 1.33155, 'Bus/Gate Leakage': 0.00662954, 'Bus/Peak Dynamic': 0.0, 'Bus/Runtime Dynamic': 0.0, 'Bus/Subthreshold Leakage': 0.0691322, 'Bus/Subthreshold Leakage with power gating': 0.0259246, 'Gate Leakage': 0.00662954, 'Peak Dynamic': 0.0, 'Runtime Dynamic': 0.0, 'Subthreshold Leakage': 0.0691322, 'Subthreshold Leakage with power gating': 0.0259246}, 'Core': [{'Area': 32.6082, 'Execution Unit/Area': 8.2042, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.125201, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.301027, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.668056, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.122718, 'Execution Unit/Instruction Scheduler/Area': 2.17927, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.826149, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 1.43059, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.820485, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 3.07723, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.714191, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 7.51418, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.12621, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0299486, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.263767, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.221488, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.389977, 'Execution Unit/Register Files/Runtime Dynamic': 0.251437, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.671668, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.94412, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155, 'Execution Unit/Runtime Dynamic': 5.97919, 'Execution Unit/Subthreshold Leakage': 1.83518, 'Execution Unit/Subthreshold Leakage with power gating': 0.709678, 'Gate Leakage': 0.372997, 'Instruction Fetch Unit/Area': 5.86007, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.0044099, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.0044099, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.0038114, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.00145926, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00318169, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.0158129, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.04334, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0590479, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.212922, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.43323, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.709301, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.723179, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 8.96874, 'Instruction Fetch Unit/Runtime Dynamic': 1.70455, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932587, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.0297012, 'L2/Runtime Dynamic': 0.0105028, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80969, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 7.68206, 'Load Store Unit/Data Cache/Runtime Dynamic': 3.10802, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0351387, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.208509, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.208509, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 8.67069, 'Load Store Unit/Runtime Dynamic': 4.34482, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.514148, 'Load Store Unit/StoreQ/Runtime Dynamic': 1.0283, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591622, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283406, 'Memory Management Unit/Area': 0.434579, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729, 'Memory Management Unit/Dtlb/Peak Dynamic': 0.182473, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.182918, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00813591, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.399995, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.116281, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.873954, 'Memory Management Unit/Runtime Dynamic': 0.299199, 'Memory Management Unit/Subthreshold Leakage': 0.0769113, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462, 'Peak Dynamic': 30.619, 'Renaming Unit/Area': 0.369768, 'Renaming Unit/FP Front End RAT/Area': 0.168486, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.440319, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0437281, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925, 'Renaming Unit/Free List/Area': 0.0414755, 'Renaming Unit/Free List/Gate Leakage': 4.15911e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0401324, 'Renaming Unit/Free List/Runtime Dynamic': 0.0475432, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987, 'Renaming Unit/Gate Leakage': 0.00863632, 'Renaming Unit/Int Front End RAT/Area': 0.114751, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.426935, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781, 'Renaming Unit/Peak Dynamic': 4.56169, 'Renaming Unit/Runtime Dynamic': 0.914797, 'Renaming Unit/Subthreshold Leakage': 0.070483, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779, 'Runtime Dynamic': 13.2531, 'Subthreshold Leakage': 6.21877, 'Subthreshold Leakage with power gating': 2.58311}, {'Area': 32.0201, 'Execution Unit/Area': 7.68434, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0447887, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.237867, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex 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Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.41547, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.209715, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.882768, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.257849, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 4.75113, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 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'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0155237, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0768131, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 4.88597, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 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'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0422097, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.235842, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.226056, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433, 'Execution Unit/Instruction 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'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.196754, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.82821, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.241735, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power 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'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.131885, 'Execution Unit/Register Files/Runtime Dynamic': 0.0851014, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.198429, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.57589, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543, 'Execution Unit/Runtime Dynamic': 2.13042, 'Execution Unit/Subthreshold Leakage': 1.79543, 'Execution Unit/Subthreshold Leakage with power gating': 0.688821, 'Gate Leakage': 0.368936, 'Instruction Fetch Unit/Area': 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with power gating': 0.0276461, 'Runtime Dynamic': 4.52606, 'Subthreshold Leakage': 6.16288, 'Subthreshold Leakage with power gating': 2.55328}, {'Area': 32.0201, 'Execution Unit/Area': 7.68434, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0357518, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.23077, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.192371, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.205958, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.332202, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.167685, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.705845, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate 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RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0758828, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0638892, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.112226, 'Execution Unit/Register Files/Runtime Dynamic': 0.072528, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.168804, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.490721, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543, 'Execution Unit/Runtime Dynamic': 1.90524, 'Execution Unit/Subthreshold Leakage': 1.79543, 'Execution Unit/Subthreshold Leakage with power gating': 0.688821, 'Gate Leakage': 0.368936, 'Instruction Fetch Unit/Area': 5.85939, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00136891, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00136891, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00121647, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000484127, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000917774, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00487206, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0122619, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0614183, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.90673, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.202575, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.208604, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 6.31485, 'Instruction Fetch Unit/Runtime Dynamic': 0.489732, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932286, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.0097511, 'L2/Runtime Dynamic': 0.0039694, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80901, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 3.08159, 'Load Store Unit/Data Cache/Runtime Dynamic': 0.89106, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0350888, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.0596731, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.059673, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 3.36338, 'Load Store Unit/Runtime Dynamic': 1.24502, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.147144, 'Load Store Unit/StoreQ/Runtime Dynamic': 0.294287, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591321, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283293, 'Memory Management Unit/Area': 0.4339, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729, 'Memory Management Unit/Dtlb/Peak Dynamic': 0.0522218, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0523678, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00808595, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.242906, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.0332097, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.488723, 'Memory Management Unit/Runtime Dynamic': 0.0855776, 'Memory Management Unit/Subthreshold Leakage': 0.0766103, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333, 'Peak Dynamic': 18.3317, 'Renaming Unit/Area': 0.303608, 'Renaming Unit/FP Front End RAT/Area': 0.131045, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.0956014, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885, 'Renaming Unit/Free List/Area': 0.0340654, 'Renaming Unit/Free List/Gate Leakage': 2.5481e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0306032, 'Renaming Unit/Free List/Runtime Dynamic': 0.0104557, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064, 'Renaming Unit/Gate Leakage': 0.00708398, 'Renaming Unit/Int Front End RAT/Area': 0.0941223, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.104383, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228, 'Renaming Unit/Peak Dynamic': 3.58947, 'Renaming Unit/Runtime Dynamic': 0.21044, 'Renaming Unit/Subthreshold Leakage': 0.0552466, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461, 'Runtime Dynamic': 3.93998, 'Subthreshold Leakage': 6.16288, 'Subthreshold Leakage with power gating': 2.55328}], 'DRAM': {'Area': 0, 'Gate Leakage': 0, 'Peak Dynamic': 1.7706167804022201, 'Runtime Dynamic': 1.7706167804022201, 'Subthreshold Leakage': 4.252, 'Subthreshold Leakage with power gating': 4.252}, 'L3': [{'Area': 61.9075, 'Gate Leakage': 0.0484137, 'Peak Dynamic': 0.0935869, 'Runtime Dynamic': 0.0534378, 'Subthreshold Leakage': 6.80085, 'Subthreshold Leakage with power gating': 3.32364}], 'Processor': {'Area': 191.908, 'Gate Leakage': 1.53485, 'Peak Dynamic': 88.8271, 'Peak Power': 121.939, 'Runtime Dynamic': 26.5534, 'Subthreshold Leakage': 31.5774, 'Subthreshold Leakage with power gating': 13.9484, 'Total Cores/Area': 128.669, 'Total Cores/Gate Leakage': 1.4798, 'Total Cores/Peak Dynamic': 88.7335, 'Total Cores/Runtime Dynamic': 26.4999, 'Total Cores/Subthreshold Leakage': 24.7074, 'Total Cores/Subthreshold Leakage with power gating': 10.2429, 'Total L3s/Area': 61.9075, 'Total L3s/Gate Leakage': 0.0484137, 'Total L3s/Peak Dynamic': 0.0935869, 'Total L3s/Runtime Dynamic': 0.0534378, 'Total L3s/Subthreshold Leakage': 6.80085, 'Total L3s/Subthreshold Leakage with power gating': 3.32364, 'Total Leakage': 33.1122, 'Total NoCs/Area': 1.33155, 'Total NoCs/Gate Leakage': 0.00662954, 'Total NoCs/Peak Dynamic': 0.0, 'Total NoCs/Runtime Dynamic': 0.0, 'Total NoCs/Subthreshold Leakage': 0.0691322, 'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}

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ba2564d20d7ae3305a076ea6bfb661e958289202

149

py

Python

models/read_vectors/read_vectors.py

zankner/DNC

2596fa3a1ee9bf0a9f160f3f953639e70bb25fe7

[ "MIT" ]

3

2020-03-20T17:46:33.000Z

2020-03-23T16:48:59.000Z

models/read_vectors/read_vectors.py

zankner/DNC

2596fa3a1ee9bf0a9f160f3f953639e70bb25fe7

[ "MIT" ]

null

models/read_vectors/read_vectors.py

zankner/DNC

2596fa3a1ee9bf0a9f160f3f953639e70bb25fe7

[ "MIT" ]

1

2020-03-20T17:55:55.000Z

import tensorflow as tf def read_vectors(memory_matrix, read_weightings): return tf.linalg.matmul(tf.transpose(memory_matrix), read_weightings)

29.8

73

0.818792

21

149

5.571429

0.666667

0.205128

0.273504

0.444444

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null

0

1

0

1

0

9

d75a5189b7e9ca381e0b5d39df53d5d8e0e58c64

36

py

Python

devo/common/loadenv/__init__.py

imposeren/python-sdk

c772da98664a31d86207f86bc005ecb2128e74d7

[ "MIT" ]

18

2018-09-25T11:47:28.000Z

2021-12-14T20:28:39.000Z

devo/common/loadenv/__init__.py

imposeren/python-sdk

c772da98664a31d86207f86bc005ecb2128e74d7

[ "MIT" ]

57

2018-11-08T12:40:30.000Z

2022-03-31T13:01:19.000Z

devo/common/loadenv/__init__.py

imposeren/python-sdk

c772da98664a31d86207f86bc005ecb2128e74d7

[ "MIT" ]

34

2018-11-05T16:09:15.000Z

2022-03-08T10:51:34.000Z

from .load_env import load_env_file

18

35

0.861111

7

36

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0.875

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1

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1

0

7

d7685a296b789b8c5ff51a1c315c62da012bf676

23,791

py

Python

OpenGLCffi/FFI/_glxffi.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/FFI/_glxffi.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/FFI/_glxffi.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

# auto-generated file import _cffi_backend from xcffib._ffi import ffi as _ffi0 ffi = _cffi_backend.FFI('FFI._glxffi', _version = 0x2601, _types = 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d76b2b2dc7116687ad579b6f901b3ec73ffee13a

40,452

py

Python

swagger_client/apis/accommodation_api.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

[ "Apache-2.0" ]

null

swagger_client/apis/accommodation_api.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

[ "Apache-2.0" ]

null

swagger_client/apis/accommodation_api.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

[ "Apache-2.0" ]

null

# coding: utf-8 """ Scubawhere API Documentation This is the documentation for scubawhere's RMS API. This API is only to be used by authorized parties with valid auth tokens. [Learn about scubawhere](http://www.scubawhere.com) to become an authorized consumer of our API OpenAPI spec version: 1.0.0 Contact: bryan@scubawhere.com Generated by: https://github.com/swagger-api/swagger-codegen.git Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class AccommodationApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def add_accommodation(self, name, capacity, base_prices, **kwargs): """ Create an accommodation This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.add_accommodation(name, capacity, base_prices, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: Name of the type of accommodation (required) :param int capacity: Number of beds in the accommodation (required) :param int base_prices: Price of the accommodation and the dates of when the price is applicable (required) :param str description: Description of the accommodation :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.add_accommodation_with_http_info(name, capacity, base_prices, **kwargs) else: (data) = self.add_accommodation_with_http_info(name, capacity, base_prices, **kwargs) return data def add_accommodation_with_http_info(self, name, capacity, base_prices, **kwargs): """ Create an accommodation This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.add_accommodation_with_http_info(name, capacity, base_prices, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: Name of the type of accommodation (required) :param int capacity: Number of beds in the accommodation (required) :param int base_prices: Price of the accommodation and the dates of when the price is applicable (required) :param str description: Description of the accommodation :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ all_params = ['name', 'capacity', 'base_prices', 'description'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method add_accommodation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `add_accommodation`") # verify the required parameter 'capacity' is set if ('capacity' not in params) or (params['capacity'] is None): raise ValueError("Missing the required parameter `capacity` when calling `add_accommodation`") # verify the required parameter 'base_prices' is set if ('base_prices' not in params) or (params['base_prices'] is None): raise ValueError("Missing the required parameter `base_prices` when calling `add_accommodation`") resource_path = '/accommodation/add'.replace('{format}', 'json') path_params = {} query_params = {} if 'name' in params: query_params['name'] = params['name'] if 'description' in params: query_params['description'] = params['description'] if 'capacity' in params: query_params['capacity'] = params['capacity'] if 'base_prices' in params: query_params['base_prices'] = params['base_prices'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse200', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def delete_accommodation(self, body, **kwargs): """ Delete an accommodation by ID This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_accommodation(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int body: ID of the accommodation (required) :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.delete_accommodation_with_http_info(body, **kwargs) else: (data) = self.delete_accommodation_with_http_info(body, **kwargs) return data def delete_accommodation_with_http_info(self, body, **kwargs): """ Delete an accommodation by ID This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_accommodation_with_http_info(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int body: ID of the accommodation (required) :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ all_params = ['body'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_accommodation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `delete_accommodation`") resource_path = '/accommodation/delete'.replace('{format}', 'json') path_params = {} query_params = {} if 'body' in params: query_params['body'] = params['body'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse200', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def edit_agent(self, id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, **kwargs): """ Create a new agent This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.edit_agent(id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int id: (required) :param int name: (required) :param str branch_name: (required) :param str branch_address: (required) :param str branch_phone: (required) :param str branch_email: (required) :param float commission: (required) :param str terms: (required) :param str website: :param str billing_address: :param str billing_phone: :param str billing_email: :return: InlineResponse2004 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.edit_agent_with_http_info(id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, **kwargs) else: (data) = self.edit_agent_with_http_info(id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, **kwargs) return data def edit_agent_with_http_info(self, id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, **kwargs): """ Create a new agent This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.edit_agent_with_http_info(id, name, branch_name, branch_address, branch_phone, branch_email, commission, terms, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int id: (required) :param int name: (required) :param str branch_name: (required) :param str branch_address: (required) :param str branch_phone: (required) :param str branch_email: (required) :param float commission: (required) :param str terms: (required) :param str website: :param str billing_address: :param str billing_phone: :param str billing_email: :return: InlineResponse2004 If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'name', 'branch_name', 'branch_address', 'branch_phone', 'branch_email', 'commission', 'terms', 'website', 'billing_address', 'billing_phone', 'billing_email'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method edit_agent" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `edit_agent`") # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `edit_agent`") # verify the required parameter 'branch_name' is set if ('branch_name' not in params) or (params['branch_name'] is None): raise ValueError("Missing the required parameter `branch_name` when calling `edit_agent`") # verify the required parameter 'branch_address' is set if ('branch_address' not in params) or (params['branch_address'] is None): raise ValueError("Missing the required parameter `branch_address` when calling `edit_agent`") # verify the required parameter 'branch_phone' is set if ('branch_phone' not in params) or (params['branch_phone'] is None): raise ValueError("Missing the required parameter `branch_phone` when calling `edit_agent`") # verify the required parameter 'branch_email' is set if ('branch_email' not in params) or (params['branch_email'] is None): raise ValueError("Missing the required parameter `branch_email` when calling `edit_agent`") # verify the required parameter 'commission' is set if ('commission' not in params) or (params['commission'] is None): raise ValueError("Missing the required parameter `commission` when calling `edit_agent`") # verify the required parameter 'terms' is set if ('terms' not in params) or (params['terms'] is None): raise ValueError("Missing the required parameter `terms` when calling `edit_agent`") resource_path = '/agent/edit'.replace('{format}', 'json') path_params = {} query_params = {} if 'id' in params: query_params['id'] = params['id'] if 'name' in params: query_params['name'] = params['name'] if 'website' in params: query_params['website'] = params['website'] if 'branch_name' in params: query_params['branch_name'] = params['branch_name'] if 'branch_address' in params: query_params['branch_address'] = params['branch_address'] if 'branch_phone' in params: query_params['branch_phone'] = params['branch_phone'] if 'branch_email' in params: query_params['branch_email'] = params['branch_email'] if 'billing_address' in params: query_params['billing_address'] = params['billing_address'] if 'billing_phone' in params: query_params['billing_phone'] = params['billing_phone'] if 'billing_email' in params: query_params['billing_email'] = params['billing_email'] if 'commission' in params: query_params['commission'] = params['commission'] if 'terms' in params: query_params['terms'] = params['terms'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse2004', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def filter_accommodation(self, **kwargs): """ Get all the accommodations matching a filter Get all the accommodations and their bookings between certain dates and / or an accommodation id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.filter_accommodation(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param date before: The date for the upper boundary of the dates :param date after: The date for the lower boundary of the dates :param int accommodation_id: ID Accommodation to filter by :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.filter_accommodation_with_http_info(**kwargs) else: (data) = self.filter_accommodation_with_http_info(**kwargs) return data def filter_accommodation_with_http_info(self, **kwargs): """ Get all the accommodations matching a filter Get all the accommodations and their bookings between certain dates and / or an accommodation id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.filter_accommodation_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param date before: The date for the upper boundary of the dates :param date after: The date for the lower boundary of the dates :param int accommodation_id: ID Accommodation to filter by :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ all_params = ['before', 'after', 'accommodation_id'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method filter_accommodation" % key ) params[key] = val del params['kwargs'] resource_path = '/accommodation/filter'.replace('{format}', 'json') path_params = {} query_params = {} if 'before' in params: query_params['before'] = params['before'] if 'after' in params: query_params['after'] = params['after'] if 'accommodation_id' in params: query_params['accommodation_id'] = params['accommodation_id'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse200', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def find_accommodation(self, id, **kwargs): """ Retrieve an accommodation by ID This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.find_accommodation(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param list[int] id: ID of the accommodation to be retrieved (required) :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.find_accommodation_with_http_info(id, **kwargs) else: (data) = self.find_accommodation_with_http_info(id, **kwargs) return data def find_accommodation_with_http_info(self, id, **kwargs): """ Retrieve an accommodation by ID This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.find_accommodation_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param list[int] id: ID of the accommodation to be retrieved (required) :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method find_accommodation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `find_accommodation`") resource_path = '/accommodation'.replace('{format}', 'json') path_params = {} query_params = {} if 'id' in params: query_params['id'] = params['id'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse200', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def get_all_accommodations(self, **kwargs): """ Retrieve all accommodation This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_accommodations(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[Accommodation] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_all_accommodations_with_http_info(**kwargs) else: (data) = self.get_all_accommodations_with_http_info(**kwargs) return data def get_all_accommodations_with_http_info(self, **kwargs): """ Retrieve all accommodation This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_accommodations_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[Accommodation] If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_accommodations" % key ) params[key] = val del params['kwargs'] resource_path = '/accommodations/all'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Accommodation]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def get_all_with_trashed_accommodations(self, **kwargs): """ Retrieve all accommodation including any deleted models This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_with_trashed_accommodations(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[Accommodation] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_all_with_trashed_accommodations_with_http_info(**kwargs) else: (data) = self.get_all_with_trashed_accommodations_with_http_info(**kwargs) return data def get_all_with_trashed_accommodations_with_http_info(self, **kwargs): """ Retrieve all accommodation including any deleted models This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_with_trashed_accommodations_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[Accommodation] If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_with_trashed_accommodations" % key ) params[key] = val del params['kwargs'] resource_path = '/accommodations/all-with-trashed'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Accommodation]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def update_accommodation(self, id, **kwargs): """ Update an Accommodation Updates the accommodation by id using the specified fields This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_accommodation(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int id: ID of the Accommodation to be updated (required) :param str name: Name of the Accommodation :param int capacity: Number of rooms the accommodation holds :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.update_accommodation_with_http_info(id, **kwargs) else: (data) = self.update_accommodation_with_http_info(id, **kwargs) return data def update_accommodation_with_http_info(self, id, **kwargs): """ Update an Accommodation Updates the accommodation by id using the specified fields This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_accommodation_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param int id: ID of the Accommodation to be updated (required) :param str name: Name of the Accommodation :param int capacity: Number of rooms the accommodation holds :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'name', 'capacity'] all_params.append('callback') all_params.append('_return_http_data_only') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_accommodation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `update_accommodation`") resource_path = '/accommodation/edit'.replace('{format}', 'json') path_params = {} query_params = {} if 'id' in params: query_params['id'] = params['id'] if 'name' in params: query_params['name'] = params['name'] if 'capacity' in params: query_params['capacity'] = params['capacity'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InlineResponse200', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'))

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0.025461

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null

0

1

0

1

0

null

0

7

ad3ac30b8104022dc104da85fefbec495973bac1

133

py

Python

gmpack/__init__.py

odakan/gmpack

7d57be190784955cd90b55c4878edf12dabf9e83

[ "MIT" ]

null

gmpack/__init__.py

odakan/gmpack

7d57be190784955cd90b55c4878edf12dabf9e83

[ "MIT" ]

null

gmpack/__init__.py

odakan/gmpack

7d57be190784955cd90b55c4878edf12dabf9e83

[ "MIT" ]

null

from gmpack.Rp_Spectra import * from gmpack.Plot_Spectra import * from gmpack.Flatten_Record import * from gmpack.F_Spectra import *

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8

ad668919d0466cd06513420076e380158dac6298

11,186

py

Python

somaticseq/utilities/dockered_pipelines/somatic_mutations/VarDict.py

bioinform/somaticseq

71f058dcdfea78ec056aa46f96a40cc737cc559f

[ "BSD-2-Clause" ]

159

2015-07-26T15:14:44.000Z

2022-03-31T03:29:25.000Z

somaticseq/utilities/dockered_pipelines/somatic_mutations/VarDict.py

lethalfang/somaticseq

e6f5b1c6b98b324d418407154392778164215a65

[ "BSD-2-Clause" ]

77

2016-06-12T21:44:43.000Z

2022-03-31T19:33:49.000Z

somaticseq/utilities/dockered_pipelines/somatic_mutations/VarDict.py

lethalfang/somaticseq

e6f5b1c6b98b324d418407154392778164215a65

[ "BSD-2-Clause" ]

64

2015-10-26T01:34:32.000Z

2022-03-14T14:43:08.000Z

import sys, argparse, os, re import subprocess from datetime import datetime import somaticseq.utilities.dockered_pipelines.container_option as container from somaticseq._version import __version__ as VERSION ts = re.sub(r'[:-]', '.', datetime.now().isoformat() ) DEFAULT_PARAMS = {'vardict_image' : 'lethalfang/vardictjava:1.7.0', 'MEM' : '8G', 'threads' : 1, 'normal_bam' : None, 'tumor_bam' : None, 'genome_reference' : None, 'inclusion_region' : None, 'output_directory' : os.curdir, 'outfile' : 'VarDict.vcf', 'action' : 'echo', 'vardict_arguments' : '', 'extra_docker_options' : '', 'script' : 'vardict.{}.cmd'.format(ts), 'min_MQ' : 1, 'minimum_VAF' : 0.05, 'process_bed' : True, } def tumor_normal(input_parameters, tech='docker' ): for param_i in DEFAULT_PARAMS: if param_i not in input_parameters: input_parameters[param_i] = DEFAULT_PARAMS[param_i] # The following are required: assert os.path.exists( input_parameters['normal_bam'] ) assert os.path.exists( input_parameters['tumor_bam'] ) assert os.path.exists( input_parameters['genome_reference'] ) logdir = os.path.join( input_parameters['output_directory'], 'logs' ) outfile = os.path.join( logdir, input_parameters['script'] ) all_paths = [] for path_i in input_parameters['normal_bam'], input_parameters['tumor_bam'], input_parameters['genome_reference'], input_parameters['output_directory'], input_parameters['inclusion_region']: if path_i: all_paths.append( path_i ) container_line, fileDict = container.container_params( input_parameters['vardict_image'], tech=tech, files=all_paths, extra_args=input_parameters['extra_docker_options'] ) minVAF = input_parameters['minimum_VAF'] total_bases = 0 num_lines = 0 if input_parameters['inclusion_region']: bed_file = input_parameters['inclusion_region'] with open(bed_file) as bed: line_i = bed.readline().rstrip() while line_i.startswith('track'): line_i = bed.readline().rstrip() while line_i: item = line_i.rstrip().split('\t') total_bases = total_bases + int(item[2]) - int(item[1]) num_lines += 1 line_i = bed.readline().rstrip() else: fai_file = input_parameters['genome_reference'] + '.fai' bed_file = os.path.join(input_parameters['output_directory'], 'genome.bed') with open(fai_file) as fai, open(bed_file, 'w') as wgs_bed: for line_i in fai: item = line_i.split('\t') total_bases += int( item[1] ) num_lines += 1 wgs_bed.write( '{}\t{}\t{}\n'.format(item[0], '0', item[1]) ) # However the "bed_file" is defined here, create a dockered line and mount dictionary for it: bed_split_line, bedDict = container.container_params( 'lethalfang/somaticseq:{}'.format(VERSION), tech, (bed_file, input_parameters['output_directory']) ) # Mounted paths for all the input files and output directory: mounted_genome_reference = fileDict[ input_parameters['genome_reference'] ]['mount_path'] mounted_tumor_bam = fileDict[ input_parameters['tumor_bam'] ]['mount_path'] mounted_normal_bam = fileDict[ input_parameters['normal_bam'] ]['mount_path'] mounted_outdir = fileDict[ input_parameters['output_directory'] ]['mount_path'] mounted_bed = bedDict[ bed_file ]['mount_path'] with open(outfile, 'w') as out: out.write( "#!/bin/bash\n\n" ) out.write(f'#$ -o {logdir}\n' ) out.write(f'#$ -e {logdir}\n' ) out.write( '#$ -S /bin/bash\n' ) out.write( '#$ -l h_vmem={}\n'.format( input_parameters['MEM'] ) ) out.write( 'set -e\n\n' ) out.write( 'echo -e "Start at `date +"%Y/%m/%d %H:%M:%S"`" 1>&2\n\n' ) # Decide if Bed file needs to be "split" such that each line has a small enough region if input_parameters['process_bed'] or total_bases/num_lines > 50000: out.write(f'{bed_split_line} \\\n' ) out.write( '/opt/somaticseq/somaticseq/utilities/split_mergedBed.py \\\n' ) out.write( '-infile {} -outfile {}/split_regions.bed\n\n'.format(mounted_bed, bedDict[input_parameters['output_directory']]['mount_path']) ) bed_file = '{}/split_regions.bed'.format( mounted_outdir ) out.write(f'{container_line} bash -c \\\n' ) out.write( '"/opt/VarDict-1.7.0/bin/VarDict \\\n' ) if input_parameters['vardict_arguments']: out.write( '{} \\\n'.format(input_parameters['vardict_arguments']) ) out.write( '-G {} \\\n'.format( mounted_genome_reference ) ) out.write( '-f {} -h \\\n'.format( minVAF ) ) out.write( '-b \'{}|{}\' \\\n'.format(mounted_tumor_bam, mounted_normal_bam) ) out.write( '-Q 1 -c 1 -S 2 -E 3 -g 4 {} \\\n'.format(bed_file) ) out.write( '> {}/vardict.var"\n\n'.format(mounted_outdir) ) out.write( '\n' ) out.write(f'{container_line} \\\n' ) out.write( 'bash -c "cat {}/vardict.var | awk \'NR!=1\' | /opt/VarDict/testsomatic.R | /opt/VarDict/var2vcf_paired.pl -N \'TUMOR|NORMAL\' -f {} \\\n'.format(mounted_outdir, minVAF ) ) out.write( '> {}/{}"\n\n'.format(mounted_outdir, input_parameters['outfile']) ) out.write( '\necho -e "Done at `date +"%Y/%m/%d %H:%M:%S"`" 1>&2\n' ) # "Run" the script that was generated command_line = '{} {}'.format( input_parameters['action'], outfile ) returnCode = subprocess.call( command_line, shell=True ) return outfile def tumor_only(input_parameters, tech='docker' ): for param_i in DEFAULT_PARAMS: if param_i not in input_parameters: input_parameters[param_i] = DEFAULT_PARAMS[param_i] # The following are required: assert os.path.exists( input_parameters['bam'] ) assert os.path.exists( input_parameters['genome_reference'] ) logdir = os.path.join( input_parameters['output_directory'], 'logs' ) outfile = os.path.join( logdir, input_parameters['script'] ) all_paths = [] for path_i in input_parameters['bam'], input_parameters['genome_reference'], input_parameters['output_directory'], input_parameters['inclusion_region']: if path_i: all_paths.append( path_i ) container_line, fileDict = container.container_params( input_parameters['vardict_image'], tech=tech, files=all_paths, extra_args=input_parameters['extra_docker_options'] ) minVAF = input_parameters['minimum_VAF'] total_bases = 0 num_lines = 0 if input_parameters['inclusion_region']: bed_file = input_parameters['inclusion_region'] with open(bed_file) as bed: line_i = bed.readline().rstrip() while line_i.startswith('track'): line_i = bed.readline().rstrip() while line_i: item = line_i.rstrip().split('\t') total_bases = total_bases + int(item[2]) - int(item[1]) num_lines += 1 line_i = bed.readline().rstrip() else: fai_file = input_parameters['genome_reference'] + '.fai' bed_file = os.path.join(input_parameters['output_directory'], 'genome.bed') with open(fai_file) as fai, open(bed_file, 'w') as wgs_bed: for line_i in fai: item = line_i.split('\t') total_bases += int( item[1] ) num_lines += 1 wgs_bed.write( '{}\t{}\t{}\n'.format(item[0], '0', item[1]) ) # However the "bed_file" is defined here, create a dockered line and mount dictionary for it: bed_split_line, bedDict = container.container_params( 'lethalfang/somaticseq:{}'.format(VERSION), tech, (bed_file, input_parameters['output_directory']) ) # Mounted paths for all the input files and output directory: mounted_genome_reference = fileDict[ input_parameters['genome_reference'] ]['mount_path'] mounted_tumor_bam = fileDict[ input_parameters['bam'] ]['mount_path'] mounted_outdir = fileDict[ input_parameters['output_directory'] ]['mount_path'] mounted_bed = bedDict[ bed_file ]['mount_path'] with open(outfile, 'w') as out: out.write( "#!/bin/bash\n\n" ) out.write(f'#$ -o {logdir}\n' ) out.write(f'#$ -e {logdir}\n' ) out.write( '#$ -S /bin/bash\n' ) out.write( '#$ -l h_vmem={}\n'.format( input_parameters['MEM'] ) ) out.write( 'set -e\n\n' ) out.write( 'echo -e "Start at `date +"%Y/%m/%d %H:%M:%S"`" 1>&2\n\n' ) # Decide if Bed file needs to be "split" such that each line has a small enough region if input_parameters['process_bed'] or total_bases/num_lines > 50000: out.write(f'{bed_split_line} \\\n' ) out.write( '/opt/somaticseq/somaticseq/utilities/split_mergedBed.py \\\n' ) out.write( '-infile {} -outfile {}/split_regions.bed\n\n'.format(mounted_bed, bedDict[input_parameters['output_directory']]['mount_path']) ) bed_file = '{}/split_regions.bed'.format( mounted_outdir ) out.write(f'{container_line} bash -c \\\n' ) out.write( '"/opt/VarDict-1.7.0/bin/VarDict \\\n' ) if input_parameters['vardict_arguments']: out.write( '{} \\\n'.format(input_parameters['vardict_arguments']) ) out.write( '-G {} \\\n'.format( mounted_genome_reference ) ) out.write( '-f {} -h \\\n'.format( minVAF ) ) out.write( '-b \'{}\' \\\n'.format(mounted_tumor_bam) ) out.write( '-Q 1 -c 1 -S 2 -E 3 -g 4 {} \\\n'.format(bed_file) ) out.write( '> {}/vardict.var"\n\n'.format(mounted_outdir) ) out.write(f'{container_line} \\\n' ) out.write( 'bash -c "cat {}/vardict.var | awk \'NR!=1\' | /opt/VarDict/teststrandbias.R | /opt/VarDict/var2vcf_valid.pl -N \'TUMOR\' -f {} \\\n'.format(mounted_outdir, minVAF ) ) out.write( '> {}/{}"\n\n'.format(mounted_outdir, input_parameters['outfile']) ) out.write( '\necho -e "Done at `date +"%Y/%m/%d %H:%M:%S"`" 1>&2\n' ) # "Run" the script that was generated command_line = '{} {}'.format( input_parameters['action'], outfile ) returnCode = subprocess.call( command_line, shell=True ) return outfile

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7

ada030ca64b2dfa74610511f19c39635a53f5378

2,828

py

Python

tests/services/admin_test.py

lsst/jwt_authorizer

76b984c809ad10843f2cd6f543e88ee1002bdb96

[ "MIT" ]

null

tests/services/admin_test.py

lsst/jwt_authorizer

76b984c809ad10843f2cd6f543e88ee1002bdb96

[ "MIT" ]

5

2019-06-18T17:28:52.000Z

2020-04-20T22:15:54.000Z

tests/services/admin_test.py

lsst/gafaelfawr

a9dd91c7770e194d609f64fee6fd955a27231bd6

[ "MIT" ]

1

2019-06-25T16:04:57.000Z

"""Tests for the service that handles token administrators.""" from __future__ import annotations import pytest from gafaelfawr.exceptions import PermissionDeniedError from gafaelfawr.factory import Factory from gafaelfawr.models.admin import Admin @pytest.mark.asyncio async def test_add(factory: Factory) -> None: admin_service = factory.create_admin_service() async with factory.session.begin(): assert await admin_service.get_admins() == [Admin(username="admin")] await admin_service.add_admin( "example", actor="admin", ip_address="192.168.0.1" ) async with factory.session.begin(): assert await admin_service.get_admins() == [ Admin(username="admin"), Admin(username="example"), ] assert await admin_service.is_admin("example") assert not await admin_service.is_admin("foo") async with factory.session.begin(): with pytest.raises(PermissionDeniedError): await admin_service.add_admin( "foo", actor="bar", ip_address="127.0.0.1" ) async with factory.session.begin(): await admin_service.add_admin( "foo", actor="<bootstrap>", ip_address="127.0.0.1" ) async with factory.session.begin(): assert await admin_service.is_admin("foo") assert not await admin_service.is_admin("<bootstrap>") @pytest.mark.asyncio async def test_delete(factory: Factory) -> None: admin_service = factory.create_admin_service() async with factory.session.begin(): assert await admin_service.get_admins() == [Admin(username="admin")] async with factory.session.begin(): with pytest.raises(PermissionDeniedError): await admin_service.delete_admin( "admin", actor="admin", ip_address="127.0.0.1" ) async with factory.session.begin(): await admin_service.add_admin( "example", actor="admin", ip_address="127.0.0.1" ) async with factory.session.begin(): await admin_service.delete_admin( "admin", actor="admin", ip_address="127.0.0.1" ) async with factory.session.begin(): assert await admin_service.is_admin("example") assert not await admin_service.is_admin("admin") assert await admin_service.get_admins() == [Admin(username="example")] async with factory.session.begin(): await admin_service.add_admin( "other", actor="example", ip_address="127.0.0.1" ) async with factory.session.begin(): await admin_service.delete_admin( "other", actor="<bootstrap>", ip_address="127.0.0.1" ) async with factory.session.begin(): assert await admin_service.get_admins() == [Admin(username="example")]

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a8f1eb55cd06ad9ccf0bfbde01210e56f0d49e97

8,718

py

Python

tests/test_resource_token.py

andraune/Run4IT_BackEnd

a481427a0d1189a1f08c42e7ac1b452af6bbfc8d

[ "MIT" ]

1

2022-03-29T06:11:20.000Z

tests/test_resource_token.py

andraune/run4it_backend

a481427a0d1189a1f08c42e7ac1b452af6bbfc8d

[ "MIT" ]

null

tests/test_resource_token.py

andraune/run4it_backend

a481427a0d1189a1f08c42e7ac1b452af6bbfc8d

[ "MIT" ]

null

import pytest import datetime as dt from run4it.api.token.model import TokenRegistry from run4it.api.token.resource import Token from .helpers import ( get_response_json, register_and_login_confirmed_user, register_and_login_user_with_unfresh_token, get_authorization_header) @pytest.mark.usefixtures('db') class TestTokenResource: def test_content_type_is_json(self, api, client): url = api.url_for(Token, token_id=1) response = client.get(url) assert(response.headers["Content-Type"] == 'application/json') def test_get_token_not_logged_in(self, api, client): url = api.url_for(Token, token_id=1) response = client.get(url) response_json = get_response_json(response.data) assert(response.status_code == 401) assert(response_json["errors"]["auth"] is not None) def test_get_token_logged_in(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=1) response = client.get(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 200) assert("jti" not in response_json) assert(response_json["id"] == 1) assert(response_json["tokenType"] in ("access", "refresh")) assert(response_json["username"] == "tokenreader") assert(response_json["revoked"] == False) assert(response_json["expires"] is not None) def test_get_token_with_unfresh_token(self, api, client): unfresh_token = register_and_login_user_with_unfresh_token(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=3) response = client.get(url, headers=get_authorization_header(unfresh_token)) response_json = get_response_json(response.data) assert(response.status_code == 200) def test_get_other_user_token(self, api, client): new_token = TokenRegistry('12345', 'access', 'another_user', False, dt.datetime.now() + dt.timedelta(hours=1)) new_token.save() token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=new_token.id) response = client.get(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 403) assert(response_json["errors"]["token"] is not None) def test_request_nonexisting_token(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=999) response = client.get(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 404) assert(response_json["errors"]["token"] is not None) def test_delete_token_not_logged_in(self, api, client): url = api.url_for(Token, token_id=2) response = client.delete(url) response_json = get_response_json(response.data) assert(response.status_code == 401) assert(response_json["errors"]["auth"] is not None) def test_delete_token_logged_in(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=2) response = client.delete(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 200) assert(response_json["messages"]["token"] is not None) assert(TokenRegistry.get_by_id(1) is not None) assert(TokenRegistry.get_by_id(2) is None) # should have been deleted def test_delete_token_with_unfresh_token(self, api, client): unfresh_token = register_and_login_user_with_unfresh_token(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=2) response = client.delete(url, headers=get_authorization_header(unfresh_token)) response_json = get_response_json(response.data) assert(response.status_code == 401) assert(response_json["errors"]["auth"] is not None) def test_delete_other_user_token(self, api, client): new_token = TokenRegistry('12345', 'access', 'another_user', False, dt.datetime.now() + dt.timedelta(hours=1)) new_token.save() token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=new_token.id) response = client.delete(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 403) assert(response_json["errors"]["token"] is not None) def test_delete_nonexisting_token(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=999) response = client.delete(url, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 404) assert(response_json["errors"]["token"] is not None) def test_update_token_not_logged_in(self, api, client): url = api.url_for(Token, token_id=2) response = client.put(url) response_json = get_response_json(response.data) assert(response.status_code == 401) assert(response_json["errors"]["auth"] is not None) def test_update_token_revoke(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=2) response = client.put(url, data={'revoked' : 'True'}, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 200) assert(response_json["revoked"] == True) def test_update_token_unrevoke(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") update_token = TokenRegistry.get_by_id(2) update_token.revoked = True url = api.url_for(Token, token_id=2) response = client.put(url, data={'revoked' : 'False'}, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 200) assert(response_json["revoked"] == False) def test_update_token_actually_saved(self, api, client): update_token = TokenRegistry('jti', 'access', 'tokenreader', False, dt.datetime(2001, 1, 2, 12, 11, 10, 9)) update_token.save() token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=update_token.id) response = client.put(url, data={'revoked':'True','jti':'newjti','tokenType':'refresh','username':'newuser','expires':str(dt.datetime(2002, 2, 3, 16, 15, 14, 13))}, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(update_token.jti == 'jti') assert(update_token.token_type == 'access') assert(update_token.username == 'tokenreader') assert(update_token.revoked == True) assert(update_token.expires == dt.datetime(2001, 1, 2, 12, 11, 10, 9)) def test_update_token_with_unfresh_token(self, api, client): unfresh_token = register_and_login_user_with_unfresh_token(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=2) response = client.put(url, data={'revoked' : 'True'}, headers=get_authorization_header(unfresh_token)) response_json = get_response_json(response.data) assert(response.status_code == 401) assert(response_json["errors"]["auth"] is not None) def test_update_other_user_token(self, api, client): new_token = TokenRegistry('12345', 'access', 'another_user', False, dt.datetime.now() + dt.timedelta(hours=1)) new_token.save() token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=new_token.id) response = client.put(url, data={'revoked' : 'True'}, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 403) assert(response_json["errors"]["token"] is not None) def test_update_nonexisting_token(self, api, client): token,_ = register_and_login_confirmed_user(api, client, "tokenreader", "token@reader.com", "passwd") url = api.url_for(Token, token_id=999) response = client.put(url, data={'revoked' : 'True'}, headers=get_authorization_header(token)) response_json = get_response_json(response.data) assert(response.status_code == 404) assert(response_json["errors"]["token"] is not None) def test_post_token_not_supported(self, api, client): url = api.url_for(Token, token_id=1) response = client.post(url) assert(response.status_code == 405) # not allowed

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207

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0.820464

0.806555

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0.123377

false

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0

null

0

1

0

null

0

1

0

7

d103e9ab2331e1527c962428d6a8839a13359a86

14,585

py

Python

playtime/lesson02_99bottles.py

govex/python-lessons

e692f48b6db008a45df0b941dee1e580f5a6c800

[ "MIT" ]

425

2015-01-13T03:19:10.000Z

2022-03-13T00:34:44.000Z

playtime/lesson02_99bottles.py

Supercodero/python-lessons

38409c318e7a62d30b2ffd68f8a7a5a5ec00778d

[ "MIT" ]

null

playtime/lesson02_99bottles.py

Supercodero/python-lessons

38409c318e7a62d30b2ffd68f8a7a5a5ec00778d

[ "MIT" ]

178

2015-01-08T05:01:05.000Z

2021-12-02T00:56:58.000Z

# Difficulty Level: Beginner # Can you make Python print out the song for 99 bottles of beer on the wall? # Note: You can use range() in three different ways # First: # range(5) will give you a list containing [0, 1, 2, 3, 4] # In this case, range assumes you want to start counting at 0, and the parameter you give is the number to stop *just* short of. # Second: # range(5, 10) will give you a list containing [5, 6, 7, 8, 9] # In this case, the two parameters you give to range() are the number to start at and the number to stop *just* short of. # Helpful mnemonic: range(start, stop) # Third: # range(5, 15, 3) will give you a list containing [5, 8, 11, 14] # In this case, the three parameters you give to range() are the number to start at, the number to stop *just* short of, and the number to increment each time by. # Note that normally, the number to increment each time by is assumed to be 1. (In other words, you add 1 each time through.) # That's why it goes [0, 1, 2, 3, 4] unless you specify that third parameter, called the step. # Helpful mnemonic: range(start, stop, step) # Using range() and a loop, print out the song. Your output should look like this: # 99 bottles of beer on the wall, 99 bottles of beer ... # If one of those bottles should happen to fall, 98 bottles of beer on the wall # 98 bottles of beer on the wall, 98 bottles of beer ... # If one of those bottles should happen to fall, 97 bottles of beer on the wall # 97 bottles of beer on the wall, 97 bottles of beer ... # If one of those bottles should happen to fall, 96 bottles of beer on the wall # 96 bottles of beer on the wall, 96 bottles of beer ... # If one of those bottles should happen to fall, 95 bottles of beer on the wall # 95 bottles of beer on the wall, 95 bottles of beer ... # If one of those bottles should happen to fall, 94 bottles of beer on the wall # 94 bottles of beer on the wall, 94 bottles of beer ... # If one of those bottles should happen to fall, 93 bottles of beer on the wall # 93 bottles of beer on the wall, 93 bottles of beer ... # If one of those bottles should happen to fall, 92 bottles of beer on the wall # 92 bottles of beer on the wall, 92 bottles of beer ... # If one of those bottles should happen to fall, 91 bottles of beer on the wall # 91 bottles of beer on the wall, 91 bottles of beer ... # If one of those bottles should happen to fall, 90 bottles of beer on the wall # 90 bottles of beer on the wall, 90 bottles of beer ... # If one of those bottles should happen to fall, 89 bottles of beer on the wall # 89 bottles of beer on the wall, 89 bottles of beer ... # If one of those bottles should happen to fall, 88 bottles of beer on the wall # 88 bottles of beer on the wall, 88 bottles of beer ... # If one of those bottles should happen to fall, 87 bottles of beer on the wall # 87 bottles of beer on the wall, 87 bottles of beer ... # If one of those bottles should happen to fall, 86 bottles of beer on the wall # 86 bottles of beer on the wall, 86 bottles of beer ... # If one of those bottles should happen to fall, 85 bottles of beer on the wall # 85 bottles of beer on the wall, 85 bottles of beer ... # If one of those bottles should happen to fall, 84 bottles of beer on the wall # 84 bottles of beer on the wall, 84 bottles of beer ... # If one of those bottles should happen to fall, 83 bottles of beer on the wall # 83 bottles of beer on the wall, 83 bottles of beer ... # If one of those bottles should happen to fall, 82 bottles of beer on the wall # 82 bottles of beer on the wall, 82 bottles of beer ... # If one of those bottles should happen to fall, 81 bottles of beer on the wall # 81 bottles of beer on the wall, 81 bottles of beer ... # If one of those bottles should happen to fall, 80 bottles of beer on the wall # 80 bottles of beer on the wall, 80 bottles of beer ... # If one of those bottles should happen to fall, 79 bottles of beer on the wall # 79 bottles of beer on the wall, 79 bottles of beer ... # If one of those bottles should happen to fall, 78 bottles of beer on the wall # 78 bottles of beer on the wall, 78 bottles of beer ... # If one of those bottles should happen to fall, 77 bottles of beer on the wall # 77 bottles of beer on the wall, 77 bottles of beer ... # If one of those bottles should happen to fall, 76 bottles of beer on the wall # 76 bottles of beer on the wall, 76 bottles of beer ... # If one of those bottles should happen to fall, 75 bottles of beer on the wall # 75 bottles of beer on the wall, 75 bottles of beer ... # If one of those bottles should happen to fall, 74 bottles of beer on the wall # 74 bottles of beer on the wall, 74 bottles of beer ... # If one of those bottles should happen to fall, 73 bottles of beer on the wall # 73 bottles of beer on the wall, 73 bottles of beer ... # If one of those bottles should happen to fall, 72 bottles of beer on the wall # 72 bottles of beer on the wall, 72 bottles of beer ... # If one of those bottles should happen to fall, 71 bottles of beer on the wall # 71 bottles of beer on the wall, 71 bottles of beer ... # If one of those bottles should happen to fall, 70 bottles of beer on the wall # 70 bottles of beer on the wall, 70 bottles of beer ... # If one of those bottles should happen to fall, 69 bottles of beer on the wall # 69 bottles of beer on the wall, 69 bottles of beer ... # If one of those bottles should happen to fall, 68 bottles of beer on the wall # 68 bottles of beer on the wall, 68 bottles of beer ... # If one of those bottles should happen to fall, 67 bottles of beer on the wall # 67 bottles of beer on the wall, 67 bottles of beer ... # If one of those bottles should happen to fall, 66 bottles of beer on the wall # 66 bottles of beer on the wall, 66 bottles of beer ... # If one of those bottles should happen to fall, 65 bottles of beer on the wall # 65 bottles of beer on the wall, 65 bottles of beer ... # If one of those bottles should happen to fall, 64 bottles of beer on the wall # 64 bottles of beer on the wall, 64 bottles of beer ... # If one of those bottles should happen to fall, 63 bottles of beer on the wall # 63 bottles of beer on the wall, 63 bottles of beer ... # If one of those bottles should happen to fall, 62 bottles of beer on the wall # 62 bottles of beer on the wall, 62 bottles of beer ... # If one of those bottles should happen to fall, 61 bottles of beer on the wall # 61 bottles of beer on the wall, 61 bottles of beer ... # If one of those bottles should happen to fall, 60 bottles of beer on the wall # 60 bottles of beer on the wall, 60 bottles of beer ... # If one of those bottles should happen to fall, 59 bottles of beer on the wall # 59 bottles of beer on the wall, 59 bottles of beer ... # If one of those bottles should happen to fall, 58 bottles of beer on the wall # 58 bottles of beer on the wall, 58 bottles of beer ... # If one of those bottles should happen to fall, 57 bottles of beer on the wall # 57 bottles of beer on the wall, 57 bottles of beer ... # If one of those bottles should happen to fall, 56 bottles of beer on the wall # 56 bottles of beer on the wall, 56 bottles of beer ... # If one of those bottles should happen to fall, 55 bottles of beer on the wall # 55 bottles of beer on the wall, 55 bottles of beer ... # If one of those bottles should happen to fall, 54 bottles of beer on the wall # 54 bottles of beer on the wall, 54 bottles of beer ... # If one of those bottles should happen to fall, 53 bottles of beer on the wall # 53 bottles of beer on the wall, 53 bottles of beer ... # If one of those bottles should happen to fall, 52 bottles of beer on the wall # 52 bottles of beer on the wall, 52 bottles of beer ... # If one of those bottles should happen to fall, 51 bottles of beer on the wall # 51 bottles of beer on the wall, 51 bottles of beer ... # If one of those bottles should happen to fall, 50 bottles of beer on the wall # 50 bottles of beer on the wall, 50 bottles of beer ... # If one of those bottles should happen to fall, 49 bottles of beer on the wall # 49 bottles of beer on the wall, 49 bottles of beer ... # If one of those bottles should happen to fall, 48 bottles of beer on the wall # 48 bottles of beer on the wall, 48 bottles of beer ... # If one of those bottles should happen to fall, 47 bottles of beer on the wall # 47 bottles of beer on the wall, 47 bottles of beer ... # If one of those bottles should happen to fall, 46 bottles of beer on the wall # 46 bottles of beer on the wall, 46 bottles of beer ... # If one of those bottles should happen to fall, 45 bottles of beer on the wall # 45 bottles of beer on the wall, 45 bottles of beer ... # If one of those bottles should happen to fall, 44 bottles of beer on the wall # 44 bottles of beer on the wall, 44 bottles of beer ... # If one of those bottles should happen to fall, 43 bottles of beer on the wall # 43 bottles of beer on the wall, 43 bottles of beer ... # If one of those bottles should happen to fall, 42 bottles of beer on the wall # 42 bottles of beer on the wall, 42 bottles of beer ... # If one of those bottles should happen to fall, 41 bottles of beer on the wall # 41 bottles of beer on the wall, 41 bottles of beer ... # If one of those bottles should happen to fall, 40 bottles of beer on the wall # 40 bottles of beer on the wall, 40 bottles of beer ... # If one of those bottles should happen to fall, 39 bottles of beer on the wall # 39 bottles of beer on the wall, 39 bottles of beer ... # If one of those bottles should happen to fall, 38 bottles of beer on the wall # 38 bottles of beer on the wall, 38 bottles of beer ... # If one of those bottles should happen to fall, 37 bottles of beer on the wall # 37 bottles of beer on the wall, 37 bottles of beer ... # If one of those bottles should happen to fall, 36 bottles of beer on the wall # 36 bottles of beer on the wall, 36 bottles of beer ... # If one of those bottles should happen to fall, 35 bottles of beer on the wall # 35 bottles of beer on the wall, 35 bottles of beer ... # If one of those bottles should happen to fall, 34 bottles of beer on the wall # 34 bottles of beer on the wall, 34 bottles of beer ... # If one of those bottles should happen to fall, 33 bottles of beer on the wall # 33 bottles of beer on the wall, 33 bottles of beer ... # If one of those bottles should happen to fall, 32 bottles of beer on the wall # 32 bottles of beer on the wall, 32 bottles of beer ... # If one of those bottles should happen to fall, 31 bottles of beer on the wall # 31 bottles of beer on the wall, 31 bottles of beer ... # If one of those bottles should happen to fall, 30 bottles of beer on the wall # 30 bottles of beer on the wall, 30 bottles of beer ... # If one of those bottles should happen to fall, 29 bottles of beer on the wall # 29 bottles of beer on the wall, 29 bottles of beer ... # If one of those bottles should happen to fall, 28 bottles of beer on the wall # 28 bottles of beer on the wall, 28 bottles of beer ... # If one of those bottles should happen to fall, 27 bottles of beer on the wall # 27 bottles of beer on the wall, 27 bottles of beer ... # If one of those bottles should happen to fall, 26 bottles of beer on the wall # 26 bottles of beer on the wall, 26 bottles of beer ... # If one of those bottles should happen to fall, 25 bottles of beer on the wall # 25 bottles of beer on the wall, 25 bottles of beer ... # If one of those bottles should happen to fall, 24 bottles of beer on the wall # 24 bottles of beer on the wall, 24 bottles of beer ... # If one of those bottles should happen to fall, 23 bottles of beer on the wall # 23 bottles of beer on the wall, 23 bottles of beer ... # If one of those bottles should happen to fall, 22 bottles of beer on the wall # 22 bottles of beer on the wall, 22 bottles of beer ... # If one of those bottles should happen to fall, 21 bottles of beer on the wall # 21 bottles of beer on the wall, 21 bottles of beer ... # If one of those bottles should happen to fall, 20 bottles of beer on the wall # 20 bottles of beer on the wall, 20 bottles of beer ... # If one of those bottles should happen to fall, 19 bottles of beer on the wall # 19 bottles of beer on the wall, 19 bottles of beer ... # If one of those bottles should happen to fall, 18 bottles of beer on the wall # 18 bottles of beer on the wall, 18 bottles of beer ... # If one of those bottles should happen to fall, 17 bottles of beer on the wall # 17 bottles of beer on the wall, 17 bottles of beer ... # If one of those bottles should happen to fall, 16 bottles of beer on the wall # 16 bottles of beer on the wall, 16 bottles of beer ... # If one of those bottles should happen to fall, 15 bottles of beer on the wall # 15 bottles of beer on the wall, 15 bottles of beer ... # If one of those bottles should happen to fall, 14 bottles of beer on the wall # 14 bottles of beer on the wall, 14 bottles of beer ... # If one of those bottles should happen to fall, 13 bottles of beer on the wall # 13 bottles of beer on the wall, 13 bottles of beer ... # If one of those bottles should happen to fall, 12 bottles of beer on the wall # 12 bottles of beer on the wall, 12 bottles of beer ... # If one of those bottles should happen to fall, 11 bottles of beer on the wall # 11 bottles of beer on the wall, 11 bottles of beer ... # If one of those bottles should happen to fall, 10 bottles of beer on the wall # 10 bottles of beer on the wall, 10 bottles of beer ... # If one of those bottles should happen to fall, 9 bottles of beer on the wall # 9 bottles of beer on the wall, 9 bottles of beer ... # If one of those bottles should happen to fall, 8 bottles of beer on the wall # 8 bottles of beer on the wall, 8 bottles of beer ... # If one of those bottles should happen to fall, 7 bottles of beer on the wall # 7 bottles of beer on the wall, 7 bottles of beer ... # If one of those bottles should happen to fall, 6 bottles of beer on the wall # 6 bottles of beer on the wall, 6 bottles of beer ... # If one of those bottles should happen to fall, 5 bottles of beer on the wall # 5 bottles of beer on the wall, 5 bottles of beer ... # If one of those bottles should happen to fall, 4 bottles of beer on the wall # 4 bottles of beer on the wall, 4 bottles of beer ... # If one of those bottles should happen to fall, 3 bottles of beer on the wall # 3 bottles of beer on the wall, 3 bottles of beer ... # If one of those bottles should happen to fall, 2 bottles of beer on the wall # 2 bottles of beer on the wall, 2 bottles of beer ... # If one of those bottles should happen to fall, 1 bottles of beer on the wall

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208

py

Python

bin/setup.py

bb12489/slideshow

7c9c803ca29d8660490fa24cdaccf807e1fe3a50

[ "MIT" ]

3

2018-05-15T07:52:15.000Z

2019-08-18T20:54:46.000Z

bin/setup.py

bb12489/slideshow

7c9c803ca29d8660490fa24cdaccf807e1fe3a50

[ "MIT" ]

null

bin/setup.py

bb12489/slideshow

7c9c803ca29d8660490fa24cdaccf807e1fe3a50

[ "MIT" ]

1

2019-07-09T12:12:01.000Z

from subprocess import STDOUT, check_call import os #check_call(['sudo', 'apt-get', 'update', '-y']) #check_call(['sudo', 'apt-get', 'upgrade', '-y']) subprocess.call("(cd ~/temp/slideshow/)", shell=True)

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py

Python

aws_managers/athena/__init__.py

vahndi/aws-managers

bdbfb2b8a9258a53e3ea4dfbbfe5491a34113899

[ "MIT" ]

null

aws_managers/athena/__init__.py

vahndi/aws-managers

bdbfb2b8a9258a53e3ea4dfbbfe5491a34113899

[ "MIT" ]

null

aws_managers/athena/__init__.py

vahndi/aws-managers

bdbfb2b8a9258a53e3ea4dfbbfe5491a34113899

[ "MIT" ]

null

from aws_managers.athena.athena_frame import AthenaFrame from aws_managers.athena.queries.athena_query_generator import AthenaQueryGenerator

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py

Python

sam/sim/test/unit-apps/test_unit_bv_vec_elemmul.py

weiya711/scadi_graph

5ce78fe09286e9722c2627f7f959c4ad3f2288eb

[ "MIT" ]

null

sam/sim/test/unit-apps/test_unit_bv_vec_elemmul.py

weiya711/scadi_graph

5ce78fe09286e9722c2627f7f959c4ad3f2288eb

[ "MIT" ]

null

sam/sim/test/unit-apps/test_unit_bv_vec_elemmul.py

weiya711/scadi_graph

5ce78fe09286e9722c2627f7f959c4ad3f2288eb

[ "MIT" ]

null

import pytest import random from sam.sim.src.rd_scanner import BVRdScan, CompressedCrdRdScan from sam.sim.src.bitvector import BV, BVDrop from sam.sim.src.wr_scanner import ValsWrScan, CompressWrScan from sam.sim.src.joiner import IntersectBV2 from sam.sim.src.compute import Multiply2 from sam.sim.src.array import Array from sam.sim.src.split import Split from sam.sim.src.base import remove_emptystr from sam.sim.test.test import TIMEOUT, check_arr, check_seg_arr, remove_zeros def bv(ll): result = 0 for elem in ll: result |= 1 << elem return result def inner_bv(ll, size, sf): result = [] for i in range(int(size / sf) + 2): temp = bv([elem % sf for elem in ll if max((i - 1) * sf, 0) <= elem < i * sf]) if temp: result.append(temp) return result @pytest.mark.parametrize("nnz", [1, 10, 100, 500, 1000]) def test_vec_bv_split(nnz, debug_sim, max_val=999, size=1000, fill=0): sf = 32 crd_arr1 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr1 = sorted(set(crd_arr1)) seg_arr1 = [0, len(crd_arr1)] vals_arr1 = [random.randint(0, max_val) for _ in range(len(crd_arr1))] crd_arr2 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr2 = sorted(set(crd_arr2)) seg_arr2 = [0, len(crd_arr2)] vals_arr2 = [random.randint(0, max_val) for _ in range(len(crd_arr2))] if debug_sim: print("Compressed VECTOR 1:\n", seg_arr1, "\n", crd_arr1, "\n", vals_arr1) print("Compressed VECTOR 2:\n", seg_arr2, "\n", crd_arr2, "\n", vals_arr2) gold_bv1_1 = [bv([int(elem / sf) for elem in crd_arr1])] gold_bv1_0 = inner_bv(crd_arr1, size, sf) gold_bv1_0 += (32 - len(gold_bv1_0)) * [0] gold_bv2_1 = [bv([int(elem / sf) for elem in crd_arr2])] gold_bv2_0 = inner_bv(crd_arr2, size, sf) gold_bv2_0 += (32 - len(gold_bv2_0)) * [0] crdscan1 = CompressedCrdRdScan(seg_arr=seg_arr1, crd_arr=crd_arr1, debug=debug_sim) crdscan2 = CompressedCrdRdScan(seg_arr=seg_arr2, crd_arr=crd_arr2, debug=debug_sim) split1 = Split(split_factor=sf, orig_crd=False, debug=debug_sim) split2 = Split(split_factor=sf, orig_crd=False, debug=debug_sim) bv1_0 = BV(debug=debug_sim) bv1_1 = BV(debug=debug_sim) bv2_0 = BV(debug=debug_sim) bv2_1 = BV(debug=debug_sim) wrscan1_0 = ValsWrScan(size=sf, fill=fill) wrscan1_1 = ValsWrScan(size=1, fill=fill) wrscan2_0 = ValsWrScan(size=sf, fill=fill) wrscan2_1 = ValsWrScan(size=1, fill=fill) in_ref1 = [0, 'D'] in_ref2 = [0, 'D'] done = False time = 0 out_split1_0 = [] out_split1_1 = [] out_split2_0 = [] out_split2_1 = [] while not done and time < TIMEOUT: if len(in_ref1) > 0: crdscan1.set_in_ref(in_ref1.pop(0)) crdscan1.update() if len(in_ref2) > 0: crdscan2.set_in_ref(in_ref2.pop(0)) crdscan2.update() split1.set_in_crd(crdscan1.out_crd()) split1.update() split2.set_in_crd(crdscan2.out_crd()) split2.update() out_split1_0.append(split1.out_inner_crd()) out_split1_1.append(split1.out_outer_crd()) out_split2_0.append(split2.out_inner_crd()) out_split2_1.append(split2.out_outer_crd()) bv1_0.set_in_crd(split1.out_inner_crd()) bv1_1.set_in_crd(split1.out_outer_crd()) bv2_0.set_in_crd(split2.out_inner_crd()) bv2_1.set_in_crd(split2.out_outer_crd()) bv1_0.update() bv1_1.update() bv2_0.update() bv2_1.update() wrscan1_0.set_input(bv1_0.out_bv_int()) wrscan1_1.set_input(bv1_1.out_bv_int()) wrscan2_0.set_input(bv2_0.out_bv_int()) wrscan2_1.set_input(bv2_1.out_bv_int()) wrscan1_0.update() wrscan1_1.update() wrscan2_0.update() wrscan2_1.update() print("Timestep", time, "\t Done -- \n", "\nRdScan1:", crdscan1.out_done(), "\tRdScan2:", crdscan2.out_done(), "\nSplit1:", split1.out_done(), "\tSplit2:", split2.out_done(), "\nBV:", bv1_0.out_done(), bv1_1.out_done(), bv2_0.out_done(), bv2_1.out_done(), "\nWrScan:", wrscan1_0.out_done(), wrscan1_1.out_done(), wrscan2_0.out_done(), wrscan2_1.out_done() ) done = wrscan2_0.out_done() and wrscan2_1.out_done() and wrscan1_1.out_done() and wrscan1_0.out_done() time += 1 if debug_sim: print(remove_emptystr(out_split1_0)) print(remove_emptystr(out_split1_1)) print(remove_emptystr(out_split2_0)) print(remove_emptystr(out_split2_1)) print([bin(i) for i in wrscan1_0.get_arr()]) print([bin(i) for i in wrscan1_1.get_arr()]) print([bin(i) for i in wrscan2_0.get_arr()]) print([bin(i) for i in wrscan2_1.get_arr()]) check_arr(wrscan1_0, gold_bv1_0) check_arr(wrscan1_1, gold_bv1_1) check_arr(wrscan2_0, gold_bv2_0) check_arr(wrscan2_1, gold_bv2_1) # TODO: BV already set vecmul ONLY and then combined @pytest.mark.parametrize("nnz", [1, 10, 100, 500, 1000]) def test_mat_elemmul_bvonly(nnz, debug_sim, max_val=1000, size=1001, fill=0): assert (size > max_val) sf = 32 crd_arr1 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr1 = sorted(set(crd_arr1)) seg_arr1 = [0, len(crd_arr1)] vals_arr1 = [random.randint(0, max_val) for _ in range(len(crd_arr1))] crd_arr2 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr2 = sorted(set(crd_arr2)) seg_arr2 = [0, len(crd_arr2)] vals_arr2 = [random.randint(0, max_val) for _ in range(len(crd_arr2))] if debug_sim: print("Compressed VECTOR 1:\n", seg_arr1, "\n", crd_arr1, "\n", vals_arr1) print("Compressed VECTOR 2:\n", seg_arr2, "\n", crd_arr2, "\n", vals_arr2) gold_bv1_1 = [bv([int(elem / sf) for elem in crd_arr1])] gold_bv1_0 = inner_bv(crd_arr1, size, sf) gold_bv1_0 += (32 - len(gold_bv1_0)) * [0] gold_bv2_1 = [bv([int(elem / sf) for elem in crd_arr2])] gold_bv2_0 = inner_bv(crd_arr2, size, sf) gold_bv2_0 += (32 - len(gold_bv2_0)) * [0] gold_crd = sorted(set(crd_arr1) & set(crd_arr2)) gold_seg = [0, len(gold_crd)] gold_vals = [] gold_bv1 = [] gold_bv0 = [] if gold_crd: gold_vals = [vals_arr1[crd_arr1.index(i)] * vals_arr2[crd_arr2.index(i)] for i in gold_crd] gold_bv1 = [bv([int(elem / sf) for elem in gold_crd])] gold_bv0 = inner_bv(gold_crd, size, sf) if debug_sim: print("Compressed RESULT :\n", gold_seg, "\n", gold_crd, "\n", gold_vals) print("BV arr1 0", gold_bv1_0) print("BV arr1 1", gold_bv1_1) print("BV arr2 0", gold_bv2_0) print("BV arr2 1", gold_bv2_1) bvscan1_0 = BVRdScan(bv_arr=gold_bv1_0, debug=debug_sim) bvscan1_1 = BVRdScan(bv_arr=gold_bv1_1, debug=debug_sim) bvscan2_0 = BVRdScan(bv_arr=gold_bv2_0, debug=debug_sim) bvscan2_1 = BVRdScan(bv_arr=gold_bv2_1, debug=debug_sim) inter0 = IntersectBV2(debug=debug_sim) inter1 = IntersectBV2(debug=debug_sim) val1 = Array(init_arr=vals_arr1, debug=debug_sim) val2 = Array(init_arr=vals_arr2, debug=debug_sim) mul = Multiply2(debug=debug_sim) bvdrop = BVDrop(debug=debug_sim) oval_wrscan = ValsWrScan(size=size, fill=fill) wrscan0 = ValsWrScan(size=size, fill=fill) wrscan1 = ValsWrScan(size=1, fill=fill) temp1 = [] temp2 = [] temp3 = [] temp4 = [] in_ref1 = [0, 'D'] in_ref2 = [0, 'D'] done = False time = 0 while not done and time < TIMEOUT: if len(in_ref1) > 0: bvscan1_1.set_in_ref(in_ref1.pop(0)) bvscan1_1.update() if len(in_ref2) > 0: bvscan2_1.set_in_ref(in_ref2.pop(0)) bvscan2_1.update() inter1.set_in1(bvscan1_1.out_ref(), bvscan1_1.out_bv()) inter1.set_in2(bvscan2_1.out_ref(), bvscan2_1.out_bv()) inter1.update() temp1.append(inter0.out_ref1()) print(remove_emptystr(temp1)) temp2.append(inter0.out_ref2()) print(remove_emptystr(temp2)) bvscan1_0.set_in_ref(inter1.out_ref1()) bvscan1_0.update() bvscan2_0.set_in_ref(inter1.out_ref2()) bvscan2_0.update() inter0.set_in1(bvscan1_0.out_ref(), bvscan1_0.out_bv()) inter0.set_in2(bvscan2_0.out_ref(), bvscan2_0.out_bv()) inter0.update() val1.set_load(inter0.out_ref1()) val2.set_load(inter0.out_ref2()) val1.update() val2.update() mul.set_in1(val1.out_load()) mul.set_in2(val2.out_load()) mul.update() oval_wrscan.set_input(mul.out_val()) oval_wrscan.update() temp3.append(inter0.out_bv()) temp4.append(inter1.out_bv()) bvdrop.set_inner_bv(inter0.out_bv()) bvdrop.set_outer_bv(inter1.out_bv()) bvdrop.update() wrscan0.set_input(bvdrop.out_bv_inner()) wrscan0.update() wrscan1.set_input(bvdrop.out_bv_outer()) wrscan1.update() print("Timestep", time, "\t Done --", "\nRdScan1:", bvscan1_0.out_done(), bvscan2_0.out_done(), bvscan1_1.out_done(), bvscan2_1.out_done(), "\nInter:", inter0.out_done(), inter1.out_done(), "\nArr:", val1.out_done(), val2.out_done(), "\tMul:", mul.out_done(), "\nOutVal:", oval_wrscan.out_done(), "\tOutBV1:", wrscan1.out_done(), "\tOutBV0:", wrscan0.out_done() ) done = wrscan0.out_done() and wrscan1.out_done() and oval_wrscan.out_done() time += 1 if debug_sim: print(oval_wrscan.get_arr()) print(temp3) print(temp4) print(wrscan0.get_arr()) print(gold_bv0) print(wrscan1.get_arr()) print(gold_bv1) check_arr(oval_wrscan, gold_vals) if gold_crd: check_arr(wrscan0, gold_bv0) check_arr(wrscan1, gold_bv1) # NOTE: This is the full vector elementwise multiplication as a bitvector @pytest.mark.parametrize("nnz", [1, 10, 100, 500, 1000]) def test_vec_elemmul_bv_split(nnz, debug_sim, max_val=999, size=1000, fill=0): sf = 32 crd_arr1 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr1 = sorted(set(crd_arr1)) seg_arr1 = [0, len(crd_arr1)] vals_arr1 = [random.randint(0, max_val) for _ in range(len(crd_arr1))] crd_arr2 = [random.randint(0, max_val) for _ in range(nnz)] crd_arr2 = sorted(set(crd_arr2)) seg_arr2 = [0, len(crd_arr2)] vals_arr2 = [random.randint(0, max_val) for _ in range(len(crd_arr2))] if debug_sim: print("Compressed VECTOR 1:\n", seg_arr1, "\n", crd_arr1, "\n", vals_arr1) print("Compressed VECTOR 2:\n", seg_arr2, "\n", crd_arr2, "\n", vals_arr2) gold_bv1_1 = [bv([int(elem / sf) for elem in crd_arr1])] gold_bv1_0 = inner_bv(crd_arr1, size, sf) gold_bv1_0 += (32 - len(gold_bv1_0)) * [0] gold_bv2_1 = [bv([int(elem / sf) for elem in crd_arr2])] gold_bv2_0 = inner_bv(crd_arr2, size, sf) gold_bv2_0 += (32 - len(gold_bv2_0)) * [0] gold_crd = sorted(set(crd_arr1) & set(crd_arr2)) gold_seg = [0, len(gold_crd)] gold_vals = [] gold_bv1 = [] gold_bv0 = [] if gold_crd: gold_vals = [vals_arr1[crd_arr1.index(i)] * vals_arr2[crd_arr2.index(i)] for i in gold_crd] gold_bv1 = [bv([int(elem / sf) for elem in gold_crd])] gold_bv0 = inner_bv(gold_crd, size, sf) if debug_sim: print("Compressed RESULT :\n", gold_seg, "\n", gold_crd, "\n", gold_vals) print("BV arr1 0", gold_bv1_0) print("BV arr1 1", gold_bv1_1) print("BV arr2 0", gold_bv2_0) print("BV arr2 1", gold_bv2_1) crdscan1 = CompressedCrdRdScan(seg_arr=seg_arr1, crd_arr=crd_arr1, debug=debug_sim) crdscan2 = CompressedCrdRdScan(seg_arr=seg_arr2, crd_arr=crd_arr2, debug=debug_sim) split1 = Split(split_factor=sf, orig_crd=False, debug=debug_sim) split2 = Split(split_factor=sf, orig_crd=False, debug=debug_sim) bv1_0 = BV(debug=debug_sim) bv1_1 = BV(debug=debug_sim) bv2_0 = BV(debug=debug_sim) bv2_1 = BV(debug=debug_sim) wrscan1_0 = ValsWrScan(size=sf, fill=fill) wrscan1_1 = ValsWrScan(size=1, fill=fill) wrscan2_0 = ValsWrScan(size=sf, fill=fill) wrscan2_1 = ValsWrScan(size=1, fill=fill) in_ref1 = [0, 'D'] in_ref2 = [0, 'D'] done = False time1 = 0 out_split1_0 = [] out_split1_1 = [] out_split2_0 = [] out_split2_1 = [] while not done and time1 < TIMEOUT: if len(in_ref1) > 0: crdscan1.set_in_ref(in_ref1.pop(0)) crdscan1.update() if len(in_ref2) > 0: crdscan2.set_in_ref(in_ref2.pop(0)) crdscan2.update() split1.set_in_crd(crdscan1.out_crd()) split1.update() split2.set_in_crd(crdscan2.out_crd()) split2.update() out_split1_0.append(split1.out_inner_crd()) out_split1_1.append(split1.out_outer_crd()) out_split2_0.append(split2.out_inner_crd()) out_split2_1.append(split2.out_outer_crd()) bv1_0.set_in_crd(split1.out_inner_crd()) bv1_1.set_in_crd(split1.out_outer_crd()) bv2_0.set_in_crd(split2.out_inner_crd()) bv2_1.set_in_crd(split2.out_outer_crd()) bv1_0.update() bv1_1.update() bv2_0.update() bv2_1.update() wrscan1_0.set_input(bv1_0.out_bv_int()) wrscan1_1.set_input(bv1_1.out_bv_int()) wrscan2_0.set_input(bv2_0.out_bv_int()) wrscan2_1.set_input(bv2_1.out_bv_int()) wrscan1_0.update() wrscan1_1.update() wrscan2_0.update() wrscan2_1.update() print("Timestep", time1, "\t Done -- \n", "\nRdScan1:", crdscan1.out_done(), "\tRdScan2:", crdscan2.out_done(), "\nSplit1:", split1.out_done(), "\tSplit2:", split2.out_done(), "\nBV:", bv1_0.out_done(), bv1_1.out_done(), bv2_0.out_done(), bv2_1.out_done(), "\nWrScan:", wrscan1_0.out_done(), wrscan1_1.out_done(), wrscan2_0.out_done(), wrscan2_1.out_done() ) done = wrscan2_0.out_done() and wrscan2_1.out_done() and wrscan1_1.out_done() and wrscan1_0.out_done() time1 += 1 if debug_sim: print(remove_emptystr(out_split1_0)) print(remove_emptystr(out_split1_1)) print(remove_emptystr(out_split2_0)) print(remove_emptystr(out_split2_1)) print([bin(i) for i in wrscan1_0.get_arr()]) print([bin(i) for i in wrscan1_1.get_arr()]) print([bin(i) for i in wrscan2_0.get_arr()]) print([bin(i) for i in wrscan2_1.get_arr()]) check_arr(wrscan1_0, gold_bv1_0) check_arr(wrscan1_1, gold_bv1_1) check_arr(wrscan2_0, gold_bv2_0) check_arr(wrscan2_1, gold_bv2_1) bvscan1_0 = BVRdScan(bv_arr=wrscan1_0.get_arr(), debug=debug_sim) bvscan1_1 = BVRdScan(bv_arr=wrscan1_1.get_arr(), debug=debug_sim) bvscan2_0 = BVRdScan(bv_arr=wrscan2_0.get_arr(), debug=debug_sim) bvscan2_1 = BVRdScan(bv_arr=wrscan2_1.get_arr(), debug=debug_sim) inter0 = IntersectBV2(debug=debug_sim) inter1 = IntersectBV2(debug=debug_sim) val1 = Array(init_arr=vals_arr1, debug=debug_sim) val2 = Array(init_arr=vals_arr2, debug=debug_sim) mul = Multiply2(debug=debug_sim) bvdrop = BVDrop(debug=debug_sim) oval_wrscan = ValsWrScan(size=size, fill=fill) wrscan0 = ValsWrScan(size=size, fill=fill) wrscan1 = ValsWrScan(size=1, fill=fill) in_ref1 = [0, 'D'] in_ref2 = [0, 'D'] done = False time2 = 0 while not done and time1 < TIMEOUT: if len(in_ref1) > 0: bvscan1_1.set_in_ref(in_ref1.pop(0)) bvscan1_1.update() if len(in_ref2) > 0: bvscan2_1.set_in_ref(in_ref2.pop(0)) bvscan2_1.update() inter1.set_in1(bvscan1_1.out_ref(), bvscan1_1.out_bv()) inter1.set_in2(bvscan2_1.out_ref(), bvscan2_1.out_bv()) inter1.update() bvscan1_0.set_in_ref(inter1.out_ref1()) bvscan1_0.update() bvscan2_0.set_in_ref(inter1.out_ref2()) bvscan2_0.update() inter0.set_in1(bvscan1_0.out_ref(), bvscan1_0.out_bv()) inter0.set_in2(bvscan2_0.out_ref(), bvscan2_0.out_bv()) inter0.update() val1.set_load(inter0.out_ref1()) val2.set_load(inter0.out_ref2()) val1.update() val2.update() mul.set_in1(val1.out_load()) mul.set_in2(val2.out_load()) mul.update() oval_wrscan.set_input(mul.out_val()) oval_wrscan.update() bvdrop.set_inner_bv(inter0.out_bv()) bvdrop.set_outer_bv(inter1.out_bv()) bvdrop.update() wrscan0.set_input(bvdrop.out_bv_inner()) wrscan0.update() wrscan1.set_input(bvdrop.out_bv_outer()) wrscan1.update() print("Timestep", time2, "\t Done --", "\nRdScan1:", bvscan1_0.out_done(), bvscan2_0.out_done(), bvscan1_1.out_done(), bvscan2_1.out_done(), "\nInter:", inter0.out_done(), inter1.out_done(), "\nArr:", val1.out_done(), val2.out_done(), "\tMul:", mul.out_done(), "\nOutVal:", oval_wrscan.out_done(), "\tOutBV1:", wrscan1.out_done(), "\tOutBV0:", wrscan0.out_done() ) done = wrscan0.out_done() and wrscan1.out_done() and oval_wrscan.out_done() time2 += 1 if debug_sim: print("TOTAL TIME:", time1 + time2) print(oval_wrscan.get_arr()) print(wrscan0.get_arr()) print(gold_bv0) print(wrscan1.get_arr()) print(gold_bv1) check_arr(oval_wrscan, gold_vals) if gold_crd: check_arr(wrscan0, gold_bv0) check_arr(wrscan1, gold_bv1)

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0.059038

0.041739

0.045009

0.019619

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0.892768

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0.22975

17,815

502

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35.488048

0.68904

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0.012165

false

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0.026764

0

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0.124088

0

null

0

1

0

1

0

null

0

7

0f7b259d190892996744486c93ef886a56611948

578

py

Python

Funny_Js_Crack/91-wallhere_spider/use_pypackage_anti_cloudflare.py

qqizai/Func_Js_Crack

8cc8586107fecace4b71d0519cfbc760584171b1

[ "MIT" ]

18

2020-12-09T06:49:46.000Z

2022-01-27T03:20:36.000Z

Funny_Js_Crack/91-wallhere_spider/use_pypackage_anti_cloudflare.py

useafter/Func_Js_Crack

8cc8586107fecace4b71d0519cfbc760584171b1

[ "MIT" ]

null

Funny_Js_Crack/91-wallhere_spider/use_pypackage_anti_cloudflare.py

useafter/Func_Js_Crack

8cc8586107fecace4b71d0519cfbc760584171b1

[ "MIT" ]

9

2020-12-20T08:52:09.000Z

2021-12-19T09:13:09.000Z

import cfscrape # 实例化一个CloudflareScraper对象 scraper = cfscrape.create_scraper() # 或者scraper = cfscrape.CloudflareScraper()也可以 # 如果出现错误可以加个延迟 # scraper = cfscrape.create_scraper(delay = 10) # 获取真实网页源代码 web_data = scraper.get("https://wallhere.com/").content print(web_data) # pip install cfscrape # 处理post的CloudFlare # import cfscrape # 实例化一个CloudflareScraper对象 # scraper = cfscrape.create_scraper() # 或者scraper = cfscrape.CloudflareScraper()也可以 # 如果出现错误可以加个延迟 # scraper = cfscrape.create_scraper(delay = 10) # 获取真实网页源代码 # web_data = scraper.post("http://example.com").content

25.130435

55

0.780277

61

578

7.278689

0.42623

0.135135

0.189189

0.252252

0.779279

0

0.007737

0.105536

578

22

56

26.272727

0.851064

0.726644

0

0.148936

0

1

0

false

0

0.25

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0.25

0

null

0

1

0

1

0

null

0

7

7e661bf7c03da5cfc2cf394cf35c30237a5fbced

365

py

Python

Website_to_CSV_Functions/__init__.py

dniamir/FantasyFootballScraper

3ba86cb8a976e45a852b32bc6450264e072259ba

[ "MIT" ]

null

Website_to_CSV_Functions/__init__.py

dniamir/FantasyFootballScraper

3ba86cb8a976e45a852b32bc6450264e072259ba

[ "MIT" ]

null

Website_to_CSV_Functions/__init__.py

dniamir/FantasyFootballScraper

3ba86cb8a976e45a852b32bc6450264e072259ba

[ "MIT" ]

null

from Website_to_CSV_Functions.Basic_Stats_Class import * from Website_to_CSV_Functions.Career_Stats_Class import * from Website_to_CSV_Functions.Game_Logs_Class import * from Website_to_CSV_Functions.Obtain_Players_from_Website import * from Website_to_CSV_Functions.NFL_Glossary import * from Website_to_CSV_Functions.Functions_Needed_For_All_Stats import *

52.142857

70

0.884932

56

365

5.196429

0.339286

0.264605

0.268041

0.329897

0.704467

0.618557

0.405498

0.281787

0

0.082192

365

6

71

60.833333

0.868657

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

7e70d80fc9d9ef5824c8c5f79fd3447dec5ed5ce

67,154

py

Python

tests/test_path.py

sobolevn/action-hero

75ff10dc8b01ee8d00367c63e8eccbbee9cc7d42

[ "MIT" ]

91

2019-09-26T20:55:55.000Z

2021-10-19T22:27:21.000Z

tests/test_path.py

kadimisetty/action-heroes

f203e2e130dce970db803d6447bf7518c5e54285

[ "MIT" ]

1

2020-02-07T02:51:40.000Z

tests/test_path.py

kadimisetty/action-heroes

f203e2e130dce970db803d6447bf7518c5e54285

[ "MIT" ]

5

2020-02-02T03:40:47.000Z

2020-11-05T10:53:11.000Z

import os import tempfile from action_hero.utils import ActionHeroTestCase from action_hero import ( DirectoryDoesNotExistAction, DirectoryExistsAction, DirectoryIsExecutableAction, DirectoryIsNotExecutableAction, DirectoryIsNotReadableAction, DirectoryIsNotWritableAction, DirectoryIsReadableAction, DirectoryIsValidAction, DirectoryIsWritableAction, EnsureDirectoryAction, EnsureFileAction, FileDoesNotExistAction, FileExistsAction, FileIsEmptyAction, FileIsExecutableAction, FileIsNotEmptyAction, FileIsNotExecutableAction, FileIsNotReadableAction, FileIsNotWritableAction, FileIsReadableAction, FileIsWritableAction, FileHasExtensionAction, PathDoesNotExistsAction, PathExistsAction, PathIsExecutableAction, PathIsNotExecutableAction, PathIsNotReadableAction, PathIsNotWritableAction, PathIsReadableAction, PathIsValidAction, PathIsWritableAction, ResolvePathAction, ) from action_hero.path_utils import ( add_execute_permission, is_empty_file, is_executable_directory, is_executable_file, is_existing_directory, is_existing_file, is_existing_path, is_readable_directory, is_readable_file, is_readable_path, is_valid_directory, is_valid_file, is_valid_path, is_writable_file, remove_execute_permission, remove_read_permission, remove_write_permission, resolve_path, ) class TestResolvePathAction(ActionHeroTestCase): def test_processes_path(self): self.parser.add_argument("--path", action=ResolvePathAction) with tempfile.TemporaryDirectory() as dir1: args = self.parser.parse_args(["--path", dir1]) self.assertIn("path", args) def test_on_single_path(self): self.parser.add_argument("--path", action=ResolvePathAction) with tempfile.TemporaryDirectory() as dir1: args = self.parser.parse_args(["--path", dir1]) expected = resolve_path(dir1) self.assertEqual(args.path, expected) def test_on_list_of_paths(self): self.parser.add_argument("--path", nargs="+", action=ResolvePathAction) # Create few temporary paths path1 = tempfile.mkdtemp() path2 = tempfile.mkdtemp() path3 = tempfile.mkdtemp() temp_paths = [path1, path2, path3] # Parse args with list of paths args = self.parser.parse_args(["--path", *temp_paths]) expected = [resolve_path(path) for path in temp_paths] self.assertEqual(args.path, expected) # Delete all temporary paths [os.rmdir(path) for path in temp_paths] class TestEnsureDirectoryAction(ActionHeroTestCase): def test_on_nonexisting_directory(self): self.parser.add_argument("--path", action=EnsureDirectoryAction) with tempfile.TemporaryDirectory() as parent_directory: # Specify unique directory name dir1 = os.path.join(parent_directory, "NEWDIRT") # Assert specified directory does not exist self.assertFalse(os.path.isdir(dir1)) # Parse args with --path as specified directory self.parser.parse_args(["--path", dir1]) # Assert specified directory does exist self.assertTrue(os.path.isdir(dir1)) def test_on_existing_directory(self): self.parser.add_argument("--path", action=EnsureDirectoryAction) # Specify directory to check with tempfile.TemporaryDirectory() as dir1: # Assert specified directory exists self.assertTrue(os.path.isdir(dir1)) # Parse args with --path as specified directory self.parser.parse_args(["--path", dir1]) # Assert specified directory still exist self.assertTrue(os.path.isdir(dir1)) def test_on_multiple_mixed_existing_directories(self): self.parser.add_argument( "--path", nargs="+", action=EnsureDirectoryAction ) # Specify few new temporary directories dir1 = tempfile.mkdtemp() dir2 = tempfile.mkdtemp() # Directories deleted immediately to confirm they do not exist dir3 = tempfile.mkdtemp() os.rmdir(dir3) dir4 = tempfile.mkdtemp() os.rmdir(dir4) mixed_dirs = [dir1, dir2, dir3, dir4] # Assert that mixed_dirs contain existing and non-existing directories self.assertIn(True, [os.path.isdir(d) for d in mixed_dirs]) self.assertIn(False, [os.path.isdir(d) for d in mixed_dirs]) # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", *mixed_dirs]) # Assert that all directories in mixed_dirs now exist self.assertNotIn(False, [os.path.isdir(d) for d in mixed_dirs]) # Tear down temporary directories [os.rmdir(d) for d in mixed_dirs] class TestEnsureFileAction(ActionHeroTestCase): def test_on_nonexisting_file(self): self.parser.add_argument("--path", action=EnsureFileAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(os.path.isfile(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(os.path.isfile(file1)) # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", file1]) # Assert specified file now exists self.assertTrue(os.path.isfile(file1)) def test_on_existing_file(self): self.parser.add_argument("--path", action=EnsureFileAction) # Specify file to check with tempfile.NamedTemporaryFile() as file1: # Assert specified file exists self.assertTrue(os.path.isfile(file1.name)) # Parse args with --path as specified file self.parser.parse_args(["--path", file1.name]) # Assert specified file still exists self.assertTrue(os.path.isfile(file1.name)) def test_on_multiple_mixed_existing_files(self): self.parser.add_argument("--path", nargs="+", action=EnsureFileAction) with tempfile.TemporaryDirectory() as parent_directory: # Specify few new temporary files file1 = tempfile.mkstemp(dir=parent_directory)[1] file2 = tempfile.mkstemp(dir=parent_directory)[1] # files deleted immediately to confirm they do not exist file3 = tempfile.mkstemp(dir=parent_directory)[1] os.remove(file3) file4 = tempfile.mkstemp(dir=parent_directory)[1] os.remove(file4) mixed_files = [file1, file2, file3, file4] # Assert that mixed_files contain existing and non-existing files self.assertIn(True, [os.path.isfile(f) for f in mixed_files]) self.assertIn(False, [os.path.isfile(f) for f in mixed_files]) # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", *mixed_files]) # Assert that all files in mixed_files now exist self.assertNotIn(False, [os.path.isfile(f) for f in mixed_files]) # Tear down temporary files [os.remove(f) for f in mixed_files] class TestPathIsValidAction(ActionHeroTestCase): def test_on_valid_path(self): self.parser.add_argument("--path", action=PathIsValidAction) with tempfile.TemporaryDirectory() as path1: # Assert path is valid path self.assertTrue(is_valid_path(path1)) # Parse args with list of paths args = self.parser.parse_args(["--path", path1]) # Assert path from args is valid path self.assertTrue(is_valid_path(args.path)) def test_on_multiple_valid_paths(self): self.parser.add_argument("--path", nargs="+", action=PathIsValidAction) # Create few temporary paths path1 = tempfile.mkdtemp() path2 = tempfile.mkdtemp() path3 = tempfile.mkdtemp() paths = [path1, path2, path3] # Parse args with list of paths self.parser.parse_args(["--path", *paths]) self.assertNotIn(False, [is_valid_path(p) for p in paths]) # Delete all temporary paths [os.rmdir(path) for path in paths] def test_on_invalid_path(self): self.parser.add_argument("--path", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" file_name = "SOMEFILE{}".format(forbidden_char) file_path = os.path.join(parent_directory, file_name) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_path(file_path)) with self.assertRaises(ValueError): # Parse args with prohibited filename self.parser.parse_args(["--path", file_path]) def test_on_mixed_valid_and_invalid_path(self): self.parser.add_argument("--path", nargs="+", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" invalid_path_name = "SOMEFILE{}".format(forbidden_char) invalid_path = os.path.join(parent_directory, invalid_path_name) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_path(invalid_path)) # Create valid path with tempfile.TemporaryDirectory() as valid_dir_path: # Assemble mixed valid and invalid path paths = [invalid_path, valid_dir_path] with self.assertRaises(ValueError): # Parse args with list of paths self.parser.parse_args(["--path", *paths]) class TestFileIsValidAction(ActionHeroTestCase): def test_on_valid_file_path(self): self.parser.add_argument("--path", action=PathIsValidAction) with tempfile.NamedTemporaryFile() as file_path: # Assert file path is valid file path self.assertTrue(is_valid_file(file_path.name)) # Parse args with list of paths args = self.parser.parse_args(["--path", file_path.name]) # Assert path from args is valid path self.assertTrue(is_valid_file(args.path)) def test_on_multiple_valid_file_paths(self): self.parser.add_argument("--path", nargs="+", action=PathIsValidAction) # Create few temporary paths file_path1 = tempfile.mkstemp()[1] file_path2 = tempfile.mkstemp()[1] file_path3 = tempfile.mkstemp()[1] file_paths = [file_path1, file_path2, file_path3] # Parse args with list of paths self.parser.parse_args(["--path", *file_paths]) self.assertNotIn(False, [is_valid_path(p) for p in file_paths]) # Delete all temporary file paths [os.remove(path) for path in file_paths] def test_on_invalid_file_path(self): self.parser.add_argument("--path", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" file_name = "SOMEFILE{}".format(forbidden_char) file_path = os.path.join(parent_directory, file_name) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_file(file_path)) with self.assertRaises(ValueError): # Parse args with prohibited filename self.parser.parse_args(["--path", file_path]) def test_on_mixed_valid_and_invalid_file_path(self): self.parser.add_argument("--path", nargs="+", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" invalid_file_name = "SOMEFILE{}".format(forbidden_char) invalid_file_path = os.path.join( parent_directory, invalid_file_name ) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_file(invalid_file_path)) # Create valid path with tempfile.NamedTemporaryFile() as valid_file_path: # Assemble mixed valid and invalid path paths = [invalid_file_path, valid_file_path.name] with self.assertRaises(ValueError): # Parse args with list of paths self.parser.parse_args(["--path", *paths]) class TestDirectoryIsValidAction(ActionHeroTestCase): def test_on_valid_directory_path(self): self.parser.add_argument("--path", action=DirectoryIsValidAction) with tempfile.TemporaryDirectory() as dir1: # Assert path is valid path self.assertTrue(is_valid_directory(dir1)) # Parse args with list of paths args = self.parser.parse_args(["--path", dir1]) # Assert path from args is valid path self.assertTrue(is_valid_directory(args.path)) def test_on_multiple_valid_directory_paths(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsValidAction ) # Create few temporary paths dir1 = tempfile.mkdtemp() dir2 = tempfile.mkdtemp() dir3 = tempfile.mkdtemp() dirs = [dir1, dir2, dir3] # Parse args with list of paths self.parser.parse_args(["--path", *dirs]) self.assertNotIn(False, [is_valid_directory(d) for d in dirs]) # Delete all temporary file paths [os.rmdir(d) for d in dirs] def test_on_invalid_directory_path(self): self.parser.add_argument("--path", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" dir_name = "SOMEFILE{}".format(forbidden_char) dir_path = os.path.join(parent_directory, dir_name) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_file(dir_path)) with self.assertRaises(ValueError): # Parse args with prohibited filename self.parser.parse_args(["--path", dir_path]) def test_on_mixed_valid_and_invalid_file_path(self): self.parser.add_argument("--path", nargs="+", action=PathIsValidAction) with tempfile.TemporaryDirectory() as parent_directory: # Create a file name with a char forbidden in POSIX and WIN* forbidden_char = "/" invalid_dir_name = "SOMEDIR{}".format(forbidden_char) invalid_dir_path = os.path.join(parent_directory, invalid_dir_name) # Assert that the forbidden character prohibited path creation self.assertFalse(is_valid_file(invalid_dir_path)) # Create valid path with tempfile.TemporaryDirectory() as valid_dir_path: # Assemble mixed valid and invalid path paths = [invalid_dir_path, valid_dir_path] with self.assertRaises(ValueError): # Parse args with list of paths self.parser.parse_args(["--path", *paths]) class TestPathExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=PathExistsAction) # Specify file to check with tempfile.NamedTemporaryFile() as file1: # Assert specified file exists self.assertTrue(is_existing_path(file1.name)) # Parse args with --path as specified file self.parser.parse_args(["--path", file1.name]) # Assert specified file still exists self.assertTrue(is_existing_path(file1.name)) def test_on_nonexisting_path(self): self.parser.add_argument("--path", action=PathExistsAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_path(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_path(file1)) with self.assertRaises(ValueError): # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", file1]) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument("--path", nargs="+", action=PathExistsAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_path(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_path(file1)) # Assemble mixed list of existing and nonexisting paths paths = [dir1, file1] with self.assertRaises(ValueError): self.parser.parse_args(["--path", *paths]) class TestPathDoesNotExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=PathDoesNotExistsAction) # Specify file to check with tempfile.NamedTemporaryFile() as file1: with self.assertRaises(ValueError): # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", file1.name]) def test_on_nonexisting_path(self): self.parser.add_argument("--path", action=PathDoesNotExistsAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_path(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_path(file1)) # Parse args with --path as specified file self.parser.parse_args(["--path", file1]) # Assert specified file no longer exists self.assertFalse(is_existing_path(file1)) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument( "--path", nargs="+", action=PathDoesNotExistsAction ) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_path(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_path(file1)) # Assemble mixed list of existing and nonexisting paths paths = [dir1, file1] with self.assertRaises(ValueError): self.parser.parse_args(["--path", *paths]) class TestFileExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=FileExistsAction) # Specify file to check with tempfile.NamedTemporaryFile() as file1: # Assert specified file exists self.assertTrue(is_existing_file(file1.name)) # Parse args with --path as specified file self.parser.parse_args(["--path", file1.name]) # Assert specified file still exists self.assertTrue(is_existing_file(file1.name)) def test_on_nonexisting_file(self): self.parser.add_argument("--path", action=FileExistsAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_file(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_file(file1)) with self.assertRaises(ValueError): # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", file1]) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument("--path", nargs="+", action=FileExistsAction) with tempfile.TemporaryDirectory() as directory: # Specify file to check file1 = tempfile.mkstemp(dir=directory)[1] file2 = tempfile.mkstemp(dir=directory)[1] file3 = tempfile.mkstemp(dir=directory)[1] # Assert specified files exists self.assertTrue(is_existing_file(file1)) self.assertTrue(is_existing_file(file2)) self.assertTrue(is_existing_file(file3)) # Remove file 1 os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_file(file1)) # Assemble mixed list of existing and nonexisting paths paths = [file1, file2, file3] with self.assertRaises(ValueError): self.parser.parse_args(["--path", *paths]) class TestFileDoesNotExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=FileDoesNotExistAction) # Specify file to check with tempfile.NamedTemporaryFile() as file1: with self.assertRaises(ValueError): # Parse args with --path as specified file that does not exist self.parser.parse_args(["--path", file1.name]) def test_on_nonexisting_path(self): self.parser.add_argument("--path", action=FileDoesNotExistAction) with tempfile.TemporaryDirectory() as dir1: # Specify a file to check file1 = tempfile.mkstemp(dir=dir1)[1] # Assert specified file exists self.assertTrue(is_existing_file(file1)) # Remove file os.remove(file1) # Assert specified file no longer exists self.assertFalse(is_existing_file(file1)) # Parse args with --path as specified file self.parser.parse_args(["--path", file1]) # Assert specified file no longer exists self.assertFalse(is_existing_file(file1)) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument( "--path", nargs="+", action=FileDoesNotExistAction ) # Specify a file to check file1 = tempfile.mkstemp()[1] file2 = tempfile.mkstemp()[1] # Assert specified file exists self.assertTrue(is_existing_file(file1)) self.assertTrue(is_existing_file(file2)) # Remove file os.remove(file1) self.assertFalse(is_existing_file(file1)) # Assemble mixed list of existing and nonexisting paths paths = [file1, file2] with self.assertRaises(ValueError): self.parser.parse_args(["--path", *paths]) # Tear down remaining temporary files os.remove(file2) class TestDirectoryExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=DirectoryExistsAction) # Specify directory to check with tempfile.TemporaryDirectory() as dir1: # Assert specified directory exists self.assertTrue(is_existing_directory(dir1)) # Parse args with --path as specified directory args = self.parser.parse_args(["--path", dir1]) # Assert specified directory still exists self.assertTrue(is_existing_path(dir1)) self.assertTrue(is_existing_path(args.path)) def test_on_nonexisting_path(self): self.parser.add_argument("--path", action=DirectoryExistsAction) # Specifiy directory dir1 = tempfile.mkdtemp() # Assert specified directory exists self.assertTrue(is_existing_directory(dir1)) # Remove specified directory os.rmdir(dir1) # Assert specified directory doesnt exist self.assertFalse(is_existing_directory(dir1)) with self.assertRaises(ValueError): # Parse args with list of paths self.parser.parse_args(["--path", dir1]) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument("--path", action=DirectoryExistsAction) # Specifiy directores dir1 = tempfile.mkdtemp() dir2 = tempfile.mkdtemp() # Assert specified directory exists self.assertTrue(is_existing_directory(dir1)) self.assertTrue(is_existing_directory(dir2)) # Remove specified directory os.rmdir(dir1) # Assert specified directory doesnt exist self.assertFalse(is_existing_directory(dir1)) with self.assertRaises(ValueError): # Parse args with list of paths self.parser.parse_args(["--path", dir1, dir2]) class TestDirectoryDoesNotExistsAction(ActionHeroTestCase): def test_on_existing_path(self): self.parser.add_argument("--path", action=DirectoryDoesNotExistAction) with tempfile.TemporaryDirectory() as dir1: with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_nonexisting_path(self): self.parser.add_argument("--path", action=DirectoryDoesNotExistAction) # Specify directory dir1 = tempfile.mkdtemp() # Assert directory exists self.assertTrue(is_existing_directory(dir1)) # Remove specified directory os.rmdir(dir1) # Pargs args with removed specified directory self.parser.parse_args(["--path", dir1]) def test_on_mixed_existing_and_nonexisting_path(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryDoesNotExistAction ) # Specify directories dir1 = tempfile.mkdtemp() dir2 = tempfile.mkdtemp() # Assert directories exists self.assertTrue(is_existing_directory(dir1)) self.assertTrue(is_existing_directory(dir2)) # Remove one specified directory os.rmdir(dir1) # Pargs args with one removed specified directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) # Tear down remaining temporary directories os.rmdir(dir2) class TestFileIsWritableAction(ActionHeroTestCase): def test_on_writable_file(self): self.parser.add_argument("--path", action=FileIsWritableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert fil eis writable self.assertTrue(is_writable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) # Assert file is still writable self.assertTrue(is_writable_file(file1.name)) def test_on_unwritable_file(self): self.parser.add_argument("--path", action=FileIsWritableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert fileis writable self.assertTrue(is_writable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) def test_on_mixed_writable_and_unwritable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify writable and unwritable file file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_write_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestFileIsNotWritableAction(ActionHeroTestCase): def test_on_writable_file(self): self.parser.add_argument("--path", action=FileIsNotWritableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is writable self.assertTrue(is_writable_file(file1.name)) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_unwritable_file(self): self.parser.add_argument("--path", action=FileIsNotWritableAction) with tempfile.TemporaryDirectory() as dir1: # Specify file and remove write permission file1 = tempfile.mkstemp(dir=dir1)[1] remove_write_permission(file1) # Assert file is unwritable self.assertFalse(is_writable_file(file1)) # No Error on parse args self.parser.parse_args(["--path", file1]) # Assert file is unwritable self.assertFalse(is_writable_file(file1)) def test_on_mixed_writable_and_unwritable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsNotWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify writable and unwritable files file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_write_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestDirectoryIsWritableAction(ActionHeroTestCase): def test_on_writable_directory(self): self.parser.add_argument("--path", action=DirectoryIsWritableAction) # Specify writable directory with tempfile.TemporaryDirectory() as dir1: # Parse with readable directory self.parser.parse_args(["--path", dir1]) def test_on_wunwritable_directory(self): self.parser.add_argument("--path", action=DirectoryIsWritableAction) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir2]) def test_on_writable_and_unwritable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestDirectoryIsNotWritableAction(ActionHeroTestCase): def test_on_writable_directory(self): self.parser.add_argument("--path", action=DirectoryIsNotWritableAction) # Specify writable directory with tempfile.TemporaryDirectory() as dir1: # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unwritable_directory(self): self.parser.add_argument("--path", action=DirectoryIsNotWritableAction) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Parse with readable directory self.parser.parse_args(["--path", dir2]) def test_on_writable_and_unwritable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsNotWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsWritableAction(ActionHeroTestCase): def test_on_writable_directory(self): self.parser.add_argument("--path", action=PathIsWritableAction) # Specify writable directory with tempfile.TemporaryDirectory() as dir1: # Parse with readable directory self.parser.parse_args(["--path", dir1]) def test_on_unwritable_directory(self): self.parser.add_argument("--path", action=PathIsWritableAction) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir2]) def test_on_writable_and_unwritable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsNotWritableAction(ActionHeroTestCase): def test_on_writable_directory(self): self.parser.add_argument("--path", action=PathIsNotWritableAction) # Specify writable directory with tempfile.TemporaryDirectory() as dir1: # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unwritable_directory(self): self.parser.add_argument("--path", action=PathIsNotWritableAction) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Parse with readable directory self.parser.parse_args(["--path", dir2]) def test_on_writable_and_unwritable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsNotWritableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify unwritable directory and remove write permissions dir2 = tempfile.mkdtemp(dir=dir1) remove_write_permission(dir2) # Asserts error on parsing unwritable directory with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestFileIsReadableAction(ActionHeroTestCase): def test_on_readable_file(self): self.parser.add_argument("--path", action=FileIsReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) # Assert file is still readable self.assertTrue(is_readable_file(file1.name)) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=FileIsReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) def test_on_mixed_readable_and_unreadable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsReadableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable file file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_read_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestFileIsNotReadableAction(ActionHeroTestCase): def test_on_readable_file(self): self.parser.add_argument("--path", action=FileIsNotReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=FileIsNotReadableAction) with tempfile.TemporaryDirectory() as dir1: # Specify file and remove write permission file1 = tempfile.mkstemp(dir=dir1)[1] remove_read_permission(file1) # Assert file is unreadable self.assertFalse(is_readable_file(file1)) # No Error on parse args self.parser.parse_args(["--path", file1]) # Assert file is unreadable self.assertFalse(is_readable_file(file1)) def test_on_mixed_readable_and_unreadable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsNotReadableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable files file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_write_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestDirectoryIsReadableAction(ActionHeroTestCase): def test_on_readable_directory(self): self.parser.add_argument("--path", action=DirectoryIsReadableAction) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is readable self.assertTrue(is_readable_directory(dir1)) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still readable self.assertTrue(is_readable_directory(dir1)) def test_on_unreadable_directory(self): self.parser.add_argument("--path", action=DirectoryIsReadableAction) # Specify dir amd make unreadable dir1 = tempfile.mkdtemp() remove_read_permission(dir1) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) # Tear down temp dirs os.rmdir(dir1) def test_on_mixed_readable_and_unreadable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsReadableAction ) # Specify readable and unreadable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_read_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestDirectoryIsNotReadableAction(ActionHeroTestCase): def test_on_readable_directory(self): self.parser.add_argument("--path", action=DirectoryIsNotReadableAction) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is readable self.assertTrue(is_readable_directory(dir1)) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unreadable_directory(self): self.parser.add_argument("--path", action=DirectoryIsNotReadableAction) # Specify dir amd make unreadable dir1 = tempfile.mkdtemp() remove_read_permission(dir1) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still unreadable self.assertFalse(is_readable_directory(dir1)) # Tear down temp dirs os.rmdir(dir1) def test_on_mixed_readable_and_unreadable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsNotReadableAction ) # Specify readable and unreadable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_read_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsReadableAction(ActionHeroTestCase): def test_on_readable_file(self): self.parser.add_argument("--path", action=PathIsReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) # Assert file is still readable self.assertTrue(is_readable_file(file1.name)) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=PathIsReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) def test_on_mixed_readable_and_unreadable_file(self): self.parser.add_argument( "--path", nargs="+", action=PathIsReadableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable file file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_read_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) def test_on_readable_directory(self): self.parser.add_argument("--path", action=PathIsReadableAction) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is readable self.assertTrue(is_readable_directory(dir1)) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still readable self.assertTrue(is_readable_directory(dir1)) def test_on_unreadable_directory(self): self.parser.add_argument("--path", action=PathIsReadableAction) # Specify dir amd make unreadable dir1 = tempfile.mkdtemp() remove_read_permission(dir1) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) # Tear down temp dirs os.rmdir(dir1) def test_on_mixed_readable_and_unreadable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsReadableAction ) # Specify readable and unreadable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_read_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsNotReadableAction(ActionHeroTestCase): def test_on_readable_file(self): self.parser.add_argument("--path", action=PathIsNotReadableAction) # Specify file with tempfile.NamedTemporaryFile() as file1: # Assert file is readable self.assertTrue(is_readable_file(file1.name)) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=PathIsNotReadableAction) with tempfile.TemporaryDirectory() as dir1: # Specify file and remove write permission file1 = tempfile.mkstemp(dir=dir1)[1] remove_read_permission(file1) # Assert file is unreadable self.assertFalse(is_readable_file(file1)) # No Error on parse args self.parser.parse_args(["--path", file1]) # Assert file is unreadable self.assertFalse(is_readable_path(file1)) def test_on_mixed_readable_and_unreadable_file(self): self.parser.add_argument( "--path", nargs="+", action=PathIsNotReadableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable files file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] remove_write_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) def test_on_readable_directory(self): self.parser.add_argument("--path", action=PathIsNotReadableAction) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is readable self.assertTrue(is_readable_directory(dir1)) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unreadable_directory(self): self.parser.add_argument("--path", action=PathIsNotReadableAction) # Specify dir amd make unreadable dir1 = tempfile.mkdtemp() remove_read_permission(dir1) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still unreadable self.assertFalse(is_readable_directory(dir1)) # Tear down temp dirs os.rmdir(dir1) def test_on_mixed_readable_and_unreadable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsNotReadableAction ) # Specify readable and unreadable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_read_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestFileIsExecutableAction(ActionHeroTestCase): def test_on_executable_file(self): self.parser.add_argument("--path", action=FileIsExecutableAction) # Specify file and make executable with tempfile.NamedTemporaryFile() as file1: add_execute_permission(file1.name) self.assertTrue(is_executable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) def test_on_unexecutable_file(self): self.parser.add_argument("--path", action=FileIsExecutableAction) # Specify file and assert not executable with tempfile.NamedTemporaryFile() as file1: self.assertFalse(is_executable_file(file1.name)) # Assert ValueError on parsing with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_mixed_executable_and_unexecutable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsExecutableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable file file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] add_execute_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestFileIsNotExecutableAction(ActionHeroTestCase): def test_on_executable_file(self): self.parser.add_argument("--path", action=FileIsNotExecutableAction) # Specify file and make executable with tempfile.NamedTemporaryFile() as file1: add_execute_permission(file1.name) self.assertTrue(is_executable_file(file1.name)) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=FileIsNotExecutableAction) with tempfile.TemporaryDirectory() as dir1: # Specify file and remove write permission file1 = tempfile.mkstemp(dir=dir1)[1] # Assert file is unexecutable self.assertFalse(is_executable_file(file1)) # No Error on parse args self.parser.parse_args(["--path", file1]) # Assert file is unexecutable self.assertFalse(is_executable_file(file1)) def test_on_mixed_executable_and_unexecutable_file(self): self.parser.add_argument( "--path", nargs="+", action=FileIsNotExecutableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify executable and unexecutable files file1 = tempfile.mkstemp(dir=dir1)[1] add_execute_permission(file1) file2 = tempfile.mkstemp(dir=dir1)[1] # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) class TestDirectoryIsExecutableAction(ActionHeroTestCase): def test_on_executable_directory(self): self.parser.add_argument("--path", action=DirectoryIsExecutableAction) # Specify directory and make executable with tempfile.TemporaryDirectory() as dir1: self.assertTrue(is_executable_directory(dir1)) # No errors when parsing args self.parser.parse_args(["--path", dir1]) def test_on_unexecutable_directory(self): self.parser.add_argument("--path", action=DirectoryIsExecutableAction) # Specify dir and make unexecutable with tempfile.TemporaryDirectory() as dir1: remove_execute_permission(dir1) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_mixed_executable_and_unexecutable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsExecutableAction ) # Specify executable and unexecutable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_execute_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestDirectoryIsNotExecutableAction(ActionHeroTestCase): def test_on_executable_directory(self): self.parser.add_argument( "--path", action=DirectoryIsNotExecutableAction ) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is executable self.assertTrue(is_executable_directory(dir1)) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unexecutable_directory(self): self.parser.add_argument( "--path", action=DirectoryIsNotExecutableAction ) # Specify dir amd make unexecutable with tempfile.TemporaryDirectory() as dir1: dir1 = tempfile.mkdtemp() remove_execute_permission(dir1) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still unreadable self.assertFalse(is_executable_directory(dir1)) def test_on_mixed_executable_and_unexecutable_directories(self): self.parser.add_argument( "--path", nargs="+", action=DirectoryIsNotExecutableAction ) # Specify executable and unexecutable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_execute_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsExecutableAction(ActionHeroTestCase): def test_on_executable_file(self): self.parser.add_argument("--path", action=PathIsExecutableAction) # Specify file and make executable with tempfile.NamedTemporaryFile() as file1: add_execute_permission(file1.name) self.assertTrue(is_executable_file(file1.name)) # No errors when parsing args self.parser.parse_args(["--path", file1.name]) def test_on_unexecutable_file(self): self.parser.add_argument("--path", action=PathIsExecutableAction) # Specify file and assert not executable with tempfile.NamedTemporaryFile() as file1: self.assertFalse(is_executable_file(file1.name)) # Assert ValueError on parsing with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_mixed_executable_and_unexecutable_file(self): self.parser.add_argument( "--path", nargs="+", action=PathIsExecutableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify readable and unreadable file file1 = tempfile.mkstemp(dir=dir1)[1] file2 = tempfile.mkstemp(dir=dir1)[1] add_execute_permission(file2) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) def test_on_executable_directory(self): self.parser.add_argument("--path", action=PathIsExecutableAction) # Specify directory and make executable with tempfile.TemporaryDirectory() as dir1: self.assertTrue(is_executable_directory(dir1)) # No errors when parsing args self.parser.parse_args(["--path", dir1]) def test_on_unexecutable_directory(self): self.parser.add_argument("--path", action=PathIsExecutableAction) # Specify dir and make unexecutable with tempfile.TemporaryDirectory() as dir1: remove_execute_permission(dir1) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_mixed_executable_and_unexecutable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsExecutableAction ) # Specify executable and unexecutable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_execute_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestPathIsNotExecutableAction(ActionHeroTestCase): def test_on_executable_file(self): self.parser.add_argument("--path", action=PathIsNotExecutableAction) # Specify file and make executable with tempfile.NamedTemporaryFile() as file1: add_execute_permission(file1.name) self.assertTrue(is_executable_file(file1.name)) # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_unreadable_file(self): self.parser.add_argument("--path", action=PathIsNotExecutableAction) with tempfile.TemporaryDirectory() as dir1: # Specify file and remove write permission file1 = tempfile.mkstemp(dir=dir1)[1] # Assert file is unexecutable self.assertFalse(is_executable_file(file1)) # No Error on parse args self.parser.parse_args(["--path", file1]) # Assert file is unexecutable self.assertFalse(is_executable_file(file1)) def test_on_mixed_executable_and_unexecutable_file(self): self.parser.add_argument( "--path", nargs="+", action=PathIsNotExecutableAction ) with tempfile.TemporaryDirectory() as dir1: # Specify executable and unexecutable files file1 = tempfile.mkstemp(dir=dir1)[1] add_execute_permission(file1) file2 = tempfile.mkstemp(dir=dir1)[1] # Check if ValueError raised on parse with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1, file2]) def test_on_executable_directory(self): self.parser.add_argument("--path", action=PathIsNotExecutableAction) # Specify directory with tempfile.TemporaryDirectory() as dir1: # Assert directory is executable self.assertTrue(is_executable_directory(dir1)) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1]) def test_on_unexecutable_directory(self): self.parser.add_argument("--path", action=PathIsNotExecutableAction) # Specify dir amd make unexecutable with tempfile.TemporaryDirectory() as dir1: dir1 = tempfile.mkdtemp() remove_execute_permission(dir1) # No errors when parsing args self.parser.parse_args(["--path", dir1]) # Assert directory is still unreadable self.assertFalse(is_executable_directory(dir1)) def test_on_mixed_executable_and_unexecutable_directories(self): self.parser.add_argument( "--path", nargs="+", action=PathIsNotExecutableAction ) # Specify executable and unexecutable dirs with tempfile.TemporaryDirectory() as dir1: dir2 = tempfile.mkdtemp() remove_execute_permission(dir2) # Assert ValueError raised when parsing args with self.assertRaises(ValueError): self.parser.parse_args(["--path", dir1, dir2]) class TestFileIsEmptyAction(ActionHeroTestCase): def test_on_empty_file(self): self.parser.add_argument("--path", action=FileIsEmptyAction) with tempfile.NamedTemporaryFile() as file1: self.assertTrue(is_empty_file(file1.name)) self.parser.parse_args(["--path", file1.name]) def test_on_nonempty_file(self): self.parser.add_argument("--path", action=FileIsEmptyAction) with tempfile.NamedTemporaryFile() as file1: with open(file1.name, "a") as file_for_writing: file_for_writing.write("SOME TEXT") self.assertFalse(is_empty_file(file1.name)) with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_list_of_empty_and_nonempty_files(self): self.parser.add_argument("--path", nargs="+", action=FileIsEmptyAction) with tempfile.NamedTemporaryFile() as file1: with tempfile.NamedTemporaryFile() as file2: with open(file2.name, "a") as file_for_writing: file_for_writing.write("SOME TEXT") self.assertTrue(is_empty_file(file1.name)) self.assertFalse(is_empty_file(file2.name)) with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name, file2.name]) class TestFileIsNotEmptyAction(ActionHeroTestCase): def test_on_empty_file(self): self.parser.add_argument("--path", action=FileIsNotEmptyAction) with tempfile.NamedTemporaryFile() as file1: self.assertTrue(is_empty_file(file1.name)) with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name]) def test_on_nonempty_file(self): self.parser.add_argument("--path", action=FileIsNotEmptyAction) with tempfile.NamedTemporaryFile() as file1: with open(file1.name, "a") as file_for_writing: file_for_writing.write("SOME TEXT") self.assertFalse(is_empty_file(file1.name)) self.parser.parse_args(["--path", file1.name]) def test_on_list_of_empty_and_nonempty_files(self): self.parser.add_argument( "--path", nargs="+", action=FileIsNotEmptyAction ) with tempfile.NamedTemporaryFile() as file1: with tempfile.NamedTemporaryFile() as file2: with open(file2.name, "a") as file_for_writing: file_for_writing.write("SOME TEXT") self.assertTrue(is_empty_file(file1.name)) self.assertFalse(is_empty_file(file2.name)) with self.assertRaises(ValueError): self.parser.parse_args(["--path", file1.name, file2.name]) class TestFileHasExtensionAction(ActionHeroTestCase): def test_on_parser_with_extension(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["txt"] ) def test_on_parser_without_extension(self): with self.assertRaises(ValueError): self.parser.add_argument( "--filename", action=FileHasExtensionAction ) def test_on_filename_with_matching_extension(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["txt"] ) self.parser.parse_args(["--filename", "diary.txt"]) def test_on_filename_with_nonmatching_extension(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["txt"] ) with self.assertRaises(ValueError): self.parser.parse_args(["--filename", "diary.md"]) def test_on_list_of_filenames_with_matching_extension(self): self.parser.add_argument( "--filename", nargs="+", action=FileHasExtensionAction, action_values=["txt"], ) self.parser.parse_args( ["--filename", "diary.txt", "log.txt", "lyrics.txt"] ) def test_on_list_of_filenames_with_nonmatching_extension(self): self.parser.add_argument( "--filename", nargs="+", action=FileHasExtensionAction, action_values=["txt"], ) with self.assertRaises(ValueError): self.parser.parse_args( ["--filename", "diary.md", "README.rst", "history.sh"] ) def test_on_list_of_filenames_with_mixed_matching_extensions(self): self.parser.add_argument( "--filename", nargs="+", action=FileHasExtensionAction, action_values=["txt"], ) with self.assertRaises(ValueError): self.parser.parse_args( [ "--filename", "notes.txt", "diary.md", "README.rst", "history.sh", ] ) def test_on_multiple_action_values(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["md", "markdown"], ) self.parser.parse_args(["--filename", "diary.md"]) def test_on_multiple_action_values_with_expected_filenames(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["md", "markdown"], ) with self.assertRaises(ValueError): self.parser.parse_args( ["--filename", "README.md", "blogentry.markdown"] ) def test_on_multiple_action_values_with_unexpected_filenames(self): self.parser.add_argument( "--filename", action=FileHasExtensionAction, action_values=["md", "markdown"], ) with self.assertRaises(ValueError): self.parser.parse_args(["--filename", "config.yml"]) def test_on_multiple_action_values_with_mixed_expected_filenames(self): self.parser.add_argument( "--filename", nargs="+", action=FileHasExtensionAction, action_values=["md", "markdown"], ) with self.assertRaises(ValueError): self.parser.parse_args(["--filename", "config.yml", "README.rst"])

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7ead05d3f9b40123d5b838866a8a290b3a4e5104

21,378

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Python

project/grid.py

Kyle-Tran/Game-of-Life

ebb65956e42393444857e3fcc9389f8dae2a62f0

[ "MIT" ]

1

2021-07-19T16:29:28.000Z

project/grid.py

Kyle-Tran/Game-of-Life

ebb65956e42393444857e3fcc9389f8dae2a62f0

[ "MIT" ]

null

project/grid.py

Kyle-Tran/Game-of-Life

ebb65956e42393444857e3fcc9389f8dae2a62f0

[ "MIT" ]

null

import pygame, random import numpy as np class Conway: ################################### # Class for Conway's Game of Life # ################################### def __init__(self, width, height, scale, border, percentRandom): self.scale = scale self.rows = int(width / scale) self.columns = int(height / scale) self.size = (self.rows, self.columns) self.curr_array = np.ndarray(shape=self.size) # Field as 2d array self.border = border # Lines between cells self.percentRandom = percentRandom def update(self, dead, live, surface): """ Updates cells color correlating to dead or live """ for x in range(self.rows): for y in range(self.columns): x_pos, y_pos = x * self.scale, y * self.scale if self.curr_array[x][y] == 1: pygame.draw.rect(surface, live, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) else: pygame.draw.rect(surface, dead, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) def transition(self): """ Rules for transitions between generations """ new_array = np.ndarray(shape=self.size) for x in range(self.rows): for y in range(self.columns): state = self.curr_array[x][y] neighbors = self.get_neighbors(x, y) # Any live cell with two or three live neighbors survives. if state == 1 and (neighbors == 2 or neighbors == 3): new_array[x][y] = 1 # Any dead cell with three live neighbors becomes a live cell. elif state == 0 and neighbors == 3: new_array[x][y] = 1 # All other live cells die in the next generation. # Similarly, all other dead cells stay dead. else: new_array[x][y] = 0 # update previous field with next generation's field self.curr_array = new_array def get_neighbors(self, x, y): """ Check state of 8 cells around current cell Returns number of live neighbors """ neighbors = 0 for n in range(-1, 2): for m in range(-1, 2): if not (n == m == 0): # Ignore self during check # Since field is finite, stitch edges to yield toroidal array x_edge = (x + n + self.rows) % self.rows y_edge = (y + m + self.columns) % self.columns neighbors += self.curr_array[x_edge][y_edge] return neighbors def click(self, pos): """ Clicking on cell will change it's state from dead to live or vice versa """ x, y = int(pos[0] / self.scale), int(pos[1] / self.scale) if self.curr_array[x][y] == 1: self.curr_array[x][y] = 0 else: self.curr_array[x][y] = 1 def random_field(self): """ Generates random field of cells """ for x in range(self.rows): for y in range(self.columns): # self.curr_array[x][y] = random.randint(0, 1) self.curr_array[x][y] = random.choices( [0, 1], [1 - self.percentRandom, self.percentRandom])[0] # Fills grid with percentRandom live cells def reset(self): """ Clears entire field to all dead cells """ for x in range(self.rows): for y in range(self.columns): self.curr_array[x][y] = 0 class RPS: ############################################### # Class for ternary/quinary multi-state world # ############################################### # Rock = -1, White = 0, Paper = 1, Scissors = 2, Lizard = 3, Spock = 4 def __init__(self, width, height, scale, border, numColors): self.scale = scale self.rows = int(width / scale) self.columns = int(height / scale) self.size = (self.rows, self.columns) self.curr_array = np.ndarray(shape=self.size) # Field as 2d array self.border = border # Lines between cells self.numColors = numColors def update(self, rock, paper, scissors, lizard, spock, surface): """ Updates cells colors on field """ for x in range(self.rows): for y in range(self.columns): x_pos, y_pos = x * self.scale, y * self.scale curr = self.curr_array[x][y] if -1 < curr < 1: # Fix rounding error near 0 for numpy array pygame.draw.rect(surface, (255, 255, 255), [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) elif curr == -1: pygame.draw.rect(surface, rock, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) elif curr == 1: pygame.draw.rect(surface, paper, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) elif curr == 2: pygame.draw.rect(surface, scissors, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) elif curr == 3 and self.numColors == 5: pygame.draw.rect(surface, lizard, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) elif curr == 4 and self.numColors == 5: pygame.draw.rect(surface, spock, [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) def transition(self): """ Updates current field with next generation field """ new_array = np.ndarray(shape=self.size) for x in range(self.rows): for y in range(self.columns): state = self.curr_array[x][y] neighbors, dominating = self.get_neighbors(x, y, state) if neighbors > 2: # if more than 2 cells dominate current cell, convert cell # if current cell is touched by more than 2 cells of both dominating colors, # then convert current cell to the dominant color with the greater frequency # Example: Rock surrounded by 3 paper and 5 spock, rock becomes spock new_array[x][y] = most_freq(dominating) else: # otherwise cell stays the same new_array[x][y] = state # update previous field with next generation's field self.curr_array = new_array def get_neighbors(self, x, y, state): """ Rules for transitions between generations total: number of dominant neighbors num_dominating: list of dominant neighbors Example: state = rock, total = 8 num_dominating = [paper, paper, paper, spock, spock, spock, spock, spock] """ total, num_dominating = 0, [] # check 8 cells around current cell for n in range(-1, 2): for m in range(-1, 2): if not (n == m == 0): # Ignore self during check # Since field is finite, stitch edges to yield toroidal array x_edge = (x + n + self.rows) % self.rows y_edge = (y + m + self.columns) % self.columns neighbor = self.curr_array[x_edge][y_edge] if self.numColors == 3: # Normal Rock, Paper, Scissor rules if (state == -1 and neighbor == 1) or (state == 1 and neighbor == 2) \ or (state == 2 and neighbor == -1): total += 1 num_dominating.append(neighbor) elif self.numColors == 5: # Rock (-1), Paper (1), Scissor(2), Lizard(3), Spock(4) rules # Rock > Scissors, Lizard # Paper > Rock, Spock # Scissors > Paper, Lizard # Lizard > Paper, Spock # Spock > Scissors, Rock if (state == -1 and (neighbor == 1 or neighbor == 4)) or \ (state == 1 and (neighbor == 2 or neighbor == 3)) \ or (state == 2 and (neighbor == -1 or neighbor == 4)) \ or (state == 3 and (neighbor == -1 or neighbor == 2)) \ or (state == 4 and (neighbor == 1 or neighbor == 3)): total += 1 num_dominating.append(neighbor) return total, num_dominating def click(self, pos, choice): """ Clicking on cell will change it's state to choice of color currently pressed (1-5) Default is white """ x, y = int(pos[0] / self.scale), int(pos[1] / self.scale) self.curr_array[x][y] = choice def random_field(self): """ Generates random field of cells """ for x in range(self.rows): for y in range(self.columns): if self.numColors == 3: self.curr_array[x][y] = random.choices([-1, 1, 2])[0] elif self.numColors == 5: self.curr_array[x][y] = random.choices([-1, 1, 2, 3, 4])[0] def reset(self): """ Clears entire field to all white cells """ for x in range(self.rows): for y in range(self.columns): self.curr_array[x][y] = 0 def most_freq(neighbors): """ Returns the dominant color with the greater frequency Example: num_dominating = [paper, paper, paper, spock, spock, spock, spock, spock] Returns: spock """ return max(set(neighbors), key=neighbors.count) class Langton: ########################### # Class for Langton's Ant # ########################### def __init__(self, width, height, scale, border, colors, rules): self.scale = scale self.rows = int(width / scale) self.columns = int(height / scale) self.size = (self.rows, self.columns) self.curr_array = np.ndarray(shape=self.size) # Field as 2d array self.border = border # Lines between cells self.direction = "N" # N, E, S, W self.ant = (-1, -1) # Ant current position on field # Colors [(x,y,z), ..., (xn,yn,zn)], Rules = "RL..." self.rules = rules self.colors = colors def transition(self, surface): """ Updates cells colors on field between each transition """ ant_xpos, ant_ypos = self.ant[0], self.ant[1] ant_xcoord, ant_ycoord = ant_xpos * self.scale, ant_ypos * self.scale if self.curr_array[ant_xpos][ant_ypos] == -1: # curr cell is white (default) self.curr_array[ant_xpos][ant_ypos] = 0 # change cell to first color self.rotate(self.rules[0]) # rotate direction based on first rule # Update color of cell ant is currently on # Move ant forward in current direction # Draw ant on that forward cell pygame.draw.rect(surface, self.colors[0], [ant_xcoord, ant_ycoord, self.scale - self.border, self.scale - self.border]) self.move() pygame.draw.rect(surface, (255, 0, 0), [self.ant[0] * self.scale, self.ant[1] * self.scale, self.scale - self.border, self.scale - self.border]) else: # updates value of cell to n+1 color # if end of color list, return to index 0 update_idx = (int(self.curr_array[ant_xpos][ant_ypos]) + 1) % len(self.colors) self.curr_array[ant_xpos][ant_ypos] = update_idx # rotate direction based on rule of next color self.rotate(self.rules[update_idx]) # Update color of cell ant is currently on # Move ant forward in current direction # Draw ant on that forward cell pygame.draw.rect(surface, self.colors[update_idx], [ant_xcoord, ant_ycoord, self.scale - self.border, self.scale - self.border]) self.move() pygame.draw.rect(surface, (255, 0, 0), [self.ant[0] * self.scale, self.ant[1] * self.scale, self.scale - self.border, self.scale - self.border]) def move(self): """ Changes ant's current location to cell 1 away in it's current direction """ x, y = self.ant[0], self.ant[1] # Stitches field for when ant is at edge addx, addy = (x + 1) % self.rows, (y+1) % self.columns minusx, minusy = (x - 1) % self.rows, (y - 1) % self.columns if self.direction == "N": self.ant = (x, minusy) elif self.direction == "E": self.ant = (addx, y) elif self.direction == "S": self.ant = (x, addy) elif self.direction == "W": self.ant = (minusx, y) def rotate(self, rule): """ Changes current direction based on rule """ if rule == "R": if self.direction == "N": self.direction = "E" elif self.direction == "E": self.direction = "S" elif self.direction == "S": self.direction = "W" elif self.direction == "W": self.direction = "N" elif rule == "L": if self.direction == "N": self.direction = "W" elif self.direction == "E": self.direction = "N" elif self.direction == "S": self.direction = "E" elif self.direction == "W": self.direction = "S" def click(self, pos, direction, surface): """ Clicking on cell spawns ant in specified direction """ x, y = int(pos[0] / self.scale), int(pos[1] / self.scale) prev_x, prev_y = self.ant[0] * self.scale, self.ant[1] * self.scale new_x, new_y = x * self.scale, y * self.scale if self.ant != (-1, -1): # There is an ant on the field currently # make sure previous cell where ant was can still update later # by making that cell empty (white) self.curr_array[self.ant[0], self.ant[1]] = -1 # On clicking, deletes previous ant pygame.draw.rect(surface, (255, 255, 255), [prev_x, prev_y, self.scale - self.border, self.scale - self.border]) # Creates new ant in specified direction self.ant = (x, y) pygame.draw.rect(surface, (255, 0, 0), [new_x, new_y, self.scale - self.border, self.scale - self.border]) self.direction = direction def reset(self, surface): """ Clears entire field to all dead cells """ for x in range(self.rows): for y in range(self.columns): x_pos, y_pos = x * self.scale, y * self.scale self.curr_array[x][y] = -1 # initial field array to all empty (-1) pygame.draw.rect(surface, (255, 255, 255), [x_pos, y_pos, self.scale - self.border, self.scale - self.border]) class Turmite: ###################### # Class for Turmites # ###################### def __init__(self, width, height, scale, border, colors, rules): self.scale = scale self.rows = int(width / scale) self.columns = int(height / scale) self.size = (self.rows, self.columns) self.curr_array = np.ndarray(shape=self.size) # Field as 2d array self.border = border # Lines between cells self.direction = "N" # N, E, S, W self.ant = (-1, -1) # Ant current position on field # Colors [(x,y,z), ..., (xn,yn,zn)], Rules = "RL..." self.rules = rules self.colors = colors def transition(self, surface): """ Updates cells colors on field between each transition """ ant_xpos, ant_ypos = self.ant[0], self.ant[1] ant_xcoord, ant_ycoord = ant_xpos * self.scale, ant_ypos * self.scale if self.curr_array[ant_xpos][ant_ypos] == -1: # curr cell is white (default) self.curr_array[ant_xpos][ant_ypos] = 0 # change cell to first color self.rotate(self.rules[0]) # rotate direction based on first rule # Update color of cell ant is currently on # Move ant forward in current direction # Draw ant on that forward cell pygame.draw.rect(surface, self.colors[0], [ant_xcoord, ant_ycoord, self.scale - self.border, self.scale - self.border]) self.move() pygame.draw.rect(surface, (255, 0, 0), [self.ant[0] * self.scale, self.ant[1] * self.scale, self.scale - self.border, self.scale - self.border]) else: # updates value of cell to n+1 color # if end of color list, return to index 0 update_idx = (int(self.curr_array[ant_xpos][ant_ypos]) + 1) % len(self.colors) self.curr_array[ant_xpos][ant_ypos] = update_idx # rotate direction based on rule of next color self.rotate(self.rules[update_idx]) # Update color of cell ant is currently on # Move ant forward in current direction # Draw ant on that forward cell pygame.draw.rect(surface, self.colors[update_idx], [ant_xcoord, ant_ycoord, self.scale - self.border, self.scale - self.border]) self.move() pygame.draw.rect(surface, (255, 0, 0), [self.ant[0] * self.scale, self.ant[1] * self.scale, self.scale - self.border, self.scale - self.border]) def move(self): """ Changes ant's current location to cell 1 away in it's current direction """ x, y = self.ant[0], self.ant[1] # Stitches field for when ant is at edge addx, addy = (x + 1) % self.rows, (y+1) % self.columns minusx, minusy = (x - 1) % self.rows, (y - 1) % self.columns if self.direction == "N": self.ant = (x, minusy) elif self.direction == "E": self.ant = (addx, y) elif self.direction == "S": self.ant = (x, addy) elif self.direction == "W": self.ant = (minusx, y) def rotate(self, rule): """ Changes current direction based on rule """ if rule == "R": if self.direction == "N": self.direction = "E" elif self.direction == "E": self.direction = "S" elif self.direction == "S": self.direction = "W" elif self.direction == "W": self.direction = "N" elif rule == "L": if self.direction == "N": self.direction = "W" elif self.direction == "E": self.direction = "N" elif self.direction == "S": self.direction = "E" elif self.direction == "W": self.direction = "S" def click(self, pos, direction, surface): """ Clicking on cell spawns ant in specified direction """ x, y = int(pos[0] / self.scale), int(pos[1] / self.scale) prev_x, prev_y = self.ant[0] * self.scale, self.ant[1] * self.scale new_x, new_y = x * self.scale, y * self.scale if self.ant != (-1, -1): # There is an ant on the field currently # make sure previous cell where ant was can still update later # by making that cell empty (white) self.curr_array[self.ant[0], self.ant[1]] = -1 # On clicking, deletes previous ant pygame.draw.rect(surface, (255, 255, 255), [prev_x, prev_y, self.scale - self.border, self.scale - self.border]) # Creates new ant in specified direction self.ant = (x, y) pygame.draw.rect(surface, (255, 0, 0), [new_x, new_y, self.scale - self.border, self.scale - self.border]) self.direction = direction def reset(self, surface): """ Clears entire field to all dead cells """ for x in range(self.rows): for y in range(self.columns): x_pos, y_pos = x * self.scale, y * self.scale self.curr_array[x][y] = -1 # initial field array to all empty (-1) pygame.draw.rect(surface, (255, 255, 255), [x_pos, y_pos, self.scale - self.border, self.scale - self.border])

41.59144

120

0.511975

2,643

21,378

4.076807

0.088157

0.070162

0.06877

0.077587

0.836009

0.811508

0.796381

0.772065

0.740696

0.736984

0

0.018397

0.366872

21,378

514

121

41.59144

0.777687

0.214286

0

0.807818

0

0.002898

0

1

0.087948

false

0

0.006515

0

0.117264

0

null

0

1

0

1

0

null

0

7

0e3e240ac39b8e648c6ed7956774dce3d4bcc62c

503

py

Python

pyais/ais/binary_broadcast.py

reinderien/pyais

c65ad5296966b2c69da7307b8f43e991aa285cb0

[ "MIT" ]

null

pyais/ais/binary_broadcast.py

reinderien/pyais

c65ad5296966b2c69da7307b8f43e991aa285cb0

[ "MIT" ]

null

pyais/ais/binary_broadcast.py

reinderien/pyais

c65ad5296966b2c69da7307b8f43e991aa285cb0

[ "MIT" ]

null

from ..bits import Bits def decode(bits: Bits) -> dict: return {} ''' def decode_msg_8(bit_vector): """ Binary Broadcast Message TODO: data needs to be interpreted depending DAC-FID """ return { 'type': to_int(bit_vector[0:6], 2), 'repeat': to_int(bit_vector[6:8], 2), 'mmsi': to_int(bit_vector[8:38], 2), 'dac': to_int(bit_vector[40:50], 2), 'fid': to_int(bit_vector[50:56], 2), 'data': to_int(bit_vector[56::], 2), } '''

21.869565

56

0.564612

76

503

3.539474

0.447368

0.234201

0.178439

0.312268

0

0.064171

0.256461

503

22

57

22.863636

0.65508

0

0.045455

0

1

0.333333

false

0

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

0e44ae8236f3e4fbeed7b1bb625d36523b32f807

232,192

py

Python

lib/quantile_airs.py

L2UQ/airs_uq

fa12000432ba20eae6fe2222af639532528ca3b1

[ "Apache-2.0" ]

null

lib/quantile_airs.py

L2UQ/airs_uq

fa12000432ba20eae6fe2222af639532528ca3b1

[ "Apache-2.0" ]

null

lib/quantile_airs.py

L2UQ/airs_uq

fa12000432ba20eae6fe2222af639532528ca3b1

[ "Apache-2.0" ]

null

# Quantile utilities for processing MERRA/AIRS data import numpy import numpy.ma as ma import calculate_VPD import netCDF4 from netCDF4 import Dataset from numpy import random, linalg import datetime import pandas import os, sys from scipy import stats import h5py def quantile_cloud_locmask(airsdr, mtdr, indr, dtdr, yrlst, mnst, mnfn, hrchc, rgchc, msk): # Construct cloud variable quantiles and z-scores, with a possibly irregular location mask # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (airsdr) f = Dataset(rnm,'r') plev = f['level'][:] prbs = f['probability'][:] alts = f['altitude'][:] f.close() nyr = len(yrlst) nprb = prbs.shape[0] # Mask, lat, lon fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[0],hrchc) f = Dataset(fnm,'r') mask = f[msk][:,:] latmet = f['plat'][:] lonmet = f['plon'][:] f.close() mask[mask <= 0] = 0 lnsq = numpy.arange(lonmet.shape[0]) ltsq = numpy.arange(latmet.shape[0]) # Subset a bit lnsm = numpy.sum(mask,axis=0) print(lnsq.shape) print(lnsm.shape) print(lnsm) ltsm = numpy.sum(mask,axis=1) print(ltsq.shape) print(ltsm.shape) print(ltsm) lnmn = numpy.amin(lnsq[lnsm > 0]) lnmx = numpy.amax(lnsq[lnsm > 0]) + 1 ltmn = numpy.amin(ltsq[ltsm > 0]) ltmx = numpy.amax(ltsq[ltsm > 0]) + 1 stridx = 'Lon Range: %d, %d\nLat Range: %d, %d \n' % (lnmn,lnmx,ltmn,ltmx) print(stridx) #latflt = latin.flatten() #lonflt = lonin.flatten() #mskflt = mask.flatten() #lcsq = numpy.arange(mskflt.shape[0]) #lcsb = lcsq[mskflt > 0] nx = lnmx - lnmn ny = ltmx - ltmn lnrp = numpy.tile(lonmet[lnmn:lnmx],ny) ltrp = numpy.repeat(latmet[ltmn:ltmx],nx) mskblk = mask[ltmn:ltmx,lnmn:lnmx] mskflt = mskblk.flatten() tsmp = 0 for k in range(nyr): dyinit = datetime.date(yrlst[k],6,1) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) jdsq = numpy.arange(jst,jfn) print(jdsq) tmhld = numpy.repeat(jdsq,nx*ny) print(tmhld.shape) print(numpy.amin(tmhld)) print(numpy.amax(tmhld)) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing_IncludesCloudParams.h5' % (indr,yrlst[k],hrchc) f = h5py.File(fnm,'r') ctyp1 = f['/ctype'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] ctyp2 = f['/ctype2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt1 = f['/cprtop'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt2 = f['/cprtop2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb1 = f['/cprbot'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb2 = f['/cprbot2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc1 = f['/cfrac'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc2 = f['/cfrac2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc12 = f['/cfrac12'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt1 = f['/cngwat'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt2 = f['/cngwat2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp1 = f['/cstemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp2 = f['/cstemp2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() mtnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = Dataset(mtnm,'r') psfc = f.variables['spres'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() nt = ctyp1.shape[0] mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] mskstr = 'Total Obs: %d, Within Mask: %d \n' % (msksq.shape[0],msksb.shape[0]) print(mskstr) lthld = numpy.tile(ltrp,nt) lnhld = numpy.tile(lnrp,nt) ctyp1 = ctyp1.flatten() ctyp2 = ctyp2.flatten() cfrc1 = cfrc1.flatten() cfrc2 = cfrc2.flatten() cfrc12 = cfrc12.flatten() cngwt1 = cngwt1.flatten() cngwt2 = cngwt2.flatten() cttp1 = cttp1.flatten() cttp2 = cttp2.flatten() psfc = psfc.flatten() # Number of slabs nslbtmp = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) nslbtmp[(ctyp1 > 100) & (ctyp2 > 100)] = 2 nslbtmp[(ctyp1 > 100) & (ctyp2 < 100)] = 1 if tsmp == 0: nslabout = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) nslabout[:] = nslbtmp[msksb] else: nslabout = numpy.append(nslabout,nslbtmp[msksb]) flsq = numpy.arange(ctyp1.shape[0]) # For two slabs, slab 1 must have highest cloud bottom pressure cprt1 = cprt1.flatten() cprt2 = cprt2.flatten() cprb1 = cprb1.flatten() cprb2 = cprb2.flatten() slabswap = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) swpsq = flsq[(nslbtmp == 2) & (cprb1 < cprb2)] slabswap[swpsq] = 1 print(numpy.mean(slabswap)) # Cloud Pressure variables pbttmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp1[nslbtmp >= 1] = cprb1[nslbtmp >= 1] pbttmp1[swpsq] = cprb2[swpsq] ptptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp1[nslbtmp >= 1] = cprt1[nslbtmp >= 1] ptptmp1[swpsq] = cprt2[swpsq] pbttmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp2[nslbtmp == 2] = cprb2[nslbtmp == 2] pbttmp2[swpsq] = cprb1[swpsq] ptptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp2[nslbtmp == 2] = cprt2[nslbtmp == 2] ptptmp2[swpsq] = cprt1[swpsq] # DP Cloud transformation dptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp1[nslbtmp >= 1] = pbttmp1[nslbtmp >= 1] - ptptmp1[nslbtmp >= 1] dpslbtmp = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dpslbtmp[nslbtmp == 2] = ptptmp1[nslbtmp == 2] - pbttmp2[nslbtmp == 2] dptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp2[nslbtmp == 2] = pbttmp2[nslbtmp == 2] - ptptmp2[nslbtmp == 2] # Adjust negative DPSlab values dpnsq = flsq[(nslbtmp == 2) & (dpslbtmp < 0.0) & (dpslbtmp > -1000.0)] dpadj = numpy.zeros((ctyp1.shape[0],)) dpadj[dpnsq] = numpy.absolute(dpslbtmp[dpnsq]) dpslbtmp[dpnsq] = 1.0 dptmp1[dpnsq] = dptmp1[dpnsq] / 2.0 dptmp2[dpnsq] = dptmp2[dpnsq] / 2.0 # Sigma / Logit Adjustments zpbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp1tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdslbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp2tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 ncldct = 0 for t in range(psfc.shape[0]): if ( (pbttmp1[t] >= 0.0) and (dpslbtmp[t] >= 0.0) ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], dpslbtmp[t] / psfc[t], \ dptmp2[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 prptmp[4] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] - prptmp[3] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = ztmp[2] zdp2tmp[t] = ztmp[3] elif ( pbttmp1[t] >= 0.0 ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 prptmp[2] = 1.0 - prptmp[0] - prptmp[1] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 else: zpbtmp[t] = -9999.0 zdp1tmp[t] = -9999.0 zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 str1 = 'Cloud Bot Pres Below Sfc: %d ' % (ncldct) print(str1) if tsmp == 0: psfcout = numpy.zeros((msksb.shape[0],)) - 9999.0 psfcout[:] = psfc[msksb] prsbot1out = numpy.zeros((msksb.shape[0],)) - 9999.0 prsbot1out[:] = zpbtmp[msksb] dpcld1out = numpy.zeros((msksb.shape[0],)) - 9999.0 dpcld1out[:] = zdp1tmp[msksb] dpslbout = numpy.zeros((msksb.shape[0],)) - 9999.0 dpslbout[:] = zdslbtmp[msksb] dpcld2out = numpy.zeros((msksb.shape[0],)) - 9999.0 dpcld2out[:] = zdp2tmp[msksb] else: psfcout = numpy.append(psfcout,psfc[msksb]) prsbot1out = numpy.append(prsbot1out,zpbtmp[msksb]) dpcld1out = numpy.append(dpcld1out,zdp1tmp[msksb]) dpslbout = numpy.append(dpslbout,zdslbtmp[msksb]) dpcld2out = numpy.append(dpcld2out,zdp2tmp[msksb]) # Slab Types: 101.0 = Liquid, 201.0 = Ice, None else # Output: 0 = Liquid, 1 = Ice typtmp1 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp1[nslbtmp >= 1] = (ctyp1[nslbtmp >= 1] - 1.0) / 100.0 - 1.0 typtmp1[swpsq] = (ctyp2[swpsq] - 1.0) / 100.0 - 1.0 typtmp2 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp2[nslbtmp == 2] = (ctyp2[nslbtmp == 2] - 1.0) / 100.0 - 1.0 typtmp2[swpsq] = (ctyp1[swpsq] - 1.0) / 100.0 - 1.0 if tsmp == 0: slbtyp1out = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) slbtyp1out[:] = typtmp1[msksb] slbtyp2out = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) slbtyp2out[:] = typtmp2[msksb] else: slbtyp1out = numpy.append(slbtyp1out,typtmp1[msksb]) slbtyp2out = numpy.append(slbtyp2out,typtmp2[msksb]) # Cloud Fraction Logit, still account for swapping z1tmp = numpy.zeros((cfrc1.shape[0],)) - 9999.0 z2tmp = numpy.zeros((cfrc1.shape[0],)) - 9999.0 z12tmp = numpy.zeros((cfrc1.shape[0],)) - 9999.0 for t in range(z1tmp.shape[0]): if ( (cfrc1[t] > 0.0) and (cfrc2[t] > 0.0) and (cfrc12[t] > 0.0) ): # Must adjust amounts if (slabswap[t] == 0): prptmp = numpy.array( [cfrc1[t]-cfrc12[t], cfrc2[t]-cfrc12[t], cfrc12[t], 0.0] ) else: prptmp = numpy.array( [cfrc2[t]-cfrc12[t], cfrc1[t]-cfrc12[t], cfrc12[t], 0.0] ) prptmp[3] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t] = ztmp[0] z2tmp[t] = ztmp[1] z12tmp[t] = ztmp[2] elif ( (cfrc1[t] > 0.0) and (cfrc2[t] > 0.0) ): if (slabswap[t] == 0): prptmp = numpy.array( [cfrc1[t], cfrc2[t], 0.0] ) else: prptmp = numpy.array( [cfrc2[t], cfrc1[t], 0.0] ) prptmp[2] = 1.0 - prptmp[0] - prptmp[1] ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t] = ztmp[0] z2tmp[t] = ztmp[1] z12tmp[t] = -9999.0 elif ( cfrc1[t] > 0.0 ): prptmp = numpy.array( [cfrc1[t], 1.0 - cfrc1[t] ] ) ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t] = ztmp[0] z2tmp[t] = -9999.0 z12tmp[t] = -9999.0 else: z1tmp[t] = -9999.0 z2tmp[t] = -9999.0 z12tmp[t] = -9999.0 if tsmp == 0: cfclgt1out = numpy.zeros((msksb.shape[0],)) - 9999.0 cfclgt1out[:] = z1tmp[msksb] cfclgt2out = numpy.zeros((msksb.shape[0],)) - 9999.0 cfclgt2out[:] = z2tmp[msksb] cfclgt12out = numpy.zeros((msksb.shape[0],)) - 9999.0 cfclgt12out[:] = z12tmp[msksb] else: cfclgt1out = numpy.append(cfclgt1out,z1tmp[msksb]) cfclgt2out = numpy.append(cfclgt2out,z2tmp[msksb]) cfclgt12out = numpy.append(cfclgt12out,z12tmp[msksb]) # Cloud Non-Gas Water ngwttmp1 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp1[nslbtmp >= 1] = cngwt1[nslbtmp >= 1] ngwttmp1[swpsq] = cngwt2[swpsq] ngwttmp2 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp2[nslbtmp == 2] = cngwt2[nslbtmp == 2] ngwttmp2[swpsq] = cngwt1[swpsq] if tsmp == 0: ngwt1out = numpy.zeros((msksb.shape[0],)) - 9999.0 ngwt1out[:] = ngwttmp1[msksb] ngwt2out = numpy.zeros((msksb.shape[0],)) - 9999.0 ngwt2out[:] = ngwttmp2[msksb] else: ngwt1out = numpy.append(ngwt1out,ngwttmp1[msksb]) ngwt2out = numpy.append(ngwt2out,ngwttmp2[msksb]) # Cloud Top Temperature cttptmp1 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp1[nslbtmp >= 1] = cttp1[nslbtmp >= 1] cttptmp1[swpsq] = cttp2[swpsq] cttptmp2 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp2[nslbtmp == 2] = cttp2[nslbtmp == 2] cttptmp2[swpsq] = cttp1[swpsq] if tsmp == 0: cttp1out = numpy.zeros((msksb.shape[0],)) - 9999.0 cttp1out[:] = cttptmp1[msksb] cttp2out = numpy.zeros((msksb.shape[0],)) - 9999.0 cttp2out[:] = cttptmp2[msksb] else: cttp1out = numpy.append(cttp1out,cttptmp1[msksb]) cttp2out = numpy.append(cttp2out,cttptmp2[msksb]) # Loc/Time if tsmp == 0: latout = numpy.zeros((msksb.shape[0],)) - 9999.0 latout[:] = lthld[msksb] lonout = numpy.zeros((msksb.shape[0],)) - 9999.0 lonout[:] = lnhld[msksb] yrout = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) yrout[:] = yrlst[k] jdyout = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) jdyout[:] = tmhld[msksb] else: latout = numpy.append(latout,lthld[msksb]) lonout = numpy.append(lonout,lnhld[msksb]) yrtmp = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) yrtmp[:] = yrlst[k] yrout = numpy.append(yrout,yrtmp) jdyout = numpy.append(jdyout,tmhld[msksb]) tsmp = tsmp + msksb.shape[0] # Process quantiles nslbqs = calculate_VPD.quantile_msgdat_discrete(nslabout,prbs) str1 = '%.2f Number Slab Quantile: %d' % (prbs[53],nslbqs[53]) print(str1) print(nslbqs) psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) str1 = '%.2f Surface Pressure Quantile: %.3f' % (prbs[53],psfcqs[53]) print(str1) prsbt1qs = calculate_VPD.quantile_msgdat(prsbot1out,prbs) str1 = '%.2f CldBot1 Pressure Quantile: %.3f' % (prbs[53],prsbt1qs[53]) print(str1) dpcld1qs = calculate_VPD.quantile_msgdat(dpcld1out,prbs) str1 = '%.2f DPCloud1 Quantile: %.3f' % (prbs[53],dpcld1qs[53]) print(str1) dpslbqs = calculate_VPD.quantile_msgdat(dpslbout,prbs) str1 = '%.2f DPSlab Quantile: %.3f' % (prbs[53],dpslbqs[53]) print(str1) dpcld2qs = calculate_VPD.quantile_msgdat(dpcld2out,prbs) str1 = '%.2f DPCloud2 Quantile: %.3f' % (prbs[53],dpcld2qs[53]) print(str1) slb1qs = calculate_VPD.quantile_msgdat_discrete(slbtyp1out,prbs) str1 = '%.2f Type1 Quantile: %d' % (prbs[53],slb1qs[53]) print(str1) slb2qs = calculate_VPD.quantile_msgdat_discrete(slbtyp2out,prbs) str1 = '%.2f Type2 Quantile: %d' % (prbs[53],slb2qs[53]) print(str1) lgt1qs = calculate_VPD.quantile_msgdat(cfclgt1out,prbs) str1 = '%.2f Logit 1 Quantile: %.3f' % (prbs[53],lgt1qs[53]) print(str1) lgt2qs = calculate_VPD.quantile_msgdat(cfclgt2out,prbs) str1 = '%.2f Logit 2 Quantile: %.3f' % (prbs[53],lgt2qs[53]) print(str1) lgt12qs = calculate_VPD.quantile_msgdat(cfclgt12out,prbs) str1 = '%.2f Logit 1/2 Quantile: %.3f' % (prbs[53],lgt12qs[53]) print(str1) ngwt1qs = calculate_VPD.quantile_msgdat(ngwt1out,prbs) str1 = '%.2f NGWater1 Quantile: %.3f' % (prbs[53],ngwt1qs[53]) print(str1) ngwt2qs = calculate_VPD.quantile_msgdat(ngwt2out,prbs) str1 = '%.2f NGWater2 Quantile: %.3f' % (prbs[53],ngwt2qs[53]) print(str1) cttp1qs = calculate_VPD.quantile_msgdat(cttp1out,prbs) str1 = '%.2f CTTemp1 Quantile: %.3f' % (prbs[53],cttp1qs[53]) print(str1) cttp2qs = calculate_VPD.quantile_msgdat(cttp2out,prbs) str1 = '%.2f CTTemp2 Quantile: %.3f' % (prbs[53],cttp2qs[53]) print(str1) # Should be no missing for number of slabs print('Slab summary') print(numpy.amin(nslabout)) print(numpy.amax(nslabout)) print(tsmp) # Output Quantiles mstr = dyst.strftime('%b') qfnm = '%s/%s_US_JJA_%02dUTC_%04d_Cloud_Quantile.nc' % (dtdr,rgchc,hrchc,yrlst[k]) qout = Dataset(qfnm,'w') dimp = qout.createDimension('probability',nprb) varprb = qout.createVariable('probability','f4',['probability'], fill_value = -9999) varprb[:] = prbs varprb.long_name = 'Probability break points' varprb.units = 'none' varprb.missing_value = -9999 varnslb = qout.createVariable('NumberSlab_quantile','i2',['probability'], fill_value = -99) varnslb[:] = nslbqs varnslb.long_name = 'Number of cloud slabs quantiles' varnslb.units = 'Count' varnslb.missing_value = -99 varcbprs = qout.createVariable('CloudBot1Logit_quantile','f4',['probability'], fill_value = -9999) varcbprs[:] = prsbt1qs varcbprs.long_name = 'Slab 1 cloud bottom pressure logit quantiles' varcbprs.units = 'hPa' varcbprs.missing_value = -9999 vardpc1 = qout.createVariable('DPCloud1Logit_quantile','f4',['probability'], fill_value = -9999) vardpc1[:] = dpcld1qs vardpc1.long_name = 'Slab 1 cloud pressure depth logit quantiles' vardpc1.units = 'hPa' vardpc1.missing_value = -9999 vardpslb = qout.createVariable('DPSlabLogit_quantile','f4',['probability'], fill_value = -9999) vardpslb[:] = dpslbqs vardpslb.long_name = 'Two-slab vertical separation logit quantiles' vardpslb.units = 'hPa' vardpslb.missing_value = -9999 vardpc2 = qout.createVariable('DPCloud2Logit_quantile','f4',['probability'], fill_value = -9999) vardpc2[:] = dpcld2qs vardpc2.long_name = 'Slab 2 cloud pressure depth logit quantiles' vardpc2.units = 'hPa' vardpc2.missing_value = -9999 vartyp1 = qout.createVariable('CType1_quantile','i2',['probability'], fill_value = -99) vartyp1[:] = slb1qs vartyp1.long_name = 'Slab 1 cloud type quantiles' vartyp1.units = 'None' vartyp1.missing_value = -99 vartyp1.comment = 'Cloud slab type: 0=Liquid, 1=Ice' vartyp2 = qout.createVariable('CType2_quantile','i2',['probability'], fill_value = -99) vartyp2[:] = slb2qs vartyp2.long_name = 'Slab 2 cloud type quantiles' vartyp2.units = 'None' vartyp2.missing_value = -99 vartyp2.comment = 'Cloud slab type: 0=Liquid, 1=Ice' varlgt1 = qout.createVariable('CFrcLogit1_quantile','f4',['probability'], fill_value = -9999) varlgt1[:] = lgt1qs varlgt1.long_name = 'Slab 1 cloud fraction (cfrac1x) logit quantiles' varlgt1.units = 'None' varlgt1.missing_value = -9999 varlgt2 = qout.createVariable('CFrcLogit2_quantile','f4',['probability'], fill_value = -9999) varlgt2[:] = lgt2qs varlgt2.long_name = 'Slab 2 cloud fraction (cfrac2x) logit quantiles' varlgt2.units = 'None' varlgt2.missing_value = -9999 varlgt12 = qout.createVariable('CFrcLogit12_quantile','f4',['probability'], fill_value = -9999) varlgt12[:] = lgt12qs varlgt12.long_name = 'Slab 1/2 overlap fraction (cfrac12) logit quantiles' varlgt12.units = 'None' varlgt12.missing_value = -9999 varngwt1 = qout.createVariable('NGWater1_quantile','f4',['probability'], fill_value = -9999) varngwt1[:] = ngwt1qs varngwt1.long_name = 'Slab 1 cloud non-gas water quantiles' varngwt1.units = 'g m^-2' varngwt1.missing_value = -9999 varngwt2 = qout.createVariable('NGWater2_quantile','f4',['probability'], fill_value = -9999) varngwt2[:] = ngwt2qs varngwt2.long_name = 'Slab 2 cloud non-gas water quantiles' varngwt2.units = 'g m^-2' varngwt2.missing_value = -9999 varcttp1 = qout.createVariable('CTTemp1_quantile','f4',['probability'], fill_value = -9999) varcttp1[:] = cttp1qs varcttp1.long_name = 'Slab 1 cloud top temperature' varcttp1.units = 'K' varcttp1.missing_value = -9999 varcttp2 = qout.createVariable('CTTemp2_quantile','f4',['probability'], fill_value = -9999) varcttp2[:] = cttp2qs varcttp2.long_name = 'Slab 2 cloud top temperature' varcttp2.units = 'K' varcttp2.missing_value = -9999 qout.close() # Set up transformations znslb = calculate_VPD.std_norm_quantile_from_obs(nslabout, nslbqs, prbs, msgval=-99) zpsfc = calculate_VPD.std_norm_quantile_from_obs(psfcout, psfcqs, prbs, msgval=-9999.) zprsbt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(prsbot1out, prsbt1qs, prbs, msgval=-9999.) zdpcld1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld1out, dpcld1qs, prbs, msgval=-9999.) zdpslb = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpslbout, dpslbqs, prbs, msgval=-9999.) zdpcld2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld2out, dpcld2qs, prbs, msgval=-9999.) zctyp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp1out, slb1qs, prbs, msgval=-99) zctyp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp2out, slb2qs, prbs, msgval=-99) zlgt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt1out, lgt1qs, prbs, msgval=-9999.) zlgt2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt2out, lgt2qs, prbs, msgval=-9999.) zlgt12 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt12out, lgt12qs, prbs, msgval=-9999.) zngwt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt1out, ngwt1qs, prbs, msgval=-9999.) zngwt2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt2out, ngwt2qs, prbs, msgval=-9999.) zcttp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp1out, cttp1qs, prbs, msgval=-9999.) zcttp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp2out, cttp2qs, prbs, msgval=-9999.) # Output transformed quantile samples zfnm = '%s/%s_US_JJA_%02dUTC_%04d_Cloud_StdGausTrans.nc' % (dtdr,rgchc,hrchc,yrlst[k]) zout = Dataset(zfnm,'w') dimsmp = zout.createDimension('sample',tsmp) varlon = zout.createVariable('Longitude','f4',['sample']) varlon[:] = lonout varlon.long_name = 'Longitude' varlon.units = 'degrees_east' varlat = zout.createVariable('Latitude','f4',['sample']) varlat[:] = latout varlat.long_name = 'Latitude' varlat.units = 'degrees_north' varjdy = zout.createVariable('JulianDay','i2',['sample']) varjdy[:] = jdyout varjdy.long_name = 'JulianDay' varjdy.units = 'day' varyr = zout.createVariable('Year','i2',['sample']) varyr[:] = yrout varyr.long_name = 'Year' varyr.units = 'year' varnslb = zout.createVariable('NumberSlab_StdGaus','f4',['sample'], fill_value = -9999) varnslb[:] = znslb varnslb.long_name = 'Quantile transformed number of cloud slabs' varnslb.units = 'None' varnslb.missing_value = -9999. varcbprs = zout.createVariable('CloudBot1Logit_StdGaus','f4',['sample'], fill_value = -9999) varcbprs[:] = zprsbt1 varcbprs.long_name = 'Quantile transformed slab 1 cloud bottom pressure logit' varcbprs.units = 'None' varcbprs.missing_value = -9999. vardpc1 = zout.createVariable('DPCloud1Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc1[:] = zdpcld1 vardpc1.long_name = 'Quantile transformed slab 1 cloud pressure depth logit' vardpc1.units = 'None' vardpc1.missing_value = -9999. vardpslb = zout.createVariable('DPSlabLogit_StdGaus','f4',['sample'], fill_value = -9999) vardpslb[:] = zdpslb vardpslb.long_name = 'Quantile transformed two-slab vertical separation logit' vardpslb.units = 'None' vardpslb.missing_value = -9999. vardpc2 = zout.createVariable('DPCloud2Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc2[:] = zdpcld2 vardpc2.long_name = 'Quantile transformed slab 2 cloud pressure depth logit' vardpc2.units = 'None' vardpc2.missing_value = -9999. vartyp1 = zout.createVariable('CType1_StdGaus','f4',['sample'], fill_value = -9999) vartyp1[:] = zctyp1 vartyp1.long_name = 'Quantile transformed slab 1 cloud type logit' vartyp1.units = 'None' vartyp1.missing_value = -9999. vartyp2 = zout.createVariable('CType2_StdGaus','f4',['sample'], fill_value = -9999) vartyp2[:] = zctyp2 vartyp2.long_name = 'Quantile transformed slab 2 cloud type' vartyp2.units = 'None' vartyp2.missing_value = -9999. varlgt1 = zout.createVariable('CFrcLogit1_StdGaus','f4',['sample'], fill_value = -9999) varlgt1[:] = zlgt1 varlgt1.long_name = 'Quantile transformed slab 1 cloud fraction logit' varlgt1.units = 'None' varlgt1.missing_value = -9999. varlgt2 = zout.createVariable('CFrcLogit2_StdGaus','f4',['sample'], fill_value = -9999) varlgt2[:] = zlgt2 varlgt2.long_name = 'Quantile transformed slab 2 cloud fraction logit' varlgt2.units = 'None' varlgt2.missing_value = -9999. varlgt12 = zout.createVariable('CFrcLogit12_StdGaus','f4',['sample'], fill_value = -9999) varlgt12[:] = zlgt12 varlgt12.long_name = 'Quantile transformed slab 1/2 overlap fraction logit' varlgt12.units = 'None' varlgt12.missing_value = -9999. varngwt1 = zout.createVariable('NGWater1_StdGaus','f4',['sample'], fill_value = -9999) varngwt1[:] = zngwt1 varngwt1.long_name = 'Quantile transformed slab 1 non-gas water' varngwt1.units = 'None' varngwt1.missing_value = -9999. varngwt2 = zout.createVariable('NGWater2_StdGaus','f4',['sample'], fill_value = -9999) varngwt2[:] = zngwt2 varngwt2.long_name = 'Quantile transformed slab 2 non-gas water' varngwt2.units = 'None' varngwt2.missing_value = -9999. varcttp1 = zout.createVariable('CTTemp1_StdGaus','f4',['sample'], fill_value = -9999) varcttp1[:] = zcttp1 varcttp1.long_name = 'Quantile transformed slab 1 cloud top temperature' varcttp1.units = 'None' varcttp1.missing_value = -9999. varcttp2 = zout.createVariable('CTTemp2_StdGaus','f4',['sample'], fill_value = -9999) varcttp2[:] = zcttp2 varcttp2.long_name = 'Quantile transformed slab 2 cloud top temperature' varcttp2.units = 'None' varcttp2.missing_value = -9999. zout.close() return # Temp/RH Quantiles def quantile_profile_locmask(airsdr, mtdr, indr, dtdr, yrlst, mnst, mnfn, hrchc, rgchc, msk): # Construct profile/sfc variable quantiles and z-scores, with a possibly irregular location mask # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (airsdr) f = Dataset(rnm,'r') plev = f['level'][:] prbs = f['probability'][:] alts = f['altitude'][:] f.close() nyr = len(yrlst) nprb = prbs.shape[0] nzout = 101 tmpqout = numpy.zeros((nzout,nprb)) - 9999. rhqout = numpy.zeros((nzout,nprb)) - 9999. sftmpqs = numpy.zeros((nprb,)) - 9999. sfaltqs = numpy.zeros((nprb,)) - 9999. psfcqs = numpy.zeros((nprb,)) - 9999. altmed = numpy.zeros((nzout,)) - 9999. # Mask, lat, lon fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[0],hrchc) f = Dataset(fnm,'r') mask = f[msk][:,:] latmet = f['plat'][:] lonmet = f['plon'][:] f.close() mask[mask <= 0] = 0 lnsq = numpy.arange(lonmet.shape[0]) ltsq = numpy.arange(latmet.shape[0]) # Subset a bit lnsm = numpy.sum(mask,axis=0) print(lnsq.shape) print(lnsm.shape) print(lnsm) ltsm = numpy.sum(mask,axis=1) print(ltsq.shape) print(ltsm.shape) print(ltsm) lnmn = numpy.amin(lnsq[lnsm > 0]) lnmx = numpy.amax(lnsq[lnsm > 0]) + 1 ltmn = numpy.amin(ltsq[ltsm > 0]) ltmx = numpy.amax(ltsq[ltsm > 0]) + 1 stridx = 'Lon Range: %d, %d\nLat Range: %d, %d \n' % (lnmn,lnmx,ltmn,ltmx) print(stridx) nx = lnmx - lnmn ny = ltmx - ltmn lnrp = numpy.tile(lonmet[lnmn:lnmx],ny) ltrp = numpy.repeat(latmet[ltmn:ltmx],nx) mskblk = mask[ltmn:ltmx,lnmn:lnmx] mskflt = mskblk.flatten() tsmp = 0 for k in range(nyr): dyinit = datetime.date(yrlst[k],6,1) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) jdsq = numpy.arange(jst,jfn) tmhld = numpy.repeat(jdsq,nx*ny) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) mtnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = h5py.File(mtnm,'r') stparr = f['/stemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] psfarr = f['/spres'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] salarr = f['/salti'][ltmn:ltmx,lnmn:lnmx] f.close() nt = psfarr.shape[0] msksq1 = numpy.arange(mskflt.shape[0]) msksb1 = msksq1[mskflt > 0] mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] mskstr = 'Total Obs: %d, Within Mask: %d \n' % (msksq.shape[0],msksb.shape[0]) print(mskstr) lthld = numpy.tile(ltrp,nt) lnhld = numpy.tile(lnrp,nt) stparr = stparr.flatten() psfarr = psfarr.flatten() salarr = salarr.flatten() if tsmp == 0: sftmpout = numpy.zeros((msksb.shape[0],)) - 9999.0 sftmpout[:] = stparr[msksb] psfcout = numpy.zeros((msksb.shape[0],)) - 9999.0 psfcout[:] = psfarr[msksb] sfaltout = numpy.zeros((msksb.shape[0],)) - 9999.0 sfaltout[:] = numpy.tile(salarr[msksb1],nt) else: sftmpout = numpy.append(sftmpout,stparr[msksb]) psfcout = numpy.append(psfcout,psfarr[msksb]) sfaltout = numpy.append(sfaltout,numpy.tile(salarr[msksb1],nt)) # Loc/Time if tsmp == 0: latout = numpy.zeros((msksb.shape[0],)) - 9999.0 latout[:] = lthld[msksb] lonout = numpy.zeros((msksb.shape[0],)) - 9999.0 lonout[:] = lnhld[msksb] yrout = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) yrout[:] = yrlst[k] jdyout = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) jdyout[:] = tmhld[msksb] else: latout = numpy.append(latout,lthld[msksb]) lonout = numpy.append(lonout,lnhld[msksb]) yrtmp = numpy.zeros((msksb.shape[0],),dtype=numpy.int16) yrtmp[:] = yrlst[k] yrout = numpy.append(yrout,yrtmp) jdyout = numpy.append(jdyout,tmhld[msksb]) tsmp = tsmp + msksb.shape[0] # Vertical profiles tmpmerout = numpy.zeros((tsmp,nzout)) - 9999. h2omerout = numpy.zeros((tsmp,nzout)) - 9999. altout = numpy.zeros((tsmp,nzout)) - 9999. sidx = 0 for k in range(nyr): dyinit = datetime.date(yrlst[k],6,1) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) jdsq = numpy.arange(jst,jfn) tmhld = numpy.repeat(jdsq,nx*ny) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) mtnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_South_Southeast_US_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = h5py.File(mtnm,'r') tmparr = f['/ptemp'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] h2oarr = f['/rh'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] altarr = f['/palts'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] f.close() nt = tmparr.shape[0] mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] lthld = numpy.tile(ltrp,nt) lnhld = numpy.tile(lnrp,nt) fidx = sidx + msksb.shape[0] for j in range(nzout): tmpvec = tmparr[:,j,:,:].flatten() tmpvec[tmpvec > 1e30] = -9999. tmpmerout[sidx:fidx,j] = tmpvec[msksb] altvec = altarr[:,j,:,:].flatten() altout[sidx:fidx,j] = altvec[msksb] h2ovec = h2oarr[:,j,:,:].flatten() h2ovec[h2ovec > 1e30] = -9999. h2omerout[sidx:fidx,j] = h2ovec[msksb] sidx = sidx + msksb.shape[0] # Quantiles ztmpout = numpy.zeros((tsmp,nzout)) - 9999. zrhout = numpy.zeros((tsmp,nzout)) - 9999. zsftmpout = numpy.zeros((tsmp,)) - 9999. zsfaltout = numpy.zeros((tsmp,)) - 9999. zpsfcout = numpy.zeros((tsmp,)) - 9999. for j in range(nzout): tmptmp = calculate_VPD.quantile_msgdat(tmpmerout[:,j],prbs) tmpqout[j,:] = tmptmp[:] str1 = 'Plev %.2f, %.2f Temp Quantile: %.3f' % (plev[j],prbs[103],tmptmp[103]) print(str1) # Transform ztmp = calculate_VPD.std_norm_quantile_from_obs(tmpmerout[:,j], tmptmp, prbs, msgval=-9999.) ztmpout[:,j] = ztmp[:] alttmp = calculate_VPD.quantile_msgdat(altout[:,j],prbs) altmed[j] = alttmp[103] str1 = 'Plev %.2f, %.2f Alt Quantile: %.3f' % (plev[j],prbs[103],alttmp[103]) print(str1) # Adjust RH over 100 rhadj = h2omerout[:,j] rhadj[rhadj > 1.0] = 1.0 rhqtmp = calculate_VPD.quantile_msgdat(rhadj,prbs) rhqout[j,:] = rhqtmp[:] str1 = 'Plev %.2f, %.2f RH Quantile: %.4f' % (plev[j],prbs[103],rhqtmp[103]) print(str1) zrh = calculate_VPD.std_norm_quantile_from_obs(rhadj, rhqtmp, prbs, msgval=-9999.) zrhout[:,j] = zrh[:] psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) str1 = '%.2f PSfc Quantile: %.2f' % (prbs[103],psfcqs[103]) print(str1) zpsfcout = calculate_VPD.std_norm_quantile_from_obs(psfcout, psfcqs, prbs, msgval=-9999.) sftpqs = calculate_VPD.quantile_msgdat(sftmpout,prbs) str1 = '%.2f SfcTmp Quantile: %.2f' % (prbs[103],sftpqs[103]) print(str1) zsftmpout = calculate_VPD.std_norm_quantile_from_obs(sftmpout, sftpqs, prbs, msgval=-9999.) sfalqs = calculate_VPD.quantile_msgdat(sfaltout,prbs) str1 = '%.2f SfcAlt Quantile: %.2f' % (prbs[103],sfalqs[103]) print(str1) zsfaltout = calculate_VPD.std_norm_quantile_from_obs(sfaltout, sfalqs, prbs, msgval=-9999.) # Output Quantiles mstr = dyst.strftime('%b') qfnm = '%s/%s_US_JJA_%02dUTC_%04d_TempRHSfc_Quantile.nc' % (dtdr,rgchc,hrchc,yrlst[k]) qout = Dataset(qfnm,'w') dimz = qout.createDimension('level',nzout) dimp = qout.createDimension('probability',nprb) varlvl = qout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varprb = qout.createVariable('probability','f4',['probability'], fill_value = -9999) varprb[:] = prbs varprb.long_name = 'Probability break points' varprb.units = 'none' varprb.missing_value = -9999 # Altitude grid varalt = qout.createVariable('Altitude_median', 'f4', ['level'], fill_value = -9999) varalt[:] = altmed varalt.long_name = 'Altitude median value' varalt.units = 'm' varalt.missing_value = -9999 vartmp = qout.createVariable('Temperature_quantile', 'f4', ['level','probability'], fill_value = -9999) vartmp[:] = tmpqout vartmp.long_name = 'Temperature quantiles' vartmp.units = 'K' vartmp.missing_value = -9999. varrh = qout.createVariable('RH_quantile', 'f4', ['level','probability'], fill_value = -9999) varrh[:] = rhqout varrh.long_name = 'Relative humidity quantiles' varrh.units = 'Unitless' varrh.missing_value = -9999. varstmp = qout.createVariable('SfcTemp_quantile', 'f4', ['probability'], fill_value = -9999) varstmp[:] = sftpqs varstmp.long_name = 'Surface temperature quantiles' varstmp.units = 'K' varstmp.missing_value = -9999. varpsfc = qout.createVariable('SfcPres_quantile', 'f4', ['probability'], fill_value = -9999) varpsfc[:] = psfcqs varpsfc.long_name = 'Surface pressure quantiles' varpsfc.units = 'hPa' varpsfc.missing_value = -9999. varsalt = qout.createVariable('SfcAlt_quantile', 'f4', ['probability'], fill_value = -9999) varsalt[:] = sfalqs varsalt.long_name = 'Surface altitude quantiles' varsalt.units = 'm' varsalt.missing_value = -9999. qout.close() # Output transformed quantile samples zfnm = '%s/%s_US_JJA_%02dUTC_%04d_TempRHSfc_StdGausTrans.nc' % (dtdr,rgchc,hrchc,yrlst[k]) zout = Dataset(zfnm,'w') dimz = zout.createDimension('level',nzout) dimsmp = zout.createDimension('sample',tsmp) varlvl = zout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varlon = zout.createVariable('Longitude','f4',['sample']) varlon[:] = lonout varlon.long_name = 'Longitude' varlon.units = 'degrees_east' varlat = zout.createVariable('Latitude','f4',['sample']) varlat[:] = latout varlat.long_name = 'Latitude' varlat.units = 'degrees_north' varjdy = zout.createVariable('JulianDay','i2',['sample']) varjdy[:] = jdyout varjdy.long_name = 'JulianDay' varjdy.units = 'day' varyr = zout.createVariable('Year','i2',['sample']) varyr[:] = yrout varyr.long_name = 'Year' varyr.units = 'year' varsrt3 = zout.createVariable('Temperature_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt3[:] = ztmpout varsrt3.long_name = 'Quantile transformed temperature' varsrt3.units = 'None' varsrt3.missing_value = -9999. varsrt4 = zout.createVariable('RH_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt4[:] = zrhout varsrt4.long_name = 'Quantile transformed relative humidity' varsrt4.units = 'None' varsrt4.missing_value = -9999. varsrts1 = zout.createVariable('SfcTemp_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts1[:] = zsftmpout varsrts1.long_name = 'Quantile transformed surface temperature' varsrts1.units = 'None' varsrts1.missing_value = -9999. varsrts2 = zout.createVariable('SfcPres_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts2[:] = zpsfcout varsrts2.long_name = 'Quantile transformed surface pressure' varsrts2.units = 'None' varsrts2.missing_value = -9999. varsrts3 = zout.createVariable('SfcAlt_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts3[:] = zsfaltout varsrts3.long_name = 'Quantile transformed surface pressure' varsrts3.units = 'None' varsrts3.missing_value = -9999. zout.close() return def expt_near_sfc_summary(inpdr, outdr, expfl, qclrfl, outfnm): # Produce experiment near-surface summaries # inpdr: Name of input directory # outdr: Name of output directory # expfl: Name of file with experiment results # qclrfl: Input quantile file # outfnm: Ouptut file name nzairs = 100 nzsrt = 101 # Read simulation results f = h5py.File(expfl,'r') tmprtr = f['airs_ptemp'][:,:] h2ortr = f['airs_h2o'][:,:] tqflg = f['airs_ptemp_qc'][:,:] hqflg = f['airs_h2o_qc'][:,:] tmpsrt = f['ptemp'][:,1:nzsrt] h2osrt = f['gas_1'][:,1:nzsrt] psfc = f['spres'][:] lvs = f['level'][1:nzsrt] f.close() nszout = tmprtr.shape[0] tqflg = tqflg.astype(numpy.int16) hqflg = hqflg.astype(numpy.int16) # Altitude info qin = Dataset(qclrfl,'r') alts = qin['Altitude_median'][:] qin.close() alth2o = numpy.zeros((nszout,nzsrt)) alth2o[:,nzsrt-4] = alts[nzsrt-4] curdlt = 0.0 for j in range(nzsrt-5,-1,-1): #str1 = 'Level %d: %.4f' % (j,curdlt) #print(str1) if (alts[j] > alts[j+1]): curdlt = alts[j] - alts[j+1] alth2o[:,j] = alts[j] else: alth2o[:,j] = alts[j+1] + curdlt * 2.0 curdlt = curdlt * 2.0 alth2o[:,97] = 0.0 tsfcsrt = calculate_VPD.near_sfc_temp(tmpsrt, lvs, psfc, passqual = False, qual = None) print(tsfcsrt[0:10]) tsfcrtr, tqflgsfc = calculate_VPD.near_sfc_temp(tmprtr, lvs, psfc, passqual = True, qual = tqflg) print(tsfcrtr[0:10]) print(tqflgsfc[0:10]) qvsrt, rhsrt, vpdsrt = calculate_VPD.calculate_QV_and_VPD(h2osrt,tmpsrt,lvs,alth2o[:,1:nzsrt]) qvrtr, rhrtr, vpdrtr = calculate_VPD.calculate_QV_and_VPD(h2ortr,tmprtr,lvs,alth2o[:,1:nzsrt]) qsfsrt, rhsfsrt = calculate_VPD.near_sfc_qv_rh(qvsrt, tsfcsrt, lvs, psfc, passqual = False, qual = None) qsfrtr, rhsfrtr, qflgsfc = calculate_VPD.near_sfc_qv_rh(qvrtr, tsfcrtr, lvs, psfc, passqual = True, qual = hqflg) print(tqflgsfc.dtype) print(qflgsfc.dtype) # Output: Sfc Temp and qflg, SfC QV, RH and qflg fldbl = numpy.array([-9999.],dtype=numpy.float64) flflt = numpy.array([-9999.],dtype=numpy.float32) flshrt = numpy.array([-99],dtype=numpy.int16) #outfnm = '%s/MAGIC_%s_%s_%02dUTC_SR%02d_Sfc_UQ_Output.h5' % (outdr,rgchc,mnchc,hrchc,scnrw) f = h5py.File(outfnm,'w') dft1 = f.create_dataset('TSfcAir_True',data=tsfcsrt) dft1.attrs['missing_value'] = fldbl dft1.attrs['_FillValue'] = fldbl dft2 = f.create_dataset('TSfcAir_Retrieved',data=tsfcrtr) dft2.attrs['missing_value'] = fldbl dft2.attrs['_FillValue'] = fldbl dft3 = f.create_dataset('TSfcAir_QC',data=tqflgsfc) dfq1 = f.create_dataset('QVSfcAir_True',data=qsfsrt) dfq1.attrs['missing_value'] = fldbl dfq1.attrs['_FillValue'] = fldbl dfq2 = f.create_dataset('QVSfcAir_Retrieved',data=qsfrtr) dfq2.attrs['missing_value'] = fldbl dfq2.attrs['_FillValue'] = fldbl dfq3 = f.create_dataset('RHSfcAir_True',data=rhsfsrt) dfq3.attrs['missing_value'] = fldbl dfq3.attrs['_FillValue'] = fldbl dfq4 = f.create_dataset('RHSfcAir_Retrieved',data=rhsfrtr) dfq4.attrs['missing_value'] = fldbl dfq4.attrs['_FillValue'] = fldbl dfq5 = f.create_dataset('RHSfcAir_QC',data=qflgsfc) dfp1 = f.create_dataset('SfcPres',data=psfc) dfp1.attrs['missing_value'] = fldbl dfp1.attrs['_FillValue'] = fldbl f.close() return def quantile_cfrac_locmask_conus(rfdr, mtdr, csdr, airdr, dtdr, yrlst, mnst, mnfn, hrchc, rgchc, mskvr, mskvl): # Construct cloud variable quantiles and z-scores, with a possibly irregular location mask # rfdr: Directory for reference data (Levels/Quantiles) # mtdr: Directory for MERRA data # csdr: Directory for cloud slab data # airdr: Directory for AIRS cloud fraction # dtdr: Output directory # yrlst: List of years to process # mnst: Starting Month # mnfn: Ending Month # hrchc: Template Hour Choice # rgchc: Template Region Choice # mskvr: Name of region mask variable # mskvl: Value of region mask for Region Choice # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (rfdr) f = Dataset(rnm,'r') plev = f['level'][:] prbs = f['probability'][:] alts = f['altitude'][:] f.close() nyr = len(yrlst) nprb = prbs.shape[0] # RN generator sdchc = 542354 + yrlst[0] + hrchc random.seed(sdchc) # Mask, lat, lon fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[0],hrchc) f = Dataset(fnm,'r') mask = f.variables[mskvr][:,:] latmet = f.variables['plat'][:] lonmet = f.variables['plon'][:] tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() mskind = numpy.zeros((mask.shape),dtype=mask.dtype) print(mskvl) mskind[mask == mskvl] = 1 lnsq = numpy.arange(lonmet.shape[0]) ltsq = numpy.arange(latmet.shape[0]) # Subset a bit lnsm = numpy.sum(mskind,axis=0) #print(lnsq.shape) #print(lnsm.shape) #print(lnsm) ltsm = numpy.sum(mskind,axis=1) #print(ltsq.shape) #print(ltsm.shape) #print(ltsm) lnmn = numpy.amin(lnsq[lnsm > 0]) lnmx = numpy.amax(lnsq[lnsm > 0]) + 1 ltmn = numpy.amin(ltsq[ltsm > 0]) ltmx = numpy.amax(ltsq[ltsm > 0]) + 1 stridx = 'Lon Range: %d, %d\nLat Range: %d, %d \n' % (lnmn,lnmx,ltmn,ltmx) print(stridx) nx = lnmx - lnmn ny = ltmx - ltmn lnrp = numpy.tile(lonmet[lnmn:lnmx],ny) ltrp = numpy.repeat(latmet[ltmn:ltmx],nx) mskblk = mskind[ltmn:ltmx,lnmn:lnmx] mskflt = mskblk.flatten() tsmp = 0 for k in range(nyr): fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = Dataset(fnm,'r') tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() tmunit = tmunit.replace("days since ","") dybs = datetime.datetime.strptime(tmunit,"%Y-%m-%d %H:%M:%S") print(dybs) dy0 = dybs + datetime.timedelta(days=tminf[0]) dyinit = datetime.date(dy0.year,dy0.month,dy0.day) print(dyinit) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) jdsq = numpy.arange(jst,jfn) print(jdsq) tmhld = numpy.repeat(jdsq,nx*ny) #print(tmhld.shape) #print(numpy.amin(tmhld)) #print(numpy.amax(tmhld)) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing_IncludesCloudParams.h5' % (csdr,yrlst[k],hrchc) f = h5py.File(fnm,'r') tms = f['/time'][:,dystidx:dyfnidx] ctyp1 = f['/ctype'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] ctyp2 = f['/ctype2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt1 = f['/cprtop'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt2 = f['/cprtop2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb1 = f['/cprbot'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb2 = f['/cprbot2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc1 = f['/cfrac'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc2 = f['/cfrac2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc12 = f['/cfrac12'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt1 = f['/cngwat'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt2 = f['/cngwat2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp1 = f['/cstemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp2 = f['/cstemp2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() tmflt = tms.flatten() nt = tmflt.shape[0] lnhld = numpy.tile(lnrp,nt) lthld = numpy.tile(ltrp,nt) mtnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = Dataset(mtnm,'r') psfc = f.variables['spres'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() nt = ctyp1.shape[0] mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] mskstr = 'Total Obs: %d, Within Mask: %d \n' % (msksq.shape[0],msksb.shape[0]) print(mskstr) # lthld = numpy.tile(ltrp,nt) # lnhld = numpy.tile(lnrp,nt) nslbtmp = numpy.zeros((ctyp1.shape),dtype=numpy.int16) nslbtmp[(ctyp1 > 100) & (ctyp2 > 100)] = 2 nslbtmp[(ctyp1 > 100) & (ctyp2 < 100)] = 1 # AIRS clouds anm = '%s/CONUS_AIRS_CldFrc_Match_JJA_%d_%02d_UTC.nc' % (airdr,yrlst[k],hrchc) f = Dataset(anm,'r') arsfrc1 = f.variables['AIRS_CldFrac_1'][:,dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] arsfrc2 = f.variables['AIRS_CldFrac_2'][:,dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() # Sum frctot = arsfrc1 + arsfrc2 # Construct Clr/PC/Ovc indicator for AIRS total cloud frac totclr = numpy.zeros(frctot.shape,dtype=numpy.int16) totclr[frctot == 0.0] = -1 totclr[frctot == 1.0] = 1 totclr = ma.masked_array(totclr, mask = frctot.mask) frc0 = frctot[0,:,:,:] frc0 = frc0.flatten() frcsq = numpy.arange(tmhld.shape[0]) # Subset by AIRS matchup and location masks frcsb = frcsq[(numpy.logical_not(frc0.mask)) & (mskall > 0)] nairs = frcsb.shape[0] print(tmhld.shape) print(frcsb.shape) ctyp1 = ctyp1.flatten() ctyp2 = ctyp2.flatten() nslbtmp = nslbtmp.flatten() cngwt1 = cngwt1.flatten() cngwt2 = cngwt2.flatten() cttp1 = cttp1.flatten() cttp2 = cttp2.flatten() psfc = psfc.flatten() # Number of slabs if tsmp == 0: nslabout = numpy.zeros((nairs,),dtype=numpy.int16) nslabout[:] = nslbtmp[frcsb] else: nslabout = numpy.append(nslabout,nslbtmp[frcsb]) # For two slabs, slab 1 must have highest cloud bottom pressure cprt1 = cprt1.flatten() cprt2 = cprt2.flatten() cprb1 = cprb1.flatten() cprb2 = cprb2.flatten() slabswap = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) swpsq = frcsq[(nslbtmp == 2) & (cprb1 < cprb2)] slabswap[swpsq] = 1 # Cloud Pressure variables pbttmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp1[nslbtmp >= 1] = cprb1[nslbtmp >= 1] pbttmp1[swpsq] = cprb2[swpsq] ptptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp1[nslbtmp >= 1] = cprt1[nslbtmp >= 1] ptptmp1[swpsq] = cprt2[swpsq] pbttmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp2[nslbtmp == 2] = cprb2[nslbtmp == 2] pbttmp2[swpsq] = cprb1[swpsq] ptptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp2[nslbtmp == 2] = cprt2[nslbtmp == 2] ptptmp2[swpsq] = cprt1[swpsq] # DP Cloud transformation dptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp1[nslbtmp >= 1] = pbttmp1[nslbtmp >= 1] - ptptmp1[nslbtmp >= 1] dpslbtmp = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dpslbtmp[nslbtmp == 2] = ptptmp1[nslbtmp == 2] - pbttmp2[nslbtmp == 2] dptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp2[nslbtmp == 2] = pbttmp2[nslbtmp == 2] - ptptmp2[nslbtmp == 2] # Adjust negative DPSlab values dpnsq = frcsq[(nslbtmp == 2) & (dpslbtmp < 0.0) & (dpslbtmp > -1000.0)] dpadj = numpy.zeros((ctyp1.shape[0],)) dpadj[dpnsq] = numpy.absolute(dpslbtmp[dpnsq]) dpslbtmp[dpnsq] = 1.0 dptmp1[dpnsq] = dptmp1[dpnsq] / 2.0 dptmp2[dpnsq] = dptmp2[dpnsq] / 2.0 # Sigma / Logit Adjustments zpbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp1tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdslbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp2tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 ncldct = 0 for t in range(psfc.shape[0]): if ( (pbttmp1[t] >= 0.0) and (dpslbtmp[t] >= 0.0) ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], dpslbtmp[t] / psfc[t], \ dptmp2[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 prptmp[4] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] - prptmp[3] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = ztmp[2] zdp2tmp[t] = ztmp[3] elif ( pbttmp1[t] >= 0.0 ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 prptmp[2] = 1.0 - prptmp[0] - prptmp[1] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 else: zpbtmp[t] = -9999.0 zdp1tmp[t] = -9999.0 zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 str1 = 'Cloud Bot Pres Below Sfc: %d ' % (ncldct) print(str1) if tsmp == 0: psfcout = numpy.zeros((frcsb.shape[0],)) - 9999.0 psfcout[:] = psfc[frcsb] prsbot1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 prsbot1out[:] = zpbtmp[frcsb] dpcld1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpcld1out[:] = zdp1tmp[frcsb] dpslbout = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpslbout[:] = zdslbtmp[frcsb] dpcld2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpcld2out[:] = zdp2tmp[frcsb] else: psfcout = numpy.append(psfcout,psfc[frcsb]) prsbot1out = numpy.append(prsbot1out,zpbtmp[frcsb]) dpcld1out = numpy.append(dpcld1out,zdp1tmp[frcsb]) dpslbout = numpy.append(dpslbout,zdslbtmp[frcsb]) dpcld2out = numpy.append(dpcld2out,zdp2tmp[frcsb]) # Slab Types: 101.0 = Liquid, 201.0 = Ice, None else # Output: 0 = Liquid, 1 = Ice typtmp1 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp1[nslbtmp >= 1] = (ctyp1[nslbtmp >= 1] - 1.0) / 100.0 - 1.0 typtmp1[swpsq] = (ctyp2[swpsq] - 1.0) / 100.0 - 1.0 typtmp2 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp2[nslbtmp == 2] = (ctyp2[nslbtmp == 2] - 1.0) / 100.0 - 1.0 typtmp2[swpsq] = (ctyp1[swpsq] - 1.0) / 100.0 - 1.0 if tsmp == 0: slbtyp1out = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) slbtyp1out[:] = typtmp1[frcsb] slbtyp2out = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) slbtyp2out[:] = typtmp2[frcsb] else: slbtyp1out = numpy.append(slbtyp1out,typtmp1[frcsb]) slbtyp2out = numpy.append(slbtyp2out,typtmp2[frcsb]) # Cloud Cover Indicators totclrtmp = numpy.zeros((frcsb.shape[0],3,3),dtype=numpy.int16) cctr = 0 for frw in range(3): for fcl in range(3): clrvec = totclr[cctr,:,:,:].flatten() totclrtmp[:,frw,fcl] = clrvec[frcsb] cctr = cctr + 1 if tsmp == 0: totclrout = numpy.zeros(totclrtmp.shape,dtype=numpy.int16) totclrout[:,:,:] = totclrtmp else: totclrout = numpy.append(totclrout,totclrtmp,axis=0) # Cloud Fraction Logit, still account for swapping z1tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 z2tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 z12tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 # Cloud Fraction cctr = 0 for frw in range(3): for fcl in range(3): frcvect = frctot[cctr,:,:,:].flatten() frcvec1 = arsfrc1[cctr,:,:,:].flatten() frcvec2 = arsfrc2[cctr,:,:,:].flatten() # Quick fix for totals over 1.0 fvsq = numpy.arange(frcvect.shape[0]) fvsq2 = fvsq[frcvect > 1.0] frcvect[fvsq2] = frcvect[fvsq2] / 1.0 frcvec1[fvsq2] = frcvec1[fvsq2] / 1.0 frcvec2[fvsq2] = frcvec2[fvsq2] / 1.0 for t in range(nairs): crslb = nslbtmp[frcsb[t]] crclr = totclrtmp[t,frw,fcl] if ( (crslb == 0) or (crclr == -1) ): z1tmp[t,frw,fcl] = -9999.0 z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 elif ( (crslb == 1) and (crclr == 1) ): z1tmp[t,frw,fcl] = -9999.0 z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 elif ( (crslb == 1) and (crclr == 0) ): prptmp = numpy.array( [frcvect[frcsb[t]], 1.0 - frcvect[frcsb[t]] ] ) ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 # For 2 slabs, recall AIRS cloud layers go upper/lower, ours is opposite # Also apply random overlap adjust AIRS zero values elif ( (crslb == 2) and (crclr == 0) ): frcs = numpy.array([frcvec2[frcsb[t]],frcvec1[frcsb[t]]]) if (numpy.sum(frcs) < 0.01): frcs[0] = 0.005 frcs[1] = 0.005 elif frcs[0] < 0.005: frcs[0] = 0.005 frcs[1] = frcs[1] - 0.005 elif frcs[1] < 0.005: frcs[1] = 0.005 frcs[0] = frcs[0] - 0.005 mnfrc = numpy.amin(frcs) c12tmp = random.uniform(0.0,mnfrc,size=1) prptmp = numpy.array( [frcs[0] - c12tmp[0]*frcs[1], \ frcs[1] - c12tmp[0]*frcs[0], c12tmp[0], 0.0]) prptmp[3] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = ztmp[1] z12tmp[t,frw,fcl] = ztmp[2] elif ( (crslb == 2) and (crclr == 1) ): frcs = numpy.array([frcvec2[frcsb[t]],frcvec1[frcsb[t]]]) if frcs[0] < 0.005: frcs[0] = 0.005 frcs[1] = frcs[1] - 0.005 elif frcs[1] < 0.005: frcs[1] = 0.005 frcs[0] = frcs[0] - 0.005 mnfrc = numpy.amin(frcs) c12tmp = random.uniform(0.0,mnfrc,size=1) prptmp = numpy.array( [0.999 * (frcs[0] - c12tmp[0]*frcs[1]), \ 0.999 * (frcs[1] - c12tmp[0]*frcs[0]), 0.999 * c12tmp[0], 0.001]) prptmp[3] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] ztmp = calculate_VPD.lgtzs(prptmp) z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = ztmp[1] z12tmp[t,frw,fcl] = ztmp[2] cctr = cctr + 1 if tsmp == 0: cfclgt1out = numpy.zeros(z1tmp.shape) cfclgt1out[:,:,:] = z1tmp cfclgt2out = numpy.zeros(z2tmp.shape) cfclgt2out[:,:,:] = z2tmp cfclgt12out = numpy.zeros(z12tmp.shape) cfclgt12out[:,:,:] = z12tmp else: cfclgt1out = numpy.append(cfclgt1out,z1tmp,axis=0) cfclgt2out = numpy.append(cfclgt2out,z2tmp,axis=0) cfclgt12out = numpy.append(cfclgt12out,z12tmp,axis=0) # Cloud Non-Gas Water ngwttmp1 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp1[nslbtmp >= 1] = cngwt1[nslbtmp >= 1] ngwttmp1[swpsq] = cngwt2[swpsq] ngwttmp2 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp2[nslbtmp == 2] = cngwt2[nslbtmp == 2] ngwttmp2[swpsq] = cngwt1[swpsq] if tsmp == 0: ngwt1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 ngwt1out[:] = ngwttmp1[frcsb] ngwt2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 ngwt2out[:] = ngwttmp2[frcsb] else: ngwt1out = numpy.append(ngwt1out,ngwttmp1[frcsb]) ngwt2out = numpy.append(ngwt2out,ngwttmp2[frcsb]) # Cloud Top Temperature cttptmp1 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp1[nslbtmp >= 1] = cttp1[nslbtmp >= 1] cttptmp1[swpsq] = cttp2[swpsq] cttptmp2 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp2[nslbtmp == 2] = cttp2[nslbtmp == 2] cttptmp2[swpsq] = cttp1[swpsq] if tsmp == 0: cttp1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 cttp1out[:] = cttptmp1[frcsb] cttp2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 cttp2out[:] = cttptmp2[frcsb] else: cttp1out = numpy.append(cttp1out,cttptmp1[frcsb]) cttp2out = numpy.append(cttp2out,cttptmp2[frcsb]) # Loc/Time if tsmp == 0: latout = numpy.zeros((frcsb.shape[0],)) - 9999.0 latout[:] = lthld[frcsb] lonout = numpy.zeros((frcsb.shape[0],)) - 9999.0 lonout[:] = lnhld[frcsb] yrout = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) yrout[:] = yrlst[k] jdyout = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) jdyout[:] = tmhld[frcsb] else: latout = numpy.append(latout,lthld[frcsb]) lonout = numpy.append(lonout,lnhld[frcsb]) yrtmp = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) yrtmp[:] = yrlst[k] yrout = numpy.append(yrout,yrtmp) jdyout = numpy.append(jdyout,tmhld[frcsb]) tsmp = tsmp + nairs # Process quantiles nslbqs = calculate_VPD.quantile_msgdat_discrete(nslabout,prbs) str1 = '%.2f Number Slab Quantile: %d' % (prbs[103],nslbqs[103]) print(str1) print(nslbqs) # psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) # str1 = '%.2f Surface Pressure Quantile: %.3f' % (prbs[53],psfcqs[53]) # print(str1) prsbt1qs = calculate_VPD.quantile_msgdat(prsbot1out,prbs) str1 = '%.2f CldBot1 Pressure Quantile: %.3f' % (prbs[103],prsbt1qs[103]) print(str1) dpcld1qs = calculate_VPD.quantile_msgdat(dpcld1out,prbs) str1 = '%.2f DPCloud1 Quantile: %.3f' % (prbs[103],dpcld1qs[103]) print(str1) dpslbqs = calculate_VPD.quantile_msgdat(dpslbout,prbs) str1 = '%.2f DPSlab Quantile: %.3f' % (prbs[103],dpslbqs[103]) print(str1) dpcld2qs = calculate_VPD.quantile_msgdat(dpcld2out,prbs) str1 = '%.2f DPCloud2 Quantile: %.3f' % (prbs[103],dpcld2qs[103]) print(str1) slb1qs = calculate_VPD.quantile_msgdat_discrete(slbtyp1out,prbs) str1 = '%.2f Type1 Quantile: %d' % (prbs[103],slb1qs[103]) print(str1) slb2qs = calculate_VPD.quantile_msgdat_discrete(slbtyp2out,prbs) str1 = '%.2f Type2 Quantile: %d' % (prbs[103],slb2qs[103]) print(str1) # Indicators totclrqout = numpy.zeros((3,3,nprb)) - 99 lgt1qs = numpy.zeros((3,3,nprb)) - 9999.0 lgt2qs = numpy.zeros((3,3,nprb)) - 9999.0 lgt12qs = numpy.zeros((3,3,nprb)) - 9999.0 for frw in range(3): for fcl in range(3): tmpclr = calculate_VPD.quantile_msgdat_discrete(totclrout[:,frw,fcl],prbs) totclrqout[frw,fcl,:] = tmpclr[:] str1 = 'Clr/Ovc Indicator %d, %d %.2f Quantile: %d' % (frw,fcl,prbs[103],tmpclr[103]) print(str1) tmplgtq = calculate_VPD.quantile_msgdat(cfclgt1out[:,frw,fcl],prbs) lgt1qs[frw,fcl,:] = tmplgtq[:] tmplgtq = calculate_VPD.quantile_msgdat(cfclgt2out[:,frw,fcl],prbs) lgt2qs[frw,fcl,:] = tmplgtq[:] tmplgtq = calculate_VPD.quantile_msgdat(cfclgt12out[:,frw,fcl],prbs) lgt12qs[frw,fcl,:] = tmplgtq[:] str1 = 'CFrac Logit %d, %d %.2f Quantile: %.3f, %.3f, %.3f' % (frw,fcl,prbs[103], \ lgt1qs[frw,fcl,103],lgt2qs[frw,fcl,103],lgt12qs[frw,fcl,103]) print(str1) ngwt1qs = calculate_VPD.quantile_msgdat(ngwt1out,prbs) str1 = '%.2f NGWater1 Quantile: %.3f' % (prbs[103],ngwt1qs[103]) print(str1) ngwt2qs = calculate_VPD.quantile_msgdat(ngwt2out,prbs) str1 = '%.2f NGWater2 Quantile: %.3f' % (prbs[103],ngwt2qs[103]) print(str1) cttp1qs = calculate_VPD.quantile_msgdat(cttp1out,prbs) str1 = '%.2f CTTemp1 Quantile: %.3f' % (prbs[103],cttp1qs[103]) print(str1) cttp2qs = calculate_VPD.quantile_msgdat(cttp2out,prbs) str1 = '%.2f CTTemp2 Quantile: %.3f' % (prbs[103],cttp2qs[103]) print(str1) # Output Quantiles qfnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_Cloud_Quantile.nc' % (dtdr,yrlst[k],hrchc,rgchc) qout = Dataset(qfnm,'w') dimp = qout.createDimension('probability',nprb) dimfov1 = qout.createDimension('fovrow',3) dimfov2 = qout.createDimension('fovcol',3) varprb = qout.createVariable('probability','f4',['probability'], fill_value = -9999) varprb[:] = prbs varprb.long_name = 'Probability break points' varprb.units = 'none' varprb.missing_value = -9999 varnslb = qout.createVariable('NumberSlab_quantile','i2',['probability'], fill_value = -99) varnslb[:] = nslbqs varnslb.long_name = 'Number of cloud slabs quantiles' varnslb.units = 'Count' varnslb.missing_value = -99 varcbprs = qout.createVariable('CloudBot1Logit_quantile','f4',['probability'], fill_value = -9999) varcbprs[:] = prsbt1qs varcbprs.long_name = 'Slab 1 cloud bottom pressure logit quantiles' varcbprs.units = 'hPa' varcbprs.missing_value = -9999 vardpc1 = qout.createVariable('DPCloud1Logit_quantile','f4',['probability'], fill_value = -9999) vardpc1[:] = dpcld1qs vardpc1.long_name = 'Slab 1 cloud pressure depth logit quantiles' vardpc1.units = 'hPa' vardpc1.missing_value = -9999 vardpslb = qout.createVariable('DPSlabLogit_quantile','f4',['probability'], fill_value = -9999) vardpslb[:] = dpslbqs vardpslb.long_name = 'Two-slab vertical separation logit quantiles' vardpslb.units = 'hPa' vardpslb.missing_value = -9999 vardpc2 = qout.createVariable('DPCloud2Logit_quantile','f4',['probability'], fill_value = -9999) vardpc2[:] = dpcld2qs vardpc2.long_name = 'Slab 2 cloud pressure depth logit quantiles' vardpc2.units = 'hPa' vardpc2.missing_value = -9999 vartyp1 = qout.createVariable('CType1_quantile','i2',['probability'], fill_value = -99) vartyp1[:] = slb1qs vartyp1.long_name = 'Slab 1 cloud type quantiles' vartyp1.units = 'None' vartyp1.missing_value = -99 vartyp1.comment = 'Cloud slab type: 0=Liquid, 1=Ice' vartyp2 = qout.createVariable('CType2_quantile','i2',['probability'], fill_value = -99) vartyp2[:] = slb2qs vartyp2.long_name = 'Slab 2 cloud type quantiles' vartyp2.units = 'None' vartyp2.missing_value = -99 vartyp2.comment = 'Cloud slab type: 0=Liquid, 1=Ice' varcvr = qout.createVariable('CCoverInd_quantile','i2',['fovrow','fovcol','probability'], fill_value = 99) varcvr[:] = totclrqout varcvr.long_name = 'Cloud cover indicator quantiles' varcvr.units = 'None' varcvr.missing_value = -99 varcvr.comment = 'Cloud cover indicators: -1=Clear, 0=Partly cloudy, 1=Overcast' varlgt1 = qout.createVariable('CFrcLogit1_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varlgt1[:] = lgt1qs varlgt1.long_name = 'Slab 1 cloud fraction (cfrac1x) logit quantiles' varlgt1.units = 'None' varlgt1.missing_value = -9999 varlgt2 = qout.createVariable('CFrcLogit2_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varlgt2[:] = lgt2qs varlgt2.long_name = 'Slab 2 cloud fraction (cfrac2x) logit quantiles' varlgt2.units = 'None' varlgt2.missing_value = -9999 varlgt12 = qout.createVariable('CFrcLogit12_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varlgt12[:] = lgt12qs varlgt12.long_name = 'Slab 1/2 overlap fraction (cfrac12) logit quantiles' varlgt12.units = 'None' varlgt12.missing_value = -9999 varngwt1 = qout.createVariable('NGWater1_quantile','f4',['probability'], fill_value = -9999) varngwt1[:] = ngwt1qs varngwt1.long_name = 'Slab 1 cloud non-gas water quantiles' varngwt1.units = 'g m^-2' varngwt1.missing_value = -9999 varngwt2 = qout.createVariable('NGWater2_quantile','f4',['probability'], fill_value = -9999) varngwt2[:] = ngwt2qs varngwt2.long_name = 'Slab 2 cloud non-gas water quantiles' varngwt2.units = 'g m^-2' varngwt2.missing_value = -9999 varcttp1 = qout.createVariable('CTTemp1_quantile','f4',['probability'], fill_value = -9999) varcttp1[:] = cttp1qs varcttp1.long_name = 'Slab 1 cloud top temperature' varcttp1.units = 'K' varcttp1.missing_value = -9999 varcttp2 = qout.createVariable('CTTemp2_quantile','f4',['probability'], fill_value = -9999) varcttp2[:] = cttp2qs varcttp2.long_name = 'Slab 2 cloud top temperature' varcttp2.units = 'K' varcttp2.missing_value = -9999 qout.close() # Set up transformations zccvout = numpy.zeros((tsmp,3,3,)) - 9999. zlgt1 = numpy.zeros((tsmp,3,3)) - 9999. zlgt2 = numpy.zeros((tsmp,3,3)) - 9999. zlgt12 = numpy.zeros((tsmp,3,3)) - 9999. znslb = calculate_VPD.std_norm_quantile_from_obs(nslabout, nslbqs, prbs, msgval=-99) zprsbt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(prsbot1out, prsbt1qs, prbs, msgval=-9999.) zdpcld1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld1out, dpcld1qs, prbs, msgval=-9999.) zdpslb = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpslbout, dpslbqs, prbs, msgval=-9999.) zdpcld2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld2out, dpcld2qs, prbs, msgval=-9999.) zctyp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp1out, slb1qs, prbs, msgval=-99) zctyp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp2out, slb2qs, prbs, msgval=-99) for frw in range(3): for fcl in range(3): ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(totclrout[:,frw,fcl], totclrqout[frw,fcl,:], \ prbs, msgval=-99) zccvout[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt1out[:,frw,fcl], lgt1qs[frw,fcl,:], \ prbs, msgval=-9999.) zlgt1[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt2out[:,frw,fcl], lgt2qs[frw,fcl,:], \ prbs, msgval=-9999.) zlgt2[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt12out[:,frw,fcl], lgt12qs[frw,fcl,:], \ prbs, msgval=-9999.) zlgt12[:,frw,fcl] = ztmp[:] zngwt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt1out, ngwt1qs, prbs, msgval=-9999.) zngwt2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt2out, ngwt2qs, prbs, msgval=-9999.) zcttp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp1out, cttp1qs, prbs, msgval=-9999.) zcttp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp2out, cttp2qs, prbs, msgval=-9999.) # Output transformed quantile samples zfnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_Cloud_StdGausTrans.nc' % (dtdr,yrlst[k],hrchc,rgchc) zout = Dataset(zfnm,'w') dimsmp = zout.createDimension('sample',tsmp) dimfov1 = zout.createDimension('fovrow',3) dimfov2 = zout.createDimension('fovcol',3) varlon = zout.createVariable('Longitude','f4',['sample']) varlon[:] = lonout varlon.long_name = 'Longitude' varlon.units = 'degrees_east' varlat = zout.createVariable('Latitude','f4',['sample']) varlat[:] = latout varlat.long_name = 'Latitude' varlat.units = 'degrees_north' varjdy = zout.createVariable('JulianDay','i2',['sample']) varjdy[:] = jdyout varjdy.long_name = 'JulianDay' varjdy.units = 'day' varyr = zout.createVariable('Year','i2',['sample']) varyr[:] = yrout varyr.long_name = 'Year' varyr.units = 'year' varnslb = zout.createVariable('NumberSlab_StdGaus','f4',['sample'], fill_value = -9999) varnslb[:] = znslb varnslb.long_name = 'Quantile transformed number of cloud slabs' varnslb.units = 'None' varnslb.missing_value = -9999. varcbprs = zout.createVariable('CloudBot1Logit_StdGaus','f4',['sample'], fill_value = -9999) varcbprs[:] = zprsbt1 varcbprs.long_name = 'Quantile transformed slab 1 cloud bottom pressure logit' varcbprs.units = 'None' varcbprs.missing_value = -9999. vardpc1 = zout.createVariable('DPCloud1Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc1[:] = zdpcld1 vardpc1.long_name = 'Quantile transformed slab 1 cloud pressure depth logit' vardpc1.units = 'None' vardpc1.missing_value = -9999. vardpslb = zout.createVariable('DPSlabLogit_StdGaus','f4',['sample'], fill_value = -9999) vardpslb[:] = zdpslb vardpslb.long_name = 'Quantile transformed two-slab vertical separation logit' vardpslb.units = 'None' vardpslb.missing_value = -9999. vardpc2 = zout.createVariable('DPCloud2Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc2[:] = zdpcld2 vardpc2.long_name = 'Quantile transformed slab 2 cloud pressure depth logit' vardpc2.units = 'None' vardpc2.missing_value = -9999. vartyp1 = zout.createVariable('CType1_StdGaus','f4',['sample'], fill_value = -9999) vartyp1[:] = zctyp1 vartyp1.long_name = 'Quantile transformed slab 1 cloud type logit' vartyp1.units = 'None' vartyp1.missing_value = -9999. vartyp2 = zout.createVariable('CType2_StdGaus','f4',['sample'], fill_value = -9999) vartyp2[:] = zctyp2 vartyp2.long_name = 'Quantile transformed slab 2 cloud type' vartyp2.units = 'None' vartyp2.missing_value = -9999. varcov = zout.createVariable('CCoverInd_StdGaus','f4',['sample','fovrow','fovcol'], fill_value= -9999) varcov[:] = zccvout varcov.long_name = 'Quantile transformed cloud cover indicator' varcov.units = 'None' varcov.missing_value = -9999. varlgt1 = zout.createVariable('CFrcLogit1_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varlgt1[:] = zlgt1 varlgt1.long_name = 'Quantile transformed slab 1 cloud fraction logit' varlgt1.units = 'None' varlgt1.missing_value = -9999. varlgt2 = zout.createVariable('CFrcLogit2_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varlgt2[:] = zlgt2 varlgt2.long_name = 'Quantile transformed slab 2 cloud fraction logit' varlgt2.units = 'None' varlgt2.missing_value = -9999. varlgt12 = zout.createVariable('CFrcLogit12_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varlgt12[:] = zlgt12 varlgt12.long_name = 'Quantile transformed slab 1/2 overlap fraction logit' varlgt12.units = 'None' varlgt12.missing_value = -9999. varngwt1 = zout.createVariable('NGWater1_StdGaus','f4',['sample'], fill_value = -9999) varngwt1[:] = zngwt1 varngwt1.long_name = 'Quantile transformed slab 1 non-gas water' varngwt1.units = 'None' varngwt1.missing_value = -9999. varngwt2 = zout.createVariable('NGWater2_StdGaus','f4',['sample'], fill_value = -9999) varngwt2[:] = zngwt2 varngwt2.long_name = 'Quantile transformed slab 2 non-gas water' varngwt2.units = 'None' varngwt2.missing_value = -9999. varcttp1 = zout.createVariable('CTTemp1_StdGaus','f4',['sample'], fill_value = -9999) varcttp1[:] = zcttp1 varcttp1.long_name = 'Quantile transformed slab 1 cloud top temperature' varcttp1.units = 'None' varcttp1.missing_value = -9999. varcttp2 = zout.createVariable('CTTemp2_StdGaus','f4',['sample'], fill_value = -9999) varcttp2[:] = zcttp2 varcttp2.long_name = 'Quantile transformed slab 2 cloud top temperature' varcttp2.units = 'None' varcttp2.missing_value = -9999. zout.close() return def quantile_profile_locmask_conus(rfdr, mtdr, csdr, airdr, dtdr, yrlst, mnst, mnfn, hrchc, rgchc, mskvr, mskvl): # Construct profile/sfc variable quantiles and z-scores, with a possibly irregular location mask # rfdr: Directory for reference data (Levels/Quantiles) # mtdr: Directory for MERRA data # csdr: Directory for cloud slab data # airdr: Directory for AIRS cloud fraction # dtdr: Output directory # yrlst: List of years to process # mnst: Starting Month # mnfn: Ending Month # hrchc: Template Hour Choice # rgchc: Template Region Choice # mskvr: Name of region mask variable # mskvl: Value of region mask for Region Choice # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (rfdr) f = Dataset(rnm,'r') plev = f['level'][:] prbs = f['probability'][:] alts = f['altitude'][:] f.close() nyr = len(yrlst) nprb = prbs.shape[0] nzout = 101 tmpqout = numpy.zeros((nzout,nprb)) - 9999. rhqout = numpy.zeros((nzout,nprb)) - 9999. sftmpqs = numpy.zeros((nprb,)) - 9999. sfaltqs = numpy.zeros((nprb,)) - 9999. psfcqs = numpy.zeros((nprb,)) - 9999. altmed = numpy.zeros((nzout,)) - 9999. # Mask, lat, lon fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[0],hrchc) f = Dataset(fnm,'r') mask = f.variables[mskvr][:,:] latmet = f.variables['plat'][:] lonmet = f.variables['plon'][:] tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() mskind = numpy.zeros((mask.shape),dtype=mask.dtype) print(mskvl) mskind[mask == mskvl] = 1 lnsq = numpy.arange(lonmet.shape[0]) ltsq = numpy.arange(latmet.shape[0]) # Subset a bit lnsm = numpy.sum(mskind,axis=0) #print(lnsq.shape) #print(lnsm.shape) #print(lnsm) ltsm = numpy.sum(mskind,axis=1) #print(ltsq.shape) #print(ltsm.shape) #print(ltsm) lnmn = numpy.amin(lnsq[lnsm > 0]) lnmx = numpy.amax(lnsq[lnsm > 0]) + 1 ltmn = numpy.amin(ltsq[ltsm > 0]) ltmx = numpy.amax(ltsq[ltsm > 0]) + 1 stridx = 'Lon Range: %d, %d\nLat Range: %d, %d \n' % (lnmn,lnmx,ltmn,ltmx) print(stridx) nx = lnmx - lnmn ny = ltmx - ltmn lnrp = numpy.tile(lonmet[lnmn:lnmx],ny) ltrp = numpy.repeat(latmet[ltmn:ltmx],nx) mskblk = mskind[ltmn:ltmx,lnmn:lnmx] mskflt = mskblk.flatten() tsmp = 0 for k in range(nyr): fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = Dataset(fnm,'r') tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() tmunit = tmunit.replace("days since ","") dybs = datetime.datetime.strptime(tmunit,"%Y-%m-%d %H:%M:%S") print(dybs) dy0 = dybs + datetime.timedelta(days=tminf[0]) dyinit = datetime.date(dy0.year,dy0.month,dy0.day) print(dyinit) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) jdsq = numpy.arange(jst,jfn) print(jdsq) tmhld = numpy.repeat(jdsq,nx*ny) #print(tmhld.shape) #print(numpy.amin(tmhld)) #print(numpy.amax(tmhld)) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) # MERRA variables fnm = '%s/interpolated_merra2_for_SARTA_two_slab_%d_JJA_CONUS_with_NCA_regions_%02dUTC_no_vertical_variation_for_missing.nc' % (mtdr,yrlst[k],hrchc) f = Dataset(fnm,'r') tms = f.variables['time'][:] stparr = f['/stemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] psfarr = f['/spres'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] salarr = f['/salti'][ltmn:ltmx,lnmn:lnmx] tmparr = f['/ptemp'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] h2oarr = f['/rh'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] altarr = f['/palts'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] f.close() tmflt = tms.flatten() nt = tmflt.shape[0] lnhld = numpy.tile(lnrp,nt) lthld = numpy.tile(ltrp,nt) mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] mskstr = 'Total Obs: %d, Within Mask: %d \n' % (msksq.shape[0],msksb.shape[0]) print(mskstr) # AIRS Clouds anm = '%s/CONUS_AIRS_CldFrc_Match_JJA_%d_%02d_UTC.nc' % (airdr,yrlst[k],hrchc) f = Dataset(anm,'r') arsfrc1 = f.variables['AIRS_CldFrac_1'][:,dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] arsfrc2 = f.variables['AIRS_CldFrac_2'][:,dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() # Sum frctot = arsfrc1 + arsfrc2 frc0 = frctot[0,:,:,:] frc0 = frc0.flatten() frcsq = numpy.arange(tmhld.shape[0]) # Subset by AIRS matchup and location masks frcsb = frcsq[(numpy.logical_not(frc0.mask)) & (mskall > 0)] nairs = frcsb.shape[0] print(tmhld.shape) print(frcsb.shape) tmptmp = numpy.zeros((nairs,nzout)) h2otmp = numpy.zeros((nairs,nzout)) alttmp = numpy.zeros((nairs,nzout)) for j in range(nzout): tmpvec = tmparr[:,j,:,:].flatten() tmpvec[tmpvec > 1e30] = -9999. tmptmp[:,j] = tmpvec[frcsb] altvec = altarr[:,j,:,:].flatten() alttmp[:,j] = altvec[frcsb] h2ovec = h2oarr[:,j,:,:].flatten() h2ovec[h2ovec > 1e30] = -9999. h2otmp[:,j] = h2ovec[frcsb] if tsmp == 0: tmpmerout = numpy.zeros(tmptmp.shape) tmpmerout[:,:] = tmptmp h2omerout = numpy.zeros(h2otmp.shape) h2omerout[:,:] = h2otmp altout = numpy.zeros(alttmp.shape) altout[:,:] = alttmp else: tmpmerout = numpy.append(tmpmerout,tmptmp,axis=0) h2omerout = numpy.append(h2omerout,h2otmp,axis=0) altout = numpy.append(altout,alttmp,axis=0) stparr = stparr.flatten() psfarr = psfarr.flatten() salarr = salarr.flatten() salfl = numpy.tile(salarr[:],nt) if tsmp == 0: sftmpout = numpy.zeros((nairs,)) - 9999.0 sftmpout[:] = stparr[frcsb] psfcout = numpy.zeros((nairs,)) - 9999.0 psfcout[:] = psfarr[frcsb] sfaltout = numpy.zeros((nairs,)) - 9999.0 sfaltout[:] = salfl[frcsb] else: sftmpout = numpy.append(sftmpout,stparr[frcsb]) psfcout = numpy.append(psfcout,psfarr[frcsb]) sfaltout = numpy.append(sfaltout,salfl[frcsb]) # Loc/Time if tsmp == 0: latout = numpy.zeros((nairs,)) - 9999.0 latout[:] = lthld[frcsb] lonout = numpy.zeros((nairs,)) - 9999.0 lonout[:] = lnhld[frcsb] yrout = numpy.zeros((nairs,),dtype=numpy.int16) yrout[:] = yrlst[k] jdyout = numpy.zeros((nairs,),dtype=numpy.int16) jdyout[:] = tmhld[frcsb] else: latout = numpy.append(latout,lthld[frcsb]) lonout = numpy.append(lonout,lnhld[frcsb]) yrtmp = numpy.zeros((nairs,),dtype=numpy.int16) yrtmp[:] = yrlst[k] yrout = numpy.append(yrout,yrtmp) jdyout = numpy.append(jdyout,tmhld[frcsb]) tsmp = tsmp + nairs # Quantiles tmpqout = numpy.zeros((nzout,nprb)) - 9999. rhqout = numpy.zeros((nzout,nprb)) - 9999. sftmpqs = numpy.zeros((nprb,)) - 9999. sfaltqs = numpy.zeros((nprb,)) - 9999. psfcqs = numpy.zeros((nprb,)) - 9999. altmed = numpy.zeros((nzout,)) - 9999. ztmpout = numpy.zeros((tsmp,nzout)) - 9999. zrhout = numpy.zeros((tsmp,nzout)) - 9999. zsftmpout = numpy.zeros((tsmp,)) - 9999. zsfaltout = numpy.zeros((tsmp,)) - 9999. zpsfcout = numpy.zeros((tsmp,)) - 9999. # Quantiles for j in range(nzout): tmptmp = calculate_VPD.quantile_msgdat(tmpmerout[:,j],prbs) tmpqout[j,:] = tmptmp[:] str1 = 'Plev %.2f, %.2f Temp Quantile: %.3f' % (plev[j],prbs[103],tmptmp[103]) print(str1) # Transform ztmp = calculate_VPD.std_norm_quantile_from_obs(tmpmerout[:,j], tmptmp, prbs, msgval=-9999.) ztmpout[:,j] = ztmp[:] alttmp = calculate_VPD.quantile_msgdat(altout[:,j],prbs) altmed[j] = alttmp[103] str1 = 'Plev %.2f, %.2f Alt Quantile: %.3f' % (plev[j],prbs[103],alttmp[103]) print(str1) # Adjust RH over 100 rhadj = h2omerout[:,j] rhadj[rhadj > 1.0] = 1.0 rhqtmp = calculate_VPD.quantile_msgdat(rhadj,prbs) rhqout[j,:] = rhqtmp[:] str1 = 'Plev %.2f, %.2f RH Quantile: %.4f' % (plev[j],prbs[103],rhqtmp[103]) print(str1) zrh = calculate_VPD.std_norm_quantile_from_obs(rhadj, rhqtmp, prbs, msgval=-9999.) zrhout[:,j] = zrh[:] psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) str1 = '%.2f PSfc Quantile: %.2f' % (prbs[103],psfcqs[103]) print(str1) zpsfcout = calculate_VPD.std_norm_quantile_from_obs(psfcout, psfcqs, prbs, msgval=-9999.) sftpqs = calculate_VPD.quantile_msgdat(sftmpout,prbs) str1 = '%.2f SfcTmp Quantile: %.2f' % (prbs[103],sftpqs[103]) print(str1) zsftmpout = calculate_VPD.std_norm_quantile_from_obs(sftmpout, sftpqs, prbs, msgval=-9999.) sfalqs = calculate_VPD.quantile_msgdat(sfaltout,prbs) str1 = '%.2f SfcAlt Quantile: %.2f' % (prbs[103],sfalqs[103]) print(str1) zsfaltout = calculate_VPD.std_norm_quantile_from_obs(sfaltout, sfalqs, prbs, msgval=-9999.) # Output Quantiles qfnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_TempRHSfc_Quantile.nc' % (dtdr,yrlst[k],hrchc,rgchc) qout = Dataset(qfnm,'w') dimz = qout.createDimension('level',nzout) dimp = qout.createDimension('probability',nprb) varlvl = qout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varprb = qout.createVariable('probability','f4',['probability'], fill_value = -9999) varprb[:] = prbs varprb.long_name = 'Probability break points' varprb.units = 'none' varprb.missing_value = -9999 # Altitude grid varalt = qout.createVariable('Altitude_median', 'f4', ['level'], fill_value = -9999) varalt[:] = altmed varalt.long_name = 'Altitude median value' varalt.units = 'm' varalt.missing_value = -9999 vartmp = qout.createVariable('Temperature_quantile', 'f4', ['level','probability'], fill_value = -9999) vartmp[:] = tmpqout vartmp.long_name = 'Temperature quantiles' vartmp.units = 'K' vartmp.missing_value = -9999. varrh = qout.createVariable('RH_quantile', 'f4', ['level','probability'], fill_value = -9999) varrh[:] = rhqout varrh.long_name = 'Relative humidity quantiles' varrh.units = 'Unitless' varrh.missing_value = -9999. varstmp = qout.createVariable('SfcTemp_quantile', 'f4', ['probability'], fill_value = -9999) varstmp[:] = sftpqs varstmp.long_name = 'Surface temperature quantiles' varstmp.units = 'K' varstmp.missing_value = -9999. varpsfc = qout.createVariable('SfcPres_quantile', 'f4', ['probability'], fill_value = -9999) varpsfc[:] = psfcqs varpsfc.long_name = 'Surface pressure quantiles' varpsfc.units = 'hPa' varpsfc.missing_value = -9999. varsalt = qout.createVariable('SfcAlt_quantile', 'f4', ['probability'], fill_value = -9999) varsalt[:] = sfalqs varsalt.long_name = 'Surface altitude quantiles' varsalt.units = 'm' varsalt.missing_value = -9999. qout.close() # Output transformed quantile samples zfnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_TempRHSfc_StdGausTrans.nc' % (dtdr,yrlst[k],hrchc,rgchc) zout = Dataset(zfnm,'w') dimz = zout.createDimension('level',nzout) dimsmp = zout.createDimension('sample',tsmp) varlvl = zout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varlon = zout.createVariable('Longitude','f4',['sample']) varlon[:] = lonout varlon.long_name = 'Longitude' varlon.units = 'degrees_east' varlat = zout.createVariable('Latitude','f4',['sample']) varlat[:] = latout varlat.long_name = 'Latitude' varlat.units = 'degrees_north' varjdy = zout.createVariable('JulianDay','i2',['sample']) varjdy[:] = jdyout varjdy.long_name = 'JulianDay' varjdy.units = 'day' varyr = zout.createVariable('Year','i2',['sample']) varyr[:] = yrout varyr.long_name = 'Year' varyr.units = 'year' varsrt3 = zout.createVariable('Temperature_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt3[:] = ztmpout varsrt3.long_name = 'Quantile transformed temperature' varsrt3.units = 'None' varsrt3.missing_value = -9999. varsrt4 = zout.createVariable('RH_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt4[:] = zrhout varsrt4.long_name = 'Quantile transformed relative humidity' varsrt4.units = 'None' varsrt4.missing_value = -9999. varsrts1 = zout.createVariable('SfcTemp_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts1[:] = zsftmpout varsrts1.long_name = 'Quantile transformed surface temperature' varsrts1.units = 'None' varsrts1.missing_value = -9999. varsrts2 = zout.createVariable('SfcPres_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts2[:] = zpsfcout varsrts2.long_name = 'Quantile transformed surface pressure' varsrts2.units = 'None' varsrts2.missing_value = -9999. varsrts3 = zout.createVariable('SfcAlt_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts3[:] = zsfaltout varsrts3.long_name = 'Quantile transformed surface pressure' varsrts3.units = 'None' varsrts3.missing_value = -9999. zout.close() return def airscld_invtransf_mix_cloud9_conus_nosfc(rfdr, dtdr, yrchc, hrchc, rgchc, rfmn, rfdy, rfgrn, scnrw, nrep = 10, \ l2dir = '/archive/AIRSOps/airs/gdaac/v6'): # Read in mixture model parameters, draw random samples and set up SARTA input files # Use AIRS FOV cloud fraction information # Use designated AIRS reference granule, and pull surface pressure temperature from there # dtdr: Output directory # yrchc: Template Year Choice # hrchc: Template Hour Choice # rgchc: Template Region Choice # rfmn: Month for reference granule # rfdy: Day for reference granule # rfgrn: Reference granule number # scnrw: Scan row for experiment # nrep: Number of replicate granules # l2dir: Local AIRS Level 2 directory (to retrieve reference info) # RN Generator sdchc = 165434 + yrchc + hrchc random.seed(sdchc) cldprt = numpy.array([0.4,0.2,0.08]) nszout = 45 * 30 * nrep sfrps = 45 * nrep nlvsrt = 98 msgdbl = -9999.0 # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (rfdr) f = Dataset(rnm,'r') airs_sarta_levs = f['level'][:] f.close() # Get reference granule info airsdr = '%s/%04d/%02d/%02d/airs2sup' % (l2dir,yrchc,rfmn,rfdy) if (os.path.exists(airsdr)): fllst = os.listdir(airsdr) l2str = 'AIRS.%04d.%02d.%02d.%03d' % (yrchc,rfmn,rfdy,rfgrn) rffd = -1 j = 0 while ( (j < len(fllst)) and (rffd < 0) ): lncr = len(fllst[j]) l4 = lncr - 4 if ( (fllst[j][l4:lncr] == '.hdf') and (l2str in fllst[j])): l2fl = '%s/%s' % (airsdr,fllst[j]) ncl2 = Dataset(l2fl) psfc = ncl2.variables['PSurfStd'][:,:] topg = ncl2.variables['topog'][:,:] ncl2.close() rffd = j j = j + 1 else: print('L2 directory not found') # Surface replicates psfcvc = psfc[scnrw-1,:] topgvc = topg[scnrw-1,:] spres = numpy.tile(psfcvc,(sfrps,)) salti = numpy.tile(topgvc,(sfrps,)) # Variable list clrlst = ['Temperature','RH','SfcTemp'] clrst = [1,64,0] clrct = [98,35,1] cldlst = ['NumberSlab','CloudBot1Logit','DPCloud1Logit','DPSlabLogit','DPCloud2Logit', \ 'CType1','CType2','CCoverInd','CFrcLogit1','CFrcLogit2','CFrcLogit12', \ 'NGWater1','NGWater2','CTTemp1','CTTemp2'] cldst = [0,0,0,0,0, 0,0,0,0,0,0, 0,0,0,0] cldct = [1,1,1,1,1, 1,1,9,9,9,9, 1,1,1,1] nvar = 0 for q in range(len(clrct)): nvar = nvar + clrct[q] nclr = nvar for q in range(len(cldlst)): nvar = nvar + cldct[q] ncld = nvar - nclr # Discrete/Continuous Indicator typind = [] for q in range(len(clrct)): for p in range(clrct[q]): typind.append('Continuous') cldtypind = ['Discrete','Continuous','Continuous','Continuous','Continuous', \ 'Discrete','Discrete','Discrete','Continuous','Continuous','Continuous', \ 'Continuous','Continuous','Continuous','Continuous'] for q in range(len(cldct)): for p in range(cldct[q]): typind.append(cldtypind[q]) # Quantile files qclrnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_TempRHSfc_Quantile.nc' % (dtdr,yrchc,hrchc,rgchc) qcldnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_Cloud_Quantile.nc' % (dtdr,yrchc,hrchc,rgchc) qin = Dataset(qclrnm,'r') prbs = qin.variables['probability'][:] nprb = prbs.shape[0] qsclr = numpy.zeros((nclr,nprb)) lvs = qin.variables['level'][:] alts = qin.variables['Altitude_median'][:] rhmd = qin.variables['RH_quantile'][:,103] nlvl = lvs.shape[0] cctr = 0 for j in range(len(clrlst)): print(clrlst[j]) if clrst[j] == 0: vr1 = '%s_quantile' % (clrlst[j]) qsclr[cctr,:] = qin.variables[vr1][:] else: inst = clrst[j] - 1 infn = inst + clrct[j] otst = cctr otfn = cctr + clrct[j] vr1 = '%s_quantile' % (clrlst[j]) qsclr[otst:otfn,:] = qin.variables[vr1][inst:infn,:] cctr = cctr + clrct[j] qin.close() print('Clear medians') print(qsclr[:,103]) cldnmout = [] qin = Dataset(qcldnm,'r') qscld = numpy.zeros((ncld,nprb)) dctr = 0 for j in range(len(cldlst)): print(cldlst[j]) vr1 = '%s_quantile' % (cldlst[j]) vrinf = qin.variables[vr1] if cldct[j] == 1: qscld[dctr,:] = qin.variables[vr1][:] dctr = dctr + 1 cldnmout.append(cldlst[j]) elif (len(vrinf.shape) == 2): inst = cldst[j] infn = inst + cldct[j] for n2 in range(inst,infn): clnm = '%s_%d' % (cldlst[j],n2) cldnmout.append(clnm) otst = dctr otfn = dctr + cldct[j] vr1 = '%s_quantile' % (clrlst[j]) qscld[otst:otfn,:] = qin.variables[vr1][inst:infn,:] dctr = dctr + cldct[j] elif (len(vrinf.shape) == 3): for cl0 in range(vrinf.shape[0]): for rw0 in range(vrinf.shape[1]): otst = dctr otfn = dctr + 1 qscld[otst:otfn,:] = qin.variables[vr1][cl0,rw0,:] clnm = '%s_%d_%d' % (cldlst[j],cl0,rw0) cldnmout.append(clnm) dctr = dctr + 1 qin.close() print('Cloud medians') print(qscld[:,103]) # Read GMM Results gmmnm = '%s/CONUS_AIRS_JJA_%04d_%02dUTC_%s_GMM_parameters.nc' % (dtdr,yrchc,hrchc,rgchc) gmin = Dataset(gmmnm,'r') gmnms = gmin['State_Vector_Names'][:,:] gmmean = gmin['Mean'][:,:] gmpkcv = gmin['Packed_Covariance'][:,:] gmprps = gmin['Mixture_Proportion'][:] gmin.close() nmclps = gmnms.tolist() strvrs = list(map(calculate_VPD.clean_byte_list,nmclps)) if sys.version_info[0] < 3: print('Version 2') strvrs = map(str,strvrs) nmix = gmmean.shape[0] nmxvar = gmmean.shape[1] mrgcv = numpy.zeros((nmix,nmxvar,nmxvar),dtype=numpy.float64) for j in range(nmix): mrgcv[j,:,:] = calculate_VPD.unpackcov(gmpkcv[j,:], nelm=nmxvar) # Component sizes dtall = numpy.zeros((nszout,nmxvar),dtype=numpy.float) cmpidx = numpy.zeros((nszout,),dtype=numpy.int16) csmp = random.multinomial(nszout,pvals=gmprps) cmsz = 0 for j in range(nmix): cvfl = mrgcv[j,:,:] s1 = numpy.sqrt(numpy.diagonal(cvfl)) crmt = calculate_VPD.cov2cor(cvfl) sdmt = numpy.diag(numpy.sqrt(cvfl.diagonal())) w, v = linalg.eig(crmt) print(numpy.amin(w)) sdfn = cmsz + csmp[j] dtz = random.multivariate_normal(numpy.zeros((nmxvar,)),crmt,size=csmp[j]) dttmp = numpy.tile(gmmean[j,:],(csmp[j],1)) + numpy.dot(dtz,sdmt) dtall[cmsz:sdfn,:] = dttmp[:,:] cmpidx[cmsz:sdfn] = j + 1 cmsz = cmsz + csmp[j] # Re-shuffle ssq = numpy.arange(nszout) sqsmp = random.choice(ssq,size=nszout,replace=False) csmpshf = cmpidx[sqsmp] dtshf = dtall[sqsmp,:] print(dtshf.shape) ### Inverse Transform qout = numpy.zeros(dtshf.shape) for j in range(nclr): if typind[j] == 'Discrete': qout[:,j] = calculate_VPD.data_quantile_from_std_norm_discrete(dtshf[:,j],qsclr[j,:],prbs,minval=qsclr[j,0],maxval=qsclr[j,nprb-1]) else: qout[:,j] = calculate_VPD.data_quantile_from_std_norm(dtshf[:,j],qsclr[j,:],prbs,minval=qsclr[j,0],maxval=qsclr[j,nprb-1]) for j in range(nclr,nvar): if typind[j] == 'Discrete': qout[:,j] = calculate_VPD.data_quantile_from_std_norm_discrete(dtshf[:,j],qscld[j-nclr,:],prbs,minval=qsclr[j-nclr,0],maxval=qscld[j-nclr,nprb-1]) else: qout[:,j] = calculate_VPD.data_quantile_from_std_norm(dtshf[:,j],qscld[j-nclr,:],prbs,minval=qscld[j-nclr,0],maxval=qsclr[j-nclr,nprb-1]) ### Prepare for SARTA varlstout = ['cngwat','cngwat2','cprbot','cprbot2','cprtop','cprtop2', \ 'cpsize','cpsize2','cstemp','cstemp2','ctype','ctype2','salti','spres','stemp'] # Adjust altitudes alth2o = numpy.zeros((nszout,nlvsrt+3)) alth2o[:,nlvsrt-1] = alts[nlvsrt-1] curdlt = 0.0 for j in range(nlvsrt-2,-1,-1): str1 = 'Level %d: %.4f' % (j,curdlt) print(str1) if (alts[j] > alts[j+1]): curdlt = alts[j] - alts[j+1] alth2o[:,j] = alts[j] else: alth2o[:,j] = alts[j+1] + curdlt * 2.0 curdlt = curdlt * 2.0 alth2o[:,97] = 0.0 # Convert cloud items to data frame smpfrm = pandas.DataFrame(data=qout[:,nclr:nvar],columns=cldnmout) dtout = numpy.zeros((nszout,len(varlstout)), dtype=numpy.float64) frmout = pandas.DataFrame(data=dtout,columns=varlstout) # Cloud Types frmout['ctype'] = (smpfrm['CType1'] + 1.0) * 100.0 + 1.0 frmout['ctype2'] = (smpfrm['CType2'] + 1.0) * 100.0 + 1.0 frmout.loc[(smpfrm.NumberSlab == 0),'ctype'] = msgdbl frmout.loc[(smpfrm.NumberSlab < 2),'ctype2'] = msgdbl # Met/Sfc Components, arrays sized for SARTA and AIRS cctr = 0 prhout = numpy.zeros((nszout,nlvsrt+3)) - 9999.0 ptmpout = numpy.zeros((nszout,nlvsrt+3)) - 9999.0 for j in range(len(clrst)): if clrst[j] == 0: if clrlst[j] == 'SfcTemp': frmout['stemp'] = qout[:,cctr] elif clrlst[j] == 'Temperature': inst = clrst[j] - 1 infn = inst + clrct[j] otst = cctr otfn = cctr + clrct[j] ptmpout[:,inst:infn] = qout[:,otst:otfn] elif clrlst[j] == 'RH': inst = clrst[j] - 1 infn = inst + clrct[j] otst = cctr otfn = cctr + clrct[j] prhout[:,inst:infn] = qout[:,otst:otfn] bsrh = rhmd[inst] for k in range(inst-1,-1,-1): if ma.is_masked(rhmd[k]): prhout[:,k] = bsrh / 2.0 t2 = 'RH masked: %d' % (k) print(t2) elif rhmd[k] < 0: t2 = 'RH below 0: %d' % (k) print(t2) prhout[:,k] = bsrh else: prhout[:,k] = rhmd[k] bsrh = rhmd[k] cctr = cctr + clrct[j] str1 = '''RH at Level 1: %.4e, %.4e ''' % (numpy.amin(prhout[:,0]),rhmd[0]) str2 = '''RH at Level 2: %.4e, %.4e ''' % (numpy.amin(prhout[:,1]),rhmd[1]) print(str1) print(str2) h2oout = calculate_VPD.calculate_h2odens(prhout,ptmpout,airs_sarta_levs,alth2o) # Surface from reference frmout['salti'] = salti # Need for clouds frmout['spres'] = spres smpfrm['SfcPres'] = spres # Pressure Variables for i in range(nszout): if smpfrm['NumberSlab'][smpfrm.index[i]] == 0: frmout.at[i,'cprbot'] = msgdbl frmout.at[i,'cprtop'] = msgdbl frmout.at[i,'cprbot2'] = msgdbl frmout.at[i,'cprtop2'] = msgdbl elif smpfrm['NumberSlab'][smpfrm.index[i]] == 1: tmplgts = numpy.array( [smpfrm['CloudBot1Logit'][smpfrm.index[i]], \ smpfrm['DPCloud1Logit'][smpfrm.index[i]] ] ) frctmp = calculate_VPD.lgttoprp(tmplgts) frmout.at[i,'cprbot'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0]) frmout.at[i,'cprtop'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0] - frctmp[1]) frmout.at[i,'cprbot2'] = msgdbl frmout.at[i,'cprtop2'] = msgdbl elif smpfrm['NumberSlab'][smpfrm.index[i]] == 2: tmplgts = numpy.array( [smpfrm['CloudBot1Logit'][smpfrm.index[i]], \ smpfrm['DPCloud1Logit'][smpfrm.index[i]], \ smpfrm['DPSlabLogit'][smpfrm.index[i]], \ smpfrm['DPCloud2Logit'][smpfrm.index[i]] ] ) frctmp = calculate_VPD.lgttoprp(tmplgts) frmout.at[i,'cprbot'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0]) frmout.at[i,'cprtop'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0] - frctmp[1]) frmout.at[i,'cprbot2'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0] - frctmp[1] - frctmp[2]) frmout.at[i,'cprtop2'] = smpfrm['SfcPres'][smpfrm.index[i]] * (1.0 - frctmp[0] - frctmp[1] - frctmp[2] - frctmp[3]) # Non-Gas Water frmout['cngwat'] = smpfrm['NGWater1'] frmout.loc[(smpfrm.NumberSlab == 0),'cngwat'] = msgdbl frmout['cngwat2'] = smpfrm['NGWater2'] frmout.loc[(smpfrm.NumberSlab < 2),'cngwat2'] = msgdbl # Temperature frmout['cstemp'] = smpfrm['CTTemp1'] frmout.loc[(smpfrm.NumberSlab == 0),'cstemp'] = msgdbl frmout['cstemp2'] = smpfrm['CTTemp2'] frmout.loc[(smpfrm.NumberSlab < 2),'cstemp2'] = msgdbl # Particle Size, from Sergio's paper # 20 for water, 80 for ice #'cpsize','cpsize2','cstemp','cstemp2','ctype','ctype2'] frmout.loc[(frmout.ctype == 101.0),'cpsize'] = 20 frmout.loc[(frmout.ctype == 201.0),'cpsize'] = 80 frmout.loc[(frmout.ctype < 0.0),'cpsize'] = msgdbl frmout.loc[(frmout.ctype2 == 101.0),'cpsize2'] = 20 frmout.loc[(frmout.ctype2 == 201.0),'cpsize2'] = 80 frmout.loc[(frmout.ctype2 < 0.0),'cpsize2'] = msgdbl # Fractions, 3D Arrays cfrc1out = numpy.zeros((nszout,3,3)) - 9999.0 cfrc2out = numpy.zeros((nszout,3,3)) - 9999.0 cfrc12out = numpy.zeros((nszout,3,3)) - 9999.0 for i in range(nszout): if smpfrm['NumberSlab'][smpfrm.index[i]] == 0: cfrc1out[i,:,:] = 0.0 cfrc2out[i,:,:] = 0.0 cfrc12out[i,:,:] = 0.0 elif smpfrm['NumberSlab'][smpfrm.index[i]] == 1: for q in range(3): for p in range(3): ccvnm = 'CCoverInd_%d_%d' % (q,p) lgtnm1 = 'CFrcLogit1_%d_%d' % (q,p) if (smpfrm[ccvnm][smpfrm.index[i]] == -1): cfrc1out[i,q,p] = 0.0 elif (smpfrm[ccvnm][smpfrm.index[i]] == 1): cfrc1out[i,q,p] = 1.0 else: tmplgts = numpy.array( [smpfrm[lgtnm1][smpfrm.index[i]]] ) frctmp = calculate_VPD.lgttoprp(tmplgts) cfrc1out[i,q,p] = frctmp[0] cfrc2out[i,:,:] = 0.0 cfrc12out[i,:,:] = 0.0 elif smpfrm['NumberSlab'][smpfrm.index[i]] == 2: for q in range(3): for p in range(3): ccvnm = 'CCoverInd_%d_%d' % (q,p) lgtnm1 = 'CFrcLogit1_%d_%d' % (q,p) lgtnm2 = 'CFrcLogit2_%d_%d' % (q,p) lgtnm12 = 'CFrcLogit12_%d_%d' % (q,p) if (smpfrm[ccvnm][smpfrm.index[i]] == -1): cfrc1out[i,q,p] = 0.0 cfrc2out[i,q,p] = 0.0 cfrc12out[i,q,p] = 0.0 elif (smpfrm[ccvnm][smpfrm.index[i]] == 1): tmplgts = numpy.array( [smpfrm[lgtnm1][smpfrm.index[i]], \ smpfrm[lgtnm2][smpfrm.index[i]], \ smpfrm[lgtnm12][smpfrm.index[i]]] ) frctmp = calculate_VPD.lgttoprp(tmplgts) frcadj = 1.0 - frctmp[3] cfrc1out[i,q,p] = (frctmp[0] + frctmp[2]) / frcadj cfrc2out[i,q,p] = (frctmp[1] + frctmp[2]) / frcadj cfrc12out[i,q,p] = frctmp[2] / frcadj else: tmplgts = numpy.array( [smpfrm[lgtnm1][smpfrm.index[i]], \ smpfrm[lgtnm2][smpfrm.index[i]], \ smpfrm[lgtnm12][smpfrm.index[i]]] ) frctmp = calculate_VPD.lgttoprp(tmplgts) cfrc1out[i,q,p] = frctmp[0] + frctmp[2] cfrc2out[i,q,p] = frctmp[1] + frctmp[2] cfrc12out[i,q,p] = frctmp[2] # Write Sample Output print(frmout[166:180]) fldbl = numpy.array([-9999.],dtype=numpy.float64) flflt = numpy.array([-9999.],dtype=numpy.float32) flshrt = numpy.array([-99],dtype=numpy.int16) dfnm = '%s/SampledStateVectors/CONUS_AIRS_JJA_%04d_%02dUTC_%s_SR%02d_SimSARTAStates_Mix_CloudFOV.h5' % (dtdr,yrchc,hrchc,rgchc,scnrw) f = h5py.File(dfnm,'w') for j in range(len(varlstout)): dftmp = f.create_dataset(varlstout[j],data=frmout[varlstout[j]]) dftmp.attrs['missing_value'] = -9999. dftmp.attrs['_FillValue'] = -9999. dfpt = f.create_dataset('ptemp',data=ptmpout) dfpt.attrs['missing_value'] = fldbl dfpt.attrs['_FillValue'] = fldbl dfrh = f.create_dataset('relative_humidity',data=prhout) dfrh.attrs['missing_value'] = fldbl dfrh.attrs['_FillValue'] = fldbl dfgs = f.create_dataset('gas_1',data=h2oout) dfgs.attrs['missing_value'] = fldbl dfgs.attrs['_FillValue'] = fldbl dfcf1 = f.create_dataset('cfrac',data=cfrc1out) dfcf1.attrs['missing_value'] = fldbl dfcf1.attrs['_FillValue'] = fldbl dfcf2 = f.create_dataset('cfrac2',data=cfrc2out) dfcf2.attrs['missing_value'] = fldbl dfcf2.attrs['_FillValue'] = fldbl dfcf12 = f.create_dataset('cfrac12',data=cfrc12out) dfcf12.attrs['missing_value'] = fldbl dfcf12.attrs['_FillValue'] = fldbl dfcsmp = f.create_dataset('mixture_component',data=csmpshf) dfcsmp.attrs['missing_value'] = flshrt dfcsmp.attrs['_FillValue'] = flshrt dflv = f.create_dataset('level',data=airs_sarta_levs) f.close() return def setup_airs_cloud(flnm, tms, lats, lons, tmunit = 'Seconds since 1993-01-01 00:00:00'): # Set up matched AIRS/MERRA cloud file # flnm: Name of output file # tms: Time variable array # lats: Latitude variable array # lons: Longitude variable array ntm = tms.shape[0] nlat = lats.shape[0] nlon = lons.shape[0] # Create Output file qout = Dataset(flnm,'w') dimln = qout.createDimension('lon',nlon) dimlt = qout.createDimension('lat',nlat) dimtm = qout.createDimension('time',ntm) dimtrk = qout.createDimension('AIRSFOV',9) if (lons.dtype == numpy.float32): lntp = 'f4' else: lntp = 'f8' varlon = qout.createVariable('lon',lntp,['lon'], fill_value = -9999) varlon[:] = lons varlon.long_name = 'longitude' varlon.units='degrees_east' varlon.missing_value = -9999 if (lats.dtype == numpy.float32): lttp = 'f4' else: lttp = 'f8' varlat = qout.createVariable('lat',lttp,['lat'], fill_value = -9999) varlat[:] = lats varlat.long_name = 'latitude' varlat.units='degrees_north' varlat.missing_value = -9999 if (tms.dtype == numpy.float32): tmtp = 'f4' else: tmtp = 'f8' vartm = qout.createVariable('time',lttp,['time'], fill_value = -9999) vartm[:] = tms vartm.long_name = 'time' vartm.units = tmunit vartm.missing_value = -9999 # Other output variables varcfrc1 = qout.createVariable('AIRS_CldFrac_1','f4',['time','lat','lon','AIRSFOV'], fill_value = -9999) varcfrc1.long_name = 'AIRS cloud fraction, upper level' varcfrc1.units = 'unitless' varcfrc1.missing_value = -9999 varcfrc2 = qout.createVariable('AIRS_CldFrac_2','f4',['time','lat','lon','AIRSFOV'], fill_value = -9999) varcfrc2.long_name = 'AIRS cloud fraction, lower level' varcfrc2.units = 'unitless' varcfrc2.missing_value = -9999 varcqc1 = qout.createVariable('AIRS_CldFrac_QC_1','i2',['time','lat','lon','AIRSFOV'], fill_value = -99) varcqc1.long_name = 'AIRS cloud fraction quality flag, upper level' varcqc1.units = 'unitless' varcqc1.missing_value = -9999 varcqc2 = qout.createVariable('AIRS_CldFrac_QC_2','i2',['time','lat','lon','AIRSFOV'], fill_value = -99) varcqc2.long_name = 'AIRS cloud fraction quality flag, lower level' varcqc2.units = 'unitless' varcqc2.missing_value = -9999 varncld = qout.createVariable('AIRS_nCld','i2',['time','lat','lon','AIRSFOV'], fill_value = -99) varncld.long_name = 'AIRS number of cloud layers' varncld.units = 'unitless' varncld.missing_value = -9999 qout.close() return def airs_cfrac_match_merra(flnm, tmidx, tmday, lats, lons, msgvl = -9999, \ l2srch = '/archive/AIRSOps/airs/gdaac/v6'): # Set up matched AIRS/MERRA cloud file # flnm: Name of output file # tms: Time index in output # tmday: Datetime object with time information # lats: Longitude variable array # lons: Longitude variable array # Search AIRS Level 2 airsdr = '%s/%04d/%02d/%02d/airs2ret' % (l2srch,tmday.year,tmday.month,tmday.day) dsclst = [] asclst = [] nlat = lats.shape[0] nlon = lons.shape[0] lonmn = lons[0] - 5.0 lonmx = lons[nlon-1] + 5.0 latmn = lats[0] - 5.0 latmx = lats[nlat-1] + 5.0 d0 = datetime.datetime(1993,1,1,0,0,0) ddif = tmday - d0 bsdif = ddif.total_seconds() # Set up reference frame ltrp = numpy.repeat(lats,nlon) ltidx = numpy.repeat(numpy.arange(nlat),nlon) lnrp = numpy.tile(lons,nlat) lnidx = numpy.tile(numpy.arange(nlon),nlat) merfrm = pandas.DataFrame({'GridLonIdx': lnidx, 'GridLatIdx': ltidx, \ 'GridLon': lnrp, 'GridLat': ltrp}) if (os.path.exists(airsdr)): fllst = os.listdir(airsdr) #print(fllst) for j in range(len(fllst)): lncr = len(fllst[j]) l4 = lncr - 4 if (fllst[j][l4:lncr] == '.hdf'): l2fl = '%s/%s' % (airsdr,fllst[j]) ncl2 = Dataset(l2fl) slrzn = ncl2.variables['solzen'][:,:] l2lat = ncl2.variables['Latitude'][:,:] l2lon = ncl2.variables['Longitude'][:,:] l2tm = ncl2.variables['Time'][:,:] ncl2.close() # Check lat/lon ranges and asc/dsc l2tmdf = numpy.absolute(l2tm - bsdif) l2mntm = numpy.min(l2tmdf) # Within 4 hours if l2mntm < 14400.0: ltflt = l2lat.flatten() lnflt = l2lon.flatten() latsb = ltflt[(ltflt >= latmn) & (ltflt <= latmx)] lonsb = lnflt[(lnflt >= lonmn) & (lnflt <= lonmx)] if ( (latsb.shape[0] > 0) and (lonsb.shape[0] > 0) ): asclst.append(fllst[j]) sstr = '%s %.2f' % (fllst[j], l2mntm) print(sstr) # Set up outputs cld1arr = numpy.zeros((nlat,nlon,9),dtype=numpy.float32) + msgvl cld2arr = numpy.zeros((nlat,nlon,9),dtype=numpy.float32) + msgvl cld1qc = numpy.zeros((nlat,nlon,9),dtype=numpy.int16) - 99 cld2qc = numpy.zeros((nlat,nlon,9),dtype=numpy.int16) - 99 ncldarr = numpy.zeros((nlat,nlon,9),dtype=numpy.int16) - 99 #print(asclst) if (len(asclst) > 0): # Start matchups for j in range(len(asclst)): l2fl = '%s/%s' % (airsdr,asclst[j]) ncl2 = Dataset(l2fl) l2lat = ncl2.variables['Latitude'][:,:] l2lon = ncl2.variables['Longitude'][:,:] cfrcair = ncl2.variables['CldFrcStd'][:,:,:,:,:] cfrcaqc = ncl2.variables['CldFrcStd_QC'][:,:,:,:,:] ncldair = ncl2.variables['nCld'][:,:,:,:] ncl2.close() nairtrk = l2lat.shape[0] nairxtk = l2lat.shape[1] # Data Frame tkidx = numpy.repeat(numpy.arange(nairtrk),nairxtk) xtidx = numpy.tile(numpy.arange(nairxtk),nairtrk) l2lnflt = l2lon.flatten().astype(numpy.float64) l2ltflt = l2lat.flatten().astype(numpy.float64) l2frm = pandas.DataFrame({'L2LonIdx': xtidx, 'L2LatIdx': tkidx, \ 'L2Lon': l2lnflt, 'L2Lat': l2ltflt}) l2frm['GridLon'] = numpy.around(l2frm['L2Lon']/0.625) * 0.625 l2frm['GridLat'] = numpy.around(l2frm['L2Lat']/0.5) * 0.5 l2mrg = pandas.merge(l2frm,merfrm,on=['GridLon','GridLat']) print(l2mrg.shape) #if j == 0: # print(asclst[j]) # print(l2mrg[0:15]) # Output data if available for k in range(l2mrg.shape[0]): yidxout = l2mrg['GridLatIdx'].values[k] xidxout = l2mrg['GridLatIdx'].values[k] yidxl2 = l2mrg['L2LatIdx'].values[k] xidxl2 = l2mrg['L2LonIdx'].values[k] cld1arr[yidxout,xidxout,:] = cfrcair[yidxl2,xidxl2,:,:,0].flatten().astype(numpy.float32) cld2arr[yidxout,xidxout,:] = cfrcair[yidxl2,xidxl2,:,:,1].flatten().astype(numpy.float32) cld1qc[yidxout,xidxout,:] = cfrcaqc[yidxl2,xidxl2,:,:,0].flatten().astype(numpy.int16) cld2qc[yidxout,xidxout,:] = cfrcaqc[yidxl2,xidxl2,:,:,1].flatten().astype(numpy.int16) ncldarr[yidxout,xidxout,:] = ncldair[yidxl2,xidxl2,:,:].flatten().astype(numpy.int16) # Output qout = Dataset(flnm,'r+') varcfrc1 = qout.variables['AIRS_CldFrac_1'] varcfrc1[tmidx,:,:,:] = cld1arr[:,:,:] varcfrc2 = qout.variables['AIRS_CldFrac_2'] varcfrc2[tmidx,:,:,:] = cld2arr[:,:,:] varcfqc1 = qout.variables['AIRS_CldFrac_QC_1'] varcfqc1[tmidx,:,:,:] = cld1qc[:,:,:] varcfqc2 = qout.variables['AIRS_CldFrac_QC_2'] varcfqc2[tmidx,:,:,:] = cld2qc[:,:,:] varncld = qout.variables['AIRS_nCld'] varncld[tmidx,:,:,:] = ncldarr[:,:,:] qout.close() return def quantile_allstate_locmask_conus(rfdr, mtlst, cslst, airslst, dtdr, yrlst, mnst, mnfn, hrchc, rgchc, sstr, mskvr, mskvl): # Construct quantiles and z-scores, with a possibly irregular location mask, # for joint atmospheric state (AIRS/SARTA) # rfdr: Directory for reference data (Levels/Quantiles) # mtlst: Meteorology (MERRA) file list # cslst: Cloud slab file list # airslst: AIRS cloud fraction file list # dtdr: Output directory # yrlst: List of years to process # mnst: Starting Month # mnfn: Ending Month # hrchc: Template Hour Choice # rgchc: Template Region Choice # sstr: Season string # mskvr: Name of region mask variable # mskvl: Value of region mask for Region Choice # Read probs and pressure levels rnm = '%s/AIRS_Levels_Quantiles.nc' % (rfdr) f = Dataset(rnm,'r') plev = f['level'][:] prbs = f['probability'][:] alts = f['altitude'][:] f.close() nyr = len(yrlst) nprb = prbs.shape[0] # RN generator sdchc = 542354 + yrlst[0] + hrchc random.seed(sdchc) # Mask, lat, lon f = Dataset(mtlst[0],'r') mask = f.variables[mskvr][:,:] latmet = f.variables['lat'][:] lonmet = f.variables['lon'][:] tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() mskind = numpy.zeros((mask.shape),dtype=mask.dtype) print(mskvl) mskind[mask == mskvl] = 1 lnsq = numpy.arange(lonmet.shape[0]) ltsq = numpy.arange(latmet.shape[0]) # Subset a bit lnsm = numpy.sum(mskind,axis=0) ltsm = numpy.sum(mskind,axis=1) lnmn = numpy.amin(lnsq[lnsm > 0]) lnmx = numpy.amax(lnsq[lnsm > 0]) + 1 ltmn = numpy.amin(ltsq[ltsm > 0]) ltmx = numpy.amax(ltsq[ltsm > 0]) + 1 stridx = 'Lon Range: %d, %d\nLat Range: %d, %d \n' % (lnmn,lnmx,ltmn,ltmx) print(stridx) nx = lnmx - lnmn ny = ltmx - ltmn nzout = 101 lnrp = numpy.tile(lonmet[lnmn:lnmx],ny) ltrp = numpy.repeat(latmet[ltmn:ltmx],nx) mskblk = mskind[ltmn:ltmx,lnmn:lnmx] mskflt = mskblk.flatten() tsmp = 0 for k in range(nyr): f = Dataset(mtlst[k],'r') tminf = f.variables['time'][:] tmunit = f.variables['time'].units[:] f.close() tmunit = tmunit.replace("days since ","") dybs = datetime.datetime.strptime(tmunit,"%Y-%m-%d %H:%M:%S") print(dybs) dy0 = dybs + datetime.timedelta(days=tminf[0]) dyinit = datetime.date(dy0.year,dy0.month,dy0.day) print(dyinit) dyst = datetime.date(yrlst[k],mnst,1) ttst = dyst.timetuple() jst = ttst.tm_yday if mnfn < mnst: dyfn = datetime.date(yrlst[k]+1,mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jftmp = tt31.tm_yday + 1 jsq1 = numpy.arange(jst,jftmp) jsq2 = numpy.arange(1,jfn) jdsq = numpy.append(jsq1,jsq2) elif mnfn < 12: dyfn = datetime.date(yrlst[k],mnfn+1,1) ttfn = dyfn.timetuple() jfn = ttfn.tm_yday jdsq = numpy.arange(jst,jfn) else: dyfn = datetime.date(yrlst[k]+1,1,1) dy31 = datetime.date(yrlst[k],12,31) tt31 = dy31.timetuple() jfn = tt31.tm_yday + 1 print(dyst) print(dyfn) dystidx = abs((dyst-dyinit).days) dyfnidx = abs((dyfn-dyinit).days) print(jdsq) tmhld = numpy.repeat(jdsq,nx*ny) stridx = 'Day Range: %d, %d\n' % (dystidx,dyfnidx) print(stridx) # Cloud slab: HDF5 or NetCDF lncr = len(cslst[k]) l3 = lncr - 3 if (cslst[k][l3:lncr] == '.h5'): f = h5py.File(cslst[k],'r') tms = f['/time'][:,dystidx:dyfnidx] ctyp1 = f['/ctype'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] ctyp2 = f['/ctype2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt1 = f['/cprtop'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt2 = f['/cprtop2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb1 = f['/cprbot'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb2 = f['/cprbot2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc1 = f['/cfrac'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc2 = f['/cfrac2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cfrc12 = f['/cfrac12'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt1 = f['/cngwat'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt2 = f['/cngwat2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp1 = f['/cstemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp2 = f['/cstemp2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() elif (cslst[k][l3:lncr] == '.nc'): f = Dataset(cslst[k],'r') tms = f.variables['time'][dystidx:dyfnidx] ctyp1 = f.variables['ctype1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] ctyp2 = f.variables['ctype2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt1 = f.variables['cprtop1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprt2 = f.variables['cprtop2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb1 = f.variables['cprbot1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cprb2 = f.variables['cprbot2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt1 = f.variables['cngwat1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cngwt2 = f.variables['cngwat2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp1 = f.variables['cstemp1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] cttp2 = f.variables['cstemp2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] f.close() tmflt = tms.flatten() nt = tmflt.shape[0] lnhld = numpy.tile(lnrp,nt) lthld = numpy.tile(ltrp,nt) # MERRA variables f = Dataset(mtlst[k],'r') psfc = f.variables['spres'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] stparr = f.variables['stemp'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] salinf = f.variables['salti'] if salinf.ndim == 3: salarr = f.variables['salti'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx] elif salinf.ndim == 2: salarr = f.variables['salti'][ltmn:ltmx,lnmn:lnmx] tmparr = f.variables['ptemp'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] h2oarr = f.variables['rh'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] altarr = f.variables['palts'][dystidx:dyfnidx,:,ltmn:ltmx,lnmn:lnmx] f.close() # Mask print(ctyp1.shape) nt = ctyp1.shape[0] mskall = numpy.tile(mskflt,nt) msksq = numpy.arange(mskall.shape[0]) msksb = msksq[mskall > 0] mskstr = 'Total Obs: %d, Within Mask: %d \n' % (msksq.shape[0],msksb.shape[0]) print(mskstr) nslbtmp = numpy.zeros((ctyp1.shape),dtype=numpy.int16) nslbtmp[(ctyp1 > 100) & (ctyp2 > 100)] = 2 nslbtmp[(ctyp1 > 100) & (ctyp2 < 100)] = 1 # AIRS clouds f = Dataset(airslst[k],'r') arsfrc1 = f.variables['AIRS_CldFrac_1'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx,:] arsfrc2 = f.variables['AIRS_CldFrac_2'][dystidx:dyfnidx,ltmn:ltmx,lnmn:lnmx,:] f.close() # Sum frctot = arsfrc1 + arsfrc2 # Construct Clr/PC/Ovc indicator for AIRS total cloud frac totclr = numpy.zeros(frctot.shape,dtype=numpy.int16) totclr[frctot == 0.0] = -1 totclr[frctot == 1.0] = 1 totclr = ma.masked_array(totclr, mask = frctot.mask) frc0 = frctot[:,:,:,0] frc0 = frc0.flatten() frcsq = numpy.arange(tmhld.shape[0]) # Subset by AIRS matchup and location masks frcsb = frcsq[(numpy.logical_not(frc0.mask)) & (mskall > 0)] nairs = frcsb.shape[0] print(tmhld.shape) print(frcsb.shape) ctyp1 = ctyp1.flatten() ctyp2 = ctyp2.flatten() nslbtmp = nslbtmp.flatten() cngwt1 = cngwt1.flatten() cngwt2 = cngwt2.flatten() cttp1 = cttp1.flatten() cttp2 = cttp2.flatten() psfc = psfc.flatten() # Number of slabs if tsmp == 0: nslabout = numpy.zeros((nairs,),dtype=numpy.int16) nslabout[:] = nslbtmp[frcsb] else: nslabout = numpy.append(nslabout,nslbtmp[frcsb]) # For two slabs, slab 1 must have highest cloud bottom pressure cprt1 = cprt1.flatten() cprt2 = cprt2.flatten() cprb1 = cprb1.flatten() cprb2 = cprb2.flatten() slabswap = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) swpsq = frcsq[(nslbtmp == 2) & (cprb1 < cprb2)] slabswap[swpsq] = 1 # Cloud Pressure variables pbttmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp1[nslbtmp >= 1] = cprb1[nslbtmp >= 1] pbttmp1[swpsq] = cprb2[swpsq] ptptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp1[nslbtmp >= 1] = cprt1[nslbtmp >= 1] ptptmp1[swpsq] = cprt2[swpsq] pbttmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 pbttmp2[nslbtmp == 2] = cprb2[nslbtmp == 2] pbttmp2[swpsq] = cprb1[swpsq] ptptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 ptptmp2[nslbtmp == 2] = cprt2[nslbtmp == 2] ptptmp2[swpsq] = cprt1[swpsq] # DP Cloud transformation dptmp1 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp1[nslbtmp >= 1] = pbttmp1[nslbtmp >= 1] - ptptmp1[nslbtmp >= 1] dpslbtmp = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dpslbtmp[nslbtmp == 2] = ptptmp1[nslbtmp == 2] - pbttmp2[nslbtmp == 2] dptmp2 = numpy.zeros((ctyp1.shape[0],)) - 9999.0 dptmp2[nslbtmp == 2] = pbttmp2[nslbtmp == 2] - ptptmp2[nslbtmp == 2] # Adjust negative DPSlab values dpnsq = frcsq[(nslbtmp == 2) & (dpslbtmp <= 0.0) & (dpslbtmp > -1000.0)] dpadj = numpy.zeros((ctyp1.shape[0],)) dpadj[dpnsq] = numpy.absolute(dpslbtmp[dpnsq]) dpslbtmp[dpnsq] = 10.0 dptmp1[dpnsq] = dptmp1[dpnsq] / 2.0 dptmp2[dpnsq] = dptmp2[dpnsq] / 2.0 # Sigma / Logit Adjustments zpbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp1tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdslbtmp = numpy.zeros((psfc.shape[0],)) - 9999.0 zdp2tmp = numpy.zeros((psfc.shape[0],)) - 9999.0 ncldct = 0 for t in range(psfc.shape[0]): if ( (pbttmp1[t] >= 0.0) and (dpslbtmp[t] >= 0.0) ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], dpslbtmp[t] / psfc[t], \ dptmp2[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] prptmp[2] = prptmp[2] + prpadj*prptmp[2] prptmp[3] = prptmp[3] + prpadj*prptmp[3] ncldct = ncldct + 1 prptmp[4] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] - prptmp[3] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = ztmp[2] zdp2tmp[t] = ztmp[3] elif ( pbttmp1[t] >= 0.0 ): prptmp = numpy.array( [ (psfc[t] - pbttmp1[t]) / psfc[t], \ dptmp1[t] / psfc[t], 0.0 ] ) if (prptmp[0] < 0.0): # Adjustment needed prpadj = prptmp[0] prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 elif (prptmp[0] == 0.0): # Adjustment needed prpadj = -0.01 prptmp[0] = 0.01 prptmp[1] = prptmp[1] + prpadj*prptmp[1] ncldct = ncldct + 1 prptmp[2] = 1.0 - prptmp[0] - prptmp[1] ztmp = calculate_VPD.lgtzs(prptmp) zpbtmp[t] = ztmp[0] zdp1tmp[t] = ztmp[1] zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 else: zpbtmp[t] = -9999.0 zdp1tmp[t] = -9999.0 zdslbtmp[t] = -9999.0 zdp2tmp[t] = -9999.0 str1 = 'Cloud Bot Pres Below Sfc: %d ' % (ncldct) print(str1) if tsmp == 0: psfcout = numpy.zeros((frcsb.shape[0],)) - 9999.0 psfcout[:] = psfc[frcsb] prsbot1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 prsbot1out[:] = zpbtmp[frcsb] dpcld1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpcld1out[:] = zdp1tmp[frcsb] dpslbout = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpslbout[:] = zdslbtmp[frcsb] dpcld2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 dpcld2out[:] = zdp2tmp[frcsb] else: psfcout = numpy.append(psfcout,psfc[frcsb]) prsbot1out = numpy.append(prsbot1out,zpbtmp[frcsb]) dpcld1out = numpy.append(dpcld1out,zdp1tmp[frcsb]) dpslbout = numpy.append(dpslbout,zdslbtmp[frcsb]) dpcld2out = numpy.append(dpcld2out,zdp2tmp[frcsb]) # Slab Types: 101.0 = Liquid, 201.0 = Ice, None else # Output: 0 = Liquid, 1 = Ice typtmp1 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp1[nslbtmp >= 1] = (ctyp1[nslbtmp >= 1] - 1.0) / 100.0 - 1.0 typtmp1[swpsq] = (ctyp2[swpsq] - 1.0) / 100.0 - 1.0 typtmp2 = numpy.zeros((ctyp1.shape[0],),dtype=numpy.int16) - 99 typtmp2[nslbtmp == 2] = (ctyp2[nslbtmp == 2] - 1.0) / 100.0 - 1.0 typtmp2[swpsq] = (ctyp1[swpsq] - 1.0) / 100.0 - 1.0 if tsmp == 0: slbtyp1out = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) slbtyp1out[:] = typtmp1[frcsb] slbtyp2out = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) slbtyp2out[:] = typtmp2[frcsb] else: slbtyp1out = numpy.append(slbtyp1out,typtmp1[frcsb]) slbtyp2out = numpy.append(slbtyp2out,typtmp2[frcsb]) # Cloud Cover Indicators totclrtmp = numpy.zeros((frcsb.shape[0],3,3),dtype=numpy.int16) frctottmp = numpy.zeros((frcsb.shape[0],3,3),dtype=frctot.dtype) cctr = 0 for frw in range(3): for fcl in range(3): clrvec = totclr[:,:,:,cctr].flatten() frcvec = frctot[:,:,:,cctr].flatten() totclrtmp[:,frw,fcl] = clrvec[frcsb] frctottmp[:,frw,fcl] = frcvec[frcsb] cctr = cctr + 1 if tsmp == 0: totclrout = numpy.zeros(totclrtmp.shape,dtype=numpy.int16) totclrout[:,:,:] = totclrtmp frctotout = numpy.zeros(frctottmp.shape,dtype=frctottmp.dtype) frctotout[:,:,:] = frctottmp else: totclrout = numpy.append(totclrout,totclrtmp,axis=0) frctotout = numpy.append(frctotout,frctottmp,axis=0) # Cloud Fraction Logit, still account for swapping #z1tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 z2tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 z12tmp = numpy.zeros((frcsb.shape[0],3,3)) - 9999.0 # Cloud Fraction cctr = 0 for frw in range(3): for fcl in range(3): frcvect = frctot[:,:,:,cctr].flatten() frcvec1 = arsfrc1[:,:,:,cctr].flatten() frcvec2 = arsfrc2[:,:,:,cctr].flatten() # Quick fix for totals over 1.0 fvsq = numpy.arange(frcvect.shape[0]) fvsq2 = fvsq[frcvect > 1.0] frcvect[fvsq2] = frcvect[fvsq2] / 1.0 frcvec1[fvsq2] = frcvec1[fvsq2] / 1.0 frcvec2[fvsq2] = frcvec2[fvsq2] / 1.0 for t in range(nairs): crslb = nslbtmp[frcsb[t]] crclr = totclrtmp[t,frw,fcl] if ( (crslb == 0) or (crclr == -1) ): #z1tmp[t,frw,fcl] = -9999.0 z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 elif ( (crslb == 1) and (crclr == 1) ): #z1tmp[t,frw,fcl] = -9999.0 z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 elif ( (crslb == 1) and (crclr == 0) ): #prptmp = numpy.array( [frcvect[frcsb[t]], 1.0 - frcvect[frcsb[t]] ] ) #ztmp = calculate_VPD.lgtzs(prptmp) #z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = -9999.0 z12tmp[t,frw,fcl] = -9999.0 # For 2 slabs, recall AIRS cloud layers go upper/lower, ours is opposite # Also apply random overlap adjust AIRS zero values elif ( (crslb == 2) and (crclr == 0) ): frcs = numpy.array([frcvec2[frcsb[t]],frcvec1[frcsb[t]]]) if (numpy.sum(frcs) < 0.01): frcs[0] = 0.005 frcs[1] = 0.005 elif frcs[0] < 0.005: frcs[0] = 0.005 frcs[1] = frcs[1] - 0.005 elif frcs[1] < 0.005: frcs[1] = 0.005 frcs[0] = frcs[0] - 0.005 mnfrc = numpy.amin(frcs) c12tmp = random.uniform(0.0,mnfrc,size=1) prptmp = numpy.array( [frcs[0] - c12tmp[0]*frcs[1], \ frcs[1] - c12tmp[0]*frcs[0], c12tmp[0], 0.0]) prptmp[3] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] prpcld = (prptmp[0] + prptmp[1] + prptmp[2]) prpfnl = numpy.array([prptmp[1] / prpcld, prptmp[2] / prpcld, prptmp[0] / prpcld]) ztmp = calculate_VPD.lgtzs(prpfnl) #z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = ztmp[0] z12tmp[t,frw,fcl] = ztmp[1] elif ( (crslb == 2) and (crclr == 1) ): frcs = numpy.array([frcvec2[frcsb[t]],frcvec1[frcsb[t]]]) if frcs[0] < 0.005: frcs[0] = 0.005 frcs[1] = frcs[1] - 0.005 elif frcs[1] < 0.005: frcs[1] = 0.005 frcs[0] = frcs[0] - 0.005 mnfrc = numpy.amin(frcs) c12tmp = random.uniform(0.0,mnfrc,size=1) prptmp = numpy.array( [0.999 * (frcs[0] - c12tmp[0]*frcs[1]), \ 0.999 * (frcs[1] - c12tmp[0]*frcs[0]), 0.999 * c12tmp[0], 0.001]) prptmp[3] = 1.0 - prptmp[0] - prptmp[1] - prptmp[2] prpcld = (prptmp[0] + prptmp[1] + prptmp[2]) prpfnl = numpy.array([prptmp[1] / prpcld, prptmp[2] / prpcld, prptmp[0] / prpcld]) ztmp = calculate_VPD.lgtzs(prpfnl) #z1tmp[t,frw,fcl] = ztmp[0] z2tmp[t,frw,fcl] = ztmp[0] z12tmp[t,frw,fcl] = ztmp[1] cctr = cctr + 1 if tsmp == 0: #cfclgt1out = numpy.zeros(z1tmp.shape) #cfclgt1out[:,:,:] = z1tmp cfclgt2out = numpy.zeros(z2tmp.shape) cfclgt2out[:,:,:] = z2tmp cfclgt12out = numpy.zeros(z12tmp.shape) cfclgt12out[:,:,:] = z12tmp else: #cfclgt1out = numpy.append(cfclgt1out,z1tmp,axis=0) cfclgt2out = numpy.append(cfclgt2out,z2tmp,axis=0) cfclgt12out = numpy.append(cfclgt12out,z12tmp,axis=0) # Cloud Non-Gas Water ngwttmp1 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp1[nslbtmp >= 1] = cngwt1[nslbtmp >= 1] ngwttmp1[swpsq] = cngwt2[swpsq] ngwttmp2 = numpy.zeros(cngwt1.shape[0]) - 9999.0 ngwttmp2[nslbtmp == 2] = cngwt2[nslbtmp == 2] ngwttmp2[swpsq] = cngwt1[swpsq] if tsmp == 0: ngwt1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 ngwt1out[:] = ngwttmp1[frcsb] ngwt2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 ngwt2out[:] = ngwttmp2[frcsb] else: ngwt1out = numpy.append(ngwt1out,ngwttmp1[frcsb]) ngwt2out = numpy.append(ngwt2out,ngwttmp2[frcsb]) # Cloud Top Temperature cttptmp1 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp1[nslbtmp >= 1] = cttp1[nslbtmp >= 1] cttptmp1[swpsq] = cttp2[swpsq] cttptmp2 = numpy.zeros(cttp1.shape[0]) - 9999.0 cttptmp2[nslbtmp == 2] = cttp2[nslbtmp == 2] cttptmp2[swpsq] = cttp1[swpsq] if tsmp == 0: cttp1out = numpy.zeros((frcsb.shape[0],)) - 9999.0 cttp1out[:] = cttptmp1[frcsb] cttp2out = numpy.zeros((frcsb.shape[0],)) - 9999.0 cttp2out[:] = cttptmp2[frcsb] else: cttp1out = numpy.append(cttp1out,cttptmp1[frcsb]) cttp2out = numpy.append(cttp2out,cttptmp2[frcsb]) # Temp/RH profiles tmptmp = numpy.zeros((nairs,nzout)) h2otmp = numpy.zeros((nairs,nzout)) alttmp = numpy.zeros((nairs,nzout)) for j in range(nzout): tmpvec = tmparr[:,j,:,:].flatten() tmpvec[tmpvec > 1e30] = -9999. tmptmp[:,j] = tmpvec[frcsb] altvec = altarr[:,j,:,:].flatten() alttmp[:,j] = altvec[frcsb] h2ovec = h2oarr[:,j,:,:].flatten() h2ovec[h2ovec > 1e30] = -9999. h2otmp[:,j] = h2ovec[frcsb] if tsmp == 0: tmpmerout = numpy.zeros(tmptmp.shape) tmpmerout[:,:] = tmptmp h2omerout = numpy.zeros(h2otmp.shape) h2omerout[:,:] = h2otmp altout = numpy.zeros(alttmp.shape) altout[:,:] = alttmp else: tmpmerout = numpy.append(tmpmerout,tmptmp,axis=0) h2omerout = numpy.append(h2omerout,h2otmp,axis=0) altout = numpy.append(altout,alttmp,axis=0) # Surface stparr = stparr.flatten() psfarr = psfc.flatten() if salarr.ndim == 2: salarr = salarr.flatten() salfl = numpy.tile(salarr[:],nt) elif salarr.ndim == 3: salfl = salarr.flatten() if tsmp == 0: sftmpout = numpy.zeros((nairs,)) - 9999.0 sftmpout[:] = stparr[frcsb] psfcout = numpy.zeros((nairs,)) - 9999.0 psfcout[:] = psfarr[frcsb] sfaltout = numpy.zeros((nairs,)) - 9999.0 sfaltout[:] = salfl[frcsb] else: sftmpout = numpy.append(sftmpout,stparr[frcsb]) psfcout = numpy.append(psfcout,psfarr[frcsb]) sfaltout = numpy.append(sfaltout,salfl[frcsb]) # Loc/Time if tsmp == 0: latout = numpy.zeros((frcsb.shape[0],)) - 9999.0 latout[:] = lthld[frcsb] lonout = numpy.zeros((frcsb.shape[0],)) - 9999.0 lonout[:] = lnhld[frcsb] yrout = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) yrout[:] = yrlst[k] jdyout = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) jdyout[:] = tmhld[frcsb] else: latout = numpy.append(latout,lthld[frcsb]) lonout = numpy.append(lonout,lnhld[frcsb]) yrtmp = numpy.zeros((frcsb.shape[0],),dtype=numpy.int16) yrtmp[:] = yrlst[k] yrout = numpy.append(yrout,yrtmp) jdyout = numpy.append(jdyout,tmhld[frcsb]) tsmp = tsmp + nairs # Process quantiles nslbqs = calculate_VPD.quantile_msgdat_discrete(nslabout,prbs) str1 = '%.2f Number Slab Quantile: %d' % (prbs[103],nslbqs[103]) print(str1) print(nslbqs) # psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) # str1 = '%.2f Surface Pressure Quantile: %.3f' % (prbs[53],psfcqs[53]) # print(str1) prsbt1qs = calculate_VPD.quantile_msgdat(prsbot1out,prbs) str1 = '%.2f CldBot1 Pressure Quantile: %.3f' % (prbs[103],prsbt1qs[103]) print(str1) dpcld1qs = calculate_VPD.quantile_msgdat(dpcld1out,prbs) str1 = '%.2f DPCloud1 Quantile: %.3f' % (prbs[103],dpcld1qs[103]) print(str1) dpslbqs = calculate_VPD.quantile_msgdat(dpslbout,prbs) str1 = '%.2f DPSlab Quantile: %.3f' % (prbs[103],dpslbqs[103]) print(str1) dpcld2qs = calculate_VPD.quantile_msgdat(dpcld2out,prbs) str1 = '%.2f DPCloud2 Quantile: %.3f' % (prbs[103],dpcld2qs[103]) print(str1) slb1qs = calculate_VPD.quantile_msgdat_discrete(slbtyp1out,prbs) str1 = '%.2f Type1 Quantile: %d' % (prbs[103],slb1qs[103]) print(str1) slb2qs = calculate_VPD.quantile_msgdat_discrete(slbtyp2out,prbs) str1 = '%.2f Type2 Quantile: %d' % (prbs[103],slb2qs[103]) print(str1) # Indicators totclrqout = numpy.zeros((3,3,nprb)) - 99 frctotqout = numpy.zeros((3,3,nprb)) - 9999.0 #lgt1qs = numpy.zeros((3,3,nprb)) - 9999.0 lgt2qs = numpy.zeros((3,3,nprb)) - 9999.0 lgt12qs = numpy.zeros((3,3,nprb)) - 9999.0 for frw in range(3): for fcl in range(3): tmpclr = calculate_VPD.quantile_msgdat_discrete(totclrout[:,frw,fcl],prbs) totclrqout[frw,fcl,:] = tmpclr[:] str1 = 'Clr/Ovc Indicator %d, %d %.2f Quantile: %d' % (frw,fcl,prbs[103],tmpclr[103]) print(str1) tmpfrcq = calculate_VPD.quantile_msgdat(frctotout[:,frw,fcl],prbs) frctotqout[frw,fcl,:] = tmpfrcq[:] str1 = 'Tot Cld Frac %d, %d %.2f Quantile: %.4f' % (frw,fcl,prbs[103],tmpfrcq[103]) print(str1) #tmplgtq = calculate_VPD.quantile_msgdat(cfclgt1out[:,frw,fcl],prbs) #lgt1qs[frw,fcl,:] = tmplgtq[:] tmplgtq = calculate_VPD.quantile_msgdat(cfclgt2out[:,frw,fcl],prbs) lgt2qs[frw,fcl,:] = tmplgtq[:] tmplgtq = calculate_VPD.quantile_msgdat(cfclgt12out[:,frw,fcl],prbs) lgt12qs[frw,fcl,:] = tmplgtq[:] str1 = 'CFrac Logit %d, %d %.2f Quantile: %.3f, %.3f' % (frw,fcl,prbs[103], \ lgt2qs[frw,fcl,103],lgt12qs[frw,fcl,103]) print(str1) ngwt1qs = calculate_VPD.quantile_msgdat(ngwt1out,prbs) str1 = '%.2f NGWater1 Quantile: %.3f' % (prbs[103],ngwt1qs[103]) print(str1) ngwt2qs = calculate_VPD.quantile_msgdat(ngwt2out,prbs) str1 = '%.2f NGWater2 Quantile: %.3f' % (prbs[103],ngwt2qs[103]) print(str1) cttp1qs = calculate_VPD.quantile_msgdat(cttp1out,prbs) str1 = '%.2f CTTemp1 Quantile: %.3f' % (prbs[103],cttp1qs[103]) print(str1) cttp2qs = calculate_VPD.quantile_msgdat(cttp2out,prbs) str1 = '%.2f CTTemp2 Quantile: %.3f' % (prbs[103],cttp2qs[103]) print(str1) # Temp/RH Quantiles tmpqout = numpy.zeros((nzout,nprb)) - 9999. rhqout = numpy.zeros((nzout,nprb)) - 9999. sftmpqs = numpy.zeros((nprb,)) - 9999. sfaltqs = numpy.zeros((nprb,)) - 9999. psfcqs = numpy.zeros((nprb,)) - 9999. altmed = numpy.zeros((nzout,)) - 9999. ztmpout = numpy.zeros((tsmp,nzout)) - 9999. zrhout = numpy.zeros((tsmp,nzout)) - 9999. zsftmpout = numpy.zeros((tsmp,)) - 9999. zsfaltout = numpy.zeros((tsmp,)) - 9999. zpsfcout = numpy.zeros((tsmp,)) - 9999. # Quantiles for j in range(nzout): tmptmp = calculate_VPD.quantile_msgdat(tmpmerout[:,j],prbs) tmpqout[j,:] = tmptmp[:] str1 = 'Plev %.2f, %.2f Temp Quantile: %.3f' % (plev[j],prbs[103],tmptmp[103]) print(str1) # Transform if some not missing if (tmptmp[0] != -9999.): ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(tmpmerout[:,j], tmptmp, prbs, msgval=-9999.) ztmpout[:,j] = ztmp[:] alttmp = calculate_VPD.quantile_msgdat(altout[:,j],prbs) altmed[j] = alttmp[103] str1 = 'Plev %.2f, %.2f Alt Quantile: %.3f' % (plev[j],prbs[103],alttmp[103]) print(str1) # Adjust RH over 100 rhadj = h2omerout[:,j] rhadj[rhadj > 1.0] = 1.0 rhqtmp = calculate_VPD.quantile_msgdat(rhadj,prbs) rhqout[j,:] = rhqtmp[:] str1 = 'Plev %.2f, %.2f RH Quantile: %.4f' % (plev[j],prbs[103],rhqtmp[103]) print(str1) if (rhqtmp[0] != -9999.): zrh = calculate_VPD.std_norm_quantile_from_obs_fill_msg(rhadj, rhqtmp, prbs, msgval=-9999.) zrhout[:,j] = zrh[:] h2omerout[:,j] = rhadj psfcqs = calculate_VPD.quantile_msgdat(psfcout,prbs) str1 = '%.2f PSfc Quantile: %.2f' % (prbs[103],psfcqs[103]) print(str1) zpsfcout = calculate_VPD.std_norm_quantile_from_obs(psfcout, psfcqs, prbs, msgval=-9999.) sftpqs = calculate_VPD.quantile_msgdat(sftmpout,prbs) str1 = '%.2f SfcTmp Quantile: %.2f' % (prbs[103],sftpqs[103]) print(str1) zsftmpout = calculate_VPD.std_norm_quantile_from_obs(sftmpout, sftpqs, prbs, msgval=-9999.) sfalqs = calculate_VPD.quantile_msgdat(sfaltout,prbs) str1 = '%.2f SfcAlt Quantile: %.2f' % (prbs[103],sfalqs[103]) print(str1) zsfaltout = calculate_VPD.std_norm_quantile_from_obs(sfaltout, sfalqs, prbs, msgval=-9999.) # Output Quantiles qfnm = '%s/CONUS_AIRS_%s_%04d_%02dUTC_%s_State_Quantile.nc' % (dtdr,sstr,yrlst[k],hrchc,rgchc) qout = Dataset(qfnm,'w') dimp = qout.createDimension('probability',nprb) dimfov1 = qout.createDimension('fovrow',3) dimfov2 = qout.createDimension('fovcol',3) dimz = qout.createDimension('level',nzout) varlvl = qout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varprb = qout.createVariable('probability','f4',['probability'], fill_value = -9999) varprb[:] = prbs varprb.long_name = 'Probability break points' varprb.units = 'none' varprb.missing_value = -9999 varnslb = qout.createVariable('NumberSlab_quantile','i2',['probability'], fill_value = -99) varnslb[:] = nslbqs varnslb.long_name = 'Number of cloud slabs quantiles' varnslb.units = 'Count' varnslb.missing_value = -99 varcbprs = qout.createVariable('CloudBot1Logit_quantile','f4',['probability'], fill_value = -9999) varcbprs[:] = prsbt1qs varcbprs.long_name = 'Slab 1 cloud bottom pressure logit quantiles' varcbprs.units = 'hPa' varcbprs.missing_value = -9999 vardpc1 = qout.createVariable('DPCloud1Logit_quantile','f4',['probability'], fill_value = -9999) vardpc1[:] = dpcld1qs vardpc1.long_name = 'Slab 1 cloud pressure depth logit quantiles' vardpc1.units = 'hPa' vardpc1.missing_value = -9999 vardpslb = qout.createVariable('DPSlabLogit_quantile','f4',['probability'], fill_value = -9999) vardpslb[:] = dpslbqs vardpslb.long_name = 'Two-slab vertical separation logit quantiles' vardpslb.units = 'hPa' vardpslb.missing_value = -9999 vardpc2 = qout.createVariable('DPCloud2Logit_quantile','f4',['probability'], fill_value = -9999) vardpc2[:] = dpcld2qs vardpc2.long_name = 'Slab 2 cloud pressure depth logit quantiles' vardpc2.units = 'hPa' vardpc2.missing_value = -9999 vartyp1 = qout.createVariable('CType1_quantile','i2',['probability'], fill_value = -99) vartyp1[:] = slb1qs vartyp1.long_name = 'Slab 1 cloud type quantiles' vartyp1.units = 'None' vartyp1.missing_value = -99 vartyp1.comment = 'Cloud slab type: 0=Liquid, 1=Ice' vartyp2 = qout.createVariable('CType2_quantile','i2',['probability'], fill_value = -99) vartyp2[:] = slb2qs vartyp2.long_name = 'Slab 2 cloud type quantiles' vartyp2.units = 'None' vartyp2.missing_value = -99 vartyp2.comment = 'Cloud slab type: 0=Liquid, 1=Ice' varcvr = qout.createVariable('CCoverInd_quantile','i2',['fovrow','fovcol','probability'], fill_value = 99) varcvr[:] = totclrqout varcvr.long_name = 'Cloud cover indicator quantiles' varcvr.units = 'None' varcvr.missing_value = -99 varcvr.comment = 'Cloud cover indicators: -1=Clear, 0=Partly cloudy, 1=Overcast' varfrc = qout.createVariable('TotCFrc_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varfrc[:] = frctotqout varfrc.long_name = 'Total cloud fraction quantiles' varfrc.units = 'None' varfrc.missing_value = -9999 #varlgt1 = qout.createVariable('CFrcLogit1_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) #varlgt1[:] = lgt1qs #varlgt1.long_name = 'Slab 1 cloud fraction (cfrac1x) logit quantiles' #varlgt1.units = 'None' #varlgt1.missing_value = -9999 varlgt2 = qout.createVariable('CFrcLogit2_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varlgt2[:] = lgt2qs varlgt2.long_name = 'Slab 2 cloud fraction (cfrac2x) logit quantiles' varlgt2.units = 'None' varlgt2.missing_value = -9999 varlgt12 = qout.createVariable('CFrcLogit12_quantile','f4',['fovrow','fovcol','probability'], fill_value = -9999) varlgt12[:] = lgt12qs varlgt12.long_name = 'Slab 1/2 overlap fraction (cfrac12) logit quantiles' varlgt12.units = 'None' varlgt12.missing_value = -9999 varngwt1 = qout.createVariable('NGWater1_quantile','f4',['probability'], fill_value = -9999) varngwt1[:] = ngwt1qs varngwt1.long_name = 'Slab 1 cloud non-gas water quantiles' varngwt1.units = 'g m^-2' varngwt1.missing_value = -9999 varngwt2 = qout.createVariable('NGWater2_quantile','f4',['probability'], fill_value = -9999) varngwt2[:] = ngwt2qs varngwt2.long_name = 'Slab 2 cloud non-gas water quantiles' varngwt2.units = 'g m^-2' varngwt2.missing_value = -9999 varcttp1 = qout.createVariable('CTTemp1_quantile','f4',['probability'], fill_value = -9999) varcttp1[:] = cttp1qs varcttp1.long_name = 'Slab 1 cloud top temperature' varcttp1.units = 'K' varcttp1.missing_value = -9999 varcttp2 = qout.createVariable('CTTemp2_quantile','f4',['probability'], fill_value = -9999) varcttp2[:] = cttp2qs varcttp2.long_name = 'Slab 2 cloud top temperature' varcttp2.units = 'K' varcttp2.missing_value = -9999 # Altitude grid varalt = qout.createVariable('Altitude_median', 'f4', ['level'], fill_value = -9999) varalt[:] = altmed varalt.long_name = 'Altitude median value' varalt.units = 'm' varalt.missing_value = -9999 vartmp = qout.createVariable('Temperature_quantile', 'f4', ['level','probability'], fill_value = -9999) vartmp[:] = tmpqout vartmp.long_name = 'Temperature quantiles' vartmp.units = 'K' vartmp.missing_value = -9999. varrh = qout.createVariable('RH_quantile', 'f4', ['level','probability'], fill_value = -9999) varrh[:] = rhqout varrh.long_name = 'Relative humidity quantiles' varrh.units = 'Unitless' varrh.missing_value = -9999. varstmp = qout.createVariable('SfcTemp_quantile', 'f4', ['probability'], fill_value = -9999) varstmp[:] = sftpqs varstmp.long_name = 'Surface temperature quantiles' varstmp.units = 'K' varstmp.missing_value = -9999. varpsfc = qout.createVariable('SfcPres_quantile', 'f4', ['probability'], fill_value = -9999) varpsfc[:] = psfcqs varpsfc.long_name = 'Surface pressure quantiles' varpsfc.units = 'hPa' varpsfc.missing_value = -9999. varsalt = qout.createVariable('SfcAlt_quantile', 'f4', ['probability'], fill_value = -9999) varsalt[:] = sfalqs varsalt.long_name = 'Surface altitude quantiles' varsalt.units = 'm' varsalt.missing_value = -9999. qout.close() # Set up transformations zccvout = numpy.zeros((tsmp,3,3,)) - 9999. zfrcout = numpy.zeros((tsmp,3,3,)) - 9999. #zlgt1 = numpy.zeros((tsmp,3,3)) - 9999. zlgt2 = numpy.zeros((tsmp,3,3)) - 9999. zlgt12 = numpy.zeros((tsmp,3,3)) - 9999. znslb = calculate_VPD.std_norm_quantile_from_obs(nslabout, nslbqs, prbs, msgval=-99) zprsbt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(prsbot1out, prsbt1qs, prbs, msgval=-9999.) zdpcld1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld1out, dpcld1qs, prbs, msgval=-9999.) zdpslb = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpslbout, dpslbqs, prbs, msgval=-9999.) zdpcld2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(dpcld2out, dpcld2qs, prbs, msgval=-9999.) zctyp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp1out, slb1qs, prbs, msgval=-99) zctyp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(slbtyp2out, slb2qs, prbs, msgval=-99) for frw in range(3): for fcl in range(3): ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(totclrout[:,frw,fcl], totclrqout[frw,fcl,:], \ prbs, msgval=-99) zccvout[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(frctotout[:,frw,fcl], frctotqout[frw,fcl,:], \ prbs, msgval=-9999.) zfrcout[:,frw,fcl] = ztmp[:] #ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt1out[:,frw,fcl], lgt1qs[frw,fcl,:], \ # prbs, msgval=-9999.) #zlgt1[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt2out[:,frw,fcl], lgt2qs[frw,fcl,:], \ prbs, msgval=-9999.) zlgt2[:,frw,fcl] = ztmp[:] ztmp = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cfclgt12out[:,frw,fcl], lgt12qs[frw,fcl,:], \ prbs, msgval=-9999.) zlgt12[:,frw,fcl] = ztmp[:] zngwt1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt1out, ngwt1qs, prbs, msgval=-9999.) zngwt2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(ngwt2out, ngwt2qs, prbs, msgval=-9999.) zcttp1 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp1out, cttp1qs, prbs, msgval=-9999.) zcttp2 = calculate_VPD.std_norm_quantile_from_obs_fill_msg(cttp2out, cttp2qs, prbs, msgval=-9999.) # Output transformed quantile samples zfnm = '%s/CONUS_AIRS_%s_%04d_%02dUTC_%s_State_StdGausTrans.nc' % (dtdr,sstr,yrlst[k],hrchc,rgchc) zout = Dataset(zfnm,'w') dimsmp = zout.createDimension('sample',tsmp) dimfov1 = zout.createDimension('fovrow',3) dimfov2 = zout.createDimension('fovcol',3) dimz = zout.createDimension('level',nzout) varlon = zout.createVariable('Longitude','f4',['sample']) varlon[:] = lonout varlon.long_name = 'Longitude' varlon.units = 'degrees_east' varlat = zout.createVariable('Latitude','f4',['sample']) varlat[:] = latout varlat.long_name = 'Latitude' varlat.units = 'degrees_north' varlvl = zout.createVariable('level','f4',['level'], fill_value = -9999) varlvl[:] = plev varlvl.long_name = 'AIRS/SARTA pressure levels' varlvl.units = 'hPa' varlvl.missing_value = -9999 varjdy = zout.createVariable('JulianDay','i2',['sample']) varjdy[:] = jdyout varjdy.long_name = 'JulianDay' varjdy.units = 'day' varyr = zout.createVariable('Year','i2',['sample']) varyr[:] = yrout varyr.long_name = 'Year' varyr.units = 'year' varnslb = zout.createVariable('NumberSlab_StdGaus','f4',['sample'], fill_value = -9999) varnslb[:] = znslb varnslb.long_name = 'Quantile transformed number of cloud slabs' varnslb.units = 'None' varnslb.missing_value = -9999. vdtnslb = zout.createVariable('NumberSlab_Data','i2',['sample'], fill_value = -99) vdtnslb[:] = nslabout vdtnslb.long_name = 'Number of cloud slabs' vdtnslb.units = 'None' vdtnslb.missing_value = -99 varcbprs = zout.createVariable('CloudBot1Logit_StdGaus','f4',['sample'], fill_value = -9999) varcbprs[:] = zprsbt1 varcbprs.long_name = 'Quantile transformed slab 1 cloud bottom pressure logit' varcbprs.units = 'None' varcbprs.missing_value = -9999. vdtcbprs = zout.createVariable('CloudBot1Logit_Data','f4',['sample'], fill_value = -9999) vdtcbprs[:] = prsbot1out vdtcbprs.long_name = 'Slab 1 cloud bottom pressure logit' vdtcbprs.units = 'None' vdtcbprs.missing_value = -9999. vardpc1 = zout.createVariable('DPCloud1Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc1[:] = zdpcld1 vardpc1.long_name = 'Quantile transformed slab 1 cloud pressure depth logit' vardpc1.units = 'None' vardpc1.missing_value = -9999. vdtdpc1 = zout.createVariable('DPCloud1Logit_Data','f4',['sample'], fill_value = -9999) vdtdpc1[:] = dpcld1out vdtdpc1.long_name = 'Slab 1 cloud pressure depth logit' vdtdpc1.units = 'None' vdtdpc1.missing_value = -9999. vardpslb = zout.createVariable('DPSlabLogit_StdGaus','f4',['sample'], fill_value = -9999) vardpslb[:] = zdpslb vardpslb.long_name = 'Quantile transformed two-slab vertical separation logit' vardpslb.units = 'None' vardpslb.missing_value = -9999. vdtdpslb = zout.createVariable('DPSlabLogit_Data','f4',['sample'], fill_value = -9999) vdtdpslb[:] = dpslbout vdtdpslb.long_name = 'Two-slab vertical separation logit' vdtdpslb.units = 'None' vdtdpslb.missing_value = -9999. vardpc2 = zout.createVariable('DPCloud2Logit_StdGaus','f4',['sample'], fill_value = -9999) vardpc2[:] = zdpcld2 vardpc2.long_name = 'Quantile transformed slab 2 cloud pressure depth logit' vardpc2.units = 'None' vardpc2.missing_value = -9999. vdtdpc2 = zout.createVariable('DPCloud2Logit_Data','f4',['sample'], fill_value = -9999) vdtdpc2[:] = dpcld2out vdtdpc2.long_name = 'Slab 2 cloud pressure depth logit' vdtdpc2.units = 'None' vdtdpc2.missing_value = -9999. vartyp1 = zout.createVariable('CType1_StdGaus','f4',['sample'], fill_value = -9999) vartyp1[:] = zctyp1 vartyp1.long_name = 'Quantile transformed slab 1 cloud type' vartyp1.units = 'None' vartyp1.missing_value = -9999. vdttyp1 = zout.createVariable('CType1_Data','i2',['sample'], fill_value = -99) vdttyp1[:] = slbtyp1out vdttyp1.long_name = 'Slab 1 cloud type' vdttyp1.units = 'None' vdttyp1.missing_value = -99 vartyp2 = zout.createVariable('CType2_StdGaus','f4',['sample'], fill_value = -9999) vartyp2[:] = zctyp2 vartyp2.long_name = 'Quantile transformed slab 2 cloud type' vartyp2.units = 'None' vartyp2.missing_value = -9999. vdttyp2 = zout.createVariable('CType2_Data','i2',['sample'], fill_value = -99) vdttyp2[:] = slbtyp2out vdttyp2.long_name = 'Slab 2 cloud type logit' vdttyp2.units = 'None' vdttyp2.missing_value = -99 varcov = zout.createVariable('CCoverInd_StdGaus','f4',['sample','fovrow','fovcol'], fill_value= -9999) varcov[:] = zccvout varcov.long_name = 'Quantile transformed cloud cover indicator' varcov.units = 'None' varcov.missing_value = -9999. vdtcov = zout.createVariable('CCoverInd_Data','i2',['sample','fovrow','fovcol'], fill_value= -99) vdtcov[:] = totclrout vdtcov.long_name = 'Cloud cover indicator' vdtcov.units = 'None' vdtcov.missing_value = -99 varfrc = zout.createVariable('TotCFrc_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varfrc[:] = zfrcout varfrc.long_name = 'Quantile transformed total cloud fraction' varfrc.units = 'None' varfrc.missing_value = -9999 vdtfrc = zout.createVariable('TotCFrc_Data','f4',['sample','fovrow','fovcol'], fill_value = -9999) vdtfrc[:] = frctotout vdtfrc.long_name = 'Total cloud fraction' vdtfrc.units = 'None' vdtfrc.missing_value = -9999 #varlgt1 = zout.createVariable('CFrcLogit1_StdGaus','f4',['fovrow','fovcol','sample'], fill_value = -9999) #varlgt1[:] = zlgt1 #varlgt1.long_name = 'Quantile transformed slab 1 cloud fraction logit' #varlgt1.units = 'None' #varlgt1.missing_value = -9999. varlgt2 = zout.createVariable('CFrcLogit2_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varlgt2[:] = zlgt2 varlgt2.long_name = 'Quantile transformed slab 2 cloud fraction logit' varlgt2.units = 'None' varlgt2.missing_value = -9999. vdtlgt2 = zout.createVariable('CFrcLogit2_Data','f4',['sample','fovrow','fovcol'], fill_value = -9999) vdtlgt2[:] = cfclgt2out vdtlgt2.long_name = 'Slab 2 cloud fraction logit' vdtlgt2.units = 'None' vdtlgt2.missing_value = -9999. varlgt12 = zout.createVariable('CFrcLogit12_StdGaus','f4',['sample','fovrow','fovcol'], fill_value = -9999) varlgt12[:] = zlgt12 varlgt12.long_name = 'Quantile transformed slab 1/2 overlap fraction logit' varlgt12.units = 'None' varlgt12.missing_value = -9999. vdtlgt12 = zout.createVariable('CFrcLogit12_Data','f4',['sample','fovrow','fovcol'], fill_value = -9999) vdtlgt12[:] = cfclgt12out vdtlgt12.long_name = 'Slab 1/2 overlap fraction logit' vdtlgt12.units = 'None' vdtlgt12.missing_value = -9999. varngwt1 = zout.createVariable('NGWater1_StdGaus','f4',['sample'], fill_value = -9999) varngwt1[:] = zngwt1 varngwt1.long_name = 'Quantile transformed slab 1 non-gas water' varngwt1.units = 'None' varngwt1.missing_value = -9999. vdtngwt1 = zout.createVariable('NGWater1_Data','f4',['sample'], fill_value = -9999) vdtngwt1[:] = ngwt1out vdtngwt1.long_name = 'Slab 1 non-gas water' vdtngwt1.units = 'None' vdtngwt1.missing_value = -9999. varngwt2 = zout.createVariable('NGWater2_StdGaus','f4',['sample'], fill_value = -9999) varngwt2[:] = zngwt2 varngwt2.long_name = 'Quantile transformed slab 2 non-gas water' varngwt2.units = 'None' varngwt2.missing_value = -9999. vdtngwt2 = zout.createVariable('NGWater2_Data','f4',['sample'], fill_value = -9999) vdtngwt2[:] = ngwt2out vdtngwt2.long_name = 'Slab 2 non-gas water' vdtngwt2.units = 'None' vdtngwt2.missing_value = -9999. varcttp1 = zout.createVariable('CTTemp1_StdGaus','f4',['sample'], fill_value = -9999) varcttp1[:] = zcttp1 varcttp1.long_name = 'Quantile transformed slab 1 cloud top temperature' varcttp1.units = 'None' varcttp1.missing_value = -9999. vdtcttp1 = zout.createVariable('CTTemp1_Data','f4',['sample'], fill_value = -9999) vdtcttp1[:] = cttp1out vdtcttp1.long_name = 'Slab 1 cloud top temperature' vdtcttp1.units = 'K' vdtcttp1.missing_value = -9999. varcttp2 = zout.createVariable('CTTemp2_StdGaus','f4',['sample'], fill_value = -9999) varcttp2[:] = zcttp2 varcttp2.long_name = 'Quantile transformed slab 2 cloud top temperature' varcttp2.units = 'None' varcttp2.missing_value = -9999. vdtcttp2 = zout.createVariable('CTTemp2_Data','f4',['sample'], fill_value = -9999) vdtcttp2[:] = cttp2out vdtcttp2.long_name = 'Slab 2 cloud top temperature' vdtcttp2.units = 'K' vdtcttp2.missing_value = -9999. varsrt3 = zout.createVariable('Temperature_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt3[:] = ztmpout varsrt3.long_name = 'Quantile transformed temperature' varsrt3.units = 'None' varsrt3.missing_value = -9999. vdtsrt3 = zout.createVariable('Temperature_Data', 'f4', ['sample','level'], fill_value = -9999) vdtsrt3[:] = tmpmerout vdtsrt3.long_name = 'Temperature' vdtsrt3.units = 'K' vdtsrt3.missing_value = -9999. varsrt4 = zout.createVariable('RH_StdGaus', 'f4', ['sample','level'], fill_value = -9999) varsrt4[:] = zrhout varsrt4.long_name = 'Quantile transformed relative humidity' varsrt4.units = 'None' varsrt4.missing_value = -9999. vdtsrt4 = zout.createVariable('RH_Data', 'f4', ['sample','level'], fill_value = -9999) vdtsrt4[:] = h2omerout vdtsrt4.long_name = 'Relative humidity' vdtsrt4.units = 'None' vdtsrt4.missing_value = -9999. varsrts1 = zout.createVariable('SfcTemp_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts1[:] = zsftmpout varsrts1.long_name = 'Quantile transformed surface temperature' varsrts1.units = 'None' varsrts1.missing_value = -9999. vdtsrts1 = zout.createVariable('SfcTemp_Data', 'f4', ['sample'], fill_value = -9999) vdtsrts1[:] = sftmpout vdtsrts1.long_name = 'Surface temperature' vdtsrts1.units = 'None' vdtsrts1.missing_value = -9999. varsrts2 = zout.createVariable('SfcPres_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts2[:] = zpsfcout varsrts2.long_name = 'Quantile transformed surface pressure' varsrts2.units = 'None' varsrts2.missing_value = -9999. vdtsrts2 = zout.createVariable('SfcPres_Data', 'f4', ['sample'], fill_value = -9999) vdtsrts2[:] = psfcout vdtsrts2.long_name = 'Surface pressure' vdtsrts2.units = 'hPa' vdtsrts2.missing_value = -9999. varsrts3 = zout.createVariable('SfcAlt_StdGaus', 'f4', ['sample'], fill_value = -9999) varsrts3[:] = zsfaltout varsrts3.long_name = 'Quantile transformed surface altitude' varsrts3.units = 'None' varsrts3.missing_value = -9999. vdtsrts3 = zout.createVariable('SfcAlt_Data', 'f4', ['sample'], fill_value = -9999) vdtsrts3[:] = sfaltout vdtsrts3.long_name = 'Surface altitude' vdtsrts3.units = 'm' vdtsrts3.missing_value = -9999. zout.close() return def zscore_update_mcem(outfile, qfile, zfile, dfile, cnffile, probs, niter = 50, sdchc = 553133): # Monte Carlo expectation maximization update for zscores # outfile: Output file with updated z-scores, MCEM results # qfile: Quantile file # zfile: Input z-score file # dfile: Data file # cnffile: Configuration file (CSV) # probs: Probability levels for quantile # niter: Maximum number of EM iterations # sdchc: Random seed df = pandas.read_csv(cnffile, dtype = {'Order':int, 'ZScore_Name':str, 'Quantile_Name':str, \ 'Data_Name':str, 'Start':int, 'Length':int, 'DType':str }) tsz = df['Length'].sum() szstr = '%d Total State Vector Elements' % (tsz) print(szstr) nrw = df.shape[0] nsmp = -1 stctr = 0 # RN generator random.seed(sdchc) # Initialize MVN parameters mu0 = numpy.zeros((tsz,),dtype=numpy.float64) cv0 = numpy.zeros((tsz,tsz),dtype=numpy.float64) # Loop through groups to initialize print(qfile) print(zfile) for q in range(nrw): if (df['Length'].values[q] == 1): cv0[stctr,stctr] = 1.0 else: cst = stctr cfn = stctr + df['Length'].values[q] diagvl = numpy.zeros( (df['Length'].values[q],), dtype=numpy.float64) + 0.6 cvblk = numpy.zeros( (df['Length'].values[q],df['Length'].values[q]), dtype=numpy.float64) + 0.4 + \ numpy.diagflat( diagvl) cv0[cst:cfn,cst:cfn] = cvblk qvrnm = df['Quantile_Name'].values[q] fqs = Dataset(qfile,'r') if (df['Group'].values[q] == 'CloudFrac'): qtmp = fqs.variables[qvrnm][:,:,:] elif (df['Length'].values[q] > 1): qtmp = fqs.variables[qvrnm][:,:] else: qtmp = fqs.variables[qvrnm][:] fqs.close() zvrnm = df['ZScore_Name'].values[q] fzs = Dataset(zfile,'r') if (df['Group'].values[q] == 'CloudFrac'): ztmp = fzs.variables[zvrnm][:,:,:] elif (df['Length'].values[q] > 1): ztmp = fzs.variables[zvrnm][:,:] else: ztmp = fzs.variables[zvrnm][:] if nsmp < 0: nsmp = ztmp.shape[0] zscrarr = numpy.zeros((nsmp,tsz),dtype=numpy.float32) zlwrarr = numpy.zeros((nsmp,tsz),dtype=numpy.float32) zuprarr = numpy.zeros((nsmp,tsz),dtype=numpy.float32) fzs.close() yvrnm = df['Data_Name'].values[q] fys = Dataset(dfile,'r') if (df['Group'].values[q] == 'CloudFrac'): dttmp = fys.variables[yvrnm][:,:,:] elif (df['Length'].values[q] > 1): dttmp = fys.variables[yvrnm][:,:] else: dttmp = fys.variables[yvrnm][:] msgvl = fys.variables[yvrnm].missing_value fys.close() # Find z-score limits if (df['Group'].values[q] == 'CloudFrac'): cctr = 0 for frw in range(3): for fcl in range(3): ztmplwr, ztmpupr = calculate_VPD.std_norm_limits_from_obs_fill_msg(dttmp[:,frw,fcl], qtmp[frw,fcl,:], probs, msgvl) cctr = cctr + 1 zlwrarr[:,stctr] = ztmplwr[:] zuprarr[:,stctr] = ztmpupr[:] zchk = ztmp[:,frw,fcl] zmsg = zchk[zchk < -10.0] zchk[zchk < -10.0] = random.uniform(size=zmsg.shape[0]) zscrarr[:,stctr] = zchk[:] zdif = ztmpupr - ztmplwr zsm = numpy.sum( (zdif < 0)) if zsm > 0: zstr = 'Lower Upper Mismatch\n %s (%d): %d' % (df['ZScore_Name'].values[q],cctr,zsm) print(zstr) stctr = stctr + 1 elif (df['Length'].values[q] > 1): stidx = df['Start'].values[q] - 1 fnidx = stidx + df['Length'].values[q] for k in range(stidx,fnidx): ztmplwr, ztmpupr = calculate_VPD.std_norm_limits_from_obs_fill_msg(dttmp[:,k], qtmp[k,:], probs, msgvl) zlwrarr[:,stctr] = ztmplwr[:] zuprarr[:,stctr] = ztmpupr[:] zchk = ztmp[:,k] zmsg = zchk[zchk < -10.0] zchk[zchk < -10.0] = random.uniform(size=zmsg.shape[0]) zscrarr[:,stctr] = zchk[:] zdif = ztmpupr - ztmplwr zsm = numpy.sum( (zdif < 0)) if zsm > 0: zstr = 'Lower Upper Mismatch\n %s (%d): %d' % (df['ZScore_Name'].values[q],k,zsm) print(zstr) stctr = stctr + 1 else: ztmplwr, ztmpupr = calculate_VPD.std_norm_limits_from_obs_fill_msg(dttmp, qtmp, probs, msgvl) zlwrarr[:,stctr] = ztmplwr[:] zuprarr[:,stctr] = ztmpupr[:] zchk = ztmp[:] zmsg = zchk[zchk < -10.0] zchk[zchk < -10.0] = random.uniform(size=zmsg.shape[0]) zscrarr[:,stctr] = zchk[:] zdif = ztmpupr - ztmplwr zsm = numpy.sum( (zdif < 0)) if zsm > 0: zstr = 'Lower Upper Mismatch\n %s: %d' % (df['ZScore_Name'].values[q],zsm) print(zstr) stctr = stctr + 1 print(nsmp) lgdns = stats.multivariate_normal.logpdf(zscrarr, mean=mu0, cov=cv0) cmpllk = numpy.sum(lgdns) lkstr = 'Initial Log-likelihood: %.4e' % (cmpllk) print(lkstr) mucr = mu0 cvcr = cv0 crlk = cmpllk lkdf = 1e8 zfnl = zscrarr # Setup output emout = Dataset(outfile,'w') dimiter = emout.createDimension('iteration',niter) dimstate = emout.createDimension('state',tsz) dimsmp = emout.createDimension('sample',nsmp) varlk = emout.createVariable('logLike','f8',['iteration'], fill_value = -9999) varlk.long_name = 'Complete information log likelihood' varlk.units = 'None' varlk.missing_value = -9999 varmn = emout.createVariable('state_mean','f4',['iteration','state'], fill_value = -9999) varmn.long_name = 'Multivariate state mean vector' varmn.units = 'None' varmn.missing_value = -9999 varcv = emout.createVariable('state_cov','f4',['iteration','state','state'], fill_value = -9999) varcv.long_name = 'Multivariate state covariance matrix' varcv.units = 'None' varcv.missing_value = -9999 varest = emout.createVariable('state_samples','f4',['iteration','sample','state'], fill_value = -9999) varest.long_name = 'State variable expected values' varest.units = 'None' varest.missing_value = -9999 emout.close() critr = 0 while ( (critr < niter) and (lkdf > 1e3)): # MCMC prccr = linalg.inv(cvcr) zfnl, zmn1 = calculate_VPD.trnc_norm_mcmc(zfnl, mucr, prccr, zlwrarr, zuprarr, \ niter = 450, nburn = 50, nvec = nsmp, nstate = tsz) # Mean and Cov cvcr = numpy.cov(zmn1.T) mucr = numpy.mean(zmn1,axis=0) w, v = linalg.eig(cvcr) wsq = numpy.arange(w.shape[0]) wsb = wsq[w < 1.5e-8] if wsb.shape[0] > 0: s1 = 'Lifting %d eigenvalues' % (wsb.shape[0]) print(s1) print(w[150:174]) w[wsb] = 1.5e-8 wdg = numpy.diagflat(w) cvcr = numpy.dot(v, numpy.dot(wdg,v.T)) lgdns = stats.multivariate_normal.logpdf(zmn1, mean=mucr, cov=cvcr) cmpllk = numpy.sum(lgdns) lkdf = cmpllk - crlk lkstrcr = '''At EM Iteration %d, Log-likelihood: %.4e Log-like increase: %.4e Minimimum Eigenvalue: %.6e''' % (critr,cmpllk,lkdf,numpy.amin(w)) print(lkstrcr) crlk = cmpllk # Save results emout = Dataset(outfile,'r+') varlk = emout.variables['logLike'] varlk[critr] = cmpllk varmn = emout.variables['state_mean'] varmn[critr,:] = mucr varcv = emout.variables['state_cov'] varcv[critr,:,:] = cvcr varest = emout.variables['state_samples'] varest[critr,:,:] = zmn1 emout.close() critr = critr + 1 return def airs_raw_l2_summary(expdir, outfnm, nrep=10): # Extract desired AIRS L2 files directly from experiment results # expfl: Name of file with experiment results # outfnm: Ouptut file name # nrep: Number of replicates of the reference AIRS granule # Experiment should have one directory per replicate nzairs = 100 nzsrt = 101 nsmpout = nrep * 45 * 30 # Set up output (PSfc, temp profile and QC) qout = Dataset(outfnm,'w') dimsmp = qout.createDimension('sample',nsmpout) dimlev = qout.createDimension('level',nzairs) varpsfc = qout.createVariable('PSurfStd','f4',['sample'], fill_value = -9999) varpsfc.long_name = 'Surface pressure' varpsfc.units = 'hPa' varpsfc.missing_value = -9999 var2m = qout.createVariable('TSurfAir','f4',['sample'], fill_value = -9999) var2m.long_name = 'Near-surface air temperature' var2m.units = 'K' var2m.missing_value = -9999 vart2qc = qout.createVariable('TSurfAir_QC','i2',['sample'], fill_value = -99) vart2qc.long_name = 'Near-surface air temperature QC' vart2qc.units = 'none' vart2qc.missing_value = -99 vartmp = qout.createVariable('TAirSup','f4',['sample','level'], fill_value = -9999) vartmp.long_name = 'Air temperature' vartmp.units = 'K' vartmp.missing_value = -9999 vartqc = qout.createVariable('TAirSup_QC','i2',['sample','level'], fill_value = -99) vartqc.long_name = 'Air temperature QC' vartqc.units = 'none' vartqc.missing_value = -99 qout.close() for k in range(nrep): simdir = '%sindex_%d' % (expdir,k+1) print(simdir) if os.path.exists(simdir): flst = os.listdir(simdir) l2lst = [] for j in range(len(flst)): if ('L2.RetSup' in flst[j]): l2lst.append(flst[j]) # Sort by L2 run index xlst = [] for j in range(len(l2lst)): l2prs = l2lst[j].split('.') lnl2 = len(l2prs) xstr = l2prs[lnl2-2] lnx = len(xstr) tstr = xstr[1:lnx] xlst.append(int(tstr)) print(xlst) l2frm = pandas.DataFrame({'L2SupFile': l2lst, 'RunIndex': xlst}) l2frm = l2frm.sort_values(by=['RunIndex'], ascending=[True]) # Use only most recent 45 l2ln = l2frm.shape[0] if l2ln > 45: lidxst = l2ln-45 lidxfn = l2ln else: lidxst = 0 lidxfn = l2ln l2frm = l2frm[lidxst:lidxfn] tmparr = numpy.zeros( (45,30), dtype=numpy.float32) - 9999.0 for j in range(l2frm.shape[0]): l2fl = '%s/%s' % (simdir,l2frm['L2SupFile'].values[j]) ncl2 = Dataset(l2fl) psfc = ncl2.variables['PSurfStd'][0,:] tprf = ncl2.variables['TAirSup'][0,:,:] tmpqc = ncl2.variables['TAirSup_QC'][0,:,:] t2m = ncl2.variables['TSurfAir'][0,:] t2mqc = ncl2.variables['TSurfAir_QC'][0,:] ncl2.close() ost = k*45*30 + j*30 ofn = k*45*30 + (j+1)*30 ncout = Dataset(outfnm,'r+') varpsfc = ncout.variables['PSurfStd'] varpsfc[ost:ofn] = psfc vartmp = ncout.variables['TAirSup'] vartmp[ost:ofn,:] = tprf varqc = ncout.variables['TAirSup_QC'] varqc[ost:ofn,:] = tmpqc vart2m = ncout.variables['TSurfAir'] vart2m[ost:ofn] = t2m var2qc = ncout.variables['TSurfAir_QC'] var2qc[ost:ofn] = t2mqc ncout.close() return def airscld_invtransf_stateconf_cloud9(rffl, qfl, gmmfl, outfl, stcnf, yrchc, rfmn, rfdy, rfgrn, scnrw, nrep = 10, \ clearsky = False, l2dir = '/archive/AIRSOps/airs/gdaac/v6'): # Read in mixture model parameters and quantiles, draw random samples and set up SARTA input files # Use AIRS FOV cloud fraction information # Use state vector reference configuration # Use designated AIRS reference granule, and pull surface pressure temperature from there # rffl: Reference level file # qfl: Template quantile file # gmmfl: Gaussian mixture model results file # outfl: Output file # stcnf: State vector configuration file # yrchc: Template Year Choice # rfmn: Month for reference granule # rfdy: Day for reference granule # rfgrn: Reference granule number # scnrw: Scan row for experiment # nrep: Number of replicate granules # cloud: Simulate clouds, use False for clear-sky only # l2dir: Local AIRS Level 2 directory (to retrieve reference info) # RN Generator sdchc = 452546 + yrchc + rfmn*100 random.seed(sdchc) cldprt = numpy.array([0.4,0.2,0.08]) nszout = 45 * 30 * nrep sfrps = 45 * nrep nlvsrt = 98 msgdbl = -9999.0 # Read probs and pressure levels f = Dataset(rffl,'r') airs_sarta_levs = f.variables['level'][:] f.close() # Get reference granule info airsdr = '%s/%04d/%02d/%02d/airs2sup' % (l2dir,yrchc,rfmn,rfdy) if (os.path.exists(airsdr)): fllst = os.listdir(airsdr) l2str = 'AIRS.%04d.%02d.%02d.%03d' % (yrchc,rfmn,rfdy,rfgrn) rffd = -1 j = 0 while ( (j < len(fllst)) and (rffd < 0) ): lncr = len(fllst[j]) l4 = lncr - 4 if ( (fllst[j][l4:lncr] == '.hdf') and (l2str in fllst[j])): l2fl = '%s/%s' % (airsdr,fllst[j]) ncl2 = Dataset(l2fl) psfc = ncl2.variables['PSurfStd'][:,:] topg = ncl2.variables['topog'][:,:] ncl2.close() rffd = j j = j + 1 else: print('L2 directory not found') # Surface replicates psfcvc = psfc[scnrw-1,:] topgvc = topg[scnrw-1,:] spres = numpy.tile(psfcvc,(sfrps,)) salti = numpy.tile(topgvc,(sfrps,)) # Altitude for H2O processing qin = Dataset(qfl,'r') lvs = qin.variables['level'][:] alts = qin.variables['Altitude_median'][:] qin.close() altrw = numpy.zeros((30,nlvsrt+3),dtype=numpy.float64) for i in range(30): # Set lowest levels to surface topog altrw[i,:] = alts[:] altrw[i, alts < topgvc[i]] = topgvc[i] alth2o = numpy.tile(altrw,(sfrps,1)) print(alth2o[15,80:100]) print(alth2o[75,80:100]) print(alth2o[80,80:100]) print(alth2o.shape) # Variable list, from configuration df = pandas.read_csv(stcnf, dtype = {'Order':int, 'ZScore_Name':str, 'Quantile_Name':str, \ 'Data_Name':str, 'Start':int, 'Length':int, 'DType':str }) tsz = df['Length'].sum() szstr = '%d Total State Vector Elements' % (tsz) print(szstr) nrw = df.shape[0] nsmp = -1 stctr = 0 # Discrete/Continuous Indicator df['DiscCont'] = 'Continuous' typind = [] stvrnms = [] for q in range(nrw): if ( (df['Group'].values[q] == 'NumCloud') or (df['Group'].values[q] == 'CloudType') ): df['DiscCont'].values[q] = 'Discrete' for p in range(df['Length'].values[q]): typind.append(df['DiscCont'].values[q]) cspt = df['Start'].values[q] + p vnm = '%s_%d' % (df['Data_Name'].values[q],cspt) stvrnms.append(vnm) # Quantile files qin = Dataset(qfl,'r') prbs = qin.variables['probability'][:] nprb = prbs.shape[0] qsall = numpy.zeros((tsz,nprb)) lvs = qin.variables['level'][:] alts = qin.variables['Altitude_median'][:] rhmd = qin.variables['RH_quantile'][:,103] nlvl = lvs.shape[0] cctr = 0 for j in range(nrw): if (df['Length'].values[j] == 1): vr1 = df['Quantile_Name'].values[j] qsall[cctr,:] = qin.variables[vr1][:] cctr = cctr + df['Length'].values[j] elif (df['Group'].values[j] == 'CloudFrac'): for cl0 in range(3): for rw0 in range(3): otst = cctr otfn = cctr + 1 vr1 = df['Quantile_Name'].values[j] qsall[otst:otfn,:] = qin.variables[vr1][cl0,rw0,:] cctr = cctr + 1 else: inst = df['Start'].values[j] - 1 infn = inst + df['Length'].values[j] otst = cctr otfn = cctr + df['Length'].values[j] vr1 = df['Quantile_Name'].values[j] qsall[otst:otfn,:] = qin.variables[vr1][inst:infn,:] cctr = cctr + df['Length'].values[j] qin.close() print('State medians') print(qsall[:,103]) # Read GMM Results gmin = Dataset(gmmfl,'r') gmnms = gmin['State_Vector_Names'][:,:] gmmean = gmin['Mean'][:,:] gmpkcv = gmin['Packed_Covariance'][:,:] gmprps = gmin['Mixture_Proportion'][:] gmin.close() nmclps = gmnms.tolist() strvrs = list(map(calculate_VPD.clean_byte_list,nmclps)) if sys.version_info[0] < 3: print('Version 2') strvrs = map(str,strvrs) nmix = gmmean.shape[0] nmxvar = gmmean.shape[1] mrgcv = numpy.zeros((nmix,nmxvar,nmxvar),dtype=numpy.float64) for j in range(nmix): mrgcv[j,:,:] = calculate_VPD.unpackcov(gmpkcv[j,:], nelm=nmxvar) # Component sizes dtall = numpy.zeros((nszout,nmxvar),dtype=numpy.float) cmpidx = numpy.zeros((nszout,),dtype=numpy.int16) csmp = random.multinomial(nszout,pvals=gmprps) cmsz = 0 for j in range(nmix): cvfl = mrgcv[j,:,:] s1 = numpy.sqrt(numpy.diagonal(cvfl)) crmt = calculate_VPD.cov2cor(cvfl) sdmt = numpy.diag(numpy.sqrt(cvfl.diagonal())) w, v = linalg.eig(crmt) print(numpy.amin(w)) sdfn = cmsz + csmp[j] dtz = random.multivariate_normal(numpy.zeros((nmxvar,)),crmt,size=csmp[j]) dttmp = numpy.tile(gmmean[j,:],(csmp[j],1)) + numpy.dot(dtz,sdmt) dtall[cmsz:sdfn,:] = dttmp[:,:] cmpidx[cmsz:sdfn] = j + 1 cmsz = cmsz + csmp[j] # Re-shuffle ssq = numpy.arange(nszout) sqsmp = random.choice(ssq,size=nszout,replace=False) csmpshf = cmpidx[sqsmp] dtshf = dtall[sqsmp,:] print(dtshf.shape) ### Inverse Transform qout = numpy.zeros(dtshf.shape) for j in range(tsz): if typind[j] == 'Discrete': qout[:,j] = calculate_VPD.data_quantile_from_std_norm_discrete(dtshf[:,j],qsall[j,:],prbs,minval=qsall[j,0],maxval=qsall[j,nprb-1]) else: qout[:,j] = calculate_VPD.data_quantile_from_std_norm(dtshf[:,j],qsall[j,:],prbs,minval=qsall[j,0],maxval=qsall[j,nprb-1]) ### Prepare for SARTA varlstout = ['cngwat','cngwat2','cprbot','cprbot2','cprtop','cprtop2', \ 'cpsize','cpsize2','cstemp','cstemp2','ctype','ctype2','salti','spres','stemp'] # Convert to data frame smpfrm = pandas.DataFrame(data=qout,columns=stvrnms) dtout = numpy.zeros((nszout,len(varlstout)), dtype=numpy.float64) frmout = pandas.DataFrame(data=dtout,columns=varlstout) # Clear-sky? if clearsky: smpfrm['NumberSlab_Data_1'] = 0 # Cloud Types frmout['ctype'] = (smpfrm['CType1_Data_1'] + 1.0) * 100.0 + 1.0 frmout['ctype2'] = (smpfrm['CType2_Data_1'] + 1.0) * 100.0 + 1.0 frmout.loc[(smpfrm.NumberSlab_Data_1 == 0),'ctype'] = msgdbl frmout.loc[(smpfrm.NumberSlab_Data_1 < 2),'ctype2'] = msgdbl # Met/Sfc Components, arrays sized for SARTA and AIRS cctr = 0 prhout = numpy.zeros((nszout,nlvsrt+3)) - 9999.0 ptmpout = numpy.zeros((nszout,nlvsrt+3)) - 9999.0 for j in range(nrw): if (df['Group'].values[j] == 'Temperature'): inst = df['Start'].values[j] - 1 infn = inst + df['Length'].values[j] otst = cctr otfn = cctr + df['Length'].values[j] ptmpout[:,inst:infn] = qout[:,otst:otfn] elif (df['Group'].values[j] == 'RelHum'): inst = df['Start'].values[j] - 1 infn = inst + df['Length'].values[j] otst = cctr otfn = cctr + df['Length'].values[j] prhout[:,inst:infn] = qout[:,otst:otfn] bsrh = rhmd[inst] for k in range(inst-1,-1,-1): if ma.is_masked(rhmd[k]): prhout[:,k] = bsrh / 2.0 t2 = 'RH masked: %d' % (k) print(t2) elif rhmd[k] < 0: t2 = 'RH below 0: %d' % (k) print(t2) prhout[:,k] = bsrh else: prhout[:,k] = rhmd[k] bsrh = rhmd[k] elif (df['Group'].values[j] == 'Surface'): frmout['stemp'] = qout[:,cctr] cctr = cctr + df['Length'].values[j] str1 = '''RH at Level 1: %.4e, %.4e ''' % (numpy.amin(prhout[:,0]),rhmd[0]) str2 = '''RH at Level 2: %.4e, %.4e ''' % (numpy.amin(prhout[:,1]),rhmd[1]) print(str1) print(str2) h2oout = calculate_VPD.calculate_h2odens(prhout,ptmpout,airs_sarta_levs,alth2o) # Surface from reference frmout['salti'] = salti # Need for clouds frmout['spres'] = spres #smpfrm['SfcPres'] = spres # Pressure Variables for i in range(nszout): if smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 0: frmout.at[i,'cprbot'] = msgdbl frmout.at[i,'cprtop'] = msgdbl frmout.at[i,'cprbot2'] = msgdbl frmout.at[i,'cprtop2'] = msgdbl elif smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 1: tmplgts = numpy.array( [smpfrm['CloudBot1Logit_Data_1'][smpfrm.index[i]], \ smpfrm['DPCloud1Logit_Data_1'][smpfrm.index[i]] ] ) frctmp = calculate_VPD.lgttoprp(tmplgts) frmout.at[i,'cprbot'] = spres[i] * (1.0 - frctmp[0]) frmout.at[i,'cprtop'] = spres[i] * (1.0 - frctmp[0] - frctmp[1]) frmout.at[i,'cprbot2'] = msgdbl frmout.at[i,'cprtop2'] = msgdbl elif smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 2: tmplgts = numpy.array( [smpfrm['CloudBot1Logit_Data_1'][smpfrm.index[i]], \ smpfrm['DPCloud1Logit_Data_1'][smpfrm.index[i]], \ smpfrm['DPSlabLogit_Data_1'][smpfrm.index[i]], \ smpfrm['DPCloud2Logit_Data_1'][smpfrm.index[i]] ] ) frctmp = calculate_VPD.lgttoprp(tmplgts) frmout.at[i,'cprbot'] = spres[i] * (1.0 - frctmp[0]) frmout.at[i,'cprtop'] = spres[i] * (1.0 - frctmp[0] - frctmp[1]) frmout.at[i,'cprbot2'] = spres[i] * (1.0 - frctmp[0] - frctmp[1] - frctmp[2]) frmout.at[i,'cprtop2'] = spres[i] * (1.0 - frctmp[0] - frctmp[1] - frctmp[2] - frctmp[3]) # Non-Gas Water frmout['cngwat'] = smpfrm['NGWater1_Data_1'] frmout.loc[(smpfrm.NumberSlab_Data_1 == 0),'cngwat'] = msgdbl frmout['cngwat2'] = smpfrm['NGWater2_Data_1'] frmout.loc[(smpfrm.NumberSlab_Data_1 < 2),'cngwat2'] = msgdbl # Temperature frmout['cstemp'] = smpfrm['CTTemp1_Data_1'] frmout.loc[(smpfrm.NumberSlab_Data_1 == 0),'cstemp'] = msgdbl frmout['cstemp2'] = smpfrm['CTTemp2_Data_1'] frmout.loc[(smpfrm.NumberSlab_Data_1 < 2),'cstemp2'] = msgdbl # Particle Size, from Sergio's paper # 20 for water, 80 for ice #'cpsize','cpsize2','cstemp','cstemp2','ctype','ctype2'] frmout.loc[(frmout.ctype == 101.0),'cpsize'] = 20 frmout.loc[(frmout.ctype == 201.0),'cpsize'] = 80 frmout.loc[(frmout.ctype < 0.0),'cpsize'] = msgdbl frmout.loc[(frmout.ctype2 == 101.0),'cpsize2'] = 20 frmout.loc[(frmout.ctype2 == 201.0),'cpsize2'] = 80 frmout.loc[(frmout.ctype2 < 0.0),'cpsize2'] = msgdbl # Fractions, 3D Arrays cfrc1out = numpy.zeros((nszout,3,3)) - 9999.0 cfrc2out = numpy.zeros((nszout,3,3)) - 9999.0 cfrc12out = numpy.zeros((nszout,3,3)) - 9999.0 for i in range(nszout): cldctr = 0 if smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 0: cfrc1out[i,:,:] = 0.0 cfrc2out[i,:,:] = 0.0 cfrc12out[i,:,:] = 0.0 elif smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 1: for q in range(3): for p in range(3): cfcnm = 'TotCFrc_Data_%d' % (cldctr + 1) cfrc1out[i,q,p] = smpfrm[cfcnm].values[i] cldctr = cldctr + 1 cfrc2out[i,:,:] = 0.0 cfrc12out[i,:,:] = 0.0 elif smpfrm['NumberSlab_Data_1'][smpfrm.index[i]] == 2: for q in range(3): for p in range(3): cfcnm = 'TotCFrc_Data_%d' % (cldctr + 1) lg2nm = 'CFrcLogit2_Data_%d' % (cldctr + 1) lg12nm = 'CFrcLogit12_Data_%d' % (cldctr + 1) tcfrc = smpfrm[cfcnm].values[i] zlgt2 = smpfrm[cfcnm].values[i] zlgt12 = smpfrm[cfcnm].values[i] tmplgts = numpy.array( [zlgt2, zlgt12] ) frctmp = calculate_VPD.lgttoprp(tmplgts) cfrc1out[i,q,p] = tcfrc * (frctmp[2] + frctmp[1]) cfrc2out[i,q,p] = tcfrc * (frctmp[0] + frctmp[1]) cfrc12out[i,q,p] = tcfrc * (frctmp[1]) cldctr = cldctr + 1 # Write Sample Output print(frmout[166:180]) fldbl = numpy.array([-9999.],dtype=numpy.float64) flflt = numpy.array([-9999.],dtype=numpy.float32) flshrt = numpy.array([-99],dtype=numpy.int16) f = h5py.File(outfl,'w') for j in range(len(varlstout)): dftmp = f.create_dataset(varlstout[j],data=frmout[varlstout[j]]) dftmp.attrs['missing_value'] = -9999. dftmp.attrs['_FillValue'] = -9999. dfpt = f.create_dataset('ptemp',data=ptmpout) dfpt.attrs['missing_value'] = fldbl dfpt.attrs['_FillValue'] = fldbl dfrh = f.create_dataset('relative_humidity',data=prhout) dfrh.attrs['missing_value'] = fldbl dfrh.attrs['_FillValue'] = fldbl dfgs = f.create_dataset('gas_1',data=h2oout) dfgs.attrs['missing_value'] = fldbl dfgs.attrs['_FillValue'] = fldbl dfcf1 = f.create_dataset('cfrac',data=cfrc1out) dfcf1.attrs['missing_value'] = fldbl dfcf1.attrs['_FillValue'] = fldbl dfcf2 = f.create_dataset('cfrac2',data=cfrc2out) dfcf2.attrs['missing_value'] = fldbl dfcf2.attrs['_FillValue'] = fldbl dfcf12 = f.create_dataset('cfrac12',data=cfrc12out) dfcf12.attrs['missing_value'] = fldbl dfcf12.attrs['_FillValue'] = fldbl dfcsmp = f.create_dataset('mixture_component',data=csmpshf) dfcsmp.attrs['missing_value'] = flshrt dfcsmp.attrs['_FillValue'] = flshrt dflv = f.create_dataset('level',data=airs_sarta_levs) f.close() return def extract_airs_supp(rffl, qfl, gmmfl, outfl, stcnf, yrchc, rfmn, rfdy, rfgrn, scnrw, \ l2dir = '/archive/AIRSOps/airs/gdaac/v6'): # Use designated AIRS reference granule, and pull reference information # dtdr: Output directory # yrchc: Template Year Choice # hrchc: Template Hour Choice # rgchc: Template Region Choice # rfmn: Month for reference granule # rfdy: Day for reference granule # rfgrn: Reference granule number # scnrw: Scan row for experiment # nrep: Number of replicate granules # l2dir: Local AIRS Level 2 directory (to retrieve reference info) #sfrps = 45 * nrep #nlvsrt = 98 msgdbl = -9999.0 # Read probs and pressure levels f = Dataset(rffl,'r') airs_sarta_levs = f['level'][:] f.close() # Get reference granule info airsdr = '%s/%04d/%02d/%02d/airs2sup' % (l2dir,yrchc,rfmn,rfdy) if (os.path.exists(airsdr)): fllst = os.listdir(airsdr) l2str = 'AIRS.%04d.%02d.%02d.%03d' % (yrchc,rfmn,rfdy,rfgrn) rffd = -1 j = 0 while ( (j < len(fllst)) and (rffd < 0) ): lncr = len(fllst[j]) l4 = lncr - 4 if ( (fllst[j][l4:lncr] == '.hdf') and (l2str in fllst[j])): l2fl = '%s/%s' % (airsdr,fllst[j]) ncl2 = Dataset(l2fl) psfc = ncl2.variables['PSurfStd'][:,:] topg = ncl2.variables['topog'][:,:] freqemis = ncl2.variables['freqEmis'][:,:,:] emisIR = ncl2.variables['emisIRStd'][:,:,:] lndfrc = ncl2.variables['landFrac'][:,:] tsrf = ncl2.variables['TSurfStd'][:,:] print('Emis Freq Dims') print(freqemis.shape) print('Emis IR Dims') print(emisIR.shape) print('Land Frac Dims') print(lndfrc.shape) latfor = ncl2.variables['Latitude'][:,:] lonfor = ncl2.variables['Longitude'][:,:] ncl2.close() rffd = j j = j + 1 else: print('L2 directory not found') latout = latfor[scnrw-1,:] lonout = lonfor[scnrw-1,:] pscvc = psfc[scnrw-1,:] topgvc = topg[scnrw-1,:] emsv = emisIR[scnrw-1,:,:] frqemsv = freqemis[scnrw-1,:,:] lfrcout = lndfrc[scnrw-1,:] tsrfout = tsrf[scnrw-1,:] fldbl = numpy.array([-9999.],dtype=numpy.float64) flflt = numpy.array([-9999.],dtype=numpy.float32) flshrt = numpy.array([-99],dtype=numpy.int16) f = h5py.File(outfl,'w') dflt = f.create_dataset('Latitude',data=latout) dfln = f.create_dataset('Longitude',data=lonout) dfps = f.create_dataset('PSurfStd',data=pscvc) dftp = f.create_dataset('topog',data=topgvc) dfem = f.create_dataset('emisIRStd',data=emsv) dffq = f.create_dataset('freqEmis',data=frqemsv) dflf = f.create_dataset('landFrac',data=lfrcout) dtsf = f.create_dataset('TSurfStd',data=tsrfout) f.close() return def airs_post_match_l2(flnm, tmidx, tmday, lats, lons, mskarr, rgnfrm, \ gmmdir, nsmp = 0, msgvl = -9999, \ l2srch = '/archive/AIRSOps/airs/gdaac/v6'): # Match AIRS Level 2 to region masks and execute posterior analysis # flnm: Name of output file (NetCDF expected) # tms: Time index in output # tmday: Datetime object with time information # lats: Longitude variable array # lons: Longitude variable array # mskarr: Region mask array # rgnfrm: Data frame with region indicators # gmmdir: Directory with GMM results # nsmp: Number of posterior samples to draw (optional) # msgvl: Missing value # l2srch: Level 2 search directory # Search AIRS Level 2 airsdr = '%s/%04d/%02d/%02d/airs2ret' % (l2srch,tmday.year,tmday.month,tmday.day) asupdr = '%s/%04d/%02d/%02d/airs2sup' % (l2srch,tmday.year,tmday.month,tmday.day) dsclst = [] asclst = [] nlat = lats.shape[0] nlon = lons.shape[0] lonmn = lons[0] - 5.0 lonmx = lons[nlon-1] + 5.0 latmn = lats[0] - 5.0 latmx = lats[nlat-1] + 5.0 d0 = datetime.datetime(1993,1,1,0,0,0) ddif = tmday - d0 bsdif = ddif.total_seconds() # Seed sdchc = 151444 + tmday.year*10 + int(bsdif) random.seed(sdchc) # Set up reference frame, with region mask info ltrp = numpy.repeat(lats,nlon) ltidx = numpy.repeat(numpy.arange(nlat),nlon) lnrp = numpy.tile(lons,nlat) lnidx = numpy.tile(numpy.arange(nlon),nlat) mskflt = mskarr.flatten() merfrm = pandas.DataFrame({'GridLonIdx': lnidx, 'GridLatIdx': ltidx, \ 'GridLon': lnrp, 'GridLat': ltrp, 'RgnMask': mskflt}) merfrm.loc[pandas.isnull(merfrm.RgnMask),'RgnMask'] = -99 merfrm['RgnMask'] = merfrm['RgnMask'].astype('int32') if (os.path.exists(asupdr)): # Set up a list of files/granules that might match up fllst = os.listdir(asupdr) #print(fllst) for j in range(len(fllst)): lncr = len(fllst[j]) l4 = lncr - 4 if (fllst[j][l4:lncr] == '.hdf'): l2fl = '%s/%s' % (asupdr,fllst[j]) ncl2 = Dataset(l2fl) slrzn = ncl2.variables['solzen'][:,:] l2lat = ncl2.variables['Latitude'][:,:] l2lon = ncl2.variables['Longitude'][:,:] l2tm = ncl2.variables['Time'][:,:] ncl2.close() # Check lat/lon ranges and asc/dsc l2tmdf = numpy.absolute(l2tm - bsdif) l2mntm = numpy.min(l2tmdf) # Within 4 hours if l2mntm < 14400.0: ltflt = l2lat.flatten() lnflt = l2lon.flatten() latsb = ltflt[(ltflt >= latmn) & (ltflt <= latmx)] lonsb = lnflt[(lnflt >= lonmn) & (lnflt <= lonmx)] if ( (latsb.shape[0] > 0) and (lonsb.shape[0] > 0) ): asclst.append(fllst[j]) #sstr = '%s %.2f' % (fllst[j], l2mntm) #print(sstr) # Region posterior model names hrcr = rgnfrm['Hour'].values[0] abrvcr = rgnfrm['Abbrev'].values[0] sstr = rgnfrm['Season'].values[0] rgnfl = '%s/PostGMM_%s_%s_%02dUTC.nc' % (gmmdir,abrvcr,sstr,hrcr) ncgm = Dataset(rgnfl) rtnms = ncgm.variables['state_names_retrieved'][:] lvs = ncgm.variables['level'][:] ncgm.close() nmclps = rtnms.tolist() strvrs = list(map(calculate_VPD.clean_byte_list,nmclps)) # General AIRS level sequence lsqair = numpy.arange(34,97) lv850air = 90 tairpc = 0 for i in range(len(strvrs)): if ('TempPC' in strvrs[i]): tairpc = tairpc + 1 strpc = 'Number TAir PCs: %d' % (tairpc) print(strpc) # Region GMM output, grab eigenvectors nrgn = rgnfrm.shape[0] nlev = lvs.shape[0] maxcmp = 0 if tairpc > 0: taireig = numpy.zeros((nrgn,tairpc,nlev),dtype=numpy.float64) tairmnvc = numpy.zeros((nrgn,nlev),dtype=numpy.float64) for j in range(nrgn): hrcr = rgnfrm['Hour'].values[j] abrvcr = rgnfrm['Abbrev'].values[j] sstr = rgnfrm['Season'].values[j] rgnfl = '%s/PostGMM_%s_%s_%02dUTC.nc' % (gmmdir,abrvcr,sstr,hrcr) ncgm = Dataset(rgnfl) gmm_prp = ncgm.variables['mixture_proportion'][:] ncgm.close() nmxcmp = gmm_prp.shape[0] if nmxcmp > maxcmp: maxcmp = nmxcmp if tairpc > 0: ncgm = Dataset(rgnfl) tairmnvc[j,:] = ncgm.variables['temp_prof_mean'][:] taireig[j,:,:] = ncgm.variables['temp_eigenvector'][0:tairpc,:] ncgm.close() # Check temp prof tmpmx = numpy.nanmax(tairmnvc[j,:]) for q1 in range(tairmnvc.shape[1]): if numpy.isnan(tairmnvc[j,q1]): tairmnvc[j,q1] = tmpmx # Level 2 processing # Extract lat, lon, granules # Additional processing # 1. Cloud summaries # 2. PCA of vertical profiles (region specific) tmch = 0 if (len(asclst) > 0): # Start matchups for j in range(len(asclst)): l2fl = '%s/%s' % (asupdr,asclst[j]) ncl2 = Dataset(l2fl) l2lat = ncl2.variables['Latitude'][:,:] l2lon = ncl2.variables['Longitude'][:,:] l2tm = ncl2.variables['Time'][:,:] cfrcair = ncl2.variables['CldFrcStd'][:,:,:,:,:] cfrcaqc = ncl2.variables['CldFrcStd_QC'][:,:,:,:,:] tsfcqc = ncl2.variables['TSurfAir_QC'][:,:] tsfair = ncl2.variables['TSurfAir'][:,:] tsferr = ncl2.variables['TSurfAirErr'][:,:] psfc = ncl2.variables['PSurfStd'][:,:] tairsp = ncl2.variables['TAirSup'][:,:,:] ncldair = ncl2.variables['nCld'][:,:,:,:] ncl2.close() nairtrk = l2lat.shape[0] nairxtk = l2lat.shape[1] # Extract granule asplt = asclst[j].split('.') grnchc = asplt[4] frctot = cfrcair[:,:,:,:,0] + cfrcair[:,:,:,:,1] cldsmarr = numpy.zeros((nairtrk,nairxtk,4),frctot.dtype) ncldmx = numpy.zeros((nairtrk,nairxtk),ncldair.dtype) for q1 in range(nairtrk): for p1 in range(nairxtk): cldsmarr[q1,p1,:] = calculate_VPD.cloud_frac_summary(frctot[q1,p1,:,:]) ncldmx[q1,p1] = numpy.amax(ncldair[q1,p1,:,:]) # Data Frame tkidx = numpy.repeat(numpy.arange(nairtrk),nairxtk) xtidx = numpy.tile(numpy.arange(nairxtk),nairtrk) l2lnflt = l2lon.flatten().astype(numpy.float64) l2ltflt = l2lat.flatten().astype(numpy.float64) l2tmflt = l2tm.flatten().astype(numpy.float64) l2frm = pandas.DataFrame({'L2LonIdx': xtidx, 'L2LatIdx': tkidx, \ 'L2Lon': l2lnflt, 'L2Lat': l2ltflt, 'L2Time': l2tmflt}) l2frm['GridLon'] = numpy.around(l2frm['L2Lon']/0.625) * 0.625 l2frm['GridLat'] = numpy.around(l2frm['L2Lat']/0.5) * 0.5 l2frm['Granule'] = int(grnchc) # Sfc info sfcspt = calculate_VPD.sfclvl(psfc,lvs) sfcspt = sfcspt + lsqair[0] tdftmp = tairsp[:,:,lv850air] - tsfair for q1 in range(nairtrk): for p1 in range(nairxtk): if sfcspt[q1,p1] <= lv850air: tdftmp[q1,p1] = tairsp[q1,p1,sfcspt[q1,p1]-2] - tsfair[q1,p1] #str1 = 'Sfc below 850 hPa: %d, %d, %.4f' % (q1,p1,tdftmp[q1,p1]) #print(str1) ttmp = tsfair.flatten() tdftmp = tdftmp.flatten() ertmp = tsferr.flatten() if ttmp.dtype.byteorder == '>': l2frm['NSTRtrv'] = ttmp.byteswap().newbyteorder() else: l2frm['NSTRtrv'] = ttmp if ertmp.dtype.byteorder == '>': l2frm['NSTL2Err'] = ertmp.byteswap().newbyteorder() else: l2frm['NSTL2Err'] = ertmp if tdftmp.dtype.byteorder == '>': l2frm['TDif850'] = tdftmp.byteswap().newbyteorder() else: l2frm['TDif850'] = tdftmp qcmp = tsfcqc.flatten() if qcmp.dtype.byteorder == '>': l2frm['NSTRtrvQF'] = qcmp.byteswap().newbyteorder() else: l2frm['NSTRtrvQF'] = qcmp ncldtmp = ncldmx.flatten() if ncldtmp.dtype.byteorder == '>': l2frm['NCloud'] = ncldtmp.byteswap().newbyteorder() else: l2frm['NCloud'] = ncldtmp psftmp = psfc.flatten() if ncldtmp.dtype.byteorder == '>': l2frm['PSfc'] = psftmp.byteswap().newbyteorder() else: l2frm['PSfc'] = psftmp l2frm['CFrcMean'] = cldsmarr[:,:,0].flatten() l2frm['CFrcSD'] = cldsmarr[:,:,1].flatten() l2frm['NClr'] = cldsmarr[:,:,2].flatten() l2frm['NOvc'] = cldsmarr[:,:,3].flatten() # Set up temp PCs tpcnms = [] for t in range(tairpc): pcnm = 'TempPC%d' % (t+1) tpcnms.append(pcnm) l2frm[pcnm] = numpy.zeros( (l2frm.shape[0],), dtype=cldsmarr.dtype) l2mrg = pandas.merge(l2frm,merfrm,on=['GridLon','GridLat']) l2mrg = l2mrg[l2mrg['RgnMask'] >= 0] print(l2mrg.shape) nl2 = l2mrg.shape[0] if nl2 > 0: # PCA processing nlv = lsqair.shape[0] lsq = numpy.arange(nlv) for i in range(nl2): rgidx = l2mrg['RgnMask'].values[i] - 1 atrk = l2mrg['L2LatIdx'].values[i] ctrk = l2mrg['L2LonIdx'].values[i] tprftmp = tairsp[atrk,ctrk,lsqair] tprftmp = ma.masked_where(tprftmp < 0,tprftmp) msq = ma.is_masked(tprftmp) tprfscr = ma.filled(tprftmp, fill_value=tairmnvc[rgidx,:]) tpcsr = numpy.dot(taireig[rgidx,:,:],tprfscr) for t in range(tairpc): pcnm = 'TempPC%d' % (t+1) l2mrg[pcnm].values[i] = tpcsr[t] if ( (i % 100) == 0): rgstr = 'Region %d' % (rgidx+1) print(rgstr) print(tprfscr[50:nlv]) print(tpcsr) # Append to master frame if tmch == 0: mrg_out = l2mrg else: mrg_out = mrg_out.append(l2mrg,ignore_index=True) if (nl2 > 50): print(l2mrg[20:30]) print(l2mrg.columns) tmch = tmch + nl2 # Loop through regions and match # Region GMM output nrgn = rgnfrm.shape[0] totsdg = 0 print(strvrs) for j in range(nrgn): hrcr = rgnfrm['Hour'].values[j] abrvcr = rgnfrm['Abbrev'].values[j] sstr = rgnfrm['Season'].values[j] rgnfl = '%s/PostGMM_%s_%s_%02dUTC.nc' % (gmmdir,abrvcr,sstr,hrcr) ncgm = Dataset(rgnfl) #rtnms = ncgm.variables['state_names_retrieved'][:] gmm_prp = ncgm.variables['mixture_proportion'][:] gmm_mux = ncgm.variables['mean_true'][:,:] gmm_muy = ncgm.variables['mean_retrieved'][:,:] gmm_varx = ncgm.variables['varcov_true'][:,:,:] gmm_varxy = ncgm.variables['varcov_cross'][:,:,:] gmm_vary = ncgm.variables['varcov_retrieved'][:,:,:] gmm_prcy = ncgm.variables['precmat_retrieved'][:,:,:] gmm_pstvarx = ncgm.variables['varcov_post_true'][:,:,:] ncgm.close() frmsb = mrg_out[mrg_out['RgnMask'] == (j+1)] print(frmsb.shape) nsdg = frmsb.shape[0] nmxcmp = gmm_prp.shape[0] nrtrv = gmm_muy.shape[1] nrtbs = nrtrv - tairpc nxprd = gmm_mux.shape[1] # Set up a data array print(abrvcr) ydattmp = numpy.zeros((nsdg,nrtrv),dtype=numpy.float64) for q in range(nrtbs): ydattmp[:,q] = frmsb[strvrs[q]] for q in range(tairpc): ydattmp[:,q+nrtbs] = frmsb[tpcnms[q]] print(ydattmp[0:4,:]) ## Apply GMM, from gmm_post_pred in airs_post_expt_support.R # Densities f_y_c = numpy.zeros((nsdg,nmxcmp),dtype=numpy.float64) #p_c_y = numpy.zeros((nsdg,nmxcmp),dtype=numpy.float64) print('Computing f_y_c') for k in range(nmxcmp): w, v = linalg.eig(gmm_vary[k,:,:]) wsq = numpy.arange(w.shape[0]) wsb = wsq[w < 5.0e-5] if wsb.shape[0] > 0: s1 = 'Lifting %d eigenvalues' % (wsb.shape[0]) print(s1) w[wsb] = 5.0e-5 wdg = numpy.diagflat(w) gmm_vary[k,:,:] = numpy.dot(v, numpy.dot(wdg,v.T)) w, v = linalg.eig(gmm_vary[k,:,:]) print(numpy.amin(w)) if nrtrv > 1: f_y_c[:,k] = stats.multivariate_normal.logpdf(ydattmp, mean=gmm_muy[k,:], cov=gmm_vary[k,:,:]) elif ntrv == 1: # Univariate density ltr = 0 # Adjust for possible underflow mxdns = numpy.amax(f_y_c,axis=1) mxarr = numpy.transpose(numpy.tile(mxdns,reps=(nmxcmp,1))) adjdns = f_y_c - mxarr # Compute the conditional probabilities, p_c_y print('computing p_c_y') prprep = numpy.tile(gmm_prp,reps=(nsdg,1)) cmplk = prprep * numpy.exp(adjdns) sumlk = numpy.sum(cmplk,axis=1) sumrep = numpy.transpose(numpy.tile(sumlk,reps=(nmxcmp,1))) cmpprb = cmplk / sumrep print('predicting E_X_Y') ex_y_c = numpy.zeros((nsdg,nxprd,nmxcmp),dtype=numpy.float64) ex_y = numpy.zeros((nsdg,nxprd),dtype=numpy.float64) for k in range(nmxcmp): muxrp = numpy.tile(gmm_mux[k,:],reps=(nsdg,1)) muyrp = numpy.tile(gmm_muy[k,:],reps=(nsdg,1)) ydevcr = ydattmp - muyrp prcdev = numpy.dot(gmm_prcy[k,:,:], numpy.transpose(ydevcr)) cvxytmp = numpy.transpose(gmm_varxy[k,:,:]) ex_y_c[:,:,k] = muxrp + numpy.transpose(numpy.dot(cvxytmp,prcdev)) print(prcdev.shape) print(muxrp.shape) print(muyrp.shape) for k in range(nxprd): cmpmns = cmpprb * ex_y_c[:,k,:] ex_y[:,k] = numpy.sum(cmpmns,axis=1) print(ex_y[8:12,0]) print('predicting Sigma_X_Y') Sigma_X_Y_C_bet = numpy.zeros((nsdg,nxprd,nxprd,nmxcmp),dtype=numpy.float64) Sigma_X_Y_C_wth = numpy.zeros((nsdg,nxprd,nxprd,nmxcmp),dtype=numpy.float64) Sigma_X_Y = numpy.zeros((nsdg,nxprd,nxprd),dtype=numpy.float64) for k in range(nmxcmp): wthcv = gmm_pstvarx[k,:,:] mndv = ex_y_c[:,:,k] - ex_y prbrp = numpy.repeat(cmpprb[:,k],nxprd*nxprd) prbrp = numpy.reshape(prbrp,(nsdg,nxprd,nxprd)) wthrp = numpy.tile(wthcv.flatten(),nsdg) wthrp = numpy.reshape(wthrp,(nsdg,nxprd,nxprd)) Sigma_X_Y_C_wth[:,:,:,k] = wthrp for i in range(nsdg): Sigma_X_Y_C_bet[i,:,:,k] = numpy.outer(mndv[i,:],mndv[i,:]) Sigma_X_Y = Sigma_X_Y + prbrp * (Sigma_X_Y_C_wth[:,:,:,k] + Sigma_X_Y_C_bet[:,:,:,k]) print(prbrp.shape) print(wthrp.shape) # Optionally sample # Posterior samples if nsmp > 0: smpsv = numpy.zeros((nsdg,nsmp,nxprd),dtype=numpy.float) skwsv = numpy.zeros((nsdg,nxprd),dtype=numpy.float) kursv = numpy.zeros((nsdg,nxprd),dtype=numpy.float) for i in range(nsdg): tmpsmp = numpy.zeros((nsmp,nxprd),dtype=numpy.float) cmpidx = numpy.zeros((nsmp,),dtype=numpy.int16) csmp = random.multinomial(nsmp,pvals = cmpprb[i,:]) cmsz = 0 for k in range(nmxcmp): if csmp[k] > 0: sdfn = cmsz + csmp[k] dtz = random.multivariate_normal(numpy.zeros((nxprd,)), gmm_pstvarx[k,:,:], size=csmp[k]) dttmp = numpy.tile(ex_y_c[i,:,k],(csmp[k],1)) + dtz tmpsmp[cmsz:sdfn,:] = dttmp[:,:] cmpidx[cmsz:sdfn] = k + 1 cmsz = cmsz + csmp[k] # Re-shuffle ssq = numpy.arange(nsmp) sqsmp = random.choice(ssq,size=nsmp,replace=False) cmpshf = cmpidx[sqsmp] smpsv[i,:,:] = tmpsmp[sqsmp,:] for s1 in range(nxprd): skwsv[:,s1] = stats.skew(smpsv[:,:,s1],axis=1) kursv[:,s1] = stats.kurtosis(smpsv[:,:,s1],axis=1,fisher=True) #print(skwtmp.shape) #strskw = ' Skew %.3f \n' % (skwtmp[10]) #print(strskw) # Create/update output arrays # Region Indicator # AIRS cross-track index # AIRS along-track index # Latitude # Longitude # Time # Granule # AIRS quality flag # Predictor data array # Posterior mean array # Posterior (co)variance array if totsdg == 0: rgout = numpy.zeros((nsdg,),dtype=numpy.int16) rgout[:] = j + 1 qfout = numpy.zeros((nsdg,),dtype=numpy.int16) qfout[:] = frmsb['NSTRtrvQF'] lnidxout = numpy.zeros((nsdg,),dtype=numpy.int16) lnidxout[:] = frmsb['L2LonIdx'] ltidxout = numpy.zeros((nsdg,),dtype=numpy.int16) ltidxout[:] = frmsb['L2LatIdx'] grnout = numpy.zeros((nsdg,),dtype=numpy.int16) grnout[:] = frmsb['Granule'] latout = numpy.zeros((nsdg,),dtype=numpy.float32) latout[:] = frmsb['L2Lat'] lonout = numpy.zeros((nsdg,),dtype=numpy.float32) lonout[:] = frmsb['L2Lon'] tmout = numpy.zeros((nsdg,),dtype=numpy.float64) tmout[:] = frmsb['L2Time'] psfout = numpy.zeros((nsdg,),dtype=numpy.float32) psfout[:] = frmsb['PSfc'] l2errout = numpy.zeros((nsdg,),dtype=numpy.float32) l2errout[:] = frmsb['NSTL2Err'] prdmnout = numpy.zeros((nsdg,nxprd),dtype=numpy.float32) prdmnout[:,:] = ex_y if nsmp > 0: skwout = numpy.zeros((nsdg,nxprd),dtype=numpy.float32) skwout[:,:] = skwsv kurout = numpy.zeros((nsdg,nxprd),dtype=numpy.float32) kurout[:,:] = kursv smpout = numpy.zeros((nsdg,nsmp,nxprd),dtype=numpy.float32) smpout[:,:,:] = smpsv sigxyout = numpy.zeros((nsdg,nxprd,nxprd),dtype=numpy.float32) sigxyout[:,:] = Sigma_X_Y rtryout = numpy.zeros((nsdg,nrtrv),dtype=numpy.float32) rtryout[:,:] = ydattmp cmpprbout = numpy.zeros((nsdg,maxcmp),dtype=numpy.float32) cmpprbout[:,0:nmxcmp] = cmpprb else: rgtmp = numpy.zeros((nsdg,),dtype=numpy.int16) rgtmp[:] = j + 1 rgout = numpy.append(rgout,rgtmp) qftmp = frmsb['NSTRtrvQF'] qfout = numpy.append(qfout,qftmp) errtmp = frmsb['NSTL2Err'] l2errout = numpy.append(l2errout,errtmp) lnidxtmp = frmsb['L2LonIdx'] lnidxout = numpy.append(lnidxout,lnidxtmp) ltidxtmp = frmsb['L2LatIdx'] ltidxout = numpy.append(ltidxout,ltidxtmp) grntmp = frmsb['Granule'] grnout = numpy.append(grnout,grntmp) lontmp = frmsb['L2Lon'] lonout = numpy.append(lonout,lontmp) lattmp = frmsb['L2Lat'] latout = numpy.append(latout,lattmp) tmtmp = frmsb['L2Time'] tmout = numpy.append(tmout,tmtmp) psftmp = frmsb['PSfc'] psfout = numpy.append(psfout,psftmp) prdmnout = numpy.append(prdmnout,ex_y,axis=0) if nsmp > 0: skwout = numpy.append(skwout,skwsv,axis=0) kurout = numpy.append(kurout,kursv,axis=0) smpout = numpy.append(smpout,smpsv,axis=0) rtryout = numpy.append(rtryout,ydattmp,axis=0) sigxyout = numpy.append(sigxyout,Sigma_X_Y,axis=0) cmpprbtmp = numpy.zeros((nsdg,maxcmp),dtype=numpy.float32) cmpprbtmp[:,0:nmxcmp] = cmpprb cmpprbout = numpy.append(cmpprbout,cmpprbtmp,axis=0) totsdg = totsdg + nsdg ## Prepare output file qout = Dataset(flnm,'w') dimprd = qout.createDimension('state_retrieved',nrtrv) dimxtr = qout.createDimension('state_true',nxprd) dimsdg = qout.createDimension('sounding',totsdg) dimchr = qout.createDimension('charnm',30) dimmix = qout.createDimension('mixture_component',maxcmp) if nsmp > 0: dimsmp = qout.createDimension('posterior_sample',nsmp) str_out = netCDF4.stringtochar(numpy.array(strvrs,'S30')) print(str_out) varnms = qout.createVariable('state_names_retrieved','S1',['state_retrieved','charnm']) varnms[:] = str_out varrgn = qout.createVariable('region_indicator','i2',['sounding'], fill_value = -99) varrgn[:] = rgout varrgn.long_name = 'NCA CONUS region number' varrgn.units = 'None' varrgn.missing_value = -99 varxidx = qout.createVariable('airs_x_index','i2',['sounding'], fill_value = -99) varxidx[:] = lnidxout varxidx.long_name = 'AIRS cross-track index (0-based)' varxidx.units = 'None' varxidx.missing_value = -99 varyidx = qout.createVariable('airs_y_index','i2',['sounding'], fill_value = -99) varyidx[:] = ltidxout varyidx.long_name = 'AIRS along-track index (0-based)' varyidx.units = 'None' varyidx.missing_value = -99 vargrn = qout.createVariable('airs_granule','i2',['sounding'], fill_value = -99) vargrn[:] = grnout vargrn.long_name = 'AIRS granule number' vargrn.units = 'None' vargrn.missing_value = -99 varqf = qout.createVariable('airs_tsurfair_qc','i2',['sounding'], fill_value = -99) varqf[:] = qfout varqf.long_name = 'AIRS near-surface temperature quality flag' varqf.units = 'None' varqf.missing_value = -99 varlon = qout.createVariable('longitude','f4',['sounding'], fill_value = -9999) varlon[:] = lonout varlon.long_name = 'AIRS FOR center longitude' varlon.units = 'degrees_east' varlon.missing_value = -9999 varlat = qout.createVariable('latitude','f4',['sounding'], fill_value = -9999) varlat[:] = latout varlat.long_name = 'AIRS FOR center latitude' varlat.units = 'degrees_north' varlat.missing_value = -9999 vartm = qout.createVariable('time','f8',['sounding'], fill_value = -9999) vartm[:] = tmout vartm.long_name = 'AIRS observation time' vartm.units = 'Seconds since 1993-01-01' vartm.missing_value = -9999 varpsf = qout.createVariable('surface_pressure','f4',['sounding'], fill_value = -9999) varpsf[:] = psfout varpsf.long_name = 'AIRS FOR surface pressure' varpsf.units = 'hPa' varpsf.missing_value = -9999 varl2er = qout.createVariable('airs_tsurfair_err','f4',['sounding'], fill_value = -9999) varl2er[:] = l2errout varl2er.long_name = 'AIRS Level 2 near-surface temperature error estimate' varl2er.units = 'K' varl2er.missing_value = -9999 varmn = qout.createVariable('pred_post_mean','f4',['sounding','state_true'], fill_value = -9999) varmn[:] = prdmnout varmn.long_name = 'Posterior mean for true state' varmn.units = '' varmn.missing_value = -9999 if nsmp > 0: varskw = qout.createVariable('pred_post_skew','f4',['sounding','state_true'], fill_value = -9999) varskw[:] = skwout varskw.long_name = 'Posterior skewness for true state' varskw.units = '' varskw.missing_value = -9999 varkur = qout.createVariable('pred_post_kurtosis','f4',['sounding','state_true'], fill_value = -9999) varkur[:] = kurout varkur.long_name = 'Posterior kurtosis for true state' varkur.units = '' varkur.missing_value = -9999 varsmp = qout.createVariable('pred_post_samples','f4',['sounding','posterior_sample','state_true'], fill_value = -9999) varsmp[:] = smpout varsmp.long_name = 'Posterior samples for true state' varsmp.units = '' varsmp.missing_value = -9999 varmn = qout.createVariable('pred_post_var','f4',['sounding','state_true','state_true'], fill_value = -9999) varmn[:] = sigxyout varmn.long_name = 'Posterior (co)variance for true state' varmn.units = '' varmn.missing_value = -9999 varrtr = qout.createVariable('airs_ret_covariate','f4',['sounding','state_retrieved'], fill_value = -9999) varrtr[:] = rtryout varrtr.long_name = 'Retrieved covariates' varrtr.units = '' varrtr.missing_value = -9999 varprb = qout.createVariable('pred_post_prob','f4',['sounding','mixture_component'], fill_value = -9999) varprb[:] = cmpprbout varprb.long_name = 'Mixture component posterior probabilities' varprb.units = 'None' varprb.missing_value = -9999 qout.close() return def airs_add_isd_val(flnm, vlnm, tmidx, tmday, rgnfrm, gmmdir): # Read validation matchups for AIRS outputs # flnm: Name of output file (NetCDF expected) # vlnm: Location of validation data (CSV) # tms: Time index in output # tmday: Datetime object with time information # rgnfrm: Data frame with region indicators # gmmdir: Directory with GMM results flflt = numpy.array([-9999.], dtype=numpy.float32) flshr = numpy.array([-99], dtype=numpy.int16) # Read validation #vlfrm = pandas.read_csv(vlnm, dtype = {'isd_temperature':float, 'N':int}, na_values = 'NA') vlfrm = pandas.read_csv(vlnm, na_values = 'NA') #print(vlfrm[0:10]) #vlfrm['isd_temperature'] = df['isd_temperature'].astype( print(vlfrm.dtypes) isdtout = ma.array(vlfrm['isd_temperature'],dtype=numpy.float32) isdtout = ma.masked_invalid(isdtout) # Convert to K isdtout = isdtout + 273.15 print(isdtout[0:10]) isdtout = ma.filled(isdtout, fill_value = flflt) vlctout = ma.array(vlfrm['N'],dtype=numpy.int16) vlctout = ma.masked_invalid(vlctout) vlctout = ma.filled(vlctout, fill_value = flshr) # Merge with existing file ncout = Dataset(flnm,'r+') dm1 = ncout.dimensions['sounding'] if ('ISD' in ncout.groups): str1 = 'ISD group present' vlgrp = ncout.groups['ISD'] else: vlgrp = ncout.createGroup('ISD') if ('ISD_temperature' in vlgrp.variables): vartisd = vlgrp.variables['ISD_temperature'] vartisd[:] = isdtout else: vrtisd = vlgrp.createVariable('ISD_temperature','f4',['sounding'], fill_value = flflt[0]) vrtisd[:] = isdtout vrtisd.long_name = 'Near-surface temperature at validation sites' vrtisd.units = 'K' vrtisd.missing_value = flflt[0] if ('ISD_count' in vlgrp.variables): varnisd = vlgrp.variables['ISD_count'] varnisd[:] = isdtout else: vrnisd = vlgrp.createVariable('ISD_count','i2',['sounding'], fill_value = flshr[0]) vrnisd[:] = vlctout vrnisd.long_name = 'Number of validation observation sites' vrnisd.units = 'none' vrnisd.missing_value = flshr[0] ncout.close() return def qsummary(df, grpvr, vlvr): # Quantile summary for grouped data frame tmpdt = df[vlvr] dtvld = tmpdt[numpy.isfinite(tmpdt)] nmtch = dtvld.shape[0] plvs = numpy.array([10.0,25.0,50.0,75.0,90.0]) dtqs = numpy.percentile(dtvld,q=plvs) dfout = pandas.DataFrame({'NSmp' : nmtch, 'Q10' : dtqs[0], 'Q25' : dtqs[1], 'Q50' : dtqs[2], \ 'Q75' : dtqs[3], 'Q90' : dtqs[4]}, index=[0]) return dfout

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232,192

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30,253

py

Python

tests/test_topology.py

techlib/adminator

f7f6695778dc5fb741f118fe2e0358bdda632c7b

[ "MIT" ]

1

2019-04-27T22:51:56.000Z

tests/test_topology.py

techlib/adminator

f7f6695778dc5fb741f118fe2e0358bdda632c7b

[ "MIT" ]

2

2016-11-25T10:02:15.000Z

2017-05-31T08:29:03.000Z

tests/test_topology.py

techlib/adminator

f7f6695778dc5fb741f118fe2e0358bdda632c7b

[ "MIT" ]

1

2021-12-01T05:26:43.000Z

import flexmock from adminator.topology_agent import ConMapHTMLParser, AGUpdater real_html = ''' <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>AMPTRAC Analyzer (ID=1)</title> <link media="all" href="/FS/analyzer1.css" type="text/css" rel="stylesheet"> <link media="all" href="/FS/analyzer2.css" type="text/css" rel="stylesheet"> <meta content="text/html; charset=UTF-8" http-equiv="Content-Type"/> <link type="image/x-icon" href="/FS/favicon.ico" rel="SHORTCUT ICON"> <script type="text/javascript"> function reload_page() { window.location.reload(true); } function download_file(fileURL) { window.location.assign(fileURL); } </script> <style media="all" type="text/css"> /* Styles for the ConnMap table elements */ td.connmap-na { cursor: pointer; background-color: lightGray; } td.connmap-clr { cursor: pointer; background-color: white; } td.connmap-con { cursor: pointer; background-color: lime; } td.connmap-dis { cursor: pointer; background-color: red; } td.connmap-lock { cursor: pointer; background-color: yellow; } td.connmap-err { background-color: blue; } td.connmap-db25 { background-color: beige; } </style></head> <body> <table id="frame" cellspacing="0" cellpadding="0" border="0"> <thead> <tr> <td rowspan="2"> <img style="margin: 5px 0pt 5px 5px;" src="/FS/TELogo.gif"/> </td> <td id="naviTop" colspan="2"> <a href="http://www.te.com/industry/enterprisenetworks/">Go to Enterprise Networks Web Site</a> <a href="/Logout.html" style="position: absolute; right: 10px;" >Log Out</a> </td> </tr> <tr> <td id="naviMain" colspan="2"> <ul> <li> <a href="/index.html">Home</a> </li> <li> <a href="/NetworkSettings.html">Settings</a> </li> <li> <a class="selected" href="/ConnMap.html">Maps</a> </li> <li> <a href="/AlarmsLog.html">Logs</a> </li> </ul> </td> </tr> <tr id="lines"> <td id="left"> <img align="middle" src="/FS/shadow-navi-top.gif"/> </td> <td id="centre"> </td> <td style="vertical-align: top;"> <img align="middle" src="/FS/lines-right.gif"/> </td> </tr> </thead> <tbody> <tr> <td id="naviSide" style="text-align: center;"> <table cellspacing="0" cellpadding="0" style="display: inline;"> <tbody> <tr> <td colspan="2" class="leftHeader" height="22"> Maps </td> </tr> <tr> <td colspan="2" class="blueLine" height="2"> </td> </tr> <tr> <td width="12" height="24"> <a href="/ConnMap.html"> <img border="0" src="/FS/dots.gif"/> </a> </td> <td> <a class="boldTxtGlobal" href="/ConnMap.html"> Connection Map</a> </td> </tr> <tr> <td width="12" height="24"> <a href="/ZoneMap.html"> <img border="0" src="/FS/arrow.gif"/> </a> </td> <td> <a class="txtGlobal" href="/ZoneMap.html"> Zone Map</a> </td> </tr> </tbody> </table> </td> <td id="content" rowspan="2" colspan="2"> <form action="/ProcessForm/ConnMap.html" method="post"> <table cellpadding="1" border="0" style="text-align: center; width: 80%;" title="Connection Map"> <tr> <td align="center"> <table cellpadding="5" border="0" style="text-align: center; width: 70%;"> <tr style="text-align: center; width: 100%;"> <td colspan="2"> </td></tr> <tr> <td class="header2Bg" colspan="2"> Connection Map </td> </tr> <tr> <td colspan="2"> </td></tr> <tr> <td colspan="2"> <table border="1" style="border-collapse: collapse; text-align: center;" cellpadding="0px"> <tr> <td> <table border="1" style="border-collapse: collapse; text-align: center;" cellpadding="3px"> <tr> <td class="connmap-db25"> DB#01 </td> </tr> <tr> <td class="connmap-db25"> DB#02 </td> </tr> <tr> <td class="connmap-db25"> DB#03 </td> </tr> <tr> <td class="connmap-db25"> DB#04 </td> </tr> <tr> <td class="connmap-db25"> DB#05 </td> </tr> <tr> <td class="connmap-db25"> DB#06 </td> </tr> <tr> <td class="connmap-db25"> DB#07 </td> </tr> </table> </td> <td> <table border="1" style="border-collapse: collapse; text-align: center;" cellpadding="3px"> <tr> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 06">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 11">04</td> <td class="connmap-clr" title="No Connection">05</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 05">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-clr" title="No Connection">08</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 20">09</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 10">10</td> <td class="connmap-clr" title="No Connection">11</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 12">12</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 09">13</td> <td class="connmap-clr" title="No Connection">14</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 08">15</td> <td class="connmap-clr" title="No Connection">16</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 07">17</td> <td class="connmap-clr" title="No Connection">18</td> <td class="connmap-clr" title="No Connection">19</td> <td class="connmap-clr" title="No Connection">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 04">24</td> </tr> <tr> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 14">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-clr" title="No Connection">04</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 03">05</td> <td class="connmap-clr" title="No Connection">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 17">08</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 22">09</td> <td class="connmap-clr" title="No Connection">10</td> <td class="connmap-clr" title="No Connection">11</td> <td class="connmap-clr" title="No Connection">12</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 13">13</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 01">14</td> <td class="connmap-clr" title="No Connection">15</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 19">16</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 21">17</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 18">18</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 15">19</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#04 Port 16">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> <tr> <td class="connmap-clr" title="No Connection">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-clr" title="No Connection">04</td> <td class="connmap-clr" title="No Connection">05</td> <td class="connmap-clr" title="No Connection">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-clr" title="No Connection">08</td> <td class="connmap-clr" title="No Connection">09</td> <td class="connmap-clr" title="No Connection">10</td> <td class="connmap-clr" title="No Connection">11</td> <td class="connmap-clr" title="No Connection">12</td> <td class="connmap-clr" title="No Connection">13</td> <td class="connmap-clr" title="No Connection">14</td> <td class="connmap-clr" title="No Connection">15</td> <td class="connmap-clr" title="No Connection">16</td> <td class="connmap-clr" title="No Connection">17</td> <td class="connmap-clr" title="No Connection">18</td> <td class="connmap-clr" title="No Connection">19</td> <td class="connmap-clr" title="No Connection">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> <tr> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 14">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 05">03</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 24">04</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 06">05</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 01">06</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 17">07</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 15">08</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 13">09</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 10">10</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 04">11</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 12">12</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 13">13</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 01">14</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 19">15</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 20">16</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 08">17</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 18">18</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 16">19</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#01 Port 09">20</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 17">21</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#02 Port 09">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> <tr> <td class="connmap-clr" title="No Connection">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-clr" title="No Connection">04</td> <td class="connmap-clr" title="No Connection">05</td> <td class="connmap-clr" title="No Connection">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-clr" title="No Connection">08</td> <td class="connmap-clr" title="No Connection">09</td> <td class="connmap-clr" title="No Connection">10</td> <td class="connmap-clr" title="No Connection">11</td> <td class="connmap-clr" title="No Connection">12</td> <td class="connmap-clr" title="No Connection">13</td> <td class="connmap-clr" title="No Connection">14</td> <td class="connmap-clr" title="No Connection">15</td> <td class="connmap-clr" title="No Connection">16</td> <td class="connmap-clr" title="No Connection">17</td> <td class="connmap-clr" title="No Connection">18</td> <td class="connmap-clr" title="No Connection">19</td> <td class="connmap-clr" title="No Connection">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> <tr> <td class="connmap-clr" title="No Connection">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-clr" title="No Connection">04</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#06 Port 11">05</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#06 Port 12">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-clr" title="No Connection">08</td> <td class="connmap-clr" title="No Connection">09</td> <td class="connmap-clr" title="No Connection">10</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#06 Port 05">11</td> <td class="connmap-con" title="Connected to: Analyzer 1 DB#06 Port 06">12</td> <td class="connmap-clr" title="No Connection">13</td> <td class="connmap-clr" title="No Connection">14</td> <td class="connmap-clr" title="No Connection">15</td> <td class="connmap-clr" title="No Connection">16</td> <td class="connmap-clr" title="No Connection">17</td> <td class="connmap-clr" title="No Connection">18</td> <td class="connmap-clr" title="No Connection">19</td> <td class="connmap-clr" title="No Connection">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> <tr> <td class="connmap-clr" title="No Connection">01</td> <td class="connmap-clr" title="No Connection">02</td> <td class="connmap-clr" title="No Connection">03</td> <td class="connmap-clr" title="No Connection">04</td> <td class="connmap-clr" title="No Connection">05</td> <td class="connmap-clr" title="No Connection">06</td> <td class="connmap-clr" title="No Connection">07</td> <td class="connmap-clr" title="No Connection">08</td> <td class="connmap-clr" title="No Connection">09</td> <td class="connmap-clr" title="No Connection">10</td> <td class="connmap-clr" title="No Connection">11</td> <td class="connmap-clr" title="No Connection">12</td> <td class="connmap-clr" title="No Connection">13</td> <td class="connmap-clr" title="No Connection">14</td> <td class="connmap-clr" title="No Connection">15</td> <td class="connmap-clr" title="No Connection">16</td> <td class="connmap-clr" title="No Connection">17</td> <td class="connmap-clr" title="No Connection">18</td> <td class="connmap-clr" title="No Connection">19</td> <td class="connmap-clr" title="No Connection">20</td> <td class="connmap-clr" title="No Connection">21</td> <td class="connmap-clr" title="No Connection">22</td> <td class="connmap-clr" title="No Connection">23</td> <td class="connmap-clr" title="No Connection">24</td> </tr> </table> </td> </tr> </table> </td> </tr> <tr> <td colspan="2"> </td></tr> <tr> <td class="errorText" colspan="2"> <input type="button" value=" Refresh " onClick="reload_page();" /> </td> </tr> </table> </td> </tr> </table> </form> </td> </tr> <tr> <td id="naviFooter"> </td> </tr> </tbody> </table> </body> </html>''' real_table = [[ {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 06'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 11'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 05'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 20'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 10'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 12'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 09'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 08'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 07'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 04'} ], [ {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 14'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 03'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 17'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 22'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 13'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 01'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 19'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 21'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 18'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 15'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#04 Port 16'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ], [ {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ], [ {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 14'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 05'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 24'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 06'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 01'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 17'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 15'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 13'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 10'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 04'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 12'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 13'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 01'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 19'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 20'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 08'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 18'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 16'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 09'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 17'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 09'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ], [ {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ], [ {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#06 Port 11'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#06 Port 12'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#06 Port 05'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#06 Port 06'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ], [ {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'} ]] real_connections = { 1: { 1: { 1: (1, 4, 6), 2: None, 3: None, 4: (1, 4, 11), 5: None, 6: (1, 4, 5), 7: None, 8: None, 9: (1, 4, 20), 10: (1, 4, 10), 11: None, 12: (1, 4, 12), 13: (1, 4, 9), 14: None, 15: (1, 4, 8), 16: None, 17: (1, 4, 7), 18: None, 19: None, 20: None, 21: None, 22: None, 23: None, 24: (1, 4, 4) }, 2: { 1: (1, 4, 14), 2: None, 3: None, 4: None, 5: (1, 4, 3), 6: None, 7: None, 8: (1, 4, 17), 9: (1, 4, 22), 10: None, 11: None, 12: None, 13: (1, 4, 13), 14: (1, 4, 1), 15: None, 16: (1, 4, 19), 17: (1, 4, 21), 18: (1, 4, 18), 19: (1, 4, 15), 20: (1, 4, 16), 21: None, 22: None, 23: None, 24: None }, 3: { 1: None, 2: None, 3: None, 4: None, 5: None, 6: None, 7: None, 8: None, 9: None, 10: None, 11: None, 12: None, 13: None, 14: None, 15: None, 16: None, 17: None, 18: None, 19: None, 20: None, 21: None, 22: None, 23: None, 24: None }, 4: { 1: (1, 2, 14), 2: None, 3: (1, 2, 5), 4: (1, 1, 24), 5: (1, 1, 6), 6: (1, 1, 1), 7: (1, 1, 17), 8: (1, 1, 15), 9: (1, 1, 13), 10: (1, 1, 10), 11: (1, 1, 4), 12: (1, 1, 12), 13: (1, 2, 13), 14: (1, 2, 1), 15: (1, 2, 19), 16: (1, 2, 20), 17: (1, 2, 8), 18: (1, 2, 18), 19: (1, 2, 16), 20: (1, 1, 9), 21: (1, 2, 17), 22: (1, 2, 9), 23: None, 24: None }, 5: { 1: None, 2: None, 3: None, 4: None, 5: None, 6: None, 7: None, 8: None, 9: None, 10: None, 11: None, 12: None, 13: None, 14: None, 15: None, 16: None, 17: None, 18: None, 19: None, 20: None, 21: None, 22: None, 23: None, 24: None }, 6: { 1: None, 2: None, 3: None, 4: None, 5: (1, 6, 11), 6: (1, 6, 12), 7: None, 8: None, 9: None, 10: None, 11: (1, 6, 5), 12: (1, 6, 6), 13: None, 14: None, 15: None, 16: None, 17: None, 18: None, 19: None, 20: None, 21: None, 22: None, 23: None, 24: None }, 7: { 1: None, 2: None, 3: None, 4: None, 5: None, 6: None, 7: None, 8: None, 9: None, 10: None, 11: None, 12: None, 13: None, 14: None, 15: None, 16: None, 17: None, 18: None, 19: None, 20: None, 21: None, 22: None, 23: None, 24: None } } } multi_an_tables = { 1: [ [ {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 03'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 01'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 01'}, ], [ {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#01 Port 04'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 2 DB#01 Port 04'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 2 DB#01 Port 03'}, ], ], 2: [ [ {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-clr', 'title': 'No Connection'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 04'}, {'class': 'connmap-con', 'title': 'Connected to: Analyzer 1 DB#02 Port 03'}, ], ], } multi_an_connections = { 1: { 1: { 1: (1, 1, 3), 2: None, 3: (1, 1, 1), 4: (1, 2, 1) }, 2: { 1: (1, 1, 4), 2: None, 3: (2, 1, 4), 4: (2, 1, 3) } }, 2: { 1: { 1: None, 2: None, 3: (1, 2, 4), 4: (1, 2, 3) } } } analyzer1 = flexmock(analyzer_id_in_group = 1) analyzer2 = flexmock(analyzer_id_in_group = 2) analyzer_group1 = [analyzer1] analyzer_group2 = [analyzer1, analyzer2] def test_real_html_parse(): p = ConMapHTMLParser() p.feed(real_html) assert p.get_table() == real_table def test_real_get_connections(): agu = AGUpdater(None, None) assert agu.get_connections(analyzer_group1, {1: real_table} ) == real_connections def test_multi_an_get_connections(): agu = AGUpdater(None, None) assert agu.get_connections(analyzer_group2, multi_an_tables) == multi_an_connections

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ads/fundamentals/disjoint_sets.py

Aminul-Momin/Algorithms_and_Data_Structures

cba73b36b73ad92fb34bc34a0e03503f7a137713

[ "MIT" ]

null

ads/fundamentals/disjoint_sets.py

Aminul-Momin/Algorithms_and_Data_Structures

cba73b36b73ad92fb34bc34a0e03503f7a137713

[ "MIT" ]

null

ads/fundamentals/disjoint_sets.py

Aminul-Momin/Algorithms_and_Data_Structures

cba73b36b73ad92fb34bc34a0e03503f7a137713

[ "MIT" ]

null

""" The module provides a 'union-find' data type also known as 'Disjoint Sets' data type. """ class DisjointSetsQF(): """ The class represents a 'Union-Find' data structures where 'find' operation is optimized to have constant time complexity. """ def __init__(self, N): """Initializes an empty DisjointSetQU with 'N' elements 0 through "N'-1. Initially each element is in it's own component Args: N (int): the number of elements. """ self.n = N # Number of elements self.parent = [i for i in range(self.n)] # parent[i] = parent of i def find(self, i): """Find the canonical element of the set containing element 'i'. Args: i (int): an element. Returns: int: the canonical element of the set containing element 'i'. """ def union(self, x, y): """Merges the set containing element 'x' with the set containing element 'y'. Args: x (int): one element. y (int): the other element. """ def is_connected(self, x, y): """Check if element 'x' and 'y' are connected or not. Args: x (int): one element y (int): the other element Returns: bool: True if 'x' an 'y' are in the same set False otherwise. """ return self.find(x) == self.find(y) def count(self): """Count the number of total elements. Returns: int: the number of total elements. """ return self.n class DisjointSetsQU(DisjointSetsQF): """ The class represents a 'Union-Find' data structures where 'union' operation is optimized to have constant time complexity. """ def __init__(self, N): """Initializes an empty DisjointSetQU with 'N' elements 0 through "N'-1. Initially each element is in it's own component Args: N (int): the number of elements. """ super(DisjointSetsQU, self).__init__(N) def union(self, x, y): """Merges the set containing element 'x' with the set containing element 'y'. Args: x (int): one element. y (int): the other element. """ i = self.find(x) j = self.find(y) self.parent[i] = self.parent[j] def find(self, i): """Find the canonical element of the set containing element 'i'. Args: i (int): an element. Returns: int: the canonical element of the set containing element 'i'. """ while i != self.parent[i]: i = self.parent[i] return i class DisjointSetsWeightedQU(DisjointSetsQU): """ The class represents a 'Union-Find' data structures where 'union' operation is optimized to have constant time complexity. """ def __init__(self, N): """Initializes an empty DisjointSetQU with 'N' elements 0 through "N'-1. Initially each element is in it's own component Args: N (int): the number of elements. """ super(DisjointSetsQU, self).__init__(N) def union(self, x, y): """Merges the set containing element 'x' with the set containing element 'y'. Args: x (int): one element. y (int): the other element. """ pass def find(self, i): """Find the canonical element of the set containing element 'i'. Args: i (int): an element. Returns: int: the canonical element of the set containing element 'i'. """ pass

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0.562654

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4.396552

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0.094118

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0

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0.336336

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null

0

1

0

1

0

1

0

8

0e9642f2e3113c059424329e4460efe39ac72bee

1,713

py

Python

extract/tests/test_extract_invalid.py

SbastianGarzon/o2r-meta

ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff

[ "Apache-2.0" ]

2

2017-06-28T14:47:57.000Z

2020-11-10T01:59:11.000Z

extract/tests/test_extract_invalid.py

SbastianGarzon/o2r-meta

ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff

[ "Apache-2.0" ]

95

2016-07-14T13:21:52.000Z

2021-04-08T12:51:53.000Z

extract/tests/test_extract_invalid.py

SbastianGarzon/o2r-meta

ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff

[ "Apache-2.0" ]

4

2016-07-21T12:16:37.000Z

2021-10-04T13:31:40.000Z

# pylint: skip-file import os import json def test_invalid_compendium(script_runner, tmpdir): ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract', '-i', 'extract/tests/compendium_invalid', '-o', str(tmpdir), '-xo', '-m') print(ret.stdout) print(ret.stderr) assert ret.success, "process should return success" assert ret.stderr == '', "stderr should be empty" metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json'))) assert metadata['displayfile'] is None, "missing displayfile should be none" assert metadata['mainfile'] is None, "missing mainfile should be none" assert metadata['displayfile'] != "", "missing displayfile should be none not empty string" assert metadata['mainfile'] != "", "missing mainfile should be none not empty string" def test_invalid_compendium_basedir(script_runner, tmpdir): ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract', '-i', 'extract/tests/compendium_invalid', '-b', 'extract/tests/compendium_invalid', '-o', str(tmpdir), '-xo', '-m') print(ret.stdout) print(ret.stderr) assert ret.success, "process should return success" assert ret.stderr == '', "stderr should be empty" metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json'))) assert metadata['displayfile'] is None, "missing displayfile should be none" assert metadata['mainfile'] is None, "missing mainfile should be none" assert metadata['displayfile'] != "", "missing displayfile should be none not empty string" assert metadata['mainfile'] != "", "missing mainfile should be none not empty string"

45.078947

95

0.675423

213

1,713

5.366197

0.239437

0.069991

0.08399

0.090989

0.92301

0

0.002859

0.183304

1,713

38

96

45.078947

0.814153

0.009924

0

0.83871

0

0.422419

0.056637

0

0.387097

1

0.064516

false

0

0.064516

0

0.129032

0

null

0

1

0

1

0

null

0

7

7ec1a884b4108519cc6ea47221479b0bd91c66b2

23,608

py

Python

imagetrac_docker/b5/migrations/0001_initial.py

arsenalstriker14/imagetraccloud

04004d5eabc82e85596bc9e110c9250d5f882e17

[ "MIT" ]

null

imagetrac_docker/b5/migrations/0001_initial.py

arsenalstriker14/imagetraccloud

04004d5eabc82e85596bc9e110c9250d5f882e17

[ "MIT" ]

null

imagetrac_docker/b5/migrations/0001_initial.py

arsenalstriker14/imagetraccloud

04004d5eabc82e85596bc9e110c9250d5f882e17

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2017-01-20 09:04 from __future__ import unicode_literals import datetime from django.conf import settings import django.contrib.postgres.fields.jsonb from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='AdProduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('ad_date', models.CharField(blank=True, default=None, max_length=20, null=True)), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('mfg', models.CharField(blank=True, max_length=30, null=True)), ('desc', models.CharField(blank=True, max_length=200, null=True)), ('vendor_number', models.CharField(blank=True, max_length=30, null=True)), ('order_date', models.CharField(blank=True, max_length=30, null=True)), ('received_dc', models.CharField(blank=True, max_length=30, null=True)), ('received_137', models.CharField(blank=True, max_length=30, null=True)), ('received_buyer', models.CharField(blank=True, max_length=40, null=True)), ('received_other', models.CharField(blank=True, default=None, max_length=50, null=True)), ('photo_dldate', models.CharField(blank=True, max_length=50, null=True)), ('whowhen', models.CharField(blank=True, max_length=100, null=True)), ('studio_out', models.CharField(blank=True, max_length=30, null=True)), ('checked_out', models.CharField(blank=True, max_length=100, null=True)), ('have_image', models.CharField(blank=True, max_length=30, null=True)), ('confirmed_placed', models.CharField(blank=True, default='None', max_length=200, null=True)), ('shooting_instructions', models.CharField(blank=True, default=None, max_length=200, null=True)), ('studio_in', models.CharField(blank=True, max_length=50, null=True)), ('notes', models.CharField(blank=True, max_length=200, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('short_sku', models.CharField(blank=True, max_length=30, null=True)), ('from_file', models.CharField(blank=True, max_length=30, null=True)), ('sku', models.CharField(blank=True, max_length=30, null=True)), ('sku_ns', models.CharField(blank=True, max_length=30, null=True)), ('first', models.CharField(blank=True, max_length=5, null=True)), ('first_date', models.CharField(blank=True, max_length=30, null=True)), ('buyer', models.CharField(blank=True, max_length=50, null=True)), ('merch_to_137', models.CharField(blank=True, max_length=200, null=True)), ('product_class', models.CharField(blank=True, max_length=4, null=True)), ('dc_received_u', models.IntegerField(blank=True, null=True)), ('curr_dc_oh_u', models.IntegerField(blank=True, null=True)), ('dc_curr_oo_u', models.IntegerField(blank=True, null=True)), ('na', models.CharField(blank=True, max_length=5, null=True)), ('size_type', models.CharField(blank=True, max_length=10, null=True)), ('color_desc', models.CharField(blank=True, max_length=200, null=True)), ('version', models.CharField(blank=True, max_length=20, null=True)), ], ), migrations.CreateModel( name='Buyers', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('buyer', models.CharField(blank=True, max_length=50, null=True)), ('department', models.CharField(blank=True, max_length=3, null=True)), ('product_class', models.CharField(blank=True, max_length=4, null=True, unique=True)), ('description', models.CharField(blank=True, max_length=150, null=True)), ], ), migrations.CreateModel( name='CheckProduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sku_ns', models.CharField(max_length=30)), ('brand', models.CharField(blank=True, max_length=20, null=True)), ('desc', models.CharField(blank=True, max_length=200, null=True)), ('confirmed_placed', models.CharField(blank=True, default='None', max_length=200, null=True)), ('ad_date', models.CharField(blank=True, max_length=20, null=True)), ('mfg', models.CharField(blank=True, max_length=30, null=True)), ('already_tracked', models.CharField(blank=True, default='None', max_length=300, null=True)), ('na', models.NullBooleanField(default=False)), ], ), migrations.CreateModel( name='ColorCode', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=3, unique=True)), ('color', models.CharField(blank=True, max_length=30, null=True)), ], ), migrations.CreateModel( name='ColorGrid', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('color', models.CharField(blank=True, max_length=30, null=True)), ('hexcode', models.CharField(max_length=6, unique=True)), ('description', models.CharField(max_length=300, unique=True)), ], ), migrations.CreateModel( name='Department', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(choices=[('Admin', 'Admin'), ('Advertising', 'Advertising'), ('Art', 'Art'), ('Layout', 'Layout'), ('Copy', 'Copy'), ('Purchasing', 'Purchasing'), ('IT', 'IT')], max_length=64)), ], ), migrations.CreateModel( name='Deployed', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('operator', models.CharField(blank=True, max_length=50, null=True)), ('filenames', django.contrib.postgres.fields.jsonb.JSONField()), ], ), migrations.CreateModel( name='FirstReceipt', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('buyer', models.CharField(blank=True, max_length=30, null=True)), ('dc_received_u', models.IntegerField(blank=True, null=True)), ('curr_dc_oh_u', models.IntegerField(blank=True, null=True)), ('dc_curr_oo_u', models.IntegerField(blank=True, null=True)), ('date_received', models.CharField(blank=True, max_length=20, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('short_sku', models.CharField(blank=True, max_length=30, null=True)), ('size_type', models.CharField(blank=True, max_length=10, null=True)), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('vendor_style', models.CharField(blank=True, max_length=30, null=True)), ('description', models.CharField(blank=True, max_length=200, null=True)), ('color_desc', models.CharField(blank=True, max_length=200, null=True)), ('have_image', models.CharField(blank=True, max_length=30, null=True)), ('ad_date', models.CharField(blank=True, max_length=50, null=True)), ('order_date', models.CharField(blank=True, max_length=50, null=True)), ('received_dc', models.CharField(blank=True, max_length=30, null=True)), ('received_137', models.CharField(blank=True, max_length=30, null=True)), ('from_file', models.CharField(blank=True, max_length=30, null=True)), ('photo_dldate', models.DateField(blank=True, null=True)), ('whowhen', models.CharField(blank=True, max_length=100, null=True)), ('studio_out', models.CharField(blank=True, max_length=50, null=True)), ('checked_out', models.CharField(blank=True, max_length=100, null=True)), ('confirmed_placed', models.CharField(blank=True, default='None', max_length=200, null=True)), ('studio_in', models.CharField(blank=True, max_length=50, null=True)), ('merch_to_137', models.CharField(blank=True, max_length=200, null=True)), ('product_class', models.CharField(blank=True, max_length=4, null=True)), ], ), migrations.CreateModel( name='HotItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(max_length=30, unique=True)), ('ad_date', models.CharField(blank=True, default=None, max_length=20, null=True)), ('create_date', models.DateField(default=datetime.date.today)), ('item_name', models.CharField(blank=True, max_length=210, null=True)), ('comments', models.TextField(blank=True, max_length=2000, null=True)), ('reply', models.TextField(blank=True, max_length=2000, null=True)), ('confirmed_placed', models.CharField(blank=True, default=None, max_length=200, null=True)), ], ), migrations.CreateModel( name='InventoryProduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sku', models.CharField(blank=True, max_length=7, null=True)), ('item_no', models.CharField(blank=True, max_length=30, null=True, unique=True)), ('desc', models.CharField(blank=True, max_length=200, null=True)), ('quantity', models.CharField(max_length=3)), ('source', models.CharField(blank=True, max_length=100, null=True)), ], ), migrations.CreateModel( name='LargeWebfiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('long_sku', models.CharField(max_length=30)), ('filename', models.CharField(max_length=50)), ('mod_date', models.CharField(blank=True, max_length=200, null=True)), ('item_ns', models.CharField(max_length=30, null=True)), ('sku', models.CharField(max_length=30, null=True)), ('sku_ns', models.CharField(max_length=30, null=True)), ], ), migrations.CreateModel( name='MSWebfiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('long_sku', models.CharField(max_length=30)), ('filename', models.CharField(max_length=50)), ('item_ns', models.CharField(max_length=30, null=True)), ('sku', models.CharField(max_length=30, null=True)), ('sku_ns', models.CharField(max_length=30, null=True)), ], ), migrations.CreateModel( name='OneImageFiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(max_length=30)), ], ), migrations.CreateModel( name='PrintFile', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('assoc_sku', models.CharField(max_length=30)), ('filename', models.CharField(blank=True, max_length=500, null=True)), ('path', models.CharField(blank=True, max_length=200, null=True)), ('mod_date', models.CharField(blank=True, max_length=200, null=True)), ], ), migrations.CreateModel( name='ProcessedFiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(max_length=30)), ('filename', models.CharField(blank=True, max_length=50, null=True)), ('processor', models.CharField(blank=True, max_length=50, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('sku', models.CharField(blank=True, max_length=30, null=True)), ('sku_ns', models.CharField(blank=True, max_length=30, null=True)), ('product_class', models.CharField(blank=True, max_length=10, null=True)), ('upload_date', models.CharField(blank=True, max_length=30, null=True)), ], ), migrations.CreateModel( name='Product', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('ad_date', models.CharField(blank=True, default=None, max_length=20, null=True)), ('item_no', models.CharField(blank=True, max_length=30, null=True, unique=True)), ('mfg', models.CharField(blank=True, max_length=30, null=True)), ('desc', models.CharField(blank=True, max_length=200, null=True)), ('vendor_number', models.CharField(blank=True, max_length=30, null=True)), ('order_date', models.DateField(blank=True, null=True)), ('received_dc', models.DateField(blank=True, null=True)), ('received_137', models.CharField(blank=True, max_length=30, null=True)), ('received_buyer', models.CharField(blank=True, max_length=40, null=True)), ('received_other', models.CharField(blank=True, default=None, max_length=50, null=True)), ('photo_dldate', models.CharField(blank=True, max_length=50, null=True)), ('whowhen', models.CharField(blank=True, max_length=100, null=True)), ('studio_out', models.DateField(blank=True, null=True)), ('checked_out', models.CharField(blank=True, max_length=100, null=True)), ('have_image', models.CharField(blank=True, max_length=30, null=True)), ('confirmed_placed', models.CharField(blank=True, default='None', max_length=200, null=True)), ('shooting_instructions', models.CharField(blank=True, default=None, max_length=200, null=True)), ('studio_in', models.CharField(blank=True, max_length=50, null=True)), ('notes', models.CharField(blank=True, max_length=200, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('short_sku', models.CharField(blank=True, max_length=30, null=True)), ('from_file', models.CharField(blank=True, max_length=30, null=True)), ('sku', models.CharField(blank=True, max_length=30, null=True)), ('sku_ns', models.CharField(blank=True, max_length=30, null=True)), ('first', models.CharField(blank=True, max_length=5, null=True)), ('first_date', models.CharField(blank=True, max_length=30, null=True)), ('buyer', models.CharField(blank=True, max_length=50, null=True)), ('merch_to_137', models.CharField(blank=True, max_length=200, null=True)), ('dc_received_u', models.IntegerField(blank=True, null=True)), ('curr_dc_oh_u', models.IntegerField(blank=True, null=True)), ('dc_curr_oo_u', models.IntegerField(blank=True, null=True)), ('na', models.CharField(blank=True, max_length=5, null=True)), ('size_type', models.CharField(blank=True, max_length=10, null=True)), ('color_desc', models.CharField(blank=True, max_length=200, null=True)), ('product_class', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='b5.Buyers', to_field='product_class')), ], ), migrations.CreateModel( name='RegularWebfiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('long_sku', models.CharField(max_length=30)), ('filename', models.CharField(max_length=50)), ('item_ns', models.CharField(max_length=30, null=True)), ('sku', models.CharField(max_length=30, null=True)), ('sku_ns', models.CharField(max_length=30, null=True)), ], ), migrations.CreateModel( name='ReplacedImage', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sku', models.CharField(blank=True, max_length=30, null=True)), ('sku_ns', models.CharField(blank=True, max_length=30, null=True)), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('old_filename', models.CharField(blank=True, max_length=50, null=True)), ('new_filename', models.CharField(blank=True, max_length=50, null=True)), ('change_date', models.DateField(blank=True, default=datetime.date.today, null=True)), ], ), migrations.CreateModel( name='RumbaProduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('mfg', models.CharField(blank=True, max_length=30, null=True)), ('desc', models.CharField(blank=True, max_length=200, null=True)), ('vendor_number', models.CharField(blank=True, max_length=30, null=True)), ('confirmed_placed', models.CharField(blank=True, default='None', max_length=200, null=True)), ('item_ns', models.CharField(blank=True, max_length=30, null=True)), ('short_sku', models.CharField(blank=True, max_length=30, null=True)), ('sku', models.CharField(blank=True, max_length=30, null=True)), ('sku_ns', models.CharField(blank=True, max_length=30, null=True)), ('product_class', models.CharField(blank=True, max_length=4, null=True)), ('merch_to_137', models.CharField(blank=True, max_length=200, null=True)), ('dc_received_u', models.IntegerField(blank=True, null=True)), ('curr_dc_oh_u', models.IntegerField(blank=True, null=True)), ('dc_curr_oo_u', models.IntegerField(blank=True, null=True)), ('size_type', models.CharField(blank=True, max_length=10, null=True)), ('size', models.CharField(blank=True, max_length=10, null=True)), ('color_desc', models.CharField(blank=True, max_length=200, null=True)), ], ), migrations.CreateModel( name='ThumbWebfiles', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('long_sku', models.CharField(max_length=30)), ('filename', models.CharField(max_length=50)), ('item_ns', models.CharField(max_length=30, null=True)), ('sku', models.CharField(max_length=30, null=True)), ('sku_ns', models.CharField(max_length=30, null=True)), ], ), migrations.CreateModel( name='UserProfile', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fullname', models.CharField(max_length=64)), ('position', models.CharField(blank=True, max_length=64, null=True)), ('phone', models.CharField(blank=True, max_length=15, null=True)), ('extension', models.CharField(blank=True, max_length=15, null=True)), ('mobile', models.CharField(blank=True, max_length=15, null=True)), ('fax', models.CharField(blank=True, max_length=15, null=True)), ('notes', models.TextField(blank=True, max_length=2000, null=True)), ('email', models.EmailField(max_length=254)), ('user', models.OneToOneField(null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL)), ], options={ 'ordering': ['user__last_name'], }, ), migrations.CreateModel( name='WatchedItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('item_no', models.CharField(blank=True, max_length=30, null=True)), ('desc', models.CharField(blank=True, max_length=210, null=True)), ('comments', models.TextField(blank=True, max_length=2000, null=True)), ('confirmed_placed', models.CharField(blank=True, default=None, max_length=200, null=True)), ('watched_by', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='b5.UserProfile')), ], ), migrations.AddField( model_name='replacedimage', name='processor', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='b5.UserProfile'), ), migrations.AddField( model_name='oneimagefiles', name='filenames', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='b5.PrintFile'), ), migrations.AlterUniqueTogether( name='inventoryproduct', unique_together=set([('sku', 'source')]), ), migrations.AddField( model_name='department', name='member', field=models.ManyToManyField(to='b5.UserProfile'), ), ]

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7ed7bc1694f73741d38255d44b474ff7878f3e2b

4,021

py

Python

tests/bindings/polymer/test_predicates.py

sizmailov/pyxmolpp2

9395ba1b1ddc957e0b33dc6decccdb711e720764

[ "MIT" ]

4

2020-06-24T11:07:57.000Z

2022-01-15T23:00:30.000Z

tests/bindings/polymer/test_predicates.py

sizmailov/pyxmolpp2

9395ba1b1ddc957e0b33dc6decccdb711e720764

[ "MIT" ]

84

2018-04-22T12:29:31.000Z

2020-06-17T15:03:37.000Z

tests/bindings/polymer/test_predicates.py

sizmailov/pyxmolpp2

9395ba1b1ddc957e0b33dc6decccdb711e720764

[ "MIT" ]

6

2018-06-04T09:16:26.000Z

2022-03-12T11:05:54.000Z

import pytest import os from make_polygly import make_polyglycine def test_atom_name(): from pyxmolpp2 import aName frame = make_polyglycine([("A", 10)]) assert frame.atoms.filter(aName == "CA").size == 10 assert frame.atoms.filter(aName.is_in({"CA", "N"})).size == 20 assert frame.atoms.filter(aName.is_in("CA", "N")).size == 20 assert frame.atoms.filter(~aName.is_in({"CA", "N"})).size == 50 assert frame.atoms.filter(~aName.is_in("CA", "N")).size == 50 assert frame.atoms.filter((aName == "CA") | (aName == "N")).size == 20 def test_residue_name(): from pyxmolpp2 import rName frame = make_polyglycine([("A", 10)]) assert frame.atoms.filter(rName == "GLY").size == 70 assert frame.atoms.filter(rName.is_in({"GLY", "LYS"})).size == 70 assert frame.atoms.filter(rName.is_in("GLY", "LYS")).size == 70 assert frame.atoms.filter(~rName.is_in({"GLY"})).size == 0 assert frame.atoms.filter(~rName.is_in("GLY")).size == 0 assert frame.atoms.filter((rName == "GLY") | (rName != "GLY")).size == 70 assert frame.residues.filter(rName == "GLY").size == 10 assert frame.residues.filter(rName.is_in({"GLY", "LYS"})).size == 10 assert frame.residues.filter(rName.is_in("GLY", "LYS")).size == 10 assert frame.residues.filter(~rName.is_in({"GLY"})).size == 0 assert frame.residues.filter(~rName.is_in("GLY")).size == 0 assert frame.residues.filter((rName == "GLY") | (rName != "GLY")).size == 10 def test_chain_name(): from pyxmolpp2 import mName frame = make_polyglycine([("A", 10),("B",20)]) assert frame.atoms.filter(mName == "A").size == 10*7 assert frame.atoms.filter(mName.is_in({"A", "B"})).size == 30*7 assert frame.atoms.filter(~mName.is_in({"B"})).size == 10*7 assert frame.atoms.filter((mName == "A") | (mName != "B")).size == 10*7 assert frame.residues.filter(mName == "A").size == 10 assert frame.residues.filter(mName.is_in({"A", "B"})).size == 30 assert frame.residues.filter(mName.is_in("A", "B")).size == 30 assert frame.residues.filter(~mName.is_in({"B"})).size == 10 assert frame.residues.filter(~mName.is_in("B")).size == 10 assert frame.residues.filter((mName == "A") | (mName != "B")).size == 10 assert frame.molecules.filter(mName == "A").size == 1 assert frame.molecules.filter(mName.is_in({"A", "B"})).size == 2 assert frame.molecules.filter(mName.is_in("A", "B")).size == 2 assert frame.molecules.filter(~mName.is_in({"B"})).size == 1 assert frame.molecules.filter(~mName.is_in("B")).size == 1 assert frame.molecules.filter((mName == "A") | (mName != "B")).size == 1 def test_atom_id(): from pyxmolpp2 import aId frame = make_polyglycine([("A", 10)]) assert frame.atoms.filter(aId == 5).size == 1 assert frame.atoms.filter(aId.is_in({1,2,3})).size == 3 assert frame.atoms.filter(aId.is_in(1,2,3)).size == 3 assert frame.atoms.filter(~aId.is_in({1,2,3})).size == 70-3 assert frame.atoms.filter(~aId.is_in(1,2,3)).size == 70-3 assert frame.atoms.filter((aId == 2) | (aId == 3)).size == 2 def test_residue_id(): from pyxmolpp2 import rId, ResidueId frame = make_polyglycine([("A", 10)]) assert frame.atoms.filter(rId == 5).size == 1*7 assert frame.atoms.filter(rId.is_in({1,2,3})).size == 3*7 assert frame.atoms.filter(rId.is_in(1,2,3)).size == 3*7 assert frame.atoms.filter(~rId.is_in({1,2,3})).size == 7*7 assert frame.atoms.filter(~rId.is_in(1,2,3)).size == 7*7 assert frame.atoms.filter((rId == 2) | (rId == 3)).size == 2*7 assert frame.residues.filter(rId == 5).size == 1 assert frame.residues.filter(rId.is_in({1,2,3})).size == 3 assert frame.residues.filter(rId.is_in(1,2,3)).size == 3 assert frame.residues.filter(~rId.is_in({1,2,3})).size == 7 assert frame.residues.filter(~rId.is_in(1,2,3)).size == 7 assert frame.residues.filter((rId == 2) | (rId == 3)).size == 2 assert frame.residues.filter(rId == ResidueId(5,"A")).size == 0

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null

0

1

0

9

7d1c98a7a9ddad54bf9674e7f255da961ba1786a

197

py

Python

tests/basics/builtin_hex.py

peterson79/pycom-micropython-sigfox

3f93fc2c02567c96f18cff4af9125db8fd7a6fb4

[ "MIT" ]

303

2015-07-11T17:12:55.000Z

2018-01-08T03:02:37.000Z

tests/basics/builtin_hex.py

peterson79/pycom-micropython-sigfox

3f93fc2c02567c96f18cff4af9125db8fd7a6fb4

[ "MIT" ]

27

2015-01-02T16:17:37.000Z

2015-09-07T19:21:26.000Z

tests/basics/builtin_hex.py

peterson79/pycom-micropython-sigfox

3f93fc2c02567c96f18cff4af9125db8fd7a6fb4

[ "MIT" ]

26

2018-01-18T09:15:33.000Z

2022-02-07T13:09:14.000Z

# test builtin hex function print(hex(1)) print(hex(-1)) print(hex(15)) print(hex(-15)) print(hex(12345)) print(hex(0x12345)) print(hex(12345678901234567890)) print(hex(0x12345678901234567890))

15.153846

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1

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null

0

1

0

1

0

7

7d3d2743257a8ee0b01c6779b35fadba0bfa615c

6,762

py

Python

marionette/tor_browser_tests/test_noscript.py

boklm/tbb-testsuite

308a0861a110c92a1f1378b6577e8db9a9f11c6c

[ "CC0-1.0", "BSD-3-Clause" ]

1

2015-07-06T18:40:14.000Z

marionette/tor_browser_tests/test_noscript.py

boklm/tbb-testsuite

308a0861a110c92a1f1378b6577e8db9a9f11c6c

[ "CC0-1.0", "BSD-3-Clause" ]

null

marionette/tor_browser_tests/test_noscript.py

boklm/tbb-testsuite

308a0861a110c92a1f1378b6577e8db9a9f11c6c

[ "CC0-1.0", "BSD-3-Clause" ]

1

2017-10-04T22:11:52.000Z

# https://trac.torproject.org/projects/tor/ticket/13053 from marionette_driver.errors import NoSuchElementException from marionette_harness import MarionetteTestCase import testsuite class Test(MarionetteTestCase): def setUp(self): MarionetteTestCase.setUp(self) ts = testsuite.TestSuite() self.ts = ts self.http_url = "%s/noscript/" % ts.t['options']['test_data_url'] self.https_url = "%s/noscript/" % ts.t['options']['test_data_url_https'] def test_noscript(self): self.marionette.timeout.implicit = 1 with self.marionette.using_context('content'): # http page sourcing http js self.marionette.navigate("%s/http_src.html" % self.http_url) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="http page sourcing http js") # https page sourcing http js self.marionette.navigate("%s/http_src.html" % self.https_url) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="https page sourcing http js") # https page sourcing http js (alternate hostname) self.marionette.navigate("%s/alternate_http_src.html" % self.https_url) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="https page sourcing http js (alternate hostname)") # http page sourcing https js self.marionette.navigate("%s/https_src.html" % self.http_url) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="http page sourcing https js") # https page sourcing https js self.marionette.navigate("%s/https_src.html" % self.https_url) res = True try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = False self.assertTrue(res, msg="https page sourcing https js") self.assertEqual('JavaScriptEnabled', elt.text, msg="https page sourcing https js") # https page sourcing https js (alternate hostname) self.marionette.navigate("%s/alternate_https_src.html" % self.https_url) res = True try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = False self.assertTrue(res, msg="https page sourcing https js (alternate hostname)") self.assertEqual('JavaScriptEnabled', elt.text, msg="https page sourcing https js (alternate hostname)") # http page with http iframe self.marionette.navigate("%s/http_iframe.html" % self.http_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="http page with http iframe") self.marionette.switch_to_default_content() # http page with https iframe self.marionette.navigate("%s/https_iframe.html" % self.http_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="http page with https iframe") self.marionette.switch_to_default_content() # https page with http iframe self.marionette.navigate("%s/http_iframe.html" % self.https_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="https page with http iframe") self.marionette.switch_to_default_content() # https page sourcing https js (alternate hostname) self.marionette.navigate("%s/alternate_http_iframe.html" % self.https_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = False try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = True self.assertTrue(res, msg="https page sourcing https js (alternate hostname)") self.marionette.switch_to_default_content() # https page with https iframe self.marionette.navigate("%s/https_iframe.html" % self.https_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = True try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = False self.assertTrue(res, msg="https page with https iframe") self.assertEqual(elt.text, 'JavaScriptEnabled', msg="https page with https iframe") self.marionette.switch_to_default_content() # https page with https iframe (alternate hostname) self.marionette.navigate("%s/alternate_https_iframe.html" % self.https_url) iframe = self.marionette.find_element('id', 'iframe') self.marionette.switch_to_frame(iframe) res = True try: elt = self.marionette.find_element('id', 'test_result') except NoSuchElementException: res = False self.assertTrue(res, msg="https page with https iframe") self.assertEqual(elt.text, 'JavaScriptEnabled', msg="https page with https iframe") self.marionette.switch_to_default_content()

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null

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7

7d4eb1c22faaec86f73202be1c7f11c7139c9ac4

6,279

py

Python

pyaz/afd/route/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/afd/route/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/afd/route/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

1

2022-02-03T09:12:01.000Z

''' Manage routes under an AFD endpoint. ''' from ... pyaz_utils import _call_az def show(endpoint_name, profile_name, resource_group, route_name): ''' Show route details. Required Parameters: - endpoint_name -- Name of the endpoint. - profile_name -- Name of the CDN profile which is unique within the resource group. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - route_name -- Name of the route. ''' return _call_az("az afd route show", locals()) def list(endpoint_name, profile_name, resource_group): ''' List all the routes within the specified endpoint. Required Parameters: - endpoint_name -- Name of the endpoint. - profile_name -- Name of the CDN profile which is unique within the resource group. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` ''' return _call_az("az afd route list", locals()) def create(endpoint_name, forwarding_protocol, https_redirect, origin_group, profile_name, resource_group, route_name, supported_protocols, content_types_to_compress=None, custom_domains=None, enable_compression=None, link_to_default_domain=None, origin_path=None, patterns_to_match=None, query_string_caching_behavior=None, rule_sets=None): ''' Creates a new route within the specified endpoint. Required Parameters: - endpoint_name -- Name of the endpoint. - forwarding_protocol -- Protocol this rule will use when forwarding traffic to backends. - https_redirect -- Whether to automatically redirect HTTP traffic to HTTPS traffic. - origin_group -- Name or ID of the origin group to be associated with. - profile_name -- Name of the CDN profile which is unique within the resource group. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - route_name -- Name of the route. - supported_protocols -- List of supported protocols for this route. Optional Parameters: - content_types_to_compress -- List of content types on which compression applies. The value should be a valid MIME type. - custom_domains -- Custom domains referenced by this endpoint. - enable_compression -- Indicates whether content compression is enabled on AzureFrontDoor. Default value is false. If compression is enabled, content will be served as compressed if user requests for a compressed version. Content won't be compressed on AzureFrontDoor when requested content is smaller than 1 byte or larger than 1 MB. - link_to_default_domain -- Whether this route will be linked to the default endpoint domain. - origin_path -- A directory path on the origin that AFD can use to retrieve content from. E.g, "/img/*" - patterns_to_match -- The route patterns of the rule. - query_string_caching_behavior -- Defines how CDN caches requests that include query strings. You can ignore any query strings when caching, bypass caching to prevent requests that contain query strings from being cached, or cache every request with a unique URL. - rule_sets -- Collection of ID or name of rule set referenced by the route. ''' return _call_az("az afd route create", locals()) def update(endpoint_name, profile_name, resource_group, route_name, content_types_to_compress=None, custom_domains=None, enable_compression=None, forwarding_protocol=None, https_redirect=None, link_to_default_domain=None, origin_group=None, origin_path=None, patterns_to_match=None, query_string_caching_behavior=None, rule_sets=None, supported_protocols=None): ''' Update an existing route within the specified endpoint. Required Parameters: - endpoint_name -- Name of the endpoint. - profile_name -- Name of the CDN profile which is unique within the resource group. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - route_name -- Name of the route. Optional Parameters: - content_types_to_compress -- List of content types on which compression applies. The value should be a valid MIME type. - custom_domains -- Custom domains referenced by this endpoint. - enable_compression -- Indicates whether content compression is enabled on AzureFrontDoor. Default value is false. If compression is enabled, content will be served as compressed if user requests for a compressed version. Content won't be compressed on AzureFrontDoor when requested content is smaller than 1 byte or larger than 1 MB. - forwarding_protocol -- Protocol this rule will use when forwarding traffic to backends. - https_redirect -- Whether to automatically redirect HTTP traffic to HTTPS traffic. - link_to_default_domain -- Whether this route will be linked to the default endpoint domain. - origin_group -- Name or ID of the origin group to be associated with. - origin_path -- A directory path on the origin that AFD can use to retrieve content from. E.g, "/img/*" - patterns_to_match -- The route patterns of the rule. - query_string_caching_behavior -- Defines how CDN caches requests that include query strings. You can ignore any query strings when caching, bypass caching to prevent requests that contain query strings from being cached, or cache every request with a unique URL. - rule_sets -- Collection of ID or name of rule set referenced by the route. - supported_protocols -- List of supported protocols for this route. ''' return _call_az("az afd route update", locals()) def delete(endpoint_name, profile_name, resource_group, route_name, yes=None): ''' Delete an existing route within the specified endpoint. Required Parameters: - endpoint_name -- Name of the endpoint. - profile_name -- Name of the CDN profile which is unique within the resource group. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - route_name -- Name of the route. Optional Parameters: - yes -- Do not prompt for confirmation. ''' return _call_az("az afd route delete", locals())

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0

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1

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8

7d50f68006ec02c191e80e8c74981ff83674c568

120

py

Python

draugr/os_utilities/windows_utilities/task_scheduler/enums/__init__.py

pything/draugr

2fda662f2fa97236e4495a6af2b8237516fa428b

[ "Apache-2.0" ]

null

draugr/os_utilities/windows_utilities/task_scheduler/enums/__init__.py

pything/draugr

2fda662f2fa97236e4495a6af2b8237516fa428b

[ "Apache-2.0" ]

16

2021-02-15T07:58:01.000Z

2022-02-20T15:16:23.000Z

draugr/os_utilities/windows_utilities/task_scheduler/enums/__init__.py

pything/draugr

2fda662f2fa97236e4495a6af2b8237516fa428b

[ "Apache-2.0" ]

null

from .task_action_type import * from .task_creation import * from .task_logon_type import * from .task_trigger import *

24

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adbe77a6568042d5ad531931eaabc8ad2496f9b7

27,386

py

Python

pynos/versions/ver_7/ver_7_1_0/yang/brocade_ras_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

12

2015-09-21T23:56:09.000Z

2018-03-30T04:35:32.000Z

pynos/versions/ver_7/ver_7_1_0/yang/brocade_ras_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

10

2016-09-15T19:03:27.000Z

2017-07-17T23:38:01.000Z

pynos/versions/ver_7/ver_7_1_0/yang/brocade_ras_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

6

2015-08-14T08:05:23.000Z

2022-02-03T15:33:54.000Z

#!/usr/bin/env python import xml.etree.ElementTree as ET class brocade_ras_ext(object): """Auto generated class. """ def __init__(self, **kwargs): self._callback = kwargs.pop('callback') def show_raslog_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog input = ET.SubElement(show_raslog, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_input_number_of_latest_events(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog input = ET.SubElement(show_raslog, "input") number_of_latest_events = ET.SubElement(input, "number-of-latest-events") number_of_latest_events.text = kwargs.pop('number_of_latest_events') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") rbridge_id = ET.SubElement(show_all_raslog, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_number_of_entries(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") number_of_entries = ET.SubElement(show_all_raslog, "number-of-entries") number_of_entries.text = kwargs.pop('number_of_entries') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_index(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") index = ET.SubElement(raslog_entries, "index") index.text = kwargs.pop('index') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message_id = ET.SubElement(raslog_entries, "message-id") message_id.text = kwargs.pop('message_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_date_and_time_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") date_and_time_info = ET.SubElement(raslog_entries, "date-and-time-info") date_and_time_info.text = kwargs.pop('date_and_time_info') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_severity(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") severity = ET.SubElement(raslog_entries, "severity") severity.text = kwargs.pop('severity') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_repeat_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") repeat_count = ET.SubElement(raslog_entries, "repeat-count") repeat_count.text = kwargs.pop('repeat_count') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message = ET.SubElement(raslog_entries, "message") message.text = kwargs.pop('message') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message_flag(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message_flag = ET.SubElement(raslog_entries, "message-flag") message_flag.text = kwargs.pop('message_flag') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_log_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") log_type = ET.SubElement(raslog_entries, "log-type") log_type.text = kwargs.pop('log_type') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_switch_or_chassis_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") switch_or_chassis_name = ET.SubElement(raslog_entries, "switch-or-chassis-name") switch_or_chassis_name.text = kwargs.pop('switch_or_chassis_name') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_cmd_status_error_msg(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") cmd_status_error_msg = ET.SubElement(output, "cmd-status-error-msg") cmd_status_error_msg.text = kwargs.pop('cmd_status_error_msg') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status input = ET.SubElement(show_support_save_status, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") rbridge_id = ET.SubElement(show_support_save_status, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_status(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") status = ET.SubElement(show_support_save_status, "status") status.text = kwargs.pop('status') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_message(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") message = ET.SubElement(show_support_save_status, "message") message.text = kwargs.pop('message') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_percentage_of_completion(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") percentage_of_completion = ET.SubElement(show_support_save_status, "percentage-of-completion") percentage_of_completion.text = kwargs.pop('percentage_of_completion') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info input = ET.SubElement(show_system_info, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_output_show_system_info_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info output = ET.SubElement(show_system_info, "output") show_system_info = ET.SubElement(output, "show-system-info") rbridge_id = ET.SubElement(show_system_info, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_output_show_system_info_stack_mac(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info output = ET.SubElement(show_system_info, "output") show_system_info = ET.SubElement(output, "show-system-info") stack_mac = ET.SubElement(show_system_info, "stack-mac") stack_mac.text = kwargs.pop('stack_mac') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog input = ET.SubElement(show_raslog, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_input_number_of_latest_events(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog input = ET.SubElement(show_raslog, "input") number_of_latest_events = ET.SubElement(input, "number-of-latest-events") number_of_latest_events.text = kwargs.pop('number_of_latest_events') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") rbridge_id = ET.SubElement(show_all_raslog, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_number_of_entries(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") number_of_entries = ET.SubElement(show_all_raslog, "number-of-entries") number_of_entries.text = kwargs.pop('number_of_entries') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_index(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") index = ET.SubElement(raslog_entries, "index") index.text = kwargs.pop('index') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message_id = ET.SubElement(raslog_entries, "message-id") message_id.text = kwargs.pop('message_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_date_and_time_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") date_and_time_info = ET.SubElement(raslog_entries, "date-and-time-info") date_and_time_info.text = kwargs.pop('date_and_time_info') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_severity(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") severity = ET.SubElement(raslog_entries, "severity") severity.text = kwargs.pop('severity') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_repeat_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") repeat_count = ET.SubElement(raslog_entries, "repeat-count") repeat_count.text = kwargs.pop('repeat_count') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message = ET.SubElement(raslog_entries, "message") message.text = kwargs.pop('message') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_message_flag(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") message_flag = ET.SubElement(raslog_entries, "message-flag") message_flag.text = kwargs.pop('message_flag') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_log_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") log_type = ET.SubElement(raslog_entries, "log-type") log_type.text = kwargs.pop('log_type') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_show_all_raslog_raslog_entries_switch_or_chassis_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") show_all_raslog = ET.SubElement(output, "show-all-raslog") raslog_entries = ET.SubElement(show_all_raslog, "raslog-entries") switch_or_chassis_name = ET.SubElement(raslog_entries, "switch-or-chassis-name") switch_or_chassis_name.text = kwargs.pop('switch_or_chassis_name') callback = kwargs.pop('callback', self._callback) return callback(config) def show_raslog_output_cmd_status_error_msg(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_raslog = ET.Element("show_raslog") config = show_raslog output = ET.SubElement(show_raslog, "output") cmd_status_error_msg = ET.SubElement(output, "cmd-status-error-msg") cmd_status_error_msg.text = kwargs.pop('cmd_status_error_msg') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status input = ET.SubElement(show_support_save_status, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") rbridge_id = ET.SubElement(show_support_save_status, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_status(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") status = ET.SubElement(show_support_save_status, "status") status.text = kwargs.pop('status') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_message(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") message = ET.SubElement(show_support_save_status, "message") message.text = kwargs.pop('message') callback = kwargs.pop('callback', self._callback) return callback(config) def show_support_save_status_output_show_support_save_status_percentage_of_completion(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_support_save_status = ET.Element("show_support_save_status") config = show_support_save_status output = ET.SubElement(show_support_save_status, "output") show_support_save_status = ET.SubElement(output, "show-support-save-status") percentage_of_completion = ET.SubElement(show_support_save_status, "percentage-of-completion") percentage_of_completion.text = kwargs.pop('percentage_of_completion') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info input = ET.SubElement(show_system_info, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_output_show_system_info_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info output = ET.SubElement(show_system_info, "output") show_system_info = ET.SubElement(output, "show-system-info") rbridge_id = ET.SubElement(show_system_info, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def show_system_info_output_show_system_info_stack_mac(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_system_info = ET.Element("show_system_info") config = show_system_info output = ET.SubElement(show_system_info, "output") show_system_info = ET.SubElement(output, "show-system-info") stack_mac = ET.SubElement(show_system_info, "stack-mac") stack_mac.text = kwargs.pop('stack_mac') callback = kwargs.pop('callback', self._callback) return callback(config)

43.127559

106

0.661469

3,227

27,386

5.291602

0.021072

0.081986

0.066995

0.100843

0.99227

0

0.228767

27,386

635

107

43.127559

0.808484

0.048309

0

0.99115

1

0

0.132905

0.027402

0

1

0.099558

false

0

0.002212

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0.201327

0

null

0

1

0

1

0

null

0

8

ade803b163caa3a9a47e903eb04ba5dfbadc159e

109

py

Python

python/testData/psi/PatternMatchingRecoveryAsPatternsWithIllegalTarget.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

python/testData/psi/PatternMatchingRecoveryAsPatternsWithIllegalTarget.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

python/testData/psi/PatternMatchingRecoveryAsPatternsWithIllegalTarget.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

match x: case 1 as foo.bar: pass case 1 as foo[0]: pass case 1 as _: pass

15.571429

22

0.458716

18

109

2.722222

0.5

0.306122

0.428571

0.408163

0

0.070175

0.477064

109

7

23

15.571429

0.789474

0

0.428571

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null

0.428571

0

null

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

bc3ae3f744ea2c23a629d23bebc471bf396f11f3

70

py

Python

eunice012716/Week1/ch2/2.6/exercise3.py

coookie89/Intern-Training

6e3b26edfee5bdcc98dd5ac05d35cef125778ad5

[ "MIT" ]

1

2021-08-24T12:14:46.000Z

eunice012716/Week1/ch2/2.6/exercise3.py

coookie89/Intern-Training

6e3b26edfee5bdcc98dd5ac05d35cef125778ad5

[ "MIT" ]

14

2021-07-09T07:48:35.000Z

2021-08-19T03:06:31.000Z

eunice012716/Week1/ch2/2.6/exercise3.py

coookie89/Intern-Training

6e3b26edfee5bdcc98dd5ac05d35cef125778ad5

[ "MIT" ]

11

2021-07-09T07:35:24.000Z

2021-08-15T07:19:43.000Z

if __name__ == "__main__": print("P(A,B,C)=P(A)*P(B|A)*P(C|B)")

23.333333

41

0.5

16

70

1.6875

0.5

0.148148

0

0.157143

70

2

42

35

0.457627

0

0.5

0.514706

0.397059

0

1

0

true

0

0.5

1

0

1

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

70d92b584769b44a4d43922d45cb52a981d0afaa

71,895

py

Python

tests/unit_tests/iolibs/test_group_subprocs.py

jlrainbolt/MG5_v2_6_1

241f0c6f309342d6e8b813284467b2edd393c7d6

[ "NCSA" ]

5

2018-10-23T14:37:18.000Z

2021-11-22T20:59:02.000Z

tests/unit_tests/iolibs/test_group_subprocs.py

jlrainbolt/MG5_v2_6_1

241f0c6f309342d6e8b813284467b2edd393c7d6

[ "NCSA" ]

26

2018-10-08T15:49:32.000Z

2020-05-15T13:33:36.000Z

tests/unit_tests/iolibs/test_group_subprocs.py

jlrainbolt/MG5_v2_6_1

241f0c6f309342d6e8b813284467b2edd393c7d6

[ "NCSA" ]

4

2019-02-18T11:42:18.000Z

2021-11-11T20:46:08.000Z

################################################################################ # # Copyright (c) 2009 The MadGraph5_aMC@NLO Development team and Contributors # # This file is a part of the MadGraph5_aMC@NLO project, an application which # automatically generates Feynman diagrams and matrix elements for arbitrary # high-energy processes in the Standard Model and beyond. # # It is subject to the MadGraph5_aMC@NLO license which should accompany this # distribution. # # For more information, visit madgraph.phys.ucl.ac.be and amcatnlo.web.cern.ch # ################################################################################ """Unit test library for the export v4 format routines""" import StringIO import copy import fractions import os import tests.unit_tests as unittest import madgraph.various.misc as misc import madgraph.iolibs.export_v4 as export_v4 import madgraph.iolibs.file_writers as writers import madgraph.iolibs.group_subprocs as group_subprocs import madgraph.iolibs.helas_call_writers as helas_call_writers import madgraph.core.base_objects as base_objects import madgraph.core.helas_objects as helas_objects import madgraph.core.diagram_generation as diagram_generation import madgraph.core.color_algebra as color import tests.unit_tests.iolibs.test_file_writers as test_file_writers import tests.unit_tests.iolibs.test_helas_call_writers as \ test_helas_call_writers #=============================================================================== # SubProcessGroupTest #=============================================================================== class SubProcessGroupTest(unittest.TestCase): """Test class for the SubProcessGroup class""" def setUp(self): mypartlist = base_objects.ParticleList() myinterlist = base_objects.InteractionList() # A gluon mypartlist.append(base_objects.Particle({'name':'g', 'antiname':'g', 'spin':3, 'color':8, 'mass':'zero', 'width':'zero', 'texname':'g', 'antitexname':'g', 'line':'curly', 'charge':0., 'pdg_code':21, 'propagating':True, 'is_part':True, 'self_antipart':True})) g = mypartlist[-1] # A quark U and its antiparticle mypartlist.append(base_objects.Particle({'name':'u', 'antiname':'u~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'u', 'antitexname':'\bar u', 'line':'straight', 'charge':2. / 3., 'pdg_code':2, 'propagating':True, 'is_part':True, 'self_antipart':False})) u = mypartlist[-1] antiu = copy.copy(u) antiu.set('is_part', False) # A quark D and its antiparticle mypartlist.append(base_objects.Particle({'name':'d', 'antiname':'d~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'d', 'antitexname':'\bar d', 'line':'straight', 'charge':-1. / 3., 'pdg_code':1, 'propagating':True, 'is_part':True, 'self_antipart':False})) d = mypartlist[-1] antid = copy.copy(d) antid.set('is_part', False) # A photon mypartlist.append(base_objects.Particle({'name':'a', 'antiname':'a', 'spin':3, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'\gamma', 'antitexname':'\gamma', 'line':'wavy', 'charge':0., 'pdg_code':22, 'propagating':True, 'is_part':True, 'self_antipart':True})) a = mypartlist[-1] # A electron and positron mypartlist.append(base_objects.Particle({'name':'e-', 'antiname':'e+', 'spin':2, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'e^-', 'antitexname':'e^+', 'line':'straight', 'charge':-1., 'pdg_code':11, 'propagating':True, 'is_part':True, 'self_antipart':False})) eminus = mypartlist[-1] eplus = copy.copy(eminus) eplus.set('is_part', False) # A Z mypartlist.append(base_objects.Particle({'name':'z', 'antiname':'z', 'spin':3, 'color':1, 'mass':'MZ', 'width':'WZ', 'texname':'Z', 'antitexname':'Z', 'line':'wavy', 'charge':0., 'pdg_code':23, 'propagating':True, 'is_part':True, 'self_antipart':True})) z = mypartlist[-1] # 3 gluon vertiex myinterlist.append(base_objects.Interaction({ 'id': 1, 'particles': base_objects.ParticleList(\ [g] * 3), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'G'}, 'orders':{'QCD':1}})) # 4 gluon vertex myinterlist.append(base_objects.Interaction({ 'id': 2, 'particles': base_objects.ParticleList(\ [g] * 4), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'G^2'}, 'orders':{'QCD':2}})) # Gluon and photon couplings to quarks myinterlist.append(base_objects.Interaction({ 'id': 3, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 4, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 5, 'particles': base_objects.ParticleList(\ [d, \ antid, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 6, 'particles': base_objects.ParticleList(\ [d, \ antid, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) # Coupling of e to gamma myinterlist.append(base_objects.Interaction({ 'id': 7, 'particles': base_objects.ParticleList(\ [eminus, \ eplus, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) # Coupling of Z to quarks and electrons myinterlist.append(base_objects.Interaction({ 'id': 8, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 9, 'particles': base_objects.ParticleList(\ [d, \ antid, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 10, 'particles': base_objects.ParticleList(\ [eplus, \ eminus, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) self.mymodel = base_objects.Model() self.mymodel.set('particles', mypartlist) self.mymodel.set('interactions', myinterlist) self.mymodel.set('name', 'sm') def test_group_subprocs_and_get_diagram_maps(self): """Test grouping subprocs and generating HelasMatrixElements""" max_fs = 2 p = [21, 1, -1, 2, -2] my_multi_leg = base_objects.MultiLeg({'ids': p, 'state': True}); diagram_maps = [[{0: [0, 1, 2, 3]}, {0: [1, 2, 3]}, {0: [1, 2, 3], 1: [1, 3, 2]}, {0: [1, 2, 3], 1: [1, 3, 2]}, {0: [1, 2, 3, 4, 5, 6], 1: [7, 8, 9, 1, 2, 3], 2: [7, 8, 9], 3: [1, 2, 3], 4: [1, 2, 3], 5: [7, 8, 9, 4, 5, 6], 6: [7, 8, 9], 7: [1, 2, 3, 4, 5, 6], 8: [1, 2, 3], 9: [1, 2, 3]}, {0: [1, 2, 3], 1: [1, 3, 2]}]] diags_for_config = [[[[2], [3], [4]], [[1], [2], [3]], [[1, 1], [2, 3], [3, 2]], [[1, 1], [2, 3], [3, 2]], [[1, 4, 0, 1, 1, 0, 0, 1, 1, 1], [2, 5, 0, 2, 2, 0, 0, 2, 2, 2], [3, 6, 0, 3, 3, 0, 0, 3, 3, 3], [4, 0, 0, 0, 0, 4, 0, 4, 0, 0], [5, 0, 0, 0, 0, 5, 0, 5, 0, 0], [6, 0, 0, 0, 0, 6, 0, 6, 0, 0], [0, 1, 1, 0, 0, 1, 1, 0, 0, 0], [0, 2, 2, 0, 0, 2, 2, 0, 0, 0], [0, 3, 3, 0, 0, 3, 3, 0, 0, 0]], [[1, 1], [2, 3], [3, 2]]]] #new_diagram_maps = [] #new_diags_for_config = [] for nfs in range(2, max_fs + 1): # Define the multiprocess my_multi_leglist = base_objects.MultiLegList([copy.copy(leg) for leg in [my_multi_leg] * (2 + nfs)]) my_multi_leglist[0].set('state', False) my_multi_leglist[1].set('state', False) my_process_definition = base_objects.ProcessDefinition({\ 'legs':my_multi_leglist, 'model':self.mymodel, 'orders': {'QED': nfs}}) my_multiprocess = diagram_generation.MultiProcess(\ {'process_definitions':\ base_objects.ProcessDefinitionList([my_process_definition])}) nproc = 0 # Calculate diagrams for all processes amplitudes = my_multiprocess.get('amplitudes') subprocess_groups = group_subprocs.SubProcessGroup.\ group_amplitudes(amplitudes, "madevent") #dmaps = [] #diags = [] for igroup, group in enumerate(subprocess_groups): group.get('matrix_elements') #dmaps.append(group.get('diagram_maps')) self.assertEqual(group.get('diagram_maps'), diagram_maps[nfs-2][igroup]) #diags.append([group.get_subproc_diagrams_for_config(ic) for\ # ic in range(len(group.get('mapping_diagrams')))]) for iconfig, config in enumerate(group.get('mapping_diagrams')): self.assertEqual(group.get_subproc_diagrams_for_config(\ iconfig), diags_for_config[nfs-2][igroup][iconfig]) pass #new_diagram_maps.append(dmaps) #new_diags_for_config.append(diags) #print 'diagram_maps = ',new_diagram_maps #print 'diags_for_config = ',new_diags_for_config def test_find_process_classes_and_mapping_diagrams(self): """Test the find_process_classes and find_mapping_diagrams function.""" max_fs = 3 p = [21, 1, -1, 2, -2] my_multi_leg = base_objects.MultiLeg({'ids': p, 'state': True}); proc_classes = [{0: 0, 1: 1, 2: 1, 3: 2, 4: 2, 5: 2, 6: 2, 7: 3, 8: 4, 9: 5, 10: 4, 11: 4, 12: 4, 13: 4, 14: 3, 15: 5, 16: 4, 17: 4, 18: 4, 19: 4, 20: 4, 21: 3, 22: 4, 23: 4, 24: 4, 25: 5, 26: 4, 27: 4, 28: 3, 29: 4, 30: 4, 31: 5, 32: 4, 33: 4, 34: 4}, {0: 0, 1: 1, 2: 1, 3: 2, 4: 3, 5: 3, 6: 2, 7: 3, 8: 3, 9: 2, 10: 3, 11: 3, 12: 2, 13: 3, 14: 3, 15: 4, 16: 5, 17: 5, 18: 6, 19: 7, 20: 6, 21: 6, 22: 6, 23: 6, 24: 4, 25: 5, 26: 5, 27: 7, 28: 6, 29: 6, 30: 6, 31: 6, 32: 6, 33: 4, 34: 5, 35: 5, 36: 6, 37: 6, 38: 6, 39: 7, 40: 6, 41: 6, 42: 4, 43: 5, 44: 5, 45: 6, 46: 6, 47: 7, 48: 6, 49: 6, 50: 6}] all_diagram_maps = [[{0: [0, 1, 2, 3]}, {0: [1, 2, 3], 1: [1, 2, 3]}, {0: [1, 2, 3], 1: [1, 3, 2], 2: [1, 2, 3], 3: [1, 3, 2]}, {0: [1, 2, 3], 1: [1, 3, 2], 2: [1, 2, 3], 3: [1, 3, 2]}, {0: [1, 2, 3, 4, 5, 6], 1: [7, 8, 9, 1, 2, 3], 2: [7, 8, 9], 3: [1, 2, 3], 4: [1, 2, 3], 5: [7, 8, 9, 4, 5, 6], 6: [7, 8, 9], 7: [1, 2, 3, 4, 5, 6], 8: [1, 2, 3], 9: [1, 2, 3], 10: [4, 5, 6], 11: [4, 5, 6], 12: [1, 2, 3, 4, 5, 6], 13: [7, 8, 9], 14: [7, 8, 9, 1, 2, 3], 15: [4, 5, 6], 16: [4, 5, 6], 17: [7, 8, 9], 18: [7, 8, 9, 4, 5, 6], 19: [1, 2, 3, 4, 5, 6]}, {0: [1, 2, 3], 1: [1, 3, 2], 2: [1, 2, 3], 3: [1, 3, 2]}], [{0: [1, 2, 3, 0, 4, 5, 6, 0, 7, 8, 9, 0, 10, 11, 12, 0, 13, 14, 15, 0, 0, 0, 0, 0, 0]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 1: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 1: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0], 2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 3: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 1: [4, 5, 6, 10, 11, 12, 13, 14, 15, 19, 20, 21, 25], 2: [27, 28, 29, 16, 17, 18, 30, 31, 32, 1, 2, 3, 7, 8, 9, 33, 34, 35, 22, 23, 24, 36, 37, 38, 26, 39], 3: [10, 11, 12, 4, 5, 6, 13, 14, 15, 19, 20, 21, 25], 4: [27, 28, 29, 33, 34, 35, 36, 37, 38, 30, 31, 32, 39], 5: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 6: [27, 28, 29, 33, 34, 35, 30, 31, 32, 36, 37, 38, 39], 7: [27, 28, 29, 16, 17, 18, 30, 31, 32, 1, 2, 3, 7, 8, 9, 33, 34, 35, 22, 23, 24, 36, 37, 38, 26, 39]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 1: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0], 2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 3: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 1: [4, 5, 6, 10, 11, 12, 13, 14, 15, 19, 20, 21, 25], 2: [27, 28, 29, 16, 17, 18, 30, 31, 32, 1, 2, 3, 7, 8, 9, 33, 34, 35, 22, 23, 24, 36, 37, 38, 26, 39], 3: [10, 11, 12, 4, 5, 6, 13, 14, 15, 19, 20, 21, 25], 4: [27, 28, 29, 33, 34, 35, 36, 37, 38, 30, 31, 32, 39], 5: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 6: [27, 28, 29, 33, 34, 35, 30, 31, 32, 36, 37, 38, 39], 7: [27, 28, 29, 16, 17, 18, 30, 31, 32, 1, 2, 3, 7, 8, 9, 33, 34, 35, 22, 23, 24, 36, 37, 38, 26, 39]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 1: [4, 5, 6, 27, 28, 29, 19, 20, 21, 30, 31, 32, 33, 34, 35, 10, 11, 12, 36, 37, 38, 13, 14, 15, 39, 25], 2: [27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], 3: [4, 5, 6, 10, 11, 12, 13, 14, 15, 19, 20, 21, 25], 4: [4, 5, 6, 10, 11, 12, 19, 20, 21, 13, 14, 15, 25], 5: [22, 23, 24, 30, 31, 32, 1, 2, 3, 27, 28, 29, 33, 34, 35, 7, 8, 9, 36, 37, 38, 16, 17, 18, 39, 26], 6: [30, 31, 32, 27, 28, 29, 33, 34, 35, 36, 37, 38, 39], 7: [7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 19, 20, 21, 22, 23, 24, 13, 14, 15, 16, 17, 18, 25, 26], 8: [10, 11, 12, 4, 5, 6, 13, 14, 15, 19, 20, 21, 25], 9: [10, 11, 12, 4, 5, 6, 19, 20, 21, 13, 14, 15, 25], 10: [22, 23, 24, 7, 8, 9, 16, 17, 18, 1, 2, 3, 26], 11: [7, 8, 9, 22, 23, 24, 16, 17, 18, 1, 2, 3, 26], 12: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], 13: [36, 37, 38, 33, 34, 35, 30, 31, 32, 27, 28, 29, 39], 14: [4, 5, 6, 27, 28, 29, 19, 20, 21, 30, 31, 32, 33, 34, 35, 10, 11, 12, 36, 37, 38, 13, 14, 15, 39, 25], 15: [22, 23, 24, 7, 8, 9, 1, 2, 3, 16, 17, 18, 26], 16: [7, 8, 9, 22, 23, 24, 1, 2, 3, 16, 17, 18, 26], 17: [36, 37, 38, 33, 34, 35, 27, 28, 29, 30, 31, 32, 39], 18: [22, 23, 24, 30, 31, 32, 1, 2, 3, 27, 28, 29, 33, 34, 35, 7, 8, 9, 36, 37, 38, 16, 17, 18, 39, 26], 19: [7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 19, 20, 21, 22, 23, 24, 13, 14, 15, 16, 17, 18, 25, 26]}, {0: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 1: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0], 2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0], 3: [2, 1, 3, 5, 4, 6, 10, 11, 12, 7, 8, 9, 13, 15, 14, 0]}]] #new_diagram_maps = [] for nfs in range(2, max_fs + 1): # Define the multiprocess my_multi_leglist = base_objects.MultiLegList([copy.copy(leg) for leg in [my_multi_leg] * (2 + nfs)]) my_multi_leglist[0].set('state', False) my_multi_leglist[1].set('state', False) my_process_definition = base_objects.ProcessDefinition({\ 'legs':my_multi_leglist, 'model':self.mymodel, 'orders': {'QED': nfs}}) my_multiprocess = diagram_generation.MultiProcess(\ {'process_definitions':\ base_objects.ProcessDefinitionList([my_process_definition])}) nproc = 0 # Calculate diagrams for all processes amplitudes = my_multiprocess.get('amplitudes') process_classes = group_subprocs.SubProcessGroup.\ find_process_classes(amplitudes, "madevent") #print process_classes self.assertEqual(process_classes, proc_classes[nfs-2]) subproc_groups = group_subprocs.SubProcessGroup.\ group_amplitudes(amplitudes, "madevent") #dmaps = [] for inum, group in enumerate(subproc_groups): mapping_diagrams, diagram_maps = group.find_mapping_diagrams() #print "mapping_diagrams: " #print "\n".join(["%d: %s" % (i+1, str(a)) for i,a in \ # enumerate(mapping_diagrams)]) #dmaps.append(diagram_maps) for iamp, amplitude in enumerate(group.get('amplitudes')): #print amplitude.nice_string() self.assertEqual(diagram_maps[iamp], all_diagram_maps[nfs-2][inum][iamp]) pass #new_diagram_maps.append(dmaps) #print "all_diagram_maps = ",new_diagram_maps def test_group_decay_chains(self): """Test group_amplitudes for decay chains.""" max_fs = 2 # 3 procs = [[1,-1,2,-2,23], [2,2,2,2,23], [2,-2,21,21,23], [1,-1,21,21,23]] decays = [[23,1,-1,21], [23,11,-11]] coreamplitudes = diagram_generation.AmplitudeList() decayamplitudes = diagram_generation.AmplitudeList() decayprocs = base_objects.ProcessList() for proc in procs: # Define the multiprocess my_leglist = base_objects.LegList([\ base_objects.Leg({'id': id, 'state': True}) for id in proc]) my_leglist[0].set('state', False) my_leglist[1].set('state', False) my_process = base_objects.Process({'legs':my_leglist, 'model':self.mymodel, 'orders':{'QED':1}}) my_amplitude = diagram_generation.Amplitude(my_process) coreamplitudes.append(my_amplitude) for proc in decays: # Define the multiprocess my_leglist = base_objects.LegList([\ base_objects.Leg({'id': id, 'state': True}) for id in proc]) my_leglist[0].set('state', False) my_process = base_objects.Process({'legs':my_leglist, 'model':self.mymodel, 'is_decay_chain': True}) my_amplitude = diagram_generation.Amplitude(my_process) decayamplitudes.append(my_amplitude) decayprocs.append(my_process) decays = diagram_generation.DecayChainAmplitudeList([\ diagram_generation.DecayChainAmplitude({\ 'amplitudes': decayamplitudes})]) decay_chains = diagram_generation.DecayChainAmplitude({\ 'amplitudes': coreamplitudes, 'decay_chains': decays}) dc_subproc_group = group_subprocs.DecayChainSubProcessGroup.\ group_amplitudes(\ diagram_generation.DecayChainAmplitudeList([decay_chains])) #print dc_subproc_group.nice_string() self.assertEqual(dc_subproc_group.nice_string(), """Group 1: Process: d d~ > u u~ z QED<=1 4 diagrams: 1 ((1(-1),2(1)>1(21),id:5),(3(2),5(23)>3(2),id:8),(1(21),3(2),4(-2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 2 ((1(-1),2(1)>1(21),id:5),(4(-2),5(23)>4(-2),id:8),(1(21),3(2),4(-2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 3 ((1(-1),5(23)>1(-1),id:9),(3(2),4(-2)>3(21),id:3),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 4 ((2(1),5(23)>2(1),id:9),(3(2),4(-2)>3(21),id:3),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) Process: u u > u u z QED<=1 8 diagrams: 1 ((1(-2),3(2)>1(21),id:3),(2(-2),5(23)>2(-2),id:8),(1(21),2(-2),4(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 2 ((1(-2),3(2)>1(21),id:3),(4(2),5(23)>4(2),id:8),(1(21),2(-2),4(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 3 ((1(-2),4(2)>1(21),id:3),(2(-2),5(23)>2(-2),id:8),(1(21),2(-2),3(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 4 ((1(-2),4(2)>1(21),id:3),(3(2),5(23)>3(2),id:8),(1(21),2(-2),3(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 5 ((1(-2),5(23)>1(-2),id:8),(2(-2),3(2)>2(21),id:3),(1(-2),2(21),4(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 6 ((1(-2),5(23)>1(-2),id:8),(2(-2),4(2)>2(21),id:3),(1(-2),2(21),3(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 7 ((2(-2),3(2)>2(21),id:3),(4(2),5(23)>4(2),id:8),(1(-2),2(21),4(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) 8 ((2(-2),4(2)>2(21),id:3),(3(2),5(23)>3(2),id:8),(1(-2),2(21),3(2),id:3)) (QCD=2,QED=1,WEIGHTED=4) Group 2: Process: u u~ > g g z QED<=1 8 diagrams: 1 ((1(-2),3(21)>1(-2),id:3),(2(2),4(21)>2(2),id:3),(1(-2),2(2),5(23),id:8)) (QCD=2,QED=1,WEIGHTED=4) 2 ((1(-2),3(21)>1(-2),id:3),(2(2),5(23)>2(2),id:8),(1(-2),2(2),4(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) 3 ((1(-2),4(21)>1(-2),id:3),(2(2),3(21)>2(2),id:3),(1(-2),2(2),5(23),id:8)) (QCD=2,QED=1,WEIGHTED=4) 4 ((1(-2),4(21)>1(-2),id:3),(2(2),5(23)>2(2),id:8),(1(-2),2(2),3(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) 5 ((1(-2),5(23)>1(-2),id:8),(2(2),3(21)>2(2),id:3),(1(-2),2(2),4(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) 6 ((1(-2),5(23)>1(-2),id:8),(2(2),4(21)>2(2),id:3),(1(-2),2(2),3(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) 7 ((1(-2),5(23)>1(-2),id:8),(3(21),4(21)>3(21),id:1),(1(-2),2(2),3(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) 8 ((2(2),5(23)>2(2),id:8),(3(21),4(21)>3(21),id:1),(1(-2),2(2),3(21),id:3)) (QCD=2,QED=1,WEIGHTED=4) Process: d d~ > g g z QED<=1 8 diagrams: 1 ((1(-1),3(21)>1(-1),id:5),(2(1),4(21)>2(1),id:5),(1(-1),2(1),5(23),id:9)) (QCD=2,QED=1,WEIGHTED=4) 2 ((1(-1),3(21)>1(-1),id:5),(2(1),5(23)>2(1),id:9),(1(-1),2(1),4(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 3 ((1(-1),4(21)>1(-1),id:5),(2(1),3(21)>2(1),id:5),(1(-1),2(1),5(23),id:9)) (QCD=2,QED=1,WEIGHTED=4) 4 ((1(-1),4(21)>1(-1),id:5),(2(1),5(23)>2(1),id:9),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 5 ((1(-1),5(23)>1(-1),id:9),(2(1),3(21)>2(1),id:5),(1(-1),2(1),4(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 6 ((1(-1),5(23)>1(-1),id:9),(2(1),4(21)>2(1),id:5),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 7 ((1(-1),5(23)>1(-1),id:9),(3(21),4(21)>3(21),id:1),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) 8 ((2(1),5(23)>2(1),id:9),(3(21),4(21)>3(21),id:1),(1(-1),2(1),3(21),id:5)) (QCD=2,QED=1,WEIGHTED=4) Decay groups: Group 1: Process: z > d d~ g 2 diagrams: 1 ((2(1),4(21)>2(1),id:5),(2(1),3(-1)>2(23),id:9),(1(23),2(23),id:0)) (QCD=1,QED=1,WEIGHTED=3) 2 ((3(-1),4(21)>3(-1),id:5),(2(1),3(-1)>2(23),id:9),(1(23),2(23),id:0)) (QCD=1,QED=1,WEIGHTED=3) Group 2: Process: z > e- e+ 1 diagrams: 1 ((2(11),3(-11)>2(23),id:10),(1(23),2(23),id:0)) (QCD=0,QED=1,WEIGHTED=2)""") subproc_groups = \ dc_subproc_group.generate_helas_decay_chain_subproc_groups() self.assertEqual(len(subproc_groups), 4) group_names = ['qq_qqz_z_qqg', 'qq_qqz_z_ll', 'qq_ggz_z_qqg', 'qq_ggz_z_ll'] for igroup, group in enumerate(subproc_groups): self.assertEqual(group.get('name'), group_names[igroup]) def test_special_group_decay_chain(self): """Test group_amplitudes for special decay chains.""" mypartlist = base_objects.ParticleList() myinterlist = base_objects.InteractionList() # A gluon mypartlist.append(base_objects.Particle({'name':'g', 'antiname':'g', 'spin':3, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'g', 'antitexname':'g', 'line':'curly', 'charge':0., 'pdg_code':21, 'propagating':True, 'is_part':True, 'self_antipart':True})) g = mypartlist[-1] # A gluino mypartlist.append(base_objects.Particle({'name':'go', 'antiname':'go', 'spin':2, 'color':1, 'mass':'MGO', 'width':'WGO', 'texname':'go', 'antitexname':'go', 'line':'curly', 'charge':0., 'pdg_code':1000021, 'propagating':True, 'is_part':True, 'self_antipart':True})) go = mypartlist[-1] # A quark D and its antiparticle mypartlist.append(base_objects.Particle({'name':'d', 'antiname':'d~', 'spin':2, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'d', 'antitexname':'\bar d', 'line':'straight', 'charge':-1. / 3., 'pdg_code':1, 'propagating':True, 'is_part':True, 'self_antipart':False})) d = mypartlist[-1] antid = copy.copy(d) antid.set('is_part', False) # A d squark and its antiparticle mypartlist.append(base_objects.Particle({'name':'dl', 'antiname':'dl~', 'spin':0, 'color':1, 'mass':'MDL', 'width':'WDL', 'texname':'dl', 'antitexname':'\bar dl', 'line':'straight', 'charge':-1. / 3., 'pdg_code':1000001, 'propagating':True, 'is_part':True, 'self_antipart':False})) dl = mypartlist[-1] antidl = copy.copy(dl) antidl.set('is_part', False) # A neutralino mypartlist.append(base_objects.Particle({'name':'n1', 'antiname':'n1', 'spin':2, 'color':1, 'mass':'MN1', 'width':'WN1', 'texname':'n1', 'antitexname':'n1', 'line':'wavy', 'charge':0., 'pdg_code':1000022, 'propagating':True, 'is_part':True, 'self_antipart':True})) n1 = mypartlist[-1] # 3 gluon vertiex myinterlist.append(base_objects.Interaction({ 'id': 1, 'particles': base_objects.ParticleList(\ [g] * 3), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'G'}, 'orders':{'QCD':1}})) # Gluon couplings to gluinos myinterlist.append(base_objects.Interaction({ 'id': 3, 'particles': base_objects.ParticleList(\ [go, \ go, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) # Gluino and neutralino couplings to quarks and squarks myinterlist.append(base_objects.Interaction({ 'id': 4, 'particles': base_objects.ParticleList(\ [go, d, antidl]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 5, 'particles': base_objects.ParticleList(\ [antid, go, dl]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 6, 'particles': base_objects.ParticleList(\ [n1, \ d, \ antidl]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 7, 'particles': base_objects.ParticleList(\ [antid, \ n1, \ dl]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QED':1}})) mymodel = base_objects.Model() mymodel.set('particles', mypartlist) mymodel.set('interactions', myinterlist) mymodel.set('name', 'sm') # Multiparticle labels ds = [1,-1] dls = [1000001,-1000001] proc = [21,21,1000021,1000021] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': [id]}) for id in proc]) my_leglist[0].set('state', False) my_leglist[1].set('state', False) process = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decayproc1 = [[1000021],ds,dls] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decayproc1]) my_leglist[0].set('state', False) decayprocess1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decayproc2 = [dls,ds,[1000022]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decayproc2]) my_leglist[0].set('state', False) decayprocess2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decayprocess1.get('decay_chains').append(decayprocess2) process.get('decay_chains').append(decayprocess1) process.get('decay_chains').append(decayprocess1) my_amplitude = diagram_generation.DecayChainAmplitude(process) dc_subproc_group = group_subprocs.DecayChainSubProcessGroup.\ group_amplitudes(\ diagram_generation.DecayChainAmplitudeList([my_amplitude])) subproc_groups = \ dc_subproc_group.generate_helas_decay_chain_subproc_groups() self.assertEqual(len(subproc_groups), 1) self.assertEqual(len(subproc_groups[0].get('matrix_elements')),3) me_strings = ["""Process: g g > go go WEIGHTED<=2 Decay: go > d dl~ WEIGHTED<=1 Decay: dl~ > d~ n1 WEIGHTED<=2 Decay: go > d dl~ WEIGHTED<=1 Decay: dl~ > d~ n1 WEIGHTED<=2""", """Process: g g > go go WEIGHTED<=2 Decay: go > d dl~ WEIGHTED<=1 Decay: dl~ > d~ n1 WEIGHTED<=2 Decay: go > d~ dl WEIGHTED<=1 Decay: dl > d n1 WEIGHTED<=2""", """Process: g g > go go WEIGHTED<=2 Decay: go > d~ dl WEIGHTED<=1 Decay: dl > d n1 WEIGHTED<=2 Decay: go > d~ dl WEIGHTED<=1 Decay: dl > d n1 WEIGHTED<=2"""] for i,me in enumerate(subproc_groups[0].get('matrix_elements')): self.assertEqual(me.get('processes')[0].nice_string(), me_strings[i]) def test_even_more_special_group_decay_chain(self): """Test group_amplitudes for even more special decay chain""" mypartlist = base_objects.ParticleList() myinterlist = base_objects.InteractionList() # A d quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'d', 'antiname':'d~', 'spin':2, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'d', 'antitexname':'\bar d', 'line':'straight', 'charge':-1. / 3., 'pdg_code':1, 'propagating':True, 'is_part':True, 'self_antipart':False})) d = mypartlist[-1] antid = copy.copy(d) antid.set('is_part', False) # A u quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'u', 'antiname':'u~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'u', 'antitexname':'\bar u', 'line':'straight', 'charge':2. / 3., 'pdg_code':2, 'propagating':True, 'is_part':True, 'self_antipart':False})) u = mypartlist[len(mypartlist) - 1] antiu = copy.copy(u) antiu.set('is_part', False) # An s and its antiparticle mypartlist.append(base_objects.Particle({'name':'s', 'antiname':'s~', 'spin':2, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'d', 'antitexname':'\bar d', 'line':'straight', 'charge':-1. / 3., 'pdg_code':3, 'propagating':True, 'is_part':True, 'self_antipart':False})) s = mypartlist[-1] antis = copy.copy(s) antis.set('is_part', False) # A c quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'c', 'antiname':'c~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'c', 'antitexname':'\bar c', 'line':'straight', 'charge':2. / 3., 'pdg_code':4, 'propagating':True, 'is_part':True, 'self_antipart':False})) c = mypartlist[len(mypartlist) - 1] antic = copy.copy(c) antic.set('is_part', False) # A b quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'b', 'antiname':'b~', 'spin':2, 'color':1, 'mass':'MB', 'width':'zero', 'texname':'b', 'antitexname':'\bar b', 'line':'straight', 'charge':-1. / 3., 'pdg_code':5, 'propagating':True, 'is_part':True, 'self_antipart':False})) b = mypartlist[-1] antib = copy.copy(b) antib.set('is_part', False) # A t quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'t', 'antiname':'t~', 'spin':2, 'color':3, 'mass':'MT', 'width':'zero', 'texname':'t', 'antitexname':'\bar t', 'line':'straight', 'charge':2. / 3., 'pdg_code':6, 'propagating':True, 'is_part':True, 'self_antipart':False})) t = mypartlist[len(mypartlist) - 1] antit = copy.copy(t) antit.set('is_part', False) # A funny Zprime mypartlist.append(base_objects.Particle({ 'name': 'Zp', 'antiname': 'Zp', 'spin': 3, 'color': 1, 'charge': 0.00, 'mass': 'MZp', 'width': 'WZp', 'pdg_code': 9900032, 'texname': 'Zp', 'antitexname': 'Zp', 'line': 'wavy', 'propagating': True, 'is_part': True, 'self_antipart': True})) Zp = mypartlist[-1] # A funny neutralino mypartlist.append(base_objects.Particle({ 'name': '~n1', 'antiname': '~n1', 'spin': 2, 'color': 1, 'charge': 0.00, 'mass': 'MnH1', 'width': 'WnH1', 'pdg_code': 9910012, 'texname': '~n1', 'antitexname': '~n1', 'line': 'swavy', 'propagating': True, 'is_part': True, 'self_antipart': True})) n1 = mypartlist[-1] # A W mypartlist.append(base_objects.Particle({'name':'W+', 'antiname':'W-', 'spin':3, 'color':1, 'mass':'MW', 'width':'WW', 'texname':'W^+', 'antitexname':'W^-', 'line':'wavy', 'charge':1., 'pdg_code':24, 'propagating':True, 'is_part':True, 'self_antipart':False})) Wplus = mypartlist[len(mypartlist) - 1] Wminus = copy.copy(Wplus) Wminus.set('is_part', False) # A electron and positron mypartlist.append(base_objects.Particle({'name':'e-', 'antiname':'e+', 'spin':2, 'color':1, 'mass':'me', 'width':'zero', 'texname':'e^-', 'antitexname':'e^+', 'line':'straight', 'charge':-1., 'pdg_code':11, 'propagating':True, 'is_part':True, 'self_antipart':False})) eminus = mypartlist[len(mypartlist) - 1] eplus = copy.copy(eminus) eplus.set('is_part', False) # Interactions myinterlist.append(base_objects.Interaction({ 'id': 1, 'particles': base_objects.ParticleList(\ [antid,u,Wminus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_35'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 2, 'particles': base_objects.ParticleList(\ [antiu,d,Wplus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_112'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 3, 'particles': base_objects.ParticleList(\ [antis,c,Wminus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_35'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 4, 'particles': base_objects.ParticleList(\ [antic,s,Wplus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_112'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 5, 'particles': base_objects.ParticleList(\ [antib,t,Wminus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_35'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 6, 'particles': base_objects.ParticleList(\ [antit,b,Wplus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_112'}, 'orders': {'QED': 1}})) myinterlist.append(base_objects.Interaction({ 'id': 7, 'particles': base_objects.ParticleList(\ [antid,d,Zp]), 'color': [], 'lorentz': ['FFV1'], 'couplings': {(0, 0): 'GC_7'}, 'orders': {'QED': 1} })) myinterlist.append(base_objects.Interaction({ 'id': 8, 'particles': base_objects.ParticleList(\ [n1,n1,Zp]), 'color': [], 'lorentz': ['FFV2'], 'couplings': {(0, 0): 'GC_22'}, 'orders': {'QED': 1} })) myinterlist.append(base_objects.Interaction({ 'id': 9, 'particles': base_objects.ParticleList(\ [eplus,n1,Wminus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_46'}, 'orders': {'QED': 1} })) myinterlist.append(base_objects.Interaction({ 'id': 10, 'particles': base_objects.ParticleList(\ [n1,eminus,Wplus]), 'color': [], 'lorentz': ['FFV3'], 'couplings': {(0, 0): 'GC_46'}, 'orders': {'QED': 1} })) myinterlist.append(base_objects.Interaction({ 'id': 11, 'particles': base_objects.ParticleList(\ [antit,c,Zp]), 'color': [], 'lorentz': ['FFV4'], 'couplings': {(0, 0): 'GC_50'}, 'orders': {'QED': 1} })) myinterlist.append(base_objects.Interaction({ 'id': 12, 'particles': base_objects.ParticleList(\ [antic,t,Zp]), 'color': [], 'lorentz': ['FFV4'], 'couplings': {(0, 0): 'GC_50'}, 'orders': {'QED': 1} })) mymodel = base_objects.Model() mymodel.set('particles', mypartlist) mymodel.set('interactions', myinterlist) mymodel.set('name', 'sm') # Multiparticle labels ds = [1,-1] qs = [1,3,2,4,-1,-3,-2,-4] my_leglist = base_objects.MultiLegList() my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) core_process = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1proc1 = [[n1.get('pdg_code')], [11], [24]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay1proc1]) my_leglist[0].set('state', False) decay1process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc1 = [[24], qs, qs] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc1]) my_leglist[0].set('state', False) decay2process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc2 = [[24], [6], [-5]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc2]) my_leglist[0].set('state', False) decay2process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process1.get('decay_chains').append(decay2process1) decay1process2.get('decay_chains').append(decay2process2) core_process.get('decay_chains').append(decay1process1) core_process.get('decay_chains').append(decay1process2) my_amplitude = diagram_generation.DecayChainAmplitude(core_process) dc_subproc_group = group_subprocs.DecayChainSubProcessGroup.\ group_amplitudes(\ diagram_generation.DecayChainAmplitudeList([my_amplitude])) subproc_groups = \ dc_subproc_group.generate_helas_decay_chain_subproc_groups() self.assertEqual(len(subproc_groups), 1) self.assertEqual(len(subproc_groups[0].get('matrix_elements')),2) me_strings = ["""Process: d d~ > ~n1 ~n1 WEIGHTED<=2 Decay: ~n1 > e- W+ WEIGHTED<=1 Decay: W+ > u d~ WEIGHTED<=1 Decay: ~n1 > e- W+ WEIGHTED<=1 Decay: W+ > t b~ WEIGHTED<=1""", """Process: d~ d > ~n1 ~n1 WEIGHTED<=2 Decay: ~n1 > e- W+ WEIGHTED<=1 Decay: W+ > u d~ WEIGHTED<=1 Decay: ~n1 > e- W+ WEIGHTED<=1 Decay: W+ > t b~ WEIGHTED<=1"""] for i,me in enumerate(subproc_groups[0].get('matrix_elements')): self.assertEqual(me.get('processes')[0].nice_string(), me_strings[i]) # Now test also for different process ids ds = [1,-1] qs = [1,3,2,4,-1,-3,-2,-4] # First process my_leglist = base_objects.MultiLegList() my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) core_process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel, 'id': 1}) decay1proc1 = [[n1.get('pdg_code')], [11], [24]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay1proc1]) my_leglist[0].set('state', False) decay1process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc1 = [[24], qs, qs] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc1]) my_leglist[0].set('state', False) decay2process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc2 = [[24], [6], [-5]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc2]) my_leglist[0].set('state', False) decay2process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process1.get('decay_chains').append(decay2process1) decay1process2.get('decay_chains').append(decay2process2) core_process1.get('decay_chains').append(decay1process1) core_process1.get('decay_chains').append(decay1process2) my_amplitude1 = diagram_generation.DecayChainAmplitude(core_process1) # Second process my_leglist = base_objects.MultiLegList() my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': ds, 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) my_leglist.append(base_objects.MultiLeg({'ids': [n1.get('pdg_code')]})) core_process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel, 'id': 2}) decay1proc1 = [[n1.get('pdg_code')], [11], [24]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay1proc1]) my_leglist[0].set('state', False) decay1process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc1 = [[24], [6], [-5]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc1]) my_leglist[0].set('state', False) decay2process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay2proc2 = [[24], [6], [-5]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay2proc2]) my_leglist[0].set('state', False) decay2process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1process1.get('decay_chains').append(decay2process1) decay1process2.get('decay_chains').append(decay2process2) core_process2.get('decay_chains').append(decay1process1) core_process2.get('decay_chains').append(decay1process2) my_amplitude2 = diagram_generation.DecayChainAmplitude(core_process2) dc_subproc_group = group_subprocs.DecayChainSubProcessGroup.\ group_amplitudes(\ diagram_generation.DecayChainAmplitudeList([my_amplitude1, my_amplitude2])) subproc_groups = \ dc_subproc_group.generate_helas_decay_chain_subproc_groups() self.assertEqual(len(subproc_groups), 2) self.assertEqual(len(subproc_groups[0].get('matrix_elements')),2) self.assertEqual(len(subproc_groups[1].get('matrix_elements')),2) def test_single_decay_combinations(self): """Test combination of single decay of t and t~: b b~ > t t~, t > c d d~ and b b~ > t t~, t~ > c~ d d~""" mypartlist = base_objects.ParticleList() myinterlist = base_objects.InteractionList() # A gluon mypartlist.append(base_objects.Particle({'name':'g', 'antiname':'g', 'spin':3, 'color':8, 'mass':'zero', 'width':'zero', 'texname':'g', 'antitexname':'g', 'line':'curly', 'charge':0., 'pdg_code':21, 'propagating':True, 'is_part':True, 'self_antipart':True})) g = mypartlist[-1] # A quark U and its antiparticle mypartlist.append(base_objects.Particle({'name':'u', 'antiname':'u~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'u', 'antitexname':'\bar u', 'line':'straight', 'charge':2. / 3., 'pdg_code':2, 'propagating':True, 'is_part':True, 'self_antipart':False})) u = mypartlist[-1] antiu = copy.copy(u) antiu.set('is_part', False) # A quark D and its antiparticle mypartlist.append(base_objects.Particle({'name':'d', 'antiname':'d~', 'spin':2, 'color':3, 'mass':'zero', 'width':'zero', 'texname':'d', 'antitexname':'\bar d', 'line':'straight', 'charge':-1. / 3., 'pdg_code':1, 'propagating':True, 'is_part':True, 'self_antipart':False})) d = mypartlist[-1] antid = copy.copy(d) antid.set('is_part', False) # A top quark and its antiparticle mypartlist.append(base_objects.Particle({'name':'t', 'antiname':'t~', 'spin':2, 'color':3, 'mass':'MT', 'width':'zero', 'texname':'t', 'antitexname':'\bar t', 'line':'straight', 'charge':2. / 3., 'pdg_code':6, 'propagating':True, 'is_part':True, 'self_antipart':False})) t = mypartlist[len(mypartlist) - 1] antit = copy.copy(t) antit.set('is_part', False) # A electron and positron mypartlist.append(base_objects.Particle({'name':'e-', 'antiname':'e+', 'spin':2, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'e^-', 'antitexname':'e^+', 'line':'straight', 'charge':-1., 'pdg_code':11, 'propagating':True, 'is_part':True, 'self_antipart':False})) eminus = mypartlist[-1] eplus = copy.copy(eminus) eplus.set('is_part', False) # A photon mypartlist.append(base_objects.Particle({'name':'a', 'antiname':'a', 'spin':3, 'color':1, 'mass':'zero', 'width':'zero', 'texname':'\gamma', 'antitexname':'\gamma', 'line':'wavy', 'charge':0., 'pdg_code':22, 'propagating':True, 'is_part':True, 'self_antipart':True})) a = mypartlist[-1] # A Z mypartlist.append(base_objects.Particle({'name':'z', 'antiname':'z', 'spin':3, 'color':1, 'mass':'MZ', 'width':'WZ', 'texname':'Z', 'antitexname':'Z', 'line':'wavy', 'charge':0., 'pdg_code':23, 'propagating':True, 'is_part':True, 'self_antipart':True})) z = mypartlist[-1] # 3 gluon vertiex myinterlist.append(base_objects.Interaction({ 'id': 1, 'particles': base_objects.ParticleList(\ [g] * 3), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'G'}, 'orders':{'QCD':1}})) # 4 gluon vertex myinterlist.append(base_objects.Interaction({ 'id': 2, 'particles': base_objects.ParticleList(\ [g] * 4), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'G^2'}, 'orders':{'QCD':2}})) # Gluon and photon couplings to quarks myinterlist.append(base_objects.Interaction({ 'id': 3, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 4, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 5, 'particles': base_objects.ParticleList(\ [d, \ antid, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 6, 'particles': base_objects.ParticleList(\ [antit, \ t, \ g]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQQ'}, 'orders':{'QCD':1}})) myinterlist.append(base_objects.Interaction({ 'id': 7, 'particles': base_objects.ParticleList(\ [d, \ antid, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) # Coupling of e to gamma myinterlist.append(base_objects.Interaction({ 'id': 8, 'particles': base_objects.ParticleList(\ [eminus, \ eplus, \ a]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) # Coupling of Z to quarks and electrons myinterlist.append(base_objects.Interaction({ 'id': 9, 'particles': base_objects.ParticleList(\ [u, \ antiu, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 10, 'particles': base_objects.ParticleList(\ [d, \ antid, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 11, 'particles': base_objects.ParticleList(\ [eplus, \ eminus, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GQED'}, 'orders':{'QED':1}})) # FCNC coupling myinterlist.append(base_objects.Interaction({ 'id': 12, 'particles': base_objects.ParticleList(\ [antit, \ u, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GFCNC'}, 'orders':{'QED':1}})) myinterlist.append(base_objects.Interaction({ 'id': 13, 'particles': base_objects.ParticleList(\ [antiu, \ t, \ z]), 'color': [], 'lorentz':['L1'], 'couplings':{(0, 0):'GFCNC'}, 'orders':{'QED':1}})) mymodel = base_objects.Model() mymodel.set('particles', mypartlist) mymodel.set('interactions', myinterlist) mymodel.set('name', 'sm') # d d~ > t t~, t > u Z my_leglist = base_objects.MultiLegList() my_leglist.append(base_objects.MultiLeg({'ids': [1], 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [-1], 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [6]})) my_leglist.append(base_objects.MultiLeg({'ids': [-6]})) core_process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1proc1 = [[6], [2], [23]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay1proc1]) my_leglist[0].set('state', False) decay1process1 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) core_process1.get('decay_chains').append(decay1process1) my_amplitude1 = diagram_generation.DecayChainAmplitude(core_process1) # d d~ > t t~, t~ > u~ Z my_leglist = base_objects.MultiLegList() my_leglist.append(base_objects.MultiLeg({'ids': [1], 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [-1], 'state': False})) my_leglist.append(base_objects.MultiLeg({'ids': [6]})) my_leglist.append(base_objects.MultiLeg({'ids': [-6]})) core_process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) decay1proc2 = [[-6], [-2], [23]] my_leglist = base_objects.MultiLegList([\ base_objects.MultiLeg({'ids': id}) for id in decay1proc2]) my_leglist[0].set('state', False) decay1process2 = base_objects.ProcessDefinition({'legs':my_leglist, 'model':mymodel}) core_process2.get('decay_chains').append(decay1process2) my_amplitude2 = diagram_generation.DecayChainAmplitude(core_process2) dc_subproc_group = group_subprocs.DecayChainSubProcessGroup.\ group_amplitudes(\ diagram_generation.DecayChainAmplitudeList([my_amplitude1, my_amplitude2])) subproc_groups = \ dc_subproc_group.generate_helas_decay_chain_subproc_groups() self.assertEqual(len(subproc_groups), 2) self.assertEqual(len(subproc_groups[0].get('matrix_elements')),1) me_strings = ["""Process: d d~ > t t~ WEIGHTED<=2 Decay: t > u z WEIGHTED<=2""", """Process: d d~ > t t~ WEIGHTED<=2 Decay: t~ > u~ z WEIGHTED<=2"""] for i, group in enumerate(subproc_groups): self.assertEqual(group.get('matrix_elements')[0].\ get('processes')[0].nice_string(), me_strings[i])

44.352252

1,507

0.411322

7,511

71,895

3.83158

0.049927

0.081796

0.052573

0.03989

0.8403

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0.787797

0.768199

0.750096

0.716912

0

0.096976

0.427721

71,895

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1,508

44.37963

0.602494

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0.005627

false

0.001608

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0.019293

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null

0

1

0

1

0

1

0

null

0

8

70f645e712a2ce2a7d19f08614547b232c99b11d

345

py

Python

central/__init__.py

Mitsj0l/SDbranch-lab

cab76c9c06d63828dee791d050e5d2ef660089aa

[ "MIT" ]

2

2021-12-10T02:53:54.000Z

2021-12-17T12:34:38.000Z

central/__init__.py

Mitsj0l/SDbranch-lab

cab76c9c06d63828dee791d050e5d2ef660089aa

[ "MIT" ]

null

central/__init__.py

Mitsj0l/SDbranch-lab

cab76c9c06d63828dee791d050e5d2ef660089aa

[ "MIT" ]

1

2020-11-26T13:01:27.000Z

import central.authentication.central_auth import central.authentication.central_frontend_auth import central.authentication.database import central.authentication.check_config import central.configuration.VGW_Deployment import central.configuration.configuration_device_fix import central.configuration.sites import central.configuration.labels

43.125

53

0.910145

39

345

7.871795

0.384615

0.338762

0.351792

0.221498

0

0.043478

345

8

54

43.125

0.930303

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

cb093769b9429c1caee1aab2f12f43cff5265415

107

py

Python

ui/__init__.py

Darkblader24/material-combiner-addon

ff76134e904fc7543ea18cd6ca82c12a39bdafa9

[ "MIT" ]

192

2018-08-21T21:57:45.000Z

2022-03-31T14:37:54.000Z

ui/__init__.py

vinhowe/material-combiner-addon

2087d7f8dd35e5824d56aed70ad989fd48f224cb

[ "MIT" ]

34

2018-08-21T10:20:00.000Z

2022-03-22T19:54:47.000Z

ui/__init__.py

vinhowe/material-combiner-addon

2087d7f8dd35e5824d56aed70ad989fd48f224cb

[ "MIT" ]

30

2018-08-21T08:39:03.000Z

2022-03-28T00:36:07.000Z

from . import credits_menu from . import main_menu from . import properties_menu from . import update_menu

21.4

29

0.813084

16

107

5.1875

0.4375

0.481928

0.506024

0

0.149533

107

4

30

26.75

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0

1

0

true

0

1

0

1

0

1

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null

1

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1

0

null

0

1

0

1

0

1

0

7

cb2cfaae6307cce721d693b337827875c2b5cc2c

76

py

Python

peach/__init__.py

iesl/KISP

2c8ffacc36abcefc86b6d19dcdd49213241c6ff8

[ "MIT" ]

null

peach/__init__.py

iesl/KISP

2c8ffacc36abcefc86b6d19dcdd49213241c6ff8

[ "MIT" ]

null

peach/__init__.py

iesl/KISP

2c8ffacc36abcefc86b6d19dcdd49213241c6ff8

[ "MIT" ]

null

from peach import utils from peach import tf_nn from peach import bert

15.2

24

0.776316

13

76

4.461538

0.538462

0.465517

0.775862

0

0.223684

76

4

25

19

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0

true

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1

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1

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null

0

1

0

1

0

1

0

7

cb85d33f82671ae2d2a687aa0e825c1585d4b9fe

134,695

py

Python

exportacao/views.py

bcunhasa/nutriodonto

3ff20377bc85bc4960619f63688b7732e6eebba9

[ "CC0-1.0" ]

null

exportacao/views.py

bcunhasa/nutriodonto

3ff20377bc85bc4960619f63688b7732e6eebba9

[ "CC0-1.0" ]

null

exportacao/views.py

bcunhasa/nutriodonto

3ff20377bc85bc4960619f63688b7732e6eebba9

[ "CC0-1.0" ]

null

from django.contrib.auth.mixins import LoginRequiredMixin from django.http import HttpResponse from django.urls import reverse from django.shortcuts import render from django.views import View import csv from administracao.models import * from administracao.const import * class LoginRequired(LoginRequiredMixin): """Configurações para o login""" login_url = 'administracao/login/' redirect_field_name = 'next' class ExportacaoView(LoginRequired, View): """Permite a exportacao de dados do banco""" def get(self, request): context = { 'pagina_exportacao': True, } return render(self.request, 'exportacao/exportacao.html', context) class DownloadCompletoView(LoginRequired, View): """Gera e envia o arquivo csv para a base completa""" def get(self, request): alunos = Aluno.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="base.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['campanha.nome', 'acao.nome', 'escola.id', 'escola.nome', 'escola.latitude', 'escola.longitude', 'aluno.numero_identificacao', 'aluno.periodo', 'aluno.turma', 'aluno.nascimento', 'aluno.sexo', 'aluno.raca', 'diretor.data', 'diretor.questao_1', 'diretor.questao_2', 'diretor.questao_3', 'diretor.questao_4', 'diretor.questao_5', 'diretor.questao_6', 'diretor.questao_7', 'diretor.questao_8', 'diretor.questao_9', 'diretor.questao_10', 'diretor.questao_11', 'diretor.questao_12', 'diretor.questao_13', 'diretor.questao_14', 'diretor.questao_15', 'diretor.questao_16', 'diretor.questao_17', 'diretor.questao_18', 'diretor.questao_19', 'diretor.questao_20', 'diretor.questao_21', 'diretor.questao_22', 'diretor.questao_23', 'diretor.questao_24', 'diretor.questao_25', 'diretor.questao_26', 'diretor.questao_27', 'diretor.questao_28', 'diretor.questao_29', 'diretor.questao_30', 'diretor.questao_31', 'diretor.questao_32', 'diretor.questao_33', 'diretor.questao_34', 'diretor.questao_35', 'diretor.questao_36', 'diretor.questao_37', 'diretor.questao_38', 'diretor.questao_39', 'diretor.questao_40', 'diretor.questao_41', 'diretor.questao_42', 'diretor.questao_43', 'diretor.questao_44', 'diretor.questao_45', 'diretor.questao_46', 'diretor.questao_47', 'diretor.questao_48', 'diretor.questao_49', 'diretor.questao_50', 'diretor.questao_51', 'diretor.questao_52', 'diretor.questao_53', 'diretor.questao_54', 'diretor.questao_55', 'diretor.questao_56', 'diretor.questao_57', 'diretor.questao_58', 'diretor.questao_59', 'diretor.questao_60', 'diretor.questao_61', 'diretor.questao_62', 'diretor.questao_63', 'diretor.questao_64', 'diretor.questao_65', 'diretor.questao_66', 'diretor.questao_67', 'diretor.questao_68', 'diretor.questao_69', 'diretor.questao_70', 'diretor.questao_71', 'diretor.questao_72', 'diretor.questao_73', 'diretor.questao_74', 'diretor.questao_75', 'diretor.questao_76', 'diretor.questao_77', 'diretor.questao_78', 'diretor.questao_79', 'diretor.questao_80', 'diretor.questao_81', 'diretor.questao_82', 'diretor.questao_83', 'diretor.questao_84', 'questionario.data', 'questionario.questao_1', 'questionario.questao_2', 'questionario.questao_3', 'questionario.questao_4', 'questionario.questao_5', 'questionario.questao_6', 'questionario.questao_7', 'questionario.questao_8', 'questionario.questao_9', 'questionario.questao_10', 'questionario.questao_11', 'questionario.questao_12', 'questionario.questao_13', 'questionario.questao_14', 'questionario.questao_15', 'questionario.questao_16', 'questionario.questao_17', 'questionario.questao_18', 'questionario.questao_19', 'questionario.questao_20', 'questionario.questao_21', 'questionario.questao_22', 'questionario.questao_23', 'questionario.questao_24', 'questionario.questao_25', 'questionario.questao_26', 'questionario.questao_27', 'questionario.questao_28', 'questionario.questao_29', 'questionario.questao_30', 'questionario.questao_31', 'questionario.questao_32', 'questionario.questao_33', 'questionario.questao_34', 'questionario.questao_35', 'questionario.questao_36', 'questionario.questao_37', 'questionario.questao_38', 'questionario.questao_39', 'questionario.questao_40', 'questionario.questao_41', 'questionario.questao_42', 'questionario.questao_43', 'questionario.questao_44', 'questionario.questao_45', 'questionario.questao_46', 'questionario.questao_47', 'questionario.questao_48', 'questionario.questao_49', 'questionario.questao_50', 'questionario.questao_51', 'questionario.questao_52', 'questionario.questao_53', 'questionario.questao_54', 'questionario.questao_55', 'questionario.questao_56', 'questionario.questao_57', 'questionario.questao_58', 'questionario.questao_59', 'questionario.questao_60', 'questionario.questao_61', 'questionario.questao_62', 'questionario.questao_63', 'questionario.questao_64', 'questionario.questao_65', 'questionario.questao_66', 'questionario.questao_67', 'questionario.questao_68', 'questionario.questao_69', 'questionario.questao_70', 'questionario.questao_71', 'questionario.questao_72', 'questionario.questao_73', 'questionario.questao_74', 'questionario.questao_75', 'questionario.questao_76', 'questionario.questao_77', 'questionario.questao_78', 'questionario.questao_79', 'questionario.questao_80', 'questionario.questao_81', 'questionario.questao_82', 'questionario.questao_83', 'questionario.questao_84', 'questionario.questao_85', 'questionario.questao_86', 'questionario.questao_87', 'questionario.questao_88', 'questionario.questao_89', 'questionario.questao_90', 'questionario.questao_91', 'questionario.questao_92', 'questionario.questao_93', 'questionario.questao_94', 'questionario.questao_95', 'questionario.questao_96', 'questionario.questao_97', 'questionario.questao_98', 'questionario.questao_99', 'questionario.questao_100', 'questionario.questao_101', 'questionario.questao_102', 'questionario.questao_103', 'questionario.questao_104', 'questionario.questao_105', 'questionario.questao_106', 'questionario.questao_107', 'questionario.questao_108', 'questionario.questao_109', 'questionario.questao_110', 'questionario.questao_111', 'questionario.questao_112', 'questionario.questao_113', 'questionario.questao_114', 'questionario.questao_115', 'questionario.questao_116', 'questionario.questao_117', 'questionario.questao_118', 'questionario.questao_119', 'questionario.questao_120', 'questionario.questao_121', 'questionario.questao_122', 'questionario.questao_123', 'questionario.questao_124', 'questionario.questao_125', 'questionario.questao_126', 'questionario.questao_127', 'questionario.questao_128', 'questionario.questao_129', 'questionario.questao_130', 'questionario.questao_131', 'questionario.questao_132', 'questionario.questao_133', 'questionario.questao_134', 'questionario.questao_135', 'questionario.questao_136', 'questionario.questao_137', 'questionario.questao_138', 'questionario.questao_139', 'questionario.questao_140', 'questionario.questao_141', 'questionario.questao_142', 'questionario.questao_143', 'questionario.questao_144', 'questionario.questao_145', 'questionario.questao_146', 'exame.data', 'exame.examinador', 'exame.anotador', 'exame.carie_coroa_18', 'exame.carie_tratamento_18', 'exame.carie_coroa_17', 'exame.carie_tratamento_17', 'exame.carie_coroa_16', 'exame.carie_tratamento_16', 'exame.carie_coroa_15', 'exame.carie_tratamento_15', 'exame.carie_coroa_14', 'exame.carie_tratamento_14', 'exame.carie_coroa_13', 'exame.carie_tratamento_13', 'exame.carie_coroa_12', 'exame.carie_tratamento_12', 'exame.carie_coroa_11', 'exame.carie_tratamento_11', 'exame.carie_coroa_21', 'exame.carie_tratamento_21', 'exame.carie_coroa_22', 'exame.carie_tratamento_22', 'exame.carie_coroa_23', 'exame.carie_tratamento_23', 'exame.carie_coroa_24', 'exame.carie_tratamento_24', 'exame.carie_coroa_25', 'exame.carie_tratamento_25', 'exame.carie_coroa_26', 'exame.carie_tratamento_26', 'exame.carie_coroa_27', 'exame.carie_tratamento_27', 'exame.carie_coroa_28', 'exame.carie_tratamento_28', 'exame.carie_coroa_38', 'exame.carie_tratamento_38', 'exame.carie_coroa_37', 'exame.carie_tratamento_37', 'exame.carie_coroa_36', 'exame.carie_tratamento_36', 'exame.carie_coroa_35', 'exame.carie_tratamento_35', 'exame.carie_coroa_34', 'exame.carie_tratamento_34', 'exame.carie_coroa_33', 'exame.carie_tratamento_33', 'exame.carie_coroa_32', 'exame.carie_tratamento_32', 'exame.carie_coroa_31', 'exame.carie_tratamento_31', 'exame.carie_coroa_41', 'exame.carie_tratamento_41', 'exame.carie_coroa_42', 'exame.carie_tratamento_42', 'exame.carie_coroa_43', 'exame.carie_tratamento_43', 'exame.carie_coroa_44', 'exame.carie_tratamento_44', 'exame.carie_coroa_45', 'exame.carie_tratamento_45', 'exame.carie_coroa_46', 'exame.carie_tratamento_46', 'exame.carie_coroa_47', 'exame.carie_tratamento_47', 'exame.carie_coroa_48', 'exame.carie_tratamento_48', 'exame.periodontal_sangramento_1716', 'exame.periodontal_calculo_1716', 'exame.periodontal_bolsa_1716', 'exame.periodontal_sangramento_11', 'exame.periodontal_calculo_11', 'exame.periodontal_bolsa_11', 'exame.periodontal_sangramento_2627', 'exame.periodontal_calculo_2627', 'exame.periodontal_bolsa_2627', 'exame.periodontal_sangramento_3736', 'exame.periodontal_calculo_3736', 'exame.periodontal_bolsa_3736', 'exame.periodontal_sangramento_31', 'exame.periodontal_calculo_31', 'exame.periodontal_bolsa_31', 'exame.periodontal_sangramento_4647', 'exame.periodontal_calculo_4647', 'exame.periodontal_bolsa_4647', 'cpod',]) for aluno in alunos: diretor = Diretor.objects.get(escola_id=aluno.escola_id) resultados = { "cpod": 0, } try: exame = Exame.objects.get(aluno_id=aluno.id) # cálculo do cpo-d if exame.carie_coroa_18 == '1': resultados["cpod"] += 1 if exame.carie_coroa_18 == '2': resultados["cpod"] += 1 if exame.carie_coroa_18 == '3': resultados["cpod"] += 1 if exame.carie_coroa_18 == '4': resultados["cpod"] += 1 if exame.carie_coroa_18 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_18 == '6': resultados["cpod"] += 1 if exame.carie_coroa_17 == '1': resultados["cpod"] += 1 if exame.carie_coroa_17 == '2': resultados["cpod"] += 1 if exame.carie_coroa_17 == '3': resultados["cpod"] += 1 if exame.carie_coroa_17 == '4': resultados["cpod"] += 1 if exame.carie_coroa_17 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_17 == '6': resultados["cpod"] += 1 if exame.carie_coroa_16 == '1': resultados["cpod"] += 1 if exame.carie_coroa_16 == '2': resultados["cpod"] += 1 if exame.carie_coroa_16 == '3': resultados["cpod"] += 1 if exame.carie_coroa_16 == '4': resultados["cpod"] += 1 if exame.carie_coroa_16 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_16 == '6': resultados["cpod"] += 1 if exame.carie_coroa_15 == '1': resultados["cpod"] += 1 if exame.carie_coroa_15 == '2': resultados["cpod"] += 1 if exame.carie_coroa_15 == '3': resultados["cpod"] += 1 if exame.carie_coroa_15 == '4': resultados["cpod"] += 1 if exame.carie_coroa_15 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_15 == '6': resultados["cpod"] += 1 if exame.carie_coroa_14 == '1': resultados["cpod"] += 1 if exame.carie_coroa_14 == '2': resultados["cpod"] += 1 if exame.carie_coroa_14 == '3': resultados["cpod"] += 1 if exame.carie_coroa_14 == '4': resultados["cpod"] += 1 if exame.carie_coroa_14 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_14 == '6': resultados["cpod"] += 1 if exame.carie_coroa_13 == '1': resultados["cpod"] += 1 if exame.carie_coroa_13 == '2': resultados["cpod"] += 1 if exame.carie_coroa_13 == '3': resultados["cpod"] += 1 if exame.carie_coroa_13 == '4': resultados["cpod"] += 1 if exame.carie_coroa_13 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_13 == '6': resultados["cpod"] += 1 if exame.carie_coroa_12 == '1': resultados["cpod"] += 1 if exame.carie_coroa_12 == '2': resultados["cpod"] += 1 if exame.carie_coroa_12 == '3': resultados["cpod"] += 1 if exame.carie_coroa_12 == '4': resultados["cpod"] += 1 if exame.carie_coroa_12 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_12 == '6': resultados["cpod"] += 1 if exame.carie_coroa_11 == '1': resultados["cpod"] += 1 if exame.carie_coroa_11 == '2': resultados["cpod"] += 1 if exame.carie_coroa_11 == '3': resultados["cpod"] += 1 if exame.carie_coroa_11 == '4': resultados["cpod"] += 1 if exame.carie_coroa_11 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_11 == '6': resultados["cpod"] += 1 if exame.carie_coroa_21 == '1': resultados["cpod"] += 1 if exame.carie_coroa_21 == '2': resultados["cpod"] += 1 if exame.carie_coroa_21 == '3': resultados["cpod"] += 1 if exame.carie_coroa_21 == '4': resultados["cpod"] += 1 if exame.carie_coroa_21 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_21 == '6': resultados["cpod"] += 1 if exame.carie_coroa_22 == '1': resultados["cpod"] += 1 if exame.carie_coroa_22 == '2': resultados["cpod"] += 1 if exame.carie_coroa_22 == '3': resultados["cpod"] += 1 if exame.carie_coroa_22 == '4': resultados["cpod"] += 1 if exame.carie_coroa_22 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_22 == '6': resultados["cpod"] += 1 if exame.carie_coroa_23 == '1': resultados["cpod"] += 1 if exame.carie_coroa_23 == '2': resultados["cpod"] += 1 if exame.carie_coroa_23 == '3': resultados["cpod"] += 1 if exame.carie_coroa_23 == '4': resultados["cpod"] += 1 if exame.carie_coroa_23 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_23 == '6': resultados["cpod"] += 1 if exame.carie_coroa_24 == '1': resultados["cpod"] += 1 if exame.carie_coroa_24 == '2': resultados["cpod"] += 1 if exame.carie_coroa_24 == '3': resultados["cpod"] += 1 if exame.carie_coroa_24 == '4': resultados["cpod"] += 1 if exame.carie_coroa_24 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_24 == '6': resultados["cpod"] += 1 if exame.carie_coroa_25 == '1': resultados["cpod"] += 1 if exame.carie_coroa_25 == '2': resultados["cpod"] += 1 if exame.carie_coroa_25 == '3': resultados["cpod"] += 1 if exame.carie_coroa_25 == '4': resultados["cpod"] += 1 if exame.carie_coroa_25 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_25 == '6': resultados["cpod"] += 1 if exame.carie_coroa_26 == '1': resultados["cpod"] += 1 if exame.carie_coroa_26 == '2': resultados["cpod"] += 1 if exame.carie_coroa_26 == '3': resultados["cpod"] += 1 if exame.carie_coroa_26 == '4': resultados["cpod"] += 1 if exame.carie_coroa_26 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_26 == '6': resultados["cpod"] += 1 if exame.carie_coroa_27 == '1': resultados["cpod"] += 1 if exame.carie_coroa_27 == '2': resultados["cpod"] += 1 if exame.carie_coroa_27 == '3': resultados["cpod"] += 1 if exame.carie_coroa_27 == '4': resultados["cpod"] += 1 if exame.carie_coroa_27 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_27 == '6': resultados["cpod"] += 1 if exame.carie_coroa_28 == '1': resultados["cpod"] += 1 if exame.carie_coroa_28 == '2': resultados["cpod"] += 1 if exame.carie_coroa_28 == '3': resultados["cpod"] += 1 if exame.carie_coroa_28 == '4': resultados["cpod"] += 1 if exame.carie_coroa_28 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_28 == '6': resultados["cpod"] += 1 if exame.carie_coroa_38 == '1': resultados["cpod"] += 1 if exame.carie_coroa_38 == '2': resultados["cpod"] += 1 if exame.carie_coroa_38 == '3': resultados["cpod"] += 1 if exame.carie_coroa_38 == '4': resultados["cpod"] += 1 if exame.carie_coroa_38 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_38 == '6': resultados["cpod"] += 1 if exame.carie_coroa_37 == '1': resultados["cpod"] += 1 if exame.carie_coroa_37 == '2': resultados["cpod"] += 1 if exame.carie_coroa_37 == '3': resultados["cpod"] += 1 if exame.carie_coroa_37 == '4': resultados["cpod"] += 1 if exame.carie_coroa_37 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_37 == '6': resultados["cpod"] += 1 if exame.carie_coroa_36 == '1': resultados["cpod"] += 1 if exame.carie_coroa_36 == '2': resultados["cpod"] += 1 if exame.carie_coroa_36 == '3': resultados["cpod"] += 1 if exame.carie_coroa_36 == '4': resultados["cpod"] += 1 if exame.carie_coroa_36 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_36 == '6': resultados["cpod"] += 1 if exame.carie_coroa_35 == '1': resultados["cpod"] += 1 if exame.carie_coroa_35 == '2': resultados["cpod"] += 1 if exame.carie_coroa_35 == '3': resultados["cpod"] += 1 if exame.carie_coroa_35 == '4': resultados["cpod"] += 1 if exame.carie_coroa_35 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_35 == '6': resultados["cpod"] += 1 if exame.carie_coroa_34 == '1': resultados["cpod"] += 1 if exame.carie_coroa_34 == '2': resultados["cpod"] += 1 if exame.carie_coroa_34 == '3': resultados["cpod"] += 1 if exame.carie_coroa_34 == '4': resultados["cpod"] += 1 if exame.carie_coroa_34 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_34 == '6': resultados["cpod"] += 1 if exame.carie_coroa_33 == '1': resultados["cpod"] += 1 if exame.carie_coroa_33 == '2': resultados["cpod"] += 1 if exame.carie_coroa_33 == '3': resultados["cpod"] += 1 if exame.carie_coroa_33 == '4': resultados["cpod"] += 1 if exame.carie_coroa_33 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_33 == '6': resultados["cpod"] += 1 if exame.carie_coroa_32 == '1': resultados["cpod"] += 1 if exame.carie_coroa_32 == '2': resultados["cpod"] += 1 if exame.carie_coroa_32 == '3': resultados["cpod"] += 1 if exame.carie_coroa_32 == '4': resultados["cpod"] += 1 if exame.carie_coroa_32 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_32 == '6': resultados["cpod"] += 1 if exame.carie_coroa_31 == '1': resultados["cpod"] += 1 if exame.carie_coroa_31 == '2': resultados["cpod"] += 1 if exame.carie_coroa_31 == '3': resultados["cpod"] += 1 if exame.carie_coroa_31 == '4': resultados["cpod"] += 1 if exame.carie_coroa_31 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_31 == '6': resultados["cpod"] += 1 if exame.carie_coroa_41 == '1': resultados["cpod"] += 1 if exame.carie_coroa_41 == '2': resultados["cpod"] += 1 if exame.carie_coroa_41 == '3': resultados["cpod"] += 1 if exame.carie_coroa_41 == '4': resultados["cpod"] += 1 if exame.carie_coroa_41 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_41 == '6': resultados["cpod"] += 1 if exame.carie_coroa_42 == '1': resultados["cpod"] += 1 if exame.carie_coroa_42 == '2': resultados["cpod"] += 1 if exame.carie_coroa_42 == '3': resultados["cpod"] += 1 if exame.carie_coroa_42 == '4': resultados["cpod"] += 1 if exame.carie_coroa_42 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_42 == '6': resultados["cpod"] += 1 if exame.carie_coroa_43 == '1': resultados["cpod"] += 1 if exame.carie_coroa_43 == '2': resultados["cpod"] += 1 if exame.carie_coroa_43 == '3': resultados["cpod"] += 1 if exame.carie_coroa_43 == '4': resultados["cpod"] += 1 if exame.carie_coroa_43 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_43 == '6': resultados["cpod"] += 1 if exame.carie_coroa_44 == '1': resultados["cpod"] += 1 if exame.carie_coroa_44 == '2': resultados["cpod"] += 1 if exame.carie_coroa_44 == '3': resultados["cpod"] += 1 if exame.carie_coroa_44 == '4': resultados["cpod"] += 1 if exame.carie_coroa_44 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_44 == '6': resultados["cpod"] += 1 if exame.carie_coroa_45 == '1': resultados["cpod"] += 1 if exame.carie_coroa_45 == '2': resultados["cpod"] += 1 if exame.carie_coroa_45 == '3': resultados["cpod"] += 1 if exame.carie_coroa_45 == '4': resultados["cpod"] += 1 if exame.carie_coroa_45 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_45 == '6': resultados["cpod"] += 1 if exame.carie_coroa_46 == '1': resultados["cpod"] += 1 if exame.carie_coroa_46 == '2': resultados["cpod"] += 1 if exame.carie_coroa_46 == '3': resultados["cpod"] += 1 if exame.carie_coroa_46 == '4': resultados["cpod"] += 1 if exame.carie_coroa_46 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_46 == '6': resultados["cpod"] += 1 if exame.carie_coroa_47 == '1': resultados["cpod"] += 1 if exame.carie_coroa_47 == '2': resultados["cpod"] += 1 if exame.carie_coroa_47 == '3': resultados["cpod"] += 1 if exame.carie_coroa_47 == '4': resultados["cpod"] += 1 if exame.carie_coroa_47 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_47 == '6': resultados["cpod"] += 1 if exame.carie_coroa_48 == '1': resultados["cpod"] += 1 if exame.carie_coroa_48 == '2': resultados["cpod"] += 1 if exame.carie_coroa_48 == '3': resultados["cpod"] += 1 if exame.carie_coroa_48 == '4': resultados["cpod"] += 1 if exame.carie_coroa_48 == '5': resultados["cpod"] += 1 if exame.carie_tratamento_48 == '6': resultados["cpod"] += 1 except: pass tem_questionario = True tem_exame = True try: questionario = Questionario.objects.get(aluno_id=aluno.id) except: tem_questionario = False try: exame = Exame.objects.get(aluno_id=aluno.id) except: tem_exame = False if not tem_questionario and tem_exame: writer.writerow([ aluno.escola.acao.campanha.nome, aluno.escola.acao.nome, aluno.escola.id, aluno.escola.nome, aluno.escola.latitude, aluno.escola.longitude, aluno.numero_identificacao, aluno.periodo, # get__display() aluno.turma, aluno.nascimento, aluno.sexo, # get__display() aluno.raca, # get__display() diretor.data, diretor.questao_1, diretor.questao_2, # get__display() diretor.questao_3, diretor.questao_4, # get__display() diretor.questao_5, # get__display() diretor.questao_6, # get__display() diretor.questao_7, # get__display() diretor.questao_8, # get__display() diretor.questao_9, # get__display() diretor.questao_10, # get__display() diretor.questao_11, # get__display() diretor.questao_12, # get__display() diretor.questao_13, # get__display() diretor.questao_14, # get__display() diretor.questao_15, # get__display() diretor.questao_16, # get__display() diretor.questao_17, # get__display() diretor.questao_18, # get__display() diretor.questao_19, # get__display() diretor.questao_20, # get__display() diretor.questao_21, # get__display() diretor.questao_22, # get__display() diretor.questao_23, # get__display() diretor.questao_24, # get__display() diretor.questao_25, # get__display() diretor.questao_26, # get__display() diretor.questao_27, # get__display() diretor.questao_28, diretor.questao_29, # get__display() diretor.questao_30, # get__display() diretor.questao_31, diretor.questao_32, # get__display() diretor.questao_33, diretor.questao_34, # get__display() diretor.questao_35, # get__display() diretor.questao_36, # get__display() diretor.questao_37, diretor.questao_38, # get__display() diretor.questao_39, diretor.questao_40, # get__display() diretor.questao_41, # get__display() diretor.questao_42, # get__display() diretor.questao_43, # get__display() diretor.questao_44, # get__display() diretor.questao_45, # get__display() diretor.questao_46, # get__display() diretor.questao_47, # get__display() diretor.questao_48, # get__display() diretor.questao_49, # get__display() diretor.questao_50, # get__display() diretor.questao_51, # get__display() diretor.questao_52, # get__display() diretor.questao_53, # get__display() diretor.questao_54, # get__display() diretor.questao_55, # get__display() diretor.questao_56, # get__display() diretor.questao_57, # get__display() diretor.questao_58, # get__display() diretor.questao_59, # get__display() diretor.questao_60, # get__display() diretor.questao_61, # get__display() diretor.questao_62, # get__display() diretor.questao_63, # get__display() diretor.questao_64, # get__display() diretor.questao_65, # get__display() diretor.questao_66, # get__display() diretor.questao_67, # get__display() diretor.questao_68, # get__display() diretor.questao_69, # get__display() diretor.questao_70, # get__display() diretor.questao_71, # get__display() diretor.questao_72, # get__display() diretor.questao_73, # get__display() diretor.questao_74, # get__display() diretor.questao_75, # get__display() diretor.questao_76, # get__display() diretor.questao_77, # get__display() diretor.questao_78, # get__display() diretor.questao_79, # get__display() diretor.questao_80, # get__display() diretor.questao_81, # get__display() diretor.questao_82, # get__display() diretor.questao_83, # get__display() diretor.questao_84, # get__display() None, None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, # get__display() None, exame.data, exame.examinador, exame.anotador, exame.carie_coroa_18, exame.carie_tratamento_18, exame.carie_coroa_17, exame.carie_tratamento_17, exame.carie_coroa_16, exame.carie_tratamento_16, exame.carie_coroa_15, exame.carie_tratamento_15, exame.carie_coroa_14, exame.carie_tratamento_14, exame.carie_coroa_13, exame.carie_tratamento_13, exame.carie_coroa_12, exame.carie_tratamento_12, exame.carie_coroa_11, exame.carie_tratamento_11, exame.carie_coroa_21, exame.carie_tratamento_21, exame.carie_coroa_22, exame.carie_tratamento_22, exame.carie_coroa_23, exame.carie_tratamento_23, exame.carie_coroa_24, exame.carie_tratamento_24, exame.carie_coroa_25, exame.carie_tratamento_25, exame.carie_coroa_26, exame.carie_tratamento_26, exame.carie_coroa_27, exame.carie_tratamento_27, exame.carie_coroa_28, exame.carie_tratamento_28, exame.carie_coroa_38, exame.carie_tratamento_38, exame.carie_coroa_37, exame.carie_tratamento_37, exame.carie_coroa_36, exame.carie_tratamento_36, exame.carie_coroa_35, exame.carie_tratamento_35, exame.carie_coroa_34, exame.carie_tratamento_34, exame.carie_coroa_33, exame.carie_tratamento_33, exame.carie_coroa_32, exame.carie_tratamento_32, exame.carie_coroa_31, exame.carie_tratamento_31, exame.carie_coroa_41, exame.carie_tratamento_41, exame.carie_coroa_42, exame.carie_tratamento_42, exame.carie_coroa_43, exame.carie_tratamento_43, exame.carie_coroa_44, exame.carie_tratamento_44, exame.carie_coroa_45, exame.carie_tratamento_45, exame.carie_coroa_46, exame.carie_tratamento_46, exame.carie_coroa_47, exame.carie_tratamento_47, exame.carie_coroa_48, exame.carie_tratamento_48, exame.periodontal_sangramento_1716, exame.periodontal_calculo_1716, exame.periodontal_bolsa_1716, exame.periodontal_sangramento_11, exame.periodontal_calculo_11, exame.periodontal_bolsa_11, exame.periodontal_sangramento_2627, exame.periodontal_calculo_2627, exame.periodontal_bolsa_2627, exame.periodontal_sangramento_3736, exame.periodontal_calculo_3736, exame.periodontal_bolsa_3736, exame.periodontal_sangramento_31, exame.periodontal_calculo_31, exame.periodontal_bolsa_31, exame.periodontal_sangramento_4647, exame.periodontal_calculo_4647, exame.periodontal_bolsa_4647, resultados["cpod"], ]) continue if tem_questionario and not tem_exame: writer.writerow([ aluno.escola.acao.campanha.nome, aluno.escola.acao.nome, aluno.escola.id, aluno.escola.nome, aluno.escola.latitude, aluno.escola.longitude, aluno.numero_identificacao, aluno.periodo, # get__display() aluno.turma, aluno.nascimento, aluno.sexo, # get__display() aluno.raca, # get__display() diretor.data, diretor.questao_1, diretor.questao_2, # get__display() diretor.questao_3, diretor.questao_4, # get__display() diretor.questao_5, # get__display() diretor.questao_6, # get__display() diretor.questao_7, # get__display() diretor.questao_8, # get__display() diretor.questao_9, # get__display() diretor.questao_10, # get__display() diretor.questao_11, # get__display() diretor.questao_12, # get__display() diretor.questao_13, # get__display() diretor.questao_14, # get__display() diretor.questao_15, # get__display() diretor.questao_16, # get__display() diretor.questao_17, # get__display() diretor.questao_18, # get__display() diretor.questao_19, # get__display() diretor.questao_20, # get__display() diretor.questao_21, # get__display() diretor.questao_22, # get__display() diretor.questao_23, # get__display() diretor.questao_24, # get__display() diretor.questao_25, # get__display() diretor.questao_26, # get__display() diretor.questao_27, # get__display() diretor.questao_28, diretor.questao_29, # get__display() diretor.questao_30, # get__display() diretor.questao_31, diretor.questao_32, # get__display() diretor.questao_33, diretor.questao_34, # get__display() diretor.questao_35, # get__display() diretor.questao_36, # get__display() diretor.questao_37, diretor.questao_38, # get__display() diretor.questao_39, diretor.questao_40, # get__display() diretor.questao_41, # get__display() diretor.questao_42, # get__display() diretor.questao_43, # get__display() diretor.questao_44, # get__display() diretor.questao_45, # get__display() diretor.questao_46, # get__display() diretor.questao_47, # get__display() diretor.questao_48, # get__display() diretor.questao_49, # get__display() diretor.questao_50, # get__display() diretor.questao_51, # get__display() diretor.questao_52, # get__display() diretor.questao_53, # get__display() diretor.questao_54, # get__display() diretor.questao_55, # get__display() diretor.questao_56, # get__display() diretor.questao_57, # get__display() diretor.questao_58, # get__display() diretor.questao_59, # get__display() diretor.questao_60, # get__display() diretor.questao_61, # get__display() diretor.questao_62, # get__display() diretor.questao_63, # get__display() diretor.questao_64, # get__display() diretor.questao_65, # get__display() diretor.questao_66, # get__display() diretor.questao_67, # get__display() diretor.questao_68, # get__display() diretor.questao_69, # get__display() diretor.questao_70, # get__display() diretor.questao_71, # get__display() diretor.questao_72, # get__display() diretor.questao_73, # get__display() diretor.questao_74, # get__display() diretor.questao_75, # get__display() diretor.questao_76, # get__display() diretor.questao_77, # get__display() diretor.questao_78, # get__display() diretor.questao_79, # get__display() diretor.questao_80, # get__display() diretor.questao_81, # get__display() diretor.questao_82, # get__display() diretor.questao_83, # get__display() diretor.questao_84, # get__display() questionario.data, questionario.questao_1, # get__display() questionario.questao_2, # get__display() questionario.questao_3, # get__display() questionario.questao_4, # get__display() questionario.questao_5, # get__display() questionario.questao_6, # get__display() questionario.questao_7, # get__display() questionario.questao_8, # get__display() questionario.questao_9, # get__display() questionario.questao_10, # get__display() questionario.questao_11, # get__display() questionario.questao_12, # get__display() questionario.questao_13, # get__display() questionario.questao_14, # get__display() questionario.questao_15, # get__display() questionario.questao_16, # get__display() questionario.questao_17, # get__display() questionario.questao_18, # get__display() questionario.questao_19, # get__display() questionario.questao_20, # get__display() questionario.questao_21, # get__display() questionario.questao_22, # get__display() questionario.questao_23, # get__display() questionario.questao_24, # get__display() questionario.questao_25, # get__display() questionario.questao_26, # get__display() questionario.questao_27, # get__display() questionario.questao_28, # get__display() questionario.questao_29, # get__display() questionario.questao_30, # get__display() questionario.questao_31, # get__display() questionario.questao_32, # get__display() questionario.questao_33, # get__display() questionario.questao_34, # get__display() questionario.questao_35, # get__display() questionario.questao_36, # get__display() questionario.questao_37, # get__display() questionario.questao_38, # get__display() questionario.questao_39, # get__display() questionario.questao_40, # get__display() questionario.questao_41, # get__display() questionario.questao_42, # get__display() questionario.questao_43, # get__display() questionario.questao_44, # get__display() questionario.questao_45, # get__display() questionario.questao_46, # get__display() questionario.questao_47, # get__display() questionario.questao_48, # get__display() questionario.questao_49, # get__display() questionario.questao_50, # get__display() questionario.questao_51, # get__display() questionario.questao_52, # get__display() questionario.questao_53, # get__display() questionario.questao_54, # get__display() questionario.questao_55, # get__display() questionario.questao_56, # get__display() questionario.questao_57, # get__display() questionario.questao_58, # get__display() questionario.questao_59, # get__display() questionario.questao_60, questionario.questao_61, # get__display() questionario.questao_62, # get__display() questionario.questao_63, # get__display() questionario.questao_64, # get__display() questionario.questao_65, # get__display() questionario.questao_66, # get__display() questionario.questao_67, # get__display() questionario.questao_68, # get__display() questionario.questao_69, # get__display() questionario.questao_70, # get__display() questionario.questao_71, # get__display() questionario.questao_72, # get__display() questionario.questao_73, # get__display() questionario.questao_74, # get__display() questionario.questao_75, # get__display() questionario.questao_76, # get__display() questionario.questao_77, # get__display() questionario.questao_78, # get__display() questionario.questao_79, # get__display() questionario.questao_80, # get__display() questionario.questao_81, # get__display() questionario.questao_82, # get__display() questionario.questao_83, # get__display() questionario.questao_84, # get__display() questionario.questao_85, # get__display() questionario.questao_86, # get__display() questionario.questao_87, # get__display() questionario.questao_88, # get__display() questionario.questao_89, # get__display() questionario.questao_90, # get__display() questionario.questao_91, # get__display() questionario.questao_92, # get__display() questionario.questao_93, # get__display() questionario.questao_94, # get__display() questionario.questao_95, # get__display() questionario.questao_96, # get__display() questionario.questao_97, # get__display() questionario.questao_98, # get__display() questionario.questao_99, # get__display() questionario.questao_100, # get__display() questionario.questao_101, # get__display() questionario.questao_102, # get__display() questionario.questao_103, # get__display() questionario.questao_104, # get__display() questionario.questao_105, # get__display() questionario.questao_106, # get__display() questionario.questao_107, # get__display() questionario.questao_108, # get__display() questionario.questao_109, # get__display() questionario.questao_110, # get__display() questionario.questao_111, # get__display() questionario.questao_112, # get__display() questionario.questao_113, # get__display() questionario.questao_114, # get__display() questionario.questao_115, # get__display() questionario.questao_116, # get__display() questionario.questao_117, # get__display() questionario.questao_118, # get__display() questionario.questao_119, # get__display() questionario.questao_120, # get__display() questionario.questao_121, # get__display() questionario.questao_122, # get__display() questionario.questao_123, # get__display() questionario.questao_124, # get__display() questionario.questao_125, # get__display() questionario.questao_126, # get__display() questionario.questao_127, # get__display() questionario.questao_128, # get__display() questionario.questao_129, # get__display() questionario.questao_130, # get__display() questionario.questao_131, # get__display() questionario.questao_132, # get__display() questionario.questao_133, # get__display() questionario.questao_134, # get__display() questionario.questao_135, # get__display() questionario.questao_136, # get__display() questionario.questao_137, # get__display() questionario.questao_138, # get__display() questionario.questao_139, # get__display() questionario.questao_140, # get__display() questionario.questao_141, # get__display() questionario.questao_142, # get__display() questionario.questao_143, # get__display() questionario.questao_144, # get__display() questionario.questao_145, # get__display() questionario.questao_146, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, ]) continue # if questionario.questao_55 == '1': # questionario.questao_55 = 'Não' if tem_questionario and tem_exame: writer.writerow([ aluno.escola.acao.campanha.nome, aluno.escola.acao.nome, aluno.escola.id, aluno.escola.nome, aluno.escola.latitude, aluno.escola.longitude, aluno.numero_identificacao, aluno.periodo, # get__display() aluno.turma, aluno.nascimento, aluno.sexo, # get__display() aluno.raca, # get__display() diretor.data, diretor.questao_1, diretor.questao_2, # get__display() diretor.questao_3, diretor.questao_4, # get__display() diretor.questao_5, # get__display() diretor.questao_6, # get__display() diretor.questao_7, # get__display() diretor.questao_8, # get__display() diretor.questao_9, # get__display() diretor.questao_10, # get__display() diretor.questao_11, # get__display() diretor.questao_12, # get__display() diretor.questao_13, # get__display() diretor.questao_14, # get__display() diretor.questao_15, # get__display() diretor.questao_16, # get__display() diretor.questao_17, # get__display() diretor.questao_18, # get__display() diretor.questao_19, # get__display() diretor.questao_20, # get__display() diretor.questao_21, # get__display() diretor.questao_22, # get__display() diretor.questao_23, # get__display() diretor.questao_24, # get__display() diretor.questao_25, # get__display() diretor.questao_26, # get__display() diretor.questao_27, # get__display() diretor.questao_28, diretor.questao_29, # get__display() diretor.questao_30, # get__display() diretor.questao_31, diretor.questao_32, # get__display() diretor.questao_33, diretor.questao_34, # get__display() diretor.questao_35, # get__display() diretor.questao_36, # get__display() diretor.questao_37, diretor.questao_38, # get__display() diretor.questao_39, diretor.questao_40, # get__display() diretor.questao_41, # get__display() diretor.questao_42, # get__display() diretor.questao_43, # get__display() diretor.questao_44, # get__display() diretor.questao_45, # get__display() diretor.questao_46, # get__display() diretor.questao_47, # get__display() diretor.questao_48, # get__display() diretor.questao_49, # get__display() diretor.questao_50, # get__display() diretor.questao_51, # get__display() diretor.questao_52, # get__display() diretor.questao_53, # get__display() diretor.questao_54, # get__display() diretor.questao_55, # get__display() diretor.questao_56, # get__display() diretor.questao_57, # get__display() diretor.questao_58, # get__display() diretor.questao_59, # get__display() diretor.questao_60, # get__display() diretor.questao_61, # get__display() diretor.questao_62, # get__display() diretor.questao_63, # get__display() diretor.questao_64, # get__display() diretor.questao_65, # get__display() diretor.questao_66, # get__display() diretor.questao_67, # get__display() diretor.questao_68, # get__display() diretor.questao_69, # get__display() diretor.questao_70, # get__display() diretor.questao_71, # get__display() diretor.questao_72, # get__display() diretor.questao_73, # get__display() diretor.questao_74, # get__display() diretor.questao_75, # get__display() diretor.questao_76, # get__display() diretor.questao_77, # get__display() diretor.questao_78, # get__display() diretor.questao_79, # get__display() diretor.questao_80, # get__display() diretor.questao_81, # get__display() diretor.questao_82, # get__display() diretor.questao_83, # get__display() diretor.questao_84, # get__display() questionario.data, questionario.questao_1, # get__display() questionario.questao_2, # get__display() questionario.questao_3, # get__display() questionario.questao_4, # get__display() questionario.questao_5, # get__display() questionario.questao_6, # get__display() questionario.questao_7, # get__display() questionario.questao_8, # get__display() questionario.questao_9, # get__display() questionario.questao_10, # get__display() questionario.questao_11, # get__display() questionario.questao_12, # get__display() questionario.questao_13, # get__display() questionario.questao_14, # get__display() questionario.questao_15, # get__display() questionario.questao_16, # get__display() questionario.questao_17, # get__display() questionario.questao_18, # get__display() questionario.questao_19, # get__display() questionario.questao_20, # get__display() questionario.questao_21, # get__display() questionario.questao_22, # get__display() questionario.questao_23, # get__display() questionario.questao_24, # get__display() questionario.questao_25, # get__display() questionario.questao_26, # get__display() questionario.questao_27, # get__display() questionario.questao_28, # get__display() questionario.questao_29, # get__display() questionario.questao_30, # get__display() questionario.questao_31, # get__display() questionario.questao_32, # get__display() questionario.questao_33, # get__display() questionario.questao_34, # get__display() questionario.questao_35, # get__display() questionario.questao_36, # get__display() questionario.questao_37, # get__display() questionario.questao_38, # get__display() questionario.questao_39, # get__display() questionario.questao_40, # get__display() questionario.questao_41, # get__display() questionario.questao_42, # get__display() questionario.questao_43, # get__display() questionario.questao_44, # get__display() questionario.questao_45, # get__display() questionario.questao_46, # get__display() questionario.questao_47, # get__display() questionario.questao_48, # get__display() questionario.questao_49, # get__display() questionario.questao_50, # get__display() questionario.questao_51, # get__display() questionario.questao_52, # get__display() questionario.questao_53, # get__display() questionario.questao_54, # get__display() questionario.questao_55, # get__display() questionario.questao_56, # get__display() questionario.questao_57, # get__display() questionario.questao_58, # get__display() questionario.questao_59, # get__display() questionario.questao_60, questionario.questao_61, # get__display() questionario.questao_62, # get__display() questionario.questao_63, # get__display() questionario.questao_64, # get__display() questionario.questao_65, # get__display() questionario.questao_66, # get__display() questionario.questao_67, # get__display() questionario.questao_68, # get__display() questionario.questao_69, # get__display() questionario.questao_70, # get__display() questionario.questao_71, # get__display() questionario.questao_72, # get__display() questionario.questao_73, # get__display() questionario.questao_74, # get__display() questionario.questao_75, # get__display() questionario.questao_76, # get__display() questionario.questao_77, # get__display() questionario.questao_78, # get__display() questionario.questao_79, # get__display() questionario.questao_80, # get__display() questionario.questao_81, # get__display() questionario.questao_82, # get__display() questionario.questao_83, # get__display() questionario.questao_84, # get__display() questionario.questao_85, # get__display() questionario.questao_86, # get__display() questionario.questao_87, # get__display() questionario.questao_88, # get__display() questionario.questao_89, # get__display() questionario.questao_90, # get__display() questionario.questao_91, # get__display() questionario.questao_92, # get__display() questionario.questao_93, # get__display() questionario.questao_94, # get__display() questionario.questao_95, # get__display() questionario.questao_96, # get__display() questionario.questao_97, # get__display() questionario.questao_98, # get__display() questionario.questao_99, # get__display() questionario.questao_100, # get__display() questionario.questao_101, # get__display() questionario.questao_102, # get__display() questionario.questao_103, # get__display() questionario.questao_104, # get__display() questionario.questao_105, # get__display() questionario.questao_106, # get__display() questionario.questao_107, # get__display() questionario.questao_108, # get__display() questionario.questao_109, # get__display() questionario.questao_110, # get__display() questionario.questao_111, # get__display() questionario.questao_112, # get__display() questionario.questao_113, # get__display() questionario.questao_114, # get__display() questionario.questao_115, # get__display() questionario.questao_116, # get__display() questionario.questao_117, # get__display() questionario.questao_118, # get__display() questionario.questao_119, # get__display() questionario.questao_120, # get__display() questionario.questao_121, # get__display() questionario.questao_122, # get__display() questionario.questao_123, # get__display() questionario.questao_124, # get__display() questionario.questao_125, # get__display() questionario.questao_126, # get__display() questionario.questao_127, # get__display() questionario.questao_128, # get__display() questionario.questao_129, # get__display() questionario.questao_130, # get__display() questionario.questao_131, # get__display() questionario.questao_132, # get__display() questionario.questao_133, # get__display() questionario.questao_134, # get__display() questionario.questao_135, # get__display() questionario.questao_136, # get__display() questionario.questao_137, # get__display() questionario.questao_138, # get__display() questionario.questao_139, # get__display() questionario.questao_140, # get__display() questionario.questao_141, # get__display() questionario.questao_142, # get__display() questionario.questao_143, # get__display() questionario.questao_144, # get__display() questionario.questao_145, # get__display() questionario.questao_146, exame.data, exame.examinador, exame.anotador, exame.carie_coroa_18, exame.carie_tratamento_18, exame.carie_coroa_17, exame.carie_tratamento_17, exame.carie_coroa_16, exame.carie_tratamento_16, exame.carie_coroa_15, exame.carie_tratamento_15, exame.carie_coroa_14, exame.carie_tratamento_14, exame.carie_coroa_13, exame.carie_tratamento_13, exame.carie_coroa_12, exame.carie_tratamento_12, exame.carie_coroa_11, exame.carie_tratamento_11, exame.carie_coroa_21, exame.carie_tratamento_21, exame.carie_coroa_22, exame.carie_tratamento_22, exame.carie_coroa_23, exame.carie_tratamento_23, exame.carie_coroa_24, exame.carie_tratamento_24, exame.carie_coroa_25, exame.carie_tratamento_25, exame.carie_coroa_26, exame.carie_tratamento_26, exame.carie_coroa_27, exame.carie_tratamento_27, exame.carie_coroa_28, exame.carie_tratamento_28, exame.carie_coroa_38, exame.carie_tratamento_38, exame.carie_coroa_37, exame.carie_tratamento_37, exame.carie_coroa_36, exame.carie_tratamento_36, exame.carie_coroa_35, exame.carie_tratamento_35, exame.carie_coroa_34, exame.carie_tratamento_34, exame.carie_coroa_33, exame.carie_tratamento_33, exame.carie_coroa_32, exame.carie_tratamento_32, exame.carie_coroa_31, exame.carie_tratamento_31, exame.carie_coroa_41, exame.carie_tratamento_41, exame.carie_coroa_42, exame.carie_tratamento_42, exame.carie_coroa_43, exame.carie_tratamento_43, exame.carie_coroa_44, exame.carie_tratamento_44, exame.carie_coroa_45, exame.carie_tratamento_45, exame.carie_coroa_46, exame.carie_tratamento_46, exame.carie_coroa_47, exame.carie_tratamento_47, exame.carie_coroa_48, exame.carie_tratamento_48, exame.periodontal_sangramento_1716, exame.periodontal_calculo_1716, exame.periodontal_bolsa_1716, exame.periodontal_sangramento_11, exame.periodontal_calculo_11, exame.periodontal_bolsa_11, exame.periodontal_sangramento_2627, exame.periodontal_calculo_2627, exame.periodontal_bolsa_2627, exame.periodontal_sangramento_3736, exame.periodontal_calculo_3736, exame.periodontal_bolsa_3736, exame.periodontal_sangramento_31, exame.periodontal_calculo_31, exame.periodontal_bolsa_31, exame.periodontal_sangramento_4647, exame.periodontal_calculo_4647, exame.periodontal_bolsa_4647, resultados["cpod"], ]) if not tem_questionario and not tem_exame: writer.writerow([ aluno.escola.acao.campanha.nome, aluno.escola.acao.nome, aluno.escola.id, aluno.escola.nome, aluno.escola.latitude, aluno.escola.longitude, aluno.numero_identificacao, aluno.periodo, aluno.turma, aluno.nascimento, aluno.sexo, aluno.raca, diretor.data, diretor.questao_1, diretor.questao_2, diretor.questao_3, diretor.questao_4, diretor.questao_5, diretor.questao_6, diretor.questao_7, diretor.questao_8, diretor.questao_9, diretor.questao_10, diretor.questao_11, diretor.questao_12, diretor.questao_13, diretor.questao_14, diretor.questao_15, diretor.questao_16, diretor.questao_17, diretor.questao_18, diretor.questao_19, diretor.questao_20, diretor.questao_21, diretor.questao_22, diretor.questao_23, diretor.questao_24, diretor.questao_25, diretor.questao_26, diretor.questao_27, diretor.questao_28, diretor.questao_29, diretor.questao_30, diretor.questao_31, diretor.questao_32, diretor.questao_33, diretor.questao_34, diretor.questao_35, diretor.questao_36, diretor.questao_37, diretor.questao_38, diretor.questao_39, diretor.questao_40, diretor.questao_41, diretor.questao_42, diretor.questao_43, diretor.questao_44, diretor.questao_45, diretor.questao_46, diretor.questao_47, diretor.questao_48, diretor.questao_49, diretor.questao_50, diretor.questao_51, diretor.questao_52, diretor.questao_53, diretor.questao_54, diretor.questao_55, diretor.questao_56, diretor.questao_57, diretor.questao_58, diretor.questao_59, diretor.questao_60, diretor.questao_61, diretor.questao_62, diretor.questao_63, diretor.questao_64, diretor.questao_65, diretor.questao_66, diretor.questao_67, diretor.questao_68, diretor.questao_69, diretor.questao_70, diretor.questao_71, diretor.questao_72, diretor.questao_73, diretor.questao_74, diretor.questao_75, diretor.questao_76, diretor.questao_77, diretor.questao_78, diretor.questao_79, diretor.questao_80, diretor.questao_81, diretor.questao_82, diretor.questao_83, diretor.questao_84, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, ]) return response class DownloadAlunoQuestionarioExameView(LoginRequired, View): """Gera e envia o arquivo csv para os alunos que fizeram o questionário e o exame""" def get(self, request): alunos = Aluno.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="aluno_questionario_exame.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['escola.nome', 'aluno.numero_identificacao', 'aluno.periodo', 'aluno.turma', 'aluno.nascimento', 'aluno.sexo', 'aluno.raca', 'questionario.data', 'questionario.questao_1', 'questionario.questao_2', 'questionario.questao_3', 'questionario.questao_4', 'questionario.questao_5', 'questionario.questao_6', 'questionario.questao_7', 'questionario.questao_8', 'questionario.questao_9', 'questionario.questao_10', 'questionario.questao_11', 'questionario.questao_12', 'questionario.questao_13', 'questionario.questao_14', 'questionario.questao_15', 'questionario.questao_16', 'questionario.questao_17', 'questionario.questao_18', 'questionario.questao_19', 'questionario.questao_20', 'questionario.questao_21', 'questionario.questao_22', 'questionario.questao_23', 'questionario.questao_24', 'questionario.questao_25', 'questionario.questao_26', 'questionario.questao_27', 'questionario.questao_28', 'questionario.questao_29', 'questionario.questao_30', 'questionario.questao_31', 'questionario.questao_32', 'questionario.questao_33', 'questionario.questao_34', 'questionario.questao_35', 'questionario.questao_36', 'questionario.questao_37', 'questionario.questao_38', 'questionario.questao_39', 'questionario.questao_40', 'questionario.questao_41', 'questionario.questao_42', 'questionario.questao_43', 'questionario.questao_44', 'questionario.questao_45', 'questionario.questao_46', 'questionario.questao_47', 'questionario.questao_48', 'questionario.questao_49', 'questionario.questao_50', 'questionario.questao_51', 'questionario.questao_52', 'questionario.questao_53', 'questionario.questao_54', 'questionario.questao_55', 'questionario.questao_56', 'questionario.questao_57', 'questionario.questao_58', 'questionario.questao_59', 'questionario.questao_60', 'questionario.questao_61', 'questionario.questao_62', 'questionario.questao_63', 'questionario.questao_64', 'questionario.questao_65', 'questionario.questao_66', 'questionario.questao_67', 'questionario.questao_68', 'questionario.questao_69', 'questionario.questao_70', 'questionario.questao_71', 'questionario.questao_72', 'questionario.questao_73', 'questionario.questao_74', 'questionario.questao_75', 'questionario.questao_76', 'questionario.questao_77', 'questionario.questao_78', 'questionario.questao_79', 'questionario.questao_80', 'questionario.questao_81', 'questionario.questao_82', 'questionario.questao_83', 'questionario.questao_84', 'questionario.questao_85', 'questionario.questao_86', 'questionario.questao_87', 'questionario.questao_88', 'questionario.questao_89', 'questionario.questao_90', 'questionario.questao_91', 'questionario.questao_92', 'questionario.questao_93', 'questionario.questao_94', 'questionario.questao_95', 'questionario.questao_96', 'questionario.questao_97', 'questionario.questao_98', 'questionario.questao_99', 'questionario.questao_100', 'questionario.questao_101', 'questionario.questao_102', 'questionario.questao_103', 'questionario.questao_104', 'questionario.questao_105', 'questionario.questao_106', 'questionario.questao_107', 'questionario.questao_108', 'questionario.questao_109', 'questionario.questao_110', 'questionario.questao_111', 'questionario.questao_112', 'questionario.questao_113', 'questionario.questao_114', 'questionario.questao_115', 'questionario.questao_116', 'questionario.questao_117', 'questionario.questao_118', 'questionario.questao_119', 'questionario.questao_120', 'questionario.questao_121', 'questionario.questao_122', 'questionario.questao_123', 'questionario.questao_124', 'questionario.questao_125', 'questionario.questao_126', 'questionario.questao_127', 'questionario.questao_128', 'questionario.questao_129', 'questionario.questao_130', 'questionario.questao_131', 'questionario.questao_132', 'questionario.questao_133', 'questionario.questao_134', 'questionario.questao_135', 'questionario.questao_136', 'questionario.questao_137', 'questionario.questao_138', 'questionario.questao_139', 'questionario.questao_140', 'questionario.questao_141', 'questionario.questao_142', 'questionario.questao_143', 'questionario.questao_144', 'questionario.questao_145', 'questionario.questao_146', 'exame.data', 'exame.examinador', 'exame.anotador', 'exame.carie_coroa_18', 'exame.carie_tratamento_18', 'exame.carie_coroa_17', 'exame.carie_tratamento_17', 'exame.carie_coroa_16', 'exame.carie_tratamento_16', 'exame.carie_coroa_15', 'exame.carie_tratamento_15', 'exame.carie_coroa_14', 'exame.carie_tratamento_14', 'exame.carie_coroa_13', 'exame.carie_tratamento_13', 'exame.carie_coroa_12', 'exame.carie_tratamento_12', 'exame.carie_coroa_11', 'exame.carie_tratamento_11', 'exame.carie_coroa_21', 'exame.carie_tratamento_21', 'exame.carie_coroa_22', 'exame.carie_tratamento_22', 'exame.carie_coroa_23', 'exame.carie_tratamento_23', 'exame.carie_coroa_24', 'exame.carie_tratamento_24', 'exame.carie_coroa_25', 'exame.carie_tratamento_25', 'exame.carie_coroa_26', 'exame.carie_tratamento_26', 'exame.carie_coroa_27', 'exame.carie_tratamento_27', 'exame.carie_coroa_28', 'exame.carie_tratamento_28', 'exame.carie_coroa_38', 'exame.carie_tratamento_38', 'exame.carie_coroa_37', 'exame.carie_tratamento_37', 'exame.carie_coroa_36', 'exame.carie_tratamento_36', 'exame.carie_coroa_35', 'exame.carie_tratamento_35', 'exame.carie_coroa_34', 'exame.carie_tratamento_34', 'exame.carie_coroa_33', 'exame.carie_tratamento_33', 'exame.carie_coroa_32', 'exame.carie_tratamento_32', 'exame.carie_coroa_31', 'exame.carie_tratamento_31', 'exame.carie_coroa_41', 'exame.carie_tratamento_41', 'exame.carie_coroa_42', 'exame.carie_tratamento_42', 'exame.carie_coroa_43', 'exame.carie_tratamento_43', 'exame.carie_coroa_44', 'exame.carie_tratamento_44', 'exame.carie_coroa_45', 'exame.carie_tratamento_45', 'exame.carie_coroa_46', 'exame.carie_tratamento_46', 'exame.carie_coroa_47', 'exame.carie_tratamento_47', 'exame.carie_coroa_48', 'exame.carie_tratamento_48', 'exame.periodontal_sangramento_1716', 'exame.periodontal_calculo_1716', 'exame.periodontal_bolsa_1716', 'exame.periodontal_sangramento_11', 'exame.periodontal_calculo_11', 'exame.periodontal_bolsa_11', 'exame.periodontal_sangramento_2627', 'exame.periodontal_calculo_2627', 'exame.periodontal_bolsa_2627', 'exame.periodontal_sangramento_3736', 'exame.periodontal_calculo_3736', 'exame.periodontal_bolsa_3736', 'exame.periodontal_sangramento_31', 'exame.periodontal_calculo_31', 'exame.periodontal_bolsa_31', 'exame.periodontal_sangramento_4647', 'exame.periodontal_calculo_4647', 'exame.periodontal_bolsa_4647',]) for aluno in alunos: try: questionario = Questionario.objects.get(aluno_id=aluno.id) exame = Exame.objects.get(aluno_id=aluno.id) except: continue writer.writerow([ aluno.escola.nome, aluno.numero_identificacao, aluno.periodo, # get__display() aluno.turma, aluno.nascimento, aluno.sexo, # get__display() aluno.raca, # get__display() questionario.data, questionario.questao_1, # get__display() questionario.questao_2, # get__display() questionario.questao_3, # get__display() questionario.questao_4, # get__display() questionario.questao_5, # get__display() questionario.questao_6, # get__display() questionario.questao_7, # get__display() questionario.questao_8, # get__display() questionario.questao_9, # get__display() questionario.questao_10, # get__display() questionario.questao_11, # get__display() questionario.questao_12, # get__display() questionario.questao_13, # get__display() questionario.questao_14, # get__display() questionario.questao_15, # get__display() questionario.questao_16, # get__display() questionario.questao_17, # get__display() questionario.questao_18, # get__display() questionario.questao_19, # get__display() questionario.questao_20, # get__display() questionario.questao_21, # get__display() questionario.questao_22, # get__display() questionario.questao_23, # get__display() questionario.questao_24, # get__display() questionario.questao_25, # get__display() questionario.questao_26, # get__display() questionario.questao_27, # get__display() questionario.questao_28, # get__display() questionario.questao_29, # get__display() questionario.questao_30, # get__display() questionario.questao_31, # get__display() questionario.questao_32, # get__display() questionario.questao_33, # get__display() questionario.questao_34, # get__display() questionario.questao_35, # get__display() questionario.questao_36, # get__display() questionario.questao_37, # get__display() questionario.questao_38, # get__display() questionario.questao_39, # get__display() questionario.questao_40, # get__display() questionario.questao_41, # get__display() questionario.questao_42, # get__display() questionario.questao_43, # get__display() questionario.questao_44, # get__display() questionario.questao_45, # get__display() questionario.questao_46, # get__display() questionario.questao_47, # get__display() questionario.questao_48, # get__display() questionario.questao_49, # get__display() questionario.questao_50, # get__display() questionario.questao_51, # get__display() questionario.questao_52, # get__display() questionario.questao_53, # get__display() questionario.questao_54, # get__display() questionario.questao_55, # get__display() questionario.questao_56, # get__display() questionario.questao_57, # get__display() questionario.questao_58, # get__display() questionario.questao_59, # get__display() questionario.questao_60, questionario.questao_61, # get__display() questionario.questao_62, # get__display() questionario.questao_63, # get__display() questionario.questao_64, # get__display() questionario.questao_65, # get__display() questionario.questao_66, # get__display() questionario.questao_67, # get__display() questionario.questao_68, # get__display() questionario.questao_69, # get__display() questionario.questao_70, # get__display() questionario.questao_71, # get__display() questionario.questao_72, # get__display() questionario.questao_73, # get__display() questionario.questao_74, # get__display() questionario.questao_75, # get__display() questionario.questao_76, # get__display() questionario.questao_77, # get__display() questionario.questao_78, # get__display() questionario.questao_79, # get__display() questionario.questao_80, # get__display() questionario.questao_81, # get__display() questionario.questao_82, # get__display() questionario.questao_83, # get__display() questionario.questao_84, # get__display() questionario.questao_85, # get__display() questionario.questao_86, # get__display() questionario.questao_87, # get__display() questionario.questao_88, # get__display() questionario.questao_89, # get__display() questionario.questao_90, # get__display() questionario.questao_91, # get__display() questionario.questao_92, # get__display() questionario.questao_93, # get__display() questionario.questao_94, # get__display() questionario.questao_95, # get__display() questionario.questao_96, # get__display() questionario.questao_97, # get__display() questionario.questao_98, # get__display() questionario.questao_99, # get__display() questionario.questao_100, # get__display() questionario.questao_101, # get__display() questionario.questao_102, # get__display() questionario.questao_103, # get__display() questionario.questao_104, # get__display() questionario.questao_105, # get__display() questionario.questao_106, # get__display() questionario.questao_107, # get__display() questionario.questao_108, # get__display() questionario.questao_109, # get__display() questionario.questao_110, # get__display() questionario.questao_111, # get__display() questionario.questao_112, # get__display() questionario.questao_113, # get__display() questionario.questao_114, # get__display() questionario.questao_115, # get__display() questionario.questao_116, # get__display() questionario.questao_117, # get__display() questionario.questao_118, # get__display() questionario.questao_119, # get__display() questionario.questao_120, # get__display() questionario.questao_121, # get__display() questionario.questao_122, # get__display() questionario.questao_123, # get__display() questionario.questao_124, # get__display() questionario.questao_125, # get__display() questionario.questao_126, # get__display() questionario.questao_127, # get__display() questionario.questao_128, # get__display() questionario.questao_129, # get__display() questionario.questao_130, # get__display() questionario.questao_131, # get__display() questionario.questao_132, # get__display() questionario.questao_133, # get__display() questionario.questao_134, # get__display() questionario.questao_135, # get__display() questionario.questao_136, # get__display() questionario.questao_137, # get__display() questionario.questao_138, # get__display() questionario.questao_139, # get__display() questionario.questao_140, # get__display() questionario.questao_141, # get__display() questionario.questao_142, # get__display() questionario.questao_143, # get__display() questionario.questao_144, # get__display() questionario.questao_145, # get__display() questionario.questao_146, exame.data, exame.examinador, exame.anotador, exame.carie_coroa_18, exame.carie_tratamento_18, exame.carie_coroa_17, exame.carie_tratamento_17, exame.carie_coroa_16, exame.carie_tratamento_16, exame.carie_coroa_15, exame.carie_tratamento_15, exame.carie_coroa_14, exame.carie_tratamento_14, exame.carie_coroa_13, exame.carie_tratamento_13, exame.carie_coroa_12, exame.carie_tratamento_12, exame.carie_coroa_11, exame.carie_tratamento_11, exame.carie_coroa_21, exame.carie_tratamento_21, exame.carie_coroa_22, exame.carie_tratamento_22, exame.carie_coroa_23, exame.carie_tratamento_23, exame.carie_coroa_24, exame.carie_tratamento_24, exame.carie_coroa_25, exame.carie_tratamento_25, exame.carie_coroa_26, exame.carie_tratamento_26, exame.carie_coroa_27, exame.carie_tratamento_27, exame.carie_coroa_28, exame.carie_tratamento_28, exame.carie_coroa_38, exame.carie_tratamento_38, exame.carie_coroa_37, exame.carie_tratamento_37, exame.carie_coroa_36, exame.carie_tratamento_36, exame.carie_coroa_35, exame.carie_tratamento_35, exame.carie_coroa_34, exame.carie_tratamento_34, exame.carie_coroa_33, exame.carie_tratamento_33, exame.carie_coroa_32, exame.carie_tratamento_32, exame.carie_coroa_31, exame.carie_tratamento_31, exame.carie_coroa_41, exame.carie_tratamento_41, exame.carie_coroa_42, exame.carie_tratamento_42, exame.carie_coroa_43, exame.carie_tratamento_43, exame.carie_coroa_44, exame.carie_tratamento_44, exame.carie_coroa_45, exame.carie_tratamento_45, exame.carie_coroa_46, exame.carie_tratamento_46, exame.carie_coroa_47, exame.carie_tratamento_47, exame.carie_coroa_48, exame.carie_tratamento_48, exame.periodontal_sangramento_1716, exame.periodontal_calculo_1716, exame.periodontal_bolsa_1716, exame.periodontal_sangramento_11, exame.periodontal_calculo_11, exame.periodontal_bolsa_11, exame.periodontal_sangramento_2627, exame.periodontal_calculo_2627, exame.periodontal_bolsa_2627, exame.periodontal_sangramento_3736, exame.periodontal_calculo_3736, exame.periodontal_bolsa_3736, exame.periodontal_sangramento_31, exame.periodontal_calculo_31, exame.periodontal_bolsa_31, exame.periodontal_sangramento_4647, exame.periodontal_calculo_4647, exame.periodontal_bolsa_4647, ]) return response class DownloadListaCampanhasView(LoginRequired, View): """Gera e envia o arquivo csv da lista de campanhas""" def get(self, request): campanhas = Campanha.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_campanhas.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['campanha.nome',]) for campanha in campanhas: writer.writerow([ campanha.nome, ]) return response class DownloadListaAcoesView(LoginRequired, View): """Gera e envia o arquivo csv da lista de ações""" def get(self, request): acoes = Acao.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_acoes.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['acao.nome',]) for acao in acoes: writer.writerow([ acao.nome, ]) return response class DownloadListaEscolasView(LoginRequired, View): """Gera e envia o arquivo csv da lista de escolas""" def get(self, request): escolas = Escola.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_escolas.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['escola.nome', 'escola.latitude', 'escola.longitude']) for escola in escolas: writer.writerow([ escola.nome, escola.latitude, escola.longitude, ]) return response class DownloadListaAlunosView(LoginRequired, View): """Gera e envia o arquivo csv da lista de alunos""" def get(self, request): alunos = Aluno.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_alunos.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['aluno.escola.nome', 'aluno.numero_identificacao', 'aluno.periodo', 'aluno.turma', 'aluno.nascimento', 'aluno.sexo', 'aluno.raca',]) for aluno in alunos: writer.writerow([ aluno.escola.nome, aluno.numero_identificacao, aluno.periodo, # get__display() aluno.turma, aluno.nascimento, aluno.sexo, # get__display() aluno.raca, # get__display() ]) return response class DownloadListaQuestionariosView(LoginRequired, View): """Gera e envia o arquivo csv da lista de questionários""" def get(self, request): questionarios = Questionario.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_questionarios.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['aluno.numero_identificacao', 'questionario.data', 'questionario.questao_1', 'questionario.questao_2', 'questionario.questao_3', 'questionario.questao_4', 'questionario.questao_5', 'questionario.questao_6', 'questionario.questao_7', 'questionario.questao_8', 'questionario.questao_9', 'questionario.questao_10', 'questionario.questao_11', 'questionario.questao_12', 'questionario.questao_13', 'questionario.questao_14', 'questionario.questao_15', 'questionario.questao_16', 'questionario.questao_17', 'questionario.questao_18', 'questionario.questao_19', 'questionario.questao_20', 'questionario.questao_21', 'questionario.questao_22', 'questionario.questao_23', 'questionario.questao_24', 'questionario.questao_25', 'questionario.questao_26', 'questionario.questao_27', 'questionario.questao_28', 'questionario.questao_29', 'questionario.questao_30', 'questionario.questao_31', 'questionario.questao_32', 'questionario.questao_33', 'questionario.questao_34', 'questionario.questao_35', 'questionario.questao_36', 'questionario.questao_37', 'questionario.questao_38', 'questionario.questao_39', 'questionario.questao_40', 'questionario.questao_41', 'questionario.questao_42', 'questionario.questao_43', 'questionario.questao_44', 'questionario.questao_45', 'questionario.questao_46', 'questionario.questao_47', 'questionario.questao_48', 'questionario.questao_49', 'questionario.questao_50', 'questionario.questao_51', 'questionario.questao_52', 'questionario.questao_53', 'questionario.questao_54', 'questionario.questao_55', 'questionario.questao_56', 'questionario.questao_57', 'questionario.questao_58', 'questionario.questao_59', 'questionario.questao_60', 'questionario.questao_61', 'questionario.questao_62', 'questionario.questao_63', 'questionario.questao_64', 'questionario.questao_65', 'questionario.questao_66', 'questionario.questao_67', 'questionario.questao_68', 'questionario.questao_69', 'questionario.questao_70', 'questionario.questao_71', 'questionario.questao_72', 'questionario.questao_73', 'questionario.questao_74', 'questionario.questao_75', 'questionario.questao_76', 'questionario.questao_77', 'questionario.questao_78', 'questionario.questao_79', 'questionario.questao_80', 'questionario.questao_81', 'questionario.questao_82', 'questionario.questao_83', 'questionario.questao_84', 'questionario.questao_85', 'questionario.questao_86', 'questionario.questao_87', 'questionario.questao_88', 'questionario.questao_89', 'questionario.questao_90', 'questionario.questao_91', 'questionario.questao_92', 'questionario.questao_93', 'questionario.questao_94', 'questionario.questao_95', 'questionario.questao_96', 'questionario.questao_97', 'questionario.questao_98', 'questionario.questao_99', 'questionario.questao_100', 'questionario.questao_101', 'questionario.questao_102', 'questionario.questao_103', 'questionario.questao_104', 'questionario.questao_105', 'questionario.questao_106', 'questionario.questao_107', 'questionario.questao_108', 'questionario.questao_109', 'questionario.questao_110', 'questionario.questao_111', 'questionario.questao_112', 'questionario.questao_113', 'questionario.questao_114', 'questionario.questao_115', 'questionario.questao_116', 'questionario.questao_117', 'questionario.questao_118', 'questionario.questao_119', 'questionario.questao_120', 'questionario.questao_121', 'questionario.questao_122', 'questionario.questao_123', 'questionario.questao_124', 'questionario.questao_125', 'questionario.questao_126', 'questionario.questao_127', 'questionario.questao_128', 'questionario.questao_129', 'questionario.questao_130', 'questionario.questao_131', 'questionario.questao_132', 'questionario.questao_133', 'questionario.questao_134', 'questionario.questao_135', 'questionario.questao_136', 'questionario.questao_137', 'questionario.questao_138', 'questionario.questao_139', 'questionario.questao_140', 'questionario.questao_141', 'questionario.questao_142', 'questionario.questao_143', 'questionario.questao_144', 'questionario.questao_145', 'questionario.questao_146', ]) for questionario in questionarios: writer.writerow([ questionario.aluno.numero_identificacao, questionario.data, questionario.questao_1, # get__display() questionario.questao_2, # get__display() questionario.questao_3, # get__display() questionario.questao_4, # get__display() questionario.questao_5, # get__display() questionario.questao_6, # get__display() questionario.questao_7, # get__display() questionario.questao_8, # get__display() questionario.questao_9, # get__display() questionario.questao_10, # get__display() questionario.questao_11, # get__display() questionario.questao_12, # get__display() questionario.questao_13, # get__display() questionario.questao_14, # get__display() questionario.questao_15, # get__display() questionario.questao_16, # get__display() questionario.questao_17, # get__display() questionario.questao_18, # get__display() questionario.questao_19, # get__display() questionario.questao_20, # get__display() questionario.questao_21, # get__display() questionario.questao_22, # get__display() questionario.questao_23, # get__display() questionario.questao_24, # get__display() questionario.questao_25, # get__display() questionario.questao_26, # get__display() questionario.questao_27, # get__display() questionario.questao_28, # get__display() questionario.questao_29, # get__display() questionario.questao_30, # get__display() questionario.questao_31, # get__display() questionario.questao_32, # get__display() questionario.questao_33, # get__display() questionario.questao_34, # get__display() questionario.questao_35, # get__display() questionario.questao_36, # get__display() questionario.questao_37, # get__display() questionario.questao_38, # get__display() questionario.questao_39, # get__display() questionario.questao_40, # get__display() questionario.questao_41, # get__display() questionario.questao_42, # get__display() questionario.questao_43, # get__display() questionario.questao_44, # get__display() questionario.questao_45, # get__display() questionario.questao_46, # get__display() questionario.questao_47, # get__display() questionario.questao_48, # get__display() questionario.questao_49, # get__display() questionario.questao_50, # get__display() questionario.questao_51, # get__display() questionario.questao_52, # get__display() questionario.questao_53, # get__display() questionario.questao_54, # get__display() questionario.questao_55, # get__display() questionario.questao_56, # get__display() questionario.questao_57, # get__display() questionario.questao_58, # get__display() questionario.questao_59, # get__display() questionario.questao_60, questionario.questao_61, # get__display() questionario.questao_62, # get__display() questionario.questao_63, # get__display() questionario.questao_64, # get__display() questionario.questao_65, # get__display() questionario.questao_66, # get__display() questionario.questao_67, # get__display() questionario.questao_68, # get__display() questionario.questao_69, # get__display() questionario.questao_70, # get__display() questionario.questao_71, # get__display() questionario.questao_72, # get__display() questionario.questao_73, # get__display() questionario.questao_74, # get__display() questionario.questao_75, # get__display() questionario.questao_76, # get__display() questionario.questao_77, # get__display() questionario.questao_78, # get__display() questionario.questao_79, # get__display() questionario.questao_80, # get__display() questionario.questao_81, # get__display() questionario.questao_82, # get__display() questionario.questao_83, # get__display() questionario.questao_84, # get__display() questionario.questao_85, # get__display() questionario.questao_86, # get__display() questionario.questao_87, # get__display() questionario.questao_88, # get__display() questionario.questao_89, # get__display() questionario.questao_90, # get__display() questionario.questao_91, # get__display() questionario.questao_92, # get__display() questionario.questao_93, # get__display() questionario.questao_94, # get__display() questionario.questao_95, # get__display() questionario.questao_96, # get__display() questionario.questao_97, # get__display() questionario.questao_98, # get__display() questionario.questao_99, # get__display() questionario.questao_100, # get__display() questionario.questao_101, # get__display() questionario.questao_102, # get__display() questionario.questao_103, # get__display() questionario.questao_104, # get__display() questionario.questao_105, # get__display() questionario.questao_106, # get__display() questionario.questao_107, # get__display() questionario.questao_108, # get__display() questionario.questao_109, # get__display() questionario.questao_110, # get__display() questionario.questao_111, # get__display() questionario.questao_112, # get__display() questionario.questao_113, # get__display() questionario.questao_114, # get__display() questionario.questao_115, # get__display() questionario.questao_116, # get__display() questionario.questao_117, # get__display() questionario.questao_118, # get__display() questionario.questao_119, # get__display() questionario.questao_120, # get__display() questionario.questao_121, # get__display() questionario.questao_122, # get__display() questionario.questao_123, # get__display() questionario.questao_124, # get__display() questionario.questao_125, # get__display() questionario.questao_126, # get__display() questionario.questao_127, # get__display() questionario.questao_128, # get__display() questionario.questao_129, # get__display() questionario.questao_130, # get__display() questionario.questao_131, # get__display() questionario.questao_132, # get__display() questionario.questao_133, # get__display() questionario.questao_134, # get__display() questionario.questao_135, # get__display() questionario.questao_136, # get__display() questionario.questao_137, # get__display() questionario.questao_138, # get__display() questionario.questao_139, # get__display() questionario.questao_140, # get__display() questionario.questao_141, # get__display() questionario.questao_142, # get__display() questionario.questao_143, # get__display() questionario.questao_144, # get__display() questionario.questao_145, # get__display() questionario.questao_146, ]) return response class DownloadListaExamesView(LoginRequired, View): """Gera e envia o arquivo csv da lista de exames""" def get(self, request): exames = Exame.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_exames.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['aluno.numero_identificacao', 'exame.data', 'exame.examinador', 'exame.anotador', 'exame.carie_coroa_18', 'exame.carie_tratamento_18', 'exame.carie_coroa_17', 'exame.carie_tratamento_17', 'exame.carie_coroa_16', 'exame.carie_tratamento_16', 'exame.carie_coroa_15', 'exame.carie_tratamento_15', 'exame.carie_coroa_14', 'exame.carie_tratamento_14', 'exame.carie_coroa_13', 'exame.carie_tratamento_13', 'exame.carie_coroa_12', 'exame.carie_tratamento_12', 'exame.carie_coroa_11', 'exame.carie_tratamento_11', 'exame.carie_coroa_21', 'exame.carie_tratamento_21', 'exame.carie_coroa_22', 'exame.carie_tratamento_22', 'exame.carie_coroa_23', 'exame.carie_tratamento_23', 'exame.carie_coroa_24', 'exame.carie_tratamento_24', 'exame.carie_coroa_25', 'exame.carie_tratamento_25', 'exame.carie_coroa_26', 'exame.carie_tratamento_26', 'exame.carie_coroa_27', 'exame.carie_tratamento_27', 'exame.carie_coroa_28', 'exame.carie_tratamento_28', 'exame.carie_coroa_38', 'exame.carie_tratamento_38', 'exame.carie_coroa_37', 'exame.carie_tratamento_37', 'exame.carie_coroa_36', 'exame.carie_tratamento_36', 'exame.carie_coroa_35', 'exame.carie_tratamento_35', 'exame.carie_coroa_34', 'exame.carie_tratamento_34', 'exame.carie_coroa_33', 'exame.carie_tratamento_33', 'exame.carie_coroa_32', 'exame.carie_tratamento_32', 'exame.carie_coroa_31', 'exame.carie_tratamento_31', 'exame.carie_coroa_41', 'exame.carie_tratamento_41', 'exame.carie_coroa_42', 'exame.carie_tratamento_42', 'exame.carie_coroa_43', 'exame.carie_tratamento_43', 'exame.carie_coroa_44', 'exame.carie_tratamento_44', 'exame.carie_coroa_45', 'exame.carie_tratamento_45', 'exame.carie_coroa_46', 'exame.carie_tratamento_46', 'exame.carie_coroa_47', 'exame.carie_tratamento_47', 'exame.carie_coroa_48', 'exame.carie_tratamento_48', 'exame.periodontal_sangramento_1716', 'exame.periodontal_calculo_1716', 'exame.periodontal_bolsa_1716', 'exame.periodontal_sangramento_11', 'exame.periodontal_calculo_11', 'exame.periodontal_bolsa_11', 'exame.periodontal_sangramento_2627', 'exame.periodontal_calculo_2627', 'exame.periodontal_bolsa_2627', 'exame.periodontal_sangramento_3736', 'exame.periodontal_calculo_3736', 'exame.periodontal_bolsa_3736', 'exame.periodontal_sangramento_31', 'exame.periodontal_calculo_31', 'exame.periodontal_bolsa_31', 'exame.periodontal_sangramento_4647', 'exame.periodontal_calculo_4647', 'exame.periodontal_bolsa_4647',]) for exame in exames: writer.writerow([ exame.aluno.numero_identificacao, exame.data, exame.examinador, exame.anotador, exame.carie_coroa_18, exame.carie_tratamento_18, exame.carie_coroa_17, exame.carie_tratamento_17, exame.carie_coroa_16, exame.carie_tratamento_16, exame.carie_coroa_15, exame.carie_tratamento_15, exame.carie_coroa_14, exame.carie_tratamento_14, exame.carie_coroa_13, exame.carie_tratamento_13, exame.carie_coroa_12, exame.carie_tratamento_12, exame.carie_coroa_11, exame.carie_tratamento_11, exame.carie_coroa_21, exame.carie_tratamento_21, exame.carie_coroa_22, exame.carie_tratamento_22, exame.carie_coroa_23, exame.carie_tratamento_23, exame.carie_coroa_24, exame.carie_tratamento_24, exame.carie_coroa_25, exame.carie_tratamento_25, exame.carie_coroa_26, exame.carie_tratamento_26, exame.carie_coroa_27, exame.carie_tratamento_27, exame.carie_coroa_28, exame.carie_tratamento_28, exame.carie_coroa_38, exame.carie_tratamento_38, exame.carie_coroa_37, exame.carie_tratamento_37, exame.carie_coroa_36, exame.carie_tratamento_36, exame.carie_coroa_35, exame.carie_tratamento_35, exame.carie_coroa_34, exame.carie_tratamento_34, exame.carie_coroa_33, exame.carie_tratamento_33, exame.carie_coroa_32, exame.carie_tratamento_32, exame.carie_coroa_31, exame.carie_tratamento_31, exame.carie_coroa_41, exame.carie_tratamento_41, exame.carie_coroa_42, exame.carie_tratamento_42, exame.carie_coroa_43, exame.carie_tratamento_43, exame.carie_coroa_44, exame.carie_tratamento_44, exame.carie_coroa_45, exame.carie_tratamento_45, exame.carie_coroa_46, exame.carie_tratamento_46, exame.carie_coroa_47, exame.carie_tratamento_47, exame.carie_coroa_48, exame.carie_tratamento_48, exame.periodontal_sangramento_1716, exame.periodontal_calculo_1716, exame.periodontal_bolsa_1716, exame.periodontal_sangramento_11, exame.periodontal_calculo_11, exame.periodontal_bolsa_11, exame.periodontal_sangramento_2627, exame.periodontal_calculo_2627, exame.periodontal_bolsa_2627, exame.periodontal_sangramento_3736, exame.periodontal_calculo_3736, exame.periodontal_bolsa_3736, exame.periodontal_sangramento_31, exame.periodontal_calculo_31, exame.periodontal_bolsa_31, exame.periodontal_sangramento_4647, exame.periodontal_calculo_4647, exame.periodontal_bolsa_4647, ]) return response class DownloadListaDiretoresView(LoginRequired, View): """Gera e envia o arquivo csv da lista de questionários de diretores""" def get(self, request): diretores = Diretor.objects.order_by('id') response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename="lista_diretores.csv"' writer = csv.writer(response, delimiter=';') writer.writerow(['escola.nome', 'diretor.data', 'diretor.questao_1', 'diretor.questao_2', 'diretor.questao_3', 'diretor.questao_4', 'diretor.questao_5', 'diretor.questao_6', 'diretor.questao_7', 'diretor.questao_8', 'diretor.questao_9', 'diretor.questao_10', 'diretor.questao_11', 'diretor.questao_12', 'diretor.questao_13', 'diretor.questao_14', 'diretor.questao_15', 'diretor.questao_16', 'diretor.questao_17', 'diretor.questao_18', 'diretor.questao_19', 'diretor.questao_20', 'diretor.questao_21', 'diretor.questao_22', 'diretor.questao_23', 'diretor.questao_24', 'diretor.questao_25', 'diretor.questao_26', 'diretor.questao_27', 'diretor.questao_28', 'diretor.questao_29', 'diretor.questao_30', 'diretor.questao_31', 'diretor.questao_32', 'diretor.questao_33', 'diretor.questao_34', 'diretor.questao_35', 'diretor.questao_36', 'diretor.questao_37', 'diretor.questao_38', 'diretor.questao_39', 'diretor.questao_40', 'diretor.questao_41', 'diretor.questao_42', 'diretor.questao_43', 'diretor.questao_44', 'diretor.questao_45', 'diretor.questao_46', 'diretor.questao_47', 'diretor.questao_48', 'diretor.questao_49', 'diretor.questao_50', 'diretor.questao_51', 'diretor.questao_52', 'diretor.questao_53', 'diretor.questao_54', 'diretor.questao_55', 'diretor.questao_56', 'diretor.questao_57', 'diretor.questao_58', 'diretor.questao_59', 'diretor.questao_60', 'diretor.questao_61', 'diretor.questao_62', 'diretor.questao_63', 'diretor.questao_64', 'diretor.questao_65', 'diretor.questao_66', 'diretor.questao_67', 'diretor.questao_68', 'diretor.questao_69', 'diretor.questao_70', 'diretor.questao_71', 'diretor.questao_72', 'diretor.questao_73', 'diretor.questao_74', 'diretor.questao_75', 'diretor.questao_76', 'diretor.questao_77', 'diretor.questao_78', 'diretor.questao_79', 'diretor.questao_80', 'diretor.questao_81', 'diretor.questao_82', 'diretor.questao_83', 'diretor.questao_84',]) for diretor in diretores: writer.writerow([ diretor.escola.nome, diretor.data, diretor.questao_1, diretor.questao_2, # get__display() diretor.questao_3, diretor.questao_4, # get__display() diretor.questao_5, # get__display() diretor.questao_6, # get__display() diretor.questao_7, # get__display() diretor.questao_8, # get__display() diretor.questao_9, # get__display() diretor.questao_10, # get__display() diretor.questao_11, # get__display() diretor.questao_12, # get__display() diretor.questao_13, # get__display() diretor.questao_14, # get__display() diretor.questao_15, # get__display() diretor.questao_16, # get__display() diretor.questao_17, # get__display() diretor.questao_18, # get__display() diretor.questao_19, # get__display() diretor.questao_20, # get__display() diretor.questao_21, # get__display() diretor.questao_22, # get__display() diretor.questao_23, # get__display() diretor.questao_24, # get__display() diretor.questao_25, # get__display() diretor.questao_26, # get__display() diretor.questao_27, # get__display() diretor.questao_28, diretor.questao_29, # get__display() diretor.questao_30, # get__display() diretor.questao_31, diretor.questao_32, # get__display() diretor.questao_33, diretor.questao_34, # get__display() diretor.questao_35, # get__display() diretor.questao_36, # get__display() diretor.questao_37, diretor.questao_38, # get__display() diretor.questao_39, diretor.questao_40, # get__display() diretor.questao_41, # get__display() diretor.questao_42, # get__display() diretor.questao_43, # get__display() diretor.questao_44, # get__display() diretor.questao_45, # get__display() diretor.questao_46, # get__display() diretor.questao_47, # get__display() diretor.questao_48, # get__display() diretor.questao_49, # get__display() diretor.questao_50, # get__display() diretor.questao_51, # get__display() diretor.questao_52, # get__display() diretor.questao_53, # get__display() diretor.questao_54, # get__display() diretor.questao_55, # get__display() diretor.questao_56, # get__display() diretor.questao_57, # get__display() diretor.questao_58, # get__display() diretor.questao_59, # get__display() diretor.questao_60, # get__display() diretor.questao_61, # get__display() diretor.questao_62, # get__display() diretor.questao_63, # get__display() diretor.questao_64, # get__display() diretor.questao_65, # get__display() diretor.questao_66, # get__display() diretor.questao_67, # get__display() diretor.questao_68, # get__display() diretor.questao_69, # get__display() diretor.questao_70, # get__display() diretor.questao_71, # get__display() diretor.questao_72, # get__display() diretor.questao_73, # get__display() diretor.questao_74, # get__display() diretor.questao_75, # get__display() diretor.questao_76, # get__display() diretor.questao_77, # get__display() diretor.questao_78, # get__display() diretor.questao_79, # get__display() diretor.questao_80, # get__display() diretor.questao_81, # get__display() diretor.questao_82, # get__display() diretor.questao_83, # get__display() diretor.questao_84, # get__display() ]) return response

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1dc57c0d12f238518d38818ae0945c4a1f83ee90

5,322

py

Python

tests/test_config/test_config_file_only.py

plato79/UnofficialDDNSnix

4a2a67cc06a6346f90726c33ee388374b7922f2e

[ "MIT" ]

3

2015-10-18T09:14:59.000Z

2018-02-25T09:41:58.000Z

tests/test_config/test_config_file_only.py

plato79/UnofficialDDNSnix

4a2a67cc06a6346f90726c33ee388374b7922f2e

[ "MIT" ]

3

2015-02-05T00:52:30.000Z

2020-04-17T06:21:00.000Z

tests/test_config/test_config_file_only.py

plato79/UnofficialDDNSnix

4a2a67cc06a6346f90726c33ee388374b7922f2e

[ "MIT" ]

3

2016-01-09T04:36:10.000Z

2020-04-17T06:57:47.000Z

#!/usr/bin/env python2.6 import os import pytest from UnofficialDDNS import __doc__ as uddns_doc from UnofficialDDNS import __version__ as uddns_ver from docopt import docopt import libs def test_config_file_only_with_invalid_binary_data(config_file): config_file.write(os.urandom(1024)) config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Unable to read config file %s, invalid data." % config_file.name == str(e.value) def test_config_file_only_with_nonexistent_file(): argv = ['-c', '/tmp/doesNotExist.28520'] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Config file /tmp/doesNotExist.28520 does not exist, not a file, or no permission." == str(e.value) def test_config_file_only_with_no_read_permissions(): argv = ['-c', '/etc/sudoers'] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Unable to read config file /etc/sudoers." == str(e.value) def test_config_file_only_with_directory_instead_of_file(): argv = ['-c', '/etc'] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Config file /etc does not exist, not a file, or no permission." == str(e.value) def test_config_file_only_with_invalid_text_data_not_yaml(config_file): config_file.write("daemon\n") config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Config file %s contents didn't yield dict or not YAML: daemon" % config_file.name == str(e.value) def test_config_file_only_with_invalid_text_data_not_yaml_big(config_file): config_file.write(""" domain mydomain.com # i am a comment user thisuser#comment #another comment passwd abc" """) config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Config file %s contents not YAML formatted:" % config_file.name in str(e.value) def test_config_file_only_with_invalid_text_data_unknown_option(config_file): config_file.write("test: true\n") config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Unknown option test in config file %s." % config_file.name == str(e.value) def test_config_file_only_with_invalid_text_data_unknown_value(config_file): config_file.write("daemon: unknown\n") config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Config file option daemon must be True or False." == str(e.value) def test_config_file_only_missing_log_value(config_file): config_file.write("domain: mydomain.com\nuser: thisuser\npasswd: abc\nlog: #True\n") config_file.flush() argv = ['-c', config_file.name] config = libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert None == config['log'] def test_config_file_only_tab_character(config_file): config_file.write("domain: mydomain.com\nuser:\tthisuser\npasswd: abc") config_file.flush() argv = ['-c', config_file.name] with pytest.raises(libs.MultipleConfigSources.ConfigError) as e: libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert "Tab character found in config file %s. Must use spaces only!" % config_file.name == str(e.value) def test_config_file_only_with_full_valid_data(config_file): config_file.write("domain: mydomain.com\nuser: thisuser\npasswd: abc") config_file.flush() argv = ['-c', config_file.name] expected = dict(log=None, daemon=False, verbose=False, interval=60, pid=None, quiet=False, version=False, registrar='name.com', config=config_file.name, help=False, user='thisuser', passwd='abc', domain='mydomain.com') actual = libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert expected == actual def test_config_file_only_with_full_valid_data_and_comments(config_file): config_file.write(""" domain: mydomain.com # i am a comment user: thisuser #comment #another comment passwd: abc """) config_file.flush() argv = ['-c', config_file.name] expected = dict(log=None, daemon=False, verbose=False, interval=60, pid=None, quiet=False, version=False, registrar='name.com', config=config_file.name, help=False, user='thisuser', passwd='abc', domain='mydomain.com') actual = libs.get_config(docopt(uddns_doc, version=uddns_ver, argv=argv)) assert expected == actual

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7

1ded8a15af9380e20301cb57a2fc887ac18e7d90

10,461

py

Python

DQM/Physics/python/topSingleLeptonDQM_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

DQM/Physics/python/topSingleLeptonDQM_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

DQM/Physics/python/topSingleLeptonDQM_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms #Primary vertex selection PVCut = "abs(z) < 24. & position.rho < 2. & ndof > 4 & !isFake" #Jet selection looseJetCut = "(chargedHadronEnergyFraction()>0 && chargedMultiplicity()>0 && chargedEmEnergyFraction()<0.99 && neutralHadronEnergyFraction()<0.99 && neutralEmEnergyFraction()<0.99 && (chargedMultiplicity()+neutralMultiplicity())>1) && abs(eta)<=2.4 " tightJetCut = "(chargedHadronEnergyFraction()>0 && chargedMultiplicity()>0 && chargedEmEnergyFraction()<0.99 && neutralHadronEnergyFraction()<0.90 && neutralEmEnergyFraction()<0.90 && (chargedMultiplicity()+neutralMultiplicity())>1) && abs(eta)<=2.4 " #Loose muon selection looseMuonCut = "(muonRef.isNonnull && (muonRef.isGlobalMuon || muonRef.isTrackerMuon) && muonRef.isPFMuon)" looseIsoCut = "((muonRef.pfIsolationR04.sumChargedHadronPt + max(0., muonRef.pfIsolationR04.sumNeutralHadronEt + muonRef.pfIsolationR04.sumPhotonEt - 0.5 * muonRef.pfIsolationR04.sumPUPt) ) / muonRef.pt < 0.25)" #Medium muon selection. Also requires either good global muon or tight segment compatibility mediumMuonCut = looseMuonCut + " muonRef.innerTrack.validFraction > 0.8" #Tight muon selection. Lacks distance to primary vertex variables, dz<0.5, dxy < 0.2. Now done at .cc tightMuonCut = "muonRef.isNonnull && muonRef.isGlobalMuon && muonRef.isPFMuon && muonRef.globalTrack.normalizedChi2 < 10. && muonRef.globalTrack.hitPattern.numberOfValidMuonHits > 0 && " + \ "muonRef.numberOfMatchedStations > 1 && muonRef.innerTrack.hitPattern.numberOfValidPixelHits > 0 && muonRef.innerTrack.hitPattern.trackerLayersWithMeasurement > 5 " tightIsoCut = "(muonRef.pfIsolationR04.sumChargedHadronPt + max(0., muonRef.pfIsolationR04.sumNeutralHadronEt + muonRef.pfIsolationR04.sumPhotonEt - 0.5 * muonRef.pfIsolationR04.sumPUPt) ) / muonRef.pt < 0.15" #Electron selections looseEleCut = "(( gsfElectronRef.full5x5_sigmaIetaIeta() < 0.011 && gsfElectronRef.superCluster().isNonnull() && gsfElectronRef.superCluster().seed().isNonnull() && (gsfElectronRef.deltaEtaSuperClusterTrackAtVtx() - gsfElectronRef.superCluster().eta() + gsfElectronRef.superCluster().seed().eta()) < 0.00477 && abs(gsfElectronRef.deltaPhiSuperClusterTrackAtVtx()) < 0.222 && gsfElectronRef.hadronicOverEm() < 0.298 && abs(1.0 - gsfElectronRef.eSuperClusterOverP())*1.0/gsfElectronRef.ecalEnergy() < 0.241 && gsfElectronRef.gsfTrack.hitPattern().numberOfLostHits('MISSING_INNER_HITS') <= 1 && abs(gsfElectronRef.superCluster().eta()) < 1.479) || (gsfElectronRef.full5x5_sigmaIetaIeta() < 0.0314 && gsfElectronRef.superCluster().isNonnull() && gsfElectronRef.superCluster().seed().isNonnull() && (gsfElectronRef.deltaEtaSuperClusterTrackAtVtx() - gsfElectronRef.superCluster().eta() + gsfElectronRef.superCluster().seed().eta()) < 0.00868 && abs(gsfElectronRef.deltaPhiSuperClusterTrackAtVtx()) < 0.213 && gsfElectronRef.hadronicOverEm() < 0.101 && abs(1.0 - gsfElectronRef.eSuperClusterOverP())*1.0/gsfElectronRef.ecalEnergy() < 0.14 && gsfElectronRef.gsfTrack.hitPattern().numberOfLostHits('MISSING_INNER_HITS') <= 1 && abs(gsfElectronRef.superCluster().eta()) > 1.479))" tightEleCut = "((gsfElectronRef.full5x5_sigmaIetaIeta() < 0.00998 && gsfElectronRef.superCluster().isNonnull() && gsfElectronRef.superCluster().seed().isNonnull() && (gsfElectronRef.deltaEtaSuperClusterTrackAtVtx() - gsfElectronRef.superCluster().eta() + gsfElectronRef.superCluster().seed().eta()) < 0.00308 && abs(gsfElectronRef.deltaPhiSuperClusterTrackAtVtx()) < 0.0816 && gsfElectronRef.hadronicOverEm() < 0.0414 && abs(1.0 - gsfElectronRef.eSuperClusterOverP())*1.0/gsfElectronRef.ecalEnergy() < 0.0129 && gsfElectronRef.gsfTrack.hitPattern().numberOfLostHits('MISSING_INNER_HITS') <= 1 && abs(gsfElectronRef.superCluster().eta()) < 1.479) || (gsfElectronRef.full5x5_sigmaIetaIeta() < 0.0292 && gsfElectronRef.superCluster().isNonnull() && gsfElectronRef.superCluster().seed().isNonnull() && (gsfElectronRef.deltaEtaSuperClusterTrackAtVtx() - gsfElectronRef.superCluster().eta() + gsfElectronRef.superCluster().seed().eta()) < 0.00605 && abs(gsfElectronRef.deltaPhiSuperClusterTrackAtVtx()) < 0.0394 && gsfElectronRef.hadronicOverEm() < 0.0641 && abs(1.0 - gsfElectronRef.eSuperClusterOverP())*1.0/gsfElectronRef.ecalEnergy() < 0.0129 && gsfElectronRef.gsfTrack.hitPattern().numberOfLostHits('MISSING_INNER_HITS') <= 1 && abs(gsfElectronRef.superCluster().eta()) > 1.479))" from DQMServices.Core.DQMEDAnalyzer import DQMEDAnalyzer topSingleMuonMediumDQM = DQMEDAnalyzer('TopSingleLeptonDQM', ## ------------------------------------------------------ ## SETUP ## ## configuration of the MonitoringEnsemble(s) ## [mandatory] : optional PSets may be omitted ## setup = cms.PSet( directory = cms.string("Physics/Top/TopSingleMuonMediumDQM/"), sources = cms.PSet( muons = cms.InputTag("pfIsolatedMuonsEI"), elecs = cms.InputTag("pfIsolatedElectronsEI"), jets = cms.InputTag("ak4PFJetsCHS"), mets = cms.VInputTag("pfMet"), pvs = cms.InputTag("offlinePrimaryVertices") ), monitoring = cms.PSet( verbosity = cms.string("DEBUG") ), pvExtras = cms.PSet( select = cms.string(PVCut) ), elecExtras = cms.PSet( select = cms.string(tightEleCut + "& pt>20 & abs(eta)<2.5 & (abs(gsfElectronRef.superCluster().eta()) <= 1.4442 || abs(gsfElectronRef.superCluster().eta()) >= 1.5660)"), rho = cms.InputTag("fixedGridRhoFastjetAll"), ), muonExtras = cms.PSet( select = cms.string(tightMuonCut + " && pt>20 & abs(eta)<2.4"), #select = cms.string(looseMuonCut + " && pt>20 & abs(eta)<2.4"), isolation = cms.string(looseIsoCut) ), jetExtras = cms.PSet( jetCorrector = cms.InputTag("dqmAk4PFCHSL1FastL2L3Corrector"), #Use pak4PFCHSL1FastL2L3Residual for data!!! select = cms.string("pt>30 & abs(eta)< 2.4"), jetBTaggers = cms.PSet( cvsVertex = cms.PSet( label = cms.InputTag("pfCombinedInclusiveSecondaryVertexV2BJetTags"), workingPoint = cms.double(0.890) # CSV Medium from https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation74X ) ), ), massExtras = cms.PSet( lowerEdge = cms.double( 70.), upperEdge = cms.double(110.) ), ), preselection = cms.PSet( vertex = cms.PSet( src = cms.InputTag("offlinePrimaryVertices"), select = cms.string(PVCut) ) ), selection = cms.VPSet( cms.PSet( label = cms.string("muons:step0"), src = cms.InputTag("pfIsolatedMuonsEI"), select = cms.string(tightMuonCut + " && pt>20 & abs(eta)<2.4"), min = cms.int32(1), ), cms.PSet( label = cms.string("jets/pf:step1"), src = cms.InputTag("ak4PFJetsCHS"), select = cms.string("pt>30 & abs(eta)<2.4"), min = cms.int32(4), ), cms.PSet( label = cms.string("met:step2"), src = cms.InputTag("pfMet"), select = cms.string("pt>30"), ), ) ) topSingleElectronMediumDQM = DQMEDAnalyzer('TopSingleLeptonDQM', ## ------------------------------------------------------ ## SETUP ## ## configuration of the MonitoringEnsemble(s) ## [mandatory] : optional PSets may be omitted ## setup = cms.PSet( directory = cms.string("Physics/Top/TopSingleElectronMediumDQM/"), sources = cms.PSet( muons = cms.InputTag("pfIsolatedMuonsEI"), elecs = cms.InputTag("pfIsolatedElectronsEI"), jets = cms.InputTag("ak4PFJetsCHS"), mets = cms.VInputTag("pfMet"), pvs = cms.InputTag("offlinePrimaryVertices") ), monitoring = cms.PSet( verbosity = cms.string("DEBUG") ), pvExtras = cms.PSet( select = cms.string(PVCut) ), elecExtras = cms.PSet( select = cms.string(tightEleCut + "& pt>20 & abs(eta)<2.5 & (abs(gsfElectronRef.superCluster().eta()) <= 1.4442 || abs(gsfElectronRef.superCluster().eta()) >= 1.5660)"), rho = cms.InputTag("fixedGridRhoFastjetAll"), ), muonExtras = cms.PSet( select = cms.string(tightMuonCut + " & pt>20 & abs(eta)<2.4"), isolation = cms.string(looseIsoCut), ), jetExtras = cms.PSet( jetCorrector = cms.InputTag("dqmAk4PFCHSL1FastL2L3Corrector"), #Use pak4PFCHSL1FastL2L3Residual for data!!! select = cms.string("pt>30 & abs(eta)<2.4"), jetBTaggers = cms.PSet( cvsVertex = cms.PSet( label = cms.InputTag("pfCombinedInclusiveSecondaryVertexV2BJetTags"), workingPoint = cms.double(0.890) # CSV Medium from https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation74X ) ), ), massExtras = cms.PSet( lowerEdge = cms.double( 70.), upperEdge = cms.double(110.) ), ), preselection = cms.PSet( vertex = cms.PSet( src = cms.InputTag("offlinePrimaryVertices"), select = cms.string(PVCut) ) ), selection = cms.VPSet( cms.PSet( label = cms.string("elecs:step0"), src = cms.InputTag("pfIsolatedElectronsEI"), select = cms.string("pt>20 & abs(eta)<2.5 & (abs(gsfElectronRef.superCluster().eta()) <= 1.4442 || abs(gsfElectronRef.superCluster().eta()) >= 1.5660) &&" + tightEleCut), # select = cms.string("pt>30 & abs(eta)<2.5 & abs(gsfElectronRef.gsfTrack.d0)<0.02 & gsfElectronRef.gsfTrack.hitPattern().numberOfLostHits('MISSING_INNER_HITS') <= 0 & (abs(gsfElectronRef.superCluster.eta) <= 1.4442 || abs(gsfElectronRef.superCluster.eta) >= 1.5660) & " + EletightIsoCut), min = cms.int32(1), ), cms.PSet( label = cms.string("jets/pf:step1"), src = cms.InputTag("ak4PFJetsCHS"), select = cms.string("pt>30 & abs(eta)<2.4"), min = cms.int32(4), ), cms.PSet( label = cms.string("met:step2"), src = cms.InputTag("pfMet"), select = cms.string("pt>30"), ), ) )

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0

8

1df9add4ef7ba56c68b966626bfbd57cb88b1cbc

7,462

py

Python

tests/test_provider_chanzuckerberg_snowflake.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

tests/test_provider_chanzuckerberg_snowflake.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

tests/test_provider_chanzuckerberg_snowflake.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# tests/test_provider_chanzuckerberg_snowflake.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:27:18 UTC) def test_provider_import(): import terrascript.provider.chanzuckerberg.snowflake def test_resource_import(): from terrascript.resource.chanzuckerberg.snowflake import snowflake_account_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_api_integration from terrascript.resource.chanzuckerberg.snowflake import snowflake_database from terrascript.resource.chanzuckerberg.snowflake import snowflake_database_grant from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_external_function, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_external_table from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_external_table_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_file_format from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_file_format_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_function from terrascript.resource.chanzuckerberg.snowflake import snowflake_function_grant from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_integration_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_managed_account from terrascript.resource.chanzuckerberg.snowflake import snowflake_masking_policy from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_masking_policy_grant, ) from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_materialized_view, ) from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_materialized_view_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_network_policy from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_network_policy_attachment, ) from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_notification_integration, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_pipe from terrascript.resource.chanzuckerberg.snowflake import snowflake_pipe_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_procedure from terrascript.resource.chanzuckerberg.snowflake import snowflake_procedure_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_resource_monitor from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_resource_monitor_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_role from terrascript.resource.chanzuckerberg.snowflake import snowflake_role_grants from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_row_access_policy, ) from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_row_access_policy_grant, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_schema from terrascript.resource.chanzuckerberg.snowflake import snowflake_schema_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_scim_integration from terrascript.resource.chanzuckerberg.snowflake import snowflake_sequence from terrascript.resource.chanzuckerberg.snowflake import snowflake_sequence_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_share from terrascript.resource.chanzuckerberg.snowflake import snowflake_stage from terrascript.resource.chanzuckerberg.snowflake import snowflake_stage_grant from terrascript.resource.chanzuckerberg.snowflake import ( snowflake_storage_integration, ) from terrascript.resource.chanzuckerberg.snowflake import snowflake_stream from terrascript.resource.chanzuckerberg.snowflake import snowflake_stream_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_table from terrascript.resource.chanzuckerberg.snowflake import snowflake_table_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_task from terrascript.resource.chanzuckerberg.snowflake import snowflake_task_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_user from terrascript.resource.chanzuckerberg.snowflake import snowflake_user_public_keys from terrascript.resource.chanzuckerberg.snowflake import snowflake_view from terrascript.resource.chanzuckerberg.snowflake import snowflake_view_grant from terrascript.resource.chanzuckerberg.snowflake import snowflake_warehouse from terrascript.resource.chanzuckerberg.snowflake import snowflake_warehouse_grant def test_datasource_import(): from terrascript.data.chanzuckerberg.snowflake import snowflake_current_account from terrascript.data.chanzuckerberg.snowflake import snowflake_external_functions from terrascript.data.chanzuckerberg.snowflake import snowflake_external_tables from terrascript.data.chanzuckerberg.snowflake import snowflake_file_formats from terrascript.data.chanzuckerberg.snowflake import snowflake_functions from terrascript.data.chanzuckerberg.snowflake import snowflake_masking_policies from terrascript.data.chanzuckerberg.snowflake import snowflake_materialized_views from terrascript.data.chanzuckerberg.snowflake import snowflake_pipes from terrascript.data.chanzuckerberg.snowflake import snowflake_procedures from terrascript.data.chanzuckerberg.snowflake import snowflake_resource_monitors from terrascript.data.chanzuckerberg.snowflake import snowflake_row_access_policies from terrascript.data.chanzuckerberg.snowflake import snowflake_schemas from terrascript.data.chanzuckerberg.snowflake import snowflake_sequences from terrascript.data.chanzuckerberg.snowflake import snowflake_stages from terrascript.data.chanzuckerberg.snowflake import snowflake_storage_integrations from terrascript.data.chanzuckerberg.snowflake import snowflake_streams from terrascript.data.chanzuckerberg.snowflake import ( snowflake_system_generate_scim_access_token, ) from terrascript.data.chanzuckerberg.snowflake import ( snowflake_system_get_aws_sns_iam_policy, ) from terrascript.data.chanzuckerberg.snowflake import ( snowflake_system_get_privatelink_config, ) from terrascript.data.chanzuckerberg.snowflake import ( snowflake_system_get_snowflake_platform_info, ) from terrascript.data.chanzuckerberg.snowflake import snowflake_tables from terrascript.data.chanzuckerberg.snowflake import snowflake_tasks from terrascript.data.chanzuckerberg.snowflake import snowflake_views from terrascript.data.chanzuckerberg.snowflake import snowflake_warehouses # TODO: Shortcut imports without namespace for official and supported providers. # TODO: This has to be moved into a required_providers block. # def test_version_source(): # # import terrascript.provider.chanzuckerberg.snowflake # # t = terrascript.provider.chanzuckerberg.snowflake.snowflake() # s = str(t) # # assert 'https://github.com/chanzuckerberg/terraform-provider-snowflake' in s # assert '0.25.19' in s

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0.366038

0.479636

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35.875

0.919175

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0

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0

1

0.026549

true

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null

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null

0

1

0

1

0

1

0

11

382d6564470c2075fd0ec32a401d0c39033d0e9b

14,293

py

Python

product/migrations/0001_initial.py

JiajiaHuang/smonus

95ec209ae3562ea73ee9ce4c22a0d3a3f0975210

[ "Unlicense" ]

null

product/migrations/0001_initial.py

JiajiaHuang/smonus

95ec209ae3562ea73ee9ce4c22a0d3a3f0975210

[ "Unlicense" ]

null

product/migrations/0001_initial.py

JiajiaHuang/smonus

95ec209ae3562ea73ee9ce4c22a0d3a3f0975210

[ "Unlicense" ]

null

# Generated by Django 2.2.1 on 2019-09-11 09:58 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='SmBrand', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('bramd_id', models.IntegerField(blank=True, null=True, verbose_name='品牌ID')), ('bramd_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='品牌')), ('brand_order', models.IntegerField(blank=True, null=True, verbose_name='排序')), ('is_status', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否启用')), ('hide_value', models.IntegerField(blank=True, default=0, null=True, verbose_name='隐藏的字数')), ], ), migrations.CreateModel( name='SmCatGoods', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cat_id', models.IntegerField(blank=True, null=True, verbose_name='目录ID（goods_category表）')), ('goods_id', models.IntegerField(blank=True, null=True, verbose_name='商品ID')), ('goods_price', models.FloatField(blank=True, null=True, verbose_name='商品价格')), ('expand_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='商品扩展名')), ('is_status', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否启用')), ('add_time', models.DateTimeField(blank=True, null=True, verbose_name='添加时间')), ('note', models.CharField(blank=True, max_length=1024, null=True, verbose_name='备注')), ], ), migrations.CreateModel( name='SmCatGoodsBackup', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cat_id', models.IntegerField(blank=True, null=True, verbose_name='目录ID（goods_category表）')), ('goods_id', models.IntegerField(blank=True, null=True, verbose_name='商品ID')), ('goods_price', models.FloatField(blank=True, null=True, verbose_name='商品价格')), ('expand_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='商品扩展名')), ('is_status', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否启用')), ('add_time', models.DateTimeField(blank=True, null=True, verbose_name='添加时间')), ('note', models.CharField(blank=True, max_length=1024, null=True, verbose_name='备注')), ], ), migrations.CreateModel( name='SmCoupon', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('coupon_id_type', models.IntegerField(blank=True, null=True, verbose_name='分类ID')), ('coupon_sn', models.CharField(blank=True, max_length=256, null=True, verbose_name='优惠券号')), ('user_id', models.IntegerField(blank=True, null=True, verbose_name='使用会员ID')), ('used_time', models.DateTimeField(blank=True, null=True, verbose_name='使用时间')), ('order_sn', models.CharField(blank=True, max_length=256, null=True, verbose_name='使用订单号')), ('soruce_order_sn', models.CharField(blank=True, max_length=256, null=True, verbose_name='由该订单产生的优惠券')), ('emailed', models.CharField(blank=True, max_length=64, null=True, verbose_name='邮箱地址')), ('send_type', models.BooleanField(blank=True, default=False, null=True, verbose_name='是否启用')), ('send_phone', models.CharField(blank=True, max_length=64, null=True, verbose_name='发送的手机号码')), ('send_time', models.DateTimeField(blank=True, null=True, verbose_name='发送时间')), ], ), migrations.CreateModel( name='SmCouponType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('type_money', models.IntegerField(blank=True, null=True, verbose_name='类别金额')), ('type_name', models.CharField(blank=True, max_length=256, null=True, verbose_name='类别名称')), ('send_type', models.IntegerField(blank=True, null=True, verbose_name='发送类型')), ('min_amount', models.IntegerField(blank=True, null=True, verbose_name='最小使用金额')), ('max_amount', models.IntegerField(blank=True, null=True, verbose_name='最大使用金额')), ('send_start_date', models.DateTimeField(blank=True, null=True, verbose_name='发送开始时间')), ('send_end_date', models.DateTimeField(blank=True, null=True, verbose_name='发送最后时间')), ('use_start_date', models.DateTimeField(blank=True, null=True, verbose_name='使用开始时间')), ('use_end_date', models.DateTimeField(blank=True, null=True, verbose_name='最后使用时间')), ('min_goods_amount', models.IntegerField(blank=True, null=True, verbose_name='最小使用商品金额')), ('add_time', models.DateTimeField(blank=True, null=True, verbose_name='添加时间')), ], ), migrations.CreateModel( name='SmGoods', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cat_id', models.IntegerField(blank=True, null=True, verbose_name='')), ('goods_sn', models.CharField(blank=True, max_length=64, null=True, verbose_name='商品货号')), ('goods_name', models.CharField(blank=True, max_length=256, null=True, verbose_name='商品名字')), ('goods_name_style', models.CharField(blank=True, max_length=256, null=True, verbose_name='商品类型')), ('click_count', models.IntegerField(blank=True, default=0, null=True, verbose_name='点击数量')), ('brand_id', models.IntegerField(blank=True, null=True, verbose_name='品牌ID')), ('provider_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='')), ('goods_number', models.IntegerField(blank=True, null=True, verbose_name='品牌ID')), ('goods_weight', models.FloatField(blank=True, null=True, verbose_name='')), ('market_price', models.FloatField(blank=True, null=True, verbose_name='市场价')), ('shop_price', models.FloatField(blank=True, null=True, verbose_name='销售价')), ('promote_price', models.FloatField(blank=True, null=True, verbose_name='促销价')), ('promote_start_date', models.DateField(blank=True, null=True, verbose_name='促销开始日期')), ('promote_end_date', models.DateField(blank=True, null=True, verbose_name='促销开始日期')), ('warn_number', models.IntegerField(blank=True, null=True, verbose_name='')), ('keywords', models.CharField(blank=True, max_length=256, null=True, verbose_name='关键词')), ('goods_brief', models.CharField(blank=True, max_length=1024, null=True, verbose_name='货物简介')), ('goods_desc', models.TextField(blank=True, null=True, verbose_name='货物详细')), ('goods_thumb', models.CharField(blank=True, max_length=64, null=True, verbose_name='')), ('goods_img', models.CharField(blank=True, max_length=64, null=True, verbose_name='')), ('original_img', models.CharField(blank=True, max_length=64, null=True, verbose_name='')), ('is_real', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否审核')), ('extension_code', models.CharField(blank=True, max_length=64, null=True, verbose_name='')), ('integral', models.IntegerField(blank=True, null=True, verbose_name='')), ('add_time', models.DateTimeField(blank=True, null=True, verbose_name='添加时间')), ('sort_order', models.IntegerField(blank=True, null=True, verbose_name='排序')), ('is_delete', models.BooleanField(blank=True, default=False, null=True, verbose_name='是否删除')), ('is_best', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否最好')), ('is_new', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否最新')), ('is_hot', models.BooleanField(blank=True, default=False, null=True, verbose_name='是否最热')), ('is_promote', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否公开')), ('bonus_type_id', models.IntegerField(blank=True, null=True, verbose_name='利润类型')), ('last_update', models.DateTimeField(blank=True, null=True, verbose_name='更新时间')), ('goods_type', models.IntegerField(blank=True, null=True, verbose_name='商品类型，促销有用')), ('goods_info', models.CharField(blank=True, max_length=10000, null=True, verbose_name='商品属性')), ('seller_note', models.CharField(blank=True, max_length=64, null=True, verbose_name='票据信息')), ('give_integral', models.IntegerField(blank=True, default=0, null=True, verbose_name='积分')), ('comment_status', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否评论')), ('warehouse_id', models.IntegerField(blank=True, null=True, verbose_name='仓库ID')), ('goods_status', models.IntegerField(blank=True, default=0, null=True, verbose_name='商品上下架，-1是回收站，0是缺货，1是下架')), ('is_taozhuang', models.BooleanField(blank=True, default=False, null=True, verbose_name='是否套餐')), ('gift_id', models.IntegerField(blank=True, null=True, verbose_name='赠品ID')), ('series_id', models.IntegerField(blank=True, null=True, verbose_name='系列ID')), ('reserved_field', models.CharField(blank=True, max_length=64, null=True, verbose_name='保留字段')), ], ), migrations.CreateModel( name='SmGoodsCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cat_name', models.CharField(blank=True, max_length=256, null=True, verbose_name='目录名称')), ('keywords', models.CharField(blank=True, max_length=256, null=True, verbose_name='关键字')), ('cat_desc', models.CharField(blank=True, max_length=256, null=True, verbose_name='目录描述')), ('parent_id', models.IntegerField(blank=True, null=True, verbose_name='父ID')), ('g_level', models.IntegerField(blank=True, null=True, verbose_name='层级')), ('sort_order', models.IntegerField(blank=True, null=True, verbose_name='排序')), ('template_file', models.CharField(blank=True, max_length=256, null=True, verbose_name='')), ('measure_unit', models.CharField(blank=True, max_length=256, null=True, verbose_name='')), ('show_in_nav', models.IntegerField(blank=True, null=True, verbose_name='')), ('style', models.CharField(blank=True, max_length=256, null=True, verbose_name='')), ('is_show', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否显示')), ('grade', models.IntegerField(blank=True, null=True, verbose_name='')), ('filter_attr', models.IntegerField(blank=True, null=True, verbose_name='')), ('site_id', models.IntegerField(blank=True, default=0, null=True, verbose_name='')), ], ), migrations.CreateModel( name='SmOrderGoods', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('order_id', models.IntegerField(blank=True, null=True, verbose_name='订单编号开发用')), ('goods_id', models.IntegerField(blank=True, default=0, null=True, verbose_name='商品编号')), ('goods_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='商品')), ('goods_sn', models.CharField(blank=True, max_length=64, null=True, verbose_name='货号')), ('goods_number', models.IntegerField(blank=True, default=1, null=True, verbose_name='数量')), ('market_price', models.FloatField(blank=True, null=True, verbose_name='市价')), ('goods_price', models.FloatField(blank=True, null=True, verbose_name='商品价')), ('goods_old_price', models.FloatField(blank=True, null=True, verbose_name='临时变量，保存因为折扣用的价格在里面，没怎么用')), ('goods_attr', models.CharField(blank=True, max_length=1024, null=True, verbose_name='商品口属性')), ('send_number', models.IntegerField(blank=True, default=0, null=True, verbose_name='')), ('is_real', models.IntegerField(blank=True, default=1, null=True, verbose_name='')), ('parent_id', models.IntegerField(blank=True, null=True, verbose_name='优惠券')), ('is_gift', models.BooleanField(blank=True, default=False, null=True, verbose_name='是否赠品')), ('add_time', models.DateTimeField(auto_now_add=True)), ('is_active', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否显示')), ('goods_type', models.IntegerField(blank=True, null=True, verbose_name='商品类型，用于打折')), ('admin_id', models.IntegerField(blank=True, null=True, verbose_name='操作人')), ('shop_price', models.FloatField(blank=True, null=True, verbose_name='商品实际单价，等于折扣后的价格*数量')), ('bramd_id', models.IntegerField(blank=True, null=True, verbose_name='品牌ID')), ('bramd_name', models.CharField(blank=True, max_length=64, null=True, verbose_name='品牌')), ('comment_status', models.BooleanField(blank=True, default=True, null=True, verbose_name='是否评论')), ], ), ]

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9

698ecde81b62aeaa9bf3fe5a0d960ad9b9475ac1

99,441

py

Python

source_code/icesatIO.py

carlos-alberto-silva/PhoREAL

4e582d6c4e2ddc1830dc2692ae136f9b5c80c9d8

[ "BSD-4-Clause-UC" ]

2

2020-02-20T16:48:17.000Z

2021-01-09T17:42:23.000Z

source_code/icesatIO.py

dpoursanidis/PhoREAL

4e582d6c4e2ddc1830dc2692ae136f9b5c80c9d8

[ "BSD-4-Clause-UC" ]

null

source_code/icesatIO.py

dpoursanidis/PhoREAL

4e582d6c4e2ddc1830dc2692ae136f9b5c80c9d8

[ "BSD-4-Clause-UC" ]

2

2020-02-14T23:12:38.000Z

2020-03-24T19:57:56.000Z

# -*- coding: utf-8 -*- """ Script that provides basic I/O functionality for ATL03 Copyright 2019 Applied Research Laboratories, University of Texas at Austin This package is free software; the copyright holder gives unlimited permission to copy and/or distribute, with or without modification, as long as this notice is preserved. Authors: Mike Alonzo Eric Guenther Date: September 20, 2019 """ # Import modules import os import sys import warnings import csv import numpy as np import h5py import laspy from laspy.file import File from scipy.io import loadmat import simplekml # Object for readKmlBounds function class kmlStruct: # Define class with designated fields def __init__(self, regionName, lonMin, lonMax, latMin, latMax,headerFilePath, truthFilePath): self.regionName = regionName self.lonMin = lonMin self.lonMax = lonMax self.latMin = latMin self.latMax = latMax self.headerFilePath = headerFilePath self.truthFilePath = truthFilePath # Object for readHeaderFile function class headerStruct: # Define class with designated fields def __init__(self, coordType, zone, hemi, ellipsoid, xmin, xmax, ymin, ymax, tileName): self.coordType = coordType self.zone = zone self.hemi = hemi self.ellipsoid = ellipsoid self.xmin = np.c_[xmin] self.xmax = np.c_[xmax] self.ymin = np.c_[ymin] self.ymax = np.c_[ymax] self.tileName = np.c_[tileName] # Object for readLas function class lasStruct: # Define class with designated fields def __init__(self, x, y, z, classification, intensity, headerData): self.x = np.c_[x] self.y = np.c_[y] self.z = np.c_[z] self.classification = np.c_[classification] self.intensity = np.c_[intensity] self.headerData = np.c_[headerData] # Object for readGeoidFile function class geoidStruct: # Define class with designated fields def __init__(self, lats, lons, geoidalHeights): self.lats = lats self.lons = lons self.geoidalHeights = geoidalHeights ##### Function to read kmlBounds.txt def readTruthRegionsTxtFile(kmlBoundsTextFile): # Initialize output parameters regionName = [] lonMin = [] lonMax = [] latMin = [] latMax = [] headerFilePath = [] truthFilePath = [] # Open file for reading f = open(kmlBoundsTextFile,'r') # Get all lines of file into a list allLines = list(f) # Close file for reading f.close() # Read lines with path info headerPathLine = allLines[2] headerPath = headerPathLine.split(',')[1].strip() truthPathLine = allLines[3] truthPath = truthPathLine.split(',')[1].strip() # Read rest of lines, skip first six lines (comments) textLines = allLines[6:] # Loop through each line in text file for line in textLines: # If line text exists if line: # Split line by commas fields = line.split(',') # Store field names into lists regionName.append(fields[0].strip()) lonMin.append(float(fields[1].strip())) lonMax.append(float(fields[2].strip())) latMin.append(float(fields[3].strip())) latMax.append(float(fields[4].strip())) headerFilePath.append(headerPath + fields[5].strip()) truthFilePath.append(truthPath + fields[6].strip()) # Endif # Endfor # Call class to populate field names kmlInfo = kmlStruct(regionName, lonMin, lonMax, latMin, latMax, headerFilePath, truthFilePath) # Return output return kmlInfo ##### Function to read header truth .mat file def readHeaderMatFile(headerFilePath): # Initialize output data coordType = [] zone = [] hemi = [] # Get coordinate type from header .mat file (1 = UTM, 2 = Lat/Lon) matData = loadmat(headerFilePath) coordNum= matData['headerData'][0][0][10][0][0] # Convert lat/lon data to UTM coordinates if(coordNum==1): coordType = 'UTM' # Get UTM zone and hemisphere zone = str(matData['headerData'][0][0][7][0][0]) hemi = matData['headerData'][0][0][8][0][0] ellipsoid = matData['headerData'][0][0][9][0][0] else: coordType = 'Lat/Lon' # Endif # Get x/y min/max data and truth tile name for each truth tile xmin = [matData['headerData'][0][i][0][0][0] for i in range(len(matData['headerData'][0]))] xmax = [matData['headerData'][0][i][1][0][0] for i in range(len(matData['headerData'][0]))] ymin = [matData['headerData'][0][i][2][0][0] for i in range(len(matData['headerData'][0]))] ymax = [matData['headerData'][0][i][3][0][0] for i in range(len(matData['headerData'][0]))] tileName = [matData['headerData'][0][i][12][0] for i in range(len(matData['headerData'][0]))] # Store data as object headerData = headerStruct(coordType, zone, hemi, ellipsoid, xmin, xmax, ymin, ymax, tileName) # Return data return headerData ##### Functions to read ATL03 .h5 files def readAtl03H5(in_file03, fieldName, label): # fieldName Options: # lat_ph # lon_ph # h_ph # delta_time # crossing_time # signal_conf_ph if not os.path.isfile(in_file03): print('ATL03 file does not exist') try: with h5py.File(in_file03, 'r') as f: dsname=''.join([label,'/heights/', fieldName]) if dsname in f: dataOut = np.array(f[dsname]) if(fieldName == 'signal_conf_ph'): dataOut = dataOut[:,0] else: dataOut = [] except Exception as e: print('Python message: %s\n' % e) return dataOut ##### Functions to read ATL08 .h5 files def readAtl08H5(in_file08, fieldName, label): # fieldName Options: # /land_segments/longitude # /land_segments/latitude # /land_segments/canopy/h_max_canopy_abs # /land_segments/terrain/h_te_best_fit # /land_segments/terrain/h_te_median if not os.path.isfile(in_file08): print('ATL03 file does not exist') try: with h5py.File(in_file08, 'r') as f: dsname=''.join([label, fieldName]) if dsname in f: dataOut = np.array(f[dsname]) else: dataOut = [] except Exception as e: print('Python message: %s\n' % e) return dataOut ##### Function to read ATL03 .h5 files for mapping def readAtl03DataMapping(in_file03, label): # # Reads the data from ATL03 # # Open the file # if not os.path.isfile(in_file03): print('File does not exist') try: f = h5py.File(in_file03, 'r') except Exception as e: print('Python message: %s\n' % e) # endif # # segment_ph_cnt # # # segment_id # dsname=label+'/geolocation/segment_id' if dsname in f: segment_id=np.array(f[dsname]) else: segment_id=[] # endif # # segment_lat # # # ph_index_beg # dsname=label+'/geolocation/ph_index_beg' if dsname in f: ph_index_beg=np.array(f[dsname]) else: ph_index_beg=[] # endif # # # Close the file # f.close() return ph_index_beg, segment_id ##### Function to read ATL08 .h5 files for mapping def readAtl08DataMapping(in_file08, label): # # Reads the data from ATL08 # # Open the file # if not os.path.isfile(in_file08): print('File does not exist') try: f = h5py.File(in_file08, 'r') except Exception as e: print('Python message: %s\n' % e) # endif # # classed_pc_indx # dsname=label+'/signal_photons/classed_pc_indx' if dsname in f: classed_pc_indx=np.array(f[dsname]) else: classed_pc_indx=[] # endif # # classed_pc_flag # dsname=label+'/signal_photons/classed_pc_flag' if dsname in f: classed_pc_flag=np.array(f[dsname]) else: classed_pc_flag=[] # endif # # d_flag # # seg08_id # dsname=label+'/signal_photons/ph_segment_id' if dsname in f: seg08_id=np.array(f[dsname]) else: seg08_id=[] # endif # # # Close the file # f.close() return classed_pc_indx, classed_pc_flag, seg08_id ##### Function to read geoid .mat file def readGeoidFile(geoidFile): # Read .mat file matFile = os.path.normpath(geoidFile) matData = loadmat(matFile) # Get lats, lons, and geoidal heights lats = matData['geoid']['lats'][0][0] lons = matData['geoid']['lons'][0][0] geoidalHeights = matData['geoid']['geoidalHeight'][0][0] # Store data as an object geoid = geoidStruct(lats, lons, geoidalHeights) # Return output return geoid ##### Function to read .las files def readLas(lasFilePath): # Read contents of .las file with File(lasFilePath, mode = 'r') as lasFile: # Store output from .las file x = lasFile.x y = lasFile.y z = lasFile.z classification = lasFile.classification intensity = lasFile.intensity headerData = lasFile.header # Store output into class structure lasData = lasStruct(x, y, z, classification, intensity, headerData) # EndWith return lasData ##### Functions to write .las files def selectwkt(proj,hemi=None,zone=None): if proj.lower() == "utm": if zone: zone = str(zone) if hemi.lower() == "n": if zone == "1": wkt = b'''PROJCS["WGS 84 / UTM zone 1N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-177],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32601"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "2": wkt = b'''PROJCS["WGS 84 / UTM zone 2N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-171],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32602"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "3": wkt == b'''ROJCS["WGS 84 / UTM zone 3N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-165],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32603"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "4": wkt = b'''PROJCS["WGS 84 / UTM zone 4N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-159],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32604"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "5": wkt = b'''PROJCS["WGS 84 / UTM zone 5N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-153],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32605"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "6": wkt = b'''PROJCS["WGS 84 / UTM zone 6N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-147],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32606"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "7": wkt = b'''PROJCS["WGS 84 / UTM zone 7N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-141],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32607"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "8": wkt = b'''PROJCS["WGS 84 / UTM zone 8N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-135],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32608"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "9": wkt = b'''PROJCS["WGS 84 / UTM zone 9N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-129],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32609"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "10": wkt = b'''PROJCS["WGS 84 / UTM zone 10N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-123],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32610"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "11": wkt = b'''PROJCS["WGS 84 / UTM zone 11N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-117],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32611"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "12": wkt = b'''PROJCS["WGS 84 / UTM zone 12N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-111],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32612"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "13": wkt = b'''PROJCS["WGS 84 / UTM zone 13N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32613"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "14": wkt = b'''PROJCS["WGS 84 / UTM zone 14N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-99],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32614"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "15": wkt = b'''PROJCS["WGS 84 / UTM zone 15N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32615"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "16": wkt = b'''PROJCS["WGS 84 / UTM zone 16N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-87],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32616"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "17": wkt = b'''PROJCS["WGS 84 / UTM zone 17N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-81],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32617"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "18": wkt = b'''PROJCS["WGS 84 / UTM zone 18N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-75],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32618"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "19": wkt = b'''PROJCS["WGS 84 / UTM zone 19N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-69],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32619"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "20": wkt = b'''PROJCS["WGS 84 / UTM zone 20N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-63],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32620"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "21": wkt = b'''PROJCS["WGS 84 / UTM zone 21N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-57],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32621"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "22": wkt = b'''PROJCS["WGS 84 / UTM zone 22N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-51],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32622"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "23": wkt = b'''PROJCS["WGS 84 / UTM zone 23N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-45],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32623"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "24": wkt = b'''PROJCS["WGS 84 / UTM zone 24N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-39],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32624"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "25": wkt = b'''PROJCS["WGS 84 / UTM zone 25N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-33],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32625"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "26": wkt = b'''PROJCS["WGS 84 / UTM zone 26N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-27],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32626"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "27": wkt = b'''PROJCS["WGS 84 / UTM zone 27N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-21],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32627"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "28": wkt = b'''PROJCS["WGS 84 / UTM zone 28N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32628"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "29": wkt = b'''PROJCS["WGS 84 / UTM zone 29N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32629"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "30": wkt = b'''PROJCS["WGS 84 / UTM zone 30N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-3],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32630"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "31": wkt = b'''PROJCS["WGS 84 / UTM zone 31N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",3],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32631"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "32": wkt = b'''PROJCS["WGS 84 / UTM zone 32N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32632"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "33": wkt = b'''PROJCS["WGS 84 / UTM zone 33N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32633"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "34": wkt = b'''PROJCS["WGS 84 / UTM zone 34N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",21],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32634"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "35": wkt = b'''PROJCS["WGS 84 / UTM zone 35N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",27],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32635"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "36": wkt = b'''PROJCS["WGS 84 / UTM zone 36N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",33],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32636"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "37": wkt = b'''PROJCS["WGS 84 / UTM zone 37N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",39],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32637"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "38": wkt = b'''PROJCS["WGS 84 / UTM zone 38N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",45],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32638"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "39": wkt = b'''PROJCS["WGS 84 / UTM zone 39N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",51],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32639"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "40": wkt = b'''PROJCS["WGS 84 / UTM zone 40N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",57],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32640"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "41": wkt = b'''PROJCS["WGS 84 / UTM zone 41N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",63],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32641"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "42": wkt = b'''PROJCS["WGS 84 / UTM zone 42N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",69],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32642"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "43": wkt = b'''PROJCS["WGS 84 / UTM zone 43N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",75],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32643"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "44": wkt = b'''PROJCS["WGS 84 / UTM zone 44N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",81],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32644"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "45": wkt = b'''PROJCS["WGS 84 / UTM zone 45N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",87],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32645"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "46": wkt = b'''PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32646"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "47": wkt = b'''PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32646"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "48": wkt = b'''PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32648"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "49": wkt = b'''PROJCS["WGS 84 / UTM zone 49N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",111],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32649"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "50": wkt = b'''PROJCS["WGS 84 / UTM zone 50N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",117],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32650"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "51": wkt = b'''PROJCS["WGS 84 / UTM zone 51N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",123],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32651"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "52": wkt = b'''PROJCS["WGS 84 / UTM zone 52N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",129],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32652"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "53": wkt = b'''PROJCS["WGS 84 / UTM zone 53N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",135],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32653"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "54": wkt = b'''PROJCS["WGS 84 / UTM zone 54N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",141],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32654"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "55": wkt = b'''PROJCS["WGS 84 / UTM zone 55N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",147],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32655"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "56": wkt = b'''PROJCS["WGS 84 / UTM zone 56N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",153],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32656"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "57": wkt = b'''PROJCS["WGS 84 / UTM zone 57N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",159],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32657"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "58": wkt = b'''PROJCS["WGS 84 / UTM zone 58N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",165],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32658"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "59": wkt = b'''PROJCS["WGS 84 / UTM zone 59N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",171],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32659"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "60": wkt = b'''PROJCS["WGS 84 / UTM zone 60N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",177],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],AUTHORITY["EPSG","32660"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif hemi.lower() == "s": if zone == "1": wkt = b'''PROJCS["WGS 84 / UTM zone 1S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-177],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32701"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "2": wkt = b'''PROJCS["WGS 84 / UTM zone 2S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-171],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32702"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "3": wkt = b'''PROJCS["WGS 84 / UTM zone 3S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-165],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32703"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "4": wkt = b'''PROJCS["WGS 84 / UTM zone 4S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-159],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32704"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "5": wkt = b'''PROJCS["WGS 84 / UTM zone 5S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-153],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32705"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "6": wkt = b'''PROJCS["WGS 84 / UTM zone 6S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-147],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32706"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "7": wkt = b'''PROJCS["WGS 84 / UTM zone 7S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-141],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32707"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "8": wkt = b'''PROJCS["WGS 84 / UTM zone 8S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-135],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32708"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "9": wkt = b'''PROJCS["WGS 84 / UTM zone 9S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-129],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32709"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "10": wkt = b'''PROJCS["WGS 84 / UTM zone 10S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-123],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32710"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "11": wkt = b'''PROJCS["WGS 84 / UTM zone 11S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-117],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32711"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "12": wkt = b'''PROJCS["WGS 84 / UTM zone 12S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-111],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32712"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "13": wkt = b'''PROJCS["WGS 84 / UTM zone 13S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32713"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "14": wkt = b'''PROJCS["WGS 84 / UTM zone 14S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-99],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32714"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "15": wkt = b'''PROJCS["WGS 84 / UTM zone 15S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32715"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "16": wkt = b'''PROJCS["WGS 84 / UTM zone 16S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-87],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32716"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "17": wkt = b'''PROJCS["WGS 84 / UTM zone 17S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-81],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32717"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "18": wkt = b'''PROJCS["WGS 84 / UTM zone 18S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-75],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32718"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "19": wkt = b'''PROJCS["WGS 84 / UTM zone 19S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-69],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32719"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "20": wkt = b'''PROJCS["WGS 84 / UTM zone 20S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-63],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32720"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "21": wkt = b'''PROJCS["WGS 84 / UTM zone 21S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-57],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32721"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "22": wkt = b'''PROJCS["WGS 84 / UTM zone 22S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-51],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32722"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "23": wkt = b'''PROJCS["WGS 84 / UTM zone 23S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-45],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32723"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "24": wkt = b'''PROJCS["WGS 84 / UTM zone 24S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-39],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32724"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "25": wkt = b'''PROJCS["WGS 84 / UTM zone 25S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-33],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32725"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "26": wkt = b'''PROJCS["WGS 84 / UTM zone 26S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-27],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32726"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "27": wkt = b'''PROJCS["WGS 84 / UTM zone 27S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-21],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32727"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "28": wkt = b'''PROJCS["WGS 84 / UTM zone 28S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32728"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "29": wkt = b'''PROJCS["WGS 84 / UTM zone 29S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32729"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "30": wkt = b'''PROJCS["WGS 84 / UTM zone 30S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-3],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32730"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "31": wkt = b'''PROJCS["WGS 84 / UTM zone 31S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",3],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32731"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "32": wkt = b'''PROJCS["WGS 84 / UTM zone 32S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32732"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "33": wkt = b'''PROJCS["WGS 84 / UTM zone 33S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32733"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "34": wkt = b'''PROJCS["WGS 84 / UTM zone 34S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",21],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32734"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "35": wkt = b'''PROJCS["WGS 84 / UTM zone 35S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",27],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32735"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "36": wkt = b'''PROJCS["WGS 84 / UTM zone 36S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",33],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32736"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "37": wkt = b'''PROJCS["WGS 84 / UTM zone 37S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",39],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32737"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "38": wkt = b'''PROJCS["WGS 84 / UTM zone 38S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",45],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32738"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "39": wkt = b'''PROJCS["WGS 84 / UTM zone 39S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",51],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32739"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "40": wkt = b'''PROJCS["WGS 84 / UTM zone 40S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",57],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32740"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "41": wkt = b'''PROJCS["WGS 84 / UTM zone 41S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",63],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32741"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "42": wkt = b'''PROJCS["WGS 84 / UTM zone 42S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",69],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32742"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "43": wkt = b'''PROJCS["WGS 84 / UTM zone 43S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",75],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32743"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "44": wkt = b'''PROJCS["WGS 84 / UTM zone 44S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",81],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32744"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "45": wkt = b'''PROJCS["WGS 84 / UTM zone 45S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",87],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32745"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "46": wkt = b'''PROJCS["WGS 84 / UTM zone 46S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32746"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "47": wkt = b'''PROJCS["WGS 84 / UTM zone 47S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",99],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32747"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "48": wkt = b'''PROJCS["WGS 84 / UTM zone 48S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32748"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "49": wkt = b'''PROJCS["WGS 84 / UTM zone 49S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",111],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32749"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "50": wkt = b'''PROJCS["WGS 84 / UTM zone 50S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",117],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32750"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "51": wkt = b'''PROJCS["WGS 84 / UTM zone 51S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",123],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32751"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "52": wkt = b'''PROJCS["WGS 84 / UTM zone 52S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",129],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32752"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "53": wkt = b'''PROJCS["WGS 84 / UTM zone 53S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",135],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32753"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "54": wkt = b'''PROJCS["WGS 84 / UTM zone 54S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",141],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32754"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "55": wkt = b'''PROJCS["WGS 84 / UTM zone 55S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",147],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32755"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "56": wkt = b'''PROJCS["WGS 84 / UTM zone 56S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",153],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32756"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "57": wkt = b'''PROJCS["WGS 84 / UTM zone 57S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",159],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32757"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "58": wkt = b'''PROJCS["WGS 84 / UTM zone 58S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",165],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32758"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "59": wkt = b'''PROJCS["WGS 84 / UTM zone 59S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",171],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32759"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif zone == "60": wkt = b'''PROJCS["WGS 84 / UTM zone 60S",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],UNIT["metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",177],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],AUTHORITY["EPSG","32760"],AXIS["Easting",EAST],AXIS["Northing",NORTH]]''' elif proj.lower() == "wgs84": wkt = b'''GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]]''' else: print("No defined Projected Coordinate System Selected") return wkt def writeLas(xx,yy,zz,proj,output_file,classification,intensity,hemi=None,zone=None): wkt = selectwkt(proj,hemi,zone) #Create new VLR new_vlr = laspy.header.VLR(user_id = "LASF_Projection", record_id = 2112, VLR_body = wkt, description = "OGC Coordinate System WKT") inVLRs = [] inVLRs.append(new_vlr) #Create new Header hdr = laspy.header.Header() hdr.file_sig = 'LASF' #Create new las file with Header and VLR outfile = laspy.file.File(output_file, mode="w", header=hdr) outfile.header.vlrs = inVLRs outfile.header.set_wkt = 1 #Establish offset xmin = np.min(xx) ymin = np.min(yy) zmin = np.min(zz) xmax = np.max(xx) ymax = np.max(yy) zmax = np.max(zz) #Calculate x, y, and z scale factor if xmax == xmin: xscale = 1 else: xscale = (xmax - xmin) / 100000000; if ymax == ymin: yscale = 1 else: yscale = (ymax - ymin) / 100000000; if zmax == zmin: zscale = 1 else: zscale = (zmax - zmin) / 100000000; in_scale = [xscale, yscale, zscale] outfile.header.offset = [xmin,ymin,zmin] #Establish scale outfile.header.scale = in_scale #Write x, y, z data and if available classification and intensity data outfile.x = xx outfile.y = yy outfile.z = zz if classification is not None: outfile.raw_classification = classification if intensity is not None: outfile.intensity = intensity #Close las outfile.close() ##### Functions to write .kml files def writeKml(lat, lon, time, kmlName): # Suppress warnings that may come from simple kml if not sys.warnoptions: warnings.simplefilter("ignore") # endif # Open Simple KML kml = simplekml.Kml() # Plot line for ground track latLon = np.column_stack((lon, lat)) latLonTuple = tuple(latLon) ls = kml.newlinestring(name = 'test', coords=latLonTuple) ls.extrude = 1 ls.altitudemode = simplekml.AltitudeMode.clamptoground ls.style.linestyle.width = 5 ls.style.linestyle.color = simplekml.Color.blue # Open Simple KML style editor style = simplekml.Style() style.iconstyle.icon.href = 'http://maps.google.com/mapfiles/kml/shapes/placemark_circle.png' # Loop through all lat/lon values and make KML markers for i in range(0,len(lon)): # Get time string timeRounded = str(np.round(time[i],1)) + ' sec' # Plot marker points pnt = kml.newpoint(name = timeRounded, coords=[(lon[i][0], lat[i][0])]) pnt.style = style # EndFor # Save output KML file kml.save(kmlName) def writeArrayToCSV(csv_out,namelist,datalist): if datalist: in_data = datalist[0] if len(datalist) > 0: for data in datalist[1:]: in_data = np.column_stack((in_data,data)) with open(csv_out, 'w', newline = '') as csvFile: writer = csv.writer(csvFile) writer.writerow(namelist) writer.writerows(in_data) csvFile.close def writeATL08toCSV(in_file08,groundtrack,csv_out): delta_time = readAtl08H5(in_file08, '/land_segments/delta_time', groundtrack) lat = readAtl08H5(in_file08, '/land_segments/latitude', groundtrack) lon = readAtl08H5(in_file08, '/land_segments/longitude', groundtrack) h_max_canopy_abs = readAtl08H5(in_file08, '/land_segments/canopy/h_max_canopy_abs', groundtrack) h_te_best_fit = readAtl08H5(in_file08, '/land_segments/terrain/h_te_best_fit', groundtrack) h_te_median = readAtl08H5(in_file08, '/land_segments/terrain/h_te_median', groundtrack) namelist = ['Delta Time','Latitude','Longitude', 'Absolute Max Canopy Height','Best Fit Ground Height', 'Median Ground Height'] datalist = [delta_time,lat,lon,h_max_canopy_abs,h_te_best_fit,h_te_median] writeArrayToCSV(csv_out,namelist,datalist) def writeATL03toCSV(in_file03,groundtrack,csv_out): delta_time = readAtl03H5(in_file03, 'delta_time', groundtrack) lat = readAtl03H5(in_file03, 'lat_ph', groundtrack) lon = readAtl03H5(in_file03, 'lon_ph', groundtrack) h_ph = readAtl03H5(in_file03, 'h_ph', groundtrack) signal_conf_ph = readAtl03H5(in_file03, 'signal_conf_ph', groundtrack) namelist = ['Delta Time','Latitude','Longitude','Height', 'Signal Confidence'] datalist = [delta_time,lat,lon,h_ph,signal_conf_ph] writeArrayToCSV(csv_out,namelist,datalist) def createHTMLChart(ytrack, h_ph, classification, classification_list = [1,2,3],output_folder = "", in_file03_name = "ATL03", blank = "Viewer_blank.html"): total_photons = 20000 classification_list = [1,2,3] num_returns = 0 classification_to_list = classification.tolist() for class_num in classification_list: num_returns = num_returns + classification_to_list.count(class_num) file_returns = int(np.ceil(num_returns/total_photons)) start = 0 for i in range(0,file_returns): end = min([(start + total_photons),num_returns]) viewer_output = ("Viewer_" + in_file03_name + "_" + str(start) + "_to_" + str(end) + ".html") #Copy the Blank Template into with open(blank) as f: lines = f.readlines() lines = [l for l in lines] with open(viewer_output, "w") as f1: f1.writelines(lines) #Read file and load it to memory with open(viewer_output, "r") as in_file: buf = in_file.readlines() #Write data into the HTML file with open(viewer_output, "w") as out_file: for line in buf: if line == "var data = [\n": j = i * total_photons while j < end: if ((classification[j] == 0) & (0 in classification_list)): line = line + ("{ytrack: " + str(ytrack[j]) + ", zheight: " + str(h_ph[j]) + ", color: '#C2C5CC' }, \n") elif ((classification[j] == 1) & (1 in classification_list)): line = line + ("{ytrack: " + str(ytrack[j]) + ", zheight: " + str(h_ph[j]) + ", color: '#D2B826' }, \n") elif ((classification[j] == 2) & (2 in classification_list)): line = line + ("{ytrack: " + str(ytrack[j]) + ", zheight: " + str(h_ph[j]) + ", color: '#45811A' }, \n") elif ((classification[j] == 3) & (3 in classification_list)): line = line + ("{ytrack: " + str(ytrack[j]) + ", zheight: " + str(h_ph[j]) + ", color: '#85F334' }, \n") j += 1 out_file.write(line) start = start + total_photons

116.441452

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116.441452

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0e0f19ffc2331f8d79b2f20a09ef4e866816f3e8

15,773

py

Python

tests/test_dask_image/test_ndmorph/test_ndmorph.py

jakirkham/dask-image

f28094d4ee705b015f3437ed60a9b0495031b156

[ "BSD-3-Clause" ]

null

tests/test_dask_image/test_ndmorph/test_ndmorph.py

jakirkham/dask-image

f28094d4ee705b015f3437ed60a9b0495031b156

[ "BSD-3-Clause" ]

null

tests/test_dask_image/test_ndmorph/test_ndmorph.py

jakirkham/dask-image

f28094d4ee705b015f3437ed60a9b0495031b156

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import absolute_import import pytest import numpy as np import scipy.ndimage as spnd import dask.array as da import dask.array.utils as dau import dask_image.ndmorph as da_ndm @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "err_type, input, structure, origin", [ ( RuntimeError, da.ones([1, 2], dtype=bool, chunks=(1, 2,)), da.arange(2, dtype=bool, chunks=(2,)), 0 ), ( TypeError, da.arange(2, dtype=bool, chunks=(2,)), 2.0, 0 ), ( TypeError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 0.0 ), ] ) def test_errs_binary_ops(funcname, err_type, input, structure, origin): da_func = getattr(da_ndm, funcname) with pytest.raises(err_type): da_func( input, structure=structure, origin=origin ) @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "err_type, input, structure, iterations, origin", [ ( TypeError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 1.0, 0 ), ( NotImplementedError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 0, 0 ) ] ) def test_errs_binary_ops_iter(funcname, err_type, input, structure, iterations, origin): da_func = getattr(da_ndm, funcname) with pytest.raises(err_type): da_func( input, structure=structure, iterations=iterations, origin=origin ) @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "err_type, input, structure, iterations, mask, border_value, origin" ", brute_force", [ ( RuntimeError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 1, da.arange(2, dtype=bool, chunks=(2,))[None], 0, 0, False ), ( TypeError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 1, da.arange(2, dtype=bool, chunks=(2,)), 2.0, 0, False ), ( NotImplementedError, da.ones([2], dtype=bool, chunks=(2,)), da.arange(2, dtype=bool, chunks=(2,)), 1, da.arange(2, dtype=bool, chunks=(2,)), 0, 0, True ), ] ) def test_errs_binary_ops_expanded(funcname, err_type, input, structure, iterations, mask, border_value, origin, brute_force): da_func = getattr(da_ndm, funcname) with pytest.raises(err_type): da_func( input, structure=structure, iterations=iterations, mask=mask, border_value=border_value, origin=origin, brute_force=brute_force ) @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "input, structure, origin", [ ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), None, 0 ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 0 ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 1 ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), -1 ), ] ) def test_binary_ops(funcname, input, structure, origin): da_func = getattr(da_ndm, funcname) sp_func = getattr(spnd, funcname) da_result = da_func( input, structure=structure, origin=origin ) sp_result = sp_func( input, structure=structure, origin=origin ) dau.assert_eq(sp_result, da_result) @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "input, structure, iterations, origin", [ ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 3, 0 ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 3, 1 ), ] ) def test_binary_ops_iter(funcname, input, structure, iterations, origin): da_func = getattr(da_ndm, funcname) sp_func = getattr(spnd, funcname) da_result = da_func( input, structure=structure, iterations=iterations, origin=origin ) sp_result = sp_func( input, structure=structure, iterations=iterations, origin=origin ) dau.assert_eq(sp_result, da_result) @pytest.mark.parametrize( "funcname", [ "binary_closing", "binary_dilation", "binary_erosion", "binary_opening", ] ) @pytest.mark.parametrize( "input, structure, iterations, mask, border_value, origin, brute_force", [ ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 1, None, 1, 0, False ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 1, da.from_array( np.array( [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool ), chunks=(5, 6) ), 0, 0, False ), ( da.from_array( np.array( [[0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1], [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1], [0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0], [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0]], dtype=bool ), chunks=(5, 6) ), np.ones([3, 3], dtype=bool), 3, da.from_array( np.array( [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool ), chunks=(5, 6) ), 0, 0, False ), ] ) def test_binary_ops_expanded(funcname, input, structure, iterations, mask, border_value, origin, brute_force): da_func = getattr(da_ndm, funcname) sp_func = getattr(spnd, funcname) da_result = da_func( input, structure=structure, iterations=iterations, mask=mask, border_value=border_value, origin=origin, brute_force=brute_force ) sp_result = sp_func( input, structure=structure, iterations=iterations, mask=mask, border_value=border_value, origin=origin, brute_force=brute_force ) dau.assert_eq(sp_result, da_result)

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12

38534ca19054395ae02d1e9c3c8cd593669073ed

3,393

py

Python

ModernWarfare/XAssets/kiosks.py

Mario-Kart-Felix/Hyde

eaaae703cf04752caa009a93c3928959de8047bd

[ "MIT" ]

14

2020-05-01T13:54:48.000Z

2022-02-14T21:58:35.000Z

ModernWarfare/XAssets/kiosks.py

Mario-Kart-Felix/Hyde

eaaae703cf04752caa009a93c3928959de8047bd

[ "MIT" ]

3

2020-06-09T19:24:48.000Z

2021-03-06T11:34:04.000Z

ModernWarfare/XAssets/kiosks.py

Mario-Kart-Felix/Hyde

eaaae703cf04752caa009a93c3928959de8047bd

[ "MIT" ]

4

2020-05-24T19:15:08.000Z

2022-02-04T21:20:29.000Z

import logging from typing import Any, Dict, List, TypedDict from utility import Utility log: logging.Logger = logging.getLogger(__name__) class BRKioskPurchases(TypedDict): """Structure of mp/brkioskpurchases.csv""" index: int type: str ref: str cost: int title: str desc: str icon: str tabNum: int slotLabel: str fireSaleDiscount: int perkDiscount: int overrideFileOnly: int # bool class BRKioskPurchasesTruckWar(TypedDict): """Structure of mp/brkioskpurchases_truckwar.csv""" index: int type: str ref: str cost: int title: str desc: str icon: str tabNum: int slotLabel: str fireSaleDiscount: int perkDiscount: int overrideFileOnly: int # bool class KioskBR: """Battle Royale Kiosk Purchases XAssets.""" def Compile(self: Any) -> None: """Compile the Battle Royale Kiosk Purchases XAssets.""" items: List[Dict[str, Any]] = [] items = KioskBR.IDs(self, items) Utility.WriteFile(self, f"{self.eXAssets}/kioskBR.json", items) log.info(f"Compiled {len(items):,} Kiosk Items (BR)") def IDs(self: Any, items: List[Dict[str, Any]]) -> List[Dict[str, Any]]: """Compile the mp/brkioskpurchases.csv XAsset.""" ids: List[Dict[str, Any]] = Utility.ReadCSV( self, f"{self.iXAssets}/mp/brkioskpurchases.csv", BRKioskPurchasesTruckWar, ) if ids is None: return items for entry in ids: items.append( { "altId": entry.get("ref"), "name": self.localize.get(entry.get("title")), "description": self.localize.get(entry.get("desc")), "label": self.localize.get(entry.get("slotLabel")), "type": entry.get("type"), "price": entry.get("cost") * 100, "image": entry.get("icon"), } ) return items class KioskBRTruck: """Battle Royale Kiosk Purchases (Truck War) XAssets.""" def Compile(self: Any) -> None: """Compile the Battle Royale Kiosk Purchases (Truck War) XAssets.""" items: List[Dict[str, Any]] = [] items = KioskBRTruck.IDs(self, items) Utility.WriteFile(self, f"{self.eXAssets}/kioskBRTruck.json", items) log.info(f"Compiled {len(items):,} Kiosk Items (BR Truck War)") def IDs(self: Any, items: List[Dict[str, Any]]) -> List[Dict[str, Any]]: """Compile the mp/brkioskpurchases_truckwar.csv XAsset.""" ids: List[Dict[str, Any]] = Utility.ReadCSV( self, f"{self.iXAssets}/mp/brkioskpurchases_truckwar.csv", BRKioskPurchasesTruckWar, ) if ids is None: return items for entry in ids: items.append( { "altId": entry.get("ref"), "name": self.localize.get(entry.get("title")), "description": self.localize.get(entry.get("desc")), "label": self.localize.get(entry.get("slotLabel")), "type": entry.get("type"), "price": entry.get("cost") * 100, "image": entry.get("icon"), } ) return items

27.144

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0.547893

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3,393

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0

null

0

1

0

1

0

null

0

7

387151169fb56903951502857173f6a5897a61dc

237

py

Python

deep_sdf/__init__.py

TMats/DeepSDF

eafda02220ff25c6e2afd16697a9c5bc526ff2d1

[ "MIT" ]

889

2019-07-08T22:50:39.000Z

2022-03-29T11:50:08.000Z

deep_sdf/__init__.py

TMats/DeepSDF

eafda02220ff25c6e2afd16697a9c5bc526ff2d1

[ "MIT" ]

90

2019-07-09T20:33:09.000Z

2022-03-29T08:59:37.000Z

deep_sdf/__init__.py

TMats/DeepSDF

eafda02220ff25c6e2afd16697a9c5bc526ff2d1

[ "MIT" ]

214

2019-07-09T00:55:04.000Z

2022-03-19T03:10:48.000Z

#!/usr/bin/env python3 # Copyright 2004-present Facebook. All Rights Reserved. from deep_sdf.data import * from deep_sdf.mesh import * from deep_sdf.metrics.chamfer import * from deep_sdf.utils import * from deep_sdf.workspace import *

26.333333

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0.78903

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4.918919

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0.21978

0.302198

0.373626

0

0.024155

0.126582

237

8

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null

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0

1

0

1

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7

387627a7bf29d326bf5bdd9daa17c169f3e87a20

9,579

py

Python

bcn/solvers.py

a378ec99/bcn

51c8984d74dc5945bf6296137caffadb91c142ff

[ "MIT" ]

null

bcn/solvers.py

a378ec99/bcn

51c8984d74dc5945bf6296137caffadb91c142ff

[ "MIT" ]

null

bcn/solvers.py

a378ec99/bcn

51c8984d74dc5945bf6296137caffadb91c142ff

[ "MIT" ]

null

"""Solvers for matrix recovery. Note ---- Currently only supports conjugate gradient methods. """ from __future__ import division, absolute_import import numpy as np from pymanopt import Problem from pymanopt.solvers import ConjugateGradient, SteepestDescent from pymanopt.manifolds import FixedRankEmbedded class ConjugateGradientSolver(object): def __init__(self, mixed, cost_func, guess_func, rank, n_restarts=10, guess_noise_amplitude=5.0, maxiter=1000, maxtime=100, mingradnorm=1e-12, minstepsize=1e-12, n_retries_svd=10, verbosity=2): """Solver for matrix recovery. Parameters ---------- mixed : numpy.ndarray, shape=(n_samples, n_features) Corrupted signal to be cleaned. cost_func : func Cost function based on linear operators A and targets y. guess_func : func Guess function that guesses an intial point for the solver to start optimizing at. rank : int Rank of the matrix to be recovered and of the initial guess. n_restarts : int Number of restats of the solver with a fresh initial guess. guess_noise_amplitude : float Noise amplitude for the random low-rank initial guess. maxiter : int Maximum number of iterations of solver. maxtime : int Maximum run time of solver in seconds. mingradnorm : float Minimal gradient norm of solver (before stopping). minstepsize : int Minimal step size of solver (before stopping). n_retries_svd : int Number of retries when LinAlgError. verbosiy : int, values=(0, 1, 2) Higher verbosity means more information printed. """ self.mixed = mixed self.shape = self.mixed.shape self.guess_func = guess_func self.cost_func = cost_func self.rank = rank self.n_restarts = n_restarts self.guess_noise_amplitude = guess_noise_amplitude self.manifold = FixedRankEmbedded( self.shape[0], self.shape[1], self.rank) self.problem = Problem(manifold=self.manifold, cost=self.cost_func, verbosity=verbosity) self.maxiter = maxiter self.maxtime = maxtime self.mingradnorm = mingradnorm self.minstepsize = minstepsize self.solver = ConjugateGradient(logverbosity=2, maxiter=self.maxiter, maxtime=self.maxtime, mingradnorm=self.mingradnorm, minstepsize=self.minstepsize) self.n_retries_svd = n_retries_svd def solve(self, guess): """ Solve a matrix recovery problem based on the given constraints and an initial guess. Parameters ---------- guess : tuple, values=(u, s, vt) Descomposed random low-rank matrix. Returns ------- X : numpy.ndarray, shape=(n_samples, n_features) Solution of the recovery problem. stopping_reason : str Why the solver finished, e.g. out of time, out of steps, etc. final_cost : float Final value of the cost function. """ worked = False for n in xrange(self.n_retries_svd): try: usvt, optlog = self.solver.solve(self.problem, x=guess) worked = True break except np.linalg.LinAlgError: continue if worked == False: raise Exception('Not enough SVD restarts.') stopping_reason = optlog['stoppingreason'] final_cost = optlog['final_values']['f(x)'] X = usvt[0].dot(np.diag(usvt[1])).dot(usvt[2]) return X, stopping_reason, final_cost def recover(self): """ Runs the solver n_restarts times and picks the best run. Returns ------- results : dict Results of the recovery with initial guess, estimated signal, estimated bias and final cost. """ estimates, errors, guesses_X, guesses_usvt = [], [], [], [] for k in xrange(self.n_restarts): guess = self.guess_func( self.shape, self.rank, noise_amplitude=self.guess_noise_amplitude) X, stopping_reason, final_cost = self.solve(guess['usvt']) estimates.append(X) guesses_X.append(guess['X']) guesses_usvt.append(guess['usvt']) errors.append(final_cost) index = np.argmin(errors) error = errors[index] estimated_bias = estimates[index] guess_X = guesses_X[index] guess_usvt = guesses_usvt[index] results = {'guess_X': guess_X, 'guess_usvt': guess_usvt, 'estimated_bias': estimated_bias, 'estimated_signal': self.mixed - estimated_bias, 'final_cost': error} return results class SteepestDescentSolver(object): def __init__(self, mixed, cost_func, guess_func, rank, n_restarts=10, guess_noise_amplitude=5.0, maxiter=1000, maxtime=100, mingradnorm=1e-12, minstepsize=1e-12, n_retries_svd=10, verbosity=2): """Solver for matrix recovery. Parameters ---------- mixed : numpy.ndarray, shape=(n_samples, n_features) Corrupted signal to be cleaned. cost_func : func Cost function based on linear operators A and targets y. guess_func : func Guess function that guesses an intial point for the solver to start optimizing at. rank : int Rank of the matrix to be recovered and of the initial guess. n_restarts : int Number of restats of the solver with a fresh initial guess. guess_noise_amplitude : float Noise amplitude for the random low-rank initial guess. maxiter : int Maximum number of iterations of solver. maxtime : int Maximum run time of solver in seconds. mingradnorm : float Minimal gradient norm of solver (before stopping). minstepsize : int Minimal step size of solver (before stopping). n_retries_svd : int Number of retries when LinAlgError. verbosiy : int, values=(0, 1, 2) Higher verbosity means more information printed. """ self.mixed = mixed self.shape = self.mixed.shape self.guess_func = guess_func self.cost_func = cost_func self.rank = rank self.n_restarts = n_restarts self.guess_noise_amplitude = guess_noise_amplitude self.manifold = FixedRankEmbedded( self.shape[0], self.shape[1], self.rank) self.problem = Problem(manifold=self.manifold, cost=self.cost_func, verbosity=verbosity) self.maxiter = maxiter self.maxtime = maxtime self.mingradnorm = mingradnorm self.minstepsize = minstepsize self.solver = SteepestDescent(logverbosity=2, maxiter=self.maxiter, maxtime=self.maxtime, mingradnorm=self.mingradnorm, minstepsize=self.minstepsize) self.n_retries_svd = n_retries_svd def solve(self, guess): """ Solve a matrix recovery problem based on the given constraints and an initial guess. Parameters ---------- guess : tuple, values=(u, s, vt) Descomposed random low-rank matrix. Returns ------- X : numpy.ndarray, shape=(n_samples, n_features) Solution of the recovery problem. stopping_reason : str Why the solver finished, e.g. out of time, out of steps, etc. final_cost : float Final value of the cost function. """ worked = False for n in xrange(self.n_retries_svd): try: usvt, optlog = self.solver.solve(self.problem, x=guess) worked = True break except np.linalg.LinAlgError: continue if worked == False: raise Exception('Not enough SVD restarts.') stopping_reason = optlog['stoppingreason'] final_cost = optlog['final_values']['f(x)'] X = usvt[0].dot(np.diag(usvt[1])).dot(usvt[2]) return X, stopping_reason, final_cost def recover(self): """ Runs the solver n_restarts times and picks the best run. Returns ------- results : dict Results of the recovery with initial guess, estimated signal, estimated bias and final cost. """ estimates, errors, guesses_X, guesses_usvt = [], [], [], [] for k in xrange(self.n_restarts): guess = self.guess_func( self.shape, self.rank, noise_amplitude=self.guess_noise_amplitude) X, stopping_reason, final_cost = self.solve(guess['usvt']) estimates.append(X) guesses_X.append(guess['X']) guesses_usvt.append(guess['usvt']) errors.append(final_cost) index = np.argmin(errors) error = errors[index] estimated_bias = estimates[index] guess_X = guesses_X[index] guess_usvt = guesses_usvt[index] results = {'guess_X': guess_X, 'guess_usvt': guess_usvt, 'estimated_bias': estimated_bias, 'estimated_signal': self.mixed - estimated_bias, 'final_cost': error} return results

39.582645

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false

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0

null

0

1

0

1

0

null

0

7

387a2b855279bc596b39818974a170c5434bd0ed

18,366

py

Python

IndiaFacts/skill_env/ask_sdk_model/services/reminder_management/reminder_management_service_client.py

JeremieBou/AlexaSkills

5d81c2c6e7ca8068e3850e8f2f2ebb3d9cca87cd

[ "Apache-2.0" ]

1

2019-02-04T21:07:06.000Z

ask_sdk_model/services/reminder_management/reminder_management_service_client.py

GR3C0/VLC_skill

ae0c85058ef9f12828c7ffccb9ad65baeb81f881

[ "MIT" ]

9

2020-03-24T16:32:57.000Z

2022-03-11T23:37:22.000Z

IndiaFacts/skill_env/ask_sdk_model/services/reminder_management/reminder_management_service_client.py

JeremieBou/AlexaSkills

5d81c2c6e7ca8068e3850e8f2f2ebb3d9cca87cd

[ "Apache-2.0" ]

null

# coding: utf-8 # # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file # except in compliance with the License. A copy of the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for # the specific language governing permissions and limitations under the License. # import sys import os import re import six import typing from ask_sdk_model.services.base_service_client import BaseServiceClient from ask_sdk_model.services.api_configuration import ApiConfiguration from ask_sdk_model.services.service_client_response import ServiceClientResponse if typing.TYPE_CHECKING: from typing import Dict, List, Union from datetime import datetime from ask_sdk_model.services.reminder_management.get_reminders_response import GetRemindersResponse from ask_sdk_model.services.reminder_management.get_reminder_response import GetReminderResponse from ask_sdk_model.services.reminder_management.reminder_response import ReminderResponse from ask_sdk_model.services.reminder_management.reminder_request import ReminderRequest from ask_sdk_model.services.reminder_management.error import Error class ReminderManagementServiceClient(BaseServiceClient): """ServiceClient for calling the ReminderManagementService APIs. :param api_configuration: Instance of :py:class:`ask_sdk_model.services.api_configuration.ApiConfiguration` :type api_configuration: ask_sdk_model.services.api_configuration.ApiConfiguration """ def __init__(self, api_configuration): # type: (ApiConfiguration) -> None """ :param api_configuration: Instance of :py:class:`ask_sdk_model.services.api_configuration.ApiConfiguration` :type api_configuration: ask_sdk_model.services.api_configuration.ApiConfiguration """ super(ReminderManagementServiceClient, self).__init__(api_configuration) def delete_reminder(self, alert_token, **kwargs): # type: (str) -> Union[Error] """ This API is invoked by the skill to delete a single reminder. :param alert_token: (required) :type alert_token: str :rtype: None """ operation_name = "delete_reminder" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] # verify the required parameter 'alert_token' is set if ('alert_token' not in params) or (params['alert_token'] is None): raise ValueError( "Missing the required parameter `alert_token` when calling `" + operation_name + "`") resource_path = '/v1/alerts/reminders/{alertToken}'.replace('{format}', 'json') path_params = {} if 'alert_token' in params: path_params['alertToken'] = params['alert_token'] query_params = [] header_params = [] body_params = None header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type=None, status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=401, message="UserAuthenticationException. Request is not authorized/authenticated e.g. If customer does not have permission to create a reminder.")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) self.invoke( method="DELETE", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type=None) def get_reminder(self, alert_token, **kwargs): # type: (str) -> Union[GetReminderResponse, Error] """ This API is invoked by the skill to get a single reminder. :param alert_token: (required) :type alert_token: str :rtype: Union[GetReminderResponse, Error] """ operation_name = "get_reminder" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] # verify the required parameter 'alert_token' is set if ('alert_token' not in params) or (params['alert_token'] is None): raise ValueError( "Missing the required parameter `alert_token` when calling `" + operation_name + "`") resource_path = '/v1/alerts/reminders/{alertToken}'.replace('{format}', 'json') path_params = {} if 'alert_token' in params: path_params['alertToken'] = params['alert_token'] query_params = [] header_params = [] body_params = None header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.get_reminder_response.GetReminderResponse", status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=401, message="UserAuthenticationException. Request is not authorized/authenticated e.g. If customer does not have permission to create a reminder.")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) return self.invoke( method="GET", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type="ask_sdk_model.services.reminder_management.get_reminder_response.GetReminderResponse") def update_reminder(self, alert_token, reminder_request, **kwargs): # type: (str, ReminderRequest) -> Union[ReminderResponse, Error] """ This API is invoked by the skill to update a reminder. :param alert_token: (required) :type alert_token: str :param reminder_request: (required) :type reminder_request: ask_sdk_model.services.reminder_management.reminder_request.ReminderRequest :rtype: Union[ReminderResponse, Error] """ operation_name = "update_reminder" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] # verify the required parameter 'alert_token' is set if ('alert_token' not in params) or (params['alert_token'] is None): raise ValueError( "Missing the required parameter `alert_token` when calling `" + operation_name + "`") # verify the required parameter 'reminder_request' is set if ('reminder_request' not in params) or (params['reminder_request'] is None): raise ValueError( "Missing the required parameter `reminder_request` when calling `" + operation_name + "`") resource_path = '/v1/alerts/reminders/{alertToken}'.replace('{format}', 'json') path_params = {} if 'alert_token' in params: path_params['alertToken'] = params['alert_token'] query_params = [] header_params = [] body_params = None if 'reminder_request' in params: body_params = params['reminder_request'] header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.reminder_response.ReminderResponse", status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=400, message="Bad Request")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=404, message="NotFoundException e.g. Retured when reminder is not found")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=409, message="UserAuthenticationException. Request is not authorized/authenticated e.g. If customer does not have permission to create a reminder.")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) return self.invoke( method="PUT", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type="ask_sdk_model.services.reminder_management.reminder_response.ReminderResponse") def delete_reminders(self, **kwargs): # type: () -> Union[Error] """ This API is invoked by the skill to delete all reminders created by the caller. :rtype: None """ operation_name = "delete_reminders" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] resource_path = '/v1/alerts/reminders/'.replace('{format}', 'json') path_params = {} query_params = [] header_params = [] body_params = None header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type=None, status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=401, message="UserAuthenticationException. Request is not authorized/authenticated e.g. If customer does not have permission to create a reminder.")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) self.invoke( method="DELETE", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type=None) def get_reminders(self, **kwargs): # type: () -> Union[GetRemindersResponse, Error] """ This API is invoked by the skill to get a all reminders created by the caller. :rtype: Union[GetRemindersResponse, Error] """ operation_name = "get_reminders" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] resource_path = '/v1/alerts/reminders/'.replace('{format}', 'json') path_params = {} query_params = [] header_params = [] body_params = None header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.get_reminders_response.GetRemindersResponse", status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=401, message="UserAuthenticationException. Request is not authorized/authenticated e.g. If customer does not have permission to create a reminder.")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) return self.invoke( method="GET", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type="ask_sdk_model.services.reminder_management.get_reminders_response.GetRemindersResponse") def create_reminder(self, reminder_request, **kwargs): # type: (ReminderRequest) -> Union[ReminderResponse, Error] """ This API is invoked by the skill to create a new reminder. :param reminder_request: (required) :type reminder_request: ask_sdk_model.services.reminder_management.reminder_request.ReminderRequest :rtype: Union[ReminderResponse, Error] """ operation_name = "create_reminder" params = locals() for key, val in six.iteritems(params['kwargs']): params[key] = val del params['kwargs'] # verify the required parameter 'reminder_request' is set if ('reminder_request' not in params) or (params['reminder_request'] is None): raise ValueError( "Missing the required parameter `reminder_request` when calling `" + operation_name + "`") resource_path = '/v1/alerts/reminders/'.replace('{format}', 'json') path_params = {} query_params = [] header_params = [] body_params = None if 'reminder_request' in params: body_params = params['reminder_request'] header_params.append(('Content-type', 'application/json')) # Authentication setting authorization_value = "Bearer " + self._authorization_value header_params.append(("Authorization", authorization_value)) error_definitions = [] error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.reminder_response.ReminderResponse", status_code=200, message="Success")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=400, message="Bad Request")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=403, message="Forbidden")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=429, message="RateExceededException e.g. When the skill is throttled for exceeding the max rate")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=500, message="Internal Server Error")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=503, message="Service Unavailable")) error_definitions.append(ServiceClientResponse(response_type="ask_sdk_model.services.reminder_management.error.Error", status_code=504, message="Gateway Timeout")) return self.invoke( method="POST", endpoint=self._api_endpoint, path=resource_path, path_params=path_params, query_params=query_params, header_params=header_params, body=body_params, response_definitions=error_definitions, response_type="ask_sdk_model.services.reminder_management.reminder_response.ReminderResponse")

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2a09700a53378403a34f8c196125564bb6e4c5ae

131,510

py

Python

ports/rp2/natmod/picantepy/tileset_dungeon.py

mrgkingcs/micropython

1d7f16a98edd7e505c4a230623ab2268637d0848

[ "MIT" ]

null

ports/rp2/natmod/picantepy/tileset_dungeon.py

mrgkingcs/micropython

1d7f16a98edd7e505c4a230623ab2268637d0848

[ "MIT" ]

null

ports/rp2/natmod/picantepy/tileset_dungeon.py

mrgkingcs/micropython

1d7f16a98edd7e505c4a230623ab2268637d0848

[ "MIT" ]

null

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py

Python

metal/models/batches_api.py

displague/metal-python

96e64e9ac41025d85ff6f61693165e29e1c366db

[ "MIT" ]

null

metal/models/batches_api.py

displague/metal-python

96e64e9ac41025d85ff6f61693165e29e1c366db

[ "MIT" ]

3

2021-09-27T05:10:36.000Z

2021-09-27T06:10:57.000Z

metal/models/batches_api.py

displague/metal-python

96e64e9ac41025d85ff6f61693165e29e1c366db

[ "MIT" ]

null

# coding: utf-8 """ Metal API This is the API for Equinix Metal. The API allows you to programmatically interact with all of your Equinix Metal resources, including devices, networks, addresses, organizations, projects, and your user account. The official API docs are hosted at <https://metal.equinix.com/developers/api>. # noqa: E501 The version of the OpenAPI document: 1.0.0 Contact: support@equinixmetal.com Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from metal.api_client import ApiClient from metal.exceptions import ( # noqa: F401 ApiTypeError, ApiValueError ) class BatchesApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def create_device_batch(self, id, batch, **kwargs): # noqa: E501 """Create a devices batch # noqa: E501 Creates new devices in batch and provisions them in our datacenter. Type-specific options (such as operating_system for baremetal devices) should be included in the main data structure alongside hostname and plan. The features attribute allows you to optionally specify what features your server should have. For example, if you require a server with a TPM chip, you may specify `{ \"features\": { \"tpm\": \"required\" } }` (or `{ \"features\": [\"tpm\"] }` in shorthand). The request will fail if there are no available servers matching your criteria. Alternatively, if you do not require a certain feature, but would prefer to be assigned a server with that feature if there are any available, you may specify that feature with a preferred value (see the example request below). The request will not fail if we have no servers with that feature in our inventory. The facilities attribute specifies in what datacenter you wish to create the device. You can either specify a single facility `{ \"facility\": \"f1\" }` , or you can instruct to create the device in the best available datacenter `{ \"facility\": \"any\" }`. Additionally it is possible to set a prioritized location selection. For example `{ \"facility\": [\"f3\", \"f2\", \"any\"] }` will try to assign to the facility f3, if there are no available f2, and so on. If \"any\" is not specified for \"facility\", the request will fail unless it can assign in the selected locations. With `{ \"facility\": \"any\" }` you have the option to diversify to indicate how many facilities you are willing to be spread across. For this purpose use parameter: `facility_diversity_level = N`. For example: `{ \"facilities\": [\"sjc1\", \"ewr1\", \"any\"] , \"facility_diversity_level\" = 1, \"quantity\" = 10 }` will assign 10 devices into the same facility, trying first in \"sjc1\", and if there aren’t available, it will try in \"ewr1\", otherwise any other. The `ip_addresses` attribute will allow you to specify the addresses you want created with your device. To maintain backwards compatibility, If the attribute is not sent in the request, it will be treated as if `{ \"ip_addresses\": [{ \"address_family\": 4, \"public\": true }, { \"address_family\": 4, \"public\": false }, { \"address_family\": 6, \"public\": true }] }` was sent. The private IPv4 address is required and always need to be sent in the array. Not all operating systems support no public IPv4 address, so in those cases you will receive an error message. For example, to only configure your server with a private IPv4 address, you can send `{ \"ip_addresses\": [{ \"address_family\": 4, \"public\": false }] }`. Note: when specifying a subnet size larger than a /30, you will need to supply the UUID(s) of existing ip_reservations in your project to assign IPs from. For example, `{ \"ip_addresses\": [..., {\"address_family\": 4, \"public\": true, \"ip_reservations\": [\"uuid1\", \"uuid2\"]}] }` To access a server without public IPs, you can use our Out-of-Band console access (SOS) or use another server with public IPs as a proxy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_device_batch(id, batch, async_req=True) >>> result = thread.get() :param id: Project UUID (required) :type id: str :param batch: Batches to create (required) :type batch: InstancesBatchCreateInput :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: BatchesList """ kwargs['_return_http_data_only'] = True return self.create_device_batch_with_http_info(id, batch, **kwargs) # noqa: E501 def create_device_batch_with_http_info(self, id, batch, **kwargs): # noqa: E501 """Create a devices batch # noqa: E501 Creates new devices in batch and provisions them in our datacenter. Type-specific options (such as operating_system for baremetal devices) should be included in the main data structure alongside hostname and plan. The features attribute allows you to optionally specify what features your server should have. For example, if you require a server with a TPM chip, you may specify `{ \"features\": { \"tpm\": \"required\" } }` (or `{ \"features\": [\"tpm\"] }` in shorthand). The request will fail if there are no available servers matching your criteria. Alternatively, if you do not require a certain feature, but would prefer to be assigned a server with that feature if there are any available, you may specify that feature with a preferred value (see the example request below). The request will not fail if we have no servers with that feature in our inventory. The facilities attribute specifies in what datacenter you wish to create the device. You can either specify a single facility `{ \"facility\": \"f1\" }` , or you can instruct to create the device in the best available datacenter `{ \"facility\": \"any\" }`. Additionally it is possible to set a prioritized location selection. For example `{ \"facility\": [\"f3\", \"f2\", \"any\"] }` will try to assign to the facility f3, if there are no available f2, and so on. If \"any\" is not specified for \"facility\", the request will fail unless it can assign in the selected locations. With `{ \"facility\": \"any\" }` you have the option to diversify to indicate how many facilities you are willing to be spread across. For this purpose use parameter: `facility_diversity_level = N`. For example: `{ \"facilities\": [\"sjc1\", \"ewr1\", \"any\"] , \"facility_diversity_level\" = 1, \"quantity\" = 10 }` will assign 10 devices into the same facility, trying first in \"sjc1\", and if there aren’t available, it will try in \"ewr1\", otherwise any other. The `ip_addresses` attribute will allow you to specify the addresses you want created with your device. To maintain backwards compatibility, If the attribute is not sent in the request, it will be treated as if `{ \"ip_addresses\": [{ \"address_family\": 4, \"public\": true }, { \"address_family\": 4, \"public\": false }, { \"address_family\": 6, \"public\": true }] }` was sent. The private IPv4 address is required and always need to be sent in the array. Not all operating systems support no public IPv4 address, so in those cases you will receive an error message. For example, to only configure your server with a private IPv4 address, you can send `{ \"ip_addresses\": [{ \"address_family\": 4, \"public\": false }] }`. Note: when specifying a subnet size larger than a /30, you will need to supply the UUID(s) of existing ip_reservations in your project to assign IPs from. For example, `{ \"ip_addresses\": [..., {\"address_family\": 4, \"public\": true, \"ip_reservations\": [\"uuid1\", \"uuid2\"]}] }` To access a server without public IPs, you can use our Out-of-Band console access (SOS) or use another server with public IPs as a proxy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_device_batch_with_http_info(id, batch, async_req=True) >>> result = thread.get() :param id: Project UUID (required) :type id: str :param batch: Batches to create (required) :type batch: InstancesBatchCreateInput :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(BatchesList, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id', 'batch' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method create_device_batch" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `create_device_batch`") # noqa: E501 # verify the required parameter 'batch' is set if self.api_client.client_side_validation and ('batch' not in local_var_params or # noqa: E501 local_var_params['batch'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `batch` when calling `create_device_batch`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'batch' in local_var_params: body_params = local_var_params['batch'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['x_auth_token'] # noqa: E501 response_types_map = { 201: "BatchesList", 401: "Error", 403: "Error", 404: "Error", 422: "Error", } return self.api_client.call_api( '/projects/{id}/devices/batch', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def delete_batch(self, id, **kwargs): # noqa: E501 """Delete the Batch # noqa: E501 Deletes the Batch. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_batch(id, async_req=True) >>> result = thread.get() :param id: Batch UUID (required) :type id: str :param remove_associated_instances: Delete all instances created from this batch :type remove_associated_instances: bool :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: None """ kwargs['_return_http_data_only'] = True return self.delete_batch_with_http_info(id, **kwargs) # noqa: E501 def delete_batch_with_http_info(self, id, **kwargs): # noqa: E501 """Delete the Batch # noqa: E501 Deletes the Batch. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_batch_with_http_info(id, async_req=True) >>> result = thread.get() :param id: Batch UUID (required) :type id: str :param remove_associated_instances: Delete all instances created from this batch :type remove_associated_instances: bool :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: None """ local_var_params = locals() all_params = [ 'id', 'remove_associated_instances' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method delete_batch" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `delete_batch`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] if 'remove_associated_instances' in local_var_params and local_var_params['remove_associated_instances'] is not None: # noqa: E501 query_params.append(('remove_associated_instances', local_var_params['remove_associated_instances'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['x_auth_token'] # noqa: E501 response_types_map = {} return self.api_client.call_api( '/batches/{id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def find_batch_by_id(self, id, **kwargs): # noqa: E501 """Retrieve a Batch # noqa: E501 Returns a Batch # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.find_batch_by_id(id, async_req=True) >>> result = thread.get() :param id: Batch UUID (required) :type id: str :param include: Nested attributes to include. Included objects will return their full attributes. Attribute names can be dotted (up to 3 levels) to included deeply nested objects. :type include: list[str] :param exclude: Nested attributes to exclude. Excluded objects will return only the href attribute. Attribute names can be dotted (up to 3 levels) to exclude deeply nested objects. :type exclude: list[str] :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: Batch """ kwargs['_return_http_data_only'] = True return self.find_batch_by_id_with_http_info(id, **kwargs) # noqa: E501 def find_batch_by_id_with_http_info(self, id, **kwargs): # noqa: E501 """Retrieve a Batch # noqa: E501 Returns a Batch # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.find_batch_by_id_with_http_info(id, async_req=True) >>> result = thread.get() :param id: Batch UUID (required) :type id: str :param include: Nested attributes to include. Included objects will return their full attributes. Attribute names can be dotted (up to 3 levels) to included deeply nested objects. :type include: list[str] :param exclude: Nested attributes to exclude. Excluded objects will return only the href attribute. Attribute names can be dotted (up to 3 levels) to exclude deeply nested objects. :type exclude: list[str] :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(Batch, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id', 'include', 'exclude' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method find_batch_by_id" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `find_batch_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] if 'include' in local_var_params and local_var_params['include'] is not None: # noqa: E501 query_params.append(('include', local_var_params['include'])) # noqa: E501 collection_formats['include'] = 'csv' # noqa: E501 if 'exclude' in local_var_params and local_var_params['exclude'] is not None: # noqa: E501 query_params.append(('exclude', local_var_params['exclude'])) # noqa: E501 collection_formats['exclude'] = 'csv' # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['x_auth_token'] # noqa: E501 response_types_map = { 200: "Batch", 401: "Error", 404: "Error", } return self.api_client.call_api( '/batches/{id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def find_batches_by_project(self, id, **kwargs): # noqa: E501 """Retrieve all batches by project # noqa: E501 Returns all batches for the given project # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.find_batches_by_project(id, async_req=True) >>> result = thread.get() :param id: Project UUID (required) :type id: str :param include: Nested attributes to include. Included objects will return their full attributes. Attribute names can be dotted (up to 3 levels) to included deeply nested objects. :type include: list[str] :param exclude: Nested attributes to exclude. Excluded objects will return only the href attribute. Attribute names can be dotted (up to 3 levels) to exclude deeply nested objects. :type exclude: list[str] :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: BatchesList """ kwargs['_return_http_data_only'] = True return self.find_batches_by_project_with_http_info(id, **kwargs) # noqa: E501 def find_batches_by_project_with_http_info(self, id, **kwargs): # noqa: E501 """Retrieve all batches by project # noqa: E501 Returns all batches for the given project # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.find_batches_by_project_with_http_info(id, async_req=True) >>> result = thread.get() :param id: Project UUID (required) :type id: str :param include: Nested attributes to include. Included objects will return their full attributes. Attribute names can be dotted (up to 3 levels) to included deeply nested objects. :type include: list[str] :param exclude: Nested attributes to exclude. Excluded objects will return only the href attribute. Attribute names can be dotted (up to 3 levels) to exclude deeply nested objects. :type exclude: list[str] :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(BatchesList, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id', 'include', 'exclude' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method find_batches_by_project" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `find_batches_by_project`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] if 'include' in local_var_params and local_var_params['include'] is not None: # noqa: E501 query_params.append(('include', local_var_params['include'])) # noqa: E501 collection_formats['include'] = 'csv' # noqa: E501 if 'exclude' in local_var_params and local_var_params['exclude'] is not None: # noqa: E501 query_params.append(('exclude', local_var_params['exclude'])) # noqa: E501 collection_formats['exclude'] = 'csv' # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['x_auth_token'] # noqa: E501 response_types_map = { 200: "BatchesList", 401: "Error", 403: "Error", 404: "Error", } return self.api_client.call_api( '/projects/{id}/batches', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth'))

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3,108

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4,176

34,582

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0.030628

0.048171

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0

0.014241

0.301515

34,582

639

3,109

54.118936

0.840033

0.576456

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0

0.166306

0.043158

0

1

0.031802

false

0

0.017668

0

0.081272

0

null

0

1

0

1

0

1

0

null

0

8

aa8a6fb84fcfabba1bf104091f77ba282184c086

972

py

Python

tests/test_autoexecute.py

Rayapur/pytest-play

c39a1a7e74d90aebeb30797a61d0e491942557e8

[ "Apache-2.0" ]

51

2018-04-26T09:02:38.000Z

2021-11-21T10:57:32.000Z

tests/test_autoexecute.py

Rayapur/pytest-play

c39a1a7e74d90aebeb30797a61d0e491942557e8

[ "Apache-2.0" ]

39

2017-12-20T14:27:33.000Z

2018-04-05T22:45:12.000Z

tests/test_autoexecute.py

tierratelematics/pytest-play

c39a1a7e74d90aebeb30797a61d0e491942557e8

[ "Apache-2.0" ]

5

2018-06-30T15:51:39.000Z

2020-04-13T19:31:25.000Z

def test_autoexecute_yml_pass(testdir): yml_file = testdir.makefile(".yml", """ --- - provider: python type: assert expression: "1" """) assert yml_file.basename.startswith('test_') assert yml_file.basename.endswith('.yml') result = testdir.runpytest() result.assert_outcomes(passed=1) def test_autoexecute_yml_fail(testdir): yml_file = testdir.makefile(".yml", """ --- - provider: python type: assert expression: "0" """) assert yml_file.basename.startswith('test_') assert yml_file.basename.endswith('.yml') result = testdir.runpytest() result.assert_outcomes(failed=1) def test_autoexecute_yml_cli_pass(testdir): yml_file = testdir.makefile(".yml", """ --- - provider: python type: assert expression: "1" """) assert yml_file.basename.startswith('test_') assert yml_file.basename.endswith('.yml') result = testdir.runpytest(yml_file.strpath) result.assert_outcomes(passed=1)

22.090909

48

0.686214

115

972

5.573913

0.226087

0.109204

0.121685

0.196568

0.923557

0.803432

0

0.007417

0.167695

972

43

49

22.604651

0.78492

0

0.818182

0

0.228395

0

0.363636

1

0.090909

false

0.121212

0

0.090909

0

null

0

1

0

1

0

null

0

1

0

9

aa8a7dfd07a3303ed33f55b36c61bd943da2e475

24,475

py

Python

test_autoastro/unit/profiles/test_light_and_mass_profiles.py

woodyZootopia/PyAutoAstro

6500b9746b3e73c3f3129fcbaa3a0419bb400915

[ "MIT" ]

null

test_autoastro/unit/profiles/test_light_and_mass_profiles.py

woodyZootopia/PyAutoAstro

6500b9746b3e73c3f3129fcbaa3a0419bb400915

[ "MIT" ]

null

test_autoastro/unit/profiles/test_light_and_mass_profiles.py

woodyZootopia/PyAutoAstro

6500b9746b3e73c3f3129fcbaa3a0419bb400915

[ "MIT" ]

null

import numpy as np import pytest import autofit as af import autoarray as aa import autoastro as aast grid = aa.grid_irregular.manual_1d([[1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [2.0, 4.0]]) @pytest.fixture(autouse=True) def reset_config(): """ Use configuration from the default path. You may want to change this to set a specific path. """ af.conf.instance = af.conf.default class TestGaussian(object): def test__constructor_and_units(self): gaussian = aast.lmp.EllipticalGaussian( centre=(1.0, 2.0), axis_ratio=0.5, phi=45.0, intensity=1.0, sigma=4.0, mass_to_light_ratio=10.0, ) assert gaussian.centre == (1.0, 2.0) assert isinstance(gaussian.centre[0], aast.dim.Length) assert isinstance(gaussian.centre[1], aast.dim.Length) assert gaussian.centre[0].unit == "arcsec" assert gaussian.centre[1].unit == "arcsec" assert gaussian.axis_ratio == 0.5 assert isinstance(gaussian.axis_ratio, float) assert gaussian.phi == 45.0 assert isinstance(gaussian.phi, float) assert gaussian.intensity == 1.0 assert isinstance(gaussian.intensity, aast.dim.Luminosity) assert gaussian.intensity.unit == "eps" assert gaussian.sigma == 4.0 assert isinstance(gaussian.sigma, aast.dim.Length) assert gaussian.sigma.unit_length == "arcsec" assert gaussian.mass_to_light_ratio == 10.0 assert isinstance(gaussian.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert gaussian.mass_to_light_ratio.unit == "angular / eps" def test__grid_calculations__same_as_gaussian(self): gaussian_lp = aast.lmp.EllipticalGaussian( axis_ratio=0.7, phi=1.0, intensity=1.0, sigma=5.0 ) gaussian_mp = aast.lmp.EllipticalGaussian( axis_ratio=0.7, phi=1.0, intensity=1.0, sigma=5.0, mass_to_light_ratio=2.0 ) gaussian_lmp = aast.lmp.EllipticalGaussian( axis_ratio=0.7, phi=1.0, intensity=1.0, sigma=5.0, mass_to_light_ratio=2.0 ) assert ( gaussian_lp.profile_image_from_grid(grid=grid) == gaussian_lmp.profile_image_from_grid(grid=grid) ).all() assert ( gaussian_mp.convergence_from_grid(grid=grid) == gaussian_lmp.convergence_from_grid(grid=grid) ).all() # assert (sersic_mp.potential_from_grid(grid=grid) == sersic_lmp.potential_from_grid(grid=grid)).all() assert ( gaussian_mp.deflections_from_grid(grid=grid) == gaussian_lmp.deflections_from_grid(grid=grid) ).all() class TestSersic: def test__constructor_and_units(self): sersic = aast.lmp.EllipticalSersic( centre=(1.0, 2.0), axis_ratio=0.5, phi=45.0, intensity=1.0, effective_radius=0.6, sersic_index=4.0, mass_to_light_ratio=10.0, ) assert sersic.centre == (1.0, 2.0) assert isinstance(sersic.centre[0], aast.dim.Length) assert isinstance(sersic.centre[1], aast.dim.Length) assert sersic.centre[0].unit == "arcsec" assert sersic.centre[1].unit == "arcsec" assert sersic.axis_ratio == 0.5 assert isinstance(sersic.axis_ratio, float) assert sersic.phi == 45.0 assert isinstance(sersic.phi, float) assert sersic.intensity == 1.0 assert isinstance(sersic.intensity, aast.dim.Luminosity) assert sersic.intensity.unit == "eps" assert sersic.effective_radius == 0.6 assert isinstance(sersic.effective_radius, aast.dim.Length) assert sersic.effective_radius.unit_length == "arcsec" assert sersic.sersic_index == 4.0 assert isinstance(sersic.sersic_index, float) assert sersic.mass_to_light_ratio == 10.0 assert isinstance(sersic.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert sersic.mass_to_light_ratio.unit == "angular / eps" assert sersic.sersic_constant == pytest.approx(7.66925, 1e-3) assert sersic.elliptical_effective_radius == 0.6 / np.sqrt(0.5) sersic = aast.lmp.SphericalSersic( centre=(1.0, 2.0), intensity=1.0, effective_radius=0.6, sersic_index=4.0, mass_to_light_ratio=10.0, ) assert sersic.centre == (1.0, 2.0) assert isinstance(sersic.centre[0], aast.dim.Length) assert isinstance(sersic.centre[1], aast.dim.Length) assert sersic.centre[0].unit == "arcsec" assert sersic.centre[1].unit == "arcsec" assert sersic.axis_ratio == 1.0 assert isinstance(sersic.axis_ratio, float) assert sersic.phi == 0.0 assert isinstance(sersic.phi, float) assert sersic.intensity == 1.0 assert isinstance(sersic.intensity, aast.dim.Luminosity) assert sersic.intensity.unit == "eps" assert sersic.effective_radius == 0.6 assert isinstance(sersic.effective_radius, aast.dim.Length) assert sersic.effective_radius.unit_length == "arcsec" assert sersic.sersic_index == 4.0 assert isinstance(sersic.sersic_index, float) assert sersic.mass_to_light_ratio == 10.0 assert isinstance(sersic.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert sersic.mass_to_light_ratio.unit == "angular / eps" assert sersic.sersic_constant == pytest.approx(7.66925, 1e-3) assert sersic.elliptical_effective_radius == 0.6 def test__grid_calculations__same_as_sersic(self): sersic_lp = aast.lmp.EllipticalSersic( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, ) sersic_mp = aast.lmp.EllipticalSersic( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, mass_to_light_ratio=2.0, ) sersic_lmp = aast.lmp.EllipticalSersic( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, mass_to_light_ratio=2.0, ) assert ( sersic_lp.profile_image_from_grid(grid=grid) == sersic_lmp.profile_image_from_grid(grid=grid) ).all() assert ( sersic_mp.convergence_from_grid(grid=grid) == sersic_lmp.convergence_from_grid(grid=grid) ).all() # assert (sersic_mp.potential_from_grid(grid=grid) == sersic_lmp.potential_from_grid(grid=grid)).all() assert ( sersic_mp.deflections_from_grid(grid=grid) == sersic_lmp.deflections_from_grid(grid=grid) ).all() def test__spherical_and_elliptical_identical(self): elliptical = aast.lmp.EllipticalSersic( centre=(0.0, 0.0), axis_ratio=1.0, phi=0.0, intensity=1.0, effective_radius=1.0, sersic_index=2.0, mass_to_light_ratio=2.0, ) spherical = aast.lmp.SphericalSersic( centre=(0.0, 0.0), intensity=1.0, effective_radius=1.0, sersic_index=2.0, mass_to_light_ratio=2.0, ) assert ( elliptical.profile_image_from_grid(grid=grid) == spherical.profile_image_from_grid(grid=grid) ).all() assert ( elliptical.convergence_from_grid(grid=grid) == spherical.convergence_from_grid(grid=grid) ).all() # assert (elliptical.potential_from_grid(grid=grid) == spherical.potential_from_grid(grid=grid)).all() np.testing.assert_almost_equal( elliptical.deflections_from_grid(grid=grid), spherical.deflections_from_grid(grid=grid), ) class TestExponential: def test__constructor_and_units(self): exponential = aast.lmp.EllipticalExponential( centre=(1.0, 2.0), axis_ratio=0.5, phi=45.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=10.0, ) assert exponential.centre == (1.0, 2.0) assert isinstance(exponential.centre[0], aast.dim.Length) assert isinstance(exponential.centre[1], aast.dim.Length) assert exponential.centre[0].unit == "arcsec" assert exponential.centre[1].unit == "arcsec" assert exponential.axis_ratio == 0.5 assert isinstance(exponential.axis_ratio, float) assert exponential.phi == 45.0 assert isinstance(exponential.phi, float) assert exponential.intensity == 1.0 assert isinstance(exponential.intensity, aast.dim.Luminosity) assert exponential.intensity.unit == "eps" assert exponential.effective_radius == 0.6 assert isinstance(exponential.effective_radius, aast.dim.Length) assert exponential.effective_radius.unit_length == "arcsec" assert exponential.sersic_index == 1.0 assert isinstance(exponential.sersic_index, float) assert exponential.mass_to_light_ratio == 10.0 assert isinstance(exponential.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert exponential.mass_to_light_ratio.unit == "angular / eps" assert exponential.sersic_constant == pytest.approx(1.67838, 1e-3) assert exponential.elliptical_effective_radius == 0.6 / np.sqrt(0.5) exponential = aast.lmp.SphericalExponential( centre=(1.0, 2.0), intensity=1.0, effective_radius=0.6, mass_to_light_ratio=10.0, ) assert exponential.centre == (1.0, 2.0) assert isinstance(exponential.centre[0], aast.dim.Length) assert isinstance(exponential.centre[1], aast.dim.Length) assert exponential.centre[0].unit == "arcsec" assert exponential.centre[1].unit == "arcsec" assert exponential.axis_ratio == 1.0 assert isinstance(exponential.axis_ratio, float) assert exponential.phi == 0.0 assert isinstance(exponential.phi, float) assert exponential.intensity == 1.0 assert isinstance(exponential.intensity, aast.dim.Luminosity) assert exponential.intensity.unit == "eps" assert exponential.effective_radius == 0.6 assert isinstance(exponential.effective_radius, aast.dim.Length) assert exponential.effective_radius.unit_length == "arcsec" assert exponential.sersic_index == 1.0 assert isinstance(exponential.sersic_index, float) assert exponential.mass_to_light_ratio == 10.0 assert isinstance(exponential.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert exponential.mass_to_light_ratio.unit == "angular / eps" assert exponential.sersic_constant == pytest.approx(1.67838, 1e-3) assert exponential.elliptical_effective_radius == 0.6 def test__grid_calculations__same_as_exponential(self): sersic_lp = aast.lmp.EllipticalExponential( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6 ) sersic_mp = aast.lmp.EllipticalExponential( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=2.0, ) sersic_lmp = aast.lmp.EllipticalExponential( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=2.0, ) assert ( sersic_lp.profile_image_from_grid(grid=grid) == sersic_lmp.profile_image_from_grid(grid=grid) ).all() assert ( sersic_mp.convergence_from_grid(grid=grid) == sersic_lmp.convergence_from_grid(grid=grid) ).all() # assert (sersic_mp.potential_from_grid(grid=grid) == sersic_lmp.potential_from_grid(grid=grid)).all() assert ( sersic_mp.deflections_from_grid(grid=grid) == sersic_lmp.deflections_from_grid(grid=grid) ).all() def test__spherical_and_elliptical_identical(self): elliptical = aast.lmp.EllipticalExponential( centre=(0.0, 0.0), axis_ratio=1.0, phi=0.0, intensity=1.0, effective_radius=1.0, ) spherical = aast.lmp.SphericalExponential( centre=(0.0, 0.0), intensity=1.0, effective_radius=1.0 ) assert ( elliptical.profile_image_from_grid(grid=grid) == spherical.profile_image_from_grid(grid=grid) ).all() assert ( elliptical.convergence_from_grid(grid=grid) == spherical.convergence_from_grid(grid=grid) ).all() # assert elliptical.potential_from_grid(grid=grid) == spherical.potential_from_grid(grid=grid) np.testing.assert_almost_equal( elliptical.deflections_from_grid(grid=grid), spherical.deflections_from_grid(grid=grid), ) class TestDevVaucouleurs: def test__constructor_and_units(self): dev_vaucouleurs = aast.lmp.EllipticalDevVaucouleurs( centre=(1.0, 2.0), axis_ratio=0.5, phi=45.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=10.0, ) assert dev_vaucouleurs.centre == (1.0, 2.0) assert isinstance(dev_vaucouleurs.centre[0], aast.dim.Length) assert isinstance(dev_vaucouleurs.centre[1], aast.dim.Length) assert dev_vaucouleurs.centre[0].unit == "arcsec" assert dev_vaucouleurs.centre[1].unit == "arcsec" assert dev_vaucouleurs.axis_ratio == 0.5 assert isinstance(dev_vaucouleurs.axis_ratio, float) assert dev_vaucouleurs.phi == 45.0 assert isinstance(dev_vaucouleurs.phi, float) assert dev_vaucouleurs.intensity == 1.0 assert isinstance(dev_vaucouleurs.intensity, aast.dim.Luminosity) assert dev_vaucouleurs.intensity.unit == "eps" assert dev_vaucouleurs.effective_radius == 0.6 assert isinstance(dev_vaucouleurs.effective_radius, aast.dim.Length) assert dev_vaucouleurs.effective_radius.unit_length == "arcsec" assert dev_vaucouleurs.sersic_index == 4.0 assert isinstance(dev_vaucouleurs.sersic_index, float) assert dev_vaucouleurs.mass_to_light_ratio == 10.0 assert isinstance( dev_vaucouleurs.mass_to_light_ratio, aast.dim.MassOverLuminosity ) assert dev_vaucouleurs.mass_to_light_ratio.unit == "angular / eps" assert dev_vaucouleurs.sersic_constant == pytest.approx(7.66924, 1e-3) assert dev_vaucouleurs.elliptical_effective_radius == 0.6 / np.sqrt(0.5) dev_vaucouleurs = aast.lmp.SphericalDevVaucouleurs( centre=(1.0, 2.0), intensity=1.0, effective_radius=0.6, mass_to_light_ratio=10.0, ) assert dev_vaucouleurs.centre == (1.0, 2.0) assert isinstance(dev_vaucouleurs.centre[0], aast.dim.Length) assert isinstance(dev_vaucouleurs.centre[1], aast.dim.Length) assert dev_vaucouleurs.centre[0].unit == "arcsec" assert dev_vaucouleurs.centre[1].unit == "arcsec" assert dev_vaucouleurs.axis_ratio == 1.0 assert isinstance(dev_vaucouleurs.axis_ratio, float) assert dev_vaucouleurs.phi == 0.0 assert isinstance(dev_vaucouleurs.phi, float) assert dev_vaucouleurs.intensity == 1.0 assert isinstance(dev_vaucouleurs.intensity, aast.dim.Luminosity) assert dev_vaucouleurs.intensity.unit == "eps" assert dev_vaucouleurs.effective_radius == 0.6 assert isinstance(dev_vaucouleurs.effective_radius, aast.dim.Length) assert dev_vaucouleurs.effective_radius.unit_length == "arcsec" assert dev_vaucouleurs.sersic_index == 4.0 assert isinstance(dev_vaucouleurs.sersic_index, float) assert dev_vaucouleurs.mass_to_light_ratio == 10.0 assert isinstance( dev_vaucouleurs.mass_to_light_ratio, aast.dim.MassOverLuminosity ) assert dev_vaucouleurs.mass_to_light_ratio.unit == "angular / eps" assert dev_vaucouleurs.sersic_constant == pytest.approx(7.66924, 1e-3) assert dev_vaucouleurs.elliptical_effective_radius == 0.6 def test__grid_calculations__same_as_dev_vaucouleurs(self): sersic_lp = aast.lmp.EllipticalDevVaucouleurs( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6 ) sersic_mp = aast.lmp.EllipticalDevVaucouleurs( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=2.0, ) sersic_lmp = aast.lmp.EllipticalDevVaucouleurs( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, mass_to_light_ratio=2.0, ) assert ( sersic_lp.profile_image_from_grid(grid=grid) == sersic_lmp.profile_image_from_grid(grid=grid) ).all() assert ( sersic_mp.convergence_from_grid(grid=grid) == sersic_lmp.convergence_from_grid(grid=grid) ).all() # assert (sersic_mp.potential_from_grid(grid=grid) == sersic_lmp.potential_from_grid(grid=grid)).all() assert ( sersic_mp.deflections_from_grid(grid=grid) == sersic_lmp.deflections_from_grid(grid=grid) ).all() def test__spherical_and_elliptical_identical(self): elliptical = aast.lmp.EllipticalDevVaucouleurs( centre=(0.0, 0.0), axis_ratio=1.0, phi=0.0, intensity=1.0, effective_radius=1.0, ) spherical = aast.lmp.SphericalDevVaucouleurs( centre=(0.0, 0.0), intensity=1.0, effective_radius=1.0 ) assert ( elliptical.profile_image_from_grid(grid=grid) == spherical.profile_image_from_grid(grid=grid) ).all() assert ( elliptical.convergence_from_grid(grid=grid) == spherical.convergence_from_grid(grid=grid) ).all() # assert elliptical.potential_from_grid(grid=grid) == spherical.potential_from_grid(grid=grid) np.testing.assert_almost_equal( elliptical.deflections_from_grid(grid=grid), spherical.deflections_from_grid(grid=grid), ) class TestSersicRadialGradient: def test__constructor_and_units(self): sersic = aast.lmp.EllipticalSersicRadialGradient( centre=(1.0, 2.0), axis_ratio=0.5, phi=45.0, intensity=1.0, effective_radius=0.6, sersic_index=4.0, mass_to_light_ratio=10.0, mass_to_light_gradient=-1.0, ) assert sersic.centre == (1.0, 2.0) assert isinstance(sersic.centre[0], aast.dim.Length) assert isinstance(sersic.centre[1], aast.dim.Length) assert sersic.centre[0].unit == "arcsec" assert sersic.centre[1].unit == "arcsec" assert sersic.axis_ratio == 0.5 assert isinstance(sersic.axis_ratio, float) assert sersic.phi == 45.0 assert isinstance(sersic.phi, float) assert sersic.intensity == 1.0 assert isinstance(sersic.intensity, aast.dim.Luminosity) assert sersic.intensity.unit == "eps" assert sersic.effective_radius == 0.6 assert isinstance(sersic.effective_radius, aast.dim.Length) assert sersic.effective_radius.unit_length == "arcsec" assert sersic.sersic_index == 4.0 assert isinstance(sersic.sersic_index, float) assert sersic.mass_to_light_ratio == 10.0 assert isinstance(sersic.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert sersic.mass_to_light_ratio.unit == "angular / eps" assert sersic.mass_to_light_gradient == -1.0 assert isinstance(sersic.mass_to_light_gradient, float) assert sersic.sersic_constant == pytest.approx(7.66925, 1e-3) assert sersic.elliptical_effective_radius == 0.6 / np.sqrt(0.5) sersic = aast.lmp.SphericalSersicRadialGradient( centre=(1.0, 2.0), intensity=1.0, effective_radius=0.6, sersic_index=4.0, mass_to_light_ratio=10.0, mass_to_light_gradient=-1.0, ) assert sersic.centre == (1.0, 2.0) assert isinstance(sersic.centre[0], aast.dim.Length) assert isinstance(sersic.centre[1], aast.dim.Length) assert sersic.centre[0].unit == "arcsec" assert sersic.centre[1].unit == "arcsec" assert sersic.axis_ratio == 1.0 assert isinstance(sersic.axis_ratio, float) assert sersic.phi == 0.0 assert isinstance(sersic.phi, float) assert sersic.intensity == 1.0 assert isinstance(sersic.intensity, aast.dim.Luminosity) assert sersic.intensity.unit == "eps" assert sersic.effective_radius == 0.6 assert isinstance(sersic.effective_radius, aast.dim.Length) assert sersic.effective_radius.unit_length == "arcsec" assert sersic.sersic_index == 4.0 assert isinstance(sersic.sersic_index, float) assert sersic.mass_to_light_ratio == 10.0 assert isinstance(sersic.mass_to_light_ratio, aast.dim.MassOverLuminosity) assert sersic.mass_to_light_ratio.unit == "angular / eps" assert sersic.mass_to_light_gradient == -1.0 assert isinstance(sersic.mass_to_light_gradient, float) assert sersic.sersic_constant == pytest.approx(7.66925, 1e-3) assert sersic.elliptical_effective_radius == 0.6 def test__grid_calculations__same_as_sersic_radial_gradient(self): sersic_lp = aast.lmp.EllipticalSersic( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, ) sersic_mp = aast.lmp.EllipticalSersicRadialGradient( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, mass_to_light_ratio=2.0, mass_to_light_gradient=0.5, ) sersic_lmp = aast.lmp.EllipticalSersicRadialGradient( axis_ratio=0.7, phi=1.0, intensity=1.0, effective_radius=0.6, sersic_index=2.0, mass_to_light_ratio=2.0, mass_to_light_gradient=0.5, ) assert ( sersic_lp.profile_image_from_grid(grid=grid) == sersic_lmp.profile_image_from_grid(grid=grid) ).all() assert ( sersic_mp.convergence_from_grid(grid=grid) == sersic_lmp.convergence_from_grid(grid=grid) ).all() # assert (sersic_mp.potential_from_grid(grid=grid) == sersic_lmp.potential_from_grid(grid=grid)).all() assert ( sersic_mp.deflections_from_grid(grid=grid) == sersic_lmp.deflections_from_grid(grid=grid) ).all() def test__spherical_and_elliptical_identical(self): elliptical = aast.lmp.EllipticalSersicRadialGradient( centre=(0.0, 0.0), axis_ratio=1.0, phi=0.0, intensity=1.0, effective_radius=1.0, ) spherical = aast.lmp.SphericalSersicRadialGradient( centre=(0.0, 0.0), intensity=1.0, effective_radius=1.0 ) assert ( elliptical.profile_image_from_grid(grid=grid) == spherical.profile_image_from_grid(grid=grid) ).all() assert ( elliptical.convergence_from_grid(grid=grid) == spherical.convergence_from_grid(grid=grid) ).all() # assert elliptical.potential_from_grid(grid=grid) == spherical.potential_from_grid(grid=grid) np.testing.assert_almost_equal( elliptical.deflections_from_grid(grid=grid), spherical.deflections_from_grid(grid=grid), )

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aaa9e12aff7dccc530ed459f70a72608562d7dce

702

py

Python

examples/python/cpu/tensors/ocean_arange_01.py

kant/ocean-tensor-package

fb3fcff8bba7f4ef6cd8b8d02f0e1be1258da02d

[ "Apache-2.0" ]

27

2018-08-16T21:32:49.000Z

2021-11-30T10:31:08.000Z

examples/python/cpu/tensors/ocean_arange_01.py

kant/ocean-tensor-package

fb3fcff8bba7f4ef6cd8b8d02f0e1be1258da02d

[ "Apache-2.0" ]

null

examples/python/cpu/tensors/ocean_arange_01.py

kant/ocean-tensor-package

fb3fcff8bba7f4ef6cd8b8d02f0e1be1258da02d

[ "Apache-2.0" ]

13

2018-08-17T17:33:16.000Z

2021-11-30T10:31:09.000Z

import pyOcean_cpu as ocean print(ocean.arange(10)) print(ocean.arange(2,10)) print(ocean.arange(2,10,3,ocean.int8)) print(ocean.arange(10,2,-3,ocean.half)) print(ocean.arange(10.)) print(ocean.arange(2.,10)) print(ocean.arange(2,10,3.,ocean.int8)) print(ocean.arange(10,2.,-3,ocean.half)) print("\n--------- Non-integer step ---------") print(ocean.arange(2,5,0.3)) print("\n--------- Single element ---------") print(ocean.arange(2,5,10)) print(ocean.arange(2,5,ocean.inf)) print("\n--------- Empty ---------") print(ocean.arange(5,2)) print(ocean.arange(2,5,-10)) print(ocean.arange(2,5,-ocean.inf)) print(ocean.arange(5,2.)) print(ocean.arange(2,5,-10.)) print(ocean.arange(2,5,-ocean.inf))

24.206897

47

0.652422

123

702

3.715447

0.178862

0.371991

0.595186

0.40919

0.857768

0.818381

0

0.081448

0.055556

702

28

48

25.071429

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0.095238

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0.14408

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1

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11

2ad81f3a256e53fb3497681f735a0f1d7340de0c

27,629

py

Python

digsby/src/tests/mock/mockprofiles.py

ifwe/digsby

f5fe00244744aa131e07f09348d10563f3d8fa99

[ "Python-2.0" ]

35

2015-08-15T14:32:38.000Z

2021-12-09T16:21:26.000Z

digsby/src/tests/mock/mockprofiles.py

niterain/digsby

16a62c7df1018a49eaa8151c0f8b881c7e252949

[ "Python-2.0" ]

4

2015-09-12T10:42:57.000Z

2017-02-27T04:05:51.000Z

digsby/src/tests/mock/mockprofiles.py

niterain/digsby

16a62c7df1018a49eaa8151c0f8b881c7e252949

[ "Python-2.0" ]

15

2015-07-10T23:58:07.000Z

2022-01-23T22:16:33.000Z

from util import Storage MockProfiles = Storage( Aaron=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Aaron JID:  brok3nhalo@gmail.com Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> """, Chris=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Chis JID:  stelminator@gmail.com Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> """, Jeff=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Jeff JID:  Jeff@aol.com Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> """, Kevin=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Kevin JID:  Kevin@yahoo.com Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> Once upon a midnight dreary, while my thumbs grew weak and weary My whole library of Zelda games laid out upon the floor Each I conquered, fully finished, from original to "Minish," Yet my thirst did not diminish for a kingdom to explore Instantly I wanted more With my catalog completed, I began to feel defeated And absurdly missed the heated battles waged throughout the war RPGs, I felt, were boring, but my friends replied, ignoring, And at once began assuring that I simply would adore The next game to hit to the store So they told me, with great vigor, that this new game would be bigger Than the last hit, "Chrono Trigger," which they took months to explore But the fighting style I hated. To attack, my turn I waited As my enemy invaded, and did knock me on the floor 'Twas entitled, "Evermore" And they asked me, "Don't you love it?" But I said that they could shove it I was sick and tired of it and its "Gotcha Last" type war Though they thought that it was uncool, I retreated to the old school And proceeded to save Hyrule like the good old days of yore There I'll stay, forevermore ( <a href="http://forums.progressiveboink.com/">Add Comment</a> ) """, Mike=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Mike JID:  Mike@hotmail.com Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> """, Steve=""" <TABLE WIDTH=100% cellpadding=1 border=0><TR><TD> <TABLE WIDTH=100% cellpadding=0> <TR><TD valign=center><IMG SRC="C:\jabber.png">  Steve JID:  shaps776@jabber.org Subscription:  Both <TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Gaim (5) Status:  Free for Chat Getting ready for class and then making a GUI for this IM client because it roxorssssssssss<TABLE WIDTH=100% BORDER=0 CELLPADDING=2 CELLSPACING=0> <TR><TD><IMG SRC="C:\line.png" width='210'></TD></TR></TABLE> Resource:  Psi (10) Status:  Extended Away Getting ready for class and then making a GUI for this IM client because it roxorssssssssss</TD><TD width=64 valign=top align=center> <table cellpadding=2 border=0><tr><td align=center><img src="C:\icon.png"> </td></tr></table> <a href=#>Hide Profile </a> </TD></TR></TABLE> <TABLE WIDTH=100% cellpadding=0 border=0><TR><TD><img src="C:\line.png" width='270'> <table cellpadding=1 cellspacing=1><tr><td></td></tr></table> Full Name:  Steve Shapiro Birthday:  11/20/1982 Phone:  917-757-7555 Email:  <a href=mailto:shaps776@gmail.com>shaps776@gmail.com</a> Website:  <a href=http://www.digsby.com>http://www.digsby.com</a> <table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Additional Information: Here is my extensive information section which may have a whole paragraph<table cellpadding=4 cellspacing=0><tr><td></td></tr></table> Home Address: (<a href=http://maps.google.com>Map</a>) Address Line 125 Tech Park Drive Rochester, NY 14623 <table cellpadding=4 cellspacing=0><tr><td></td></tr></table>Company:  dotSyntax, LLC Department:  Software Position:  HCI Guy Role:  Do stuff Website:  <a href=http://www.dotsyntax.com>http://www.dotsyntax.com</a> </TD></TR></TABLE> </TD></TR></TABLE> """, Dude=""" Once upon a midnight dreary, while my thumbs grew weak and weary My whole library of Zelda games laid out upon the floor Each I conquered, fully finished, from original to "Minish," Yet my thirst did not diminish for a kingdom to explore Instantly I wanted more With my catalog completed, I began to feel defeated And absurdly missed the heated battles waged throughout the war RPGs, I felt, were boring, but my friends replied, ignoring, And at once began assuring that I simply would adore The next game to hit to the store So they told me, with great vigor, that this new game would be bigger Than the last hit, "Chrono Trigger," which they took months to explore But the fighting style I hated. To attack, my turn I waited As my enemy invaded, and did knock me on the floor 'Twas entitled, "Evermore" And they asked me, "Don't you love it?" But I said that they could shove it I was sick and tired of it and its "Gotcha Last" type war Though they thought that it was uncool, I retreated to the old school And proceeded to save Hyrule like the good old days of yore There I'll stay, forevermore ( <a href="http://forums.progressiveboink.com/">Add Comment</a> ) """ )

73.874332

475

0.605016

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27,629

3.826047

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0.093324

0.122039

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0.164863

27,629

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73.874332

0.66005

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0.99358

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1

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1

0

null

0

9

6301c66be5c3ce9864787b7b8b4bebdf8f82c11c

3,183

py

Python

tests/test_loss.py

jcreinhold/uncertaintorch

0cdc9f25fefad938c9f0bd3a6b40dfaa362dfca5

[ "Apache-2.0" ]

1

2021-03-21T23:13:45.000Z

tests/test_loss.py

jcreinhold/uncertaintorch

0cdc9f25fefad938c9f0bd3a6b40dfaa362dfca5

[ "Apache-2.0" ]

null

tests/test_loss.py

jcreinhold/uncertaintorch

0cdc9f25fefad938c9f0bd3a6b40dfaa362dfca5

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ tests.test_loss test the uncertaintorch loss functions Author: Jacob Reinhold (jacob.reinhold@jhu.edu) Created on: Jan 14, 2020 """ import unittest import torch from uncertaintorch.learn import * class TestLoss(unittest.TestCase): def setUp(self): pass def test_mseonlyloss_nomask(self): fn = MSEOnlyLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,1,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_mseonlyloss_mask(self): fn = MSEOnlyLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,2,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_gaussiandiagloss_nomask(self): fn = GaussianDiagLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,1,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_gaussiandiagloss_mask(self): fn = GaussianDiagLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,2,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_l1onlyloss_nomask(self): fn = L1OnlyLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,1,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_l1onlyloss_mask(self): fn = L1OnlyLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,2,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_laplaciandiagloss_nomask(self): fn = LaplacianDiagLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,1,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_laplaciandiagloss_mask(self): fn = LaplacianDiagLoss() x, y = (torch.zeros((2,1,2,2,2)), torch.zeros((2,1,2,2,2))), torch.zeros((2,2,2,2,2)) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_focalloss_nomask(self): fn = FocalLoss() x, y = torch.zeros((2,2,2,2,2)), torch.zeros((2,2,2,2),dtype=torch.long) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_focalloss_mask(self): fn = FocalLoss() x, y = torch.zeros((2,2,2,2,2)), torch.zeros((2,2,2,2),dtype=torch.long) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_extendedcrossentropy_nomask(self): fn = ExtendedCrossEntropy() x, y = (torch.zeros((2,2,2,2,2)), torch.zeros((2,2,2,2,2))), torch.zeros((2,2,2,2),dtype=torch.long) loss = fn(x, y) self.assertEqual(loss.item(), 0) def test_extendedcrossentropy_mask(self): fn = ExtendedCrossEntropy() x, y = (torch.zeros((2,2,2,2,2)), torch.zeros((2,2,2,2,2))), torch.zeros((2,2,2,2),dtype=torch.long) loss = fn(x, y) self.assertEqual(loss.item(), 0) def tearDown(self): pass if __name__ == '__main__': unittest.main()

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3,183

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0.11284

0.103024

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0.053751

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0

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0.229658

3,183

102

109

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0.651305

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0

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0.171429

1

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0

null

0

1

0

1

0

null

0

7

2d77e1daac5983e56351de236bcde1ac2993133a

2,308

py

Python

agents/dqn.py

pvnieo/beating-atari

a38a3f106cb4e717ded205c37a95b857d8d91e4d

[ "Apache-2.0" ]

1

2019-12-12T22:16:10.000Z

agents/dqn.py

pvnieo/beating-atari

a38a3f106cb4e717ded205c37a95b857d8d91e4d

[ "Apache-2.0" ]

null

agents/dqn.py

pvnieo/beating-atari

a38a3f106cb4e717ded205c37a95b857d8d91e4d

[ "Apache-2.0" ]

null

# 3p import torch from torch.nn.functional import smooth_l1_loss # project from .base_model import DQNBasedModel class DQNNips(DQNBasedModel): def __init__(self, env, network, policy, memory, optimizer, outputs_dir, logger, discount_factor=0.99): super().__init__(env, network, policy, memory, optimizer, outputs_dir, logger, discount_factor) @property def name(self): return "dqn_nips" def fit_batch(self, states, actions, rewards, next_states, is_terminals): target_q_values = self.online_net(next_states) # If terminal, we use y_i = r_i instead of y_i = r_i + gamma * max Q target_q_values[is_terminals] = 0 # Compute targets: y_i = r_i + gamma * max Q target_q_values = (torch.FloatTensor(rewards) + self.discount_factor * torch.max(target_q_values, dim=1)[0]).reshape(-1, 1) # compute loss predicted_q_values = torch.gather(self.online_net(states), 1, torch.LongTensor(actions).reshape(-1, 1)) loss = smooth_l1_loss(predicted_q_values, target_q_values) # optimize self.optimizer.zero_grad() loss.backward() return loss.item() def update_target_net(self): pass class DQN(DQNBasedModel): def __init__(self, env, network, policy, memory, optimizer, outputs_dir, logger, discount_factor=0.99): super().__init__(env, network, policy, memory, optimizer, outputs_dir, logger, discount_factor) @property def name(self): return "dqn" def fit_batch(self, states, actions, rewards, next_states, is_terminals): target_q_values = self.target_net(next_states) # If terminal, we use y_i = r_i instead of y_i = r_i + gamma * max Q target_q_values[is_terminals] = 0 # Compute targets: y_i = r_i + gamma * max Q- target_q_values = (torch.FloatTensor(rewards) + self.discount_factor * torch.max(target_q_values, dim=1)[0]).reshape(-1, 1) # compute loss predicted_q_values = torch.gather(self.online_net(states), 1, torch.LongTensor(actions).reshape(-1, 1)) loss = smooth_l1_loss(predicted_q_values, target_q_values) # optimize self.optimizer.zero_grad() loss.backward() return loss.item()

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0.233969

2,308

58

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false

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null

0

1

0

1

0

null

0

7

2dd6d094ccdefa5b0bafd66fb85b544a22dccf6b

110

py

Python

unitpy/units/__init__.py

jenders97/unitpy

a39fefe1c109b57c174eeba53b877f32f044de0f

[ "MIT" ]

null

unitpy/units/__init__.py

jenders97/unitpy

a39fefe1c109b57c174eeba53b877f32f044de0f

[ "MIT" ]

null

unitpy/units/__init__.py

jenders97/unitpy

a39fefe1c109b57c174eeba53b877f32f044de0f

[ "MIT" ]

null

from unitpy.units.mass import * from unitpy.units.current import * from unitpy.units.light_intensity import *

27.5

42

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16

110

5.5

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0.511364

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0

0.109091

110

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36.666667

0.897959

0

1

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true

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null

1

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null

0

1

0

1

0

1

0

8

fa939b8643aed6c3d712b68340c7d3b25e6242ce

7,952

py

Python

cifar_nets.py

sashkarivkind/imagewalker

999e1ae78cfe1512e1be894d9e7891a7d0c41233

[ "Apache-2.0" ]

2

2021-04-28T13:33:45.000Z

2021-11-09T14:31:09.000Z

cifar_nets.py

sashkarivkind/imagewalker

999e1ae78cfe1512e1be894d9e7891a7d0c41233

[ "Apache-2.0" ]

null

cifar_nets.py

sashkarivkind/imagewalker

999e1ae78cfe1512e1be894d9e7891a7d0c41233

[ "Apache-2.0" ]

1

2021-03-07T13:25:59.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ cifar syclop selected nets """ import sys sys.path.insert(1, '/home/labs/ahissarlab/orra/imagewalker') import numpy as np import tensorflow.keras as keras import tensorflow as tf def cnn_gru(n_timesteps = 5, hidden_size = 128,input_size = 32, cnn_dropout=0.4,rnn_dropout=0.2, lr = 5e-4, concat = True): ''' CNN GRU combination that extends the CNN to a network that achieves ~80% accuracy on full res cifar. Reaches 62% on low_res syclop with hyperparameters: hs = 256, sample_size = 10, cnn_dropout = 0.4 and rnn dropout = 0.2 lr = 5e-4 res = 8 ''' inputA = keras.layers.Input(shape=(n_timesteps,input_size,input_size,3)) inputB = keras.layers.Input(shape=(n_timesteps,2)) # define CNN model x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3),activation='relu', padding = 'same'))(inputA) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) print(x1.shape) x1=keras.layers.TimeDistributed(keras.layers.Flatten())(x1) print(x1.shape) if concat: x = keras.layers.Concatenate()([x1,inputB]) else: x = x1 print(x.shape) # define LSTM model x = keras.layers.GRU(hidden_size,input_shape=(n_timesteps, None), return_sequences=True,recurrent_dropout=rnn_dropout, kernel_regularizer=keras.regularizers.l1_l2(l1=0.01, l2=0.01))(x) x = keras.layers.Flatten()(x) x = keras.layers.Dense(10,activation="softmax")(x) model = keras.models.Model(inputs=[inputA,inputB],outputs=x, name = 'cnn_gru_{}'.format(concat)) opt=tf.keras.optimizers.Adam(lr=lr) model.compile( optimizer=opt, loss="sparse_categorical_crossentropy", metrics=["sparse_categorical_accuracy"], ) return model def parallel_gru(n_timesteps = 10, hidden_size = 256,input_size = 8, cnn_dropout=0.4,rnn_dropout=0.2, lr = 5e-4, concat = True): ''' CNN RNN combination that extends the CNN to a network that achieves ~80% accuracy on full res cifar. Parameters ---------- n_timesteps : TYPE, optional DESCRIPTION. The default is 5. img_dim : TYPE, optional DESCRIPTION. The default is 32. hidden_size : TYPE, optional DESCRIPTION. The default is 128. input_size : TYPE, optional DESCRIPTION. The default is 32. Returns ------- model : TYPE DESCRIPTION. ''' inputA = keras.layers.Input(shape=(n_timesteps,input_size,input_size,3)) inputB = keras.layers.Input(shape=(n_timesteps,2)) ###################### CNN Chanell 1####################################### x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3), activation='relu',padding = 'same'))(inputA) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3), activation='relu',padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) ###################### Parallel Chanell 1################################## rnn_temp = keras.layers.TimeDistributed(keras.layers.Flatten())(x1) if concat: rnn_temp = keras.layers.Concatenate()([rnn_temp,inputB]) else: rnn_temp = rnn_temp print('flat shape after cnn1', rnn_temp.shape) rnn_x = keras.layers.GRU( hidden_size,input_shape=(n_timesteps, None), kernel_regularizer=keras.regularizers.l1_l2(l1=0.01, l2=0.01), return_sequences=True,recurrent_dropout=2*rnn_dropout, )(rnn_temp) print('gru hidden states 1 ', rnn_x.shape) ###################### CNN Chanell 2 ####################################### x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2),name = 'test'),name = 'test')(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) ###################### Parallel Chanell 2 ################################## rnn_temp = keras.layers.TimeDistributed(keras.layers.Flatten())(x1) print('flat shape after cnn2',rnn_temp.shape) if concat: rnn_temp = keras.layers.Concatenate()([rnn_x,rnn_temp,inputB]) else: rnn_temp = keras.layers.Concatenate()([rnn_x,rnn_temp]) print(' cnn2 input combined with fst hidden state', rnn_temp.shape) rnn_x = keras.layers.GRU( hidden_size,input_shape=(n_timesteps, None), kernel_regularizer=keras.regularizers.l1_l2(l1=0.01, l2=0.01), return_sequences=True,recurrent_dropout=2*rnn_dropout, )(rnn_temp) print('gru hidden states 2 ', rnn_x.shape) ###################### CNN Chanell 3 ####################################### x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1) x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1) x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1) print(x1.shape) ###################### Parallel Chanell 3 ################################## # rnn_temp = keras.layers.TimeDistributed(keras.layers.Flatten())(x1) # print('flat shape after cnn3',rnn_temp.shape) # if concat: # rnn_temp = keras.layers.Concatenate()([rnn_x,rnn_temp,inputB]) # else: # rnn_temp = keras.layers.Concatenate()([rnn_x,rnn_temp]) # print(' cnn23input combined with snd hidden state', rnn_temp.shape) # rnn_x = keras.layers.GRU(hidden_size,input_shape=(n_timesteps, None),return_sequences=True,recurrent_dropout=2*rnn_dropout)(rnn_temp) # print('gru hidden states 3 ', rnn_x.shape) x1=keras.layers.TimeDistributed(keras.layers.Flatten())(x1) if concat: x = keras.layers.Concatenate()([x1,rnn_x,inputB]) else: x = keras.layers.Concatenate()([x1,rnn_x]) print(x.shape) # define LSTM model x = keras.layers.GRU(hidden_size,input_shape=(n_timesteps, None),return_sequences=True,recurrent_dropout=rnn_dropout)(x) x = keras.layers.Flatten()(x) x = keras.layers.Dense(10,activation="softmax")(x) model = keras.models.Model(inputs=[inputA,inputB],outputs=x, name = 'parallel_gru_v1_{}'.format(concat)) opt=tf.keras.optimizers.Adam(lr=lr) model.compile( optimizer=opt, loss="sparse_categorical_crossentropy", metrics=["sparse_categorical_accuracy"], ) return model

43.933702

139

0.638707

1,024

7,952

4.839844

0.142578

0.175343

0.152139

0.181396

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0.867837

0.856538

0.811138

0.803672

0.76937

0

0.03871

0.181338

7,952

181

140

43.933702

0.722581

0.177943

0

0.712871

0

0.070199

0.025497

0

1

0.019802

false

0

0.039604

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0.079208

0.09901

0

null

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1

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1

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null

0

8

87b0afdec783608333a5a0082af09774d6493ad3

22,455

py

Python

v0/aia_eis_v0/goa/evolution_based/differential_evolution/de_0.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

1

2022-03-02T12:57:19.000Z

v0/aia_eis_v0/goa/evolution_based/differential_evolution/de_0.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

null

v0/aia_eis_v0/goa/evolution_based/differential_evolution/de_0.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

null

import copy import math import random from time import perf_counter import os import sys sys.path.append('../../../') from utils.file_utils.filename_utils import get_ecm_num_str, get_Num_len from data_processor.GOA_simulation.GOA_ECMs_simulation import load_sim_ecm_para_config_dict from goa.GOA_criterions import goa_criterion_pack from GA_pack.fittness_functions.eis_fitness import cal_EIS_WSE_fitness_1 class DE_0: """ Refer: Paper: paper0: Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces webs: 差分进化算法（Differential Evolution) https://blog.csdn.net/qq_37423198/article/details/77856744 Adjustable parameters: casual: number of search agents number of iteration unique: Attention: Version: 0 """ class Entity: def __init__(self, limits_list, fitness_function): self.limits_list = limits_list self.fitness_function = fitness_function self.x_list = [random.uniform(limit[0], limit[1]) for limit in limits_list] self.fitness = fitness_function(self.x_list) def update(self): for i in range(len(self.limits_list)): if self.x_list[i] > self.limits_list[i][1]: self.x_list[i] = self.limits_list[i][1] if self.x_list[i] < self.limits_list[i][0]: self.x_list[i] = self.limits_list[i][0] self.fitness = self.fitness_function(self.x_list) def __init__(self, iter_num, entity_num, limits_list, fitness_function, F=None, CR=0.9): self.iter_num = iter_num # paper0: a reasonable choice for entity_num is 5 * D ~ 10 * D (D: dimension), and has to > 4 self.entity_num = entity_num self.limits_list = limits_list self.fitness_function = fitness_function # paper0: F = 0.5 self.F = F # paper0: CR = 0.1 self.CR = CR self.entities_list = [self.Entity(limits_list, fitness_function) for i in range(entity_num)] self.global_best_entity = self.Entity(limits_list, fitness_function) def search(self): current_best_entity_list = [] global_best_entity_list = [] for iter_index in range(self.iter_num): current_best_entity = sorted(self.entities_list, key=lambda entity:entity.fitness, reverse=False)[0] current_best_entity_list.append(current_best_entity) if current_best_entity.fitness < self.global_best_entity.fitness: self.global_best_entity = copy.deepcopy(current_best_entity) global_best_entity_list.append(current_best_entity) else: global_best_entity_list.append(self.global_best_entity) if self.F == None: self.F = random.random() / 2 + 0.5 for x_index in range(self.entity_num): x1_index = random.randint(0, self.entity_num - 1) while x1_index == x_index: x1_index = random.randint(0, self.entity_num - 1) x2_index = random.randint(0, self.entity_num - 1) while (x2_index == x1_index) or (x2_index == x_index): x2_index = random.randint(0, self.entity_num - 1) x3_index = random.randint(0, self.entity_num - 1) while (x3_index == x2_index) or (x3_index == x1_index) or (x3_index == x_index): x3_index = random.randint(0, self.entity_num - 1) tmp_x_list = [] counter = 0 for a, b, c in zip(self.entities_list[x1_index].x_list, self.entities_list[x2_index].x_list, self.entities_list[x3_index].x_list): # Mutation t_x = a + self.F * (b - c) # Crossover if random.random() < self.CR: tmp_x_list.append(t_x) else: tmp_x_list.append(self.entities_list[x_index].x_list[counter]) counter += 1 tmp_entity = self.Entity(self.limits_list, self.fitness_function) tmp_entity.x_list = tmp_x_list tmp_entity.update() # Selection (Greedy) if tmp_entity.fitness < self.entities_list[x_index].fitness: self.entities_list[x_index] = copy.deepcopy(tmp_entity) return current_best_entity_list, global_best_entity_list # if __name__ == '__main__': # iter_num = 1000 # entity_num = 10 # dim = 5 # # f1_limits_list = [[-180, 70] for i in range(dim)] # from GA_pack.fittness_functions.f1 import f1 # f1_fitness_function = f1 # # de = DE_0(iter_num, entity_num, f1_limits_list, f1_fitness_function) # current_best_entity_list, global_best_entity_list = de.search() # print('Best entity position:', de.global_best_entity.x_list) # print('Fitness:', de.global_best_entity.fitness) # # # Draw the best universe in each iteration. # iter_list = [i for i in range(iter_num)] # cur_fitness_list = [entity.fitness for entity in current_best_entity_list] # cur_global_fitness_list = [entity.fitness for entity in global_best_entity_list] # # import matplotlib.pyplot as plt # fig, ax = plt.subplots() # line1, = ax.plot(iter_list, cur_fitness_list, label='Current Iteration {0}\nentity number {1}\nDimension {2}'.format(iter_num, entity_num, dim)) # line1.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break # # line2, = ax.plot(iter_list, cur_global_fitness_list, label='Current Global Iteration {0}\nentity number {1}\nDimension {2}'.format(iter_num, entity_num, dim)) # # line2.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break # ax.legend() # plt.xlabel('Iteration times') # plt.ylabel('Error rate') # plt.title('Search the minimum of f1 = sum(Xi ^ 2)') # plt.show() class DE_1: """ Refer: Paper: paper0: Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces webs: 差分进化算法（Differential Evolution) https://blog.csdn.net/qq_37423198/article/details/77856744 Adjustable parameters: casual: number of search agents number of iteration unique: Attention: Version: 0 """ class Entity: def __init__(self, limits_list, fitness_function): self.limits_list = limits_list self.fitness_function = fitness_function self.x_list = [random.uniform(limit[0], limit[1]) for limit in limits_list] self.fitness = fitness_function(self.x_list) def update(self): for i in range(len(self.limits_list)): if self.x_list[i] > self.limits_list[i][1]: self.x_list[i] = self.limits_list[i][1] if self.x_list[i] < self.limits_list[i][0]: self.x_list[i] = self.limits_list[i][0] self.fitness = self.fitness_function(self.x_list) def __init__(self, iter_num, entity_num, limits_list, fitness_function, F=None, CR=0.9): self.iter_num = iter_num # paper0: a reasonable choice for entity_num is 5 * D ~ 10 * D (D: dimension), and has to > 4 self.entity_num = entity_num self.limits_list = limits_list self.fitness_function = fitness_function # paper0: F = 0.5 self.F = F # paper0: CR = 0.1 self.CR = CR self.entities_list = [self.Entity(limits_list, fitness_function) for i in range(entity_num)] self.global_best_entity = self.Entity(limits_list, fitness_function) def search(self): current_best_entity_list = [] global_best_entity_list = [] for iter_index in range(self.iter_num): self.entities_list.sort(key=lambda en:en.fitness, reverse=False) current_best_entity = self.entities_list[0] if current_best_entity.fitness < self.global_best_entity.fitness: self.global_best_entity = copy.deepcopy(current_best_entity) current_best_entity_list.append(copy.deepcopy(current_best_entity)) global_best_entity_list.append(copy.deepcopy(self.global_best_entity)) if self.F == None: self.F = random.random() / 2 + 0.5 for x_index in range(self.entity_num): x1_index, x2_index, x3_index = random.sample(range(self.entity_num), 3) tmp_x_list = [] for i, a, b, c in zip(range(len(self.limits_list)), self.entities_list[x1_index].x_list, self.entities_list[x2_index].x_list, self.entities_list[x3_index].x_list): # Mutation t_x = a + self.F * (b - c) # Crossover if random.random() < self.CR: tmp_x_list.append(t_x) else: tmp_x_list.append(self.entities_list[x_index].x_list[i]) tmp_entity = self.Entity(self.limits_list, self.fitness_function) tmp_entity.x_list = tmp_x_list tmp_entity.update() # Selection (Greedy) if tmp_entity.fitness < self.entities_list[x_index].fitness: self.entities_list[x_index] = copy.deepcopy(tmp_entity) return current_best_entity_list, global_best_entity_list # if __name__ == '__main__': # iter_num = 1000 # entity_num = 10 # dim = 5 # # f1_limits_list = [[-180, 70] for i in range(dim)] # from GA_pack.fittness_functions.f1 import f1 # # f1_fitness_function = f1 # # de = DE_1(iter_num, entity_num, f1_limits_list, f1_fitness_function) # current_best_entity_list, global_best_entity_list = de.search() # print('Best entity position:', de.global_best_entity.x_list) # print('Fitness:', de.global_best_entity.fitness) # # # Draw the best universe in each iteration. # iter_list = [i for i in range(iter_num)] # cur_fitness_list = [entity.fitness for entity in current_best_entity_list] # cur_global_fitness_list = [entity.fitness for entity in global_best_entity_list] # # import matplotlib.pyplot as plt # # fig, ax = plt.subplots() # line1, = ax.plot(iter_list, cur_fitness_list, # label='Current Iteration {0}\nentity number {1}\nDimension {2}'.format(iter_num, entity_num, dim)) # line1.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break # # line2, = ax.plot(iter_list, cur_global_fitness_list, label='Current Global Iteration {0}\nentity number {1}\nDimension {2}'.format(iter_num, entity_num, dim)) # # line2.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break # ax.legend() # plt.xlabel('Iteration times') # plt.ylabel('Error rate') # plt.title('Search the minimum of f1 = sum(Xi ^ 2)') # plt.show() class DE_EIS: """ Refer: Paper: paper0: Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces webs: 差分进化算法（Differential Evolution) https://blog.csdn.net/qq_37423198/article/details/77856744 Adjustable parameters: casual: number of search agents number of iteration unique: Attention: Version: 0 """ class Entity: def __init__(self, exp_data_dict, fitness_function): self.exp_data_dict = exp_data_dict self.limits_list = exp_data_dict['limit'] self.fitness_function = fitness_function self.x_list = [random.uniform(limit[0], limit[1]) for limit in self.limits_list] self.fitness = fitness_function(self.exp_data_dict, self.x_list) def update(self): for i in range(len(self.limits_list)): if self.x_list[i] > self.limits_list[i][1]: self.x_list[i] = self.limits_list[i][1] if self.x_list[i] < self.limits_list[i][0]: self.x_list[i] = self.limits_list[i][0] self.fitness = self.fitness_function(self.exp_data_dict, self.x_list) def __init__(self, exp_data_dict, iter_num, entity_num, fitness_function=cal_EIS_WSE_fitness_1, F=None, CR=0.9): self.exp_data_dict = exp_data_dict self.limits_list = exp_data_dict['limit'] self.iter_num = iter_num # paper0: a reasonable choice for entity_num is 5 * D ~ 10 * D (D: dimension), and has to > 4 self.entity_num = entity_num self.fitness_function = fitness_function # paper0: F = 0.5 self.F = F # paper0: CR = 0.1 self.CR = CR self.entities_list = [self.Entity(self.exp_data_dict, fitness_function) for i in range(entity_num)] self.global_best_entity = self.Entity(self.exp_data_dict, fitness_function) def search(self): current_best_entity_list = [] global_best_entity_list = [] continue_criterion = True iter = 0 while continue_criterion: self.entities_list.sort(key=lambda en:en.fitness, reverse=False) current_best_entity = self.entities_list[0] if current_best_entity.fitness < self.global_best_entity.fitness: self.global_best_entity = copy.deepcopy(current_best_entity) current_best_entity_list.append(copy.deepcopy(current_best_entity)) global_best_entity_list.append(copy.deepcopy(self.global_best_entity)) if self.F == None: self.F = random.random() / 2 + 0.5 for x_index in range(self.entity_num): x1_index, x2_index, x3_index = random.sample(range(self.entity_num), 3) tmp_x_list = [] for i, a, b, c in zip(range(len(self.limits_list)), self.entities_list[x1_index].x_list, self.entities_list[x2_index].x_list, self.entities_list[x3_index].x_list): # Mutation t_x = a + self.F * (b - c) # Crossover if random.random() < self.CR: tmp_x_list.append(t_x) else: tmp_x_list.append(self.entities_list[x_index].x_list[i]) tmp_entity = self.Entity(self.exp_data_dict, self.fitness_function) tmp_entity.x_list = tmp_x_list tmp_entity.update() # Selection (Greedy) if tmp_entity.fitness < self.entities_list[x_index].fitness: self.entities_list[x_index] = copy.deepcopy(tmp_entity) # -------------------------------------- Update global settings -------------------------------------- # There are two entities only after at least two iteration # If there is global_best_entity_list, use it, # If not, use current_best_entity_list to replace if iter >= 1: x_lists_list = [global_best_entity_list[-2].x_list, global_best_entity_list[-1].x_list] goa_criterion, chi_squared = goa_criterion_pack(x_lists_list=x_lists_list, iter=iter, max_iter_time=self.iter_num, data_dict=self.exp_data_dict) if goa_criterion: continue_criterion = False iter += 1 return current_best_entity_list, global_best_entity_list, iter, chi_squared class DE_EIS_access: """ Refer: Paper: paper0: Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces webs: 差分进化算法（Differential Evolution) https://blog.csdn.net/qq_37423198/article/details/77856744 Adjustable parameters: casual: number of search agents number of iteration unique: Attention: Version: 0 """ class Entity: def __init__(self, exp_data_dict, fitness_function): self.exp_data_dict = exp_data_dict self.limits_list = exp_data_dict['limit'] self.fitness_function = fitness_function self.x_list = [random.uniform(limit[0], limit[1]) for limit in self.limits_list] self.fitness = fitness_function(self.exp_data_dict, self.x_list) def update(self): for i in range(len(self.limits_list)): if self.x_list[i] > self.limits_list[i][1]: self.x_list[i] = self.limits_list[i][1] if self.x_list[i] < self.limits_list[i][0]: self.x_list[i] = self.limits_list[i][0] self.fitness = self.fitness_function(self.exp_data_dict, self.x_list) def __init__(self, exp_data_dict, iter_num, entity_num, fitness_function=cal_EIS_WSE_fitness_1, F=None, CR=0.9): self.exp_data_dict = exp_data_dict self.limits_list = exp_data_dict['limit'] self.iter_num = iter_num # paper0: a reasonable choice for entity_num is 5 * D ~ 10 * D (D: dimension), and has to > 4 self.entity_num = entity_num self.fitness_function = fitness_function # paper0: F = 0.5 self.F = F # paper0: CR = 0.1 self.CR = CR self.entities_list = [self.Entity(self.exp_data_dict, fitness_function) for i in range(entity_num)] self.global_best_entity = self.Entity(self.exp_data_dict, fitness_function) def search(self, res_fn, start_time): current_best_entity_list = [] global_best_entity_list = [] continue_criterion = True iter = 0 while continue_criterion: self.entities_list.sort(key=lambda en:en.fitness, reverse=False) current_best_entity = self.entities_list[0] if current_best_entity.fitness < self.global_best_entity.fitness: self.global_best_entity = copy.deepcopy(current_best_entity) current_best_entity_list.append(copy.deepcopy(current_best_entity)) global_best_entity_list.append(copy.deepcopy(self.global_best_entity)) if self.F == None: self.F = random.random() / 2 + 0.5 for x_index in range(self.entity_num): x1_index, x2_index, x3_index = random.sample(range(self.entity_num), 3) tmp_x_list = [] for i, a, b, c in zip(range(len(self.limits_list)), self.entities_list[x1_index].x_list, self.entities_list[x2_index].x_list, self.entities_list[x3_index].x_list): # Mutation t_x = a + self.F * (b - c) # Crossover if random.random() < self.CR: tmp_x_list.append(t_x) else: tmp_x_list.append(self.entities_list[x_index].x_list[i]) tmp_entity = self.Entity(self.exp_data_dict, self.fitness_function) tmp_entity.x_list = tmp_x_list tmp_entity.update() # Selection (Greedy) if tmp_entity.fitness < self.entities_list[x_index].fitness: self.entities_list[x_index] = copy.deepcopy(tmp_entity) # -------------------------------------- Update global settings -------------------------------------- # There are two entities only after at least two iteration # If there is global_best_entity_list, use it, # If not, use current_best_entity_list to replace if iter >= 1: x_lists_list = [global_best_entity_list[-2].x_list, global_best_entity_list[-1].x_list] goa_criterion, chi_squared = goa_criterion_pack(x_lists_list=x_lists_list, \ iter=iter, \ max_iter_time=self.iter_num, \ data_dict=self.exp_data_dict, \ CS_limit=1e-70) # Write R(RC)_IS_lin-kk_res.txt into a txt file # R(RC)_IS_lin-kk_res.txt = iter_time + fitted_para_list + Chi-Squared + Code running time with open(res_fn, 'a+') as file: line = str(iter) + ',[' \ + ','.join([str(para) for para in global_best_entity_list[-1].x_list]) + '],' \ + str(chi_squared) + ',' + str(perf_counter() - start_time) + '\n' file.write(line) if goa_criterion: continue_criterion = False iter += 1 def access_DE_EIS(): counter = 0 # Iterate on 9 ECMs # for i in range(1, 10): for i in range(2, 10): ecm_sim_folder = '../../../datasets/goa_datasets/simulated' ecm_num = i ecm_num_str = get_ecm_num_str(ecm_num) file_path = os.path.join(ecm_sim_folder, 'ecm_' + ecm_num_str) sim_ecm = load_sim_ecm_para_config_dict(ecm_num, file_path) para_num = len(sim_ecm['para']) # Iterate for 100 times for j in range(100): t_start = perf_counter() # ------------------------------ Change GOA name ------------------------------ goa = DE_EIS_access(exp_data_dict=sim_ecm, iter_num=10000, entity_num=10*para_num) res_fn = 'de_ecm{0}_'.format(i) + get_Num_len(num=j, length=2) + '.txt' # ------------------------------ Change GOA name ------------------------------ goa.search(res_fn, start_time=t_start) counter += 1 print('DE left: {0}'.format(900 - counter)) # access_DE_EIS()

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1

0

1

0

null

0

7

87ba4103abcfd0f5321cf2ea8c53a47098bc5159

143

py

Python

rlagent/memories/__init__.py

YunjaeChoi/rlagent

41062fc1beaa2d5a0765bb782e1a55d1962ab058

[ "MIT" ]

null

rlagent/memories/__init__.py

YunjaeChoi/rlagent

41062fc1beaa2d5a0765bb782e1a55d1962ab058

[ "MIT" ]

null

rlagent/memories/__init__.py

YunjaeChoi/rlagent

41062fc1beaa2d5a0765bb782e1a55d1962ab058

[ "MIT" ]

null

from rlagent.memories.base import Memory from rlagent.memories.replaybuffer import ReplayBuffer from rlagent.memories.nstep import NStepMemory

35.75

54

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7

87dc7c1a3342c1a50641f800e2325fadf800f738

2,006

py

Python

malaya_speech/supervised/unet.py

dtx525942103/malaya-speech

212c4e890d0cbcbbca0037c89a698b68b05db393

[ "MIT" ]

null

malaya_speech/supervised/unet.py

dtx525942103/malaya-speech

212c4e890d0cbcbbca0037c89a698b68b05db393

[ "MIT" ]

null

malaya_speech/supervised/unet.py

dtx525942103/malaya-speech

212c4e890d0cbcbbca0037c89a698b68b05db393

[ "MIT" ]

1

2021-08-19T02:34:41.000Z

from malaya_speech.utils import ( check_file, load_graph, generate_session, nodes_session, ) from malaya_speech.model.tf import UNET, UNETSTFT, UNET1D def load(model, module, quantized = False, **kwargs): path = check_file( file = model, module = module, keys = {'model': 'model.pb'}, quantized = quantized, **kwargs, ) g = load_graph(path['model'], **kwargs) inputs = ['Placeholder'] outputs = ['logits'] input_nodes, output_nodes = nodes_session(g, inputs, outputs) return UNET( input_nodes = input_nodes, output_nodes = output_nodes, sess = generate_session(graph = g, **kwargs), model = model, name = module, ) def load_stft(model, module, instruments, quantized = False, **kwargs): path = check_file( file = model, module = module, keys = {'model': 'model.pb'}, quantized = quantized, **kwargs, ) g = load_graph(path['model'], **kwargs) inputs = ['Placeholder'] outputs = [f'logits_{i}' for i in range(len(instruments))] input_nodes, output_nodes = nodes_session(g, inputs, outputs) return UNETSTFT( input_nodes = input_nodes, output_nodes = output_nodes, instruments = instruments, sess = generate_session(graph = g, **kwargs), model = model, name = module, ) def load_1d(model, module, quantized = False, **kwargs): path = check_file( file = model, module = module, keys = {'model': 'model.pb'}, quantized = quantized, **kwargs, ) g = load_graph(path['model'], **kwargs) inputs = ['Placeholder'] outputs = ['logits'] input_nodes, output_nodes = nodes_session(g, inputs, outputs) return UNET1D( input_nodes = input_nodes, output_nodes = output_nodes, sess = generate_session(graph = g, **kwargs), model = model, name = module, )

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null

0

7

87e9a1a8199362aa568853bda77b869ca855236b

8,901

py

Python

onnxruntime/test/python/contrib_ops/onnx_test_trilu.py

dennyac/onnxruntime

d5175795d2b7f2db18b0390f394a49238f814668

[ "MIT" ]

6,036

2019-05-07T06:03:57.000Z

2022-03-31T17:59:54.000Z

onnxruntime/test/python/contrib_ops/onnx_test_trilu.py

dennyac/onnxruntime

d5175795d2b7f2db18b0390f394a49238f814668

[ "MIT" ]

5,730

2019-05-06T23:04:55.000Z

2022-03-31T23:55:56.000Z

onnxruntime/test/python/contrib_ops/onnx_test_trilu.py

dennyac/onnxruntime

d5175795d2b7f2db18b0390f394a49238f814668

[ "MIT" ]

1,566

2019-05-07T01:30:07.000Z

2022-03-31T17:06:50.000Z

# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. # # Test reference implementation and model for ONNX Runtime conrtib op trilu import onnx import unittest import numpy as np from onnx_contrib_ops_helper import expect def triu_reference_implementation(x, k=0): return np.triu(x, k) def tril_reference_implementation(x, k=0): return np.tril(x, k) class ONNXReferenceImplementationTest(unittest.TestCase): def test_triu(self): node = onnx.helper.make_node( 'Trilu', inputs=['x'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) y = triu_reference_implementation(x) expect(node, inputs=[x], outputs=[y], name='test_triu') def test_triu_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([-1]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_neg') def test_triu_out_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([-7]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_out_neg') def test_triu_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([2]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_pos') def test_triu_out_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([6]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_out_pos') def test_triu_square(self): node = onnx.helper.make_node( 'Trilu', inputs=['x'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) y = triu_reference_implementation(x) expect(node, inputs=[x], outputs=[y], name='test_triu_square') def test_triu_square_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) k = np.array([-1]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_square_neg') def test_triu_one_row_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 1, 5).astype(np.float32) k = np.array([-7]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_one_row_neg') def test_triu_square_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) k = np.array([2]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_square_pos') def test_triu_zero(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], domain="com.microsoft", ) x = np.random.randn(3, 0, 5).astype(np.float32) k = np.array([6]).astype(np.int64) y = triu_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_triu_zero') def test_tril(self): node = onnx.helper.make_node( 'Trilu', inputs=['x'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) y = tril_reference_implementation(x) expect(node, inputs=[x], outputs=[y], name='test_tril') def test_tril_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([-1]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_neg') def test_tril_out_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([-7]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_out_neg') def test_tril_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([2]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_pos') def test_tril_out_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 4, 5).astype(np.float32) k = np.array([6]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_out_pos') def test_tril_square(self): node = onnx.helper.make_node( 'Trilu', inputs=['x'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) y = tril_reference_implementation(x) expect(node, inputs=[x], outputs=[y], name='test_tril_square') def test_tril_square_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) k = np.array([-1]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_square_neg') def test_tril_one_row_neg(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 1, 5).astype(np.float32) k = np.array([-7]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_one_row_neg') def test_tril_square_pos(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 5, 5).astype(np.float32) k = np.array([2]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_square_pos') def test_tril_zero(self): node = onnx.helper.make_node( 'Trilu', inputs=['x', 'k'], outputs=['y'], upper=0, domain="com.microsoft", ) x = np.random.randn(3, 0, 5).astype(np.float32) k = np.array([6]).astype(np.int64) y = tril_reference_implementation(x, k) expect(node, inputs=[x, k], outputs=[y], name='test_tril_zero') if __name__ == '__main__': unittest.main(module=__name__, buffer=True)

30.693103

78

0.530053

1,135

8,901

3.999119

0.068722

0.022913

0.0564

0.10575

0.877286

0.864948

0.862304

0.847323

0

0.026025

0.309291

8,901

289

79

30.799308

0.712264

0.018313

0

0.700422

0

0.085194

0.004809

0

1

0.092827

false

0

0.016878

0.008439

0.122363

0

null

0

1

0

1

0

null

0

7

87fcae1cfd2dd4c21ad48fdbc16ed252caa5898f

13,133

py

Python

scripts/populate_completed_meta_data.py

Cooops/ABUpower

ec84f8f0177b09a09195a974357d328376df7efc

[ "MIT" ]

2

2018-10-09T01:17:21.000Z

2019-05-17T11:01:46.000Z

scripts/populate_completed_meta_data.py

Cooops/ABUpower

ec84f8f0177b09a09195a974357d328376df7efc

[ "MIT" ]

null

scripts/populate_completed_meta_data.py

Cooops/ABUpower

ec84f8f0177b09a09195a974357d328376df7efc

[ "MIT" ]

null

import pandas as pd from db_queries import fetch_data, get_trace_and_log, prune_completed from gen_utils import database_connection, get_search_words, POWER_CONFIG, DUALS_CONFIG def generate_stat_history(setCheck, boolCheck): dataArray = [] if setCheck == 'Alpha' and boolCheck == 'Power': query = ( f""" SELECT completed_product_nick, avg(completed_product_prices), min(completed_product_prices), max(completed_product_prices), count(completed_product_prices), CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as average_length, sum(completed_product_prices) FROM completed_products WHERE completed_product_nick IN ('{setCheck} Black Lotus', '{setCheck} Mox Sapphire', '{setCheck} Mox Jet', '{setCheck} Mox Pearl', '{setCheck} Mox Ruby', '{setCheck} Mox Emerald', '{setCheck} Timetwister', '{setCheck} Ancestral Recall', '{setCheck} Time Walk') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray elif setCheck != 'Alpha' and boolCheck == 'Power': query = ( f""" SELECT completed_product_nick, avg(completed_product_prices), min(completed_product_prices), max(completed_product_prices), count(completed_product_prices), CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as average_length, sum(completed_product_prices) FROM completed_products WHERE completed_product_nick IN ('{setCheck} Black Lotus MTG', '{setCheck} Mox Sapphire', '{setCheck} Mox Jet', '{setCheck} Mox Pearl', '{setCheck} Mox Ruby', '{setCheck} Mox Emerald', '{setCheck} Timetwister', '{setCheck} Ancestral Recall', '{setCheck} Time Walk') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray elif boolCheck == 'Duals': query = ( f""" SELECT completed_product_nick, avg(completed_product_prices), min(completed_product_prices), max(completed_product_prices), count(completed_product_prices), CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as average_length, sum(completed_product_prices) FROM completed_products WHERE completed_product_nick IN ('{setCheck} Tundra MTG', '{setCheck} Underground Sea MTG', '{setCheck} Badlands MTG', '{setCheck} Taiga MTG', '{setCheck} Savannah MTG', '{setCheck} Scrubland MTG', '{setCheck} Volcanic Island MTG', '{setCheck} Bayou MTG', '{setCheck} Plateau MTG', '{setCheck} Tropical Island MTG') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray def generate_index_history(setCheck, setId, boolCheck): dataArray = [] if setCheck == 'Alpha' and boolCheck == 'Power': query = ( f""" SELECT '{setCheck}', '{setId}', sum(stats.avger), sum(stats.miner), sum(stats.maxer), avg(stats.lengther), sum(stats.counter) ,sum(stats.sumer) FROM (SELECT completed_product_nick, avg(completed_product_prices) as avger, min(completed_product_prices) as miner, max(completed_product_prices) as maxer, count(completed_product_prices) as counter, CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as lengther, sum(completed_product_prices) as sumer FROM completed_products WHERE completed_product_nick IN ('{setCheck} Black Lotus', '{setCheck} Mox Sapphire', '{setCheck} Mox Jet', '{setCheck} Mox Pearl', '{setCheck} Mox Ruby', '{setCheck} Mox Emerald', '{setCheck} Timetwister', '{setCheck} Ancestral Recall', '{setCheck} Time Walk') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick) stats; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray elif setCheck != 'Alpha' and boolCheck == 'Power': query = ( f""" SELECT '{setCheck}', '{setId}', sum(stats.avger), sum(stats.miner), sum(stats.maxer), avg(stats.lengther), sum(stats.counter) ,sum(stats.sumer) FROM (SELECT completed_product_nick, avg(completed_product_prices) as avger, min(completed_product_prices) as miner, max(completed_product_prices) as maxer, count(completed_product_prices) as counter, CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as lengther, sum(completed_product_prices) as sumer FROM completed_products WHERE completed_product_nick IN ('{setCheck} Black Lotus MTG', '{setCheck} Mox Sapphire', '{setCheck} Mox Jet', '{setCheck} Mox Pearl', '{setCheck} Mox Ruby', '{setCheck} Mox Emerald', '{setCheck} Timetwister', '{setCheck} Ancestral Recall', '{setCheck} Time Walk') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick) stats; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray elif boolCheck == 'Duals': query = ( f""" SELECT '{setCheck}', '{setId}', sum(stats.avger), sum(stats.miner), sum(stats.maxer), avg(stats.lengther), sum(stats.counter) ,sum(stats.sumer) FROM (SELECT completed_product_nick, avg(completed_product_prices) as avger, min(completed_product_prices) as miner, max(completed_product_prices) as maxer, count(completed_product_prices) as counter, CAST(sum(completed_product_end::date - completed_product_start::date) as double precision)/count(completed_product_end) as lengther, sum(completed_product_prices) as sumer FROM completed_products WHERE completed_product_nick IN ('{setCheck} Tundra MTG', '{setCheck} Underground Sea MTG', '{setCheck} Badlands MTG', '{setCheck} Taiga MTG', '{setCheck} Savannah MTG', '{setCheck} Scrubland MTG', '{setCheck} Volcanic Island MTG', '{setCheck} Bayou MTG', '{setCheck} Plateau MTG', '{setCheck} Tropical Island MTG') AND completed_product_end::date > current_timestamp - interval '90' day GROUP BY completed_product_nick) stats; """ ) data = fetch_data(query) dataArray.append(data.values) return dataArray def insert_stats(cursor, mtgArray): for neach in mtgArray: for each in neach: try: cursor.execute("""INSERT INTO production_completed_products_stats(completed_product_nick, completed_product_avg, completed_product_min, completed_product_max, completed_product_depth, completed_product_avg_length, completed_product_sum) VALUES (%s, %s, %s, %s, %s, %s, %s)""", (each[0], each[1], each[2], each[3], each[4], each[5], each[6])) except Exception as e: get_trace_and_log(e) def insert_index(cursor, mtgArray): for neach in mtgArray: for each in neach: try: cursor.execute("""INSERT INTO production_completed_products_index(completed_product_set_name, completed_product_set_id, completed_product_index_avg, completed_product_index_min, completed_product_index_max, completed_product_index_length_avg, completed_product_index_count_sum, completed_product_index_sum) VALUES (%s, %s, %s, %s, %s, %s, %s, %s)""", (each[0], each[1], each[2], each[3], each[4], each[5], each[6], each[7])) except Exception as e: get_trace_and_log(e) def pipe_duals_stats(): # generate `cursor` (used to execute db queries) cursor = database_connection() # iterate over `DUALS_CONFIG` and pipe each nested array. for each in DUALS_CONFIG: print(f"Pulling {DUALS_CONFIG[each]} from {each}") dualsArray = generate_stat_history(setCheck=each, boolCheck=DUALS_CONFIG[each]) if len(dualsArray) > 0: print(f"Piping nested arrays") insert_stats(cursor=cursor, mtgArray=dualsArray) def pipe_power_stats(): cursor = database_connection() for each in POWER_CONFIG: print(f"Pulling {POWER_CONFIG[each]} from {each}") powerArray = generate_stat_history(setCheck=each, boolCheck=POWER_CONFIG[each]) if len(powerArray) > 0: print(f"Piping nested arrays") insert_stats(cursor=cursor, mtgArray=powerArray) def pipe_duals_index(): cursor = database_connection() for each in DUALS_CONFIG: if each == 'Alpha': print(f"Forming {DUALS_CONFIG[each]} index from {each} stats") dualsArray = generate_index_history(setCheck=each, setId=4, boolCheck=DUALS_CONFIG[each]) if len(dualsArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=dualsArray) elif each == 'Beta': print(f"Forming {DUALS_CONFIG[each]} index from {each} stats") dualsArray = generate_index_history(setCheck=each, setId=5, boolCheck=DUALS_CONFIG[each]) if len(dualsArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=dualsArray) elif each == 'Unlimited': print(f"Forming {DUALS_CONFIG[each]} index from {each} stats") dualsArray = generate_index_history(setCheck=each, setId=6, boolCheck=DUALS_CONFIG[each]) if len(dualsArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=dualsArray) elif each == 'Revised': print(f"Forming {DUALS_CONFIG[each]} index from {each} stats") dualsArray = generate_index_history(setCheck=each, setId=7, boolCheck=DUALS_CONFIG[each]) if len(dualsArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=dualsArray) def pipe_power_index(): cursor = database_connection() for each in POWER_CONFIG: if each == 'Alpha': print(f"Pulling {POWER_CONFIG[each]} from {each} stats") powerArray = generate_index_history(setCheck=each, setId=1, boolCheck=POWER_CONFIG[each]) if len(powerArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=powerArray) elif each == 'Beta': print(f"Pulling {POWER_CONFIG[each]} from {each} stats") powerArray = generate_index_history(setCheck=each, setId=2, boolCheck=POWER_CONFIG[each]) if len(powerArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=powerArray) elif each == 'Unlimited': print(f"Pulling {POWER_CONFIG[each]} from {each} stats") powerArray = generate_index_history(setCheck=each, setId=3, boolCheck=POWER_CONFIG[each]) if len(powerArray) > 0: print(f"Piping nested arrays") insert_index(cursor=cursor, mtgArray=powerArray) def prune_db(cursor): """(cursor) -> () Prunes active_products before making any further calculations (averages, etc.)""" words = get_search_words() # words = ['Revised Tundra MTG'] for value in words: print(f'Pruning {value}....') prune_completed(value, cursor) print('-------------------------------------') print('Succesfully pruned completed_products') print('-------------------------------------') if __name__ == '__main__': inputCheck = input('Beginning once-a-day batch calc script -- are you sure you want to proceed?: ') if inputCheck in ('Y', 'y'): print('I understand. Beggining once-a-day batch script.') prune_db(cursor=database_connection()) print() # begin piping stats pipe_power_stats() print() pipe_duals_stats() print() # begin piping index pipe_power_index() print() pipe_duals_index() print() print('Batch process completed. Data has been successfully inserted.') elif inputCheck in ('N', 'n'): print('Exiting batch process.')

61.657277

389

0.645473

1,509

13,133

5.404241

0.121935

0.170693

0.080932

0.044145

0.828571

0.820356

0.809319

0.799877

0.784672

0.782342

0

0.004324

0.242747

13,133

212

390

61.948113

0.815686

0.02033

0

0.725389

1

0.088083

0.576266

0.208623

0

1

0.046632

false

0

0.015544

0

0.093264

0.15544

0

null

0

1

0

1

0

null

0

8

354c9052b6484bd2a8ee53de9c8d18d73e6ff7f9

5,712

py

Python

stats/user_activity.py

mchubby-3rdparty/mattermost-privileged

8b7eff7eb4c823686b686cf6f4cd14dc7c0f5369

[ "MIT" ]

null

stats/user_activity.py

mchubby-3rdparty/mattermost-privileged

8b7eff7eb4c823686b686cf6f4cd14dc7c0f5369

[ "MIT" ]

null

stats/user_activity.py

mchubby-3rdparty/mattermost-privileged

8b7eff7eb4c823686b686cf6f4cd14dc7c0f5369

[ "MIT" ]

null

#!/usr/bin/env python3 # Someone's Mattermost scripts. # Copyright (c) 2016-2021 by Someone <someone@somenet.org> (aka. Jan Vales <jan@jvales.net>) # published under MIT-License # # Users online # import psycopg2 import psycopg2.extras import config def main(dbconn): msg = "#user_activity #mmstats distinct user activity.\n\n|users ...|day|week|month|since "+config.cutoff_date+"|\n|---|---:|---:|---:|---:|\n" # online cur = dbconn.cursor(cursor_factory=psycopg2.extras.DictCursor) cur.execute(""" SELECT sum(CASE WHEN lastactivity > extract(epoch FROM (NOW() - INTERVAL '1 day'))*1000 THEN 1 ELSE 0 END) AS cnt_day, sum(CASE WHEN lastactivity > extract(epoch FROM (NOW() - INTERVAL '1 week'))*1000 THEN 1 ELSE 0 END) AS cnt_week, sum(CASE WHEN lastactivity > extract(epoch FROM (NOW() - INTERVAL '1 month'))*1000 THEN 1 ELSE 0 END) AS cnt_month, sum(CASE WHEN lastactivity > extract(epoch FROM TIMESTAMP '"""+config.cutoff_date+"""')*1000 THEN 1 ELSE 0 END) AS cnt_cutoff FROM (SELECT users.id, GREATEST(status.lastactivityat, MAX(sessions.lastactivityat), users.updateat) as lastactivity FROM users LEFT JOIN status ON (users.id = status.userid) LEFT JOIN sessions ON (users.id = sessions.userid) GROUP BY users.id, status.lastactivityat, users.updateat) AS a; """) record = cur.fetchall()[0] msg += "|online|"+str(record["cnt_day"])+"|"+str(record["cnt_week"])+"|"+str(record["cnt_month"])+"|"+str(record["cnt_cutoff"])+"|\n" # posts cur = dbconn.cursor(cursor_factory=psycopg2.extras.DictCursor) cur.execute(""" SELECT sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 day'))*1000 THEN 1 ELSE 0 END) AS cnt_day, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 week'))*1000 THEN 1 ELSE 0 END) AS cnt_week, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 month'))*1000 THEN 1 ELSE 0 END) AS cnt_month, sum(CASE WHEN createat > extract(epoch FROM TIMESTAMP '"""+config.cutoff_date+"""')*1000 THEN 1 ELSE 0 END) AS cnt_cutoff FROM (select userid, max(createat) as createat FROM posts GROUP BY userid ORDER BY createat DESC) AS a limit 10 """) record = cur.fetchall()[0] msg += "|posted|"+str(record["cnt_day"])+"|"+str(record["cnt_week"])+"|"+str(record["cnt_month"])+"|"+str(record["cnt_cutoff"])+"|\n" # pubchan posts cur = dbconn.cursor(cursor_factory=psycopg2.extras.DictCursor) cur.execute(""" SELECT sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 day'))*1000 THEN 1 ELSE 0 END) AS cnt_day, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 week'))*1000 THEN 1 ELSE 0 END) AS cnt_week, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 month'))*1000 THEN 1 ELSE 0 END) AS cnt_month, sum(CASE WHEN createat > extract(epoch FROM TIMESTAMP '"""+config.cutoff_date+"""')*1000 THEN 1 ELSE 0 END) AS cnt_cutoff FROM (select userid, max(posts.createat) as createat FROM posts JOIN channels ON (posts.channelid = channels.id) WHERE channels.type='O' GROUP BY userid ORDER BY createat DESC) AS a """) record = cur.fetchall()[0] msg += "|posted in pubchan|"+str(record["cnt_day"])+"|"+str(record["cnt_week"])+"|"+str(record["cnt_month"])+"|"+str(record["cnt_cutoff"])+"|\n" # privchan posts cur = dbconn.cursor(cursor_factory=psycopg2.extras.DictCursor) cur.execute(""" SELECT sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 day'))*1000 THEN 1 ELSE 0 END) AS cnt_day, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 week'))*1000 THEN 1 ELSE 0 END) AS cnt_week, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 month'))*1000 THEN 1 ELSE 0 END) AS cnt_month, sum(CASE WHEN createat > extract(epoch FROM TIMESTAMP '"""+config.cutoff_date+"""')*1000 THEN 1 ELSE 0 END) AS cnt_cutoff FROM (select userid, max(posts.createat) as createat FROM posts JOIN channels ON (posts.channelid = channels.id) WHERE channels.type='P' GROUP BY userid ORDER BY createat DESC) AS a """) record = cur.fetchall()[0] msg += "|posted in privchan|"+str(record["cnt_day"])+"|"+str(record["cnt_week"])+"|"+str(record["cnt_month"])+"|"+str(record["cnt_cutoff"])+"|\n" # privchan posts cur = dbconn.cursor(cursor_factory=psycopg2.extras.DictCursor) cur.execute(""" SELECT sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 day'))*1000 THEN 1 ELSE 0 END) AS cnt_day, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 week'))*1000 THEN 1 ELSE 0 END) AS cnt_week, sum(CASE WHEN createat > extract(epoch FROM (NOW() - INTERVAL '1 month'))*1000 THEN 1 ELSE 0 END) AS cnt_month, sum(CASE WHEN createat > extract(epoch FROM TIMESTAMP '"""+config.cutoff_date+"""')*1000 THEN 1 ELSE 0 END) AS cnt_cutoff FROM (select userid, max(posts.createat) as createat FROM posts JOIN channels ON (posts.channelid = channels.id) WHERE channels.type NOT IN ('O', 'P') GROUP BY userid ORDER BY createat DESC) AS a """) record = cur.fetchall()[0] return msg + "|posted private|"+str(record["cnt_day"])+"|"+str(record["cnt_week"])+"|"+str(record["cnt_month"])+"|"+str(record["cnt_cutoff"])+"|\n"

72.303797

211

0.628501

797

5,712

4.439147

0.130489

0.03957

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0.073488

0.838044

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78

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73.230769

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false

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0

null

0

1

0

1

0

null

0

8

ea3745240198ab0475cdc66a6b1d87cea5d43a77

212

py

Python

codewof/programming/content/en/simple-calculator/solution.py

uccser-admin/programming-practice-prototype

3af4c7d85308ac5bb35bb13be3ec18cac4eb8308

[ "MIT" ]

3

2019-08-29T04:11:22.000Z

2021-06-22T16:05:51.000Z

codewof/programming/content/en/simple-calculator/solution.py

uccser-admin/programming-practice-prototype

3af4c7d85308ac5bb35bb13be3ec18cac4eb8308

[ "MIT" ]

265

2019-05-30T03:51:46.000Z

2022-03-31T01:05:12.000Z

codewof/programming/content/en/simple-calculator/solution.py

samuelsandri/codewof

c9b8b378c06b15a0c42ae863b8f46581de04fdfc

[ "MIT" ]

7

2019-06-29T12:13:37.000Z

2021-09-06T06:49:14.000Z

def calculate(x, y, operator): if operator == '+': return x + y if operator == '-': return x - y if operator == 'x': return x * y if operator == '/': return x // y

21.2

30

0.448113

26

212

3.653846

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0.105263

0.336842

0.536842

0.757895

0.547368

0

0.396226

212

9

31

23.555556

0.742188

0

0.018868

0

1

0.111111

false

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0.555556

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

7

ea775556ee3e42a1c0554dd058ed6efaf62de2ae

460

py

Python

tests/test_d.py

zozzz/yapic.json

becd15702af3f95e3d981d03d823dd859fe51ac4

[ "BSD-2-Clause-FreeBSD" ]

15

2020-04-07T00:08:18.000Z

2022-03-25T11:40:49.000Z

tests/test_d.py

zozzz/yapic.json

becd15702af3f95e3d981d03d823dd859fe51ac4

[ "BSD-2-Clause-FreeBSD" ]

14

2020-04-07T00:15:45.000Z

2021-09-27T11:27:24.000Z

tests/test_d.py

zozzz/yapic.json

becd15702af3f95e3d981d03d823dd859fe51ac4

[ "BSD-2-Clause-FreeBSD" ]

3

2020-04-05T23:20:42.000Z

2021-04-08T07:07:51.000Z

import json as py_json from yapic import json def test_d(): # print(len(json.dumpb(["almafa" * 30000, "almafa" * 30000]))) assert json.dumpb("Á", ensure_ascii=False) == py_json.dumps("Á", ensure_ascii=False).encode("utf-8") assert json.dumpb("\xFF", ensure_ascii=False) == py_json.dumps("\xFF", ensure_ascii=False).encode("utf-8") assert json.dumpb("\uFFFF", ensure_ascii=False) == py_json.dumps("\uFFFF", ensure_ascii=False).encode("utf-8")

46

114

0.68913

71

460

4.309859

0.352113

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0.313725

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0.617647

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460

9

115

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true

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null

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null

0

1

0

1

0

1

0

7

576c01844bb58de116583ed992c60d0a1f015c6d

1,961

py

Python

python/testData/inspections/PyTypeCheckerInspection/BitwiseOrUnionsAndOldStyleUnionsAreEquivalent.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

python/testData/inspections/PyTypeCheckerInspection/BitwiseOrUnionsAndOldStyleUnionsAreEquivalent.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

python/testData/inspections/PyTypeCheckerInspection/BitwiseOrUnionsAndOldStyleUnionsAreEquivalent.py

06needhamt/intellij-community

63d7b8030e4fdefeb4760e511e289f7e6b3a5c5b

[ "Apache-2.0" ]

null

from typing import Union, Optional def expect_old_union(u: Union[int, str]): expect_new_union(u) expect_new_union(42) expect_new_union("42") expect_new_union(<warning descr="Expected type 'int | str', got 'list[int]' instead">[42]</warning>) def expect_new_union(u: int | str): expect_old_union(u) expect_old_union(42) expect_old_union("42") expect_old_union(<warning descr="Expected type 'int | str', got 'list[int]' instead">[42]</warning>) def expect_old_optional(u: Optional[int]): expect_new_optional_none_first(u) expect_new_optional_none_first(42) expect_new_optional_none_first(None) expect_new_optional_none_first(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>) expect_new_optional_none_last(u) expect_new_optional_none_last(42) expect_new_optional_none_last(None) expect_new_optional_none_last(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>) def expect_new_optional_none_first(u: None | int): expect_old_optional(u) expect_old_optional(42) expect_old_optional(None) expect_old_optional(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>) expect_new_optional_none_last(u) expect_new_optional_none_last(42) expect_new_optional_none_last(None) expect_new_optional_none_last(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>) def expect_new_optional_none_last(u: int | None): expect_old_optional(u) expect_old_optional(42) expect_old_optional(None) expect_old_optional(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>) expect_new_optional_none_first(u) expect_new_optional_none_first(42) expect_new_optional_none_first(None) expect_new_optional_none_first(<warning descr="Expected type 'int | None', got 'list[int]' instead">[42]</warning>)

40.020408

119

0.744008

293

1,961

4.604096

0.078498

0.153447

0.226835

0.280208

0.898443

0.890289

0.829503

0.827279

0

0.021176

0.133095

1,961

48

120

40.854167

0.772353

0

0.631579

0

0.209077

0

null

0

0.026316

null

0

null

0

1

0

null

0

1

0

9

57de3582b01a9d54a61fbd1e32d7b51c956b06a0

252

py

Python

Codewars/8kyu/exclamation-marks-series-number-11-replace-all-vowel-to-exclamation-mark-in-the-sentence/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

7

2017-09-20T16:40:39.000Z

2021-08-31T18:15:08.000Z

Codewars/8kyu/exclamation-marks-series-number-11-replace-all-vowel-to-exclamation-mark-in-the-sentence/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

Codewars/8kyu/exclamation-marks-series-number-11-replace-all-vowel-to-exclamation-mark-in-the-sentence/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

# Python - 3.6.0 Test.assert_equals(replace_exclamation('Hi!'), 'H!!') Test.assert_equals(replace_exclamation('!Hi! Hi!'), '!H!! H!!') Test.assert_equals(replace_exclamation('aeiou'), '!!!!!') Test.assert_equals(replace_exclamation('ABCDE'), '!BCD!')

36

63

0.694444

33

252

5.060606

0.424242

0.239521

0.383234

0.550898

0.850299

0.646707

0

0.012658

0.059524

252

6

64

42

0.691983

0.055556

0

0.177966

0

1

0

true

0

null

1

0

1

0

null

0

1

0

1

0

7

17b37ef8ea3f9693d36d41b4d2faf86dcc2bce54

16,853

py

Python

bottlechest/src/template/func/median.py

biolab/bottlechest

31a04204a56aebbea1024e0dfc926186d7ee77ac

[ "BSD-2-Clause" ]

2

2017-10-05T19:06:51.000Z

2020-04-27T12:23:14.000Z

bottlechest/src/template/func/median.py

biolab/bottlechest

31a04204a56aebbea1024e0dfc926186d7ee77ac

[ "BSD-2-Clause" ]

null

bottlechest/src/template/func/median.py

biolab/bottlechest

31a04204a56aebbea1024e0dfc926186d7ee77ac

[ "BSD-2-Clause" ]

null

"median template" from copy import deepcopy import bottlechest as bn __all__ = ["median", "nanmedian"] FLOAT_DTYPES = [x for x in bn.dtypes if 'float' in x] INT_DTYPES = [x for x in bn.dtypes if 'int' in x] # loops --------------------------------------------------------------------- loop = {} loop[1] = """\ if nINDEX0 == 0: return np.FLOAT(NAN) k = nAXIS >> 1 l = 0 r = nAXIS - 1 with nogil: while l < r: x = b[k] i = l j = r while 1: while b[i] < x: i += 1 while x < b[j]: j -= 1 if i <= j: tmp = b[i] b[i] = b[j] b[j] = tmp i += 1 j -= 1 if i > j: break if j < k: l = i if k < i: r = j if nAXIS % 2 == 0: amax = MINDTYPE for i in range(k): ai = b[i] if ai >= amax: amax = ai return np.FLOAT(0.5 * (b[k] + amax)) else: return np.FLOAT(b[k]) """ loop[2] = """\ if nINDEX1 == 0: PyArray_FillWithScalar(y, NAN) return y for iINDEX0 in range(nINDEX0): k = nAXIS >> 1 l = 0 r = nAXIS - 1 while l < r: x = b[INDEXREPLACE|k|] i = l j = r while 1: while b[INDEXREPLACE|i|] < x: i += 1 while x < b[INDEXREPLACE|j|]: j -= 1 if i <= j: tmp = b[INDEXREPLACE|i|] b[INDEXREPLACE|i|] = b[INDEXREPLACE|j|] b[INDEXREPLACE|j|] = tmp i += 1 j -= 1 if i > j: break if j < k: l = i if k < i: r = j if nAXIS % 2 == 0: amax = MINDTYPE for i in range(k): ai = b[INDEXREPLACE|i|] if ai >= amax: amax = ai y[INDEXPOP] = 0.5 * (b[INDEXREPLACE|k|] + amax) else: y[INDEXPOP] = CASTb[INDEXREPLACE|k|] return y """ # Float dtypes (not axis=None) ---------------------------------------------- floats = {} floats['dtypes'] = FLOAT_DTYPES floats['axisNone'] = False floats['force_output_dtype'] = False floats['reuse_non_nan_func'] = False floats['top'] = """ @cython.boundscheck(False) @cython.wraparound(False) def NAME_NDIMd_DTYPE_axisAXIS(np.ndarray[np.DTYPE_t, ndim=NDIM] a): "Median of NDIMd array with dtype=DTYPE along axis=AXIS." cdef np.npy_intp i, j = 0, l, r, k cdef np.DTYPE_t x, tmp, amax, ai cdef np.ndarray[np.DTYPE_t, ndim=NDIM] b = PyArray_Copy(a) """ floats['loop'] = {} floats['loop'][1] = loop[1].replace('FLOAT', 'DTYPE') floats['loop'][2] = loop[2].replace('CAST', '') # Int dtypes (not axis=None) ------------------------------------------------ ints = deepcopy(floats) ints['dtypes'] = INT_DTYPES ints['force_output_dtype'] = 'float64' ints['loop'] = {} ints['loop'][1] = loop[1].replace('FLOAT', 'float64') ints['loop'][2] = loop[2].replace('CAST', '<np.float64_t> ') # Slow, unaccelerated ndim/dtype -------------------------------------------- slow = {} slow['name'] = "median" slow['signature'] = "arr" slow['func'] = "bn.slow.median(arr, axis=AXIS)" # Template ------------------------------------------------------------------ median = {} median['name'] = 'median' median['is_reducing_function'] = True median['cdef_output'] = True median['slow'] = slow median['templates'] = {} median['templates']['float'] = floats median['templates']['int'] = ints median['pyx_file'] = 'func/%sbit/median.pyx' median['main'] = '''"median auto-generated from template" # Select smallest k elements code used for inner loop of median method: # http://projects.scipy.org/numpy/attachment/ticket/1213/quickselect.pyx # (C) 2009 Sturla Molden # SciPy license # # From the original C function (code in public domain) in: # Fast median search: an ANSI C implementation # Nicolas Devillard - ndevilla AT free DOT fr # July 1998 # which, in turn, took the algorithm from # Wirth, Niklaus # Algorithms + data structures = programs, p. 366 # Englewood Cliffs: Prentice-Hall, 1976 # # Adapted and expanded for Bottleneck: # (C) 2010 Keith Goodman def median(arr, axis=None): """ Median of array elements along given axis. Parameters ---------- arr : array_like Input array. If `arr` is not an array, a conversion is attempted. axis : {int, None}, optional Axis along which the median is computed. The default (axis=None) is to compute the median of the flattened array. Returns ------- y : ndarray An array with the same shape as `arr`, except that the specified axis has been removed. If `arr` is a 0d array, or if axis is None, a scalar is returned. `float64` return values are used for integer inputs. See also -------- bottlechest.nanmedian: Median along specified axis ignoring NaNs. Notes ----- This function returns the same output as NumPy's median except when the input contains NaN. Examples -------- >>> a = np.array([[10, 7, 4], [3, 2, 1]]) >>> a array([[10, 7, 4], [ 3, 2, 1]]) >>> bn.median(a) 3.5 >>> bn.median(a, axis=0) array([ 6.5, 4.5, 2.5]) >>> bn.median(a, axis=1) array([ 7., 2.]) """ func, arr = median_selector(arr, axis) return func(arr) def median_selector(arr, axis): """ Return median function and array that matches `arr` and `axis`. Under the hood Bottleneck uses a separate Cython function for each combination of ndim, dtype, and axis. A lot of the overhead in bn.median() is in checking that `axis` is within range, converting `arr` into an array (if it is not already an array), and selecting the function to use to calculate the mean. You can get rid of the overhead by doing all this before you, for example, enter an inner loop, by using the this function. Parameters ---------- arr : array_like Input array. If `arr` is not an array, a conversion is attempted. axis : {int, None} Axis along which the median is to be computed. Returns ------- func : function The median function that matches the number of dimensions and dtype of the input array and the axis along which you wish to find the median. a : ndarray If the input array `arr` is not a ndarray, then `a` will contain the result of converting `arr` into a ndarray. Examples -------- Create a numpy array: >>> arr = np.array([1.0, 2.0, 3.0]) Obtain the function needed to determine the median of `arr` along axis=0: >>> func, a = bn.func.median_selector(arr, axis=0) >>> func <function median_1d_float64_axis0> Use the returned function and array to determine the median: >>> func(a) 2.0 """ cdef np.ndarray a if type(arr) is np.ndarray: a = arr else: a = np.array(arr, copy=False) cdef tuple key cdef int ndim = PyArray_NDIM(a) cdef int dtype = PyArray_TYPE(a) if axis is not None: if axis < 0: axis += ndim else: a = PyArray_Ravel(a, NPY_CORDER) axis = 0 ndim = 1 key = (ndim, dtype, axis) try: func = median_dict[key] except KeyError: if (axis < 0) or (axis >= ndim): raise ValueError("axis(=%d) out of bounds" % axis) try: func = median_slow_dict[axis] except KeyError: tup = (str(ndim), str(a.dtype), str(axis)) raise TypeError("Unsupported ndim/dtype/axis (%s/%s/%s)." % tup) return func, a ''' "nanmedian template" from copy import deepcopy import bottlechest as bn FLOAT_DTYPES = [x for x in bn.dtypes if 'float' in x] INT_DTYPES = [x for x in bn.dtypes if 'int' in x] # loops --------------------------------------------------------------------- loop = {} loop[1] = """\ if nINDEX0 == 0: return np.FLOAT(NAN) j = nAXIS - 1 flag = 1 for i in range(nINDEX0): if b[i] != b[i]: while b[j] != b[j]: if j <= 0: break j -= 1 if i >= j: flag = 0 break tmp = b[i] b[i] = b[j] b[j] = tmp n = i + flag k = n >> 1 l = 0 r = n - 1 with nogil: while l < r: x = b[k] i = l j = r while 1: while b[i] < x: i += 1 while x < b[j]: j -= 1 if i <= j: tmp = b[i] b[i] = b[j] b[j] = tmp i += 1 j -= 1 if i > j: break if j < k: l = i if k < i: r = j if n % 2 == 0: amax = MINDTYPE allnan = 1 for i in range(k): ai = b[i] if ai >= amax: amax = ai allnan = 0 if allnan == 0: return np.FLOAT(0.5 * (b[k] + amax)) else: return np.FLOAT(b[k]) else: return np.FLOAT(b[k]) """ loop[2] = """\ if nINDEX1 == 0: PyArray_FillWithScalar(y, NAN) return y for iINDEX0 in range(nINDEX0): j = nAXIS - 1 flag = 1 for i in range(nINDEX1): if b[INDEXREPLACE|i|] != b[INDEXREPLACE|i|]: while b[INDEXREPLACE|j|] != b[INDEXREPLACE|j|]: if j <= 0: break j -= 1 if i >= j: flag = 0 break tmp = b[INDEXREPLACE|i|] b[INDEXREPLACE|i|] = b[INDEXREPLACE|j|] b[INDEXREPLACE|j|] = tmp n = i + flag k = n >> 1 l = 0 r = n - 1 while l < r: x = b[INDEXREPLACE|k|] i = l j = r while 1: while b[INDEXREPLACE|i|] < x: i += 1 while x < b[INDEXREPLACE|j|]: j -= 1 if i <= j: tmp = b[INDEXREPLACE|i|] b[INDEXREPLACE|i|] = b[INDEXREPLACE|j|] b[INDEXREPLACE|j|] = tmp i += 1 j -= 1 if i > j: break if j < k: l = i if k < i: r = j if n % 2 == 0: amax = MINDTYPE allnan = 1 for i in range(k): ai = b[INDEXREPLACE|i|] if ai >= amax: amax = ai allnan = 0 if allnan == 0: y[INDEXPOP] = 0.5 * (b[INDEXREPLACE|k|] + amax) else: y[INDEXPOP] = CASTb[INDEXREPLACE|k|] else: y[INDEXPOP] = CASTb[INDEXREPLACE|k|] return y """ # Float dtypes (not axis=None) ---------------------------------------------- floats = {} floats['dtypes'] = FLOAT_DTYPES floats['axisNone'] = False floats['force_output_dtype'] = False floats['reuse_non_nan_func'] = False floats['top'] = """ @cython.boundscheck(False) @cython.wraparound(False) def NAME_NDIMd_DTYPE_axisAXIS(np.ndarray[np.DTYPE_t, ndim=NDIM] a): "Median of NDIMd array with dtype=DTYPE along axis=AXIS." cdef int allnan = 1, flag = 0 cdef np.npy_intp i = 0, j = 0, l, r, k, n cdef np.DTYPE_t x, tmp, amax, ai cdef np.ndarray[np.DTYPE_t, ndim=NDIM] b = PyArray_Copy(a) """ floats['loop'] = {} floats['loop'][1] = loop[1].replace('FLOAT', 'DTYPE') floats['loop'][2] = loop[2].replace('CAST', '') # Int dtypes (not axis=None) ------------------------------------------------ ints = deepcopy(floats) ints['dtypes'] = INT_DTYPES ints['reuse_non_nan_func'] = True # Slow, unaccelerated ndim/dtype -------------------------------------------- slow = {} slow['name'] = "nanmedian" slow['signature'] = "arr" slow['func'] = "bn.slow.nanmedian(arr, axis=AXIS)" # Template ------------------------------------------------------------------ nanmedian = {} nanmedian['name'] = 'nanmedian' nanmedian['is_reducing_function'] = True nanmedian['cdef_output'] = True nanmedian['slow'] = slow nanmedian['templates'] = {} nanmedian['templates']['float'] = floats nanmedian['templates']['int'] = ints nanmedian['pyx_file'] = 'func/%sbit/median.pyx' nanmedian['main'] = '''"nanmedian auto-generated from template" # Select smallest k elements code used for inner loop of median method: # http://projects.scipy.org/numpy/attachment/ticket/1213/quickselect.pyx # (C) 2009 Sturla Molden # SciPy license # # From the original C function (code in public domain) in: # Fast median search: an ANSI C implementation # Nicolas Devillard - ndevilla AT free DOT fr # July 1998 # which, in turn, took the algorithm from # Wirth, Niklaus # Algorithms + data structures = programs, p. 366 # Englewood Cliffs: Prentice-Hall, 1976 # # Adapted and expanded for Bottleneck: # (C) 2010 Keith Goodman def nanmedian(arr, axis=None): """ Median of array elements along given axis ignoring NaNs. Parameters ---------- arr : array_like Input array. If `arr` is not an array, a conversion is attempted. axis : {int, None}, optional Axis along which the median is computed. The default (axis=None) is to compute the median of the flattened array. Returns ------- y : ndarray An array with the same shape as `arr`, except that the specified axis has been removed. If `arr` is a 0d array, or if axis is None, a scalar is returned. `float64` return values are used for integer inputs. See also -------- bottlechest.median: Median along specified axis. Examples -------- >>> a = np.array([[np.nan, 7, 4], [3, 2, 1]]) >>> a array([[ nan, 7., 4.], [ 3., 2., 1.]]) >>> bn.nanmedian(a) 3.0 >> bn.nanmedian(a, axis=0) array([ 3. , 4.5, 2.5]) >> bn.nanmedian(a, axis=1) array([ 5.5, 2. ]) """ func, arr = nanmedian_selector(arr, axis) return func(arr) def nanmedian_selector(arr, axis): """ Return nanmedian function and array that matches `arr` and `axis`. Under the hood Bottleneck uses a separate Cython function for each combination of ndim, dtype, and axis. A lot of the overhead in bn.nanmedian() is in checking that `axis` is within range, converting `arr` into an array (if it is not already an array), and selecting the function to use to calculate the mean. You can get rid of the overhead by doing all this before you, for example, enter an inner loop, by using the this function. Parameters ---------- arr : array_like Input array. If `arr` is not an array, a conversion is attempted. axis : {int, None} Axis along which the median is to be computed. Returns ------- func : function The nanmedian function that matches the number of dimensions and dtype of the input array and the axis along which you wish to find the median. a : ndarray If the input array `arr` is not a ndarray, then `a` will contain the result of converting `arr` into a ndarray. Examples -------- Create a numpy array: >>> arr = np.array([1.0, 2.0, 3.0]) Obtain the function needed to determine the median of `arr` along axis=0: >>> func, a = bn.func.nanmedian_selector(arr, axis=0) >>> func <function nanmedian_1d_float64_axis0> Use the returned function and array to determine the median: >>> func(a) 2.0 """ cdef np.ndarray a if type(arr) is np.ndarray: a = arr else: a = np.array(arr, copy=False) cdef tuple key cdef int ndim = PyArray_NDIM(a) cdef int dtype = PyArray_TYPE(a) if axis is not None: if axis < 0: axis += ndim else: a = PyArray_Ravel(a, NPY_CORDER) axis = 0 ndim = 1 key = (ndim, dtype, axis) try: func = nanmedian_dict[key] except KeyError: if (axis < 0) or (axis >= ndim): raise ValueError("axis(=%d) out of bounds" % axis) try: func = nanmedian_slow_dict[axis] except KeyError: tup = (str(ndim), str(a.dtype), str(axis)) raise TypeError("Unsupported ndim/dtype/axis (%s/%s/%s)." % tup) return func, a '''

29.309565

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0

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false

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null

0

1

0

1

0

1

0

null

0

8

17fd526fa96a0aac0149c64f6d95b50358a904b4

5,667

py

Python

skactiveml/stream/budget_manager/tests/test_estimated_budget.py

scikit-activeml/scikit-activeml

2191ba452ca4d0fe349678d2a86b1906d79cb96a

[ "BSD-3-Clause" ]

40

2020-09-22T00:50:52.000Z

2022-03-15T14:16:42.000Z

skactiveml/stream/budget_manager/tests/test_estimated_budget.py

scikit-activeml/scikit-activeml

2191ba452ca4d0fe349678d2a86b1906d79cb96a

[ "BSD-3-Clause" ]

161

2020-08-10T09:24:03.000Z

2022-03-29T13:39:46.000Z

skactiveml/stream/budget_manager/tests/test_estimated_budget.py

scikit-activeml/scikit-activeml

2191ba452ca4d0fe349678d2a86b1906d79cb96a

[ "BSD-3-Clause" ]

3

2021-11-15T09:10:59.000Z

2021-12-15T11:40:47.000Z

import unittest import numpy as np from skactiveml.stream.budget_manager import ( FixedUncertaintyBudget, VarUncertaintyBudget, SplitBudget, ) class TemplateTestEstimatedBudget: def setUp(self): # initialise var for sampled var tests self.utilities = np.array([True, False]) def test_init_param_budget(self): # budget must be defined as a float with a range of: 0 < budget <= 1 budget_manager = self.get_budget_manager()(budget="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(budget=1.1) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(budget=-1.0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) def test_init_param_w(self): # w must be defined as an int with a range of w > 0 budget_manager = self.get_budget_manager()(w="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(w=None) self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(w=1.1) self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(w=0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(w=-1) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) def test_query_param_utilities(self): # s must be defined as a float ndarray budget_manager = self.get_budget_manager()() self.assertRaises( TypeError, budget_manager.query_by_utility, utilities="string" ) self.assertRaises( TypeError, budget_manager.query_by_utility, utilities=None ) self.assertRaises( TypeError, budget_manager.query_by_utility, utilities=[10, 10] ) def test_update_without_query(self): bm = self.get_budget_manager()() bm.update(np.array([[0], [1], [2]]), np.array([0, 2])) class TestFixedUncertaintyBudget( TemplateTestEstimatedBudget, unittest.TestCase ): def get_budget_manager(self): return FixedUncertaintyBudget def test_init_param_num_classes(self): # num_classes must be defined as an int and greater than 0 budget_manager = self.get_budget_manager()(num_classes="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(num_classes=-1) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(num_classes=0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) class TestVarUncertaintyBudget(TemplateTestEstimatedBudget, unittest.TestCase): def get_budget_manager(self): return VarUncertaintyBudget def test_init_param_theta(self): # theta must be defined as a float budget_manager = self.get_budget_manager()(theta="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) def test_init_param_s(self): # s must be defined as a float with a range of: 0 < s <= 1 budget_manager = self.get_budget_manager()(s="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(s=1.1) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(s=0.0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(s=-1.0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) class TestSplitBudget(TestVarUncertaintyBudget): def get_budget_manager(self): return SplitBudget def test_init_param_random_state(self): # v must be defined as an float with a range of: 0 < v < 1 budget_manager = self.get_budget_manager()(random_state="string") self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) def test_init_param_v(self): # v must be defined as an float with a range of: 0 < v < 1 budget_manager = self.get_budget_manager()(v="string") self.assertRaises( TypeError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(v=1.1) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(v=0.0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities ) budget_manager = self.get_budget_manager()(v=-1.0) self.assertRaises( ValueError, budget_manager.query_by_utility, self.utilities )

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0.66349

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5,667

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0.110272

0.265158

0.123498

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0.252691

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155

80

36.56129

0.835419

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0.02381

0.18254

0

null

1

0

1

0

null

0

7

aa0838f24d216107ca7930904f920c9ce6c304b1

6,267

py

Python

flowcelltool/flowcells/emails.py

bihealth/flowcelltool

6e16190fc34c54d834ecd23888a462f3af47611d

[ "MIT" ]

7

2016-10-12T12:56:09.000Z

2020-10-27T17:08:09.000Z

flowcelltool/flowcells/emails.py

iamh2o/flowcelltool

6e16190fc34c54d834ecd23888a462f3af47611d

[ "MIT" ]

94

2016-10-24T06:28:31.000Z

2018-08-06T10:35:13.000Z

flowcelltool/flowcells/emails.py

iamh2o/flowcelltool

6e16190fc34c54d834ecd23888a462f3af47611d

[ "MIT" ]

1

2022-03-23T15:57:16.000Z

# -*- coding: utf-8 -*- """Module for sending out emails """ from django.core.mail import send_mass_mail from django.db.models import Q from django.conf import settings from flowcelltool.users.models import User from . import rules # Templates ------------------------------------------------------------------- TEMPLATE_FLOWCELL_CREATED = r""" Dear {recipient}, The user {user} just created a new flow cell with the following id: {full_name} You can see the created flow cell at the following URL: {flowcell_url} You are receiving this email because you have the Demultiplexing Administrator or the Demultiplexing Operator role. """.lstrip() TEMPLATE_FLOWCELL_UPDATED = r""" Dear {recipient}, The user {user} just updated the flow cell with the following id: {full_name} You can see the created flow cell at the following URL: {flowcell_url} You are receiving this email because you have the Demultiplexing Administrator or the Demultiplexing Operator role, or you have been assigned as the demultiplexing operator for this flow cell. """.lstrip() TEMPLATE_FLOWCELL_DELETED = r""" Dear {recipient}, The user {user} just deleted the flow cell with the following id: {full_name} You are receiving this email because you have the Demultiplexing Administrator or the Demultiplexing Operator role, or you have were assigned as the demultiplexing operator for this flow cell. """.lstrip() # Helper Functions ------------------------------------------------------------ def _or_queries(queries): """Helper function that concatenates lazy Django queries""" result = queries.pop() for item in queries: result |= item return result # Signal Handlers ------------------------------------------------------------- def email_flowcell_created(user, flowcell, request=None): """Send email on flow cell creation""" if not settings.FLOWCELLS_SEND_EMAILS: return # Gather groups to send emails to to_groups = (rules.DEMUX_ADMIN, rules.DEMUX_OPERATOR) # Build queries and perform the actual sending of emails queries = [Q(groups__name=group_name) for group_name in to_groups] queries.append(Q(is_superuser=True)) queries.append(Q(pk=user.pk)) if flowcell.demux_operator: queries.append(Q(pk=flowcell.demux_operator.pk)) if flowcell.owner: queries.append(Q(pk=flowcell.owner.pk)) users = User.objects.filter(_or_queries(queries)) users = users.exclude(email__isnull=True).exclude(email__exact='') # Prepare values to push into email absolute_url = flowcell.get_absolute_url() if request: absolute_url = request.build_absolute_uri(absolute_url) vals = { 'EMAIL_SUBJECT_PREFIX': settings.EMAIL_SUBJECT_PREFIX, 'full_name': flowcell.get_full_name(), 'flowcell_url': absolute_url, 'user': user, } # Create email data tuple generator template_subject = ( '{EMAIL_SUBJECT_PREFIX}{user} created new flow cell {full_name}') emails = ( ( template_subject.format(**vals), TEMPLATE_FLOWCELL_CREATED.format(recipient=u, **vals), settings.EMAIL_SENDER, [u.email] ) for u in users) # Actually send the emails send_mass_mail(emails, fail_silently=not settings.DEBUG) def email_flowcell_updated(user, flowcell, request=None): """Send email on flow cell update""" if not settings.FLOWCELLS_SEND_EMAILS: return # Gather groups to send emails to to_groups = (rules.DEMUX_ADMIN, rules.DEMUX_OPERATOR) # Build queries and perform the actual sending of emails queries = [Q(groups__name=group_name) for group_name in to_groups] queries.append(Q(is_superuser=True)) queries.append(Q(pk=user.pk)) if flowcell.owner: queries.append(Q(pk=flowcell.owner.pk)) if flowcell.demux_operator: queries.append(Q(pk=flowcell.demux_operator.pk)) users = User.objects.filter(_or_queries(queries)) users = users.exclude(email__isnull=True).exclude(email__exact='') # Prepare values to push into email absolute_url = flowcell.get_absolute_url() if request: absolute_url = request.build_absolute_uri(absolute_url) vals = { 'EMAIL_SUBJECT_PREFIX': settings.EMAIL_SUBJECT_PREFIX, 'full_name': flowcell.get_full_name(), 'flowcell_url': absolute_url, 'user': user, } # Create email data tuple generator template_subject = ( '{EMAIL_SUBJECT_PREFIX}{user} updated flow cell {full_name}') emails = ( ( template_subject.format(**vals), TEMPLATE_FLOWCELL_UPDATED.format(recipient=u, **vals), settings.EMAIL_SENDER, [u.email] ) for u in users) # Actually send the emails send_mass_mail(emails, fail_silently=not settings.DEBUG) def email_flowcell_deleted(user, flowcell, request=None): """Send email on flow cell deletion""" if not settings.FLOWCELLS_SEND_EMAILS: return # Gather groups to send emails to to_groups = (rules.DEMUX_ADMIN, rules.DEMUX_OPERATOR) # Build queries and perform the actual sending of emails queries = [Q(groups__name=group_name) for group_name in to_groups] queries.append(Q(is_superuser=True)) queries.append(Q(pk=user.pk)) if flowcell.owner: queries.append(Q(pk=flowcell.owner.pk)) if flowcell.demux_operator: queries.append(Q(pk=flowcell.demux_operator.pk)) users = User.objects.filter(_or_queries(queries)) users = users.exclude(email__isnull=True).exclude(email__exact='') # Prepare values to push into email vals = { 'EMAIL_SUBJECT_PREFIX': settings.EMAIL_SUBJECT_PREFIX, 'full_name': flowcell.get_full_name(), 'user': user, } # Create email data tuple generator template_subject = ( '{EMAIL_SUBJECT_PREFIX}{user} deleted flow cell {full_name}') emails = ( ( template_subject.format(**vals), TEMPLATE_FLOWCELL_DELETED.format(recipient=u, **vals), settings.EMAIL_SENDER, [u.email] ) for u in users) # Actually send the emails send_mass_mail(emails, fail_silently=not settings.DEBUG)

33.335106

79

0.675124

802

6,267

5.088529

0.164589

0.025484

0.041166

0.035285

0.866209

0.844891

0.814016

0

0.000201

0.206159

6,267

187

80

33.513369

0.820101

0.155896

0

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0

0.242326

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0

1

0.031008

false

0

0.03876

0

0.100775

0

null

0

1

0

1

0

null

0

7

aa3ca64a8ad24a42a4da70d951f5bd9e0b34ea2f

5,710

py

Python

Python/importData.py

klocey/MicroMETE

5bac4e039be75f4528ccfd8b7ba85500a5495b96

[ "Unlicense", "MIT" ]

null

Python/importData.py

klocey/MicroMETE

5bac4e039be75f4528ccfd8b7ba85500a5495b96

[ "Unlicense", "MIT" ]

null

Python/importData.py

klocey/MicroMETE

5bac4e039be75f4528ccfd8b7ba85500a5495b96

[ "Unlicense", "MIT" ]

null

import numpy as np def import_obs_pred_data(input_filename): # TAKEN FROM THE mete_sads.py script used for White et al. (2012) if '75' in input_filename: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8", names = ['site','obs', 'predPln', 'pred7525'], delimiter = " ") else: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8", names = ['site','obs','pred'], delimiter = " ") #test = data[0:10000] #return test return data def import_subsampled_data(input_filename): if ('zipf' in input_filename): # 33 for zipf # this needs to be fixesd, I put the file name twice in old code data = np.genfromtxt(input_filename, \ dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','site2','N0','S0','Nmax', \ 'N0_05','S0_05','Nmax_05', 'r2_05', 'gamma_05', \ 'N0_025','S0_025','Nmax_025', 'r2_025', 'gamma_025', \ 'N0_0125','S0_0125','Nmax_0125', 'r2_0125', 'gamma_0125', \ 'N0_00625','S0_00625','Nmax_00625', 'r2_00625', 'gamma_00625', \ 'N0_003125','S0_003125','Nmax_003125', 'r2_003125', 'gamma_003125', 'N0_0015625','S0_0015625','Nmax_0015625','r2_0015625', 'gamma_0015625'], \ delimiter = " ") else: # 27 columns for mete and geom data = np.genfromtxt(input_filename, \ dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N0','S0','Nmax', \ 'N0_05','S0_05','Nmax_05','r2_05', \ 'N0_025','S0_025','Nmax_025','r2_025', \ 'N0_0125','S0_0125','Nmax_0125','r2_0125', \ 'N0_00625','S0_00625','Nmax_00625','r2_00625', \ 'N0_003125','S0_003125','Nmax_003125','r2_003125', \ 'N0_0015625','S0_0015625','Nmax_0015625','r2_0015625'], \ delimiter = " ") return data def import_subsampled_data_pandas(input_filename): if ('zipf' in input_filename): names = ['site','site2','N0','S0','Nmax', \ 'N0_05','S0_05','Nmax_05', 'r2_05', 'gamma_05', \ 'N0_025','S0_025','Nmax_025', 'r2_025', 'gamma_025', \ 'N0_0125','S0_0125','Nmax_0125', 'r2_0125', 'gamma_0125', \ 'N0_00625','S0_00625','Nmax_00625', 'r2_00625', 'gamma_00625', \ 'N0_003125','S0_003125','Nmax_003125', 'r2_003125', 'gamma_003125', 'N0_0015625','S0_0015625','Nmax_0015625','r2_0015625', 'gamma_0015625'] #data_table = pd.read_table(input_filename, names = names, header = None, sep=' ') else: names = ['site','N0','S0','Nmax', \ 'N0_05','S0_05','Nmax_05','r2_05', \ 'N0_025','S0_025','Nmax_025','r2_025', \ 'N0_0125','S0_0125','Nmax_0125','r2_0125', \ 'N0_00625','S0_00625','Nmax_00625','r2_00625', \ 'N0_003125','S0_003125','Nmax_003125','r2_003125', \ 'N0_0015625','S0_0015625','Nmax_0015625','r2_0015625'] data_table = pd.read_table(input_filename, names = names, header = None, sep=' ') return data_table def import_NSR2_data(input_filename): # TAKEN FROM THE mete_sads.py script used for White et al. (2012) input_filename_str = str(input_filename) #NSR2_method = input_filename_split[-4] #method = str(NSR2_method.split('/')[1]) if 'Stratified' in input_filename_str: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred','R2'], delimiter = " ") else: if 'HMP' in input_filename_str: if ('zipf' in input_filename_str) : if ('glm' in input_filename_str) : data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred','R2', 'NAP'], delimiter = " ") else: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred','R2', 'NAP'], delimiter = " ") else: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred', 'R2','NAP'], delimiter = " ") else: if 'zipf' in input_filename_str: if ('glm' in input_filename_str) : data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred', 'R2'], delimiter = " ") else: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S', 'NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred','gamma', 'R2'], delimiter = " ") # 'gammma' else: data = np.genfromtxt(input_filename, dtype = "f8,f8,f8,f8,f8,f8,f8,f8,f8,f8", \ names = ['site','N','S','NmaxObs', 'NmaxPred', 'evennessObs', \ 'evennessPred', 'skewnessObs', 'skewnessPred', 'R2'], delimiter = " ") return data

53.867925

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0.561996

744

5,710

4.092742

0.129032

0.172085

0.236453

0.286371

0.87619

0.870279

0.840723

0.818391

0

0.173569

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5,710

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54.380952

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0

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0

0.069767

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0

1

0.046512

false

0

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null

0

1

0

1

0

null

0

9

a4b427b5c53333a7f41b2cc5b3fefdd3ebb9aa6a

15,288

py

Python

test/functional/tests/lazy_writes/test_lazy_writes_clean.py

sirizhou/open-cas-linux

e623c44b3b637238a8c6041f8659d8eb3766b91c

[ "BSD-3-Clause-Clear" ]

null

test/functional/tests/lazy_writes/test_lazy_writes_clean.py

sirizhou/open-cas-linux

e623c44b3b637238a8c6041f8659d8eb3766b91c

[ "BSD-3-Clause-Clear" ]

null

test/functional/tests/lazy_writes/test_lazy_writes_clean.py

sirizhou/open-cas-linux

e623c44b3b637238a8c6041f8659d8eb3766b91c

[ "BSD-3-Clause-Clear" ]

null

# # Copyright(c) 2020 Intel Corporation # SPDX-License-Identifier: BSD-3-Clause-Clear # import pytest from api.cas import casadm from api.cas.cache_config import CacheMode, CleaningPolicy, CacheModeTrait, SeqCutOffPolicy from storage_devices.device import Device from storage_devices.disk import DiskType, DiskTypeSet, DiskTypeLowerThan from core.test_run import TestRun from test_tools.dd import Dd from test_tools.disk_utils import Filesystem from test_tools.fs_utils import create_random_test_file, remove from test_tools.iostat import IOstatBasic from test_utils.filesystem.file import File from test_utils.os_utils import Udev, sync from test_utils.size import Size, Unit bs = Size(512, Unit.KibiByte) mnt_point = "/mnt/cas/" @pytest.mark.parametrizex("cache_mode", CacheMode.with_traits(CacheModeTrait.LazyWrites)) @pytest.mark.require_disk("cache", DiskTypeSet([DiskType.optane, DiskType.nand])) @pytest.mark.require_disk("core", DiskTypeLowerThan("cache")) def test_clean_stop_cache(cache_mode): """ title: Test of the ability to stop cache in modes with lazy writes. description: | Test if OpenCAS stops cache in modes with lazy writes without data loss. pass_criteria: - Cache stopping works properly. - Writes to exported object and core device during OpenCAS's work are equal - Data on core device is correct after cache is stopped. """ with TestRun.step("Prepare devices for cache and core."): cache_dev = TestRun.disks['cache'] cache_dev.create_partitions([Size(256, Unit.MebiByte)]) cache_part = cache_dev.partitions[0] core_dev = TestRun.disks['core'] core_dev.create_partitions([Size(512, Unit.MebiByte)]) core_part = core_dev.partitions[0] Udev.disable() with TestRun.step(f"Start cache in {cache_mode} mode."): cache = casadm.start_cache(cache_part, cache_mode) with TestRun.step("Add core to cache."): core = cache.add_core(core_part) with TestRun.step("Disable cleaning and sequential cutoff."): cache.set_cleaning_policy(CleaningPolicy.nop) cache.set_seq_cutoff_policy(SeqCutOffPolicy.never) with TestRun.step("Read IO stats before test"): core_disk_writes_initial = check_device_write_stats(core_part) exp_obj_writes_initial = check_device_write_stats(core) with TestRun.step("Write data to the exported object."): test_file_main = create_random_test_file("/tmp/test_file_main", Size(64, Unit.MebiByte)) dd = Dd().output(core.path) \ .input(test_file_main.full_path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_md5sum_main = test_file_main.md5sum() with TestRun.step("Read IO stats after write to the exported object."): core_disk_writes_increase = ( check_device_write_stats(core_part) - core_disk_writes_initial ) exp_obj_writes_increase = ( check_device_write_stats(core) - exp_obj_writes_initial ) with TestRun.step("Validate IO stats after write to the exported object."): if core_disk_writes_increase > 0: TestRun.LOGGER.error("Writes should occur only on the exported object.") if exp_obj_writes_increase != test_file_main.size.value: TestRun.LOGGER.error("Not all writes reached the exported object.") with TestRun.step("Read data from the exported object."): test_file_1 = File.create_file("/tmp/test_file_1") dd = Dd().output(test_file_1.full_path) \ .input(core.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_1.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_1.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Read data from the core device."): test_file_2 = File.create_file("/tmp/test_file_2") dd = Dd().output(test_file_2.full_path) \ .input(core_part.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_2.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main == test_file_2.md5sum(): TestRun.LOGGER.error("Md5 sums should be different.") with TestRun.step("Read IO stats before stopping cache."): core_disk_writes_before_stop = check_device_write_stats(core_part) with TestRun.step("Stop cache."): cache.stop() with TestRun.step("Read IO stats after stopping cache."): core_disk_writes_increase = ( check_device_write_stats(core_part) - core_disk_writes_before_stop ) with TestRun.step("Validate IO stats after stopping cache."): if core_disk_writes_increase == 0: TestRun.LOGGER.error("Writes should occur on the core device after stopping cache.") if core_disk_writes_increase != exp_obj_writes_increase: TestRun.LOGGER.error("Write statistics for the core device should be equal " "to those from the exported object.") with TestRun.step("Read data from the core device."): test_file_3 = File.create_file("/tmp/test_file_2") dd = Dd().output(test_file_3.full_path) \ .input(core_part.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_3.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_3.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Delete test files."): test_file_main.remove(True) test_file_1.remove(True) test_file_2.remove(True) test_file_3.remove(True) @pytest.mark.parametrizex("fs", Filesystem) @pytest.mark.parametrizex("cache_mode", CacheMode.with_traits(CacheModeTrait.LazyWrites)) @pytest.mark.require_disk("cache", DiskTypeSet([DiskType.optane, DiskType.nand])) @pytest.mark.require_disk("core", DiskTypeLowerThan("cache")) def test_clean_remove_core_with_fs(cache_mode, fs): """ title: Test of the ability to remove core from cache in lazy-write modes with filesystem. description: | Test if OpenCAS removes core from cache in modes with lazy writes and with different filesystems without data loss. pass_criteria: - Core removing works properly. - Data on core device is correct after core is removed. """ with TestRun.step("Prepare devices for cache and core."): cache_dev = TestRun.disks['cache'] cache_dev.create_partitions([Size(256, Unit.MebiByte)]) cache_part = cache_dev.partitions[0] core_dev = TestRun.disks['core'] core_dev.create_partitions([Size(512, Unit.MebiByte)]) core_part = core_dev.partitions[0] Udev.disable() with TestRun.step(f"Start cache in {cache_mode} mode."): cache = casadm.start_cache(cache_part, cache_mode) with TestRun.step(f"Add core with {fs.name} filesystem to cache and mount it."): core_part.create_filesystem(fs) core = cache.add_core(core_part) core.mount(mnt_point) with TestRun.step("Disable cleaning and sequential cutoff."): cache.set_cleaning_policy(CleaningPolicy.nop) cache.set_seq_cutoff_policy(SeqCutOffPolicy.never) with TestRun.step("Create test file and read its md5 sum."): test_file_main = create_random_test_file("/tmp/test_file_main", Size(64, Unit.MebiByte)) test_file_md5sum_main = test_file_main.md5sum() with TestRun.step("Copy test file to the exported object."): test_file_1 = File.create_file(mnt_point + "test_file_1") dd = Dd().output(test_file_1.full_path) \ .input(test_file_main.full_path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_1.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_1.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Unmount and remove core."): core.unmount() core.remove_core() with TestRun.step("Mount core device."): core_part.mount(mnt_point) with TestRun.step("Read data from the core device."): test_file_2 = File.create_file("/tmp/test_file_2") dd = Dd().output(test_file_2.full_path) \ .input(test_file_1.full_path) \ .block_size(bs) \ .count(int(test_file_1.size / bs)) \ .oflag("direct") dd.run() test_file_2.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_2.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Delete test files."): test_file_main.remove(True) test_file_1.remove(True) test_file_2.remove(True) with TestRun.step("Unmount core device."): core_part.unmount() remove(mnt_point, True, True, True) @pytest.mark.parametrizex("cache_mode", CacheMode.with_traits(CacheModeTrait.LazyWrites)) @pytest.mark.require_disk("cache", DiskTypeSet([DiskType.optane, DiskType.nand])) @pytest.mark.require_disk("core", DiskTypeLowerThan("cache")) def test_clean_remove_core_without_fs(cache_mode): """ title: Test of the ability to remove core from cache in lazy-write modes without filesystem. description: | Test if OpenCAS removes core without filesystem in modes with lazy writes without data loss. pass_criteria: - Core removing works properly. - Writes to exported object and core device during OpenCAS's work are equal - Data on core device is correct after core is removed. """ with TestRun.step("Prepare devices for cache and core."): cache_dev = TestRun.disks['cache'] cache_dev.create_partitions([Size(256, Unit.MebiByte)]) cache_part = cache_dev.partitions[0] core_dev = TestRun.disks['core'] core_dev.create_partitions([Size(512, Unit.MebiByte)]) core_part = core_dev.partitions[0] Udev.disable() with TestRun.step(f"Start cache in {cache_mode} mode."): cache = casadm.start_cache(cache_part, cache_mode) with TestRun.step("Add core to cache."): core = cache.add_core(core_part) with TestRun.step("Disable cleaning and sequential cutoff."): cache.set_cleaning_policy(CleaningPolicy.nop) cache.set_seq_cutoff_policy(SeqCutOffPolicy.never) with TestRun.step("Read IO stats before test"): core_disk_writes_initial = check_device_write_stats(core_part) exp_obj_writes_initial = check_device_write_stats(core) with TestRun.step("Write data to exported object."): test_file_main = create_random_test_file("/tmp/test_file_main", Size(64, Unit.MebiByte)) dd = Dd().output(core.path) \ .input(test_file_main.full_path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_md5sum_main = test_file_main.md5sum() with TestRun.step("Read IO stats after write to the exported object."): core_disk_writes_increase = ( check_device_write_stats(core_part) - core_disk_writes_initial ) exp_obj_writes_increase = ( check_device_write_stats(core) - exp_obj_writes_initial ) with TestRun.step("Validate IO stats after write to the exported object."): if core_disk_writes_increase > 0: TestRun.LOGGER.error("Writes should occur only on the exported object.") if exp_obj_writes_increase != test_file_main.size.value: TestRun.LOGGER.error("Not all writes reached the exported object.") with TestRun.step("Read data from the exported object."): test_file_1 = File.create_file("/tmp/test_file_1") dd = Dd().output(test_file_1.full_path) \ .input(core.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_1.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_1.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Read data from the core device."): test_file_2 = File.create_file("/tmp/test_file_2") dd = Dd().output(test_file_2.full_path) \ .input(core_part.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_2.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main == test_file_2.md5sum(): TestRun.LOGGER.error("Md5 sums should be different.") with TestRun.step("Read IO stats before removing core."): core_disk_writes_before_remove = check_device_write_stats(core_part) with TestRun.step("Remove core."): core.remove_core() with TestRun.step("Read IO stats after removing core."): core_disk_writes_increase = ( check_device_write_stats(core_part) - core_disk_writes_before_remove ) with TestRun.step("Validate IO stats after removing core."): if core_disk_writes_increase == 0: TestRun.LOGGER.error("Writes should occur on the core device after removing core.") if core_disk_writes_increase != exp_obj_writes_increase: TestRun.LOGGER.error("Write statistics for the core device should be equal " "to those from the exported object.") with TestRun.step("Read data from core device again."): test_file_3 = File.create_file("/tmp/test_file_3") dd = Dd().output(test_file_3.full_path) \ .input(core_part.path) \ .block_size(bs) \ .count(int(test_file_main.size / bs)) \ .oflag("direct") dd.run() test_file_3.refresh_item() sync() with TestRun.step("Compare md5 sum of test files."): if test_file_md5sum_main != test_file_3.md5sum(): TestRun.LOGGER.error("Md5 sums should be equal.") with TestRun.step("Delete test files."): test_file_main.remove(True) test_file_1.remove(True) test_file_2.remove(True) test_file_3.remove(True) remove(mnt_point, True, True, True) def check_device_write_stats(device: Device): return IOstatBasic.get_iostat_list(devices_list=[device])[0].total_writes.value

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35141e07bedec1abf1406391c6bb709f3a8cf026

549

py

Python

parsers/twitter_creds.py

Bassem95/Test26

7703ae439945ec83005881d31ff3712844c77c97

[ "MIT" ]

105

2019-07-07T13:15:32.000Z

2022-03-25T09:32:43.000Z

parsers/twitter_creds.py

Bassem95/Test26

7703ae439945ec83005881d31ff3712844c77c97

[ "MIT" ]

2

2020-03-11T15:40:14.000Z

2021-03-05T23:23:38.000Z

parsers/twitter_creds.py

Bassem95/Test26

7703ae439945ec83005881d31ff3712844c77c97

[ "MIT" ]

9

2020-02-14T06:39:59.000Z

2022-01-15T01:47:50.000Z

# -*- coding: utf-8 -*- #!/usr/bin/python """ """ import twitter def TwitterApi(): return twitter.Api(consumer_key='[consumer key]', consumer_secret='[consumer secret]', access_token_key='[access token]', access_token_secret='[access token secret]') def TwitterApiContext(): return twitter.Api(consumer_key='[consumer key]', consumer_secret='[consumer secret]', access_token_key='[access token]', access_token_secret='[access token secret]')

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py

Python

src/genie/libs/parser/iosxr/tests/ShowL2vpnBridgeDomain/cli/equal/golden_output6_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/iosxr/tests/ShowL2vpnBridgeDomain/cli/equal/golden_output6_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/iosxr/tests/ShowL2vpnBridgeDomain/cli/equal/golden_output6_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "bridge_group": { "GTT_DIP": { "bridge_domain": { "GPF-CID-2723": { "id": 45, "state": "up", "shg_id": 0, "mst_i": 0, "mac_aging_time": 300, "mac_limit": 4000, "mac_limit_action": "none", "mac_limit_notification": "syslog", "filter_mac_address": 0, "ac": { "num_ac": 2, "num_ac_up": 2, "interfaces": { "Bundle-Ether53.2723": { "state": "up", "static_mac_address": 0, }, "TenGigabitEthernet0/2/0/3.2723": { "state": "up", "static_mac_address": 0, }, }, }, "vfi": { "num_vfi": 1, "GPF-CID01": { "state": "up", "neighbor": { "172.16.74.2": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.3": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.6": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.7": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.8": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.12": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.71.14": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.74.15": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.17": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.74.20": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.71.26": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.74.26": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.160": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, "172.16.70.165": { "pw_id": { 2723: {"state": "up", "static_mac_address": 0} } }, }, }, }, "pw": {"num_pw": 14, "num_pw_up": 14}, "pbb": {"num_pbb": 0, "num_pbb_up": 0}, "vni": {"num_vni": 0, "num_vni_up": 0}, }, "BPI-DIP196-BD": { "id": 46, "state": "up", "shg_id": 0, "mst_i": 0, "mac_aging_time": 300, "mac_limit": 4000, "mac_limit_action": "none", "mac_limit_notification": "syslog", "filter_mac_address": 0, "ac": { "num_ac": 1, "num_ac_up": 1, "interfaces": { "Bundle-Ether53.196": { "state": "up", "static_mac_address": 0, } }, }, "vfi": { "num_vfi": 1, "BPI196-VFI01": { "state": "up", "neighbor": { "172.16.70.160": { "pw_id": { 196: {"state": "up", "static_mac_address": 0} } } }, }, }, "pw": {"num_pw": 1, "num_pw_up": 1}, "pbb": {"num_pbb": 0, "num_pbb_up": 0}, "vni": {"num_vni": 0, "num_vni_up": 0}, }, } } } }

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Python

tienda/migrations/0001_initial.py

FreyderUrbano/mypets

8dffc425979ca2b5b97eaa004afb8b057e3a2a43

[ "MIT" ]

null

tienda/migrations/0001_initial.py

FreyderUrbano/mypets

8dffc425979ca2b5b97eaa004afb8b057e3a2a43

[ "MIT" ]

null

tienda/migrations/0001_initial.py

FreyderUrbano/mypets

8dffc425979ca2b5b97eaa004afb8b057e3a2a43

[ "MIT" ]

null

# Generated by Django 3.2.6 on 2021-10-09 19:56 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='City', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=10)), ('name', models.CharField(max_length=150)), ('abrev', models.CharField(max_length=4)), ], ), migrations.CreateModel( name='Country', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=10)), ('name', models.CharField(max_length=150)), ('abrev', models.CharField(max_length=4)), ], ), migrations.CreateModel( name='Identification_type', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('type', models.CharField(max_length=150)), ('abrow', models.CharField(max_length=4)), ], ), migrations.CreateModel( name='Pet', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=10)), ('name', models.CharField(max_length=150)), ], ), migrations.CreateModel( name='Race', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=10)), ('name', models.CharField(max_length=150)), ('abrev', models.CharField(max_length=4)), ], ), migrations.CreateModel( name='Session', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('ip', models.CharField(max_length=200)), ], ), migrations.CreateModel( name='Type', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.CharField(max_length=100)), ('name', models.CharField(max_length=150)), ('abrev', models.CharField(max_length=4)), ], ), migrations.CreateModel( name='user', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(max_length=200)), ('last_name', models.CharField(max_length=128)), ('email', models.CharField(max_length=200)), ('password', models.CharField(max_length=200)), ], ), ]

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108fb60a826ff84afba27a35951fe50710080c5c

138

py

Python

test/integration/samples_in/simple_str_return.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

487

2019-06-10T17:44:56.000Z

2022-03-26T01:28:19.000Z

test/integration/samples_in/simple_str_return.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

118

2019-07-03T12:26:39.000Z

2022-03-06T22:40:17.000Z

test/integration/samples_in/simple_str_return.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

25

2019-07-10T08:39:58.000Z

2022-03-03T14:44:15.000Z

"echo '{}'\r".format(self.FLUSH_CMD) "echo '{}'\\r".format(self.FLUSH_CMD) "echo '%s'\r" % self.FLUSH_CMD "echo '%s'\\r" % self.FLUSH_CMD

27.6

37

0.623188

24

138

3.416667

0.291667

0.439024

0.585366

1

0.585366

0

0.086957

138

4

38

34.5

0.650794

0

0.333333

0

1

0

true

0

1

0

null

1

0

1

0

null

0

1

0

9

52a62195734b7bdeab98009d6ad57e496f5597ab

6,683

py

Python

loldib/getratings/models/NA/na_skarner/na_skarner_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_skarner/na_skarner_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_skarner/na_skarner_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

from getratings.models.ratings import Ratings class NA_Skarner_Bot_Aatrox(Ratings): pass class NA_Skarner_Bot_Ahri(Ratings): pass class NA_Skarner_Bot_Akali(Ratings): pass class NA_Skarner_Bot_Alistar(Ratings): pass class NA_Skarner_Bot_Amumu(Ratings): pass class NA_Skarner_Bot_Anivia(Ratings): pass class NA_Skarner_Bot_Annie(Ratings): pass class NA_Skarner_Bot_Ashe(Ratings): pass class NA_Skarner_Bot_AurelionSol(Ratings): pass class NA_Skarner_Bot_Azir(Ratings): pass class NA_Skarner_Bot_Bard(Ratings): pass class NA_Skarner_Bot_Blitzcrank(Ratings): pass class NA_Skarner_Bot_Brand(Ratings): pass class NA_Skarner_Bot_Braum(Ratings): pass class NA_Skarner_Bot_Caitlyn(Ratings): pass class NA_Skarner_Bot_Camille(Ratings): pass class NA_Skarner_Bot_Cassiopeia(Ratings): pass class NA_Skarner_Bot_Chogath(Ratings): pass class NA_Skarner_Bot_Corki(Ratings): pass class NA_Skarner_Bot_Darius(Ratings): pass class NA_Skarner_Bot_Diana(Ratings): pass class NA_Skarner_Bot_Draven(Ratings): pass class NA_Skarner_Bot_DrMundo(Ratings): pass class NA_Skarner_Bot_Ekko(Ratings): pass class NA_Skarner_Bot_Elise(Ratings): pass class NA_Skarner_Bot_Evelynn(Ratings): pass class NA_Skarner_Bot_Ezreal(Ratings): pass class NA_Skarner_Bot_Fiddlesticks(Ratings): pass class NA_Skarner_Bot_Fiora(Ratings): pass class NA_Skarner_Bot_Fizz(Ratings): pass class NA_Skarner_Bot_Galio(Ratings): pass class NA_Skarner_Bot_Gangplank(Ratings): pass class NA_Skarner_Bot_Garen(Ratings): pass class NA_Skarner_Bot_Gnar(Ratings): pass class NA_Skarner_Bot_Gragas(Ratings): pass class NA_Skarner_Bot_Graves(Ratings): pass class NA_Skarner_Bot_Hecarim(Ratings): pass class NA_Skarner_Bot_Heimerdinger(Ratings): pass class NA_Skarner_Bot_Illaoi(Ratings): pass class NA_Skarner_Bot_Irelia(Ratings): pass class NA_Skarner_Bot_Ivern(Ratings): pass class NA_Skarner_Bot_Janna(Ratings): pass class NA_Skarner_Bot_JarvanIV(Ratings): pass class NA_Skarner_Bot_Jax(Ratings): pass class NA_Skarner_Bot_Jayce(Ratings): pass class NA_Skarner_Bot_Jhin(Ratings): pass class NA_Skarner_Bot_Jinx(Ratings): pass class NA_Skarner_Bot_Kalista(Ratings): pass class NA_Skarner_Bot_Karma(Ratings): pass class NA_Skarner_Bot_Karthus(Ratings): pass class NA_Skarner_Bot_Kassadin(Ratings): pass class NA_Skarner_Bot_Katarina(Ratings): pass class NA_Skarner_Bot_Kayle(Ratings): pass class NA_Skarner_Bot_Kayn(Ratings): pass class NA_Skarner_Bot_Kennen(Ratings): pass class NA_Skarner_Bot_Khazix(Ratings): pass class NA_Skarner_Bot_Kindred(Ratings): pass class NA_Skarner_Bot_Kled(Ratings): pass class NA_Skarner_Bot_KogMaw(Ratings): pass class NA_Skarner_Bot_Leblanc(Ratings): pass class NA_Skarner_Bot_LeeSin(Ratings): pass class NA_Skarner_Bot_Leona(Ratings): pass class NA_Skarner_Bot_Lissandra(Ratings): pass class NA_Skarner_Bot_Lucian(Ratings): pass class NA_Skarner_Bot_Lulu(Ratings): pass class NA_Skarner_Bot_Lux(Ratings): pass class NA_Skarner_Bot_Malphite(Ratings): pass class NA_Skarner_Bot_Malzahar(Ratings): pass class NA_Skarner_Bot_Maokai(Ratings): pass class NA_Skarner_Bot_MasterYi(Ratings): pass class NA_Skarner_Bot_MissFortune(Ratings): pass class NA_Skarner_Bot_MonkeyKing(Ratings): pass class NA_Skarner_Bot_Mordekaiser(Ratings): pass class NA_Skarner_Bot_Morgana(Ratings): pass class NA_Skarner_Bot_Nami(Ratings): pass class NA_Skarner_Bot_Nasus(Ratings): pass class NA_Skarner_Bot_Nautilus(Ratings): pass class NA_Skarner_Bot_Nidalee(Ratings): pass class NA_Skarner_Bot_Nocturne(Ratings): pass class NA_Skarner_Bot_Nunu(Ratings): pass class NA_Skarner_Bot_Olaf(Ratings): pass class NA_Skarner_Bot_Orianna(Ratings): pass class NA_Skarner_Bot_Ornn(Ratings): pass class NA_Skarner_Bot_Pantheon(Ratings): pass class NA_Skarner_Bot_Poppy(Ratings): pass class NA_Skarner_Bot_Quinn(Ratings): pass class NA_Skarner_Bot_Rakan(Ratings): pass class NA_Skarner_Bot_Rammus(Ratings): pass class NA_Skarner_Bot_RekSai(Ratings): pass class NA_Skarner_Bot_Renekton(Ratings): pass class NA_Skarner_Bot_Rengar(Ratings): pass class NA_Skarner_Bot_Riven(Ratings): pass class NA_Skarner_Bot_Rumble(Ratings): pass class NA_Skarner_Bot_Ryze(Ratings): pass class NA_Skarner_Bot_Sejuani(Ratings): pass class NA_Skarner_Bot_Shaco(Ratings): pass class NA_Skarner_Bot_Shen(Ratings): pass class NA_Skarner_Bot_Shyvana(Ratings): pass class NA_Skarner_Bot_Singed(Ratings): pass class NA_Skarner_Bot_Sion(Ratings): pass class NA_Skarner_Bot_Sivir(Ratings): pass class NA_Skarner_Bot_Skarner(Ratings): pass class NA_Skarner_Bot_Sona(Ratings): pass class NA_Skarner_Bot_Soraka(Ratings): pass class NA_Skarner_Bot_Swain(Ratings): pass class NA_Skarner_Bot_Syndra(Ratings): pass class NA_Skarner_Bot_TahmKench(Ratings): pass class NA_Skarner_Bot_Taliyah(Ratings): pass class NA_Skarner_Bot_Talon(Ratings): pass class NA_Skarner_Bot_Taric(Ratings): pass class NA_Skarner_Bot_Teemo(Ratings): pass class NA_Skarner_Bot_Thresh(Ratings): pass class NA_Skarner_Bot_Tristana(Ratings): pass class NA_Skarner_Bot_Trundle(Ratings): pass class NA_Skarner_Bot_Tryndamere(Ratings): pass class NA_Skarner_Bot_TwistedFate(Ratings): pass class NA_Skarner_Bot_Twitch(Ratings): pass class NA_Skarner_Bot_Udyr(Ratings): pass class NA_Skarner_Bot_Urgot(Ratings): pass class NA_Skarner_Bot_Varus(Ratings): pass class NA_Skarner_Bot_Vayne(Ratings): pass class NA_Skarner_Bot_Veigar(Ratings): pass class NA_Skarner_Bot_Velkoz(Ratings): pass class NA_Skarner_Bot_Vi(Ratings): pass class NA_Skarner_Bot_Viktor(Ratings): pass class NA_Skarner_Bot_Vladimir(Ratings): pass class NA_Skarner_Bot_Volibear(Ratings): pass class NA_Skarner_Bot_Warwick(Ratings): pass class NA_Skarner_Bot_Xayah(Ratings): pass class NA_Skarner_Bot_Xerath(Ratings): pass class NA_Skarner_Bot_XinZhao(Ratings): pass class NA_Skarner_Bot_Yasuo(Ratings): pass class NA_Skarner_Bot_Yorick(Ratings): pass class NA_Skarner_Bot_Zac(Ratings): pass class NA_Skarner_Bot_Zed(Ratings): pass class NA_Skarner_Bot_Ziggs(Ratings): pass class NA_Skarner_Bot_Zilean(Ratings): pass class NA_Skarner_Bot_Zyra(Ratings): pass

16.026379

46

0.77151

972

6,683

4.878601

0.151235

0.203712

0.407423

0.494728

0.808941

0

0.166243

6,683

416

47

16.064904

0.851041

0

0.498195

0

1

0

true

0.498195

0.00361

0

0.501805

0

null

1

0

null

0

1

0

7

52b4f66346b98c4762465c9924332faed815e0d7

62

py

Python

src/practice/list_example.py

Yasilagit/Python_Workspace

dc2274e685661e29e91b4f9f09cc9f228b17fe17

[ "MIT" ]

null

src/practice/list_example.py

Yasilagit/Python_Workspace

dc2274e685661e29e91b4f9f09cc9f228b17fe17

[ "MIT" ]

null

src/practice/list_example.py

Yasilagit/Python_Workspace

dc2274e685661e29e91b4f9f09cc9f228b17fe17

[ "MIT" ]

null

a=[1,2,3,4,5,6] print(a) del a[0] print(a) del a print(a)

10.333333

16

0.548387

18

62

1.888889

0.555556

0.529412

0.588235

0

0.14

0.193548

62

6

17

10.333333

0.54

0

0.5

0

1

0

false

0

0.5

1

0

1

null

1

0

1

0

null

0

1

0

7

52f414dc20b33ccc328de0aa04642b44294ef904

4,868

py

Python

ia_programino.py

gabrielepessoa/programino

c9c775efd79fb846b9ee0117519674a2955c58ae

[ "MIT" ]

null

ia_programino.py

gabrielepessoa/programino

c9c775efd79fb846b9ee0117519674a2955c58ae

[ "MIT" ]

null

ia_programino.py

gabrielepessoa/programino

c9c775efd79fb846b9ee0117519674a2955c58ae

[ "MIT" ]

null

import programino from .game import Game import math import copy class IAProgramino: def __init__(self): self.run = 0 # qtd de iterações do algoritmo def chose_better_move(self, game): move = self.play_max(game, True) # print(self.run) return move def play_max(self, game, is_root=False): # humano é player 0 # máquina é player 1 # se o jogo acabou: retorna +1, se maquina venceu; retorna -1 se humano venceu; retorna 0, se empate. self.run += 1 game = copy.deepcopy(game) if not game.valid_moves: if game.turn == 0: # print("Humano venceu!\n") return -1 # humano venceu elif game.turn == 1: # print("Máquina venceu!\n") return 1 # máquina venceu else: # print("Empate!\n") return 0 # empate vmax = -math.inf max_move = None # para cada peça X do conjunto JOGÁVEL (pela máquina) for move in game.valid_moves: gcopy = copy.deepcopy(game) # cria uma cópia do jogo gcopy.make_move(*move) # faz jogada para a máquina v = self.play_min(gcopy) # chama o play_min para o humano if v > vmax: vmax = v max_move = move return max_move if is_root else vmax def play_min(self, game): # humano é player 0 # máquina é player 1 # se o jogo acabou: retorna +1, se maquina venceu; retorna -1 se humano venceu; retorna 0, se empate. self.run += 1 game = copy.deepcopy(game) if not game.valid_moves: if game.turn == 0: # print("Humano venceu!\n") return -1 # humano venceu elif game.turn == 1: # print("Máquina venceu!\n") return 1 # máquina venceu else: # print("Empate!\n") return 0 # empate vmin = math.inf min_move = None # para cada peça X do conjunto JOGÁVEL (pelo humano) for move in game.valid_moves: gcopy = copy.deepcopy(game) # cria uma cópia do jogo gcopy.make_move(*move) # faz jogada para o humano v = self.play_max(gcopy) # chama o play_max para a máquina if v < vmin: vmin = v min_move = move return vmin class Worst: def __init__(self): self.run = 0 # qtd de iterações do algoritmo def chose_worst_move(self, game): move = self.play_max(game, True) # print(self.run) return move def play_max(self, game, is_root=False): # humano é player 0 # máquina é player 1 # se o jogo acabou: retorna +1, se maquina venceu; retorna -1 se humano venceu; retorna 0, se empate. self.run += 1 game = copy.deepcopy(game) if not game.valid_moves: if game.turn == 0: # print("Humano venceu!\n") return -1 # humano venceu elif game.turn == 1: # print("Máquina venceu!\n") return 1 # máquina venceu else: # print("Empate!\n") return 0 # empate vmax = -math.inf max_move = None # para cada peça X do conjunto JOGÁVEL (pela máquina) for move in game.valid_moves: gcopy = copy.deepcopy(game) # cria uma cópia do jogo gcopy.make_move(*move) # faz jogada para a máquina v = self.play_min(gcopy) # chama o play_min para o humano if v > vmax: vmax = v max_move = move return max_move if is_root else vmax def play_min(self, game): # humano é player 0 # máquina é player 1 # se o jogo acabou: retorna +1, se maquina venceu; retorna -1 se humano venceu; retorna 0, se empate. self.run += 1 game = copy.deepcopy(game) if not game.valid_moves: if game.turn == 0: # print("Humano venceu!\n") return 1 # humano venceu elif game.turn == 1: # print("Máquina venceu!\n") return -1 # máquina venceu else: # print("Empate!\n") return 0 # empate vmin = math.inf min_move = None # para cada peça X do conjunto JOGÁVEL (pelo humano) for move in game.valid_moves: gcopy = copy.deepcopy(game) # cria uma cópia do jogo gcopy.make_move(*move) # faz jogada para o humano v = self.play_max(gcopy) # chama o play_max para a máquina if v < vmin: vmin = v min_move = move return vmin

34.28169

109

0.525062

628

4,868

3.987261

0.122611

0.014377

0.031949

0.044728

0.963259

0

0.01563

0.39544

4,868

141

110

34.524823

0.835202

0.328061

0

0.916667

0

1

0.083333

false

0

0.041667

0

0.333333

0

null

0

1

0

1

0

null

0

7

d81a1c1ca780fbe0c10704402600cdd9d60e45b6

12,079

py

Python

pygitea/resources.py

jo-nas/pygitea

0937d26dbd33523c728e2eefa80f327d952864a5

[ "WTFPL" ]

null

pygitea/resources.py

jo-nas/pygitea

0937d26dbd33523c728e2eefa80f327d952864a5

[ "WTFPL" ]

null

pygitea/resources.py

jo-nas/pygitea

0937d26dbd33523c728e2eefa80f327d952864a5

[ "WTFPL" ]

2

2019-01-04T18:43:34.000Z

2021-10-18T17:43:25.000Z

#!/usr/env/bin python ''' Resources hash. I don't know how to make it less dirty.. Please, send help ''' resources = {u'/user/times': {u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/issues/{index}/times': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/statuses/{sha}': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'sha': True}}, u'get': {'parameters': {u'owner': True, u'repo': True, u'sha': True}}}, u'/orgs/{org}/members': {u'get': {'parameters': {u'org': True}}}, u'/users/search': {u'get': {'parameters': {u'q': False, u'limit': False}}}, u'/repos/{owner}/{repo}/branches/{branch}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'branch': True}}}, u'/users/{username}/repos': {u'get': {'parameters': {u'username': True}}}, u'/repos/{owner}/{repo}/issues/comments/{id}': {u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True}}}, u'/admin/users/{username}/orgs': {u'post': {'parameters': {u'username': True}}}, u'/user/gpg_keys': {u'post': {'parameters': {u'Form': False}}, u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/keys/{id}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True}}}, u'/repos/{owner}/{repo}/keys': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/orgs/{org}/public_members': {u'get': {'parameters': {u'org': True}}}, u'/teams/{id}': {u'get': {'parameters': {u'id': True}}, u'delete': {'parameters': {u'id': True}}, u'patch': {'parameters': {u'body': False, u'id': True}}}, u'/user/gpg_keys/{id}': {u'get': {'parameters': {u'id': True}}, u'delete': {'parameters': {u'id': True}}}, u'/repos/{owner}/{repo}': {u'get': {'parameters': {u'owner': True, u'repo': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/times': {u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/users/{username}/tokens': {u'post': {'parameters': {u'name': False}}, u'get': {'parameters': {}}}, u'/user/following/{username}': {u'put': {'parameters': {u'username': True}}, u'delete': {'parameters': {u'username': True}}}, u'/teams/{id}/repos': {u'get': {'parameters': {u'id': True}}}, u'/markdown/raw': {u'post': {'parameters': {u'body': False}}}, u'/orgs/{org}': {u'get': {'parameters': {u'org': True}}, u'patch': {'parameters': {u'body': False, u'org': True}}}, u'/users/{username}/followers': {u'get': {'parameters': {u'username': True}}}, u'/repos/{owner}/{repo}/releases': {u'get': {'parameters': {u'owner': True, u'repo': True, u'body': False}}}, u'/teams/{id}/members/{username}': {u'put': {'parameters': {u'username': True, u'id': True}}, u'delete': {'parameters': {u'username': True, u'id': True}}}, u'/repos/{owner}/{repo}/milestones': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True, u'id': True}}}, u'/repos/{owner}/{repo}/collaborators': {u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/releases/{id}': {u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True}}}, u'/repos/{owner}/{repo}/subscription': {u'put': {'parameters': {u'owner': True, u'repo': True}}, u'get': {'parameters': {u'owner': True, u'repo': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/issues/comments': {u'get': {'parameters': {u'owner': True, u'repo': True, u'string': False}}}, u'/teams/{id}/members': {u'get': {'parameters': {u'id': True}}}, u'/repos/{owner}/{repo}/raw/{filepath}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'filepath': True}}}, u'/orgs/{org}/hooks': {u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/issue/{index}/labels/{id}': {u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True, u'index': True}}}, u'/repos/{owner}/{repo}/branches': {u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/users/{username}': {u'get': {'parameters': {u'username': True}}}, u'/user/orgs': {u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/hooks': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/subscribers': {u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/admin/users': {u'post': {'parameters': {u'body': False}}}, u'/orgs/{org}/repos': {u'get': {'parameters': {u'org': True}}}, u'/users/{username}/following': {u'get': {'parameters': {u'username': True}}}, u'/repos/{owner}/{repo}/mirror-sync': {u'post': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/editorconfig/{filepath}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'filepath': True}}}, u'/user/following': {u'get': {'parameters': {}}}, u'/admin/users/{username}/repos': {u'post': {'parameters': {u'username': True}}}, u'/org/{org}/repos': {u'post': {'parameters': {u'body': False, u'org': True}}}, u'/repos/{owner}/{repo}/issue/{index}/labels': {u'put': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'index': True}}, u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'index': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True, u'index': True}}}, u'/repos/{owner}/{repo}/pulls/{index}/merge': {u'post': {'parameters': {u'owner': True, u'repo': True, u'index': True}}, u'get': {'parameters': {u'owner': True, u'repo': True, u'index': True}}}, u'/user/repos': {u'post': {'parameters': {u'body': False}}, u'get': {'parameters': {}}}, u'/users/{follower}/following/{followee}': {u'get': {'parameters': {u'follower': True, u'followee': True}}}, u'/repos/{owner}/{repo}/collaborators/{collaborator}': {u'put': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'collaborator': True}}, u'get': {'parameters': {u'owner': True, u'repo': True, u'collaborator': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True, u'collaborator': True}}}, u'/user/keys': {u'post': {'parameters': {u'body': False}}, u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/times/{tracker}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'user': True}}}, u'/repos/search': {u'get': {'parameters': {u'exclusive': False, u'uid': False, u'q': False, u'limit': False, u'mode': False, u'page': False}}}, u'/users/{username}/gpg_keys': {u'get': {'parameters': {u'username': True}}}, u'/orgs/{org}/hooks/': {u'post': {'parameters': {}}}, u'/user/subscriptions': {u'get': {'parameters': {}}}, u'/markdown': {u'post': {'parameters': {u'body': False}}}, u'/repos/{owner}/{repo}/issue/{index}/comments': {u'get': {'parameters': {u'owner': True, u'repo': True, u'id': True, u'string': False}}}, u'/orgs/{org}/teams': {u'post': {'parameters': {u'body': False, u'org': True}}, u'get': {'parameters': {u'org': True}}}, u'/user/emails': {u'post': {'parameters': {u'body': False}}, u'get': {'parameters': {}}, u'delete': {'parameters': {u'body': False}}}, u'/repos/{owner}/{repo}/issues': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True, u'state': False, u'page': False}}}, u'/user/following/{followee}': {u'get': {'parameters': {u'followee': True}}}, u'/user/{username}/orgs': {u'get': {'parameters': {u'username': False}}}, u'/repos/migrate': {u'post': {'parameters': {u'body': False}}}, u'/users/{username}/subscriptions': {u'get': {'parameters': {u'username': False}}}, u'/user/starred/{owner}/{repo}': {u'put': {'parameters': {u'owner': True, u'repo': True}}, u'get': {'parameters': {u'owner': True, u'repo': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True}}}, u'/orgs/{org}/hooks/{id}': {u'get': {'parameters': {}}, u'delete': {'parameters': {}}, u'patch': {'parameters': {}}}, u'/repos/{owner}/{repo}/hooks/{id}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False}}}, u'/repos/{owner}/{repo}/archive/{filepath}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'archive': True}}}, u'/repos/{owner}/{repo}/stargazers': {u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/user/keys/{id}': {u'get': {'parameters': {u'id': True}}, u'delete': {'parameters': {u'id': True}}}, u'/user': {u'get': {'parameters': {}}}, u'/admin/users/{username}': {u'delete': {'parameters': {u'username': True}}, u'patch': {'parameters': {u'username': True, u'body': False}}}, u'/repos/{owner}/{repo}/milestones/{id}': {u'get': {'parameters': {}}, u'delete': {'parameters': {u'owner': True, u'repo': True, u'body': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False}}}, u'/admin/users/{username}/keys': {u'post': {'parameters': {u'username': True}}}, u'/orgs/{org}/members/{username}': {u'get': {'parameters': {u'username': True, u'org': True}}, u'delete': {'parameters': {u'username': True, u'org': True}}}, u'/orgs/{org}/public_members/{username}': {u'put': {'parameters': {u'username': True, u'org': True}}, u'get': {'parameters': {u'username': True, u'org': True}}, u'delete': {'parameters': {u'username': True, u'org': True}}}, u'/repos/{owner}/{repo}/commits/{ref}/statuses': {u'get': {'parameters': {u'owner': True, u'repo': True, u'ref': True}}}, u'/users/{username}/keys': {u'get': {'parameters': {u'username': True}}}, u'/repos/{owner}/{repo}/labels': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/issues/{index}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'index': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'index': True}}}, u'/repos/{owner}/{repo}/issues/{index}/labels': {u'get': {'parameters': {u'owner': True, u'repo': True, u'index': True}}}, u'/repos/{owner}/{repo}/forks': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/repos/{owner}/{repo}/pulls': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False}}, u'get': {'parameters': {u'owner': True, u'repo': True}}}, u'/user/starred': {u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/pulls/{index}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'index': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'index': True}}}, u'/repos/{owner}/{repo}/labels/{id}': {u'get': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True}}}, u'/repositories/{id}': {u'get': {'parameters': {u'id': True}}}, u'/repos/{user}/{repo}/hooks/{id}': {u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True}}}, u'/repos/{owner}/{repo}/issues/{index}/comments': {u'post': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True}}}, u'/admin/users/{username}/keys/{id}': {u'delete': {'parameters': {u'username': True, u'id': True}}}, u'/users/{username}/starred': {u'get': {'parameters': {u'username': True}}}, u'/user/followers': {u'get': {'parameters': {}}}, u'/repos/{owner}/{repo}/issues/{index}/comments/{id}': {u'delete': {'parameters': {u'owner': True, u'repo': True, u'id': True, u'index': True}}, u'patch': {'parameters': {u'owner': True, u'repo': True, u'body': False, u'id': True, u'index': True}}}, u'/teams/{id}/repos/{org}/{repo}': {u'put': {'parameters': {u'repo': True, u'org': True, u'id': True}}, u'delete': {'parameters': {u'repo': True, u'org': True, u'id': True}}}, u'/version': {u'get': {'parameters': {}}}}

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null

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1

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1

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null

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7

d8374f2140d12fa51924eb213eefc65678901851

129

py

Python

pccm/main.py

FindDefinition/PCCM

fa0cc4e41f886f288bbacf92cea1625d927a54ad

[ "MIT" ]

3

2021-10-21T06:26:46.000Z

2022-03-10T11:14:40.000Z

pccm/main.py

FindDefinition/PCCM

fa0cc4e41f886f288bbacf92cea1625d927a54ad

[ "MIT" ]

1

2021-09-13T02:25:05.000Z

2021-09-13T02:27:50.000Z

pccm/main.py

FindDefinition/PCCM

fa0cc4e41f886f288bbacf92cea1625d927a54ad

[ "MIT" ]

null

""" pccm xxx.yyy.Class -o xxx.so --shared pccm-gen xxx.yyy.Class1 xxx.yyy.Class2 xxx.yyy.Class3 --output_dir . """ import fire

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1

0

7

dc6baf36ccaa3b18edc32cd47bff50ec3775cbce

83

py

Python

Python_Exercicios/ex097.py

gabrieldepaiva/Exercicios-CursoEmVideo

118231c24f040ca0ac3d3b6e6bf633e4eaa06858

[ "MIT" ]

null

Python_Exercicios/ex097.py

gabrieldepaiva/Exercicios-CursoEmVideo

118231c24f040ca0ac3d3b6e6bf633e4eaa06858

[ "MIT" ]

null

Python_Exercicios/ex097.py

gabrieldepaiva/Exercicios-CursoEmVideo

118231c24f040ca0ac3d3b6e6bf633e4eaa06858

[ "MIT" ]

null

def print2(txt): print('~' * len(txt)) print(txt) print('~' * len(txt))

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null

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7

dc711d40e276db66e776db4b7667565a1f805b56

365

py

Python

src/model/__init__.py

week-with-me/quiz-server

35287496aba8381119cf9fc3fcbb8a06d34c7a34

[ "MIT" ]

null

src/model/__init__.py

week-with-me/quiz-server

35287496aba8381119cf9fc3fcbb8a06d34c7a34

[ "MIT" ]

null

src/model/__init__.py

week-with-me/quiz-server

35287496aba8381119cf9fc3fcbb8a06d34c7a34

[ "MIT" ]

null

from src.model.actor import Actor from src.model.movie import Movie from src.model.genre import Genre from src.model.nation import Nation from src.model.director import Director from src.model.movie_actor import MovieActor from src.model.movie_genre import MovieGenre from src.model.movie_nation import MovieNation from src.model.movie_director import MovieDirector

40.555556

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0.854795

58

365

5.310345

0.224138

0.204545

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0.275974

0

0.09589

365

9

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true

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null

0

1

0

1

0

1

0

7

f4fc2a0f59cecb0119d1e80788abb0dd52bdb761

12,211

py

Python

tests/test_ncclimo.py

jhkennedy/processflow

c404bd3ad043fd6ae18d4f24d735777574faa660

[ "MIT" ]

null

tests/test_ncclimo.py

jhkennedy/processflow

c404bd3ad043fd6ae18d4f24d735777574faa660

[ "MIT" ]

null

tests/test_ncclimo.py

jhkennedy/processflow

c404bd3ad043fd6ae18d4f24d735777574faa660

[ "MIT" ]

null

import os import sys import unittest import inspect from configobj import ConfigObj if sys.path[0] != '.': sys.path.insert(0, os.path.abspath('.')) from jobs.Ncclimo import Climo as Ncclimo from jobs.JobStatus import JobStatus from lib.events import EventList from lib.util import print_message class TestNcclimo(unittest.TestCase): def __init__(self, *args, **kwargs): super(TestNcclimo, self).__init__(*args, **kwargs) config_path = os.path.join( os.getcwd(), 'tests', 'test_configs', 'test_run_no_sta.cfg') self.config = ConfigObj(config_path) self.project_path = os.path.join(os.getcwd(), '..', 'testproject') def test_ncclimo_setup(self): """ Run ncclimo setup on valid config """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') config = { 'account': '', 'year_set': 1, 'start_year': 50, 'end_year': 55, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.project_path, 'input'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'ne30', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'fv129x256', 'climo', '5yr'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.project_path, 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status.name, 'VALID') def test_ncclimo_valid_prevalidate(self): """ Test that valid input config will be marked as valid by the job """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') config = { 'account': '', 'year_set': 1, 'start_year': 50, 'end_year': 55, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.project_path, 'input'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'ne30', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'fv129x256', 'climo', '5yr'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.project_path, 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) ncclimo.status = JobStatus.VALID self.assertFalse(ncclimo.prevalidate(config)) def test_ncclimo_missing_input(self): """ Test that a missing input item will invalidate the job """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') config = { 'account': '', 'year_set': 1, 'start_year': 50, 'end_year': 55, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', #'input_directory': os.path.join(self.project_path, 'input'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'ne30', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'fv129x256', 'climo', '5yr'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.project_path, 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status.name, 'INVALID') def test_ncclimo_execute_not_completed(self): """ Test that ncclimo will do all proper setup in an incomplete run """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') start_year = 51 end_year = 55 self.config['global']['project_path'] = '/p/user_pub/e3sm/baldwin32/E3SM_test_data/DECKv1b_1pctCO2_not_complete' self.config['global']['exeriment'] = '20171011.beta2_FCT2-icedeep_branch.A_WCYCL1850S.ne30_oECv3_ICG.edison' year_set_string = '{start:04d}-{end:04d}'.format( start=start_year, end=end_year) config = { 'account': '', 'year_set': 1, 'start_year': start_year, 'end_year': end_year, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.config['global']['project_path'], 'input', 'atm'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'ne30', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'pp', 'fv129x256', 'climo', '5yr'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.config['global']['project_path'], 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status, JobStatus.VALID) self.assertFalse(ncclimo.execute(dryrun=True)) self.assertEqual(ncclimo.status.name, 'COMPLETED') def test_ncclimo_execute_completed(self): """ test that if ncclimo is told to run on a project thats already completed ncclimo for the given yearset it will varify that the output is present and not run again """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') start_year = 1 end_year = 10 # REAL DATA project_path = '/p/user_pub/e3sm/baldwin32/E3SM_test_data/DECKv1b_1pctCO2_complete' year_set_string = '{start:04d}-{end:04d}'.format( start=start_year, end=end_year) config = { 'account': '', 'year_set': 1, 'start_year': start_year, 'end_year': end_year, 'caseId': '20180129.DECKv1b_piControl.ne30_oEC.edison', 'annual_mode': 'sdd', 'input_directory': os.path.join(project_path, 'input', 'atm'), 'climo_output_directory': os.path.join(project_path, 'output', 'pp', 'ne30', 'climo', '10yr'), 'regrid_output_directory': os.path.join(project_path, 'output', 'pp', 'fv129x256', 'climo', '10yr'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(project_path, 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status, JobStatus.VALID) ncclimo.execute(dryrun=True) self.assertTrue(ncclimo.postvalidate()) def test_ncclimo_execute_bad_year(self): """ test that if given the wrong input year ncclimo will exit correctly """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') start_year = 55 end_year = 60 self.config['global']['project_path'] = '/p/user_pub/e3sm/baldwin32/E3SM_test_data/DECKv1b_1pctCO2_complete' self.config['global']['exeriment'] = '20180215.DECKv1b_1pctCO2.ne30_oEC.edison' year_set_string = '{start:04d}-{end:04d}'.format( start=start_year, end=end_year) config = { 'account': '', 'year_set': 1, 'start_year': start_year, 'end_year': end_year, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.config['global']['project_path'], 'input', 'atm'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'climo_regrid'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.config['global']['project_path'], 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status, JobStatus.VALID) self.assertFalse(ncclimo.postvalidate()) def test_ncclimo_execute_bad_regrid_dir(self): print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') start_year = 56 end_year = 60 self.config['global']['project_path'] = '/p/cscratch/acme/baldwin32/20171016/' self.config['global']['exeriment'] = '20171011.beta2_FCT2-icedeep_branch.A_WCYCL1850S.ne30_oECv3_ICG.edison' year_set_string = '{start:04d}-{end:04d}'.format( start=start_year, end=end_year) config = { 'account': '', 'year_set': 1, 'start_year': start_year, 'end_year': end_year, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.config['global']['project_path'], 'input', 'atm'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'climo', '5yr'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'XXYYZZ'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.config['global']['project_path'], 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status, JobStatus.VALID) self.assertFalse(ncclimo.postvalidate()) def test_ncclimo_execute_bad_climo_dir(self): """ test that ncclimo will correctly exit if given a non-existant climo dir """ print '\n'; print_message('---- Starting Test: {} ----'.format(inspect.stack()[0][3]), 'ok') start_year = 56 end_year = 60 self.config['global']['project_path'] = '/p/cscratch/acme/baldwin32/20171016/' self.config['global']['exeriment'] = '20171011.beta2_FCT2-icedeep_branch.A_WCYCL1850S.ne30_oECv3_ICG.edison' year_set_string = '{start:04d}-{end:04d}'.format( start=start_year, end=end_year) config = { 'account': '', 'year_set': 1, 'start_year': start_year, 'end_year': end_year, 'caseId': self.config['global']['experiment'], 'annual_mode': 'sdd', 'input_directory': os.path.join(self.config['global']['project_path'], 'input', 'atm'), 'climo_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'climo', 'XXYYZZ'), 'regrid_output_directory': os.path.join(self.config['global']['project_path'], 'output', 'climo_regrid'), 'regrid_map_path': self.config['ncclimo']['regrid_map_path'], 'year_set': 1, 'run_scripts_path': os.path.join(self.config['global']['project_path'], 'output', 'run_scripts') } ncclimo = Ncclimo( config=config, event_list=EventList()) self.assertEqual(ncclimo.status, JobStatus.VALID) self.assertFalse(ncclimo.postvalidate()) if __name__ == '__main__': unittest.main()

46.965385

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null

0

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8

7601183f480a507e53beec4a7a2c174bc0e2743b

31,667

py

Python

tests/python/spec/test_stl_spec_discrete_time_online_evaluation.py

sguysc/rtamt

a16db77b61028f774d81457ff22e666229a5432c

[ "BSD-3-Clause" ]

24

2019-12-04T00:20:16.000Z

2022-03-24T17:48:14.000Z

tests/python/spec/test_stl_spec_discrete_time_online_evaluation.py

sguysc/rtamt

a16db77b61028f774d81457ff22e666229a5432c

[ "BSD-3-Clause" ]

142

2020-01-16T15:36:21.000Z

2022-03-28T20:40:45.000Z

tests/python/spec/test_stl_spec_discrete_time_online_evaluation.py

sguysc/rtamt

a16db77b61028f774d81457ff22e666229a5432c

[ "BSD-3-Clause" ]

17

2020-07-07T20:32:08.000Z

2022-03-07T07:20:22.000Z

import unittest import math import rtamt class TestSTLSpecDiscreteTimeOnlineEvaluation(unittest.TestCase): def __init__(self, *args, **kwargs): super(TestSTLSpecDiscreteTimeOnlineEvaluation, self).__init__(*args, **kwargs) self.left1 = 100 self.right1 = 20 self.left2 = -1 self.right2 = -2 self.left3 = -2 self.right3 = 10 self.left4 = 5 self.right4 = 4 self.left5 = -1 self.right5 = -1 def test_constant(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('out', 'float') spec.spec = 'out = 5' spec.parse(); out1 = spec.update(0, []) out2 = spec.update(1, []) self.assertEqual(out1, 5, "input 1") self.assertEqual(out2, 5, "input 2") def test_constant_2(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_const('c', 'int', 5) spec.declare_var('out', 'float') spec.spec = 'out = c' spec.parse(); out1 = spec.update(0, []) out2 = spec.update(1, []) self.assertEqual(out1, 5, "input 1") self.assertEqual(out2, 5, "input 2") def test_addition(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req + gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 120, "input 1") self.assertEqual(out2, -3, "input 2") self.assertEqual(out3, 8, "input 3") self.assertEqual(out4, 9, "input 4") self.assertEqual(out5, -2, "input 5") def test_subtraction(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req - gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 80, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, -12, "input 3") self.assertEqual(out4, 1, "input 4") self.assertEqual(out5, 0, "input 5") def test_multiplication(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req * gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 2000, "input 1") self.assertEqual(out2, 2, "input 2") self.assertEqual(out3, -20, "input 3") self.assertEqual(out4, 20, "input 4") self.assertEqual(out5, 1, "input 5") def test_division(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req / gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 100 / 20, "input 1") self.assertEqual(out2, -1 / -2, "input 2") self.assertEqual(out3, -2 / 10, "input 3") self.assertEqual(out4, 5 / 4, "input 4") self.assertEqual(out5, -1 / -1, "input 5") def test_abs(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = abs(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, 2, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, 1, "input 5") def test_sqrt(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = sqrt(req)' spec.parse(); out1 = spec.update(0, [('req', 2)]) out2 = spec.update(1, [('req', 3.3)]) out3 = spec.update(2, [('req', 4.5)]) out4 = spec.update(3, [('req', 0.1)]) out5 = spec.update(4, [('req', 1)]) self.assertEqual(out1, math.sqrt(2), "input 1") self.assertEqual(out2, math.sqrt(3.3), "input 2") self.assertEqual(out3, math.sqrt(4.5), "input 3") self.assertEqual(out4, math.sqrt(0.1), "input 4") self.assertEqual(out5, math.sqrt(1), "input 5") def test_previous(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = prev(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, float("inf"), "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, -2, "input 4") self.assertEqual(out5, 5, "input 5") def test_next_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = next(req)' spec.parse() self.assertRaises(rtamt.LTLNotImplementedException, spec.update, 0, [('req', self.left1)]) def test_next_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = next(req)' spec.parse() spec.pastify() out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, -1, "input 5") def test_and(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req and gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 20, "input 1") self.assertEqual(out2, -2, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, 4, "input 4") self.assertEqual(out5, -1, "input 5") def test_or(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req or gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, 10, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, -1, "input 5") def test_iff(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req iff gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, -80, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -12, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, 0, "input 5") def test_xor(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req xor gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 80, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, 12, "input 3") self.assertEqual(out4, 1, "input 4") self.assertEqual(out5, 0, "input 5") def test_implies(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req -> gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 20, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, 10, "input 3") self.assertEqual(out4, 4, "input 4") self.assertEqual(out5, 1, "input 5") def test_always_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = always(req)' spec.parse() self.assertRaises(rtamt.LTLNotImplementedException, spec.update, 0, [('req', self.left1)]) def test_always_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = always(req)' spec.parse() self.assertRaises(rtamt.LTLPastifyException, spec.pastify) def test_eventually_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = eventually(req)' spec.parse() self.assertRaises(rtamt.LTLNotImplementedException, spec.update, 0, [('req', self.left1)]) def test_eventually_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = eventually(req)' spec.parse() self.assertRaises(rtamt.LTLPastifyException, spec.pastify) def test_historically(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = historically(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, -2, "input 4") self.assertEqual(out5, -2, "input 5") def test_once(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = once(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, 100, "input 3") self.assertEqual(out4, 100, "input 4") self.assertEqual(out5, 100, "input 5") def test_since(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req since gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 20, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, 10, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, -1, "input 5") def test_until_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification() spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req until gnt' spec.parse() self.assertRaises(rtamt.LTLNotImplementedException, spec.update, 0, [('req', self.left1), ('gnt', self.right1)]) def test_always_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification() spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req until gnt' spec.parse() self.assertRaises(rtamt.LTLPastifyException, spec.pastify) def test_eventually_0_1_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = eventually[0,1](req)' spec.parse() self.assertRaises(rtamt.STLNotImplementedException, spec.update, 0, [('req', self.left1)]) def test_eventually_0_1_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = eventually[0,1](req)' spec.parse() spec.pastify() out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, 5, "input 5") def test_once_0_1(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = once[0,1](req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, 5, "input 5") def test_once_1_2(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = once[1,2](req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, -float("inf"), "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, 100, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, 5, "input 5") def test_always_0_1_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = always[0,1](req)' spec.parse() self.assertRaises(rtamt.STLNotImplementedException, spec.update, 0, [('req', self.left1)]) def test_always_0_1_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = always[0,1](req)' spec.parse(); spec.pastify() out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, -2, "input 4") self.assertEqual(out5, -1, "input 5") def test_historically_0_1(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = historically[0,1](req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, -2, "input 4") self.assertEqual(out5, -1, "input 5") def test_historically_1_2(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = historically[1,2](req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, float("inf"), "input 1") self.assertEqual(out2, 100, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, -2, "input 4") self.assertEqual(out5, -2, "input 5") def test_until_0_1_without_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req until[0,1] gnt' spec.parse() self.assertRaises(rtamt.STLNotImplementedException, spec.update, 0, [('req', self.left1), ('gnt', self.right1)]) def test_until_1_2_with_pastify(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req until[1,2] gnt' spec.parse(); spec.pastify(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 20, "input 1") self.assertEqual(out2, 20, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, -2, "input 5") def test_since_0_1(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req since[0,1] gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 20, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, 10, "input 3") self.assertEqual(out4, 5, "input 4") self.assertEqual(out5, -1, "input 5") def test_not(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = not(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, -100, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, 2, "input 3") self.assertEqual(out4, -5, "input 4") self.assertEqual(out5, 1, "input 5") def test_rise(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = rise(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, 100, "input 1") self.assertEqual(out2, -100, "input 2") self.assertEqual(out3, -2, "input 3") self.assertEqual(out4, 2, "input 4") self.assertEqual(out5, -5, "input 5") def test_fall(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('out', 'float') spec.spec = 'out = fall(req)' spec.parse(); out1 = spec.update(0, [('req', self.left1)]) out2 = spec.update(1, [('req', self.left2)]) out3 = spec.update(2, [('req', self.left3)]) out4 = spec.update(3, [('req', self.left4)]) out5 = spec.update(4, [('req', self.left5)]) self.assertEqual(out1, -100, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, -1, "input 3") self.assertEqual(out4, -5, "input 4") self.assertEqual(out5, 1, "input 5") def test_predicate_leq(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req <= gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, -80, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, 12, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, 0, "input 5") def test_predicate_less(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req < gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, -80, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, 12, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, 0, "input 5") def test_predicate_geq(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req >= gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 80, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, -12, "input 3") self.assertEqual(out4, 1, "input 4") self.assertEqual(out5, 0, "input 5") def test_predicate_greater(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req > gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 80, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, -12, "input 3") self.assertEqual(out4, 1, "input 4") self.assertEqual(out5, 0, "input 5") def test_predicate_eq(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req == gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, -80, "input 1") self.assertEqual(out2, -1, "input 2") self.assertEqual(out3, -12, "input 3") self.assertEqual(out4, -1, "input 4") self.assertEqual(out5, 0, "input 5") def test_predicate_neq(self): spec = rtamt.STLDiscreteTimeSpecification(); spec.declare_var('req', 'float') spec.declare_var('gnt', 'float') spec.declare_var('out', 'float') spec.spec = 'out = req !== gnt' spec.parse(); out1 = spec.update(0, [('req', self.left1), ('gnt', self.right1)]) out2 = spec.update(1, [('req', self.left2), ('gnt', self.right2)]) out3 = spec.update(2, [('req', self.left3), ('gnt', self.right3)]) out4 = spec.update(3, [('req', self.left4), ('gnt', self.right4)]) out5 = spec.update(4, [('req', self.left5), ('gnt', self.right5)]) self.assertEqual(out1, 80, "input 1") self.assertEqual(out2, 1, "input 2") self.assertEqual(out3, 12, "input 3") self.assertEqual(out4, 1, "input 4") self.assertEqual(out5, 0, "input 5") if __name__ == '__main__': unittest.main()

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7616b78ee8c643a1b358ee3c436ad160c22a48c6

1,565

py

Python

system/t06_publish/show.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

666

2018-04-21T19:27:02.000Z

2022-03-31T22:58:06.000Z

system/t06_publish/show.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

460

2018-04-18T18:35:24.000Z

2022-03-31T13:39:22.000Z

system/t06_publish/show.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

141

2018-05-31T12:13:37.000Z

2022-03-31T11:07:22.000Z

from lib import BaseTest class PublishShow1Test(BaseTest): """ publish show: existing snapshot """ fixtureDB = True fixturePool = True fixtureCmds = [ "aptly snapshot create snap1 from mirror gnuplot-maverick", "aptly publish snapshot -keyring=${files}/aptly.pub -secret-keyring=${files}/aptly.sec snap1", ] runCmd = "aptly publish show maverick" class PublishShow2Test(BaseTest): """ publish show: under prefix """ fixtureDB = True fixturePool = True fixtureCmds = [ "aptly snapshot create snap1 from mirror gnuplot-maverick", "aptly publish snapshot -keyring=${files}/aptly.pub -secret-keyring=${files}/aptly.sec snap1 ppa/smira", ] runCmd = "aptly publish show maverick ppa/smira" class PublishShow3Test(BaseTest): """ publish show json: existing snapshot """ fixtureDB = True fixturePool = True fixtureCmds = [ "aptly snapshot create snap1 from mirror gnuplot-maverick", "aptly publish snapshot -keyring=${files}/aptly.pub -secret-keyring=${files}/aptly.sec snap1", ] runCmd = "aptly publish show -json maverick" class PublishShow4Test(BaseTest): """ publish show json: under prefix """ fixtureDB = True fixturePool = True fixtureCmds = [ "aptly snapshot create snap1 from mirror gnuplot-maverick", "aptly publish snapshot -keyring=${files}/aptly.pub -secret-keyring=${files}/aptly.sec snap1 ppa/smira", ] runCmd = "aptly publish show -json maverick ppa/smira"

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76292cbebd84ed742fee6d813ffe16cea3ed4ab6

112,112

py

Python

tests/dhcpv6/kea_only/config_backend/test_cb_v6_cmds_api.py

isc-projects/forge

dfec8b41003d6b5a229f69ee93616e0e5cc6d71b

[ "0BSD" ]

22

2015-02-27T11:51:05.000Z

2022-02-28T12:39:29.000Z

tests/dhcpv6/kea_only/config_backend/test_cb_v6_cmds_api.py

isc-projects/forge

dfec8b41003d6b5a229f69ee93616e0e5cc6d71b

[ "0BSD" ]

16

2018-10-30T15:00:12.000Z

2019-01-11T17:55:13.000Z

tests/dhcpv6/kea_only/config_backend/test_cb_v6_cmds_api.py

isc-projects/forge

dfec8b41003d6b5a229f69ee93616e0e5cc6d71b

[ "0BSD" ]

11

2015-02-27T11:51:36.000Z

2021-03-30T08:33:54.000Z

"""Kea database config backend commands hook testing""" import pytest import srv_msg from cb_model import setup_server_for_config_backend_cmds pytestmark = [pytest.mark.v6, pytest.mark.kea_only, pytest.mark.controlchannel, pytest.mark.hook, pytest.mark.config_backend, pytest.mark.cb_cmds] @pytest.fixture(autouse=True) def run_around_tests(): setup_server_for_config_backend_cmds() cmd = dict(command="remote-server6-set", arguments={"remote": {"type": "mysql"}, "servers": [{"server-tag": "abc"}]}) srv_msg.send_ctrl_cmd(cmd, exp_result=0) def test_availability(): cmd = dict(command='list-commands') response = srv_msg.send_ctrl_cmd(cmd) for cmd in ["remote-global-parameter6-del", "remote-global-parameter6-get", "remote-global-parameter6-get-all", "remote-global-parameter6-set", "remote-network6-del", "remote-network6-get", "remote-network6-list", "remote-network6-set", "remote-option-def6-del", "remote-option-def6-get", "remote-option-def6-get-all", "remote-option-def6-set", "remote-option6-global-del", "remote-option6-global-get", "remote-option6-global-get-all", "remote-option6-global-set", "remote-subnet6-del-by-id", "remote-subnet6-del-by-prefix", "remote-subnet6-get-by-id", "remote-subnet6-get-by-prefix", "remote-subnet6-list", "remote-subnet6-set"]: assert cmd in response['arguments'] # subnet tests @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_subnet6_set_basic(channel): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "interface": "$(SERVER_IFACE)", "id": 1, "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_set_empty_subnet(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-network-name": "", "subnets": [{"subnet": "", "id": 1, "interface": "$(SERVER_IFACE)"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "subnet configuration failed: Invalid subnet syntax (prefix/len expected)" in response["text"] def test_remote_subnet6_set_missing_subnet(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-network-name": "", "subnets": [{"interface": "$(SERVER_IFACE)", "id": 1}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "subnet configuration failed: mandatory 'subnet' parameter " \ "is missing for a subnet being configured" in response["text"] def test_remote_subnet6_set_stateless(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "shared-network-name": "", "interface": "$(SERVER_IFACE)"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_set_id(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 5, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 5, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_set_duplicated_id(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 5, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 5, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:2::/64", "id": 5, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:2::1-2001:db8:2::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 5, "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "subnets": [{"id": 5, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "1 IPv6 subnet(s) found."} def test_remote_subnet6_set_duplicated_subnet(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 5, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 5, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_set_all_values(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"shared-network-name": "", "require-client-classes": ["XYZ"], "id": 2, "interface": "$(SERVER_IFACE)", "pools": [{"pool": "2001:db8:1::1-2001:db8:1::10", "option-data": [{"code": 7, "data": "12", "always-send": True, "csv-format": True}]}], "pd-pools": [{ "delegated-len": 91, "prefix": "2001:db8:2::", "prefix-len": 90}], "reservation-mode": "all", "subnet": "2001:db8:1::/64", "valid-lifetime": 1000, "rebind-timer": 500, "renew-timer": 200, "option-data": [{"code": 7, "data": "123", "always-send": True, "csv-format": True}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 2, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_get_all_values(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"shared-network-name": "", "require-client-classes": ["XYZ"], "id": 2, "interface": "$(SERVER_IFACE)", "pools": [{"pool": "2001:db8:1::1-2001:db8:1::10", "option-data": [{"code": 7, "data": "12", "always-send": True, "csv-format": True}]}], "pd-pools": [{ "delegated-len": 91, "prefix": "2001:db8:2::", "prefix-len": 90}], "reservation-mode": "all", "subnet": "2001:db8:1::/64", "valid-lifetime": 1000, "rebind-timer": 500, "renew-timer": 200, "option-data": [{"code": 7, "data": "123", "always-send": True, "csv-format": True}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 2, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": { "count": 1, "subnets": [{ "metadata": {"server-tags": ["abc"]}, "require-client-classes": ["XYZ"], "shared-network-name": None, "id": 2, "interface": srv_msg.get_interface(), "option-data": [{"always-send": True, "code": 7, "csv-format": True, "name": "preference", "space": "dhcp6", "data": "123"}], "pools": [{ "option-data": [{"code": 7, "data": "12", "name": "preference", "always-send": True, "csv-format": True, "space": "dhcp6"}], "pool": "2001:db8:1::1-2001:db8:1::10"}], "pd-pools": [{ "option-data": [], "delegated-len": 91, "prefix": "2001:db8:2::", "prefix-len": 90}], "reservations-global": False, "reservations-in-subnet": True, "reservations-out-of-pool": False, "subnet": "2001:db8:1::/64", "rebind-timer": 500, "renew-timer": 200, "relay": {"ip-addresses": []}, "valid-lifetime": 1000}]}, "result": 0, "text": "IPv6 subnet 2001:db8:1::/64 found."} # reservation-mode is integer in db, so we need to check if it's converted correctly def test_remote_subnet6_set_reservation_mode_all_old(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservation-mode": "all", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response["arguments"]["subnets"][0]["reservations-global"] is False assert response["arguments"]["subnets"][0]["reservations-in-subnet"] is True assert response["arguments"]["subnets"][0]["reservations-out-of-pool"] is False def test_remote_subnet6_set_reservation_mode_all_new(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservations-global": False, "reservations-in-subnet": True, "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is False assert subnet["reservations-in-subnet"] is True if "reservations-out-of-pool" in subnet: assert subnet["reservations-out-of-pool"] is False def test_remote_subnet6_set_reservation_mode_global_old(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservation-mode": "global", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is True assert subnet["reservations-in-subnet"] is False if "reservations-out-of-pool" in subnet: assert subnet["reservations-out-of-pool"] is False def test_remote_subnet6_set_reservation_mode_global_new(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservations-global": True, "reservations-in-subnet": False, "reservations-out-of-pool": False, "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is True assert subnet["reservations-in-subnet"] is False if "reservations-out-of-pool" in subnet: assert subnet["reservations-out-of-pool"] is False def test_remote_subnet6_set_reservation_mode_out_pool_old(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservation-mode": "out-of-pool", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is False assert subnet["reservations-in-subnet"] is True assert subnet["reservations-out-of-pool"] is True def test_remote_subnet6_set_reservation_mode_out_pool_new(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "reservations-global": False, "reservations-in-subnet": True, "reservations-out-of-pool": True, "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is False assert subnet["reservations-in-subnet"] is True assert subnet["reservations-out-of-pool"] is True def test_remote_subnet6_set_reservation_mode_disabled_old(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "shared-network-name": "", "interface": "$(SERVER_IFACE)", "reservation-mode": "disabled"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is False assert subnet["reservations-in-subnet"] is False if "reservations-out-of-pool" in subnet: assert subnet["reservations-out-of-pool"] is False def test_remote_subnet6_set_reservation_mode_disabled_new(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "shared-network-name": "", "interface": "$(SERVER_IFACE)", "reservations-global": False, "reservations-in-subnet": False, "reservations-out-of-pool": False}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) subnet = response["arguments"]["subnets"][0] assert subnet["reservations-global"] is False assert subnet["reservations-in-subnet"] is False if "reservations-out-of-pool" in subnet: assert subnet["reservations-out-of-pool"] is False def _subnet_set(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 5, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 5, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} def test_remote_subnet6_del_by_id(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": 5}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 subnet(s) deleted."} def test_remote_subnet6_del_by_id_incorrect_id(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": 15}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 IPv6 subnet(s) deleted."} def test_remote_subnet6_del_id_negative_missing_subnet(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'id' parameter"} def test_remote_subnet6_del_by_prefix(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 subnet(s) deleted."} def test_remote_subnet6_del_by_prefix_non_existing_subnet(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:2::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 IPv6 subnet(s) deleted."} def test_remote_subnet6_del_by_prefix_missing_subnet_(): _subnet_set() cmd = dict(command="remote-subnet6-del-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": 2}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'subnet' parameter"} def test_remote_subnet6_get_by_id(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"shared-network-name": "", "id": 2, "interface": "$(SERVER_IFACE)", "pools": [{"pool": "2001:db8:1::1-2001:db8:1::10", "option-data": [{"code": 7, "data": "123", "always-send": True, "csv-format": True}]}], "reservation-mode": "global", "subnet": "2001:db8:1::/64", "valid-lifetime": 1000, "rebind-timer": 500, "renew-timer": 200, "option-data": [{"code": 7, "data": "12", "always-send": True, "csv-format": True}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 2, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": 2}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "subnets": [{"metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "id": 2, "interface": srv_msg.get_interface(), "option-data": [{"always-send": True, "code": 7, "csv-format": True, "data": "12", "name": "preference", "space": "dhcp6"}], "pools": [{"option-data": [{"always-send": True, "code": 7, "csv-format": True, "data": "123", "name": "preference", "space": "dhcp6"}], "pool": "2001:db8:1::1-2001:db8:1::10"}], "rebind-timer": 500, "renew-timer": 200, "reservations-global": True, "reservations-in-subnet": False, "pd-pools": [], "relay": {"ip-addresses": []}, "subnet": "2001:db8:1::/64", "valid-lifetime": 1000}]}, "result": 0, "text": "IPv6 subnet 2 found."} def test_remote_subnet6_get_by_id_incorrect_id(): _subnet_set() cmd = dict(command="remote-subnet6-get-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": 3}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "subnets": []}, "result": 3, "text": "IPv6 subnet 3 not found."} def test_remote_subnet6_get_by_id_missing_id(): _subnet_set() cmd = dict(command="remote-subnet6-get-by-id", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": 3}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'id' parameter"} def test_remote_subnet6_get_by_prefix(): cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"shared-network-name": "", "interface": "$(SERVER_IFACE)", "pools": [ {"pool": "2001:db8:1::1-2001:db8:1::10"}], "reservation-mode": "all", "require-client-classes": ["XYZ"], "subnet": "2001:db8:1::/64", "id": 1, "valid-lifetime": 1000}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:1::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": { "count": 1, "subnets": [{ "metadata": {"server-tags": ["abc"]}, "require-client-classes": ["XYZ"], "shared-network-name": None, "id": 1, "interface": srv_msg.get_interface(), "option-data": [], "pools": [{ "option-data": [], "pool": "2001:db8:1::1-2001:db8:1::10"}], "reservations-global": False, "reservations-in-subnet": True, "reservations-out-of-pool": False, "pd-pools": [], "relay": {"ip-addresses": []}, "subnet": "2001:db8:1::/64", "valid-lifetime": 1000}]}, "result": 0, "text": "IPv6 subnet 2001:db8:1::/64 found."} def test_remote_subnet6_get_by_prefix_negative(): _subnet_set() cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "2001:db8:2::/63"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "subnets": []}, "result": 3, "text": "IPv6 subnet 2001:db8:2::/63 not found."} def test_remote_subnet6_get_by_prefix_incorrect_prefix(): _subnet_set() cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"subnet": "::/64"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "unable to parse invalid IPv6 prefix ::/64"} def test_remote_subnet6_get_by_prefix_missing_prefix(): _subnet_set() cmd = dict(command="remote-subnet6-get-by-prefix", arguments={"remote": {"type": "mysql"}, "subnets": [{"id": "2001:db8:2::/63"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'subnet' parameter"} def test_remote_subnet6_list(): _subnet_set() cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:2::/64", "id": 3, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:2::1-2001:db8:2::10"}]}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:3::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "", "pools": [ {"pool": "2001:db8:3::1-2001:db8:3::10"}]}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 3, "subnets": [{"id": 1, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:3::/64"}, {"id": 3, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:2::/64"}, {"id": 5, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "3 IPv6 subnet(s) found."} # network tests @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_network6_set_basic(channel): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{"name": "floor13"}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"shared-networks": [{"name": "floor13"}]}, "result": 0, "text": "IPv6 shared network successfully set."} def test_remote_network6_set_missing_name(): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "missing parameter 'name'" in response["text"] def test_remote_network6_set_empty_name(): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": ""}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "'name' parameter must not be empty"} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_network6_get_basic(channel): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd, channel=channel) cmd = dict(command="remote-network6-get", arguments={"remote": {"type": "mysql"}, "shared-networks": [{ "name": "net1"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "shared-networks": [{"interface": srv_msg.get_interface(), "name": "net1", "metadata": {"server-tags": ["abc"]}, "option-data": [], "relay": {"ip-addresses": []}}]}, "result": 0, "text": "IPv6 shared network 'net1' found."} def test_remote_network6_get_all_values(): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "client-class": "abc", "require-client-classes": ["XYZ"], "rebind-timer": 200, "renew-timer": 100, "calculate-tee-times": True, "t1-percent": 0.5, "t2-percent": 0.8, "rapid-commit": True, "valid-lifetime": 300, "reservation-mode": "global", "user-context": {"some weird network": 55}, "interface": "$(SERVER_IFACE)", "option-data": [{"code": 7, "data": "123", "always-send": True, "csv-format": True}]}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-network6-get", arguments={"remote": {"type": "mysql"}, "shared-networks": [{ "name": "net1"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "shared-networks": [{"client-class": "abc", "rebind-timer": 200, "renew-timer": 100, "valid-lifetime": 300, "reservations-global": True, "reservations-in-subnet": False, "interface": srv_msg.get_interface(), "metadata": {"server-tags": ["abc"]}, "require-client-classes": ["XYZ"], "calculate-tee-times": True, "t1-percent": 0.5, "t2-percent": 0.8, "rapid-commit": True, "name": "net1", "option-data": [{"always-send": True, "code": 7, "csv-format": True, "data": "123", "name": "preference", "space": "dhcp6"}], "relay": {"ip-addresses": []}, "user-context": {"some weird network": 55}}]}, "result": 0, "text": "IPv6 shared network 'net1' found."} def test_remote_network6_set_t1_t2(): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "calculate-tee-times": True, "t1-percent": 0.5, "t2-percent": 10, "interface": "$(SERVER_IFACE)"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'t2-percent' parameter is not a real" in response["text"] cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "calculate-tee-times": True, "t1-percent": 10, "t2-percent": 0.5, "interface": "$(SERVER_IFACE)"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'t1-percent' parameter is not a real" in response["text"] cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "calculate-tee-times": True, "t1-percent": 0.5, "t2-percent": 0.1, "interface": "$(SERVER_IFACE)"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "t1-percent: 0.5 is invalid, it must be less than t2-percent: 0.1" in response["text"] @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_network6_list_basic(channel): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd, channel=channel) cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net2", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd, channel=channel) cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net1"}, {"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "2 IPv6 shared network(s) found."} def test_remote_network6_list_no_networks(): cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "shared-networks": []}, "result": 3, "text": "0 IPv6 shared network(s) found."} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_network6_del_basic(channel): cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd, channel=channel) cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net2", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd, channel=channel) cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 2, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net1"}, {"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "2 IPv6 shared network(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "shared-networks": [{"name": "net1"}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "1 IPv6 shared network(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "shared-networks": [{"name": "net2"}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel, exp_result=3) assert response == {"arguments": {"count": 0, "shared-networks": []}, "result": 3, "text": "0 IPv6 shared network(s) found."} def test_remote_network6_del_subnet_keep(): # add networks cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net2", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net1"}, {"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "2 IPv6 shared network(s) found."} # add subnets to networks cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "net1", "pools": [{ "pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:2::/64", "id": 2, "interface": "$(SERVER_IFACE)", "shared-network-name": "net2", "pools": [{ "pool": "2001:db8:2::1-2001:db8:2::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 2, "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} # we want to have 2 subnets cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "subnets": [{"id": 1, "subnet": "2001:db8:1::/64", "shared-network-name": "net1", "metadata": {"server-tags": ["abc"]}}, {"id": 2, "subnet": "2001:db8:2::/64", "shared-network-name": "net2", "metadata": {"server-tags": ["abc"]}}]}, "result": 0, "text": "2 IPv6 subnet(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "subnets-action": "keep", "shared-networks": [{"name": "net1"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "1 IPv6 shared network(s) found."} # after deleting network we still want to have 2 subnets cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "subnets": [{"id": 1, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:1::/64"}, {"id": 2, "metadata": {"server-tags": ["abc"]}, "shared-network-name": "net2", "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "2 IPv6 subnet(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "subnets-action": "keep", "shared-networks": [{"name": "net2"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "shared-networks": []}, "result": 3, "text": "0 IPv6 shared network(s) found."} # after removing all networks we still want to have both subnets cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "subnets": [{"id": 1, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:1::/64"}, {"id": 2, "metadata": {"server-tags": ["abc"]}, "shared-network-name": None, "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "2 IPv6 subnet(s) found."} def test_remote_network6_del_subnet_delete(): # add networks cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net1", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-network6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "shared-networks": [{ "name": "net2", "interface": "$(SERVER_IFACE)"}]}) srv_msg.send_ctrl_cmd(cmd) cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net1"}, {"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "2 IPv6 shared network(s) found."} # add subnets to networks cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:1::/64", "id": 1, "interface": "$(SERVER_IFACE)", "shared-network-name": "net1", "pools": [{ "pool": "2001:db8:1::1-2001:db8:1::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 1, "subnet": "2001:db8:1::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} cmd = dict(command="remote-subnet6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "subnets": [{"subnet": "2001:db8:2::/64", "id": 2, "interface": "$(SERVER_IFACE)", "shared-network-name": "net2", "pools": [{ "pool": "2001:db8:2::1-2001:db8:2::10"}]}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"subnets": [{"id": 2, "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "IPv6 subnet successfully set."} # we want to have 2 subnets cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "subnets": [{"id": 1, "subnet": "2001:db8:1::/64", "shared-network-name": "net1", "metadata": {"server-tags": ["abc"]}}, {"id": 2, "subnet": "2001:db8:2::/64", "shared-network-name": "net2", "metadata": {"server-tags": ["abc"]}}]}, "result": 0, "text": "2 IPv6 subnet(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "subnets-action": "delete", "shared-networks": [{"name": "net1"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "shared-networks": [{"metadata": {"server-tags": ["abc"]}, "name": "net2"}]}, "result": 0, "text": "1 IPv6 shared network(s) found."} # after deleting network we still want to have 2 subnets cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "subnets": [{"id": 2, "metadata": {"server-tags": ["abc"]}, "shared-network-name": "net2", "subnet": "2001:db8:2::/64"}]}, "result": 0, "text": "1 IPv6 subnet(s) found."} cmd = dict(command="remote-network6-del", arguments={"remote": {"type": "mysql"}, "subnets-action": "delete", "shared-networks": [{"name": "net2"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 IPv6 shared network(s) deleted."} cmd = dict(command="remote-network6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "shared-networks": []}, "result": 3, "text": "0 IPv6 shared network(s) found."} # all subnets should be removed now cmd = dict(command="remote-subnet6-list", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "subnets": []}, "result": 3, "text": "0 IPv6 subnet(s) found."} def _set_global_parameter(): cmd = dict(command="remote-global-parameter6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": { "decline-probation-period": 123456}}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "parameters": {"decline-probation-period": 123456}}, "result": 0, "text": "1 DHCPv6 global parameter(s) successfully set."} # global-parameter tests def test_remote_global_parameter6_set_integer(): cmd = dict(command="remote-global-parameter6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": {"valid-lifetime": 1000}}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "parameters": {"valid-lifetime": 1000}}, "result": 0, "text": "1 DHCPv6 global parameter(s) successfully set."} def test_remote_global_parameter6_set_incorrect_parameter(): cmd = dict(command="remote-global-parameter6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": {"decline-aaa-period": 1234556}}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "unknown parameter 'decline-aaa-period'"} def test_remote_global_parameter6_del(): _set_global_parameter() cmd = dict(command="remote-global-parameter6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": ["decline-probation-period"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 global parameter(s) deleted."} def test_remote_global_parameter6_del_not_existing_parameter(): cmd = dict(command="remote-global-parameter6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": ["decline-probation-period"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 DHCPv6 global parameter(s) deleted."} def test_remote_global_parameter6_get(): _set_global_parameter() cmd = dict(command="remote-global-parameter6-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": ["decline-probation-period"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "parameters": {"decline-probation-period": 123456, "metadata": {"server-tags": ["abc"]}}}, "result": 0, "text": "'decline-probation-period' DHCPv6 global parameter found."} def test_remote_global_parameter6_get_all_one(): _set_global_parameter() cmd = dict(command="remote-global-parameter6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "parameters": [{"decline-probation-period": 123456, "metadata": {"server-tags": ["abc"]}}]}, "result": 0, "text": "1 DHCPv6 global parameter(s) found."} def test_remote_global_parameter6_get_all_multiple(): _set_global_parameter() cmd = dict(command="remote-global-parameter6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "parameters": {"calculate-tee-times": True}}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "parameters": {"calculate-tee-times": True}}, "result": 0, "text": "1 DHCPv6 global parameter(s) successfully set."} cmd = dict(command="remote-global-parameter6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response["result"] == 0 assert response["text"] == "2 DHCPv6 global parameter(s) found." assert response["arguments"]["count"] == 2 assert {"calculate-tee-times": True, "metadata": {"server-tags": ["abc"]}} in response["arguments"]["parameters"] assert {"decline-probation-period": 123456, "metadata": {"server-tags": ["abc"]}} in response["arguments"]["parameters"] def test_remote_global_parameter6_get_all_zero(): cmd = dict(command="remote-global-parameter6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "parameters": []}, "result": 3, "text": "0 DHCPv6 global parameter(s) found."} def _set_option_def(channel='http'): cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 222, "type": "uint32"}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"option-defs": [{"code": 222, "space": "dhcp6"}]}, "result": 0, "text": "DHCPv6 option definition successfully set."} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_option_def6_set_basic(channel): _set_option_def(channel) def test_remote_option_def6_set_using_zero_as_code(): cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 0, "type": "uint32"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "invalid option code '0': reserved value" in response["text"] def test_remote_option_def6_set_using_standard_code(): cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 24, "type": "uint32"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "an option with code 24 already exists in space 'dhcp6'"} def test_remote_option_def6_set_missing_parameters(): cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "code": 222, "type": "uint32", "array": False, "record-types": "", "space": "dhcp6", "encapsulate": ""}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "missing parameter 'name'" in response["text"] cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "aa", "type": "uint32", "array": False, "record-types": "", "space": "dhcp6", "encapsulate": ""}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "missing parameter 'code'" in response["text"] cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "aa", "code": 234, "array": False, "record-types": "", "space": "dhcp6", "encapsulate": ""}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "missing parameter 'type'" in response["text"] @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_option_def6_get_basic(channel): _set_option_def() cmd = dict(command="remote-option-def6-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "code": 222}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1, "option-defs": [{"array": False, "code": 222, "encapsulate": "", "name": "foo", "record-types": "", "space": "dhcp6", "metadata": {"server-tags": ["abc"]}, "type": "uint32"}]}, "result": 0, "text": "DHCPv6 option definition 222 in 'dhcp6' found."} def test_remote_option_def6_get_multiple_defs(): _set_option_def() cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 222, "type": "uint32", "space": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"option-defs": [{"code": 222, "space": "abc"}]}, "result": 0, "text": "DHCPv6 option definition successfully set."} cmd = dict(command="remote-option-def6-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "code": 222, "space": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "option-defs": [{"array": False, "code": 222, "encapsulate": "", "name": "foo", "record-types": "", "space": "abc", "metadata": {"server-tags": ["abc"]}, "type": "uint32"}]}, "result": 0, "text": "DHCPv6 option definition 222 in 'abc' found."} def test_remote_option_def6_get_missing_code(): cmd = dict(command="remote-option-def6-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'code' parameter"} def test_remote_option_def6_get_all_option_not_defined(): cmd = dict(command="remote-option-def6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "option-defs": []}, "result": 3, "text": "0 DHCPv6 option definition(s) found."} def test_remote_option_def6_get_all_multiple_defs(): _set_option_def() cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 222, "type": "uint32", "space": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"option-defs": [{"code": 222, "space": "abc"}]}, "result": 0, "text": "DHCPv6 option definition successfully set."} cmd = dict(command="remote-option-def6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "option-defs": [{"array": False, "code": 222, "encapsulate": "", "name": "foo", "record-types": "", "space": "abc", "metadata": {"server-tags": ["abc"]}, "type": "uint32"}, {"array": False, "code": 222, "encapsulate": "", "name": "foo", "record-types": "", "space": "dhcp6", "metadata": {"server-tags": ["abc"]}, "type": "uint32"}]}, "result": 0, "text": "2 DHCPv6 option definition(s) found."} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_option_def6_get_all_basic(channel): _set_option_def() cmd = dict(command="remote-option-def6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1, "option-defs": [{"array": False, "code": 222, "encapsulate": "", "metadata": {"server-tags": ["abc"]}, "name": "foo", "record-types": "", "space": "dhcp6", "type": "uint32"}]}, "result": 0, "text": "1 DHCPv6 option definition(s) found."} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_option_def6_del_basic(channel): _set_option_def() cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"code": 222}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 option definition(s) deleted."} def test_remote_option_def6_del_different_space(): _set_option_def() cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"code": 222, "space": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 DHCPv6 option definition(s) deleted."} def test_remote_option_def6_del_incorrect_code(): cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"name": 22}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'code' parameter"} cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'code' parameter"} cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"code": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "'code' parameter is not an integer"} def test_remote_option_def6_del_missing_option(): cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"code": 212}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 DHCPv6 option definition(s) deleted."} def test_remote_option_def6_del_multiple_options(): _set_option_def() cmd = dict(command="remote-option-def6-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{ "name": "foo", "code": 222, "type": "uint32", "space": "abc"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"option-defs": [{"code": 222, "space": "abc"}]}, "result": 0, "text": "DHCPv6 option definition successfully set."} cmd = dict(command="remote-option-def6-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "option-defs": [{"code": 222}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 option definition(s) deleted."} cmd = dict(command="remote-option-def6-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "option-defs": [{"array": False, "code": 222, "encapsulate": "", "metadata": {"server-tags": ["abc"]}, "name": "foo", "record-types": "", "space": "abc", "type": "uint32"}]}, "result": 0, "text": "1 DHCPv6 option definition(s) found."} def _set_global_option(channel='http'): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "code": 7, "data": "123"}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"result": 0, "text": "DHCPv6 option successfully set.", "arguments": {"options": [{"code": 7, "space": "dhcp6"}]}} @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_global_option6_global_set_basic(channel): _set_global_option(channel) def test_remote_global_option6_global_set_missing_data(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "code": 7}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "no option value specified" in response["text"] def test_remote_global_option6_global_set_name(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "name": "sip-server-dns", "data": "isc.example.com"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"options": [{"code": 21, "space": "dhcp6"}]}, "result": 0, "text": "DHCPv6 option successfully set."} def test_remote_global_option6_global_set_incorrect_code_missing_name(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "code": "aaa"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'code' parameter is not an integer" in response["text"] def test_remote_global_option6_global_set_incorrect_name_missing_code(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "name": 123}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'name' parameter is not a string" in response["text"] def test_remote_global_option6_global_set_missing_code_and_name(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "option data configuration requires one of 'code' or 'name' parameters to be specified" in response["text"] def test_remote_global_option6_global_set_incorrect_code(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": "aa", "name": "cc"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'code' parameter is not an integer" in response["text"] def test_remote_global_option6_global_set_incorrect_name(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7, "name": 7, "data": "123"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "'name' parameter is not a string" in response["text"] @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_global_option6_global_get_basic(channel): _set_global_option() cmd = dict(command="remote-option6-global-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1, "options": [{"always-send": False, "code": 7, "csv-format": True, "data": "123", "metadata": {"server-tags": ["abc"]}, "name": "preference", "space": "dhcp6"}]}, "result": 0, "text": "DHCPv6 option 7 in 'dhcp6' found."} def test_remote_global_option6_global_set_different_space(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7, "data": "123", "always-send": True, "csv-format": True, "space": "xyz"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "definition for the option 'xyz.' having code '7' does not exist" in response["text"] def test_remote_global_option6_global_set_csv_false_incorrect(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7, "data": "12Z3", "always-send": True, "csv-format": False}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "option data is not a valid string of hexadecimal digits: 12Z3" in response["text"] def test_remote_global_option6_global_set_csv_false_incorrect_hex(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7, "data": "C0000201Z", "always-send": True, "csv-format": False}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert "option data is not a valid string of hexadecimal digits: C0000201Z" in response["text"] @pytest.mark.parametrize('channel', ['socket', 'http']) def test_remote_global_option6_global_del_basic(channel): _set_global_option() cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7}]}) response = srv_msg.send_ctrl_cmd(cmd, channel=channel) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 option(s) deleted."} def test_remote_global_option6_global_del_missing_code(): cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"ab": 7}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'code' parameter"} def test_remote_global_option6_global_del_incorrect_code(): cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": "7"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "'code' parameter is not an integer"} def test_remote_global_option6_global_del_missing_option(): cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0}, "result": 3, "text": "0 DHCPv6 option(s) deleted."} def test_remote_global_option6_global_get_missing_code(): cmd = dict(command="remote-option6-global-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"ab": 6}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "missing 'code' parameter"} def test_remote_global_option6_global_get_incorrect_code(): cmd = dict(command="remote-option6-global-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": "7"}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=1) assert response == {"result": 1, "text": "'code' parameter is not an integer"} def test_remote_global_option6_global_get_missing_option(): cmd = dict(command="remote-option6-global-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 6}]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "options": []}, "result": 3, "text": "DHCPv6 option 6 in 'dhcp6' not found."} def test_remote_global_option6_global_get_csv_false(): cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 22, # in data: 1 IPv6 address encoded as 16 octets "data": "C0000301C00003020a0b0c0d0e0f0807", "always-send": True, "csv-format": False}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"result": 0, "text": "DHCPv6 option successfully set.", "arguments": {"options": [{"code": 22, "space": "dhcp6"}]}} cmd = dict(command="remote-option6-global-get", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 22}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "options": [{"always-send": True, "code": 22, "csv-format": False, "data": "C0000301C00003020A0B0C0D0E0F0807", "metadata": {"server-tags": ["abc"]}, "name": "sip-server-addr", "space": "dhcp6"}]}, "result": 0, "text": "DHCPv6 option 22 in 'dhcp6' found."} def test_remote_global_option6_global_get_all(): _set_global_option() cmd = dict(command="remote-option6-global-set", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{ "code": 22, "data": "2001:db8::2"}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"result": 0, "text": "DHCPv6 option successfully set.", "arguments": {"options": [{"code": 22, "space": "dhcp6"}]}} cmd = dict(command="remote-option6-global-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 2, "options": [{"always-send": False, "code": 7, "csv-format": True, "metadata": {"server-tags": ["abc"]}, "data": "123", "name": "preference", "space": "dhcp6"}, {"always-send": False, "code": 22, "csv-format": True, "metadata": {"server-tags": ["abc"]}, "data": "2001:db8::2", "name": "sip-server-addr", "space": "dhcp6"}]}, "result": 0, "text": "2 DHCPv6 option(s) found."} cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 7}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 option(s) deleted."} cmd = dict(command="remote-option6-global-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1, "options": [{"always-send": False, "code": 22, "csv-format": True, "data": "2001:db8::2", "name": "sip-server-addr", "metadata": {"server-tags": ["abc"]}, "space": "dhcp6"}]}, "result": 0, "text": "1 DHCPv6 option(s) found."} cmd = dict(command="remote-option6-global-del", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"], "options": [{"code": 22}]}) response = srv_msg.send_ctrl_cmd(cmd) assert response == {"arguments": {"count": 1}, "result": 0, "text": "1 DHCPv6 option(s) deleted."} cmd = dict(command="remote-option6-global-get-all", arguments={"remote": {"type": "mysql"}, "server-tags": ["abc"]}) response = srv_msg.send_ctrl_cmd(cmd, exp_result=3) assert response == {"arguments": {"count": 0, "options": []}, "result": 3, "text": "0 DHCPv6 option(s) found."}

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Python

trakt/core/components/__init__.py

jmolinski/traktpy

e6ff22acaf273b7b45070a4f8938c210fe4d63d7

[ "MIT" ]

null

trakt/core/components/__init__.py

jmolinski/traktpy

e6ff22acaf273b7b45070a4f8938c210fe4d63d7

[ "MIT" ]

1

2019-04-13T10:15:48.000Z

trakt/core/components/__init__.py

jmolinski/traktpy

e6ff22acaf273b7b45070a4f8938c210fe4d63d7

[ "MIT" ]

null

# flake8: noqa: F403 from trakt.core.components.cache import CacheManager, FrozenRequest from trakt.core.components.http_component import DefaultHttpComponent from trakt.core.components.oauth import DefaultOauthComponent

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5e9087b7af825c28d957d5ea97fd019874a1cff9

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py

Python

incapsulaminer/node.py

bilalbox/incapsula-miner

7bf8ab22ae546a8ce6734702d0bbd350bd3fe1b4

[ "Apache-2.0" ]

1

2019-05-30T18:54:28.000Z

incapsulaminer/node.py

bilalbox/incapsula-miner

7bf8ab22ae546a8ce6734702d0bbd350bd3fe1b4

[ "Apache-2.0" ]

1

2017-12-05T09:42:49.000Z

2017-12-05T09:47:01.000Z

incapsulaminer/node.py

bilalbox/incapsula-miner

7bf8ab22ae546a8ce6734702d0bbd350bd3fe1b4

[ "Apache-2.0" ]

null

from __future__ import absolute_import import logging import requests import json from minemeld.ft.basepoller import BasePollerFT LOG = logging.getLogger(__name__) class IPv4(BasePollerFT): def configure(self): super(IPv4, self).configure() self.polling_timeout = self.config.get('polling_timeout', 20) self.verify_cert = self.config.get('verify_cert', False) self.url = 'https://my.incapsula.com/api/integration/v1/ips' def _process_item(self, item): # called on each item returned by _build_iterator # it should return a list of (indicator, value) pairs if item is None: LOG.error('%s - no IP information found', self.name) return [] else: value = { 'type': 'IPv4', 'confidence': 100 } return [[item, value]] def _build_iterator(self, now): # called at every polling interval # here you should retrieve and return the list of items rkwargs = dict( stream=False, verify=self.verify_cert, timeout=self.polling_timeout, data=[('resp_format','json'),] ) r = requests.post( self.url, **rkwargs ) try: r.raise_for_status() except: LOG.debug('%s - exception in request: %s %s', self.name, r.status_code, r.content) raise # parse the results into a list return iter(json.loads(r.text)['ipRanges']) class IPv6(BasePollerFT): def configure(self): super(IPv6, self).configure() self.polling_timeout = self.config.get('polling_timeout', 20) self.verify_cert = self.config.get('verify_cert', False) self.url = 'https://my.incapsula.com/api/integration/v1/ips' def _process_item(self, item): # called on each item returned by _build_iterator # it should return a list of (indicator, value) pairs if item is None: LOG.error('%s - no IP information found', self.name) return [] else: value = { 'type': 'IPv6', 'confidence': 100 } return [[item, value]] def _build_iterator(self, now): # called at every polling interval # here you should retrieve and return the list of items rkwargs = dict( stream=False, verify=self.verify_cert, timeout=self.polling_timeout, data=[('resp_format','json'),] ) r = requests.post( self.url, **rkwargs ) try: r.raise_for_status() except: LOG.debug('%s - exception in request: %s %s', self.name, r.status_code, r.content) raise # parse the results into a list return iter(json.loads(r.text)['ipv6Ranges'])

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Python

audio_dspy/adaptive_filt.py

jatinchowdhury18/AudioDSPy

96ce0e223877cb5515f14da4f6d2ce8282d81f3c

[ "MIT" ]

37

2019-11-06T07:47:40.000Z

2022-03-07T10:50:45.000Z

audio_dspy/adaptive_filt.py

jatinchowdhury18/AudioDSPy

96ce0e223877cb5515f14da4f6d2ce8282d81f3c

[ "MIT" ]

3

2019-10-22T03:24:09.000Z

2022-01-30T00:45:21.000Z

audio_dspy/adaptive_filt.py

jatinchowdhury18/AudioDSPy

96ce0e223877cb5515f14da4f6d2ce8282d81f3c

[ "MIT" ]

3

2020-09-09T20:18:37.000Z

2022-03-17T00:48:05.000Z

import numpy as np def LMS(input, desired, mu, L): """ Performs LMS adpative filtering on input signal Parameters: input : array-like Input signa; desired : array-like Desired signal mu : float Learning rate L : int Length of adaptive filter Return: y : array-like Filtered signal e : array-like Error signal w : array-like Final filter coefficients (of length L) """ assert len(input) == len( desired), 'Desired and input signals must have equal length' N = len(input) w = np.zeros(L) y = np.zeros(N) x_win = np.zeros(L) e = np.zeros(N) for n in range(N): x_win = np.concatenate((x_win[1:L], [input[n]])) y[n] = np.dot(w, x_win) e[n] = desired[n] - y[n] w = w + mu * e[n] * x_win return y, e, w def NLMS(input, desired, mu=0.1, L=7): """ Performs Norm LMS adpative filtering on input signal Parameters: input : array-like Input signa; desired : array-like Desired signal mu : float Learning rate L : int Length of adaptive filter Return: y : array-like Filtered signal e : array-like Error signal w : array-like Final filter coefficients (of length L) """ assert len(input) == len( desired), 'Desired and input signals must have equal length' N = len(input) w = np.zeros(L) y = np.zeros(N) x_win = np.zeros(L) e = np.zeros(N) for n in range(N): x_win = np.concatenate((x_win[1:L], [input[n]])) y[n] = np.dot(w, x_win) e[n] = desired[n] - y[n] w = w + mu * e[n] * x_win / np.sqrt(np.sum(x_win**2)) return y, e, w def NL_LMS(input, desired, mu, L, g, g_prime): """ Performs Nonlinear LMS adaptive filtering on input signal Parameters: input : array-like Input signa; desired : array-like Desired signal mu : float Learning rate L : int Length of adaptive filter g : lambda (float) : float Nonlinear function, ex: tanh(x) g_prime : lambda (float) : float Derivative of nonlinear function, ex 1/cosh(x)^2 Return: y : array-like Filtered signal e : array-like Error signal w : array-like Final filter coefficients (of length L) """ assert len(input) == len( desired), 'Desired and input signals must have equal length' N = len(input) w = np.zeros(L) y = np.zeros(N) x_win = np.zeros(L) e = np.zeros(N) for n in range(N): x_win = np.concatenate((x_win[1:L], [input[n]])) y[n] = np.dot(w, x_win) e[n] = desired[n] - g(y[n]) w = w + mu * e[n] * x_win * g_prime(y[n]) return y, e, w

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py

Python

tests/unit/utils/test_platforms.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

tests/unit/utils/test_platforms.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

tests/unit/utils/test_platforms.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ tests.unit.utils.test_platforms ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tests for saltfactories.utils.platforms """ import mock import saltfactories.utils.platform def test_is_windows(): return_value = True with mock.patch("salt.utils.platform.is_windows", return_value=return_value): assert saltfactories.utils.platform.is_windows() is return_value def test_is_not_windows(): return_value = True with mock.patch("salt.utils.platform.is_windows", return_value=return_value): assert saltfactories.utils.platform.is_windows() is return_value def test_is_linux(): return_value = True with mock.patch("salt.utils.platform.is_linux", return_value=return_value): assert saltfactories.utils.platform.is_linux() is return_value def test_is_not_linux(): return_value = True with mock.patch("salt.utils.platform.is_linux", return_value=return_value): assert saltfactories.utils.platform.is_linux() is return_value def test_is_darwin(): return_value = True with mock.patch("salt.utils.platform.is_darwin", return_value=return_value): assert saltfactories.utils.platform.is_darwin() is return_value def test_is_not_darwin(): return_value = True with mock.patch("salt.utils.platform.is_darwin", return_value=return_value): assert saltfactories.utils.platform.is_darwin() is return_value def test_is_sunos(): return_value = True with mock.patch("salt.utils.platform.is_sunos", return_value=return_value): assert saltfactories.utils.platform.is_sunos() is return_value def test_is_not_sunos(): return_value = True with mock.patch("salt.utils.platform.is_sunos", return_value=return_value): assert saltfactories.utils.platform.is_sunos() is return_value def test_is_smartos(): return_value = True with mock.patch("salt.utils.platform.is_smartos", return_value=return_value): assert saltfactories.utils.platform.is_smartos() is return_value def test_is_not_smartos(): return_value = True with mock.patch("salt.utils.platform.is_smartos", return_value=return_value): assert saltfactories.utils.platform.is_smartos() is return_value def test_is_freebsd(): return_value = True with mock.patch("salt.utils.platform.is_freebsd", return_value=return_value): assert saltfactories.utils.platform.is_freebsd() is return_value def test_is_not_freebsd(): return_value = True with mock.patch("salt.utils.platform.is_freebsd", return_value=return_value): assert saltfactories.utils.platform.is_freebsd() is return_value def test_is_netbsd(): return_value = True with mock.patch("salt.utils.platform.is_netbsd", return_value=return_value): assert saltfactories.utils.platform.is_netbsd() is return_value def test_is_not_netbsd(): return_value = True with mock.patch("salt.utils.platform.is_netbsd", return_value=return_value): assert saltfactories.utils.platform.is_netbsd() is return_value def test_is_openbsd(): return_value = True with mock.patch("salt.utils.platform.is_openbsd", return_value=return_value): assert saltfactories.utils.platform.is_openbsd() is return_value def test_is_not_openbsd(): return_value = True with mock.patch("salt.utils.platform.is_openbsd", return_value=return_value): assert saltfactories.utils.platform.is_openbsd() is return_value def test_is_aix(): return_value = True with mock.patch("salt.utils.platform.is_aix", return_value=return_value): assert saltfactories.utils.platform.is_aix() is return_value def test_is_not_aix(): return_value = True with mock.patch("salt.utils.platform.is_aix", return_value=return_value): assert saltfactories.utils.platform.is_aix() is return_value

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