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454092ee1b28c156b5d51654c926c944a14e324b34eeef403ef0c07877948cad | @property
def is_suppressed(self):
'\n Gets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :return: The is_suppressed of this LogAnalyticsWarning.\n :rtype: bool\n '
return self._is_suppressed | Gets the is_suppressed of this LogAnalyticsWarning.
A flag indicating if the warning is currently suppressed
:return: The is_suppressed of this LogAnalyticsWarning.
:rtype: bool | src/oci/log_analytics/models/log_analytics_warning.py | is_suppressed | ezequielramos/oci-python-sdk | 249 | python | @property
def is_suppressed(self):
'\n Gets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :return: The is_suppressed of this LogAnalyticsWarning.\n :rtype: bool\n '
return self._is_suppressed | @property
def is_suppressed(self):
'\n Gets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :return: The is_suppressed of this LogAnalyticsWarning.\n :rtype: bool\n '
return self._is_suppressed<|docstring|>Gets the is_suppressed of this LogAnalyticsWarning.
A flag indicating if the warning is currently suppressed
:return: The is_suppressed of this LogAnalyticsWarning.
:rtype: bool<|endoftext|> |
5c862c189179ef3758431fa9f4658a83bd14c02569768459de6107a9f43145de | @is_suppressed.setter
def is_suppressed(self, is_suppressed):
'\n Sets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :param is_suppressed: The is_suppressed of this LogAnalyticsWarning.\n :type: bool\n '
self._is_suppressed = is_suppressed | Sets the is_suppressed of this LogAnalyticsWarning.
A flag indicating if the warning is currently suppressed
:param is_suppressed: The is_suppressed of this LogAnalyticsWarning.
:type: bool | src/oci/log_analytics/models/log_analytics_warning.py | is_suppressed | ezequielramos/oci-python-sdk | 249 | python | @is_suppressed.setter
def is_suppressed(self, is_suppressed):
'\n Sets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :param is_suppressed: The is_suppressed of this LogAnalyticsWarning.\n :type: bool\n '
self._is_suppressed = is_suppressed | @is_suppressed.setter
def is_suppressed(self, is_suppressed):
'\n Sets the is_suppressed of this LogAnalyticsWarning.\n A flag indicating if the warning is currently suppressed\n\n\n :param is_suppressed: The is_suppressed of this LogAnalyticsWarning.\n :type: bool\n '
self._is_suppressed = is_suppressed<|docstring|>Sets the is_suppressed of this LogAnalyticsWarning.
A flag indicating if the warning is currently suppressed
:param is_suppressed: The is_suppressed of this LogAnalyticsWarning.
:type: bool<|endoftext|> |
43ab154f3f19b412d86d95ddeafb7700069dd31b0f9d42092c56394c0d33d7cc | @property
def time_of_latest_warning(self):
'\n Gets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :return: The time_of_latest_warning of this LogAnalyticsWarning.\n :rtype: datetime\n '
return self._time_of_latest_warning | Gets the time_of_latest_warning of this LogAnalyticsWarning.
The most recent date on which the warning was triggered
:return: The time_of_latest_warning of this LogAnalyticsWarning.
:rtype: datetime | src/oci/log_analytics/models/log_analytics_warning.py | time_of_latest_warning | ezequielramos/oci-python-sdk | 249 | python | @property
def time_of_latest_warning(self):
'\n Gets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :return: The time_of_latest_warning of this LogAnalyticsWarning.\n :rtype: datetime\n '
return self._time_of_latest_warning | @property
def time_of_latest_warning(self):
'\n Gets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :return: The time_of_latest_warning of this LogAnalyticsWarning.\n :rtype: datetime\n '
return self._time_of_latest_warning<|docstring|>Gets the time_of_latest_warning of this LogAnalyticsWarning.
The most recent date on which the warning was triggered
:return: The time_of_latest_warning of this LogAnalyticsWarning.
:rtype: datetime<|endoftext|> |
64a63cea8ac49a31c0a188c8ac6a827941b43a94d241cc9828499a41b7cdef96 | @time_of_latest_warning.setter
def time_of_latest_warning(self, time_of_latest_warning):
'\n Sets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :param time_of_latest_warning: The time_of_latest_warning of this LogAnalyticsWarning.\n :type: datetime\n '
self._time_of_latest_warning = time_of_latest_warning | Sets the time_of_latest_warning of this LogAnalyticsWarning.
The most recent date on which the warning was triggered
:param time_of_latest_warning: The time_of_latest_warning of this LogAnalyticsWarning.
:type: datetime | src/oci/log_analytics/models/log_analytics_warning.py | time_of_latest_warning | ezequielramos/oci-python-sdk | 249 | python | @time_of_latest_warning.setter
def time_of_latest_warning(self, time_of_latest_warning):
'\n Sets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :param time_of_latest_warning: The time_of_latest_warning of this LogAnalyticsWarning.\n :type: datetime\n '
self._time_of_latest_warning = time_of_latest_warning | @time_of_latest_warning.setter
def time_of_latest_warning(self, time_of_latest_warning):
'\n Sets the time_of_latest_warning of this LogAnalyticsWarning.\n The most recent date on which the warning was triggered\n\n\n :param time_of_latest_warning: The time_of_latest_warning of this LogAnalyticsWarning.\n :type: datetime\n '
self._time_of_latest_warning = time_of_latest_warning<|docstring|>Sets the time_of_latest_warning of this LogAnalyticsWarning.
The most recent date on which the warning was triggered
:param time_of_latest_warning: The time_of_latest_warning of this LogAnalyticsWarning.
:type: datetime<|endoftext|> |
224a726b0fc3856e8b3f9a35e41ca5c9f4302e36d970aa5b97ef66938884c904 | @property
def warning_level(self):
'\n Gets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :return: The warning_level of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_level | Gets the warning_level of this LogAnalyticsWarning.
The warning level - either pattern, rule, or source.
:return: The warning_level of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | warning_level | ezequielramos/oci-python-sdk | 249 | python | @property
def warning_level(self):
'\n Gets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :return: The warning_level of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_level | @property
def warning_level(self):
'\n Gets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :return: The warning_level of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_level<|docstring|>Gets the warning_level of this LogAnalyticsWarning.
The warning level - either pattern, rule, or source.
:return: The warning_level of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
5ce29d7748afd48aa2bd776a2271defa034bcdeef45bec81e98cdeb45bc06e79 | @warning_level.setter
def warning_level(self, warning_level):
'\n Sets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :param warning_level: The warning_level of this LogAnalyticsWarning.\n :type: str\n '
self._warning_level = warning_level | Sets the warning_level of this LogAnalyticsWarning.
The warning level - either pattern, rule, or source.
:param warning_level: The warning_level of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | warning_level | ezequielramos/oci-python-sdk | 249 | python | @warning_level.setter
def warning_level(self, warning_level):
'\n Sets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :param warning_level: The warning_level of this LogAnalyticsWarning.\n :type: str\n '
self._warning_level = warning_level | @warning_level.setter
def warning_level(self, warning_level):
'\n Sets the warning_level of this LogAnalyticsWarning.\n The warning level - either pattern, rule, or source.\n\n\n :param warning_level: The warning_level of this LogAnalyticsWarning.\n :type: str\n '
self._warning_level = warning_level<|docstring|>Sets the warning_level of this LogAnalyticsWarning.
The warning level - either pattern, rule, or source.
:param warning_level: The warning_level of this LogAnalyticsWarning.
:type: str<|endoftext|> |
47f33b0db92c22e537bbdc6ee5eeea3c0e084398c55edfb5e8ec679fbbab847c | @property
def warning_message(self):
'\n Gets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :return: The warning_message of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_message | Gets the warning_message of this LogAnalyticsWarning.
A description of the warning intended for the consumer of the warning. It will
usually detail the cause of the warning, may suggest a remedy, and can contain any
other relevant information the consumer might find useful
:return: The warning_message of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | warning_message | ezequielramos/oci-python-sdk | 249 | python | @property
def warning_message(self):
'\n Gets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :return: The warning_message of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_message | @property
def warning_message(self):
'\n Gets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :return: The warning_message of this LogAnalyticsWarning.\n :rtype: str\n '
return self._warning_message<|docstring|>Gets the warning_message of this LogAnalyticsWarning.
A description of the warning intended for the consumer of the warning. It will
usually detail the cause of the warning, may suggest a remedy, and can contain any
other relevant information the consumer might find useful
:return: The warning_message of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
29289e13447bc1437147777752e59807cb70bd34f658f5fc0c5d0a98a3abeff0 | @warning_message.setter
def warning_message(self, warning_message):
'\n Sets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :param warning_message: The warning_message of this LogAnalyticsWarning.\n :type: str\n '
self._warning_message = warning_message | Sets the warning_message of this LogAnalyticsWarning.
A description of the warning intended for the consumer of the warning. It will
usually detail the cause of the warning, may suggest a remedy, and can contain any
other relevant information the consumer might find useful
:param warning_message: The warning_message of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | warning_message | ezequielramos/oci-python-sdk | 249 | python | @warning_message.setter
def warning_message(self, warning_message):
'\n Sets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :param warning_message: The warning_message of this LogAnalyticsWarning.\n :type: str\n '
self._warning_message = warning_message | @warning_message.setter
def warning_message(self, warning_message):
'\n Sets the warning_message of this LogAnalyticsWarning.\n A description of the warning intended for the consumer of the warning. It will\n usually detail the cause of the warning, may suggest a remedy, and can contain any\n other relevant information the consumer might find useful\n\n\n :param warning_message: The warning_message of this LogAnalyticsWarning.\n :type: str\n '
self._warning_message = warning_message<|docstring|>Sets the warning_message of this LogAnalyticsWarning.
A description of the warning intended for the consumer of the warning. It will
usually detail the cause of the warning, may suggest a remedy, and can contain any
other relevant information the consumer might find useful
:param warning_message: The warning_message of this LogAnalyticsWarning.
:type: str<|endoftext|> |
cfcfa9e2812719ef14e822f757e1d16278195ed43ea481391529a0fd4b12af09 | @property
def pattern_id(self):
'\n Gets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :return: The pattern_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_id | Gets the pattern_id of this LogAnalyticsWarning.
The unique identifier of the warning pattern
:return: The pattern_id of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | pattern_id | ezequielramos/oci-python-sdk | 249 | python | @property
def pattern_id(self):
'\n Gets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :return: The pattern_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_id | @property
def pattern_id(self):
'\n Gets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :return: The pattern_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_id<|docstring|>Gets the pattern_id of this LogAnalyticsWarning.
The unique identifier of the warning pattern
:return: The pattern_id of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
a12953f5b94307ff89d424cc9d45a7881cfc155b094e203ef109b6d054cd38ba | @pattern_id.setter
def pattern_id(self, pattern_id):
'\n Sets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :param pattern_id: The pattern_id of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_id = pattern_id | Sets the pattern_id of this LogAnalyticsWarning.
The unique identifier of the warning pattern
:param pattern_id: The pattern_id of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | pattern_id | ezequielramos/oci-python-sdk | 249 | python | @pattern_id.setter
def pattern_id(self, pattern_id):
'\n Sets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :param pattern_id: The pattern_id of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_id = pattern_id | @pattern_id.setter
def pattern_id(self, pattern_id):
'\n Sets the pattern_id of this LogAnalyticsWarning.\n The unique identifier of the warning pattern\n\n\n :param pattern_id: The pattern_id of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_id = pattern_id<|docstring|>Sets the pattern_id of this LogAnalyticsWarning.
The unique identifier of the warning pattern
:param pattern_id: The pattern_id of this LogAnalyticsWarning.
:type: str<|endoftext|> |
991b9798b456f9521880e6cfe9b3239048d3d69a98fbb1c07dab104d5c058642 | @property
def pattern_text(self):
'\n Gets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :return: The pattern_text of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_text | Gets the pattern_text of this LogAnalyticsWarning.
The text of the pattern used by the warning
:return: The pattern_text of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | pattern_text | ezequielramos/oci-python-sdk | 249 | python | @property
def pattern_text(self):
'\n Gets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :return: The pattern_text of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_text | @property
def pattern_text(self):
'\n Gets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :return: The pattern_text of this LogAnalyticsWarning.\n :rtype: str\n '
return self._pattern_text<|docstring|>Gets the pattern_text of this LogAnalyticsWarning.
The text of the pattern used by the warning
:return: The pattern_text of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
b3aa173042f5443f2214658bbd9586097b57bde5b165e092cfdac71441e8c6f4 | @pattern_text.setter
def pattern_text(self, pattern_text):
'\n Sets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :param pattern_text: The pattern_text of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_text = pattern_text | Sets the pattern_text of this LogAnalyticsWarning.
The text of the pattern used by the warning
:param pattern_text: The pattern_text of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | pattern_text | ezequielramos/oci-python-sdk | 249 | python | @pattern_text.setter
def pattern_text(self, pattern_text):
'\n Sets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :param pattern_text: The pattern_text of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_text = pattern_text | @pattern_text.setter
def pattern_text(self, pattern_text):
'\n Sets the pattern_text of this LogAnalyticsWarning.\n The text of the pattern used by the warning\n\n\n :param pattern_text: The pattern_text of this LogAnalyticsWarning.\n :type: str\n '
self._pattern_text = pattern_text<|docstring|>Sets the pattern_text of this LogAnalyticsWarning.
The text of the pattern used by the warning
:param pattern_text: The pattern_text of this LogAnalyticsWarning.
:type: str<|endoftext|> |
822af900dab0db3a20eceaa3d45805770ad910208db8f0c901c3cc5953877f6c | @property
def rule_id(self):
'\n Gets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :return: The rule_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._rule_id | Gets the rule_id of this LogAnalyticsWarning.
The unique identifier of the rule associated with the warning
:return: The rule_id of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | rule_id | ezequielramos/oci-python-sdk | 249 | python | @property
def rule_id(self):
'\n Gets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :return: The rule_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._rule_id | @property
def rule_id(self):
'\n Gets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :return: The rule_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._rule_id<|docstring|>Gets the rule_id of this LogAnalyticsWarning.
The unique identifier of the rule associated with the warning
:return: The rule_id of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
65f158af3abdd9e5429a82d693adff04475c41a37121d1cd02f48ff86278c8e3 | @rule_id.setter
def rule_id(self, rule_id):
'\n Sets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :param rule_id: The rule_id of this LogAnalyticsWarning.\n :type: str\n '
self._rule_id = rule_id | Sets the rule_id of this LogAnalyticsWarning.
The unique identifier of the rule associated with the warning
:param rule_id: The rule_id of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | rule_id | ezequielramos/oci-python-sdk | 249 | python | @rule_id.setter
def rule_id(self, rule_id):
'\n Sets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :param rule_id: The rule_id of this LogAnalyticsWarning.\n :type: str\n '
self._rule_id = rule_id | @rule_id.setter
def rule_id(self, rule_id):
'\n Sets the rule_id of this LogAnalyticsWarning.\n The unique identifier of the rule associated with the warning\n\n\n :param rule_id: The rule_id of this LogAnalyticsWarning.\n :type: str\n '
self._rule_id = rule_id<|docstring|>Sets the rule_id of this LogAnalyticsWarning.
The unique identifier of the rule associated with the warning
:param rule_id: The rule_id of this LogAnalyticsWarning.
:type: str<|endoftext|> |
092071f62ff2191f81caf8efe27adcefbd44f36dd839bec99ff326b331e88fbd | @property
def source_id(self):
'\n Gets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :return: The source_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._source_id | Gets the source_id of this LogAnalyticsWarning.
The unique identifier of the source associated with the warning
:return: The source_id of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | source_id | ezequielramos/oci-python-sdk | 249 | python | @property
def source_id(self):
'\n Gets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :return: The source_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._source_id | @property
def source_id(self):
'\n Gets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :return: The source_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._source_id<|docstring|>Gets the source_id of this LogAnalyticsWarning.
The unique identifier of the source associated with the warning
:return: The source_id of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
f30a0e3edba0159cc36840fa17db3ddce1150b4b2726358bc0c22b9708961b89 | @source_id.setter
def source_id(self, source_id):
'\n Sets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :param source_id: The source_id of this LogAnalyticsWarning.\n :type: str\n '
self._source_id = source_id | Sets the source_id of this LogAnalyticsWarning.
The unique identifier of the source associated with the warning
:param source_id: The source_id of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | source_id | ezequielramos/oci-python-sdk | 249 | python | @source_id.setter
def source_id(self, source_id):
'\n Sets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :param source_id: The source_id of this LogAnalyticsWarning.\n :type: str\n '
self._source_id = source_id | @source_id.setter
def source_id(self, source_id):
'\n Sets the source_id of this LogAnalyticsWarning.\n The unique identifier of the source associated with the warning\n\n\n :param source_id: The source_id of this LogAnalyticsWarning.\n :type: str\n '
self._source_id = source_id<|docstring|>Sets the source_id of this LogAnalyticsWarning.
The unique identifier of the source associated with the warning
:param source_id: The source_id of this LogAnalyticsWarning.
:type: str<|endoftext|> |
9ca14982bbeb1375fea051f6fdc063e17b2038d1d0911e2e64cb1f59e4874d68 | @property
def suppressed_by(self):
'\n Gets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :return: The suppressed_by of this LogAnalyticsWarning.\n :rtype: str\n '
return self._suppressed_by | Gets the suppressed_by of this LogAnalyticsWarning.
The user who suppressed the warning, or empty if the warning is not suppressed
:return: The suppressed_by of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | suppressed_by | ezequielramos/oci-python-sdk | 249 | python | @property
def suppressed_by(self):
'\n Gets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :return: The suppressed_by of this LogAnalyticsWarning.\n :rtype: str\n '
return self._suppressed_by | @property
def suppressed_by(self):
'\n Gets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :return: The suppressed_by of this LogAnalyticsWarning.\n :rtype: str\n '
return self._suppressed_by<|docstring|>Gets the suppressed_by of this LogAnalyticsWarning.
The user who suppressed the warning, or empty if the warning is not suppressed
:return: The suppressed_by of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
da9bd5002cf0198522e9922d73647462e5f536dd3c21330e183958994dda73f6 | @suppressed_by.setter
def suppressed_by(self, suppressed_by):
'\n Sets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :param suppressed_by: The suppressed_by of this LogAnalyticsWarning.\n :type: str\n '
self._suppressed_by = suppressed_by | Sets the suppressed_by of this LogAnalyticsWarning.
The user who suppressed the warning, or empty if the warning is not suppressed
:param suppressed_by: The suppressed_by of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | suppressed_by | ezequielramos/oci-python-sdk | 249 | python | @suppressed_by.setter
def suppressed_by(self, suppressed_by):
'\n Sets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :param suppressed_by: The suppressed_by of this LogAnalyticsWarning.\n :type: str\n '
self._suppressed_by = suppressed_by | @suppressed_by.setter
def suppressed_by(self, suppressed_by):
'\n Sets the suppressed_by of this LogAnalyticsWarning.\n The user who suppressed the warning, or empty if the warning is not suppressed\n\n\n :param suppressed_by: The suppressed_by of this LogAnalyticsWarning.\n :type: str\n '
self._suppressed_by = suppressed_by<|docstring|>Sets the suppressed_by of this LogAnalyticsWarning.
The user who suppressed the warning, or empty if the warning is not suppressed
:param suppressed_by: The suppressed_by of this LogAnalyticsWarning.
:type: str<|endoftext|> |
ad8fe9ade70ecd0aa536de9f2a1d362344a796485960e8d6a1289c4376b49d16 | @property
def entity_id(self):
'\n Gets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :return: The entity_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_id | Gets the entity_id of this LogAnalyticsWarning.
The unique identifier of the entity associated with the warning
:return: The entity_id of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_id | ezequielramos/oci-python-sdk | 249 | python | @property
def entity_id(self):
'\n Gets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :return: The entity_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_id | @property
def entity_id(self):
'\n Gets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :return: The entity_id of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_id<|docstring|>Gets the entity_id of this LogAnalyticsWarning.
The unique identifier of the entity associated with the warning
:return: The entity_id of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
abc77b454dfb8a71d8f1fa212e55f6bad57df3a61704d9f46a0897f92abb0961 | @entity_id.setter
def entity_id(self, entity_id):
'\n Sets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :param entity_id: The entity_id of this LogAnalyticsWarning.\n :type: str\n '
self._entity_id = entity_id | Sets the entity_id of this LogAnalyticsWarning.
The unique identifier of the entity associated with the warning
:param entity_id: The entity_id of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_id | ezequielramos/oci-python-sdk | 249 | python | @entity_id.setter
def entity_id(self, entity_id):
'\n Sets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :param entity_id: The entity_id of this LogAnalyticsWarning.\n :type: str\n '
self._entity_id = entity_id | @entity_id.setter
def entity_id(self, entity_id):
'\n Sets the entity_id of this LogAnalyticsWarning.\n The unique identifier of the entity associated with the warning\n\n\n :param entity_id: The entity_id of this LogAnalyticsWarning.\n :type: str\n '
self._entity_id = entity_id<|docstring|>Sets the entity_id of this LogAnalyticsWarning.
The unique identifier of the entity associated with the warning
:param entity_id: The entity_id of this LogAnalyticsWarning.
:type: str<|endoftext|> |
aa9059880c4c63053dd4368956554f1d0af0238fc5e2a540c230597a9bac4db6 | @property
def entity_type(self):
'\n Gets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :return: The entity_type of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type | Gets the entity_type of this LogAnalyticsWarning.
The type of the entity associated with the warning
:return: The entity_type of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_type | ezequielramos/oci-python-sdk | 249 | python | @property
def entity_type(self):
'\n Gets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :return: The entity_type of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type | @property
def entity_type(self):
'\n Gets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :return: The entity_type of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type<|docstring|>Gets the entity_type of this LogAnalyticsWarning.
The type of the entity associated with the warning
:return: The entity_type of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
a430b9210b676bfebbe7378336554541a7ab45163de33edfcb5dbc3c705a09af | @entity_type.setter
def entity_type(self, entity_type):
'\n Sets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :param entity_type: The entity_type of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type = entity_type | Sets the entity_type of this LogAnalyticsWarning.
The type of the entity associated with the warning
:param entity_type: The entity_type of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_type | ezequielramos/oci-python-sdk | 249 | python | @entity_type.setter
def entity_type(self, entity_type):
'\n Sets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :param entity_type: The entity_type of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type = entity_type | @entity_type.setter
def entity_type(self, entity_type):
'\n Sets the entity_type of this LogAnalyticsWarning.\n The type of the entity associated with the warning\n\n\n :param entity_type: The entity_type of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type = entity_type<|docstring|>Sets the entity_type of this LogAnalyticsWarning.
The type of the entity associated with the warning
:param entity_type: The entity_type of this LogAnalyticsWarning.
:type: str<|endoftext|> |
df9ea207b5d7d5954eaa9ce6eefe6a58f7fc9d7fd56d04e4566e944b6c32333d | @property
def entity_type_display_name(self):
'\n Gets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :return: The entity_type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type_display_name | Gets the entity_type_display_name of this LogAnalyticsWarning.
The display name of the entity type associated with the warning
:return: The entity_type_display_name of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_type_display_name | ezequielramos/oci-python-sdk | 249 | python | @property
def entity_type_display_name(self):
'\n Gets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :return: The entity_type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type_display_name | @property
def entity_type_display_name(self):
'\n Gets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :return: The entity_type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._entity_type_display_name<|docstring|>Gets the entity_type_display_name of this LogAnalyticsWarning.
The display name of the entity type associated with the warning
:return: The entity_type_display_name of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
f65a6f5cab238b8e0dc5acbe10743f2a45179edbb80ace8998f6c8f3fa62979d | @entity_type_display_name.setter
def entity_type_display_name(self, entity_type_display_name):
'\n Sets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :param entity_type_display_name: The entity_type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type_display_name = entity_type_display_name | Sets the entity_type_display_name of this LogAnalyticsWarning.
The display name of the entity type associated with the warning
:param entity_type_display_name: The entity_type_display_name of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | entity_type_display_name | ezequielramos/oci-python-sdk | 249 | python | @entity_type_display_name.setter
def entity_type_display_name(self, entity_type_display_name):
'\n Sets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :param entity_type_display_name: The entity_type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type_display_name = entity_type_display_name | @entity_type_display_name.setter
def entity_type_display_name(self, entity_type_display_name):
'\n Sets the entity_type_display_name of this LogAnalyticsWarning.\n The display name of the entity type associated with the warning\n\n\n :param entity_type_display_name: The entity_type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._entity_type_display_name = entity_type_display_name<|docstring|>Sets the entity_type_display_name of this LogAnalyticsWarning.
The display name of the entity type associated with the warning
:param entity_type_display_name: The entity_type_display_name of this LogAnalyticsWarning.
:type: str<|endoftext|> |
bd7d70e35bd71203da5bfb6a6d55e727542020def17ef04e8bbfc56d63eecc90 | @property
def type_display_name(self):
'\n Gets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :return: The type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_display_name | Gets the type_display_name of this LogAnalyticsWarning.
The display name of the warning type
:return: The type_display_name of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | type_display_name | ezequielramos/oci-python-sdk | 249 | python | @property
def type_display_name(self):
'\n Gets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :return: The type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_display_name | @property
def type_display_name(self):
'\n Gets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :return: The type_display_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_display_name<|docstring|>Gets the type_display_name of this LogAnalyticsWarning.
The display name of the warning type
:return: The type_display_name of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
5ad023d6b94e487077568630b845bee982c18126b3fc0b0b864c7a0efc70d672 | @type_display_name.setter
def type_display_name(self, type_display_name):
'\n Sets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :param type_display_name: The type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_display_name = type_display_name | Sets the type_display_name of this LogAnalyticsWarning.
The display name of the warning type
:param type_display_name: The type_display_name of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | type_display_name | ezequielramos/oci-python-sdk | 249 | python | @type_display_name.setter
def type_display_name(self, type_display_name):
'\n Sets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :param type_display_name: The type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_display_name = type_display_name | @type_display_name.setter
def type_display_name(self, type_display_name):
'\n Sets the type_display_name of this LogAnalyticsWarning.\n The display name of the warning type\n\n\n :param type_display_name: The type_display_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_display_name = type_display_name<|docstring|>Sets the type_display_name of this LogAnalyticsWarning.
The display name of the warning type
:param type_display_name: The type_display_name of this LogAnalyticsWarning.
:type: str<|endoftext|> |
611c6279595a0e5575cfe1ba210b6893f3168bcf6d00c3ccfab9530c8c9f16fa | @property
def type_name(self):
'\n Gets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :return: The type_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_name | Gets the type_name of this LogAnalyticsWarning.
The internal name of the warning
:return: The type_name of this LogAnalyticsWarning.
:rtype: str | src/oci/log_analytics/models/log_analytics_warning.py | type_name | ezequielramos/oci-python-sdk | 249 | python | @property
def type_name(self):
'\n Gets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :return: The type_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_name | @property
def type_name(self):
'\n Gets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :return: The type_name of this LogAnalyticsWarning.\n :rtype: str\n '
return self._type_name<|docstring|>Gets the type_name of this LogAnalyticsWarning.
The internal name of the warning
:return: The type_name of this LogAnalyticsWarning.
:rtype: str<|endoftext|> |
4ba6a03f7d935a77f738006f20db75a3ee873d8810a13a71c0791b62d38e83e9 | @type_name.setter
def type_name(self, type_name):
'\n Sets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :param type_name: The type_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_name = type_name | Sets the type_name of this LogAnalyticsWarning.
The internal name of the warning
:param type_name: The type_name of this LogAnalyticsWarning.
:type: str | src/oci/log_analytics/models/log_analytics_warning.py | type_name | ezequielramos/oci-python-sdk | 249 | python | @type_name.setter
def type_name(self, type_name):
'\n Sets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :param type_name: The type_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_name = type_name | @type_name.setter
def type_name(self, type_name):
'\n Sets the type_name of this LogAnalyticsWarning.\n The internal name of the warning\n\n\n :param type_name: The type_name of this LogAnalyticsWarning.\n :type: str\n '
self._type_name = type_name<|docstring|>Sets the type_name of this LogAnalyticsWarning.
The internal name of the warning
:param type_name: The type_name of this LogAnalyticsWarning.
:type: str<|endoftext|> |
fef39eadaac9e3a11a6b7687e17968f8b6ca5e5a6b92ab57c01d0375ec233599 | @property
def severity(self):
'\n Gets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :return: The severity of this LogAnalyticsWarning.\n :rtype: int\n '
return self._severity | Gets the severity of this LogAnalyticsWarning.
The warning severity
:return: The severity of this LogAnalyticsWarning.
:rtype: int | src/oci/log_analytics/models/log_analytics_warning.py | severity | ezequielramos/oci-python-sdk | 249 | python | @property
def severity(self):
'\n Gets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :return: The severity of this LogAnalyticsWarning.\n :rtype: int\n '
return self._severity | @property
def severity(self):
'\n Gets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :return: The severity of this LogAnalyticsWarning.\n :rtype: int\n '
return self._severity<|docstring|>Gets the severity of this LogAnalyticsWarning.
The warning severity
:return: The severity of this LogAnalyticsWarning.
:rtype: int<|endoftext|> |
8683e1629d76b2994dcfebf4f11864824b8c1aac7fc363316e0f2e8d1eeda6e0 | @severity.setter
def severity(self, severity):
'\n Sets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :param severity: The severity of this LogAnalyticsWarning.\n :type: int\n '
self._severity = severity | Sets the severity of this LogAnalyticsWarning.
The warning severity
:param severity: The severity of this LogAnalyticsWarning.
:type: int | src/oci/log_analytics/models/log_analytics_warning.py | severity | ezequielramos/oci-python-sdk | 249 | python | @severity.setter
def severity(self, severity):
'\n Sets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :param severity: The severity of this LogAnalyticsWarning.\n :type: int\n '
self._severity = severity | @severity.setter
def severity(self, severity):
'\n Sets the severity of this LogAnalyticsWarning.\n The warning severity\n\n\n :param severity: The severity of this LogAnalyticsWarning.\n :type: int\n '
self._severity = severity<|docstring|>Sets the severity of this LogAnalyticsWarning.
The warning severity
:param severity: The severity of this LogAnalyticsWarning.
:type: int<|endoftext|> |
0dc0b17d49132dd699444e782d106279b2c7bd2bffb0834bfe8ee5cd6814858c | def register(linter: PyLinter) -> None:
'Register the checker.'
linter.register_checker(HassConstructorFormatChecker(linter)) | Register the checker. | pylint/plugins/hass_constructor.py | register | orcema/core | 30,023 | python | def register(linter: PyLinter) -> None:
linter.register_checker(HassConstructorFormatChecker(linter)) | def register(linter: PyLinter) -> None:
linter.register_checker(HassConstructorFormatChecker(linter))<|docstring|>Register the checker.<|endoftext|> |
1938c4662a2a8d355c0e65df4c4709eeb56a997c4587222f724f6722d9a2f6bd | def visit_functiondef(self, node: nodes.FunctionDef) -> None:
'Called when a FunctionDef node is visited.'
if ((not node.is_method()) or (node.name != '__init__')):
return
args = node.args
annotations = ((args.posonlyargs_annotations + args.annotations) + args.kwonlyargs_annotations)[1:]
if (args.vararg is not None):
annotations.append(args.varargannotation)
if (args.kwarg is not None):
annotations.append(args.kwargannotation)
if ((not annotations) or (None in annotations)):
return
if ((not isinstance(node.returns, nodes.Const)) or (node.returns.value is not None)):
self.add_message('hass-constructor-return', node=node) | Called when a FunctionDef node is visited. | pylint/plugins/hass_constructor.py | visit_functiondef | orcema/core | 30,023 | python | def visit_functiondef(self, node: nodes.FunctionDef) -> None:
if ((not node.is_method()) or (node.name != '__init__')):
return
args = node.args
annotations = ((args.posonlyargs_annotations + args.annotations) + args.kwonlyargs_annotations)[1:]
if (args.vararg is not None):
annotations.append(args.varargannotation)
if (args.kwarg is not None):
annotations.append(args.kwargannotation)
if ((not annotations) or (None in annotations)):
return
if ((not isinstance(node.returns, nodes.Const)) or (node.returns.value is not None)):
self.add_message('hass-constructor-return', node=node) | def visit_functiondef(self, node: nodes.FunctionDef) -> None:
if ((not node.is_method()) or (node.name != '__init__')):
return
args = node.args
annotations = ((args.posonlyargs_annotations + args.annotations) + args.kwonlyargs_annotations)[1:]
if (args.vararg is not None):
annotations.append(args.varargannotation)
if (args.kwarg is not None):
annotations.append(args.kwargannotation)
if ((not annotations) or (None in annotations)):
return
if ((not isinstance(node.returns, nodes.Const)) or (node.returns.value is not None)):
self.add_message('hass-constructor-return', node=node)<|docstring|>Called when a FunctionDef node is visited.<|endoftext|> |
53b07ad8eabb960a34ddebfed0787ab87f826b67d5d96d32fa2284270f35ca18 | def test_insert(server: Eve):
'Test to ensure records can be inserted into DynamoDB\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
assert server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}]) | Test to ensure records can be inserted into DynamoDB
:param Eve server: Eve server
:raises: AssertionError | test/test_insert.py | test_insert | jlane9/eve-dynamodb | 0 | python | def test_insert(server: Eve):
'Test to ensure records can be inserted into DynamoDB\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
assert server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}]) | def test_insert(server: Eve):
'Test to ensure records can be inserted into DynamoDB\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
assert server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}])<|docstring|>Test to ensure records can be inserted into DynamoDB
:param Eve server: Eve server
:raises: AssertionError<|endoftext|> |
c5370a725fbd78808dd2fe5e76944f771214c8284bf91f7312e13e8bad9b618a | def test_duplicate_insert(server: Eve):
'Test to ensure id must remain unique\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}])
server.data.insert('actor', [{id_field: '1', 'fname': 'Kanye'}]) | Test to ensure id must remain unique
:param Eve server: Eve server
:raises: AssertionError | test/test_insert.py | test_duplicate_insert | jlane9/eve-dynamodb | 0 | python | def test_duplicate_insert(server: Eve):
'Test to ensure id must remain unique\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}])
server.data.insert('actor', [{id_field: '1', 'fname': 'Kanye'}]) | def test_duplicate_insert(server: Eve):
'Test to ensure id must remain unique\n\n :param Eve server: Eve server\n :raises: AssertionError\n '
with server.app_context():
id_field = server.config['DOMAIN']['actor']['id_field']
server.data.insert('actor', [{id_field: '1', 'fname': 'Oprah'}])
server.data.insert('actor', [{id_field: '1', 'fname': 'Kanye'}])<|docstring|>Test to ensure id must remain unique
:param Eve server: Eve server
:raises: AssertionError<|endoftext|> |
e1ff9581088552106023f21575d0661d949059d43f29b7b40dfd2b29e7e190ad | def get_performance_test_results(self, page_url: str=None, metric_names: str=None, start_date: str=None, end_date: str=None):
'\n https://docs.saucelabs.com/dev/api/performance/#get-performance-test-results\n\n Retrieves the results of performance tests run by the requesting account and returns the\n metric values for those tests.\n :param page_url: Filter results to return only tests run on a specific URL\n :param metric_names: Provide a list of specific metric values to return\n :param start_date: Filter results based on tests run on or after this date\n :param end_date: Filter results based on tests run on or before this date\n :return:\n '
params = {key: value for (key, value) in locals().items() if ((value is not None) and (key != 'self'))}
return self._valid(self._session.request('get', f'{self.__sub_host}/', params=params), Performance, 'items') | https://docs.saucelabs.com/dev/api/performance/#get-performance-test-results
Retrieves the results of performance tests run by the requesting account and returns the
metric values for those tests.
:param page_url: Filter results to return only tests run on a specific URL
:param metric_names: Provide a list of specific metric values to return
:param start_date: Filter results based on tests run on or after this date
:param end_date: Filter results based on tests run on or before this date
:return: | saucelab_api_client/base_classes/performance_api.py | get_performance_test_results | Slamnlc/saucelab-api-client | 0 | python | def get_performance_test_results(self, page_url: str=None, metric_names: str=None, start_date: str=None, end_date: str=None):
'\n https://docs.saucelabs.com/dev/api/performance/#get-performance-test-results\n\n Retrieves the results of performance tests run by the requesting account and returns the\n metric values for those tests.\n :param page_url: Filter results to return only tests run on a specific URL\n :param metric_names: Provide a list of specific metric values to return\n :param start_date: Filter results based on tests run on or after this date\n :param end_date: Filter results based on tests run on or before this date\n :return:\n '
params = {key: value for (key, value) in locals().items() if ((value is not None) and (key != 'self'))}
return self._valid(self._session.request('get', f'{self.__sub_host}/', params=params), Performance, 'items') | def get_performance_test_results(self, page_url: str=None, metric_names: str=None, start_date: str=None, end_date: str=None):
'\n https://docs.saucelabs.com/dev/api/performance/#get-performance-test-results\n\n Retrieves the results of performance tests run by the requesting account and returns the\n metric values for those tests.\n :param page_url: Filter results to return only tests run on a specific URL\n :param metric_names: Provide a list of specific metric values to return\n :param start_date: Filter results based on tests run on or after this date\n :param end_date: Filter results based on tests run on or before this date\n :return:\n '
params = {key: value for (key, value) in locals().items() if ((value is not None) and (key != 'self'))}
return self._valid(self._session.request('get', f'{self.__sub_host}/', params=params), Performance, 'items')<|docstring|>https://docs.saucelabs.com/dev/api/performance/#get-performance-test-results
Retrieves the results of performance tests run by the requesting account and returns the
metric values for those tests.
:param page_url: Filter results to return only tests run on a specific URL
:param metric_names: Provide a list of specific metric values to return
:param start_date: Filter results based on tests run on or after this date
:param end_date: Filter results based on tests run on or before this date
:return:<|endoftext|> |
81f36f98172ff5c05d9b22a18c153665997e45466cc2a00351edde07e0a59011 | def get_performance_test_results_for_test(self, job_id: str, full: bool=True):
'\n https://docs.saucelabs.com/performance/one-page/#get-performance-results-for-a-specific-test\n\n Retrieves the results of a specific performance test run by the requesting account\n :param job_id: The unique identifier of the requested test results\n :param full: Set to false to return only basic job data, excluding metric values. Defaults to true\n :return:\n '
params = {'full': full}
return self._valid(self._session.request('get', f'{self.__sub_host}/{job_id}', params=params), PerformanceJob) | https://docs.saucelabs.com/performance/one-page/#get-performance-results-for-a-specific-test
Retrieves the results of a specific performance test run by the requesting account
:param job_id: The unique identifier of the requested test results
:param full: Set to false to return only basic job data, excluding metric values. Defaults to true
:return: | saucelab_api_client/base_classes/performance_api.py | get_performance_test_results_for_test | Slamnlc/saucelab-api-client | 0 | python | def get_performance_test_results_for_test(self, job_id: str, full: bool=True):
'\n https://docs.saucelabs.com/performance/one-page/#get-performance-results-for-a-specific-test\n\n Retrieves the results of a specific performance test run by the requesting account\n :param job_id: The unique identifier of the requested test results\n :param full: Set to false to return only basic job data, excluding metric values. Defaults to true\n :return:\n '
params = {'full': full}
return self._valid(self._session.request('get', f'{self.__sub_host}/{job_id}', params=params), PerformanceJob) | def get_performance_test_results_for_test(self, job_id: str, full: bool=True):
'\n https://docs.saucelabs.com/performance/one-page/#get-performance-results-for-a-specific-test\n\n Retrieves the results of a specific performance test run by the requesting account\n :param job_id: The unique identifier of the requested test results\n :param full: Set to false to return only basic job data, excluding metric values. Defaults to true\n :return:\n '
params = {'full': full}
return self._valid(self._session.request('get', f'{self.__sub_host}/{job_id}', params=params), PerformanceJob)<|docstring|>https://docs.saucelabs.com/performance/one-page/#get-performance-results-for-a-specific-test
Retrieves the results of a specific performance test run by the requesting account
:param job_id: The unique identifier of the requested test results
:param full: Set to false to return only basic job data, excluding metric values. Defaults to true
:return:<|endoftext|> |
8d28d7602be19d3f5d722265ec6bc474bea7c63c9be56b5ff4489908f1067e31 | def main():
' MAIN! '
SW1 = NetworkDevice('172.16.63.100', 'cisco', 'cisco')
R1 = NetworkDevice('172.16.63.101', 'cisco', 'cisco')
R2 = NetworkDevice('172.16.63.102', 'cisco', 'cisco')
network_devices = [SW1, R1, R2]
for device in network_devices:
print()
device.get_device_details()
for (key, value) in device.device_details.items():
print(('%15s : %-30s' % (key, value)))
pickle.dump(network_devices, open('foo.pickle', 'wb'))
print('\n')
print('Reading objects from pickle files:')
with open('foo.pickle', 'rb') as f:
netdev_objects = pickle.load(f)
for netdev_obj in netdev_objects:
print((50 * '-'))
for (key, value) in netdev_obj.device_details.items():
print(('%15s : %-30s' % (key, value)))
print((50 * '-')) | MAIN! | week10/NetworkDevice.py | main | gerards/pynet_learning_python | 0 | python | def main():
' '
SW1 = NetworkDevice('172.16.63.100', 'cisco', 'cisco')
R1 = NetworkDevice('172.16.63.101', 'cisco', 'cisco')
R2 = NetworkDevice('172.16.63.102', 'cisco', 'cisco')
network_devices = [SW1, R1, R2]
for device in network_devices:
print()
device.get_device_details()
for (key, value) in device.device_details.items():
print(('%15s : %-30s' % (key, value)))
pickle.dump(network_devices, open('foo.pickle', 'wb'))
print('\n')
print('Reading objects from pickle files:')
with open('foo.pickle', 'rb') as f:
netdev_objects = pickle.load(f)
for netdev_obj in netdev_objects:
print((50 * '-'))
for (key, value) in netdev_obj.device_details.items():
print(('%15s : %-30s' % (key, value)))
print((50 * '-')) | def main():
' '
SW1 = NetworkDevice('172.16.63.100', 'cisco', 'cisco')
R1 = NetworkDevice('172.16.63.101', 'cisco', 'cisco')
R2 = NetworkDevice('172.16.63.102', 'cisco', 'cisco')
network_devices = [SW1, R1, R2]
for device in network_devices:
print()
device.get_device_details()
for (key, value) in device.device_details.items():
print(('%15s : %-30s' % (key, value)))
pickle.dump(network_devices, open('foo.pickle', 'wb'))
print('\n')
print('Reading objects from pickle files:')
with open('foo.pickle', 'rb') as f:
netdev_objects = pickle.load(f)
for netdev_obj in netdev_objects:
print((50 * '-'))
for (key, value) in netdev_obj.device_details.items():
print(('%15s : %-30s' % (key, value)))
print((50 * '-'))<|docstring|>MAIN!<|endoftext|> |
2e8ba65e952fc708c4cd6a96dddb8d0528add04ed0804c896b7a1d5b2e71d10b | def _connect(self, disable_paging=True):
' Setup connect to network device '
remote_conn_pre = paramiko.SSHClient()
remote_conn_pre.set_missing_host_key_policy(paramiko.AutoAddPolicy())
remote_conn_pre.connect(self.ipaddr, username=self.username, password=self.password, look_for_keys=False, allow_agent=False)
remote_conn = remote_conn_pre.invoke_shell()
if disable_paging:
remote_conn.send('terminal length 0\n')
time.sleep(1)
remote_conn.recv(1000)
return remote_conn | Setup connect to network device | week10/NetworkDevice.py | _connect | gerards/pynet_learning_python | 0 | python | def _connect(self, disable_paging=True):
' '
remote_conn_pre = paramiko.SSHClient()
remote_conn_pre.set_missing_host_key_policy(paramiko.AutoAddPolicy())
remote_conn_pre.connect(self.ipaddr, username=self.username, password=self.password, look_for_keys=False, allow_agent=False)
remote_conn = remote_conn_pre.invoke_shell()
if disable_paging:
remote_conn.send('terminal length 0\n')
time.sleep(1)
remote_conn.recv(1000)
return remote_conn | def _connect(self, disable_paging=True):
' '
remote_conn_pre = paramiko.SSHClient()
remote_conn_pre.set_missing_host_key_policy(paramiko.AutoAddPolicy())
remote_conn_pre.connect(self.ipaddr, username=self.username, password=self.password, look_for_keys=False, allow_agent=False)
remote_conn = remote_conn_pre.invoke_shell()
if disable_paging:
remote_conn.send('terminal length 0\n')
time.sleep(1)
remote_conn.recv(1000)
return remote_conn<|docstring|>Setup connect to network device<|endoftext|> |
1f1eab6d0532b9a6557acfeb0738e143611e4bfdce68d1f43a6e4970992001e1 | def send_command(self, command):
' Send command to network device and return output '
remote_conn = self._connect()
remote_conn.send((('\n' + command) + '\n'))
time.sleep(2)
output = remote_conn.recv(65535)
output = output.decode()
remote_conn.close()
return output | Send command to network device and return output | week10/NetworkDevice.py | send_command | gerards/pynet_learning_python | 0 | python | def send_command(self, command):
' '
remote_conn = self._connect()
remote_conn.send((('\n' + command) + '\n'))
time.sleep(2)
output = remote_conn.recv(65535)
output = output.decode()
remote_conn.close()
return output | def send_command(self, command):
' '
remote_conn = self._connect()
remote_conn.send((('\n' + command) + '\n'))
time.sleep(2)
output = remote_conn.recv(65535)
output = output.decode()
remote_conn.close()
return output<|docstring|>Send command to network device and return output<|endoftext|> |
cb5d72a2ef8893356949a88d182d24e3f2124447315d47ceb08038b0bc5ee9f3 | def get_device_details(self):
' Return device details pulled from show version '
show_version = self.send_command('show version')
show_version_lines = show_version.split('\n')
for line in show_version_lines:
if ('Cisco IOS Software' in line):
vendor_line = line.split(', ')
self.device_details['vendor'] = vendor_line[0].split()[0]
self.device_details['model'] = vendor_line[1].split()[0]
self.device_details['os_version'] = vendor_line[2].split()[1]
if (' uptime is ' in line):
(self.device_details['hostname'], uptime_line) = line.split(' uptime is ')
uptime_line = uptime_line.split(', ')
seconds_per_minute = 60
seconds_per_hour = (60 * seconds_per_minute)
seconds_per_day = (24 * seconds_per_hour)
seconds_per_week = (7 * seconds_per_day)
seconds_per_year = (52 * seconds_per_week)
for time_period in uptime_line:
if ('year' in time_period):
self.device_details['uptime'] = (seconds_per_year * int(time_period.split()[0]))
if ('week' in time_period):
self.device_details['uptime'] += (seconds_per_week * int(time_period.split()[0]))
if ('day' in time_period):
self.device_details['uptime'] += (seconds_per_day * int(time_period.split()[0]))
if ('hour' in time_period):
self.device_details['uptime'] += (seconds_per_hour * int(time_period.split()[0]))
if ('minute' in time_period):
self.device_details['uptime'] += (seconds_per_minute * int(time_period.split()[0]))
if ('Processor board ID ' in line):
serial_line = line.split('Processor board ID ')
self.device_details['serial_number'] = serial_line[1].strip()
return self.device_details | Return device details pulled from show version | week10/NetworkDevice.py | get_device_details | gerards/pynet_learning_python | 0 | python | def get_device_details(self):
' '
show_version = self.send_command('show version')
show_version_lines = show_version.split('\n')
for line in show_version_lines:
if ('Cisco IOS Software' in line):
vendor_line = line.split(', ')
self.device_details['vendor'] = vendor_line[0].split()[0]
self.device_details['model'] = vendor_line[1].split()[0]
self.device_details['os_version'] = vendor_line[2].split()[1]
if (' uptime is ' in line):
(self.device_details['hostname'], uptime_line) = line.split(' uptime is ')
uptime_line = uptime_line.split(', ')
seconds_per_minute = 60
seconds_per_hour = (60 * seconds_per_minute)
seconds_per_day = (24 * seconds_per_hour)
seconds_per_week = (7 * seconds_per_day)
seconds_per_year = (52 * seconds_per_week)
for time_period in uptime_line:
if ('year' in time_period):
self.device_details['uptime'] = (seconds_per_year * int(time_period.split()[0]))
if ('week' in time_period):
self.device_details['uptime'] += (seconds_per_week * int(time_period.split()[0]))
if ('day' in time_period):
self.device_details['uptime'] += (seconds_per_day * int(time_period.split()[0]))
if ('hour' in time_period):
self.device_details['uptime'] += (seconds_per_hour * int(time_period.split()[0]))
if ('minute' in time_period):
self.device_details['uptime'] += (seconds_per_minute * int(time_period.split()[0]))
if ('Processor board ID ' in line):
serial_line = line.split('Processor board ID ')
self.device_details['serial_number'] = serial_line[1].strip()
return self.device_details | def get_device_details(self):
' '
show_version = self.send_command('show version')
show_version_lines = show_version.split('\n')
for line in show_version_lines:
if ('Cisco IOS Software' in line):
vendor_line = line.split(', ')
self.device_details['vendor'] = vendor_line[0].split()[0]
self.device_details['model'] = vendor_line[1].split()[0]
self.device_details['os_version'] = vendor_line[2].split()[1]
if (' uptime is ' in line):
(self.device_details['hostname'], uptime_line) = line.split(' uptime is ')
uptime_line = uptime_line.split(', ')
seconds_per_minute = 60
seconds_per_hour = (60 * seconds_per_minute)
seconds_per_day = (24 * seconds_per_hour)
seconds_per_week = (7 * seconds_per_day)
seconds_per_year = (52 * seconds_per_week)
for time_period in uptime_line:
if ('year' in time_period):
self.device_details['uptime'] = (seconds_per_year * int(time_period.split()[0]))
if ('week' in time_period):
self.device_details['uptime'] += (seconds_per_week * int(time_period.split()[0]))
if ('day' in time_period):
self.device_details['uptime'] += (seconds_per_day * int(time_period.split()[0]))
if ('hour' in time_period):
self.device_details['uptime'] += (seconds_per_hour * int(time_period.split()[0]))
if ('minute' in time_period):
self.device_details['uptime'] += (seconds_per_minute * int(time_period.split()[0]))
if ('Processor board ID ' in line):
serial_line = line.split('Processor board ID ')
self.device_details['serial_number'] = serial_line[1].strip()
return self.device_details<|docstring|>Return device details pulled from show version<|endoftext|> |
92f2aaab1106c6f2ede4d7b6e3fd5dd15939afe98150a46b4884ba72012372ba | def __init__(self, phantom_model: str, phantom_dim: PhantomDimensions, human_mesh: Optional[str]=None):
'Create the phantom of choice.\n\n Parameters\n ----------\n phantom_model : str\n Type of phantom to create. Valid selections are \'plane\',\n \'cylinder\', \'human\', "table" an "pad".\n phantom_dim : PhantomDimensions\n instance of class PhantomDimensions containing dimensions for\n all phantoms models except human phantoms: Length, width, radius,\n thickness etc.\n human_mesh : str, optional\n Choose which human mesh phantom to use. Valid selection are names\n of the *.stl-files in the phantom_data folder (The default is none.\n\n Raises\n ------\n ValueError\n Raises value error if unsupported phantom type are selected,\n or if phantom_model=\'human\' selected, without specifying\n human_mesh\n\n '
self.phantom_model = phantom_model.lower()
if (self.phantom_model not in VALID_PHANTOM_MODELS):
raise ValueError(f"Unknown phantom model selected. Valid type:{'.'.join(VALID_PHANTOM_MODELS)}")
self.r_ref: np.array
self.table_length = phantom_dim.table_length
if (phantom_model == 'plane'):
if (phantom_dim.plane_resolution.lower() == 'dense'):
res_length = res_width = 2.0
elif (phantom_dim.plane_resolution.lower() == 'sparse'):
res_length = res_width = 1.0
x = np.linspace(((- phantom_dim.plane_width) / 2), ((+ phantom_dim.plane_width) / 2), ((res_width * phantom_dim.plane_width) + 1))
y = np.linspace(0, phantom_dim.plane_length, (res_length * phantom_dim.plane_length))
(x_plane, y_plane) = np.meshgrid(x, y)
t = phantom_dim.plane_width
i2: List[int] = []
i1 = j1 = k1 = i2
for i in range((len(x) - 1)):
for j in range((len(y) - 1)):
i1 = (i1 + [((j * len(x)) + i)])
j1 = (j1 + [(((j * len(x)) + i) + 1)])
k1 = (k1 + [(((j * len(x)) + i) + len(x))])
i2 = (i2 + [((((j * len(x)) + i) + len(x)) + 1)])
self.r = np.column_stack((x_plane.ravel(), y_plane.ravel(), np.zeros(len(x_plane.ravel()))))
self.ijk = np.column_stack(((i1 + i2), (j1 + k1), (k1 + j1)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'cylinder'):
if (phantom_dim.cylinder_resolution.lower() == 'dense'):
res_length = 4
res_width = 0.05
elif (phantom_dim.cylinder_resolution.lower() == 'sparse'):
res_length = 1.0
res_width = 0.1
t = np.arange((0 * np.pi), (2 * np.pi), res_width)
x = (phantom_dim.cylinder_radii_a * np.cos(t)).tolist()
z = (phantom_dim.cylinder_radii_b * np.sin(t)).tolist()
nx = (np.cos(t) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
ny = np.zeros(len(t))
nz = ((2 * np.sin(t)) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
nx = nx.tolist()
ny = ny.tolist()
nz = nz.tolist()
n = [[nx[ind], ny[ind], nz[ind]] for ind in range(len(t))]
output: Dict = dict(n=[], x=[], y=[], z=[])
for index in range(0, (int(res_length) * (phantom_dim.cylinder_length + 2)), 1):
output['x'] = (output['x'] + x)
output['y'] = (output['y'] + ([((1 / res_length) * index)] * len(x)))
output['z'] = (output['z'] + z)
output['n'] = (output['n'] + n)
i1 = list(range(0, (len(output['x']) - len(t))))
j1 = list(range(1, ((len(output['x']) - len(t)) + 1)))
k1 = list(range(len(t), len(output['x'])))
i2 = list(range(0, (len(output['x']) - len(t))))
k2 = list(range((len(t) - 1), (len(output['x']) - 1)))
j2 = list(range(len(t), len(output['x'])))
self.r = np.column_stack((output['x'], output['y'], output['z']))
self.ijk = np.column_stack(((i1 + i2), (j1 + j2), (k1 + k2)))
self.dose = np.zeros(len(self.r))
self.n = np.asarray(output['n'])
elif (phantom_model == 'human'):
if (human_mesh is None):
raise ValueError('Human model needs to be specified forphantom_model = "human"')
phantom_path = os.path.join(os.path.dirname(__file__), 'phantom_data', f'{human_mesh}.stl')
phantom_mesh = mesh.Mesh.from_file(phantom_path)
r = phantom_mesh.vectors
n = phantom_mesh.normals
self.r = np.asarray([el for el_list in r for el in el_list])
self.n = np.asarray([x for pair in zip(n, n, n) for x in pair])
self.ijk = np.column_stack((np.arange(0, (len(self.r) - 3), 3), np.arange(1, (len(self.r) - 2), 3), np.arange(2, (len(self.r) - 1), 3)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'table'):
x_tab = [(index * phantom_dim.table_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_tab = [(index * phantom_dim.table_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_tab = [(index * phantom_dim.table_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1)]]
i_tab = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_tab = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_tab = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_tab, y_tab, z_tab))
self.ijk = np.column_stack((i_tab, j_tab, k_tab))
elif (phantom_model == 'pad'):
x_pad = [(index * phantom_dim.pad_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_pad = [(index * phantom_dim.pad_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_pad = [(index * phantom_dim.pad_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1]]
i_pad = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_pad = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_pad = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_pad, y_pad, z_pad))
self.ijk = np.column_stack((i_pad, j_pad, k_pad)) | Create the phantom of choice.
Parameters
----------
phantom_model : str
Type of phantom to create. Valid selections are 'plane',
'cylinder', 'human', "table" an "pad".
phantom_dim : PhantomDimensions
instance of class PhantomDimensions containing dimensions for
all phantoms models except human phantoms: Length, width, radius,
thickness etc.
human_mesh : str, optional
Choose which human mesh phantom to use. Valid selection are names
of the *.stl-files in the phantom_data folder (The default is none.
Raises
------
ValueError
Raises value error if unsupported phantom type are selected,
or if phantom_model='human' selected, without specifying
human_mesh | src/pyskindose/phantom_class.py | __init__ | notZaki/PySkinDose | 0 | python | def __init__(self, phantom_model: str, phantom_dim: PhantomDimensions, human_mesh: Optional[str]=None):
'Create the phantom of choice.\n\n Parameters\n ----------\n phantom_model : str\n Type of phantom to create. Valid selections are \'plane\',\n \'cylinder\', \'human\', "table" an "pad".\n phantom_dim : PhantomDimensions\n instance of class PhantomDimensions containing dimensions for\n all phantoms models except human phantoms: Length, width, radius,\n thickness etc.\n human_mesh : str, optional\n Choose which human mesh phantom to use. Valid selection are names\n of the *.stl-files in the phantom_data folder (The default is none.\n\n Raises\n ------\n ValueError\n Raises value error if unsupported phantom type are selected,\n or if phantom_model=\'human\' selected, without specifying\n human_mesh\n\n '
self.phantom_model = phantom_model.lower()
if (self.phantom_model not in VALID_PHANTOM_MODELS):
raise ValueError(f"Unknown phantom model selected. Valid type:{'.'.join(VALID_PHANTOM_MODELS)}")
self.r_ref: np.array
self.table_length = phantom_dim.table_length
if (phantom_model == 'plane'):
if (phantom_dim.plane_resolution.lower() == 'dense'):
res_length = res_width = 2.0
elif (phantom_dim.plane_resolution.lower() == 'sparse'):
res_length = res_width = 1.0
x = np.linspace(((- phantom_dim.plane_width) / 2), ((+ phantom_dim.plane_width) / 2), ((res_width * phantom_dim.plane_width) + 1))
y = np.linspace(0, phantom_dim.plane_length, (res_length * phantom_dim.plane_length))
(x_plane, y_plane) = np.meshgrid(x, y)
t = phantom_dim.plane_width
i2: List[int] = []
i1 = j1 = k1 = i2
for i in range((len(x) - 1)):
for j in range((len(y) - 1)):
i1 = (i1 + [((j * len(x)) + i)])
j1 = (j1 + [(((j * len(x)) + i) + 1)])
k1 = (k1 + [(((j * len(x)) + i) + len(x))])
i2 = (i2 + [((((j * len(x)) + i) + len(x)) + 1)])
self.r = np.column_stack((x_plane.ravel(), y_plane.ravel(), np.zeros(len(x_plane.ravel()))))
self.ijk = np.column_stack(((i1 + i2), (j1 + k1), (k1 + j1)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'cylinder'):
if (phantom_dim.cylinder_resolution.lower() == 'dense'):
res_length = 4
res_width = 0.05
elif (phantom_dim.cylinder_resolution.lower() == 'sparse'):
res_length = 1.0
res_width = 0.1
t = np.arange((0 * np.pi), (2 * np.pi), res_width)
x = (phantom_dim.cylinder_radii_a * np.cos(t)).tolist()
z = (phantom_dim.cylinder_radii_b * np.sin(t)).tolist()
nx = (np.cos(t) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
ny = np.zeros(len(t))
nz = ((2 * np.sin(t)) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
nx = nx.tolist()
ny = ny.tolist()
nz = nz.tolist()
n = [[nx[ind], ny[ind], nz[ind]] for ind in range(len(t))]
output: Dict = dict(n=[], x=[], y=[], z=[])
for index in range(0, (int(res_length) * (phantom_dim.cylinder_length + 2)), 1):
output['x'] = (output['x'] + x)
output['y'] = (output['y'] + ([((1 / res_length) * index)] * len(x)))
output['z'] = (output['z'] + z)
output['n'] = (output['n'] + n)
i1 = list(range(0, (len(output['x']) - len(t))))
j1 = list(range(1, ((len(output['x']) - len(t)) + 1)))
k1 = list(range(len(t), len(output['x'])))
i2 = list(range(0, (len(output['x']) - len(t))))
k2 = list(range((len(t) - 1), (len(output['x']) - 1)))
j2 = list(range(len(t), len(output['x'])))
self.r = np.column_stack((output['x'], output['y'], output['z']))
self.ijk = np.column_stack(((i1 + i2), (j1 + j2), (k1 + k2)))
self.dose = np.zeros(len(self.r))
self.n = np.asarray(output['n'])
elif (phantom_model == 'human'):
if (human_mesh is None):
raise ValueError('Human model needs to be specified forphantom_model = "human"')
phantom_path = os.path.join(os.path.dirname(__file__), 'phantom_data', f'{human_mesh}.stl')
phantom_mesh = mesh.Mesh.from_file(phantom_path)
r = phantom_mesh.vectors
n = phantom_mesh.normals
self.r = np.asarray([el for el_list in r for el in el_list])
self.n = np.asarray([x for pair in zip(n, n, n) for x in pair])
self.ijk = np.column_stack((np.arange(0, (len(self.r) - 3), 3), np.arange(1, (len(self.r) - 2), 3), np.arange(2, (len(self.r) - 1), 3)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'table'):
x_tab = [(index * phantom_dim.table_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_tab = [(index * phantom_dim.table_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_tab = [(index * phantom_dim.table_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1)]]
i_tab = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_tab = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_tab = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_tab, y_tab, z_tab))
self.ijk = np.column_stack((i_tab, j_tab, k_tab))
elif (phantom_model == 'pad'):
x_pad = [(index * phantom_dim.pad_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_pad = [(index * phantom_dim.pad_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_pad = [(index * phantom_dim.pad_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1]]
i_pad = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_pad = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_pad = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_pad, y_pad, z_pad))
self.ijk = np.column_stack((i_pad, j_pad, k_pad)) | def __init__(self, phantom_model: str, phantom_dim: PhantomDimensions, human_mesh: Optional[str]=None):
'Create the phantom of choice.\n\n Parameters\n ----------\n phantom_model : str\n Type of phantom to create. Valid selections are \'plane\',\n \'cylinder\', \'human\', "table" an "pad".\n phantom_dim : PhantomDimensions\n instance of class PhantomDimensions containing dimensions for\n all phantoms models except human phantoms: Length, width, radius,\n thickness etc.\n human_mesh : str, optional\n Choose which human mesh phantom to use. Valid selection are names\n of the *.stl-files in the phantom_data folder (The default is none.\n\n Raises\n ------\n ValueError\n Raises value error if unsupported phantom type are selected,\n or if phantom_model=\'human\' selected, without specifying\n human_mesh\n\n '
self.phantom_model = phantom_model.lower()
if (self.phantom_model not in VALID_PHANTOM_MODELS):
raise ValueError(f"Unknown phantom model selected. Valid type:{'.'.join(VALID_PHANTOM_MODELS)}")
self.r_ref: np.array
self.table_length = phantom_dim.table_length
if (phantom_model == 'plane'):
if (phantom_dim.plane_resolution.lower() == 'dense'):
res_length = res_width = 2.0
elif (phantom_dim.plane_resolution.lower() == 'sparse'):
res_length = res_width = 1.0
x = np.linspace(((- phantom_dim.plane_width) / 2), ((+ phantom_dim.plane_width) / 2), ((res_width * phantom_dim.plane_width) + 1))
y = np.linspace(0, phantom_dim.plane_length, (res_length * phantom_dim.plane_length))
(x_plane, y_plane) = np.meshgrid(x, y)
t = phantom_dim.plane_width
i2: List[int] = []
i1 = j1 = k1 = i2
for i in range((len(x) - 1)):
for j in range((len(y) - 1)):
i1 = (i1 + [((j * len(x)) + i)])
j1 = (j1 + [(((j * len(x)) + i) + 1)])
k1 = (k1 + [(((j * len(x)) + i) + len(x))])
i2 = (i2 + [((((j * len(x)) + i) + len(x)) + 1)])
self.r = np.column_stack((x_plane.ravel(), y_plane.ravel(), np.zeros(len(x_plane.ravel()))))
self.ijk = np.column_stack(((i1 + i2), (j1 + k1), (k1 + j1)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'cylinder'):
if (phantom_dim.cylinder_resolution.lower() == 'dense'):
res_length = 4
res_width = 0.05
elif (phantom_dim.cylinder_resolution.lower() == 'sparse'):
res_length = 1.0
res_width = 0.1
t = np.arange((0 * np.pi), (2 * np.pi), res_width)
x = (phantom_dim.cylinder_radii_a * np.cos(t)).tolist()
z = (phantom_dim.cylinder_radii_b * np.sin(t)).tolist()
nx = (np.cos(t) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
ny = np.zeros(len(t))
nz = ((2 * np.sin(t)) / np.sqrt(np.square((np.cos(t) + (4 * np.square(np.sin(t)))))))
nx = nx.tolist()
ny = ny.tolist()
nz = nz.tolist()
n = [[nx[ind], ny[ind], nz[ind]] for ind in range(len(t))]
output: Dict = dict(n=[], x=[], y=[], z=[])
for index in range(0, (int(res_length) * (phantom_dim.cylinder_length + 2)), 1):
output['x'] = (output['x'] + x)
output['y'] = (output['y'] + ([((1 / res_length) * index)] * len(x)))
output['z'] = (output['z'] + z)
output['n'] = (output['n'] + n)
i1 = list(range(0, (len(output['x']) - len(t))))
j1 = list(range(1, ((len(output['x']) - len(t)) + 1)))
k1 = list(range(len(t), len(output['x'])))
i2 = list(range(0, (len(output['x']) - len(t))))
k2 = list(range((len(t) - 1), (len(output['x']) - 1)))
j2 = list(range(len(t), len(output['x'])))
self.r = np.column_stack((output['x'], output['y'], output['z']))
self.ijk = np.column_stack(((i1 + i2), (j1 + j2), (k1 + k2)))
self.dose = np.zeros(len(self.r))
self.n = np.asarray(output['n'])
elif (phantom_model == 'human'):
if (human_mesh is None):
raise ValueError('Human model needs to be specified forphantom_model = "human"')
phantom_path = os.path.join(os.path.dirname(__file__), 'phantom_data', f'{human_mesh}.stl')
phantom_mesh = mesh.Mesh.from_file(phantom_path)
r = phantom_mesh.vectors
n = phantom_mesh.normals
self.r = np.asarray([el for el_list in r for el in el_list])
self.n = np.asarray([x for pair in zip(n, n, n) for x in pair])
self.ijk = np.column_stack((np.arange(0, (len(self.r) - 3), 3), np.arange(1, (len(self.r) - 2), 3), np.arange(2, (len(self.r) - 1), 3)))
self.dose = np.zeros(len(self.r))
elif (phantom_model == 'table'):
x_tab = [(index * phantom_dim.table_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_tab = [(index * phantom_dim.table_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_tab = [(index * phantom_dim.table_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1), (- 1)]]
i_tab = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_tab = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_tab = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_tab, y_tab, z_tab))
self.ijk = np.column_stack((i_tab, j_tab, k_tab))
elif (phantom_model == 'pad'):
x_pad = [(index * phantom_dim.pad_width) for index in [0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5, 0.5, 0.25, 0.25, (- 0.25), (- 0.25), (- 0.5), (- 0.5), 0.5]]
y_pad = [(index * phantom_dim.pad_length) for index in [1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0, 1.0, 1.0, 1, 1, 1.0, 1.0, 0, 0]]
z_pad = [(index * phantom_dim.pad_thickness) for index in [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1]]
i_pad = [0, 0, 1, 1, 8, 8, 9, 9, 0, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7]
j_pad = [5, 6, 2, 3, 13, 14, 10, 11, 7, 15, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15]
k_pad = [6, 7, 3, 4, 14, 15, 11, 12, 8, 8, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14]
self.r = np.column_stack((x_pad, y_pad, z_pad))
self.ijk = np.column_stack((i_pad, j_pad, k_pad))<|docstring|>Create the phantom of choice.
Parameters
----------
phantom_model : str
Type of phantom to create. Valid selections are 'plane',
'cylinder', 'human', "table" an "pad".
phantom_dim : PhantomDimensions
instance of class PhantomDimensions containing dimensions for
all phantoms models except human phantoms: Length, width, radius,
thickness etc.
human_mesh : str, optional
Choose which human mesh phantom to use. Valid selection are names
of the *.stl-files in the phantom_data folder (The default is none.
Raises
------
ValueError
Raises value error if unsupported phantom type are selected,
or if phantom_model='human' selected, without specifying
human_mesh<|endoftext|> |
dd7814745a7bafa28c94ea7048e64b266191675db3065cf0ab1bee0f612c24ea | def rotate(self, angles: List[int]) -> None:
'Rotate the phantom about the angles specified in rotation.\n\n Parameters\n ----------\n angles: List[int]\n list of angles in degrees the phantom should be rotated about,\n given as [x_rot: <int>, y_rot: <int>, z_rot: <int>]. E.g.\n rotation = [0, 90, 0] will rotate the phantom 90 degrees about the\n y-axis.\n\n '
angles = np.deg2rad(angles)
x_rot = angles[0]
y_rot = angles[1]
z_rot = angles[2]
Rx = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(x_rot)), (- np.sin(x_rot))], [(+ 0), (+ np.sin(x_rot)), (+ np.cos(x_rot))]])
Ry = np.array([[(+ np.cos(y_rot)), (+ 0), (+ np.sin(y_rot))], [(+ 0), (+ 1), (+ 0)], [(- np.sin(y_rot)), (+ 0), (+ np.cos(y_rot))]])
Rz = np.array([[(+ np.cos(z_rot)), (- np.sin(z_rot)), (+ 0)], [(+ np.sin(z_rot)), (+ np.cos(z_rot)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.r.T))).T
if (self.phantom_model in ['cylinder', 'human']):
self.n = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.n.T))).T | Rotate the phantom about the angles specified in rotation.
Parameters
----------
angles: List[int]
list of angles in degrees the phantom should be rotated about,
given as [x_rot: <int>, y_rot: <int>, z_rot: <int>]. E.g.
rotation = [0, 90, 0] will rotate the phantom 90 degrees about the
y-axis. | src/pyskindose/phantom_class.py | rotate | notZaki/PySkinDose | 0 | python | def rotate(self, angles: List[int]) -> None:
'Rotate the phantom about the angles specified in rotation.\n\n Parameters\n ----------\n angles: List[int]\n list of angles in degrees the phantom should be rotated about,\n given as [x_rot: <int>, y_rot: <int>, z_rot: <int>]. E.g.\n rotation = [0, 90, 0] will rotate the phantom 90 degrees about the\n y-axis.\n\n '
angles = np.deg2rad(angles)
x_rot = angles[0]
y_rot = angles[1]
z_rot = angles[2]
Rx = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(x_rot)), (- np.sin(x_rot))], [(+ 0), (+ np.sin(x_rot)), (+ np.cos(x_rot))]])
Ry = np.array([[(+ np.cos(y_rot)), (+ 0), (+ np.sin(y_rot))], [(+ 0), (+ 1), (+ 0)], [(- np.sin(y_rot)), (+ 0), (+ np.cos(y_rot))]])
Rz = np.array([[(+ np.cos(z_rot)), (- np.sin(z_rot)), (+ 0)], [(+ np.sin(z_rot)), (+ np.cos(z_rot)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.r.T))).T
if (self.phantom_model in ['cylinder', 'human']):
self.n = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.n.T))).T | def rotate(self, angles: List[int]) -> None:
'Rotate the phantom about the angles specified in rotation.\n\n Parameters\n ----------\n angles: List[int]\n list of angles in degrees the phantom should be rotated about,\n given as [x_rot: <int>, y_rot: <int>, z_rot: <int>]. E.g.\n rotation = [0, 90, 0] will rotate the phantom 90 degrees about the\n y-axis.\n\n '
angles = np.deg2rad(angles)
x_rot = angles[0]
y_rot = angles[1]
z_rot = angles[2]
Rx = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(x_rot)), (- np.sin(x_rot))], [(+ 0), (+ np.sin(x_rot)), (+ np.cos(x_rot))]])
Ry = np.array([[(+ np.cos(y_rot)), (+ 0), (+ np.sin(y_rot))], [(+ 0), (+ 1), (+ 0)], [(- np.sin(y_rot)), (+ 0), (+ np.cos(y_rot))]])
Rz = np.array([[(+ np.cos(z_rot)), (- np.sin(z_rot)), (+ 0)], [(+ np.sin(z_rot)), (+ np.cos(z_rot)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.r.T))).T
if (self.phantom_model in ['cylinder', 'human']):
self.n = np.matmul(Rx, np.matmul(Ry, np.matmul(Rz, self.n.T))).T<|docstring|>Rotate the phantom about the angles specified in rotation.
Parameters
----------
angles: List[int]
list of angles in degrees the phantom should be rotated about,
given as [x_rot: <int>, y_rot: <int>, z_rot: <int>]. E.g.
rotation = [0, 90, 0] will rotate the phantom 90 degrees about the
y-axis.<|endoftext|> |
17470644cfc134ba6ae9c8d369650e36db5d53194d85da167066a647ac503e6c | def translate(self, dr: List[int]) -> None:
'Translate the phantom in the x, y or z direction.\n\n Parameters\n ----------\n dr : List[int]\n list of distances the phantom should be translated, given in cm.\n Specified as dr = [dx: <int>, dy: <int>, dz: <int>]. E.g.\n dr = [0, 0, 10] will translate the phantom 10 cm in the z direction\n\n '
self.r[(:, 0)] += dr[0]
self.r[(:, 1)] += dr[1]
self.r[(:, 2)] += dr[2] | Translate the phantom in the x, y or z direction.
Parameters
----------
dr : List[int]
list of distances the phantom should be translated, given in cm.
Specified as dr = [dx: <int>, dy: <int>, dz: <int>]. E.g.
dr = [0, 0, 10] will translate the phantom 10 cm in the z direction | src/pyskindose/phantom_class.py | translate | notZaki/PySkinDose | 0 | python | def translate(self, dr: List[int]) -> None:
'Translate the phantom in the x, y or z direction.\n\n Parameters\n ----------\n dr : List[int]\n list of distances the phantom should be translated, given in cm.\n Specified as dr = [dx: <int>, dy: <int>, dz: <int>]. E.g.\n dr = [0, 0, 10] will translate the phantom 10 cm in the z direction\n\n '
self.r[(:, 0)] += dr[0]
self.r[(:, 1)] += dr[1]
self.r[(:, 2)] += dr[2] | def translate(self, dr: List[int]) -> None:
'Translate the phantom in the x, y or z direction.\n\n Parameters\n ----------\n dr : List[int]\n list of distances the phantom should be translated, given in cm.\n Specified as dr = [dx: <int>, dy: <int>, dz: <int>]. E.g.\n dr = [0, 0, 10] will translate the phantom 10 cm in the z direction\n\n '
self.r[(:, 0)] += dr[0]
self.r[(:, 1)] += dr[1]
self.r[(:, 2)] += dr[2]<|docstring|>Translate the phantom in the x, y or z direction.
Parameters
----------
dr : List[int]
list of distances the phantom should be translated, given in cm.
Specified as dr = [dx: <int>, dy: <int>, dz: <int>]. E.g.
dr = [0, 0, 10] will translate the phantom 10 cm in the z direction<|endoftext|> |
44fdc1119a5ecc365bf8ed89a3f76611d487207565f2884b13b575511819a952 | def save_position(self) -> None:
'Store a reference position of the phantom.\n\n This function is supposed to be used to store the patient fixation\n conducted in the function position_geometry\n\n '
r_ref = copy.copy(self.r)
self.r_ref = r_ref | Store a reference position of the phantom.
This function is supposed to be used to store the patient fixation
conducted in the function position_geometry | src/pyskindose/phantom_class.py | save_position | notZaki/PySkinDose | 0 | python | def save_position(self) -> None:
'Store a reference position of the phantom.\n\n This function is supposed to be used to store the patient fixation\n conducted in the function position_geometry\n\n '
r_ref = copy.copy(self.r)
self.r_ref = r_ref | def save_position(self) -> None:
'Store a reference position of the phantom.\n\n This function is supposed to be used to store the patient fixation\n conducted in the function position_geometry\n\n '
r_ref = copy.copy(self.r)
self.r_ref = r_ref<|docstring|>Store a reference position of the phantom.
This function is supposed to be used to store the patient fixation
conducted in the function position_geometry<|endoftext|> |
3be814430079b375017c320c69b6e60a1e60ec0cebe8e2146cbc79fb8d17e31c | def position(self, data_norm: pd.DataFrame, event: int) -> None:
'Position the phantom for a event by adding RDSR table displacement.\n\n Positions the phantom from reference position to actual position\n according to the table displacement info in data_norm.\n\n Parameters\n ----------\n data_norm : pd.DataFrame\n Table containing dicom RDSR information from each irradiation event\n See rdsr_normalizer.py for more information.\n event : int\n Irradiation event index\n\n '
self.r = copy.copy(self.r_ref)
self.r[(:, 2)] += (self.table_length / 2)
rot = np.deg2rad(data_norm['At1'][event])
tilt = np.deg2rad(data_norm['At2'][event])
cradle = np.deg2rad(data_norm['At3'][event])
R1 = np.array([[(+ np.cos(rot)), 0, (+ np.sin(rot))], [0, 1, 0], [(- np.sin(rot)), 0, (+ np.cos(rot))]])
R2 = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(tilt)), (- np.sin(tilt))], [(+ 0), (+ np.sin(tilt)), (+ np.cos(tilt))]])
R3 = np.array([[(+ np.cos(cradle)), (- np.sin(cradle)), 0], [(+ np.sin(cradle)), (+ np.cos(cradle)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(np.matmul(R3, np.matmul(R2, R1)), self.r.T).T
self.r[(:, 2)] -= (self.table_length / 2)
t = np.array([data_norm.Tx[event], data_norm.Ty[event], data_norm.Tz[event]])
self.r = (self.r + t) | Position the phantom for a event by adding RDSR table displacement.
Positions the phantom from reference position to actual position
according to the table displacement info in data_norm.
Parameters
----------
data_norm : pd.DataFrame
Table containing dicom RDSR information from each irradiation event
See rdsr_normalizer.py for more information.
event : int
Irradiation event index | src/pyskindose/phantom_class.py | position | notZaki/PySkinDose | 0 | python | def position(self, data_norm: pd.DataFrame, event: int) -> None:
'Position the phantom for a event by adding RDSR table displacement.\n\n Positions the phantom from reference position to actual position\n according to the table displacement info in data_norm.\n\n Parameters\n ----------\n data_norm : pd.DataFrame\n Table containing dicom RDSR information from each irradiation event\n See rdsr_normalizer.py for more information.\n event : int\n Irradiation event index\n\n '
self.r = copy.copy(self.r_ref)
self.r[(:, 2)] += (self.table_length / 2)
rot = np.deg2rad(data_norm['At1'][event])
tilt = np.deg2rad(data_norm['At2'][event])
cradle = np.deg2rad(data_norm['At3'][event])
R1 = np.array([[(+ np.cos(rot)), 0, (+ np.sin(rot))], [0, 1, 0], [(- np.sin(rot)), 0, (+ np.cos(rot))]])
R2 = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(tilt)), (- np.sin(tilt))], [(+ 0), (+ np.sin(tilt)), (+ np.cos(tilt))]])
R3 = np.array([[(+ np.cos(cradle)), (- np.sin(cradle)), 0], [(+ np.sin(cradle)), (+ np.cos(cradle)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(np.matmul(R3, np.matmul(R2, R1)), self.r.T).T
self.r[(:, 2)] -= (self.table_length / 2)
t = np.array([data_norm.Tx[event], data_norm.Ty[event], data_norm.Tz[event]])
self.r = (self.r + t) | def position(self, data_norm: pd.DataFrame, event: int) -> None:
'Position the phantom for a event by adding RDSR table displacement.\n\n Positions the phantom from reference position to actual position\n according to the table displacement info in data_norm.\n\n Parameters\n ----------\n data_norm : pd.DataFrame\n Table containing dicom RDSR information from each irradiation event\n See rdsr_normalizer.py for more information.\n event : int\n Irradiation event index\n\n '
self.r = copy.copy(self.r_ref)
self.r[(:, 2)] += (self.table_length / 2)
rot = np.deg2rad(data_norm['At1'][event])
tilt = np.deg2rad(data_norm['At2'][event])
cradle = np.deg2rad(data_norm['At3'][event])
R1 = np.array([[(+ np.cos(rot)), 0, (+ np.sin(rot))], [0, 1, 0], [(- np.sin(rot)), 0, (+ np.cos(rot))]])
R2 = np.array([[(+ 1), (+ 0), (+ 0)], [(+ 0), (+ np.cos(tilt)), (- np.sin(tilt))], [(+ 0), (+ np.sin(tilt)), (+ np.cos(tilt))]])
R3 = np.array([[(+ np.cos(cradle)), (- np.sin(cradle)), 0], [(+ np.sin(cradle)), (+ np.cos(cradle)), (+ 0)], [(+ 0), (+ 0), (+ 1)]])
self.r = np.matmul(np.matmul(R3, np.matmul(R2, R1)), self.r.T).T
self.r[(:, 2)] -= (self.table_length / 2)
t = np.array([data_norm.Tx[event], data_norm.Ty[event], data_norm.Tz[event]])
self.r = (self.r + t)<|docstring|>Position the phantom for a event by adding RDSR table displacement.
Positions the phantom from reference position to actual position
according to the table displacement info in data_norm.
Parameters
----------
data_norm : pd.DataFrame
Table containing dicom RDSR information from each irradiation event
See rdsr_normalizer.py for more information.
event : int
Irradiation event index<|endoftext|> |
0ad9557eaa7d38fa4fb4e9eafd837f6bb1ce10e6c4420ad0df3ba1ce556e8ed7 | def plot_dosemap(self, dark_mode: bool=True, notebook_mode: bool=False):
'Plot a map of the absorbed skindose upon the patient phantom.\n\n This function creates and plots an offline plotly graph of the\n skin dose distribution on the phantom. The colorscale is mapped to the\n absorbed skin dose value. Only available for phantom type: "plane",\n "cylinder" or "human"\n\n Parameters\n ----------\n dark_mode : bool\n set dark for for plot\n notebook_mode : bool, default is true\n optimize plot size and margin for notebooks.\n\n '
(COLOR_CANVAS, COLOR_PLOT_TEXT, COLOR_GRID, COLOR_ZERO_LINE) = fetch_plot_colors(dark_mode=dark_mode)
(PLOT_HEIGHT, PLOT_WIDTH) = fetch_plot_size(notebook_mode=notebook_mode)
PLOT_MARGINS = fetch_plot_margin(notebook_mode=notebook_mode)
lat_text = [f'<b>lat:</b> {np.around(self.r[(ind, 2)], 2)} cm<br>' for ind in range(len(self.r))]
lon_text = [f'<b>lon:</b> {np.around(self.r[(ind, 0)], 2)} cm<br>' for ind in range(len(self.r))]
ver_text = [f'<b>ver:</b> {np.around(self.r[(ind, 1)], 2)} cm<br>' for ind in range(len(self.r))]
dose_text = [f'<b>skin dose:</b> {round(self.dose[ind], 2)} mGy' for ind in range(len(self.r))]
hover_text = [(((lat_text[cell] + lon_text[cell]) + ver_text[cell]) + dose_text[cell]) for cell in range(len(self.r))]
phantom_mesh = [go.Mesh3d(x=self.r[(:, 0)], y=self.r[(:, 1)], z=self.r[(:, 2)], i=self.ijk[(:, 0)], j=self.ijk[(:, 1)], k=self.ijk[(:, 2)], intensity=self.dose, colorscale=DOSEMAP_COLORSCALE, showscale=True, hoverinfo='text', text=hover_text, name='Human', colorbar=dict(tickfont=dict(color=COLOR_PLOT_TEXT), title='Skin dose [mGy]', titlefont=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT)))]
layout = go.Layout(height=PLOT_HEIGHT, width=PLOT_WIDTH, margin=PLOT_MARGINS, font=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT, size=PLOT_FONT_SIZE), hoverlabel=dict(font=dict(family=PLOT_HOVERLABEL_FONT_FAMILY, size=PLOT_HOVERLABEL_FONT_SIZE)), title='<b>P</b>y<b>S</b>kin<b>D</b>ose [mode: dosemap]', titlefont=dict(family=PLOT_FONT_FAMILY, size=PLOT_FONT_SIZE, color=COLOR_PLOT_TEXT), paper_bgcolor=COLOR_CANVAS, scene=dict(aspectmode=PLOT_ASPECTMODE_PLOT_DOSEMAP, xaxis=dict(title='', backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), yaxis=dict(title='', backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), zaxis=dict(title='', backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False)))
fig = go.Figure(data=phantom_mesh, layout=layout)
fig.show() | Plot a map of the absorbed skindose upon the patient phantom.
This function creates and plots an offline plotly graph of the
skin dose distribution on the phantom. The colorscale is mapped to the
absorbed skin dose value. Only available for phantom type: "plane",
"cylinder" or "human"
Parameters
----------
dark_mode : bool
set dark for for plot
notebook_mode : bool, default is true
optimize plot size and margin for notebooks. | src/pyskindose/phantom_class.py | plot_dosemap | notZaki/PySkinDose | 0 | python | def plot_dosemap(self, dark_mode: bool=True, notebook_mode: bool=False):
'Plot a map of the absorbed skindose upon the patient phantom.\n\n This function creates and plots an offline plotly graph of the\n skin dose distribution on the phantom. The colorscale is mapped to the\n absorbed skin dose value. Only available for phantom type: "plane",\n "cylinder" or "human"\n\n Parameters\n ----------\n dark_mode : bool\n set dark for for plot\n notebook_mode : bool, default is true\n optimize plot size and margin for notebooks.\n\n '
(COLOR_CANVAS, COLOR_PLOT_TEXT, COLOR_GRID, COLOR_ZERO_LINE) = fetch_plot_colors(dark_mode=dark_mode)
(PLOT_HEIGHT, PLOT_WIDTH) = fetch_plot_size(notebook_mode=notebook_mode)
PLOT_MARGINS = fetch_plot_margin(notebook_mode=notebook_mode)
lat_text = [f'<b>lat:</b> {np.around(self.r[(ind, 2)], 2)} cm<br>' for ind in range(len(self.r))]
lon_text = [f'<b>lon:</b> {np.around(self.r[(ind, 0)], 2)} cm<br>' for ind in range(len(self.r))]
ver_text = [f'<b>ver:</b> {np.around(self.r[(ind, 1)], 2)} cm<br>' for ind in range(len(self.r))]
dose_text = [f'<b>skin dose:</b> {round(self.dose[ind], 2)} mGy' for ind in range(len(self.r))]
hover_text = [(((lat_text[cell] + lon_text[cell]) + ver_text[cell]) + dose_text[cell]) for cell in range(len(self.r))]
phantom_mesh = [go.Mesh3d(x=self.r[(:, 0)], y=self.r[(:, 1)], z=self.r[(:, 2)], i=self.ijk[(:, 0)], j=self.ijk[(:, 1)], k=self.ijk[(:, 2)], intensity=self.dose, colorscale=DOSEMAP_COLORSCALE, showscale=True, hoverinfo='text', text=hover_text, name='Human', colorbar=dict(tickfont=dict(color=COLOR_PLOT_TEXT), title='Skin dose [mGy]', titlefont=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT)))]
layout = go.Layout(height=PLOT_HEIGHT, width=PLOT_WIDTH, margin=PLOT_MARGINS, font=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT, size=PLOT_FONT_SIZE), hoverlabel=dict(font=dict(family=PLOT_HOVERLABEL_FONT_FAMILY, size=PLOT_HOVERLABEL_FONT_SIZE)), title='<b>P</b>y<b>S</b>kin<b>D</b>ose [mode: dosemap]', titlefont=dict(family=PLOT_FONT_FAMILY, size=PLOT_FONT_SIZE, color=COLOR_PLOT_TEXT), paper_bgcolor=COLOR_CANVAS, scene=dict(aspectmode=PLOT_ASPECTMODE_PLOT_DOSEMAP, xaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), yaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), zaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False)))
fig = go.Figure(data=phantom_mesh, layout=layout)
fig.show() | def plot_dosemap(self, dark_mode: bool=True, notebook_mode: bool=False):
'Plot a map of the absorbed skindose upon the patient phantom.\n\n This function creates and plots an offline plotly graph of the\n skin dose distribution on the phantom. The colorscale is mapped to the\n absorbed skin dose value. Only available for phantom type: "plane",\n "cylinder" or "human"\n\n Parameters\n ----------\n dark_mode : bool\n set dark for for plot\n notebook_mode : bool, default is true\n optimize plot size and margin for notebooks.\n\n '
(COLOR_CANVAS, COLOR_PLOT_TEXT, COLOR_GRID, COLOR_ZERO_LINE) = fetch_plot_colors(dark_mode=dark_mode)
(PLOT_HEIGHT, PLOT_WIDTH) = fetch_plot_size(notebook_mode=notebook_mode)
PLOT_MARGINS = fetch_plot_margin(notebook_mode=notebook_mode)
lat_text = [f'<b>lat:</b> {np.around(self.r[(ind, 2)], 2)} cm<br>' for ind in range(len(self.r))]
lon_text = [f'<b>lon:</b> {np.around(self.r[(ind, 0)], 2)} cm<br>' for ind in range(len(self.r))]
ver_text = [f'<b>ver:</b> {np.around(self.r[(ind, 1)], 2)} cm<br>' for ind in range(len(self.r))]
dose_text = [f'<b>skin dose:</b> {round(self.dose[ind], 2)} mGy' for ind in range(len(self.r))]
hover_text = [(((lat_text[cell] + lon_text[cell]) + ver_text[cell]) + dose_text[cell]) for cell in range(len(self.r))]
phantom_mesh = [go.Mesh3d(x=self.r[(:, 0)], y=self.r[(:, 1)], z=self.r[(:, 2)], i=self.ijk[(:, 0)], j=self.ijk[(:, 1)], k=self.ijk[(:, 2)], intensity=self.dose, colorscale=DOSEMAP_COLORSCALE, showscale=True, hoverinfo='text', text=hover_text, name='Human', colorbar=dict(tickfont=dict(color=COLOR_PLOT_TEXT), title='Skin dose [mGy]', titlefont=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT)))]
layout = go.Layout(height=PLOT_HEIGHT, width=PLOT_WIDTH, margin=PLOT_MARGINS, font=dict(family=PLOT_FONT_FAMILY, color=COLOR_PLOT_TEXT, size=PLOT_FONT_SIZE), hoverlabel=dict(font=dict(family=PLOT_HOVERLABEL_FONT_FAMILY, size=PLOT_HOVERLABEL_FONT_SIZE)), title='<b>P</b>y<b>S</b>kin<b>D</b>ose [mode: dosemap]', titlefont=dict(family=PLOT_FONT_FAMILY, size=PLOT_FONT_SIZE, color=COLOR_PLOT_TEXT), paper_bgcolor=COLOR_CANVAS, scene=dict(aspectmode=PLOT_ASPECTMODE_PLOT_DOSEMAP, xaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), yaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False), zaxis=dict(title=, backgroundcolor=COLOR_CANVAS, showgrid=False, zeroline=False, showticklabels=False)))
fig = go.Figure(data=phantom_mesh, layout=layout)
fig.show()<|docstring|>Plot a map of the absorbed skindose upon the patient phantom.
This function creates and plots an offline plotly graph of the
skin dose distribution on the phantom. The colorscale is mapped to the
absorbed skin dose value. Only available for phantom type: "plane",
"cylinder" or "human"
Parameters
----------
dark_mode : bool
set dark for for plot
notebook_mode : bool, default is true
optimize plot size and margin for notebooks.<|endoftext|> |
ac8835bde3f1b68dbe6d3b49fa29159c7ee706aa2da498ab9f0d022ab13e8ae0 | def plot_graph(vertices, edges, ax, xlim=None, highlight=None, highlight_color='magenta', node_color='b', edge_color='#999999', label=None):
'Takes a graph given as vertices and edges and visualizes its structure'
start = vertices.ravel().min()
stop = vertices.ravel().max()
ax.grid(b=True, which='major', linestyle='--', linewidth=0.2, color='#222222')
ax.yaxis.grid(False)
patchlist = []
exon_num = np.zeros(((stop - start),))
exon_loc = np.zeros((1, (stop - start)))
exon_level = np.zeros((vertices.shape[1],))
for i in range(vertices.shape[1]):
cur_vertex = (vertices[(:, i)] - start)
exon_num[cur_vertex[0]:cur_vertex[1]] += 1
if np.all((exon_num < 2)):
exon_loc[(0, :)] = exon_num
level = 0
elif (exon_num.max() > exon_loc.shape[0]):
exon_loc = np.r_[(exon_loc, np.zeros((1, (stop - start))))]
exon_loc[((- 1), cur_vertex[0]:cur_vertex[1])] = 1
level = (exon_loc.shape[0] - 1)
elif (exon_num.max() <= exon_loc.shape[0]):
idx = np.where(np.all((exon_loc[(:, cur_vertex[0]:cur_vertex[1])] == 0), 1))[0].min()
exon_loc[(idx, cur_vertex[0]:cur_vertex[1])] = 1
level = idx
exon_level[i] = level
patchlist.append(mpatches.Rectangle([(cur_vertex[0] + start), (20 + (level * 20))], (cur_vertex[1] - cur_vertex[0]), 10, facecolor=node_color, edgecolor='none', alpha=0.7))
linelist = []
intron_loc = np.zeros((1, (stop - start)))
if (edges.shape[0] > 1):
(ii, jj) = np.where((np.triu(edges) > 0))
for (i, j) in zip(ii, jj):
if (vertices[(0, i)] < vertices[(0, j)]):
istart = vertices[(1, i)]
istop = vertices[(0, j)]
level1 = exon_level[i]
level2 = exon_level[j]
else:
istart = vertices[(1, j)]
istop = vertices[(0, i)]
level1 = exon_level[j]
level2 = exon_level[i]
cur_intron = [(istart - start), (istop - start)]
intron_loc[cur_intron[0]:cur_intron[1]] += 1
leveli = [((istart + istop) * 0.5), ((level1 + level2) * 0.5)]
linelist.append(mlines.Line2D([istart, leveli[0], istop], [(25 + (level1 * 20)), (32 + (leveli[1] * 20)), (25 + (level2 * 20))], color=edge_color, linewidth=0.5))
for node in patchlist:
ax.add_patch(node)
for line in linelist:
ax.add_line(line)
if label:
ax.text((start + ((stop - start) / 2)), 12, label, verticalalignment='center', horizontalalignment='center')
if (xlim is not None):
ax.set_xlim(xlim)
else:
ax.set_xlim([max((start - 20), 0), (stop + 20)])
ax.set_ylim([0, (40 + (exon_loc.shape[0] * 20))])
ax.set_yticks([])
if (highlight is not None):
rect = patches.Rectangle((highlight[0], 0), (highlight[1] - highlight[0]), ax.get_ylim()[1], facecolor=highlight_color, edgecolor='none', alpha=0.5)
ax.add_patch(rect) | Takes a graph given as vertices and edges and visualizes its structure | spladder/viz/graph.py | plot_graph | ratschlab/spladder | 96 | python | def plot_graph(vertices, edges, ax, xlim=None, highlight=None, highlight_color='magenta', node_color='b', edge_color='#999999', label=None):
start = vertices.ravel().min()
stop = vertices.ravel().max()
ax.grid(b=True, which='major', linestyle='--', linewidth=0.2, color='#222222')
ax.yaxis.grid(False)
patchlist = []
exon_num = np.zeros(((stop - start),))
exon_loc = np.zeros((1, (stop - start)))
exon_level = np.zeros((vertices.shape[1],))
for i in range(vertices.shape[1]):
cur_vertex = (vertices[(:, i)] - start)
exon_num[cur_vertex[0]:cur_vertex[1]] += 1
if np.all((exon_num < 2)):
exon_loc[(0, :)] = exon_num
level = 0
elif (exon_num.max() > exon_loc.shape[0]):
exon_loc = np.r_[(exon_loc, np.zeros((1, (stop - start))))]
exon_loc[((- 1), cur_vertex[0]:cur_vertex[1])] = 1
level = (exon_loc.shape[0] - 1)
elif (exon_num.max() <= exon_loc.shape[0]):
idx = np.where(np.all((exon_loc[(:, cur_vertex[0]:cur_vertex[1])] == 0), 1))[0].min()
exon_loc[(idx, cur_vertex[0]:cur_vertex[1])] = 1
level = idx
exon_level[i] = level
patchlist.append(mpatches.Rectangle([(cur_vertex[0] + start), (20 + (level * 20))], (cur_vertex[1] - cur_vertex[0]), 10, facecolor=node_color, edgecolor='none', alpha=0.7))
linelist = []
intron_loc = np.zeros((1, (stop - start)))
if (edges.shape[0] > 1):
(ii, jj) = np.where((np.triu(edges) > 0))
for (i, j) in zip(ii, jj):
if (vertices[(0, i)] < vertices[(0, j)]):
istart = vertices[(1, i)]
istop = vertices[(0, j)]
level1 = exon_level[i]
level2 = exon_level[j]
else:
istart = vertices[(1, j)]
istop = vertices[(0, i)]
level1 = exon_level[j]
level2 = exon_level[i]
cur_intron = [(istart - start), (istop - start)]
intron_loc[cur_intron[0]:cur_intron[1]] += 1
leveli = [((istart + istop) * 0.5), ((level1 + level2) * 0.5)]
linelist.append(mlines.Line2D([istart, leveli[0], istop], [(25 + (level1 * 20)), (32 + (leveli[1] * 20)), (25 + (level2 * 20))], color=edge_color, linewidth=0.5))
for node in patchlist:
ax.add_patch(node)
for line in linelist:
ax.add_line(line)
if label:
ax.text((start + ((stop - start) / 2)), 12, label, verticalalignment='center', horizontalalignment='center')
if (xlim is not None):
ax.set_xlim(xlim)
else:
ax.set_xlim([max((start - 20), 0), (stop + 20)])
ax.set_ylim([0, (40 + (exon_loc.shape[0] * 20))])
ax.set_yticks([])
if (highlight is not None):
rect = patches.Rectangle((highlight[0], 0), (highlight[1] - highlight[0]), ax.get_ylim()[1], facecolor=highlight_color, edgecolor='none', alpha=0.5)
ax.add_patch(rect) | def plot_graph(vertices, edges, ax, xlim=None, highlight=None, highlight_color='magenta', node_color='b', edge_color='#999999', label=None):
start = vertices.ravel().min()
stop = vertices.ravel().max()
ax.grid(b=True, which='major', linestyle='--', linewidth=0.2, color='#222222')
ax.yaxis.grid(False)
patchlist = []
exon_num = np.zeros(((stop - start),))
exon_loc = np.zeros((1, (stop - start)))
exon_level = np.zeros((vertices.shape[1],))
for i in range(vertices.shape[1]):
cur_vertex = (vertices[(:, i)] - start)
exon_num[cur_vertex[0]:cur_vertex[1]] += 1
if np.all((exon_num < 2)):
exon_loc[(0, :)] = exon_num
level = 0
elif (exon_num.max() > exon_loc.shape[0]):
exon_loc = np.r_[(exon_loc, np.zeros((1, (stop - start))))]
exon_loc[((- 1), cur_vertex[0]:cur_vertex[1])] = 1
level = (exon_loc.shape[0] - 1)
elif (exon_num.max() <= exon_loc.shape[0]):
idx = np.where(np.all((exon_loc[(:, cur_vertex[0]:cur_vertex[1])] == 0), 1))[0].min()
exon_loc[(idx, cur_vertex[0]:cur_vertex[1])] = 1
level = idx
exon_level[i] = level
patchlist.append(mpatches.Rectangle([(cur_vertex[0] + start), (20 + (level * 20))], (cur_vertex[1] - cur_vertex[0]), 10, facecolor=node_color, edgecolor='none', alpha=0.7))
linelist = []
intron_loc = np.zeros((1, (stop - start)))
if (edges.shape[0] > 1):
(ii, jj) = np.where((np.triu(edges) > 0))
for (i, j) in zip(ii, jj):
if (vertices[(0, i)] < vertices[(0, j)]):
istart = vertices[(1, i)]
istop = vertices[(0, j)]
level1 = exon_level[i]
level2 = exon_level[j]
else:
istart = vertices[(1, j)]
istop = vertices[(0, i)]
level1 = exon_level[j]
level2 = exon_level[i]
cur_intron = [(istart - start), (istop - start)]
intron_loc[cur_intron[0]:cur_intron[1]] += 1
leveli = [((istart + istop) * 0.5), ((level1 + level2) * 0.5)]
linelist.append(mlines.Line2D([istart, leveli[0], istop], [(25 + (level1 * 20)), (32 + (leveli[1] * 20)), (25 + (level2 * 20))], color=edge_color, linewidth=0.5))
for node in patchlist:
ax.add_patch(node)
for line in linelist:
ax.add_line(line)
if label:
ax.text((start + ((stop - start) / 2)), 12, label, verticalalignment='center', horizontalalignment='center')
if (xlim is not None):
ax.set_xlim(xlim)
else:
ax.set_xlim([max((start - 20), 0), (stop + 20)])
ax.set_ylim([0, (40 + (exon_loc.shape[0] * 20))])
ax.set_yticks([])
if (highlight is not None):
rect = patches.Rectangle((highlight[0], 0), (highlight[1] - highlight[0]), ax.get_ylim()[1], facecolor=highlight_color, edgecolor='none', alpha=0.5)
ax.add_patch(rect)<|docstring|>Takes a graph given as vertices and edges and visualizes its structure<|endoftext|> |
06c765a786afb757be1866036a0e7080ea8f24eab589dd8e1b4fd11b86bff1a4 | def __init__(self, classes_root_dir, this_root_dir, yolo_config, augment=False):
'\n :param root_dir:\n :param yolo_config: dictionary that contain the require data for yolo (C, B, K)\n '
self.augment = augment
self.root_dir = this_root_dir
self.C = yolo_config['C']
self.B = yolo_config['B']
self.K = yolo_config['K']
(classes, class_to_idx) = find_classes(classes_root_dir)
self.class_to_idx = class_to_idx
self.classes = classes
spects = []
count = 0
dir = os.path.expanduser(this_root_dir)
for target in sorted(os.listdir(dir)):
d = os.path.join(dir, target)
if (not os.path.isdir(d)):
continue
if (target not in classes):
continue
for (root, _, fnames) in sorted(os.walk(d)):
for fname in sorted(fnames):
count += 1
if is_audio_file(fname):
path = os.path.join(root, fname)
x = os.path.getsize(path)
if (x < 1000):
print(path)
continue
label = os.path.join(root, fname.replace('.wav', '.wrd'))
tclass = self.class_to_idx[target]
item = (path, label, tclass)
spects.append(item)
self.data = spects | :param root_dir:
:param yolo_config: dictionary that contain the require data for yolo (C, B, K) | Multitask/ImageAudioClassifier/Helper.py | __init__ | nileshpd1211/SRIP-UCSD---Efficient-Deep-Networks | 0 | python | def __init__(self, classes_root_dir, this_root_dir, yolo_config, augment=False):
'\n :param root_dir:\n :param yolo_config: dictionary that contain the require data for yolo (C, B, K)\n '
self.augment = augment
self.root_dir = this_root_dir
self.C = yolo_config['C']
self.B = yolo_config['B']
self.K = yolo_config['K']
(classes, class_to_idx) = find_classes(classes_root_dir)
self.class_to_idx = class_to_idx
self.classes = classes
spects = []
count = 0
dir = os.path.expanduser(this_root_dir)
for target in sorted(os.listdir(dir)):
d = os.path.join(dir, target)
if (not os.path.isdir(d)):
continue
if (target not in classes):
continue
for (root, _, fnames) in sorted(os.walk(d)):
for fname in sorted(fnames):
count += 1
if is_audio_file(fname):
path = os.path.join(root, fname)
x = os.path.getsize(path)
if (x < 1000):
print(path)
continue
label = os.path.join(root, fname.replace('.wav', '.wrd'))
tclass = self.class_to_idx[target]
item = (path, label, tclass)
spects.append(item)
self.data = spects | def __init__(self, classes_root_dir, this_root_dir, yolo_config, augment=False):
'\n :param root_dir:\n :param yolo_config: dictionary that contain the require data for yolo (C, B, K)\n '
self.augment = augment
self.root_dir = this_root_dir
self.C = yolo_config['C']
self.B = yolo_config['B']
self.K = yolo_config['K']
(classes, class_to_idx) = find_classes(classes_root_dir)
self.class_to_idx = class_to_idx
self.classes = classes
spects = []
count = 0
dir = os.path.expanduser(this_root_dir)
for target in sorted(os.listdir(dir)):
d = os.path.join(dir, target)
if (not os.path.isdir(d)):
continue
if (target not in classes):
continue
for (root, _, fnames) in sorted(os.walk(d)):
for fname in sorted(fnames):
count += 1
if is_audio_file(fname):
path = os.path.join(root, fname)
x = os.path.getsize(path)
if (x < 1000):
print(path)
continue
label = os.path.join(root, fname.replace('.wav', '.wrd'))
tclass = self.class_to_idx[target]
item = (path, label, tclass)
spects.append(item)
self.data = spects<|docstring|>:param root_dir:
:param yolo_config: dictionary that contain the require data for yolo (C, B, K)<|endoftext|> |
2251cf9211e0219bbd7950e779b5de897420674c4ab917c64b86c61b8e3cc913 | def __getitem__(self, idx):
'\n :param idx:\n :return:\n '
features_path = self.data[idx][0]
add_augment = False
if self.augment:
add_augment = utils.random_onoff()
(features, dot_len, real_features_len, sr) = utils.spect_loader(features_path, max_len=101, augment=add_augment)
target_path = self.data[idx][1]
target = open(target_path, 'r').readlines()
(_, num_features, features_wav_len) = features.shape
'\n # the labels file, is file with few lines,\n # each line represents one item in the wav file and contains : start (in sr), end (in sr), class.\n # yolo needs more details\n # x - represent the center of the box relative to the bounds of the grid cell.\n # w - predicted relative to the whole wav.\n # iou - the confidence prediction represents the IOU between the predicted box and any ground truth box\n\n '
divide = (sr / features_wav_len)
width_cell = ((1.0 * features_wav_len) / self.C)
line_yolo_data = []
for line_str in target:
line = line_str.replace('\t', '_').split(' ')
feature_start = math.floor((float(line[0]) / divide))
feature_end = math.floor((float(line[1]) / divide))
object_width = (feature_end - feature_start)
center_x = (feature_start + (object_width / 2.0))
cell_index = int((center_x / width_cell))
object_norm_x = ((float(center_x) / width_cell) - int((center_x / width_cell)))
object_norm_w = (object_width / features_wav_len)
class_label = line[2]
object_class = self.class_to_idx[class_label]
line_yolo_data.append([cell_index, object_norm_x, object_norm_w, object_class])
kwspotting_target = (torch.ones([self.K]) * (- 1))
target = torch.zeros([self.C, (((self.B * 3) + self.K) + 1)], dtype=torch.float32)
for yolo_item in line_yolo_data:
index = yolo_item[0]
x = yolo_item[1]
w = math.sqrt(yolo_item[2])
obj_class = yolo_item[3]
target[(index, ((self.B * 3) + obj_class))] = 1
target[(index, (- 1))] = 1
for box in range(0, self.B):
target[(index, ((box * 3) + 2))] = 1
target[(index, (box * 3))] = x
target[(index, ((box * 3) + 1))] = w
kwspotting_target[obj_class] = 1
return (features, target, features_path, kwspotting_target) | :param idx:
:return: | Multitask/ImageAudioClassifier/Helper.py | __getitem__ | nileshpd1211/SRIP-UCSD---Efficient-Deep-Networks | 0 | python | def __getitem__(self, idx):
'\n :param idx:\n :return:\n '
features_path = self.data[idx][0]
add_augment = False
if self.augment:
add_augment = utils.random_onoff()
(features, dot_len, real_features_len, sr) = utils.spect_loader(features_path, max_len=101, augment=add_augment)
target_path = self.data[idx][1]
target = open(target_path, 'r').readlines()
(_, num_features, features_wav_len) = features.shape
'\n # the labels file, is file with few lines,\n # each line represents one item in the wav file and contains : start (in sr), end (in sr), class.\n # yolo needs more details\n # x - represent the center of the box relative to the bounds of the grid cell.\n # w - predicted relative to the whole wav.\n # iou - the confidence prediction represents the IOU between the predicted box and any ground truth box\n\n '
divide = (sr / features_wav_len)
width_cell = ((1.0 * features_wav_len) / self.C)
line_yolo_data = []
for line_str in target:
line = line_str.replace('\t', '_').split(' ')
feature_start = math.floor((float(line[0]) / divide))
feature_end = math.floor((float(line[1]) / divide))
object_width = (feature_end - feature_start)
center_x = (feature_start + (object_width / 2.0))
cell_index = int((center_x / width_cell))
object_norm_x = ((float(center_x) / width_cell) - int((center_x / width_cell)))
object_norm_w = (object_width / features_wav_len)
class_label = line[2]
object_class = self.class_to_idx[class_label]
line_yolo_data.append([cell_index, object_norm_x, object_norm_w, object_class])
kwspotting_target = (torch.ones([self.K]) * (- 1))
target = torch.zeros([self.C, (((self.B * 3) + self.K) + 1)], dtype=torch.float32)
for yolo_item in line_yolo_data:
index = yolo_item[0]
x = yolo_item[1]
w = math.sqrt(yolo_item[2])
obj_class = yolo_item[3]
target[(index, ((self.B * 3) + obj_class))] = 1
target[(index, (- 1))] = 1
for box in range(0, self.B):
target[(index, ((box * 3) + 2))] = 1
target[(index, (box * 3))] = x
target[(index, ((box * 3) + 1))] = w
kwspotting_target[obj_class] = 1
return (features, target, features_path, kwspotting_target) | def __getitem__(self, idx):
'\n :param idx:\n :return:\n '
features_path = self.data[idx][0]
add_augment = False
if self.augment:
add_augment = utils.random_onoff()
(features, dot_len, real_features_len, sr) = utils.spect_loader(features_path, max_len=101, augment=add_augment)
target_path = self.data[idx][1]
target = open(target_path, 'r').readlines()
(_, num_features, features_wav_len) = features.shape
'\n # the labels file, is file with few lines,\n # each line represents one item in the wav file and contains : start (in sr), end (in sr), class.\n # yolo needs more details\n # x - represent the center of the box relative to the bounds of the grid cell.\n # w - predicted relative to the whole wav.\n # iou - the confidence prediction represents the IOU between the predicted box and any ground truth box\n\n '
divide = (sr / features_wav_len)
width_cell = ((1.0 * features_wav_len) / self.C)
line_yolo_data = []
for line_str in target:
line = line_str.replace('\t', '_').split(' ')
feature_start = math.floor((float(line[0]) / divide))
feature_end = math.floor((float(line[1]) / divide))
object_width = (feature_end - feature_start)
center_x = (feature_start + (object_width / 2.0))
cell_index = int((center_x / width_cell))
object_norm_x = ((float(center_x) / width_cell) - int((center_x / width_cell)))
object_norm_w = (object_width / features_wav_len)
class_label = line[2]
object_class = self.class_to_idx[class_label]
line_yolo_data.append([cell_index, object_norm_x, object_norm_w, object_class])
kwspotting_target = (torch.ones([self.K]) * (- 1))
target = torch.zeros([self.C, (((self.B * 3) + self.K) + 1)], dtype=torch.float32)
for yolo_item in line_yolo_data:
index = yolo_item[0]
x = yolo_item[1]
w = math.sqrt(yolo_item[2])
obj_class = yolo_item[3]
target[(index, ((self.B * 3) + obj_class))] = 1
target[(index, (- 1))] = 1
for box in range(0, self.B):
target[(index, ((box * 3) + 2))] = 1
target[(index, (box * 3))] = x
target[(index, ((box * 3) + 1))] = w
kwspotting_target[obj_class] = 1
return (features, target, features_path, kwspotting_target)<|docstring|>:param idx:
:return:<|endoftext|> |
b71335bbad624951a0b6757bf15e0ecd2d1cbf4ebd02e5de403f832d60394d49 | def hIndex(self, citations):
'\n :type citations: List[int]\n :rtype: int\n '
n = len(citations)
(left, right) = (0, (n - 1))
while (left <= right):
mid = (left + ((right - left) / 2))
if (citations[mid] >= (n - mid)):
right = (mid - 1)
else:
left = (mid + 1)
return (n - left) | :type citations: List[int]
:rtype: int | tools/leetcode.275.H-Index II/leetcode.275.H-Index II.submission1.py | hIndex | tedye/leetcode | 4 | python | def hIndex(self, citations):
'\n :type citations: List[int]\n :rtype: int\n '
n = len(citations)
(left, right) = (0, (n - 1))
while (left <= right):
mid = (left + ((right - left) / 2))
if (citations[mid] >= (n - mid)):
right = (mid - 1)
else:
left = (mid + 1)
return (n - left) | def hIndex(self, citations):
'\n :type citations: List[int]\n :rtype: int\n '
n = len(citations)
(left, right) = (0, (n - 1))
while (left <= right):
mid = (left + ((right - left) / 2))
if (citations[mid] >= (n - mid)):
right = (mid - 1)
else:
left = (mid + 1)
return (n - left)<|docstring|>:type citations: List[int]
:rtype: int<|endoftext|> |
d240279e07d79914326ff5bc4417f2c7fa32f54eb5f39c1740e7f0eba3320d3a | def is_alien_sorted(self, a, x):
'\n Determines whether input strings follow specified lexographic order.\n\n :param list[str] a: input array of ordered strings\n :param str x: string representing target lexographic order\n :return: True if input array is sorted by target lexographic order\n :rtype: bool\n '
if ((not a) or (not x)):
return False
d = {c: i for (i, c) in enumerate(x, 1)}
d[''] = 0
n = (len(a) - 1)
m = max((len(s) for s in a))
j = 0
while (j < m):
for i in range(n, 0, (- 1)):
if (j >= len(a[i])):
u = ''
else:
u = a[i][j]
if (j >= len(a[(i - 1)])):
v = ''
else:
v = a[(i - 1)][j]
if (d[u] > d[v]):
a[i] = a[(i - 1)]
elif (u == v):
continue
else:
return False
j += 1
return True | Determines whether input strings follow specified lexographic order.
:param list[str] a: input array of ordered strings
:param str x: string representing target lexographic order
:return: True if input array is sorted by target lexographic order
:rtype: bool | 0953_verifying_alien_dictionary/python_source.py | is_alien_sorted | arthurdysart/LeetCode | 0 | python | def is_alien_sorted(self, a, x):
'\n Determines whether input strings follow specified lexographic order.\n\n :param list[str] a: input array of ordered strings\n :param str x: string representing target lexographic order\n :return: True if input array is sorted by target lexographic order\n :rtype: bool\n '
if ((not a) or (not x)):
return False
d = {c: i for (i, c) in enumerate(x, 1)}
d[] = 0
n = (len(a) - 1)
m = max((len(s) for s in a))
j = 0
while (j < m):
for i in range(n, 0, (- 1)):
if (j >= len(a[i])):
u =
else:
u = a[i][j]
if (j >= len(a[(i - 1)])):
v =
else:
v = a[(i - 1)][j]
if (d[u] > d[v]):
a[i] = a[(i - 1)]
elif (u == v):
continue
else:
return False
j += 1
return True | def is_alien_sorted(self, a, x):
'\n Determines whether input strings follow specified lexographic order.\n\n :param list[str] a: input array of ordered strings\n :param str x: string representing target lexographic order\n :return: True if input array is sorted by target lexographic order\n :rtype: bool\n '
if ((not a) or (not x)):
return False
d = {c: i for (i, c) in enumerate(x, 1)}
d[] = 0
n = (len(a) - 1)
m = max((len(s) for s in a))
j = 0
while (j < m):
for i in range(n, 0, (- 1)):
if (j >= len(a[i])):
u =
else:
u = a[i][j]
if (j >= len(a[(i - 1)])):
v =
else:
v = a[(i - 1)][j]
if (d[u] > d[v]):
a[i] = a[(i - 1)]
elif (u == v):
continue
else:
return False
j += 1
return True<|docstring|>Determines whether input strings follow specified lexographic order.
:param list[str] a: input array of ordered strings
:param str x: string representing target lexographic order
:return: True if input array is sorted by target lexographic order
:rtype: bool<|endoftext|> |
8a4918fa56de7fc7952f0af094a56d509d17c7994152e56659752c54a5a213bd | def stdin(self, sys_stdin):
'\n Imports standard input.\n\n :param _io.TextIOWrapper sys_stdin: standard input\n :return: input array of ordered strings and target string\n :rtype: tup[list[str], str]\n '
inputs = [x.strip('[]"\n') for x in sys_stdin]
if (inputs[0] == ''):
a = list()
else:
a = [str(x).strip('"') for x in inputs[0].split('","')]
x = inputs[1]
return (a, x) | Imports standard input.
:param _io.TextIOWrapper sys_stdin: standard input
:return: input array of ordered strings and target string
:rtype: tup[list[str], str] | 0953_verifying_alien_dictionary/python_source.py | stdin | arthurdysart/LeetCode | 0 | python | def stdin(self, sys_stdin):
'\n Imports standard input.\n\n :param _io.TextIOWrapper sys_stdin: standard input\n :return: input array of ordered strings and target string\n :rtype: tup[list[str], str]\n '
inputs = [x.strip('[]"\n') for x in sys_stdin]
if (inputs[0] == ):
a = list()
else:
a = [str(x).strip('"') for x in inputs[0].split('","')]
x = inputs[1]
return (a, x) | def stdin(self, sys_stdin):
'\n Imports standard input.\n\n :param _io.TextIOWrapper sys_stdin: standard input\n :return: input array of ordered strings and target string\n :rtype: tup[list[str], str]\n '
inputs = [x.strip('[]"\n') for x in sys_stdin]
if (inputs[0] == ):
a = list()
else:
a = [str(x).strip('"') for x in inputs[0].split('","')]
x = inputs[1]
return (a, x)<|docstring|>Imports standard input.
:param _io.TextIOWrapper sys_stdin: standard input
:return: input array of ordered strings and target string
:rtype: tup[list[str], str]<|endoftext|> |
77d0f790ef6024adf98538666e66cf5336cfea9f80fe28bfc3b50a08c1e3a9fe | def test_empty_dag(self):
'Empty DAG has empty counts.'
circuit = QuantumCircuit()
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
self.assertDictEqual(pass_.property_set['count_ops_longest_path'], {}) | Empty DAG has empty counts. | test/python/transpiler/test_count_ops_longest_path_pass.py | test_empty_dag | ikkoham/qiskit-core | 1,456 | python | def test_empty_dag(self):
circuit = QuantumCircuit()
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
self.assertDictEqual(pass_.property_set['count_ops_longest_path'], {}) | def test_empty_dag(self):
circuit = QuantumCircuit()
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
self.assertDictEqual(pass_.property_set['count_ops_longest_path'], {})<|docstring|>Empty DAG has empty counts.<|endoftext|> |
22ab0475905474e90ced6c8c5b7291ffb9ec334cf3604f96d37cf1819b9392d1 | def test_just_qubits(self):
'A dag with 9 operations (3 CXs, 2Xs, 2Ys and 2 Hs) on the longest\n path\n '
qr = QuantumRegister(2)
circuit = QuantumCircuit(qr)
circuit.cx(qr[0], qr[1])
circuit.x(qr[0])
circuit.y(qr[0])
circuit.h(qr[0])
circuit.cx(qr[0], qr[1])
circuit.x(qr[1])
circuit.y(qr[1])
circuit.h(qr[1])
circuit.cx(qr[0], qr[1])
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
count_ops = pass_.property_set['count_ops_longest_path']
self.assertDictEqual(count_ops, {'cx': 3, 'x': 2, 'y': 2, 'h': 2}) | A dag with 9 operations (3 CXs, 2Xs, 2Ys and 2 Hs) on the longest
path | test/python/transpiler/test_count_ops_longest_path_pass.py | test_just_qubits | ikkoham/qiskit-core | 1,456 | python | def test_just_qubits(self):
'A dag with 9 operations (3 CXs, 2Xs, 2Ys and 2 Hs) on the longest\n path\n '
qr = QuantumRegister(2)
circuit = QuantumCircuit(qr)
circuit.cx(qr[0], qr[1])
circuit.x(qr[0])
circuit.y(qr[0])
circuit.h(qr[0])
circuit.cx(qr[0], qr[1])
circuit.x(qr[1])
circuit.y(qr[1])
circuit.h(qr[1])
circuit.cx(qr[0], qr[1])
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
count_ops = pass_.property_set['count_ops_longest_path']
self.assertDictEqual(count_ops, {'cx': 3, 'x': 2, 'y': 2, 'h': 2}) | def test_just_qubits(self):
'A dag with 9 operations (3 CXs, 2Xs, 2Ys and 2 Hs) on the longest\n path\n '
qr = QuantumRegister(2)
circuit = QuantumCircuit(qr)
circuit.cx(qr[0], qr[1])
circuit.x(qr[0])
circuit.y(qr[0])
circuit.h(qr[0])
circuit.cx(qr[0], qr[1])
circuit.x(qr[1])
circuit.y(qr[1])
circuit.h(qr[1])
circuit.cx(qr[0], qr[1])
dag = circuit_to_dag(circuit)
pass_ = CountOpsLongestPath()
_ = pass_.run(dag)
count_ops = pass_.property_set['count_ops_longest_path']
self.assertDictEqual(count_ops, {'cx': 3, 'x': 2, 'y': 2, 'h': 2})<|docstring|>A dag with 9 operations (3 CXs, 2Xs, 2Ys and 2 Hs) on the longest
path<|endoftext|> |
82a1f146eaf101a08df80a614ffdd02e2a64a51ae7616d3478a392ea8c08ad80 | @staticmethod
def add_args(arg_parser: argparse.ArgumentParser) -> None:
"\n Override this to add arguments to the CLI argument parser. These args\n will show up when the user invokes ``libcst.tool codemod`` with\n ``--help``. They will also be presented to your class's ``__init__``\n method. So, if you define a command with an argument 'foo', you should also\n have a corresponding 'foo' positional or keyword argument in your\n class's ``__init__`` method.\n "
pass | Override this to add arguments to the CLI argument parser. These args
will show up when the user invokes ``libcst.tool codemod`` with
``--help``. They will also be presented to your class's ``__init__``
method. So, if you define a command with an argument 'foo', you should also
have a corresponding 'foo' positional or keyword argument in your
class's ``__init__`` method. | libcst/codemod/_command.py | add_args | Instagram/LibCST | 880 | python | @staticmethod
def add_args(arg_parser: argparse.ArgumentParser) -> None:
"\n Override this to add arguments to the CLI argument parser. These args\n will show up when the user invokes ``libcst.tool codemod`` with\n ``--help``. They will also be presented to your class's ``__init__``\n method. So, if you define a command with an argument 'foo', you should also\n have a corresponding 'foo' positional or keyword argument in your\n class's ``__init__`` method.\n "
pass | @staticmethod
def add_args(arg_parser: argparse.ArgumentParser) -> None:
"\n Override this to add arguments to the CLI argument parser. These args\n will show up when the user invokes ``libcst.tool codemod`` with\n ``--help``. They will also be presented to your class's ``__init__``\n method. So, if you define a command with an argument 'foo', you should also\n have a corresponding 'foo' positional or keyword argument in your\n class's ``__init__`` method.\n "
pass<|docstring|>Override this to add arguments to the CLI argument parser. These args
will show up when the user invokes ``libcst.tool codemod`` with
``--help``. They will also be presented to your class's ``__init__``
method. So, if you define a command with an argument 'foo', you should also
have a corresponding 'foo' positional or keyword argument in your
class's ``__init__`` method.<|endoftext|> |
180f5fe5fb058f75111ecb2593a0ba537116919fc788ded2d7561772987014b8 | @abstractmethod
def transform_module_impl(self, tree: Module) -> Module:
'\n Override this with your transform. You should take in the tree, optionally\n mutate it and then return the mutated version. The module reference and all\n calculated metadata are available for the lifetime of this function.\n '
... | Override this with your transform. You should take in the tree, optionally
mutate it and then return the mutated version. The module reference and all
calculated metadata are available for the lifetime of this function. | libcst/codemod/_command.py | transform_module_impl | Instagram/LibCST | 880 | python | @abstractmethod
def transform_module_impl(self, tree: Module) -> Module:
'\n Override this with your transform. You should take in the tree, optionally\n mutate it and then return the mutated version. The module reference and all\n calculated metadata are available for the lifetime of this function.\n '
... | @abstractmethod
def transform_module_impl(self, tree: Module) -> Module:
'\n Override this with your transform. You should take in the tree, optionally\n mutate it and then return the mutated version. The module reference and all\n calculated metadata are available for the lifetime of this function.\n '
...<|docstring|>Override this with your transform. You should take in the tree, optionally
mutate it and then return the mutated version. The module reference and all
calculated metadata are available for the lifetime of this function.<|endoftext|> |
085b981ec8b43303f55ea9740aa6d6d6dabdcd498361d21424514019017cfe05 | @abstractmethod
def get_transforms(self) -> Generator[(Type[Codemod], None, None)]:
'\n A generator which yields one or more subclasses of\n :class:`~libcst.codemod.Codemod`. In the general case, you will usually\n yield a series of classes, but it is possible to programmatically decide\n which classes to yield depending on the contents of the context\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n\n Note that you should yield classes, not instances of classes, as the\n point of :class:`~libcst.codemod.MagicArgsCodemodCommand` is to\n instantiate them for you with the contents of\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n '
... | A generator which yields one or more subclasses of
:class:`~libcst.codemod.Codemod`. In the general case, you will usually
yield a series of classes, but it is possible to programmatically decide
which classes to yield depending on the contents of the context
:attr:`~libcst.codemod.CodemodContext.scratch`.
Note that you should yield classes, not instances of classes, as the
point of :class:`~libcst.codemod.MagicArgsCodemodCommand` is to
instantiate them for you with the contents of
:attr:`~libcst.codemod.CodemodContext.scratch`. | libcst/codemod/_command.py | get_transforms | Instagram/LibCST | 880 | python | @abstractmethod
def get_transforms(self) -> Generator[(Type[Codemod], None, None)]:
'\n A generator which yields one or more subclasses of\n :class:`~libcst.codemod.Codemod`. In the general case, you will usually\n yield a series of classes, but it is possible to programmatically decide\n which classes to yield depending on the contents of the context\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n\n Note that you should yield classes, not instances of classes, as the\n point of :class:`~libcst.codemod.MagicArgsCodemodCommand` is to\n instantiate them for you with the contents of\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n '
... | @abstractmethod
def get_transforms(self) -> Generator[(Type[Codemod], None, None)]:
'\n A generator which yields one or more subclasses of\n :class:`~libcst.codemod.Codemod`. In the general case, you will usually\n yield a series of classes, but it is possible to programmatically decide\n which classes to yield depending on the contents of the context\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n\n Note that you should yield classes, not instances of classes, as the\n point of :class:`~libcst.codemod.MagicArgsCodemodCommand` is to\n instantiate them for you with the contents of\n :attr:`~libcst.codemod.CodemodContext.scratch`.\n '
...<|docstring|>A generator which yields one or more subclasses of
:class:`~libcst.codemod.Codemod`. In the general case, you will usually
yield a series of classes, but it is possible to programmatically decide
which classes to yield depending on the contents of the context
:attr:`~libcst.codemod.CodemodContext.scratch`.
Note that you should yield classes, not instances of classes, as the
point of :class:`~libcst.codemod.MagicArgsCodemodCommand` is to
instantiate them for you with the contents of
:attr:`~libcst.codemod.CodemodContext.scratch`.<|endoftext|> |
c4395fbe5ef6cc471595ca298803691eea6ed88bec1ab6db552f028ffe9e9705 | @app.http_get('/api/architectures')
@app.authenticated
async def get_architectures(request):
'\n Gets a list of all architectures from\n the database.\n\n ---\n description: Returns a list of architectures\n tags:\n - Architectures\n produces:\n - text/json\n responses:\n "200":\n description: successful\n "500":\n description: internal server error\n '
query = request.cirrina.db_session.query(Architecture)
data = {'total_result_count': query.count(), 'results': []}
for architecture in query.filter((Architecture.name != 'all')).all():
data['results'].append({'id': architecture.id, 'name': architecture.name})
return web.json_response(data) | Gets a list of all architectures from
the database.
---
description: Returns a list of architectures
tags:
- Architectures
produces:
- text/json
responses:
"200":
description: successful
"500":
description: internal server error | molior/api/architecture.py | get_architectures | randombenj/molior | 0 | python | @app.http_get('/api/architectures')
@app.authenticated
async def get_architectures(request):
'\n Gets a list of all architectures from\n the database.\n\n ---\n description: Returns a list of architectures\n tags:\n - Architectures\n produces:\n - text/json\n responses:\n "200":\n description: successful\n "500":\n description: internal server error\n '
query = request.cirrina.db_session.query(Architecture)
data = {'total_result_count': query.count(), 'results': []}
for architecture in query.filter((Architecture.name != 'all')).all():
data['results'].append({'id': architecture.id, 'name': architecture.name})
return web.json_response(data) | @app.http_get('/api/architectures')
@app.authenticated
async def get_architectures(request):
'\n Gets a list of all architectures from\n the database.\n\n ---\n description: Returns a list of architectures\n tags:\n - Architectures\n produces:\n - text/json\n responses:\n "200":\n description: successful\n "500":\n description: internal server error\n '
query = request.cirrina.db_session.query(Architecture)
data = {'total_result_count': query.count(), 'results': []}
for architecture in query.filter((Architecture.name != 'all')).all():
data['results'].append({'id': architecture.id, 'name': architecture.name})
return web.json_response(data)<|docstring|>Gets a list of all architectures from
the database.
---
description: Returns a list of architectures
tags:
- Architectures
produces:
- text/json
responses:
"200":
description: successful
"500":
description: internal server error<|endoftext|> |
dcf375c490e7c5191f9b9da8cafa661abe6c9112b4a2b6d71f6a911ed708d6ad | def _showvid(video_name, from_frame=0):
'\n HELPER FUNCTION\n Navigate through video frame by frame from a certain frame.\n\n :param video_name: videopath\n :param from_frame: show vid from this frame\n :return: nothing\n '
cap = cv2.VideoCapture(str(video_name))
cap.set(1, from_frame)
for i in range(from_frame, (from_frame + 999999)):
(ret, frame) = cap.read()
if (not ret):
print('Grab frame unsuccessful. ABORT MISSION!')
break
cv2.imshow(('frame: ' + str(i)), frame)
key = cv2.waitKey()
if (key == ord('q')):
break
cv2.destroyAllWindows()
cv2.destroyAllWindows()
cv2.destroyAllWindows() | HELPER FUNCTION
Navigate through video frame by frame from a certain frame.
:param video_name: videopath
:param from_frame: show vid from this frame
:return: nothing | PredictFeatures/OrientationLabeler.py | _showvid | Iglohut/autoscore_3d | 0 | python | def _showvid(video_name, from_frame=0):
'\n HELPER FUNCTION\n Navigate through video frame by frame from a certain frame.\n\n :param video_name: videopath\n :param from_frame: show vid from this frame\n :return: nothing\n '
cap = cv2.VideoCapture(str(video_name))
cap.set(1, from_frame)
for i in range(from_frame, (from_frame + 999999)):
(ret, frame) = cap.read()
if (not ret):
print('Grab frame unsuccessful. ABORT MISSION!')
break
cv2.imshow(('frame: ' + str(i)), frame)
key = cv2.waitKey()
if (key == ord('q')):
break
cv2.destroyAllWindows()
cv2.destroyAllWindows()
cv2.destroyAllWindows() | def _showvid(video_name, from_frame=0):
'\n HELPER FUNCTION\n Navigate through video frame by frame from a certain frame.\n\n :param video_name: videopath\n :param from_frame: show vid from this frame\n :return: nothing\n '
cap = cv2.VideoCapture(str(video_name))
cap.set(1, from_frame)
for i in range(from_frame, (from_frame + 999999)):
(ret, frame) = cap.read()
if (not ret):
print('Grab frame unsuccessful. ABORT MISSION!')
break
cv2.imshow(('frame: ' + str(i)), frame)
key = cv2.waitKey()
if (key == ord('q')):
break
cv2.destroyAllWindows()
cv2.destroyAllWindows()
cv2.destroyAllWindows()<|docstring|>HELPER FUNCTION
Navigate through video frame by frame from a certain frame.
:param video_name: videopath
:param from_frame: show vid from this frame
:return: nothing<|endoftext|> |
9e369e65be931b91d23a29a3edeff0c7c0a6096f6582921674fbd8d462592ad5 | def _vidlength(video_name):
'\n\n :param video_name: path to video\n :return: number of frames in video\n '
cap = cv2.VideoCapture(str(video_name))
property_id = int(cv2.CAP_PROP_FRAME_COUNT)
length = int(cv2.VideoCapture.get(cap, property_id))
return length | :param video_name: path to video
:return: number of frames in video | PredictFeatures/OrientationLabeler.py | _vidlength | Iglohut/autoscore_3d | 0 | python | def _vidlength(video_name):
'\n\n :param video_name: path to video\n :return: number of frames in video\n '
cap = cv2.VideoCapture(str(video_name))
property_id = int(cv2.CAP_PROP_FRAME_COUNT)
length = int(cv2.VideoCapture.get(cap, property_id))
return length | def _vidlength(video_name):
'\n\n :param video_name: path to video\n :return: number of frames in video\n '
cap = cv2.VideoCapture(str(video_name))
property_id = int(cv2.CAP_PROP_FRAME_COUNT)
length = int(cv2.VideoCapture.get(cap, property_id))
return length<|docstring|>:param video_name: path to video
:return: number of frames in video<|endoftext|> |
dec98e363ba80c4fc077be997195ccf59efa8720611dcebb02e270464ee71a2c | def myKalman(measurements):
'\n This Kalman smoothes a timeseries of (x, y) coordinates for a single limb.\n :param measurements: coordinate tuple list [(x1, y1), ..., (xn, yx)]\n :return: kalman smoothed coordinates list: [[x]], [y]]\n '
initial_state_mean = [measurements[(0, 0)], 0, measurements[(0, 1)], 0]
transition_matrix = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]
observation_matrix = [[1, 0, 0, 0], [0, 0, 1, 0]]
kf1 = KalmanFilter(transition_matrices=transition_matrix, observation_matrices=observation_matrix, initial_state_mean=initial_state_mean)
kf1 = kf1.em(measurements, n_iter=5)
(smoothed_state_means, smoothed_state_covariances) = kf1.smooth(measurements)
return [smoothed_state_means[(:, 0)], smoothed_state_means[(:, 2)]] | This Kalman smoothes a timeseries of (x, y) coordinates for a single limb.
:param measurements: coordinate tuple list [(x1, y1), ..., (xn, yx)]
:return: kalman smoothed coordinates list: [[x]], [y]] | PredictFeatures/OrientationLabeler.py | myKalman | Iglohut/autoscore_3d | 0 | python | def myKalman(measurements):
'\n This Kalman smoothes a timeseries of (x, y) coordinates for a single limb.\n :param measurements: coordinate tuple list [(x1, y1), ..., (xn, yx)]\n :return: kalman smoothed coordinates list: [[x]], [y]]\n '
initial_state_mean = [measurements[(0, 0)], 0, measurements[(0, 1)], 0]
transition_matrix = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]
observation_matrix = [[1, 0, 0, 0], [0, 0, 1, 0]]
kf1 = KalmanFilter(transition_matrices=transition_matrix, observation_matrices=observation_matrix, initial_state_mean=initial_state_mean)
kf1 = kf1.em(measurements, n_iter=5)
(smoothed_state_means, smoothed_state_covariances) = kf1.smooth(measurements)
return [smoothed_state_means[(:, 0)], smoothed_state_means[(:, 2)]] | def myKalman(measurements):
'\n This Kalman smoothes a timeseries of (x, y) coordinates for a single limb.\n :param measurements: coordinate tuple list [(x1, y1), ..., (xn, yx)]\n :return: kalman smoothed coordinates list: [[x]], [y]]\n '
initial_state_mean = [measurements[(0, 0)], 0, measurements[(0, 1)], 0]
transition_matrix = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]
observation_matrix = [[1, 0, 0, 0], [0, 0, 1, 0]]
kf1 = KalmanFilter(transition_matrices=transition_matrix, observation_matrices=observation_matrix, initial_state_mean=initial_state_mean)
kf1 = kf1.em(measurements, n_iter=5)
(smoothed_state_means, smoothed_state_covariances) = kf1.smooth(measurements)
return [smoothed_state_means[(:, 0)], smoothed_state_means[(:, 2)]]<|docstring|>This Kalman smoothes a timeseries of (x, y) coordinates for a single limb.
:param measurements: coordinate tuple list [(x1, y1), ..., (xn, yx)]
:return: kalman smoothed coordinates list: [[x]], [y]]<|endoftext|> |
2227b6f4d1fb6fc20d0ac56e3aec3cbd5e16b044cf89728da70b1d6b2d31048b | def kalman_df(df):
'\n Doe skalman smoothing on all bodyparts of df\n :param df: DataFrame with only bodyparts (no HD yet!)\n :return: smoothed df\n '
cols = df.columns.values.tolist()[1:]
cols = [col for col in cols if ('likelihood' not in col)]
for idx in range(0, len(cols), 2):
bodylimb_x = cols[idx]
bodylimb_y = cols[(idx + 1)]
measurements = np.asarray(list(zip(list(df[bodylimb_x]), list(df[bodylimb_y]))))
estimated_measurements = myKalman(measurements)
estimated_x = estimated_measurements[0]
estimated_y = estimated_measurements[1]
df[bodylimb_x] = estimated_x
df[bodylimb_y] = estimated_y
return df | Doe skalman smoothing on all bodyparts of df
:param df: DataFrame with only bodyparts (no HD yet!)
:return: smoothed df | PredictFeatures/OrientationLabeler.py | kalman_df | Iglohut/autoscore_3d | 0 | python | def kalman_df(df):
'\n Doe skalman smoothing on all bodyparts of df\n :param df: DataFrame with only bodyparts (no HD yet!)\n :return: smoothed df\n '
cols = df.columns.values.tolist()[1:]
cols = [col for col in cols if ('likelihood' not in col)]
for idx in range(0, len(cols), 2):
bodylimb_x = cols[idx]
bodylimb_y = cols[(idx + 1)]
measurements = np.asarray(list(zip(list(df[bodylimb_x]), list(df[bodylimb_y]))))
estimated_measurements = myKalman(measurements)
estimated_x = estimated_measurements[0]
estimated_y = estimated_measurements[1]
df[bodylimb_x] = estimated_x
df[bodylimb_y] = estimated_y
return df | def kalman_df(df):
'\n Doe skalman smoothing on all bodyparts of df\n :param df: DataFrame with only bodyparts (no HD yet!)\n :return: smoothed df\n '
cols = df.columns.values.tolist()[1:]
cols = [col for col in cols if ('likelihood' not in col)]
for idx in range(0, len(cols), 2):
bodylimb_x = cols[idx]
bodylimb_y = cols[(idx + 1)]
measurements = np.asarray(list(zip(list(df[bodylimb_x]), list(df[bodylimb_y]))))
estimated_measurements = myKalman(measurements)
estimated_x = estimated_measurements[0]
estimated_y = estimated_measurements[1]
df[bodylimb_x] = estimated_x
df[bodylimb_y] = estimated_y
return df<|docstring|>Doe skalman smoothing on all bodyparts of df
:param df: DataFrame with only bodyparts (no HD yet!)
:return: smoothed df<|endoftext|> |
6203267fdea6a1c652fd9f304bc6a6b5893415fe605a68363695239b6c6db77b | @MAX_API.doc('predict')
@MAX_API.expect(input_parser)
def post(self):
'Generate audio embedding from input data'
result = {'status': 'error'}
true_start = time.time()
args = input_parser.parse_args()
if ((args['audio'] is None) and (args['url'] is None)):
e = BadRequest()
e.data = {'status': 'error', 'message': 'Need to provide either an audio or url argument'}
raise e
audio_data = {}
uuid_map = {}
if (args['url'] is not None):
url_splt = args['url'].split(',')
for url in url_splt:
audio_data[url] = urllib.request.urlopen(url).read()
else:
audio_data[args['audio'].filename] = args['audio'].read()
print(f'audio_data: {audio_data.keys()}')
for filestring in audio_data.keys():
uuid_map[filestring] = uuid.uuid1()
if ('mp3' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.mp3')
file = open(f'/{uuid_map[filestring]}.mp3', 'wb+')
file.write(audio_data[filestring])
file.close()
elif ('wav' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.wav')
file = open(f'/{uuid_map[filestring]}.wav', 'wb+')
file.write(audio_data[filestring])
file.close()
else:
e = BadRequest()
e.data = {'status': 'error', 'message': 'Invalid file type/extension'}
raise e
start = time.time()
commands = [(f'ffmpeg -i /{uuid_map[x]}.mp3 /{uuid_map[x]}.wav' if ('mp3' in x) else '') for x in uuid_map.keys()]
threads = []
for command in commands:
if (command != ''):
print(f' Running command: {command}')
threads.append(threading.Thread(target=run_sys, args=(command,)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
print(f'Converted mp3 files in {(time.time() - start)}s')
start = time.time()
for filestring in uuid_map.keys():
audio_data[filestring] = open(f'/{uuid_map[filestring]}.wav', 'rb').read()
os.remove(f'/{uuid_map[filestring]}.wav')
if ('mp3' in filestring):
os.remove(f'/{uuid_map[filestring]}.mp3')
print(f'Deleted files in {(time.time() - start)}s')
res = {}
threads = []
for filestring in audio_data.keys():
threads.append(threading.Thread(target=run_model, args=(self.model_wrapper.predict, filestring, audio_data[filestring], res)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
result['embedding'] = res
result['status'] = 'ok'
print(f'Completed processing in {(time.time() - true_start)}s')
return result | Generate audio embedding from input data | api/predict.py | post | dad9489/MAX-Audio-Embedding-Generator | 0 | python | @MAX_API.doc('predict')
@MAX_API.expect(input_parser)
def post(self):
result = {'status': 'error'}
true_start = time.time()
args = input_parser.parse_args()
if ((args['audio'] is None) and (args['url'] is None)):
e = BadRequest()
e.data = {'status': 'error', 'message': 'Need to provide either an audio or url argument'}
raise e
audio_data = {}
uuid_map = {}
if (args['url'] is not None):
url_splt = args['url'].split(',')
for url in url_splt:
audio_data[url] = urllib.request.urlopen(url).read()
else:
audio_data[args['audio'].filename] = args['audio'].read()
print(f'audio_data: {audio_data.keys()}')
for filestring in audio_data.keys():
uuid_map[filestring] = uuid.uuid1()
if ('mp3' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.mp3')
file = open(f'/{uuid_map[filestring]}.mp3', 'wb+')
file.write(audio_data[filestring])
file.close()
elif ('wav' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.wav')
file = open(f'/{uuid_map[filestring]}.wav', 'wb+')
file.write(audio_data[filestring])
file.close()
else:
e = BadRequest()
e.data = {'status': 'error', 'message': 'Invalid file type/extension'}
raise e
start = time.time()
commands = [(f'ffmpeg -i /{uuid_map[x]}.mp3 /{uuid_map[x]}.wav' if ('mp3' in x) else ) for x in uuid_map.keys()]
threads = []
for command in commands:
if (command != ):
print(f' Running command: {command}')
threads.append(threading.Thread(target=run_sys, args=(command,)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
print(f'Converted mp3 files in {(time.time() - start)}s')
start = time.time()
for filestring in uuid_map.keys():
audio_data[filestring] = open(f'/{uuid_map[filestring]}.wav', 'rb').read()
os.remove(f'/{uuid_map[filestring]}.wav')
if ('mp3' in filestring):
os.remove(f'/{uuid_map[filestring]}.mp3')
print(f'Deleted files in {(time.time() - start)}s')
res = {}
threads = []
for filestring in audio_data.keys():
threads.append(threading.Thread(target=run_model, args=(self.model_wrapper.predict, filestring, audio_data[filestring], res)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
result['embedding'] = res
result['status'] = 'ok'
print(f'Completed processing in {(time.time() - true_start)}s')
return result | @MAX_API.doc('predict')
@MAX_API.expect(input_parser)
def post(self):
result = {'status': 'error'}
true_start = time.time()
args = input_parser.parse_args()
if ((args['audio'] is None) and (args['url'] is None)):
e = BadRequest()
e.data = {'status': 'error', 'message': 'Need to provide either an audio or url argument'}
raise e
audio_data = {}
uuid_map = {}
if (args['url'] is not None):
url_splt = args['url'].split(',')
for url in url_splt:
audio_data[url] = urllib.request.urlopen(url).read()
else:
audio_data[args['audio'].filename] = args['audio'].read()
print(f'audio_data: {audio_data.keys()}')
for filestring in audio_data.keys():
uuid_map[filestring] = uuid.uuid1()
if ('mp3' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.mp3')
file = open(f'/{uuid_map[filestring]}.mp3', 'wb+')
file.write(audio_data[filestring])
file.close()
elif ('wav' in filestring):
print(f'Creating file: /{uuid_map[filestring]}.wav')
file = open(f'/{uuid_map[filestring]}.wav', 'wb+')
file.write(audio_data[filestring])
file.close()
else:
e = BadRequest()
e.data = {'status': 'error', 'message': 'Invalid file type/extension'}
raise e
start = time.time()
commands = [(f'ffmpeg -i /{uuid_map[x]}.mp3 /{uuid_map[x]}.wav' if ('mp3' in x) else ) for x in uuid_map.keys()]
threads = []
for command in commands:
if (command != ):
print(f' Running command: {command}')
threads.append(threading.Thread(target=run_sys, args=(command,)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
print(f'Converted mp3 files in {(time.time() - start)}s')
start = time.time()
for filestring in uuid_map.keys():
audio_data[filestring] = open(f'/{uuid_map[filestring]}.wav', 'rb').read()
os.remove(f'/{uuid_map[filestring]}.wav')
if ('mp3' in filestring):
os.remove(f'/{uuid_map[filestring]}.mp3')
print(f'Deleted files in {(time.time() - start)}s')
res = {}
threads = []
for filestring in audio_data.keys():
threads.append(threading.Thread(target=run_model, args=(self.model_wrapper.predict, filestring, audio_data[filestring], res)))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
result['embedding'] = res
result['status'] = 'ok'
print(f'Completed processing in {(time.time() - true_start)}s')
return result<|docstring|>Generate audio embedding from input data<|endoftext|> |
566995742683f5de5548e42f1f4836c041fad16e6bf20e877bc12523313fe440 | def __init__(self, laser_int):
"\n\t\tInitialize class. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tlaser_int: str\n\t\t\tlaser intensity (in filename). e.g. `_0.5mW' \n\t\t\t\n\t\t"
self.dirs_to_plot = None
self.data = None
self.genotypes = None
self.laser_int = laser_int | Initialize class.
Parameters
----------
laser_int: str
laser intensity (in filename). e.g. `_0.5mW' | analysis/plot_fwd_pcts.py | __init__ | faymanns/Qbio_2018 | 0 | python | def __init__(self, laser_int):
"\n\t\tInitialize class. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tlaser_int: str\n\t\t\tlaser intensity (in filename). e.g. `_0.5mW' \n\t\t\t\n\t\t"
self.dirs_to_plot = None
self.data = None
self.genotypes = None
self.laser_int = laser_int | def __init__(self, laser_int):
"\n\t\tInitialize class. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tlaser_int: str\n\t\t\tlaser intensity (in filename). e.g. `_0.5mW' \n\t\t\t\n\t\t"
self.dirs_to_plot = None
self.data = None
self.genotypes = None
self.laser_int = laser_int<|docstring|>Initialize class.
Parameters
----------
laser_int: str
laser intensity (in filename). e.g. `_0.5mW'<|endoftext|> |
7a1c493ccce05b259b9f49525928ef640133598a2b000d6b1cc3436ccfcff9e0 | def get_all_dirs(self, in_dir):
'\n\t\tGet all directories in the analysis output directory corresponding \n\t\tto the desired genotype. All directories containing genotype will\n\t\tbe appended to dirs_to_plot.\n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir: str\n\t\t\tanalysis directory.\n\t\t\n\t\t'
if (not os.path.isdir(in_dir)):
print(('%s does not exist!' % in_dir))
quit()
full_dir = os.path.join(in_dir, '_centroid')
all_dirs = next(os.walk(full_dir))[1]
self.dirs_to_plot = []
self.genotypes = []
for dir in all_dirs:
if (self.laser_int in dir):
self.dirs_to_plot.append(os.path.join(full_dir, dir))
self.genotypes.append(('%s' % dir.replace(self.laser_int, '')))
self.genotypes = sp.array(self.genotypes, dtype='object') | Get all directories in the analysis output directory corresponding
to the desired genotype. All directories containing genotype will
be appended to dirs_to_plot.
Parameters
----------
in_dir: str
analysis directory. | analysis/plot_fwd_pcts.py | get_all_dirs | faymanns/Qbio_2018 | 0 | python | def get_all_dirs(self, in_dir):
'\n\t\tGet all directories in the analysis output directory corresponding \n\t\tto the desired genotype. All directories containing genotype will\n\t\tbe appended to dirs_to_plot.\n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir: str\n\t\t\tanalysis directory.\n\t\t\n\t\t'
if (not os.path.isdir(in_dir)):
print(('%s does not exist!' % in_dir))
quit()
full_dir = os.path.join(in_dir, '_centroid')
all_dirs = next(os.walk(full_dir))[1]
self.dirs_to_plot = []
self.genotypes = []
for dir in all_dirs:
if (self.laser_int in dir):
self.dirs_to_plot.append(os.path.join(full_dir, dir))
self.genotypes.append(('%s' % dir.replace(self.laser_int, )))
self.genotypes = sp.array(self.genotypes, dtype='object') | def get_all_dirs(self, in_dir):
'\n\t\tGet all directories in the analysis output directory corresponding \n\t\tto the desired genotype. All directories containing genotype will\n\t\tbe appended to dirs_to_plot.\n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir: str\n\t\t\tanalysis directory.\n\t\t\n\t\t'
if (not os.path.isdir(in_dir)):
print(('%s does not exist!' % in_dir))
quit()
full_dir = os.path.join(in_dir, '_centroid')
all_dirs = next(os.walk(full_dir))[1]
self.dirs_to_plot = []
self.genotypes = []
for dir in all_dirs:
if (self.laser_int in dir):
self.dirs_to_plot.append(os.path.join(full_dir, dir))
self.genotypes.append(('%s' % dir.replace(self.laser_int, )))
self.genotypes = sp.array(self.genotypes, dtype='object')<|docstring|>Get all directories in the analysis output directory corresponding
to the desired genotype. All directories containing genotype will
be appended to dirs_to_plot.
Parameters
----------
in_dir: str
analysis directory.<|endoftext|> |
86de5e1aa6bdf8bc5a235a335d96e9d0d7f2894efa12f474c37040f070eb11a3 | def plot_pct_fwds(self):
'\n\t\tPlot the pct of forward motion for each genotype.\n\t\t'
Nn = len(self.dirs_to_plot)
for (iD, dir) in enumerate(self.dirs_to_plot):
filename = os.path.join(dir, 'pct_fwd.txt')
tmp_data = sp.loadtxt(filename)
if (self.data is None):
self.data = sp.zeros((Nn, len(tmp_data)))
self.data[(iD, :)] = tmp_data
self.avgs = (sp.average(self.data, axis=1) * 100)
self.stds = (sp.std(self.data, axis=1) * 100)
sort_idxs = sp.argsort(self.avgs)[::(- 1)]
if (sort_idxs[0] != 0):
zero_idx = sp.argwhere((sort_idxs == 0))[0]
change_idx = sort_idxs[zero_idx]
sort_idxs[zero_idx] = sort_idxs[0]
sort_idxs[0] = 0
sort_labels = self.genotypes[sort_idxs]
sort_avgs = self.avgs[sort_idxs]
sort_stds = self.stds[sort_idxs]
fig = plt.figure()
fig.set_size_inches(3, 4)
plt.errorbar(range(Nn), sort_avgs, sort_stds, lw=0, elinewidth=1.5, capsize=5, color='k')
plt.scatter(range(Nn), sort_avgs, c=sp.arange(Nn), cmap=plt.cm.winter, zorder=100, s=30)
plt.ylim(0, 105)
plt.xticks(rotation=90)
plt.xticks(range(Nn), sort_labels) | Plot the pct of forward motion for each genotype. | analysis/plot_fwd_pcts.py | plot_pct_fwds | faymanns/Qbio_2018 | 0 | python | def plot_pct_fwds(self):
'\n\t\t\n\t\t'
Nn = len(self.dirs_to_plot)
for (iD, dir) in enumerate(self.dirs_to_plot):
filename = os.path.join(dir, 'pct_fwd.txt')
tmp_data = sp.loadtxt(filename)
if (self.data is None):
self.data = sp.zeros((Nn, len(tmp_data)))
self.data[(iD, :)] = tmp_data
self.avgs = (sp.average(self.data, axis=1) * 100)
self.stds = (sp.std(self.data, axis=1) * 100)
sort_idxs = sp.argsort(self.avgs)[::(- 1)]
if (sort_idxs[0] != 0):
zero_idx = sp.argwhere((sort_idxs == 0))[0]
change_idx = sort_idxs[zero_idx]
sort_idxs[zero_idx] = sort_idxs[0]
sort_idxs[0] = 0
sort_labels = self.genotypes[sort_idxs]
sort_avgs = self.avgs[sort_idxs]
sort_stds = self.stds[sort_idxs]
fig = plt.figure()
fig.set_size_inches(3, 4)
plt.errorbar(range(Nn), sort_avgs, sort_stds, lw=0, elinewidth=1.5, capsize=5, color='k')
plt.scatter(range(Nn), sort_avgs, c=sp.arange(Nn), cmap=plt.cm.winter, zorder=100, s=30)
plt.ylim(0, 105)
plt.xticks(rotation=90)
plt.xticks(range(Nn), sort_labels) | def plot_pct_fwds(self):
'\n\t\t\n\t\t'
Nn = len(self.dirs_to_plot)
for (iD, dir) in enumerate(self.dirs_to_plot):
filename = os.path.join(dir, 'pct_fwd.txt')
tmp_data = sp.loadtxt(filename)
if (self.data is None):
self.data = sp.zeros((Nn, len(tmp_data)))
self.data[(iD, :)] = tmp_data
self.avgs = (sp.average(self.data, axis=1) * 100)
self.stds = (sp.std(self.data, axis=1) * 100)
sort_idxs = sp.argsort(self.avgs)[::(- 1)]
if (sort_idxs[0] != 0):
zero_idx = sp.argwhere((sort_idxs == 0))[0]
change_idx = sort_idxs[zero_idx]
sort_idxs[zero_idx] = sort_idxs[0]
sort_idxs[0] = 0
sort_labels = self.genotypes[sort_idxs]
sort_avgs = self.avgs[sort_idxs]
sort_stds = self.stds[sort_idxs]
fig = plt.figure()
fig.set_size_inches(3, 4)
plt.errorbar(range(Nn), sort_avgs, sort_stds, lw=0, elinewidth=1.5, capsize=5, color='k')
plt.scatter(range(Nn), sort_avgs, c=sp.arange(Nn), cmap=plt.cm.winter, zorder=100, s=30)
plt.ylim(0, 105)
plt.xticks(rotation=90)
plt.xticks(range(Nn), sort_labels)<|docstring|>Plot the pct of forward motion for each genotype.<|endoftext|> |
4a17b5feb45fdb8db3fecf5fd897c9f9e1b09e25004cf605a9f005a39897df04 | def save_data(self, in_dir):
'\n\t\tOutput fwd and bkwd percent averages and stds. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir : str\n\t\t\tDirectory of where to save data / same as input directory.\n\t\t\n\t\t'
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.png' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file)
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.svg' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file) | Output fwd and bkwd percent averages and stds.
Parameters
----------
in_dir : str
Directory of where to save data / same as input directory. | analysis/plot_fwd_pcts.py | save_data | faymanns/Qbio_2018 | 0 | python | def save_data(self, in_dir):
'\n\t\tOutput fwd and bkwd percent averages and stds. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir : str\n\t\t\tDirectory of where to save data / same as input directory.\n\t\t\n\t\t'
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.png' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file)
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.svg' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file) | def save_data(self, in_dir):
'\n\t\tOutput fwd and bkwd percent averages and stds. \n\t\t\n\t\tParameters\n\t\t----------\n\t\tin_dir : str\n\t\t\tDirectory of where to save data / same as input directory.\n\t\t\n\t\t'
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.png' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file)
out_file = os.path.join(in_dir, '_centroid', ('pct_fwds%s.svg' % self.laser_int))
plt.tight_layout()
plt.savefig(out_file)<|docstring|>Output fwd and bkwd percent averages and stds.
Parameters
----------
in_dir : str
Directory of where to save data / same as input directory.<|endoftext|> |
a3e4201dbb722285f9540dfa52030508336618feb630d5967a2b12fde0e50d91 | def load_test(tstfile):
'Load a test from file.\n\n This reads a test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
row = _nextr(data)
if (row[0] != 'Testtype'):
raise Exception
if (row[1] == 'PumpingTest'):
routine = _load_pumping_test
else:
raise Exception
except Exception:
raise Exception(('loadTest: loading the test ' + 'was not possible'))
return routine(tstfile) | Load a test from file.
This reads a test from a csv file.
Parameters
----------
tstfile : :class:`str`
Path to the file | welltestpy/data/testslib.py | load_test | kinverarity1/welltestpy | 2 | python | def load_test(tstfile):
'Load a test from file.\n\n This reads a test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
row = _nextr(data)
if (row[0] != 'Testtype'):
raise Exception
if (row[1] == 'PumpingTest'):
routine = _load_pumping_test
else:
raise Exception
except Exception:
raise Exception(('loadTest: loading the test ' + 'was not possible'))
return routine(tstfile) | def load_test(tstfile):
'Load a test from file.\n\n This reads a test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
row = _nextr(data)
if (row[0] != 'Testtype'):
raise Exception
if (row[1] == 'PumpingTest'):
routine = _load_pumping_test
else:
raise Exception
except Exception:
raise Exception(('loadTest: loading the test ' + 'was not possible'))
return routine(tstfile)<|docstring|>Load a test from file.
This reads a test from a csv file.
Parameters
----------
tstfile : :class:`str`
Path to the file<|endoftext|> |
c224e5dc5a0224e5f02c3af6d53d508f8705a013e292a8472f4e92475114325f | def _load_pumping_test(tstfile):
'Load a pumping test from file.\n\n This reads a pumping test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
if (next(data)[1] != 'PumpingTest'):
raise Exception
name = next(data)[1]
description = next(data)[1]
timeframe = next(data)[1]
pumpingwell = next(data)[1]
pumpingrate = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferdepth = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferradius = load_var(TxtIO(zfile.open(next(data)[1])))
obscnt = np.int(next(data)[1])
observations = {}
for __ in range(obscnt):
row = _nextr(data)
observations[row[0]] = load_obs(BytIO(zfile.read(row[1])))
pumpingtest = PumpingTest(name, pumpingwell, pumpingrate, observations, aquiferdepth, aquiferradius, description, timeframe)
except Exception:
raise Exception(('loadPumpingTest: loading the pumpingtest ' + 'was not possible'))
return pumpingtest | Load a pumping test from file.
This reads a pumping test from a csv file.
Parameters
----------
tstfile : :class:`str`
Path to the file | welltestpy/data/testslib.py | _load_pumping_test | kinverarity1/welltestpy | 2 | python | def _load_pumping_test(tstfile):
'Load a pumping test from file.\n\n This reads a pumping test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
if (next(data)[1] != 'PumpingTest'):
raise Exception
name = next(data)[1]
description = next(data)[1]
timeframe = next(data)[1]
pumpingwell = next(data)[1]
pumpingrate = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferdepth = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferradius = load_var(TxtIO(zfile.open(next(data)[1])))
obscnt = np.int(next(data)[1])
observations = {}
for __ in range(obscnt):
row = _nextr(data)
observations[row[0]] = load_obs(BytIO(zfile.read(row[1])))
pumpingtest = PumpingTest(name, pumpingwell, pumpingrate, observations, aquiferdepth, aquiferradius, description, timeframe)
except Exception:
raise Exception(('loadPumpingTest: loading the pumpingtest ' + 'was not possible'))
return pumpingtest | def _load_pumping_test(tstfile):
'Load a pumping test from file.\n\n This reads a pumping test from a csv file.\n\n Parameters\n ----------\n tstfile : :class:`str`\n Path to the file\n '
try:
with zipfile.ZipFile(tstfile, 'r') as zfile:
info = TxtIO(zfile.open('info.csv'))
data = csv.reader(info)
if (next(data)[1] != 'PumpingTest'):
raise Exception
name = next(data)[1]
description = next(data)[1]
timeframe = next(data)[1]
pumpingwell = next(data)[1]
pumpingrate = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferdepth = load_var(TxtIO(zfile.open(next(data)[1])))
aquiferradius = load_var(TxtIO(zfile.open(next(data)[1])))
obscnt = np.int(next(data)[1])
observations = {}
for __ in range(obscnt):
row = _nextr(data)
observations[row[0]] = load_obs(BytIO(zfile.read(row[1])))
pumpingtest = PumpingTest(name, pumpingwell, pumpingrate, observations, aquiferdepth, aquiferradius, description, timeframe)
except Exception:
raise Exception(('loadPumpingTest: loading the pumpingtest ' + 'was not possible'))
return pumpingtest<|docstring|>Load a pumping test from file.
This reads a pumping test from a csv file.
Parameters
----------
tstfile : :class:`str`
Path to the file<|endoftext|> |
fab1a3c2c8cb3b3cd725df62c63bae968f3032f896b9750b7935ba59a91de521 | @property
def testtype(self):
':class:`str`: String containing the test type'
return self._testtype | :class:`str`: String containing the test type | welltestpy/data/testslib.py | testtype | kinverarity1/welltestpy | 2 | python | @property
def testtype(self):
return self._testtype | @property
def testtype(self):
return self._testtype<|docstring|>:class:`str`: String containing the test type<|endoftext|> |
ca09f0967451fde4c69efe2576303327263db9621891c5a5a51cb85a52623886 | @property
def wells(self):
':class:`tuple` of :class:`str`: all well names'
tmp = list(self.__observations.keys())
tmp.append(self.pumpingwell)
return tuple(set(tmp)) | :class:`tuple` of :class:`str`: all well names | welltestpy/data/testslib.py | wells | kinverarity1/welltestpy | 2 | python | @property
def wells(self):
tmp = list(self.__observations.keys())
tmp.append(self.pumpingwell)
return tuple(set(tmp)) | @property
def wells(self):
tmp = list(self.__observations.keys())
tmp.append(self.pumpingwell)
return tuple(set(tmp))<|docstring|>:class:`tuple` of :class:`str`: all well names<|endoftext|> |
a8bdf55ac8df6b50afdbdc9b43d7d5cd409b0d3bbaf06312f14152081ad38add | @property
def pumpingrate(self):
':class:`float`: pumping rate at the pumping well'
return self._pumpingrate.value | :class:`float`: pumping rate at the pumping well | welltestpy/data/testslib.py | pumpingrate | kinverarity1/welltestpy | 2 | python | @property
def pumpingrate(self):
return self._pumpingrate.value | @property
def pumpingrate(self):
return self._pumpingrate.value<|docstring|>:class:`float`: pumping rate at the pumping well<|endoftext|> |
fb7212229268e3a199810db49e0bf9143a6f55b60576c9d144d334cf0e723d41 | @property
def aquiferdepth(self):
':class:`float`: aquifer depth at the field site'
return self._aquiferdepth.value | :class:`float`: aquifer depth at the field site | welltestpy/data/testslib.py | aquiferdepth | kinverarity1/welltestpy | 2 | python | @property
def aquiferdepth(self):
return self._aquiferdepth.value | @property
def aquiferdepth(self):
return self._aquiferdepth.value<|docstring|>:class:`float`: aquifer depth at the field site<|endoftext|> |
590e85b2ed67637e8c6832bde79e60cbc6d27f5f01cdce17dce447ecd4010bca | @property
def aquiferradius(self):
':class:`float`: aquifer radius at the field site'
return self._aquiferradius.value | :class:`float`: aquifer radius at the field site | welltestpy/data/testslib.py | aquiferradius | kinverarity1/welltestpy | 2 | python | @property
def aquiferradius(self):
return self._aquiferradius.value | @property
def aquiferradius(self):
return self._aquiferradius.value<|docstring|>:class:`float`: aquifer radius at the field site<|endoftext|> |
682b0e58f04a2e5ae333f66ea5755226b70f4b6399ace49c36a7b1cf574d4aef | @property
def observations(self):
':class:`dict`: observations made at the field site'
return self.__observations | :class:`dict`: observations made at the field site | welltestpy/data/testslib.py | observations | kinverarity1/welltestpy | 2 | python | @property
def observations(self):
return self.__observations | @property
def observations(self):
return self.__observations<|docstring|>:class:`dict`: observations made at the field site<|endoftext|> |
f2c67e29e9f682b617f1ae9a2200a9cc844e640e5c030365758795579d6bbbcb | def add_steady_obs(self, well, observation, description='Steady State Drawdown observation'):
'\n Add steady drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Steady observation"``\n '
obs = StdyHeadObs(well, observation, description)
self.addobservations(obs) | Add steady drawdown observations.
Parameters
----------
well : :class:`str`
well where the observation is made.
observation : :class:`Variable`
Observation.
description : :class:`str`, optional
Description of the Variable. Default: ``"Steady observation"`` | welltestpy/data/testslib.py | add_steady_obs | kinverarity1/welltestpy | 2 | python | def add_steady_obs(self, well, observation, description='Steady State Drawdown observation'):
'\n Add steady drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Steady observation"``\n '
obs = StdyHeadObs(well, observation, description)
self.addobservations(obs) | def add_steady_obs(self, well, observation, description='Steady State Drawdown observation'):
'\n Add steady drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Steady observation"``\n '
obs = StdyHeadObs(well, observation, description)
self.addobservations(obs)<|docstring|>Add steady drawdown observations.
Parameters
----------
well : :class:`str`
well where the observation is made.
observation : :class:`Variable`
Observation.
description : :class:`str`, optional
Description of the Variable. Default: ``"Steady observation"``<|endoftext|> |
4d5a57c2170e6666867fa19c14cdca83e4fd48717fde30c08659b7e6d9bb1f4f | def add_transient_obs(self, well, time, observation, description='Transient Drawdown observation'):
'\n Add transient drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n time : :class:`Variable`\n Time points of observation.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Drawdown observation"``\n '
obs = DrawdownObs(well, time, observation, description)
self.addobservations(obs) | Add transient drawdown observations.
Parameters
----------
well : :class:`str`
well where the observation is made.
time : :class:`Variable`
Time points of observation.
observation : :class:`Variable`
Observation.
description : :class:`str`, optional
Description of the Variable. Default: ``"Drawdown observation"`` | welltestpy/data/testslib.py | add_transient_obs | kinverarity1/welltestpy | 2 | python | def add_transient_obs(self, well, time, observation, description='Transient Drawdown observation'):
'\n Add transient drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n time : :class:`Variable`\n Time points of observation.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Drawdown observation"``\n '
obs = DrawdownObs(well, time, observation, description)
self.addobservations(obs) | def add_transient_obs(self, well, time, observation, description='Transient Drawdown observation'):
'\n Add transient drawdown observations.\n\n Parameters\n ----------\n well : :class:`str`\n well where the observation is made.\n time : :class:`Variable`\n Time points of observation.\n observation : :class:`Variable`\n Observation.\n description : :class:`str`, optional\n Description of the Variable. Default: ``"Drawdown observation"``\n '
obs = DrawdownObs(well, time, observation, description)
self.addobservations(obs)<|docstring|>Add transient drawdown observations.
Parameters
----------
well : :class:`str`
well where the observation is made.
time : :class:`Variable`
Time points of observation.
observation : :class:`Variable`
Observation.
description : :class:`str`, optional
Description of the Variable. Default: ``"Drawdown observation"``<|endoftext|> |
3d18a563517c283907a0a2809b5e7cb7019f91fde132f0a1aad08816b30ad12e | def addobservations(self, obs):
'Add some specified observations.\n\n This will add observations to the pumping test.\n\n Parameters\n ----------\n obs : :class:`dict`\n Observations to be added.\n '
if isinstance(obs, dict):
for k in obs:
if (not isinstance(obs[k], Observation)):
raise ValueError((('PumpingTest_addobservations: some ' + "'observations' are not ") + 'of type Observation'))
if (k in self.observations):
raise ValueError(('PumpingTest_addobservations: some ' + "'observations' are already present"))
for k in obs:
self.__observations[k] = dcopy(obs[k])
elif isinstance(obs, Observation):
if (obs in self.observations):
raise ValueError(('PumpingTest_addobservations: ' + "'observation' are already present"))
self.__observations[obs.name] = dcopy(obs)
else:
raise ValueError(("PumpingTest_addobservations: 'observations' " + 'should be given as dictonary with well as key')) | Add some specified observations.
This will add observations to the pumping test.
Parameters
----------
obs : :class:`dict`
Observations to be added. | welltestpy/data/testslib.py | addobservations | kinverarity1/welltestpy | 2 | python | def addobservations(self, obs):
'Add some specified observations.\n\n This will add observations to the pumping test.\n\n Parameters\n ----------\n obs : :class:`dict`\n Observations to be added.\n '
if isinstance(obs, dict):
for k in obs:
if (not isinstance(obs[k], Observation)):
raise ValueError((('PumpingTest_addobservations: some ' + "'observations' are not ") + 'of type Observation'))
if (k in self.observations):
raise ValueError(('PumpingTest_addobservations: some ' + "'observations' are already present"))
for k in obs:
self.__observations[k] = dcopy(obs[k])
elif isinstance(obs, Observation):
if (obs in self.observations):
raise ValueError(('PumpingTest_addobservations: ' + "'observation' are already present"))
self.__observations[obs.name] = dcopy(obs)
else:
raise ValueError(("PumpingTest_addobservations: 'observations' " + 'should be given as dictonary with well as key')) | def addobservations(self, obs):
'Add some specified observations.\n\n This will add observations to the pumping test.\n\n Parameters\n ----------\n obs : :class:`dict`\n Observations to be added.\n '
if isinstance(obs, dict):
for k in obs:
if (not isinstance(obs[k], Observation)):
raise ValueError((('PumpingTest_addobservations: some ' + "'observations' are not ") + 'of type Observation'))
if (k in self.observations):
raise ValueError(('PumpingTest_addobservations: some ' + "'observations' are already present"))
for k in obs:
self.__observations[k] = dcopy(obs[k])
elif isinstance(obs, Observation):
if (obs in self.observations):
raise ValueError(('PumpingTest_addobservations: ' + "'observation' are already present"))
self.__observations[obs.name] = dcopy(obs)
else:
raise ValueError(("PumpingTest_addobservations: 'observations' " + 'should be given as dictonary with well as key'))<|docstring|>Add some specified observations.
This will add observations to the pumping test.
Parameters
----------
obs : :class:`dict`
Observations to be added.<|endoftext|> |
f818f8f7b7d65db37976e8e70aabc6f381176edd1b2778881b3a8092cbe5184d | def delobservations(self, obs):
'Delete some specified observations.\n\n This will delete observations from the pumping test. You can give a\n list of observations or a single observation by name.\n\n Parameters\n ----------\n obs : :class:`list` of :class:`str` or :class:`str`\n Observations to be deleted.\n '
if isinstance(obs, (list, tuple)):
for k in obs:
if (k in self.observations):
del self.__observations[k]
elif (obs in self.observations):
del self.__observations[obs] | Delete some specified observations.
This will delete observations from the pumping test. You can give a
list of observations or a single observation by name.
Parameters
----------
obs : :class:`list` of :class:`str` or :class:`str`
Observations to be deleted. | welltestpy/data/testslib.py | delobservations | kinverarity1/welltestpy | 2 | python | def delobservations(self, obs):
'Delete some specified observations.\n\n This will delete observations from the pumping test. You can give a\n list of observations or a single observation by name.\n\n Parameters\n ----------\n obs : :class:`list` of :class:`str` or :class:`str`\n Observations to be deleted.\n '
if isinstance(obs, (list, tuple)):
for k in obs:
if (k in self.observations):
del self.__observations[k]
elif (obs in self.observations):
del self.__observations[obs] | def delobservations(self, obs):
'Delete some specified observations.\n\n This will delete observations from the pumping test. You can give a\n list of observations or a single observation by name.\n\n Parameters\n ----------\n obs : :class:`list` of :class:`str` or :class:`str`\n Observations to be deleted.\n '
if isinstance(obs, (list, tuple)):
for k in obs:
if (k in self.observations):
del self.__observations[k]
elif (obs in self.observations):
del self.__observations[obs]<|docstring|>Delete some specified observations.
This will delete observations from the pumping test. You can give a
list of observations or a single observation by name.
Parameters
----------
obs : :class:`list` of :class:`str` or :class:`str`
Observations to be deleted.<|endoftext|> |
ccc554dfb8b981269ec483fa5406778027d6b630ac5d007a26aa080388b7dcb9 | def _addplot(self, plt_ax, wells, exclude=None):
'Generate a plot of the pumping test.\n\n This will plot the pumping test on the given figure axes.\n\n Parameters\n ----------\n ax : :class:`Axes`\n Axes where the plot should be done.\n wells : :class:`dict`\n Dictonary containing the well classes sorted by name.\n exclude: :class:`list`, optional\n List of wells that should be excluded from the plot.\n Default: ``None``\n\n Notes\n -----\n This will be used by the Campaign class.\n '
if (exclude is None):
exclude = []
for k in self.observations:
if (k in exclude):
continue
if (k != self.pumpingwell):
dist = (wells[k] - wells[self.pumpingwell])
else:
dist = wells[self.pumpingwell].radius
if (self.pumpingrate > 0):
displace = np.maximum(self.observations[k].value[1], 0.0)
else:
displace = np.minimum(self.observations[k].value[1], 0.0)
plt_ax.plot(self.observations[k].value[0], displace, linewidth=2, label=(self.observations[k].name + ' r={:1.2f}'.format(dist)))
plt_ax.set_xlabel(self.observations[k].labels[0])
plt_ax.set_ylabel(self.observations[k].labels[1])
plt_ax.set_title(repr(self))
plt_ax.legend(loc='center right', fancybox=True, framealpha=0.75) | Generate a plot of the pumping test.
This will plot the pumping test on the given figure axes.
Parameters
----------
ax : :class:`Axes`
Axes where the plot should be done.
wells : :class:`dict`
Dictonary containing the well classes sorted by name.
exclude: :class:`list`, optional
List of wells that should be excluded from the plot.
Default: ``None``
Notes
-----
This will be used by the Campaign class. | welltestpy/data/testslib.py | _addplot | kinverarity1/welltestpy | 2 | python | def _addplot(self, plt_ax, wells, exclude=None):
'Generate a plot of the pumping test.\n\n This will plot the pumping test on the given figure axes.\n\n Parameters\n ----------\n ax : :class:`Axes`\n Axes where the plot should be done.\n wells : :class:`dict`\n Dictonary containing the well classes sorted by name.\n exclude: :class:`list`, optional\n List of wells that should be excluded from the plot.\n Default: ``None``\n\n Notes\n -----\n This will be used by the Campaign class.\n '
if (exclude is None):
exclude = []
for k in self.observations:
if (k in exclude):
continue
if (k != self.pumpingwell):
dist = (wells[k] - wells[self.pumpingwell])
else:
dist = wells[self.pumpingwell].radius
if (self.pumpingrate > 0):
displace = np.maximum(self.observations[k].value[1], 0.0)
else:
displace = np.minimum(self.observations[k].value[1], 0.0)
plt_ax.plot(self.observations[k].value[0], displace, linewidth=2, label=(self.observations[k].name + ' r={:1.2f}'.format(dist)))
plt_ax.set_xlabel(self.observations[k].labels[0])
plt_ax.set_ylabel(self.observations[k].labels[1])
plt_ax.set_title(repr(self))
plt_ax.legend(loc='center right', fancybox=True, framealpha=0.75) | def _addplot(self, plt_ax, wells, exclude=None):
'Generate a plot of the pumping test.\n\n This will plot the pumping test on the given figure axes.\n\n Parameters\n ----------\n ax : :class:`Axes`\n Axes where the plot should be done.\n wells : :class:`dict`\n Dictonary containing the well classes sorted by name.\n exclude: :class:`list`, optional\n List of wells that should be excluded from the plot.\n Default: ``None``\n\n Notes\n -----\n This will be used by the Campaign class.\n '
if (exclude is None):
exclude = []
for k in self.observations:
if (k in exclude):
continue
if (k != self.pumpingwell):
dist = (wells[k] - wells[self.pumpingwell])
else:
dist = wells[self.pumpingwell].radius
if (self.pumpingrate > 0):
displace = np.maximum(self.observations[k].value[1], 0.0)
else:
displace = np.minimum(self.observations[k].value[1], 0.0)
plt_ax.plot(self.observations[k].value[0], displace, linewidth=2, label=(self.observations[k].name + ' r={:1.2f}'.format(dist)))
plt_ax.set_xlabel(self.observations[k].labels[0])
plt_ax.set_ylabel(self.observations[k].labels[1])
plt_ax.set_title(repr(self))
plt_ax.legend(loc='center right', fancybox=True, framealpha=0.75)<|docstring|>Generate a plot of the pumping test.
This will plot the pumping test on the given figure axes.
Parameters
----------
ax : :class:`Axes`
Axes where the plot should be done.
wells : :class:`dict`
Dictonary containing the well classes sorted by name.
exclude: :class:`list`, optional
List of wells that should be excluded from the plot.
Default: ``None``
Notes
-----
This will be used by the Campaign class.<|endoftext|> |
1f2c27d7bab3679f065cd99372781dce9862c66454b0984ee1538b0f45fb204e | def save(self, path='', name=None):
'Save a pumping test to file.\n\n This writes the variable to a csv file.\n\n Parameters\n ----------\n path : :class:`str`, optional\n Path where the variable should be saved. Default: ``""``\n name : :class:`str`, optional\n Name of the file. If ``None``, the name will be generated by\n ``"Test_"+name``. Default: ``None``\n\n Notes\n -----\n The file will get the suffix ``".tst"``.\n '
path = os.path.normpath(path)
if (not os.path.exists(path)):
os.makedirs(path)
if (name is None):
name = ('Test_' + self.name)
if (name[(- 4):] != '.tst'):
name += '.tst'
name = _formname(name)
patht = os.path.join(path, '.tmptest')
if os.path.exists(patht):
shutil.rmtree(patht, ignore_errors=True)
os.makedirs(patht)
with open(os.path.join(patht, 'info.csv'), 'w') as csvf:
writer = csv.writer(csvf, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(['Testtype', 'PumpingTest'])
writer.writerow(['name', self.name])
writer.writerow(['description', self.description])
writer.writerow(['timeframe', self.timeframe])
writer.writerow(['pumpingwell', self.pumpingwell])
pumprname = (name[:(- 4)] + '_PprVar.var')
aquidname = (name[:(- 4)] + '_AqdVar.var')
aquirname = (name[:(- 4)] + '_AqrVar.var')
writer.writerow(['pumpingrate', pumprname])
self._pumpingrate.save(patht, pumprname)
writer.writerow(['aquiferdepth', aquidname])
self._aquiferdepth.save(patht, aquidname)
writer.writerow(['aquiferradius', aquirname])
self._aquiferradius.save(patht, aquirname)
okeys = tuple(self.observations.keys())
writer.writerow(['Observations', len(okeys)])
obsname = {}
for k in okeys:
obsname[k] = (((name[:(- 4)] + '_') + k) + '_Obs.obs')
writer.writerow([k, obsname[k]])
self.observations[k].save(patht, obsname[k])
with zipfile.ZipFile(os.path.join(path, name), 'w') as zfile:
zfile.write(os.path.join(patht, 'info.csv'), 'info.csv')
zfile.write(os.path.join(patht, pumprname), pumprname)
zfile.write(os.path.join(patht, aquidname), aquidname)
zfile.write(os.path.join(patht, aquirname), aquirname)
for k in okeys:
zfile.write(os.path.join(patht, obsname[k]), obsname[k])
shutil.rmtree(patht, ignore_errors=True) | Save a pumping test to file.
This writes the variable to a csv file.
Parameters
----------
path : :class:`str`, optional
Path where the variable should be saved. Default: ``""``
name : :class:`str`, optional
Name of the file. If ``None``, the name will be generated by
``"Test_"+name``. Default: ``None``
Notes
-----
The file will get the suffix ``".tst"``. | welltestpy/data/testslib.py | save | kinverarity1/welltestpy | 2 | python | def save(self, path=, name=None):
'Save a pumping test to file.\n\n This writes the variable to a csv file.\n\n Parameters\n ----------\n path : :class:`str`, optional\n Path where the variable should be saved. Default: ````\n name : :class:`str`, optional\n Name of the file. If ``None``, the name will be generated by\n ``"Test_"+name``. Default: ``None``\n\n Notes\n -----\n The file will get the suffix ``".tst"``.\n '
path = os.path.normpath(path)
if (not os.path.exists(path)):
os.makedirs(path)
if (name is None):
name = ('Test_' + self.name)
if (name[(- 4):] != '.tst'):
name += '.tst'
name = _formname(name)
patht = os.path.join(path, '.tmptest')
if os.path.exists(patht):
shutil.rmtree(patht, ignore_errors=True)
os.makedirs(patht)
with open(os.path.join(patht, 'info.csv'), 'w') as csvf:
writer = csv.writer(csvf, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(['Testtype', 'PumpingTest'])
writer.writerow(['name', self.name])
writer.writerow(['description', self.description])
writer.writerow(['timeframe', self.timeframe])
writer.writerow(['pumpingwell', self.pumpingwell])
pumprname = (name[:(- 4)] + '_PprVar.var')
aquidname = (name[:(- 4)] + '_AqdVar.var')
aquirname = (name[:(- 4)] + '_AqrVar.var')
writer.writerow(['pumpingrate', pumprname])
self._pumpingrate.save(patht, pumprname)
writer.writerow(['aquiferdepth', aquidname])
self._aquiferdepth.save(patht, aquidname)
writer.writerow(['aquiferradius', aquirname])
self._aquiferradius.save(patht, aquirname)
okeys = tuple(self.observations.keys())
writer.writerow(['Observations', len(okeys)])
obsname = {}
for k in okeys:
obsname[k] = (((name[:(- 4)] + '_') + k) + '_Obs.obs')
writer.writerow([k, obsname[k]])
self.observations[k].save(patht, obsname[k])
with zipfile.ZipFile(os.path.join(path, name), 'w') as zfile:
zfile.write(os.path.join(patht, 'info.csv'), 'info.csv')
zfile.write(os.path.join(patht, pumprname), pumprname)
zfile.write(os.path.join(patht, aquidname), aquidname)
zfile.write(os.path.join(patht, aquirname), aquirname)
for k in okeys:
zfile.write(os.path.join(patht, obsname[k]), obsname[k])
shutil.rmtree(patht, ignore_errors=True) | def save(self, path=, name=None):
'Save a pumping test to file.\n\n This writes the variable to a csv file.\n\n Parameters\n ----------\n path : :class:`str`, optional\n Path where the variable should be saved. Default: ````\n name : :class:`str`, optional\n Name of the file. If ``None``, the name will be generated by\n ``"Test_"+name``. Default: ``None``\n\n Notes\n -----\n The file will get the suffix ``".tst"``.\n '
path = os.path.normpath(path)
if (not os.path.exists(path)):
os.makedirs(path)
if (name is None):
name = ('Test_' + self.name)
if (name[(- 4):] != '.tst'):
name += '.tst'
name = _formname(name)
patht = os.path.join(path, '.tmptest')
if os.path.exists(patht):
shutil.rmtree(patht, ignore_errors=True)
os.makedirs(patht)
with open(os.path.join(patht, 'info.csv'), 'w') as csvf:
writer = csv.writer(csvf, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(['Testtype', 'PumpingTest'])
writer.writerow(['name', self.name])
writer.writerow(['description', self.description])
writer.writerow(['timeframe', self.timeframe])
writer.writerow(['pumpingwell', self.pumpingwell])
pumprname = (name[:(- 4)] + '_PprVar.var')
aquidname = (name[:(- 4)] + '_AqdVar.var')
aquirname = (name[:(- 4)] + '_AqrVar.var')
writer.writerow(['pumpingrate', pumprname])
self._pumpingrate.save(patht, pumprname)
writer.writerow(['aquiferdepth', aquidname])
self._aquiferdepth.save(patht, aquidname)
writer.writerow(['aquiferradius', aquirname])
self._aquiferradius.save(patht, aquirname)
okeys = tuple(self.observations.keys())
writer.writerow(['Observations', len(okeys)])
obsname = {}
for k in okeys:
obsname[k] = (((name[:(- 4)] + '_') + k) + '_Obs.obs')
writer.writerow([k, obsname[k]])
self.observations[k].save(patht, obsname[k])
with zipfile.ZipFile(os.path.join(path, name), 'w') as zfile:
zfile.write(os.path.join(patht, 'info.csv'), 'info.csv')
zfile.write(os.path.join(patht, pumprname), pumprname)
zfile.write(os.path.join(patht, aquidname), aquidname)
zfile.write(os.path.join(patht, aquirname), aquirname)
for k in okeys:
zfile.write(os.path.join(patht, obsname[k]), obsname[k])
shutil.rmtree(patht, ignore_errors=True)<|docstring|>Save a pumping test to file.
This writes the variable to a csv file.
Parameters
----------
path : :class:`str`, optional
Path where the variable should be saved. Default: ``""``
name : :class:`str`, optional
Name of the file. If ``None``, the name will be generated by
``"Test_"+name``. Default: ``None``
Notes
-----
The file will get the suffix ``".tst"``.<|endoftext|> |
96c7322beb5d8ab3fbcfff7907ea73f68352abd03abf88acd321bcb8ec011125 | def __init__(self):
' Initialization '
self._headers = {} | Initialization | wtf/app/response.py | __init__ | ndparker/wtf | 1 | python | def __init__(self):
' '
self._headers = {} | def __init__(self):
' '
self._headers = {}<|docstring|>Initialization<|endoftext|> |
9d0e3b504d397a82ccf39671a8b54bc550ed0933b2548ad66a369f6e7c93ee34 | def __contains__(self, name):
'\n Check if header is already set\n\n :Parameters:\n - `name`: Header name\n\n :Types:\n - `name`: ``str``\n\n :return: Does the header already exist?\n :rtype: ``bool``\n '
return (name.lower() in self._headers) | Check if header is already set
:Parameters:
- `name`: Header name
:Types:
- `name`: ``str``
:return: Does the header already exist?
:rtype: ``bool`` | wtf/app/response.py | __contains__ | ndparker/wtf | 1 | python | def __contains__(self, name):
'\n Check if header is already set\n\n :Parameters:\n - `name`: Header name\n\n :Types:\n - `name`: ``str``\n\n :return: Does the header already exist?\n :rtype: ``bool``\n '
return (name.lower() in self._headers) | def __contains__(self, name):
'\n Check if header is already set\n\n :Parameters:\n - `name`: Header name\n\n :Types:\n - `name`: ``str``\n\n :return: Does the header already exist?\n :rtype: ``bool``\n '
return (name.lower() in self._headers)<|docstring|>Check if header is already set
:Parameters:
- `name`: Header name
:Types:
- `name`: ``str``
:return: Does the header already exist?
:rtype: ``bool``<|endoftext|> |
7995a790dce5ff563348b1458f481dca9267036836b51117aaec0e6eefaab52e | def __iter__(self):
' Header tuple iterator '
for (name, values) in self._headers.iteritems():
for value in values:
(yield (name, value)) | Header tuple iterator | wtf/app/response.py | __iter__ | ndparker/wtf | 1 | python | def __iter__(self):
' '
for (name, values) in self._headers.iteritems():
for value in values:
(yield (name, value)) | def __iter__(self):
' '
for (name, values) in self._headers.iteritems():
for value in values:
(yield (name, value))<|docstring|>Header tuple iterator<|endoftext|> |
2de996f8326151a6c59ebc99a0dd35b53d2a7705e3a428841c666b7f26fda7cb | def get(self, name):
'\n Determine the value list of a header\n\n :Parameters:\n - `name`: The header name\n\n :Types:\n - `name`: ``str``\n\n :return: The value list or ``None``\n :rtype: ``list``\n '
return self._headers.get(name.lower()) | Determine the value list of a header
:Parameters:
- `name`: The header name
:Types:
- `name`: ``str``
:return: The value list or ``None``
:rtype: ``list`` | wtf/app/response.py | get | ndparker/wtf | 1 | python | def get(self, name):
'\n Determine the value list of a header\n\n :Parameters:\n - `name`: The header name\n\n :Types:\n - `name`: ``str``\n\n :return: The value list or ``None``\n :rtype: ``list``\n '
return self._headers.get(name.lower()) | def get(self, name):
'\n Determine the value list of a header\n\n :Parameters:\n - `name`: The header name\n\n :Types:\n - `name`: ``str``\n\n :return: The value list or ``None``\n :rtype: ``list``\n '
return self._headers.get(name.lower())<|docstring|>Determine the value list of a header
:Parameters:
- `name`: The header name
:Types:
- `name`: ``str``
:return: The value list or ``None``
:rtype: ``list``<|endoftext|> |
6f8da64a055ed8e25447a16c80ceed25091bb06c9fc5166f06a12833688c750f | def set(self, name, *values):
"\n Set a header, replacing any same-named header previously set\n\n :Parameters:\n - `name`: The header name\n - `values`: List of values (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers[name.lower()] = list(values) | Set a header, replacing any same-named header previously set
:Parameters:
- `name`: The header name
- `values`: List of values (``('value', ...)``)
:Types:
- `name`: ``str``
- `values`: ``tuple`` | wtf/app/response.py | set | ndparker/wtf | 1 | python | def set(self, name, *values):
"\n Set a header, replacing any same-named header previously set\n\n :Parameters:\n - `name`: The header name\n - `values`: List of values (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers[name.lower()] = list(values) | def set(self, name, *values):
"\n Set a header, replacing any same-named header previously set\n\n :Parameters:\n - `name`: The header name\n - `values`: List of values (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers[name.lower()] = list(values)<|docstring|>Set a header, replacing any same-named header previously set
:Parameters:
- `name`: The header name
- `values`: List of values (``('value', ...)``)
:Types:
- `name`: ``str``
- `values`: ``tuple``<|endoftext|> |
b60b124e21e7b50ce2550d357190308dc55b73ac403a9468b9f8778a6e1f58cf | def add(self, name, *values):
"\n Add a value list to a header\n\n The old values are preserved\n\n :Parameters:\n - `name`: Header name\n - `values`: Values to add (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers.setdefault(name.lower(), []).extend(list(values)) | Add a value list to a header
The old values are preserved
:Parameters:
- `name`: Header name
- `values`: Values to add (``('value', ...)``)
:Types:
- `name`: ``str``
- `values`: ``tuple`` | wtf/app/response.py | add | ndparker/wtf | 1 | python | def add(self, name, *values):
"\n Add a value list to a header\n\n The old values are preserved\n\n :Parameters:\n - `name`: Header name\n - `values`: Values to add (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers.setdefault(name.lower(), []).extend(list(values)) | def add(self, name, *values):
"\n Add a value list to a header\n\n The old values are preserved\n\n :Parameters:\n - `name`: Header name\n - `values`: Values to add (``('value', ...)``)\n\n :Types:\n - `name`: ``str``\n - `values`: ``tuple``\n "
self._headers.setdefault(name.lower(), []).extend(list(values))<|docstring|>Add a value list to a header
The old values are preserved
:Parameters:
- `name`: Header name
- `values`: Values to add (``('value', ...)``)
:Types:
- `name`: ``str``
- `values`: ``tuple``<|endoftext|> |
a98c5f43d93908c32a1c86344580910ee8d1c0df547b5f692f6733a3b6956ed9 | def remove(self, name, value=None):
'\n Remove a header by name (plus optionally by value)\n\n If the header does not exist alrady, it is not an error.\n\n :Parameters:\n - `name`: Header name\n - `value`: Particular value to remove\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n '
name = name.lower()
if (name in self._headers):
if (value is None):
del self._headers[name]
else:
try:
while True:
self._headers[name].remove(value)
except ValueError:
pass | Remove a header by name (plus optionally by value)
If the header does not exist alrady, it is not an error.
:Parameters:
- `name`: Header name
- `value`: Particular value to remove
:Types:
- `name`: ``str``
- `value`: ``str`` | wtf/app/response.py | remove | ndparker/wtf | 1 | python | def remove(self, name, value=None):
'\n Remove a header by name (plus optionally by value)\n\n If the header does not exist alrady, it is not an error.\n\n :Parameters:\n - `name`: Header name\n - `value`: Particular value to remove\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n '
name = name.lower()
if (name in self._headers):
if (value is None):
del self._headers[name]
else:
try:
while True:
self._headers[name].remove(value)
except ValueError:
pass | def remove(self, name, value=None):
'\n Remove a header by name (plus optionally by value)\n\n If the header does not exist alrady, it is not an error.\n\n :Parameters:\n - `name`: Header name\n - `value`: Particular value to remove\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n '
name = name.lower()
if (name in self._headers):
if (value is None):
del self._headers[name]
else:
try:
while True:
self._headers[name].remove(value)
except ValueError:
pass<|docstring|>Remove a header by name (plus optionally by value)
If the header does not exist alrady, it is not an error.
:Parameters:
- `name`: Header name
- `value`: Particular value to remove
:Types:
- `name`: ``str``
- `value`: ``str``<|endoftext|> |
6550ebffe6eab4d2d299ea9a2477bafaf3e67d5a101aeb2074488e0e5af9adf0 | def __init__(self, request, start_response):
'\n Initialization\n\n :Parameters:\n - `request`: Request object\n - `start_response`: WSGI start_response callable\n\n :Types:\n - `request`: `wtf.app.request.Request`\n - `start_response`: ``callable``\n '
self.request = _weakref.proxy(request)
self.http = http
self.status(200)
self.headers = HeaderCollection()
self.content_type('text/html')
def first_write(towrite):
' First write flushes all '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite)
self.write = first_write | Initialization
:Parameters:
- `request`: Request object
- `start_response`: WSGI start_response callable
:Types:
- `request`: `wtf.app.request.Request`
- `start_response`: ``callable`` | wtf/app/response.py | __init__ | ndparker/wtf | 1 | python | def __init__(self, request, start_response):
'\n Initialization\n\n :Parameters:\n - `request`: Request object\n - `start_response`: WSGI start_response callable\n\n :Types:\n - `request`: `wtf.app.request.Request`\n - `start_response`: ``callable``\n '
self.request = _weakref.proxy(request)
self.http = http
self.status(200)
self.headers = HeaderCollection()
self.content_type('text/html')
def first_write(towrite):
' First write flushes all '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite)
self.write = first_write | def __init__(self, request, start_response):
'\n Initialization\n\n :Parameters:\n - `request`: Request object\n - `start_response`: WSGI start_response callable\n\n :Types:\n - `request`: `wtf.app.request.Request`\n - `start_response`: ``callable``\n '
self.request = _weakref.proxy(request)
self.http = http
self.status(200)
self.headers = HeaderCollection()
self.content_type('text/html')
def first_write(towrite):
' First write flushes all '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite)
self.write = first_write<|docstring|>Initialization
:Parameters:
- `request`: Request object
- `start_response`: WSGI start_response callable
:Types:
- `request`: `wtf.app.request.Request`
- `start_response`: ``callable``<|endoftext|> |
41bfb06f6c58f66debd5e95f3f4deedbad1d4dfbb48646a2ad3995ffa7122ac9 | def __getattr__(self, name):
"\n Resolve unknown attributes\n\n We're looking for special env variables inserted by the middleware\n stack: ``wtf.response.<name>``. These are expected to be factories,\n which are lazily initialized with the response object and return\n the actual attribute, which is cached in the response object for\n further use.\n\n :Parameters:\n - `name`: The name to look up\n\n :Types:\n - `name`: ``str``\n\n :return: The attribute in question\n :rtype: any\n\n :Exceptions:\n - `AttributeError`: Attribute could not be resolved\n "
try:
factory = self.request.env[('wtf.response.%s' % name)]
except KeyError:
pass
else:
setattr(self, name, factory(_weakref.proxy(self)))
return super(Response, self).__getattribute__(name) | Resolve unknown attributes
We're looking for special env variables inserted by the middleware
stack: ``wtf.response.<name>``. These are expected to be factories,
which are lazily initialized with the response object and return
the actual attribute, which is cached in the response object for
further use.
:Parameters:
- `name`: The name to look up
:Types:
- `name`: ``str``
:return: The attribute in question
:rtype: any
:Exceptions:
- `AttributeError`: Attribute could not be resolved | wtf/app/response.py | __getattr__ | ndparker/wtf | 1 | python | def __getattr__(self, name):
"\n Resolve unknown attributes\n\n We're looking for special env variables inserted by the middleware\n stack: ``wtf.response.<name>``. These are expected to be factories,\n which are lazily initialized with the response object and return\n the actual attribute, which is cached in the response object for\n further use.\n\n :Parameters:\n - `name`: The name to look up\n\n :Types:\n - `name`: ``str``\n\n :return: The attribute in question\n :rtype: any\n\n :Exceptions:\n - `AttributeError`: Attribute could not be resolved\n "
try:
factory = self.request.env[('wtf.response.%s' % name)]
except KeyError:
pass
else:
setattr(self, name, factory(_weakref.proxy(self)))
return super(Response, self).__getattribute__(name) | def __getattr__(self, name):
"\n Resolve unknown attributes\n\n We're looking for special env variables inserted by the middleware\n stack: ``wtf.response.<name>``. These are expected to be factories,\n which are lazily initialized with the response object and return\n the actual attribute, which is cached in the response object for\n further use.\n\n :Parameters:\n - `name`: The name to look up\n\n :Types:\n - `name`: ``str``\n\n :return: The attribute in question\n :rtype: any\n\n :Exceptions:\n - `AttributeError`: Attribute could not be resolved\n "
try:
factory = self.request.env[('wtf.response.%s' % name)]
except KeyError:
pass
else:
setattr(self, name, factory(_weakref.proxy(self)))
return super(Response, self).__getattribute__(name)<|docstring|>Resolve unknown attributes
We're looking for special env variables inserted by the middleware
stack: ``wtf.response.<name>``. These are expected to be factories,
which are lazily initialized with the response object and return
the actual attribute, which is cached in the response object for
further use.
:Parameters:
- `name`: The name to look up
:Types:
- `name`: ``str``
:return: The attribute in question
:rtype: any
:Exceptions:
- `AttributeError`: Attribute could not be resolved<|endoftext|> |
60c2a5838db4b4ff470fdb067f90d9ae9b041bc2937c92862ffe48167a993e6a | def status(self, status=None, reason=None):
"\n Set/get response status\n\n :Parameters:\n - `status`: Response status code\n - `reason`: Reason phrase\n\n :Types:\n - `status`: ``int``\n - `reason`: ``str``\n\n :return: Tuple of previous status and reason phrase\n (``(int, 'reason')``)\n :rtype: ``tuple``\n "
oldstatus = self._status
if (status is not None):
if (reason is None):
reason = (http.reasons.get(status) or ('Status %d' % status))
status = (int(status), reason)
elif (reason is not None):
status = (oldstatus[0], reason)
self._status = status
return oldstatus | Set/get response status
:Parameters:
- `status`: Response status code
- `reason`: Reason phrase
:Types:
- `status`: ``int``
- `reason`: ``str``
:return: Tuple of previous status and reason phrase
(``(int, 'reason')``)
:rtype: ``tuple`` | wtf/app/response.py | status | ndparker/wtf | 1 | python | def status(self, status=None, reason=None):
"\n Set/get response status\n\n :Parameters:\n - `status`: Response status code\n - `reason`: Reason phrase\n\n :Types:\n - `status`: ``int``\n - `reason`: ``str``\n\n :return: Tuple of previous status and reason phrase\n (``(int, 'reason')``)\n :rtype: ``tuple``\n "
oldstatus = self._status
if (status is not None):
if (reason is None):
reason = (http.reasons.get(status) or ('Status %d' % status))
status = (int(status), reason)
elif (reason is not None):
status = (oldstatus[0], reason)
self._status = status
return oldstatus | def status(self, status=None, reason=None):
"\n Set/get response status\n\n :Parameters:\n - `status`: Response status code\n - `reason`: Reason phrase\n\n :Types:\n - `status`: ``int``\n - `reason`: ``str``\n\n :return: Tuple of previous status and reason phrase\n (``(int, 'reason')``)\n :rtype: ``tuple``\n "
oldstatus = self._status
if (status is not None):
if (reason is None):
reason = (http.reasons.get(status) or ('Status %d' % status))
status = (int(status), reason)
elif (reason is not None):
status = (oldstatus[0], reason)
self._status = status
return oldstatus<|docstring|>Set/get response status
:Parameters:
- `status`: Response status code
- `reason`: Reason phrase
:Types:
- `status`: ``int``
- `reason`: ``str``
:return: Tuple of previous status and reason phrase
(``(int, 'reason')``)
:rtype: ``tuple``<|endoftext|> |
74acc9f0902a3d93638e018df84884a0acd7e32070fa5a7398bb64b02879386f | def cookie(self, name, value, path='/', expires=None, max_age=None, domain=None, secure=None, comment=None, version=None, codec=None):
'\n Set response cookie\n\n :Parameters:\n - `name`: Cookie name\n - `value`: Cookie value (if a codec is given, the type should be\n applicable for the codec encoder).\n - `path`: Valid URL base path for the cookie. It should always be set\n to a reasonable path (at least ``/``), otherwise the cookie will\n only be valid for the current URL and below.\n - `expires`: Expire time of the cookie. If unset or ``None`` the\n cookie is dropped when the browser is closed. See also the\n `max_age` parameter.\n - `max_age`: Max age of the cookie in seconds. If set, make sure it\n matches the expiry time. The difference is that expires will be\n transformed to a HTTP date, while max-age will stay an integer.\n The expires parameter is the older one and better understood by\n the clients out there. For that reason if you set max_age only,\n expires will be set automatically to ``now + max_age``. If unset\n or ``None`` the cookie will be dropped when the browser is closed.\n - `domain`: Valid domain\n - `secure`: Whether this is an SSL-only cookie or not\n - `comment`: Cookie comment\n - `version`: Cookie spec version. See `RFC 2965`_\n - `codec`: Cookie codec to apply. If unset or ``None``, the codec\n specified in the application configuration is applied.\n\n .. _RFC 2965: http://www.ietf.org/rfc/rfc2965.txt\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n - `path`: ``str``\n - `expires`: ``datetime.datetime``\n - `max_age`: ``int``\n - `domain`: ``str``\n - `secure`: ``bool``\n - `comment`: ``str``\n - `version`: ``int``\n - `codec`: `CookieCodecInterface`\n '
if (codec is None):
codec = self.request.env.get('wtf.codec.cookie')
cstring = _httputil.make_cookie(name, value, codec, path=path, expires=expires, max_age=max_age, domain=domain, secure=secure, comment=comment, version=version)
self.headers.add('Set-Cookie', cstring) | Set response cookie
:Parameters:
- `name`: Cookie name
- `value`: Cookie value (if a codec is given, the type should be
applicable for the codec encoder).
- `path`: Valid URL base path for the cookie. It should always be set
to a reasonable path (at least ``/``), otherwise the cookie will
only be valid for the current URL and below.
- `expires`: Expire time of the cookie. If unset or ``None`` the
cookie is dropped when the browser is closed. See also the
`max_age` parameter.
- `max_age`: Max age of the cookie in seconds. If set, make sure it
matches the expiry time. The difference is that expires will be
transformed to a HTTP date, while max-age will stay an integer.
The expires parameter is the older one and better understood by
the clients out there. For that reason if you set max_age only,
expires will be set automatically to ``now + max_age``. If unset
or ``None`` the cookie will be dropped when the browser is closed.
- `domain`: Valid domain
- `secure`: Whether this is an SSL-only cookie or not
- `comment`: Cookie comment
- `version`: Cookie spec version. See `RFC 2965`_
- `codec`: Cookie codec to apply. If unset or ``None``, the codec
specified in the application configuration is applied.
.. _RFC 2965: http://www.ietf.org/rfc/rfc2965.txt
:Types:
- `name`: ``str``
- `value`: ``str``
- `path`: ``str``
- `expires`: ``datetime.datetime``
- `max_age`: ``int``
- `domain`: ``str``
- `secure`: ``bool``
- `comment`: ``str``
- `version`: ``int``
- `codec`: `CookieCodecInterface` | wtf/app/response.py | cookie | ndparker/wtf | 1 | python | def cookie(self, name, value, path='/', expires=None, max_age=None, domain=None, secure=None, comment=None, version=None, codec=None):
'\n Set response cookie\n\n :Parameters:\n - `name`: Cookie name\n - `value`: Cookie value (if a codec is given, the type should be\n applicable for the codec encoder).\n - `path`: Valid URL base path for the cookie. It should always be set\n to a reasonable path (at least ``/``), otherwise the cookie will\n only be valid for the current URL and below.\n - `expires`: Expire time of the cookie. If unset or ``None`` the\n cookie is dropped when the browser is closed. See also the\n `max_age` parameter.\n - `max_age`: Max age of the cookie in seconds. If set, make sure it\n matches the expiry time. The difference is that expires will be\n transformed to a HTTP date, while max-age will stay an integer.\n The expires parameter is the older one and better understood by\n the clients out there. For that reason if you set max_age only,\n expires will be set automatically to ``now + max_age``. If unset\n or ``None`` the cookie will be dropped when the browser is closed.\n - `domain`: Valid domain\n - `secure`: Whether this is an SSL-only cookie or not\n - `comment`: Cookie comment\n - `version`: Cookie spec version. See `RFC 2965`_\n - `codec`: Cookie codec to apply. If unset or ``None``, the codec\n specified in the application configuration is applied.\n\n .. _RFC 2965: http://www.ietf.org/rfc/rfc2965.txt\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n - `path`: ``str``\n - `expires`: ``datetime.datetime``\n - `max_age`: ``int``\n - `domain`: ``str``\n - `secure`: ``bool``\n - `comment`: ``str``\n - `version`: ``int``\n - `codec`: `CookieCodecInterface`\n '
if (codec is None):
codec = self.request.env.get('wtf.codec.cookie')
cstring = _httputil.make_cookie(name, value, codec, path=path, expires=expires, max_age=max_age, domain=domain, secure=secure, comment=comment, version=version)
self.headers.add('Set-Cookie', cstring) | def cookie(self, name, value, path='/', expires=None, max_age=None, domain=None, secure=None, comment=None, version=None, codec=None):
'\n Set response cookie\n\n :Parameters:\n - `name`: Cookie name\n - `value`: Cookie value (if a codec is given, the type should be\n applicable for the codec encoder).\n - `path`: Valid URL base path for the cookie. It should always be set\n to a reasonable path (at least ``/``), otherwise the cookie will\n only be valid for the current URL and below.\n - `expires`: Expire time of the cookie. If unset or ``None`` the\n cookie is dropped when the browser is closed. See also the\n `max_age` parameter.\n - `max_age`: Max age of the cookie in seconds. If set, make sure it\n matches the expiry time. The difference is that expires will be\n transformed to a HTTP date, while max-age will stay an integer.\n The expires parameter is the older one and better understood by\n the clients out there. For that reason if you set max_age only,\n expires will be set automatically to ``now + max_age``. If unset\n or ``None`` the cookie will be dropped when the browser is closed.\n - `domain`: Valid domain\n - `secure`: Whether this is an SSL-only cookie or not\n - `comment`: Cookie comment\n - `version`: Cookie spec version. See `RFC 2965`_\n - `codec`: Cookie codec to apply. If unset or ``None``, the codec\n specified in the application configuration is applied.\n\n .. _RFC 2965: http://www.ietf.org/rfc/rfc2965.txt\n\n :Types:\n - `name`: ``str``\n - `value`: ``str``\n - `path`: ``str``\n - `expires`: ``datetime.datetime``\n - `max_age`: ``int``\n - `domain`: ``str``\n - `secure`: ``bool``\n - `comment`: ``str``\n - `version`: ``int``\n - `codec`: `CookieCodecInterface`\n '
if (codec is None):
codec = self.request.env.get('wtf.codec.cookie')
cstring = _httputil.make_cookie(name, value, codec, path=path, expires=expires, max_age=max_age, domain=domain, secure=secure, comment=comment, version=version)
self.headers.add('Set-Cookie', cstring)<|docstring|>Set response cookie
:Parameters:
- `name`: Cookie name
- `value`: Cookie value (if a codec is given, the type should be
applicable for the codec encoder).
- `path`: Valid URL base path for the cookie. It should always be set
to a reasonable path (at least ``/``), otherwise the cookie will
only be valid for the current URL and below.
- `expires`: Expire time of the cookie. If unset or ``None`` the
cookie is dropped when the browser is closed. See also the
`max_age` parameter.
- `max_age`: Max age of the cookie in seconds. If set, make sure it
matches the expiry time. The difference is that expires will be
transformed to a HTTP date, while max-age will stay an integer.
The expires parameter is the older one and better understood by
the clients out there. For that reason if you set max_age only,
expires will be set automatically to ``now + max_age``. If unset
or ``None`` the cookie will be dropped when the browser is closed.
- `domain`: Valid domain
- `secure`: Whether this is an SSL-only cookie or not
- `comment`: Cookie comment
- `version`: Cookie spec version. See `RFC 2965`_
- `codec`: Cookie codec to apply. If unset or ``None``, the codec
specified in the application configuration is applied.
.. _RFC 2965: http://www.ietf.org/rfc/rfc2965.txt
:Types:
- `name`: ``str``
- `value`: ``str``
- `path`: ``str``
- `expires`: ``datetime.datetime``
- `max_age`: ``int``
- `domain`: ``str``
- `secure`: ``bool``
- `comment`: ``str``
- `version`: ``int``
- `codec`: `CookieCodecInterface`<|endoftext|> |
6486355a8054dac6c69eaa5df8deef458106bec128bfbab80581d0f588bdf7f7 | def content_type(self, ctype=None, charset=None):
'\n Set/get response content type\n\n :Parameters:\n - `ctype`: Content-Type\n - `charset`: Charset\n\n :Types:\n - `ctype`: ``str``\n - `charset`: ``str``\n\n :return: Full previous content type header (maybe ``None``)\n :rtype: ``str``\n '
oldtype = (self.headers.get('content-type') or [None])[0]
if (charset is not None):
charset = ('"%s"' % charset.replace('"', '\\"'))
if (ctype is None):
ctype = (oldtype or 'text/plain')
pos = ctype.find(';')
if (pos > 0):
ctype = ctype[:pos]
ctype = ctype.strip()
ctype = ('%s; charset=%s' % (ctype, charset))
if (ctype is not None):
self.headers.set('content-type', ctype)
return oldtype | Set/get response content type
:Parameters:
- `ctype`: Content-Type
- `charset`: Charset
:Types:
- `ctype`: ``str``
- `charset`: ``str``
:return: Full previous content type header (maybe ``None``)
:rtype: ``str`` | wtf/app/response.py | content_type | ndparker/wtf | 1 | python | def content_type(self, ctype=None, charset=None):
'\n Set/get response content type\n\n :Parameters:\n - `ctype`: Content-Type\n - `charset`: Charset\n\n :Types:\n - `ctype`: ``str``\n - `charset`: ``str``\n\n :return: Full previous content type header (maybe ``None``)\n :rtype: ``str``\n '
oldtype = (self.headers.get('content-type') or [None])[0]
if (charset is not None):
charset = ('"%s"' % charset.replace('"', '\\"'))
if (ctype is None):
ctype = (oldtype or 'text/plain')
pos = ctype.find(';')
if (pos > 0):
ctype = ctype[:pos]
ctype = ctype.strip()
ctype = ('%s; charset=%s' % (ctype, charset))
if (ctype is not None):
self.headers.set('content-type', ctype)
return oldtype | def content_type(self, ctype=None, charset=None):
'\n Set/get response content type\n\n :Parameters:\n - `ctype`: Content-Type\n - `charset`: Charset\n\n :Types:\n - `ctype`: ``str``\n - `charset`: ``str``\n\n :return: Full previous content type header (maybe ``None``)\n :rtype: ``str``\n '
oldtype = (self.headers.get('content-type') or [None])[0]
if (charset is not None):
charset = ('"%s"' % charset.replace('"', '\\"'))
if (ctype is None):
ctype = (oldtype or 'text/plain')
pos = ctype.find(';')
if (pos > 0):
ctype = ctype[:pos]
ctype = ctype.strip()
ctype = ('%s; charset=%s' % (ctype, charset))
if (ctype is not None):
self.headers.set('content-type', ctype)
return oldtype<|docstring|>Set/get response content type
:Parameters:
- `ctype`: Content-Type
- `charset`: Charset
:Types:
- `ctype`: ``str``
- `charset`: ``str``
:return: Full previous content type header (maybe ``None``)
:rtype: ``str``<|endoftext|> |
b975b346cf9fbcb4ec537f7a3b53bb405f9dba842bc31099401995bf5dfb0f64 | def content_length(self, length):
'\n Add content length information\n\n :Parameters:\n - `length`: The expected length in octets\n\n :Types:\n - `length`: ``int``\n '
self.headers.set('Content-Length', str(length)) | Add content length information
:Parameters:
- `length`: The expected length in octets
:Types:
- `length`: ``int`` | wtf/app/response.py | content_length | ndparker/wtf | 1 | python | def content_length(self, length):
'\n Add content length information\n\n :Parameters:\n - `length`: The expected length in octets\n\n :Types:\n - `length`: ``int``\n '
self.headers.set('Content-Length', str(length)) | def content_length(self, length):
'\n Add content length information\n\n :Parameters:\n - `length`: The expected length in octets\n\n :Types:\n - `length`: ``int``\n '
self.headers.set('Content-Length', str(length))<|docstring|>Add content length information
:Parameters:
- `length`: The expected length in octets
:Types:
- `length`: ``int``<|endoftext|> |
00233f77471deaa97827af77026f5c9a4c39776399b6b21f5ad6a52a35030fcb | def last_modified(self, last_modified):
'\n Add last-modified information\n\n :Parameters:\n - `last_modified`: Last modification date (UTC)\n\n :Types:\n - `last_modified`: ``datetime.datetime``\n '
self.headers.set('Last-Modified', _httputil.make_date(last_modified)) | Add last-modified information
:Parameters:
- `last_modified`: Last modification date (UTC)
:Types:
- `last_modified`: ``datetime.datetime`` | wtf/app/response.py | last_modified | ndparker/wtf | 1 | python | def last_modified(self, last_modified):
'\n Add last-modified information\n\n :Parameters:\n - `last_modified`: Last modification date (UTC)\n\n :Types:\n - `last_modified`: ``datetime.datetime``\n '
self.headers.set('Last-Modified', _httputil.make_date(last_modified)) | def last_modified(self, last_modified):
'\n Add last-modified information\n\n :Parameters:\n - `last_modified`: Last modification date (UTC)\n\n :Types:\n - `last_modified`: ``datetime.datetime``\n '
self.headers.set('Last-Modified', _httputil.make_date(last_modified))<|docstring|>Add last-modified information
:Parameters:
- `last_modified`: Last modification date (UTC)
:Types:
- `last_modified`: ``datetime.datetime``<|endoftext|> |
bb29fbd1736fe2029b44c51a44397e4689e5300bfb096f154aa650fa707ebd70 | def cache(self, expiry, audience=None):
'\n Add cache information\n\n :Parameters:\n - `expiry`: Expiry time in seconds from now\n - `audience`: Caching audience; ``private`` or ``public``\n\n :Types:\n - `expiry`: ``int``\n - `audience`: ``str``\n '
expiry = max(0, expiry)
self.headers.set('Expires', _httputil.make_date((_datetime.datetime.utcnow() + _datetime.timedelta(seconds=expiry))))
fields = [('max-age=%s' % expiry)]
if (audience in ('private', 'public')):
fields.append(audience)
self.headers.set('Cache-Control', ', '.join(fields))
if (expiry == 0):
self.headers.set('Pragma', 'no-cache') | Add cache information
:Parameters:
- `expiry`: Expiry time in seconds from now
- `audience`: Caching audience; ``private`` or ``public``
:Types:
- `expiry`: ``int``
- `audience`: ``str`` | wtf/app/response.py | cache | ndparker/wtf | 1 | python | def cache(self, expiry, audience=None):
'\n Add cache information\n\n :Parameters:\n - `expiry`: Expiry time in seconds from now\n - `audience`: Caching audience; ``private`` or ``public``\n\n :Types:\n - `expiry`: ``int``\n - `audience`: ``str``\n '
expiry = max(0, expiry)
self.headers.set('Expires', _httputil.make_date((_datetime.datetime.utcnow() + _datetime.timedelta(seconds=expiry))))
fields = [('max-age=%s' % expiry)]
if (audience in ('private', 'public')):
fields.append(audience)
self.headers.set('Cache-Control', ', '.join(fields))
if (expiry == 0):
self.headers.set('Pragma', 'no-cache') | def cache(self, expiry, audience=None):
'\n Add cache information\n\n :Parameters:\n - `expiry`: Expiry time in seconds from now\n - `audience`: Caching audience; ``private`` or ``public``\n\n :Types:\n - `expiry`: ``int``\n - `audience`: ``str``\n '
expiry = max(0, expiry)
self.headers.set('Expires', _httputil.make_date((_datetime.datetime.utcnow() + _datetime.timedelta(seconds=expiry))))
fields = [('max-age=%s' % expiry)]
if (audience in ('private', 'public')):
fields.append(audience)
self.headers.set('Cache-Control', ', '.join(fields))
if (expiry == 0):
self.headers.set('Pragma', 'no-cache')<|docstring|>Add cache information
:Parameters:
- `expiry`: Expiry time in seconds from now
- `audience`: Caching audience; ``private`` or ``public``
:Types:
- `expiry`: ``int``
- `audience`: ``str``<|endoftext|> |
bb552e0c4c10c0dec5c7604644ab6c09c5a30df1737b7aa061f9dc7fe0386275 | def raise_error(self, status, **param):
'\n Raise an HTTP error\n\n :Parameters:\n - `status`: Status code\n - `param`: Additional parameters for the accompanying class in\n `http_response`. The request object is passed automagically.\n\n :Types:\n - `status`: ``int``\n - `param`: ``dict``\n\n :Exceptions:\n - `KeyError`: The status code is not available\n - `HTTPResponse`: The requested HTTP exception\n '
cls = http.classes[status]
raise cls(self.request, **param) | Raise an HTTP error
:Parameters:
- `status`: Status code
- `param`: Additional parameters for the accompanying class in
`http_response`. The request object is passed automagically.
:Types:
- `status`: ``int``
- `param`: ``dict``
:Exceptions:
- `KeyError`: The status code is not available
- `HTTPResponse`: The requested HTTP exception | wtf/app/response.py | raise_error | ndparker/wtf | 1 | python | def raise_error(self, status, **param):
'\n Raise an HTTP error\n\n :Parameters:\n - `status`: Status code\n - `param`: Additional parameters for the accompanying class in\n `http_response`. The request object is passed automagically.\n\n :Types:\n - `status`: ``int``\n - `param`: ``dict``\n\n :Exceptions:\n - `KeyError`: The status code is not available\n - `HTTPResponse`: The requested HTTP exception\n '
cls = http.classes[status]
raise cls(self.request, **param) | def raise_error(self, status, **param):
'\n Raise an HTTP error\n\n :Parameters:\n - `status`: Status code\n - `param`: Additional parameters for the accompanying class in\n `http_response`. The request object is passed automagically.\n\n :Types:\n - `status`: ``int``\n - `param`: ``dict``\n\n :Exceptions:\n - `KeyError`: The status code is not available\n - `HTTPResponse`: The requested HTTP exception\n '
cls = http.classes[status]
raise cls(self.request, **param)<|docstring|>Raise an HTTP error
:Parameters:
- `status`: Status code
- `param`: Additional parameters for the accompanying class in
`http_response`. The request object is passed automagically.
:Types:
- `status`: ``int``
- `param`: ``dict``
:Exceptions:
- `KeyError`: The status code is not available
- `HTTPResponse`: The requested HTTP exception<|endoftext|> |
38fa2df410bfe3ef949c9f693a5408c1a5202c81bbc45e9b06ca2c7b11c04123 | def raise_redirect(self, location, status=302):
'\n Raise HTTP redirect\n\n :Parameters:\n - `location`: URL to redirect to\n - `status`: Response code\n\n :Types:\n - `location`: ``str``\n - `status`: ``int``\n\n :Exceptions:\n - `http.HTTPRedirectResponse`: The redirect exception\n '
cls = http.classes[status]
assert issubclass(cls, http.HTTPRedirectResponse)
raise cls(self.request, location=location) | Raise HTTP redirect
:Parameters:
- `location`: URL to redirect to
- `status`: Response code
:Types:
- `location`: ``str``
- `status`: ``int``
:Exceptions:
- `http.HTTPRedirectResponse`: The redirect exception | wtf/app/response.py | raise_redirect | ndparker/wtf | 1 | python | def raise_redirect(self, location, status=302):
'\n Raise HTTP redirect\n\n :Parameters:\n - `location`: URL to redirect to\n - `status`: Response code\n\n :Types:\n - `location`: ``str``\n - `status`: ``int``\n\n :Exceptions:\n - `http.HTTPRedirectResponse`: The redirect exception\n '
cls = http.classes[status]
assert issubclass(cls, http.HTTPRedirectResponse)
raise cls(self.request, location=location) | def raise_redirect(self, location, status=302):
'\n Raise HTTP redirect\n\n :Parameters:\n - `location`: URL to redirect to\n - `status`: Response code\n\n :Types:\n - `location`: ``str``\n - `status`: ``int``\n\n :Exceptions:\n - `http.HTTPRedirectResponse`: The redirect exception\n '
cls = http.classes[status]
assert issubclass(cls, http.HTTPRedirectResponse)
raise cls(self.request, location=location)<|docstring|>Raise HTTP redirect
:Parameters:
- `location`: URL to redirect to
- `status`: Response code
:Types:
- `location`: ``str``
- `status`: ``int``
:Exceptions:
- `http.HTTPRedirectResponse`: The redirect exception<|endoftext|> |
5f6aecdf910b2674ddb6bfaea5669c8df48ea89ee9c59feb2f0fcb74c58aadb7 | def raise_basic_auth(self, realm, message=None):
'\n Raise a 401 error for HTTP Basic authentication\n\n :Parameters:\n - `realm`: The realm to authenticate\n - `message`: Optional default overriding message\n\n :Types:\n - `realm`: ``str``\n - `message`: ``str``\n \n :Exceptions:\n - `http.AuthorizationRequired`: The 401 exception\n '
self.raise_error(401, message=message, auth_type='Basic', realm=realm) | Raise a 401 error for HTTP Basic authentication
:Parameters:
- `realm`: The realm to authenticate
- `message`: Optional default overriding message
:Types:
- `realm`: ``str``
- `message`: ``str``
:Exceptions:
- `http.AuthorizationRequired`: The 401 exception | wtf/app/response.py | raise_basic_auth | ndparker/wtf | 1 | python | def raise_basic_auth(self, realm, message=None):
'\n Raise a 401 error for HTTP Basic authentication\n\n :Parameters:\n - `realm`: The realm to authenticate\n - `message`: Optional default overriding message\n\n :Types:\n - `realm`: ``str``\n - `message`: ``str``\n \n :Exceptions:\n - `http.AuthorizationRequired`: The 401 exception\n '
self.raise_error(401, message=message, auth_type='Basic', realm=realm) | def raise_basic_auth(self, realm, message=None):
'\n Raise a 401 error for HTTP Basic authentication\n\n :Parameters:\n - `realm`: The realm to authenticate\n - `message`: Optional default overriding message\n\n :Types:\n - `realm`: ``str``\n - `message`: ``str``\n \n :Exceptions:\n - `http.AuthorizationRequired`: The 401 exception\n '
self.raise_error(401, message=message, auth_type='Basic', realm=realm)<|docstring|>Raise a 401 error for HTTP Basic authentication
:Parameters:
- `realm`: The realm to authenticate
- `message`: Optional default overriding message
:Types:
- `realm`: ``str``
- `message`: ``str``
:Exceptions:
- `http.AuthorizationRequired`: The 401 exception<|endoftext|> |
4399788d10ed577e07442c3f70ee0a7f55d1f227bcf5fdc0e677969a3cdfd8e2 | def first_write(towrite):
' First write flushes all '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite) | First write flushes all | wtf/app/response.py | first_write | ndparker/wtf | 1 | python | def first_write(towrite):
' '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite) | def first_write(towrite):
' '
if (self.write == first_write):
resp_code = ('%03d %s' % self._status)
headers = list(self.headers)
self.write = start_response(resp_code, headers)
return self.write(towrite)<|docstring|>First write flushes all<|endoftext|> |
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