hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bd08982bcc4692244ff83ef046ae6dc82c4489af
| 35,642
|
py
|
Python
|
spark_fhir_schemas/stu3/complex_types/medicationrequest.py
|
icanbwell/SparkFhirSchemas
|
8c828313c39850b65f8676e67f526ee92b7d624e
|
[
"Apache-2.0"
] | 2
|
2020-10-31T23:25:01.000Z
|
2021-06-09T14:12:42.000Z
|
spark_fhir_schemas/stu3/complex_types/medicationrequest.py
|
icanbwell/SparkFhirSchemas
|
8c828313c39850b65f8676e67f526ee92b7d624e
|
[
"Apache-2.0"
] | null | null | null |
spark_fhir_schemas/stu3/complex_types/medicationrequest.py
|
icanbwell/SparkFhirSchemas
|
8c828313c39850b65f8676e67f526ee92b7d624e
|
[
"Apache-2.0"
] | null | null | null |
from typing import Union, List, Optional
from pyspark.sql.types import StructType, StructField, StringType, ArrayType, DataType
# This file is auto-generated by generate_schema so do not edit manually
# noinspection PyPep8Naming
class MedicationRequestSchema:
"""
An order or request for both supply of the medication and the instructions for
administration of the medication to a patient. The resource is called
"MedicationRequest" rather than "MedicationPrescription" or "MedicationOrder"
to generalize the use across inpatient and outpatient settings, including care
plans, etc., and to harmonize with workflow patterns.
"""
# noinspection PyDefaultArgument
@staticmethod
def get_schema(
max_nesting_depth: Optional[int] = 6,
nesting_depth: int = 0,
nesting_list: List[str] = [],
max_recursion_limit: Optional[int] = 2,
include_extension: Optional[bool] = False,
extension_fields: Optional[List[str]] = [
"valueBoolean",
"valueCode",
"valueDate",
"valueDateTime",
"valueDecimal",
"valueId",
"valueInteger",
"valuePositiveInt",
"valueString",
"valueTime",
"valueUnsignedInt",
"valueUri",
"valueQuantity",
],
extension_depth: int = 0,
max_extension_depth: Optional[int] = 2,
) -> Union[StructType, DataType]:
"""
An order or request for both supply of the medication and the instructions for
administration of the medication to a patient. The resource is called
"MedicationRequest" rather than "MedicationPrescription" or "MedicationOrder"
to generalize the use across inpatient and outpatient settings, including care
plans, etc., and to harmonize with workflow patterns.
id: The logical id of the resource, as used in the URL for the resource. Once
assigned, this value never changes.
extension: May be used to represent additional information that is not part of the basic
definition of the resource. In order to make the use of extensions safe and
manageable, there is a strict set of governance applied to the definition and
use of extensions. Though any implementer is allowed to define an extension,
there is a set of requirements that SHALL be met as part of the definition of
the extension.
meta: The metadata about the resource. This is content that is maintained by the
infrastructure. Changes to the content may not always be associated with
version changes to the resource.
implicitRules: A reference to a set of rules that were followed when the resource was
constructed, and which must be understood when processing the content.
language: The base language in which the resource is written.
text: A human-readable narrative that contains a summary of the resource, and may be
used to represent the content of the resource to a human. The narrative need
not encode all the structured data, but is required to contain sufficient
detail to make it "clinically safe" for a human to just read the narrative.
Resource definitions may define what content should be represented in the
narrative to ensure clinical safety.
contained: These resources do not have an independent existence apart from the resource
that contains them - they cannot be identified independently, and nor can they
have their own independent transaction scope.
resourceType: This is a MedicationRequest resource
identifier: This records identifiers associated with this medication request that are
defined by business processes and/or used to refer to it when a direct URL
reference to the resource itself is not appropriate. For example a re-
imbursement system might issue its own id for each prescription that is
created. This is particularly important where FHIR only provides part of an
entire workflow process where records must be tracked through an entire
system.
definition: Protocol or definition followed by this request.
basedOn: A plan or request that is fulfilled in whole or in part by this medication
request.
groupIdentifier: A shared identifier common to all requests that were authorized more or less
simultaneously by a single author, representing the identifier of the
requisition or prescription.
status: A code specifying the current state of the order. Generally this will be
active or completed state.
intent: Whether the request is a proposal, plan, or an original order.
category: Indicates the type of medication order and where the medication is expected to
be consumed or administered.
priority: Indicates how quickly the Medication Request should be addressed with respect
to other requests.
medicationCodeableConcept: Identifies the medication being requested. This is a link to a resource that
represents the medication which may be the details of the medication or simply
an attribute carrying a code that identifies the medication from a known list
of medications.
medicationReference: Identifies the medication being requested. This is a link to a resource that
represents the medication which may be the details of the medication or simply
an attribute carrying a code that identifies the medication from a known list
of medications.
subject: A link to a resource representing the person or set of individuals to whom the
medication will be given.
context: A link to an encounter, or episode of care, that identifies the particular
occurrence or set occurrences of contact between patient and health care
provider.
supportingInformation: Include additional information (for example, patient height and weight) that
supports the ordering of the medication.
authoredOn: The date (and perhaps time) when the prescription was initially written or
authored on.
requester: The individual, organization or device that initiated the request and has
responsibility for its activation.
recorder: The person who entered the order on behalf of another individual for example
in the case of a verbal or a telephone order.
reasonCode: The reason or the indication for ordering the medication.
reasonReference: Condition or observation that supports why the medication was ordered.
note: Extra information about the prescription that could not be conveyed by the
other attributes.
dosageInstruction: Indicates how the medication is to be used by the patient.
dispenseRequest: Indicates the specific details for the dispense or medication supply part of a
medication request (also known as a Medication Prescription or Medication
Order). Note that this information is not always sent with the order. There
may be in some settings (e.g. hospitals) institutional or system support for
completing the dispense details in the pharmacy department.
substitution: Indicates whether or not substitution can or should be part of the dispense.
In some cases substitution must happen, in other cases substitution must not
happen. This block explains the prescriber's intent. If nothing is specified
substitution may be done.
priorPrescription: A link to a resource representing an earlier order related order or
prescription.
detectedIssue: Indicates an actual or potential clinical issue with or between one or more
active or proposed clinical actions for a patient; e.g. Drug-drug interaction,
duplicate therapy, dosage alert etc.
eventHistory: Links to Provenance records for past versions of this resource or fulfilling
request or event resources that identify key state transitions or updates that
are likely to be relevant to a user looking at the current version of the
resource.
"""
from spark_fhir_schemas.stu3.complex_types.extension import ExtensionSchema
from spark_fhir_schemas.stu3.complex_types.meta import MetaSchema
from spark_fhir_schemas.stu3.complex_types.narrative import NarrativeSchema
from spark_fhir_schemas.stu3.simple_types.resourcelist import ResourceListSchema
from spark_fhir_schemas.stu3.complex_types.identifier import IdentifierSchema
from spark_fhir_schemas.stu3.complex_types.reference import ReferenceSchema
from spark_fhir_schemas.stu3.complex_types.codeableconcept import (
CodeableConceptSchema,
)
from spark_fhir_schemas.stu3.complex_types.medicationrequest_requester import (
MedicationRequest_RequesterSchema,
)
from spark_fhir_schemas.stu3.complex_types.annotation import AnnotationSchema
from spark_fhir_schemas.stu3.complex_types.dosage import DosageSchema
from spark_fhir_schemas.stu3.complex_types.medicationrequest_dispenserequest import (
MedicationRequest_DispenseRequestSchema,
)
from spark_fhir_schemas.stu3.complex_types.medicationrequest_substitution import (
MedicationRequest_SubstitutionSchema,
)
if (
max_recursion_limit
and nesting_list.count("MedicationRequest") >= max_recursion_limit
) or (max_nesting_depth and nesting_depth >= max_nesting_depth):
return StructType([StructField("id", StringType(), True)])
# add my name to recursion list for later
my_nesting_list: List[str] = nesting_list + ["MedicationRequest"]
schema = StructType(
[
# The logical id of the resource, as used in the URL for the resource. Once
# assigned, this value never changes.
StructField("id", StringType(), True),
# May be used to represent additional information that is not part of the basic
# definition of the resource. In order to make the use of extensions safe and
# manageable, there is a strict set of governance applied to the definition and
# use of extensions. Though any implementer is allowed to define an extension,
# there is a set of requirements that SHALL be met as part of the definition of
# the extension.
StructField(
"extension",
ArrayType(
ExtensionSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# The metadata about the resource. This is content that is maintained by the
# infrastructure. Changes to the content may not always be associated with
# version changes to the resource.
StructField(
"meta",
MetaSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# A reference to a set of rules that were followed when the resource was
# constructed, and which must be understood when processing the content.
StructField("implicitRules", StringType(), True),
# The base language in which the resource is written.
StructField("language", StringType(), True),
# A human-readable narrative that contains a summary of the resource, and may be
# used to represent the content of the resource to a human. The narrative need
# not encode all the structured data, but is required to contain sufficient
# detail to make it "clinically safe" for a human to just read the narrative.
# Resource definitions may define what content should be represented in the
# narrative to ensure clinical safety.
StructField(
"text",
NarrativeSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# These resources do not have an independent existence apart from the resource
# that contains them - they cannot be identified independently, and nor can they
# have their own independent transaction scope.
StructField(
"contained",
ArrayType(
ResourceListSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# This is a MedicationRequest resource
StructField("resourceType", StringType(), True),
# This records identifiers associated with this medication request that are
# defined by business processes and/or used to refer to it when a direct URL
# reference to the resource itself is not appropriate. For example a re-
# imbursement system might issue its own id for each prescription that is
# created. This is particularly important where FHIR only provides part of an
# entire workflow process where records must be tracked through an entire
# system.
StructField(
"identifier",
ArrayType(
IdentifierSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Protocol or definition followed by this request.
StructField(
"definition",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# A plan or request that is fulfilled in whole or in part by this medication
# request.
StructField(
"basedOn",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# A shared identifier common to all requests that were authorized more or less
# simultaneously by a single author, representing the identifier of the
# requisition or prescription.
StructField(
"groupIdentifier",
IdentifierSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# A code specifying the current state of the order. Generally this will be
# active or completed state.
StructField("status", StringType(), True),
# Whether the request is a proposal, plan, or an original order.
StructField("intent", StringType(), True),
# Indicates the type of medication order and where the medication is expected to
# be consumed or administered.
StructField(
"category",
CodeableConceptSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# Indicates how quickly the Medication Request should be addressed with respect
# to other requests.
StructField("priority", StringType(), True),
# Identifies the medication being requested. This is a link to a resource that
# represents the medication which may be the details of the medication or simply
# an attribute carrying a code that identifies the medication from a known list
# of medications.
StructField(
"medicationCodeableConcept",
CodeableConceptSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# Identifies the medication being requested. This is a link to a resource that
# represents the medication which may be the details of the medication or simply
# an attribute carrying a code that identifies the medication from a known list
# of medications.
StructField(
"medicationReference",
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# A link to a resource representing the person or set of individuals to whom the
# medication will be given.
StructField(
"subject",
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# A link to an encounter, or episode of care, that identifies the particular
# occurrence or set occurrences of contact between patient and health care
# provider.
StructField(
"context",
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# Include additional information (for example, patient height and weight) that
# supports the ordering of the medication.
StructField(
"supportingInformation",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# The date (and perhaps time) when the prescription was initially written or
# authored on.
StructField("authoredOn", StringType(), True),
# The individual, organization or device that initiated the request and has
# responsibility for its activation.
StructField(
"requester",
MedicationRequest_RequesterSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# The person who entered the order on behalf of another individual for example
# in the case of a verbal or a telephone order.
StructField(
"recorder",
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# The reason or the indication for ordering the medication.
StructField(
"reasonCode",
ArrayType(
CodeableConceptSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Condition or observation that supports why the medication was ordered.
StructField(
"reasonReference",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Extra information about the prescription that could not be conveyed by the
# other attributes.
StructField(
"note",
ArrayType(
AnnotationSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Indicates how the medication is to be used by the patient.
StructField(
"dosageInstruction",
ArrayType(
DosageSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Indicates the specific details for the dispense or medication supply part of a
# medication request (also known as a Medication Prescription or Medication
# Order). Note that this information is not always sent with the order. There
# may be in some settings (e.g. hospitals) institutional or system support for
# completing the dispense details in the pharmacy department.
StructField(
"dispenseRequest",
MedicationRequest_DispenseRequestSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# Indicates whether or not substitution can or should be part of the dispense.
# In some cases substitution must happen, in other cases substitution must not
# happen. This block explains the prescriber's intent. If nothing is specified
# substitution may be done.
StructField(
"substitution",
MedicationRequest_SubstitutionSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# A link to a resource representing an earlier order related order or
# prescription.
StructField(
"priorPrescription",
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth + 1,
max_extension_depth=max_extension_depth,
),
True,
),
# Indicates an actual or potential clinical issue with or between one or more
# active or proposed clinical actions for a patient; e.g. Drug-drug interaction,
# duplicate therapy, dosage alert etc.
StructField(
"detectedIssue",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
# Links to Provenance records for past versions of this resource or fulfilling
# request or event resources that identify key state transitions or updates that
# are likely to be relevant to a user looking at the current version of the
# resource.
StructField(
"eventHistory",
ArrayType(
ReferenceSchema.get_schema(
max_nesting_depth=max_nesting_depth,
nesting_depth=nesting_depth + 1,
nesting_list=my_nesting_list,
max_recursion_limit=max_recursion_limit,
include_extension=include_extension,
extension_fields=extension_fields,
extension_depth=extension_depth,
max_extension_depth=max_extension_depth,
)
),
True,
),
]
)
if not include_extension:
schema.fields = [
c
if c.name != "extension"
else StructField("extension", StringType(), True)
for c in schema.fields
]
return schema
| 52.108187
| 111
| 0.558078
| 3,351
| 35,642
| 5.735303
| 0.13011
| 0.06556
| 0.041365
| 0.062438
| 0.853895
| 0.846662
| 0.846662
| 0.82741
| 0.819137
| 0.809928
| 0
| 0.002636
| 0.403962
| 35,642
| 683
| 112
| 52.18448
| 0.902043
| 0.340722
| 0
| 0.732143
| 1
| 0
| 0.024453
| 0.002034
| 0
| 0
| 0
| 0
| 0
| 1
| 0.002232
| false
| 0
| 0.03125
| 0
| 0.040179
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
9526539c5b7d7479924cdfd05109651ccbaa5924
| 11,103
|
py
|
Python
|
localedb/mockup.py
|
cuker/django-localedb
|
e6ff25af28301fc6c4f1a99a6681d2bba2ed35dc
|
[
"BSD-3-Clause"
] | 2
|
2015-05-18T13:49:30.000Z
|
2015-05-18T14:37:26.000Z
|
localedb/mockup.py
|
cuker/django-localedb
|
e6ff25af28301fc6c4f1a99a6681d2bba2ed35dc
|
[
"BSD-3-Clause"
] | null | null | null |
localedb/mockup.py
|
cuker/django-localedb
|
e6ff25af28301fc6c4f1a99a6681d2bba2ed35dc
|
[
"BSD-3-Clause"
] | null | null | null |
CURRENCY_DATA = {
('de_DE.UTF-8', -57.049999999999997, True, True, True): u'-EUR 57,05',
('de_DE.UTF-8', -57.000050000000002, False, False, False): u'-57,00',
('de_DE.UTF-8', -57.000050000000002, True, False, False): u'-Eu57,00',
('de_DE.UTF-8', -57.000050000000002, True, False, True): u'-EUR 57,00',
('de_DE.UTF-8', -57.000050000000002, True, True, False): u'-Eu57,00',
('de_DE.UTF-8', 5, False, False, False): u'5,00',
('de_DE.UTF-8', 5, True, False, False): u'Eu5,00',
('de_DE.UTF-8', 5, True, False, True): u'EUR 5,00',
('de_DE.UTF-8', 5, True, True, False): u'Eu5,00',
('de_DE.UTF-8', 500000, False, False, False): u'500000,00',
('de_DE.UTF-8', 500000, True, False, False): u'Eu500000,00',
('de_DE.UTF-8', 500000, True, False, True): u'EUR 500000,00',
('de_DE.UTF-8', 500000, True, True, False): u'Eu500.000,00',
('en_US.UTF-8', -57.049999999999997, True, True, True): u'-USD 57.05',
('en_US.UTF-8', -57.000050000000002, False, False, False): u'-57.00',
('en_US.UTF-8', -57.000050000000002, True, False, False): u'-$57.00',
('en_US.UTF-8', -57.000050000000002, True, False, True): u'-USD 57.00',
('en_US.UTF-8', -57.000050000000002, True, True, False): u'-$57.00',
('en_US.UTF-8', 5, False, False, False): u'5.00',
('en_US.UTF-8', 5, True, False, False): u'$5.00',
('en_US.UTF-8', 5, True, False, True): u'USD 5.00',
('en_US.UTF-8', 5, True, True, False): u'$5.00',
('en_US.UTF-8', 500000, False, False, False): u'500000.00',
('en_US.UTF-8', 500000, True, False, False): u'$500000.00',
('en_US.UTF-8', 500000, True, False, True): u'USD 500000.00',
('en_US.UTF-8', 500000, True, True, False): u'$500,000.00',
('fr_FR.UTF-8', -57.049999999999997, True, True, True): u'57,05 EUR -',
('fr_FR.UTF-8', -57.000050000000002, False, False, False): u'57,00-',
('fr_FR.UTF-8', -57.000050000000002, True, False, False): u'57,00 Eu-',
('fr_FR.UTF-8', -57.000050000000002, True, False, True): u'57,00 EUR -',
('fr_FR.UTF-8', -57.000050000000002, True, True, False): u'57,00 Eu-',
('fr_FR.UTF-8', 5, False, False, False): u'5,00',
('fr_FR.UTF-8', 5, True, False, False): u'5,00 Eu',
('fr_FR.UTF-8', 5, True, False, True): u'5,00 EUR ',
('fr_FR.UTF-8', 5, True, True, False): u'5,00 Eu',
('fr_FR.UTF-8', 500000, False, False, False): u'500000,00',
('fr_FR.UTF-8', 500000, True, False, False): u'500000,00 Eu',
('fr_FR.UTF-8', 500000, True, False, True): u'500000,00 EUR ',
('fr_FR.UTF-8', 500000, True, True, False): u'500000,00 Eu',
('hy_AM.UTF-8', -57.049999999999997, True, True, True): u'-57.05 AMD ',
('hy_AM.UTF-8', -57.000050000000002, False, False, False): u'-57.00',
('hy_AM.UTF-8', -57.000050000000002, True, False, False): u'-57.00 \u0534\u0550 ',
('hy_AM.UTF-8', -57.000050000000002, True, False, True): u'-57.00 AMD ',
('hy_AM.UTF-8', -57.000050000000002, True, True, False): u'-57.00 \u0534\u0550 ',
('hy_AM.UTF-8', 5, False, False, False): u'5.00',
('hy_AM.UTF-8', 5, True, False, False): u'5.00 \u0534\u0550 ',
('hy_AM.UTF-8', 5, True, False, True): u'5.00 AMD ',
('hy_AM.UTF-8', 5, True, True, False): u'5.00 \u0534\u0550 ',
('hy_AM.UTF-8', 500000, False, False, False): u'500000.00',
('hy_AM.UTF-8', 500000, True, False, False): u'500000.00 \u0534\u0550 ',
('hy_AM.UTF-8', 500000, True, False, True): u'500000.00 AMD ',
('hy_AM.UTF-8', 500000, True, True, False): u'500,000.00 \u0534\u0550 ',
('it_IT.UTF-8', -57.049999999999997, True, True, True): u'-EUR 57,05',
('it_IT.UTF-8', -57.000050000000002, False, False, False): u'-57,00',
('it_IT.UTF-8', -57.000050000000002, True, False, False): u'-Eu 57,00',
('it_IT.UTF-8', -57.000050000000002, True, False, True): u'-EUR 57,00',
('it_IT.UTF-8', -57.000050000000002, True, True, False): u'-Eu 57,00',
('it_IT.UTF-8', 5, False, False, False): u'5,00',
('it_IT.UTF-8', 5, True, False, False): u'Eu 5,00',
('it_IT.UTF-8', 5, True, False, True): u'EUR 5,00',
('it_IT.UTF-8', 5, True, True, False): u'Eu 5,00',
('it_IT.UTF-8', 500000, False, False, False): u'500000,00',
('it_IT.UTF-8', 500000, True, False, False): u'Eu 500000,00',
('it_IT.UTF-8', 500000, True, False, True): u'EUR 500000,00',
('it_IT.UTF-8', 500000, True, True, False): u'Eu 500.000,00',
('ja_JP.UTF-8', -57.049999999999997, True, True, True): u'JPY 57-',
('ja_JP.UTF-8', -57.000050000000002, False, False, False): u'57-',
('ja_JP.UTF-8', -57.000050000000002, True, False, False): u'\xa557-',
('ja_JP.UTF-8', -57.000050000000002, True, False, True): u'JPY 57-',
('ja_JP.UTF-8', -57.000050000000002, True, True, False): u'\xa557-',
('ja_JP.UTF-8', 5, False, False, False): u'5',
('ja_JP.UTF-8', 5, True, False, False): u'\xa55',
('ja_JP.UTF-8', 5, True, False, True): u'JPY 5',
('ja_JP.UTF-8', 5, True, True, False): u'\xa55',
('ja_JP.UTF-8', 500000, False, False, False): u'500000',
('ja_JP.UTF-8', 500000, True, False, False): u'\xa5500000',
('ja_JP.UTF-8', 500000, True, False, True): u'JPY 500000',
('ja_JP.UTF-8', 500000, True, True, False): u'\xa5500,000',
('no_NO.UTF-8', -57.049999999999997, True, True, True): u'NOK 57,05-',
('no_NO.UTF-8', -57.000050000000002, False, False, False): u'57,00-',
('no_NO.UTF-8', -57.000050000000002, True, False, False): u'kr57,00-',
('no_NO.UTF-8', -57.000050000000002, True, False, True): u'NOK 57,00-',
('no_NO.UTF-8', -57.000050000000002, True, True, False): u'kr57,00-',
('no_NO.UTF-8', 5, False, False, False): u'5,00',
('no_NO.UTF-8', 5, True, False, False): u'kr5,00',
('no_NO.UTF-8', 5, True, False, True): u'NOK 5,00',
('no_NO.UTF-8', 5, True, True, False): u'kr5,00',
('no_NO.UTF-8', 500000, False, False, False): u'500000,00',
('no_NO.UTF-8', 500000, True, False, False): u'kr500000,00',
('no_NO.UTF-8', 500000, True, False, True): u'NOK 500000,00',
('no_NO.UTF-8', 500000, True, True, False): u'kr500.000,00',
('sr_YU.UTF-8', -57.049999999999997, True, True, True): u'57,05 YUD -',
('sr_YU.UTF-8', -57.000050000000002, False, False, False): u'57,00-',
('sr_YU.UTF-8', -57.000050000000002, True, False, False): u'57,00 din-',
('sr_YU.UTF-8', -57.000050000000002, True, False, True): u'57,00 YUD -',
('sr_YU.UTF-8', -57.000050000000002, True, True, False): u'57,00 din-',
('sr_YU.UTF-8', 5, False, False, False): u'5,00',
('sr_YU.UTF-8', 5, True, False, False): u'5,00 din',
('sr_YU.UTF-8', 5, True, False, True): u'5,00 YUD ',
('sr_YU.UTF-8', 5, True, True, False): u'5,00 din',
('sr_YU.UTF-8', 500000, False, False, False): u'500000,00',
('sr_YU.UTF-8', 500000, True, False, False): u'500000,00 din',
('sr_YU.UTF-8', 500000, True, False, True): u'500000,00 YUD ',
('sr_YU.UTF-8', 500000, True, True, False): u'500000,00 din',
('uk_UA.UTF-8', -57.049999999999997, True, True, True): u'-57,05 UAH ',
('uk_UA.UTF-8', -57.000050000000002, False, False, False): u'-57,00',
('uk_UA.UTF-8', -57.000050000000002, True, False, False): u'-57,00 \u0433\u0440\u043d.',
('uk_UA.UTF-8', -57.000050000000002, True, False, True): u'-57,00 UAH ',
('uk_UA.UTF-8', -57.000050000000002, True, True, False): u'-57,00 \u0433\u0440\u043d.',
('uk_UA.UTF-8', 5, False, False, False): u'5,00',
('uk_UA.UTF-8', 5, True, False, False): u'5,00 \u0433\u0440\u043d.',
('uk_UA.UTF-8', 5, True, False, True): u'5,00 UAH ',
('uk_UA.UTF-8', 5, True, True, False): u'5,00 \u0433\u0440\u043d.',
('uk_UA.UTF-8', 500000, False, False, False): u'500000,00',
('uk_UA.UTF-8', 500000, True, False, False): u'500000,00 \u0433\u0440\u043d.',
('uk_UA.UTF-8', 500000, True, False, True): u'500000,00 UAH ',
('uk_UA.UTF-8', 500000, True, True, False): u'500000,00 \u0433\u0440\u043d.',
('zh_HK.UTF-8', -57.049999999999997, True, True, True): u'(HKD57.05)',
('zh_HK.UTF-8', -57.000050000000002, False, False, False): u'(57.00)',
('zh_HK.UTF-8', -57.000050000000002, True, False, False): u'(HK$57.00)',
('zh_HK.UTF-8', -57.000050000000002, True, False, True): u'(HKD57.00)',
('zh_HK.UTF-8', -57.000050000000002, True, True, False): u'(HK$57.00)',
('zh_HK.UTF-8', 5, False, False, False): u'5.00',
('zh_HK.UTF-8', 5, True, False, False): u'HK$5.00',
('zh_HK.UTF-8', 5, True, False, True): u'HKD5.00',
('zh_HK.UTF-8', 5, True, True, False): u'HK$5.00',
('zh_HK.UTF-8', 500000, False, False, False): u'500000.00',
('zh_HK.UTF-8', 500000, True, False, False): u'HK$500000.00',
('zh_HK.UTF-8', 500000, True, False, True): u'HKD500000.00',
('zh_HK.UTF-8', 500000, True, True, False): u'HK$500,000.00',
('zh_TW.UTF-8', -57.049999999999997, True, True, True): u'TWD 57.05-',
('zh_TW.UTF-8', -57.000050000000002, False, False, False): u'57.00-',
('zh_TW.UTF-8', -57.000050000000002, True, False, False): u'NT$57.00-',
('zh_TW.UTF-8', -57.000050000000002, True, False, True): u'TWD 57.00-',
('zh_TW.UTF-8', -57.000050000000002, True, True, False): u'NT$57.00-',
('zh_TW.UTF-8', 5, False, False, False): u'5.00',
('zh_TW.UTF-8', 5, True, False, False): u'NT$5.00',
('zh_TW.UTF-8', 5, True, False, True): u'TWD 5.00',
('zh_TW.UTF-8', 5, True, True, False): u'NT$5.00',
('zh_TW.UTF-8', 500000, False, False, False): u'500000.00',
('zh_TW.UTF-8', 500000, True, False, False): u'NT$500000.00',
('zh_TW.UTF-8', 500000, True, False, True): u'TWD 500000.00',
('zh_TW.UTF-8', 500000, True, True, False): u'NT$500,000.00'}
AVAILABLE_LOCALES = set()
for key in CURRENCY_DATA.iterkeys():
AVAILABLE_LOCALES.add(key[0])
class LocaleMockup(object):
def __init__(self, name):
self.name = name
def currency(self, val, symbol=True, grouping=False, international=False):
return CURRENCY_DATA[(self.name, val, symbol, grouping, international)]
def build_mockup(names, params):
import locale
info = dict()
for name in names:
name = str(name+'.UTF-8')
try:
locale.setlocale(locale.LC_ALL, name)
except locale.Error:
print 'Unsuported locale:', name
continue
for paramset in params:
key = tuple([name] + list(paramset))
if locale.nl_langinfo(locale.CODESET):
info[key] = unicode(locale.currency(*paramset), locale.nl_langinfo(locale.CODESET))
else:
info[key] = locale.currency(*paramset)
from pprint import pprint
pprint(info)
if __name__ == '__main__':
build_mockup(AVAILABLE_LOCALES, [(-57.049999999999997, True, True, True),
(-57.000050000000002, False, False, False),
(-57.000050000000002, True, False, False),
(-57.000050000000002, True, False, True),
(-57.000050000000002, True, True, False),
(5, False, False, False),
(5, True, False, False),
(5, True, False, True),
(5, True, True, False),
(500000, False, False, False),
(500000, True, False, False),
(500000, True, False, True),
(500000, True, True, False)])
| 58.13089
| 99
| 0.598577
| 1,903
| 11,103
| 3.40515
| 0.060431
| 0.088889
| 0.112037
| 0.142593
| 0.88071
| 0.834259
| 0.808179
| 0.734259
| 0.607716
| 0.341204
| 0
| 0.249322
| 0.169504
| 11,103
| 190
| 100
| 58.436842
| 0.453422
| 0
| 0
| 0
| 0
| 0
| 0.273194
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.01087
| null | null | 0.016304
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1f00826f57b68e1d97cf3b41af887a773f02c6a7
| 169
|
py
|
Python
|
DEODR/pytorch/__init__.py
|
Vozf/DEODR
|
e56cacffa4026170a6a0df01103de537e66e2111
|
[
"BSD-2-Clause"
] | 1
|
2021-04-02T16:48:44.000Z
|
2021-04-02T16:48:44.000Z
|
DEODR/pytorch/__init__.py
|
Vozf/DEODR
|
e56cacffa4026170a6a0df01103de537e66e2111
|
[
"BSD-2-Clause"
] | null | null | null |
DEODR/pytorch/__init__.py
|
Vozf/DEODR
|
e56cacffa4026170a6a0df01103de537e66e2111
|
[
"BSD-2-Clause"
] | null | null | null |
from .triangulated_mesh_pytorch import *
from .differentiable_renderer_pytorch import *
from .laplacian_rigid_energy_pytorch import *
from .mesh_fitter_pytorch import *
| 33.8
| 46
| 0.857988
| 21
| 169
| 6.47619
| 0.52381
| 0.382353
| 0.375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.094675
| 169
| 4
| 47
| 42.25
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
2f0f47daa8f0c22ca30b503a5cbec1db19d1c8a6
| 183,158
|
py
|
Python
|
tutorial.py
|
mooneyse/deep-fields-scripts
|
b0d9a5e8051742a1ebbbafd0e966043d1f74ff18
|
[
"MIT"
] | null | null | null |
tutorial.py
|
mooneyse/deep-fields-scripts
|
b0d9a5e8051742a1ebbbafd0e966043d1f74ff18
|
[
"MIT"
] | null | null | null |
tutorial.py
|
mooneyse/deep-fields-scripts
|
b0d9a5e8051742a1ebbbafd0e966043d1f74ff18
|
[
"MIT"
] | null | null | null |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Blazars at low frequencies"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* The bulk velocity is $ v $.\n",
"* The bulk Lorentz factor is $$ \\gamma = \\frac{1}{\\sqrt{1 - \\beta^{2}}} $$ where $ \\beta = \\frac{v}{c} $.\n",
"* The angle of the jet to our line of sight is $ \\theta $.\n",
"* The specific intensity the $ e^{-} $ emit at is $ I_{\\nu} \\propto \\nu^{\\alpha} $ (a power law) between $ \\nu_{1} $ and $ \\nu_{2} $, and $ \\frac{I_{\\nu}}{\\nu^{3}} $ is Lorentz invariant.\n",
"\n",
"* The $ \\nu $ of jet pointing at us is Doppler shifted (in frequency) by $ D_{+} = \\gamma (1 + \\beta \\cos \\theta) $. (The $ 1 + \\beta \\cos \\theta $ is the non-relativistic Doppler shifting and the $ \\gamma $ comes from time dilation.)\n",
"* The amplitude of the spectrum is boosted by $ D_{+}^{3} $, from the Lorentz invariant quantity above. The slope, $ \\alpha $, does not change.\n",
"* The counterjet is deboosted by $ D_{-} = \\gamma (1 - \\beta \\cos \\theta) $.\n",
"* See this [Berkley tutorial](http://w.astro.berkeley.edu/~echiang/rad/ps8aans.pdf).\n",
"* A common way of finding the Doppler factor is using the equipartition of energy argument, the X-ray flux density, or (in [this](https://iopscience.iop.org/article/10.1086/307587) case), total flux density variation monitoring data at 22 GHz and 37 GHz.\n",
"* An important application of precise Doppler factors is calculating the Lorentz factors and viewing angles of AGN relativistic outflows."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import scipy.constants as sc\n",
"import matplotlib.pyplot as plt\n",
"import math\n",
"from IPython.display import Image\n",
"\n",
"import warnings\n",
"warnings.simplefilter(action='ignore', category=FutureWarning)\n",
"\n",
"from matplotlib import pylab\n",
"pylab.rcParams['figure.figsize'] = (12, 8)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def beta(v):\n",
" ''' velocity '''\n",
" return v / sc.c\n",
"\n",
"\n",
"def gamma(v):\n",
" ''' lorentz factor '''\n",
" return 1 / np.sqrt(1 - beta(v) ** 2)\n",
"\n",
"\n",
"def doppler(v, theta, jet='forward'):\n",
" ''' doppler factor '''\n",
" if jet == 'forward':\n",
" return gamma(v) * (1 + beta(v) * np.cos(math.radians(theta)))\n",
" elif jet == 'away':\n",
" return gamma(v) * (1 - beta(v) * np.cos(math.radians(theta)))\n",
" \n",
" \n",
"def alpha(v, s, verbose=False):\n",
" ''' spectral index '''\n",
" a = np.log(s[0] / s[1]) / np.log(v[0] / v[1])\n",
" if verbose:\n",
" print('alpha =', np.round(a, 3))\n",
" return a\n",
" \n",
"\n",
"def scale_flux(old_v, new_v, old_s, alpha):\n",
" ''' scale the flux density using the spectral index relation '''\n",
" return old_s * (new_v / old_v) ** alpha\n",
"\n",
" \n",
"def make_plot(x, y, x2='', y2='', x3='', y3='', xlabel='', ylabel='', Log=' '):\n",
" ''' plot the data '''\n",
" plt.xlabel(xlabel)\n",
" plt.ylabel(ylabel)\n",
" plt.plot(x, y, color='w')\n",
" if y2 != '':\n",
" if x2 == '':\n",
" x2 = x\n",
" plt.plot(x2, y2, color='r')\n",
" if y3 != '':\n",
" if x3 == '':\n",
" x3 = x\n",
" plt.plot(x3, y3, color='b')\n",
" if 'x' in Log:\n",
" plt.xscale('log')\n",
" if 'y' in Log:\n",
" plt.yscale('log') \n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "dark"
},
"output_type": "display_data"
}
],
"source": [
"fraction_of_c, lorentz_factors = [], []\n",
"\n",
"for i in np.linspace(0, 1, 1000):\n",
" if i != 1: # prevents inf\n",
" fraction_of_c.append(i)\n",
" lorentz_factors.append(gamma(v=i * sc.c))\n",
"\n",
"make_plot(x=fraction_of_c, y=lorentz_factors, xlabel='Fraction of $c$',\n",
" ylabel='Lorentz factor')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "dark"
},
"output_type": "display_data"
}
],
"source": [
"angle, doppler_forward, doppler_away = [], [], []\n",
"\n",
"for i in np.linspace(0, 90, 1000):\n",
" angle.append(i)\n",
" doppler_forward.append(doppler(0.99 * sc.c, theta=i, jet='forward'))\n",
" doppler_away.append(doppler(0.99 * sc.c, theta=i, jet='away'))\n",
"\n",
"make_plot(x=angle, y=doppler_forward, y2=doppler_away, xlabel='Angle (degree)',\n",
" ylabel='Doppler factor')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We have know the intrinsic values of $ I_{\\nu} $ from a source at 10 MHz and 100 MHz from both jet lobes.\n",
"\n",
"* $ I_{10+} = 10 $ Jy.\n",
"* $ I_{100+} = 5 $ Jy.\n",
"\n",
"We will shift it for $ v = 0.95 c $ and $ \\theta = 10 $ degrees."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "dark"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"alpha = -0.301\n",
"alpha = -0.301\n",
"alpha = -0.301\n"
]
}
],
"source": [
"frequencies = np.array([10, 100]) # mhz\n",
"intensities = np.array([10, 5]) # jy\n",
"\n",
"v = 0.95 * sc.c\n",
"theta = math.radians(10)\n",
"\n",
"# forward jet\n",
"forward_frequencies = frequencies * doppler(v=v, theta=theta, jet='forward')\n",
"forward_intensities = intensities * doppler(v=v, theta=theta, jet='forward') ** 3\n",
"\n",
"# away jet\n",
"away_frequencies = frequencies * doppler(v=v, theta=theta, jet='away')\n",
"away_intensities = intensities * doppler(v=v, theta=theta, jet='away') ** 3\n",
"\n",
"make_plot(x=frequencies, y=intensities, x2=forward_frequencies, y2=forward_intensities,\n",
" x3=away_frequencies, y3=away_intensities, xlabel=r'$\\nu$ (MHz)',\n",
" ylabel=r'$I_{\\nu}$ (Jy)', Log='xy')\n",
"\n",
"# spectral index does not change\n",
"old_alpha = alpha(v=frequencies, s=intensities, verbose=True)\n",
"forward_alpha = alpha(v=forward_frequencies, s=forward_intensities, verbose=True)\n",
"away_alpha = alpha(v=away_frequencies, s=away_intensities, verbose=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"What is the difference in $ I_{\\nu} $ between the jets at a given $ \\nu $?"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "dark"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Intensity difference = 178657\n"
]
}
],
"source": [
"new_intensities = []\n",
"\n",
"# scale the counterjet to the forward jet frequencies\n",
" \n",
"new_intensities.append(scale_flux(old_v=away_frequencies[0], new_v=forward_frequencies[0],\n",
" old_s=away_intensities[0], alpha=old_alpha))\n",
"new_intensities.append(scale_flux(old_v=away_frequencies[1], new_v=forward_frequencies[1],\n",
" old_s=away_intensities[1], alpha=old_alpha))\n",
"\n",
"make_plot(x=forward_frequencies, y=new_intensities, x2=forward_frequencies,\n",
" y2=forward_intensities, x3=away_frequencies, y3=away_intensities,\n",
" xlabel=r'$\\nu$ (MHz)', ylabel=r'$I_{\\nu}$ (Jy)', Log='xy')\n",
"\n",
"print('Intensity difference =', int(np.mean(forward_intensities) / np.mean(new_intensities)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For M87, the ratio in brightness between the jets is 450 and $ \\alpha = -0.5 $. i.e.\n",
"$$ \\Big( \\frac{D_{+}}{D_{-}} \\Big)^{3 - \\alpha} = 450 $$\n",
"where the $ \\alpha $ is a correction factor arising because we scale. Then \n",
"$$ \\Big( \\frac{\\gamma (1 + \\beta \\cos \\theta)}{\\gamma (1 - \\beta \\cos \\theta)} \\Big)^{3 - \\alpha} = 450 \\\\\n",
"\\Big( \\frac{1 + \\beta \\cos \\theta}{1 - \\beta \\cos \\theta} \\Big)^{-3.5} = 450 $$\n",
"\n",
"We constain the following:\n",
"\n",
"* 45 degrees $ > \\theta > $ 0 degrees by definition.\n",
"* $ \\gamma > 1.4 $\n",
"* $ v > 0.7 c $\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"v > 0.7c\n"
]
}
],
"source": [
"def v_from_gamma(gamma):\n",
" ''' get the constaint on the bulk velocity from the lorentz factor '''\n",
" return np.sqrt(sc.c ** 2 - (sc.c / gamma) ** 2)/ sc.c\n",
"\n",
"print('v >', str(np.round(v_from_gamma(1.4), 2)) + 'c')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Burbidge's minimum energy argument\n",
"\n",
"This argument gets a value for the magnetic field by minimising the total energy density.\n",
"\n",
"This relies on a measurement of the volume emissivity, $ j_{\\nu} $. The units are $ \\mathrm{erg} \\; \\mathrm{s}^{-1} \\; \\mathrm{cm}^{-3} \\; \\mathrm{Hz}^{-1} \\; \\mathrm{sr}^{-1} $. It can be measured for optically thin media and we emasure it at the frequency at which the electrons radiate that are carrying the bulk of the kinetic energy density. The bulk energy density is carried by the lowest $ \\gamma $ electrons because they are the most numerous. This holds so long as $ p < -2 $ where $$ \\alpha = \\frac{1 + p}{2}. $$\n",
"\n",
"In the below image from [Carilli et al. (1991)](http://articles.adsabs.harvard.edu/pdf/1991ApJ...383..554C), we calculate $j_{\\nu} $ at $ \\nu = 10^{2.8} $ MHz as that is the lowest frequency for which the power law holds. $$ j_{\\nu} \\propto \\frac{L_{\\nu}}{V} $$ where $ V $ is the volume of the hotspot (we can assume a sphere) and $ L_{\\nu} $ is the luminosity per hertz. To go from a sky scale to a radius, which is needed for the volume, we have to know the redshift. Likewise, the luminosity will also depend on the distance.\n",
"\n",
"Doing this analysis gives $ B \\approx 3 \\times 10^{4} $ G (where 1 T = 10,000 G). Is it possible do find $ B $ with this line of reasoning for blazars? It requires the following:\n",
"\n",
"* We need the volume emissivity, $ j_{\\nu} $.\n",
" * To find out what $ \\nu $ to calculate $ j $ at, we need to ensure $ p < -2 $.\n",
" * To get $ p $, we need the spectral index, $ \\alpha $.\n",
"* $ j_{\\nu} $ requires $ L_{\\nu} $, the luminosity per hertz.\n",
" * For $ L_{\\nu} $, we need the flux density $ S_{\\nu} $ (which has to be converted from $ \\mathrm{Jy} \\; \\mathrm{beam}^{-1} $, requiring the beam size),\n",
" * the luminosity distance $D_{L} $,\n",
" * the redshift, $ z $,\n",
" * and the spectral index, $ \\alpha $ (already mentioned).\n",
"* $ j_{\\nu} $ also requires the volume, $ V $.\n",
" * $ V $ requires the radius, $ r $, if we assume a sphere.\n",
" * $ r $ requires the distance, $ z $ (already mentioned).\n",
" * $ r $ requires the size of the radio lobe on the radio map in arcseconds.\n",
"* Then $ j_{\\nu} \\approx n_{e} \\cdot P_{\\mathrm{single \\; e^{-}}} \\cdot \\frac{1}{4 \\pi} \\cdot \\frac{1}{\\nu}$\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
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py
|
Python
|
DFL168A/GPS.py
|
Dafulai/DFL168A_python
|
95825a27f2c145afbd02c207c3d622d6a77ceff2
|
[
"MIT"
] | null | null | null |
DFL168A/GPS.py
|
Dafulai/DFL168A_python
|
95825a27f2c145afbd02c207c3d622d6a77ceff2
|
[
"MIT"
] | null | null | null |
DFL168A/GPS.py
|
Dafulai/DFL168A_python
|
95825a27f2c145afbd02c207c3d622d6a77ceff2
|
[
"MIT"
] | null | null | null |
import time
import DFL168A
def getGPSinfo():
Latitude=0.0
Longitude=0.0
Speed=0.0
Time='' #format:hh:mm::ss
Date='' #format:dd/mm/yyyy
DFL168A.Ser4DFL168A.timeout=DFL168A.GPSTimeOut+0.05
if not DFL168A.ATCommand('ATDEV1SIGBSOF1'):
DFL168A.Ser4DFL168A.timeout=DFL168A.TimeOut+2.0
return False,Latitude,Longitude,Speed, Time,Date
DFL168A.Ser4DFL168A.timeout=DFL168A.TimeOut+2.0
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 LAT\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Latitude,Longitude,Speed, Time,Date
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Latitude,Longitude,Speed, Time,Date
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Latitude,Longitude,Speed, Time,Date
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='?':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='N':
return False,Latitude,Longitude,Speed, Time,Date
if '-'==temp[0]:
Minus_Result=True
else:
Minus_Result=False
Space_Index=temp.find(' ')
if Space_Index!=-1:
Latitude=float(temp[0:Space_Index])
temp=temp[Space_Index+1:]
else:
Latitude=0.0
Space_Index=temp.find('\'')
tempF=float(temp[0:Space_Index])
tempF=tempF/60.0
if Minus_Result:
Latitude=Latitude-tempF
else:
Latitude=Latitude+tempF
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 LONG\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Latitude,Longitude,Speed, Time,Date
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Latitude,Longitude,Speed, Time,Date
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Latitude,Longitude,Speed, Time,Date
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='?':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='N':
return False,Latitude,Longitude,Speed, Time,Date
if '-'==temp[0]:
Minus_Result=True
else:
Minus_Result=False
Space_Index=temp.find(' ')
if Space_Index!=-1:
Longitude=float(temp[0:Space_Index])
temp=temp[Space_Index+1:]
else:
Longitude=0.0
Space_Index=temp.find('\'')
tempF=float(temp[0:Space_Index])
tempF=tempF/60.0
if Minus_Result:
Longitude=Longitude-tempF
else:
Longitude=Longitude+tempF
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 SPEED\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Latitude,Longitude,Speed, Time,Date
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Latitude,Longitude,Speed, Time,Date
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Latitude,Longitude,Speed, Time,Date
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='?':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='N':
return False,Latitude,Longitude,Speed, Time,Date
Speed=float(temp)
Speed=Speed*1.852
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 TIME\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Latitude,Longitude,Speed, Time,Date
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Latitude,Longitude,Speed, Time,Date
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Latitude,Longitude,Speed, Time,Date
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='?':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='N':
return False,Latitude,Longitude,Speed, Time,Date
Time=temp
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 DATE\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Latitude,Longitude,Speed, Time,Date
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Latitude,Longitude,Speed, Time,Date
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Latitude,Longitude,Speed, Time,Date
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='?':
return False,Latitude,Longitude,Speed, Time,Date
if temp[0]=='N':
return False,Latitude,Longitude,Speed, Time,Date
Date=temp
return True, Latitude,Longitude,Speed, Time,Date
def getAltitude():
Altitude=0
DFL168A.Ser4DFL168A.timeout=DFL168A.GPSTimeOut+0.05
if not DFL168A.ATCommand('ATDEV1SIGBSOF2'):
DFL168A.Ser4DFL168A.timeout=DFL168A.TimeOut+2.0
return False,Altitude
DFL168A.Ser4DFL168A.timeout=DFL168A.TimeOut+2.0
# Catch Sleep warning, or cannel warning
#get all receiving data for catching Sleep Warning
if DFL168A.Ser4DFL168A.in_waiting!=0:
temp=DFL168A.Ser4DFL168A.read(DFL168A.Ser4DFL168A.in_waiting)
if 'S'.encode('utf-8') in temp: # Sleep Warning
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'leep'.encode('utf-8') in temp:
DFL168A.SleepWarning=True
elif 'C'.encode('utf-8') in temp: # Cancel Sleep Warning
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
else:
time.sleep(0.01)
if DFL168A.Ser4DFL168A.in_waiting:
temp=DFL168A.Ser4DFL168A.read_all()
if 'ancel'.encode('utf-8') in temp:
DFL168A.SleepWarning=False
#Now send cmd
DFL168A.Ser4DFL168A.write('AT DEV1 ALT\r\n'.encode('utf-8'))
temp=DFL168A.Ser4DFL168A.read_until('>')
#Jan 30 2021 add for warning and Cancel-----Begin
if 'Sleep'.encode('utf-8') in temp: # Sleep Warning
DFL168A.SleepWarning=True
return False,Altitude
elif 'Cancel'.encode('utf-8') in temp: # Cancel Sleep Warning
DFL168A.SleepWarning=False
return False,Altitude
#Jan 30 2021 add for warning and Cancel-----End
if temp[-1:]!='>'.encode('utf-8'):
return False,Altitude
temp=temp[:-1] #remove '>'
temp=temp.decode('utf-8')
temp=temp.strip()
temp=temp.upper() #in case lowercase
if temp=='':
return False,Altitude
if temp[0]=='?':
return False,Altitude
if temp[0]=='N':
return False,Altitude
Altitude=float(temp)
return True,Altitude
| 41.706395
| 71
| 0.574963
| 1,729
| 14,347
| 4.736264
| 0.053788
| 0.032238
| 0.073269
| 0.070338
| 0.94859
| 0.944926
| 0.938454
| 0.938454
| 0.934791
| 0.922091
| 0
| 0.081645
| 0.305081
| 14,347
| 344
| 72
| 41.706395
| 0.739719
| 0.127762
| 0
| 0.903654
| 0
| 0
| 0.055271
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.006645
| false
| 0
| 0.006645
| 0
| 0.146179
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c8408dd90c203ca0eac052d0508313b61347e486
| 312
|
py
|
Python
|
temboo/core/Library/Zendesk/ActivityStream/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 7
|
2016-03-07T02:07:21.000Z
|
2022-01-21T02:22:41.000Z
|
temboo/core/Library/Zendesk/ActivityStream/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | null | null | null |
temboo/core/Library/Zendesk/ActivityStream/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 8
|
2016-06-14T06:01:11.000Z
|
2020-04-22T09:21:44.000Z
|
from temboo.Library.Zendesk.ActivityStream.ListActivity import ListActivity, ListActivityInputSet, ListActivityResultSet, ListActivityChoreographyExecution
from temboo.Library.Zendesk.ActivityStream.ShowActivity import ShowActivity, ShowActivityInputSet, ShowActivityResultSet, ShowActivityChoreographyExecution
| 104
| 155
| 0.910256
| 22
| 312
| 12.909091
| 0.636364
| 0.070423
| 0.119718
| 0.169014
| 0.267606
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.044872
| 312
| 2
| 156
| 156
| 0.95302
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
c0f26e58fa607e08fa839330c5c47ae27aa35c47
| 191
|
py
|
Python
|
utils/ops/__init__.py
|
lartpang/ZoomNet
|
1f329e80db5469eaf6a513ec384cd19bafdaece2
|
[
"MIT"
] | 37
|
2022-03-05T09:19:35.000Z
|
2022-03-30T02:16:50.000Z
|
utils/ops/__init__.py
|
lartpang/ZoomNet
|
1f329e80db5469eaf6a513ec384cd19bafdaece2
|
[
"MIT"
] | 1
|
2022-03-29T18:36:49.000Z
|
2022-03-30T04:18:48.000Z
|
utils/ops/__init__.py
|
lartpang/ZoomNet
|
1f329e80db5469eaf6a513ec384cd19bafdaece2
|
[
"MIT"
] | 4
|
2022-03-08T04:37:04.000Z
|
2022-03-22T22:49:43.000Z
|
# -*- coding: utf-8 -*-
# @Time : 2020/12/19
# @Author : Lart Pang
# @GitHub : https://github.com/lartpang
from .array_ops import *
from .module_ops import *
from .tensor_ops import *
| 19.1
| 40
| 0.643979
| 27
| 191
| 4.444444
| 0.740741
| 0.225
| 0.216667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058442
| 0.193717
| 191
| 9
| 41
| 21.222222
| 0.720779
| 0.539267
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
8d0bb463c7bfe9d872037bc427f47b9db4ed8a8f
| 118
|
py
|
Python
|
mystique/clients/ResNet50.py
|
EduardaChagas/Cybersecurity-FL
|
52db1a31e71e021f2ce57231a27341c4c080ad3b
|
[
"MIT"
] | 4
|
2021-07-14T08:45:13.000Z
|
2021-08-24T15:36:51.000Z
|
mystique/clients/ResNet50.py
|
EduardaChagas/Cybersecurity-FL
|
52db1a31e71e021f2ce57231a27341c4c080ad3b
|
[
"MIT"
] | null | null | null |
mystique/clients/ResNet50.py
|
EduardaChagas/Cybersecurity-FL
|
52db1a31e71e021f2ce57231a27341c4c080ad3b
|
[
"MIT"
] | 3
|
2021-07-22T08:24:13.000Z
|
2021-12-08T09:20:39.000Z
|
from resnet import ResNetSplit, BasicBlock
def ResNetSplitClient():
return ResNetSplit(BasicBlock, [3, 4, 6, 3])
| 23.6
| 48
| 0.745763
| 14
| 118
| 6.285714
| 0.785714
| 0.477273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.152542
| 118
| 4
| 49
| 29.5
| 0.84
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 8
|
2384a1d0ad530bc56c04e6993f0c4b1eb5d39648
| 8,210
|
py
|
Python
|
fuzzy_system/obstacle_avoidance_controller.py
|
mohameddhameem/fuzzy-robot
|
f5fee20edca4395a161d6a4973c19349d5082078
|
[
"MIT"
] | null | null | null |
fuzzy_system/obstacle_avoidance_controller.py
|
mohameddhameem/fuzzy-robot
|
f5fee20edca4395a161d6a4973c19349d5082078
|
[
"MIT"
] | null | null | null |
fuzzy_system/obstacle_avoidance_controller.py
|
mohameddhameem/fuzzy-robot
|
f5fee20edca4395a161d6a4973c19349d5082078
|
[
"MIT"
] | null | null | null |
import skfuzzy.control as ctrl
from fuzzy_system.moo_fuzzy_controller import MooFuzzyController
class ObstacleAvoidanceController(MooFuzzyController):
def validate(self, values):
t = 1.5
temp = super().validate(values)
temp2 = (values["input_dl"] <= t or values["input_df"] <= t or values["input_dr"] <= t)
return temp and temp2
def inputs(self, dl, df, dr, a, p, ed):
return {
"input_dl": dl,
"input_df": df,
"input_dr": dr,
"input_a": a
}
def build_rules(self):
return [
# ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['F'], self.output_u['S']),
# ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['F'], self.output_w['PO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['N'], self.output_w['ZO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['N'], self.output_w['LPO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['M'], self.output_u['M']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['M'], self.output_w['LPO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['F'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['F'], self.output_w['LNO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['M'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['M'], self.output_w['NO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['F'], self.output_u['M']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['F'], self.output_w['LPO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['F'], self.output_u['M']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['F'], self.output_w['NO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['M'], self.output_u['M']),
ctrl.Rule(self.input_dl['F'] & self.input_df['N'] & self.input_dr['M'], self.output_w['PO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'], self.output_u['S']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['M'], self.output_u['S']),
ctrl.Rule(self.input_dl['M'] & self.input_df['N'] & self.input_dr['M'], self.output_w['PO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['M'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['M'], self.output_w['NO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['F'], self.output_u['M']),
ctrl.Rule(self.input_dl['N'] & self.input_df['M'] & self.input_dr['F'], self.output_w['NO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['M'], self.output_u['M']),
# ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['M'], self.output_w['NO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['M'], self.output_w['ZO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['LN'],
self.output_u['S']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['LN'],
self.output_w['LNO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['N'],
self.output_u['S']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['N'],
self.output_w['NO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['Z'],
self.output_u['L']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['Z'],
self.output_w['ZO']),
# ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'] & self.input_a['LP'],
# self.output_u['L']),
# ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'] & self.input_a['LP'],
# self.output_w['ZO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'] & self.input_a['LP'],
self.output_u['S']),
ctrl.Rule(self.input_dl['N'] & self.input_df['N'] & self.input_dr['N'] & self.input_a['LP'],
self.output_w['PO']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['P'],
self.output_u['L']),
ctrl.Rule(self.input_dl['N'] & self.input_df['F'] & self.input_dr['F'] & self.input_a['P'],
self.output_w['ZO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['M'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['M'] & self.input_df['M'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['M'] & self.input_dr['N'], self.output_u['M']),
ctrl.Rule(self.input_dl['F'] & self.input_df['M'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['F'] & self.input_dr['N'], self.output_u['M']),
# ctrl.Rule(self.input_dl['M'] & self.input_df['F'] & self.input_dr['N'], self.output_w['PO']),
ctrl.Rule(self.input_dl['M'] & self.input_df['F'] & self.input_dr['N'], self.output_w['ZO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['LN'],
self.output_u['L']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['LN'],
self.output_w['ZO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['N'],
self.output_u['L']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['N'],
self.output_w['ZO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['Z'],
self.output_u['L']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['Z'],
self.output_w['ZO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['LP'],
self.output_u['S']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['LP'],
self.output_w['LPO']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['P'],
self.output_u['S']),
ctrl.Rule(self.input_dl['F'] & self.input_df['F'] & self.input_dr['N'] & self.input_a['P'],
self.output_w['LPO']),
]
| 74.636364
| 107
| 0.540804
| 1,295
| 8,210
| 3.208494
| 0.040927
| 0.45704
| 0.173285
| 0.257762
| 0.918652
| 0.918652
| 0.918652
| 0.918412
| 0.918412
| 0.916005
| 0
| 0.00063
| 0.226553
| 8,210
| 109
| 108
| 75.321101
| 0.653701
| 0.075883
| 0
| 0.410526
| 0
| 0
| 0.04579
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.031579
| false
| 0
| 0.021053
| 0.021053
| 0.094737
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
23af4f21c373ca60f73f18d41939acf5700217a3
| 745
|
py
|
Python
|
steps/step40.py
|
choiking10/mytorch
|
67140b608b14e2ec6ecca1638705af91d2d71b6b
|
[
"MIT"
] | null | null | null |
steps/step40.py
|
choiking10/mytorch
|
67140b608b14e2ec6ecca1638705af91d2d71b6b
|
[
"MIT"
] | null | null | null |
steps/step40.py
|
choiking10/mytorch
|
67140b608b14e2ec6ecca1638705af91d2d71b6b
|
[
"MIT"
] | null | null | null |
import numpy as np
from mytorch import as_variable
def ex1():
x0 = as_variable(np.array([1, 2, 3]))
x1 = as_variable(np.array([10]))
y = x0 + x1
y.backward()
print(y)
print(x0.grad, x1.grad)
def ex2():
x0 = as_variable(np.array([1, 2, 3]))
x1 = as_variable(np.array([10]))
y = x0 * x1
y.backward()
print(y)
print(x0.grad, x1.grad)
def ex3():
x0 = as_variable(np.array([1, 2, 3]))
x1 = as_variable(np.array([10]))
y = x0 - x1
y.backward()
print(y)
print(x0.grad, x1.grad)
def ex4():
x0 = as_variable(np.array([1, 2, 3]))
x1 = as_variable(np.array([10]))
y = x0 / x1
y.backward()
print(y)
print(x0.grad, x1.grad)
ex1()
ex2()
ex3()
ex4()
| 15.204082
| 41
| 0.546309
| 125
| 745
| 3.184
| 0.184
| 0.226131
| 0.241206
| 0.341709
| 0.826633
| 0.826633
| 0.826633
| 0.826633
| 0.826633
| 0.826633
| 0
| 0.095064
| 0.265772
| 745
| 48
| 42
| 15.520833
| 0.632541
| 0
| 0
| 0.588235
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.117647
| false
| 0
| 0.058824
| 0
| 0.176471
| 0.235294
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
23b7e1e330d3b3f64f9e82b209d7b9cf3e8d1193
| 997
|
py
|
Python
|
tests/arn_test.py
|
VynOpenSource/boto-assume-role-with-mfa
|
ca1c09a51c8d0ba809a1e034ce1e1ed867c8ee0a
|
[
"MIT"
] | null | null | null |
tests/arn_test.py
|
VynOpenSource/boto-assume-role-with-mfa
|
ca1c09a51c8d0ba809a1e034ce1e1ed867c8ee0a
|
[
"MIT"
] | null | null | null |
tests/arn_test.py
|
VynOpenSource/boto-assume-role-with-mfa
|
ca1c09a51c8d0ba809a1e034ce1e1ed867c8ee0a
|
[
"MIT"
] | null | null | null |
import unittest
from boto_assume_role_with_mfa.arn import ARN
class ARNTest(unittest.TestCase):
def test_admin_role_arn(self):
role_arn = ARN("arn:aws:iam::123456789012:role/administrator")
self.assertEqual(role_arn.account, "123456789012")
self.assertEqual(role_arn.resource_type, "role")
self.assertEqual(role_arn.resource, "administrator")
def test_role_arn_with_slash(self):
role_arn = ARN("arn:aws:iam::123456789012:role/common-roles/developer")
self.assertEqual(role_arn.account, "123456789012")
self.assertEqual(role_arn.resource_type, "role")
self.assertEqual(role_arn.resource, "common-roles/developer")
def test_role_arn_with_colon(self):
role_arn = ARN("arn:aws:iam::123456789012:role:common-roles/developer")
self.assertEqual(role_arn.account, "123456789012")
self.assertEqual(role_arn.resource_type, "role")
self.assertEqual(role_arn.resource, "common-roles/developer")
| 39.88
| 79
| 0.726179
| 127
| 997
| 5.464567
| 0.228346
| 0.151297
| 0.246398
| 0.285303
| 0.806916
| 0.755043
| 0.755043
| 0.755043
| 0.755043
| 0.698847
| 0
| 0.085511
| 0.155466
| 997
| 24
| 80
| 41.541667
| 0.738717
| 0
| 0
| 0.444444
| 0
| 0
| 0.255767
| 0.194584
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0.166667
| false
| 0
| 0.111111
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
23f8d89aed42a8da83c5cd22a0131f06139e0cb5
| 10,571
|
py
|
Python
|
indico/modules/events/registration/privacy_test.py
|
pedroo21/indico
|
41b33b6ba82e4fb1f70844b19c79b5dce0d4173d
|
[
"MIT"
] | null | null | null |
indico/modules/events/registration/privacy_test.py
|
pedroo21/indico
|
41b33b6ba82e4fb1f70844b19c79b5dce0d4173d
|
[
"MIT"
] | null | null | null |
indico/modules/events/registration/privacy_test.py
|
pedroo21/indico
|
41b33b6ba82e4fb1f70844b19c79b5dce0d4173d
|
[
"MIT"
] | null | null | null |
# This file is part of Indico.
# Copyright (C) 2002 - 2022 CERN
#
# Indico is free software; you can redistribute it and/or
# modify it under the terms of the MIT License; see the
# LICENSE file for more details.
from datetime import datetime, timedelta
import pytest
from pytz import utc
from indico.modules.events.features.util import set_feature_enabled
from indico.modules.events.registration.models.registrations import (PublishRegistrationsMode, Registration,
RegistrationState, RegistrationVisibility)
pytest_plugins = 'indico.modules.events.registration.testing.fixtures'
def assert_visibility(reg, visibility, test_visibility_prop=True):
def _is_publishable_query(is_participant):
return Registration.query.with_parent(reg.event).filter(Registration.is_publishable(is_participant)).has_rows()
if test_visibility_prop:
assert reg.visibility == visibility
if visibility == RegistrationVisibility.nobody:
assert not reg.is_publishable(True)
assert not reg.is_publishable(False)
assert not _is_publishable_query(True)
assert not _is_publishable_query(False)
elif visibility == RegistrationVisibility.participants:
assert reg.is_publishable(True)
assert not reg.is_publishable(False)
assert _is_publishable_query(True)
assert not _is_publishable_query(False)
elif visibility == RegistrationVisibility.all:
assert reg.is_publishable(True)
assert reg.is_publishable(False)
assert _is_publishable_query(True)
assert _is_publishable_query(False)
@pytest.mark.usefixtures('dummy_reg')
def test_registration_visibility(dummy_event, dummy_regform):
set_feature_enabled(dummy_event, 'registration', True)
reg = dummy_event.registrations.one()
assert dummy_regform.publish_registrations_public == PublishRegistrationsMode.hide_all
assert dummy_regform.publish_registrations_participants == PublishRegistrationsMode.show_with_consent
assert reg.consent_to_publish == RegistrationVisibility.nobody
assert not reg.participant_hidden
assert reg.is_active
assert reg.state == RegistrationState.complete
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.participants)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.participants)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.hide_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_public = PublishRegistrationsMode.show_with_consent
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_with_consent
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.all)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.participants)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.all)
dummy_regform.publish_registrations_public = PublishRegistrationsMode.show_all
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.all)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.all)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.all)
reg.state = RegistrationState.rejected
assert not reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
reg.state = RegistrationState.withdrawn
assert not reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
reg.state = RegistrationState.pending
assert reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
@pytest.mark.usefixtures('dummy_reg')
def test_registration_visibility_hide_participants(dummy_event, dummy_regform):
set_feature_enabled(dummy_event, 'registration', True)
reg = dummy_event.registrations.one()
reg.participant_hidden = True
assert dummy_regform.publish_registrations_public == PublishRegistrationsMode.hide_all
assert dummy_regform.publish_registrations_participants == PublishRegistrationsMode.show_with_consent
assert reg.consent_to_publish == RegistrationVisibility.nobody
assert reg.is_active
assert reg.state == RegistrationState.complete
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.hide_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_public = PublishRegistrationsMode.show_with_consent
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_with_consent
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
dummy_regform.publish_registrations_public = PublishRegistrationsMode.show_all
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
reg.consent_to_publish = RegistrationVisibility.nobody
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.participants
assert_visibility(reg, RegistrationVisibility.nobody)
reg.consent_to_publish = RegistrationVisibility.all
assert_visibility(reg, RegistrationVisibility.nobody)
reg.state = RegistrationState.rejected
assert not reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
reg.state = RegistrationState.withdrawn
assert not reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
reg.state = RegistrationState.pending
assert reg.is_active
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
@pytest.mark.usefixtures('dummy_reg')
def test_visibility_duration(dummy_event, dummy_regform, freeze_time):
set_feature_enabled(dummy_event, 'registration', True)
reg = dummy_event.registrations.one()
dummy_regform.publish_registrations_participants = PublishRegistrationsMode.show_all
dummy_regform.publish_registrations_public = PublishRegistrationsMode.show_all
freeze_time(datetime(2022, 1, 1, tzinfo=utc))
dummy_event.start_dt = datetime(2020, 1, 1, tzinfo=utc)
dummy_event.end_dt = datetime(2021, 1, 1, tzinfo=utc)
assert not reg.participant_hidden
assert reg.is_active
assert reg.state == RegistrationState.complete
assert dummy_regform.publish_registrations_duration is None
assert_visibility(reg, RegistrationVisibility.all)
dummy_regform.publish_registrations_duration = timedelta(days=1*30)
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
dummy_regform.publish_registrations_duration = timedelta(days=12*30)
assert_visibility(reg, RegistrationVisibility.nobody, test_visibility_prop=False)
dummy_regform.publish_registrations_duration = timedelta(days=13*30)
assert_visibility(reg, RegistrationVisibility.all)
dummy_regform.publish_registrations_duration = timedelta(days=20*30)
assert_visibility(reg, RegistrationVisibility.all)
| 49.629108
| 119
| 0.81506
| 1,093
| 10,571
| 7.587374
| 0.10064
| 0.092608
| 0.109972
| 0.232365
| 0.889304
| 0.879658
| 0.864223
| 0.864223
| 0.855541
| 0.846859
| 0
| 0.004428
| 0.124113
| 10,571
| 212
| 120
| 49.863208
| 0.891241
| 0.01892
| 0
| 0.818713
| 0
| 0
| 0.011
| 0.004921
| 0
| 0
| 0
| 0
| 0.479532
| 1
| 0.02924
| false
| 0
| 0.02924
| 0.005848
| 0.064327
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
f1b905541f950fe2b35d1038963b33b475fd7133
| 49
|
py
|
Python
|
turnout_election_schemes/schemes/singletransferablevote/__init__.py
|
devfort/turnout-election-schemes
|
d9097f6f6241ebc8f5b17b03f09d2bc34189f2cc
|
[
"MIT"
] | null | null | null |
turnout_election_schemes/schemes/singletransferablevote/__init__.py
|
devfort/turnout-election-schemes
|
d9097f6f6241ebc8f5b17b03f09d2bc34189f2cc
|
[
"MIT"
] | null | null | null |
turnout_election_schemes/schemes/singletransferablevote/__init__.py
|
devfort/turnout-election-schemes
|
d9097f6f6241ebc8f5b17b03f09d2bc34189f2cc
|
[
"MIT"
] | null | null | null |
from .scheme import SingleTransferableVoteScheme
| 24.5
| 48
| 0.897959
| 4
| 49
| 11
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081633
| 49
| 1
| 49
| 49
| 0.977778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
f1f1008e566381e6540880fd6256ee3a8500e1be
| 3,551
|
py
|
Python
|
CGS/gnn/CGS/get_model.py
|
Junyoungpark/CGS
|
a0230d9898f13d1456f8d706b97a93d814b51e64
|
[
"MIT"
] | 24
|
2021-06-05T05:01:23.000Z
|
2022-03-19T20:03:29.000Z
|
CGS/gnn/CGS/get_model.py
|
Junyoungpark/CGS
|
a0230d9898f13d1456f8d706b97a93d814b51e64
|
[
"MIT"
] | null | null | null |
CGS/gnn/CGS/get_model.py
|
Junyoungpark/CGS
|
a0230d9898f13d1456f8d706b97a93d814b51e64
|
[
"MIT"
] | 2
|
2021-06-18T05:45:53.000Z
|
2022-03-04T10:34:05.000Z
|
from CGS.gnn.CGS.CGS import CGS, GraphTaskCGS
from CGS.nn.MLP import MLP
from CGS.nn.MPNN import AttnMPNN
from CGS.utils.gnn_utils import BasicReadout
def get_model(num_heads: int,
gamma: float,
num_hidden_gn: int,
nf_dim: int,
ef_dim: int,
sol_dim: int,
n_hidden_dim: int = 64,
e_hidden_dim: int = 64,
non_linear: str = 'Identity',
mlp_dp: float = 0.0,
mlp_num_neurons: list = [64, 64],
reg_dp: float = 0.0,
reg_num_neurons: list = [],
activation: str = 'ReLU',
node_aggregator: str = 'mean'):
mlp_num_neurons = list(mlp_num_neurons)
reg_num_neurons = list(reg_num_neurons)
enc = AttnMPNN(node_in_dim=nf_dim,
edge_in_dim=ef_dim,
node_hidden_dim=n_hidden_dim,
edge_hidden_dim=e_hidden_dim,
node_out_dim=num_heads,
edge_out_dim=num_heads,
num_hidden_gn=num_hidden_gn,
node_aggregator=node_aggregator,
mlp_params={'dropout_prob': mlp_dp,
'num_neurons': mlp_num_neurons,
'hidden_act': activation,
'out_act': activation})
dec = MLP(input_dim=num_heads,
num_neurons=reg_num_neurons,
hidden_act=activation,
output_dim=sol_dim,
dropout_prob=reg_dp)
cgs = CGS(encoder=enc,
decoder=dec,
gamma=gamma,
non_linear=non_linear)
return cgs
def get_graphtask_model(num_heads: int,
gamma: float,
num_hidden_gn: int,
nf_dim: int,
ef_dim: int,
sol_dim: int,
n_hidden_dim: int = 64,
e_hidden_dim: int = 64,
non_linear: str = 'Identity',
node_readout='sum',
mlp_dp: float = 0.0,
mlp_num_neurons: list = [64, 64],
reg_dp: float = 0.0,
reg_num_neurons: list = [],
activation: str = 'ReLU',
node_aggregator: str = 'mean'):
mlp_num_neurons = list(mlp_num_neurons)
reg_num_neurons = list(reg_num_neurons)
enc = AttnMPNN(node_in_dim=nf_dim,
edge_in_dim=ef_dim,
node_hidden_dim=n_hidden_dim,
edge_hidden_dim=e_hidden_dim,
node_out_dim=num_heads,
edge_out_dim=num_heads,
num_hidden_gn=num_hidden_gn,
node_aggregator=node_aggregator,
mlp_params={'dropout_prob': mlp_dp,
'num_neurons': mlp_num_neurons,
'hidden_act': activation,
'out_act': activation})
readout = BasicReadout(op=node_readout)
dec = MLP(input_dim=num_heads,
num_neurons=reg_num_neurons,
hidden_act=activation,
output_dim=sol_dim,
dropout_prob=reg_dp)
cgs = GraphTaskCGS(encoder=enc,
readout=readout,
decoder=dec,
gamma=gamma,
non_linear=non_linear)
return cgs
| 36.234694
| 62
| 0.489158
| 384
| 3,551
| 4.132813
| 0.15625
| 0.126024
| 0.065532
| 0.035287
| 0.849401
| 0.849401
| 0.849401
| 0.849401
| 0.849401
| 0.849401
| 0
| 0.01203
| 0.438186
| 3,551
| 97
| 63
| 36.608247
| 0.783459
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| false
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| 0.047059
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| 0
| 0
|
0
| 7
|
f1f6a340705c6da30c1a4b06505fc42604947a48
| 92
|
py
|
Python
|
parameters_8080.py
|
chitohugo/MassiveSMS
|
05b528de146498531c967aff1ee4fe72720febb3
|
[
"BSD-3-Clause"
] | null | null | null |
parameters_8080.py
|
chitohugo/MassiveSMS
|
05b528de146498531c967aff1ee4fe72720febb3
|
[
"BSD-3-Clause"
] | null | null | null |
parameters_8080.py
|
chitohugo/MassiveSMS
|
05b528de146498531c967aff1ee4fe72720febb3
|
[
"BSD-3-Clause"
] | null | null | null |
password="pbkdf2(1000,20,sha512)$860470d7e88047b1$c6fe79dcbdbe05a26715d6a19c43190bc4949ee9"
| 46
| 91
| 0.891304
| 7
| 92
| 11.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.505495
| 0.01087
| 92
| 1
| 92
| 92
| 0.395604
| 0
| 0
| 0
| 0
| 0
| 0.869565
| 0.869565
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 1
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| 0
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| 1
| null | 0
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| 0
| 0
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| 0
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| 1
| 0
| 0
| 1
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| 0
| 1
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| 0
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| 1
| null | 0
| 0
| 0
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| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
9e2bf575e425898e4d900a95504876cf339d4a74
| 6,934
|
py
|
Python
|
meiduo_mall/apps/oauth/views.py
|
joinik/meiduo_mall
|
08da8e789941ee0bb4d9cd658c4faaa4f9f0f67a
|
[
"MIT"
] | null | null | null |
meiduo_mall/apps/oauth/views.py
|
joinik/meiduo_mall
|
08da8e789941ee0bb4d9cd658c4faaa4f9f0f67a
|
[
"MIT"
] | null | null | null |
meiduo_mall/apps/oauth/views.py
|
joinik/meiduo_mall
|
08da8e789941ee0bb4d9cd658c4faaa4f9f0f67a
|
[
"MIT"
] | null | null | null |
import json
from django.contrib.auth import login
from django.http import JsonResponse
from django.shortcuts import render
# Create your views here.
from django.views import View
from QQLoginTool.QQtool import OAuthQQ
from apps.oauth.models import OAuthQQUser
from apps.oauth.utils import generate_access_token, check_access_token
from apps.users.models import User
from django.conf import settings
from utils.weiboOauthTool import OAuthWeibo
"""
生成跳转的链接
前端 用户点击qq登录按钮，发送一个 axios请求 /qq/authorization/
后端
接收请求
逻辑 使用QQloginTool生成跳转链接
响应 返回链接 {"code":0,"login_url":'http://xxx.qq.com/fdfds'}
路由 get /qq/authorization/
"""
class QQLoginUrlView(View):
def get(self, request):
# - 1使用QQloginTool生成跳转链接
# 1.1 生成 oauth对象
oauth = OAuthQQ(
client_id=settings.QQ_CLIENT_ID,
client_secret=settings.QQ_CLIENT_SECRET,
redirect_uri=settings.QQ_REDIRECT_URI,
state='abc')
# 获取扫码后的 authorization code
login_url = oauth.get_qq_url()
# - 2返回响应
return JsonResponse({'code': 0, "login_url": login_url})
"""
需求 获取code 根据code获取token 根据 token获取openid
前端：
发送axios请求 把code发送给后端 /oauth_callback/?code=fjdsskfklsdjl
后端
接收请求 接收参数 code
逻辑 根据code获取token 根据 token获取openid
响应
路由 get /oauth_callback/?code=fjdsskfklsdjl
"""
class OauthView(View):
def get(self, request):
# 1获取code
code = request.GET.get("code")
print('获取code:', code)
# 2根据code获取token
oauth = OAuthQQ(
client_id=settings.QQ_CLIENT_ID,
client_secret=settings.QQ_CLIENT_SECRET,
redirect_uri=settings.QQ_REDIRECT_URI,
state='abc')
token = oauth.get_access_token(code)
print('获取token', token)
# 3根据token获取openid
openid = oauth.get_open_id(token)
print('openid', openid)
# 4根据openid 去数据库查询 QAuthQQuser 账号信息
try:
qquesr = OAuthQQUser.objects.get(openid=openid)
except Exception as e:
# 不存在捕获异常 并且返回 加密的openid
print(e)
# 加密的openid
openid = generate_access_token(openid)
print('openid ----加密', openid)
return JsonResponse({'code': 400, 'access_token': openid})
else:
# 如果存在，返回正常的数据， 保持登录状态
login(request, qquesr.user)
# cookie
resp = JsonResponse({'code': 0, 'errmsg': 'ok'})
resp.set_cookie('username', qquesr.user.username)
return resp
def post(self,request):
# 接收请求
body_dict = json.loads(request.body)
# 2 获取请求参数，手机号，密码，短信验证码
password = body_dict.get('password')
mobile = body_dict.get('mobile')
sms_code = body_dict.get('sms_code')
openid = body_dict.get('access_token')
# 对openid 解密 获取源数据
openid = check_access_token(openid)
print('解密----openid',openid)
# 验证参数省略
# 根据手机号， 查询是否已经注册
try:
user = User.objects.get(mobile = mobile)
except Exception as e:
print(e)
# 捕获异常，说明没有注册，创建 user对象，绑定 用户和openid
user = User.objects.create_user(username=mobile,mobile=mobile,password=password)
else:
# 用户存在， 进行进行 密码验证
if not user.check_password(password):
return JsonResponse({'code':400,'errmsg':'账号或密码错误'})
try:
# 绑定user， openid
OAuthQQUser.objects.create(user=user,openid=openid)
except Exception as e:
print(e)
return JsonResponse({'code':400,'errmsg':'账号已绑定，无法绑定'})
# 6 状态保持
login(request, user)
response = JsonResponse({"code": 0, "errmsg": "ok"})
response.set_cookie("username", user.username)
# 7 返回响应
return response
class WEIBOLoginUrlView(View):
def get(self, request):
# - 1使用QQloginTool生成跳转链接
# 1.1 生成 oauth对象
oauth = OAuthWeibo(
client_id=settings.WEIBO_Key,
client_secret=settings.WEIBO_Secret,
redirect_uri=settings.QQ_REDIRECT_URI,
state='abc')
# 获取扫码后的 authorization code
login_url = oauth.get_weibo_url()
# - 2返回响应
return JsonResponse({'code': 0, "login_url": login_url})
class WeiboOauthView(View):
def get(self, request):
# 1获取code
code = request.GET.get("code")
print('获取code:', code)
# 2根据code获取token
oauth = OAuthWeibo(
client_id=settings.WEIBO_Key,
client_secret=settings.WEIBO_Secret,
redirect_uri=settings.QQ_REDIRECT_URI,
state='abc')
token = oauth.get_access_token(code)
print('获取token', token)
# 3根据token获取openid
openid = oauth.get_uid(token)
print('openid', openid)
# 4根据openid 去数据库查询 QAuthQQuser 账号信息
try:
qquesr = OAuthQQUser.objects.get(openid=openid)
except Exception as e:
# 不存在捕获异常 并且返回 加密的openid
print(e)
# 加密的openid
openid = generate_access_token(openid)
print('openid ----加密', openid)
return JsonResponse({'code': 400, 'access_token': openid})
else:
# 如果存在，返回正常的数据， 保持登录状态
login(request, qquesr.user)
# cookie
resp = JsonResponse({'code': 0, 'errmsg': 'ok'})
resp.set_cookie('username', qquesr.user.username)
return resp
def post(self,request):
# 接收请求
body_dict = json.loads(request.body)
# 2 获取请求参数，手机号，密码，短信验证码
password = body_dict.get('password')
mobile = body_dict.get('mobile')
sms_code = body_dict.get('sms_code')
openid = body_dict.get('access_token')
# 对openid 解密 获取源数据
openid = check_access_token(openid)
print('解密----openid',openid)
# 验证参数省略
# 根据手机号， 查询是否已经注册
# try:
# user = User.objects.get(mobile = mobile)
# except Exception as e:
# print(e)
# # 捕获异常，说明没有注册，创建 user对象，绑定 用户和openid
# user = User.objects.create_user(username=mobile,mobile=mobile,password=password)
# else:
# # 用户存在， 进行进行 密码验证
# if not user.check_password(password):
# return JsonResponse({'code':400,'errmsg':'账号或密码错误'})
#
# try:
# # 绑定user， openid
# OAuthQQUser.objects.create(user=user,openid=openid)
# except Exception as e:
# print(e)
# return JsonResponse({'code':400,'errmsg':'账号已绑定，无法绑定'})
# # 6 状态保持
# login(request, user)
# response = JsonResponse({"code": 0, "errmsg": "ok"})
# response.set_cookie("username", user.username)
#
# # 7 返回响应
# return response
return JsonResponse({"code": 0, "errmsg": "ok"})
| 31.09417
| 94
| 0.588261
| 749
| 6,934
| 5.325768
| 0.214953
| 0.052143
| 0.049637
| 0.027074
| 0.807972
| 0.801705
| 0.801705
| 0.801705
| 0.801705
| 0.801705
| 0
| 0.009971
| 0.30574
| 6,934
| 223
| 95
| 31.09417
| 0.818654
| 0.190943
| 0
| 0.734513
| 0
| 0
| 0.067304
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.053097
| false
| 0.035398
| 0.097345
| 0
| 0.274336
| 0.123894
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c87230b597aa54b7d6f8a90ea3d55663f3298692
| 3,877
|
py
|
Python
|
tests/dataset/distribution/test_buyer_repetition.py
|
open-contracting/pelican-backend
|
dee9afb48f7485f94544bcfbb977558d638098cd
|
[
"BSD-3-Clause"
] | 1
|
2021-07-21T15:23:22.000Z
|
2021-07-21T15:23:22.000Z
|
tests/dataset/distribution/test_buyer_repetition.py
|
open-contracting/pelican-backend
|
dee9afb48f7485f94544bcfbb977558d638098cd
|
[
"BSD-3-Clause"
] | 40
|
2021-06-29T23:53:14.000Z
|
2022-02-23T20:14:11.000Z
|
tests/dataset/distribution/test_buyer_repetition.py
|
open-contracting/pelican-backend
|
dee9afb48f7485f94544bcfbb977558d638098cd
|
[
"BSD-3-Clause"
] | null | null | null |
from dataset.distribution import buyer_repetition
from tests import is_subset_dict
item_unset = {"ocid": "0"}
def test_undefined():
scope = {}
result = buyer_repetition.get_result(scope)
assert result["result"] is None
assert result["value"] is None
assert result["meta"] == {"reason": "no data items were processed"}
scope = {}
scope = buyer_repetition.add_item(scope, item_unset, 0)
result = buyer_repetition.get_result(scope)
assert result["result"] is None
assert result["value"] is None
assert result["meta"] == {"reason": "there are not enough resources with check-specific properties"}
items_test_passed1 = []
items_test_passed1.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": -1}}} for _ in range(20)])
items_test_passed1.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": num}}} for num in range(980)])
items_test_passed2 = []
items_test_passed2.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": -1}}} for _ in range(490)])
items_test_passed2.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": num}}} for num in range(510)])
def test_passed():
scope = {}
id = 0
for item in items_test_passed1:
scope = buyer_repetition.add_item(scope, item, id)
id += 1
result = buyer_repetition.get_result(scope)
assert result["result"] is True
assert result["value"] == 100
assert result["meta"] == {
"total_ocid_count": 1000,
"ocid_count": 20,
"ocid_share": 20 / 1000,
"examples": [{"ocid": "0", "item_id": id} for id in range(20)],
"specifics": {"buyer.identifier.id": -1, "buyer.identifier.scheme": "ICO"},
}
scope = {}
id = 0
for item in items_test_passed2:
scope = buyer_repetition.add_item(scope, item, id)
id += 1
result = buyer_repetition.get_result(scope)
assert result["result"] is True
assert result["value"] == 100
assert is_subset_dict(
{
"total_ocid_count": 1000,
"ocid_count": 490,
"ocid_share": 490 / 1000,
"specifics": {"buyer.identifier.id": -1, "buyer.identifier.scheme": "ICO"},
},
result["meta"],
)
items_test_failed1 = []
items_test_failed1.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": -1}}} for _ in range(10)])
items_test_failed1.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": num}}} for num in range(990)])
items_test_failed2 = []
items_test_failed2.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": -1}}} for _ in range(500)])
items_test_failed2.extend([{"ocid": "0", "buyer": {"identifier": {"scheme": "ICO", "id": num}}} for num in range(500)])
def test_failed():
scope = {}
id = 0
for item in items_test_failed1:
scope = buyer_repetition.add_item(scope, item, id)
id += 1
result = buyer_repetition.get_result(scope)
assert result["result"] is False
assert result["value"] == 0
assert result["meta"] == {
"total_ocid_count": 1000,
"ocid_count": 10,
"ocid_share": 10 / 1000,
"examples": [{"ocid": "0", "item_id": id} for id in range(10)],
"specifics": {"buyer.identifier.id": -1, "buyer.identifier.scheme": "ICO"},
}
scope = {}
id = 0
for item in items_test_failed2:
scope = buyer_repetition.add_item(scope, item, id)
id += 1
result = buyer_repetition.get_result(scope)
assert result["result"] is False
assert result["value"] == 0
assert is_subset_dict(
{
"total_ocid_count": 1000,
"ocid_count": 500,
"ocid_share": 500 / 1000,
"specifics": {"buyer.identifier.id": -1, "buyer.identifier.scheme": "ICO"},
},
result["meta"],
)
| 32.855932
| 119
| 0.598917
| 490
| 3,877
| 4.559184
| 0.146939
| 0.085944
| 0.112802
| 0.128917
| 0.823635
| 0.823635
| 0.823635
| 0.80752
| 0.784244
| 0.751119
| 0
| 0.043261
| 0.224916
| 3,877
| 117
| 120
| 33.136752
| 0.700166
| 0
| 0
| 0.537634
| 0
| 0
| 0.217694
| 0.02373
| 0
| 0
| 0
| 0
| 0.193548
| 1
| 0.032258
| false
| 0.096774
| 0.021505
| 0
| 0.053763
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
c8a7f62881b8f22972c3d7d6a87b23386afc9ad7
| 41,413
|
py
|
Python
|
inst/python/rfmt/rparsetab.py
|
sorawee/rfmt
|
640525ce57843c61598310adcd428a0dfe214d66
|
[
"Apache-2.0"
] | 91
|
2015-08-08T09:08:37.000Z
|
2022-03-22T08:23:02.000Z
|
inst/python/rfmt/rparsetab.py
|
sorawee/rfmt
|
640525ce57843c61598310adcd428a0dfe214d66
|
[
"Apache-2.0"
] | 3
|
2016-05-27T12:45:53.000Z
|
2022-03-21T08:37:09.000Z
|
inst/python/rfmt/rparsetab.py
|
sorawee/rfmt
|
640525ce57843c61598310adcd428a0dfe214d66
|
[
"Apache-2.0"
] | 23
|
2015-08-07T05:05:43.000Z
|
2022-03-21T08:31:33.000Z
|
# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# parsetab.py
# This file is automatically generated. Do not edit.
_tabversion = '3.8'
_lr_method = 'LALR'
_lr_signature = 'm%\x1f\x13\xa8{\x7f\xb1\x0f\xb4\x8fr\x0cc\x8b\x0e'
_lr_action_items = 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58,58,-25,58,-14,-15,58,-29,-27,-28,-30,-22,-36,-41,58,-26,-42,58,-38,-3,-40,-37,58,-39,-23,-24,-43,58,-47,-32,-31,-34,-16,-71,58,58,58,58,-72,-65,-60,-62,-64,-61,]),'@':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,50,50,50,50,50,-63,50,-48,50,-58,50,-25,50,-14,-15,50,50,50,50,50,50,50,50,50,-26,50,50,50,-3,50,50,50,50,-23,-24,50,50,50,50,50,50,-16,-71,50,50,50,50,-72,-65,-60,-62,-64,-61,]),'LBB':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,56,56,56,56,56,-63,56,-48,56,-58,56,56,56,-14,-15,56,56,56,56,56,56,56,56,56,56,56,56,56,-3,56,56,56,56,56,56,56,56,56,56,56,56,-16,-71,56,56,56,56,-72,-65,-60,-62,-64,-61,]),']':([9,10,16,17,19,20,22,26,28,29,31,37,56,66,71,72,78,80,81,82,83,84,85,86,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,123,124,125,126,127,128,129,136,137,138,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,-2,-19,-18,-17,-21,-63,-49,-49,-20,-48,-58,-25,-33,-49,-14,-15,-53,-50,-29,-27,-28,-30,-22,-36,-41,-35,-26,-42,-44,-38,-3,-40,128,-37,-46,-39,-23,-24,-43,-45,-47,-32,129,-31,-34,-51,-56,-54,-49,-16,139,-71,-57,-55,-52,-72,-65,-60,-62,-64,-61,]),'^':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,67,67,67,67,67,-63,67,-48,67,-58,67,-25,67,-14,-15,67,67,67,67,67,67,67,67,67,-26,67,67,67,-3,67,67,67,67,-23,-24,67,67,67,67,67,67,-16,-71,67,67,67,67,-72,-65,-60,-62,-64,-61,]),'COMMENT':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,]),'FOR':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,]),'LBRACE':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,]),'NS_GET_INT':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,61,61,61,61,61,-63,61,-48,61,-58,61,61,61,-14,-15,61,61,61,61,61,61,61,61,61,61,61,61,61,-3,61,61,61,61,-23,-24,61,61,61,61,61,61,-16,-71,61,61,61,61,-72,-65,-60,-62,-64,-61,]),'$end':([1,2,7,9,10,11,16,17,19,20,22,23,24,26,28,29,30,31,32,37,69,70,71,72,78,80,81,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,115,116,127,129,139,141,142,143,146,147,],[-4,0,-4,-12,-10,-4,-11,-13,-14,-15,-2,-5,-1,-19,-18,-17,-7,-21,-6,-63,-4,-4,-20,-48,-58,-25,-33,-29,-27,-28,-30,-22,-36,-41,-35,-26,-42,-44,-38,-3,-40,-37,-46,-39,-23,-24,-43,-45,-47,-32,-31,-34,-9,-8,-16,-71,-72,-65,-60,-62,-64,-61,]),'STR_CONST':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,83,19,19,19,19,19,19,19,19,19,19,19,19,19,19,83,19,19,19,19,19,19,19,19,19,83,19,19,19,19,83,19,19,19,19,83,19,19,19,19,19,]),'BEGIN':([0,],[1,]),'RIGHT_ASSIGN':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,64,-19,-18,-17,64,-63,-20,-48,64,-58,64,-25,64,-14,-15,64,-29,-27,-28,-30,-22,-36,-41,64,-26,-42,64,-38,-3,-40,-37,64,-39,-23,-24,-43,64,-47,-32,-31,-34,-16,-71,64,64,64,64,-72,-65,-60,-62,-64,-61,]),'RBRACE':([7,9,10,11,15,16,17,19,20,22,23,26,28,29,30,31,32,36,37,69,70,71,72,78,80,81,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,115,116,127,129,139,141,142,143,146,147,],[-4,-12,-10,-4,-4,-11,-13,-14,-15,-2,-5,-19,-18,-17,-7,-21,-6,78,-63,-4,-4,-20,-48,-58,-25,-33,-29,-27,-28,-30,-22,-36,-41,-35,-26,-42,-44,-38,-3,-40,-37,-46,-39,-23,-24,-43,-45,-47,-32,-31,-34,-9,-8,-16,-71,-72,-65,-60,-62,-64,-61,]),'~':([1,3,4,5,6,7,8,9,10,11,15,16,17,18,19,20,22,25,26,28,29,31,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,77,78,79,80,81,82,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,117,118,124,125,126,127,129,130,131,133,134,135,136,137,139,141,142,143,144,145,146,147,],[25,25,25,25,25,25,25,-12,-10,25,25,-11,-13,25,-14,-15,68,25,-19,-18,-17,68,25,-63,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,-20,-48,68,-58,68,-25,68,25,-14,-15,68,-29,-27,-28,-30,-22,-36,-41,68,-26,-42,68,-38,-3,-40,-37,68,-39,-23,-24,-43,68,68,-32,-31,-34,25,25,25,25,25,-16,-71,68,68,25,25,25,68,68,-72,-65,-60,-62,25,25,-64,-61,]),'AND2':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,52,-19,-18,-17,-21,-63,-20,-48,52,-58,52,-25,52,-14,-15,52,-29,-27,-28,-30,-22,-36,-41,-35,-26,-42,52,-38,-3,-40,-37,-46,-39,-23,-24,-43,52,-47,-32,-31,-34,-16,-71,52,52,52,52,-72,-65,-60,-62,-64,-61,]),'SPECIAL':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,65,65,-18,-17,65,-63,65,-48,65,-58,65,-25,65,-14,-15,65,65,65,65,65,-22,65,65,65,-26,65,65,65,-3,65,65,65,65,-23,-24,65,65,65,-32,-31,65,-16,-71,65,65,65,65,-72,-65,-60,-62,-64,-61,]),'NS_GET':([9,10,16,17,19,20,22,26,28,29,31,37,71,72,77,78,79,80,81,83,84,85,88,89,90,91,92,93,94,95,96,97,98,99,100,101,103,104,105,106,107,108,109,110,111,113,114,127,129,130,131,136,137,139,141,142,143,146,147,],[-12,-10,-11,-13,-14,-15,60,60,60,60,60,-63,60,-48,60,-58,60,60,60,-14,-15,60,60,60,60,60,60,60,60,60,60,60,60,60,-3,60,60,60,60,-23,-24,60,60,60,60,60,60,-16,-71,60,60,60,60,-72,-65,-60,-62,-64,-61,]),'REPEAT':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,]),}
_lr_action = { }
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = { }
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'prog':([0,],[2,]),'expr':([1,3,4,5,6,7,8,11,15,18,25,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,82,117,118,124,125,126,133,134,135,144,145,],[22,26,22,28,29,22,31,22,22,22,71,77,79,80,81,85,88,89,90,91,92,93,94,95,96,97,98,99,22,101,85,103,104,105,106,107,108,109,110,111,85,113,114,22,22,85,130,131,136,137,85,22,22,22,22,22,]),'eatlines':([76,77,79,130,],[120,121,122,140,]),'sublist':([41,56,66,82,126,],[87,102,112,123,138,]),'form':([34,119,],[75,75,]),'expr_or_assign':([1,4,7,11,15,18,54,69,70,133,134,135,144,145,],[23,27,23,23,23,37,100,23,23,141,142,143,146,147,]),'formlist':([34,119,],[76,132,]),'exprlist':([1,7,11,15,69,70,],[24,30,32,36,115,116,]),'sub':([41,56,66,82,126,],[86,86,86,86,86,]),}
_lr_goto = { }
for _k, _v in _lr_goto_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_goto: _lr_goto[_x] = { }
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> prog","S'",1,None,None,None),
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('expr_or_assign -> expr','expr_or_assign',1,'p_expr_or_assign','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',789),
('expr_or_assign -> expr EQ_ASSIGN expr_or_assign','expr_or_assign',3,'p_expr_or_assign','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',790),
('exprlist -> <empty>','exprlist',0,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',799),
('exprlist -> expr_or_assign','exprlist',1,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',800),
('exprlist -> CR exprlist','exprlist',2,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',801),
('exprlist -> ; exprlist','exprlist',2,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',802),
('exprlist -> expr_or_assign CR exprlist','exprlist',3,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',803),
('exprlist -> expr_or_assign ; exprlist','exprlist',3,'p_exprlist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',804),
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('expr -> NUM_CONST','expr',1,'p_expr_atom','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',833),
('expr -> STR_CONST','expr',1,'p_expr_atom','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',834),
('expr -> SYMBOL','expr',1,'p_expr_atom','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',835),
('expr -> expr ( sublist )','expr',4,'p_expr_function_call','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',841),
('expr -> - expr','expr',2,'p_expr_unop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',847),
('expr -> + expr','expr',2,'p_expr_unop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',848),
('expr -> ! expr','expr',2,'p_expr_unop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',849),
('expr -> ~ expr','expr',2,'p_expr_unop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',850),
('expr -> ? expr','expr',2,'p_expr_unop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',851),
('expr -> expr : expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',857),
('expr -> expr NS_GET expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',858),
('expr -> expr NS_GET_INT expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',859),
('expr -> expr $ expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',860),
('expr -> expr @ expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',861),
('expr -> expr + expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',862),
('expr -> expr - expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',863),
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('expr -> expr SPECIAL expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',867),
('expr -> expr % expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',868),
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('expr -> expr GE expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',875),
('expr -> expr > expr','expr',3,'p_expr_binop','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',876),
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('sublist -> , sublist','sublist',2,'p_sublist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',901),
('sublist -> sub , sublist','sublist',3,'p_sublist','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',902),
('sub -> expr','sub',1,'p_sub','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',915),
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('sub -> STR_CONST EQ_ASSIGN expr','sub',3,'p_sub','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',919),
('expr -> LBRACE exprlist RBRACE','expr',3,'p_expr_braced_block','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',928),
('eatlines -> <empty>','eatlines',0,'p_eatlines','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',934),
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('expr -> IF ( expr eatlines ) expr_or_assign ELSE expr_or_assign','expr',8,'p_expr_if_else','/usr/local/google/users/pyelland/perforce/pyelland5_Piper/google3/blaze-bin/third_party/R/tools/rfmt/rfmt.runfiles/google3/third_party/R/tools/rfmt/formatter/r_language.py',946),
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c8ffd1f79e349e6d54543dfdcd1d8eaf2b658efd
| 5,390
|
py
|
Python
|
csdmpy/numpy_wrapper/apodize.py
|
deepanshs/csdmpy
|
bd4e138b10694491113b10177a89305697f1752c
|
[
"BSD-3-Clause"
] | 7
|
2021-07-07T09:55:20.000Z
|
2022-01-22T06:34:17.000Z
|
csdmpy/numpy_wrapper/apodize.py
|
deepanshs/csdmpy
|
bd4e138b10694491113b10177a89305697f1752c
|
[
"BSD-3-Clause"
] | 16
|
2021-06-09T06:28:27.000Z
|
2022-03-01T18:12:33.000Z
|
csdmpy/numpy_wrapper/apodize.py
|
deepanshs/csdmpy
|
bd4e138b10694491113b10177a89305697f1752c
|
[
"BSD-3-Clause"
] | 1
|
2020-01-03T17:04:16.000Z
|
2020-01-03T17:04:16.000Z
|
# -*- coding: utf-8 -*-
"""
A wrapper to the Numpy functions used to apodize the components along a given
dimension. If :math:`x` is the coordinates along the dimension, the apodization
function follows,
.. math::
y = function(a x),
where :math:`a` is the argument of the function. The dimensionality of :math:`a`
must be reciprocal of that of :math:`x`.
The list of supported functions are:
- sin
- cos
- ...
"""
import numpy as np
from csdmpy.csdm import _get_new_csdm_object_after_apodization
__all__ = ("sin", "cos", "tan", "arcsin", "arccos", "arctan", "exp")
# Trigonometric functions
def sin(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\sin(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the sine of the
dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.sin, arg, dimension)
def cos(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\cos(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the cosine of the
dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.cos, arg, dimension)
def tan(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\tan(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the tangent of the
dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.tan, arg, dimension)
def arcsin(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\arcsin(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the inverse sine of the
dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.arcsin, arg, dimension)
def arccos(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\arccos(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the inverse cosine of
the dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.arccos, arg, dimension)
def arctan(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\arctan(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the inverse tangent of
the dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.arctan, arg, dimension)
def exp(csdm, arg, dimension=0):
r"""Apodize the components along the `dimension` with :math:`\exp(a x)`.
Args:
csdm: A CSDM object.
arg: String or Quantity object. The function argument :math:`a`.
dimension: An integer or tuple of `m` integers cooresponding to the
index/indices of the dimensions along which the exp of the
dependent variable components is performed.
Return:
A CSDM object with `d-m` dimensions, where `d` is the total
number of dimensions from the original `csdm` object.
"""
return _get_new_csdm_object_after_apodization(csdm, np.exp, arg, dimension)
| 39.057971
| 86
| 0.660668
| 744
| 5,390
| 4.716398
| 0.114247
| 0.082645
| 0.043887
| 0.056996
| 0.834711
| 0.834711
| 0.825591
| 0.825591
| 0.825591
| 0.825591
| 0
| 0.001996
| 0.256401
| 5,390
| 137
| 87
| 39.343066
| 0.873503
| 0.748794
| 0
| 0
| 0
| 0
| 0.029326
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.291667
| false
| 0
| 0.083333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
a8108bd1add60b7a125bf076c43fee0116201b91
| 4,045
|
py
|
Python
|
backend/apps/info/migrations/0001_initial.py
|
offurface/logistic-company
|
1e98b1191fd9ee63fbd9d6c2eef1354822e53d14
|
[
"MIT"
] | null | null | null |
backend/apps/info/migrations/0001_initial.py
|
offurface/logistic-company
|
1e98b1191fd9ee63fbd9d6c2eef1354822e53d14
|
[
"MIT"
] | null | null | null |
backend/apps/info/migrations/0001_initial.py
|
offurface/logistic-company
|
1e98b1191fd9ee63fbd9d6c2eef1354822e53d14
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.2.8 on 2019-12-18 10:06
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Client',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('address', models.CharField(max_length=255)),
('inn', models.CharField(max_length=255)),
('phone', models.CharField(max_length=25)),
],
),
migrations.CreateModel(
name='Driver',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=150, verbose_name='Имя')),
('surname', models.CharField(max_length=150, verbose_name='Фамилия')),
('patronymic', models.CharField(max_length=150, verbose_name='Отчество')),
],
),
migrations.CreateModel(
name='ExecutorLegal',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=100, verbose_name='Сокращенное наименование')),
('full_name', models.CharField(max_length=255, verbose_name='Полное наименование')),
],
),
migrations.CreateModel(
name='ExecutorPerson',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=150, verbose_name='Имя')),
('surname', models.CharField(max_length=150, verbose_name='Фамилия')),
('patronymic', models.CharField(max_length=150, verbose_name='Отчество')),
],
),
migrations.CreateModel(
name='Goods',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=100, verbose_name='Наименование')),
('weight', models.DecimalField(decimal_places=2, max_digits=100, verbose_name='Вес (кг.)')),
('x', models.DecimalField(decimal_places=2, max_digits=100, verbose_name='Ширина (м.)')),
('y', models.DecimalField(decimal_places=2, max_digits=100, verbose_name='Длинна (м.)')),
('z', models.DecimalField(decimal_places=2, max_digits=100, verbose_name='Высота (м.)')),
],
),
migrations.CreateModel(
name='Locality',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=100)),
],
),
migrations.CreateModel(
name='Organization',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=100, verbose_name='Сокращенное наименование')),
('full_name', models.CharField(max_length=255, verbose_name='Полное наименование')),
],
),
migrations.CreateModel(
name='Tariff',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=50)),
],
),
migrations.CreateModel(
name='Transport',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('mark', models.CharField(max_length=100, verbose_name='Наименование')),
],
),
]
| 44.944444
| 114
| 0.569098
| 393
| 4,045
| 5.679389
| 0.198473
| 0.123208
| 0.137097
| 0.182796
| 0.811828
| 0.787634
| 0.787634
| 0.787634
| 0.759857
| 0.759857
| 0
| 0.02773
| 0.286774
| 4,045
| 89
| 115
| 45.449438
| 0.745927
| 0.011125
| 0
| 0.670732
| 1
| 0
| 0.102801
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.012195
| 0
| 0.060976
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
b52f46274cff46186a06e9a4674792f8a7cc75ad
| 100
|
py
|
Python
|
QuickDemos/random_number_module_demo.py
|
owenbres01/CMPT-120L-910-20F
|
c9840f5316688f023b7cca555ffc97ccb429aae8
|
[
"MIT"
] | 1
|
2020-08-25T23:50:45.000Z
|
2020-08-25T23:50:45.000Z
|
QuickDemos/random_number_module_demo.py
|
owenbres01/CMPT-120L-910-20F
|
c9840f5316688f023b7cca555ffc97ccb429aae8
|
[
"MIT"
] | 1
|
2020-09-18T01:20:58.000Z
|
2020-09-18T01:20:58.000Z
|
QuickDemos/random_number_module_demo.py
|
owenbres01/CMPT-120L-910-20F
|
c9840f5316688f023b7cca555ffc97ccb429aae8
|
[
"MIT"
] | 21
|
2020-08-25T03:52:56.000Z
|
2020-09-09T01:32:45.000Z
|
import random_number
print(random_number.random_number10())
print(random_number.random_number100())
| 25
| 39
| 0.86
| 13
| 100
| 6.230769
| 0.461538
| 0.444444
| 0.419753
| 0.567901
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052083
| 0.04
| 100
| 4
| 39
| 25
| 0.791667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0.666667
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 8
|
b533dcf7ef9d00467cf6498c3c38aea923c35a9c
| 5,488
|
py
|
Python
|
test.py
|
alsugiharto/auto-meetup-rsvp
|
59c393c0caec556d3fe357117e616e0e947a3a04
|
[
"MIT"
] | null | null | null |
test.py
|
alsugiharto/auto-meetup-rsvp
|
59c393c0caec556d3fe357117e616e0e947a3a04
|
[
"MIT"
] | null | null | null |
test.py
|
alsugiharto/auto-meetup-rsvp
|
59c393c0caec556d3fe357117e616e0e947a3a04
|
[
"MIT"
] | 2
|
2021-03-12T14:39:28.000Z
|
2022-03-11T03:11:04.000Z
|
import unittest
import time
import auto_meetup_rsvp_bot
# Test variables
# You need to find several meetup groups with the following criteria
GROUP_NAME_NO_EVENT = ""
GROUP_NAME_MULTI_EVENTS = ""
GROUP_NAME_ONE_AVAILABLE = ""
GROUP_NAME_ONE_CANNOT_GO = ""
GROUP_NAME_ONE_ALREADY_RSVP = ""
# difficult to find a group with cancelled upcoming event
GROUP_NAME_ONE_CANCELLED = ""
class TestSum(unittest.TestCase):
# login function test
def test01_login(self):
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# test after login
after_login = auto_meetup_rsvp_bot.is_logged_in(browser)
self.assertEqual(after_login, True)
# new_coming_event_count function test
def test02_count_no_event(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_NO_EVENT)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# new_coming_event_count function test
test_result = auto_meetup_rsvp_bot.new_coming_event_count(browser)
self.assertEqual(test_result, 0)
def test03_count_multi_event(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_MULTI_EVENTS)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# new_coming_event_count function test
test_result = auto_meetup_rsvp_bot.new_coming_event_count(browser)
self.assertGreater(test_result, 1)
def test04_count_one_already_rsvp(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_ALREADY_RSVP)
# get browsr
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# new_coming_event_count function test
test_result = auto_meetup_rsvp_bot.new_coming_event_count(browser)
self.assertEqual(test_result, 1)
def test05_count_one_available(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_AVAILABLE)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# new_coming_event_count function test
test_result = auto_meetup_rsvp_bot.new_coming_event_count(browser)
self.assertEqual(test_result, 1)
# is_event_available function test
def test06_available_one_already_rsvp(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_ALREADY_RSVP)
# get browsr
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# is_event_available function test
test_result = auto_meetup_rsvp_bot.is_event_available(browser)
self.assertEqual(test_result, 2)
def test07_available_one_cannot_go(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_CANNOT_GO)
browser = auto_meetup_rsvp_bot.setup()
auto_meetup_rsvp_bot.login(browser)
# new_coming_event_count function test
test_result = auto_meetup_rsvp_bot.new_coming_event_count(browser)
self.assertEqual(test_result, 1)
# is_event_available function test
test_result = auto_meetup_rsvp_bot.is_event_available(browser)
self.assertEqual(test_result, 3)
def test08_available_one_available(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_AVAILABLE)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# is_event_available function test
test_result = auto_meetup_rsvp_bot.is_event_available(browser)
self.assertEqual(test_result, 4)
# RSVP function test
def test09_rsvp_is_rsvp_check_yes(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_ALREADY_RSVP)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# is rsvp check yes test
test_result = auto_meetup_rsvp_bot.is_rsvp_check(browser)
self.assertEqual(test_result, True)
def test10_rsvp_is_rsvp_check_no(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_AVAILABLE)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# is rsvp check no test
test_result = auto_meetup_rsvp_bot.is_rsvp_check(browser)
self.assertEqual(test_result, False)
# WILL ACTUALLY RSVP!
def test11_rsvp_final(self):
# update group name
auto_meetup_rsvp_bot.update_group_name(GROUP_NAME_ONE_AVAILABLE)
# get browser
browser = auto_meetup_rsvp_bot.setup()
# login
auto_meetup_rsvp_bot.login(browser)
# delay
time.sleep(10)
# rsvp
auto_meetup_rsvp_bot.rsvp(browser)
# delay
time.sleep(10)
# after rsvp
# is rsvp check yes test
test_result = auto_meetup_rsvp_bot.is_rsvp_check(browser)
self.assertEqual(test_result, True)
if __name__ == '__main__':
unittest.main()
| 34.955414
| 75
| 0.703717
| 727
| 5,488
| 4.850069
| 0.115543
| 0.130459
| 0.182643
| 0.221781
| 0.805729
| 0.767158
| 0.750142
| 0.750142
| 0.750142
| 0.750142
| 0
| 0.008111
| 0.236152
| 5,488
| 156
| 76
| 35.179487
| 0.833015
| 0.186042
| 0
| 0.573171
| 0
| 0
| 0.001813
| 0
| 0
| 0
| 0
| 0
| 0.146341
| 1
| 0.134146
| false
| 0
| 0.036585
| 0
| 0.182927
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
b583170312f4445956849a9776c057ab5e473936
| 223
|
py
|
Python
|
ToolsNLP/__init__.py
|
9en/ToolsNLP
|
05bcbfd83857b87fe19fbe561013717589b21171
|
[
"MIT"
] | null | null | null |
ToolsNLP/__init__.py
|
9en/ToolsNLP
|
05bcbfd83857b87fe19fbe561013717589b21171
|
[
"MIT"
] | 1
|
2019-09-01T02:38:38.000Z
|
2019-09-01T06:12:50.000Z
|
ToolsNLP/__init__.py
|
9en/ToolsNLP
|
05bcbfd83857b87fe19fbe561013717589b21171
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from ToolsNLP.mecab_wrapper import MecabWrapper
from ToolsNLP.mecab_wrapper import TokenizerSentiment
from ToolsNLP.mecab_wrapper import Tokenizer
from ToolsNLP.topic_model import TopicModelWrapper
| 31.857143
| 53
| 0.843049
| 27
| 223
| 6.814815
| 0.518519
| 0.26087
| 0.277174
| 0.391304
| 0.48913
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004975
| 0.098655
| 223
| 6
| 54
| 37.166667
| 0.910448
| 0.09417
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
b5b174cb5fd882e734b5ede1bb127e45a6bd50c7
| 30,124
|
py
|
Python
|
twitter_api/guest_access_tweepy/guest_access_twitter_flask.py
|
glciampaglia/infodiversity-mock-social-media
|
d7b56d236dfd910a1ea760a4d6fb37121eecf565
|
[
"MIT"
] | 1
|
2021-01-18T21:18:38.000Z
|
2021-01-18T21:18:38.000Z
|
twitter_api/guest_access_tweepy/guest_access_twitter_flask.py
|
glciampaglia/infodiversity-mock-social-media
|
d7b56d236dfd910a1ea760a4d6fb37121eecf565
|
[
"MIT"
] | 93
|
2020-12-08T14:37:57.000Z
|
2021-10-07T13:32:10.000Z
|
twitter_api/guest_access_tweepy/guest_access_twitter_flask.py
|
glciampaglia/infodiversity-mock-social-media
|
d7b56d236dfd910a1ea760a4d6fb37121eecf565
|
[
"MIT"
] | null | null | null |
""" Read the credentials from credentials.txt and place them into the `cred` dictionary """
import os
import re
import numpy as np
import datetime
import json
import Cardinfo
import requests
from flask import Flask, render_template, request, url_for, jsonify
from requests_oauthlib import OAuth1Session
from configparser import ConfigParser
import xml
import xml.sax.saxutils
#import requests as rq
app = Flask(__name__)
app.debug = False
def config(filename,section):
# create a parser
parser = ConfigParser()
# read config file
parser.read(filename)
# get section, default to postgresql
db = {}
if parser.has_section(section):
params = parser.items(section)
for param in params:
db[param[0]] = param[1]
else:
raise Exception('Section {0} not found in the {1} file'.format(section, filename))
return db
@app.route('/getfeedprereg', methods=['GET'])
def get_feed_prereg():
access_token = request.args.get('access_token')
access_token_secret = request.args.get('access_token_secret')
attn = int(request.args.get('attn'))
page = int(request.args.get('page'))
cookiee = request.args.get('cookiee')
print("page : "+str(page))
print("attn : "+str(attn))
print("cookie : "+str(cookiee))
cred = config('../../config.ini','twitterapp')
cred['token'] = access_token.strip()
cred['token_secret'] = access_token_secret.strip()
oauth = OAuth1Session(cred['key'],
client_secret=cred['key_secret'],
resource_owner_key=cred['token'],
resource_owner_secret=cred['token_secret'])
public_tweets = None
worker_id = request.args.get('worker_id')
refresh = 0
#check cookie here and set attn and page to 0 and increment refresh
if cookiee == "NO":
attn = 0
refresh = refresh + 1
new_session = False
if attn == 0:
new_session = True
params = {"count": "30","tweet_mode": "extended"}
response = oauth.get("https://api.twitter.com/1.1/statuses/home_timeline.json", params = params)
public_tweets = json.loads(response.text)
#print(tweets)
if public_tweets == "{'errors': [{'message': 'Rate limit exceeded', 'code': 88}]}":
print("Rate limit exceeded.")
db_tweet_payload = []
db_tweet_attn_payload = []
attn_idx = []
num_tweets_attn = len(public_tweets) - 5
for i in range(3):
present_idx = np.random.choice(5,size=2)
absent_idx = np.random.choice(num_tweets_attn,size=2) + 5
each_attn_idx = np.concatenate((present_idx,absent_idx),axis=0)
print(each_attn_idx)
np.random.shuffle(each_attn_idx)
attn_idx.append(each_attn_idx)
print(attn_idx)
db_tweet_attn_1_payload = []
db_tweet_attn_2_payload = []
db_tweet_attn_3_payload = []
rank_attn_1 = 1
for idx in attn_idx[0]:
tweet = public_tweets[idx]
present = False
if idx < 5:
present = True
db_tweet = {
'tweet_id':tweet["id"],
'rank':rank_attn_1,
'attnlevel':1,
'present':present
}
db_tweet_attn_1_payload.append(db_tweet)
rank_attn_1 = rank_attn_1 + 1
rank_attn_2 = 1
for idx in attn_idx[1]:
tweet = public_tweets[idx]
present = False
if idx < 5:
present = True
db_tweet = {
'tweet_id':tweet["id"],
'rank':rank_attn_1,
'attnlevel':2,
'present':present
}
db_tweet_attn_2_payload.append(db_tweet)
rank_attn_2 = rank_attn_2 + 1
rank_attn_3 = 1
for idx in attn_idx[2]:
tweet = public_tweets[idx]
present = False
if idx < 5:
present = True
db_tweet = {
'tweet_id':tweet["id"],
'rank':rank_attn_1,
'attnlevel':3,
'present':present
}
db_tweet_attn_3_payload.append(db_tweet)
rank_attn_3 = rank_attn_3 + 1
for tweet in public_tweets:
db_tweet = {
'tweet_id':tweet["id"],
'tweet_json':tweet
}
db_tweet_payload.append(db_tweet)
finalJson = []
finalJson.append(db_tweet_payload)
finalJson.append(db_tweet_attn_1_payload)
finalJson.append(db_tweet_attn_2_payload)
finalJson.append(db_tweet_attn_3_payload)
finalJson.append(worker_id)
requests.post('http://127.0.0.1:5052/insert_prereg',json=finalJson)
public_tweets = public_tweets[0:5]
else:
print("page : "+str(page))
db_response = requests.get('http://127.0.0.1:5052/get_prereg_tweets?worker_id='+str(worker_id)+'&attnlevel='+str(page+1))
db_response = db_response.json()['data']
public_tweets = [d[2] for d in db_response]
feed_json = []
rankk = 1
for tweet in public_tweets: # Modify what tweet is for this loop in order to change the logic ot use our data or twitters.
# Checking for an image in the tweet. Adds all the links of any media type to the eimage list.
actor_name = tweet["user"]["name"]
#tweet_id = str(tweet.id)
full_text = tweet["full_text"]
url_start = []
url_end = []
url_display = []
url_extend = []
url_actual = []
if "entities" in tweet.keys():
if "urls" in tweet["entities"]:
for url_dict in tweet["entities"]["urls"]:
url_start.append(url_dict["indices"][0])
url_end.append(url_dict["indices"][1])
url_display.append(url_dict["display_url"])
url_extend.append(url_dict["expanded_url"])
url_actual.append(url_dict["url"])
last_url_arr = re.findall("(?P<url>https?://[^\s]+)", full_text)
if last_url_arr:
last_url = last_url_arr[-1]
if last_url not in url_actual:
full_text = full_text.replace(last_url,'')
full_text_json = []
if url_actual:
normal_idx = 0
url_idx = 0
for i in range(len(url_start)):
url_idx_start = url_start[i]
full_text_json.append({"text":full_text[normal_idx:url_idx_start],"url":""})
full_text_json.append({"text":url_extend[i],"url":url_extend[i]})
normal_idx = url_end[i]
if normal_idx < len(full_text):
full_text_json.append({"text":full_text[normal_idx:len(full_text)],"url":""})
else:
full_text_json.append({"text":full_text,"url":""})
isRetweet = False
retweeted_by = ""
actor_picture = tweet["user"]["profile_image_url"]
actor_username = tweet["user"]["screen_name"]
tempLikes = tweet["favorite_count"]
quoted_by = ""
quoted_by_text = ""
quoted_by_actor_username = ""
quoted_by_actor_picture = ""
isQuote = False
try: # This will handle retweet case and nested try will handle retweeted quote
full_text = tweet["retweeted_status"]["full_text"]
retweeted_by = actor_name # Grab it here before changing the name
# Now I need to check if the retweeted status is a quoted status I think.
try:
full_text = tweet["retweeted_status"]["quoted_status"]["full_text"]
quoted_by = tweet["retweeted_status"]["user"]["name"] # name of the retweet who quoted
quoted_by_text = tweet["retweeted_status"]["full_text"]
quoted_by_actor_username = tweet["retweeted_status"]["user"]["screen_name"]
quoted_by_actor_picture = tweet["retweeted_status"]["user"]["profile_image_url"]
actor_name = tweet["retweeted_status"]["quoted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["retweeted_status"]["quoted_status"]["user"]["screen_name"]
actor_picture = tweet["retweeted_status"]["quoted_status"]["user"]["profile_image_url"]
tempLikes = tweet["retweeted_status"]["quoted_status"]["favorite_count"]
isQuote = True
except: # if its not a quote default to normal retweet settings
actor_name = tweet["retweeted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["retweeted_status"]["user"]["screen_name"]
actor_picture = tweet["retweeted_status"]["user"]["profile_image_url"]
tempLikes = tweet["retweeted_status"]["favorite_count"]
isRetweet = True
isRetweet = True
except:
isRetweet = False
if not isRetweet: # case where its not a retweet but still could be a quote.
try:
full_text = tweet["quoted_status"]["full_text"]
quoted_by = tweet["user"]["name"] # name of the person who quoted
quoted_by_text = tweet["full_text"]
quoted_by_actor_username = tweet["user"]["screen_name"]
quoted_by_actor_picture = tweet["user"]["profile_image_url"]
actor_name = tweet["quoted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["quoted_status"]["user"]["screen_name"]
actor_picture = tweet["quoted_status"]["user"]["profile_image_url"]
tempLikes = tweet["quoted_status"]["favorite_count"]
isQuote = True
except:
isQuote = False
entities_keys = ""
all_urls = ""
urls_list = []
expanded_urls_list = []
urls = ""
expanded_urls = ""
image_raw = ""
picture_heading = ""
picture_description = ""
mediaArr = ""
# Decision making for the block to retrieve article cards AND embedded images
if isQuote and isRetweet: # Check for the case of a quote within a retweet.
entities_keys = tweet["retweeted_status"]["quoted_status"]["entities"].keys()
mediaArr = tweet["retweeted_status"]["quoted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["retweeted_status"]["quoted_status"]["entities"]["urls"]
elif isQuote: # quote only case
entities_keys = tweet["quoted_status"]["entities"].keys()
mediaArr = tweet["quoted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["quoted_status"]["entities"]["urls"]
elif isRetweet:
entities_keys = tweet["retweeted_status"]["entities"].keys()
mediaArr = tweet["retweeted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["retweeted_status"]["entities"]["urls"]
else:
entities_keys = tweet["entities"].keys()
mediaArr = tweet['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["entities"]["urls"]
# Redesigned block to retrieve the Cardinfo data. Old placement and OG version.
#if "urls" in entities_keys:
# for each_url in all_urls:
# urls_list.append(each_url["url"])
# expanded_urls_list.append(each_url["expanded_url"])
# urls = ",".join(urls_list)
# expanded_urls = ",".join(expanded_urls_list)
#if len(expanded_urls_list) > 0 and not isQuote: # not isQuote is to save time in the case of a quote. no card needed
# card_url = expanded_urls_list[0]
# card_data = Cardinfo.getCardData(card_url)
# if "image" in card_data.keys():
# image_raw = card_data['image']
# picture_heading = card_data["title"]
# picture_description = card_data["description"]
# Embedded image retrieval (edited to handle retweets also now)
hasEmbed = False
eimage = []
try: # Not sure why this has an issue all of a sudden.
flag_image = False
if len(mediaArr) > 0:
for x in range(len(mediaArr)):
if mediaArr[x]['type'] == 'photo':
hasEmbed = True
if "sizes" in mediaArr[x].keys():
if "small" in mediaArr[x]["sizes"].keys():
small_width = int(mediaArr[x]["sizes"]["small"]["w"])
small_height = int(mediaArr[x]["sizes"]["small"]["h"])
small_aspect_ratio = small_height/small_width
if small_aspect_ratio > 0.89:
if "thumb" in mediaArr[x]["sizes"].keys():
eimage.append(mediaArr[x]['media_url']+':thumb')
else:
eimage.append(mediaArr[x]['media_url']+':small')
else:
eimage.append(mediaArr[x]['media_url']+':small')
else:
eimage.append(mediaArr[x]['media_url'])
else:
eimage.append(mediaArr[x]['media_url'])
flag_image = True
if not flag_image:
eimage.append("")
except Exception as error:
print(error)
eimage[0] = ""
# Redesigned block to retrieve the Cardinfo data.
if "urls" in entities_keys and not hasEmbed:
for each_url in all_urls:
urls_list.append(each_url["url"])
expanded_urls_list.append(each_url["expanded_url"])
urls = ",".join(urls_list)
expanded_urls = ",".join(expanded_urls_list)
if len(expanded_urls_list) > 0 and not isQuote and not hasEmbed: # not isQuote is to save time in the case of a quote. no card needed
card_url = expanded_urls_list[0]
card_data = Cardinfo.getCardData(card_url)
if card_data:
if "image" in card_data.keys():
image_raw = card_data['image']
picture_heading = card_data["title"]
picture_description = card_data["description"]
#if isRetweet:
#print("Is a retweet.")
for urll in urls_list:
full_text = full_text.replace(urll,"")
#print(full_text)
full_text = xml.sax.saxutils.unescape(full_text)
body = full_text
date_string_temp = tweet['created_at'].split()
date_string = date_string_temp[1] + " " + date_string_temp[2] + " " + date_string_temp[3] + " " + date_string_temp[5]
td = (datetime.datetime.now() - datetime.datetime.strptime(date_string,"%b %d %H:%M:%S %Y"))
hours, remainder = divmod(td.seconds, 3600) # can we scrap this and the line below ______-------________-----________---------______--------
minutes, seconds = divmod(remainder, 60)
time = ""
if minutes < 10:
time = "-00:0"+str(minutes)
else:
time = "-00:"+str(minutes)
#time.append(td.seconds)
# Fixing the like system
finalLikes = ""
if (tempLikes <= 999):
finalLikes = str(tempLikes)
elif (tempLikes >= 1000):
counterVar = 1
while(True):
if (tempLikes - 1000 > 0):
tempLikes = tempLikes - 1000
counterVar = counterVar + 1
else:
finalLikes = str(counterVar) + "." + str(tempLikes)[0] + "k"
break
# Fixing the retweet system
finalRetweets = ""
tempRetweets = tweet["retweet_count"]
if (tempRetweets <= 999):
finalRetweets = str(tempRetweets)
elif (tempRetweets >= 1000):
counterVar = 1
while(True):
if (tempRetweets - 1000 > 0):
tempRetweets = tempRetweets - 1000
counterVar = counterVar + 1
else:
finalRetweets = str(counterVar) + "." + str(tempRetweets)[0] + "k"
break
profile_link = ""
if tweet["user"]["url"]:
profile_link = tweet["user"]["url"]
#print("PROFILE LINK: " + tweet["user"]["url"])
feed = {
'body':body,
'body_json':full_text_json,
'likes': finalLikes,
'urls':urls,
'expanded_urls':expanded_urls,
'experiment_group':'var1',
'post_id':rankk,
'tweet_id':str(tweet["id"]),
'worker_id':str(worker_id),
'refreshh':str(refresh),
'rank':str(rankk),
'picture':image_raw,
'picture_heading':picture_heading,
'picture_description':picture_description,
'actor_name':actor_name,
'actor_picture': actor_picture,
'actor_username': actor_username,
'time':time,
'embedded_image': eimage[0],
'retweet_count': finalRetweets,
'profile_link': profile_link,
'user_retweet': str(tweet['retweeted']),
'user_fav': str(tweet['favorited']),
'retweet_by': retweeted_by,
'quoted_by': quoted_by,
'quoted_by_text' : quoted_by_text,
'quoted_by_actor_username' : quoted_by_actor_username,
'quoted_by_actor_picture' : quoted_by_actor_picture
}
feed_json.append(feed)
rankk = rankk + 1
return jsonify(feed_json) # What is this doing?? Is this where we are sending the json of our feed_json to the other script?
@app.route('/getfeed', methods=['GET'])
def get_feed():
#Experimental code, need to make this so I can get the package back from the request, also need to add cookie checking here eventually.
print("IN GET FEED!!!")
access_token = request.args.get('access_token')
access_token_secret = request.args.get('access_token_secret')
attn = int(request.args.get('attn'))
page = int(request.args.get('page'))
cookiee = request.args.get('cookiee')
print("page : "+str(page))
print("attn : "+str(attn))
print("cookie : "+str(cookiee))
cred = config('../../config.ini','twitterapp')
cred['token'] = access_token.strip()
cred['token_secret'] = access_token_secret.strip()
oauth = OAuth1Session(cred['key'],
client_secret=cred['key_secret'],
resource_owner_key=cred['token'],
resource_owner_secret=cred['token_secret'])
public_tweets = None
worker_id = request.args.get('worker_id')
refresh = 0
#check cookie here and set attn and page to 0 and increment refresh
if cookiee == "NO":
attn = 0
page = 0
refresh = refresh + 1
new_session = False
if attn == 0 and page == 0:
new_session = True
params = {"count": "50","tweet_mode": "extended"}
response = oauth.get("https://api.twitter.com/1.1/statuses/home_timeline.json", params = params)
public_tweets = json.loads(response.text)
#print(tweets)
if public_tweets == "{'errors': [{'message': 'Rate limit exceeded', 'code': 88}]}":
print("Rate limit exceeded.")
db_tweet_payload = []
db_tweet_session_payload = []
db_tweet_attn_payload = []
rankk = 1
all_tweet_ids = [tweet['id'] for tweet in public_tweets]
min_tweet_id = min(all_tweet_ids)
max_tweet_id = max(all_tweet_ids)
for tweet in public_tweets:
if_min_tweet_id = False
if tweet["id"] == min_tweet_id:
if_min_tweet_id = True
if_max_tweet_id = False
if tweet["id"] == max_tweet_id:
if_max_tweet_id = True
db_tweet = {
'tweet_id':tweet["id"],
'tweet_json':tweet
}
db_tweet_payload.append(db_tweet)
db_tweet_session = {
'fav_before':str(tweet['favorited']),
'tid':str(tweet["id"]),
'rtbefore':str(tweet['retweeted']),
'rank':str(rankk),
'tweet_min':str(if_min_tweet_id),
'tweet_max':str(if_max_tweet_id),
'refresh':str(refresh)
}
db_tweet_session_payload.append(db_tweet_session)
if rankk < 20:
db_tweet_attn = {
'tweet_id':str(tweet["id"]),
'rank':str(rankk)
}
db_tweet_attn_payload.append(db_tweet_attn)
rankk = rankk + 1
finalJson = []
finalJson.append(db_tweet_payload)
finalJson.append(db_tweet_session_payload)
finalJson.append(db_tweet_attn_payload)
finalJson.append(worker_id)
requests.post('http://127.0.0.1:5052/insert_tweet',json=finalJson)
public_tweets = public_tweets[0:10]
else:
if attn == 1:
db_response = requests.get('http://127.0.0.1:5052/get_existing_attn_tweets?worker_id='+str(worker_id))
db_response = db_response.json()['data']
public_tweets = [d[1] for d in db_response]
public_tweets = public_tweets[page*5:(page+1)*5]
else:
db_response = requests.get('http://127.0.0.1:5052/get_existing_tweets?worker_id='+str(worker_id)) # This definetely doesnt work right now.
db_response = db_response.json()['data']
public_tweets = [d[4] for d in db_response]
public_tweets = public_tweets[page*10:(page+1)*10]
"""
This is for refresh
if data_db != 'NEW':
tweet_ids = [d[0] for d in data_db]
min_ids = [d[1] for d in data_db]
max_ids = [d[2] for d in data_db]
refresh = data_db[0][3] + 1
max_tweet_id = tweet_ids[max_ids.index(True)]
min_tweet_id = tweet_ids[min_ids.index(True)]
params = {"since_id": str(min_tweet_id-1),"tweet_mode": "extended"}
response = oauth.get("https://api.twitter.com/1.1/statuses/home_timeline.json", params = params)
all_tweets = json.loads(response.text)
new_tweet_ids = []
for tweet in all_tweets:
new_tweet_ids.append(tweet["id"])
deleted_tweet_ids = list(set(tweet_ids) - set(new_tweet_ids))
deleted_tweet_payload = []
for del_tweet in deleted_tweet_ids:
deleted_tweet_payload.append({'del_tweet':str(del_tweet)})
if deleted_tweet_payload:
requests.post('http://127.0.0.1:5052/set_deleted_tweets',json=deleted_tweet_payload)
public_tweets = all_tweets[:20]
"""
feed_json = []
rankk = 1
for tweet in public_tweets: # Modify what tweet is for this loop in order to change the logic ot use our data or twitters.
# Checking for an image in the tweet. Adds all the links of any media type to the eimage list.
actor_name = tweet["user"]["name"]
#tweet_id = str(tweet.id)
full_text = tweet["full_text"]
url_start = []
url_end = []
url_display = []
url_extend = []
url_actual = []
if "entities" in tweet.keys():
if "urls" in tweet["entities"]:
for url_dict in tweet["entities"]["urls"]:
url_start.append(url_dict["indices"][0])
url_end.append(url_dict["indices"][1])
url_display.append(url_dict["display_url"])
url_extend.append(url_dict["expanded_url"])
url_actual.append(url_dict["url"])
last_url_arr = re.findall("(?P<url>https?://[^\s]+)", full_text)
if last_url_arr:
last_url = last_url_arr[-1]
if last_url not in url_actual:
full_text = full_text.replace(last_url,'')
full_text_json = []
if url_actual:
normal_idx = 0
url_idx = 0
for i in range(len(url_start)):
url_idx_start = url_start[i]
full_text_json.append({"text":full_text[normal_idx:url_idx_start],"url":""})
full_text_json.append({"text":url_extend[i],"url":url_extend[i]})
normal_idx = url_end[i]
if normal_idx < len(full_text):
full_text_json.append({"text":full_text[normal_idx:len(full_text)],"url":""})
else:
full_text_json.append({"text":full_text,"url":""})
isRetweet = False
retweeted_by = ""
actor_picture = tweet["user"]["profile_image_url"]
actor_username = tweet["user"]["screen_name"]
tempLikes = tweet["favorite_count"]
quoted_by = ""
quoted_by_text = ""
quoted_by_actor_username = ""
quoted_by_actor_picture = ""
isQuote = False
try: # This will handle retweet case and nested try will handle retweeted quote
full_text = tweet["retweeted_status"]["full_text"]
retweeted_by = actor_name # Grab it here before changing the name
# Now I need to check if the retweeted status is a quoted status I think.
try:
full_text = tweet["retweeted_status"]["quoted_status"]["full_text"]
quoted_by = tweet["retweeted_status"]["user"]["name"] # name of the retweet who quoted
quoted_by_text = tweet["retweeted_status"]["full_text"]
quoted_by_actor_username = tweet["retweeted_status"]["user"]["screen_name"]
quoted_by_actor_picture = tweet["retweeted_status"]["user"]["profile_image_url"]
actor_name = tweet["retweeted_status"]["quoted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["retweeted_status"]["quoted_status"]["user"]["screen_name"]
actor_picture = tweet["retweeted_status"]["quoted_status"]["user"]["profile_image_url"]
tempLikes = tweet["retweeted_status"]["quoted_status"]["favorite_count"]
isQuote = True
except: # if its not a quote default to normal retweet settings
actor_name = tweet["retweeted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["retweeted_status"]["user"]["screen_name"]
actor_picture = tweet["retweeted_status"]["user"]["profile_image_url"]
tempLikes = tweet["retweeted_status"]["favorite_count"]
isRetweet = True
isRetweet = True
except:
isRetweet = False
if not isRetweet: # case where its not a retweet but still could be a quote.
try:
full_text = tweet["quoted_status"]["full_text"]
quoted_by = tweet["user"]["name"] # name of the person who quoted
quoted_by_text = tweet["full_text"]
quoted_by_actor_username = tweet["user"]["screen_name"]
quoted_by_actor_picture = tweet["user"]["profile_image_url"]
actor_name = tweet["quoted_status"]["user"]["name"] # original tweeter info used below.
actor_username = tweet["quoted_status"]["user"]["screen_name"]
actor_picture = tweet["quoted_status"]["user"]["profile_image_url"]
tempLikes = tweet["quoted_status"]["favorite_count"]
isQuote = True
except:
isQuote = False
entities_keys = ""
all_urls = ""
urls_list = []
expanded_urls_list = []
urls = ""
expanded_urls = ""
image_raw = ""
picture_heading = ""
picture_description = ""
mediaArr = ""
# Decision making for the block to retrieve article cards AND embedded images
if isQuote and isRetweet: # Check for the case of a quote within a retweet.
entities_keys = tweet["retweeted_status"]["quoted_status"]["entities"].keys()
mediaArr = tweet["retweeted_status"]["quoted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["retweeted_status"]["quoted_status"]["entities"]["urls"]
elif isQuote: # quote only case
entities_keys = tweet["quoted_status"]["entities"].keys()
mediaArr = tweet["quoted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["quoted_status"]["entities"]["urls"]
elif isRetweet:
entities_keys = tweet["retweeted_status"]["entities"].keys()
mediaArr = tweet["retweeted_status"]['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["retweeted_status"]["entities"]["urls"]
else:
entities_keys = tweet["entities"].keys()
mediaArr = tweet['entities'].get('media',[])
if "urls" in entities_keys:
all_urls = tweet["entities"]["urls"]
# Redesigned block to retrieve the Cardinfo data. Old placement and OG version.
#if "urls" in entities_keys:
# for each_url in all_urls:
# urls_list.append(each_url["url"])
# expanded_urls_list.append(each_url["expanded_url"])
# urls = ",".join(urls_list)
# expanded_urls = ",".join(expanded_urls_list)
#if len(expanded_urls_list) > 0 and not isQuote: # not isQuote is to save time in the case of a quote. no card needed
# card_url = expanded_urls_list[0]
# card_data = Cardinfo.getCardData(card_url)
# if "image" in card_data.keys():
# image_raw = card_data['image']
# picture_heading = card_data["title"]
# picture_description = card_data["description"]
# Embedded image retrieval (edited to handle retweets also now)
hasEmbed = False
eimage = []
try: # Not sure why this has an issue all of a sudden.
flag_image = False
if len(mediaArr) > 0:
for x in range(len(mediaArr)):
if mediaArr[x]['type'] == 'photo':
hasEmbed = True
if "sizes" in mediaArr[x].keys():
if "small" in mediaArr[x]["sizes"].keys():
small_width = int(mediaArr[x]["sizes"]["small"]["w"])
small_height = int(mediaArr[x]["sizes"]["small"]["h"])
small_aspect_ratio = small_height/small_width
if small_aspect_ratio > 0.89:
if "thumb" in mediaArr[x]["sizes"].keys():
eimage.append(mediaArr[x]['media_url']+':thumb')
else:
eimage.append(mediaArr[x]['media_url']+':small')
else:
eimage.append(mediaArr[x]['media_url']+':small')
else:
eimage.append(mediaArr[x]['media_url'])
else:
eimage.append(mediaArr[x]['media_url'])
flag_image = True
if not flag_image:
eimage.append("")
except Exception as error:
print(error)
eimage[0] = ""
# Redesigned block to retrieve the Cardinfo data.
if "urls" in entities_keys and not hasEmbed:
for each_url in all_urls:
urls_list.append(each_url["url"])
expanded_urls_list.append(each_url["expanded_url"])
urls = ",".join(urls_list)
expanded_urls = ",".join(expanded_urls_list)
if len(expanded_urls_list) > 0 and not isQuote and not hasEmbed: # not isQuote is to save time in the case of a quote. no card needed
card_url = expanded_urls_list[0]
card_data = Cardinfo.getCardData(card_url)
if card_data:
if "image" in card_data.keys():
image_raw = card_data['image']
picture_heading = card_data["title"]
picture_description = card_data["description"]
#if isRetweet:
#print("Is a retweet.")
for urll in urls_list:
full_text = full_text.replace(urll,"")
#print(full_text)
full_text = xml.sax.saxutils.unescape(full_text)
body = full_text
date_string_temp = tweet['created_at'].split()
date_string = date_string_temp[1] + " " + date_string_temp[2] + " " + date_string_temp[3] + " " + date_string_temp[5]
td = (datetime.datetime.now() - datetime.datetime.strptime(date_string,"%b %d %H:%M:%S %Y"))
hours, remainder = divmod(td.seconds, 3600) # can we scrap this and the line below ______-------________-----________---------______--------
minutes, seconds = divmod(remainder, 60)
time = ""
if minutes < 10:
time = "-00:0"+str(minutes)
else:
time = "-00:"+str(minutes)
#time.append(td.seconds)
# Fixing the like system
finalLikes = ""
if (tempLikes <= 999):
finalLikes = str(tempLikes)
elif (tempLikes >= 1000):
counterVar = 1
while(True):
if (tempLikes - 1000 > 0):
tempLikes = tempLikes - 1000
counterVar = counterVar + 1
else:
finalLikes = str(counterVar) + "." + str(tempLikes)[0] + "k"
break
# Fixing the retweet system
finalRetweets = ""
tempRetweets = tweet["retweet_count"]
if (tempRetweets <= 999):
finalRetweets = str(tempRetweets)
elif (tempRetweets >= 1000):
counterVar = 1
while(True):
if (tempRetweets - 1000 > 0):
tempRetweets = tempRetweets - 1000
counterVar = counterVar + 1
else:
finalRetweets = str(counterVar) + "." + str(tempRetweets)[0] + "k"
break
profile_link = ""
if tweet["user"]["url"]:
profile_link = tweet["user"]["url"]
#print("PROFILE LINK: " + tweet["user"]["url"])
feed = {
'body':body,
'body_json':full_text_json,
'likes': finalLikes,
'urls':urls,
'expanded_urls':expanded_urls,
'experiment_group':'var1',
'post_id':rankk,
'tweet_id':str(tweet["id"]),
'worker_id':str(worker_id),
'refreshh':str(refresh),
'rank':str(rankk),
'picture':image_raw,
'picture_heading':picture_heading,
'picture_description':picture_description,
'actor_name':actor_name,
'actor_picture': actor_picture,
'actor_username': actor_username,
'time':time,
'embedded_image': eimage[0],
'retweet_count': finalRetweets,
'profile_link': profile_link,
'user_retweet': str(tweet['retweeted']),
'user_fav': str(tweet['favorited']),
'retweet_by': retweeted_by,
'quoted_by': quoted_by,
'quoted_by_text' : quoted_by_text,
'quoted_by_actor_username' : quoted_by_actor_username,
'quoted_by_actor_picture' : quoted_by_actor_picture
}
feed_json.append(feed)
rankk = rankk + 1
return jsonify(feed_json) # What is this doing?? Is this where we are sending the json of our feed_json to the other script?
@app.after_request
def add_headers(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization')
return response
if __name__ == "__main__":
app.run(host = "0.0.0.0", port = 5051)
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0
| 7
|
a94e59ac44d1fe3562afde682f2f3a4656f5c95e
| 145,260
|
py
|
Python
|
startup/95-sample-custom.py
|
tacaswell/profile_collection-1
|
aca17c69fd0482901de9d48b1609b3156eb90f17
|
[
"BSD-3-Clause"
] | null | null | null |
startup/95-sample-custom.py
|
tacaswell/profile_collection-1
|
aca17c69fd0482901de9d48b1609b3156eb90f17
|
[
"BSD-3-Clause"
] | 6
|
2017-05-09T15:25:14.000Z
|
2021-01-22T21:28:43.000Z
|
startup/95-sample-custom.py
|
tacaswell/profile_collection-1
|
aca17c69fd0482901de9d48b1609b3156eb90f17
|
[
"BSD-3-Clause"
] | 2
|
2018-08-30T18:45:21.000Z
|
2021-12-31T02:01:08.000Z
|
################################################################################
# Code for customer-made holders and sample stages,
# Samples include :
# 1. SampleTSAXS_Generic : TSAXS/TWAXS
# 2. SampleGISAXS_Generic : GISAXS/GIWAXS
# 3. SampleXR_WAXS : XR and th-2th scan
# 4. SampleCDSAXS_Generic : CD SAXS/GISAXS
# 5. SampleGonio_Generic : SmartAct Goniometer
# 6. SampleSecondStage : 2nd sample stage
# Holders include :
# 1. CapillaryHolder : TSAXS
# 2. GIBar : GISAXS/GIWAXS bar
# 3. CapillaryHolderHeated : heat stage for transmission
# 4. GIBar_long_thermal : heat stage for GI
# 5. WellPlateHolder: well plate
# 6. PaloniThermalStage: special stage made in brass by UCSB group.
# 7. DSCStage : tranmission stage for DSC capsules
# 8. InstecStage60 : HCS 60, From Sam Sprunt (Kent State U. )
# 9. InstecStage402 : HCS 402, beamline owned
# 10.OffCenteredHoder: GTSAXS
# TODO: some clean-ups.
# 1. make rotational stage as custom stage with phi, strans, strans2, tilt, tilt2 stages.
#
################################################################################
# custmer-made samples.
class SampleTSAXS_Generic(Sample_Generic):
################# Direct beam transmission measurement ####################
def intMeasure(self, output_file, exposure_time):
'''Measure the transmission intensity of the sample by ROI4.
The intensity will be saved in output_file
'''
if abs(beam.energy(verbosity=0) - 13.5) < 0.1:
beam.setAbsorber(4)
elif abs(beam.energy(verbosity=0) - 17) < 0.1:
beam.setAbsorber(6)
print('Absorber is moved to position {}'.format(beam.absorber()[0]))
detselect([pilatus2M])
if beam.absorber()[0]>=4:
bsx.move(bsx.position+6)
beam.setTransmission(1)
self.measure(exposure_time)
temp_data = self.transmission_data_output(beam.absorber()[0])
cms.modeMeasurement()
#beam.setAbsorber(0)
beam.absorber_out()
#output_data = output_data.iloc[0:0]
#create a data file to save the INT data
INT_FILENAME='{}/data/{}.csv'.format(os.path.dirname(__file__) , output_file)
if os.path.isfile(INT_FILENAME):
output_data = pds.read_csv(INT_FILENAME, index_col=0)
output_data = output_data.append(temp_data, ignore_index=True)
output_data.to_csv(INT_FILENAME)
else:
temp_data.to_csv(INT_FILENAME)
def transmission_data_output(self, slot_pos):
'''Output the tranmission of direct beam
'''
h = db[-1]
dtable = h.table()
#beam.absorber_transmission_list = [1, 0.041, 0.0017425, 0.00007301075, 0.00000287662355, 0.000000122831826, 0.00000000513437]
scan_id = h.start['scan_id']
I_bim5 = h.start['beam_int_bim5'] #beam intensity from bim5
I0 = dtable.pilatus2M_stats4_total
filename = h.start['sample_name']
exposure_time = h.start['sample_exposure_time']
#I2 = dtable.pilatus2M_stats2_total
#I3 = 2*dtable.pilatus2M_stats1_total - dtable.pilatus2M_stats2_total
#In = I3 / beam.absorber_transmission_list[slot_pos] / exposure_time
current_data = {'a_filename': filename,
'b_scanID': scan_id,
'c_I0': I0,
'd_I_bim5': I_bim5,
'e_absorber_slot': slot_pos,
#'f_absorber_ratio': beam.absorber_transmission_list[slot_pos],
'f_absorber_ratio': beam.absorber()[1],
'g_exposure_seconds': exposure_time}
return pds.DataFrame(data=current_data)
class SampleGISAXS_Generic(Sample_Generic):
def __init__(self, name, base=None, **md):
super().__init__(name=name, base=base, **md)
self.naming_scheme = ['name', 'extra', 'th', 'exposure_time']
self.incident_angles_default = [0.08, 0.10, 0.12, 0.15, 0.20]
self.measure_setting={}
self.alignDone=False
def measureSpots(self, num_spots=2, translation_amount=0.1, axis='x', exposure_time=None, extra=None, measure_type='measureSpots', **md):
super().measureSpots(num_spots=num_spots, translation_amount=translation_amount, axis=axis, exposure_time=exposure_time, extra=extra, measure_type=measure_type, **md)
def measureIncidentAngle(self, angle, exposure_time=None, extra=None, tiling=None, **md):
self.thabs(angle)
while sth.moving==True:
time.sleep(.1)
self.measure(exposure_time=exposure_time, extra=extra, tiling=tiling, **md)
def measureIncidentAngles(self, angles=None, exposure_time=None, extra=None, tiling=None, **md):
#measure the incident angles first and then change the tiling features.
if angles is None:
angles = self.incident_angles_default
for angle in angles:
self.measureIncidentAngle(angle, exposure_time=exposure_time, extra=extra, tiling=tiling, **md)
def measureIncidentAngles_Stitch(self, angles=None, exposure_time=None, extra=None, tiling=None, verbosity=3, **md):
#measure the incident angles first and then change the tiling features.
if tiling == None:
if angles is None:
angles = self.incident_angles_default
for angle in angles:
self.measureIncidentAngle(angle, exposure_time=exposure_time, extra=extra, tiling=tiling, **md)
elif tiling=='ygaps':
if angles is None:
angles = self.incident_angles_default
#pos1
for angle in angles:
self.thabs(angle)
while sth.moving==True:
time.sleep(0.1)
time.sleep(.5)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
MAXSy_o = MAXSy.user_readback.value
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
for angle in angles:
self.thabs(angle)
while sth.moving==True:
time.sleep(0.1)
time.sleep(.5)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
if MAXSy.user_readback.value != MAXSy_o:
MAXSy.move(MAXSy_o)
elif tiling == 'xygaps':
if angles is None:
angles = self.incident_angles_default
#pos1
for angle in angles:
self.thabs(angle)
time.sleep(.5)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower_left'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
#MAXSy_o = MAXSy.user_readback.value
for angle in angles:
self.thabs(angle)
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos4 #comment out to save time
for angle in angles:
self.thabs(angle)
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o + 5.16)
extra_current = 'pos4' if extra is None else '{}_pos4'.format(extra)
md['detector_position'] = 'upper_right'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos3
for angle in angles:
self.thabs(angle)
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy_o)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o)
extra_current = 'pos3' if extra is None else '{}_pos3'.format(extra)
md['detector_position'] = 'lower_right'
self.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if WAXSx.user_readback.value != WAXSx_o:
WAXSx.move(WAXSx_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
if SAXSx.user_readback.value != SAXSx_o:
SAXSx.move(SAXSx_o)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
def _alignOld(self, step=0):
'''Align the sample with respect to the beam. GISAXS alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
# TODO: Deprecate and delete
if step<=0:
# TODO: Check what mode we are in, change if necessary...
# get_beamline().modeAlignment()
beam.on()
# TODO: Improve implementation
if step<=2:
#fit_scan(smy, 2.6, 35, fit='HM')
fit_scan(smy, 2.6, 35, fit='sigmoid_r')
if step<=4:
#fit_scan(smy, 0.6, 17, fit='HM')
fit_scan(smy, 0.6, 17, fit='sigmoid_r')
fit_scan(sth, 1.2, 21, fit='max')
#if step<=6:
# fit_scan(smy, 0.3, 17, fit='sigmoid_r')
# fit_scan(sth, 1.2, 21, fit='COM')
if step<=8:
fit_scan(smy, 0.2, 17, fit='sigmoid_r')
fit_scan(sth, 0.8, 21, fit='gauss')
if step<=9:
#self._testing_refl_pos()
#movr(sth,.1)
#fit_scan(sth, 0.2, 41, fit='gauss')
#fit_scan(smy, 0.2, 21, fit='gauss')
#movr(sth,-.1)
beam.off()
def align(self, step=0, reflection_angle=0.08, verbosity=3):
'''Align the sample with respect to the beam. GISAXS alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam. Finally, the angle is re-optimized
in reflection mode.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
if verbosity>=4:
print(' Aligning {}'.format(self.name))
if step<=0:
# Prepare for alignment
if RE.state!='idle':
RE.abort()
if get_beamline().current_mode!='alignment':
#if verbosity>=2:
#print("WARNING: Beamline is not in alignment mode (mode is '{}')".format(get_beamline().current_mode))
print("Switching to alignment mode (current mode is '{}')".format(get_beamline().current_mode))
get_beamline().modeAlignment()
get_beamline().setDirectBeamROI()
beam.on()
if step<=2:
if verbosity>=4:
print(' align: searching')
# Estimate full-beam intensity
value = None
if True:
# You can eliminate this, in which case RE.md['beam_intensity_expected'] is used by default
self.yr(-2)
#detector = gs.DETS[0]
detector = get_beamline().detector[0]
value_name = get_beamline().TABLE_COLS[0]
RE(count([detector]))
value = detector.read()[value_name]['value']
self.yr(+2)
if 'beam_intensity_expected' in RE.md:
if value<RE.md['beam_intensity_expected']*0.75:
print('WARNING: Direct beam intensity ({}) lower than it should be ({})'.format(value, RE.md['beam_intensity_expected']))
# Find the step-edge
self.ysearch(step_size=0.5, min_step=0.005, intensity=value, target=0.5, verbosity=verbosity, polarity=-1)
# Find the peak
self.thsearch(step_size=0.4, min_step=0.01, target='max', verbosity=verbosity)
if step<=4:
if verbosity>=4:
print(' align: fitting')
fit_scan(smy, 1.2, 21, fit='HMi')
##time.sleep(2)
fit_scan(sth, 1.5, 21, fit='max')
##time.sleep(2)
#if step<=5:
# #fit_scan(smy, 0.6, 17, fit='sigmoid_r')
# fit_edge(smy, 0.6, 17)
# fit_scan(sth, 1.2, 21, fit='max')
if step<=8:
#fit_scan(smy, 0.3, 21, fit='sigmoid_r')
fit_edge(smy, 0.6, 21)
#time.sleep(2)
#fit_edge(smy, 0.4, 21)
fit_scan(sth, 0.8, 21, fit='COM')
#time.sleep(2)
self.setOrigin(['y', 'th'])
if step<=9 and reflection_angle is not None:
# Final alignment using reflected beam
if verbosity>=4:
print(' align: reflected beam')
get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0)
#get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0, size=[12,2])
self.thabs(reflection_angle)
result = fit_scan(sth, 0.4, 41, fit='max')
#result = fit_scan(sth, 0.2, 81, fit='max') #it's useful for alignment of SmarAct stage
sth_target = result.values['x_max']-reflection_angle
if result.values['y_max']>50:
th_target = self._axes['th'].motor_to_cur(sth_target)
self.thsetOrigin(th_target)
#fit_scan(smy, 0.2, 21, fit='max')
#self.setOrigin(['y'])
if step<=10:
self.thabs(0.0)
beam.off()
def _test_align(self, step=0, reflection_angle=0.12, verbosity=3):
'''Align the sample with respect to the beam. GISAXS alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam. Finally, the angle is re-optimized
in reflection mode.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
if verbosity>=4:
print(' Aligning {}'.format(self.name))
if step<=0:
# Prepare for alignment
if RE.state!='idle':
RE.abort()
if get_beamline().current_mode!='alignment':
#if verbosity>=2:
#print("WARNING: Beamline is not in alignment mode (mode is '{}')".format(get_beamline().current_mode))
print("Switching to alignment mode (current mode is '{}')".format(get_beamline().current_mode))
get_beamline().modeAlignment()
get_beamline().setDirectBeamROI()
#if step<=2:
#if verbosity>=4:
#print(' align: searching')
#beam.on()
## Estimate full-beam intensity
#value = None
#if True:
## You can eliminate this, in which case RE.md['beam_intensity_expected'] is used by default
#self.yr(-2)
##detector = gs.DETS[0]
#detector = get_beamline().detector[0]
#value_name = get_beamline().TABLE_COLS[0]
#RE(count([detector]))
#value = detector.read()[value_name]['value']
#self.yr(+2)
#if 'beam_intensity_expected' in RE.md and value<RE.md['beam_intensity_expected']*0.75:
#print('WARNING: Direct beam intensity ({}) lower than it should be ({})'.format(value, RE.md['beam_intensity_expected']))
## Find the step-edge
#self.ysearch(step_size=0.5, min_step=0.005, intensity=value, target=0.5, verbosity=verbosity, polarity=-1)
## Find the peak
#self.thsearch(step_size=0.4, min_step=0.01, target='max', verbosity=verbosity)
if step<=4:
if verbosity>=4:
print(' align: fitting')
fit_scan(smy, 1.2, 21, fit='HMi')
##time.sleep(2)
fit_scan(sth, 1.5, 21, fit='max')
##time.sleep(2)
#if step<=8 and reflection_angle==None:
#fit_edge(smy, 0.6, 21)
##time.sleep(2)
#fit_scan(sth, 0.8, 21, fit='COM')
#self.setOrigin(['y', 'th'])
if step<=9 and reflection_angle is not None:
# Final alignment using reflected beam
if verbosity>=4:
print(' align: reflected beam')
get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0)
#sth scan
self.thabs(reflection_angle)
result = fit_scan(sth, 0.4, 41, fit='max')
sth_target = result.values['x_max']-reflection_angle
if result.values['y_max']>50:
th_target = self._axes['th'].motor_to_cur(sth_target)
self.thsetOrigin(th_target)
#y scan
fit_scan(smy, 0.2, 21, fit='max')
self.setOrigin(['y'])
if step<=10:
self.thabs(0.0)
beam.off()
def alignQuick(self, align_step=8, reflection_angle=0.08, verbosity=3):
get_beamline().modeAlignment()
#self.yo()
self.tho()
beam.on()
self.align(step=align_step, reflection_angle=reflection_angle, verbosity=verbosity)
def level(self, step=0,pos_x_left=-5, pos_x_right=5):
#TODO: Move this code. (This should be a property of the GIBar object.)
#level sample by checking bar height at pos_left and pos_right
print('checking the level of Sample')
if step<=1:
cms.modeAlignment()
self.tho()
self.yo()
self.xabs(pos_x_left)
#beam.on()
fit_edge(smy, .6, 17) #it's better not to move smy after scan but only the center position
time.sleep(1)
pos_y_left=smy.position
#pos_y_left=smy.user_readback.value
print('BEFORE LEVEL: pos_y_left = {}'.format(pos_y_left))
self.xabs(pos_x_right)
fit_edge(smy, .6, 17) #it's better not to move smy after scan but only the center position
time.sleep(1)
pos_y_right=smy.position
print('BEFORE LEVEL: pos_y_right = {}'.format(pos_y_right))
offset_schi=(pos_y_right-pos_y_left)/(pos_x_right-pos_x_left)*180/np.pi
print('The schi offset is {} degrees'.format(offset_schi))
schi.move(schi.position - offset_schi)
#double-check the chi offset
self.xabs(pos_x_left)
fit_edge(smy, .6, 17) #it's better not to move smy after scan but only the center position
time.sleep(1)
pos_y_left=smy.position
print('AFTER LEVEL: pos_y_left = {}'.format(pos_y_left))
self.xabs(pos_x_right)
fit_edge(smy, .6, 17) #it's better not to move smy after scan but only the center position
time.sleep(1)
pos_y_right=smy.position
print('AFTER LEVEL: pos_y_right = {}'.format(pos_y_right))
#beam.off()
self.xo()
offset_schi=(pos_y_right-pos_y_left)/(pos_x_right-pos_x_left)*180/np.pi
if offset_schi<=0.1:
print('schi offset is aligned successfully!')
else:
print('schi offset is WRONG. Please redo the level command')
fit_edge(smy, .6, 17) #it's better not to move smy after scan but only the center position
self.setOrigin(['y'])
def do(self, step=0, align_step=0, **md):
if step<=1:
get_beamline().modeAlignment()
if step<=2:
self.xo() # goto origin
if step<=4:
self.yo()
self.tho()
if step<=5:
self.align(step=align_step, reflection_angle=0.12)
#self.setOrigin(['y','th']) # This is done within align
#if step<=7:
#self.xr(0.2)
if step<=8:
get_beamline().modeMeasurement()
if step<=10:
#detselect([pilatus300, psccd])
#detselect(psccd)
#detselect(pilatus300)
detselect(pilatus2M)
for detector in get_beamline().detector:
if detector.name == 'pilatus2M':
RE(detector.setExposureTime(self.md['exposure_time']))
else:
detector.setExposureTime(self.md['exposure_time'])
self.measureIncidentAngles(self.incident_angles_default, **md)
self.thabs(0.0)
def backup_do_SAXS(self, step=0, align_step=0, measure_setting=None, **md):
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
self.xo() # goto origin
if step<=4:
self.yo()
self.tho()
if step<=5:
self.align(step=align_step, reflection_angle=0.12)
#self.setOrigin(['y','th']) # This is done within align
#if step<=7:
#self.xr(0.2)
if step<=8:
get_beamline().modeMeasurement()
if step<=10:
if measure_setting==None:
measure_setting=measure_setting
if self.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
self.measureIncidentAngles_Stitch(incident_angles, exposure_time=self.SAXS_time, tiling='ygaps', **md)
def do_SAXS(self, step=0, align_step=0, measure_setting=None, **md):
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
self.xo() # goto origin
if step<=4:
self.yo()
self.tho()
if step<=5:
self.align(step=align_step, reflection_angle=0.12)
#self.setOrigin(['y','th']) # This is done within align
#if step<=7:
#self.xr(0.2)
if step<=8:
get_beamline().modeMeasurement()
self.alignDone=True
if step<=10:
if self.measure_setting['incident_angles']==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.measure_setting['incident_angles']
if self.measure_setting['exposure_time']==None:
exposure_time = self.SAXS_time
else:
if type(self.measure_setting['exposure_time'])==list:
exposure_time = self.measure_setting['exposure_time'][0]
else:
exposure_time = self.measure_setting['exposure_time']
tiling = self.measure_setting['tiling']
self.measureIncidentAngles_Stitch(incident_angles, exposure_time=exposure_time, tiling=tiling, **md)
def do_WAXS_only(self, step=0, align_step=0, **md):
if step<5:
self.xo()
self.yo()
self.tho()
get_beamline().modeMeasurement()
if step<=10:
if self.measure_setting['incident_angles']==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.measure_setting['incident_angles']
if self.measure_setting['exposure_time']==None:
exposure_time = self.SAXS_time
else:
if type(self.measure_setting['exposure_time'])==list:
exposure_time = self.measure_setting['exposure_time'][0]
else:
exposure_time = self.measure_setting['exposure_time']
tiling = self.measure_setting['tiling']
waxs_on()
self.measureIncidentAngles_Stitch(incident_angles, exposure_time=exposure_time, tiling=tiling, **md)
self.thabs(0.0)
def _backup_do_WAXS(self, step=0, align_step=0, **md):
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
self.xo() # goto origin
if step<=4:
self.yo()
self.tho()
if step<=5:
self.align(step=align_step, reflection_angle=0.12)
#self.setOrigin(['y','th']) # This is done within align
#if step<=7:
#self.xr(0.2)
if step<=8:
get_beamline().modeMeasurement()
if step<=10:
if self.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
waxs_on() # edited from waxs_on 3/25/19 through a saxs_on error
#for detector in get_beamline().detector:
#detector.setExposureTime(self.MAXS_time)
self._test2_measureIncidentAngles(incident_angles, exposure_time=self.WAXS_time, tiling='ygaps', **md)
#if self.exposure_time_MAXS==None:
#self.measureIncidentAngles(incident_angles, exposure_time=self.MAXS_time, tiling=self.tiling, **md)
#else:
#self.measureIncidentAngles(incident_angles, exposure_time=self.exposure_time_MAXS, tiling=self.tiling, **md)
self.thabs(0.0)
def do_WAXS(self, step=0, align_step=0, **md):
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
self.xo() # goto origin
if step<=4:
self.yo()
self.tho()
if step<=5:
self.align(step=align_step, reflection_angle=0.12)
#self.setOrigin(['y','th']) # This is done within align
#if step<=7:
#self.xr(0.2)
if step<=8:
get_beamline().modeMeasurement()
if step<=10:
if self.measure_setting['incident_angles']==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.measure_setting['incident_angles']
if self.measure_setting['exposure_time']==None:
exposure_time = self.SAXS_time
else:
if type(self.measure_setting['exposure_time'])==list:
exposure_time = self.measure_setting['exposure_time'][0]
else:
exposure_time = self.measure_setting['exposure_time']
tiling = self.measure_setting['tiling']
waxs_on()
self.measureIncidentAngles_Stitch(incident_angles, exposure_time=exposure_time, tiling=tiling, **md)
self.thabs(0.0)
class SampleCDSAXS_Generic(Sample_Generic):
def __init__(self, name, base=None, **md):
super().__init__(name=name, base=base, **md)
self.naming_scheme = ['name', 'extra', 'phi', 'exposure_time']
self.rot_angles_default = np.arange(-45, +45+1, +1)
#self.rot_angles_default = np.linspace(-45, +45, num=90, endpoint=True)
def _set_axes_definitions(self):
'''Internal function which defines the axes for this stage. This is kept
as a separate function so that it can be over-ridden easily.'''
super()._set_axes_definitions()
self._axes_definitions.append( {'name': 'phi',
'motor': srot,
'enabled': True,
'scaling': +1.0,
'units': 'deg',
'hint': None,
} )
def measureAngle(self, angle, exposure_time=None, extra=None, measure_type='measure', **md):
self.phiabs(angle)
self.measure(exposure_time=exposure_time, extra=extra, measure_type=measure_type, **md)
def measureAngles(self, angles=None, exposure_time=None, extra=None, measure_type='measureAngles', **md):
if angles is None:
angles = self.rot_angles_default
for angle in angles:
self.measureAngle(angle, exposure_time=exposure_time, extra=extra, measure_type=measure_type, **md)
class SampleXR_WAXS(SampleGISAXS_Generic):
################# Specular reflectivity (XR) measurement ####################
def XR_scan(self, scan_type='theta_scan', theta_range=[0,1.6], theta_delta=0.1, theta_list=None, qz_list=None, roi_size=[12,30], exposure_time=1, threshold=20000, max_exposure_time=10, extra='XR_scan', output_file=None, **md):
''' Run x-ray reflectivity measurement for thin film samples on WAXS pilatus800k.
There will be two WAXSy positions for XR.
The 1st position is the beam shining directly on the detector with maximum attenuation.
This position is defined by cms.WAXS.setCalibration([734, 1090],0.255, [-65, -73])
The 2nd position is the beam out of the WAXS detector.
The detector will be moved to the 2nd position when the reflected beam out of beam stop.
Parameters
----------
scan_type : list
theta_scan: in step of theta
q_scan: in step of q
theta_range: list
The scanning range. It can be single section or multiple sections with various step_size.
Examples:
[0, 1.6] or
[[0, .3],[0.3, 1], [1, 1.6]]
theta_delta: float or list
The scaning step. Examples:
0.02 or
[0.005, 0.1, 0.2]
roi_size: float
The szie of ROI1.
exposure_time: float
The mininum exposure time
min_step : float
The final (minimum) step size to try
intensity : float
The expected full-beam intensity readout
threshold : float
The threshold of minimum intensity. Exposure time increases automatically if < max_exposure_time
max_exposure_time : float
The maximum of exposure time to limit the total time.
'''
#TODO:
#if theta_end < theta_start:
# print("The theta_end is larger than theta_start!!!")
#disable the besteffortcallback and plot all ROIs
#bec.disable_table()
cms.modeXRMeasurement()
cms.definePos(size=roi_size)
bec.disable_plots()
cms.WAXS.detector.stats1.total.kind = 'hinted'
cms.WAXS.detector.stats2.total.kind = 'hinted'
self.naming_scheme_hold = self.naming_scheme
self.naming_scheme = ['name', 'extra', 'x', 'th', 'exposure_time']
#default_WAXSy = WAXSy.position
#move in absorber and move out the beamstop
slot_pos = 4
beam.setAbsorber(slot_pos)
if beam.absorber()[0]>=4:
bsx.move(bsx.position+6)
beam.setTransmission(1)
#create a clean dataframe and a direct beam images
self.yr(-2)
self.tho()
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
direct_beam_slot = 4
#Energy = 17kev
if abs(beam.energy(verbosity=1)-17) < 0.1:
direct_beam_slot = 6
slot_pos = 6
#Energy = 17kev
if abs(beam.energy(verbosity=1)-10) < 0.1:
direct_beam_slot = 3
beam.setAbsorber(direct_beam_slot)
#TODO:move detector to the 1st position and setROI
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos1)
get_beamline().setXRROI(total_angle=0,size=roi_size,default_WAXSy=None)
self.measure(exposure_time, extra='direct_beam')
self.yo()
output_data = self.XR_data_output(direct_beam_slot, exposure_time)
#output_data = output_data.iloc[0:0]
#create a data file to save the XRR data
if output_file is None:
header = db[-1]
#XR_FILENAME='{}/data/{}.csv'.format(os.path.dirname(__file__) , header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}_{}.csv'.format(header.start['experiment_alias_directory'],header.start['sample_name'], header.get('start').get('scan_id')+1)
XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], header.start['filename'])
print('FILENAME= {}'.format(XR_FILENAME))
else:
XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], output_file)
#load theta positions in scan
if scan_type == 'theta_scan':
#list the sth positions in scan
if theta_list==None:
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
else:
theta_list = theta_list
#
'''
if np.size(theta_range) == 2:
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
#multiple sections for measurement
else:
theta_list=[]
if np.shape(theta_range)[0] != np.size(theta_delta):
print("The theta_range does not match theta_delta")
return
if np.shape(theta_range)[-1] != 2:
print("The input of theta_range is incorrect.")
return
for number, item in enumerate(theta_range):
theta_list_temp = np.arange(item[0], item[1], theta_delta[number])
theta_list.append(theta_list_temp)
theta_list = np.hstack(theta_list)
'''
elif scan_type == 'qz_scan':
if qz_list is not None:
qz_list = qz_list
else:
qz_list = self.qz_list_default
theta_list = np.rad2deg(np.arcsin(qz_list * header.start['calibration_wavelength_A']/4/np.pi))
pos_flag = 0
for theta in theta_list:
self.thabs(theta)
#get_beamline().setSpecularReflectivityROI(total_angle=theta*2,size=roi_size,default_SAXSy=-73)
#if cms.out_of_beamstop(total_angle=theta*2, size=roi_size):
if cms.beamOutXR(total_angle=theta*2,roi=cms.XR_pos2)==False:
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos1)
get_beamline().setXRROI(total_angle=theta*2,size=roi_size)
print('WAXS in POS1 for XR')
elif pos_flag == 0:
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos2)
get_beamline().setXRROI(total_angle=theta*2,size=roi_size)
print('WAXS in POS2 for XR')
pos_flag=1
else:
get_beamline().setXRROI(total_angle=theta*2,size=roi_size)
print('WAXS in POS2 for XR')
pos_flag=1
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
print('data = {}'.format(temp_data))
#initial exposure period
N = 1
N_last = 1
if threshold is not None and type(threshold) == int :
while temp_data['e_I1'][temp_data.index[-1]] < threshold and N < max_exposure_time:
if slot_pos > 0:
if temp_data['e_I1'][temp_data.index[-1]] < threshold: #The count is too small to evaluate the next slot_pos.
slot_pos = slot_pos - 1
else:
slot_current = beam.absorber_transmission_list[slot_pos]*threshold/temp_data['e_I1'][temp_data.index[-1]]
for slot_no in np.arange(5, 0, -1):
if slot_current > beam.absorber_transmission_list[slot_no]:
slot_pos = slot_no - 1
beam.setAbsorber(slot_pos)
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
else:
if threshold/float(temp_data['e_I1'][temp_data.index[-1]]) < max_exposure_time and N_last < max_exposure_time:
N = np.ceil(N_last*threshold/float(temp_data['e_I1'][temp_data.index[-1]]))
print('e_I1={}'.format(float(temp_data['e_I1'][temp_data.index[-1]])))
print('N={}'.format(N))
print('exposure time = {}'.format(N*exposure_time))
else:
N = max_exposure_time
print('exposure time is MAX')
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(N*exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, N*exposure_time)
N_last = N
elif len(threshold)>1 and temp_data['e_I1'][temp_data.index[-1]] > threshold[-1]:
slot_pos = slot_pos+1
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
beam.setAbsorber(slot_pos)
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
output_data = output_data.append(temp_data, ignore_index=True)
#save to file
output_data.to_csv(XR_FILENAME)
#reset the changed items
bec.enable_plots()
#bec.enable_table()
self.naming_scheme = self.naming_scheme_hold
#remove the absorber completely out of the beam
beam.absorber_out()
def XR_abort(self):
'''Reset the beamline status back to origin before XRR measurement.
'''
beam.off()
cms.modeMeasurement()
beam.setAbsorber(0)
#remove the absorber completely out of the beam
beam.absorber_out()
self.xo()
self.yo()
self.tho()
bec.enable_plots()
bec.enable_table()
pilatus_name.hints = {'fields': ['pilatus800_stats3_total', 'pilatus800_stats4_total']}
def XR_data_output(self, slot_pos, exposure_time):
'''XRR data output in DataFrame format, including:
'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
'''
h = db[-1]
dtable = h.table()
#beam.absorber_transmission_list = [1, 0.041, 0.0017425, 0.00007301075, 0.00000287662355, 0.000000122831826, 0.00000000513437]
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_13p5kev
#Energy = 17kev
elif abs(beam.energy(verbosity=1)-17) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_17kev
elif abs(beam.energy(verbosity=1)-10) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_10kev
else:
print("The absorber has not been calibrated under current Energy!!!")
sth_pos = h.start['sample_th']
qz = 4*np.pi*np.sin(np.deg2rad(sth_pos))/h.start['calibration_wavelength_A']
scan_id = h.start['scan_id']
I0 = h.start['beam_int_bim5'] #beam intensity from bim5
I1 = dtable.pilatus800_stats1_total
I2 = dtable.pilatus800_stats2_total
I3 = 2*dtable.pilatus800_stats1_total - dtable.pilatus800_stats2_total
In = I3 / beam.absorber_transmission_list[slot_pos] / exposure_time
current_data = {'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
return pds.DataFrame(data=current_data)
def XR_align(self, step=0, reflection_angle=0.15, verbosity=3):
'''Specific alignment for XRR
Align the sample with respect to the beam. XR alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam. Finally, the angle is re-optimized
in reflection mode.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
#
if verbosity>=4:
print(' Aligning {}'.format(self.name))
if step<=0:
cms.modeXRAlignment()
cms.modeAlignment()
beam.setTransmission(1e-4)
detselect(pilatus2M)
# Prepare for alignment
if RE.state!='idle':
RE.abort()
if get_beamline().current_mode!='alignment':
if verbosity>=2:
print("WARNING: Beamline is not in alignment mode (mode is '{}')".format(get_beamline().current_mode))
#get_beamline().modeAlignment()
get_beamline().setDirectBeamROI()
beam.on()
if step<=2:
if verbosity>=4:
print(' align: searching')
# Estimate full-beam intensity
value = None
if True:
# You can eliminate this, in which case RE.md['beam_intensity_expected'] is used by default
self.yr(-2)
#detector = gs.DETS[0]
detector = get_beamline().detector[0]
value_name = get_beamline().TABLE_COLS[0]
RE(count([detector]))
value = detector.read()[value_name]['value']
self.yr(+2)
if 'beam_intensity_expected' in RE.md and value<RE.md['beam_intensity_expected']*0.75:
print('WARNING: Direct beam intensity ({}) lower than it should be ({})'.format(value, RE.md['beam_intensity_expected']))
# Find the step-edge
self.ysearch(step_size=0.5, min_step=0.005, intensity=value, target=0.5, verbosity=verbosity, polarity=-1)
# Find the peak
self.thsearch(step_size=0.4, min_step=0.01, target='max', verbosity=verbosity)
if step<=4:
if verbosity>=4:
print(' align: fitting')
fit_scan(smy, 1.2, 21, fit='HMi')
#time.sleep(2)
fit_scan(sth, 1.5, 21, fit='max')
#time.sleep(2)
if step<=8:
#fit_scan(smy, 0.6, 21, fit='sigmoid_r')
fit_edge(smy, 0.6, 21)
#time.sleep(2)
#fit_edge(smy, 0.4, 21)
fit_scan(sth, 0.8, 21, fit='COM')
#time.sleep(2)
self.setOrigin(['y', 'th'])
if step<=9 and reflection_angle is not None:
# Final alignment using reflected beam
if verbosity>=4:
print(' align: reflected beam')
if abs(beam.energy(verbosity)-17)<0.1:
reflection_angle = 0.15
get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0)
#get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0, size=[12,2])
self.thabs(reflection_angle)
result = fit_scan(sth, 0.1, 41, fit='max')
#result = fit_scan(sth, 0.2, 81, fit='max') #it's useful for alignment of SmarAct stage
sth_target = result.values['x_max']-reflection_angle
if result.values['y_max']>50:
th_target = self._axes['th'].motor_to_cur(sth_target)
self.thsetOrigin(th_target)
#fit_scan(smy, 0.2, 21, fit='max')
#self.setOrigin(['y'])
if step<=10:
self.thabs(0.0)
beam.off()
detselect(pilatus800)
def XR_check_alignment(self, th_angle=1, exposure_time=1, roi_size=[10, 10]):
''' Check the alignment of the XR.
The total_angle is the incident angle.
The reflection spot should be located in the center of ROI2'''
cms.modeXRMeasurement()
#TODO: set a default position
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos2)
get_beamline().setXRROI(total_angle=th_angle*2,size=roi_size)
#sam.xo()
sam.yo()
sam.thabs(th_angle)
sam.measure(exposure_time)
print('===========sam.th moves to {}deg and ROI1 is set at {}deg. ============'.format(th_angle, th_angle*2))
print('======Please check the ROI whether at the reflected position. =======')
print('========If not, modify sam.th or schi to meet the reflected beam. ===========')
#define a theta-2theta scan by rotating sample by sth and accordingly changing roi1 and roi2 at 2theta position
def th2thscan(self, scan_type='theta_scan', theta_range=[1,4], theta_delta=0.1, qz_list=None, roi_size=[10,10], exposure_time=1, threshold=20000, max_exposure_time=10, extra='th2th_scan', output_file=None):
''' Run x-ray reflectivity measurement for thin film samples on WAXS pilatus800k.
There will be two WAXSy positions for XR.
The 1st position is the beam shining directly on the detector with maximum attenuation.
This position is defined by cms.WAXS.setCalibration([734, 1090],0.255, [-65, -73])
The 2nd position is the beam out of the WAXS detector.
The detector will be moved to the 2nd position when the reflected beam out of beam stop.
Parameters
----------
scan_type : list
theta_scan: in step of theta
q_scan: in step of q
theta_range: list
The scanning range. It can be single section or multiple sections with various step_size.
Examples:
[0, 1.6] or
[[0, .3],[0.3, 1], [1, 1.6]]
theta_delta: float or list
The scaning step. Examples:
0.02 or
[0.005, 0.1, 0.2]
roi_size: float
The szie of ROI1.
exposure_time: float
The mininum exposure time
min_step : float
The final (minimum) step size to try
intensity : float
The expected full-beam intensity readout
threshold : float
The threshold of minimum intensity. Exposure time increases automatically if < max_exposure_time
max_exposure_time : float
The maximum of exposure time to limit the total time.
'''
#TODO:
[theta_start, theta_end] = theta_range
if theta_end < theta_start:
print("The theta_end is larger than theta_start!!!")
if theta_start<.25:
print("For th2th scan, the start of the scan has to be larger than 0.5deg")
return
#disable the besteffortcallback and plot all ROIs
#bec.disable_table()
cms.modeXRMeasurement()
cms.definePos(size=roi_size)
bec.disable_plots()
cms.WAXS.detector.stats1.total.kind = 'hinted'
cms.WAXS.detector.stats2.total.kind = 'hinted'
self.naming_scheme_hold = self.naming_scheme
self.naming_scheme = ['name', 'extra', 'th', 'exposure_time']
#default_WAXSy = WAXSy.position
#move in absorber and move out the beamstop
slot_pos = 6
beam.setAbsorber(slot_pos)
if beam.absorber()[0]>=4:
bsx.move(bsx.position+6)
beam.setTransmission(1)
#create a clean dataframe and a direct beam images
self.yr(-2)
self.tho()
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
direct_beam_slot = 4
#Energy = 17kev
if abs(beam.energy(verbosity=1)-17) < 0.1:
direct_beam_slot = 5
slot_pos = 5
beam.setAbsorber(direct_beam_slot)
#move detector to the 1st position and setROI
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos1)
get_beamline().setXRROI(total_angle=0,size=roi_size,default_WAXSy=None)
self.measure(exposure_time, extra='direct_beam')
self.yo()
#move detector to POS2 and start the th2th scan
get_beamline().setWAXSpos(total_angle=0, roi=cms.XR_pos2)
output_data = self.XR_data_output(direct_beam_slot, exposure_time)
#output_data = output_data.iloc[0:0]
#create a data file to save the XRR data
if output_file is None:
header = db[-1]
#XR_FILENAME='{}/data/{}.csv'.format(os.path.dirname(__file__) , header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], header.get('start').get('scan_id')+1)
th2th_FILENAME='{}/data/{}_{}.csv'.format(header.start['experiment_alias_directory'],header.start['sample_name'], header.get('start').get('scan_id')+1)
else:
th2th_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], output_file)
#load theta positions in scan
if scan_type == 'theta_scan':
#list the sth positions in scan
theta_list=np.arange(theta_start, theta_end+0.001, theta_delta)
elif scan_type == 'qz_scan':
if qz_list is not None:
qz_list = qz_list
else:
qz_list = self.qz_list_default
theta_list = np.rad2deg(np.arcsin(qz_list * header.start['calibration_wavelength_A']/4/np.pi))
pos_flag = 0
for theta in theta_list:
self.thabs(theta)
#th2th scan starts with POS2 directly
get_beamline().setXRROI_update(total_angle=theta*2,size=roi_size)
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
#initial exposure period
if threshold is not None and type(threshold) == int :
if slot_pos > 0:
if temp_data['e_I1'][temp_data.index[-1]] < 10: #The count is too small to evaluate the next slot_pos.
slot_pos = slot_pos - 1
else:
slot_current = beam.absorber_transmission_list[slot_pos]*threshold/temp_data['e_I1'][temp_data.index[-1]]
for slot_no in np.arange(5, 0, -1):
if slot_current > beam.absorber_transmission_list[slot_no]:
slot_pos = slot_no - 1
beam.setAbsorber(slot_pos)
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
#else:
##self.measure(exposure_time, extra=extra)
#temp_data = self.XR_data_output(slot_pos, exposure_time)
elif len(threshold)>1 and temp_data['e_I1'][temp_data.index[-1]] > threshold[-1]:
slot_pos = slot_pos+1
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
beam.setAbsorber(slot_pos)
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
output_data = output_data.append(temp_data, ignore_index=True)
#save to file
output_data.to_csv(th2th_FILENAME)
#reset the changed items
bec.enable_plots()
#bec.enable_table()
self.naming_scheme = self.naming_scheme_hold
#remove the absorber completely out of the beam
beam.absorber_out()
class SampleGonio_Generic(SampleGISAXS_Generic):
'''Goniometer stage made by SmarAct
'''
def __init__(self, name='Goniometer', base=None, **md):
super().__init__(name=name, base=base, **md)
self._axes['x'].origin = -17.7
self._axes['y'].origin = 9
def _set_axes_definitions(self):
'''Internal function which defines the axes for this stage. This is kept
as a separate function so that it can be over-ridden easily.'''
super()._set_axes_definitions()
# The _axes_definitions array holds a list of dicts, each defining an axis
self._axes_definitions.append = [ {'name': 'phi',
'motor': srot,
'enabled': True,
'scaling': +1.0,
'units': 'deg',
'hint': None,
},
{'name': 'trans',
'motor': strans,
'enabled': True,
'scaling': +1.0,
'units': 'mm',
'hint': None,
},
{'name': 'trans2',
'motor': strans2,
'enabled': True,
'scaling': +1.0,
'units': 'mm',
'hint': None,
},
]
class SampleSecondStage(SampleGISAXS_Generic):
''' The second sample stage with the large open space
Note: steps to initiallize it.
1. Break vacuum of both chamber and pipe.
2. Remove the connected tubing and
3. open 10-motors.py. set beamline_stage = 'open_MAXS'
'''
def __init__(self, name, base=None, **md):
super().__init__(name=name, base=base, **md)
self._axes['x'].origin = -1.9
self._axes['y'].origin = 18.97
self._axes['th'].origin = 0.348
# custmer-made holders
class GIBar(PositionalHolder):
'''This class is a sample bar for grazing-incidence (GI) experiments.'''
# Core methods
########################################
def __init__(self, name='GIBar', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._positional_axis = 'x'
self.xsetOrigin(-71.89405)
#self.ysetOrigin(10.37925)
self.ysetOrigin(5.38)
self.mark('right edge', x=+108.2)
self.mark('left edge', x=0)
self.mark('center', x=54.1, y=0)
#measurement measure_settings
self.detector=None
self.exposure_time = None
self.incident_angles = None
self.tiling = None
self.measure_setting={}
def _backup_addSampleSlotPosition(self, sample, slot, position, detector_opt='SAXS', incident_angles=None, account_substrate=True, exposure_time=None, thickness=0):
'''Adds a sample to the specified "slot" (defined/numbered sample
holding spot on this holder).'''
super().addSampleSlotPosition(sample=sample, slot=slot, position=position, detector_opt=detector_opt, incident_angles=incident_angles)
# Adjust y-origin to account for substrate thickness
if account_substrate and 'substrate_thickness' in sample.md:
sample.ysetOrigin( -1.0*sample.md['substrate_thickness'] )
sample.detector=detector_opt
sample.exposure_time=exposure_time
sample.thickness=exposure_time
# Adjust y-origin to account for substrate thickness
if thickness !=0:
sample.ysetOrigin( -1.0*thickness )
def addSampleSlotPosition(self, sample, slot, position, detector_opt=None, incident_angles=None, exposure_time=None, tiling=None, thickness=0):
'''Adds a sample to the specified "slot" (defined/numbered sample
holding spot on this holder).'''
super().addSampleSlotPosition(sample=sample, slot=slot, position=position, detector_opt=detector_opt, incident_angles=incident_angles)
# Adjust y-origin to account for substrate thickness
if thickness !=0:
sample.ysetOrigin( -1.0*thickness )
if detector_opt==None:
sample.measure_setting['detector'] = self.detector
else:
sample.measure_setting['detector'] = detector_opt
if exposure_time==None:
sample.measure_setting['exposure_time'] = self.exposure_time
else:
sample.measure_setting['exposure_time'] = exposure_time
if incident_angles==None:
sample.measure_setting['incident_angles'] =self.incident_angles
else:
sample.measure_setting['incident_angles'] =incident_angles
if tiling==None:
sample.measure_setting['tiling'] = self.tiling
else:
sample.measure_setting['tiling'] = tiling
def setMeasure(self, detector, incident_angles, exposure_time, tiling):
'''define the measurement setting for the holder, including:
detector: 'SAXS', 'WAXS', or 'BOTH';
incident_angles: [0.05, 0.10.2];
exposure_time: in second, corresponding to the detector setting;
tiling: 'x', 'y', 'xy', None
'''
if detector == 'BOTH':
detector = ['SAXS', 'WAXS']
if type(exposure_time) == int:
exposure_time = [exposure_time, exposure_time]
self.measure_setting['detector'] = detector
self.measure_setting['incident_angles'] = incident_angles
self.measure_setting['exposure_time'] = exposure_time
self.measure_setting['tiling'] = tiling
self.detector = detector
self.incident_angles = incident_angles
self.exposure_time = exposure_time
self.tiling = tiling
return self.measure_setting
def alignSamples(self, range=None, step=0, align_step=0, x_offset=0, verbosity=3, **md):
'''Iterates through the samples on the holder, aligning each one.'''
if step<=0:
get_beamline().modeAlignment()
if step<=5:
for sample in self.getSamples(range=range):
sample.gotoOrigin(['x','y','th'])
sample.gotoOrigin(['x'])
sample.xr(x_offset)
sample.align(step=align_step, reflection_angle=0.12)
if step<=10:
if verbosity>=3:
print('Alignment complete.')
for i, sample in enumerate(self.getSamples()):
print('Sample {} ({})'.format(i+1, sample.name))
print(sample.save_state())
def alignSamplesQuick(self, range=None, step=0, x_offset=0, verbosity=3, **md):
'''Iterates through the samples on the holder, aligning each one.'''
if step<=0:
get_beamline().modeAlignment()
if step<=5:
for sample in self.getSamples(range=range):
sample.gotoOrigin(['x','y','th'])
sample.gotoOrigin(['x'])
sample.xr(x_offset)
sample.alignQuick(reflection_angle=0.12) #=0.07)
if step<=10:
if verbosity>=3:
print('Alignment complete.')
for i, sample in enumerate(self.getSamples()):
print('Sample {} ({})'.format(i+1, sample.name))
print(sample.save_state())
def alignSamplesVeryQuick(self, range=None, step=0, x_offset=0, verbosity=3, **md):
'''Iterates through the samples on the holder, aligning each one.'''
if step<=0:
get_beamline().modeAlignment()
beam.on()
caput('XF:11BMB-ES{Det:SAXS}:cam1:AcquireTime', 0.25)
caput('XF:11BMB-ES{Det:SAXS}:cam1:AcquirePeriod', 0.30)
if step<=5:
for sample in self.getSamples(range=range):
sample.gotoOrigin(['x','y','th'])
sample.gotoOrigin(['x'])
sample.xr(x_offset)
sample.alignVeryQuick(intensity=INTENSITY_EXPECTED_025, mode_control=False)
if step<=8:
beam.off()
if step<=10:
if verbosity>=3:
print('Alignment complete.')
for i, sample in enumerate(self.getSamples()):
print('Sample {} ({})'.format(i+1, sample.name))
print(sample.save_state())
def measureSamples(self, range=None, step=0, angles=None, exposure_time=15, x_offset=0, verbosity=3, **md):
'''Measures all the samples.
If the optional range argument is provided (2-tuple), then only sample
numbers within that range (inclusive) are run. If range is instead a
string, then all samples with names that match are returned.'''
if step<=0:
get_beamline().modeMeasurement()
if step<=5:
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Measuring sample {}...'.format(sample.name))
sample.gotoOrigin(['x','y','th'])
sample.gotoOrigin(['x'])
sample.xr(x_offset)
sample.measureIncidentAngles(angles=angles, verbosity=verbosity, exposure_time=exposure_time, **md)
def printSaveStates(self, range=None, verbosity=3, **md):
if range is None:
range_start = 0
else:
range_start = range[0]
save_string = 'origins = [\n'
for i, sample in enumerate(self.getSamples(range=range)):
sample_id = range_start + i + 1
save_string += ' {} , # Sample {}\n'.format(sample.save_state(), sample_id)
#save_string += ' {} , # Sample {} ({})\n'.format(sample.save_state(), sample_id, sample.name)
save_string += ' ]\n'
save_string += 'for origin, sample in zip(origins, hol.getSamples()):\n'
save_string += ' sample.restore_state(origin)\n'
print(save_string)
def _backup_doSamples(self, range=None, verbosity=3):
#saxs_on()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if sample.detector=='SAXS' or sample.detector=='BOTH':
sample.do_SAXS()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if sample.detector=='BOTH':
sample.do_WAXS_only()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if sample.detector=='WAXS':
sample.do_WAXS()
def doSamples(self, range=None, verbosity=3):
#saxs_on()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if 'SAXS' in sample.detector or sample.detector=='BOTH':
sample.do_SAXS()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if 'SAXS' in sample.detector and 'WAXS' in sample.detector:
sample.do_WAXS_only()
elif sample.detector=='BOTH':
sample.do_WAXS_only()
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if sample.detector=='WAXS':
sample.do_WAXS()
def doSamples_Stitch(self, angles=None, exposure_time=None, extra=None, tiling=None, verbosity=3, **md):
if exposure_time == None:
exposure_time = self.exposure_time
#measure the incident angles first and then change the tiling features.
if tiling == None:
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
for angle in angles:
self.measureIncidentAngle(angle, exposure_time=exposure_time, extra=extra, tiling=tiling, **md)
elif tiling=='ygaps':
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
#pos1
for sample in self.getSamples():
sample.gotoOrigin()
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
for angle in angles:
sample.thabs(angle)
time.sleep(.5)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
#MAXSy_o = MAXSy.user_readback.value
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
for sample in self.getSamples():
sample.gotoOrigin()
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
for angle in angles:
sample.thabs(angle)
time.sleep(.5)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
#if MAXSy.user_readback.value != MAXSy_o:
#MAXSy.move(MAXSy_o)
elif tiling == 'xygaps':
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
#pos1
for sample in self.getSamples():
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
sample.gotoOrigin()
for angle in angles:
sample.thabs(angle)
time.sleep(.5)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower_left'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
for sample in self.getSamples():
sample.gotoOrigin()
for angle in angles:
sample.thabs(angle)
time.sleep(.2)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos4 #comment out to save time
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy.o + 5.16)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o + 5.16)
for sample in self.getSamples():
sample.gotoOrigin()
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
for angle in angles:
sample.thabs(angle)
time.sleep(.2)
extra_current = 'pos4' if extra is None else '{}_pos4'.format(extra)
md['detector_position'] = 'upper_right'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos3
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy_o)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o)
for sample in self.getSamples():
sample.gotoOrigin()
if angles is None:
if sample.incident_angles==None:
incident_angles = self.incident_angles_default
else:
incident_angles = self.incident_angles
for angle in angles:
sample.thabs(angle)
time.sleep(.2)
extra_current = 'pos3' if extra is None else '{}_pos3'.format(extra)
md['detector_position'] = 'lower_right'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if WAXSx.user_readback.value != WAXSx_o:
WAXSx.move(WAXSx_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
if SAXSx.user_readback.value != SAXSx_o:
SAXSx.move(SAXSx_o)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
class CapillaryHolder(PositionalHolder):
'''This class is a sample holder that has 15 slots for capillaries.'''
# Core methods
########################################
def __init__(self, name='CapillaryHolder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._positional_axis = 'x'
self.x_spacing = 6.342 # 3.5 inches / 14 spaces
# slot 1; smx = +26.60
# slot 8; smx = -17.80
# slot 15; smx = -61.94
# Set the x and y origin to be the center of slot 8
#self.xsetOrigin(-16.7)
#self.ysetOrigin(-2.36985)
#self.ysetOrigin(-2.36985)
#self.xsetOrigin(-16.7+-0.3)
self.ysetOrigin(-1.8)
self.xsetOrigin(-17.2)
self.mark('right edge', x=+54.4)
self.mark('left edge', x=-54.4)
self.mark('bottom edge', y=-12.71)
self.mark('center', x=0, y=0)
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
return +1*self.x_spacing*(slot-8)
def measure_Stitch(self, exposure_time=None, extra=None, tiling=None, verbosity=3, **md):
#measure the incident angles first and then change the tiling features.
if tiling == None:
for sample in self.getSamples():
sample.gotoOrigin()
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
elif tiling=='ygaps':
#pos1
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
#MAXSy_o = MAXSy.user_readback.value
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
#if MAXSy.user_readback.value != MAXSy_o:
#MAXSy.move(MAXSy_o)
elif tiling == 'xygaps':
#pos1
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
extra_current = 'pos1' if extra is None else '{}_pos1'.format(extra)
md['detector_position'] = 'lower_left'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos2
SAXSy_o = SAXSy.user_readback.value
SAXSx_o = SAXSx.user_readback.value
WAXSy_o = WAXSy.user_readback.value
WAXSx_o = WAXSx.user_readback.value
#MAXSy_o = MAXSy.user_readback.value
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSy.move(WAXSy_o + 5.16)
if pilatus300 in cms.detector:
MAXSy.move(MAXSy_o + 5.16)
extra_current = 'pos2' if extra is None else '{}_pos2'.format(extra)
md['detector_position'] = 'upper'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos4 #comment out to save time
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy_o + 5.16)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o + 5.16)
extra_current = 'pos4' if extra is None else '{}_pos4'.format(extra)
md['detector_position'] = 'upper_right'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
#pos3
for sample in self.getSamples():
sample.gotoOrigin()
time.sleep(.2)
if pilatus2M in cms.detector:
SAXSx.move(SAXSx_o + 5.16)
SAXSy.move(SAXSy_o)
if pilatus800 in cms.detector:
WAXSx.move(WAXSx_o - 5.16)
WAXSy.move(WAXSy_o)
extra_current = 'pos3' if extra is None else '{}_pos3'.format(extra)
md['detector_position'] = 'lower_right'
sample.measure_single(exposure_time=exposure_time, extra=extra_current, verbosity=verbosity, stitchback=True,**md)
if WAXSx.user_readback.value != WAXSx_o:
WAXSx.move(WAXSx_o)
if WAXSy.user_readback.value != WAXSy_o:
WAXSy.move(WAXSy_o)
if SAXSx.user_readback.value != SAXSx_o:
SAXSx.move(SAXSx_o)
if SAXSy.user_readback.value != SAXSy_o:
SAXSy.move(SAXSy_o)
def measureSamples(self, range=None, step=0, angles=None, exposure_time=15, x_offset=0, verbosity=3, **md):
'''Measures all the samples.
If the optional range argument is provided (2-tuple), then only sample
numbers within that range (inclusive) are run. If range is instead a
string, then all samples with names that match are returned.'''
if step<=0:
get_beamline().modeMeasurement()
if step<=5:
for sample in self.getSamples(range=range):
if verbosity>=3:
print('Measuring sample {}...'.format(sample.name))
sample.gotoOrigin(['x','y'])
sample.gotoOrigin(['x'])
sample.xr(x_offset)
sample.measureIncident(exposure_time=exposure_time, verbosity=verbosity, **md)
class CapillaryHolderHeated(CapillaryHolder):
def update_sample_names(self):
for sample in self.getSamples():
if 'temperature' not in sample.naming_scheme:
sample.naming_scheme.insert(-1, 'temperature')
def doHeatCool(self, heat_temps, cool_temps, exposure_time=None, stabilization_time=120, temp_tolerance=0.5, step=1):
if step<=1:
for temperature in heat_temps:
try:
self.setTemperature(temperature)
while self.temperature(verbosity=0) < temperature-temp_tolerance:
time.sleep(5)
time.sleep(stabilization_time)
for sample in self.getSamples():
sample.gotoOrigin()
sample.xr(-0.05)
sample.measure(exposure_time)
except HTTPError:
pass
if step<=5:
for temperature in heat_temps:
try:
self.setTemperature(temperature)
self.setTemperature(temperature)
while self.temperature(verbosity=0) > temperature+temp_tolerance:
time.sleep(5)
time.sleep(stabilization_time)
for sample in self.getSamples():
sample.gotoOrigin()
sample.xr(0.1)
sample.measure(exposure_time)
except HTTPError:
pass
class GIBar_long_thermal(GIBar):
'''This class is a sample bar with heating/cooling feature and 6" long bar for grazing-incidence (GI) experiments.'''
# Core methods
########################################
def __init__(self, name='GIBar', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._positional_axis = 'x'
# Set the x and y origin to be the center of slot 8
#self.xsetOrigin(-71.89405-22.1) # TODO: Update this value
#self._axes['y'].origin = 7.06
self._axes['y'].origin = 2.06
self.mark('right edge', x=+152.4)
self.mark('left edge', x=0)
self.mark('center', x=76.2, y=0)
def alignSamples(self, step=0, align_step=0, verbosity=3, **md):
for sample in self.getSamples():
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
sample.xo() # goto origin
if step<=4:
sample.yo()
sample.tho()
if step<=5:
sample.align(step=align_step)
def alignSamples_Custom(self, step=0, align_step=8, verbosity=3, **md):
#first_sample = self.getSamples()
#hol_xcenter = 4.3*25.4/2
cali_sample = self.getSample(1)
sample_pos_list = []
for sample in self.getSamples():
sample_pos_list.append(sample.position)
hol_xcenter = min(sample_pos_list)/2+max(sample_pos_list)/2
print(sample_pos_list)
#locate the sample for alignning the holder
for sample in self.getSamples():
if abs(sample.position-hol_xcenter) < abs(cali_sample.position-hol_xcenter):
cali_sample = sample
print('The current calibraion sample is {}'.format(cali_sample.name))
print('The calibraion sample is {}'.format(cali_sample.name))
#full alignment on cali_sample
#cali_sample.align()
if verbosity>=3:
print('Doing holder on sample {}...'.format(cali_sample.name))
saxs_on()
get_beamline().modeAlignment()
cali_sample.xo() # goto origin
cali_sample.yo()
cali_sample.tho()
cali_sample.align(step=0)
cali_sample.xo()
cali_sample.yo()
cali_sample.tho()
for sample in self.getSamples():
sample.setOrigin(['th', 'y'])
for sample in self.getSamples():
if verbosity>=3:
print('Doing sample {}...'.format(sample.name))
if step<=1:
saxs_on()
get_beamline().modeAlignment()
if step<=2:
sample.xo() # goto origin
sample.yo()
sample.tho()
if step<=5:
sample.align(step=align_step)
def measureSamples(self, det='SWAXS', tiling=None, verbosity=3, **md):
cms.modeMeasurement()
if det == 'SAXS':
saxs_on()
for sample in self.getSamples():
sample.gotoOrigin()
if sample.incident_angles==None:
incident_angles = sample.incident_angles_default
else:
incident_angles = sample.incident_angles
sample.measureIncidentAngles_Stitch(incident_angles, exposure_time=sample.SAXS_time, tiling=tiling, **md)
elif det == 'WAXS':
waxs_on() # edited from waxs_on 3/25/19 through a saxs_on error
for sample in self.getSamples():
sample.gotoOrigin()
if sample.incident_angles==None:
incident_angles = sample.incident_angles_default
else:
incident_angles = sample.incident_angles
#for detector in get_beamline().detector:
#detector.setExposureTime(self.MAXS_time)
sample.measureIncidentAngles_Stitch(incident_angles, exposure_time=sample.WAXS_time, tiling=tiling, **md)
sample.gotoOrigin()
elif det == 'SWAXS':
swaxs_on()
for sample in self.getSamples():
sample.gotoOrigin()
if sample.incident_angles==None:
incident_angles = sample.incident_angles_default
else:
incident_angles = sample.incident_angles
sample.measureIncidentAngles_Stitch(incident_angles, exposure_time=sample.SWAXS_time, tiling=tiling, **md)
elif det == 'BOTH':
saxs_on()
for sample in self.getSamples():
sample.gotoOrigin()
if sample.incident_angles==None:
incident_angles = sample.incident_angles_default
else:
incident_angles = sample.incident_angles
sample.measureIncidentAngles_Stitch(incident_angles, exposure_time=sample.SAXS_time, tiling=tiling, **md)
waxs_on() # edited from waxs_on 3/25/19 through a saxs_on error
for sample in self.getSamples():
sample.gotoOrigin()
if sample.incident_angles==None:
incident_angles = sample.incident_angles_default
else:
incident_angles = sample.incident_angles
#for detector in get_beamline().detector:
#detector.setExposureTime(self.MAXS_time)
sample.measureIncidentAngles_Stitch(incident_angles, exposure_time=sample.WAXS_time, tiling=tiling, **md)
sample.gotoOrigin()
else:
print('Wrong det input. Options are SAXS/WAXS/SWAXS/BOTH')
def doTemperatures(self, temperature_list=None, output_file='Transmission_output', int_measure=False, wait_time=600, WAXS_expo_time=5, temperature_probe='A', output_channel='1', temperature_tolerance=1, range=None, verbosity=3, poling_period=2.0, **md):
#cms.modeMeasurement()
if temperature_list==None:
temperature_list = self.temperature_list
for index, temperature in enumerate(temperature_list):
# Set new temperature
#self.setTemperature(temperature, output_channel=output_channel, verbosity=verbosity)
# Wait until we reach the temperature
#while abs(self.temperature(verbosity=0) - temperature)>temperature_tolerance:
while abs(self.temperature(temperature_probe=temperature_probe, verbosity=0) - temperature)>temperature_tolerance:
if verbosity>=3:
print(' setpoint = {:.3f}°C, Temperature = {:.3f}°C \r'.format(self.temperature_setpoint()-273.15, self.temperature(temperature_probe=temperature_probe, verbosity=0)), end='')
time.sleep(poling_period)
# Allow for additional equilibration at this temperature
if index%4 == 0:
self.alignSamples_Custom()
#self.alignSamples()
elif wait_time is not None:
time.sleep(wait_time)
post_to_slack('set to Temperature {}'.format(temperature))
self.measureSamples()
#self.doSamples(SAXS_expo_time=SAXS_expo_time, verbosity=verbosity, **md)
if int_measure:
self.intMeasure(output_file=output_file)
self.setTemperature(25)
class WellPlateHolder(PositionalHolder):
'''This class is a sample holder for 96 well plate.
row: A--E; column: 1--12
The sample names are like: 'A1', 'D3', 'E12'
It uses two stages, smx and smy2 to locate the sample.
'''
# Core methods
########################################
def __init__(self, name='CapillaryHolder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._positional_axis = ['x','yy']
self._axes['y'].origin = -5 #smy stage should be set with the limit [-5.5, -5]
self._axes['x'].origin = -49.25
self._axes['yy'].origin = 3.3
self.x_spacing = 9 # 9mm seperation both in x and yy direction
self.yy_spacing = 9
def _set_axes_definitions(self):
'''Internal function which defines the axes for this stage. This is kept
as a separate function so that it can be over-ridden easily.'''
# The _axes_definitions array holds a list of dicts, each defining an axis
super()._set_axes_definitions()
self._axes_definitions.append ( {'name': 'yy',
'motor': smy2,
'enabled': True,
'scaling': +1.0,
'units': 'mm',
'hint': 'positive moves stage up',
} )
def slot(self, sample_number):
'''Moves to the selected slot in the holder.'''
getattr(self, self._positional_axis[0]+'abs')( self.get_slot_position(sample_number) )
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
# This method should be over-ridden in sub-classes, so as to properly
# implement the positioning appropriate for that holder.
# slot is like 'A1', 'D12'
sample_row = ord(slot[0])-ord('A')
sample_column = int(slot[1:])-1
#sample_number = sample_row*12 + sample_column
return sample_column*self.x_spacing, sample_row*self.yy_spacing
def addSample(self, sample, sample_number=None):
'''Add a sample to this holder/bar.'''
if sample_number is None:
if len(self._samples)==0:
sample_number = 1
else:
ki = [ int(key) for key in self._samples.keys() ]
sample_number = np.max(ki) + 1
if sample_number in self._samples.keys():
print('Warning: Sample number {} is already defined on holder "{:s}". Use "replaceSample" if you are sure you want to eliminate the existing sample from the holder.'.format(sample_number, self.name) )
else:
self._samples[sample_number] = sample
self._samples[sample_number] = sample
sample.set_base_stage(self)
sample.md['holder_sample_number'] = sample_number
def addSampleSlot(self, sample, slot):
'''Adds a sample to the specified "slot" (defined/numbered sample
holding spot on this holder).'''
self.addSample(sample, sample_number=slot)
sample.setOrigin( ['x'], [self.get_slot_position(slot)[0]] )
sample.setOrigin( ['yy'], [self.get_slot_position(slot)[1]] )
def listSamplesPositions(self):
'''Print a list of the current samples associated with this holder/
bar.'''
for sample_number, sample in self._samples.items():
pos = getattr(sample, self._positional_axis+'pos')(verbosity=0)
print( '%s: %s (%s = %.3f)' % (str(sample_number), sample.name, self._positional_axis, pos) )
def listSamples(self):
'''Print a list of the current samples associated with this holder/
bar.'''
for sample_number, sample in sorted(self._samples.items()):
print( '{}: {:s}'.format(sample_number, sample.name) )
def gotoAlignedPosition(self):
'''Goes to the currently-defined 'aligned' position for this stage. If
no specific aligned position is defined, then the zero-point for the stage
is used instead.'''
# TODO: Optional offsets? (Like goto mark?)
self.gotoOrigin(axes=self._positional_axis)
#time.sleep(10)
def getSample(self, sample_number, verbosity=3):
'''Return the requested sample object from this holder/bar.
One can provide an integer, in which case the corresponding sample
(from the holder's inventory) is returned. If a string is provided,
the closest-matching sample (by name) is returned.'''
if sample_number not in self._samples:
if verbosity>=1:
print('Error: Sample {} not defined.'.format(sample_number))
return None
sample_match = self._samples[sample_number]
if verbosity>=3:
print('{}: {:s}'.format(sample_number, sample_match.name))
return sample_match
def namingWellPlate(name,row_range=['A', 'G'], column_range=[1, 12]):
'''Name the samples in the well plate.
The format is 'NAME_A05_'
'''
md = {
'owner' : 'J. Paloni (MIT) group' ,
'series' : 'various' ,
}
for row_number in range(ord(row_range[0]), ord(row_range[1])+1):
row=chr(row_number)
#print(row)
for column in range(column_range[0], column_range[1]+1):
#print(column)
sample_name = '{}_{}{}'.format(name, row, column)
position = '{}'.format(row)+'{0:0=2d}'.format(column)
self.addSampleSlot( SampleTSAXS( sample_name), position )
class PaloniThermalStage(CapillaryHolder):
'''This class is a sample holder made by Jason Paloni.
It's made by copper with chiller cooling.
The stage has 5(x) by 2(z) = 10 samples in total.
It uses two stages, smx and smy2 to locate the sample.
Note: need to enable the smy2 stage (~4inch travel distance in y direction).
1. %mov smy -5, set the limit as -5
2. mount the special smy2 stage onto the sample stage and connect the smy2 motor
3. enable ('yy') in sam._set_axes_definitions of 94-sample.py
'''
def __init__(self, name='CapillaryHolder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
#self._axes['y'].origin -= 0.5357125
self._positional_axis = ['x','yy']
self._axes['y'].origin = -5
self._axes['x'].origin = -.25
self._axes['yy'].origin = 1.5
self.x_spacing = 1.375 *25.4 # 1.375 seperation in x
self.yy_spacing = 32.13 + 23.25 # 2.25 seperation in y
#self.yy_spacing = 2.25 *25.4 # 2.25 seperation in y
def _set_axes_definitions(self):
'''Internal function which defines the axes for this stage. This is kept
as a separate function so that it can be over-ridden easily.'''
# The _axes_definitions array holds a list of dicts, each defining an axis
super()._set_axes_definitions()
self._axes_definitions.append ( {'name': 'yy',
'motor': smy2,
'enabled': True,
'scaling': +1.0,
'units': 'mm',
'hint': 'positive moves stage up',
} )
def slot(self, sample_number):
'''Moves to the selected slot in the holder.'''
getattr(self, self._positional_axis[0]+'abs')( self.get_slot_position(sample_number) )
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
# This method should be over-ridden in sub-classes, so as to properly
# implement the positioning appropriate for that holder.
# This is the critical to define the position for the 10 samples.
if slot < 5.5:
position_x = 0.0 + slot - 3
if slot > 5.5:
position_x = 0.0 + slot -5 -3
position_yy = 0.0 + int(slot/6)*1.0
return position_x*self.x_spacing, position_yy*self.yy_spacing
def addSampleSlot(self, sample, slot):
'''Adds a sample to the specified "slot" (defined/numbered sample
holding spot on this holder).'''
self.addSample(sample, sample_number=slot)
sample.setOrigin( ['x'], [self.get_slot_position(slot)[0]] )
sample.setOrigin( ['yy'], [self.get_slot_position(slot)[1]] )
class DSCStage(CapillaryHolder):
'''This class is a sample holder for DSC pans.
The stage has 11(x) by 2(z) = 22 samples in total.
It has the same dimension as the regular capillary holder.
It uses two stages, smx and smy to locate the sample.
X origin is the center. Y origin is the top rack.
'''
def __init__(self, name='CapillaryHolder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
#TODO: search the origin position and check the spacing
self._axes['y'].origin = -2.2
self.x_spacing = 9.2 #0.325 *25.4 # 0.375 seperation in x
self.y_spacing = 12.7 # 1/2 inch seperation in y
def slot(self, sample_number):
'''Moves to the selected slot in the holder.'''
getattr(self, self._positional_axis[0]+'abs')( self.get_slot_position(sample_number) )
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
# This method should be over-ridden in sub-classes, so as to properly
# implement the positioning appropriate for that holder.
# This is the critical to define the position for the 10 samples.
if slot < 11.5:
position_x = 0.0 + slot - 6
elif slot > 11.5:
position_x = 0.0 + slot -11 -6
position_y = 0.0 + int(slot/11.5)*1.0
return position_x*self.x_spacing, position_y*self.y_spacing
def addSampleSlot(self, sample, slot):
'''Adds a sample to the specified "slot" (defined/numbered sample
holding spot on this holder).'''
self.addSample(sample, sample_number=slot)
sample.setOrigin( ['x'], [self.get_slot_position(slot)[0]] )
sample.setOrigin( ['y'], [self.get_slot_position(slot)[1]] )
class GIBarSecondStage(GIBar):
'''This class is a sample bar for grazing-incidence (GI) experiments at the 2nd sample stage.'''
# Core methods
########################################
def __init__(self, name='GIBar', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._axes['x'].origin = -58.4
self._axes['y'].origin = 22.35
self._axes['th'].origin = 0.348
class HumidityStage(GIBar):
'''This class is for the humidity stage for multiple samples.'''
def __init__(self, name='GIBar', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._axes['x'].origin = -64.4
self._axes['y'].origin = 10
self._axes['th'].origin = 0
def humidity(self, AI_chan=7, temperature=25, verbosity=3):
#AI_chan=7, the independent sensor
#AI_chan=3, the integrated sensor in the flow control panel
return ioL.readRH(AI_chan=AI_chan, temperature=temperature, verbosity=verbosity)
def setFlow(self, channel, voltage=0):
#device = 'A1'
ioL.set(AO[channel], 0)
time.sleep(1)
ioL.set(AO[channel], voltage)
#MFC.setMode(channeldevice=device, mode=1)
class InstecStage60(CapillaryHolder):
def __init__(self, name='CapillaryHolder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._axes['y'].origin = 13.4 #smy position for slot 4 of 7-capillary cassette
self._axes['x'].origin = -15.6 #smx position for slot 4 of 7-capillary cassette
self.y_pos_default = []
self.x_spacing = 0.2 *25.4 # 0.2" seperation in x
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
# This method should be over-ridden in sub-classes, so as to properly
# implement the positioning appropriate for that holder.
position_x = 0.0 + slot - 4
return position_x*self.x_spacing
def tscan(self, temperature_start, temperature_final, num_intervals, wait_time, temp_update_time=5, exposure_time=0):
if temperature_start == None or temperature_start < 0.0 or temperature_start >= 250:
print('temperature_start must be set between 0 and 250 degC.\n')
return 0
if temperature_final == None or temperature_final < 0.0 or temperature_final >= 250:
print('temperature_final must be set between 0 and 250 degC.\n')
return 0
temperature_step = (temperature_final - temperature_start)/abs(num_intervals)
if temperature_final < temperature_start:
temperature_series = np.arange(temperature_start, temperature_final-0.0001, temperature_step)
else:
temperature_series = np.arange(temperature_start, temperature_final+0.0001, temperature_step)
tscan_zero_time = time.time()
self.tscan_seconds = []
self.tscan_degC = []
self.tscan_data = []
#dump all the (seconds, degC) data into a file; use filename like "<sam.name>_tscan_<first_ID>-<last_ID>.csv" under *user/tscan directory
self.tscan_filename = '{}/tscan/{}_tscan_{}.csv'.format(RE.md['experiment_alias_directory'], self.name, RE.md['scan_id'])
self.tscan_data = pds.DataFrame(columns=['scan_id', 'degC', 'seconds'])
#f=open(filename,'w')
for temperature_setpoint in temperature_series:
self.setTemperature(temperature_setpoint, output_channel='3')
self.temperature(temperature_probe='C', output_channel='3')
#f.write('# scan_ID seconds degC\n')
for t_wait in np.arange(0, wait_time, temp_update_time):
time.sleep(temp_update_time)
current_time = time.time() - tscan_zero_time
current_temperature = self.temperature(temperature_probe='C', output_channel='3', verbosity=2)
self.tscan_seconds.append(current_time)
self.tscan_degC.append(current_temperature)
print('{:.3f} {:.3f}'.format(current_time, current_temperature))
#f.write('{:d} {:.3f} {:.3f}\n'.format(RE.md['scan_id'], current_time, current_temperature))
self.tscan_data = self.tscan_data.append({'scan_id':RE.md['scan_id'], 'degC':current_temperature, 'seconds':current_time}, ignore_index=True)
#while self.IC_int() == False:
#print('The beam intensity is lower than it should be. Beam may be lost.')
#sleep(120)
if exposure_time > 0:
self.measure(exposure_time)
self.tscan_data.to_csv(self.tscan_filename)
#f.close()
#def tscan_save to recover tscan data when prematurely terminated
def tscan_save(self):
#filename = '{}/tscan/{}_tscan_{}.csv'.format(RE.md['experiment_alias_directory'], self.name, RE.md['scan_id']-1)
##I'm not sure whether tscan_data is saved or not when terminating tscans. If not, try to load the data into datafrme again.
#tscan_data = pds.DataFrame(columns=['scan_id', 'degC', 'seconds'])
#for ii in len(self.tscan_seconds):
#tscan_data = tscan_data.append({'scan_id':RE.md['scan_id']-1-len(self.tscan_seconds)+ii, 'degC':self.tscan_degC, 'seconds':self.tscan_seconds}, ignore_index=True)
self.tscan_data.to_csv(self.tscan_filename)
class OffCenteredHoder(GIBar):
'''The special sample holder for GTSAXS and TSAXS along thin film edges.
It contains 17 slots with fixed position, similar to Capillary Holders. But the holder dimensions and functions are similar to GIBar.
'''
def __init__(self, name='OffCenteredHoder', base=None, **kwargs):
super().__init__(name=name, base=base, **kwargs)
self._positional_axis = 'x'
self.x_spacing = 6.342 # 3.5 inches / 16 spaces
# slot 1; smx = +26.60
# slot 8; smx = -17.80
# slot 15; smx = -61.94
# Set the x and y origin to be the center of slot 8
self._axes['x'].origin = -17.2 # -0.3
self._axes['y'].origin = 5.38 # -0.1
#self.ysetOrigin(5.38)
#self.xsetOrigin(-17.2)
self.mark('right edge', x=+54.4)
self.mark('left edge', x=-54.4)
self.mark('bottom edge', y=-12.71)
self.mark('center', x=0, y=0)
#measurement measure_settings
self.detector=None
self.exposure_time = None
self.incident_angles = None
self.tiling = None
self.measure_setting={}
def get_slot_position(self, slot):
'''Return the motor position for the requested slot number.'''
return +1*self.x_spacing*(slot-8)
"""#abandoned code
class SampleXR(SampleGISAXS_Generic):
################# Specular reflectivity (XR) measurement by SAXS detector ####################
def XR_scan(self, scan_type='theta_scan', theta_range=[0,1.6], theta_delta=0.1, qz_list=None, roi_size=[12,30], exposure_time=1, threshold=20000, max_exposure_time=10, extra='XR_scan', output_file=None):
''' Run x-ray reflectivity measurement for thin film samples.
Parameters
----------
scan_type : list
theta_scan: in step of theta
q_scan: in step of q
theta_range: list
The scanning range. It can be single section or multiple sections with various step_size.
Examples:
[0, 1.6] or
[[0, .3],[0.3, 1], [1, 1.6]]
theta_delta: float or list
The scaning step. Examples:
0.02 or
[0.005, 0.1, 0.2]
roi_size: float
The szie of ROI1.
exposure_time: float
The mininum exposure time
min_step : float
The final (minimum) step size to try
intensity : float
The expected full-beam intensity readout
threshold : float
The threshold of minimum intensity. Exposure time increases automatically if < max_exposure_time
max_exposure_time : float
The maximum of exposure time to limit the total time.
'''
#TODO:
#if theta_end < theta_start:
# print("The theta_end is larger than theta_start!!!")
#disable the besteffortcallback and plot all ROIs
#bec.disable_table()
cms.modeMeasurement()
bec.disable_plots()
pilatus_name.stats1.total.kind = 'hinted'
pilatus_name.stats2.total.kind = 'hinted'
self.naming_scheme_hold = self.naming_scheme
self.naming_scheme = ['name', 'extra', 'x', 'th', 'exposure_time']
default_SAXSy = SAXSy.position
#initial exposure period
#N = 1
#move in absorber and move out the beamstop
slot_pos = 6
beam.setAbsorber(slot_pos)
if beam.absorber()[0]>=4:
bsx.move(bsx.position+6)
beam.setTransmission(1)
#create a clean dataframe and a direct beam images
self.yr(-2)
self.tho()
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
direct_beam_slot = 4
#Energy = 17kev
if abs(beam.energy(verbosity=1)-17) < 0.1:
direct_beam_slot = 5
slot_pos = 5
beam.setAbsorber(direct_beam_slot)
get_beamline().setSpecularReflectivityROI(total_angle=0,size=roi_size,default_SAXSy=-73)
self.measure(exposure_time, extra='direct_beam')
self.yo()
output_data = self.XR_data_output(direct_beam_slot, exposure_time)
#output_data = output_data.iloc[0:0]
#create a data file to save the XRR data
if output_file is None:
header = db[-1]
#XR_FILENAME='{}/data/{}.csv'.format(os.path.dirname(__file__) , header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], header.get('start').get('scan_id')+1)
XR_FILENAME='{}/data/{}_{}.csv'.format(header.start['experiment_alias_directory'],header.start['sample_name'], header.get('start').get('scan_id')+1)
else:
XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], output_file)
#load theta positions in scan
if scan_type == 'theta_scan':
#list the sth positions in scan
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
#
'''
if np.size(theta_range) == 2:
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
#multiple sections for measurement
else:
theta_list=[]
if np.shape(theta_range)[0] != np.size(theta_delta):
print("The theta_range does not match theta_delta")
return
if np.shape(theta_range)[-1] != 2:
print("The input of theta_range is incorrect.")
return
for number, item in enumerate(theta_range):
theta_list_temp = np.arange(item[0], item[1], theta_delta[number])
theta_list.append(theta_list_temp)
theta_list = np.hstack(theta_list)
'''
elif scan_type == 'qz_scan':
if qz_list is not None:
qz_list = qz_list
else:
qz_list = self.qz_list_default
theta_list = np.rad2deg(np.arcsin(qz_list * header.start['calibration_wavelength_A']/4/np.pi))
for theta in theta_list:
self.thabs(theta)
#get_beamline().setSpecularReflectivityROI(total_angle=theta*2,size=roi_size,default_SAXSy=-73)
get_beamline().setSpecularReflectivityROI_update(total_angle=theta*2,size=roi_size,default_SAXSy=-73)
if cms.out_of_beamstop(total_angle=theta*2, size=roi_size):
cms.modeMeasurement()
print('=========The beamstop is inserted to block the direct beam.=============')
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
#initial exposure period
N = 1
N_last = 1
if threshold is not None and type(threshold) == int :
while temp_data['e_I1'][temp_data.index[-1]] < threshold and N < max_exposure_time:
if slot_pos > 0:
if temp_data['e_I1'][temp_data.index[-1]] < 10: #The count is too small to evaluate the next slot_pos.
slot_pos = slot_pos - 1
else:
slot_current = beam.absorber_transmission_list[slot_pos]*threshold/temp_data['e_I1'][temp_data.index[-1]]
for slot_no in np.arange(5, 0, -1):
if slot_current > beam.absorber_transmission_list[slot_no]:
slot_pos = slot_no - 1
beam.setAbsorber(slot_pos)
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
else:
if threshold/float(temp_data['e_I1'][temp_data.index[-1]]) < max_exposure_time and N_last < max_exposure_time:
N = np.ceil(N_last*threshold/float(temp_data['e_I1'][temp_data.index[-1]]))
print('e_I1={}'.format(float(temp_data['e_I1'][temp_data.index[-1]])))
print('N={}'.format(N))
print('exposure time = {}'.format(N*exposure_time))
else:
N = max_exposure_time
print('exposure time is MAX')
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(N*exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, N*exposure_time)
N_last = N
elif len(threshold)>1 and temp_data['e_I1'][temp_data.index[-1]] > threshold[-1]:
slot_pos = slot_pos+1
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
beam.setAbsorber(slot_pos)
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
output_data = output_data.append(temp_data, ignore_index=True)
#save to file
output_data.to_csv(XR_FILENAME)
#reset the changed items
bec.enable_plots()
#bec.enable_table()
self.naming_scheme = self.naming_scheme_hold
#remove the absorber completely out of the beam
beam.absorber_out()
pilatus_name.stats3.total.kind = 'hinted'
pilatus_name.stats4.total.kind = 'hinted'
SAXSy.move(default_SAXSy)
def XR_abort(self):
'''Reset the beamline status back to origin before XRR measurement.
'''
beam.off()
cms.modeMeasurement()
beam.setAbsorber(0)
#remove the absorber completely out of the beam
beam.absorber_out()
self.xo()
self.yo()
self.tho()
bec.enable_plots()
bec.enable_table()
pilatus_name.hints = {'fields': ['pilatus2M_stats3_total', 'pilatus2M_stats4_total']}
def XR_data_output(self, slot_pos, exposure_time):
'''XRR data output in DataFrame format, including:
'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
'''
h = db[-1]
dtable = h.table()
#beam.absorber_transmission_list = [1, 0.041, 0.0017425, 0.00007301075, 0.00000287662355, 0.000000122831826, 0.00000000513437]
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_13p5kev
#Energy = 17kev
elif abs(beam.energy(verbosity=1)-17) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_17kev
else:
print("The absorber has not been calibrated under current Energy!!!")
sth_pos = h.start['sample_th']
qz = 4*np.pi*np.sin(np.deg2rad(sth_pos))/h.start['calibration_wavelength_A']
scan_id = h.start['scan_id']
I0 = h.start['beam_int_bim5'] #beam intensity from bim5
I1 = dtable.pilatus2M_stats1_total
I2 = dtable.pilatus2M_stats2_total
I3 = 2*dtable.pilatus2M_stats1_total - dtable.pilatus2M_stats2_total
In = I3 / beam.absorber_transmission_list[slot_pos] / exposure_time
current_data = {'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
return pds.DataFrame(data=current_data)
def XR_align(self, step=0, reflection_angle=0.15, verbosity=3):
'''Specific alignment for XRR
Align the sample with respect to the beam. XR alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam. Finally, the angle is re-optimized
in reflection mode.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
cms.modeAlignment()
if verbosity>=4:
print(' Aligning {}'.format(self.name))
if step<=0:
# Prepare for alignment
cms.modeAlignment()
if RE.state!='idle':
RE.abort()
if get_beamline().current_mode!='alignment':
if verbosity>=2:
print("WARNING: Beamline is not in alignment mode (mode is '{}')".format(get_beamline().current_mode))
#get_beamline().modeAlignment()
get_beamline().setDirectBeamROI()
beam.on()
if step<=2:
if verbosity>=4:
print(' align: searching')
# Estimate full-beam intensity
value = None
if True:
# You can eliminate this, in which case RE.md['beam_intensity_expected'] is used by default
self.yr(-2)
#detector = gs.DETS[0]
detector = get_beamline().detector[0]
value_name = get_beamline().TABLE_COLS[0]
RE(count([detector]))
value = detector.read()[value_name]['value']
self.yr(+2)
if 'beam_intensity_expected' in RE.md and value<RE.md['beam_intensity_expected']*0.75:
print('WARNING: Direct beam intensity ({}) lower than it should be ({})'.format(value, RE.md['beam_intensity_expected']))
# Find the step-edge
self.ysearch(step_size=0.5, min_step=0.005, intensity=value, target=0.5, verbosity=verbosity, polarity=-1)
# Find the peak
self.thsearch(step_size=0.4, min_step=0.01, target='max', verbosity=verbosity)
if step<=4:
if verbosity>=4:
print(' align: fitting')
fit_scan(smy, 1.2, 21, fit='HMi')
#time.sleep(2)
fit_scan(sth, 1.5, 21, fit='max')
#time.sleep(2)
if step<=8:
#fit_scan(smy, 0.6, 21, fit='sigmoid_r')
fit_edge(smy, 0.6, 21)
#time.sleep(2)
#fit_edge(smy, 0.4, 21)
fit_scan(sth, 0.8, 21, fit='COM')
#time.sleep(2)
self.setOrigin(['y', 'th'])
if step<=9 and reflection_angle is not None:
# Final alignment using reflected beam
if verbosity>=4:
print(' align: reflected beam')
if abs(beam.energy(verbosity)-17)<0.1:
reflection_angle = 0.15
get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0)
#get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0, size=[12,2])
self.thabs(reflection_angle)
result = fit_scan(sth, 0.1, 41, fit='max')
#result = fit_scan(sth, 0.2, 81, fit='max') #it's useful for alignment of SmarAct stage
sth_target = result.values['x_max']-reflection_angle
if result.values['y_max']>50:
th_target = self._axes['th'].motor_to_cur(sth_target)
self.thsetOrigin(th_target)
#fit_scan(smy, 0.2, 21, fit='max')
#self.setOrigin(['y'])
if step<=10:
self.thabs(0.0)
beam.off()
def XR_check_alignment(self, int_angle=1, exposure_time=1, roi_size=[12, 30]):
''' Check the alignment of the XR.
The total_angle is the incident angle.
The reflection spot should be located in the center of ROI2'''
cms.modeMeasurement()
cms.setSpecularReflectivityROI(total_angle=int_angle*2, size=roi_size, default_SAXSy=-73)
#sam.xo()
sam.yo()
sam.thabs(int_angle)
sam.measure(exposure_time)
print('===========sam.th moves to {}deg and ROI1 is set at {}deg. ============'.format(int_angle, int_angle*2))
print('======Please check the ROI whether at the reflected position. =======')
print('========If not, modify sam.th or schi to meet the reflected beam. ===========')
#test code for pilatus800
class SampleXR_test(SampleGISAXS_Generic):
################# Specular reflectivity (XR) measurement ####################
def XR_scan(self, scan_type='theta_scan', theta_range=[0,1.6], theta_delta=0.1, qz_list=None, roi_size=[12,30], exposure_time=1, threshold=20000, max_exposure_time=10, extra='XR_scan', output_file=None):
''' Run x-ray reflectivity measurement for thin film samples.
Parameters
----------
scan_type : list
theta_scan: in step of theta
q_scan: in step of q
theta_range: list
The scanning range. It can be single section or multiple sections with various step_size.
Examples:
[0, 1.6] or
[[0, .3],[0.3, 1], [1, 1.6]]
theta_delta: float or list
The scaning step. Examples:
0.02 or
[0.005, 0.1, 0.2]
roi_size: float
The szie of ROI1.
exposure_time: float
The mininum exposure time
min_step : float
The final (minimum) step size to try
intensity : float
The expected full-beam intensity readout
threshold : float
The threshold of minimum intensity. Exposure time increases automatically if < max_exposure_time
max_exposure_time : float
The maximum of exposure time to limit the total time.
'''
#TODO:
#if theta_end < theta_start:
# print("The theta_end is larger than theta_start!!!")
#disable the besteffortcallback and plot all ROIs
#bec.disable_table()
cms.modeXRMeasurement()
bec.disable_plots()
pilatus_name.stats1.total.kind = 'hinted'
pilatus_name.stats2.total.kind = 'hinted'
self.naming_scheme_hold = self.naming_scheme
self.naming_scheme = ['name', 'extra', 'th', 'exposure_time']
default_SAXSy = SAXSy.position
#initial exposure period
#N = 1
#move in absorber and move out the beamstop
slot_pos = 6
beam.setAbsorber(slot_pos)
if beam.absorber()[0]>=4:
bsx.move(bsx.position+6)
beam.setTransmission(1)
#create a clean dataframe and a direct beam images
self.yr(-2)
self.tho()
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
direct_beam_slot = 4
#Energy = 17kev
if abs(beam.energy(verbosity=1)-17) < 0.1:
direct_beam_slot = 5
slot_pos = 5
beam.setAbsorber(direct_beam_slot)
get_beamline().setSpecularReflectivityROI(total_angle=0,size=roi_size,default_SAXSy=-73)
self.measure(exposure_time, extra='direct_beam')
self.yo()
output_data = self.XR_data_output(direct_beam_slot, exposure_time)
#output_data = output_data.iloc[0:0]
#create a data file to save the XRR data
if output_file is None:
header = db[-1]
#XR_FILENAME='{}/data/{}.csv'.format(os.path.dirname(__file__) , header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], header.get('start').get('scan_id')+1)
#XR_FILENAME='{}/data/{}_{}.csv'.format(header.start['experiment_alias_directory'],header.start['sample_name'], header.get('start').get('scan_id')+1)
XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'],md['filename'])
else:
XR_FILENAME='{}/data/{}.csv'.format(header.start['experiment_alias_directory'], output_file)
#load theta positions in scan
if scan_type == 'theta_scan':
#list the sth positions in scan
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
#
'''
if np.size(theta_range) == 2:
theta_list=np.arange(theta_range[0], theta_range[1], theta_delta)
#multiple sections for measurement
else:
theta_list=[]
if np.shape(theta_range)[0] != np.size(theta_delta):
print("The theta_range does not match theta_delta")
return
if np.shape(theta_range)[-1] != 2:
print("The input of theta_range is incorrect.")
return
for number, item in enumerate(theta_range):
theta_list_temp = np.arange(item[0], item[1], theta_delta[number])
theta_list.append(theta_list_temp)
theta_list = np.hstack(theta_list)
'''
elif scan_type == 'qz_scan':
if qz_list is not None:
qz_list = qz_list
else:
qz_list = self.qz_list_default
theta_list = np.rad2deg(np.arcsin(qz_list * header.start['calibration_wavelength_A']/4/np.pi))
for theta in theta_list:
self.thabs(theta)
#get_beamline().setSpecularReflectivityROI(total_angle=theta*2,size=roi_size,default_SAXSy=-73)
get_beamline().setSpecularReflectivityROI_update(total_angle=theta*2,size=roi_size,default_WAXSy=-73)
if cms.beamOutXR(total_angle=theta*2, size=roi_size):
cms.modeXRMeasurement()
print('=========The beamstop is inserted to block the direct beam.=============')
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
#initial exposure period
N = 1
N_last = 1
if threshold is not None and type(threshold) == int :
while temp_data['e_I1'][temp_data.index[-1]] < threshold and N < max_exposure_time:
if slot_pos > 0:
if temp_data['e_I1'][temp_data.index[-1]] < 10: #The count is too small to evaluate the next slot_pos.
slot_pos = slot_pos - 1
else:
slot_current = beam.absorber_transmission_list[slot_pos]*threshold/temp_data['e_I1'][temp_data.index[-1]]
for slot_no in np.arange(5, 0, -1):
if slot_current > beam.absorber_transmission_list[slot_no]:
slot_pos = slot_no - 1
beam.setAbsorber(slot_pos)
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
else:
if threshold/float(temp_data['e_I1'][temp_data.index[-1]]) < max_exposure_time and N_last < max_exposure_time:
N = np.ceil(N_last*threshold/float(temp_data['e_I1'][temp_data.index[-1]]))
print('e_I1={}'.format(float(temp_data['e_I1'][temp_data.index[-1]])))
print('N={}'.format(N))
print('exposure time = {}'.format(N*exposure_time))
else:
N = max_exposure_time
print('exposure time is MAX')
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
self.measure(N*exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, N*exposure_time)
N_last = N
elif len(threshold)>1 and temp_data['e_I1'][temp_data.index[-1]] > threshold[-1]:
slot_pos = slot_pos+1
print('The absorber is slot {}\n'.format(slot_pos))
print('The theta is {}\n'.format(theta))
beam.setAbsorber(slot_pos)
self.measure(exposure_time, extra=extra)
temp_data = self.XR_data_output(slot_pos, exposure_time)
output_data = output_data.append(temp_data, ignore_index=True)
#save to file
output_data.to_csv(XR_FILENAME)
#reset the changed items
bec.enable_plots()
#bec.enable_table()
self.naming_scheme = self.naming_scheme_hold
#remove the absorber completely out of the beam
beam.absorber_out()
pilatus_name.stats3.total.kind = 'hinted'
pilatus_name.stats4.total.kind = 'hinted'
SAXSy.move(default_SAXSy)
def XR_abort(self):
'''Reset the beamline status back to origin before XRR measurement.
'''
beam.off()
cms.modeXRMeasurement()
beam.setAbsorber(0)
#remove the absorber completely out of the beam
beam.absorber_out()
self.xo()
self.yo()
self.tho()
bec.enable_plots()
bec.enable_table()
pilatus_name.hints = {'fields': ['pilatus800_stats3_total', 'pilatus800_stats4_total']}
def XR_data_output(self, slot_pos, exposure_time):
'''XRR data output in DataFrame format, including:
'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
'''
h = db[-1]
dtable = h.table()
#beam.absorber_transmission_list = [1, 0.041, 0.0017425, 0.00007301075, 0.00000287662355, 0.000000122831826, 0.00000000513437]
#Energy = 13.5kev
if abs(beam.energy(verbosity=1)-13.5) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_13p5kev
#Energy = 17kev
elif abs(beam.energy(verbosity=1)-17) < 0.1:
beam.absorber_transmission_list = beam.absorber_transmission_list_17kev
else:
print("The absorber has not been calibrated under current Energy!!!")
sth_pos = h.start['sample_th']
qz = 4*np.pi*np.sin(np.deg2rad(sth_pos))/h.start['calibration_wavelength_A']
scan_id = h.start['scan_id']
I0 = h.start['beam_int_bim5'] #beam intensity from bim5
I1 = dtable.pilatus800_stats1_total
I2 = dtable.pilatus800_stats2_total
I3 = 2*dtable.pilatus800_stats1_total - dtable.pilatus800_stats2_total
In = I3 / beam.absorber_transmission_list[slot_pos] / exposure_time
current_data = {'a_qz': qz, #qz
'b_th':sth_pos, #incident angle
'c_scanID': scan_id, #scan ID
'd_I0': I0, #bim5 flux
'e_I1': I1, #ROI1
'f_I2': I2, #ROI2
'g_I3': I3, #2*ROI1-ROI2
'h_In': In, #reflectivity
'i_absorber_slot': slot_pos, #absorption slot No.
'j_exposure_seconds': exposure_time} #exposure time
return pds.DataFrame(data=current_data)
def XR_align(self, step=0, reflection_angle=0.15, verbosity=3):
'''Specific alignment for XRR
Align the sample with respect to the beam. XR alignment involves
vertical translation to the beam center, and rocking theta to get the
sample plane parralel to the beam. Finally, the angle is re-optimized
in reflection mode.
The 'step' argument can optionally be given to jump to a particular
step in the sequence.'''
cms.modeAlignment()
if verbosity>=4:
print(' Aligning {}'.format(self.name))
if step<=0:
# Prepare for alignment
cms.modeAlignment()
if RE.state!='idle':
RE.abort()
if get_beamline().current_mode!='alignment':
if verbosity>=2:
print("WARNING: Beamline is not in alignment mode (mode is '{}')".format(get_beamline().current_mode))
#get_beamline().modeAlignment()
get_beamline().setDirectBeamROI()
beam.on()
if step<=2:
if verbosity>=4:
print(' align: searching')
# Estimate full-beam intensity
value = None
if True:
# You can eliminate this, in which case RE.md['beam_intensity_expected'] is used by default
self.yr(-2)
#detector = gs.DETS[0]
detector = get_beamline().detector[0]
value_name = get_beamline().TABLE_COLS[0]
RE(count([detector]))
value = detector.read()[value_name]['value']
self.yr(+2)
if 'beam_intensity_expected' in RE.md and value<RE.md['beam_intensity_expected']*0.75:
print('WARNING: Direct beam intensity ({}) lower than it should be ({})'.format(value, RE.md['beam_intensity_expected']))
# Find the step-edge
self.ysearch(step_size=0.5, min_step=0.005, intensity=value, target=0.5, verbosity=verbosity, polarity=-1)
# Find the peak
self.thsearch(step_size=0.4, min_step=0.01, target='max', verbosity=verbosity)
if step<=4:
if verbosity>=4:
print(' align: fitting')
fit_scan(smy, 1.2, 21, fit='HMi')
#time.sleep(2)
fit_scan(sth, 1.5, 21, fit='max')
#time.sleep(2)
if step<=8:
#fit_scan(smy, 0.6, 21, fit='sigmoid_r')
fit_edge(smy, 0.6, 21)
#time.sleep(2)
#fit_edge(smy, 0.4, 21)
fit_scan(sth, 0.8, 21, fit='COM')
#time.sleep(2)
self.setOrigin(['y', 'th'])
if step<=9 and reflection_angle is not None:
# Final alignment using reflected beam
if verbosity>=4:
print(' align: reflected beam')
if abs(beam.energy(verbosity)-17)<0.1:
reflection_angle = 0.15
get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0)
#get_beamline().setReflectedBeamROI(total_angle=reflection_angle*2.0, size=[12,2])
self.thabs(reflection_angle)
result = fit_scan(sth, 0.1, 41, fit='max')
#result = fit_scan(sth, 0.2, 81, fit='max') #it's useful for alignment of SmarAct stage
sth_target = result.values['x_max']-reflection_angle
if result.values['y_max']>50:
th_target = self._axes['th'].motor_to_cur(sth_target)
self.thsetOrigin(th_target)
#fit_scan(smy, 0.2, 21, fit='max')
#self.setOrigin(['y'])
if step<=10:
self.thabs(0.0)
beam.off()
def XR_check_alignment(self, int_angle=1, exposure_time=1, roi_size=[12, 30]):
''' Check the alignment of the XR.
The total_angle is the incident angle.
The reflection spot should be located in the center of ROI2'''
cms.modeXRMeasurement()
#cms.setXRROI(total_angle=int_angle*2, size=roi_size, default_WAXSy=-73)
self.yo()
self.thabs(int_angle)
self.measure(exposure_time)
print('===========sam.th moves to {}deg and ROI1 is set at {}deg. ============'.format(int_angle, int_angle*2))
print('======Please check the ROI whether at the reflected position. =======')
print('========If not, modify sam.th or schi to meet the reflected beam. ===========')
"""#abandoned code
| 41.538462
| 257
| 0.542689
| 16,837
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| 0
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| 0.350468
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| 0.054945
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| null | 0
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0
| 7
|
a97465f7d0a8b81a94c39ab477a2dedb9d8e980a
| 146,658
|
py
|
Python
|
pyboto3/workdocs.py
|
gehad-shaat/pyboto3
|
4a0c2851a8bc04fb1c71c36086f7bb257e48181d
|
[
"MIT"
] | 91
|
2016-12-31T11:38:37.000Z
|
2021-09-16T19:33:23.000Z
|
pyboto3/workdocs.py
|
gehad-shaat/pyboto3
|
4a0c2851a8bc04fb1c71c36086f7bb257e48181d
|
[
"MIT"
] | 7
|
2017-01-02T18:54:23.000Z
|
2020-08-11T13:54:02.000Z
|
pyboto3/workdocs.py
|
gehad-shaat/pyboto3
|
4a0c2851a8bc04fb1c71c36086f7bb257e48181d
|
[
"MIT"
] | 26
|
2016-12-31T13:11:00.000Z
|
2022-03-03T21:01:12.000Z
|
'''
The MIT License (MIT)
Copyright (c) 2016 WavyCloud
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
'''
def abort_document_version_upload(AuthenticationToken=None, DocumentId=None, VersionId=None):
"""
Aborts the upload of the specified document version that was previously initiated by InitiateDocumentVersionUpload . The client should make this call only when it no longer intends to upload the document version, or fails to do so.
See also: AWS API Documentation
Exceptions
:example: response = client.abort_document_version_upload(
AuthenticationToken='string',
DocumentId='string',
VersionId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe ID of the version.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def activate_user(UserId=None, AuthenticationToken=None):
"""
Activates the specified user. Only active users can access Amazon WorkDocs.
See also: AWS API Documentation
Exceptions
:example: response = client.activate_user(
UserId='string',
AuthenticationToken='string'
)
:type UserId: string
:param UserId: [REQUIRED]\nThe ID of the user.\n
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:rtype: dict
ReturnsResponse Syntax
{
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
Response Structure
(dict) --
User (dict) --
The user information.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def add_resource_permissions(AuthenticationToken=None, ResourceId=None, Principals=None, NotificationOptions=None):
"""
Creates a set of permissions for the specified folder or document. The resource permissions are overwritten if the principals already have different permissions.
See also: AWS API Documentation
Exceptions
:example: response = client.add_resource_permissions(
AuthenticationToken='string',
ResourceId='string',
Principals=[
{
'Id': 'string',
'Type': 'USER'|'GROUP'|'INVITE'|'ANONYMOUS'|'ORGANIZATION',
'Role': 'VIEWER'|'CONTRIBUTOR'|'OWNER'|'COOWNER'
},
],
NotificationOptions={
'SendEmail': True|False,
'EmailMessage': 'string'
}
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type Principals: list
:param Principals: [REQUIRED]\nThe users, groups, or organization being granted permission.\n\n(dict) --Describes the recipient type and ID, if available.\n\nId (string) -- [REQUIRED]The ID of the recipient.\n\nType (string) -- [REQUIRED]The type of the recipient.\n\nRole (string) -- [REQUIRED]The role of the recipient.\n\n\n\n\n
:type NotificationOptions: dict
:param NotificationOptions: The notification options.\n\nSendEmail (boolean) --Boolean value to indicate an email notification should be sent to the receipients.\n\nEmailMessage (string) --Text value to be included in the email body.\n\n\n
:rtype: dict
ReturnsResponse Syntax
{
'ShareResults': [
{
'PrincipalId': 'string',
'InviteePrincipalId': 'string',
'Role': 'VIEWER'|'CONTRIBUTOR'|'OWNER'|'COOWNER',
'Status': 'SUCCESS'|'FAILURE',
'ShareId': 'string',
'StatusMessage': 'string'
},
]
}
Response Structure
(dict) --
ShareResults (list) --
The share results.
(dict) --
Describes the share results of a resource.
PrincipalId (string) --
The ID of the principal.
InviteePrincipalId (string) --
The ID of the invited user.
Role (string) --
The role.
Status (string) --
The status.
ShareId (string) --
The ID of the resource that was shared.
StatusMessage (string) --
The status message.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'ShareResults': [
{
'PrincipalId': 'string',
'InviteePrincipalId': 'string',
'Role': 'VIEWER'|'CONTRIBUTOR'|'OWNER'|'COOWNER',
'Status': 'SUCCESS'|'FAILURE',
'ShareId': 'string',
'StatusMessage': 'string'
},
]
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def can_paginate(operation_name=None):
"""
Check if an operation can be paginated.
:type operation_name: string
:param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo').
"""
pass
def create_comment(AuthenticationToken=None, DocumentId=None, VersionId=None, ParentId=None, ThreadId=None, Text=None, Visibility=None, NotifyCollaborators=None):
"""
Adds a new comment to the specified document version.
See also: AWS API Documentation
Exceptions
:example: response = client.create_comment(
AuthenticationToken='string',
DocumentId='string',
VersionId='string',
ParentId='string',
ThreadId='string',
Text='string',
Visibility='PUBLIC'|'PRIVATE',
NotifyCollaborators=True|False
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe ID of the document version.\n
:type ParentId: string
:param ParentId: The ID of the parent comment.
:type ThreadId: string
:param ThreadId: The ID of the root comment in the thread.
:type Text: string
:param Text: [REQUIRED]\nThe text of the comment.\n
:type Visibility: string
:param Visibility: The visibility of the comment. Options are either PRIVATE, where the comment is visible only to the comment author and document owner and co-owners, or PUBLIC, where the comment is visible to document owners, co-owners, and contributors.
:type NotifyCollaborators: boolean
:param NotifyCollaborators: Set this parameter to TRUE to send an email out to the document collaborators after the comment is created.
:rtype: dict
ReturnsResponse Syntax
{
'Comment': {
'CommentId': 'string',
'ParentId': 'string',
'ThreadId': 'string',
'Text': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'Status': 'DRAFT'|'PUBLISHED'|'DELETED',
'Visibility': 'PUBLIC'|'PRIVATE',
'RecipientId': 'string'
}
}
Response Structure
(dict) --
Comment (dict) --
The comment that has been created.
CommentId (string) --
The ID of the comment.
ParentId (string) --
The ID of the parent comment.
ThreadId (string) --
The ID of the root comment in the thread.
Text (string) --
The text of the comment.
Contributor (dict) --
The details of the user who made the comment.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
CreatedTimestamp (datetime) --
The time that the comment was created.
Status (string) --
The status of the comment.
Visibility (string) --
The visibility of the comment. Options are either PRIVATE, where the comment is visible only to the comment author and document owner and co-owners, or PUBLIC, where the comment is visible to document owners, co-owners, and contributors.
RecipientId (string) --
If the comment is a reply to another user\'s comment, this field contains the user ID of the user being replied to.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DocumentLockedForCommentsException
WorkDocs.Client.exceptions.InvalidCommentOperationException
:return: {
'Comment': {
'CommentId': 'string',
'ParentId': 'string',
'ThreadId': 'string',
'Text': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'Status': 'DRAFT'|'PUBLISHED'|'DELETED',
'Visibility': 'PUBLIC'|'PRIVATE',
'RecipientId': 'string'
}
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DocumentLockedForCommentsException
WorkDocs.Client.exceptions.InvalidCommentOperationException
"""
pass
def create_custom_metadata(AuthenticationToken=None, ResourceId=None, VersionId=None, CustomMetadata=None):
"""
Adds one or more custom properties to the specified resource (a folder, document, or version).
See also: AWS API Documentation
Exceptions
:example: response = client.create_custom_metadata(
AuthenticationToken='string',
ResourceId='string',
VersionId='string',
CustomMetadata={
'string': 'string'
}
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type VersionId: string
:param VersionId: The ID of the version, if the custom metadata is being added to a document version.
:type CustomMetadata: dict
:param CustomMetadata: [REQUIRED]\nCustom metadata in the form of name-value pairs.\n\n(string) --\n(string) --\n\n\n\n
:rtype: dict
ReturnsResponse Syntax
{}
Response Structure
(dict) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.CustomMetadataLimitExceededException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {}
:returns:
(dict) --
"""
pass
def create_folder(AuthenticationToken=None, Name=None, ParentFolderId=None):
"""
Creates a folder with the specified name and parent folder.
See also: AWS API Documentation
Exceptions
:example: response = client.create_folder(
AuthenticationToken='string',
Name='string',
ParentFolderId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type Name: string
:param Name: The name of the new folder.
:type ParentFolderId: string
:param ParentFolderId: [REQUIRED]\nThe ID of the parent folder.\n
:rtype: dict
ReturnsResponse Syntax
{
'Metadata': {
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
}
}
Response Structure
(dict) --
Metadata (dict) --
The metadata of the folder.
Id (string) --
The ID of the folder.
Name (string) --
The name of the folder.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the folder was created.
ModifiedTimestamp (datetime) --
The time when the folder was updated.
ResourceState (string) --
The resource state of the folder.
Signature (string) --
The unique identifier created from the subfolders and documents of the folder.
Labels (list) --
List of labels on the folder.
(string) --
Size (integer) --
The size of the folder metadata.
LatestVersionSize (integer) --
The size of the latest version of the folder metadata.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.LimitExceededException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Metadata': {
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
}
}
:returns:
(string) --
"""
pass
def create_labels(ResourceId=None, Labels=None, AuthenticationToken=None):
"""
Adds the specified list of labels to the given resource (a document or folder)
See also: AWS API Documentation
Exceptions
:example: response = client.create_labels(
ResourceId='string',
Labels=[
'string',
],
AuthenticationToken='string'
)
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type Labels: list
:param Labels: [REQUIRED]\nList of labels to add to the resource.\n\n(string) --\n\n
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:rtype: dict
ReturnsResponse Syntax
{}
Response Structure
(dict) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.TooManyLabelsException
:return: {}
:returns:
(dict) --
"""
pass
def create_notification_subscription(OrganizationId=None, Endpoint=None, Protocol=None, SubscriptionType=None):
"""
Configure Amazon WorkDocs to use Amazon SNS notifications. The endpoint receives a confirmation message, and must confirm the subscription.
For more information, see Subscribe to Notifications in the Amazon WorkDocs Developer Guide .
See also: AWS API Documentation
Exceptions
:example: response = client.create_notification_subscription(
OrganizationId='string',
Endpoint='string',
Protocol='HTTPS',
SubscriptionType='ALL'
)
:type OrganizationId: string
:param OrganizationId: [REQUIRED]\nThe ID of the organization.\n
:type Endpoint: string
:param Endpoint: [REQUIRED]\nThe endpoint to receive the notifications. If the protocol is HTTPS, the endpoint is a URL that begins with https .\n
:type Protocol: string
:param Protocol: [REQUIRED]\nThe protocol to use. The supported value is https, which delivers JSON-encoded messages using HTTPS POST.\n
:type SubscriptionType: string
:param SubscriptionType: [REQUIRED]\nThe notification type.\n
:rtype: dict
ReturnsResponse Syntax
{
'Subscription': {
'SubscriptionId': 'string',
'EndPoint': 'string',
'Protocol': 'HTTPS'
}
}
Response Structure
(dict) --
Subscription (dict) --
The subscription.
SubscriptionId (string) --
The ID of the subscription.
EndPoint (string) --
The endpoint of the subscription.
Protocol (string) --
The protocol of the subscription.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.TooManySubscriptionsException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Subscription': {
'SubscriptionId': 'string',
'EndPoint': 'string',
'Protocol': 'HTTPS'
}
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.TooManySubscriptionsException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def create_user(OrganizationId=None, Username=None, EmailAddress=None, GivenName=None, Surname=None, Password=None, TimeZoneId=None, StorageRule=None, AuthenticationToken=None):
"""
Creates a user in a Simple AD or Microsoft AD directory. The status of a newly created user is "ACTIVE". New users can access Amazon WorkDocs.
See also: AWS API Documentation
Exceptions
:example: response = client.create_user(
OrganizationId='string',
Username='string',
EmailAddress='string',
GivenName='string',
Surname='string',
Password='string',
TimeZoneId='string',
StorageRule={
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
},
AuthenticationToken='string'
)
:type OrganizationId: string
:param OrganizationId: The ID of the organization.
:type Username: string
:param Username: [REQUIRED]\nThe login name of the user.\n
:type EmailAddress: string
:param EmailAddress: The email address of the user.
:type GivenName: string
:param GivenName: [REQUIRED]\nThe given name of the user.\n
:type Surname: string
:param Surname: [REQUIRED]\nThe surname of the user.\n
:type Password: string
:param Password: [REQUIRED]\nThe password of the user.\n
:type TimeZoneId: string
:param TimeZoneId: The time zone ID of the user.
:type StorageRule: dict
:param StorageRule: The amount of storage for the user.\n\nStorageAllocatedInBytes (integer) --The amount of storage allocated, in bytes.\n\nStorageType (string) --The type of storage.\n\n\n
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:rtype: dict
ReturnsResponse Syntax
{
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
Response Structure
(dict) --
User (dict) --
The user information.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
Exceptions
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
:returns:
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def deactivate_user(UserId=None, AuthenticationToken=None):
"""
Deactivates the specified user, which revokes the user\'s access to Amazon WorkDocs.
See also: AWS API Documentation
Exceptions
:example: response = client.deactivate_user(
UserId='string',
AuthenticationToken='string'
)
:type UserId: string
:param UserId: [REQUIRED]\nThe ID of the user.\n
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def delete_comment(AuthenticationToken=None, DocumentId=None, VersionId=None, CommentId=None):
"""
Deletes the specified comment from the document version.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_comment(
AuthenticationToken='string',
DocumentId='string',
VersionId='string',
CommentId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe ID of the document version.\n
:type CommentId: string
:param CommentId: [REQUIRED]\nThe ID of the comment.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DocumentLockedForCommentsException
"""
pass
def delete_custom_metadata(AuthenticationToken=None, ResourceId=None, VersionId=None, Keys=None, DeleteAll=None):
"""
Deletes custom metadata from the specified resource.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_custom_metadata(
AuthenticationToken='string',
ResourceId='string',
VersionId='string',
Keys=[
'string',
],
DeleteAll=True|False
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource, either a document or folder.\n
:type VersionId: string
:param VersionId: The ID of the version, if the custom metadata is being deleted from a document version.
:type Keys: list
:param Keys: List of properties to remove.\n\n(string) --\n\n
:type DeleteAll: boolean
:param DeleteAll: Flag to indicate removal of all custom metadata properties from the specified resource.
:rtype: dict
ReturnsResponse Syntax
{}
Response Structure
(dict) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {}
:returns:
(dict) --
"""
pass
def delete_document(AuthenticationToken=None, DocumentId=None):
"""
Permanently deletes the specified document and its associated metadata.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_document(
AuthenticationToken='string',
DocumentId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.ConcurrentModificationException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def delete_folder(AuthenticationToken=None, FolderId=None):
"""
Permanently deletes the specified folder and its contents.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_folder(
AuthenticationToken='string',
FolderId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.ConcurrentModificationException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def delete_folder_contents(AuthenticationToken=None, FolderId=None):
"""
Deletes the contents of the specified folder.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_folder_contents(
AuthenticationToken='string',
FolderId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def delete_labels(ResourceId=None, AuthenticationToken=None, Labels=None, DeleteAll=None):
"""
Deletes the specified list of labels from a resource.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_labels(
ResourceId='string',
AuthenticationToken='string',
Labels=[
'string',
],
DeleteAll=True|False
)
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type Labels: list
:param Labels: List of labels to delete from the resource.\n\n(string) --\n\n
:type DeleteAll: boolean
:param DeleteAll: Flag to request removal of all labels from the specified resource.
:rtype: dict
ReturnsResponse Syntax
{}
Response Structure
(dict) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {}
:returns:
(dict) --
"""
pass
def delete_notification_subscription(SubscriptionId=None, OrganizationId=None):
"""
Deletes the specified subscription from the specified organization.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_notification_subscription(
SubscriptionId='string',
OrganizationId='string'
)
:type SubscriptionId: string
:param SubscriptionId: [REQUIRED]\nThe ID of the subscription.\n
:type OrganizationId: string
:param OrganizationId: [REQUIRED]\nThe ID of the organization.\n
:returns:
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.ProhibitedStateException
"""
pass
def delete_user(AuthenticationToken=None, UserId=None):
"""
Deletes the specified user from a Simple AD or Microsoft AD directory.
See also: AWS API Documentation
Exceptions
:example: response = client.delete_user(
AuthenticationToken='string',
UserId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Do not set this field when using administrative API actions, as in accessing the API using AWS credentials.
:type UserId: string
:param UserId: [REQUIRED]\nThe ID of the user.\n
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_activities(AuthenticationToken=None, StartTime=None, EndTime=None, OrganizationId=None, ActivityTypes=None, ResourceId=None, UserId=None, IncludeIndirectActivities=None, Limit=None, Marker=None):
"""
Describes the user activities in a specified time period.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_activities(
AuthenticationToken='string',
StartTime=datetime(2015, 1, 1),
EndTime=datetime(2015, 1, 1),
OrganizationId='string',
ActivityTypes='string',
ResourceId='string',
UserId='string',
IncludeIndirectActivities=True|False,
Limit=123,
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type StartTime: datetime
:param StartTime: The timestamp that determines the starting time of the activities. The response includes the activities performed after the specified timestamp.
:type EndTime: datetime
:param EndTime: The timestamp that determines the end time of the activities. The response includes the activities performed before the specified timestamp.
:type OrganizationId: string
:param OrganizationId: The ID of the organization. This is a mandatory parameter when using administrative API (SigV4) requests.
:type ActivityTypes: string
:param ActivityTypes: Specifies which activity types to include in the response. If this field is left empty, all activity types are returned.
:type ResourceId: string
:param ResourceId: The document or folder ID for which to describe activity types.
:type UserId: string
:param UserId: The ID of the user who performed the action. The response includes activities pertaining to this user. This is an optional parameter and is only applicable for administrative API (SigV4) requests.
:type IncludeIndirectActivities: boolean
:param IncludeIndirectActivities: Includes indirect activities. An indirect activity results from a direct activity performed on a parent resource. For example, sharing a parent folder (the direct activity) shares all of the subfolders and documents within the parent folder (the indirect activity).
:type Limit: integer
:param Limit: The maximum number of items to return.
:type Marker: string
:param Marker: The marker for the next set of results.
:rtype: dict
ReturnsResponse Syntax
{
'UserActivities': [
{
'Type': 'DOCUMENT_CHECKED_IN'|'DOCUMENT_CHECKED_OUT'|'DOCUMENT_RENAMED'|'DOCUMENT_VERSION_UPLOADED'|'DOCUMENT_VERSION_DELETED'|'DOCUMENT_VERSION_VIEWED'|'DOCUMENT_VERSION_DOWNLOADED'|'DOCUMENT_RECYCLED'|'DOCUMENT_RESTORED'|'DOCUMENT_REVERTED'|'DOCUMENT_SHARED'|'DOCUMENT_UNSHARED'|'DOCUMENT_SHARE_PERMISSION_CHANGED'|'DOCUMENT_SHAREABLE_LINK_CREATED'|'DOCUMENT_SHAREABLE_LINK_REMOVED'|'DOCUMENT_SHAREABLE_LINK_PERMISSION_CHANGED'|'DOCUMENT_MOVED'|'DOCUMENT_COMMENT_ADDED'|'DOCUMENT_COMMENT_DELETED'|'DOCUMENT_ANNOTATION_ADDED'|'DOCUMENT_ANNOTATION_DELETED'|'FOLDER_CREATED'|'FOLDER_DELETED'|'FOLDER_RENAMED'|'FOLDER_RECYCLED'|'FOLDER_RESTORED'|'FOLDER_SHARED'|'FOLDER_UNSHARED'|'FOLDER_SHARE_PERMISSION_CHANGED'|'FOLDER_SHAREABLE_LINK_CREATED'|'FOLDER_SHAREABLE_LINK_REMOVED'|'FOLDER_SHAREABLE_LINK_PERMISSION_CHANGED'|'FOLDER_MOVED',
'TimeStamp': datetime(2015, 1, 1),
'IsIndirectActivity': True|False,
'OrganizationId': 'string',
'Initiator': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'Participants': {
'Users': [
{
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
],
'Groups': [
{
'Id': 'string',
'Name': 'string'
},
]
},
'ResourceMetadata': {
'Type': 'FOLDER'|'DOCUMENT',
'Name': 'string',
'OriginalName': 'string',
'Id': 'string',
'VersionId': 'string',
'Owner': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'ParentId': 'string'
},
'OriginalParent': {
'Type': 'FOLDER'|'DOCUMENT',
'Name': 'string',
'OriginalName': 'string',
'Id': 'string',
'VersionId': 'string',
'Owner': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'ParentId': 'string'
},
'CommentMetadata': {
'CommentId': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'CommentStatus': 'DRAFT'|'PUBLISHED'|'DELETED',
'RecipientId': 'string'
}
},
],
'Marker': 'string'
}
Response Structure
(dict) --
UserActivities (list) --
The list of activities for the specified user and time period.
(dict) --
Describes the activity information.
Type (string) --
The activity type.
TimeStamp (datetime) --
The timestamp when the action was performed.
IsIndirectActivity (boolean) --
Indicates whether an activity is indirect or direct. An indirect activity results from a direct activity performed on a parent resource. For example, sharing a parent folder (the direct activity) shares all of the subfolders and documents within the parent folder (the indirect activity).
OrganizationId (string) --
The ID of the organization.
Initiator (dict) --
The user who performed the action.
Id (string) --
The ID of the user.
Username (string) --
The name of the user.
GivenName (string) --
The given name of the user before a rename operation.
Surname (string) --
The surname of the user.
EmailAddress (string) --
The email address of the user.
Participants (dict) --
The list of users or groups impacted by this action. This is an optional field and is filled for the following sharing activities: DOCUMENT_SHARED, DOCUMENT_SHARED, DOCUMENT_UNSHARED, FOLDER_SHARED, FOLDER_UNSHARED.
Users (list) --
The list of users.
(dict) --
Describes the metadata of the user.
Id (string) --
The ID of the user.
Username (string) --
The name of the user.
GivenName (string) --
The given name of the user before a rename operation.
Surname (string) --
The surname of the user.
EmailAddress (string) --
The email address of the user.
Groups (list) --
The list of user groups.
(dict) --
Describes the metadata of a user group.
Id (string) --
The ID of the user group.
Name (string) --
The name of the group.
ResourceMetadata (dict) --
The metadata of the resource involved in the user action.
Type (string) --
The type of resource.
Name (string) --
The name of the resource.
OriginalName (string) --
The original name of the resource before a rename operation.
Id (string) --
The ID of the resource.
VersionId (string) --
The version ID of the resource. This is an optional field and is filled for action on document version.
Owner (dict) --
The owner of the resource.
Id (string) --
The ID of the user.
Username (string) --
The name of the user.
GivenName (string) --
The given name of the user before a rename operation.
Surname (string) --
The surname of the user.
EmailAddress (string) --
The email address of the user.
ParentId (string) --
The parent ID of the resource before a rename operation.
OriginalParent (dict) --
The original parent of the resource. This is an optional field and is filled for move activities.
Type (string) --
The type of resource.
Name (string) --
The name of the resource.
OriginalName (string) --
The original name of the resource before a rename operation.
Id (string) --
The ID of the resource.
VersionId (string) --
The version ID of the resource. This is an optional field and is filled for action on document version.
Owner (dict) --
The owner of the resource.
Id (string) --
The ID of the user.
Username (string) --
The name of the user.
GivenName (string) --
The given name of the user before a rename operation.
Surname (string) --
The surname of the user.
EmailAddress (string) --
The email address of the user.
ParentId (string) --
The parent ID of the resource before a rename operation.
CommentMetadata (dict) --
Metadata of the commenting activity. This is an optional field and is filled for commenting activities.
CommentId (string) --
The ID of the comment.
Contributor (dict) --
The user who made the comment.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
CreatedTimestamp (datetime) --
The timestamp that the comment was created.
CommentStatus (string) --
The status of the comment.
RecipientId (string) --
The ID of the user being replied to.
Marker (string) --
The marker for the next set of results.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'UserActivities': [
{
'Type': 'DOCUMENT_CHECKED_IN'|'DOCUMENT_CHECKED_OUT'|'DOCUMENT_RENAMED'|'DOCUMENT_VERSION_UPLOADED'|'DOCUMENT_VERSION_DELETED'|'DOCUMENT_VERSION_VIEWED'|'DOCUMENT_VERSION_DOWNLOADED'|'DOCUMENT_RECYCLED'|'DOCUMENT_RESTORED'|'DOCUMENT_REVERTED'|'DOCUMENT_SHARED'|'DOCUMENT_UNSHARED'|'DOCUMENT_SHARE_PERMISSION_CHANGED'|'DOCUMENT_SHAREABLE_LINK_CREATED'|'DOCUMENT_SHAREABLE_LINK_REMOVED'|'DOCUMENT_SHAREABLE_LINK_PERMISSION_CHANGED'|'DOCUMENT_MOVED'|'DOCUMENT_COMMENT_ADDED'|'DOCUMENT_COMMENT_DELETED'|'DOCUMENT_ANNOTATION_ADDED'|'DOCUMENT_ANNOTATION_DELETED'|'FOLDER_CREATED'|'FOLDER_DELETED'|'FOLDER_RENAMED'|'FOLDER_RECYCLED'|'FOLDER_RESTORED'|'FOLDER_SHARED'|'FOLDER_UNSHARED'|'FOLDER_SHARE_PERMISSION_CHANGED'|'FOLDER_SHAREABLE_LINK_CREATED'|'FOLDER_SHAREABLE_LINK_REMOVED'|'FOLDER_SHAREABLE_LINK_PERMISSION_CHANGED'|'FOLDER_MOVED',
'TimeStamp': datetime(2015, 1, 1),
'IsIndirectActivity': True|False,
'OrganizationId': 'string',
'Initiator': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'Participants': {
'Users': [
{
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
],
'Groups': [
{
'Id': 'string',
'Name': 'string'
},
]
},
'ResourceMetadata': {
'Type': 'FOLDER'|'DOCUMENT',
'Name': 'string',
'OriginalName': 'string',
'Id': 'string',
'VersionId': 'string',
'Owner': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'ParentId': 'string'
},
'OriginalParent': {
'Type': 'FOLDER'|'DOCUMENT',
'Name': 'string',
'OriginalName': 'string',
'Id': 'string',
'VersionId': 'string',
'Owner': {
'Id': 'string',
'Username': 'string',
'GivenName': 'string',
'Surname': 'string',
'EmailAddress': 'string'
},
'ParentId': 'string'
},
'CommentMetadata': {
'CommentId': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'CommentStatus': 'DRAFT'|'PUBLISHED'|'DELETED',
'RecipientId': 'string'
}
},
],
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_comments(AuthenticationToken=None, DocumentId=None, VersionId=None, Limit=None, Marker=None):
"""
List all the comments for the specified document version.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_comments(
AuthenticationToken='string',
DocumentId='string',
VersionId='string',
Limit=123,
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe ID of the document version.\n
:type Limit: integer
:param Limit: The maximum number of items to return.
:type Marker: string
:param Marker: The marker for the next set of results. This marker was received from a previous call.
:rtype: dict
ReturnsResponse Syntax
{
'Comments': [
{
'CommentId': 'string',
'ParentId': 'string',
'ThreadId': 'string',
'Text': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'Status': 'DRAFT'|'PUBLISHED'|'DELETED',
'Visibility': 'PUBLIC'|'PRIVATE',
'RecipientId': 'string'
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Comments (list) --
The list of comments for the specified document version.
(dict) --
Describes a comment.
CommentId (string) --
The ID of the comment.
ParentId (string) --
The ID of the parent comment.
ThreadId (string) --
The ID of the root comment in the thread.
Text (string) --
The text of the comment.
Contributor (dict) --
The details of the user who made the comment.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
CreatedTimestamp (datetime) --
The time that the comment was created.
Status (string) --
The status of the comment.
Visibility (string) --
The visibility of the comment. Options are either PRIVATE, where the comment is visible only to the comment author and document owner and co-owners, or PUBLIC, where the comment is visible to document owners, co-owners, and contributors.
RecipientId (string) --
If the comment is a reply to another user\'s comment, this field contains the user ID of the user being replied to.
Marker (string) --
The marker for the next set of results. This marker was received from a previous call.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Comments': [
{
'CommentId': 'string',
'ParentId': 'string',
'ThreadId': 'string',
'Text': 'string',
'Contributor': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
'CreatedTimestamp': datetime(2015, 1, 1),
'Status': 'DRAFT'|'PUBLISHED'|'DELETED',
'Visibility': 'PUBLIC'|'PRIVATE',
'RecipientId': 'string'
},
],
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_document_versions(AuthenticationToken=None, DocumentId=None, Marker=None, Limit=None, Include=None, Fields=None):
"""
Retrieves the document versions for the specified document.
By default, only active versions are returned.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_document_versions(
AuthenticationToken='string',
DocumentId='string',
Marker='string',
Limit=123,
Include='string',
Fields='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call.)
:type Limit: integer
:param Limit: The maximum number of versions to return with this call.
:type Include: string
:param Include: A comma-separated list of values. Specify 'INITIALIZED' to include incomplete versions.
:type Fields: string
:param Fields: Specify 'SOURCE' to include initialized versions and a URL for the source document.
:rtype: dict
ReturnsResponse Syntax
{
'DocumentVersions': [
{
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
],
'Marker': 'string'
}
Response Structure
(dict) --
DocumentVersions (list) --
The document versions.
(dict) --
Describes a version of a document.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.ProhibitedStateException
:return: {
'DocumentVersions': [
{
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
],
'Marker': 'string'
}
:returns:
(string) --
(string) --
"""
pass
def describe_folder_contents(AuthenticationToken=None, FolderId=None, Sort=None, Order=None, Limit=None, Marker=None, Type=None, Include=None):
"""
Describes the contents of the specified folder, including its documents and subfolders.
By default, Amazon WorkDocs returns the first 100 active document and folder metadata items. If there are more results, the response includes a marker that you can use to request the next set of results. You can also request initialized documents.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_folder_contents(
AuthenticationToken='string',
FolderId='string',
Sort='DATE'|'NAME',
Order='ASCENDING'|'DESCENDING',
Limit=123,
Marker='string',
Type='ALL'|'DOCUMENT'|'FOLDER',
Include='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:type Sort: string
:param Sort: The sorting criteria.
:type Order: string
:param Order: The order for the contents of the folder.
:type Limit: integer
:param Limit: The maximum number of items to return with this call.
:type Marker: string
:param Marker: The marker for the next set of results. This marker was received from a previous call.
:type Type: string
:param Type: The type of items.
:type Include: string
:param Include: The contents to include. Specify 'INITIALIZED' to include initialized documents.
:rtype: dict
ReturnsResponse Syntax
{
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Documents': [
{
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Folders (list) --
The subfolders in the specified folder.
(dict) --
Describes a folder.
Id (string) --
The ID of the folder.
Name (string) --
The name of the folder.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the folder was created.
ModifiedTimestamp (datetime) --
The time when the folder was updated.
ResourceState (string) --
The resource state of the folder.
Signature (string) --
The unique identifier created from the subfolders and documents of the folder.
Labels (list) --
List of labels on the folder.
(string) --
Size (integer) --
The size of the folder metadata.
LatestVersionSize (integer) --
The size of the latest version of the folder metadata.
Documents (list) --
The documents in the specified folder.
(dict) --
Describes the document.
Id (string) --
The ID of the document.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the document was created.
ModifiedTimestamp (datetime) --
The time when the document was updated.
LatestVersionMetadata (dict) --
The latest version of the document.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
ResourceState (string) --
The resource state.
Labels (list) --
List of labels on the document.
(string) --
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.ProhibitedStateException
:return: {
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Documents': [
{
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
],
'Marker': 'string'
}
:returns:
(string) --
"""
pass
def describe_groups(AuthenticationToken=None, SearchQuery=None, OrganizationId=None, Marker=None, Limit=None):
"""
Describes the groups specified by the query. Groups are defined by the underlying Active Directory.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_groups(
AuthenticationToken='string',
SearchQuery='string',
OrganizationId='string',
Marker='string',
Limit=123
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type SearchQuery: string
:param SearchQuery: [REQUIRED]\nA query to describe groups by group name.\n
:type OrganizationId: string
:param OrganizationId: The ID of the organization.
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call.)
:type Limit: integer
:param Limit: The maximum number of items to return with this call.
:rtype: dict
ReturnsResponse Syntax
{
'Groups': [
{
'Id': 'string',
'Name': 'string'
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Groups (list) --
The list of groups.
(dict) --
Describes the metadata of a user group.
Id (string) --
The ID of the user group.
Name (string) --
The name of the group.
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Groups': [
{
'Id': 'string',
'Name': 'string'
},
],
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_notification_subscriptions(OrganizationId=None, Marker=None, Limit=None):
"""
Lists the specified notification subscriptions.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_notification_subscriptions(
OrganizationId='string',
Marker='string',
Limit=123
)
:type OrganizationId: string
:param OrganizationId: [REQUIRED]\nThe ID of the organization.\n
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call.)
:type Limit: integer
:param Limit: The maximum number of items to return with this call.
:rtype: dict
ReturnsResponse Syntax
{
'Subscriptions': [
{
'SubscriptionId': 'string',
'EndPoint': 'string',
'Protocol': 'HTTPS'
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Subscriptions (list) --
The subscriptions.
(dict) --
Describes a subscription.
SubscriptionId (string) --
The ID of the subscription.
EndPoint (string) --
The endpoint of the subscription.
Protocol (string) --
The protocol of the subscription.
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Subscriptions': [
{
'SubscriptionId': 'string',
'EndPoint': 'string',
'Protocol': 'HTTPS'
},
],
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_resource_permissions(AuthenticationToken=None, ResourceId=None, PrincipalId=None, Limit=None, Marker=None):
"""
Describes the permissions of a specified resource.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_resource_permissions(
AuthenticationToken='string',
ResourceId='string',
PrincipalId='string',
Limit=123,
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type PrincipalId: string
:param PrincipalId: The ID of the principal to filter permissions by.
:type Limit: integer
:param Limit: The maximum number of items to return with this call.
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call)
:rtype: dict
ReturnsResponse Syntax
{
'Principals': [
{
'Id': 'string',
'Type': 'USER'|'GROUP'|'INVITE'|'ANONYMOUS'|'ORGANIZATION',
'Roles': [
{
'Role': 'VIEWER'|'CONTRIBUTOR'|'OWNER'|'COOWNER',
'Type': 'DIRECT'|'INHERITED'
},
]
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Principals (list) --
The principals.
(dict) --
Describes a resource.
Id (string) --
The ID of the resource.
Type (string) --
The type of resource.
Roles (list) --
The permission information for the resource.
(dict) --
Describes the permissions.
Role (string) --
The role of the user.
Type (string) --
The type of permissions.
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Principals': [
{
'Id': 'string',
'Type': 'USER'|'GROUP'|'INVITE'|'ANONYMOUS'|'ORGANIZATION',
'Roles': [
{
'Role': 'VIEWER'|'CONTRIBUTOR'|'OWNER'|'COOWNER',
'Type': 'DIRECT'|'INHERITED'
},
]
},
],
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def describe_root_folders(AuthenticationToken=None, Limit=None, Marker=None):
"""
Describes the current user\'s special folders; the RootFolder and the RecycleBin . RootFolder is the root of user\'s files and folders and RecycleBin is the root of recycled items. This is not a valid action for SigV4 (administrative API) clients.
This action requires an authentication token. To get an authentication token, register an application with Amazon WorkDocs. For more information, see Authentication and Access Control for User Applications in the Amazon WorkDocs Developer Guide .
See also: AWS API Documentation
Exceptions
:example: response = client.describe_root_folders(
AuthenticationToken='string',
Limit=123,
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: [REQUIRED]\nAmazon WorkDocs authentication token.\n
:type Limit: integer
:param Limit: The maximum number of items to return.
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call.)
:rtype: dict
ReturnsResponse Syntax
{
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Folders (list) --
The user\'s special folders.
(dict) --
Describes a folder.
Id (string) --
The ID of the folder.
Name (string) --
The name of the folder.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the folder was created.
ModifiedTimestamp (datetime) --
The time when the folder was updated.
ResourceState (string) --
The resource state of the folder.
Signature (string) --
The unique identifier created from the subfolders and documents of the folder.
Labels (list) --
List of labels on the folder.
(string) --
Size (integer) --
The size of the folder metadata.
LatestVersionSize (integer) --
The size of the latest version of the folder metadata.
Marker (string) --
The marker for the next set of results.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Marker': 'string'
}
:returns:
(string) --
"""
pass
def describe_users(AuthenticationToken=None, OrganizationId=None, UserIds=None, Query=None, Include=None, Order=None, Sort=None, Marker=None, Limit=None, Fields=None):
"""
Describes the specified users. You can describe all users or filter the results (for example, by status or organization).
By default, Amazon WorkDocs returns the first 24 active or pending users. If there are more results, the response includes a marker that you can use to request the next set of results.
See also: AWS API Documentation
Exceptions
:example: response = client.describe_users(
AuthenticationToken='string',
OrganizationId='string',
UserIds='string',
Query='string',
Include='ALL'|'ACTIVE_PENDING',
Order='ASCENDING'|'DESCENDING',
Sort='USER_NAME'|'FULL_NAME'|'STORAGE_LIMIT'|'USER_STATUS'|'STORAGE_USED',
Marker='string',
Limit=123,
Fields='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type OrganizationId: string
:param OrganizationId: The ID of the organization.
:type UserIds: string
:param UserIds: The IDs of the users.
:type Query: string
:param Query: A query to filter users by user name.
:type Include: string
:param Include: The state of the users. Specify 'ALL' to include inactive users.
:type Order: string
:param Order: The order for the results.
:type Sort: string
:param Sort: The sorting criteria.
:type Marker: string
:param Marker: The marker for the next set of results. (You received this marker from a previous call.)
:type Limit: integer
:param Limit: The maximum number of items to return.
:type Fields: string
:param Fields: A comma-separated list of values. Specify 'STORAGE_METADATA' to include the user storage quota and utilization information.
:rtype: dict
ReturnsResponse Syntax
{
'Users': [
{
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
],
'TotalNumberOfUsers': 123,
'Marker': 'string'
}
Response Structure
(dict) --
Users (list) --
The users.
(dict) --
Describes a user.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
TotalNumberOfUsers (integer) --
The total number of users included in the results.
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.RequestedEntityTooLargeException
:return: {
'Users': [
{
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
},
],
'TotalNumberOfUsers': 123,
'Marker': 'string'
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.RequestedEntityTooLargeException
"""
pass
def generate_presigned_url(ClientMethod=None, Params=None, ExpiresIn=None, HttpMethod=None):
"""
Generate a presigned url given a client, its method, and arguments
:type ClientMethod: string
:param ClientMethod: The client method to presign for
:type Params: dict
:param Params: The parameters normally passed to\nClientMethod.
:type ExpiresIn: int
:param ExpiresIn: The number of seconds the presigned url is valid\nfor. By default it expires in an hour (3600 seconds)
:type HttpMethod: string
:param HttpMethod: The http method to use on the generated url. By\ndefault, the http method is whatever is used in the method\'s model.
"""
pass
def get_current_user(AuthenticationToken=None):
"""
Retrieves details of the current user for whom the authentication token was generated. This is not a valid action for SigV4 (administrative API) clients.
This action requires an authentication token. To get an authentication token, register an application with Amazon WorkDocs. For more information, see Authentication and Access Control for User Applications in the Amazon WorkDocs Developer Guide .
See also: AWS API Documentation
Exceptions
:example: response = client.get_current_user(
AuthenticationToken='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: [REQUIRED]\nAmazon WorkDocs authentication token.\n
:rtype: dict
ReturnsResponse Syntax{
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
Response Structure
(dict) --
User (dict) --Metadata of the user.
Id (string) --The ID of the user.
Username (string) --The login name of the user.
EmailAddress (string) --The email address of the user.
GivenName (string) --The given name of the user.
Surname (string) --The surname of the user.
OrganizationId (string) --The ID of the organization.
RootFolderId (string) --The ID of the root folder.
RecycleBinFolderId (string) --The ID of the recycle bin folder.
Status (string) --The status of the user.
Type (string) --The type of user.
CreatedTimestamp (datetime) --The time when the user was created.
ModifiedTimestamp (datetime) --The time when the user was modified.
TimeZoneId (string) --The time zone ID of the user.
Locale (string) --The locale of the user.
Storage (dict) --The storage for the user.
StorageUtilizedInBytes (integer) --The amount of storage used, in bytes.
StorageRule (dict) --The storage for a user.
StorageAllocatedInBytes (integer) --The amount of storage allocated, in bytes.
StorageType (string) --The type of storage.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
"""
pass
def get_document(AuthenticationToken=None, DocumentId=None, IncludeCustomMetadata=None):
"""
Retrieves details of a document.
See also: AWS API Documentation
Exceptions
:example: response = client.get_document(
AuthenticationToken='string',
DocumentId='string',
IncludeCustomMetadata=True|False
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type IncludeCustomMetadata: boolean
:param IncludeCustomMetadata: Set this to TRUE to include custom metadata in the response.
:rtype: dict
ReturnsResponse Syntax
{
'Metadata': {
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
'CustomMetadata': {
'string': 'string'
}
}
Response Structure
(dict) --
Metadata (dict) --
The metadata details of the document.
Id (string) --
The ID of the document.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the document was created.
ModifiedTimestamp (datetime) --
The time when the document was updated.
LatestVersionMetadata (dict) --
The latest version of the document.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
ResourceState (string) --
The resource state.
Labels (list) --
List of labels on the document.
(string) --
CustomMetadata (dict) --
The custom metadata on the document.
(string) --
(string) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.InvalidPasswordException
:return: {
'Metadata': {
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
'CustomMetadata': {
'string': 'string'
}
}
:returns:
(string) --
(string) --
"""
pass
def get_document_path(AuthenticationToken=None, DocumentId=None, Limit=None, Fields=None, Marker=None):
"""
Retrieves the path information (the hierarchy from the root folder) for the requested document.
By default, Amazon WorkDocs returns a maximum of 100 levels upwards from the requested document and only includes the IDs of the parent folders in the path. You can limit the maximum number of levels. You can also request the names of the parent folders.
See also: AWS API Documentation
Exceptions
:example: response = client.get_document_path(
AuthenticationToken='string',
DocumentId='string',
Limit=123,
Fields='string',
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type Limit: integer
:param Limit: The maximum number of levels in the hierarchy to return.
:type Fields: string
:param Fields: A comma-separated list of values. Specify NAME to include the names of the parent folders.
:type Marker: string
:param Marker: This value is not supported.
:rtype: dict
ReturnsResponse Syntax
{
'Path': {
'Components': [
{
'Id': 'string',
'Name': 'string'
},
]
}
}
Response Structure
(dict) --
Path (dict) --
The path information.
Components (list) --
The components of the resource path.
(dict) --
Describes the resource path.
Id (string) --
The ID of the resource path.
Name (string) --
The name of the resource path.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Path': {
'Components': [
{
'Id': 'string',
'Name': 'string'
},
]
}
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def get_document_version(AuthenticationToken=None, DocumentId=None, VersionId=None, Fields=None, IncludeCustomMetadata=None):
"""
Retrieves version metadata for the specified document.
See also: AWS API Documentation
Exceptions
:example: response = client.get_document_version(
AuthenticationToken='string',
DocumentId='string',
VersionId='string',
Fields='string',
IncludeCustomMetadata=True|False
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe version ID of the document.\n
:type Fields: string
:param Fields: A comma-separated list of values. Specify 'SOURCE' to include a URL for the source document.
:type IncludeCustomMetadata: boolean
:param IncludeCustomMetadata: Set this to TRUE to include custom metadata in the response.
:rtype: dict
ReturnsResponse Syntax
{
'Metadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'CustomMetadata': {
'string': 'string'
}
}
Response Structure
(dict) --
Metadata (dict) --
The version metadata.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
CustomMetadata (dict) --
The custom metadata on the document version.
(string) --
(string) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.InvalidPasswordException
:return: {
'Metadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'CustomMetadata': {
'string': 'string'
}
}
:returns:
(string) --
(string) --
"""
pass
def get_folder(AuthenticationToken=None, FolderId=None, IncludeCustomMetadata=None):
"""
Retrieves the metadata of the specified folder.
See also: AWS API Documentation
Exceptions
:example: response = client.get_folder(
AuthenticationToken='string',
FolderId='string',
IncludeCustomMetadata=True|False
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:type IncludeCustomMetadata: boolean
:param IncludeCustomMetadata: Set to TRUE to include custom metadata in the response.
:rtype: dict
ReturnsResponse Syntax
{
'Metadata': {
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
'CustomMetadata': {
'string': 'string'
}
}
Response Structure
(dict) --
Metadata (dict) --
The metadata of the folder.
Id (string) --
The ID of the folder.
Name (string) --
The name of the folder.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the folder was created.
ModifiedTimestamp (datetime) --
The time when the folder was updated.
ResourceState (string) --
The resource state of the folder.
Signature (string) --
The unique identifier created from the subfolders and documents of the folder.
Labels (list) --
List of labels on the folder.
(string) --
Size (integer) --
The size of the folder metadata.
LatestVersionSize (integer) --
The size of the latest version of the folder metadata.
CustomMetadata (dict) --
The custom metadata on the folder.
(string) --
(string) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.ProhibitedStateException
:return: {
'Metadata': {
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
'CustomMetadata': {
'string': 'string'
}
}
:returns:
(string) --
"""
pass
def get_folder_path(AuthenticationToken=None, FolderId=None, Limit=None, Fields=None, Marker=None):
"""
Retrieves the path information (the hierarchy from the root folder) for the specified folder.
By default, Amazon WorkDocs returns a maximum of 100 levels upwards from the requested folder and only includes the IDs of the parent folders in the path. You can limit the maximum number of levels. You can also request the parent folder names.
See also: AWS API Documentation
Exceptions
:example: response = client.get_folder_path(
AuthenticationToken='string',
FolderId='string',
Limit=123,
Fields='string',
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:type Limit: integer
:param Limit: The maximum number of levels in the hierarchy to return.
:type Fields: string
:param Fields: A comma-separated list of values. Specify 'NAME' to include the names of the parent folders.
:type Marker: string
:param Marker: This value is not supported.
:rtype: dict
ReturnsResponse Syntax
{
'Path': {
'Components': [
{
'Id': 'string',
'Name': 'string'
},
]
}
}
Response Structure
(dict) --
Path (dict) --
The path information.
Components (list) --
The components of the resource path.
(dict) --
Describes the resource path.
Id (string) --
The ID of the resource path.
Name (string) --
The name of the resource path.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Path': {
'Components': [
{
'Id': 'string',
'Name': 'string'
},
]
}
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def get_paginator(operation_name=None):
"""
Create a paginator for an operation.
:type operation_name: string
:param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo').
:rtype: L{botocore.paginate.Paginator}
ReturnsA paginator object.
"""
pass
def get_resources(AuthenticationToken=None, UserId=None, CollectionType=None, Limit=None, Marker=None):
"""
Retrieves a collection of resources, including folders and documents. The only CollectionType supported is SHARED_WITH_ME .
See also: AWS API Documentation
Exceptions
:example: response = client.get_resources(
AuthenticationToken='string',
UserId='string',
CollectionType='SHARED_WITH_ME',
Limit=123,
Marker='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: The Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type UserId: string
:param UserId: The user ID for the resource collection. This is a required field for accessing the API operation using IAM credentials.
:type CollectionType: string
:param CollectionType: The collection type.
:type Limit: integer
:param Limit: The maximum number of resources to return.
:type Marker: string
:param Marker: The marker for the next set of results. This marker was received from a previous call.
:rtype: dict
ReturnsResponse Syntax
{
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Documents': [
{
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
],
'Marker': 'string'
}
Response Structure
(dict) --
Folders (list) --
The folders in the specified folder.
(dict) --
Describes a folder.
Id (string) --
The ID of the folder.
Name (string) --
The name of the folder.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the folder was created.
ModifiedTimestamp (datetime) --
The time when the folder was updated.
ResourceState (string) --
The resource state of the folder.
Signature (string) --
The unique identifier created from the subfolders and documents of the folder.
Labels (list) --
List of labels on the folder.
(string) --
Size (integer) --
The size of the folder metadata.
LatestVersionSize (integer) --
The size of the latest version of the folder metadata.
Documents (list) --
The documents in the specified collection.
(dict) --
Describes the document.
Id (string) --
The ID of the document.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the document was created.
ModifiedTimestamp (datetime) --
The time when the document was updated.
LatestVersionMetadata (dict) --
The latest version of the document.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
ResourceState (string) --
The resource state.
Labels (list) --
List of labels on the document.
(string) --
Marker (string) --
The marker to use when requesting the next set of results. If there are no additional results, the string is empty.
Exceptions
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.InvalidArgumentException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
:return: {
'Folders': [
{
'Id': 'string',
'Name': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Signature': 'string',
'Labels': [
'string',
],
'Size': 123,
'LatestVersionSize': 123
},
],
'Documents': [
{
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
],
'Marker': 'string'
}
:returns:
(string) --
"""
pass
def get_waiter(waiter_name=None):
"""
Returns an object that can wait for some condition.
:type waiter_name: str
:param waiter_name: The name of the waiter to get. See the waiters\nsection of the service docs for a list of available waiters.
:rtype: botocore.waiter.Waiter
"""
pass
def initiate_document_version_upload(AuthenticationToken=None, Id=None, Name=None, ContentCreatedTimestamp=None, ContentModifiedTimestamp=None, ContentType=None, DocumentSizeInBytes=None, ParentFolderId=None):
"""
Creates a new document object and version object.
The client specifies the parent folder ID and name of the document to upload. The ID is optionally specified when creating a new version of an existing document. This is the first step to upload a document. Next, upload the document to the URL returned from the call, and then call UpdateDocumentVersion .
To cancel the document upload, call AbortDocumentVersionUpload .
See also: AWS API Documentation
Exceptions
:example: response = client.initiate_document_version_upload(
AuthenticationToken='string',
Id='string',
Name='string',
ContentCreatedTimestamp=datetime(2015, 1, 1),
ContentModifiedTimestamp=datetime(2015, 1, 1),
ContentType='string',
DocumentSizeInBytes=123,
ParentFolderId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type Id: string
:param Id: The ID of the document.
:type Name: string
:param Name: The name of the document.
:type ContentCreatedTimestamp: datetime
:param ContentCreatedTimestamp: The timestamp when the content of the document was originally created.
:type ContentModifiedTimestamp: datetime
:param ContentModifiedTimestamp: The timestamp when the content of the document was modified.
:type ContentType: string
:param ContentType: The content type of the document.
:type DocumentSizeInBytes: integer
:param DocumentSizeInBytes: The size of the document, in bytes.
:type ParentFolderId: string
:param ParentFolderId: [REQUIRED]\nThe ID of the parent folder.\n
:rtype: dict
ReturnsResponse Syntax
{
'Metadata': {
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
'UploadMetadata': {
'UploadUrl': 'string',
'SignedHeaders': {
'string': 'string'
}
}
}
Response Structure
(dict) --
Metadata (dict) --
The document metadata.
Id (string) --
The ID of the document.
CreatorId (string) --
The ID of the creator.
ParentFolderId (string) --
The ID of the parent folder.
CreatedTimestamp (datetime) --
The time when the document was created.
ModifiedTimestamp (datetime) --
The time when the document was updated.
LatestVersionMetadata (dict) --
The latest version of the document.
Id (string) --
The ID of the version.
Name (string) --
The name of the version.
ContentType (string) --
The content type of the document.
Size (integer) --
The size of the document, in bytes.
Signature (string) --
The signature of the document.
Status (string) --
The status of the document.
CreatedTimestamp (datetime) --
The timestamp when the document was first uploaded.
ModifiedTimestamp (datetime) --
The timestamp when the document was last uploaded.
ContentCreatedTimestamp (datetime) --
The timestamp when the content of the document was originally created.
ContentModifiedTimestamp (datetime) --
The timestamp when the content of the document was modified.
CreatorId (string) --
The ID of the creator.
Thumbnail (dict) --
The thumbnail of the document.
(string) --
(string) --
Source (dict) --
The source of the document.
(string) --
(string) --
ResourceState (string) --
The resource state.
Labels (list) --
List of labels on the document.
(string) --
UploadMetadata (dict) --
The upload metadata.
UploadUrl (string) --
The URL of the upload.
SignedHeaders (dict) --
The signed headers.
(string) --
(string) --
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.StorageLimitExceededException
WorkDocs.Client.exceptions.StorageLimitWillExceedException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DraftUploadOutOfSyncException
WorkDocs.Client.exceptions.ResourceAlreadyCheckedOutException
:return: {
'Metadata': {
'Id': 'string',
'CreatorId': 'string',
'ParentFolderId': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'LatestVersionMetadata': {
'Id': 'string',
'Name': 'string',
'ContentType': 'string',
'Size': 123,
'Signature': 'string',
'Status': 'INITIALIZED'|'ACTIVE',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'ContentCreatedTimestamp': datetime(2015, 1, 1),
'ContentModifiedTimestamp': datetime(2015, 1, 1),
'CreatorId': 'string',
'Thumbnail': {
'string': 'string'
},
'Source': {
'string': 'string'
}
},
'ResourceState': 'ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED',
'Labels': [
'string',
]
},
'UploadMetadata': {
'UploadUrl': 'string',
'SignedHeaders': {
'string': 'string'
}
}
}
:returns:
(string) --
(string) --
"""
pass
def remove_all_resource_permissions(AuthenticationToken=None, ResourceId=None):
"""
Removes all the permissions from the specified resource.
See also: AWS API Documentation
Exceptions
:example: response = client.remove_all_resource_permissions(
AuthenticationToken='string',
ResourceId='string'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def remove_resource_permission(AuthenticationToken=None, ResourceId=None, PrincipalId=None, PrincipalType=None):
"""
Removes the permission for the specified principal from the specified resource.
See also: AWS API Documentation
Exceptions
:example: response = client.remove_resource_permission(
AuthenticationToken='string',
ResourceId='string',
PrincipalId='string',
PrincipalType='USER'|'GROUP'|'INVITE'|'ANONYMOUS'|'ORGANIZATION'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type ResourceId: string
:param ResourceId: [REQUIRED]\nThe ID of the resource.\n
:type PrincipalId: string
:param PrincipalId: [REQUIRED]\nThe principal ID of the resource.\n
:type PrincipalType: string
:param PrincipalType: The principal type of the resource.
:returns:
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def update_document(AuthenticationToken=None, DocumentId=None, Name=None, ParentFolderId=None, ResourceState=None):
"""
Updates the specified attributes of a document. The user must have access to both the document and its parent folder, if applicable.
See also: AWS API Documentation
Exceptions
:example: response = client.update_document(
AuthenticationToken='string',
DocumentId='string',
Name='string',
ParentFolderId='string',
ResourceState='ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type Name: string
:param Name: The name of the document.
:type ParentFolderId: string
:param ParentFolderId: The ID of the parent folder.
:type ResourceState: string
:param ResourceState: The resource state of the document. Only ACTIVE and RECYCLED are supported.
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.LimitExceededException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.ConcurrentModificationException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def update_document_version(AuthenticationToken=None, DocumentId=None, VersionId=None, VersionStatus=None):
"""
Changes the status of the document version to ACTIVE.
Amazon WorkDocs also sets its document container to ACTIVE. This is the last step in a document upload, after the client uploads the document to an S3-presigned URL returned by InitiateDocumentVersionUpload .
See also: AWS API Documentation
Exceptions
:example: response = client.update_document_version(
AuthenticationToken='string',
DocumentId='string',
VersionId='string',
VersionStatus='ACTIVE'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type DocumentId: string
:param DocumentId: [REQUIRED]\nThe ID of the document.\n
:type VersionId: string
:param VersionId: [REQUIRED]\nThe version ID of the document.\n
:type VersionStatus: string
:param VersionStatus: The status of the version.
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConcurrentModificationException
WorkDocs.Client.exceptions.InvalidOperationException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def update_folder(AuthenticationToken=None, FolderId=None, Name=None, ParentFolderId=None, ResourceState=None):
"""
Updates the specified attributes of the specified folder. The user must have access to both the folder and its parent folder, if applicable.
See also: AWS API Documentation
Exceptions
:example: response = client.update_folder(
AuthenticationToken='string',
FolderId='string',
Name='string',
ParentFolderId='string',
ResourceState='ACTIVE'|'RESTORING'|'RECYCLING'|'RECYCLED'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type FolderId: string
:param FolderId: [REQUIRED]\nThe ID of the folder.\n
:type Name: string
:param Name: The name of the folder.
:type ParentFolderId: string
:param ParentFolderId: The ID of the parent folder.
:type ResourceState: string
:param ResourceState: The resource state of the folder. Only ACTIVE and RECYCLED are accepted values from the API.
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.EntityAlreadyExistsException
WorkDocs.Client.exceptions.ProhibitedStateException
WorkDocs.Client.exceptions.ConflictingOperationException
WorkDocs.Client.exceptions.ConcurrentModificationException
WorkDocs.Client.exceptions.LimitExceededException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
"""
pass
def update_user(AuthenticationToken=None, UserId=None, GivenName=None, Surname=None, Type=None, StorageRule=None, TimeZoneId=None, Locale=None, GrantPoweruserPrivileges=None):
"""
Updates the specified attributes of the specified user, and grants or revokes administrative privileges to the Amazon WorkDocs site.
See also: AWS API Documentation
Exceptions
:example: response = client.update_user(
AuthenticationToken='string',
UserId='string',
GivenName='string',
Surname='string',
Type='USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
StorageRule={
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
},
TimeZoneId='string',
Locale='en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
GrantPoweruserPrivileges='TRUE'|'FALSE'
)
:type AuthenticationToken: string
:param AuthenticationToken: Amazon WorkDocs authentication token. Not required when using AWS administrator credentials to access the API.
:type UserId: string
:param UserId: [REQUIRED]\nThe ID of the user.\n
:type GivenName: string
:param GivenName: The given name of the user.
:type Surname: string
:param Surname: The surname of the user.
:type Type: string
:param Type: The type of the user.
:type StorageRule: dict
:param StorageRule: The amount of storage for the user.\n\nStorageAllocatedInBytes (integer) --The amount of storage allocated, in bytes.\n\nStorageType (string) --The type of storage.\n\n\n
:type TimeZoneId: string
:param TimeZoneId: The time zone ID of the user.
:type Locale: string
:param Locale: The locale of the user.
:type GrantPoweruserPrivileges: string
:param GrantPoweruserPrivileges: Boolean value to determine whether the user is granted Poweruser privileges.
:rtype: dict
ReturnsResponse Syntax
{
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
Response Structure
(dict) --
User (dict) --
The user information.
Id (string) --
The ID of the user.
Username (string) --
The login name of the user.
EmailAddress (string) --
The email address of the user.
GivenName (string) --
The given name of the user.
Surname (string) --
The surname of the user.
OrganizationId (string) --
The ID of the organization.
RootFolderId (string) --
The ID of the root folder.
RecycleBinFolderId (string) --
The ID of the recycle bin folder.
Status (string) --
The status of the user.
Type (string) --
The type of user.
CreatedTimestamp (datetime) --
The time when the user was created.
ModifiedTimestamp (datetime) --
The time when the user was modified.
TimeZoneId (string) --
The time zone ID of the user.
Locale (string) --
The locale of the user.
Storage (dict) --
The storage for the user.
StorageUtilizedInBytes (integer) --
The amount of storage used, in bytes.
StorageRule (dict) --
The storage for a user.
StorageAllocatedInBytes (integer) --
The amount of storage allocated, in bytes.
StorageType (string) --
The type of storage.
Exceptions
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.IllegalUserStateException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DeactivatingLastSystemUserException
WorkDocs.Client.exceptions.InvalidArgumentException
:return: {
'User': {
'Id': 'string',
'Username': 'string',
'EmailAddress': 'string',
'GivenName': 'string',
'Surname': 'string',
'OrganizationId': 'string',
'RootFolderId': 'string',
'RecycleBinFolderId': 'string',
'Status': 'ACTIVE'|'INACTIVE'|'PENDING',
'Type': 'USER'|'ADMIN'|'POWERUSER'|'MINIMALUSER'|'WORKSPACESUSER',
'CreatedTimestamp': datetime(2015, 1, 1),
'ModifiedTimestamp': datetime(2015, 1, 1),
'TimeZoneId': 'string',
'Locale': 'en'|'fr'|'ko'|'de'|'es'|'ja'|'ru'|'zh_CN'|'zh_TW'|'pt_BR'|'default',
'Storage': {
'StorageUtilizedInBytes': 123,
'StorageRule': {
'StorageAllocatedInBytes': 123,
'StorageType': 'UNLIMITED'|'QUOTA'
}
}
}
}
:returns:
WorkDocs.Client.exceptions.EntityNotExistsException
WorkDocs.Client.exceptions.UnauthorizedOperationException
WorkDocs.Client.exceptions.UnauthorizedResourceAccessException
WorkDocs.Client.exceptions.IllegalUserStateException
WorkDocs.Client.exceptions.FailedDependencyException
WorkDocs.Client.exceptions.ServiceUnavailableException
WorkDocs.Client.exceptions.DeactivatingLastSystemUserException
WorkDocs.Client.exceptions.InvalidArgumentException
"""
pass
| 27.063665
| 850
| 0.641861
| 14,293
| 146,658
| 6.562163
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| 0
| 0
| 0
|
0
| 9
|
8d6ba5f1dce0838ec5d1f09ee0e22db11a23f622
| 3,507
|
py
|
Python
|
home/migrations/0021_auto_20210201_1434.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 4
|
2019-03-28T06:42:17.000Z
|
2021-06-06T13:10:51.000Z
|
home/migrations/0021_auto_20210201_1434.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 177
|
2018-09-28T14:21:56.000Z
|
2022-03-30T21:45:26.000Z
|
home/migrations/0021_auto_20210201_1434.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 8
|
2018-10-25T20:43:10.000Z
|
2022-03-17T14:19:27.000Z
|
# Generated by Django 2.2.13 on 2021-02-01 14:34
from django.db import migrations
import wagtail.core.blocks
import wagtail.core.fields
import wagtail.images.blocks
class Migration(migrations.Migration):
dependencies = [
('home', '0020_spamsettings'),
]
operations = [
migrations.AddField(
model_name='homepage',
name='flexible_features',
field=wagtail.core.fields.StreamField([('feature', wagtail.core.blocks.StructBlock([('title', wagtail.core.blocks.CharBlock(classname='title', help_text='Feature title.', icon='title')), ('description', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock(required=False)), ('button_text', wagtail.core.blocks.CharBlock(help_text='Button text.', required=False)), ('button_url', wagtail.core.blocks.URLBlock(help_text='Button URL.', required=False))]))], blank=True, null=True),
),
migrations.AddField(
model_name='homepage',
name='flexible_features_en',
field=wagtail.core.fields.StreamField([('feature', wagtail.core.blocks.StructBlock([('title', wagtail.core.blocks.CharBlock(classname='title', help_text='Feature title.', icon='title')), ('description', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock(required=False)), ('button_text', wagtail.core.blocks.CharBlock(help_text='Button text.', required=False)), ('button_url', wagtail.core.blocks.URLBlock(help_text='Button URL.', required=False))]))], blank=True, null=True),
),
migrations.AddField(
model_name='homepage',
name='flexible_features_es',
field=wagtail.core.fields.StreamField([('feature', wagtail.core.blocks.StructBlock([('title', wagtail.core.blocks.CharBlock(classname='title', help_text='Feature title.', icon='title')), ('description', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock(required=False)), ('button_text', wagtail.core.blocks.CharBlock(help_text='Button text.', required=False)), ('button_url', wagtail.core.blocks.URLBlock(help_text='Button URL.', required=False))]))], blank=True, null=True),
),
migrations.AddField(
model_name='homepage',
name='flexible_features_fr',
field=wagtail.core.fields.StreamField([('feature', wagtail.core.blocks.StructBlock([('title', wagtail.core.blocks.CharBlock(classname='title', help_text='Feature title.', icon='title')), ('description', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock(required=False)), ('button_text', wagtail.core.blocks.CharBlock(help_text='Button text.', required=False)), ('button_url', wagtail.core.blocks.URLBlock(help_text='Button URL.', required=False))]))], blank=True, null=True),
),
migrations.AddField(
model_name='homepage',
name='flexible_features_pt',
field=wagtail.core.fields.StreamField([('feature', wagtail.core.blocks.StructBlock([('title', wagtail.core.blocks.CharBlock(classname='title', help_text='Feature title.', icon='title')), ('description', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock(required=False)), ('button_text', wagtail.core.blocks.CharBlock(help_text='Button text.', required=False)), ('button_url', wagtail.core.blocks.URLBlock(help_text='Button URL.', required=False))]))], blank=True, null=True),
),
]
| 83.5
| 525
| 0.700599
| 397
| 3,507
| 6.088161
| 0.148615
| 0.145635
| 0.182871
| 0.107571
| 0.910219
| 0.910219
| 0.910219
| 0.910219
| 0.887464
| 0.887464
| 0
| 0.006519
| 0.125178
| 3,507
| 41
| 526
| 85.536585
| 0.781291
| 0.013117
| 0
| 0.571429
| 1
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| 0.184446
| 0
| 0
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| 0
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| false
| 0
| 0.114286
| 0
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| null | 0
| 1
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| 1
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| null | 0
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| 0
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| 0
| 0
| 0
|
0
| 8
|
570555c9b7f1f393fa51618470d4c1fd0a9626b9
| 68,648
|
py
|
Python
|
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_pinned/cmp_gobmk/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_pinned/cmp_gobmk/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_pinned/cmp_gobmk/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
power = {'BUSES': {'Area': 1.33155,
'Bus/Area': 1.33155,
'Bus/Gate Leakage': 0.00662954,
'Bus/Peak Dynamic': 0.0,
'Bus/Runtime Dynamic': 0.0,
'Bus/Subthreshold Leakage': 0.0691322,
'Bus/Subthreshold Leakage with power gating': 0.0259246,
'Gate Leakage': 0.00662954,
'Peak Dynamic': 0.0,
'Runtime Dynamic': 0.0,
'Subthreshold Leakage': 0.0691322,
'Subthreshold Leakage with power gating': 0.0259246},
'Core': [{'Area': 32.6082,
'Execution Unit/Area': 8.2042,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 1.88938e-06,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.20269,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 3.03604e-05,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.122718,
'Execution Unit/Instruction Scheduler/Area': 2.17927,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.3257,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.563995,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.323467,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 1.21316,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.321937,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.50532,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 5.73574e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0118069,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0853788,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0873192,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0853846,
'Execution Unit/Register Files/Runtime Dynamic': 0.0991261,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.206311,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.553835,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155,
'Execution Unit/Runtime Dynamic': 2.47419,
'Execution Unit/Subthreshold Leakage': 1.83518,
'Execution Unit/Subthreshold Leakage with power gating': 0.709678,
'Gate Leakage': 0.372997,
'Instruction Fetch Unit/Area': 5.86007,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00309226,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00309226,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00274233,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.00108839,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00125435,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.0101812,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0278984,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0590479,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0839422,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.33945,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.267377,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.285106,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.82106,
'Instruction Fetch Unit/Runtime Dynamic': 0.674505,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932587,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0505317,
'L2/Runtime Dynamic': 0.0135391,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80969,
'Load Store Unit/Data Cache/Area': 6.84535,
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'Load Store Unit/Data Cache/Peak Dynamic': 3.4972,
'Load Store Unit/Data Cache/Runtime Dynamic': 1.10569,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0351387,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0731189,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0731189,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.84389,
'Load Store Unit/Runtime Dynamic': 1.53941,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
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'Load Store Unit/StoreQ/Runtime Dynamic': 0.360597,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591622,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283406,
'Memory Management Unit/Area': 0.434579,
'Memory Management Unit/Dtlb/Area': 0.0879726,
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'Memory Management Unit/Dtlb/Peak Dynamic': 0.0639887,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0644165,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00813591,
'Memory Management Unit/Itlb/Area': 0.301552,
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'Memory Management Unit/Peak Dynamic': 0.60111,
'Memory Management Unit/Runtime Dynamic': 0.10923,
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'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462,
'Peak Dynamic': 22.3836,
'Renaming Unit/Area': 0.369768,
'Renaming Unit/FP Front End RAT/Area': 0.168486,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731,
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'Renaming Unit/FP Front End RAT/Runtime Dynamic': 2.00155e-05,
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'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925,
'Renaming Unit/Free List/Area': 0.0414755,
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'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987,
'Renaming Unit/Gate Leakage': 0.00863632,
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'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.17093,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781,
'Renaming Unit/Peak Dynamic': 4.56169,
'Renaming Unit/Runtime Dynamic': 0.187605,
'Renaming Unit/Subthreshold Leakage': 0.070483,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779,
'Runtime Dynamic': 4.99848,
'Subthreshold Leakage': 6.21877,
'Subthreshold Leakage with power gating': 2.58311},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 9.4469e-07,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.20269,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 2.02403e-05,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.187504,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.302436,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.15266,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.6426,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.214446,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.24255,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 3.82383e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00786475,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0568717,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0581646,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0568755,
'Execution Unit/Register Files/Runtime Dynamic': 0.0660294,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.119813,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.321632,
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'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.63833,
'Execution Unit/Subthreshold Leakage': 1.79543,
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'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00218605,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00218605,
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'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00197094,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000799573,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000835539,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00717857,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0185694,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0559151,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.55668,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.17826,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.189913,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.94781,
'Instruction Fetch Unit/Runtime Dynamic': 0.449836,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0335487,
'L2/Runtime Dynamic': 0.0089839,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.74279,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.736561,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.048712,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0487119,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 2.97282,
'Load Store Unit/Runtime Dynamic': 1.0255,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.120115,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.240231,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
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'Memory Management Unit/Dtlb/Peak Dynamic': 0.0426294,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0429123,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
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'Memory Management Unit/Peak Dynamic': 0.45048,
'Memory Management Unit/Runtime Dynamic': 0.0727895,
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'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 17.2367,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 9.80115e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
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'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.00845977,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
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'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
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'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.104782,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.30022,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
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'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
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'Execution Unit/Complex ALUs/Peak Dynamic': 9.4469e-07,
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'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
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'Execution Unit/Floating Point Units/Area': 4.6585,
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'Execution Unit/Floating Point Units/Peak Dynamic': 2.02403e-05,
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'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.187513,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.302452,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.152667,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.642632,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.214458,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.24257,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 3.82383e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00786514,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0568748,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0581675,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0568786,
'Execution Unit/Register Files/Runtime Dynamic': 0.0660327,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.119819,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.321648,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.63838,
'Execution Unit/Subthreshold Leakage': 1.79543,
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'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00218616,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00218616,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00197105,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000799617,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000835581,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00717896,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0185704,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0559179,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.55686,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.17827,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.189922,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.948,
'Instruction Fetch Unit/Runtime Dynamic': 0.44986,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0335487,
'L2/Runtime Dynamic': 0.00898508,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.74287,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.736603,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0487145,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0487146,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 2.97291,
'Load Store Unit/Runtime Dynamic': 1.02556,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.120122,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.240244,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0426316,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0429147,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.221153,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0298789,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.450495,
'Memory Management Unit/Runtime Dynamic': 0.0727936,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 17.237,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 9.80115e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.00846019,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0963174,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.104787,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.30037,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 9.4469e-07,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.20269,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 2.02403e-05,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.187525,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.302471,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.152677,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.642673,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.214472,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.2426,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 3.82383e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00786564,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0568785,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0581712,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0568823,
'Execution Unit/Register Files/Runtime Dynamic': 0.0660369,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.119827,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.321667,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.63844,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00218632,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00218632,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00197119,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000799674,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000835634,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00717947,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0185717,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0559215,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.55709,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.178281,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.189935,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.94824,
'Instruction Fetch Unit/Runtime Dynamic': 0.449888,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0335487,
'L2/Runtime Dynamic': 0.00898409,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.74294,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.736636,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.048717,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.048717,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 2.973,
'Load Store Unit/Runtime Dynamic': 1.02561,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.120128,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.240255,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0426337,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0429167,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.221167,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0298807,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.450513,
'Memory Management Unit/Runtime Dynamic': 0.0727974,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 17.2374,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 9.80115e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.00846073,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0963235,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.104794,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.30052,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328}],
'DRAM': {'Area': 0,
'Gate Leakage': 0,
'Peak Dynamic': 0.22089883829319112,
'Runtime Dynamic': 0.22089883829319112,
'Subthreshold Leakage': 4.252,
'Subthreshold Leakage with power gating': 4.252},
'L3': [{'Area': 61.9075,
'Gate Leakage': 0.0484137,
'Peak Dynamic': 0.10377,
'Runtime Dynamic': 0.0655018,
'Subthreshold Leakage': 6.80085,
'Subthreshold Leakage with power gating': 3.32364}],
'Processor': {'Area': 191.908,
'Gate Leakage': 1.53485,
'Peak Dynamic': 74.1984,
'Peak Power': 107.311,
'Runtime Dynamic': 14.9651,
'Subthreshold Leakage': 31.5774,
'Subthreshold Leakage with power gating': 13.9484,
'Total Cores/Area': 128.669,
'Total Cores/Gate Leakage': 1.4798,
'Total Cores/Peak Dynamic': 74.0946,
'Total Cores/Runtime Dynamic': 14.8996,
'Total Cores/Subthreshold Leakage': 24.7074,
'Total Cores/Subthreshold Leakage with power gating': 10.2429,
'Total L3s/Area': 61.9075,
'Total L3s/Gate Leakage': 0.0484137,
'Total L3s/Peak Dynamic': 0.10377,
'Total L3s/Runtime Dynamic': 0.0655018,
'Total L3s/Subthreshold Leakage': 6.80085,
'Total L3s/Subthreshold Leakage with power gating': 3.32364,
'Total Leakage': 33.1122,
'Total NoCs/Area': 1.33155,
'Total NoCs/Gate Leakage': 0.00662954,
'Total NoCs/Peak Dynamic': 0.0,
'Total NoCs/Runtime Dynamic': 0.0,
'Total NoCs/Subthreshold Leakage': 0.0691322,
'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}
| 75.107221
| 124
| 0.68203
| 8,098
| 68,648
| 5.775747
| 0.066189
| 0.123493
| 0.112888
| 0.093389
| 0.94285
| 0.93556
| 0.921577
| 0.894146
| 0.869088
| 0.849397
| 0
| 0.131983
| 0.224202
| 68,648
| 914
| 125
| 75.107221
| 0.746249
| 0
| 0
| 0.66302
| 0
| 0
| 0.657038
| 0.048071
| 0
| 0
| 0
| 0
| 0
| 1
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| false
| 0
| 0
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| null | 0
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| 1
| 1
| 1
| 1
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| 0
| 0
| 0
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| 0
| 0
| 0
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| 0
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| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
575a47ea776d19056cca0d32c70cb66e3128fa3f
| 714
|
py
|
Python
|
overseed_tests/__init__.py
|
Raihanbook/overseed
|
73d7bfdd967d4c43b88d8aadd0cd0abbbd5f2842
|
[
"MIT"
] | null | null | null |
overseed_tests/__init__.py
|
Raihanbook/overseed
|
73d7bfdd967d4c43b88d8aadd0cd0abbbd5f2842
|
[
"MIT"
] | null | null | null |
overseed_tests/__init__.py
|
Raihanbook/overseed
|
73d7bfdd967d4c43b88d8aadd0cd0abbbd5f2842
|
[
"MIT"
] | null | null | null |
import unittest
from overseed_tests.test_account_list import TestAccountList
from overseed_tests.test_assign_user import TestAssignUser
from overseed_tests.test_companies_list import TestCompaniesList
from overseed_tests.test_create_device import TestCreateDevice
from overseed_tests.test_create_plant import TestCreatePlant
from overseed_tests.test_create_user import TestCreateUser
from overseed_tests.test_devices_list import TestDevicesList
from overseed_tests.test_login import TestLogin
from overseed_tests.test_plant import TestPlant
from overseed_tests.test_plants_list import TestPlantsList
from overseed_tests.test_reset_password import TestResetPassword
if __name__ == '__main__':
unittest.main()
| 42
| 64
| 0.893557
| 93
| 714
| 6.44086
| 0.354839
| 0.220367
| 0.312187
| 0.385643
| 0.135225
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.079832
| 714
| 16
| 65
| 44.625
| 0.91172
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| 0
| 0.011204
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| true
| 0.071429
| 0.857143
| 0
| 0.857143
| 0
| 0
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| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
93e6ba943a2952e539f346e822aa7435360a6ced
| 9,514
|
py
|
Python
|
test/unit/wenet/interface/test_task_manager.py
|
Dyuko/common-models-py
|
a1d152334816ef650f01175002af0cfcdef41da5
|
[
"Apache-2.0"
] | null | null | null |
test/unit/wenet/interface/test_task_manager.py
|
Dyuko/common-models-py
|
a1d152334816ef650f01175002af0cfcdef41da5
|
[
"Apache-2.0"
] | null | null | null |
test/unit/wenet/interface/test_task_manager.py
|
Dyuko/common-models-py
|
a1d152334816ef650f01175002af0cfcdef41da5
|
[
"Apache-2.0"
] | 2
|
2022-01-12T19:38:57.000Z
|
2022-02-15T10:04:31.000Z
|
from __future__ import absolute_import, annotations
from unittest import TestCase
from unittest.mock import Mock
from test.unit.wenet.interface.mock.client import MockApikeyClient
from test.unit.wenet.interface.mock.response import MockResponse
from wenet.interface.exceptions import AuthenticationException, NotFound, CreationError
from wenet.interface.task_manager import TaskManagerInterface
from wenet.model.task.task import TaskPage, Task, TaskGoal
from wenet.model.task.transaction import TaskTransactionPage, TaskTransaction
class TestTaskManagerInterface(TestCase):
def setUp(self):
super().setUp()
self.task_manager = TaskManagerInterface(MockApikeyClient(), "")
def test_get_all_tasks(self):
response = MockResponse(TaskPage(0, 1, [Task("task_id", None, None, "", "", "app_id", None, TaskGoal("", ""))]).to_repr())
response.status_code = 200
self.task_manager._client.get = Mock(return_value=response)
self.assertEqual([Task("task_id", None, None, "", "", "app_id", None, TaskGoal("", ""))], self.task_manager.get_all_tasks(app_id="app_id"))
def test_get_all_tasks_exception(self):
response = MockResponse(None)
response.status_code = 500
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.get_all_tasks(app_id="app_id")
def test_get_all_tasks_unauthorized(self):
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.get_all_tasks(app_id="app_id")
def test_get_all_transactions(self):
response = MockResponse(TaskTransactionPage(0, 1, [TaskTransaction("transaction_id", "task_id", "", 1, 1, "", None)]).to_repr())
response.status_code = 200
self.task_manager._client.get = Mock(return_value=response)
self.assertEqual([TaskTransaction("transaction_id", "task_id", "", 1, 1, "", None)], self.task_manager.get_all_transactions(app_id="app_id"))
def test_get_all_transactions_exception(self):
response = MockResponse(None)
response.status_code = 500
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.get_all_transactions(app_id="app_id")
def test_get_all_transactions_unauthorized(self):
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.get_all_transactions(app_id="app_id")
def test_get_task(self):
response = MockResponse(Task("task_id", None, None, "", "", "app_id", None, TaskGoal("", "")).to_repr())
response.status_code = 200
self.task_manager._client.get = Mock(return_value=response)
self.assertEqual(Task.from_repr(response.json()), self.task_manager.get_task("task_id"))
def test_get_task_exception(self):
response = MockResponse(None)
response.status_code = 500
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.get_task("task_id")
def test_get_task_not_found(self):
response = MockResponse(None)
response.status_code = 404
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(NotFound):
self.task_manager.get_task("task_id")
def test_get_task_unauthorized(self):
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.get_task("task_id")
def test_get_task_page(self):
response = MockResponse(TaskPage(0, 1, [Task("task_id", None, None, "", "", "app_id", None, TaskGoal("", ""))]).to_repr())
response.status_code = 200
self.task_manager._client.get = Mock(return_value=response)
self.assertEqual(TaskPage.from_repr(response.json()), self.task_manager.get_task_page(app_id="app_id"))
def test_get_task_page_exception(self):
response = MockResponse(None)
response.status_code = 500
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.get_task_page(app_id="app_id")
def test_get_task_page_unauthorized(self):
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.get_task_page(app_id="app_id")
def test_get_transaction_page(self):
response = MockResponse(TaskTransactionPage(0, 1, [TaskTransaction("transaction_id", "task_id", "", 1, 1, "", None)]).to_repr())
response.status_code = 200
self.task_manager._client.get = Mock(return_value=response)
self.assertEqual(TaskTransactionPage.from_repr(response.json()), self.task_manager.get_transaction_page(app_id="app_id"))
def test_get_transaction_page_exception(self):
response = MockResponse(None)
response.status_code = 500
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.get_transaction_page(app_id="app_id")
def test_get_transaction_page_unauthorized(self):
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.get = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.get_transaction_page(app_id="app_id")
def test_create_task(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 200
self.task_manager._client.post = Mock(return_value=response)
self.assertIsNone(self.task_manager.create_task(task))
def test_create_task_exception(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 400
self.task_manager._client.post = Mock(return_value=response)
with self.assertRaises(CreationError):
self.task_manager.create_task(task)
def test_create_task_unauthorized(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.post = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.create_task(task)
def test_update_task(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 200
self.task_manager._client.put = Mock(return_value=response)
self.assertIsNone(self.task_manager.update_task(task))
def test_update_task_exception(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 400
self.task_manager._client.put = Mock(return_value=response)
with self.assertRaises(Exception):
self.task_manager.update_task(task)
def test_update_task_not_found(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 404
self.task_manager._client.put = Mock(return_value=response)
with self.assertRaises(NotFound):
self.task_manager.update_task(task)
def test_update_task_unauthorized(self):
task = Task("task_id", None, None, "", "", "", None, TaskGoal("", ""))
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.put = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.update_task(task)
def test_create_task_transaction(self):
transaction = TaskTransaction(None, "", "", 1, 1, "", None)
response = MockResponse(None)
response.status_code = 200
self.task_manager._client.post = Mock(return_value=response)
self.assertIsNone(self.task_manager.create_task_transaction(transaction))
def test_create_task_transaction_exception(self):
transaction = TaskTransaction(None, "", "", 1, 1, "", None)
response = MockResponse(None)
response.status_code = 400
self.task_manager._client.post = Mock(return_value=response)
with self.assertRaises(CreationError):
self.task_manager.create_task_transaction(transaction)
def test_create_task_transaction_unauthorized(self):
transaction = TaskTransaction(None, "", "", 1, 1, "", None)
response = MockResponse(None)
response.status_code = 401
self.task_manager._client.post = Mock(return_value=response)
with self.assertRaises(AuthenticationException):
self.task_manager.create_task_transaction(transaction)
| 46.866995
| 149
| 0.68888
| 1,124
| 9,514
| 5.544484
| 0.061388
| 0.077022
| 0.127567
| 0.087612
| 0.903562
| 0.898909
| 0.886072
| 0.8819
| 0.866496
| 0.846438
| 0
| 0.012785
| 0.194345
| 9,514
| 202
| 150
| 47.09901
| 0.800261
| 0
| 0
| 0.719298
| 0
| 0
| 0.027749
| 0
| 0
| 0
| 0
| 0
| 0.152047
| 1
| 0.157895
| false
| 0
| 0.052632
| 0
| 0.216374
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
f56b03275d06ed332c0f49d671788d4a175df2cf
| 149
|
py
|
Python
|
ramda/uniq_by_test.py
|
jakobkolb/ramda.py
|
982b2172f4bb95b9a5b09eff8077362d6f2f0920
|
[
"MIT"
] | 56
|
2018-08-06T08:44:58.000Z
|
2022-03-17T09:49:03.000Z
|
ramda/uniq_by_test.py
|
jakobkolb/ramda.py
|
982b2172f4bb95b9a5b09eff8077362d6f2f0920
|
[
"MIT"
] | 28
|
2019-06-17T11:09:52.000Z
|
2022-02-18T16:59:21.000Z
|
ramda/uniq_by_test.py
|
jakobkolb/ramda.py
|
982b2172f4bb95b9a5b09eff8077362d6f2f0920
|
[
"MIT"
] | 5
|
2019-09-18T09:24:38.000Z
|
2021-07-21T08:40:23.000Z
|
from ramda import *
from ramda.private.asserts import *
def uniq_by_test():
assert_equal(uniq_by(abs, [-1, -5, 2, 10, 1, 2]), [-1, -5, 2, 10])
| 21.285714
| 70
| 0.624161
| 27
| 149
| 3.296296
| 0.592593
| 0.202247
| 0.067416
| 0.11236
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098361
| 0.181208
| 149
| 6
| 71
| 24.833333
| 0.631148
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0.25
| true
| 0
| 0.5
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| 0.75
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| 0
| null | 1
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
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| 1
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
f580a4309c60840ca1f993501458f585b5d3e08c
| 5,838
|
py
|
Python
|
lambda/tests/unit/runner/test_hcaptcha.py
|
voquis/aws-lambda-contact-form-handler
|
b1ab4309137ad8225bf8ad34cf92623dbe4f6e52
|
[
"MIT"
] | null | null | null |
lambda/tests/unit/runner/test_hcaptcha.py
|
voquis/aws-lambda-contact-form-handler
|
b1ab4309137ad8225bf8ad34cf92623dbe4f6e52
|
[
"MIT"
] | 8
|
2021-12-31T13:42:23.000Z
|
2022-01-09T16:07:03.000Z
|
lambda/tests/unit/runner/test_hcaptcha.py
|
voquis/aws-lambda-contact-form-handler
|
b1ab4309137ad8225bf8ad34cf92623dbe4f6e52
|
[
"MIT"
] | null | null | null |
"""
Runner unit tests
"""
import os
import pytest
import httpretty
from app_handler.provider.request import RequestProvider
from app_handler.provider.response import ResponseProvider
from app_handler.runner.hcaptcha import HcaptchaRunner
import tests.unit.service.hcaptcha_utils as utils
def test_runner_not_enabled(monkeypatch):
"""
Test runner is not enabled.
Running should not produce any errors
"""
payload = {'version': '1.0','body': {}}
request_provider = RequestProvider(payload)
response_provider = ResponseProvider(payload)
monkeypatch.setenv('HCAPTCHA_ENABLE', '')
runner = HcaptchaRunner()
runner.configure()
assert runner.enable == False
runner.run(request_provider, response_provider)
assert not runner.error_response
def test_runner_enabled_not_configured(monkeypatch):
"""
Test enabling but not properly configuring runner.
Configuring should throw an exception.
"""
monkeypatch.setenv('HCAPTCHA_ENABLE', 'True')
monkeypatch.setenv('HCAPTCHA_SITEKEY', '')
runner = HcaptchaRunner()
with pytest.raises(ValueError) as exception:
runner.configure()
assert 'HCAPTCHA_SITEKEY' in str(exception.value)
@httpretty.activate(allow_net_connect=False)
def test_runner_enabled_and_configured_missing_field(monkeypatch):
"""
Test configured runner catches service exception correctly
Trying to POST with invalid credentials should be caught
"""
monkeypatch.setenv('HCAPTCHA_ENABLE', 'True')
monkeypatch.setenv('HCAPTCHA_SITEKEY', 'abc')
monkeypatch.setenv('HCAPTCHA_SECRET', '123')
monkeypatch.setenv('HCAPTCHA_RESPONSE_FIELD', 'test-captcha-field')
runner = HcaptchaRunner()
runner.configure()
assert runner.enable == True
assert runner.sitekey == 'abc'
assert runner.secret == '123'
assert runner.verify_url == 'https://hcaptcha.com/siteverify'
assert runner.response_field == 'test-captcha-field'
payload = {'version': '1.0','body': {'not-field': 'abc'}}
request_provider = RequestProvider(payload)
response_provider = ResponseProvider(payload)
response = runner.run(request_provider, response_provider)
assert runner.error_response['statusCode'] == 400
assert not response
@httpretty.activate(allow_net_connect=False)
def test_runner_enabled_and_configured_service_error(monkeypatch):
"""
Test configured runner catches service exception correctly
Trying to POST with invalid credentials should be caught
"""
monkeypatch.setenv('HCAPTCHA_ENABLE', 'True')
monkeypatch.setenv('HCAPTCHA_SITEKEY', 'abc')
monkeypatch.setenv('HCAPTCHA_SECRET', '123')
monkeypatch.setenv('HCAPTCHA_RESPONSE_FIELD', 'test-captcha-field')
runner = HcaptchaRunner()
runner.configure()
assert runner.enable == True
assert runner.sitekey == 'abc'
assert runner.secret == '123'
assert runner.verify_url == 'https://hcaptcha.com/siteverify'
assert runner.response_field == 'test-captcha-field'
payload = {'version': '1.0','body': {'test-captcha-field': 'abc'}}
request_provider = RequestProvider(payload)
response_provider = ResponseProvider(payload)
# Prepare mocked error call to hCaptcha API
utils.httpretty_register_hcaptcha_siteverify_error()
response = runner.run(request_provider, response_provider)
assert runner.error_response['statusCode'] == 500
assert not response
@httpretty.activate(allow_net_connect=False)
def test_runner_enabled_and_configured_service_success_validation_fail(monkeypatch):
"""
Test configured runner catches service exception correctly
Trying to POST with invalid credentials should be caught
"""
monkeypatch.setenv('HCAPTCHA_ENABLE', 'True')
monkeypatch.setenv('HCAPTCHA_SITEKEY', 'abc')
monkeypatch.setenv('HCAPTCHA_SECRET', '123')
monkeypatch.setenv('HCAPTCHA_RESPONSE_FIELD', 'test-captcha-field')
runner = HcaptchaRunner()
runner.configure()
assert runner.enable == True
assert runner.sitekey == 'abc'
assert runner.secret == '123'
assert runner.verify_url == 'https://hcaptcha.com/siteverify'
assert runner.response_field == 'test-captcha-field'
payload = {'version': '1.0','body': {'test-captcha-field': 'abc'}}
request_provider = RequestProvider(payload)
response_provider = ResponseProvider(payload)
# # Prepare mocked call to Discord API
utils.httpretty_register_hcaptcha_siteverify_failure()
response = runner.run(request_provider, response_provider)
assert runner.error_response['statusCode'] == 401
assert response['status'] == 200
@httpretty.activate(allow_net_connect=False)
def test_runner_enabled_and_configured_service_success_validation_success(monkeypatch):
"""
Test configured runner catches service exception correctly
Trying to POST with invalid credentials should be caught
"""
monkeypatch.setenv('HCAPTCHA_ENABLE', 'True')
monkeypatch.setenv('HCAPTCHA_SITEKEY', 'abc')
monkeypatch.setenv('HCAPTCHA_SECRET', '123')
monkeypatch.setenv('HCAPTCHA_RESPONSE_FIELD', 'test-captcha-field')
runner = HcaptchaRunner()
runner.configure()
assert runner.enable == True
assert runner.sitekey == 'abc'
assert runner.secret == '123'
assert runner.verify_url == 'https://hcaptcha.com/siteverify'
assert runner.response_field == 'test-captcha-field'
payload = {'version': '1.0','body': {'test-captcha-field': 'abc'}}
request_provider = RequestProvider(payload)
response_provider = ResponseProvider(payload)
# # Prepare mocked call to Discord API
utils.httpretty_register_hcaptcha_siteverify_success()
response = runner.run(request_provider, response_provider)
assert not runner.error_response
assert response['status'] == 200
| 33.94186
| 87
| 0.734327
| 649
| 5,838
| 6.42681
| 0.154083
| 0.069048
| 0.113882
| 0.046032
| 0.8269
| 0.822105
| 0.811796
| 0.799089
| 0.77895
| 0.762887
| 0
| 0.009976
| 0.158616
| 5,838
| 171
| 88
| 34.140351
| 0.839169
| 0.128811
| 0
| 0.737864
| 0
| 0
| 0.173589
| 0.018548
| 0
| 0
| 0
| 0
| 0.300971
| 1
| 0.058252
| false
| 0
| 0.067961
| 0
| 0.126214
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
f5903d72ebcd9874eda5b29d30aa6151abbfbb09
| 203
|
py
|
Python
|
bentoml/statsmodels.py
|
francoisserra/BentoML
|
213e9e9b39e055286f2649c733907df88e6d2503
|
[
"Apache-2.0"
] | 1
|
2021-06-12T17:04:07.000Z
|
2021-06-12T17:04:07.000Z
|
bentoml/statsmodels.py
|
francoisserra/BentoML
|
213e9e9b39e055286f2649c733907df88e6d2503
|
[
"Apache-2.0"
] | 4
|
2021-05-16T08:06:25.000Z
|
2021-11-13T08:46:36.000Z
|
bentoml/statsmodels.py
|
francoisserra/BentoML
|
213e9e9b39e055286f2649c733907df88e6d2503
|
[
"Apache-2.0"
] | null | null | null |
from ._internal.frameworks.statsmodels import load
from ._internal.frameworks.statsmodels import save
from ._internal.frameworks.statsmodels import load_runner
__all__ = ["load", "load_runner", "save"]
| 33.833333
| 57
| 0.812808
| 24
| 203
| 6.5
| 0.375
| 0.230769
| 0.423077
| 0.634615
| 0.801282
| 0.551282
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08867
| 203
| 5
| 58
| 40.6
| 0.843243
| 0
| 0
| 0
| 0
| 0
| 0.093596
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
5ff0d80a65c900432aeec381c1f196f50c61fe48
| 459
|
py
|
Python
|
src/apps/home/models.py
|
IOwebapps/sigtest
|
4440d08fa187b5287ff98cb0263cfb5cfd819e2e
|
[
"MIT"
] | 1
|
2022-03-29T15:09:03.000Z
|
2022-03-29T15:09:03.000Z
|
src/apps/home/models.py
|
IOwebapps/sigtest
|
4440d08fa187b5287ff98cb0263cfb5cfd819e2e
|
[
"MIT"
] | null | null | null |
src/apps/home/models.py
|
IOwebapps/sigtest
|
4440d08fa187b5287ff98cb0263cfb5cfd819e2e
|
[
"MIT"
] | null | null | null |
# from django.db import models
# class code(models.Model):
# title = models.CharField(max_length=30,blank=False)
# def __str__(self):
# return self.title
# class staff(models.Model):
# title = models.CharField(max_length=30,blank=False)
# def __str__(self):
# return self.title
# class classitem(models.Model):
# title = models.CharField(max_length=30,blank=False)
# def __str__(self):
# return self.title
| 24.157895
| 57
| 0.660131
| 59
| 459
| 4.881356
| 0.355932
| 0.114583
| 0.166667
| 0.229167
| 0.836806
| 0.836806
| 0.836806
| 0.836806
| 0.836806
| 0.836806
| 0
| 0.016575
| 0.211329
| 459
| 18
| 58
| 25.5
| 0.779006
| 0.930283
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
5ffc73277873baa577cba74fa904c9ba20a9b9cc
| 6,794
|
py
|
Python
|
core/encoder/vggs.py
|
liuph0119/Semantic_Segmentation_Keras
|
b595f0e2d62c471256dcc800f9539dbdf354d391
|
[
"Apache-2.0"
] | 17
|
2019-03-18T08:00:24.000Z
|
2021-03-10T06:52:18.000Z
|
core/encoder/vggs.py
|
123fengye741/Semantic_Segmentation_Keras
|
b595f0e2d62c471256dcc800f9539dbdf354d391
|
[
"Apache-2.0"
] | 2
|
2019-05-15T00:18:38.000Z
|
2019-05-22T03:21:11.000Z
|
core/encoder/vggs.py
|
123fengye741/Semantic_Segmentation_Keras
|
b595f0e2d62c471256dcc800f9539dbdf354d391
|
[
"Apache-2.0"
] | 8
|
2019-03-08T15:42:31.000Z
|
2019-12-19T02:33:18.000Z
|
from keras.layers import Input
from keras.layers.normalization import BatchNormalization
from keras.layers.pooling import MaxPooling2D
from keras.models import Model
from ..utils.net_utils import conv_bn_act_block
def vgg_16(input_shape,
weight_decay=1e-4,
kernel_initializer="he_normal",
bn_epsilon=1e-3,
bn_momentum=0.99):
""" build a vgg-16 encoder.
:param input_shape: tuple, i.e., (height, width, channel).
:param weight_decay: float, default 1e-4.
:param kernel_initializer: string, default "he_normal".
:param bn_epsilon: float, default 1e-3.
:param bn_momentum: float, default 0.99.
:return: a Keras Moodel instance.
"""
input_x = Input(shape=input_shape)
x = BatchNormalization(epsilon=bn_epsilon, momentum=bn_momentum)(input_x)
x = conv_bn_act_block(x, 64, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 64, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 128, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 128, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
return Model(input_x, x)
def vgg_19(input_shape,
weight_decay=1e-4,
kernel_initializer="he_normal",
bn_epsilon=1e-3,
bn_momentum=0.99):
""" build a vgg-16 encoder.
:param input_shape: tuple, i.e., (height, width, channel).
:param weight_decay: float, default 1e-4.
:param kernel_initializer: string, default "he_normal".
:param bn_epsilon: float, default 1e-3.
:param bn_momentum: float, default 0.99.
:return: a Keras Moodel instance.
"""
input_x = Input(shape=input_shape)
x = BatchNormalization(epsilon=bn_epsilon, momentum=bn_momentum)(input_x)
x = conv_bn_act_block(x, 64, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 64, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 128, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 128, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 256, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = conv_bn_act_block(x, 512, weight_decay=weight_decay, kernel_initializer=kernel_initializer,
bn_epsilon=bn_epsilon, bn_momentum=bn_momentum)
x = MaxPooling2D(pool_size=(2, 2))(x)
return Model(input_x, x)
| 55.688525
| 99
| 0.69841
| 923
| 6,794
| 4.750813
| 0.063922
| 0.127252
| 0.140479
| 0.092588
| 0.955074
| 0.955074
| 0.955074
| 0.955074
| 0.955074
| 0.955074
| 0
| 0.02759
| 0.215779
| 6,794
| 122
| 100
| 55.688525
| 0.79542
| 0.087283
| 0
| 0.91954
| 0
| 0
| 0.002936
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.022989
| false
| 0
| 0.057471
| 0
| 0.103448
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
fdc5a102a8ccc22e72124598aac93550c49c6319
| 2,936
|
py
|
Python
|
tests/test_rules_2048.py
|
Dratui/AI-Arena
|
e9693e34a90523bbb86eb2ad3b2c3e9797beed5c
|
[
"MIT"
] | 2
|
2018-11-16T08:18:42.000Z
|
2018-11-22T08:44:10.000Z
|
tests/test_rules_2048.py
|
Dratui/2048_online
|
e9693e34a90523bbb86eb2ad3b2c3e9797beed5c
|
[
"MIT"
] | 15
|
2018-11-16T10:52:24.000Z
|
2018-11-23T08:36:17.000Z
|
tests/test_rules_2048.py
|
Dratui/AI-Arena
|
e9693e34a90523bbb86eb2ad3b2c3e9797beed5c
|
[
"MIT"
] | 2
|
2018-11-15T09:32:36.000Z
|
2018-11-16T08:56:54.000Z
|
from src.games.game_2048.rules_2048 import *
from pytest import *
from src.board import *
from src.games.game_2048.themes import THEMES
from src.games.games import *
def test_evolve_line():
assert evolve_line([None for i in range(4)]) == [None for i in range(4)]
assert evolve_line([None,4,4,8]) == [8,8,None,None]
assert evolve_line([2, None, None, 2]) == [4,None,None,None]
assert evolve_line([2, 4, None, 2]) == [2,4,2,None]
def test_make_a_move():
game = init_game("2048")
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]])
game.make_a_move(3)
assert game.list_board[0].get_all_tiles() == generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [4, None, None, None]]).get_all_tiles()
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]])
game.make_a_move(1)
assert game.list_board[0].get_all_tiles() == generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [None, None, None, 4]]).get_all_tiles()
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]])
game.make_a_move(0)
assert game.list_board[0].get_all_tiles() == generate_board_from_list([[2, None, None, 2], [None, None, None, None], [None, None, None, None], [None, None, None, None]]).get_all_tiles()
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]])
game.make_a_move(2)
assert game.list_board[0].get_all_tiles() == generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]]).get_all_tiles()
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, 4, 2]])
game.make_a_move(1)
assert game.list_board[0].get_all_tiles() == generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [None, 2, 4, 2]]).get_all_tiles()
def test_is_over():
game = init_game("2048")
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, None], [2, None, None, 2]])
assert game.is_over()[0] == False
game.list_board[0] = generate_board_from_list([[2*2**i,4*2**i,8*2**i,16*2**i] for i in range(4)])
assert game.is_over()[0] == True
def test_calc_score():
game = init_game("2048")
game.list_board[0] = generate_board_from_list([[None, None, None, None], [None, None, None, None], [None, None, None, 2048], [2, 4, 16, 2]])
assert calc_score(game.list_board, 0) == 2072
| 68.27907
| 192
| 0.66485
| 498
| 2,936
| 3.708835
| 0.086345
| 0.64104
| 0.812128
| 0.961559
| 0.840823
| 0.798051
| 0.740661
| 0.740661
| 0.721711
| 0.721711
| 0
| 0.042147
| 0.143392
| 2,936
| 42
| 193
| 69.904762
| 0.692247
| 0
| 0
| 0.27027
| 0
| 0
| 0.004087
| 0
| 0
| 0
| 0
| 0
| 0.324324
| 1
| 0.108108
| false
| 0
| 0.135135
| 0
| 0.243243
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
8bfc1edbd7ea7c48c0ecb41610ee336e4016893c
| 113
|
py
|
Python
|
koopmania/benchmark/__init__.py
|
EthanJamesLew/koopmania
|
37b18742f6534711f430b7a92443571ff93629fb
|
[
"BSD-3-Clause"
] | 1
|
2022-03-27T11:18:24.000Z
|
2022-03-27T11:18:24.000Z
|
koopmania/benchmark/__init__.py
|
salmajouini/koopmania
|
8d59b36e1de71317f883e0b55412b963629231b0
|
[
"BSD-3-Clause"
] | null | null | null |
koopmania/benchmark/__init__.py
|
salmajouini/koopmania
|
8d59b36e1de71317f883e0b55412b963629231b0
|
[
"BSD-3-Clause"
] | 1
|
2022-01-30T01:58:14.000Z
|
2022-01-30T01:58:14.000Z
|
from koopmania.benchmark.fhn import FitzHughNagumo
from koopmania.benchmark.vp import VanDerPol, CoupledVanDerPol
| 56.5
| 62
| 0.884956
| 13
| 113
| 7.692308
| 0.692308
| 0.26
| 0.44
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.070796
| 113
| 2
| 62
| 56.5
| 0.952381
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
e31ff74dfa099a7b62e6c8a5cc91ba616fd9ab85
| 12,718
|
py
|
Python
|
cpdb/utils/tests/test_copa_utils.py
|
invinst/CPDBv2_backend
|
b4e96d620ff7a437500f525f7e911651e4a18ef9
|
[
"Apache-2.0"
] | 25
|
2018-07-20T22:31:40.000Z
|
2021-07-15T16:58:41.000Z
|
cpdb/utils/tests/test_copa_utils.py
|
invinst/CPDBv2_backend
|
b4e96d620ff7a437500f525f7e911651e4a18ef9
|
[
"Apache-2.0"
] | 13
|
2018-06-18T23:08:47.000Z
|
2022-02-10T07:38:25.000Z
|
cpdb/utils/tests/test_copa_utils.py
|
invinst/CPDBv2_backend
|
b4e96d620ff7a437500f525f7e911651e4a18ef9
|
[
"Apache-2.0"
] | 6
|
2018-05-17T21:59:43.000Z
|
2020-11-17T00:30:26.000Z
|
from django.test import TestCase
from robber import expect
from utils.copa_utils import extract_copa_executive_summary
class CopaUtilsTestCase(TestCase):
def test_extract_copa_executive_summary(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nSUMMARY REPORT OF INVESTIGATION1'
'\nI. EXECUTIVE SUMMARY'
'\nDate of Incident: September 25, 2015'
'\nTime of Incident: 8:53 pm.'
'\nLocation of Incident: N. Central Park Avenue, Chicago, IL'
'\nDate of COPA Notification: September 25, 2015'
'\nTime of COPA Notification: 9:15 pm.'
'\nOn September 25, 2015, at approximately 8:50 pm, Officers A and responded to a'
'\ncall of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'\nN. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian'
'\nmother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting'
'\ncrazy, had a knife, and would not come out of his bedroom.'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
'\nInvolved Individual#1: Involved Civilian 1, DOB: 1982, Male, Black.'
'\n1 On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 25, 2015, at approximately 8:50 pm, Officers A and responded to a '
'call of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'N. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian '
'mother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting '
'crazy, had a knife, and would not come out of his bedroom.'
)
def test_extract_executive_summary_of_incident_pattern_from_copa_attachment(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nSUMMARY REPORT OF INVESTIGATION1'
'\nSUMMARY OF INCIDENT'
'\nOn September 25, 2015, at approximately 8:50 pm, Officers A and responded to a'
'\ncall of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'\nN. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian'
'\nmother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting'
'\ncrazy, had a knife, and would not come out of his bedroom.'
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\n1 On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 25, 2015, at approximately 8:50 pm, Officers A and responded to a '
'call of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'N. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian '
'mother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting '
'crazy, had a knife, and would not come out of his bedroom.'
)
def test_extract_executive_summary_introduction_pattern_from_copa_attachment(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nSUMMARY OF INCIDENT'
'\nOn September 25, 2015, at approximately 8:50 pm, Officers A and responded to a'
'\ncall of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'\nN. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian'
'\nmother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting'
'\ncrazy, had a knife, and would not come out of his bedroom.'
'\nALLEGATIONS'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nINVESTIGATION'
'\n1 On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 25, 2015, at approximately 8:50 pm, Officers A and responded to a '
'call of a disturbance with a mentally ill subject, Involved Civilian 1 (Involved Civilian 1), at '
'N. Central Park Avenue, Chicago, IL. Upon arrival, the officers met with Involved Civilian '
'mother, Involved Civilian 2 (Involved Civilian 2), who stated that Involved Civilian 1 was acting '
'crazy, had a knife, and would not come out of his bedroom.'
)
def test_extract_copa_executive_summary_with_exact_before_text_from_copa_attachment(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINTRODUCTION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nINVESTIGATION'
'\n1 On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'Involved Officer Officer A, star Employee Date of '
'Appointment: Chicago Police Officer, Unit of'
)
def test_extract_copa_executive_summary_with_exclude_text(self):
text_content = (
'\nINTRODUCTION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nCIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nAppointment: Chicago Police Officer, Unit of'
'\nINVESTIGATION'
'\n1 On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'Involved Officer Officer A, star Employee Date of '
'Appointment: Chicago Police Officer, Unit of'
)
def test_extract_copa_executive_summary_with_date_time_text(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nDate of IPRA'
'\n10:12 PM'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'10:12 PM '
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_extract_copa_executive_summary_with_summary_title(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nSUMMARY OF INCIDENT'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_extract_copa_executive_summary_with_summary_title_end_with_colon(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nSummary of incident:'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_extract_copa_executive_summary_with_exact_summary_title(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nSUMMARY OF'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_extract_copa_executive_summary_with_exact_summary_title_end_with_colon(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nSummary of:'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nII. INVOLVED PARTIES'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_extract_copa_executive_summary_with_alternative_title(self):
text_content = (
'CIVILIAN OFFICE OF POLICE ACCOUNTABILITY '
'\nINVESTIGATION'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nTime of COPA'
'\nOn September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'\nIndependent Police'
'\nThis is an alternative title:'
'\nInvolved Officer Officer A, star Employee Date of'
'\nAppointment: Chicago Police Officer, Unit of'
'\nAssignment: XX, DOB: 1983, Male White.'
)
expect(extract_copa_executive_summary(text_content)).to.eq(
'On September 15, 2017, the Civilian Office of Police Accountability (COPA) replaced the '
'Independent Police'
)
def test_can_not_extract_copa_executive_summary(self):
text_content = 'This is invalid text content.'
expect(extract_copa_executive_summary(text_content)).to.be.none()
| 51.076305
| 113
| 0.638622
| 1,466
| 12,718
| 5.431105
| 0.095498
| 0.074353
| 0.049234
| 0.098468
| 0.934815
| 0.929289
| 0.925019
| 0.916353
| 0.906933
| 0.898392
| 0
| 0.027971
| 0.288803
| 12,718
| 248
| 114
| 51.282258
| 0.852294
| 0
| 0
| 0.742081
| 0
| 0
| 0.620616
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.054299
| false
| 0
| 0.013575
| 0
| 0.072398
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
8b5084b15a0d1d3f8e7b73ded0f9b75179968d97
| 27,778
|
py
|
Python
|
codigo/utils.py
|
xKuZz/tfg
|
3161e65a2870b306ebc76eca9e34465b41742740
|
[
"MIT"
] | null | null | null |
codigo/utils.py
|
xKuZz/tfg
|
3161e65a2870b306ebc76eca9e34465b41742740
|
[
"MIT"
] | null | null | null |
codigo/utils.py
|
xKuZz/tfg
|
3161e65a2870b306ebc76eca9e34465b41742740
|
[
"MIT"
] | null | null | null |
import numba
from numba import cuda
import numpy as np
"""
Implementación de scan inclusivo
"""
@cuda.jit
def scan_block(d_data, d_scan, aux):
temp = cuda.shared.array(shape=32, dtype=numba.float32)
tid = cuda.threadIdx.x
idx = cuda.grid(1)
temp1 = d_data[tid+cuda.blockIdx.x*cuda.blockDim.x]
d = 1
while d < 32:
temp2 = cuda.shfl_up_sync(-1, temp1, d)
if tid % 32 >= d:
temp1 += temp2
d <<=1
if tid % 32 == 31:
temp[tid//32] = temp1
cuda.syncthreads()
if tid < 32:
temp2 = 0.0
if tid < cuda.blockDim.x/32:
temp2 = temp[tid]
d = 1
while d < 32:
temp3 = cuda.shfl_up_sync(-1, temp2, d)
if tid % 32 >= d:
temp2 += temp3
d<<=1
if tid < cuda.blockDim.x//32:
temp[tid] = temp2
cuda.syncthreads()
if tid >= 32:
temp1 += temp[tid//32-1]
cuda.syncthreads()
if idx < d_scan.size:
d_scan[idx] = temp1
if tid == cuda.blockDim.x-1:
aux[cuda.blockIdx.x] = temp1
@cuda.jit
def scan_sum(data, aux):
# Índices
bidx = cuda.blockIdx.x
idx = cuda.grid(1)
if cuda.blockDim.x <= idx < data.size:
data[idx] += aux[cuda.blockIdx.x-1]
def scan(d_x, d_scan, tpb=1024):
aux = np.empty(d_x.size//tpb, dtype=d_x.dtype)
scan_block[d_x.size//tpb+1, tpb](d_x, d_scan, aux)
scan_sum[d_x.size//tpb+1, tpb](d_scan, np.cumsum(aux))
@cuda.jit
def multi_scan_block(d_data, d_scan, aux):
temp = cuda.shared.array(shape=32, dtype=numba.float32)
tid = cuda.threadIdx.x
idx = tid+cuda.blockIdx.x*cuda.blockDim.x
if idx < d_data.shape[1]:
temp1 = d_data[cuda.blockIdx.y, idx]
d = 1
while d < 32:
temp2 = cuda.shfl_up_sync(-1, temp1, d)
if tid % 32 >= d:
temp1 += temp2
d <<=1
if tid % 32 == 31:
temp[tid//32] = temp1
cuda.syncthreads()
if tid < 32:
temp2 = 0.0
if tid < cuda.blockDim.x/32:
temp2 = temp[tid]
d = 1
while d < 32:
temp3 = cuda.shfl_up_sync(-1, temp2, d)
if tid % 32 >= d:
temp2 += temp3
d<<=1
if tid < cuda.blockDim.x//32:
temp[tid] = temp2
cuda.syncthreads()
if tid >= 32:
temp1 += temp[tid//32-1]
cuda.syncthreads()
if idx < d_data.shape[1]:
d_scan[cuda.blockIdx.y, idx] = temp1
if tid == cuda.blockDim.x-1:
for i in range(cuda.blockIdx.x, cuda.gridDim.x):
cuda.atomic.add(aux, (cuda.blockIdx.y, i), temp1)
@cuda.jit
def multi_scan_sum(data, aux):
col = cuda.threadIdx.x+cuda.blockIdx.x*cuda.blockDim.x
if cuda.blockDim.x <= col < data.shape[1]:
data[cuda.blockIdx.y, col] += aux[cuda.blockIdx.y, cuda.blockIdx.x-1]
@cuda.jit
def multi_scan_sum_with_gini(data, values, aux, my_min):
row = cuda.blockIdx.y
col = cuda.threadIdx.x+cuda.blockIdx.x*cuda.blockDim.x
n = data.shape[1]
total_true = aux[0,aux.shape[1] - 1]
if cuda.grid(1) == 0:
my_min[0] = np.inf
if cuda.blockDim.x <= col < data.shape[1]:
data[row, col] += aux[row, cuda.blockIdx.x-1]
if col < data.shape[1]:
n_i = col % n + 1
n_d = n - n_i
if n_d != 0 and values[row, col] != values[row, col + 1]:
t_i = data[row, col]
t_d = total_true - t_i
data[row, col] = (t_i * (n_i - t_i)/(n_i)) + (t_d * (n_d - t_d)/(n_d))
else:
data[row, col] = n
@cuda.jit
def multi_scan_sum_with_addresses(data, aux, address, my_flag, my_offset):
row = cuda.blockIdx.y
col = cuda.threadIdx.x+cuda.blockIdx.x*cuda.blockDim.x
total_false = aux[0, aux.shape[1] - 1]
if cuda.blockDim.x <= col < data.shape[1]:
data[row, col] += aux[row, cuda.blockIdx.x-1]
if col < my_flag.shape[1]:
address[row, col] = col + total_false - data[row, col] if my_flag[row, col] else data[row, col] - 1
address[row, col] += my_offset
def multi_scan(d_x, d_scan, tpb=1024, stream=0):
aux = cuda.device_array((d_x.shape[0], d_x.shape[1]//tpb+1), dtype=d_x.dtype, stream=stream)
aux[:,:] = 0
blocks = (d_x.shape[1]//tpb+1, d_x.shape[0])
multi_scan_block[blocks, tpb, stream](d_x, d_scan, aux)
multi_scan_sum[blocks, tpb, stream](d_scan, aux)
def multi_scan_with_gini(d_x, d_scan, d_values, my_min, aux, tpb=1024, stream=0):
blocks = (d_x.shape[1]//tpb+1, d_x.shape[0])
multi_scan_block[blocks, tpb, stream](d_x, d_scan, aux)
multi_scan_sum_with_gini[blocks, tpb, stream](d_scan, d_values, aux, my_min)
return aux[0].copy_to_host(stream=stream)[aux.shape[1]-1]
def multi_scan_with_address(d_x, d_scan, address, my_flag, aux, my_offset, tpb=1024, stream=0):
blocks = (d_x.shape[1]//tpb+1, d_x.shape[0])
multi_scan_block[blocks, tpb, stream](d_x, d_scan, aux)
multi_scan_sum_with_addresses[blocks, tpb, stream](d_scan, aux, address, my_flag, my_offset)
"""
La implementación se corresponde a
https://developer.download.nvidia.com/assets/cuda/files/reduction.pdf
pero adaptada a encontrar el mínimo en vez de la suma.
"""
@cuda.jit
def cuda_min_element(my_array, my_mins, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=128, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=128, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
idx = cuda.blockDim.x * cuda.blockIdx.x + tidx
# 3. Inicialiamos a infinito
shared_mem[tidx] = np.inf
# 4. Cada thread comprueba un stride del grid
while idx < my_array.size:
if my_array[idx] < shared_mem[tidx]:
shared_mem[tidx] = my_array[idx]
shared_idx[tidx] = idx
idx += cuda.blockDim.x * cuda.gridDim.x
cuda.syncthreads()
idx = cuda.blockDim.x * cuda.blockIdx.x + tidx
# 5. Unroll de bloque
# Consideramos que estamos usando 128 hebras por bloque.
if tidx < 64:
if shared_mem[tidx + 64] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 64]
shared_idx[tidx] = shared_idx[tidx + 64]
cuda.syncthreads()
# 6. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
# Si da para más de un bloque, luego hay que reaplicar el kernel
if tidx == 0:
my_mins[cuda.blockIdx.x] = shared_mem[tidx]
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
def reduce_min_index(a):
list_indexes = []
def set_kernel_params(a):
threads = 128
blocks = a.size // threads + 1
sm_size = threads * 2 * 4
mins = np.empty(blocks, np.float32)
indexes = np.empty(blocks, np.int32)
return blocks, threads, 0, sm_size, a, mins, indexes
def run_kernel(p):
cuda_min_element[p[0], p[1]](p[4], p[5], p[6])
p = set_kernel_params(a)
if p[0] == 1:
run_kernel(p)
return p[6][0]
else:
while p[0] > 2:
run_kernel(p)
list_indexes.append(p[6])
a = p[5]
p = set_kernel_params(a)
run_kernel(p)
list_indexes.append(p[6])
output_index = 0
for indexes in list_indexes[::-1]:
output_index = indexes[output_index]
return output_index
"""
Implementación de reducción para suma, similar a la anterior
pero para realizar sumas
"""
@cuda.jit
def cuda_sum(my_array, my_sums):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=128, dtype=numba.float32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
idx = cuda.blockDim.x * cuda.blockIdx.x + tidx
# 3. Inicialiamos a cero
shared_mem[tidx] = 0
# 4. Cada thread comprueba un stride doble del grid
while idx < my_array.size:
shared_mem[tidx] += my_array[idx]
idx += cuda.blockDim.x * cuda.gridDim.x
cuda.syncthreads()
# 5. Unroll de bloque
# Consideramos que estamos usando 128 hebras por bloque.
if tidx < 64:
shared_mem[tidx] += shared_mem[tidx+64]
cuda.syncthreads()
# 6. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
shared_mem[tidx] += shared_mem[tidx+32]
shared_mem[tidx] += shared_mem[tidx+16]
shared_mem[tidx] += shared_mem[tidx+8]
shared_mem[tidx] += shared_mem[tidx+4]
shared_mem[tidx] += shared_mem[tidx+2]
shared_mem[tidx] += shared_mem[tidx+1]
# El primer thread de cada bloque indica su suma
# Si da para más de un bloque, luego hay que reaplicar el kernel
if tidx == 0:
my_sums[cuda.blockIdx.x] = shared_mem[tidx]
def reduce_sum(a):
def set_kernel_params(a):
threads = 128
blocks = a.size // threads + 1
sm_size = threads * 4
sums = np.empty(blocks, np.float32)
return blocks, threads, 0, sm_size, a, sums
def run_kernel(p):
cuda_sum[p[0], p[1]](p[4], p[5])
p = set_kernel_params(a)
if p[0] == 1:
run_kernel(p)
return p[5][0]
else:
while p[0] > 2:
run_kernel(p)
a = p[5]
p = set_kernel_params(a)
run_kernel(p)
return p[5][0]
"""
Multi reducción por filas. Una fila no puede tener más de 1024 elementos.
"""
@cuda.jit
def cuda_multi_min_element_64(my_array, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=64, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=64, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
bidx = cuda.blockIdx.x
# 3. Inicialiamos el bloque y rellenamos con infinito
if tidx < my_array.shape[1]:
shared_mem[tidx] = my_array[bidx, tidx]
else:
shared_mem[tidx] = np.inf
shared_idx[tidx] = tidx
cuda.syncthreads()
# 4. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
if tidx == 0:
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
@cuda.jit
def cuda_multi_min_element_128(my_array, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=128, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=128, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
bidx = cuda.blockIdx.x
# 3. Inicialiamos el bloque y rellenamos con infinito
if tidx < my_array.shape[1]:
shared_mem[tidx] = my_array[bidx, tidx]
else:
shared_mem[tidx] = np.inf
shared_idx[tidx] = tidx
cuda.syncthreads()
# 4. Unroll de bloque
# Consideramos que estamos usando 128 hebras por bloque.
if tidx < 64:
if shared_mem[tidx + 64] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 64]
shared_idx[tidx] = shared_idx[tidx + 64]
cuda.syncthreads()
# 5. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
if tidx == 0:
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
@cuda.jit
def cuda_multi_min_element_256(my_array, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=256, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=256, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
bidx = cuda.blockIdx.x
# 3. Inicialiamos el bloque y rellenamos con infinito
if tidx < my_array.shape[1]:
shared_mem[tidx] = my_array[bidx, tidx]
else:
shared_mem[tidx] = np.inf
shared_idx[tidx] = tidx
cuda.syncthreads()
# 4. Unroll de bloque
if tidx < 128:
if shared_mem[tidx + 128] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 128]
shared_idx[tidx] = shared_idx[tidx + 128]
cuda.syncthreads()
if tidx < 64:
if shared_mem[tidx + 64] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 64]
shared_idx[tidx] = shared_idx[tidx + 64]
cuda.syncthreads()
# 5. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
if tidx == 0:
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
@cuda.jit
def cuda_multi_min_element_512(my_array, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=512, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=512, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
bidx = cuda.blockIdx.x
# 3. Inicialiamos el bloque y rellenamos con infinito
if tidx < my_array.shape[1]:
shared_mem[tidx] = my_array[bidx, tidx]
else:
shared_mem[tidx] = np.inf
shared_idx[tidx] = tidx
cuda.syncthreads()
# 4. Unroll de bloque
if tidx < 256:
if shared_mem[tidx + 256] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 256]
shared_idx[tidx] = shared_idx[tidx + 256]
cuda.syncthreads()
if tidx < 128:
if shared_mem[tidx + 128] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 128]
shared_idx[tidx] = shared_idx[tidx + 128]
cuda.syncthreads()
if tidx < 64:
if shared_mem[tidx + 64] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 64]
shared_idx[tidx] = shared_idx[tidx + 64]
cuda.syncthreads()
# 5. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
if tidx == 0:
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
@cuda.jit
def cuda_multi_min_element_1024(my_array, my_indexes):
# 1. Declaramos la memoria compartida
shared_mem = cuda.shared.array(shape=1024, dtype=numba.float32)
shared_idx = cuda.shared.array(shape=1024, dtype=numba.int32)
# 2. Obtenemos los índices
tidx = cuda.threadIdx.x
bidx = cuda.blockIdx.x
# 3. Inicialiamos el bloque y rellenamos con infinito
if tidx < my_array.shape[1]:
shared_mem[tidx] = my_array[bidx, tidx]
else:
shared_mem[tidx] = np.inf
shared_idx[tidx] = tidx
cuda.syncthreads()
# 4. Unroll de bloque
if tidx < 512:
if shared_mem[tidx + 512] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 512]
shared_idx[tidx] = shared_idx[tidx + 512]
cuda.syncthreads()
if tidx < 256:
if shared_mem[tidx + 256] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 256]
shared_idx[tidx] = shared_idx[tidx + 256]
cuda.syncthreads()
if tidx < 128:
if shared_mem[tidx + 128] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 128]
shared_idx[tidx] = shared_idx[tidx + 128]
cuda.syncthreads()
if tidx < 64:
if shared_mem[tidx + 64] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 64]
shared_idx[tidx] = shared_idx[tidx + 64]
cuda.syncthreads()
# 5. Hacemos unroll para un warp (nos ahorramos syncthreads)
if tidx < 32:
if shared_mem[tidx + 32] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 32]
shared_idx[tidx] = shared_idx[tidx + 32]
if shared_mem[tidx + 16] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 16]
shared_idx[tidx] = shared_idx[tidx + 16]
if shared_mem[tidx + 8] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 8]
shared_idx[tidx] = shared_idx[tidx + 8]
if shared_mem[tidx + 4] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 4]
shared_idx[tidx] = shared_idx[tidx + 4]
if shared_mem[tidx + 2] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 2]
shared_idx[tidx] = shared_idx[tidx + 2]
if shared_mem[tidx + 1] < shared_mem[tidx]:
shared_mem[tidx] = shared_mem[tidx + 1]
shared_idx[tidx] = shared_idx[tidx + 1]
# El primer thread de cada bloque indica su minimo
if tidx == 0:
my_indexes[cuda.blockIdx.x] = shared_idx[tidx]
def multi_reduce_min_index(device_array):
blocks, row_size = device_array.shape
device_indexes = cuda.device_array(blocks)
if 0 < row_size <= 64:
cuda_multi_min_element_64[blocks,64](device_array, device_indexes)
elif 64 < row_size <= 128:
cuda_multi_min_element_128[blocks,128](device_array, device_indexes)
elif 128 < row_size <= 256:
cuda_multi_min_element_256[blocks, 256](device_array, device_indexes)
elif 256 < row_size <= 512:
cuda_multi_min_element_512[blocks, 512](device_array, device_indexes)
elif 512 < row_size <= 1024:
cuda_multi_min_element_1024[blocks, 1024](device_array, device_indexes)
else:
return np.array([reduce_min_index(device_array[i]) for i in range(blocks)])
return device_indexes
@cuda.jit
def min_index_reduction(my_data, my_min, my_idx, aux, lock):
block_mins = cuda.shared.array(shape=32, dtype=numba.float32)
block_mins_idx = cuda.shared.array(shape=32, dtype=numba.int32)
row = cuda.blockIdx.y
col = cuda.threadIdx.x +cuda.blockIdx.x*cuda.blockDim.x
if col < my_data.shape[1]:
data1 = my_data[row, col]
else:
data1 = np.inf
idx1 = col
# 1. Reducción min_index en cada warp
data2 = cuda.shfl_up_sync(-1, data1, 1)
idx2 = cuda.shfl_up_sync(-1, idx1, 1)
if data2 < data1:
data1 = data2
idx1 = idx2
data2 = cuda.shfl_up_sync(-1, data1, 2)
idx2 = cuda.shfl_up_sync(-1, idx1, 2)
if data2 < data1:
data1 = data2
idx1 = idx2
data2 = cuda.shfl_up_sync(-1, data1, 4)
idx2 = cuda.shfl_up_sync(-1, idx1, 4)
if data2 < data1:
data1 = data2
idx1 = idx2
data2 = cuda.shfl_up_sync(-1, data1, 8)
idx2 = cuda.shfl_up_sync(-1, idx1, 8)
if data2 < data1:
data1 = data2
idx1 = idx2
data2 = cuda.shfl_up_sync(-1, data1, 16)
idx2 = cuda.shfl_up_sync(-1, idx1, 16)
if data2 < data1:
data1 = data2
idx1 = idx2
if cuda.threadIdx.x%32 == 31:
block_mins[cuda.threadIdx.x//32] = data1
block_mins_idx[cuda.threadIdx.x//32] = idx1
cuda.syncthreads()
# 2. Reducción del bloque completo en el primer warp
if cuda.threadIdx.x < 32:
if cuda.threadIdx.x < cuda.blockDim.x // 32:
data2 = block_mins[cuda.threadIdx.x]
idx2 = block_mins_idx[cuda.threadIdx.x]
else:
data2 = np.inf
idx2 = col
data3 = cuda.shfl_up_sync(-1, data2, 1)
idx3 = cuda.shfl_up_sync(-1, idx2, 1)
if data3 < data2:
data2 = data3
idx2 = idx3
data3 = cuda.shfl_up_sync(-1, data2, 2)
idx3 = cuda.shfl_up_sync(-1, idx2, 2)
if data3 < data2:
data2 = data3
idx2 = idx3
data3 = cuda.shfl_up_sync(-1, data2, 4)
idx3 = cuda.shfl_up_sync(-1, idx2, 4)
if data3 < data2:
data2 = data3
idx2 = idx3
data3 = cuda.shfl_up_sync(-1, data2, 8)
idx3 = cuda.shfl_up_sync(-1, idx2, 8)
if data3 < data2:
data2 = data3
idx2 = idx3
data3 = cuda.shfl_up_sync(-1, data2, 16)
idx3 = cuda.shfl_up_sync(-1, idx2, 16)
if data3 < data2:
data2 = data3
idx2 = idx3
if cuda.threadIdx.x == 31:
aux[cuda.blockIdx.y, cuda.blockIdx.x] = 0
while cuda.atomic.compare_and_swap(lock, 0, 1) == 1:
continue
if data2 < my_min[0]:
my_min[0] = data2
my_idx[0] = cuda.blockIdx.y
my_idx[1] = idx2
cuda.threadfence()
lock[0] = 0
@cuda.jit
def warp_based_reduce_sum(my_data, my_sum):
block_sums = cuda.shared.array(shape=32, dtype=numba.int32)
col = cuda.grid(1)
if col < my_data.shape[0]:
data1 = my_data[col]
else:
data1 = 0
# 1. Reducción min_index en cada warp
data2 = cuda.shfl_up_sync(-1, data1, 1)
data1 += data2
data2 = cuda.shfl_up_sync(-1, data1, 2)
data1 += data2
data2 = cuda.shfl_up_sync(-1, data1, 4)
data1 += data2
data2 = cuda.shfl_up_sync(-1, data1, 8)
data1 += data2
data2 = cuda.shfl_up_sync(-1, data1, 16)
data1 += data2
if cuda.threadIdx.x%32 == 31:
block_sums[cuda.threadIdx.x//32] = data1
cuda.syncthreads()
# 2. Reducción del bloque completo en el primer warp
if cuda.threadIdx.x < 32:
if cuda.threadIdx.x < cuda.blockDim.x // 32:
data2 = block_sums[cuda.threadIdx.x]
else:
data2 = 0
data3 = cuda.shfl_up_sync(-1, data2, 1)
data2 += data3
data3 = cuda.shfl_up_sync(-1, data2, 2)
data2 += data3
data3 = cuda.shfl_up_sync(-1, data2, 4)
data2 += data3
data3 = cuda.shfl_up_sync(-1, data2, 8)
data2 += data3
data3 = cuda.shfl_up_sync(-1, data2, 16)
data2 += data3
if cuda.threadIdx.x == 31:
cuda.atomic.add(my_sum, 0, data2)
| 34.125307
| 108
| 0.566491
| 3,887
| 27,778
| 3.866478
| 0.052225
| 0.135338
| 0.189434
| 0.128951
| 0.85854
| 0.811498
| 0.783751
| 0.734314
| 0.709096
| 0.666711
| 0
| 0.052129
| 0.321153
| 27,778
| 813
| 109
| 34.167282
| 0.744869
| 0.078371
| 0
| 0.736134
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.043697
| false
| 0
| 0.005042
| 0
| 0.063866
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 8
|
8b577ef34727b2a20da6cf58120f90203990f19f
| 88
|
py
|
Python
|
torchtools/tensors/__init__.py
|
cjwcommuny/torch-tools
|
a64c0bdd87df065744fb49644f767165d3516b27
|
[
"MIT"
] | null | null | null |
torchtools/tensors/__init__.py
|
cjwcommuny/torch-tools
|
a64c0bdd87df065744fb49644f767165d3516b27
|
[
"MIT"
] | null | null | null |
torchtools/tensors/__init__.py
|
cjwcommuny/torch-tools
|
a64c0bdd87df065744fb49644f767165d3516b27
|
[
"MIT"
] | null | null | null |
from torchtools.tensors.function import *
from torchtools.tensors.tensor_group import *
| 29.333333
| 45
| 0.840909
| 11
| 88
| 6.636364
| 0.636364
| 0.383562
| 0.575342
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 88
| 2
| 46
| 44
| 0.9125
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| true
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| null | 1
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| null | 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
8b5de279a5957a1255aa25a8ebfea07605301447
| 2,824
|
py
|
Python
|
iati_standard/migrations/0005_auto_20200603_2005.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 4
|
2019-03-28T06:42:17.000Z
|
2021-06-06T13:10:51.000Z
|
iati_standard/migrations/0005_auto_20200603_2005.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 177
|
2018-09-28T14:21:56.000Z
|
2022-03-30T21:45:26.000Z
|
iati_standard/migrations/0005_auto_20200603_2005.py
|
IATI/new-website
|
b90783e32d19ac4c821c5ea018a52997a11b5286
|
[
"MIT"
] | 8
|
2018-10-25T20:43:10.000Z
|
2022-03-17T14:19:27.000Z
|
# Generated by Django 2.2.12 on 2020-06-03 20:05
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('iati_standard', '0004_auto_20200603_1955'),
]
operations = [
migrations.AddField(
model_name='standardguidanceindexpage',
name='button_link_text',
field=models.CharField(blank=True, help_text='Button text to be shown on Guidance and Support page', max_length=255, null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='button_link_text_en',
field=models.CharField(blank=True, help_text='Button text to be shown on Guidance and Support page', max_length=255, null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='button_link_text_es',
field=models.CharField(blank=True, help_text='Button text to be shown on Guidance and Support page', max_length=255, null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='button_link_text_fr',
field=models.CharField(blank=True, help_text='Button text to be shown on Guidance and Support page', max_length=255, null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='button_link_text_pt',
field=models.CharField(blank=True, help_text='Button text to be shown on Guidance and Support page', max_length=255, null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='section_summary',
field=models.TextField(blank=True, help_text='Summary seen on Guidance and Support page', null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='section_summary_en',
field=models.TextField(blank=True, help_text='Summary seen on Guidance and Support page', null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='section_summary_es',
field=models.TextField(blank=True, help_text='Summary seen on Guidance and Support page', null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='section_summary_fr',
field=models.TextField(blank=True, help_text='Summary seen on Guidance and Support page', null=True),
),
migrations.AddField(
model_name='standardguidanceindexpage',
name='section_summary_pt',
field=models.TextField(blank=True, help_text='Summary seen on Guidance and Support page', null=True),
),
]
| 44.125
| 140
| 0.645892
| 313
| 2,824
| 5.661342
| 0.182109
| 0.10158
| 0.129797
| 0.15237
| 0.902935
| 0.902935
| 0.902935
| 0.902935
| 0.902935
| 0.863431
| 0
| 0.022381
| 0.256374
| 2,824
| 63
| 141
| 44.825397
| 0.821429
| 0.016289
| 0
| 0.701754
| 1
| 0
| 0.335014
| 0.098343
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.017544
| 0
| 0.070175
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
8bbb315b7e21588153c4674a43f429dbfb38a46e
| 27,882
|
py
|
Python
|
venv/lib/python3.6/site-packages/ansible_collections/netapp/ontap/tests/unit/plugins/modules/test_na_ontap_cluster.py
|
usegalaxy-no/usegalaxy
|
75dad095769fe918eb39677f2c887e681a747f3a
|
[
"MIT"
] | 1
|
2020-01-22T13:11:23.000Z
|
2020-01-22T13:11:23.000Z
|
venv/lib/python3.6/site-packages/ansible_collections/netapp/ontap/tests/unit/plugins/modules/test_na_ontap_cluster.py
|
usegalaxy-no/usegalaxy
|
75dad095769fe918eb39677f2c887e681a747f3a
|
[
"MIT"
] | 12
|
2020-02-21T07:24:52.000Z
|
2020-04-14T09:54:32.000Z
|
venv/lib/python3.6/site-packages/ansible_collections/netapp/ontap/tests/unit/plugins/modules/test_na_ontap_cluster.py
|
usegalaxy-no/usegalaxy
|
75dad095769fe918eb39677f2c887e681a747f3a
|
[
"MIT"
] | null | null | null |
# (c) 2018, NetApp, Inc
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
''' unit tests ONTAP Ansible module: na_ontap_cluster '''
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import json
import pytest
from ansible.module_utils import basic
from ansible.module_utils._text import to_bytes
from ansible_collections.netapp.ontap.tests.unit.compat import unittest
from ansible_collections.netapp.ontap.tests.unit.compat.mock import patch, Mock, call
import ansible_collections.netapp.ontap.plugins.module_utils.netapp as netapp_utils
from ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster \
import NetAppONTAPCluster as my_module # module under test
if not netapp_utils.has_netapp_lib():
pytestmark = pytest.mark.skip('skipping as missing required netapp_lib')
def set_module_args(args):
"""prepare arguments so that they will be picked up during module creation"""
args = json.dumps({'ANSIBLE_MODULE_ARGS': args})
basic._ANSIBLE_ARGS = to_bytes(args) # pylint: disable=protected-access
class AnsibleExitJson(Exception):
"""Exception class to be raised by module.exit_json and caught by the test case"""
class AnsibleFailJson(Exception):
"""Exception class to be raised by module.fail_json and caught by the test case"""
def exit_json(*args, **kwargs): # pylint: disable=unused-argument
"""function to patch over exit_json; package return data into an exception"""
if 'changed' not in kwargs:
kwargs['changed'] = False
raise AnsibleExitJson(kwargs)
def fail_json(*args, **kwargs): # pylint: disable=unused-argument
"""function to patch over fail_json; package return data into an exception"""
kwargs['failed'] = True
raise AnsibleFailJson(kwargs)
class MockONTAPConnection(object):
''' mock server connection to ONTAP host '''
def __init__(self, kind=None):
''' save arguments '''
self.type = kind
self.xml_in = None
self.xml_out = None
def invoke_successfully(self, xml, enable_tunneling): # pylint: disable=unused-argument
''' mock invoke_successfully returning xml data '''
self.xml_in = xml
if self.type == 'cluster':
xml = self.build_cluster_info()
if self.type == 'cluster_success':
xml = self.build_cluster_info_success()
elif self.type == 'cluster_add':
xml = self.build_add_node_info()
elif self.type == 'cluster_extra_input':
self.type = 'cluster' # success on second call
raise netapp_utils.zapi.NaApiError(code='TEST1', message="Extra input: single-node-cluster")
elif self.type == 'cluster_extra_input_loop':
raise netapp_utils.zapi.NaApiError(code='TEST2', message="Extra input: single-node-cluster")
elif self.type == 'cluster_extra_input_other':
raise netapp_utils.zapi.NaApiError(code='TEST3', message="Extra input: other-unexpected-element")
elif self.type == 'cluster_fail':
raise netapp_utils.zapi.NaApiError(code='TEST4', message="This exception is from the unit test")
self.xml_out = xml
return xml
def autosupport_log(self):
''' mock autosupport log'''
return None
@staticmethod
def build_cluster_info():
''' build xml data for cluster-create-join-progress-info '''
xml = netapp_utils.zapi.NaElement('xml')
attributes = {
'attributes': {
'cluster-create-join-progress-info': {
'is-complete': 'true',
'status': 'whatever'
}
}
}
xml.translate_struct(attributes)
return xml
@staticmethod
def build_cluster_info_success():
''' build xml data for cluster-create-join-progress-info '''
xml = netapp_utils.zapi.NaElement('xml')
attributes = {
'attributes': {
'cluster-create-join-progress-info': {
'is-complete': 'false',
'status': 'success'
}
}
}
xml.translate_struct(attributes)
return xml
@staticmethod
def build_add_node_info():
''' build xml data for cluster-create-add-node-status-info '''
xml = netapp_utils.zapi.NaElement('xml')
attributes = {
'attributes-list': {
'cluster-create-add-node-status-info': {
'failure-msg': '',
'status': 'success'
}
}
}
xml.translate_struct(attributes)
return xml
# using pytest natively, without unittest.TestCase
@pytest.fixture
def patch_ansible():
with patch.multiple(basic.AnsibleModule,
exit_json=exit_json,
fail_json=fail_json) as mocks:
yield mocks
class TestMyModule(unittest.TestCase):
''' a group of related Unit Tests '''
def setUp(self):
self.mock_module_helper = patch.multiple(basic.AnsibleModule,
exit_json=exit_json,
fail_json=fail_json)
self.mock_module_helper.start()
self.addCleanup(self.mock_module_helper.stop)
self.server = MockONTAPConnection()
self.use_vsim = False
def set_default_args(self, use_rest='never'):
hostname = '10.10.10.10'
username = 'admin'
password = 'password'
cluster_name = 'abc'
return dict({
'hostname': hostname,
'username': username,
'password': password,
'cluster_name': cluster_name,
'use_rest': use_rest
})
def test_module_fail_when_required_args_missing(self):
''' required arguments are reported as errors '''
with pytest.raises(AnsibleFailJson) as exc:
set_module_args({})
my_module()
print('Info: %s' % exc.value.args[0]['msg'])
@patch('time.sleep')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
def test_ensure_apply_for_cluster_called(self, get_cl_id, sleep_mock):
''' creating cluster and checking idempotency '''
get_cl_id.return_value = None
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
assert exc.value.args[0]['changed']
@patch('time.sleep')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.create_cluster')
def test_cluster_create_called(self, cluster_create, get_cl_id, sleep_mock):
''' creating cluster'''
get_cl_id.return_value = None
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_success')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
cluster_create.assert_called_with()
@patch('time.sleep')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
def test_cluster_create_old_api(self, get_cl_id, sleep_mock):
''' creating cluster'''
get_cl_id.return_value = None
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_extra_input')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
assert exc.value.args[0]['changed']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
def test_cluster_create_old_api_loop(self, get_cl_id):
''' creating cluster'''
get_cl_id.return_value = None
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_extra_input_loop')
with pytest.raises(AnsibleFailJson) as exc:
my_obj.apply()
msg = 'TEST2:Extra input: single-node-cluster'
print('Info: test_cluster_apply: %s' % repr(exc.value))
assert msg in exc.value.args[0]['msg']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
def test_cluster_create_old_api_other_extra(self, get_cl_id):
''' creating cluster'''
get_cl_id.return_value = None
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_extra_input_other')
with pytest.raises(AnsibleFailJson) as exc:
my_obj.apply()
msg = 'TEST3:Extra input: other-unexpected-element'
print('Info: test_cluster_apply: %s' % repr(exc.value))
assert msg in exc.value.args[0]['msg']
@patch('time.sleep')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_ip_addresses')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.add_node')
def test_add_node_called(self, add_node, get_cl_id, get_cl_ips, sleep_mock):
''' creating add_node'''
get_cl_ips.return_value = []
get_cl_id.return_value = None
data = self.set_default_args()
del data['cluster_name']
data['cluster_ip_address'] = '10.10.10.10'
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
add_node.assert_called_with()
assert exc.value.args[0]['changed']
def test_if_all_methods_catch_exception(self):
module_args = {}
module_args.update(self.set_default_args())
set_module_args(module_args)
my_obj = my_module()
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_fail')
with pytest.raises(AnsibleFailJson) as exc:
my_obj.create_cluster()
assert 'Error creating cluster' in exc.value.args[0]['msg']
data = self.set_default_args()
data['cluster_ip_address'] = '10.10.10.10'
set_module_args(data)
my_obj = my_module()
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_fail')
with pytest.raises(AnsibleFailJson) as exc:
my_obj.add_node()
assert 'Error adding node with ip' in exc.value.args[0]['msg']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_ip_addresses')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.add_node')
def test_add_node_idempotent(self, add_node, get_cl_id, get_cl_ips):
''' creating add_node'''
get_cl_ips.return_value = ['10.10.10.10']
get_cl_id.return_value = None
data = self.set_default_args()
del data['cluster_name']
data['cluster_ip_address'] = '10.10.10.10'
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
try:
add_node.assert_not_called()
except AttributeError:
# not supported with python <= 3.4
pass
assert not exc.value.args[0]['changed']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_ip_addresses')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.remove_node')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.node_remove_wait')
def test_remove_node_ip(self, wait, remove_node, get_cl_id, get_cl_ips):
''' creating add_node'''
get_cl_ips.return_value = ['10.10.10.10']
get_cl_id.return_value = None
wait.return_value = None
data = self.set_default_args()
# del data['cluster_name']
data['cluster_ip_address'] = '10.10.10.10'
data['state'] = 'absent'
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
remove_node.assert_called_with()
assert exc.value.args[0]['changed']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_ip_addresses')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.remove_node')
def test_remove_node_ip_idempotent(self, remove_node, get_cl_id, get_cl_ips):
''' creating add_node'''
get_cl_ips.return_value = []
get_cl_id.return_value = None
data = self.set_default_args()
# del data['cluster_name']
data['cluster_ip_address'] = '10.10.10.10'
data['state'] = 'absent'
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
try:
remove_node.assert_not_called()
except AttributeError:
# not supported with python <= 3.4
pass
assert not exc.value.args[0]['changed']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_nodes')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.remove_node')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.node_remove_wait')
def test_remove_node_name(self, wait, remove_node, get_cl_id, get_cl_nodes):
''' creating add_node'''
get_cl_nodes.return_value = ['node1', 'node2']
get_cl_id.return_value = None
wait.return_value = None
data = self.set_default_args()
# del data['cluster_name']
data['node_name'] = 'node2'
data['state'] = 'absent'
data['force'] = True
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
remove_node.assert_called_with()
assert exc.value.args[0]['changed']
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_nodes')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.get_cluster_identity')
@patch('ansible_collections.netapp.ontap.plugins.modules.na_ontap_cluster.NetAppONTAPCluster.remove_node')
def test_remove_node_name_idempotent(self, remove_node, get_cl_id, get_cl_nodes):
''' creating add_node'''
get_cl_nodes.return_value = ['node1', 'node2']
get_cl_id.return_value = None
data = self.set_default_args()
# del data['cluster_name']
data['node_name'] = 'node3'
data['state'] = 'absent'
set_module_args(data)
my_obj = my_module()
my_obj.autosupport_log = Mock(return_value=None)
if not self.use_vsim:
my_obj.server = MockONTAPConnection('cluster_add')
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print('Info: test_cluster_apply: %s' % repr(exc.value))
try:
remove_node.assert_not_called()
except AttributeError:
# not supported with python <= 3.4
pass
assert not exc.value.args[0]['changed']
def test_remove_node_name_and_id(self):
''' creating add_node'''
data = self.set_default_args()
# del data['cluster_name']
data['cluster_ip_address'] = '10.10.10.10'
data['node_name'] = 'node3'
data['state'] = 'absent'
set_module_args(data)
with pytest.raises(AnsibleFailJson) as exc:
my_module()
print('Info: test_remove_node_name_and_id: %s' % repr(exc.value))
msg = 'when state is "absent", parameters are mutually exclusive: cluster_ip_address|node_name'
assert msg in exc.value.args[0]['msg']
SRR = {
# common responses
'is_rest': (200, dict(version=dict(generation=9, major=7, minor=0, full='dummy_9_7_0')), None),
'is_rest_95': (200, dict(version=dict(generation=9, major=5, minor=0, full='dummy_9_5_0')), None),
'is_rest_96': (200, dict(version=dict(generation=9, major=6, minor=0, full='dummy_9_6_0')), None),
'is_rest_97': (200, dict(version=dict(generation=9, major=7, minor=0, full='dummy_9_7_0')), None),
'is_zapi': (400, {}, "Unreachable"),
'empty_good': ({}, None, None),
'zero_record': (200, {'records': []}, None),
'precluster': (500, None, {'message': 'are available in precluster.'}),
'cluster_identity': (200, {'location': 'Oz', 'name': 'abc'}, None),
'nodes': (200, {'records': [
{'name': 'node2', 'uuid': 'uuid2', 'cluster_interfaces': [{'ip': {'address': '10.10.10.2'}}]}
]}, None),
'end_of_sequence': (None, None, "Unexpected call to send_request"),
'generic_error': (None, "Expected error"),
}
def set_default_args(use_rest='auto'):
hostname = '10.10.10.10'
username = 'admin'
password = 'password'
cluster_name = 'abc'
return dict({
'hostname': hostname,
'username': username,
'password': password,
'cluster_name': cluster_name,
'use_rest': use_rest
})
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_create(mock_request, patch_ansible):
''' create cluster '''
args = dict(set_default_args())
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['precluster'], # get
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
assert exc.value.args[0]['changed'] is True
print(mock_request.mock_calls)
assert len(mock_request.mock_calls) == 3
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_create_single(mock_request, patch_ansible):
''' create cluster '''
args = dict(set_default_args())
args['single_node_cluster'] = True
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['precluster'], # get
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
assert exc.value.args[0]['changed'] is True
print(mock_request.mock_calls)
assert len(mock_request.mock_calls) == 3
post_call = call('POST', 'cluster', {'return_timeout': 30, 'single_node_cluster': True}, json={'name': 'abc'}, headers=None)
assert post_call in mock_request.mock_calls
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_modify(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
args['cluster_location'] = 'Mars'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is True
assert len(mock_request.mock_calls) == 3
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_modify_idempotent(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
args['cluster_location'] = 'Oz'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is False
assert len(mock_request.mock_calls) == 2
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_add_node(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
args['node_name'] = 'node2'
args['cluster_ip_address'] = '10.10.10.2'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['zero_record'], # get nodes
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is True
assert len(mock_request.mock_calls) == 4
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_remove_node_by_ip(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
# args['node_name'] = 'node2'
args['cluster_ip_address'] = '10.10.10.2'
args['state'] = 'absent'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['nodes'], # get nodes
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is True
assert len(mock_request.mock_calls) == 4
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_remove_node_by_ip_idem(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
# args['node_name'] = 'node2'
args['cluster_ip_address'] = '10.10.10.3'
args['state'] = 'absent'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['nodes'], # get nodes
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is False
assert len(mock_request.mock_calls) == 3
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_remove_node_by_name(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
args['node_name'] = 'node2'
# args['cluster_ip_address'] = '10.10.10.2'
args['state'] = 'absent'
args['force'] = True
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['nodes'], # get nodes
SRR['empty_good'], # post
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is True
assert len(mock_request.mock_calls) == 4
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_remove_node_by_name_idem(mock_request, patch_ansible):
''' modify cluster location '''
args = dict(set_default_args())
args['node_name'] = 'node3'
# args['cluster_ip_address'] = '10.10.10.2'
args['state'] = 'absent'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest'],
SRR['cluster_identity'], # get
SRR['nodes'], # get nodes
SRR['end_of_sequence']
]
my_obj = my_module()
with pytest.raises(AnsibleExitJson) as exc:
my_obj.apply()
print(mock_request.mock_calls)
assert exc.value.args[0]['changed'] is False
assert len(mock_request.mock_calls) == 3
@patch('ansible_collections.netapp.ontap.plugins.module_utils.netapp.OntapRestAPI.send_request')
def test_rest_remove_node_by_name_rest_96(mock_request, patch_ansible):
''' revert to ZAPI for 9.6 '''
args = dict(set_default_args())
args['node_name'] = 'node3'
# args['cluster_ip_address'] = '10.10.10.2'
args['state'] = 'absent'
set_module_args(args)
mock_request.side_effect = [
SRR['is_rest_96'],
SRR['end_of_sequence']
]
my_obj = my_module()
# revert to ZAPI for 9.6
assert not my_obj.use_rest
| 40.526163
| 128
| 0.658023
| 3,515
| 27,882
| 4.934282
| 0.089047
| 0.02018
| 0.055351
| 0.066882
| 0.833083
| 0.81815
| 0.797509
| 0.781365
| 0.758937
| 0.741524
| 0
| 0.012151
| 0.223693
| 27,882
| 687
| 129
| 40.585153
| 0.789143
| 0.076788
| 0
| 0.70483
| 0
| 0
| 0.260047
| 0.150314
| 0
| 0
| 0
| 0
| 0.071556
| 1
| 0.06619
| false
| 0.012522
| 0.0161
| 0
| 0.101968
| 0.041145
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
8bbd31421c22e9979cc697f500e9243b7ec53b6b
| 243
|
py
|
Python
|
sweepstakes_stack_manager.py
|
HTGoldston/sweepstakes_starter
|
53ff2a02b217b5e78decf9ac6b4b9b7c93fe3b63
|
[
"MIT"
] | null | null | null |
sweepstakes_stack_manager.py
|
HTGoldston/sweepstakes_starter
|
53ff2a02b217b5e78decf9ac6b4b9b7c93fe3b63
|
[
"MIT"
] | null | null | null |
sweepstakes_stack_manager.py
|
HTGoldston/sweepstakes_starter
|
53ff2a02b217b5e78decf9ac6b4b9b7c93fe3b63
|
[
"MIT"
] | null | null | null |
class Sweepstakes_Stack_Manager:
def __init__(self, stack):
self.sweepstakes_stack_manager = Sweepstakes_Stack_Manager
self.stack = stack
def insert_sweepstakes(sweepstakes): pass
def get_sweepstakes(): Sweepstake
| 30.375
| 66
| 0.748971
| 27
| 243
| 6.296296
| 0.407407
| 0.282353
| 0.405882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1893
| 243
| 8
| 67
| 30.375
| 0.862944
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0.166667
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 7
|
4795c5777ce317cc596d9d327ade79109c496477
| 3,231
|
py
|
Python
|
pyaz/acr/private_endpoint_connection/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | null | null | null |
pyaz/acr/private_endpoint_connection/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | null | null | null |
pyaz/acr/private_endpoint_connection/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | 1
|
2022-02-03T09:12:01.000Z
|
2022-02-03T09:12:01.000Z
|
from ... pyaz_utils import _call_az
def delete(name, registry_name, resource_group=None):
'''
Delete a private endpoint connection request for a container registry
Required Parameters:
- name -- The name of the private endpoint connection
- registry_name -- The name of the container registry. You can configure the default registry name using `az configure --defaults acr=<registry name>`
Optional Parameters:
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
'''
return _call_az("az acr private-endpoint-connection delete", locals())
def show(name, registry_name, resource_group=None):
'''
Show details of a container registry's private endpoint connection
Required Parameters:
- name -- The name of the private endpoint connection
- registry_name -- The name of the container registry. You can configure the default registry name using `az configure --defaults acr=<registry name>`
Optional Parameters:
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
'''
return _call_az("az acr private-endpoint-connection show", locals())
def list(registry_name, resource_group=None):
'''
List all private endpoint connections to a container registry
Required Parameters:
- registry_name -- The name of the container registry. You can configure the default registry name using `az configure --defaults acr=<registry name>`
Optional Parameters:
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
'''
return _call_az("az acr private-endpoint-connection list", locals())
def approve(name, registry_name, description=None, resource_group=None):
'''
Approve a private endpoint connection request for a container registry
Required Parameters:
- name -- The name of the private endpoint connection
- registry_name -- The name of the container registry. You can configure the default registry name using `az configure --defaults acr=<registry name>`
Optional Parameters:
- description -- Approval description. For example, the reason for approval.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
'''
return _call_az("az acr private-endpoint-connection approve", locals())
def reject(name, registry_name, description=None, resource_group=None):
'''
Reject a private endpoint connection request for a container registry
Required Parameters:
- name -- The name of the private endpoint connection
- registry_name -- The name of the container registry. You can configure the default registry name using `az configure --defaults acr=<registry name>`
Optional Parameters:
- description -- Rejection description. For example, the reason for rejection.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
'''
return _call_az("az acr private-endpoint-connection reject", locals())
| 44.260274
| 154
| 0.735067
| 418
| 3,231
| 5.602871
| 0.114833
| 0.102477
| 0.13877
| 0.076857
| 0.885141
| 0.857387
| 0.801025
| 0.801025
| 0.760034
| 0.760034
| 0
| 0
| 0.185701
| 3,231
| 72
| 155
| 44.875
| 0.890156
| 0.715258
| 0
| 0
| 0
| 0
| 0.273342
| 0.182679
| 0
| 0
| 0
| 0
| 0
| 1
| 0.454545
| false
| 0
| 0.090909
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
4798a1130ed2b0b345e28b0a0b2b2ed791b4915d
| 56,730
|
py
|
Python
|
watevrCTF-2019/challenges/reverse/watshell/solve.py
|
bemrdo/CTF-2019
|
424512f7c43278d72091aa737da78907c14f9fc1
|
[
"MIT"
] | null | null | null |
watevrCTF-2019/challenges/reverse/watshell/solve.py
|
bemrdo/CTF-2019
|
424512f7c43278d72091aa737da78907c14f9fc1
|
[
"MIT"
] | null | null | null |
watevrCTF-2019/challenges/reverse/watshell/solve.py
|
bemrdo/CTF-2019
|
424512f7c43278d72091aa737da78907c14f9fc1
|
[
"MIT"
] | 1
|
2020-03-14T07:24:12.000Z
|
2020-03-14T07:24:12.000Z
|
import time
from pwn import *
flag = input("flag: ").replace("\n", "")
ip, port = input("service: ").split(":")
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#here is the map for the first 9000 or so numbers. wtih it we can find an index that has the ordinal we want and then get the index and input that
searchfor = "give_me_the_flag_please"
what_to_input = " ".join([str(mapping.index(str(ord(x)))) for x in searchfor]) + " "
r = remote(str(ip), int(port))
r.sendline(what_to_input) #send rsa encrypted for /bin/sh
time.sleep(0.1)
resp = str(r.recvuntil("}", timeout=10))
print(resp)
if flag in resp:
exit(0)
exit(1)
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0
| 10
|
47e6d19b8ef19612996066bc83832671282b29dd
| 11,652
|
py
|
Python
|
icumove/samples/models.py
|
gblanchard4/ICU_Move
|
a93728b084bc68087c8a8afa67e3cf1cae98975e
|
[
"MIT"
] | null | null | null |
icumove/samples/models.py
|
gblanchard4/ICU_Move
|
a93728b084bc68087c8a8afa67e3cf1cae98975e
|
[
"MIT"
] | null | null | null |
icumove/samples/models.py
|
gblanchard4/ICU_Move
|
a93728b084bc68087c8a8afa67e3cf1cae98975e
|
[
"MIT"
] | null | null | null |
from django.db import models
from django.core.exceptions import ValidationError
from datetime import date
from django.core.validators import MaxValueValidator, MinValueValidator
# Global values
DAY_1 = date(2015,07,28)
# Air sample model
class Air(models.Model):
ICU_CHOICES = (
('1', 'UMC Tower-1'),
('2', 'UMC Tower-2'),
('3', 'UMC Tower-3')
)
COLOR_CHOICES = (
('R', 'Red'),
('G', 'Green'),
('P', 'Purple')
)
PUMP_CHOICES = (
('A', 'ICS Station A'),
('B', 'ICS Station B'),
('C', 'ICS Station C'),
('E', 'Exterior')
)
SIDE_CHOICES = (
('1', 'Filter 1'),
('2', 'Filter 2')
)
# DateTime
sample_date = models.DateField(verbose_name="Sample Date: Date of Deployment")
#time = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(24)], verbose_name="Hour of Sample: 24hr Clock")
# Sample Information
icu = models.CharField(max_length=1, choices=ICU_CHOICES, verbose_name='ICU Location')
color = models.CharField(max_length=1, choices=COLOR_CHOICES, verbose_name='Tape Color')
pump = models.CharField(max_length=1, choices=PUMP_CHOICES, verbose_name='Pump Letter')
side = models.CharField(max_length=1, choices=SIDE_CHOICES, verbose_name='Pump Side')
# Storage Location
rack = models.CharField(max_length=2, verbose_name='Freezer Rack', blank=True)
box = models.CharField(max_length=2, verbose_name='Box', blank=True)
# Calculated
day = models.CharField(max_length=2, default='00')
uid = models.CharField(primary_key=True, max_length=16, unique=True)
# Notes
notes = models.TextField(verbose_name="Notes", blank=True)
def __str__(self):
return str("A-{}-{}{}-{}".format(self.color, self.pump, self.side, self.sample_date.strftime('%m%d%y')))
# Unique together
class Meta:
unique_together = ("sample_date", "icu", "pump", "side")
unique_together = ("rack", "box")
def clean(self):
# Validate unique Freezer/Shelf/Rack/Box
#Ehhh
# Validate Tower to Color
tower_to_color_dict = {'1':'R','2':'G','3':'P'}
if not tower_to_color_dict[self.icu] == self.color:
raise ValidationError("{} is not the right color for tower {}".format(self.color, self.icu))
def save(self):
# calculate day from DAY_1
self.day = "%02d" % (self.sample_date - DAY_1).days
# UID
self.uid = str("A-{}-{}{}-{}".format(self.color, self.pump, self.side, self.sample_date.strftime('%m%d%y')))
super(Air, self).save()
class Stool(models.Model):
ICU_CHOICES = (
('M', 'ILH M-ICU'),
('T', 'ILH T-ICU'),
('1', 'UMC Tower-1'),
('2', 'UMC Tower-2'),
('3', 'UMC Tower-3')
)
PRESSURE_CHOICES = (
('NAN', 'Not Pressured'),
('NEG', 'Negative Pressure'),
('POS', 'Positive Pressure')
)
#DateTime
sample_date = models.DateField(verbose_name="Date Collected")
time = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(24)], verbose_name="Hour Sample Collected (24hr Clock)")
# Sample Location
icu = models.CharField(max_length=1, choices=ICU_CHOICES, verbose_name="ICU Location")
room = models.CharField(max_length=4, verbose_name="Room Number")
# Metadata
emr = models.CharField(max_length=10, verbose_name="Epic Medical Record Number")
emr_check = models.CharField(max_length=10, verbose_name="Epic Medical Record Number")
# Storage Location
rack = models.CharField(max_length=2, verbose_name='Freezer Rack', blank=True)
box = models.CharField(max_length=2, verbose_name='Box', blank=True)
# Calculated
day = models.CharField(max_length=2, default='00')
uid = models.CharField(primary_key=True, max_length=27, unique=True)
pressure = models.CharField(max_length=3, choices=PRESSURE_CHOICES, verbose_name="Room pressure")
# Notes
notes = models.TextField(verbose_name="Notes", blank=True)
def __str__(self):
return str("S-{}-{}-{}".format(self.room, self.sample_date.strftime('%m%d'), "%02d" % self.time))
# Unique together
class Meta:
unique_together = ("sample_date", "time", "icu", "room", "emr")
# Clean Overide for Validation
def clean(self):
if not self.emr == self.emr_check:
raise ValidationError('EMR Does not match')
# Validate Room numbers for POG
valid_room_enders = ['15','16','17','18','19','20','32','33','34','35','36','37','41','42','43','44','45','46','61','62','63','64','65','66']
if self.icu in ['1', '2,', '3']:
if not self.icu == self.room[1]:
raise ValidationError('Room %s can not be in tower %s' % (self.room, self.icu))
if not self.room[2::] in valid_room_enders:
raise ValidationError('Room %s is not a valid room, hint check %s' % (self.room, self.room[2::]))
def save(self):
# calculate day from DAY_1
self.day = "%02d" % (self.sample_date - DAY_1).days
# UID
self.uid = str("S-{}-{}-{}".format(self.room, self.sample_date.strftime('%m%d%y'), "%02d" % self.time))
# Pressure
neg_pressure_rooms = ['4115','4116','4117','4141','4142','4143','4215','4241','4315','4341']
if self.room in neg_pressure_rooms:
self.pressure = "NEG"
else:
self.pressure = "NOR"
super(Stool, self).save()
class Environment(models.Model):
# DateTime
sample_date = models.DateField(verbose_name="Sample Date")
#time = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(24)], verbose_name="Hour of Sample (24-hour Clock")
exterior_temp = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(50)], verbose_name="Exterior: Temperature in C", blank=True, null=True)
exterior_humi = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(100)], verbose_name="Exterior: Percent Relative Humidity", blank=True, null=True)
exterior_pres = models.IntegerField(validators=[MinValueValidator(740), MaxValueValidator(780)], verbose_name="Exterior: Barometric Pressure", blank=True, null=True)
# Tower-1
tower1_B_temp = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(50)], verbose_name="ICS-B: Temperature in C", blank=True, null=True)
tower1_B_humi = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(100)], verbose_name="ICS-B: Percent Relative Humidity", blank=True, null=True)
tower1_B_pres = models.IntegerField(validators=[MinValueValidator(740), MaxValueValidator(780)], verbose_name="ICS-B: Barometric Pressure", blank=True, null=True)
# Tower-2
tower2_B_temp = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(50)], verbose_name="ICS-B: Temperature in C", blank=True, null=True)
tower2_B_humi = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(100)], verbose_name="ICS-B: Percent Relative Humidity", blank=True, null=True)
tower2_B_pres = models.IntegerField(validators=[MinValueValidator(740), MaxValueValidator(780)], verbose_name="ICS-B: Barometric Pressure", blank=True, null=True)
# Tower-3
tower3_A_temp = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(50)], verbose_name="ICS-A: Temperature in C", blank=True, null=True)
tower3_A_humi = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(100)], verbose_name="ICS-A: Percent Relative Humidity", blank=True, null=True)
tower3_A_pres = models.IntegerField(validators=[MinValueValidator(740), MaxValueValidator(780)], verbose_name="ICS-A: Barometric Pressure", blank=True, null=True)
# Calculated
day = models.CharField(max_length=2, default='00')
# Notes
notes = models.TextField(verbose_name="Notes", blank=True)
def __str__(self):
return str("E-{}".format(self.sample_date.strftime('%m%d%y')))
def save(self):
# calculate day from DAY_1
self.day = "%02d" % (self.sample_date - DAY_1).days
super(Environment, self).save()
class Toilet(models.Model):
ICU_CHOICES = (
('1', 'UMC Tower-1'),
('2', 'UMC Tower-2'),
('3', 'UMC Tower-3')
)
# DateTime
sample_date = models.DateField(verbose_name="Sample Date")
# Sample Location
icu = models.CharField(max_length=1, choices=ICU_CHOICES, verbose_name='ICU Location')
room = models.CharField(max_length=4, verbose_name="Room Number")
# Storage Location
rack = models.CharField(max_length=2, verbose_name='Freezer Rack', blank=True)
box = models.CharField(max_length=2, verbose_name='Box', blank=True)
# Calculated
day = models.CharField(max_length=2, default='00')
uid = models.CharField(primary_key=True, max_length=16, unique=True)
# Notes
notes = models.TextField(verbose_name="Notes", blank=True)
def __str__(self):
return str("T-{}-{}".format(self.room, self.sample_date.strftime('%m%d%y')))
# Unique together
class Meta:
unique_together = ("icu", "room", "sample_date")
def clean(self):
# Validate unique Freezer/Shelf/Rack/Box
# Validate Room numbers for POG
if not self.icu == self.room[1]:
raise ValidationError('Room %s can not be in tower %s' % (self.room, self.icu))
valid_room_enders = ['15','16','17','18','19','20','32','33','34','35','36','37','41','42','43','44','45','46','61','62','63','64','65','66']
if not self.room[2::] in valid_room_enders:
raise ValidationError('Room %s is not a valid room, hint check %s' % (self.room, self.room[2::]))
def save(self):
# calculate day from DAY_1
self.day = "%02d" % (self.sample_date - DAY_1).days
# UID
self.uid = str("T-{}-{}".format(self.room, self.sample_date.strftime('%m%d%y')))
super(Toilet, self).save()
# class Door(models.Model):
# sample_date = models.DateField(verbose_name="Sample Date")
# time = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(24)], verbose_name="Hour of Sample (24-hour Clock")
# icu = models.CharField(max_length=1, choices=ICU_CHOICES, verbose_name='ICU Location')
# day = models.CharField(max_length=2, default='00')
# uid = models.CharField(primary_key=True, max_length=16, unique=True)
# # Storage Location
# rack = models.CharField(max_length=2, verbose_name='Freezer Rack', blank=True)
# shelf = models.CharField(max_length=2, verbose_name='Shelf', blank=True)
# box = models.CharField(max_length=2, verbose_name='Box', blank=True)
# def __str__(self):
# return str("D-{}-{}-{}-{}DC{}".format(self.icu, self.sample_date.strftime('%m%d'), self.time, self.icu, self.day))
# # Unique together
# class Meta:
# unique_together = ("sample_date", "icu", "day")
# def save(self):
# # calculate day from DAY_1
# self.day = "%02d" % (self.sample_date - DAY_1).days
# # UID
# self.uid = str("D-{}-{}-{}-{}DC{}".format(self.icu, self.sample_date.strftime('%m%d'), self.time, self.icu, self.day))
# super(Door, self).save()
# class Floor(models.Model):
# sample_date = models.DateField(verbose_name="Sample Date")
# time = models.IntegerField(validators=[MinValueValidator(0), MaxValueValidator(24)], verbose_name="Hour of Sample (24-hour Clock")
# icu = models.CharField(max_length=1, choices=ICU_CHOICES, verbose_name="ICU Location")
# day = models.CharField(max_length=2, default='00')
# uid = models.CharField(primary_key=True, max_length=16, unique=True)
# # Storage Location
# rack = models.CharField(max_length=2, verbose_name='Freezer Rack', blank=True)
# shelf = models.CharField(max_length=2, verbose_name='Shelf', blank=True)
# box = models.CharField(max_length=2, verbose_name='Box', blank=True)
# def __str__(self):
# return str("F-{}-{}-{}-{}FC{}".format(self.icu, self.sample_date.strftime('%m%d'), self.time, self.icu, self.day))
# # Unique together
# class Meta:
# unique_together = ("sample_date", "icu", "day")
# def save(self):
# # calculate day from DAY_1
# self.day = "%02d" % (self.sample_date - DAY_1).days
# # UID
# self.uid = str("F-{}-{}-{}-{}FC{}".format(self.icu, self.sample_date.strftime('%m%d'), self.time, self.icu, self.day))
# super(Floor, self).save()
| 41.173145
| 170
| 0.702712
| 1,649
| 11,652
| 4.831413
| 0.124318
| 0.071796
| 0.070039
| 0.093385
| 0.823397
| 0.815112
| 0.794402
| 0.762897
| 0.755742
| 0.728254
| 0
| 0.034251
| 0.120494
| 11,652
| 282
| 171
| 41.319149
| 0.743169
| 0.272657
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| 0.427586
| 0
| 0
| 0.176611
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.027586
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| null | 0
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| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
9a5886535bdcca3053981250a5563d6ba7b5c356
| 198
|
py
|
Python
|
tests/test_unit/test_formatters.py
|
best-doctor/Mario
|
a6c83b9f7e7558a4e71d8acb00b8d164fe8eec6f
|
[
"MIT"
] | 12
|
2020-01-30T02:19:16.000Z
|
2022-01-20T04:00:43.000Z
|
tests/test_unit/test_formatters.py
|
best-doctor/Mario
|
a6c83b9f7e7558a4e71d8acb00b8d164fe8eec6f
|
[
"MIT"
] | 32
|
2019-12-07T14:06:05.000Z
|
2020-06-26T07:12:03.000Z
|
tests/test_unit/test_formatters.py
|
best-doctor/Mario
|
a6c83b9f7e7558a4e71d8acb00b8d164fe8eec6f
|
[
"MIT"
] | 3
|
2020-08-21T07:54:53.000Z
|
2021-01-11T12:05:48.000Z
|
from super_mario.utils.formatters import format_object_for_logging
def test_format_object_for_logging():
assert format_object_for_logging(list(range(100)), max_length=10) == '[0, 1, 2, 3...]'
| 33
| 90
| 0.772727
| 31
| 198
| 4.548387
| 0.741935
| 0.255319
| 0.319149
| 0.468085
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.050562
| 0.10101
| 198
| 5
| 91
| 39.6
| 0.741573
| 0
| 0
| 0
| 0
| 0
| 0.075758
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
9a640fdfdda9f6062d7f3e5b1fbefbcf9e97cd86
| 81
|
py
|
Python
|
model/__init__.py
|
SCUT-BIP-Lab/SCUT-DHGA
|
1a75998b4ddc09e21da9352e6a51bed0c39ddfb8
|
[
"MIT"
] | 6
|
2020-10-06T07:43:33.000Z
|
2022-03-21T00:12:27.000Z
|
model/__init__.py
|
SCUT-BIP-Lab/SCUT-DHGA
|
1a75998b4ddc09e21da9352e6a51bed0c39ddfb8
|
[
"MIT"
] | null | null | null |
model/__init__.py
|
SCUT-BIP-Lab/SCUT-DHGA
|
1a75998b4ddc09e21da9352e6a51bed0c39ddfb8
|
[
"MIT"
] | 2
|
2021-12-23T11:37:15.000Z
|
2021-12-24T02:24:13.000Z
|
from model.i3d_auth import i3d_auth
from model.i3d_auth_RGBD import i3d_auth_RGBD
| 40.5
| 45
| 0.888889
| 16
| 81
| 4.125
| 0.375
| 0.424242
| 0.363636
| 0.484848
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.054054
| 0.08642
| 81
| 2
| 45
| 40.5
| 0.837838
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
7bd157150b4415d58d59e7bfbbc788261860b6e3
| 5,134
|
py
|
Python
|
tests/contrib/test_automl_sklearn_unsupervised.py
|
fsadannn/autogoal
|
ad23f0a3dcb5d4658bbc6b68a5b428d8de7432de
|
[
"MIT"
] | 1
|
2021-11-04T03:47:38.000Z
|
2021-11-04T03:47:38.000Z
|
tests/contrib/test_automl_sklearn_unsupervised.py
|
cbermudez97/autogoal
|
fd45110b01c55a5f51ed440a1a4f093d8afbb9ac
|
[
"MIT"
] | null | null | null |
tests/contrib/test_automl_sklearn_unsupervised.py
|
cbermudez97/autogoal
|
fd45110b01c55a5f51ed440a1a4f093d8afbb9ac
|
[
"MIT"
] | null | null | null |
from autogoal.kb import MatrixContinuousDense, Supervised, VectorCategorical
from autogoal.ml import AutoML, calinski_harabasz_score
import numpy as np
def test_run_unsupervised():
X = np.array(
[
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
1.0,
0.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
1.0,
0.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
1.0,
0.0,
0.0,
],
[
0.0,
0.0,
0.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
1.0,
0.0,
0.0,
1.0,
0.0,
],
]
)
automl = AutoML(
input=MatrixContinuousDense,
output=VectorCategorical,
score_metric=calinski_harabasz_score,
search_timeout=120,
)
automl.fit(X, logger=loggers)
| 20.618474
| 76
| 0.140242
| 465
| 5,134
| 1.531183
| 0.068817
| 0.839888
| 1.082865
| 1.207865
| 0.589888
| 0.589888
| 0.589888
| 0.589888
| 0.589888
| 0.589888
| 0
| 0.3525
| 0.766264
| 5,134
| 248
| 77
| 20.701613
| 0.240833
| 0
| 0
| 0.897959
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.004082
| false
| 0
| 0.012245
| 0
| 0.016327
| 0
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
7becbb3850cbef48b78cb7c06bb76da72e9c5614
| 4,956
|
py
|
Python
|
compile_metadata_and_tierpsy_analysis_files/compile_window_summaires_and_feat_names.py
|
Tom-OBrien/Disease-Modelling
|
c1a9c3b179ee39a0148ca0bd685c2e0d44202dad
|
[
"CC0-1.0"
] | null | null | null |
compile_metadata_and_tierpsy_analysis_files/compile_window_summaires_and_feat_names.py
|
Tom-OBrien/Disease-Modelling
|
c1a9c3b179ee39a0148ca0bd685c2e0d44202dad
|
[
"CC0-1.0"
] | null | null | null |
compile_metadata_and_tierpsy_analysis_files/compile_window_summaires_and_feat_names.py
|
Tom-OBrien/Disease-Modelling
|
c1a9c3b179ee39a0148ca0bd685c2e0d44202dad
|
[
"CC0-1.0"
] | null | null | null |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 12 14:06:18 2021
@author: tobrien
Script for compliling window summaries and feature names for disease model
screen
"""
from pathlib import Path
from tierpsytools.read_data.compile_features_summaries import compile_tierpsy_summaries
import pdb
import sys
sys.path.insert(0, '/Users/tobrien/analysis_repo')
from summarieshelper import (
concatenate_day_summaries,
fnamesfeatsmeta_filt_to_full,
parse_window_number,
detect_outliers,
plot_pccontours_2groups_animate,
)
sum_root_dir = Path('/Volumes/behavgenom$/Tom/Data/Hydra/DiseaseModel/RawData/Results')
list_days = [item for item in sum_root_dir.glob('*/') if item.is_dir() and str(item.stem).startswith('20')]
win_0_fnames_df, win_0_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='0')
win_0_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_0.csv')
win_0_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_0.csv')
win_1_fnames_df, win_1_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='1')
win_1_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_1.csv')
win_1_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_1.csv')
win_2_fnames_df, win_2_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='2')
win_2_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_2.csv')
win_2_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_2.csv')
win_3_fnames_df, win_3_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='3')
win_3_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_3.csv')
win_3_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_3.csv')
win_4_fnames_df, win_4_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='4')
win_4_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_4.csv')
win_4_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_4.csv')
win_5_fnames_df, win_5_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='5')
win_5_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_5.csv')
win_5_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_5.csv')
win_6_fnames_df, win_6_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='6')
win_6_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_6.csv')
win_6_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_6.csv')
win_7_fnames_df, win_7_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='7')
win_7_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_7.csv')
win_7_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_7.csv')
win_8_fnames_df, win_8_feats_df = concatenate_day_summaries(
sum_root_dir, list_days,
window='8')
win_8_fnames_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/filenames_summary_tierpsy_plate_filtered_traj_compiled_window_8.csv')
win_8_feats_df.to_csv('/Users/tobrien/Documents/Imperial : MRC/Disease Model Screen/window_summaries/features_summary_tierpsy_plate_filtered_traj_compiled_window_8.csv')
| 53.869565
| 171
| 0.819209
| 738
| 4,956
| 5.01897
| 0.139566
| 0.076944
| 0.092333
| 0.058315
| 0.800216
| 0.800216
| 0.800216
| 0.800216
| 0.800216
| 0.798056
| 0
| 0.018117
| 0.097861
| 4,956
| 92
| 172
| 53.869565
| 0.810333
| 0.03632
| 0
| 0.152542
| 0
| 0
| 0.567534
| 0.485529
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.084746
| 0
| 0.084746
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 1
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d08ffb7b290b3a41f5525b3d3f8f845f944964f1
| 134
|
py
|
Python
|
auxein/parents/distributions/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | 1
|
2019-05-08T14:53:27.000Z
|
2019-05-08T14:53:27.000Z
|
auxein/parents/distributions/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | 2
|
2020-08-26T09:16:47.000Z
|
2020-10-30T16:47:03.000Z
|
auxein/parents/distributions/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | null | null | null |
# flake8: noqa
from .core import Distribution
from .core import Fps
from .core import FpsWithWindowing
from .core import SigmaScaling
| 22.333333
| 34
| 0.813433
| 18
| 134
| 6.055556
| 0.5
| 0.293578
| 0.513761
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008696
| 0.141791
| 134
| 5
| 35
| 26.8
| 0.93913
| 0.089552
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| 0
| 0
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| 0
| 1
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| true
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
efcbe52c6d670d0deded824b643f49d588de7269
| 234
|
py
|
Python
|
param_teller/__init__.py
|
chanzuckerberg/param-teller
|
6c69bd619a80fbb1a1141be679a80c2c7db258b1
|
[
"MIT"
] | null | null | null |
param_teller/__init__.py
|
chanzuckerberg/param-teller
|
6c69bd619a80fbb1a1141be679a80c2c7db258b1
|
[
"MIT"
] | null | null | null |
param_teller/__init__.py
|
chanzuckerberg/param-teller
|
6c69bd619a80fbb1a1141be679a80c2c7db258b1
|
[
"MIT"
] | null | null | null |
from param_teller.parameter_store import ParameterStore
from param_teller.secrets_manager import SecretsManager
from param_teller.project_store import ProjectParameterStore
from param_teller.project_store import ProjectSecretsManager
| 46.8
| 60
| 0.91453
| 28
| 234
| 7.357143
| 0.464286
| 0.174757
| 0.291262
| 0.213592
| 0.320388
| 0.320388
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068376
| 234
| 4
| 61
| 58.5
| 0.944954
| 0
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| 0
| true
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| 0
| 1
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| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
| 0
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
3229a6ec9758a0ad4339e4327b972aac2cb1af3b
| 151
|
py
|
Python
|
earthvision2021/utils/criteria/__init__.py
|
solcummings/earthvision2021-weakly-supervised
|
d008a3cd7bf53ee43aa3c2682416954d6a5bb102
|
[
"Apache-2.0"
] | 9
|
2021-06-19T20:26:40.000Z
|
2022-03-17T08:39:59.000Z
|
earthvision2021/utils/criteria/__init__.py
|
solcummings/earthvision2021-weakly-supervised
|
d008a3cd7bf53ee43aa3c2682416954d6a5bb102
|
[
"Apache-2.0"
] | 2
|
2021-12-21T07:42:21.000Z
|
2022-01-23T02:10:32.000Z
|
earthvision2021/utils/criteria/__init__.py
|
solcummings/earthvision2021-weakly-supervised
|
d008a3cd7bf53ee43aa3c2682416954d6a5bb102
|
[
"Apache-2.0"
] | null | null | null |
from utils.criteria.build import build
from utils.criteria import jaccard_loss
from utils.criteria import dice_loss
from utils.criteria import metric
| 25.166667
| 39
| 0.854305
| 23
| 151
| 5.521739
| 0.391304
| 0.283465
| 0.535433
| 0.543307
| 0.425197
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112583
| 151
| 5
| 40
| 30.2
| 0.947761
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| 0
| 1
| 0
|
0
| 8
|
32303ac583006ab2bc12e153c601ea71cbc36829
| 7,955
|
py
|
Python
|
sdi_pipeline/test.py
|
andrewhstewart/SDI
|
19d52bd5e13c2128c083776712672becf8b6ab45
|
[
"MIT"
] | null | null | null |
sdi_pipeline/test.py
|
andrewhstewart/SDI
|
19d52bd5e13c2128c083776712672becf8b6ab45
|
[
"MIT"
] | null | null | null |
sdi_pipeline/test.py
|
andrewhstewart/SDI
|
19d52bd5e13c2128c083776712672becf8b6ab45
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Sep 29 13:10:04 2018
@author: andrew
"""
import requests
from initialize import loc
import obtain
import os
import ref_image
import align_astroalign
import combine_numpy
from astropy.io import fits
from scipy.ndimage.filters import gaussian_filter
import numpy as np
import glob
import sex
import psf
import subtract_ais
import align_chi2
import align_imreg
import align_skimage
import check_saturation
def TEST():
#get data from LCO public archive and put in target directory under 'TEST' folder
print("-> Getting data from LCO...")
response = requests.get('https://archive-api.lco.global/frames/?' +
'RLEVEL=91&' +
'PROPID='+'standard&'
'OBJECT='+'L113&' +
'FILTER='+'B&'
'start='+'2018-9-14'+'&' +
'end='+'2018-9-15'+'&'
).json()
frames = response['results']
#delete bad images
del_fr = []
for fr in frames:
if fr['id'] != 9602135 and fr['id'] != 9602132:
del_fr.append(fr)
for delete in del_fr:
del frames[frames.index(delete)]
#download data
temp_loc = loc + '/sdi/temp/'
os.mkdir(temp_loc+'test_data')
for frame in frames:
with open(temp_loc + 'test_data/' + frame['filename'], 'wb') as f:
f.write(requests.get(frame['url']).content)
#funpack and move to 'TEST' folder
obtain.process()
obtain.movetar()
old_data_location = obtain.rename()
data_location = old_data_location.replace('L113', 'TEST')
os.rename(old_data_location[:29], data_location[:29])
#align and combine images
test_loc = data_location[:-5]
check_saturation.check_saturate(test_loc + '/data')
ref_image.ref_image(test_loc + '/data')
align_astroalign.align2(test_loc + '/data')
# align_skimage.skimage(test_loc + '/data')
combine_numpy.combine_median(test_loc + '/data')
# align_skimage.skimage_template(test_loc + '/data')
#add three fake stars to reference image
print("\n-> Adding fake stars to test image...")
hdu = fits.getdata(test_loc + '/data/09:14:00.260_A_.fits')
h, w = img_shape = np.shape(hdu)
pos_x = [1500,2000,1200]
pos_y = [1600,1400,2200]
array = np.array([ 0.65343465, 0.50675629, 0.84946314])
fluxes = 2000000.0 + array * 300.0
img = np.zeros(img_shape)
for x, y, f in zip(pos_x, pos_y, fluxes):
img[x, y] = f
img = gaussian_filter(img, sigma=15.0, mode='constant')
final = fits.PrimaryHDU(hdu+img)
final.writeto(test_loc + '/data/09:14:00.260_A_.fits', overwrite=True)
#subtract images using ISIS
subtract_ais.isis_sub_test(test_loc)
#get PSFs then perform SExtractor on residual images
sex.sextractor_psf(test_loc)
psf.psfex(test_loc)
sex.sextractor(test_loc)
#test the results of the test function against known values
# with open(test_loc + '/sources/sources.txt', 'r') as source:
# lines = source.readlines()
# source.close()
#
# with open(os.path.dirname(sex.__file__) + '/test_config/test_sources.txt', 'r') as test_source:
# lines2 = test_source.readlines()
# test_source.close()
res_image_loc = os.path.dirname(sex.__file__) + '/test_config/09:14:00.260_A_residual_.fits'
test_image_data = fits.getdata(res_image_loc)
residual = glob.glob(test_loc + '/residuals/*_A_residual_.fits')
residual_data = fits.getdata(residual[0])
#
# if lines == lines2:
# print("\t-> Sources matched to control")
if test_image_data.all() == residual_data.all():
print("-> Residuals matched to control\n-> TEST SUCCESSFUL!")
# if lines == lines2 and test_image_data.all() == residual_data.all():
# print("\t-> Test successful!")
if test_image_data.all() != residual_data.all():
print("-> Test failure: Results do not match controls")
#display final residual test image
os.system('ds9 %s -scale zscale' % (residual[0]))
if __name__ == '__main__':
#get data from LCO public archive and put in target directory under 'TEST' folder
print("-> Getting data from LCO...")
response = requests.get('https://archive-api.lco.global/frames/?' +
'RLEVEL=91&' +
'PROPID='+'standard&'
'OBJECT='+'L113&' +
'FILTER='+'B&'
'start='+'2018-9-14'+'&' +
'end='+'2018-9-15'+'&'
).json()
frames = response['results']
#delete bad images
del_fr = []
for fr in frames:
if fr['id'] != 9602135 and fr['id'] != 9602132:
del_fr.append(fr)
for delete in del_fr:
del frames[frames.index(delete)]
#download data
temp_loc = loc + '/sdi/temp/'
os.mkdir(temp_loc+'test_data')
for frame in frames:
with open(temp_loc + 'test_data/' + frame['filename'], 'wb') as f:
f.write(requests.get(frame['url']).content)
#funpack and move to 'TEST' folder
obtain.process()
obtain.movetar()
old_data_location = obtain.rename()
data_location = old_data_location.replace('L113', 'TEST')
os.rename(old_data_location[:29], data_location[:29])
#align and combine images
test_loc = data_location[:-5]
check_saturation.check_saturate(test_loc + '/data')
ref_image.ref_image(test_loc + '/data')
align_astroalign.align2(test_loc + '/data')
# align_skimage.skimage(test_loc + '/data')
combine_numpy.combine_median(test_loc + '/data')
# align_skimage.skimage_template(test_loc + '/data')
#add three fake stars to reference image
print("\n-> Adding fake stars to test image...")
hdu = fits.getdata(test_loc + '/data/09:14:00.260_A_.fits')
h, w = img_shape = np.shape(hdu)
pos_x = [1500,2000,1200]
pos_y = [1600,1400,2200]
array = np.array([ 0.65343465, 0.50675629, 0.84946314])
fluxes = 2000000.0 + array * 300.0
img = np.zeros(img_shape)
for x, y, f in zip(pos_x, pos_y, fluxes):
img[x, y] = f
img = gaussian_filter(img, sigma=15.0, mode='constant')
final = fits.PrimaryHDU(hdu+img)
final.writeto(test_loc + '/data/09:14:00.260_A_.fits', overwrite=True)
#subtract images using ISIS
subtract_ais.isis_sub_test(test_loc)
#get PSFs then perform SExtractor on residual images
sex.sextractor_psf(test_loc)
psf.psfex(test_loc)
sex.sextractor(test_loc)
#test the results of the test function against known values
# with open(test_loc + '/sources/sources.txt', 'r') as source:
# lines = source.readlines()
# source.close()
#
# with open(os.path.dirname(sex.__file__) + '/test_config/test_sources.txt', 'r') as test_source:
# lines2 = test_source.readlines()
# test_source.close()
res_image_loc = os.path.dirname(sex.__file__) + '/test_config/09:14:00.260_A_residual_.fits'
test_image_data = fits.getdata(res_image_loc)
residual = glob.glob(test_loc + '/residuals/*_A_residual_.fits')
residual_data = fits.getdata(residual[0])
#
# if lines == lines2:
# print("\t-> Sources matched to control")
if test_image_data.all() == residual_data.all():
print("-> Residuals matched to control\n-> TEST SUCCESSFUL!")
# if lines == lines2 and test_image_data.all() == residual_data.all():
# print("\t-> Test successful!")
if test_image_data.all() != residual_data.all():
print("-> Test failure: Results do not match controls")
#display final residual test image
os.system('ds9 %s -scale zscale' % (residual[0]))
| 34.586957
| 100
| 0.612319
| 1,059
| 7,955
| 4.407932
| 0.203966
| 0.044987
| 0.042416
| 0.020566
| 0.916881
| 0.916881
| 0.916881
| 0.916881
| 0.916881
| 0.916881
| 0
| 0.049933
| 0.252294
| 7,955
| 230
| 101
| 34.586957
| 0.734869
| 0.249403
| 0
| 0.850746
| 0
| 0
| 0.174472
| 0.041589
| 0.029851
| 0
| 0
| 0
| 0
| 1
| 0.007463
| false
| 0
| 0.134328
| 0
| 0.141791
| 0.059701
| 0
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| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
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| null | 0
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| 0
| 0
|
0
| 7
|
329edb5f87b9ce4a481fb66c756c66e9bb5704f9
| 14,374
|
py
|
Python
|
src/seg_nets/keras_models.py
|
NickleDave/compare-seg-models
|
dd98954509344abfe39ba676646c1ab374a9ff88
|
[
"BSD-3-Clause"
] | null | null | null |
src/seg_nets/keras_models.py
|
NickleDave/compare-seg-models
|
dd98954509344abfe39ba676646c1ab374a9ff88
|
[
"BSD-3-Clause"
] | null | null | null |
src/seg_nets/keras_models.py
|
NickleDave/compare-seg-models
|
dd98954509344abfe39ba676646c1ab374a9ff88
|
[
"BSD-3-Clause"
] | null | null | null |
# adapted from [1]_
# and https://github.com/colincsl/TemporalConvolutionalNetworks
#
# [1]René, Colin Lea Michael D. Flynn, and Vidal Austin Reiter Gregory D. Hager.
# "Temporal convolutional networks for action segmentation and detection." (2017).
from keras.models import Model
from keras.layers import Input, TimeDistributed, Add, Multiply, Dense, Reshape
from keras.layers.core import Activation, SpatialDropout1D, Lambda
from keras.layers.convolutional import Conv1D, Conv2D, ZeroPadding1D, Cropping1D
from keras.layers.convolutional import MaxPooling1D, MaxPooling2D, UpSampling1D
from keras.layers import Bidirectional
from keras.layers.recurrent import LSTM
from keras import regularizers
import tensorflow as tf
from keras import backend as K
from keras.activations import relu
from functools import partial
clipped_relu = partial(relu, max_value=5)
# utility functions
def max_filter(x):
# Max over the best filter score (like ICRA paper)
max_values = K.max(x, 2, keepdims=True)
max_flag = tf.greater_equal(x, max_values)
out = x * tf.cast(max_flag, tf.float32)
return out
def channel_normalization(x):
# Normalize by the highest activation
max_values = K.max(K.abs(x), 2, keepdims=True)+1e-5
out = x / max_values
return out
def WaveNet_activation(x):
tanh_out = Activation('tanh')(x)
sigm_out = Activation('sigmoid')(x)
return Multiply()([tanh_out, sigm_out])
def pool_output(input, pool_size, stride):
return ((input - pool_size) // stride) + 1
def upsample_output(input, size):
return input * size
def ed_tcn_output_size(input, n_nodes, pool_size=2):
output = input
for encoder_layer in range(len(n_nodes)):
output = pool_output(output, pool_size, pool_size)
for decoder_layer in range(len(n_nodes)):
output = upsample_output(output, pool_size)
return output
# models
def ED_TCN(n_nodes, conv_len, n_classes, n_feat, max_len,
loss='categorical_crossentropy', causal=False,
optimizer="rmsprop", activation='norm_relu'):
n_layers = len(n_nodes)
inputs = Input(shape=(max_len, n_feat))
model = inputs
# ---- Encoder ----
for i in range(n_layers):
# Pad beginning of sequence to prevent usage of future data
if causal: model = ZeroPadding1D((conv_len // 2, 0))(model)
model = Conv1D(n_nodes[i], conv_len, padding='same',
kernel_regularizer=regularizers.l2(0.001))(model)
if causal: model = Cropping1D((0, conv_len // 2))(model)
model = SpatialDropout1D(0.3)(model)
if activation == 'norm_relu':
model = Activation('relu')(model)
model = Lambda(channel_normalization,
name="encoder_norm_{}".format(i))(model)
elif activation == 'wavenet':
model = WaveNet_activation(model)
else:
model = Activation(activation)(model)
model = MaxPooling1D(2)(model)
# ---- Decoder ----
for i in range(n_layers):
model = UpSampling1D(2)(model)
if causal: model = ZeroPadding1D((conv_len // 2, 0))(model)
model = Conv1D(n_nodes[-i - 1], conv_len, padding='same',
kernel_regularizer=regularizers.l2(0.001))(model)
if causal: model = Cropping1D((0, conv_len // 2))(model)
model = SpatialDropout1D(0.3)(model)
if activation == 'norm_relu':
model = Activation('relu')(model)
model = Lambda(channel_normalization,
name="decoder_norm_{}".format(i))(model)
elif activation == 'wavenet':
model = WaveNet_activation(model)
else:
model = Activation(activation)(model)
# Output FC layer
model = TimeDistributed(Dense(n_classes, activation="softmax",
kernel_regularizer=regularizers.l2(0.001)))(model)
model = Model(inputs=inputs, outputs=model)
model.compile(loss=loss, optimizer=optimizer, metrics=['accuracy'])
return model
def CNN_ED_TCN(n_nodes, conv_len, n_classes, n_feat, max_len,
n_filters_by_layer=(32, 64),
loss='categorical_crossentropy', causal=False,
optimizer="rmsprop", activation='norm_relu'):
inputs = Input(shape=(max_len, n_feat))
# add "channel" for conv2d layers
model = inputs
new_shape = (max_len, n_feat, 1)
model = Reshape(new_shape)(model)
for n_filters in n_filters_by_layer:
model = Conv2D(n_filters, kernel_size=(5, 5),
kernel_regularizer=regularizers.l2(0.001),
padding="same", activation='relu')(model)
model = MaxPooling2D(pool_size=(1, 8),
strides=(1, 8))(model)
shape = model.get_shape().as_list()
new_shape = [shape[1], shape[2] * shape[3]]
# combine filters into one axis so we can apply 1d convolution
model = Reshape(new_shape)(model)
n_layers = len(n_nodes)
# ---- Encoder ----
for i in range(n_layers):
# Pad beginning of sequence to prevent usage of future data
if causal: model = ZeroPadding1D((conv_len // 2, 0))(model)
model = Conv1D(n_nodes[i], conv_len, padding='same',
kernel_regularizer=regularizers.l2(0.001))(model)
if causal: model = Cropping1D((0, conv_len // 2))(model)
model = SpatialDropout1D(0.3)(model)
if activation == 'norm_relu':
model = Activation('relu')(model)
model = Lambda(channel_normalization,
name="encoder_norm_{}".format(i))(model)
elif activation == 'wavenet':
model = WaveNet_activation(model)
else:
model = Activation(activation)(model)
model = MaxPooling1D(2)(model)
# ---- Decoder ----
for i in range(n_layers):
model = UpSampling1D(2)(model)
if causal: model = ZeroPadding1D((conv_len // 2, 0))(model)
model = Conv1D(n_nodes[-i - 1], conv_len, padding='same',
kernel_regularizer=regularizers.l2(0.001))(model)
if causal: model = Cropping1D((0, conv_len // 2))(model)
model = SpatialDropout1D(0.3)(model)
if activation == 'norm_relu':
model = Activation('relu')(model)
model = Lambda(channel_normalization,
name="decoder_norm_{}".format(i))(model)
elif activation == 'wavenet':
model = WaveNet_activation(model)
else:
model = Activation(activation)(model)
# Output FC layer
model = TimeDistributed(Dense(n_classes, activation="softmax",
kernel_regularizer=regularizers.l2(0.001)))(model)
model = Model(inputs=inputs, outputs=model)
model.compile(loss=loss, optimizer=optimizer, metrics=['accuracy'])
return model
def Dilated_TCN(num_feat, num_classes, nb_filters, dilation_depth, nb_stacks,
max_len, activation="wavenet", tail_conv=1,
use_skip_connections=True, causal=False,
optimizer='adam', loss='categorical_crossentropy'):
"""
dilation_depth : number of layers per stack
nb_stacks : number of stacks.
"""
def residual_block(x, s, i, activation):
original_x = x
if causal:
x = ZeroPadding1D(((2 ** i) // 2, 0))(x)
conv = Conv1D(nb_filters, 2, dilation_rate=2 ** i,
padding='same',
name='dilated_conv_%d_tanh_s%d' % (2 ** i, s))(x)
conv = Cropping1D((0, (2 ** i) // 2))(conv)
else:
conv = Conv1D(nb_filters, 3, dilation_rate=2 ** i,
padding='same',
name='dilated_conv_%d_tanh_s%d' % (2 ** i, s),
kernel_regularizer=regularizers.l2(0.001))(x)
conv = SpatialDropout1D(0.3)(conv)
# x = WaveNet_activation(conv)
if activation == 'norm_relu':
x = Activation('relu')(conv)
x = Lambda(channel_normalization)(x)
elif activation == 'wavenet':
x = WaveNet_activation(conv)
else:
x = Activation(activation)(conv)
# res_x = Convolution1D(nb_filters, 1, border_mode='same')(x)
# skip_x = Convolution1D(nb_filters, 1, border_mode='same')(x)
x = Conv1D(nb_filters, 1, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
res_x = Add()([original_x, x])
# return res_x, skip_x
return res_x, x
input_layer = Input(shape=(max_len, num_feat))
skip_connections = []
x = input_layer
if causal:
x = ZeroPadding1D((1, 0))(x)
x = Conv1D(nb_filters, 2, padding='same',
name='initial_conv')(x)
x = Cropping1D((0, 1))(x)
else:
x = Conv1D(nb_filters, 3, padding='same', name='initial_conv',
kernel_regularizer=regularizers.l2(0.001))(x)
for s in range(nb_stacks):
for i in range(0, dilation_depth + 1):
x, skip_out = residual_block(x, s, i, activation)
skip_connections.append(skip_out)
if use_skip_connections:
x = Add()(skip_connections)
x = Activation('relu')(x)
x = Conv1D(nb_filters, tail_conv, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
x = Activation('relu')(x)
x = Conv1D(num_classes, tail_conv, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
x = Activation('softmax', name='output_softmax')(x)
model = Model(inputs=input_layer, outputs=x)
model.compile(loss=loss, optimizer=optimizer,metrics=['accuracy'])
return model
def CNN_Dilated_TCN(num_feat, num_classes, nb_filters, dilation_depth, nb_stacks,
max_len, n_filters_by_layer=(32, 64),activation="wavenet",
tail_conv=1, use_skip_connections=True, causal=False,
optimizer='adam', loss='categorical_crossentropy'):
"""
dilation_depth : number of layers per stack
nb_stacks : number of stacks.
"""
def residual_block(x, s, i, activation):
original_x = x
if causal:
x = ZeroPadding1D(((2 ** i) // 2, 0))(x)
conv = Conv1D(nb_filters, 2, dilation_rate=2 ** i,
padding='same',
name='dilated_conv_%d_tanh_s%d' % (2 ** i, s))(x)
conv = Cropping1D((0, (2 ** i) // 2))(conv)
else:
conv = Conv1D(nb_filters, 3, dilation_rate=2 ** i,
padding='same',
name='dilated_conv_%d_tanh_s%d' % (2 ** i, s),
kernel_regularizer=regularizers.l2(0.001))(x)
conv = SpatialDropout1D(0.3)(conv)
# x = WaveNet_activation(conv)
if activation == 'norm_relu':
x = Activation('relu')(conv)
x = Lambda(channel_normalization)(x)
elif activation == 'wavenet':
x = WaveNet_activation(conv)
else:
x = Activation(activation)(conv)
# res_x = Convolution1D(nb_filters, 1, border_mode='same')(x)
# skip_x = Convolution1D(nb_filters, 1, border_mode='same')(x)
x = Conv1D(nb_filters, 1, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
res_x = Add()([original_x, x])
# return res_x, skip_x
return res_x, x
input_layer = Input(shape=(max_len, num_feat))
# add "channel" for conv2d layers
x = input_layer
new_shape = (max_len, num_feat, 1)
x = Reshape(new_shape)(x)
for n_filters in n_filters_by_layer:
x = Conv2D(n_filters, kernel_size=(5, 5),
kernel_regularizer=regularizers.l2(0.001),
padding="same", activation='relu')(x)
x = MaxPooling2D(pool_size=(1, 8),
strides=(1, 8))(x)
shape = x.get_shape().as_list()
new_shape = [shape[1], shape[2] * shape[3]]
# combine filters into one axis so we can apply 1d convolution
x = Reshape(new_shape)(x)
skip_connections = []
if causal:
x = ZeroPadding1D((1, 0))(x)
x = Conv1D(nb_filters, 2, padding='same',
name='initial_conv')(x)
x = Cropping1D((0, 1))(x)
else:
x = Conv1D(nb_filters, 3, padding='same', name='initial_conv',
kernel_regularizer=regularizers.l2(0.001))(x)
for s in range(nb_stacks):
for i in range(0, dilation_depth + 1):
x, skip_out = residual_block(x, s, i, activation)
skip_connections.append(skip_out)
if use_skip_connections:
x = Add()(skip_connections)
x = Activation('relu')(x)
x = Conv1D(nb_filters, tail_conv, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
x = Activation('relu')(x)
x = Conv1D(num_classes, tail_conv, padding='same',
kernel_regularizer=regularizers.l2(0.001))(x)
x = Activation('softmax', name='output_softmax')(x)
model = Model(inputs=input_layer, outputs=x)
model.compile(loss=loss, optimizer=optimizer,metrics=['accuracy'])
return model
def CNN_biLSTM(n_classes, n_feat, max_len,
n_filters_by_layer=(32, 64),
loss='categorical_crossentropy',
optimizer='Adam'):
inputs = Input(shape=(max_len, n_feat))
x = inputs
new_shape = (max_len, n_feat, 1)
x = Reshape(new_shape)(x)
for n_filters in n_filters_by_layer:
x = Conv2D(n_filters, kernel_size=(5, 5),
kernel_regularizer=regularizers.l2(0.001),
padding="same", activation='relu')(x)
x = MaxPooling2D(pool_size=(1, 8),
strides=(1, 8))(x)
conv_out_shape = x.get_shape().as_list()
num_hidden = conv_out_shape[2] * conv_out_shape[3]
new_shape = (-1, num_hidden)
x = Reshape(new_shape)(x)
x = Bidirectional(
LSTM(num_hidden, return_sequences=True, dropout=0.25,
recurrent_dropout=0.1))(x)
x = TimeDistributed(Dense(n_classes, activation="softmax"))(x)
model = Model(inputs=inputs, outputs = x)
model.compile(loss=loss, optimizer=optimizer, metrics=['accuracy'])
return model
| 37.142119
| 84
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| 14,374
| 4.646532
| 0.115772
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| 0.070896
| 0.818368
| 0.791767
| 0.777203
| 0.760953
| 0.745908
| 0.745908
| 0
| 0.029251
| 0.274593
| 14,374
| 386
| 85
| 37.238342
| 0.767527
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| 0.01654
| 0
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| 1
| 0.046595
| false
| 0
| 0.043011
| 0.007168
| 0.136201
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
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|
0
| 7
|
08785b559700a7458b3ae2edbbf0452f4011b06a
| 23,105
|
py
|
Python
|
models.py
|
sisl/nns-as-gps
|
a19e76df31335d9e32fc07a749eb33672e3c9224
|
[
"MIT"
] | 6
|
2018-03-13T00:09:56.000Z
|
2021-12-15T21:05:47.000Z
|
models.py
|
sisl/nns-as-gps
|
a19e76df31335d9e32fc07a749eb33672e3c9224
|
[
"MIT"
] | null | null | null |
models.py
|
sisl/nns-as-gps
|
a19e76df31335d9e32fc07a749eb33672e3c9224
|
[
"MIT"
] | null | null | null |
import numpy as np
import tensorflow as tf
import pdb
class EnsembleMSE(object):
def __init__(self,
sess,
obs_dim,
output_dim,
name,
ensemble_size = 10,
hidden_sizes = [64,32,32,32],
learning_rate = 1e-3,
batch_size = 4,
validation_ratio = 0.0,
max_epochs = 300,
use_bn = False,
dropout_rate = 0.0,
weight_reg = 1e-3,
):
self.sess = sess
self.obs_dim = obs_dim
self.output_dim = output_dim
self.hidden_sizes = hidden_sizes
self.ensemble_size = ensemble_size
self.name = name
self.learning_rate = learning_rate
self.batch_size = batch_size
self.validation_ratio = validation_ratio
self.max_epochs = max_epochs
self.use_bn = use_bn
self.dropout_rate = dropout_rate
self.weight_reg = weight_reg
self.inputs = tf.placeholder(tf.float32, [None, obs_dim], name='inputs')
self.labels = tf.placeholder(tf.float32, [None, output_dim], name='outputs')
self.phase = tf.placeholder(tf.bool, name='phase')
self.outputs = [None] * ensemble_size
for en in range(ensemble_size):
with tf.variable_scope(name+str(en)) as scope:
hidden = tf.layers.dense(
self.inputs, hidden_sizes[0],
name = 'h0',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=self.phase)
for i in range(1, len(hidden_sizes)):
hidden = tf.layers.dense(
hidden_, hidden_sizes[i],
name = 'h%d' % i,
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=self.phase)
self.outputs[en] = tf.layers.dense(hidden_, output_dim, name='output',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
self.losses = [tf.nn.l2_loss(output - self.labels) for output in self.outputs]
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
self.optims = [tf.train.AdamOptimizer(learning_rate=learning_rate,
name='adam_emse'+str(en)).minimize(
loss) for en, loss in enumerate(self.losses)]
# self.optims = [tf.train.GradientDescentOptimizer(learning_rate=learning_rate,
# name='adam_emse'+str(en)).minimize(
# loss) for en, loss in enumerate(self.losses)]
return
def load_data(self, data):
self.dataset_X = data[0]
self.dataset_Y = data[1]
def split_train_test(self):
N = self.dataset_X.shape[0]
if(self.validation_ratio > 0.0):
Ntrain = int(N * (1-self.validation_ratio))
Ntest = N - Ntrain
shuffle_inds = np.arange(N)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.dataset_X[shuffle_inds[:Ntrain], :]
self.train_data_Y = self.dataset_Y[shuffle_inds[:Ntrain], :]
self.test_data_X = self.dataset_X[shuffle_inds[Ntrain:], :]
self.test_data_Y = self.dataset_Y[shuffle_inds[Ntrain:], :]
else:
self.train_data_X = self.dataset_X
self.train_data_Y = self.dataset_Y
self.test_data_X = None
self.test_data_Y = None
def train(self, model_name = None,
verbose=False):
# if model_name == None then it will not save
min_test_loss = np.Inf
for epoch in range(self.max_epochs):
Ntrain = self.train_data_X.shape[0]
num_batches = Ntrain // self.batch_size
for en in range(self.ensemble_size):
# shuffle train data
shuffle_inds = np.arange(Ntrain)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.train_data_X[shuffle_inds,:]
self.train_data_Y = self.train_data_Y[shuffle_inds,:]
for idx in range(num_batches):
batch_ind_start = idx*self.batch_size
batch_ind_end = (idx+1)*self.batch_size
batch_X = self.train_data_X[batch_ind_start:batch_ind_end,:]
batch_Y = self.train_data_Y[batch_ind_start:batch_ind_end,:]
self.sess.run(self.optims[en],
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[batch_X, batch_Y, True])))
if verbose: print('Epoch %d Train Loss: %.3f' % (epoch,
self.eval_performance_single(self.train_data_X, self.train_data_Y,en)))
if(self.test_data_X is not None):
test_loss = self.eval_performance_single(self.test_data_X, self.test_data_Y,en)
if verbose: print('Epoch %d Test Loss: %.3f' % (epoch, test_loss))
def eval_performance_single(self, x, labels, en):
N = x.shape[0]
return self.sess.run(self.losses[en],
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[x, labels, False]))) / N
def eval(self, x):
means_en = self.sess.run(self.outputs,
feed_dict = dict(zip([self.inputs, self.phase],
[x, False])))
means_en = np.squeeze(np.array(means_en))
means = np.mean(means_en,axis=0)
sigsqs = np.std(means_en,axis=0) ** 2
return means, sigsqs
def get_output(self,x):
x = np.expand_dims(x, axis=0)
outputs = self.sess.run(self.outputs,
feed_dict = dict(zip([self.inputs, self.phase],
[x, False])))
outputs = np.array(outputs)
# reshape to samples of each output dim
outputs = outputs.reshape(-1, outputs.shape[-1]).T
mean_outputs = np.mean(outputs,axis=1)
cov_outputs = np.cov(outputs)
if(self.output_dim == 1):
cov_outputs = cov_outputs.reshape((1,1))
return mean_outputs, dict(mean=mean_outputs,cov=cov_outputs)
class EnsembleNLL(object):
def __init__(self,
sess,
obs_dim,
output_dim,
name,
ensemble_size = 10,
hidden_sizes = [64,32,32,32],
learning_rate = 1e-3,
batch_size = 4,
validation_ratio = 0.0,
max_epochs = 300,
use_bn = False,
dropout_rate = 0.0,
weight_reg = 1e-3,
):
self.sess = sess
self.obs_dim = obs_dim
self.output_dim = output_dim
self.hidden_sizes = hidden_sizes
self.ensemble_size = ensemble_size
self.name = name
self.learning_rate = learning_rate
self.batch_size = batch_size
self.validation_ratio = validation_ratio
self.max_epochs = max_epochs
self.use_bn = use_bn
self.dropout_rate = dropout_rate
self.weight_reg = weight_reg
self.inputs = tf.placeholder(tf.float32, [None, obs_dim], name='inputs')
self.labels = tf.placeholder(tf.float32, [None, output_dim], name='outputs')
self.phase = tf.placeholder(tf.bool, name='phase')
self.means = [None] * ensemble_size
self.vars = [None] * ensemble_size
self.losses = [None] * ensemble_size
for en in range(ensemble_size):
with tf.variable_scope(name+str(en)) as scope:
hidden = tf.layers.dense(
self.inputs, hidden_sizes[0],
name = 'h0',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=self.phase)
for i in range(1, len(hidden_sizes)-1):
hidden = tf.layers.dense(
hidden_, hidden_sizes[i],
name = 'h%d' % i,
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=self.phase)
i = len(hidden_sizes)-1
hidden = tf.layers.dense(
hidden_, hidden_sizes[-1]*2,
name = 'h%d' % i,
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=self.phase)
mu_, rawvar_ = tf.split(hidden_, [hidden_sizes[-1], hidden_sizes[-1]], axis=1)
mu = tf.layers.dense(mu_, output_dim, name='outputmu',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
rawvar = tf.layers.dense(rawvar_, output_dim, name='outputrw',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
sigsq = tf.nn.softplus(rawvar) + 1e-6 # enforce positivity and numerical stability
self.means[en] = mu
self.vars[en] = sigsq
# Negative log likelihood loss
self.losses[en] = 0.5*tf.reduce_mean( tf.log(sigsq) + (self.labels - mu)**2 / sigsq )
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
self.optims = [tf.train.AdamOptimizer(learning_rate=learning_rate,
name='adam_enll'+str(en)).minimize(
loss) for en, loss in enumerate(self.losses)]
# self.optims = [tf.train.GradientDescentOptimizer(learning_rate=learning_rate,
# name='sgd_enll'+str(en)).minimize(
# loss) for en, loss in enumerate(self.losses)]
return
def load_data(self, data):
self.dataset_X = data[0]
self.dataset_Y = data[1]
def split_train_test(self):
N = self.dataset_X.shape[0]
if(self.validation_ratio > 0.0):
Ntrain = int(N * (1-self.validation_ratio))
Ntest = N - Ntrain
shuffle_inds = np.arange(N)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.dataset_X[shuffle_inds[:Ntrain], :]
self.train_data_Y = self.dataset_Y[shuffle_inds[:Ntrain], :]
self.test_data_X = self.dataset_X[shuffle_inds[Ntrain:], :]
self.test_data_Y = self.dataset_Y[shuffle_inds[Ntrain:], :]
else:
self.train_data_X = self.dataset_X
self.train_data_Y = self.dataset_Y
self.test_data_X = None
self.test_data_Y = None
def train(self, model_name = None,
verbose=False):
# if model_name == None then it will not save
min_test_loss = np.Inf
for epoch in range(self.max_epochs):
Ntrain = self.train_data_X.shape[0]
num_batches = Ntrain // self.batch_size
for en in range(self.ensemble_size):
# shuffle train data
shuffle_inds = np.arange(Ntrain)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.train_data_X[shuffle_inds,:]
self.train_data_Y = self.train_data_Y[shuffle_inds,:]
for idx in range(num_batches):
batch_ind_start = idx*self.batch_size
batch_ind_end = (idx+1)*self.batch_size
batch_X = self.train_data_X[batch_ind_start:batch_ind_end,:]
batch_Y = self.train_data_Y[batch_ind_start:batch_ind_end,:]
self.sess.run(self.optims[en],
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[batch_X, batch_Y, True])))
if verbose: print('Epoch %d Train Loss: %.3f' % (epoch,
self.eval_performance_single(self.train_data_X, self.train_data_Y,en)))
if(self.test_data_X is not None):
test_loss = self.eval_performance_single(self.test_data_X, self.test_data_Y,en)
if verbose: print('Epoch %d Test Loss: %.3f' % (epoch, test_loss))
def eval_performance_single(self, x, labels, en):
N = x.shape[0]
return self.sess.run(self.losses[en],
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[x, labels, False]))) / N
def eval(self, x):
means_en, sigsqs_en = self.sess.run([self.means, self.vars],
feed_dict = dict(zip([self.inputs, self.phase],
[x, False])))
means_en = np.squeeze(np.array(means_en))
sigsqs_en = np.squeeze(np.array(sigsqs_en))
means = np.mean(means_en,axis=0)
sigsqs = np.mean(sigsqs_en + means_en**2,axis=0) - means**2
return means, sigsqs
def get_output(self,x):
x = np.expand_dims(x, axis=0)
means, sigsqs = self.eval(x)
means = np.array(means)
sigsqs = np.array(sigsqs)
# reshape to samples of each output dim
means = means.reshape(-1, means.shape[-1]).T
sigsqs = means.reshape(-1, sigsqs.shape[-1]).T
mean_outputs = np.mean(means,axis=1)
cov_outputs = np.mean(sigsqs + means**2,axis=1) - mean_outputs**2
if(self.output_dim == 1):
cov_outputs = cov_outputs.reshape((1,1))
return mean_outputs, dict(mean=mean_outputs,cov=cov_outputs)
class MCDropoutMSE(object):
def __init__(self,
sess,
obs_dim,
output_dim,
name,
hidden_sizes = [64,32,32,32],
learning_rate = 1e-3,
batch_size = 4,
validation_ratio = 0.0,
max_epochs = 300,
use_bn = False,
dropout_rate = 0.0,
weight_reg = 1e-3,
):
self.sess = sess
self.obs_dim = obs_dim
self.output_dim = output_dim
self.hidden_sizes = hidden_sizes
self.name = name
self.learning_rate = learning_rate
self.batch_size = batch_size
self.validation_ratio = validation_ratio
self.max_epochs = max_epochs
self.use_bn = use_bn
self.dropout_rate = dropout_rate
self.weight_reg = weight_reg
self.inputs = tf.placeholder(tf.float32, [None, obs_dim], name='inputs')
self.labels = tf.placeholder(tf.float32, [None, output_dim], name='outputs')
self.phase = tf.placeholder(tf.bool, name='phase')
self.output = None
with tf.variable_scope(name) as scope:
hidden = tf.layers.dense(
self.inputs, hidden_sizes[0],
name = 'h0',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=True)
for i in range(1, len(hidden_sizes)):
hidden = tf.layers.dense(
hidden_, hidden_sizes[i],
name = 'h%d' % i,
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
if(use_bn):
hidden_bn = tf.contrib.layers.batch_norm(hidden,
center=True, scale=True,
is_training=self.phase)
else:
hidden_bn = hidden
hidden_relu = tf.nn.relu(hidden_bn)
hidden_ = tf.layers.dropout(hidden_relu, rate = dropout_rate, training=True)
self.output = tf.layers.dense(hidden_, output_dim, name='output',
kernel_regularizer=tf.contrib.layers.l1_regularizer(weight_reg),
kernel_initializer=tf.contrib.layers.xavier_initializer())
self.loss = tf.reduce_mean(tf.nn.l2_loss(self.output - self.labels))
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
self.optim = tf.train.AdamOptimizer(learning_rate=learning_rate, name='adam_dmse').minimize(
self.loss)
# self.optim = tf.train.GradientDescentOptimizer(learning_rate=learning_rate, name='sgd_dmse').minimize(
# self.loss)
self.saver = tf.train.Saver()
return
def load_data(self, data):
self.dataset_X = data[0]
self.dataset_Y = data[1]
def split_train_test(self):
N = self.dataset_X.shape[0]
if(self.validation_ratio > 0.0):
Ntrain = int(N * (1-self.validation_ratio))
Ntest = N - Ntrain
shuffle_inds = np.arange(N)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.dataset_X[shuffle_inds[:Ntrain], :]
self.train_data_Y = self.dataset_Y[shuffle_inds[:Ntrain], :]
self.test_data_X = self.dataset_X[shuffle_inds[Ntrain:], :]
self.test_data_Y = self.dataset_Y[shuffle_inds[Ntrain:], :]
else:
self.train_data_X = self.dataset_X
self.train_data_Y = self.dataset_Y
self.test_data_X = None
self.test_data_Y = None
def train(self, model_name = None,
verbose=False):
# if model_name == None then it will not save
min_test_loss = np.Inf
for epoch in range(self.max_epochs):
Ntrain = self.train_data_X.shape[0]
num_batches = Ntrain // self.batch_size
shuffle_inds = np.arange(Ntrain)
np.random.shuffle(shuffle_inds)
self.train_data_X = self.train_data_X[shuffle_inds,:]
self.train_data_Y = self.train_data_Y[shuffle_inds,:]
for idx in range(num_batches):
batch_ind_start = idx*self.batch_size
batch_ind_end = (idx+1)*self.batch_size
batch_X = self.train_data_X[batch_ind_start:batch_ind_end,:]
batch_Y = self.train_data_Y[batch_ind_start:batch_ind_end,:]
self.sess.run(self.optim,
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[batch_X, batch_Y, True])))
if verbose: print('Epoch %d Train Loss: %.3f' % (epoch,
self.eval_performance_single(self.train_data_X, self.train_data_Y)))
if(self.test_data_X is not None):
test_loss = self.eval_performance_single(self.test_data_X, self.test_data_Y)
if verbose: print('Epoch %d Test Loss: %.3f' % (epoch, test_loss))
def eval_performance_single(self, x, labels):
N = x.shape[0]
return self.sess.run(self.loss,
feed_dict = dict(zip([self.inputs, self.labels, self.phase],
[x, labels, False]))) / N
def eval(self, x):
samps = self.sess.run(self.output,
feed_dict = dict(zip([self.inputs, self.phase],
[np.vstack([x]*100), False])))
samps = samps.reshape([100]+list(x.shape))
samps = np.squeeze(np.array(samps))
means = np.mean(samps,axis=0)
sigsqs = np.std(samps,axis=0) ** 2
return means, sigsqs
def get_output(self,x):
x = np.expand_dims(x, axis=0)
outputs = self.sess.run(self.output,
feed_dict = dict(zip([self.inputs, self.phase],
[np.array([x]*10), False])))
outputs = np.array(outputs)
# reshape to samples of each output dim
outputs = outputs.reshape(-1, outputs.shape[-1]).T
mean_outputs = np.mean(outputs,axis=1)
cov_outputs = np.cov(outputs)
if(self.output_dim == 1):
cov_outputs = cov_outputs.reshape((1,1))
return mean_outputs, dict(mean=mean_outputs,cov=cov_outputs)
| 37.326333
| 116
| 0.556633
| 2,810
| 23,105
| 4.340214
| 0.06726
| 0.030256
| 0.041571
| 0.024106
| 0.922598
| 0.910954
| 0.910954
| 0.906445
| 0.906445
| 0.894474
| 0
| 0.012272
| 0.340489
| 23,105
| 618
| 117
| 37.386731
| 0.788096
| 0.035057
| 0
| 0.871622
| 0
| 0
| 0.0123
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.047297
| false
| 0
| 0.006757
| 0
| 0.087838
| 0.013514
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
08a10fee833ffb54d2b73424c1b5671399504b67
| 10,731
|
py
|
Python
|
tests/test_cardnet.py
|
lummax/switching-lattice-synth
|
47cf9e64c900cb179c392b46a392049e99dfebab
|
[
"MIT"
] | null | null | null |
tests/test_cardnet.py
|
lummax/switching-lattice-synth
|
47cf9e64c900cb179c392b46a392049e99dfebab
|
[
"MIT"
] | null | null | null |
tests/test_cardnet.py
|
lummax/switching-lattice-synth
|
47cf9e64c900cb179c392b46a392049e99dfebab
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
import unittest
import pyeda.boolalg.expr as expr
import synth.constraint.cardnet as cardnet
class TestBase(unittest.TestCase):
def setUp(self):
self.pos = tuple(expr.exprvar(p) for p in "abc")
self.neg = tuple(expr.exprvar(p) for p in "uvwxyz")
self.function = expr.And(*self.pos, ~expr.Or(*self.neg))
class TestCardnetAtMost(TestBase):
def test_at_most_zero_small(self):
(a, _b, _c) = self.pos
self.function = a
cardinality = cardnet.at_most(self.function.support, 0)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_at_most_zero(self):
cardinality = cardnet.at_most(self.function.support, 0)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_at_most_one_small(self):
(a, _b, _c) = self.pos
self.function = a
cardinality = cardnet.at_most(self.function.support, 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(a), 1)
def test_at_most_one(self):
cardinality = cardnet.at_most(self.function.support, 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_at_most_lower(self):
cardinality = cardnet.at_most(self.function.support,
len(self.pos) - 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_at_most_is(self):
cardinality = cardnet.at_most(self.function.support,
len(self.pos))
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_most_higher(self):
cardinality = cardnet.at_most(self.function.support,
len(self.pos) + 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_most_is_equivalent(self):
at_most = expr.exprvar("at_most")
cardinality = cardnet.at_most(self.function.support,
len(self.pos),
at_most)
sat = expr.And(self.function, at_most, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_most), 1)
def test_at_most_is_not_equivalent(self):
at_most = expr.exprvar("at_most")
cardinality = cardnet.at_most(self.function.support,
len(self.pos),
~at_most)
sat = expr.And(self.function, ~at_most, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_most), 0)
def test_not_at_most_is_equivalent(self):
at_most = expr.exprvar("at_most")
cardinality = cardnet.at_most(self.function.support,
len(self.pos) - 1,
at_most)
sat = expr.And(self.function, ~at_most, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_most), 0)
def test_not_at_most_is_not_equivalent(self):
at_most = expr.exprvar("at_most")
cardinality = cardnet.at_most(self.function.support,
len(self.pos) - 1,
~at_most)
sat = expr.And(self.function, at_most, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_most), 1)
class TestCardnetAtLeast(TestBase):
def test_at_least_zero(self):
cardinality = cardnet.at_least(self.function.support, 0)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_least_one(self):
cardinality = cardnet.at_least(self.function.support, 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_least_lower(self):
cardinality = cardnet.at_least(self.function.support,
len(self.pos) - 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_least_is(self):
cardinality = cardnet.at_least(self.function.support,
len(self.pos))
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_at_least_higher(self):
cardinality = cardnet.at_least(self.function.support,
len(self.pos) + 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_at_least_is_equivalent(self):
at_least = expr.exprvar("at_least")
cardinality = cardnet.at_least(self.function.support,
len(self.pos),
at_least)
sat = expr.And(self.function, at_least, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_least), 1)
def test_at_least_is_not_equivalent(self):
at_least = expr.exprvar("at_least")
cardinality = cardnet.at_least(self.function.support,
len(self.pos),
~at_least)
sat = expr.And(self.function, ~at_least, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(at_least), 0)
class TestCardnetEquals(TestBase):
def test_equals_zero(self):
cardinality = cardnet.equals(self.function.support, 0)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_equals_one_small(self):
(a, _b, _c) = self.pos
self.function = a
cardinality = cardnet.equals(self.function.support, 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(a), 1)
def test_equals_one(self):
cardinality = cardnet.equals(self.function.support, 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_equals_lower(self):
cardinality = cardnet.equals(self.function.support,
len(self.pos) - 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_equals_is(self):
cardinality = cardnet.equals(self.function.support,
len(self.pos))
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
solution = {x: sat.get(x) for x in self.pos}
self.assertEqual(solution, {x: 1 for x in self.pos})
def test_equals_higher(self):
cardinality = cardnet.equals(self.function.support,
len(self.pos) + 1)
sat = expr.And(self.function, *cardinality).to_cnf().satisfy_one()
self.assertIsNone(sat)
def test_equals_is_equivalent(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos),
equals)
sat = expr.And(self.function, equals,
*cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 1)
def test_equals_is_not_equivalent(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos),
~equals)
sat = expr.And(self.function, ~equals, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 0)
def test_not_equals_lower(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos) - 1,
equals)
sat = expr.And(self.function, ~equals, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 0)
def test_not_equals_lower_not_equivalent(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos) - 1,
~equals)
sat = expr.And(self.function, equals, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 1)
def test_not_equals_higher(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos) + 1,
equals)
sat = expr.And(self.function, ~equals, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 0)
def test_not_equals_higher(self):
equals = expr.exprvar("equals")
cardinality = cardnet.equals(self.function.support,
len(self.pos) + 1,
~equals)
sat = expr.And(self.function, equals, *cardinality).to_cnf().satisfy_one()
self.assertIsNotNone(sat)
self.assertEqual(sat.get(equals), 1)
if __name__ == '__main__':
unittest.main()
| 40.49434
| 85
| 0.586525
| 1,282
| 10,731
| 4.735569
| 0.053042
| 0.126503
| 0.056169
| 0.069181
| 0.937737
| 0.921924
| 0.921924
| 0.909076
| 0.898205
| 0.898205
| 0
| 0.005691
| 0.295872
| 10,731
| 264
| 86
| 40.647727
| 0.797777
| 0.001957
| 0
| 0.755869
| 0
| 0
| 0.009058
| 0
| 0
| 0
| 0
| 0
| 0.239437
| 1
| 0.14554
| false
| 0
| 0.014085
| 0
| 0.178404
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
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| null | 0
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|
0
| 7
|
08da3b9994c2ee1c5351391e8c69ca33e5a7502b
| 9,420
|
py
|
Python
|
project/detect_modality.py
|
ylavinia/pulearning632
|
b4ed5e721aee85c9aa8375bf817e64237f6b298d
|
[
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | null | null | null |
project/detect_modality.py
|
ylavinia/pulearning632
|
b4ed5e721aee85c9aa8375bf817e64237f6b298d
|
[
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | null | null | null |
project/detect_modality.py
|
ylavinia/pulearning632
|
b4ed5e721aee85c9aa8375bf817e64237f6b298d
|
[
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | null | null | null |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn import *
import glob, sys, os
from pathlib import Path
from src.utils import get_proj_root
import warnings
warnings.filterwarnings("ignore")
def find_peaks(df, col_name_str, min_peak_fraction):
"""
Find peak points and indices via KDE
:param df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:return a list containing the peak indices, the density value of the peaks, KDE x-values, KDE y-values
"""
from scipy.signal import find_peaks, peak_prominences
plt.figure()
# get the x-values and y-values of the kde plot
density_x, density_y = sns.kdeplot(df[col_name_str]).get_lines()[0].get_data()
# want to find peaks that are greater than min_peak_fraction of max peak
# to exclude peaks that are too small
min_peak = min_peak_fraction * max(density_y)
# find peaks with density more than min_peak
peaks, _ = find_peaks(x=density_y, prominence=min_peak)
prominences = peak_prominences(density_y, peaks)[0]
x_peaks = [density_x[idx] for idx in peaks]
return peaks, x_peaks, density_x, density_y
def find_peaks_no_header(df, col_num, min_peak_fraction):
"""
Find peak points and indices via KDE
:param df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:return a list containing the peak indices, the density value of the peaks, KDE x-values, KDE y-values
"""
from scipy.signal import find_peaks, peak_prominences
plt.figure()
# get the x-values and y-values of the kde plot
density_x, density_y = sns.kdeplot(df.iloc[col_num]).get_lines()[0].get_data()
# want to find peaks that are greater than min_peak_fraction of max peak
# to exclude peaks that are too small
min_peak = min_peak_fraction * max(density_y)
# find peaks with density more than min_peak
peaks, _ = find_peaks(x=density_y, prominence=min_peak)
prominences = peak_prominences(density_y, peaks)[0]
x_peaks = [density_x[idx] for idx in peaks]
return peaks, x_peaks, density_x, density_y
def find_lowest_points_between_peaks_no_header(df, col_num, min_peak_fraction=0.1):
"""
Search for the lowest points between peaks, store the points in a list
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param min_peak_fraction: float between 0.0 and 1.0 to specify peak size to be considered a peak
:return a list containing the lowest points
"""
# find the peaks
peaks, x_peaks, density_x, density_y = find_peaks_no_header(df, col_num, min_peak_fraction)
valley_indices = []
valley_points = []
for i in range(len(peaks)-1):
peak = peaks[i]
next_peak = peaks[i+1]
valley_idx = peak + np.argmin(density_y[peak:next_peak+1])
valley_indices.append(valley_idx)
valley_points.append(density_x[valley_idx])
# plot the density
plt.plot(density_x, density_y)
# plot the peaks
plt.plot(x_peaks, density_y[peaks], "x")
# plot the lowest point between the peaks
plt.plot(valley_points, density_y[valley_indices], "o", c="red")
# plot a vertical line for the peaks
plt.vlines(x=x_peaks, ymin=0, ymax=density_y[peaks])
# plot a vertical line for the lowest point
plt.vlines(x=valley_points, ymin=0, ymax=density_y[valley_indices])
plt.title("Density Plot with Peaks and Lowest Point Between Peaks")
plt.ylabel("Density")
plt.xlabel("RTT (ms)")
return valley_points
def find_lowest_points_between_peaks(df, col_name_str, min_peak_fraction=0.1):
"""
Search for the lowest points between peaks, store the points in a list
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param min_peak_fraction: float between 0.0 and 1.0 to specify peak size to be considered a peak
:return a list containing the lowest points
"""
# find the peaks
peaks, x_peaks, density_x, density_y = find_peaks(df, col_name_str, min_peak_fraction)
valley_indices = []
valley_points = []
for i in range(len(peaks)-1):
peak = peaks[i]
next_peak = peaks[i+1]
valley_idx = peak + np.argmin(density_y[peak:next_peak+1])
valley_indices.append(valley_idx)
valley_points.append(density_x[valley_idx])
# plot the density
plt.plot(density_x, density_y)
# plot the peaks
plt.plot(x_peaks, density_y[peaks], "x")
# plot the lowest point between the peaks
plt.plot(valley_points, density_y[valley_indices], "o", c="red")
# plot a vertical line for the peaks
plt.vlines(x=x_peaks, ymin=0, ymax=density_y[peaks])
# plot a vertical line for the lowest point
plt.vlines(x=valley_points, ymin=0, ymax=density_y[valley_indices])
plt.title("Density Plot with Peaks and Lowest Point Between Peaks")
plt.ylabel("Density")
plt.xlabel("RTT (ms)")
return valley_points
def split_2_peaks(df, col_name_str, valley_points):
'''
In case of bimodal data, split data into 2 subsets with the valley point as the separator
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param valley_points: A list containing the lowest point between peaks on the x-axis
:return List of two DataFrames separated by the valley_points
'''
df_1 = df[df[col_name_str] < valley_points[0]]
df_2 = df[df[col_name_str] >= valley_points[0]]
return [df_1, df_2]
def split_2_peaks_no_header(df, col_num, valley_points):
'''
In case of bimodal data, split data into 2 subsets with the valley point as the separator
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param valley_points: A list containing the lowest point between peaks on the x-axis
:return List of two DataFrames separated by the valley_points
'''
df_1 = df[df.iloc[col_num] < valley_points[0]]
df_2 = df[df.iloc[col_num] >= valley_points[0]]
return [df_1, df_2]
def divide_data_based_on_peaks(df, col_name_str, valley_points):
"""
Split data at the lowest points to create unimodal subsets
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param valley_points: A list containing the lowest point on the x-axis
:return DataFrame of the subsets
"""
subset_list = []
num_valleys = len(valley_points)
num_peaks = num_valleys + 1
# if data has no valley, thus it is unimodal
if num_valleys == 0:
subset_list.append(df)
# if data has 1 valley and 2 peaks (bimodal)
elif num_valleys == 1:
two_subsets_list = split_2_peaks(df, col_name_str=col_name_str, valley_points=valley_points)
subset_list.extend(two_subsets_list)
# if there are at least 2 valleys (at least 3 peaks)
else:
# the first subset is always the data less than the first valley point
df_first = df[df[col_name_str] < valley_points[0]]
subset_list.append(df_first)
i = 0
# remember num_valleys is at least 2
while (i < num_valleys-1):
df_subset = df[(df[col_name_str] >= valley_points[i]) & (df[col_name_str] < valley_points[i+1])]
subset_list.append(df_subset)
i += 1
# the last subset is always the data greater than the last valley point
df_last = df[df[col_name_str] >= valley_points[-1]]
subset_list.append(df_last)
return subset_list
def divide_data_based_on_peaks_no_header(df, col_num, valley_points):
"""
Split data at the lowest points to create unimodal subsets
:param: df: DataFrame containing the desired column
:param col_name_str: The desired column name in string
:param valley_points: A list containing the lowest point on the x-axis
:return DataFrame of the subsets
"""
subset_list = []
num_valleys = len(valley_points)
num_peaks = num_valleys + 1
# if data has no valley, thus it is unimodal
if num_valleys == 0:
subset_list.append(df)
# if data has 1 valley and 2 peaks (bimodal)
elif num_valleys == 1:
two_subsets_list = split_2_peaks_no_header(df, col_num=col_num, valley_points=valley_points)
subset_list.extend(two_subsets_list)
# if there are at least 2 valleys (at least 3 peaks)
else:
# the first subset is always the data less than the first valley point
df_first = df[df.iloc[col_num] < valley_points[0]]
subset_list.append(df_first)
i = 0
# remember num_valleys is at least 2
while (i < num_valleys-1):
df_subset = df[(df.iloc[col_num] >= valley_points[i]) & (df.iloc[col_num] < valley_points[i+1])]
subset_list.append(df_subset)
i += 1
# the last subset is always the data greater than the last valley point
df_last = df[df.iloc[col_num] >= valley_points[-1]]
subset_list.append(df_last)
return subset_list
| 35.018587
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0
| 7
|
3eaaddab0aed62c0206e1eecb22c3f759bf1b597
| 21,129
|
py
|
Python
|
src/application-insights/azext_applicationinsights/vendored_sdks/mgmt_applicationinsights/v2019_09_01_preview/operations/_query_packs_operations.py
|
Mannan2812/azure-cli-extensions
|
e2b34efe23795f6db9c59100534a40f0813c3d95
|
[
"MIT"
] | 8
|
2021-01-13T23:44:08.000Z
|
2021-03-17T10:13:36.000Z
|
src/application-insights/azext_applicationinsights/vendored_sdks/mgmt_applicationinsights/v2019_09_01_preview/operations/_query_packs_operations.py
|
Mannan2812/azure-cli-extensions
|
e2b34efe23795f6db9c59100534a40f0813c3d95
|
[
"MIT"
] | 226
|
2019-07-24T07:57:21.000Z
|
2019-10-15T01:07:24.000Z
|
src/application-insights/azext_applicationinsights/vendored_sdks/mgmt_applicationinsights/v2019_09_01_preview/operations/_query_packs_operations.py
|
Mannan2812/azure-cli-extensions
|
e2b34efe23795f6db9c59100534a40f0813c3d95
|
[
"MIT"
] | 5
|
2020-05-09T17:47:09.000Z
|
2020-10-01T19:52:06.000Z
|
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
import uuid
from msrest.pipeline import ClientRawResponse
from .. import models
class QueryPacksOperations(object):
"""QueryPacksOperations operations.
You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
:ivar api_version: The API version to use for this operation. Constant value: "2019-09-01-preview".
"""
models = models
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.api_version = "2019-09-01-preview"
self.config = config
def list(
self, custom_headers=None, raw=False, **operation_config):
"""Gets a list of all Log Analytics QueryPacks within a subscription.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: An iterator like instance of LogAnalyticsQueryPack
:rtype:
~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPackPaged[~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPack]
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
def prepare_request(next_link=None):
if not next_link:
# Construct URL
url = self.list.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
else:
url = next_link
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.get(url, query_parameters, header_parameters)
return request
def internal_paging(next_link=None):
request = prepare_request(next_link)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
return response
# Deserialize response
header_dict = None
if raw:
header_dict = {}
deserialized = models.LogAnalyticsQueryPackPaged(internal_paging, self._deserialize.dependencies, header_dict)
return deserialized
list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/microsoft.insights/queryPacks'}
def list_by_resource_group(
self, resource_group_name, custom_headers=None, raw=False, **operation_config):
"""Gets a list of Log Analytics QueryPacks within a resource group.
:param resource_group_name: The name of the resource group. The name
is case insensitive.
:type resource_group_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: An iterator like instance of LogAnalyticsQueryPack
:rtype:
~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPackPaged[~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPack]
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
def prepare_request(next_link=None):
if not next_link:
# Construct URL
url = self.list_by_resource_group.metadata['url']
path_format_arguments = {
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'),
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
else:
url = next_link
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.get(url, query_parameters, header_parameters)
return request
def internal_paging(next_link=None):
request = prepare_request(next_link)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
return response
# Deserialize response
header_dict = None
if raw:
header_dict = {}
deserialized = models.LogAnalyticsQueryPackPaged(internal_paging, self._deserialize.dependencies, header_dict)
return deserialized
list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/microsoft.insights/queryPacks'}
def delete(
self, resource_group_name, query_pack_name, custom_headers=None, raw=False, **operation_config):
"""Deletes a Log Analytics QueryPack.
:param resource_group_name: The name of the resource group. The name
is case insensitive.
:type resource_group_name: str
:param query_pack_name: The name of the Log Analytics QueryPack
resource.
:type query_pack_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
# Construct URL
url = self.delete.metadata['url']
path_format_arguments = {
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'),
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1),
'queryPackName': self._serialize.url("query_pack_name", query_pack_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
# Construct headers
header_parameters = {}
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.delete(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200, 204]:
raise models.ErrorResponseException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/microsoft.insights/queryPacks/{queryPackName}'}
def get(
self, resource_group_name, query_pack_name, custom_headers=None, raw=False, **operation_config):
"""Returns a Log Analytics QueryPack.
:param resource_group_name: The name of the resource group. The name
is case insensitive.
:type resource_group_name: str
:param query_pack_name: The name of the Log Analytics QueryPack
resource.
:type query_pack_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: LogAnalyticsQueryPack or ClientRawResponse if raw=true
:rtype:
~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPack
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
# Construct URL
url = self.get.metadata['url']
path_format_arguments = {
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'),
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1),
'queryPackName': self._serialize.url("query_pack_name", query_pack_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.get(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LogAnalyticsQueryPack', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/microsoft.insights/queryPacks/{queryPackName}'}
def create_or_update(
self, resource_group_name, query_pack_name, location, tags=None, custom_headers=None, raw=False, **operation_config):
"""Creates (or updates) a Log Analytics QueryPack. Note: You cannot
specify a different value for InstrumentationKey nor AppId in the Put
operation.
:param resource_group_name: The name of the resource group. The name
is case insensitive.
:type resource_group_name: str
:param query_pack_name: The name of the Log Analytics QueryPack
resource.
:type query_pack_name: str
:param location: Resource location
:type location: str
:param tags: Resource tags
:type tags: dict[str, str]
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: LogAnalyticsQueryPack or ClientRawResponse if raw=true
:rtype:
~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPack
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
log_analytics_query_pack_payload = models.LogAnalyticsQueryPack(location=location, tags=tags)
# Construct URL
url = self.create_or_update.metadata['url']
path_format_arguments = {
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'),
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1),
'queryPackName': self._serialize.url("query_pack_name", query_pack_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(log_analytics_query_pack_payload, 'LogAnalyticsQueryPack')
# Construct and send request
request = self._client.put(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LogAnalyticsQueryPack', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/microsoft.insights/queryPacks/{queryPackName}'}
def update_tags(
self, resource_group_name, query_pack_name, tags=None, custom_headers=None, raw=False, **operation_config):
"""Updates an existing QueryPack's tags. To update other fields use the
CreateOrUpdate method.
:param resource_group_name: The name of the resource group. The name
is case insensitive.
:type resource_group_name: str
:param query_pack_name: The name of the Log Analytics QueryPack
resource.
:type query_pack_name: str
:param tags: Resource tags
:type tags: dict[str, str]
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: LogAnalyticsQueryPack or ClientRawResponse if raw=true
:rtype:
~azure.mgmt.applicationinsights.v2019_09_01_preview.models.LogAnalyticsQueryPack
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.applicationinsights.v2019_09_01_preview.models.ErrorResponseException>`
"""
query_pack_tags = models.TagsResource(tags=tags)
# Construct URL
url = self.update_tags.metadata['url']
path_format_arguments = {
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'),
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str', min_length=1),
'queryPackName': self._serialize.url("query_pack_name", query_pack_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str', min_length=1)
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(query_pack_tags, 'TagsResource')
# Construct and send request
request = self._client.patch(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LogAnalyticsQueryPack', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
update_tags.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/microsoft.insights/queryPacks/{queryPackName}'}
| 48.239726
| 176
| 0.674949
| 2,277
| 21,129
| 6.045674
| 0.093983
| 0.026878
| 0.030873
| 0.031382
| 0.893506
| 0.875708
| 0.863722
| 0.849557
| 0.849266
| 0.842293
| 0
| 0.011389
| 0.227034
| 21,129
| 437
| 177
| 48.350114
| 0.831496
| 0.30664
| 0
| 0.770335
| 0
| 0
| 0.164187
| 0.087892
| 0
| 0
| 0
| 0
| 0
| 1
| 0.052632
| false
| 0
| 0.014354
| 0
| 0.138756
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
3efcd072f6961e6471eba22cbb2c9f77628e623b
| 213
|
py
|
Python
|
plugins/core/__init__.py
|
ajenti/ajen
|
177c1a67278a7763ed06eb2f773d7b409a85ec77
|
[
"MIT"
] | 3,777
|
2015-02-21T00:10:12.000Z
|
2022-03-30T15:33:22.000Z
|
plugins/core/__init__.py
|
ajenti/ajen
|
177c1a67278a7763ed06eb2f773d7b409a85ec77
|
[
"MIT"
] | 749
|
2015-03-12T14:17:03.000Z
|
2022-03-25T13:22:28.000Z
|
plugins/core/__init__.py
|
ajenti/ajen
|
177c1a67278a7763ed06eb2f773d7b409a85ec77
|
[
"MIT"
] | 687
|
2015-03-21T10:42:33.000Z
|
2022-03-21T23:18:12.000Z
|
# pyflakes: disable-all
from .main import *
from .views.api import *
from .views.config import *
from .views.main import *
from .views.resource_server import *
from .views.push import *
from .views.tasks import *
| 23.666667
| 36
| 0.746479
| 31
| 213
| 5.096774
| 0.419355
| 0.379747
| 0.56962
| 0.240506
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14554
| 213
| 8
| 37
| 26.625
| 0.868132
| 0.098592
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
f5b8321a2435490b82bb0b28a7590e767a6d8f79
| 214
|
py
|
Python
|
mmhoidet/core/__init__.py
|
noobying/mmhoidet
|
138e3fbf34ecbc66f98ad26b10e08a9d49a61c38
|
[
"Apache-2.0"
] | 2
|
2021-09-06T13:09:42.000Z
|
2021-09-15T09:18:00.000Z
|
mmhoidet/core/__init__.py
|
noobying/mmhoidet
|
138e3fbf34ecbc66f98ad26b10e08a9d49a61c38
|
[
"Apache-2.0"
] | null | null | null |
mmhoidet/core/__init__.py
|
noobying/mmhoidet
|
138e3fbf34ecbc66f98ad26b10e08a9d49a61c38
|
[
"Apache-2.0"
] | null | null | null |
# Copyright (c) OpenMMLab. All rights reserved.
from .utils import * # noqa: F401, F403
from .visualization import * # noqa
from .evaluation import * # noqa
from .bbox import * # noqa
from .hoi import * # noqa
| 35.666667
| 47
| 0.696262
| 28
| 214
| 5.321429
| 0.571429
| 0.33557
| 0.281879
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.035088
| 0.200935
| 214
| 6
| 48
| 35.666667
| 0.836257
| 0.383178
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
eb387114db73cd56e2cc97c2272eb1d6a83070c9
| 6,323
|
py
|
Python
|
python/tests/temperatures_unit_test.py
|
Bengt/FanControl
|
6b3958230e5eacf175e84d9a5927d74cd3f6b83a
|
[
"MIT"
] | 9
|
2015-11-25T13:39:22.000Z
|
2018-10-16T21:09:10.000Z
|
python/tests/temperatures_unit_test.py
|
Bengt/FanControl
|
6b3958230e5eacf175e84d9a5927d74cd3f6b83a
|
[
"MIT"
] | 6
|
2019-07-04T13:45:08.000Z
|
2022-01-15T18:30:10.000Z
|
python/tests/temperatures_unit_test.py
|
Bengt/FanControl
|
6b3958230e5eacf175e84d9a5927d74cd3f6b83a
|
[
"MIT"
] | 3
|
2020-08-12T13:31:50.000Z
|
2021-06-16T22:12:20.000Z
|
"""
Tests for the temperature data source.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from unittest.case import TestCase
from fancontrol.sense.temperatures import (ChipFeatureMismatchError,
NoSuchChipError, NoSuchFeatureError,
_get_detected_chips, _get_index,
_get_temperatures)
from mock import MagicMock, Mock
from nose.tools import assert_raises
class GetIndexUnitTests(TestCase):
def test_get_index(self):
chips = ['k10temp']
chip = Mock()
chip.prefix = 'k10temp'
features = ['temp1']
feature = Mock()
feature.name = 'temp1'
start_index = 0
index = _get_index(
chips, chip, features, feature, start_index)
assert index == 0
def test_get_index_no_such_chip_beyond(self):
chips = ['k10temp']
chip = Mock()
chip.prefix = 'k10temp'
features = ['temp1', 'temp1']
feature = Mock()
feature.name = 'temp1'
start_index = 1
assert_raises(NoSuchChipError, _get_index,
chips, chip, features, feature, start_index)
def test_get_index_no_such_feature_beyond(self):
chips = ['k10temp', 'k10temp']
chip = Mock()
chip.prefix = 'k10temp'
features = ['temp1']
feature = Mock()
feature.name = 'temp1'
start_index = 1
assert_raises(NoSuchFeatureError, _get_index,
chips, chip, features, feature, start_index)
def test_get_index_this_is_not_the_chip_you_are_looking_for(self):
chips = ['k10temp', 'it8718', 'k10temp']
chip = Mock()
chip.prefix = 'k10temp'
features = ['temp1', 'temp1', 'temp1']
feature = Mock()
feature.name = 'temp1'
start_index = 1
assert_raises(ChipFeatureMismatchError, _get_index,
chips, chip, features, feature, start_index)
def test_get_index_this_is_not_the_feature_you_are_looking_for(self):
chips = ['k10temp', 'k10temp', 'it8718', ]
chip = Mock()
chip.prefix = 'k10temp'
features = ['temp1', 'temp2', 'temp1']
feature = Mock()
feature.name = 'temp1'
start_index = 1
assert_raises(ChipFeatureMismatchError, _get_index,
chips, chip, features, feature, start_index)
class GetTemperaturesUnitTests(TestCase):
def test_get_temperatures_same_sensor_two_fans(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp]
chips = ['k10temp', 'k10temp']
features = ['temp1', 'temp1']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] == 42
assert temps[1] == 42
def test_get_temperatures_chip_not_requested(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp]
chips = ['it8718', 'it8718']
features = ['temp1', 'temp1']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] is None
assert temps[1] is None
def test_get_temperatures_feature_not_requested(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp]
chips = ['k10temp', 'k10temp']
features = ['temp2', 'temp2']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] is None
assert temps[1] is None
def test_get_temperatures_no_such_feature(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp, k10temp]
chips = ['k10temp', 'k10temp']
features = ['temp1', 'temp2']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] == 42
assert temps[1] is None
def test_get_temperatures_no_such_chip(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp, k10temp]
chips = ['k10temp', 'it8718']
features = ['temp1', 'temp1']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] == 42
assert temps[1] is None
def test_get_temperatures_chip_feature_missmatch(self):
k10temp = MagicMock()
k10temp.prefix = 'k10temp'
temp1 = MagicMock()
temp1.name = 'temp1'
temp1.get_value.return_value = 42
k10temp.__iter__.return_value = [temp1]
chips_detected = [k10temp, k10temp]
chips = ['k10temp', 'it8718', 'k10temp']
features = ['temp1', 'temp2', 'temp2']
temps = _get_temperatures(chips=chips,
features=features,
chips_detected=chips_detected)
assert temps[0] == 42
assert temps[1] is None
assert temps[2] is None
| 31.773869
| 79
| 0.566978
| 615
| 6,323
| 5.539837
| 0.120325
| 0.068682
| 0.032286
| 0.038744
| 0.810684
| 0.801878
| 0.788083
| 0.758145
| 0.745817
| 0.732609
| 0
| 0.055688
| 0.338289
| 6,323
| 198
| 80
| 31.934343
| 0.758604
| 0.00601
| 0
| 0.75817
| 0
| 0
| 0.064043
| 0
| 0
| 0
| 0
| 0
| 0.124183
| 1
| 0.071895
| false
| 0
| 0.03268
| 0
| 0.117647
| 0.006536
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
de423c2472822110d25fdc6f29793ba3e5d26ceb
| 74
|
py
|
Python
|
tests/utils.py
|
Trigition/pypeline
|
239ac896a7bd8363a1bc4afd5fc6d2ef4450935d
|
[
"MIT"
] | null | null | null |
tests/utils.py
|
Trigition/pypeline
|
239ac896a7bd8363a1bc4afd5fc6d2ef4450935d
|
[
"MIT"
] | null | null | null |
tests/utils.py
|
Trigition/pypeline
|
239ac896a7bd8363a1bc4afd5fc6d2ef4450935d
|
[
"MIT"
] | null | null | null |
def mul_by_2(num):
return num*2
def mul_by_3(num):
return num*3
| 10.571429
| 18
| 0.648649
| 16
| 74
| 2.75
| 0.4375
| 0.272727
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 0.243243
| 74
| 6
| 19
| 12.333333
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
de558ba3c7b671a7d1de870cb1810c203a6995b8
| 242
|
py
|
Python
|
networkx/algorithms/traversal/__init__.py
|
tempcyc/networkx
|
cae83ba501c242567cb2454f97f851898276f06e
|
[
"BSD-3-Clause"
] | 12
|
2015-03-25T20:20:26.000Z
|
2021-11-14T19:44:56.000Z
|
networkx/algorithms/traversal/__init__.py
|
tempcyc/networkx
|
cae83ba501c242567cb2454f97f851898276f06e
|
[
"BSD-3-Clause"
] | 71
|
2015-01-05T16:50:55.000Z
|
2020-09-30T19:17:47.000Z
|
networkx/algorithms/traversal/__init__.py
|
tempcyc/networkx
|
cae83ba501c242567cb2454f97f851898276f06e
|
[
"BSD-3-Clause"
] | 14
|
2015-02-15T22:19:18.000Z
|
2020-09-30T18:54:54.000Z
|
import networkx.algorithms.traversal.depth_first_search
from networkx.algorithms.traversal.depth_first_search import *
import networkx.algorithms.traversal.breadth_first_search
from networkx.algorithms.traversal.breadth_first_search import *
| 48.4
| 64
| 0.892562
| 30
| 242
| 6.933333
| 0.3
| 0.346154
| 0.519231
| 0.317308
| 0.884615
| 0.884615
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049587
| 242
| 4
| 65
| 60.5
| 0.904348
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 9
|
de8bdd7deafc95032ffd2e271f3aa209baf3232c
| 168
|
py
|
Python
|
new_app/views.py
|
Sravan996/demo-app
|
b20410d78d09c7a6a30a35301133f1563b4eab33
|
[
"MIT"
] | null | null | null |
new_app/views.py
|
Sravan996/demo-app
|
b20410d78d09c7a6a30a35301133f1563b4eab33
|
[
"MIT"
] | 5
|
2021-03-18T23:26:07.000Z
|
2021-09-22T18:31:33.000Z
|
new_app/views.py
|
Sravan996/demo-app
|
b20410d78d09c7a6a30a35301133f1563b4eab33
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
from django.shortcuts import HttpResponse
# Create your views here.
def index(request):
return HttpResponse("Hello, world.")
| 18.666667
| 41
| 0.77381
| 21
| 168
| 6.190476
| 0.761905
| 0.153846
| 0.292308
| 0.384615
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14881
| 168
| 8
| 42
| 21
| 0.909091
| 0.136905
| 0
| 0
| 0
| 0
| 0.090909
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.5
| 0.25
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 8
|
ded7a0c680027b3374c3c07220afc66ee970919d
| 373
|
py
|
Python
|
tests/internal/strategies/test_strategies_partition_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | null | null | null |
tests/internal/strategies/test_strategies_partition_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | null | null | null |
tests/internal/strategies/test_strategies_partition_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | 1
|
2021-12-15T11:58:22.000Z
|
2021-12-15T11:58:22.000Z
|
# Testing module strategies.partition
import pytest
import ec2_compare.internal.strategies.partition
def test_get_internal_data_strategies_partition_get_instances_list():
assert len(ec2_compare.internal.strategies.partition.get_instances_list()) > 0
def test_get_internal_data_strategies_partition_get():
assert len(ec2_compare.internal.strategies.partition.get) > 0
| 37.3
| 80
| 0.857909
| 50
| 373
| 6.02
| 0.36
| 0.378738
| 0.292359
| 0.27907
| 0.827243
| 0.61794
| 0.61794
| 0.61794
| 0
| 0
| 0
| 0.014409
| 0.069705
| 373
| 9
| 81
| 41.444444
| 0.853026
| 0.093834
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 9
|
a0e17dcfa9b4b587766f6c8f8881b46a60f94800
| 143
|
py
|
Python
|
src/django_handy_models/tests.py
|
Feelixe-tin/django-handy-models
|
dbc279ff95c5d7e5f5eaa308612d1d7fc3abb005
|
[
"MIT"
] | 2
|
2021-06-12T20:32:27.000Z
|
2021-06-25T06:37:05.000Z
|
src/django_handy_models/tests.py
|
Feelixe-tin/django-handy-models
|
dbc279ff95c5d7e5f5eaa308612d1d7fc3abb005
|
[
"MIT"
] | null | null | null |
src/django_handy_models/tests.py
|
Feelixe-tin/django-handy-models
|
dbc279ff95c5d7e5f5eaa308612d1d7fc3abb005
|
[
"MIT"
] | null | null | null |
from django.test import TestCase
class HandyModelsTestCase(TestCase):
fixtures = ['django_handy_models/fixtures/django_handy_models.json']
| 35.75
| 72
| 0.825175
| 17
| 143
| 6.705882
| 0.647059
| 0.245614
| 0.333333
| 0.438596
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 143
| 4
| 72
| 35.75
| 0.876923
| 0
| 0
| 0
| 0
| 0
| 0.368056
| 0.368056
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
a0efcf2e22a2f06884bbf4d5b58fc770851807a5
| 205
|
py
|
Python
|
coms/src/mapmerge/__init__.py
|
tylerferrara/coms
|
5070b65836f0ff3538f787e4cbe46203355270ea
|
[
"MIT"
] | null | null | null |
coms/src/mapmerge/__init__.py
|
tylerferrara/coms
|
5070b65836f0ff3538f787e4cbe46203355270ea
|
[
"MIT"
] | 5
|
2022-02-11T00:22:24.000Z
|
2022-02-15T01:31:28.000Z
|
coms/src/mapmerge/__init__.py
|
tylerferrara/coms
|
5070b65836f0ff3538f787e4cbe46203355270ea
|
[
"MIT"
] | null | null | null |
from mapmerge.constants import *
from mapmerge.keypoint_merge import *
from mapmerge.merge_utils import *
from mapmerge.ros_utils import *
from mapmerge.hough_merge import *
from mapmerge.service import *
| 29.285714
| 37
| 0.82439
| 28
| 205
| 5.892857
| 0.357143
| 0.436364
| 0.545455
| 0.278788
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117073
| 205
| 6
| 38
| 34.166667
| 0.911602
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
9d2be5a4699f2d1df5be2d2c855fd50cc635a501
| 10,748
|
py
|
Python
|
tests/validators/test_data_set.py
|
ScholarPack/api-tools
|
6547e0f289391d2a3fc69eaafebc80f92c406513
|
[
"MIT"
] | 3
|
2020-07-04T18:51:01.000Z
|
2020-07-29T08:41:11.000Z
|
tests/validators/test_data_set.py
|
ScholarPack/api-tools
|
6547e0f289391d2a3fc69eaafebc80f92c406513
|
[
"MIT"
] | 6
|
2020-07-08T09:26:36.000Z
|
2021-09-23T11:10:40.000Z
|
tests/validators/test_data_set.py
|
ScholarPack/flask-api-tools
|
6547e0f289391d2a3fc69eaafebc80f92c406513
|
[
"MIT"
] | null | null | null |
from cerberus import DocumentError
from datetime import date, datetime
from flask_api_tools.validators import DataSet, Validator
import pytest
class TestDataSet:
def test_validate_object(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
"string_2": {"type": "string", "coerce": "to_string"},
"string_3": {
"type": "string",
"nullable": True,
"coerce": "to_nullable_string",
},
"integer_1": {"type": "integer", "coerce": "to_integer"},
"integer_2": {
"type": "integer",
"nullable": True,
"coerce": "to_nullable_integer",
},
"boolean_1": {"coerce": "to_bool"},
"float_1": {"type": "float", "coerce": "to_float"},
"float_2": {
"type": "float",
"nullable": True,
"coerce": "to_nullable_float",
},
}
data = {
"string_1": "7c674878-e544-431c-8c11-f11565299cac",
"string_2": None,
"string_3": None,
"integer_1": None,
"integer_2": None,
"boolean_1": 1,
"float_1": None,
"float_2": None,
}
result = {
"string_1": "7c674878-e544-431c-8c11-f11565299cac",
"string_2": "",
"string_3": None,
"integer_1": 0,
"integer_2": None,
"boolean_1": True,
"float_1": 0.0,
"float_2": None,
}
validated = Example.validate_object(data)
assert validated == result
def test_validate_objects(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
"string_2": {"type": "string", "coerce": "to_string"},
"string_3": {
"type": "string",
"nullable": True,
"coerce": "to_nullable_string",
},
"integer_1": {"type": "integer", "coerce": "to_integer"},
"integer_2": {
"type": "integer",
"nullable": True,
"coerce": "to_nullable_integer",
},
"boolean_1": {"coerce": "to_bool"},
"float_1": {"type": "float", "coerce": "to_float"},
"float_2": {
"type": "float",
"nullable": True,
"coerce": "to_nullable_float",
},
}
data = {
"string_1": "7c674878-e544-431c-8c11-f11565299cac",
"string_2": None,
"string_3": None,
"integer_1": None,
"integer_2": None,
"boolean_1": 1,
"float_1": None,
"float_2": None,
}
result = {
"string_1": "7c674878-e544-431c-8c11-f11565299cac",
"string_2": "",
"string_3": None,
"integer_1": 0,
"integer_2": None,
"boolean_1": True,
"float_1": 0.0,
"float_2": None,
}
validated = Example.validate_objects([data])
assert validated == [result]
def test_validate_one(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {
"data": [
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
]
}
result = {
"string_1": "7c674878-e544-431c-8c11-f11565299cac",
}
validated = Example.validate_one(data)
assert validated == result
def test_validate_one_no_data(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {}
result = {}
validated = Example.validate_one(data)
assert validated == result
def test_validate_many(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {
"data": [
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
]
}
result = [
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
{"string_1": "7c674878-e544-431c-8c11-f11565299cac"},
]
validated = Example.validate_many(data)
assert validated == result
def test_validate_many_no_data(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {}
result = []
validated = Example.validate_many(data)
assert validated == result
def test_a_simple_validation_failure(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string"},
}
data = {
"string_1": 1337,
}
with pytest.raises(DocumentError):
validated = Example.validate_object(data)
with pytest.raises(DocumentError):
validated = Example.validate_objects([data])
with pytest.raises(DocumentError):
validated = Example.validate_one({"data": [data]})
with pytest.raises(DocumentError):
validated = Example.validate_many({"data": [data, data]})
def test_validate_object_unknown_key(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
result = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
with pytest.raises(DocumentError):
validated = Example.validate_object(data)
Example.allow_unknown = True
validated = Example.validate_object(data)
assert validated == result
def test_validate_objects_unknown_key(self):
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
result = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
with pytest.raises(DocumentError):
validated = Example.validate_objects([data])
Example.allow_unknown = True
validated = Example.validate_objects([data])
assert validated == [result]
def test_local_config_updates_validator(self):
class Example1(DataSet):
allow_unknown = True
ignore_none_values = True
purge_readonly = True
purge_unknown = True
require_all = False
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
class Example2(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
assert not Example1._validator.allow_unknown
assert not Example1._validator.ignore_none_values
assert not Example1._validator.purge_readonly
assert not Example1._validator.purge_unknown
assert not Example1._validator.require_all
assert not Example2._validator.allow_unknown
assert not Example2._validator.ignore_none_values
assert not Example2._validator.purge_readonly
assert not Example2._validator.purge_unknown
assert not Example2._validator.require_all
data = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
result = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
validated = Example1.validate_object(data)
assert not Example1._validator.allow_unknown
assert not Example1._validator.ignore_none_values
assert not Example1._validator.purge_readonly
assert not Example1._validator.purge_unknown
assert not Example1._validator.require_all
with pytest.raises(DocumentError):
validated = Example2.validate_object(data)
assert not Example2._validator.allow_unknown
assert not Example2._validator.ignore_none_values
assert not Example2._validator.purge_readonly
assert not Example2._validator.purge_unknown
assert not Example2._validator.require_all
def test_local_config_only_affects_local_dataset(self):
class Example1(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
class Example2(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
data = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
result = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
with pytest.raises(DocumentError):
validated = Example1.validate_object(data)
with pytest.raises(DocumentError):
validated = Example2.validate_object(data)
Example1.allow_unknown = True
validated = Example1.validate_object(data)
assert validated == result
with pytest.raises(DocumentError):
validated = Example2.validate_object(data)
def test_replacing_validator(self):
DataSet.set_validator(Validator(allow_unknown=True))
class Example(DataSet):
schema = {
"string_1": {"type": "string", "check_with": "uuid"},
}
assert Example._validator.allow_unknown
assert not Example._validator.ignore_none_values
assert not Example._validator.purge_readonly
assert not Example._validator.purge_unknown
assert not Example._validator.require_all
data = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
result = {
"string_2": "7c674878-e544-431c-8c11-f11565299cac",
}
validated = Example.validate_object(data)
assert validated == result
| 31.893175
| 73
| 0.526424
| 986
| 10,748
| 5.494929
| 0.080122
| 0.033592
| 0.062016
| 0.077519
| 0.903285
| 0.877076
| 0.855666
| 0.855666
| 0.809524
| 0.736988
| 0
| 0.090175
| 0.355136
| 10,748
| 336
| 74
| 31.988095
| 0.691531
| 0
| 0
| 0.72695
| 0
| 0
| 0.200223
| 0.070339
| 0
| 0
| 0
| 0
| 0.124113
| 1
| 0.042553
| false
| 0
| 0.014184
| 0
| 0.109929
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
9d520c28806c199f0a0461cfe3bae06f96e0124c
| 174
|
py
|
Python
|
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/nixi/calculators/calc_freq_offset_comp.py
|
lmnotran/gecko_sdk
|
2e82050dc8823c9fe0e8908c1b2666fb83056230
|
[
"Zlib"
] | 82
|
2016-06-29T17:24:43.000Z
|
2021-04-16T06:49:17.000Z
|
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/nixi/calculators/calc_freq_offset_comp.py
|
lmnotran/gecko_sdk
|
2e82050dc8823c9fe0e8908c1b2666fb83056230
|
[
"Zlib"
] | 6
|
2022-01-12T18:22:08.000Z
|
2022-03-25T10:19:27.000Z
|
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/nixi/calculators/calc_freq_offset_comp.py
|
lmnotran/gecko_sdk
|
2e82050dc8823c9fe0e8908c1b2666fb83056230
|
[
"Zlib"
] | 56
|
2016-08-02T10:50:50.000Z
|
2021-07-19T08:57:34.000Z
|
from pyradioconfig.parts.jumbo.calculators.calc_freq_offset_comp import CALC_Freq_Offset_Comp_jumbo
class CALC_Freq_Offset_Comp_nixi(CALC_Freq_Offset_Comp_jumbo):
pass
| 29
| 99
| 0.885057
| 27
| 174
| 5.148148
| 0.481481
| 0.230216
| 0.402878
| 0.517986
| 0.330935
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074713
| 174
| 6
| 100
| 29
| 0.863354
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 9
|
c23391c86fe90f92feed5932fe15aaa4022e147f
| 27,727
|
py
|
Python
|
datcore-sdk/python/datcore_sdk/api/annotations_api.py
|
mguidon/aiohttp-dsm
|
612e4c7f6f73df7d6752269965c428fda0276191
|
[
"MIT"
] | null | null | null |
datcore-sdk/python/datcore_sdk/api/annotations_api.py
|
mguidon/aiohttp-dsm
|
612e4c7f6f73df7d6752269965c428fda0276191
|
[
"MIT"
] | null | null | null |
datcore-sdk/python/datcore_sdk/api/annotations_api.py
|
mguidon/aiohttp-dsm
|
612e4c7f6f73df7d6752269965c428fda0276191
|
[
"MIT"
] | null | null | null |
# coding: utf-8
"""
Blackfynn Swagger
Swagger documentation for the Blackfynn api # noqa: E501
OpenAPI spec version: 1.0.0
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from datcore_sdk.api_client import ApiClient
class AnnotationsApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def create_annotation(self, create_annotation_request, **kwargs): # noqa: E501
"""creates an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_annotation(create_annotation_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateAnnotationRequest create_annotation_request: (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.create_annotation_with_http_info(create_annotation_request, **kwargs) # noqa: E501
else:
(data) = self.create_annotation_with_http_info(create_annotation_request, **kwargs) # noqa: E501
return data
def create_annotation_with_http_info(self, create_annotation_request, **kwargs): # noqa: E501
"""creates an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_annotation_with_http_info(create_annotation_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateAnnotationRequest create_annotation_request: (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['create_annotation_request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method create_annotation" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'create_annotation_request' is set
if ('create_annotation_request' not in local_var_params or
local_var_params['create_annotation_request'] is None):
raise ValueError("Missing the required parameter `create_annotation_request` when calling `create_annotation`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'create_annotation_request' in local_var_params:
body_params = local_var_params['create_annotation_request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='AnnotationResponse', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def create_layer(self, create_layer_request, **kwargs): # noqa: E501
"""creates an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_layer(create_layer_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateLayerRequest create_layer_request: (required)
:return: AnnotationLayer
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.create_layer_with_http_info(create_layer_request, **kwargs) # noqa: E501
else:
(data) = self.create_layer_with_http_info(create_layer_request, **kwargs) # noqa: E501
return data
def create_layer_with_http_info(self, create_layer_request, **kwargs): # noqa: E501
"""creates an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_layer_with_http_info(create_layer_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateLayerRequest create_layer_request: (required)
:return: AnnotationLayer
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['create_layer_request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method create_layer" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'create_layer_request' is set
if ('create_layer_request' not in local_var_params or
local_var_params['create_layer_request'] is None):
raise ValueError("Missing the required parameter `create_layer_request` when calling `create_layer`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'create_layer_request' in local_var_params:
body_params = local_var_params['create_layer_request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/layer', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='AnnotationLayer', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_annotation(self, id, **kwargs): # noqa: E501
"""delete an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_annotation(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:param bool with_discussions: true if we want to delete related discussions too
:return: int
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_annotation_with_http_info(id, **kwargs) # noqa: E501
else:
(data) = self.delete_annotation_with_http_info(id, **kwargs) # noqa: E501
return data
def delete_annotation_with_http_info(self, id, **kwargs): # noqa: E501
"""delete an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_annotation_with_http_info(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:param bool with_discussions: true if we want to delete related discussions too
:return: int
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['id', 'with_discussions'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_annotation" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in local_var_params or
local_var_params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `delete_annotation`") # noqa: E501
collection_formats = {}
path_params = {}
if 'id' in local_var_params:
path_params['id'] = local_var_params['id'] # noqa: E501
query_params = []
if 'with_discussions' in local_var_params:
query_params.append(('withDiscussions', local_var_params['with_discussions'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/{id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='int', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_layer(self, id, **kwargs): # noqa: E501
"""delete an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_layer(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int id: the id of the layer to delete (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_layer_with_http_info(id, **kwargs) # noqa: E501
else:
(data) = self.delete_layer_with_http_info(id, **kwargs) # noqa: E501
return data
def delete_layer_with_http_info(self, id, **kwargs): # noqa: E501
"""delete an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_layer_with_http_info(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int id: the id of the layer to delete (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_layer" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in local_var_params or
local_var_params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `delete_layer`") # noqa: E501
collection_formats = {}
path_params = {}
if 'id' in local_var_params:
path_params['id'] = local_var_params['id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/layer/{id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def get_annotation_operation(self, id, **kwargs): # noqa: E501
"""get an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_annotation_operation(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_annotation_operation_with_http_info(id, **kwargs) # noqa: E501
else:
(data) = self.get_annotation_operation_with_http_info(id, **kwargs) # noqa: E501
return data
def get_annotation_operation_with_http_info(self, id, **kwargs): # noqa: E501
"""get an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_annotation_operation_with_http_info(id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_annotation_operation" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in local_var_params or
local_var_params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `get_annotation_operation`") # noqa: E501
collection_formats = {}
path_params = {}
if 'id' in local_var_params:
path_params['id'] = local_var_params['id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/{id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='AnnotationResponse', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def update_annotation(self, id, update_annotation_request, **kwargs): # noqa: E501
"""updates an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_annotation(id, update_annotation_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:param UpdateAnnotationRequest update_annotation_request: the comment to add (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.update_annotation_with_http_info(id, update_annotation_request, **kwargs) # noqa: E501
else:
(data) = self.update_annotation_with_http_info(id, update_annotation_request, **kwargs) # noqa: E501
return data
def update_annotation_with_http_info(self, id, update_annotation_request, **kwargs): # noqa: E501
"""updates an annotation # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_annotation_with_http_info(id, update_annotation_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str id: the id of the annotation (required)
:param UpdateAnnotationRequest update_annotation_request: the comment to add (required)
:return: AnnotationResponse
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['id', 'update_annotation_request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method update_annotation" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in local_var_params or
local_var_params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `update_annotation`") # noqa: E501
# verify the required parameter 'update_annotation_request' is set
if ('update_annotation_request' not in local_var_params or
local_var_params['update_annotation_request'] is None):
raise ValueError("Missing the required parameter `update_annotation_request` when calling `update_annotation`") # noqa: E501
collection_formats = {}
path_params = {}
if 'id' in local_var_params:
path_params['id'] = local_var_params['id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'update_annotation_request' in local_var_params:
body_params = local_var_params['update_annotation_request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/{id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='AnnotationResponse', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def update_layer(self, update_layer_request, **kwargs): # noqa: E501
"""update an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_layer(update_layer_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param UpdateLayerRequest update_layer_request: (required)
:return: AnnotationLayer
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.update_layer_with_http_info(update_layer_request, **kwargs) # noqa: E501
else:
(data) = self.update_layer_with_http_info(update_layer_request, **kwargs) # noqa: E501
return data
def update_layer_with_http_info(self, update_layer_request, **kwargs): # noqa: E501
"""update an annotation layer # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_layer_with_http_info(update_layer_request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param UpdateLayerRequest update_layer_request: (required)
:return: AnnotationLayer
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['update_layer_request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method update_layer" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'update_layer_request' is set
if ('update_layer_request' not in local_var_params or
local_var_params['update_layer_request'] is None):
raise ValueError("Missing the required parameter `update_layer_request` when calling `update_layer`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'update_layer_request' in local_var_params:
body_params = local_var_params['update_layer_request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/annotations/layer/{id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='AnnotationLayer', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
| 39.61
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| 0.624698
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| 0.050657
| 0.050934
| 0.077135
| 0.030854
| 0.95225
| 0.944965
| 0.930089
| 0.92917
| 0.91962
| 0.918886
| 0
| 0.01418
| 0.290367
| 27,727
| 699
| 138
| 39.666667
| 0.81602
| 0.306344
| 0
| 0.759259
| 1
| 0
| 0.177521
| 0.050736
| 0
| 0
| 0
| 0
| 0
| 1
| 0.039683
| false
| 0
| 0.010582
| 0
| 0.108466
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
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| null | 0
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|
0
| 8
|
c23a841a37858c79e582eb2af44025fd8f43ea50
| 22,519
|
py
|
Python
|
tests/unit/test_master.py
|
MeAndTheFirefly/salt
|
77fc3ec3ee25c1b769cc66ddee09067d18080844
|
[
"Apache-2.0"
] | 2
|
2016-11-14T15:08:53.000Z
|
2016-11-20T09:25:30.000Z
|
tests/unit/test_master.py
|
snetsystems/salt
|
6f8bedfc2453624e00037f80b8099ed010fad506
|
[
"Apache-2.0"
] | 3
|
2021-03-31T19:53:24.000Z
|
2021-12-13T20:46:19.000Z
|
tests/unit/test_master.py
|
snetsystems/salt
|
6f8bedfc2453624e00037f80b8099ed010fad506
|
[
"Apache-2.0"
] | 2
|
2020-11-04T06:32:02.000Z
|
2020-11-06T11:01:18.000Z
|
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import salt.config
import salt.master
from tests.support.helpers import slowTest
from tests.support.mock import MagicMock, patch
from tests.support.unit import TestCase
class TransportMethodsTest(TestCase):
def test_transport_methods(self):
class Foo(salt.master.TransportMethods):
expose_methods = ["bar"]
def bar(self):
pass
def bang(self):
pass
foo = Foo()
assert foo.get_method("bar") is not None
assert foo.get_method("bang") is None
def test_aes_funcs_white(self):
"""
Validate methods exposed on AESFuncs exist and are callable
"""
opts = salt.config.master_config(None)
aes_funcs = salt.master.AESFuncs(opts)
for name in aes_funcs.expose_methods:
func = getattr(aes_funcs, name, None)
assert callable(func)
def test_aes_funcs_black(self):
"""
Validate methods on AESFuncs that should not be called remotely
"""
opts = salt.config.master_config(None)
aes_funcs = salt.master.AESFuncs(opts)
# Any callable that should not explicitly be allowed should be added
# here.
blacklist_methods = [
"_AESFuncs__setup_fileserver",
"_AESFuncs__verify_load",
"_AESFuncs__verify_minion",
"_AESFuncs__verify_minion_publish",
"__class__",
"__delattr__",
"__dir__",
"__eq__",
"__format__",
"__ge__",
"__getattribute__",
"__gt__",
"__hash__",
"__init__",
"__init_subclass__",
"__le__",
"__lt__",
"__ne__",
"__new__",
"__reduce__",
"__reduce_ex__",
"__repr__",
"__setattr__",
"__sizeof__",
"__str__",
"__subclasshook__",
"get_method",
"run_func",
]
for name in dir(aes_funcs):
if name in aes_funcs.expose_methods:
continue
if not callable(getattr(aes_funcs, name)):
continue
assert name in blacklist_methods, name
def test_clear_funcs_white(self):
"""
Validate methods exposed on ClearFuncs exist and are callable
"""
opts = salt.config.master_config(None)
clear_funcs = salt.master.ClearFuncs(opts, {})
for name in clear_funcs.expose_methods:
func = getattr(clear_funcs, name, None)
assert callable(func)
def test_clear_funcs_black(self):
"""
Validate methods on ClearFuncs that should not be called remotely
"""
opts = salt.config.master_config(None)
clear_funcs = salt.master.ClearFuncs(opts, {})
blacklist_methods = [
"__class__",
"__delattr__",
"__dir__",
"__eq__",
"__format__",
"__ge__",
"__getattribute__",
"__gt__",
"__hash__",
"__init__",
"__init_subclass__",
"__le__",
"__lt__",
"__ne__",
"__new__",
"__reduce__",
"__reduce_ex__",
"__repr__",
"__setattr__",
"__sizeof__",
"__str__",
"__subclasshook__",
"_prep_auth_info",
"_prep_jid",
"_prep_pub",
"_send_pub",
"_send_ssh_pub",
"get_method",
]
for name in dir(clear_funcs):
if name in clear_funcs.expose_methods:
continue
if not callable(getattr(clear_funcs, name)):
continue
assert name in blacklist_methods, name
class ClearFuncsTestCase(TestCase):
"""
TestCase for salt.master.ClearFuncs class
"""
@classmethod
def setUpClass(cls):
opts = salt.config.master_config(None)
cls.clear_funcs = salt.master.ClearFuncs(opts, {})
@classmethod
def tearDownClass(cls):
del cls.clear_funcs
def test_get_method(self):
assert getattr(self.clear_funcs, "_send_pub", None) is not None
assert self.clear_funcs.get_method("_send_pub") is None
# runner tests
@slowTest
def test_runner_token_not_authenticated(self):
"""
Asserts that a TokenAuthenticationError is returned when the token can't authenticate.
"""
mock_ret = {
"error": {
"name": "TokenAuthenticationError",
"message": 'Authentication failure of type "token" occurred.',
}
}
ret = self.clear_funcs.runner({"token": "asdfasdfasdfasdf"})
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_token_authorization_error(self):
"""
Asserts that a TokenAuthenticationError is returned when the token authenticates, but is
not authorized.
"""
token = "asdfasdfasdfasdf"
clear_load = {"token": token, "fun": "test.arg"}
mock_token = {"token": token, "eauth": "foo", "name": "test"}
mock_ret = {
"error": {
"name": "TokenAuthenticationError",
"message": 'Authentication failure of type "token" occurred '
"for user test.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_token", MagicMock(return_value=mock_token)
), patch("salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])):
ret = self.clear_funcs.runner(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_token_salt_invocation_error(self):
"""
Asserts that a SaltInvocationError is returned when the token authenticates, but the
command is malformed.
"""
token = "asdfasdfasdfasdf"
clear_load = {"token": token, "fun": "badtestarg"}
mock_token = {"token": token, "eauth": "foo", "name": "test"}
mock_ret = {
"error": {
"name": "SaltInvocationError",
"message": "A command invocation error occurred: Check syntax.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_token", MagicMock(return_value=mock_token)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=["testing"])
):
ret = self.clear_funcs.runner(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_eauth_not_authenticated(self):
"""
Asserts that an EauthAuthenticationError is returned when the user can't authenticate.
"""
mock_ret = {
"error": {
"name": "EauthAuthenticationError",
"message": 'Authentication failure of type "eauth" occurred for '
"user UNKNOWN.",
}
}
ret = self.clear_funcs.runner({"eauth": "foo"})
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_eauth_authorization_error(self):
"""
Asserts that an EauthAuthenticationError is returned when the user authenticates, but is
not authorized.
"""
clear_load = {"eauth": "foo", "username": "test", "fun": "test.arg"}
mock_ret = {
"error": {
"name": "EauthAuthenticationError",
"message": 'Authentication failure of type "eauth" occurred for '
"user test.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_eauth", MagicMock(return_value=True)
), patch("salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])):
ret = self.clear_funcs.runner(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_eauth_salt_invocation_error(self):
"""
Asserts that an EauthAuthenticationError is returned when the user authenticates, but the
command is malformed.
"""
clear_load = {"eauth": "foo", "username": "test", "fun": "bad.test.arg.func"}
mock_ret = {
"error": {
"name": "SaltInvocationError",
"message": "A command invocation error occurred: Check syntax.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_eauth", MagicMock(return_value=True)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=["testing"])
):
ret = self.clear_funcs.runner(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_runner_user_not_authenticated(self):
"""
Asserts that an UserAuthenticationError is returned when the user can't authenticate.
"""
mock_ret = {
"error": {
"name": "UserAuthenticationError",
"message": 'Authentication failure of type "user" occurred',
}
}
ret = self.clear_funcs.runner({})
self.assertDictEqual(mock_ret, ret)
# wheel tests
@slowTest
def test_wheel_token_not_authenticated(self):
"""
Asserts that a TokenAuthenticationError is returned when the token can't authenticate.
"""
mock_ret = {
"error": {
"name": "TokenAuthenticationError",
"message": 'Authentication failure of type "token" occurred.',
}
}
ret = self.clear_funcs.wheel({"token": "asdfasdfasdfasdf"})
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_token_authorization_error(self):
"""
Asserts that a TokenAuthenticationError is returned when the token authenticates, but is
not authorized.
"""
token = "asdfasdfasdfasdf"
clear_load = {"token": token, "fun": "test.arg"}
mock_token = {"token": token, "eauth": "foo", "name": "test"}
mock_ret = {
"error": {
"name": "TokenAuthenticationError",
"message": 'Authentication failure of type "token" occurred '
"for user test.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_token", MagicMock(return_value=mock_token)
), patch("salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])):
ret = self.clear_funcs.wheel(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_token_salt_invocation_error(self):
"""
Asserts that a SaltInvocationError is returned when the token authenticates, but the
command is malformed.
"""
token = "asdfasdfasdfasdf"
clear_load = {"token": token, "fun": "badtestarg"}
mock_token = {"token": token, "eauth": "foo", "name": "test"}
mock_ret = {
"error": {
"name": "SaltInvocationError",
"message": "A command invocation error occurred: Check syntax.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_token", MagicMock(return_value=mock_token)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=["testing"])
):
ret = self.clear_funcs.wheel(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_eauth_not_authenticated(self):
"""
Asserts that an EauthAuthenticationError is returned when the user can't authenticate.
"""
mock_ret = {
"error": {
"name": "EauthAuthenticationError",
"message": 'Authentication failure of type "eauth" occurred for '
"user UNKNOWN.",
}
}
ret = self.clear_funcs.wheel({"eauth": "foo"})
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_eauth_authorization_error(self):
"""
Asserts that an EauthAuthenticationError is returned when the user authenticates, but is
not authorized.
"""
clear_load = {"eauth": "foo", "username": "test", "fun": "test.arg"}
mock_ret = {
"error": {
"name": "EauthAuthenticationError",
"message": 'Authentication failure of type "eauth" occurred for '
"user test.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_eauth", MagicMock(return_value=True)
), patch("salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])):
ret = self.clear_funcs.wheel(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_eauth_salt_invocation_error(self):
"""
Asserts that an EauthAuthenticationError is returned when the user authenticates, but the
command is malformed.
"""
clear_load = {"eauth": "foo", "username": "test", "fun": "bad.test.arg.func"}
mock_ret = {
"error": {
"name": "SaltInvocationError",
"message": "A command invocation error occurred: Check syntax.",
}
}
with patch(
"salt.auth.LoadAuth.authenticate_eauth", MagicMock(return_value=True)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=["testing"])
):
ret = self.clear_funcs.wheel(clear_load)
self.assertDictEqual(mock_ret, ret)
@slowTest
def test_wheel_user_not_authenticated(self):
"""
Asserts that an UserAuthenticationError is returned when the user can't authenticate.
"""
mock_ret = {
"error": {
"name": "UserAuthenticationError",
"message": 'Authentication failure of type "user" occurred',
}
}
ret = self.clear_funcs.wheel({})
self.assertDictEqual(mock_ret, ret)
# publish tests
@slowTest
def test_publish_user_is_blacklisted(self):
"""
Asserts that an AuthorizationError is returned when the user has been blacklisted.
"""
mock_ret = {
"error": {
"name": "AuthorizationError",
"message": "Authorization error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=True)
):
self.assertEqual(
mock_ret, self.clear_funcs.publish({"user": "foo", "fun": "test.arg"})
)
@slowTest
def test_publish_cmd_blacklisted(self):
"""
Asserts that an AuthorizationError is returned when the command has been blacklisted.
"""
mock_ret = {
"error": {
"name": "AuthorizationError",
"message": "Authorization error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=True)
):
self.assertEqual(
mock_ret, self.clear_funcs.publish({"user": "foo", "fun": "test.arg"})
)
@slowTest
def test_publish_token_not_authenticated(self):
"""
Asserts that an AuthenticationError is returned when the token can't authenticate.
"""
mock_ret = {
"error": {
"name": "AuthenticationError",
"message": "Authentication error occurred.",
}
}
load = {
"user": "foo",
"fun": "test.arg",
"tgt": "test_minion",
"kwargs": {"token": "asdfasdfasdfasdf"},
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_token_authorization_error(self):
"""
Asserts that an AuthorizationError is returned when the token authenticates, but is not
authorized.
"""
token = "asdfasdfasdfasdf"
load = {
"user": "foo",
"fun": "test.arg",
"tgt": "test_minion",
"arg": "bar",
"kwargs": {"token": token},
}
mock_token = {"token": token, "eauth": "foo", "name": "test"}
mock_ret = {
"error": {
"name": "AuthorizationError",
"message": "Authorization error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.auth.LoadAuth.authenticate_token", MagicMock(return_value=mock_token)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_eauth_not_authenticated(self):
"""
Asserts that an AuthenticationError is returned when the user can't authenticate.
"""
load = {
"user": "test",
"fun": "test.arg",
"tgt": "test_minion",
"kwargs": {"eauth": "foo"},
}
mock_ret = {
"error": {
"name": "AuthenticationError",
"message": "Authentication error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_eauth_authorization_error(self):
"""
Asserts that an AuthorizationError is returned when the user authenticates, but is not
authorized.
"""
load = {
"user": "test",
"fun": "test.arg",
"tgt": "test_minion",
"kwargs": {"eauth": "foo"},
"arg": "bar",
}
mock_ret = {
"error": {
"name": "AuthorizationError",
"message": "Authorization error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.auth.LoadAuth.authenticate_eauth", MagicMock(return_value=True)
), patch(
"salt.auth.LoadAuth.get_auth_list", MagicMock(return_value=[])
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_user_not_authenticated(self):
"""
Asserts that an AuthenticationError is returned when the user can't authenticate.
"""
load = {"user": "test", "fun": "test.arg", "tgt": "test_minion"}
mock_ret = {
"error": {
"name": "AuthenticationError",
"message": "Authentication error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_user_authenticated_missing_auth_list(self):
"""
Asserts that an AuthenticationError is returned when the user has an effective user id and is
authenticated, but the auth_list is empty.
"""
load = {
"user": "test",
"fun": "test.arg",
"tgt": "test_minion",
"kwargs": {"user": "test"},
"arg": "foo",
}
mock_ret = {
"error": {
"name": "AuthenticationError",
"message": "Authentication error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.auth.LoadAuth.authenticate_key",
MagicMock(return_value="fake-user-key"),
), patch(
"salt.utils.master.get_values_of_matching_keys", MagicMock(return_value=[])
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
@slowTest
def test_publish_user_authorization_error(self):
"""
Asserts that an AuthorizationError is returned when the user authenticates, but is not
authorized.
"""
load = {
"user": "test",
"fun": "test.arg",
"tgt": "test_minion",
"kwargs": {"user": "test"},
"arg": "foo",
}
mock_ret = {
"error": {
"name": "AuthorizationError",
"message": "Authorization error occurred.",
}
}
with patch(
"salt.acl.PublisherACL.user_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.acl.PublisherACL.cmd_is_blacklisted", MagicMock(return_value=False)
), patch(
"salt.auth.LoadAuth.authenticate_key",
MagicMock(return_value="fake-user-key"),
), patch(
"salt.utils.master.get_values_of_matching_keys",
MagicMock(return_value=["test"]),
), patch(
"salt.utils.minions.CkMinions.auth_check", MagicMock(return_value=False)
):
self.assertEqual(mock_ret, self.clear_funcs.publish(load))
| 34.016616
| 101
| 0.558062
| 2,137
| 22,519
| 5.605054
| 0.087506
| 0.026883
| 0.070129
| 0.032643
| 0.896393
| 0.883203
| 0.863416
| 0.85657
| 0.842545
| 0.824261
| 0
| 0.000066
| 0.331365
| 22,519
| 661
| 102
| 34.068079
| 0.795444
| 0.117989
| 0
| 0.720238
| 0
| 0
| 0.260144
| 0.10045
| 0
| 0
| 0
| 0
| 0.061508
| 1
| 0.065476
| false
| 0.003968
| 0.011905
| 0
| 0.083333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
5f0d1f28da677613425d2d9e28e889364af266dd
| 1,506
|
py
|
Python
|
tests/test_91.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
tests/test_91.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
tests/test_91.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import pytest
"""
Test 91. Decode Ways
"""
@pytest.fixture(scope="session")
def init_variables_91():
from src.leetcode_91_decode_ways import Solution
solution = Solution()
def _init_variables_91():
return solution
yield _init_variables_91
class TestClass91:
def test_solution_0(self, init_variables_91):
assert init_variables_91().numDecodings("12") == 2
def test_solution_1(self, init_variables_91):
assert init_variables_91().numDecodings("226") == 3
def test_solution_2(self, init_variables_91):
assert init_variables_91().numDecodings("0") == 0
def test_solution_3(self, init_variables_91):
assert init_variables_91().numDecodings("06") == 0
#!/usr/bin/env python
import pytest
"""
Test 91. Decode Ways
"""
@pytest.fixture(scope="session")
def init_variables_91():
from src.leetcode_91_decode_ways import Solution
solution = Solution()
def _init_variables_91():
return solution
yield _init_variables_91
class TestClass91:
def test_solution_0(self, init_variables_91):
assert init_variables_91().numDecodings("12") == 2
def test_solution_1(self, init_variables_91):
assert init_variables_91().numDecodings("226") == 3
def test_solution_2(self, init_variables_91):
assert init_variables_91().numDecodings("0") == 0
def test_solution_3(self, init_variables_91):
assert init_variables_91().numDecodings("06") == 0
| 21.826087
| 59
| 0.703851
| 200
| 1,506
| 4.95
| 0.17
| 0.288889
| 0.333333
| 0.153535
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0.071895
| 0.187251
| 1,506
| 68
| 60
| 22.147059
| 0.736928
| 0.02656
| 0
| 1
| 0
| 0
| 0.021307
| 0
| 0
| 0
| 0
| 0
| 0.235294
| 1
| 0.352941
| false
| 0
| 0.117647
| 0.058824
| 0.588235
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 11
|
5f1c6d7cba7bac5bca1df3a194065e24c31f8016
| 1,432
|
bzl
|
Python
|
ttoo/moonx.bzl
|
csuyangpeng/bazelexample_hitcache
|
2878753694ace940bd92705b8aa8e9a15b795a03
|
[
"Apache-2.0"
] | 1
|
2019-03-20T12:38:25.000Z
|
2019-03-20T12:38:25.000Z
|
ttoo/moonx.bzl
|
csuyangpeng/bazelexample_hitcache
|
2878753694ace940bd92705b8aa8e9a15b795a03
|
[
"Apache-2.0"
] | null | null | null |
ttoo/moonx.bzl
|
csuyangpeng/bazelexample_hitcache
|
2878753694ace940bd92705b8aa8e9a15b795a03
|
[
"Apache-2.0"
] | null | null | null |
def mx_cc_copts():
return ["-fdiagnostics-color=always", "-Werror"]
def mx_cuda_copts():
return ["-xcuda", "-std=c++11"]
def mx_cc_library(
name,
srcs = [],
deps = [],
copts = [],
**kwargs):
native.cc_library(
name = name,
copts = mx_cc_copts() + copts,
srcs = srcs,
deps = deps,
**kwargs
)
def mx_cc_binary(
name,
srcs = [],
deps = [],
copts = [],
**kwargs):
native.cc_binary(
name = name,
copts = mx_cc_copts() + copts,
srcs = srcs,
deps = deps,
**kwargs
)
def mx_cc_test(
name,
srcs = [],
deps = [],
copts = [],
**kwargs):
native.cc_test(
name = name,
copts = mx_cc_copts() + copts,
srcs = srcs,
deps = deps,
**kwargs
)
def mx_cuda_library(
name,
srcs = [],
deps = [],
copts = [],
**kwargs):
native.cc_library(
name = name,
copts = mx_cuda_copts() + copts,
srcs = srcs,
deps = deps,
**kwargs
)
def mx_cuda_binary(
name,
srcs = [],
deps = [],
copts = [],
**kwargs):
native.cc_binary(
name = name,
copts = mx_cuda_copts() + copts,
srcs = srcs,
deps = deps,
**kwargs
)
| 17.463415
| 52
| 0.425978
| 138
| 1,432
| 4.210145
| 0.15942
| 0.137694
| 0.10327
| 0.146299
| 0.839931
| 0.839931
| 0.839931
| 0.786575
| 0.786575
| 0.786575
| 0
| 0.002472
| 0.435056
| 1,432
| 81
| 53
| 17.679012
| 0.715698
| 0
| 0
| 0.782609
| 0
| 0
| 0.034242
| 0.018169
| 0
| 0
| 0
| 0
| 0
| 1
| 0.101449
| false
| 0
| 0
| 0.028986
| 0.130435
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
a043b701797543abb78c74811fe0477e46fe801b
| 48
|
py
|
Python
|
bnpy/mergemove/__init__.py
|
jun2tong/bnp-anomaly
|
c7fa106b5bb29ed6688a3d91e3f302a0a130b896
|
[
"BSD-3-Clause"
] | null | null | null |
bnpy/mergemove/__init__.py
|
jun2tong/bnp-anomaly
|
c7fa106b5bb29ed6688a3d91e3f302a0a130b896
|
[
"BSD-3-Clause"
] | null | null | null |
bnpy/mergemove/__init__.py
|
jun2tong/bnp-anomaly
|
c7fa106b5bb29ed6688a3d91e3f302a0a130b896
|
[
"BSD-3-Clause"
] | null | null | null |
from .MPlanner import selectCandidateMergePairs
| 24
| 47
| 0.895833
| 4
| 48
| 10.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 48
| 1
| 48
| 48
| 0.977273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 1
| 1
| 1
| null | 0
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| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
a05cd3f59f0625997dde54e36194ec4b3a496972
| 4,649
|
py
|
Python
|
custom/icds_reports/migrations/0194_auto_20200528_1024.py
|
dankohn/commcare-hq
|
42c40ad5881485d5192aab3dea5696942ee40810
|
[
"BSD-3-Clause"
] | 1
|
2020-07-14T13:00:23.000Z
|
2020-07-14T13:00:23.000Z
|
custom/icds_reports/migrations/0194_auto_20200528_1024.py
|
dankohn/commcare-hq
|
42c40ad5881485d5192aab3dea5696942ee40810
|
[
"BSD-3-Clause"
] | null | null | null |
custom/icds_reports/migrations/0194_auto_20200528_1024.py
|
dankohn/commcare-hq
|
42c40ad5881485d5192aab3dea5696942ee40810
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.28 on 2020-05-28 10:24
from __future__ import unicode_literals
from django.db import migrations, models
from custom.icds_reports.utils.migrations import get_view_migrations
class Migration(migrations.Migration):
dependencies = [
('icds_reports', '0193_adding_fields_to_sdd'),
]
operations = [
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_0_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_15_20_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_1_7_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_21_24_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_21_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_25_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_8_14_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='child_thr_eligible',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_0_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_15_20_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_1_7_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_21_24_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_21_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_25_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_8_14_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='lw_thr_eligible',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_0_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_15_20_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_1_7_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_21_24_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_21_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_25_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_8_14_days',
field=models.IntegerField(null=True),
),
migrations.AddField(
model_name='aggservicedeliveryreport',
name='pw_thr_eligible',
field=models.IntegerField(null=True),
)
]
| 33.934307
| 68
| 0.59045
| 418
| 4,649
| 6.284689
| 0.138756
| 0.164446
| 0.210126
| 0.246669
| 0.90217
| 0.90217
| 0.90217
| 0.887324
| 0.864484
| 0.864484
| 0
| 0.023647
| 0.308669
| 4,649
| 136
| 69
| 34.183824
| 0.793715
| 0.014842
| 0
| 0.736434
| 1
| 0
| 0.218484
| 0.131309
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.023256
| 0
| 0.046512
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
a06faea34dd6f63bdb6542f24a3d852383812013
| 23,973
|
py
|
Python
|
nova/tests/unit/api/openstack/compute/test_instance_usage_audit_log.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/api/openstack/compute/test_instance_usage_audit_log.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/api/openstack/compute/test_instance_usage_audit_log.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | 2
|
2017-07-20T17:31:34.000Z
|
2020-07-24T02:42:19.000Z
|
begin_unit
comment|'# Copyright (c) 2012 OpenStack Foundation'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n'
comment|'# a copy of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT'
nl|'\n'
comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the'
nl|'\n'
comment|'# License for the specific language governing permissions and limitations'
nl|'\n'
comment|'# under the License.'
nl|'\n'
nl|'\n'
name|'import'
name|'datetime'
newline|'\n'
nl|'\n'
name|'from'
name|'oslo_utils'
name|'import'
name|'fixture'
name|'as'
name|'utils_fixture'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
op|'.'
name|'api'
op|'.'
name|'openstack'
op|'.'
name|'compute'
name|'import'
name|'instance_usage_audit_log'
name|'as'
name|'v21_ial'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'api'
op|'.'
name|'openstack'
op|'.'
name|'compute'
op|'.'
name|'legacy_v2'
op|'.'
name|'contrib'
name|'import'
name|'instance_usage_audit_log'
name|'as'
name|'ial'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'context'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'exception'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'test'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
op|'.'
name|'api'
op|'.'
name|'openstack'
name|'import'
name|'fakes'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
op|'.'
name|'objects'
name|'import'
name|'test_service'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'utils'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|service_base
name|'service_base'
op|'='
name|'test_service'
op|'.'
name|'fake_service'
newline|'\n'
DECL|variable|TEST_COMPUTE_SERVICES
name|'TEST_COMPUTE_SERVICES'
op|'='
op|'['
name|'dict'
op|'('
name|'service_base'
op|','
name|'host'
op|'='
string|"'foo'"
op|','
name|'topic'
op|'='
string|"'compute'"
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'service_base'
op|','
name|'host'
op|'='
string|"'bar'"
op|','
name|'topic'
op|'='
string|"'compute'"
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'service_base'
op|','
name|'host'
op|'='
string|"'baz'"
op|','
name|'topic'
op|'='
string|"'compute'"
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'service_base'
op|','
name|'host'
op|'='
string|"'plonk'"
op|','
name|'topic'
op|'='
string|"'compute'"
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'service_base'
op|','
name|'host'
op|'='
string|"'wibble'"
op|','
name|'topic'
op|'='
string|"'bogus'"
op|')'
op|','
nl|'\n'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|begin1
name|'begin1'
op|'='
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2012'
op|','
number|'7'
op|','
number|'4'
op|','
number|'6'
op|','
number|'0'
op|','
number|'0'
op|')'
newline|'\n'
name|'begin2'
op|'='
name|'end1'
op|'='
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2012'
op|','
number|'7'
op|','
number|'5'
op|','
number|'6'
op|','
number|'0'
op|','
number|'0'
op|')'
newline|'\n'
name|'begin3'
op|'='
name|'end2'
op|'='
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2012'
op|','
number|'7'
op|','
number|'6'
op|','
number|'6'
op|','
number|'0'
op|','
number|'0'
op|')'
newline|'\n'
DECL|variable|end3
name|'end3'
op|'='
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2012'
op|','
number|'7'
op|','
number|'7'
op|','
number|'6'
op|','
number|'0'
op|','
number|'0'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
comment|'# test data'
nl|'\n'
nl|'\n'
nl|'\n'
DECL|variable|TEST_LOGS1
name|'TEST_LOGS1'
op|'='
op|'['
nl|'\n'
comment|'# all services done, no errors.'
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"plonk"'
op|','
name|'period_beginning'
op|'='
name|'begin1'
op|','
name|'period_ending'
op|'='
name|'end1'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'23'
op|','
name|'message'
op|'='
string|'"test1"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"baz"'
op|','
name|'period_beginning'
op|'='
name|'begin1'
op|','
name|'period_ending'
op|'='
name|'end1'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'17'
op|','
name|'message'
op|'='
string|'"test2"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"bar"'
op|','
name|'period_beginning'
op|'='
name|'begin1'
op|','
name|'period_ending'
op|'='
name|'end1'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'10'
op|','
name|'message'
op|'='
string|'"test3"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"foo"'
op|','
name|'period_beginning'
op|'='
name|'begin1'
op|','
name|'period_ending'
op|'='
name|'end1'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'7'
op|','
name|'message'
op|'='
string|'"test4"'
op|')'
op|','
nl|'\n'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|TEST_LOGS2
name|'TEST_LOGS2'
op|'='
op|'['
nl|'\n'
comment|'# some still running...'
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"plonk"'
op|','
name|'period_beginning'
op|'='
name|'begin2'
op|','
name|'period_ending'
op|'='
name|'end2'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'23'
op|','
name|'message'
op|'='
string|'"test5"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"baz"'
op|','
name|'period_beginning'
op|'='
name|'begin2'
op|','
name|'period_ending'
op|'='
name|'end2'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'17'
op|','
name|'message'
op|'='
string|'"test6"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"bar"'
op|','
name|'period_beginning'
op|'='
name|'begin2'
op|','
name|'period_ending'
op|'='
name|'end2'
op|','
nl|'\n'
name|'state'
op|'='
string|'"RUNNING"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'10'
op|','
name|'message'
op|'='
string|'"test7"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"foo"'
op|','
name|'period_beginning'
op|'='
name|'begin2'
op|','
name|'period_ending'
op|'='
name|'end2'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'7'
op|','
name|'message'
op|'='
string|'"test8"'
op|')'
op|','
nl|'\n'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|TEST_LOGS3
name|'TEST_LOGS3'
op|'='
op|'['
nl|'\n'
comment|'# some errors..'
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"plonk"'
op|','
name|'period_beginning'
op|'='
name|'begin3'
op|','
name|'period_ending'
op|'='
name|'end3'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'23'
op|','
name|'message'
op|'='
string|'"test9"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"baz"'
op|','
name|'period_beginning'
op|'='
name|'begin3'
op|','
name|'period_ending'
op|'='
name|'end3'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'2'
op|','
name|'task_items'
op|'='
number|'17'
op|','
name|'message'
op|'='
string|'"test10"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"bar"'
op|','
name|'period_beginning'
op|'='
name|'begin3'
op|','
name|'period_ending'
op|'='
name|'end3'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'0'
op|','
name|'task_items'
op|'='
number|'10'
op|','
name|'message'
op|'='
string|'"test11"'
op|')'
op|','
nl|'\n'
name|'dict'
op|'('
name|'host'
op|'='
string|'"foo"'
op|','
name|'period_beginning'
op|'='
name|'begin3'
op|','
name|'period_ending'
op|'='
name|'end3'
op|','
nl|'\n'
name|'state'
op|'='
string|'"DONE"'
op|','
name|'errors'
op|'='
number|'1'
op|','
name|'task_items'
op|'='
number|'7'
op|','
name|'message'
op|'='
string|'"test12"'
op|')'
op|','
nl|'\n'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_task_log_get_all
name|'def'
name|'fake_task_log_get_all'
op|'('
name|'context'
op|','
name|'task_name'
op|','
name|'begin'
op|','
name|'end'
op|','
nl|'\n'
name|'host'
op|'='
name|'None'
op|','
name|'state'
op|'='
name|'None'
op|')'
op|':'
newline|'\n'
indent|' '
name|'assert'
name|'task_name'
op|'=='
string|'"instance_usage_audit"'
newline|'\n'
nl|'\n'
name|'if'
name|'begin'
op|'=='
name|'begin1'
name|'and'
name|'end'
op|'=='
name|'end1'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'TEST_LOGS1'
newline|'\n'
dedent|''
name|'if'
name|'begin'
op|'=='
name|'begin2'
name|'and'
name|'end'
op|'=='
name|'end2'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'TEST_LOGS2'
newline|'\n'
dedent|''
name|'if'
name|'begin'
op|'=='
name|'begin3'
name|'and'
name|'end'
op|'=='
name|'end3'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'TEST_LOGS3'
newline|'\n'
dedent|''
name|'raise'
name|'AssertionError'
op|'('
string|'"Invalid date %s to %s"'
op|'%'
op|'('
name|'begin'
op|','
name|'end'
op|')'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_last_completed_audit_period
dedent|''
name|'def'
name|'fake_last_completed_audit_period'
op|'('
name|'unit'
op|'='
name|'None'
op|','
name|'before'
op|'='
name|'None'
op|')'
op|':'
newline|'\n'
indent|' '
name|'audit_periods'
op|'='
op|'['
op|'('
name|'begin3'
op|','
name|'end3'
op|')'
op|','
nl|'\n'
op|'('
name|'begin2'
op|','
name|'end2'
op|')'
op|','
nl|'\n'
op|'('
name|'begin1'
op|','
name|'end1'
op|')'
op|']'
newline|'\n'
name|'if'
name|'before'
name|'is'
name|'not'
name|'None'
op|':'
newline|'\n'
indent|' '
name|'for'
name|'begin'
op|','
name|'end'
name|'in'
name|'audit_periods'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'before'
op|'>'
name|'end'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'begin'
op|','
name|'end'
newline|'\n'
dedent|''
dedent|''
name|'raise'
name|'AssertionError'
op|'('
string|'"Invalid before date %s"'
op|'%'
op|'('
name|'before'
op|')'
op|')'
newline|'\n'
dedent|''
name|'return'
name|'begin1'
op|','
name|'end1'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|InstanceUsageAuditLogTestV21
dedent|''
name|'class'
name|'InstanceUsageAuditLogTestV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'InstanceUsageAuditLogTestV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'context'
op|'='
name|'context'
op|'.'
name|'get_admin_context'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'useFixture'
op|'('
nl|'\n'
name|'utils_fixture'
op|'.'
name|'TimeFixture'
op|'('
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2012'
op|','
number|'7'
op|','
number|'5'
op|','
number|'10'
op|','
number|'0'
op|','
number|'0'
op|')'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_set_up_controller'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'host_api'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'host_api'
newline|'\n'
nl|'\n'
DECL|function|fake_service_get_all
name|'def'
name|'fake_service_get_all'
op|'('
name|'context'
op|','
name|'disabled'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertIsNone'
op|'('
name|'disabled'
op|')'
newline|'\n'
name|'return'
name|'TEST_COMPUTE_SERVICES'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'utils'
op|','
string|"'last_completed_audit_period'"
op|','
nl|'\n'
name|'fake_last_completed_audit_period'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stub_out'
op|'('
string|"'nova.db.service_get_all'"
op|','
name|'fake_service_get_all'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stub_out'
op|'('
string|"'nova.db.task_log_get_all'"
op|','
name|'fake_task_log_get_all'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|')'
newline|'\n'
nl|'\n'
DECL|member|_set_up_controller
dedent|''
name|'def'
name|'_set_up_controller'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'controller'
op|'='
name|'v21_ial'
op|'.'
name|'InstanceUsageAuditLogController'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_index
dedent|''
name|'def'
name|'test_index'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'index'
op|'('
name|'self'
op|'.'
name|'req'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'instance_usage_audit_logs'"
op|','
name|'result'
op|')'
newline|'\n'
name|'logs'
op|'='
name|'result'
op|'['
string|"'instance_usage_audit_logs'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'57'
op|','
name|'logs'
op|'['
string|"'total_instances'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'total_errors'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'len'
op|'('
name|'logs'
op|'['
string|"'log'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts_done'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_running'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_not_run'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|'"ALL hosts done. 0 errors."'
op|','
name|'logs'
op|'['
string|"'overall_status'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show
dedent|''
name|'def'
name|'test_show'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|'('
name|'self'
op|'.'
name|'req'
op|','
string|"'2012-07-05 10:00:00'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'instance_usage_audit_log'"
op|','
name|'result'
op|')'
newline|'\n'
name|'logs'
op|'='
name|'result'
op|'['
string|"'instance_usage_audit_log'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'57'
op|','
name|'logs'
op|'['
string|"'total_instances'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'total_errors'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'len'
op|'('
name|'logs'
op|'['
string|"'log'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts_done'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_running'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_not_run'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|'"ALL hosts done. 0 errors."'
op|','
name|'logs'
op|'['
string|"'overall_status'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_with_running
dedent|''
name|'def'
name|'test_show_with_running'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|'('
name|'self'
op|'.'
name|'req'
op|','
string|"'2012-07-06 10:00:00'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'instance_usage_audit_log'"
op|','
name|'result'
op|')'
newline|'\n'
name|'logs'
op|'='
name|'result'
op|'['
string|"'instance_usage_audit_log'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'57'
op|','
name|'logs'
op|'['
string|"'total_instances'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'total_errors'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'len'
op|'('
name|'logs'
op|'['
string|"'log'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'3'
op|','
name|'logs'
op|'['
string|"'num_hosts_done'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'1'
op|','
name|'logs'
op|'['
string|"'num_hosts_running'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_not_run'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|'"3 of 4 hosts done. 0 errors."'
op|','
nl|'\n'
name|'logs'
op|'['
string|"'overall_status'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_with_errors
dedent|''
name|'def'
name|'test_show_with_errors'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|'('
name|'self'
op|'.'
name|'req'
op|','
string|"'2012-07-07 10:00:00'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'instance_usage_audit_log'"
op|','
name|'result'
op|')'
newline|'\n'
name|'logs'
op|'='
name|'result'
op|'['
string|"'instance_usage_audit_log'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'57'
op|','
name|'logs'
op|'['
string|"'total_instances'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'3'
op|','
name|'logs'
op|'['
string|"'total_errors'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'len'
op|'('
name|'logs'
op|'['
string|"'log'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'4'
op|','
name|'logs'
op|'['
string|"'num_hosts_done'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_running'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'logs'
op|'['
string|"'num_hosts_not_run'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|'"ALL hosts done. 3 errors."'
op|','
nl|'\n'
name|'logs'
op|'['
string|"'overall_status'"
op|']'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|InstanceUsageAuditLogTest
dedent|''
dedent|''
name|'class'
name|'InstanceUsageAuditLogTest'
op|'('
name|'InstanceUsageAuditLogTestV21'
op|')'
op|':'
newline|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'InstanceUsageAuditLogTest'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|','
name|'use_admin_context'
op|'='
name|'True'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'non_admin_req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|')'
newline|'\n'
nl|'\n'
DECL|member|_set_up_controller
dedent|''
name|'def'
name|'_set_up_controller'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'controller'
op|'='
name|'ial'
op|'.'
name|'InstanceUsageAuditLogController'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_index_non_admin
dedent|''
name|'def'
name|'test_index_non_admin'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'index'
op|','
name|'self'
op|'.'
name|'non_admin_req'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_non_admin
dedent|''
name|'def'
name|'test_show_non_admin'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|','
name|'self'
op|'.'
name|'non_admin_req'
op|','
nl|'\n'
string|"'2012-07-05 10:00:00'"
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|InstanceUsageAuditPolicyEnforcementV21
dedent|''
dedent|''
name|'class'
name|'InstanceUsageAuditPolicyEnforcementV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'InstanceUsageAuditPolicyEnforcementV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
name|'v21_ial'
op|'.'
name|'InstanceUsageAuditLogController'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_index_policy_failed
dedent|''
name|'def'
name|'test_index_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-instance-usage-audit-log"'
newline|'\n'
name|'self'
op|'.'
name|'policy'
op|'.'
name|'set_rules'
op|'('
op|'{'
name|'rule_name'
op|':'
string|'"project_id:non_fake"'
op|'}'
op|')'
newline|'\n'
name|'exc'
op|'='
name|'self'
op|'.'
name|'assertRaises'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'index'
op|','
name|'self'
op|'.'
name|'req'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
nl|'\n'
string|'"Policy doesn\'t allow %s to be performed."'
op|'%'
name|'rule_name'
op|','
nl|'\n'
name|'exc'
op|'.'
name|'format_message'
op|'('
op|')'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_policy_failed
dedent|''
name|'def'
name|'test_show_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-instance-usage-audit-log"'
newline|'\n'
name|'self'
op|'.'
name|'policy'
op|'.'
name|'set_rules'
op|'('
op|'{'
name|'rule_name'
op|':'
string|'"project_id:non_fake"'
op|'}'
op|')'
newline|'\n'
name|'exc'
op|'='
name|'self'
op|'.'
name|'assertRaises'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|','
name|'self'
op|'.'
name|'req'
op|','
string|"'2012-07-05 10:00:00'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
nl|'\n'
string|'"Policy doesn\'t allow %s to be performed."'
op|'%'
name|'rule_name'
op|','
nl|'\n'
name|'exc'
op|'.'
name|'format_message'
op|'('
op|')'
op|')'
newline|'\n'
dedent|''
dedent|''
endmarker|''
end_unit
| 12.046734
| 88
| 0.595503
| 3,553
| 23,973
| 3.939769
| 0.068111
| 0.164595
| 0.075011
| 0.076011
| 0.855765
| 0.820117
| 0.792327
| 0.757394
| 0.728747
| 0.697385
| 0
| 0.013231
| 0.098319
| 23,973
| 1,989
| 89
| 12.05279
| 0.634345
| 0
| 0
| 0.951232
| 0
| 0
| 0.349518
| 0.043007
| 0
| 0
| 0
| 0
| 0.023127
| 0
| null | null | 0
| 0.005028
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
a0706b31d2c1a03975ca77a33a608300d74af52e
| 3,712
|
py
|
Python
|
tests/test_provider_davidji99_herokux.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 507
|
2017-07-26T02:58:38.000Z
|
2022-01-21T12:35:13.000Z
|
tests/test_provider_davidji99_herokux.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 135
|
2017-07-20T12:01:59.000Z
|
2021-10-04T22:25:40.000Z
|
tests/test_provider_davidji99_herokux.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 81
|
2018-02-20T17:55:28.000Z
|
2022-01-31T07:08:40.000Z
|
# tests/test_provider_davidji99_herokux.py
# Automatically generated by tools/makecode.py (24-Sep-2021 15:18:42 UTC)
def test_provider_import():
import terrascript.provider.davidji99.herokux
def test_resource_import():
from terrascript.resource.davidji99.herokux import herokux_app_container_release
from terrascript.resource.davidji99.herokux import herokux_app_github_integration
from terrascript.resource.davidji99.herokux import herokux_app_webhook
from terrascript.resource.davidji99.herokux import herokux_connect_mappings
from terrascript.resource.davidji99.herokux import herokux_data_connector
from terrascript.resource.davidji99.herokux import herokux_formation_alert
from terrascript.resource.davidji99.herokux import herokux_formation_autoscaling
from terrascript.resource.davidji99.herokux import herokux_kafka_consumer_group
from terrascript.resource.davidji99.herokux import herokux_kafka_mtls_iprule
from terrascript.resource.davidji99.herokux import herokux_kafka_topic
from terrascript.resource.davidji99.herokux import herokux_oauth_authorization
from terrascript.resource.davidji99.herokux import (
herokux_pipeline_ephemeral_apps_config,
)
from terrascript.resource.davidji99.herokux import (
herokux_pipeline_github_integration,
)
from terrascript.resource.davidji99.herokux import herokux_pipeline_member
from terrascript.resource.davidji99.herokux import herokux_postgres_backup_schedule
from terrascript.resource.davidji99.herokux import (
herokux_postgres_connection_pooling,
)
from terrascript.resource.davidji99.herokux import herokux_postgres_credential
from terrascript.resource.davidji99.herokux import herokux_postgres_data_link
from terrascript.resource.davidji99.herokux import herokux_postgres_dataclip
from terrascript.resource.davidji99.herokux import (
herokux_postgres_dataclip_team_association,
)
from terrascript.resource.davidji99.herokux import (
herokux_postgres_dataclip_user_association,
)
from terrascript.resource.davidji99.herokux import (
herokux_postgres_maintenance_window,
)
from terrascript.resource.davidji99.herokux import herokux_postgres_mtls
from terrascript.resource.davidji99.herokux import herokux_postgres_mtls_certificate
from terrascript.resource.davidji99.herokux import herokux_postgres_mtls_iprule
from terrascript.resource.davidji99.herokux import herokux_postgres_settings
from terrascript.resource.davidji99.herokux import herokux_privatelink
from terrascript.resource.davidji99.herokux import herokux_redis_config
from terrascript.resource.davidji99.herokux import herokux_redis_maintenance_window
from terrascript.resource.davidji99.herokux import herokux_scheduler_job
from terrascript.resource.davidji99.herokux import herokux_shield_private_space
def test_datasource_import():
from terrascript.data.davidji99.herokux import herokux_addons
from terrascript.data.davidji99.herokux import herokux_kafka_mtls_iprules
from terrascript.data.davidji99.herokux import herokux_postgres_mtls_certificate
from terrascript.data.davidji99.herokux import herokux_registry_image
# TODO: Shortcut imports without namespace for official and supported providers.
# TODO: This has to be moved into a required_providers block.
# def test_version_source():
#
# import terrascript.provider.davidji99.herokux
#
# t = terrascript.provider.davidji99.herokux.herokux()
# s = str(t)
#
# assert 'https://github.com/davidji99/terraform-provider-herokux' in s
# assert '0.30.3' in s
| 34.691589
| 88
| 0.813039
| 425
| 3,712
| 6.863529
| 0.254118
| 0.213918
| 0.26397
| 0.34796
| 0.773055
| 0.744943
| 0.741858
| 0.601988
| 0.308536
| 0
| 0
| 0.029907
| 0.135237
| 3,712
| 106
| 89
| 35.018868
| 0.878816
| 0.135776
| 0
| 0.117647
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009434
| 0
| 1
| 0.058824
| true
| 0
| 0.764706
| 0
| 0.823529
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 9
|
a0829bccb2f43404a086a5d01022c9560fdf617b
| 34,308
|
py
|
Python
|
psr/migrations/0001_initial.py
|
dennereed/paleocore
|
d6da6c39cde96050ee4b9e7213ec1200530cbeee
|
[
"MIT"
] | 1
|
2021-02-05T19:50:13.000Z
|
2021-02-05T19:50:13.000Z
|
psr/migrations/0001_initial.py
|
dennereed/paleocore
|
d6da6c39cde96050ee4b9e7213ec1200530cbeee
|
[
"MIT"
] | 59
|
2020-06-17T22:21:51.000Z
|
2022-02-10T05:00:01.000Z
|
psr/migrations/0001_initial.py
|
dennereed/paleocore
|
d6da6c39cde96050ee4b9e7213ec1200530cbeee
|
[
"MIT"
] | 2
|
2020-07-01T14:11:09.000Z
|
2020-08-10T17:27:26.000Z
|
# Generated by Django 2.2.13 on 2021-02-05 15:17
import ckeditor.fields
import django.contrib.gis.db.models.fields
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='ExcavationUnit',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('unit', models.CharField(max_length=6)),
('extent', django.contrib.gis.db.models.fields.MultiPointField(blank=True, null=True, srid=4326)),
],
options={
'verbose_name': 'PSR Excavation Unit',
'verbose_name_plural': 'PSR Excavation Units',
},
),
migrations.CreateModel(
name='GeologicalContext',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('georeference_remarks', models.TextField(blank=True, max_length=500, null=True)),
('formation', models.CharField(blank=True, max_length=50, null=True)),
('member', models.CharField(blank=True, max_length=50, null=True)),
('name', models.TextField(blank=True, max_length=255, null=True)),
('context_type', models.CharField(blank=True, max_length=255, null=True)),
('context_number', models.IntegerField(blank=True, null=True)),
('basis_of_record', models.CharField(blank=True, help_text='e.g. Observed item or Collected item', max_length=50, verbose_name='Basis of Record')),
('collecting_method', models.CharField(blank=True, max_length=50, null=True, verbose_name='Collecting Method')),
('collection_code', models.CharField(blank=True, max_length=10, null=True)),
('description', models.TextField(blank=True, max_length=255, null=True)),
('stratigraphic_section', models.CharField(blank=True, max_length=50, null=True)),
('stratigraphic_formation', models.CharField(blank=True, max_length=255, null=True, verbose_name='Formation')),
('stratigraphic_member', models.CharField(blank=True, max_length=255, null=True, verbose_name='Member')),
('upper_limit_in_section', models.DecimalField(blank=True, decimal_places=8, default=None, max_digits=38, null=True)),
('lower_limit_in_section', models.DecimalField(blank=True, decimal_places=8, default=None, max_digits=38, null=True)),
('analytical_unit_1', models.CharField(blank=True, max_length=255, null=True)),
('analytical_unit_2', models.CharField(blank=True, max_length=255, null=True)),
('analytical_unit_3', models.CharField(blank=True, max_length=255, null=True)),
('analytical_unit_found', models.CharField(blank=True, max_length=255, null=True)),
('analytical_unit_likely', models.CharField(blank=True, max_length=255, null=True)),
('analytical_unit_simplified', models.CharField(blank=True, max_length=255, null=True)),
('in_situ', models.BooleanField(blank=True, default=None, null=True)),
('ranked', models.BooleanField(blank=True, default=False, null=True)),
('weathering', models.SmallIntegerField(blank=True, null=True)),
('surface_modification', models.CharField(blank=True, max_length=255, null=True, verbose_name='Surface Mod')),
('geology_type', models.TextField(blank=True, max_length=255, null=True)),
('dip', models.CharField(blank=True, max_length=255, null=True)),
('strike', models.CharField(blank=True, max_length=255, null=True)),
('color', models.CharField(blank=True, max_length=255, null=True)),
('texture', models.CharField(blank=True, max_length=255, null=True)),
('height', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('width', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('depth', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('slope_character', models.TextField(blank=True, max_length=64000, null=True)),
('sediment_presence', models.BooleanField(blank=True, default=None, null=True)),
('sediment_character', models.TextField(blank=True, max_length=64000, null=True)),
('cave_mouth_character', models.TextField(blank=True, max_length=64000, null=True)),
('rockfall_character', models.TextField(blank=True, max_length=64000, null=True)),
('speleothem_character', models.TextField(blank=True, max_length=64000, null=True)),
('size_of_loess', models.CharField(blank=True, max_length=255, null=True)),
('mean_thickness', models.DecimalField(blank=True, decimal_places=8, default=None, max_digits=38, null=True)),
('max_thickness', models.DecimalField(blank=True, decimal_places=8, default=None, max_digits=38, null=True)),
('landscape_position', models.CharField(blank=True, max_length=255, null=True)),
('surface_inclination', models.CharField(blank=True, max_length=255, null=True)),
('presence_coarse_components', models.BooleanField(blank=True, default=None, null=True)),
('amount_coarse_components', models.DecimalField(blank=True, decimal_places=8, default=None, max_digits=38, null=True)),
('number_sediment_layers', models.SmallIntegerField(blank=True, null=True)),
('number_soil_horizons', models.SmallIntegerField(blank=True, null=True)),
('number_cultural_horizons', models.SmallIntegerField(blank=True, null=True)),
('number_coarse_layers', models.SmallIntegerField(blank=True, null=True)),
('presence_vertical_profile', models.BooleanField(default=False)),
('context_remarks', models.TextField(blank=True, max_length=500, null=True, verbose_name='Context Remarks')),
('error_notes', models.CharField(blank=True, max_length=255, null=True)),
('notes', models.CharField(blank=True, max_length=254, null=True)),
('geom', django.contrib.gis.db.models.fields.GeometryField(srid=4326)),
('point', django.contrib.gis.db.models.fields.GeometryField(srid=4326)),
('date_collected', models.DateTimeField(blank=True, null=True, verbose_name='Date Collected')),
('date_last_modified', models.DateTimeField(auto_now=True, verbose_name='Date Last Modified')),
('image', models.FileField(blank=True, max_length=255, null=True, upload_to='uploads/images/psr')),
],
options={
'verbose_name': 'PSR Geological Context',
'verbose_name_plural': 'PSR Geological Contexts',
'ordering': ['context_number'],
},
),
migrations.CreateModel(
name='IdentificationQualifier',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('name', models.CharField(blank=True, max_length=15, unique=True)),
('qualified', models.BooleanField(default=False)),
],
options={
'verbose_name': 'PSR ID Qualifier',
'verbose_name_plural': 'PSR ID Qualifiers',
},
),
migrations.CreateModel(
name='Occurrence',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, max_length=255, null=True)),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('georeference_remarks', models.TextField(blank=True, max_length=500, null=True)),
('date_recorded', models.DateTimeField(blank=True, help_text='Date and time the item was observed or collected.', null=True, verbose_name='Date Rec')),
('year_collected', models.IntegerField(blank=True, help_text='The year, event or field campaign during which the item was found.', null=True, verbose_name='Year')),
('barcode', models.IntegerField(blank=True, help_text='For collected items only.', null=True, verbose_name='Barcode')),
('field_number', models.CharField(blank=True, max_length=50, null=True)),
('basis_of_record', models.CharField(blank=True, help_text='e.g. Observed item or Collected item', max_length=50, verbose_name='Basis of Record')),
('find_type', models.CharField(blank=True, max_length=255, verbose_name='Find Type')),
('item_number', models.IntegerField(blank=True, null=True, verbose_name='Item #')),
('item_type', models.CharField(blank=True, max_length=255, verbose_name='Item Type')),
('item_description', models.CharField(blank=True, max_length=255, null=True, verbose_name='Description')),
('item_count', models.IntegerField(blank=True, default=1, null=True, verbose_name='Item Count')),
('collector', models.CharField(blank=True, max_length=50, null=True, verbose_name='Collector')),
('finder', models.CharField(blank=True, max_length=50, null=True, verbose_name='Finder')),
('collecting_method', models.CharField(blank=True, max_length=50, null=True, verbose_name='Collecting Method')),
('field_id', models.CharField(blank=True, max_length=50, null=True, verbose_name='Field ID')),
('suffix', models.IntegerField(blank=True, null=True, verbose_name='Suffix')),
('cat_number', models.CharField(blank=True, max_length=255, null=True, verbose_name='Cat Number')),
('prism', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('point', django.contrib.gis.db.models.fields.GeometryField(blank=True, null=True, srid=4326)),
('geom', django.contrib.gis.db.models.fields.GeometryField(blank=True, null=True, srid=4326)),
('item_part', models.CharField(blank=True, max_length=10, null=True, verbose_name='Item Part')),
('disposition', models.CharField(blank=True, max_length=255, null=True, verbose_name='Disposition')),
('preparation_status', models.CharField(blank=True, max_length=50, null=True, verbose_name='Prep Status')),
('collection_remarks', models.TextField(blank=True, max_length=255, null=True, verbose_name='Collection Remarks')),
('date_collected', models.DateTimeField(blank=True, null=True, verbose_name='Date Collected')),
('problem', models.BooleanField(blank=True, default=False, null=True)),
('problem_remarks', models.TextField(blank=True, max_length=64000, null=True)),
('collection_code', models.CharField(blank=True, max_length=20, null=True, verbose_name='Collection Code')),
('drainage_region', models.CharField(blank=True, max_length=255, null=True, verbose_name='Drainage Region')),
('image', models.FileField(blank=True, max_length=255, null=True, upload_to='uploads/images/psr')),
],
options={
'verbose_name': 'PSR Survey Occurrence',
'verbose_name_plural': 'PSR Survey Occurrences',
'ordering': ['collection_code', 'geological_context', 'item_number', 'item_part'],
},
),
migrations.CreateModel(
name='Person',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, max_length=255, null=True)),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('last_name', models.CharField(blank=True, max_length=256, null=True, verbose_name='Last Name')),
('first_name', models.CharField(blank=True, max_length=256, null=True, verbose_name='First Name')),
],
options={
'verbose_name': 'PSR Person',
'verbose_name_plural': 'PSR People',
'ordering': ['last_name', 'first_name'],
},
),
migrations.CreateModel(
name='TaxonRank',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('name', models.CharField(max_length=50, unique=True)),
('plural', models.CharField(max_length=50, unique=True)),
('ordinal', models.IntegerField(unique=True)),
],
options={
'verbose_name': 'PSR Taxon Rank',
'verbose_name_plural': 'PSR Taxon Ranks',
},
),
migrations.CreateModel(
name='Aggregate',
fields=[
('occurrence_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Occurrence')),
('screen_size', models.CharField(blank=True, max_length=255, null=True)),
('burning', models.BooleanField(default=False)),
('bone', models.BooleanField(default=False)),
('microfauna', models.BooleanField(default=False)),
('pebbles', models.BooleanField(default=False)),
('smallplatforms', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('smalldebris', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('tinyplatforms', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('tinydebris', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('counts', models.IntegerField(blank=True, null=True)),
('weights', models.IntegerField(blank=True, null=True)),
('bull_find_remarks', models.TextField(blank=True, max_length=64000, null=True)),
],
options={
'verbose_name': 'PSR Bulk Find',
'verbose_name_plural': 'PSR Bulk Finds',
},
bases=('psr.occurrence',),
),
migrations.CreateModel(
name='Archaeology',
fields=[
('occurrence_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Occurrence')),
('archaeology_type', models.CharField(blank=True, max_length=255, null=True)),
('period', models.CharField(blank=True, max_length=255, null=True)),
('archaeology_preparation', models.CharField(blank=True, max_length=255, null=True)),
('archaeology_remarks', models.TextField(blank=True, max_length=64000, null=True)),
('length_mm', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('width_mm', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('thick_mm', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('weight', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('archaeology_notes', models.TextField(blank=True, max_length=64000, null=True)),
],
options={
'verbose_name': 'PSR Survey Archaeology',
'verbose_name_plural': 'PSR Survey Archaeology',
},
bases=('psr.occurrence',),
),
migrations.CreateModel(
name='Geology',
fields=[
('occurrence_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Occurrence')),
('geology_type', models.CharField(blank=True, max_length=255, null=True)),
('dip', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('strike', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('color', models.CharField(blank=True, max_length=255, null=True)),
('texture', models.CharField(blank=True, max_length=255, null=True)),
],
options={
'verbose_name': 'PSR Survey Geology',
'verbose_name_plural': 'PSR Survey Geology',
},
bases=('psr.occurrence',),
),
migrations.CreateModel(
name='Taxon',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, max_length=255, null=True)),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('label', models.CharField(blank=True, help_text='For a species, the name field contains the specific epithet and the label contains the full\n scientific name, e.g. Homo sapiens, name = sapiens, label = Homo sapiens', max_length=244, null=True)),
('parent', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.Taxon')),
('rank', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.TaxonRank')),
],
options={
'verbose_name': 'PSR Taxon',
'verbose_name_plural': 'PSR Taxa',
},
),
migrations.AddField(
model_name='occurrence',
name='found_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='occurrence_found_by', to='psr.Person'),
),
migrations.AddField(
model_name='occurrence',
name='geological_context',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.GeologicalContext'),
),
migrations.AddField(
model_name='occurrence',
name='recorded_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='occurrence_recorded_by', to='psr.Person'),
),
migrations.AddField(
model_name='occurrence',
name='unit',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.ExcavationUnit'),
),
migrations.CreateModel(
name='Image',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('image', models.ImageField(blank=True, null=True, upload_to='uploads/images')),
('description', models.TextField(blank=True, null=True)),
('locality', models.ForeignKey(default='', on_delete=django.db.models.deletion.CASCADE, related_name='psr_contexts_image', to='psr.GeologicalContext')),
('occurrence', models.ForeignKey(blank=True, default='', null=True, on_delete=django.db.models.deletion.CASCADE, related_name='psr_occurrences_image', to='psr.Occurrence')),
],
),
migrations.AddField(
model_name='geologicalcontext',
name='recorded_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='geo_context_recorded_by', to='psr.Person'),
),
migrations.CreateModel(
name='File',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('file', models.FileField(blank=True, null=True, upload_to='uploads/files')),
('description', models.TextField(blank=True, null=True)),
('locality', models.ForeignKey(default='', on_delete=django.db.models.deletion.CASCADE, related_name='psr_contexts_file', to='psr.GeologicalContext')),
('occurrence', models.ForeignKey(blank=True, default='', null=True, on_delete=django.db.models.deletion.CASCADE, related_name='psr_occurrences_file', to='psr.Occurrence')),
],
),
migrations.AddField(
model_name='excavationunit',
name='geological_context',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.GeologicalContext'),
),
migrations.CreateModel(
name='ExcavationOccurrence',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, max_length=255, null=True)),
('date_created', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was first created.', verbose_name='Created')),
('date_last_modified', models.DateTimeField(default=django.utils.timezone.now, help_text='The date and time this resource was last altered.', verbose_name='Modified')),
('problem', models.BooleanField(default=False, help_text='Is there a problem with this record that needs attention?')),
('problem_comment', models.TextField(blank=True, help_text='Description of the problem.', max_length=255, null=True)),
('remarks', ckeditor.fields.RichTextField(blank=True, help_text='General remarks about this database record.', null=True, verbose_name='Record Remarks')),
('last_import', models.BooleanField(default=False)),
('georeference_remarks', models.TextField(blank=True, max_length=500, null=True)),
('geom', django.contrib.gis.db.models.fields.PointField(blank=True, null=True, srid=4326)),
('date_recorded', models.DateTimeField(blank=True, help_text='Date and time the item was observed or collected.', null=True, verbose_name='Date Rec')),
('year_collected', models.IntegerField(blank=True, help_text='The year, event or field campaign during which the item was found.', null=True, verbose_name='Year')),
('barcode', models.IntegerField(blank=True, help_text='For collected items only.', null=True, verbose_name='Barcode')),
('field_number', models.CharField(blank=True, max_length=50, null=True)),
('field_id', models.CharField(blank=True, max_length=50, null=True, verbose_name='Field ID')),
('cat_number', models.CharField(blank=True, max_length=255, null=True, verbose_name='Cat Number')),
('prism', models.CharField(blank=True, max_length=50, null=True)),
('level', models.CharField(blank=True, max_length=100, null=True)),
('type', models.CharField(blank=True, max_length=100, null=True)),
('excavator', models.CharField(blank=True, max_length=100, null=True)),
('point', django.contrib.gis.db.models.fields.MultiPointField(blank=True, dim=3, null=True, srid=-1)),
('date_collected', models.DateTimeField(blank=True, null=True, verbose_name='Date Collected')),
('found_by', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='excav_occurrence_found_by', to='psr.Person')),
('geological_context', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.GeologicalContext')),
('unit', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='psr.ExcavationUnit')),
],
options={
'verbose_name': 'PSR Excavated Occurrence',
'verbose_name_plural': 'PSR Excavated Occurrences',
},
),
migrations.CreateModel(
name='Bone',
fields=[
('archaeology_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Archaeology')),
('cutmarks', models.BooleanField(default=False)),
('burning', models.BooleanField(default=False)),
('part', models.CharField(blank=True, max_length=255, null=True)),
],
options={
'verbose_name': 'PSR Archaeological Fauna',
'verbose_name_plural': 'PSR Archaeological Fauna',
},
bases=('psr.archaeology',),
),
migrations.CreateModel(
name='Ceramic',
fields=[
('archaeology_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Archaeology')),
('type', models.CharField(blank=True, max_length=255, null=True)),
('decorated', models.BooleanField(default=False)),
],
options={
'verbose_name': 'PSR Ceramic',
'verbose_name_plural': 'PSR Ceramic',
},
bases=('psr.archaeology',),
),
migrations.CreateModel(
name='Lithic',
fields=[
('archaeology_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Archaeology')),
('dataclass', models.CharField(blank=True, max_length=255, null=True)),
('fbtype', models.SmallIntegerField(blank=True, null=True)),
('form', models.CharField(blank=True, max_length=255, null=True)),
('technique', models.CharField(blank=True, max_length=255, null=True)),
('cortex', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('coretype', models.CharField(blank=True, max_length=255, null=True)),
('platsurf', models.CharField(blank=True, max_length=255, null=True)),
('scarmorph', models.CharField(blank=True, max_length=255, null=True)),
('edgedamage', models.CharField(blank=True, max_length=255, null=True)),
('platwidth', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('platthick', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('epa', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
('scarlength', models.DecimalField(blank=True, decimal_places=8, max_digits=38, null=True)),
],
options={
'verbose_name': 'PSR Lithic',
'verbose_name_plural': 'PSR Lithics',
},
bases=('psr.archaeology',),
),
migrations.CreateModel(
name='Biology',
fields=[
('occurrence_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='psr.Occurrence')),
('biology_type', models.CharField(blank=True, max_length=255, null=True)),
('sex', models.CharField(blank=True, max_length=50, null=True, verbose_name='Sex')),
('life_stage', models.CharField(blank=True, max_length=50, null=True, verbose_name='Life Stage')),
('size_class', models.CharField(blank=True, max_length=50, null=True, verbose_name='Size Class')),
('verbatim_taxon', models.CharField(blank=True, max_length=1024, null=True)),
('verbatim_identification_qualifier', models.CharField(blank=True, max_length=255, null=True)),
('taxonomy_remarks', models.TextField(blank=True, max_length=500, null=True)),
('type_status', models.CharField(blank=True, max_length=50, null=True)),
('fauna_notes', models.TextField(blank=True, max_length=64000, null=True)),
('identification_qualifier', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='bio_occurrences', to='psr.IdentificationQualifier')),
('taxon', models.ForeignKey(default=0, on_delete=django.db.models.deletion.SET_DEFAULT, related_name='bio_occurrences', to='psr.Taxon')),
],
options={
'verbose_name': 'PSR Survey Biology',
'verbose_name_plural': 'PSR Survey Biology',
},
bases=('psr.occurrence',),
),
]
| 76.923767
| 266
| 0.633293
| 3,850
| 34,308
| 5.487013
| 0.082857
| 0.079243
| 0.054533
| 0.081799
| 0.850272
| 0.829586
| 0.793467
| 0.769941
| 0.740686
| 0.667834
| 0
| 0.016579
| 0.226419
| 34,308
| 445
| 267
| 77.096629
| 0.77939
| 0.001341
| 0
| 0.468037
| 1
| 0.002283
| 0.215966
| 0.01763
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.027397
| 0
| 0.03653
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
2627b3197635723494fba664bdff83195be808a7
| 2,754
|
py
|
Python
|
tests/test_entrypoint.py
|
Talentia-Software-OSS/github-action-python-template
|
d49b2f30188d608394b5be838a79aafd1746eeff
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_entrypoint.py
|
Talentia-Software-OSS/github-action-python-template
|
d49b2f30188d608394b5be838a79aafd1746eeff
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_entrypoint.py
|
Talentia-Software-OSS/github-action-python-template
|
d49b2f30188d608394b5be838a79aafd1746eeff
|
[
"BSD-3-Clause"
] | 1
|
2021-09-22T10:10:48.000Z
|
2021-09-22T10:10:48.000Z
|
from unittest.mock import patch
from github_action_template.entrypoint import main
from github_action_template.framework import ActionError
@patch("github_action_template.entrypoint.sys")
@patch("github_action_template.entrypoint.os")
@patch("github_action_template.entrypoint.importlib")
@patch("github_action_template.entrypoint.GitHubEnvironment")
def test_main_should_call_action(mock_env, mock_importlib, mock_os, mock_sys):
mock_os.environ = {"X": "Y", "Y": "Z"}
mock_sys.argv = ["entrypoint.sh", "pkg.action.Class", "x", "y"]
assert main() == 0
mock_env.assert_called_with(mock_os.environ)
mock_importlib.import_module.assert_called_with("pkg.action")
mock_importlib.import_module.return_value.Class.assert_called_with(mock_env.return_value)
mock_importlib.import_module.return_value.Class.return_value.run.assert_called_with(["x", "y"])
@patch("github_action_template.entrypoint.sys")
@patch("github_action_template.entrypoint.os")
@patch("github_action_template.entrypoint.importlib")
@patch("github_action_template.entrypoint.GitHubEnvironment")
def test_main_should_return_one_on_instantiate_failure(mock_env, mock_importlib, mock_os, mock_sys):
mock_os.environ = {"X": "Y", "Y": "Z"}
mock_importlib.import_module.return_value.Class.side_effect = TypeError("Problem")
mock_sys.argv = ["entrypoint.sh", "pkg.action.Class", "x", "y"]
assert main() == 1
mock_env.assert_called_with(mock_os.environ)
@patch("github_action_template.entrypoint.sys")
@patch("github_action_template.entrypoint.os")
@patch("github_action_template.entrypoint.importlib")
@patch("github_action_template.entrypoint.GitHubEnvironment")
def test_main_should_return_two_on_failure(mock_env, mock_importlib, mock_os, mock_sys):
mock_os.environ = {"X": "Y", "Y": "Z"}
mock_importlib.import_module.return_value.Class.return_value.run.side_effect = ActionError("Failure")
mock_sys.argv = ["entrypoint.sh", "pkg.action.Class", "x", "y"]
assert main() == 2
mock_env.assert_called_with(mock_os.environ)
mock_importlib.import_module.return_value.Class.return_value.run.assert_called_with(["x", "y"])
@patch("github_action_template.entrypoint.sys")
@patch("github_action_template.entrypoint.os")
@patch("github_action_template.entrypoint.importlib")
@patch("github_action_template.entrypoint.GitHubEnvironment")
def test_main_should_return_two_on_runtime_error(mock_env, mock_importlib, mock_os, mock_sys):
mock_os.environ = {"X": "Y", "Y": "Z"}
mock_importlib.import_module.return_value.Class.return_value.run.side_effect = TypeError("Problem")
mock_sys.argv = ["entrypoint.sh", "pkg.action.Class", "x", "y"]
assert main() == 2
mock_env.assert_called_with(mock_os.environ)
| 43.03125
| 105
| 0.775599
| 383
| 2,754
| 5.219321
| 0.130548
| 0.108054
| 0.18009
| 0.255128
| 0.88094
| 0.88094
| 0.88094
| 0.86043
| 0.842421
| 0.842421
| 0
| 0.001591
| 0.087146
| 2,754
| 63
| 106
| 43.714286
| 0.793556
| 0
| 0
| 0.695652
| 0
| 0
| 0.3061
| 0.242556
| 0
| 0
| 0
| 0
| 0.26087
| 1
| 0.086957
| false
| 0
| 0.391304
| 0
| 0.478261
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 9
|
26d357892cb88f627e237a481dae79a2359d72f0
| 736,566
|
py
|
Python
|
rl_agents/awac_agent_small_8_32_1_norm_v3-160_deterministic.py
|
IsaiahPressman/Kaggle_Santa_2020
|
ff5c6aa78dbe234cef338f4c721cc30d7dbc3df8
|
[
"MIT"
] | null | null | null |
rl_agents/awac_agent_small_8_32_1_norm_v3-160_deterministic.py
|
IsaiahPressman/Kaggle_Santa_2020
|
ff5c6aa78dbe234cef338f4c721cc30d7dbc3df8
|
[
"MIT"
] | null | null | null |
rl_agents/awac_agent_small_8_32_1_norm_v3-160_deterministic.py
|
IsaiahPressman/Kaggle_Santa_2020
|
ff5c6aa78dbe234cef338f4c721cc30d7dbc3df8
|
[
"MIT"
] | null | null | null |
serialized_string = 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'
import base64
import pickle
import torch
from torch import distributions, nn
import torch.nn.functional as F
class FullyConnectedGNNLayer(nn.Module):
def __init__(self, n_nodes, in_features, out_features,
activation_func=nn.ReLU(), normalize=False, squeeze_out=False):
super().__init__()
self.n_nodes = n_nodes
self.activation_func = activation_func
self.normalize = normalize
if self.normalize:
self.norm_layer = nn.BatchNorm1d(out_features)
else:
self.norm_layer = None
self.transform_features = nn.Linear(in_features, out_features)
self.message_passing_mat = nn.Parameter(
(torch.ones((n_nodes, n_nodes)) - torch.eye(n_nodes)) / (n_nodes - 1),
requires_grad=False
)
self.recombine_features = nn.Linear(out_features*2, out_features)
self.squeeze_out = squeeze_out
# Initialize linear layer weights
nn.init.normal_(self.transform_features.weight, mean=0., std=0.2)
nn.init.normal_(self.recombine_features.weight, mean=0., std=0.2)
nn.init.constant_(self.transform_features.bias, 0.)
nn.init.constant_(self.recombine_features.bias, 0.)
def forward(self, features):
features_transformed = self.activation_func(
self.transform_features(features)
)
messages = torch.matmul(self.message_passing_mat, features_transformed)
out = self.recombine_features(torch.cat([features_transformed, messages], dim=-1))
if self.normalize:
out_shape = out.shape
out = out.view(torch.prod(torch.tensor(out_shape[:-2])).item(), *out_shape[-2:])
out = self.norm_layer(out.transpose(1, 2)).transpose(1, 2)
out = out.view(out_shape)
out = self.activation_func(out)
if self.squeeze_out:
return out.squeeze(dim=-1)
else:
return out
def reset_hidden_states(self):
pass
class SmallFullyConnectedGNNLayer(nn.Module):
def __init__(self, n_nodes, in_features, out_features,
activation_func=nn.ReLU(), normalize=False, squeeze_out=False):
super().__init__()
self.n_nodes = n_nodes
self.activation_func = activation_func
self.normalize = normalize
if self.normalize:
self.norm_layer = nn.BatchNorm1d(out_features)
else:
self.norm_layer = None
self.message_passing_mat = nn.Parameter(
(torch.ones((n_nodes, n_nodes)) - torch.eye(n_nodes)) / (n_nodes - 1),
requires_grad=False
)
self.recombine_features = nn.Linear(in_features * 2, out_features)
self.squeeze_out = squeeze_out
# Initialize linear layer weights
nn.init.normal_(self.recombine_features.weight, mean=0., std=0.2)
nn.init.constant_(self.recombine_features.bias, 0.)
def forward(self, features):
messages = torch.matmul(self.message_passing_mat, features)
out = self.recombine_features(torch.cat([features, messages], dim=-1))
if self.normalize:
out_shape = out.shape
out = out.view(torch.prod(torch.tensor(out_shape[:-2])).item(), *out_shape[-2:])
out = self.norm_layer(out.transpose(1, 2)).transpose(1, 2)
out = out.view(out_shape)
out = self.activation_func(out)
if self.squeeze_out:
return out.squeeze(dim=-1)
else:
return out
def reset_hidden_states(self):
pass
class SmallRecurrentGNNLayer(nn.Module):
def __init__(self, n_nodes, in_features, out_features, recurrent_layer_class=nn.LSTM, squeeze_out=False, **kwargs):
super().__init__()
self.n_nodes = n_nodes
self.message_passing_mat = nn.Parameter(
(torch.ones((n_nodes, n_nodes)) - torch.eye(n_nodes)) / (n_nodes - 1),
requires_grad=False
)
self.recombine_features = recurrent_layer_class(in_features * 2, out_features)
self.rf_hidden = None
self.squeeze_out = squeeze_out
# Initialize LSTM layer weights
#nn.init.normal_(self.recombine_features.weight_ih_l0, mean=0., std=0.2)
#nn.init.normal_(self.recombine_features.weight_hh_l0, mean=0., std=0.2)
#nn.init.normal_(self.recombine_features.bias_ih_l0, mean=0., std=0.2)
#nn.init.normal_(self.recombine_features.bias_hh_l0, mean=0., std=0.2)
def forward(self, features):
orig_shape = features.shape
messages = torch.matmul(self.message_passing_mat, features)
"""
if self.rf_hidden is None:
features_messages_combined, self.rf_hidden = self.recombine_features(
torch.cat([features, messages], dim=-1).view(orig_shape[0], -1, orig_shape[-1] * 2)
)
else:
features_messages_combined, self.rf_hidden = self.recombine_features(
torch.cat([features, messages], dim=-1).view(orig_shape[0], -1, orig_shape[-1] * 2),
self.rf_hidden
)"""
features_messages_combined, self.rf_hidden = self.recombine_features(
torch.cat([features, messages], dim=-1).view(orig_shape[0], -1, orig_shape[-1] * 2),
self.rf_hidden
)
features_messages_combined = features_messages_combined.view((*orig_shape[:-1], -1))
if self.squeeze_out:
return features_messages_combined.squeeze(dim=-1)
else:
return features_messages_combined
def reset_hidden_states(self):
self.rf_hidden = None
def detach_hidden_states(self):
self.rf_hidden = [h.detach() for h in self.rf_hidden]
class GraphNNResidualBase(nn.Module):
def __init__(self, layers, skip_connection_n):
super().__init__()
assert skip_connection_n >= 1
self.layers = nn.ModuleList(layers)
self.skip_connection_n = skip_connection_n
def forward(self, x):
identity = None
for layer_num, layer in enumerate(self.layers):
if (len(self.layers) - layer_num - 1) % self.skip_connection_n == 0:
x = layer(x)
if identity is not None and identity.shape == x.shape:
x = x + identity
identity = x
else:
x = layer(x)
return x
def reset_hidden_states(self):
[layer.reset_hidden_states() for layer in self.layers]
def detach_hidden_states(self):
[layer.detach_hidden_states() for layer in self.layers]
class GraphNNActorCritic(nn.Module):
def __init__(self, in_features, n_nodes, n_hidden_layers, layer_sizes, layer_class,
preprocessing_layer=False, activation_func=nn.ReLU(), skip_connection_n=1, normalize=False):
super().__init__()
# Define network
if type(layer_sizes) == int:
layer_sizes = [layer_sizes] * (n_hidden_layers + 1 + preprocessing_layer)
elif len(layer_sizes) == 1:
layer_sizes = layer_sizes * (n_hidden_layers + 1 + preprocessing_layer)
if len(layer_sizes) != n_hidden_layers + 1 + preprocessing_layer:
raise ValueError(f'len(layer_sizes) must equal n_hidden_layers + 1 (+ 1 again if preprocessing_layer), '
f'was {len(layer_sizes)} but should have been {n_hidden_layers+1+preprocessing_layer}')
if preprocessing_layer:
layers = [nn.Sequential(nn.Linear(in_features, layer_sizes[0]),
activation_func),
layer_class(n_nodes, layer_sizes[0], layer_sizes[1], activation_func=activation_func)]
else:
layers = [layer_class(n_nodes, in_features, layer_sizes[0], activation_func=activation_func)]
for i in range(n_hidden_layers):
layers.append(layer_class(n_nodes, layer_sizes[i+preprocessing_layer], layer_sizes[i+1+preprocessing_layer],
activation_func=activation_func, normalize=normalize))
if skip_connection_n == 0:
self.base = nn.Sequential(*layers)
else:
self.base = GraphNNResidualBase(layers, skip_connection_n)
self.actor = layer_class(n_nodes, layer_sizes[-1], 1, activation_func=nn.Identity(), squeeze_out=True)
self.critic = layer_class(n_nodes, layer_sizes[-1], 1, activation_func=nn.Identity(), squeeze_out=True)
def forward(self, states):
base_out = self.base(states)
return self.actor(base_out), self.critic(base_out).mean(dim=-1)
def sample_action(self, states, train=False):
if train:
logits, values = self.forward(states)
else:
with torch.no_grad():
logits, values = self.forward(states)
probs = F.softmax(logits, dim=-1)
seq_len, n_envs, n_players, n_bandits = probs.shape
m = distributions.Categorical(probs.view(seq_len * n_envs * n_players, n_bandits))
sampled_actions = m.sample().view(seq_len, n_envs, n_players)
if train:
return sampled_actions, (logits, values)
else:
return sampled_actions
def choose_best_action(self, states):
with torch.no_grad():
logits, _ = self.forward(states)
return logits.argmax(dim=-1)
def reset_hidden_states(self):
self.base.reset_hidden_states()
self.actor.reset_hidden_states()
self.critic.reset_hidden_states()
def detach_hidden_states(self):
self.base.detach_hidden_states()
self.actor.detach_hidden_states()
self.critic.detach_hidden_states()
class GraphNNPolicy(nn.Module):
def __init__(self, in_features, n_nodes, n_hidden_layers, layer_sizes, layer_class,
activation_func=nn.ReLU(), skip_connection_n=1, normalize=False):
super().__init__()
# Define network
if type(layer_sizes) == int:
layer_sizes = [layer_sizes] * (n_hidden_layers + 1)
elif len(layer_sizes) == 1:
layer_sizes = layer_sizes * (n_hidden_layers + 1)
if len(layer_sizes) != n_hidden_layers + 1:
raise ValueError(f'len(layer_sizes) must equal n_hidden_layers + 1, '
f'was {len(layer_sizes)} but should have been {n_hidden_layers + 1}')
layers = [layer_class(n_nodes, in_features, layer_sizes[0], activation_func=activation_func)]
for i in range(n_hidden_layers):
layers.append(layer_class(n_nodes, layer_sizes[i], layer_sizes[i + 1],
activation_func=activation_func, normalize=normalize))
if skip_connection_n == 0:
self.base = nn.Sequential(*layers)
else:
self.base = GraphNNResidualBase(layers, skip_connection_n)
self.actor = layer_class(n_nodes, layer_sizes[-1], 1, activation_func=nn.Identity(), squeeze_out=True)
def forward(self, states):
return self.actor(self.base(states))
def sample_action(self, states, train=False):
if train:
logits = self.forward(states)
else:
with torch.no_grad():
logits = self.forward(states)
probs = F.softmax(logits, dim=-1)
probs_shape = probs.shape
m = distributions.Categorical(probs.view(torch.prod(torch.tensor(probs_shape[:-1])).item(), probs_shape[-1]))
sampled_actions = m.sample().view(probs_shape[:-1])
if train:
return sampled_actions, logits
else:
return sampled_actions
def choose_best_action(self, states):
with torch.no_grad():
logits = self.forward(states)
return logits.argmax(dim=-1)
class GraphNNQ(nn.Module):
def __init__(self, in_features, n_nodes, n_hidden_layers, layer_sizes, layer_class,
activation_func=nn.ReLU(), skip_connection_n=1, normalize=False):
super().__init__()
self.action_space = n_nodes
# Define network
if type(layer_sizes) == int:
layer_sizes = [layer_sizes] * (n_hidden_layers + 1)
elif len(layer_sizes) == 1:
layer_sizes = layer_sizes * (n_hidden_layers + 1)
if len(layer_sizes) != n_hidden_layers + 1:
raise ValueError(f'len(layer_sizes) must equal n_hidden_layers + 1, '
f'was {len(layer_sizes)} but should have been {n_hidden_layers + 1}')
layers = [layer_class(n_nodes, in_features, layer_sizes[0], activation_func=activation_func)]
for i in range(n_hidden_layers):
layers.append(layer_class(n_nodes, layer_sizes[i], layer_sizes[i + 1],
activation_func=activation_func, normalize=normalize))
if skip_connection_n == 0:
self.base = nn.Sequential(*layers)
else:
self.base = GraphNNResidualBase(layers, skip_connection_n)
self.critic = layer_class(n_nodes, layer_sizes[-1], 1, activation_func=nn.Identity(), squeeze_out=True)
def forward(self, states):
return self.critic(self.base(states))
def sample_action_epsilon_greedy(self, states, epsilon):
actions = self.choose_best_action(states)
actions = torch.where(
torch.rand(actions.shape, device=actions.device) < epsilon,
torch.randint(self.action_space, size=actions.shape, device=actions.device),
actions
)
return actions
def choose_best_action(self, states):
with torch.no_grad():
q_vals = self.forward(states)
return q_vals.argmax(dim=-1)
class ActorCriticAgent:
def __init__(self, configuration, serialized_string):
self.n_bandits = configuration.banditCount
self.n_steps = 1999 # TODO: Get this info from configuration somehow?
self.total_reward = 0
self.pull_rewards = torch.zeros((self.n_bandits, 1), dtype=torch.float)
self.player_n_pulls = torch.zeros((self.n_bandits, 2), dtype=torch.float)
self.timestep = torch.zeros((self.n_bandits, 1), dtype=torch.float)
state_dict_bytes = base64.b64decode(serialized_string)
state_dicts = pickle.loads(state_dict_bytes)
self.model = GraphNNActorCritic(
in_features=4,
n_nodes=100,
n_hidden_layers=8,
layer_sizes=32,
layer_class=SmallFullyConnectedGNNLayer,
skip_connection_n=1,
normalize=True
)
self.model.load_state_dict(state_dicts['model_state_dict'])
self.model.eval()
def get_obs(self):
# Obs must be of shape (n_batches, n_envs, n_players, n_bandits, n_features
# Since we are only selecting an action for a single agent, this translates to: (1, 1, 1, n_bandits, -1)
return torch.cat([
self.player_n_pulls,
self.pull_rewards,
(self.timestep / self.n_bandits)
], dim=-1).view(1, 1, 1, self.n_bandits, -1) * self.n_bandits / self.n_steps
def get_action(self, observation):
if observation.step > 0:
# Get r
r = observation.reward - self.total_reward
self.total_reward = observation.reward
# Update pull_rewards and player_n_pulls
opp_last_act = observation.lastActions[not observation.agentIndex]
self.pull_rewards[self.last_act] += r
self.player_n_pulls[self.last_act, 0] += 1
self.player_n_pulls[opp_last_act, 1] += 1
self.last_act = self.model.choose_best_action(self.get_obs()).item()
self.timestep += 1
return self.last_act
curr_agent = None
def agent(observation, configuration):
global curr_agent
if curr_agent is None:
curr_agent = ActorCriticAgent(configuration, serialized_string)
return curr_agent.get_action(observation)
| 1,938.331579
| 720,495
| 0.935091
| 43,645
| 736,566
| 15.767923
| 0.121961
| 1.487465
| 2.159989
| 2.785041
| 0.809143
| 0.80856
| 0.807991
| 0.807571
| 0.807318
| 0.80667
| 0
| 0.177527
| 0.005818
| 736,566
| 379
| 720,496
| 1,943.44591
| 0.762263
| 0.000934
| 0
| 0.546358
| 0
| 0.003311
| 0.980282
| 0.979805
| 0
| 1
| 0
| 0.002639
| 0.003311
| 1
| 0.10596
| false
| 0.02649
| 0.016556
| 0.009934
| 0.218543
| 0
| 0
| 0
| 1
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
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| null | 1
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| 0
|
0
| 15
|
f894ed03cc2d271ac7e83b32157f17d94082c1cf
| 15,894
|
py
|
Python
|
userframes.py
|
Aliossandro/WDOntoHistory
|
d9b9abd73a037abab25e36a990bf1d2be8e54ed5
|
[
"MIT"
] | null | null | null |
userframes.py
|
Aliossandro/WDOntoHistory
|
d9b9abd73a037abab25e36a990bf1d2be8e54ed5
|
[
"MIT"
] | null | null | null |
userframes.py
|
Aliossandro/WDOntoHistory
|
d9b9abd73a037abab25e36a990bf1d2be8e54ed5
|
[
"MIT"
] | null | null | null |
import pandas as pd
import psycopg2
import pickle
import numpy as np
# counterS = 0
# global counterS
# global valGlob
# from sqlalchemy import create_engine
# -*- coding: utf-8 -*-
import os
import sys
import copy
# fileName = '/Users/alessandro/Documents/PhD/OntoHistory/WDTaxo_October2014.csv'
# connection parameters
def get_db_params():
params = {
'database': 'wikidb',
'user': 'postgres',
'password': 'postSonny175',
'host': 'localhost',
'port': '5432'
}
conn = psycopg2.connect(**params)
return conn
# create table
def create_table():
###statement table query
query_table = """CREATE TABLE IF NOT EXISTS tempData AS (SELECT p.itemId, p.revId, (p.timestamp::timestamp) AS tS, t.statementId, t.statProperty, t.statvalue FROM
(SELECT itemId, revId, timestamp FROM revisionData_201710) p, (SELECT revId, statementId, statProperty, statvalue FROM statementsData_201710 WHERE statProperty = 'P279' OR statProperty = 'P31') t
WHERE p.revId = t.revId)"""
queryStatData = """CREATE TABLE IF NOT EXISTS statementDated AS (SELECT p.itemid, p.statproperty, p.statvalue, p.statementid, p.revid, t.timestamp, t.username
FROM statementsData_201710 p LEFT JOIN revisionData_201710 t ON p.revid::int = t.revid::int);"""
conn = None
try:
conn = get_db_params()
cur = conn.cursor()
cur.execute(query_table)
cur.close()
conn.commit()
except (Exception, psycopg2.DatabaseError) as error:
print(error)
finally:
if conn is not None:
conn.close()
conn = None
try:
conn = get_db_params()
cur = conn.cursor()
cur.execute(queryStatData)
cur.close()
conn.commit()
except (Exception, psycopg2.DatabaseError) as error:
print(error)
finally:
if conn is not None:
conn.close()
def queryexecutor():
# dictStats = {}
# conn = get_db_params()
# cur = conn.cursor()
for i in range(13, 18):
for j in range(1, 10):
date = "20" + str(i) + "-0" + str(j) + "-01"
if j == 1:
yr = i-1
datePrev = "20" + str(yr) + "-12-01"
else:
datePrev = "20" + str(i) + "-0" + str(j-1) + "-01"
print(date)
try:
queryStart = """
SELECT * INTO timetable_temp FROM revisionData_201710 WHERE (timestamp > '"""+ datePrev + """ 00:00:00' AND timestamp < '"""+ date + """ 00:00:00');
"""
conn = get_db_params()
cur = conn.cursor()
cur.execute(queryStart)
cur.close()
conn.commit()
queryBig = """
WITH revTempo AS (SELECT itemid, revid, timestamp, username FROM timetable_temp
WHERE (username NOT IN (SELECT bot_name FROM bot_list)
AND username !~ '([0-9]{1,3}[.]){3}[0-9]{1,3}|(([0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(:[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(ffff(:0{1,4}){0,1}:){0,1}((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])|([0-9a-fA-F]{1,4}:){1,4}:((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9]))'))
SELECT username, COUNT(*) AS noEdits, COUNT(DISTINCT itemid) AS itemDiv, (COUNT(*)/COUNT(DISTINCT itemid)::float) AS editRatio
FROM revTempo
GROUP BY username;
"""
#EXTRACT(EPOCH FROM ('2016-10-01 00:00:00'::timestamp - MIN(timestamp))) AS oldEdit,
# print(query)
df = pd.DataFrame()
for chunk in pd.read_sql(queryBig, con=conn, chunksize=1000):
df = df.append(chunk)
#columns: username, noEdits, itemDiv, editRatio
df['timeframe'] = date
queryOntoedit="""
SELECT username, COUNT(*) AS noOntoedit
FROM (SELECT * FROM timetable_temp WHERE itemId IN (SELECT DISTINCT statvalue FROM tempData) OR itemId IN (SELECT DISTINCT itemId FROM tempData WHERE statproperty != 'P31')) poopi
GROUP BY username;
"""
# print(query)
df_ontoedits = pd.DataFrame()
for chunk in pd.read_sql(queryOntoedit, con=conn, chunksize=1000):
df_ontoedits = df_ontoedits.append(chunk)
#columns: username, noOntoedit
df = df.merge(df_ontoedits, how='left')
queryPropedit="""
SELECT username, COUNT(*) AS noPropEdits
FROM timetable_temp WHERE itemId ~* '[P][0-9]{1,}'
GROUP BY username;
"""
# print(query)
df_Propedits = pd.DataFrame()
for chunk in pd.read_sql(queryPropedit, con=conn, chunksize=1000):
df_Propedits = df_Propedits.append(chunk)
#columns: username, noPropEdits
df = df.merge(df_Propedits, how='left')
queryCommedit="""
SELECT user_name AS username, COUNT(*) AS noCommEdits
FROM revision_pages_201710 WHERE (time_stamp > '"""+ datePrev + """ 00:00:00' AND time_stamp < '"""+ date + """ 00:00:00') AND (user_name NOT IN (SELECT bot_name FROM bot_list))
AND item_id !~* 'Property:P*'
GROUP BY user_name;
"""
# print(query)
df_Commedits = pd.DataFrame()
for chunk in pd.read_sql(queryCommedit, con=conn, chunksize=1000):
df_Commedits = df_Commedits.append(chunk)
#columns: username, noCommEdits
df = df.merge(df_Commedits, how='left')
queryTaxo = """
SELECT username, COUNT(*) AS noTaxoEdits
FROM statementDated WHERE (timestamp > '"""+ datePrev + """ 00:00:00' AND timestamp < '"""+ date + """ 00:00:00')
AND username NOT IN (SELECT bot_name FROM bot_list) AND (statProperty = 'P31' or statProperty = 'P279')
AND username !~ '([0-9]{1,3}[.]){3}[0-9]{1,3}|(([0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(:[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(ffff(:0{1,4}){0,1}:){0,1}((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])|([0-9a-fA-F]{1,4}:){1,4}:((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9]))')
GROUP BY username
"""
# print(query)
df_Taxedits = pd.DataFrame()
for chunk in pd.read_sql(queryTaxo, con=conn, chunksize=1000):
df_Taxedits = df_Taxedits.append(chunk)
#columns: username, noTaxoEdits
df = df.merge(df_Taxedits, how='left')
queryBatch = """
SELECT user_name AS username, COUNT(*) AS noBatchedit
FROM (SELECT * FROM revision_history_tagged WHERE automated_tool = 't'
AND (time_stamp > '"""+ datePrev + """ 00:00:00' AND time_stamp < '"""+ date + """ 00:00:00')) AS pippo
GROUP BY user_name
"""
# print(query)
df_Batchedits = pd.DataFrame()
for chunk in pd.read_sql(queryBatch, con=conn, chunksize=1000):
df_Batchedits = df_Batchedits.append(chunk)
#columns: username, noBatchedit
df = df.merge(df_Batchedits, how='left')
fileName = "WDuserstats-" + date + ".csv"
df.to_csv(fileName, index=False)
queryClose = """
DROP TABLE timetable_temp;
"""
# conn = get_db_params()
# cur = conn.cursor()
cur.execute(queryClose)
cur.close()
conn.commit()
except Exception as e:
print(e, "no df available")
queryClose = """
DROP TABLE timetable_temp;
"""
# conn = get_db_params()
# cur = conn.cursor()
cur.execute(queryClose)
cur.close()
conn.commit()
for j in range(10, 13):
date = "20" + str(i) + "-" + str(j) + "-01"
if j == 10:
mt = '09'
datePrev = "20" + str(i) + "-" + mt + "-01"
else:
date = "20" + str(i) + "-" + str(j-1) + "-01"
print(date)
try:
queryStart = """
SELECT * INTO timetable_temp FROM revisionData_201710 WHERE (timestamp > '"""+ datePrev + """ 00:00:00' AND timestamp < '"""+ date + """ 00:00:00');
"""
conn = get_db_params()
cur = conn.cursor()
cur.execute(queryStart)
cur.close()
conn.commit()
queryBig = """
WITH revTempo AS (SELECT itemid, revid, timestamp, username FROM timetable_temp
WHERE (username NOT IN (SELECT bot_name FROM bot_list)
AND username !~ '([0-9]{1,3}[.]){3}[0-9]{1,3}|(([0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(:[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(ffff(:0{1,4}){0,1}:){0,1}((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])|([0-9a-fA-F]{1,4}:){1,4}:((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9]))'))
SELECT username, COUNT(*) AS noEdits, COUNT(DISTINCT itemid) AS itemDiv, (COUNT(*)/COUNT(DISTINCT itemid)::float) AS editRatio
FROM revTempo
GROUP BY username;
"""
#EXTRACT(EPOCH FROM ('2016-10-01 00:00:00'::timestamp - MIN(timestamp))) AS oldEdit,
# print(query)
df = pd.DataFrame()
for chunk in pd.read_sql(queryBig, con=conn, chunksize=1000):
df = df.append(chunk)
#columns: username, noEdits, itemDiv, editRatio
df['timeframe'] = date
queryOntoedit="""
SELECT username, COUNT(*) AS noOntoedit
FROM (SELECT * FROM timetable_temp WHERE itemId IN (SELECT DISTINCT statvalue FROM tempData) OR itemId IN (SELECT DISTINCT itemId FROM tempData WHERE statproperty != 'P31')) poopi
GROUP BY username;
"""
# print(query)
df_ontoedits = pd.DataFrame()
for chunk in pd.read_sql(queryOntoedit, con=conn, chunksize=1000):
df_ontoedits = df_ontoedits.append(chunk)
#columns: username, noOntoedit
df = df.merge(df_ontoedits, how='left')
queryPropedit="""
SELECT username, COUNT(*) AS noPropEdits
FROM timetable_temp WHERE itemId ~* '[P][0-9]{1,}'
GROUP BY username;
"""
# print(query)
df_Propedits = pd.DataFrame()
for chunk in pd.read_sql(queryPropedit, con=conn, chunksize=1000):
df_Propedits = df_Propedits.append(chunk)
#columns: username, noPropEdits
df = df.merge(df_Propedits, how='left')
queryCommedit="""
SELECT user_name AS username, COUNT(*) AS noCommEdits
FROM revision_pages_201710 WHERE (time_stamp > '"""+ datePrev + """ 00:00:00' AND time_stamp < '"""+ date + """ 00:00:00') AND (user_name NOT IN (SELECT bot_name FROM bot_list))
AND item_id !~* 'Property:P*'
GROUP BY user_name;
"""
# print(query)
df_Commedits = pd.DataFrame()
for chunk in pd.read_sql(queryCommedit, con=conn, chunksize=1000):
df_Commedits = df_Commedits.append(chunk)
#columns: username, noCommEdits
df = df.merge(df_Commedits, how='left')
queryTaxo = """
SELECT username, COUNT(*) AS noTaxoEdits
FROM statementDated WHERE (timestamp > '"""+ datePrev + """ 00:00:00' AND timestamp < '"""+ date + """ 00:00:00')
AND username NOT IN (SELECT bot_name FROM bot_list) AND (statProperty = 'P31' or statProperty = 'P279')
AND username !~ '([0-9]{1,3}[.]){3}[0-9]{1,3}|(([0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(:[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(ffff(:0{1,4}){0,1}:){0,1}((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])|([0-9a-fA-F]{1,4}:){1,4}:((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])[.]){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9]))')
GROUP BY username
"""
# print(query)
df_Taxedits = pd.DataFrame()
for chunk in pd.read_sql(queryTaxo, con=conn, chunksize=1000):
df_Taxedits = df_Taxedits.append(chunk)
#columns: username, noTaxoEdits
df = df.merge(df_Taxedits, how='left')
queryBatch = """
SELECT user_name AS username, COUNT(*) AS noBatchedit
FROM (SELECT * FROM revision_history_tagged WHERE automated_tool = 't'
AND (time_stamp > '"""+ datePrev + """ 00:00:00' AND time_stamp < '"""+ date + """ 00:00:00')) AS pippo
GROUP BY user_name
"""
# print(query)
df_Batchedits = pd.DataFrame()
for chunk in pd.read_sql(queryBatch, con=conn, chunksize=1000):
df_Batchedits = df_Batchedits.append(chunk)
#columns: username, noBatchedit
df = df.merge(df_Batchedits, how='left')
fileName = "WDuserstats-" + date + ".csv"
df.to_csv(fileName, index=False)
queryClose = """
DROP TABLE timetable_temp;
"""
# conn = get_db_params()
# cur = conn.cursor()
cur.execute(queryClose)
cur.close()
conn.commit()
except Exception as e:
print(e, "no df available")
queryClose = """
DROP TABLE timetable_temp;
"""
# conn = get_db_params()
# cur = conn.cursor()
cur.execute(queryClose)
cur.close()
conn.commit()
# try:
# pickle_out = open("WDdata.pickle", "wb")
# pickle.dump(dictStats, pickle_out)
# pickle_out.close()
# except:
# print("suca")
def main():
# create_table()
queryexecutor()
if __name__ == "__main__":
main()
| 42.84097
| 730
| 0.510255
| 2,296
| 15,894
| 3.466463
| 0.09277
| 0.021108
| 0.045232
| 0.054278
| 0.859153
| 0.848348
| 0.843071
| 0.839553
| 0.839553
| 0.839553
| 0
| 0.095082
| 0.289984
| 15,894
| 370
| 731
| 42.956757
| 0.610191
| 0.083868
| 0
| 0.821577
| 0
| 0.053942
| 0.508101
| 0.205171
| 0
| 0
| 0
| 0
| 0
| 1
| 0.016598
| false
| 0.004149
| 0.029046
| 0
| 0.049793
| 0.024896
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
f8a2a6433069df6a41eee5c260ab9bb65e689684
| 4,882
|
py
|
Python
|
tests/commands/test_templates_status.py
|
hs4man21/datakit-project
|
97fe2fc7d900fd1ae22e6f40a5d1302ab2860abe
|
[
"0BSD"
] | 24
|
2018-03-09T05:36:29.000Z
|
2022-03-10T09:18:47.000Z
|
tests/commands/test_templates_status.py
|
hs4man21/datakit-project
|
97fe2fc7d900fd1ae22e6f40a5d1302ab2860abe
|
[
"0BSD"
] | 32
|
2017-02-03T22:55:12.000Z
|
2021-08-11T01:40:54.000Z
|
tests/commands/test_templates_status.py
|
hs4man21/datakit-project
|
97fe2fc7d900fd1ae22e6f40a5d1302ab2860abe
|
[
"0BSD"
] | 4
|
2018-03-21T11:16:30.000Z
|
2022-03-31T17:29:38.000Z
|
import os
import re
import shutil
import subprocess
from unittest import mock
import cookiecutter.config as cc_config
import pytest
from datakit_project import cookiecutters, Templates
from datakit_project import exceptions as dkit_exceptions
def test_noupdate_status(caplog, cookiecutter_home, deploy_template, monkeypatch, tmpdir):
deploy_template(cookiecutter_home, 'tests/fake-repo')
deploy_template(cookiecutter_home, 'tests/fake-repo-two')
# Switch directories
monkeypatch.chdir(tmpdir)
# Mock the return value for Cookiecutters.info
with mock.patch('datakit_project.commands.templates.Cookiecutters') as MockClass:
instance = MockClass.return_value
instance.info.return_value = [
{
'Name': 'fake-repo',
'SHA': 'a11706f',
'Date': '2017-02-02',
'Subject': 'Testing',
'upstream_sha': 'a11706f',
'upstream_date': '2017-02-02',
'upstream_subject': 'Testing',
'commits_behind': 'Up-to-date'
},
{
'Name': 'fake-repo-two',
'SHA': '55f62a0',
'Date': '2019-03-06',
'Subject': 'Testing',
'upstream_sha': '55f62a0',
'upstream_date': '2019-03-06',
'upstream_subject': 'Testing',
'commits_behind': 'Up-to-date'
},
]
# Run the command
parsed_args = mock.Mock()
# Set status flag to true
parsed_args.status = True
cmd = Templates(None, None, cmd_name='project templates')
cmd.run(parsed_args)
header = "Name SHA Date Upstream SHA Upstream Date Commits behind"
repo1 = "fake-repo a11706f 2017-02-02 a11706f 2017-02-02 Up-to-date"
repo2 = "fake-repo-two 55f62a0 2019-03-06 55f62a0 2019-03-06 Up-to-date"
expected = [header, repo1, repo2]
# Some gross cleanup of caplog.text is necessary because it displays log level info
actual = [re.sub(r"templates.py\s+\d+\sINFO", "", line).strip() for line in caplog.text.split('\n')]
# Test that expected lines appear in displayed text
for line in expected:
assert line in actual
# Test alpha sortting by repo name
header_idx = actual.index(header)
repo1_idx = actual.index(repo1)
repo2_idx = actual.index(repo2)
assert header_idx < repo1_idx
assert repo1_idx < repo2_idx
def test_repo_behind_upstream(caplog, cookiecutter_home, deploy_template, monkeypatch, tmpdir):
deploy_template(cookiecutter_home, 'tests/fake-repo')
deploy_template(cookiecutter_home, 'tests/fake-repo-two')
# Switch directories
monkeypatch.chdir(tmpdir)
# Mock the return value for Cookiecutters.info
with mock.patch('datakit_project.commands.templates.Cookiecutters') as MockClass:
instance = MockClass.return_value
instance.info.return_value = [
{
'Name': 'fake-repo',
'SHA': 'a11706f',
'Date': '2017-02-02',
'Subject': 'Testing',
'upstream_sha': 'c18705e',
'upstream_date': '2017-06-01',
'upstream_subject': 'Some newer commit',
'commits_behind': 3
},
{
'Name': 'fake-repo-two',
'SHA': '55f62a0',
'Date': '2019-03-06',
'Subject': 'Testing',
'upstream_sha': '55f62a0',
'upstream_date': '2019-03-06',
'upstream_subject': 'Testing',
'commits_behind': 'Up-to-date'
},
]
# Run the command
parsed_args = mock.Mock()
# Set status flag to true
parsed_args.status = True
cmd = Templates(None, None, cmd_name='project templates')
cmd.run(parsed_args)
header = "Name SHA Date Upstream SHA Upstream Date Commits behind"
repo1 = "fake-repo a11706f 2017-02-02 c18705e 2017-06-01 3"
repo2 = "fake-repo-two 55f62a0 2019-03-06 55f62a0 2019-03-06 Up-to-date"
expected = [header, repo1, repo2]
# Some gross cleanup of caplog.text is necessary because it displays log level info
actual = [re.sub(r"templates.py\s+\d+\sINFO", "", line).strip() for line in caplog.text.split('\n')]
# Test that expected lines appear in displayed text
for line in expected:
assert line in actual
# Test alpha sortting by repo name
header_idx = actual.index(header)
repo1_idx = actual.index(repo1)
repo2_idx = actual.index(repo2)
assert header_idx < repo1_idx
assert repo1_idx < repo2_idx
| 41.372881
| 109
| 0.582343
| 555
| 4,882
| 5.005405
| 0.207207
| 0.034557
| 0.023038
| 0.043197
| 0.859251
| 0.859251
| 0.859251
| 0.859251
| 0.843773
| 0.843773
| 0
| 0.069316
| 0.31442
| 4,882
| 117
| 110
| 41.726496
| 0.760681
| 0.109996
| 0
| 0.701031
| 0
| 0.020619
| 0.299538
| 0.033256
| 0
| 0
| 0
| 0
| 0.061856
| 1
| 0.020619
| false
| 0
| 0.092784
| 0
| 0.113402
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| null | 0
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| 0
| 0
|
0
| 7
|
f8b176789cd0254772d99a59b6ab6781d184ae9a
| 4,276
|
py
|
Python
|
process_annotation.py
|
CCC-123/ECCVC
|
322009a3423dba831cb3ae4182e7129be3441e70
|
[
"MIT"
] | null | null | null |
process_annotation.py
|
CCC-123/ECCVC
|
322009a3423dba831cb3ae4182e7129be3441e70
|
[
"MIT"
] | null | null | null |
process_annotation.py
|
CCC-123/ECCVC
|
322009a3423dba831cb3ae4182e7129be3441e70
|
[
"MIT"
] | null | null | null |
# -----------------------------------------------------
# Transform Annotation Information to Structured Data
#
# Author: Liangqi Li
# Creating Date: May 30, 2018
# Latest rectifying: May 30, 2018
# -----------------------------------------------------
import os
import json
import numpy as np
import pandas as pd
def process_train_set(anno_dir):
"""Read training annotation files and transfer into DataFrame"""
q_movies = []
q_ids = []
q_ims = []
g_movies = []
g_ids = []
g_ims = []
g_boxes = np.zeros((1, 4), dtype=np.int32)
g_pids = []
with open(os.path.join(anno_dir, 'train.json'), 'r') as f:
train = json.load(f)
for movie, images in train.items():
casts = images['cast']
candidates = images['candidates']
for cast in casts:
id_num = cast['id'].split('_')[-1]
assert id_num == cast['label']
im_name = cast['img'].split('/')[-1]
q_movies.append(movie)
q_ids.append(id_num)
q_ims.append(im_name)
for cand in candidates:
id_num = cand['id'].split('_')[-1]
im_name = cand['img'].split('/')[-1]
box = np.array(cand['bbox'])
pid = cand['label']
g_movies.append(movie)
g_ids.append(id_num)
g_ims.append(im_name)
g_boxes = np.vstack((g_boxes, box))
g_pids.append(pid)
queries = pd.DataFrame({'movie': q_movies, 'imname': q_ims, 'pid': q_ids})
# Remove the first row
g_boxes = g_boxes[1:]
galleries = pd.DataFrame(g_boxes, columns=['x1', 'y1', 'del_x', 'del_y'])
galleries['movie'] = g_movies
galleries['id'] = g_ids
galleries['imname'] = g_ims
galleries['pid'] = g_pids
# Indicate the order of the column names
ordered_columns = ['movie', 'imname', 'id', 'x1', 'y1', 'del_x', 'del_y',
'pid']
galleries = galleries[ordered_columns]
# Save the DataFrames to csv files
queries.to_csv(os.path.join(anno_dir, 'trainQueriesDF.csv'), index=False)
galleries.to_csv(os.path.join(anno_dir, 'trainGalleriesDF.csv'),
index=False)
def process_val_set(anno_dir):
"""Read validate annotation files and transfer into DataFrame"""
q_movies = []
q_ids = []
q_ims = []
g_movies = []
g_ids = []
g_ims = []
g_boxes = np.zeros((1, 4), dtype=np.int32)
g_pids = []
with open(os.path.join(anno_dir, 'val.json'), 'r') as f:
val = json.load(f)
for movie, images in val.items():
casts = images['cast']
candidates = images['candidates']
for cast in casts:
id_num = cast['id'].split('_')[-1]
assert id_num == cast['label']
im_name = cast['img'].split('/')[-1]
q_movies.append(movie)
q_ids.append(id_num)
q_ims.append(im_name)
for cand in candidates:
id_num = cand['id'].split('_')[-1]
im_name = cand['img'].split('/')[-1]
box = np.array(cand['bbox'])
pid = cand['label']
g_movies.append(movie)
g_ids.append(id_num)
g_ims.append(im_name)
g_boxes = np.vstack((g_boxes, box))
g_pids.append(pid)
queries = pd.DataFrame({'movie': q_movies, 'imname': q_ims, 'pid': q_ids})
# Remove the first row
g_boxes = g_boxes[1:]
galleries = pd.DataFrame(g_boxes, columns=['x1', 'y1', 'del_x', 'del_y'])
galleries['movie'] = g_movies
galleries['id'] = g_ids
galleries['imname'] = g_ims
galleries['pid'] = g_pids
# Indicate the order of the column names
ordered_columns = ['movie', 'imname', 'id', 'x1', 'y1', 'del_x', 'del_y',
'pid']
galleries = galleries[ordered_columns]
# Save the DataFrames to csv files
queries.to_csv(os.path.join(anno_dir, 'valQueriesDF.csv'), index=False)
galleries.to_csv(os.path.join(anno_dir, 'valGalleriesDF.csv'),
index=False)
def main():
anno_dir = '/home/liliangqi/hdd/datasets/ECCVchallenge/' +\
'person_search_trainval'
process_train_set(anno_dir)
process_val_set(anno_dir)
if __name__ == '__main__':
main()
| 30.326241
| 78
| 0.554724
| 559
| 4,276
| 4.026834
| 0.21288
| 0.031986
| 0.026655
| 0.037317
| 0.825411
| 0.788094
| 0.788094
| 0.765882
| 0.765882
| 0.765882
| 0
| 0.012238
| 0.273854
| 4,276
| 140
| 79
| 30.542857
| 0.712721
| 0.126988
| 0
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| 0
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| 0.01752
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| 0.020202
| 1
| 0.030303
| false
| 0
| 0.040404
| 0
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| 0
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| 0
| null | 0
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| 1
| 1
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|
0
| 7
|
3e40f9fb0756b661895559fe9f1519fdf7d23cec
| 2,459
|
py
|
Python
|
create_invoices.py
|
MrDionesalvi/APU
|
a992cffca3332bcc7ba1e3ed5d42f3f4789d0b8b
|
[
"MIT"
] | null | null | null |
create_invoices.py
|
MrDionesalvi/APU
|
a992cffca3332bcc7ba1e3ed5d42f3f4789d0b8b
|
[
"MIT"
] | null | null | null |
create_invoices.py
|
MrDionesalvi/APU
|
a992cffca3332bcc7ba1e3ed5d42f3f4789d0b8b
|
[
"MIT"
] | null | null | null |
from utils import *
from database import Database
from datetime import date
import html
import json
def create_Allinvoice():
users = get_Users()
today = date.today()
datetoPrint = today.strftime('%d-%m-%Y')
for i in json.loads(users):
data = {
'common_bees': 0,
'precious_bees': 0,
'mineral_bees': 0,
'nether_bees': 0,
'price_bees': 0
}
user = i['username']
user_apiarys = get_ApiarysFromUser(user)
for j in json.loads(user_apiarys):
if int(j['typeBee']) == 0:
data['common_bees'] += 1
elif int(j['typeBee']) == 1:
data['precious_bees'] += 1
elif int(j['typeBee']) == 2:
data['mineral_bees'] += 1
elif int(j['typeBee']) == 3:
data['nether_bees'] += 1
taxesToPay = count_taxes(data['common_bees'], data['precious_bees'], data['mineral_bees'], data['nether_bees'])
if taxesToPay > 0:
db = Database()
db_session = db.session
db_session.add(db.invoices(user = user, date = datetoPrint, ammount = taxesToPay))
print(user, datetoPrint, taxesToPay)
db_session.commit()
db.session.close()
def create_invoice(user):
today = date.today()
datetoPrint = today.strftime('%d-%m-%Y')
data = {
'common_bees': 0,
'precious_bees': 0,
'mineral_bees': 0,
'nether_bees': 0,
'price_bees': 0
}
user_apiarys = get_ApiarysFromUser(user)
for j in json.loads(user_apiarys):
if int(j['typeBee']) == 0:
data['common_bees'] += 1
elif int(j['typeBee']) == 1:
data['precious_bees'] += 1
elif int(j['typeBee']) == 2:
data['mineral_bees'] += 1
elif int(j['typeBee']) == 3:
data['nether_bees'] += 1
taxesToPay = count_taxes(data['common_bees'], data['precious_bees'], data['mineral_bees'], data['nether_bees'])
if taxesToPay > 0:
db = Database()
db_session = db.session
db_session.add(db.invoices(user = user, date = datetoPrint, ammount = taxesToPay))
print(user, datetoPrint, taxesToPay)
db_session.commit()
db.session.close()
if __name__ == '__main__':
create_Allinvoice()
| 31.126582
| 120
| 0.52867
| 275
| 2,459
| 4.538182
| 0.207273
| 0.040064
| 0.070513
| 0.057692
| 0.847756
| 0.847756
| 0.847756
| 0.847756
| 0.847756
| 0.782051
| 0
| 0.017115
| 0.334689
| 2,459
| 79
| 121
| 31.126582
| 0.745721
| 0
| 0
| 0.787879
| 0
| 0
| 0.163728
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.030303
| false
| 0
| 0.075758
| 0
| 0.106061
| 0.030303
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
3e5fe053198c3f814cf81735accdc4572a776617
| 3,872
|
py
|
Python
|
MCBS_dividendos.py
|
cadovid/finance-math-bsmc
|
ab720c62fab4e2a20b12839689724942b950b44b
|
[
"Apache-2.0"
] | null | null | null |
MCBS_dividendos.py
|
cadovid/finance-math-bsmc
|
ab720c62fab4e2a20b12839689724942b950b44b
|
[
"Apache-2.0"
] | null | null | null |
MCBS_dividendos.py
|
cadovid/finance-math-bsmc
|
ab720c62fab4e2a20b12839689724942b950b44b
|
[
"Apache-2.0"
] | 1
|
2020-07-05T11:40:33.000Z
|
2020-07-05T11:40:33.000Z
|
# -*- coding: utf-8 -*-
"""
En este apartado se establecen las funciones con los metodos de Monte Carlo y
Black Scholes para evaluar opciones europeas vainillas de compra y de venta con
dividendos.
Funcion metodo de Monte Carlo:
Permite estimar el valor de una opcion vainilla europea tanto de compra como de
venta con dividendos.
Inputs de la funcion def montecarlo_d(S0,K,r,sigma,T,I,D0):
S0=17. Es el valor inicial del activo
K=15. Es el precio de ejercicio o strike
r=0.03 Es el tipo de interes constante
sigma=0.25 Es la volatilidad del activo
T=0.25 Es el periodo a vencimiento dado en numero de anos
I=1000000 Es el numero de trayectorias del metodo (Opcional)
D0=0.015 Es la tasa de dividendos continuos (Opcional)
Funcion metodo de Black Scholes:
Permite estimar el valor de una opcion vainilla europea tanto de compra como de
venta con dividendos.
Inputs de la funcion def bs_d(S0,K,T,r,sigma,D0):
S0=17. Es el valor inicial del activo
K=15. Es el precio de ejercicio o strike
T=0.25 Es el periodo a vencimiento dado en numero de anos
r=0.03 Es el tipo de interes constante
sigma=0.25 Es la volatilidad del activo
D0=0.015 Es la tasa de dividendos continuos (Opcional)
David Camino Perdones
"""
def montecarlo_d(S0,K,r,sigma,T,I=1000000,D0=0):
import numpy as np
menu={1:'Evaluar opcion de compra',2:'Evaluar opcion de venta'}
choice=eval(input('Elija la operacion deseada:\n1: Evaluar opcion de compra\n2: Evaluar opcion de venta\n'))
if choice==1:
print('Ha seleccionado:',menu[choice])
ST=S0*np.exp((r-D0-sigma**2/2)*T+sigma*np.sqrt(T)*np.random.standard_normal(I))
hT=np.maximum(ST-K,0)
V0=np.exp(-r*T)*np.sum(hT)/I
std=np.sqrt(sum((np.exp(-r*T)*hT-V0)**2)/I) #desviacion tipica
s=r'%' #Calculo del intervalo de confianza al 95%
print("Intervalo de confianza al 95"+s+"(%f,%f)"%(V0-1.96*std/np.sqrt(I),V0+1.96*std/np.sqrt(I)))
print('El precio de la opcion es %f' %V0)
elif choice==2:
print('Ha seleccionado:',menu[choice])
ST=S0*np.exp((r-D0-sigma**2/2)*T+sigma*np.sqrt(T)*np.random.standard_normal(I))
hT=np.maximum(K-ST,0)
V0=np.exp(-r*T)*np.sum(hT)/I
std=np.sqrt(sum((np.exp(-r*T)*hT-V0)**2)/I) #desviacion tipica
s=r'%' #Calculo del intervalo de confianza al 95%
print("Intervalo de confianza al 95"+s+"(%f,%f)"%(V0-1.96*std/np.sqrt(I),V0+1.96*std/np.sqrt(I)))
print('El precio de la opcion es %f' %V0)
else:
print('Ha seleccionado una opcion no valida. Intentelo de nuevo.')
return None
def bs_d(S0,K,T,r,sigma,D0=0):
import math
from scipy import stats
menu={1:'Evaluar opcion de compra',2:'Evaluar opcion de venta'}
choice=eval(input('Elija la operacion deseada:\n1: Evaluar opcion de compra\n2: Evaluar opcion de venta\n'))
if choice==1:
print('Ha seleccionado:',menu[choice])
d1=(math.log(S0/K)+(r-D0+0.5*sigma**2)*T)/(sigma*math.sqrt(T))
d2=(math.log(S0/K)+(r-D0-0.5*sigma**2)*T)/(sigma*math.sqrt(T))
valor=(S0*math.exp(-D0*T)*stats.norm.cdf(d1,0.0,1.0)-K*math.exp(-r*T)*stats.norm.cdf(d2,0.0,1.0))
print('El precio de la opcion es %f' %valor)
elif choice==2:
print('Ha seleccionado:',menu[choice])
d1=(math.log(S0/K)+(r-D0+0.5*sigma**2)*T)/(sigma*math.sqrt(T))
d2=(math.log(S0/K)+(r-D0-0.5*sigma**2)*T)/(sigma*math.sqrt(T))
valor=(K*math.exp(-r*T)*stats.norm.cdf(-d2,0.0,1.0)-S0*math.exp(-D0*T)*stats.norm.cdf(-d1,0.0,1.0))
print('El precio de la opcion es %f' %valor)
else:
print('Ha seleccionado una opcion no valida. Intentelo de nuevo.')
return None
| 48.4
| 113
| 0.630424
| 691
| 3,872
| 3.523878
| 0.206946
| 0.014784
| 0.049281
| 0.034497
| 0.863244
| 0.863244
| 0.863244
| 0.863244
| 0.854209
| 0.822177
| 0
| 0.054726
| 0.221333
| 3,872
| 79
| 114
| 49.012658
| 0.752902
| 0.371643
| 0
| 0.8
| 0
| 0
| 0.268147
| 0
| 0
| 0
| 0
| 0.050633
| 0
| 1
| 0.044444
| false
| 0
| 0.066667
| 0
| 0.155556
| 0.266667
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
3e8f55b0523dbc33877d3dec73cc5ce8996a623b
| 37,341
|
py
|
Python
|
src/test/python/thalesians/tsa/testdistrs.py
|
saarahrasheed/tsa
|
e4460f707eeecb737663c48d8fc3245f0acb124c
|
[
"Apache-2.0"
] | null | null | null |
src/test/python/thalesians/tsa/testdistrs.py
|
saarahrasheed/tsa
|
e4460f707eeecb737663c48d8fc3245f0acb124c
|
[
"Apache-2.0"
] | null | null | null |
src/test/python/thalesians/tsa/testdistrs.py
|
saarahrasheed/tsa
|
e4460f707eeecb737663c48d8fc3245f0acb124c
|
[
"Apache-2.0"
] | null | null | null |
import unittest
import numpy as np
import numpy.testing as npt
import thalesians.tsa.distrs as distrs
import thalesians.tsa.numpyutils as npu
import thalesians.tsa.randomness as rnd
import thalesians.tsa.stats as stats
class TestDistrs(unittest.TestCase):
def test_wide_sense_distr(self):
std_wide_sense_1d = distrs.WideSenseDistr(dim=1)
npt.assert_almost_equal(std_wide_sense_1d.mean, 0.)
npt.assert_almost_equal(std_wide_sense_1d.cov, 1.)
npt.assert_almost_equal(std_wide_sense_1d.vol, 1.)
with self.assertRaises(NotImplementedError):
std_wide_sense_1d.sample()
std_wide_sense_2d = distrs.WideSenseDistr(dim=2)
npt.assert_almost_equal(std_wide_sense_2d.mean, npu.col_of(2, 0.))
npt.assert_almost_equal(std_wide_sense_2d.cov, np.eye(2))
npt.assert_almost_equal(std_wide_sense_2d.vol, np.eye(2))
with self.assertRaises(NotImplementedError):
std_wide_sense_2d.sample()
sd1=3.; sd2=4.; cor=-.5
wide_sense_2d = distrs.WideSenseDistr(mean=[1., 2.], cov=stats.make_cov_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(wide_sense_2d.mean, npu.col(1., 2.))
npt.assert_almost_equal(wide_sense_2d.cov, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(wide_sense_2d.vol, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
with self.assertRaises(NotImplementedError):
wide_sense_2d.sample()
wide_sense_2d = distrs.WideSenseDistr(mean=[1., 2.], vol=stats.make_vol_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(wide_sense_2d.mean, npu.col(1., 2.))
npt.assert_almost_equal(wide_sense_2d.cov, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(wide_sense_2d.vol, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
with self.assertRaises(NotImplementedError):
wide_sense_2d.sample()
def test_normal_distr(self):
rnd.random_state(np.random.RandomState(seed=42), force=True)
std_normal_1d = distrs.NormalDistr(dim=1)
npt.assert_almost_equal(std_normal_1d.mean, 0.)
npt.assert_almost_equal(std_normal_1d.cov, 1.)
npt.assert_almost_equal(std_normal_1d.vol, 1.)
sample = std_normal_1d.sample()
self.assertEqual(np.shape(sample), (1, 1))
npt.assert_almost_equal(sample, [[ 0.49671415]])
sample = std_normal_1d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 1))
npt.assert_almost_equal(sample, [
[-0.1382643 ],
[ 0.64768854],
[ 1.52302986],
[-0.23415337],
[-0.23413696],
[ 1.57921282],
[ 0.76743473],
[-0.46947439],
[ 0.54256004],
[-0.46341769]])
std_normal_2d = distrs.NormalDistr(dim=2)
npt.assert_almost_equal(std_normal_2d.mean, npu.col_of(2, 0.))
npt.assert_almost_equal(std_normal_2d.cov, np.eye(2))
npt.assert_almost_equal(std_normal_2d.vol, np.eye(2))
sample = std_normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[-0.46572975, 0.24196227],
[-1.91328024, -1.72491783],
[-0.56228753, -1.01283112],
[ 0.31424733, -0.90802408],
[-1.4123037 , 1.46564877],
[-0.2257763 , 0.0675282 ],
[-1.42474819, -0.54438272],
[ 0.11092259, -1.15099358],
[ 0.37569802, -0.60063869],
[-0.29169375, -0.60170661]])
sd1=3.; sd2=4.; cor=-.5
normal_2d = distrs.NormalDistr(mean=[1., 2.], cov=stats.make_cov_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(normal_2d.mean, npu.col(1., 2.))
npt.assert_almost_equal(normal_2d.cov, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(normal_2d.vol, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
sample = normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[-3.09581812, 9.06710684],
[ 5.00400357, -1.07912958],
[ 4.10821238, -2.42324481],
[ 2.58989516, -7.05256838],
[ 2.07671635, 3.61955714],
[ 0.38728403, 2.5195548 ],
[-1.36010204, -0.88681309],
[ 1.63968707, -1.29329703],
[-0.61960168, 6.44566548],
[ 5.53451941, -4.36131646]])
normal_2d = distrs.NormalDistr(mean=[1., 2.], vol=stats.make_vol_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(normal_2d.mean, npu.col(1., 2.))
npt.assert_almost_equal(normal_2d.cov, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(normal_2d.vol, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
sample = normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 0.4624506 , -0.26705979],
[ 1.76344545, 5.54913479],
[-2.76038957, 4.57609973],
[ 2.35608833, 1.20642031],
[-2.1218454 , 5.16796697],
[-0.85307657, -0.00850715],
[ 5.28771297, -1.62048489],
[-2.12592264, 7.1016208 ],
[-0.46508111, 6.26189296],
[ 3.15543223, -0.04269231]])
def test_dirac_delta_distr(self):
std_dirac_delta_1d = distrs.DiracDeltaDistr(dim=1)
npt.assert_almost_equal(std_dirac_delta_1d.mean, 0.)
npt.assert_almost_equal(std_dirac_delta_1d.cov, 0.)
npt.assert_almost_equal(std_dirac_delta_1d.vol, 0.)
sample = std_dirac_delta_1d.sample()
self.assertEqual(np.shape(sample), (1, 1))
npt.assert_almost_equal(sample, [[ 0. ]])
sample = std_dirac_delta_1d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 1))
npt.assert_almost_equal(sample, [
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.],
[ 0.]])
std_dirac_delta_2d = distrs.DiracDeltaDistr(dim=2)
npt.assert_almost_equal(std_dirac_delta_2d.mean, npu.col_of(2, 0.))
npt.assert_almost_equal(std_dirac_delta_2d.cov, np.zeros((2, 2)))
npt.assert_almost_equal(std_dirac_delta_2d.vol, np.zeros((2, 2)))
sample = std_dirac_delta_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.],
[ 0., 0.]])
dirac_delta_2d = distrs.DiracDeltaDistr(mean=[1., 2.], dim=2)
npt.assert_almost_equal(dirac_delta_2d.mean, [[1.], [2.]])
npt.assert_almost_equal(dirac_delta_2d.cov, np.zeros((2, 2)))
npt.assert_almost_equal(dirac_delta_2d.vol, np.zeros((2, 2)))
sample = dirac_delta_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.],
[ 1., 2.]])
def test_log_normal_distr(self):
rnd.random_state(np.random.RandomState(seed=42), force=True)
std_log_normal_1d = distrs.LogNormalDistr(dim=1)
npt.assert_almost_equal(std_log_normal_1d.mean, [[ 1.6487213]])
npt.assert_almost_equal(std_log_normal_1d.cov, [[ 4.6707743]])
npt.assert_almost_equal(std_log_normal_1d.vol, [[ 2.1611974]])
sample = std_log_normal_1d.sample(size=1)
self.assertEqual(np.shape(sample), (1, 1))
npt.assert_almost_equal(sample, [[ 1.6433127]])
sample = std_log_normal_1d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 1))
npt.assert_almost_equal(sample, [
[ 0.87086849],
[ 1.91111824],
[ 4.58609939],
[ 0.79124045],
[ 0.79125344],
[ 4.85113557],
[ 2.15423297],
[ 0.62533086],
[ 1.72040554],
[ 0.62912979]])
std_log_normal_2d = distrs.LogNormalDistr(dim=2)
npt.assert_almost_equal(std_log_normal_2d.mean, [
[ 1.6487213],
[ 1.6487213]])
npt.assert_almost_equal(std_log_normal_2d.cov, [
[ 4.6707743, 0. ],
[ 0. , 4.6707743]])
npt.assert_almost_equal(std_log_normal_2d.vol, [
[ 2.1611974, 0. ],
[ 0. , 2.1611974]])
sample = std_log_normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 0.62767689, 1.27374614],
[ 0.14759544, 0.17818769],
[ 0.5699039 , 0.36318929],
[ 1.36922835, 0.40332037],
[ 0.2435815 , 4.33035173],
[ 0.79789657, 1.06986043],
[ 0.24056903, 0.58019982],
[ 1.11730841, 0.31632232],
[ 1.45600738, 0.54846123],
[ 0.74699727, 0.54787583]])
sd1=.4; sd2=.4; cor=-.5
log_normal_2d = distrs.LogNormalDistr(mean_of_log=[1., 1.3], cov_of_log=stats.make_cov_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(log_normal_2d.mean_of_log, npu.col(1., 1.3))
npt.assert_almost_equal(log_normal_2d.cov_of_log, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(log_normal_2d.vol_of_log, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
npt.assert_almost_equal(log_normal_2d.mean, [[ 2.9446796], [ 3.9749016]])
npt.assert_almost_equal(log_normal_2d.cov, [[ 1.5045366, -0.8999087], [-0.8999087, 2.7414445]])
npt.assert_almost_equal(log_normal_2d.vol, [[ 1.2265956, 0. ], [-0.7336637, 1.484312 ]])
sample = log_normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 1.42711164, 6.95143797],
[ 4.62238496, 2.99848502],
[ 4.32618186, 2.50643161],
[ 4.10913455, 1.42691268],
[ 2.94320341, 4.55346303],
[ 2.50304159, 3.80468825],
[ 2.24476532, 2.45957906],
[ 3.18112082, 2.60781028],
[ 2.01884543, 5.66848303],
[ 5.34174201, 2.12565878]])
log_normal_2d = distrs.LogNormalDistr(mean_of_log=[1., 1.3], vol_of_log=stats.make_vol_2d(sd1=sd1, sd2=sd2, cor=cor))
npt.assert_almost_equal(log_normal_2d.mean_of_log, npu.col(1., 1.3))
npt.assert_almost_equal(log_normal_2d.cov_of_log, [[sd1*sd1, cor*sd1*sd2], [cor*sd1*sd2, sd2*sd2]])
npt.assert_almost_equal(log_normal_2d.vol_of_log, [[sd1, 0.], [cor*sd2, np.sqrt(1.-cor*cor)*sd2]])
npt.assert_almost_equal(log_normal_2d.mean, npu.col(2.9446796, 3.9749016))
npt.assert_almost_equal(log_normal_2d.cov, [[ 1.5045366, -0.8999087], [-0.8999087, 2.7414445]])
npt.assert_almost_equal(log_normal_2d.vol, [[ 1.2265956, 0. ], [-0.7336637, 1.484312 ]])
sample = log_normal_2d.sample(size=10)
self.assertEqual(np.shape(sample), (10, 2))
npt.assert_almost_equal(sample, [
[ 2.71288329, 2.80448293],
[ 2.70285608, 5.57387658],
[ 1.66454464, 4.28346127],
[ 3.23285936, 3.52238521],
[ 1.76160691, 4.67441442],
[ 2.32343609, 2.75776026],
[ 4.8398479 , 2.85230385],
[ 1.67494888, 5.78583855],
[ 2.06409776, 5.58431178],
[ 3.6537541 , 3.15441508]])
def test_empirical_distr(self):
rnd.random_state(np.random.RandomState(seed=42), force=True)
trivial_empirical_1d = distrs.EmpiricalDistr(particles=[[0.]], weights=[1.])
self.assertEqual(trivial_empirical_1d.particle_count, 1)
npt.assert_almost_equal(trivial_empirical_1d.effective_particle_count, 1.)
self.assertEqual(trivial_empirical_1d.dim, 1)
npt.assert_almost_equal(trivial_empirical_1d.particles, np.array([[0.]]))
npt.assert_almost_equal(trivial_empirical_1d.particle(0), np.array([[0.]]))
npt.assert_almost_equal(trivial_empirical_1d.weights, np.array([[1.]]))
npt.assert_almost_equal(trivial_empirical_1d.weight(0), 1.)
npt.assert_almost_equal(trivial_empirical_1d.normalised_weights, np.array([[1.]]))
npt.assert_almost_equal(trivial_empirical_1d.normalised_weight(0), 1.)
self.assertEqual(trivial_empirical_1d.weight_sum, 1.)
self.assertEqual(trivial_empirical_1d.mean, 0.)
self.assertEqual(trivial_empirical_1d.var_n, 0.)
npt.assert_almost_equal(trivial_empirical_1d.var_n_minus_1, np.nan)
self.assertEqual(trivial_empirical_1d.var, 0.)
self.assertEqual(trivial_empirical_1d.cov_n, 0.)
npt.assert_almost_equal(trivial_empirical_1d.cov_n_minus_1, np.nan)
self.assertEqual(trivial_empirical_1d.cov, 0.)
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
trivial_empirical_1d.vol_n
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
trivial_empirical_1d.vol_n_minus_1
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
trivial_empirical_1d.vol
simple_empirical_1d = distrs.EmpiricalDistr(particles=[[-1.], [1.]], weights=[.5, .5])
self.assertEqual(simple_empirical_1d.particle_count, 2)
npt.assert_almost_equal(simple_empirical_1d.effective_particle_count, 2.)
self.assertEqual(simple_empirical_1d.dim, 1)
npt.assert_almost_equal(simple_empirical_1d.particles, np.array([[-1.], [1.]]))
npt.assert_almost_equal(simple_empirical_1d.particle(0), np.array([[-1.]]))
npt.assert_almost_equal(simple_empirical_1d.weights, np.array([[.5], [.5]]))
npt.assert_almost_equal(simple_empirical_1d.weight(0), .5)
npt.assert_almost_equal(simple_empirical_1d.normalised_weights, np.array([[.5], [.5]]))
npt.assert_almost_equal(simple_empirical_1d.normalised_weight(0), .5)
self.assertEqual(simple_empirical_1d.weight_sum, 1.)
self.assertEqual(simple_empirical_1d.mean, 0.)
self.assertEqual(simple_empirical_1d.var_n, 1.)
# "n minus 1" (unbiased) stats don't make sense as we are not using "repeat"-type weights, meaning that each
# weight represents the number of occurrences of one observation:
npt.assert_almost_equal(simple_empirical_1d.var_n_minus_1, np.inf)
self.assertEqual(simple_empirical_1d.cov_n, 1.)
# "n minus 1" (unbiased) stats don't make sense as we are not using "repeat"-type weights, meaning that each
# weight represents the number of occurrences of one observation:
npt.assert_almost_equal(simple_empirical_1d.cov_n_minus_1, np.inf)
self.assertEqual(simple_empirical_1d.cov, 1.)
self.assertEqual(simple_empirical_1d.vol_n, 1.)
# "n minus 1" (unbiased) stats don't make sense as we are not using "repeat"-type weights, meaning that each
# weight represents the number of occurrences of one observation:
self.assertEqual(simple_empirical_1d.vol_n_minus_1, np.inf)
self.assertEqual(simple_empirical_1d.vol, 1.)
# The weights can be specified as a one-dimensional array...
simple_empirical_1d = distrs.EmpiricalDistr(particles=[[-1.], [1.]], weights=[.5, .5])
self.assertEqual(simple_empirical_1d.particle_count, 2)
npt.assert_almost_equal(simple_empirical_1d.effective_particle_count, 2.)
self.assertEqual(simple_empirical_1d.dim, 1)
npt.assert_almost_equal(simple_empirical_1d.particles, np.array([[-1.], [1.]]))
# ...but they come back as a (two-dimensional) column vector:
npt.assert_almost_equal(simple_empirical_1d.weights, np.array([[.5], [.5]]))
# ...alternatively, the weights can be specified as a (two-dimensional) column vector:
simple_empirical_1d = distrs.EmpiricalDistr(particles=[[-1.], [1.]], weights=[[.5], [.5]])
self.assertEqual(simple_empirical_1d.particle_count, 2)
npt.assert_almost_equal(simple_empirical_1d.effective_particle_count, 2.)
self.assertEqual(simple_empirical_1d.dim, 1)
npt.assert_almost_equal(simple_empirical_1d.particles, np.array([[-1.], [1.]]))
# ...they always come back as a (two-dimensional) column vector:
npt.assert_almost_equal(simple_empirical_1d.weights, np.array([[.5], [.5]]))
# If the particles are specified as a one-dimensional array, they are interpreted as...
simple_empirical_1d = distrs.EmpiricalDistr(particles=[-1., 1.], weights=[.5, .5])
self.assertEqual(simple_empirical_1d.particle_count, 2)
npt.assert_almost_equal(simple_empirical_1d.effective_particle_count, 2.)
self.assertEqual(simple_empirical_1d.dim, 1)
# ...multiple one-dimensional particles (each row corresponds to a particle, each column to a dimension):
npt.assert_almost_equal(simple_empirical_1d.particles, np.array([[-1.], [1.]]))
npt.assert_almost_equal(simple_empirical_1d.weights, np.array([[.5], [.5]]))
# Now we shall be using "repeat"-type weights:
repeat_empirical_1d = distrs.EmpiricalDistr(particles=[[-1.], [1.]], weights=[2., 1.])
self.assertEqual(repeat_empirical_1d.particle_count, 2)
npt.assert_almost_equal(repeat_empirical_1d.effective_particle_count, 1.7999999999999998)
self.assertEqual(repeat_empirical_1d.dim, 1)
npt.assert_almost_equal(repeat_empirical_1d.particles, np.array([[-1.], [1.]]))
npt.assert_almost_equal(repeat_empirical_1d.particle(0), np.array([[-1.]]))
npt.assert_almost_equal(repeat_empirical_1d.weights, np.array([[2.], [1.]]))
npt.assert_almost_equal(repeat_empirical_1d.weight(0), 2.)
npt.assert_almost_equal(repeat_empirical_1d.normalised_weights, np.array([[ 0.6666667], [ 0.3333333]]))
npt.assert_almost_equal(repeat_empirical_1d.normalised_weight(0), 0.6666667)
self.assertEqual(repeat_empirical_1d.weight_sum, 3.)
npt.assert_almost_equal(repeat_empirical_1d.mean, -0.33333333)
npt.assert_almost_equal(repeat_empirical_1d.var_n, 0.88888889)
npt.assert_almost_equal(repeat_empirical_1d.var_n_minus_1, 1.3333333)
npt.assert_almost_equal(repeat_empirical_1d.cov_n, 0.88888889)
npt.assert_almost_equal(repeat_empirical_1d.cov_n_minus_1, 1.3333333)
npt.assert_almost_equal(repeat_empirical_1d.cov, 0.88888889)
npt.assert_almost_equal(repeat_empirical_1d.vol_n, 0.94280904)
npt.assert_almost_equal(repeat_empirical_1d.vol_n_minus_1, 1.15470054)
npt.assert_almost_equal(repeat_empirical_1d.vol, 0.94280904)
# Now we shall be using "repeat"-type weights. There are three two-dimensional particles:
repeat_empirical_2d = distrs.EmpiricalDistr(particles=[[-2., 2.], [0., 0.], [1., -1.]], weights=[2., 1., 1.])
self.assertEqual(repeat_empirical_2d.particle_count, 3)
npt.assert_almost_equal(repeat_empirical_2d.effective_particle_count, 2.6666666666666665)
self.assertEqual(repeat_empirical_2d.dim, 2)
npt.assert_almost_equal(repeat_empirical_2d.particles, np.array([[-2., 2.], [0., 0.], [1., -1.]]))
npt.assert_almost_equal(repeat_empirical_2d.particle(0), np.array([[-2.], [2.]]))
npt.assert_almost_equal(repeat_empirical_2d.weights, np.array([[2.], [1.], [1.]]))
npt.assert_almost_equal(repeat_empirical_2d.weight(0), 2.)
npt.assert_almost_equal(repeat_empirical_2d.normalised_weights, np.array([[ 0.5 ], [ 0.25], [ 0.25]]))
npt.assert_almost_equal(repeat_empirical_2d.normalised_weight(0), .5)
self.assertEqual(repeat_empirical_2d.weight_sum, 4.)
npt.assert_almost_equal(repeat_empirical_2d.mean, [[-0.75], [ 0.75]])
npt.assert_almost_equal(repeat_empirical_2d.var_n, [[ 1.6875], [ 1.6875]])
npt.assert_almost_equal(repeat_empirical_2d.var_n_minus_1, [[ 2.25], [ 2.25]])
npt.assert_almost_equal(repeat_empirical_2d.cov_n, [[ 1.6875, -1.6875], [-1.6875, 1.6875]])
npt.assert_almost_equal(repeat_empirical_2d.cov_n_minus_1, [[ 2.25, -2.25], [-2.25, 2.25]])
npt.assert_almost_equal(repeat_empirical_2d.cov, [[ 1.6875, -1.6875], [-1.6875, 1.6875]])
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
repeat_empirical_2d.vol_n
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
repeat_empirical_2d.vol_n_minus_1
with self.assertRaises(np.linalg.LinAlgError): # Matrix is not positive definite
repeat_empirical_2d.vol
normal_distr = distrs.NormalDistr(mean=[10., 100.], cov=[[4., -3.], [-3., 9.]])
particles = normal_distr.sample(size=100)
approx_normal_empirical_2d = distrs.EmpiricalDistr(particles=particles, weights=np.ones((100,)))
self.assertEqual(approx_normal_empirical_2d.particle_count, 100)
npt.assert_almost_equal(approx_normal_empirical_2d.effective_particle_count, 100.)
self.assertEqual(approx_normal_empirical_2d.dim, 2)
npt.assert_almost_equal(approx_normal_empirical_2d.particles, particles)
npt.assert_almost_equal(approx_normal_empirical_2d.particle(0), npu.col(*particles[0]))
npt.assert_almost_equal(approx_normal_empirical_2d.weights, npu.col(*np.ones((100,))))
npt.assert_almost_equal(approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((100,))) / 100.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weight(0), .01)
self.assertEqual(approx_normal_empirical_2d.weight_sum, 100.)
npt.assert_almost_equal(approx_normal_empirical_2d.mean, [[ 10.2077457], [ 99.6856645]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n, [[ 3.3516275], [ 6.7649298]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n_minus_1, [[ 3.3854823], [ 6.8332624]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n, [[ 3.3516275, -1.8258307], [-1.8258307, 6.7649298]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n_minus_1, [[ 3.3854823, -1.8442735], [-1.8442735, 6.8332624]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov, [[ 3.3516275, -1.8258307], [-1.8258307, 6.7649298]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n, [[ 1.8307451, 0. ], [-0.9973157, 2.4021431]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n_minus_1, [[ 1.839968 , 0. ], [-1.00234 , 2.4142446]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol, [[ 1.8307451, 0. ], [-0.9973157, 2.4021431]])
# Using more particles more faithfully approximates the mean and covariance of the normal distribution:
normal_distr = distrs.NormalDistr(mean=[10., 100.], cov=[[4., -3.], [-3., 9.]])
particles = normal_distr.sample(size=100000)
approx_normal_empirical_2d = distrs.EmpiricalDistr(particles=particles, weights=np.ones((100000,)))
self.assertEqual(approx_normal_empirical_2d.particle_count, 100000)
npt.assert_almost_equal(approx_normal_empirical_2d.effective_particle_count, 100000.)
self.assertEqual(approx_normal_empirical_2d.dim, 2)
npt.assert_almost_equal(approx_normal_empirical_2d.particles, particles)
npt.assert_almost_equal(approx_normal_empirical_2d.particle(0), npu.col(*particles[0]))
npt.assert_almost_equal(approx_normal_empirical_2d.weights, npu.col(*np.ones((100000,))))
npt.assert_almost_equal(approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((100000,))) / 100000.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weight(0), .00001)
self.assertEqual(approx_normal_empirical_2d.weight_sum, 100000.)
npt.assert_almost_equal(approx_normal_empirical_2d.mean, [[ 9.9863195], [ 100.0145412]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n, [[ 3.9901799], [ 9.0390325]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n_minus_1, [[ 3.9902198], [ 9.0391229]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n, [[ 3.9901799, -3.0120428], [-3.0120428, 9.0390325]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n_minus_1, [[ 3.9902198, -3.0120729], [-3.0120729, 9.0391229]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov, [[ 3.9901799, -3.0120428], [-3.0120428, 9.0390325]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n, [[ 1.9975435, 0. ], [-1.5078735, 2.6010287]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n_minus_1, [[ 1.9975535, 0. ], [-1.507881 , 2.6010417]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol, [[ 1.9975435, 0. ], [-1.5078735, 2.6010287]])
def test_multinomial_resample(self):
rnd.random_state(np.random.RandomState(seed=42), force=True)
normal_distr = distrs.NormalDistr(mean=[10., 100.], cov=[[4., -3.], [-3., 9.]])
particles = normal_distr.sample(size=100000)
approx_normal_empirical_2d = distrs.EmpiricalDistr(particles=particles, weights=np.ones((100000,)))
self.assertEqual(approx_normal_empirical_2d.particle_count, 100000)
npt.assert_almost_equal(approx_normal_empirical_2d.effective_particle_count, 100000.)
self.assertEqual(approx_normal_empirical_2d.dim, 2)
npt.assert_almost_equal(approx_normal_empirical_2d.particles, particles)
npt.assert_almost_equal(approx_normal_empirical_2d.particle(0), npu.col(*particles[0]))
npt.assert_almost_equal(approx_normal_empirical_2d.weights, npu.col(*np.ones((100000,))))
npt.assert_almost_equal(approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((100000,))) / 100000.)
npt.assert_almost_equal(approx_normal_empirical_2d.normalised_weight(0), .00001)
self.assertEqual(approx_normal_empirical_2d.weight_sum, 100000.)
npt.assert_almost_equal(approx_normal_empirical_2d.mean, [[ 9.9866994], [ 100.0141095]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n, [[ 3.9902435], [ 9.0362717]])
npt.assert_almost_equal(approx_normal_empirical_2d.var_n_minus_1, [[ 3.9902834], [ 9.036362 ]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov_n_minus_1, [[ 3.9902834, -3.0112521], [-3.0112521, 9.036362 ]])
npt.assert_almost_equal(approx_normal_empirical_2d.cov, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol_n_minus_1, [[ 1.9975694, 0. ], [-1.5074581, 2.6007561]])
npt.assert_almost_equal(approx_normal_empirical_2d.vol, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]])
rnd.random_state(np.random.RandomState(seed=43), force=True)
resampled_approx_normal_empirical_2d = distrs.multinomial_resample(approx_normal_empirical_2d)
self.assertEqual(resampled_approx_normal_empirical_2d.particle_count, 100000)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.effective_particle_count, 100000.)
self.assertEqual(resampled_approx_normal_empirical_2d.dim, 2)
# The resampled particles should ("almost certainly") be different from the original ones:
self.assertFalse(np.sum(resampled_approx_normal_empirical_2d.particles) == np.sum(particles))
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.particle(0), npu.col(*particles[1]))
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.weights, npu.col(*np.ones((100000,))))
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((100000,))) / 100000.)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.normalised_weight(0), .00001)
self.assertEqual(resampled_approx_normal_empirical_2d.weight_sum, 100000.)
# But the stats should be pretty close to those of the original empirical distribution, though not to seven
# decimal places:
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.mean, [[ 9.9866994], [ 100.0141095]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.var_n, [[ 3.9902435], [ 9.0362717]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.var_n_minus_1, [[ 3.9902834], [ 9.036362 ]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.cov_n, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.cov_n_minus_1, [[ 3.9902834, -3.0112521], [-3.0112521, 9.036362 ]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.cov, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.vol_n, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.vol_n_minus_1, [[ 1.9975694, 0. ], [-1.5074581, 2.6007561]], decimal=1)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d.vol, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
rnd.random_state(np.random.RandomState(seed=43), force=True)
resampled_approx_normal_empirical_2d_particles = approx_normal_empirical_2d.sample(size=100000)
npt.assert_almost_equal(resampled_approx_normal_empirical_2d_particles, resampled_approx_normal_empirical_2d.particles)
subsampled_approx_normal_empirical_2d = distrs.multinomial_resample(approx_normal_empirical_2d, target_particle_count=40000)
self.assertEqual(subsampled_approx_normal_empirical_2d.particle_count, 40000)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.effective_particle_count, 40000.)
self.assertEqual(subsampled_approx_normal_empirical_2d.dim, 2)
# The resampled particles should ("almost certainly") be different from the original ones:
self.assertFalse(np.sum(subsampled_approx_normal_empirical_2d.particles) == np.sum(particles))
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.particle(0), npu.col(*particles[1]))
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.weights, npu.col(*np.ones((40000,))))
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((40000,))) / 40000.)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.normalised_weight(0), .000025)
self.assertEqual(subsampled_approx_normal_empirical_2d.weight_sum, 40000.)
# But the stats should be pretty close to those of the original empirical distribution, though not to seven
# decimal places:
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.mean, [[ 9.9866994], [ 100.0141095]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.var_n, [[ 3.9902435], [ 9.0362717]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.var_n_minus_1, [[ 3.9902834], [ 9.036362 ]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.cov_n, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.cov_n_minus_1, [[ 3.9902834, -3.0112521], [-3.0112521, 9.036362 ]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.cov, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.vol_n, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.vol_n_minus_1, [[ 1.9975694, 0. ], [-1.5074581, 2.6007561]], decimal=1)
npt.assert_almost_equal(subsampled_approx_normal_empirical_2d.vol, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
supersampled_approx_normal_empirical_2d = distrs.multinomial_resample(approx_normal_empirical_2d, target_particle_count=300000)
self.assertEqual(supersampled_approx_normal_empirical_2d.particle_count, 300000)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.effective_particle_count, 300000.)
self.assertEqual(supersampled_approx_normal_empirical_2d.dim, 2)
# The resampled particles should ("almost certainly") be different from the original ones:
self.assertFalse(np.sum(supersampled_approx_normal_empirical_2d.particles) == np.sum(particles))
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.particle(0), npu.col(*particles[0]))
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.weights, npu.col(*np.ones((300000,))))
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.weight(0), 1.)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.normalised_weights, npu.col(*np.ones((300000,))) / 300000.)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.normalised_weight(0), 3.3333333333333333e-06)
self.assertEqual(supersampled_approx_normal_empirical_2d.weight_sum, 300000.)
# But the stats should be pretty close to those of the original empirical distribution, though not to seven
# decimal places:
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.mean, [[ 9.9866994], [ 100.0141095]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.var_n, [[ 3.9902435], [ 9.0362717]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.var_n_minus_1, [[ 3.9902834], [ 9.036362 ]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.cov_n, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.cov_n_minus_1, [[ 3.9902834, -3.0112521], [-3.0112521, 9.036362 ]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.cov, [[ 3.9902435, -3.011222 ], [-3.011222 , 9.0362717]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.vol_n, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.vol_n_minus_1, [[ 1.9975694, 0. ], [-1.5074581, 2.6007561]], decimal=1)
npt.assert_almost_equal(supersampled_approx_normal_empirical_2d.vol, [[ 1.9975594, 0. ], [-1.5074505, 2.6007431]], decimal=1)
if __name__ == '__main__':
unittest.main()
| 65.054007
| 152
| 0.654562
| 4,935
| 37,341
| 4.642756
| 0.078622
| 0.084454
| 0.140756
| 0.187675
| 0.887221
| 0.861208
| 0.834323
| 0.793733
| 0.744413
| 0.689988
| 0
| 0.141964
| 0.216197
| 37,341
| 573
| 153
| 65.167539
| 0.640871
| 0.054337
| 0
| 0.308163
| 0
| 0
| 0.00023
| 0
| 0
| 0
| 0
| 0
| 0.591837
| 1
| 0.012245
| false
| 0
| 0.014286
| 0
| 0.028571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
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| 0
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| 0
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|
0
| 8
|
e455dd81cff2752c7630005b8aa15c51052f74d5
| 55,326
|
py
|
Python
|
SBaaS_quantification/stage01_quantification_replicatesMI_query.py
|
dmccloskey/SBaaS_quantification
|
b2a9c7a9a0d318f22ff20e311f94c213852ba914
|
[
"MIT"
] | null | null | null |
SBaaS_quantification/stage01_quantification_replicatesMI_query.py
|
dmccloskey/SBaaS_quantification
|
b2a9c7a9a0d318f22ff20e311f94c213852ba914
|
[
"MIT"
] | null | null | null |
SBaaS_quantification/stage01_quantification_replicatesMI_query.py
|
dmccloskey/SBaaS_quantification
|
b2a9c7a9a0d318f22ff20e311f94c213852ba914
|
[
"MIT"
] | null | null | null |
#lims
from SBaaS_LIMS.lims_experiment_postgresql_models import *
from SBaaS_LIMS.lims_sample_postgresql_models import *
from .stage01_quantification_replicatesMI_postgresql_models import *
from SBaaS_base.sbaas_base_query_update import sbaas_base_query_update
from SBaaS_base.sbaas_base_query_drop import sbaas_base_query_drop
from SBaaS_base.sbaas_base_query_initialize import sbaas_base_query_initialize
from SBaaS_base.sbaas_base_query_insert import sbaas_base_query_insert
from SBaaS_base.sbaas_base_query_select import sbaas_base_query_select
from SBaaS_base.sbaas_base_query_delete import sbaas_base_query_delete
from SBaaS_base.sbaas_template_query import sbaas_template_query
from listDict.listDict import listDict
class stage01_quantification_replicatesMI_query(sbaas_template_query):
def initialize_supportedTables(self):
'''Set the supported tables dict for
'''
tables_supported = {'data_stage01_quantification_replicatesmi':data_stage01_quantification_replicatesMI,
};
self.set_supportedTables(tables_supported);
# Query sample names from data_stage01_quantification_replicatesMI:
def get_sampleNameShort_experimentIDAndSampleNameAbbreviationAndComponentNameAndTimePoint_dataStage01ReplicatesMI(self,experiment_id_I,sample_name_abbreviation_I,component_name_I,time_point_I,exp_type_I=4):
'''Query sample names that are used from the experiment by sample name abbreviation and sample description'''
try:
sample_names = self.session.query(data_stage01_quantification_replicatesMI.sample_name_short).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
sample_description.time_point.like(time_point_I),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.sample_name_short).order_by(
data_stage01_quantification_replicatesMI.sample_name_short.asc()).all();
sample_names_short_O = [];
for sn in sample_names: sample_names_short_O.append(sn.sample_name_short);
return sample_names_short_O;
except SQLAlchemyError as e:
print(e);
def get_sampleNameShort_experimentIDAndSampleNameAbbreviationAndComponentNameAndTimePointAndCalculatedConcentrationUnits_dataStage01ReplicatesMI(
self,experiment_id_I,sample_name_abbreviation_I,component_name_I,time_point_I,calculated_concentration_units_I,exp_type_I=4):
'''Query sample names that are used from the experiment by sample name abbreviation and sample description'''
try:
sample_names = self.session.query(data_stage01_quantification_replicatesMI.sample_name_short).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
sample_description.time_point.like(time_point_I),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(calculated_concentration_units_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.sample_name_short).order_by(
data_stage01_quantification_replicatesMI.sample_name_short.asc()).all();
sample_names_short_O = [];
for sn in sample_names: sample_names_short_O.append(sn.sample_name_short);
return sample_names_short_O;
except SQLAlchemyError as e:
print(e);
def get_SampleNameShort_experimentID_dataStage01ReplicatesMI(self,experiment_id_I):
'''Query sample names short that are used from the experiment'''
try:
sample_names = self.session.query(data_stage01_quantification_replicatesMI.sample_name_short).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.sample_name_short).order_by(
data_stage01_quantification_replicatesMI.sample_name_short.asc()).all();
sample_names_O = [];
for sn in sample_names: sample_names_O.append(sn.sample_name_short);
return sample_names_O;
except SQLAlchemyError as e:
print(e);
def get_sampleNameAbbreviations_experimentID_dataStage01ReplicatesMI(self,experiment_id_I,exp_type_I=4):
'''Query sample names (i.e. unknowns) that are used from
the experiment'''
try:
sample_names = self.session.query(sample_description.sample_name_abbreviation).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
sample_description.sample_name_abbreviation).order_by(
sample_description.sample_name_abbreviation.asc()).all();
sample_names_O = [];
for sn in sample_names: sample_names_O.append(sn.sample_name_abbreviation);
return sample_names_O;
except SQLAlchemyError as e:
print(e);
def get_sampleNameAbbreviations_experimentIDAndTimePointAndComponentName_dataStage01ReplicatesMI(self,experiment_id_I,time_point_I,component_name_I,exp_type_I=4):
'''Query sample names (i.e. unknowns) that are used from
the experiment'''
try:
sample_names = self.session.query(sample_description.sample_name_abbreviation).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
sample_description.sample_name_abbreviation).order_by(
sample_description.sample_name_abbreviation.asc()).all();
sample_names_O = [];
for sn in sample_names: sample_names_O.append(sn.sample_name_abbreviation);
return sample_names_O;
except SQLAlchemyError as e:
print(e);
# Query component names from data_stage01_quantification_replicatesMI:
def get_componentNames_experimentID_dataStage01ReplicatesMI(self,experiment_id_I):
'''Query component Names that are used from the experiment'''
try:
component_names = self.session.query(data_stage01_quantification_replicatesMI.component_name).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.component_name).order_by(
data_stage01_quantification_replicatesMI.component_name.asc()).all();
component_names_O = [];
for cn in component_names: component_names_O.append(cn.component_name);
return component_names_O;
except SQLAlchemyError as e:
print(e);
def get_componentNames_experimentIDAndSampleNameAbbreviation_dataStage01ReplicatesMI(self,experiment_id_I,sample_name_abbreviation_I,exp_type_I=4):
'''Query component names that are used and not internal standards from
the experiment and sample abbreviation'''
try:
component_names = self.session.query(data_stage01_quantification_replicatesMI.component_name).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.component_name).order_by(
data_stage01_quantification_replicatesMI.component_name.asc()).all();
component_names_O = [];
for cn in component_names: component_names_O.append(cn.component_name);
return component_names_O;
except SQLAlchemyError as e:
print(e);
def get_componentNames_experimentIDAndTimePoint_dataStage01ReplicatesMI(self,experiment_id_I,time_point_I):
'''Query component names that are used and not internal standards from
the experiment and time point'''
try:
component_names = self.session.query(data_stage01_quantification_replicatesMI.component_name).filter(
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.component_name).order_by(
data_stage01_quantification_replicatesMI.component_name.asc()).all();
component_names_O = [];
for cn in component_names: component_names_O.append(cn.component_name);
return component_names_O;
except SQLAlchemyError as e:
print(e);
# Query time points from data_stage01_quantification_replicatesMI
def get_timePoint_experimentID_dataStage01ReplicatesMI(self,experiment_id_I):
'''Query time points that are used from the experiment'''
try:
time_points = self.session.query(data_stage01_quantification_replicatesMI.time_point).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.time_point).order_by(
data_stage01_quantification_replicatesMI.time_point.asc()).all();
time_points_O = [];
for tp in time_points: time_points_O.append(tp.time_point);
return time_points_O;
except SQLAlchemyError as e:
print(e);
def get_timePoint_experimentIDAndSampleNameShort_dataStage01ReplicatesMI(self,experiment_id_I,sample_name_short_I):
'''Query time points that are used from the experiment'''
try:
time_points = self.session.query(data_stage01_quantification_replicatesMI.time_point).filter(
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.time_point).order_by(
data_stage01_quantification_replicatesMI.time_point.asc()).all();
time_points_O = [];
for tp in time_points: time_points_O.append(tp.time_point);
return time_points_O;
except SQLAlchemyError as e:
print(e);
def get_timePoint_experimentIDAndSampleNameAbbreviation_dataStage01ReplicatesMI(self,experiment_id_I,sample_name_abbreviation_I,exp_type_I=4):
'''Query time points that are used from the experiment'''
try:
time_points = self.session.query(data_stage01_quantification_replicatesMI.time_point).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
sample_description.sample_name_short.like(data_stage01_quantification_replicatesMI.sample_name_short),
sample_description.time_point.like(data_stage01_quantification_replicatesMI.time_point),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.time_point).order_by(
data_stage01_quantification_replicatesMI.time_point.asc()).all();
time_points_O = [];
for tp in time_points: time_points_O.append(tp.time_point);
return time_points_O;
except SQLAlchemyError as e:
print(e);
def get_timePoint_experimentIDAndComponentName_dataStage01ReplicatesMI(self,experiment_id_I,component_name_I):
'''Query time points that are used from the experiment'''
try:
time_points = self.session.query(data_stage01_quantification_replicatesMI.time_point).filter(
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.time_point).order_by(
data_stage01_quantification_replicatesMI.time_point.asc()).all();
time_points_O = [];
for tp in time_points: time_points_O.append(tp.time_point);
return time_points_O;
except SQLAlchemyError as e:
print(e);
# query concentration units:
def get_calculatedConcentrationUnits_experimentID_dataStage01ReplicatesMI(self,experiment_id_I):
'''Query calculated_concentration_units that are used from the experiment'''
try:
calculated_concentration_units = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True),).group_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units).order_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units.asc()).all();
calculated_concentration_units_O = [];
for tp in calculated_concentration_units: calculated_concentration_units_O.append(tp.calculated_concentration_units);
return calculated_concentration_units_O;
except SQLAlchemyError as e:
print(e);
# query rows data_stage01_quantification_replicates
def get_rows_experimentIDAndSampleNameShortAndTimePointAndCalculatedConcentrationUnits_dataStage01ReplicatesMI(self,
experiment_id_I, sample_name_short_I, time_point_I,calculated_concentration_units_I):
"""query rows"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(calculated_concentration_units_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
data_O = [];
for d in data:
data_O.append(d.__repr__dict__());
return data_O;
except SQLAlchemyError as e:
print(e);
# Query data from data_stage01_quantification_replicatesMI:
def get_data_experimentID_dataStage01ReplicatesMI(self, experiment_id_I):
"""get data from experiment ID"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.component_group_name).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
data_O = [];
for d in data:
data_1 = {};
data_1['sample_name_short'] = d.sample_name_short;
data_1['component_group_name'] = d.component_group_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_O.append(data_1);
return data_O;
except SQLAlchemyError as e:
print(e);
def get_calculatedConcentrations_experimentIDAndSampleNameAbbreviationAndTimePointAndComponentName_dataStage01ReplicatesMI(self, experiment_id_I, sample_name_abbreviation_I, time_point_I, component_name_I,exp_type_I=4):
"""Query calculatedConcentrations"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
sample_description.time_point.like(time_point_I),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.calculated_concentration).all();
ratios_O = [];
for d in data:
ratios_O.append(d[0]);
return ratios_O;
except SQLAlchemyError as e:
print(e);
def get_calculatedConcentration_experimentIDAndSampleNameShortAndTimePointAndComponentName_dataStage01ReplicatesMI(self, experiment_id_I, sample_name_short_I, time_point_I, component_name_I):
"""Query calculated concentrations"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
if len(data)>1:
print('more than 1 calculated_concentration retrieved per component_name')
if data:
calc_conc_O = data[0].calculated_concentration;
else:
calc_conc_O = None;
return calc_conc_O;
except SQLAlchemyError as e:
print(e);
def get_calculatedConcentration_experimentIDAndSampleNameShortAndTimePointAndComponentNameAndCalculatedConcentrationUnits_dataStage01ReplicatesMI(
self, experiment_id_I, sample_name_short_I, time_point_I, component_name_I, calculated_concentration_units_I):
"""Query calculated concentrations"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(calculated_concentration_units_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
if len(data)>1:
print('more than 1 calculated_concentration retrieved per component_name')
if data:
calc_conc_O = data[0].calculated_concentration;
else:
calc_conc_O = None;
return calc_conc_O;
except SQLAlchemyError as e:
print(e);
def get_concAndConcUnits_experimentIDAndSampleNameShortAndTimePointAndComponentName_dataStage01ReplicatesMI(self, experiment_id_I, sample_name_short_I, time_point_I, component_name_I):
"""Query calculated concentrations"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
if len(data)>1:
print('more than 1 calculated_concentration retrieved per component_name')
if data:
conc_O = data[0][0];
conc_units_O = data[0][1];
else:
conc_O = None;
conc_units_O = None;
return conc_O, conc_units_O;
except SQLAlchemyError as e:
print(e);
def get_concAndConcUnits_experimentIDAndSampleNameShortAndTimePointAndComponentGroupName_dataStage01ReplicatesMI(self, experiment_id_I, sample_name_short_I, time_point_I, component_group_name_I):
"""Query calculated concentrations"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_group_name.like(component_group_name_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).all();
if len(data)>1:
print('more than 1 calculated_concentration retrieved per component_name')
if data:
conc_O = data[0][0];
conc_units_O = data[0][1];
else:
conc_O = None;
conc_units_O = None;
return conc_O, conc_units_O;
except SQLAlchemyError as e:
print(e);
def get_sampleNameShort_experimentIDAndSampleNameAbbreviationAndTimePoint_dataStage01ReplicatesMI(self,experiment_id_I,sample_name_abbreviation_I,time_point_I,exp_type_I=4):
'''Query sample names that are used from the experiment by sample name abbreviation and sample description'''
#Not tested
try:
sample_names = self.session.query(data_stage01_quantification_replicatesMI.sample_name_short).filter(
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
sample_description.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.sample_name_short).order_by(
data_stage01_quantification_replicatesMI.sample_name_short.asc()).all();
sample_names_short_O = [];
for sn in sample_names: sample_names_short_O.append(sn.sample_name_short);
return sample_names_short_O;
except SQLAlchemyError as e:
print(e);
def get_data_experimentIDAndTimePointAndSampleNameShortAndUnits_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,sample_name_short_I,concentration_units_I,exp_type_I=4):
"""get data from experiment ID"""
#Tested
try:
data = self.session.query(data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(concentration_units_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).all();
data_O = [];
for d in data:
data_1 = {};
data_1['experiment_id'] = d.experiment_id;
data_1['sample_name_abbreviation'] = d.sample_name_abbreviation;
data_1['sample_replicate'] = d.sample_replicate;
data_1['sample_name_short'] = d.sample_name_short;
data_1['time_point'] = d.time_point;
data_1['component_group_name'] = d.component_group_name;
data_1['component_name'] = d.component_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_1['calculated_concentration_units'] = d.calculated_concentration_units;
data_O.append(data_1);
return data_O;
except SQLAlchemyError as e:
print(e);
def get_data_experimentIDAndTimePointAndUnits_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,concentration_units_I,exp_type_I=4):
"""get data from experiment ID"""
#Tested
try:
data = self.session.query(data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(concentration_units_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).all();
data_O = [];
for d in data:
data_1 = {};
data_1['experiment_id'] = d.experiment_id;
data_1['sample_name_abbreviation'] = d.sample_name_abbreviation;
data_1['sample_replicate'] = d.sample_replicate;
data_1['sample_name_short'] = d.sample_name_short;
data_1['time_point'] = d.time_point;
data_1['component_group_name'] = d.component_group_name;
data_1['component_name'] = d.component_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_1['calculated_concentration_units'] = d.calculated_concentration_units;
data_O.append(data_1);
return data_O;
except SQLAlchemyError as e:
print(e);
def get_RExpressionData_experimentIDAndTimePointAndUnits_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,concentration_units_I,exp_type_I=4):
"""get data from experiment ID"""
#Tested
try:
data = self.session.query(data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(concentration_units_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).all();
data_O = [];
for d in data:
data_1 = {};
data_1['experiment_id'] = d.experiment_id;
data_1['sample_name_abbreviation'] = d.sample_name_abbreviation;
data_1['sample_replicate'] = d.sample_replicate;
data_1['sample_name_short'] = d.sample_name_short;
data_1['time_point'] = d.time_point;
data_1['component_group_name'] = d.component_group_name;
data_1['component_name'] = d.component_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_1['calculated_concentration_units'] = d.calculated_concentration_units;
data_O.append(data_1);
return data_O;
except SQLAlchemyError as e:
print(e);
def get_RExpressionData_experimentIDAndTimePointAndUnitsAndSampleNameShort_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,concentration_units_I,sample_name_short_I,exp_type_I=4):
"""get data from experiment ID"""
#Tested
try:
data = self.session.query(data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(concentration_units_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).all();
data_O = [];
for d in data:
data_1 = {};
data_1['experiment_id'] = d.experiment_id;
data_1['sample_name_abbreviation'] = d.sample_name_abbreviation;
data_1['sample_replicate'] = d.sample_replicate;
data_1['sample_name_short'] = d.sample_name_short;
data_1['time_point'] = d.time_point;
data_1['component_group_name'] = d.component_group_name;
data_1['component_name'] = d.component_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_1['calculated_concentration_units'] = d.calculated_concentration_units;
data_O.append(data_1);
return data_O;
except SQLAlchemyError as e:
print(e);
def get_RDataList_experimentIDAndTimePointAndUnitsAndComponentNamesAndSampleNameAbbreviation_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,concentration_units_I,component_name_I,sample_name_abbreviation_I,exp_type_I=4):
"""get data from experiment ID"""
#Tested
try:
data = self.session.query(data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.component_name.like(component_name_I),
sample_description.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage01_quantification_replicatesMI.calculated_concentration_units.like(concentration_units_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
sample_description.sample_id.like(sample.sample_id),
sample.sample_name.like(experiment.sample_name),
experiment.id.like(experiment_id_I),
experiment.exp_type_id == exp_type_I,
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.experiment_id,
sample_description.sample_name_abbreviation,
sample_description.sample_replicate,
data_stage01_quantification_replicatesMI.sample_name_short,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.calculated_concentration,
data_stage01_quantification_replicatesMI.calculated_concentration_units).all();
data_O = [];
concentrations_O = [];
for d in data:
concentrations_O.append(d.calculated_concentration);
data_1 = {};
data_1['experiment_id'] = d.experiment_id;
data_1['sample_name_abbreviation'] = d.sample_name_abbreviation;
data_1['sample_replicate'] = d.sample_replicate;
data_1['sample_name_short'] = d.sample_name_short;
data_1['time_point'] = d.time_point;
data_1['component_group_name'] = d.component_group_name;
data_1['component_name'] = d.component_name;
data_1['calculated_concentration'] = d.calculated_concentration;
data_1['calculated_concentration_units'] = d.calculated_concentration_units;
data_O.append(data_1);
return data_O,concentrations_O;
except SQLAlchemyError as e:
print(e);
# Query concentration_units from data_stage01_quantification_replicatesMI:
def get_concentrationUnits_experimentIDAndTimePoint_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I):
"""get concentration_units from experiment ID and time point"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units).order_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units.asc()).all();
units_O = [];
for d in data:
units_O.append(d[0]);
return units_O;
except SQLAlchemyError as e:
print(e);
def get_concentrationUnits_experimentIDAndTimePointAndSampleNameShort_dataStage01ReplicatesMI(self, experiment_id_I,time_point_I,sample_name_short_I):
"""get concentration_units from experiment ID and time point"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.time_point.like(time_point_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_name_short_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units).order_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units.asc()).all();
units_O = [];
for d in data:
units_O.append(d[0]);
return units_O;
except SQLAlchemyError as e:
print(e);
def get_concentrationUnits_experimentID_dataStage01ReplicatesMI(self, experiment_id_I):
"""get concentration_units from experiment ID"""
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration_units).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.used_.is_(True)).group_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units).order_by(
data_stage01_quantification_replicatesMI.calculated_concentration_units.asc()).all();
units_O = [];
for d in data:
units_O.append(d[0]);
return units_O;
except SQLAlchemyError as e:
print(e);
def reset_dataStage01_quantification_replicatesMI(self,experiment_id_I):
try:
if experiment_id_I:
reset = self.session.query(data_stage01_quantification_replicatesMI).filter(data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
def drop_dataStage01_quantification_replicatesMI(self):
try:
data_stage01_quantification_replicatesMI.__table__.drop(self.engine,True);
except SQLAlchemyError as e:
print(e);
def initialize_dataStage01_quantification_replicatesMI(self):
try:
data_stage01_quantification_replicatesMI.__table__.create(self.engine,True);
except SQLAlchemyError as e:
print(e);
#Query unique rows from data_stage01_quantification_replicatesMI
def get_sampleNameAbbreviationsAndCalculatedConcentrationUnitsAndTimePointsAndComponentNames_experimentID_dataStage01QuantificationReplicatesMI(
self,experiment_id_I,sample_name_abbreviations_I,time_points_I,calculated_concentration_units_I,exp_type_I=4):
'''unique calculated_concentration_units/sample_name_abbreviations/component_names/component_group_names/time_points
that are used by the experiment_id'''
try:
data = self.session.query(data_stage01_quantification_replicatesMI.calculated_concentration_units,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_name,
sample_description.sample_name_abbreviation
).filter(
data_stage01_quantification_replicatesMI.experiment_id.like(experiment_id_I),
data_stage01_quantification_replicatesMI.sample_name_short.like(sample_description.sample_name_short),
data_stage01_quantification_replicatesMI.used_.is_(True),
sample_description.time_point.like(data_stage01_quantification_replicatesMI.time_point),
experiment.exp_type_id == exp_type_I,
experiment.id.like(experiment_id_I),
experiment.sample_name.like(sample.sample_name),
sample.sample_id.like(sample_description.sample_id)
).group_by(data_stage01_quantification_replicatesMI.calculated_concentration_units,
data_stage01_quantification_replicatesMI.component_name,
data_stage01_quantification_replicatesMI.component_group_name,
data_stage01_quantification_replicatesMI.time_point,
data_stage01_quantification_replicatesMI.component_name,
sample_description.sample_name_abbreviation
).order_by(data_stage01_quantification_replicatesMI.calculated_concentration_units.asc(),
data_stage01_quantification_replicatesMI.component_name.asc(),
data_stage01_quantification_replicatesMI.component_group_name.asc(),
data_stage01_quantification_replicatesMI.time_point.asc(),
data_stage01_quantification_replicatesMI.component_name.asc(),
sample_description.sample_name_abbreviation.asc()
).all();
data_O=[];
if data:
data_O = listDict(record_I=data);
data_O.convert_record2DataFrame();
data_O.filterIn_byDictList({
'sample_name_abbreviation':sample_name_abbreviations_I,
'time_point':time_points_I,
'calculated_concentration_units':calculated_concentration_units_I,
});
data_O.convert_dataFrame2ListDict();
return data_O.get_listDict();
except SQLAlchemyError as e:
print(e);
def get_rows_experimentIDsAndSampleNames_dataStage01QuantificationReplicatesMI(
self,
experiment_ids_I = [],
sample_name_shorts_I=[],
component_names_I=[],
component_group_names_I=[],
calculated_concentration_units_I=[],
used__I=True):
'''Query rows from data_stage01_quantification_replicatesmi
INPUT:
experiment_id_I = string
sample_names_I = string list of names
used__I = boolean
OUTPUT:
[{}]
'''
from SBaaS_base.postgresql_orm import execute_query
try:
cmd = '''SELECT experiment_id,
sample_name_short,
time_point,
component_group_name, component_name,
imputation_method,
imputation_options,
calculated_concentration,calculated_concentration_units,
used_,
comment_
FROM "data_stage01_quantification_replicatesmi"
WHERE '''
if experiment_ids_I:
cmd_q = '''"data_stage01_quantification_replicatesmi"."experiment_id" =ANY ('{%s}'::text[]) ''' %(self.convert_list2string(experiment_ids_I));
cmd+=cmd_q;
if sample_name_shorts_I:
cmd_q = '''AND "data_stage01_quantification_replicatesmi"."sample_name_short" =ANY ('{%s}'::text[]) ''' %(self.convert_list2string(sample_name_shorts_I));
cmd+=cmd_q;
if component_names_I:
cmd_q = '''AND "data_stage01_quantification_replicatesmi"."component_name" =ANY ('{%s}'::text[]) ''' %(self.convert_list2string(component_names_I));
cmd+=cmd_q;
if component_group_names_I:
cmd_q = '''AND "data_stage01_quantification_replicatesmi"."component_group_name" =ANY ('{%s}'::text[]) ''' %(self.convert_list2string(component_group_names_I));
cmd+=cmd_q;
if calculated_concentration_units_I:
cmd_q = '''AND "data_stage01_quantification_replicatesmi"."calculated_concentration_units" =ANY ('{%s}'::text[]) ''' %(self.convert_list2string(calculated_concentration_units_I));
cmd+=cmd_q;
if used__I:
cmd += '''AND used_ '''
cmd += '''ORDER BY
experiment_id ASC,
sample_name_short ASC,
component_name ASC,
calculated_concentration_units ASC;'''
data_O = [dict(d) for d in execute_query(self.session,cmd,
verbose_I=False,
execute_I=True,
commit_I=False,
return_response_I=True,
return_cmd_I=False)];
return data_O;
except SQLAlchemyError as e:
print(e);
| 67.143204
| 236
| 0.686639
| 5,647
| 55,326
| 6.23818
| 0.03099
| 0.212564
| 0.266983
| 0.297244
| 0.908337
| 0.893746
| 0.875153
| 0.849008
| 0.833707
| 0.818435
| 0
| 0.017911
| 0.25019
| 55,326
| 824
| 237
| 67.143204
| 0.831236
| 0.009363
| 0
| 0.81746
| 0
| 0
| 0.043526
| 0.020367
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.015873
| null | null | 0.050265
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
90318b614fea4f63a31ee633c4a3edd9c2609e6e
| 150
|
py
|
Python
|
cuda-lip/LIP/__init__.py
|
sebgao/LIP
|
6724ec63c1f1ebefa25d7269e29d17c4411a7941
|
[
"MIT"
] | 209
|
2019-08-13T01:51:49.000Z
|
2022-03-28T09:59:28.000Z
|
cuda-lip/LIP/__init__.py
|
Abel1997/LIP
|
6724ec63c1f1ebefa25d7269e29d17c4411a7941
|
[
"MIT"
] | 12
|
2019-08-14T07:39:47.000Z
|
2021-09-24T10:08:55.000Z
|
cuda-lip/LIP/__init__.py
|
Abel1997/LIP
|
6724ec63c1f1ebefa25d7269e29d17c4411a7941
|
[
"MIT"
] | 26
|
2019-08-15T02:37:05.000Z
|
2021-12-10T06:32:40.000Z
|
from .pyinterface import cuda_lip2d, primitive_lip2d, inplace_primitive_lip2d
__all__ = ['cuda_lip2d', 'primitive_lip2d', 'inplace_primitive_lip2d']
| 37.5
| 77
| 0.826667
| 18
| 150
| 6.222222
| 0.444444
| 0.5
| 0.321429
| 0.410714
| 0.785714
| 0.785714
| 0.785714
| 0
| 0
| 0
| 0
| 0.043478
| 0.08
| 150
| 3
| 78
| 50
| 0.768116
| 0
| 0
| 0
| 0
| 0
| 0.32
| 0.153333
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 8
|
904a27257da3f8a0865fe9ed739f17761a8040da
| 1,617
|
py
|
Python
|
src/user/serializers.py
|
ravihansa/django-multiple-user-auth
|
7b6d1c783fc72d30cb7a5bcdf3a262f6ac0772b1
|
[
"bzip2-1.0.6"
] | 1
|
2019-10-07T15:26:24.000Z
|
2019-10-07T15:26:24.000Z
|
src/user/serializers.py
|
ravihansa/django-multiple-user-auth
|
7b6d1c783fc72d30cb7a5bcdf3a262f6ac0772b1
|
[
"bzip2-1.0.6"
] | null | null | null |
src/user/serializers.py
|
ravihansa/django-multiple-user-auth
|
7b6d1c783fc72d30cb7a5bcdf3a262f6ac0772b1
|
[
"bzip2-1.0.6"
] | null | null | null |
from rest_framework import serializers
from .models import User, Customer, Merchant
import bcrypt
class UserSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = (
"id",
"email",
"phone_no",
"password",
"pic_path",
)
def create(self, validated_data):
salt = self.saltSecret()
user = User.objects.create(
email=validated_data["email"],
phone_no=validated_data["phone_no"],
is_customer=True,
password=bcrypt.hashpw(
validated_data["password"].encode("utf8"), salt),
)
return user
def saltSecret(self):
return bcrypt.gensalt()
class MerchantSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = (
"id",
"email",
"phone_no",
"password",
"pic_path",
)
def create(self, validated_data):
salt = self.saltSecret()
user = User.objects.create(
email=validated_data["email"],
phone_no=validated_data["phone_no"],
is_merchant=True,
password=bcrypt.hashpw(
validated_data["password"].encode("utf8"), salt),
)
return user
def saltSecret(self):
return bcrypt.gensalt()
class UserProfileSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = (
"id",
"email",
"phone_no",
"pic_path",
)
| 24.134328
| 65
| 0.531849
| 144
| 1,617
| 5.826389
| 0.277778
| 0.123957
| 0.071514
| 0.125149
| 0.805721
| 0.805721
| 0.805721
| 0.805721
| 0.805721
| 0.805721
| 0
| 0.001946
| 0.364255
| 1,617
| 66
| 66
| 24.5
| 0.814202
| 0
| 0
| 0.767857
| 0
| 0
| 0.083488
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.071429
| false
| 0.107143
| 0.053571
| 0.035714
| 0.303571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
5f6aa3c6baca756c3c7b4985ef655dc9c3434ddc
| 31
|
py
|
Python
|
tiankafei-code-python/demo/package1/__init__.py
|
tiankafei/java
|
9ff39cb47b8f2144851856b4412b1b0b7781cb09
|
[
"Apache-2.0"
] | 1
|
2021-08-23T03:10:33.000Z
|
2021-08-23T03:10:33.000Z
|
tiankafei-code-python/demo/package1/__init__.py
|
tiankafei/java
|
9ff39cb47b8f2144851856b4412b1b0b7781cb09
|
[
"Apache-2.0"
] | 8
|
2020-09-02T15:14:03.000Z
|
2021-01-08T00:34:26.000Z
|
tiankafei-code-python/demo/package1/__init__.py
|
tiankafei/java
|
9ff39cb47b8f2144851856b4412b1b0b7781cb09
|
[
"Apache-2.0"
] | 2
|
2020-11-25T07:58:22.000Z
|
2021-01-28T00:15:11.000Z
|
# 作者：甜咖啡
# 新建时间：2021/4/6 20:27
| 10.333333
| 21
| 0.612903
| 8
| 31
| 2.375
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.384615
| 0.16129
| 31
| 2
| 22
| 15.5
| 0.346154
| 0.83871
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
5f9c25c158f4836098ae4c10841956609ccf413e
| 1,481
|
py
|
Python
|
venv/lib/python2.7/site-packages/pychart/afm/Utopia_Bold.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | 1
|
2019-12-19T01:53:13.000Z
|
2019-12-19T01:53:13.000Z
|
venv/lib/python2.7/site-packages/pychart/afm/Utopia_Bold.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | null | null | null |
venv/lib/python2.7/site-packages/pychart/afm/Utopia_Bold.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | null | null | null |
# AFM font Utopia-Bold (path: /usr/share/fonts/afms/adobe/putb8a.afm).
# Derived from Ghostscript distribution.
# Go to www.cs.wisc.edu/~ghost to get the Ghostcript source code.
import dir
dir.afm["Utopia-Bold"] = (500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 210, 278, 473, 560, 560, 887, 748, 252, 365, 365, 442, 600, 280, 392, 280, 378, 560, 560, 560, 560, 560, 560, 560, 560, 560, 560, 280, 280, 600, 600, 600, 456, 833, 644, 683, 689, 777, 629, 593, 726, 807, 384, 386, 707, 585, 918, 739, 768, 650, 768, 684, 561, 624, 786, 645, 933, 634, 617, 614, 335, 379, 335, 600, 500, 252, 544, 605, 494, 605, 519, 342, 533, 631, 316, 316, 582, 309, 948, 638, 585, 615, 597, 440, 446, 370, 629, 520, 774, 522, 524, 483, 365, 284, 365, 600, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 278, 560, 560, 100, 560, 560, 566, 560, 252, 473, 487, 287, 287, 639, 639, 500, 500, 510, 486, 280, 500, 552, 455, 252, 473, 473, 487, 1000, 1289, 500, 456, 500, 430, 430, 430, 430, 430, 430, 430, 430, 500, 430, 430, 500, 430, 430, 430, 1000, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 879, 500, 405, 500, 500, 500, 500, 591, 768, 1049, 427, 500, 500, 500, 500, 500, 806, 500, 500, 500, 316, 500, 500, 321, 585, 866, 662, )
| 246.833333
| 1,291
| 0.621202
| 287
| 1,481
| 3.205575
| 0.404181
| 0.586957
| 0.802174
| 0.991304
| 0.361957
| 0.326087
| 0.326087
| 0.3
| 0.3
| 0.267391
| 0
| 0.632585
| 0.187711
| 1,481
| 5
| 1,292
| 296.2
| 0.13217
| 0.115463
| 0
| 0
| 0
| 0
| 0.008423
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 10
|
396ff9dd40d64b9f6267cdb2eff448df96b5d8ea
| 2,085
|
py
|
Python
|
tests/test_views_oauth2.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | null | null | null |
tests/test_views_oauth2.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | 2
|
2020-06-03T12:44:25.000Z
|
2020-06-22T09:32:01.000Z
|
tests/test_views_oauth2.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | null | null | null |
import uuid
from uuid import UUID
from chaosplt_auth.views.web.backend import OAuthBackend
def test_get_oauth_token_before_create(oauth_backend: OAuthBackend,
user_id: UUID):
token = oauth_backend.get_oauth_token(user_id)
assert token == None
def test_get_oauth_token_after_create(oauth_backend: OAuthBackend,
user_id: UUID):
token = oauth_backend.get_oauth_token(user_id)
assert token == None
new_token = oauth_backend.create_oauth_token(
user_id, "github", "12345", {"token": "12335"})
token = oauth_backend.get_oauth_token(user_id)
assert token == new_token
def test_delete_oauth_token_after_create(oauth_backend: OAuthBackend,
user_id: UUID):
token = oauth_backend.get_oauth_token(user_id)
assert token == None
new_token = oauth_backend.create_oauth_token(
user_id, "github", uuid.uuid4().hex, {"token": "12335"})
token = oauth_backend.get_oauth_token(user_id)
assert token == new_token
oauth_backend.delete_oauth_token(user_id)
token = oauth_backend.get_oauth_token(user_id)
assert token == None
def test_get_oauth_token_by_provider(oauth_backend: OAuthBackend,
user_id: UUID):
token = oauth_backend.get_oauth_token(user_id)
assert token == None
provider_id = uuid.uuid4().hex
new_token = oauth_backend.create_oauth_token(
user_id, "github", provider_id, {"token": "12335"})
token = oauth_backend.get_oauth_token_by_provider("github", provider_id)
assert token == new_token
def test_update_oauth_token(oauth_backend: OAuthBackend, user_id: UUID):
token = oauth_backend.get_oauth_token(user_id)
assert token == None
token = oauth_backend.create_oauth_token(
user_id, "github", uuid.uuid4().hex, {"token": "12335"})
oauth_backend.set_oauth_token(user_id, {"token": "456789"})
token = oauth_backend.get_oauth_token(user_id)
assert token.token == {"token": "456789"}
| 31.590909
| 76
| 0.683453
| 272
| 2,085
| 4.841912
| 0.121324
| 0.159453
| 0.20653
| 0.182232
| 0.839787
| 0.781321
| 0.781321
| 0.754746
| 0.724374
| 0.724374
| 0
| 0.024661
| 0.222062
| 2,085
| 65
| 77
| 32.076923
| 0.7873
| 0
| 0
| 0.627907
| 0
| 0
| 0.046523
| 0
| 0
| 0
| 0
| 0
| 0.232558
| 1
| 0.116279
| false
| 0
| 0.069767
| 0
| 0.186047
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
397a66993cd9ce5fc8571d3bfa6c4626d76df39a
| 44,991
|
py
|
Python
|
rongcloud/message.py
|
rongcloud/server-sdk-python
|
0f9b5e3b74b9ad4b305a87775f1e91cb87e49f99
|
[
"MIT"
] | 56
|
2015-03-25T05:42:32.000Z
|
2021-11-09T07:01:19.000Z
|
rongcloud/message.py
|
rongcloud/server-sdk-python
|
0f9b5e3b74b9ad4b305a87775f1e91cb87e49f99
|
[
"MIT"
] | 10
|
2016-11-09T04:32:59.000Z
|
2020-03-07T22:55:47.000Z
|
rongcloud/message.py
|
rongcloud/server-sdk-python
|
0f9b5e3b74b9ad4b305a87775f1e91cb87e49f99
|
[
"MIT"
] | 49
|
2015-01-06T11:20:14.000Z
|
2021-08-24T13:21:25.000Z
|
import json
import urllib
from rongcloud.module import Module, ParamException
class Message(Module):
def __init__(self, rc):
super().__init__(rc)
self._user_info = None
def set_user_info(self, user_id, name, icon, extra=None):
param_dict = locals().copy()
format_str = '"id":"{{ user_id }}","name":"{{ name }}","icon":"{{ icon }}","extra":"{{ extra }}"'
self._user_info = self._render(param_dict, format_str)
def broadcast(self, from_user_id, object_name, content, push_content=None, push_data=None, os=None,
content_available=0, push_ext=None):
"""
单个应用每小时只能发送 2 次，每天最多发送 3 次。如需要调整发送频率，可联系销售，电话 13161856839。
:param from_user_id: 发送人用户 Id。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，以避免与融云系统内置消息的 ObjectName 重名。
（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。 如果为自定义消息，
则 pushContent 为自定义消息显示的 Push 内容，如果不传则用户不会收到 Push 通知。（非必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param os: 针对操作系统发送 Push，值为 iOS 表示对 iOS 手机用户发送 Push ,
为 Android 时表示对 Android 手机用户发送 Push ，
如对所有用户发送 Push 信息，则不需要传 os 参数。（非必传）
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0。（非必传）
:param push_ext 推送通知属性设置，详细查看 pushExt 结构说明，pushExt 为 JSON 结构请求时需要做转义处理。disablePush 为 true 时此属性无效。暂不支持海外数据中心（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/broadcast.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if push_content is not none %}&pushContent={{ push_content }}{% endif %}' \
'{% if push_data is not none %}&pushData={{ push_data }}{% endif %}' \
'{% if os is not none %}&os={{ os }}{% endif %}' \
'{% if content_available != 0 %}&contentAvailable={{ content_available }}{% endif %}' \
'{% if push_ext is not none %}&pushExt={{ push_ext }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(push_content, str)
self._check_param(push_data, str)
self._check_param(os, str)
self._check_param(content_available, int, '0~1')
self._check_param(push_ext, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def get_private(self):
return Private(self._rc)
def get_group(self):
return Group(self._rc)
def get_chatroom(self):
return Chatroom(self._rc)
def get_system(self):
return System(self._rc)
def get_history(self):
return History(self._rc)
class Private(Module):
def __init__(self, rc):
super().__init__(rc)
def send(self, from_user_id, to_user_ids, object_name, content, push_content=None, push_data=None,
count=-1, verify_blacklist=0, is_persisted=1, is_include_sender=0, content_available=0, expansion=False, disable_push=False, push_ext=None):
"""
发送单聊消息。
:param from_user_id: 发送人用户 Id。（必传）
:param to_user_ids: 接收用户 Id，可以实现向多人发送消息，每次上限为 1000 人。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，则发送后用户一定会收到 Push 信息。
如果为自定义消息，则 pushContent 为自定义消息显示的 Push 内容，
如果不传则用户不会收到 Push 通知。（非必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param count: 针对 iOS 平台，Push 时用来控制未读消息显示数，只有在 to_user_ids 为一个用户 Id 的时候有效，
客户端获取远程推送内容时为 badge 查看详细，
为 -1 时不改变角标数，传入相应数字表示把角标数改为指定的数字，最大不超过 9999。（非必传）
:param verify_blacklist: 是否过滤接收用户黑名单列表，0 表示为不过滤，1 表示为过滤，默认为 0 不过滤。（非必传）
:param is_persisted: 针对融云服务端是否存储此条消息，客户端则根据消息注册的 ISPERSISTED 标识判断是否存储，
如果旧版客户端上未注册该消息时，收到该消息后默认为存储，但无法解析显示。
0 表示为不存储，1 表示为存储，默认为 1 存储消息。（非必传）
:param is_include_sender: 发送用户自己是否接收消息，0 表示为不接收，1 表示为接收，默认为 0 不接收，
只有在 toUserId 为一个用户 Id 的时候有效。（非必传）
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0（非必传）
:param attach_user_info: 是否携带用户信息，默认为 False。（非必传）
:param expansion 是否为可扩展消息，默认为 false，设为 true 时终端在收到该条消息后，可对该条消息设置扩展信息。暂不支持海外数据中心（非必传）
:param disable_push 是否为静默消息，默认为 false，设为 true 时终端用户离线情况下不会收到通知提醒。暂不支持海外数据中心（非必传）
:param push_ext 推送通知属性设置，详细查看 pushExt 结构说明，pushExt 为 JSON 结构请求时需要做转义处理。disablePush 为 true 时此属性无效。暂不支持海外数据中心（非必传）
:return: 返回码，200 为正常。如：{"code":200}
"""
to_user_ids = self._tran_list(to_user_ids)
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/private/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'{% for item in to_user_ids %}&toUserId={{ item }}{% endfor %}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if push_content is not none %}&pushContent={{ push_content }}{% endif %}' \
'{% if push_data is not none %}&pushData={{ push_data }}{% endif %}' \
'{% if count != -1 %}&count={{ count }}{% endif %}' \
'{% if verify_blacklist != 0 %}&verifyBlacklist={{ verify_blacklist }}{% endif %}' \
'{% if is_persisted != 1 %}&isPersisted={{ is_persisted }}{% endif %}' \
'{% if is_include_sender != 0 %}&isIncludeSender={{ is_include_sender }}{% endif %}' \
'{% if content_available != 0 %}&contentAvailable={{ content_available }}{% endif %}' \
'{% if expansion != False %}&expansion={{ expansion }}{% endif %}' \
'{% if disable_push != False %}&disablePush={{ disable_push }}{% endif %}' \
'{% if push_ext is not none %}&pushExt={{ push_ext }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_user_ids, list, '1~1000')
for to_user_id in to_user_ids:
self._check_param(to_user_id, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(push_content, str)
self._check_param(push_data, str)
self._check_param(count, int, '-1~9999')
self._check_param(verify_blacklist, int, '0~1')
self._check_param(is_persisted, int, '0~1')
self._check_param(is_include_sender, int, '0~1')
self._check_param(content_available, int, '0~1')
self._check_param(expansion, bool)
self._check_param(disable_push, bool)
self._check_param(push_ext, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def recall(self, from_user_id, target_id, uid, sent_time, is_admin=0, is_delete=0, extra=None):
"""
撤回已发送的单聊消息，撤回时间无限制，只允许撤回用户自己发送的消息。
:param from_user_id: 消息发送人用户 Id。（必传）
:param target_id: 对方用户 Id。（必传）
:param uid: 消息唯一标识，可通过服务端实时消息路由获取，对应名称为 msgUID。（必传）
:param sent_time: 消息发送时间，可通过服务端实时消息路由获取，对应名称为 msgTimestamp。（必传）
:param is_admin: 是否为管理员，默认为 0，设为 1 时，IMKit 收到此条消息后，小灰条默认显示为
“管理员 撤加了一条消息”。（非必传）
:param is_delete: 是否删除消息，默认为 0 撤回该条消息同时，用户端将该条消息删除并替换为一条小灰条撤回提示消息；
为 1 时，该条消息删除后，不替换为小灰条提示消息。（非必传）
:param extra: 扩展信息，可以放置任意的数据内容。（非必传）
:return: 返回码，200 为正常。如：{"code":200}
"""
param_dict = locals().copy()
url = '/message/recall.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&conversationType=1' \
'&targetId={{ target_id }}' \
'&messageUID={{ uid }}' \
'&sentTime={{ sent_time }}' \
'{% if is_admin is not none %}&isAdmin={{ is_admin }}{% endif %}' \
'{% if is_delete is not none %}&isDelete={{ is_delete }}{% endif %}' \
'{% if extra is not none %}&extra={{ extra }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(target_id, str, '1~64')
self._check_param(uid, str)
self._check_param(sent_time, int)
self._check_param(is_admin, int)
self._check_param(is_delete, int)
self._check_param(extra, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def send_template(self, from_user_id, to_user_ids, object_name, values, content,
push_content=None, push_data=None, verify_blacklist=0, content_available=0, disable_push=False):
"""
发送单聊模板消息。一个用户向多个用户发送不同消息内容，单条消息最大 128k。
:param from_user_id: 发送人用户 Id。（必传）
:param to_user_ids: 接收用户 Id，提供多个本参数可以实现向多人发送消息，上限为 1000 人。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param values: 消息内容中，标识位对应内容。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。如果为自定义消息，定义显示的 Push 内容，
内容中定义标识通过 values 中设置的标识位内容进行替换。
如消息类型为自定义不需要 Push 通知，则对应数组传空值即可。（必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param verify_blacklist: 是否过滤发送人黑名单列表，0 为不过滤、 1 为过滤，默认为 0 不过滤。（非必传）
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0。（非必传）
:param disable_push 是否为静默消息，默认为 false，设为 true 时终端用户离线情况下不会收到通知提醒。暂不支持海外数据中心（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
if push_content is None:
push_content = []
to_user_ids = self._tran_list(to_user_ids)
content = json.dumps(content).replace('\"', '\\"')
param_dict = locals().copy()
url = '/message/private/publish_template.json'
format_str = '{' \
'"fromUserId":"{{ from_user_id }}"' \
',"toUserId":[{% for item in to_user_ids %}"{{ item }}"' \
'{% if not loop.last %},{% endif %}{% endfor %}]' \
',"objectName":"{{ object_name }}"' \
',"values":[{% for item in values %}{% raw %}{{% endraw %}' \
'{% for key, value in item.items() %}"{{ key }}":"{{ value }}"{% if not loop.last %},{% endif %}' \
'{% endfor %}{% raw %}}{% endraw %}{% if not loop.last %},{% endif %}{% endfor %}]' \
',"content":"{{ content }}"' \
',"pushContent":' \
'[{% for item in push_content %}"{{ item }}"{% if not loop.last %},{% endif %}{% endfor %}]' \
'{% if push_data is not none %},"pushData":' \
'[{% for item in push_data %}"{{ item }}"{% if not loop.last %},{% endif %}{% endfor %}]' \
'{% endif %}' \
'{% if (verify_blacklist != 0) %},"verifyBlacklist":{{ verify_blacklist }}{% endif %}' \
'{% if (content_available != 0) %},"contentAvailable":{{ content_available }}{% endif %}' \
'{% if (disable_push != False) %},"disablePush":\"{{ disable_push }}\"{% endif %}' \
'}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_user_ids, list, '1~1000')
for user in to_user_ids:
self._check_param(user, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(values, list)
self._check_param(push_content, list)
self._check_param(push_data, list)
self._check_param(verify_blacklist, int, '0~1')
self._check_param(content_available, int, '0~1')
self._check_param(disable_push, bool)
xx = self._render(param_dict, format_str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def send_status_message(self, from_user_id, to_user_ids, object_name, content, verify_blacklist=0, is_include_sender=0):
'''
发送单聊状态消息
:param from_user_id: 发送人用户 Id。（必传）
:param to_user_id: 接收用户 Id，可以实现向多人发送消息，每次上限为 1000 人。（必传）
:param object_name: 消息类型，可自定义消息类型，长度不超过 32 个字符，在自定义消息时需要注意，
不要以 "RC:" 开头，以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，单条消息最大 128k，详见消息结构示例；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传）
:param verify_blacklist: 是否过滤发送人黑名单列表，0 表示为不过滤、 1 表示为过滤，默认为 0 不过滤。（非必传）
:param is_include_sender: 发送用户自己是否接收消息，0 表示为不接收，1 表示为接收，默认为 0 不接收。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
'''
content = urllib.parse.quote(json.dumps(content))
to_user_ids = self._tran_list(to_user_ids)
param_dict = locals().copy()
url = '/statusmessage/private/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'{% for item in to_user_ids %}&toUserId={{ item }}{% endfor %}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if verify_blacklist != 0 %}&verifyBlacklist={{ verify_blacklist }}{% endif %}' \
'{% if is_include_sender != 0 %}&isIncludeSender={{ is_include_sender }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_user_ids, list, '1~1000')
for user in to_user_ids:
self._check_param(user, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(verify_blacklist, int, '0~1')
self._check_param(is_include_sender, int, '0~1')
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e.info))
class Group(Module):
def __init__(self, rc):
super().__init__(rc)
def send(self, from_user_id, to_group_id, object_name, content, push_content=None, push_data=None,
is_persisted=1, is_include_sender=0, is_mentioned=0, content_available=0, expansion=False, disable_push=False, push_ext=None):
"""
发送群组消息，以一个用户身份向群组发送消息，单条消息最大 128k。
:param from_user_id: 发送人用户 Id 。（必传）
:param to_group_id: 接收群 Id。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；
可自定义消息类型，长度不超过 32 个字符，您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。如果为自定义消息，
则 pushContent 为自定义消息显示的 Push 内容，如果不传则用户不会收到 Push 通知。（非必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param is_persisted: 针对融云服务端是否存储此条消息，客户端则根据消息注册的 ISPERSISTED 标识判断是否存储，
如果旧版客户端上未注册该消息时，收到该消息后默认为存储，但无法解析显示。
0 表示为不存储、 1 表示为存储，默认为 1 存储消息。（非必传）
:param is_include_sender: 发送用户自己是否接收消息，0 表示为不接收，1 表示为接收，默认为 0 不接收，
只有在 toGroupId 为一个群组 Id 的时候有效。（非必传）
:param is_mentioned: 是否为 @ 消息，0 表示为普通消息，1 表示为 @ 消息，默认为 0。
当为 1 时 content 参数中必须携带 mentionedInfo @消息的详细内容。
为 0 时则不需要携带 mentionedInfo。（非必传）
当指定了 toUserId 时，则 @ 的用户必须为 toUserId 中的用户。
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0（非必传）
:param attach_user_info: 是否携带用户信息，默认为 False。（非必传）
:param expansion 是否为可扩展消息，默认为 false，设为 true 时终端在收到该条消息后，可对该条消息设置扩展信息。暂不支持海外数据中心（非必传）
:param disable_push 是否为静默消息，默认为 false，设为 true 时终端用户离线情况下不会收到通知提醒。暂不支持海外数据中心
:param push_ext 推送通知属性设置，详细查看 pushExt 结构说明，pushExt 为 JSON 结构请求时需要做转义处理。
disablePush 为 true 时此属性无效。暂不支持海外数据中心（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/group/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&toGroupId={{ to_group_id }}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if push_content is not none %}&pushContent={{ push_content }}{% endif %}' \
'{% if push_data is not none %}&pushData={{ push_data }}{% endif %}' \
'{% if (is_persisted != 1) %}&isPersisted={{ is_persisted }}{% endif %}' \
'{% if (is_include_sender != 0) %}&isIncludeSender={{ is_include_sender }}{% endif %}' \
'{% if (is_mentioned != 0) %}&isMentioned={{ is_mentioned }}{% endif %}' \
'{% if (content_available != 0) %}&contentAvailable={{ content_available }}{% endif %}' \
'{% if (expansion != False) %}&expansion={{ expansion }}{% endif %}' \
'{% if (disable_push != False) %}&disablePush={{ disable_push }}{% endif %}' \
'{% if push_ext is not none %}&pushExt={{ push_ext }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_group_id, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(push_content, str)
self._check_param(push_data, str)
self._check_param(is_persisted, int, '0~1')
self._check_param(is_include_sender, int, '0~1')
self._check_param(is_mentioned, int, '0~1')
self._check_param(content_available, int, '0~1')
self._check_param(expansion, bool)
self._check_param(disable_push, bool)
self._check_param(push_ext, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def send_direction(self, from_user_id, to_group_id, to_user_ids, object_name, content, push_content=None, push_data=None,
is_persisted=1, is_include_sender=0, is_mentioned=0, content_available=0):
"""
发送群组定向消息
:param from_user_id: 发送人用户 Id 。（必传）
:param to_group_id: 接收群 Id。（必传）
:param to_user_ids: 群定向消息功能，向群中指定的一个或多个用户发送消息，群中其他用户无法收到该消息，当 toGroupId 为一个群组时此参数有效。（必传）
注：如果开通了单群聊消息云存储功能，群定向消息不会存储到云端，向群中部分用户发送消息阅读状态回执时可使用此功能。
:param object_name: 消息类型，参考融云消息类型表.消息标志；
可自定义消息类型，长度不超过 32 个字符，您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。如果为自定义消息，
则 pushContent 为自定义消息显示的 Push 内容，如果不传则用户不会收到 Push 通知。（非必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param is_persisted: 针对融云服务端是否存储此条消息，客户端则根据消息注册的 ISPERSISTED 标识判断是否存储，
如果旧版客户端上未注册该消息时，收到该消息后默认为存储，但无法解析显示。
0 表示为不存储、 1 表示为存储，默认为 1 存储消息。（非必传）
:param is_include_sender: 发送用户自己是否接收消息，0 表示为不接收，1 表示为接收，默认为 0 不接收，
只有在 toGroupId 为一个群组 Id 的时候有效。（非必传）
:param is_mentioned: 是否为 @ 消息，0 表示为普通消息，1 表示为 @ 消息，默认为 0。
当为 1 时 content 参数中必须携带 mentionedInfo @消息的详细内容。
为 0 时则不需要携带 mentionedInfo。（非必传）
当指定了 toUserId 时，则 @ 的用户必须为 toUserId 中的用户。
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0（非必传）
:param attach_user_info: 是否携带用户信息，默认为 False。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
to_user_ids = self._tran_list(to_user_ids)
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/group/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&toGroupId={{ to_group_id }}' \
'{% for item in to_user_ids %}&toUserId={{ item }}{% endfor %}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if push_content is not none %}&pushContent={{ push_content }}{% endif %}' \
'{% if push_data is not none %}&pushData={{ push_data }}{% endif %}' \
'{% if (is_persisted != 1) %}&isPersisted={{ is_persisted }}{% endif %}' \
'{% if (is_include_sender != 0) %}&isIncludeSender={{ is_include_sender }}{% endif %}' \
'{% if (is_mentioned != 0) %}&isMentioned={{ is_mentioned }}{% endif %}' \
'{% if (content_available != 0) %}&contentAvailable={{ content_available }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_group_id, str, '1~64')
for user in to_user_ids:
self._check_param(user, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(push_content, str)
self._check_param(push_data, str)
self._check_param(is_persisted, int, '0~1')
self._check_param(is_include_sender, int, '0~1')
self._check_param(is_mentioned, int, '0~1')
self._check_param(content_available, int, '0~1')
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def recall(self, from_user_id, group_id, uid, sent_time, is_admin=None, is_delete=None, extra=None):
"""
撤回已发送的群聊消息，撤回时间无限制，只允许撤回用户自己发送的消息。
:param from_user_id: 消息发送人用户 Id。（必传）
:param group_id: 群组会话 Id。（必传）
:param uid: 消息唯一标识，可通过服务端实时消息路由获取，对应名称为 msgUID。（必传）
:param sent_time: 消息发送时间，可通过服务端实时消息路由获取，对应名称为 msgTimestamp。（必传）
:param is_admin: 是否为管理员，默认为 0，设为 1 时，IMKit 收到此条消息后，小灰条默认显示为
“管理员 撤加了一条消息”。（非必传）
:param is_delete: 是否删除消息，默认为 0 撤回该条消息同时，用户端将该条消息删除并替换为一条小灰条撤回提示消息；
为 1 时，该条消息删除后，不替换为小灰条提示消息。（非必传）
:param extra: 扩展信息，可以放置任意的数据内容。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
param_dict = locals().copy()
url = '/message/recall.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&conversationType=3' \
'&targetId={{ group_id }}' \
'&messageUID={{ uid }}' \
'&sentTime={{ sent_time }}' \
'{% if is_admin is not none %}&isAdmin={{ is_admin }}{% endif %}' \
'{% if is_delete is not none %}&isDelete={{ is_delete }}{% endif %}' \
'{% if extra is not none %}&extra={{ extra }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(group_id, str, '1~64')
self._check_param(uid, str)
self._check_param(sent_time, int)
self._check_param(is_admin, int)
self._check_param(is_delete, int)
self._check_param(extra, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def send_status_message(self, from_user_id, to_group_ids, object_name, content, verify_blacklist=0, is_include_sender=0):
'''
发送群聊状态消息
:param from_user_id: 发送人用户 Id。（必传）
:param to_group_ids: 接收群Id，提供多个本参数可以实现向多群发送消息，最多不超过 3 个群组。（必传）
:param object_name: 消息类型，可自定义消息类型，长度不超过 32 个字符，在自定义消息时需要注意，
不要以 "RC:" 开头，以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，单条消息最大 128k，详见消息结构示例；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传）
:param verify_blacklist: 是否过滤发送人黑名单列表，0 表示为不过滤、 1 表示为过滤，默认为 0 不过滤。（非必传）
:param is_include_sender: 发送用户自己是否接收消息，0 表示为不接收，1 表示为接收，默认为 0 不接收。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
'''
content = urllib.parse.quote(json.dumps(content))
to_group_ids = self._tran_list(to_group_ids)
param_dict = locals().copy()
url = '/statusmessage/group/publish.json'
# format_str = 'fromUserId={{ from_user_id }}' \
# '&toGroupId={{ to_group_id }}' \
# '&objectName={{ object_name }}' \
# '&content={{ content }}' \
# '{% if verify_blacklist != 0 %}&verifyBlacklist={{ verify_blacklist }}{% endif %}' \
# '{% if is_include_sender != 0 %}&isIncludeSender={{ is_include_sender }}{% endif %}'
format_str = 'fromUserId={{ from_user_id }}' \
'{% for item in to_group_ids %}&toGroupId={{ item }}{% endfor %}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if verify_blacklist != 0 %}&verifyBlacklist={{ verify_blacklist }}{% endif %}' \
'{% if is_include_sender != 0 %}&isIncludeSender={{ is_include_sender }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_group_ids, list, '1~3')
for group in to_group_ids:
self._check_param(group, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(verify_blacklist, int, '0~1')
self._check_param(is_include_sender, int, '0~1')
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e.info))
class Chatroom(Module):
def __init__(self, rc):
super().__init__(rc)
def send(self, from_user_id, to_chatroom_id, object_name, content):
"""
发送聊天室消息。一个用户向聊天室发送消息，单条消息最大 128k。
:param from_user_id: 发送人用户 Id。（必传）
:param to_chatroom_id: 接收聊天室 Id，提供多个本参数可以实现向多个聊天室发送消息，建议最多不超过 10 个聊天室。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，以避免与融云系统内置消息的 ObjectName 重名。
（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/chatroom/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&toChatroomId={{ to_chatroom_id }}' \
'&objectName={{ object_name }}' \
'&content={{ content }}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_chatroom_id, str)
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def recall(self, from_user_id, chatroom_id, uid, sent_time, is_admin=None, is_delete=None, extra=None):
"""
撤回已发送的聊天室消息，撤回时间无限制，只允许撤回用户自己发送的消息。
:param from_user_id: 消息发送人用户 Id。（必传）
:param chatroom_id: 聊天室 Id。（必传）
:param uid: 消息唯一标识，可通过服务端实时消息路由获取，对应名称为 msgUID。（必传）
:param sent_time: 消息发送时间，可通过服务端实时消息路由获取，对应名称为 msgTimestamp。（必传）
:param is_admin: 是否为管理员，默认为 0，设为 1 时，IMKit 收到此条消息后，小灰条默认显示为
“管理员 撤加了一条消息”。（非必传）
:param is_delete: 是否删除消息，默认为 0 撤回该条消息同时，用户端将该条消息删除并替换为一条小灰条撤回提示消息；
为 1 时，该条消息删除后，不替换为小灰条提示消息。（非必传）
:param extra: 扩展信息，可以放置任意的数据内容。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
param_dict = locals().copy()
url = '/message/recall.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&conversationType=4' \
'&targetId={{ chatroom_id }}' \
'&messageUID={{ uid }}' \
'&sentTime={{ sent_time }}' \
'{% if is_admin is not none %}&isAdmin={{ is_admin }}{% endif %}' \
'{% if is_delete is not none %}&isDelete={{ is_delete }}{% endif %}' \
'{% if extra is not none %}&extra={{ extra }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(chatroom_id, str, '1~64')
self._check_param(uid, str)
self._check_param(sent_time, int)
self._check_param(is_admin, int)
self._check_param(is_delete, int)
self._check_param(extra, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def broadcast(self, from_user_id, object_name, content):
"""
向应用中的所有聊天室发送一条消息，单条消息最大 128k。
此服务在开通 IM 商用版的情况下，可申请开通，详细请联系商务，电话：13161856839。
:param from_user_id: 发送人用户 Id。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/chatroom/broadcast.json'
format_str = 'fromUserId={{ from_user_id }}' \
'&objectName={{ object_name }}' \
'&content={{ content }}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
class System(Module):
def __init__(self, rc):
super().__init__(rc)
def send(self, from_user_id, to_user_ids, object_name, content, push_content=None, push_data=None,
is_persisted=1, content_available=0, disable_push=False, push_ext=None):
"""
发送系统消息，一个用户向一个或多个用户发送系统消息，单条消息最大 128k，会话类型为 SYSTEM。
:param from_user_id: 发送人用户 Id。（必传）
:param to_user_ids: 接收用户Id，提供多个本参数可以实现向多用户发送系统消息，上限为 100 人。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。如果为自定义消息，
则 pushContent 为自定义消息显示的 Push 内容，如果不传则用户不会收到 Push 通知。（非必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param is_persisted: 针对融云服务端是否存储此条消息，客户端则根据消息注册的 ISPERSISTED 标识判断是否存储，
如果旧版客户端上未注册该消息时，收到该消息后默认为存储，但无法解析显示。
0 表示为不存储，1 表示为存储，默认为 1 存储消息。
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0。（非必传）
:param disable_push 是否为静默消息，默认为 false，设为 true 时终端用户离线情况下不会收到通知提醒。暂不支持海外数据中心（非必传）
:param push_ext 推送通知属性设置，详细查看 pushExt 结构说明，pushExt 为 JSON 结构请求时需要做转义处理。disablePush 为 true 时此属性无效。暂不支持海外数据中心（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
to_user_ids = self._tran_list(to_user_ids)
content = urllib.parse.quote(json.dumps(content))
param_dict = locals().copy()
url = '/message/system/publish.json'
format_str = 'fromUserId={{ from_user_id }}' \
'{% for item in to_user_ids %}&toUserId={{ item }}{% endfor %}' \
'&objectName={{ object_name }}' \
'&content={{ content }}' \
'{% if push_content is not none %}&pushContent={{ push_content }}{% endif %}' \
'{% if push_data is not none %}&pushData={{ push_data }}{% endif %}' \
'{% if (is_persisted != 1) %}&isPersisted={{ is_persisted }}{% endif %}' \
'{% if (content_available != 0) %}&contentAvailable={{ content_available }}{% endif %}' \
'{% if disable_push != False %}&disablePush={{ disable_push }}{% endif %}' \
'{% if push_ext is not none %}&pushExt={{ push_ext }}{% endif %}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_user_ids, list, '1~100')
for to_user_id in to_user_ids:
self._check_param(to_user_id, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(push_content, str)
self._check_param(push_data, str)
self._check_param(is_persisted, int, '0~1')
self._check_param(content_available, int, '0~1')
self._check_param(disable_push, bool)
self._check_param(push_ext, str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def send_template(self, from_user_id, to_user_ids, object_name, content, values,
push_content=None, push_data=None, content_available=0):
"""
发送系统模板消息。一个用户向一个或多个用户发送系统消息，单条消息最大 128k，会话类型为 SYSTEM。
:param from_user_id: 发送人用户 Id。（必传）
:param to_user_ids: 接收用户 Id，提供多个本参数可以实现向多人发送消息，上限为 100 人。（必传）
:param object_name: 消息类型，参考融云消息类型表.消息标志；可自定义消息类型，长度不超过 32 个字符，
您在自定义消息时需要注意，不要以 "RC:" 开头，
以避免与融云系统内置消息的 ObjectName 重名。（必传）
:param content: 消息内容中，标识位对应内容。（必传）
:param values: 发送消息内容，内置消息以 JSON 方式进行数据序列化，详见融云内置消息结构详解；
如果 objectName 为自定义消息类型，该参数可自定义格式，不限于 JSON。（必传）
:param push_content: 定义显示的 Push 内容，如果 objectName 为融云内置消息类型时，
则发送后用户一定会收到 Push 信息。如果为自定义消息，定义显示的 Push 内容，
内容中定义标识通过 values 中设置的标识位内容进行替换。
如消息类型为自定义不需要 Push 通知，则对应数组传空值即可。（必传）
:param push_data: 针对 iOS 平台为 Push 通知时附加到 payload 中，客户端获取远程推送内容时为 appData 查看详细，
Android 客户端收到推送消息时对应字段名为 pushData。（非必传）
:param content_available: 针对 iOS 平台，对 SDK 处于后台暂停状态时为静默推送，是 iOS7 之后推出的一种推送方式。
允许应用在收到通知后在后台运行一段代码，且能够马上执行，查看详细。
1 表示为开启，0 表示为关闭，默认为 0。（非必传）
:return: 请求返回结果，code 返回码，200 为正常。如：{"code":200}
"""
if push_content is None:
push_content = []
"""
向多个用户发送不同内容的系统消息。。
"""
content = json.dumps(content).replace('\"', '\\"')
param_dict = locals().copy()
url = '/message/system/publish_template.json'
format_str = '{' \
'"fromUserId":"{{ from_user_id }}"' \
',"toUserId":[{% for item in to_user_ids %}"{{ item }}"' \
'{% if not loop.last %},{% endif %}{% endfor %}]' \
',"objectName":"{{ object_name }}"' \
',"values":[{% for item in values %}{% raw %}{{% endraw %}' \
'{% for key, value in item.items() %}"{{ key }}":"{{ value }}"' \
'{% if not loop.last %},{% endif %}{% endfor %}{% raw %}}{% endraw %}' \
'{% if not loop.last %},{% endif %}{% endfor %}]' \
',"content":"{{ content }}"' \
',"pushContent":' \
'[{% for item in push_content %}"{{ item }}"{% if not loop.last %},{% endif %}{% endfor %}]' \
'{% if push_data is not none %},"pushData":' \
'[{% for item in push_data %}"{{ item }}"{% if not loop.last %},{% endif %}{% endfor %}]' \
'{% endif %}' \
'{% if (content_available != 0) %},"contentAvailable":{{ content_available }}{% endif %}' \
'}'
try:
self._check_param(from_user_id, str, '1~64')
self._check_param(to_user_ids, list, '1~1000')
for user in to_user_ids:
self._check_param(user, str, '1~64')
self._check_param(object_name, str, '1~32')
self._check_param(content, str)
self._check_param(values, list)
self._check_param(push_content, list)
self._check_param(push_data, list)
self._check_param(content_available, int, '0~1')
xx = self._render(param_dict, format_str)
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
class History(Module):
def __init__(self, rc):
super().__init__(rc)
def query(self, date):
"""
免费获取 APP 内指定某天某小时内的所有会话消息记录的下载地址。
（目前支持二人会话，讨论组，群组，聊天室，客服，系统通知消息历史记录下载），
消息记录以日志文件方式提供，并对文件进行 ZIP 压缩。
:param date: 国内数据中心为指定北京时间某天某小时，格式为字符串 "2014010101"，
表示获取 2014 年 1 月 1 日凌晨 1 点至 2 点的数据。
如使用的是融云海外数据中心为 UTC 时间。（必传）
:return: 请求返回结果，code 返回码，200 为正常；
url 历史记录下载地址，如没有消息记录数据时，则 url 值为空。date 历史记录时间。
如：{
"code":200,
"url":"http://aa.com/1/c6720eea-452b-4f93-8159-7af3046611f1.gz",
"date":"2014010101"
}
"""
param_dict = locals().copy()
url = '/message/history.json'
format_str = 'date={{ date }}'
try:
self._check_param(date, str, '10~10')
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
def remove(self, date):
"""
删除服务端消息记录日志文件，文件内容为 APP 内指定某天某小时内的所有会话消息记录，删除后文件将在随后的 10 分钟内被永久删除。
开通单群聊消息云存储功能后存储在云端的数据不会被删除，只是无法再通过“消息历史记录下载地址获取方法”获取消息日志文件。
:param date: 指定北京时间某天某小时，格式为字符串 "2014010101"，
表示：2014 年 1 月 1 日凌晨1点。返回成功后，消息记录文件将在随后的 10 分钟内被永久删除。（必传）
:return: 请求返回结果，code 返回码，200 为正常；如：{"code":200}
"""
param_dict = locals().copy()
url = '/message/history/delete.json'
format_str = 'date={{ date }}'
try:
self._check_param(date, str, '10~10')
return self._http_post(url, self._render(param_dict, format_str))
except ParamException as e:
return json.loads(str(e))
| 57.167726
| 153
| 0.532595
| 4,827
| 44,991
| 4.745598
| 0.084317
| 0.047933
| 0.074562
| 0.018335
| 0.907757
| 0.904789
| 0.897542
| 0.887502
| 0.882481
| 0.878247
| 0
| 0.020586
| 0.351115
| 44,991
| 786
| 154
| 57.240458
| 0.764061
| 0.381098
| 0
| 0.801354
| 0
| 0.002257
| 0.291819
| 0.029743
| 0
| 0
| 0
| 0
| 0
| 1
| 0.063205
| false
| 0
| 0.006772
| 0.011287
| 0.167043
| 0
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| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
| 1
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0
| 7
|
39ca7f5e1c302555a2285f632fbbda705525acd7
| 17,747
|
py
|
Python
|
XWikis-Corpus/baselines/xrank.py
|
lauhaide/clads
|
9462ea090cf2ceabdcae879b409ceea23d391ff8
|
[
"MIT"
] | 6
|
2021-12-10T05:48:33.000Z
|
2022-03-16T15:30:47.000Z
|
XWikis-Corpus/baselines/xrank.py
|
lauhaide/clads
|
9462ea090cf2ceabdcae879b409ceea23d391ff8
|
[
"MIT"
] | null | null | null |
XWikis-Corpus/baselines/xrank.py
|
lauhaide/clads
|
9462ea090cf2ceabdcae879b409ceea23d391ff8
|
[
"MIT"
] | 1
|
2022-01-28T08:54:54.000Z
|
2022-01-28T08:54:54.000Z
|
## adapted from https://github.com/crabcamp/lexrank
import math
from collections import Counter, defaultdict
import numpy as np
from power_method import stationary_distribution
from text import tokenize
from scipy.stats import entropy
from numpy.linalg import norm
import numpy as np
def JSD(P, Q):
_P = P / norm(P, ord=1)
_Q = Q / norm(Q, ord=1)
_M = 0.5 * (_P + _Q)
return 0.5 * (entropy(_P, _M) + entropy(_Q, _M))
class LexRank:
def __init__(
self,
documents,
stopwords=None,
keep_numbers=False,
keep_emails=False,
keep_urls=False,
include_new_words=True,
):
if stopwords is None:
self.stopwords = set()
else:
self.stopwords = stopwords
self.keep_numbers = keep_numbers
self.keep_emails = keep_emails
self.keep_urls = keep_urls
self.include_new_words = include_new_words
self.idf_score = self._calculate_idf(documents)
def get_summary(
self,
sentences,
summary_size=1,
threshold=.03,
fast_power_method=True,
):
if not isinstance(summary_size, int) or summary_size < 1:
raise ValueError('\'summary_size\' should be a positive integer')
lex_scores = self.rank_sentences(
sentences,
threshold=threshold,
fast_power_method=fast_power_method,
)
sorted_ix = np.argsort(lex_scores)[::-1]
summary = [sentences[i] for i in sorted_ix[:summary_size]]
return summary
def rank_sentences(
self,
sentences,
threshold=.03,
fast_power_method=True,
):
if not (
threshold is None or
isinstance(threshold, float) and 0 <= threshold < 1
):
raise ValueError(
'\'threshold\' should be a floating-point number '
'from the interval [0, 1) or None',
)
tf_scores = [
Counter(self.tokenize_sentence(sentence)) for sentence in sentences
]
similarity_matrix = self._calculate_similarity_matrix(tf_scores)
if threshold is None:
markov_matrix = self._markov_matrix(similarity_matrix)
else:
markov_matrix = self._markov_matrix_discrete(
similarity_matrix,
threshold=threshold,
)
scores = stationary_distribution(
markov_matrix,
increase_power=fast_power_method,
normalized=False,
)
return scores
def sentences_similarity(self, sentence_1, sentence_2):
tf_1 = Counter(self.tokenize_sentence(sentence_1))
tf_2 = Counter(self.tokenize_sentence(sentence_2))
similarity = self._idf_modified_cosine([tf_1, tf_2], 0, 1)
return similarity
def tokenize_sentence(self, sentence):
tokens = tokenize(
sentence,
self.stopwords,
keep_numbers=self.keep_numbers,
keep_emails=self.keep_emails,
keep_urls=self.keep_urls,
)
return tokens
def _calculate_idf(self, documents):
bags_of_words = []
for doc in documents:
doc_words = set()
for sentence in doc:
words = self.tokenize_sentence(sentence)
doc_words.update(words)
if doc_words:
bags_of_words.append(doc_words)
if not bags_of_words:
raise ValueError('documents are not informative')
doc_number_total = len(bags_of_words)
if self.include_new_words:
default_value = math.log(doc_number_total + 1)
else:
default_value = 0
idf_score = defaultdict(lambda: default_value)
for word in set.union(*bags_of_words):
doc_number_word = sum(1 for bag in bags_of_words if word in bag)
idf_score[word] = math.log(doc_number_total / doc_number_word)
return idf_score
def _calculate_similarity_matrix(self, tf_scores):
length = len(tf_scores)
similarity_matrix = np.zeros([length] * 2)
for i in range(length):
for j in range(i, length):
similarity = self._idf_modified_cosine(tf_scores, i, j)
if similarity:
similarity_matrix[i, j] = similarity
similarity_matrix[j, i] = similarity
return similarity_matrix
def _idf_modified_cosine(self, tf_scores, i, j):
if i == j:
return 1
tf_i, tf_j = tf_scores[i], tf_scores[j]
words_i, words_j = set(tf_i.keys()), set(tf_j.keys())
nominator = 0
for word in words_i & words_j:
idf = self.idf_score[word]
nominator += tf_i[word] * tf_j[word] * idf ** 2
if math.isclose(nominator, 0):
return 0
denominator_i, denominator_j = 0, 0
for word in words_i:
tfidf = tf_i[word] * self.idf_score[word]
denominator_i += tfidf ** 2
for word in words_j:
tfidf = tf_j[word] * self.idf_score[word]
denominator_j += tfidf ** 2
similarity = nominator / math.sqrt(denominator_i * denominator_j)
return similarity
def _markov_matrix(self, weights_matrix):
n_1, n_2 = weights_matrix.shape
if n_1 != n_2:
raise ValueError('\'weights_matrix\' should be square')
row_sum = weights_matrix.sum(axis=1, keepdims=True)
return weights_matrix / row_sum
def _markov_matrix_discrete(self, weights_matrix, threshold):
discrete_weights_matrix = np.zeros(weights_matrix.shape)
ixs = np.where(weights_matrix >= threshold)
discrete_weights_matrix[ixs] = 1
return self._markov_matrix(discrete_weights_matrix)
def getMarkovMatrix(self, similarity_matrix, threshold):
""""""
if threshold is None:
markov_matrix = self._markov_matrix(similarity_matrix)
else:
markov_matrix = self._markov_matrix_discrete(
similarity_matrix,
threshold=threshold,
)
return markov_matrix
class NeuralRank:
def __init__(
self,
ldaModel,
stopwords=None,
keep_numbers=False,
keep_emails=False,
keep_urls=False,
include_new_words=True,
):
if stopwords is None:
self.stopwords = set()
else:
self.stopwords = stopwords
self.keep_numbers = keep_numbers
self.keep_emails = keep_emails
self.keep_urls = keep_urls
self.include_new_words = include_new_words
self.ldaModel = gensim.models.ldamodel.LdaModel.load(ldaModel)
self.topickeys = getTopicKeys(self.ldaModel)
#self.idf_score = self._calculate_idf(documents)
def get_summary(
self,
sentences,
summary_size=1,
threshold=.03,
fast_power_method=True,
):
if not isinstance(summary_size, int) or summary_size < 1:
raise ValueError('\'summary_size\' should be a positive integer')
lex_scores = self.rank_sentences(
sentences,
threshold=threshold,
fast_power_method=fast_power_method,
)
sorted_ix = np.argsort(lex_scores)[::-1]
summary = [sentences[i] for i in sorted_ix[:summary_size]]
return summary
def getRankedParagraphs(self, paraFullText, paraPreprocBoW, d, K, useNTtopics, threshold, topicVectors=None):
"""
:param paraFullText: a list of strings, i.e. each is a paragraph
:param paraPreprocBoW: a list of lists of words, i.e. list of words in a paragraph
:return:
"""
scores = self.rankParagraph(paraFullText, paraPreprocBoW, d, K, useNTtopics, threshold, topicVectors=topicVectors)
sortedIndex = np.argsort(scores)[::-1]
if paraPreprocBoW is not None:
return [paraFullText[i][0] for i in sortedIndex], [paraPreprocBoW[i] for i in sortedIndex]
else:
return [paraFullText[i][0] for i in sortedIndex], None
def getTopicDistrib(self, paraPreprocBoW, K, useNTtopics):
""""""
return topicDistrib(paraPreprocBoW, self.ldaModel, K, useNTtopics, self.topickeys)
def rankParagraph(self, paraFullText, paraPreprocBoW, d, K, useNTtopics, threshold, fast_power_method=True, topicVectors=None):
""""""
assert len(paraFullText)==(len(topicVectors) if topicVectors else len(paraPreprocBoW))
if topicVectors:
if not useNTtopics:
topic_scores = topicVectors
else:
# use onlly top N topics
topic_scores = []
for tv in topicVectors:
max_n_idx = tv.argsort()[-useNTtopics:]
top_tv = np.zeros(tv.shape)
for i in max_n_idx:
top_tv[i] = tv[i]
topic_scores.append(top_tv)
assert len(tv)==len(top_tv)
else:
topic_scores= topicDistrib(paraPreprocBoW, self.ldaModel, K, useNTtopics, self.topickeys)
similarity_matrix = self._calculate_topic_similarity_matrix(topic_scores)
query_relevance = np.zeros([len(topic_scores)] * 2)
for i, (p,s) in enumerate(paraFullText):
query_relevance[:,i] = s
row_sum = query_relevance.sum(axis=1, keepdims=True)
query_relevance = query_relevance / row_sum
if threshold is None:
markov_matrix = self._markov_matrix(similarity_matrix)
else:
markov_matrix = self._markov_matrix_discrete(
similarity_matrix,
threshold=threshold,
)
Q = ( d * query_relevance ) + ( (1-d) * markov_matrix)
scores = stationary_distribution(
Q,
increase_power=fast_power_method,
normalized=False,
)
#print("scores")
#print(scores)
return scores
def rankParagraphSearchMatrix(self, paraFullText, paraPreprocBoW, K, useNTtopics, topicVectors=None):
""""""
assert len(paraFullText)==(len(topicVectors) if topicVectors else len(paraPreprocBoW)), \
"{}/{}".format(len(paraFullText), (len(topicVectors) if topicVectors else len(paraPreprocBoW)))
if topicVectors:
if not useNTtopics:
topic_scores = topicVectors
else:
# use onlly top N topics
topic_scores = []
for tv in topicVectors:
max_n_idx = tv.argsort()[-useNTtopics:]
top_tv = np.zeros(tv.shape)
for i in max_n_idx:
top_tv[i] = tv[i]
topic_scores.append(top_tv)
assert len(tv)==len(top_tv)
else:
topic_scores= topicDistrib(paraPreprocBoW, self.ldaModel, K, useNTtopics, self.topickeys)
similarity_matrix = self._calculate_topic_similarity_matrix(topic_scores)
query_relevance = np.zeros([len(topic_scores)] * 2)
for i, (p,s) in enumerate(paraFullText):
query_relevance[:,i] = s
row_sum = query_relevance.sum(axis=1, keepdims=True)
query_relevance = query_relevance / row_sum
return similarity_matrix, query_relevance
def getMarkovMatrix(self, similarity_matrix, threshold):
""""""
if threshold is None:
markov_matrix = self._markov_matrix(similarity_matrix)
else:
markov_matrix = self._markov_matrix_discrete(
similarity_matrix,
threshold=threshold,
)
return markov_matrix
def getRankedScores(self, paraFullText, markov_matrix, query_relevance, d, fast_power_method=True):
""""""
Q = ( d * query_relevance ) + ( (1-d) * markov_matrix)
scores = stationary_distribution(
Q,
increase_power=fast_power_method,
normalized=False,
)
#print("scores")
#print(scores)
sortedIndex = np.argsort(scores)[::-1]
return [paraFullText[i][0] for i in sortedIndex]
def rank_sentences(
self,
sentences,
threshold=.03,
fast_power_method=True,
):
if not (
threshold is None or
isinstance(threshold, float) and 0 <= threshold < 1
):
raise ValueError(
'\'threshold\' should be a floating-point number '
'from the interval [0, 1) or None',
)
tf_scores = [
Counter(self.tokenize_sentence(sentence)) for sentence in sentences
]
similarity_matrix = self._calculate_similarity_matrix(tf_scores)
if threshold is None:
markov_matrix = self._markov_matrix(similarity_matrix)
else:
markov_matrix = self._markov_matrix_discrete(
similarity_matrix,
threshold=threshold,
)
scores = stationary_distribution(
markov_matrix,
increase_power=fast_power_method,
normalized=False,
)
return scores
def sentences_similarity(self, sentence_1, sentence_2):
tf_1 = Counter(self.tokenize_sentence(sentence_1))
tf_2 = Counter(self.tokenize_sentence(sentence_2))
similarity = self._idf_modified_cosine([tf_1, tf_2], 0, 1)
return similarity
def tokenize_sentence(self, sentence):
tokens = tokenize(
sentence,
self.stopwords,
keep_numbers=self.keep_numbers,
keep_emails=self.keep_emails,
keep_urls=self.keep_urls,
)
return tokens
def _calculate_idf(self, documents):
bags_of_words = []
for doc in documents:
doc_words = set()
for sentence in doc:
words = self.tokenize_sentence(sentence)
doc_words.update(words)
if doc_words:
bags_of_words.append(doc_words)
if not bags_of_words:
raise ValueError('documents are not informative')
doc_number_total = len(bags_of_words)
if self.include_new_words:
default_value = math.log(doc_number_total + 1)
else:
default_value = 0
idf_score = defaultdict(lambda: default_value)
for word in set.union(*bags_of_words):
doc_number_word = sum(1 for bag in bags_of_words if word in bag)
idf_score[word] = math.log(doc_number_total / doc_number_word)
return idf_score
def _calculate_similarity_matrix(self, tf_scores):
length = len(tf_scores)
similarity_matrix = np.zeros([length] * 2)
for i in range(length):
for j in range(i, length):
similarity = self._idf_modified_cosine(tf_scores, i, j)
if similarity:
similarity_matrix[i, j] = similarity
similarity_matrix[j, i] = similarity
return similarity_matrix
def _idf_modified_cosine(self, tf_scores, i, j):
if i == j:
return 1
tf_i, tf_j = tf_scores[i], tf_scores[j]
words_i, words_j = set(tf_i.keys()), set(tf_j.keys())
nominator = 0
for word in words_i & words_j:
idf = self.idf_score[word]
nominator += tf_i[word] * tf_j[word] * idf ** 2
if math.isclose(nominator, 0):
return 0
denominator_i, denominator_j = 0, 0
for word in words_i:
tfidf = tf_i[word] * self.idf_score[word]
denominator_i += tfidf ** 2
for word in words_j:
tfidf = tf_j[word] * self.idf_score[word]
denominator_j += tfidf ** 2
similarity = nominator / math.sqrt(denominator_i * denominator_j)
return similarity
def _calculate_topic_similarity_matrix(self, topic_scores):
length = len(topic_scores)
similarity_matrix = np.zeros([length] * 2)
for i in range(length):
for j in range(i, length):
similarity = self._topic_similarity(topic_scores, i, j)
#print("{},{}\t{}".format(i,j,similarity))
if similarity:
similarity_matrix[i, j] = similarity
similarity_matrix[j, i] = similarity
return similarity_matrix
def _topic_similarity(self, topic_scores, i, j):
if i == j:
#return 1
return 0
# Jensen-Shannon similarity measurer
return JSD(topic_scores[i], topic_scores[j])
#return max(1 - JSD(topic_scores[i], topic_scores[j]), 0)
def _markov_matrix(self, similarity_matrix):
row_sum = similarity_matrix.sum(axis=1, keepdims=True)
similarity_matrix = 1 - (similarity_matrix / row_sum)
row_sum = similarity_matrix.sum(axis=1, keepdims=True)
return similarity_matrix / row_sum
def _markov_matrix_discrete(self, similarity_matrix, threshold):
markov_matrix = np.zeros(similarity_matrix.shape)
for i in range(len(similarity_matrix)):
#columns = np.where(similarity_matrix[i] > threshold)[0]
columns = np.where(similarity_matrix[i] < threshold)[0]
markov_matrix[i, columns] = 1 / len(columns)
#print( 1 / len(columns))
#exit()
return markov_matrix
| 29.38245
| 131
| 0.591255
| 2,014
| 17,747
| 4.956802
| 0.093843
| 0.075328
| 0.021036
| 0.022037
| 0.837624
| 0.832215
| 0.8236
| 0.796754
| 0.761394
| 0.75298
| 0
| 0.008592
| 0.324506
| 17,747
| 603
| 132
| 29.431177
| 0.824157
| 0.032682
| 0
| 0.819512
| 0
| 0
| 0.016223
| 0
| 0
| 0
| 0
| 0
| 0.009756
| 1
| 0.073171
| false
| 0
| 0.019512
| 0
| 0.180488
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
8435aee0e75e7d180ca1f9b15ebdbae593028741
| 4,844
|
py
|
Python
|
tests/test_judg_list.py
|
tanjie123/hello-ltr
|
fe1ad1989e1bb17dfc8d1c09931480becf59766e
|
[
"Apache-2.0"
] | 109
|
2019-04-18T01:24:29.000Z
|
2022-03-12T17:37:30.000Z
|
tests/test_judg_list.py
|
tanjie123/hello-ltr
|
fe1ad1989e1bb17dfc8d1c09931480becf59766e
|
[
"Apache-2.0"
] | 63
|
2019-04-14T01:01:24.000Z
|
2022-03-03T20:48:41.000Z
|
tests/test_judg_list.py
|
tanjie123/hello-ltr
|
fe1ad1989e1bb17dfc8d1c09931480becf59766e
|
[
"Apache-2.0"
] | 41
|
2019-04-22T15:22:41.000Z
|
2022-02-26T00:03:02.000Z
|
import unittest
def clean_jl(judg_list_str):
import textwrap
dedented=textwrap.dedent(judg_list_str)[1:]
return dedented
class JudgmentsTestCase(unittest.TestCase):
def test_string_io_unsorted_throws(self):
judgment_list=clean_jl("""
# qid:1: rambo*1
# qid:2: rocky ii*1
1 qid:2 # 9876 rocky ii
4 qid:1 # 1234 rambo
3 qid:1 # 5670 rambo""")
from ltr.judgments import judgments_reader
from io import StringIO
judg_string_io=StringIO(judgment_list)
with self.assertRaises(ValueError):
with judgments_reader(judg_string_io) as judg_list:
for j in judg_list:
print(j)
def test_string_io_read(self):
judgment_list=clean_jl("""
# qid:1: rambo*1
# qid:2: rocky ii*1
4 qid:1 # 1234 rambo
3 qid:1 # 5670 rambo
1 qid:2 # 9876 rocky ii""")
from ltr.judgments import judgments_reader
from io import StringIO
judg_string_io=StringIO(judgment_list)
read_judgments=0
with judgments_reader(judg_string_io) as judg_list:
from itertools import groupby
for qid, query_judgments in groupby(judg_list, key=lambda j: j.qid):
query_judgments = [j for j in query_judgments]
read_judgments += len(query_judgments)
if qid == 1:
self.assertEqual(len(query_judgments),2)
for j in query_judgments:
self.assertEqual(j.keywords,'rambo')
self.assertEqual(j.qid,qid)
if j.docId == '1234':
self.assertEqual(j.grade, 4)
elif j.docId == '5670':
self.assertEqual(j.grade, 3)
else:
print("DocID:{} should not be present in qid:{}".format(j.docId, qid))
assert False
if qid == 2:
self.assertEqual(len(query_judgments),1)
for j in query_judgments:
self.assertEqual(j.keywords,'rocky ii')
self.assertEqual(j.qid, qid)
if j.docId == '9876':
self.assertEqual(j.grade,1)
else:
self.fail("DocID:{} should not be present in qid:{}".format(j.docId, qid))
self.assertEqual(read_judgments,3)
def test_write_read(self):
from ltr.judgments import judgments_open, Judgment
import tempfile
import os
temp_path=tempfile.gettempdir()
judgment_file=os.path.join(temp_path, 'judgments.txt')
print(judgment_file)
with judgments_open(judgment_file, 'w') as judg_list:
judg_list.write(judgment=Judgment(keywords='rambo', qid=1, grade=4, docId=1234))
judg_list.write(judgment=Judgment(keywords='rambo', qid=1, grade=3, docId=5670))
judg_list.write(judgment=Judgment(keywords='rocky ii', qid=2, grade=1, docId=9876))
read_judgments=0
with judgments_open(judgment_file, 'r') as judg_list:
from itertools import groupby
for qid, query_judgments in groupby(judg_list, key=lambda j: j.qid):
query_judgments = [j for j in query_judgments]
read_judgments += len(query_judgments)
if qid == 1:
self.assertEqual(len(query_judgments),2)
for j in query_judgments:
self.assertEqual(j.keywords,'rambo')
self.assertEqual(j.qid,qid)
if j.docId == '1234':
self.assertEqual(j.grade, 4)
elif j.docId == '5670':
self.assertEqual(j.grade, 3)
else:
print("DocID:{} should not be present in qid:{}".format(j.docId, qid))
assert False
if qid == 2:
self.assertEqual(len(query_judgments),1)
for j in query_judgments:
self.assertEqual(j.keywords,'rocky ii')
self.assertEqual(j.qid, qid)
if j.docId == '9876':
self.assertEqual(j.grade,1)
else:
self.fail("DocID:{} should not be present in qid:{}".format(j.docId, qid))
self.assertEqual(read_judgments,3)
if __name__ == "__main__":
unittest.main()
| 41.050847
| 102
| 0.50929
| 536
| 4,844
| 4.451493
| 0.154851
| 0.125733
| 0.093881
| 0.027661
| 0.810562
| 0.761526
| 0.732607
| 0.732607
| 0.732607
| 0.702431
| 0
| 0.036219
| 0.401528
| 4,844
| 117
| 103
| 41.401709
| 0.786823
| 0
| 0
| 0.707071
| 0
| 0
| 0.141412
| 0
| 0
| 0
| 0
| 0
| 0.232323
| 1
| 0.040404
| false
| 0
| 0.111111
| 0
| 0.171717
| 0.040404
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
ffc1a6d1e7009ade00635ac4c48888cb16f477b1
| 23,513
|
py
|
Python
|
Support.records/Run.Time.Evaluation/Calculate.RunTime.Simulated.py
|
mills-lab/svelter
|
d318b06d588483fe8a8ebcac8c8a6c7878f2c2b3
|
[
"MIT"
] | 21
|
2015-11-02T06:31:52.000Z
|
2021-12-20T03:14:04.000Z
|
Support.records/Run.Time.Evaluation/Calculate.RunTime.Simulated.py
|
mills-lab/svelter
|
d318b06d588483fe8a8ebcac8c8a6c7878f2c2b3
|
[
"MIT"
] | 14
|
2016-03-02T21:12:53.000Z
|
2019-08-02T20:01:02.000Z
|
Support.records/Run.Time.Evaluation/Calculate.RunTime.Simulated.py
|
mills-lab/svelter
|
d318b06d588483fe8a8ebcac8c8a6c7878f2c2b3
|
[
"MIT"
] | 6
|
2015-08-19T18:33:02.000Z
|
2017-05-16T03:42:57.000Z
|
def read_in_run_time(log_file):
fin=os.popen(r'''head -1 %s'''%(log_file))
pin=fin.readline().strip().split()
start=float(pin[0])
fin.close()
fin=os.popen(r'''tail -1 %s'''%(log_file))
pin=fin.readline().strip().split()
end=float(pin[0])
fin.close()
return [end-start]
def chromos_readin(ref):
fin=open(ref+'.fai')
chromos=[]
for line in fin:
pin=line.strip().split()
chromos.append(pin[0])
fin.close()
return chromos
import os
ppre='/scratch/remills_flux/xuefzhao/Simulation.Xuefang/Simulate.FussyJunc/'
#Het
run_time_hash={}
#Delly
het=ppre+'Simulate.het/pbs/'
delly_path=het+'pbs_Delly/'
run_time_hash['delly']={}
for k1 in os.listdir(delly_path):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[1]
if not RD in run_time_hash['delly'].keys():
run_time_hash['delly'][RD]=[read_in_run_time(delly_path+k1)]
else:
run_time_hash['delly'][RD]+=[read_in_run_time(delly_path+k1)]
#Lumpy
lumpy_path=het+'pbs_Lumpy/'
lumpy_path_1=lumpy_path+'Prepare.Ab.Reads.axiom/'
lumpy_path_2=lumpy_path+'Lumpy2/'
run_time_hash['lumpy']={}
for k1 in os.listdir(lumpy_path_1):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-5]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_1+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_1+k1)]
for k1 in os.listdir(lumpy_path_2):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-4]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_2+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_2+k1)]
#SVelter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#SVelter_Deter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter_deterministic']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter_deterministic'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4_deterministic/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4_deterministic/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#pindel
pindel_path=het+'pbs_Pindel/'
pindel_path_1=pindel_path+'pbs_Pindel_step1/'
pindel_path_2=pindel_path+'pbs_Pindel_step2/'
run_time_hash['pindel']={}
for k1 in os.listdir(pindel_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['pindel'][chromo_name]=[read_in_run_time(pindel_path_1+k1)]
for k1 in os.listdir(pindel_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-2]
if chromo_name in run_time_hash['pindel'].keys():
run_time_hash['pindel'][chromo_name]+=[read_in_run_time(pindel_path_2+k1)]
#erds
erds_path=het+'pbs_erds/'
erds_path_1=erds_path+'pbs_erders_step3_erds/'
run_time_hash['erds']={}
for k1 in os.listdir(erds_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['erds'][chromo_name]=[read_in_run_time(erds_path_1+k1)]
erds_path_2=erds_path+'pbs_erders_step2_SNPs_calling/'
run_time_hash['erds_SNP']={}
for k1 in os.listdir(erds_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['erds_SNP'][chromo_name]=[read_in_run_time(erds_path_2+k1)]
algorithms=run_time_hash.keys()
rds=sorted(run_time_hash['delly'].keys())
fo=open(ppre+'Run_time_Sumi','w')
print >>fo,' '.join(['het']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([sum(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo,' '.join([k1]+[str(i) for i in test])
print >>fo,' '.join(['het_Paralelle']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([max(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo, ' '.join([k1]+[str(i) for i in test])
fo.close()
#Homo
run_time_hash={}
#Delly
het=ppre+'Simulate.homo/pbs/'
delly_path=het+'pbs_Delly/'
run_time_hash['delly']={}
for k1 in os.listdir(delly_path):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[1]
if not RD in run_time_hash['delly'].keys():
run_time_hash['delly'][RD]=[read_in_run_time(delly_path+k1)]
else:
run_time_hash['delly'][RD]+=[read_in_run_time(delly_path+k1)]
#Lumpy
lumpy_path=het+'pbs_Lumpy/'
lumpy_path_1=lumpy_path+'Prepare.Ab.Reads.axiom/'
lumpy_path_2=lumpy_path+'Lumpy2/'
run_time_hash['lumpy']={}
for k1 in os.listdir(lumpy_path_1):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-5]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_1+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_1+k1)]
for k1 in os.listdir(lumpy_path_2):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-4]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_2+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_2+k1)]
#SVelter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#SVelter_Deter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter_deterministic']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter_deterministic'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4_deterministic/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4_deterministic/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#pindel
pindel_path=het+'pbs_Pindel/'
pindel_path_1=pindel_path+'pbs_Pindel_step1/'
pindel_path_2=pindel_path+'pbs_Pindel_step2/'
run_time_hash['pindel']={}
for k1 in os.listdir(pindel_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['pindel'][chromo_name]=[read_in_run_time(pindel_path_1+k1)]
for k1 in os.listdir(pindel_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-2]
if chromo_name in run_time_hash['pindel'].keys():
run_time_hash['pindel'][chromo_name]+=[read_in_run_time(pindel_path_2+k1)]
#erds
erds_path=het+'pbs_erds/'
erds_path_1=erds_path+'pbs_erders_step3_erds/'
run_time_hash['erds']={}
for k1 in os.listdir(erds_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['erds'][chromo_name]=[read_in_run_time(erds_path_1+k1)]
erds_path_2=erds_path+'pbs_erders_step2_SNPs_calling/'
run_time_hash['erds_SNP']={}
for k1 in os.listdir(erds_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['erds_SNP'][chromo_name]=[read_in_run_time(erds_path_2+k1)]
fo=open(ppre+'Run_time_Sumi','a')
print >>fo,' '.join(['homo']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([sum(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo,' '.join([k1]+[str(i) for i in test])
print >>fo,' '.join(['homo_Paralelle']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([max(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo, ' '.join([k1]+[str(i) for i in test])
fo.close()
#Comp Het
run_time_hash={}
#Delly
het=ppre+'Simulate.comp.het/pbs/'
delly_path=het+'pbs_Delly/'
run_time_hash['delly']={}
for k1 in os.listdir(delly_path):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[2]
if not RD in run_time_hash['delly'].keys():
run_time_hash['delly'][RD]=[read_in_run_time(delly_path+k1)]
else:
run_time_hash['delly'][RD]+=[read_in_run_time(delly_path+k1)]
#Lumpy
lumpy_path=het+'pbs_Lumpy/'
lumpy_path_1=lumpy_path+'Prepare.Ab.Reads.axiom/'
lumpy_path_2=lumpy_path+'Lumpy2/'
run_time_hash['lumpy']={}
for k1 in os.listdir(lumpy_path_1):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-5]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_1+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_1+k1)]
for k1 in os.listdir(lumpy_path_2):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-4]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_2+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_2+k1)]
#SVelter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#SVelter_Deter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter_deterministic']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter_deterministic'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4_deterministic/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4_deterministic/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#pindel
pindel_path=het+'pbs_Pindel/'
pindel_path_1=pindel_path+'pbs_Pindel_step1/'
pindel_path_2=pindel_path+'pbs_Pindel_step2/'
run_time_hash['pindel']={}
for k1 in os.listdir(pindel_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['pindel'][chromo_name]=[read_in_run_time(pindel_path_1+k1)]
for k1 in os.listdir(pindel_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-2]
if chromo_name in run_time_hash['pindel'].keys():
run_time_hash['pindel'][chromo_name]+=[read_in_run_time(pindel_path_2+k1)]
#erds
erds_path=het+'pbs_erds/'
erds_path_1=erds_path+'pbs_erders_step3_erds/'
run_time_hash['erds']={}
for k1 in os.listdir(erds_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['erds'][chromo_name]=[read_in_run_time(erds_path_1+k1)]
erds_path_2=erds_path+'pbs_erders_step2_SNPs_calling/'
run_time_hash['erds_SNP']={}
for k1 in os.listdir(erds_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['erds_SNP'][chromo_name]=[read_in_run_time(erds_path_2+k1)]
algorithms=run_time_hash.keys()
rds=sorted(run_time_hash['delly'].keys())
fo=open(ppre+'Run_time_Sumi','a')
print >>fo,' '.join(['comp.het']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([sum(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo,' '.join([k1]+[str(i) for i in test])
print >>fo,' '.join(['comp.het_Paralelle']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([max(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo, ' '.join([k1]+[str(i) for i in test])
fo.close()
#Comp Homo
run_time_hash={}
#Delly
het=ppre+'Simulate.comp.homo/pbs/'
delly_path=het+'pbs_Delly/'
run_time_hash['delly']={}
for k1 in os.listdir(delly_path):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[3]
if not RD in run_time_hash['delly'].keys():
run_time_hash['delly'][RD]=[read_in_run_time(delly_path+k1)]
else:
run_time_hash['delly'][RD]+=[read_in_run_time(delly_path+k1)]
#Lumpy
lumpy_path=het+'pbs_Lumpy/'
lumpy_path_1=lumpy_path+'Prepare.Ab.Reads.axiom/'
lumpy_path_2=lumpy_path+'Lumpy2/'
run_time_hash['lumpy']={}
for k1 in os.listdir(lumpy_path_1):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-5]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_1+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_1+k1)]
for k1 in os.listdir(lumpy_path_2):
if k1.split('.')[-1]=='log':
RD=k1.split('.')[-4]
if not RD in run_time_hash['lumpy'].keys():
run_time_hash['lumpy'][RD]=[read_in_run_time(lumpy_path_2+k1)]
else:
run_time_hash['lumpy'][RD]+=[read_in_run_time(lumpy_path_2+k1)]
#SVelter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#SVelter_Deter
svelter_path=het+'pbs_SVelter/'
run_time_hash['svelter_deterministic']={}
for k1 in os.listdir(svelter_path+'SVelter1/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name]=[read_in_run_time(svelter_path+'SVelter1/'+k1),[]]
for k1 in os.listdir(svelter_path+'SVelter2/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter2/'+k1)
for k1 in os.listdir(svelter_path+'SVelter3/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter3/'+k1))
run_time_hash['svelter_deterministic'][chromo_name].append([])
for k1 in os.listdir(svelter_path+'SVelter4_deterministic/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name][-1]+=read_in_run_time(svelter_path+'SVelter4_deterministic/'+k1)
for k1 in os.listdir(svelter_path+'SVelter5/'):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['svelter_deterministic'][chromo_name].append(read_in_run_time(svelter_path+'SVelter5/'+k1))
#pindel
pindel_path=het+'pbs_Pindel/'
pindel_path_1=pindel_path+'pbs_Pindel_step1/'
pindel_path_2=pindel_path+'pbs_Pindel_step2/'
run_time_hash['pindel']={}
for k1 in os.listdir(pindel_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['pindel'][chromo_name]=[read_in_run_time(pindel_path_1+k1)]
for k1 in os.listdir(pindel_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-2]
if chromo_name in run_time_hash['pindel'].keys():
run_time_hash['pindel'][chromo_name]+=[read_in_run_time(pindel_path_2+k1)]
#erds
erds_path=het+'pbs_erds/'
erds_path_1=erds_path+'pbs_erders_step3_erds/'
run_time_hash['erds']={}
for k1 in os.listdir(erds_path_1):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-5]
run_time_hash['erds'][chromo_name]=[read_in_run_time(erds_path_1+k1)]
erds_path_2=erds_path+'pbs_erders_step2_SNPs_calling/'
run_time_hash['erds_SNP']={}
for k1 in os.listdir(erds_path_2):
if k1.split('.')[-1]=='log':
chromo_name=k1.split('.')[-4]
run_time_hash['erds_SNP'][chromo_name]=[read_in_run_time(erds_path_2+k1)]
algorithms=run_time_hash.keys()
rds=sorted(run_time_hash['delly'].keys())
fo=open(ppre+'Run_time_Sumi','a')
print >>fo,' '.join(['comp.homo']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([sum(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo,' '.join([k1]+[str(i) for i in test])
print >>fo,' '.join(['comp.homo_Paralelle']+algorithms)
for k1 in rds:
test=[]
for k2 in algorithms:
if k1 in run_time_hash[k2].keys():
test.append(sum([max(i) for i in run_time_hash[k2][k1]])/3600)
else:
test.append('*')
print >>fo, ' '.join([k1]+[str(i) for i in test])
fo.close()
| 36.624611
| 127
| 0.641645
| 3,642
| 23,513
| 3.836079
| 0.028281
| 0.121752
| 0.124401
| 0.07537
| 0.982607
| 0.978455
| 0.978455
| 0.978455
| 0.968005
| 0.963281
| 0
| 0.035861
| 0.159146
| 23,513
| 641
| 128
| 36.681747
| 0.67078
| 0.007825
| 0
| 0.941176
| 0
| 0
| 0.147811
| 0.050901
| 0
| 0
| 0
| 0
| 0
| 1
| 0.003922
| false
| 0
| 0.001961
| 0
| 0.009804
| 0.031373
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
f291283ddc7db4b6a4bf2deb4cb3ccfaafda1ac7
| 7,481
|
py
|
Python
|
test/create_keystore.py
|
unification-com/haiku-node-prototype
|
ea77aa90f6b3f08d004be1c24e6b8d62e83bc66b
|
[
"MIT"
] | 3
|
2018-06-15T18:02:05.000Z
|
2018-07-06T02:32:18.000Z
|
test/create_keystore.py
|
unification-com/haiku-node-prototype
|
ea77aa90f6b3f08d004be1c24e6b8d62e83bc66b
|
[
"MIT"
] | 4
|
2018-08-17T06:51:34.000Z
|
2018-08-17T08:39:24.000Z
|
test/create_keystore.py
|
unification-com/haiku-node-prototype
|
ea77aa90f6b3f08d004be1c24e6b8d62e83bc66b
|
[
"MIT"
] | null | null | null |
import os
from pathlib import Path
import click
from cryptography.fernet import Fernet
from haiku_node.keystore.keystore import UnificationKeystore
keystore = {
'app1': {
'private_key': '-----BEGIN RSA PRIVATE KEY-----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\nCTpjvpXSgbCt5ZUcHsMWDpQIPpxhORxwg//D+5ysQBYweGX1/qsojw==\n-----END RSA PRIVATE KEY-----\n', # noqa
'public_key': '-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEApakS8qunhjD+/rLhs90s\nX4QIh7qWV/6kirBF6plZZHBUHQUz90nZQH0zl0feneHXxOEvm1ogLkLtj8qqByzU\nl7mvzsEdGvtn2AuZt6WzkCThKyhQoVU3GVG48xUz8YviR/CruUSlPFeg0DT67IEW\n3iKYsLWxr9R4D+W5ffRk92/s41Tu6b1n4KobTyzvvFSzKlJo6I9a7M4ZvyikWQQr\ni0MUyezMzjDgYNXueGG8gX2VP7OQbvPMb40okN4J3G2gmj9SXf89o8pPDAnk3c1f\nl1RJ25MjZcVCLFMnI6PBIleCjmtV5YqgFznCyLXFcfqieiMb0sPRqhrmB77WjWzV\nnwIDAQAB\n-----END PUBLIC KEY-----\n', # noqa
},
'app2': {
'private_key': '-----BEGIN RSA PRIVATE KEY-----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\nYbZ54bknWfUyBENKm/a2sI7+4wcB20atHELAXGyUmLBqrUtT0Gs=\n-----END RSA PRIVATE KEY-----\n', # noqa
'public_key': '-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAyC/fG5vnBrGwarNkxgLd\nYEvYcvmRcC9XnW+h/xLtwlGALlVx+1R+MzxcmOTxYzoPAlWKyDlsWp3iNkA0twcR\ny5S5Sz1NilUwVNNWjaPVAbuab/Bo98wVdYHhVc4Jq5honvX/mXp/E+UjWPgWbjrv\nNtRTM+LfeEi5680rA/q5EfPxUr2Z13Z0pr97opGtYCt7Eo0QEIQctQ6t/o2ZDEcv\nCLKV+gCvWZoSgO98uld3hHXdG2W8+DlthJZpZo0kLIDdlVohHNDQfdlTlcTdZwGN\n+KfNIfhCjr9osB1jQiaprDrL2M0wjb3V7CcdS6CQ8xtILAeZJ36R0+DMjZP0Mu+U\nfQIDAQAB\n-----END PUBLIC KEY-----\n', # noqa
},
'app3': {
'private_key': '-----BEGIN RSA PRIVATE KEY-----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\nWdy0Lvb3CTr24H9YXqYXfJ6hcMMjeG2UbpYccD1ObzRjsJ1ibH0yl3J1\n-----END RSA PRIVATE KEY-----\n', # noqa
'public_key': '-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA4QwOP1q93KCKLbasK4yv\nOW5+ZjjO5SAhGr5Qa4C4AawZ5+ndKpQZO9ntlYEgA/v4Q4URMOZMYVYSngrJoN7P\nWUuHDuVzqaaU6wotCtW9q0DarM/zgQxtDYkatre5jmyah2cACisDuJ5LVWbx1V/S\n/+/6v+Z2GYQUsBi/cpv322a82wDjHd8G1WYmOpprypM4BPpsjd0W/sgLFqPT0zqY\nCeoXMfchzW6SBSGeR2tJ3xC3+227yJ2dzAOf3Te7a3YcPQEKvHYw5Nc+nuizO4Sp\ncWpBhpEZM3XoRGhCVZs5RuZAzj42Y01OLu0ASgPcOkmuZGvAz+ZejRF8rR1fOLDP\n4wIDAQAB\n-----END PUBLIC KEY-----\n' # noqa
}
}
def generate_keystore(app_name):
password = Fernet.generate_key()
click.echo(password)
current_path = Path(os.path.dirname(os.path.abspath(__file__)))
ks_path = current_path / Path(f'data/keys')
ks = UnificationKeystore(password, app_name=app_name, keystore_path=ks_path)
pub = keystore[app_name]['public_key']
priv = keystore[app_name]['private_key']
ks.set_rpc_auth_keys(pub, priv)
@click.command()
@click.argument('app_name')
def cli(app_name):
generate_keystore(app_name)
if __name__ == "__main__":
cli()
| 155.854167
| 1,739
| 0.895602
| 426
| 7,481
| 15.633803
| 0.652582
| 0.015015
| 0.011712
| 0.008108
| 0.040991
| 0.040991
| 0.02027
| 0.02027
| 0.02027
| 0.02027
| 0
| 0.119956
| 0.03275
| 7,481
| 47
| 1,740
| 159.170213
| 0.800442
| 0.003876
| 0
| 0
| 0
| 0.176471
| 0.888516
| 0.839221
| 0
| 1
| 0
| 0
| 0
| 1
| 0.058824
| false
| 0.088235
| 0.147059
| 0
| 0.205882
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
f2a591667f8f3b07bed645bd7b0cd94d33fe5b4a
| 101
|
py
|
Python
|
tests/parser/bug.48.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/bug.48.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/bug.48.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
input = """
x(X) :- X > 1, X < 3.%, #int(X).
"""
output = """
x(X) :- X > 1, X < 3.%, #int(X).
"""
| 14.428571
| 33
| 0.306931
| 18
| 101
| 1.722222
| 0.333333
| 0.258065
| 0.193548
| 0.258065
| 0.645161
| 0.645161
| 0.645161
| 0.645161
| 0
| 0
| 0
| 0.054795
| 0.277228
| 101
| 6
| 34
| 16.833333
| 0.369863
| 0
| 0
| 0.666667
| 0
| 0
| 0.686869
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
4b5744f28dc140ec65b63d69e4702452d9466718
| 143
|
py
|
Python
|
allennlp/common/__init__.py
|
lvyufeng/elmo_standalone
|
1bcafe17a8579bb9450ba937a0e6276ff6731259
|
[
"MIT"
] | null | null | null |
allennlp/common/__init__.py
|
lvyufeng/elmo_standalone
|
1bcafe17a8579bb9450ba937a0e6276ff6731259
|
[
"MIT"
] | null | null | null |
allennlp/common/__init__.py
|
lvyufeng/elmo_standalone
|
1bcafe17a8579bb9450ba937a0e6276ff6731259
|
[
"MIT"
] | null | null | null |
from allennlp.common.registrable import Registrable
from allennlp.common.tee_logger import TeeLogger
from allennlp.common.util import JsonDict
| 35.75
| 51
| 0.874126
| 19
| 143
| 6.526316
| 0.526316
| 0.290323
| 0.435484
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083916
| 143
| 3
| 52
| 47.666667
| 0.946565
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
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