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tests/unit/plotting_functions_tests/test_plot_gcfs.py create mode 100644 tests/unit/plotting_functions_tests/test_plot_get_cdict.py create mode 100644 tests/unit/plotting_functions_tests/test_plot_set_legend.py diff --git a/CONTRIBUTING.rst b/CONTRIBUTING.rst index cf778831..4daa5fb7 100644 --- a/CONTRIBUTING.rst +++ b/CONTRIBUTING.rst @@ -256,3 +256,160 @@ To generate the documentation locally: make html - Open `_build/html/index.html` in a browser. + +Use ChatGPT! +============ +Leverage the power of ChatGPT to optimize various facets of your software development process, +including code checking, interface optimization, and effective testing. + +Simply use the templates provided below and fill in the blank spaces between +``START OF CODE`` and ``END OF CODE`` with the specifics of your task. + +Due to the token limit of ChatGPT, the answers might not be complete. Use this prompt to continue the answer of ChatGPT: + +.. code-block:: none + + "Continue from where you left off." + +Code checking +------------- +For reviewing your code's logic, ensuring conciseness, and promoting clarity, try the following prompt: + +.. code-block:: none + + " + Analyze and evaluate the provided TARGET CODE to ensure it adheres to best coding practices and is free from logical errors. + + Inputs: + TARGET CODE: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: Identify vulnerabilities, inefficiencies, and areas of improvement. This is crucial. + + Requirements: + + 1. Syntax and Formatting: + - Ensure consistent indentation and formatting throughout. + - Use meaningful variable and function names. + - Avoid hard-coded values; suggest constants or configuration inputs if necessary. + + 2. Logic and Flow: + - Confirm that the logic flows correctly and efficiently. + - Identify any potential issues like infinite loops, off-by-one errors, or misused conditions. + + 3. Error Handling: + - Suggest robust error handling mechanisms. + - Highlight potential areas where exceptions might arise and are not currently handled. + + 4. General Guidelines: + - Suggest improvements for readability and maintainability. + - Do not leave any placeholders like "TODO", "Fix this", "Add ..." without suggestions. + - Offer potential refactorings if they simplify the code without losing clarity. + + Output Expectations: + - Detailed feedback on the TARGET CODE with line references. + - Suggestions for improvements and potential refactorings. + - Highlighted vulnerabilities and their proposed resolutions. + " + + + +Interface optimization +---------------------- +To enhance the public interface or signature of your functions and classes, employ the following prompt: + +.. code-block:: none + + " + Review and suggest improvements for the interface of the given TARGET FUNCTION to enhance its usability, clarity, and integration capabilities. + + Inputs: + TARGET FUNCTION: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: The interface should be intuitive, versatile, and easy for other developers to integrate and use. + + Requirements: + + 1. Signature Clarity: + - Ensure function/method names are descriptive and concise. + - Parameters should have clear names and, if possible, default values that make sense. + + 2. Documentation: + - Suggest comprehensive docstrings for the function. + - Propose comments for complex code blocks to aid understanding. + + 3. Return Values and Types: + - Advise on consistent return types, considering scenarios like error or null conditions. + - Recommend clear naming for returned objects, especially if using data structures like dictionaries or tuples. + + 4. General Guidelines: + - Avoid overloading the interface with too many parameters; suggest alternatives if needed. + - Consider common use cases and ensure they are easily achievable with the proposed interface. + - The interface should promote good coding practices and be resistant to misuse. + + Output Expectations: + - Feedback and suggestions on function/method signatures. + - Proposed docstrings and comments. + - Recommendations for ensuring a consistent and intuitive interface. + " + +Testing +------- +For generating efficient tests with extensive coverage and considering edge cases, utilize the prompt template below: + +.. code-block:: none + + " + Generate test functions for a given TARGET FUNCTION using the style of the provided TESTING TEMPLATE. + + Inputs: + TARGET FUNCTION: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + TESTING TEMPLATE: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: For the Normal Cases Test Class, EACH function MUST test ONLY ONE individual parameter of the TARGET FUNCTION using Hypothesis for property-based testing. This is crucial. + + Requirements: + + 1. Normal Cases Test Class: + - Name: 'Test[TARGET FUNCTION NAME]'. + - Objective: Test EACH parameter *INDIVIDUALLY*. + - Tests: For EACH parameter, at least 10 positive and 10 negative tests. + + 2. Complex Cases Test Class: + - Name: 'Test[TARGET FUNCTION NAME]Complex'. + - Objective: Test combinations of the TARGET FUNCTION parameters. + - Tests: At least 5 positive and 5 negative that intricately challenge the TARGET FUNCTION. + + 3. General Guidelines: + - Use Hypothesis for property-based testing, but test parameters individually for the Normal Cases Test Class . + - Tests should be clear, concise, and non-redundant. + - Do not leave any placeholders like "TODO", "Fill this", "Add ..." incomplete. + - Expose potential issues in the TARGET FUNCTION. + + Output Expectations: + - Two test classes: one for normal cases (individual parameters) and one for complex cases (combinations). + - In Normal Cases, one function = one parameter tested. + - Total: at least 30 unique tests, 150+ lines of code. + + Reminder: In Normal Cases, it's crucial to test parameters individually. + " diff --git a/README.rst b/README.rst index 7d80e3b8..bc114419 100644 --- a/README.rst +++ b/README.rst @@ -48,6 +48,8 @@ providing the following algorithms: Moreover, AAanalysis provides functions for loading protein benchmark datasets (**load_data**), amino acid scale sets (**load_scales**), and their in-depth two-level classification (**AAontology**). +If you are only looking for making publication-ready plots easily, see our `Plotting Prelude `. + Install ======= **AAanalysis** can be installed either from `PyPi `_ or @@ -61,14 +63,13 @@ Install Contributions ============= - -We welcome bug reports, feature requests, or updates on documentations and code. For details, refer to our -`CONTRIBUTING.rst `_. -Please email stephanbreimann@gmail.com for further questions or suggestions? +We appreciate bug reports, feature requests, or updates on documentation and code. For details, please refer to our +`CONTRIBUTING.rst `_. This guide includes +not only specifics related to `AAanalysis`, but also general software development hacks such as handy ChatGPT prompts. +For further questions or suggestions, please email stephanbreimann@gmail.com. Citations ========= - If you use 'AAanalysis' in your work, please cite the respective publication as follows: **AAclust**: diff --git a/aaanalysis/__pycache__/utils.cpython-39.pyc b/aaanalysis/__pycache__/utils.cpython-39.pyc index 353003d8678e8fc23833dff76bc824f0e76914e0..332f8c004fafe5420e4234420e05821c4afcd137 100644 GIT binary patch delta 2257 zcmZ`)U2s!H6lU|+aMLC&p@HcSErg~G0ZRH~2WKdxA+(kLq)8g!Qn+NYHzjS7hD}Oo z5fCYg6cAh)9mW}*L6q{NmN*O#px~?cz>A|-AL^SvIF5skBQLsVFKs|DnS42W&UbeA zoIQK?pUm-5bEK$9Sin9XxJu-+9p}sy=+unMsyTvNMHz1tV|bG|h&|$7+$P3l9oAs) zX@tXgGxklQV@MpD*KNaFa68uxbN57UTJyl*P_$mZU(^LVJbqE@^@J2*bEh{Xd3(Eh1ENut zJs~==@B-RQO9iLp1dAl2gLt%NL^^4=@M67}jhsl)X5_R}OMGmk7>OLgQZ%!lw1ZJg zn%EzC37~`C6zrBWOw7;ImHSzEs6$ujkCr=zUSI|2y>(WhpNXHsFidY3Z$Lr%sMu+E ztoX@NL473yuINY zS<88BUvXouYVm1=eDr#$9r@{l(gfN@TWu93BD0DMhmu%INeMYcVszNnYv=}_9(vbS zY61e00Ah63W<&4LzigvuJeOSZwZ_=T^wSy=q?^i?^TmDzVwet>UGxru2nR*>0>lCQ z0J{JZ0A&D428uqO!twz{2MJaTI6Iz}Gh~SNl{cEkfW$L+n7&!Q6n#f8m%Gu4i%Pks zI>2nxh&0So_+dbjwTO9z>7&YPoa98r{VYjPNppFtcGTKoMso65s)DQWmjYIt^9s2E9agiIaN|?%>g59 zie)84zo@A&)T{d0nn6}L9ga$Vmd&bi#PQ*V|Bn*Z$R8+7N{#}&3UCbIJoVSweA}3) z6vPsdY*tPwhDbUsr!ZLo1Slem^mpf>#UBItG6Qz6 z^_g@co_*rJ1=P^rUj_LnaH;tSsmir3kN|W=^qU5|)u|zz&rD1`&*ud&uFl!x?th|D9aNR~ z+_W~w=?qw7)~6#RoB2;o9#^>s8}^%~pELhS)qKCClD^PbXXkf?-@gk$e!9G;RPNEn zww;4u<%xjqq8NfQiL-9O-T5K#R>O;O2&g>o6(FqyfNtb0RE&`MQNkQQ2Q4q4F}kd& zKFl*a!IYv&ZS_1fu_zhOuxmRgsgYg>ug?Hrqb!Yl20j-rL9<$dbE^!{i%tFL7X7=a z4iUPd*fW7797G1O6fo{;y`gbb@9eVsV T7*U~~{fvS~s1&M%wL;my?By_{ delta 2260 zcmah~T};zg6!*5YLZOT=QQAtYMQEu}3OF=Iw^~sV++s_wT*wh_Ysb)mU;TpdA4C7t=HU9cEJI4GZr;kZ{ zGtD=8_$2Ql+X5X1XUP#6O)Ljv(iSqYU4FtBd9T(9kCdED)y9+wr&f67H#Ju%K^_Rj z_K9XRYDJ^`5IYdI!4rf1m6K9@e%8+9%KWD}>|n7cXO7&{*u$r>tNuvPi=K+YR3q+YJ5E`v%cwtYu&-aoPR&Z8yRI0$r22 z;U>94xa4YOwjl13%ZzmyTypE6rL@u!L`^pLd*m+RF-vo9m0BGkR8uI~h@TR1#=0De z%Iq%ml4Z^t8IzR_M3m?Yf!`-@2?;M;T2hrfTE-dk!cR-=tR3>pBdiyu$}Pox(!)=O zMClL?bLAbIT9Mp_upVIp0@g*g4hiB-1df1(QVT+1B{Uk~gMpZ`_Z+yF#@YVlwWVKa zayz7XUL(37VOn9pj{S%vAIzC%oeGLLA7T(;2%#Ne55fq731JlWnk!fsPMaI5;;5hw zy@L|nUYNOkA}A(f58#p6%}&ggSu{2*(mWIO85R;~a{fZW2aT1tSSNg6xrBn#GE~l3 zx7w)(r~XaLArGlf)We5XC!DkHFug2~FjCv$S8I))5*Y=ntz1uu9fFOvYW*>EH~>So zv+Ni6&DO-uC)cc4rD1`j&(2uwThgrR1|#FaNs&NTN|zGPq+p>~;BeK$beSUrDeqUwLJ5qX6^^oJ)B;|*~K@o_Bf)OS5!Xax?&hyn*eA$!5yPtOs zFB69m-bFZq020)^eM)F@Tnr}^RTqyAk4Hr>T&^+I;-sjHg)$Kdh7_k!P%cN2b`D_% z;W$DZeyFK4ACRJ|84IPy@*+Nn9lXx|ixOOup@mP!eoYZ5%x~1wq zj}i?ojljY=2&aNK)jg=EI?%eI1(}TzB?g{(9XI8n+L}72Mi5zAr1rnA6GTq!w@q0$ z=VU6VKi#nUPWm*t({%KXUzou|>2MP3XX+jBsJ_K-5g4u@)p%A>cN17O1({ySR|Vk5Nmr z8Hc{cwR&pQ6r5?a)!jtXM+g{=tS`9{fhOVEZc8843*R;NvU||5&cViDV4d4Y5$dAx zv5B_@BrmRe%GfZRZK|-3r0r&Z`j)6^#vrMquXEjTn>0WKKij2JCU;=;RM2Ygjs~!2=`!qLp8e&UvIcj VYRqK?I{BY#@EDdGtcEoP(?5)h0xtjn diff --git a/aaanalysis/explainer/__init__.py b/aaanalysis/explainer/__init__.py index 14853156..e69de29b 100644 --- a/aaanalysis/explainer/__init__.py +++ b/aaanalysis/explainer/__init__.py @@ -1,5 +0,0 @@ -from aaanalysis.data_loader import load_dataset, load_scales -from aaanalysis.aaclust import AAclust -from aaanalysis.cpp import CPP, CPPPlot, SequenceFeature, SplitRange -from aaanalysis.dpulearn import dPULearn -from aaanalysis.plotting import plot_settings, plot_set_legend, plot_gcfs, plot_get_cmap, plot_get_cdict diff --git a/aaanalysis/explainer/tree_based.py b/aaanalysis/explainer/tree_based.py index 244e22bf..e763646c 100644 --- a/aaanalysis/explainer/tree_based.py +++ b/aaanalysis/explainer/tree_based.py @@ -16,7 +16,7 @@ # COL_FEAT_IMPACT = "feat_impact" # II Main Functions -class Tree: +class TreeModel: """A wrapper for Tree based prediction models and Tree explainer from SHAP package to explain prediction (typically binary classification) results at global and individual level""" def __init__(self, model=None): @@ -32,7 +32,7 @@ def add_feat_import(self, df_feat=None): """""" -class TreeSHAP: +class ShapModel: """A wrapper for Tree explainer from SHAP package""" def __init__(self, model=None): """""" diff --git a/aaanalysis/plotting/__pycache__/plotting_functions.cpython-39.pyc b/aaanalysis/plotting/__pycache__/plotting_functions.cpython-39.pyc index bc019695f3ffaaef528b649b1668ec81e405b36a..0fec9a4955c72f4b40dc967ee4db5e9e663a9f01 100644 GIT binary patch delta 3004 zcmZWrZ)_CD72nz2JMXRU&gZ}Q{O`^-cDxvD2ZI4)pSd1&NC;;Gmo#yK&H85VICK9x zyM#Y6brTR(r9u^rXg>s^r1=zuRzy~aR7FH>qkOF@^-K3dtEx&ROO;YoRj7&5^u0O9 z5aX49^XAQaZ{EE3=FNR|mE65bLRKiGOYryBaHIXx*F)W8@b%%tD|v~kza$G0x|{lG z-4(LXNGE83>OeKoJv2x|KsD37G)xHzRb28Xz5~+vxBWX`z=MpyPBGxX?%CW9 z$H)M`?@JJ!kNJDYHrZ&X*~qg3HLddnXAn*J(FCZ20fWEl|D*$b_HxXft}&_(F57#mVditIVEUwcJqnwf%->c!(R8QGlHa@p2@#6O-X- zWixA+A+?*+(o`!gC@b?^!98u}t!kNn9Eo)mP)$kA&#&1)f#-1;)|1cw6&W~q2j;G{ zMBrbBePKU6qn$wUduRk4E~^rE5PN~nm-rgO3P1Ih*bCs*m8|pT%T|%?!(}3r(uU5k z2k7wD4t&;s%rwCPx6?Y>YmqFU; 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Must be >=2 for 'CPP' and 'SHAP' and 2-9 for 'TAB'. + Number of colors in the color map. Must be >=2 for 'CPP' and 'SHAP' and 2-9 for 'CAT'. facecolor_dark Whether central color in 'CPP' and 'SHAP' is black (if ``True``) or white. Returns ------- list - List with colors given as RGB tuples (for 'CPP' and 'SHAP') or matplotlib color names (for 'TAB'). + List with colors given as RGB tuples (for 'CPP' and 'SHAP') or matplotlib color names (for 'CAT'). Examples -------- @@ -167,7 +162,7 @@ def plot_get_cmap(name: str = "CPP", >>> import matplotlib.pyplot as plt >>> import seaborn as sns >>> import aaanalysis as aa - >>> colors = aa.plot_get_cmap(name="TAB", n_colors=4) + >>> colors = aa.plot_get_cmap(name="CAT", n_colors=4) >>> data = {'Classes': ['Class A', 'Class B', 'Class C', "Class D"], 'Values': [23, 27, 43, 38]} >>> aa.plot_settings(no_ticks_x=True, font_scale=1.2) >>> sns.barplot(x='Classes', y='Values', data=data, palette=colors) @@ -181,19 +176,19 @@ def plot_get_cmap(name: str = "CPP", * `Matplotlib color names `_ """ # Check input - list_names = [STR_CMAP_CPP, STR_CMAP_SHAP, STR_CMAP_TAB] + list_names = [ut.STR_CMAP_CPP, ut.STR_CMAP_SHAP, ut.STR_CMAP_CAT] if name not in list_names: raise ValueError(f"'name' must be one of following: {list_names}") ut.check_bool(name="facecolor_dark", val=facecolor_dark) # Get color maps - if name == STR_CMAP_SHAP: + if name == ut.STR_CMAP_SHAP: ut.check_non_negative_number(name="n_colors", val=n_colors, min_val=3, just_int=True) return _get_shap_cmap(n_colors=n_colors, facecolor_dark=facecolor_dark) - elif name == STR_CMAP_CPP: + elif name == ut.STR_CMAP_CPP: ut.check_non_negative_number(name="n_colors", val=n_colors, min_val=3, just_int=True) return _get_cpp_cmap(n_colors=n_colors, facecolor_dark=facecolor_dark) - elif name == STR_CMAP_TAB: + elif name == ut.STR_CMAP_CAT: ut.check_non_negative_number(name="n_colors", val=n_colors, min_val=2, max_val=9, just_int=True) return _get_tab_color(n_colors=n_colors) @@ -221,15 +216,16 @@ def plot_get_cdict(name: str = "DICT_COLOR") -> dict: >>> dict_color = aa.plot_get_cdict(name="DICT_COLOR") """ - list_names = [STR_DICT_COLOR, STR_DICT_CAT] + list_names = [ut.STR_DICT_COLOR, ut.STR_DICT_CAT] if name not in list_names: raise ValueError(f"'name' must be one of following: {list_names}") - if name == STR_DICT_COLOR: + if name == ut.STR_DICT_COLOR: return ut.DICT_COLOR else: return ut.DICT_COLOR_CAT -# TODO test + +# Plotting adjuster def plot_settings(font_scale: float = 1, font: str = "Arial", fig_format: str = "pdf", @@ -310,7 +306,7 @@ def plot_settings(font_scale: float = 1, >>> import seaborn as sns >>> import aaanalysis as aa >>> data = {'Classes': ['Class A', 'Class B', 'Class C'], 'Values': [23, 27, 43]} - >>> colors = aa.plot_get_cmap(name="TAB", n_colors=3) + >>> colors = aa.plot_get_cmap(name="CAT", n_colors=3) >>> aa.plot_settings() >>> sns.barplot(x='Classes', y='Values', data=data, palette=colors) >>> sns.despine() diff --git a/aaanalysis/utils.py b/aaanalysis/utils.py index 8c48c02f..0dc60b15 100644 --- a/aaanalysis/utils.py +++ b/aaanalysis/utils.py @@ -122,6 +122,13 @@ def _folder_path(super_folder, folder_name): "Shape": "tab:cyan", "Structure-Activity": "tab:brown"} +# Parameter options for cmaps and color dicts +STR_CMAP_CPP = "CPP" +STR_CMAP_SHAP = "SHAP" +STR_CMAP_CAT = "CAT" +STR_DICT_COLOR = "DICT_COLOR" +STR_DICT_CAT = "DICT_CAT" + # II 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-
  • n_colors (int) – Number of colors in the color map. Must be >=2 for ‘CPP’ and ‘SHAP’ and 2-9 for ‘TAB’.

  • +
  • n_colors (int) – Number of colors in the color map. Must be >=2 for ‘CPP’ and ‘SHAP’ and 2-9 for ‘CAT’.

  • facecolor_dark (bool) – Whether central color in ‘CPP’ and ‘SHAP’ is black (if True) or white.

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zkxSO->BISY@!DbAwGk`B^x-MpX|xGz*tj^yRxLw_^@w*ny?A3%0+@pV_Gh%Hk<$F1?u1IR*1YH!zRWA4Yqgf2g5eZ;mv?2ydld8SzvY-h+CT(Hq7B< zkk@f*tnSFL{H@48`GiGPX z=zV@(QNRuj2%J#;(Pp6RvvbQA6)b7mn2ly!5mAOb=}tm34%U;e-ta?NYce!5WvsRV zl$SAdN?&ACzlNtQQ^qE6iZTFzJE+TEUzRT_Sdxsh(Tpp@mvI#|<6wOm16U5tALfl2 zRrekH^>(?3gMRl~+V2`ac#ik!{R?4QhzdgX=l%Qgyz&D$R-YJLbCE%`MejNC#EHQJ zh)lx?KqfKFjXQ^zmxsmta<{#nD^W*7gX|l3g8sFYP_~Bn4Z(ncxpBvDkU9l8wK4;K zXYj~yhY{Jgh6E7+waQw0cnE=~_#p^oXZ$0G

    Returns:
    -

    List with colors given as RGB tuples (for ‘CPP’ and ‘SHAP’) or matplotlib color names (for ‘TAB’).

    +

    List with colors given as RGB tuples (for ‘CPP’ and ‘SHAP’) or matplotlib color names (for ‘CAT’).

    Return type:

    list

    @@ -159,7 +159,7 @@

    aaanalysis.plot_get_cmap
    >>> import matplotlib.pyplot as plt
     >>> import seaborn as sns
     >>> import aaanalysis as aa
    ->>> colors = aa.plot_get_cmap(name="TAB", n_colors=4)
    +>>> colors = aa.plot_get_cmap(name="CAT", n_colors=4)
     >>> data = {'Classes': ['Class A', 'Class B', 'Class C', "Class D"], 'Values': [23, 27, 43, 38]}
     >>> aa.plot_settings(no_ticks_x=True, font_scale=1.2)
     >>> sns.barplot(x='Classes', y='Values', data=data, palette=colors)
    diff --git a/docs/build/html/generated/aaanalysis.plot_set_legend.html b/docs/build/html/generated/aaanalysis.plot_set_legend.html
    index caadacba..fc0f69d1 100644
    --- a/docs/build/html/generated/aaanalysis.plot_set_legend.html
    +++ b/docs/build/html/generated/aaanalysis.plot_set_legend.html
    @@ -129,7 +129,7 @@
     

    aaanalysis.plot_set_legend

    -aaanalysis.plot_set_legend(ax=None, handles=None, dict_color=None, list_cat=None, labels=None, y=-0.2, x=0.5, ncol=3, fontsize=11, weight='normal', lw=0, edgecolor=None, return_handles=False, loc='upper left', labelspacing=0.2, columnspacing=1, title=None, fontsize_legend=None, title_align_left=True, fontsize_weight='normal', shape=None, **kwargs)[source]
    +aaanalysis.plot_set_legend(ax=None, handles=None, dict_color=None, list_cat=None, labels=None, y=-0.2, x=0.5, ncol=3, fontsize=11, weight='normal', lw=0, edgecolor=None, return_handles=False, loc='upper left', labelspacing=0.2, columnspacing=1, title=None, fontsize_legend=None, title_align_left=True, fontsize_weight='normal', shape=None, **kwargs)[source]

    Set a customizable legend for a plot.

    Parameters:
    diff --git a/docs/build/html/generated/aaanalysis.plot_settings.html b/docs/build/html/generated/aaanalysis.plot_settings.html index 57157c7c..e2418fe0 100644 --- a/docs/build/html/generated/aaanalysis.plot_settings.html +++ b/docs/build/html/generated/aaanalysis.plot_settings.html @@ -129,7 +129,7 @@

    aaanalysis.plot_settings

    -aaanalysis.plot_settings(font_scale=1, font='Arial', fig_format='pdf', weight_bold=True, adjust_only_font=False, adjust_further_elements=True, grid=False, grid_axis='y', no_ticks=False, short_ticks=False, no_ticks_x=False, short_ticks_x=False, no_ticks_y=False, short_ticks_y=False, show_options=False)[source]
    +aaanalysis.plot_settings(font_scale=1, font='Arial', fig_format='pdf', weight_bold=True, adjust_only_font=False, adjust_further_elements=True, grid=False, grid_axis='y', no_ticks=False, short_ticks=False, no_ticks_x=False, short_ticks_x=False, no_ticks_y=False, short_ticks_y=False, show_options=False)[source]

    Configure general settings for plot visualization with various customization options.

    This function modifies the global settings of matplotlib and seaborn libraries. PDFs are embedded such that they can be edited using image editing software.

    @@ -177,7 +177,7 @@

    aaanalysis.plot_settings>>> import seaborn as sns >>> import aaanalysis as aa >>> data = {'Classes': ['Class A', 'Class B', 'Class C'], 'Values': [23, 27, 43]} ->>> colors = aa.plot_get_cmap(name="TAB", n_colors=3) +>>> colors = aa.plot_get_cmap(name="CAT", n_colors=3) >>> aa.plot_settings() >>> sns.barplot(x='Classes', y='Values', data=data, palette=colors) >>> sns.despine() diff --git a/docs/build/html/index/CONTRIBUTING_COPY.html b/docs/build/html/index/CONTRIBUTING_COPY.html index 1888aec0..4cc7a30b 100644 --- a/docs/build/html/index/CONTRIBUTING_COPY.html +++ b/docs/build/html/index/CONTRIBUTING_COPY.html @@ -6,12 +6,12 @@ - + - - - + + + @@ -98,6 +98,12 @@
  • Building the Docs
  • +
  • Use ChatGPT! +
  • @@ -148,6 +154,7 @@

    ContributingInstallation

  • Pull Requests

  • Documentation

  • +
  • Use ChatGPT!

  • @@ -368,6 +375,155 @@

    Building the Docs +

    Use ChatGPT!

    +

    Leverage the power of ChatGPT to optimize various facets of your software development process, +including code checking, interface optimization, and effective testing.

    +

    Simply use the templates provided below and fill in the blank spaces between +START OF CODE and END OF CODE with the specifics of your task.

    +

    Due to the token limit of ChatGPT, the answers might not be complete. Use this prompt to continue the answer of ChatGPT:

    +
    "Continue from where you left off."
    +
    +
    +
    +

    Code checking

    +

    For reviewing your code’s logic, ensuring conciseness, and promoting clarity, try the following prompt:

    +
    "
    +Analyze and evaluate the provided TARGET CODE to ensure it adheres to best coding practices and is free from logical errors.
    +
    +Inputs:
    +TARGET CODE:
    +- START OF CODE
    +-------------------------------------
    +your code
    +-------------------------------------
    +- END OF CODE
    +
    +**Key Directive**: Identify vulnerabilities, inefficiencies, and areas of improvement. This is crucial.
    +
    +Requirements:
    +
    +1. Syntax and Formatting:
    +- Ensure consistent indentation and formatting throughout.
    +- Use meaningful variable and function names.
    +- Avoid hard-coded values; suggest constants or configuration inputs if necessary.
    +
    +2. Logic and Flow:
    +- Confirm that the logic flows correctly and efficiently.
    +- Identify any potential issues like infinite loops, off-by-one errors, or misused conditions.
    +
    +3. Error Handling:
    +- Suggest robust error handling mechanisms.
    +- Highlight potential areas where exceptions might arise and are not currently handled.
    +
    +4. General Guidelines:
    +- Suggest improvements for readability and maintainability.
    +- Do not leave any placeholders like "TODO", "Fix this", "Add ..." without suggestions.
    +- Offer potential refactorings if they simplify the code without losing clarity.
    +
    +Output Expectations:
    +- Detailed feedback on the TARGET CODE with line references.
    +- Suggestions for improvements and potential refactorings.
    +- Highlighted vulnerabilities and their proposed resolutions.
    +"
    +
    +
    +
    +
    +

    Interface optimization

    +

    To enhance the public interface or signature of your functions and classes, employ the following prompt:

    +
    "
    +Review and suggest improvements for the interface of the given TARGET FUNCTION to enhance its usability, clarity, and integration capabilities.
    +
    +Inputs:
    +TARGET FUNCTION:
    +- START OF CODE
    +-------------------------------------
    +your code
    +-------------------------------------
    +- END OF CODE
    +
    +**Key Directive**: The interface should be intuitive, versatile, and easy for other developers to integrate and use.
    +
    +Requirements:
    +
    +1. Signature Clarity:
    +- Ensure function/method names are descriptive and concise.
    +- Parameters should have clear names and, if possible, default values that make sense.
    +
    +2. Documentation:
    +- Suggest comprehensive docstrings for the function.
    +- Propose comments for complex code blocks to aid understanding.
    +
    +3. Return Values and Types:
    +- Advise on consistent return types, considering scenarios like error or null conditions.
    +- Recommend clear naming for returned objects, especially if using data structures like dictionaries or tuples.
    +
    +4. General Guidelines:
    +- Avoid overloading the interface with too many parameters; suggest alternatives if needed.
    +- Consider common use cases and ensure they are easily achievable with the proposed interface.
    +- The interface should promote good coding practices and be resistant to misuse.
    +
    +Output Expectations:
    +- Feedback and suggestions on function/method signatures.
    +- Proposed docstrings and comments.
    +- Recommendations for ensuring a consistent and intuitive interface.
    +"
    +
    +
    +
    +
    +

    Testing

    +

    For generating efficient tests with extensive coverage and considering edge cases, utilize the prompt template below:

    +
    "
    +Generate test functions for a given TARGET FUNCTION using the style of the provided TESTING TEMPLATE.
    +
    +Inputs:
    +TARGET FUNCTION:
    +- START OF CODE
    +-------------------------------------
    +your code
    +-------------------------------------
    +- END OF CODE
    +
    +TESTING TEMPLATE:
    +- START OF CODE
    +-------------------------------------
    +your code
    +-------------------------------------
    +- END OF CODE
    +
    +**Key Directive**: For the Normal Cases Test Class, EACH function MUST test ONLY ONE individual parameter of the TARGET FUNCTION using Hypothesis for property-based testing. This is crucial.
    +
    +Requirements:
    +
    +1. Normal Cases Test Class:
    +- Name: 'Test[TARGET FUNCTION NAME]'.
    +- Objective: Test EACH parameter *INDIVIDUALLY*.
    +- Tests: For EACH parameter, at least 10 positive and 10 negative tests.
    +
    +2. Complex Cases Test Class:
    +- Name: 'Test[TARGET FUNCTION NAME]Complex'.
    +- Objective: Test combinations of the TARGET FUNCTION parameters.
    +- Tests: At least 5 positive and 5 negative that intricately challenge the TARGET FUNCTION.
    +
    +3. General Guidelines:
    +- Use Hypothesis for property-based testing, but test parameters individually for the Normal Cases Test Class .
    +- Tests should be clear, concise, and non-redundant.
    +- Do not leave any placeholders like "TODO", "Fill this", "Add ..." incomplete.
    +- Expose potential issues in the TARGET FUNCTION.
    +
    +Output Expectations:
    +- Two test classes: one for normal cases (individual parameters) and one for complex cases (combinations).
    +- In Normal Cases, one function = one parameter tested.
    +- Total: at least 30 unique tests, 150+ lines of code.
    +
    +Reminder: In Normal Cases, it's crucial to test parameters individually.
    +"
    +
    +
    +
    +

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z4sSAl!}`UuiY+g%z^zr~+2IP@7wVT=Hf1Z?G1##iSHHxq;Ao$*zS^n=-MY8<2XI%o z+rHGa9J`72tKN=%!)ajSRc}M>A6d7D>(^|J-BkJHEqt4jDPnyW%eYlszuxKSLHnRg zS2y6=7PTJf9{@gA!(vUc!>gCzu0omg6;87 NpGinb{|_&kU^-WX1JmWb|wHy>IMD) diff --git a/docs/build/plot_directive/generated/aaanalysis-plot_get_cmap-1.py b/docs/build/plot_directive/generated/aaanalysis-plot_get_cmap-1.py index 4b87f962..a7a0a0ad 100644 --- a/docs/build/plot_directive/generated/aaanalysis-plot_get_cmap-1.py +++ b/docs/build/plot_directive/generated/aaanalysis-plot_get_cmap-1.py @@ -1,7 +1,7 @@ import matplotlib.pyplot as plt import seaborn as sns import aaanalysis as aa -colors = aa.plot_get_cmap(name="TAB", n_colors=4) +colors = aa.plot_get_cmap(name="CAT", n_colors=4) data = {'Classes': ['Class A', 'Class B', 'Class C', "Class D"], 'Values': [23, 27, 43, 38]} aa.plot_settings(no_ticks_x=True, font_scale=1.2) sns.barplot(x='Classes', y='Values', data=data, palette=colors) diff --git a/docs/build/plot_directive/generated/aaanalysis-plot_settings-1.pdf b/docs/build/plot_directive/generated/aaanalysis-plot_settings-1.pdf index c529060e6843430570b4f3de5f89287944008c6e..fd99020df64ae429773dcaf3b08946486bc76374 100644 GIT binary patch delta 19 acmZ1yuq0r^92GW0BNH=2qs@y{nwSAdM+S`m delta 19 acmZ1yuq0r^92GVL3quP-v(1ZCnwSAdg$9)X diff --git a/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.pdf b/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.pdf index d9827b4658804c92d14f8f37177d6e9a36f316e8..2644a11ebd133303e3fd48e053d77dcd113e89e9 100644 GIT binary patch delta 19 acmcazdb@PPISV#JBNH=2qs><=*qH!Wx(8JN delta 19 acmcazdb@PPISV!e3quP-v&~m5*qH!W_y=78 diff --git a/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.py b/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.py index 238ad202..3d0cf45c 100644 --- a/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.py +++ b/docs/build/plot_directive/generated/aaanalysis-plot_settings-2.py @@ -2,7 +2,7 @@ import seaborn as sns import aaanalysis as aa data = {'Classes': ['Class A', 'Class B', 'Class C'], 'Values': [23, 27, 43]} -colors = aa.plot_get_cmap(name="TAB", n_colors=3) +colors = aa.plot_get_cmap(name="CAT", n_colors=3) aa.plot_settings() sns.barplot(x='Classes', y='Values', data=data, palette=colors) sns.despine() diff --git a/docs/source/index/CONTRIBUTING_COPY.rst b/docs/source/index/CONTRIBUTING_COPY.rst index a2751ceb..6fda7bac 100644 --- a/docs/source/index/CONTRIBUTING_COPY.rst +++ b/docs/source/index/CONTRIBUTING_COPY.rst @@ -256,3 +256,160 @@ To generate the documentation locally: make html - Open `_build/html/index.html` in a browser. + +Use ChatGPT! +============ +Leverage the power of ChatGPT to optimize various facets of your software development process, +including code checking, interface optimization, and effective testing. + +Simply use the templates provided below and fill in the blank spaces between +``START OF CODE`` and ``END OF CODE`` with the specifics of your task. + +Due to the token limit of ChatGPT, the answers might not be complete. Use this prompt to continue the answer of ChatGPT: + +.. code-block:: none + + "Continue from where you left off." + +Code checking +------------- +For reviewing your code's logic, ensuring conciseness, and promoting clarity, try the following prompt: + +.. code-block:: none + + " + Analyze and evaluate the provided TARGET CODE to ensure it adheres to best coding practices and is free from logical errors. + + Inputs: + TARGET CODE: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: Identify vulnerabilities, inefficiencies, and areas of improvement. This is crucial. + + Requirements: + + 1. Syntax and Formatting: + - Ensure consistent indentation and formatting throughout. + - Use meaningful variable and function names. + - Avoid hard-coded values; suggest constants or configuration inputs if necessary. + + 2. Logic and Flow: + - Confirm that the logic flows correctly and efficiently. + - Identify any potential issues like infinite loops, off-by-one errors, or misused conditions. + + 3. Error Handling: + - Suggest robust error handling mechanisms. + - Highlight potential areas where exceptions might arise and are not currently handled. + + 4. General Guidelines: + - Suggest improvements for readability and maintainability. + - Do not leave any placeholders like "TODO", "Fix this", "Add ..." without suggestions. + - Offer potential refactorings if they simplify the code without losing clarity. + + Output Expectations: + - Detailed feedback on the TARGET CODE with line references. + - Suggestions for improvements and potential refactorings. + - Highlighted vulnerabilities and their proposed resolutions. + " + + + +Interface optimization +---------------------- +To enhance the public interface or signature of your functions and classes, employ the following prompt: + +.. code-block:: none + + " + Review and suggest improvements for the interface of the given TARGET FUNCTION to enhance its usability, clarity, and integration capabilities. + + Inputs: + TARGET FUNCTION: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: The interface should be intuitive, versatile, and easy for other developers to integrate and use. + + Requirements: + + 1. Signature Clarity: + - Ensure function/method names are descriptive and concise. + - Parameters should have clear names and, if possible, default values that make sense. + + 2. Documentation: + - Suggest comprehensive docstrings for the function. + - Propose comments for complex code blocks to aid understanding. + + 3. Return Values and Types: + - Advise on consistent return types, considering scenarios like error or null conditions. + - Recommend clear naming for returned objects, especially if using data structures like dictionaries or tuples. + + 4. General Guidelines: + - Avoid overloading the interface with too many parameters; suggest alternatives if needed. + - Consider common use cases and ensure they are easily achievable with the proposed interface. + - The interface should promote good coding practices and be resistant to misuse. + + Output Expectations: + - Feedback and suggestions on function/method signatures. + - Proposed docstrings and comments. + - Recommendations for ensuring a consistent and intuitive interface. + " + +Testing +------- +For generating efficient tests with extensive coverage and considering edge cases, utilize the prompt template below: + +.. code-block:: none + + " + Generate test functions for a given TARGET FUNCTION using the style of the provided TESTING TEMPLATE. + + Inputs: + TARGET FUNCTION: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + TESTING TEMPLATE: + - START OF CODE + ------------------------------------- + your code + ------------------------------------- + - END OF CODE + + **Key Directive**: For the Normal Cases Test Class, EACH function MUST test ONLY ONE individual parameter of the TARGET FUNCTION using Hypothesis for property-based testing. This is crucial. + + Requirements: + + 1. Normal Cases Test Class: + - Name: 'Test[TARGET FUNCTION NAME]'. + - Objective: Test EACH parameter *INDIVIDUALLY*. + - Tests: For EACH parameter, at least 10 positive and 10 negative tests. + + 2. Complex Cases Test Class: + - Name: 'Test[TARGET FUNCTION NAME]Complex'. + - Objective: Test combinations of the TARGET FUNCTION parameters. + - Tests: At least 5 positive and 5 negative that intricately challenge the TARGET FUNCTION. + + 3. 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b/tests/unit/plotting_functions_tests/test_plot_gcfs.py new file mode 100644 index 00000000..c72d44bc --- /dev/null +++ b/tests/unit/plotting_functions_tests/test_plot_gcfs.py @@ -0,0 +1,22 @@ +""" +This is a script for testing the aa.plot_gcfs function. +""" +import seaborn as sns +import aaanalysis as aa + +class TestPlotGCFS: + """Test plot_gcfs function""" + + # Positive test cases + def test_retrieve_current_font_size(self): + """Test that function retrieves the current font size.""" + current_context = sns.plotting_context() + expected_font_size = current_context['font.size'] + + font_size = aa.plot_gcfs() + assert font_size == expected_font_size + + def test_font_size_not_none(self): + """Test that function doesn't return None.""" + font_size = aa.plot_gcfs() + assert font_size is not None diff --git a/tests/unit/plotting_functions_tests/test_plot_get_cdict.py b/tests/unit/plotting_functions_tests/test_plot_get_cdict.py new file mode 100644 index 00000000..87e5d959 --- /dev/null +++ b/tests/unit/plotting_functions_tests/test_plot_get_cdict.py @@ -0,0 +1,41 @@ +""" +This is a script for testing the aa.plot_get_cdict function. +""" +from hypothesis import given, example +import hypothesis.strategies as some +import aaanalysis.utils as ut +import pytest +import aaanalysis as aa + +class TestPlotGetCDict: + """Test plot_get_cdict function""" + + # Positive test cases + @given(name=some.sampled_from(["DICT_COLOR", "DICT_CAT"])) + def test_valid_dict_names(self, name): + """Test function with valid dictionary names.""" + color_dict = aa.plot_get_cdict(name=name) + if name == "DICT_COLOR": + assert color_dict == ut.DICT_COLOR + else: + assert color_dict == ut.DICT_COLOR_CAT + + # Negative test cases + @given(invalid_name=some.text().filter(lambda x: x not in ["DICT_COLOR", "DICT_CAT"])) + @example(invalid_name="INVALID_NAME") + def test_invalid_dict_names(self, invalid_name): + """Test function with invalid dictionary names.""" + with pytest.raises(ValueError): + aa.plot_get_cdict(name=invalid_name) + + @given(invalid_type=some.one_of(some.integers(), some.floats(), some.lists(some.text()))) + def test_invalid_types(self, invalid_type): + """Test function with unexpected types as dictionary name.""" + with pytest.raises(ValueError): + aa.plot_get_cdict(name=invalid_type) + + @given(empty_str=some.just("")) + def test_empty_string_as_name(self, empty_str): + """Test function with an empty string as dictionary name.""" + with pytest.raises(ValueError): + aa.plot_get_cdict(name=empty_str) diff --git a/tests/unit/plotting_functions_tests/test_plot_get_cmap.py b/tests/unit/plotting_functions_tests/test_plot_get_cmap.py index 16c49bbe..2d6197da 100644 --- a/tests/unit/plotting_functions_tests/test_plot_get_cmap.py +++ b/tests/unit/plotting_functions_tests/test_plot_get_cmap.py @@ -2,13 +2,9 @@ This is a script for testing the aa.plot_get_cmap function. """ from hypothesis import given, strategies as st -from typing import List, Tuple, Union import pytest import aaanalysis as aa - -STR_CMAP_CPP = "CPP" -STR_CMAP_SHAP = "SHAP" -STR_CMAP_TAB = "TAB" +import aaanalysis.utils as ut class TestPlotGetCMap: @@ -17,41 +13,41 @@ class TestPlotGetCMap: # Positive testing @given(n_colors=st.integers(min_value=3, max_value=1000)) def test_valid_n_colors_cpp(self, n_colors): - colors = aa.plot_get_cmap(name=STR_CMAP_CPP, n_colors=n_colors) + colors = aa.plot_get_cmap(name=ut.STR_CMAP_CPP, n_colors=n_colors) assert len(colors) == n_colors @given(n_colors=st.integers(min_value=3, max_value=1000)) def test_valid_n_colors_shap(self, n_colors): - colors = aa.plot_get_cmap(name=STR_CMAP_SHAP, n_colors=n_colors) + colors = aa.plot_get_cmap(name=ut.STR_CMAP_SHAP, n_colors=n_colors) assert len(colors) == n_colors @given(n_colors=st.integers(min_value=2, max_value=9)) def test_valid_n_colors_tab(self, n_colors): - colors = aa.plot_get_cmap(name=STR_CMAP_TAB, n_colors=n_colors) + colors = aa.plot_get_cmap(name=ut.STR_CMAP_CAT, n_colors=n_colors) assert len(colors) == n_colors - @given(name=st.sampled_from([STR_CMAP_CPP, STR_CMAP_SHAP, STR_CMAP_TAB])) + @given(name=st.sampled_from([ut.STR_CMAP_CPP, ut.STR_CMAP_SHAP, ut.STR_CMAP_CAT])) def test_valid_name(self, name): colors = aa.plot_get_cmap(name=name, n_colors=5) assert colors is not None def test_facecolor_dark_toggle(self): - light_colors = aa.plot_get_cmap(name=STR_CMAP_CPP, facecolor_dark=False) - dark_colors = aa.plot_get_cmap(name=STR_CMAP_CPP, facecolor_dark=True) + light_colors = aa.plot_get_cmap(name=ut.STR_CMAP_CPP, facecolor_dark=False) + dark_colors = aa.plot_get_cmap(name=ut.STR_CMAP_CPP, facecolor_dark=True) assert light_colors != dark_colors def test_return_type_cpp(self): - colors = aa.plot_get_cmap(name=STR_CMAP_CPP) + colors = aa.plot_get_cmap(name=ut.STR_CMAP_CPP) assert all(isinstance(color, tuple) and len(color) == 3 for color in colors) def test_return_type_tab(self): - colors = aa.plot_get_cmap(name=STR_CMAP_TAB, n_colors=7) + colors = aa.plot_get_cmap(name=ut.STR_CMAP_CAT, n_colors=7) assert all(isinstance(color, str) for color in colors) # Negative testing @given(name=st.text()) def test_invalid_name(self, name): - if name not in [STR_CMAP_CPP, STR_CMAP_SHAP, STR_CMAP_TAB]: + if name not in [ut.STR_CMAP_CPP, ut.STR_CMAP_SHAP, ut.STR_CMAP_CAT]: with pytest.raises(ValueError): aa.plot_get_cmap(name=name) @@ -64,12 +60,12 @@ def test_invalid_n_colors(self, n_colors): @given(n_colors=st.integers(min_value=-1000, max_value=1)) def test_invalid_n_colors_for_cpp(self, n_colors): with pytest.raises(ValueError): - aa.plot_get_cmap(name=STR_CMAP_CPP, n_colors=n_colors) + aa.plot_get_cmap(name=ut.STR_CMAP_CPP, n_colors=n_colors) @given(n_colors=st.one_of(st.integers(min_value=-1000, max_value=1), st.integers(min_value=10, max_value=1000))) def test_invalid_n_colors_for_tab(self, n_colors): with pytest.raises(ValueError): - aa.plot_get_cmap(name=STR_CMAP_TAB, n_colors=n_colors) + aa.plot_get_cmap(name=ut.STR_CMAP_CAT, n_colors=n_colors) @given(n_colors=st.floats()) def test_non_integer_n_colors(self, n_colors): @@ -79,16 +75,16 @@ def test_non_integer_n_colors(self, n_colors): @given(facecolor_dark=st.one_of(st.text(), st.integers(), st.floats(), st.lists(st.booleans()))) def test_invalid_facecolor_dark_type(self, facecolor_dark): with pytest.raises(ValueError): - aa.plot_get_cmap(name=STR_CMAP_CPP, facecolor_dark=facecolor_dark) + aa.plot_get_cmap(name=ut.STR_CMAP_CPP, facecolor_dark=facecolor_dark) @given(n_colors=st.integers(min_value=-1000, max_value=2)) def test_invalid_n_colors_for_shap(self, n_colors): with pytest.raises(ValueError): - aa.plot_get_cmap(name=STR_CMAP_SHAP, n_colors=n_colors) + aa.plot_get_cmap(name=ut.STR_CMAP_SHAP, n_colors=n_colors) @given(name=st.text(), n_colors=st.integers(min_value=-1000, max_value=1)) def test_invalid_name_and_n_colors(self, name, n_colors): - if name not in [STR_CMAP_CPP, STR_CMAP_SHAP, STR_CMAP_TAB]: + if name not in [ut.STR_CMAP_CPP, ut.STR_CMAP_SHAP, ut.STR_CMAP_CAT]: with pytest.raises(ValueError): aa.plot_get_cmap(name=name, n_colors=n_colors) @@ -96,7 +92,7 @@ def test_name_as_none(self): with pytest.raises(ValueError): aa.plot_get_cmap(name=None) - @given(name=st.sampled_from([STR_CMAP_CPP, STR_CMAP_SHAP])) + @given(name=st.sampled_from([ut.STR_CMAP_CPP, ut.STR_CMAP_SHAP])) def test_zero_n_colors(self, name): with pytest.raises(ValueError): aa.plot_get_cmap(name=name, n_colors=0) diff --git a/tests/unit/plotting_functions_tests/test_plot_set_legend.py b/tests/unit/plotting_functions_tests/test_plot_set_legend.py new file mode 100644 index 00000000..aee100c9 --- /dev/null +++ b/tests/unit/plotting_functions_tests/test_plot_set_legend.py @@ -0,0 +1,75 @@ +""" +This is a script for testing the aa.aa.plot_set_legend function. +""" +import matplotlib.pyplot as plt +import matplotlib as mpl +import hypothesis.strategies as some +from hypothesis import given, settings, example +import aaanalysis as aa +import pytest + + +# Helper function +def random_colors(): + """Generate random colors.""" + return some.tuples(some.integers(min_value=0, max_value=255), + some.integers(min_value=0, max_value=255), + some.integers(min_value=0, max_value=255)).map(lambda x: '#%02X%02X%02X' % x) + + +class TestPlotSetLegend: + """Test aa.plot_set_legend function""" + + # Property-based testing for positive cases + @given(x=some.floats(min_value=0, max_value=1), y=some.floats(min_value=-1, max_value=1), + ncol=some.integers(min_value=1, max_value=5), fontsize=some.integers(min_value=8, max_value=15), + lw=some.floats(min_value=0, max_value=2), labelspacing=some.floats(min_value=0, max_value=1), + columnspacing=some.floats(min_value=0, max_value=2)) + def test_basic_legend(self, x, y, ncol, fontsize, lw, labelspacing, columnspacing): + """Test basic legend functionality.""" + dict_color = {'Cat1': 'red', 'Cat2': 'blue'} + fig, ax = plt.subplots() + aa.plot_set_legend(ax=ax, dict_color=dict_color, x=x, y=y, ncol=ncol, fontsize=fontsize, lw=lw, + labelspacing=labelspacing, columnspacing=columnspacing) + # Assert legend created + assert ax.get_legend() is not None + + @given(dict_color=some.dictionaries(keys=some.text(min_size=1, max_size=5), values=random_colors(), min_size=2, + max_size=5), shape=some.sampled_from(['o', 's', '^', 'v', 'D', '*', 'X'])) + def test_color_and_shapes(self, dict_color, shape): + """Test different colors and marker shapes.""" + fig, ax = plt.subplots() + aa.plot_set_legend(ax=ax, dict_color=dict_color, shape=shape) + # Assert legend created with specified colors and shapes + assert ax.get_legend() is not None # TODO: Add more specific assertions to check the colors and shapes + + +class TestPlotSetLegendComplex: + """Test aa.plot_set_legend function with complex scenarios""" + + def test_combined_parameters(self): + """Test a combination of parameters.""" + dict_color = {'Cat1': 'red', 'Cat2': 'blue', 'Cat3': 'green'} + labels = ['Category 1', 'Category 2', 'Category 3'] + fig, ax = plt.subplots() + aa.plot_set_legend(ax=ax, dict_color=dict_color, labels=labels, x=0.8, y=-0.5, ncol=2, fontsize=13, weight="bold", + lw=1.5, labelspacing=0.5, columnspacing=1.2, title="Test Title", fontsize_legend=15, + title_align_left=False, shape='s') + # Assert legend created with the combined settings + assert ax.get_legend() is not None # TODO: Add specific assertions to verify each of the settings + + def test_invalid_input_combinations(self): + """Test invalid combinations of parameters.""" + dict_color = {'Cat1': 'red', 'Cat2': 'blue'} + fig, ax = plt.subplots() + + # Invalid number of labels + labels = ['Category 1'] + with pytest.raises(ValueError): + aa.plot_set_legend(ax=ax, dict_color=dict_color, labels=labels) + + # Invalid x and y combination + with pytest.raises(ValueError): + aa.plot_set_legend(ax=ax, dict_color=dict_color, x=2, y=2) + + # TODO: Add more invalid combinations to test robustness diff --git a/tests/unit/plotting_functions_tests/test_plot_settings.py b/tests/unit/plotting_functions_tests/test_plot_settings.py index caa8ed22..9c3d1d43 100644 --- a/tests/unit/plotting_functions_tests/test_plot_settings.py +++ b/tests/unit/plotting_functions_tests/test_plot_settings.py @@ -2,79 +2,80 @@ This is a script for testing the aa.plot_settings function. """ import pytest -from hypothesis import given, strategies as st, assume, example, settings +from hypothesis import given, strategies as st, example, settings import matplotlib as mpl -from aaanalysis import plot_settings +import aaanalysis as aa + class TestPlotSettings: # Positive Tests def test_default_params(self): - plot_settings() + aa.plot_settings() assert mpl.rcParams["font.family"] == ["sans-serif"] def test_font(self): - plot_settings(font="Verdana") + aa.plot_settings(font="Verdana") assert "Verdana" in mpl.rcParams["font.sans-serif"] def test_fig_format_pdf(self): - plot_settings(fig_format="pdf") + aa.plot_settings(fig_format="pdf") assert mpl.rcParams["pdf.fonttype"] == 42 def test_weight_bold(self): - plot_settings(weight_bold=True) + aa.plot_settings(weight_bold=True) assert mpl.rcParams["axes.labelweight"] == "bold" def test_adjust_only_font(self): - plot_settings(adjust_only_font=True) + aa.plot_settings(adjust_only_font=True) assert mpl.rcParams["font.family"] == ["sans-serif"] def test_grid_axis_y(self): - plot_settings(grid_axis="y") + aa.plot_settings(grid_axis="y") assert mpl.rcParams["axes.grid.axis"] == "y" def test_no_ticks(self): - plot_settings(no_ticks=True) + aa.plot_settings(no_ticks=True) assert mpl.rcParams["xtick.major.size"] == 0 assert mpl.rcParams["ytick.major.size"] == 0 def test_grid_true(self): - plot_settings(grid=True) + aa.plot_settings(grid=True) assert mpl.rcParams["axes.grid"] == True def test_adjust_further_elements(self): - plot_settings(adjust_further_elements=True) + aa.plot_settings(adjust_further_elements=True) assert mpl.rcParams["errorbar.capsize"] == 10 assert mpl.rcParams["legend.frameon"] == False # Negative Tests def test_negative_font_scale(self): with pytest.raises(ValueError): - plot_settings(font_scale=-1.0) + aa.plot_settings(font_scale=-1.0) def test_invalid_font(self): with pytest.raises(ValueError): - plot_settings(font="InvalidFont") + aa.plot_settings(font="InvalidFont") def test_invalid_fig_format(self): with pytest.raises(ValueError): - plot_settings(fig_format="exe") + aa.plot_settings(fig_format="exe") def test_invalid_grid_axis(self): with pytest.raises(ValueError): - plot_settings(grid_axis="z") + aa.plot_settings(grid_axis="z") def test_both_no_ticks_and_short_ticks(self): with pytest.warns(UserWarning): - plot_settings(no_ticks=True, short_ticks=True) + aa.plot_settings(no_ticks=True, short_ticks=True) def test_both_no_ticks_x_and_short_ticks_x(self): with pytest.warns(UserWarning): - plot_settings(no_ticks_x=True, short_ticks_x=True) + aa.plot_settings(no_ticks_x=True, short_ticks_x=True) def test_both_no_ticks_y_and_short_ticks_y(self): with pytest.warns(UserWarning): - plot_settings(no_ticks_y=True, short_ticks_y=True) + aa.plot_settings(no_ticks_y=True, short_ticks_y=True) class TestPlotSettingsComplexCases: @@ -91,7 +92,7 @@ class TestPlotSettingsComplexCases: @example(1.0, "Verdana", "png", False, True, True, False, True, "x") @settings(max_examples=5) def test_complex_positive_cases(self, font_scale, font, fig_format, weight_bold, adjust_only_font, adjust_further_elements, grid, no_ticks, grid_axis): - plot_settings(font_scale=font_scale, font=font, fig_format=fig_format, weight_bold=weight_bold, adjust_only_font=adjust_only_font, adjust_further_elements=adjust_further_elements, grid=grid, no_ticks=no_ticks, grid_axis=grid_axis) + aa.plot_settings(font_scale=font_scale, font=font, fig_format=fig_format, weight_bold=weight_bold, adjust_only_font=adjust_only_font, adjust_further_elements=adjust_further_elements, grid=grid, no_ticks=no_ticks, grid_axis=grid_axis) @given(st.floats(max_value=-0.01, allow_nan=False, allow_infinity=False), st.text(), @@ -106,5 +107,5 @@ def test_complex_positive_cases(self, font_scale, font, fig_format, weight_bold, @settings(max_examples=5) def test_complex_negative_cases(self, font_scale, font, fig_format, weight_bold, adjust_only_font, adjust_further_elements, grid, no_ticks, grid_axis): with pytest.raises(Exception): - plot_settings(font_scale=font_scale, font=font, fig_format=fig_format, weight_bold=weight_bold, adjust_only_font=adjust_only_font, adjust_further_elements=adjust_further_elements, grid=grid, no_ticks=no_ticks, grid_axis=grid_axis) + aa.plot_settings(font_scale=font_scale, font=font, fig_format=fig_format, weight_bold=weight_bold, adjust_only_font=adjust_only_font, adjust_further_elements=adjust_further_elements, grid=grid, no_ticks=no_ticks, grid_axis=grid_axis)

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